Watershed Ecology and the Environment最新文献

{"title":"Integrated watershed management for transforming dryland livelihoods: A climate-smart strategy for sustainable dryland agriculture in India","authors":"Ram A. Jat ,&nbsp;Dinesh Jinger ,&nbsp;Anita Kumawat ,&nbsp;Saswat Kumar Kar ,&nbsp;Indu Rawat ,&nbsp;Suresh Kumar ,&nbsp;Venkatesh Paramesh ,&nbsp;Vijay Singh Meena ,&nbsp;Rajesh Kaushal ,&nbsp;Kuldeep Kumar ,&nbsp;Hari Singh Meena ,&nbsp;S.P. Wani ,&nbsp;Rajbir Singh ,&nbsp;M. Madhu","doi":"10.1016/j.wsee.2025.03.006","DOIUrl":"10.1016/j.wsee.2025.03.006","url":null,"abstract":"<div><div>In India, 51 % of the net sown area relies on rainfed agriculture, with 40 % of landholdings unirrigated and 13 % partially irrigated. Rainfed farming produces 40 % of food grains and supports two-thirds of the livestock population but faces challenges like land degradation, low productivity, and biodiversity loss due to erratic monsoons and extreme weather. Additionally, India’s water scarcity is worsening, with per capita availability expected to reduce from 802 cubic meters in 2022 to 677 cubic meters by 2050. Therefore, to meet the diverse food requirements of the burgeoning population of the country, conservation of natural resources, and improving the living standard of the resource-poor small and marginal farmers is imperative. Integrated watershed management (IWM) has emerged as a climate-smart strategy to address these challenges by enhancing soil and water conservation, agricultural productivity, and livelihoods in dryland systems. This study assesses the impact of IWM on dryland agriculture in India by analyzing various interventions such as <em>in-situ</em> and <em>ex-situ</em> water conservation, soil health management, and the use of modern technologies like remote sensing (RS) and geographic information systems (GIS). The results revealed that the adoption of IWM practices has led to significant improvements in soil moisture retention (20–25 %), soil organic carbon (22–32 %) agricultural productivity (30–45 %), and water use efficiency (15–25 %). Additionally, soil conservation techniques have reduced soil loss and runoff by 25–50 % and 50–60 %, respectively. Furthermore, the cultivation of lemon grass (<em>Cymbopogon flexuosus</em>), anjan grass (<em>Cenchrus ciliaris</em>), and bamboo (<em>Bambusa spp</em>.) could be the nature-based solutions for mitigating the impact of climate change due to their soil binding capacity and carbon sequestration potential. Moreover, this review indicates the potential of fast-growing trees (<em>Melia dubia</em>) under the agroforestry system in enhancing carbon sequestration by &gt;100 % over sole cultivation. These results demonstrate that IWM is a sustainable solution to mitigate the adverse effects of climate change on dryland farming systems and improve rural livelihoods. Further, the study suggests that IWM practices helps to achieve sustainable development goals (SDGs) such as zero hunger, no poverty, and climate action etc., particularly in the face of climate change in water-scarce regions.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 159-177"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143816974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydrochemical characteristics, water quality and diatom assemblage in Dordi River, Nepal","authors":"Punam Phuyal ,&nbsp;Shraddha Ranabhat ,&nbsp;Sanjal Khatri ,&nbsp;Nabin Lamichhane ,&nbsp;Ramesh Raj Pant ,&nbsp;Lal Bahadur Thapa ,&nbsp;Ram Kailash Prasad Yadav","doi":"10.1016/j.wsee.2024.12.002","DOIUrl":"10.1016/j.wsee.2024.12.002","url":null,"abstract":"<div><div>Understanding hydrochemistry and diatom assemblage is important for assessing the health of aquatic ecosystems. This study has analyzed the water quality and diatom communities in the Dordi River, which is one of the major tributaries of the Marsyangdi River in Nepal. The primary research question being addressed in the study was what is the state of water quality parameters of Dordi River and how do they relate to the distribution and composition of diatoms. The water quality parameters of the river like temperature, pH, electric conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), turbidity, and total alkalinity (TA) were measured <em>in-situ</em>, whereas concentrations of major ions (Ca²⁺, Mg²⁺, K⁺, Na⁺, NH₄⁺, HCO₃^–, Cl^–, SO₄^2–, NO₃^–, and PO₄^3–), biological oxygen demand (BOD) and chemical oxygen demand (COD) were analyzed in the laboratory by collecting water samples from different parts of the river. Piper plot, Gibbs plot, Mixing plots, redundancy analysis, and principal component analysis were applied for evaluating the spatial variation of anions and cations in water. The results showed alkaline water following the pattern: Ca²⁺&gt;Mg²⁺&gt;Na⁺&gt;K⁺&gt;NH₄⁺ for cation and HCO₃^–&gt;Cl^–&gt;SO₄^2–&gt;PO₄^3–&gt;NO₃^– for anion with calcium-bicarbonate dominant lithology in the river. Overall, the results highlight that the drinking and irrigation water qualities of the river were found to be excellent. Additionally, among 75 diatom species observed in the samples, the Bacillariophyceae was the dominant class covering 92% of the species. The results indicated that the diatom species richness declined as elevation increased. The distribution of diatoms was also influenced by the land use types near the water sampling points, tributaries and the main river. Overall, the physico-chemical quality of water showed significant influence on diatom species composition. The findings of this study could be useful for understanding hydrochemistry and association of water quality and diatoms in river basins of the Himalaya.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 23-35"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143158894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Closed depressions and karst landforms in Rif Alpine Cordillera (Northern Morocco): The case of dolomitic Jbel Dersa Massif","authors":"Samira Kaddouri ,&nbsp;Younes EL Kharim ,&nbsp;Kamal Agharroud ,&nbsp;Ali Bounab ,&nbsp;Youssef El Miloudi ,&nbsp;Reda Sahrane ,&nbsp;Ahmed Taoufik Ouahabi","doi":"10.1016/j.wsee.2025.08.002","DOIUrl":"10.1016/j.wsee.2025.08.002","url":null,"abstract":"<div><div>The morphology, distribution, and structural control of karst closed depressions in a dolomitic karst landscape are the focus of this study. The study area is the Jbel Dersa Massif (JDM), part of the “Dorsale Calcaire” (DC) unit within the Rif Mountain range in northern Morocco. A combined analysis of geomorphological mapping and structural studies reveal that the Pliocene dismantling phase smoothed the crests of the original imbricate thrust fronts, characteristic feature of the DC unit’s structure. The flattening of the massif’s summit facilitated the dissolution of the rock surface. In addition to the massif’s ruiniform landscape, the observed karstic features include fracture lapies, closed karstic depressions at the summit, and travertine deposits along the structural contacts with the bordering non-karstic units. The 26 identified closed depressions are dissolution dolines. Morphometric analysis indicates that these dolines are primarily located in the endorheic and axial zones of the massif and are preferentially aligned along tectonic faults. Structural, geomorphological, and ERT profile analyses of two sinkholes confirm the structural control over their development and demonstrate that seepage occurs through the fractured material along fault planes. This study highlights the scientific, environmental, and water-supply significance of the JDM. Its karst depressions, serving as primary infiltration zones, play a crucial role in local hydrogeology, providing water sources for several settlements that rely on the massif’s springs.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 398-412"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence applications in hydrological studies and ecological restoration of watersheds: A systematic review","authors":"Fernando Morante-Carballo ,&nbsp;Mirka Arcentales-Rosado ,&nbsp;Jhon Caicedo-Potosí ,&nbsp;Paúl Carrión-Mero","doi":"10.1016/j.wsee.2025.05.004","DOIUrl":"10.1016/j.wsee.2025.05.004","url":null,"abstract":"<div><div>Water resources management is fundamental to the sustainability of river basins. Water quality is affected by pollution caused by human activities. In this context, the restoration of degraded watersheds helps soil recovery, sustainable water management, reforestation, biodiversity conservation and mitigation of human impacts. Artificial intelligence (AI) innovates data management and analysis processes by optimising decision-making and data analysis in hydrological studies and ecological restoration. This research aims to analyse scientific information related to the integration of AI in studies on hydrogeology and ecological restoration of watersheds by analysing scientific databases for knowledge of the intellectual structure, lines and trends of research. The methodology includes three phases: i) search criteria and data processing (Scopus-Web of Science); ii) analysis of the intellectual and conceptual structure; and iii) application of the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) method. The results indicate that there is a total of 171 records, with a 4.49% growth in scientific production in the last four years, focusing on artificial neural networks (10.53%), artificial intelligence (3.51%), genetic algorithms (1.17%) and machine learning (1.17%). This increase is due to the climatic variation generated in recent years, driven by anthropogenic pressures, especially in the agricultural sector due to the high demand for fertiliser and pesticide pollution. This problem has prompted the search for more far-reaching environmental management technologies, making it a potential niche for study. China (72.51%) and the United States (25.73%) are the most outstanding contributors to production in this area. On the other hand, there is less research in this area in developing countries such as South Africa (2.92%), Colombia (1.17%), and Argentina (0.58%), among others. This analysis identifies opportunities and challenges in applying AI for water resource optimisation and water quality prediction, providing an innovative conceptual framework for sustainable watershed management.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 230-248"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144105700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of vegetation-wetland-soil ecological water retention capacity in the source region of the Yangtze and Yellow rivers (SRYY)","authors":"Zhiyi Li ,&nbsp;Lingyan Dong ,&nbsp;Liang Xu ,&nbsp;Li Wang ,&nbsp;Zhe Yuan","doi":"10.1016/j.wsee.2025.05.005","DOIUrl":"10.1016/j.wsee.2025.05.005","url":null,"abstract":"<div><div>Ecological Regulation and Storage (ERS), a crucial natural regulatory mechanism in river basins, is vital in assessing watershed resilience and guiding water resource management. This study establishes a novel tripartite framework (vegetation-wetland-soil) to quantify ERS dynamics in the ecologically fragile Source Region of the Yangtze and Yellow Rivers (SRYY). Integrating multi-source hydrological data (2000–2020) with improved modeling approaches, including a modified SCS-CN method incorporating organic matter dynamics and NDVI-driven vegetation modules, we reveal three key insights: (1) Total ERS exhibited a distinct V-shaped trajectory during 2000–2020, underscoring the system’s resilience and recovery potential; (2) Wetland regulation dominated temporal fluctuations, followed by soil regulation, while canopy interception and litter retention functioned as stabilizing components; (3) Vegetation regulation displayed pronounced seasonal variability, with a robust positive correlation between canopy interception and litter retention (r = 0.94, p = 0.019), revealing synergistic hydrological coordination within the vegetation layer.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 260-273"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144184738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying investment priority areas for soil conservation in the Winike watershed, upper Omo Gibe Basin of Ethiopia","authors":"Abreham Berta Aneseyee ,&nbsp;Eyasu Elias ,&nbsp;Teshome Sorromessa","doi":"10.1016/j.wsee.2025.05.008","DOIUrl":"10.1016/j.wsee.2025.05.008","url":null,"abstract":"<div><div>Sustainable land management is necessary for soil erosion control, vegetation recovery, and land restoration. This study was conducted to identify the soil erosion susceptibility areas in the Winike watershed, upper Omo Gibe Basin of Ethiopia. Analytic Hierarchy Process (AHP) and InVEST modeling combined with GIS were used to generate primary data on soil erosion severity. Land use types, slope, elevation, NDVI, rainfall, drainage density, and soil types were important variables analyzed for soil erosion rate determination. The result shows a significant variation in soil erosion vulnerability among sub-watersheds ranging from low to very high vulnerability. The watershed’s very highly vulnerable eastern part accounts for 108.23 km² (9.91 %) due to lacks vegetation cover, while the less vulnerable to the western part covers 179.66 km² (16.46 %). Analysis of the Geo-environmental parameters shows that rainfall (26 %) is the most significant influencing factor, followed by vegetation cover (i.e., land use types), explaining about 23 % of the erosion severity. Comparing soil erosion vulnerability using the AHP and InVEST SDR models was 14.01 % and 16 %, respectively, suggesting insignificant variation between the erosion vulnerability analysis models. The study emphasizes the usefulness of erosion vulnerability modeling for identifying investment priority areas based on soil erosion status for soil conservation intervention, offering a range of decision-making options for land management.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 327-337"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144670219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Five-year microbial and chemical assessment of the Blue Marsh Watershed in Reading, Pennsylvania","authors":"Jill M. Felker,&nbsp;Zachary T. Weagly,&nbsp;Tami H. Mysliwiec","doi":"10.1016/j.wsee.2025.03.003","DOIUrl":"10.1016/j.wsee.2025.03.003","url":null,"abstract":"<div><div>Recreational, agricultural, and industrial utilizations of areas surrounding waterways provide opportunities for collecting chemical and pollutant runoff, which influence the chemical makeup of the waterways and connecting watersheds. Human activities within watersheds can result in conditions that enable pathogenic microorganisms to thrive and allow unique microbial communities to emerge. The study area consisted of three locations at the Blue.</div><div>Marsh Watershed in Reading, Pennsylvania, with different surrounding land use and anthropogenic activities. The study areas were monitored monthly during the five-year project to assess seasonal variations in chemical levels and microbial count changes.</div><div>Chemical testing included inorganic nitrates, inorganic phosphates, and dissolved oxygen. Additional microbial testing included monthly counts for <em>Escherichia coli</em> and <em>Enterococcus</em> spp. to assess potential pathogenic microbial populations. On most occasions, chemical analyses found nitrate and phosphate concentrations above natural environmental levels.</div><div>During the five years, <em>Escherichia coli</em> and <em>Enterococcus</em> spp. concentrations were above the EPA recreational water recommendations 52% and 83% of the time, respectively. These results suggest that recreational, agricultural, and industrial utilization of surrounding waterways may influence chemical and microbial characteristics, including pathogenic microorganisms in the Blue Marsh Watershed.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 119-130"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143768638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating artificial intelligence for sustainable waste management: Insights from machine learning and deep learning","authors":"Son V.T. Dao,&nbsp;Tuan M. Le,&nbsp;Hieu M. Tran,&nbsp;Hung V. Pham,&nbsp;Minh T. Vu,&nbsp;Tuan Chu","doi":"10.1016/j.wsee.2025.07.001","DOIUrl":"10.1016/j.wsee.2025.07.001","url":null,"abstract":"<div><div>As global waste production grows, sustainable waste management (WM) has become an issue for modern societies. This paper explores the integration of Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), to improve waste management (WM) systems by enhancing automation, classification accuracy, operational efficiency, and real-time decision-making. Current trends and potential future directions are identified with bibliometric and scientometric analysis, which assess methodologies and data in the field. By automating processes such as waste classification, sorting, and transportation, AI-driven models have the potential to optimize operational efficiency and reduce environmental impact. A comprehensive review of recent AI research in WM is presented, with a focus on their effectiveness, scalability, and limitations. Moreover, in the proposed framework, the data augmentation approach has been utilized to improve the model’s performance by increasing the amount of samples. Furthermore, the MobileNetV3 DL model is employed for feature extraction. Besides, the<!--> <!-->feature selection method − Harris Hawk Optimization (HHO) is also utilized to choose the best subset of features and reduce the irrelevant features. Then these selected features are fed into Machine Learning algorithms such as Decision Tree (DT), Logistic Regression (LR), and Random Forest (RF). In summary, this review highlights key case studies and research insights, offering a roadmap for future developments in AI-driven WM solutions.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 353-382"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144702707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Wetland bird utilisation of ephemerally flooded rice paddies in late winter snowmelt season in central Japan","authors":"Masumi Hisano ,&nbsp;Shota Deguchi ,&nbsp;Keinosuke Sannoh ,&nbsp;Ken Motomura ,&nbsp;Da-Li Lin","doi":"10.1016/j.wsee.2025.04.002","DOIUrl":"10.1016/j.wsee.2025.04.002","url":null,"abstract":"<div><div>This study highlights the importance of rice paddies in snow-rich regions of central Japan as habitat for wetland bird species during snow-melting late winter season. During the study period, we recorded seven wetland species, including waders, egrets, and waterfowls. The abundance and richness of these birds were not significantly associated with the patch size of rice paddies. However, bird abundance presented a marginally positive association with the coverage of open water bodies within the landscape, while species richness showed a marginal relationship with the distance to the nearest water body. Our findings suggest that snowmelt-created wetlands may provide functions as critical stopover sites for migratory birds along the East Asian-Australian Flyway, and that enhancing water features in agricultural landscapes may yield greater conservation benefits than simply modifying the patch size of agricultural wetlands.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 178-186"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143865135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recent research trends in mangrove management systems (2014–2023) and predictions of future research; A bibliometric analysis","authors":"Muh Ainun Beddu ,&nbsp;Rijal Idrus ,&nbsp;Farid Samawi ,&nbsp;Aidil Zulhaq Paradiman ,&nbsp;Islamuddin Jafar","doi":"10.1016/j.wsee.2025.04.003","DOIUrl":"10.1016/j.wsee.2025.04.003","url":null,"abstract":"<div><div>This review of the scientific literature on mangrove management systems using bibliometric methods aimed to identify research trends, key topics, and collaboration between researchers. Data were collected from a one-time search of the Scopus database over the last ten-year period (2014– 2023). Bibliometric analysis was conducted using Microsoft Excel, OpenRefine, RStudio, Tableau, and VOSviewer to visualize keyword networks, publication trends, and research collaboration. The study showed a significant increase in publications related to mangrove management systems in the last decade. The most frequently discussed topics included global analysis, restoration, climate mitigation, ecosystem services, and blue carbon. The collaboration network showed extensive international cooperation, especially between researchers from Australia and Southeast Asia. The analysis revealed gaps in the coverage of key research areas in mangrove management systems, particularly in addressing long-term sustainability and effective stakeholder collaboration, such as the need for a multidisciplinary and collaborative approach involving various stakeholders, including local communities, governments, scientists, and sustainable management approaches.</div></div>","PeriodicalId":101280,"journal":{"name":"Watershed Ecology and the Environment","volume":"7 ","pages":"Pages 187-198"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}