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16 pages, 2981 KB

Open AccessArticle

Assessing the Spatiotemporal Patterns and Afforestation Impacts on Land-Use Carbon Storage in the Yellow River Basin Using Multi-Source Remote Sensing Products

by Libing Luo, Ming Liu, Ying Wang, Hao Zhang and Xiangnan Liu

Forests 2025, 16(11), 1731; https://doi.org/10.3390/f16111731 (registering DOI) - 15 Nov 2025

Abstract

Afforestation plays a vital role in reshaping land systems and enhancing carbon sequestration, particularly in ecologically fragile regions. However, the carbon implications and spatial dynamics of large-scale planted-forest (PF) expansion in the Yellow River Basin (YRB) remain insufficiently understood. Focusing on the YRB, [...] Read more.

Afforestation plays a vital role in reshaping land systems and enhancing carbon sequestration, particularly in ecologically fragile regions. However, the carbon implications and spatial dynamics of large-scale planted-forest (PF) expansion in the Yellow River Basin (YRB) remain insufficiently understood. Focusing on the YRB, this study integrates multi-source land-use, forest type, and carbon datasets to evaluate land-use transitions (2000–2020) and quantify changes in total ecosystem carbon (TEC), aboveground carbon (AGC), and PF-derived AGC (PF-AGC) from 2005 to 2020 under the IPCC-based accounting framework. The results show cumulative land-use conversion of 118,481 km², with forest land expanded to 11.89% of the basin, mainly due to afforestation efforts in the middle reaches. TEC followed a rise–decline–rebound trajectory, yielding a net gain of 1.96 × 10⁸ t, while AGC increased by 4.37 × 10⁸ t. With the expansion of PF, PF-AGC contributed 1.60 × 10⁸ t (36.61% of AGC gains), primarily sourced from grassland (40.51%), natural forests (35.15%), and cropland (23.56%). PFs were dominated by young stands (≤40 years), spatially clustered in the middle–lower reaches, and exhibited higher carbon sink potential than natural forests. Spatially, AGC and PF distributions underwent staged reconfiguration. Standard deviational ellipse and centroid analyses revealed eastward shifts and axis changes in AGC, and southwestward migration of PFs, indicating PF expansion as a major driver of carbon redistribution. These findings clarify the forest age–land-use–carbon nexus and highlight the spatial impact of afforestation, offering critical insights for region-specific low-carbon strategies and sustainable land governance in the YRB. Full article

(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)

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26 pages, 386 KB

Open AccessArticle

Hybrid Telehealth Adaptation of COMPASS for Hope: Parent-Mediated Outcomes in Autism

by Alexis D. Rodgers, Brittany A. Dale and Lisa A. Ruble

Behav. Sci. 2025, 15(11), 1561; https://doi.org/10.3390/bs15111561 (registering DOI) - 15 Nov 2025

Abstract

There are limited empirically supported interventions that target three outcomes—behavior of children with ASD (instead of using adjectives such as “disruptive,” “interfering,” “problem,” or “challenging” behavior, we use “behavior” to avoid ableist language), parent stress, and parenting sense of competence. To help address [...] Read more.

There are limited empirically supported interventions that target three outcomes—behavior of children with ASD (instead of using adjectives such as “disruptive,” “interfering,” “problem,” or “challenging” behavior, we use “behavior” to avoid ableist language), parent stress, and parenting sense of competence. To help address this need, we tested a hybrid telehealth adaptation of COMPASS for Hope (C-HOPE), an 8-week parent-mediated program originally offered via face-to-face or synchronous telehealth delivery. The present study incorporated asynchronous group discussion board sessions hosted on a learning-management platform together with synchronous individual coaching sessions by telephone. Using a pre-post design, 10 caregivers completed the intervention. Effect sizes were calculated for three treatment outcomes of child behavior, parent stress, and parenting sense of competence. There was a statistically significant difference in the scores for child behavior, with a large effect size (d = 0.73) and a statistically significant difference in parent stress, with a medium effect size (d = 0.50). No difference was observed for parenting sense of competence. Treatment adherence and caregiver satisfaction for the intervention were acceptable. Findings support the feasibility and promise of combining asynchronous and synchronous telehealth elements to increase access to evidence-based parent-mediated interventions for ASD. Full article

(This article belongs to the Special Issue Psychosocial and Behavioral Interventions for Youth with Neurodevelopmental Disorders)

14 pages, 2318 KB

Open AccessArticle

Synergistic Effects of MXene and Carbon Nanotubes in Multi-Stimuli-Responsive Chitosan Materials: Combining Shape Memory and Electromagnetic Shielding Functions

by Ziyun Li, Shuai Yang, Sitong Wang, Jiaying Liu, Ning Guo, Zhichao He, Zijian Song and Yingchun Li

Coatings 2025, 15(11), 1332; https://doi.org/10.3390/coatings15111332 (registering DOI) - 15 Nov 2025

Abstract

Shape memory polymers (SMPs) are a class of smart materials that exhibit unique shape-fixing and recovery abilities, attracting wide attention for applications in electronics, aerospace, and biomedical engineering. Chitosan (CS) as a renewable biopolymer, possessing good biocompatibility, biodegradability, and antimicrobial properties; its use [...] Read more.

Shape memory polymers (SMPs) are a class of smart materials that exhibit unique shape-fixing and recovery abilities, attracting wide attention for applications in electronics, aerospace, and biomedical engineering. Chitosan (CS) as a renewable biopolymer, possessing good biocompatibility, biodegradability, and antimicrobial properties; its use as a matrix enhances the environmental compatibility and bio-adaptability of SMPs. MXene, as a novel two-dimensional material, is characterized by high electrical conductivity, abundant surface functional groups and good hydrophilicity, showing potential in energy storage, electromagnetic shielding and sensing. In this work, CS and poly (vinyl alcohol) (PVA) were used as the polymer matrix, and carbon nanotubes (CNTs) together with MXene were introduced as co-fillers to construct multifunctional composites. The effect of the CNTs/MXene hybrid fillers on mechanical properties, electromagnetic shielding and multi-stimuli-responsive shape memory behavior was systematically investigated. After ratio optimization, the composites showed excellent comprehensive performance: tensile strength reached up to 20.0 MPa, Young’s modulus up to 292.2 MPa, and maximum elongation at break of 23.2%; electromagnetic interference shielding effectiveness (SE_T) in the X-band (8.2–12.4 GHz) reached a maximum of 10.6 dB; shape fixation rates exceeded 90%; under thermal stimulation, a shape recovery ratio of 98.3% was achieved within 41.7 s; light-driven recovery rate reached 86.5% with a minimal recovery time of 82.3 s; under electrical stimulation the highest recovery rate was 94.1% with a shortest recovery time of 30 s. This study successfully prepared functional multi-stimuli-responsive shape memory composite films and provided a new strategy for the design of green smart materials. Full article

(This article belongs to the Special Issue Multifunctional Polymer Thin Films for Surface Engineering)

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28 pages, 3812 KB

Open AccessArticle

Vertical vs. Horizontal Integration in HBM and Market-Implied Valuation: A Text-Mining Study

by Hyang Ja Yang and Cheong Kim

Appl. Sci. 2025, 15(22), 12127; https://doi.org/10.3390/app152212127 (registering DOI) - 15 Nov 2025

Abstract

High-bandwidth memory (HBM) has become a strategic bottleneck in AI-centric systems, shifting competitive advantage from computing power alone to a design that is orchestrated by memory and packaging. We investigate whether publicly available information about companies’ integration decisions—vertical integration by Samsung Electronics and [...] Read more.

High-bandwidth memory (HBM) has become a strategic bottleneck in AI-centric systems, shifting competitive advantage from computing power alone to a design that is orchestrated by memory and packaging. We investigate whether publicly available information about companies’ integration decisions—vertical integration by Samsung Electronics and horizontal partnerships by SK Hynix—is included in market-expected valuation. We create a Korean-language news corpus spanning January 2023 to September 2025 and use seed-guided topic models to obtain firms’ vertical and horizontal integration. We verify qualitative distinguishability with t-SNE embeddings and use firm-specific ordinary least squares specifications to link topic intensities to equity prices. According to research findings, for Samsung, consolidation-oriented vertical indicators (M&A and risk ring-fencing) positively correlate with valuation, whereas supplier-enablement or operational vertical topics are not reliably factored into their valuation. Vendor-assisted scale-up and joint development topics support positive valuation for SK Hynix. This study provides a scalable framework for text evaluation, which distinguishes between general sentiment and strategic architecture, as well as evidence that capital markets reward consolidation and alliance execution differently depending on the management of the HBM bottleneck. Full article

(This article belongs to the Special Issue Big Data Technology and Its Applications)

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12 pages, 1917 KB

Open AccessArticle

Compressed Snow Blocks: Evaluating the Feasibility of Adapting Earth Block Technology for Cold Regions

by Katie L. Duggan DiDominic, Terry D. Melendy, Jr. and Chrestien M. Charlebois

Glacies 2025, 2(4), 14; https://doi.org/10.3390/glacies2040014 (registering DOI) - 15 Nov 2025

Abstract

Snow construction plays a crucial role in military operations in cold regions, providing tactical fortifications, thermal insulation, and emergency infrastructure in environments where conventional building materials are scarce or require extensive infrastructure for support. Current snow construction methods, including manual piling and compaction, [...] Read more.

Snow construction plays a crucial role in military operations in cold regions, providing tactical fortifications, thermal insulation, and emergency infrastructure in environments where conventional building materials are scarce or require extensive infrastructure for support. Current snow construction methods, including manual piling and compaction, are labor-intensive and inconsistent, limiting their use in large-scale or time-sensitive operations. This study explores the feasibility of adapting a compressed earth block (CEB) machine to produce compressed snow blocks (CSBs) as modular, uniform building units for cold-region applications. Using an AECT Impact 2001A hydraulic press, naturally occurring snow was processed with a snowblower and compacted at maximum operating pressure (i.e., 20,684 kPa) to evaluate block formation, dimensional consistency, and density. The machine successfully produced relatively consistent CSBs, but the initial 3–4 blocks following block height adjustment were generally unsuccessful (e.g., incorrect block height or collapsed/broke) while the machine reached its steady state cyclic condition. These blocks were discarded and excluded from the dataset. The successful CSBs had mean block heights of 7.76 ± 0.56 cm and densities comparable to ice (i.e., 0.83 g/cm³). Variations in block height and mass may be attributed to manual snow loading and minor material impurities. While the dataset is limited, the results warrant further investigation into this technology, particularly regarding CSB strength (i.e., hardness and compressive strength) and performance under variable snow and environmental conditions. Mechanized snow compaction using existing CEB technology is technically feasible and capable of producing uniform, structurally stable CSBs but requires further investigation and modifications to reach its full potential. With design improvements such as automated snow feeding, cold-resistant components, and system winterization, this approach could enable scalable CSB production for rapid, on-site construction of snow-based structures in Arctic environments, supporting the military and civilian needs. Full article

(This article belongs to the Special Issue Current Snow Science Research 2025–2026)

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15 pages, 2610 KB

Open AccessArticle

Parameter Identification of SiC MOSFET Half-Bridge Converters Using a Multi-Objective Optimization Method

by Salvatore Monteleone, Luigi Danilo Tornello, Davide Patti, Giacomo Scelba, Maurizio Palesi, Enrico Russo, Mario Pulvirenti and Luciano Salvo

Electronics 2025, 14(22), 4458; https://doi.org/10.3390/electronics14224458 (registering DOI) - 15 Nov 2025

Abstract

Silicon carbide (SiC) power converters are attracting increasing interest due to their significant advantages in terms of efficiency, switching speed, and greater temperature tolerance compared to traditional silicon-based converters. Tools to improve the design process, such as those to predict the switching behavior [...] Read more.

Silicon carbide (SiC) power converters are attracting increasing interest due to their significant advantages in terms of efficiency, switching speed, and greater temperature tolerance compared to traditional silicon-based converters. Tools to improve the design process, such as those to predict the switching behavior of silicon carbide-based power converters, can be of great help, e.g., in studying critical electrical/thermal stress in power devices. This work aims to present an effective multi-objective optimization method to identify the main parasitic parameters of a SiC half-bridge power converter related to the board layout and device packaging. This goal was achieved by minimizing the errors between the system responses carried out by the simulated power converter and the measurements collected from a limited number of experimental tests. The feasibility and effectiveness of the method are verified by tests performed on a 1200 V, 75 A, SiC half-bridge converter. Although this methodology has been validated for a specific converter topology, it can be extended to model more complex power converter structures. Full article

(This article belongs to the Special Issue Efficiency- and Reliability-Oriented Design of Power Electronic Devices, Converters, and Systems)

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15 pages, 2144 KB

Open AccessArticle

Mathematical Modeling of the Influence of Equilibrium Coefficient Variation on the Steady-State Transport of a Binary Electrolyte in the Cross-Section of a Desalination Channel

by Evgenia Kirillova, Natalia Chubyr, Roman Nazarov, Anna Kovalenko and Makhamet Urtenov

Axioms 2025, 14(11), 839; https://doi.org/10.3390/axioms14110839 (registering DOI) - 15 Nov 2025

Abstract

This paper presents the first theoretical investigation of the effect of a variable equilibrium coefficient on the steady-state transport of a binary electrolyte in a desalination channel cross-section of the electrodialyzer. To address this problem, we developed a new mathematical model in the [...] Read more.

This paper presents the first theoretical investigation of the effect of a variable equilibrium coefficient on the steady-state transport of a binary electrolyte in a desalination channel cross-section of the electrodialyzer. To address this problem, we developed a new mathematical model in the form of a boundary value problem for an extended system of stationary Nernst–Planck–Poisson equations. We obtained a numerical solution to this problem using the finite element method. Analysis of this solution revealed that the channel cross-section has a complex structure: it is divided into seven regions dominated by different processes, and, consequently, the solution to the boundary value problem behaves differently in each of them. Existing models of the diffusion layer or channel cross-section typically assume a constant equilibrium coefficient. In this paper, we demonstrated that in the channel cross-section, the velocity change corresponding to the equilibrium constant is related not only to the field strength but also to the magnitude of the space charge. In the space-charge region, in the boundary layers near the ion-exchange membranes, intense dissociation of water molecules occurs, and the higher the equilibrium coefficient, the more intense this dissociation is. We have shown that an internal boundary layer (recombination region) arises deep within the solution, associated with the recombination reaction of H+ and OH− ions. In this study, we found that with increasing equilibrium coefficient, fluxes increase, while with increasing fluxes, the electric field strength decreases proportionally, and equilibrium is reached. We demonstrate that by calibrating a single fitting parameter in the model, the simulation results can be matched to experimental data with high accuracy. Thus, our proposed model and its numerical solution provide a completely new understanding of the ion transport process in electromembrane systems, taking into account the influence of the dissociation/recombination reaction of water molecules. Full article

(This article belongs to the Special Issue Advances in Nonlinear Analysis and Numerical Modeling)

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8 pages, 209 KB

Open AccessEditorial

Editorial: The Role of Telemedicine in Transforming Healthcare Delivery—Capabilities and Barriers

by Motti Haimi

Healthcare 2025, 13(22), 2927; https://doi.org/10.3390/healthcare13222927 (registering DOI) - 15 Nov 2025

Abstract

The rapid evolution of digital health technologies has fundamentally reshaped healthcare delivery worldwide, with telemedicine emerging as a cornerstone of modern patient care [...] Full article

(This article belongs to the Special Issue The Role of Telemedicine in Transforming Healthcare Delivery—Capabilities and Barriers)

29 pages, 3845 KB

Open AccessArticle

Modeling Approaches for Digital Plant Phenotyping Under Dynamic Conditions of Natural, Climatic and Anthropogenic Factors

by Bagdat Yagaliyeva, Olga Ivashchuk and Dmitry Goncharov

Algorithms 2025, 18(11), 720; https://doi.org/10.3390/a18110720 (registering DOI) - 15 Nov 2025

Abstract

Methods, algorithms, and models for the creation and practical application of digital twins (3D models) of agricultural crops are presented, illustrating their condition under different levels of atmospheric CO₂ concentration, soil, and meteorological conditions. An algorithm for digital phenotyping using machine learning [...] Read more.

Methods, algorithms, and models for the creation and practical application of digital twins (3D models) of agricultural crops are presented, illustrating their condition under different levels of atmospheric CO₂ concentration, soil, and meteorological conditions. An algorithm for digital phenotyping using machine learning methods with the U²-Net architecture are proposed for segmenting plants into elements and assessing their condition. To obtain a dataset and conduct verification experiments, a prototype of a software and hardware complex has been developed that implements the process of cultivation and digital phenotyping without disturbing the microclimate inside the chamber and eliminating the subjectivity of measurements. In order to identify new data and confirm the data published in open scientific sources on the effects of CO₂ on crop growth and development, plants (ten species) were grown at different CO₂ concentrations (0.015–0.03% and 0.07–0.09%) with a 10-fold repetition. A model has been built and trained to distinguish between cases when plant segments need to be combined because they belong to the same leaf (p-value = 0.05), and when they belong to a separate leaf (p-value = 0.03). A knowledge base has been formed, including: 790 3D models of plants and data on their physiological characteristics. Full article

(This article belongs to the Special Issue AI Applications and Modern Industry)

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26 pages, 595 KB

Open AccessArticle

Natural Language Processing as a Scalable Method for Evaluating Educational Text Personalization by LLMs

by Linh Huynh and Danielle S. McNamara

Appl. Sci. 2025, 15(22), 12128; https://doi.org/10.3390/app152212128 (registering DOI) - 15 Nov 2025

Abstract

Four versions of science and history texts were tailored to diverse hypothetical reader profiles (high and low reading skills and domain knowledge), generated by four Large Language Models (i.e., Claude, Llama, ChatGPT, and Gemini). The Natural Language Processing (NLP) technique was applied to [...] Read more.

Four versions of science and history texts were tailored to diverse hypothetical reader profiles (high and low reading skills and domain knowledge), generated by four Large Language Models (i.e., Claude, Llama, ChatGPT, and Gemini). The Natural Language Processing (NLP) technique was applied to examine variations in Large Language Model (LLM) text personalization capabilities. NLP was leveraged to extract and quantify linguistic features of these texts, capturing linguistic variations as a function of LLMs, text genres, and reader profiles. An approach leveraging NLP-based analyses provides an automated and scalable solution for evaluating alignment between LLM-generated personalized texts and readers’ needs. Findings indicate that NLP offers a valid and generalizable means of tracking linguistic variation in personalized educational texts, supporting its use as an evaluation framework for text personalization. Full article

(This article belongs to the Special Issue Neural Network Technologies in Natural Language Processing and Data Mining)

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13 pages, 329 KB

Open AccessArticle

Conservative Hypothesis Test of Multivariate Data from an Uncertain Population with Symmetry Analysis in Music Statistics

by Anshui Li, Jiajia Wang, Shiqi Yao and Wenxing Zeng

Symmetry 2025, 17(11), 1973; https://doi.org/10.3390/sym17111973 (registering DOI) - 15 Nov 2025

Abstract

Music data exhibits numerous distinct symmetric and asymmetric patterns—ranging from symmetric pitch sequences and rhythmic cycles to asymmetric phrase structures and dynamic shifts. These varied and often subjective patterns present notable challenges for data analysis, such as distinguishing meaningful structural features from noise [...] Read more.

Music data exhibits numerous distinct symmetric and asymmetric patterns—ranging from symmetric pitch sequences and rhythmic cycles to asymmetric phrase structures and dynamic shifts. These varied and often subjective patterns present notable challenges for data analysis, such as distinguishing meaningful structural features from noise and adapting analytical methods to accommodate both regularity and irregularity. To tackle this challenge, we present a novel uncertain hypothesis test, referred to as the conservative hypothesis test, which is designed to assess the validity of statistical hypotheses associated with the symmetric and asymmetric patterns exhibited by two multivariate normal uncertain populations. Specifically, we extend the uncertain hypothesis test for the mean difference between two single-characteristic normal uncertain populations to the multivariate case, filling a research gap in uncertainty theory. Building on this two-population multivariate hypothesis test, we propose the conservative hypothesis test—a feasible uncertain hypothesis testing method for multivariable scenarios, developed based on multiple comparison procedures. To demonstrate the practical utility of these methods, we apply them to music-related statistical data, assessing whether two groups of evaluators use consistent criteria to score music. In essence, the hypothesis tests proposed in this paper hold significant value for social sciences, particularly music statistics, where data inherently contains ambiguity and uncertainty. Full article

(This article belongs to the Special Issue Symmetry Analysis of Uncertainty Theory and Uncertain Statistics and Their Interdisciplinary Applications)

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16 pages, 1253 KB

Open AccessArticle

Co-Designing a Web-Based, Gamified, Auditory–Cognitive Dual-Task Training System for Older Adults with Hearing Loss

by Ivy Yan Zhao, Tsz Wai Lau, Chen Li, Janet Ho-Yee Ng, Eleanor Holroyd, Robert Sweetow, Engle Angela Chan and Angela Y. M. Leung

Healthcare 2025, 13(22), 2926; https://doi.org/10.3390/healthcare13222926 (registering DOI) - 15 Nov 2025

Abstract

Background: Age-related hearing loss (ARHL) is associated with decreased communication, reduced social engagement, cognitive decline and an increased risk of dementia globally. Although increasing studies report the benefits of combing auditory and cognitive training for older adults with ARHL, more evidence is needed [...] Read more.

Background: Age-related hearing loss (ARHL) is associated with decreased communication, reduced social engagement, cognitive decline and an increased risk of dementia globally. Although increasing studies report the benefits of combing auditory and cognitive training for older adults with ARHL, more evidence is needed to examine its effects. Moreover, existing training programs have been developed with minimal end-user involvement leading to low adherence rates. This study aimed to investigate the role of co-design in the development of an auditory–cognitive training system for older adults with ARHL. Methods: A co-design methodology was employed. Digital recordings of the co-design workshops were transcribed verbatim. An established reflexive thematic analysis methodology was used. Results: Fifteen older adults with ARHL, referred to as “co-researchers”, participated in three co-design workshops until data saturation was achieved. Consultations were held with two key service providers. Three key themes emerged: (1) older adults with ARHL prefer a user-friendly auditory–cognitive training system; (2) clear, localized and colloquial instructions for the training tasks are necessary; and (3) diversified, tailor-made and dual-task training tasks, performed in an interactive and game-like mode, can motivate and sustain usage of the training system. As a result, a prototype of a web-based, gamified, and adaptive auditory–cognitive dual-task training system was co-designed. Conclusions: Our findings affirmed the importance of genuinely listening to the voices of end-users and creating a system that is responsive to their needs and preferences. Future study is recommended to examine the effects of this system on older adults with ARHL. Full article

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19 pages, 14156 KB

Open AccessArticle

Image Prompt Adapter-Based Stable Diffusion for Enhanced Multi-Class Weed Generation and Detection

by Boyang Deng and Yuzhen Lu

AgriEngineering 2025, 7(11), 389; https://doi.org/10.3390/agriengineering7110389 (registering DOI) - 15 Nov 2025

Abstract

The curation of large-scale, diverse datasets for robust weed detection is extremely time-consuming and resource-intensive in practice. Generative artificial intelligence (AI) opens up opportunities for image generation to supplement real-world image acquisition and annotation efforts. However, it is not a trial task to [...] Read more.

The curation of large-scale, diverse datasets for robust weed detection is extremely time-consuming and resource-intensive in practice. Generative artificial intelligence (AI) opens up opportunities for image generation to supplement real-world image acquisition and annotation efforts. However, it is not a trial task to generate high-quality, multi-class weed images that capture the nuances and variations in visual representations for enhanced weed detection. This study presents a novel investigation of advanced stable diffusion (SD) integrated with a module with image prompt capability, IP-Adapter, for weed image generation. Using the IP-Adapter-based model, two image feature encoders, CLIP (contrastive language image pre-training) and BioCLIP (a vision foundation model for biological images), were utilized to generate weed instances, which were then inserted into existing weed images. Image generation and weed detection experiments are conducted on a 10-class weed dataset captured in vegetable fields. The perceptual quality of generated images is assessed in terms of Fréchet Inception Distance (FID) and Inception Score (IS). YOLOv11 (You Only Look Once version 11) models were trained for weed detection, achieving an improved mAP@50:95 of 1.26% on average when combining inserted weed instances with real ones in training, compared to using original images alone. Both the weed dataset and software programs in this study will be made publicly available. This study offers valuable perspectives into the use of IP-adapter-based SD for generating weed images and weed detection. Full article

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46 pages, 1191 KB

Open AccessArticle

E2E-MDC: End-to-End Multi-Modal Darknet Traffic Classification with Conditional Hierarchical Mechanism

by Junyuan Zhang, Yang Chen, Qingbing Ji, Wei Yu, Lulin Ni, Chengpeng Dai, Lu Kang and Jie Luo

Electronics 2025, 14(22), 4457; https://doi.org/10.3390/electronics14224457 (registering DOI) - 15 Nov 2025

Abstract

Accurate identification and classification of Darknet traffic is a critical technical challenge for network security supervision. Existing methods predominantly adopt single-modal features and independent classification strategies, making it difficult to effectively handle the hierarchical structural characteristics and complex encryption patterns of Darknet traffic. [...] Read more.

Accurate identification and classification of Darknet traffic is a critical technical challenge for network security supervision. Existing methods predominantly adopt single-modal features and independent classification strategies, making it difficult to effectively handle the hierarchical structural characteristics and complex encryption patterns of Darknet traffic. This paper proposes E2E-MDC (End-to-End Multi-modal Darknet Classification), an end-to-end deep learning framework based on conditional hierarchical mechanism for three-level hierarchical classification of Darknet traffic. The framework integrates four complementary feature extractors—byte-level CNN, packet sequence TCN, bidirectional LSTM, and Transformer—to comprehensively capture traffic patterns from multiple perspectives. A soft conditional hierarchical classification architecture explicitly models dependencies among Level 1 (Darknet type), Level 2 (application category), and Level 3 (specific behavior) by using upper-level prediction probability distributions as conditional input for lower-level classification. On the self-collected Tor dataset containing 8 applications and 8 behavior types, the system achieves 94.90% cascade accuracy, with Level 3 fine-grained classification accuracy reaching 95.02%. On the public Darknet-2020 dataset, cascade accuracy reaches 92.65%, representing improvements of 12% and 15% over existing state-of-the-art methods, respectively, while reducing hierarchical violation rate to below 0.8%. Experimental results demonstrate that the conditional hierarchical mechanism and multi-modal fusion strategy significantly enhance the accuracy and robustness of Darknet traffic classification, providing effective technical support for network security protection. Full article

20 pages, 443 KB

Open AccessArticle

Disinformation in Crisis Contexts—Perception of Russia Today’s Narratives in Ecuador

by Abel Suing

Journal. Media 2025, 6(4), 192; https://doi.org/10.3390/journalmedia6040192 (registering DOI) - 15 Nov 2025

Abstract

Disinformation poses a substantive challenge to democratic governance, particularly in contexts marked by foreign influence. While the broadcasting of Russia Today (RT) in Europe has received significant attention, comparatively little is known about its impact and audience reception in Latin America. This study [...] Read more.

Disinformation poses a substantive challenge to democratic governance, particularly in contexts marked by foreign influence. While the broadcasting of Russia Today (RT) in Europe has received significant attention, comparatively little is known about its impact and audience reception in Latin America. This study addresses this gap by analysing Ecuadorians’ perceptions and uptake of RT’s broadcast narratives during a period of acute economic and security crisis. The objectives are (1) to establish the news narratives presented on RT, (2) to identify citizens’ perceptions of the news narratives, and (3) to determine the uptake of the narratives. A mixed methodological approach is undertaken, including narrative analysis of three audiovisual news pieces published by RT in Spanish, a survey, and three online focus groups. The results reveal the deployment of sophisticated narrative strategies that mix information with unsubstantiated claims and emotional appeals, resulting in a discernible bias favouring Russian perspectives. The findings underscore the urgency of strengthening media literacy and public policy responses in Latin America to counter the internalisation of such narratives. In addition, the research contributes to debates on information security, democratic resilience, and the protection of public opinion in vulnerable environments. Full article

(This article belongs to the Special Issue Social Media in Disinformation Studies)

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25 pages, 399 KB

Open AccessArticle

Tropical Solution of Discrete Best Approximation Problems

by Nikolai Krivulin

Mathematics 2025, 13(22), 3660; https://doi.org/10.3390/math13223660 (registering DOI) - 15 Nov 2025

Abstract

We consider discrete best approximation problems in the setting of tropical algebra, which is concerned with the theory and application of algebraic systems with idempotent operations. Given a set of input–output pairs of an unknown function defined on a tropical semifield, the problem [...] Read more.

We consider discrete best approximation problems in the setting of tropical algebra, which is concerned with the theory and application of algebraic systems with idempotent operations. Given a set of input–output pairs of an unknown function defined on a tropical semifield, the problem is to determine an approximating rational function formed by two Puiseux polynomials as numerator and denominator. With specified numbers of monomials in both polynomials, the approximation aims at evaluating the exponent and coefficient for each monomial in the polynomials to fit the rational function to the data in the sense of a tropical distance function. To solve the problem, we transform it into an approximation of a vector equation with unknown vectors on both sides, where one side corresponds to the numerator polynomial and the other side to the denominator. Each side involves a matrix with entries dependent on the unknown exponents, multiplied by the vector of unknown coefficients of monomials. We propose an algorithm that constructs a series of approximate solutions by alternately fixing one side of the equation to an already-found result and leaving the other side intact. Each equation obtained is approximated with respect to the vector of coefficients, which yields this vector and approximation error, both parameterized by exponents. The exponents are found by minimizing the error with an optimization procedure based on an agglomerative clustering technique. To illustrate, we present results for an approximation problem in terms of max-plus algebra (a real semifield with addition defined as maximum and multiplication as arithmetic addition), which corresponds to an ordinary problem of piecewise linear approximation of real functions. As our numerical experience shows, the proposed algorithm converges in a finite number of steps and provides a reasonably accurate solution to the problems considered. Full article

(This article belongs to the Special Issue Approximation and Computation for Numerical Analysis: Latest Advances and Prospects)

20 pages, 995 KB

Open AccessReview

Exploring Chronic Pain, Immune Dysfunction and Lifestyle: A Focus on T Cell Exhaustion and Senescence

by Yanthe Buntinx, Jolien Hendrix, Arne Wyns, Jente Van Campenhout, Huan-Yu Xiong, Thessa Laeremans, Sara Cuesta-Sancho, Joeri L. Aerts, Jo Nijs and Andrea Polli

Biomolecules 2025, 15(11), 1601; https://doi.org/10.3390/biom15111601 (registering DOI) - 15 Nov 2025

Abstract

Chronic pain conditions are debilitating and have an enormous impact on quality of life, yet underlying biological mechanisms remain poorly understood, hindering the development of diagnostic tools and effective treatments. Emerging evidence suggests a role for immune dysfunction in chronic pain. Among the [...] Read more.

Chronic pain conditions are debilitating and have an enormous impact on quality of life, yet underlying biological mechanisms remain poorly understood, hindering the development of diagnostic tools and effective treatments. Emerging evidence suggests a role for immune dysfunction in chronic pain. Among the various forms of immune dysfunction, T cell exhaustion and senescence, well-characterized in cancer and chronic infections, remain largely unexplored in chronic pain research. At the same time, lifestyle factors such as sleep, stress, physical activity, and diet are increasingly recognized as modulators of both pain and immune function. This review explores the potential interplay between these behavioural factors, immune exhaustion/senescence, and chronic pain. Critical gaps in current knowledge are identified, and future directions are outlined to clarify immune dysfunction and the influence of lifestyle factors in chronic pain conditions. Full article

(This article belongs to the Section Molecular Biology)

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21 pages, 330 KB

Open AccessArticle

Walking to/with Queen Saint Elizabeth: “Where Your Very Steps Lead Me”

by Vera Lúcia Rodrigues

Religions 2025, 16(11), 1454; https://doi.org/10.3390/rel16111454 (registering DOI) - 15 Nov 2025

Abstract

The cult of Queen Saint Elizabeth constitutes one of the most persistent manifestations of popular religiosity in central Portugal, especially in Coimbra. Following her death, popular veneration of this saint rapidly consolidated, later legitimized by her beatification in 1516 and canonization in 1625. [...] Read more.

The cult of Queen Saint Elizabeth constitutes one of the most persistent manifestations of popular religiosity in central Portugal, especially in Coimbra. Following her death, popular veneration of this saint rapidly consolidated, later legitimized by her beatification in 1516 and canonization in 1625. This article aims to understand how Elizabethan devotion currently constructs an identity in Coimbra, Portugal. To characterize the pilgrimage and expressions of faith, I observe the biennial festivities, the processional routes, sacrifices, adherence, and generational beliefs in this feminine cult, relating them to the pursuit of health. The article studies the main institutions that regulate devotion in modern times (notably the Confraternity of Queen Saint Elizabeth) and explores some processes of its patrimonialization and touristification. Finally, I also analyze the performativity of rituals and the identity of pilgrims, highlighting how expressions of faith also constitute social, cultural and economic practices. The study is based on ethnographic fieldwork, interviews and documentary analysis. The ethnography (still ongoing) on this very Portuguese pilgrimage already reveals points of differentiation and of commonality with other more famous pilgrimages, such as Fátima and Lourdes, while remaining a significant and unique part of the character of popular religiosity and the local identity of Coimbra. Full article

(This article belongs to the Special Issue Pilgrimage: Diversity, Past and Present of Sacred Routes)

16 pages, 2396 KB

Open AccessArticle

Chemical Profile and Evaluation of the Antioxidant, Anti-Enzymatic, and Antibacterial Activity of Astragalus strictispinus and Astragalus macrocephalus subsp. finitimus

by Saba Shahrivari-Baviloliaei, Ilkay Erdogan Orhan, Fatma Sezer Senol Deniz, Mustafa Abdullah Yilmaz, Agnieszka Viapiana, Agnieszka Konopacka, Osman Tugay and Alina Plenis

Plants 2025, 14(22), 3485; https://doi.org/10.3390/plants14223485 (registering DOI) - 15 Nov 2025

Abstract

Astragalus species are characterized by rich active compounds, mainly polysaccharides, saponins, and polyphenols, with various important bioactivities, such as antioxidant, antitumor, anti-diabetes, antiviral, etc. In this study, the chemical profiles of ethanol, ethyl acetate, and dichloromethane extracts from different parts (leaves, flowers, and [...] Read more.

Astragalus species are characterized by rich active compounds, mainly polysaccharides, saponins, and polyphenols, with various important bioactivities, such as antioxidant, antitumor, anti-diabetes, antiviral, etc. In this study, the chemical profiles of ethanol, ethyl acetate, and dichloromethane extracts from different parts (leaves, flowers, and roots) of two endemic Astragalus species growing in Türkiye, i.e., A. strictispinus and A. macrocephalus subsp. finitimus were determined, along with their antioxidant, anti-enzymatic, and antibacterial properties. According to the results, naringenin and apigenin were identified as two common phenolic compounds of both Astragalus species, while only ethanol extracts of the roots and leaves and ethyl acetate extracts of flowers of A. strictispinis exhibited a low level of antioxidant activity (5–16%). Moreover, AChE and BChE inhibitory activities were higher in the ethyl acetate extract of A. macrocephalus subsp. finitimus leaves, while all leaf extracts of the analyzed Astragalus species, except dichloromethane extract of A. strictispinus, exhibited antibacterial activity against S. aureus. In conclusion, this study provides detailed information that may serve as the scientific basis for the use of Astragalus species as sources of bioactive compounds with multiple functions in the nutraceutical, cosmetic, and pharmaceutical industries. Full article

(This article belongs to the Section Phytochemistry)

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12 pages, 376 KB

Open AccessArticle

Seroprevalence and Vaccination Determinants of Varicella Zoster Virus Among Pediatric and Adolescent Populations in Northern Lebanon

by Nourhan Farhat, Dima El Safadi, Jana Massoud and Sara Khalife

Vaccines 2025, 13(11), 1166; https://doi.org/10.3390/vaccines13111166 (registering DOI) - 15 Nov 2025

Abstract

Background: Varicella zoster virus (VZV) remains a significant cause of pediatric morbidity in populations in Lebanon, yet comprehensive data on population immunity and vaccination uptake are limited. This study aimed to estimate VZV seroprevalence and identify factors associated with immunity and vaccine uptake [...] Read more.

Background: Varicella zoster virus (VZV) remains a significant cause of pediatric morbidity in populations in Lebanon, yet comprehensive data on population immunity and vaccination uptake are limited. This study aimed to estimate VZV seroprevalence and identify factors associated with immunity and vaccine uptake among children and adolescents in Northern Lebanon. Methods: A cross-sectional study was conducted among 180 participants aged 1–18 years recruited from urban and rural settings in North Lebanon. After receiving informed parental consent, sociodemographic and clinical information were collected via structured questionnaires. Anti-VZV IgG and IgM antibodies were measured using validated Enzyme-Linked Immunosorbent Assays (ELISA). Associations with seropositivity and vaccination uptake were analyzed using multivariable logistic regression. Results: IgG seroprevalence was 79.4% (95% CI: 72.7–85.1), indicating prior exposure or immunization, while IgM antibodies, reflecting recent infection, were detected in 5.0% (95% CI: 2.3–9.4) of participants. Among vaccinated participants, IgG seropositivity was 63.6% (95% CI: 43.5–83.7) in the one-dose group and 89.5% (95% CI: 83.0–96.0) in the two-dose group. Completing the two-dose regimen was significantly associated with a higher IgG seropositivity (OR = 0.110, 95% CI: 3.2–52.4, p = 0.002). Parental reporting of history of varicella showed high sensitivity (99.0%) and overall accuracy (90.8%) in predicting seropositivity. Primary vaccination barriers included preference for natural infection (67%), perceived non-necessity (19%), and cost (10%). Regular pediatric follow-up strongly predicted vaccination (OR = 15.239, p < 0.001), whereas low parental awareness was associated with decreased vaccine uptake (OR = 0.027, p = 0.015). Conclusions: Suboptimal VZV vaccination coverage and persistent susceptibility underscore the need to integrate varicella vaccination into Lebanon’s national immunization schedule. Targeted educational efforts and enhanced pediatric healthcare engagement are critical to increasing vaccine uptake and reducing disease burden. Full article

(This article belongs to the Special Issue Bacterial and Viral Infections: Current Challenges and Vaccine Innovations)

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8 pages, 613 KB

Open AccessCommunication

Wild Mammals as Sentinels for West Nile Virus Circulation: Evidence from Serbia

by Ljubiša Veljović, Milan Paunović, Dimitrije Glišić, Sofija Šolaja, Zorana Zurovac Sapundžić, Jelena Maletić, Bojan Milovanović and Vesna Milićević

Pathogens 2025, 14(11), 1167; https://doi.org/10.3390/pathogens14111167 (registering DOI) - 15 Nov 2025

Abstract

West Nile fever is a mosquito-borne zoonotic disease caused by West Nile virus (WNV), maintained in an enzootic cycle between avian hosts and Culex mosquitoes. While birds are the principal reservoirs, WNV also infects a wide range of mammals, including humans, horses, and [...] Read more.

West Nile fever is a mosquito-borne zoonotic disease caused by West Nile virus (WNV), maintained in an enzootic cycle between avian hosts and Culex mosquitoes. While birds are the principal reservoirs, WNV also infects a wide range of mammals, including humans, horses, and wildlife species. In this study, we assessed WNV seroprevalence in wild ungulates, wild boars, golden jackals, and the invasive rodent nutria in Serbia. A total of 522 serum samples from wild animals were tested. Antibodies against WNV were detected across all tested species, with seroprevalence rates of 37% in wild boars, 11.9% in nutrias, 32.4% in golden jackals, 50.6% in red deer, and 9.1% in roe deer. Detection of antibodies in both adults and juveniles provides evidence of recent transmission during the study period. These findings confirm widespread circulation of WNV in Serbian wildlife and suggest that wild ungulates, carnivores, and invasive rodents may serve as useful sentinel species for monitoring WNV prevalence and geographic spread in natural ecosystems. Full article

(This article belongs to the Special Issue Epidemiology of Infectious Diseases in Wild Animals)

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26 pages, 2251 KB

Open AccessArticle

Viral Coinfections Potentially Associated with Feline Chronic Gingivostomatitis in Cats with Feline Infectious Peritonitis

by Jennifer Wenk, Marina L. Meli, Solène M. Meunier, Sandra Felten, Celia C. de Witt Curtius, Aline Crespo Bouzon, Ilaria Cerchiaro, Benita Pineroli, Anja Kipar, Stefan Unterer, Katharina Zwicklbauer, Katrin Hartmann, Regina Hofmann-Lehmann and Andrea M. Spiri

Viruses 2025, 17(11), 1505; https://doi.org/10.3390/v17111505 (registering DOI) - 15 Nov 2025

Abstract

Feline infectious peritonitis (FIP) is a fatal but now treatable disease in cats caused by feline coronavirus (FCoV). This study prospectively investigated viral coinfections in 100 cats diagnosed with FIP and subsequently treated with oral GS-441524 (Bova UK) and their influence on outcome, [...] Read more.

Feline infectious peritonitis (FIP) is a fatal but now treatable disease in cats caused by feline coronavirus (FCoV). This study prospectively investigated viral coinfections in 100 cats diagnosed with FIP and subsequently treated with oral GS-441524 (Bova UK) and their influence on outcome, focusing on viruses potentially associated with feline chronic gingivostomatitis (FCGS). Cats were tested for feline leukemia virus (FeLV), feline immunodeficiency virus (FIV), feline calicivirus (FCV), feline herpesvirus (FHV), feline foamy virus (FFV), and feline gammaherpesvirus (FcaGHV1). Coinfections were identified at the following frequencies: FCV (27), FFV (22), FHV (6), FIV (4), FcaGHV1 (2), and FeLV (2, both progressive infections). FFV infection was significantly associated with FIV (p_F = 0.0021) and FHV (p_F = 0.0226) infection. FCGS was present in 25/97 cats with FCV infection being associated with FCGS (pF = 0.0032); no significant associa-tions were found for the other viruses and FCGS. The 42-day oral GS-441524 treatment’s success rate was 94% (five cats died, one relapsed). Coinfections did not significantly influence disease severity or treatment outcome, although the low number of cases for some pathogens warrants further investigation. However, advanced age was associated with treatment failure, potentially due to delayed diagnosis as FIP is considered to be less common in older individuals, or to age-related changes in immune function. In summary, viral coinfections, particularly with FCV, were common and should be considered in the clinical and hygienic management of cats with FIP. Full article

(This article belongs to the Section Animal Viruses)

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12 pages, 295 KB

Open AccessArticle

Environmental Stressors, Anemia, and Depressive Symptoms in Pregnancy: Unpacking the Combined Risks

by Ruth A. Pobee, Rebecca K. Campbell, Prathiba Balakumar, Yongchao Huang, Beatriz Peñalver Bernabé and Mary Dawn Koenig

Int. J. Environ. Res. Public Health 2025, 22(11), 1727; https://doi.org/10.3390/ijerph22111727 (registering DOI) - 15 Nov 2025

Abstract

Chronic exposure to structural violence and environmental hazards may disrupt stress regulation, trigger inflammation, and impair iron metabolism in women. Iron deficiency has been associated with depression, but the combined impact of environmental stressors and anemia on maternal mental health remains understudied. We [...] Read more.

Chronic exposure to structural violence and environmental hazards may disrupt stress regulation, trigger inflammation, and impair iron metabolism in women. Iron deficiency has been associated with depression, but the combined impact of environmental stressors and anemia on maternal mental health remains understudied. We analyzed associations between 28 neighborhood-level environmental stressors, hemoglobin levels, and depressive symptoms (measured by the Patient Health Questionnaire-9) during early pregnancy, using retrospective data from 1964 pregnant patients (2015–2019) at an urban health center in Chicago. Demographic and residential data were linked to environmental indicators from the Chicago Health Atlas. Factor analysis reduced the environmental variables, and multivariable regression models examined associations with PHQ-9 scores at first pregnancy encounter. Participants were predominantly non-Hispanic Black (56%) and Hispanic (27%), with 13% anemic and 16% screening positive for depressive symptoms. Poverty, non-Hispanic Black race, single status, public or no insurance, and unemployment were associated with higher depressive symptoms. Among anemic individuals, neighborhood crime was significantly associated with depressive symptoms, while hemoglobin levels and gestational age were not. These findings highlight how environmental and social inequities contribute to maternal mental health disparities and support the need for integrated, equity-focused prenatal care interventions. Full article

26 pages, 2157 KB

Open AccessArticle

Resident Satisfaction-Based Evaluation Framework and Policy Optimization for Small-Town Infrastructure: Evidence from Wuhan, China

by Zihang Zhou, Xiang Duan and Yang Tan

Sustainability 2025, 17(22), 10223; https://doi.org/10.3390/su172210223 (registering DOI) - 15 Nov 2025

Abstract

This study evaluates resident satisfaction with small-town infrastructure and generates a policy-ready ranking of improvement priorities using a modified importance–performance analysis (IPA) that infers indicator importance statistically rather than from self-reported scores. We surveyed small towns in the new districts of Wuhan, China, [...] Read more.

This study evaluates resident satisfaction with small-town infrastructure and generates a policy-ready ranking of improvement priorities using a modified importance–performance analysis (IPA) that infers indicator importance statistically rather than from self-reported scores. We surveyed small towns in the new districts of Wuhan, China, and developed a resident satisfaction-based evaluation framework spanning road and transport, basic living facilities, public services, public activity space, and townscape and character. We assessed reliability in SPSS, estimated implicit importance via partial correlations with overall satisfaction, and mapped indicators into quadrants to set priorities. Results indicate that overall performance is perceived as generally good, yet road and transport and townscape and character consistently emerge as high importance/low satisfaction domains, and there was notable variation across towns. The framework offers a replicable, user-centered diagnostic that turns resident feedback into a ranked set of priority indicators to guide targeted investment and operations, with transferability to comparable regions. Full article

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11 pages, 232 KB

Open AccessArticle

The Relationship Between Experiencing Neighborhood Violence and Mental Health Outcomes Among High School Students in the United States, YRBS 2023

by Krystina R. Hart, Monique K. Swaby, Austine Oniya, Ebele Okoye, Nwanne Onumah, Diamond Bowens and Elizabeth Jones

Psychol. Int. 2025, 7(4), 93; https://doi.org/10.3390/psycholint7040093 (registering DOI) - 15 Nov 2025

Abstract

Background: Mental health conditions are a growing public health concern among U.S. adolescents, particularly high school students. Emerging data show a strong link between exposure to neighborhood violence and increased risk of poor mental health outcomes, such as depression, anxiety, and persistent sadness. [...] Read more.

Background: Mental health conditions are a growing public health concern among U.S. adolescents, particularly high school students. Emerging data show a strong link between exposure to neighborhood violence and increased risk of poor mental health outcomes, such as depression, anxiety, and persistent sadness. Objective: This study examined the relationship between neighborhood violence exposure and mental health outcomes among high school students. Method: This is a cross-sectional study using the 2023 Youth Risk Behavior Survey. The sample included 19,910 students in grades 9–12 across gender and race. Mental health status and exposure to neighborhood violence were analyzed using chi-square tests and logistic regression models. Results: Students exposed to neighborhood violence had significantly higher odds of reporting poor mental health outcomes (AOR = 1.789, 95% CI: 1.573–2.035, p < 0.001) than the unexposed. Additionally, female, Hispanic/Latino, and multiracial students reported higher rates of mental health disorders than the male students. Conclusions: Neighborhood violence exposure was significantly associated with poor mental health outcomes among high school students. These findings signify the need for targeted interventions to support affected students and reduce neighborhood violence exposure, particularly in marginalized communities. The findings will inform public health professionals, educators, and policymakers to make targeted school-based mental health interventions and community-centered policies addressing neighborhood safety and adolescent mental health. Full article

(This article belongs to the Section Neuropsychology, Clinical Psychology, and Mental Health)

16 pages, 3531 KB

Open AccessArticle

Research on Reliability of Vehicle Line Detection and Lane Keeping Systems

by Vytenis Surblys, Vidas Žuraulis and Tadas Tinginys

Sustainability 2025, 17(22), 10222; https://doi.org/10.3390/su172210222 (registering DOI) - 15 Nov 2025

Abstract

This research focuses on vehicle Advanced Driver Assistance Systems (ADAS), with particular emphasis on Lane Keeping Assist (LKA) systems which is designed to help drivers keep a vehicle centered within its lane and reduce the risk of unintentional lane departures. These kinds of [...] Read more.

This research focuses on vehicle Advanced Driver Assistance Systems (ADAS), with particular emphasis on Lane Keeping Assist (LKA) systems which is designed to help drivers keep a vehicle centered within its lane and reduce the risk of unintentional lane departures. These kinds of systems detect lane boundaries using computer vision algorithms applied to video data captured by a forward-facing camera and interpret this visual information to provide corrective steering inputs or driver alerts. The research investigates the performance, reliability, sustainability, and limitations of LKA systems under adverse road and environmental conditions, such as wet pavement and in the presence of degraded, partially visible, or missing horizontal road markings. Improving the reliability of lane detection and keeping systems enhances road safety, reducing traffic accidents caused by lane departures, which directly supports social sustainability. For the theoretical test, a modified road model using MATLAB software was used to simulate poor road markings and to investigate possible test outcomes. A series of field tests were conducted on multiple passenger vehicles equipped with LKA technologies to evaluate their response in real-world scenarios. The results show that it is very important to ensure high quality horizontal road markings as specified in UNECE Regulation No. 130, as lane keeping aids are not uniformly effective. Furthermore, the study highlights the need to develop more robust line detection algorithms capable of adapting to diverse road and weather conditions, thereby enhancing overall driving safety and system reliability. LKA system research supports sustainable mobility strategies promoted by international organizations—aiming to transition to safer, smarter, and less polluting transportation systems. Full article

(This article belongs to the Special Issue Intelligent Transportation Systems Applications for Sustainability and Safety)

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20 pages, 6600 KB

Open AccessArticle

Analysis of the Spatio-Temporal Evolution Characteristics and Influencing Factors of Extreme Climate Events in Jilin Province from 1970 to 2020

by Siwen Zhang, Zhenyu Zhang and Jiafu Liu

Sustainability 2025, 17(22), 10224; https://doi.org/10.3390/su172210224 (registering DOI) - 15 Nov 2025

Abstract

Under global warming, the rising frequency and intensity of extreme climate events pose challenges to disaster prevention and sustainable development. Based on daily meteorological observations from 1970 to 2020 in Jilin Province, this study analyzes the spatiotemporal evolution and driving mechanisms of extreme [...] Read more.

Under global warming, the rising frequency and intensity of extreme climate events pose challenges to disaster prevention and sustainable development. Based on daily meteorological observations from 1970 to 2020 in Jilin Province, this study analyzes the spatiotemporal evolution and driving mechanisms of extreme temperature and precipitation events. Linear trend analysis and the Mann–Kendall test were employed to examine temporal trends and abrupt change years in extreme temperature and precipitation indices. Wavelet analysis was used to identify dominant periodicities and multi-scale variability. Empirical Orthogonal Function Analysis (EOF) revealed the spatial distribution characteristics of variability in extreme precipitation and temperature across Jilin Province, identifying high-incidence zones for extreme temperature and precipitation events. Additionally, Pearson correlation analysis was to investigate the correlation patterns between extreme climate indices in Jilin Province and geographical environmental factors alongside atmospheric circulation indicators. Results show that: (1) Warm-related temperature indices display significant upward trends, while cold-related indices generally decline, with abrupt changes mainly occurring in the 1980s–1990s and dominant periodicities of 3–5 years. Precipitation indices, though variable, show general increases with 3–4year cycles. (2) Spatially, most indices follow an east–high to west–low gradient. Temperature indices exhibit spatial coherence, while precipitation indices vary, especially between the northwest and central-southern regions. (3) The Arctic Oscillation (AO) exhibits a significant negative correlation with the extreme cold index, with correlation coefficients ranging from −0.31 to −0.46. It shows a positive correlation with the extreme warm index, with correlation coefficients between 0.16 and 0.18, confirming its regulatory role in cold air activity over Northeast China, particularly elevation and latitude, influence the spatial distribution of precipitation. These findings enhance understanding of extreme climate behaviors in Northeast China and inform regional risk management strategies. Full article

(This article belongs to the Section Air, Climate Change and Sustainability)

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