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Volume 13
Issue 8
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Technologies, Volume 13, Issue 8 (August 2025) – 66 articles

Cover Story (view full-size image): This paper presents a unified, step-by-step methodology for designing robotic systems, applicable across diverse fields from healthcare to industry. The approach integrates mathematical modeling, simulation, and optimization into six sequential phases: from defining product specifications to virtual prototyping and experimental validation. By combining kinematics, dynamics, control theory, and parametric CAD tools, the framework ensures that each design choice is theoretically sound and practically feasible. It reduces development time and costs, improves reproducibility, and fosters collaboration among multidisciplinary teams. This systematic workflow bridges the gap between research and real-world deployment, offering a reliable blueprint for creating robust, adaptable, and high-performance robotic solutions. View this paper
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12 pages, 6191 KB  
Article
Influence of Filament Moisture on 3D Printing Nylon
by Haijun Gong, Michael Runzi, Zezheng Wang, Lianjun Wu and Yue Zhang
Technologies 2025, 13(8), 376; https://doi.org/10.3390/technologies13080376 - 21 Aug 2025
Viewed by 413
Abstract
Nylon filament is a widely used thermoplastic material in extrusion-based 3D printing, favored for its strength, durability, and excellent printability. It enables the fabrication of parts with complex geometries, high design flexibility, and cost-effective production, making it ideal for both prototyping and functional [...] Read more.
Nylon filament is a widely used thermoplastic material in extrusion-based 3D printing, favored for its strength, durability, and excellent printability. It enables the fabrication of parts with complex geometries, high design flexibility, and cost-effective production, making it ideal for both prototyping and functional components. However, one significant drawback of nylon is its hygroscopic nature—it readily absorbs moisture from the surrounding environment, often at a rapid rate. This moisture uptake can negatively impact the filament’s performance during printing, leading to poor surface finish, reduced mechanical strength, and altered thermal behavior in the final printed parts. To better understand the effects of moisture absorption, this study investigates the mechanical and thermal properties of nylon parts printed using filaments with varying levels of moisture content. The nylon filament was conditioned in a controlled humidity chamber for different durations to simulate moisture exposure over time. Specimens were then printed using these conditioned filaments, and a series of tests were performed to assess their mechanical integrity and thermal stability. By analyzing the test results, the study aims to establish a correlation between filament moisture content and part quality, offering valuable insights into the degradation mechanisms and guiding best practices for filament handling and storage in nylon 3D printing applications. Full article
(This article belongs to the Section Innovations in Materials Science and Materials Processing)
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15 pages, 3242 KB  
Article
Comparative Analysis of Multi-Layer and Single-Layer Injection Methods for Offshore CCS in Saline Aquifer Storage
by Jiayi Shen, Futao Mo, Tao Xuan, Qi Li and Yi Hong
Technologies 2025, 13(8), 375; https://doi.org/10.3390/technologies13080375 - 21 Aug 2025
Viewed by 285
Abstract
The aim of this study is to compare the performance of the multi-layer and the single-layer CO2 injection methods used in offshore carbon capture and storage (CCS) through TOUGH-FLAC numerical simulations. Four key indicators, namely CO2 saturation, pore pressure, vertical displacement, [...] Read more.
The aim of this study is to compare the performance of the multi-layer and the single-layer CO2 injection methods used in offshore carbon capture and storage (CCS) through TOUGH-FLAC numerical simulations. Four key indicators, namely CO2 saturation, pore pressure, vertical displacement, and Coulomb Failure Stress (CFS), are employed as indices to assess the storage capacity of reservoirs and the mechanical stability of caprocks. Numerical simulation results show that the multi-layer injection method increases the CO2 migration distance and reduces CFS values compared with the single-layer injection method. After 1 year of injection, the combined CO2 migration distance across two aquifers in Case 3 is 610 m, which is greater than that obtained using single-layer injection in Cases 1 and 2 (350 m and 380 m, respectively). Additionally, deep saline aquifers demonstrate superior CO2 storage capacity due to higher overburden pressure, which also reduces the risk of caprock failures. After 30 years of injection, in Cases 1 and 2, the maximum CFS values are 0.591 and 0.567, respectively, and the CO2 migration distances are 2400 m and 2650 m, respectively. Overall, the findings of this study indicate that the multi-layer injection method, particularly in deep saline aquifers, provides a safer and more efficient CO2 injection approach for offshore CCS projects. Full article
(This article belongs to the Section Environmental Technology)
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30 pages, 1923 KB  
Article
Perceived AI Consumer-Driven Decision Integrity: Assessing Mediating Effect of Cognitive Load and Response Bias
by Syed Md Faisal Ali Khan and Yasser Moustafa Shehawy
Technologies 2025, 13(8), 374; https://doi.org/10.3390/technologies13080374 - 20 Aug 2025
Viewed by 515
Abstract
This study examines the influence of artificial intelligence (AI) system transparency, cognitive load, response bias, and individual values on perceived AI decision integrity. Using a quantitative approach, data were collected through surveys and analyzed via SEM-PLS. The findings highlight that AI transparency and [...] Read more.
This study examines the influence of artificial intelligence (AI) system transparency, cognitive load, response bias, and individual values on perceived AI decision integrity. Using a quantitative approach, data were collected through surveys and analyzed via SEM-PLS. The findings highlight that AI transparency and familiarity significantly impact users’ trust and perception of decision fairness. Response biases were found to be increased by the cognitive load and decision fatigue, affecting decision integrity. This study identifies mediating effects of sensitivity to errors and response bias in AI-driven decision-making. Practical implications imply that lowering the cognitive load and increasing transparency will help to increase the acceptance of AI, and incorporating ethical considerations into AI system design helps to minimize bias. This study contributes to AI ethics by emphasizing fairness, explainability, and user-centered trust mechanisms. Future research should explore AI decision-making across industries and cultural contexts. The findings of this study offer managerial, theoretical, and practical insights into responsible AI deployment. Full article
(This article belongs to the Section Information and Communication Technologies)
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18 pages, 2540 KB  
Article
Using Solar Sails to Rendezvous with Asteroid 2024 YR4
by Alessandro A. Quarta
Technologies 2025, 13(8), 373; https://doi.org/10.3390/technologies13080373 - 20 Aug 2025
Viewed by 243
Abstract
This paper aims to present a set of possible transfer trajectories for a rendezvous mission with asteroid 2024 YR4, using a spacecraft propelled by a photonic solar sail. Asteroid 2024 YR4 was discovered in late December 2024 and was briefly classified as Torino [...] Read more.
This paper aims to present a set of possible transfer trajectories for a rendezvous mission with asteroid 2024 YR4, using a spacecraft propelled by a photonic solar sail. Asteroid 2024 YR4 was discovered in late December 2024 and was briefly classified as Torino Scale 3 for three weeks in early 2025, before being downgraded to zero at the end of February. In this study, rapid Earth-to-asteroid transfers are analyzed by solving a typical optimal control problem, in which the thrust vector generated by the solar sail is modeled using the optical force approach. Numerical simulations are carried out assuming a low-to-medium performance solar sail, considering both a simplified orbit-to-orbit transfer and a more accurate scenario that incorporates the actual ephemerides of the celestial bodies. The numerical results indicate that a medium-performance solar sail can reach asteroid 2024 YR4, achieving the global minimum flight time and arriving before its perihelion passage in late December 2032. Full article
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18 pages, 1956 KB  
Article
FCNet: A Transformer-Based Context-Aware Segmentation Framework for Detecting Camouflaged Fruits in Orchard Environments
by Ivan Roy Evangelista, Argel Bandala and Elmer Dadios
Technologies 2025, 13(8), 372; https://doi.org/10.3390/technologies13080372 - 20 Aug 2025
Viewed by 274
Abstract
Fruit segmentation is an essential task due to its importance in accurate disease prevention, yield estimation, and automated harvesting. However, accurate object segmentation in agricultural environments remains challenging due to visual complexities such as background clutter, occlusion, small object size, and color–texture similarities [...] Read more.
Fruit segmentation is an essential task due to its importance in accurate disease prevention, yield estimation, and automated harvesting. However, accurate object segmentation in agricultural environments remains challenging due to visual complexities such as background clutter, occlusion, small object size, and color–texture similarities that lead to camouflaging. Traditional methods often struggle to detect partially occluded or visually blended fruits, leading to poor detection performance. In this study, we propose a context-aware segmentation framework designed for orchard-level mango fruit detection. We integrate multiscale feature extraction based on PVTv2 architecture, a feature enhancement module using Atrous Spatial Pyramid Pooling (ASPP) and attention techniques, and a novel refinement mechanism employing a Position-based Layer Normalization (PLN). We conducted a comparative study against established segmentation models, employing both quantitative and qualitative evaluations. Results demonstrate the superior performance of our model across all metrics. An ablation study validated the contributions of the enhancement and refinement modules, with the former yielding performance gains of 2.43%, 3.10%, 5.65%, 4.19%, and 4.35% in S-measure, mean E-measure, weighted F-measure, mean F-measure, and IoU, respectively, and the latter achieving improvements of 2.07%, 1.93%, 6.85%, 4.84%, and 2.73%, in the said metrics. Full article
(This article belongs to the Special Issue Artificial Intelligence and Smart Information Systems: Trends and Innovations)
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17 pages, 1796 KB  
Article
High-Efficiency Broadband Doherty Power Amplifier Optimization Based on Genetic Algorithms and Neural Networks
by Jianping Xing, Yicheng Cai, Yixian Xu, Weiqing Dong and Jing Xia
Technologies 2025, 13(8), 371; https://doi.org/10.3390/technologies13080371 - 19 Aug 2025
Viewed by 270
Abstract
This paper proposes a design method for high-efficiency broadband Doherty power amplifiers (DPAs) optimized through a co-simulation approach combining genetic algorithms and neural networks. The method integrates the global search capability of genetic algorithms with the predictive power of neural networks to efficiently [...] Read more.
This paper proposes a design method for high-efficiency broadband Doherty power amplifiers (DPAs) optimized through a co-simulation approach combining genetic algorithms and neural networks. The method integrates the global search capability of genetic algorithms with the predictive power of neural networks to efficiently optimize the DPA matching network parameters. Key performance metrics such as output power, efficiency, and gain are incorporated into the objective function for comprehensive optimization. A DPA operating from 1.5 GHz to 2.6 GHz was designed and fabricated. Measurement results demonstrate that the optimized amplifier achieves saturated output power between 42.19 dBm and 44.7 dBm, saturated efficiency from 51.4% to 61.8%, and 6 dB back-off efficiency ranging from 44.3% to 56.4% across the bandwidth. These results verify the feasibility and effectiveness of the proposed optimization method. Full article
(This article belongs to the Section Information and Communication Technologies)
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26 pages, 304 KB  
Review
Vibration Measurement and Monitoring in Railway Vehicles
by Gabriel Popa, Razvan Andrei Oprea, Emil Tudor, Marius Alin Gheti and Iulian Sorin Munteanu
Technologies 2025, 13(8), 370; https://doi.org/10.3390/technologies13080370 - 19 Aug 2025
Viewed by 250
Abstract
The main purpose of this paper is to present a comprehensive and systematically organized overview of the current state of vibration monitoring and measurement techniques used in railway stock. It aims to raise awareness of significant technological developments in recent years and their [...] Read more.
The main purpose of this paper is to present a comprehensive and systematically organized overview of the current state of vibration monitoring and measurement techniques used in railway stock. It aims to raise awareness of significant technological developments in recent years and their practical applications. The scope of the analysis is strongly informed by established European norms, fundamental research efforts across the continent, and the practical needs of the railway sector. Last but not least, we hope this paper serves as a valuable reference point for engineers, researchers, and decision-makers working within the complex context of railway system design, maintenance, and evolving regulations. For effective monitoring of railway vehicle vibrations, a combination of specialized measurement methods and system architectures is recommended. These approaches are carefully developed to capture the dynamic responses of critical components of the railway vehicle, thereby providing invaluable data. This information is essential for thorough condition monitoring, improved ride comfort, and a deeper structural understanding of vehicle quality throughout its lifecycle. Full article
(This article belongs to the Special Issue Emerging Paradigms in AI, Autonomous Systems, and Intelligent Technologies)
35 pages, 4292 KB  
Article
A Framework for Standardizing the Development of Serious Games with Real-Time Self-Adaptation Capabilities Using Digital Twins
by Spyros Loizou and Andreas S. Andreou
Technologies 2025, 13(8), 369; https://doi.org/10.3390/technologies13080369 - 18 Aug 2025
Viewed by 441
Abstract
Serious games are an important tool for education and training that offers interactive and powerful experience. However, a significant challenge lays with adapting a game to meet the specific needs of each player in real-time. The present paper introduces a framework to guide [...] Read more.
Serious games are an important tool for education and training that offers interactive and powerful experience. However, a significant challenge lays with adapting a game to meet the specific needs of each player in real-time. The present paper introduces a framework to guide the development of serious games using a phased approach. The framework introduces a level of standardization for the game elements, scenarios and data descriptions, mainly to support portability, interpretability and comprehension. This standardization is achieved through semantic annotation and it is utilized by digital twins to support self-adaptation. The proposed approach describes the game environment using ontologies and specific semantic structures, while it collects and semantically tags data during players’ interactions, including performance metrics, decision-making patterns and levels of engagement. This information is then used by a digital twin for automatically adjusting the game experience using a set of rules defined by a group of domain experts. The framework thus follows a hybrid approach, combing expert knowledge with automated adaptation actions being performed to ensure meaningful educational content delivery and flexible, real-time personalization. Real-time adaptation includes modifying the game’s level of difficulty, controlling the learning ability support and maintaining a suitable level of challenge for each player based on progress. The framework is demonstrated and evaluated using two real-word examples, the first targeting at supporting the education of children with syndromes that affect their learning abilities in close collaboration with speech therapists and the second being involved with training engineers in a poultry meat factory. Preliminary, small-scale experimentation indicated that this framework promotes personalized and dynamic user experience, with improved engagement through the adjustment of gaming elements in real-time to match each player’s unique profile, actions and achievements. Using a specially prepared questionnaire the framework was evaluated by domain experts that suggested high levels of usability and game adaptation. Comparison with similar approaches via a set of properties and features indicated the superiority of the proposed framework. Full article
(This article belongs to the Topic Internet of Things Architectures, Applications, and Strategies: Emerging Paradigms, Technologies, and Advancing AI Integration)
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20 pages, 6571 KB  
Article
Effect of Foreign Object Damage on Corrosion Fatigue Behavior in Surface-Strengthened EA4T Railway Axle Steel
by Yan Luo, Gang Li, Cunhai Li, Chuanqi Qi, Yongxu Hu and Ping Yuan
Technologies 2025, 13(8), 368; https://doi.org/10.3390/technologies13080368 - 17 Aug 2025
Viewed by 335
Abstract
The electrochemical behavior and corrosion fatigue property of the surface-strengthened EA4T axle steel subjected to foreign object damage (FOD) is investigated in this study. It is found that the corrosion resistance can be enhanced after being impacted by the foreign object due to [...] Read more.
The electrochemical behavior and corrosion fatigue property of the surface-strengthened EA4T axle steel subjected to foreign object damage (FOD) is investigated in this study. It is found that the corrosion resistance can be enhanced after being impacted by the foreign object due to the introduced hardening layer. Specifically, compared to the smoothed sample, the 167 m/s sample exhibited a 13.88% higher corrosion potential (Ecorr) and a 67.61% lower current density (icorr). The facture surface demonstrates that the corrosion pits on the surface are the main crack initiation location for the smoothed specimens. In contrast, for the surface-damaged specimens, cracks initiate around the crater. The foreign object impact speed has a significant influence on the corrosion fatigue strength; specifically, the faster the impact velocity, the greater the surface damage of the axle specimen, and the shorter its fatigue life at the same stress level. To address the combined influence of size effect and surface defects on fatigue performance, we constructed an improved Kitagawa–Takahashi (KT) diagram by incorporating the theoretical corrosion fatigue limit of full-scale axles with a surface damage of 270 MPa based on conditional probability density function (CPDF). Comparative analysis demonstrates that the revised KT diagram defines a narrower yet more conservative fatigue loading safety zone than the standard KT diagram. This refinement enhances reliability in practical applications where surface imperfections and scale effects dominate failure mechanisms. Full article
(This article belongs to the Section Innovations in Materials Science and Materials Processing)
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24 pages, 8256 KB  
Article
Dual-Element Wideband CP Slot-Integrated MIMO Antenna with X-Notch Square AMC for DSRC Applications
by Chanwit Musika, Nathapat Supreeyatitikul, Jessada Konpang, Pongsathorn Chomtong and Prayoot Akkaraekthalin
Technologies 2025, 13(8), 367; https://doi.org/10.3390/technologies13080367 - 17 Aug 2025
Viewed by 600
Abstract
This study proposes a dual-element wideband circularly polarized (CP) slot-integrated multiple-input multiple-output (MIMO) antenna with an X-notch square-shaped artificial magnetic conductor (AMC) for dedicated short-range communications (DSRC) applications. The proposed antenna design consists of two substrate layers separated by an air gap. The [...] Read more.
This study proposes a dual-element wideband circularly polarized (CP) slot-integrated multiple-input multiple-output (MIMO) antenna with an X-notch square-shaped artificial magnetic conductor (AMC) for dedicated short-range communications (DSRC) applications. The proposed antenna design consists of two substrate layers separated by an air gap. The upper layer features a dual-element coplanar waveguide-fed slot antenna and a defected ground structure decoupling isolator, while the lower layer comprises an 8 × 8 array of X-notch square-shaped elemental units, functioning as an AMC reflector. Characteristic mode analysis shows that circular polarization is produced by the dominant orthogonal mode pair (modes J5 and J6), whose modal significance exceeds 0.92 and whose characteristic angle separation is 82° around the 5.9 GHz DSRC band. An I-shaped slot embedded in the ground plane of the upper layer serves as a defected ground structure isolator to suppress mutual coupling between antenna elements. Meanwhile, the X-notch square AMC reflector enhances radiation characteristics and antenna gain. The measured return loss bandwidth and axial ratio bandwidth are 32% (4.72–6.61 GHz) and 21.18% (5.2–6.45 GHz), respectively. The dual-element antenna scheme achieves high isolation exceeding 19 dB, with a maximum gain of 8.6 dBic at 5.9 GHz. The envelop correlation coefficient remains below 0.003, while the diversity gain exceeds 9.98 dB. Full article
(This article belongs to the Section Information and Communication Technologies)
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30 pages, 12979 KB  
Article
Optimizing Water Distribution in a Grid-Based Irrigation System Using Evolutionary Methods
by Doru Anastasiu Popescu, Anna Sotiropoulou, Nicolae Bold and Ion Alexandru Popescu
Technologies 2025, 13(8), 366; https://doi.org/10.3390/technologies13080366 - 17 Aug 2025
Viewed by 291
Abstract
This paper investigates the optimization of an irrigation system distributed over an agricultural area discretized into unit cells, using evolutionary algorithms for the control of water irrigation points (taps). The model simulates the distribution of water through strategically placed irrigation points, considering the [...] Read more.
This paper investigates the optimization of an irrigation system distributed over an agricultural area discretized into unit cells, using evolutionary algorithms for the control of water irrigation points (taps). The model simulates the distribution of water through strategically placed irrigation points, considering the individual requirements of each cell. The main objective is to minimize the difference between the amount of water needed and delivered, while reducing the total consumption. The dynamics of fitness over generations are analyzed, as well as the average behavior of deficit, surplus, and relative humidity. The results highlight a relatively uniform distribution of delivered water and a stable convergence of the fitness function, demonstrating the efficiency of the proposed method in managing water resources in a sustainable way. In this matter, compared to the full-activation scenario, the presented model reduced total water use by more than 50%, achieving zero deficit, minimal surplus, and a 46% improvement in overall fitness. Although the approach demonstrates promising results in simulated scenarios, it does not currently incorporate real-time sensor data or field validation, which are planned for future development. The study provides a solid basis for the development of smart irrigation systems, adaptable to the variability of soil and climatic conditions. Full article
(This article belongs to the Section Information and Communication Technologies)
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34 pages, 593 KB  
Review
Technology-Enhanced Musical Practice Using Brain–Computer Interfaces: A Topical Review
by André Perrotta, Jacinto Estima, Jorge C. S. Cardoso, Licínio Roque, Miguel Pais-Vieira and Carla Pais-Vieira
Technologies 2025, 13(8), 365; https://doi.org/10.3390/technologies13080365 - 16 Aug 2025
Viewed by 1302
Abstract
High-performance musical instrument training is a demanding discipline that engages cognitive, neurological, and physical skills. Professional musicians invest substantial time and effort into mastering their repertoire and developing the muscle memory and reflexes required to perform complex works in high-stakes settings. While existing [...] Read more.
High-performance musical instrument training is a demanding discipline that engages cognitive, neurological, and physical skills. Professional musicians invest substantial time and effort into mastering their repertoire and developing the muscle memory and reflexes required to perform complex works in high-stakes settings. While existing surveys have explored the use of music in therapeutic and general training contexts, there is a notable lack of work focused specifically on the needs of professional musicians and advanced instrumental practice. This topical review explores the potential of EEG-based brain–computer interface (BCI) technologies to integrate real-time feedback of biomechanic and cognitive features in advanced musical practice. Building on a conceptual framework of technology-enhanced musical practice (TEMP), we review empirical studies of broad contexts, addressing the EEG signal decoding of biomechanic and cognitive tasks that closely relates to the specified TEMP features (movement and muscle activity, posture and balance, fine motor movements and dexterity, breathing control, head and facial movement, movement intention, tempo processing, ptich recognition, and cognitive engagement), assessing their feasibility and limitations. Our analysis highlights current gaps and provides a foundation for future development of BCI-supported musical training systems to support high-performance instrumental practice. Full article
(This article belongs to the Section Assistive Technologies)
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24 pages, 1153 KB  
Review
Cryogenic Technologies for Biogas Upgrading: A Critical Review of Processes, Performance, and Prospects
by Dolores Hidalgo and Jesús M. Martín-Marroquín
Technologies 2025, 13(8), 364; https://doi.org/10.3390/technologies13080364 - 16 Aug 2025
Viewed by 607
Abstract
Cryogenic upgrading represents a promising route for the production of high-purity biomethane, aligning with current decarbonization goals and the increasing demand for renewable gases. This review provides a critical assessment of cryogenic technologies applied to biogas purification, focusing on process fundamentals, technological configurations, [...] Read more.
Cryogenic upgrading represents a promising route for the production of high-purity biomethane, aligning with current decarbonization goals and the increasing demand for renewable gases. This review provides a critical assessment of cryogenic technologies applied to biogas purification, focusing on process fundamentals, technological configurations, energy and separation performance, and their industrial integration potential. The analysis covers standalone cryogenic systems as well as hybrid configurations combining cryogenic separation with membrane or chemical pretreatment to enhance efficiency and reduce operating costs. A comparative evaluation of key performance indicators—including methane recovery, specific energy demand, product purity, and technology readiness level—is presented, along with a discussion of representative industrial applications. In addition, recent techno-economic studies are examined to contextualize cryogenic upgrading within the broader landscape of CO2 separation technologies. Environmental trade-offs, investment thresholds, and sensitivity to gas prices and CO2 taxation are also discussed. The review identifies existing technical and economic barriers, outlines research and innovation priorities, and highlights the relevance of process integration with natural gas networks. Overall, cryogenic upgrading is confirmed as a technically viable and environmentally competitive solution for biomethane production, particularly in contexts requiring liquefied biomethane or CO2 recovery. Strategic deployment and regulatory support will be key to accelerating its industrial adoption. The objectives of this review have been met by consolidating the current state of knowledge and identifying specific gaps that warrant further investigation. Future work is expected to address these gaps through targeted experimental studies and technology demonstrations. Full article
(This article belongs to the Section Environmental Technology)
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23 pages, 10266 KB  
Article
Application of Passive Serration Technologies for Aero-Engine Noise Control in Turbulent Inflow Environments
by Andrei-George Totu, Daniel-Eugeniu Crunțeanu, Marius Deaconu, Grigore Cican, Laurențiu Cristea and Constantin Levențiu
Technologies 2025, 13(8), 363; https://doi.org/10.3390/technologies13080363 - 15 Aug 2025
Viewed by 360
Abstract
This study explores the aeroacoustic influence of leading-edge serrations applied to stator blades subjected to turbulent inflow, which is representative of rotor–stator interaction in turbomachinery. A set of serrated geometries—75 mm span, with up to 9 teeth corresponding to 10% chord amplitude—was fabricated [...] Read more.
This study explores the aeroacoustic influence of leading-edge serrations applied to stator blades subjected to turbulent inflow, which is representative of rotor–stator interaction in turbomachinery. A set of serrated geometries—75 mm span, with up to 9 teeth corresponding to 10% chord amplitude—was fabricated via 3D printing and tested experimentally in a dedicated aeroacoustic facility at COMOTI. The turbulent inflow was generated using a passive grid, and far-field acoustic data were acquired using a semicircular microphone array placed in multiple inclined planes covering 15°–90° elevation and 0–180° azimuthal angles. The analysis combined power spectral density and autocorrelation techniques to extract turbulence-related quantities, such as integral length scale and velocity fluctuations. Beamforming methods were applied to reconstruct spatial distributions of sound pressure level (SPL), complemented by polar directivity curves to assess angular effects. Compared to the reference case, configurations with serrations demonstrated broadband noise reductions between 2 and 6 dB in the mid- and high-frequency range (1–4 kHz), with spatial consistency observed across measurement planes. The results extend the existing literature by linking turbulence properties to spatially resolved acoustic maps, offering new insights into the directional effects of serrated stator blades. Full article
(This article belongs to the Special Issue Aviation Science and Technology Applications)
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18 pages, 1981 KB  
Article
Enrichment of the HEPscore Benchmark by Energy Consumption Assessment
by Taras V. Panchenko and Nikita D. Piatygorskiy
Technologies 2025, 13(8), 362; https://doi.org/10.3390/technologies13080362 - 15 Aug 2025
Viewed by 320
Abstract
The HEPscore benchmark, widely used for evaluating computational performance in high-energy physics, has been identified as requiring energy consumption metrics to address the increasing importance of energy efficiency in large-scale computing infrastructures. This study introduces an energy measurement extension for HEPscore, designed to [...] Read more.
The HEPscore benchmark, widely used for evaluating computational performance in high-energy physics, has been identified as requiring energy consumption metrics to address the increasing importance of energy efficiency in large-scale computing infrastructures. This study introduces an energy measurement extension for HEPscore, designed to operate across diverse hardware platforms without requiring administrative privileges or physical modifications. The extension utilizes the Running Average Power Limit (RAPL) interface available in modern processors and dynamically selects the most suitable measurement method based on system capabilities. When RAPL access is unavailable, the system automatically switches to alternative measurement approaches. To validate the accuracy of the software-based measurements, external hardware monitoring devices were used to collect reference data directly from the power supply circuit. Obtained results demonstrate a significant correlation across multiple test platforms running standard HEP workloads. The developed extension integrates energy consumption data into standard HEPscore reports, enabling the calculation of energy efficiency metrics such as HEPscore/Watt. This implementation meets the requirements of the HEPiX Benchmarking Working Group, providing a reliable and portable solution for quantifying energy efficiency alongside computational performance. The proposed method supports informed decision making in resource planning and hardware acquisition for HEP computing environments. Full article
(This article belongs to the Section Information and Communication Technologies)
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18 pages, 3219 KB  
Article
Designing Trustworthy AI Systems for PTSD Follow-Up
by María Cazares, Jorge Miño-Ayala, Iván Ortiz and Roberto Andrade
Technologies 2025, 13(8), 361; https://doi.org/10.3390/technologies13080361 - 15 Aug 2025
Viewed by 347
Abstract
Post-Traumatic Stress Disorder (PTSD) poses complex clinical challenges due to its emotional volatility, contextual sensitivity, and need for personalized care. Conventional AI systems often fall short in therapeutic contexts due to lack of explainability, ethical safeguards, and narrative understanding. We propose a hybrid [...] Read more.
Post-Traumatic Stress Disorder (PTSD) poses complex clinical challenges due to its emotional volatility, contextual sensitivity, and need for personalized care. Conventional AI systems often fall short in therapeutic contexts due to lack of explainability, ethical safeguards, and narrative understanding. We propose a hybrid neuro-symbolic architecture that combines Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), symbolic controllers, and ensemble classifiers to support clinicians in PTSD follow-up. The proposal integrates real-time anonymization, session memory through patient-specific RAG, and a Human-in-the-Loop (HITL) interface. It ensures clinical safety via symbolic logic rules derived from trauma-informed protocols. The proposed architecture enables safe, personalized AI-driven responses by combining statistical language modeling with explicit therapeutic constraints. Through modular integration, it supports affective signal adaptation, longitudinal memory, and ethical traceability. A comparative evaluation against state-of-the-art approaches highlights improvements in contextual alignment, privacy protection, and clinician supervision. Full article
(This article belongs to the Special Issue AI-Enabled Smart Healthcare Systems)
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35 pages, 2065 KB  
Article
Methodological Framework for the Integrated Technical, Economic, and Environmental Evaluation of Solar Photovoltaic Systems in Agroindustrial Environments
by Reinier Jiménez Borges, Yoisdel Castillo Alvarez, Luis Angel Iturralde Carrera, Mariano Garduño Aparicio, Berlan Rodríguez Pérez and Juvenal Rodríguez-Reséndiz
Technologies 2025, 13(8), 360; https://doi.org/10.3390/technologies13080360 - 14 Aug 2025
Viewed by 295
Abstract
The transition to sustainable energy systems in the agroindustrial sector requires rigorous methodologies that enable a comprehensive and quantitative assessment of the technical and economic viability and environmental impact of photovoltaic integration. This study develops and validates a hybrid multi-criteria methodology structured in [...] Read more.
The transition to sustainable energy systems in the agroindustrial sector requires rigorous methodologies that enable a comprehensive and quantitative assessment of the technical and economic viability and environmental impact of photovoltaic integration. This study develops and validates a hybrid multi-criteria methodology structured in three phases: (i) analytical modeling of the load profile and preliminary sizing, (ii) advanced energy simulation using PVsyst for operational optimization and validation against empirical data, and (iii) environmental assessment using life cycle analysis (LCA) under ISO 14040/44 standards. The methodology is applied to a Cuban agroindustrial plant with an annual electricity demand of 290,870 kWh, resulting in the design of a 200 kWp photovoltaic system capable of supplying 291,513 kWh/year, thereby achieving total coverage of the electricity demand. The economic analysis yields an LCOE of 0.064 USD/kWh and an NPV of USD 139,408, while the environmental component allows for a mitigation of 113 t CO2-eq/year. The robustness of the model is validated by comparison with historical records, yielding an MBE of −0.65%, an RMSE of 2.87%, an MAPE of 2.62%, and an R2 of 0.98. This comprehensive approach demonstrates its superiority over previous methodologies by effectively integrating the three pillars of sustainability in an agroindustrial context, thus offering a scientifically sound, replicable, and adaptable tool for decision-making in advanced energy projects. The results position this methodology as a benchmark for future research and applications in emerging production scales. Full article
(This article belongs to the Special Issue Sustainable Water and Environmental Technologies of Global Relevance)
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39 pages, 6883 KB  
Article
SYNTHUA-DT: A Methodological Framework for Synthetic Dataset Generation and Automatic Annotation from Digital Twins in Urban Accessibility Applications
by Santiago Felipe Luna Romero, Mauren Abreu de Souza and Luis Serpa Andrade
Technologies 2025, 13(8), 359; https://doi.org/10.3390/technologies13080359 - 14 Aug 2025
Viewed by 356
Abstract
Urban scene understanding for inclusive smart cities remains challenged by the scarcity of training data capturing people with mobility impairments. We propose SYNTHUA-DT, a novel methodological framework that integrates unmanned aerial vehicle (UAV) photogrammetry, 3D digital twin modeling, and high-fidelity simulation in Unreal [...] Read more.
Urban scene understanding for inclusive smart cities remains challenged by the scarcity of training data capturing people with mobility impairments. We propose SYNTHUA-DT, a novel methodological framework that integrates unmanned aerial vehicle (UAV) photogrammetry, 3D digital twin modeling, and high-fidelity simulation in Unreal Engine to generate annotated synthetic datasets for urban accessibility applications. This framework produces photo-realistic images with automatic pixel-perfect segmentation labels, dramatically reducing the need for manual annotation. Focusing on the detection of individuals using mobility aids (e.g., wheelchairs) in complex urban environments, SYNTHUA-DT is designed as a generalized, replicable pipeline adaptable to different cities and scenarios. The novelty lies in combining real-city digital twins with procedurally placed virtual agents, enabling diverse viewpoints and scenarios that are impractical to capture in real life. The computational efficiency and scale of this synthetic data generation offer significant advantages over conventional datasets (such as Cityscapes or KITTI), which are limited in accessibility-related content and costly to annotate. A case study using a digital twin of Curitiba, Brazil, validates the framework’s real-world applicability: 22,412 labeled images were synthesized to train and evaluate vision models for mobility aids user detection. The results demonstrate improved recognition performance and robustness, highlighting SYNTHUA-DT’s potential to advance urban accessibility by providing abundant, bias-mitigating training data. This work paves the way for inclusive computer vision systems in smart cities through a rigorously engineered synthetic data pipeline. Full article
(This article belongs to the Topic Digital Twins and Artificial Intelligence for Advancing Smart Green Building and City Resilience)
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13 pages, 939 KB  
Article
Iterative User-Centered Design of the Mobile Device Assessment Tool (MoDAT)
by Andrea D. Fairman, Firdaus Ardhana Indradhirmaya, Ryan B. Osal and Andi Saptono
Technologies 2025, 13(8), 358; https://doi.org/10.3390/technologies13080358 - 14 Aug 2025
Viewed by 259
Abstract
The objective of this manuscript is to describe the iterative user-centered development of the Mobile Device Assessment Tool (MoDAT) and to present early usability results involving persons with disabilities and assistive technology (AT) professionals. Smartphones have become a ubiquitous tool for use in [...] Read more.
The objective of this manuscript is to describe the iterative user-centered development of the Mobile Device Assessment Tool (MoDAT) and to present early usability results involving persons with disabilities and assistive technology (AT) professionals. Smartphones have become a ubiquitous tool for use in everyday life. However, there are limited tools and resources available for AT providers to assess the needs of persons with disabilities in using smartphones. The MoDAT is being developed to help determine the most effective accessibility and AT options for smartphone use by individuals with functional limitations. A user-centered approach has been implemented, including preliminary guidance by advisory committees, focus groups, and usability testing by persons with disabilities and providers who recommend AT solutions. This process has guided the development of a pilot system that can generate personalized recommendations on smartphone device setup and configuration. The MoDAT consists of a series of simulated typical tasks completed on a smartphone application. Individuals complete these tasks to assess their functional capacity, with data regarding their performance gathered and sent to the provider portal. Data is securely stored in the portal for review to help determine accessibility settings and AT that may improve smartphone use. These results and the iterative process are described in this manuscript. Future research will focus on establishing the psychometric properties of the MoDAT as an assessment tool and outcomes. Full article
(This article belongs to the Special Issue Innovations in Design, Development and Evaluation of Assistive Technologies)
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26 pages, 6989 KB  
Article
Model-Based and Data-Driven Global Optimization of Rainbow-Trapping Mufflers
by Cédric Maury, Teresa Bravo, Daniel Mazzoni, Muriel Amielh and Antonio J. Reinoso
Technologies 2025, 13(8), 356; https://doi.org/10.3390/technologies13080356 - 14 Aug 2025
Viewed by 332
Abstract
Compared to rigidly-backed absorbers, the selection of appropriate optimization techniques for the optimal design of broadband acoustic mufflers remains under-investigated. This study determines the most effective optimization strategy for maximizing the total dissipation of rainbow-trapping silencers (RTSs), composed of graded side-branch cavities that [...] Read more.
Compared to rigidly-backed absorbers, the selection of appropriate optimization techniques for the optimal design of broadband acoustic mufflers remains under-investigated. This study determines the most effective optimization strategy for maximizing the total dissipation of rainbow-trapping silencers (RTSs), composed of graded side-branch cavities that enable broadband dissipation of sound through visco-thermal effects. Model-based and data-driven optimization strategies are compared, particularly in high-dimensional design spaces with flat cost function landscapes where gradient-based approaches are inadequate. It is found that model-based particle swarm optimization (PSO) outperforms simulated annealing, genetic algorithm, and surrogate method in maximizing RTS total dissipation, especially in high-dimensional designs. PSO uniquely handles flat or valleyed cost landscapes through efficient exploration–exploitation trade-offs. Data-driven approaches using Bayesian regularization neural networks (BRNNs) drastically reduce computational cost in high-dimensional spaces, though they require large datasets to avoid over-smoothing. In low dimensions, direct optimization on BRNN outputs suffices, making global search unnecessary. Both model-based and BRNN methods show robustness to input errors, but data-driven approaches handle output noise better. These findings, validated using transfer matrix models, offer strategic guidance for selecting optimization methods, especially when using computationally expensive visco-thermal finite element simulations. Full article
(This article belongs to the Section Environmental Technology)
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18 pages, 4865 KB  
Article
A Multi-Scale Cross-Layer Fusion Method for Robotic Grasping Detection
by Chengxuan Huang, Jing Xu, Xinyu Cai and Shiying Shen
Technologies 2025, 13(8), 357; https://doi.org/10.3390/technologies13080357 - 13 Aug 2025
Viewed by 368
Abstract
Measurement of grasp configurations (position, orientation, and width) in unstructured environments is critical for robotic systems. Accurate and robust prediction relies on rich multi-scale object representations; however, detail loss and fusion conflicts in multi-scale processing often cause measurement errors, particularly for complex objects. [...] Read more.
Measurement of grasp configurations (position, orientation, and width) in unstructured environments is critical for robotic systems. Accurate and robust prediction relies on rich multi-scale object representations; however, detail loss and fusion conflicts in multi-scale processing often cause measurement errors, particularly for complex objects. This study proposes a multi-scale and cross-layer fusion grasp detection network (MCFG-Net) based on a skip-connected encoder–decoder architecture. The sampling module in the encoder–decoder is optimized, and the multi-scale fusion strategy is improved, enabling pixel-level grasp rectangles to be generated in real time. A multi-scale spatial feature enhancement module (MSFEM) addresses spatial detail loss in traditional feature pyramids and preserves spatial consistency by capturing contextual information within the same scale. In addition, a cascaded fusion attention module (CFAM) is designed to assist skip connections and mitigate redundant information and semantic mismatch during feature fusion. Experimental results show that MCFG-Net achieves grasp detection accuracies of 99.62% ± 0.11% on the Cornell dataset and 94.46% ± 0.22% on the Jacquard dataset. Real-world tests on an AUBO i5 robot yield success rates of 98.5% for single-target and 95% for multi-target grasping tasks, demonstrating practical applicability in unstructured environments. Full article
(This article belongs to the Special Issue AI Robotics Technologies and Their Applications)
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28 pages, 9730 KB  
Article
Interplay of Connectivity and Unwanted Physical Interactions Within the Architecture of the D-Wave 2000Q Chimera Processor
by Jessica Park, Susan Stepney and Irene D’Amico
Technologies 2025, 13(8), 355; https://doi.org/10.3390/technologies13080355 - 12 Aug 2025
Viewed by 273
Abstract
We consider dynamics relevant to annealing in qubit networks modelled on the architecture of the D-Wave 2000Q quantum processor (known as the Chimera topology). Our results report on the effects of the qubits’ connectivity and variable coupling strengths (based on physical interactions) on [...] Read more.
We consider dynamics relevant to annealing in qubit networks modelled on the architecture of the D-Wave 2000Q quantum processor (known as the Chimera topology). Our results report on the effects of the qubits’ connectivity and variable coupling strengths (based on physical interactions) on the dynamics of network. The networks we examine are up to 32 qubits in size and include coupling lengths varying by almost an order of magnitude. We show that while information transfer within the network can be strongly affected by the different interactions, the system maintains similar clusters of qubits with comparable fidelities even in the presence of some of the physical interactions. This suggests an intrinsic robustness of the Chimera topology to these perturbations, even if it includes such a variety of coupling lengths. Moreover, a similar clustering geometry was observed for other qubit properties in previous analysis of actual data from D-Wave 2000Q. This comparable behaviour suggests that the real quantum annealing chip is subject to little or no unwanted effects due to interactions that scale with the coupling lengths. This could be due to absence of the most damaging type of physical interactions and/or to D-Wave calibration methods tuning the control lines such that the couplings perform as if there is no effect due to their physical length. Our results are also relevant to the use of chaining for the creation of logical qubits. They show that even with very strong interactions between the chain, significant unwanted perturbations may occur due to the inhomogeneous fidelities of the overall dynamics and inhomogeneous dynamics should be expected for any given algorithm. Full article
(This article belongs to the Section Quantum Technologies)
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19 pages, 5302 KB  
Article
Localized Ultrasonic Cleaning for Injection Mold Cavities: A Scalable In Situ Process with Surface Quality Monitoring
by Deviprasad Chalicheemalapalli Jayasankar, Thomas Tröster and Thorsten Marten
Technologies 2025, 13(8), 354; https://doi.org/10.3390/technologies13080354 - 11 Aug 2025
Viewed by 381
Abstract
As global industries seek to reduce energy consumption and lower CO2 emissions, the need for sustainable, efficient maintenance processes in manufacturing has become increasingly important. Traditional mold cleaning methods often require complete tool disassembly, extended downtime, and heavy use of solvents, resulting [...] Read more.
As global industries seek to reduce energy consumption and lower CO2 emissions, the need for sustainable, efficient maintenance processes in manufacturing has become increasingly important. Traditional mold cleaning methods often require complete tool disassembly, extended downtime, and heavy use of solvents, resulting in high energy costs and environmental impact. This study presents a novel localized ultrasonic cleaning process for injection molding tools that enables targeted, in situ cleaning of mold cavities without removing the tool from the press. A precisely positioned ultrasonic transducer delivers cleaning energy directly to contaminated areas, eliminating the need for complete mold removal. Multiple cleaning agents, including alkaline and organic acid solutions, were evaluated for their effectiveness in combination with ultrasonic excitation. Surface roughness measurements were used to assess cleaning performance over repeated contamination and cleaning cycles. Although initial tests were performed manually in the lab, results indicate that the method can be scaled up and automated effectively. This process offers a promising path toward energy-efficient, low-emission tool maintenance across a wide range of injection molding applications. Full article
(This article belongs to the Section Manufacturing Technology)
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20 pages, 14906 KB  
Article
Dual-Channel ADCMix–BiLSTM Model with Attention Mechanisms for Multi-Dimensional Sentiment Analysis of Danmu
by Wenhao Ping, Zhihui Bai and Yubo Tao
Technologies 2025, 13(8), 353; https://doi.org/10.3390/technologies13080353 - 10 Aug 2025
Viewed by 645
Abstract
Sentiment analysis methods for interactive services such as Danmu in online videos are challenged by their colloquial style and diverse sentiment expressions. For instance, the existing methods cannot easily distinguish between similar sentiments. To address these limitations, this paper proposes a dual-channel model [...] Read more.
Sentiment analysis methods for interactive services such as Danmu in online videos are challenged by their colloquial style and diverse sentiment expressions. For instance, the existing methods cannot easily distinguish between similar sentiments. To address these limitations, this paper proposes a dual-channel model integrated with attention mechanisms for multi-dimensional sentiment analysis of Danmu. First, we replace word embeddings with character embeddings to better capture the colloquial nature of Danmu text. Second, the dual-channel multi-dimensional sentiment encoder extracts both the high-level semantic and raw contextual information. Channel I of the encoder learns the sentiment features from different perspectives through a mixed model that combines the benefits of self-Attention and Dilated CNN (ADCMix) and performs contextual modeling through bidirectional long short-term memory (BiLSTM) with attention mechanisms. Channel II mitigates potential biases and omissions in the sentiment features. The model combines the two channels to erase the fuzzy boundaries between similar sentiments. Third, a multi-dimensional sentiment decoder is designed to handle the diversity in sentiment expressions. The superior performance of the proposed model is experimentally demonstrated on two datasets. Our model outperformed the state-of-the-art methods on both datasets, with improvements of at least 2.05% in accuracy and 3.28% in F1-score. Full article
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38 pages, 6389 KB  
Review
Mobility and Handover Management in 5G/6G Networks: Challenges, Innovations, and Sustainable Solutions
by Bilal Saoud, Ibraheem Shayea, Mohammad Ahmed Alnakhli and Hafizal Mohamad
Technologies 2025, 13(8), 352; https://doi.org/10.3390/technologies13080352 - 8 Aug 2025
Viewed by 1337
Abstract
Compared to 4G long-term evolution (LTE) networks, 5G and 6G networks provide fast data transmission with little delay, larger base station capacity, enhanced quality of service (QoS), and extensive multiple-input-multiple-output (MIMO) channels. Nevertheless, the attainment of mobility and handover (HO) in 5/6G networks [...] Read more.
Compared to 4G long-term evolution (LTE) networks, 5G and 6G networks provide fast data transmission with little delay, larger base station capacity, enhanced quality of service (QoS), and extensive multiple-input-multiple-output (MIMO) channels. Nevertheless, the attainment of mobility and handover (HO) in 5/6G networks has been hindered by substantial changes in intelligent devices and the high-definition applications of multimedia. Therefore, the existing cellular network is compared with difficulties in transmitting large amounts of data at a faster rate, ensuring high QoS, minimizing latency, and efficiently managing HOs and mobility. This paper primarily addresses the difficulties related to HO and mobility management in 5G/6G networks. The findings of this paper emphasize the importance of aligning mobility and HO strategies with sustainable development goals to reduce energy consumption and improve resource allocation. It focuses on integrating innovative technologies such as artificial intelligence and machine learning to enhance the sustainability and efficiency of mobility and HO management. The paper provides a comprehensive analysis of the current body of the literature and explores essential metrics for measuring performance (known as KPIs) and potential solutions for difficulties linked to HO and mobility. The analysis takes into account established standards in the field. Furthermore, it assesses the effectiveness of existing models in dealing with HO and mobility management problems, considering criteria such as energy efficiency, dependability, latency, and scalability. This survey concludes by highlighting key challenges associated with HO and mobility management in existing research models. It also offers comprehensive assessments of the proposed solutions, accompanied by suggestions for future research. Full article
(This article belongs to the Section Information and Communication Technologies)
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20 pages, 3290 KB  
Article
Sodium Alginate-Pomegranate Peel Hydrogels for the Remediation of Heavy Metals from Water
by Punita Lalchand, Nirusha Thavarajah and Xavier Fernando
Technologies 2025, 13(8), 351; https://doi.org/10.3390/technologies13080351 - 8 Aug 2025
Viewed by 801
Abstract
The use of agrochemicals in agriculture is widespread globally, as it enables increased crop yields. However, they also contain heavy metals such as copper and nickel, which can leach into the drinking water and harm the environment and human health. As such, it [...] Read more.
The use of agrochemicals in agriculture is widespread globally, as it enables increased crop yields. However, they also contain heavy metals such as copper and nickel, which can leach into the drinking water and harm the environment and human health. As such, it is imperative that they are removed from drinking water. One way to achieve this is through adsorption using biosorbents. This proof-of-concept study aimed to synthesize and characterize environmentally friendly hydrogels from sodium alginate (SA) and pomegranate peel powder (PPP). The gels were characterized using Fourier-Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and water uptake tests. The FTIR analysis confirmed the presence of the expected functional groups, SEM revealed that incorporating PPP enhanced the roughness and porosity of the gels, and gels with PPP incorporation were able to absorb 1.58 times more water than SA-only gels. Moreover, their ability to remediate copper and nickel from contaminated water was tested. Here, the effects of contact time, pH, and adsorbent amount were tested for copper, demonstrating that the optimal contact time was 60 min, the optimal pH was ~5, and 0.01 g of adsorbent was needed for optimal adsorption. The effect of contact time was tested for nickel, and it was found that the optimal contact time was 5 min. Overall, these gels show promising results for the remediation of copper and nickel from contaminated water. Full article
(This article belongs to the Special Issue Technological Advances in Science, Medicine, and Engineering 2024)
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15 pages, 562 KB  
Article
Predicting Disease Activity Score in Rheumatoid Arthritis Patients Treated with Biologic Disease-Modifying Antirheumatic Drugs Using Machine Learning Models
by Fatemeh Salehi, Sara Zarifi, Sara Bayat, Mahdis Habibpour, Amirreza Asemanrafat, Arnd Kleyer, Georg Schett, Ruth Fritsch-Stork and Bjoern M. Eskofier
Technologies 2025, 13(8), 350; https://doi.org/10.3390/technologies13080350 - 8 Aug 2025
Viewed by 477
Abstract
Rheumatoid arthritis (RA) is a chronic autoimmune disease marked by joint inflammation and progressive disability. While biological disease-modifying antirheumatic drugs (bDMARDs) have significantly improved disease control, predicting individual treatment response remains clinically challenging. This study presents a machine learning approach to predict 12-month [...] Read more.
Rheumatoid arthritis (RA) is a chronic autoimmune disease marked by joint inflammation and progressive disability. While biological disease-modifying antirheumatic drugs (bDMARDs) have significantly improved disease control, predicting individual treatment response remains clinically challenging. This study presents a machine learning approach to predict 12-month disease activity, measured by DAS28-CRP, in RA patients beginning bDMARD therapy. We trained and evaluated eight regression models, including Ridge, Lasso, Support Vector Regression, and XGBoost, using baseline clinical features from 154 RA patients treated at University Hospital Erlangen. A rigorous nested cross-validation strategy was applied for internal model selection and validation. Importantly, model generalizability was assessed using an independent external dataset from the Austrian BioReg registry, which includes a more diverse, real-world RA patient population from across multiple clinical sites. The Ridge regression model achieved the best internal performance (MAE: 0.633, R2: 0.542) and showed strong external validity when applied to unseen BioReg data (MAE: 0.678, R2: 0.491). These results indicate robust cross-cohort generalization. By predicting continuous DAS28-CRP scores instead of binary remission labels, our approach supports flexible, individualized treatment planning based on local or evolving clinical thresholds. This work demonstrates the feasibility and clinical value of externally validated, data-driven tools for precision treatment planning in RA. Full article
(This article belongs to the Special Issue Applications of Artificial Intelligence in Healthcare and Information Processing)
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20 pages, 1737 KB  
Review
A Systematic Review on Assistive Technology Terminologies, Concepts, and Definitions
by Jordam Wilson Lourenço, Paulo Alexandre Correia de Jesus, Franciele Lourenço, Osiris Canciglieri Junior and Jones Luís Schaefer
Technologies 2025, 13(8), 349; https://doi.org/10.3390/technologies13080349 - 7 Aug 2025
Viewed by 665
Abstract
This study examines the diversity of terminologies associated with assistive technology (AT), a crucial field that promotes autonomy and inclusion for people with disabilities. Although the wide use of assistive technology is observed in the literature, a variety of terms are often used [...] Read more.
This study examines the diversity of terminologies associated with assistive technology (AT), a crucial field that promotes autonomy and inclusion for people with disabilities. Although the wide use of assistive technology is observed in the literature, a variety of terms are often used interchangeably, which hinders research, technological development, and the formulation of public policies. In this sense, this systematic review aimed to identify, categorise, and analyse the diversity of terms used to describe AT in the scientific literature, contributing to greater conceptual clarity and supporting structured and interdisciplinary development in the field. A comprehensive search was conducted in July 2024 across the Scopus, Web of Science, and PubMed databases, covering publications from 1989 to 2024. Eligible studies were peer-reviewed journal articles in English that conceptually defined at least one AT-related term. The selection process followed the PRISMA 2020 guidelines and included studies from Q1 and Q2 journals to ensure academic rigour. A total of 117 studies were included out of 11,941 initial records. Sixteen distinct terms were identified and grouped into five clusters based on semantic and functional similarities: Cluster 1—Technologies for assistance and inclusion. Cluster 2—Functional assistive devices. Cluster 3—Assistive interaction interfaces. Cluster 4—Assistive environmental technologies. Cluster 5—Assistive systems. A complementary meta-analysis revealed geographic and temporal trends, indicating that terms such as “assistive technology” and “assistive device” are globally dominant. In contrast, others, like “enabling technology,” are more context-specific and emerging. The findings contribute theoretically by providing a structured framework for understanding AT terminology and practically by supporting the design of public policy and interdisciplinary communication. Full article
(This article belongs to the Special Issue Innovations in Design, Development and Evaluation of Assistive Technologies)
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33 pages, 3472 KB  
Article
Real-Time Detection and Response to Wormhole and Sinkhole Attacks in Wireless Sensor Networks
by Tamara Zhukabayeva, Lazzat Zholshiyeva, Yerik Mardenov, Atdhe Buja, Shafiullah Khan and Noha Alnazzawi
Technologies 2025, 13(8), 348; https://doi.org/10.3390/technologies13080348 - 7 Aug 2025
Viewed by 349
Abstract
Wireless sensor networks have become a vital technology that is extensively applied across multiple industries, including agriculture, industrial operations, and smart cities, as well as residential smart homes and environmental monitoring systems. Security threats emerge in these systems through hidden routing-level attacks such [...] Read more.
Wireless sensor networks have become a vital technology that is extensively applied across multiple industries, including agriculture, industrial operations, and smart cities, as well as residential smart homes and environmental monitoring systems. Security threats emerge in these systems through hidden routing-level attacks such as Wormhole and Sinkhole attacks. The aim of this research was to develop a methodology for detecting security incidents in WSNs by conducting real-time analysis of Wormhole and Sinkhole attacks. Furthermore, the paper proposes a novel detection methodology combined with architectural enhancements to improve network robustness, measured by hop counts, delays, false data ratios, and route integrity. A real-time WSN infrastructure was developed using ZigBee and Global System for Mobile Communications/General Packet Radio Service (GSM/GPRS) technologies. To realistically simulate Wormhole and Sinkhole attack scenarios and conduct evaluations, we developed a modular cyber–physical architecture that supports real-time monitoring, repeatability, and integration of ZigBee- and GSM/GPRS-based attacker nodes. During the experimentation, Wormhole attacks caused the hop count to decrease from 4 to 3, while the average delay increased by 40%, and false sensor readings were introduced in over 30% of cases. Additionally, Sinkhole attacks led to a 27% increase in traffic concentration at the malicious node, disrupting load balancing and route integrity. The proposed multi-stage methodology includes data collection, preprocessing, anomaly detection using the 3-sigma rule, and risk-based decision making. Simulation results demonstrated that the methodology successfully detected route shortening, packet loss, and data manipulation in real time. Thus, the integration of anomaly-based detection with ZigBee and GSM/GPRS enables a timely response to security threats in critical WSN deployments. Full article
(This article belongs to the Special Issue New Technologies for Sensors)
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18 pages, 5296 KB  
Article
Grid-Search-Optimized, Gated Recurrent Unit-Based Prediction Model for Ionospheric Total Electron Content
by Shuo Zhou, Ziyi Yang, Qiao Yu and Jian Wang
Technologies 2025, 13(8), 347; https://doi.org/10.3390/technologies13080347 - 7 Aug 2025
Viewed by 328
Abstract
Accurately predicting the ionosphere’s Total Electron Content (TEC) is significant for ensuring the regular operation of satellite navigation and communication systems and space weather prediction. To further improve the accuracy of TEC prediction, this paper proposes a TEC prediction model based on the [...] Read more.
Accurately predicting the ionosphere’s Total Electron Content (TEC) is significant for ensuring the regular operation of satellite navigation and communication systems and space weather prediction. To further improve the accuracy of TEC prediction, this paper proposes a TEC prediction model based on the grid-optimized Gate Recurrent Unit (GRU). This model has the following main features: (1) it uses statistical learning methods to interpolate the missing data of TEC observations; (2) it constructs a sliding time window by using the multi-dimensional time series features of two types of solar activity indices to support modeling; (3) It adopts grid search combined with optimization of network depth, time step length, and other hyperparameters to significantly enhance the model’s ability to extract the characteristics of the ionospheric 11-year cycle and seasonal variations. Taking the EGLIN station as an example, the proposed model is verified. The experimental results show that the root mean square error of the GRU model during the period from 2019 to 2020 was 0.78 TECU, which was significantly lower than those of the CCIR, URSI, and statistical machine learning models. Compared with the other three models, the RMSE error of the GRU model was reduced by 72.73%, 72.64%, and 57.38%, respectively. The above research verifies the advantages of the proposed model in predicting TEC and provides a new idea for ionospheric modeling. Full article
(This article belongs to the Section Environmental Technology)
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