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Recent Articles  

29 pages, 26156 KB  
Article
Multi-Dimensional Benefit Evaluation of Urban Spaces Driven by Consumer Preferences
by Xin Zhang, Yi Yu and Lei Cao
Land 2025, 14(12), 2322; https://doi.org/10.3390/land14122322 (registering DOI) - 26 Nov 2025
Abstract
Against the backdrop of efforts to improve the quality of urban spatial stock, assessments of spatial benefits driven by consumption preferences integrate subjective decision-making and objective environmental factors to provide quantitative evidence for urban planning and public investment. This study constructed a “environment-perception–behavior” [...] Read more.
Against the backdrop of efforts to improve the quality of urban spatial stock, assessments of spatial benefits driven by consumption preferences integrate subjective decision-making and objective environmental factors to provide quantitative evidence for urban planning and public investment. This study constructed a “environment-perception–behavior” analytical framework grounded in SOR (stimulus–organism–response) theory. We combined structural equation modeling with the hedonic pricing method to identify causal pathways and quantify the marginal value of spatial elements. XGBoost was employed to uncover consumption-preference thresholds, Coupling Coordination Degree (CCD) was used to identify spatial supply–demand relationships, and Social Return on Investment (SROI) was applied to evaluate multidimensional urban spatial benefits. The results showed that transportation accessibility, commercial diversity, green-space quality, and cultural ambiance significantly shaped distinct consumption preferences. Central urban areas approached supply saturation in commercial and daily consumption and exhibited diminishing marginal returns, whereas peripheral zones demonstrated greater potential for sports and cultural consumption. Based on these findings, we reveal the underlying logic of spatial benefit distribution and classify the study area into High-efficiency matching zones, transition matching zones, and potential zones. We further propose targeted optimization recommendations that can inform policy on urban spatial functional positioning and social investment and provide evaluation criteria for prioritizing interventions. Full article
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15 pages, 5414 KB  
Article
Performance Evolution of Gd2O3-Yb2O3-Y2O3-ZrO2 (GYYZO) Thermal Barrier Coatings After Thermal Cycling
by Shengcong Zeng, Shanping Gao, Zhongda Wang, Yisong Huang, Qiwei He and Chongran Jiang
Coatings 2025, 15(12), 1380; https://doi.org/10.3390/coatings15121380 (registering DOI) - 26 Nov 2025
Abstract
Ions of Gd3+ and Yb3+ have radii similar to those of Zr4+, enabling them to form limited solid solutions in the ZrO2 lattice through substitution. After solid solution formation, oxygen vacancy defects and complex defect aggregates are generated, [...] Read more.
Ions of Gd3+ and Yb3+ have radii similar to those of Zr4+, enabling them to form limited solid solutions in the ZrO2 lattice through substitution. After solid solution formation, oxygen vacancy defects and complex defect aggregates are generated, which are crucial for stabilizing the high-temperature phase structure and reducing thermal conductivity. Therefore, in this study, 8 wt% Y2O3 and 5 wt% Yb2O3 were doped with 5 wt%, 10 wt%, and 15 wt% Gd2O3, respectively, to stabilize zirconia powders. GYYZO thermal barrier coatings (TBCs) were fabricated via atmospheric plasma spraying (APS). Subsequently, the GYYZO coatings with different Gd2O3 addition amounts were subjected to continuous thermal shock cycling at 1100 °C for 10, 30, 60, 90, and 150 cycles. The results indicate that the incorporation of Gd2O3, Yb2O3, and Y2O3 leads to the formation of stable tetragonal ZrO2 phase in the GYYZO coatings. Although increasing the Gd2O3 addition amount reduces the thermal conductivity of the coatings, excessive Gd2O3 addition causes coating spallation. The GYYZO coating with 10 wt% Gd2O3 exhibits the lowest thermal conductivity of 0.59 W/(m·K). Additionally, the GYYZO coating with 10 wt% Gd2O3 can withstand thermal cycling for 150 cycles, while the one with 5 wt% Gd2O3 can endure 90 of thermal cycles. In contrast, the 8YSZ coating cracks and spalls after 60 thermal cycles. These findings demonstrate that doping ZrO2 with Gd2O3, Yb2O3, and Y2O3 can enhance the thermal cycling resistance of the coatings and effectively reduce their thermal conductivity, but excessive Gd2O3 addition will decrease the coating adhesion strength. Full article
(This article belongs to the Section Surface Characterization, Deposition and Modification)
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22 pages, 425 KB  
Article
Predictors of Digital Fraud: Evidence from Thailand
by Tanpat Kraiwanit, Pongsakorn Limna, Rattaphong Sonsuphap and Veraphong Chutipat
J. Risk Financial Manag. 2025, 18(12), 671; https://doi.org/10.3390/jrfm18120671 (registering DOI) - 26 Nov 2025
Abstract
This study examined the complex interplay of demographic characteristics, behavioral patterns, and technological factors that contribute to digital fraud victimization within the context of a developing economy, focusing specifically on Thailand. Utilizing data collected from 1200 respondents and applying binary logistic regression analysis, [...] Read more.
This study examined the complex interplay of demographic characteristics, behavioral patterns, and technological factors that contribute to digital fraud victimization within the context of a developing economy, focusing specifically on Thailand. Utilizing data collected from 1200 respondents and applying binary logistic regression analysis, the research identified key predictors of fraud exposure, including age, income, student status, use of portable devices, and social media engagement. A paradoxical finding emerged: stronger perceived digital security was associated with higher fraud risk, indicating that overconfidence in platform safeguards may unintentionally increase vulnerability. Interestingly, users’ perceptions of digital security—such as confidence in identity verification and password protocols—were positively associated with fraud victimization, indicating potential cognitive biases and overconfidence in digital environments. The findings revealed a high prevalence of fraud experiences among participants, highlighting the gap between perceived and actual digital safety. These results emphasized the urgent need for user-centered fraud prevention measures, enhanced digital literacy, and targeted public awareness campaigns. The study contributes to the broader understanding of cybersecurity challenges in emerging markets and offers policy-relevant insights for strengthening digital financial resilience. Full article
(This article belongs to the Section Risk)
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20 pages, 1908 KB  
Article
Triple-Flow Dynamic Graph Convolutional Network for Wind Power Forecasting
by Bin Li, Bo Ding, Wei Pang and Hongyin Ni
Symmetry 2025, 17(12), 2026; https://doi.org/10.3390/sym17122026 (registering DOI) - 26 Nov 2025
Abstract
Wind energy is a clean but intermittent and volatile energy source, and its large-scale integration into power systems poses great challenges to ensuring safe and stable operation and achieving scheduling optimization and effective energy planning of the power systems. Accurate wind power forecasting [...] Read more.
Wind energy is a clean but intermittent and volatile energy source, and its large-scale integration into power systems poses great challenges to ensuring safe and stable operation and achieving scheduling optimization and effective energy planning of the power systems. Accurate wind power forecasting is an effective way to mitigate the impact of wind power instability on power systems. However, wind power data are often in the form of multivariate time series. Existing wind power forecasting research often directly models the temporal and spatial characteristics of coupled wind power time-series data, ignoring the heterogeneity of time and space, thereby limiting the model’s expressive power. To address the above problems, we propose a triple-flow dynamic graph convolutional network (TFDGCN) for short-term wind power forecasting. The proposed TFDGCN is a symmetric dynamic graph neural network with three branches. It decouples and learns features of three different dimensions: within a wind power variable sequence, between sequences, and between wind turbines. The proposed TFDGCN constructs dynamic sparse graphs based on cosine similarities within variable sequences, between variable sequences, and between wind turbine nodes, and feeds them into their respective dynamic graph convolution modules. Afterwards, TFDGCN utilizes linear attention encoders which fuse local position encoding (LePE) and rotational position encoding (RoPE) to learn global dependencies within variable sequences, between sequences, and between wind turbines, and provide prediction results. Extensive experimental results on two real-world datasets demonstrate that the proposed TFDGCN outperforms other state-of-the-art methods. On the SDWPF and SD23 datasets, the proposed TFDGCN achieved mean absolute error values of 37.16 and 14.63, respectively, as well as root mean square error values of 44.84 and 17.56, respectively. Full article
(This article belongs to the Special Issue Symmetry in Deep Learning Networks and Its Applications in the Real World)
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15 pages, 303 KB  
Article
Improving Mathematics Performance Through After-School Interventions: A Gender-Based Analysis of Low-Achieving Students
by Oluwaseyi Aina Gbolade Opesemowo, Gbolagade Ramon Olosunde and Simeon Oluniyi Ariyo
Educ. Sci. 2025, 15(12), 1587; https://doi.org/10.3390/educsci15121587 (registering DOI) - 26 Nov 2025
Abstract
Despite growing global interest in improving mathematics outcomes, there has been limited empirical research in Nigeria that has rigorously evaluated the impact of structured after-school intervention programs on low-achieving students, particularly through a gender-based lens. This study addresses this gap by examining the [...] Read more.
Despite growing global interest in improving mathematics outcomes, there has been limited empirical research in Nigeria that has rigorously evaluated the impact of structured after-school intervention programs on low-achieving students, particularly through a gender-based lens. This study addresses this gap by examining the effectiveness of after-school mathematics instruction on the performance of senior secondary school students in Oyo State, Nigeria. The researchers adopted a quasi-experimental pretest–posttest control group design with a 2 × 2 factorial structure. The sample consisted of 92 purposively selected low-achieving students (47 males and 45 females) from eight public, co-educational secondary schools, who were randomly assigned to experimental and control groups. Over the course of six weeks, the experimental group received structured after-school mathematics lessons that targeted foundational skills, while the control group continued with conventional classroom instruction. Data was collected using a researcher-developed Mathematics Achievement Test (MAT), which was validated by mathematics education experts and yielded a Cronbach’s alpha of 0.82. Analysis of Covariance (ANCOVA) revealed a statistically significant improvement in the mathematics achievement of students in the intervention group (F(1, 87) = 114.88, p < 0.05), with a large effect size (Partial η2 = 0.569). Although no significant interaction effect between gender and treatment was observed (F(1, 87) = 0.208, p > 0.05). This study contributes to the limited literature on gender-responsive after-school interventions in sub-Saharan African contexts. Findings support the implementation of targeted support programs to enhance mathematics outcomes for struggling learners, regardless of gender. Full article
20 pages, 714 KB  
Review
The Role of the Gut Microbiome in Type 2 Diabetes Mellitus
by Rahaf Mashal, Amnah Al-Muhanna, Salma Khader, Aiman Khudair, Ahmed Khudair and Alexandra E. Butler
Int. J. Mol. Sci. 2025, 26(23), 11412; https://doi.org/10.3390/ijms262311412 (registering DOI) - 26 Nov 2025
Abstract
The gastrointestinal tract in humans hosts trillions of microorganisms, collectively termed the gut microbiota, which perform essential physiological processes and roles, including nutrient metabolism and immunomodulation. Influenced by genetics, age, diet, medication, and the environment, the disruption of this system leads to dysbiosis, [...] Read more.
The gastrointestinal tract in humans hosts trillions of microorganisms, collectively termed the gut microbiota, which perform essential physiological processes and roles, including nutrient metabolism and immunomodulation. Influenced by genetics, age, diet, medication, and the environment, the disruption of this system leads to dysbiosis, which has been linked to a range of diseases, notably type 2 diabetes mellitus (T2DM). As the global prevalence of T2DM continues to trend upwards, research investigating and highlighting the influence the gut microbiome exerts on this disease is warranted. The literature was examined regarding microbial metabolites and metabolic signaling pathways, as well as interventions relating to diet, prebiotics, probiotics, pharmacological agents, and fecal microbiota transplantation (FMT). The gut microbiome, through its effects on insulin resistance, inflammation, bile acid signaling, and glucose–lipid metabolism, impacts the development and progression of T2DM. Furthermore, patients with T2DM have demonstrated reduced microbial diversity, depletion of butyrate-producing bacteria, and an increase in pathogenic species. Interventions including high-fiber diets, metformin, probiotics, and FMT were shown to enrich beneficial microbes and improve metabolic outcomes. Targeted modulation of the microbiome, such as through next-generation probiotics and CRISPR-based therapies, may enhance metabolic control in the context of the future of personalized medicine. This review investigates the intricate relationship between the gut microbiome and T2DM, emphasizing its role in disease pathogenesis, the factors that may impact the microbiome in these patients, as well as therapeutic approaches toward its management. Full article
(This article belongs to the Special Issue Interplay Between the Human Microbiome and Diseases)
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13 pages, 977 KB  
Article
Can Insulin Drops Accelerate Corneal Healing After Corneal Cross-Linking? A Preliminary Case Series
by Freja Bagatin, Ante Vukojević, Karla Ranđelović, Ivana Radman, Renata Iveković, Valentina Lacmanović Lončar, Ivanka Petric Vicković and Zoran Vatavuk
Medicina 2025, 61(12), 2101; https://doi.org/10.3390/medicina61122101 (registering DOI) - 26 Nov 2025
Abstract
Background and Objectives: Corneal cross-linking (CXL) is the standard treatment for progressive keratoconus, but delayed epithelial healing remains a concern, increasing infection risk and patient discomfort. Studies suggest that insulin may promote corneal epithelial cell migration and proliferation, potentially accelerating wound healing. Its [...] Read more.
Background and Objectives: Corneal cross-linking (CXL) is the standard treatment for progressive keratoconus, but delayed epithelial healing remains a concern, increasing infection risk and patient discomfort. Studies suggest that insulin may promote corneal epithelial cell migration and proliferation, potentially accelerating wound healing. Its benefit has been observed in neurotrophic keratitis and diabetic epithelial defects, and it may offer similar effects post-CXL. Our objective is to evaluate the effect of topical insulin on epithelial healing after CXL in a small case series. Materials and Methods: Eight patients undergoing CXL for keratoconus were divided into two groups (n = 4 each). The insulin group received topical insulin eye drops (1 IU/mL in Systane®) five times daily, in addition to standard postoperative care. The control group received Systane® alone with the same regimen. Daily follow-up included slit-lamp exam, anterior segment OCT, and photodocumentation until epithelial defect closure. Results: Baseline parameters (central corneal thickness, keratoconus stage, Schirmer test, tear break up test) were comparable. While not statistically significant, the insulin group showed numerically smaller epithelial defects on day 2, suggesting a possible trend toward faster healing. By day 3, re-epithelialization was complete in all patients. Pain decreased over time in both groups without significant differences. No adverse effects were noted. Conclusions: Topical insulin may modestly accelerate epithelial healing after CXL, as suggested by smaller defects on day 2 in the insulin group. Although results were not statistically significant, the trend warrants further investigation in larger studies. Full article
(This article belongs to the Special Issue Advances in Corneal Management)
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19 pages, 3005 KB  
Article
Coordinated FRT Control for Paralleled Grid-Following and Grid-Forming Generators Connected to Weak Grid
by Tao Tan, Shengli He, Yuqin Gao, Hao Xiao and Xia Shen
Processes 2025, 13(12), 3816; https://doi.org/10.3390/pr13123816 (registering DOI) - 26 Nov 2025
Abstract
The combination of grid-forming (GFM) and grid-following (GFL) distributed renewable resources (DERs) can leverage their complementary functionalities to achieve superior resilience, reliability, and power quality compared to systems employing a single control strategy. Several studies have focused on the steady-state power coordinated control [...] Read more.
The combination of grid-forming (GFM) and grid-following (GFL) distributed renewable resources (DERs) can leverage their complementary functionalities to achieve superior resilience, reliability, and power quality compared to systems employing a single control strategy. Several studies have focused on the steady-state power coordinated control under stiff power grids, while the transient interaction and coordinated fault ride-through (FRT) issue between the parallel GMF and GFL DERs under weak power grids remains underexplored. To fill this gap, the transient interaction model of the hybrid system under weak grids is developed to guide the stability enhancement-oriented controller design. It is revealed that the GFM DER should help to enhance the GFL DER under transient state since the latter’s PLL has a high probability of lose lock under a weak grid. Moreover, a coordinated FRT control is proposed according to the coupling mechanism. The GMF DER has no need to switch the operation modes, while the system frequency deviation and voltage inrush could be reduced by 0.2% and 40% compared with conventional methods. Finally, simulation verifications based on PSCAD/EMTDC are provided to validate the correctness of the theoretical analysis and the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Advances in Hydrogen Energy Systems Integration, Modeling and Optimization)
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27 pages, 3744 KB  
Article
Early-Life Demographic Factors Shape Gut Microbiome Patterns Associated with Rotavirus Gastroenteritis Severity
by Eman R. Abdelbary, Mohammed Ramadan, Ibrahim A. Amin, Fatma S. Abd-Elsamea, Ashraf Mohamed Elsaghier, Eman Ahmed Abd-Alrahman, Hani A. Ozbak, Hassan A. Hemeg, Yahya A. Almutawif, Shadi A. Zaki, Ali A. Abdelrahman and Mohammed Salah
Viruses 2025, 17(12), 1542; https://doi.org/10.3390/v17121542 (registering DOI) - 26 Nov 2025
Abstract
Background: Rotavirus gastroenteritis (RVGE) remains a leading cause of severe infant diarrhea worldwide, with growing evidence supporting the role of the gut microbiome in modulating the disease. However, the interplay between early-life demographic factors, the gut microbiome, and their combined impact on RVGE [...] Read more.
Background: Rotavirus gastroenteritis (RVGE) remains a leading cause of severe infant diarrhea worldwide, with growing evidence supporting the role of the gut microbiome in modulating the disease. However, the interplay between early-life demographic factors, the gut microbiome, and their combined impact on RVGE clinical severity remains inadequately characterized, particularly in specific geographic populations. Aim: We aimed to investigate how demographic determinants shape gut microbiome composition and function in RVGE and how these features relate to clinical severity. Methods: In our comprehensive case–control study of 165 infants (120 RVGE cases and 45 healthy controls, aged 0–12 months), we utilized 16S rRNA sequencing combined with advanced statistical modeling and machine learning to investigate how demographic factors influence microbiome composition and clinical outcomes. Results: RVGE cases exhibited significantly reduced bacterial diversity (Kruskal–Wallis, Static = 14.85, p < 0.001) and distinct patterns, with community structure most strongly associated with dehydration severity (PERMANOVA; R2 = 0.15, p < 0.001). Substantial taxonomic alterations were identified characterized by depletion of beneficial commensals including Akkermansia (LDA score = 3.8, p < 0.001), Faecalibacterium (Random Forest AUC = 0.82, p < 0.001), and Bifidobacterium (r = −0.42 with breastfeeding, p < 0.001), alongside enrichment of inflammation-associated taxa such as Escherichia-Shigella (WBC; r = 0.49, p < 0.001, and CRP; r = 0.56, p < 0.001), Streptococcus (LDA score = 4.2, p < 0.001), and Staphylococcus. Proteobacteria was the top potential biomarker of severe outcomes (Random Forest AUC = 0.85), with abundance positively correlated with systemic inflammation (CRP: r = 0.51, p = 0.003). Functional predictions revealed increased lipopolysaccharide biosynthesis (ko00540) and reduced butanoate metabolism (ko00650, p < 0.001) in severe disease. Importantly, demographic factors significantly modulated clinical outcomes: cesarean-delivered, formula-fed infants presented the most dysbiotic profiles and experienced 3.2-fold longer hospitalization (95% CI: 1.8–5.6, p < 0.001) than vaginally delivered, breastfed infants did. Conclusions: Collectively, these findings demonstrate that early-life demographic factors potentially shape the gut microbiome composition and function, may influence RVGE severity and recovery trajectories, thus providing candidate biomarkers for risk stratification and identifying targets for microbiota-based interventions. Full article
(This article belongs to the Section Human Virology and Viral Diseases)
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30 pages, 1911 KB  
Review
β-Cell Mitochondrial Dysfunction: Underlying Mechanisms and Potential Therapeutic Strategies
by Radwan Darwish, Yasmine Alcibahy, Ghena Abu-Sharia and Alexandra E. Butler
Cells 2025, 14(23), 1861; https://doi.org/10.3390/cells14231861 (registering DOI) - 26 Nov 2025
Abstract
Mitochondria are essential for β-cell function, coupling glucose metabolism to ATP production and insulin secretion. In diabetes, β-cell mitochondrial dysfunction arises from oxidative stress, impaired quality control and disrupted dynamics, leading to reduced oxidative phosphorylation, defective insulin release and progressive cell loss. Key [...] Read more.
Mitochondria are essential for β-cell function, coupling glucose metabolism to ATP production and insulin secretion. In diabetes, β-cell mitochondrial dysfunction arises from oxidative stress, impaired quality control and disrupted dynamics, leading to reduced oxidative phosphorylation, defective insulin release and progressive cell loss. Key transcriptional regulators link genetic susceptibility to mitochondrial dysfunction in both type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM). These disruptions impair mitophagy, mitochondrial translation and redox homeostasis. Therapeutic strategies that restore mitochondrial function, including mitophagy enhancers, mitochondrial antioxidants, and transcriptional regulators, have shown potential in preserving β-cell integrity. As mitochondrial failure precedes β-cell loss, targeting mitochondrial pathways may represent a critical approach to modifying diabetes progression. Full article
(This article belongs to the Special Issue Aging and Metabolic Diseases)
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21 pages, 3073 KB  
Review
Relevance and Evolution of Benchmarking in Computer Systems: A Comprehensive Historical and Conceptual Review
by Isaac Zablah, Lilian Sosa-Díaz and Antonio Garcia-Loureiro
Computers 2025, 14(12), 516; https://doi.org/10.3390/computers14120516 (registering DOI) - 26 Nov 2025
Abstract
Benchmarking has been central to performance evaluation for more than four decades. Reinhold P. Weicker’s 1990 survey in IEEE Computer offered an early, rigorous critique of standard benchmarks, warning about pitfalls that continue to surface in contemporary practice. This review synthesizes the evolution [...] Read more.
Benchmarking has been central to performance evaluation for more than four decades. Reinhold P. Weicker’s 1990 survey in IEEE Computer offered an early, rigorous critique of standard benchmarks, warning about pitfalls that continue to surface in contemporary practice. This review synthesizes the evolution from classical synthetic benchmarks (Whetstone, Dhrystone) and application kernels (LINPACK) to modern suites (SPEC CPU2017), domain-specific metrics (TPC), data-intensive and graph workloads (Graph500), and Artificial Intelligence/Machine Learning (AI/ML) benchmarks (MLPerf, TPCx-AI). We emphasize energy and sustainability (Green500, SPECpower, MLPerf Power), reproducibility (artifacts, environments, rules), and domain-specific representativeness, especially in biomedical and bioinformatics contexts. Building upon Weicker’s methodological cautions, we formulate a concise checklist for fair, multidimensional, reproducible benchmarking and identify open challenges and future directions. Full article
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17 pages, 2402 KB  
Article
Microbial Biotransformation of the Sesquiterpene Carotol: Generation of Hydroxylated Metabolites with Potential Cytotoxic and Target-Specific Binding Activities
by Hanan G. Sary, Mohammed A. Khedr, Mohamed M. Radwan, Mickey Vinodh and Khaled Y. Orabi
Biomolecules 2025, 15(12), 1651; https://doi.org/10.3390/biom15121651 (registering DOI) - 26 Nov 2025
Abstract
Carotol, the major sesquiterpene alcohol in carrot essential oil, possesses notable cytotoxic activity against various cancer cell lines, yet its metabolic fate remains poorly understood. This study explored microbial biotransformation as a tool for generating novel carotol derivatives with potential pharmacological value. Seventeen [...] Read more.
Carotol, the major sesquiterpene alcohol in carrot essential oil, possesses notable cytotoxic activity against various cancer cell lines, yet its metabolic fate remains poorly understood. This study explored microbial biotransformation as a tool for generating novel carotol derivatives with potential pharmacological value. Seventeen microbial strains were screened, with Absidia coerulea ATCC 6647 identified as the most effective biocatalyst. Preparative-scale fermentation with this strain afforded three new metabolites, CM1, CM2, and CM3, in yields of 30%, 9.96%, and 3.28%, respectively, which were structurally characterized by 1D and 2D NMR, HRMS, and single-crystal X-ray diffraction. These were identified as 9α-hydroxydaucol (CM1), 9α,13-dihydroxydaucol (CM2), and a diol derivative of daucol (CM3). Cytotoxicity evaluation against human carcinoma cell lines (HepG-2, HCT-116, MCF-7, A-549) and normal lung fibroblasts (MRC-5) revealed that carotol exhibited notable activity with IC50 values of 25.68 and 28.65 µM against HCT-116 and A-549 cell lines, respectively. Among the metabolites, CM2 showed selective cytotoxicity with IC50 values of 180.64 (HCT-116) and 138.21 µM (A-549), indicating that microbial transformation modulates the cytotoxic profile of carotol and yields metabolites with distinct bioactivity patterns. Molecular docking studies further revealed that carotol and CM2 demonstrated higher binding affinities and more stable interactions with human NADPH oxidase, suggesting that inhibition of this enzyme may underlie their cytotoxic effects. This work provides the first detailed microbial biotransformation pathway of carotol, highlighting A. coerulea as a promising source of new hydroxylated metabolites. The results underscore the potential of carotol derivatives in anticancer drug development and warrant further pharmacokinetic studies. Full article
(This article belongs to the Section Natural and Bio-derived Molecules)
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36 pages, 29637 KB  
Review
Environmental Pollution in the Alto Atoyac Basin, Mexico: A Systematic, Spatial, and Temporal Review of Contaminants and Monitoring Efforts
by Eduardo Torres, Blanca Erendira Ramírez-Anguiano and Itzel F. Arroyo-Ortega
Environments 2025, 12(12), 456; https://doi.org/10.3390/environments12120456 (registering DOI) - 26 Nov 2025
Abstract
The Alto Atoyac Basin (AAB) in central Mexico is one of the most environmentally degraded regions in the country. This review systematically compiles 60 peer-reviewed studies on environmental contamination from 1975 to 2024. A unified, standardized database supported spatial and temporal analyses using [...] Read more.
The Alto Atoyac Basin (AAB) in central Mexico is one of the most environmentally degraded regions in the country. This review systematically compiles 60 peer-reviewed studies on environmental contamination from 1975 to 2024. A unified, standardized database supported spatial and temporal analyses using GIS and non-parametric tests, revealing pollution hotspots and disparities in monitoring coverage. Spatial analysis showed a high concentration of studies along the Atoyac River, while nineteen municipalities lacked any records. Research primarily focused on surface water and sediments, with limited attention given to groundwater, soils, air, and food matrices. Data on human exposure remains scarce and fragmented, limiting risk assessment. The evidence reveals widespread contamination linked to industrial, urban, and agricultural pressures. Detected pollutants include pathogens, heavy metals, and diverse organic compounds exceeding national and international thresholds. Spatial analysis highlights pollutant concentrations in densely populated and industrialized zones, while temporal patterns show ongoing degradation from continuous discharges and limited remediation efforts. The findings emphasize long-term ecological degradation and potential health risks, underscoring the need for integrated monitoring and spatially informed management to guide recovery and policy actions. Future efforts should focus on continuous monitoring, multivariate and spatial modeling, and integrated basin-management frameworks to support restoration in the AAB. Full article
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15 pages, 1061 KB  
Article
Model and Simulations of Contact Between a Vibrating Beam and an Obstacle Using the Damped Normal Compliance Condition
by Giselle Saylor, Meir Shillor and Cornelius Vordey
Axioms 2025, 14(12), 866; https://doi.org/10.3390/axioms14120866 (registering DOI) - 26 Nov 2025
Abstract
This work constructs a new mathematical model for the vibrations of a Bernoulli beam that can come in contact with a reactive obstacle situated below its right end. The obstacle reaction is described by the Damped Normal Compliance (DNC) contact condition. This condition, [...] Read more.
This work constructs a new mathematical model for the vibrations of a Bernoulli beam that can come in contact with a reactive obstacle situated below its right end. The obstacle reaction is described by the Damped Normal Compliance (DNC) contact condition. This condition, unlike the usual Normal Compliance (NC) contact condition, takes into account the energy dissipation during the contact process. The steady states of the model are described and the model is studied computationally for different values of obstacle stiffness and damping. The computational scheme is shown numerically to converge with a rate higher than 1. The numerical simulations illustrate how the beam’s end penetration and vibrations differ in soft vs. stiff obstacle environments, and how damping modifies the dynamic behavior. The results may be useful for vibration control and material interaction in settings when collisions or repetitive contacts occur. By providing computational and analytical insights, the study is an addition to the currently maturing Mathematical Theory of Contact Mechanics (MTCM). Full article
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31 pages, 13373 KB  
Article
An Online Collaborative Approach to Developing Ontologies to Study Questions About Behaviour
by Suvodeep Mazumdar, Fatima Maikore, Vitaveska Lanfranchi, Harriet Baird, Fabio Ciravegna, Vyv Huddy, Paul Norman, Richard Rowe, Alexander J. Scott and Thomas L. Webb
Knowledge 2025, 5(4), 26; https://doi.org/10.3390/knowledge5040026 (registering DOI) - 26 Nov 2025
Abstract
Almost all societal grand challenges, whether concerning the environment, health, well-being, or the development of sustainable economic models, have at their heart a need to understand people’s behaviour. However, uniting data and insights across disparate fields requires an explicit and shared understanding of [...] Read more.
Almost all societal grand challenges, whether concerning the environment, health, well-being, or the development of sustainable economic models, have at their heart a need to understand people’s behaviour. However, uniting data and insights across disparate fields requires an explicit and shared understanding of concepts, variables, and ideas (e.g., how to characterise and differentiate behaviours). Ontologies provide a mechanism for creating this explicit and shared understanding and are starting to be developed and used in the social and behavioural sciences. This paper proposes an online co-design approach to use and develop ontologies of behaviour to specify the characteristics of behaviour (e.g., habitual, changeable, effortless) and studies that investigate behaviour as part of a project designed to understand how behaviours are related. We report on our experience of collaborative co-development of ontologies using real-time interactive tools and reflect on the benefits and challenges of our approach. We also offer a set of recommendations for researchers interested in applying such methods to co-develop ontologies. The work contributes to efforts to understand the characteristics of behaviour and enable these to be used to understand questions about behaviour (e.g., is poor sleep associated with greater engagement in habitual behaviours?). Full article
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19 pages, 5187 KB  
Article
Genome-Wide Association Studies of Growth and Carcass Traits in Charolais Cattle Based on High-Coverage Whole-Genome Resequencing
by Feng Zhang, Chengmei Wang, Aishao Shangguan, Xiaojun Suo, Mengjie Chen, Hu Tao, Fan Jiang, Tian Xu, Nian Zhang, Zaidong Hua, Jin Chai and Qi Xiong
Int. J. Mol. Sci. 2025, 26(23), 11411; https://doi.org/10.3390/ijms262311411 (registering DOI) - 25 Nov 2025
Abstract
Growth and carcass traits are key economic traits in beef cattle production, and identifying their associated genetic markers is crucial for improving breeding efficiency. Charolais cattle, as a superior beef breed, exhibit excellent performance in growth rate and meat production. The aim of [...] Read more.
Growth and carcass traits are key economic traits in beef cattle production, and identifying their associated genetic markers is crucial for improving breeding efficiency. Charolais cattle, as a superior beef breed, exhibit excellent performance in growth rate and meat production. The aim of this study was to utilize the preferred high-coverage whole-genome resequencing (hcWGS) as a replacement for single nucleotide polymorphism (SNP) chips to identify significant SNPs and candidate genes associated with growth (body weight, body height, cross height, body length, and chest measurement across different growth stages) and carcass traits (live backfat thickness and eye muscle area at 18 months) in 240 Charolais cattle, thereby providing guidance for beef cattle breeding. Through hcWGS (approximately 13× coverage) and quality control, 4,088,633 SNPs were identified and subsequently used for genetic analyses. Through FarmCPU-based genome-wide association studies, 196 potentially significant SNPs associated with growth traits and 29 SNPs with carcass traits were identified. Annotation analyses revealed 353 candidate genes (such as RBM33, KCTD17, PTHLH, RAC2, CHD6, TRDN, WBP1L, TLL2, CH25H, and ST13) linked to growth traits and 26 candidate genes linked to carcass traits (such as CHST11, LRRK2, RIOK2, and INTS10). Additionally, three SNPs (g.8674692C>G, g.54418624G>T, and g.71085551G>A) were validated via polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP), enabling efficient marker-assisted selection. Furthermore, eight SNPs in the Acyl-CoA oxidase 1 (ACOX1) gene were found to be associated with growth and backfat thickness traits. These findings provide valuable preliminary insights into the genetic mechanisms underlying growth and carcass traits in Charolais cattle, facilitating genome-assisted breeding. Full article
(This article belongs to the Topic Advances in Molecular Genetics and Breeding of Cattle, Sheep, and Goats)
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22 pages, 4316 KB  
Article
LisseMars: A Lightweight Semantic Segmentation Model for Mars Helicopter
by Boyu Lin, Fei Wang, Qingeng Li, Bo Zheng, Meibao Yao, Xueming Xiao, Yifan Qi, Hutao Cui and Xiangyu Huang
Aerospace 2025, 12(12), 1049; https://doi.org/10.3390/aerospace12121049 - 25 Nov 2025
Abstract
With the continuous deepening of Mars exploration missions, the Mars helicopter has become a key platform for acquiring high-resolution near-ground imagery. However, accurate semantic segmentation of the Martian surface remains challenging due to complex terrain morphology, sandstorm interference, and the limited onboard computational [...] Read more.
With the continuous deepening of Mars exploration missions, the Mars helicopter has become a key platform for acquiring high-resolution near-ground imagery. However, accurate semantic segmentation of the Martian surface remains challenging due to complex terrain morphology, sandstorm interference, and the limited onboard computational resources that restrict real-time processing. Existing models either introduce high computational overhead unsuitable for deployment on Mars aerial platforms or fail to jointly capture fine-grained local texture and global contextual structure information. To address these limitations, we propose LisseMars, a lightweight semantic segmentation network designed for efficient onboard perception. The model integrates a Window Movable Attention (WMA) module for enhanced global context extraction and a multi-convolutional feedforward module (CFFN) to strengthen local detail representation. A Dynamic Polygon Convolution (DPC) module is further introduced to improve segmentation performance on geometrically heterogeneous objects, while a Group Fusion Module (GFM) enables effective multi-scale semantic integration. Extensive experiments are conducted on both real Tianwen-1 Mars helicopter imagery and synthetic datasets. The results show that our method achieved a mean IoU of 78.56% with only 0.12 MB of model parameters, validating the effectiveness of the proposed framework. The real-time performance of proposed method on edge device deployment further demonstrate potential application for real Mars airborne missions. Full article
(This article belongs to the Section Astronautics & Space Science)
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20 pages, 3615 KB  
Article
Heavy Metal Pollution and Health Risk Assessment in Black Soil Region of Inner Mongolia Province, China
by Lin Xu, Zijie Gao, Jie Jiang and Guoxin Sun
Agronomy 2025, 15(12), 2717; https://doi.org/10.3390/agronomy15122717 - 25 Nov 2025
Abstract
In order to investigate the current status of soil heavy metal pollution, ecological risk, and risk sources in the black soil area of the Eastern Inner Mongolia Province, topsoil (0–20 cm) samples from farmland in the black soil area (N = 163) were [...] Read more.
In order to investigate the current status of soil heavy metal pollution, ecological risk, and risk sources in the black soil area of the Eastern Inner Mongolia Province, topsoil (0–20 cm) samples from farmland in the black soil area (N = 163) were collected to determine the contents of seven heavy metals. The levels of soil heavy metal pollution and ecological risk in the study area were evaluated by combining the geo-accumulation index, potential ecological risk index, and static environmental carrying capacity; the positive matrix factorization (PMF) model was used to identify the pollution sources and contributions of heavy metals in the soil and analyze the risk levels to adults and children. The soil was predominantly weakly acidic, with mean values of Cr, Ni, Cu, As, Cd, Pb, and Zn of 61.77, 26.77, 17.07, 12.11, 0.08, 12.61, and 85.71 mg·kg−1. The mean concentrations of heavy metals exceeded the background values, except for Pb, the mean concentration of which was lower than the soil background. Ni concentrations of 6.21% at the sampling sites exceeded the risk screening value for agricultural soils. The geo-accumulation index showed that Cr (55.15%) and As (54.00%) were mainly mild pollutants; the static environmental carrying capacity indicated that the soils were slightly polluted by Ni, As, and Zn; and the potential ecological risk indices of Cd, Ni, and As were at moderate levels. The PMF model analyzed three pollution sources: mixed agricultural practice–transportation sources (39.46%), mineral-related activity sources (27.01%), and pesticide–fertilizer agricultural practices (33.53%). The human health risk assessment indicated that 46.58% of sampling sites posed a carcinogenic risk to children, with Ni as the main carcinogenic element. In conclusion, the potential contamination of As, Cd, Ni, Cr, and Zn in the Eastern Inner Mongolia farmland black soil area should be further studied. Full article
(This article belongs to the Section Agroecology Innovation: Achieving System Resilience)
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13 pages, 1917 KB  
Article
Occupational Ergonomic Risks Among Women in Underground Coal Mining, South Africa
by Ouma S. Mokwena, Joyce Shirinde and Thabiso J. Morodi
Safety 2025, 11(4), 116; https://doi.org/10.3390/safety11040116 - 25 Nov 2025
Abstract
Although women have participated in mining activities across the world for centuries, the industry continues to be perceived as predominantly male-oriented. This perception persists largely due to the male-dominated workforce and the physically demanding nature of mining operations. This paper examines the ergonomic [...] Read more.
Although women have participated in mining activities across the world for centuries, the industry continues to be perceived as predominantly male-oriented. This perception persists largely due to the male-dominated workforce and the physically demanding nature of mining operations. This paper examines the ergonomic impacts of mining machinery on female mineworkers. The study was conducted in three underground coal mining operations located in Mpumalanga, South Africa, using a quantitative research approach. To evaluate the ergonomic demands placed on women working underground, the researchers employed the Rapid Entire Body Assessment (REBA) in combination with direct observation techniques. The findings revealed that female mineworkers experience considerable challenges when performing tasks requiring significant physical strength and endurance. The observed female mineworker recorded a final REBA score of seven, indicating a medium-risk level. Ergonomic challenges in underground coal mining are further intensified for female mineworkers due to the absence of gender-specific considerations in equipment design, task allocation, and the overall working environment. Although the risk classification was moderate, the results underscore the need for further investigation and the timely implementation of corrective measures. Addressing these issues will require the integration of inclusive ergonomic principles that account for gender diversity within the mining workforce. Full article
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11 pages, 2357 KB  
Article
Visual Servo-Based Real-Time Eye Tracking by Delta Robot
by Maria Muzamil Memon, Aarif Hussain, Abdulrhman Mohammed, Ali Manthar, Songjing Li and Weiyang Lin
Appl. Sci. 2025, 15(23), 12521; https://doi.org/10.3390/app152312521 - 25 Nov 2025
Abstract
This work presents and validates an eye-tracking-based visual system for driving the delta robot. A delta robot is tracked by image processing based on vision servo control. The vision servo program is developed in C++ to perform image processing-based object detection. For image [...] Read more.
This work presents and validates an eye-tracking-based visual system for driving the delta robot. A delta robot is tracked by image processing based on vision servo control. The vision servo program is developed in C++ to perform image processing-based object detection. For image processing, Haar classifier-based methods are used. Finally, image processing and motion controller movements are integrated into one system to perform the visual servo-based motion of the end effector of the delta robot. Experiments are performed to validate the proposed method from the perspective of image processing. Moreover, this paper validates the kinematic analysis, which is vital for obtaining 3D information on the end-effector of the delta robot. The presented model can be implemented in eye clinics to facilitate ophthalmologists by replacing manual eye-checking equipment with automatic, unattended, computerized eye checkups. Full article
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23 pages, 5372 KB  
Article
Correcting Atmospheric Temperature and Vapor Density Profiles of Ground-Based Microwave Radiometer in Diverse Skies by Regression Model and Artificial Neural Network Methods
by Guirong Xu, Yonglan Tang, Aning Gou, Yiqin Wang, Weifa Yang and Jing Yan
Remote Sens. 2025, 17(23), 3819; https://doi.org/10.3390/rs17233819 - 25 Nov 2025
Abstract
A ground-based microwave radiometer (MWR) can retrieve temperature and vapor density profiles with a temporal resolution at the minute level, which is significant for studying atmospheric thermodynamic stratification and its evolution. Improving MWR retrieval accuracy is crucial for MWR application research. Based on [...] Read more.
A ground-based microwave radiometer (MWR) can retrieve temperature and vapor density profiles with a temporal resolution at the minute level, which is significant for studying atmospheric thermodynamic stratification and its evolution. Improving MWR retrieval accuracy is crucial for MWR application research. Based on 9-year observations of MWR and radiosonde in Wuhan, China, this study adopts regression model and artificial neural network (ANN) methods to correct MWR temperature and vapor density deviations against radiosondes in diverse skies. Due to the impacts of solar heating and raindrops, MWR temperature presents a cold bias from radiosondes in clear and cloudy skies, but a warm bias in rainy skies, while the MWR vapor density is generally wetter than radiosondes, especially in rainy skies. The validation results show that both regression and ANN models can reduce the biases of MWR temperature and vapor density against radiosondes to around zero in diverse skies, and the MWR vapor density RMSE in rainy skies shows a marked decrease. After correcting using the regression model, the RMSE of MWR temperature (vapor density) declines by 14% (7%), 7% (4%), and 12% (29%) in clear, cloudy, and rainy skies, respectively, and the correction effect of the ANN model is slightly better than the regression model, with corresponding decreases of 19% (8%), 10% (8%), and 12% (30%), respectively. However, the consistency of MWR retrievals with radiosondes is rarely improved after the corrections of regression and ANN models. These results indicate that the regression and ANN models have a reasonable ability to correct MWR retrieval deviation in diverse skies, and there is remaining room for further improvement in MWR retrieval accuracy. Full article
(This article belongs to the Special Issue Advances in Microwave Remote Sensing for Earth Observation (EO))
17 pages, 5411 KB  
Article
Synergistic Effects of Hybrid Basalt Fibers on the Durability of Recycled Aggregate Concrete Under Freeze–Thaw and Chloride Conditions
by Qiao Sun, Zehui Ye, Renjie Cai and Dongwei Li
Appl. Sci. 2025, 15(23), 12520; https://doi.org/10.3390/app152312520 - 25 Nov 2025
Abstract
To address the poor resistance of recycled aggregate concrete (RAC) to chloride ion penetration and freeze–thaw deterioration in cold coastal regions, this study introduces basalt fibers (BFs) as a reinforcement to improve its durability and structural integrity. Rapid freeze–thaw and electric flux tests, [...] Read more.
To address the poor resistance of recycled aggregate concrete (RAC) to chloride ion penetration and freeze–thaw deterioration in cold coastal regions, this study introduces basalt fibers (BFs) as a reinforcement to improve its durability and structural integrity. Rapid freeze–thaw and electric flux tests, combined with scanning electron microscopy (SEM), were employed to systematically evaluate the effects of fiber volume fraction and length configuration on the frost resistance and chloride impermeability of basalt fiber-reinforced RAC (BFRAC). The experimental results demonstrated that the incorporation of basalt fibers markedly enhanced the coupled durability of RAC, with the mixture containing 0.15% fiber volume and a balanced hybrid of short (12 mm) and long (18 mm) fibers achieving the most favorable performance. This mixture effectively reduced mass loss and strength degradation under repeated freeze–thaw cycles while substantially lowering chloride ion penetration compared with plain RAC. Microstructural observations revealed that the hybrid fiber system formed a multi-scale three-dimensional network, in which short fibers restrained microcrack initiation and long fibers bridged macrocracks, jointly refining the pore structure and improving the interfacial bonding between recycled aggregates and the cement matrix. This synergistic mechanism enhanced matrix compactness and obstructed chloride transport, leading to a more stable and durable composite. The findings not only establish an optimal basalt fiber design for improving RAC durability but also elucidate the fundamental mechanism underlying hybrid fiber synergy. These insights provide valuable theoretical guidance and practical strategies for developing sustainable, high-performance concrete suitable for long-term service in cold-region coastal infrastructures. Full article
(This article belongs to the Section Civil Engineering)
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20 pages, 1023 KB  
Article
Integrating Indigenous Financial Frameworks in Zimbabwean Banks: A Decolonial Economics’ Approach to Sustainable Finance
by Gilbert Tepetepe and Lawrence Ogechukwu Obokoh
Economies 2025, 13(12), 343; https://doi.org/10.3390/economies13120343 - 25 Nov 2025
Abstract
This study explores, from decolonial economics perspective, how nineteen Zimbabwean banks engage with both Euro-American and indigenous knowledge systems in their sustainable finance practices. Despite growing global interest in sustainability, limited research has examined the relevance of these models within Zimbabwe’s socio-economic context. [...] Read more.
This study explores, from decolonial economics perspective, how nineteen Zimbabwean banks engage with both Euro-American and indigenous knowledge systems in their sustainable finance practices. Despite growing global interest in sustainability, limited research has examined the relevance of these models within Zimbabwe’s socio-economic context. Addressing this gap, the study employs transformative sequential mixed methods, incorporating 289 structured questionnaires, 30 focus group discussions, and 45 archival documents. Data were subjected to descriptive statistics, narrative analysis, Marxist immanent critique, and decolonial theory. Findings reveal that Zimbabwean banks predominantly adopt Euro-American sustainability frameworks such as the UN Sustainable Development Goals, Paris Accords and accounting standards. However, these frameworks often misalign with local realities, obscuring sustainability colonialism, promoting exclusion of indigenous knowledge, reinforcing Global North dominance, and perpetuating weak sustainability theory. This results in superficial compliance that conceals extractive investments and carbon-intensive practices. Moreover, these models deepen subordinated financialization, commodification, elite capture, resource expropriation, and socio-environmental inequalities. The study calls for a paradigm shift, either rejecting Euro-American models in favor of indigenous approaches or adopting a hybrid model that integrates indigenous knowledge. Such a shift would promote strong sustainability, pluralism, and decolonized institutional frameworks to foster financial inclusion, community resilience, and ecological regeneration in Zimbabwe. Full article
(This article belongs to the Section Economic Development)
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28 pages, 1726 KB  
Article
Energy Efficiency Optimization in Heterogeneous 5G Networks Using DUDe
by Chrysostomos-Athanasios Katsigiannis, Konstantinos Tsachrelias, Vasileios Kokkinos, Apostolos Gkamas, Christos Bouras and Philippos Pouyioutas
Electronics 2025, 14(23), 4641; https://doi.org/10.3390/electronics14234641 - 25 Nov 2025
Abstract
To meet the escalating data demands of 5G and beyond networks, densified Heterogeneous Networks (HetNets) provide a promising solution, deploying small base stations for improved spectral and energy efficiency. However, HetNets pose challenges, particularly in user association. This journal introduces the Downlink/Uplink Decoupling [...] Read more.
To meet the escalating data demands of 5G and beyond networks, densified Heterogeneous Networks (HetNets) provide a promising solution, deploying small base stations for improved spectral and energy efficiency. However, HetNets pose challenges, particularly in user association. This journal introduces the Downlink/Uplink Decoupling (DUDe) approach, which enhances uplink performance in HetNets by allowing different access points for uplink and downlink associations. We assess DUDe’s energy efficiency through extensive simulations across various scenarios, demonstrating substantial energy savings compared to centralized 5G systems. Our findings underscore the importance of energy-efficient design for reducing network operational costs and carbon footprint in 5G networks. In addition to energy efficiency gains, DUDe also offers improved resource allocation and network flexibility, making it a valuable solution for evolving wireless communication ecosystems. Full article
(This article belongs to the Special Issue Feature Papers in Networks: 2025–2026 Edition)
32 pages, 3549 KB  
Article
BeamSecure-AI: AI-Driven Beam-Level Attack Detection in mmWave RAN
by Faris Alsulami
Electronics 2025, 14(23), 4642; https://doi.org/10.3390/electronics14234642 - 25 Nov 2025
Abstract
Millimeter-wave radio access networks have a high level of security risks due to the vulnerability of having security threats at the beam level as hackers can exploit this by breaking network integrity and user privacy. This paper proposes BeamSecure-AI, an artificial intelligence-based framework [...] Read more.
Millimeter-wave radio access networks have a high level of security risks due to the vulnerability of having security threats at the beam level as hackers can exploit this by breaking network integrity and user privacy. This paper proposes BeamSecure-AI, an artificial intelligence-based framework that allows locating beam-level attacks and overcoming them in mmWave RAN networks in real-time. The proposed system combines deep reinforcement learning and explainable AI modules to enable it to dynamically detect threats and be transparent about the operations of the decision-making processes. We mathematically formulate the dynamic beam alignment patterns covering the multi-dimensional feature extraction through space, time, and spectral space. Experimental results validate the effectiveness of the proposed method across a range of attack scenarios, where significantly higher improvement in detection rates (96.7%) and response latency of 42.5 ms, with false-positive rates below ≤2.3%, are observed as compared to other methods. The framework can detect complex attacks such as beam stealing, jamming, and spoofing while maintaining low false-positive rates and consistent performance across urban, suburban, and rural deployment scenarios. Full article
(This article belongs to the Special Issue Secure Networking: Advances in Network Attack Detection and Protocol Security)
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19 pages, 5251 KB  
Article
Influence of Cross-Sectional Curve Equation on Flow Field Evolution and Particle Separation in the Spiral Concentrator of the First Turn
by Shuling Gao, Chunyu Liu, Xiaohong Zhou, Xintong Zhang, Qian Wang and Cong Han
Separations 2025, 12(12), 327; https://doi.org/10.3390/separations12120327 - 25 Nov 2025
Abstract
The flow field evolution in the first turn of the spiral concentrator is decisive for the separation efficiency of solid particles. A laboratory-scale Φ300 mm spiral concentrator was employed as the study subject. The fluid phase was simulated using the RNG k-ε (Renormalization [...] Read more.
The flow field evolution in the first turn of the spiral concentrator is decisive for the separation efficiency of solid particles. A laboratory-scale Φ300 mm spiral concentrator was employed as the study subject. The fluid phase was simulated using the RNG k-ε (Renormalization Group) turbulence model and the VOF (Volume of Fluid) multiphase model, while the particles were calculated with an Eulerian multi-fluid VOF model that incorporates the Bagnold effect. The influence of the cross-sectional curve equation on the evolution of flow field parameters in the first turn and on the separation behavior of hematite and quartz particles was systematically investigated. The results indicated that the evolution characteristics of fluid parameters, such as the depth of flow film, the tangential velocity of surface flow, the velocity of secondary circulation, and radial flux, were similar. All parameters were observed to undergo an initial decrease or increase, eventually stabilizing as the longitudinal travel progressed. A negative correlation was identified between the index of the cross-sectional curve equation and both the depth of flow film and the tangential velocity of surface flow in the inner half of the trough, whereas an inverse relationship was noted in the outer half. With an increase in the index of the cross-sectional curve equation, the outward circulation velocity in the initial stage and its radial flux in the outer zone were enhanced, while the fluctuations in the evolution of local fluid parameters were suppressed, with more active fluid radial migration observed at the indices of the cross-sectional curve equation of 2.5 and 3. As the flow field evolved, axial separation between hematite and quartz particles was progressively achieved by gravity due to their density difference. In the middle and inner-outer zones, the migration directions of hematite and quartz were observed to become opposite in the later stage of evolution, while the difference in their migration magnitudes was also found to be widened. With an increase in the index of the cross-sectional curve equation, the disparity in the axial separation and movement between hematite and quartz was enhanced, albeit with a diminishing rate of increase. The maximum separation efficiency between hematite and quartz particles was significantly improved with increased longitudinal travel, reaching over 60% by the end of the first turn; higher indices were determined to be more favorable for achieving this performance. Based on the previous research, the variation in separation indices in the third turn was investigated under both independent adjustment of the index of the cross-sectional curve equation and its combined adjustment with the downward bevel angle. Relatively high and stable separation performance was achieved with the indices of the cross-sectional curve equation of 2.5 and 3, where a maximum separation efficiency of 82.02% was obtained, thereby validating the high efficiency and suitability of the selected spiral concentrator profile. This research elucidated the decisive role of the flow field evolution through the first turn in particle separation behavior from the perspective of quantitative description of hydrodynamic parameters, providing beneficial references for the cross-sectional structure design of spirals and the prediction of the separation index of specific feed. Full article
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18 pages, 545 KB  
Review
Robotic Pancreaticoduodenectomy: Current Evidence and Future Perspectives
by Silvio Caringi, Antonella Delvecchio, Annachiara Casella, Cataldo De Palma, Valentina Ferraro, Rosalinda Filippo, Matteo Stasi, Nunzio Tralli, Tommaso Maria Manzia, Riccardo Memeo and Michele Tedeschi
J. Clin. Med. 2025, 14(23), 8372; https://doi.org/10.3390/jcm14238372 - 25 Nov 2025
Abstract
Background: Robotic pancreaticoduodenectomy (RPD) is a less invasive alternative to open pancreaticoduodenectomy (OPD) with the potential for perioperative advantage. Concerns remain regarding its technical difficulty, cost, and oncologic adequacy. Methods: Review of PubMed, MEDLINE, Scopus, and Embase databases was conducted (January [...] Read more.
Background: Robotic pancreaticoduodenectomy (RPD) is a less invasive alternative to open pancreaticoduodenectomy (OPD) with the potential for perioperative advantage. Concerns remain regarding its technical difficulty, cost, and oncologic adequacy. Methods: Review of PubMed, MEDLINE, Scopus, and Embase databases was conducted (January 2000–October 2025), focusing on systematic reviews, meta-analyses, and significant comparative studies of RPD. Outcomes assessed were perioperative outcomes, oncologic sufficiency, learning curve, model training, cost-effectiveness, and future developments. Results: Several studies report comparable R0 rates and lymph node yield between RPD and OPD, with reduced blood loss, shorter postoperative hospital stay, and faster recovery in high-volume centers. Morbidity (35–50%) and 90-day mortality (<2%) are similar to open or laparoscopic surgery. Competence is usually achieved after 40–60 cases, while optimal outcomes are achieved after 80–100 procedures. Structured mentorship and simulation training improve safety and reproducibility. Novel technologies such as augmented reality, intraoperative fluorescence, and artificial intelligence-based navigation may also enhance accuracy and shorten the learning curve. Conclusions: RPD appears to be a safe and effective minimally invasive option in carefully selected patients if done in specialized, high-volume centers. Future studies need to resolve long-term oncologic results, cost-effectiveness, and the role of next-generation robotic systems. Full article
(This article belongs to the Special Issue State of the Art in Hepato-Pancreato-Biliary (HPB) Surgery)
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