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12 pages, 736 KiB  
Article
Hybrid Framework of Fermi–Dirac Spin Hydrodynamics
by Zbigniew Drogosz
Physics 2025, 7(3), 31; https://doi.org/10.3390/physics7030031 - 1 Aug 2025
Viewed by 82
Abstract
The paper outlines the hybrid framework of spin hydrodynamics, combining classical kinetic theory with the Israel–Stewart method of introducing dissipation. The local equilibrium expressions for the baryon current, the energy–momentum tensor, and the spin tensor of particles with spin 1/2 following the Fermi–Dirac [...] Read more.
The paper outlines the hybrid framework of spin hydrodynamics, combining classical kinetic theory with the Israel–Stewart method of introducing dissipation. The local equilibrium expressions for the baryon current, the energy–momentum tensor, and the spin tensor of particles with spin 1/2 following the Fermi–Dirac statistics are obtained and compared with the earlier derived versions where the Boltzmann approximation was used. The expressions in the two cases are found to have the same form, but the coefficients are shown to be governed by different functions. The relative differences between the tensor coefficients in the Fermi–Dirac and Boltzmann cases are found to grow exponentially with the baryon chemical potential. In the proposed formalism, nonequilibrium processes are studied including mathematically possible dissipative corrections. Standard conservation laws are applied, and the condition of positive entropy production is shown to allow for the transfer between the spin and orbital parts of angular momentum. Full article
(This article belongs to the Special Issue High Energy Heavy Ion Physics—Zimányi School 2024)
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16 pages, 2713 KiB  
Article
Change in C, N, and P Characteristics of Hypericum kouytchense Organs in Response to Altitude Gradients in Karst Regions of SW China
by Yage Li, Chunyan Zhao, Jiajun Wu, Suyan Ba, Shuo Liu and Panfeng Dai
Plants 2025, 14(15), 2307; https://doi.org/10.3390/plants14152307 - 26 Jul 2025
Viewed by 165
Abstract
The environmental heterogeneity caused by altitude can lead to trade-offs in nutrient utilization and allocation strategies among plant organs; however, there is still a lack of research on the nutrient variation in the “flower–leaf–branch–fine root–soil” systems of native shrubs along altitude gradients in [...] Read more.
The environmental heterogeneity caused by altitude can lead to trade-offs in nutrient utilization and allocation strategies among plant organs; however, there is still a lack of research on the nutrient variation in the “flower–leaf–branch–fine root–soil” systems of native shrubs along altitude gradients in China’s unique karst regions. Therefore, we analyzed the carbon (C), nitrogen (N), and phosphorus (P) contents and their ratios in flowers, leaves, branches, fine roots, and surface soil of Hypericum kouytchense shrubs across 2200–2700 m altitudinal range in southwestern China’s karst areas, where this species is widely distributed and grows well. The results show that H. kouytchense organs had higher N content than both global and Chinese plant averages. The order of C:N:P value across plant organs was branches > fine roots > flowers > leaves. Altitude significantly affected the nutrient dynamics in plant organs and soil. With increasing altitude, P content in plant organs exhibited a significant concave pattern, leading to unimodal trends in the C:P of plant organs, as well as the N:P of leaves and fine roots. Meanwhile, plant organs except branches displayed significant homeostasis coefficients in C:P and fine root P, indicating a shift in H. kouytchense’s P utilization strategy from acquisitive-type to conservative-type. Strong positive relationships between plant organs and soil P and available P revealed that P was the key driver of nutrient cycling in H. kouytchense shrubs, enhancing plant organ–soil coupling relationships. In conclusion, H. kouytchense demonstrates flexible adaptability, suggesting that future vegetation restoration and conservation management projects in karst ecosystems should consider the nutrient adaptation strategies of different species, paying particular attention to P utilization. Full article
(This article belongs to the Special Issue Plant Functional Diversity and Nutrient Cycling in Forest Ecosystems)
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13 pages, 704 KiB  
Article
Population Substructures of Castanopsis tribuloides in Northern Thailand Revealed Using Autosomal STR Variations
by Patcharawadee Thongkumkoon, Jatupol Kampuansai, Maneesawan Dansawan, Pimonrat Tiansawat, Nuttapol Noirungsee, Kittiyut Punchay, Nuttaluck Khamyong and Prasit Wangpakapattanawong
Plants 2025, 14(15), 2306; https://doi.org/10.3390/plants14152306 - 26 Jul 2025
Viewed by 227
Abstract
This study investigates the genetic diversity and population structure of Castanopsis tribuloides, a vital tree species in Asian forest ecosystems. Understanding the genetic patterns of keystone forest species provides critical insights into forest resilience and ecosystem function and informs conservation strategies. We [...] Read more.
This study investigates the genetic diversity and population structure of Castanopsis tribuloides, a vital tree species in Asian forest ecosystems. Understanding the genetic patterns of keystone forest species provides critical insights into forest resilience and ecosystem function and informs conservation strategies. We analyzed population samples collected from three distinct locations within Doi Suthep Mountain in northern Thailand using Short Tandem Repeat (STR) markers to assess both intra- and inter-population genetic relationships. DNA was extracted from leaf samples and analyzed using a panel of polymorphic microsatellite loci specifically optimized for Castanopsis species. Statistical analyses included the assessment of forensic parameters (number of alleles, observed and expected heterozygosity, gene diversity, polymorphic information content), population differentiation metrics (GST), inbreeding coefficients (FIS), and gene flow estimates (Nm). We further examined population history through bottleneck analysis using three models (IAM, SMM, and TPM) and visualized genetic relationships through principal coordinate analysis and cluster analysis. Our results revealed significant patterns of genetic structuring across the sampled populations, with genetic distance metrics showing statistically significant differentiation between certain population pairs. The PCA and cluster analyses confirmed distinct population groupings that correspond to geographic distribution patterns. These findings provide the first comprehensive assessment of C. tribuloides population genetics in this region, establishing baseline data for monitoring genetic diversity and informing conservation strategies. This research contributes to our understanding of how landscape features and ecological factors shape genetic diversity patterns in essential forest tree species, with implications for managing forest genetic resources in the face of environmental change. Full article
(This article belongs to the Section Plant Genetic Resources)
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18 pages, 2456 KiB  
Article
The Characterization of the Mechanical Harmonic Oscillator Extremum Envelope Shape According to Different Friction Types
by João C. Fernandes
Axioms 2025, 14(8), 554; https://doi.org/10.3390/axioms14080554 - 23 Jul 2025
Viewed by 115
Abstract
To characterize a phenomenological model of a mechanical oscillator, it is important to know the properties of the envelope of the three main physical motion variables: deviation from equilibrium, velocity, and acceleration. Experimental data show that friction forces restrict the shape of these [...] Read more.
To characterize a phenomenological model of a mechanical oscillator, it is important to know the properties of the envelope of the three main physical motion variables: deviation from equilibrium, velocity, and acceleration. Experimental data show that friction forces restrict the shape of these functions. A linear, exponential, or more abrupt decay can be observed depending on the different physical systems and conditions. This paper aimed to contribute to clarifying the role that some types of friction forces play in these shapes. Three types of friction—constant sliding friction, pressure drag proportional to the square of velocity, and friction drag proportional to velocity—were considered to characterize the line connecting the maxima and minima of displacement for a generic mechanical harmonic oscillator. The ordinary differential equation (ODE), describing the harmonic oscillator simultaneously containing the three types of dissipative forces (constant, viscous, and quadratic), was numerically solved to obtain energy dissipation, and the extrema of both displacement and velocity. The differential equation ruling the behavior of the amplitude, as a function of the friction force coefficients, was obtained from energy considerations. Solving this equation, we obtained analytical functions, parametrized by the force coefficients that describe the oscillator tail. A comparison between these functions and the predicted oscillator ODE extrema was made, and the results were in agreement for all the situations tested. Information from the velocity extrema and nulls was enough to obtain a second function that rules completely the ODE solution. The correlations obtained allow for the reverse operation: from the identified extremum data, it was possible to identify univocally the three friction coefficients fitting used in the model. Motion equations were solved, and some physical properties, namely energy conservation and work of friction forces, were revisited. Full article
(This article belongs to the Section Mathematical Physics)
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21 pages, 6005 KiB  
Article
Archetype Identification and Energy Consumption Prediction for Old Residential Buildings Based on Multi-Source Datasets
by Chengliang Fan, Rude Liu and Yundan Liao
Buildings 2025, 15(14), 2573; https://doi.org/10.3390/buildings15142573 - 21 Jul 2025
Viewed by 321
Abstract
Assessing energy consumption in existing old residential buildings is key for urban energy conservation and decarbonization. Previous studies on old residential building energy assessment face challenges due to data limitations and inadequate prediction methods. This study develops a novel approach integrating building energy [...] Read more.
Assessing energy consumption in existing old residential buildings is key for urban energy conservation and decarbonization. Previous studies on old residential building energy assessment face challenges due to data limitations and inadequate prediction methods. This study develops a novel approach integrating building energy simulation and machine learning to predict large-scale old residential building energy use using multi-source datasets. Using Guangzhou as a case study, open-source building data was collected to identify 31,209 old residential buildings based on age thresholds and areas of interest (AOIs). Key building form parameters (i.e., long side, short side, number of floors) were then classified to identify residential archetypes. Building energy consumption data for each prototype was generated using EnergyPlus (V23.2.0) simulations. Furthermore, XGBoost and Random Forest machine learning algorithms were used to predict city-scale old residential building energy consumption. Results indicated that five representative prototypes exhibited cooling energy use ranging from 17.32 to 21.05 kWh/m2, while annual electricity consumption ranged from 60.10 to 66.53 kWh/m2. The XGBoost model demonstrated strong predictive performance (R2 = 0.667). SHAP (Shapley Additive Explanations) analysis identified the Building Shape Coefficient (BSC) as the most significant positive predictor of energy consumption (SHAP value = 0.79). This framework enables city-level energy assessment for old residential buildings, providing critical support for retrofitting strategies in sustainable urban renewal planning. Full article
(This article belongs to the Special Issue Enhancing Building Resilience Under Climate Change)
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17 pages, 1154 KiB  
Article
Correlation and Path Analysis of Morphological Traits and Body Mass in Perca schrenkii
by Qing Ji, Zhengwei Wang, Huale Lu, Huimin Hao, Syeda Maira Hamid, Qing Xiao, Wentao Zhu, Tao Ai, Zhaohua Huang, Jie Wei and Zhulan Nie
Fishes 2025, 10(7), 359; https://doi.org/10.3390/fishes10070359 - 20 Jul 2025
Viewed by 161
Abstract
Perca schrenkii populations are experiencing significant declines, yet comprehensive morphological studies are still lacking. Understanding the relationship between morphological traits and body weight is crucial for conservation and breeding programs. We analyzed 13 morphological traits in 100 P. schrenkii specimens from Hamsigou Reservoir [...] Read more.
Perca schrenkii populations are experiencing significant declines, yet comprehensive morphological studies are still lacking. Understanding the relationship between morphological traits and body weight is crucial for conservation and breeding programs. We analyzed 13 morphological traits in 100 P. schrenkii specimens from Hamsigou Reservoir using correlation analysis, path analysis, and principal component analysis (PCA). Body weight exhibited the highest variability (CV = 39.76%). Strong correlations were observed between body weight and body length (R = 0.942), total length, and body width. A four-variable regression model explained 94.1% of body weight variation, with body length showing the strongest direct effect (path coefficient = 0.623). The first three principal components accounted for 76.687% of the total variance. Our findings demonstrate that BL, BW, BD, and ES can effectively predict body weight, providing valuable insights for the conservation and selective breeding of P. schrenkii. Full article
(This article belongs to the Special Issue Vantage Points in the Morphology of Aquatic Organisms)
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18 pages, 2666 KiB  
Article
Allometric Equations for Aboveground Biomass Estimation in Natural Forest Trees: Generalized or Species-Specific?
by Yuxin Shang, Yutong Xia, Xiaodie Ran, Xiao Zheng, Hui Ding and Yanming Fang
Diversity 2025, 17(7), 493; https://doi.org/10.3390/d17070493 - 18 Jul 2025
Viewed by 408
Abstract
Accurate estimation of aboveground biomass (AGB) in tree–shrub communities is critical for quantifying forest ecosystem productivity and carbon sequestration potential. Although generalized allometric equations offer expediency in natural forest AGB estimation, their neglect of interspecific variability introduces methodological pitfalls. Precise AGB prediction necessitates [...] Read more.
Accurate estimation of aboveground biomass (AGB) in tree–shrub communities is critical for quantifying forest ecosystem productivity and carbon sequestration potential. Although generalized allometric equations offer expediency in natural forest AGB estimation, their neglect of interspecific variability introduces methodological pitfalls. Precise AGB prediction necessitates resolving two biological constraints: phylogenetic conservation of allometric coefficients and ontogenetic regulation of scaling relationships. This study establishes an integrated framework combining the following: (1) phylogenetic signal detection (Blomberg’s K/Pagel’s λ) across 157 species’ allometric equations, revealing weak but significant evolutionary constraints (λ = 0.1249, p = 0.0027; K ≈ 0, p = 0.621); (2) hierarchical error decomposition of 9105 stems in a Mt. Wuyishan forest dynamics plot (15 species), identifying family-level error stratification (e.g., Theaceae vs. Myrtaceae, Δerror > 25%); (3) ontogenetic trajectory analysis of Castanopsis eyrei between Mt. Wuyishan and Mt. Huangshan, demonstrating significant biomass deviations in small trees (5–15 cm DBH, p < 0.05). Key findings resolve the following hypotheses: (1) absence of strong phylogenetic signals validates generalized models for phylogenetically diverse communities; (2) ontogenetic regulation dominates error magnitude, particularly in early developmental stages; (3) differential modeling is recommended: species-specific equations for pure forests/seedlings vs. generalized equations for mixed mature forests. This work establishes an error hierarchy: ontogeny > taxonomy > phylogeny, providing a mechanistic basis for optimizing forest carbon stock assessments. Full article
(This article belongs to the Section Plant Diversity)
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33 pages, 3914 KiB  
Article
Ecological Status of the Small Rivers of the East Kazakhstan Region
by Natalya Seraya, Gulzhan Daumova, Olga Petrova, Ricardo Garcia-Mira and Arina Polyakova
Sustainability 2025, 17(14), 6525; https://doi.org/10.3390/su17146525 - 16 Jul 2025
Viewed by 620
Abstract
The article presents a long-term assessment of the surface water quality of six small rivers in the East Kazakhstan region (Breksa, Tikhaya, Ulba, Glubochanka, Krasnoyarka, and Oba) based on hydrochemical monitoring data from the Kazhydromet State Enterprise for the period 2017–2024. A unified [...] Read more.
The article presents a long-term assessment of the surface water quality of six small rivers in the East Kazakhstan region (Breksa, Tikhaya, Ulba, Glubochanka, Krasnoyarka, and Oba) based on hydrochemical monitoring data from the Kazhydromet State Enterprise for the period 2017–2024. A unified water quality classification system was applied, along with statistical methods, including multiple linear regression. The Glubochanka and Krasnoyarka rivers were identified as the most polluted (reaching classes 4–5), with multiple exceedances of Zn (up to 2.96 mg/dm3), Cd (up to 0.8 mg/dm3), and Cu (up to 0.051 mg/dm3). The most stable and highest water quality was recorded in the Oba River, where from 2021 to 2024, water consistently corresponded to Class 2. Regression models of water quality class as a function of time and annual precipitation were constructed to assess the influence of climatic factors. Statistical analysis revealed no consistent linear correlation between average annual precipitation and water quality (correlation coefficients ranging from −0.49 to +0.37), indicating a complex interplay between climatic and anthropogenic factors. Significant relationships were found for the Breksa (R2 = 0.903), Glubochanka (R2 = 0.602), and Tikhaya (R2 = 0.555) rivers, suggesting an influence of temporal and climatic factors on water quality. In contrast, the Oba (R2 = 0.130), Ulba (R2 = 0.100), and Krasnoyarka (R2 = 0.018) rivers exhibited low coefficients, indicating the predominance of other, likely local, sources of pollution. It was found that summer periods are characterized by the highest pollution due to low water flow, while episodes of acid runoff occur in spring. A decrease in pH below 7.0 was first recorded in 2023–2024 in the Ulba and Tikhaya rivers. Forecasts to 2030 suggest relative stability in water quality under current climatic conditions; however, by 2050, the risk of water quality deterioration is expected to rise due to increased precipitation and extreme weather events. This study presents, for the first time, a systematic long-term analysis of small rivers in the East Kazakhstan region, offering deeper insight into the dynamics of surface water quality and providing a scientific foundation for developing adaptive strategies for the protection and sustainable use of water resources under climate change and anthropogenic pressure. The results emphasize the importance of prioritizing rivers with high variability in water quality for regular monitoring and the development of adaptive conservation measures. The research holds strong applied significance for shaping a sustainable water use strategy in the region. Full article
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33 pages, 10985 KiB  
Article
Integrating AHP-Entropy and IPA Models for Strategic Rural Revitalization: A Case Study of Traditional Villages in Northeast China
by Chenghao Wang, Guangping Zhang and Yunying Zhai
Buildings 2025, 15(14), 2475; https://doi.org/10.3390/buildings15142475 - 15 Jul 2025
Viewed by 305
Abstract
Traditional villages are critical to preserving cultural heritage and promoting sustainable rural development. This study evaluates the development potential of 47 traditional villages in Jilin Province from the perspectives of spatial planning, architectural conservation, and rural real estate revitalization. A Development Potential Assessment [...] Read more.
Traditional villages are critical to preserving cultural heritage and promoting sustainable rural development. This study evaluates the development potential of 47 traditional villages in Jilin Province from the perspectives of spatial planning, architectural conservation, and rural real estate revitalization. A Development Potential Assessment (DPA) framework is constructed based on five dimensions: geographical position, cultural resources, socio-economic factors, natural ecology, and living environment. The AHP-entropy weighting method is applied to ensure objectivity in scoring, while kernel density analysis and coefficient of variation techniques identify spatial patterns and internal disparities. To further inform strategic planning and targeted investment, an Importance–Performance Analysis (IPA) model is introduced, aligning resource advantages with development performance. Key findings include the following: (1) significant spatial heterogeneity, with higher potential concentrated in the southeast and lower levels in the northwest; (2) cultural and socio-economic dimensions are the most influential factors in differentiating development types; and (3) a subset of villages shows a disconnect between resource endowment and realized potential, indicating the need for tailored design interventions and investment strategies. This research offers a visual and data-driven basis for differentiated revitalization strategies, integrating urban science methods, architectural thinking, and real estate development logic. It supports refined policy implementation, spatial design decisions, and the activation of underutilized rural assets through context-sensitive planning. Full article
(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)
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27 pages, 8538 KiB  
Article
Optimizing Hyperspectral Desertification Monitoring Through Metaheuristic-Enhanced Wavelet Packet Noise Reduction and Feature Band Selection
by Weichao Liu, Jiapeng Xiao, Rongyuan Liu, Yan Liu, Yunzhu Tao, Tian Zhang, Fuping Gan, Ping Zhou, Yuanbiao Dong and Qiang Zhou
Remote Sens. 2025, 17(14), 2444; https://doi.org/10.3390/rs17142444 - 14 Jul 2025
Viewed by 238
Abstract
Land desertification represents a significant and sensitive global ecological issue. In the Inner Mongolia region of China, soil desertification and salinization are widespread, resulting from the combined effects of extreme drought conditions and human activities. Using Gaofen 5B AHSI imagery as our data [...] Read more.
Land desertification represents a significant and sensitive global ecological issue. In the Inner Mongolia region of China, soil desertification and salinization are widespread, resulting from the combined effects of extreme drought conditions and human activities. Using Gaofen 5B AHSI imagery as our data source, we collected spectral data for seven distinct land cover types: lush vegetation, yellow sand, white sand, saline soil, saline shell, saline soil with saline vegetation, and sandy soil. We applied Particle Swarm Optimization (PSO) to fine-tune the Wavelet Packet (WP) decomposition levels, thresholds, and wavelet basis function, ensuring optimal spectral decomposition and reconstruction. Subsequently, PSO was deployed to optimize key hyperparameters of the Random Forest algorithm and compare its performance with the ResNet-Transformer model. Our results indicate that PSO effectively automates the search for optimal WP decomposition parameters, preserving essential spectral information while efficiently reducing high-frequency spectral noise. The Genetic Algorithm (GA) was also found to be effective in extracting feature bands relevant to land desertification, which enhances the classification accuracy of the model. Among all the models, integrating wavelet packet denoising, genetic algorithm feature selection, the first-order differential (FD), and the hybrid architecture of the ResNet-Transformer, the WP-GA-FD-ResNet-Transformer model achieved the highest accuracy in extracting soil sandification and salinization, with Kappa coefficients and validation set accuracies of 0.9746 and 97.82%, respectively. This study contributes to the field by advancing hyperspectral desertification monitoring techniques and suggests that the approach could be valuable for broader ecological conservation and land management efforts. Full article
(This article belongs to the Section Ecological Remote Sensing)
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12 pages, 2564 KiB  
Article
Genetic Diversity and Population Structure Analysis of Luhua chickens Based on Genome-Wide Markers
by Qianwen Yang, Wei Han, Jun Yan, Chenghao Zhou, Guohui Li, Huiyong Zhang, Jianmei Yin and Xubin Lu
Animals 2025, 15(14), 2071; https://doi.org/10.3390/ani15142071 - 14 Jul 2025
Viewed by 258
Abstract
The Luhua chicken is an outstanding local breed in China that has been placed under conservation due to the impact of specialized breeding and the widespread adoption of commercial varieties. As such, this study analyzed reproductive traits across three consecutive generations and utilized [...] Read more.
The Luhua chicken is an outstanding local breed in China that has been placed under conservation due to the impact of specialized breeding and the widespread adoption of commercial varieties. As such, this study analyzed reproductive traits across three consecutive generations and utilized whole-genome resequencing data from 60 Luhua chickens to assess conservation efficacy through genetic diversity, run of homozygosity (ROH) distribution, kinship, and population structure so as to better conserve the breed. The results show that, across generations, the body weight at first egg increased, the age at first egg was delayed, and the egg weight at first laying increased. No significant variations were found in the body weight at 300 d or the total egg number. The key genetic parameters of the polymorphism information content (PIC), expected heterozygosity (HE), observed heterozygosity (HO), and mean identical-by-state (IBS) distance were 0.234, 0.351, 0.277, and 0.782, respectively. The majority of ROHs ranged from 0.5 to 1 Mb, and the inbreeding coefficient based on ROHs was calculated at 0.021. The findings reveal that these traits remained unchanged across the three generations. Our research suggests that optimizing the mating plan of Luhua chickens is essential to minimize inbreeding risk. Furthermore, the methodology applied in this study provides a valuable reference for the conservation monitoring of other indigenous chicken breeds. Full article
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22 pages, 5318 KiB  
Article
Spatiotemporal Analysis of Eco-Geological Environment Using the RAGA-PP Model in Zigui County, China
by Xueling Wu, Jiaxin Lu, Chaojie Lv, Liuting Qin, Rongrui Liu and Yanjuan Zheng
Remote Sens. 2025, 17(14), 2414; https://doi.org/10.3390/rs17142414 - 12 Jul 2025
Viewed by 270
Abstract
The Three Gorges Reservoir Area in China presents a critical conflict between industrial development and ecological conservation. It functions as a key hub for water management, energy production, and shipping, while also serving as a vital zone for ecological and environmental protection. Focusing [...] Read more.
The Three Gorges Reservoir Area in China presents a critical conflict between industrial development and ecological conservation. It functions as a key hub for water management, energy production, and shipping, while also serving as a vital zone for ecological and environmental protection. Focusing on Zigui County, this study developed a 16-indicator evaluation system integrating geological, ecological, and socioeconomic factors. It utilized the Analytic Hierarchy Process (AHP), coefficient of variation (CV), and the Real-Coded Accelerating Genetic Algorithm-Projection Pursuit (RAGA-PP) model for evaluation, the latter of which optimizes the projection direction and utilizes PP to transform high-dimensional data into a low-dimensional space, thereby obtaining the values of the projection indices. The findings indicate the following: (1) The RAGA-PP model outperforms conventional AHP-CV methods in assessing Zigui County’s eco-geological environment, showing superior accuracy (higher Moran’s I) and spatial consistency. (2) Hotspot analysis confirms these results, revealing distinct spatial patterns. (3) From 2000 to 2020, “bad” quality areas decreased from 17.31% to 12.33%, while “moderate” or “better” zones expanded. (4) This improvement reflects favorable natural conditions and reduced human impacts. These trends underscore the effectiveness of China’s ecological civilization policies, which have prioritized sustainable development through targeted environmental governance, afforestation initiatives, and stringent regulations on industrial activities. Full article
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14 pages, 4249 KiB  
Article
Increased Temporal Overlap in Diel Activity Patterns Potentially Intensifies Interspecific Competition Among Sympatric Large Carnivores in the Sanjiangyuan Region of China
by Dong Wang, Quanbang Li, Jingyu Gao, Xu Su and Xinming Lian
Animals 2025, 15(14), 2059; https://doi.org/10.3390/ani15142059 - 12 Jul 2025
Viewed by 258
Abstract
Activity patterns constitute a critical adaptive trait in large carnivores, enabling them to manage interspecific competition, enhance their foraging efficiency, and adapt to fluctuating environmental conditions. At the community level, elucidating the temporal activity allocation of sympatric large carnivores is essential for understanding [...] Read more.
Activity patterns constitute a critical adaptive trait in large carnivores, enabling them to manage interspecific competition, enhance their foraging efficiency, and adapt to fluctuating environmental conditions. At the community level, elucidating the temporal activity allocation of sympatric large carnivores is essential for understanding species coexistence mechanisms. However, the activity patterns of most large carnivores remain inadequately explored. In this study, spanning a survey period from June 2014 to April 2024, we employed infrared camera technology to collect a total of 3312, 352, 240, and 79 independently validated photographs of snow leopards (Panthera uncia Schreber, 1775), wolves (Canis lupus Linnaeus, 1758), brown bears (Ursus arctos Linnaeus, 1758), and Eurasian lynx (Lynx lynx Linnaeus, 1758), respectively, across six distinct regions in the Sanjiangyuan Region (SR) and during different monitoring time periods. We utilized kernel density estimation and the coefficient of overlaps to assess diel activity pattern overlap and competitive intensities through pairwise comparisons among these four large carnivores. An analysis of the diel activity rhythm curves revealed that all four large carnivores predominantly exhibited nocturnal behavior, although their peak activity periods differed notably. Furthermore, the diel activity rhythm overlap between each pair of species showed moderate to high intensity throughout the year (0.5 ≤ Δ < 1), including during both the cold and warm seasons. Specifically, the diel activity rhythms of snow leopards and wolves, snow leopards and Eurasian lynx, and wolves and Eurasian lynx exhibited high levels of overlap annually and during the cold season (0.8 ≤ Δ < 1) but only moderate overlap during the warm season (0.5 ≤ Δ < 0.8). Our findings suggest that the diel activity rhythms of these four large carnivore species exhibited considerable overlap, potentially intensifying interspecific competition. This study advances our knowledge on the competitive and coexistence mechanisms of large carnivores in high-altitude mountainous ecosystems, offering critical data for their conservation and management. Full article
(This article belongs to the Section Wildlife)
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22 pages, 2749 KiB  
Article
Genetic Diversity, Population Structure, and Historical Gene Flow Patterns of Nine Indigenous Greek Sheep Breeds
by Sofia Michailidou, Maria Kyritsi, Eleftherios Pavlou, Antiopi Tsoureki and Anagnostis Argiriou
Biology 2025, 14(7), 845; https://doi.org/10.3390/biology14070845 - 10 Jul 2025
Viewed by 436
Abstract
Ιn this study, we evaluated the genetic resources of nine Greek sheep breeds. The genotyping data of 292 animals were acquired from Illumina’s OvineSNP50 Genotyping BeadChip. The genetic diversity and inbreeding levels were evaluated using the observed and expected heterozygosity indices, the F [...] Read more.
Ιn this study, we evaluated the genetic resources of nine Greek sheep breeds. The genotyping data of 292 animals were acquired from Illumina’s OvineSNP50 Genotyping BeadChip. The genetic diversity and inbreeding levels were evaluated using the observed and expected heterozygosity indices, the FIS inbreeding coefficient, and runs of homozygosity (ROH). The genetic differentiation of breeds was assessed using the FST index, whereas their population structure was analyzed using admixture and principal components analysis (PCA). Historical recombination patterns and genetic drift were evaluated based on linkage disequilibrium, effective population sizes, and gene flow analysis to reveal migration patterns. PCA revealed distinct clusters mostly separating mountainous, insular, and lowland breeds. The FST value was the lowest between Serres and Karagouniko breeds (0.050). Admixture analysis revealed a genetic substructure for Serres and Kalarritiko breeds, while Chios, followed by Katsika, demonstrated the highest within-breed genetic uniformity. ROH analysis revealed low levels of inbreeding for all breeds. Genetic introgression from both Anatolia and Eastern Europe has been evidenced for Greek sheep breeds. The results also revealed that Greek sheep breeds maintain adequate levels of genetic diversity, without signs of excessive inbreeding, and can serve as valuable resources for the conservation of local biodiversity. Full article
(This article belongs to the Special Issue Genetic Variability within and between Populations)
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21 pages, 3919 KiB  
Article
Comparative Analysis of Resampling Techniques for Class Imbalance in Financial Distress Prediction Using XGBoost
by Guodong Hou, Dong Ling Tong, Soung Yue Liew and Peng Yin Choo
Mathematics 2025, 13(13), 2186; https://doi.org/10.3390/math13132186 - 4 Jul 2025
Viewed by 397
Abstract
One of the key challenges in financial distress data is class imbalance, where the data are characterized by a highly imbalanced ratio between the number of distressed and non-distressed samples. This study examines eight resampling techniques for improving distress prediction using the XGBoost [...] Read more.
One of the key challenges in financial distress data is class imbalance, where the data are characterized by a highly imbalanced ratio between the number of distressed and non-distressed samples. This study examines eight resampling techniques for improving distress prediction using the XGBoost algorithm. The study was performed on a dataset acquired from the CSMAR database, containing 26,383 firm-quarter samples from 639 Chinese A-share listed companies (2007–2024), with only 12.1% of the cases being distressed. Results show that standard Synthetic Minority Oversampling Technique (SMOTE) enhanced F1-score (up to 0.73) and Matthews Correlation Coefficient (MCC, up to 0.70), while SMOTE-Tomek and Borderline-SMOTE further boosted recall, slightly sacrificing precision. These oversampling and hybrid methods also maintained reasonable computational efficiency. However, Random Undersampling (RUS), though yielding high recall (0.85), suffered from low precision (0.46) and weaker generalization, but was the fastest method. Among all techniques, Bagging-SMOTE achieved balanced performance (AUC 0.96, F1 0.72, PR-AUC 0.80, MCC 0.68) using a minority-to-majority ratio of 0.15, demonstrating that ensemble-based resampling can improve robustness with minimal impact on the original class distribution, albeit with higher computational cost. The compared findings highlight that no single approach fits all use cases, and technique selection should align with specific goals. Techniques favoring recall (e.g., Bagging-SMOTE, SMOTE-Tomek) are suited for early warning, while conservative techniques (e.g., Tomek Links) help reduce false positives in risk-sensitive applications, and efficient methods such as RUS are preferable when computational speed is a priority. Full article
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