Search Results (12,394)

As a form of living cultural heritage, local residential landscapes manifest the essence of long-term, resilient human–land interactions. The Wuling Corridor, a vital ethnic and cultural passage connecting the Central Plains with Southwest China in Chinese history, serves as a crucial region for the mixed residence and cultural exchange of Tujia, Miao, Dong, Han, and other ethnic groups. Within this region, Ganlan stands as both the most representative vernacular architectural heritage and a residential form that is still extensively used, constituting a continuous and unique residential landscape. The spatial distribution patterns of Ganlan are the physical witness of the history of ethnic groups adapting to the complex topographic and cultural conditions. Current research focuses on the case description of single Ganlan forms, failing to systematically investigate the spatial formation mechanisms of Ganlan as a residential landscape from a geographical continuum perspective. Therefore, this study establishes a geographical database encompassing 9425 Ganlan samples from the Wuling Corridor. It integrates the geographic information system (GIS) with clustering algorithms to systematically identify the distribution patterns of Ganlan within specific geographic–cultural units and their coupling relationships with natural environments. It conducts quantitative analysis on the key driving factors concerning the emergence and evolution of Ganlan in the study area; the findings reveal the following: (1) Ganlan buildings exhibit a spatially aggregated distribution pattern along major water systems, demonstrating characteristics of multi-ethnic sharing and spatial interweaving. (2) Their distribution is constrained by natural geographical factors and influenced by the transmission pathways of construction techniques during ancient ethnic migrations to the southwest China. (3) Within multi-ethnic settlement structures, inter-ethnic cultural interactions (particularly with Central Plains culture) serve as a key driving force for the typological evolution of Ganlan. (4) The evolutionary lineage of “full-Ganlan,” “semi-Ganlan,” and “courtyard-style Ganlan” systematically demonstrates the dynamic adaptive capacity of local residential systems. Additionally, by integrating massive Ganlan heritage data with multiple spatial analysis methods, the study serves as a typical case study illuminating the adaptive strategies and resilience mechanisms of Ganlan as a local residential landscape formed in response to the environmental conditions and social changes. Also, it provides a scientific basis for the holistic conservation of architectural heritages shared by multiple ethnic groups and the integrated development of local cultural tourism industries. Full article

Investigating the optimal planting strategies for brassica vegetables under variable climatic conditions is essential for developing sustainable production systems in northern agricultural regions. However, comprehensive knowledge about how planting timing modulates growth, physiological responses, and yield parameters across different cultivars remains limited. We investigated vegetative development, root morphology, physiological efficiency, and marketable yield in six cauliflower cultivars (‘Amazing’, ‘Cheddar’, ‘Clementine’, ‘Flame Star’, ‘Snow Crown’, and ‘Vitaverde’) subjected to four planting dates (May 1, May 15, June 1, and June 15) across two growing seasons (2023–2024), followed by detailed morphological and physiological profiling. Planting date, cultivar selection, and seasonal variation significantly influenced all measured parameters (p < 0.001), with notable interaction effects observed for fresh root weight, stomatal conductance, water use efficiency, and yield components. Early planted cultivars consistently demonstrated superior performance under variable environmental conditions, maintaining higher growth rates, enhanced root development, and improved physiological efficiency, particularly ‘Flame Star’, ‘Snow Crown’, and ‘Cheddar’, compared to late-planted treatments. Recovery of optimal plant development was most pronounced at May planting dates, with early-established crops showing better maintenance of vegetative growth patterns and enhanced yield potential, including higher curd weights (585.7 g for ‘Flame Star’) and superior marketable grades. Morphological profiling revealed distinct clustering patterns, with early-planted cultivars forming separate groups characterized by elevated root biomass, enhanced physiological parameters, and superior yield characteristics. In contrast, late-planted crops showed reduced performance, indicative of environmental stress responses. We conclude that strategic early planting significantly enhances cauliflower production resilience through comprehensive optimization of growth, physiological, and yield parameters, particularly under May establishment conditions. The differential performance responses between planting dates provide insights for timing-based management strategies, while the quantitative morphological and physiological profiles offer valuable parameters for assessing crop adaptation and commercial viability potential under variable climatic scenarios in northern agricultural systems. Full article

Water scarcity has become a significant constraint to agricultural development in China. In this study, we employed bibliometric methods to systematically review the current research on crop water use efficiency (WUE) and the development trends in the North China Plain (NCP) and Northwest China (NWC). We analyzed 1569 articles (NCP = 788; NWC = 781) from the Web of Science Core Collection (1995–2025) using visualization tools such as CiteSpace and VOSviewer to investigate annual numbers of publications, leading scholars and research institutions, and then to map keyword co-occurrence and co-citation structures. Our results showed that keyword clustering exhibited high structural quality (NCP: Q = 0.7345, S = 0.8634; NWC: Q = 0.758, S = 0.8912), supporting reliable thematic interpretation. The bibliometric analysis indicates a steady growth in annual publications since 1995, with the Chinese Academy of Sciences and China Agricultural University as leading contributors. From 1995 to 2005, studies centered on irrigation, yield and field-scale WUE, emphasizing the optimization of irrigation strategies and crop productivity. During 2006–2015, the thematic focus has broadened to encompass nitrogen use efficiency, crop quality and eco-environmental performance, thereby moving toward integrated evaluation frameworks that capture ecological synergies. Since 2016, the literature now emphasizes system integration, regional adaptability, climate-response mechanisms and the ecological co-benefits of agricultural practices. Future studies are expected to incorporate indicators such as crop quality, water footprint and carbon isotope indicators to support the sustainable development of agricultural water use. This study offers insights and recommendations for developing a comprehensive crop WUE evaluation framework in China, which will support sustainable agricultural water management and the realization of national “dual carbon” targets. Full article

Urban air pollution caused by vehicular emissions remains one of the most pressing environmental challenges, negatively affecting both public health and climate processes. In Kokshetau, Kazakhstan, where electric vehicle (EV) adoption accounts for only 0.019% of the total fleet and charging infrastructure is nearly absent, reducing transport-related emissions requires short-term and cost-effective solutions. This study proposes an integrated approach combining urban ecology principles with computational modeling to optimize traffic signal control for emission reduction. An artificial neural network (ANN) was trained using intersection-specific traffic data to predict emissions of carbon monoxide (CO), nitrogen oxides (NO_x), sulfur dioxide (SO₂), and particulate matter (PM_2.5). The ANN was incorporated into a nonlinear optimization framework to determine traffic signal timings that minimize total emissions without increasing traffic delays. The results demonstrate reductions in emissions of CO by 12.4%, NO_x by 9.8%, SO₂ by 7.6%, and PM_2.5 by 10.3% at major congestion hotspots. These findings highlight the potential of the proposed framework to improve urban air quality, reduce ecological risks, and support sustainable transport planning. The method is scalable and adaptable to other cities with similar urban and environmental characteristics, facilitating the transition toward eco-friendly mobility and integrating data-driven traffic management into broader climate and public health policies. Full article

We present a high-resolution infrared spectroscopic study of four vibrational bands of the ¹³CF₄ isotopologue: the symmetric stretching fundamental ${\nu }_1$, the triply degenerate bending mode ${\nu }_4$, the combination band ${\nu }_1+{\nu }_4$, and the hot band ${\nu }_1-{\nu }_4$. A global analysis was performed using a tensorial formalism adapted to the $T_{\mathrm{d}}$ symmetry group, allowing for consistent modelling of rotational structures. Reduced energy levels were extracted and fitted simultaneously for the four levels, yielding precise spectroscopic constants. The derived parameters enhance the spectroscopic characterization of ¹³CF₄, a species of interest for isotopic studies and environmental monitoring. A total of 8992 transitions were assigned in the investigated spectral regions. The quality of fit is confirmed by a root mean square (RMS) deviation of about 0.0022 cm⁻¹, highlighting the accuracy of the effective Hamiltonian model. These results provide a robust framework for future line list development and integration into spectroscopic databases such as TFMeCaSDa, HITRAN and GEISA. Full article

Crack segmentation in images plays a pivotal role in the monitoring of structural surfaces, serving as a fundamental technique for assessing structural integrity. However, existing methods that rely solely on RGB images exhibit high sensitivity to light conditions, which significantly restricts their adaptability in complex environmental scenarios. To address this, we propose a structure-aware progressive multi-modal fusion network (SPMFNet) for RGB-thermal (RGB-T) crack segmentation. The main idea is to integrate complementary information from RGB and thermal images and incorporate structural priors (edge information) to achieve accurate segmentation. Here, to better fuse multi-layer features from different modalities, a progressive multi-modal fusion strategy is designed. In the shallow encoder layers, two gate control attention (GCA) modules are introduced to dynamically regulate the fusion process through a gating mechanism, allowing the network to adaptively integrate modality-specific structural details based on the input. In the deeper layers, two attention feature fusion (AFF) modules are employed to enhance semantic consistency by leveraging both local and global attention, thereby facilitating the effective interaction and complementarity of high-level multi-modal features. In addition, edge prior information is introduced to encourage the predicted crack regions to preserve structural integrity, which is constrained by a joint loss of edge-guided loss, multi-scale focal loss, and adaptive fusion loss. Experimental results on publicly available RGB-T crack detection datasets demonstrate that the proposed method outperforms both classical and advanced approaches, verifying the effectiveness of the progressive fusion strategy and the utilization of the structural prior. Full article

Distributed measurement networks, from semiconductor testing arrays to environmental sensor grids, medical diagnostic systems, and agricultural monitoring stations, face a fundamental challenge: undetected site-to-site variations that silently corrupt data integrity. These variations create systematic biases between supposedly identical measurement units, which undermine scientific reproducibility and yield. The current site-to-site variation detection methods require extensive sampling or make rigid distributional assumptions, making them impractical for many applications. We introduce a novel framework that transforms measurement data into density-based feature vectors using Kernel Density Estimation, followed by anomaly detection with Isolation Forest. To automate the final classification, we then apply a novel probabilistic thresholding method using Gaussian Mixture Models, which removes the need for user-defined anomaly proportions. This approach identifies problematic measurement sites without predefined anomaly proportions or distributional constraints. Unlike traditional methods, our method works efficiently with limited samples and adapts to diverse measurement contexts. We demonstrate its effectiveness using semiconductor multisite testing as a case study, where our approach consistently outperforms state-of-the-art methods in detection accuracy and sample efficiency when validated against industrial testing environments. Full article

Rising urban temperatures driven by the Urban Heat Island (UHI) effect highlight the need for architectural strategies that enhance thermal comfort while promoting environmental sustainability. In Budapest’s District 7, characterized by diverse multi-family historical buildings, existing studies predominantly address energy consumption for heating, leaving a gap in passive cooling research. The categorization of typologies derived from the Tabula database, the ZBR strategy, and architectural surveys of the old Jewish quarter is based on heating potential. While historic courtyards offer natural shading and ventilation possibilities, passive cooling strategies remain fragmented. To address this, the paper introduces the “Adaptive Block,” a mid-rise, modular typology integrating courtyard ventilation, dynamic shading, high-albedo surfaces, and low-conductivity insulation. Climate Consultant software is used to analyze passive cooling strategies based on climate data from a local meteorological station, the Budapest Meteorological Center station (WMO ID: 12840), which is an official national station. This serves as a preliminary step to guide future energy simulations by narrowing down the most effective design interventions. The Climate Consultant tool was applied not as a final performance simulation but as a Passive Strategy Pre-Assessment. This pre-assessment bridges regional climate data with building-scale adaptation by identifying which passive cooling options are climatically justified before typology-specific constraints are introduced. By combining the most promising adaptive features from existing typologies, the Adaptive Block presents a scalable framework that supports urban climate resilience while respecting architectural heritage. The findings contribute to adaptive urban design and invite further exploration of its applicability in other existing urban contexts. Full article

Morphological plasticity (MP) is an essential strategy for plants in nutrient acquisition, disturbance alleviation, and community coexistence during environmental and climatic changes. However, to date, there has been little research concerning the MP for alpine–subalpine forests on the Qinghai–Tibet plateau. These forests are representative of the ectomycorrhizal (ECM) type, and morphological traits of these ECM roots, such as root tip lengths, diameters, and their adherent hyphal lengths and exploration types, have rarely been studied in the context of nutrient and environmental gradients. In this study, we examined the morphological traits of ECM roots for faxon fir (Abies fargesii var. faxoniana), which dominated in subalpine forests across nine elevations on the Eastern Qinghai–Tibet plateau. By quantifying ca. 90,000 root tips, the hyphal lengths of ectomycorrhizal extraradical mycelium (EEM, i.e., short- and long-distance exploration types) reached up to 1.1 × 10⁶ cm/m³ in soil, which decreased significantly due to gradually increasing altitude. In contrast, the variability of ECM root traits (diameter, length, and superficial area) was highly conserved along the altitudinal gradients, yet the root tip lengths were positively associated with soil protease enzyme activity. The increase in diameter and length of ECM root tips was climate-independent yet significantly associated with increasing root N concentration. In the studied forests, a long-distance exploration type of ECM hyphae was controlled by precipitation (p < 0.05), whereas the short-distance one was controlled by precipitation and temperature simultaneously. The EEM lengths of short- and long-distance exploration types were associated with high C concentration and low N concentration in host tree root tissues. Our findings demonstrated that MP expression in nutrient-foraging strategies for the dominant coniferous trees facilitates the adaptation to changing environments by specialized hyphal structures. In conclusion, ECM root tips and hyphal structures are two dimensions of functional traits linked to root N concentration in opposite ways, and their MP collectively ensures the temporal stability and resistance of subalpine forests on the Qinghai–Tibet plateau. These results provide new insights into ECM morphological traits and their adaptation in changing environments, which is valuable for understanding responses of subalpine forests to climate change. Full article

Przewalski’s gazelle (Procapra przewalskii) is an endangered ungulate endemic to the Qinghai–Tibet Plateau, with a small population size and exposure to multiple ecological pressures. Its gut microbiota may play a crucial role in host environmental adaptation. To investigate the functional divergence of gut microbial communities, we performed high-throughput metagenomic sequencing on 105 wild fecal samples collected from 10 geographic regions around Qinghai Lake. The results revealed significant regional differentiation in key functional modules related to metabolism, antibiotic resistance mechanisms, and virulence-associated pathways. All populations showed enrichment in core metabolic pathways such as carbohydrate and amino acid metabolism, with carbohydrate-active enzymes dominated by glycoside hydrolases (GHs) and glycosyltransferases (GTs), exhibiting overall functional conservation. Although populations shared many antibiotic- and virulence-related reference genetic markers, the marker composition associated with distinct resistance mechanisms and pathogenic processes exhibited clear population-specific patterns, suggesting differential microbial responses to local environmental pressures. Correlation network analysis further identified core taxa (e.g., Arthrobacter and Oscillospiraceae/Bacteroidales lineages) as key genera linking community structure with core metabolic, resistance-related, and virulence-associated marker functions. Overall, the gut microbiota of Przewalski’s gazelle exhibits a complex spatially structured functional differentiation, reflecting host–microbiome co-adaptation under region-specific ecological pressures. These findings provide critical methodological and theoretical support for microecological health assessment and regionally informed conservation management of this endangered species. Full article

In the context of global efforts toward energy conservation and emission reduction, accurate short-term electric load forecasting plays a crucial role in improving energy efficiency, enabling low-carbon dispatching, and supporting sustainable power system operations. To address the growing demand for accuracy and stability in this domain, this paper proposes a novel prediction model tailored for power systems. The proposed method combines Spearman correlation analysis with modal decomposition techniques to compress redundant features while preserving key information, resulting in more informative and cleaner input representations. In terms of model architecture, this study integrates Bidirectional Gated Recurrent Units (BiGRUs) with dilated convolution. This design improves the model’s capacity to capture long-range dependencies and complex relationships. For parameter optimization, an Improved Beluga Whale Optimization (IBWO) algorithm is introduced, incorporating dynamic population initialization, adaptive Lévy flight mechanisms, and refined convergence procedures to enhance search efficiency and robustness. Experiments on real-world datasets demonstrate that the proposed model achieves excellent forecasting performance (RMSE = 26.1706, MAE = 18.5462, R² = 0.9812), combining high predictive accuracy with strong generalization. These advancements contribute to more efficient energy scheduling and reduced environmental impact, making the model well-suited for intelligent and sustainable load forecasting applications in environmentally conscious power systems. Full article

The application of Artificial Intelligence (AI) in river basin pollution control shows great potential to improve governance efficiency through real-time monitoring, pollution prediction, and intelligent decision-making. However, its rapid development also brings regulatory challenges, including data privacy, algorithmic bias, responsibility definition, and cross-regional coordination. Based on the SETO loop framework (Scoping, Existing Regulation Assessment, Tool Selection, and Organizational Design), this paper systematically analyzes the regulatory needs and pathways for AI in watershed water pollution control through typical case studies from countries such as China and the United States. The study first defines the regulatory scope, focusing on protecting the ecological environment, public health, and data security. It then assesses the shortcomings of existing environmental regulations in governing AI, such as their inability to adapt to dynamic pollution sources. Subsequently, it explores suitable regulatory tools, including information disclosure requirements, algorithmic transparency standards, and hybrid regulatory models. Finally, it proposes a multi-tiered organizational scheme that integrates international norms, national legislation, and local practices to achieve flexible and effective regulation. This study demonstrates that the SETO loop provides a viable framework for balancing technological innovation with risk prevention and control. It offers a scientific basis for policymakers and calls for establishing a dynamic, layered regulatory system to address the complex challenges of AI in environmental governance. Full article

The Mediterranean Diet (MD) is globally recognized not only for its well-established benefits to human health but also for its potential as a sustainable dietary model from environmental perspectives. Primarily based on plant-based foods, olive oil, fish, and seasonal and local products, the MD stands out for its ability to reduce overall mortality and the incidence of chronic diseases. At the same time, it is a low environmental impact dietary approach, contributing to the reduction in greenhouse gas emissions, water savings, biodiversity conservation, and soil regeneration. This narrative review was conducted by searching the Scopus and PubMed databases, covering all publications up to 2011, applying predefined inclusion and exclusion criteria, and ultimately including 33 studies. The paper provides a synthesis of the key elements that make the MD a paradigm of sustainability, analyzing critical indicators such as carbon, water, and energy footprints, land use, food waste generation, and carbon sequestration. It also addresses the decline in adherence to the MD, even in Mediterranean countries, highlighting the socio-economic, cultural, and behavioral causes, as well as the necessary strategies to promote its rediscovery and adaptation to contemporary contexts. Full article

The laser-directed energy deposition (L-DED) technique, with its excellent environmental adaptability and superior repair capability, shows great potential for the repair of damaged X70 pipeline steel. In this work, the microstructure and mechanical properties of L-DED repaired X70 steel were systematically investigated. The deposited material exhibited inhomogeneity along the building direction. From the bottom to the top, the grains gradually coarsened, and the proportion of polygonal ferrite increased. This was mainly attributed to increasing thermal accumulation with deposition height, which reduced the cooling rate and promoted solid-state transformations at higher temperatures. Meanwhile, the heat accumulation and intrinsic heat treatment reduced the dislocation density and promoted Fe₃C precipitation within grains and along boundaries. Microhardness was highest in the bottom region and decreased along the building direction due to the gradual coarsening of microstructure and decreasing in dislocation density. The L-DED X70 showed lower yield strength (435 MPa) and ultimate tensile strength (513 MPa) compared to the base material and API 5L requirements. The elongation of the L-DED X70 was 42.9%, which was 58% higher than that of the base material, indicating excellent ductility. These results revealed a thermal history-dependent strength–ductility trade-off in the L-DED repaired X70 steel. Therefore, more efforts are needed to control the L-DED thermal process, tailor the microstructure, enhance strength, and meet the service requirements of harsh environments. Full article

In an era of global warming, sustainable agriculture, which emphasises the conservation of biodiversity and the rational use of natural resources, is growing in importance. One of the key elements is to increase the genetic diversity of crops through the use of crop wild relatives (CWRs) and local varieties, which provide a source of genes for resistance to biotic and abiotic stresses. Modern agricultural systems are characterised by low biodiversity, which increases the susceptibility of plants to diseases and pests. Growing mixtures of varieties, both intra- and interspecific, is a practical strategy to increase plant resistance, stabilise yields and reduce pathogen pressure. This manuscript has a review character and synthesises the current literature on the use of CWRs, local varieties, and variety mixtures in sustainable agriculture. The main research question of the study is to what extent plant genetic resources, including CWRs and local varieties, as well as the cultivation of variety mixtures, can promote plant resistance, stabilise yields and contribute to sustainable agriculture under climate change. The objectives of the study are to assess the role of genetic resources and variety mixtures in maintaining biodiversity and yield stability, and to analyse the potential of CWRs and local varieties in enhancing plant resistance. Additionally, the study investigates the impact of variety mixtures in reducing disease and pest development, and identifies barriers to the use of genetic resources in breeding along with strategies to overcome them. The study takes an interdisciplinary approach including literature and gene bank data analysis (in situ and ex situ), field trials of cultivar mixtures under different environmental conditions, genetic and molecular analysis of CWRs, the use of modern genome editing techniques (CRISPR/Cas9) and assessment of ecological mechanisms of mixed crops such as barrier effect, and induced resistance and complementarity. In addition, the study considers collaboration with participatory and evolutionary breeding programmes (EPBs/PPBs) to adapt local varieties to specific environmental conditions. The results of the study indicate that the integration of plant genetic resources with the practice of cultivating variety mixtures creates a synergistic model that enhances plant resilience and stabilises yields. This approach also promotes agroecosystem conservation, contributing to sustainable agriculture under climate change. Full article