Natural Hazards Research最新文献

{"title":"Flood risk assessment of the Kosi River Basin in North Bihar using Synthetic Aperture Radar (SAR) data and AHP approach","authors":"Sourav Kumar ,&nbsp;Bikash Ranjan Parida ,&nbsp;K.K. Basheer Ahammed","doi":"10.1016/j.nhres.2025.02.002","DOIUrl":"10.1016/j.nhres.2025.02.002","url":null,"abstract":"<div><div>Flood is a recurrent destructive natural calamity in the Kosi River Basin (KRB) in north Bihar in India. Geospatial modelling of these recurrent floods becomes imperative for effective disaster management. The KRB is renowned for its high vulnerability to flooding due to its sudden bending and heavy rainfall in the upper catchment of the basin located in Nepal. This study presents a comprehensive assessment of flood risk over the KRB, by utilizing the Analytical Hierarchy Process approach and Synthetic Aperture Radar data. The risk map was generated by considering multivariate set of factors including physical (elevation, slope), geological and hydrological variables (flood frequency, rainfall intensity, drainage network). Flood inundation and rainfall intensity are calculated over six years (2015–2020) to understand the dynamic nature of floods. The results of this analysis provide detailed flood inundation and risk maps, highlighting areas at varying levels of vulnerability and risk. Higher flood inundation was seen in downstream areas, which accounted for 6526.3 ​km² (33%) of geographical areas. Flood inundation was highest in 2020 and 2019 accounting for 27.93% and 20.72% of areas, respectively, whereas the lowest flood inundation was seen in 2015 (4.14%). Areas under higher flood risk were 1383.7 ​km² (7%), whereas 3820.9 ​km² (19.4%) were at lower flood risk. Extremely flat downstream areas near riverbanks were at higher risk (7% of KRB) that has correspondence with higher flood frequency. The spatially explicit flood risk zone information can be invaluable for disaster preparedness and policymakers. Furthermore, flood risk assessment can reinforce resilience to improve land use planning, insurance planning, flood-prone area management, and raising public awareness of potential flood risks.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 3","pages":"Pages 618-632"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128448","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":"Emergent groups and the informal digital emergent response to hurricane florence in the United States","authors":"Andrew S. Pyle ,&nbsp;Hillary Smith ,&nbsp;Ryan P. Fuller","doi":"10.1016/j.nhres.2025.02.003","DOIUrl":"10.1016/j.nhres.2025.02.003","url":null,"abstract":"<div><div>Our study presents a thematic analysis of 1582 posts from five digital emergent Facebook groups during Hurricane Florence, affecting North and South Carolina in the United States in 2018. We pose four research questions related to the formation and functioning of digital emergent groups during a disaster. Specifically, we examined how groups contributed to response efforts; messages developed across stages of the disaster; grassroots groups' organized disaster response; and how proximity affected group functioning. Participants contributed to disaster response by sharing and seeking information and aid. Groups coordinated logistics; offered affirmation; and provided commentary and humor. Group members supported the formal response through information sharing. Moreover, group members' proximity to the disaster and group structures designed to moderate groups were influential in the groups’ goal attainment. We see an opportunity for emergency managers to coordinate with digital emergent groups through trusted sources such as nonprofits active in disaster response. Implications for theory and practice are discussed.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 3","pages":"Pages 633-643"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128450","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":"Machine learning reveals lithology and soil as critical parameters in landslide susceptibility for Petrópolis (Rio de Janeiro State, Brazil)","authors":"Enner Alcântara ,&nbsp;Cheila Flávia Baião ,&nbsp;Yasmim Carvalho Guimarães ,&nbsp;José Roberto Mantovani ,&nbsp;Jose Antonio Marengo","doi":"10.1016/j.nhres.2025.01.008","DOIUrl":"10.1016/j.nhres.2025.01.008","url":null,"abstract":"<div><div>Petrópolis, located in the mountainous region of Rio de Janeiro, Brazil, is frequently impacted by severe landslides, exacerbated by intense rainfall, steep topography, and unregulated urban growth. This study employs machine learning to assess and predict landslide susceptibility, integrating geological, hydrological, and anthropogenic factors. Five models—Random Forest, CatBoost, Support Vector Machine, Artificial Artificial Neural Network (ANN), and XGBoost—were evaluated, with CatBoost emerging as the optimal model (F1-score: 0.82; AUC-ROC: 0.88). Variable importance analysis revealed soil type and erodibility as critical soil parameters influencing susceptibility, alongside lithology, underscoring the significance of geological over purely topographic factors. These findings emphasize the utility of machine learning for landslide modeling, providing scalable methodologies applicable to similar geospatial risk assessments worldwide. Beyond local applications, this work offers actionable insights for urban planning and disaster risk management in mountainous urban regions.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 3","pages":"Pages 539-553"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128514","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":"Modeling the Atami debris flow using the depth-integrated particle method and GIS: Flow characteristics and future risk assessment","authors":"F.H. Chowdhury,&nbsp;T. Matsushima","doi":"10.1016/j.nhres.2025.03.008","DOIUrl":"10.1016/j.nhres.2025.03.008","url":null,"abstract":"<div><div>The Depth-Integrated Particle Method (DIPM) is a numerical approach for simulating sediment disasters, such as debris flows and mudflows. This study applies DIPM to the 2021 Atami debris flow in Shizuoka Prefecture, Japan, triggered by heavy rainfall and slope collapse. DIPM models the moving mass as computational particles, represented as soil columns, with pairwise interactions between particles derived from the hydraulic gradient of the soil columns. A numerical test confirmed the reliability of the hydraulic pressure gradient model. Digital Elevation Models (DEMs) were created from pre-disaster grid data at 0.5-m resolution, processed into 5-m and 1-m meshes. Sensitivity analyses identified optimal parameters (Manning's coefficient, <span><math><mrow><mi>n</mi></mrow></math></span> ​= ​0.1; critical deposition angle, <span><math><mrow><msub><mi>i</mi><mrow><mi>c</mi><mi>r</mi></mrow></msub></mrow></math></span> ​= ​8.5°), closely matching observed flow velocities and average sediment deposition height (1.65 ​m). Cross-sectional comparisons at the existing check dam validated the model, demonstrating its applicability for hazard assessment. DIPM also evaluated the Izusan check dam, confirming its capacity of 10,800 ​m³ aligns with simulation predictions, supporting its role in debris flow mitigation. These findings highlight versatility of DIPM for debris flow modeling and risk evaluation.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 3","pages":"Pages 705-718"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128402","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":"Comprehensive flood vulnerability analysis and mapping for the Awash River Basin, Ethiopia","authors":"Abebe M. Legass ,&nbsp;Tena Alamirew ,&nbsp;Solomon G. Gebrehiwot ,&nbsp;Mark V. Bernhofen","doi":"10.1016/j.nhres.2025.01.012","DOIUrl":"10.1016/j.nhres.2025.01.012","url":null,"abstract":"<div><div>The Awash River Basin is increasingly susceptible to significant flood risks driven by a complex interplay of hydrometeorological and socio-environmental factors, which have detrimental effects on local populations and infrastructure. Despite some advancements in flood risk assessment, existing mapping methodologies, including ArcGIS and HEC-RAS, often fail to account for critical dynamics within the river system, leading to gaps in flood hazard assessments that overlook vital regions and create discrepancies in estimates of vulnerable populations during recent flooding events. This study employs comprehensive mapping techniques, utilizing global datasets, HEC-RAS, GIS, and satellite data to characterize various flooding types throughout the basin. Among the methodologies analyzed, the Fathom and Aqueduct models demonstrated superior accuracy in estimating flood impacts, while the CAMA-UNEP and JRC models revealed significant limitations, especially in capturing flood risks in the upper reaches of the basin. By enhancing real-time monitoring and vulnerability assessments, this research aims to improve resource allocation and intervention strategies, ultimately safeguarding at-risk communities and mitigating socio-economic repercussions from flooding events in the Awash River Basin. The findings support the recommendation of the Fathom and ensemble models for conservative flood mapping, while the Aqueduct model is recognized as a valuable alternative for accurate estimations.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 3","pages":"Pages 596-608"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128443","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":"Potential laharic risks associated with the Millennium Eruption products of Tianchi volcano, NE China","authors":"Zhengquan Chen ,&nbsp;Haiquan Wei ,&nbsp;Yuan Wan ,&nbsp;Bo Zhao ,&nbsp;Xiaoxuan Li","doi":"10.1016/j.nhres.2025.01.004","DOIUrl":"10.1016/j.nhres.2025.01.004","url":null,"abstract":"<div><div>Tianchi volcano has experienced continuous eruptions, including the Millennium Eruption (ME) event that produced a volcanic explosivity index of 6–7 in approximately 946 CE, which is among the most hazardous eruptions in human history. We take notice that the voluminous ME pyroclastics provided highly erodible sediments. Post eruption and secondary lahars took place frequently and could travelled up to approximately 500 ​km along the three main rivers that sourced from the Tianchi volcano. Thus, the post eruption or secondary lahar threaten people in this area. To assess the secondary lahar risk in the specified area, a comprehensive analysis is required focusing on several aspects: the triggering mechanisms, interaction between ME pyroclastic materials and the local topography, and the population that could be affected by lahars. This study investigates and reviews the distributions and field data (thickness, structure, and grain size) of ME pyroclastics from different origins (fallout, PDCs, and lahar). The frequent re-depositioin of ME pyroclastic materials, particularly in the form of debris flow, poses significant hazards after ME. However, the mobilization of ME pyroclastic materials and water supply are various in catchments. Secondary lahar hazards can be triggered by various factors, including extreme runoff (flood), failure of temporary block lake, and disturbances in caldera lake. The ME pyroclastic deposits changed topography, which reflecting by drainage density in different drainage basins, and consequently have various responses to rainfall and runoff. Thus, we distinguish different potential mechanisms of secondary lahars in each of the drainage basins. Finally, residential sites scatter on and near to the post ME lahar deposits were plotted on a geological map, the number of population are estimated based on demographic census data, revealing that more than 462,000 residents are threatened by secondary lahar hazards. According to various hazard triggers and road network system, communities in the four drainage basins face complications regarding evacuation during the occurrence of a lahar, especially those located on the border.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 3","pages":"Pages 495-508"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128511","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":"Early warning systems in climate risk management: Roles and implementations in eradicating barriers and overcoming challenges","authors":"Md Mujahidul Islam ,&nbsp;Mehedi Hasan ,&nbsp;Md Saju Mia ,&nbsp;Abdullah Al Masud ,&nbsp;Abu Reza Md Towfiqul Islam","doi":"10.1016/j.nhres.2025.01.007","DOIUrl":"10.1016/j.nhres.2025.01.007","url":null,"abstract":"<div><div>Early Warning Systems (EWS) are essential tools for alleviating the effects of natural hazards, particularly floods, cyclones, and droughts, by giving early warnings and actionable information. Currently, there is a lack of common standards, detailed guidelines, and a clear understanding of how EWS operates in challenging environments, making it difficult to evaluate their efficacy. However, various human and social factors often compromise their efficacy. Barriers resulting from human behavior, social systems, and cultural settings could hinder the dissemination, comprehension, and response to early warnings. To assist decision-makers in identifying optimal risk mitigation measures and EWS mechanisms, the current study intends to determine their roles and overcome implementation barriers and challenges associated with EWS. The current study primarily considered 669 articles, selecting 37 relevant ones through 4 steps: identification, screening, eligibility, and inclusion, based on the PRISMA framework for data extraction and review. The study findings include several human and social factors as barriers to EWS such as socio-cultural constraints, political instabilities, communication challenges, insufficient technology, inadequate finance, lack of community involvement, and so on. The review shows how community-based EWSs provide power-driven warnings to societies in disaster-prone vulnerable regions, primarily floods, droughts, and tropical cyclones. This paper discusses Bangladesh's EWS success story, elucidating climate risk management techniques and their roles in floods, cyclones, and droughts. The most significant gap is the lack of suitable equipment for monitoring hazards, making predictions, and spreading EWS. Overall, the outcomes of this study have profound implications across social, environmental, and financial sectors, which strengthen disaster risk reduction initiatives, influence policy and technical advancements, and support local, national, and global resilience. These insights derived from this research will eventually enhance community safety, preparedness, and sustainability.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 3","pages":"Pages 523-538"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128513","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":"Escalating risks and impacts of rainfall-induced geohazards","authors":"Saier Wu ,&nbsp;Chong Xu ,&nbsp;Junxue Ma ,&nbsp;Huiran Gao","doi":"10.1016/j.nhres.2025.03.003","DOIUrl":"10.1016/j.nhres.2025.03.003","url":null,"abstract":"<div><div>The increasing impact of climate change has significantly intensified the frequency and severity of rainfall-induced geohazards, posing substantial threats to public safety and economic stability. Between 2019 and 2023, China recorded an annual average of 84 fatalities or missing persons due to such hazards, while the global average reached 494. Data from 2024 indicate a substantial rise, with 273 fatalities in China and 1570 globally. Increasingly intense and frequent precipitation events have been identified as key drivers of the rising frequency and severity of these geohazards. This study provides a retrospective analysis of recent rainfall-induced geohazard events and their characteristics, based on national disaster records. Key challenges in current risk management frameworks are identified, and integrated risk mitigation strategies are proposed to enhance societal resilience against both present and emerging threats.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 3","pages":"Pages 447-454"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128451","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":"Evaluating CMIP6 precipitation simulations across different rainfall regimes in the Amhara Region, Ethiopia","authors":"Tilahun Wubu Tiku ,&nbsp;Gashaw Bimrew Tarekegn ,&nbsp;Dejene Sahlu ,&nbsp;Gezahegn Bekele Tashebo ,&nbsp;Fekadie Bazie Enyew ,&nbsp;Yakob Umer ,&nbsp;Sisay E. Debele","doi":"10.1016/j.nhres.2025.03.002","DOIUrl":"10.1016/j.nhres.2025.03.002","url":null,"abstract":"<div><div>Precipitation patterns play a crucial role in sustaining rainfed agriculture, particularly in regions like Ethiopia, where millions depend on it for their livelihoods. Understanding the ability of climate models to simulate precipitation accurately is essential for predicting the potential impacts of climate change, especially in regions with complex topography like Ethiopia. This study assesses the performance of 16 CMIP6 climate models in simulating precipitation patterns across different rainfall regimes in the Amhara region. By comparing model outputs with observed data, the research aims to identify which models best capture the seasonal and annual variability in precipitation, thereby informing climate adaptation strategies.</div><div>To conduct the analysis, observational data from the Enhanced National Climate Services and Climate Hazard Infrared Precipitation with Stations datasets were utilized. The study focused on evaluating the models' performance over the period 1985–2014 using statistical metrics such as the coefficient of determination (R²), root mean square error (RMSE), mean bias (MB), and Student's t-test. In the Western Amhara region, the models were further assessed with Taylor Skill Score (TSS), Inter-annual Variability Score (IVS), and Comprehensive Rating Method (CRM). The top-performing models for simulating the annual rainfall cycle in this region were GFDL-ESM4 (CRM: 0.88), EC-Earth3-Veg (CRM: 0.85), and CESM2 (CRM: 0.82). Other notable models included MRI-ESM2.0, MPI-ESM1-2-HR, and IPSL-CM6A-LR. In the Eastern Amhara region, which follows a bi-modal rainfall pattern, EC-Earth3-Veg (CRM: 0.85, R: 0.83, RMSE: 52.4 ​mm/month) showed the best performance, followed by MRI-ESM2.0 (CRM: 0.76, R: 0.76, RMSE: 55.6 ​mm/month) and CESM2 (CRM: 0.82, R: 0.88, RMSE: 65.46 ​mm/month). GFDL-ESM4 also demonstrated strong performance (CRM: 0.88, R: 0.77, RMSE: 55.6 ​mm/month). CMCC-ESM2, although lower-ranked in Western Amhara (CRM: ∼0.41), performed better in the Eastern region. However, most models exhibited a dry bias and substantial inter-model variability, particularly in simulating rainfall patterns in highland areas. Only 31 ​% and 44 ​% of models successfully captured the seasonality of rainfall in the Western and Eastern Amhara regions, respectively. Even the top models showed significant discrepancies compared to observed rainfall, indicating ongoing challenges in model accuracy. These findings provide valuable insights for developing targeted climate adaptation strategies in the Amhara region and highlight the need for improving climate models to better assess future climate change impacts in Ethiopia.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 3","pages":"Pages 689-704"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128445","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":"Development of rainfall threshold equation and bayesian probabilistic analysis for landslide prediction: A case study of Shimla, Northwestern Himalaya, India","authors":"Jugraj Singh ,&nbsp;Mahesh Thakur ,&nbsp;Raj Kiran Dhiman ,&nbsp;Vishwa B.S. Chandel ,&nbsp;Naval Kishore ,&nbsp;Akshay Raj Manocha","doi":"10.1016/j.nhres.2024.12.004","DOIUrl":"10.1016/j.nhres.2024.12.004","url":null,"abstract":"<div><div>Landslides are the most dangerous and recurring disaster in mountainous regions. The majority of landslides in the Himalayas are triggered during the monsoon season as oversaturated slopes get destabilized by incessant rainfall. While numerous global efforts have explored the relationship between landslides and rainfall, the specific rainfall thresholds for landslide occurrence in Himachal Pradesh have not been extensively studied. This research aims to develop an early warning system based on rainfall thresholds for Shimla, Himachal Pradesh, which is the state capital and a major tourist destination in India. The Rainfall Intensity-Duration (ID) threshold for landslides is developed for the Shimla area using the past 31 years (1990–2020) landslide data and daily rainfall data, using differential evolution optimization method. The threshold equation (I ​= ​7.20∗D^−0.26) was derived to define the conditions under which landslides are most likely to occur. Bayesian probability analysis was applied to assess the likelihood of landslides under varying rainfall intensities and durations. The results show an increase in probability from 0.06 for 1 day of rainfall duration to 1 for 10 day of rainfall duration. The influence of antecedent rainfall on landslide occurrence is analyzed using cumulative rainfall data for periods of 3, 7, 10, 15, 20, and 30 days prior to the landslide. The results indicate that 110 ​mm of antecedent rainfall over 30 days is sufficient to trigger landslides in the study area. These findings provide a framework for early warning systems and risk management strategies in Shimla, Himachal Pradesh.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"5 3","pages":"Pages 455-467"},"PeriodicalIF":0.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145128452","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}