Search Results (19,590)

Mental fatigue is an increasingly important concern among collegiate athletes whose academic–athletic roles require sustained cognitive effort, emotional regulation, and recovery across overlapping performance contexts. This structured narrative review synthesizes behavioral science, sport psychology, and athlete mental health literature to clarify how perceived stress, competitive anxiety, and psychological resilience may interact in the development and regulation of mental fatigue among collegiate athletes. Rather than treating mental fatigue as simple tiredness or an isolated performance symptom, this review conceptualizes it as a cognitive–emotional and psychobiological outcome shaped by stress appraisal, attentional load, effort regulation, and resource depletion. The main contribution of this review is to integrate previously separate lines of research into a collegiate-athlete-focused behavioral science framework in which perceived stress is positioned as an upstream appraisal-based condition, competitive anxiety as a proximal emotional mechanism, and psychological resilience as a dynamic regulatory resource that may buffer fatigue-related vulnerability. Tennis and Chinese/non-Western collegiate sport contexts are used as illustrative applications rather than exclusive empirical targets, highlighting how individual accountability, academic–athletic role demands, cultural expectations, and support structures may shape fatigue processes. This review also distinguishes established empirical evidence from theoretical inference and identifies key gaps in measurement heterogeneity, methodological transparency, longitudinal evidence, and culturally diverse collegiate athlete research. By refining the stress–anxiety–fatigue pathway and identifying resilience, recovery, and contextual support as important regulatory factors, this review provides a conceptual foundation for future empirical testing and for more targeted behavioral interventions to support collegiate athlete well-being and performance sustainability. Full article

Rapid coastal urbanization poses severe threats to biodiversity through habitat fragmentation, making continuous monitoring of urban ecosystems essential. While birds serve as sensitive bio-indicators, the long-term spatiotemporal dynamics of their habitats and temporal shifts in environmental drivers remain poorly understood in high-density megacities. This study addresses this gap by developing a trend-explainable machine learning framework to evaluate avian habitat suitability across the western coast of Shenzhen from 2010 to 2020. We applied a standardized filtering protocol to citizen science data and integrated occupancy modeling with a Random Forest algorithm to simulate habitat distributions at 30 m resolution. Spatiotemporal habitat alterations were quantified using Mann–Kendall trend analysis, while SHAP was utilized to diagnose the changing importance and non-linear thresholds of ecological drivers over the decade. Our findings reveal pronounced spatial heterogeneity among six avian guilds. Habitat quality for terrestrial birds, raptors, and songbirds degraded severely in northern industrial regions, whereas targeted ecological restoration facilitated recovery in southern and western urban cores. The analysis further demonstrates dynamic temporal shifts in environmental responses. The restrictive impact of anthropogenic stressors including population density and nighttime light weakened for terrestrial and canopy-dwelling guilds but intensified for waterfowl. Concurrently, natural elements such as vegetation coverage and proximity to water bodies became increasingly important. Based on these spatiotemporal patterns, we delineated five ecological zones to guide targeted conservation interventions. This research provides an analytical framework linking predictive modeling with mechanistic insights, supporting evidence-based biodiversity conservation and sustainable urban planning in rapidly developing coastal landscapes. Full article

This paper aims to assess the relationship between foreign direct investment (FDI) and economic development/employment rate over the period 2013–2023 for Romania, as well as for other European Union country groups (Central and Eastern Europe, Northern and Western Europe and Peripheral Europe). In this respect, we used the Panel FEGLS method adjusted with cross-section SUR and found a positive relationship between FDI and Gross Domestic Product (GDP) per capita for all panels, the strongest estimated relationship being identified for Romania (followed by the one specific to Central and Eastern European states), considering the important role of the level of economic development in shaping these differences. Regarding the relationship between FDI and employment rate, we also found positive coefficients, the highest ones being identified for Central and Eastern Europe and Romania. However, the weakest estimated relationship between FDI and GDP per capita/employment was identified for the Peripheral Europe countries. Full article

Digital transformation is increasingly viewed as a strategic driver of operational efficiency, financial performance, and organisational resilience in rural transition economies. Existing research, however, largely assumes homogeneous digitalisation effects across firms while overlooking the structural conditions shaping integration efficiency. This study investigates the threshold relationship between supply chain integration and financial–economic performance using a threshold regression framework. The analysis is based on firm-level data from 80 agricultural, agritourism, and tourism-related firms operating in rural Northern Albania. Methodologically, the study combines Hansen’s threshold estimation with robust OLS and threshold logistic regression models, complemented by exploratory macro-level threshold analysis for Western Balkan economies. The findings reveal significant regime-dependent dynamics. Below the estimated socio-economic integration threshold, supply chain integration generates weak and statistically insignificant effects. Above the threshold, integration mechanisms produce substantially stronger financial and operational outcomes, indicating that digital transformation becomes economically productive primarily under sufficiently integrated organisational conditions. Additional diagnostics further show that highly integrated firms achieve superior coordination efficiency, resource allocation, and financial resilience. The study contributes to the literature by advancing a managerial-financial and coordination-based interpretation of digital transformation and its threshold performance effects in rural transition economies. Full article

Adaptive construction techniques in traditional vernacular dwellings play an important role in improving the wind–thermal microclimate of buildings. However, comparative studies on such techniques across different regions remain limited. Moving beyond a static regional perspective, this study selects six representative skywell dwellings along the historical migration route from Jiangxi to Hunan. Through field monitoring and CFD numerical simulation using PHOENICS, the wind–thermal performance of these dwellings under extreme summer high-temperature conditions is comparatively analyzed. The results reveal case-based regional differences characterized by “shared origins and regional differentiation.” The western Jiangxi dwellings tend to adopt ventilation as the main spatial logic, using open spaces to enhance convective heat dissipation. In contrast, the northern Hunan dwellings show more prominent shading and heat control characteristics, relying on optimized skywell geometry to achieve geometric shading and reduce radiative heat gain. This study clarifies that adaptive construction techniques vary significantly under regional influences, and the findings may provide quantitative data support and design references for optimizing the microenvironment of contemporary buildings. Full article

Long-term monitoring of surface-water dynamics in hyper-arid reservoir systems requires consistent remote-sensing methods that can distinguish open water from bright desert surfaces, shallow water, wet sand, and mixed shoreline pixels. This study evaluates Landsat-derived spectral water indices for delineating surface water in Lake Nasser and the adjacent Tushka Lakes, generates a multi-decadal record of surface-water extent using Google Earth Engine, and places the resulting surface-water patterns in the context of available hydrogeological observations. Landsat TM and OLI surface reflectance imagery was used to compare seven commonly applied water indices (NDWI, EWI, NDX, WRI, AWEI_nsh, TCW, and NWI) based on mapped water area, relative area differences, and classification accuracy metrics derived from 1000 stratified reference samples. Among the tested indices, NDWI provided stable water–land separation (overall accuracy ≈ 93.6%; κ ≈ 0.898) and was selected for long-term mapping. The NDWI-based workflow was implemented in Google Earth Engine to generate quarterly composites of surface-water extent for the period 1987–2026. The resulting time series reveals stable, persistent surface water in the central and southern sectors of Lake Nasser, in contrast to pronounced seasonal and interannual variability in the shallow, intermittently connected Tushka basins. Total mapped water area increased from 2631 km² in 1987 to 8923 km² in early 2026, with Lake Nasser ranging from 2411 to 6060.7 km² and the Tushka Lakes expanding from no mapped water before 1998 to more than 3300 km² during 2025. To assess possible surface–subsurface interaction, daily lake-stage records (1965–2014) and monthly groundwater levels from 44 observation wells were used to estimate potential seepage losses from Lake Nasser to the Nubian Sandstone Aquifer System using Darcy’s law. Annual seepage estimates ranged from 15.58 × 10⁶ to 36.68 × 10⁶ m³/year, suggesting spatial variability in potential lake–aquifer seepage along the western lake margin. The combined remote-sensing and hydrogeologic results provide complementary, non-causal evidence for interpreting where surface-water persistence and estimated seepage may co-occur. Because spatial correlation analysis, calibrated ground-water modeling, full water-budget analysis, and independent field validation were not performed, the inferred seepage–surface-water relation should be regarded as a cautious hypothesis rather than proof of causality. Full article

Carbon storage dynamics in dryland and semi-arid ecosystems remain a major uncertainty in global carbon cycle assessments, particularly in regions like the Yellow River Basin (YRB). Using the Arid Ecosystem Model (AEM), we simulated the spatiotemporal evolution of four major carbon pools—total carbon (TOTC), vegetation carbon (VEGC), soil organic carbon (SOC), and litter carbon (LTRC)—from 1981 to 2060 under factorial climate scenarios. During 1981–2020, TOTC increased by 0.09 Pg C (+3.54%), driven by gains in VEGC (+0.03 Pg C, +21.43%) and SOC (+0.06 Pg C, +2.78%). LTRC showed minimal net change but was highly sensitive to interannual variability. From 2021 to 2060, under the high-emission SSP5 scenario, TOTC is projected to increase by 0.114 Pg C (+4.81%), with VEGC contributing most of the gain (+23.87%). CO₂_only simulations showed similar increases, underscoring the dominant role of CO₂ fertilization. In contrast, warming and precipitation alone produced weaker and more variable effects. Spatially, upper YRB regions are expected to maintain strong sink capacity, while the Loess Plateau and central-western subregions remain vulnerable to warming and moisture decline. LTRC exhibited the highest variability across scenarios (−18% to +22%), highlighting its role as a sensitive indicator of sink stability. These findings emphasize the need to account for nonlinear climate–carbon interactions and regional heterogeneity. Region-specific, adaptive strategies that integrate ecological restoration and climate adaptation will be critical to enhancing carbon sinks and supporting China’s carbon neutrality targets in the Yellow River Basin. Full article

Traditional grazing maintains essential ecosystem services, yet this activity is rapidly disappearing across Europe. Understanding the geobotanical features of traditionally grazed areas is critical for predicting biodiversity shifts driven by pastoral decline. This study provides a geobotanical characterisation of traditional sheep farms in north-western Spain. We integrated bioclimatic, phytosociological, and biogeographical approaches with spatial autocorrelation analyses, including global Moran’s I, Local Indicators of Spatial Association (LISA), and join-count tests, to assess spatial patterns in vegetation richness and plant community organisation. The results indicate that 28.22% of the studied farms were located in the Castilian Duero sector, 93.45% within the supramediterranean thermotype, and 75.46% within the subhumid ombrotype. A high diversity of vegetation was recorded, with 111 plant communities identified. These include several priority habitats of community interest within the European Union, notably belonging to the phytosociological classes Molinio-Arrhenatheretea, Festuco-Brometea, and Poetea bulbosae. This spatial approach characterises the vegetation mosaics within a fixed buffer around the holdings, although it does not directly measure actual forage use. As a key scientific novelty, this work provides, for the first time, a macro-regional and quantitatively validated integration that explicitly links broad environmental filters with localized pastoral vegetation mosaics. By providing a statistically robust diagnosis of landscape aggregation and segregation, this geobotanical characterisation serves as a fundamental tool for land managers and shepherds, contributing directly to the conservation and sustainable management of endangered traditional pastoral landscapes under changing environmental conditions. Full article

Background: Impaired insulin secretion by pancreatic beta cells drives chronic hyperglycemia, which characterizes type 2 diabetes mellitus. The mechanosensitive ion channel Piezo2 has been implicated in various physiological processes. However, its expression and functional role in pancreatic endocrine cells remain poorly understood. Methods: We investigated the expression, cellular localization, and potential functional significance of Piezo2 in the pancreatic islets of mice fed normal- and high-fat diets (HFD) using molecular, immunohistochemical, and immunofluorescence approaches. Results: Piezo2 mRNA and protein expression were detected in rat pancreatic tissue and the pancreatic beta cell line INS-1 via polymerase chain reaction and Western blotting analyses. Hematoxylin and eosin staining and histopathological analysis were performed to determine the localization of Piezo2, insulin, and glucagon in the islets of Langerhans from mouse pancreas. Immunofluorescence revealed that Piezo2 colocalized with insulin, glucagon, pancreatic polypeptide (PP, a pancreatic cell marker), and insulin/PP (suggesting Ppy-lineage beta cells). Piezo2 expression is significantly reduced in islets from HFD-fed mice and downregulated under high glucose conditions in INS-1 cells. Stretch stimulation, with or without D-GsMTx4 (a Piezo2-specific inhibitor), enhanced glucose-stimulated insulin secretion, whereas ruthenium red (a non-specific Piezo channel inhibitor) did not alter the response to high glucose. Conclusions: These findings demonstrate Piezo2 expression in pancreatic islets and suggest that it is enriched in beta cells and Ppy-lineage beta cells, minority in alpha cells and is responsive to metabolic stress. Although Piezo2 may contribute to beta-cell adaptation, its role in insulin secretion remains unclear. Full article

Persistent urban–rural inequality remains a major challenge for sustainable regional development, especially in countries where rural communities still face limited access to markets, employment, and public services. This study examines whether rural road network density promotes inclusive regional growth in China. Using county-level panel data from 2013 to 2024, we construct an inclusive regional growth index that combines economic output, nighttime-light-measured economic activity, rural income, and the urban–rural income gap. rural road network density is measured by the length of county, township, and village roads per 100 square kilometers. Two-way fixed-effects models, mechanism tests, robustness checks, instrumental-variable estimation, and heterogeneity analysis are employed. The results show that rural road network density significantly improves inclusive regional growth. Dimensional analysis indicates that higher rural road network density increases real GDP per capita, strengthens nighttime-light-measured economic activity, raises rural income, and reduces the urban–rural income gap. Mechanism analysis shows that these effects operate through labor mobility, market access, and non-agricultural industrial development. The results remain robust to alternative road measures, lagged specifications, outlier treatment, sample restrictions, and instrumental-variable estimation. Heterogeneity analysis further shows that the effects are larger in central-western counties, low-accessibility counties, and less-developed counties. These findings suggest that rural road network density is not only a transport infrastructure indicator but also a key spatial condition for promoting sustainable and inclusive regional development. Full article

B Dengue fever represents a significant public health challenge in Saudi Arabia, yet comprehensive molecular characterization of circulating serotypes remains limited. This study combines epidemiological and phylogenetic analyses to understand dengue virus (DENV) dynamics in the Kingdom. A systematic review and meta-analysis of dengue epidemiological data from Saudi Arabia (1992–2026) was the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. All available DENV envelope (E) gene sequences from Saudi human cases (1992–2023) were retrieved from GenBank and Global Initiative on Sharing All Influenza Data (GISAID). Phylogenetic trees were constructed using maximum likelihood with 1000 bootstrap replicates and best-fit models. Selection pressure was analyzed using SLAC, FEL, FUBAR, and MEME methods, while glycosylation sites were predicted with NetNGlyc and NetOGlyc. The pooled seroprevalence from 25 studies (n = 32,393) was 40.71% (95% CI: 26.96–56.10%). DENV-2 predominated (80.25%), followed by DENV-1 and DENV-3, with DENV-4 remaining rare (0.42%). Males (67–78%) and adults aged 25–44 years were most affected. Phylogenetic analysis of 50 Saudi isolates showed DENV-1 strains clustered within American–African (1994) and Asian (2004–2011) genotypes, all DENV-2 within the Cosmopolitan genotype, and all DENV-3 within Genotype III (bootstrap support 99–100%). Selection pressure analysis indicated pervasive positive selection in DENV-2, episodic selection across serotypes, and strong purifying selection in the E gene. Several amino acid substitutions with potential functional importance were identified. No DENV-4 E gene sequences from Saudi Arabia are publicly available. Dengue in western Saudi Arabia is characterized by DENV-2 predominance, co-circulation of three serotypes, and multiple introductions. The absence of DENV-4 sequences highlights critical surveillance gaps. Sustained molecular surveillance, expanded genomic sequencing, and data sharing are essential for effective prevention and vaccine preparedness. Full article

Background: Polycystic ovary syndrome (PCOS) is a frequently encountered endocrine disturbance with a still poorly defined etiology that arises in women during their reproductive years. Increased apoptosis of granulosa cells has been identified as one of the key factors contributing to abnormal follicular development. This study aimed to elucidate the role of six-transmembrane epithelial antigen of prostate 4 (STEAP4) in granulosa cell function using in vitro and in vivo models relevant to PCOS. Methods: We treated KGN cells (a human granulosa-like cell line) and C57BL/6 mice with dehydroepiandrosterone (DHEA) to establish experimental models mimicking PCOS features. STEAP4 expression was assessed by qRT–PCR, Western blot, and immunohistochemistry. Proliferative capacity and apoptotic rates were gauged with CCK-8 assays, EdU labeling, and flow cytometry. The regulatory mechanisms were investigated through immunofluorescence staining for nuclear factor erythroid–2–related factor 2 (Nrf2) nuclear translocation and immunoprecipitation assays for HIF-1α ubiquitination. Results: Exposure to androgen markedly raised both STEAP4 transcript and protein abundance in KGN cells as well as in PCOS model mice. STEAP4 knockdown resulted in increased proliferation and reduced apoptosis in DHEA–treated KGN cells. Mechanistically, STEAP4 enhanced reactive oxygen species levels, promoted Nrf2 nuclear translocation, and stabilized HIF–1α protein by reducing its ubiquitination, leading to increased TERT expression and subsequent TP53 pathway activation. In vivo, STEAP4 silencing significantly alleviated hormonal imbalances, estrous cycle disorders, and reduced oxidative stress levels in ovarian tissue of DHEA-induced PCOS–like mice. Conclusions: Taken together, evidence from these experimental models indicates that STEAP4 shapes oxidative stress and granulosa cell apoptosis by operating through the ROS–TERT–TP53 axis. The data point to a possible contribution of STEAP4 to PCOS pathogenesis and mark it as a candidate therapeutic target that merits additional clinical study. Full article

Chronic hyperglycemia and excessive reactive oxygen species (ROS) production are defining features of endothelial dysfunction, a key driver of diabetic vascular complications such as diabetic nephropathy. Microvesicles (MV-enriched fraction), a subtype of extracellular vesicles, and the stress-responsive antioxidant protein Sestrin2 (SESN2) have emerged as important contributors to these processes. This study investigated the role of the MV-enriched fraction in endothelial cell communication under diabetic conditions, with a particular focus on oxidative stress signaling. To model diabetic injury, EA.hy926 endothelial cells were treated with methylglyoxal (MGO), and the resulting MV-enriched fraction was isolated and then applied to two recipient models: naïve endothelial cells and SESN2 knockdown (KD) cells. Protein expression of key antioxidant markers, including endothelial nitric oxide synthase (eNOS), was assessed by Western blot. Nitric oxide (NO) bioavailability was quantified via nitrite measurement using 2,3-diaminonaphthalene (DAN), while mitochondrial and cytosolic ROS levels were evaluated using MitoSOX and dihydroethidium (DHE), respectively. Results demonstrated that the MV-enriched fraction derived from diabetic conditions triggers a complex antioxidant response in healthy endothelial cells, characterized by upregulation of SESN2, superoxide dismutase 1 (SOD1), and heme oxygenase-1 (HO-1). This suggests a compensatory mechanism that mitigates oxidative stress. Notably, SESN2 KD cells exhibited increased ROS production and reduced NO levels upon MV treatment, underscoring the essential role of SESN2 in maintaining redox homeostasis. Overall, this study highlights the dual role of the MV-enriched fraction as a mediator of both protective and detrimental redox signaling in diabetic endothelial dysfunction and suggests potential therapeutic targets for managing diabetic vascular complications. Full article

The red palm weevil, Rhynchophorus ferrugineus (Olivier, 1791), is among the most destructive pests of date palm (Phoenix dactylifera L.) globally, posing a severe and escalating threat to agricultural productivity across the Arabian Peninsula. Despite its well-documented economic impact, the potential influence of climate change on its future distributional dynamics within this region remains poorly quantified. This study employed Maximum Entropy (MaxEnt) species distribution modelling to assess current and projected habitat suitability for R. ferrugineus across the Arabian Peninsula (~3.2 million km²) under two contrasting Shared Socioeconomic Pathways (SSP1-2.6 and SSP5-8.5) for the mid-century (2050) and late-century (2070). The model was calibrated using 52 spatially thinned occurrence records and six non-collinear environmental predictors selected following Variance Inflation Factor (VIF) analysis, with sampling bias corrected through a kernel density-based background weighting approach. Model performance was robust, with mean training and test AUC values of 0.921 ± 0.023 and 0.840 ± 0.052, respectively, and a mean TSS of 0.583 ± 0.046. Precipitation of the coldest quarter (Bio 19) and precipitation seasonality (Bio 15) emerged as the most influential predictors of habitat suitability, followed by elevation. Currently, approximately 727,589.8 km² (26.11%) of the peninsula is classified as suitable habitat, concentrated along the eastern Arabian Gulf coastline and the western Red Sea plain. Under SSP1-2.6, suitable habitat is projected to expand by 16.34% and 31.60% by 2050 and 2070, respectively. Under the high-emission SSP5-8.5 scenario, expansions are considerably more pronounced, reaching 34.11% by 2050 and 60.15% by 2070, with total suitable area approaching 1,158,474.8 km² (41.58%) by late-century. Habitat contraction was negligible across all scenarios, indicating a unidirectional range expansion dynamic. These findings highlight the substantial threat posed by climate-driven habitat expansion of R. ferrugineus and provide spatially explicit projections to inform proactive biosecurity planning and pest management strategies for date palm cultivation across the Arabian Peninsula. Full article

Coastal dune ecosystems of the Moroccan Atlantic coast are among the most threatened environments of the western Mediterranean basin, yet the ecological preferences of their constituent psammophilous flora remain poorly documented. Using the ecological profile method, corrected frequencies, species and descriptor entropy, mutual information and ecological barycentres were calculated for three environmental descriptors, distance to the tidal fluctuation zone, topographic position and soil organic matter content, applied to a presence–absence matrix of 53 vascular taxa across 123 plots distributed among three dune facies. Of the total taxa inventoried, 41 were retained as ecologically active. Topography and soil organic matter emerged as the most efficient descriptors, both exceeding the 5% activity threshold. Cross-referencing of ecological groups identified three phytoecological assemblages: characteristic psammophytes of embryonic dunes, species of the primary foredune and species of the enriched backdune. The dominance of intermediate ecological amplitudes and the convergence of introduced species towards organic matter-rich backdune conditions signal chronic anthropogenic disturbance. This study provides a quantitative characterisation of psammophilous species ecological preferences and phytoecological assemblages along the coast–inland gradient of the Haouzia Bay SBEI, constituting an operational reference framework for targeted conservation and restoration management of this threatened coastal site. Full article