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Hybrid modeling techniques are increasingly important for improving predictive accuracy and control in biomanufacturing, particularly in data-limited conditions. This study develops and experimentally validates a hybrid deep learning model predictive control (MPC) framework for recombinant P. pastoris fed-batch fermentations. Bayesian optimization and grid search techniques were employed to identify the best-performing hybrid model architecture: an LSTM layer with 2 hidden units followed by a fully connected layer with 8 nodes and ReLU activation. This design balanced accuracy (NRMSE 4.93%) and computational efficiency (AICc 998). This architecture was adapted to a new, smaller dataset of bacteriophage Qβ coat protein production using transfer learning, yielding strong predictive performance with low validation (3.53%) and test (5.61%) losses. Finally, the hybrid model was integrated into a novel MPC system and experimentally validated, demonstrating robust real-time substrate feed control in a way that allows it to maintain specific target growth rates. The system achieved predictive accuracies of 6.51% for biomass and 14.65% for product estimation, with an average tracking error of 10.64%. In summary, this work establishes a robust, adaptable, and efficient hybrid modeling framework for MPC in P. pastoris bioprocesses. By integrating automated architecture searching, transfer learning, and MPC, the approach offers a practical and generalizable solution for real-time control and supports scalable digital twin deployment in industrial biotechnology. Full article

(This article belongs to the Special Issue Computer and Mathematical Simulation of Microbial Fermentations: The Choice of Models, Parameter Estimation and Applications)

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13 pages, 3341 KiB

Open AccessArticle

Design and Experimentation of Variable-Density Damping Materials Based on Topology Optimization

by Xiangkun Zeng, Biaojie Han, Ziheng Kuang, Han Ding, Kaixin Wang, Canyi Du, Wei Wu, Hongluo Li and Jiangang Wang

Processes 2025, 13(7), 2276; https://doi.org/10.3390/pr13072276 (registering DOI) - 17 Jul 2025

Abstract

In engineering structures, damping materials are an effective way to improve vibration characteristics, but they can significantly increase the weight and cost of the structure. In this study, based on the variable density topology optimization algorithm, combined with finite element simulation and experimental validation, the vibration damping performance of a composite structure with steel plate and damping material is optimized. With the objective of minimizing the resonance response and the constraint of damping material volume, the material distribution of the damping layer is optimized, and the amount of damping material used is successfully reduced by 31.2%. By building a test rig and comparing the vibration responses under the three working conditions of no damping, full damping coverage, and optimized damping, the effectiveness of the optimization strategy is verified, and a significant reduction in vibration response is achieved. This study provides an innovative solution for lightweight design and cost control in engineering. Full article

(This article belongs to the Special Issue Structural Design and Performance Optimization of High-Performance Composites)

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14 pages, 2452 KiB

Open AccessArticle

Energy Yield Analysis of Bifacial Solar Cells in Northeast Mexico: Comparison Between Vertical and Tilted Configurations

by Angel Eduardo Villarreal-Villela, Osvaldo Vigil-Galán, Eugenio Rodríguez González, Jesús Roberto González Castillo, Daniel Jiménez-Olarte, Ana Bertha López-Oyama and Deyanira Del Angel-López

Energies 2025, 18(14), 3784; https://doi.org/10.3390/en18143784 (registering DOI) - 17 Jul 2025

Abstract

Bifacial photovoltaic technology is made up of solar cells with the ability to generate electrical power on both sides of the cell (front and rear), consequently, they generate more energy in the same area compared to conventional or monofacial solar cells. The present work deals with the calculation of the energy yield using bifacial solar cells under the specific environmental conditions of Tampico, Tamaulipas, Mexico. Two configurations were compared: (1) tilted, optimized in height and angle, oriented to the south, and (2) vertically optimized in height, oriented east–west. The results were also compared with a standard monofacial solar cell optimally tilted and oriented south. The experimental data were acquired using a current–voltage (I-V) curve tracer designed for this purpose. This study shows that the vertically optimized bifacial solar cell produces similar electrical power to the conventional monofacial solar cell, with the benefit of maximum production in peak hours (8:30 and 16:30). In contrast, in the case of the inclined bifacial solar cell, about 26% more in the production of electrical power was reached. These results guide similar studies in other places of the Mexican Republic and regions with similar latitudes and climate. Full article

(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)

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13 pages, 485 KiB

Open AccessArticle

Cognitive Systems and Artificial Consciousness: What It Is Like to Be a Bat Is Not the Point

by Javier Arévalo-Royo, Juan-Ignacio Latorre-Biel and Francisco-Javier Flor-Montalvo

Metrics 2025, 2(3), 11; https://doi.org/10.3390/metrics2030011 (registering DOI) - 17 Jul 2025

Abstract

A longstanding ambiguity surrounds the operationalization of consciousness in artificial systems, complicated by the philosophical and cultural weight of subjective experience. This work examines whether cognitive architectures may be designed to support a functionally explicit form of artificial consciousness, focusing not on the replication of phenomenology, but rather on measurable, technically realizable introspective mechanisms. Drawing on a critical review of foundational and contemporary literature, this study articulates a conceptual and methodological shift: from investigating the experiential perspective of agents (“what it is like to be a bat”) to analyzing the informational, self-regulatory, and adaptive structures that enable purposive behavior. The approach combines theoretical analysis with a comparative review of major cognitive architectures, evaluating their capacity to implement access consciousness and internal monitoring. Findings indicate that several state-of-the-art systems already display core features associated with functional consciousness—such as self-explanation, context-sensitive adaptation, and performance evaluation—without invoking subjective states. These results support the thesis that cognitive engineering may progress more effectively by focusing on operational definitions of consciousness that are amenable to implementation and empirical validation. In conclusion, this perspective enables the development of artificial agents capable of autonomous reasoning and self-assessment, grounded in technical clarity rather than speculative constructs. Full article

(This article belongs to the Special Issue AI and the Digital Cultural Ecosystem: Enhancing or Eroding Socio-Cultural Dynamics)

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19 pages, 1827 KiB

Open AccessArticle

Discrete Element Modeling of Concrete Under Dynamic Tensile Loading

by Ahmad Omar and Laurent Daudeville

Materials 2025, 18(14), 3347; https://doi.org/10.3390/ma18143347 (registering DOI) - 17 Jul 2025

Abstract

Concrete is a fundamental material in structural engineering, widely used in critical infrastructure such as bridges, nuclear power plants, and dams. These structures may be subjected to extreme dynamic loads resulting from natural disasters, industrial accidents, or missile impacts. Therefore, a comprehensive understanding of concrete behavior under high strain rates is essential for safe and resilient design. Experimental investigations, particularly spalling tests, have highlighted the strain-rate sensitivity of concrete in dynamic tensile loading conditions. This study presents a macroscopic 3D discrete element model specifically developed to simulate the dynamic response of concrete subjected to extreme loading. Unlike conventional continuum-based models, the proposed discrete element framework is particularly suited to capturing damage and fracture mechanisms in cohesive materials. A key innovation lies in incorporating a physically grounded strain-rate dependency directly into the local cohesive laws that govern inter-element interactions. The originality of this work is further underlined by the validation of the discrete element model under dynamic tensile loading through the simulation of spalling tests on normalstrength concrete at strain rates representative of severe impact scenarios (30–115 s⁻¹). After calibrating the model under quasi-static loading, the simulations accurately reproduce key experimental outcomes, including rear-face velocity profiles and failure characteristics. Combined with prior validations under high confining pressure, this study reinforces the capability of the discrete element method for modeling concrete subjected to extreme dynamic loading, offering a robust tool for predictive structural assessment and design. Full article

(This article belongs to the Section Construction and Building Materials)

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11 pages, 7216 KiB

Open AccessArticle

Low-Finesse Fabry–Perot Cavity Design Based on a Reflective Sphere

by Ju Wang, Ye Gao, Jinlong Yu, Hao Luo, Xuemin Su, Xu Han, Yang Gao, Ben Cai and Chuang Ma

Photonics 2025, 12(7), 723; https://doi.org/10.3390/photonics12070723 (registering DOI) - 17 Jul 2025

Abstract

Low-finesse Fabry–Perot (F–P) cavities, widely applied in the field of micro-displacement measurement, offer significant advantages in reducing the influence of higher-order reflections and improving the accuracy of measurement systems. Generally, an F–P cavity finesse of 0.5 is required to achieve high-precision micro-displacement measurements. However, in optical design, low-finesse cavities impose strict requirements on reflectivity, and maintaining fine stability during cavity movement is challenging. Achieving ideal orthogonal interference with a finesse of 0.5 thus presents considerable difficulties. This study proposes a novel low-finesse F–P cavity design that employs a high-reflectivity spherical reflector and the end face of a fiber collimator as the reflective surfaces of the cavity. By utilizing beam divergence characteristics and geometric parameters, a structure with a finesse of approximately 0.5 is quantitatively designed, enabling a simplified implementation without the need for angular alignment. Compared with conventional approaches, this method eliminates the need for precise angular alignment of the reflective surfaces, significantly simplifying implementation. The experimental results show that, under fixed receiving field angles and beam radii of the fiber collimators, ideal orthogonal interference can be achieved by selecting the radius of the reflective sphere. Under varying working distances, the average finesse values of the interference spectra measured by Collimators 1 and 2 are 0.496 and 0.502, respectively, both close to the theoretical design value of 0.5, thereby meeting the design requirements. Full article

(This article belongs to the Section Optical Communication and Network)

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17 pages, 10396 KiB

Open AccessArticle

Feature Selection Based on Three-Dimensional Correlation Graphs

by Adam Dudáš and Aneta Szoliková

AppliedMath 2025, 5(3), 91; https://doi.org/10.3390/appliedmath5030091 (registering DOI) - 17 Jul 2025

Abstract

The process of feature selection is a critical component of any decision-making system incorporating machine or deep learning models applied to multidimensional data. Feature selection on input data can be performed using a variety of techniques, such as correlation-based methods, wrapper-based methods, or embedded methods. However, many conventionally used approaches do not support backwards interpretability of the selected features, making their application in real-world scenarios impractical and difficult to implement. This work addresses that limitation by proposing a novel correlation-based strategy for feature selection in regression tasks, based on a three-dimensional visualization of correlation analysis results—referred to as three-dimensional correlation graphs. The main objective of this study is the design, implementation, and experimental evaluation of this graphical model through a case study using a multidimensional dataset with 28 attributes. The experiments assess the clarity of the visualizations and their impact on regression model performance, demonstrating that the approach reduces dimensionality while maintaining or improving predictive accuracy, enhances interpretability by uncovering hidden relationships, and achieves better or comparable results to conventional feature selection methods. Full article

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18 pages, 4432 KiB

Open AccessArticle

Radial Temperature Distribution Characteristics of Long-Span Transmission Lines Under Forced Convection Conditions

by Feng Wang, Chuanxing Song, Xinghua Chen and Zhangjun Liu

Processes 2025, 13(7), 2273; https://doi.org/10.3390/pr13072273 - 16 Jul 2025

Abstract

This study proposes an iterative method based on thermal equilibrium equations to calculate the radial temperature distribution of long-span overhead transmission lines under forced convection. This paper takes the ACSR 500/280 conductor as the research object, establishes the three-dimensional finite element model considering the helix angle of the conductor, and carries out the experimental validation for the LGJ 300/40 conductor under the same conditions. The model captures internal temperature distribution through contour analysis and examines the effects of current, wind speed, and ambient temperature. Unlike traditional models assuming uniform conductor temperature, this method reveals internal thermal gradients and introduces a novel three-stage radial attenuation characterization. The iterative method converges and accurately reflects temperature variations. The results show a non-uniform radial distribution, with a maximum temperature difference of 8 °C and steeper gradients in aluminum than in steel. Increasing current raises temperature nonlinearly, enlarging the radial difference. Higher wind speeds reduce both temperature and radial difference, while rising ambient temperatures increase conductor temperature with a stable radial profile. This work provides valuable insights for the safe operation and optimal design of long-span transmission lines and supports future research on dynamic and environmental coupling effects. Full article

(This article belongs to the Section Energy Systems)

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25 pages, 1708 KiB

Open AccessArticle

The Kinematics of a New Schönflies Motion Generator Parallel Manipulator Using Screw Theory

by Jaime Gallardo-Alvarado, Horacio Orozco-Mendoza, Ramon Rodriguez-Castro, Alvaro Sanchez-Rodriguez and Luis A. Alcaraz-Caracheo

Mathematics 2025, 13(14), 2291; https://doi.org/10.3390/math13142291 - 16 Jul 2025

Abstract

In this work, an innovative Schönflies motion generator manipulator is introduced, featuring a parallel architecture composed of serial chains with mixed degrees of freedom. Fundamental kinematic aspects essential to any manipulator such as displacement, velocity, acceleration, and singularity analyses are thoroughly addressed. Screw theory is employed to derive compact input–output expressions for velocity and acceleration, leveraging the properties of reciprocal screws and lines associated with the constrained degrees of freedom in the parallel manipulator. A key advantage of the proposed design is its near-complete avoidance of singular configurations, which significantly enhances its applicability in robotic manipulation. Numerical examples are provided to validate the theoretical results, with corroboration from specialized tools such as ADAMS™ software and data fitting algorithms. These results confirm the reliability and robustness of the developed kinematic analysis approach. Full article

(This article belongs to the Section E1: Mathematics and Computer Science)

32 pages, 5175 KiB

Open AccessArticle

Scheduling and Routing of Device Maintenance for an Outdoor Air Quality Monitoring IoT

by Peng-Yeng Yin

Sustainability 2025, 17(14), 6522; https://doi.org/10.3390/su17146522 - 16 Jul 2025

Abstract

Air quality monitoring IoT is one of the approaches to achieving a sustainable future. However, the large area of IoT and the high number of monitoring microsites pose challenges for device maintenance to guarantee quality of service (QoS) in monitoring. This paper proposes a novel maintenance programming model for a large-area IoT containing 1500 monitoring microsites. In contrast to classic device maintenance, the addressed programming scenario considers the division of appropriate microsites into batches, the determination of the batch maintenance date, vehicle routing for the delivery of maintenance services, and a set of hard constraints such as QoS in air quality monitoring, the maximum number of labor working hours, and an upper limit on the total CO₂ emissions. Heuristics are proposed to generate the batches of microsites and the scheduled maintenance date for the batches. A genetic algorithm is designed to find the shortest routes by which to visit the batch microsites by a fleet of vehicles. Simulations are conducted based on government open data. The experimental results show that the maintenance and transportation costs yielded by the proposed model grow linearly with the number of microsites if the fleet size is also linearly related to the microsite number. The mean time between two consecutive cycles is around 17 days, which is generally sufficient for the preparation of the required maintenance materials and personnel. With the proposed method, the decision-maker can circumvent the difficulties in handling the hard constraints, and the allocation of maintenance resources, including budget, materials, and engineering personnel, is easier to manage. Full article

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

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18 pages, 20927 KiB

Open AccessArticle

Numerical and Experimental Study on the Deformation of Adaptive Elastomer Fibre-Reinforced Composites with Embedded Shape Memory Alloy Wire Actuators

by Holger Böhm, Andreas Hornig, Chokri Cherif and Maik Gude

J. Compos. Sci. 2025, 9(7), 371; https://doi.org/10.3390/jcs9070371 (registering DOI) - 16 Jul 2025

Abstract

In this work, a finite element modelling methodology is presented for the prediction of the bending behaviour of a glass fibre-reinforced elastomer composite with embedded shape memory alloy (SMA) wire actuators. Three configurations of a multi-layered composite with differences in structural stiffness and thickness are experimentally and numerically analysed. The bending experiments are realised by Joule heating of the SMA, resulting in deflection angles of up to 58 deg. It is shown that a local degradation in the structural stiffness in the form of a hinge significantly increases the amount of deflection. Modelling is fully elaborated in the finite element software ANSYS, based on material characterisation experiments of the composite and SMA materials. The thermomechanical material behaviour of the SMA is modelled via the Souza–Auricchio model, based on differential scanning calorimetry (DSC) and isothermal tensile experiments. The methodology allows for the consideration of an initial pre-stretch for straight-line positioned SMA wires and an evaluation of their phase transformation state during activation. The results show a good agreement of the bending angle for all configurations at the activation temperature of 120 °C reached in the experiments. The presented methodology enables an efficient design and evaluation process for soft robot structures with embedded SMA actuator wires. Full article

(This article belongs to the Special Issue Theoretical and Computational Investigation on Composite Materials)

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19 pages, 5460 KiB

Open AccessArticle

New Perspectives on Digital Representation: The Case of the ‘Santa Casa de Misericórdia’ in São Carlos (Brazil)

by Cristiana Bartolomei, Luca Budriesi, Alfonso Ippolito, Davide Mezzino and Caterina Morganti

Buildings 2025, 15(14), 2502; https://doi.org/10.3390/buildings15142502 - 16 Jul 2025

Abstract

This research aims to investigate the Italian architectural heritage in Brazil through the analysis of the ‘Santa Casa de Misericórdia’ hospital in São Carlos, in the state of São Paulo. As part of the KNOW.IT national project, the work aims to recover and digitally enhance Italian heritage abroad from the 19th and 20th centuries. The buildings analysed were either designed or built by Italian architects who emigrated to South America or constructed using materials and techniques typical of Italian architecture of those years. The hospital, designed by the Italian architect Samuele Malfatti in 1891, was chosen for its historical value and its role in the urban context of the city of São Carlos, which, moreover, continues to perform its function even today. The study aims to create a digital archive with 3D models and two-dimensional graphical drawings. The methodology includes historical analysis, photogrammetric survey, and digital modelling using Agisoft Metashape and 3DF Zephyr software. A total of 636 images were processed, with the maximum resolution achieved in the models being 3526 × 2097 pixels. The results highlight the influence of Italian architecture on late 19th-century São Carlos and promote its virtual accessibility and wide-ranging knowledge. Full article

(This article belongs to the Special Issue Analysis, Conservation, and Refurbishment Methods of Heritage Architecture Based on Modern Technology)

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40 pages, 17591 KiB

Open AccessArticle

Research and Education in Robotics: A Comprehensive Review, Trends, Challenges, and Future Directions

by Mutaz Ryalat, Natheer Almtireen, Ghaith Al-refai, Hisham Elmoaqet and Nathir Rawashdeh

J. Sens. Actuator Netw. 2025, 14(4), 76; https://doi.org/10.3390/jsan14040076 - 16 Jul 2025

Abstract

Robotics has emerged as a transformative discipline at the intersection of the engineering, computer science, and cognitive sciences. This state-of-the-art review explores the current trends, methodologies, and challenges in both robotics research and education. This paper presents a comprehensive review of the evolution of robotics, tracing its development from early automation to intelligent, autonomous systems. Key enabling technologies, such as Artificial Intelligence (AI), soft robotics, the Internet of Things (IoT), and swarm intelligence, are examined along with real-world applications in healthcare, manufacturing, agriculture, and sustainable smart cities. A central focus is placed on robotics education, where hands-on, interdisciplinary learning is reshaping curricula from K–12 to postgraduate levels. This paper analyzes instructional models including project-based learning, laboratory work, capstone design courses, and robotics competitions, highlighting their effectiveness in developing both technical and creative competencies. Widely adopted platforms such as the Robot Operating System (ROS) are briefly discussed in the context of their educational value and real-world alignment. Through case studies, institutional insights, and synthesis of academic and industry practices, this review underscores the vital role of robotics education in fostering innovation, systems thinking, and workforce readiness. The paper concludes by identifying the key challenges and future directions to guide researchers, educators, industry stakeholders, and policymakers in advancing robotics as both technological and educational frontiers. Full article

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22 pages, 2239 KiB

Open AccessArticle

Relationship Between Aquatic Fungal Diversity in Surface Water and Environmental Factors in Yunnan Dashanbao Black-Necked Crane National Nature Reserve, China

by Kaize Shen, Yufeng Tang, Jiaoxu Shi, Zhongxiang Hu, Meng He, Jinzhen Li, Yuanjian Wang, Mingcui Shao and Honggao Liu

J. Fungi 2025, 11(7), 526; https://doi.org/10.3390/jof11070526 - 16 Jul 2025

Abstract

Aquatic fungi serve as core ecological engines in freshwater ecosystems, driving organic matter decomposition and energy flow to sustain environmental balance. Wetlands, with their distinct hydrological dynamics and nutrient-rich matrices, serve as critical habitats for these microorganisms. As an internationally designated Ramsar Site, Yunnan Dashanbao Black-Necked Crane National Nature Reserve in China not only sustains endangered black-necked cranes but also harbors a cryptic reservoir of aquatic fungi within its peat marshes and alpine lakes. This study employed high-throughput sequencing to characterize fungal diversity and community structure across 12 understudied wetland sites in the reserve, while analyzing key environmental parameters (dissolved oxygen, pH, total nitrogen, and total phosphorus). A total of 5829 fungal operational taxonomic units (OTUs) spanning 649 genera and 15 phyla were identified, with Tausonia (4.17%) and Cladosporium (1.89%) as dominant genera. Environmental correlations revealed 19 genera significantly linked to abiotic factors. FUNGuild functional profiling highlighted saprotrophs (organic decomposers) and pathogens as predominant trophic guilds. Saprotrophs exhibited strong associations with pH, total nitrogen, and phosphorus, whereas pathogens correlated primarily with pH. These findings unveil the hidden diversity and ecological roles of aquatic fungi in alpine wetlands, emphasizing their sensitivity to environmental gradients. By establishing baseline data on fungal community dynamics, this work advances the understanding of wetland microbial ecology and informs conservation strategies for Ramsar sites. Full article

(This article belongs to the Section Environmental and Ecological Interactions of Fungi)

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10 pages, 238 KiB

Open AccessArticle

Teaching Sociology Through Community-Engaged Learning with a Multinational Student Body: Garnering Sociological Insights from Lived Experiences Across National Contexts

by Katherine Lyon

Soc. Sci. 2025, 14(7), 436; https://doi.org/10.3390/socsci14070436 - 16 Jul 2025

Abstract

Community-engaged learning (CEL) is a popular educational approach for sociology teaching across Canada and globally. Students in sociology courses with this experiential component can opt in to enhance their learning by working with community members and organizations in structured, low-stakes ways that forward community priorities. Evidence shows that CEL in sociology courses supports students in developing a wide variety of skills. However, little is known about how international students in sociology courses engage with this pedagogy. Drawing on 20 semi-structured interviews with international students from Asia, South America, and Eastern Europe who completed CEL programming as part of their sociology course curriculum at a large Canadian university, I show how these students engaged in unique learning practices. The findings indicate that international students draw upon their life experiences from diverse national contexts to navigate and reflect upon their CEL placement in sociological ways. These students’ voices offer rich insights for sociology educators designing course-based CEL opportunities with a multinational student body. Full article

(This article belongs to the Special Issue Global and Virtual Sociological Teaching—Challenges & Opportunities)

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