Groundwater for Sustainable Development最新文献

{"title":"Application of machine learning and fuzzy AHP for identification of suitable groundwater potential zones using field based hydrogeophysical and soil hydraulic factors in a complex hydrogeological terrain","authors":"","doi":"10.1016/j.gsd.2024.101329","DOIUrl":"10.1016/j.gsd.2024.101329","url":null,"abstract":"<div><p>The eastern section of West Bengal grapples with limited surface water availability in its hard rock terrain, compounded by a semi-arid climate, variable rainfall, and a plateau topography, prompting communities to adapt groundwater water-use practices, leading to unsustainable extraction and misuse. Thus, the novel objective of the present research was to produce groundwater potential maps by comparing machine learning techniques with a Fuzzy MCDM model using specific field-based conditioning factors. In the first step, 285 wells were identified, of which 70 percent were used for training and 30 percent for the validation of the models. Secondly, field-based conditioning factors including, longitudinal conductance (SC), longitudinal resistance (ρl), transverse resistance (TR), coefficient of electrical anisotropy (λ), resistivity of formation (ρm), fracture porosity (φf), reflection coefficients (r), hydraulic conductivity (K), transmissivity(T<em>r</em>), bulk density, porosity, permeability, soil moisture content and water holding capacity were used to analyze the association between these conditioning factors and groundwater occurrences. In the following steps, the XGBoost, Random Forest, and Naïve Bayes models were executed using the training dataset, and factor weights were calculated using Fuzzy Analytical Hierarchy Process of Extent analysis method. To validate and compare the performance of four models, ROC curves, AUCs, MCAs, and correlation plots were used. In general, all four models were successful in evaluating the potential of groundwater occurrences. The predictive capability of the XGBoost techniques with the highest AUC values (0.79) and the highest correlation value (0.78) is superior to those of other machine learning and MCDM models. Geophysical survey revealed that transmissivity and hydraulic conductivity of the aquifer of the river basin range from 1.55 to 440.11 m/day and 10.15–2253 m²/day, indicating a moderate to good hydrodynamic potential. Planners and engineers can use such groundwater potential maps to manage water resources effectively.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142168417","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":"Identification of groundwater potential zones for sustainable groundwater resource management using an integrated approach in Sirkole watershed, Western Ethiopia","authors":"","doi":"10.1016/j.gsd.2024.101328","DOIUrl":"10.1016/j.gsd.2024.101328","url":null,"abstract":"<div><p>The increasing population in the Sirkole watershed has led to a higher demand for groundwater resources essential for socio-economic development. To ensure sustainable groundwater management, accurate quantitative assessments are necessary, which can be achieved by utilizing scientific principles and modern techniques. This article discusses the use of RS and GIS techniques to evaluate Groundwater Potential Zones in a section of the Sirkole watershed in Western Ethiopia. The study analyzed various spatial data layers involving drainage density, land use, lineaments, slope, lithology, rainfall, geomorphology, and soil type to understand the factors influencing groundwater occurrence and movement. The eight thematic layers were weighted according to their significance. Additionally, a hierarchical ranking was performed using a pairwise comparison matrix (PCM) within the analytic hierarchy process (AHP) to determine the final normalized weights of these layers. Lineaments were extracted using PCI Geomatica and Rockwork software, and their orientations were determined. The sub-basin was divided into five zones based on the resulting GWPZ map: very high, high, moderate, low, and very low. The watershed was divided into two categories: high to very high potential for 22.8% of the area and very low to low potential for 45.4% of it. Validation against existing pumping wells showed a prediction accuracy of 75.9%, affirming the reliability of the GIS and RS techniques have been utilized for the identification of potential zones in the research area. The findings of this study can be utilized for the sustainable development of groundwater resources by pinpointing areas with high groundwater potential.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142151948","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":"Integrating GEE and IWQI for sustainable irrigation: A geospatial water quality assessment","authors":"","doi":"10.1016/j.gsd.2024.101332","DOIUrl":"10.1016/j.gsd.2024.101332","url":null,"abstract":"<div><p>The surface and sub-surface water quality is one of the decisive parameters for sustainable agriculture and water resources management. Deteriorating water quality impacts the irrigation, crop production, and human health. Therefore, the present work made an attempt to identify the water suitability for irrigation using the contemporary approach i.e. Irrigation Water Quality Index (IWQI) and Zone mapping using GIS techniques, and demonstrated for case of Wadhwan, Gujarat India. Three indices i.e., NDVI, NDWI, and LSWI were mapped using Landsat satellite imagery, whereas, Watermask index was mapped using Sentinel II satellite imagery for the assessment of the availability of water in different forms. The IWQI has applied to categorize the water quality as severe, high, moderate, low, and no restriction. The IWQI in the study area ranges from 6.4 to 62.5. The overall the water quality of study area shows that the 13.64 % of the region in severe restriction range, 56.82% in high restriction range, and 29.54% in moderate restriction range, which is in alarming for farmers and policy makers. The GIS zoning map effectively visualized the spatial distribution of IWQI, helping decision-makers to identify severity zones. Furthermore, the Piper diagram analysis has been performed, which shows that the water quality of the study area falls under mixed Ca²⁺-Mg²⁺-Cl^-, mixed Ca²⁺-Na⁺-HCO₃^-, and Na-HCO₃ types. The results revealed that major areas are in moderate to severe restriction zones, lying under deteriorated water quality, and need immediate attention for improvement before use. The IWQI advances SDG 2 (Zero Hunger) by optimizing water quality for crop production and SDG 6 (Clean Water and Sanitation) by ensuring sustainable water resource management, while indirectly supporting SDG 15 (Life on Land) through improved soil health and land management practices.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142229393","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":"Nanotechnology advancements in groundwater remediation: A comprehensive analysis of current research and future prospects","authors":"","doi":"10.1016/j.gsd.2024.101330","DOIUrl":"10.1016/j.gsd.2024.101330","url":null,"abstract":"<div><p>Groundwater contamination is a critical environmental issue with vital health implications. This review evaluates the advancements in nanotechnology for groundwater remediation, highlighting major findings and their relevance to Sustainable Development Goals (SDGs). Key findings include the superior adsorption capabilities of multi-walled carbon nanotubes functionalized with various groups for removing heavy metals and aromatic pollutants, outperforming traditional sorbents. The review also discusses the potential of nanomaterials like zero-valent iron nanoparticles for effective contaminant degradation. Despite promising results in the studies, challenges such as the movement and dispersion of engineered nanomaterials in porous media and the need for innovative delivery methods are identified. Furthermore, this review explores the environmental and health risks associated with the use of nanomaterials, emphasizing the need for risk assessments to ensure safe application. The novel delivery methods assessed, such as the use of groundwater circulation wells and the combination of nanoremediation with other techniques like bioremediation, demonstrate potential to enhance remediation efficiency. The integration of nanotechnology in groundwater remediation directly contributes to Clean Water and Sanitation by providing innovative solutions for the purification of water resources. Advanced nanomaterials not only improve contaminant removal efficiency but also promote sustainable water management practices. Additionally, the environmental benefits align with Life on Land, as the reduction of hazardous substances in groundwater protects terrestrial ecosystems and promotes biodiversity conservation. This review study aims to enhance understanding and identify future opportunities for nanotechnology in groundwater remediation. By addressing current challenges and proposing innovative solutions, this review underscores the importance of interdisciplinary research and collaboration in advancing sustainable development.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142168319","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":"Spatio-temporal analysis of hydrometeorological variables for terrestrial and groundwater storage assessment","authors":"","doi":"10.1016/j.gsd.2024.101333","DOIUrl":"10.1016/j.gsd.2024.101333","url":null,"abstract":"<div><p>Groundwater is a vital resource supporting various sectors such as agriculture, industry, and drinking water supplies. Gravity Recovery and Climate Experiment (GRACE) and its follow-on (GRACE-FO) can accurately assess variations in terrestrial water storage (TWS) at a regional scale, exhibiting precise measurements of spatio-temporal variations. This study aims to integrate GRACE/GRACE-FO and hydrometeorological variables to understand groundwater storage trends in Pakistan from 2002 to 2023. Precipitation, soil moisture, temperature, potential evapotranspiration, snow water equivalent, and Normalized Difference Vegetation Index (NDVI) are examined to understand the fluctuations in groundwater storage (GWS). Google Earth Engine (GEE) has been used for data collection and pixel-based Sen's slope analysis. The analysis revealed a consistent decline in terrestrial and groundwater storage in Pakistan over the study period. The soil moisture levels and snow water equivalent have decreased, while the levels of NDVI and precipitation have increased. Between 2002 and 2010, the study area experienced variations in TWS, while after 2012, the region faced severe water scarcity as the TWS decreased to 36 cm over the past 22 years. Trend analysis indicates a significant decline in groundwater storage (GWS) in Punjab province's highly urbanized and irrigated areas, averaging −1.41 cm per year. In contrast, the northern and coastal regions of the study area are experiencing an upward trend in GWS. Additionally, ground validation has been performed, yielding an R² value of 0.31. These findings emphasize the urgent need for effective urbanization policies and informed groundwater management. Implementing water conservation strategies in agriculture is essential to tackle water scarcity throughout Pakistan.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142151947","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":"Exploring the adsorption of catechol and resorcinol onto Croton caudatus activated carbon: An integrated experimental and theoretical approach","authors":"","doi":"10.1016/j.gsd.2024.101325","DOIUrl":"10.1016/j.gsd.2024.101325","url":null,"abstract":"<div><p>The present work aimed to examine the process for adsorption of Catechol (CT) and Resorcinol (RS) onto activated carbon that was obtained from <em>Croton caudatus</em> biomass (CAB). Using a batch method, the maximum removal efficiencies of 99.23 % for CT and 98.68 % for RS was achieved at adsorbent dosage-0.2 g L⁻¹, reaction time-60 min; concentration-100 mgL⁻¹ CT and 80 mgL⁻¹ RS; and pH 6.0 CT and pH 4.0 RS, respectively. A maximum equilibrium adsorption of 56.05 mgg⁻¹ and 61.85 mgg⁻¹ was achieved at pH 6.0 and pH 4.0 for CT and RS. The adsorption behavior of both adsorbates on activated carbon were best described by the Langmuir model (correlation coefficients (R²) = 0.996 for CT and 0.995 for RS) and the pseudo-second order kinetic model. The values of ΔG, ΔS, and ΔH suggest that the adsorption process is spontaneous and endothermic. Additionally, the adsorption process is easily reversible, enabling the reuse of the adsorbate even after fifth cycle. Further, density functional theory (DFT) simulations demonstrated that the CT and RS adsorption onto the AC adsorbent is favorable. Among the oxygen functional groups analysed, the carboxyl group showed the greatest effect on the adsorption process, exhibiting the most negative adsorption energy at −44.869 (CT) and −45.082 kJmol^-1 (RS), respectively. Therefore, the activated carbon derived from CAB has significant potential for effectively removing phenolic contaminants from wastewater.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142122631","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":"Protection of groundwater resources from multi-hazards: An integration of risk assessment and watershed management","authors":"","doi":"10.1016/j.gsd.2024.101326","DOIUrl":"10.1016/j.gsd.2024.101326","url":null,"abstract":"<div><p>Mining areas are abundant in this basin and were allocated high values of <em>H</em> and low to high values of <em>V</em>, requesting implementation of groundwater monitoring and periodic inspection of mining sites, even more because groundwater contamination with iron could be clearly associated with the presence of mine-tailings. The improving groundwater resource protection depends on aligning contamination risk mapping with aquifer protection measures. However, existing methods often fail to align with aquifer protection goals, hindering practical implementation. The study demonstrated integrating vulnerability assessment, hazard evaluation, and groundwater protection initiatives using an L-Matrix approach. Testing this model in a well-documented watershed with multiple hazards to illustrates its applicability, providing a reference for similar scenarios. The risk was assessed through evaluation of aquifer vulnerability, using the DRASTIC method, coupled with the evaluation of a hazard potential considering industrial, livestock/agriculture and urban infrastructure sources in separate. The L-Matrix diagrams consisted of cartesian representations of V versus H, ranging from 0 to 1, segmented into four quadrants bounded by the cut-off lines V = 0.5 and H = 0.5. The quadrants were then linked to aquifer protection measures, with site inspection (high V and H), groundwater monitoring (low V and high H), land use planning (high V and low H), and tolerable expansion of hazardous activities (low V and H). The Paraopeba River basin was used as test site. Mining areas are abundant in this basin and were allocated high values of <em>H</em> and low to high values of <em>V</em>, requesting implementation of groundwater monitoring and periodic inspection of mining sites, even more because groundwater contamination with iron could be clearly associated with the presence of mine-tailings. In the results, it was observed that the DRASTIC vulnerability map of the aquifers has a mean vulnerability around the central value (V = 0.48 ± 0.08). Regarding the distribution of hazards, the average rounds to the value for to (H_industry = 0.41 ± 0.37, H_agriculture = 0.33 ± 0.09 and H_{infrastructure} = 0.27 ± 0.14). Thus, it is noted that for industrial activities, the risk of contamination could be moderate to high, while for agricultural and livestock activities, the risk lies between low and moderate contamination impact.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352801X24002492/pdfft?md5=71d259e68c918eefb47589891de5cd3b&pid=1-s2.0-S2352801X24002492-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142117487","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":"A generalized machine learning approach for cost-effective monitoring of irrigation suitability: A demonstration case in El Fahs aquifer (Tunisia)","authors":"","doi":"10.1016/j.gsd.2024.101324","DOIUrl":"10.1016/j.gsd.2024.101324","url":null,"abstract":"<div><p>This study develops and evaluates the performance of machine learning (ML) regression models, namely the Support Vector Regression (SVR), Random Forest (RF), k-Nearest Neighbors (kNN) and eXtreme Gradient Boosting (XgBoost), for estimating the Irrigation Water Quality Index (IWQI) based on groundwater samples collected from El Fahs aquifer in Tunisia. The groundwater data are used as predictors for training and testing the machine learning models. Results indicate that sodium concentration has the most influence on the IWQI estimations for all ML models. The best-performing algorithms are found to be the SVR and XgBoost. Different datasets are also collected from existing studies, and merged to generate a single dataset that is used to develop generalized machine learning models. Despite regional variations, the generalized models performed adequately when tested against the unseen data, particularly the data collected from El Fahs case site. This work highlights the potential of using ML models, together with established metrics, as screening tools for predicting and classifying the irrigation suitability of groundwater based on available literature, even when metrics are not universally applicable. The findings of this study can be used by the water authorities in data scarce environments as cost-effective monitoring tools to assess water suitability for irrigation purposes.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352801X24002479/pdfft?md5=f607bd0aa02da4ea05e044ade4f0ce94&pid=1-s2.0-S2352801X24002479-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137114","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":"Anisotropic effect of shear zone on groundwater potentiality in crystalline hard rock terrain","authors":"","doi":"10.1016/j.gsd.2024.101320","DOIUrl":"10.1016/j.gsd.2024.101320","url":null,"abstract":"<div><p>Assessment of potential groundwater recharge sites and sustainable water resource management in semi-arid crystalline rock terrain is a challenging task. Globally, analysis of remote sensing satellite imagery data for delineation of groundwater potential zones over sheared crystalline hard rock terrains has been fairly successful. But there is no existing study present at our disposal which discusses the factors controlling the inconsistent groundwater potentiality that exits along the shear zones. This study attempts to analyse the major geological factors controlling the irregular groundwater potentiality of shear zones within older crystalline rock terrain. Therefore, the study area selected for this analysis is the Purulia district of West Bengal, NE India, composed mostly of Precambrian metamorphic rocks i.e., quartzite, granite gneisses, porphyroclastic granite-gneiss, quartzo-feldspathic-granite-gneiss, mylonitic granites, quartz-biotite-granite gneiss, quartzites, carbonatites and phyllites. Satellite imagery study of IRS-P6 LISS IV standard FCC image reveals the presence of two bifurcating shear zones namely North Purulia Shear Zone (NPSZ) and South Purulia Shear Zone (SPSZ) over the study area. Careful analysis of rock structure, different lithotypes, soil thickness, electrical resistivity tomography data and water table data with an emphasis on high water table fluctuation, shows a strong spatial relation between the potentially good groundwater recharge zones and the branching/confluence sites of shear zones present in the study area. The study constructs an attempt to demonstrate the relationship between shear zone conjunctions and significant groundwater recharge sites in Precambrian crystalline fractured-rock aquifer system.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142050111","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":"Multi-contamination groundwater risk assessment based on integrated OSPRC framework considering receptor and consequence components","authors":"","doi":"10.1016/j.gsd.2024.101321","DOIUrl":"10.1016/j.gsd.2024.101321","url":null,"abstract":"<div><p>This study evaluates the risks associated with geogenic and anthropogenic contaminants in the Azarshahr aquifer situated in the Lake Urmia watershed in NW Iran, an area critically affected by both natural mineral deposits and intensive agricultural activities. This region, characterized by its significant geological diversity and extensive use of pesticides and fertilizers, presents a unique opportunity to study the interaction between natural and human-induced groundwater contamination. Employing the Origin-Source-Pathway-Receptors-Consequence (OSPRC) framework, the research focuses on the linkage between these contaminants and waterborne diseases, particularly examining the less-studied “Receptor” and “Consequence” components using the Groundwater Quality Index (GQI) and health risk indices. Our approach integrates vulnerability assessments through the DRASTIC and SPECTR methods, enhanced by Sugeno fuzzy logic, to produce a detailed risk map highlighting two critical zones: Risk Cell 1, impacted predominantly by agricultural contaminants including nitrate and chlorpyrifos, and Risk Cell 2, affected by geogenic contaminants such as arsenic, lead, nickel, and chromium. This comprehensive analysis not only maps out the source and migration pathways of these contaminants but also evaluates their impact on human health. The findings underscore a strong correlation between identified risks and health impacts, emphasizing the pressing need for targeted health interventions and improved management of water resources in the region. By advancing the application of the OSPRC framework, this research fills a vital gap in our understanding of aquifer contamination dynamics and sets a new standard for future groundwater risk assessments.</p></div>","PeriodicalId":37879,"journal":{"name":"Groundwater for Sustainable Development","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142130250","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}