Geosfera Indonesia最新文献

{"title":"Analysis of the Dynamics of Water Flow and Suspension Flow Discharge in Volcano Watershed with Settlement Land Use","authors":"L. Hadini, J. Sartohadi, M. Setiawan, D. Mardiatno, Nugroho Crhristanto","doi":"10.19184/geosi.v8i1.30921","DOIUrl":"https://doi.org/10.19184/geosi.v8i1.30921","url":null,"abstract":"Suspension flow into the upstream of volcano watershed is sensitive to land use. In Indonesia, a settlement is a form of land use in several volcanic landscapes. There is currently no detailed study on the suspension flow sediment from the settlement land use. The purpose of this study is to investigate the characteristics of the relationship between water and suspension flow discharge. The study was conducted through the measurements at a gully outlet that produced 747 suspension load data. For each rainfall event, suspension load measurements were made in the field, followed by laboratory analysis. Additionally, field surveys were used to determine the characteristics of settlement land use and the water flow into the gully system. According to the findings, the peak flow discharge corresponds to the peak suspension discharge, the peak flow discharge comes before the peak suspension discharge, and the peak flow discharge happens after the peak suspension discharge. The average time lag between initial rainfall events and suspension flow was 10.36 minutes, and the suspension peak content varied by an average of 2.22 gl-1. The grain size was also dominated by the clay fraction, averaging 67.86% on the ascending branch and 67.82% on the descending branch. \u0000Keywords: Erosion; Discharge; Settlements; Suspension; Watershed \u0000  \u0000Copyright (c) 2023 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44631613","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":"Species Distribution Modelling Using Bioclimatic Variables on Endangered Endemic Species (Bubalus depressicornis and Bubalus quarlesi)","authors":"S. Aldiansyah, Khalil Abdul Wahid","doi":"10.19184/geosi.v8i1.31862","DOIUrl":"https://doi.org/10.19184/geosi.v8i1.31862","url":null,"abstract":"Sulawesi Island is an island located in the Wallacea area. Most of the fauna on the island of Sulawesi is a transitional fauna from Australia and Asia. This study aims to model the potential distribution of the species Bubalus depressicornis and Bubalus quarlesi using famous models in the present and in the future as a result of climate change phenomena throughout the island of Sulawesi and beyond their natural habitat. The parameters used are bioclimatic variables and in-situ presence data. The method used is Maximum Entropy by comparing the GLM, SVM, and RF algorithms. The model is evaluated with reference to the values of AUC, COR, TSS, Deviance, and observation data. The RF model is quite good in modeling the distribution of B. depressicornis and B. quarlesi species with AUC values of 0.92 and 1, COR values of 0.59 and 0.84, TSS values of 0.87 and 1, and Deviance values of 0.37 and 0.08, respectively, while the results of data observations show values of 80% and 84%. B. depressicornis was most affected by bio14=0.665, while B. quarlesi was most affected by bio2=0.525, which means that this endemic species is suitable to live in a tropical climate with a warm and wet climate throughout the year, where the difference in temperature at night and during the day is very large. In the future, B. depressicornis and B. quarlesi are estimated to be compatible in an area of 143,281.78 km2 (81%) and 136,892.89 km2 (77%) of the Sulawesi. \u0000Keywords : Species Distribution Model; Bubalus depressicornis; Bubalus quarlesi; Bioclimatic; Climate Change \u0000  \u0000Copyright (c) 2023 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41913257","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":"Analysis of Sea Surface Dynamics during the Coastal Floods in Manado","authors":"Audia Azizah Azani, U. Efendi","doi":"10.19184/geosi.v8i1.35091","DOIUrl":"https://doi.org/10.19184/geosi.v8i1.35091","url":null,"abstract":"Coastal flooding is one of the serious problems facing most coastal areas in the world. On January 17 and December 7, 2021, coastal flooding hit the coastal area of Manado, North Sulawesi, Indonesia. The disaster disrupted economic activities on the coast of Manado Bay. This study analyzed the dynamics of the atmosphere and the sea during coastal flood events using water level data from the Geospatial Information Agency, which was then filtered to separate residual and atmospheric tide, and oceanographic reanalysis data of Wavewatch-III from BMKG Ocean Forecast System (OFS). The results show that events on January 17 and December 7, 2021, coincided with the occurrence of the maximum tide. The residual water level shows a significant value of around 0.2 – 0.3 m, indicating the influence of atmospheric phenomena on sea level rise. According to oceanographical data, the local wind is the main factor of flood occurrence, which is shown by wind speed data which increased wave height significantly to 1,5 m on January 17, 2021, and to 2,0 m on December 7, 2021, around Manado Bay coast. Another factor that might contribute to the event is Manado's land morphology. Further study must be conducted to discover the influence of land morphology on coastal floods. \u0000Keywords: Coastal flood; Water level; Tide \u0000  \u0000  \u0000Copyright (c) 2023 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44360138","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":"The Implementation of Disaster Curriculum Toward Disaster Preparedness Campus at Syiah Kuala University","authors":"A. N. Gadeng, E. Maryani, E. Ningrum, I. Setiawan","doi":"10.19184/geosi.v7i3.30246","DOIUrl":"https://doi.org/10.19184/geosi.v7i3.30246","url":null,"abstract":"The earthquake and tsunami disasters in Aceh Province, Indonesia led to several injuries, deaths, unfound bodies, and high property losses on 26 December 2004. This hazardous period has reportedly become a valuable case for Syiah Kuala University, where various solutions are being considered for eradicating subsequent occurrences. Therefore, this study aims to determine the implementation patterns of the disaster curriculum developed and applied at Syiah Kuala University, to achieve a DPC (Disaster Preparedness Campus) reputation and enhance DP (Disaster Preparedness) among community members, especially students. A qualitative verification method outlined as a description was used, due to being an inductive approach to the entire experimental process. Data collection was also carried out through observation and literature review, as well as several interviews with the following, (1) The head of the technical implementation unit general course of Syiah Kuala University, (2) The coordinator and lecturer of disaster and environmental knowledge course, and (3) The students of Syiah Kuala University studying the course. After this process, a Delphi method was used to analyze the data obtained, with the outcomes confirmed by a competent expert. Based on the results, three important steps were found to improve disaster preparedness among the people of Aceh and Syiah Kuala University students, namely (1) The establishment of the Tsunami Disaster Mitigation Research Center in 2006, (2) The establishment of the Master Program Study of Disaster Science in the university's Postgraduate Program in 2010, and (3) Development of the general course of disaster knowledge and environment in 2016, which was a compulsory requirement for all students from various faculties, departments, and programs. This indicated that Syiah Kuala University was the first campus to mandate a disaster science course in Indonesia. These results are expected to improve disaster preparedness for students, with Syiah Kuala University becoming a DPC (Disaster Preparedness Campus) in Indonesia. \u0000Keywords : Implementation; Disaster Curriculum; Disaster Preparedness Campus \u0000  \u0000Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43317523","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":"The Compatibility of Area Functions Map with Actual Site Conditions in Konawe Selatan District","authors":"L. O. Nursalam, Agus Sugiarto, Putri Tipa Anasi, Ahmad Tarmidzi Abd Karim, F. Ikhsan, A. Sejati","doi":"10.19184/geosi.v7i3.34637","DOIUrl":"https://doi.org/10.19184/geosi.v7i3.34637","url":null,"abstract":"The Konawe Selatan District region is characterized by Karst hills, various soil types, and steep slopes. Functional classification considers the physical and non-physical characteristics of the location to determine its many uses. The map developed by the Regulation of the Agriculture Minister of Indonesia should be checked with the actual condition for the validation process before presenting to the society and Local government. Therefore, this research aimed to determine the compatibility of the area function map result with the actual conditions in Konawe Selatan District, Southeast Sulawesi, Indonesia. The research is a regional survey, collecting data from interviews and observations, and the data were analyzed descriptively and quantitatively with percentages. The results show that the compatibility of the Konawe Selatan District area function map is 89.61%, functioning as a guideline in the land use plan. Furthermore, the map could guide potential land-use planning functions such as protected forests, limited production forests, rice fields, and settlements. In conclusion, the map is appropriate for disseminating information and material for land use policies in Konawe Selatan District to stakeholders. \u0000Keywords : actual condition; area function; compatibility; map \u0000  \u0000Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49602074","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":"Exploration of Knowledge and Community Preparedness in Flood Disaster Mitigation","authors":"E. Syarif, M. Maddatuang, H. Hasriyanti, Alief Saputro","doi":"10.19184/geosi.v7i3.35066","DOIUrl":"https://doi.org/10.19184/geosi.v7i3.35066","url":null,"abstract":"Floods are natural disasters that should be highly considered due to their threats to human lives and the economy. It is also the third largest natural disaster in the world, which has claimed many lives and properties. Therefore, this study aims to identify community knowledge about floods and determine the efforts to increase preparedness strategies. A qualitative study was conducted in the village of Sapanan, Binamu District, Jeneponto Regency, Indonesia. Subsequently, data collection was carried out by observation, interviews, and documentation with various selected informants. Based on the results, the following were obtained, 1) The level of knowledge and actions performed by the Sapanan people was quite good regarding flooding. This was due to the experience of the community with the disaster, which they had decided to use as a learning platform, 2) The impacts often caused after flooding were the outbreaks of many diseases, which hindered the community from performing their usual activities. This was because they were busy cleaning their homes, with children consequently unable to attend school regarding the muddy state of the chairs and environment, and 3) The community's efforts to increase preparedness for the disasters included land use monitoring and prone location planning in safe areas. In this case, the level of knowledge and actions performed by the people of Sapanan village was quite good concerning flooding. This was because of their numerous experience with the disaster, which they had decided to use as a learning platform. \u0000Keywords : knowledge; preparedness; the community; flood \u0000  \u0000Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42334923","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":"Simulation of Rainfall Using Two Statistical Data Driven Models: A Study on Santhal Pargana Division of Jharkhand State, India","authors":"Shrinwantu Raha, Shasanka Kumar Gayen","doi":"10.19184/geosi.v7i3.34487","DOIUrl":"https://doi.org/10.19184/geosi.v7i3.34487","url":null,"abstract":"Although the variability and prediction of rainfall is an essential issue of the Santhal Pargana Division of the Jharkhand State but the issue is still far from its’ conclusive statement till date. Therefore, this study aimed to simulate the monthly rainfall from 1901 to 2020 using an eight-step procedure. After downloading the monthly rainfall for the Santhal Pargana Division from 1901 to 2020, the TBATS and Naive models were used to simulate the rainfall. The accuracy assessment of each model was done by using the MASE, MAE, RMSE, ME, and R. For the Naïve model, the Godda station was noticed with a comparatively high combined error. The lowest combined error was found for the Pakur station in case of Naïve models. Similar result was also obtained for the TBATS model. The TBATS was found with comparatively higher accuracy, as the combined error was less for the TBATS. The spatial assessment for the standardized rainfall varied from 84.419 mm. to 149.225 mm. For the Naïve predicted model, the rainfall was marked in between 8.133 mm. to 67.059 mm. For the TBATS fitted model, the rainfall fluctuated from the 37.127 mm. to 62.993 mm. Dumka station was noticed with comparatively low rainfall (i.e.,37.127 mm.). Deoghar and Jamtara stations were marked with a moderate rainfall. Remaining stations were marked with higher amount of rainfall for the TBATS fitted model. The Wilcoxon test proved that each model was significant at 95% confidence interval. The result produced in this research is fruitful enough to be utilized for agricultural planning in the Santhal Pargana Division of the Jharkhand state, India. \u0000Keywords : TBATS model; Naive model; simulation; accuracy \u0000  \u0000Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41729734","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":"Performance of UAV Image for Flood Mapping with 2 Dimensional Model in Kaliputih River, Panti District","authors":"I. Derka, E. Hidayah, G. Halik","doi":"10.19184/geosi.v7i3.30169","DOIUrl":"https://doi.org/10.19184/geosi.v7i3.30169","url":null,"abstract":"In January 2006, the flash flood in Panti Sub-district was a national disaster, causing damage to building infrastructure and fatalities. From this incident, it is necessary to have flood mitigation by providing a map of the distribution of flood inundation using a 2D hydraulic model to provide information regarding the extent of flood inundation in the study area. Due to the limited DEM data for 2D modeling, it is necessary to use UAV images to provide a DSM with good and higher resolution. This study aims to assess the performance of 2D flood modeling results using HEC-RAS equipped with RAS Mapper through UAV processing as input. There are 21 GCP in the study area as an increase in accuracy, the RMSE value in the horizontal direction is 0.3853m, and the vertical direction is 0.1836m. From the CE90 accuracy test results for a horizontal accuracy of 0.58m and LE90 for a vertical accuracy of 0.30m, it can be concluded that the map accuracy test meets the 1:2500 scale. Terrain maps are input to HEC-RAS; selected meshes are 5x5m and 2x2m. The modeling results can show the inundation depth in each GCP from the min-max depth. The model calibration shows an RMSE value of 0.183, while the flood depth validation shows an RMSE value of 0.13. In other words, modeling can represent the distribution of flood inundation in the study area and provide benefits for the community to be more alert in the event of a flood in the coming year. \u0000Keywords : UAV; GCP; DSM; HEC-RA; Flood mapping \u0000  \u0000Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42100700","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":"Utilization of Sentinel-2 Imagery in Mapping the Distribution and Estimation of Mangroves' Carbon Stocks in Bengkulu City","authors":"Ayub Sugara, A. H. Lukman, A. W. Rudiastuti, A. Anggoro, M. F. Hidayat, Feri Nugroho, A. M. Muslih, A. Suci, Rifi Zulhendri, Marissa Rahmania","doi":"10.19184/geosi.v7i3.30294","DOIUrl":"https://doi.org/10.19184/geosi.v7i3.30294","url":null,"abstract":"The mangroves' aboveground biomass significantly contributes to the global carbon cycle or economic and ecological values. This makes knowledge about the spatial extent of the mangroves indispensable for policymakers. The sequence of mangroves’ condition range also requires remote sensing data to update the geographical information and synthesize carbon stock in Bengkulu. Therefore, this study aims to create a spatial distrribution of mangroves and evaluate their carbon stock in Bengkulu City using Sentinel-2 imagery. The semi-empirical method uses Sentinel-2 imagery through NDVI to appraise and picture the mangroves' aboveground carbon stock. An allometric equation was used to compute the mangroves' aboveground carbon stock from field measurements. Non-linear regression was used to establish a connection between the NDVI calculated from the Sentinel-2 imagery and the mangroves' aboveground biomass measured in the field, which was subsequently used for aboveground carbon estimation. The results showed that mangroves mapping could derive overall accuracy of 89.09%, where the high-density class existed in 135.12 Ha of total area. It was also discovered that Sentinel-2 imagery could estimate mangroves carbon stock up to 61%. The carbon stock estimation based on the imagery has a value of 16.3992 – 115.134 t C/ha, while that of field survey data ranges from 19.69 to 326.06 t C/ha. These results showed that Sentinel-2B spectral data is functional and has a good chance of being able to predict carbon stock. \u0000  \u0000Keywords : Carbon; mangroves; NDVI; remote sensing; sentinel-2B \u0000  \u0000Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47012645","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":"The Application of Multi Temporal Satellite Data For Land Cover Mapping of Bawean Island, East Java","authors":"Z. Hidayah, H. Armono, M. Wardhani, Dwi Budi Wiyanto","doi":"10.19184/geosi.v7i3.30797","DOIUrl":"https://doi.org/10.19184/geosi.v7i3.30797","url":null,"abstract":"Land cover dynamics in a small island can be determined using Geographic Information System (GIS) approach based on multitemporal image analysis. This study aimed to classify major land cover types and to map land cover changes of Bawean Island. Two sets of 10 meter resolution satellite data ALOS AVNIR (2010) and Sentinel-2A (2020) were used in this study. Satellite image analysis was carried out through several stages namely image pre-processing including radiometric and geometric correction, supervised image classification and accuracy test. Image classification results from 2010 to 2020 showed a significant change in land cover on Bawean Island. The forest vegetation land cover declined significantly from 13,470.5 Ha in 2010 to 8,543.4 Ha in 2020. Most of the area have been converted into paddy fields and built-up areas. The accuracy test and validation were determined by comparing the 2020 Sentinel image classification results with field observation conducted in 2021. The analysis showed good results with 82.52% overall accuracy and 79.66 Kappa coefficient. Further investigation found that changes in land cover on Bawean Island occured due to the agriculture and infrastucture development. \u0000Keywords : Geographic Information System (GIS); land cover; satellite images; small island \u0000  \u0000Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember \u0000 This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License","PeriodicalId":33276,"journal":{"name":"Geosfera Indonesia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42835966","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}