Search Results (22,024)

Against the backdrop of high-density Asian cities shifting from production- to consumption-oriented spaces, commercial pedestrian streets are key to urban public life and vitality. This study selects six major commercial pedestrian streets in Chongqing and employs natural language processing (NLP) and importance–performance analysis (IPA) methods to construct a four-dimensional evaluation framework (spatial, commercial, cultural, location/facility). It analyzes public perception and experience based on user-generated content (UGC). Findings show that: (1) Significant differences across dimensions form three development types: cultural identity, functional hub, and distinctive growth, reflecting structural bottlenecks in transitioning from single- to multi-functional spaces. (2) IPA identifies “business formats,” “cultural activities,” and “consumption experience” as priorities for improvement, while “commercial atmosphere” and “transportation conditions” are current strengths to maintain. (3) Sentiment analysis reveals that negative perceptions focus on basic functions and sense of place, whereas positive sentiments relate to cultural expression and spatial esthetics, highlighting the role of cultural soft power and visual design in street appeal. This study reveals public perception patterns via big data analysis, offering empirical support for the refined renewal, cultural preservation, and sustainable management of commercial pedestrian streets in high-density Asian cities. Full article

With the advancement of healthy city development and community renewal practices, the influence of perceived community environmental quality on residents’ psychological well-being has attracted increasing attention. Previous research has shown that the built environment is closely related to residents’ well-being; however, most studies have focused on objective spatial elements or facility provision and have paid insufficient attention to the mechanisms through which subjective environmental perceptions operate in the process by which the environment affects psychological well-being. From the perspective of Homo Urbanicus theory, this study takes 36 communities in Yangpu District, Shanghai, as cases and uses data from 882 valid questionnaires. Structural equation modeling is employed to examine the relationships among perceived community environmental quality, perceived environmental restorativeness, and residents’ psychological well-being, and to further explore age-related patterns among young-old, middle-old, and oldest-old groups. The results show that perceived community environmental quality has a significant positive effect on residents’ psychological well-being and produces a significant indirect effect through perceived environmental restorativeness. Exploratory age-stratified analyses further suggested different pathway patterns among the young-old, middle-old, and oldest-old groups. On this basis, the study further proposes a four-quadrant model of spatial contact opportunities and a five-category accessibility classification and accordingly develops community environment optimization strategies for older adults of different ages. The findings provide a theoretical basis and practical reference for healthy-community development and age-friendly community renewal. Full article

A Transmission Control Protocol (TCP) throughput map represents communication quality over road networks and supports communication-aware applications in intelligent transportation systems. Maintaining such a map online is challenging because vehicular measurements are sparse and unevenly distributed, network conditions vary rapidly, and sensing-budget constraints limit the number of vehicles from which onboard communication measurements can be uploaded at each time step. This work addresses online TCP throughput map maintenance under sparse vehicular observations and sensing-budget constraints. To support budget-constrained sensing, we combine discoverability-guided vehicle selection and probabilistic map updating within a digital twin (DT)-assisted vehicular sensing architecture. The resulting sensing-and-mapping method, referred to as Discoverability-aware and Statistical Mapping (DISMAP), maintains a spatio-temporal discoverability map to characterize historical sensing coverage and select vehicles that improve the coverage of under-represented regions. It then uses Gaussian Process Regression (GPR) as a probabilistic mapping engine to estimate the mean TCP throughput and predictive standard deviation, where the standard deviation is adjusted using local vehicle density. Simulation results show that DISMAP reduces the mean absolute error (MAE) and mean standard deviation (MSTD) by up to 23.7% and 37.5%, respectively, and achieves a prediction-interval miss rate (PIMR) of 0.048, which is close to the nominal value of 0.05. These results indicate a favorable balance among prediction accuracy, interval sharpness, calibration, and spatial representativeness across different traffic-density conditions. Full article

This study investigates the impact of critical raw material mining and processing on surface water quality within a representative catchment area, using the Luda Yana River Basin in Southern Bulgaria as a case study. Water quality was evaluated using the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI), based on data collected from five monitoring stations. The analysis focused on key heavy metals, including Cu, Zn, Pb, Cd, Fe, Mn, Ni, and As, reflecting the influence of both active and historical mining activities in the region. Index values were calculated for the period 2008–2024 and revealed considerable temporal variability and pronounced spatial differences in water quality along the river course. This study provides one of the first long-term integrated assessments of heavy-metal-related water quality in a mining-impacted river basin in Bulgaria using the CCME WQI framework and offers new evidence on the cumulative effects of historical and ongoing mining activities on surface waters. The calculated CCME WQI values ranged from very low levels indicating poor conditions to moderate values corresponding to marginal and, occasionally, fair conditions. Overall, the predominant water quality categories were “poor” and “marginal.” The results demonstrate that the waters of the studied river basin remain below the thresholds for “fair” physicochemical status as defined by the European Water Framework Directive (2000/60/EC) and the corresponding Bulgarian legislation, including Regulation No. H-4/2012 on surface water characterization and the 2010 Ordinance on environmental quality standards for priority substances and certain pollutants. The findings highlight the persistent anthropogenic pressure exerted on the river system and emphasize the need for improved water management strategies. The study further underlines the importance of integrating environmental protection measures into the exploitation of critical raw materials in order to balance economic development with the sustainable management of water resources. Full article

The scientific problem addressed in this study is how a continuous mechanical architecture can maintain stable lettuce handling while improving treatment-medium access to irregular, overlapping leaf surfaces. We formulate this problem as a morphology-informed design and evaluation task. The proposed machine integrates soil removal, a reserved vision-based yellow-leaf detection and root-trimming station, multi-angle disinfection, water–air washing, combined airflow drying, film wrapping, weighing, and boxing modules on a chain-conveyor platform with bowl-shaped fixtures. The evaluation follows a design-to-evidence workflow: lettuce morphology and process requirements are mapped to module geometry; chain, lead-screw, gear, and motor parameters are checked analytically; an application-oriented geometric spray-coverage model tests fixed versus swinging bilateral nozzles; static finite element analysis screens the frame under defined design loads; and prototype assembly verifies spatial compatibility. The covered-surface proxy increased from 7.24% for fixed bilateral spraying to 13.58% for a ±35° swinging case under explicit screening assumptions, while the frame analysis gave 0.0224 mm maximum deformation and 7.30 MPa maximum von Mises stress. These outputs support a preliminary, mechanically feasible platform and a testable explanation for why adjustable spray orientation may improve access to complex lettuce surfaces. They do not constitute measured cleaning, microbial, trimming, drying, packaging, throughput, or reliability performance. Full article

Contemporary urban development imposes an increasingly pronounced need for aligned spatial transformations with the preservation of natural resources, adaptation to climate change, and the improvement of quality of life. In this context, the concept of green infrastructure has been recognized as an integrative framework that connects ecological processes with spatial and urban planning. However, the ways in which green infrastructure is strategically articulated and operationalized through planning processes vary depending on the institutional and spatial context. The aim of this paper is to identify the dominant strategic approaches to green infrastructure planning and to examine their implications for spatial and urban planning. The research is based on a qualitative comparative analysis of selected European green infrastructure strategies, while the Green Infrastructure Strategy of the City of Belgrade is considered as an analytical case study within the specific institutional and planning context of Serbia. The analysis focuses on three key components of strategic articulation—visions, objectives, and measures—in order to identify recurring patterns that shape the integration of green infrastructure into planning practice. The results indicate a high degree of convergence among strategic approaches, particularly regarding the emphasis on quality of life, ecosystem services, biodiversity conservation, and the strengthening of climate resilience. The identified patterns indicate the need for transformation of regulatory frameworks, the improvement of planning procedures and instruments, and the adoption of a spatial logic based on connectivity and multifunctionality. The analytical examination of the Belgrade Strategy shows that its structure of visions, objectives, and measures encompasses the key regulatory, procedural, and spatial prerequisites for incorporating green infrastructure into planning practice, and at the same time, its operationalization depends on institutional capacities, information systems, financial instruments, and mechanisms of intersectoral coordination. The paper concludes that green infrastructure strategies play an important role in mediating between public policies and spatial planning solutions, while their effectiveness depends on the alignment of regulatory, procedural, and spatial instruments. Full article

This study evaluates the structural dynamics of the landscape within the Sierra de San Pedro and Embalse de Cornalvo Special Areas of Conservation between 2006 and 2018 to determine the effect of land-use spatial configuration on ecosystem stability. Methodologically, Corine Land Cover cartography was geoprocessed in QuantumGIS utilising the LecoS plugin to calculate five landscape metrics. The results reveal marked stability within the agroforestry matrix of both protected areas, demonstrating the effectiveness of their conservation status against drastic land-use changes. Nonetheless, contrasting internal trajectories were identified: the Sierra de San Pedro experienced a process of silent reforestation and the unification of natural habitats (characterised by a reduction in patch numbers and an increase in mean patch size), whereas the Cornalvo landscape exhibited strong structural homogeneity dominated by human activity. It is concluded that while the Sierra de San Pedro is evolving towards forest maturation and robust internal connectivity, Cornalvo maintains a structural inertia of absolute stability. These findings demonstrate the importance of incorporating spatial metrics into environmental management to strengthen ecosystem resilience to change. Full article

This study focuses on the Northern New District of Liaoyuan City, Jilin Province, and develops an indicator-based relative spatial assessment framework for geological environmental carrying capacity. Fourteen indicators were selected from the geological, ecological, and socio-economic dimensions to characterize spatial differences in regional geological environmental conditions. The weights of the indicators were determined by integrating subjective and objective methods, where the Fuzzy Analytic Hierarchy Process (FAHP) and the CRITIC method were applied respectively, and the final composite weights were obtained through a game theory-based combination weighting approach. Based on the weighted results, ArcGIS was used to perform spatial analysis, and the geological environmental carrying capacity was classified into four levels: excellent, good, moderate, and poor. The results indicate significant spatial heterogeneity in geological environmental carrying capacity. Moderate-capacity areas dominate the study area, with poor-capacity areas mainly distributed in the central and southeastern regions. The proposed framework provides spatial information for identifying areas with different geological environmental conditions and supports differentiated environmental management and planning in mining areas. Full article

Hybrid CNN–Transformer (HCT) synthesis for automated neurodevelopmental diagnostics is an effective approach to constructing intelligent detection systems that are not merely oriented toward feature classification but primarily toward solving spatiotemporal pattern recognition problems in motor disorder assessment. In neurodevelopmental diagnostics, existing automated methods rely on fixed, single-model architectures that process spatial or temporal motion features independently, failing to adapt to the heterogeneous motor irregularities characteristic of developmental coordination disorder and degrading detection sensitivity and generalization across diverse patient populations. There is therefore a pressing need for models capable of simultaneously capturing intra-frame spatial coordination patterns and inter-frame temporal movement dependencies against interrelated diagnostic criteria including accuracy, sensitivity, and motor irregularity specificity. To address this challenge, this paper proposes HCT, a novel framework that integrates ResNet-based spatial feature extraction from optical flow maps and pose estimation skeletons with multi-head self-attention Transformer encoding for modeling long-range temporal dependencies across multi-frame motion sequences. Unlike conventional single-stream approaches, where spatial and temporal processing remain confined to independent architectures, HCT decouples spatiotemporal feature learning through a cross-modal fusion pipeline, constructing a unified discriminative architecture that captures motor coordination dependencies between motion imaging inputs and multiple diagnostic criteria simultaneously. The convolutional encoder generates diverse joint displacement features, which are consolidated through cross-modal attention fusion into a robust, unified embedding with enhanced generalization and resilience to inter-individual motor variability. Integration within neurodevelopmental assessment frameworks facilitates reliable developmental coordination disorder classification, motor irregularity prediction, and interpretable diagnostic decision support, advancing the accuracy, flexibility, and clinical validity of intelligent motor disorder diagnostic systems. Full article

Accurate protein function prediction (PFP) is essential for understanding biological systems. However, structure-based graph neural networks often rely on fixed-distance contact maps, which may inadequately capture continuous, multi-scale spatial topologies, while the long-tail distribution of Gene Ontology (GO) labels may bias prediction toward frequent functions. We propose DHST, a deep hybrid structure–topology framework that integrates sequence semantics from a pretrained protein language model with local structural information learned by a residual graph convolutional network. DHST further introduces site-specific persistent homology to encode multi-scale topological invariants and a topology-guided residue-wise gated fusion module to modulate structure–semantics representations using local topological embeddings. The fused residue features are aggregated through dual-path pooling, and a weighted binary cross-entropy loss is used to mitigate the adverse effects of label imbalance. On the PDB dataset, DHST achieved area under the precision–recall curve (AUPR) scores of 0.779, 0.481, and 0.557 for molecular function (MF), biological process (BP), and cellular component (CC), respectively; on the AF2 dataset, the corresponding scores were 0.729, 0.390, and 0.459. The model also demonstrated robust generalization to low-homology proteins and maintained strong predictive performance across GO terms with different levels of functional specificity. Ablation results supported the contributions of the main components. Full article

Gut-derived indole metabolites are implicated in the gut–kidney axis, but the factors controlling the intestinal conversion of indole-3-acetic acid (IAA) to skatole remain incompletely defined. We developed a deterministic, hypothesis-generating framework that represents this conversion as a finite-pool allocation process governed by $\mathrm{pH}$-dependent ecological permissiveness, terminal-conversion capacity, precursor availability, spatial progression, and competing loss. The model separates the available-pool scale from a dimensionless integrated conversion exposure, $\Psi$. Across 5400 loss-free scenarios spanning 10 pH profiles and graded metabolic and host-associated constraints, the distal endpoint normalized to the available pool followed the analytically derived relationship $1-\exp \left(-\Psi \right)$. Thus, distinct combinations of mechanistically relevant parameters produced the same normalized distal endpoint, demonstrating that this endpoint alone cannot uniquely identify the underlying mechanism. Competing loss further separated absolute, total-pool-normalized, and conditional outputs, showing that mechanistic interpretation depends on endpoint normalization. Analytical and numerical checks supported internal consistency. The framework was not fitted to biological data, and concentration values were used only as technical scaling references. This biologically unvalidated model generates experimentally testable hypotheses regarding the roles of $\mathrm{pH}$, terminal-conversion capacity, precursor availability, and competing loss in intestinal IAA-to-skatole metabolism; it is not intended to provide physiological or clinical predictions. Full article

Global commodity chains reshape rural territories through interconnected environmental and socioeconomic processes; these dynamics are often examined through the lens of land-use change. Export-oriented agricultural frontiers illustrate how global market integration can generate landscape and societal transformations. In western Mexico, the expansion of the avocado industry exemplifies commodity-driven territorial change, linking land-use dynamics with transformations in rural economies and livelihoods. This study analyzes how export integration into the international avocado commodity chain was associated with transformations in land systems and socioeconomic dynamics across four municipalities in Michoacán, Mexico, between 2003 and 2023. Using high-resolution land-use maps alongside demographic and socioeconomic indicators, we apply a qualitative, comparative and inductive synthesis of spatial and census data to examine how commodity integration interacted with local conditions to shape landscape and territorial organization. Avocado expansion coincided with territorial transformation, including the conversion of pine-oak forest and traditional agricultural lands, as well as changes in labor arrangements, demographic dynamics, and rural livelihood systems. Land-use analysis shows continued orchard expansion and accelerated land conversion after 2015. Socioeconomic indicators reveal population growth, increased female employment, and persistent income inequality, highlighting the uneven incorporation of rural territories into global commodity chains. We identified four territorial pathways: agricultural specialization, agro-industrial urbanization, transitional diversification, and rural commodity integration. These findings contribute to debates on uneven geographical development and commodity frontier expansion by showing how global commodity integration intersects with ecological, economic, and social processes to generate distinct pathways. Full article

Objectives: The pathological progression of Parkinson’s disease (PD) involves alterations across multiple neural cell types, and glial–neuronal communication substantially influences neuronal function. Oligodendrocytes (OLs) have been implicated in PD pathology, but the underlying regulatory mechanisms remain incompletely understood. Methods: In this study, single-nucleus RNA sequencing and spatial transcriptomics were used to characterize OL-associated changes and explore potentially relevant mechanisms in the substantia nigra pars compacta (SNpc) of MPTP-induced parkinsonian mice. Molecular validation was subsequently performed in an exercise intervention cohort. Results: These analyses revealed a significant reduction in OL abundance in the SNpc, accompanied by enrichment of ferroptosis-related pathways. Aerobic exercise partially restored the expression of the OL marker gene Plp1 and the antioxidant pathway-related molecules Nrf2 and Gpx4, while reducing ferroptosis-related oxidative stress. These changes were associated with improvements in PD-like pathological phenotypes. Exploratory untargeted metabolomics further identified candidate alterations in metabolites and pathways related to redox homeostasis, energy metabolism, and myelin-associated processes after MPTP treatment and exercise intervention. Conclusions: Collectively, exercise-associated improvements in MPTP-induced PD-like phenotypes coincided with reductions in OL/myelin-related injury and ferroptosis-related stress. These findings suggest that OL-associated ferroptosis-related stress may represent one of several processes contributing to neuronal injury in PD and may be responsive to aerobic exercise. This study provides a theoretical basis for further investigation of exercise-based rehabilitation strategies and potential therapeutic targets for PD. Full article

In silico studies of microbiological systems are essential for predicting and controlling the impact of external factors on bacterial communities. Quorum sensing represents one of the key mechanisms of bacterial communication, particularly in pathogenic bacteria, realized as a cell-density-dependent regulatory process governed by diffusible signaling molecules. The present study proposes a Physics-Informed Neural Network (PINN)-based computational framework for a spatially independent model of bacterial quorum sensing and population dynamics. The approach solves both the forward and inverse problems for a spatially independent model formalized by a system of nonlinear ordinary differential equations. The forward problem is solved numerically by reconstructing the dynamics of three key characteristics: signaling molecule concentration, degrading enzyme concentration, and bacterial biomass density. The obtained PINN solutions are compared with numerical solutions computed using the Radau IIA implicit Runge–Kutta method. The inverse problem capability is evaluated by recovering system parameters that are difficult to measure directly in experimental settings. The framework is implemented using the DeepXDE library with a PyTorch backend, employing hard constraints for initial conditions, singularity-avoiding loss reformulations, and a multi-stage Adam–L-BFGS optimization strategy. Validation is performed on a Monod chemostat benchmark and the Pseudomonas putida IsoF quorum sensing regulatory network. The proposed PINN-based framework extends the applied mathematical toolkit for in silico studies of microbial systems, enabling accurate reconstruction of emergent population dynamics and robust inference of regulatory parameters that are inaccessible to direct experimental measurement. Full article

Industrial heritage tourism depends on more than the preservation of visible structures; it also requires visitors to perceive historical and cultural meaning. This study examines public perceptions of eight representative industrial heritage tourism sites in Wuhan. Drawing on Scene Theory, we developed a three-dimensional framework encompassing physical, social, and cultural scenes. We collected user-generated content (UGC) from Dianping.com and evaluated 12 perception elements using semantic network analysis and a modified Importance–Performance Analysis based on topic salience and satisfaction. Public perceptions were dominated by visual aesthetics and social-media engagement. Ecological atmosphere received favourable evaluations despite its lower salience, whereas homogeneous commercial offerings weakened the visitor experience. Era memory and industrial heritage combined relatively high salience with low satisfaction, revealing a gap between visible physical remains and the communication of industrial history and collective memory. A hierarchical analysis further showed that only 8.40% of culture-related reviews contained deep industrial narratives. We therefore propose strategies that improve spatial interpretation, embed site-specific industrial identity in commercial and social experiences, and connect heritage objects with historical processes and workers’ memories. These findings provide an evidence-based framework for strengthening cultural interpretation in the revitalization of Wuhan’s industrial heritage. Full article