Applied Sciences

93 pages, 6700 KB

Open AccessReview

Artificial Vision in Renewable Photovoltaic Systems: A Review and Vision of Specific Applications and Technologies

by Tito G. Amaral, Armando Cordeiro and Vitor Fernão Pires

Appl. Sci. 2025, 15(24), 13285; https://doi.org/10.3390/app152413285 - 18 Dec 2025

Cited by 2 | Viewed by 1604

Renewable energy resources have become extremely important in the current context of air pollution and the production of significant amounts of greenhouse gas emissions that contribute to global warming. One of the most important renewable energy sources that has shown the highest growth [...] Read more.

Renewable energy resources have become extremely important in the current context of air pollution and the production of significant amounts of greenhouse gas emissions that contribute to global warming. One of the most important renewable energy sources that has shown the highest growth in recent years is photovoltaic (PV) systems. Due to their significance, this research presents a review of the applications in which artificial computer vision can be used in photovoltaic systems. From the results presented in this review, it will be evident that artificial vision can be applied for several different purposes. The advantages of using this technique will also be highlighted. Additionally, a systematic literature review is presented on the research associated with this topic. Through this review, it will be evident that many advanced algorithms related to image acquisition equipment have been proposed to ensure high reliability and fast results. This review does not merely focus on a specific topic or algorithms associated with image processing applied to photovoltaic systems. Rather, this work presents a broad and comprehensive review detailing all viable applications and associated computer vision technologies that can be deployed within these systems. Besides that, the review will clearly specify which work one is based on public datasets. To allow future reproducibility or research, the links to all public datasets utilized in the works based on them are included. Full article

(This article belongs to the Special Issue Feature Review Papers in Energy Science and Technology)

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28 pages, 2632 KB

Open AccessArticle

Coordinated Truck–Shovel Allocation for Heterogeneous Diesel and Electric Truck Fleets in Open-Pit Mining Using an Improved Multi-Objective Particle Swarm Optimization Algorithm

by Gang Chen, Yuning Shi, Huabo Lu, Xuaner Lin and Xiaolei Ma

Appl. Sci. 2025, 15(24), 13284; https://doi.org/10.3390/app152413284 - 18 Dec 2025

Viewed by 1147

Abstract

Efficient truck–shovel allocation is essential for optimizing open-pit mining operations, but the integration of heterogeneous diesel and electric fleets introduces complex scheduling challenges, including charging requirements, range limitations, and equipment capacity constraints. This study proposes an integrated allocation framework tailored to heterogeneous fleets, [...] Read more.

Efficient truck–shovel allocation is essential for optimizing open-pit mining operations, but the integration of heterogeneous diesel and electric fleets introduces complex scheduling challenges, including charging requirements, range limitations, and equipment capacity constraints. This study proposes an integrated allocation framework tailored to heterogeneous fleets, formulating a multi-objective optimization model that minimizes transportation cost and waiting time under realistic constraints. An enhanced multi-objective particle swarm optimization algorithm with adaptive penalty mechanisms is developed, providing superior convergence and computational efficiency compared to traditional methods. A case study demonstrates that heterogeneous fleets achieve a better trade-off, with a balanced fleet configuration reducing transportation cost by 26.1% and waiting time by 19.2% compared to pure diesel and electric fleets, respectively. Sensitivity analyses reveal that fluctuations in fuel and electricity prices reshape the trade-off, while faster charging enhances electric truck competitiveness but increases diesel idle time. These findings offer practical insights for configuring heterogeneous fleets and adapting scheduling strategies in dynamic energy and technology environments, supporting sustainable mining operations. Full article

(This article belongs to the Section Transportation and Future Mobility)

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19 pages, 3290 KB

Open AccessArticle

Switching-Based Cooperative Avoidance Control for Multi-Agent Quadrotor Dynamic Systems in Dense Environments

by Wenxue Zhang, Chunlei Zhao, Dongliang Yang and Dušan M. Stipanović

Appl. Sci. 2025, 15(24), 13283; https://doi.org/10.3390/app152413283 - 18 Dec 2025

Viewed by 736

Abstract

This paper presents a control framework for multi-unmanned aerial vehicle systems that achieves safe and cooperative navigation in complex environments through a unified collision avoidance and trajectory guidance strategy. The principal innovation lies in the incorporation of velocity information into the design of [...] Read more.

This paper presents a control framework for multi-unmanned aerial vehicle systems that achieves safe and cooperative navigation in complex environments through a unified collision avoidance and trajectory guidance strategy. The principal innovation lies in the incorporation of velocity information into the design of a switching function, enabling more accurate assessment of collision risk and effectively reducing system conservativeness. Building upon this, an adaptive trajectory guidance mechanism is developed using collision avoidance information to ensure safe motion coordination among the vehicles. In addition, a closed-form solution for the dynamic system is derived, and its safety and stability are rigorously established through Lyapunov-based analysis. The effectiveness of the proposed framework is validated through simulation studies conducted on the MATLAB/Simulink platform (version R2020b), confirming reliable cooperative navigation in densely cluttered environments and guaranteeing dynamic safety. Full article

(This article belongs to the Special Issue Future Horizons in Multi-Agent Systems: Pioneering Trends and Breakthrough Innovations)

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19 pages, 5147 KB

Open AccessArticle

Triple-Passive Harmonic Suppression Method for Delta-Connected Rectifier to Reduce the Harmonic Content on the Grid Side

by Shuang Rong, Xueting Lei, Fangang Meng, Bowen Gu, Zexin Mu, Jiapeng Cui, Kailai Ye, Shengren Yong, Pengju Zhang and Jianan Guan

Appl. Sci. 2025, 15(24), 13282; https://doi.org/10.3390/app152413282 - 18 Dec 2025

Cited by 1 | Viewed by 612

Abstract

With the development of distributed energy sources such as photovoltaic and wind power, power grids have imposed increasingly higher requirements on power quality. As common nonlinear loads in power grids, multi-pulse rectifiers (MPRs) inject significant harmonics into the grid side. To reduce harmonic [...] Read more.

With the development of distributed energy sources such as photovoltaic and wind power, power grids have imposed increasingly higher requirements on power quality. As common nonlinear loads in power grids, multi-pulse rectifiers (MPRs) inject significant harmonics into the grid side. To reduce harmonic pollution at the source, this paper proposes a novel triple-passive harmonic suppression method to reduce the input current harmonics of MPRs. The proposed 48-pulse rectifier comprises a main circuit based on delta-connected auto-transformer (DCT) and a triple-passive harmonic suppression circuit (TPHSC). The TPHSC consists of two interphase reactors (IPRs) and eight diodes. Based on Kirchhoff’s Current Law (KCL), the output currents of the main circuit are calculated, and the operating modes of the TPHSC are analyzed. From the main circuit’s output currents and the DCT topology, the rectifier’s input currents are derived, and the optimal turns ratio of the IPRs for minimizing the input current total harmonic distortion (THD) is determined. The total capacity of the IPRs accounts for only 2.3% of the output load power. Experimental results show that the measured input current THD is close to the theoretical value of 3.8%. Overall, the proposed rectifier offers a cost-effective solution with stronger harmonic suppression capability, making it suitable for applications requiring low grid harmonic pollution. Full article

(This article belongs to the Section Electrical, Electronics and Communications Engineering)

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15 pages, 3527 KB

Open AccessArticle

Interfacial Evaluation of Wind Blade Carbon Spar-Cap Depending on Elimination Method of Intermediate Medium

by Jeong-Wan Park, Ha-Seung Park, Pyeong-Su Shin, Ki-Weon Kang and Sang-Il Lee

Appl. Sci. 2025, 15(24), 13281; https://doi.org/10.3390/app152413281 - 18 Dec 2025

Viewed by 693

Abstract

An Ultrasonic Test (UT), a type of non-destructive test, is used to inspect the manufacturing integrity of carbon spar-caps of wind blades. When performing a UT, an intermediate medium is used to improve the signal detection ability between the inspection target and the [...] Read more.

An Ultrasonic Test (UT), a type of non-destructive test, is used to inspect the manufacturing integrity of carbon spar-caps of wind blades. When performing a UT, an intermediate medium is used to improve the signal detection ability between the inspection target and the probe. However, if the intermediate-medium residue is not removed, it acts as a contaminant in the interface between the spar-cap and the blade skin. This has a negative effect on the adhesion characteristics. A quantitative method is required for removing the intermediate medium and peel ply after the UT. After the UT, the interfacial characteristics of the spar-cap surface are examined according to the method of removing the intermediate medium in this study. The static contact angle and the work of adhesion (W_a) were measured according to various surface treatment conditions. In addition, shear strength of the Carbon Fiber-Reinforced Plastic (CFRP) spar-cap was evaluated by the lap shear test. An optimized method of peel-ply removal combined with an intermediate medium was found in this study. An optimal guideline for intermediate-medium treatment could be proposed when evaluating the manufacturing integrity of real wind blade spar-caps using UT. Full article

(This article belongs to the Special Issue Optimized Design and Analysis of Mechanical Structure)

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13 pages, 2655 KB

Open AccessArticle

Valorization of Grapefruit Juice Extraction Residue Using Pectin Extraction, Cellulose Purification, and Sonication

by Marina Ishida, Alisa Pattarapisitporn, Noriko Ryuda and Seiji Noma

Appl. Sci. 2025, 15(24), 13280; https://doi.org/10.3390/app152413280 - 18 Dec 2025

Viewed by 862

Abstract

The effects of pectin extraction, cellulose purification, and sonication on the juice extraction residue from grapefruit were investigated. Pectin extraction using pressurized carbon dioxide (pCO₂) in a sodium oxalate solution (U-OX) lowered the cellulose content and increased the hemicellulose and lignin [...] Read more.

The effects of pectin extraction, cellulose purification, and sonication on the juice extraction residue from grapefruit were investigated. Pectin extraction using pressurized carbon dioxide (pCO₂) in a sodium oxalate solution (U-OX) lowered the cellulose content and increased the hemicellulose and lignin contents, whereas pectin extraction in deionized water (U-DW) did not affect these contents. Pectin extraction and cellulose purification induced hydrolysis and removal of non-crystalline cellulose regions. The sonication of the purified cellulose samples formed fiber-like structures with widths of <100 nm on their surfaces. The cellulose purification process increased the surface charge and formed a gel-like structure with increased hardness, adhesiveness, and film structure. These processes enhance the absorption of amphiphilic dyes, although to a lesser extent than that of the untreated juice extraction residue (UJR) after sonication. Before sonication, UJR adsorbed cationic dyes, whereas after, UJR adsorbed both polar and nonpolar dyes. These results suggest that juice residue could be used as a biomaterial with diverse potential applications. Full article

(This article belongs to the Section Agricultural Science and Technology)

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Graphical abstract

23 pages, 2982 KB

Open AccessArticle

The Creation of Alternatives for the Built-in Apps in the Android System to Increase Productivity

by Roland Szabo

Appl. Sci. 2025, 15(24), 13279; https://doi.org/10.3390/app152413279 - 18 Dec 2025

Viewed by 691

Abstract

This paper aims to present the development, challenges, and obstacles faced when creating two reduced complexity utility applications for Android mobile devices. The purpose of this paper is to present the challenges behind the development of these applications and the issues faced during [...] Read more.

This paper aims to present the development, challenges, and obstacles faced when creating two reduced complexity utility applications for Android mobile devices. The purpose of this paper is to present the challenges behind the development of these applications and the issues faced during their creation. The first app is a simplified gallery app that tries to be as simple as possible. It only has the functionality of a photo gallery; it loads images and videos—nothing less, nothing more. The second app is the simplified file manager app, which will perform only the basic functions of a file manager (Details, New Folder, Cut, Copy, Paste, Rename, Share, and Delete). These apps were also made because of the countless functionalities that are not even used. Full article

(This article belongs to the Special Issue Advances in Mobile Applications Related to Human–Computer Interaction (HCI))

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18 pages, 2185 KB

Open AccessArticle

Coastal Environments: Threats to Investment Processes in the Coastal Area

by Dariusz Kloskowski, Norbert Chamier-Gliszczynski and Maciej Niedziela

Appl. Sci. 2025, 15(24), 13278; https://doi.org/10.3390/app152413278 - 18 Dec 2025

Viewed by 661

Abstract

One of the key problems humanity faces in this age of profound digitalization is globalization-related threats, which no longer affect just one country but pose a threat to a very large area, encompassing several or even a dozen countries, or, in the case [...] Read more.

One of the key problems humanity faces in this age of profound digitalization is globalization-related threats, which no longer affect just one country but pose a threat to a very large area, encompassing several or even a dozen countries, or, in the case of global warming, a threat to all of humanity worldwide. This topic inspired the investigation and verification of this threat in the Baltic Sea, along with other threats operating in the Baltic Sea region. This topic is highly topical, as estimates from maritime institutions indicate that the rate of sea level rise is an irreversible process, which, when combined with other threats, could lead to the degradation of the sea and the population living in the coastal zone. This led to the delegation clarifying the main objective of the article: to demonstrate the impact of potential global threats on the investment process in the Polish coastal belt. Based on this, an analysis of threats in the Baltic Sea region was conducted, preceded by a review of the literature and data from online resources, including data from industry portals in the maritime sector. This article presents a simulation of erosion-accumulation changes in selected areas of Poland’s Southern Baltic coast, focusing on the coastal real estate market and indicating the propensity to invest in these areas. Simulating erosion changes, using a cartographic base with a generated digital terrain model and interpolation tools to visualize the changes, represents an innovative approach to issues related to the outflow of investment land in the real estate market. This emphasizes the directionality of land changes, thus providing a predictive tool for decision-making and spatial planning in the coastal area. Full article

(This article belongs to the Special Issue Advances in Coastal Environments and Renewable Energy)

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22 pages, 10870 KB

Open AccessArticle

Fracture Prediction Based on a Complex Lithology Fracture Facies Model: A Case Study from the Linxing Area, Ordos Basin

by Yangyang Zhao, Zhicheng Ren, Xiaoming Chen, Wenxiang He, Zhixuan Zhang, Zijian Wei and Yong Hu

Appl. Sci. 2025, 15(24), 13277; https://doi.org/10.3390/app152413277 - 18 Dec 2025

Viewed by 623

Abstract

In the Ordos Basin, the lengths of cores are disproportionate to image logging data (1:9) and fracture research is difficult because of their complex lithology and fracture patterns. Based on the characteristics of conventional logging and cores, this paper describes the color, shape, [...] Read more.

In the Ordos Basin, the lengths of cores are disproportionate to image logging data (1:9) and fracture research is difficult because of their complex lithology and fracture patterns. Based on the characteristics of conventional logging and cores, this paper describes the color, shape, geophysical characteristics and geological features of the basin to establish an image recognition template and to identify nine distinct lithologies. The genesis, type, occurrence, opening mode, cutting depth, host lithology, density and tectonic stress of the fractures are used to define four types of fracture facies (bedding fracture facies, N100° tectonic fracture facies, N10° tectonic fracture facies and coal fracture facies) and to build four models. The comprehensive coherence among the neural network results, curvatures, ant bodies, lithologies, and thicknesses was used to predict the type of different fracture facies. The results show that the fracture prediction model fully reflects the genesis of the cracks and influencing factors and provides insights into optimal areas for future exploration and development. Full article

(This article belongs to the Special Issue Technologies and Methods for Exploitation of Geological Resources, 2nd Edition)

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23 pages, 2581 KB

Open AccessArticle

A Multistage Manufacturing Process Path Planning Method Based on AEC-FU Hybrid Decision-Making

by Wanlu Chen and Xinqin Gao

Appl. Sci. 2025, 15(24), 13276; https://doi.org/10.3390/app152413276 - 18 Dec 2025

Viewed by 899

Abstract

As product complexity and customization levels continue to rise in high-end manufacturing, optimizing and controlling multistage manufacturing processes (MMPs) presents growing challenges. However, existing MMP research has largely focused on optimizing relatively fixed process routes, while limited attention has been paid to the [...] Read more.

As product complexity and customization levels continue to rise in high-end manufacturing, optimizing and controlling multistage manufacturing processes (MMPs) presents growing challenges. However, existing MMP research has largely focused on optimizing relatively fixed process routes, while limited attention has been paid to the route selection problem itself, particularly the global selection of process routes under real-world conditions where MMPs stages are mutually coupled and characterized by uncertainty. Therefore, the present study focuses on the fundamental challenge of process route decision-making for complex products within MMPs. A hybrid decision model is developed that incorporates expert knowledge and explicitly quantifies uncertainty arising from decision inconsistency and linguistic ambiguity. The proposed model consists of three main components: expert weighting, criterion weighting, and comprehensive ranking of process schemes. Expert and criterion weights are derived using the Enhanced Analytic Hierarchy Process (EAHP) to address inconsistency in expert judgments, while the ranking of alternatives is performed using a novel Combined Compromise Solution (CoCoSo) rule within an Interval Type-2 Fuzzy Sets (IT2FS) linguistic environment. Furthermore, the effectiveness of the proposed framework is validated through a case study on the multistage manufacturing process of compact aerospace heat exchangers. The results demonstrate that the proposed approach provides effective decision support for selecting robust process schemes during the initial planning phase of MMPs. Full article

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18 pages, 2333 KB

Open AccessArticle

Self-Supervised Representation Learning for EEG-Based Detection of Neurodegenerative Diseases

by Federico Del Pup, Louis Fabrice Tshimanga, Andrea Zanola, Luca Taffarello, Elisa Tentori and Manfredo Atzori

Appl. Sci. 2025, 15(24), 13275; https://doi.org/10.3390/app152413275 - 18 Dec 2025

Cited by 2 | Viewed by 1435

Abstract

Electroencephalography (EEG) is an important noninvasive diagnostic tool for detecting neurodegenerative disorders. In this context, EEG-based deep learning models show promise due to their ability to capture nonlinear brain dynamics but often suffer from poor generalizability caused by high inter-subject variability. Self-supervised learning [...] Read more.

Electroencephalography (EEG) is an important noninvasive diagnostic tool for detecting neurodegenerative disorders. In this context, EEG-based deep learning models show promise due to their ability to capture nonlinear brain dynamics but often suffer from poor generalizability caused by high inter-subject variability. Self-supervised learning (SSL) offers a promising solution by enabling models to learn robust representations from large unlabeled datasets. This study introduces a double-masking representation learning framework for EEG analysis. Using data aggregated from eight multi-center datasets (3156 subjects; 439 h of EEG recordings), a hybrid convolutional-transformer model (TransformEEG) is pretrained to enhance generalization in neurodegenerative disease classification, focusing on Parkinson’s and Alzheimer’s diseases. This approach combines phase-swap data augmentation, designed to facilitate the learning of EEG phase-amplitude coupling, with a double-masking function that operates at both the signal and the transformer’s token levels. The pretrained model was evaluated against a fully supervised baseline using Monte Carlo cross-validation with 100 splits across three public pathology detection datasets. Pretraining led to consistent improvements in both median balanced accuracy and Inter-Quartile Range (IQR) across all fine-tuning datasets. Compared to the fully supervised baseline, the proposed approach increases median balanced accuracy by 2.8% for Parkinson’s disease detection and by 4.2% for Alzheimer’s disease detection, while also reducing performance variability across 100 Monte Carlo splits. These results demonstrate that SSL can enhance EEG deep learning performance, though achieving robust generalization in clinical applications remains an open research challenge. Full article

(This article belongs to the Section Biomedical Engineering)

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15 pages, 2362 KB

Open AccessArticle

Seismic Vulnerability of Single-Story Precast Industrial Buildings in Romania

by Viorel Popa, Eugen Lozincă, Dietlinde Köber and Mihai Pavel

Appl. Sci. 2025, 15(24), 13274; https://doi.org/10.3390/app152413274 - 18 Dec 2025

Cited by 1 | Viewed by 885

Abstract

The paper investigates the seismic vulnerability of single-story precast industrial buildings constructed in Romania during the 1970s, with particular reference to the damage observed following the 1977 Romanian earthquake. More than 800 structures were analytically assessed using a displacement-based evaluation procedure grounded in [...] Read more.

The paper investigates the seismic vulnerability of single-story precast industrial buildings constructed in Romania during the 1970s, with particular reference to the damage observed following the 1977 Romanian earthquake. More than 800 structures were analytically assessed using a displacement-based evaluation procedure grounded in their original design specifications. Several displacement capacity models for flexure-controlled concrete columns were applied, and their suitability for the analyzed buildings is critically discussed. The study also includes a detailed case study that illustrates the practical application of the assessment methodology and highlights specific structural behaviors under seismic loading. The results demonstrate that the displacement-based assessment provides realistic predictions of seismic performance, consistent with observations from similar buildings constructed after the 1977 Vrancea earthquake. The conclusions indicate that the analyzed buildings generally exhibit favorable seismic behavior, with flexural hinging preceding shear failure and displacement-based methods offering more realistic and less conservative assessments than traditional force-based approaches. The scientific contribution of this work lies in using a comprehensive framework for evaluating the seismic response of existing precast industrial structures, offering insights into the effectiveness of different column capacity models, and establishing a foundation for future research on retrofitting strategies and the interaction of structural and non-structural components under seismic actions. Full article

(This article belongs to the Topic Degradation, Repair and Rehabilitation of Reinforced Concrete Structures)

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22 pages, 5177 KB

Open AccessArticle

Generalizations of Choquet-like Integrals by Restricted Dissimilarity Functions Applied to Multi-Channel Edge Detection Problems

by Miqueias Amorim, Giancarlo Lucca, Bruno L. Dalmazo, Cedric Marco-Detchart and Graçaliz Pereira Dimuro

Appl. Sci. 2025, 15(24), 13273; https://doi.org/10.3390/app152413273 - 18 Dec 2025

Cited by 2 | Viewed by 1854

Abstract

Edge detection is a fundamental component of vision tasks, yet the fusion stage that combines multi-cue evidence has received limited attention. We explore the use of a family of Choquet-based fusion operators generalised by restricted dissimilarity functions for robust, training-free, single-scale edge detection [...] Read more.

Edge detection is a fundamental component of vision tasks, yet the fusion stage that combines multi-cue evidence has received limited attention. We explore the use of a family of Choquet-based fusion operators generalised by restricted dissimilarity functions for robust, training-free, single-scale edge detection on the BSDS500 dataset. Local cues are extracted from eight connected neighbours after Gaussian or Gravitational smoothing; ordered samples are aggregated with a fuzzy power measure using three operator families: d-CF, d-XC, and d-CC integrals. Binary edge maps are obtained through non-maximum suppression and Rosin thresholding. Evaluation follows the Bezdek framework for edge detection, utilising the Estrada–Jepson correspondence, and extracts precision, recall, and the F-score. All inferential statistics are restricted to within-family comparisons among our variants. The main results are that gravitational smoothing consistently improves performance, and the best performance is achieved with the absolute-difference restricted dissimilarity under gravitational smoothing. Under Gaussian smoothing, the best performance is obtained with the modulus of the squared difference and with the squared difference of the roots. These findings indicate that restricted-dissimilarity-based Choquet operators, particularly d-CC integrals with gravitational smoothing, form a straightforward and interpretable fusion mechanism, motivating further analysis of component interactions and multi-scale extensions. Full article

(This article belongs to the Special Issue Image Processing: Technologies, Methods, Apparatus)

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26 pages, 7907 KB

Open AccessReview

Non-Destructive Testing for Conveyor Belt Monitoring and Diagnostics: A Review

by Aleksandra Rzeszowska, Ryszard Błażej and Leszek Jurdziak

Appl. Sci. 2025, 15(24), 13272; https://doi.org/10.3390/app152413272 - 18 Dec 2025

Cited by 9 | Viewed by 3340

Abstract

Conveyor belts are among the most critical components of material transport systems across various industrial sectors, including mining, energy, cement production, metallurgy, and logistics. Their reliability directly affects the continuity and operational costs. Traditional methods for assessing belt condition often require downtime, are [...] Read more.

Conveyor belts are among the most critical components of material transport systems across various industrial sectors, including mining, energy, cement production, metallurgy, and logistics. Their reliability directly affects the continuity and operational costs. Traditional methods for assessing belt condition often require downtime, are labor-intensive, and involve a degree of subjectivity. In recent years, there has been a growing interest in non-destructive and remote diagnostic techniques that enable continuous and automated condition monitoring. This paper provides a comprehensive review of current diagnostic solutions, including machine vision systems, infrared thermography, ultrasonic and acoustic techniques, magnetic inspection methods, vibration sensors, and modern approaches based on radar and hyperspectral imaging. Particular attention is paid to the integration of measurement systems with artificial intelligence algorithms for automated damage detection, classification, and failure prediction. The advantages and limitations of each method are discussed, along with the perspectives for future development, such as digital twin concepts and predictive maintenance. The review aims to present recent trends in non-invasive diagnostics of conveyor belts using remote and non-destructive testing techniques, and to identify research directions that can enhance the reliability and efficiency of industrial transport systems. Full article

(This article belongs to the Special Issue Nondestructive Testing and Metrology for Advanced Manufacturing)

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31 pages, 8215 KB

Open AccessArticle

ANSYS/LS-DYNA Simulation and Experimental Study of a Corrugated Hob-Type Laver Harvesting Device

by Yizhi Chang, Shuai Lv, Yazhou Yang, Shang Ni, Bin Xu, Guochen Zhang, Xiuchen Li, Hanbing Zhang, Qian Zhang, Hangqi Li, Hao Wu and Gang Mu

Appl. Sci. 2025, 15(24), 13271; https://doi.org/10.3390/app152413271 - 18 Dec 2025

Viewed by 734

Abstract

Harvesting of laver is an important link in the laver culture chain, and a new type of corrugated harvesting blade with a curved edge angle was designed to solve the problems of low cutting ratio in laver harvesting. The mechanical model of the [...] Read more.

Harvesting of laver is an important link in the laver culture chain, and a new type of corrugated harvesting blade with a curved edge angle was designed to solve the problems of low cutting ratio in laver harvesting. The mechanical model of the corrugated blade cutting laver was established to elucidate the dynamic characteristics of laver cutting under single-point support. Based on the measured biomechanical characteristic parameters of Porphyra yezoensis, a rigid-flexible coupling model of laver harvesting was established based on ANSYS/LS-DYNA2022R2. The Box–Behnken design (BBD) test method was used to study the influence of the main structural parameters of the corrugated blade on the harvesting of laver, and the optimal structural parameter combinations of the corrugated blade were determined as follows: a slip angle of 21°, blade inclination angle of 106°, and curved edge angle of 15°; the slip-cutting mowing force of the laver was 11.18 N and the tensile force was 1.4 N. A bench test was completed, and the results showed that the corrugated blade could be used for harvesting laver. The results showed that the average loss rate of the harvesting equipment was 1.85% and the average net recovery rate was 98.75% when the corrugated blade rotational speed was 900 rpm and the boat speed was 0.71 m/s; compared to the traditional straight-blade hob-type harvesting machine, the cutting force on laver has increased by 45.26%, and the tensile force has decreased by 68.35%, which satisfied the requirements of laver harvesting. This study provides theoretical and simulation model references for the design, analysis, and optimization of laver harvesting equipment. Full article

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26 pages, 1908 KB

Open AccessArticle

Carbon-Rich Sediment Amendments and Aging: Effects on Desorption and Maize Phytoextraction of 4-Octylphenol and 4-Nonylphenol

by Slaven Tenodi, Snežana Maletić, Marijana Kragulj Isakovski, Aleksandra Tubić, Srđan Rončević, Kristiana Zrnić Tenodi and Jasmina Agbaba

Appl. Sci. 2025, 15(24), 13270; https://doi.org/10.3390/app152413270 - 18 Dec 2025

Cited by 1 | Viewed by 861

Abstract

Carbonaceous amendments are widely proposed to sequester hydrophobic organic contaminants in sediments, yet their effectiveness for alkylphenolic endocrine disruptors in organic-rich freshwater systems—and its time dependence—remains poorly constrained. Here, we compared activated carbon (AC), biochar (BC), and humic compost (HC) for reducing desorption [...] Read more.

Carbonaceous amendments are widely proposed to sequester hydrophobic organic contaminants in sediments, yet their effectiveness for alkylphenolic endocrine disruptors in organic-rich freshwater systems—and its time dependence—remains poorly constrained. Here, we compared activated carbon (AC), biochar (BC), and humic compost (HC) for reducing desorption and maize phytoexposure to 4-octylphenol (4-OP) and 4-nonylphenol (4-NP) in canal sediment from the Jegrička River. Sediment was spiked (~1.1 mg kg⁻¹ 4-OP; 1.2 mg kg⁻¹ 4-NP), amended with 0.5–10% (w/w) AC, BC, or HC, and aged for up to 180 days prior to multi-step XAD-4 desorption tests. A two-compartment first-order model resolved fast- and slow-desorbing pools, while a 10-day maize (Zea mays L.) pot experiment quantified early phytoextraction and sediment–plant–loss mass balances for AC and HC treatments. The unamended sediment exhibited high operational bioavailability: ~98% of both alkylphenols were XAD-4-extractable, and 83–89% of the desorbable pool was released within 24 h. AC produced the most rapid immobilization; at 0.5–1%, it halved XAD-4-extractable fractions within weeks and reduced them to near-zero within months, whereas BC and HC achieved comparable reductions only after longer aging. Plant uptake was a minor sink: in the control, shoots accumulated ~21 µg kg⁻¹ sediment of 4-OP and 65 µg kg⁻¹ sediment of 4-NP (≈2% and 5% of the initial inventory). HC generally lowered uptake, and high AC doses kept plant burdens consistently low. Overall, amendment-enhanced sorption and sequestration dominated attenuation, with AC delivering the fastest risk reduction and HC representing a more plant-compatible amendment option. Full article

(This article belongs to the Section Environmental Sciences)

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13 pages, 1720 KB

Open AccessArticle

The Effect of Water Contamination on the Thermal Oxidation Stability of Complex Calcium Greases Thickened with Overbased Calcium Sulfonate

by Ewa Barglik, Agnieszka Skibinska, Wojciech Krasodomski and Maciej Paszkowski

Appl. Sci. 2025, 15(24), 13269; https://doi.org/10.3390/app152413269 - 18 Dec 2025

Viewed by 787

Abstract

Sulfonate greases, which have excellent performance characteristics—high dropping point, good mechanical and structural stability, water resistance, high thermal oxidation stability, and good anticorrosive properties—are widely used in various industries. The greases are exposed to water during operation: moisture in the environment, water-based coolants, [...] Read more.

Sulfonate greases, which have excellent performance characteristics—high dropping point, good mechanical and structural stability, water resistance, high thermal oxidation stability, and good anticorrosive properties—are widely used in various industries. The greases are exposed to water during operation: moisture in the environment, water-based coolants, operation in the presence of water vapor, etc. Water can affect the properties of the greases during operation. The subject of the study was a commercial complex grease thickened with overbased calcium sulfonate, with a water additive in amounts ranging from 1% to 50% by weight. This paper presents two standardized methods for testing the thermal oxidation stability of lubricants—according to ASTM D942 and ASTM D8206, in standard programs, and with an extension of oxidation duration to 100 h and a temperature increase to 100 °C. The aim of the study was to investigate how the addition of water affected the thermal oxidation stability of this grease. The presentation concludes with an analysis of FTIR differential spectra. The tests showed that as the water content in the grease samples increased, its resistance to oxidation decreased. Water also caused a change in the consistency of the grease at a concentration of just 1% by weight. Mechanical stress affected the thermal oxidation stability of the grease tested. Each method presented separate mechanisms of oxidation initiation, including different sample quantities during the test, the presence of water in the classic method, and different contact with oxygen as a catalyst for this reaction. The work provided a comprehensive presentation of the possibilities for testing the thermal oxidation resistance of greases and a detailed comparison of the two methods. Full article

(This article belongs to the Section Materials Science and Engineering)

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19 pages, 9103 KB

Open AccessArticle

Sustainable Investigation on Metal Coin Clipped Blank, Using 3D Modeling and FEM Analysis

by Cornel Cătălin Gavrilă and Mihai Tiberiu Lateş

Appl. Sci. 2025, 15(24), 13268; https://doi.org/10.3390/app152413268 - 18 Dec 2025

Viewed by 793

Abstract

The modern coinage industry ensures dimensional and weight precision, as well as improved surface quality, for its products. The speed of coin mass production requires increased performance for used machines and tools. Despite these, error incidence cannot be excluded. Some of these errors [...] Read more.

The modern coinage industry ensures dimensional and weight precision, as well as improved surface quality, for its products. The speed of coin mass production requires increased performance for used machines and tools. Despite these, error incidence cannot be excluded. Some of these errors are recorded inside the punching machine and generate clipped blank disks; on their turn, those malformed disks lead to the clipped coins. In the first part, the paper presents the premises underlying the appearance of clipped blanks. There are some exemplified coins having different types of clips: curved, straight, and ragged. The literature review in the coinage field covers the following subjects: coin and die behavior under the striking load, viewpoints on 3D modeling, and finite element method (FEM) analysis, insights on various striking errors, with most of them more or less valued as collection metal pieces. The paper’s main purpose is outlined as follows: to study, using the available modern techniques, the particularities of different clipped coin types. In the second part of the paper, we introduced the adequate tridimensional (3D) model, for parts such as the die, collar, and the coin. It follows the assembled model corresponding to each studied case, which consists of the obverse and reverse striking dies and the collar, having inside them the coin. For each of the models, based on the initial conditions, the finite element analysis was performed. The paper’s last part presents the analysis’ results, the discussions, and the conclusions. Full article

(This article belongs to the Special Issue Modernly Designed Materials and Their Processing)

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17 pages, 3565 KB

Open AccessArticle

Interplay of Cationic Site Occupancy in Mn-Co Spinel Oxides: Correlating Structural, Vibrational, Morphological, and Electrochemical Properties

by Afrah Bardaoui, Souha Aouini, Amira Siai, Ana M. Ferraria and Diogo M. F. Santos

Appl. Sci. 2025, 15(24), 13267; https://doi.org/10.3390/app152413267 - 18 Dec 2025

Cited by 2 | Viewed by 1066

Abstract

MnCo₂O₄ and CoMn₂O₄ were successfully synthesized on a stainless-steel substrate using the hydrothermal method. The structural and morphological characteristics of the spinel samples were investigated using X-ray diffraction (XRD) and scanning electron microscopy (SEM). The electronic and [...] Read more.

MnCo₂O₄ and CoMn₂O₄ were successfully synthesized on a stainless-steel substrate using the hydrothermal method. The structural and morphological characteristics of the spinel samples were investigated using X-ray diffraction (XRD) and scanning electron microscopy (SEM). The electronic and vibrational properties were studied through X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR). Electrochemical properties were also evaluated using a three-electrode system associated with an electrochemical workstation. The studies revealed that the inversion of Mn and Co cation distribution between the spinel structure sites not only modifies the crystal structure and morphology but also alters specific functional properties. MnCo₂O₄ crystallized in a cubic spinel phase, exhibiting spherical particles, pronounced microstrain, and stronger metal–oxygen bonding. In contrast, CoMn₂O₄ adopted a tetragonal spinel structure with rod-like crystallites, lower microstrain, and more flexible bonding environments. Electrochemical impedance spectroscopy further revealed distinct charge-transfer dynamics, indicating differences in surface redox activity. This comparative analysis elucidates how cation site occupancy governs the performance of the synthesized spinel oxides and underscores their potential as efficient catalysts or catalyst supports for redox and energy-related applications. Full article

(This article belongs to the Section Chemical and Molecular Sciences)

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30 pages, 1688 KB

Open AccessArticle

Exploring Adaptive, Adaptable, Mixed, and Static Arabic Rule-Based Chatbot Effects on Usability, Learning Success, and Engagement

by Dalal Al Faia and Khalid Alomar

Appl. Sci. 2025, 15(24), 13266; https://doi.org/10.3390/app152413266 - 18 Dec 2025

Cited by 1 | Viewed by 841

Abstract

Personalized e-learning emphasizes a learner-centered instruction approach by adapting educational content to individual needs. This study empirically evaluates three personalization methods (adaptive, adaptable, and mixed) alongside a non-personalized static method, implemented within Moalemy, an Arabic rule-based educational chatbot. A 4 × 3 within-subjects [...] Read more.

Personalized e-learning emphasizes a learner-centered instruction approach by adapting educational content to individual needs. This study empirically evaluates three personalization methods (adaptive, adaptable, and mixed) alongside a non-personalized static method, implemented within Moalemy, an Arabic rule-based educational chatbot. A 4 × 3 within-subjects experiment involving 52 students across three levels of task difficulty (easy, medium, and hard) was performed to examine usability, learner engagement, and learning outcomes as key indicators of user experience in educational chatbots. Results showed no statistically significant differences in learning gain or relative learning gain across the four methods, indicating comparable effectiveness in supporting learning success. Engagement differed significantly by method, with the adaptable approach obtaining the highest scores. Descriptive usability results further suggested that the adaptable method achieved numerically higher scores in SUS, efficiency, and effectiveness under lower task difficulty, while static and adaptive showed comparatively stronger tendencies at higher levels. However, these patterns represent exploratory trends rather than statistically confirmed performance advantages. This study provides a controlled comparison of system-driven, learner-driven, shared-control, and non-personalization strategies in an Arabic e-learning context, offering empirical insights into how different learning methods influence usability, learning success, and engagement within Arabic educational chatbots. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

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19 pages, 1893 KB

Open AccessReview

Associations Between Lifestyle, Habits, Quality of Life and Non-Carious Diseases: A Scoping Review

by Rodrigo Silveira Tosta Figueiredo, Luiz Renato Paranhos, Gabriela Melo Terra Palazzo, Gustavo Henrick Ferreira Mendonça, Eduarda Betiati Menegazzo, Paulo Vinícius Soares and Jaqueline Vilela Bulgareli

Appl. Sci. 2025, 15(24), 13265; https://doi.org/10.3390/app152413265 - 18 Dec 2025

Cited by 1 | Viewed by 1003

Abstract

This scoping review aimed to map and synthesize the scientific evidence on how lifestyle factors and quality of life are associated with the onset and progression of non-carious diseases (NCDs) in young and adult populations, identifying patterns, methodological characteristics, and gaps in the [...] Read more.

This scoping review aimed to map and synthesize the scientific evidence on how lifestyle factors and quality of life are associated with the onset and progression of non-carious diseases (NCDs) in young and adult populations, identifying patterns, methodological characteristics, and gaps in the existing literature. A systematic literature search was conducted across PubMed, Embase, Scopus, and Web of Science databases to retrieve studies evaluating the influence of lifestyle habits and quality of life indicators on NCDs development and worsening. Most included studies were conducted in Brazil, with cross-sectional designs being the most prevalent. The main modulating factors identified included gastroesophageal reflux, post-bariatric conditions, smoking, bruxism, and anxiety. The results were summarized through a descriptive narrative synthesis. Considerable methodological heterogeneity was observed, particularly due to the absence of standardized protocols for NCDs assessment. Methodological quality was also evaluated to contextualize the robustness of the available evidence. Overall, lifestyle and quality of life factors play an important role in the progression of NCDs, underscoring the need for their integration into diagnostic and therapeutic planning. Further clinical studies are warranted to deepen the understanding of the relationship between NCDs and broader health domains, with particular attention to early oral aging syndrome (EOAS). Full article

(This article belongs to the Special Issue Periodontal Therapy: Latest Advances and Prospects)

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26 pages, 1338 KB

Open AccessReview

Plastic Waste in Romania: Between European Union Commitments and Actual Realities

by Madalina-Maria Enache, Daniela Gavrilescu, George Barjoveanu and Carmen Teodosiu

Appl. Sci. 2025, 15(24), 13264; https://doi.org/10.3390/app152413264 - 18 Dec 2025

Viewed by 1575

Abstract

Plastic waste management in Romania represents a critical challenge, situated between ambitious European Union (EU) circular economy commitments and the complex realities of national implementation. The analysis was carried out following the methodological steps and transparent reporting guidelines of Preferred Reporting Items for [...] Read more.

Plastic waste management in Romania represents a critical challenge, situated between ambitious European Union (EU) circular economy commitments and the complex realities of national implementation. The analysis was carried out following the methodological steps and transparent reporting guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Out of 200 studies included in this study from major databases (Scopus, Web of Science, Google Scholar) only 77 were retained. This systematic review critically synthesizes existing scientific evidence regarding this disparity through the lens of Life Cycle Assessment (LCA). The analysis highlights three critical findings. Firstly, regarding the status of LCA research, a significant scarcity of primary data for Romania is revealed, with existing studies predominantly relying on static attributional methods that fail to capture dynamic market shifts. Secondly, concerning the alignment with EU directives, the results indicate a severe ‘compliance gap’. While the implementation of the Deposit-Return System (SGR) has successfully diverted Polyethylene Terephthalate (PET) streams, the infrastructure for other plastic fractions remains stagnant, contradicting the efficiency required by EU targets. Finally, regarding strategic recommendations, it is demonstrated that current policies are hindered by a lack of LCA institutionalization. Consequently, the adoption of dynamic LCA models and harmonized reporting standards is proposed as a necessary mechanism to bridge the disparity between sustainability objectives and local operational realities. Full article

(This article belongs to the Section Environmental Sciences)

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22 pages, 2732 KB

Open AccessArticle

Coordinated Allocation of Channel-Tugboat-Berth Resources Under Tidal Constraints at Liquid Terminal

by Lingxin Kong, Hanbin Xiao, Yudong Wang, Keming Chen and Min Liu

Appl. Sci. 2025, 15(24), 13263; https://doi.org/10.3390/app152413263 - 18 Dec 2025

Cited by 1 | Viewed by 858

Abstract

Driven by the surging global demand for crude oil and its byproducts, liquid tanker vessels have undergone a marked shift toward ultra-large dimensions. This growth, while enhancing transport capacity, has also intensified congestion across many liquid terminals. As the Dead Weight Tonnage (DWT) [...] Read more.

Driven by the surging global demand for crude oil and its byproducts, liquid tanker vessels have undergone a marked shift toward ultra-large dimensions. This growth, while enhancing transport capacity, has also intensified congestion across many liquid terminals. As the Dead Weight Tonnage (DWT) of vessels rises, so does their draft, often requiring tide-dependent navigation for safe entry into ports. To address the resulting operational complexities, this study investigates the coordinated scheduling of three critical resources—channels, tugboats, and berths—at liquid terminals. A novel optimization framework, termed the Channel-Tugboat-Berth-Tide (CUBT) model, is proposed. The primary objective is to minimize the total operational cost over a planning horizon, accounting for anchorage waiting time, channel occupancy, tugboat utilization, and penalties from delayed departures. To solve this model efficiently, we adopt an enhanced variant of the Logistic-Hybrid-Adaptive Black Widow Optimization Algorithm (LHA-BWOA), incorporating Logistic-Sine-Cosine Chaotic Map (LSC-CM) initialization, hybrid reproduction mechanisms, and dynamic parameter adaptation. A series of case studies involving varying planning cycles are conducted to validate the model’s practical viability. Furthermore, sensitivity analyses are performed to evaluate the impact of channel choice, tugboat allocation, and vessel waiting time. Results indicate that tugboat operations account for the largest portion of the total costs. Notably, while two-way channels result in lower direct channel costs, they do not always yield the lowest overall expenditure. Among the service strategies evaluated, the First-In–First-Out (FIFO) rule is found to be the most cost-efficient. The results offer practical guidance for port improving the operational efficiency of liquid terminals under complex tidal and resource constraints. Full article

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18 pages, 7658 KB

Open AccessArticle

Modeling a 6 MV FFF Beam from the CyberKnife M6 to Produce Data for Training Artificial Neural Networks

by Justyna Rostocka, Joanna Prażmowska, Adam Konefał, Agnieszka Kapłon, Andrzej Orlef and Maria Sokół

Appl. Sci. 2025, 15(24), 13262; https://doi.org/10.3390/app152413262 - 18 Dec 2025

Viewed by 741

Abstract

A Monte Carlo-based model of the CyberKnife M6 6 MV Flattening Filter-Free (FFF) beam was developed to produce the data that can be used to train artificial neural networks. The data include the energy spectra of the beam, its average energy, the spatial [...] Read more.

A Monte Carlo-based model of the CyberKnife M6 6 MV Flattening Filter-Free (FFF) beam was developed to produce the data that can be used to train artificial neural networks. The data include the energy spectra of the beam, its average energy, the spatial distributions of the beam, and the distributions of the photon propagation directions for two selected radiation fields—a large one with a diameter of 60 mm, and a small one with a diameter of 15 mm. The GEANT4 code was used to develop the beam model. The developed model was verified by comparing the depth-dose distributions along the beam axis and the profiles obtained in both simulations and measurements. The data included in this paper, intended for training neural networks, will be made available via Google Drive. Full article

(This article belongs to the Special Issue Gamma and X-Ray Technologies for Medical Research: Image Analysis, Disease Discovered and Detection Techniques)

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30 pages, 4190 KB

Open AccessArticle

Reinventing a Mine Shaft for a Zero-G and Reduced-Gravity Space Research Facility: A Concept

by Dariusz Michalak, Jarosław Tokarczyk, Bartosz Orzeł, Magdalena Rozmus and Kamil Szewerda

Appl. Sci. 2025, 15(24), 13261; https://doi.org/10.3390/app152413261 - 18 Dec 2025

Cited by 1 | Viewed by 1432

Abstract

This paper presents an innovative concept for the adaptive transformation of decommissioned coal mine shafts into advanced reduced-gravity research facilities, addressing both post-mining land management and continuous advancements in microgravity research. The proposed solution leverages existing underground infrastructure to create an exceptionally long [...] Read more.

This paper presents an innovative concept for the adaptive transformation of decommissioned coal mine shafts into advanced reduced-gravity research facilities, addressing both post-mining land management and continuous advancements in microgravity research. The proposed solution leverages existing underground infrastructure to create an exceptionally long drop tower, approximately 900 m, surpassing the operational capabilities of all current global facilities. The facility employs electromagnetic propulsion and braking systems compatible with maglev technology, enabling extended microgravity durations and the precise simulation of multiple planetary gravity environments. Comprehensive numerical simulations, taking into account realistic mining shaft geometries, aerodynamic resistance, and mechanical vibration isolation, demonstrate that the system achieves free-fall periods of at least 10 s, which will be longer in the case of a capsule drop for research in reduced-gravity conditions (controlled deceleration of the capsule during the drop). The six-point suspension system effectively isolates experimental payloads from vibrations generated during descent. Beyond technological innovation, the facility exemplifies multidimensional sustainability by integrating scientific advancement with regional economic revitalization, employment generation for mining communities, industrial heritage preservation, and alignment with European Green Deal objectives. This globally unique research center would provide unprecedented opportunities for materials science, space biology, and industrial experimentation, while demonstrating innovative repurposing of post-mining assets. Full article

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23 pages, 3297 KB

Open AccessArticle

Numerical Study on Thermal Performance of Radiant Panels Coupled with V-Shaped Grooves and Phase Change Materials

by Haoze Wang and Zhitao Han

Appl. Sci. 2025, 15(24), 13260; https://doi.org/10.3390/app152413260 - 18 Dec 2025

Cited by 1 | Viewed by 598

Abstract

This study focuses on a proposed aluminum alloy radiant panel with 60° V-shaped grooves and integrated copper tubes. A numerical model of this novel grooved phase change material (PCM)-integrated radiant panel was established via Fluent 2022 R1 software. Through numerical simulations, the complete [...] Read more.

This study focuses on a proposed aluminum alloy radiant panel with 60° V-shaped grooves and integrated copper tubes. A numerical model of this novel grooved phase change material (PCM)-integrated radiant panel was established via Fluent 2022 R1 software. Through numerical simulations, the complete melting and solidification processes of two PCMs (n-hexadecane and LTXC-PCM-A-18) were analyzed, and differences in their phase change heat transfer performance were compared—revealing the role of the groove structure in enhancing PCM heat transfer and the material-structure compatibility. Results indicate that the groove structure effectively enhances convective heat transfer in the PCM liquid phase. During the melting stage, LTXC-PCM-A-18 exhibited a preheating rate of 0.00125 K/s, which is 67% higher than that of n-hexadecane (0.00075 K/s); its liquid fraction growth rate (0.0002 s⁻¹) was 2.67 times that of n-hexadecane, and the melting completion time was accelerated by 20% (2000 s). During solidification, LTXC-PCM-A-18’s initial cooling rate (0.0006 K/s) was 50% higher than that of n-hexadecane (0.0004 K/s), with a liquid fraction decay rate twice that of n-hexadecane. Additionally, its solidification temperature plateau was 1 K higher, providing superior thermal output stability. These findings reflect two distinct technical strategies: “steady-state temperature control” and “dynamic regulation.” n-Hexadecane exhibits smoother melting and solidification processes, making it suitable for continuous heating applications. In contrast, LTXC-PCM-A-18 demonstrates superior thermal responsiveness and phase change efficiency, aligning with intermittent heating requirements. This study provides quantitative guidance for PCM selection in grooved radiant panels. Full article

(This article belongs to the Special Issue Sustainability in Energy and Buildings: Future Perspectives and Challenges: 2nd Edition)

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19 pages, 3822 KB

Open AccessArticle

Comparison of Artificial Neural Network-Based Fuzzy Logic Model and Analytical Model for the Prediction of Optimum Material Parameters in a Heat-Generating, Functionally Graded Solid Cylinder

by Ali Öztürk and Mustafa Tınkır

Appl. Sci. 2025, 15(24), 13259; https://doi.org/10.3390/app152413259 - 18 Dec 2025

Cited by 1 | Viewed by 603

Abstract

This study presents an artificial intelligence-based predictive framework as an efficient alternative to conventional analytical procedures for evaluating elastic–plastic thermal stresses in long functionally graded solid cylinders (FGSCs) subjected to uniform internal heat generation. A hybrid artificial neural network-based fuzzy logic (ANNBFL) model [...] Read more.

This study presents an artificial intelligence-based predictive framework as an efficient alternative to conventional analytical procedures for evaluating elastic–plastic thermal stresses in long functionally graded solid cylinders (FGSCs) subjected to uniform internal heat generation. A hybrid artificial neural network-based fuzzy logic (ANNBFL) model is developed to estimate dimensionless thermal load parameters at both the cylinder center and outer surface by learning from validated analytical reference solutions. The material properties, including yield strength, elastic modulus, thermal conductivity, and thermal expansion coefficient, are assumed to vary radially following a parabolic gradation law. Eight influential material parameters are incorporated as input variables to describe the coupled thermo-mechanical behavior of the FGSC. Multiple ANNBFL subnetworks are trained using analytically generated datasets and subsequently integrated into a unified prediction framework, enabling rapid and accurate stress field estimation without repeated analytical calculations. Model performance is systematically assessed by direct comparison with analytical solutions, demonstrating an overall prediction consistency of approximately 98.2%. The results confirm that the proposed ANNBFL approach provides a reliable, computationally efficient surrogate modeling tool for parametric evaluation and optimum material design of functionally graded cylindrical structures under thermal loading. Full article

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19 pages, 1594 KB

Open AccessArticle

Plasma-Assisted Extraction of Bioactive Compounds from Tomato Peels and Sugar Beet Leaves Monitored by Electron Paramagnetic Resonance Spectroscopy

by Sanda Pleslić, Franka Markić, Tomislava Vukušić Pavičić, Višnja Stulić and Nadica Maltar-Strmečki

Appl. Sci. 2025, 15(24), 13258; https://doi.org/10.3390/app152413258 - 18 Dec 2025

Viewed by 699

Abstract

Agricultural by-products, such as tomato peels and sugar beet leaves, represent valuable sources of bioactive compounds that can be efficiently recovered using advanced extraction techniques. This study investigated the efficiency of high-voltage electrical discharge (HVED) extraction of bioactive compounds and antioxidant properties from [...] Read more.

Agricultural by-products, such as tomato peels and sugar beet leaves, represent valuable sources of bioactive compounds that can be efficiently recovered using advanced extraction techniques. This study investigated the efficiency of high-voltage electrical discharge (HVED) extraction of bioactive compounds and antioxidant properties from tomato peel (TP) and sugar beet leaves (SBLs). The target compounds were total phenolic content (TPC), lycopene, β-carotene, and chlorophylls. HVED treatments of 1, 3, and 5 min were applied using 30% and 50% methanolic solutions. A 5 min treatment enhanced the extraction of lycopene (2.04 mg/100 mL) and β-carotene (1.14 mg/100 mL) in the 50% methanolic solution, while the shorter 3 min treatments increased TPC (0.117 mg GAE/mL in TP; 0.280 mg GAE/mL in SBLs) and chlorophyll content (25.47 mg/100 mL). For both TP and SBLs, the more concentrated methanolic solvent (50%) was more efficient in extracting bioactive components than the 30% solution. Electron paramagnetic resonance (EPR) spectroscopy confirmed increases in antioxidant activity in all treated samples, with the highest values of 45.27% for TP and 53.16% for SBLs. As a direct and sensitive technique for detecting free-radical scavenging, EPR proved highly suitable for evaluating the impact of HVED treatments. Overall, HVED demonstrated strong potential as a green and effective method for enhancing the recovery of valuable bioactives and antioxidant properties from tomato and sugar beet by-products. Full article

(This article belongs to the Special Issue Advanced Applications of Plasmas Technology in Materials and Diagnostics)

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13 pages, 3188 KB

Open AccessArticle

Measuring the Spin Polarization with a Superconducting Point Contact and Machine Learning

by Dongik Lee and Seunghun Lee

Appl. Sci. 2025, 15(24), 13257; https://doi.org/10.3390/app152413257 - 18 Dec 2025

Viewed by 741

Abstract

Measuring spin polarization (P) of materials is essential for understanding their fundamental properties and for their application in spintronics. Point contact Andreev reflection (PCAR) spectroscopy is a straightforward yet powerful technique for measuring P. However, conventional analysis methods depend on [...] Read more.

Measuring spin polarization (P) of materials is essential for understanding their fundamental properties and for their application in spintronics. Point contact Andreev reflection (PCAR) spectroscopy is a straightforward yet powerful technique for measuring P. However, conventional analysis methods depend on iterative fitting procedures that are time-consuming, subjective, and often lead to non-unique solutions. This complexity arises from the interplay of multiple physical parameters with pressure, including temperature, superconducting gap, and interfacial barrier strength. Here, we present a machine learning (ML) approach that utilizes convolutional neural networks (CNNs) to facilitate the rapid and automated extraction of P from PCAR spectra. We validate the ML model by analyzing experimental PCAR spectra from various materials reported in the literature. The predicted parameters by the CNN model show excellent agreement with the literature values, demonstrating its robust performance across a wide range of materials and parameter sets. This approach significantly reduces analysis time while maintaining accuracy, providing a practical tool for material characterization, thus accelerating materials discovery for spintronics. Full article

(This article belongs to the Section Materials Science and Engineering)

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17 pages, 3579 KB

Open AccessArticle

Evaluation of Maritime Safety Policy Using Data Envelopment Analysis and PROMETHEE Method

by Tomislav Sunko, Marko Mladineo, Zoran Medvidović and Mihael Dedo

Appl. Sci. 2025, 15(24), 13256; https://doi.org/10.3390/app152413256 - 18 Dec 2025

Viewed by 641

Abstract

Each maritime country produces annual reports on its maritime safety policy. The annual report details the implementation of established policies, plans, and regulations concerning the supervision and protection of rights and interests at sea. By analyzing the Annual Reports for the Republic of [...] Read more.

Each maritime country produces annual reports on its maritime safety policy. The annual report details the implementation of established policies, plans, and regulations concerning the supervision and protection of rights and interests at sea. By analyzing the Annual Reports for the Republic of Croatia from 2017 to 2024, maritime traffic and activities at sea were examined. The data include the number of available inspection vessels, the nautical miles traveled, fuel consumption, and similar metrics. All this information is related to the total number of inspected vessels, which is a key performance indicator for maritime traffic control. The aim of the analysis is to determine the correlation between fuel consumption, distance traveled, number of voyages, and number of inspected vessels over eight consecutive years. Data Envelopment Analysis (DEA) is used to assess the relationship between inputs and outputs to identify which years were efficient. Additionally, the multi-criteria decision-making method PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations) is used to interpret and validate the DEA results, particularly the efficiency ranking. The proposed DEA–PROMETHEE hybrid model enables decision-makers to better understand DEA results, especially when efficiency scores are very similar. In terms of practical applications, the results based on the DEA input and output analysis, extended with the PROMETHEE method, show that the optimized use of available resources contributes to increased overall maritime safety. Full article

(This article belongs to the Special Issue Risk and Safety of Maritime Transportation)

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