Search Results (1,239)

Introduction: Although gait alterations associated with excess body weight have been widely studied, most available evidence comes from laboratory-based analyses, which limit ecological validity and the translation of findings into clinical practice. This study addresses this gap by examining gait biomechanics across BMI categories using portable sensor-based insoles that allow gait assessment in real-world conditions. Methods: A cross-sectional study including 96 adults categorized as normal weight (NW), overweight (OW), or obese (OB) was conducted. Gait biomechanics were recorded using PODOSmart^® intelligent insoles, which capture spatiotemporal and angular parameters during natural walking. Foot health, quality of life and comorbildities were evaluated throught valeted questionnarires. Differences between groups were analyzed using ANOVA and chi-square tests. Age and sex, known to influence gait, were comparable across BMI groups and were considered in the interpretation of the results. Results: Overall, the participants in the OB group exhibited reduced stride length, gait speed, and swing time, increased double-support time, and greater pronation–supination and progression angles than OW and NW participants. Partial eta-squared values (η²p) were predominantly medium to large, reinforcing the robustness of these between-group differences (e.g., double-support time, p > 0.001; η²p = 0.19). Individuals with obesity reported poorer general and foot health and more difficulty finding suitable footwear. BMI was also significantly associated with hypertension, dyslipidemia, arthritis, and depression (all p <0.05), whereas diabetes, cardiopathies, knee pain, and fatigue andwalking or social activity limitations showed no significant differences. Conclusions: By using portable gait analysis technology in ecological conditions, this study provides novel evidence of clinically meaningful gait impairments across BMI groups. Higher BMI is associated with clinically relevant gait impairments, poorer perceptions of foot and general health, and a higher prevalence of several comorbidities. Full article

Marine mucilage events are intensifying in semi-enclosed seas under accelerating climate- and nutrient-driven pressures, yet their ecosystem-level consequences for aquaculture-linked coastal habitats remain insufficiently documented. This study provides an integrated spatiotemporal assessment of water quality, phytoplankton community structure, and biometric responses of Mytilus galloprovincialis during and after the 2025 mucilage outbreak in the Gulf of Erdek (Sea of Marmara, Türkiye). Mucilage accumulation was associated with sharp increases in turbidity, total suspended solids, and particulate organic matter, alongside declines in dissolved oxygen and pH. Phytoplankton assemblages exhibited marked seasonal restructuring: the mucilage period was characterized by the coexistence of mucilage-forming taxa, non-toxic bloomers, and multiple harmful algal bloom (HAB) groups, including DSP- and ASP-related species, whereas post-mucilage conditions were dominated by non-toxic diatoms with substantially reduced HAB representation. The dinoflagellate species representing the May period in terms of abundance were Noctiluca scintillans and Prorocentrum micans; the diatom species were Chaetoceros radiatus, Cylindrotheca closterium, Pseudo-nitzschia pseudodelicatissima, and Thalassiosira rotula; and the coccolithophore was Phaeocystis pouchetii. Mussel biometric analyses revealed biometric indices and condition values markedly below regional historical baselines during the mucilage event, alongside reduced meat yield, followed by pronounced compensatory growth during the post-mucilage period. Our findings demonstrate that mucilage acts as both a physical and biological stressor, driving short-term ecological shifts in phytoplankton diversity and imposing substantial but reversible physiological impacts on mussel stocks. These results underscore the need for continuous biodiversity monitoring frameworks that integrate mucilage dynamics, HAB occurrence, and aquaculture resilience in regions vulnerable to climate-enhanced organic aggregate formation. Full article

Background: This study aimed to evaluate the effects of NP associated with LDD on balance, gait and foot pressure distribution. Methods: This prospective controlled study was conducted on 42 individuals aged between 40-70 years. There were 3 groups in the study: individuals diagnosed with NP associated with LDD (n=14), individuals with LDD without NP(n=14), and the control group (n=14). The Force Plate system and Core Balance System measured static and dynamic postural balance and stability limits. Gait and dynamic plantar pressure distribution analyses were performed with a computerized gait evaluation system. Results: The Leeds Assessment of Neuropathic Signs and Symptoms (LANSS), VAS during gait, and Oswestry Disability Index (ODI)scores were higher in LDD with NP group than in LDD without NP group (p<0. 05). It was found that LDD with NP group had backward dynamic balance control (p<0. 05). There was no significant difference in balance control, dynamic plantar pressure distribution, and spatiotemporal gait parameters between the groups (p>0. 05). Conclusion: Although participants with NP had higher levels of pain severity in gait and disability, there was no difference in postural balance, dynamic plantar pressure distribution, and spatiotemporal gait parameters compared to participants with LDD without NP and healthy individuals. All participants with LDD were unilaterally affected. Therefore, postural balance and gait tasks would be able to compensate for the unaffected limb. Full article

Using a coordinated multi-year monitoring dataset collected during the 2020–2024 partial-opening management period, we examined benthic diatom assemblages across the Sejong, Gongju, and Baekje weirs in the Geum River, Republic of Korea. Seasonal surveys at eight stations were used to evaluate spatiotemporal variation in water quality and benthic diatom community structure under this hydrological management regime. Annual basin-wide averages showed gradual interannual changes in water quality, including declines in total phosphorus, total nitrogen, chlorophyll-a, turbidity, and biochemical oxygen demand after 2021, accompanied by increased dissolved oxygen. Diatom community indices based on relative-abundance data showed corresponding temporal variation, with decreased dominance and increased Shannon diversity, evenness, and taxon richness. Ordination analyses indicated gradual differentiation between the earlier (2020–2021) and later (2022–2024) monitoring groups within the study period, whereas random forest models showed limited explanatory power and were treated as exploratory. Overall, the results support benthic diatoms as sensitive descriptors of ecological change in flow-regulated monsoonal rivers while underscoring the value of long-term monitoring where true pre-intervention biological baselines are unavailable. Full article

This study systematically examines the low-carbon transition challenges faced by the Yellow River Basin, a core strategic energy base in China with a coal-dominated energy system, under the dual carbon goals. Existing studies based on traditional econometric models or single-province analyses are mostly limited to static analysis, failing to simultaneously capture the nonlinear spatiotemporal evolution, cross-regional spillover effects, and long-term changing trends of carbon emissions in the basin. To fill this gap, this study builds an Energy–Economy–Carbon (EEC) analytical framework, and develops an integrated TFT-ASTGCN deep learning framework. Specifically, we employ the Temporal Fusion Transformer (TFT) for high-precision multivariate time-series simulation and peak forecasting, while the Attention-based Spatial–Temporal Graph Convolutional Network (ASTGCN) is used to identify complex spatial dependencies of inter-provincial emissions. The empirical results confirm that: (1) Basin carbon emissions show significant coal-driven carbon lock-in, with initial decoupling between economic growth and emissions. (2) Most provinces will maintain rising emissions under the current development mode, posing severe challenges to carbon peaking. (3) Asymmetric spatial spillover effects are prominent, underscoring cross-regional collaborative governance as a critical pathway for achieving an early and stable carbon peak in the basin. Full article

The European Middle Pleistocene represents a critical spatiotemporal interval in human evolution, marked by increasing morphological variability and ongoing debate regarding the evolutionary processes leading to the emergence of Neandertals. In particular, it remains unclear whether this variability reflects the coexistence of multiple evolutionary lineages within Europe or structured variation within a single, evolving lineage. Within this context, the site of Bilzingsleben (Thuringia, Germany) provides a key contribution to discussions of European Middle Pleistocene population structure. This study presents a detailed morphological assessment of the Bilzingsleben E7 mandibular fragment, integrating qualitative anatomical observations with quantitative analyses of discrete characters. The Bilzingsleben mandible was examined directly and evaluated within a broad comparative framework including European Middle Pleistocene hominins, Neandertals, and selected African and Asian specimens. Multivariate analyses, including Principal Coordinates Analysis (PCoA) and neighbor-joining cluster analysis based on Gower distances, were used to explore patterns of morphological affinity. Qualitative analysis indicates that the Bilzingsleben mandible exhibits a mosaic combination of predominantly primitive features—such as multiple mental foramina, marked lateral relief of the corpus, and a weakly developed submandibular fossa—together with a limited number of incipiently derived traits, including posterior extension of the corpus and a downward orientation of the digastric fossae. Quantitative results consistently place Bilzingsleben within the morphological variability of European Middle Pleistocene hominins but outside the compact Neandertal cluster. In the PCoA, Bilzingsleben occupies an intermediate (PCo1) and peripheral position (PCo2), contrasting with more centrally positioned specimens such as Mauer. Taken together, these results support an interpretation of Bilzingsleben as part of a European Middle Pleistocene set of populations exhibiting mosaic morphology, rather than considering Bilzingsleben as evidence for a distinct evolutionary lineage. When integrated with evidence from other anatomical elements from Bilzingsleben, the mandibular morphology supports interpreting this population within the broader evolutionary context of the Neandertal lineage. Full article

A vital region for China’s water resource storage and ecological balance maintenance, the Yangtze River Basin is strategically significant for maintaining regional water security and promoting long-term social and economic development. Precipitation is the main driver of the hydrological cycle. In order to address current problems with the basin’s ecological environment and water supplies, comprehensive analyses of multi-source precipitation data are necessary. They provide an essential scientific basis for evaluating the sustainability of water resources in the Yangtze River Basin in the context of climate change. Most existing precipitation fusion studies utilize only a limited number of datasets and do not fully consider the independence among different data sources, which leads to less-than-ideal fusion accuracy and assessment metrics. This paper employs the Triple Collocation (TC) method to evaluate and fuse multiple precipitation datasets over a 19-year period from 2003 to 2021, with the aim of enhancing precipitation accuracy in the Yangtze River Basin. The Multi-Source Weighted-Ensemble Precipitation (MSWEP) precipitation data were found to have the highest accuracy among seven datasets, with a Correlation Coefficient (CC), Relative Bias (Rbias), and Root Mean Square Error (RMSE) of 0.907, −0.027, and 25.930 mm, respectively. The “MSWEP–PERSIANN–NOAH (MPN)” fusion was shown to be the best using the Multiplicative Triple Collocation (MTC) method in conjunction with cross-error analysis. Compared to MSWEP alone, it improved CC by 0.8% and decreased RMSE by 3.8%, with matching spatial-grid CC and RMSE improvements of 1.2% and 1.8%, respectively. Further spatiotemporal analysis of the fused data increase detection capabilities for short-term flood and waterlogging occurrences and provide better knowledge of basin water-resource status. Full article

Crop production, nitrogen use efficiency (NUE), and environmental footprint are not only of great significance for ensuring food security, but also serve as key determinants for achieving the integrated governance of agricultural development and environmental protection. However, Iran is currently facing challenges such as production in an arid climate and on degraded land, low NUE, and associated ecological and environmental pollution. Current agricultural nitrogen (N) management research is mostly limited to single crops or dimensions, leaving a gap in integrated multi-crop, multi-dimensional spatiotemporal analyses and grid-scale high-resolution spatial assessments of regional heterogeneity. Therefore, from the perspectives of food, resources, and the environment, this study systematically assessed the sown area, yield, N application rate, NUE, N surplus, and greenhouse gas emissions (GHG emissions) of six major crops (wheat, rice, barley, maize, sugarcane, and cotton) in Iran for the years 2000, 2010, and 2020. The aim was to assess the current status and spatiotemporal evolution of cropland N management in Iran. The results of this study indicate that the total N application rate in Iranian cropland exhibited an overall upward trend from 2000 to 2020, increasing from 1.095 × 10⁶ t to 1.1937 × 10⁶ t over this period. The NUE improved in some regions but remained generally low, increasing from 31.7% to 41.8%. Provinces in northern and southern Iran were characterized by high N application rates, low NUE (20–40%), substantial N surplus accumulation, and high GHG emissions. The multi-dimensional comprehensive assessment framework proposed in this study provides a scientific basis for N management in regions aiming for coordinated governance of food security and the ecological environment. Full article

CAR-T cell therapy has shown substantial efficacy in haematological malignancies, but its application to solid tumours remains limited by poor effector-cell infiltration, functional exhaustion, antigenic heterogeneity, and an immunosuppressive microenvironment. In this study, we develop a new spatiotemporal mathematical model of CAR-T therapy for solid tumours that integrates these resistance mechanisms within a single reaction–diffusion framework. The model is formulated as a system of partial differential equations describing functional and exhausted CAR-T cells, antigen-positive and antigen-low tumour subpopulations, and chemokine, immunosuppressive, and hypoxic fields. Steady-state analysis and finite-difference simulations showed that therapeutic outcome is governed by the interplay between CAR-T cell infiltration, exhaustion, and antigen escape. The model reproduces partial tumour regression followed by residual tumour persistence, therapy-driven enrichment of antigen-low cells, and reduced efficacy under stronger immunosuppressive and hypoxic conditions. In the combination therapy scenario considered here, repeated simulated CAR-T cell administration together with attenuation of the suppressive microenvironment improves tumour control. The proposed model provides a mechanistic basis for analysing resistance and for future optimisation studies of CAR-T therapy in solid tumours. Full article

The forest understory litter fraction $\left({\mathrm{F}\mathrm{V}\mathrm{C}}_{\mathrm{y}}\right)$ is a critical indicator for evaluating the effectiveness of “understory erosion” control in red soil regions; however, its high-precision, large-scale monitoring remains challenging due to canopy occlusion. This study proposes an ${\mathrm{F}\mathrm{V}\mathrm{C}}_{\mathrm{y}}$ inversion framework that integrates high-spatial-resolution Sentinel-2 imagery with multi-angular prior knowledge from MODIS BRDF products. First, a linear mapping model between multi-band reflectances at 0° and 45° view angles was constructed using 500 m MODIS MCD43A1 products $(R^2>0.8)$. This model was subsequently employed as a physical prior for anisotropic characterization and transferred to 10 m Sentinel-2 imagery to generate a long-term, dual-angle reflectance dataset. Subsequently, the four-scale geometric-optical model was utilized to decouple canopy and understory background signals, followed by quantitative ${\mathrm{F}\mathrm{V}\mathrm{C}}_{\mathrm{y}}$ inversion using a pixel-based dimidiate model. Validation results confirmed the reliability of the framework $(R^2=0.74, RMSE=0.1073)$. Spatiotemporal evolution analysis indicated a significant upward trend in ${\mathrm{F}\mathrm{V}\mathrm{C}}_{\mathrm{y}}$ across Changting County from 2016 to 2025, with over 90% of the area showing improvement. The proportion of high-coverage areas $({\mathrm{F}\mathrm{V}\mathrm{C}}_{\mathrm{y}}>0.75)$ increased from 10% to 38%, exhibiting a “high in the center, low in the periphery” spatial pattern that aligns closely with core ecological restoration zones. Stability and persistence analyses further revealed that 61.18% of the study area reached moderate-to-high stability, and 70% of pixels exhibited a “positive persistence-improvement” trend, highlighting a pronounced inertia-driven enhancement in ecological recovery. This study provides a refined technical pathway for assessing soil and water conservation benefits in red soil regions. Full article

Understanding the spatiotemporal streamflow patterns under future climate scenarios is critical for sustainable water resource management in large river basins. This study applied the Soil and Water Assessment Tool (SWAT), forced by five downscaled and bias-corrected CMIP6 global climate models, to evaluate historical (2008–2024) and future (2025–2049) streamflow patterns in the Missouri River Basin in the continental United States. Model calibration and validation were satisfactory, with NSE > 0.5, KGE ≥ 0.5, R² > 0.5, and PBIAS within ±25% at most USGS gauge stations. Future projections indicate spatially and temporally variable hydrological responses: The upper basin (Bismarck, North Dakota) is projected to experience lower flows across most percentiles and reduced extreme events, whereas the lower basin (Hermann, Missouri) shows decreased median flows but higher extremes. Recurrence interval analysis of 2-, 5-, 10-, 50-, 100-, and 500-year flows suggests that 100-year flows may decline by 11% at Bismarck and increase by 37.4% at Hermann. These results highlight the importance of integrating percentile-based and extreme event streamflow analyses with hydrologic modeling for assessing the spatiotemporal streamflow patterns under future climate scenarios in large-scale basins. Quantitative insights into future streamflow variability and its implications for flood risk mitigation, water resources management, and adaptive strategies were gained for one of North America’s largest river systems. Full article

Increasing agricultural productivity is vital for global food security, but it poses significant risks to aquatic ecosystems through diffuse pollution. As Türkiye aims to harmonise its agricultural policies with the European Green Deal, quantifying agricultural non-point-source pollution (ANPSP) is essential for sustainable water management. This study evaluates ANPSP loads, including Total Nitrogen (TN), Total Phosphorus (TP), Chemical Oxygen Demand (COD), and Ammonia Nitrogen (NH₃-N), originating from cereal production, fertiliser application, and livestock farming across Türkiye from 2015 to 2024. By employing activity data and pollution load coefficients, the spatiotemporal dynamics of ANPSP were analysed at both national and regional levels. The results demonstrate that cereal production is the predominant source of nutrient loading (60.5% TN, 64.9% TP), whereas livestock activities account for 52.2% of the COD load. Fertiliser use contributed 23.0% and 20.6% to TN and TP loads, respectively. The Marmara, Aegean, and Central Anatolia regions were identified as high-intensity pollution hotspots. These findings provide a robust baseline for developing region-specific mitigation strategies, such as precision fertilisation and circular waste-to-energy systems, to support Türkiye’s transition toward a Zero-Pollution and sustainable agricultural future. Full article

Amid the accelerating global green transition, urban Low-Carbon Sustainable Development (LCSD) has emerged as a critical governance challenge. Despite a growing body of research on low-carbon initiatives, the role of local governments in shaping urban LCSD outcomes remains inadequately explored. To address this gap, this study develops a resource–pressure analytical framework that systematically examines how local governments’ resource endowments and pressures jointly condition LCSD. Drawing on panel data from 262 Chinese cities spanning the period 2011–2021, we construct city-level composite indicators of LCSD performance and investigate the underlying driving mechanisms through a combination of statistical analyses and geographically and temporally weighted regression. Our findings yield three principal insights: (1) although overall LCSD has progressed steadily, inter-regional disparities have widened, characterized by persistent structural misalignments and a discernible shift in spatial clustering from the northeast toward southeastern coastal regions; (2) supervisory pressure and economic resources consistently emerge as the most robust and influential determinants of LCSD; and (3) both resource-based and pressure-based drivers display significant spatiotemporal heterogeneity: economic and technological resources exert particularly strong effects in the northwest and central-west regions, respectively, while policy pressures generate differentiated impacts across cities. This research contributes to the theoretical refinement of low-carbon governance frameworks and furnishes robust empirical evidence to inform context-sensitive and regionally differentiated policy design. Full article

High-precision wind power prediction improves grid stability and reduces curtailment losses. Existing methods face three limitations: static graphs cannot capture dynamic spatial correlations under weather changes, time series models miss multi-scale temporal features, and frequency-domain analyses lack physical constraints. We propose: (1) a dynamic distance correlation weighted graph that adaptively combines geographic and power correlations for weather–terrain coupling; (2) a spatio-temporal-frequency fusion framework integrating graph networks, bidirectional GRUs, and a patchwise sparse time–frequency module; (3) a turbine power curve-constrained frequency mixer for physical consistency. On the SDWPF dataset, our model achieves MAE reductions of 37.47–43.32% and RMSE reductions of 37.93–42.70% versus baselines, outperforming state-of-the-art methods. The approach demonstrates superior performance in complex spatio-temporal scenarios. Full article

Climate extremes are major constraints on agricultural productivity, especially in tropical regions experiencing rapid expansion and intensification of soybean agriculture. This study analyzes spatiotemporal changes in soybean yields in response to droughts and heatwaves across highly productive municipalities in Brazil’s five macroregions from 1989 to 2020. By combining high-resolution meteorological data, satellite-based evapotranspiration estimates, and municipal-level crop yield data, we used standardized drought indices (Standardized Precipitation Index [SPI], Standardized Precipitation Evapotranspiration Index [SPEI]) and a heat index (Warm Spell Duration Index [WSDI]) with spatiotemporal linear regression analyses to explore the links between climate variability and soybean yields across Brazil’s diverse agroclimatic zones. The results show a clear rise in the frequency and severity of compound drought–heat events, especially in the Northeast and South frontiers, where yield sensitivity to hydroclimatic stress is highest. Municipal-level linear regression analyses and spatial patterns indicate that short-term dry events, rather than long-term climate trends, are the main drivers of recent yield variability, with notable spatial spillover effects observed across municipalities. Cristalina and Bom Jesus, for example, exhibit significant negative trends (p < 0.05) in both SPEI-6 (−0.04 and −0.03) and SPI-6 (0.04 and −0.03), indicating a consistent drying tendency over time. Over the 30-year period, municipalities accumulated total soybean yield losses of 3292.3 thousand tonnes (kt), corresponding to an average reduction of 3.7% relative to 5-year detrended yield. These findings highlight the increasing vulnerability of rainfed agriculture in Brazil and emphasize the critical role of seasonal timing, crop phenology, and regional climate patterns for effective climate risk management. This study provides empirical evidence linking combined extremes to agricultural performance and presents a scalable framework for early warning systems and for climate-resilient policy development. Full article