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Frequency regulation (FR) constitutes a fundamental aspect of power system stability, particularly in the context of the growing integration of intermittent renewable energy sources (RES) and electric vehicles (EVs). The load frequency control (LFC) mechanism, essential for achieving FR, is increasingly reliant on communication infrastructures that are inherently vulnerable to cyber threats. Cyberattacks targeting these communication links can severely compromise coordination among smart grid components, resulting in erroneous control actions that jeopardize the security and stability of the power system. In light of these concerns, this study proposes a cyber-physical LFC framework incorporating a fuzzy linear active disturbance rejection controller (F-LADRC), wherein the controller parameters are systematically optimized using the quasi-opposition-based reptile search algorithm (QORSA). Furthermore, the proposed approach integrates a comprehensive cyberattack detection and prevention scheme, employing Haar wavelet transforms for anomaly detection and long short-term memory (LSTM) networks for predictive mitigation. The effectiveness of the proposed methodology is validated through simulations conducted on a restructured power system integrating RES and EVs, as well as a modified IEEE 39-bus test system. The simulation outcomes substantiate the capability of the proposed framework to deliver robust and resilient frequency regulation, maintaining system frequency and tie-line power fluctuations within nominal operational thresholds, even under adverse cyberattack scenarios. Full article

15 pages, 316 KiB

Open AccessArticle

On the Change of Measure for Brownian Processes

by Francis J. Pinski

Entropy 2025, 27(6), 594; https://doi.org/10.3390/e27060594 (registering DOI) - 31 May 2025

Abstract

Sometimes, limits can be singular, implying that they assume different values depending on the order of arithmetic operations. In other words, the limit map lacks commutativity. While all such limits are mathematically valid, only one can be the physical limit. For instance, the change of measure for Brownian processes illustrates this phenomenon. A substantial body of elegant mathematics centered around continuous-time Brownian processes has been embraced by the physics community to investigate the nonequilibrium and equilibrium thermodynamics of systems composed of atoms and molecules. In this paper, we derive the continuous-time limit of discrete-time Brownian dynamics, specifically focusing on the change of measure. We demonstrate that this result yields the physical limit that differs from the commonly used expression. Consequently, the concepts of “the most probable path”, “minimum thermodynamic action”, and “the small-noise limit” are unphysical mathematical artifacts. Full article

(This article belongs to the Section Non-equilibrium Phenomena)

23 pages, 3291 KiB

Open AccessArticle

From Contamination to Consequence: Tracing Donna Lake’s Human Environmental History

by Dean Kyne

Geographies 2025, 5(2), 24; https://doi.org/10.3390/geographies5020024 (registering DOI) - 31 May 2025

Abstract

The Donna Reservoir and Canal System (Donna Lake) in Texas has been a persistent source of environmental contamination for over a century, exposing surrounding communities to dangerous levels of polychlorinated biphenyls (PCBs). Originally built for agricultural irrigation, the system became a recreational fishing site before PCB contamination was discovered during public health investigations in the 1990s. This study examines patterns of demographic vulnerability, evaluates remediation efforts by the U.S. Environmental Protection Agency (EPA), and explores residents’ ongoing challenges related to toxic exposure. Using publicly available demographic data, EPA reports, and previous health assessments, the study analyzes variations in community characteristics by proximity to Donna Lake and reviews the effectiveness of interventions implemented to date. The results show that communities closer to the contamination site are predominantly low-income and Spanish-speaking, and that remediation efforts, although initiated, have been slow and insufficient to fully eliminate health risks. The residents continue to face gaps in risk communication and protection. The findings underscore the lasting impacts of historical contamination on vulnerable populations and highlight the urgent need for more effective, community-centered remediation strategies to address persistent environmental health disparities. Full article

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24 pages, 777 KiB

Open AccessPerspective

From Laggard to Leader: A Novel Policy Perspective of Michigan’s Preliminary Path to Climate Success

by Laura U. Schneider and Nancy Boyd

Challenges 2025, 16(2), 27; https://doi.org/10.3390/challe16020027 (registering DOI) - 31 May 2025

Abstract

The realities of climate change are here, and in the absence of encompassing U.S. federal policies directing action, it is left to the states to help set our course for the future. At the forefront of state action is Michigan, which in 2023 passed sweeping legislation requiring the state to achieve climate neutrality, a significant investment in electric vehicle infrastructure, and a commitment to environmental justice. The bold climate-forward actions by the state have been described by many as vaulting the state of Michigan into a national leader on climate policy. This perspective uses Michigan’s novel collection of climate-related policies to examine the connections between infrastructure, environmental justice, and climate change in Michigan. The legislation was passed with strong Democratic support, but Republicans and some environmentalists are concerned about the feasibility of the state to implement the legislation, especially when some states like California are having to back down from their green energy goals. We find that the legislation focuses on the triple bottom line by supporting economic growth in the state, advancing the interests of rural and urban communities alike, and embracing ambitious environmental goals. Michigan is already seeing successful implementation of this policy, and the lessons of this action can help provide a roadmap for other states seeking to move forward on climate policy. This novel perspective demonstrates the unique qualities Michigan is bringing to climate legislation, and the newness of the policies opens new research opportunities for a variety of scholarship interests. Full article

15 pages, 295 KiB

Open AccessArticle

Predictors of Low Back Pain Risk Among Farmers in Rural Communities of Loja, Ecuador

by Isabel Masson Palacios, Israel Vinueza-Fernandez, Samuel-Olegario Iñiguez-Jiminez, Mario J. Grijalva and Benjamin R. Bates

Int. J. Environ. Res. Public Health 2025, 22(6), 885; https://doi.org/10.3390/ijerph22060885 (registering DOI) - 31 May 2025

Abstract

Background: Low back pain (LBP) and musculoskeletal disorders are highly prevalent among agricultural workers. However, there is limited epidemiological evidence from rural regions of Ecuador, where working and living conditions may differ substantially from those in other settings. This study aimed to identify predictors of LBP among farmers in rural Ecuador to inform locally relevant prevention strategies. Methods: Participants aged 30 to 60 years (n = 103) were recruited through a traveling health clinic. Participants were assessed with behavioral and sociodemographic self-report questionnaires and anthropometric measurements. Low back pain (LBP) was assessed using the Standardized Nordic Musculoskeletal Questionnaire, which asked about symptoms experienced in the past 12 months. Bivariate (Chi-square and Fisher exact tests) and multivariate (binary logistic regression) analyses were conducted to explore associations between risk factors and LBP in individuals aged 30 to 60 years. Results: LBP was highly prevalent, affecting 78.6% of participants. Behavioral patterns were mixed, with low rates of smoking and moderate alcohol and coffee consumption associated with LBP. A normal body mass index (BMI) was observed in 66% of the sample, and over half reported stable mood and good self-perceived health. In the binary logistic regression analysis, only education level significantly predicted LBP, with secondary education acting as a protective factor. Conclusions: While lower back pain was widespread in the population studied, most risk factors that were analyzed were not significantly associated with its presence. Full article

17 pages, 1496 KiB

Open AccessArticle

Associations Between Eating Disorders and Sociodemographic Factors in Adolescent Patients Since the Start of the COVID-19 Pandemic

by Janet Lee, David Miller and Paulina Rugart

Children 2025, 12(6), 730; https://doi.org/10.3390/children12060730 (registering DOI) - 31 May 2025

Abstract

Background/Objectives: The COVID-19 pandemic has been associated with significant increases in mental-health-related concerns in adolescents, including eating disorders. Disparities in screening, diagnosis, and treatment impact adolescents with eating disorders. This study aimed to describe the patterns in the prevalence and the associations between eating disorder diagnoses and demographic factors in adolescent patients since the start of the COVID-19 pandemic. Methods: We performed a retrospective cohort study examining adolescent patients (aged 12 to 21) with an eating disorder (ED) diagnosis documented between January 2019 and July 2023 using Epic Systems Corporation’s Cosmos, a de-identified dataset aggregated from electronic health record (EHR) data. We examined the differences in demographic factors by utilizing chi-square and Kruskal–Wallis rank sum tests. Results: A total of 82,435 distinct adolescent and young adult patients with eating disorder diagnoses were included in the analytical dataset. The overall prevalence of EDs has increased since 2019. The median age of patients with an ED decreased between 2019 and 2023. There was a decrease in other eating disorder diagnoses and an increase in avoidant-restrictive food intake disorder (ARFID) during the study period. There was a decrease in the proportion of individuals who identified as White and an increase in the proportion of adolescents from historically minoritized racial and ethnic groups (i.e., African American or Black and Hispanic). There was also an increase, during this study period, in the proportion of adolescents with an ED diagnosis who were from more socially vulnerable communities. Conclusions: Our study describes the changes in the prevalence of sociodemographic factors in adolescent patients with EDs since the start of the COVID-19 pandemic. Further studies should address screening, diagnostic, and treatment barriers for EDs in historically underserved communities. Full article

(This article belongs to the Section Global Pediatric Health)

11 pages, 1185 KiB

Open AccessArticle

Use of a Validated Risk Perception Questionnaire for the Inclusion of People with Hearing Impairments in a Productive Environment

by Aline Franchini, Antonio Xavier and André Soares

Int. J. Environ. Res. Public Health 2025, 22(6), 884; https://doi.org/10.3390/ijerph22060884 (registering DOI) - 31 May 2025

Abstract

The inclusion of people with hearing impairments in logistics environments is a topic of increasing importance, especially when considering the promotion of diversity and accessibility in the workplace. The use of a risk perception questionnaire can represent an effective tool to identify barriers and challenges faced by these workers. The questionnaire covers several aspects, including communication between employees, the adequacy of visual signage, workplace safety and the accessibility of tools and equipment. The responses collected help to understand how people with hearing impairments perceive the risks inherent in their work activities, as well as to identify possible deficiencies in the training and awareness of their coworkers. Analysis of the data collected by the questionnaire allows companies to develop specific strategies and actions to improve inclusion, such as inclusive training, adaptation of the physical environment and implementation of auxiliary technologies. In this way, these actions not only contribute to a safer and more productive work environment, but also value diversity and the unique contribution that each worker can make to the logistics sector. Full article

(This article belongs to the Special Issue Models and Approaches to Workplace Health Promotion and Well-Being with Diverse Population Groups)

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21 pages, 2534 KiB

Open AccessArticle

GenDRA: Generative Data Reconstruction Attacks on Federated Edge Learning and Countermeasures

by Chengcheng Zhao, Shuilin Li, Yuanhang He, Wenkai Huang, Gaolei Li, Li Ding and Jianhua Li

Electronics 2025, 14(11), 2263; https://doi.org/10.3390/electronics14112263 (registering DOI) - 31 May 2025

Abstract

Federated edge learning (FEL) unites the decentralized training capabilities of multiple edge nodes to allow model gradient sharing and parameter aggregation across a peer-to-peer network. However, many intrinsic policy conflicts still exist in FEL, for example, the open accessibility of gradients will lead to the privacy leakage risk during the federal aggregation process. In this paper, we first identify that malicious users weaponized with generative artificial intelligence (GenAI) can generate fake samples that are almost identical to FEL participants’ training data. By analyzing how different configurations of GenAI affect attack effectiveness, we find that an adversary with strong patchwork and reconstruction capabilities can stealthily steal diverse training data from nearly all FEL participants. To thwart such a generative data reconstruction attack (GenDRA) scheme, we propose a novel target semantic dissolution (TSD) mechanism for enhancing the privacy-preserving ability of FEL, which encrypts only a very small number (≤10%) of gradient values in each training round that have a significant impact on human visual formation using format-preserving encryption. With TSD, the speculator cannot obtain a fake sample that is visually similar to the training sample because real gradients are actively concealed. Extensive experiments based on four benchmark datasets are performed to demonstrate the huge threat of GenAI and the effectiveness of TSD in all aspects: compelling accuracy performance, strong visual privacy guarantee, and low computing overhead. Full article

(This article belongs to the Topic Recent Advances in Security, Privacy, and Trust)

30 pages, 8909 KiB

Open AccessReview

Recent Design and Application Advances in Micro-Electro-Mechanical System (MEMS) Electromagnetic Actuators

by Jianqun Cheng, Ning Xue, Bocang Qiu, Boqi Qin, Qingchun Zhao, Gang Fang, Zhihui Yao, Wenyi Zhou and Xuguang Sun

Micromachines 2025, 16(6), 670; https://doi.org/10.3390/mi16060670 (registering DOI) - 31 May 2025

Abstract

Micro-electro-mechanical system (MEMS) electromagnetic actuators have rapidly evolved into critical components of various microscale applications, offering significant advantages including precision, controllability, high force density, and rapid responsiveness. Recent advancements in actuator design, fabrication methodologies, smart control integration, and emerging application domains have significantly broadened their capabilities and practical applications. This comprehensive review systematically analyzes the recent developments in MEMS electromagnetic actuators, highlighting core operating principles such as Lorentz force and magnetic attraction/repulsion mechanisms and examining state-of-the-art fabrication technologies, such as advanced microfabrication techniques, additive manufacturing, and innovative material applications. Additionally, we provide an in-depth discussion on recent enhancements in actuator performance through smart and adaptive integration strategies, focusing on improved reliability, accuracy, and dynamic responsiveness. Emerging application fields, particularly micro-optical systems, microrobotics, precision micromanipulation, and microfluidic components, are extensively explored, demonstrating how recent innovations have significantly impacted these sectors. Finally, critical challenges, including miniaturization constraints, integration complexities, power efficiency, and reliability issues, are identified, alongside a prospective outlook outlining promising future research directions. This review aims to serve as an authoritative resource, fostering further innovation and technological advancement in MEMS actuators and related interdisciplinary fields. Full article

(This article belongs to the Special Issue Magnetic Manipulation in Micromachines)

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27 pages, 2162 KiB

Open AccessReview

Future of Telepresence Services in the Evolving Fog Computing Environment: A Survey on Research and Use Cases

by Dang Van Thang, Artem Volkov, Ammar Muthanna, Andrey Koucheryavy, Abdelhamied A. Ateya and Dushantha Nalin K. Jayakody

Sensors 2025, 25(11), 3488; https://doi.org/10.3390/s25113488 (registering DOI) - 31 May 2025

Abstract

With the continuing development of technology, telepresence services have emerged as an essential part of modern communication systems. Concurrently, the rapid growth of fog computing presents new opportunities and challenges for integrating telepresence capabilities into distributed networks. Fog computing is a component of the cloud computing model that is used to meet the diverse computing needs of applications in the emergence and development of fifth- and sixth-generation (5G and 6G) networks. The incorporation of fog computing into this model provides benefits that go beyond the traditional model. This survey investigates the convergence of telepresence services with fog computing, evaluating the latest advancements in research developments and practical use cases. This study examines the changes brought about by the 6G network as well as the promising future directions of 6G. This study presents the concepts of fog computing and its basic structure. We analyze Cisco’s model and propose an alternative model to improve its weaknesses. Additionally, this study synthesizes, analyzes, and evaluates a body of articles on remote presence services from major bibliographic databases. Summing up, this work thoroughly reviews current research on telepresence services and fog computing for the future. Full article

(This article belongs to the Special Issue Synergistic Intelligence: Pioneering Deep Learning Paradigms for Multi-Sensor Systems)

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19 pages, 4699 KiB

Open AccessArticle

Rough-Terrain Path Planning Based on Deep Reinforcement Learning

by Yufeng Yang and Zijie Zhang

Appl. Sci. 2025, 15(11), 6226; https://doi.org/10.3390/app15116226 (registering DOI) - 31 May 2025

Abstract

Road undulations have a significant impact on path lengths and energy consumption, so rough-terrain path planning for unmanned vehicles is of great research importance for performing more tasks with limited energy. This paper proposes a Deep Q-Network (DQN)-based path-planning method, which shapes the reward by introducing a slope penalty function and a terrain penalty function. For the problem of the low exploration efficiency of the ε-greedy strategy, a hybrid exploration strategy combining stochastic exploration and the A* algorithm is proposed, after which the agent is trained on rough terrain. The results show that the algorithm can efficiently plan energy-saving paths, converge quickly, and compared with the traditional A* algorithm and RRT algorithm, performs better under three-dimensional terrain and can choose paths more rationally. Full article

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27 pages, 869 KiB

Open AccessArticle

An Automatic Code Generation Tool Using Generative Artificial Intelligence for Element Fill-in-the-Blank Problems in a Java Programming Learning Assistant System

by Zihao Zhu, Nobuo Funabiki, Mustika Mentari, Soe Thandar Aung, Wen-Chung Kao and Yi-Fang Lee

Electronics 2025, 14(11), 2261; https://doi.org/10.3390/electronics14112261 (registering DOI) - 31 May 2025

Abstract

Presently, Java is a fundamental object-oriented programming language that can be mastered by any student in information technology or computer science. To assist both teachers and students, we developed the Java Programming Learning Assistant System (JPLAS). It offers several types of practice problems with different levels and learning goals for step-by-step self-study, where any answer is automatically marked in the system. One challenge for teachers that is addressed with JPLAS is the generation of proper exercise problems that meet learning requirements. We implemented programs for generating new problems from given source codes, as collecting and evaluating suitable codes remains time-consuming. In this paper, we present an automatic code generation tool using generative AI to solve this challenge. Prompt engineering is used to help generate an appropriate source code, and the quality is controlled by optimizing the prompt based on the outputs. For applications in JPLAS, we implement a web application system to automatically generate an element fill-in-the-blank problem (EFP) in JPLAS. For evaluation, we select the element fill-in-the-blank problem (EFP) as the target type in JPLAS and generate several instances using this tool. The results confirm the validity and effectiveness of the proposed method. Full article

(This article belongs to the Special Issue New Advances in Embedded Software and Applications)

23 pages, 3886 KiB

Open AccessArticle

Anchor-Free SNR-Aware Signal Detector for Wideband Signal Detection Framework

by Chunhui Li, Xin Xiang, Hu Mao, Rui Wang and Yonglei Qi

Electronics 2025, 14(11), 2260; https://doi.org/10.3390/electronics14112260 (registering DOI) - 31 May 2025

Abstract

The spectrogram-based wideband signal detection framework has garnered increasing attention in various wireless communication applications. However, the front-end spectrograms in existing methods suffer from visual and informational deficiencies. This paper proposes a novel multichannel enhanced spectrogram (MCE spectrogram) to address these issues. The MCE spectrogram leverages additional channels for both visual and informational enhancement, highlighting signal regions and features while integrating richer recognition information across channels, thereby significantly improving feature extraction efficiency. Moreover, the back-end networks in existing methods are typically transferred from original object detection networks. Wideband signal detection, however, exhibits task-specific characteristics, such as the inherent signal-to-noise ratio (SNR) attribute of the spectrogram and the large variations in shapes of signal bounding boxes. These characteristics lead to issues like inefficient task adaptation and anchor mismatch, resulting in suboptimal performance. To tackle these challenges, we propose an SNR-aware detection network that employs an anchor-free paradigm instead of anchors for signal detection. Additionally, to address the impact of the SNR attribute, we design a trainable gating module for efficient feature fusion and introduce an auxiliary task branch to enable the network to capture more discriminative feature representations under varying SNRs. Experimental results demonstrate the superiority of the MCE spectrogram compared to those utilized in existing methods and the state-of-the-art performance of our SNR-aware Net among comparable detection networks. Full article

(This article belongs to the Section Artificial Intelligence)

21 pages, 378 KiB

Open AccessArticle

Barriers and Challenges in the Implementation of Decentralized Solar Water Disinfection Treatment Systems—A Case of Ghana

by Abdul-Rahaman Afitiri and Ernest Kofi Amankwa Afrifa

Solar 2025, 5(2), 25; https://doi.org/10.3390/solar5020025 (registering DOI) - 31 May 2025

Abstract

Decentralized solar water disinfection systems (DSODIS) in continuous flow systems are alternatives for large-scale improved water access in rural contexts. However, DSODIS in rural Ghana are limited. An exploratory sequential mixed-methods design was used to explore the enablers of and barriers to, as well as reported barrier perceptions to, the effective implementation of DSODIS in the Sawla-Tuna-Kalba (STK) District of Ghana. The qualitative data (26 respondents) were analyzed thematically, and the quantitative data (1155 household heads) were subjected to Poisson regression analyses. Enablers were categorized into themes such as willingness to pay for DSODIS, household and community participation, and willingness to use water from DSODIS. Similarly, the barriers include environmental barriers, technological barriers, economic barriers, and political and legal barriers. Household characteristics such as main water source and income, age group, education, marital status, household size, being born in the community, and years living in the community are statistically associated with reported barrier perceptions. Households with unimproved water sources and high income (IRR = 1.432, p = 0.000) and improved water sources and high income (IRR = 1.295, p = 0.000) are 43% and 30% more likely, respectively, to report more barrier perceptions compared with households with unimproved water sources and low income. Females (IRR = 1.070, p = 0.032) are marginally more likely to report more barrier perceptions compared with males. The model output also indicates that household heads with higher educational attainment (IRR = 1.152, p = 0.001) are 15% more likely to report more barrier perceptions compared with those with no formal education. These findings provide valuable information for policymakers and stakeholders aiming to provide quality water in rural Ghana where centralized systems cannot be installed. Full article

15 pages, 4317 KiB

Open AccessArticle

Food Environment Around Schools in a Capital City in Southern Brazil: Changes in the Availability of Commercial Food Establishments Between 2012 and 2019

by Lidiamara Dornelles de Souza, Elizabeth Nappi Corrêa, Adalberto Aparecido dos Santos Lopes, Cristine Garcia Gabriel and Francisco de Assis Guedes de Vasconcelos

Int. J. Environ. Res. Public Health 2025, 22(6), 877; https://doi.org/10.3390/ijerph22060877 (registering DOI) - 31 May 2025

Abstract

Objective: The objective of this article was to perform a comparative analysis of the changes in the availability of commercial food establishments around the schools in a Brazilian capital city. Methods: This is a comparative analysis between two cross-sectional panels performed in 2012 and 2019 in Florianópolis, Santa Catarina, Brazil. Secondary data from different sources were used. The location data of schools and establishments were georeferenced. For the analysis of the surroundings of schools, a network buffer of 800 m was considered. The establishments were classified based on the foods they primarily sold: fresh, mixed and ultra-processed foods. The chi-square and Wilcoxon tests were applied for the analyses, considering a significance level of 95% (p < 0.05). Results: The number of food establishments around schools increased by 63%. There was a statistically significant growth in mixed (p = 0.008) and ultra-processed (p = 0.024) food- selling establishments. Conclusion: We conclude that the increase in establishments selling ultra-processed foods around schools at the expense of establishments selling fresh food deserves attention. This condition requires public policies that help promote healthier environments, thus contributing to the health of schoolchildren. Full article

(This article belongs to the Special Issue Bridging the Gap in Studies on the Food Environment: The State-of-the-Art in Low- and Middle-Income Countries (LMICs))

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