Search Results (3,816)

Mosquitoes (Diptera: Culicidae) exhibit vertical stratification patterns in forest environments, a fundamental ecological aspect for understanding niche occupation patterns, host-seeking behavior, and consequently arbovirus transmission mechanisms. Despite the relevance of this topic, available studies mostly focus on genera such as Aedes, Haemagogus, and Sabethes which are traditionally associated with arbovirus transmission. There are still important gaps regarding stratification and seasonality in the Mansoniini tribe, whose biology and epidemiological role remain underexplored, especially in highly biodiverse ecosystems such as the Atlantic Forest. This study evaluated the influence of seasonality and vertical stratification on the mosquito community, with a detailed focus on the Mansoniini tribe, in an Atlantic Forest fragment in Brazil, between May 2023 and December 2024. Captures were performed monthly using CDC light traps positioned at 1.5 m and 10 m heights, and specimens were morphologically identified. A total of 880 mosquitoes from nine genera and 24 species were captured, of which 91 (10.3%) belonged to the Mansoniini tribe. The most abundant species were Coquillettidia fasciolata and Mansonia titillans, recorded in both strata. Our results indicate no marked vertical segregation for the studied mosquito community in this specific location, but a strong influence of seasonality, particularly for the Mansoniini tribe, reinforcing the role of meteorological data on the population structure of these species. These site-specific findings offer a foundational ecological portrait and a robust methodological template for a neglected taxon. They generate critical, testable hypotheses about niche partitioning in fragmented forests and underscore the necessity for broader spatial replication to disentangle the relative influence of seasonal versus vertical drivers in similar ecosystems. Full article

Bark beetle infestations and other natural disturbances have increasingly affected Norway spruce (Picea abies (L.) Karst.) forests across Europe resulting in devaluation and decreased applicability of woody biomass of such trees. The aim of this research was to investigate the extractive content of bark beetle-attacked and dead wind-damaged Norway spruce trees relative to healthy trees, in order to assess their potential for extractives recovery. After harvesting, three discs were dissected along the stem height of each tree, and samples of sapwood, heartwood, knots, and bark were collected. Sequential extraction of the samples was performed using cyclohexane and acetone–water mixture in an accelerated solvent extractor. Lipophilic and hydrophilic extractives were determined gravimetrically, while total phenols and proanthocyanidins were measured by UV–Vis spectrophotometry. Results showed that knotwood contained the highest amounts of hydrophilic extractives and total phenols among investigated tissues. Knots of healthy trees contained the highest amount of hydrophilic extractives (52.4% w w⁻¹), while knots of dead wind-damaged trees contained significantly higher content of total phenols (8.8% w w⁻¹). The total phenols in bark beetle-attacked and healthy trees were 7.1% w w⁻¹ and 7.2% w w⁻¹, respectively. The sapwood and heartwood of dead wind-damaged trees had higher content of hydrophilic extractives (3.4% and 2.3% w w⁻¹) than healthy and bark beetle-attacked trees. Bark from healthy trees contained more total phenols (2.7% w w⁻¹) than bark of bark beetle-attacked trees, while proanthocyanidin contents in bark were comparable among three groups of trees. Our findings revealed that woody biomass from bark beetle-attacked and dead wind-damaged Norway spruce trees contains significant levels of phenolics, indicating high potential for extracting valuable compounds in biorefineries. Full article

To meet the development needs of high-rise timber structures, current cross-laminated timber (CLT) shear walls typically feature a single-layer thickness of 35 mm with more than three laminations in the stack. However, such thickness easily leads to resource waste in small-scale residential buildings, while increasing transportation and hoisting costs, which is not conducive to the prefabrication and lightweight development of timber structures. To adapt to the development trend of China’s timber structure market towards public buildings such as cultural and tourism projects and small-scale residential buildings including new rural housing renovation, this study focuses on thin CLT shear walls with an overall thickness of 48 mm (16 mm per layer) and conducts research on their lateral load-bearing performance. Monotonic lateral static load tests and finite element (FE) simulations were carried out on thin CLT shear walls without openings, with different opening areas, and with the same opening area but different positions. A corresponding FE model was established and validated, with a focus on analyzing the influence of opening parameters on the shear performance of the walls. The research results show that wall openings significantly reduce the bearing capacity and shear stiffness of the walls: compared with the wall without openings, the ultimate load and shear stiffness of the walls with openings decrease by 20.4–28.6% and 36.3–42.3%, respectively. Among them, increasing the opening height has a more obvious weakening effect on the bearing capacity; for the same opening area, a wider opening results in a more significant decrease in stiffness. The FE model exhibits reliable accuracy, with the error between the experimental and simulation results in the elastic stage controlled within 10%, and the influence of the under-wall support on the shear stiffness is relatively small. Opening parameters have a prominent impact on the stiffness of the wall in the elastic stage, and the influence of the opening position is more critical—the smaller the distance from the opening to the top of the wall, the more obvious the decrease in overall stiffness. Full article

Based on field inventory data collected from 117 temporary plots in Sichuan Province, 19 bamboo culm height–diameter at breast height (DBH) base models for Cizhu (Bambusa emeiensis) were constructed and assessed to evaluate the effectiveness and applicability of multiple model structures and re-parameterization strategy for model performance improvement. Under a unified evaluation framework (taking the R², RMSE, and AIC as criteria), the impact of model structure on fitting and predictive performance was analyzed. Based on partial correlation analysis and field operability, the branch-free culm node number was selected as an explanatory variable and used to re-parameterize each base model at each parameter position. The performance improvement achieved through re-parameterization for different model structures was systematically assessed. The results showed that at the base model level, the overall performances of most models were roughly similar, with the growth model performing relatively better according to comprehensive evaluation indicators (R²: 0.5764, RMSE: 2.376 m, AIC: 1109.19). As for re-parameterized models, they generally exhibited varying degrees of performance improvement compared to their corresponding base models, among which the growth model re-parameterized at the position of parameter b showed the best performance according to comprehensive evaluation indicators (R²: 0.6445, RMSE: 2.195 m, AIC: 1071.87). Re-parameterization based on growth structure variables can substantially enhance the fitting and prediction performance of bamboo height–DBH models for B. emeiensis. It is concise and easy to implement, which may provide reference for bamboo height–DBH modeling and other related research on B. emeiensis. Full article

With the increase in mining intensity and scale, the damage to groundwater resources and surface ecology caused by coal mining has become the main problem facing coal development. Coal mining can cause a redistribution of stress field and stress concentration in local areas of overlying rock, resulting in varying degrees of movement and damage to the overlying rock. Quantitative analysis of the degree of migration and damage in different areas of overlying rock and zoning control is crucial for achieving loss reduction and green mining. In this paper, the overburden damage is divided into regions according to the different causes of formation, regional characteristics of severity, and other factors, and the specific calculation method is given. UDEC7.0 numerical simulation software is used to simulate the overlying rock damage, and the best mining parameters are provided through the area changes in different zones. The research conclusions are as follows: according to the different damage states of overburden rock, the damage of overburden rock can be divided into four parts: I, caving fracture zone, II, fracture development zone, III, sliding failure zone, and IV, slight failure zone. In the four zones, the damage in zones II and IV is relatively light. During the mining process, attention should be given to controlling the development of Zone I to prevent it from abnormally enlarging; for Zone II, hydraulic fracturing can be used when there is a thick, hard key layer that poses a water inrush risk; for Zone III, the focus should be on preventing surface step fractures caused by it. For example, when a thick, hard key layer is present in Zone II, hydraulic fracturing can be applied to avoid large area hanging roofs and severe rock pressure. When the mining height is low, it mainly affects the proportion of regions I and III. With the increase in mining height, the main affected region becomes the II region. The larger the mining height is, the larger the proportion of the II region. With the increase in propulsion speed, the impact range on the surface increases, but the area with severe damage is relatively reduced. With the increase in mining width, the proportion of relatively seriously damaged areas increased. On-site measurements have shown that when the speeds of 120,401 and 22,207 working faces are slow, the rock layer pressure shows a dense state, the overburden fracture is more fully developed, and the area proportion of I and II zones is increased, which reflects the phenomenon of dense surface fracture development on the surface. When the advancing speed is large, the area proportions of zones III and IV increase, and the damage scope decreases. The on-site testing verified the conclusions drawn from theoretical analysis and numerical simulation, which can guide other mines under similar conditions to achieve safe and green production. Full article

Climate change is increasingly exposing sweet chestnut (Castanea sativa Mill.) to more frequent and prolonged drought events, which can compromise growth and nut production, particularly in Mediterranean environments. Understanding how trees respond physiologically to ecological and environmental constraints requires a detailed analysis of their architectures. The aim of this study was to investigate how the shoot vigour and leaf water status of mature chestnut trees vary with height within the canopy. Three mature chestnut trees with distinct crown architectures were selected in a traditional chestnut orchard in Central Italy; the differences in crown structure reflected individual tree development under comparable pruning practices. Morphological traits, leaf water status, and physiological parameters related to chlorophyll were measured directly within the canopy by professional tree climbers, allowing access to both lower and upper shoots during the growing season of 2020. One tree, called “Tree 1,” characterised by low bifurcation, with all epicormic shoot cluster (complexes) located on the two main branches and none on the main stem, showed partial vertical differences, mainly in water status and chlorophyll traits. “Tree 2”, characterised by high bifurcation and shoots running along the main stem, exhibited clear vertical gradients: lower-canopy shoots had larger leaf areas and more dry mass, higher relative water content, and better photosynthetic performance index e values than upper shoots. At the end, “Tree 3”, with the same architecture as Tree 1, displayed no consistent vertical trends. These findings indicate that individual tree architecture modulates hydraulic constraints and shoot vigour, even in hydraulically efficient epicormic branches. Although canopy access constraints limited the number of trees and measurements, this study—among the few to conduct in-canopy measurements on large, mature trees—provides valuable guidance for pruning and crown management, suggesting that lowering and simplifying the crown can enhance water-use efficiency, shoot vigour, and drought resilience in traditional and low-input chestnut orchards. Full article

Seismic vulnerability assessment of reinforced concrete (RC) structures is crucial in earthquake-prone regions to mitigate risks to life and property. This study proposes a systematic three-phase framework for enhanced seismic risk assessment: (1) Automation, (2) Evaluation, and (3) Predictive Modeling. For the Automation Phase, a web-based tool was developed to digitize and streamline the Turkish Rapid Visual Screening (RVS) procedure, eliminating manual calculation errors while improving efficiency. During the Evaluation Phase, we applied this tool to assess 600 buildings, classifying them into four distinct risk categories (no, low, moderate, and high risk) through standardized scoring. Finally, in the Predictive Modeling Phase we conducted correlation analysis to identify key seismic risk factors (e.g., building height showing a strong negative correlation, while soft-story mechanisms and short columns emerged as critical vulnerabilities) and implemented three machine learning models (XGBoost, Random Forest, and AdaBoost) for risk prediction, with XGBoost achieving superior accuracy. The framework’s validation confirmed the web tool’s reliability relative to conventional methods while revealing most buildings as low-risk, demonstrating how this integrated approach—combining automated screening, large-scale assessment, and data-driven prediction—provides a scalable solution for seismic risk mitigation in vulnerable regions. Full article

Impulsive overtopping generated by dam-break surges is a critical hazard for dikes and flood-protection embankments, especially in reservoirs and mountainous catchments. Unlike classical coastal wave overtopping, which is governed by long, irregular wave trains and usually characterized by mean overtopping discharge over many waves, these dam-break-type events are dominated by one or a few strongly nonlinear bores with highly transient overtopping heights. Accurately predicting the resulting overtopping levels under such impulsive flows is therefore important for flood-risk assessment and emergency planning. Conventional cluster-then-predict approaches, which have been proposed in recent years, often first partition data into subgroups and then train separate models for each cluster. However, these methods often suffer from rigid boundaries and ignore the uncertainty information contained in clustering results. To overcome these limitations, we propose a GMM+MoE framework that integrates Gaussian Mixture Model (GMM) soft clustering with a Mixture-of-Experts (MoE) predictor. GMM provides posterior probabilities of regime membership, which are used by the MoE gating mechanism to adaptively assign expert models. Using SPH-simulated overtopping data with physically interpretable dimensionless parameters, the framework is benchmarked against XGBoost, GMM+XGBoost, MoE, and Random Forest. Results show that GMM+MoE achieves the highest accuracy ($R^2=0.9638$ on the testing dataset) and the most centralized residual distribution, confirming its robustness. Furthermore, SHAP-based feature attribution reveals that relative propagation distance and wave height are the dominant drivers of overtopping, providing physically consistent explanations. This demonstrates that combining soft clustering with adaptive expert allocation not only improves accuracy but also enhances interpretability, offering a practical tool for dike safety assessment and flood-risk management in reservoirs and mountain river valleys. Full article

Accurate quantification of field-grown rice seedlings is essential for evaluating yield potential and guiding precision field management. Unmanned aerial vehicle (UAV)-based remote sensing, with its high spatial resolution and broad coverage, provides a robust basis for accurate seedling detection and population density estimation. However, in previous studies, UAVs were typically employed at relatively low altitudes, which provided high-resolution imagery and facilitated seedling recognition but limited efficiency. To enable large-area monitoring, higher flight altitudes are required, which reduces image resolution and adversely affects rice seedling recognition accuracy. In this study, UAVs were flown at a height of 30 m, and the resulting lower-resolution imagery, combined with the small size of seedlings, their dense spatial distribution, and the complex field background, necessitated algorithmic improvements for accurate detection. To address these challenges, we propose an enhanced You Only Look Once version 8 nano (YOLOv8n)-based detection model specifically designed to improve seedling recognition under high-altitude UAV imagery. The model incorporates an improved Bidirectional Feature Pyramid Network (BiFPN) for multi-scale feature fusion and small-object detection, a Global-to-Local Spatial Aggregation (GLSA) module for enriched spatial context modeling, and a Content-Guided Attention Fusion (CGAFusion) module to enhance discriminative feature learning. Experiments on high-altitude UAV imagery demonstrate that the proposed model achieves an mAP@0.5 of 94.7%, a precision of 91.0%, and a recall of 91.2%, representing a 2.3% improvement over the original YOLOv8n. These results highlight the model’s innovation in handling high-altitude UAV imagery for large-area rice seedling detection, demonstrating its effectiveness and practical potential under complex field conditions. Full article

This study investigates whether fecal microbiota transplantation (FMT) can alleviate gut microbiota dysbiosis induced by a high-fat diet (HFD) through modulation of fatty acid metabolism, competition for nutrients, production of short-chain fatty acids (SCFAs), and restoration of mucus layer integrity. To elucidate the mechanisms by which FMT regulates colonic microbial function and host metabolic responses, 80 male Bal b/c mice were randomly assigned to four experimental groups (n = 20 per group): Normal Diet Group (NDG), High-Fat Diet Group (HDG), Restrictive Diet Group (RDG), and HDG recipients of NDG-derived fecal microbiota (FMT group). The intervention lasted for 12 weeks, during which body weight was monitored biweekly. At the end of the experiment, tissue and fecal samples were collected to assess digestive enzyme activities, intestinal histomorphology, gene expression related to gut barrier function, and gut microbiota composition via 16S rRNA gene sequencing. Results showed that mice in the HDG exhibited significantly higher final body weight and greater weight gain compared to those in the NDG and RDG (p < 0.05). Notably, FMT treatment markedly attenuated HFD-induced weight gain (p < 0.05), reducing it to levels comparable with the NDG (p > 0.05). While HFD significantly elevated the activities of α-amylase and trypsin (p < 0.05), FMT supplementation effectively suppressed these enzymatic activities (p < 0.05). Moreover, FMT ameliorated HFD-induced intestinal architectural damage, as evidenced by significant increases in villus height and the villus height-to-crypt depth ratio (V/C) (p < 0.05). At the molecular level, FMT significantly downregulated the expression of pro-inflammatory cytokines (IL-1β, IL-1α, TNF-α) and upregulated key tight junction proteins (Occludin, Claudin-1, ZO-1) and mucin-2 (MUC2) relative to the HDG (p < 0.05). 16S rRNA analysis demonstrated that FMT substantially increased the abundance of beneficial genera such as Lactobacillus and Bifidobacterium while reducing opportunistic pathogens including Romboutsia (p < 0.05). Furthermore, alpha diversity indices (Chao1 and ACE) were significantly higher in the FMT group than in all other groups (p < 0.05), indicating enhanced microbial richness and community stability. Functional prediction using PICRUSt2 revealed that FMT-enriched metabolic pathways (particularly those associated with SCFA production) and enhanced gut barrier-related functions. Collectively, this study deepens our understanding of host–microbe interactions under HFD-induced metabolic stress and provides mechanistic insights into how FMT restores gut homeostasis, highlighting its potential as a therapeutic strategy for diet-induced dysbiosis and associated metabolic disorders. Full article

It has become common to apply multiple drones to conduct plant-protection in large-scale farms, where dual-UAV synchronisation is representative. However, current studies are mainly dedicated to the spray quality of a single UAV, and it remains unclear whether synchronous operation affects spray effectiveness. This paper focuses on the spray efficacy and coupling effects of dual-UAV collaboration. Five-factor orthogonal four-level tests were conducted using the developed UAV collaboration system, and the results were compared with those of asynchronous and ideal linear superposition. It is indicated that (1) spray uniformity was impacted by the relative height between the UAVs and the flight speed of the UAVs (all the p-values < 0.02), whilst the deposition amount was affected by the relative horizontal spacing between the UAVs and the height of the left UAV relative to the forward flight direction (all the p-values < 0.04); (2) the proportion of high-quality spray in the coupling areas had a negative relation with the relative horizontal distance of the two UAVs, and the threshold of the effective coupling distance was 5 m; and (3) synchronous coupling should be avoided. If it is not, the left-side UAV (referring to the forward direction of flight) should be at a higher altitude (5 m or 6.5 m), be 0.5 m higher than the right and fly with a low or medium flight speed (3.5 m/s–4.5 m/s). The research can give a reference to the real spray operation by multiple UAVs. Full article

Soil salinization remains a critical constraint on global land sustainability, severely limiting agricultural output and ecosystem resilience. To address this issue, a field trial was implemented to investigate the interactive benefits of vermicompost (VC) and a novel soil conditioner derived from coal gasification slag-based soil conditioner (CGSS) in mitigating saline–alkali stress. The perennial forage grass Leymus chinensis, valued for its ecological robustness and economic potential under adverse soil conditions, served as the test species. Five treatments were established: CK (unamended), T1 (CGSS alone), T2 (VC alone), T3 (CGSS:VC = 1:1), T4 (CGSS:VC = 1:2), and T5 (CGSS:VC = 2:1). Study results indicate that the combined application of CGSS and VC outperformed individual amendments, with the T4 treatment demonstrating the most effective results. Compared to CK, T4 reduced soil electrical conductivity (EC) by 12.00% and pH by 5.17% (p < 0.05), while markedly enhancing key fertility indicators—including soil organic matter and the availability of nitrogen, phosphorus, and potassium. Thus, these improvements translated into superior growth of L. chinensis, reflected in significantly greater dry biomass, expanded leaf area, and increased plant height. Additionally, the T4 treatment increased soil microbial richness (Chao1 index) by 21.5% and elevated the relative abundance of the Acidobacteria functional group by 16.9% (p < 0.05). Hence, T4 treatment (CGSS: 15,000 kg·ha⁻¹; VC: 30,000 kg·ha⁻¹) was identified as the optimal remediation strategy through a fuzzy comprehensive evaluation that integrated multiple soil and plant indicators. From an economic perspective, the T4 treatment (corresponding to a VC-CGSS application ratio of 2: 1) exhibits a lower cost compared to other similar soil conditioners and organic fertilizer combinations for saline–alkali soil remediation. This study not only offers a practical and economically viable approach for reclaiming degraded saline–alkali soils but also advances the circular utilization of coal-based solid waste. Furthermore, it deepens our understanding of how integrated soil amendments modulate the soil–microbe–plant nexus under abiotic stress. Full article

In the tropical Andes, rangeland degradation has become one of the main threats to the sustainability of livestock production in the face of climate change. In this context, optimizing the yield and nutritional quality of raw material for silage is essential to sustain livestock productivity. The aim of this study was to identify local accessions (LM) of Lolium multiflorum Lam. with greater forage potential through evaluations in consecutive cuts made at the anthesis phenological stage, using a randomized complete block design with four replicates and ten local accessions (LM1, LM2, LM3, LM4, LM6, LM7, LM8, LM11, LM12 and LM13). The statistical analysis, based on linear mixed models, showed that cuts at anthesis had a significant effect among accessions, revealing high variability in agronomic and nutritional performance across cuts. In LM4, plant height at the fourth cut was 2.48-fold higher than at the first cut. Likewise, LM4 and LM13 were identified as the latest accessions to reach anthesis in the first cut, with a decreasing trend across cuts and stabilization from the third cut onward. These accessions also showed the greatest basal coverage area, increasing 9.94- and 8.18-fold in the fourth cut relative to the first. Fresh forage yields in LM4 and LM13 increased 13.2- and 10.1-fold, and dry matter yields 13.98- and 9.86-fold, compared with the first cut. They also exhibited the highest average daily dry matter ac-cumulation rate. By contrast, the fresh forage and dry matter yields of the remaining accessions were significantly lower than those of LM4 and LM13. The main difference between these two accessions was observed in dry matter percentage, with higher values and a stable trend in LM4 across all cuts. In terms of nutritional quality, LM4 presented crude protein of 24.2% in the second cut and 24.0% in the fourth cut, while digestibility was 86.2% in the second cut and 85.0% in the fourth cut. In conclusion, although the ensiling process was not evaluated in this study, LM4 showed the most stable and outstanding values in both agronomic and nutritional performance, thus emerging as a promising accession for selection and use as raw material for silage production in the tropical Andes. Full article

The increasing share of heavy and high-sulfur crude oils in refinery feed slates worldwide highlights the need for models of delayed coking units (DCUs) that are both physically meaningful and computationally efficient. In this study, we develop and calibrate a simplified yet dynamic one-dimensional model of an industrial coke drum intended for integration into digital twin frameworks. The model includes a three-phase representation of the drum contents, a temperature-dependent global kinetic scheme for vacuum residue cracking, and lumped descriptions of heat transfer and phase holdups. Only three physically interpretable parameters—the kinetic scaling factors for distillate and coke formation and an effective wall temperature—were calibrated using routinely measured plant data, namely the overhead vapor and drum head temperatures and the final coke bed height. The calibrated model reproduces the temporal evolution of the top head and overhead temperatures and the final bed height with mean relative errors of a few percent, while capturing the more complex bottom-head temperature dynamics qualitatively. Scenario simulations illustrate how the coking severity (represented here by the effective wall temperature) affects the coke yield, bed growth, and cycle duration. Overall, the results indicate that low-order dynamic models can provide a practical balance between physical fidelity and computational speed, making them suitable as mechanistic cores for digital twins and optimization tools in delayed coking operations. Full article

Exploring the spatiotemporal evolution of building stock in African countries is of great significance for understanding the urbanization process, regional development disparities, and sustainable development pathways in the Global South. Integrating long-term (1975–2020), 100 m resolution building stock data for Tanzania with multi-source environmental and socioeconomic datasets, this study employed GIS spatial analysis techniques—including optimized hotspot analysis, standard deviational ellipse, and geographical detector—to investigate the spatiotemporal evolution characteristics and influencing factors of building differentiation. The results indicate that over the 45-year period, Tanzania’s building stock underwent rapid expansion, with a 3.83-fold increase in volume and a 4.93-fold increase in area, while the average height decreased continuously by 1.04 m. This growth was predominantly driven by the expansion of residential buildings. The spatial distribution of buildings exhibited a “north-dense, south-sparse” pattern with agglomeration along traffic axes. During 1975–1990, building growth hotspots were concentrated in western and southern regions, shifting to areas surrounding Lake Victoria and central administrative centers during 2005–2020. In contrast, coldspots expanded progressively from northern, northeastern regions and Zanzibar Island to parts of the southern and eastern coasts. The building distribution consistently maintained a northwest–southeast spatial orientation, with increasingly prominent directional characteristics; the centroid of building distribution moved more than 90 km northwestward, and the agglomeration intensity continued to increase. Socioeconomic factors—including population density, road network density, and GDP density—have a significantly stronger influence on building distribution than natural factors. Among natural factors, only river network density exhibits a significant effect, while constraints such as slope and terrain relief are relatively insignificant. Full article