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Volume 15
Issue 14
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Appl. Sci., Volume 15, Issue 14 (July-2 2025) – 497 articles

Cover Story (view full-size image): Acoustic metamaterials (AMs) are artificially structured materials composed of subwavelength units that enable acoustic phenomena not achievable with conventional materials and structures. This review defines and presents a distinct category referred to as soft acoustic metamaterials (SAMs), which use soft materials or reconfigurable structures to achieve enhanced acoustic functionality. These systems make use of the inherent flexibility of their materials or the deformability of their geometry to support passive, active, and adaptive functions. This review presents a structured classification for soft acoustic metamaterials and offers a foundation for future research, with broad potential in intelligent sound systems, wearable acoustics, and architectural applications. View this paper
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16 pages, 1926 KiB  
Article
External and Internal Load Response to Different Refereeing Techniques and to Sex of Players in Basketball Games
by David Mancha-Triguero, Alberto Sánchez-Sixto, Carlos D. Gómez-Carmona and Eduardo Salazar-Martínez
Appl. Sci. 2025, 15(14), 8121; https://doi.org/10.3390/app15148121 - 21 Jul 2025
Viewed by 404
Abstract
Basketball referees play a crucial role in game management, yet the physical and physiological demands placed on them during a game remain understudied. This study analyzed the workload of 35 group 1 referees during a U-18 Spanish championship, examining the effects of refereeing [...] Read more.
Basketball referees play a crucial role in game management, yet the physical and physiological demands placed on them during a game remain understudied. This study analyzed the workload of 35 group 1 referees during a U-18 Spanish championship, examining the effects of refereeing technique (two referees vs. three referees) and competition sex (male vs. female) across game quarters. Physical and physiological demands were measured using inertial devices and heart rate monitors during 37 matches (18 men’s and 19 women’s). The results revealed that 2-referee teams experienced significantly greater physical demands, covering approximately 25% more total distance and demonstrating higher values in high-intensity running compared to 3-referee teams. Female competition elicited higher demands in specific variables, particularly in the distance covered above 16 km/h and average speed. Analysis across quarters showed distinct temporal patterns, with the first and third quarters presenting the highest demands, especially for 2-referee teams. These findings suggest that basketball referees’ physical preparation should be tailored to the officiating technique and competition sex, with a particular emphasis on developing specific conditioning programs for the 2-referee technique and implementing targeted recovery strategies between quarters to maintain optimal performance throughout the game. Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
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21 pages, 2385 KiB  
Article
Fuzzy Model Predictive Control for Unmanned Helicopter
by Łukasz Kiciński and Sebastian Topczewski
Appl. Sci. 2025, 15(14), 8120; https://doi.org/10.3390/app15148120 - 21 Jul 2025
Viewed by 391
Abstract
Unmanned helicopters, due to their agility and strong dependence on environmental conditions, require using advanced control techniques in order to ensure precise trajectory tracking in various states of flight. The following paper presents a methodology for the design of an unmanned helicopter flight [...] Read more.
Unmanned helicopters, due to their agility and strong dependence on environmental conditions, require using advanced control techniques in order to ensure precise trajectory tracking in various states of flight. The following paper presents a methodology for the design of an unmanned helicopter flight controller. The proposed solution involves the use of the Model Predictive Control framework enhanced with the Takagi–Sugeno inference algorithm. The designed system uses a Parallel Distributed Compensation architecture and utilizes multiple linear dynamics models to precisely model the helicopter’s response in transitioning from hovering to forward flight. The proposed control system was developed for the ARCHER unmanned rotorcraft, which was designed at Warsaw University of Technology. In order to evaluate control efficiency, simulation tests were conducted using the helicopter mathematical model built in the FLIGHTLAB environment, fully integrated with the Matlab/Simulink platform. The control system test results, including system step responses and performance during flight over a predefined path, highlight the differences between the conventional Model Predictive Control regulator and its fuzzy-enhanced variant. Full article
(This article belongs to the Special Issue Advances in Aircraft Design, Optimization and Flight Control)
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20 pages, 7090 KiB  
Article
The Influence of Hard Protection Structures on Shoreline Evolution in Riohacha, Colombia
by Marta Fernández-Hernández, Luis Iglesias, Jairo Escobar, José Joaquín Ortega, Jhonny Isaac Pérez-Montiel, Carlos Paredes and Ricardo Castedo
Appl. Sci. 2025, 15(14), 8119; https://doi.org/10.3390/app15148119 - 21 Jul 2025
Viewed by 508
Abstract
Over the past 50 years, coastal erosion has become an increasingly critical issue worldwide, and Colombia’s Caribbean coast is no exception. In urban areas, this challenge is further complicated by hard protection structures, which, while often implemented as immediate solutions, can disrupt sediment [...] Read more.
Over the past 50 years, coastal erosion has become an increasingly critical issue worldwide, and Colombia’s Caribbean coast is no exception. In urban areas, this challenge is further complicated by hard protection structures, which, while often implemented as immediate solutions, can disrupt sediment transport and trigger unintended long-term consequences. This study examines shoreline changes in Riohacha, the capital of La Guajira Department, over a 35-year period (1987–2022), focusing on the impacts of coastal protection structures—specifically, the construction of seven groins and a seawall between 2006 and 2009—on coastal dynamics. Using twelve images (photographs and satellite) and the Digital Shoreline Analysis System (DSAS), the evolution of both beaches and cliffs has been analyzed. The results reveal a dramatic shift in shoreline behavior: erosion rates of approximately 0.5 m/year prior to the interventions transitioned to accretion rates of up to 11 m/year within the groin field, where rapid infill occurred. However, this sediment retention has exacerbated erosion in downstream cliff areas, with retreat rates reaching 1.8 ± 0.2 m/year. To anticipate future coastal evolution, predictive models were applied through 2045, providing insights into potential risks for infrastructure and urban development. These findings highlight the need for a strategic, long-term approach to coastal management that considers both the benefits and unintended consequences of engineering interventions. Full article
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32 pages, 2698 KiB  
Article
Design and Validation of an Edge-AI Fire Safety System with SmartThings Integration for Accelerated Detection and Targeted Suppression
by Seung-Jun Lee, Hong-Sik Yun, Yang-Bae Sim and Sang-Hoon Lee
Appl. Sci. 2025, 15(14), 8118; https://doi.org/10.3390/app15148118 - 21 Jul 2025
Viewed by 521
Abstract
This study presents the design and validation of an integrated fire safety system that leverages edge AI, hybrid sensing, and precision suppression to overcome the latency and collateral limitations of conventional smoke detection and sprinkler systems. The proposed platform features a dual-mode sensor [...] Read more.
This study presents the design and validation of an integrated fire safety system that leverages edge AI, hybrid sensing, and precision suppression to overcome the latency and collateral limitations of conventional smoke detection and sprinkler systems. The proposed platform features a dual-mode sensor array for early fire recognition, motorized ventilation units for rapid smoke extraction, and a 360° directional nozzle for targeted agent discharge using a residue-free clean extinguishing agent. Experimental trials demonstrated an average fire detection time of 5.8 s and complete flame suppression within 13.2 s, with 90% smoke clearance achieved in under 95 s. No false positives were recorded during non-fire simulations, and the system remained fully functional under simulated cloud communication failure, confirming its edge-resilient architecture. A probabilistic risk analysis based on ISO 31000 and NFPA 551 frameworks showed risk reductions of 75.6% in life safety, 58.0% in property damage, and 67.1% in business disruption. The system achieved a composite risk reduction of approximately 73%, shifting the operational risk level into the ALARP region. These findings demonstrate the system’s capacity to provide proactive, energy-efficient, and spatially targeted fire response suitable for high-value infrastructure. The modular design and SmartThings Edge integration further support scalable deployment and real-time system intelligence, establishing a strong foundation for future adaptive fire protection frameworks. Full article
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22 pages, 2593 KiB  
Article
A Data-Driven Model for the Energy and Economic Assessment of Building Renovations
by Giuseppe Piras, Francesco Muzi and Zahra Ziran
Appl. Sci. 2025, 15(14), 8117; https://doi.org/10.3390/app15148117 - 21 Jul 2025
Viewed by 268
Abstract
The architectural, engineering, construction, and operation (AECO) sector is one of the main contributors to energy consumption and greenhouse gas emissions in Europe, making the renovation of the existing building stock a priority. However, defining effective and economically sustainable interventions remains a challenge, [...] Read more.
The architectural, engineering, construction, and operation (AECO) sector is one of the main contributors to energy consumption and greenhouse gas emissions in Europe, making the renovation of the existing building stock a priority. However, defining effective and economically sustainable interventions remains a challenge, partly due to the variability of building characteristics and the lack of digital tools to support data-driven decision making. This research aims to identify the main factors influencing the energy consumption of buildings by analyzing a large database of building characteristics using machine learning algorithms. Based on the parameters that the analysis shows to have the greatest impact, the average cost of energy retrofitting measures will be used to elaborate a cost–benefit analysis model and the economic payback time for each measure, individually or in combination. The expected result is the creation of a tool that will allow the operator to evaluate the choice of interventions based on the energy efficiency that can be achieved and/or the economic sustainability. The proposed methodology aims to provide a digital approach that is replicable and adaptable to different territorial realities and useful for strategic planning of energy transformation in the building sector. Full article
(This article belongs to the Special Issue Advances in Building Energy Efficiency and Design)
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23 pages, 5397 KiB  
Article
A Systematic Analysis of Influencing Factors on Wind Resilience in a Coastal Historical District of China
by Bo Huang, Zhenmin Ou, Gang Zhao, Junwu Wang, Lanjun Liu, Sijun Lv, Bin Huang and Xueqi Liu
Appl. Sci. 2025, 15(14), 8116; https://doi.org/10.3390/app15148116 - 21 Jul 2025
Viewed by 243
Abstract
Historical districts are the mark of the continuity of urban history and are non-renewable. Typhoon disasters rank among the most serious and frequent natural threats to China’s coastal regions. Improving the wind resilience of China’s coastal historical districts is of great significance for [...] Read more.
Historical districts are the mark of the continuity of urban history and are non-renewable. Typhoon disasters rank among the most serious and frequent natural threats to China’s coastal regions. Improving the wind resilience of China’s coastal historical districts is of great significance for their protection and inheritance. Accurately analyzing the different characteristics of the influencing factors of wind resilience in China’s coastal historical districts can provide a theoretical basis for alleviating the damage caused by typhoons and formulating disaster prevention measures. This paper accurately identifies the main influencing factors of wind resilience in China’s coastal historical districts and constructs an influencing factor system from four aspects: block level, building level, typhoon characteristics, and emergency management. An IIM model for the systematic analysis of influencing factors of wind resilience in China’s coastal historical districts based on the Improved Decision Making Trial and Evaluation Laboratory (IDEMATEL), Interpretive Structural Modeling (ISM), and Matrices Impacts Croises-Multiplication Appliance Classement (MICMAC) methods is established. This allows us to explore the mechanism of action of internal influencing factors of typhoon disasters and construct an influencing factor system, in order to propose prevention measures from the perspective of typhoon disaster characteristics and the overall perspective of China’s coastal historical districts. The results show that the driving force of a building’s windproof design in China’s coastal historical districts is low, but its dependence is strong; the driving forces of block morphology, typhoon level, and emergency plan are strong, but their dependence is low. A building’s windproof design is a direct influencing factor of the wind resilience of China’s coastal historical districts; block morphology, typhoon level, and emergency plan are the most fundamental and key influencing factors of the wind resilience of China’s coastal historical districts. Full article
(This article belongs to the Special Issue Novel Research on Natural Disaster Prediction and Prevention Technology)
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19 pages, 9232 KiB  
Article
Peculiarities of Assessing Body Strength When Converting a Bus from Diesel to Electric Traction Following the UNECE R100 Regulation
by Kostyantyn Holenko, Oleksandr Dykha, Eugeniusz Koda, Ivan Kernytskyy, Orest Horbay, Yuriy Royko, Ruslan Humeniuk, Yaroslav Sholudko, Vasyl Rys, Serhii Berezovetskyi, Tomasz Wierzbicki and Anna Markiewicz
Appl. Sci. 2025, 15(14), 8115; https://doi.org/10.3390/app15148115 - 21 Jul 2025
Viewed by 197
Abstract
The problem of the conversion of diesel buses to electric ones in connection with the inevitable introduction of the EURO 7 emission standards entails an automatic requirement to follow several additional United Nations Economic Commission for Europe rules, like R100 regulations. They regulate [...] Read more.
The problem of the conversion of diesel buses to electric ones in connection with the inevitable introduction of the EURO 7 emission standards entails an automatic requirement to follow several additional United Nations Economic Commission for Europe rules, like R100 regulations. They regulate the preservation of battery units at longitudinal 12 g and transverse 10 g accelerations without penetrating into the elements of the bus body. Three models (12 modes in total) of battery units with frames made of S235 steel were analysed. The maximum stress value varies between 364.89 MPa and 439.08 MPa in 10 g and 12 g modes, respectively, which is beyond the tensile strength (360 MPa) and provokes plastic deformations. The max deformations were recorded in the models with the highest average stress: 63.04 mm in the 12 g mode with an average stress of 83.18 MPa. The minimum deformations of 6.95 and 7.95 mm were found in the 10 g modes (left and right acceleration direction, respectively), which meet the manufacturer’s requirements (45–50 mm maximum). The study’s primary contribution lies in developing a practical method for assessing battery unit integrity and structural behaviour during the conversion of diesel buses to electric propulsion, fully compliant with R100 regulations. By combining transient structural simulation, mathematical centre modelling of acceleration propagation, and centre of gravity prediction, the proposed approach enables engineers to evaluate electric conversions’ safety and certification feasibility without modifying the existing bus body. Full article
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17 pages, 7542 KiB  
Article
Accelerated Tensor Robust Principal Component Analysis via Factorized Tensor Norm Minimization
by Geunseop Lee
Appl. Sci. 2025, 15(14), 8114; https://doi.org/10.3390/app15148114 - 21 Jul 2025
Viewed by 171
Abstract
In this paper, we aim to develop an efficient algorithm for the solving Tensor Robust Principal Component Analysis (TRPCA) problem, which focuses on obtaining a low-rank approximation of a tensor by separating sparse and impulse noise. A common approach is to minimize the [...] Read more.
In this paper, we aim to develop an efficient algorithm for the solving Tensor Robust Principal Component Analysis (TRPCA) problem, which focuses on obtaining a low-rank approximation of a tensor by separating sparse and impulse noise. A common approach is to minimize the convex surrogate of the tensor rank by shrinking its singular values. Due to the existence of various definitions of tensor ranks and their corresponding convex surrogates, numerous studies have explored optimal solutions under different formulations. However, many of these approaches suffer from computational inefficiency primarily due to the repeated use of tensor singular value decomposition in each iteration. To address this issue, we propose a novel TRPCA algorithm that introduces a new convex relaxation for the tensor norm and computes low-rank approximation more efficiently. Specifically, we adopt the tensor average rank and tensor nuclear norm, and further relax the tensor nuclear norm into a sum of the tensor Frobenius norms of the factor tensors. By alternating updates of the truncated factor tensors, our algorithm achieves efficient use of computational resources. Experimental results demonstrate that our algorithm achieves significantly faster performance than existing reference methods known for efficient computation while maintaining high accuracy in recovering low-rank tensors for applications such as color image recovery and background subtraction. Full article
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19 pages, 4782 KiB  
Article
PD Detection and Analysis Triggered by Metal Protrusion in GIS Through Various Methods
by Weifeng Xin, Wei Song, Manling Dong, Xiaochuan Huang, Xiaoshi Kou, Zhenyu Zhan, Xinyue Shi and Xutao Han
Appl. Sci. 2025, 15(14), 8113; https://doi.org/10.3390/app15148113 - 21 Jul 2025
Viewed by 247
Abstract
Defects in GIS can be effectively detected by detecting the partial discharge (PD). The common methods of detecting partial discharge are pulse current, ultrasonic and UHF (ultra-high frequency). However, the results of different methods may be different due to the different physical quantities [...] Read more.
Defects in GIS can be effectively detected by detecting the partial discharge (PD). The common methods of detecting partial discharge are pulse current, ultrasonic and UHF (ultra-high frequency). However, the results of different methods may be different due to the different physical quantities detected. It is important to research the differences between the PD detection methods for the PD detection and analysis. In this study, we designed metal protrusion defects in GIS, including protrusion on the conductor and enclosure. Then, we detected the PD of defects using pulse current, UHF and ultrasonic methods at the same time. The PRPD patterns, maximum discharge amplitude of different defects and PD inception voltage (PDIV) detected by the three methods were analyzed. The PRPD patterns and discharge amplitude of the different methods were very similar to each other, but the PDIVs were different. It can be concluded that the process from the PD inception to breakdown can be divided into four sections based on the PRPD and the maximum discharge amplitude. The similarity between the three methods is because their signals are all related to the pulse current during the PD process, and differences in their PDIVs are caused by the differences in sensitivity. The sensitivity of the pulse current is the lowest among the three methods due to its poor anti-jamming capability. The sensitivity of UHF is higher, and that of ultrasonic is the highest. Full article
(This article belongs to the Special Issue Advances in Monitoring and Fault Diagnosis for Power Equipment)
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27 pages, 1337 KiB  
Review
Incorporating Waste Plastics into Pavement Materials: A Review of Opportunities, Risks, Environmental Implications, and Monitoring Strategies
by Ali Ghodrati, Nuha S. Mashaan and Themelina Paraskeva
Appl. Sci. 2025, 15(14), 8112; https://doi.org/10.3390/app15148112 - 21 Jul 2025
Viewed by 265
Abstract
The integration of waste plastics into pavement materials offers a dual benefit of enhancing road performance and mitigating the environmental burden of plastic waste. This review critically examines the opportunities and challenges associated with incorporating waste plastics in pavement construction, with an emphasis [...] Read more.
The integration of waste plastics into pavement materials offers a dual benefit of enhancing road performance and mitigating the environmental burden of plastic waste. This review critically examines the opportunities and challenges associated with incorporating waste plastics in pavement construction, with an emphasis on their impact on the mechanical properties, durability, and life cycle performance of pavements. Special attention is given to the environmental implications, particularly the potential generation and release of micro- and nano-plastics during the pavement life cycle. This paper further evaluates current monitoring and analytical methodologies for detecting plastic emissions from road surfaces and explores emerging approaches for minimizing environmental risks. By providing a comprehensive synthesis of existing knowledge, this review seeks to support sustainable practices and inform policy development within the frameworks of circular economy and environmental stewardship. Full article
(This article belongs to the Special Issue Nano/Micro Plastic and Emerging Plastic in the Environment: Monitoring, Analysis, and Remediation)
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16 pages, 1309 KiB  
Review
Microbial Peptidases: Key Players in Reducing Gluten Immunogenicity Through Peptide Degradation
by Africa Sanchiz, M. Isabel San-Martín, N. Navasa, Honorina Martínez-Blanco, Miguel Ángel Ferrero, Leandro Benito Rodríguez-Aparicio and Alejandro Chamizo-Ampudia
Appl. Sci. 2025, 15(14), 8111; https://doi.org/10.3390/app15148111 - 21 Jul 2025
Viewed by 202
Abstract
Gluten-related disorders, including celiac disease (CeD) and non-celiac gluten sensitivity (NCGS), are triggered by the immune response to gluten peptides that resist complete digestion by human gastrointestinal enzymes. Microbial peptidases have emerged as promising biocatalysts capable of degrading these immunogenic peptides, offering potential [...] Read more.
Gluten-related disorders, including celiac disease (CeD) and non-celiac gluten sensitivity (NCGS), are triggered by the immune response to gluten peptides that resist complete digestion by human gastrointestinal enzymes. Microbial peptidases have emerged as promising biocatalysts capable of degrading these immunogenic peptides, offering potential therapeutic and industrial applications. This review explores the role of microbial peptidases in gluten degradation, highlighting key enzyme families, their mechanisms of action, and their effectiveness in reducing gluten immunogenicity. Additionally, we discuss advances in enzymatic therapy, food processing applications, and the challenges associated with optimizing microbial enzymes for safe and efficient gluten detoxification. Understanding the potential of microbial peptidases in mitigating gluten-related disorders paves the way for novel dietary and therapeutic strategies. Full article
(This article belongs to the Special Issue Fifth Anniversary of 'Food Science and Technology' Section—Recent Advances in Food)
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15 pages, 4319 KiB  
Article
Study on the Frost Heaving Characteristics and Strength Deterioration of Saturated Red Sandstone Under a Unidirectional Freeze–Thaw Cycle
by Zhongyao Li, Qingyang Ren, Zhen Liu, Peiqing Wang and Hao Tang
Appl. Sci. 2025, 15(14), 8110; https://doi.org/10.3390/app15148110 - 21 Jul 2025
Viewed by 256
Abstract
In order to explore the influence of the temperature gradient on rock failure degree during freezing and thawing, freeze–thaw-cycle tests were carried out on saturated red sandstone under the conditions of all-directional freeze–thaw and unidirectional freeze–thaw. The results show that the deformation behavior [...] Read more.
In order to explore the influence of the temperature gradient on rock failure degree during freezing and thawing, freeze–thaw-cycle tests were carried out on saturated red sandstone under the conditions of all-directional freeze–thaw and unidirectional freeze–thaw. The results show that the deformation behavior of saturated red sandstone during freeze–thaw cycles is significantly affected by freeze–thaw direction, and the redistribution of water during freeze–thaw cycles leads to significant strain variations. Macro-cracks caused by all-directional freeze–thaw are located in the center of the sample and crack from the inside out, while macro-cracks caused by unidirectional freeze–thaw are perpendicular to the temperature gradient direction and located in the lower part of the sample. Unidirectional freeze–thaw cycles cause the vertical inhomogeneity of the sample to be more obvious, and the uniaxial compressive strength of the sample decreases more significantly in the early stage. After 30 freeze–thaw cycles, the uniaxial strength of all-directional freeze–thaw and unidirectional freeze–thaw samples tends to be stable and virtually identical. The freeze–thaw cycles have seriously damaged the micro-structure of the sample, but the extent of damage to the cementing agents between particles is weaker than that caused by the all-directional freeze–thaw, owing to the seepage path formed in the pore water under unidirectional freeze–thaw conditions. Full article
(This article belongs to the Section Civil Engineering)
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15 pages, 3416 KiB  
Article
The Study of Tribological Characteristics of YSZ/NiCrAlY Coatings and Their Resistance to CMAS at High Temperatures
by Dastan Buitkenov, Zhuldyz Sagdoldina, Aiym Nabioldina and Cezary Drenda
Appl. Sci. 2025, 15(14), 8109; https://doi.org/10.3390/app15148109 - 21 Jul 2025
Viewed by 252
Abstract
This paper presents the results of a comprehensive study of the structure, phase composition, thermal corrosion, and tribological properties of multilayer gradient coatings based on YSZ/NiCrAlY obtained using detonation spraying. X-ray phase analysis showed that the coatings consist entirely of metastable tetragonal zirconium [...] Read more.
This paper presents the results of a comprehensive study of the structure, phase composition, thermal corrosion, and tribological properties of multilayer gradient coatings based on YSZ/NiCrAlY obtained using detonation spraying. X-ray phase analysis showed that the coatings consist entirely of metastable tetragonal zirconium dioxide (t’-ZrO2) phase stabilized by high temperature and rapid cooling during spraying. SEM analysis confirmed the multilayer gradient phase distribution and high density of the structure. Wear resistance, optical profilometry, wear quantification, and coefficient of friction measurements were used to evaluate the operational stability. The results confirm that the structural parameters of the coating, such as porosity and phase gradient, play a key role in improving its resistance to thermal corrosion and CMAS melt, which makes such coatings promising for use in high-temperature applications. It is shown that a dense and thick coating effectively prevents the penetration of aggressive media, providing a high barrier effect and minimal structural damage. Tribological tests in the temperature range from 21 °C to 650 °C revealed that the best characteristics are observed at 550 °C: minimum coefficient of friction (0.63) and high stability in the stage of stable wear. At room temperature and at 650 °C, there is an increase in wear due to the absence or destabilization of the protective layer. Full article
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20 pages, 2036 KiB  
Article
Predicting Soccer Player Salaries with Both Traditional and Automated Machine Learning Approaches
by Davronbek Malikov, Pilsu Jung and Jaeho Kim
Appl. Sci. 2025, 15(14), 8108; https://doi.org/10.3390/app15148108 - 21 Jul 2025
Viewed by 225
Abstract
Soccer’s global popularity as the world’s favorite sport is driven by many factors, with high player salaries being one of the key reasons behind its appeal. These salaries not only reflect on-field performance, but also capture a broader evaluation of player value. Despite [...] Read more.
Soccer’s global popularity as the world’s favorite sport is driven by many factors, with high player salaries being one of the key reasons behind its appeal. These salaries not only reflect on-field performance, but also capture a broader evaluation of player value. Despite the increasing use of performance data in sports analytics, a critical gap remains in establishing fair compensation models that comprehensively account for both quantifiable and intangible contributions. To address these challenges, this study adopts machine learning (ML) techniques that model player salaries based on a combination of performance metrics and contextual features. This research focuses on reducing bias and improving transparency in salary decisions through a systematic, data-driven approach. Utilizing a dataset spanning the 2016–2022 seasons, we apply both traditional and automated ML frameworks to uncover the most influential factors in salary determination. The results indicate a nearly 17% improvement in R2 and about a 30% reduction in MAE after incorporating the newly constructed features and methods, demonstrating a significant enhancement in model performance. Gradient Boosting demonstrates superior effectiveness, revealing a group of significantly underestimated and overestimated players, and showcasing the model’s proficiency in detecting valuation discrepancies. Full article
(This article belongs to the Topic Advances in Integrative AI, Machine Learning, and Big Data for Transformative Applications)
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14 pages, 1261 KiB  
Article
Ultrasonic Processing and Its Impact on the Rheology and Physical Stability of Flaxseed Fiber Dispersions
by Maria-Carmen Alfaro-Rodríguez, Maria-Carmen Garcia-González and José Muñoz
Appl. Sci. 2025, 15(14), 8107; https://doi.org/10.3390/app15148107 - 21 Jul 2025
Viewed by 232
Abstract
Ultrasonic homogenization is an emerging technique with significant potential to modify the structure and functionality of food ingredients. This study evaluated the effect of ultrasonic homogenization on the rheological behavior and physical stability of aqueous dispersions of flaxseed fiber. Flax mucilage, with health-promoting [...] Read more.
Ultrasonic homogenization is an emerging technique with significant potential to modify the structure and functionality of food ingredients. This study evaluated the effect of ultrasonic homogenization on the rheological behavior and physical stability of aqueous dispersions of flaxseed fiber. Flax mucilage, with health-promoting and techno-functional properties, is of growing interest in several industries. The samples were subjected to different ultrasonic treatments, varying in amplitude (from 40 to 100%) and duration (from 2 to 20 min), with and without preliminary rotor–stator homogenization. The rheological properties were analyzed using small-amplitude oscillatory shear (SAOS) tests and steady shear flow curves. Physical stability was assessed by multiple light scattering. The results revealed that short treatment under ultrasonic homogenization had minimal impact on the viscoelastic parameters and viscosity, regardless of the amplitude used. However, longer treatments significantly reduced both values by at least one order of magnitude or more, indicating the occurrence of microstructural degradation. The relevance of this research lies in its direct applicability to the development of functional foods, since it is concluded that control of the ultrasonic homogenization process conditions must be carefully selected to retain the desirable rheological properties and physical stability. Full article
(This article belongs to the Special Issue Emerging Processing Techniques and Their Impact on Physicochemical, Sensory, and Nutritional Properties of Foods)
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13 pages, 2975 KiB  
Article
Calculation of Aging Coefficient for Establishing Aging Condition Index of Thermoplastic Insulated Power Cables
by Seung-Won Lee, Ik-Su Kwon, Byung-Bae Park, Sung-ho Yoon, Dong-Eun Kim, Jin-Seok Lim and Hae-Jong Kim
Appl. Sci. 2025, 15(14), 8106; https://doi.org/10.3390/app15148106 - 21 Jul 2025
Viewed by 215
Abstract
The growing demand for direct current transmission emphasizes the need for advanced insulation suitable for high-capacity, long-distance applications. Thermoplastics, especially polypropylene, offer several advantages over conventional materials like XLPE (cross-linked polyethylene) and EPR (ethylene propylene rubber), including higher thermal stability, recyclability, and reduced [...] Read more.
The growing demand for direct current transmission emphasizes the need for advanced insulation suitable for high-capacity, long-distance applications. Thermoplastics, especially polypropylene, offer several advantages over conventional materials like XLPE (cross-linked polyethylene) and EPR (ethylene propylene rubber), including higher thermal stability, recyclability, and reduced space charge accumulation. However, due to the inherent rigidity and limited flexibility of PP, its mechanical aging becomes a critical factor in assessing its long-term reliability as a cable insulation. In this study, mechanical aging characteristics, specifically declines in tensile strength and elongation, were selected as key indicators of insulation aging. Accelerated aging tests were conducted at 90 °C, 110 °C, and 130 °C for up to 5000 h. The experimental data were fitted to exponential models to derive aging coefficients, which formed the basis for the proposed aging model and the ACI (aging condition index). The ACI enables quantitative assessment of the current insulation condition and estimation of the remaining lifetime until a predefined threshold (e.g., ACI = 0.5) is reached. These findings contribute to the development of condition-based maintenance strategies and long-term asset management for power cables, offering practical insights for improving the reliability of future power grid systems. Full article
(This article belongs to the Special Issue Insulation Monitoring and Diagnosis of Electrical Equipment)
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25 pages, 4844 KiB  
Article
Numerical Investigations and Optimized Design of the Active Cooling Performance with Phase Change for Aircraft Rudder Shaft
by Xiangchun Sun, Kaiyan Jin, Kuan Zhao, Hexuan Zhang, Guice Yao and Dongsheng Wen
Appl. Sci. 2025, 15(14), 8105; https://doi.org/10.3390/app15148105 - 21 Jul 2025
Viewed by 192
Abstract
During hypersonic flight, the air rudder shaft can undergo huge aerodynamic heating load, where it is necessary to design the thermal protection system of the air rudder shaft. Aiming to prevent the rudder shaft from thermal failure due to the heat endurance limit [...] Read more.
During hypersonic flight, the air rudder shaft can undergo huge aerodynamic heating load, where it is necessary to design the thermal protection system of the air rudder shaft. Aiming to prevent the rudder shaft from thermal failure due to the heat endurance limit of materials, numerical investigations are conducted systemically to predict the active cooling performance of the rudder shaft with liquid water considering phase change. The validation of the numerical simulation method considering phase-change heat transfer is further investigated by experiments. The effect of coolant injection flow velocity on the active cooling performance is further analyzed for both the steady state and transient state. Finally, to achieve better cooling performance, an optimized design of the cooling channels is performed in this work. The results of the transient numerical simulation show that, employing the initial cooling structures, it may undergo the heat transfer deterioration phenomenon under the coolant injection velocity below 0.2 m/s. For the rudder shaft with an optimized structure, the heat transfer deterioration can be significantly reduced, which significantly reduces the risk of thermal failure. Moreover, the total pressure drop of the optimized rudder shaft under the same coolant injection condition can be reduced by about 19% compared with the initial structure. This study provides a valuable contribution to the thermal protection performance for the rudder shaft, as a key component of aircraft under the aero heating process. Full article
(This article belongs to the Special Issue 5th Anniversary of Aerospace Science and Engineering Section—Recent Advances in Aerospace)
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27 pages, 16832 KiB  
Article
Effective Bus Travel Time Prediction System of Multiple Routes: Introducing PMLNet Based on MDARNN
by Jianmei Lei, Yulan Chen, Qingwen Han, Lingqiu Zeng and Guangyan He
Appl. Sci. 2025, 15(14), 8104; https://doi.org/10.3390/app15148104 - 21 Jul 2025
Viewed by 168
Abstract
Accurate bus travel time prediction is crucial for improving travel experience, especially in transfer journeys. This study introduces a novel multi-route bus travel time prediction system-based PMLNet, a partition and combination prediction framework, addressing the gap in accurate prediction models by incorporating macro [...] Read more.
Accurate bus travel time prediction is crucial for improving travel experience, especially in transfer journeys. This study introduces a novel multi-route bus travel time prediction system-based PMLNet, a partition and combination prediction framework, addressing the gap in accurate prediction models by incorporating macro and local impact factors. The system employs a pre-processing algorithm for constructing travel chains, partitions travel time into four components, utilizes LSTM along with the newly proposed MDARNN model for predicting each component, and applies four real-time traffic impact factors to calibrate the predictions of each component. Experimental validation on four bus routes demonstrates PMLNet’s superior performance, achieving mean absolute percentage errors (MAPE) as low as 2.91% and mean absolute errors (MAE) below 1.45 min, outperforming traditional models and various partitioned combination frameworks. These findings underscore PMLNet’s potential to significantly improve public transportation services by providing more accurate travel time predictions, ultimately enhancing the user experience in intelligent transportation systems. Full article
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52 pages, 2083 KiB  
Review
Large Language Models: A Structured Taxonomy and Review of Challenges, Limitations, Solutions, and Future Directions
by Pejman Peykani, Fatemeh Ramezanlou, Cristina Tanasescu and Sanly Ghanidel
Appl. Sci. 2025, 15(14), 8103; https://doi.org/10.3390/app15148103 - 21 Jul 2025
Viewed by 648
Abstract
Large language models (LLMs), as one of the most advanced achievements in the field of natural language processing (NLP), have made significant progress in areas such as natural language understanding and generation. However, attempts to achieve the widespread use of these models have [...] Read more.
Large language models (LLMs), as one of the most advanced achievements in the field of natural language processing (NLP), have made significant progress in areas such as natural language understanding and generation. However, attempts to achieve the widespread use of these models have met numerous challenges, encompassing technical, social, ethical, and legal aspects. This paper provides a comprehensive review of the various challenges associated with LLMs and analyzes the key issues related to these technologies. Among the challenges discussed are model interpretability, biases in data and model outcomes, ethical concerns regarding privacy and data security, and their high computational requirements. Furthermore, the paper examines how these challenges impact the applications of LLMs in fields such as healthcare, law, media, and education, emphasizing the importance of addressing these issues in the development and deployment of these models. Additionally, solutions for improving the robustness and control of models against biases and quality issues are proposed. Finally, the paper looks at the future of LLM research and the challenges that need to be addressed for the responsible and effective use of this technology. The goal of this paper is to provide a comprehensive analysis of the challenges and issues surrounding LLMs in order to enable the optimal and ethical use of these technologies in real-world applications. Full article
(This article belongs to the Special Issue Advances in Large Language Models: Techniques, Applications and Challenges)
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19 pages, 3456 KiB  
Article
A Probability Integral Parameter Inversion Method Integrating a Selection-Weighted Iterative Robust Genetic Algorithm
by Chuang Jiang, Wei Liu, Lei Wang, Xu Zhu and Hao Tan
Appl. Sci. 2025, 15(14), 8102; https://doi.org/10.3390/app15148102 - 21 Jul 2025
Viewed by 183
Abstract
The accurate inversion of mining subsidence prediction parameters is key to the precise prediction of deformation during mining. However, the use of traditional genetic algorithms (GA) for inversion prediction has problems such as poor resistance to differences, and the accuracy of inversion parameters [...] Read more.
The accurate inversion of mining subsidence prediction parameters is key to the precise prediction of deformation during mining. However, the use of traditional genetic algorithms (GA) for inversion prediction has problems such as poor resistance to differences, and the accuracy of inversion parameters is affected when key monitoring points are missing. In response to these issues, a probability integral parameter inversion method is proposed in this study that integrates a selection-weighted iterative robust genetic algorithm. This method combines the selection-weighted iteration method with a genetic algorithm to determine the weights of different observation values, and then a probability integral parameter inversion method is constructed for the fusion selection-weighted iterative robust GA. The results indicate that the fusion selection-weighted iterative robust GA is stronger than the traditional GA, and the parameters obtained have higher accuracy and greater reliability. An experiment using real working face engineering showed that, compared with the GA method, the RMSE (root mean square error) of the proposed method is reduced by 24.4 mm and 37.5 mm, thus verifying the usability of this method. Full article
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20 pages, 9221 KiB  
Article
Establishing Linearity of the MOSkin Detector for Ultra-High Dose-per-Pulse, Very-High-Energy Electron Radiotherapy Using Dose-Rate-Corrected EBT-XD Film
by James Cayley, Elette Engels, Tessa Charles, Paul Bennetto, Matthew Cameron, Joel Poder, Daniel Hausermann, Jason Paino, Duncan Butler, Dean Cutajar, Marco Petasecca, Anatoly Rosenfeld, Yaw-Ren Eugene Tan and Michael Lerch
Appl. Sci. 2025, 15(14), 8101; https://doi.org/10.3390/app15148101 - 21 Jul 2025
Viewed by 211
Abstract
Very-high-energy electrons, coupled with ultra-high dose rates, are being explored for their potential use in radiotherapy to treat deep-seated tumours. The dose per pulse needed to achieve ultra-high dose rates far exceeds the limit of current medical linear accelerator capabilities. A high dose [...] Read more.
Very-high-energy electrons, coupled with ultra-high dose rates, are being explored for their potential use in radiotherapy to treat deep-seated tumours. The dose per pulse needed to achieve ultra-high dose rates far exceeds the limit of current medical linear accelerator capabilities. A high dose per pulse has been observed as the limiting factor for many existing dosimeters, resulting in saturation at doses far below what is required. The MOSkin, an existing clinical quality assurance dosimeter, has previously been demonstrated as dose rate independent but has not been subjected to a high dose per pulse. Within this study, the MOSkins dose-per-pulse response was tested for linearity, with a dose per pulse as high as 23 Gy within 200 ns at the ANSTO Australian Synchrotron’s Pulsed Energetic Electrons for Research facility. While using EBT-XD film as a reference dosimeter, a dose rate dependence of the EBT-XD was discovered. Once confirmed and a correction factor established, EBT-XD was used as an independent reference measurement. This work presents confirmation of the MOSkin suitability for ultra-high dose-rate environments with an electron energy of 100 MeV, and a theoretical discussion of its dose-rate and dose-per-pulse independence; the MOSkin is the only detector suitable for both clinical quality assurance, and ultra-high dose-rate measurements in its standard, unmodified form. Full article
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15 pages, 2733 KiB  
Article
Dynamic Analysis of an Offshore Knuckle-Boom Crane Under Different Load Applications Laws
by Ivan Tomasi and Luigi Solazzi
Appl. Sci. 2025, 15(14), 8100; https://doi.org/10.3390/app15148100 - 21 Jul 2025
Viewed by 292
Abstract
This study investigates the dynamic behavior of an articulated boom offshore crane under various load application laws. The following steps were taken to perform numerical simulations using the finite-element method (FEM): Definition of the model’s geometry, materials, and boundary conditions. The modal analyses [...] Read more.
This study investigates the dynamic behavior of an articulated boom offshore crane under various load application laws. The following steps were taken to perform numerical simulations using the finite-element method (FEM): Definition of the model’s geometry, materials, and boundary conditions. The modal analyses reveal significant resonance frequencies in the direction of load application (payload). The crane’s displacement, velocity, and acceleration responses are closely related to load application laws, specifically the time required to reach the structure’s full payload (epsilon). It is highly correlated with the dynamic factor (maximum acceleration multiplied by payload), which has a wide range of effects on the structure, including the effects of overstress, overturning, buckling, and so on. The main findings reveal a very strong exponential correlation, allowing the dynamic effect to be estimated as a function of epsilon time. This is a useful tool for increasing the safety and reliability of offshore lifting operations. Full article
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13 pages, 948 KiB  
Article
Extended Photoionization Cross Section Calculations for C III
by V. Stancalie
Appl. Sci. 2025, 15(14), 8099; https://doi.org/10.3390/app15148099 - 21 Jul 2025
Viewed by 186
Abstract
Spectral features of photoionization of various levels of C III are reported. These include characteristics of Rydberg and Seaton resonances, low and high excited levels, lifetimes, and total and partial cross sections. Calculations are performed in the relativistic Breit–Pauli R-matrix method with close-coupling [...] Read more.
Spectral features of photoionization of various levels of C III are reported. These include characteristics of Rydberg and Seaton resonances, low and high excited levels, lifetimes, and total and partial cross sections. Calculations are performed in the relativistic Breit–Pauli R-matrix method with close-coupling approximation, including damping effects on the resonance structure associated with the core-excited states produced by the electron excitation of C IV and photoionization of C III. For bound channel contribution, the close-coupling wavefunction expansion for photoionization includes ground and 14 excited states of the target ion CIV and 105 states configurations of C III. Extensive sets of atomic data for bound fine-structure levels, resulting in 762 dipole-allowed transitions, radiative probabilities, and photoionization cross sections out of Jπ = 0± − 4± fine-structure levels are obtained. The ground-level photoionization cross section smoothly decreases with increasing energy, showing a very narrow, strong Rydberg resonance converging to the CIV 1s22p threshold. The work shows that prominent Seaton resonances for 2sns states with n ≥ 5, caused by photoexcitation of the core electron below the 2p threshold, visibly contribute to photoabsorption from excited states of C III. The present results provide highly accurate parameters of various model applications in plasma spectroscopy. Full article
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31 pages, 3729 KiB  
Review
Laminar Burning Velocity in Aviation Fuels: Conventional Kerosene, SAFs, and Key Hydrocarbon Components
by Zehua Song, Xinsai Yan, Ziyu Liu and Xiaoyi Yang
Appl. Sci. 2025, 15(14), 8098; https://doi.org/10.3390/app15148098 - 21 Jul 2025
Viewed by 352
Abstract
Sustainable aviation fuels (SAFs) are vitally important for aviation decarbonization. The laminar burning velocity (LBV), a key parameter reflecting the combustion behavior of fuel/oxidizer mixtures, serves as a fundamental metric for evaluating SAF performance. This paper systematically reviews and evaluates the LBV experiment [...] Read more.
Sustainable aviation fuels (SAFs) are vitally important for aviation decarbonization. The laminar burning velocity (LBV), a key parameter reflecting the combustion behavior of fuel/oxidizer mixtures, serves as a fundamental metric for evaluating SAF performance. This paper systematically reviews and evaluates the LBV experiment method and the performance of traditional aviation fuel, SAFs produced via different pathways, and individual components (n-alkanes, iso-alkanes, cycloalkanes, and aromatic hydrocarbons, as well as the impacts of isomers and homologues) in aviation fuels. It is found that LBV values of different SAFs exhibit significant fluctuations, approaching or slightly deviating from those of conventional aviation fuels. Carbon number, branching degree, substituent types, and testing methods in the components all affect LBV performance. Specifically, increased branching in iso-alkanes reduces LBV, cyclohexane and benzene show higher LBV than their methylated counterparts (methylcyclohexane and toluene), and n-alkylcyclohexanes/benzenes with short (C1–C3) side chains demonstrate minimal LBV variation. Spherical flame methods yield more consistent (and generally lower) LBV values than stagnation flame techniques. These findings provide insights for optimizing SAF–conventional fuel blends and enhancing drop-in compatibility while ensuring operational safety and usability. Full article
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12 pages, 309 KiB  
Article
Theoretical Study of the Impact of Al, Ga and In Doping on Magnetization, Polarization, and Band Gap Energy of CuFeO2
by A. T. Apostolov, I. N. Apostolova and J. M. Wesselinowa
Appl. Sci. 2025, 15(14), 8097; https://doi.org/10.3390/app15148097 - 21 Jul 2025
Viewed by 222
Abstract
We have conducted a first-time investigation into the multiferroic properties and band gap behavior of CuFeO2 doped with Al, Ga, and In ions at the Fe site, employing a microscopic model and Green’s function formalism. The tunability of the band gap across [...] Read more.
We have conducted a first-time investigation into the multiferroic properties and band gap behavior of CuFeO2 doped with Al, Ga, and In ions at the Fe site, employing a microscopic model and Green’s function formalism. The tunability of the band gap across a broad energy spectrum highlights the potential of perovskite materials for advanced applications, including photovoltaics, photodetectors, lasers, light-emitting diodes, and high-energy particle sensors. The disparity in ionic radii between the dopant and host ions introduces local lattice distortions, leading to modifications in the exchange interaction parameters. As a result, the influence of ion doping on various properties of CuFeO2 has been elucidated at microscopic level. Our findings indicate that Al doping enhances magnetization and reduces the band gap energy. In contrast, doping with Ga or In results in a decrease in magnetization and an increase in band gap energy. Additionally, it is demonstrated that ferroelectric polarization can be induced either via external magnetic fields or by Al substitution at the Fe site. The theoretical results show good qualitative agreement with experimental data, confirming the validity of the proposed model and method. Full article
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19 pages, 1602 KiB  
Article
From Classic to Cutting-Edge: A Near-Perfect Global Thresholding Approach with Machine Learning
by Nicolae Tarbă, Costin-Anton Boiangiu and Mihai-Lucian Voncilă
Appl. Sci. 2025, 15(14), 8096; https://doi.org/10.3390/app15148096 - 21 Jul 2025
Viewed by 178
Abstract
Image binarization is an important process in many computer-vision applications. This transforms the color space of the original image into black and white. Global thresholding is a quick and reliable way to achieve binarization, but it is inherently limited by image noise and [...] Read more.
Image binarization is an important process in many computer-vision applications. This transforms the color space of the original image into black and white. Global thresholding is a quick and reliable way to achieve binarization, but it is inherently limited by image noise and uneven lighting. This paper introduces a global thresholding method that uses the results of classical global thresholding algorithms and other global image features to train a regression model via machine learning. We prove through nested cross-validation that the model can predict the best possible global threshold with an average F-measure of 90.86% and a confidence of 0.79%. We apply our approach to a popular computer vision problem, document image binarization, and compare popular metrics with the best possible values achievable through global thresholding and with the values obtained through the algorithms we used to train our model. Our results show a significant improvement over these classical global thresholding algorithms, achieving near-perfect scores on all the computed metrics. We also compared our results with state-of-the-art binarization algorithms and outperformed them on certain datasets. The global threshold obtained through our method closely approximates the ideal global threshold and could be used in a mixed local-global approach for better results. Full article
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13 pages, 2300 KiB  
Article
A Hierarchically Structured Ni-NOF@ZIF-L Heterojunction Using Van Der Waals Interactions for Electrocatalytic Reduction of CO2 to HCOOH
by Liqun Wu, Xiaojun He and Jian Zhou
Appl. Sci. 2025, 15(14), 8095; https://doi.org/10.3390/app15148095 - 21 Jul 2025
Viewed by 217
Abstract
The electrocatalytic CO2 reduction reaction (CO2RR) offers an energy-saving and environmentally friendly approach to producing hydrocarbon fuels. The use of a gas diffusion electrode (GDE) flow cell has generally improved the rate of CO2RR, while the gas diffusion [...] Read more.
The electrocatalytic CO2 reduction reaction (CO2RR) offers an energy-saving and environmentally friendly approach to producing hydrocarbon fuels. The use of a gas diffusion electrode (GDE) flow cell has generally improved the rate of CO2RR, while the gas diffusion layer (GDL) remains a significant challenge. In this study, we successfully engineered a novel metal–organic framework (MOF) heterojunction through the controlled coating of zeolitic imidazolate framework (ZIF-L) on ultrathin nickel—metal–organic framework (Ni-MOF) nanosheets. This innovative architecture simultaneously integrates GDL functionality and exposes abundant solid–liquid–gas triple-phase boundaries. The resulting Ni-MOF@ZIF-L heterostructure demonstrates exceptional performance, achieving a formate Faradaic efficiency of 92.4% while suppressing the hydrogen evolution reaction (HER) to 6.7%. Through computational modeling of the optimized heterojunction configuration, we further elucidated its competitive adsorption behavior and electronic modulation effects. The experimental and theoretical results demonstrate an improvement in electrochemical CO2 reduction activity with suppressed hydrogen evolution for the heterojunction because of its hydrophobic interface, good electron transfer capability, and high CO2 adsorption at the catalyst interface. This work provides a new insight into the rational design of porous crystalline materials in electrocatalytic CO2RR. Full article
(This article belongs to the Topic Water Splitting and CO2 Reduction via Electrocatalysis and Photocatalysis)
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15 pages, 724 KiB  
Article
Multi-View Cluster Structure Guided One-Class BLS-Autoencoder for Intrusion Detection
by Qifan Yang, Yu-Ang Chen and Yifan Shi
Appl. Sci. 2025, 15(14), 8094; https://doi.org/10.3390/app15148094 - 21 Jul 2025
Viewed by 215
Abstract
Intrusion detection systems are crucial for cybersecurity applications. Network traffic data originate from diverse terminal sources, exhibiting multi-view feature spaces, while the collection of unknown intrusion data is costly. Current one-class classification (OCC) approaches are mainly designed for single-view data. Multi-view OCC approaches [...] Read more.
Intrusion detection systems are crucial for cybersecurity applications. Network traffic data originate from diverse terminal sources, exhibiting multi-view feature spaces, while the collection of unknown intrusion data is costly. Current one-class classification (OCC) approaches are mainly designed for single-view data. Multi-view OCC approaches usually require collecting multi-view traffic data from all sources and have difficulty detecting intrusion independently in each view. Furthermore, they commonly ignore the potential subcategories in normal traffic data. To address these limitations, this paper utilizes the Broad Learning System (BLS) technique and proposes an intrusion detection framework based on a multi-view cluster structure guided one-class BLS-autoencoder (IDF-MOCBLSAE). Specifically, a multi-view co-association matrix optimization objective function with doubly-stochastic constraints is first designed to capture the cross-view cluster structure. Then, a multi-view cluster structure guided one-class BLS-autoencoder (MOCBLSAEs) is proposed, which learns the discriminative patterns of normal traffic data by preserving the cross-view clustering structure while minimizing the intra-view sample reconstruction errors, thereby enabling the identification of unknown intrusion data. Finally, an intrusion detection framework is constructed based on multiple MOCBLSAEs to achieve both individual and ensemble intrusion detection. Through experimentation, IDF-MOCBLSAE is validated on real-world network traffic datasets for multi-view one-class classification tasks, demonstrating its superiority over state-of-the-art one-class approaches. Full article
(This article belongs to the Special Issue Robust and Secure Learning and Applications for Heterogeneous Data from Multiple Sources)
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27 pages, 448 KiB  
Review
A Review of Mathematical Models in Robotics
by Pubudu Suranga Dasanayake, Virginijus Baranauskas, Gintaras Dervinis and Leonas Balasevicius
Appl. Sci. 2025, 15(14), 8093; https://doi.org/10.3390/app15148093 - 21 Jul 2025
Viewed by 403
Abstract
In robotics, much emphasis is placed on mathematical modeling, as the creation, control, and optimization of robots for a wide field of work must be achieved precisely and adaptively. The aim of this paper is to present a systematic and structured approach to [...] Read more.
In robotics, much emphasis is placed on mathematical modeling, as the creation, control, and optimization of robots for a wide field of work must be achieved precisely and adaptively. The aim of this paper is to present a systematic and structured approach to the literature review of mathematical models in robotics, critically considering mathematical frameworks that influence and shape robotics in light of current and prevailing trends. The paper underlines the complexities of maintaining accurate dynamic representations in robotic systems, revealing the challenges that arise from numerical simplifications. The study outlines the development of efficient remote-control systems that consider dynamic relationships among the components comprising the robot. The findings of the recent simulation prove that the developed mathematical model effectively supports designing an adaptive control system with artificial intelligence features, especially for autonomous mobile robotics with manipulators that are inherently complex and networked systems. If models are to accelerate robotics progress toward increasingly intelligent, adaptive, and efficient systems, they must learn to overcome some of the computational challenges while leveraging disciplinary synergies. Full article
(This article belongs to the Special Issue Automation and Robotics: Latest Achievements, Challenges and Prospects, Volume 2)
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17 pages, 382 KiB  
Review
Physics-Informed Neural Networks: A Review of Methodological Evolution, Theoretical Foundations, and Interdisciplinary Frontiers Toward Next-Generation Scientific Computing
by Zhiyuan Ren, Shijie Zhou, Dong Liu and Qihe Liu
Appl. Sci. 2025, 15(14), 8092; https://doi.org/10.3390/app15148092 - 21 Jul 2025
Viewed by 559
Abstract
Physics-informed neural networks (PINNs) have emerged as a transformative methodology integrating deep learning with scientific computing. This review establishes a three-dimensional analytical framework to systematically decode PINNs’ development through methodological innovation, theoretical breakthroughs, and cross-disciplinary convergence. The contributions include threefold: First, identifying the [...] Read more.
Physics-informed neural networks (PINNs) have emerged as a transformative methodology integrating deep learning with scientific computing. This review establishes a three-dimensional analytical framework to systematically decode PINNs’ development through methodological innovation, theoretical breakthroughs, and cross-disciplinary convergence. The contributions include threefold: First, identifying the co-evolutionary path of algorithmic architectures from adaptive optimization (neural tangent kernel-guided weighting achieving 230% convergence acceleration in Navier-Stokes solutions) to hybrid numerical-deep learning integration (5× speedup via domain decomposition) and second, constructing bidirectional theory-application mappings where convergence analysis (operator approximation theory) and generalization guarantees (Bayesian-physical hybrid frameworks) directly inform engineering implementations, as validated by 72% cost reduction compared to FEM in high-dimensional spaces (p<0.01,n=15 benchmarks). Third, pioneering cross-domain knowledge transfer through application-specific architectures: TFE-PINN for turbulent flows (5.12±0.87% error in NASA hypersonic tests), ReconPINN for medical imaging (▵SSIM=+0.18±0.04 on multi-institutional MRI), and SeisPINN for seismic systems (0.52±0.18 km localization accuracy). We further present a technological roadmap highlighting three critical directions for PINN 2.0: neuro-symbolic, federated physics learning, and quantum-accelerated optimization. This work provides methodological guidelines and theoretical foundations for next-generation scientific machine learning systems. Full article
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