Abstracts of the 6th International Electronic Conference on Applied Sciences (Part 2) ^†

Abstract

This collection presents the accepted abstracts for the session on Electrical, Electronics and Communications Engineering; Mechanical and Aerospace Engineering; Energy, Environmental and Earth Science; Food Science and Technology; Applied Physical Science. as part of the 6th International Electronic Conference on Applied Sciences.

1. Electrical, Electronics and Communications Engineering

1.1. Development of a Remote Monitoring and Control System for a Medium-Voltage Substation Using IoT Infrastructure and Node-RED

• Micaela Machado Figueira ¹ and Israel Gondres Torné ²

¹ 

Course of Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

² 

PPGEEL-Postgraduate Program in Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

• Electrical substations play a critical role in energy distribution, where operational failures can lead to service interruptions and increased maintenance costs. The modernization of their monitoring systems is essential, especially in environments that demand reliability and real-time diagnostics. The monitoring of medium-voltage substations traditionally relies on local manual readings and on-site operator interventions, limiting real-time visibility and increasing operational delays. This study presents the development and implementation of a remote monitoring and control system for a medium-voltage substation using Internet of Things (IoT) infrastructure and the Node-RED platform. The objective is to enable real-time supervision and reduce the need for physical presence, improving operational efficiency and safety. The system architecture integrates smart meters, a compact programmable controller (Wago CC100), and industrial communication via the Modbus RTU protocol. The Node-RED environment, combined with FlowFuse Dashboard 2, was used to develop a human–machine interface (HMI) accessible through web browsers. The dashboard displays electrical parameters such as voltage, current, and power, and allows for remote switching operations. System development followed four stages: requirement analysis, communication infrastructure setup, HMI development, and validation testing. Functional tests demonstrated reliable data acquisition and consistent remote control response, validating the system’s performance under simulated operational conditions. The implemented solution highlights the potential of low-code IoT platforms in modernizing legacy electrical infrastructures and aligns with the principles of Industry 4.0 by integrating cyber–physical systems for enhanced supervision, predictive maintenance, and decision-making support in electrical networks.

1.2. Numerical Analysis of Temperature and Current Density Distributions in an Atmospheric Pressure Inductively Coupled Plasma Torch Under Local Thermodynamic Equilibrium

• Sayah Merazi ¹, Saad Chaouch ¹, Hani Terfa ¹, Leila Belgacem ¹, Maamar Hakem ¹ and Younes Hamache ^2,3

¹ 

Division of Welding and Assembly Techniques, Research Center in Industrial Technologies CRTI, P.O. Box 64, Cheraga 16014, Algiers, Algeria

² 

LSEI Laboratory, Faculty of Electrical Engineering, University of Science and Technology Houari Boumediene—USTHB, Algeria

³ 

Department of Technological Development, Quality and Radioprotection, Research Center in Industrial Technologies CRTI, P.O. Box 64, Cheraga 16014, Algiers, Algeria

• This study investigates the electrical and thermal behavior of an inductively coupled plasma (ICP) torch operating at atmospheric pressure. A comprehensive numerical model is developed under the assumption of local thermodynamic equilibrium (LTE), enabling the analysis of temperature and current density distributions within the plasma region. The temperature field is primarily governed by ionization phenomena and Joule heating, both of which contribute significantly to the overall energy balance. Simultaneously, the current density is influenced by the spatial variation of the plasma’s electrical properties, particularly its electrical conductivity. The model also accounts for the magnetic field induced by the alternating current in the induction coils. This self-generated magnetic field plays a critical role in plasma confinement and influences both the flow dynamics and the spatial distribution of electrical energy deposition. By coupling electromagnetic, thermal, and fluid flow equations, the simulation provides detailed insights into the physical mechanisms responsible for plasma stabilization and energy transfer. The main objective of this work is to deepen the understanding of the complex interactions between electromagnetic and thermal fields in ICP torches. Such understanding is essential for improving torch design and performance in various industrial processes, including materials processing, waste treatment, and surface modification. The results obtained can guide the optimization of operating parameters to achieve better energy efficiency, uniform temperature profiles, and improved plasma stability.

1.3. A Review on the Optimization and Performance of Lead-Free and Inorganic Perovskite Solar Cells: Comparative Insights from SCAPS-1D Simulations of CsSnCl₃, CsPbI₃, and Cs₂CuBiBr₆

• Dadoua Hadria Mohamed ¹, Gueffaf hamza ¹, Mahammedi Nassim ², Cherrak Souhaib ¹ and Fatima Zohra Hergmadji ³

¹ 

Laboratoire d’Informatique et de Mathématiques, University Amar Telidji of Laghouat, Laghouat 03000, Algeria

² 

The Interdisciplinary Centre for Security, Reliability, and Trust (SnT), University of Luxembourg, L-1855 Luxembourg City, Luxembourg

³ 

Laboratoire d’electrotrotechnique d’Annaba (LEA), University of Badji Mokhtar Annaba, Annaba, Algeria

• This review provides a comprehensive overview of recent advances in the optimization and performance analysis of lead-free and inorganic perovskite solar cells, with a particular focus on CsSnCl₃, CsPbI₃, and Cs₂CuBiBr₆. Using insights derived from SCAPS-1D-based studies, this review highlights comparative trends between lead-based and lead-free perovskites, emphasizing the environmental advantages and emerging efficiency potential of non-toxic alternatives. Reported simulation data indicate that optimized device architectures—such as ITO/CeO₂/CsSnCl₃/CBTS/Au and ITO/TiO₂/CsPbI₃/CBTS/Au—exhibit distinct variations in photovoltaic parameters. Specifically, CsSnCl₃ achieves a Voc of 0.96 V, Jsc of 32.22 mA/cm², FF of 86.40%, and a PCE of 25.1%, whereas CsPbI₃, a lead-based perovskite, delivers a Voc of 0.997 V, Jsc of 21.07 mA/cm², FF of 85.21%, and a PCE of 17.9%. For Cs₂CuBiBr₆, a lead-free double perovskite, efficiencies range from 18.69% to 19.70%, depending on the selected electron transport layer. These results collectively demonstrate that lead-free materials can achieve competitive or even superior performance while offering improved environmental compatibility. Furthermore, the review discusses the influence of absorber thickness, ETL/HTL combinations, series and shunt resistances, and temperature on overall device operation. Overall, this analysis underscores the growing potential of lead-free perovskites as sustainable, high-efficiency alternatives fornext-generation thin-film photovoltaic technologies.

1.4. An Intelligent Automated System for Monitoring and Repairing Cracks in Concrete Elements Using Integrated Sensors and Embedded Controllers

• Papa Pio Ascona García
• Academic Department of Civil Engineering, Professional School of Civil Engineering, Faculty of Engineering, Bagua, National Intercultural University Fabiola Salazar Leguía of Bagua, Bagua 01721, Peru
• This study addressed crack formation and the rehabilitation of concrete elements, such as slabs and columns, in buildings located in areas with temperatures above 25 °C, where accelerated water evaporation significantly reduces structural strength. To mitigate this phenomenon, an intelligent automated monitoring and curing system was developed, based on thermal and humidity sensors and integrated controllers.
• The research was applied, experimental, and explanatory, based on the hypothetical-deductive method. Physical models (test tubes, columns, and solid slabs) were used in a 1:2:3 ratio, integrating DS18B20 and HD-38 sensors. A visualization system was implemented in Proteus, with an LCD screen for data collection and analysis. Statistical analysis, with 95% confidence, revealed a moderate and significant correlation (r = 0.587; p = 0.001) between the environmental thermohygrometer and the DS18B20 sensor, indicating effective heat transfer. In contrast, the HD-38 sensor showed a low correlation (r = 0.143; p = 0.468), indicating a limited influence of ambient humidity on internal humidity.
• Cracks were verified 120 min after the concrete was poured, a critical moment when the system acts by sprinkling water. The system repaired the initial cracks and consumed 1680 L in 28 days, reducing water consumption by 20%. A critical evaporation peak was identified between 11:00 and 16:00 (UTC-5), not previously documented in tropical areas.

1.5. Comparative Evaluation of Sliding Mode and PI-Based PWM Current Control for Six-Phase Induction Machine Drives

• Gustavo Ojeda ¹, Jorge Rodas ², Osvaldo González ¹, Paola Maidana ², Christian Medina ², Esteban Leguizamón ¹ and Nestor Villamayor ¹

¹ 

Master in Electronics Engineering, Universidad del Cono Sur de las Americas, Asuncion, Paraguay

² 

CITHED, Dept. of Electronic and Mechatronic Engineering, Facultad de Ingeniería, Universidad Nacional de Asunción, Luque, Paraguay

• Six-phase induction machines offer inherent fault tolerance capability, reduced torque ripple, and improved reliability compared to a classical three-phase configuration. However, they impose demanding requirements on current control strategies. This study presents a comparative evaluation of Sliding Mode Control (SMC) and the well-established Proportional Integral regulator with Pulse Width Modulation (PI+PWM), both modelled and implemented in MATLAB/Simulink using the same system and identical test condition profiles to ensure a fair comparison. The mentioned controllers are evaluated using speed reversal tests at ±500 rpm (8 kHz sampling) and ±1000 rpm (12 kHz sampling), and further assessed under ±50% variations in magnetising inductance to analyse robustness. The results show that PI+PWM achieves significantly lower steady-state current tracking error, with root mean square error (RMSE) typically below 0.02 A, compared to 0.05–0.08 A for SMC. In terms of current quality, SMC maintains a total harmonic distortion (THD) of approximately 1.3% at low speed and 1.05% at high speed. In comparison, PI+PWM consistently remains below 1.1% and 0.9%, respectively, demonstrating stable performance across both operating conditions. Consequently, PI+PWM emerges as a low-complexity and effective solution for industrial applications with limited computational resources. In contrast, SMC remains advantageous in scenarios requiring strong disturbance rejection and robustness to significant parameter variations.

1.6. Eddy Current Testing of a Steam Generator with a Support Plate

• Dounia Sedira ¹, Oussama Nouar ², Abdelouhab Boussenoune Abdelouhab ², Nassira Ferkha ¹ and Mohamed Chelabi ¹

¹ 

Laboratory of Electrical Engineering and Industrial (L2EI), Faculty of Science and Technology, University of Jijel, Jijel, Algeria

² 

Electrical Engineering Departement, Faculty of Science and Technology University of Jijel, Algeria

• Industrial steam generators serve an important role in a variety of industries, including the chemical and petrochemical industry, engineering industry, and nuclear applications. These devices are used to produce steam that can be used for a variety of purposes, such as heating and sterilization. In order to ensure the safety of a steam generator, nondestructive testing (NDT) techniques are applied. Tube support plates (TSPs) maintain tubes, make sure they are properly spaced, and help avoid fretting. However, TSPs are regarded as disturbing signals for tubes. In this paper, we investigate the influence of the support plate on eddy current testing (ECT) using a differential probe of a steam generator tube made of Inconel 600 and carrying a defect. The modeling of eddy current testing is based on solving a 2D axisymmetric finite element formulation under steady-state conditions via Comsol Multiphysics Software. The impedance of the differential coil is calculated using the direct method, and the signal of the difference impedance is obtained from two simulations: with flaws and without flaws.
• The simulation of the studied system under the abovementioned conditions lets us conclude with the following points:
• The signal of the impedance difference is higher when the TSP is introduced in the simulation. The amplitude of the impedance difference increases as the TSP approaches the tube.

1.7. Modeling a Microgrid Based on the IEC-61850 Architecture Using Petri Nets

• João Victor Reis de Oliveira de Sicco and Miguel Angel Orellana Postigo
• Electronic and Electric Engineering Department, Universidade do Estado do Amazonas, Manaus 69050-025, Brazil
• Electrical microgrids are essential components for the energy transition, facilitating the integration of renewable sources and demanding robust, formally validated control strategies. The IEC 61850 architecture establishes itself as the fundamental standard for ensuring interoperability in these complex systems. To address this challenge, this paper proposes a methodology that uses Interpreted Petri Nets (IPNs) to model, validate, and implement the control logic for a microgrid compatible with this architecture. The developed formal model represents all operational modes, including autonomous, grid-connected, and fault, as well as the transitions between them, which are conditioned by the availability of energy resources (Utility, BESS, and DG) and the occurrence of grid disturbances. Formal validation, conducted through reachability analysis, state space exploration, and incidence matrix verification, demonstrated that the model possesses the desired properties: it is complete, safe, bounded, live, and free of deadlocks. The control logic extracted from the IPN model was then converted into Ladder language (IEC 61131-3) and tested in a CODESYS simulation environment, which emulates the operation of a Programmable Logic Controller (PLC). The experimental results confirmed a perfect match between the simulated behavior and practical operation, validating the proposed approach. This study consolidates IPNs as a reliable formal tool for the digitalization of microgrid control systems, ensuring a safe and verified transition from design to implementation.

1.8. Modelling Stability of the Residential Electricity Consumption

• Tetyana Mamchych and Ivan Mamchych
• Department of Computer Science and Cybersecurity, Lesya Ukrainka Volyn National University, 43000 Lutsk, Ukraine
• Introduction: Household electricity consumption is a significant part of total energy consumption. Trends in the spread of remote work and distance learning only strengthen this contribution. Modern smart grid technologies allow for detailed analysis of the consumption patterns of each individual household. However, the task of analyzing the time series in aggregate, comparing, and classifying households is not easy, since each such series is unique. Modelling the stability of consumption using time series of readings is the main subject of this presentation. We present our method for monitoring the stability of residential electricity consumption.
• Methods: As a measure of stability, we use the auto-similarity coefficient defined as the geometric mean of pairwise correlations between fragments (windows) of the corresponding time series. The method was introduced in our previous work. Here, we test the applicability of this approach to a real-world data set.
• Results: This study found that one week is an appropriate window size for studying the stability of consumption. And also the capabilities of the method are demonstrated for real data of selected Swedish households. The method also reveals seasonal differences; for example, with a high stability of the pattern in the winter months, the same household has low stability in the summer vacation period. Cases with both a high degree of stability and low stability indicators are considered.
• Conclusion: The proposed method can be applied to the analysis of the stability of electricity consumption and thus enriches the arsenal of mathematical modeling methods.

1.9. Simulation of a PARASOL Microsatellite Control System Model Based on the Linear Quadratic Regulator (LQR)

• Medfranck Obiang Mba Dit
• Department of Radio Engineering System, Faculty Radio Engineering and Telecommunications, Saint Petersburg State Electrotechnical University, Saint Petersburg 197227, Russia
• The Parasol microsatellite control system model aims to enhance the stability and performance of small satellite operations in low Earth orbit (LEO). This paper presents a simulation framework based on the Linear Quadratic Regulator (LQR) methodology, which is a widely recognized optimal control strategy. The LQR approach is particularly suited for systems requiring precise control with minimal energy expenditure, making it ideal for microsatellites that operate under strict power constraints. The simulation using the MATLAB/Simulink environment incorporates dynamic models of the microsatellite’s attitude and orbital mechanics, allowing for an assessment of the LQR controller’s effectiveness in maintaining desired orientation and trajectory. In this study, we first of all detailed the mathematical model of the Parasol’s position, including state-space representation, cost function definition, and feedback gain computation. Then we implemented the Linear Quadratic Regulatorcontroller in a closed-loop model in MATLAB/Simulink. After we provided attitude control data in the context of the Parasol microsatellite scenario and his geographic coordinates. Finally, the simulation results demonstrate the effectiveness of the implemented Linear Quadratic Regulator controller in stabilizing Parasol’s position. It shows the trajectory of the Parasol microsatellite in DCI coordinates and the simulation of the geographic coordinate with latitude equal to 61.9756 and longitude 108.119 correspondant to northeastern Siberia, Russia, within Yakutia. And the latitude equal to 1.41449 and longitude 57.7824 is located in Brazil near the Amazon rainforest region.

1.10. A Hybrid Path Planning Strategy for Mobile Robot Navigation Using A* and the Dynamic Window Approach

• Amina Nedjoua Benali and Abdelkader Benaissa
• Laboratory Intelligent Control et Electrical Power System (ICEPS), Djillali Liabes University of Sidi Bel Abbes, B.P 89 Sidi Bel Abbes 22000, Algeria
• This work explores an autonomous navigation strategy for mobile robots that combines the coordinated integration of two complementary approaches: the A* algorithm, renowned for its efficiency in global path planning, and the Dynamic Window Approach (DWA), which is well-suited for reactive local control. The aim is to ensure robust navigation in semi-structured environments by combining long-term planning with real-time adaptability. The performance of the method was evaluated in a simulated environment with fixed obstacles, through two representative scenarios. The first scenario, characterized by a high risk of blockage (dead ends, narrow passages), revealed the limitations of using DWA alone, which often becomes trapped in complex configurations. In contrast, the combined approach leverages the predictive capabilities of A* to effectively bypass problematic areas. The second, less constrained scenario aimed to compare trajectory quality under favorable conditions. Results demonstrate that the proposed integration not only enables the robot to reach the goal but also improves overall performance, as evidenced by a 1.76% reduction in average distance traveled and a 1.89% decrease in navigation time compared to DWA alone. The presented approach stands out due to its ability to dynamically adjust the robot’s behavior while maintaining a global view of the environment. This contributes to increased reliability and efficiency of autonomous navigation, especially in complex or cluttered contexts.

1.11. A Practical Approach for Acquiring the Hall–Huray Surface Ratio Using HFSS Simulations and VNA Measurements

• Fábio Arozo de Albuquerque Júnior, Raimundo Cláudio de Souza Gomes, Angilberto Muniz Ferreira Sobrinho and Israel Gondres Torné
• PPGEEL-Postgraduate Program in Electrical Engineering, State University of Amazonas (UEA), Manaus 69050-020, Brazil
• This paper presents a practical, efficient, and automated approach for determining the Hall–Huray Surface Ratio parameter, which is essential for accurately modeling conductor surface roughness losses in high-frequency PCB transmission lines manufactured with FR4 substrates. The growing complexity of modern digital systems and the demand for precise signal integrity analysis require advanced electromagnetic models to predict interconnect behavior. Among several roughness models, the Huray model is widely recognized for its ability to represent conductive losses associated with copper surface roughness in a physically meaningful way. The proposed methodology combines automated parametric sweeps in ANSYS HFSS with experimental validation using a WavePulser 40iX vector network analyzer (VNA), applying time-domain gating techniques to isolate multiple reflection effects. The 3D simulation setup adopts the Wideband Debye model for the dielectric and the snowball (Huray) model for surface roughness characterization. The Hall–Huray Surface Ratio variable was systematically adjusted from 1 to 9 to achieve close agreement with the experimental data. The results demonstrated a deviation of less than 0.04 dB at 10 GHz in insertion loss and a maximum variation of 1.05 Ω in the impedance profile obtained via TDR. Although minor mismatches in the reflection parameter (S11) were observed, the outcomes validate the accuracy, robustness, and practical applicability of the proposed method. This technique offers an effective balance between cost, complexity, and precision for high-frequency structure characterization up to 20 GHz, with promising potential for future extensions in electromagnetic compatibility (EMC) studies and advanced interconnect modeling.

1.12. Accurate Brillouin Frequency Shift Measurements Through Secondary Interaction Compensation

• Raffaele Vallifuoco, Ester Catalano, Agnese Coscetta, Luigi Zeni and Aldo Minardo
• Department of Engineering, Università della Campania Luigi Vanvitelli, Via Roma 29, 81031 Aversa, Italy
• Distributed optical fiber sensors based on stimulated Brillouin scattering (SBS) allow temperature and strain measurements at multiple points along a fiber. Conventional interrogation methods based on a pulsed pump fail to reach a cm-scale spatial resolution due to the acoustic response time of the silica fiber. Instead, the Brillouin Optical Frequency Domain Analysis (BOFDA) technique achieves a finer resolution by pre-activating the acoustic wave involved in the scattering process. Unfortunately, BOFDA also suffers from artifacts caused by the “secondary interaction” between the pump and the sidebands of the acoustic wave. These artifacts introduce systematic errors in the estimate of the Brillouin frequency shift. To correct these distortions, earlier proposed methods based on either iterative numerical compensation or high-pass filtering have some drawbacks, such as a long processing time or a degradation of the SNR. Here, we propose a method based on the direct measurement of the secondary interaction, achieved through the injection of a double-sideband-modulated pump with a suppressed carrier. Under these conditions, the SBS interaction between the sidebands of the pump and those of the acoustic wave induces a frequency-doubling modulation in the probe intensity. By acquiring such modulation, one can estimate the secondary interaction signal and subtract it from the original BOFDA signal to mitigate systematic errors. Theoretical and experimental results validate the proposed technique.

1.13. Adaptive Fault Detection in Microgrids Using LSTM-Based Neural Networks

• Júlio da Rocha Costa ¹, Erick Amazonas de Almeida ¹, Celso Vitor Leão Martins ¹ and Israel Gondres Torné ²

¹ 

Course of Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

² 

PPGEEL-Postgraduate Program in Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

• Safeguarding microgrids with decentralized generation presents challenges due to the reciprocal power flow and fluctuations in renewable energy sources. Conventional protection systems often fail to adapt to these dynamic conditions, resulting in unreliable operation. This work proposes an innovative methodology for the automatic detection and classification of faults, using a Long Short-Term Memory (LSTM) neural network. The LSTM network was selected for its proven ability to process time series data, allowing it to capture the complex transient signatures of faults, which is crucial for accurate analysis. The research utilizes an extensive set of synchrophasor data (PMU) obtained from detailed simulations of a microgrid model in the MATLAB/Simulink environment. This dataset includes a variety of fault scenarios, including line-to-ground, line-to-line, and three-phase faults. To prepare the data, signal processing techniques from the Signal Processing Toolbox are applied to extract relevant features. Subsequently, an LSTM neural network is designed and trained using the Deep Learning Toolbox to classify fault types with high precision. The results demonstrate that the proposed approach achieves high accuracy and robustness in identifying different types of faults. The methodology contributes to the advancement of adaptive protection systems, offering an intelligent and effective alternative to traditional methods, and reinforces the security and resilience of modern microgrids.

1.14. Automated Provisioning of FTP Services Using Open-Source Tools: A Comparative Analysis of Shell, Ansible, and Chef

• Pedro Escudero-Villa, Darwin Armijos-Guillen and Jenny Paredes-Fierro
• Facultad de Ingeniería, Universidad Nacional de Chimborazo, Riobamba 060108, Ecuador
• In modern network environments, the configuration of services such as FTP servers remains a time-intensive task, particularly when performed manually. This research addresses the challenge of reducing configuration time and minimizing errors through the implementation of an automated provisioning system using open-source tools. The main problem identified is the inefficiency and risk of misconfiguration associated with manual setups of FTP servers, especially in organizations lacking specialized personnel. The objective of this study is to develop a provisioning system capable of automating the configuration of FTP services to reduce deployment time and improve reliability. Our methodology utilized an experimental approach in a virtualized environment using VirtualBox and AlmaLinux. Three automation tools—Shell Script, Chef, and Ansible—were used to configure identical FTP servers. A sample of 245 configuration processes was analyzed using statistical techniques, including the Kolmogorov–Smirnov normality test and the Kruskal–Wallis non-parametric test, implemented in R. The results demonstrate that automated provisioning significantly reduces configuration time from 34.56 min manually to 2.15 min with Ansible (93.78% reduction), 3.49 min with Shell Script (89.90%), and 11.22 min with Chef (67.53%). Each tool performed the full configuration process, including user creation, firewall rules, and service setup. In conclusion, the implementation of automated provisioning tools markedly improves efficiency in server deployment, with Ansible offering the best performance. This contributes to Infrastructure as Code practices and supports scalable, error-reduced network service administration.

1.15. Automatic Irrigation System

• Parsneel Kumar, Kajal Kothari, Shiu Kumar and Ronesh Sharma
• School of Electrical & Electronics Engineering, Fiji National University, Suva, P.O. Box 3722, Samabula, Fiji
• Small Island Developing states face various challenges in the field of agriculture. One of the major challenges in Fiji is insufficient irrigation; therefore, it is crucial to develop a “smart irrigation system based on IoT” that is available for use through mobile and web applications. This article presents an innovative solution to sustainable farming that incorporates advanced IoT technologies. The system utilizes water flow, temperature, humidity, and soil moisture sensors, together with solenoid valves, and water pumps controlled using an ESP32 Node-MCU microcontroller. Continuous monitoring of real-time data on soil and environmental parameters is used to control the irrigation.
• This significantly minimizes water wastage without compromising crop health. The system mainly focuses on specific crops such as ginger, turmeric, eggplant, chili, okra, etc., which are majorly grown in Fiji. The main aim is to make this IoT system efficient yet simple and user-friendly, to be managed by farmers without much technical knowledge. It allows farmers to select a crop type, and according to previously collected and stored data, the system automatically selects parameters to provide a conducive environment for the selected crop and manages irrigation efficiently without any human intervention. It provides a new and innovative approach to maintaining resilience, sustainability, and economic development of rural communities. Real-time testing across several agricultural instances shows the system’s effectiveness. This holistic approach demonstrates dedication to Fiji’s agricultural sustainability as well as economic growth. It illustrates the integration of advanced technology to elevate Fiji’s agriculture to a level of superior effectiveness and sustainability.

1.16. Building an Affordable and Intelligent Smart Home Using ESP32, LoRa, and Cloud Services

• Antonios Krezias ¹ and Ioannis Christakis ²

¹ 

Department of Electrical and Electronics Engineering, University of West Attica, 12243 Athens, Greece

² 

Department of Electrical and Electronics Engineering, School of Engineering, Ancient Olive Grove Campus, University of West Attica, GR-12244 Athens, Greece

• This study focuses on the design and implementation of a cost-effective smart home system, which leverages Internet of Things (IoT) technologies, low-power communication via LoRa, and data processing to enable automation and remote management of household devices and environmental conditions. The growing need for more efficient, secure, and energy-sustainable homes makes such systems particularly relevant today. An ESP32 microcontroller is used as the core of the system, to which various sensors are connected, including temperature, humidity, motion detection, gas leak detection, fire detection, and others. The ESP32 is responsible for collecting and processing the sensor data, which is then transmitted via LoRa (Long Range) technology to The Things Network (TTN). TTN serves as an intermediary gateway, forwarding the data to an online monitoring and visualization platform, Datacake. There, the data is displayed in real-time through graphs and charts, allowing users to remotely monitor the home environment. Simultaneously, the data is also sent to a Raspberry Pi, which functions as the central processing unit of the system. The Raspberry Pi runs a control algorithm that analyzes the sensor readings and issues commands to activate or deactivate connected devices. Examples of such automations include turning on or off lighting, heating, or ventilation systems, and notifying the residents in case of emergencies. The proposed system integrates cutting-edge technologies to develop a smart, interconnected, and autonomous home environment, offering enhanced comfort, safety, energy efficiency, and cost-effectiveness for the user. The system is low-cost, scalable, and adaptable to various settings and needs.

1.17. Charging Speed vs. Daily Performance: A Comparative Analysis of Battery Duration in Smartphones Under Different Charging Regimens

• Dimitrios Rimpas ¹, Nikolaos Rimpas ², Vasilios Athanasios Orfanos ¹, Sofia Fragoul I ¹ and Ioannis Christakis ¹

¹ 

Department of Electrical and Electronics Engineering, University of West Attica, P. Ralli & Thivon 250, 12244 Egaleo, Greece

² 

Department of Surveying and Geoinformatics Engineering, University of West Attica, 28, Ag. Spyridonos Str., 12243 Egaleo, Greece

• Lithium-ion batteries play a crucial role in new electronic applications due to their high energy density, size, safety and efficiency, and they are considered a critical aspect of modern life. However, the increasing prevalence of fast-charging technology has raised user concerns about its impact on the immediate, daily performance of smartphone batteries. This paper investigates the hypothesis that fast charging diminishes a battery’s duration throughout a single usage cycle compared to standard charging methods. We propose a comparative study analyzing the daily battery performance of modern smartphones under various charging regimens, including fast, normal, OEM (and third-party chargers). The methodology involves developing an experimental setup of three distinct electronics devices (a tablet, a laptop and a smartphone) to continuously measure parameters like voltage, current, temperature and state of charge, under different charging conditions to assess their direct effect on single-cycle discharge duration. Findings demonstrate that fast charging generates significantly more heat—a known factor in long-term degradation—and even with sophisticated thermal management they tend to last shorter through the day with increased cell aging. This research highlights the distinction between long-term battery health and immediate daily performance, aiming to clarify consumer misconceptions and underscore the importance of certified charging hardware.

1.18. DC Bus Voltage Balancing in Three-Phase Multilevel T-Type Inverter

• Ali Berboucha, Kamel Djermouni, Said Aissou, Elyazid Amirouche and Houssam Debboucha
• Laboratoire de Maitrise des Energies Renouvelables, Faculté de Technologie, Université de Bejaia, 06000 Bejaia, Algérie
• While the Neutral Point Clamped (NPC) converter, Flying Capacitor (FC) converter, and Cascaded H-Bridge (CHB) converter represent classical multilevel topologies, these topologies possess certain disadvantages that limit their applicability in certain contexts. NPC topology encounters difficulties in capacitor voltage balancing, particularly when the number of levels is high, the increasing number of clamping diodes complicates the voltage balance algorithm.
• T-type inverters present a superior efficiency compared to their NPC counterpart, and the observed efficiency enhancement in T-type inverters can be attributed to their reduced conduction and switching losses. Furthermore, a key advantage of T-type inverters over NPC topologies lies in the elimination of clamping diodes, which are traditionally necessary for maintaining the neutral point potential at the negative or positive DC bus voltages. An active bidirectional switching device is utilized in T-type inverters to achieve voltage clamping. This device interfaces the midpoint of each phase leg with the common node of the series-stacked DC-link capacitors. Nevertheless, T-type inverters, much like NPC converters, confront the challenge of maintaining balanced voltages among the series-connected DC-link capacitor. In this paper, as a contribution, a new technique for capacitor balancing applied to three level T-type inverter based on redundant vectors of space vector modulation is presented and studied.

1.19. Design and Implementation of an Embedded Interface for I²C to Modbus TCP/RTU Integration

• Lucas Gomes Flores, Thiago Dos Santos Alves, João Caio Souza Nunes, Luis Perereira and Erico José Siqueira Coutinho de Almeida
• PPGEEL-Postgraduate Program in Electrical Engineering, State University of Amazonas (UEA), Manaus 69050-020, Brazil
• This paper presents the development of an embedded communication interface that integrates devices using different protocols: I²C, which is widely adopted in sensors and embedded systems, and Modbus TCP/RTU, which is widely used in industrial programmable logic controllers (PLCs). This study focuses on an automation scenario involving SMT (surface mount technology) lines where industrial robots handle printed circuit boards (PCBs). In this application, TF-Luna LiDAR sensors operate via the I²C protocol to provide accurate distance measurements that guide the movements of the robotic arms. However, these sensors are not natively compatible with most PLC models, which communicate via Modbus or other protocols.
• To address this incompatibility, this study proposes developing an embedded interface board that can act as a bridge between the two protocols by converting and forwarding the collected information. The interface can read multiple I²C sensors, organize the data, and make it available to the PLC via Modbus RTU or TCP, depending on the industrial network configuration. This solution contributes to precise synchronization between sensors and actuators, improves production process efficiency, and reinforces the interoperability and flexibility principles required by Industry 4.0. It also makes device interconnectivity more accessible. The proposed approach also enables modular expansion and use in various architectures, as well as greater reliability in real-time communication in industrial environments.

1.20. Design and Implementation of an Intelligent Assistant for Emotion-Based Student Readiness Assessment Using Embedded Systems

• Edward Pinto Pimenta Junior, Daniel Guzmán Del Río, Miguel Angel Orellana Postigo and Israel Gondres Torné
• PPGEEL-Postgraduate Program in Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil
• This work presents the design and implementation of an intelligent assistant embedded system that integrates emotion recognition with real-time student assessment on a low-cost hardware platform. The system is based on an ESP32 microcontroller with a camera module, responsible for capturing student facial expressions during test activities. A Convolutional Neural Network (CNN), pre-trained for facial emotion recognition, is deployed in a hybrid architecture where the ESP32 performs frame preprocessing and transmits data to a server running inference services optimized with TensorFlow Lite.
• The approach is motivated by findings in affective computing and educational psychology, which emphasize the strong correlation between emotional states, concentration, and test anxiety. To estimate student readiness, the system employs a weighted mapping method that combines output probabilities with predefined emotion weights. For example, neutral or happy expressions contribute positively to concentration, while fear or anger increase nervousness. Normalized concentration and nervousness scores are computed over time, and readiness is determined using threshold-based rules: students are considered prepared when concentration reaches at least 60/100 while nervousness remains below 50/100.
• An interactive dashboard allows teachers to monitor student states in real time and analyze historical performance. The proposed assistant demonstrates the feasibility of combining embedded devices, lightweight deep learning models, and real-time analytics for educational applications. By providing interpretable metrics of emotional conditions during assessments, the system offers a novel tool to support both student evaluation and teacher decision-making.

1.21. Design of Wideband Planar Transmissive Metasurface Based on Low-Cost PCB Technology

• Lu Chao and Jie Cui
• School of Electronic and Optical Engineering, Nanjing University of Science and Technology, No. 200 Xiao Ling Wei, Nanjing 210094, China
• High-gain antennas play an important role in long-range wireless communication systems like radar, satellite communication, and space exploration. In such applications, Microstrip array antennas and phased array antennas require complicated feeding networks to realize beamforming and directional radiation, which increases the complexity of antenna design as well as the cost. In contrast, reflective metasurface and transmissive metasurface have high gain property with low cost due to easy fabrication. Compared with reflective, transmissive metasurface offers several advantages such as no aperture blockage from the feed source and less sensitivity to fabricating tolerances. And planar transmissive metasurface shows miniaturized size and lighter weight than traditional three-dimensional (3-D) lens antennas. Despite various advantages, normal transmissive metasurface usually suffers from limited bandwidth. In this submission, a transmissive metasurface with wide gain bandwidth is proposed. The used element is realized by a four-layer rectangular slot, showing wide phase-shifting coverage and low transmission loss within a broad bandwidth. By decreasing the design frequency of the transmission elements, the realized gain of the metasurface becomes flatter. Based on low-cost PCB technology, the metasurface with the dimension of 204 mm × 204 mm is designed and fabricated. The measured results are agreed with the simulated ones well, showing good radiation characteristics with a measured gain of 28.2 dBi at 18 GHz and aperture efficiency of 35.1%. Bandwidths of 26.4% for 1-dB gain and 47.9% for 3-dB gain are achieved as well.

1.22. Design Optimization of a Brushless PM Outer Rotor Motor for Electric Scooters: A Surrogate-Based Multi-Objective Approach

• Hani Terfa ¹, Saad Chaouch ¹, Sid Ali Randi ², Younes Hamache ^1,3 and Sayah Merazi ¹

¹ 

Research Center in Industrial Technologies—CRTI, Cheraga 16014 Algiers, Algeria

² 

Ampere S.A., 78280 Guyancourt, France

³ 

LSEI Laboratory, Faculty of Electrical Engineering, University of Science and Technology Houari Boumediene—USTHB, Algeria

• This study presents a multi-objective design optimization of a Brushless Permanent Magnet Outer Rotor (BPMOR) motor intended for electric scooter applications, focusing on the impact of rotor-mounted magnet geometry. Specifically, the permanent magnet (PM) thickness, magnet arc, and magnet reduction—key design variables—were investigated for their influence on three critical performance metrics: torque ripple, back-electromotive force total harmonic distortion (BEMF THD), and torque per rotor volume (TPRV). A limited set of finite element analysis (FEA) simulations was used to generate a sensitivity dataset, which served to train Gaussian Process Regression (GPR) surrogate models. These models enabled rapid motor performance prediction during optimization—without rerunning computationally intensive FEA—using Particle Swarm Optimization (PSO). The resulting Pareto front revealed the trade-offs between conflicting objectives and identified an optimal design region that satisfies practical engineering constraints: torque ripple ≤ 10% to reduce noise, vibration, and harshness (NVH), BEMF THD ≤ 5% to ensure smoother inverter operation and better control accuracy, and maximized TPRV to achieve high torque density while minimizing magnet material cost. The final design, validated through high-fidelity FEA, demonstrates a marked reduction in torque ripple and BEMF THD, along with a notable increase in TPRV. The proposed approach provides a computationally efficient design methodology for exploring rotor topology configurations, contributing to the design of compact, cost-effective, and high-performance electric traction motors.

1.23. Detailed Equivalent Model for an MMC-HVDC Connected Offshore Wind Farm Under Normal and Fault Dynamic Performance Analysis

• Mohammed Abdedljalil Djehaf ¹, Youcef Islam Djillani Kobibi ² and Mohamed Khatir ¹

¹ 

Faculté de Génie Electrique, Djillali Liabès University of Sidi Bel Abbès, Sidi Bel Abbès 22000, Algeria

² 

Université Mustapha Stambouli Mascara, Mascara 29000, Algeria

• The increasing integration of renewable energy sources into electrical grids necessitates efficient transmission solutions, particularly for offshore wind farms requiring connection to distant onshore networks. Modular Multilevel Converters (MMCs) present significant computational challenges in HVDC system simulations due to their complex structure involving hundreds of submodules and nodes. This study presents a novel detailed equivalent modeling approach using Thevenin equivalent circuits to efficiently simulate MMC behavior while maintaining accuracy for system-wide studies and DC fault analysis.
• The research develops comprehensive Thevenin equivalent models that dramatically reduce computational complexity by representing hundreds of individual submodule nodes through three equivalent nodes per arm. The proposed modeling approach connects islanded offshore wind farms to onshore AC grids through MMC-based VSC HVDC symmetrical monopole systems, where the onshore converter controls DC voltage while the offshore converter maintains AC voltage magnitude and frequency as a slack bus.
• The developed Thevenin equivalent models demonstrate excellent performance under both normal operating conditions and fault scenarios. During normal operation, the models accurately capture steady-state power transmission characteristics, dynamic response to wind variations, and control system interactions. Under fault conditions, the models successfully represent transient phenomena, fault current contributions, and system recovery dynamics for various fault scenarios including DC line faults and AC grid disturbances. The developed modeling technique provides a computationally efficient yet accurate representation of offshore wind farm integration via MMC-HVDC systems, enabling comprehensive analysis of both normal and fault dynamic performance for renewable energy integration studies.

1.24. Development and Validation of an Efficient System for Inspecting Photovoltaic Cells Using Drones with Thermal Cameras and Computer Vision

• Rhedson Esashika, Edward Pinto Pimenta Junior, Isabella Andrade Cabral and Israel Gondres Torné
• PPGEEL-Postgraduate Program in Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil
• While unmanned aerial vehicles (UAVs) with thermal cameras are established tools for inspecting photovoltaic (PV) plants, most systems rely on offline or cloud-based data processing, which introduces latency and data transmission costs. This study presents a novel contribution by developing and validating a fully autonomous inspection system that performs real-time, onboard fault detection using embedded computer vision.
• The core innovation lies in the implementation of a lightweight convolutional neural network (CNN) on a low-cost ESP32 microcontroller, a highly resource-constrained environment. This enables the system to analyze thermal images captured by the UAV and identify anomalies—such as hotspots and burned cells—directly in the field, eliminating the need for external processing infrastructure. The CNN model was trained on a custom dataset of annotated thermographic images, using data augmentation and class balancing to ensure robust performance.
• Preliminary results demonstrate that this embedded approach enables accurate, autonomous, and non-invasive thermal inspections without requiring system shutdowns. By integrating georeferenced aerial data acquisition with immediate onboard analysis, our system significantly reduces operational costs and diagnostic latency compared to traditional methods. This work adds to the existing knowledge by proving the viability of deploying computer vision models on edge devices for industrial inspection, offering a scalable, efficient, and accessible architecture that advances intelligent predictive maintenance in the renewable energy sector.

1.25. Development of a Facial Recognition-Based Access Control System for Scientific Research Laboratories

• Sterfany da Silva Oliveira ¹, Wagner Dos Santos Farah Junior ¹ and Israel Gondres Torné ²

¹ 

Course of Electronic Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

² 

PPGEEL-Postgraduate Program in Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

• Security in academic laboratories involves not only the protection of physical resources but also the control of access to environments where research and equipment are concentrated. Conventional systems based on keys or access cards often present limitations related to loss, duplication, or lack of traceability. This project presents the development of an access control system based on facial recognition, designed for use in research laboratories. The solution integrates an ESP32-CAM module for image capture and facial identification, an ESP32 microcontroller to manage access locks, and a TFT display to show visual feedback. A web interface was implemented to register users and record access events, allowing monitoring of entry times and user identification. The development followed a structured approach: initial research and planning, definition of requirements, component selection, and staged implementation. Functionalities such as image processing, lock control, and access logging were progressively integrated and tested. The system was evaluated in a controlled environment simulating real laboratory access scenarios. It correctly recognized registered users, denied entry to unregistered individuals, and recorded access data without communication failures or delays. All components functioned as expected, including wireless data transmission and interface synchronization. The proposed system provides an alternative to traditional key-based methods by offering traceability, ease of use, and potential for replication in academic settings.

1.26. Development of an Automated Irrigation System with Remote Sensing for Rural Microentrepreneurs

• Sterfany da Silva Oliveira ¹ and Israel Gondres Torné ²

¹ 

Course of Electronic Engineering, Superior High School, State University of Amazonas (UEA), Manaus 69050-020, Brazil

² 

PPGEEL-Postgraduate Program in Electrical Engineering, Superior High School, State University of Amazonas (UEA), Manaus 69050-020, Brazil

• Water is a finite and essential resource, and its efficient use is critical, especially in agriculture, which accounts for over 70% of global freshwater consumption. Rural microentrepreneurs often face difficulties accessing efficient irrigation technologies due to high costs and operational complexity. This study presents the development of a low-cost automated irrigation system aimed at supporting small-scale farmers, combining the principles of Industry 4.0 with embedded systems and Internet of Things (IoT) technologies. The proposed system integrates an ESP32 microcontroller with wireless communication and a set of environmental sensors—soil moisture, air humidity, temperature, and rainfall. The firmware was developed in C/C++ using the Arduino IDE, and the system communicates through the MQTT protocol to enable real-time monitoring and control via a supervisory interface. The chosen irrigation method was localized drip irrigation, installed in a passion fruit plantation (Passiflora edulis), due to its efficiency in reducing water waste. A functional prototype was implemented and validated under field conditions, successfully triggering irrigation events based on predefined environmental thresholds. The results indicate that the system operates autonomously and effectively, enabling water savings and better crop management without requiring constant human intervention. The project demonstrates that accessible technological solutions can enhance productivity and sustainability in rural settings, promoting digital inclusion and more efficient use of natural resources in agriculture.

1.27. Diagnosis of Induction Machine Faults Using Vibrations Analysis Technique

• Nassira Ferkha, Amin Later, Abdelbari Guemraoui and Dounia Sedira
• Laboratory of Electrical Engineering and Industrial Electronics (L2EI), Faculty of Science and Technology, University of Jijel, Jijel, Algeria
• Abstract: This paper presents a new methodology for the diagnosis of induction machine faults. A modern and efficient diagnosis technique should be non-destructive. The proposed technique is based on the vibratory behavior analysis.
• Introduction: Vibration analysis is a very interesting and recent technique because any change in the mechanical or electrical conditions of the machine affects its dynamic conditions and thus its vibration behavior.
• Methodology: The virtual works method is applied locally for the magnetic force computation. To calculate the dynamic response of the stator to the magnetic force stresses, the dynamic equation must be solved. The vibratory response (acceleration) of the stator is equal to a linear combination of associated mode shapes.
• Numerical calculation codes based on finite elements method are developed under Matlab environment to diagnosing rotor bar breakage, short circuit and other faults. These codes were applied in healthy and faulty cases of the machine.
• The Fast Fourier Transform was investigated. So, we compared between the frequency spectra of the accelerations in the faulty and healthy cases, to predict the defect.
• Results: The obtained results prove that vibration analysis technique has the advantage of allowing the detection and the localization of defects. More details and results proving the interest of this technique for the monitoring of the induction machines will be presented in the full paper.
• Conclusion: This study has given more understanding of the dependent roles of vibration analysis in predicting and diagnosing machine faults. So, we have proved the interest of this technique for the monitoring of the electrical machines.

1.28. Effective Approach for Optimal Local Control of Distributed Generation Under High Uncertainties in Load

• Mohamed Ouail
• Electrical Engineering and Renewable Energy Laboratory, University of Chlef (UHBC), Chlef, Algeria
• This paper investigates the effectiveness of a proposed approach for local power control of distributed generation (DG) units used for power and voltage support in passive distribution networks under high uncertainty in load and unexpected daily load variations. The approach is based on the use of an intelligent algorithm, Particle Swarm Optimization (PSO), to determine an asymptotic reference for the optimal real-time power control of small-scale DGs. The optimization problem is formulated with the desired objective functions, subject to network constraints. The principle of the proposed strategy is to determine the reference voltage at the connection nodes of the distributed generators (DGs) corresponding to optimal power generation, either as a fixed value or by deriving a regression line from a two-variable dataset comprising the DG’s optimal power generation and the voltage at its connection node. The optimal regression line is derived using the statistical least squares method. The optimal power–voltage datasets are obtained from various random load scenarios by applying the Particle Swarm Optimization (PSO) algorithm. In this study, the optimization algorithm is applied to minimize power losses and improve the voltage profile. The investigation includes simulation results and analysis conducted on a modified IEEE 33-bus radial distribution system with DG units providing both active and reactive power. The impact of active and reactive power generation on the objective functions is analyzed. Asymptotic reference values for the local control of DG units are derived for different scenarios, and the results demonstrate the effectiveness of the proposed strategy.

1.29. Electro-Adhesion Force Applied to Metal Particles Using a Double-Sided Electrostatic Actuator

• Boudra Hanane, Sayah Rafik and Djehaf Mohamed Abdeljalil
• APELEC Laboratory, Djillali Liabes University of Sidi-Bel-Abbes 22000, Algeria
• Electrostatic separation is a proven technique for the selective sorting of solid materials and is widely applied in recycling and waste valorization. Conventional methods, which rely on forces acting on charged or polarized particles, often face limitations in selectivity and efficiency when treating complex metal/plastic mixtures. This study introduces and investigates a novel device, the Double-Side Electrostatic Actuator (DSEA), designed to generate a specific electro-adhesion force acting on metallic particles.
• The DSEA consists of a dielectric layer with segmented parallel electrodes on the top surface and a continuous plate electrode on the bottom side. This double-sided configuration allows the application of high-amplitude polyphase voltages without breakdown, thus improving performance compared to single-sided systems. The electro-adhesion force was quantified using an experimental setup that combined the DSEA with a suction aspirator placed 5 mm above the surface to evaluate particle retention under airflow.
• Experiments were performed with monocomponent copper particles and with binary mixtures containing 70% copper and 30% PVC. The results showed that adhesion depends strongly on electrode geometry, with smaller widths and gaps leading to stronger retention. At 2000 V and airflow ≤ 1.3 m³/min, copper recovery and purity reached 100%, while all plastic particles were completely removed. Numerical simulations with COMSOL confirmed the concentration of the electric field at electrode edges, explaining the selective adhesion mechanism.
• These results demonstrate the potential of the DSEA for efficient metal/plastic separation, combining high recovery with high purity, and provide new insights into advanced electrostatic recycling technologies.

1.30. Electronic Notice Board with Enhanced Features

• Parmeet Kumar, Kajal Kothari, Ronesh Sharma and Shiu Kumar
• School of Electrical & Electronics Engineering, Fiji National University, Suva, P.O. Box 3722, Samabula, Fiji
• Notice boards play a vital role in day-to-day life and are constructively used in various places. Using manual paper-based noticeboards at universities, and public spaces like hospitals, bus stations, and transport hubs has become a tedious task to perform daily, especially when frequent notice updates are required. There is also a risk of false notices being posted on these manual noticeboards if not secured properly. With the advancement in technologies over the last decade, electronic noticeboards have gained widespread attention due to their simplicity, flexibility, low cost, and rapid response, and are becoming an essential element for relaying messages or notices in such places. This article proposes a solar-powered wireless electronic noticeboard using an ESP8266 microcontroller. A webpage has been developed to instantly update the message or notice on the electronic noticeboard via Wi-Fi communication. To prevent unauthorized messages or notices being posted, the proposed system is password-protected and requires authentication from the users to access the webpage. The proposed system has several features that give users greater flexibility such as retrieving the current message or notice being displayed on the noticeboard, providing an option to specify a time frame for which a message or notice should be displayed, and providing an option to mark the message as an emergency message or notice, so that the alert is highlighted on the notice board for quick attention. The system also integrates a sleep mode feature which reduces its power consumption. The proposed system is low-cost and offers better efficiency and security over manual noticeboards.

1.31. Emulation of DoS Attacks in Digital Electrical Substations: A Platform for Cybersecurity Awareness and Real-Time Traffic Analysis

• Pedro Escudero-Villa, Riki Uvidia-Carrillo and Kevin Parra-Cordova
• Facultad de Ingeniería, Universidad Nacional de Chimborazo, Riobamba 060108, Ecuador
• The increasing digitalization of power substations and the integration of communication networks in electrical systems have exposed critical infrastructure to a growing number of cybersecurity threats. This study presents the design and implementation of a simulated environment to emulate cyberattacks—specifically Denial of Service (DoS) attacks—on digital substations, aiming to raise awareness and improve cybersecurity practices in operational technology (OT) networks. Using open-source tools such as Mininet, Wireshark, and hping3, a digital twin of a substation communication system was built to replicate realistic network behavior under both normal and attack conditions. During the attack scenario, SYN flood packets were sent at a rate of approximately 530 packets per second and sustained for 10 s, leading to a total of 5300 attack packets. Packet capture analysis revealed that the average packet size increased from 78 bytes (normal traffic) to over 110 bytes during the attack. Additionally, the number of TCP SYN packets increased by 90%, significantly disrupting normal communication flow. These anomalies were clearly observable in the time-sequence visualizations generated using Wireshark. The simulation demonstrated the vulnerability of digital substations to basic network-layer exploits. This emulated environment provides a valuable platform for educational and training purposes, allowing security practitioners and engineers to visualize and understand attack patterns in critical systems. This study emphasizes the importance of proactive cyber-defense strategies in modern power systems and proposes further integration with intrusion detection mechanisms and AI-based anomaly detection tools to enhance resilience.

1.32. Genetic Algorithm-Based Model for Short-Term Load Forecasting in Isolated Microgrids

• Davel Eduardo Borges Vasconcellos ¹, Eduardo Sierra Gil ¹, Jorday Arostegui Morell ², Neilson Luniere Vilaça ³ and Israel Gondres Torné ⁴

¹ 

Departament of Electrical Engineering, Faculty of Electromechanical, University of Camaguey “Ignacio Agramonte Loynaz”, Camagüey 74650, Cuba

² 

Power Systems Regime Analysis Department, Camagüey Electric Company, Camagüey 74650, Cuba

³ 

Course of Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

⁴ 

PPGEEL-Postgraduate Program in Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

• Isolated microgrids face operational challenges due to restricted generation capacity and high sensitivity to consumption fluctuations. Reliable short-term forecasting is essential to support decision-making in these constrained environments. Accurate short-term load forecasting plays a key role in the planning and operation of electrical power systems, especially in isolated microgrids with limited generation capacity. This study proposes a hybrid forecasting model that combines the Recursive Least Squares algorithm with the K-Nearest Neighbors method, enhanced through the application of Genetic Algorithm optimization techniques. The model integrates weather conditions, calendar variables, and historical consumption data to identify behavioral patterns and improve forecast performance. The implementation was carried out in MATLAB version 2024rd, using the Global Optimization Toolbox structures for Genetic Algorithm and Direct Search methods to fine-tune the model parameters. Real operational data from 2023 and 2024, collected from isolated electrical systems serving tourist areas, were used to validate the proposed model. The results show that the hybrid approach outperforms classical Recursive Least Squares and Artificial Neural Network models, particularly during periods of high demand variability. This improved forecasting capacity supports energy providers in making informed decisions for scheduling maintenance and operational actions, while ensuring efficient power generation at reduced costs. The methodology is adaptable to other isolated or small-scale power systems and contributes to improving the reliability and cost-effectiveness of energy planning in similar regional contexts.

1.33. Impact of Current and Potential Distributions on the Performance of Large Lithium-Ion Pouch Batteries

• Sayah Merazi ¹, Saad Chaouch ¹, Hani Terfa ¹, Leila Belgacem ¹, Maamar Hakem ¹ and Younes Hamache ^2,3

¹ 

Division of Welding and Assembly Techniques, Research Center in Industrial Technologies CRTI, P.O. Box 64, Cheraga 16014, Algiers, Algeria

² 

LSEI Laboratory, Faculty of Electrical Engineering, University of Science and Technology Houari Boumediene—USTHB, Algiers 16111, Algeria

³ 

Department of Technological development, Quality and Radioprotection; Research Center in Industrial Technologies CRTI, P.O. Box 64, Cheraga 16014, Algiers, Algeria

• With the growing demand for high-energy and high-power lithium-ion batteries in electric vehicles and stationary energy storage systems, large-format pouch cells have emerged as a preferred solution due to their high energy density, lightweight construction, and design flexibility. However, their large physical dimensions and the use of localized tab-based current collection introduce significant challenges, particularly in achieving uniform current and potential distribution across the electrodes. These spatial in homogeneities can result in uneven electrode utilization, localized heat accumulation, and accelerated degradation of cell components. This study presents a comprehensive three-dimensional multiphysics simulation of a large-format lithium-ion pouch cell using COMSOL Multiphysics^®. The model incorporates realistic geometry, material properties, and electrochemical parameters to investigate the influence of tab placement and collector design under different charging regimes. Fast charging at 4C is shown to induce notable ohmic voltage drops in the current collectors, approximately 5 mV in copper and 9 mV in aluminum, leading to strongly asymmetric lithium intercalation. Current density is initially concentrated near the tabs but progressively shifts toward central regions due to local saturation effects. These findings underline the critical role of cell architecture in dictating performance and reliability. Optimizing tab configuration, increasing collector conductivity, and improving electrode layout are shown to significantly enhance current uniformity, minimize thermal hotspots, and extend battery life. The results demonstrate that 3D multiphysics modeling is a powerful tool for diagnosing internal imbalances and guiding the design of next-generation lithium-ion batteries with improved durability and efficiency.

1.34. Impact of Stator Winding Insulation on Thermal Behavior in Switched Reluctance Machines

• Mama Chouitek ¹ and Houaria Neddar ²

¹ 

Department of Industrial Engineering, Institute of Industrial Maintenance and Safety, University of Oran, Oran, Algeria

² 

Department of Electrical Engineering, University of Mostaganem, Mostaganem, Algeria

• This article presents a comprehensive thermal analysis of the Switched Reluctance Machine (SRM), with the objective of improving its efficiency, reliability, and operational lifespan. The study begins with an in-depth examination of the electromechanical characteristics of the SRM, providing essential insights into its operating environment. Particular attention is given to the identification and quantification of the main sources of thermal losses, including mechanical, electrical, and magnetic losses.
• To understand heat propagation within the machine, a thermal modeling approach is applied, covering the three principal modes of heat transfer: conduction, convection, and radiation. These models make it possible to analyze the distribution of heat among the internal components of the SRM, depending on their structure and the properties of the materials. The theoretical study is supported by numerical simulations performed using the FEMM 4.2 software.
• The simulations explore different operating scenarios, including cases with insulated and non-insulated windings. This analysis highlights the crucial role of insulating materials in thermal management. More specifically, insulation enhances heat dissipation and contributes to a more uniform temperature distribution within the machine.
• The results confirm that an optimized thermal design, particularly through the careful selection and application of insulating materials, can significantly improve the thermal performance of the SRM. This is reflected in higher energy efficiency and extended lifespan, making the SRM more suitable for demanding industrial applications

1.35. Improvement of Inter-Area Oscillation Damping by Coordination of Multiple PSSs and Statcom

• Seddiki Zahira and Allaoui Tayeb
• Laboratory of Energetic and Computer Engineering (L2GEGI), University of Tiaret, Tiaret, Algeria
• The stability of an electrical grid is compromised by unbalance between production and load; therefore, across the engineering literature, stability is an important concern in interconnected power systems. The present work seeks to remedy the phenomenon of instability of a power system linked to a Static Synchronous Compensator (Statcom) by introducing power system stabilizers (PSSs). The typical two-area, four-machine, and eleven-bus system is submitted to a three-phase fault without any control. A Statcom intruduces separately at the center of the line and at the access of the two areas of the studied system, and power system stabilizers are connected to the exciter with different inputs (conventional PSS with electrical power input; conventional PSS with generator speed input; multi-band PSS (MB_PSS)), offering the possibility of returning to the permanent regime for a short period. Matlab/Simulink simulation permits us to plot the inter-area transfer rotor speed and survey the permanent divergence of the oscillatory regime. Results are compared in order to detect the best solution to achieve transient stability.
• Comparing the results of our simulation, we concluded that installing a delta w PSS with Statcom at the center of the line in the two-area power system provides the best solution to avoid the problem of instability in electrical grids.

1.36. Integrated Linear Transformer-Based Diode Bridge Rectifier for Improved Power Quality in Electric Vehicle Charging Stations

• Sugunakar Mamidala and Yellapragada Venkata Pavan Kumar
• School of Electronics Engineering, VIT-AP University, Amaravati 522241, Andhra Pradesh, India
• Electric vehicle (EV) charging stations are becoming increasingly widespread, but their front-end rectifiers often degrade grid power quality by introducing high-input current harmonics, a low power factor, and voltage distortion. Although conventional diode bridge rectifiers (DBRs) are simple and low-cost, they typically exhibit total harmonic distortion (THD) exceeding 25% and power factors below 0.80. To address these issues, active power factor correction (PFC) techniques have been employed in the literature; however, they increase system complexity, cost, and control algorithm sophistication. Thus, this paper proposes a linear integrated transformer (ILT)-based DBR, which is designed to improve power quality in EV charging stations without relying on active control mechanisms. The proposed configuration integrates a linear transformer, passive filter network, and diode bridge to achieve both voltage step-down with galvanic isolation and harmonic mitigation in a single structure. This system offers improved voltage regulation, flux balancing, filter resonance, and reduced current distortion. The proposed system is validated using MATLAB/Simulink R2021a. The results demonstrate that it achieves a THD of 4.32%, complying with IEEE 519 harmonic standards. In addition, the input power factor improves to 0.981. The system also reduces the DC output voltage ripple from 6.8% to 1.2%, enhances voltage regulation by 9.1%, and increases overall efficiency to 96.3%. These findings establish the proposed ILT-DBR as an affordable, robust, and compact solution for next-generation EV charging infrastructure, specifically designed to meet the needs of smart grid deployment and integration in Tier-2 and Tier-3 cities, where simplicity and power quality compliance are priorities.

1.37. Integration of Deep Learning Methods into the Design of Microwave Transceiver Components for 5G Mid-Band System

• Pedro Escudero-Villa, Santiago Huebla-Huilca and Jenny Paredes-Fierro
• Facultad de Ingeniería, Universidad Nacional de Chimborazo, Riobamba 060108, Ecuador
• This study evaluates the application of deep learning methods to the design of a microwave transmitter–receiver system operating in the mid-band of 5G communications. The proposed system comprises four stages—signal generation, amplification, mixing, and filtering—each designed individually using traditional microwave theory and then integrated into a full transceiver. Simulation data were generated in MATLAB and ADS, and four convolutional neural networks (CNNs) were implemented in Python (TensorFlow/Keras), with architectures ranging from 11 to 271 layers and training datasets between 4000 and 12,000 samples. Training was performed over 200–1000 epochs using Adam optimization, ReLU/linear activations, and sequential dense connections. Across all networks, the average error reduction exceeded 90%, with convergence achieved after the third training cycle for most components. For the transceiver integration, baseline design simulations indicated a transmitted power of −32.637 dBm with a gain of 1.116 dB. The deep learning-based design yielded comparable results, with a transmitted power of −33.912 dBm and a gain of 0.738 dB. These results demonstrate that the neural network models successfully approximated the behavior of microwave components without degrading system-level performance. Further analysis of scattering parameters (S-parameters) confirmed that the CNN-trained models maintained acceptable matching and frequency response across the 3.5 GHz operating band. Overall, this study demonstrates a complementary design methodology for microwave systems in 5G applications, enabling the modeling and optimization of multiple components simultaneously.

1.38. IoT-Based Energy Management and Automation System with Mobile Control for Educational Buildings

• Lucas Souza De Freitas ¹ and Israel Gondres Torné ²

¹ 

Course of Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

² 

PPGEEL-Postgraduate Program in Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

• Public institutions often face challenges in managing energy efficiently across distributed facilities with limited technical personnel. Manual control of lighting and environmental conditions contributes to unnecessary energy consumption, especially outside regular operating hours. Emerging IoT platforms offer accessible alternatives for automation without the need for complex infrastructure. Integrating mobile applications with microcontroller-based systems can support real-time monitoring and control, reducing waste and simplifying operational routines. This project explores the development of an IoT-based energy management system enabling remote device control through applications that are compatible with Android and iOS. The architecture is based on ESP32 microcontrollers integrated with temperature and humidity sensors (DHT11), LEDs, and relays. Three platforms were tested: MQTT Dashboard, ESP RainMaker, and a custom mobile app developed using MIT App Inventor. MQTT was used for data transmission and command handling via public brokers. The mobile app allowed for profile selection, room identification, sensor data visualization, and lighting control. MQTT Dashboard provided a stable interface for real-time communication, while ESP RainMaker added automation features such as scheduled routines. All approaches demonstrated consistent functionality, with MIT App Inventor standing out for its ease of use and educational value. The system supports scalability, enabling expansion to other rooms and buildings. These results confirm the feasibility of implementing remote energy control through open technologies, offering a practical solution for improving efficiency and simplifying maintenance routines in public educational institutions.

1.39. IoT-Enabled Wearable System for Real-Time Fall Detection and Elderly Monitoring

• Isabella Andrade Cabral, Fábio de Sousa Cardoso, Angilberto Muniz Ferreira Sobrinho and Israel Gondres Torné
• PPGEEL-Postgraduate Program in Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil
• Falls are one of the leading causes of injury and loss of autonomy among the elderly, especially in the context of aging populations and the growing need for real-time health-monitoring technologies. This study develops and validates a low-cost wearable system that is designed to detect falls and monitor posture using embedded Internet of Things (IoT) infrastructure. The system architecture integrates an ESP32 microcontroller with an MPU6050 inertial sensor, wirelessly transmitting motion data via the MQTT protocol to a Raspberry Pi 3, which processes the information and activates an external camera when a fall is suspected. A threshold-based algorithm was implemented to classify user postures and detect abrupt motion variations associated with fall events. The entire system was validated through controlled experiments simulating daily activities—such as standing, walking, sitting, and lying down—as well as various types of falls. The results indicated reliable performance in detecting upright and supine postures and capturing acceleration and angular velocity patterns during simulated falls. However, the system presented difficulties in distinguishing sitting from fall events and identifying soft falls, achieving an overall classification accuracy of 60%. Hardware integration, wireless communication stability, and real-time visualization through the Node-RED dashboard were implemented, highlighting the feasibility of combining embedded sensing with lightweight communication protocols for wearable elderly-monitoring applications.

1.40. Modeling the Influence of ADC Transfer Function Nonlinearity on the Spectral Characteristics of Digital Signals

• Anzhelika Stakhova ^1,2

¹ 

Department of Structural Mechanics, Faculty of Civil Engineering, Slovak University of Technology in Bratislava, Bratislava SK-810 05, Slovakia

² 

Department of System Analysis and Information Technology, Faculty of Economics and Law, Mariupol State University (Temporarily Relocated), Kyiv 03037, Ukraine

• Nonlinearity in the transfer function of analog-to-digital converters (ADCs) is a major factor contributing to measurement errors in digital signal processing systems. While ideal ADCs produce a linear mapping between input voltage and digital output code, real devices introduce deviations that distort the spectral composition of the signal. Manufacturers typically specify only integral (INL) and differential (DNL) nonlinearity parameters, which provide limited insight into the practical impact of these imperfections.
• This study presents a modeling approach for estimating the influence of ADC nonlinearity on the amplitude characteristics of digital signal spectra. Based on known values of INL and DNL, analytical relationships are used to simulate the appearance of additional harmonics and the deviation of the fundamental spectral component, without requiring experimental reconstruction of the actual ADC transfer function. Both sinusoidal and polyharmonic input signals are considered to reflect realistic measurement conditions.
• Simulation results show that even moderate nonlinearity levels can lead to measurable spectral distortion, which may compromise signal integrity in precision applications. The developed approach provides a practical framework for evaluating the suitability of ADCs in spectral measurement systems and helps anticipate performance limitations before hardware implementation.
• The findings can support engineers and designers in optimizing ADC selection and mitigating error sources in digital measurement devices, particularly in fields requiring high spectral accuracy, such as instrumentation, communications, and signal diagnostics.

1.41. Non-Invasive Diagnosis of Broken Rotor Bars in Induction Motors Using Deep Learning and GASF Representations

• Jose Luis Garcia Tucci ¹, Jordi Burriel-Valencia ², Ángel Sapena-Bañó ², Javier Martínez-Román ² and Kevin Barrera^1,2,3

¹ 

Universitat Oberta de Catalunya (UOC), Av. del Tibidabo 39-43, 08035 Barcelona, Spain

² 

Institute for Energy Engineering, Universitat Politècnica de València, Cmno. de Vera s/n, 46022 Valencia, Spain

³ 

Control, Data and Artificial Intelligence (CoDAlab), Escola d’Enginyeria de Barcelona Est (EEBE), Universitat Politècnica de Catalunya (UPC), Eduard Maristany 16, 08019 Barcelona, Spain

• Introduction and objectives: Three-phase induction motors are widely used in industry for their reliability and low maintenance. However, faults such as broken rotor bars (BRBs) can disrupt performance and increase costs. Early detection is therefore necessary. This work presents a non-invasive method that combines phase current signals with deep learning to detect and classify BRB faults in squirrel-cage induction motors.
• Methods: Signals were generated through FEMM simulations for rotors with 22, 24, 26, and 28 bars—typical configurations in industrial motors. Zero to six broken bars were considered, and the resulting phase current signals were transformed into two-dimensional images using Gramian Angular Summation Fields (GASFs) to highlight fault-related patterns. Two datasets were used: dataset A (79,086 GASF images, 11,298 per class) for training, and dataset B (22,488 time signals, with class sizes from 2459 to 3212) for testing. Several convolutional neural networks with residual connections (ResNet18 to ResNet152) were evaluated. ResNet152 was selected for its superior performance, achieving 95.13% accuracy and 96.77% sensitivity on dataset A.
• Results: Given the class imbalance in dataset B, metrics that are suited for imbalanced multiclass classification were used. The model achieved a sensitivity of 0.95, macro F1-score of 0.87, Matthews correlation coefficient of 0.82, and Jaccard index of 0.78, showing good generalization.
• Conclusion: The proposed system offers a non-invasive, data-driven approach to BRB fault diagnosis, which is capable of operating under real conditions without interrupting the motor. Its industrial applicability is reinforced by a graphical interface, allowing users to upload raw signals and obtain reliable predictions easily, supporting predictive maintenance strategies.

1.42. Open-Source Portable Spectroscopic Device for Rural Water Monitoring Applications

• Pedro Escudero, Franklin Shilquigua-Rosacela and Jenny Paredes-Fierro
• Facultad de Ingeniería, Universidad Nacional de Chimborazo, Riobamba 060108, Ecuador
• Access to reliable, real-time water quality analysis in remote regions is essential for environmental monitoring and public health. Traditional spectrophotometric methods, while accurate, are expensive and not suitable for in situ use, especially in low-resource contexts. This research addresses the lack of affordable portable instrumentation by proposing the development of a rapid, tailored, and low-cost optical spectrometer capable of characterizing water samples directly at the collection site. The main objective of this work was to design and implement a portable optical system using accessible components and open-source technology for the optical analysis of water from rural sources in Ecuador. A descriptive and experimental methodology was followed, encompassing three phases: theoretical analysis of optical systems, simulation of optical and electronic subsystems using FreeCAD and Proteus, and the physical construction of a working prototype with 3D-printed parts and a custom PCB. The system integrates a white LED, plano-convex lenses, adiffraction grating, a 3DU33 phototransistor, and an Arduino Nano with Bluetooth transmission. Water samples from four different sources were tested and compared with a commercial spectrophotometer (DR-2010). The prototype showed good agreement in the visible range with an acceptable standard deviation, making it a viable and economical alternative for field-based water quality monitoring. Future enhancements will focus on improving calibration accuracy and optical resolution.

1.43. Optimization of Electrostatic Separation of Aluminum–Plastic Composites from Electronic Waste Using an Inclined Double-Sided Conveyor

• Sayah Rafik ¹, Boudra Hanane ¹ and Djehaf Kaouthar ²

¹ 

APELEC Laboratory, Djillali Liabes University of Sidi-Bel-Abbes 22000, Algeria

² 

Department of Chemistry, Djillali Liabes University of Sidi-Bel-Abbes 22000, Algeria

• The optimization of electrostatic separation systems is essential for increasing the recycling efficiency of electrical and electronic waste (e-waste) and supporting sustainable waste management. This work presents an innovative double-sided inclined electrostatic conveyor system, assisted by controlled vibrations, for separating aluminum–plastic composites from electronic waste materials. The device combines two complementary electrical mechanisms: electro-adhesion, which retains conductive aluminum particles through applied electric fields, and traveling-wave electric fields, which repel insulating plastic particles. Vibrations enhance particle mobility, limit agglomeration, and improve separation dynamics. A systematic optimization of the electrical system was performed using a three-level full factorial design (3²). Two operational parameters were selected: applied voltage (1.0, 1.5, and 2.0 kV) and conveyor inclination angle (20°, 30°, and 40°). The responses were aluminum purity and recovery efficiency. Eighteen randomized runs were carried out, and results were analyzed statistically by analysis of variance (ANOVA).
• Experimental results confirmed that both voltage and inclination significantly affect separation performance. Increasing these electrical parameters improved aluminum purity, which reached 100% at 2.0 kV and 40°. Recovery efficiency remained consistently high, attaining 99% at optimum settings. The interaction between voltage and inclination was significant, highlighting the need to adjust these factors simultaneously. Regression models showed excellent predictive capability (R² > 98%), validating the design methodology’s robustness. This study confirms the effectiveness of factorial design for optimizing electrostatic separation systems in electrical engineering applications. The identified optimal electrical operating conditions ensure maximum aluminum purity and recovery efficiency, offering practical perspectives for industrial recycling of aluminum–plastic waste from electrical and electronic equipment.

1.44. Performance Assessment of Adaptive MRAC-PID Versus Conventional PID for Height Stabilization of Lippisch-Type WIG Vehicles

• Isabella Andrade Cabral, Edward Pinto Pimenta Junior, Rhedson Francisco Fernandes Esashika, Fábio de Sousa Cardoso, Angilberto Muniz Ferreira Sobrinho and Israel Gondres Torné
• PPGEEL-Postgraduate Program in Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil
• Wing-in-Ground Effect (WIG) vehicles operating at low altitudes benefit from increased aerodynamic efficiency but require precise control systems to maintain stable flight near surfaces. The Lippisch configuration introduces additional complexity in height stabilization due to its inherent sensitivity to disturbances. WIG vehicles with a Lippisch configuration exhibit distinctive dynamic characteristics due to their operation close to water surfaces, posing challenges for achieving robust and stable height control. Traditionally, Proportional–Integral–Derivative (PID) controllers have been employed in autopilots built on the ArduPilot platform. However, these controllers are typically tuned for specific nominal conditions, revealing limitations when facing dynamic uncertainties and environmental disturbances. This paper presents a comparative analysis between a conventional PID controller and a hybrid approach combining PID with Model Reference Adaptive Control (MRAC), specifically for altitude control of a Lippisch-type WIG vehicle subjected to wind gust disturbances. The MRAC implementation is based on a stable reference model, enabling real-time adaptive adjustment of PID gains in response to disturbances and variations induced by ground effect. Simulation results, obtained in a MATLAB/Simulink environment integrated with ArduPilot (Mission Planner SITL), demonstrate that the hybrid PID+MRAC controller achieves improvements in tracking error reduction and settling time under wind gust conditions compared to the conventional PID controller. The integration of adaptive elements with traditional PID control contributes to more consistent performance in variable operating scenarios.

1.45. Prescribed Performance Adaptive Sliding Mode Control for Foldable Quadcopter UAV

• Ibrahim Abdullahi Shehu ¹, Zaharuddeen Haruna ¹, Muhammad Bashir Mu’azu ¹, Norhaliza Abdul Wahab ² and Sani Salisu ¹

¹ 

Department of Electrical Engineering, Ahmadu Bello University, Zaria, Nigeria

² 

Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia

• Foldable quadcopter represent a new frontier in aerial robotics technology. The ability of foldable quadcopter to reconfigure its geometry inflight and adapt its self to various flight scenarios offer enhanced agility, maneuverability, aerodynamic efficiency, and mission versatility compared to traditional quadcopter. However, the folding function introduces significant parameter variations such as center of gravity, inertia, and nonlinear dynamics in addition to inherent underactuation, coupling dynamics, and external disturbances. Thus, folding mechanism presents significant challenges to conventional control approaches. To solve the drawbacks of conventional control approach, this article proposed the development of prescribed performance adaptive sliding mode control (SMC) for foldable quadcopter UAV. It models the morphing quadcopter as rigid body system with five morphing formations (X, Y, H, O, and T). The prescribed performance SMC approach systematically addresses the time varying parameter and aerodynamic impact resulting from the morphing formation. Using Lyapunov theory, the adaptive SMC that ensures the error evolution is within prescribed performance bounds, the closed loop stability, and precise trajectory tracking under parametric and nonparametric uncertainties is designed. The effectiveness of the proposed control algorithm is evaluated and benchmarked via simulation in structured and unstructured environment against conventional sliding mode control (SMC), PID, and LQR control methods. The simulation results indicate the performance of the adaptive SMC, improved robustness, and adaptability compared to benchmarked control methods. The simulation results demonstrated that, adaptive control approach is a viable and effective solution for managing the complex dynamics and uncertainties of foldable quadcopter UAV.

1.46. Prioritizing RFID Applications in Civil Engineering: A Hierarchical Approach

• Ahmet Karakurt
• Department of Civil & Environmental Engineering, University of Delaware, Newark, DE, USA
• This study utilizes the Analytic Hierarchy Process (AHP) to assess the relative impact of various Radio Frequency Identification (RFID) application subtypes within the domains of Civil Engineering and general Engineering outputs. By normalizing and assigning weighted scores to data, a structured comparison was made across four publication categories: Civil Engineering Journal Articles, Civil Engineering Conference Papers, Engineering Journal Articles, and Engineering Conference Papers. The AHP method provided a robust framework for evaluating the significance of each application type, allowing for objective prioritization. The analysis revealed that RFID applications focused on Safety and Security consistently ranked highest across all categories, highlighting their essential role in improving infrastructure management, operational reliability, and project safety. Conversely, subtypes such as Environmental Monitoring and Water Resource Management demonstrated relatively low relevance, suggesting limited impact or underutilization in current engineering literature and practice. This research is significant as it introduces a quantitative and systematic method to evaluate the effectiveness of RFID technologies in engineering contexts. The findings offer valuable insights for researchers, engineers, and policymakers, guiding future efforts in adopting RFID systems to optimize civil infrastructure, streamline construction processes, and enhance the overall efficiency and safety of engineering projects. The study thus supports evidence-based decision-making in technology adoption.

1.47. Real-Time Emotion-Based Concentration Estimation: An Educational Framework with Lightweight Neural Networks

• Edward Pinto Pimenta Junior, Daniel Guzmán Del Río, Miguel Angel Orellana Postigo and Israel Gondres Torné
• PPGEEL-Postgraduate Program in Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil
• This work presents a facial emotion-based concentration monitoring system, designed with a didactic focus for students beginning their studies in Artificial Intelligence. The application uses the OpenCV library for real-time video capture and face detection, combined with a simple neural network model trained on facial expression images to classify seven basic emotions: anger, disgust, fear, happiness, neutral, sadness, and surprise. The key innovation of this project lies in its simple and accessible structure, allowing students to grasp core concepts of computer vision and machine learning through practical experimentation. The model was intentionally trained using a reduced and simplified dataset, emphasizing how basic neural architectures can still produce functional results in real-world scenarios. Based on the detected emotion, the system applies straightforward rule-based logic to estimate the user’s concentration level (high, medium, or low), offering an intuitive application of AI in educational or interactive environments. In addition to promoting technical learning, the codebase is modular, well-documented, and easily encourages students to explore extensions such as model refinement, data preprocessing, or alternative AI approaches. This work bridges theoretical learning and hands-on AI application, highlighting how even minimal resources and simple neural models can serve as powerful tools for understanding intelligent systems and human–computer interaction.

1.48. Real-Time Energy Consumption Forecasting Using Neural Networks for Smart Management Systems

• Antony Alexsandrey Marques De Souza ¹ and Israel Gondres Torné ²

¹ 

Course of Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

² 

PPGEEL-Postgraduate Program in Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

• The growing demand for intelligent energy use requires systems capable of predicting consumption behavior in real time and adapting to different operational environments. Traditional forecasting methods often lack flexibility when integrated into modern energy monitoring platforms. Advances in neural network architectures offer alternatives for capturing nonlinear and dynamic consumption patterns. Energy forecasting also plays a central role in optimizing distributed systems and reducing operational uncertainty in energy management. This study introduces an intelligent software system designed to perform real-time energy consumption forecasting, integrated with Energy Management Systems (EMSs). The proposed solution communicates with sensing devices via the MQTT protocol, allowing continuous data acquisition and flexible system integration. Two forecasting models were implemented: a hybrid ARIMAX-NN model that combines statistical methods with neural networks and a CNN-LSTM Autoencoder (CNN-LSTM-AE) model that captures temporal dependencies and nonlinear behaviors. Public datasets from residential and commercial buildings were used for model validation. The software adapts to different input configurations without requiring structural changes, supporting a wide range of metering devices and data formats. Forecast results are updated in real time and can be seamlessly integrated into operational environments. The system’s modular design enables future expansions such as graphical interfaces and alert generation mechanisms. This approach provides a scalable foundation for supporting energy efficiency initiatives in residential, industrial, and commercial applications.

1.49. Real-Time Gain Scheduling via Adaptive Fuzzy PID Control: Application to Nonlinear Inverted Pendulum Stabilization

• Feddaoui Anis ¹ and Mohammed Abdeldjalil Djehaf ²

¹ 

Laboratory of Electromechanical Engineering, Electromechanical Dept, Faculty of Technology, Badji Mokhtar University of Annaba, Annaba, Algeria

² 

Department of Automatic Control, Faculty of Electrical Engineering, University of Djillali Liabes (UDL) of Sidi Bel Abbés, Sidi Bel Abbés, Algeria

• This work presents the design and validation of an Adaptive Fuzzy PID (PIDFA) controller for real-time stabilization of nonlinear and underactuated systems, using the inverted pendulum as a benchmark. Conventional PID controllers, while widely used, lack robustness in dynamic environments due to their fixed parameters and reliance on precise models. The proposed PIDFA architecture embeds a fuzzy inference mechanism that continuously adjusts the PID gains based on an instantaneous system error and its derivative, eliminating the need for offline tuning and improving performance under uncertainty.
• The control design integrates fuzzification, rule-based gain scheduling, and defuzzification. Separate fuzzy systems regulate the proportional, integral, and derivative components, enabling real-time gain adaptation. A set of 49 linguistic rules per gain ensures interpretable and efficient control logic. Simulations conducted in MATLAB/Simulink evaluate the controller under three scenarios: stabilization from initial deviation, step disturbance rejection, and structural parameter variation.
• Results confirm that the PIDFA achieves fast stabilization (settling time 1.2 s), low overshoot (5%), and robust performance without saturation or chattering. The controller adapts to parameter shifts and external disturbances without manual reconfiguration, demonstrating strong real-time applicability. This study supports the use of fuzzy adaptive controllers in managing uncertain and nonlinear systems and outlines a methodology transferable to broader domains such as robotics and power systems.

1.50. Real-Time Monitoring of Induction Motor Parameters Using ESP32 and MQTT Protocol

• Israel Gondres Torné ¹, Rubem Silas Dias Silva ², Lennon Brandão Freitas Nascimento ² and Alejandro González Ramírez ²

¹ 

PPGEEL-Postgraduate Program in Electrical Engineering, Superior High School, State University of Amazonas (UEA), Manaus 69050-020, Brazil

² 

Course of Electrical Engineering, Superior High School, State University of Amazonas (UEA), Manaus 69050-020, Brazil

• Three-phase induction motors are widely used in industrial systems and are responsible for a significant portion of electricity consumption. Monitoring their operating conditions is essential to support maintenance strategies and reduce unexpected downtime. This work presents the development and implementation of a real-time monitoring system for electrical and mechanical parameters of three-phase induction motors using embedded Internet of Things (IoT) technologies. The proposed system integrates an ESP32 microcontroller with multiple sensors for measuring temperature, vibration, current, and voltage. The collected data are transmitted wirelessly using the MQTT protocol to a monitoring interface built in Python, providing real-time visualization through a graphical dashboard. The firmware was developed using FreeRTOS to manage concurrent tasks for sensor acquisition and data transmission, ensuring synchronization and efficient processing. Prototyping involved two custom-printed circuit boards (PCBs): one for sensor data acquisition and system management and another dedicated to power quality measurement using the ADE7758 chip. Validation tests were conducted by coupling the system to a three-phase induction motor under laboratory conditions. The temperature and vibration sensors recorded readings that varied according to motor behavior, with the vibration sensor capturing signals during both motor startup and steady-state operation. Electrical measurements included current and voltage values obtained through the power quality monitoring circuit, with variations observed in specific intervals due to noise and assembly-related factors.

1.51. Sensitivity and Robustness Analysis of Proportional–Resonant Current Control for Six-Phase IMs

• Néstor Villamayor ¹, Magno Ayala ², Osvaldo Gonzalez ² and Gustavo Ojeda ³

¹ 

Facultad de Ingeniería, Universidad del Cono Sur de las Américas (UCSA), Asunción, Barrio Bella Vista 001534, Paraguay

² 

Laboratorio de Sistemas de Potencia y Control (LSPyC), Centro de Innovación Tecnológica (CITEC), Facultad de Ingeniería (FIUNA), Universidad Nacional de Asunción, Luque, Isla Bogado 110948, Paraguay

³ 

Facultad de Ingeniería, Universidad del Cono Sur de las Américas (UCSA), Asunción, Barrio Bella Vista 001534, Paraguay

• The development of advanced current control strategies for six-phase induction machines (IMs) has been driven by the need to take full advantage of their inherent efficiency, fault tolerance, and reliability. In that sense, proportional—resonant (PR) controllers, known for their current tracking accuracy in a stationary reference frame, are particularly well-suited to multiphase drive applications. This work presents a sensitivity and robustness analysis of a PR current controller designed for six-phase IM drives. The PR is evaluated through simulation under four rigorous test scenarios. Two tests assess current tracking accuracy and dynamic performance at low and high speeds, including full-speed reversals between ±500 r/min and ±1000 r/min. The remaining tests introduce ±50% uncertainties in stator resistance and magnetizing inductance to evaluate robustness against parameter mismatches. Across all scenarios, the controller achieves total harmonic distortion (THD) below 0.35% and root mean square error (RMSE) under 0.02 A in both the (α-β) and the (x-y) plane. Even under abrupt speed reversals, current stability is restored in approximately 2.5 s, demonstrating robust dynamic behavior. Compared with more complex model-based approaches, the proposed PR control scheme achieves comparable tracking accuracy and robustness while offering simpler implementation and lower computational demand. These results validate the feasibility of PR-based control for high-performance multiphase drives operating under variable conditions.

1.52. Standards-Oriented Gap Analysis of Traceability in Electronic System Design

• Cigdem Avci
• Assistant Professor, TOBB University of Economics and Technology, 06510 Ankara, Turkey
• Traceability, the ability to follow and interpret system behavior from design through operation, is well-established in software engineering through formal standards and structured workflows. In contrast, electronic system design often lacks comparable mechanisms, particularly at the level of physical components, signal pathways, and runtime system behavior.
• This paper presents a standards-oriented gap analysis focusing on traceability practices across three key layers of electronic system design: the circuit/component level, the embedded firmware level, and the system-level behavior. Drawing from published standards and documentation guidelines in both software and electronics disciplines, the study identifies critical areas where electronics workflows provide limited support for runtime observability and post-deployment diagnosis.
• The analysis highlights that, while validation and testing protocols exist for electronic hardware, comprehensive traceability frameworks—spanning from schematic design to deployed system behavior—are not sufficiently standardized. This gap becomes particularly relevant in safety-critical and sensor-integrated applications.
• As the research methodology, relevant standards from software engineering and electrical and electronics engineering will be selected, specifically those addressing traceability practices. Traceability-related content will be extracted and analyzed to provide a structured, comparative discussion across the two domains.
• The paper concludes by outlining future research directions for integrating traceability-aware design principles into electronic system development, using cross-disciplinary insights inspired by traceability in software engineering.

1.53. Testing and Validation Procedure of Communication Between an Industrial Robot Controller and a PLC via SLMP IoT Protocol

• Fábio Monte Braz, Angilberto Muniz Ferreira Sobrinho and Fábio de Souza Cardoso
• Universidade do Estado do Amazonas and Manaus, Manaus 69020-120, Brazil
• Introduction: One of the main challenges of Industry 4.0 is ensuring effective communication between different automation systems, such as industrial robots and Programmable Logic Controllers (PLCs). This work presents a validation test procedure for communication between an industrial robot controller and a PLC using a Seamless Message Protocol (SLMP) IoT protocol, addressing the critical need for seamless integration in modern manufacturing environments.
• Methods: The proposed solution uses TCP/IP sockets in conjunction with the SLMP protocol, developed by the CC-Link Partner Association, which enables communication between industrial devices using conventional Ethernet networks. The implementation was carried out in the RAPID language, specifically designed for industrial robot programming. Systematic validation tests were conducted to evaluate communication performance, measuring success rate, average response time, and potential communication errors across multiple test cycles.
• Results: The experimental validation demonstrated exceptional performance with a 100% success rate and an average response time of 11.3 ms over 100 consecutive test cycles. No communication errors were detected during the entire testing period, indicating robust and reliable data exchange between the robot controller and PLC.
• Conclusions: The results confirm the viability and efficiency of the proposed SLMP-based solution for applications in industrial environments that require integration of different automation equipment, providing a reliable foundation for Industry 4.0 implementations

1.54. Unstable Gait Recognition Using Trunk Inertial Data and Body Measurements of Public Datasets: A Pilot Study

• Kodai Kitagawa ¹, Chikamune Wada ² and Nobuyuki Toya ³

¹ 

Department of Industrial Systems Engineering, National Institute of Technology, Hachinohe College, Hachinohe, Japan

² 

Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, Kitakyushu, Japan

³ 

Department of Medical Management and Informatics, Hokkaido Information University, Ebetsu, Japan

• Introduction: Elderly people sometimes experience fall accidents since some of them cannot recognize their own stability in walking. Thus, fall prevention systems that measure and inform unstable walking have been developed. However, many previous systems required multiple sensors. The purpose of this study was to develop and test a gait recognition system using only a single inertial sensor for daily fall prevention. Methods: The proposed method recognizes an unstable gait by machine learning with trunk inertial data (three-axis acceleration and angular velocity) on the lower back and body measurement values (height and weight). The proposed method was trained and tested by the North American Congress on Biomechanics (NACOB) multi-surface walking dataset published by Jlassi et al. The trunk inertial data and body measurement values of 134 people in the NACOB public dataset were used in this study. The proposed method recognized two gait patterns on flat (stable) and bumpy (unstable) roads. Machine learning was implemented using the k-nearest neighbor algorithm (k = 1). Training and testing were conducted via 5-fold cross validation. The accuracy and confusion matrix of gait recognition were evaluated. Results: The results showed that the proposed method could recognize stable and unstable gait patterns with greater than 80% accuracy. This accuracy was comparable to previous gait recognition. Conclusions: The results indicate the possibility that the proposed method can be used for daily gait recognition systems using a single inertial sensor. Acknowledgements: This study was supported by JSPS KAKENHI (Grant Number: 25K16012).

1.55. Weather-Induced Effects on FSO Systems in Desert Environments: A Case Study of Algeria

• Hadjadji Narimane
• Electrical Engineering Departement, Technology Faculty, University of El Oued, B.P. 789, 39000 El Oued, Algeria
• This study investigates Free Space Optical (FSO) communication performance in Algeria’s desert environments, where extreme temperatures, low humidity, and dust storms challenge reliability. Through numerical simulations, we analyze atmospheric turbulence effects using the refractive index structure parameter (Cn²), specifically calibrated for El Oued’s severe climate conditions.
• Our research evaluates critical performance metrics including signal-to-noise ratio (SNR), bit error rate (BER), and scintillation index across different optical wavelengths. Results demonstrate that longer wavelengths (1550 nm) show significantly better turbulence resilience compared to shorter wavelengths (850 nm), providing essential guidance for FSO system design in arid regions. The study reveals a clear correlation between turbulence strength and signal degradation, with BER increasing exponentially under strong turbulence conditions.
• Furthermore, we examine climate change impacts on FSO viability, as projections indicate increasing extreme heat, droughts, and dust storms in Algeria. These changes are expected to intensify atmospheric turbulence, potentially reducing FSO reliability by 15–20% in coming decades. Our analysis shows that adaptive wavelength selection and power adjustment strategies can mitigate these effects, maintaining acceptable performance levels even under worsening conditions.
• This work provides both theoretical and practical contributions to FSO deployment in challenging environments. The Algerian case study offers valuable insights for similar desert regions worldwide, addressing the critical need for robust communication infrastructure in climate-vulnerable areas. Our findings support the development of more resilient FSO systems capable of withstanding the combined challenges of existing harsh conditions and future climate changes, while maintaining high-bandwidth performance essential for modern communication networks.

2. Mechanical and Aerospace Engineering

2.1. Construction Simulation Optimization Using Variance Reduction Techniques

• Mohammed Mawlana ¹ and Amin Hammad ²

¹ 

Department of Construction Management, Thomas Jefferson University, Philadelphia, USA

² 

Concordia Institute for Information Systems Engineering, Concordia University, Montréal, QC, Canada

• Discrete event simulation in construction research has been used extensively to evaluate the performance of construction operations. Obtaining an optimal configuration of the decision variables using simulation alone requires the evaluation of all possible combinations of the values of these variables, which is not feasible for problems with a large search space. To this end, simulation is often coupled with an optimization algorithm in order to optimize the construction operations. However, the major drawback of the current stochastic simulation optimization methods is that they require a long computational time and may present inferior solutions in the final Pareto front. This research presents a DES optimization framework that can be used by decision-makers to enhance and improve the current practice of decision-making in construction projects. The aim of the framework is to select a set of near-optimal resource combinations that minimize the total project duration and total project cost. The objective of this research is to investigate the benefits of incorporating variance reduction techniques in discrete event simulation optimization within the context of simulation optimization of construction operations. Three variance reduction techniques are studied using a case study, namely, common random numbers, antithetic variates, and a joint application of the previous two techniques. The incorporation resulted in an average time saving of 81.81% while improving the quality of Pareto solutions by 2.4% and reducing the presence of inferior solutions by 63.15%.

2.2. Distribution of Displacement Fields in Additively Manufactured Composite Parts Measured by XRay Tomography

• Jorge Guillermo Diaz Rodrigues ¹, Arthur Martins Barbosa Braga ², Renata Lorenzoni ³ and Dario Prada Parra ⁴

¹ 

Tecnologico de Monterrey. Escuela de ciencias e ingeniería. Av. General Ramon Corona 2514, Zapopan 45019, México

² 

Ouro Nova, São Cristóvão, Brazil

³ 

Federal Institute For Materials Research and Testing Primary, Berlin, Germany

⁴ 

Pontifícia Universidade Católica do Rio de Janeiro, PUC-Rio, Rio de Janeiro, Brazil

• Microcomputed tomography (mCT) is an advanced technique developed in the medical field and currently used in various areas of society to perform non-destructive testing on various materials, such as continuous fiber-reinforced composites, enabling internal evaluation of the material under loading conditions. Samples of additively manufactured composites reinforced with continuous Kevlar fibers and glass fiber were subjected to compression at two pressure levels (240 and 280 psi) using a pneumatic pressure cell transparent to the microtomograph, designed in the laboratory and optimized for maximum safety within the microtomograph. The results obtained from the mCT tests are digital images with a resolution of 34 μm in .DICOM format, a characteristic of this type of equipment. The digital images are segmented and concatenated to extract the characters necessary to calculate the displacement fields. During asymmetric bending, the (mCT) was a tool that helped observe the behavior of glass and Kevlar fibers and the short carbon fiber matrix (Onyx) under non-uniform stresses, providing important in situ information for the mechanical characterization and design optimization of composites in advanced structural applications. Differences in displacement were observed for three pressure levels (0, 240, and 280 psi), as well as opposite displacements for tension and compression. Finally, it was observed that the short carbon fiber (8 μm in diameter) embedded in the matrix exhibited transparency due to resolution.

2.3. Airflow and Thermal Analysis of a Small Data Center Under Varying Load Conditions Through Computational Fluid Dynamics in Steady-State Conditions

• Marielle Jewel Mendoza Villacarlos ¹, Justine Noel Ulat ¹, Paolo Rommel Sanchez ², Ralph Kristoffer Gallegos ² and Marita Natividad Taize De Lumen ¹

¹ 

Department of Mechanical Engineering, University of the Philippines Los Baños, College, Laguna 4031, Philippines

² 

Institute of Agricultural and Biosystems Engineering, University of the Philippines Los Baños, College, Laguna 4031, Philippines

• The optimization of cooling systems and temperature management in data centers has been widely researched; however, this focus has been overly concentrated on large enterprises, leading to an oversight of small-scale ones. This study aimed to develop a validated Computational Fluid Dynamics (CFD) model and assess airflow and temperature distribution under varying heat loads and cooling systems in steady-state conditions. The study utilized CFD simulations and validated these through experimentation at the Digital Innovation Center data center of the University of the Philippines Los Baños. Three cases were analyzed: (1) the current server load and main cooling system, (2) the operation of a backup cooling system, and (3) a scenario of a maximized server load while using the main cooling system. Our results showed that all cases maintained compliance within the ASHRAE Thermal Guidelines, with rack inlet temperatures of 22.52 °C, 26.93 °C, and 16.31 °C. On the other hand, the airflow performance metrics of the Rack Temperature Index (RTI), Supply Heat Index (SHI), and Return Heat Index (RHI) reflected that there was recirculation of air in the server room. Specifically, the mixing that was interpreted based on the SHI, with values of 0.85, 0.98, and 0.60. Using a wall fan was recommended in these cases of recirculation for small-scale data centers. In conclusion, the thermal distribution inside the room is adequate for the heat loads, while the airflow distribution requires improvement. This study offers practical recommendations to enhance energy efficiency and reliability in small-scale data center operations.

2.4. CFD Modeling of Tractor Emissions in the Near-Field: Implications for Occupational Health and Agro-Environmental Quality

• Mark Joshua R Baloria ¹, Ria Salustia DG Duminding ¹, Abel Francis B Laguardia ¹ and Ralph Kristoffer B Gallegos ^2,3

¹ 

Institute of Agricultural and Biosystems Engineering, University of the Philippines Los Baños, College, Laguna 4031, Philippines

² 

Department of Mechanical Engineering, University of the Philippines Los Baños, College, Laguna 4031, Philippines

• The operation of walking-type agricultural tractors (WTATs) emits exhaust gases, which may pose health risks to operators from extended exposure. Comprehending the dispersion characteristics of these emissions is crucial for formulating effective safety protocols. This study evaluated the near-field spatial distribution of carbon monoxide (CO) emissions from a WTAT through experimental measurements and computational fluid dynamics (CFD) simulations, considering different throttle settings, relative wind speeds, and wind angles of attack. The findings indicated that throttle settings had a significant impact on the concentration of CO emissions produced by the engine. A reduction of approximately 86% in CO concentration was observed within 20 cm from the exhaust outlet. At elevated relative wind speeds, the CO plume exhibited a tendency to disperse in alignment with the airflow direction, directing emissions toward the far-left side of the operator while maintaining a low risk of exposure, irrespective of forward speed. Ambient wind angles ranging from −15° to −30° were identified as critical, as emissions were directed toward the operator’s body, thereby increasing potential exposure. The CFD model demonstrated strong agreement with experimental data, particularly at reduced forward speeds, and effectively identified critical exposure zones. This study advocates for the utilization of personal protective equipment, including safety masks, during field operations to reduce health risks linked to inhalation of exhaust gases.

2.5. Comparative Analysis of Hydropower and Thermal-Fired Plants in Zimbabwe’s National Grid

• Hagreaves Kumba
• Department of Industrial Engineering, Durban University of Technology, Durban 4001, South Africa
• Zimbabwe’s national power generation sector heavily depends on two primary sources: hydropower and coal-fired thermal power stations. The country, with a total installed capacity of approximately 1700 MW against a demand of 5000 MW, faces persistent power shortages, leading to imports and frequent blackouts. These two sources present distinct operational characteristics, environmental implications, and resilience to climate and economic pressures. This paper presents a comparative analysis of hydropower and thermal-fired plants in Zimbabwe’s national grid, focusing on their current status, challenges, and future prospects. The study evaluates generation capacity, reliability, cost structure, environmental impact, and long-term sustainability under climate variability. The research will use data from the Zimbabwe Power Company, Zambezi River Authority, policy documents, and relevant government ministries to assess the performance of the power stations. The methodology involves techno-economic and environmental performance assessments. The key indicators to be examined include average annual generation output, operational efficiency, carbon emissions, fuel availability, vulnerability to climate change, and maintenance downtime. Expected results include a clearer understanding of the relative strengths and weaknesses of hydropower and thermal power in Zimbabwe’s energy system, including their suitability for long-term sustainability and climate resilience. The study also anticipates identifying policy and investment pathways that support a more diversified, reliable, and low-carbon electricity mix. The water–energy–climate nexus approach will serve as the analytical framework to understand the research’s interdependencies, trade-offs, and policy gaps. Finally, this paper aims to contribute to ongoing national and regional discussions on energy security and infrastructure modernization in line with sustainable development goals.

2.6. Design and Mechanical Evaluation of SLA-Fabricated Gyroid TPMS Sandwich Structures Under Three-Point Bending

• Sofia Kavafaki and Georgios Maliaris
• Hephaestus Laboratory, School of Chemistry, Faculty of Sciences, Democritus University of Thrace, GR-65404 Kavala, Greece
• Triply periodic minimal surface (TPMS) structures, particularly the gyroid topology, have been considered as appropriate next-generation lightweight structures due to their high stiffness-to-weight ratio, geometric continuity, and tunable mechanical behavior. In the present study, the mechanical performance of gyroid-based sandwich structures under three-point bending is examined, with a focus on the influence of unit cell resolution and wall thickness on the flexural response.
• Three gyroid TPMS core structures were designed using nTop software, featuring a uniform porosity of 70%, and were cast between two solid plates that are each 1 mm thick (20 × 120 mm²) to create sandwich beams with overall dimensions of 20 mm × 20 mm × 160 mm. The core configurations were as follows: (i) 2 × 2 × 10 unit cells (10 mm³ each, wall thickness ≈ 1.54 mm), (ii) 4 × 4 × 32 unit cells (each 5 mm³, wall thickness ≈ 0.77 mm), and (iii) 6 × 6 × 36 unit cells (≈3.33 mm³ each, wall thickness ≈ 0.52 mm).
• The specimens were manufactured employing the stereolithography (SLA) 3D printing technique using a photosensitive polymer resin. The three-point bending tests were performed using a standard fixture according to ASTM C393 standard to measure parameters such as core shear modulus, facing bending stiffness, and failure modes. Pre- and post-testing by Computed Tomography (CT) was carried out to inspect internal flaws, structural integrity, and damage evolution. Results are expressed in the context of unit cell optimisation and its effects on load transfer, stiffness, and energy absorption. This work contributes to the design optimisation of TPMS-based sandwich cores for structural applications with optimised mechanical performance.

2.7. Numerical Study on the Effect of Influent Flow for Film Pressure in a Helical Grooved Plain Bearing of a Canned Motor Pump

• Shinichiro Ejiri
• Fluid Technology Center, Nikkiso Co., Ltd., Tokyo 189-8520, Japan
• A canned motor pump is a turbopump with a non-seal structure that integrates the pump and the motor into a single unit. A feature of the structure is that the pumped liquid also serves as the cooling liquid for the motor and the lubricating liquid for the sliding surfaces. In canned motor pumps, helical grooved plain bearings are typically used to provide adequate cooling of the motor. The flow rate of the influent flow to this bearing varies with the internal flow of the pump. Therefore, pumps that operate under a variety of conditions require suitable design for the tribological effects of this change in the flow rate of the influent flow, but the details of this design have not yet been clarified. This study focuses on the film pressure, which is important for the design of helical grooved plain bearings for canned motor pumps. The purpose of the study is to determine the effect of this influent flow on the film pressure through numerical analysis using Computational Fluid Dynamics (CFD). The CFD software used was OpenFOAM. Calculations under different conditions were performed to analyze the changes in film pressure that occur in the helical grooved plain bearing. Since the influent flow into the bearing affects the film pressure, it is concluded that the design must take into account the pump internal circulation of the pumped liquid, even from a tribological perspective.

2.8. Safety Boundary of Driving Force for Electric Trailers: Stability Analysis of Articulated Vehicles via Co-Simulation

• Wenjun Wang, Heqian Wang, Zhaocong Sun, Shuo Wang, Han Zhang and Yifan Wang
• Tsinghua University, Beijing, China
• Introduction: Electric trailers enhance the tractive performance of conventional articulated vehicles, yet pose significant instability risks (e.g., jack-knifing) during high-torque maneuvers due to inappropriate driving force intervention. This study systematically quantifies the impact of electric trailer propulsion on vehicle stability through dynamic co-simulation and defines its safety-critical operational boundaries to inform real-time control strategies.
• Methods: A high-fidelity vehicle model integrating a tractor and electric trailer was developed in TruckSim, incorporating suspension dynamics and Pacejka tire models. Co-simulation with Simulink enabled bidirectional data exchange: TruckSim provided real-time vehicle states, while Simulink implemented driving force allocation algorithms. Stability criteria included steering angle threshold (∣δ∣ > 15°) and yaw rate deviation (∣Δω∣ > 3°/s). Critical scenarios (e.g., cornering at 0.4 g lateral acceleration, µ-split braking) were tested.
• Results: Electric trailers improved tractive performance by 18% in straight-line acceleration but increased jack-knifing risk by 120% during low-friction cornering when driving torque exceeded 1200 N·m. The safety boundary was characterized by dynamic constraints: articulation angle |θ| < 12° and yaw rate error |∆ω| < 2°/s. Model Predictive Control (MPC) enforcing these boundaries reduced instability incidents by 67% in emergency maneuvers.
• Conclusions: Electric trailers require strict driving force constraints to mitigate instability. The proposed safety boundary, validated through TruckSim-Simulink co-simulation, provides a foundational framework for real-time control systems. Future work should address sensor latency and road uncertainty.

2.9. Three-Dimensional-Printed Natural Fiber-Reinforced Composite Honeycomb Sandwich Structures Inspired by Beetle Forewings for Circular Economy Applications

• Yiheng Song ¹, Haixia Yang ², Chenwei Guo ³, Jie Chen ⁴ and Longgang Tian ²

¹ 

School of Engineering, The University of Tokyo, Tokyo 113-8656, Japan

² 

School of Civil Engineering, Southeast University, Nanjing 211189, China

³ 

School of Aerospace Engineering, Tsinghua University, Beijing 100084, China

⁴ 

Institute of Engineering Mechanics, China Earthquake Administration, Harbin 150080, China

• Introduction: In the context of a circular economy, the integration of renewable materials into structural components is a key pursuit in mechanical engineering. Honeycomb sandwich structures are widely used in energy absorption and impact mitigation due to their high strength-to-weight ratio. This study explores the use of wood-fiber-reinforced poly (lactic acid) (PLA/WF) in 3D-printed sandwich panels inspired by the end-trabecular structure of beetle elytra.
• Methods: Two structural configurations—a traditional honeycomb plate (HP) and a beetle elytron-inspired plate (EBEP)—were fabricated using fused filament fabrication with both pure PLA and PLA/WF materials. Out-of-plane compression tests were conducted alongside finite element analysis (FEA) to evaluate mechanical performance. Additionally, microstructural characterization using SEM and a cost analysis of the materials were performed.
• Results: PLA/WF-based structures exhibited a 10–17% increase in specific compressive strength and a 26–44% improvement in energy absorption compared to PLA counterparts. The EBEP design demonstrated over 90% higher structural efficiency than HP. FEA results closely matched experimental data, confirming model validity. SEM revealed multiple reinforcement mechanisms in PLA/WF, including improved stress transfer, interfacial bonding, and energy dissipation through micro-voids and crystalline domains.
• Conclusion: The synergistic effect of biomimetic geometry and natural fiber reinforcement significantly improves the compressive performance and sustainability of 3D-printed sandwich panels. The PLA/WF-based EBEP offers a lightweight, cost-effective, and eco-friendly solution for mechanical components requiring energy absorption, such as crashworthy modules or protective layers in mechanical systems.

2.10. A Study on Manufacturing of an Axial-Flow Impeller with Multi-Material Blades of Inconel 718 and SST 316L by Wire Arc Additive Manufacturing

• Shinichiro Ejiri
• Fluid Technology Center, Nikkiso Co., Ltd., Tokyo 189-8520, Japan
• Nickel-based alloys have fabrication issues such as requiring more fabrication time than general-purpose metal materials due to their hardness. However, because it is a high-strength material, it is an appropriate material when designing thinner components. This conflicting relationship between manufacturing and design makes it difficult to apply nickel-based alloys as a general-purpose material for industrial components. One way to solve this issue is to creat multi-materials by wire arc additive manufacturing (WAAM). Since the strength required for a component is not necessarily uniform throughout the component, an appropriate balance between manufacturing and design can be achieved if nickel-base alloys can be applied only to areas subjected to high stress. Several studies have conducted fundamental evaluations of the mechanical properties and other aspects of multi-materialization of nickel-base alloys and general-purpose stainless steels by WAAM. However, the study of manufacturing multi-materialized industrial components by the combination of these materials has not progressed. In this study, an experimental investigation was conducted to fabricate an axial-flow impeller with multi-material blades by WAAM and machining. The materials used were Inconel 718 and SST 316L. A 3D scan of the fabricated axial-flow impeller confirmed that it was finished according to the design dimensions. Furthermore, observation of the multi-materialized blades by X-ray CT revealed the presence of several small internal defects. Although the reduction in these internal defects is an issue for the future works, the possibility of applying multilateralization by WAAM to the manufacturing of industrial components was experimentally demonstrated.

2.11. AI-Driven Computer Vision in Collaborative Robotics: Software Frameworks, Current Gaps, and Future Directions

• Himani Varolia ^1,2, César M. A. Vasques^1,2 and Adélio M. S. Cavadas ¹

¹ 

proMetheus, Higher School of Technology and Management, Polytechnic Institute of Viana do Castelo (IPVC), Viana do Castelo, Portugal.

² 

Centre for Mechanical Technology and Automation (TEMA), Department of Mechanical Engineering, Universidade de Aveiro, Aveiro, Portugal

• The “Industry 4.0”, a technology revolution emphasized automation, connectivity, and data-driven decision-making. As the world transitions to Industry 5.0, the focus shifts to more human-centred, robust, sustainable, and intelligent industrial systems. Here, collaborative robots (cobots) emerge as key enablers, work in shared space, enhancing human capability without compromising safety and flexibility.
• Computer vision plays a key role in enabling such integration by offering perception intelligence to cobots for tasks such as object detection, gesture identification, defect detection, and adaptive navigation. These capabilities are powered by artificial intelligence strategies: classical approaches—including feature extraction, template matching, and traditional machine learning continue to offer robust solutions for structured tasks, while new methodologies—deep learning, reinforcement learning, and transformer-based architectures facilitate adaptability in unstructured and dynamic industrial environments.
• Software platforms are also critical for implementation and deployment. MATLAB remains an excellent choice for quick prototyping and algorithm validation, whereas Python-based frameworks (e.g., TensorFlow, PyTorch, OpenCV) provide scalability, open source flexibility and integration with edge and cloud platforms. Their comparison is critical to grasp the performance, accessibility and deployment readiness trade-offs.
• Applications of AI-driven, vision-enabled cobots are assembly, quality inspection, adaptive manufacturing and safe human-robot collaboration. This paper surveys conventional and emerging computer vision approaches, identifies the gaps and presents the future research directions—edge AI deployment, multimodal sensor fusion and explainable vision systems—toward reliable and efficient adoption in Industry 5.0.

2.12. Analysis of the Shear Force in an Internal Beam–Column Connection and the Factors Significantly Affecting Its Magnitude

• Albena Doicheva
• Department of Technical Mechanics, University of Architecture, Civil Engineering and Geodesy (UACEG), Sofia 1046, Bulgaria
• The beam–column connection is the main element in frame structures. It is particularly vulnerable to cyclic lateral loads such as earthquakes. The main reason for this is the occurrence of shear forces. The main components of this force are the forces that are transmitted from the beam to the column. A good knowledge of these forces will allow for the safe and accurate dimensioning of frame joints. In current codes of differently countries, as well as in Eurocode, beam forces are determined capacitively, based on the longitudinal reinforcing bars passing through the beam–column connection. However, this method does not take into account the involvement of the concrete section. Furthermore, this method does not allow the forces transmitted from the beam to the column to be determined on the basis of the applied load. Experimental studies conducted over the past few decades have shown the significant contribution of these two factors, concrete strength and applied load, to the shear force. Analytical solutions of beams of frame construction subjected to different types of loads provide an explanation to the issue of the significant influence of load and strength of concrete [1,2]. In this paper, numerical results obtained from the analytical studies will be shown and conclusions will be drawn supporting experimental observations from the literature.
• References

• Doicheva, A. Distribution of Forces in RC Interior Beam–Column Connections. Eng. Proc. 2023, 56, 114.
• Doicheva, A. Shear Force of Interior Beam–Column Joints under Symmetrical Loading with Two Transverse Forces on the Beam. Buildings 2024, 14, 3028.

2.13. Analytical Models for the Prediction of Temperatures in Injection Molds: 2D Transient Heat Transfer Analysis

• Hugo Silva
• Independent Researcher, 4815-394 Vizela, Portugal
• Injection molding is a key manufacturing process widely used in industries such as automotive, medical devices, consumer goods, and electronics due to its ability to produce complex, high-precision plastic parts at large volumes and low cost. This study aims to investigate the influence of model dimensions on thermal behavior in injection-molded parts, using a geometric scaling approach. The objective is to understand how changes in part size affect the transient temperature of the injected part during the cooling phase.
• Numerical simulations were performed in 2D using the finite element method (FEM) software ANSYS Workbench 2025 R1. Several models with different geometric scales were analyzed under equivalent boundary and initial conditions. The results show that larger models tend to retain heat for longer periods, while smaller models cool more rapidly, leading to differences in temperature gradients and potential internal stresses. Well-defined linear relationships could be established between the model dimensions and the temperature evolution in the part, indicating a predictable and scalable thermal response.
• These findings suggest that scaling laws can be effectively used to estimate thermal performance in molds of varying sizes without the need for exhaustive simulation. Future work will focus on developing analytical models for the prediction of the influence of the dimensions of the model on the temperature of the injected part.

2.14. Application of World-Class Maintenance Metrics in the Management of 3D Printing Equipment for R&D Laboratories

• Jorge Alejandro Gondres Sánchez ¹, Edry Antonio Garcia Cisneros ² and Israel Gondres Torné ³

¹ 

Course of Industrial Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

² 

Course of Mechanical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

³ 

PPGEEL-Postgraduate Program in Electrical Engineering, School of Technology, State University of Amazonas (UEA), Manaus 69050-020, Brazil

• Effective maintenance practices are critical for ensuring the availability and reliability of equipment used in Research, Development, and Innovation (R&D) laboratories. Frequent failures and lack of standardized maintenance procedures often compromise operational continuity and project schedules. The use of world-class maintenance metrics provides a structured approach to measure equipment performance and identify areas for improvement. Academic laboratories, however, face challenges in systematically applying these indicators. This study proposes and applies a methodology for determining world-class maintenance metrics in 3D printers used at the Manufacturing Laboratory of the School of Technology, Amazonas State University. The mixed-method research combined literature review, field data collection, and the calculation of indicators such as MTBF, MTTR, availability, reliability, and OEE using MCM software. Data collection included equipment mapping, operational records, and interviews with technicians and operators. Results showed that the analyzed 3D printers presented an availability of 86.96% and OEE of 72%, both below world-class benchmarks of 90% and 85%, respectively. Failures were primarily associated with calibration inconsistencies, extruder blockages, and first-layer adhesion issues. These findings highlight the need for implementing preventive and predictive maintenance routines, standardizing critical procedures, and training operators to reduce downtime. The methodology demonstrates how structured maintenance metrics can support strategic asset management and strengthen operational continuity in R&D environments.

2.15. Comparative Analysis of Reality Capture Applications for the Construction Industry

• Mohammed Mawlana and Aakash Bhanushali
• Department of Construction Management, Thomas Jefferson University, Philadelphia, USA
• Three-dimensional-visualization technologies such as 360-degree virtual tours and 3D spatial modeling have significantly increased in the domains of architecture, engineering, construction (AEC), and real estate. These 3D models can be used for creating Building Information Models (BIMs), digital twins, or educational environments, among other things. As the demand for this data is increasing, plenty of reality-capture computer software and mobile applications have been developed. Most of the previous research focused on experiential outcomes rather than technical benchmarks. This study presents a comparative study of reality-capture applications and their capability for generating 3D virtual models. Several applications are being evaluated using a 360 camera and a phone camera as the main collection devices. This study primarily evaluates the technical features, usability, cost factors, and limitations. Some of the technical features that are examined include panoramic capture, 3D walkthrough generation, 2D floor plan extraction, LiDAR integration, BIM compatibility, and virtual staging. The usability of the applications focuses on the applications’ user interface, ease of use, and intuitiveness. The results show varying capabilities of the compared applications. In addition, various suggestions are provided to fill the gap. The next step of this study includes a comparative analysis of the applications’ accuracy and the precision of the generated models.

2.16. Design of Floating Platforms Using Monolithic Closed Rectangular Tanks

• Anna Szymczak-Graczyk
• Department of Construction and Geoengineering, Faculty of Environmental and Mechanical Engineering, Poznan University of Life Sciences, Piątkowska 94, 60-649 Poznań, Poland
• The article investigates the structural behavior of closed monolithic rectangular tanks, constructed in a single technological process without interruptions or expansion joints, intended for application as floating platforms in inland waters. The research focuses on the assessment of their static performance under multiple load conditions, including hydrostatic pressure acting on the walls and bottom surfaces, as well as uniformly distributed loads applied to the upper plate. The structural analysis was conducted using the finite difference method formulated within an energy-based framework, assuming a Poisson’s ratio ν = 0. On this basis, computational results were obtained and presented in the form of diagrams that illustrate the variation of bending moments at characteristic locations of the tanks. The calculations were performed manually using custom-made spreadsheets. These diagrams provide insight into the load-bearing behavior of the system and allow identification of critical stress zones. Beyond the structural analysis, the study also includes verification of the buoyancy, overall stability, and metacentric height of a selected tank prototype fabricated for experimental evaluation. In this particular case, the influence of temperature variations and ice floe loads was additionally considered in order to simulate realistic operational conditions in inland water environments. The article concludes with photographic documentation of the pontoon prototype, demonstrating the practical implementation of the design. The results confirm that monolithic rectangular tanks exhibit favorable structural and hydrostatic characteristics, thereby validating their suitability as efficient and reliable structural units for floating platform applications.

2.17. Development of an Active Low-Cost Thread Tensioning System for a Crochet Machine

• Maximilian Kellner, Eric Posner, Jan Lukas Storck and Andrea Ehrmann
• Faculty of Engineering and Mathematics, Bielefeld University of Applied Sciences and Arts, 33619 Bielefeld, Germany
• As part of an earlier project, a crochet machine, “CroMat”, was designed and built, and a patent was filed for it. An essential part of this crochet machine is an active thread tensioning device, which is needed to regulate the thread tension on the machine’s crochet needle. Until now, a special supplier with an integrated thread return system has been used for this purpose.
• However, such commercially available supplies are very expensive and are also designed for knitting machines, whereas the newly developed crochet machine has slightly different requirements. In addition to retracting yarn, a thread tension system for the crochet machine must be able to dynamically adjust and regulate thread tension during stitch formation, which requires communication with the machine’s microcontroller. This is complicated by the fact that each type of stitch that can be formed by the crochet machine requires different lengths of yarn.
• The current project focuses on developing a thread tensioner tailored specifically to the crochet machine. Key components include a wrap brake, a return spring as a thread storage device, a driven wrap wheel, and a stepper motor controlled by an Arduino via a driver board. The thread tension is measured to control the motor using a load cell with a strain gauge.
• The poster shows the newly designed and built thread tensioner and provides an outlook on further improvement possibilities.

2.18. Effect of Seam Position on the Aerodynamic Performance of Winter Sportswear Fabrics

• Sungchan Hong
• Department of Sport and Exercise Science, Seoul Women’s University, Seoul, Republic of Korea
• This study aims to investigate the aerodynamic properties of fabrics used in winter sportswear, with a specific focus on the effect of seam placement on air resistance. To achieve this, wind tunnel experiments were conducted using two different models: a cylindrical model and an airfoil-shaped model. The experiments were designed to simulate real-world conditions encountered in high-speed winter sports and to analyze how changes in seam position affect aerodynamic performance.
• For the cylindrical model, the seam was tested at various angular positions. The results showed that placing the seam at a 30-degree angle from the front-facing direction yielded the lowest drag coefficient (Cd = 0.63) at a wind speed of 100 km/h. This represents a 25% reduction in air resistance compared to a seam positioned at the very front (0 degrees, Cd = 0.84). This suggests that seam placement away from the stagnation point can significantly reduce drag in cylindrical shapes.
• In contrast, the airfoil-shaped model exhibited the lowest drag when the seam was located directly at 0 degrees, indicating that aligning the seam with the airflow direction is most effective for this geometry.
• These findings demonstrate that seam location plays a crucial role in the aerodynamic efficiency of winter sports apparel. Depending on the shape of the body or equipment, optimal seam positioning can vary. Understanding these dynamics allows for better design strategies aimed at minimizing drag and improving athlete performance in high-speed winter sports environments.

2.19. Formulation Calculation and Mechanical Performance of Lightweight Geopolymer Lunar Concrete

• Kevin Kllobocishta ¹, Daniel Hochstein ² and Tony Kllobocishta ²

¹ 

Department of Civil Engineering and Engineering Mechanics, Columbia University, New York, NY 10027, USA

² 

Department of Civil and Environmental Engineering, Manhattan University, Riverdale, NY 10471, USA

• For the future of Lunar colonization to become a reality, the ability to create structures incorporating the materials found locally must be explored. The most abundant material that can be used on the Moon is the lunar soil itself, present across the entire surface. This abundance has led to the belief amongst student and Space agency researchers of the possibility in using a Geopolymer mixture, to create concrete from the in-situ soil. This concrete would also have to be lightweight enough to justify the transfer of Geopolymer mixture to the Lunar construction site. Using a Lunar simulant as our soil, sodium hydroxide, Potassium hydroxide, Sodium Silicate, and hydrogen peroxide, our team has been able to formulate a mixture that incorporates the high silica and alum content of the lunar regolith. We have created samples that have consistently yielded lightweight lunar concrete with a density of 880 kg/m^3, less dense than water, and with considerable strength. The other part that was addressed was the mix consistency, since due to the high silica content, the mixture would dry too quickly for the concrete to be molded into its desired shape. All of this has been properly addressed and solved through the mixture formulation. Currently, we are running strength tests to quantify its compressive and tensile strength, calculate its material properties, and calculate its feasibility to be used as a structure in a low gravity lunar environment.

2.20. Influence of the Room and Cooling Channel Temperatures in Injection Molding

• Hugo Silva
• Independent Researcher, 4815-394 Vizela, Portugal
• Injection molding is a widely adopted manufacturing process for producing plastic parts with high precision and consistency. It is extensively used in industries such as automotive, medical devices, electronics, and consumer goods due to its ability to produce complex geometries at high volumes and low cost per part. This study investigates the influence of cooling channel and ambient room temperatures on the thermal behavior of the mold and the injected part. A numerical analysis was performed using the Finite Element method (FEM) software ANSYS Workbench 2025 R1, focusing on heat transfer and cooling performance within the mold system. The simulation model incorporated realistic boundary conditions, including varying ambient temperatures and cooling channel water temperatures, to evaluate their effects on the temperature of the injected part.
• Linear relationships were identified between the input temperatures and the resulting temperature field in the injected part, indicating a predictable thermal response under controlled conditions. These findings suggest that both cooling channel and room temperatures can be strategically managed to optimize part quality and process efficiency. Future work may focus on developing analytical models to accurately predict the temperature evolution within the molded part, enabling faster process tuning and facilitating the evaluation of temperature influence with minimal computational resources.

2.21. Low-Cost Pneumatic Soft Robotic Gripper with Intelligent Sensing for Gentle Fruit Harvesting

• Saleimah Ahmed Alyammahi ¹, Fesmi Majeed ², Wasseel Al Abbas ², Amerah Almesmari ², Shammah Alkaabi ², Meerah Alkhaaldi ², Eisa Alloghani ² and Mohamed Alblooshi ²

¹ 

Department of Mechanical Engineering Technology, Engineering Technology & Science division, Faculty of Engineering, Fujairah Campus, Higher Colleges of Technology, Abu Dhabi, P.O. Box 25026, United Arab Emirates

² 

Higher Colleges of Technology, Fujairah, United Arab Emirates

• The need for gentle, efficient, and sustainable harvesting solutions in modern agriculture is becoming increasingly important as global demand for fresh produce continues to rise. Conventional rigid robotic grippers often cause mechanical damage to delicate fruits and vegetables, leading to significant post-harvest losses and food waste. To address these challenges, soft robotic technologies are emerging as effective alternatives due to their compliance, adaptability, and ability to interact safely with biological materials. This project presents a low-cost pneumatic soft robotic system designed for fruit harvesting, integrating pressure and color sensing to detect ripeness and prevent bruising. The gripper is fabricated from silicone Ecoflex using a custom 3D-printed mold and actuated through an air pump–valve assembly. A pressure sensor detects contact pressure to ensure safe gripping, while a TCS34725 color sensor evaluates ripeness based on fruit surface color. The control is implemented with an Arduino Uno, which coordinates actuation by integrating sensor data for decision-making in real time. Experimental trials are carried out on different fruits with varying hardness and ripeness levels. The results demonstrate reliable ripeness detection with over 80% accuracy and successful picking with minimal visible surface damage, confirming the effectiveness of integrating pneumatic actuation with low-cost sensing. Overall, the developed system provides a practical, sustainable, and accessible approach to precision agriculture, contributing to reduced food waste, improved crop handling, and advancement toward intelligent, automated harvesting technologies.

2.22. Modular and Container-Based Construction: Global Trends, Polish Experiences, and Future Prospects

• Julia Anna Graczyk
• Faculty of Civil and Transport Engineering, Poznan University of Technology, 60-965 Poznan, Poland
• Modular construction has emerged as one of the most dynamic innovations in the building industry, offering a response to growing demands for speed, cost efficiency, and sustainability. This paper examines the global development of modular systems, with a particular focus on container-based solutions, and evaluates their impact on contemporary architecture and construction practices. Drawing on examples from the United States, Japan, Germany, and the United Kingdom, the study demonstrates how prefabricated modules have enabled the rapid delivery of residential, commercial, and public facilities, while simultaneously supporting energy efficiency and ecological goals.
• The Polish perspective is highlighted through recent projects such as the Veterinary Medicine and Animal Sciences Faculty in Poznań and a modular hotel on the Hel Peninsula, both of which showcase the adaptability and cost-effectiveness of modular solutions. Different systems—container, panel, hybrid, and three-dimensional modules—are compared in terms of their advantages and limitations. Particular attention is paid to container-based construction, which combines high mobility and quick assembly with challenges such as insufficient thermal insulation and an unclear legal status in building regulations.
• The analysis underscores that modular construction is not only a practical alternative to traditional methods but also a forward-looking strategy for sustainable urban development. Its continued progress will depend on technological innovation, mass production, and regulatory adaptation, paving the way for greater integration with renewable energy and smart building technologies.

2.23. Neural Network-Based Mesh Optimization for Arbitrary Node Valence

• Olivier R. Gouveia ^1,2, José M. Guedes ¹ and Rui B. Ruben ²

¹ 

IDMEC, Instituto Superior Técnico, University of Lisbon, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal

² 

CDRSP, Polytechnic University of Leiria, Rua de Portugal, 2430-028 Marinha Grande, Portugal

• The quality of computational meshes plays an important role in the accuracy and efficiency of simulations, particularly in finite element analysis frameworks. Traditional smoothing techniques for unstructured meshes, such as Laplacian and optimization-based methods, typically employ Gauss–Seidel-style iterative schemes, where interior nodes are updated sequentially over multiple passes. While effective at capturing local, high-frequency changes, these methods often suffer from high computational costs and slow convergence. Recent advances in machine learning, particularly neural networks, offer a promising alternative. Existing neural-network-based mesh smoothing approaches commonly rely on separate models for each valence configuration, which limits their generalizability across diverse mesh topologies.
• This work proposes a valence-aware, feedforward neural network architecture that learns to surrogate traditional quality metric optimization processes. By explicitly encoding the local valence degree of mesh umbrellas, the network can operate across varying topological configurations within a single model. The method specifically targets improvement of the weighted inverse-Jacobian quality metric for triangular elements. A fully connected network is trained on synthetic unstructured meshes paired with optimal node placements, which are derived from conventional optimization routines. Numerical experiments demonstrate that the proposed approach provides a faster alternative to traditional smoothing and optimization methods while achieving high-quality meshes. The improvement in the quality/time ratio underscores the potential of neural networks to address complex, non-linear relationships in mesh optimization tasks.

2.24. Numerical Analysis of Geometric Scaling Effects on the Stiffness Behavior of a Robotic Gripper

• Hugo Silva
• Independent Researcher, 4815-394 Vizela, Portugal
• This study presents a comprehensive numerical investigation into the stiffness behavior of a robotic gripper subjected to geometric scaling in three principal dimensions—length, width, and height—using the Finite Element Method (FEM) within ANSYS Workbench 2025 R1. Robotic grippers play a vital role in industrial automation and precision manipulation tasks, where structural stiffness is a critical parameter influencing performance, load capacity, and accuracy. The objective of this research is to explore how changes in geometric dimensions affect the overall stiffness of the gripper, thereby guiding more informed design decisions.
• A three-dimensional baseline model of a parallel-jaw robotic gripper was developed and systematically scaled along the three primary axes to evaluate the independent and combined effects of dimensional variation. Numerical simulations were conducted under realistic boundary conditions and loading scenarios to simulate operational use cases. The analysis focused on capturing the trends in stiffness response as a function of scaling, while considering structural integrity and mechanical efficiency.
• The study offers valuable insights into how scaling strategies can influence mechanical behavior, providing a foundation for optimizing gripper geometry in future designs. Ongoing and future work aims to extend the methodology to dynamic loading conditions and explore material alternatives for enhanced performance and reduced weight.

2.25. Optimisation of 3D Printing Parameters for Enhanced Compressive Strength and Surface Quality of PLA Components

• Nejmeddine Layeb, Istvan Oldal and László Zsidai
• Institute of Technology, Hungarian University of Agriculture and Life Sciences (MATE), Gödöllő, Hungary
• Fused Deposition Modelling (FDM) is one of the most widely adopted additive manufacturing techniques due to its affordability, flexibility, and capability to produce complex geometries using biodegradable polymers such as polylactic acid (PLA). With the rising demand for reliable, high-performance 3D-printed components in engineering and biomedical sectors, optimising key process parameters to achieve enhanced mechanical strength and surface quality has become increasingly critical. This study examines the effects of selected printing parameters on the compressive strength and surface roughness of FDM-fabricated PLA specimens. A systematic experimental approach was implemented using an L9 Taguchi orthogonal array, enabling efficient planning and analysis of the influence of each parameter. Results indicated that raster orientation had the most significant impact on compressive strength, achieving a maximum of 67 MPa with a ±45° orientation, 210 °C nozzle temperature, 0.1 mm layer thickness, and 60 mm/s printing speed. In terms of surface quality, layer thickness emerged as the dominant factor, with the smoothest finish (Ra = 4.84 µm) achieved at 0.1 mm, 200 °C, 30 mm/s, and ±45° orientation. These findings provide practical insights into parameter optimisation strategies, supporting the production of PLA components with improved structural performance and refined surface characteristics. Such optimisation is vital to expand the applications of FDM-printed PLA in advanced functional, engineering, and biomedical contexts.

2.26. Parametric Diagrams of Steel and Concrete Behavior in Finite Element Modeling

• Oleksandr Horb and Anton Makhinko
• Department of Construction Computer Technologies, Faculty of Architecture, Construction and Design, State University “Kyiv Aviation Institute”, 03058 Kyiv, Ukraine
• The most accurate setting of material behavior diagrams in finite element modeling (FEM) determines the accuracy of reproducing the real mechanism of structural failure under load. Therefore, the aim of this study was to find the optimal type of diagrams that would consider the nonlinear component and the peculiarities of National Standards.
• This study used statistical analysis of the steel design parameters and the deformation-iteration method to determine the curve of dependence between stresses and strains in concrete.
• When performing FEM of composite steel and concrete (CSC) structures in the ANSYS software package, it was found necessary to consider the plastic deformation in order to more accurately reflect the actual behavior of composite sections, based on the physical and mechanical properties of the materials, which would correlate with the current codes. As a result, parametric values of key points of the plastic section of the concrete performance diagram were obtained, which made it possible to simulate the post-critical stage of CSC columns under static and dynamic loads.
• The resulting diagrams provide an appropriate representation of the materials’ nonlinear properties with an accuracy of 5–7%, allowing for a correct assessment of limit states and optimal design decisions in terms of safety and cost-effectiveness.
• Further research will help gather enough statistical data to train the neural network, which will make it way easier to check and evaluate the results of experiments on CSC structures.

2.27. Parametric Study of Stress Concentration Factors on Reinforced Tubular X-Joints Under Out-of-Plane Bending

• Muhammad Al Aiman Mohd Firdhaus, Saravanan Karuppanan and Mohsin Iqbal
• Department of Mechanical Engineering, Universiti Teknologi PETRONAS, 32610 Seri Iskandar, Malaysia
• Offshore jacket-type platforms utilize tubular X-joints, among other configurations, for their high strength-to-weight ratio and bending resistance. However, weld geometry at the brace–chord intersection induces localized stress intensities, quantified as Stress Concentration Factors (SCFs), which strongly affect fatigue performance. Accurate SCF prediction under out-of-plane bending (OPB) is especially critical in joints retrofitted with fibre-reinforced polymer (FRP) composites. While existing models address several geometric and material parameters, the influence of brace inclination (θ) has often been overlooked.
• This study develops an artificial neural network (ANN) model that incorporates θ alongside five additional parameters, which are the brace-to-chord diameter ratio (β), chord diameter-to-thickness ratio (γ), brace-to-chord thickness ratio (τ), number of FRP layers (N), and FRP-to-steel stiffness ratio (ξ), to predict SCFs in FRP-reinforced tubular X-joints. Finite element analysis (FEA) of 127 parametric joint configurations was performed in ANSYS Workbench 2024 R1, with SCFs extracted following International Institute of Welding (IIW) guidelines. Results revealed that increases in β, γ, and τ raised SCFs by up to 84.14%, 61.15%, and 58.44%, respectively, whereas steeper brace angles, additional FRP layers, and higher ξ reduced SCFs by up to 38.29%.
• The ANN, designed with a 6–8–4–1 architecture and trained in MATLAB, achieved an R² of 0.996. External validation confirmed predictive accuracy within ±10% of FEA values. This study delivers a reliable, angle-inclusive SCF prediction model, supporting more efficient fatigue assessment and retrofitting strategies for offshore tubular joints.

2.28. Simulation of a Swarm of Nanosatellites PARASOL (Based on MIMO Communication) Control System Model via Linear Quadratic Regulator (LQR)

• Medfranck Obiang Mba Dit
• Department of Radio Engineering System, Faculty Radio Engineering and Telecommunications, Saint Petersburg State Electrotechnical University, Saint Petersburg 197227, Russia
• The deployment of swarms consisting of unmanned aerial vehicles and spacecraft has recently attracted significant attention across multiple fields, ranging from spacecraft coordination to emergency response operations. The techniques associated with swarming introduce novel challenges, especially in formulating strategies for effective swarm organization and preserving their intended formations. Developing an advanced simulation to control a swarm of 15 nanosatellites using a Linear Quadratic Regulator (LQR) involves several important steps that go beyond the initial scheme. A comprehensive approach requires a deep understanding of orbital mechanics and in particular the challenges presented by the nanosatellite platform. Our work focuses on simulating the attitude control of PARASOL nanosatellite in a swarm using the Matlab/Simulink environment. Firstly, was provided a mathematical model for the relative coordinates of a nanosatellite swarm. Secondly, a mathematical model of the LQR implementation in the relative navigation was developed. Thirdly, the attitude control of the 15 nanosatellites using the Matlab/Simulink environment was simulated. Finally, by providing the swarm scenario and attitude control system data it can be affirmed that simulation of an attitude control system for 15 nanosatellites using an LQR controller in Swarm successfully demonstrated the stabilization capabilities essential for swarm operations in space environments. As results a table each nanosatellite configured for MIMO communication was shown and the link video of the simulation was given.

2.29. Simulation-Based Assessment of Banking Angle Effects on Electric Bike Lateral Stability Under Steady-State Conditions

• Naomi Isabel M Butac ¹, Carlos Emmanuel P Garcia ¹, Frederic James V Espiritu ¹, Paolo Rommel P Sanchez ² and Ralph Kristoffer B Gallegos ^1,2

¹ 

Department of Mechanical Engineering, University of the Philippines Los Baños, College, Laguna 4031, Philippines

² 

Institute of Agricultural and Biosystems Engineering, University of the Philippines Los Baños, College, Laguna 4031, Philippines

• In recent years, the number of consumers of three-wheeled vehicles has increased because of their practicality. However, along with the rise in demand comes a growing safety concern, particularly regarding vehicle lateral stability during maneuvers. This highlights the need to understand the factors that influence stability.
• This research aims to develop a validated model that evaluates the effects of the banking angle on three-wheeled e-bike lateral stability. Using simulation, the model is designed to determine critical banking angles that lead to skidding during cornering. The static model was validated by comparing the weight of the actual and simulated e-bike model. Then, the dynamic model was validated by comparing the acceleration when undergoing steady-state cornering.
• The results validate the static and dynamic models as the solved percentage difference between the actual and simulated setup was limited to 19.628%. They also show that the skid index increases as the bank angle increases and the e-bike starts to skid beyond a banking angle of 6 degrees. It was found that the e-bike understeers at low bank angles due to the increased centrifugal force. By contrast, the e-bike oversteers at high bank angles due to the influence of gravitational force.
• Drivers and passengers should be aware that driving at high speeds during cornering, especially on roads with high bank angles, could lead to accidents. To avoid accidents, drivers should consider driving at speeds less than 12 km/h and on inclines less than 6°.

2.30. Structural Analysis of Composite Vertical Axis Tidal Turbine Blade Using Finite Element Analysis

• Clement Voon Wang Tze, Saravanan Karuppanan and Mohsin Iqbal
• Department of Mechanical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Malaysia
• This study focuses on the structural optimization of a composite Vertical Axis Tidal Turbine (VATT) blade designed for low-velocity, shallow-water environments such as those found in Malaysia. Using Finite Element Analysis (FEA), a three-dimensional blade model was developed based on a NACA 0021 profile, incorporating carbon fiber reinforced polymer (CFRP) with a hybrid layup of unidirectional and woven plies. The structural response was analyzed under realistic hydrodynamic pressure derived from tidal current conditions at 5 m/s. A comprehensive parametric study was conducted to evaluate the influence of skin thickness, spar thickness, spar geometry, and number of internal ribs on blade deformation, stress distribution, and mass. Key design positions—including the center rib and ribs near the fixed supports—were held constant, while additional ribs were varied. A Weighted Decision Matrix (WDM) was employed to objectively identify the optimal configuration based on multiple performance criteria. The final optimized design consisted of a 7.5 mm skin, 6.0 mm box-shaped spar, and 10 internal ribs. This configuration yielded a maximum deflection of 0.69 mm, axial stress of 18.13 MPa, transverse stress of 8.86 MPa, and total mass of 29.83 kg—meeting structural performance targets while minimizing weight. The results validate the effectiveness of parametric optimization in improving blade efficiency and support the viability of lightweight composite blades for reliable tidal energy extraction.

2.31. The Effects of the Working Speed of a Bending Subsoiling Tool on Soil Disturbance Behaviors and Tillage Forces

• Xuezhen Wang
• College of Agricultural Equipment Engineering, Henan University of Science and Technology, Luoyang 471000, China
• Mechanical subsoiling serves as a highly effective practice for eliminating soil compaction caused by years of consecutive mechanical operations. It also significantly enhances water infiltration and promotes the robust development of crop roots. The bending subsoiling tool (BST), a fundamental implement in subsoiling activities, is employed to optimize soil structure and boost the ability of crops to absorb nutrients and water from the soil. In this study, the discrete element method was utilized to investigate the impacts of the BST’s working speed, ranging from 1.5 to 9.5 km/h, on soil disturbance behaviors and tillage forces. The findings revealed that a proper increment in the BST’s working speed could elevate a greater amount of moist soils from the deep seed and middle layers into the shallow seed zone, without severely affecting the mixing between the deep layer and other layers. The working speed of the BST had a restricted influence on the lateral soil disturbance range. As the BST’s working speed increased from 1.5 to 9.5 km/h, it led to a larger draught force, greater soil surface flatness, a higher soil rupture distance ratio, and a lower soil loosening efficiency. Notably, when the BST’s working speed increased from 7.5 to 9.5 km/h, the soil surface flatness increased rapidly. Taking soil layer mixing, soil loosening efficiency, and soil surface flatness into consideration, it is advisable that the BST operate at working speeds lower than 9.5 km/h.

2.32. Thermal Stability Analysis of MEMS Vibrating Ring Gyroscopes for Space Applications

• Nabeel Ahsan ¹, Muhammad Sajid Ali Asghar ² and Waqas Amin Gill ³

¹ 

Pakistan International Airlines, Karachi, Pakistan

² 

Department of Materials Engineering, NED University of Engineering & Technology, Karachi 75270, Pakistan

³ 

School of Civil and Mechanical Engineering, Curtin University, Perth, WA 6102, Australia

• This research presents a study into the thermal stability of a MEMS vibrating ring gyroscope, specifically designed for space and harsh environmental applications. An innovative internal vibrating ring gyroscope design configuration was modelled and analysed using finite element analysis (FEA) in ANSYS R1 2023 software. The proposed design exhibited structural stability by incorporating sixteen support springs connected to the internal vibrating ring, and the whole structure is supported through externally placed anchors. The primary objective is to study the robustness of these gyroscopes under severe thermal fluctuations, ranging from −100 °C to 100 °C. The FEA results indicate that increasing the number of semicircular support springs significantly enhances the structural integrity and thermal performance of the gyroscopes. The proposed design presents the symmetric structure of the vibrating ring gyroscope that oscillates with identical wine glass mode shapes for driving and sensing resonance frequencies. Additionally, reduced thermal deformation, thermal stresses, and thermal strains compared to the traditional vibrating ring gyroscopes. These findings corroborate the effectiveness of the proposed internal design approach, confirming the suitability of MEMS vibrating ring gyroscopes for various applications, including aerospace, defense, and automotive industries. Overall, this research work provides valuable insight into optimizing MEMS vibrating ring gyroscope designs for high-performance and thermally stable inertial sensing applications.

2.33. Varying Speed Test and Emission Performance of a Spark-Ignition Engine Fueled with Butanol–Ethanol–Propanol–Gasoline Blends

• Dane Robert C Inocando ¹, Omar F Zubia ², Carlos Emmanuel P Garcia ¹, Precious Arlene V Melendrez ¹ and Ralph Kristoffer B Gallegos ^1,2

¹ 

Department of Mechanical Engineering, University of the Philippines Los Baños, College, Laguna 4031, Philippines

² 

Institute of Agricultural and Biosystems Engineering, University of the Philippines Los Baños, College, Laguna 4031, Philippines

• The increasing demand for sustainable and cleaner fuels has encouraged the exploration of alcohol–gasoline blends as alternatives for spark-ignition (SI) engines. This study investigates the performance and emission characteristics of a single-cylinder, four-stroke SI engine fueled with ternary blends of n-butanol, ethanol, and n-propanol mixed with gasoline. A single-cylinder, four-stroke SI engine was tested using the Varying Speed Test procedure based on PNS 396–397:2024. The tests were carried out by gradually decreasing the engine’s shaft rotation speed in 100-RPM intervals (from 2900 rpm to 3800 rpm) from its rated speed, while keeping the carburetor setting constant across all fuel blends. Five fuels were used in total, G100 (100% gasoline), BE15P0 (7.5% n-butanol, 7.5% ethanol), BE10P5 (5% n-butanol, 5% ethanol, 5% n-propanol), BE5P10 (2.5% n-butanol, 2.5% ethanol, 10% n-propanol), and BE0P15 (15% n-propanol), with each blend containing 15% alcohol by volume. This study measured engine brake power (BP), brake thermal efficiency (BTE), and brake-specific fuel consumption (BSFC), as well as emissions of CO and NO_x. Results showed that among all the blends, BE0P15 stood out by recording the highest average BTE and BP, the lowest BSFC, and the lowest emissions of both CO and NO_x. These results suggest that fuel blends with higher amounts of n-propanol can improve combustion efficiency while also reducing harmful emissions. Based on the findings, n-propanol-rich blends have potential as cleaner and more efficient alternatives to pure gasoline in spark-ignition engines, especially under varying speed conditions.

3. Energy, Environmental and Earth Science

3.1. “NHSOS” Project in Chalki Island: Integrated Actions for Waste Management Optimization, Air Quality Monitoring and Carbon Footprint Mitigation

• Ioannis Logothetis ^1,2, Athanasios Kerchoulas ¹, Dimitrios-Sotirios Kourkoumpas ¹, Adamantios Mitsotakis ¹, Panagiotis Grammelis ¹, Stavros Kyzalas ³, Maria Papandreou ³, Athanasios Tamvakos ³ and Evangelos Bekiaris ³

¹ 

Centre for Research and Technology Hellas, Chemical Process and Energy Resources Institute, Thermi, GR 57001 Thessaloniki, Greece

² 

Laboratory of Atmospheric Physics, Department of Physics, Faculty of Sciences, Aristotle University of Thessaloniki, GR 54124 Thessaloniki, Greece

³ 

Centre for Research and Technology Hellas, Hellenic Institute of Transport, Thermi, GR 57001 Thessaloniki, Greece

• “NHSOS” is a multidisciplinary sustainability project that has been implemented in the islandic area of the Southeastern Aegean basin. Chalki (Halki) is a small island of about 500 citizens located in the climate-sensitive area of the Eastern Mediterranean. Focusing on Chalki Island, the project aims to reduce environmental degradation throughout three key pillars of “GReco” Island and Smart Specialization Strategy (S3) initiatives, namely waste management optimization, air quality monitoring, and carbon footprint mitigation. The project engages with authorities, the community, and tourism stakeholders in order to promote the circular economy and low emissions strategies. This study evaluates current and projected waste generation trends and outlines sustainable waste management strategies tailored to the island’s unique geographic and socioeconomic context. Air quality and meteorological recordings from sensors are used in order to investigate the concentration of air pollutants as well as the impact of meteorology and traffic activity on the variability of pollutant concentrations. All carbon emission sources are qualitatively characterized following Life Cycle Assessment (LCA) standards. Subsequently, sustainable interventions and energy autonomy solutions are outlined to reduce the island’s total carbon footprint. The “NHSOS” project provides solutions for islandic sustainability in Mediterranean regional-based ecosystems, addressing the challenges of climate change, air pollution, and unsustainable resource use.

3.2. Adiabatic Cooling Systems as a Tool for Improving Thermal Comfort in Outdoor Urban Spaces

• Ewelina Barnat
• Faculty of Civil and Environmental Engineering and Architecture, Rzeszow University of Technology, Powstancow Warszawy Street 12, 35-959 Rzeszow, Poland
• In the context of current climate change, extreme weather events such as heatwaves are becoming more frequent. These events have a particularly severe impact in urban environments due to the urban heat island effect. Providing thermal comfort for people using open public spaces requires localised cooling strategies, particularly in areas with high footfall, such as transport hubs, squares and promenades. Adiabatic cooling is a promising solution as it can lower air temperatures in an energy-efficient manner with relatively low environmental impact. This article provides an overview of current adiabatic outdoor cooling systems, assessing their energy, economic and environmental efficiency and considering various options for achieving comfortable temperatures. Particular attention is paid to integrating systems with renewable energy sources, such as solar power, and to determining the optimal ‘cooling point’ at which the system can operate autonomously, without the need for additional electrical power. The results demonstrate that, when properly sized and designed, adiabatic cooling systems can significantly enhance thermal comfort in urban outdoor spaces while minimising energy consumption. This represents a promising adaptive strategy in response to increasingly frequent urban heatwaves. The paper provides practical design guidelines and lays the groundwork for further research into the sustainable cooling of occupied outdoor spaces.

3.3. Can Public Satellite Data Management Provide an Opportunity to Develop the Function of Environmental Hazards Prediction in the Civil Protection System?

• Bruna Viscardi
• Independent Expert, Stezzano, Lombardy, Italy
• Introduction: The Civil Protection System designed by Zamberletti has helped Italy to manage environmental crises by means of the implementation of a systematic vision in which the main strategy was prevention and on-site interventions. This is a well-performing system, but it could be optimized if the use of satellite data were integrated at all different hierarchical levels.
• Currently, a major limitation in the use of public satellite data is data fragmentation in different repositories, as the volume of satellite data has increased significantly over the last twenty years, making it necessary to understand how data were collected and stored and how public and private users can exploit them.
• Methods: The evolution of satellite data collection has been studied as a support for the development of a methodological approach to public satellite platforms data management by means of a data lifecycle model (DLM) that considers privacy, security and quality criteria.
• Results: A framework has been defined for assessing the characteristics of an appropriate data management cycle, on the basis of which it is possible to identify how to address organizational, technical, and legal critical issues.
• Conclusion: Prevention and intervention on site are now established practices, while a prediction strategy is still not completely adopted as a function of the Augustus Method of the Civil Protection Institution. An environmental satellite data DLM may allow for a shift from a prevention to a prediction policy.

3.4. Assessing Dust Storm Frequency and Intensity in Egypt Under Climate Change Scenarios

• Zeinab Salah
• Egyptian Meteorological Authority, Cairo 11231, Egypt
• Dust in the air poses significant risks to human health. Non-respiratory particles larger than 10 micrometers can cause skin irritation and eye inflammation. Dust storms also have negative impacts on agriculture, reducing crop yields by burying seedlings, damaging plant tissue, reducing photosynthetic activity, and increasing soil erosion. Dust storms are a common phenomenon in Egypt, extending hundreds of kilometers, during spring and winter. They significantly impact transportation, sometimes leading to deaths and property damage due to the accompanying strong winds and reduced visibility. Therefore, there is a need to develop an indicator that represents the frequency and intensity of dust events based on different climate change scenarios (RCP4.5 and RCP8.5). Through this study, a dusty days index was calculated based on the maximum daily dust concentration simulated by the ICTP Regional Climate Model (RegCM4) over Egypt and the Middle East and North Africa (MENA) region. Dust intensity is classified by percentage as follows: normal (75th percentile), high (90th percentile), very high (95th percentile), and extreme (99th percentile). Climate Data Operator “CDO” was used to process the model output netCDF files and perform these calculations. The results of this study show a positive trend in air temperature over Egypt, accompanied by a negative trend in precipitation with the RCP4.5 scenario, which increased with the RCP8.5 scenario, potentially leading to increased dust emissions.

3.5. Environmental Occurrence and Human Health Relevance of Antimony (Sb) in Urban Soils of Alcalá De Henares

• Antonio Peña-Fernández ^1,2, Manuel Higueras ³ and María del Carmen Lobo-Bedmar ⁴

¹ 

Department of Surgery, Medical and Social Sciences, Faculty of Medicine and Health Sciences, University of Alcalá, Ctra. Madrid-Barcelona, Km. 33.600, 28871 Alcalá de Henares, Madrid, Spain

² 

Leicester School of Allied Health Sciences, De Montfort University, Leicester LE1 9BH, UK

³ 

Scientific Computation & Technological Innovation Center (SCoTIC), Universidad de La Rioja, Logroño, Spain

⁴ 

Departamento de Investigación Agroambiental. IMIDRA. Finca el Encín, Crta. Madrid-Barcelona Km, 38.2, 28800 Alcalá de Henares, Madrid, Spain

• Antimony (Sb) is a semi-metallic element increasingly used in vehicle brake pads, flame-retardant plastics, batteries, and polyethylene terephthalate (PET) bottles. Despite its recognised toxicity and classification as a priority pollutant in Europe, Sb remains insufficiently monitored in urban environments. This study assessed total Sb concentrations in 137 surface soil samples from Alcalá de Henares (Spain), collected from urban parks (n = 97), industrial zones (n = 22), and gardens (n = 18). Sb was detected in 91.8% of the samples, with significantly higher concentrations in urban soils (median: 0.352 mg/kg) than in industrial and garden areas (0.292 and 0.124 mg/kg respectively; p < 0.05). Although values remained below regional generic reference levels, pollution indices indicated localised anthropogenic inputs. Multivariate analysis grouped Sb with Rh and Mo, suggesting common emission sources—most likely traffic and industrial activities. Spatial analysis revealed elevated Sb concentrations in urban hotspots with dense road infrastructure. Inhalation risk was characterised using the US EPA methodology and was found to be below regulatory thresholds. Nevertheless, the high coefficient of variation and significant enrichment factors in some areas highlight the heterogeneity of Sb distribution and underscore its relevance as an urban soil contaminant. Given its bioaccumulative properties, persistence, and known toxicological effects—including developmental and respiratory toxicity—this study reinforces the need for Sb to be systematically included in soil monitoring and regulatory frameworks. Particular attention should be given to urban recreational spaces and garden soils, where incidental exposure through soil ingestion or dust inhalation may affect vulnerable populations such as children.

3.6. Assessing the Application of Artificial Intelligence to the Discovery of New Mineral Species

• Carlos Alves ¹, Carlos Figueiredo ², Jorge Sanjurjo-Sánchez ³ and Ana Hernández ³

¹ 

Lab2PT&School of Sciences (Earth Sciences Department), University of Minho, 4710-057 Braga, Portugal

² 

CERENA, Higher Technical Institute, University of Lisbon, 1649-004 Lisbon, Portugal

³ 

University Institute of Geology, University of A Coruña, 15071 A Coruña, Spain

• Artificial intelligence is having a revolutionary effect on diverse areas of research, such as proteins, drugs, and materials (in July of 2025, Google Scholar listed around eighty publications with “artificial intelligence” and “materials” in the title and dated from the current year), including prediction of new entities.
• The discovery of new mineral species constitutes a more demanding challenge as these predicted new mineral species must have natural occurrences resulting from geological processes. There are some initial results, however, that are not especially impressive, as we will discuss.
• We assess diverse instances of available generative artificial intelligence tools (Aria, ChatGPT, Claude, Copilot, Gemini, Grok, M365 Copilot, Meta AI, Perplexity, and YouChat) in relation to their usefulness in predicting new, undiscovered mineral species along the following main lines: the current state of the art in relation to confirmed predictions, and proposed methodologies of artificial intelligence (including potential limitations) for this goal. Special attention will be given to the issue of natural occurrence. Accordingly, we promote an evaluation of artificial intelligence potential by artificial intelligence tools.
• Results are widely variable, with some generic answers, some problems with references, and some promising suggestions regarding the conditions under which the new mineral species could be found.

3.7. Assessment of Urban Flood Vulnerability in Manila City, Philippines Under Variable Rainfall Scenarios: A Spatiotemporal Analysis Approach

• Charlize Kirsten Brodeth ¹, Alliyah Gaberielle Zulueta ¹, Candice Aura Fernandez ¹, Miko Santos ¹, Jazzie Rosales Jao ^1,2 and Edgar Vallar ²

¹ 

Department of Software Technology, College of Computer Studies, De La Salle University Manila, 2401 Taft Avenue, Manila 1004, Philippines

² 

Department of Physics, College of Science, De La Salle University Manila, 2401 Taft Avenue, Manila 1004, Philippines

• Manila, the capital of the Philippines, is among the most densely populated cities globally and is highly susceptible to flooding due to its low-lying terrain, rapid urban development, inadequate drainage infrastructure, and geographic proximity to the Pasig River and Manila Bay. The city regularly experiences pluvial, fluvial, and tidal flooding, exacerbated by climate variability and sea-level rise. This study presents a spatiotemporal analysis of urban flood vulnerability in Manila under three distinct rainfall scenarios: light, moderate, and heavy intensity. Flood hazard maps were generated for each scenario using hydrodynamic simulations and integrated with socio-demographic data at the Barangay level to evaluate population exposure and sensitivity. Spatial correlation and spatial autocorrelation techniques, including Moran’s I and Local Indicators of Spatial Association (LISA), were applied to identify statistically significant clusters of flood vulnerability. Vulnerability was assessed as a function of flood intensity, population density, poverty incidence, age distribution, and access to basic services and infrastructure. In addition to mapping high-risk areas, the study identified flood-resilient “safe zones”, geographic locations that consistently remained outside flood extents across all modeled scenarios. These areas were evaluated for their suitability as evacuation centers and emergency response sites based on proximity to vulnerable populations and existing infrastructure. Findings highlight a clear spatial overlap between flood-prone zones and socioeconomically disadvantaged communities, indicating the need for targeted disaster risk reduction and urban planning strategies. The results provide evidence-based recommendations for policy development aimed at enhancing flood resilience and adaptive capacity in Manila’s urban landscape.

3.8. Benchmarking Large Language Models (Llms) for Data-Driven End-Use Energy Analysis in u.s. Residential Buildings

• Sorena Vosoughkhosravi ¹ and Sahand Vosoughkhosravi ²

¹ 

Department of Construction Management, Thomas Jefferson University, East Falls, Philadelphia, PA, USA

² 

University of Tehran, Tehran, Iran

• Occupant behavior significantly influences residential energy consumption, yet traditional energy modeling practices commonly rely on fixed activity schedules, neglecting dynamic behavioral variations. Among household activities, Dishwashing is a notable yet often overlooked contributor to residential energy demand, as it involves both electricity and hot-water use. Its frequent occurrence after dinner significantly adds to evening peak loads. To address this gap, this study develops a high-resolution, data-driven framework specifically focused on modeling residential dishwashing behavior to support demand-flexible energy management strategies. Utilizing detailed temporal data on dishwashing activities extracted from the American Time Use Survey (ATUS), complemented by relevant household and temporal covariates, this research applies advanced machine-learning algorithms to predict both the probability and timing of dishwasher operation. The resulting occupant-informed load profiles are integrated into comprehensive building energy simulation models, facilitating the assessment of peak-shifting potential, energy-efficiency improvements, and demand-response effectiveness. Findings from this analysis provide enhanced predictive accuracy for energy demand, inform the development of occupant-centered appliance control strategies, and yield actionable insights and recommendations for incentive design and retrofit policies. Furthermore, the proposed modeling framework offers flexibility for adaptation to other occupant-driven activities, promoting broader scalability in occupant-centric energy modeling and supporting the transition toward resilient, low-carbon energy systems.

3.9. Comparison of Intelligent and Traditional Control Systems in Wastewater Treatment Process Control

• Jaloliddin Eshbobaev ¹, Adham Norkobilov ² and Zafar Turakulov ¹

¹ 

Department of Automation and digital control, Tashkent Institute of Chemical Technology, Tashkent 100011, Uzbekistan

² 

Department of Food engineering, Faculty of Shahrisabz Food Engineering, Tashkent Institute of Chemical Technology, Shahrisabz 181306, Uzbekistan

• Modern wastewater treatment plants face growing operational challenges due to increasingly variable influent compositions, stricter environmental regulations, and rising energy efficiency demands. This study provides a comprehensive evaluation of three advanced control strategies for optimizing wastewater treatment processes: conventional Proportional-Integral-Derivative (PID) control, fuzzy logic control, and the innovative Adaptive Neuro-Fuzzy Inference System (ANFIS). The research specifically focuses on addressing the critical need for intelligent systems capable of managing complex, non-linear relationships in key water quality parameters, particularly Total Dissolved Solids (TDSs) and water hardness concentrations. Through detailed MATLAB/Simulink simulations, we implemented each control methodology in a sophisticated wastewater treatment plant model that accurately replicates real-world operational conditions. The controller’s performance was rigorously assessed using multiple quantitative metrics: settling time, percentage overshoot, steady-state error, and energy consumption efficiency. Experimental results demonstrated that while the conventional PID controller achieved basic regulation, it exhibited significant limitations including 10% overshoot, prolonged 25-s settling time, and noticeable steady-state error. The fuzzy logic approach showed marked improvement, reducing overshoot to less than 1% and settling time to 13 s. The ANFIS controller outperformed both alternatives, delivering exceptional control precision with near-zero overshoot (0.2%), rapid 10-s response time, and complete elimination of steady-state error. Furthermore, the ANFIS system demonstrated superior adaptability to process variations while reducing energy consumption by 50% compared to traditional methods. These findings provide compelling empirical evidence that ANFIS-based control systems represent a transformative solution for next generation wastewater treatment infrastructure, offering unmatched performance in terms of both treatment quality and operational efficiency.

3.10. Ecological Engineering with Pandemic Waste: Transforming Discarded Face Masks into Water-Saving Plant Media for Urban Ecosystems

• Abid Hussain
• Department of Biological Sciences, Thal Univeristy Bhakkar, Bhakkar 30000, Punjab, Pakistan
• The COVID-19 pandemic has generated an unprecedented surge in disposable face mask waste, with an estimated 3.4 billion masks discarded daily, exacerbating global plastic pollution while urban agriculture faces water scarcity challenges, particularly in arid regions. This study addresses both issues by developing a circular solution that repurposes surgical masks into hydrogel-enhanced growth substrates for water-efficient urban farming. Sterilized masks were shredded and blended with cross-linked cellulose hydrogels (15% v/v) to create a water-retentive medium, tested in rooftop gardens under arid conditions over 90 days using IoT-monitored irrigation. Results demonstrated a 42% reduction in water use compared to conventional soil, while maintaining 95% crop survival rates (vs. 68% in controls) and increasing tomato yields by 27% due to stable moisture retention. Each square meter of substrate recycled ~35 masks, preventing 1.2 kg CO₂e emission from incineration. The methodology aligns with ecological engineering principles, leveraging mask-derived polypropylene fibers as a structural base for hydrogels, which also reduced microplastic leakage by 89% compared to untreated mask waste. This approach not only diverts PPE from landfills but also enhances urban food security in water-stressed areas. This study concludes that scaling this innovation could mitigate pandemic-era plastic pollution while supporting SDGs 2 (Zero Hunger), 6 (Clean Water), and 12 (Responsible Consumption), with future research needed to optimize hydrogel formulations for diverse crops and climates.

3.11. Exploring MaaS Adoption in a Car-Oriented City: Dynamic Stated-Preference Insights from Naples

• Christian Riccio
• Department of Mathematics and Physics, University of Campania Luigi Vanvitelli, 81100 Caserta, Italy
• Two-thirds of the world’s population is expected to reside in metropolitan cities by 2050, placing an unprecedented burden on energy efficiency, environmental protection, and sustainable transportation. Southern European urban agglomerations, such as Naples (Italy), face specific challenges: a highly car-dependent culture, chaotic traffic, high air pollution, and a fragmented public transportation network. In this, Mobility-as-a-Service (MaaS) promises to integrate heterogeneous modes into subscription bundles, promoting a switch to low-emission, low-resource transportation. Understanding how people perceive and set up MaaS bundles is crucial for assessing their environmental and operational feasibility. I designed a novel iOS-based tool for conducting dynamic stated preference surveys of MaaS, the first of its kind in the literature. Compared to conventional questionnaires, the app collects extensive travel diaries and socio-demographic details. It interactively guides respondents to customize MaaS packages, reconfiguring sequences of trips and budgets in real-time. A case study in Naples explores how the platform can capture behaviourally driven responses in a car-dependent, environmentally stressed metropolitan area. Initial survey results indicate the tool’s capacity to generate fine-grained microdata on adoption propensity and sensitivity to service features. Data enable the estimation of MaaS take-up scenarios and related implications for energy consumption and emissions savings. The described methodology indicates how dynamic SP tools have the potential to support evidence-based design of MaaS schemes in complex cities. The Naples case offers lessons applicable elsewhere regarding how evidence-based approaches can inform sustainable, energy-efficient urban mobility policies in cities with challenging transportation and environmental conditions.

3.12. Towards an EEW System in Greece: A Performance Study of ElarmS and VS Against the NOA Revised Bulletin

• Konstantinos Boukouras ^1,2, Christos Evangelidis ², Vassilios K. Karastathis ², Evangelos Nannos ¹ and Grigorios Koulouras ¹

¹ 

TelSiP Research Laboratory, Department of Electrical and Electronic Engineering, School of Engineering, University of West Attica, Ancient Olive Grove Campus, 250 Thivon Str., GR-12241 Athens, Greece

² 

Institute of Geodynamics, National Observatory of Athens, Thiseio, Athens, Greece

• Earthquake Early Warning Systems (EEWs) provide seconds to tens of seconds of lead time by exploiting the faster propagation of P waves relative to the more damaging S waves. We study and test the performance of two EEW systems, the Earthquake Alarm Systems (ElarmS) and the Virtual Seismologist (VS). ElarmS is developed by the University of California, Berkeley, and is part of the U.S. west-coast-wide ShakeAlert EEW. It rapidly associates P-wave triggers across stations and uses early amplitude metrics (e.g., peak displacement) with empirical ground motion scaling relationships to estimate origin time, epicenter, and magnitude. VS is currently maintained by the Swiss Seismological Service at ETH Zurich and is using a Bayesian approach using observed picks and the earliest available ground motion amplitudes, based on predefined prior information and envelope attenuation relationships, in order to estimate earthquake magnitude, location, and the distribution of peak ground shaking. We have tuned, configured, and operated these two systems for the broader Greek region, also focusing on the Attica region and the Corinth Gulf, benchmarking alert latency, epicentral misfit, and magnitude residuals against the National Observatory of Athens (NOA) revised bulletin. Results include regional latency maps and accuracy statistics that elucidate speed–accuracy trade-offs and network geometry effects for operational EEW in Greece.

3.13. A 108-Year Rainfall Dataset, Intensity-Duration-Frequency Curves Under Uncertainty, and Design Storm Generation for Limassol, Cyprus Through an Automated Python Workflow

• Angelos Alamanos ¹ and Olympia Nisiforou ²

¹ 

Independent Researcher, 10243 Berlin, Germany

² 

Cyprus University of Technology, Limassol, Cyprus

• Accurate rainfall records producing Intensity-Duration-Frequency (IDF) curves, relating rainfall intensity to its duration and return periods, and derived design storms, are cornerstones of resilient hydraulic and urban drainage design. By translating long-term rainfall statistics into specific storm profiles, engineers can reliably design and size sewers, culverts, basins, and flood defenses, and run hydrological models that predict runoff volumes and peak discharges under future extremes.
• We merged two publicly available sources (national meteorological archives and the ECA&D homogenized series) to assemble a continuous 108-year (1916–2024) daily rainfall time-series for Limassol, Cyprus. A Python-based gap-filling tool (mean, linear interpolation, moving-average) ensures applicability to other sites. We generated IDF curves from two records lengths (1990–2024, 1970–2024) by fitting Gumbel, GEV, Log-Pearson III, and Weibull distributions, evaluating goodness-of-fit (using two different tests) and selecting the optimal model.
• For each one, we produced 24-h depth tables at multiple return periods and 95% confidence bounds via bootstrap resampling. Finally, we derived hyetographs for multiple return periods, using uniform, triangular, and Chicago methods.
• This work provides the first publicly available detailed hydro-meteorological dataset, IDF analysis, and suite of design storms for Limassol, filling a critical gap in local resilience planning.
• The process is discussed step by step in a Supplementary Material, guiding modelling, selection, and design decisions that an analyst may face in similar studies.
• All steps are incorporated into user-friendly Python scripts, that are readily adaptable to other regions, and will be publicly released to support robust hydrological modelling and infrastructure design.

3.14. A Novel 3D-Printed Capacitive Deionization Process for Desalination and Nutrient Recovery Applications

• Zubairullah Khan Mohammad ¹ and Veera Gnaneswar Gude ^2,3,4

¹ 

Purdue University Northwest Water Institute, 2540 169th St. Schneider Avenue Building, Hammond, IN 46323, USA

² 

Purdue University Northwest Water Institute, Purdue University Northwest, Hammond, IN 47907, USA

³ 

Mechanical and Civil Engineering Department, Purdue University Northwest, Hammond, IN 47907, USA

⁴ 

Environmental and Ecological Engineering, Purdue University, West Lafayette, IN 47907, USA

• Membrane capacitive deionization (MCD) technology offers numerous opportunities for water, wastewater treatment, desalination, nutrient removal and recovery and high value-added chemical production. While MCD technology has been explored very well, there are many design-, material- and process-related challenges that pose barriers to their large-scale applications. In this research, we study design parameters such as the distance between the electrodes and membranes, the volume of the anode and cathode compartments and the type of electrode materials that may influence the performance of the MCD process. This study investigates the effect of electrode–membrane distance, novel carbon electrode materials and the type of ion exchange membranes on the efficiency of the MCD process. We test the novel MCD process for the application of desalination across varying concentrations of saline water. We analyze the performance of the system using different initial salt concentrations to assess its ion removal capacity and energy consumption at various electric loads and different process conditions. Key performance indicators such as salt removal efficiency, charge efficiency, and energy per ion removed were evaluated. In addition, we also evaluate the nutrient recovery potential of this novel MCD process. Nitrogen and phosphorous recovery potentials from used hydroponic nutrient water are evaluated using this process. Similar parameters such as the nutrient recovery efficiency, charge efficiency and specific energy consumption of the process are evaluated. The results demonstrate that optimal design of anode and cathode compartments, electrode–membrane distance and sustainable electrode materials may enhance resource efficiency and cost savings.

3.15. A Study on Slope Stability at Earthquake Limit State Using the Analytical and Numerical Methods

• Peng Ren
• The College of Architecture and Civil Engineering, Beijing University of Technology, Beijing 100124, China
• Phenomena of damaged ecosystems and environments have caught the widespread attention of scientists and engineers. Earthquake events are good examples, severely damaging slopes and houses. A study is conducted on slope stability at earthquake limit state so that slopes and relevant houses can be safeguarded. The novel analytical and numerical methods are applied to the study on slope stability at earthquake limit state. The analytical method consults moment equilibrium equations of slopes and a limit equilibrium theory. The numerical method uses the coupled finite elements and strength reduction approach at the earthquake limit state. In addition, earthquake effect for the analytical and numerical methods is considered as a horizontal static force through the pseudo-static method. The validation of the analytical and numerical methods is verified through a comparison between their calculation results. In engineering examples at the earthquake limit state, factors of safety of slopes are shown versus various strength factors of slopes and earthquake intensities. Factors of safety of slopes increase with the increase in strength factors of slopes, including equivalent friction angles and cohesive strength. However, factors of safety of slopes decrease with the increase in earthquake intensities. They imply slopes may be more safe with strong strength factors and low earthquake intensities. These would provide references for the protection of ecosystems and environments.

3.16. Adaptive Neuro-Fuzzy Control of a Small Wind Turbine Integrated with Battery Storage for Remote Villages in Uzbekistan

• Ulugbek Muinov and Botir Usmonov
• Department of Automation and Control, Tashkent Chemical Technological Institute, 100011 Tashkent, Uzbekistan
• Uzbekistan’s rural regions experience continuing issues in energy access because of poor grid networks and variable renewable sources. The solution is small-scale wind turbines and energy storage. But the wind speeds and load demand are variable and thus intelligent control systems are needed for them to perform at their best.
• This paper is an attempt to design an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller to control a small wind power system with a battery storage unit. The controller will be intelligent to control the flow of power between the wind turbine, battery, and local loads. A MATLAB/Simulink model is created to simulate the reaction of the system to various wind and load conditions.
• The results of the simulation prove that the ANFIS controller is better in stabilizing the voltage, reducing power fluctuations, and optimizing the battery charge–discharge cycle compared to other conventional PI and standalone fuzzy controllers. Environmental variability is effectively responded to by the system, making it more reliable and energy-efficient.
• ANFIS control and wind–battery microgrid integration provide a feasible and expandable off-grid electrification solution to remote areas. This strategy promotes the renewable energy ambitions of Uzbekistan and offers an example of smart microgrid implementation in other resource-limited rural areas. The next steps would be in practical application and hardware verification.

3.17. An IoT-Integrated Hybrid Solar- and Fuel Cell-Powered Charging Station for Portable Devices and STEM Education

• Mohammad Biswas ¹, reem salim ², Ahmed Ismail ¹, Ahmad Alhjouj ¹, Hector Villasana ¹ and Mustafa Kerem Yucedag ²

¹ 

Department of Mechanical Engineering; Houston Engineering Center, The University of Texas at Tyler, Houston, TX 77082, USA

² 

Engineering Center of Excellence, Houston Community College, Houston, TX 77082, USA

• Access to clean, reliable energy remains a persistent challenge in underserved communities, especially during periods of limited solar availability. This project introduces a hybrid solar charging station designed to power micro-mobility devices and portable electronics while supporting real-world STEM education. The initiative, jointly developed by University of Texas at Tyler and Houston City College, aims to enhance energy access and knowledge empowerment in the Greater Houston area. The system integrates a 150–250 W solar photovoltaic panel, a battery storage set, a 30–100 W hydrogen fuel cell, and a solar charger controller, coordinated through a customized energy management system. A distributed array of sensors collects performance data, which is transmitted via an IoT-enabled platform to a cloud-based dashboard for real-time monitoring, remote control, and analytics. This dual-energy production design ensures continuous power availability by using solar energy as the primary source during daylight to charge the batteries, which in turn supply power to both the electrical loads and the hydrogen generator. The fuel cell uses hydrogen that serves as a backup energy source during periods of low or no sunlight. In addition to its energy function, the station serves as a multidisciplinary educational tool. Students engage in hands-on learning across renewable energy technologies, embedded control systems, and data-driven system analysis. The platform also lays the groundwork for implementing more advanced control strategies, including predictive and adaptive methods that incorporate elements of machine learning. This system provides a model for sustainable energy deployment and workforce development in regions with limited energy access.

3.18. Artificial Intelligence for Climate Change Modeling: Challenges and Future Research Directions

• Muhammad Nda ¹, Ibrahim Wali ¹, Gideon Shabako Jiya ¹ and Ramatu Muhammad Nda ²

¹ 

Department of Civil Engineering, The Federal Polytechnic Bida, Niger State, Nigeria

² 

Faculty of Computing and Information Technology, Newgate University Minna, Niger State, Nigeria

• Climate change is one of the most important issues facing the world today; precise climate modelling is crucial for forecasting its effects, directing adaptation plans, and influencing policies. Despite their scientific rigour, traditional climate models frequently have drawbacks, such as high computational costs, coarse temporal and spatial resolutions, and difficulties accurately representing complex nonlinear processes. By facilitating the identification of hidden patterns, increasing predictive accuracy, and accelerating simulation processes, artificial intelligence (AI) has recently surfaced as a promising tool to supplement and extend traditional approaches. This manuscript reviews the current use of AI for climate change modelling, focusing primarily on machine learning, deep learning, and hybrid AI approaches for diverse tasks. Several previous studies indicate that AI-driven models can improve seasonal forecasting, enhance extreme weather event projections, and optimise resources and energy management in light of climate change. Despite these advancements, numerous challenges remain. Limited data availability and quality frequently characterise climate change-related studies, significantly impacting the reliability of AI models. Furthermore, issues with computational scalability, uncertainty quantification, and integration with physical climate models continue to constrain widespread adoption. Future work must concentrate on improving surrogate modelling techniques, building strong AI-driven early warning systems for climate-related disasters, and creating hybrid frameworks that combine AI and physical models to fill these gaps.

3.19. Assessing Convective Parameterizations in RegCM5 for Simulating Extreme Rainfall over Egypt

• Zeinab Salah, Rania Ezzeldeen and Reham Rabie
• Egyptian Meteorological Authority, Cairo 11231, Egypt
• Accurate prediction of heavy rainfall events poses a significant challenge in numerical weather prediction (NWP) due to the complex processes in the atmosphere, its dynamic behavior, the parameterization of microphysical processes, and model uncertainties. In recent decades, Egypt has experienced extreme precipitation events, particularly along its northern coast, some of which exceeded expected intensity levels. This study aims to enhance the prediction of extreme rainfall events over Egypt using the ICTP regional climate model version 5 (RegCM5). We tested various convective schemes within the following models: Emanuel (1991), Grell (1993) with the Fritsch–Chappell (1980) cumulus closure scheme, Kain–Fritsch (1990), and Tiedtke (1996), to identify the optimal schemes that capture the different rainfall cases. For our experiments, we utilized the ERA5 and FNL reanalysis datasets as the initial and boundary conditions (ICBC) for RegCM5. All simulations were conducted with a spatial resolution of 5 km. To verify our results, we compared the simulated rainfall with the measurements from four ground stations in Alexandria (El-Nouzha, Abu-Qir, Borg El-Arab, and Ras El-Tin), in addition to the precipitation data from the ERA5 reanalysis, CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), GPM, and the PERSIANN-Cloud Classification System (PERSIANN-CCS). Based on comparisons between the simulated precipitation from RegCM5 and data from the four rain gauges, the Kain–Fritsch scheme demonstrated both high performance and low mean bias error (MBE), followed closely by the Grell scheme.

3.20. Biosorptive Performance of Reactive 141 Dyestuff from Aqueous Solution Using BESP

• Hakan Çelebi ¹, Tolga Bahadir ¹, İsmail Şimşek ², Behlül Koç Bilican ¹, Şevket Tulun ¹ and İsmail Bilican ³

¹ 

Department of Environmental Engineering, Aksaray University, Aksaray 68100, Türkiye

² 

Department of Molecular Biology and Genetics, Aksaray University, Aksaray 68100, Türkiye

³ 

Department of Electronics and Automation, Aksaray University, Aksaray 68100, Türkiye

• Water is an essential resource for the survival of all living things and plays a critical role in human health, the continuity of ecosystems, and economic activities. However, anthropogenic activities arising from developing industries and a growing population are negatively impacting this indispensable resource. Dyestuffs released as a result of developing industries are carried into soil, air, and water resources, causing environmental pollution. Among these dyes, reactive red 141 (RR141), due to its high solubility, reactivity, and toxicity, poses a significant environmental threat and serious risks to human health and ecosystems. Therefore, it must be treated with appropriate methods. Biosorption is the preferred method for treatment. Eggshells, considered worthless and discarded as waste, were used as biosorbents. In recent years, waste considered garbage in water pollution studies has been incorporated into the biosorption process. Accordingly, in this study, the removal potential of membrane-separated blue eggshell powder (BESP) in its native form without any modification was investigated as an environmentally friendly, economical, and effective biosorbent material. A batch biosorption process was used in the study. The effects of BESP amount (0.1–1 g), contact time (5–90 min), pH (2–10), and temperature (20–35 °C) on the removal efficiency were evaluated. Under optimum operating conditions (pH: 4; time: 30 min.; BESP dose: 0.5 g; temperature: 20 °C), the maximum RR141 removal efficiency was found to be around 81%.

3.21. Chicken Manure Compost as an Amendment During Phytoremediation of Mercury in Soils Using Brachiaria Dyctioneura

• Valentina Cardozo ¹, Irina Patricia Tirado-Ballestas ² and Jorge L Gallego ¹

¹ 

Biodiversity, Biotechnology and Bioengineering Research Group GRINBIO, Department of Engineering, University of Medellin, 050026 Medellín, Colombia

² 

Grupo de Investigación GENOMA, Universidad del Sinú, Facultad de Medicina, 130014 Cartagena de Indias, Colombia

• Mercury contamination of soils, even at relatively low levels, remains a global environmental and health concern due to its persistence, bioaccumulation, and toxicity. Phytoremediation offers a sustainable and cost-effective strategy, and the addition of organic amendments can improve plant growth and metal uptake. This study investigated the use of chicken manure compost to enhance mercury removal by Brachiaria dyctioneura, a tropical forage species with high adaptability and biomass production. Two soils with initial mercury concentrations of 106.07 ± 13.41 μg/kg and 672.234 ± 74.59 μg/kg were amended with chicken manure at 1:4 and 3:4 ratios (manure:soil). Physicochemical properties, organic carbon, nitrogen, phosphorus, and metal contents were characterized. Seeds of B. dyctioneura (1 g per experimental unit) were sown with five replicates per treatment. After 30 days, plants were separated into roots and shoots for mercury determination using EPA Method 7473 with a RA-915LAB Direct Mercury Analyzer. Results indicated that lower amendment levels enhanced mercury accumulation in shoots, favoring aerial translocation, while higher doses increased retention in roots and reduced translocation. For Soil 1, mercury concentrations were 3.49–24.92 μg/kg in roots and 10.32–14.63 μg/kg in shoots, whereas in Soil 2 values reached 13.44–191.53 μg/kg in roots and 67.59–90.47 μg/kg in shoots. These results suggest that amendment dosage significantly influences mercury partitioning in plants. The findings highlight the potential of B. dyctioneura as a promising species for mercury phytoremediation, with chicken manure compost serving as an effective amendment to optimize remediation performance.

3.22. Comparative Time-Series Analysis of the Air Quality of Urban and Suburban Areas in the Philippines from 2020 to 2025

• Mikaela De Jesus ¹, Jazzie Jao ², Edgar Vallar ³, Floro Junior Roque ³ and Jejomar Bulan ³

¹ 

Environment and RemoTe Sensing Research (EARTH) Laboratory, Department of Physics, College of Science, De La Salle University—Manila, Manila 1004, Philippines

² 

Department of Software Technology, De La Salle University Manila, Manila 1004, Philippines

³ 

Department of Physics, College of Science, De La Salle University—Manila, Manila 1004, Philippines

• Air pollution is one of the major global concerns impacting the pillars of sustainability—economic, environmental, and social factors. In the Philippines, air pollution continues to deteriorate due to multiple factors, as reflected in the exceeding threshold value of the country’s air quality parameters set by the World Health Organization (WHO). With the rapid urbanization of the country, research shows that building morphology affects the air flow in urban and rural areas, contributing to air pollution concentration.
• This study aims to compare and analyze the concentrations of the key pollutants—PM_2.5, CO, NO₂, and SO₂—from the open dataset of Copernicus Sentinel-5P Precursor in association with the building morphology and meteorological factors of urban and suburban areas over the past five years. Moreover, two analytical methods were conducted: (1) a multivariate time-series analysis was performed to examine the trend of air pollutants in correlation with meteorological factors and urban morphology in these areas, and (2) a comparative analysis was performed to assess the similarities and differences of pollution concentrations across geographical areas. The results indicate that the concentration of the key pollutants is slightly higher in the urban areas than in the suburban areas. This pattern may be attributed to the morphology of geographical areas with low-rise and medium-rise buildings, which predominate in suburban areas, indicating a better air flow in these areas. These findings formulate recommendations that will benefit geographical areas in targeted air quality mitigation.

3.23. Comparing the Spatiotemporal Variation of Air Quality Data from Satellite Measurements and Ground Monitoring Station in Manila, Philippines Before, During, and After the COVID-19 Lockdown

• Nadine Grace Caido, James Roy Lesidan, Edgar Vallar and Maria Cecilia Galvez
• Environment and Remote Sensing Research (EARTH) Laboratory, Department of Physics, De La Salle University, Manila 0922, Philippines
• The Philippines was placed under several lockdowns to limit movements and prevent the spread of the virus during the COVID-19 pandemic. The imposed restrictions reduced the transport and industrial operations, which are primary contributors of air pollution, mainly in the cities of Metro Manila. Satellite measurements of aerosol optical depth (AOD) and greenhouse gases (GHG) such as carbon dioxide (CO₂) and tropospheric ozone (O₃) can improve surface monitoring of particulate matter (PM_1,2.5,10) and GHG but this requires a better understanding of the relationship between satellite and ground monitoring data. In this study, we used the MODIS MAIAC land AOD data at 550 nm, Sentinel-5P TROPOMI O₃ data, and OCO2 X_CO2 for the satellite data over Manila, Philippines with a concurring 5-year continuous measurement of PM_1.0,2.5,10, O₃, and CO₂ from a ground monitoring station near a busy highway. This measurement coincides with the lockdown from the COVID-19 pandemic and shows how human activities can greatly affect air quality. The results show that PM values before the lockdown period have the highest values and exceed WHO limits, while the lowest values were measured after lockdown period for the whole study period. On the other hand, CO₂ and O₃ values increased. This study also shows the correlation between satellite and ground monitoring data and shows the possibility of using remote satellite data as alternative for ground air quality measurement in Manila. Overall, these findings provide supplemental information for operative policymaking to mitigate air pollution and improve air quality in highly urbanized areas.

3.24. Data-Driven Analysis of Tree Structure Variation Across Forest Types in Tapajós National Forest, Brazil

• Jorem Ivan Boado ¹, Franelyn Dale Jose ², Sofia Andrea Linghap ², Jazzie Rosales Jao ³, Edgar Vallar ² and Maria Cecilia Galvez ²

¹ 

Department of Software Technology, College of Computer Studies, De La Salle University, Manila 1004, Philippines

² 

Department of Physics, College of Science, De La Salle University, Manila 1004, Philippines

³ 

Department of Software Technology, College of Computer Studies, De La Salle University Manila, 2401 Taft Avenue, Manila 1004, Philippines

• Understanding how tree structural traits vary across forest conditions is essential for assessing ecological integrity, detecting anthropogenic disturbances, and informing conservation strategies. This study investigates the architectural characteristics of trees within primary (PF), secondary (SF), and selectively logged forests (SLF) of the Tapajós National Forest, a representative landscape in the Brazilian Amazon. Although forest inventory datasets are increasingly available, few studies explicitly analyze the relationship between phenotypic tree traits and forest condition, or employ geometric modeling to estimate structural volume. To address this gap, we analyzed biometric data from 30 permanent plots surveyed in 2010, using a combination of statistical and geospatial techniques implemented in Python. Correlation and scatterplot analyses revealed strong associations between total tree height and maximum crown width (r > 0.8), and moderate to strong correlations among diameter at breast height (DBH), height, and crown dimensions (0.40 r 0.80). Comparative analyses among forest types showed that PF plots consistently exhibited greater DBH, crown depth, and total height than SF and SLF plots, reflecting structural degradation linked to anthropogenic disturbance. Distributions of wood density and crown morphology further highlighted ecological differences among forest types. To enhance structural assessment, we incorporated crown shape coefficients and directional crown radii to estimate individual tree crown volumes using ellipsoidal geometry. These volume estimates followed patterns consistent with other structural metrics and provided a scalable proxy for canopy structure, enabling spatially explicit comparisons. Overall, this integrative approach offers a robust framework for quantifying tree architecture and supports improved forest monitoring, carbon modeling, and biodiversity evaluation in tropical forest ecosystems.

3.25. Detection of Coastal Geomorphological Changes Using Remote Sensing and GIS Techniques: A Case Study of Artificial Inlets of the Bardawil Lagoon, Egypt

• Kamal Srogy Darwish
• Department of Geography, Faculty of Arts, Minia University, Al Minya 61519, Egypt
• Coastal geomorphological changes significantly affect the environmental integrity and socio-economic resilience of vulnerable coastal zones. This study investigates the geomorphological evolution of the artificial inlets of Bardawil Lagoon, located along Egypt’s Mediterranean coast, using multi-temporal satellite remote sensing data from Landsat 8/9 (2015–2025) and digital elevation models (DEMs). The accuracy of digital image processing techniques was validated using high-resolution Google Earth imagery. Bardawil Lagoon, a critical ecological and coastal system, has undergone substantial changes driven by both anthropogenic activities and natural processes, including sediment transport, tidal fluctuations, and engineered inlet modifications. Spatiotemporal monitoring using satellite remote sensing has become a vital tool in recent decades for mapping and assessing coastal dynamics. In this study, high-resolution imagery was processed within a GIS-based framework to analyze shoreline change rates, inlet migration, sediment deposition within navigational canals, and the performance of coastal protection structures. The Digital Shoreline Analysis System (DSAS) was used to quantify shoreline retreat and advance. Results reveal significant morphological variability in the artificial inlets, characterized by pronounced eastward migration and seasonal sediment accumulation that influence lagoon connectivity and hydrodynamic behavior. This research underscores the effectiveness of integrating remote sensing and GIS for monitoring coastal inlet dynamics and provides critical insights for sustainable coastal management, infrastructure planning, and ecological conservation in semi-enclosed systems such as Bardawil Lagoon. The approach is adaptable to other coastal environments facing similar natural and anthropogenic pressures.

3.26. Development and Characterization of Antibacterial Bioplastic Films Based on Chemically Modified Musa Paradisiaca Peel Starch and Chitosan Composites

• Henry Adolfo Lambis Miranda ¹, Juliana Puello-Mendez ², Jorgelina Pasqualino ³, Miguel Cuesta-Peña ⁴ and Isabella Rosado-Zarza ⁴

¹ 

Processes and Systems Engineering, CIPTEC Research Group, Fundación Universitaria Tecnológico Comfenalco, Cartagena, Colombia

² 

GICI Research Group, Chemical Engineering Department, Universidad de San Buenaventura Cartagena, Diag. 32 # 30-966, Cartagena, Colombia

³ 

GISAH Research Group, Environmental Engineering Program, Universidad Tecnológica de Bolívar, Campus Tecnológico, km 1 vía Turbaco Cartagena, Cartagena, Colombia

⁴ 

Processes and Systems program, Fundación Universitaria Tecnológico Comfenalco, Cartagena, Colombia

• The escalating demand for sustainable packaging materials has driven research into biodegradable polymers derived from agricultural and industrial waste. This study focuses on the development and physicochemical characterization of novel antibacterial bioplastic films based on chemically modified banana (Musa paradisiaca) peel starch and chitosan. Starch was first extracted from banana peels and subsequently subjected to a chemical modification, such as acetylation, to enhance its thermoplastic properties and reduce its inherent hydrophilicity. The modified starch was then blended with a chitosan solution at various concentrations to formulate a composite film-forming solution. The bioplastic films were fabricated using the solution casting method, followed by a controlled drying process.
• A comprehensive characterization was performed to evaluate the resulting films. Fourier-Transform Infrared Spectroscopy (FTIR) was employed to confirm the success of the chemical modification and to identify intermolecular interactions between the starch and chitosan polymers. The crystalline structure of the films was analyzed using X-ray Diffraction (XRD), while Scanning Electron Microscopy (SEM) was used to investigate the surface and cross-sectional morphology. Key physical properties, including tensile strength, elongation at break, water vapor permeability (WVP), and thermal stability via Thermogravimetric Analysis (TGA), were systematically measured. Finally, the antibacterial efficacy of the composite films was quantitatively assessed against common foodborne pathogens, such as Escherichia coli and Staphylococcus aureus, using the agar diffusion method. This methodology provides a framework for evaluating the potential of these biocomposites as a high-performance, eco-friendly packaging alternative.

3.27. Development of a Microcontroller-Based Intelligent Combustion Control System for Reformers in Industrial Applications

• Bintu Jasson and Malak Hani Rashed
• Chemical Engineering Department, University of Bahrain, College of Engineering, Sakhir 32038, Sakhir 1017, Road 5418, Zallaq 1054, Bahrain
• Industrial reformers are important parts of clean energy and making fertilizer. At their core, these systems need high-temperature heat sources to make the chemical processes happen. In the past, people had to start up the heat-generating units in reformers by hand, which was very dangerous. These concerns include the possibility of gas leaks or ignition failure, which might put people and nearby equipment in danger. Also, human control typically leads to problems like unstable fuel–air mixes and incomplete combustion, which in turn impact how much energy is used and how much work is achieved. The developed system included an Automated Thermal Management System that can control and monitor how heat sources work in the chamber by using a thermal imaging camera and different sensors. The system takes care of important duties including safe ignition sequencing, real-time flame detection, and operational regulation on its own. Some of its benefits are improved safety through automatic shutdown during failures, increased thermal efficiency through optimized fuel–air mixing, and continuous data logging to help with system diagnosis and optimization. ATMS used Raspberry Pi and IoT, where the design places a strong emphasis on safety. Also, the system uses sensors to monitor the fuel and air input and changes the ratios of these inputs on the fly to get the best combustion. The proposed system is modeled and can improve in industrial reformer situations through different controlling techniques.

3.28. Effect of Ecological Binders on the Thermal Characteristics of Walls

• Soumia Mounir and Youssed Maaloufa
• MECAD, National School of Architecture Agadir, New Complex Ibn Zohr Agadir, Hay Dakhla, 80 000 Morocco
• The world suffers from serious environmental problems related to pollution and greenhouse gases, especially from the construction sector, known for its high level of energy consumption and carbon emission. To evaluate this, the authors aimed to demonstrate the benefits of ecological binders on the thermal characteristics of walls, encouraging constructors to adopt these binders in the building sector, which would significantly reduce energy consumption, pollution, and carbon emissions from construction activities.
• This work has been divided into several sections. The first section consisted of a description of the walls studied and the materials used; the second one included a description of the thermal characteristics of modern and vernacular walls using the ecological binders plaster-cork and Tadelakt, in which thermal properties have been determined using the hot plate method. In addition, a study concerning the heat exchange of those walls using the ecological binders has been conducted to evaluate the effect of Tadelakt and plaster-cork on the thermal characteristics of walls. The final step involves a comparison between carbon emissions of the walls studied with and without those ecological binders. Results show some important findings about the thermal characteristics and the heat exchange of walls with the exterior air using the ecological binders. Moreover, the authors observe a significant carbon emission from walls using those ecological binders.

3.29. Effect of Shaft Damping on the Dynamic Performance of a Wind Turbine Drivetrain: A Two-Mass System Approach

• Hafsa Jbilou, Abdelouahed Djebli and Hilal Essaouini
• Energy Laboratory, Faculty of Sciences, Abdelmalek Essaadi University, Tetouan 93002, Morocco
• Wind turbine drivetrains are flexible mechanical systems prone to torsional oscillations, particularly when modeled as a two-mass system consisting of rotor inertia, generator inertia, and a flexible shaft. These oscillations can increase mechanical stresses, accelerate fatigue damage, and reduce power quality if not properly controlled. Shaft damping plays a critical role in shaping the dynamic response of the drivetrain, but it also introduces a trade-off between vibration suppression and energy efficiency.
• This paper investigates the effect of shaft damping on the dynamic performance of a wind turbine drivetrain modeled as a two-mass system. Transfer function models for rotor speed, generator speed, and shaft torque were derived, and both time-domain and frequency-domain analyses were performed. Step responses were used to evaluate transient metrics such as overshoot, oscillation amplitude, and settling time, while Bode diagrams captured resonance behavior and frequency sensitivity. The cumulative energy dissipated in the shaft was also computed to assess efficiency impacts.
• The results show that low shaft damping produces sharp resonance peaks and sustained oscillations, leading to poor dynamic stability. Increasing damping reduces oscillations, suppresses resonant modes, and improves torque transmission smoothness. However, higher damping levels also result in greater energy dissipation, reducing drivetrain efficiency. These findings highlight the need for optimal damping selection to balance mechanical stability with energy performance. This study provides insights into the design and optimization of wind turbine drivetrains, contributing to improved reliability and overall system performance.

3.30. Effective Outlier Detection in Smart Home Energy Consumption Using Integrated Change Point Detection and Unsupervised Learning

• Yamini Kodali ¹, Kasaraneni Purna Prakash ² and Yellapragada Venkata Pavan Kumar ³

¹ 

School of Computer Science and Engineering, VIT-AP University, Amaravati 522241, Andhra Pradesh, India

² 

Department of Computer Science and Engineering, Siddhartha Academy of Higher Education, Kanuru 520007, Andhra Pradesh, India

³ 

School of Electronics Engineering, VIT-AP University, Amaravati 522241, Andhra Pradesh, India

• As smart homes proliferate globally, smart meter energy consumption data has become vital for data-driven decisions, making data quality crucial for reliable analytics. However, smart meter data often contain anomalies such as outliers, missing values, and redundant entries, caused by communication delays, transmission errors, and device malfunctions. These anomalies can significantly compromise the accuracy of applications, including billing, contingency analysis, and energy forecasting. Among them, outliers are particularly detrimental, as they can distort statistical analysis, mislead machine learning models, and undermine overall system reliability. Thus, to address the challenge of detecting outliers in smart home energy consumption effectively, this paper focuses on hourly usage patterns and explores three methods initially: (i) a clustering-based technique using Density-Based Spatial Clustering of Applications with Noise (DBSCAN), (ii) a statistical forecasting model using Auto-Regressive Integrated Moving Average (ARIMA), and (iii) a time series segmentation method using Change Point Detection (CPD). While each method has its strengths, their standalone use is limited in handling the complexity and variability of real-world data. Therefore, to address this issue, this paper proposes three hybrid models, namely ARIMA+DBSCAN, CPD+DBSCAN, and ARIMA+CPD+DBSCAN. These models are designed to leverage temporal forecasting, structural shifts, and density-based clustering to identify both sudden and subtle deviations in energy consumption behavior. Simulations on a public smart home dataset from Kaggle show that the ARIMA+CPD+DBSCAN model outperforms others, achieving 0.96 precision, 0.89 recall, a 0.90 F1-score, and 0.98 accuracy, demonstrating the advantage of integrating statistical and clustering-based methods for robust outlier detection in smart home energy.

3.31. Effects of Cow Bone Biochar on the Microbial Properties of Different Soil Texture at Varying Depths and Land Use

• Nancy Ekene Ebido, Joshua Adejoh and Ifeyinwa Monica Uzoh
• Department of Soil Science, University of Nigeria, Nsukka, Enugu State, Nigeria
• This study investigated the effects of cowbone biochar on the microbial properties of different textures at varying depths and land use. The experiment consists of 2 × 2 × 2 × 2 factorial combinations of two biochar sources (Biochar (20 g/4 kg soil) and control), two depths (0–20 and 20–40 cm), two land uses (cultivated and fallow), and two soil textures (sandy clay loam (SCL) and sandy loam (SL)) in a completely randomized design (CRD) replicated three times. The data analyzed were microbial count (MC), microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), and microbial respiration (MR). The results showed that the alkaline nature of biochar was capable of influencing soil microbial activities. The application of biochar on fallow SCL soils had the highest significant effects on soil microbial properties. The least microbial properties were observed in the deeper depths (20–40) of cultivated SL soils, which were not amended with biochar (control). The MC, MBC, MBN, and MR of the topsoil were 66.2%, 11.1%, 26.6%, and 33.9% higher than the subsoil. The SCL textures were 42.8%, 25.0%, 78.5%, and 28.3% higher than SL. The cultivated soils were 29.4%, 16.4%, 41.1%, and 20.8% lower than the fallow soils, respectively. The application of bone biochar increased MC, MBC, and MR of the soils by 10.1%, 7.9% and 9.9% respectively. In conclusion, these findings underscore the potential of cow bone-derived biochar as a suitable soil amendment that not only recycles waste but also improves soil microbial functioning, particularly in sandy soils and degraded agroecosystems.

3.32. Effects of Process Variables in Watermelon Seed Oil Methyl Ester Production Catalyzed by Kaolin-Based Zeolite

• Ahmed Tijani Ahmed ^1,2, Hillary Ilemona Akor ^2,3 and Miroslav Variny ¹

¹ 

Department of Chemical and Biochemical Engineering, Faculty of Chemical and Food Technology, Slovak University of Technology in Bratislava, Bratislava, Slovakia

² 

Department of Chemical Engineering, Confluence University of Science and Technology, Osara, Kogi State, Nigeria

³ 

Department of Chemical Engineering, Federal University of Technology, Minna, Niger State, Nigeria

• The Fourth Industrial Revolution (4IR) drive is accompanied by substantial advancements in the use of technological materials, resulting in massive increases in the quest for a waste-free environment. Watermelon seeds, often discarded as agricultural waste, are a readily available byproduct that can be valorized through biodiesel production, reducing waste while contributing to renewable energy goals and circularity principles. Modification of catalysts for improved biodiesel yield and quality has also been attempted through scientific experimentation. In converting watermelon seed oil to biodiesel, zeolites enhance the transesterification process by improving reactant diffusion, increasing conversion efficiency, and producing higher-purity fuel. This work aims to produce biodiesel from watermelon seed oil using a kaolin-based zeolite as a heterogeneous catalyst. This catalyst is promising for the transesterification reactions of oils due to its economic benefits. Moreso, it is environmentally benign and can be unlike homogeneous catalysts. The transesterification was optimized by varying the reaction time (45 to 105 min), methanol-to-fatty acid molar ratio (1.5:1 to 7.5:1), reaction temperature (55 to 75 °C), and catalyst concentration (0.25 to 1.25 wt%) using the Response Surface Methodology (RSM). It was found that the highest yields (92% and 90%) were achieved for both predicted and actual values, with R² values of 0.9510, respectively. Comparison of the obtained biodiesel quality with relevant ASTM standards yielded positive results, with kinematic viscosity, cetane number, flash point, and free fatty acid of 4.4 mm²/s, 62.4, 156 °C, and 0.37, respectively.

3.33. Efficient Dechlorination of Industrial Wastewater via Optimized Activated Carbon Filtration

• Alisher Rakhimov ¹, Jaloliddin Eshbobaev ² and Rustam Bozorov ¹

¹ 

Karshi State Technical University, Karshi, Uzbekistan

² 

Department of Automation and Digital Control, Tashkent Institute of Chemical Technology, Tashkent 100011, Uzbekistan

• The presence of free chlorine ions in industrial wastewater poses significant environmental and operational risks due to their corrosive, oxidative, and toxic nature. Among various dechlorination techniques, activated carbon filtration has proven effective due to its high surface area and strong adsorption capacity. However, optimizing the amount of activated carbon used while ensuring maximum chlorine removal remains a practical challenge. This study presents a MATLAB-based multi-objective optimization approach for modeling and minimizing activated carbon dosage while maximizing dechlorination efficiency. A laboratory-scale experimental setup was developed to simulate the filtration process. A total of 200 experiments were conducted by varying input parameters such as flow rate (10–100 m³/h), initial chlorine concentration (1–10 mg/L), pressure (1.5–5 bar), pH (6.5–8.5), temperature (15–35 °C), and activated carbon dose (50–200 kg). These parameters and corresponding residual chlorine concentrations were used to train a neural network in MATLAB using the Levenberg–Marquardt backpropagation algorithm. The network achieved high predictive accuracy with an MSE of 0.00176 and R² = 0.9912. A built-in optimization function in MATLAB was then used to identify the optimal combination of input variables that minimized chlorine levels with the least amount of activated carbon. Results showed that a dose of 84 kg of activated carbon reduced residual chlorine to 0.02 mg/L, maintaining a 98% removal efficiency. This research demonstrates the potential of combining experimental data with intelligent modeling techniques to support sustainable and cost-effective wastewater treatment solutions in industrial applications.

3.34. Environmental Assessment of Cadmium, Mercury, and Lead in Suspended Particulate Matter from the Sogamoso River, Colombia

• Valentina Cardozo ¹, Martín E. Anaya ¹ and Jorge L Gallego ²

¹ 

Universidad de Medellín, Medellín 050026, Colombia

² 

Biodiversity, Biotechnology and Bioengineering Research Group GRINBIO, Department of Engineering, University of Medellin, Medellín 050026, Colombia

• The Sogamoso River basin, a major tributary of the Magdalena River in Colombia, is influenced by agricultural, industrial, and energy-related activities that have promoted the accumulation of trace metals, posing a significant environmental risk. While the presence of these metals in soils and sediments has been documented, their dynamics in water and suspended particulate matter (SPM) are critical to understanding their transport and ecological impact. This study evaluated concentrations of Cd, Pb, and Hg in SPM and their relationship with partitioning mechanisms associated with organic carbon and nitrogen content. Water samples collected at 10 sites along the basin were filtered through 0.45 μm membranes. Cadmium and lead were determined by graphite furnace atomic absorption, while total mercury was measured following EPA Method 7473 using a RA-915LAB Direct Mercury Analyzer. Organic carbon and nitrogen data were incorporated to examine associations with trace metals in SPM. Concentrations ranged from 4.48–63.31 ng/mg SPM for Cd, 31.77–271.66 ng/mg SPM for Pb, and 0.06–0.74 ng/mg SPM for Hg. Results showed a common trend: initial low concentrations in the upper catchment, a rise in areas dominated by cattle ranching and fruit crops, followed by continuous decline. Positive correlations with organic carbon highlight that SPM with higher organic content serves as the main carrier of these contaminants. Findings suggest that trace metals in the Sogamoso River are predominantly bound to fine suspended fractions, favoring downstream transport to the Magdalena River and enhancing ecotoxicological risk.

3.35. Evaluation of Global Warming Potential in Living Wall System in Medellín Using Life Cicle Assessment

• Maria Alejandra Rico Pérez ¹, Alejandra Balaguera, Quintero ², Francesca Olivieri ¹ and Begoña Peceño Capilla ³

¹ 

Department of Construction and Technology in Architecture, Universidad Politécnica de Madrid. ETS Arquitectura, Avda. Juan de Herrera, 4, 28040 Madrid, Spain

² 

Facultad de Ingenierías. Universidad de Medellín, Carrera 87 N° 30–65, Medellín, Colombia

³ 

Facultad de Ciencias del Mar, Escuela de Prevención de Riesgos y Medioambiente, Universidad Católica del Norte, Larrondo 1281, Coquimbo 1780000, Chile

• Life Cycle Assessments (LCAs) have emerged as essential tools for identifying critical environmental aspects across the life cycle of products, processes, or services, thereby helping to reduce associated environmental impacts, compare alternative scenarios and implement strategies for enhanced sustainability. This methodology has been applied to Living Wall Systems (LWSs), which are conceived as sustainable systems designed to improve environmental conditions in the built environment. However, context-specific analyses are required for tropical countries, as well as system designs that can more effectively account for their entire life cycle. The aim of this study is to evaluate the Global Warming category of a LWS in the city of Medellín through life cycle modeling using SimaPro software (version 10.1.0.6). For the environmental inventory, the Ecoinvent^® v3.10 database was employed, covering materials, energy, transportation, and end-of-life processes, with a focus on the Global Warming Potential (GWP) impact category. The results show a total of 39.11 kg CO₂ eq for the entire system. Of this, the Construction stage accounted for 34.67 kg CO₂ eq, representing 89% of the total (GWP) impact category. This highlights the need for special attention during this stage, particularly regarding the polyethylene pipe for the irrigation system (21.79 kg CO₂ eq) and the reinforcing steel used in the support structure (11.84 kg CO₂ eq).

3.36. Evaluation of the Solvent Effects and Photovoltaic Performance of Chlorella vulgaris Chlorophyll as a Natural Sensitizer in Dye-Sensitized Solar Cells

• Vincent Adrian Bolibol ¹, Ilian Lee Flores ¹, Alexander Sayo Jr. ¹, Czarina Maeh Torrigoza ¹, Joseph Villaviray ¹, Rugi Vicente Rubi ^1,2 and Rich Jhon Paul Latiza ^1,2

¹ 

Chemical Engineering Department, College of Engineering, Adamson University, 900 San Marcelino St., Ermita, Manila 1000, Philippines

² 

Adamson University Laboratory of Biomass, Energy and Nanotechnology (ALBEN), Adamson University, 900 San Marcelino St., Ermita, Manila 1000, Philippines

• In response to the escalating global fuel crisis, this study investigates the potential of using chlorophyll from the microalga Chlorella vulgaris as a natural, abundant, and sustainable photosensitizer for Dye-Sensitized Solar Cells (DSSCs), aiming to provide an environmentally benign alternative to conventional ruthenium-based dyes. The study investigates chlorophyll extracted from the highly abundant microalga Chlorella vulgaris as a green, cost-effective alternative to the rare and expensive ruthenium-based dyes traditionally used. The study began with a rigorous comparison of extraction solvents, determining that acetone yields a significantly higher concentration of chlorophyll (28.76 µg/L) than methanol, establishing it as the superior medium for pigment harvesting. When this chlorophyll extract was integrated as a photosensitizer in a TiO₂-based solar cell, it achieved a power conversion efficiency of 0.0115%. While modest, this represents a more than 2000-fold performance increase over the dye-free control cell, unequivocally demonstrating the pigment’s photoelectric activity. However, the results reveal a critical limitation: the inherent molecular structure of chlorophyll, while perfected for photosynthesis, inhibits robust electronic binding to the TiO₂ semiconductor surface, leading to inefficient charge injection and low overall performance. This study provides a crucial insight for the field, concluding that while Chlorella vulgaris is an excellent and sustainable source, future success for chlorophyll-based DSSCs will depend on molecular engineering strategies to enhance the crucial dye–semiconductor interface.

3.37. Geochemical Charachteristics and Geological Significance of Rare Earth Element (REE) in Oil Shale of the Ama Fatma Coastal Site in Southwest Morocco

• Samira El Aouidi ¹, Nezha Mejjad ¹, Omar Ait Malek ², Abdelmourhit Laissaoui ¹, Moncef Benmansour ¹ and Said Fakhi ³

¹ 

Centre National de l’Energie, des Sciences et des Techniques Nucléaires, Rabat, Morocco

² 

Department of Geology, Faculty of Sciences Ben M’Sik, Hassan II University of Casablanca, Casablanca, Morocco

³ 

Department of Physic, Faculty of Sciences Ben M’Sik, Hassan II University of Casablanca, Casablanca, Morocco

• The Ama Fatma oil shale area, located in the Tarfaya-Boujdour basin of southwestern Morocco, was investigated to analyze the content and vertical distribution of rare earth elements (REEs) in shale samples collected from multiple depths. REE concentrations were precisely determined using inductively coupled plasma mass spectrometry (ICP-MS) to better understand their geochemical behavior and origin. The total rare earth element content (ΣREE) ranged from 18 to 50.49 ppm. Average REE concentrations exceeded chondrite values but remained lower than those of the North American Shale Composite (NASC) and the upper continental crust (UCC). Chondrite-normalized patterns showed clear enrichment in light rare earth elements (LREEs) with an average LaN/YbN ratio of 6.4. Negative europium (Eu) anomalies (0.53 < Eu/Eu* < 0.59) and negligible cerium (Ce) anomalies (0.8 < Ce/Ce* < 0.88) were also observed. REE concentrations displayed strong positive correlations with major elements, suggesting a predominantly terrestrial detrital origin. A sequential extraction procedure fractionated REEs into five distinct fractions: exchangeable (F1), carbonate (F2), iron and manganese oxides (F3), organic matter (F4), and residual (F5). The majority of REEs were associated with the iron and manganese oxides fraction (F3), indicating their affinity to these mineral phases. These findings provide insights into the geochemical characteristics and sources of REEs in the Ama Fatma oil shale.

3.38. Geometric Optimization and Advanced Material Integration for Enhanced Thermal Performance of Compact Cross-Flow Heat Exchangers in High-Temperature Applications

• Yusuf Kepir ¹, Holger Seidlitz ¹, Lars Ulke-Winter ¹ and Felix Kuke ^1,2

¹ 

Chair of Polymer-based Lightweight Design, Brandenburg University of Technology Cottbus–Senftenberg (BTU), Cottbus, Germany

² 

Research Division Polymeric Materials and Composites PYCO, Fraunhofer Institute for Applied Polymer Research IAP, Wildau, Germany

• Introduction: Heat exchangers used in high-temperature environments require lightweight designs with high thermal resistance and efficiency. This study numerically investigates the thermal performance of a multi-channel compact cross-flow heat exchanger, focusing on geometric configurations and material selection.
• Methods: Simulations were performed under steady-state conditions to reflect the operating conditions in typical micro gas turbine recuperators. The model featured a total mass flow rate of 0.01 kg/s, with hot air at 1223 K and cold air at 453 K. Five geometric configurations (baseline, conical flow diffuser, ramped ribs, semi-circular bumps, and turbulence promoters) and two materials (stainless steel and graphene-reinforced alumina ceramic composite) were compared.
• Results: The implementation of these designs resulted in a 30.8% increase in efficiency for steel heat exchangers and a 33.4% increase for ceramic composite heat exchangers. A material change from steel to ceramic in the baseline geometry yielded an 11.3% effectiveness increase. However, geometric enhancements proved more impactful, with effectiveness increasing exponentially for both materials from baseline to the most complex geometry. This highlights geometric optimization as the primary driver of performance gains. Additionally, the ceramic material’s 50% lighter weight offers advantages in weight-constrained applications.
• Conclusion: These findings confirm that significant performance improvements in compact heat exchangers are achievable through geometric optimization and advanced materials. Geometric augmentations substantially boosted thermal effectiveness, with gains predominantly linked to geometric optimization. This study suggests that optimized flow channels and integrated internal features, facilitated by additive manufacturing, will be crucial for future high-performance heat exchanger designs.

3.39. Impact of Aerosol–Cloud Interactions and SST Updates on the Simulation of the 31 May 2025 Convective Storm over Alexandria with WRF-Chem

• Nourhan Elshafeey
• Numerical Weather Prediction Department, Egyptian Meteorological Authority (EMA), Cairo, Egypt
• Extreme rainfall events in coastal cities such as Alexandria, Egypt, are challenging to forecast due to the combined influences of local convection, sea surface conditions, and aerosol interactions. The convective storm of 31 May 2025 caused intense rainfall over Alexandria, which was poorly predicted by most operational weather models.
• In this study, the WRF-Chem model was configured to investigate this event, focusing on the role of aerosols and dust in modifying cloud microphysics and precipitation. The model setup included the MOSAIC 4-bin aerosol scheme (chem_opt = 300), dust emissions (dust_opt = 1), and the Morrison two-moment microphysics scheme (mp_physics = 10). A sea surface temperature (SST) update was applied to better represent the evolving surface conditions over the Mediterranean. Sensitivity experiments were performed to assess the effects of aerosol–cloud interactions and aerosol–radiation feedback on convective development.
• The results indicate that WRF-Chem successfully reproduced the timing, location, and intensity of the observed rainfall, outperforming typical operational forecasts. Aerosols and desert dust increased cloud condensation nuclei (CCN), which enhanced cloud water content, delayed precipitation onset, and intensified convection. The SST update was also found to play a critical role in triggering and sustaining the convective cells over coastal regions.
• This study demonstrates that coupling aerosol chemistry with advanced microphysics and SST updates can significantly improve the predictability of extreme weather events in complex coastal environments.

3.40. Improved Retrieval and Forecast of Surface Air Quality Based on Source Analysis, Numerical Modeling and Hybrid Statistical Dynamic Model

• Hugo Wai Leung Mak
• Department of Mathematics, The Chinese University of Hong Kong (CUHK) & The Hong Kong University of Science and Technology (HKUST), Hong Kong, China
• Local air quality conditions depend on local and regional climatic conditions, source contribution, emission strength of individual pollutant precursors, and the trajectory of air masses, with effects being more conspicuous in urbanized areas with complex terrain pattern, thus induces a need to develop a reliable data-analytic model to capture the realistic associations between emission changes, meteorological conditions and surrounding chemistry processes of the investigated spatial region. Using available emission database, modeled meteorological outputs and raw pollutant attributes of Hong Kong, a new Hybrid Statistical-Dynamic Model was developed by taking advantages of both statistical and deterministic features, and was applied into retrieving historical pollution profile and forecasting next-day surface pollutant concentrations.
• By considering the contribution ratio of local to regional pollutant and emission sources, influence of background source and regional meteorological conditions, the categorization of outputs from a coupled regional meteorological and chemistry model was performed, and was adopted to parametrize the equations of a statistical Generalized Additive Model (GAM) within the framework. The established model was shown capable in retrieving temporal patterns of short-term PM_2.5, PM₁₀ and NO₂ concentrations in Hong Kong, but suffered from underestimation during pollution episodes. Thus, bias-adjustment techniques like Hybrid Forecast and Kalman Filter were applied into complementing such statistical deficiency with the aid of observational datasets, and the effectiveness of these techniques were validated by categorical assessments and common statistical metrics. The development of this hybrid model opens new windows in projecting scenario-based pollutant changes, and providing project-based opportunities for acquiring reasonable pollution forecasts.

3.41. Innovation and Optimization in Solar Energy: Generating Electricity with Reflective Silver Mirrors

• Helal Uddin, Mizanur Rahman Howlader, Mohammod Rasel and Abdur Rahim Hera
• Department of Mechanical Engineering, Hajee Mohammad Danesh Science & Technology University, Basherhat, Bangladesh
• Solar Energy is a potential renewable resource; creative methods can increase its efficiency. Using reflecting silver mirrors to maximize solar energy collection for electricity generation is one such strategy. Such reflective mirrors constitute the potential integration areas of CSP systems and PV panels to enhance the absorption of input light and the conversion of energy. Various CSP technology types include parabolic troughs, solar towers, and parabolic dishes, which all rely on mirrors to concentrate the sun’s rays on a receiver, producing heat that is used to generate power. Mirrors can also be placed around PV panels to reflect sunlight and result in more electricity. This work introduces high-reflectivity silver coatings, appropriate mirror angles, and hybrid CSPPV integration. Experiments have shown that strategically placed mirrors can increase energy efficiency by 20–30%, depending on the setting. This study found that reflecting surfaces considerably boost solar radiation absorption. Future research should concentrate on automatic mirror tracking, affordable materials, and durability enhancements to achieve the best possible outcomes. This study lays the groundwork for future advancements in solar energy, opening the door to new high-performing and environmentally friendly energy options.
• The integration of reflective silver mirrors in solar energy systems, particularly in hybrid CSP-PV configurations, presents a promising pathway to significantly enhance solar energy conversion efficiency. By strategically optimizing mirror materials, placement, and tracking, it is possible to unlock new levels of performance in renewable energy generation.

3.42. Microplastic and Nanoplastic Contamination in Coastal Sediments: Sources, Ecological Risks, and Mitigation Strategies

• Vidya Padmakumar and Murugan Shanthakumar
• Department of Ecology, EcoDiversity Research Centre, Hazelton, V0J1Y0, Canada
• Plastic pollution is a growing global concern, with microplastics (5 mm) and nanoplastics (1 μm) emerging as critical threats to coastal ecosystems due to their persistence, bioaccumulation potential, and capacity to adsorb toxic contaminants. This study investigates the prevalence, polymer composition, and particle size distribution of microplastics and nanoplastics in estuarine sediments within biodiversity-rich coastal zones. Sediment samples were collected seasonally from multiple sites representing varying degrees of anthropogenic influence, from pristine mangrove-fringed estuaries to heavily urbanised river mouths. Laboratory analysis employed density separation, enzymatic digestion, and Fourier Transform Infrared (FTIR) spectroscopy for microplastic identification. At the same time, dynamic light scattering (DLS) and scanning electron microscopy (SEM) were used to characterise nanoplastic fractions. Spatial mapping and statistical source apportionment were conducted to link contamination patterns with land-based activities, including industrial discharge, aquaculture, and urban runoff. An ecological risk index (ERI) was developed by integrating contaminant load, polymer toxicity profiles, and habitat sensitivity metrics. Results revealed that hotspots of plastic contamination coincided with high sediment organic content and reduced hydrodynamic flushing, suggesting localised retention zones. The proposed mitigation strategies—ranging from targeted sediment remediation to upstream waste reduction interventions—offer a practical framework for reducing plastic burdens in vulnerable coastal environments. The findings underscore the urgent need for integrated monitoring programs that account for both micro- and nano-scale plastic pollutants to inform ecosystem protection and policy development.

3.43. Modeling Flood Dynamics and Assessing Key Infrastructure Vulnerabilities in Marikina, Philippines, with FastFlood

• Matthew Dominic A. Nuqui ¹, Edgar A. Vallar ² and Jazzie Jao ³

¹ 

The Environment And RemoTe sensing researcH (EARTH) Group, Physics Department, De La Salle University (DLSU), Manila, Philippines

² 

Applied Research for Community, Health and Environment Resilience and Sustainability (ARCHERS), Center for Natural Sciences and Environmental Research (CENS), De La Salle University, Manila 1004, Philippines

³ 

Applied Research for Community, Health and Environment, Resilience and Sustainability (ARCHERS), Departmen of Physics, De La Salle University, Manila, Philippines

• Flooding represents 44% of all disasters worldwide, and it is one of the most predominant natural disasters in the Asia–Pacific region, with the Philippines being among the vulnerable countries due to the unique characteristics of the region that favor the formation of typhoons. Most notably, Typhoon Ondoy (Ketsana) in 2009, which affected Marikina City, left it flooded due to the river overflowing. This research employs FastFlood, an open-source, rapid flood simulation tool, to model flood dynamics in Marikina and assess the vulnerability of key infrastructures under different rainfall intensities over an extended period. Rainfall intensities of 18 mm/h, 56 mm/h, and 90 mm/h, reflective of Typhoon Ondoy, were used to simulate flood events that lasted over 1, 3, 6, and 12 h. Outputs from the FFS-tool were then exported to QGIS for visualization and flood risk analysis. The results indicate that moderate rainfall can result in flooding in low-lying areas, with flood levels up to 7.43 m under extreme scenarios. Infrastructure vulnerability increases with rainfall intensity, especially in areas along the Marikina River. Despite being in early development, FastFlood proves to be valuable for its rapid modeling capabilities and interactive flood hazard mapping features. However, current limitations, like the lack of calibration and reliance on default data, highlight the requirement for further validation using real-world flood events. (Initial thesis abstract before final thesis defense).

3.44. Modelling and Optimization of Biodiesel Production from Jatropha Oil: A Comprehensive Process Simulation and Economic Analysis

• Malon Muzemba, Denzel Christopher Makepa and Chido Hermes Chihobo
• Department of Fuels and Energy Engineering, Chinhoyi University of Technology, Private Bag 7724, Chinhoyi, Zimbabwe
• The increasing global demand for sustainable energy alternatives has positioned biodiesel as a promising renewable fuel source. This study presents a comprehensive modelling and optimization approach for biodiesel production from jatropha oil using advanced process simulation and statistical optimization techniques. The research employed Aspen Plus^® V11 for process modelling, incorporating transesterification, methanol recovery, water washing, and purification stages. Response Surface Methodology (RSM) with a Central Composite Design was utilized to optimize three critical process parameters: transesterification temperature (40–80 °C), water washing flow rate (40–60 kg/h), and reflux ratio (0.7–1.3). The Peng–Robinson–Boston–Mathias thermodynamic model was selected to accurately represent the multi-component hydrocarbon system behaviour. The optimized process achieved a biodiesel yield of 83.09% under optimal conditions of 63 °C transesterification temperature, 44 kg/hr water flow rate, and 1.1 reflux ratio. The simulation demonstrated that temperature significantly influences yield until an optimal point of 68 °C is reached, beyond which methanol evaporation reduces conversion efficiency. Economic analysis revealed a minimum fuel selling price (MFSP) of $0.62/kg. Life cycle assessment using OpenLCA 2.0 and the ReCiPe 2016 methodology indicated positive environmental benefits. This integrated approach successfully demonstrates the technical and economic viability of jatropha-based biodiesel production. The optimized process parameters provide practical guidelines for industrial-scale implementation, while the comprehensive economic evaluation confirms biodiesel’s competitiveness with fossil fuels. This study contributes to sustainable energy development by offering a systematic methodology for biodiesel process optimization that balances yield maximization with economic feasibility.

3.45. Modernizing Greece’s Flood Defenses: Learning from Past Disasters and Leveraging Advanced Hydrological Tools

• Angelos Alamanos
• Independent Researcher, 10243 Berlin, Germany
• Climate change is intensifying the hydrological cycle, leading to more frequent and severe flood events worldwide. In Greece, recent disasters have exposed the vulnerability of aging infrastructure: bridges, drainage networks, flood protection structures, and river buffer zones seem to fail repeatedly because they were designed to outdated rainfall patterns. To build resilience, flood protection design must be updated to reflect current and future climates, and factors that were previously ignored, must be incorporated into the respective regulations.
• This study presents examples of disasters that lead us to this suggestion, such as the Storm Girionis (2019), Cyclone Ianos (2020), Storm Daniel (2023). It analyzes causes of failures, and discusses an overlooked factor, the role of Intermittent River and Ephemeral Streams (IRES) in increased flash-flood risks, arguing that they must be properly mapped and integrated into flood protection planning.
• Moreover, to enhance the suggested redesign of critical infrastructure, this work presents a novel Python-based tool that automates the generation of design storm hyetographs from watershed shapefiles using Greece’s official gridded intensity-duration-frequency (IDF) parameters (Ministry of Environment, 2023). For a chosen storm duration, return period, and time interval, it computes ready-to-use hyetographs. Its application is demonstrated at the national scale (10,773 sub-catchments).
• By rapidly producing site-specific design storms compatible with national standards, Catchment2Storm empowers engineers and planners to redesign flood protection works, bridges, culverts, drainage systems, and buffer zones, based on up-to-date climate data. Integrating holistic mapping and updated storm profiles to routine practice, can transform reactive repair approaches to proactive resilience.

3.46. Novel Multilevel Inverter Circuit with Solar-Thermal Energy Conversion for Low-Power Applications

• Mohamed Raffi Sheik Alaudeen ¹, Vijayaraja Loganathan ¹, Dhanasekar Ravikumar ¹, Abinandhan J ¹ and Rupa Kesavan ²

¹ 

Department of Electrical and Electronics Engineering (DEEE), Sri Sairam Institute of Technology, Chennai 600044, Tamilnadu, India

² 

Department of Computer Science and Engineering, Sri Venkateswara College of Engineering, Sriperumbadur 602117, Tamilnadu, India

• Harnessing renewable energy offers the most promising path toward sustainable power generation and advancing to a low-carbon future. The importance of harvesting sustainable energy emerged in the late 19th century and has steadily evolved into a global priority today. In this context China stands at the forefront as the world’s leading powerhouse in renewable energy production, while Bahrain remains the smallest contributor. This highlights the urgent need for sustainable power. Therefore, stronger energy policies need to be adopted for promoting and encouraging clean energy production across the globe. Also incremental innovations are essential to support low-power devices. One such advancement is proposed in this paper, where the solar energy is harvested by a thermoelectric generator (TEG), which converts heat into a stable DC voltage. Further, the stable DC voltage is fed to a novel topology of multilevel inverter to produce AC voltage across the load with minimum harmonic presence. The design is carried out in a way that the inverter setup looks compact with low cost, enabling efficiency for low-voltage AC applications. In continuation with this, the design is modeled in MATLAB, and the performance of the TEG with inverter is studied for resistive and impedance loads. From the study, it is found that the TEG with inverter performs better, and it is suitable for applications that need minimum voltages.

3.47. Optimized Climate-Resilient Desalination for Algeria’s 2030 Water Strategy

• Kaouthar Djehaf and Mohammed A. Djehaf
• Chemistry Department, LPCMA Laboratory, Faculty of Chemistry, University of Sidi Bel Abbes, Sidi Bel Abbes 22000, Algeria
• Intensifying climate change, characterized by aridification and diminishing freshwater reserves, necessitates sustainable desalination to achieve Algeria’s 2030 Water Strategy goal of 2.1 billion m³/year. Conventional seawater reverse osmosis (SWRO), with energy demands of 3–4 kWh/m³ and brine discharge of 1–1.5 times product water, poses sustainability challenges. This study introduces a novel framework integrating renewable energy, artificial intelligence (AI), and circular economy principles to enhance water security. The framework combines solar-powered SWRO, AI-driven optimization using Artificial Neural Networks and Genetic Algorithms, MCDM for site selection, and brine valorization for lithium and magnesium recovery. Solar photovoltaic systems leverage Algeria’s high solar irradiance (>5 kWh/m²/day), while AI optimizes operational efficiency. MCDM balances energy, environmental, and public health criteria, and brine valorization targets economic sustainability. Solar-powered SWRO reduces greenhouse gas emissions by 85–95% compared to fossil fuel-based systems and 70–80% versus thermal desalination. AI optimization lowers costs by 15–35%, and brine valorization offsets 10–20% of expenses, potentially yielding $50–100 million annually. The framework projects a CO₂ reduction of 2.1 million tons/year by 2030, aligning with SDGs 6, 7, 9, and 13. This framework transforms desalination into a sustainable, circular economy-driven solution, offering a replicable model for arid coastal regions globally. Strategic site selection and smart grid integration minimize ecological and health risks, ensuring climate-resilient water security.

3.48. Paracetamol Toxicity by Phytotesting with Lepidium sativum

• Nataliia Tkachuk ¹ and Liubov Zelena ²

¹ 

Department of Biology, Faculty of Mathematics and Natural Sciences, T.H. Shevchenko National University “Chernihiv Colehium”, 14013 Chernihiv, Ukraine

² 

Department of Virus Reproduction, Zabolotny Institute Microbiology and Virology, NAS of Ukraine, 03680 Kyiv, Ukraine

• Environmental pollution has been exacerbated by widely used pharmaceuticals, in particular, paracetamol. At the same time, studies on the ecotoxicity of paracetamol in vascular plants are limited. In biotesting of toxicants, Lepidium sativum L. is used as a sensitive test plant. The aim of this study was to study the toxic properties of aqueous solutions of paracetamol in a growth test with L. sativum. The methodology consisted of an experimental study of germination energy, seed germination, and biometric–morphometric indicators of L. sativum seedlings in a growth test lasting 5 days under the influence of aqueous solutions with a paracetamol content of 0.002% to 0.2% and the calculation of phytotoxic indices. Statistical data processing was used. It was found that a solution of paracetamol at a concentration of 0.002% (which is higher than that observed for wastewater—0.7 × 10⁻⁸–0.246 × 10⁻⁴%) does not significantly change the test indicators of L. sativum. It is shown that the toxic properties of this compound for L. sativum differ from previously studied test plants and confirm the species specificity in sensitivity to the toxic effects of paracetamol. However, a comparison of the results of bioassays from different publications should be treated with caution, and it is important to carry them out in cases where the same time of treatment with the toxicant is used. Further studies should focus on assessing the toxicity of paracetamol solutions with concentrations recorded for wastewater, in particular, using other plant species, e.g., Allium cepa L.

3.49. Precipitation and Temperature Projections over Greece Using CMIP6 Model Simulations Under Different SSP Scenarios

• Ioannis Logothetis ^1,2, Kleareti Tourpali ¹ and Dimitrios Melas ¹

¹ 

Laboratory of Atmospheric Physics, Department of Physics, Faculty of Sciences, Aristotle University of Thessaloniki, GR 54124 Thessaloniki, Greece

² 

Centre for Research and Technology Hellas, Chemical Process and Energy Resources Institute, Thermi, GR 57001 Thessaloniki, Greece

• This study examines the precipitation and temperature evolution over Greece covering the historical period and 21st century (the years from 1850 to 2100). Timeseries from multi-model mean precipitation and temperature, averaged over continental Greece, are calculated from twelve (12) CMIP6 (6th Phase of Coupled Model Intercomparison Project) model simulations to study future changes under different Shared Socioeconomic Pathways (namely: SSP1-2.6, SSP3-7.0, SSP2-4.5 and SSP5-8.5, respectively). The analysis focuses on the investigation of projected precipitation changes both for annual and seasonal temporal scales. Results indicate a reduction in annual precipitation over continental Greece. The maximum changes are shown under SSP3-7.0 and SSP5-8.5 scenarios. Annual precipitation is projected to decrease about 20% by the end of 21st century (relative to the historical period that covers the years from 1980 to 2005; basis period). Spring and autumn shows a reduction of precipitation that rangers between 15 and 30% for SSP3-7.0 and SSP5-8.5. Additionally, for JJA—the dryer season in Greece—a decrease of about 0.1 to 0.2 mm/day (about 30 to 40% relative to the basis period) is projected under SSP3-7.0 and SSP5-8.5 scenarios too. Regarding temperature, the CMIP6 multi-model mean indicates a substantial warming mainly during the last period of 21st century. In particular, temperature over continental Greece is projected to increase about 4.0 and 6.0 °C by the end of 21st century under SSP3-7.0 and SSP5-8.5 scenarios, respectively.

3.50. Predictive Modelling of Ionospheric Total Electron Content over the Philippines Using Machine Learning Methods

• Vincent Louie Maglambayan ¹, Jazzie Jao ^1,2 and Edgar Vallar ¹

¹ 

Department of Physics, De La Salle University Manila, Manila 1004, Philippines

² 

Department of Software Technology, De La Salle University Manila, Manila 1004, Philippines

• With the growing integration of machine learning techniques into geophysical research, their application to ionospheric modeling specifically in predicting Total Electron Content (TEC) using GNSS data, has gained significant traction. While various studies have explored this approach across different global regions, the Philippine sector remains largely unexamined despite its scientific relevance. Situated in the low-latitude ionospheric region, the Philippines experiences complex phenomena such as the Equatorial Ionization Anomaly, making it an ideal candidate for focused TEC modeling. This study presents a machine learning-based approach to predict regional ionospheric TEC using GNSS data from the PIMO receiver station (14.6° N, 121.1° E), covering the period from 2010 to 2020. Three ML algorithms—Random Forest, Support Vector Machines, and Gradient Boosting—are used to develop predictive models using features such as temporal parameters and space weather indices: average interplanetary magnetic field magnitude, Bz-component, solar wind proton density, plasma speed, flow pressure, Kp-index, Dst-index, F10.7 solar flux, AE-index, and the Lyman-alpha index. Model performance are evaluated and compared across the three algorithms, with further analysis conducted on feature importance and dimensionality reduction using Principal Component Analysis. Preliminary expectations suggest that all models will yield predictions closely aligned with observed TEC values, with the F10.7 solar flux and Lyman-alpha indices emerging as the most influential predictors. This work lays the foundation for more comprehensive TEC modeling in the Philippine region by enabling future expansion to include data from additional local GNSS stations, ultimately enhancing the spatial resolution and robustness of regional ionospheric models.

3.51. Scaling and Environmental Analysis of a Heterogeneous Photocatalytic Rotary Photoreactor for Cyanide Treatment

• Jorge L. Gallego ¹, Omar Tirado-Munoz ², Fernando Aricapa-Palacio ³, Alejandra Balaguera-Quintero. ⁴, Alejandro Silva-Cortés ⁵ and Irina Patricia Tirado-Ballestas ⁶

¹ 

Biodiversity, Biotechnology and Bioengineering Research Group GRINBIO, Department of Engineering, University of Medellin, Medellín 050026, Colombia

² 

Technological University of Bolivar, Carlos Vélez Pombo Industrial and Technological Park, Cartagena 130010, Colombia

³ 

GISAH Research Group, Environmental Engineering Program, Universidad Tecnológica de Bolívar Campus Tecnológico km 1 vía Turbaco Cartagena, Cartagena de Indias, Colombia

⁴ 

Department of Engineering, University of Medellin, Medellín 050026, Colombia

⁵ 

Department of Management Sciences, Instituto Tecnológico Metropolitano, Medellín 050034, Colombia

⁶ 

Grupo de Investigación GENOMA, Facultad de Medicina, Universidad del Sinu, Cartagena de Indias 130014, Colombia

• Cyanide contamination from mining and industrial activities represents a severe environmental hazard due to its acute toxicity and persistence in aquatic ecosystems. Effective removal technologies are urgently required to safeguard water resources and ecological health. This study addresses this challenge by evaluating the scale-up of a TiO₂-based rotary concentrator photoreactor (RCPR) specifically engineered for the photocatalytic degradation of cyanide in contaminated water. Building on a previously developed pilot-scale reactor, the system was assessed through integrated modeling and simulation approaches to enhance design efficiency. The methodology combined geometric sizing, a one-dimensional thermal energy balance, and optical simulations conducted in SolTRACE 3.0, under site-specific environmental conditions from the Colombian Caribbean. Results demonstrated that geometric configuration, optical concentration, and material selection exerted a strong influence on reactor performance. Cyanide removal efficiency was confirmed experimentally and validated by acute toxicity bioassays using Daphnia magna, which provided ecotoxicological evidence of treatment effectiveness. Degradation kinetics closely matched mathematical predictions, underscoring the robustness of the model. In addition, scenario analyses explored alternative reactor geometries and construction materials to support real-scale deployment. Environmental efficiency indicators and cost–benefit analyses further highlighted the feasibility of this technology for mining wastewater treatment. These findings deliver technical, ecological, and economic insights that advance photocatalytic processes toward sustainable and scalable water treatment solutions.

3.52. Scenario-Based Flood Susceptibility Mapping Using Machine Learning: A Case in Manila City, Philippines

• Miko Santos ¹, Candice Aura Fernandez ¹, Charlize Kirsten Brodeth ¹, Alliyah Gaberielle Zulueta ¹, Jazzie Rosales Jao ¹ and Edgar Vallar ²

¹ 

Department of Software Technology, College of Computer Studies, De La Salle University, Manila, Philippines

² 

Department of Physics, College of Science, De La Salle University, Manila, Philippines

• Manila City experiences recurrent flooding driven by its low-lying topography, high population density, and rapid urbanization. Traditional hydrodynamic models, while accurate, are computationally expensive and unsuitable for rapid scenario evaluation. This study proposes a structured, scenario-based flood susceptibility mapping framework using supervised machine learning trained on synthetic hydrodynamic simulations to address these limitations. Synthetic rainfall hyetographs each representing rainfall intensities at 5-min intervals over a 2-h duration were used to simulate flood events through two-dimensional unsteady flow modeling in HEC-RAS. The resulting maximum flood extent maps serve as ground truth data for model training. Input features consist of digital elevation model (DEM), soil type, land use, and the rainfall hyetograph vector, all preprocessed into spatially aligned raster datasets. Machine learning classifiers including Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) were trained to identify flooded areas at the pixel level and feature vectors were constructed by combining spatial characteristics with rainfall inputs. The trained models accept new input conditions comprising DEM, soil type, land use, and a defined rainfall hyetograph and produce a corresponding maximum flood susceptibility map. This capability enables flood susceptibility predictions for a wide range of hypothetical rainfall events without the need to rerun simulations wherein resulting maps can inform land-use planning, infrastructure design, evacuation planning, and disaster risk management in flood-prone urban environments such as Manila City.

3.53. Smart Mining, Safer Mines: Strategic Benefits of Technology Uptake in Deep-Level Hard-Rock Operations

• Olusegun Aanuoluwapo Oguntona ¹, Simphiwe Shangase ² and Clinton Aigbavboa ³

¹ 

Department of Built Environment, Faculty of Engineering, Built Environment and Information Technology, Walter Sisulu University, East London 5200, South Africa

² 

Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa

³ 

cidb Centre of Excellence, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg, South Africa

• The hard-rock mining industry faces persistent challenges of deep-level extraction, volatile commodity markets, and rising expectations for worker safety and environmental stewardship. These pressures have accelerated interest in “smart mining”, which entails the integration of emerging technologies (ETs) such as advanced sensing, autonomous equipment, robotics, artificial intelligence, digital twins, wearable technologies and real-time analytics. These technologies are designed to transform and revolutionise the conventional method of locating, mining and processing ore bodies. This paper critically examines the strategic benefits of technology uptake in deep-level hard-rock operations, demonstrating how smart mining enhances safety, productivity, and sustainability while strengthening long-term competitiveness. The study employed a structured, closed-ended questionnaire survey administered to highly experienced mining professionals in the South African hard-rock mining sector. The retrieved data were subjected to descriptive analysis. Findings revealed that reduced human exposure to hazardous environments, safety promotion, improved productivity, enhanced robust data analysis, easy data transfer, and optimised scheduling processes are the top benefits of adopting ETs. Therefore, the transition to smart mining presents a compelling strategy for deep-level hard-rock operations seeking to balance productivity imperatives with worker welfare and environmental responsibility. Hence, the South African experience underscores the broader global potential of emerging mining technologies to deliver safer workplaces, enhanced resource efficiency, and sustainable growth for the sector.

3.54. Solar-Powered IoT Chambers for Sustainable Mushroom Cultivation: An Energy and Environmental Impact Assessment in Rural Uttar Pradesh

• Shefali Vinod Ramteke
• Department of Applied Sciences, Indian Institute of Information Technology Allahabad, Prayagraj 211015, India
• Access to reliable and affordable energy is a key barrier limiting the adoption of controlled-environment farming in rural regions. This study evaluates the performance of Mushroom Kothi, a low-cost IoT-enabled cultivation chamber, when powered by solar photovoltaic panels, and quantifies its environmental benefits through energy use analysis and life cycle assessment (LCA). Experiments were carried out in Saeedpur Khas village, Prayagraj (Uttar Pradesh), where the device was operated under two scenarios: (i) conventional grid electricity supply and (ii) off-grid solar panels with battery backup. Power consumption was continuously monitored across full mushroom crop cycles, and energy savings were estimated against regional grid electricity baselines. In addition, a streamlined LCA was performed using the AWARE method to assess water stress implications and broader sustainability impacts. Results showed that the device consumed less than 100 W peak, and a 150 W solar panel with a small battery was sufficient to power chamber operations throughout the cultivation cycle. Solar integration reduced grid dependency by over 85%, resulting in significant cost savings and estimated CO₂ emission reductions of 0.35–0.45 kg per kg of mushrooms produced. The AWARE analysis further indicated lower water stress impacts compared with conventional open-shed cultivation due to improved microclimate regulation. These findings demonstrate that solar-powered controlled chambers can provide an energy-efficient, climate-resilient, and environmentally sustainable solution for smallholder mushroom farming. The approach holds particular relevance for the Global South, where energy insecurity and resource constraints are major challenges to scaling sustainable agriculture.

3.55. Sustainable Water Quality Monitoring: A Comparative Study Between Automated and Manual Collection in the Amazon

• Thiago Almeida Teixeira, Israel Gondres Torné and André Luiz Printes
• PPGEEL—Graduate Program in Electrical Engineering, UEA—State University of Amazonas, Manaus 69050-020, Brazil
• Environmental quality indicators are essential tools for translating complex technical data into accessible information, facilitating communication between academia, the public, and policymakers. Among these indicators, water quality plays a crucial role in public health and environmental preservation, particularly in ecologically sensitive regions such as the Amazon. This study presents a comparative analysis of water monitoring methods in the city of Parintins, Amazonas, Brazil, contrasting an automated data collection device with embedded sensors and traditional manual sampling using pre-calibrated commercial probes. Prior to this initiative, monitoring in the region relied exclusively on manual measurements performed by local researchers, limiting both the frequency and scope of analysis. The proposed prototype was deployed on a floating platform at the Port of Parintins and operated using LoRa-based data transmission to ensure functionality in areas with limited connectivity. The monitored parameters included pH, turbidity, electrical conductivity, water temperature, and dissolved oxygen. Data collected automatically were compared with those obtained from manual probes to assess the precision, stability, and feasibility of the automated system. Our results revealed a strong correlation between both methods, with the automated approach demonstrating superior consistency and frequency of measurements. The findings support the use of the proposed system as an efficient, low-cost, and reliable alternative for continuous water quality monitoring in remote regions of the Amazon, contributing to sustainable environmental management and informed decision-making.

3.56. Thermogravimetric and Proximate Characterization of Camellia japonica Flower Biomass: Assessing the Potential of Ornamental Residues for Energy Recovery

• Antía G. Pereira ^1,2, Ezgi Nur Yuksek ³, Franklin Chamorro ¹, Pauline Donn ¹, Sepidar Seyyedi Mansour ¹ and M.A. Prieto ¹

¹ 

Instituto de Agroecoloxía e Alimentación (IAA), Universidade de Vigo, Nutrition and Food Group (NuFoG), Campus Auga, 32004 Ourense, Spain

² 

Investigaciones Agroalimentarias Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, 36213 Vigo, Spain

³ 

Instituto de Agroecological e Alimentación (IAA)—CITEXVI, Department of Analytical Chemistry and Food Science, Universidade de Vigo, Nutrition and Food Group (NuFoG), 36310 Vigo, Spain

• The growing demand for renewable energy and resource-efficient waste management has intensified interest in alternative lignocellulosic feedstocks. This study investigates the thermal decomposition behavior and proximate composition of eight cultivars of Camellia japonica flowers, a widely cultivated but underutilized ornamental species. Thermogravimetric analysis was employed to assess weight loss dynamics under controlled heating, while derivative thermogravimetry and heat flow data provided further insights into decomposition stages and energy release patterns. All samples exhibited a characteristic three-step degradation: (i) initial moisture loss below 120 °C, (ii) an active devolatilization stage between 200 and 400 °C associated with hemicellulose and cellulose breakdown, and (iii) a final slow degradation phase above 450 °C, typically attributed to lignin decomposition and char formation. Among the cultivars studied, Carolyn Tuttle and Conde de la Torre showed the highest volatile matter contents (97.34–97.26%), indicating strong potential for pyrolysis-based valorization. Conversely, Elegans Variegated exhibited the highest apparent fixed carbon retention (−0.15%), with a slightly lower volatile fraction (96.59%). Ash content was consistently low. The average volatile matter content across all samples exceeded 96%, confirming the high organic fraction that is typical of floral biomass. Fixed carbon values remained within a narrow range (−0.01% to −0.15%), suggesting minimal residual char formation and indicating suitability for fast pyrolysis or combustion with limited solid waste output. These findings highlight Camellia japonica flowers as a promising biomass resource with favorable thermochemical properties. Their high volatility, low ash contents, and consistent thermal profiles support their inclusion in circular bioeconomy models and localized bioenergy strategies, particularly in regions with substantial ornamental plant waste.

3.57. Towards Sustainable Separations: Integration of Heat Recovery and Heat Pump Technologies in Pressure Swing Distillation

• Jonathan Wavomba Mtogo, Gladys Wanyaga Mugo, Bevin Nabai Kundu and Emmanuel Karimere Kariuki
• Chemical Engineering and Allied Processes Research Centre, Kenya Industrial Research and Development Institute. P.O. Box 30650-00100 Nairobi, Kenya
• Introduction: Distillation remains the powerhouse of separation processes in the chemical industry, yet its high energy demand presents economic and environmental challenges, especially when dealing with azeotropic mixtures. This study explores process intensification strategies—namely thermal coupling and heat pump techniques—to enhance energy efficiency in pressure swing distillation (PSD) of THF/water and acetone/chloroform azeotropes.
• Methods: Four configurations were evaluated: conventional PSD (CPSD), partial heat-integrated PSD (PHIPSD), full heat-integrated PSD (FHIPSD), and heat pump-assisted PSD (HPAPSD). Process design followed a structured four-step approach based on total annual cost (TAC), total energy consumption (TEC), CO₂ emissions, and second law efficiency. PHIPSD and FHIPSD utilized heat recovery between high-pressure and low-pressure columns, reducing steam and cooling utility demands. HPAPSD incorporated vapour recompression.
• Results: In the tetrahydrofuran/water system, TAC, TEC, and CO₂ emissions were reduced by up to 50%, 60%, and 83%, respectively, with thermodynamic efficiency reaching 24%. For acetone/chloroform, reductions of up to 71% in TAC, 87% in CO₂ emissions, and efficiencies of 18% were observed. While HPAPSD involved higher capital investment due to compressor systems, it achieved the greatest energy savings and environmental benefits, significantly reducing CO₂ emissions and exergy loss. Thermodynamic efficiency confirmed the HPAPSD’s superior performance across both azeotropic systems.
• Conclusions: This study illustrates the potential of electrically driven, integrated distillation schemes in minimizing operational costs and environmental emissions. Findings show the need for the broader application of HPAPSD in azeotropic separations, aligning with global sustainability goals and the transition toward renewable energy sources.

3.58. Treatment Performance of Agro-Industrial Biochar Adsorption for Arsenic-Polluted Potable Water

• Pelin Soyertaş Yapicioğlu, Muhammed Nur Elabdallah and Mehmet Irfan Yeşilnacar
• Department of Environmental Engineering, Engineering Faculty, Harran University, Sanliurfa, Turkey
• According to the water resource protection plans published by the European Union (EU), groundwater needs to be protected and sanitized. Groundwater may contain heavy metals in terms of its geological and physicochemical content. These heavy metals can accumulate in the body in the long term and cause significant health problems. One of these heavy metals is arsenic, which is a toxic element that is harmful to human health. Low-cost, porous structure, larger surface area, functional groups, and carbon negative texture have made agro-industrial biochar an effective adsorbent for removing arsenic (As) from groundwater. In order to determine the effect of irrigation on arsenic concentration, samples were taken from the Yaygılı groundwater source in Harran Plain, where arsenic concentration was previously determined, in the pre-irrigation (March) and post-irrigation (October) periods. This study demonstrated that use of malt dust-derived biochar has dual benefits as an arsenic adsorbent and also waste minimization technique in terms of a circular economy approach. On average, an efficiency rate of 98.39% for arsenic removal from potable water has been reported using malt dust-derived biochar in the post-irrigation period. A potable water quality index (PWQI) was developed based on treatment performance and water quality parameters obtained via Monte Carlo simulation. The potable water quality index was in the range of 97.3–99.1% in terms of water remediation by agro-industrial biochar adsorption for arsenic-polluted groundwater. Also, biochar is recyclable and regenerative material. The waste biochar could be regenerated after arsenic adsorption in terms of zero-waste management and circular economy policies.

3.59. Urban Land Use Influences on Platinum Group Element (PGE) Distribution in Alcalá de Henares

• Antonio Peña-Fernández ¹, Manuel Higueras ² and Carmen Lobo Bedmar ³

¹ 

Department of Surgery, Medical and Social Sciences, Faculty of Medicine and Health Sciences, University of Alcalá, Ctra. Madrid-Barcelona, Km. 33.600, 28871 Alcalá de Henares, Madrid, Spain

² 

Scientific Computation & Technological Innovation Center (SCoTIC), Universidad de La Rioja, Logroño, Spain

³ 

Departamento de Investigación Agroambiental. IMIDRA. Finca el Encín, Crta. Madrid-Barcelona Km, 38.2, 28800 Alcalá de Henares, Madrid, Spain

• Introduction: Platinum group elements (PGEs), including platinum (Pt), rhodium (Rh), and palladium (Pd), are increasingly detected in urban soils, largely due to vehicular emissions and industrial activities. Understanding how land use influences their spatial distribution is essential for exposure risk assessment and urban planning.
• Methods: A total of 137 surface soil samples were collected from urban parks (n = 97), gardens (n = 18), and industrial zones (n = 22) in Alcalá de Henares, Spain. Samples were digested using microwave-assisted acid protocols and analysed by ICP-MS. Data were statistically evaluated by Kruskal–Wallis tests and post hoc pairwise comparisons to assess inter-group differences.
• Results: Pt and Rh concentrations were significantly higher in industrial soils compared to urban parks and gardens (p < 0.05), while Pd showed no significant difference across land use categories. These patterns likely reflect the proximity of industrial zones to point sources and suggest higher vehicular density in adjacent areas. Enrichment factor (EF) analysis indicated moderate to significant anthropogenic input for Pt and Rh, with industrial areas exhibiting the highest EF values for both elements.
• Conclusions: Land use type plays a key role in PGE distribution. Industrial zones act as hotspots for Pt and Rh accumulation, emphasising the need for targeted environmental monitoring and potential remediation strategies. Future studies should explore temporal changes and linkages with human biomonitoring data to assess health implications.

3.60. Use of Microbial Carriers in Anaerobic Digestion: Scientific and Research Aspects

• Agnieszka Anna Pilarska
• Department of Hydraulic Engineering and Safety, Poznań University of Life Sciences, Poznań, Poland
• The use of microbial carriers in anaerobic digestion (AD) has been recognised as a scientifically validated method to enhance microbial activity, process efficiency, and biogas production. Research focuses on natural and modified materials that support microbial colonisation, enzymatic activity, and process stability under varied conditions.
• A promising approach is the silica/lignin system, combining the large surface area and inert nature of silica with the biochemically active components of lignin. This composite stimulates dehydrogenase activity and promotes microbial proliferation, increasing methane production during mesophilic digestion of sewage sludge.
• Another effective carrier is the diatomaceous earth/peat (DEP) composite. Its porous structure and sorptive properties create favourable conditions for microbial consortia development, especially during digestion of food waste. DEP use results in enhanced enzymatic activity and stabilised process kinetics, even under fluctuating organic loads.
• The chitosan/perlite (Ch/P) system offers a unique combination of biological functionality and structural support. Chitosan modulates microbial interactions and may reduce inhibitory effects, while perlite provides mechanical durability. This carrier improves substrate conversion efficiency and microbial retention.
• Notably, next-generation sequencing (NGS) has played a crucial role in characterising microbial communities associated with these carriers. NGS revealed shifts in the abundance of key methanogenic and fermentative taxa, confirming the carriers’ influence on microbiome structure and function.
• These findings highlight the importance of selecting appropriate microbial carriers to optimise AD processes. Continued research into such materials represents a vital step towards sustainable waste management and renewable energy production.

4. Food Science and Technology

4.1. Challenges Associated with the Composition and Nutritional Value of Oatmeal Products

• Dragica Đurđević-Milošević ¹ and Gordana Jovanović ²

¹ 

Quality Manager, Institute of Chemistry, Technology and Microbiology, Belgrade, Serbia

² 

Academy of Professional Study Šabac, Šabac, Serbia

• Oatmeal is widely recognised for its health benefits and is often used in breakfast cereals due to its favourable nutritional profile and naturally gluten-free nature. Quick-to-prepare cereals with a variety of flavours are particularly popular among consumers. Instant oatmeal is often enriched with ingredients, such as freeze-dried raspberries, apple, chocolate, coconut, etc., that enhance taste and palatability. Nutritional labelling can reveal unexpectedly high sugar content and, in some cases, the presence of gluten. This study compared the declared nutritional values of oatmeal (10 packs) with those of instant oatmeal (65 packs) available in Belgrade, Serbia, in July 2025. Sugar content was significantly higher in instant cereals (median 16 g/100 g) than in oatmeal (median 0.85 g/100 g). Protein content was higher in oatmeal (median 14 g/100 g) than in oatmeal products (median 11 g/100 g). The quantities of total fat (median 7.8 g/100 g vs. 6.85 g/100 g) and saturated fatty acids (median 2.1 g/100 g vs. 1.0 g/100 g) were slightly higher in instant cereals. Carbohydrate content was slightly lower in oatmeal (median 56 g/100 g) than in oatmeal products (median 63 g/100 g), and energy values followed the same trend (median 1624 kJ/100 g versus 1534.5 kJ/100 g). Despite oats being the main ingredient in both products, the addition of different ingredients significantly affects the nutritional profile and consumer perception of instant cereals compared to plain oatmeal. These findings are relevant both for consumers, who are concerned about the sugar content of flour, and for manufacturers developing instant oatmeal formulations.

4.2. Comparative Evaluation of Flavonoids and Water-Soluble Vitamins in Solar- and Open-Air-Dried Plantago major L. Leaves for Functional Food Applications

• Komil Usmanov ¹ and Shakhnoza Sultanova ²

¹ 

Department of Automation and Digital Control, Tashkent Institute of Chemical Technology, Tashkent 100011, Uzbekistan

² 

Department of Food, Tashkent State Technical University, Tashkent 100011, Uzbekistan

• This study investigates the impact of two drying methods—solar cabinet drying and open-air sun drying—on the retention of water-soluble vitamins (C, B₂, B₃, B₆, B₉) and flavonoids in Plantago major L. leaves. The goal is to determine which method ensures better preservation of nutraceuticals for functional food applications. Fresh Plantago leaves were divided and dried under two conditions: a solar cabinet dryer and natural open-air conditions. Both external and internal leaf zones were analyzed separately using HPLC-DAD at wavelengths of 250, 254, and 276 nm to quantify vitamin and flavonoid content. The solar dryer significantly outperformed open-air drying in preserving bioactive compounds. External tissues from solar-dried samples retained the highest level of vitamin C (971.9 mAU·s), while vitamin B₆ was best preserved in solar-dried internal tissues (512.4 mAU·s). Flavonoids such as rutin and degidrokvertsetin showed more pronounced peaks in solar-dried leaves, with degidrokvertsetin reaching 631.5 mAU·s—far higher than open-air equivalents (~437.7 mAU·s). The controlled temperature and enclosed design of the solar dryer minimized oxidative and photochemical losses compared to unregulated open-air drying. Solar cabinet drying is a superior method for retaining heat-sensitive vitamins and antioxidant flavonoids in Plantago major leaves. Its controlled microclimate leads to better quality and stability of nutraceuticals, making it more suitable for producing functional food ingredients than traditional open-air drying.

4.3. Injera Baking Stove (Mitad) Type Determines Injera Quality

• Workineh Abebe Zeleke and Oli Legessa
• Bishoftu Agricultural Research Center, Ethiopian Institute of Agricultural Research, Addis Ababa P.O. Box 2003, Ethiopia
• Injera is the national staple of Ethiopians, mainly prepared from tef grain and other cereals or their blends. Injera quality is known to vary from process to process, depending on factors like the cereal type and other ingredients used, and baking techniques. This study evaluated the texture, sensory attributes, and shelf stability (at 25 °C, 60% storage relative humidity) of injera baked using three types of injera baking stoves: biomass-fired Lakech (LS), common electric (CES), and pizza-baking-type (PBTS) stoves. PBTS exhibited the fastest reheating rate (0.22 °C/s) but produced injera with higher moisture (7.13% d.b.), lower sensory scores, accelerated texture degradation, and the shortest shelf life (56 h). LS-baked injera had superior sensory acceptance (4.9/5). slower firming and longer shelf life (80 h), while CES injera showed relatively closer performance in most parameters to LS. The findings highlight the critical role of injera baking stoves, indicating the superior performance of LS despite its energy inefficiency and inconvenience, and the need to optimize heating rate and distribution, together with moisture management in the electric-powered stoves, mainly in the PBTS.

4.4. Undaria Pinnatifida as a Biofuel Feedstock: Challenges and Opportunities

• P. Barciela ¹, A. Silva ^1,2, A. Perez-Vazquez ¹, M. Carpena ¹, F. Chamorro ¹, M. F. Barroso ² and M.A. Prieto ¹

¹ 

Instituto de Agroecoloxía e Alimentación (IAA), Universidade de Vigo, Nutrition and Food Group (NuFoG), Campus Auga, 32004 Ourense, Spain

² 

REQUIMTE/LAQV, Instituto Superior de Engenharia do Porto, Instituto Politécnico do Porto, Rua Dr António Bernardino de Almeida 431, 4200-072 Porto, Portugal

• Undaria pinnatifida, popularly known as wakame, is a brown kelp that thrives in cold water. Given its nutrient-rich composition and bioactives, it has extensive application prospects in various industries, e.g., food, cosmetics, animal feed, and bioremediation. One emerging use is biofuel production. In this connection, research on economically and technically viable approaches to successfully commercializing third-generation renewable biofuels is crucial. Seaweed is generally a more efficient converter of solar energy because its cells grow in an aqueous suspension, which gives them ready access to CO₂, water, and other nutrients. Its high oil content relative to its dry weight qualifies it as a candidate for conversion through various processes, e.g., transesterification, pyrolysis, and direct combustion. Based on laboratory data, the higher heating value (HHV) of U. pinnatifida was 2553.5 kcal kg⁻¹, which is suitable for biofuel production. Still, this value is lower than that of wood-derived biomass (≈4500–5000 kcal kg⁻¹). However, the volatile fraction (50.2%) of U. pinnatifida makes it feasible for gasification with high generation of combustible gases (H₂, CO), a process that is key to the synthesis of renewable synthetic gas. This overcomes the drawback of low HHV by expanding the scope of energy products. Thus, it could be an up-and-coming option for local circular bioenergy systems in coastal areas, as it can grow in waters unsuitable for agriculture and does not compete with food crops, ideal for biodiesel, bioethanol, biogas, and biohydrogen. Further studies are needed to develop and test existing hypotheses.

4.5. Optimizing Sour Beer Production Through High-Temperature and Glucose Supplementation with Mixed Culture Fermentation of Kveik and Lachancea thermotolerans Yeast Strains

• Christos Avramopoulos, Arhontoula Chatzilazarou, Thalia Dourtoglou and Panagiotis Tataridis
• Department of Wine, Vine and Beverage Sciences, University of West Attica, Ag. Spyridonos 28, 12243 Aigaleo, Athens, Greece
• This study focused on improving the efficiency of sour beer production through mixed fermentations of Lachancea thermotolerans and Kveik yeast strains, aiming to reduce fermentation time while preserving the sour profile characteristic of L. thermotolerans. While in earlier trials, mixed fermentations with S. cerevisiae (US-05) achieved low pH values (~3.65), they did not achieve the best sensory profiles at elevated temperatures. Kveik yeast strains were selected as an alternative due to their high-temperature tolerance and rapid fermentation kinetics.
• Fermentations were conducted at 25 °C using Kveik yeast and L. thermotolerans at ratios of 1:10, 1:20, and 1:30 (Kveik to L. thermotolerans). All fermentations were completed in under 10 days, confirming Kveik’s ability to significantly accelerate fermentation. However, final pH values remained relatively high (~3.8) compared to previous US-05 L. thermotolerans mixed cultures.
• To enhance acidification, additional fermentations were carried out with glucose supplementation, based on prior findings that glucose increases L. thermotolerans’s acidifying ability. Glucose-supplemented mixed fermentation trials using both Kveik (at 25 °C, 1:30 and 1:40) and US-05 (at 20 °C, 1:10 and 1:30) led to lower final pH values while maintaining clean sensory profiles and short fermentation times.
• Across all trials, pH and extract (ºPlato) were monitored daily. Final beers were analyzed for alcohol content, total acidity, FAN, and underwent sensory evaluation. These findings suggest that mixed fermentations with L. thermotolerans and Kveik yeast (particularly with glucose addition) are an effective strategy for producing sour beers efficiently, without compromising flavor balance or sour character.

4.6. Functional Properties and Nutri-Economic Benefits of Carob-Based vs. Cocoa-Based Food Products

• Alexios Vardakas ^1,2, Dimitrios G. Lazaridis ¹, Maria Lymperopoulou ¹, Maria Antikleia Stefanoglou ¹, Maria Argyro Kapranou ¹, Dimitra Tsoumani ¹, Maria Evangelia Giannoulou ¹, Maria Simoni ¹, Ioannis K. Karabagias ¹, Olga Malisova ¹ and Nikolaos D. Andritsos ¹

¹ 

Department of Food Science and Technology, School of Agricultural Sciences, University of Patras, GR-30100 Agrinio, Greece

² 

GAEA Products S.M. S.A., GR-30100 Agrinio, Greece

• The recent price increases in cocoa occurring worldwide have led to the search for alternative cocoa-based products; carob is being used as a nutritious sweetener alternative to cocoa and cocoa-based products (e.g., chocolate). The present study evaluated the physicochemical, microbiological, nutritional, sensorial, phenolic, and antioxidant profiles of a carob-based spreadable product in comparison with two commercially available similar chocolate–hazelnut spreads. Moreover, the economic impact of the newly developed product was also estimated. The carob-based product was slightly more acidic (pH 5.3) and had an increased water activity (a_w = 0.67) when compared to the commercial chocolate spreads. Ongoing microbiological analysis and sensory evaluation suggest that the developed product has a shelf life of over six months. In terms of nutritional value, the product is suitable for vegans, as it contains no added dairy, eggs, or preservatives, while it is also high in fiber and very low in sodium. Total phenolic (TPC) and total flavonoid (TFC) contents were quantified spectrophotometrically, while antioxidant capacity was assessed using the DPPH radical scavenging assay. Comparatively, the developed carob-based product exhibited higher TPC but lower TFC, whereas antioxidant activity was the same as the other two cocoa-based spreads. Market analysis indicates that there is a considerable margin of profit for the developed product against competition. In conclusion, this research denotes the functional properties of carob-based products with enhanced potential health benefits compared to conventional cocoa-based products. Finally, it also highlights the better nutritional profile and the competitiveness that the carob-based products exhibit when compared to their cocoa-based counterparts.

4.7. Malva sylvestris L. As a Natural Bioactive Agent for Innovative Functional Dairy Products

• Souad Djellali ^1,2, Nawel Cherbal ¹, Rime Dilmi ³, Yasmine Abdelouahed ¹ and Rachid Sahraoui ⁴

¹ 

Department of Chemistry, Faculty of Sciences, University Ferhat Abbas Setif 1, Setif, Algeria

² 

Laboratory of Physical Chemistry of High Polymers, University Ferhat Abbas Setif 1, Setif, Algeria

³ 

Department of Chemistry, Faculty of Sciences, University Ferhat Abbas Setif 1, Setif, Algeria

⁴ 

Laboratory of Valorization of Natural Biological Resources, University Setif 1, Ferhat Abbas, Algeria

• Introducion: This research explored the incorporation of Malva sylvestris L. (common mallow) extracts into yogurt to develop a functional food with enhanced nutritional value. The study focused on evaluating the plant’s antioxidant and antibacterial activities to assess its potential for creating health-promoting dietary products.
• Methods: The methodology involved extracting bioactive compounds from Malva sylvestris using maceration. The resultant extract underwent detailed phytochemical analysis to quantify total phenolics, flavonoids, tannins, and sugars. Its antioxidant efficacy was thoroughly evaluated using four distinct assays: DPPH, ABTS, FRAP, and Phenanthroline. The extract was subsequently fortified into yogurt, and the resulting product was rigorously analyzed for its physicochemical properties, sensory attributes, and antimicrobial effects.
• Results: The findings demonstrated that Malva sylvestris is abundant in bioactive constituents, notably polyphenols (217 µg GAE/mL) and sugars (131.59 µg GE/mL). This rich phytochemical profile was directly linked to a potent antioxidant capacity, confirmed by remarkably low IC₅₀ values in the radical scavenging assays. Fortification of yogurt with the extract did not significantly alter its overall sensory or physical characteristics, confirming compatibility with the food matrix. The lactic acid bacterial count in the final product complied with the Codex Alimentarius standard of 10⁷ CFU/mL. A dose-dependent increase in pH was observed with higher extract concentrations, which slightly influenced the product’s properties.
• Conclusion: Our findings confirm Malva sylvestris L. as a potent natural antioxidant source, whose successful use in yogurt reveals significant potential for functional food and nutraceutical development.

4.8. A Novel Plant-Based Cheese Alternative: A Promising Sustainable Alternative to Dairy Products

• Cristina Popovici ¹, Xin Mei Teng ^2,3 and Ravi Jadeja ^2,3

¹ 

Department of Food and Nutrition, Faculty of Food Technology, Technical University of Moldova, 168 Stefan cel Mare si Sfant blvd., Chisinau MD 2004, Republic of Moldova

² 

Robert M. Kerr Food & Agricultural Products Center, Oklahoma State University, Stillwater, OK 74078, USA

³ 

Department of Animal & Food Sciences, Oklahoma State University, Stillwater, OK 74078, USA

• The production and consumption of plant-based products, including cheese alternatives, is constantly growing and demanding special attention in food science research. There are significant gaps in product development, as well as a need for assessing the nutritional composition, ingredients, and quality of plant-based cheese alternatives. This research focused on the development of a walnut-based cheese alternative with acceptable nutritious, physical, and sensory properties. Walnut cheese formulations were prepared with walnuts, water, instant yeast, agar-agar, walnut oil, salt, and sugar. Response surface models successfully predicted the optimal ingredients levels for the walnut cheese formulation: 79% walnut milk, with a walnut/water ratio of 1/1.26, 12% walnut oil, and 1.5% instant yeast. The results demonstrated an increase in the total polyphenol (164 mg GA/100 g) and flavonoid (53 mg QE/100 g) contents, as well as in DPPH, ABTS, and antioxidant activity values (83.51%, 91.38%) of walnut formulation, compared with animal cheese. In addition, walnut cheese demonstrated a hardness value of 1271.03 g, similar to that of animal cheese 1304.27 g (p ˂ 0.05). The walnut cheese recorded a lower L* index (63.87) and higher a* (2.00) and b* (22.74) indexes compared with animal cheese. Overall, walnut cheese was found to be acceptable by sensory evaluation (≥8.27). This study provides a scientific basis for further production process of plant-based cheese.
• Acknowledgments: This research was supported by an Institutional Project, subprogram 020405, “Optimizing food processing technologies in the context of the circular bioeconomy and climate change”, Bio-OpTehPAS, being implemented at the Technical University of Moldova.

4.9. Aflatoxin M1 Retention by Exopolysaccharides from Kefir Grains: Impact of Extraction Method on Binding Efficiency

• Carlos Jiménez-Pérez ¹, Karel Silva-García ², Alma Cruz-Guerrero ¹ and Sergio Alatorre-Santamaría ¹

¹ 

Departamento de Biotecnología, Universidad Autónoma Metropolitana, Ciudad de México 09340, Mexico

² 

Universidad Nacional Autónoma de México, Ciudad de México 04510, Mexico

• Introduction: Aflatoxin M1 (AFM1) is a carcinogenic mycotoxin commonly found in dairy products from livestock consuming contaminated feed. Its thermal stability renders pasteurization ineffective, necessitating alternative detoxification strategies. This study evaluated the AFM1-binding capacity of exopolysaccharides (EPS) from kefir grains using two extraction methods.
• Methods: EPS were produced by fermenting semi-skimmed milk with 10% kefir grains. After grain removal and casein elimination, EPS were extracted via (1) cold ethanol precipitation and (2) hot aqueous extraction followed by ethanol precipitation. EPS were dialyzed (14 kDa), lyophilized, and analyzed for sugar and protein content. AFM1 retention (1 μg/L) by 1% EPS was assessed in phosphate buffer (pH 6.8, 30 °C) over 3 h with hourly sampling, ultrafiltration (30 kDa), and HPLC-fluorescence quantification.
• Results: Cold extraction yielded higher solids (9400 mg) with balanced sugar-to-protein ratios, while hot extraction reduced protein content by 69% and increased sugar concentration eight-fold. Cold-extracted EPS maintained >80% AFM1 retention throughout the assay period. Hot-extracted EPS exhibited lower, time-dependent retention. Method-dependent differences were statistically significant (p < 0.05).
• Conclusions: Extraction methodology significantly affects EPS composition and AFM1-binding efficiency. Cold-extracted EPS, retaining protein components, demonstrated superior AFM1 sequestration, suggesting protein–mycotoxin interactions are crucial for binding. These findings highlight the potential of kefir EPS as a natural mycotoxin mitigation strategy in dairy processing, warranting further investigation for industrial applications.

4.10. BIOPEP-UWM Database of Peptides from Food—Status in 2025

• Piotr Minkiewicz, Anna Iwaniak and Małgorzata Darewicz
• Department of Food Biochemistry, University of Warmia and Mazury in Olsztyn, 10-726 Olsztyn, Poland
• Peptides are extensively studied bioactive compounds from food. They are analyzed e.g., using in silico strategies. The BIOPEP-UWM database (https://biochemia.uwm.edu.pl/en/biopep-uwm-2/) has become a standard tool in peptide research. Number of visits since 2024.01.01 is c.a. 56,000 (2025.07.24) and there is over 2000 publications citing the database name or web address, as judged by Google Scholar.
• The BIOPEP-UWM is publicly available without registration and includes databases of bioactive peptides, sensory peptides and amino acids and virtually bioactive peptides (BIOPEP-UWM Virtual). They annotate 5362, 587 and 499 records respectively, representing 99 bioactivities including tastes. Currently BIOPEP-UWM offers possibility of annotation of peptides with non-proteinogenic and modified amino acids or non-amino acid residues using data of monomers from the BIOPEP-UWM repository of amino acids and modifications.
• Records of peptides containing proteinogenic amino acids and other residues are available to all options e.g., proteolysis simulation or conversion from sequence into SMILES code. BIOPEP-UWM enables annotation of peptides containing residues not investigated to date, such as sulfoxides with asymmetric sulphur atoms or anomers of lysine glycation products. The database is thus ahead of the state of knowledge in food science.
• Acknowledgements:
• This work was supported by designated subsidy of the Minister of Science and Higher Education Republic of Poland, task entitled: The Research Network of Life Sciences Universities for the Development of the Polish Dairy Industry—Research Project and by Minister of Science under “the Regional Initiative of Excellence Program”.

4.11. Centroid Mixture Design as a Tool for Enhancing Oxidative Resistance in Vegetable Oil Blends

• Ewelina Ewa Książek, Marta Bochniak and Weronika Wójcik
• Department of Agroengineering and Quality Analysis, Faculty of Production Engineering, Wroclaw University of Economics and Business, 53-345 Wrocław, Poland
• This study investigated the effect of varying proportions of rapeseed, avocado, and walnut oils on the oxidative stability of ternary lipid blends. A centroid simplex mixture design was applied, with oil fractions constrained to 100%. Oxidative quality was assessed using peroxide value (PV), acid value (AV), anisidine value (AnV), and the total oxidation index (Totox). Additionally, natural pigments, carotenoids, and chlorophylls were analyzed as response variables.
• The findings showed that increasing walnut oil content above 7% markedly raised Totox, indicating enhanced susceptibility to oxidative degradation. In contrast, blends containing at least 72% rapeseed oil and 21–22% avocado oil, with a maximum of 6% walnut oil, demonstrated the lowest Totox values, reflecting the highest oxidative stability. This suggests a synergistic interaction between rapeseed and avocado oils, reducing both primary (PV) and secondary (AnV) oxidation.
• The inclusion of carotenoids and chlorophylls as output variables highlighted their role as natural antioxidants, though their stability was strongly influenced by oil composition. Overall, the study confirms that mixture design methodology provides an effective framework for optimizing lipid systems and identifying interactions between components.
• These results emphasize the potential of carefully balanced oil blends to achieve improved oxidative resistance and pigment stability. Such formulations may contribute to the development of functional fats and oils with superior nutritional quality and extended shelf life, supporting their application in the food industry.

4.12. Chemical Analysis and In Vitro Antioxidant Activity of Taraxacum officinale with Functional Food Implications

• Rachid Sahraoui ¹, Souad Djellali ^2,3, Yasmine Abdelouahed ² and Lakhdar Gasmi ⁴

¹ 

Laboratory of Valorization of Natural Biological Resources, University Setif 1- Ferhat Abbas, Algeria

² 

Department of Chemistry, University Setif 1 Ferhat Abbas, Algeria

³ 

Laboratory of Physical-Chemistry of High Polymers, University Setif 1 Ferhat Abbas, Algeria

⁴ 

Laboratory of Phytotherapy Applied to Chronic Disease, University Ferhat Abbas Setif 1, Algeria

• Background: Taraxacum officinale (common dandelion) is a perennial herb widely valued for its nutritional and medicinal properties having strong potential in food technology as a natural source of bioactive compounds. Its vitamin- and mineral-rich leaves, inulin- and antioxidant-containing roots, and flavonoid-rich flowers highlight its potential for use in functional beverages, dietary supplements, and natural food additives.
• Methods: The research included morphological and anatomical analysis, chemical composition determination (polyphenols, flavonoids, tannins, sugars), and the assessment of antioxidant activity using DPPH method. The antibacterial activity of the prepared extracts was assessed using the disk diffusion method on Mueller-Hinton agar. The tested bacterial strains included Gram-negative (Escherichia coli, Pseudomonas aeruginosa) and Gram-positive (Staphylococcus aureus, Bacillus subtilis) species. This screening aimed to determine the inhibitory potential of the extracts against clinically relevant microorganisms.
• Results: Anatomical studies revealed well-defined vascular structures and storage parenchyma, consistent with its taxonomic classification. Phytochemical screening showed high concentrations of polyphenols (33.76 μg GAE/mg), tannins and sugars but lower flavonoids. The extract exhibited strong antioxidant capacity (IC₅₀: 143.97 μg/mL) in DPPH assays, confirming its efficacy against oxidative stress. However, antibacterial tests against standard strains revealed negligible inhibition zones. The results highlight T. officinale’s significant antioxidant properties while suggesting limited direct antimicrobial activity, supporting its traditional use in antioxidant-related therapies.
• Conclusion: Overall, T. officinale represents a promising candidate for the development of functional foods and nutraceuticals, particularly as a natural antioxidant source. Its incorporation into beverages, supplements, or as an additive could improve both the nutritional value and health-promoting properties of food products.

4.13. Compound Repurposing as an Effective Antifungal Development Strategy for the Safe Production of Crops and Foods

• Jong H. Kim, Kathleen L. Chan and DeAngela Ford
• Foodborne Toxin Detection and Prevention Research Unit, Western Regional Research Center, USDA-ARS, 800 Buchanan St., Albany, CA 94710, USA
• The infection or contamination of fungi in crops or foods trigger serious food security and safety concern worldwide. Long-term application of conventional antifungal agents, such as azole, strobilurin or fludioxonil fungicides, during crop/food production can result in the emergence of fungicide-resistant fungi, for which effective agents for treating resistant fungal pathogens or contaminants are often very limited. Since the development of entirely new antifungal agents is an expensive and time-consuming process, we investigated an innovative approach termed “compound repurposing”, which repositioned already marketed non-antifungal compounds as new antifungal agents for the control of fungal infections/contaminations. We also employed a “chemo-sensitization” strategy wherein co-application of potentiators (chemo-sensitizers), for example, redox-modulatory molecules, could enhance the antifungal efficacy of the screened compounds. We found that compounds such as polyphenol, terpenoid or medicinal agents, which have been used as nutrient supplements, non-antifungal medicines, etc., exerted potent antifungal activity against crop/food fungal pathogens or contaminants including Aspergillus sp. and Fusarium sp. Repurposed compounds also inhibited the biosynthesis of aflatoxins by Aspergillus flavus or Aspergillus parasiticus, thus ensuring safe production of crops/foods. Collectively, antifungal “compound repurposing” could serve as a promising strategy that can identify new crop/food protection molecules; “chemo-sensitization” significantly improved the antifungal efficacy of the screened compounds.

4.14. Design and Simulation of a Smart Arrow Photonic Crystal Fiber Sensor for Multimodal Optical Detection of Food Adulteration

• Sunil Sharma ^1,2, Sandip Das ³, Anu Mehra ⁴, Prashant Sharma ⁵, Athar Ahmed ⁶, Prasun Chakrabarti ⁷ and Chin Shiuh Shieh ⁸

¹ 

Department of Computer Science and Engineering, Techno NJR Institute of Technology, Udaipur, Rajasthan 313001, India

² 

National Kaohsiung University of Science and Technology, Kaohsiung, Taiwan

³ 

Computer Science and Engineering, Brainware University, Kolkata, West Bengal, India

⁴ 

Amity University, Noida, Uttar Pradesh, India

⁵ 

Computer Science and Engineering, Vivekananda Global University, Jaipur, Rajasthan, India

⁶ 

Department of CSE, Vivekanand Global University, Jaipur, India

⁷ 

Sir Padampat Singhania University, Udaipur, Rajasthan, India

⁸ 

Department of Electronic Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 807618, Taiwan

• The challenge of food adulteration has always been a major concern and thus there is a need to formulate quick, sensitive, and un-destructive methods to detect food adulteration. Authors provide the design and performance analysis of a Smart Optical Sensing platform driven by Arrow-type Silica Photonic Crystal Fiber (PCF) that is designed to specifically detect adulterants in food products. The COMSOL Multiphysics numerical simulation environment is used to increase the interaction between light and matter. The intended PCF structure has a pitch size of 1.5 µm, diameter of the air holes to be 0.75 µm and core displacement parameters to be asymmetrical (dx = 0.5 µm, dy = 0.25 µm) that leads to a robust field of evanescent confinements and proves to have high optical sensing qualities. The simulation outcomes also show a large absorbance difference (0.8512 a.u.) between non-adulterated and adulterated ones and the greatest decrease in transmittance amounting to 30% exists in the case of the adulterated specimens. Fluorescence spectral displacement of 40 nm to 75 nm and Raman based at 200 to 800 cm⁻¹ allowed distinguishing between chemicals at the level of a molecule, and identification of adulterants which include artificial food dyes, heavy metals, and chemical preservatives. A combination of NIR spectroscopy with COMSOL-based modelling will define a sound system of non-destructive, fast, and scalable food safety tests.

4.15. Determination of Pathogens Causing Mastitis in Milk by Gas Phase Analysis Using Chemical Sensors

• Anastasiia Shuba ¹, Ekaterina Anokhina ², Inna Burakova ³, Ekaterina Bogdanova ⁴, Ruslan Umarkhanov ¹ and Evgeny Mikhaylov ⁵

¹ 

Department of Physical and Analytical Chemistry, Voronezh State University of Engineering Technologies, Revolution Avenue 19, 394036 Voronezh, Russia

² 

Center for Collective Use “Testing Center”, Voronezh State University of Engineering Technologies, Revolution Avenue 19, 394036 Voronezh, Russia

³ 

Laboratory of Metagenomics and Food Biotechnology, Voronezh State University of Engineering Technologies, 394036 Voronezh, Russia

⁴ 

Department of Technology of Animal Products, Voronezh State University of Engineering Technologies, Revolution Avenue 19, 394036 Voronezh, Russia

⁵ 

FSBSI All-Russian Veterinary Research Institute of Pathology, Pharmacology and Therapy, 394061 Voronezh, Russia

• Milk is one of the most valuable products in terms of nutritional value and balanced composition. About a third of the entire herd of cows gets sick with mastitis, while milk from such cows must be disposed of due to the presence of pathogenic microorganisms and their toxins. Intensification and robotization of various areas of the agro-industrial complex requires modern systems for assessing the quality of raw materials and food products. One of the possible options for detecting mastitis milk is the use of sensor technologies. A method is proposed for detecting milk from cows with mastitis by analyzing the gas phase above milk samples using chemical sensors, including the subclinical course of the disease with a pathogenic microorganism content in milk of no more than 1000 CFU/mL, and differentiating such samples from milk with a high level of coliform bacteria and a general level of contamination, as well as with non-vital forms of pathogenic microorganisms. The work used piezoelectric quartz sensors with polycomposite coatings to identify informative sensor output data related to the presence of pathogenic microorganisms and their toxins, milk samples were analyzed in parallel using microbiological and molecular genetic methods. The work demonstrated approaches to determining Staphylococcus, Streptococcus, Klebsiella spp. in milk from mastitis cows at a level of 1000–10,000 CFU/mL with high sensitivity due to variation in the preparation of milk samples before measurement. Thus, the use of gas sensors will allow obtaining information on the microbiological safety of milk within three hours.

4.16. Effect of Germination and Toasting on the Physicochemical Properties of Protein Concentrates from ‘Guna’ (Cucumis melon Linn) Kernels

• Salamatu Mustapha ¹, Yakubu C. M ¹ and Mustapha Raji Abdullahi ²

¹ 

Food Science and Technology Department, Federal University of Technology Minna, Minna, Nigeria

² 

Biochemistry Department, Usmanu Danfodiyo University Sokoto, Sokoto, Nigeria

• This study investigated the effects of germination and toasting on the physicochemical properties of protein concentrate extracted from ‘guna’ (Cucumis melon Linn) kernel. Conducted at the Department of Animal Production, Federal University of Technology, Minna, the experiment involved measuring proximate composition, physicochemical properties, and amino acid profiles, with results expressed as means of three trials ± standard deviation. The proximate analysis revealed that the untreated ‘guna’ kernel (CGK) had a crude fat content of 2.56% ± 0.01. In comparison, germinated ‘guna’ kernel (GGK) showed a moisture content of 4.13% ± 0.09. Crude fiber was 3.33% ± 0.01 in CGK, and crude protein was highest in both GGK and toasted ‘guna’ kernel (TGK) at 77.55% ± 0.04. Ash content was 2.47% ± 0.04 in CGK and TGK, while carbohydrate content was 12.17% ± 0.02 in TGK. Physicochemical parameters such as titrable acidity, total solids, yield, and dispersibility were recorded, with values including 5.30 ± 0.01 (GGK), 97.20 ± 0.76 (TGK), and 44.93 ± 0.07 (CGK), respectively. Amino acid profiling indicated that the protein concentrate contains all essential amino acids, with notable levels of isoleucine, threonine, lysine, histidine, and methionine in TGK and GGK samples. Statistical analysis using one-way ANOVA confirmed that both toasting and germination significantly improved protein content by 1.84% and 2.06%, respectively. The study recommends further research focusing on protein isolates to explore the effects of these treatments on functional properties, aiming to enhance industrial applications of ‘guna’ kernel protein concentrates.

4.17. Effect of Thermal Processing on the Antioxidant Capacity, Microbiological Safety, and Physicochemical Properties of a Controlled Fermentation Beverage from Purple Maize (Zea mays L.)

• Laura K. Bernal-Pérez ¹, Laura M. Islas Romero ² and Ana E. Ortega-Regules ²

¹ 

Chemistry, Food and Environmental Engineering Department, Universidad de las Américas Puebla, Puebla 72810, México

² 

Health Sciences Department, Universidad de las Américas, Puebla 72810, México

• In the production of controlled fermented beverages, thermal processing is an essential step to ensure microbiological safety, while also facilitating starch gelatinization in maize-based beverages. However, it can degrade antioxidant compounds from purple maize, such as anthocyanins and polyphenols. The aim of this study was to identify an adequate thermal treatment for a purple maize beverage that maximizes antioxidant capacity while ensuring its microbiological safety prior to controlled fermentation.
• A 1:9 ratio of purple maize to water was soaked for 12 h. The mixture was then milled and strained. The resulting liquid was subjected to different heat treatments: a no-heat control (A_c), 85 °C for 5 min (A₁), 85 °C for 10 min (A₂), and 121 °C for 15 min (A₃). Total mesophilic bacteria, total coliforms, and yeasts were quantified by plate count. The pH, total soluble solids (TTSs), color based on the CIELAB parameters, and apparent viscosity were measured. Total phenolic compounds (TPCs), monomeric anthocyanins (MAAs), and in vitro antioxidant capacity were assessed via DPPH and ABTS assays. Statistical analysis was performed using one-way ANOVA, followed by Tukey’s test (p < 0.05).
• All heat treatments ensured the microbiological safety of the beverage. A₁ exhibited the highest apparent viscosity. The total color difference (ΔE) for samples A₁ and A₂ indicated minimal perceptible color changes. TPCs, MAAs, and the resulting antioxidant capacity were all significantly higher in sample A₁. Therefore, the A₁ treatment effectively enhances the extraction of TPCs and MAAs, leading to the highest antioxidant capacity. However, its viscosity requires further evaluation for consumer acceptability.

4.18. EPR Spectroscopic Study of Irradiated Saccharides

• Ahmed M. Maghraby ¹, Elsayed Salama ² and Sami Ashraf ³

¹ 

Lonizing Metrology Laboratory, National Institute of Standards, Giza, 12211, Egypt

² 

BUE—British University in Cairo, El Sherouk 11837, Egypt

³ 

Meteorological Authority in Cairo, Cairo 11784, Egypt

• Electron Paramagnetic Resonance (EPR) or electron spin resonance (ESR) spectroscopy is a non-destructive technique which used usually for the identification and investigation of compounds containing unpaired electrons and hence it is considered as an effective tool for the identification and quantification of radiation doses delivered to irradiated materials. Here we investigate the EPR spectroscopic differences among poly, di- and monosaccharides irradiated to gamma radiation. Several parameters were studied: spectral features of monomers, dimers, and polymer molecules, microwave saturation behaviour, and the modulation amplitude impact on both of the signal height and the width. Also response to different radiation doses were investigated for each molecule and the time-dependence of the radiation-induced radicals were plotted and analysed. the study included glucose and fructose as monosaccharides, sucrose as a disaccharide, and starch as a polysaccharide. The study revealed thae resembelence of EPR spectra of sucrose and its constituents clucose and fructose with minor differences while the EPR spectra of starch showed more differences either in terms of peaks positions or peaks shapes. Response to ionizing radiation doses for all of them was found to be linear over the dose range (0.5–10) kGy. The stabilities of the radiation induced radicals were traced along 50 days after irradiation.

4.19. Evaluation of the In Vitro Antioxidant and Anti Inflammatory Potentials of Artemisia arborescens Aqueous and Hydroethanolic Extracts: Insights from Moroccan Ethnopharmacology

• Majdouline Aziz ¹, Othman El Faqer ¹, Zaynab Ouadghiri ¹, Maria Tijini ¹, Samira Rais ^1,2 and El Mostafa Mtairag ¹

¹ 

Laboratory of Integrative Biology, Faculty of Sciences Ain Chock, Hassan II University, Casablanca, Morocco

² 

Department of Biology, Faculty of Sciences Ben M’Sick, Hassan II University, Casablanca, Morocco

• Artemisia arborescens (A. arborescens) holds a long-standing place in Moroccan traditional medicine and is increasing attention for its pharmacological and therapeutic potential. This study evaluates the phytochemical composition of aqueous and hydroethanolic extracts, along with their antioxidant and anti-inflammatory properties.
• Spectrophotometric analysis was used to quantify bioactive compounds. Antioxidant activity was assessed through total antioxidant capacity (TAC), while radical scavenging ability was measured using 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) and 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH), and anti-inflammatory effects were evaluated by inhibition of bovine serum albumin (BSA) denaturation.
• The aqueous extract contained phenolics (1.575 ± 0.97 mg AGE/g_DM, flavonoids (18.51 ± 0.64 mg QE/g_DM), tannins (0.615 ± 0.150 mg CE/g_DM), and flavonols (2.99 ± 0.09 mg QE/g DM). Antioxidant activity, as determined by TAC showed an IC₅₀ of 2.68 ± 0.29 mg/mL, while both DPPH and ABTS values exceeded 10 mg/mL. BSA inhibition reached 0.964 ± 0.133 mg/mL.
• In comparison, the hydroethanolic extract exhibited higher levels of phenolics (21.30 ± 1.10 mg AGE/g_DM), flavonoids (24.80 ± 0.80 mg QE/g_DM), tannins (0.550 ± 0.120 mg CE/g_DM), and flavonols (4.10 ± 0.15 mg QE/g_DM). Antioxidant activity was stronger, with TAC IC₅₀ of 1.262 ± 0.89 mg/mL, ABTS scavenging activity was 8.127 ± 0.903 mg/mL, while DPPH remained above 10 mg/mL. BSA inhibition was 0.560 ± 0.109 mg/mL.
• Overall, the hydroethanolic extract displayed a richer phytochemical profile and greater biological activity than the aqueous extract. These findings support the pharmacological potential of A. arborescens and underscore the need for further mechanistic and in vivo studies.

4.20. Evaluation of the Antioxidant Capacity of Biscuits Containing Added Ingredients

• Paula Conforti and Mariela Patrignani
• Centre for Research and Development in Food Science and Technology (CIDCA), CICPBA, CONICET, National University of La Plata (UNLP), 47 y 116, La Plata CP 1900, Argentina
• Introduction: Many chronic diseases are associated with oxidative stress imbalances. Incorporating antioxidants into biscuits could provide an effective way to protect against cell damage caused by exposure to free radicals. Various ingredients were investigated. This study aimed to identify ingredients that could enhance the antioxidant content of biscuits.
• Methods: Different ingredients were incorporated into biscuit dough. Biscuit extracts were prepared using warm water (0.5% w/w), stirring for 20 min at 600 rpm (12× g) and 45 °C. The antioxidant capacity of the aqueous extracts was determined using the ferric reducing antioxidant power (FRAP) method. A calibration curve was constructed using FeSO₄·7H₂O and the results were expressed as µmol FeSO₄/g of dry sample. The colour of the products was measured using a colourimeter to record the L*, a* and b* values.
• Results: The results showed that the colour of the biscuits was more consistent when the added ingredients were liquids rather than solids. Carob flour and cinnamon were the solid ingredients that increased antioxidant levels the most. In contrast, the antioxidant capacity did not significantly increase with the liquid extracts of Callistemon citrinus or Tropaeolum majus flowers at 0.02% w/w. The aim was to select ingredients that would significantly increase the biscuits’ antioxidant content.
• Conclusion: The antioxidant content of biscuits can be increased by adding certain ingredients to the formulation.

4.21. Evaluation of the Properties of a Sunflower–Rapeseed Oil Blend

• Natalia Murlykina ^1,2 and Olena Upatova ¹

¹ 

Department of Chemistry, Biochemistry, Microbiology and Hygiene of Nutrition, State Biotechnological University, Kharkiv 61051, Ukraine

² 

Department of Applied Chemistry, V.N. Karazin Kharkiv National University, Svobody sq., 4, Kharkiv 61022, Ukraine

• One of the key challenges in developing fat-containing foods aligned with healthy dietary trends is optimizing the fatty acid composition. Blending traditional vegetable oils is a cost-effective and practical approach for designing products with targeted levels and ratios of polyunsaturated fatty acids (PUFAs). Our previous research identified that a blend of 52% sunflower oil and 48% rapeseed oil provides a balanced ω-6:ω-3 ratio of 9.8:1.0.
• This study aimed to evaluate the physicochemical and sensory properties of this blend. Fatty acid composition was analyzed using gas–liquid chromatography, while total tocopherol and α-tocopherol contents were determined via high-performance liquid chromatography. Standard analytical methods were used to assess other physicochemical parameters. Sensory properties were evaluated using quantitative descriptive analysis based on transparency, taste, flavour, and colour. Statistical analysis was performed using parametric tests, with significance accepted at p < 0.05.
• The blend exhibited a favorable fatty acid profile for balanced nutrition, with high monounsaturated oleic acid (42.6 ± 0.3%) and sufficient ω-3 linolenic acid (4.3 ± 0.2%). It demonstrated improved hydrolytic and oxidative stability, which was confirmed by the significantly lower acid and peroxide values after 30 days of storage at (20 ± 1)°C compared to pure sunflower oil by 5.3% and 19.7%, respectively. The accumulation rate of primary oxidation products was 1.5 times lower in the blend (p < 0.05). These findings may be attributed to a higher content of antioxidant-active tocopherol isomers (β-, γ-, and δ-tocopherols) derived from rapeseed oil.
• Sensory evaluation confirmed the blend’s compliance with regulatory quality standards. The developed sunflower–rapeseed oil blend is a promising option for functional fat-containing products aimed at dietary improvement and disease prevention.

4.22. Exploring Functional and Nutritional Potential of Walnuts: Advancing the Development of Plant-Based Milk Alternatives

• Cristina Popovici ¹, Xin Mei Teng ^2,3 and Ravi Jadeja ^2,3

¹ 

Department of Food and Nutrition, Faculty of Food Technology, Technical University of Moldova, 168 Stefan cel Mare si Sfant blvd., Chisinau MD 2004, Republic of Moldova

² 

Robert M. Kerr Food & Agricultural Products Center, Oklahoma State University, Stillwater, OK 74078, USA

³ 

Department of Animal & Food Sciences, Oklahoma State University, Stillwater, OK 74078, USA

• The increasing trend of innovative plant-based milk alternatives (PBMAs) is driven by lactose intolerance, cholesterol risks, and ethical, environmental, religious and social beliefs. In this regard, walnuts can be considered a unique ingredient for the production of PBMAs due to their remarkable functional potential and nutritional value. In this context, this study formulated and evaluated walnut milk, employing Design-Expert software. The findings showed that the optimal walnut milk composition is walnuts (17%), water (79.8%), fibers (2%), sugar (0.5%), vanilla extract (0.5%), salt (0.1%), and stabilizer (0.1%). The proximate composition (g/100 g) of optimized walnut milk was proteins at 3.51 g, fats at 2.75 g, carbohydrates at 5.65 g and ash at 0.81 g. Furthermore, the microstructure analysis denoted that it is an oil-in-water emulsion with the particle size distribution of oil drops in walnut milk in the range of 0.45 … 5.40 microns. The largest part of the oil volume has an average diameter of 2.70 microns. A sensory study was also undertaken, where walnut milk was highly acceptable to the panellists. This study shows the high potential and provides a positive view of walnut milk production, which is in agreement with the current demand for sustainable alternatives to dairy milk.
• Acknowledgments. This research was supported by the Institutional Project, subprogram 020405 “Optimizing food processing technologies in the context of the circular bioeconomy and climate change”, Bio-OpTehPAS, being implemented at the Technical University of Moldova.

4.23. Functional Enhancement of Low-Fat Mozzarella Cheese Using Flaxseed Mucilage and Konjac Glucomannan as Natural Fat Replacers

• Aimen Sajid
• Graduate School of Agricultural and Life Sciences, University of Tokyo, Tokyo, Japan
• Reducing fat content in mozzarella cheese often results in compromised texture, meltability, and consumer acceptability. This study aimed to enhance the physicochemical, functional, and sensory properties of low-fat mozzarella cheese (LFMC) by utilizing flaxseed mucilage (FM) and a combination of FM with konjac glucomannan (FMKGM) as clean-label fat replacers. Cheeses were formulated using low-fat buffalo milk (2.5% fat) with varying concentrations of FM (1%, 2.5%, 5%) and FMKGM (1%, 2.5%, 5%), and compared with full-fat and low-fat controls. Results showed that FM and FMKGM significantly increased protein content and moisture retention while maintaining reduced fat levels. Treatments with 2.5% FM and 2.5% FMKGM achieved optimal performance across key parameters. These samples demonstrated superior stretchability (44.2–46.1 inches) and meltability (up to 2.0 inches), closely resembling the functional behavior of full-fat cheese. Additionally, the same treatments exhibited improved textural resistance and reduced oiling-off ratios, indicating enhanced structural integrity. Sensory evaluation confirmed higher scores in mouthfeel, flavor, and overall acceptability for FM 2.5% and FMKGM 2.5% samples. This work demonstrates the potential of FM and FMKGM as sustainable, multifunctional fat replacers in dairy reformulation, offering a viable alternative for health-conscious consumers. Their application supports functional food innovation and aligns with Sustainable Development Goals #3 (Good Health and Well-being) and #12 (Responsible Consumption and Production). The findings provide practical insights for clean-label, cost-effective cheese manufacturing using plant-derived ingredients.

4.24. Investigation of the Effect of Mullein Flower Extract Obtained by Ultrasound-Assisted Extraction on the Oxidative Stability of Linseed Oil

• Edyta Symoniuk, Monika Pawlak and Iwona Szymańska
• Department of Food Technology and Assessment, Institute of Food Science, Warsaw University of Life Sciences, Nowoursynowska 166, 02-787 Warsaw, Poland
• The aim of this study was to investigate the effect of mullein flower extract on the oxidative stability of linseed oil. The theoretical part discussed the composition, properties, and applications of linseed oil and mullein. The lipid oxidation process and techniques for enriching oils with antioxidant compounds, including the use of ultrasound, were described. In the experimental part, the ultrasound-assisted extraction of antioxidant compounds from mullein flowers was optimized, with antioxidant activity (AA) used as the optimization parameter. The optimized extract was added to linseed oil, determining the optimal addition level at 5%. Both fresh linseed oil and the oil enriched with the extract were subjected to safety analysis, and their oxidative stability and bioactive compound content were determined. The results confirmed the effectiveness of mullein extract as a natural antioxidant, with linseed oil stability increasing on average by 26%. Moreover, the oil with the extract showed a higher degree of hydrolysis and a higher level of secondary oxidation products. The addition of the extract increased the content of bioactive compounds in linseed oil, especially phenolics, which increased threefold to values ranging from 311.49 to 430.41 mg GAE/100 g of oil. The induction time of the oil was strongly positively correlated with the phenolic content (r = 0.97), anisidine value (r = 0.95), and antioxidant activity of the oil’s hydrophilic fraction (r = 0.93).

4.25. Low-Wetting Ultrasonic Micro-Mist as a Postharvest Treatment for Sliced Mushrooms (Agaricus bisporus)

• Grecia Hurtado and Carlota Moreno-Guerrero
• Centro de Investigación de Alimentos (CIAL), Ingeniería de Alimentos, Facultad de Ciencias de la Ingeniería e Industrias, Universidad UTE, EC171029 Quito, Ecuador
• Ultrasonic nebulization generates a micro-mist that rapidly wets surfaces with minimal liquid load, making it attractive as a rinse-free postharvest step for delicate, cut produce. This study evaluated an ultrasonic nebulization treatment for sliced mushrooms using 5 ppm of chlorine dioxide (ClO₂), 80 ppm of peracetic acid (PAA), water, and a non-nebulized control. Slices were treated in a sealed chamber for a total of 2 min (two cycles of 1-min ON/2-min OFF) using nebulizers with an ultrafine spray aperture (~5 μm) and stored at 5 °C and 85% RH for 11 days. Weight loss, firmness, color, browning index, overall appearance, pH, total phenolics, antioxidant capacity, and microbiology counts (total aerobic mesophiles, yeasts, and molds) were monitored every 3–4 days. Weight loss was higher for PAA and water-treated slices (p < 0.05). No significant differences were detected among treatments for firmness, browning index, color (chroma), or overall appearance across storage (p < 0.05). PAA showed the highest pH at the end of storage. Total phenolics and antioxidant capacity were higher in ClO₂-treated slices throughout storage, except on day 0, when PAA showed the greatest values (p < 0.05). Microbiological analyses showed modest but significant decreases in total aerobic counts for both ClO₂ and PAA, as well as for yeasts and molds with ClO₂, compared to the control (p < 0.05). Overall, ultrasonic nebulization with ClO₂ or PAA showed potential to reduce microbial load while maintaining sliced-mushroom quality, with ClO₂ supporting higher total phenolics and antioxidant capacity. Future work should optimize dose and duty cycle to balance antimicrobial effect with preservation of antioxidants.

4.26. Machine Learning-Based Hybrid Model for Improved Crop Yield Correlation Analysis: A Data-Driven Assessment

• Nasina Harshavardhan ¹, Yamini Kodali ¹ and Yellapragada Venkata Pavan Kumar ²

¹ 

School of Computer Science and Engineering, VIT-AP University, Amaravati 522241, Andhra Pradesh, India

² 

School of Electronics Engineering, VIT-AP University, Amaravati 522241, Andhra Pradesh, India

• Climate change greatly affects farming by reducing crop yields, thereby challenging sustainable farming. Real-time data and analytics help identify key factors to boost crop yield and support smart farming through better decision making. To study how different factors affect crop yield, this paper considers various parameters, namely, temperature, precipitation, CO₂ emissions, extreme weather, use of fertilizers/pesticides, irrigation, soil health, economic factors, and location, and their influence on the crop yield is estimated. The Pearson Correlation Coefficient (PCC) is commonly used to find relationships between variables, but it only detects linear connections. Since climate factors often change in complex, nonlinear ways, this paper suggests a hybrid approach that combines the PCC with the XGBoost machine learning method for better analysis. In the proposed hybrid model, XGBoost identifies which factors are most important, while the PCC measures their impact on crop yield, thereby performing an effective correlation analysis. Simulations show that ‘economic impact’ has the strongest direct influence on crop yield, with a correlation coefficient of 0.73. Further, it is also noticed that the combination of ‘average temperature’ and ‘economic impact’ has the highest indirect influence, with a correlation of 0.2. The proposed hybrid model performs better than the standard PCC method, achieving an R-squared of 0.57, RMSE of 0.62, and MAPE of 29.14%, compared to PCC’s R-squared of 0.55, RMSE of 0.71, and MAPE of 31.48%. This study uses the ‘climate change impact on agriculture’ dataset from Kaggle and supports UN Sustainable Development Goals (UN SDGs 13 and 15) for promoting sustainable farming.

4.27. Nutritional and Antioxidant Properties of Mangaba (Hancornia speciosa) from the Cerrado Goiano

• Lorrane dos Santos dos Santos ¹, Jéssica Silva Medeiros ¹, Fabiano Guimarães Silva ², Letícia Fleury Viana ¹ and Adriana Rodrigues Machado ¹

¹ 

Department of Food Science, Goiano Federal Institute of Education, Science and Technology, Campus Rio Verde, Rodovia Sul Goiana, Km 01, Rio Verde 75901-970, GO, Brazil

² 

Federal Institute of Education Science and Technology Goiano, Campus Rio Verde, Rodovia Sul Goiana, Km 01, Rio Verde 75901-970, GO, Brazil

• Brazil is recognized for its vast biodiversity, home to biomes such as the Cerrado, where the mangaba (Hancornia speciosa) is found, a fruit with high nutritional and medicinal potential. This study aimed to evaluate the mineral content and antioxidant activity of mangaba fruits collected in the Cerrado Goiano. The fruits were processed and analyzed for their mineral content (N, P, K, Ca, Mg, S, Fe, Mn, Cu, Zn, B), carotenoids (β-carotene and lycopene), phenolic compounds, and antioxidant capacity using the DPPH method. The results showed a high concentration of nitrogen, sulfur, and potassium, essential for the development of the fruit and beneficial for human health. In addition, relevant amounts of iron and magnesium were identified, which reinforces their nutritional value. Regarding bioactive compounds, 34.00 mg/100 g of β-carotene, 3.00 mg/100 g of lycopene, and 40.00 mg/g of DPPH were found, indicating a significant antioxidant capacity, although lower than other fruits of the Cerrado. The phenolic content was also higher than that reported in other studies, which can be attributed to environmental and methodological factors. The results show that mangaba is a rich source of minerals and antioxidant compounds, with potential for applications in the food and pharmaceutical industry. Its use can contribute to the development of natural functional products, promoting the valorization of native species of the Cerrado.

4.28. Research of Preservation of Amino Acid Components of Garlic (Allium sativum) During Drying

• Jasur Safarov ¹, Shakhnoza Sultanova ¹, Abdurahmon Mirkomilov ², Doston Samandarov ¹, Abderrahmane Ait-Kaddour ³, Mavluda Nasirova ¹, Azamat Usenov ¹ and Botir Jumaev ⁴

¹ 

Department Food Engineering, Tashkent State Technical University Named After Islam Karimov, Tashkent 100095, Uzbekistan

² 

Department Food Technology, Tashkent Institute of Chemical Technology, Tashkent 100011, Uzbekistan

³ 

Laboratory of Food Chemistry, Université Clermont Auvergne, INRAE, VetAgro Sup, F-63370 Lempdes, France

⁴ 

Tashkent Institute of Chemical Technology, Yangier Branch 121000, Uzbekistan

• This research examines the process of drying garlic on a vibration-convection drying unit. The results of experiments conducted at the Tashkent State Technical University made it possible to determine the optimal drying method that preserves the amino acid components of garlic (Allium sativum). The unit is equipped with three trays measuring 60 × 40 cm, located at a distance of 20 cm from each other. A special vibration device is fixed to the bottom of each tray. The vibrator operates at a power of 5 W, and its vibration acceleration is regulated in the range from 20 to 60 m/s², which allows the use of various drying modes. Dried garlic samples were studied at the Institute of Bioorganic Chemistry of the Academy of Sciences of the Republic of Uzbekistan for amino acid content. The results of eight samples of laboratory studies of the amino acid composition in garlic are presented. Each dried sample was prepared separately for analysis. Among the eight samples from three garlic drying methods, sample №3-garlic (cut into plate shape, 2 mm thick, dried at 30 °C, 2 m/s air flow velocity and 60 m/s² vibration acceleration, the drying time was 540 min) was dried in a vibration-convection drying unit. The amino acid concentration was as follows (mg/g): aspartic acid (2.080), glutamic acid (2.543), serine (6.928), glycine (9.691), asparagine (9.710), glutamine (1.678), threonine (1.662), arginine (9.806), alanine (9.097), proline (18.452), tyrosine (6.544), valine (4.027), histidine (9.810), isoleucine (4.299), leucine (3.579), tryptophan (4.463), and phenylalanine (4.201).

4.29. Results of the Analysis of the Quantity of Water-Soluble Vitamins in the Composition of Beet (Beta vulgaris L.)

• Jasur Safarov ¹, Shakhnoza Sultanova ¹, Mahammad Najafli ¹, Gurbuz Gunes ², Doston Samandarov ¹, Azamat Usenov ¹ and Qobil Mukhiddinov ¹

¹ 

Department Food Engineering, Tashkent State Technical University Named After Islam Karimov, Tashkent 100095, Uzbekistan

² 

Department Food Engineering, Istanbul Technical University, 34467 Istanbul, Turkey

• The purpose of this study is to analyze the amount of water-soluble vitamins in the table beet dried in an ultrasonic convective drying unit. An experimental study of table beet was conducted, as a result of which the following optimal drying parameters were determined: initial moisture content was 80–85%, final moisture content 15–17%, thickness 7–8 mm, air speed 1 m/s, ultrasound exposure at 30 kHz, drying temperature 55 °C, drying time 240 min. Drying is recommended to be carried out taking into account these parameters. Dried samples of table beet were chemically analyzed at the Institute of Bioorganic Chemistry of the Academy of Sciences of the Republic of Uzbekistan named after Academician A.S. Sadykov for the content of water-soluble vitamins: B-2—4.58 mg/g; B-6—5.92 mg/g; B-9—21.58 mg/g; B-3—7.02 mg/g; C—24.04 mg/g. Dried beet leaves contain vitamins: B-2—14.68 mg/g; B-6—5.67 mg/g; B-9—171.86 mg/g; B-3—20.49 mg/g; C—110.30 mg/g. Dried beet stems contain vitamins: B-2—4.13 mg/g; B-6—4.99 mg/g; B-9—20.77 mg/g; B-3—2.10 mg/g; C—8.70 mg/g. The amount of water-soluble vitamins was studied by high-performance liquid chromatography. The results of chemical analysis showed that water-soluble vitamins are highly preserved in dried table beets using an ultrasonic-convective drying unit.

4.30. Study of Microbial Fermentations of the Seed of Mediterranean Carob (Ceratonia siliqua, L.)

• Katerina Pyrovolou, Simeon Kouroumlidis, Ioannis Georgios Xaidaras, Alexandros Michail, Spyros Konteles, Eirini Strati, Dimitra Houhoula and Anthimia Batrinou
• Department of Food Science and Technology, University of West Attica, Egaleo, Athens, Greece
• Plant-based foods are essential to the human diet and offer solutions to health, environmental, and economic challenges. Plant proteins, especially when fermented, become more nutritionally complete. Controlled microbial fermentation enhances food quality and safety, suppresses anti-nutritional factors like phytic acid, and enables the development of innovative, functional food products. The objective of this study was to investigate the microbial fermentation of carob seeds (Ceratonia siliqua L.), a xyrophytic plant widely distributed across Mediterranean countries, and their potential applications in the food industry. These seeds were primarily selected and dried and then fermented in lab-scale solid-state type fermentation by lactic acid bacteria, Saccharomyces cerevisiae (yeast) and Aspergillus oryzae (fungus) for four days. The fermented carob seeds were then analyzed for the following: (a) in-vitro digestibility was tested by applying appropriate proteolytic enzymes and measuring pH decrease, (b) concentration of phytic acid was calculated through a biochemical assay that included measurements of free and total phosphorus and (c) protein electrophoresis was applied to analyze the degree of fragmentation of the fermented proteins from carob seeds. The results have shown a mild proteolytic activity exerted by the microbial fermentation of the carob seeds which was evident in the in-vitro digestibility study and the decrease of the concentration of phytic assay. However, protein electrophoretic patterns have not revealed new protein zones as evidence of protein hydrolysis due to seed fermentation. Further research is needed to establish the optimum conditions for solid-state microbial fermentations of carob seeds to obtain a more digestible source of protein.

4.31. Temporal Dynamics of Antioxidant Capacities in Fermentation Brines: Multi-Assay Evidence for Plant-Matrix-Driven Release of Bioactive Compounds and Prospects for Sustainable Functional Food Applications

• Imane Thaifa ¹, Hicham Wahnou ¹, Oumaima Anachad ¹, Wafaa Taha ¹, Imad Fenjar ¹, Houssam Assioui ^1,2, Faiza Bennis ¹ and Fatima Chegdani ¹

¹ 

Laboratory of Integrative Biology, Faculty of Sciences Aïn Chock, Hassan II University of Casablanca, Morocco

² 

Faculté de Médecine, Campus Santé Timone, Aix-Marseille Université, 27, Bd Jean Moulin, 13005 Marseille

• Fermentation is recognized as one of the oldest techniques for preserving and processing food. Lacto-fermented vegetables are increasingly valued as functional foods due to their enrichment with bioactive metabolites released during fermentation. While the solid vegetable fraction is widely studied, fermentation brine remains an underutilized resource despite its potential as a source of health-enhancing compounds. This study aims to examine the temporal changes in antioxidant capacities of fermentation brines.
• The antioxidant potential of brines from fermented vegetables samples prepared from different combinations of cabbage, beetroot, carrot, cucumber, and bell pepper was evaluated during fermentation. Antioxidant activity was measured at different time points (0, 12, 24, 72, 120, 240, 360, and 504 h) using four in vitro tests: ABTS, DPPH, FRAP, and TAC.
• All brine samples showed antioxidant activity, which varied significantly over time. ABTS showed a strong radical scavenging activity, reaching up to 96% on day 21, while DPPH activity was moderate, with a maximum of 54% the same sampling time. The FRAP activity highest absorbance value reached 2.071 on day 21, while TAC peaked at an absorbance value of 1.788 on the same day, confirming the antioxidant potential of brines. These variations can be explained by the plant matrix and the gradual diffusion of bioactive compounds during fermentation. Overall, this study highlights fermentation brines as a promising and lasting source of natural antioxidants. Rather than being perceived as waste, these products could be used as useful ingredients for nutritional and food applications, contributing to sustainable and circular food systems.

4.32. Valorization of Pumpkin Peel: A Sustainable Source of Bioactive Compounds for Nutritional Additive Development

• Amina Ghedjemis
• Department of Science, Teacher Education College of Setif—Messaoud Zeghar, Sétif, Algeria
• The pharmaceutical and nutraceutical industries face the challenge of optimizing resources and reducing waste. In this context, the valorization of by-products from agro-industrial fruit and vegetable processing represents a sustainable and economically relevant strategy. Inadequate disposal of these co-products generates significant environmental and economic impacts, threatening food security.
• This study aimed to evaluate the nutritional and bioactive potential of pumpkin peel to propose a valorization strategy as a food additive. We conducted a comprehensive characterization of its chemical composition, including the quantification of total sugars, lipids, vitamins, mineral salts, and ash. Simultaneously, the content of bioactive compounds (phenolic compounds, carotenoids, and flavonoids) was determined. Antioxidant activity was assessed by a battery of in vitro tests, including total antioxidant capacity (TAC), DPPH and ABTS radical scavenging tests, ferric reducing antioxidant power (FRAP), and the β-carotene bleaching test. Furthermore, antidiabetic activity was explored.
• The obtained results demonstrate that pumpkin peel is a substantial source of vitamins, mineral salts, and bioactive phytochemicals, notably carotenoids and phenolic compounds. This richness confers significant antioxidant and antidiabetic properties to this by-product. These findings suggest a high potential for integrating pumpkin peel into food formulations, particularly those intended for nutritional enrichment and the prevention or management of diabetes, thereby contributing to a circular and sustainable approach in the agro-industry.

5. Applied Physical Science

5.1. A Physical Solution to the Navier–Stokes Regularity Problem

• Miltiadis Karazoupis
• Ministry of Education and Religious Affairs, Department of Primary Education, Marousi, Athens, Greece
• The Navier–Stokes equations, which describe the motion of viscous fluids, form a cornerstone of classical physics and engineering. A central unresolved issue, designated as a Millennium Prize Problem, concerns the global existence and smoothness of their solutions in three dimensions—a quest for global predictability in fluid dynamics. While a complete mathematical proof of regularity remains elusive, the physical reality of non-singular fluid flow is empirically undisputed. This paper addresses this dichotomy by proposing a definitive physical solution, asserting that such singularities are inherently precluded by the very nature of physical fluids. We develop a rigorous analytical framework founded upon eight fundamental principles of physics, including Continuum Emergence, the Second Law of Thermodynamics, and the existence of a Natural Cutoff scale. This framework synthesizes concepts from statistical mechanics, quantum mechanics, and causality to construct a logically closed argument. We demonstrate that these principles, when taken in concert, act as intrinsic regulators that inherently constrain the dynamics of a classical fluid to exclude the formation of finite-time singularities. The analysis shows that phenomena such as infinite velocity gradients or pressure spikes are not merely mathematically challenging but are, in fact, physically impossible within the domain of applicability of the Navier–Stokes equations. This paper concludes that the regularity of solutions is a necessary consequence of the fundamental laws governing physical systems, thereby resolving the problem from a physical, rather than a purely mathematical, standpoint, and identifying the remaining analytical hurdle for mathematics.

5.2. Combining Excel Macros and Time Series to Characterize the Electrical Signal of Strawberry Plants

• Leticia Adriana Ramirez Hernandez ¹, Andrew Alberto Ayala ¹, Juan Martínez Ortiz ¹, Mayra García Reyna ¹, Beatriz Adriana Rodríguez González ², Omar Alejandro Guirette-Barbosa ², Mario Cleva ³, Oscar Cruz-Domínguez ², Marlen Hernández Ortiz ⁴ and Hector Duran-Muñoz ⁵

¹ 

Academic Unit of Mathematics, Autonomous University of Zacatecas. Jdn. Juárez #147, Historic Center, 98000 Zacatecas, Zac, Mexico

² 

Department of Industrial Engineering, Polytechnic University of Zacatecas, 99059 Fresnillo, Mexico

³ 

Facultad Regional Resistencia, Universidad Tecnológica Nacional Formación en Tecnología, Resistencia 1900, Argentina

⁴ 

Academic Unit of Economics. Autonomous University of Zacatecas. Jdn. Juárez #147, Historic Center, 98000 Zacatecas, Zacatecas, Mexico

⁵ 

Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, 98160 Zacatecas, Mexico

• The strawberry plant (Fragaria x ananassa Duchesne) is an important crop in Mexico, representing 7.8% of its production. Therefore, constant efforts are being made to increase its production and improve production techniques. One way to identify whether a plant’s growing conditions are optimal is through measuring the electrical signal that it produces. Furthermore, a plant’s electrical signal can be measured and quantitatively related to the intensity of the stimulating source, such as solar radiation or soil water content. Therefore, in this work, we propose to characterize the electrical signal of the strawberry plant. To perform the measurements, an Arduino data acquisition board was implemented as the measurement system. The experimental methodology consisted of placing an electrode on a leaf near the stem, at a distance of approximately 1 cm. The second electrode was inserted into the stem. The distance between the electrode tips was 2 cm. The electrodes were inserted parallel to the leaf, at a slight angle of 30 degrees, and at a depth of approximately 0.2 cm. Several studies have recommended placing the electrodes closer to points of high physiological activity, suggesting a better response to the electrical signal. This was measured in millivolts. The Holt method and an ARIMA (1,1,0) model were then used to analyze the plant’s electrical signal. Among the most notable results is the characterization of the electrical signal in strawberry plants under different physical conditions.

5.3. PANI-Coated Ni Nanotubes for Supercapacitors: Influence of Pore Size of the Applied Template and Fabrication Process Parameters

• Olena Okhay ^1,2, Boriana Tzaneva ¹ and Alexander Tkach ³

¹ 

Department of Chemistry, Technical University of Sofia, 1000 Sofia, Bulgaria

² 

TEMA-Centre for Mechanical Technology and Automation, Department of Mechanical Engineering, University of Aveiro, 3810-193 Aveiro, Portugal

³ 

CICECO–Aveiro Institute of Materials, Department of Materials and Ceramic Engineering, University of Aveiro, 3810-193 Aveiro, Portugal

• This work presents the fabrication and characterization of hybrid nanostructured electrodes—polyaniline supported on a nickel nanotube array—for use in supercapacitors. Ni nanotubes were prepared using a template, and the effects of the template and preparation parameters are discussed. First, an anodized aluminum oxide (AAO) template was grown in H3PO4 under the same applied field to obtain similar pore sizes and for two different time periods to obtain different AAO thicknesses. Nickel nanotubes (Ni NTs) were prepared chemically on different AAO templates, resulting in Ni NTs of the same diameter but different lengths. A thin Ni layer was then electrodeposited on top of the Ni NTs for use as a metal contact layer in the single electrode during electrochemical tests. Vertically oriented arrays of Ni NTs on a Ni layer were obtained after etching Al and AAO. The resulting Ni NT/Ni structures were used as a substrate for electrodeposition of a polyaniline (PANI) layer at two different applied voltages. The electrodeposition parameters were chosen for homogeneous polymer deposition. The microstructural characterization of the obtained structures was carried out using a scanning electron microscope, and individual Ni nanotubes with different lengths were easily observed. The vertically oriented Ni/Ni nanotube/PANI arrays were tested for electrochemical performance (using cyclic voltammetry and impedance spectroscopy) as individual electrodes for supercapacitors. The capacitance values strongly depended on the length of the tubes and the applied current during PANI deposition and showed the highest values of 325 F/cm² at 10 mV/s.

5.4. A New Stacked-Weibull Machine Learning Model for Reliable Data Prediction with Enhanced Accuracy

• Ahmad Abubakar Abubakar Suleiman ¹, Hanita Daud ¹, Aliyu Ismail Ishaq ² and Suleiman Abubakar Suleiman ³

¹ 

Fundamental and Applied Sciences Department, Universiti Teknologi PETRONAS 32610 Seri Iskandar, Perak Darul Ridzuan, Malaysia

² 

Department of Statistics, Ahmadu Bello University, Zaria 810107, Nigeria

³ 

Kano State Agro—Climatic Resilience in Semi-Arid Landscapes, Kano State Ministry of Water Resources, Kano, Nigeria

• Accurate estimation of petrophysical properties from well log data is paramount for reliable reservoir characterization and informed decision-making in hydrocarbon exploration and production. Conventional methods often struggle with the inherent complexities and non-linear relationships within geological datasets, leading to suboptimal prediction accuracy. To overcome these limitations, we propose a novel hybrid machine learning method that integrates multiple predictive models with a unique residual adjustment strategy. A novel aspect of the methodology involves fitting a Weibull distribution to the residuals of machine learning models, such as random forest, support vector regression, and artificial neural networks as foundational learners. A distinctive aspect of this approach is the application of Weibull distribution analysis to model and subsequently adjust the residuals generated by these individual base models, thereby enhancing individual model predictive accuracy. These adjusted base models were then combined into a stacked ensemble, utilizing a ridge regressor as the final meta-learner to further consolidate their predictive strengths. Performance evaluation, conducted using metrics such as R-squared (R²) and root mean squared error (RMSE), demonstrated that the proposed stacked ensemble model significantly outperformed individual models, achieving a superior predictive capability for the photoelectric factor. The integration of residual analysis through Weibull distribution further contributed to the overall predictive robustness. This research demonstrates the efficacy of advanced ensemble machine learning techniques, particularly when combined with detailed residual distribution analysis, in accurately characterizing complex subsurface properties. The developed method offers a powerful and reliable tool for enhancing reservoir modeling and supporting more effective decision-making in geological applications.

5.5. Deep Learning-Enabled Image-Free Target Recognition in Ghost Imaging at Low Sampling Rates

• Ayesha Abbas and Cao Jie
• School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
• Target recognition in ghost imaging (GI) systems presents substantial challenges at low sample ratios, when traditional approaches need computationally expensive image reconstruction or have poor accuracy. Deep learning (DL) provides a promising solution by allowing direct feature extraction from GI measurements, however existing methods frequently rely on reconstructed images or are ineffective for natural objects. This study provides an image-free DL architecture for high-accuracy target recognition in GI without intermediate reconstruction, which dramatically improves efficiency and performance. We develop an end-to-end neural network architecture for processing raw GI bucket data (single-pixel measurements) and correlating them to predetermined target classes. The model blends spatial feature encoding with attention techniques to improve discriminative performance in noisy, low-sampling environments. Training uses synthetically augmented GI data to promote generalization, whereas testing is done on experimentally captured natural items. The proposed system outperforms standard GI classification algorithms that rely on reconstructed images, achieving over 90% recognition accuracy at sampling ratios. A comparative investigation reveals a >25% increase in accuracy over conventional procedures at the same sample rate. This study presents a viable DL framework for GI-based target recognition, which eliminates the requirement for image reconstruction while maintaining good accuracy at low sampling rates. The findings highlight the potential for image-free processing in computational imaging, which could enable real-time applications in surveillance, biomedical imaging, and remote sensing. Future work will expand the approach to include dynamic situations and 3D target recovery.

5.6. Efficient Nanoparticles Sorting Through an Optofluidic Waveguide Splitter for Early Cancer Diagnosis

• Aurora Elicio, Morteza Maleki, Giuseppe Brunetti and Caterina Ciminelli
• Optoelectronics Laboratory, Department of Electrical and Information Engineering, Politecnico di Bari, 70125 Bari, Italy
• Introduction: Passive optofluidic sorting offers a precise and label-free approach for directing and stabilizing nanoparticles of various sizes along controlled trajectories by leveraging the interplay between optical and hydrodynamic forces. In this work, we analyze a device designed to separate nanoparticles, aiming to reach the exosomal size range (typically 150–200 nm), a challenging task when using passive techniques.
• Methods and results: The system consists of three silicon waveguides embedded in a CYTOP layer and arranged in a three-step directional coupler (power splitting ratio of 4:1) configuration, integrated with a microchannel through which water flows as the carrier fluid, transporting the suspended nanoparticles. Simulations were performed using the three-dimensional Finite Element Method approach, incorporating optical forces, creeping flow dynamics, and particle tracing analysis. Starting from the optical forces acting on nanoparticles of different sizes, we designed the microfluidic channel such that the drag forces counterbalance the optical ones, stabilizing particle positions. By integrating both effects and tracking the particle dynamics within the microchannel, we demonstrate controlled particle deflection and size-selective trajectory steering. Nanospheres with diameters of 500 nm, 600 nm, and 700 nm are effectively separated due to the action of transverse trapping force of 46.46 pN/W, 52,76 pN/W, and 58.26 pN/W, respectively, with input power of 20 mW.
• Conclusions: This configuration optimizes the photonic and microfluidic integration to enhance particle discrimination resolution, showing great potential for biomedical use, especially in early cancer diagnostics, where sorting exosome-sized particles is crucial.

5.7. Engineering Nematic Liquid Crystal 5CB Alignment Using Graphene Oxide Coatings

• Grazia Giuseppina Politano
• Department of Environmental Engineering, University of Calabria, 87036 Rende, CS, Italy
• Liquid crystal (LC) devices traditionally employ polyimide-coated substrates with unidirectional rubbing to establish a stable nematic director orientation. However, graphene-based surfaces offer an alternative alignment strategy due to their unique molecular interactions with nematic liquid crystals (NLCs). The honeycomb lattice of graphene, with a C–C bond length of 1.42 Å, closely matches the 1.40 Å bond length of benzene rings in typical NLC molecules, enabling epitaxial-like interactions. These interactions are dominated by π–π electron stacking between the aromatic cores of the LC molecules and the graphene lattice, producing uniform planar alignment over large areas. The resulting binding energy, estimated between 0.74 and 0.88 eV per molecule, is associated with partial charge transfer and delocalized π-orbital overlap, further stabilizing the LC orientation.
• In this study, we investigated the anchoring properties of nematic 5CB liquid crystal on graphene oxide (GO) thin films using the saturation voltage method (SVM). This approach applies a potential difference to reorient the director from planar to homeotropic, enabling quantitative assessment of anchoring strength. Measurements were performed on sandwich cells with indium–tin oxide electrodes coated with GO and compared with reference cells exhibiting strong (polyimide) and weak (formvar) anchoring. Our results demonstrate that GO substrates significantly influence nematic alignment, highlighting their potential in advanced liquid crystal technologies, including GHz–THz transducers.

5.8. Engineering Properties of Waste Cement-Based Grouts for Geotechnical Applications

• Md Shamim Hasan, A. B. M. Amrul Kaish, Aizat Mohd Taib and Jacob Lim Lok Guan
• Department of Civil Engineering, Faculty of engineering & Built Environment, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia
• In the construction industry, waste cement or shelf-life-expired (SLE) cement shows potential sustainability challenges. In geotechnical applications, grout materials are crucial for filling voids, improving load-bearing capacity, and minimising the differential settlement of the ground. Within the scope of this work, an investigation is conducted into the potential use of SLE cement as a binder in cementitious grout for geotechnical applications that require moderate intensity. The mechanical properties were confirmed through the ASTM standard for flexural and compressive strength. Simultaneously, the fresh properties were evaluated using fresh density and fluidity tests, as per ASTM and European standards. Whereas M2-type grout achieved 4.43 MPa (max.) flexural and 23.54 MPa (max.) compressive strength, M1 grout indicated better results with 5.68 MPa (max.) and 33.51 MPa (max.) at 28 days. Fluidity remained within a considerable limit for the injectable grout. This grout can be used in geotechnical applications such as void filling, settlement control in compressible soils, permeation grouting (seepage cut-off), stabilising the subgrade of light pavements, shallow slope stabilisation, temporary groundwater sealing, and soft soil improvement, where volume stability or permeability reduction is more critical than strength. Through effective resource construction and valorisation, this study reduces cement waste and the consumption of manufactured raw materials, thereby supporting the SDGs on Sustainable Cities and Communities (SDG 11) and Responsible Consumption and Production (SDG 12).

5.9. From an Analytical Formulation to a Digital Image Processing Strategy for Contour Hologram Synthesis

• Alejandra Serrano
• Facultad de Ciencias Quimicas e Ingenieria, Universidad Autonoma de Baja California, Tijuana 22390, Mexico
• The generation of structured light beams with prescribed shapes, such as Bessel or Gaussian beams, is typically achieved through analytical formulations based on known parametric expressions. However, when synthesizing beams with arbitrary, free-form contours, these methods require a laborious process to first analyze and determine the specific parametric equations that compose the desired shape. This traditional, continuous approach is not only computationally intensive but also time consuming, limiting its application in scenarios demanding rapid responses.
• In this work, a novel strategy is proposed, departing entirely from this analytical framework by adopting a digital image processing approach. The method works directly from a binary mask of the target shape, where the algorithm detects the contour edges and performs all subsequent operations in the discrete domain. By replacing symbolic parameterization and continuous integration with discrete differentiation and cumulative integration, it can achieve a substantial reduction in computational complexity. Numerical simulations demonstrate that this new method achieves high fidelity synthesis for a wide range of arbitrary contours, with the resulting light beams accurately tracing the input shapes. This research provides a new pathway for synthesizing complex light beams, transitioning from a time intensive analytical formulation to a streamlined image based process that enhances both computational efficiency and flexibility.

5.10. From Waste to Resource: Reviewing the Role of Alum Sludge in Soil Stabilization and Landfill Liner Systems

• Md Jahangir Hossain, A.B.M Amrul Kaish and Jacob Lim Lok Guan
• Faculty at Fakulti Khejuruteraan dam Alam Bina (FKAB), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Malaysia
• The increasing global demand for clean and safe drinking water has led to the widespread use of aluminum-based coagulants in water treatment plants. These coagulants are essential in the coagulation and flocculation processes but inevitably generate large volumes of alum sludge as a by-product. Traditionally, this sludge is disposed of through landfilling or discharge into natural water bodies practices that pose significant environmental, economic, and health risks. Concerns include the leaching of heavy metals, contamination of soil and water resources, ecological disruption, and financial burdens associated with sludge management and regulatory compliance. Despite these challenges, alum sludge is increasingly being explored for beneficial reuse due to its mineral-rich composition, particularly its content of aluminum hydroxide, silica, and iron oxides. These properties make it suitable for various value-added applications. This review paper focuses specifically on the reuse of alum sludge in the geotechnical sector, especially for soil stabilization and landfill liner enhancement. It evaluates current research, highlights environmental risks such as heavy metal mobility and chemical variability, and examines pretreatment methods like calcination and grinding that improve its engineering performance. By consolidating the latest findings, this review supports sustainable waste management approaches and encourages circular economy practices through the safe and effective utilization of alum sludge.

5.11. Highly Sensitive Biosensing Through Silicon Photonics: Ring Resonators for Early Detection of Viral Infections

• Annabella la Grasta and Francesco Dell’Olio
• Polytechnic University of Bari, 70126 Bari, Italy
• Silicon photonic microring resonators offer an ultra-compact, label-free platform for translating minute refractive-index perturbations into easily tracked resonance shifts. This invited lecture surveys the fundamental physics of all-pass and add-drop configurations, with emphasis on confinement, group index engineering, quality factor management, and the coupled trade-offs that ultimately define sensitivity and detection limits. Within this framework I will contextualise my doctoral contributions, beginning with a systematic comparison of multiple waveguide geometries in SOI technology, including strip, slot, PANDA and S-junction designs, working at 1550 nm. Finite-element modelling and experimental validation identified the slot ring as the most effective refractometric transducer, owing to its enhanced evanescent-field overlap and favourable balance between propagation loss and optical confinement.
• Building on these insights, the research migrated to a silicon nitride platform at 1310 nm, leveraging reduced material absorption to achieve substantially higher quality factors and correspondingly lower intrinsic detection limits under microfluidic operation. Surface functionalization with oriented monoclonal antibodies then converted optimized slot cavities from generic refractometers into robust biosensors. Assays targeting spike and fusion proteins from clinically relevant respiratory viruses demonstrated selective, real-time monitoring of binding kinetics, while preserving specificity in the presence of complex sample matrices.
• Finally, the methodology was validated using unprocessed nasopharyngeal swab extracts, achieving diagnostic concordance with reference molecular techniques and highlighting the robustness of the photonic interface. The talk concludes by outlining routes toward large-scale multiplexing, integrated fluidic handling and fibre-to-chip packaging, positioning microring resonators as a scalable foundation for near-patient infection surveillance and broader lab-on-a-chip applications.

5.12. Integrated Surface Acoustic Wave and Machine Learning System for Microplastic Detection and Filtration

• Ganna Mohamed and Mariam Mohamed
• Sharkya STEM School, Zagazig 44511, Egypt
• This research addresses microplastic contamination in water systems, where particles 5 mm are detected in 80% of global drinking water samples. We aim to develop a cost-effective, high-efficiency filtration system for scalable water treatment applications. This work introduces the first integrated system combining Surface Acoustic Wave (SAW) technology with machine learning algorithms (YOLOv8 and DeepSORT) for microplastic detection and filtration. The novel architecture features graphene-fabricated Interdigital Transducer (IDT) electrodes and replaces conventional lithium niobate with zinc oxide–glass lite substrate integrated with cellulose acetate butyrate, achieving 95% cost reduction while preserving performance. Current filtration technologies struggle to balance high removal efficiency with cost-effectiveness for large-scale deployment. Integrating acoustic manipulation with intelligent detection systems offers targeted, energy-efficient processing solutions. The SAW system uses 9 MHz signals transmitted to graphene-enhanced IDT electrodes, generating Rayleigh waves via the piezoelectric substrate. These waves concentrate microplastics at pressure antinodes, directing particles to a dedicated outlet while purified water exits independently. YOLOv8 and DeepSORT algorithms activate the signal generator only upon microplastic identification, optimizing energy consumption. The system achieves 93% removal efficiency, processing one liter every ten minutes. Machine learning detection shows 10–15% enhancement over baseline methods, identifying particles as small as 0.16 mm. Applications include residential filtration, aquaculture, and industrial processes. This integrated SAW-ML system provides scalable microplastic removal with substantial cost reduction, enabling widespread implementation. Future work includes ML hardware upgrades and real-time monitoring systems.

5.13. Overview on Cytokine Detection at a Single-Molecule Level via Low-Cost Plasmonic Alternative Approaches: Pollen-Based Disposable Biosensors and Microcuvette-Based Device

• Mimimorena Seggio ¹, Francesco Arcadio ², Rosalba Pitruzzella ², Chiara Marzano ², Federica Passeggio ², Stefano Toldo ³, Antonio Abbate ³, Luigi Zeni ², Laura Pasquardini ⁴, Maria Pesavento ⁵ and Nunzio Cennamo ²

¹ 

Department of Engineering, Pegaso University, 80143 Napoli, Italy

² 

Department of Engineering, University of Campania Luigi Vanvitelli, Via Roma 29, 81031 Aversa, Italy

³ 

Berne Cardiovascular Research Center and Division of Cardiovascular Medicine, University of Virginia, Charlottesville, VA 22908, USA

⁴ 

Indivenire Srl, Via Sommarive 18, 38123 Trento, Italy

⁵ 

Optosensing Srl, Via Carlo de Marco 69F, 80137 Naples, Italy

• The ultra-sensitive quantification of cytokines is a critical demand in biomedical diagnostics, particularly in monitoring immune dysregulation, chronic inflammation, and cancer-related signaling. This short overview presents two low-cost, simple, ultra-fast response, and small-size plasmonic point-of-care tests (PoCTs), both specifically developed for the attomolar detection of substances of interest, such as the key interleukins (e.g, IL-17A, IL-1β, and IL-18), demonstrating outstanding analytical performance without the need for amplification protocols.
• The first PoCT developed by Cennamo’s Lab is a microcuvette-based plastic optical fiber (POF) device. The device exploits the multimodal POFs characteristic to change via analyte-receptor binding, the plasmonic phenomena in an SPR D-shaped POF probe arranged in series. The system operates without surface functionalization; indeed, the bioreceptor–analyte interaction occurs freely in solution within modified POFs (the microcuvette). The second Cennamo’s PoCT exploits a nanoplasmonic biosensor chip based on pollen nanostructures covered by gold nanofilms and functionalized with specific antibodies. This architecture enables the excitation of hybrid plasmonic modes, yielding unprecedented sensitivity for cytokine detection via antibodies down to the sub-attomolar range.
• Both sensing approaches exhibit rapid response times (approximately 10 min), high molecular specificity, and excellent reproducibility, making them highly attractive for the real-time monitoring of cytokines in diluted biological fluids or other substances of interest at the single-molecule level via PoCTs.

5.14. Single-Radar Multi-Output Sensing with FMCW Radar and Plastic Waveguides

• Jean-Paul Guillet
• IMS Laboratoiry UMR CNRS 5218, University of Bordeaux, 351 cours de la Libération BAT A31, 33405 TALENCE, France
• We report in this study novel topology of terahertz imaging system, including a single-radar multi-output guided system. We propose the integration of a frequency modulated continuous wave (FMCW) radar at 120 GHz with multiple plastic waveguides allowing to do sensing in reflection mode with multiple ouputs. The FMCW radar, from Indie Semiconductor, which has an antenna on package, is directly coupled to nine HIPS waveguides which are placed front of the package. These different waveguides, made with additive manufacturing HIPS, then move away in three dimensions, each have a different distance and go towards a line on which they are all aligned, to take a measurement in reflectometry. The radar then mesure the reflected signal, and after processing, we extract the time of flight. The difference of each path allow to determine the peak coming from each pixeL This simple and direct coupling allows a compact setup without requiring expensive metal waveguide and couplers. This speed up by nice the imaging measurement which can be useful for FMCW radar imaging application like non-destructive testing, particularly in industrial process and inline control. We propose to present both tinite difference time tomain simulation with CST Mcrowave Studio software, experimental integration and results ans discussion.

5.15. Spectral Density Analysis for Light Excitation of Alkali–Metal Vapors with Variant Time-Dependent Chirping

• Abu Mohamed Alhasan ^1,* and Salah Abdulrhmann ²

¹ 

Physics Department, Faculty of Science, Assiut University, Assiut 71516, Egypt.

² 

Physics Division, Department of Physical Sciences, College of Science, Jazan University, P.O. Box 114, 45142 Jazan, Saudi Arabia

*

Current address: Bağlar Mahallesi, 31500 Ryhanlı, Hatay, Turkey

• The spectroscopic phenomena, such as electromagnetically induced transparency (EIT) and electromagnetically induced absorption (EIA), as well as switching between them, have been extensively studied in the steady-state regime for stationary excitations. The stationary line shape is understood through the imaginary part of the atomic polarization, which accounts for absorption, and the real part, which corresponds to atomic dispersion. In this paper, we adopt a time-dependent approach that allows for varying chirp mechanics through a weak probe field in the Y-type configuration of alkali vapors with two control fields. In this scenario, the absorption power spectrum (APSD) as well as the emission power spectral density (EPSD) of the atomic coherences and populations exhibit distinctive features that are beyond the traditional stationary spectrum. For weak chirping as sigmoid functions, the APSD shows a double-double EIT-like spectrum with a single EIA-like spike at the line center. For short interaction times and controlled active-chirping times, the APSD for coherence between upper levels shows a rich mixed EIA-like and EIT-like spectrum. The EPSD is analyzed through the variation of populations. Finally, the spectrum is analyzed for gain media where the atomic coherences are temporally negative at most times. We provided a fast estimation technique for APSD and EPSD based on the periodogram of signals with chirping, which might be an alternative approach to the quantum regression hypothesis and the physical spectrum.

5.16. Tailoring Adhesion Interfaces for Perfect Absorption and Mechanical Stability of Optical Metasurfaces

• Nurten Koc ¹, Ali Belarouci ² and Serap Aksu ³

¹ 

Graduate School of Sciences and Engineering, Koç University, Istanbul, 34450 Rumelifeneri Yolu, Sarıyer, Turkey

² 

Univ Lyon, ECL, INSA Lyon, CNRS, UCBL, CPE Lyon, INL, UMR5270, Lyon, 69130 Ecully, France

³ 

Physics Department, College of Sciences, Koç University, Istanbul, 34450 Rumelifeneri Yolu, Sarıyer, Turkey

• Gold film-based zero-reflection metasurfaces show significant potential for advanced optical applications, including topologically controlled laser-like thermal emission. However, most proof-of-concept studies overlook the mechanical stability provided by adhesion layers, frequently refraining from their use since they disrupt the zero-reflection condition and degrade optical performance.
• In this work, we aim to offer aluminium (Al) as a superior adhesion material for thin gold films that preserves both reflection intensity and resonance quality with high mechanical stability. We conclude that Al adhesion layer does not deteriorate the optical performance and provides near-electric field responses comparable to devices without adhesion layers. The advanced optical properties brought by Al are further demonstrated through the ultrasensitive detection of protein monolayers with higher sensitivities compared to other adhesive metals. We show that the metasurfaces maintain structural integrity under harsh water flow (50 uL/min) and sonication (40 kHz, 180 W) without delamination. More importantly, we conclude that the percolation threshold and native oxide formation play significant role for conserving the optical quality of devices. Our perspective is to offer a trusted pathway for transferring the exceptional optical properties of gold metal thin films to daily life usage. We present one of the best available solutions that simultaneously brings high robustness and high optical quality.