Search Results (1,482)

Plant branching is a complex biological trait that reflects plant adaptation to light, temperature, water, and other environmental factors. Branch architecture and patterns shape canopy morphology and physiological activities, and further affect plant growth and development. In this study, we investigated the branching structure and patterns of eight species in an urban forest in Shanghai, including four tree species (Cinnamomum camphora, Ginkgo biloba, Metasequoia glyptostroboides, Cedrus deodara), two shrub species (Prunus cerasifera f. atropurpurea, Phyllostachys nigra), and two herb species (Medicago sativa, Equisetum ramosissimum). We compared branch number and length across four horizontal directions (east, south, west, north) and two vertical directions (south, north), fitted canopy morphology models, and calculated fractal dimensions based on branch diameter distribution. For the six woody species, branch length and quantity showed no obvious horizontal asymmetry, while the two herb species had better-developed southward branches. Canopy shapes were mainly fitted with quadratic (parabolic) functions. By contrast, coniferous trees and E. ramosissimum presented linear relationships. Fractal dimension increased with plant height in woody species, whereas no such trend was observed in herbs. This study aims to address the following questions: (1) Are there quantifiable differences in horizontal and vertical branching characteristics among trees, shrubs, and herbs? (2) Can fractal dimension serve as a reliable indicator to distinguish such differences? (3) Is there a correlation between fractal dimension and plant height? This is a descriptive and exploratory study, and no biological mechanisms are examined herein. Full article

Linpan in Chengdu Plain, a distinctive form of dispersed rural settlement on the Chengdu Plain, is composed primarily of traditional rural dwellings embedded within woodlands environments. These settlements play multifunctional roles related to agricultural production, daily life, ecological sustainability, and the preservation of folk culture, thereby holding significant ecological and cultural value. In recent decades, rapid urbanization has profoundly impacted the spatial patterns, ecological environments, and livelihood systems of Linpan in western Sichuan, posing severe challenges to their preservation and development. To investigate the extent and nature of these changes, this study examines the spatiotemporal evolution of Linpan in Chengdu over five time periods from 1980 to 2020, employing both macro- and micro-scale analyses. Settlement types were classified based on their transformation trajectories, and representative cases were selected to identify and interpret the key driving forces behind these changes. The results indicate that: (1) at the macro level, Linpans have undergone a clear transition from small-scale, widely distributed, and irregularly shaped patterns to more centralized, aggregated, and standardized spatial configurations, particularly in the peri-urban areas of Chengdu; (2) at the micro level, the internal composition of Linpan has changed substantially, with a marked decline in woodlands coverage. The original integration of buildings and trees has shifted towards a spatial arrangement characterized by peripheral and fragmented vegetation; (3) Changes in production methods have prompted the spatial restructuring of Linpan settlements, transitioning from uniformly dispersed arrangements to clustered formations along road-adjacent resource points. Concurrent population and housing migration has reduced the total number of Linpan, while individual settlements have increased in size and density. Additionally, planning and construction policies have guided the morphological transformation of Linpan from organically evolved forms to geometrically regular configurations. Full article

Background: Strychnos madagascariensis Poir (Loganiaceae) is a drought-tolerant indigenous fruit tree of East and southern Africa, valued for its food, medicinal, and socio-economic contributions to rural communities. Despite its importance as a candidate food crop, intraspecific morphological and genetic diversity had not previously been characterized, and no simple sequence repeat (SSR) markers had been developed for this species, leaving breeders and conservation planners without the basic diversity baseline needed to prioritize material for domestication. Methods: This study assessed vegetative and reproductive trait variation, variance components, and broad-sense heritability, and SSR-based genetic diversity among 27 morphologically defined S. madagascariensis morphotypes at Bonamanzi Game Reserve, KwaZulu-Natal, South Africa. Three trees were measured per morphotype (81 trees total), over two growing seasons. Genetic diversity was characterized in one representative tree per morphotype using seventeen newly developed SSR loci, the first such markers reported for this species, and analyzed with population structure (STRUCTURE version 2.3.4), PCA, and Nei’s genetic distance. Results: Twenty-seven morphotypes were identified based on leaf colour, shape, hairiness and size, dominated by grey (41%), elongated (59%), less hairy (48%), and medium-sized (>50–90 mm) leaves. Fruit diameter and mass showed the highest inter-morphotype variation (r = 0.949) and also the highest broad-sense heritability (H² = 55.3% and 47.8%, respectively), indicating strong genetic control of these traits and their suitability as targets for selective breeding. Environmental variance exceeded genotypic variance for most traits. A total of 144 alleles were identified across 17 SSR loci (mean 4.24 alleles/locus; mean PIC = 0.31). Population structure gave a preliminary, tentative signal of two genetic clusters (K = 2) with substantial admixture, which we interpret cautiously, given the limited sampling depth. Conclusions: This is the first study to characterize intraspecific morphological variation in S. madagascariensis and the first to develop SSR markers for the species. The results provide a preliminary, single-site framework for conservation genetics and crop improvement that should be validated with larger, multi-site samples. Grey morphotypes GyEvH1, GyEvH2, GyEvH3, GyRlH1 and GyEH2 combined consistent fruiting performance with favourable fruit-trait values and are proposed as priority candidates for further evaluation in domestication and breeding programmes. Full article

Contemporary buildings and urban spaces are increasingly expected to support psychological well-being—a quality often termed “restorativeness.” Conventional approaches to quantifying restorativeness rely on subjective surveys or coarse green metrics, failing to capture how specific building morphologies and street-level visual configurations shape restorative experiences, particularly for stress-prone groups such as young adults. This study develops a deep-learning-driven framework linking building visual elements to youth-specific perceived restorativeness, using Changsha, China, as a testbed. The framework comprises three AI-powered modules: the TrueSkill algorithm trains a deep learning model to predict six dimensions of youth perception (e.g., beautiful, clean, safe) from pairwise comparisons of street view images; the Mask2Former architecture segments street-level imagery into 18 building and street attributes; and the XGBoost-SHAP pipeline uncovers nonlinear associations and threshold-like patterns between these attributes and the composite Built Environment Restorativeness Index (BERI). Results reveal three key insights: tree coverage shows a sustained positive association without saturation; building density exhibits a weakening association at high levels, suggesting possible saturation; and road proportion follows a bidirectional pattern, shifting from negative to positive beyond a certain range. Spatially, high BERI zones concentrate where ecological assets and diverse building functions co-occur, while youth perception exhibits systematic mismatches (e.g., “beautiful but not clean,” “safe but not lively”), traceable to imbalances in building form, street furniture, and commercial mix. These findings advance AI-assisted evaluation of built environments by shifting from one-dimensional metrics to interpretable, design-relevant diagnostics, offering a replicable evidence base for crafting youth-responsive buildings and streets. Full article

Determining the relative impacts of climate variability and human activities on vegetation dynamics remains a central theme in paleoecological research. In climate transition zones like the southeastern Marmara region, isopollen maps are important because they allow for the evaluation of spatially diverse pollen records within an integrated regional framework. The aim of this study is to present a spatially holistic reconstruction of Late Holocene vegetation change in the southern Marmara region using isopollen maps based on fossil pollen records obtained from Manyas, Iznik and Sapanca lakes. Isopollen maps were created for five time periods, approximately 2600, 2000, 1250, 800 and 400 yr BP, representing major climatic and historical phases of the Late Holocene, and the spatial distribution patterns of the major tree and herbaceous taxa were reconstructed. The results demonstrate the presence of a continuous west–east variability in the region’s vegetation structure, reflecting the transition between Mediterranean and Black Sea climate regimes. However, the temporal variation patterns show that vegetation responses cannot always be directly explained by climatic phases. In particular, Artemisia highlights the persistence and local expansion of open-area vegetation, reaching approximately 24% of the study area to the present day. Given the region’s long history of settlement, these findings indicate that vegetation dynamics during the Late Holocene were shaped by the combined effects of climatic changes, local environmental conditions and human activities. Therefore, the study emphasizes the importance of spatially integrated approaches in paleoecological reconstructions. Full article

Machine learning (ML) is highly effective for modeling the complex factors governing twinning in magnesium (Mg) alloys, but it is often limited by challenges in hyperparameter optimization and a lack of interpretability, which reduce predictive accuracy and hinder mechanistic understanding. In this work, we present an enhanced interpretable ML framework that integrates Optuna for automated hyperparameter tuning using tree-structured Parzen estimators and SHapley Additive exPlanations (SHAP) for quantitative feature attribution. This approach delivers significant performance improvements, including F1-score gains of 6.33–11.84% on dataset T and AUC increases of up to 16.31% on dataset Y, outperforming previous benchmarks. When applied to a custom dataset derived from in situ EBSD tensile tests on Mg alloys and complemented by molecular dynamics (MD) simulations, SHAP analysis reveals a previously unrecognized grain shape-orientation effect: elongated grains with long-axis orientations of 20–80° relative to the tensile direction facilitate twinning nucleation, whereas orientations of 0–20° or 80–90° suppress it. Combined EBSD observations and MD simulations indicate that this effect arises from changes in boundary-segment orientation combinations, which regulate local constraint conditions, stress-transfer paths, and effective boundary resistance. 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

The escalating energy consumption in China’s rural residences necessitates the adoption of targeted energy-efficient design strategies. However, existing studies have mainly focused on urban buildings or cold-climate rural residences, and insufficient attention has been given to form-based energy optimization for rural housing in hot summer and cold winter regions. Hangzhou was selected because it is a representative city in this climate zone, where rural residences face both summer cooling and winter heating demands. This study systematically investigates passive design pathways for rural residential buildings by optimizing architectural forms. We conducted in-depth field surveys and data analysis on 76 diverse samples, including both self-built and unified construction types, to establish three representative typical residential models (rectangular, L-shaped, U-shaped) for the Hangzhou region. DesignBuilder was employed to simulate the impacts of eight morphological elements—Shape Coefficient, building area, aspect ratio, orientation, number of floors, floor height, floor height ratio, and roof slope—on building energy consumption. The Gradient Boosting Decision Tree (GBDT) method was then used to quantify the nonlinear effects and relative importance of these elements. The results indicate clear nonlinear relationships between elements and the energy-saving rate. Floor height is identified as the most critical factor affecting energy consumption, followed by roof slope, with building area and other elements also showing significant influence. Based on the quantitative analysis, this study proposes energy-efficient design optimization strategies for rural housing in Hangzhou, offering a validated methodological framework and practical design references for the sustainable development of rural residences in hot summer and cold winter regions. Full article

This study examined the effect of east–west orientation of willow tree (Salix alba L.) rows on soil biological activity and weed dynamics in a temperate maize (Zea mays L.) intercropped agroforestry (AF) system in Eastern Hungary. The experiment evaluated how the year (2022, 2023), location (distance from the rows), and irrigation (IR) influenced spatial patterns of earthworm (EW) parameters and weed cover. The study aimed to assess how willow-based AF systems influence soil biological and weed community dynamics under varying IR and row spacing, in comparison with monoculture cropland (MC) systems, and to evaluate their potential role in climate change adaptation in arable farming. Both soil sampling for the EW survey and vegetation studies were conducted along perpendicular transects extending from the tree rows to measure EW abundance and biomass, as well as total weed cover. Experimental results revealed clear spatial gradients in EW distribution and weed abundance near the tree rows, driven by litter input, shading, moisture, and reduced disturbance. These effects were intensified under IR at narrower row spacings. No significant differences were observed between AF-South (shaded), AF-Center, and MC plots; however, significantly higher EW abundance and biomass were found on the AF-North (sunny) side. As for the location, significantly greater total EW abundance was found at AF-North (105.0 individual m⁻²) compared with the MC plots. AF systems enhance soil biological activity and shape weed dynamics through spatial ecological gradients influenced by tree row spacing and irrigation, supporting their role as sustainable land-use systems while emphasizing the need for site-specific management and further long-term optimization. Full article

This pilot study examines how experimentally induced emotional states interact with the visual properties of urban environments to shape comfort perception. A controlled laboratory experiment was conducted with 17 participants assigned to one of four emotional conditions (Fear, Anger, Sad, Happy) through audio-visual induction. Participants evaluated 73 building façade and 42 pedestrian streetscape stimuli from three urban areas in Kitakyushu, Japan (Wakamatsu, Tobata, Mojiko) using a multi-method framework combining fractal analysis (D, Λ), six pedestrian visual metrics, webcam-based eye-tracking (Visual Attention Score, VAS), and self-reported comfort votes. Emotion induction was effective for Fear and Anger groups and partial for Sad and Happy groups, with the latter attributable to experimental fatigue. Cross-method correlation analysis revealed that fractal dimension D significantly predicted comfort vote consensus (Spearman r = 0.369, p = 0.013), while VAS showed no significant relationship with comfort votes (r = 0.097, ns) or with fractal dimension (r = 0.015, ns), confirming that visual attention and comfort preference are independent dimensions. For building façades, the ‘Complex but Organized’ fractal profile (D ≥ 1.70, Λ < 0.60) was the consistent comfort driver across all emotion groups. For pedestrian streetscapes, low spatial enclosure and spatially integrated tree canopy were the primary comfort predictors. Multi-method synthesis identified five empirical paradoxes and three design principles: (1) target D ≥ 1.70 with Λ < 0.60; (2) prioritize spatially integrated canopy over visible greenery quantity; and (3) leverage civic legibility as an independent comfort pathway. These findings support the development of emotion-independent frameworks for urban comfort evaluation. Replication with larger, more diverse samples is recommended. Full article

Multi-runway sequencing of unmanned aerial vehicles (UAVs) at temporary disaster relief aerodromes presents a priority-heterogeneous scheduling problem under class-asymmetric wake turbulence constraints. We formulate this as a priority-weighted Markov decision process with a deliberately minimalist reward—per-step class weights for completed landings, with no shaping or hand-crafted safety logic—and extend it with per-UAV operational deadlines (encoding en-route endurance consumption) and per-runway queue capacity constraints that produce a non-trivial action mask. We train a Proximal Policy Optimisation (PPO) agent and benchmark it against six baselines spanning deterministic optimisation (Joint-LA-1), stochastic lookahead (Stochastic-LA), and online tree search (MCTS). Across 100 paired evaluation episodes, PPO matches the operational standard Priority-FCFS within 2.7% (p = 0.124, not significant); Joint-LA-1, the strongest non-learned baseline, outperforms PPO by 3.2% (p = 0.043). Despite near-identical aggregate throughput, PPO autonomously develops a runway specialisation pattern—concentrating 60% of high-priority landings on a single strip while routing 93% of emergency arrivals to the remaining strips—that emerges entirely from the reward signal. Under looser deadlines, the PPO–PFCFS gap narrows to −0.5%, and wake symmetry ablation reveals that PPO outperforms Priority-FCFS by 46.5% when the asymmetric wake structure is removed. These results demonstrate that priority-aware capacity reservation can emerge without embedded domain knowledge, and that simple heuristics are near-optimal under tight operational constraints—a finding with direct implications for autonomous scheduling in disaster relief aviation. Full article

This study applies the Constructal Design method to the geometric optimization of a branched symmetric concentration divider for calibrating ultrasound devices used to monitor tumor response with dynamic contrast. Accurate calibration ensures image quality and diagnostic reliability. The geometry consists of a three-dimensional, tree-shaped flow network with two inlets and three outlets, where inlet 1 carries water containing contrast particles, while inlet 2 carries only water. Laminar flow simulations are performed using Computational Fluid Dynamics (CFD) with Ansys Fluent, assuming no-slip wall conditions and zero-pressure outlets. The analysis investigates the effects of the inlet velocity ratio, the diameter ratio, and the vertical positions of the central outlet and inlet tubes, while keeping the total volume and inlet diameter constant. Additionally, velocity, pressure, particle distributions, flow partition ratio, and hydraulic resistance are evaluated. Results show nearly linear concentration responses among the outlets (100%, 50%, and 0%) when the device approaches geometric symmetry with equal inlet velocities, demonstrating efficient control of flow splitting. Although the diameter ratio imposes a trade-off with hydraulic resistance, geometric symmetry combined with Constructal Design promotes improved flow uniformity and enhanced performance, with potential applications in microfluidic mixers that require precise intermediate concentrations. Full article

The Eastern Himalayan Syntaxis in the southeastern margin of the Tibetan Plateau is a tectonically active, deeply incised, high-relief region with frequent landslides. However, the long-term evolution of landslide susceptibility and the temporal behavior of its dominant conditioning factors remain insufficiently understood. This study compiled a 30-year inventory of 1350 landslides from multi-source remote-sensing data and divided it into three periods: P1 (1991–2000), P2 (2001–2010), and P3 (2011–2020). Period-specific random forest models were developed for susceptibility mapping, and Tree-SHAP was used to interpret temporal changes in dominant factors and their nonlinear responses. The models showed reliable performance, with AUC values of 0.887, 0.848, and 0.900, respectively. Susceptibility patterns showed broad temporal stability with localized reorganization, with unchanged areas accounting for 55.62%, 51.62%, and 58.51% of the P1–P2, P2–P3, and P1–P3 transitions, respectively. High and very high susceptibility zones were persistently concentrated along the Yarlung Tsangpo–Parlung Tsangpo–Yigong Tsangpo river system and major tributary junctions. SHAP results identified elevation, slope gradient, terrain curvature, NDVI, and annual precipitation as the persistent core factor group, whereas drainage proximity, the seismic disturbance proxy, and road proximity showed stronger period-dependent effects. Nonlinear SHAP responses revealed threshold-saturation, overall decreasing or distance-decay, threshold-transition, and inverted U-shaped patterns. These findings indicate that susceptibility evolution reflects the coupling between persistent geomorphic predisposition and stage-dependent environmental and disturbance-related modifiers, providing a basis for identifying persistent and stage-specific high-susceptibility zones in high-relief valley regions. Full article

This study investigates the role of governance quality, human development, macroeconomic conditions, and energy structure in shaping CO₂ emissions and carbon intensity across countries. Despite extensive research, existing studies often analyze these factors in isolation and rely on linear models that fail to capture nonlinear relationships. To address this gap, this study applies a machine learning approach using a coarse decision tree model on an unbalanced panel dataset covering 195 countries from 1996 onward. The results reveal that governance quality is the most significant predictor of CO₂ emissions, followed by energy structure, human development, and macroeconomic factors. The findings highlight strong nonlinear and threshold effects, suggesting that improvements in institutional quality and energy systems significantly reduce emissions beyond critical levels. This study contributes by providing a unified, data-driven framework for cross-country environmental analysis and offers policy-relevant insights for achieving sustainable development. Full article

‘Fengtang’ plum is increasingly cultivated in southern China under mountain cultivation conditions, which involve lower temperatures, higher irradiance, and thinner soils. These conditions may uniquely shape the rhizosphere microbiome and influence tree health, yet their effects remain poorly understood. This study aimed to characterize the structural and taxonomic characteristics of the rhizosphere microbial community of ‘Fengtang’ plum grown under mountain cultivation conditions, and to identify key microbial groups associated with plant growth. We performed 16S rRNA and ITS high-throughput sequencing on rhizosphere and non-rhizosphere soil samples from ‘Fengtang’ plum orchards. Significant differences in α-diversity and β-diversity were observed between rhizosphere and non-rhizosphere communities. Dominant bacterial phyla included Pseudomonadota, Actinobacteriota, Acidobacteriota, and Chloroflexi; Ascomycota and Basidiomycota dominated in fungal communities. Dominant microbial groups were consistent across phylum, class, and order levels. Beneficial genera such as Streptomyces, Bacillus, and Rhizobium were enriched in the rhizosphere, and are considered putative core functional genera based on their known plant-growth-promoting traits. The microbial community in the rhizosphere shows distinct compositional patterns that may be linked to microecological balance. This study seeks to provide a comprehensive perspective for understanding the microbial communities associated with the plum tree rhizosphere. Full article