Advancing Open Science
Supporting academic communities
since 1996
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 

Recent Articles  

11 pages, 1557 KB  
Article
Aggregation Periods Influence Step Count Error in Low-Power Wearables
by Sydney Lundell and Kenton R. Kaufman
Sensors 2025, 25(22), 6998; https://doi.org/10.3390/s25226998 (registering DOI) - 16 Nov 2025
Abstract
Wearable sensors are increasingly used to monitor physical activity, yet low-power devices often rely on data aggregation to conserve battery life, potentially impacting measurement accuracy. This study evaluates the performance of a new low-power wearable (LPW), designed for monitoring steps across multiple months [...] Read more.
Wearable sensors are increasingly used to monitor physical activity, yet low-power devices often rely on data aggregation to conserve battery life, potentially impacting measurement accuracy. This study evaluates the performance of a new low-power wearable (LPW), designed for monitoring steps across multiple months in a free-living environment, compared to a research-grade sensor (RGS) that collects raw acceleration data, with a focus on how different aggregation intervals impact step count accuracy. Thirty-two participants wore both sensors over two days, with LPW data collected in 10 min, 1 min, or 10 s aggregation periods (APs). Sensitivity and specificity of wear time detection were high across all APs (0.96 and 0.98, respectively). While total daily step count error did not differ significantly between APs, the 10 min AP exhibited greater undercounting and wider limits of agreement, especially in APs containing more than 40 steps. These findings suggest that although AP does not affect total daily step count, it influences the accuracy and variability of more granular data windows. Aggregating step counts over longer intervals may obscure short, fragmented bouts common in daily activity, leading to underestimation of steps. Optimizing APs and sensor settings is critical for improving accuracy in low-power wearables used outside laboratory settings. Full article
(This article belongs to the Special Issue Ambient, Wearable Sensor, Gateway Support for Telemonitoring, Telehealth and Telemedicine Systems)
►▼ Show Figures

Figure 1

15 pages, 493 KB  
Article
Digital Gamification and Visual Modeling for Learning Regulation in Biomedical Education
by Lorena Latre-Navarro and Alejandro Quintas-Hijós
Educ. Sci. 2025, 15(11), 1542; https://doi.org/10.3390/educsci15111542 (registering DOI) - 16 Nov 2025
Abstract
Learning regulation is a central determinant of student achievement and autonomy in higher education. Grounded in Self-Determination Theory, this quasi-experimental study examined the effects of a seven-week intervention in biomedical education that combined visual modeling through drawing with gamification elements supported by digital [...] Read more.
Learning regulation is a central determinant of student achievement and autonomy in higher education. Grounded in Self-Determination Theory, this quasi-experimental study examined the effects of a seven-week intervention in biomedical education that combined visual modeling through drawing with gamification elements supported by digital tools (ClassDojo, 3D atlases, augmented reality). Participants were 116 first-year anatomy students from two universities, one receiving the experimental treatment (visual modeling with gamification) and the other serving as a control group (traditional instruction). Pre- and post-intervention measures were collected using the Self-Regulation of Learning Questionnaire to assess changes in autonomous regulation (AR), controlled regulation (CR), and the Relative Autonomy Index (RAI). Results showed no significant effects on AR, while CR was significantly higher in the experimental group. A treatment effect was also found for the RAI, although no evidence of motivational internalization toward more autonomous regulation emerged within the short intervention. This study highlights how gamified digital platforms can serve as tools for media literacy in higher education, fostering critical engagement with technology as a component of lifelong learning. Findings suggest that combining gamification with visual modeling reinforces controlled regulation, while longer and more autonomy-supportive interventions may be required to foster sustainable autonomous regulation. Full article
(This article belongs to the Special Issue Media Literacy in Lifelong Learning)
►▼ Show Figures

Figure 1

23 pages, 1396 KB  
Article
An Inverse Kinematics Solution for Mobile Manipulators in Textile Workshops Based on an Improved Particle Swarm Optimization
by Wei Xie, Zhongxu Wang, Jiachen Ma, Jun Chen and Xingjian Xie
Symmetry 2025, 17(11), 1980; https://doi.org/10.3390/sym17111980 (registering DOI) - 16 Nov 2025
Abstract
To enhance the operational performance of mobile manipulators in textile workshops and address the difficulty of inverse kinematics (IK) for this class of redundant manipulators, this paper leverages the robot’s structural symmetries and proposes a chaotic-mutation particle swarm optimization (CMPSO)-based IK algorithm for [...] Read more.
To enhance the operational performance of mobile manipulators in textile workshops and address the difficulty of inverse kinematics (IK) for this class of redundant manipulators, this paper leverages the robot’s structural symmetries and proposes a chaotic-mutation particle swarm optimization (CMPSO)-based IK algorithm for mobile manipulators, thus simplifying the solution process and ensuring balanced exploration of the search space. First, the coordinate–transformation relationships of the mobile manipulator are analyzed to establish its forward kinematic model. Then, a multi-objective constrained IK model is formulated according to the manipulator’s operating characteristics. The model incorporates a pose-error function, the ‘compliance’ principle, and joint-limit avoidance. To solve this model accurately, we refine the population initialization and boundary-violation handling of the particle swarm algorithm and introduce an asymmetric mechanism via an adaptive mutation strategy, culminating in a CMPSO-based IK solver. On this basis, single-pose IK tests and trajectory-planning experiments are conducted, and simulation results verify the effectiveness and stability of the proposed algorithm. Full article
(This article belongs to the Special Issue Symmetry-Inspired Approaches in Control, Robotics, and Intelligent Systems)
21 pages, 1735 KB  
Article
Enhancing Traceability and Reliability in Cold Chain Logistics Through Hyperledger Fabric and IoT
by Elvan Duman and Ebru Aydoğan
Appl. Sci. 2025, 15(22), 12149; https://doi.org/10.3390/app152212149 (registering DOI) - 16 Nov 2025
Abstract
Cold chain logistics is a critical process for ensuring product safety and quality assurance; however, existing systems face significant challenges due to centralized data structures, limited transparency, and low reliability. The objective of this study is to develop a blockchain infrastructure based on [...] Read more.
Cold chain logistics is a critical process for ensuring product safety and quality assurance; however, existing systems face significant challenges due to centralized data structures, limited transparency, and low reliability. The objective of this study is to develop a blockchain infrastructure based on Hyperledger Fabric, integrated with IoT technologies, to address these issues. In the proposed system, secure collaboration among producers, carrier, and retailer organizations is achieved through role-based access control and authorization mechanisms, while environmental data collected from IoT sensors are immutably recorded on the blockchain. Performance tests conducted with Hyperledger Caliper demonstrated that the system maintained stable operation even under high transaction loads. In particular, query transactions achieved the most efficient results, reaching 442 transactions per second at a send rate of 500 TPS and 818 transactions per second at a send rate of 1000 TPS, with corresponding average latencies of 0.21 and 0.26 s, respectively. The absence of failed transactions further reinforced the reliability of the system. In addition, scalability experiments were conducted to assess how the system performs as the network expands with additional peer nodes across organizations. The results confirmed that the proposed architecture maintains improved latency and throughput under both intra-organizational and network-wide scaling scenarios. The results demonstrate that the proposed system provides a reliable, transparent, and scalable infrastructure even under low hardware configurations, contributing to the rapid and trustworthy verification of product history and environmental conditions in cold chain applications. Full article
(This article belongs to the Special Issue Advances in Blockchain and Smart Contracts with Diverse Domains Applications: Second Edition)
►▼ Show Figures

Figure 1

33 pages, 10533 KB  
Article
Autonomous Suspended-Payload UAV with Self-Sensing and Anti-Swing for Outdoor Transportation
by Haoyang Lin, Zhengdong Song, Chao Liu, Shan Qi, Hongbo Zhang and Shengyi Yang
Aerospace 2025, 12(11), 1016; https://doi.org/10.3390/aerospace12111016 (registering DOI) - 16 Nov 2025
Abstract
Suspended-payload UAVs face a core dilemma in outdoor transportation: their stability is severely compromised by payload swing, yet conventional anti-swing controllers depend on real-time state feedback that is difficult to obtain without external sensors. To resolve this, we propose a fully integrated self-sensing [...] Read more.
Suspended-payload UAVs face a core dilemma in outdoor transportation: their stability is severely compromised by payload swing, yet conventional anti-swing controllers depend on real-time state feedback that is difficult to obtain without external sensors. To resolve this, we propose a fully integrated self-sensing anti-swing control strategy. Its key contribution lies in the seamless co-design of an external-sensor-free autonomous state estimation scheme and a coupled compensation control architecture: it eliminates the dependency on external sensors through an onboard estimation solution, actively suppresses swing via a coupled compensation framework, and rigorously guarantees stability through Lyapunov analysis. Specifically, an inertial measurement unit (IMU) at the suspension point fuses data with a Kalman filter for real-time payload state estimation. A sliding mode anti-swing controller is then integrated into the position control loop through dynamic coupling compensation. Strict Lyapunov-based analysis proves the bounded-error stability of this coupled system. High-fidelity simulations in CoppeliaSim under various scenarios validate the strategy’s engineering feasibility and synergistic performance. Results demonstrate that our method achieves high-precision state estimation and effective swing suppression, offering a practical and reliable solution for outdoor UAV transportation. Full article
(This article belongs to the Section Aeronautics)
32 pages, 10020 KB  
Review
Phase Engineering of Nanomaterials: Tailoring Crystal Phases for High-Performance Batteries and Supercapacitors
by Ramanadha Mangiri, Nandarapu Purushotham Reddy and Joonho Bae
Micromachines 2025, 16(11), 1289; https://doi.org/10.3390/mi16111289 (registering DOI) - 16 Nov 2025
Abstract
Phase engineering has emerged as a powerful method for manipulating the structural and electrical characteristics of nanomaterials, resulting in significant enhancements in their electrochemical performance. This paper examines the correlation among morphology, crystal phase, and electrochemical performance of nanomaterials engineered for high-performance batteries [...] Read more.
Phase engineering has emerged as a powerful method for manipulating the structural and electrical characteristics of nanomaterials, resulting in significant enhancements in their electrochemical performance. This paper examines the correlation among morphology, crystal phase, and electrochemical performance of nanomaterials engineered for high-performance batteries and supercapacitors. The discourse starts with phase engineering methodologies in metal-based nanomaterials, including the direct synthesis of atypical phases and phase transformation mechanisms that provide metastable or mixed-phase structures. Special emphasis is placed on the impact of these synthetic processes on morphology and surface properties, which subsequently regulate charge transport and ion diffusion during electrochemical reactions. Additionally, the investigation of phase engineering in transition metal dichalcogenide (TMD) nanomaterials highlights how regulated phase transitions and heterophase structures improve active sites and conductivity. The optimized phase-engineered ZnCo2O4@Ti3C2 composite exhibited a high specific capacitance of 1013.5 F g−1, a reversible capacity of 732.5 mAh g−1, and excellent cycling stability, with over 85% retention after 10,000 cycles. These results confirm that phase and morphological control can substantially enhance charge transport and electrochemical durability, offering promising strategies for next-generation batteries and supercapacitors. The paper concludes by summarizing current advancements in phase-engineered nanomaterials for lithium-ion, sodium-ion, and lithium-sulfur batteries, along with supercapacitors, emphasizing the significant relationship between phase state, morphology, and energy storage efficacy. This study offers a comprehensive understanding of the optimal integration of phase and morphological control in designing enhanced electrode materials for next-generation electrochemical energy storage systems. Full article
(This article belongs to the Special Issue Low-Dimensional Nano-Scaled Materials: From Principles to Device Application)
►▼ Show Figures

Figure 1

16 pages, 490 KB  
Article
Quality of Life, Physical Activity, and Mental and Physical Health Status in Croatian Middle-Aged and Elderly Population
by Manuela Maltarić, Mirela Kolak, Darija Vranešić Bender, Jasenka Gajdoš Kljusurić and Branko Kolarić
Healthcare 2025, 13(22), 2931; https://doi.org/10.3390/healthcare13222931 (registering DOI) - 16 Nov 2025
Abstract
Background/Objectives: The proportion of middle-aged and elderly people in the total population is increasing, and it is of utmost importance to monitor their quality of life (QoL), which largely depends on mobility, health and mental state, diet, nutritional status (especially overweight and [...] Read more.
Background/Objectives: The proportion of middle-aged and elderly people in the total population is increasing, and it is of utmost importance to monitor their quality of life (QoL), which largely depends on mobility, health and mental state, diet, nutritional status (especially overweight and obesity). The population in Croatia is among the leading in terms of the proportion of overweight and obese people, therefore the aim is to study QoL and determine which aspects can potentially be mitigated by public health actions. Methods: In accordance with the available data from the SHARE study (Survey on Health, Aging and Retirement in Europe), data were taken from the most recently published—9th wave conducted in 2021/2022. In this study, the Croatian population older than 50 years is represented by 4687 respondents. Health-related parameters were monitored (cardiovascular diseases, diabetes, mental health, handgrip strength (HGS) as a biomarker in older people and body mass index) and quality of life (self-assessed quality of life (CASP, self-assessed health SPH, physical activity) and dietary habits. A logistic regression model was used to link HGS as a biomarker in older people with quality of life and health parameters. Results: There is an undeniable decline in social and physical activity with age; the proportion of people engaged in vigorous physical activity decreased from 47% in the 51–64 age group to only 5.4% in people over 85 years of age, while physical inactivity increased from 3% to 37.7%. Chronic diseases, especially hypertension, accumulate with age, while self-rated health worsens with age, as does mental health (the proportion of depressed people (according to the EURO-D scale) increased significantly from 21.1% in the 51–64 age group to 54.1% in those over 85 years of age). Results of multinomial logistic regression showed that sports (in)activity was consistently associated with a lower likelihood of reduced handgrip strength (OR = 1.94 for low strength, p < 0.001). Conclusions: Sports activities and social engagement are crucial for maintaining good handgrip strength. Higher BMI, lower education and adverse psychological states are risk factors for a weaker handgrip. These findings highlight the need for an integrated public health approach that promotes physical activity, balanced nutrition and mental and social well-being in the older population. Full article
(This article belongs to the Special Issue The Relationship Between Diet Quality, Physical Activity, and Mental and Physical Health Status)
►▼ Show Figures

Figure 1

19 pages, 4254 KB  
Article
Multi-Parameter Synergistic Effects on Fine Coal Slurry Sedimentation in High-Gravity Fields: A CFD Study
by Lingyun Liu, Huikuan Pan, Wei Ge and Chuilei Kong
Separations 2025, 12(11), 320; https://doi.org/10.3390/separations12110320 (registering DOI) - 16 Nov 2025
Abstract
This study addresses the technical challenges of conventional coal slurry sedimentation equipment in handling fine coal particles, such as poor settling performance and strong dependence on chemical reagents, by designing a novel high-gravity sedimentation and dewatering device. Solid–liquid centrifugal separation was simulated on [...] Read more.
This study addresses the technical challenges of conventional coal slurry sedimentation equipment in handling fine coal particles, such as poor settling performance and strong dependence on chemical reagents, by designing a novel high-gravity sedimentation and dewatering device. Solid–liquid centrifugal separation was simulated on the CFD-Fluent platform using the Eulerian–Eulerian method, with the solid volume fraction and effective deposition thickness adopted as key indicators of particle settling performance. The settling behavior and flow field characteristics of particles with different sizes (0.045–0.5 mm) were elucidated under varying centrifugal radii (400–800 mm) and rotational speeds (400–1200 r·min−1), thereby providing a solid theoretical foundation for the parameter optimization of centrifugal settling processes for fine particles. The results indicate that increasing the centrifugal radius and rotational speed strengthens the centrifugal field effect, markedly enhancing the dynamic pressure gradient and interphase slip velocity. Under high-speed (ω = 1200 r·min−1) and large-radius (R = 800 mm) conditions, the dynamic pressure of fine particles (0.045 mm) reached 7.52 MPa with a radial velocity of 0.79 m·s−1, effectively compensating for the settling disadvantage of fine particles, promoting solid–liquid separation, and ensuring the stable deposition of coal particles. Meanwhile, as particle size increases, a distinct deposition thickness can be formed under different operating conditions, demonstrating that particle size is the dominant factor governing deposition behavior. The study elucidates the intrinsic mechanism of how multiple parameters—rotational speed, centrifugal radius, and coal particle size—synergistically influence particle deposition characteristics. By regulating these parameters to accommodate different particle sizes, the findings provide valuable insights for the parameter optimization of centrifugal settling processes for fine particles. Full article
(This article belongs to the Special Issue Solid Waste Recycling and Strategic Metal Extraction)
12 pages, 3867 KB  
Communication
Heterofunctional Cationic Polyester Dendrimers as Potent Nonviral Vectors for siRNA Delivery
by Arunika Singh, Ángel Buendía, Irene Rodríguez-Clemente, Natalia Sanz del Olmo, Valentín Ceña and Michael Malkoch
Pharmaceutics 2025, 17(11), 1476; https://doi.org/10.3390/pharmaceutics17111476 (registering DOI) - 16 Nov 2025
Abstract
Background/Objectives: Heterofunctional cationic polyester dendrimers derived from a 2-(bromomethyl)-2-(hydroxymethyl)propane-1,3-diol (BHP-diol) based AB2C monomer were evaluated as efficient and biodegradable nonviral carriers for siRNA delivery. Methods: These dendrimers feature dual internal and external charge architectures, enabling precise control of charge [...] Read more.
Background/Objectives: Heterofunctional cationic polyester dendrimers derived from a 2-(bromomethyl)-2-(hydroxymethyl)propane-1,3-diol (BHP-diol) based AB2C monomer were evaluated as efficient and biodegradable nonviral carriers for siRNA delivery. Methods: These dendrimers feature dual internal and external charge architectures, enabling precise control of charge distribution and siRNA interaction strength. Results: They achieved complete siRNA complexation at nitrogen-to-phosphate (N/P) ratios of 0.50–2.14 and provided up to 93% RNase protection, outperforming amino-functional scaffolds based on 2,2-bis(methylol)propionic acid (bis-MPA). In human (T98G) and murine (GL261) glioblastoma cells, the dendrimers exhibited minimal cytotoxicity while achieving 52–61% target protein knockdown, a two- to three-fold improvement over conventional polyester dendrimers, and approaching the silencing efficiency of the commercial Interferin® reagent. Conclusions: The combination of high complexation efficiency, strong nuclease resistance, and excellent biocompatibility establishes these heterofunctional dendrimers as a new generation of precisely tunable, biodegradable vectors for therapeutic siRNA delivery. Full article
(This article belongs to the Special Issue Dendrimers in Nanomedicine: Recent Advances)
►▼ Show Figures

Figure 1

21 pages, 760 KB  
Review
China’s South-to-North Water Diversion Project: A Review and Reach Beyond China’s Borders
by Yi Jia, Linus Zhang, Jianzhi Niu and Ronny Berndtsson
Water 2025, 17(22), 3275; https://doi.org/10.3390/w17223275 (registering DOI) - 16 Nov 2025
Abstract
The South-to-North Water Diversion Project (SNWDP), the world’s largest water transfer initiative, is designed to address northern China’s acute water scarcity by diverting approximately 45 km3 of water annually from the south through three major routes, with completion targeted for 2050. This [...] Read more.
The South-to-North Water Diversion Project (SNWDP), the world’s largest water transfer initiative, is designed to address northern China’s acute water scarcity by diverting approximately 45 km3 of water annually from the south through three major routes, with completion targeted for 2050. This review demonstrates that the SNWDP has already improved water security for over 150 million people, stabilized groundwater, and supported agricultural and urban development, but also presents significant challenges, including escalating costs, large-scale resettlement, and substantial environmental concerns such as ecosystem alteration, salinity intrusion, pollutant transfer, and risks to biodiversity and water quality. While mitigation and adaptive management efforts are ongoing, their long-term effectiveness remains uncertain. Notably, the SNWDP’s influence extends beyond China: by enhancing food production self-sufficiency, it can help stabilize global food markets during concurrent droughts and serves as a model—albeit a debated one—for large-scale water management and governance. The project’s hydropolitical and geopolitical dimensions, especially regarding the planned western route and potential transboundary impacts, underscore the need for international dialog and monitoring. Overall, the SNWDP exemplifies both the opportunities and dilemmas of 21st-century megaprojects, with its legacy dependent on balancing economic, environmental, and social trade-offs and on transparent, participatory governance to ensure sustainable outcomes for China and the global community. Full article
(This article belongs to the Special Issue China Water Forum, 4th Edition)
►▼ Show Figures

Figure 1

11 pages, 3368 KB  
Article
Charge-Domain Type 2.2 µm BSI Global Shutter Pixel with Dual-Depth DTI Produced by Thick-Film Epitaxial Process
by Toshifumi Yokoyama, Masafumi Tsutsui, Yoshiaki Nishi, Yoshihiro Noguchi, Masahiko Takeuchi, Masahiro Oda and Fenigstein Amos
Sensors 2025, 25(22), 6997; https://doi.org/10.3390/s25226997 (registering DOI) - 16 Nov 2025
Abstract
We developed a 2.2 µm backside-illuminated (BSI) global shutter (GS) pixel featuring true charge-domain-correlated double sampling (CDS). To enhance the inverse parasitic light sensitivity (1/PLS), we implemented a thick-film epitaxial process incorporating a dual-depth deep trench isolation (DTI) structure. The thickness of the [...] Read more.
We developed a 2.2 µm backside-illuminated (BSI) global shutter (GS) pixel featuring true charge-domain-correlated double sampling (CDS). To enhance the inverse parasitic light sensitivity (1/PLS), we implemented a thick-film epitaxial process incorporating a dual-depth deep trench isolation (DTI) structure. The thickness of the epitaxial substrate was 8.5 µm. This structure was designed using optical simulation. By using a thick epitaxial substrate, it is possible to reduce the amount of light that reaches the memory node. The dual-depth DTI design, with a shallower trench on the readout side, enables efficient signal transfer from the photodiode (PD) to the memory node. To achieve this structure, we developed a process for thick epitaxial substrate, and the dual-depth DTI can be fabricated with a single mask. This pixel represents the smallest charge-domain GS pixel developed to date. Despite its compact size, it achieves a high quantum efficiency (QE) of 83% (monochrome sample: wavelength = 560 nm) and a 1/PLS exceeding 10,000 (white halogen lamp with IR-cut filter). The pixel retains 80% of its peak QE at ±15° incident angles and maintains stable 1/PLS performance even under low F-number (F#) conditions. Full article
(This article belongs to the Special Issue Special Issue on the 2025 International Image Sensor Workshop (IISW2025))
►▼ Show Figures

Figure 1

19 pages, 5566 KB  
Article
The Influence of a Floating Wetland on Nitrate and Phosphate Reduction in Urban Waterways: A 5-Year Case Study of the North Branch Canal, Chicago, Illinois, USA
by Daniel Chukwudi, Eric W. Peterson and Phil Nicodemus
Urban Sci. 2025, 9(11), 482; https://doi.org/10.3390/urbansci9110482 (registering DOI) - 16 Nov 2025
Abstract
Urban streams often suffer from poor water quality, in part due to nutrient pollution, especially in highly developed areas. Poor water quality, driven by high concentrations of nitrate and phosphate entering waterways from runoff, wastewater, and stormwater systems, contributes to urban stream syndrome. [...] Read more.
Urban streams often suffer from poor water quality, in part due to nutrient pollution, especially in highly developed areas. Poor water quality, driven by high concentrations of nitrate and phosphate entering waterways from runoff, wastewater, and stormwater systems, contributes to urban stream syndrome. This study evaluates the long-term performance of a floating wetland (FW) system installed in a canal of the North Branch of the Chicago River near Goose Island, an area heavily impacted by urban runoff. From 2018 to 2023, surface and subsurface water samples were collected upstream and downstream of a 90 m2 FW system and analyzed for nitrate as nitrogen (NO3-N) and phosphate (PO43−) using ion chromatography. A paired t-test and two-way ANOVA revealed statistically significant reductions (p < 0.001) in NO3-N (mean: 1.31 mg/L surface, 1.02 mg/L at 0.3 m) and PO43− (mean: 0.64 mg/L surface, 0.57 mg/L at 0.3 m) between waters entering and exiting the FW, with no significant seasonal differences in removal efficiency. These results highlight the FW’s consistent, year-round nutrient mitigation performance driven by plant uptake and microbial processes. Over the five-year period of the study, the FW served as a means of improving the water quality, delivering a sustainable, low-maintenance solution for urban stream management with broader implications for ecological resilience and water quality enhancement. Full article
(This article belongs to the Special Issue Urban Water Resources Assessment and Environmental Governance)
►▼ Show Figures

Figure 1

14 pages, 6675 KB  
Article
Effect of Weighting Factors in Energy Efficiency of Predictive Control of Multi-Phase Drives
by Esteban Marsal, Manuel R. Arahal, Manuel G. Satué and Kumars Rouzbehi
Appl. Sci. 2025, 15(22), 12148; https://doi.org/10.3390/app152212148 (registering DOI) - 16 Nov 2025
Abstract
Predictive current control of variable speed drives by direct command of inverter states allows fast control. Its application to multiphase system constitutes a flexible solution that tackles several objectives by means of a cost function with several terms. Weighting factors are used to [...] Read more.
Predictive current control of variable speed drives by direct command of inverter states allows fast control. Its application to multiphase system constitutes a flexible solution that tackles several objectives by means of a cost function with several terms. Weighting factors are used to give relative importance of each term. They have a remarkable effect on figures of merit. In particular, secondary plane content and average switching frequency are usually considered as figures of merit. However, weighting factor effect on global energy efficiency has not been studied before because losses have different sources (commutations, Joule effect, etc.) that do not have a clear link with weighting factors and because trade-offs might appear. The present work uses an experimental setup with a five-phase induction machine connected to a mechanical load. By measuring the power balance, it is possible to show the effect of weighting factor tuning on losses. By tuning λxy, efficiency increases by up to 25%. In parallel, optimizing λnc reduces the average switching frequency by 9% and 18% across the evaluated configurations. This enables the selection of the most adequate values of the weighting factors. The results show that for each speed and load combination, the drive exhibits improved efficiency for some tuning. Full article
(This article belongs to the Special Issue Advanced Technologies for Power Systems—from Power Electronics to Smart Grid Optimization)
15 pages, 1251 KB  
Article
Application of a Box-Cox Transformed LSTAR-GARCH Model for Point and Interval Forecasting of Monthly Rainfall in Hainan, China
by Xiaoxuan Zhang, Yu Liu and Jun Li
Water 2025, 17(22), 3274; https://doi.org/10.3390/w17223274 (registering DOI) - 16 Nov 2025
Abstract
To improve the accuracy of monthly rainfall forecasting and reasonably quantify its uncertainty, this study developed a hybrid LSTAR-GARCH model incorporating a Box–Cox transformation. Using monthly rainfall data from 1999 to 2019 from four meteorological stations in Hainan Province (Haikou, Dongfang, Danzhou, and [...] Read more.
To improve the accuracy of monthly rainfall forecasting and reasonably quantify its uncertainty, this study developed a hybrid LSTAR-GARCH model incorporating a Box–Cox transformation. Using monthly rainfall data from 1999 to 2019 from four meteorological stations in Hainan Province (Haikou, Dongfang, Danzhou, and Qiongzhong), the non-stationarity and nonlinearity of the series were first verified using KPSS and BDS tests, and the Box–Cox transformation was applied to reduce skewness. A Logistic Smooth Transition Autoregressive (LSTAR) model was then established to capture nonlinear dynamics, followed by a GARCH(1,1) model to address heteroskedasticity in the residuals. The results indicate that: (1) The LSTAR model effectively captured the nonlinear characteristics of monthly rainfall, with Nash-Sutcliffe efficiency (NSE) values ranging from 0.565 to 0.802, though some bias remained in predicting extreme values; (2) While the GARCH component did not improve point forecast accuracy, it significantly enhanced interval forecasting performance. At the 95% confidence level, the average interval width (RIW) of the LSTAR-GARCH model was reduced to 0.065–0.130, substantially narrower than that of the LSTAR-ARCH model (RIW: 4.548–8.240), while maintaining high coverage rates (CR) between 93.8% and 97.9%; (3) The LSTAR-GARCH model effectively characterizes both the nonlinear mean process and time-varying volatility in rainfall series, proving to be an efficient and reliable tool for interval rainfall forecasting, particularly in tropical monsoon regions with high rainfall variability. This study provides a scientific basis for regional water resource management and climate change adaptation. Full article
(This article belongs to the Section Water and Climate Change)
►▼ Show Figures

Figure 1

10 pages, 1698 KB  
Article
Blast Nucleation Suppressed Growth of Large-Sized High-Quality CsPbBr3 Single Crystals for Photodetector Applications
by Xinyu Sun, Yuxia Yin, Xiaolin Xia and Teng Zhang
Molecules 2025, 30(22), 4423; https://doi.org/10.3390/molecules30224423 (registering DOI) - 16 Nov 2025
Abstract
During the growth of lead halide perovskite single crystals (SCs) with the conventional inverse temperature crystallization (ITC) method, the blast nucleation of the precursor under supersaturation conditions is always unavoidable. In the current study, three kinds of additives namely methanol (MOE), ethyl alcohol [...] Read more.
During the growth of lead halide perovskite single crystals (SCs) with the conventional inverse temperature crystallization (ITC) method, the blast nucleation of the precursor under supersaturation conditions is always unavoidable. In the current study, three kinds of additives namely methanol (MOE), ethyl alcohol (EtOH), and polyethylene glycol (PEG) are introduced to regulate the growth of CsPbBr3 SCs. Benefiting from the strong anchoring hydroxy groups (-OH) with the Pb2+ species, large-sized CsPbBr3 crystals with reduced defect densities were prepared (PEG-regulated). In addition, the viscosity of the precursor solution increases after adding PEG additive, which provides a more stabilized environment for crystal growth. Finally, the photodetectors prepared from our PEG-tuned CsPbBr3 SCs show a responsivity of 2.25 A/W and a detectivity of 6.06 × 1011 Jones, demonstrating the potential of CsPbBr3 SCs for photo-detecting applications. Full article
(This article belongs to the Special Issue Chemistry Innovatives in Perovskite Based Materials)
►▼ Show Figures

Figure 1

25 pages, 4102 KB  
Article
Reusable 3D-Printed Thermoplastic Polyurethane Honeycombs for Mechanical Energy Absorption
by Alin Bustihan, Razvan Hirian and Ioan Botiz
Polymers 2025, 17(22), 3035; https://doi.org/10.3390/polym17223035 (registering DOI) - 16 Nov 2025
Abstract
In this study, we investigate the mechanical energy absorption performance of reusable 3D-printed honeycomb structures fabricated using fused deposition modeling with three thermoplastic polyurethane variants: TPU 70A, TPU 85A, and TPU 95A. Prior to manufacturing, the mechanical properties of the TPU filaments were [...] Read more.
In this study, we investigate the mechanical energy absorption performance of reusable 3D-printed honeycomb structures fabricated using fused deposition modeling with three thermoplastic polyurethane variants: TPU 70A, TPU 85A, and TPU 95A. Prior to manufacturing, the mechanical properties of the TPU filaments were analyzed as a function of printing temperature to optimize tensile strength and layer adhesion. Four honeycomb configurations, including hexagonal and circular cell geometries, both with and without a 30° twist, were subjected to out-of-plane compression testing to evaluate energy absorption efficiency, specific energy absorption, and crushing load efficiency. The highest energy absorption efficiency, 47%, was achieved by the hexagonal honeycomb structure fabricated from TPU 95A, surpassing the expected values for expanded polystyrene and approaching the performance reported for high-cost advanced lattice structures. Additionally, twisted honeycomb configurations exhibited improved crushing load efficiency values (up to 73.5%), indicating better stress distribution and enhanced reusability. Despite variations in absorbed energy, TPU 95A demonstrated the best balance of elasticity, structural integrity, and reusability across multiple compression cycles. These findings suggest that TPU-based honeycomb structures could provide a viable, cost-effective alternative for energy-absorbing applications in impact protection systems, automotive safety, and sports equipment. Full article
(This article belongs to the Section Polymer Processing and Engineering)
►▼ Show Figures

Figure 1

21 pages, 2234 KB  
Article
Explainable and Optimized Random Forest for Anomaly Detection in IoT Networks Using the RIME Metaheuristic
by Mohamed Sasi, Oluwatayomi Rereloluwa Adegboye and Ahmad Alzubi
Electronics 2025, 14(22), 4465; https://doi.org/10.3390/electronics14224465 (registering DOI) - 16 Nov 2025
Abstract
The rapid expansion of Internet of Things (IoT) ecosystems has amplified their exposure to sophisticated cyber threats, particularly Distributed Denial-of-Service (DDoS) attacks that exploit device heterogeneity and resource constraints. Traditional machine learning-based intrusion detection systems often suffer from suboptimal performance due to poor [...] Read more.
The rapid expansion of Internet of Things (IoT) ecosystems has amplified their exposure to sophisticated cyber threats, particularly Distributed Denial-of-Service (DDoS) attacks that exploit device heterogeneity and resource constraints. Traditional machine learning-based intrusion detection systems often suffer from suboptimal performance due to poor hyperparameter configuration and a lack of interpretability, which are critical limitations in security-critical IoT environments. To address these challenges, this paper proposes an explainable, automated, and efficient anomaly detection framework that integrates a Random Forest (RF) classifier with the RIME metaheuristic optimization algorithm for hyperparameter tuning. Inspired by the physical process of rime ice formation, RIME’s dual-phase search mechanism effectively balances global exploration and local exploitation to identify near-optimal RF configurations in complex, high-dimensional search spaces. Evaluated on a real-world IoT traffic dataset encompassing twelve distinct DDoS attack vectors, the RIME-optimized RF model achieves a testing accuracy of 93.4%, outperforming baseline RF and other metaheuristic-optimized variants in both performance and convergence stability. Crucially, SHAP (SHapley Additive exPlanations) analysis provides transparent, attack-specific insights into feature importance, highlighting syn_flag_number, Protocol Type, Magnitue, Radius, and Ack_flag_number as key discriminative features, thereby enhancing model trustworthiness and operational utility. This work delivers a lightweight, interpretable, and high-performance solution well-suited for deployment in resource-constrained IoT networks, aligning with the urgent need for intelligent, adaptive, and explainable security mechanisms in next-generation network infrastructures. Full article
(This article belongs to the Special Issue Emerging Technologies for Network Security and Anomaly Detection)
►▼ Show Figures

Figure 1

27 pages, 764 KB  
Article
Oil Prices, Financial Development, and Urbanization in the Renewable Energy Transition: Empirical Evidence from E-10 Countries
by Erhan Oruç, Ali Rıza Solmaz, Muhammet Rıdvan İnce and Yavuz Kılınç
Sustainability 2025, 17(22), 10242; https://doi.org/10.3390/su172210242 (registering DOI) - 16 Nov 2025
Abstract
The factors influencing the use of renewable energy in ten significant emerging economies (E-10: Argentina, Brazil, China, Indonesia, India, Mexico, Poland, Russia, South Africa, and Turkey) are examined in this study for the years 1990–2021. In order to capture both contemporaneous and intertemporal [...] Read more.
The factors influencing the use of renewable energy in ten significant emerging economies (E-10: Argentina, Brazil, China, Indonesia, India, Mexico, Poland, Russia, South Africa, and Turkey) are examined in this study for the years 1990–2021. In order to capture both contemporaneous and intertemporal drivers of renewable energy demand, the analysis uses dynamic panel techniques (GMM) in conjunction with static panel estimations (fixed and random effects), drawing on a balanced panel dataset. The empirical findings highlight the path-dependent character of the energy transition by pointing to a clear persistence effect, in which previous renewable energy consumption significantly and favorably influences current levels. While oil prices and carbon emissions exert adverse pressures, economic growth and financial development are consistently recognized as key facilitators of the adoption of renewable energy. In several specifications, population growth appears as a constraining factor. Both static and dynamic models show that urbanization has a negative impact on the use of renewable energy. Therefore, incorporating renewable energy considerations into urban development policies may help reverse this trend and promote increased use of renewable energy. When combined, the results show how strategically important it is to promote economic growth, strengthen financial systems, and incorporate sustainability into urbanization processes. The urgent need to phase out fossil fuel subsidies, reroute financial resources toward green investment, and fortify carbon mitigation frameworks are among the policy implications. In the end, the evidence favors a multifaceted policy framework for the E-10 nations to hasten the switch to renewable energy. Full article
(This article belongs to the Special Issue Towards Sustainability: Advances in Renewable Energy Policy and Environmental Economics)
►▼ Show Figures

Figure 1

19 pages, 13554 KB  
Article
Study on the Interfacial Bonding Behavior of OPC-GGBS-SAC Composite Repair Materials
by Xiang He, Wei Zhang, Yucong Liu, Yong Zhang, Yang Yu, Mengdie Niu and Guoxin Li
Buildings 2025, 15(22), 4124; https://doi.org/10.3390/buildings15224124 (registering DOI) - 16 Nov 2025
Abstract
The bonding interface between repair materials and concrete substrate is the weakest link in the entire repair structure. If the interface bonding performance is insufficient, the repair material is prone to cracking or falling off, leading to repair failure. The shrinkage of repair [...] Read more.
The bonding interface between repair materials and concrete substrate is the weakest link in the entire repair structure. If the interface bonding performance is insufficient, the repair material is prone to cracking or falling off, leading to repair failure. The shrinkage of repair materials is one of the primary factors affecting the bonding performance of these interfaces. In this study, sulphoaluminate cement (SAC) was used to improve the repair performance of ordinary Portland cement (OPC)–granulated blast furnace slag (GGBS) composite repair materials. The influence of SAC on the mechanical properties, bonding performance, expansion behavior, impermeability, and hydration heat of OPC-GGBS-SAC composite repair materials was investigated. The results demonstrate that the rapid hydration of SAC significantly improved the early strength and mechanical properties of the composite system at negative temperatures. The hydration products filled the pores within the concrete matrix, thereby enhancing the mechanical meshing effect at the interface. The early expansion effect of SAC formed a pre-stressor at the interface, which not only strengthened the bonding force between repair materials and the substrate, but also effectively inhibited the shrinkage of the composite system and prevented crack formation, thus significantly promoting the long-term reliability of the bonding interface. An appropriate amount of SAC can accelerate the hydration process of OPC-GGBS system, advance the exothermic peak, and promote the development of early strength. However, excessive incorporation will inhibit the later hydration of the composite system due to the way in which the hydration products wrap the cement particles. When the content of SAC was 5–10%, optimal comprehensive properties of the OPC-GGBS-SAC composite system were attained. Full article
(This article belongs to the Section Building Materials, and Repair & Renovation)
►▼ Show Figures

Figure 1

27 pages, 1949 KB  
Article
Hierarchical Prompt Engineering for Remote Sensing Scene Understanding with Large Vision–Language Models
by Tianyang Chen and Jianliang Ai
Remote Sens. 2025, 17(22), 3727; https://doi.org/10.3390/rs17223727 (registering DOI) - 16 Nov 2025
Abstract
Vision–language models (VLMs) show strong potential for remote-sensing scene classification but still struggle with fine-grained categories and distribution shifts. We introduce a hierarchical prompting framework that decomposes recognition into a coarse-to-fine decision process with structured outputs, combined with parameter-efficient adaptation using LoRA/QLoRA. To [...] Read more.
Vision–language models (VLMs) show strong potential for remote-sensing scene classification but still struggle with fine-grained categories and distribution shifts. We introduce a hierarchical prompting framework that decomposes recognition into a coarse-to-fine decision process with structured outputs, combined with parameter-efficient adaptation using LoRA/QLoRA. To evaluate robustness without depending on external benchmarks, we construct five protocol variants of the AID (V0–V4) that systematically vary label granularity, class consolidation, and augmentation settings. Each variant is designed to align with a specific prompting style and hierarchy. The data pipeline follows a strict split-before-augment strategy, in which augmentation is applied only to the training split to avoid train-test leakage. We further audit leakage using rotation/flip–invariant perceptual hashing across splits to ensure reproducibility. Experiments on all five AID variants show that hierarchical prompting consistently outperforms non-hierarchical prompts and matches or exceeds full fine-tuning, while requiring substantially less compute. Ablation studies on prompt design, adaptation strategy, and model capacity—together with confusion matrices and class-wise metrics—indicate improved recognition at both coarse and fine levels, as well as robustness to rotations and flips. The proposed framework provides a strong, reproducible baseline for remote-sensing scene classification under constrained compute and includes complete prompt templates and processing scripts to support replication. Full article
►▼ Show Figures

Figure 1

12 pages, 916 KB  
Article
Prospective Quasi-Experimental Study of Postoperative Pain Following Class II Composite Restorations Using the Snow-Plow and Resin-Coating Techniques
by Alaa Al-Haddad, Tuleen Alwahesh, Tayma Dweikat, Dana Sharayiah, Alaa Sabrah and Rawan Elkarmi
J. Clin. Med. 2025, 14(22), 8107; https://doi.org/10.3390/jcm14228107 (registering DOI) - 16 Nov 2025
Abstract
Background/Objectives: Postoperative sensitivity remains a common challenge following direct composite restorations, especially in Class II cavities with deep proximal boxes. The snow-plow and resin-coating techniques have been proposed to improve marginal adaptation and reduce postoperative discomfort; however, comparative clinical data remain limited. [...] Read more.
Background/Objectives: Postoperative sensitivity remains a common challenge following direct composite restorations, especially in Class II cavities with deep proximal boxes. The snow-plow and resin-coating techniques have been proposed to improve marginal adaptation and reduce postoperative discomfort; however, comparative clinical data remain limited. This prospective, split-mouth, quasi-experimental study aimed to compare postoperative pain associated with Class II restorations placed using either the snow-plow or resin-coating technique. Methods: This prospective, split-mouth study followed 83 adult patients (aged 18–45 years) who received bilateral Class II composite restorations for one week. The study received ethical approval. Each participant received one restoration using the snow-plow technique and another using the resin-coating approach. Pain intensity was evaluated using a 10-point visual analog scale (VAS) at baseline, 24-h, 72-h, and 1-week postoperatively. Analyses included Wilcoxon signed-rank, Friedman, Chi-square, McNemar, and two-way repeated-measures ANOVA tests. Results: Pain intensity peaked at 24-h for both techniques and declined significantly by 72-h and 1 week (p < 0.001). The snow-plow technique showed slightly lower mean pain scores at 24 and 72 h (p = 0.026 and p = 0.004, respectively), though categorical analyses revealed no significant difference in pain-free or minimal-pain proportions at any interval (p > 0.05). Both techniques showed significant within-group reductions in pain over time (p < 0.001). Conclusions: Both restorative approaches demonstrated similar postoperative pain trajectories, with substantial improvement by one week. While minor differences in early mean pain intensity were observed, these were not clinically significant. The findings suggest that either technique can be effectively employed to achieve satisfactory postoperative comfort when modern adhesive protocols are applied. Clinicians can therefore select either technique based on preference and clinical circumstances, with the expectation of comparable short-term postoperative comfort outcomes. Full article
(This article belongs to the Section Dentistry, Oral Surgery and Oral Medicine)
►▼ Show Figures

Figure 1

39 pages, 8925 KB  
Review
Rainfall-Induced Landslide Prediction Models, Part I: Empirical–Statistical and Physically Based Causative Thresholds
by Kyrillos Ebrahim, Sherif M. M. H. Gomaa, Tarek Zayed and Ghasan Alfalah
Water 2025, 17(22), 3273; https://doi.org/10.3390/w17223273 (registering DOI) - 16 Nov 2025
Abstract
Introduction and Problem Statement: Landslides represent a significant geological hazard worldwide. One of the primary triggers for these landslides is rainfall, which is becoming more intense as a result of climate change. The available literature has produced extensive research. However, this largely [...] Read more.
Introduction and Problem Statement: Landslides represent a significant geological hazard worldwide. One of the primary triggers for these landslides is rainfall, which is becoming more intense as a result of climate change. The available literature has produced extensive research. However, this largely overlooks the use of mixed methodologies. Furthermore, a comprehensive review combining empirical, physically based, deterministic, and phenomenological models is still rare. Objective and Method: This study (Part I of a two-part review) addresses this gap by employing a mixed review that integrates quantitative scientometric analysis with a qualitative systematic review. The primary objective of Part I is to deliver a critical assessment, focusing on empirical and physically based causative threshold models. Main Results and Validation: Macroscopically, our analysis reveals that antecedent rainfall is a more robust indicator than classical intensity–duration (I-D) thresholds, though the latter remains widely used due to its simplicity. Physically based models provide a critical bridge when geotechnical data is scarce, correlating rainfall with internal slope responses like displacement. At a microscopic level, hybrid artificial intelligence (AI) models consistently demonstrate superior predictive accuracy by capturing complex, nonlinear relationships missed by simpler models. These findings are validated through a systematic evaluation of performance metrics across the reviewed literature. Main Conclusions and Significance: We conclude that while empirical thresholds offer operational simplicity, the future of accurate prediction lies in sophisticated hybrid AI models trained on extensive monitoring data. This review synthesizes fragmented knowledge into a unified framework, providing a clear roadmap for model selection. Full article
(This article belongs to the Special Issue Rainfall-Induced Landslides: Influencing, Modelling and Hazard Assessment: 2nd Edition)
10 pages, 832 KB  
Article
Distribution of Rotavirus alphagastroenteritidis Strains in Blantyre, Malawi, During and After the COVID-19 Pandemic
by End Chinyama, Chimwemwe Mhango, Rothwell Taia, Landilani Gauti, Jonathan Mandolo, Flywell Kawonga, Ernest Matambo, Prisca Matambo, Innocent Chibwe, Richard Wachepa, Nigel A. Cunliffe, Chisomo L. Msefula and Khuzwayo C. Jere
Pathogens 2025, 14(11), 1169; https://doi.org/10.3390/pathogens14111169 (registering DOI) - 16 Nov 2025
Abstract
Rotavirus alphagastroenteritidis remains the leading cause of severe gastroenteritis in children under five years, despite widespread vaccine use. The COVID-19 pandemic disrupted healthcare and vaccination delivery, while non-pharmacological interventions may have influenced R. alphagastroenteritidis transmission. We conducted hospital-based surveillance of R. alphagastroenteritidis gastroenteritis [...] Read more.
Rotavirus alphagastroenteritidis remains the leading cause of severe gastroenteritis in children under five years, despite widespread vaccine use. The COVID-19 pandemic disrupted healthcare and vaccination delivery, while non-pharmacological interventions may have influenced R. alphagastroenteritidis transmission. We conducted hospital-based surveillance of R. alphagastroenteritidis gastroenteritis at Queen Elizabeth Central Hospital (QECH) in Blantyre, Malawi, from October 2019 to October 2024. Children under five presenting with acute gastroenteritis were enrolled; 99.1% of vaccine-eligible participants had received at least one R. alphagastroenteritidis vaccine dose. Stool samples were tested for R. alphagastroenteritidis by enzyme immunoassay (EIA) and genotyped using RT-PCR. Among 1135 enrolled children, 29.1% (330/1135) were R. alphagastroenteritidis-positive. Cases occurred year-round except for December 2020–January 2021, when no R. alphagastroenteritidis infections were detected, and February–March 2023, when no samples were collected. The prevalence varied significantly by age group between children greater than 23 months of age to the rest of the age groups (<6 months, 6–11 months, and 12–22 months) (p = 0.0046). The most common R. alphagastroenteritidis G-genotypes were G3 (38.7%), G2 (25.4%), and G12 (17.2%), with G2 emerging as the predominant strain from June 2023. G3P[8] was the most frequent G–P combination (25%). Its overall prevalence did not change during the pandemic; however, genotype distribution shifted compared to pre-COVID-19 patterns. Sustained surveillance and genomic analyses are essential to monitor evolving strain dynamics and inform vaccine policy. Full article
(This article belongs to the Special Issue From Gastroenteritis to Emerging Threats: One Health Surveillance of Viral Infections)
►▼ Show Figures

Figure 1

15 pages, 3132 KB  
Article
Visibility-Based Calibration of Low-Cost Particulate Matter Sensors: Laboratory Evaluation and Theoretical Analysis
by Ayala Ronen
Sensors 2025, 25(22), 6995; https://doi.org/10.3390/s25226995 (registering DOI) - 16 Nov 2025
Abstract
Low-cost optical sensors for particulate matter (PM) monitoring, such as the SDS011, are widely used due to their affordability and ease of deployment. However, their accuracy strongly depends on aerosol properties and environmental conditions, necessitating reliable calibration. This study presents a theoretical and [...] Read more.
Low-cost optical sensors for particulate matter (PM) monitoring, such as the SDS011, are widely used due to their affordability and ease of deployment. However, their accuracy strongly depends on aerosol properties and environmental conditions, necessitating reliable calibration. This study presents a theoretical and laboratory evaluation of a practical calibration method based on visibility sensors, which measure atmospheric light extinction and are readily available at many meteorological stations. Experiments were conducted in a controlled aerosol chamber, using SDS011 sensors, visibility sensors (FD70 and SWS250), and gravimetric samplers. The mass extinction coefficient was determined through parallel measurements of visibility and mass concentration, enabling conversion of optical signals into accurate PM values. The calibrated SDS011 sensors demonstrated consistent response with a stable normalization factor (dependent on aerosol type, wavelength, and particle size), allowing their deployment as a spatially distributed sensor network. Comparison with manufacturer calibration revealed substantial deviations due to differences in aerosol optical properties, highlighting the importance of application-specific calibration. The visibility-based approach enables real-time, continuous calibration of low-cost sensors with minimal equipment, offering a scalable solution for PM monitoring in resource-limited or remote environments. The method’s robustness under varying environmental conditions remains to be explored. Nevertheless, the results establish visibility-based calibration as a reliable and accessible framework for enhancing the accuracy of low-cost PM sensing technologies. The method enables scalable calibration with a single gravimetric reference and is suited for future field deployment in resource-limited settings, following additional validation under real atmospheric conditions. Full article
(This article belongs to the Special Issue Advanced Sensing Techniques for Environmental and Energy Systems)
►▼ Show Figures

Figure 1

21 pages, 2624 KB  
Article
Hypersphere-Guided Reciprocal Point Learning for Open-Set Industrial Process Fault Diagnosis
by Shipeng Li, Qi Wen, Binbin Zheng and Xinhua Wang
Processes 2025, 13(11), 3698; https://doi.org/10.3390/pr13113698 (registering DOI) - 16 Nov 2025
Abstract
Deep neural networks (DNNs) have achieved superior performance in diagnosing process faults, but they lack robustness when encountering novel fault types absent from training sets. Such unknown faults commonly appear in industrial settings, and conventional DNNs often misclassify them as one of the [...] Read more.
Deep neural networks (DNNs) have achieved superior performance in diagnosing process faults, but they lack robustness when encountering novel fault types absent from training sets. Such unknown faults commonly appear in industrial settings, and conventional DNNs often misclassify them as one of the known fault types. To address this limitation, we formulate the concept of open-set fault diagnosis (OSFD), which seeks to distinguish unknown faults from known ones while correctly classifying the known faults. The primary challenge in OSFD lies in minimizing both the empirical classification risk associated with known faults and the open space risk without access to training data for unknown faults. In order to mitigate these risks, we introduce a novel approach called hypersphere-guided reciprocal point learning (SRPL). Specifically, SRPL preserves a DNN for feature extraction while constraining features to lie on a unit hypersphere. To reduce empirical classification risk, it applies an angular-margin penalty that explicitly increases intra-class compactness and inter-class separation for known faults on the hypersphere, thereby improving discriminability among known faults. Additionally, SRPL introduces reciprocal points on the hypersphere, with each point acting as a classifier by occupying the extra-class region associated with a particular known fault. The interactions among multiple reciprocal points, together with the deliberate synthesis of unknown fault features on the hypersphere, serve to lower open-space risk: the reciprocal-point interactions provide an indirect estimate of unknowns, and the synthesized unknowns provide a direct estimate, both of which enhance distinguishability between known and unknown faults. Extensive experimental results on the Tennessee Eastman process confirm the superiority of the proposed method compared to state-of-the-art OSR algorithms, e.g., an 82.32% AUROC score and a 71.50% OSFDR score. Full article
(This article belongs to the Special Issue Fault Detection Based on Deep Learning)
►▼ Show Figures

Figure 1

26 pages, 2510 KB  
Article
A Three-Machine Flowshop Scheduling Problem with Linear Fatigue Effect
by Weiping Xu, Zehou Sun, Xiaotian Ai, Baoyun Zhao, Jingyi Lu, Hanyu Zhou, Xinqi Mao, Xiaoling Wen, Chin-Chia Wu and Shufeng Liu
Mathematics 2025, 13(22), 3670; https://doi.org/10.3390/math13223670 (registering DOI) - 16 Nov 2025
Abstract
Highly customized requirements in smart manufacturing result in the unavoidable manual execution of complex operational procedures. Physical and mental fatigue from long work periods for assembly-line operators induces production issues, such as defective work-in-processes or equipment failure. An effective production schedule should account [...] Read more.
Highly customized requirements in smart manufacturing result in the unavoidable manual execution of complex operational procedures. Physical and mental fatigue from long work periods for assembly-line operators induces production issues, such as defective work-in-processes or equipment failure. An effective production schedule should account for worker fatigue. This study investigates a three-machine flowshop scheduling problem with the objective of makespan minimization, in which a linear fatigue effect function provides an approximate mathematical representation of fatigue and recovery processes in workers. A mixed integer programming (MIP) model is developed to optimize the integration of automated and human-operated production in manufacturing systems. Given its NP-hardness, an improved tabu search (ITS) algorithm is designed to obtain high-quality solutions, incorporating multiple initial solutions, a well-designed encoding-decoding strategy, and a tabu-based adaptive search mechanism to enhance efficiency. Numerical simulations indicate the veracity of the MIP model and the effectiveness of the ITS algorithm. Full article
(This article belongs to the Special Issue Recent Advances in Planning and Scheduling for Supply Chain Optimization)
►▼ Show Figures

Figure 1

9 pages, 590 KB  
Article
The Effect of Thyroid Function on GDF15 Levels
by Nicia I. Profili, Edoardo Fiorillo, Valeria Orrù, Francesco Cucca and Alessandro P. Delitala
Int. J. Mol. Sci. 2025, 26(22), 11073; https://doi.org/10.3390/ijms262211073 (registering DOI) - 16 Nov 2025
Abstract
Growth differentiation factor 15 (GDF15) is a stress-response cytokine, which exerts different actions in physiological and pathological conditions. Thyroid disorders are common in the general population and their role on GDF15 levels has not been sufficiently addressed. Serum levels of GDF-15 and thyroid [...] Read more.
Growth differentiation factor 15 (GDF15) is a stress-response cytokine, which exerts different actions in physiological and pathological conditions. Thyroid disorders are common in the general population and their role on GDF15 levels has not been sufficiently addressed. Serum levels of GDF-15 and thyroid function were assessed in a large sample from the SardiNIA cohort (n = 4413). We further collected antibodies against thyroperoxidase and anti-thyroglobulin in all participants. Thyroid function correlated with GDF15. Specifically, after adjusting for covariates, thyrotropin had a positive association with GDF15, while free thyroxine was negatively correlated. We also found that subjects with circulating antibodies against thyroperoxidase had lower GDF15 levels. The reduced level of the thyroid hormone can cause a decreased metabolic activity and higher cell stress response, which, in turn, increases the production of GDF-15 as a defense mechanism. The association between antibodies against thyroperoxidase and GDF15 deserves additional study to elucidate the pathophysiologic relationship. Full article
(This article belongs to the Collection Feature Paper Collection in Molecular Endocrinology and Metabolism)
►▼ Show Figures

Figure 1

More Articles...

Open Access Journals

► Browse by Indexing ► Browse by Subject ► Selected Journals
Explore All Journals...

Highly Accessed Articles

Latest Books

More Books and Reprints...

News

13 November 2025
MDPI is a Platinum Sponsor of the 2nd International Conference of Environmental Medicine in Chieti, Italy, 20–21 November 2025
13 November 2025
Meet Us at the 17th Canadian Science Policy Conference, 19–21 November 2025, Ottawa, Ontario
12 November 2025
MDPI Is a Sponsor for the 20th Munin Conference on Scholarly Publishing 2025, in Tromsø, Norway, 18–20 November 2025
More News & Announcements...

Blog Posts

More From Our Blog...

Topics

More Topics...
loading...

Selected Special Issues

Selected Collections

Back to TopTop