Saved Queries

by Fengyan Deng, Valentina Peña, Pedro Morales-Sosa, Andrea Bernal-Rivera, Bowen Yang, Shengping Huang, Sonia Ghosh, Maria Katt, Luciana Andrea Castellano, Lucinda Maddera, Zulin Yu, Nicolas Rohner, Chongbei Zhao and Jasmin Camacho

Cells 2025, 14(15), 1190; https://doi.org/10.3390/cells14151190 (registering DOI) - 1 Aug 2025

Abstract

Skeletal muscle regeneration depends on muscle stem cells, which give rise to myoblasts that drive muscle growth, repair, and maintenance. In bats—the only mammals capable of powered flight—these processes must also sustain contractile performance under extreme mechanical and metabolic stress. However, the cellular and molecular mechanisms underlying bat muscle physiology remain largely unknown. To enable mechanistic investigation of these traits, we established the first myoblast cell lines from the pectoralis muscle of Pteronotus mesoamericanus, a highly maneuverable aerial insectivore. Using both spontaneous immortalization and exogenous hTERT/CDK4 gene overexpression, we generated two stable cell lines that retain proliferative capacity and differentiate into contractile myotubes. These cells exhibit frequent spontaneous contractions, suggesting robust functional integrity at the neuromuscular junction. In parallel, we performed transcriptomic and metabolic profiling of native pectoralis tissue in the closely related Pteronotus parnellii to define molecular programs supporting muscle specialization. Gene expression analyses revealed enriched pathways for muscle metabolism, development, and regeneration, highlighting supporting roles in tissue maintenance and repair. Consistent with this profile, the flight muscle is triglyceride-rich, which serves as an important fuel source for energetically demanding processes, including muscle contraction and cellular recovery. Integration of transcriptomic and metabolic data identified three key metabolic modules—glucose utilization, lipid handling, and nutrient signaling—that likely coordinate ATP production and support metabolic flexibility. Together, these complementary tools and datasets provide the first in vitro platform for investigating bat muscle research, enabling direct exploration of muscle regeneration, metabolic resilience, and evolutionary physiology. Full article

(This article belongs to the Special Issue Advances in Understanding Skeletal Muscle Metabolism and Regeneration: From Mechanisms to Therapeutics)

16 pages, 1388 KiB

Open AccessArticle

Modeling and Load Capacity Analysis of Helical Anchors for Dam Foundation Reinforcement Against Water Disasters

by Dawei Lv, Zixian Shi, Zhendu Li, Songzhao Qu and Heng Liu

Water 2025, 17(15), 2296; https://doi.org/10.3390/w17152296 (registering DOI) - 1 Aug 2025

Abstract

Hydraulic actions may compromise dam foundation stability. Helical anchors have been used in dam foundation reinforcement projects because of the advantages of large uplift and compression bearing capacity, fast installation, and convenient recovery. However, the research on the anchor plate, which plays a key role in the bearing performance of helical anchors, is insufficient at present. Based on the finite element model of helical anchor, this study reveals the failure mode and influencing factors of the anchor plate and establishes the theoretical model of deformation calculation. The results showed that the helical anchor plate had obvious bending deformation when the dam foundation reinforced with a helical anchor reached large deformation. The helical anchor plate can be simplified to a flat circular disk. The stress distribution of the closed flat disk and the open flat disk was consistent with that of the helical disk. The maximum deformation of the closed flat disk was slightly smaller than that of the helical disk (less than 6%), and the deformation of the open flat disk was consistent with that of the helical disk. The results fill the blank of the design basis of helical anchor plate and provide a reference basis for the engineering design. Full article

(This article belongs to the Special Issue Disaster Analysis and Prevention of Dam and Slope Engineering)

20 pages, 1907 KiB

Open AccessArticle

Multi-Innovation-Based Parameter Identification for Vertical Dynamic Modeling of AUV Under High Maneuverability and Large Attitude Variations

by Jianping Yuan, Zhixun Luo, Lei Wan, Cenan Wang, Chi Zhang and Qingdong Chen

J. Mar. Sci. Eng. 2025, 13(8), 1489; https://doi.org/10.3390/jmse13081489 (registering DOI) - 1 Aug 2025

Abstract

The parameter identification of Autonomous Underwater Vehicles (AUVs) serves as a fundamental basis for achieving high-precision motion control, state monitoring, and system development. Currently, AUV parameter identification typically relies on the complete motion information obtained from onboard sensors. However, in practical applications, it is often challenging to accurately measure key state variables such as velocity and angular velocity, resulting in incomplete measurement data that compromises identification accuracy and model reliability. This issue is particularly pronounced in vertical motion tasks involving low-speed, large pitch angles, and highly maneuverable conditions, where the strong coupling and nonlinear characteristics of underwater vehicles become more significant. Traditional hydrodynamic models based on full-state measurements often suffer from limited descriptive capability and difficulties in parameter estimation under such conditions. To address these challenges, this study investigates a parameter identification method for AUVs operating under vertical, large-amplitude maneuvers with constrained measurement information. A control autoregressive (CAR) model-based identification approach is derived, which requires only pitch angle, vertical velocity, and vertical position data, thereby reducing the dependence on complete state observations. To overcome the limitations of the conventional Recursive Least Squares (RLS) algorithm—namely, its slow convergence and low accuracy under rapidly changing conditions—a Multi-Innovation Least Squares (MILS) algorithm is proposed to enable the efficient estimation of nonlinear hydrodynamic characteristics in complex dynamic environments. The simulation and experimental results validate the effectiveness of the proposed method, demonstrating high identification accuracy and robustness in scenarios involving large pitch angles and rapid maneuvering. The results confirm that the combined use of the CAR model and MILS algorithm significantly enhances model adaptability and accuracy, providing a solid data foundation and theoretical support for the design of AUV control systems in complex operational environments. Full article

(This article belongs to the Section Ocean Engineering)

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64 pages, 1429 KiB

Open AccessReview

Pharmacist-Driven Chondroprotection in Osteoarthritis: A Multifaceted Approach Using Patient Education, Information Visualization, and Lifestyle Integration

by Eloy del Río

Pharmacy 2025, 13(4), 106; https://doi.org/10.3390/pharmacy13040106 (registering DOI) - 1 Aug 2025

Abstract

Osteoarthritis (OA) remains a major contributor to pain and disability; however, the current management is largely reactive, focusing on symptoms rather than preventing irreversible cartilage loss. This review first examines the mechanistic foundations for pharmacological chondroprotection—illustrating how conventional agents, such as glucosamine sulfate and chondroitin sulfate, can potentially restore extracellular matrix (ECM) components, may attenuate catabolic enzyme activity, and might enhance joint lubrication—and explores the delivery challenges posed by avascular cartilage and synovial diffusion barriers. Subsequently, a practical “What–How–When” framework is introduced to guide community pharmacists in risk screening, DMOAD selection, chronotherapeutic dosing, safety monitoring, and lifestyle integration, as exemplified by the CHONDROMOVING infographic brochure designed for diverse health literacy levels. Building on these strategies, the P4–4P Chondroprotection Framework is proposed, integrating predictive risk profiling (physicians), preventive pharmacokinetic and chronotherapy optimization (pharmacists), personalized biomechanical interventions (physiotherapists), and participatory self-management (patients) into a unified, feedback-driven OA care model. To translate this framework into routine practice, I recommend the development of DMOAD-specific clinical guidelines, incorporation of chondroprotective chronotherapy and interprofessional collaboration into health-professional curricula, and establishment of multidisciplinary OA management pathways—supported by appropriate reimbursement structures, to support preventive, team-based management, and prioritization of large-scale randomized trials and real-world evidence studies to validate the long-term structural, functional, and quality of life benefits of synchronized DMOAD and exercise-timed interventions. This comprehensive, precision-driven paradigm aims to shift OA care from reactive palliation to true disease modification, preserving cartilage integrity and improving the quality of life for millions worldwide. Full article

41 pages, 1651 KiB

Open AccessReview

Progress and Challenges in the Process of Using Solid Waste as a Catalyst for Biodiesel Synthesis

by Zhaolin Dong, Kaili Dong, Haotian Li, Liangyi Zhang and Yitong Wang

Molecules 2025, 30(15), 3243; https://doi.org/10.3390/molecules30153243 (registering DOI) - 1 Aug 2025

Abstract

Biodiesel, as one of the alternatives to fossil fuels, faces significant challenges in large-scale industrial production due to its high production costs. In addition to raw material costs, catalyst costs are also a critical factor that cannot be overlooked. This review summarizes various methods for preparing biodiesel catalysts from solid waste. These methods not only enhance the utilization rate of waste but also reduce the production costs and environmental impact of biodiesel. Finally, the limitations of waste-based catalysts and future research directions are discussed. Research indicates that solid waste can serve as a catalyst carrier or active material for biodiesel production. Methods such as high-temperature calcination, impregnation, and coprecipitation facilitate structural modifications to the catalyst and the formation of active sites. The doping of metal ions not only alters the catalyst’s acid-base properties but also forms stable metal bonds with functional groups on the carrier, thereby maintaining catalyst stability. The application of microwave-assisted and ultrasound-assisted methods reduces reaction parameters, making biodiesel production more economical and sustainable. Overall, this study provides a scientific basis for the reuse of solid waste and ecological protection, emphasizes the development potential of waste-based catalysts in biodiesel production, and offers unique insights for innovation in this field, thereby accelerating the commercialization of biodiesel. Full article

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15 pages, 2172 KiB

Open AccessArticle

Quantifying Macropore Variability in Terraced Paddy Fields Using X-Ray Computed Tomography

by Rong Ma, Linlin Chu, Lidong Bi, Dan Chen and Zhaohui Luo

Agronomy 2025, 15(8), 1873; https://doi.org/10.3390/agronomy15081873 (registering DOI) - 1 Aug 2025

Abstract

Large soil pores critically influence water and solute transport in soils. The presence of preferential flow paths created by soil macropores can profoundly impact water quality, underscoring the necessity of accurately assessing the characteristics of these macropores. However, it remains unclear whether variations in macropore structure exist between different altitudes and positions of terraced paddy fields. The primary objective of this research was to utilize X-ray computed tomography (CT) and image analysis techniques to characterize the soil pore structure at both the inner field and ridge positions across different altitude levels (high, medium, and low altitude) within terraced paddy fields. The results indicate that there are significant differences in the distribution of large soil pores at different altitudes, with large pores concentrated in the surface layer (0–10 cm) in low-altitude areas, while in high-altitude areas, the distribution of large pores is more uniform. Additionally, as altitude increases, the porosity of large pores shows an increasing trend. The three-dimensional equivalent diameter and large pore volume are primarily characterized by large pores ranging from 1 to 2 mm and 0 to 5 mm³, respectively, with their morphology predominantly appearing spherical or ellipsoidal. The connectivity of large pores in the surface layer of paddy soil is stronger than that in the bunds. However, this connectivity gradually weakens with increasing soil depth. The findings from this study provide valuable quantitative insights into the unique characteristics of soil macropores that vary according to the altitude and position in terraced paddy fields. Moreover, this study emphasizes the necessity for future research that encompasses a broader range of soil types, altitudes, and terraced paddy locations to validate and further explore the identified relationships between altitude and macropore characteristics. Full article

(This article belongs to the Section Precision and Digital Agriculture)

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44 pages, 941 KiB

Open AccessArticle

Managing Surcharge Risk in Strategic Fleet Deployment: A Partial Relaxed MIP Model Framework with a Case Study on China-Built Ships

by Yanmeng Tao, Ying Yang and Shuaian Wang

Appl. Sci. 2025, 15(15), 8582; https://doi.org/10.3390/app15158582 (registering DOI) - 1 Aug 2025

Abstract

Container liner shipping companies operate within a complex environment where they must balance profitability and service reliability. Meanwhile, evolving regulatory policies, such as surcharges imposed on ships of a particular origin or type on specific trade lanes, introduce new operational challenges. This study addresses the heterogeneous ship routing and demand acceptance problem, aiming to maximize two conflicting objectives: weekly profit and total transport volume. We formulate the problem as a bi-objective mixed-integer programming model and prove that the ship chartering constraint matrix is totally unimodular, enabling the reformulation of the model into a partially relaxed MIP that preserves optimality while improving computational efficiency. We further analyze key mathematical properties showing that the Pareto frontier consists of a finite union of continuous, piecewise linear segments but is generally non-convex with discontinuities. A case study based on a realistic liner shipping network confirms the model’s effectiveness in capturing the trade-off between profit and transport volume. Sensitivity analyses show that increasing freight rates enables higher profits without large losses in volume. Notably, this paper provides a practical risk management framework for shipping companies to enhance their adaptability under shifting regulatory landscapes. Full article

(This article belongs to the Special Issue Risk and Safety of Maritime Transportation)

23 pages, 1480 KiB

Open AccessArticle

Operator Newton Method for Large-Scale Coupled Riccati Equations Arising from Jump Systems

by Bo Yu, Yiwen Liu and Ning Dong

Axioms 2025, 14(8), 601; https://doi.org/10.3390/axioms14080601 (registering DOI) - 1 Aug 2025

Abstract

Consider a class of coupled discrete-time Riccati equations arising from jump systems. To compute their solutions when systems reach a steady state, we propose an operator Newton method and correspondingly establish its quadratic convergence under suitable assumptions. The advantage of the proposed method lies in the fact that its subproblems are solved using the operator Smith method, which allows it to maintain quadratic convergence in both the inner and outer iterations. Moreover, it does not require the constant term matrix of the equation to be invertible, making it more broadly applicable than existing inverse-free iterative methods. For large-scale problems, we develop a low-rank variant by incorporating truncation and compression techniques into the operator Newton framework. A complexity analysis is also provided to assess its scalability. Numerical experiments demonstrate that the presented low-rank operator Newton method is highly effective in approximating solutions to large-scale structured coupled Riccati equations. Full article

(This article belongs to the Special Issue Advances in Linear Algebra with Applications, 2nd Edition)

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25 pages, 1138 KiB

Open AccessArticle

Quality over Quantity: An Effective Large-Scale Data Reduction Strategy Based on Pointwise V-Information

by Fei Chen and Wenchi Zhou

Electronics 2025, 14(15), 3092; https://doi.org/10.3390/electronics14153092 (registering DOI) - 1 Aug 2025

Abstract

In order to increase the effectiveness of model training, data reduction is essential to data-centric Artificial Intelligence (AI). It achieves this by locating the most instructive examples in massive datasets. To increase data quality and training efficiency, the main difficulty is choosing the best examples rather than the complete datasets. In this paper, we propose an effective data reduction strategy based on Pointwise 𝒱-Information (PVI). To enable a static method, we first use PVI to quantify instance difficulty and remove instances with low difficulty. Experiments show that classifier performance is maintained with only a 0.0001% to 0.76% decline in accuracy when 10–30% of the data is removed. Second, we train the classifiers using a progressive learning strategy on examples sorted by increasing PVI, accelerating convergence and achieving a 0.8% accuracy gain over conventional training. Our findings imply that training a classifier on the chosen optimal subset may improve model performance and increase training efficiency when combined with an efficient data reduction strategy. Furthermore, we have adapted the PVI framework, which was previously limited to English datasets, to a variety of Chinese Natural Language Processing (NLP) tasks and base models, yielding insightful results for faster training and cross-lingual data reduction. Full article

(This article belongs to the Special Issue Data Retrieval and Data Mining)

13 pages, 441 KiB

Open AccessArticle

Pulmonary Involvement in Patients with Positive Myositis Antibodies in Rheumatology: A Retrospective Monocentric Analysis

by Falk Schumacher, Malte Kanbach, Maximilian Zimmermann, Daniel Majorski, Wigbert Schulze, Maximilian Wollsching-Strobel, Doreen Kroppen, Sarah Bettina Stanzel, Wolfram Windisch, Johannes Strunk and Melanie Berger

J. Clin. Med. 2025, 14(15), 5443; https://doi.org/10.3390/jcm14155443 (registering DOI) - 1 Aug 2025

Abstract

Background: Pulmonary involvement is the most common prognosis-related organ involvement in idiopathic inflammatory myopathy (IIM). Owing to the large number of antibodies, the evidence for lung involvement and rare antibodies is limited. In everyday clinical practice, the interpretation of positive myositis antibodies represents a challenge. Methods: This study is a retrospective monocentric analysis. The data collection regarding positive myositis antibodies and possible pulmonary involvement was carried out from July 2019 to May 2022. Data analysis revealed positive results for one of the following antibodies: EJ, PL7, OJ, PL12, Mi-2α, TIF1γ, MDA5, SAE, NXP2, SRP, Ku, PM-Scl100 and PM-Scl75. In our analysis, patients with IIM, patients with inflammatory rheumatic disease other than IIM and patients without inflammatory rheumatic disease are described. The results of high-resolution computed tomography (HRCT), pulmonary function tests, echocardiographic examinations and their associated clinical findings are examined. Results: In the entire cohort, 209 patients with positive myositis antibodies were detected. In total, 22 (10.5%) patients had interstitial lung disease (ILD) patterns on HRCT. In the subgroup of patients with IIM, a significantly higher proportion of patients with lung involvement (n = 13, 35.1%) was found than in the group with other inflammatory rheumatic diseases (IRDs) (n = 6, 6.7%) or in the group without IRDs (n = 3, 3.7%). When the antibody groups were considered, the PL12-positive patients had the largest proportion of ILD (42%), followed by the MDA5-positive patients (40%). Conclusions: In patients with IIM, myositis antibodies are highly relevant for assessing the risk of lung involvement. In groups with other IRD or without IRD, antibody detection does not represent this high relevance for lung involvement. A differentiated assessment of the various MSAs or MAAs detected, as well as clinical parameters, allows for further important risk assessment for prognosis-relevant lung involvement. Full article

(This article belongs to the Section Immunology)

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19 pages, 3765 KiB

Open AccessArticle

Mathematical Study of Pulsatile Blood Flow in the Uterine and Umbilical Arteries During Pregnancy

by Anastasios Felias, Charikleia Skentou, Minas Paschopoulos, Petros Tzimas, Anastasia Vatopoulou, Fani Gkrozou and Michail Xenos

Fluids 2025, 10(8), 203; https://doi.org/10.3390/fluids10080203 (registering DOI) - 1 Aug 2025

Abstract

This study applies Computational Fluid Dynamics (CFD) and mathematical modeling to examine uterine and umbilical arterial blood flow during pregnancy, providing a more detailed understanding of hemodynamic changes across gestation. Statistical analysis of Doppler ultrasound data from a large cohort of more than [...] Read more.

P S V

) between the 22nd and 30th weeks, while uterine artery velocities remain relatively stable, suggesting adaptations in vascular resistance during pregnancy. By combining the Navier–Stokes equations with Doppler ultrasound-derived inlet velocity profiles, we quantify several key fluid dynamics parameters, including time-averaged wall shear stress (

T A W S S

), oscillatory shear index (

O S I

), relative residence time (

R R T

), Reynolds number (

R e

), and Dean number (

D e

), evaluating laminar flow stability in the uterine artery and secondary flow patterns in the umbilical artery. Since blood exhibits shear-dependent viscosity and complex rheological behavior, modeling it as a non-Newtonian fluid is essential to accurately capture pulsatile flow dynamics and wall shear stresses in these vessels. Unlike conventional imaging techniques, CFD offers enhanced visualization of blood flow characteristics such as streamlines, velocity distributions, and instantaneous particle motion, providing insights that are not easily captured by Doppler ultrasound alone. Specifically, CFD reveals secondary flow patterns in the umbilical artery, which interact with the primary flow, a phenomenon that is challenging to observe with ultrasound. These findings refine existing hemodynamic models, provide population-specific reference values for clinical assessments, and improve our understanding of the relationship between umbilical arterial flow dynamics and fetal growth restriction, with important implications for maternal and fetal health monitoring. Full article

(This article belongs to the Special Issue Advances in Computational Mechanics of Non-Newtonian Fluids, 2nd Edition)

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25 pages, 2860 KiB

Open AccessReview

Multimodal Sensing-Enabled Large Language Models for Automated Emotional Regulation: A Review of Current Technologies, Opportunities, and Challenges

by Liangyue Yu, Yao Ge, Shuja Ansari, Muhammad Imran and Wasim Ahmad

Sensors 2025, 25(15), 4763; https://doi.org/10.3390/s25154763 (registering DOI) - 1 Aug 2025

Abstract

Emotion regulation is essential for mental health. However, many people ignore their own emotional regulation or are deterred by the high cost of psychological counseling, which poses significant challenges to making effective support widely available. This review systematically examines the convergence of multimodal sensing technologies and large language models (LLMs) for the development of Automated Emotional Regulation (AER) systems. The review draws upon a comprehensive analysis of the existing literature, encompassing research papers, technical reports, and relevant theoretical frameworks. Key findings indicate that multimodal sensing offers the potential for rich, contextualized data pertaining to emotional states, while LLMs provide improved capabilities for interpreting these inputs and generating nuanced, empathetic, and actionable regulatory responses. The integration of these technologies, including physiological sensors, behavioral tracking, and advanced LLM architectures, presents the improvement of application, moving AER beyond simpler, rule-based systems towards more adaptive, context-aware, and human-like interventions. Opportunities for personalized interventions, real-time support, and novel applications in mental healthcare and other domains are considerable. However, these prospects are counterbalanced by significant challenges and limitations. In summary, this review synthesizes current technological advancements, identifies substantial opportunities for innovation and application, and critically analyzes the multifaceted technical, ethical, and practical challenges inherent in this domain. It also concludes that while the integration of multimodal sensing and LLMs holds significant potential for AER, the field is nascent and requires concerted research efforts to realize its full capacity to enhance human well-being. Full article

(This article belongs to the Section Intelligent Sensors)

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13 pages, 2583 KiB

Open AccessArticle

Hierarchical Flaky Spinel Structure with Al and Mn Co-Doping Towards Preferable Oxygen Evolution Performance

by Hengfen Shen, Hao Du, Peng Li and Mei Wang

Materials 2025, 18(15), 3633; https://doi.org/10.3390/ma18153633 (registering DOI) - 1 Aug 2025

Abstract

As an efficient clean energy technology, water electrolysis for hydrogen production has its efficiency limited by the sluggish oxygen evolution reaction (OER) kinetics, which drives the demand for the development of high-performance anode OER catalysts. This work constructs bimetallic (Al, Mn) co-doped nanoporous spinel CoFe₂O₄ (np-CFO) with a tunable structure and composition as an OER catalyst through a simple two-step dealloying strategy. The as-formed np-CFO (Al and Mn) features a hierarchical flaky configuration; that is, there are a large number of fine nanosheets attached to the surface of a regular micron-sized flake, which not only increases the number of active sites but also enhances mass transport efficiency. Consequently, the optimized catalyst exhibits a low OER overpotential of only 320 mV at a current density of 10 mA cm⁻², a minimal Tafel slope of 45.09 mV dec⁻¹, and exceptional durability. Even under industrial conditions (6 M KOH, 60 °C), it only needs 1.83 V to achieve a current density of 500 mA cm⁻² and can maintain good stability for approximately 100 h at this high current density. Theoretical simulations indicate that Al and Mn co-doping could indeed optimize the electronic structure of CFO and thus decrease the energy barrier of OER to 1.35 eV. This work offers a practical approach towards synthesizing efficient and stable OER catalysts. Full article

(This article belongs to the Special Issue High-Performance Materials for Energy Conversion)

27 pages, 39231 KiB

Open AccessArticle

Study on the Distribution Characteristics of Thermal Melt Geological Hazards in Qinghai Based on Remote Sensing Interpretation Method

by Xing Zhang, Zongren Li, Sailajia Wei, Delin Li, Xiaomin Li, Rongfang Xin, Wanrui Hu, Heng Liu and Peng Guan

Water 2025, 17(15), 2295; https://doi.org/10.3390/w17152295 (registering DOI) - 1 Aug 2025

Abstract

In recent years, large-scale linear infrastructure developments have been developed across hundreds of kilometers of permafrost regions on the Qinghai–Tibet Plateau. The implementation of major engineering projects, including the Qinghai–Tibet Highway, oil pipelines, communication cables, and the Qinghai–Tibet Railway, has spurred intensified research into permafrost dynamics. Climate warming has accelerated permafrost degradation, leading to a range of geological hazards, most notably widespread thermokarst landslides. This study investigates the spatiotemporal distribution patterns and influencing factors of thermokarst landslides in Qinghai Province through an integrated approach combining field surveys, remote sensing interpretation, and statistical analysis. The study utilized multi-source datasets, including Landsat-8 imagery, Google Earth, GF-1, and ZY-3 satellite data, supplemented by meteorological records and geospatial information. The remote sensing interpretation identified 1208 cryogenic hazards in Qinghai’s permafrost regions, comprising 273 coarse-grained soil landslides, 346 fine-grained soil landslides, 146 thermokarst slope failures, 440 gelifluction flows, and 3 frost mounds. Spatial analysis revealed clusters of hazards in Zhiduo, Qilian, and Qumalai counties, with the Yangtze River Basin and Qilian Mountains showing the highest hazard density. Most hazards occur in seasonally frozen ground areas (3500–3900 m and 4300–4900 m elevation ranges), predominantly on north and northwest-facing slopes with gradients of 10–20°. Notably, hazard frequency decreases with increasing permafrost stability. These findings provide critical insights for the sustainable development of cold-region infrastructure, environmental protection, and hazard mitigation strategies in alpine engineering projects. Full article

(This article belongs to the Special Issue Slope Stability Analyses and Landslide Risk Assessment Under Hydrodynamic Action)

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23 pages, 10868 KiB

Open AccessArticle

Quantitative Analysis and Nonlinear Response of Vegetation Dynamic to Driving Factors in Arid and Semi-Arid Regions of China

by Shihao Liu, Dazhi Yang, Xuyang Zhang and Fangtian Liu

Land 2025, 14(8), 1575; https://doi.org/10.3390/land14081575 (registering DOI) - 1 Aug 2025

Abstract

Vegetation dynamics are complexly influenced by multiple factors such as climate, human activities, and topography. In recent years, the frequency, intensity, and diversity of human activities have increased, placing substantial pressure on the growth of vegetation. Arid and semi-arid regions are particularly sensitive to climate change, and climate change and large-scale ecological restoration have led to significant changes in the dynamic of dryland vegetation. However, few studies have explored the nonlinear relationships between these factors and vegetation dynamic. In this study, we integrated trend analysis (using the Mann–Kendall test and Theil–Sen estimation) and machine learning algorithms (XGBoost-SHAP model) based on long time-series remote sensing data from 2001 to 2020 to quantify the nonlinear response patterns and threshold effects of bioclimatic variables, topographic features, soil attributes, and anthropogenic factors on vegetation dynamic. The results revealed the following key findings: (1) The kNDVI in the study area showed an overall significant increasing trend (p < 0.01) during the observation period, of which 26.7% of the area showed a significant increase. (2) The water content index (Bio 23, 19.6%), the change in land use (15.2%), multi-year average precipitation (pre, 15.0%), population density (13.2%), and rainfall seasonality (Bio 15, 10.9%) were the key factors driving the dynamic change of vegetation, with the combined contribution of natural factors amounting to 64.3%. (3) Among the topographic factors, altitude had a more significant effect on vegetation dynamics, with higher altitude regions less likely to experience vegetation greening. Both natural and anthropogenic factors exhibited nonlinear responses and interactive effects, contributing to the observed dynamic trends. This study provides valuable insights into the driving mechanisms behind the condition of vegetation in arid and semi-arid regions of China and, by extension, in other arid regions globally. Full article

(This article belongs to the Section Land Use, Impact Assessment and Sustainability)

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