Search Results (179)

Habitat fragmentation restricts the movement of large mammals across broad landscapes, leading to isolation of individuals or groups, reduced interaction with other species, and limited access to vital resources in surrounding habitats. In this study, we aimed to determine the wildlife ecological corridors for five large mammals (Ursus arctos, Cervus elaphus, Capreolus capreolus, Sus scrofa, and Canis lupus) between Kastamonu Ilgaz Mountain Wildlife Refuge and Gavurdağı Wildlife Refuge. In the field studies, we used the transect, indirect observation, and camera-trap methods to collect presence data. Maximum Entropy (MaxEnt) (v. 3.4.1) software was used to create habitat suitability models of the target species, which are based on the presence-only data approach. The results indicated that AUC values varied between 0.808 and 0.835, with water sources, stand type, and slope contributing most significantly to model performance. In order to determine wildlife ecological corridors, resistance surface maps were created using the species distribution models (SDMs), and bottleneck areas were determined. The Circuit Theory approach was used to model the connections between ecological corridors. As a result of this study, we developed connectivity models for five large mammals based on Circuit Theory, identified priority wildlife ecological corridors, and evaluated critical connection points between two protected areas, Ilgaz Mountain Wildlife Refuge and Gavurdağı Wildlife Refuge. These findings highlight the essential role of ecological corridors in sustaining landscape-level connectivity and supporting the long-term conservation of wide-ranging species. Full article

Ecological security patterns (ESPs) are fundamental to safeguarding regional ecological integrity and enhancing human well-being. Consequently, research on conservation and restoration in critical regions is vital for ensuring ecological security and optimizing territorial ecological spatial configurations. Focusing on the Henan section of the Yellow River Basin, this study established the regional ESP and conservation–restoration framework through an integrated approach: (1) assessing four key ecosystem services—soil conservation, water retention, carbon sequestration, and habitat quality; (2) identifying ecological sources based on ecosystem service importance classification; (3) calculating a comprehensive resistance surface using the entropy weight method, incorporating key factors (land cover type, NDVI, topographic relief, and slope); (4) delineating ecological corridors and nodes using Linkage Mapper and the minimum cumulative resistance (MCR) theory; and (5) integrating ecological functional zoning to synthesize the final spatial conservation and restoration strategy. Key findings reveal: (1) 20 ecological sources, totaling 8947 km² (20.9% of the study area), and 43 ecological corridors, spanning 778.24 km, were delineated within the basin. Nineteen ecological barriers (predominantly located in farmland, bare land, construction land, and low-coverage grassland) and twenty-one ecological pinch points (primarily clustered in forestland, grassland, water bodies, and wetlands) were identified. Collectively, these elements form the Henan section’s Ecological Security Pattern (ESP), integrating source areas, a corridor network, and key regional nodes for ecological conservation and restoration. (2) Building upon the ESP and the ecological baseline, and informed by ecological functional zoning, we identified a spatial framework for conservation and restoration characterized by “one axis, two cores, and multiple zones”. Tailored conservation and restoration strategies were subsequently proposed. This study provides critical data support for reconciling ecological security and economic development in the Henan Yellow River Basin, offering a scientific foundation and practical guidance for regional territorial spatial ecological restoration planning and implementation. Full article

(1) Background: Human walking involves adapting to diverse terrains, influencing gait biomechanics. This study examined how seven outdoor surfaces—flat–even, banked-right/-left, cobblestone, grass, sloped-down, and sloped-up—affect nonlinear gait dynamics in 30 healthy adults (14 females and 15 males). (2) Methods: Trunk and shank accelerations were analyzed for movement predictability (sample entropy, SE), smoothness (log dimensionless jerk, LDLJ), symmetry (step/stride regularity), and stability (short-/long-term Lyapunov exponents, LyE_s, LyE_l). (3) Results: Surface type significantly influenced all gait metrics, regardless of sex. Banked-right and sloped-down walking reduced SE, indicating less predictable movements. All surfaces except flat–even increased LDLJ, suggesting reduced smoothness. Cobblestone and sloped-down surfaces impaired step symmetry, while banked surfaces enhanced stride symmetry. LyE_s decreased on cobblestones (lower variability), while sloped-up increased it. LyE_l rose on all surfaces except cobblestones, indicating a more chaotic gait. No significant sex differences were found, though males showed a non-significant trend toward lower LyE_s. Notably, sex–surface interactions emerged for SE and stride symmetry on banked-right surfaces, with females showing decreased SE and increased symmetry. (4) Conclusions: These findings underscore the importance of terrain and sex in gait dynamics research. Full article

The evolutionary patterns and influencing factors of the coupling coordination among multiple functions of cultivated land serve as an important basis for emphasizing the value of cultivated land utilization and promoting coordinated regional development. The entropy weight TOPSIS model, coupling coordination degree (CCD) model, spatial autocorrelation analysis, and Geodetector were employed in this study along with panel data from 125 cities in the Yangtze River Economic Belt (YREB) for 2010, 2015, 2020, and 2022. Three key aspects in the region were investigated: the spatiotemporal evolution of cultivated land functions, characteristics of coupling coordination, and their underlying influencing factors. The results show the following: (1) The functions of cultivated land for food production, social support, and ecological maintenance are within the ranges of [0.023, 0.460], [0.071, 0.451], and [0.134, 0.836], respectively. The grain production function (GPF) shows a continuous increase, the social carrying function (SCF) first decreases and then increases, and the ecological maintenance function (EMF) first increases and then decreases. Spatially, these functions exhibit non-equilibrium characteristics: the grain production function is higher in the central and eastern regions and lower in the western region; the social support function is higher in the eastern and western regions and lower in the central region; and the ecological maintenance function is higher in the central and eastern regions and lower in the western region. (2) The coupling coordination degree of multiple functions of cultivated land is within the range of [0.158, 0.907], forming a spatial pattern where the eastern region takes the lead, the central region is rising, and the western region is catching up. (3) Moran’s I index increased from 0.376 in 2010 to 0.437 in 2022, indicating that the spatial agglomeration of the cultivated land multifunctionality coupling coordination degree has been continuously strengthening over time. (4) The spatial evolution of the coupling coordination of cultivated land multifunctionality is mainly influenced by the average elevation and average slope. However, the explanatory power of socioeconomic factors is continuously increasing. Interaction detection reveals characteristics of nonlinear enhancement or double-factor enhancement. The research results enrich the study of cultivated land multifunctionality and provide a decision-making basis for implementing the differentiated management of cultivated land resources and promoting mutual enhancement among different functions of cultivated land. Full article

The formation of soil cracks in soil slopes can compromise structural integrity. Guar gum, as a natural high-molecular-weight biopolymer, offers environmental and economic advantages in soil stabilizers due to its biodegradability, strong binding properties, and ability to form a three-dimensional network structure. To investigate its improvement effects, outdoor dry shrinkage cracking tests were conducted on silt loam using different guar gum dosages. Image preprocessing was performed using Photoshop software, and Python algorithms combined with the PCAS system were employed to quantitatively analyze the development process of cracks, revealing the evolution patterns of basic crack parameters, fractal dimensions, and probability entropy. The results indicate the following: (1) the addition of guar gum improves the water retention capacity of the soil, with the average moisture content of the samples decreasing as the guar gum content increases; (2) as the guar gum content increased, the total length, total area, and surface crack ratio of the cracks all increased, but the average crack width decreased significantly, with the maximum decrease reaching 9.8%, indicating that guar gum can effectively suppress the expansion of crack width and slow down the infiltration rate of rainwater; (3) the fractal dimension of crack area is less affected by guar gum content, while the fractal dimension of crack length is significantly influenced by guar gum content. Combining both parameters can effectively characterize crack morphology and distribution. The final fractal dimension of crack length generally ranges from 1.2 to 1.3, while the fractal dimension of the crack area remains stable between 1.55 and 1.65; (4) the addition of guar gum has a minor effect on the probability entropy of cracks, with a change of less than 3%, indicating that it does not significantly influence the randomness of cracks. Therefore, this study confirms that guar gum has a significant effect in controlling crack width and optimizing the uniformity of the crack network. Through its mechanisms of binding soil particles and delaying drying shrinkage, it provides an important reference for the ecological protection of cohesive soil slopes. Full article

The shear strength properties of ionic rare earth ore bodies are directly related to the stability of mine slopes, which provides important theoretical and engineering support for preventing geological disasters and ensuring the safe extraction of resources. This study investigates the effects of different confining pressures, leaching agent types, and MgSO₄ concentrations on the shear strength of ionic rare earth ores through triaxial shear tests. A scanning electron microscopy (SEM) analysis of post-shear mineral samples was conducted to examine the microscopic pore structure, revealing the evolution patterns of the ionic rare earth ore’s microscopic pore structure under various leaching conditions. The results show that the shear strength of the ore body varies significantly under different leaching conditions. After leaching, the shear strength values of the ore body, ranked from highest to lowest, are (NH₄)₂SO₄ > MgSO₄ > Al₂(SO₄)₃ > pure water. The (NH₄)₂SO₄ leaching group exhibited an average shear strength approximately 9.8% higher than the pure water group. When comparing the cohesion and internal friction angle of the pure water leaching group, the (NH₄)₂SO₄-leached ore body showed significantly higher cohesion and a smaller internal friction angle. In contrast, the MgSO₄ and Al₂(SO₄)₃ leaching groups demonstrated lower cohesion and higher internal friction angles. As the MgSO₄ concentration increases, the cohesion of the ore body gradually decreases, the internal friction angle increases, and the shear strength correspondingly increases. Under low-concentration MgSO₄ leaching, the number and area of pores in the ore samples initially increase and then decrease, leading to a more complex pore structure. At higher concentrations of MgSO₄, the variety of pore shapes increases and becomes more complex, pore randomness decreases, the probability entropy value decreases, and the pore distribution becomes more ordered. Full article

This study numerically investigates unsteady natural convection (NC) heat transfer (HT) and entropy generation (E_gen) in trapezoidal cavities filled with two thermally stratified fluids. Both air-filled and water-filled configurations are analyzed to evaluate and compare their thermal performance under varying conditions. The cavities are characterized by a heated base, thermally stratified sloped walls, and a cooled top wall. The governing equations are numerically solved using the finite volume (FV) approach. The study considers a Prandtl number (Pr) of 0.71 for air and 7.01 for water, Rayleigh numbers (Ra) ranging from 10³ to 5 × 10⁷, and an aspect ratio (AR) of 0.5. Flow behavior is examined through various parameters, including temperature time series (TTS), average Nusselt number (Nu), average entropy generation (E_avg), average Bejan number (Be_avg), and ecological coefficient of performance (ECOP). Three bifurcations are identified during the transition from steady to chaotic flow for both fluids. The first is a pitchfork bifurcation, occurring between Ra = 10⁵ and 2 × 10⁵ for air, and between Ra = 9 × 10⁴ and 10⁵ for water. The second, a Hopf bifurcation, is observed between Ra = 4.7 × 10⁵ and 4.8 × 10⁵ for air, and between Ra = 10⁵ and 2 × 10⁵ for water. The third bifurcation marks the onset of chaotic flow, occurring between Ra = 3 × 10⁷ and 4 × 10⁷ for air, and between Ra = 4 × 10⁵ and 5 × 10⁵ for water. At Ra = 10⁶, the average HT in the air-filled cavity is 85.35% higher than in the water-filled cavity, while E_avg is 94.54% greater in the air-filled cavity compared to water-filled cavity. At Ra = 10⁶, the thermal performance of the cavity filled with water is 4.96% better than that of the air-filled cavity. These findings provide valuable insights for optimizing thermal systems using trapezoidal cavities and varying working fluids. Full article

Sustainable cropland management is essential in maintaining national food security. In the black soil regions of China, which are key areas for commercial grain production, sustainable land use must be achieved urgently. To address the absence of integrated, large-scale, remote sensing-based sustainability frameworks in China’s black soil zones, we developed a comprehensive evaluation system with 13 indicators from four dimensions: the soil capacity, the natural capacity, the management level, and crop productivity. With this system and the entropy weight method, we systematically analyzed the spatiotemporal patterns of cropland sustainability in the selected black soil regions from 2010 to 2020. Additionally, a diagnostic model was applied to identify the key limiting factors constraining improvements in cropland sustainability. The results revealed that cropland sustainability in Heilongjiang Province has increased by 7% over the past decade, largely in the central and northeastern regions of the study area, with notable gains in soil capacity (+15.6%), crop productivity (+22.4%), and the management level (+4.8%). While the natural geographical characteristics show no obvious improvement in the overall score, they display significant spatial heterogeneity (with better conditions in the central/eastern regions than in the west). Sustainability increased the most in sloping dry farmland and paddy fields, followed by plain dry farmland and arid windy farmland areas. The soil organic carbon content and effective irrigation amount were the main obstacles affecting improvements in cropland sustainability in black soil regions. Promoting the implementation of technical models, strengthening investment in cropland infrastructure, and enhancing farmer engagement in black soil conservation are essential in ensuring long-term cropland sustainability. These findings provide a solid foundation for sustainable agricultural development, contributing to global food security and aligning with SDG 2 (zero hunger). Full article

This study focuses on the systematic conservation of historical architectural heritage in Heilongjiang Province, particularly addressing the challenges of point-based protection and spatial fragmentation. It explores the construction of a connected and conductive heritage corridor network, using historical building clusters across the province as empirical cases. A comprehensive analytical framework is established by integrating the nearest neighbor index, kernel density estimation, minimum cumulative resistance (MCR) model, entropy weighting, circuit theory, and network structure metrics. Kernel density analysis reveals a distinct spatial aggregation pattern, characterized by “one core, multiple zones.” Seven resistance factors—including elevation, slope, land use, road networks, and service accessibility—are constructed, with weights assigned through an entropy-based method to generate an integrated resistance surface and suitability map. Circuit theory is employed to simulate cultural “current” flows, identifying 401 potential corridors at the provincial, municipal, and district levels. A hierarchical station system is further developed based on current density, forming a coordinated structure of primary trunks, secondary branches, and complementary nodes. The corridor network’s connectivity is evaluated using graph-theoretic indices (α, β, and γ), which indicate high levels of closure, structural complexity, and accessibility. The results yield the following key findings: (1) Historical architectural resources in Heilongjiang demonstrate significant coupling with the Chinese Eastern Railway and multi-ethnic cultural corridors, forming a “one horizontal, three vertical” spatial configuration. The horizontal axis (Qiqihar–Harbin–Mudanjiang) aligns with the core cultural route of the railway, while the three vertical axes (Qiqihar–Heihe, Harbin–Heihe, and Mudanjiang–Luobei) correspond to ethnic cultural pathways. This forms a framework of “railway as backbone, ethnicity as wings.” (2) Comparative analysis of corridor paths, railways, and highways reveals structural mismatches in certain regions, including absent high-speed connections along northern trunk lines, insufficient feeder lines in secondary corridors, sparse terminal links, and missing ecological stations near regional boundaries. To address these gaps, a three-tier transportation coordination strategy is recommended: it comprises provincial corridors linked to high-speed rail, municipal corridors aligned with conventional rail, and district corridors connected via highway systems. Key enhancement zones include Yichun–Heihe, Youyi–Hulin, and Hegang–Wuying, where targeted infrastructure upgrades and integrated station hubs are proposed. Based on these findings, this study proposes a comprehensive governance paradigm for heritage corridors that balances multi-level coordination (provincial–municipal–district) with ecological planning. A closed-loop strategy of “identification–analysis–optimization” is developed, featuring tiered collaboration, cultural–ecological synergy, and multi-agent dynamic evaluation. The framework provides a replicable methodology for integrated protection and spatial sustainability of historical architecture in Heilongjiang and other cold-region contexts. Full article

Amid global rural tourism growth and rural revitalization policies, traditional villages’ resource protection and tourism development have drawn international academic attention. To guide villages’ resource planning and management, this study constructed an evaluation index system of cultural, ecological, industrial, talent, and organizational amenities in traditional villages from the perspective of tourists’ perceptions using grounded theory and measured the spatial agglomeration differences, synergistic effects and their influencing factors of traditional village amenities by using location entropy, spatial autocorrelation, and gray correlation degree analysis. The results show that (1) the spatial distributions of cultural, ecological, industrial, and organizational amenities are more balanced, while talent amenities exhibit a more concentrated distribution. (2) The spatial concentration of amenities in traditional villages has a strong positive spatial correlation, the agglomeration level of the high-high type of concentration is distributed in clusters, the low–low type tends to be contiguous, and the low–high type is distributed sporadically around the high–high type; significant synergy between ecological and industrial amenities, and organizations play a supportive role in the spatial agglomeration of cultural, ecological, ecological and talent amenities. (3) Gross regional product, slope, and distance to 3A and above scenic spots significantly influence the spatial agglomeration of amenities. This study provides reference for the sustainable development of traditional villages from the perspectives of exerting agglomeration and radiation effects, synergistically promoting villages’ development, constructing the memory symbol system, and integrating the resource structural system based on the spatial agglomeration difference characteristics of traditional village amenities. Full article

An estimate of the trigger effect of the proton flux on seismicity was obtained. The proton flux time series with a time step of 5 min, 2000–2024, was analyzed. In each time interval of 5 days, statistics of the proton flux time series were calculated: mean values, logarithm of kurtosis, spectral slope, singularities spectrum support width, wavelet-based entropy, and the Donoho–Johnston wavelet-based index. For each of the used statistics, time points of local extrema were found, and for each pair of time sequences of proton flux statistics and earthquakes with a magnitude of at least 6.5 in sliding time windows, the “advance measures” of each time sequence relative to the other were estimated using a model of the intensity of interacting point processes. The difference between the “direct” measure of the advance of time points of local extrema of proton flux statistics relative to the time moments of earthquakes and the “inverse” measure of the advance was calculated. The maximum proportion of the intensity of seismic events for which the proton flux was a trigger was estimated as 0.28 for using the points of the local minima of the singularities spectrum support width. Full article

The Loess Plateau region of China has an anomalous climate and frequent geological disasters. Hipparion laterite in seasonally frozen regions exhibits heightened susceptibility to freeze–thaw (F-T) cycling, which induces progressive structural weakening and significantly elevates the risk of slope instability through mechanisms including pore water phase transitions, aggregate disintegration, and shear strength degradation. This study focuses on the slip zone Hipparion laterite from the Nao panliang landslide in Fugu County, Shaanxi Province. We innovatively integrated F-T cycling tests with ring-shear experiments to establish a hydro-thermal–mechanical coupled multi-scale evaluation framework for assessing F-T damage in the slip zone material. The microstructural evolution of soil architecture and pore characteristics was systematically analyzed through scanning electron microscopy (SEM) tests. Quantitative characterization of mechanical degradation mechanisms was achieved using advanced microstructural parameters including orientation frequency, probabilistic entropy, and fractal dimensions, revealing the intrinsic relationship between pore network anisotropy and macroscopic strength deterioration. The experimental results demonstrate that Hipparion laterite specimens undergo progressive deterioration with increasing F-T cycles and initial moisture content, predominantly exhibiting brittle deformation patterns. The soil exhibited substantial strength degradation, with total reduction rates of 51.54% and 43.67% for peak and residual strengths, respectively. The shear stress–displacement curves transitioned from strain-softening to strain-hardening behavior, indicating plastic deformation-dominated shear damage. Moisture content critically regulates pore microstructure evolution, reducing micropore proportion to 23.57–28.62% while promoting transformation to mesopores and macropores. At 24% moisture content, the areal porosity, probabilistic entropy, and fractal dimension increased by 0.2263, 0.0401, and 0.0589, respectively. Temperature-induced pore water phase transitions significantly amplified mechanical strength variability through cyclic damage accumulation. These findings advance the theoretical understanding of Hipparion laterite’s engineering geological behavior while providing critical insights for slope stability assessment and landslide risk mitigation strategies in loess plateau regions. Full article

Probability calibration and decision threshold selection are fundamental aspects of risk prediction and classification, respectively. A strictly proper loss function is used in clinical risk prediction applications to encourage a model to predict calibrated class-posterior probabilities or risks. Recent studies have shown that training with focal loss can improve the discriminatory power of gradient-boosted decision trees (GBDT) for classification tasks with an imbalanced or skewed class distribution. However, the focal loss function is not a strictly proper loss function. Therefore, the output of GBDT trained using focal loss is not an accurate estimate of the true class-posterior probability. This study aims to address the issue of poor calibration of GBDT trained using focal loss in the context of clinical risk prediction applications. The methodology utilizes a closed-form transformation of the confidence scores of GBDT trained with focal loss to estimate calibrated risks. The closed-form transformation relates the focal loss minimizer and the true-class posterior probability. Algorithms based on Bayesian hyperparameter optimization are provided to choose the focal loss parameter that optimizes discriminatory power and calibration, as measured by the Brier score metric. We assess how the calibration of the confidence scores affects the selection of a decision threshold to optimize the balanced accuracy, defined as the arithmetic mean of sensitivity and specificity. The effectiveness of the proposed strategy was evaluated using lung transplant data extracted from the Scientific Registry of Transplant Recipients (SRTR) for predicting post-transplant cancer. The proposed strategy was also evaluated using data from the Behavioral Risk Factor Surveillance System (BRFSS) for predicting diabetes status. Probability calibration plots, calibration slope and intercept, and the Brier score show that the approach improves calibration while maintaining the same discriminatory power according to the area under the receiver operating characteristics curve (AUROC) and the H-measure. The calibrated focal-aware XGBoost achieved an AUROC, Brier score, and calibration slope of 0.700, 0.128, and 0.968 for predicting the 10-year cancer risk, respectively. The miscalibrated focal-aware XGBoost achieved equal AUROC but a worse Brier score and calibration slope (0.140 and 1.579). The proposed method compared favorably to the standard XGBoost trained using cross-entropy loss (AUROC of 0.755 versus 0.736 in predicting the 1-year risk of cancer). Comparable performance was observed with other risk prediction models in the diabetes prediction task. Full article

This study aims to investigate the Co content on a Co_xCrFeNiMo (x = 0; 0.5) high entropy alloy (HEA) but also the effects of replacing the Co element with Al in terms of single-phase structure forming, processing behavior, and microstructural characteristics when being processed by mechanical alloying with a planetary ball mill. Recent HEA-related research aimed toward identifying the effect that certain alloying elements in different concentrations influence the microstructure and properties but also regulate their composition. HEAs present promising properties (e.g., corrosion and wear resistance) being applicable in domains that require protection against harsh environmental conditions, benefiting from the specific core effects of this type of material. To obtain a high alloying and homogenization degree, for this research, mechanical alloying was selected for processing the mixtures, with the aid of N-Heptane as a process control agent (PCA). The mixtures were monitored in terms of alloying degree evolution, elemental distribution, particle morphology, crystalline structure, and also technological characterization (packing ratio, free flow, and slope angle). The results indicated that a high degree of alloying was obtained after 30 h of solid-state processing, with notable crystallization of two major phases FCC and BCC identified confirming the HEA phase stability calculations. Full article

Precision rolling bearings serve as critical components in a range of diverse industrial applications, where their continuous health monitoring is essential for preventing costly downtime and catastrophic failures. Early-stage bearing defects present significant diagnostic challenges, as they manifest as weak, nonlinear, and non-stationary transient features embedded within high-amplitude random noise. While entropy-based methods have evolved substantially since Shannon’s pioneering work—from approximate entropy to multiscale variants—existing approaches continue to face limitations in their computational efficiency and information preservation. This paper introduces the Adaptive Composite Multiscale Slope Entropy (ACMSlE) framework, which overcomes these constraints through two innovative mechanisms: a time-window shifting strategy, generating overlapping coarse-grained sequences that preserve critical signal information traditionally lost in non-overlapping segmentation, and an adaptive scale optimization algorithm that dynamically selects discriminative scales through entropy variation coefficients. In a comparative analysis against recent innovations, our integrated fault diagnosis framework—combining Fast Ensemble Empirical Mode Decomposition (FEEMD) preprocessing with Particle Swarm Optimization-Extreme Learning Machine (PSO-ELM) classification—achieves 98.7% diagnostic accuracy across multiple bearing defect types and operating conditions. Comprehensive validation through a multidimensional stability analysis, complexity discrimination testing, and data sensitivity analysis confirms this framework’s robust fault separation capability. Full article