Search Results (1,543)

Water and soil resources (WSRs) determine the healthy development of the socio-economic systems. This research seeks to clarify the spatiotemporal evolution characteristics, spatial spillover effects, and key constraint factors influencing the comprehensive carrying capacity (CCC) of WSR in the Yellow River (YR) Basin from 2012 to 2023, thereby supporting the healthy development of the river basin. Based on the structural relationships among the internal elements of this system, the entropy method and an extensible cloud model are employed in this study to evaluate the WSR-CCC. Based on the estimation theory and spatial econometrics methods, the temporal and spatial evolution process of WSR-CCC was explored, and the obstructive factors were analyzed. We made the following discoveries: (1) The WSR-CCC demonstrates a fluctuating upward tendency, gradually moving from critical overload level IV to sustainable level II, but inter-provincial disparities expand. (2) The spatial pattern exhibits a gradient of higher levels in the western region, lower levels in the eastern region, stronger intensity in the northern region, and weaker intensity in the southern region, with weak spatial correlation. However, the spatial spillover effect is significant, with club convergence and the Matthew effect coexisting. (3) The obstacle factors exhibit a drive–influence–state three-stage dominant characteristic. The findings provide actionable insights for coordinating WSR optimization and ecological conservation. Full article

Art intervention has emerged as an innovative pathway for community regeneration, significantly enhancing physical and socio-economic conditions, yet its specific impacts on community resilience remain underexplored. This study proposes an evaluation framework that integrates the BRIC community resilience model with key dimensions of art intervention. Taking three typical art villages in suburban Beijing (Feijia, Xiaopu, and Xinzhuang) as cases, 452 questionnaires were conducted. The coupling and coordination model was used to analyze interactions between subsystems, and the obstacle factor model was employed to identify barriers to their synergistic development. The results show that: (1) There is a significant positive correlation between the degree of art intervention and community resilience. (2) The coupling and coordination degree exhibits distinct stage differentiation, with art intervention directly affecting its level. Xiaopu Village has the highest coupling and coordination degree (0.8004), followed by Xinzhuang Village (0.6914) and Feijia Village (0.6400). (3) Key obstacles include participation in art activities (9.2%), influence of interactions (9.0%), cultural literacy (8.5%), use of art spaces (7.2%), and industrial influence (6.3%). This study establishes a novel theoretical framework for the synergy between art intervention and community resilience, offering practical strategies for sustainable urban village revitalization. Full article

Thyroid carcinomas are phenotypically heterogeneous malignancies. Advances in molecular and cellular technologies have revealed genetic, epigenetic, and nongenetic factors underlying this heterogeneity. Our study aimed to assess the impact of single and combined treatments with anticancer agents (Carboplatin, Doxorubicin, Paclitaxel, Avastin), natural compounds (Quercetin), and epigenetic modulators (suberoylanilide hydroxamic acid and 5-Azacytidine) on the expression of long noncoding RNAs, methylation regulators, and functional features in the human thyroid cancer cell line K1. Methods: Treated and untreated K1 cells were used throughout experiments to evaluate the drug-induced cytotoxicity, apoptosis, cell cycle distribution, cytokine release, gene expression, and global DNA methylation levels. Results: Some single- and combined-drug treatments modulated both cell cycle progression and apoptotic events, demonstrating anti-tumor activity of the tested compounds. Gene expression analysis showed treatment-specific regulation of target genes and lncRNAs, including both upregulation and downregulation across different drug combinations. All treatments resulted in increased global DNA methylation levels compared to the untreated controls. Several combinations significantly upregulated DNMT1 and DNMT3B, while concomitantly decreased EZH2 levels. Conclusions: These coordinated epigenetic changes highlight the therapeutic potential of combining epigenetic modulators with chemotherapeutic agents, suggesting a strategy to prevent or reverse treatment resistance and improve outcomes in thyroid cancer patients. Full article

An ethyl acetate extract from the deep-sea bacterium Galbibacter orientalis strain ROD011 (GOEE), collected from international waters, was investigated as a potential anti-inflammatory agent. In lipopolysaccharide (LPS)-stimulated murine macrophages, nitric oxide (NO) production fell by 72–87% at 5–20 µg/mL GOEE without detectable cytotoxicity. Cyclooxygenase-2 (COX-2 protein abundance decreased in a dose-dependent manner and was nearly absent at 20 µg/mL. In zebrafish embryos, survival was maintained up to 40 µg/mL, and LPS-induced signals were attenuated; the cell-death rate declined from 10 µg/mL onward, and at 20 µg/mL GOEE, reactive oxygen species (ROS) and NO decreased by 85% and 27%, respectively. To explain these effects, untargeted metabolomics with pathway enrichment and network mapping were performed in LPS-driven macrophages. Of the 58 KEGG pathways evaluated, 18 reached significance, notably purine and pyrimidine metabolism, vitamin B6 metabolism, and the one-carbon pool via folate. Coordinated shifts also involved amino-acid/tricarboxylic acid (TCA)-cycle linkages, glutathione and glyoxylate/dicarboxylate, and sphingolipid pathways. Network analysis identified hubs that were concomitantly reprogrammed. Collectively, GOEE achieved multi-level suppression of inflammatory outputs while preserving viability, and the metabolomic signature provides a mechanistic scaffold for its action. These findings nominate a deep-sea microbial extract as a promising anti-inflammatory lead and motivate fractionation and targeted validation of the highlighted metabolic nodes. Full article

Understanding the multidimensional sources and key drivers of differences in green transition performance (GTP) among resource-based cities is vital for accomplishing national sustainable development objectives and facilitating regional coordination. This study proposes a “Carbon Reduction–Pollution Control–Greening–Growth” evaluation framework and utilizes the entropy method to assess the GTP of China’s resource-based cities from 2013 to 2022. The Dagum Gini coefficient and variance decomposition methods are employed to investigate the GTP differences, and the Optimal Parameters-Based Geographical Detector and the Geographically and Temporally Weighted Regression model are applied to identify the driving factors. The results indicate the following trends: (1) GTP exhibits a fluctuating upward trend, accompanied by pronounced regional imbalances. A pattern of “club convergence” is observed, with cities showing a tendency to shift positively toward adjacent types. (2) Spatial differences in GTP have widened over time, with transvariation density emerging as the dominant contributor. (3) Greening differences represent the primary structural source, with an average annual contribution exceeding 60%. (4) The impact of digital economy, the level of financial development, the degree of openness, industrial structure, and urbanization level on GTP differences declines sequentially. These factors exhibit notable spatiotemporal heterogeneity, and their interactions display nonlinear enhancement effects. Full article

To achieve a complete circular economy for used electric vehicle batteries, it is essential to implement a disassembly step. Given the significant diversity of battery geometries and designs, a high degree of flexibility is required for automated disassembly processes. The incorporation of human–robot interaction provides a valuable degree of flexibility in the process workflow. However, human behavior is characterized by unpredictable timing and variable task durations, which add considerable complexity to process planning. Therefore, it is crucial to develop a robust strategy for coordinating human and robotic tasks to manage the scheduling of production activities efficiently. This study proposes a global optimization approach to the scheduling of production activities, which employs a genetic algorithm with the objective of minimizing the total production time while simultaneously reducing the idle time of both the human operator and robot. The proposed approach is concerned with optimizing the sequencing of disassembly tasks, considering both temporal and exclusion constraints, to guarantee that tasks deemed hazardous are not executed in the presence of a human. This approach is based on a two-level adaptation framework developed in RoboDK (Robot Development Kit, v5.4.3.22231, 2022, RoboDK Inc., Montréal, QC Canada). At the first level, offline optimization is performed using a genetic algorithm to determine the optimal task sequencing strategy. This stage anticipates human behavior by proposing disassembly sequences aligned with expected human availability. At the second level, an online reactive adjustment refines the plan in real time, adapting it to actual human interventions and compensating for deviations from initial forecasts. The effectiveness of this global optimization strategy is evaluated against a non-global approach, in which the problem is partitioned into independent subproblems solved separately and then integrated. The results demonstrate the efficacy of the proposed approach in comparison with a non-global approach, particularly in scenarios where humans arrive earlier than anticipated. Full article

Agricultural green development cannot be achieved without effective financial support. Based on panel data from 30 provinces in China from 2014 to 2023, this paper uses a coupling coordination model to measure and analyse the degree of coordination between digital inclusive finance and green finance; this further constructs a comprehensive evaluation system for agricultural green development, and on this basis uses a fixed-effect model and a threshold regression model to systematically examine the impact of the coordination between the two on agricultural green development. The findings are as follows: first, the coordination between digital inclusive finance and green finance shows an upward trend over time, shifting spatially from a high trend in the east to a low trend in the west to regional convergence; second, the coordination between the two has a substantial and favourable impact on green agricultural development, which is a conclusion that persists after robustness tests; third, the effect is heterogeneous, with more pronounced promotion effects in non-grain-producing regions, regions with high agricultural technology levels, and low levels of financial exclusion; fourth, the effect exhibits nonlinear characteristics, with coordination and agricultural industrial agglomeration each forming a single-threshold effect. This research lays down a foundational framework for financial coordination in supporting agricultural green development. It suggests promoting a dual-wheel coordination mechanism to effectively empower agricultural green development by strengthening technological empowerment, regional linkage, and designing differentiated policies. Full article

The interactive coupling mechanism between ecosystem service value (ESV) and urbanization has emerged as a critical research focus in ecological security and sustainable development. This study quantifies the ESV of prefecture-level cities by leveraging remote sensing data and socioeconomic statistics from the Yangtze River Delta (YRD) region spanning 2006—2020. It constructs a multidimensional evaluation index system for urbanization. We systematically assess both systems’ spatiotemporal evolution and interactions by employing entropy weighting, comprehensive indexing, and coupling coordination models. Furthermore, Geo-detectors and Geographical and Temporal Weighted Regression (GTWR) models are applied to identify driving factors influencing their coordinated development. Key findings include (1) the total amount of ESV in the YRD exhibits a fluctuating decline, primarily due to a steady increase in urbanization levels; (2) the coordination degree between ESV and urbanization demonstrates phased growth, transitioning to a “basic coordination” stage post-2009; (3) spatially, coordination patterns follow a “core–periphery” hierarchy, marked by radial diffusion and gradient disparities, with most cities being of the ESV-guidance type; (4) GTWR analysis reveals spatiotemporal heterogeneity in driving factors, ranked by intensity as Normalized Difference Vegetation Index (NDVI) > Economic density (ECON) > Degree of openness (OPEN) > Scientific and technological level (TECH) > Industrial structure upgrading index (ISUI) > Government investment efforts (GOV). This study advances methodological frameworks for analyzing ecosystem–urbanization interactions in metropolitan regions, while offering empirical support for ecological planning, dynamic redline adjustments, and territorial spatial optimization in the YRD, particularly within the Ecological Green Integrated Development Demonstration Zone. Full article

Affordable housing development is an important livelihood project for promoting the harmonious development of the urban economy and society. However, the unclear spatial–temporal characteristics of the affordable housing market and urban development are not conducive to the promotion of regional urban sustainable development. Hence, it is of great significance to research the interaction characteristics between the affordable housing market and urban development to promote sustainable development. This study constructed an evaluation index system, coupling coordination model, and spatial econometric model of the affordable housing market and urban development to analyze the development level and spatial-temporal characteristics of coupling coordination between the two systems in 70 large- and medium-sized cities in China from 2010 to 2020. The results show the following: (1) From 2010 to 2020, the development levels of the affordable housing market and urban development rose with obvious regional differences. The development of the affordable housing market and urban development had the characteristics of spatial similarity and common development trends in the horizontal distribution and kernel density aggregation distribution. (2) The coupling coordinated development level of the affordable housing market and urban development in 70 large- and medium-sized cities in China from 2010 to 2020 was generally low, showing an increasing trend year by year, with significant regional differences. The coupling coordination level of the two systems in the eastern region was much higher than those in the central, western and northeastern regions. The spatial distribution characteristics showed a spreading trend from a high level in the east to a low level in the west. The coupling coordination development levels of the two systems had obvious positive spatial correlation characteristics. There were obvious differences in the coupling coordination development level of the two systems between the cities, which need to be comprehensively improved through interactions between the cities. Full article

Background/Objectives: This study aimed to objectively assess fatigue levels using facial expressions. Methods: This study included 25 female nurses aged between 30 and 50 years. We compared their subjective and objective fatigue levels after a night shift, when accumulated fatigue was assumed, with those after a day off, when recovery was expected. Fatigue levels were subjectively assessed using questionnaires and were also quantified by the Visual Analog Scale (VAS). Objective evaluations included (1) the degree of eye-opening, (2) the maximum distance and speed of facial skin movement by tracking changes in coordinate values of facial markers on the skin during intentional smiling, and (3) analysis of high-frequency (HF) components and the low frequency-to-high frequency (LF/HF) ratio in heart rate variability (HRV). Results: After a night shift, compared to after a day off, subjective assessments of mental and physical fatigue in the questionnaires and VAS values of own fatigue were significantly elevated. Concurrently, objective evaluations revealed that the degree of eye-opening, along with the maximum movement distance and speed of the lower eyelid, cheek, and mouth corners during intentional smiling, were significantly reduced. Furthermore, the HF component, an index of parasympathetic activity, significantly decreased, whereas the LF/HF ratio, an index of sympathetic activity, significantly increased. Additionally, significant correlations were observed between subjective VAS estimation of fatigue levels and each objective parameter examined. Conclusions: Measuring facial parameters is an effective method for objectively assessing facial expressions of fatigue, and these changes are mediated through reduced parasympathetic nervous activity and increased sympathetic nervous activity during fatigue. Full article

As a major energy producer and consumer, China has witnessed rapid growth in carbon emissions, which are closely linked to changes in regional climate and the environment. Water, energy, and food (W-E-F) are the three most critical components of human production and daily life, and achieving the coordinated development of these three resources and connecting them with climate change through the carbon emissions generated during their utilization processes has become a key issue for realizing regional ecological sustainable development. This study constructs a dynamic two-stage network slack-based measure-data envelopment analysis (SBM-DEA) model, which integrates the water–energy–food (W-E-F) system with the climate change process to evaluate China’s comprehensive ecological efficiency from 2011 to 2022, and adopts the Dagum Gini coefficient decomposition, kernel density estimation, hierarchical clustering, and geographical detector model to analyze provincial panel data, thereby assessing efficiency patterns, regional differences, and driving mechanisms. The novelty and contributions of this study can be summarized in three aspects. First, it establishes a unified framework that incorporates the W-E-F nexus and climate change into a dynamic network SBM-DEA model, enabling a more systematic assessment of ecological efficiency. Second, it uncovers that interregional overlap effects and policy-driven factors are the dominant sources of spatial and temporal disparities in ecological efficiency. Third, it further quantifies the interactive effects among key driving factors using Geodetector, thus offering practical insights for regional coordination and policy design. The results show that China’s national ecological efficiency is at a medium level. Southern China has consistently maintained a leading position, while provinces in northwest and southwest China have remained relatively backward; the efficiency of the water–energy–food integration stage is relatively high, whereas the efficiency of the climate change stage is medium and exhibits significant temporal fluctuations. Interregional differences are the main source of efficiency gaps; ecological quality, environmental protection efforts, and population size are identified as the primary driving factors, and their interaction effects have intensified spatial heterogeneity. In addition, sub-indicator analysis reveals that the efficiency related to total wastewater, air pollutant emissions, and agricultural pollution shows good synergy, while the efficiency associated with sudden environmental change events is highly volatile and has weak correlations with other undesirable outputs. These findings deepen the understanding of the water–energy–food-climate system and provide policy implications for strengthening ecological governance and regional coordination. Full article

Graphite nodularity is a key indicator for evaluating the microstructure quality of ductile iron and plays a crucial role in ensuring product quality and enhancing manufacturing efficiency. Existing research often only focuses on a single type of feature and fails to utilize multi-source information in a coordinated manner. Single-feature methods are difficult to comprehensively capture microstructures, which limits the accuracy and robustness of the model. This study proposes a hybrid estimation model for the graphite nodularity of ductile cast iron based on multi-source feature extraction. A comprehensive feature engineering pipeline was established, incorporating geometric, color, and texture features extracted via Hue-Saturation-Value color space (HSV) histograms, gray level co-occurrence matrix (GLCM), Local Binary Pattern (LBP), and multi-scale Gabor filters. Dimensionality reduction was performed using Principal Component Analysis (PCA) to mitigate redundancy. An improved watershed algorithm combined with intelligent filtering was used for accurate particle segmentation. Several machine learning algorithms, including Support Vector Regression (SVR), Multi-Layer Perceptron (MLP), Random Forest (RF), Gradient Boosting Regressor (GBR), eXtreme Gradient Boosting (XGBoost) and Categorical Boosting (CatBoost), are applied to estimate graphite nodularity based on geometric features (GFs) and feature extraction. Experimental results demonstrate that the CatBoost model trained on fused features achieves high estimation accuracy and stability for geometric parameters, with R-squared (R²) exceeding 0.98. Furthermore, introducing geometric features into the fusion set enhances model generalization and suppresses overfitting. This framework offers an efficient and robust approach for intelligent analysis of metallographic images and provides valuable support for automated quality assessment in casting production. Full article

Background/Objectives: This study evaluated the effects of virtual reality (VR) on functionality, quality of life, and motivation in children with cerebral palsy (CP). Methods: The systematic review was registered in PROSPERO (CRD42022321170) and conducted using the keywords physical therapy OR physiotherapy AND “Virtual Reality”. Studies were screened based on title, abstract, and full-text review. The PEDro scale was used to assess methodological quality, and the GRADE system was applied to determine the level of certainty of the evidence. Results: A total of 10 studies showed improvements in balance, 6 in gross motor function, and 8 in upper limb coordination. Additional gains were found in daily functioning (6), gait (4), motivation (3), and spasticity (1–2). Overall, virtual reality enhanced motor abilities and engagement compared with conventional therapy, underscoring its value as a playful and motivating tool in rehabilitation. All outcome measures showed positive changes, particularly in functionality and quality of life. The primary outcomes with the most favorable responses to intervention were gross motor function and balance, followed by motivation and adherence. However, the generalities of the findings are limited due to variabilities in outcome reporting and measurement tools. Conclusions: The findings indicated clinical improvements in key outcome measures following VR interventions. Nonetheless, there were significant variabilities in the evaluation instruments used across studies. Despite this, the clinical evidence supported the integration of VR into neurorehabilitation processes for children with CP. Full article

As an energy-intensive sector, China’s iron and steel industry is crucial for achieving “Dual Carbon” goals. This study fills the research gap in systematically comparing the synergistic effects of multiple policies by evaluating five key measures (2020–2023) in ultra-low-emission retrofits and clean energy alternatives. Using public macro-data at the national level, this study quantified cumulative reductions in air pollutants (SO₂, NOx, PM, VOCs) and CO₂. A synergistic control effect coordinate system and a normalized synergistic emission reduction equivalent (AP_eq) model were employed. The results reveal significant differences: Sintering machine desulfurization and denitrification (SDD) showed the highest AP_eq but increased CO₂ emissions in 2023. Dust removal equipment upgrades (DRE) and unorganized emission control (UEC) demonstrated stable co-reduction effects. While electric furnace short-process steelmaking (ES) and hydrogen metallurgy (HM) showed limited current benefits, they represent crucial deep decarbonization pathways. The framework provides multi-dimensional policy insights beyond simple ranking, suggesting balancing short-term pollution control with long-term transition by prioritizing clean alternatives. Full article

The rapid proliferation of residential electric vehicles (EVs), rooftop photovoltaics (PVs), and behind-the-meter batteries is transforming energy communities while introducing new operational stresses to local distribution grids. Short-duration transformer overloads, often overlooked in conventional hourly or optimization-based planning models, can accelerate asset aging before voltage limits are reached. This study introduces a second-by-second, multi-agent-based simulation (MABS) framework that couples empirically calibrated Distributed Energy Resource (DER) adoption trajectories with real-time-price (RTP)–driven household charging decisions. Using a real 160-household feeder in Denmark (2024–2025), five progressively integrated DER scenarios are evaluated, ranging from EV-only adoption to fully synchronized EV–PV–battery coupling. Results reveal that uncoordinated EV charging under RTP shifts demand to early-morning hours, causing the first transformer overload within four months. PV deployment alone offers limited relief, while adding batteries delays overload onset by 55 days. Only fully coordinated EV–PV–battery adoption postponed the first overload by three months and reduced total overload hours in 2025 by 39%. The core novelty of this work lies in combining empirically grounded adoption behavior, second-level temporal fidelity, and agent-based grid dynamics to expose transient overload mechanisms invisible to coarser models. The framework provides a diagnostic and planning tool for distribution system operators to evaluate tariff designs, bundled incentives, and coordinated DER deployment strategies that enhance transformer longevity and grid resilience in future energy communities. Full article