Search Results (6,237)

This research investigates the integration of green cores as central biophilic elements in residential architecture, proposing a climate-responsive design methodology grounded in architectural optimization. The study begins with the full-scale refurbishment of a compact urban apartment, wherein interior partitions, fenestration and material systems were reconfigured to embed vegetated zones within the architectural core. Light exposure, ventilation potential and spatial coherence were maximized through data-driven design strategies and structural modifications. Integrated planting modules equipped with PAR-specific LED systems ensure sustained vegetation growth, while embedded environmental infrastructure supports automated irrigation and continuous microclimate monitoring. This plant-centered spatial model is evaluated using quantifiable performance metrics, establishing a replicable framework for optimized indoor ecosystems. Photosynthetically active radiation (PAR)-specific LED systems and embedded environmental infrastructure were incorporated to maintain vegetation viability and enable microclimate regulation. A programmable irrigation system linked to environmental sensors allows automated resource management, ensuring efficient plant sustenance. The configuration is assessed using measurable indicators such as daylight factor, solar exposure, passive thermal behavior and similar elements. Additionally, a post-occupancy expert assessment was conducted with several architects evaluating different aspects confirming the architectural and spatial improvements achieved through the refurbishment. This study not only demonstrates a viable architectural prototype but also opens future avenues for the development of metabolically active buildings, integration with decentralized energy and water systems, and the computational optimization of living infrastructure across varying climatic zones. Full article

China faces the persistent challenge of uneven spatiotemporal water resource distribution, constraining economic and social development while exacerbating regional disparities. Achieving co-evolution between water source systems and water use systems is thus a critical proposition in water resources management. Based on synergetics theory, this study takes Henan Province, a typical water-scarce social–ecological system, as the research object, and constructs a quantitative analysis framework for supply–demand bidirectional synergy. It systematically reveals the evolution patterns of water resource systems under the mutual feedback mechanism between water sources and water use. Findings indicate that between 2012 and 2022, the synergy degree of Henan’s water resource system increased by nearly 40%, exhibiting significant spatiotemporal differentiation: spatially “lower north, higher south”, and dynamically shifting from demand-constrained to supply-optimized. Specifically, the water source system’s order degree showed a “higher northwest, lower southeast” spatial pattern. Since the operation of the South-to-North Water Diversion Middle Route Project, the provincial average order degree increased significantly (annual growth rate of 0.01 units), though with distinct regional disparities. The water use system’s order degree also exhibited “lower north, higher south” pattern but achieved greater growth (annual growth rate of 0.03 units), with narrowing north–south gaps driven by improved management efficiency and technological capacity. This study innovatively integrates water source systems and water use systems into a unified analytical framework, systematically elucidating the intrinsic evolution mechanisms of water resource systems from the perspective of supply–demand mutual feedback. It provides theoretical and methodological support for advancing systematic water resource governance. Full article

This study analyses employment in the tourism sector and seeks to identify trends in the evolution of worker profiles and transformation of the structure and working conditions in Portugal’s tourism sector from 2012 to 2022. It aims to understand how profiles, qualifications, and working conditions relate to the spatial distribution among Portuguese tourist regions and the typology and scale of tourism businesses, contributing valuable insights to defining sector strategies. It applies a quantitative approach based on statistical data from the Portuguese Ministry of Labour, Solidarity, and Social Security, disaggregated by the three segments of economic activity in the tourism sector: accommodation and food services, recreational and cultural activities, and transport and logistics. Descriptive statistics, MANOVA, and ANOVA tests analyse differences based on establishment size, tourist regions, and activity segments. The results show significant employment growth, regional variations, high turnover, and an increase in fixed-term contracts. Weak but significant correlations link education, nationality, gender, and working hours, indicating potential inequalities. The study highlights gender and educational differences among workers, as well as disparities related to employment status and nationality. Full article

This study presents the development and evaluation of an automated ultraviolet-C irradiation system for maize seed treatment, emphasizing disinfection performance, environmental control, and vision-based monitoring. The system features dual 8-watt ultraviolet-C lamps, sensors for temperature and humidity, and an air extraction unit to regulate the microclimate of the chamber. Without air extraction, radiation stabilized within one minute, with internal temperatures increasing by 5.1 °C and humidity decreasing by 13.26% over 10 min. When activated, the extractor reduced heat build-up by 1.4 °C, minimized humidity fluctuations (4.6%), and removed odors, although it also attenuated the intensity of ultraviolet-C by up to 19.59%. A 10 min ultraviolet-C treatment significantly reduced the fungal infestation in maize seeds by 23.5–26.25% under both extraction conditions. Thermal imaging confirmed localized heating on seed surfaces, which stressed the importance of temperature regulation during exposure. Notable color changes ($\Delta E>2.3$) in treated seeds suggested radiation-induced pigment degradation. Ultraviolet-C intensity mapping revealed spatial non-uniformity, with measurements limited to a central axis, indicating the need for comprehensive spatial analysis. The integrated computer vision system successfully detected seed contours and color changes under high-contrast conditions, but underperformed under low-light or uneven illumination. These limitations highlight the need for improved image processing and consistent lighting to ensure accurate monitoring. Overall, the chamber shows strong potential as a non-chemical seed disinfection tool. Future research will focus on improving radiation uniformity, assessing effects on germination and plant growth, and advancing system calibration, safety mechanisms, and remote control capabilities. Full article

As climate extremes increasingly threaten global food security, precision tools for early detection of crop stress have become vital, particularly for root crops such as potato (Solanum tuberosum L.) and sweet potato (Ipomoea batatas L. Lam.), which are especially susceptible to environmental stressors throughout their life cycles. In this study, plants were monitored from the initial onset of seasonal stressors, including spring drought, heat, and episodes of excessive rainfall, through to harvest, capturing the full range of physiological and biochemical responses under seasonal, simulated conditions in greenhouses. The spectral data were obtained from regions of interest (ROIs) of each cultivar’s leaves, with over 3000 data points extracted per cultivar; these data were subsequently used for model development. A comprehensive classification framework was established by employing machine learning models, Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Partial Least Squares-Discriminant Analysis (PLS-DA), to detect stress across various growth stages. Furthermore, severity levels were objectively defined using photoreflectance indices and principal component analysis (PCA) data visualizations, which enabled consistent and reliable classification of stress responses in both individual cultivars and combined datasets. All models achieved high classification accuracy (90–98%) on independent test sets. The application of the Successive Projections Algorithm (SPA) for variable selection significantly reduced the number of wavelengths required for robust stress classification, with SPA-PLS-DA models maintaining high accuracy (90–96%) using only a subset of informative bands. Furthermore, SPA-PLS-DA-based chemical imaging enabled spatial mapping of stress severity within plant tissues, providing early, non-invasive insights into physiological and biochemical status. These findings highlight the potential of integrating hyperspectral imaging and machine learning for precise, real-time crop monitoring, thereby contributing to sustainable agricultural management and reduced yield losses. Full article

Spatial accessibility is a key principle in urban studies, shaping how people reach amenities and services across cities. While most research concentrates on large metropolitan areas and central urban services, small and medium-sized cities and their main amenities remain less studied. To bridge this gap, this study explores spatial accessibility to public amenities in relation to population density in Odense, a medium-sized city known for its compact layout and robust infrastructure supporting walking, cycling, and public transport. Despite Odense’s proactive planning and multimodal transport network, marked accessibility inequalities still exist, especially in peripheral neighbourhoods. This research uses a data-driven approach combining network-based travel time analysis with grid-cell-based spatial visualisation. Additionally, a multi-criteria accessibility scoring framework is introduced, including indicators such as amenity density, diversity of services, temporal thresholds for walking and cycling, and population distribution. The results show an uneven accessibility landscape, with significant gaps in outer districts, highlighting the limitations of uniform planning thresholds. By applying spatial analytical principles, the study uncovers embedded socio-spatial inequalities in everyday urban access. These insights offer practical guidance for planners and policymakers, underscoring the importance of context-sensitive multimodal infrastructure and decentralised service provision to support sustainable urban growth. Full article

Atmospheric sulfur (S) deposition, a key component of acid deposition, poses risks to ecosystems, human health, and sustainable development. In China, decades of coal-dominated energy use caused severe S pollution, but recent emission-control policies and energy restructuring have sought to reverse this trend. However, the effectiveness and regional differences in these measures remain insufficiently quantified. Here, we combined continuous observations from 43 monitoring sites (2013–2023), satellite-derived SO₂ vertical column density, and multi-source environmental datasets to construct a high-resolution record of wet S deposition. A random forest model, validated with R² = 0.52 and RMSE = 1.2 kg ha⁻¹ yr⁻¹, was used to estimate fluxes and spatial patterns, while ridge regression and SHAP analysis quantified the relative contributions of emissions, precipitation, and socioeconomic factors. This framework allows us to assess both the environmental and health-related sustainability implications of sulfur deposition. Results show a nationwide decline of more than 50% in wet S deposition during 2013–2023, with two-thirds of sites and 95% of grids showing significant decreases. Historical hotspots such as the North China Plain and Sichuan Basin improved markedly, while some southern provinces (e.g., Guizhou, Hunan, Jiangxi) still exhibited high deposition (>20 kg ha⁻¹ yr⁻¹). Over 90% of the reduction was attributable to emission declines, confirming the dominant effect of sustained policy-driven measures. This study extends sulfur deposition records to 2023, demonstrates the value of integrating ground monitoring with remote sensing and machine learning, and provides robust evidence that China’s emission reduction policies have delivered significant environmental and sustainability benefits. The findings offer insights for region-specific governance and for developing countries balancing economic growth with ecological protection. Full article

Hakka traditional vernacular dwellings embody regionally specific climatic adaptation strategies. This study takes the Meizhou Guangludi enclosed house as a case study to evaluate its climate adaptability with longevity and passive survivability factors of the Hakka three-hall enclosed house under subtropical climatic conditions. A mixed research method is employed, integrating visualized parametric modeling analysis and on-site measurement comparisons to quantify wind, temperature, solar radiation/illuminance, and humidity, along with human comfort zone limits and building environment. The results reveal that nature erosion in the Guangludi enclosed house is the most pronounced during winter and spring, particularly on exterior walls below 2.8 m. Key issues include bulging, spalling, molding, and fractured purlins caused by wind-driven rain, exacerbated by low wind speeds and limited solar exposure, especially at test spots like the E8–E10 and N1–N16 southeast and southern walls below 1.5 m. Fungal growth and plant intrusion are severe where surrounding trees and fengshui forests restrict wind flow and lighting. In terms of passive survivability, the Guangludi enclosed house has strong thermal insulation and buffering, aided by the Huatai mound; however, humidity and day illuminance deficiencies persist in the interstitial spaces between lateral rooms and the central hall. To address these issues, this study proposes strategies such as adding ventilation shafts and flexible partitions, optimizing patio dimensions and window-to-wall ratios, retaining the spatial layout and Fengshui pond to enhance wind airflow, and reinforcing the identified easily eroded spots with waterproofing, antimicrobial coatings, and extended eaves. Through parametric simulation and empirical validation, this study presents a climate-responsive retrofit framework that supports the sustainability and conservation of the subtropical Hakka enclosed house. Full article

Mountain settlements represent culturally rich but environmentally fragile landscapes, shaped by enduring processes of ecological adaptation and human resilience. In western Sichuan, Jiarong Tibetan villages, with their distinctive integration of defensive stone towers and settlements, embody this coupling of culture and the environment. We hypothesize that settlement cores in these villages were shaped by natural environmental factors, with subsequent expansion reinforced by the cultural significance of towers. To test this, we applied a micro-scale spatial–environmental framework to four sample villages in Suopo Township, Danba County. High-resolution World Imagery (Esri, 0.5–1 m, 2022–2023) was classified via a Random Forest algorithm to generate detailed land-use maps, and a 100 × 100 m fishnet grid extracted topographic metrics (elevation, slope, aspect) and accessibility measures (distances to streams, roads, towers). Geographically weighted regression (GWR) was then used to examine how slope, elevation, aspect, proximity to water and roads, and tower distribution affect settlement patterns. The results show built-up density peaks on southeast-facing slopes of 15–30°, at altitudes of 2600–2800 m, and within 50–500 m of streams, co-locating with historic watchtower sites. Based on these findings, we propose four zoning strategies—a Core Protected Zone, a Construction And Development Zone, an Ecological Conservation Zone, and an Industry Development Zone—to balance preservation with growth. The resulting policy recommendations offer actionable guidance for sustaining traditional settlements in complex mountain environments. Full article

Leveraging multi-source remote sensing datasets and dynamic groundwater monitoring well observations, this study explores the multiscale spatiotemporal linkages of groundwater storage changes and land deformation in North China Plain (NCP) after the South-to-North Water Diversion Project (SNWDP). Firstly, we employed Gravity Recovery and Climate Experiment (GRACE) and interferometric synthetic aperture radar (InSAR) technology to estimate groundwater storage (GWS) and land deformation. Secondly and significantly, we proposed a novel GRACE statistical downscaling algorithm that integrates a weight allocation strategy and GWS estimation applied with InSAR technology. Finally, the downscaled results were employed to analyze spatial differences in land deformation across typical ground fissure areas. The results indicate that (1) between 2018 and 2021, groundwater storage in the NCP exhibited a declining trend, with an average reduction of −3.81 ± 0.53 km³/a and a maximum land deformation rate of −177 mm/a; (2) the downscaled groundwater storage anomalies (GWSA) showed high correlation with in situ measurements (R = 0.75, RMSE = 2.91 cm); and (3) in the Shunyi fissure area, groundwater storage on the northern side increased continuously, with a maximum growth rate of 28 mm/a, resulting in surface uplift exceeding 70 mm. Full article

Linear cultural heritage poses significant challenges in tourism development, primarily due to the complexities involved in implementing scientific zoning and differentiated management strategies. Systematic optimization of its tourism spatial structure has thus become crucial for achieving sustainable utilization. This study adopts a case study approach based on deductive reasoning to examine the morphological characteristics and evolutionary patterns of the tourism space along linear cultural heritage. Taking the Beijing–Hangzhou Grand Canal as an example, it proposes a targeted optimization pathway from a spatial positioning perspective. The findings indicate that the tourism value of linear cultural heritage exhibits a “vine-shaped structure” spatially, and the development process of the tourism space structure follows the “growth pole” evolution law. Moreover, spatial optimization can be achieved through the dual dimensions of spatial form and utilization intensity. Based on this pathway, a three-level tourism zone system is constructed for the Beijing–Hangzhou Grand Canal: the primary tourism zone, located in southern sections, such as Yangzhou and Hangzhou, serves as leading regions that play a pivotal and driving role; the secondary tourism zone, encompassing Beijing, Tianjin, Langfang, and Cangzhou, requires focused enhancement and functional upgrading; and the tertiary tourism zone, mainly including Shandong Province and Xuzhou, Suqian, in Jiangsu Province, necessitate comprehensive and integrated development to achieve overall improvement. This classification not only facilitates coordinated tourism development along the entire canal from a holistic perspective but also provides a basis for formulating targeted strategies for segments with varying tourism values and utilization intensities. Full article

Historic and cultural villages in China are increasingly challenged by rapid urbanization, uneven commercial development, and fragmented preservation mechanisms. Understanding their spatiotemporal distribution and the factors shaping it is crucial for advancing the integrated development of cultural heritage conservation, ecological sustainability, and socio-economic growth. This study examines 487 historic and cultural villages using the nearest neighbor index (NNI) and kernel density analyses to reveal spatial differentiation patterns. Vector buffer analysis and the geographic detector method were further employed to identify the key drivers of village distribution. The results indicate that: (1) historic and cultural villages exhibit a distinctly clustered spatial pattern, characterized by “more in the southeast, fewer in the northwest; more in the northeast, fewer in the southwest” (NNI = 0.44, Z = –23.52, p = 0.00); (2) provincial-level spatial density demonstrates clear stratification, with high-density clusters concentrated in the Yangtze River Delta, southern Anhui, the Fujian–Zhejiang–Jiangxi junction, and along the Yellow River in Shanxi–Shaanxi–Henan. From the fifth to seventh designation batches, kernel density peaks (maximum ~0.11 × 10⁻²) increased significantly, reflecting stronger spatial clustering; and (3) the spatial distribution of villages is jointly shaped by natural geography, socio-economic conditions, transportation infrastructure, visitor markets, and tourism resources. Among these, nighttime light intensity was identified as the most influential individual factor (q = 0.6132), while the combination of slope aspect and per capita disposable income emerged as the dominant factor pair (q = 0.966). Full article

Against the backdrop of global population growth and intensified resource competition, the sustainable development of the water-energy-food system (WEF) is facing challenges. Wetlands, as key ecological hubs, play a crucial role in regulating water cycles, energy metabolism, and food production, thus serving as a breakthrough point for resolving the bottleneck of resource synergy. Incorporating wetlands into the WEF framework helps us comprehensively understand and optimize the interrelationships among water, energy, and food. This paper proposes an indicator system based on WEFW to study the coupling of water-energy-food-wetland systems and analyzes the evolution of the comprehensive development index of WEFW and its coupling relationship in Jiangxi Province from 2001 to 2022. It uses the grey correlation model to explore the sustainable development capacity of wetland resources, water resources, energy resources, and food resources in Jiangxi Province, and employs a geographical detector model to quantify the contribution of wetlands to WEFW. The research results show that (1) the comprehensive evaluation of WEFW systems in various cities in Jiangxi Province has generally improved, but there is imbalance in regional development. Cities such as Nanchang and Jiujiang have performed well, while cities like Jingdezhen and Xinyu need to enhance resource integration and sustainable development. (2) The coupling coordination degree (CCD) has experienced a process of “stability-fluctuation-recovery”, with a significant increase after 2014, and the spatial differentiation characteristics are obvious. (3) Wetlands play a dominant role in the spatial differentiation of CCD, and their interaction with water, energy, and food resources significantly enhance the explanatory power of their impact on CCD. (4) The grey model indicates that the CCDs of WEFW systems in most cities of Jiangxi Province have a projected annual growth rate of 1.8% (2022–2032), reaching 0.71–0.73 in leading cities. These results emphasize the importance of wetland protection and sustainable resource management in promoting regional coordinated development. The research and prediction of the coupling coordination relationship of water-energy-food-wetland systems can provide a scientific basis for the sustainable development of Jiangxi Province and also offer important scientific references for other regions to achieve a balance between ecological protection and resource utilization. Full article

Understanding the coupled and coordinated development of China’s urban and rural basic education systems is crucial for fostering their interaction and synergistic growth. Using China’s provincial panel data from 2011 to 2023, this study measures the coupled and coordinated development level of urban–rural basic education (CCD-URBE) via the entropy weight method, G1-method and coupling coordination degree model. On this basis, the Dagum Gini coefficient decomposition method, traditional and spatial Markov chain models, as well as convergence test models are employed for empirical research. The results show that: (1) During the study period, the CCD-URBE across the nation and the four major regions improves significantly. Both intra-regional and inter-regional disparities show a consistent downward trend. Inter-regional disparities are the main source of the overall disparities, and the contribution rate of transvariation density to the overall disparities exhibits the most significant increase. (2) The CCD-URBE demonstrates strong stability, as most regions tend to maintain their original CCD-URBE grades. Meanwhile, neighborhood grades moderate the local transition probability significantly. Neighborhoods with high CCD-URBE promote the upward improvement of the local CCD-URBE, while those with low CCD-URBE inhibit it. (3) The CCD-URBE across the nation and the four major regions shows obvious trends of σ-convergence, absolute β-convergence, and conditional β-convergence. The central region, which has lower CCD-URBE, exhibits higher convergence speed. Based on these findings, targeted policy implications are derived. Full article

Placental dysfunction underlies the major obstetric syndromes, including preeclampsia, fetal growth restriction, placenta accreta spectrum, pregnancy loss, and monochorionic twin complications. Recent molecular studies have revealed that dysregulated oxygen sensing, impaired angiogenic signaling, altered immune tolerance, and defective trophoblast fusion represent shared pathogenic pathways that converge across these disorders. Integrating morphological evidence with mechanistic data highlights how villous maldevelopment, shallow trophoblast invasion, and aberrant vascular remodeling translate into clinical disease. Advances in biomarker research have already transformed clinical care: the sFlt-1/PlGF ratio is now established in the prediction and management of preeclampsia, while placental proteins such as PAPP-A and PP13, nucleic acid signatures including cfDNA, cfRNA and miRNAs, and extracellular vesicle cargo show promising potential for early, non-invasive detection of placental pathology. Multi-omics approaches, particularly single-cell and spatial transcriptomics combined with proteomic and metabolomic profiling, are paving the way for composite diagnostic panels that capture the polygenic and multicellular nature of placental disease. This review synthesizes current knowledge of molecular mechanisms, histological correlates, and translational biomarkers, and outlines how precision obstetrics may emerge from bridging mechanistic discoveries with clinical applications. Full article