Search Results (59,745)

The housing sector in major cities is facing escalating challenges due to rapid population growth and land scarcity. Consequently, vertical growth has been adopted as a strategic solution to optimize land use while balancing economic, social, and environmental needs. This study examines the phenomenon of vertical growth of the Dammam Metropolitan Area (DMA) in Saudi Arabia, from an urban sustainability perspective, focusing on evaluating the current state of multi-story buildings, their determinants, and their impact on quality of life and infrastructure efficiency. This study utilizes a systematic review methodology and a conceptual approach to develop an integrated framework for sustainable vertical growth. Furthermore, an empirical validation was conducted by projecting this framework onto vertical housing projects in Dammam, focusing on challenges related to design, construction quality, shared service management, and the suitability of apartments for family needs. The results indicate that the shift toward vertical growth achieves land-use efficiency, limits random horizontal expansion, and provides economic opportunities. However, it faces social and cultural constraints, most notably the resistance of some families to changing traditional ownership patterns, limited privacy and green spaces, and challenges in building maintenance and operations. The study highlights the importance of integrating urban planning, governance, architectural design, and infrastructure to ensure the sustainability of vertical growth and provide suitable housing alternatives. The study recommends further field research to assess social acceptance, improve quality-of-life indicators, and develop policies encouraging sustainable vertical expansion in alignment with Saudi Vision 2030 and the 2030 Sustainable Development Goals (SDGs), ensuring cities are more resilient, efficient, sustainable, and liveable. Full article

Nanofiber scaffolds play a crucial role in bioengineering by providing structural support for tissue and organoid growth. For composite nanofibers, optimizing their properties for specific applications often requires analyzing the spatial distribution of their chemical structure. This review focuses on the applications of Raman hyperspectral imaging to the mapping of the chemical composition of nanofibers. While the technique is diffraction-limited to the size of the scanning beam, it is possible to decipher the nanoscale features of these fibers by employing oversampling during scanning. Subsequently, these oversampled data can be analyzed by a singular-value decomposition (SVD) analysis and classical least-squares (CLS) decomposition. In many cases, this technique is essential for verifying the spatial distribution of different chemical components within multi-component nanofibers. Full article

Improving the cultivated land use eco-efficiency (CLUE) is crucial to achieving sustainable land use and the green transformation of agriculture. This study is based on the data from 353 prefecture-level cities in China from 2013 to 2021. The slacks-based measurement (SBM)-undesirable model, the social network analysis (SNA), and the fuzzy set qualitative comparative analysis (fsQCA) are adopted to measure and analyze the spatial patterns, network characteristics, and multiple driving pathways of inefficiency in the cultivated land use eco-efficiency in prefecture-level administrative units. Results show the following: (1) From 2013 to 2021, CLUE in the study areas shows spatial heterogeneity, with most efficiency values at a moderate level and showing a fluctuating downward trend over time. (2) The nine major agricultural regions have formed a complex association network, with the overall network connectivity being weak but efficiency relatively high. The hierarchical structure is gradually flattening, and inter-regional cooperation is increasing. (3) There are significant differences in influence, control, and accessibility within individual networks, and the collaborative network is developing into a “multi-core-hierarchical” structure. (4) The formation of inefficiency involves multiple concurrent mechanisms. Four typical inefficiency paths were identified, with significant heterogeneity across different agricultural regions. In the future, differentiated land use and ecological protection policies should be implemented based on the spatial network characteristics and inefficiency driving pathways of each agricultural region to promote the coordinated improvement of CLUE. Full article

Quinoline derivatives constitute a privileged class of nitrogen-containing heterocycles with extensive applications in medicinal chemistry, agrochemicals, materials science, and functional organic materials. Owing to their broad biological and industrial relevance, the development of efficient, selective, and sustainable synthetic methodologies for quinoline construction remains an active area of research. This review provides a comprehensive overview of recent advances in quinoline synthesis, with particular emphasis on catalytic strategies aligned with the principles of green and sustainable chemistry. Classical transformations, including the Friedländer, Skraup, and Povarov reactions, are revisited in the context of modern catalytic developments that improve reaction efficiency, substrate scope, selectivity, and environmental compatibility. Special attention is devoted to homogeneous and heterogeneous catalytic systems based on both platinum-group and earth-abundant transition metals, highlighting the growing importance of borrowing-hydrogen and acceptorless dehydrogenative coupling methodologies. Recent progress in nanocatalysis, photocatalysis, multicomponent reactions, ionic-liquid-mediated transformations, and metal-free protocols is also critically discussed. Furthermore, solvent-free processes, microwave-assisted synthesis, and recyclable catalytic systems are examined as practical approaches toward minimizing waste generation and energy consumption. Mechanistic aspects, catalytic design principles, substrate limitations, and sustainability metrics are evaluated throughout the review to provide a critical perspective on current methodologies. Collectively, the advances summarized herein demonstrate the rapid evolution of quinoline synthesis toward more atom-economical, environmentally benign, and operationally efficient processes, while also identifying future opportunities for the development of next-generation catalytic platforms for quinoline-based heterocycle construction. Full article

Quantifying the impact of land use changes on the threat of flash-floods is a critical consideration in flood hazard planning and risk reduction, and is an area of active research. Here, a coupled Weather Research and Forecasting model hydrological extension package (i.e., WRF-Hydro) modeling approach is applied to simulate flash-flooding processes for short-duration, localized, intense precipitation events. To better understand the effect of urbanization on flash floods, a series of numerical experiments is performed surrounding Ellicott City, Maryland, a location which has experienced both significant heavy rainfall events and suburban development over the past several decades. Two intense rainfall events occurring on 30 July 2016 and 27 May 2018 are investigated, respectively, to first calibrate the hydrologic model performance and then quantify the sensitivity of flash flooding to varying degrees of urbanization. Performing the same experiments using observed historical land use states is of more limited insight, as the thrust of suburban development in the Ellicott City region significantly predates satellite-derived land use datasets. Results confirm that urbanization produces larger river streamflow, higher water stages, faster hydrologic responses to achieve peak flow discharge, and shorter recession limbs, even for very intense, short-duration events. The collective findings suggest that WRF-Hydro is applicable for both watershed flash flood prediction and hypothesis testing, and demonstrates potential utility to urban development decision-makers in locations such as Ellicott City, which could face future increases in catastrophic flooding. Full article

Climate change is progressively altering the thermal environment of European agriculture, with direct consequences for high-value perennial crops such as olive (Olea europaea L.) and grapevine (Vitis vinifera L.). Although the Growing Degree Days (GDD) index is widely applied to characterize crop thermal requirements, no systematic evidence exists on the actual GDD values accumulated at the locations where these crops are currently grown across Europe. This study introduces a “reverse agroclimatology” approach that anchors GDD calculations exclusively to olive grove and vineyard areas identified in the Corine Land Cover (CLC) dataset for five reference years (1990, 2000, 2006, 2012, and 2018), using ERA5-Land reanalysis daily temperature data as the climatological input. For each CLC reference year, GDD was computed for olive cultivation (T_base = 7 °C, January–May) and viticulture (T_base = 10 °C, April–October) exclusively over registered cultivation pixels, and per-country means were subjected to linear regression trend analysis (p < 0.05). For olive cultivation across 11 Mediterranean countries, statistically significant positive GDD trends were detected in 7 countries, with long-term (1985–2023) country means ranging from 476.2 GDD in France to 1214.3 in Cyprus, indicating that we can revise the known GDD thresholds. The first appearance of olive cultivation in Slovenia’s 2012 CLC dataset, with a median of 546.5 GDD, provides land use-mapped evidence of a spatial displacement of cultivation boundaries. For vineyard cultivation across 22 European countries, significant positive trends were identified in 18 countries, with warming rates reaching 19.25 GDD yr⁻¹ in Turkey, 15.83 GDD yr⁻¹ in Albania, and 14.89 GDD yr⁻¹ in Bosnia and Herzegovina. Mediterranean and Balkan vineyards already exceed the classical 2000 GDD threshold of viticultural suitability across all reference years. In contrast, central and northern European registered vineyards operate below it, though their warmest sites are increasingly approaching or crossing it in the most recent periods. The cultivation-anchored GDD framework, built on openly available data and a fully reproducible R-based pipeline, provides a practical and updatable tool for monitoring the evolving thermal conditions of European olive and wine production under ongoing climate change. Full article

Background/Objectives: The increasing burden of non-communicable diseases, together with accelerating environmental degradation, highlights the urgent need for sustainable dietary patterns that promote both human and planetary health. The Mediterranean diet (MedDiet), traditionally followed in countries bordering the Mediterranean basin, has gained recognition as a model of sustainable nutrition due to its well-documented health benefits and relatively low environmental impact. However, its broader role within sustainable food systems requires comprehensive and interdisciplinary evaluation. The aim of this review is to provide a state-of-the-art synthesis of the evidence on the MedDiet as a sustainable dietary pattern, integrating its health, environmental, economic, and socio-cultural dimensions. Methods: This state-of-the-art narrative review synthesizes evidence from peer-reviewed literature on the MedDiet and sustainability. Relevant studies were identified through major scientific databases, focusing on publications addressing nutritional, environmental, economic, and socio-cultural dimensions. Both observational and interventional studies, as well as modeling and life cycle assessment analyses, were included. Additional sources from international organizations and policy reports were incorporated to contextualize global trends and challenges. Results: High adherence to the MedDiet is consistently associated with a reduced risk of cardiovascular disease, type 2 diabetes, cancer, and all-cause mortality. From an environmental perspective, the MedDiet is associated with lower greenhouse gas emissions, reduced land and water use, and enhanced biodiversity conservation compared with Western dietary patterns. Economically, it may represent a cost-effective dietary model and support local food systems when grounded in traditional practices, although affordability varies across contexts. Socio-culturally, the MedDiet promotes food heritage, culinary skills, and social cohesion. Nevertheless, globalization, urbanization, and the increasing consumption of ultra-processed foods have contributed to declining adherence, posing significant challenges to its sustainability and scalability. Moreover, the sustainability benefits of the MedDiet seem to be context-dependent rather than intrinsic, raising several challenges and limitations for its adoption. Conclusions: The MedDiet should be viewed not as a definitive solution to global food-system challenges but as a valuable reference model that illustrates how dietary practices can contribute simultaneously to human health, environmental sustainability, and cultural continuity. Modern sustainable dietary strategies should build upon the strengths of the MedDiet while recognizing its limitations, embracing contextual adaptation, and addressing the structural determinants that shape food choices. Full article

Although interior-point methods (IPMs) have transformed mathematical programming since 1984, the original projective Karmarkar algorithm is rarely documented step by step on reproducible engineering examples that combine algorithmic transparency with real resource allocation constraints. This article therefore does not propose a new variant of Karmarkar’s algorithm; rather, its scientific contribution is the reproducible MATLAB implementation, canonical-form conversion, and comparative validation of the original projective method against the revised Simplex method and Barnes’ affine scaling variant in two engineering settings. The case studies are (i) the minimum-weight plastic design of a rigid frame with seven candidate plastic hinge locations and six collapse mechanisms and (ii) the optimal allocation of crop patterns in the Caplina Valley (Tacna, Southern Peru), an arid irrigated system with an irrigated command area of 1253 ha, monthly labor availability of 22,239 jornales, and water availability derived from Caplina River discharges at 75% persistence. For Case I, the algorithm reached F = 1.001 in the normalized dual space, which corresponds to F = 4.251 in the original structural objective after applying the scaling factor 17/4; relative to the analytical optimum F* = 4.25, this gives |4.251 − 4.25|/4.25 = 2.4 × 10⁻⁴ after 20 iterations. For Case II, the model yielded the maximum net production value of USD 703,135.92, allocating 948.47 ha among 12 crops while satisfying water, labor, market, and land constraints. The double validation confirms the algorithm’s strictly interior trajectory, polynomial-time rationale, and transparent internal parameters (α = 0.7968, ε = 10⁻⁸), making the implementation a reproducible benchmark for educational use and for future AI–operations research hybrid solvers in regions with limited access to commercial optimization software. Full article

Multi-modal land cover classification plays an important role in remote sensing applications such as urban monitoring and environmental analysis. By integrating complementary information from hyperspectral imagery (HSI) and LiDAR data, multimodal learning can significantly improve classification performance. However, existing Transformer-based fusion methods often suffer from high computational complexity and inefficient cross-modal interaction modeling, which limits their applicability in resource-constrained scenarios. To address these challenges, we propose LMFusion, an efficient framework for multimodal feature learning. Specifically, LMFusion enables efficient bidirectional feature interaction through a linear-complexity cross-attention mechanism and enhances long-range spatial-spectral representation learning with Mamba-based state space modeling, thereby achieving effective multimodal dependency modeling with linear computational complexity. In addition, a selective quantization-aware optimization strategy is introduced to support multiple bit-width settings (down to 1-bit), yielding a more compact and efficient model while improving representation robustness under low-bit constraints. Extensive experiments on the Houston2013, MUUFL, and Augsburg datasets demonstrate the effectiveness of LMFusion. It achieves overall accuracies of 95.84%, 94.95%, and 99.05%, respectively, consistently outperforming representative multimodal classification methods and showing strong potential for accurate and efficient multimodal remote sensing classification. Full article

Understanding trade-offs and synergies among ecosystem services (ESs) along environmental gradients is crucial for sustainable oasis management. This study investigated four key ESs—carbon storage (CS), habitat quality (HQ), water yield (WY), and soil conservation (SC)—in three typical oases along water–heat gradients in arid northwestern China. The InVEST model was used to quantify ESs in 1990, 2005, and 2022, and Pearson correlation, geographically weighted regression, K-means clustering, and random forest models were applied to analyze service relationships, ecosystem service bundles (ESBs), and driving factors. The results showed that CS and HQ maintained strong synergies, while the WY–SC relationship shifted from weak trade-offs under drier conditions to stronger synergies under more favorable water–heat conditions. Geographically weighted regression revealed spatial heterogeneity and directional asymmetry in ES relationships. Four ESB types were identified: ecologically fragile zones, ecological transition or buffer zones, agricultural production zones, and core ecological source zones. Driving-factor analysis indicated that vegetation-related services were mainly associated with land-cover structure and vegetation growth, whereas hydrological and erosion-related services were more closely linked to precipitation, potential evapotranspiration, temperature, and topography. These findings support differentiated oasis management through ecological restoration, development regulation, water-saving agriculture, and strict ecological protection. Full article

Hantaviruses are emerging rodent-borne pathogens that pose increasing global public health concerns due to their association with hemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS), both of which can result in substantial morbidity and mortality. Environmental change, climate variability, urbanization, and land-use transformation are increasingly recognized as critical drivers of hantavirus emergence and transmission. This review summarizes current evidence regarding hantavirus virology, epidemiology, pathogenesis, clinical manifestations, diagnostics, surveillance systems, prevention strategies, and One Health preparedness approaches. Emphasis is placed on the influence of climate change and ecological disruption on rodent reservoir dynamics and spillover risk, as well as major surveillance and diagnostic gaps in tropical and Caribbean regions where hantavirus circulation may be underrecognized. Advances in molecular diagnostics, genomic surveillance, vaccine development, monoclonal antibody therapies, and climate-based early warning systems are also discussed. Existing evidence highlights the importance of integrated One Health surveillance systems that combine human, animal, and environmental monitoring to improve early detection and outbreak preparedness. Strengthening laboratory capacity, ecological surveillance, regional collaboration, and public health infrastructure will be essential for reducing the global burden of hantavirus infections and improving preparedness for future zoonotic disease threats. Full article

Sustainable land-use regulation in historical and cultural cities requires balancing heritage conservation, development demand, cropland retention, and urban–rural spatial restructuring. However, the stage-wise reorganization of urban–rural construction land under these coupled pressures remains insufficiently understood. Taking Jingzhou District, China, as a case study, this study uses land-use data from 2000, 2005, 2010, 2015, and 2020 and integrates stage-wise random-forest analysis, consistency-based interaction-network mining, and multi-scenario simulation within the intPLUS framework. Population, GDP, and areal-water distance layers were matched to the corresponding stage-terminal snapshots where applicable, whereas 2020 POI data were used as contemporary spatial-context proxies. From 2000 to 2020, urban industrial land (UIL) expanded from 16.63 to 46.42 km², increasing by approximately 179.1%, whereas rural settlements (RS) increased more moderately from 56.59 to 60.27 km², increasing by approximately 6.5%. The stage-wise RF and interaction-network results show that UIL and RS followed different spatial association structures, with stronger UIL self-reinforcement and stronger RS self-continuity in the later stage. Historical validation showed overall accuracy values of approximately 91% and Kappa values around 0.80, but FoM values remained relatively low, ranging from 0.098 to 0.176. Class-specific mapping accuracy was higher for RS (81.90–82.37%) than for UIL (55.20–66.93%), indicating a weaker performance in locating UIL change. Therefore, the 2035 simulations should be interpreted as parameter-conditioned regulatory comparisons rather than deterministic pixel-level forecasts. The scenario results indicate that the conservation-oriented limited growth was associated with the restricted UIL expansion and better cropland retention under the prescribed demand and constraint settings, while the RS reduction occurred only under explicit village-consolidation and construction-land quota reallocation assumptions. By distinguishing UIL and RS, this study provides differentiated regulation-oriented evidence for sustainable land-use governance in historical and cultural cities. Full article

Due to climate change and rapid urbanization, cities worldwide face the dual challenge of improving flood resilience and providing accessible green space within limited land resources. Sponge City parks offer a landscape-based approach for integrating stormwater management with park services. However, how park morphology structures this combined performance remains insufficiently understood. This study examines 26 Sponge City parks in Shanghai and evaluates how node-, line-, and patch-type morphologies are linked to stormwater storage and service provision. Using geospatial analysis, DEM-derived catchment delineation, land-cover interpretation, and statistical analysis, this study compares estimated stormwater storage, storage efficiency, local park availability, and land-cover composition across different park morphologies. The results show that estimated performance of stormwater management and park service provision vary across morphological types, but these differences do not follow a simple node–line–patch hierarchy. Rather, the observed patterns are jointly shaped by park morphology, catchment setting, land-cover allocation, and surrounding urban context. These findings suggest that Sponge City parks should not only be evaluated by total stormwater storage. Their contribution depends on morphology, scale, catchment setting, land-cover allocation, and urban context. The study provides a morphology–performance perspective to support more differentiated planning of multifunctional green infrastructure. Full article

Rapid urbanization reshapes urban land systems and intensifies surface thermal heterogeneity, yet nonlinear day–night land surface temperature (LST) responses to grey–green spatial organization and building morphology remain insufficiently understood, particularly in thermally stressed areas across the urban–rural gradient. Using Xi’an, China, as a case study, this study develops a priority-area-based land–climate interaction framework. Priority areas were defined as grid cells where elevated LST coincided with relatively strong local explanatory relationships between LST and land-cover or morphological variables. Multiscale geographically weighted regression (MGWR), gradient boosting decision trees (GBDTs), SHAP-based interpretation, and threshold sensitivity analysis were combined to identify dominant drivers, nonlinear response patterns, and interaction structures of daytime and nighttime LST. The results show pronounced day–night differentiation: daytime hotspots were concentrated in the built-up core, whereas nighttime hotspots extended toward the urban–rural fringe. Daytime LST was mainly associated with building coverage and grey-space organization, while nighttime LST was more strongly related to mean building height and the cooling contribution of green-space coverage. The analysis further identified localized empirical response ranges for built-up intensity, grey-space connectivity, building height, and green-space coverage within the priority areas. These findings clarify how land-cover configuration and building morphology jointly shape day–night surface thermal responses and provide context-specific evidence for land-use planning and targeted urban heat mitigation. Full article

Straw return and tillage practices can alter the soil properties and regulate the bacteria communities, which mediate nitrogen (N) transformation and accumulation. This study aims to elucidate the mechanisms of microbially driven N retention, providing a foundation for soil management strategies. A field experiment was conducted in 2019–2022, six treatments were set up, including rotary tillage with/without straw (RTSR and RTNS), deep tillage with/without straw (DTSR and DTNS), subsoiling with/without straw (STSR and STNS). Soil properties, N pools/fractions and bacterial communities were measured. The results showed that straw return and tillage practices ameliorated soil environment (reducing bulk density (by 7–8% via DTSR and STSR) and salinity (with 57% and 26% increase in DTSR and STSR compared with RTSR, while rotary tillage significantly reduced salinity), increasing soil organic matter (via RTSR treatment, with 5–16% significant increase in two years) and effectively promoting N accumulation. The number of OTUs and the α-diversity significantly increased in 2022 compared with 2021. Specifically, tillage was the main driver of bacterial α-diversity, but there was no significant influence on bacterial β-diversity. Mental test results showed that N availability is a pivotal environmental factor shaping the bacteria α- and β-diversity. Structural equation modeling revealed that SON accumulation directly drove N accumulation via the “environmental improvement–specific microbial community structure” pathway. STSR is the optimal treatment for promoting N accumulation by maintaining active SON levels, which is an effective strategy for sustainable N management in the Yellow River Delta (YRD). Full article