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35 pages, 6224 KB  
Article
An AIoT Product Development Process with Integrated Sustainability and Universal Design
by Meng-Dar Shieh, Hsu-Chan Hsiao, Jui-Feng Chang, Yu-Ting Hsiao and Yuan-Jyun Jhou
Sustainability 2025, 17(19), 8874; https://doi.org/10.3390/su17198874 (registering DOI) - 4 Oct 2025
Abstract
The rapid development of contemporary artificial intelligence and Internet of Things (IoT) technologies has given rise to the emerging paradigm of the AIoT (Artificial Intelligence of Things), which is profoundly impacting human life and driving the digital transformation of industries and society. The [...] Read more.
The rapid development of contemporary artificial intelligence and Internet of Things (IoT) technologies has given rise to the emerging paradigm of the AIoT (Artificial Intelligence of Things), which is profoundly impacting human life and driving the digital transformation of industries and society. The AIoT not only enhances product functionality and convenience but also accelerates the achievement of the United Nations Sustainable Development Goals (SDGs). However, the widespread adoption of these technologies still poses challenges related to social inclusivity, particularly regarding insufficient accessibility for elderly users, which may exacerbate the digital divide and social inequality, contradicting SDG 10 (reducing inequality). This study integrates AIoT product development processes based on sustainability and universal design principles using methods such as Quality Function Deployment, the Analytic Hierarchy Process, the Scenario Method, the Entropy Weight Method, and Fuzzy Comprehensive Evaluation. The features of this process include ease of operation and high flexibility, making it suitable for cross-departmental product development while prioritizing the needs of diverse age groups throughout the development process. The research findings indicate that the AIoT product concepts proposed can meet the needs of diverse users, contributing to the realization of age-friendly products. This study provides a reference point for future AIoT product development, promoting the inclusive and sustainable development of smart technology. Full article
(This article belongs to the Section Sustainable Products and Services)
22 pages, 1156 KB  
Article
Toward 2030: Inequities in Higher Education Access in Southeast Asia
by Lin Wai Phyo and Sonia Ilie
Soc. Sci. 2025, 14(10), 592; https://doi.org/10.3390/socsci14100592 (registering DOI) - 4 Oct 2025
Abstract
The Sustainable Development Goals have galvanized efforts to improve access to higher education globally. While higher education has expanded over the last decade, access inequities endure, with economic deprivation, gender, and other dimensions of marginalization shaping individual opportunities to engage with higher education. [...] Read more.
The Sustainable Development Goals have galvanized efforts to improve access to higher education globally. While higher education has expanded over the last decade, access inequities endure, with economic deprivation, gender, and other dimensions of marginalization shaping individual opportunities to engage with higher education. Regional differences have also emerged, with some higher education systems growing at a rapid pace, driven by a variety of policy initiatives. This paper explores higher education access inequities in the Southeast Asian context, where a period of rapid higher education expansion has recently given way to complex patterns of access, against diverging national directions for higher education development. Using large-scale nationally representative data from the Demographic and Health Survey (DHS) and the Multiple Indicator Cluster Survey (MICS), this paper traces patterns of inequitable higher education access in eight Southeast Asian countries over time. This paper then discusses country-specific policy initiatives, and the levers they deploy in trying to lower higher education inequities. It explores how these country-specific policy initiatives aiming at equality or equity in higher education access sit alongside periods of sector expansion and wealth-based gaps in higher education access, to conclude about potential policy shifts which may support work towards more equitable systems. Full article
12 pages, 2104 KB  
Article
Accessible Thermoelectric Characterization: Development and Validation of Two Modular Room Temperature Measurement Instruments
by František Mihok, Katarína Gáborová, Viktor Puchý and Karel Saksl
Inorganics 2025, 13(10), 333; https://doi.org/10.3390/inorganics13100333 (registering DOI) - 4 Oct 2025
Abstract
This paper describes two low-cost, modular instruments developed for rapid room-temperature characterization of mainly thermoelectrics. The first instrument measures the Seebeck coefficient across diverse sample geometries and incorporates a four-point probe configuration for simultaneous electrical conductivity measurement, including disk-shaped samples. The second instrument [...] Read more.
This paper describes two low-cost, modular instruments developed for rapid room-temperature characterization of mainly thermoelectrics. The first instrument measures the Seebeck coefficient across diverse sample geometries and incorporates a four-point probe configuration for simultaneous electrical conductivity measurement, including disk-shaped samples. The second instrument implements the Van der Pauw method, enabling detailed investigation of charge carrier behavior within materials. Both devices prioritize accessibility, constructed primarily from 3D-printed components, basic hardware, and readily available instrumentation, ensuring ease of reproduction and modification. A unique calibration protocol using pure elemental disks and materials with well-established properties was employed for both instruments. Validation against comparable systems confirmed reliable operation. Control and data acquisition software for both devices was developed in-house and is fully documented and does not require an experienced operator. We demonstrate the utility of these instruments by characterizing the electronic properties of polycrystalline SnSe thermoelectric materials doped with Bi, Ag, and In. The results reveal highly complex charge carrier behavior significantly influenced by both dopant type and concentration. Full article
(This article belongs to the Section Inorganic Materials)
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13 pages, 2846 KB  
Article
Whole Genome Re-Sequencing Reveals Insights into the Genetic Diversity and Fruit Flesh Color of Guava
by Jiale Huang, Xianghui Yang, Chongbin Zhao, Ze Peng and Jun Chen
Horticulturae 2025, 11(10), 1194; https://doi.org/10.3390/horticulturae11101194 - 3 Oct 2025
Abstract
Guava (Psidium guajava L.), a perennial species native to tropical regions of the Americas, holds significant economic value and plays an important role in the global fruit industry. Although several reference genomes have been published, population-level genomic studies remain limited, hindering genetic [...] Read more.
Guava (Psidium guajava L.), a perennial species native to tropical regions of the Americas, holds significant economic value and plays an important role in the global fruit industry. Although several reference genomes have been published, population-level genomic studies remain limited, hindering genetic improvement efforts. In this study, we conducted whole genome re-sequencing of 62 guava accessions, primarily from Southern China and Brazil. A total of 4,887,006 high-quality SNPs and 731,469 InDels were identified for population genomic analyses. Phylogenetic and population structure analyses revealed subgroupings that largely corresponded to geographic origins. The data indicated that extensive hybridization between accessions from Brazil and or within China has contributed to the development of many dominant commercial varieties. Genetic diversity analyses showed that Brazilian accessions exhibited higher nucleotide diversity and more rapid linkage disequilibrium decay than those from China. Environmental factors and artificial selection likely imposed selective pressures that shaped guava’s adaptability and agronomic traits. A preliminary genome-wide association study (GWAS) identified PgMYB4 as a candidate gene potentially associated with fruit flesh color. These findings provide novel insights into the genetic diversity, population history, and domestication of guava, and lay a valuable foundation for future breeding and improvement strategies. Full article
(This article belongs to the Section Genetics, Genomics, Breeding, and Biotechnology (G2B2))
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13 pages, 4164 KB  
Article
FRIDA: A Four-Factor Adaptive Screening Tool for Demoralization, Anxiety, Irritability, and Depression in Hospital Patients
by Martino Belvederi Murri, Angela Muscettola, Michele Specchia, Chiara Montemitro, Luigi Zerbinati, Marco Cruciata, Tommaso Toffanin, Guido Sciavicco, Rosangela Caruso, Federica Sancassiani, Mauro Giovanni Carta, Luigi Grassi and Maria Giulia Nanni
J. Clin. Med. 2025, 14(19), 6992; https://doi.org/10.3390/jcm14196992 - 2 Oct 2025
Abstract
Background: Demoralization, anxiety, irritability, and depression are common among hospital patients and are associated with poorer outcomes and greater healthcare burden. Early identification is essential, but simultaneous screening across multiple domains is often impractical with questionnaires. Computerized Adaptive Testing (CAT) offers a [...] Read more.
Background: Demoralization, anxiety, irritability, and depression are common among hospital patients and are associated with poorer outcomes and greater healthcare burden. Early identification is essential, but simultaneous screening across multiple domains is often impractical with questionnaires. Computerized Adaptive Testing (CAT) offers a solution by tailoring item administration, reducing test length while preserving measurement precision. The aim of this study was to develop and validate FRIDA (Four-factor Rapid Interactive Diagnostic Assessment), a freely accessible, web-based CAT for rapid multidimensional screening of psychopathology in hospital patients. Methods: We analysed data from 472 medically ill in-patients at a University Hospital. Item calibration was performed using a four-factor graded response model (demoralization, anxiety, irritability, depression) in the mirt package. CAT simulations were run with 1000 virtual respondents to optimize item selection, exposure control, and stopping rules. The best configuration was applied to the real dataset. Criterion validity for demoralization was evaluated against the Diagnostic Criteria for Psychosomatic Research (DCPR). Results: The four-factor model showed good fit (CFI = 0.947, RMSEA = 0.080). Factor correlations were moderate to high, with the strongest overlap between demoralization and depression (r = 0.93). In simulations, the CAT required, on average, 7.8 items and recovered trait estimates with high accuracy (r = 0.94–0.97). In real patients, mean test length was 11 items, with accuracy of r = 0.95 across domains. FRIDA demonstrated good criterion validity for demoralization (AUC = 0.816; sensitivity 80%, specificity 67.5%). Conclusions: FRIDA is the first freely available, multidimensional CAT for rapid screening of psychopathology in hospital patients. It offers a scalable, efficient, and precise tool for integrating mental health assessment into routine hospital care. Full article
(This article belongs to the Section Mental Health)
18 pages, 788 KB  
Article
Cryptocurrencies as a Tool for Money Laundering: Risk Assessment and Perception of Threats Based on Empirical Research
by Marta Spyra, Rafał Balina, Marta Idasz-Balina, Adam Zając and Filip Różyński
Risks 2025, 13(10), 189; https://doi.org/10.3390/risks13100189 - 2 Oct 2025
Abstract
As the global economy undergoes rapid digital transformation, cryptocurrencies have emerged as a prominent alternative class of financial assets. Their decentralized nature, pseudonymity, and lack of centralized oversight have attracted considerable interest among investors while simultaneously raising significant concerns among regulators and compliance [...] Read more.
As the global economy undergoes rapid digital transformation, cryptocurrencies have emerged as a prominent alternative class of financial assets. Their decentralized nature, pseudonymity, and lack of centralized oversight have attracted considerable interest among investors while simultaneously raising significant concerns among regulators and compliance professionals. While cryptocurrencies offer benefits such as enhanced accessibility and transactional privacy, they also pose notable risks, particularly their potential misuse in financial crimes, including money laundering. This study explores the perceived risks associated with cryptocurrencies in the context of money laundering, drawing on insights from a survey conducted among 50 financial sector professionals. A quantitative research design was employed, using a structured online questionnaire to assess participants’ awareness, investment behavior, and perceptions of the role of cryptocurrencies in illicit finance and financial system security. The results reveal a complex perspective: while 70% of respondents acknowledged the potential for cryptocurrencies to facilitate money laundering, 60% expressed support for their wider adoption. Notably, statistically significant correlations emerged between active investment in cryptocurrencies and the belief that they could enhance financial market security and reduce laundering risks. However, self-reported knowledge levels and general awareness did not show a significant relationship with perceived risk. The findings underscore the importance of a balanced approach to regulation, one that fosters innovation while mitigating illicit finance risks. The study recommends increased investment in user education, the development of blockchain analytics, the adoption of global regulatory standards and enhanced international cooperation to ensure the responsible evolution of the cryptocurrency ecosystem. Full article
21 pages, 2264 KB  
Article
Thermodynamic Determinants in Antibody-Free Nucleic Acid Lateral Flow Assays (AF-NALFA): Lessons from Molecular Detection of Listeria monocytogenes, Mycobacterium leprae and Leishmania amazonensis
by Leonardo Lopes-Luz, Paula Correa Neddermeyer, Gabryele Cardoso Sampaio, Luana Michele Alves, Matheus Bernardes Torres Fogaça, Djairo Pastor Saavedra, Mariane Martins de Araújo Stefani and Samira Bührer-Sékula
Biomolecules 2025, 15(10), 1404; https://doi.org/10.3390/biom15101404 - 2 Oct 2025
Abstract
Antibody-free nucleic acid lateral flow assays (AF-NALFA) are an established approach for rapid detection of amplified pathogens DNA but can yield inconsistent signals across targets. Since AF-NALFA depends on dual hybridization of probes to single-stranded amplicons (ssDNA), site-specific thermodynamic (Gibbs free energy-ΔG) at [...] Read more.
Antibody-free nucleic acid lateral flow assays (AF-NALFA) are an established approach for rapid detection of amplified pathogens DNA but can yield inconsistent signals across targets. Since AF-NALFA depends on dual hybridization of probes to single-stranded amplicons (ssDNA), site-specific thermodynamic (Gibbs free energy-ΔG) at probe-binding regions may be crucial for performance. This study investigated how site-specific-ΔG and sequence complementarity at probe-binding regions determine Test-line signal generation, comparing native and synthetic amplicons and assessing the effects of local secondary structures and mismatches. Asymmetric PCR-generated ssDNA amplicons of Listeria monocytogenes, Mycobacterium leprae, and Leishmania amazonensis were analyzed in silico and tested in AF-NALFA prototypes with gold-labeled thiol probes and biotinylated capture probes. T-line signals were photographed, quantified (ImageJ version 1.4k), and statistically correlated with site-specific-ΔG. While native ssDNA from M. leprae and L. amazonensis failed to produce AF-NALFA T-line signals, L. monocytogenes yielded strong detection. Site-specific-ΔG below −10 kcal/mol correlated with reduced hybridization. Synthetic oligos preserved signals despite structural constraints, whereas ~3–4 mismatches, especially at capture probe regions, markedly impaired T-line intensity. The performance of AF-NALFA depends on the synergism between thermodynamic accessibility, site-specific-ΔG-induced site constraints, and sequence complementarity. Because genomic context affects hybridization, target-specific thermodynamic in silico evaluation is necessary for reliable pathogen DNA detection. Full article
(This article belongs to the Section Molecular Biology)
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22 pages, 558 KB  
Review
Smart Healthcare at Home: A Review of AI-Enabled Wearables and Diagnostics Through the Lens of the Pi-CON Methodology
by Steffen Baumann, Richard T. Stone and Esraa Abdelall
Sensors 2025, 25(19), 6067; https://doi.org/10.3390/s25196067 - 2 Oct 2025
Abstract
The rapid growth of AI-enabled medical wearables and home-based diagnostic devices has opened new pathways for preventive care, chronic disease management and user-driven health insights. Despite significant technological progress, many solutions face adoption hurdles, often due to usability challenges, episodic measurements and poor [...] Read more.
The rapid growth of AI-enabled medical wearables and home-based diagnostic devices has opened new pathways for preventive care, chronic disease management and user-driven health insights. Despite significant technological progress, many solutions face adoption hurdles, often due to usability challenges, episodic measurements and poor alignment with daily life. This review surveys the current landscape of at-home healthcare technologies, including wearable vital sign monitors, digital diagnostics and body composition assessment tools. We synthesize insights from the existing literature for this narrative review, highlighting strengths and limitations in sensing accuracy, user experience and integration into daily health routines. Special attention is given to the role of AI in enabling real-time insights, adaptive feedback and predictive monitoring across these devices. To examine persistent adoption challenges from a user-centered perspective, we reflect on the Pi-CON methodology, a conceptual framework previously introduced to stimulate discussion around passive, non-contact, and continuous data acquisition. While Pi-CON is highlighted as a representative methodology, recent external studies in multimodal sensing, RFID-based monitoring, and wearable–ambient integration confirm the broader feasibility of unobtrusive, passive, and continuous health monitoring in real-world environments. We conclude with strategic recommendations to guide the development of more accessible, intelligent and user-aligned smart healthcare solutions. Full article
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20 pages, 448 KB  
Article
Cultural Empathy in AI-Supported Collaborative Learning: Advancing Inclusive Digital Learning in Higher Education
by Idit Finkelstein and Shira Soffer-Vital
Educ. Sci. 2025, 15(10), 1305; https://doi.org/10.3390/educsci15101305 - 2 Oct 2025
Abstract
The rapid advancement of Artificial Intelligence (AI) technologies is driving a profound transformation in higher education, shifting traditional learning toward digital, remote, and AI-mediated environments. This shift—accelerated by the COVID-19 pandemic—has made computer-supported collaborative learning (CSCL) a central pedagogical model for engaging students [...] Read more.
The rapid advancement of Artificial Intelligence (AI) technologies is driving a profound transformation in higher education, shifting traditional learning toward digital, remote, and AI-mediated environments. This shift—accelerated by the COVID-19 pandemic—has made computer-supported collaborative learning (CSCL) a central pedagogical model for engaging students in virtual, interactive, and peer-based learning. However, while these environments enhance access and flexibility, they also introduce new emotional, social, and intercultural challenges that students must navigate without the benefit of face-to-face interaction. In this evolving context, Social and Emotional Learning (SEL) has become increasingly essential—not only for supporting student well-being but also for fostering the self-efficacy, adaptability, and interpersonal competencies required for success in AI-enhanced academic settings. Despite its importance, the role of SEL in higher education—particularly within CSCL frameworks—remains underexplored. This study investigates how SEL, and specifically cultural empathy, influences students’ learning experiences in multicultural CSCL environments. Grounded in Bandura’s social cognitive theory and Allport’s Contact Theory, this study builds on theoretical insights that position emotional stability, social competence, and cultural empathy as critical SEL dimensions for promoting equity, collaboration, and effective participation in diverse, AI-supported learning settings. A quantitative study was conducted with 258 bachelor’s and master’s students on a multicultural campus. Using the Multicultural Social and Emotional Learning (SEL CASTLE) model, the research examined the relationships among SEL competencies and self-efficacy in CSCL environments. Findings reveal that cultural empathy plays a mediating role between emotional and social competencies and academic self-efficacy, emphasizing its importance in enhancing collaborative learning experiences within AI-driven environments. The results highlight the urgent need to cultivate cultural empathy to support inclusive, effective digital learning across diverse educational settings. This study contributes to the fields of intercultural education and digital pedagogy by presenting the SEL CASTLE model and demonstrating the significance of integrating SEL into AI-supported collaborative learning. Strengthening these competencies is essential for preparing students to thrive in a globally interconnected academic and professional landscape. Full article
(This article belongs to the Special Issue Higher Education Development and Technological Innovation)
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30 pages, 1702 KB  
Review
Adulteration of Sports Supplements with Anabolic Steroids—From Innocent Athlete to Vicious Cheater
by Daniela Puscasiu, Corina Flangea, Daliborca Vlad, Roxana Popescu, Cristian Sebastian Vlad, Sorin Barac, Andreea Luciana Rata, Cristina Marina, Ionut Marcel Cobec and Sorina Maria Denisa Laitin
Nutrients 2025, 17(19), 3146; https://doi.org/10.3390/nu17193146 - 1 Oct 2025
Abstract
Some protein food supplements intended for athletes may be adulterated with pharmacologically active substances, including anabolic steroids and prohormones. The addition of these substances is aimed at enabling manufacturers to achieve rapid sales growth by promising quick increases in strength and muscle mass. [...] Read more.
Some protein food supplements intended for athletes may be adulterated with pharmacologically active substances, including anabolic steroids and prohormones. The addition of these substances is aimed at enabling manufacturers to achieve rapid sales growth by promising quick increases in strength and muscle mass. However, the consumption of these products will lead to a positive result in a routine anti-doping test, along with all of the consequences that will directly affect an athlete’s career and reputation. At the same time, the illicit use of anabolic steroids continues to evolve across numerous sport disciplines. Moreover, vicious cheaters try to cover up their illegal actions by using various pharmacological agents to mask detection in anti-doping tests. This narrative review focuses on two situations—the innocent athlete and the vicious cheater. The athlete involved in inadvertent doping will suffer the consequences of doping, making close collaboration with medical staff extremely important. The analytic strategies described here address anabolic steroid doping detection and cheating using masking agents. This approach, based on biochemical changes, examines how these substances interfere with the testosterone pathway, from synthesis to elimination. Using masking agents alters the steroid profile, and the modifications produced by each agent are the subject of a detailed presentation. For most honest athletes, these findings support the initiation, development, and refinement of strategies for identifying food supplements with added illegal substances. Every athlete must have access to these approaches in order to avoid becoming vulnerable to sports fraud. Full article
(This article belongs to the Special Issue Nutrition and Supplements for Athletic Training and Racing)
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15 pages, 2453 KB  
Article
Assessing REM Sleep as a Biomarker for Depression Using Consumer Wearables
by Roland Stretea, Zaki Milhem, Vadim Fîntînari, Cătălina Angela Crișan, Alexandru Stan, Dumitru Petreuș and Ioana Valentina Micluția
Diagnostics 2025, 15(19), 2498; https://doi.org/10.3390/diagnostics15192498 - 1 Oct 2025
Abstract
Background: Rapid-eye-movement (REM) sleep disinhibition—shorter REM latency and a larger nightly REM fraction—is a well-described laboratory correlate of major depression. Whether the same pattern can be captured efficiently with consumer wearables in everyday settings remains unclear. We therefore quantified REM latency and proportion [...] Read more.
Background: Rapid-eye-movement (REM) sleep disinhibition—shorter REM latency and a larger nightly REM fraction—is a well-described laboratory correlate of major depression. Whether the same pattern can be captured efficiently with consumer wearables in everyday settings remains unclear. We therefore quantified REM latency and proportion of REM sleep out of total sleep duration (labeled “REM sleep coefficient”) from Apple Watch recordings and examined their association with depressive symptoms. Methods: 191 adults wore an Apple Watch for 15 consecutive nights while a custom iOS app streamed raw accelerometry and heart-rate data. Sleep stages were scored with a neural-network model previously validated against polysomnography. REM latency and REM sleep coefficient were averaged per participant. Depressive severity was assessed twice with the Beck Depression Inventory and averaged. Descriptive statistics, normality tests, Spearman correlations, and ordinary-least-squares regressions were performed. Results: Mean ± SD values were BDI 13.52 ± 6.79, REM sleep coefficient 24.05 ± 6.52, and REM latency 103.63 ± 15.44 min. REM latency correlated negatively with BDI (Spearman ρ = −0.673, p < 0.001), whereas REM sleep coefficient correlated positively (ρ = 0.678, p < 0.001). Combined in a bivariate model, the two REM metrics explained 62% of variance in depressive severity. Conclusions: Wearable-derived REM latency and REM proportion jointly capture a large share of depressive-symptom variability, indicating their potential utility as accessible digital biomarkers. Larger longitudinal and interventional studies are needed to determine whether modifying REM architecture can alter the course of depression. Full article
(This article belongs to the Special Issue A New Era in Diagnosis: From Biomarkers to Artificial Intelligence)
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24 pages, 324 KB  
Article
Gender Role Reversal in Gig Economy Households: A Sociological Insight from Southeast Asia with Evidence from Pakistan
by Umar Daraz, Štefan Bojnec and Younas Khan
Societies 2025, 15(10), 276; https://doi.org/10.3390/soc15100276 - 1 Oct 2025
Abstract
The rapid growth of the gig economy and digital platforms is challenging traditional gender roles, particularly in developing countries where structural inequalities continue to shape labor and household dynamics. Despite growing global interest in gender equity and digital inclusion, limited research has examined [...] Read more.
The rapid growth of the gig economy and digital platforms is challenging traditional gender roles, particularly in developing countries where structural inequalities continue to shape labor and household dynamics. Despite growing global interest in gender equity and digital inclusion, limited research has examined how gig work, digital access, and women’s income contributions interact to influence household gender dynamics within culturally conservative contexts. This study aimed to investigate the multidimensional impacts of women’s participation in gig work on time use redistribution, intra-household decision making, gender ideology, and role reversal within households in Pakistan. Using a cross-sectional survey design, data were collected from a representative sample of married couples engaged in the gig economy across urban and peri-urban areas of Pakistan. A quantitative analysis was conducted employing a combination of an analysis of variance, ordinal logistic regression, hierarchical multiple regression, and structural equation modeling to evaluate the direct and indirect relationships between constructs. The findings revealed that women’s gig work participation significantly predicted enhanced digital access, greater income contributions, and increased intra-household decision-making power. These, in turn, contributed to a measurable shift in gender ideology toward equality norms and a partial reversal of traditional gender roles, particularly in household labor division. The study concludes that the intersection of economic participation and digital empowerment serves as a catalyst for progressive gender restructuring within households. Policy implications include the need for gender-responsive labor policies, investment in digital infrastructure, and targeted interventions to support empowering women in non-traditional work roles. Full article
27 pages, 1191 KB  
Review
Small RNA and Epigenetic Control of Plant Immunity
by Sopan Ganpatrao Wagh, Akshay Milind Patil, Ghanshyam Bhaurao Patil, Sumeet Prabhakar Mankar, Khushboo Rastogi and Masamichi Nishiguchi
DNA 2025, 5(4), 47; https://doi.org/10.3390/dna5040047 - 1 Oct 2025
Abstract
Plants have evolved a complex, multilayered immune system that integrates molecular recognition, signaling pathways, epigenetic regulation, and small RNA-mediated control. Recent studies have shown that DNA-level regulatory mechanisms, such as RNA-directed DNA methylation (RdDM), histone modifications, and chromatin remodeling, are critical for modulating [...] Read more.
Plants have evolved a complex, multilayered immune system that integrates molecular recognition, signaling pathways, epigenetic regulation, and small RNA-mediated control. Recent studies have shown that DNA-level regulatory mechanisms, such as RNA-directed DNA methylation (RdDM), histone modifications, and chromatin remodeling, are critical for modulating immune gene expression, allowing for rapid and accurate pathogen-defense responses. The epigenetic landscape not only maintains immunological homeostasis but also promotes stress-responsive transcription via stable chromatin modifications. These changes contribute to immunological priming, a process in which earlier exposure to pathogens or abiotic stress causes a heightened state of preparedness for future encounters. Small RNAs, including siRNAs, miRNAs, and phasiRNAs, are essential for gene silencing before and after transcription, fine-tuning immune responses, and inhibiting negative regulators. These RNA molecules interact closely with chromatin features, influencing histone acetylation/methylation (e.g., H3K4me3, H3K27me3) and guiding DNA methylation patterns. Epigenetically encoded immune memory can be stable across multiple generations, resulting in the transgenerational inheritance of stress resilience. Such memory effects have been observed in rice, tomato, maize, and Arabidopsis. This review summarizes new findings on short RNA biology, chromatin-level immunological control, and epigenetic memory in plant defense. Emerging technologies, such as ATAC-seq (Assay for Transposase-Accessible Chromatin using Sequencing), ChIP-seq (Chromatin Immunoprecipitation followed by Sequencing), bisulfite sequencing, and CRISPR/dCas9-based epigenome editing, are helping researchers comprehend these pathways. These developments hold an opportunity for establishing epigenetic breeding strategies that target the production of non-GMO, stress-resistant crops for sustainable agriculture. Full article
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15 pages, 2103 KB  
Article
Patient Diagnosis Alzheimer’s Disease with Multi-Stage Features Fusion Network and Structural MRI
by Thi My Tien Nguyen and Ngoc Thang Bui
J. Dement. Alzheimer's Dis. 2025, 2(4), 35; https://doi.org/10.3390/jdad2040035 - 1 Oct 2025
Abstract
Background: Timely intervention and effective control of Alzheimer’s disease (AD) have been shown to limit memory loss and preserve cognitive function and the ability to perform simple activities in older adults. In addition, magnetic resonance imaging (MRI) scans are one of the most [...] Read more.
Background: Timely intervention and effective control of Alzheimer’s disease (AD) have been shown to limit memory loss and preserve cognitive function and the ability to perform simple activities in older adults. In addition, magnetic resonance imaging (MRI) scans are one of the most common and effective methods for early detection of AD. With the rapid development of deep learning (DL) algorithms, AD detection based on deep learning has wide applications. Methods: In this research, we have developed an AD detection method based on three-dimensional (3D) convolutional neural networks (CNNs) for 3D MRI images, which can achieve strong accuracy when compared with traditional 3D CNN models. The proposed model has four main blocks, and the multi-layer fusion functionality of each block was used to improve the efficiency of the proposed model. The performance of the proposed model was compared with three different pre-trained 3D CNN architectures (i.e., 3D ResNet-18, 3D InceptionResNet-v2, and 3D Efficientnet-b2) in both tasks of multi-/binary-class classification of AD. Results: Our model achieved impressive classification results of 91.4% for binary-class as well as 80.6% for multi-class classification on the Open Access Series of Imaging Studies (OASIS) database. Conclusions: Such results serve to demonstrate that multi-stage feature fusion of 3D CNN is an effective solution to improve the accuracy of diagnosis of AD with 3D MRI, thus enabling earlier and more accurate diagnosis. Full article
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27 pages, 2315 KB  
Article
Study on Travel Characteristics and Satisfaction in Low-Density Areas Based on MNL and SEM Models—A Case of Lanzhou
by Minan Yang, Liyun Wang, Xin Li and Yongsheng Qian
Sustainability 2025, 17(19), 8802; https://doi.org/10.3390/su17198802 - 30 Sep 2025
Abstract
This study focuses on the challenges of resident mobility in low-density areas. Amid China’s rapid urbanization, rural landscapes and travel patterns are undergoing significant transformation. Using Lanzhou’s rural areas as a representative case study, this research employs questionnaire surveys to collect data. It [...] Read more.
This study focuses on the challenges of resident mobility in low-density areas. Amid China’s rapid urbanization, rural landscapes and travel patterns are undergoing significant transformation. Using Lanzhou’s rural areas as a representative case study, this research employs questionnaire surveys to collect data. It applies a multi-nominal logit (MNL) model to examine factors influencing travel mode choices and utilizes structural equation modeling (SEM) to assess travel satisfaction—a composite metric derived from residents’ subjective evaluations of convenience, cost, time, and comfort. Findings indicate that private cars and public transportation are the primary travel modes. The MNL model reveals that age and destination accessibility significantly influence travel choices. SEM path analysis further shows that annual household income has a direct positive effect on satisfaction, while age exerts an indirect negative influence through mediating variables. Female satisfaction levels were significantly lower than those of males. Both road density and perceived infrastructure quality significantly enhanced satisfaction, while destination accessibility may exert a slight negative indirect effect by increasing travel expectations. The study theoretically enriches research on rural travel patterns and provides practical insights into rural transportation planning and infrastructure development. Full article
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