Online multiplayer games are becoming massively popular nowadays. However, the churn of the players is becoming a significant concern as it is challenging to predict whether a player will churn or not, impacting business revenue. In this research, authors tried to solve this problem by predicting the player churn in advance using predictive analytics, thereby enabling the business owners to undertake steps to prevent player churn resulting in revenue stability. To achieve this, the authors collected the data from online and gaming platforms and then applied various pre-processing steps such as data conversion to make data suitable to use and then tested and applied a machine learning-based model for prediction by selecting churn period as the threshold value. Finally, various classifiers, such as logistic regression, were applied to predict whether a player will churn. The results were very satisfactory, as predicting churn with perfect accuracy was possible. The decision tree provides the best results, which were proximately 99.1 %, and other algorithms like logistic regression, random forest, and Adaboost gave predictive results of 96.86 %, 95.47 %, and 98.8 %, respectively. The accuracy of all the models has also been summarised. Hence, by making predictions in advance, the online platforms will take preventive measures to minimize the churn of players and increase revenue accordingly.
{"title":"An empirical study to predict churn of online multiplayer games and its impact on revenue of the game developing company","authors":"Krishna Kumar Singh, Sachin Rohatgi, M. P. Singh","doi":"10.47974/jsms-1169","DOIUrl":"https://doi.org/10.47974/jsms-1169","url":null,"abstract":"Online multiplayer games are becoming massively popular nowadays. However, the churn of the players is becoming a significant concern as it is challenging to predict whether a player will churn or not, impacting business revenue. In this research, authors tried to solve this problem by predicting the player churn in advance using predictive analytics, thereby enabling the business owners to undertake steps to prevent player churn resulting in revenue stability. To achieve this, the authors collected the data from online and gaming platforms and then applied various pre-processing steps such as data conversion to make data suitable to use and then tested and applied a machine learning-based model for prediction by selecting churn period as the threshold value. Finally, various classifiers, such as logistic regression, were applied to predict whether a player will churn. The results were very satisfactory, as predicting churn with perfect accuracy was possible. The decision tree provides the best results, which were proximately 99.1 %, and other algorithms like logistic regression, random forest, and Adaboost gave predictive results of 96.86 %, 95.47 %, and 98.8 %, respectively. The accuracy of all the models has also been summarised. Hence, by making predictions in advance, the online platforms will take preventive measures to minimize the churn of players and increase revenue accordingly.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135843298","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}
Sumera Aluru, B. V. R. Vishnu Tej, Mahathi Arkanath
Stock markets ought to be efficient while stock prices reflect all available information fairly and equitably. This bubble majorly forms when market participants inflate stock prices above the stock value based on some valuation system. Identifying the formation of these bubbles becomes imperative to provide information for the investors and these bubbles need to be validated as well, hence this paper contemplates to identify the existence of stock market bubbles between 2017 and 2022 with respect to the BSE Sensex. It also aims to analyse, if the momentum index and consumer confidence index reflect the market bubbles along with performance when the bubbles crashed. The E-views platform for the data analysis and Dickey-fuller, Augmented Dickey-Fuller, Rolling ADF, and Supremum ADF tests were deployed for identification of bubbles. It is found that a major market bubble occurred between January-May 2020. Apart from identifying the bubble that occurred previously, this paper also intends to alert investors of future bubbles following the same pattern of indices. By analysing contributing factors leading to a bubble, investors can be better prepared for the next bubble and can adjust their strategies accordingly to minimize losses. Identification of stock market bubbles and validating them with momentum and consumer confidence indices just doesn’t suffice the investor requirements. Further the factors leading to the formation of these bubbles, nature of these bubbles also attention. Bubbles happen for commodity prices, crypto-currencies and often might be of different types and might reflect entirely different behaviour, in that case how far can momentum and CC indices serve as leading indicators need to be explored as well.
{"title":"Identifying stock market bubbles and evaluation with momentum index and CCI","authors":"Sumera Aluru, B. V. R. Vishnu Tej, Mahathi Arkanath","doi":"10.47974/jsms-1183","DOIUrl":"https://doi.org/10.47974/jsms-1183","url":null,"abstract":"Stock markets ought to be efficient while stock prices reflect all available information fairly and equitably. This bubble majorly forms when market participants inflate stock prices above the stock value based on some valuation system. Identifying the formation of these bubbles becomes imperative to provide information for the investors and these bubbles need to be validated as well, hence this paper contemplates to identify the existence of stock market bubbles between 2017 and 2022 with respect to the BSE Sensex. It also aims to analyse, if the momentum index and consumer confidence index reflect the market bubbles along with performance when the bubbles crashed. The E-views platform for the data analysis and Dickey-fuller, Augmented Dickey-Fuller, Rolling ADF, and Supremum ADF tests were deployed for identification of bubbles. It is found that a major market bubble occurred between January-May 2020. Apart from identifying the bubble that occurred previously, this paper also intends to alert investors of future bubbles following the same pattern of indices. By analysing contributing factors leading to a bubble, investors can be better prepared for the next bubble and can adjust their strategies accordingly to minimize losses. Identification of stock market bubbles and validating them with momentum and consumer confidence indices just doesn’t suffice the investor requirements. Further the factors leading to the formation of these bubbles, nature of these bubbles also attention. Bubbles happen for commodity prices, crypto-currencies and often might be of different types and might reflect entirely different behaviour, in that case how far can momentum and CC indices serve as leading indicators need to be explored as well.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135843786","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}
Energy is a basic ingredient to the economic growth story. Given the increased climate change risk, India like all other countries must transit from fossil -based energy to renewable energy. The transition requires large investments from domestic and foreign actors. The major source of sustainable finance from foreign actors is through the Foreign Direct Investment and External Commercial Borrowings routes. This study analyses the causal relationship between ‘Foreign Direct Investment and Economic Growth’ and ‘External Commercial Borrowings and Economic Growth’ in India in Renewable Energy sector, also explores the causal relationship between Foreign Direct Investment and External Commercial Borrowings. The study will help in recommending policy changes to increase Foreign Direct Investment and External Commercial Borrowings into Renewable Energy in India.
{"title":"Sustainable finance from foreign actors into renewable energy and economic growth: An Indian perspective","authors":"Anita Kohli, Ritu Wadhwa, G. C. Tripathi","doi":"10.47974/jsms-1154","DOIUrl":"https://doi.org/10.47974/jsms-1154","url":null,"abstract":"Energy is a basic ingredient to the economic growth story. Given the increased climate change risk, India like all other countries must transit from fossil -based energy to renewable energy. The transition requires large investments from domestic and foreign actors. The major source of sustainable finance from foreign actors is through the Foreign Direct Investment and External Commercial Borrowings routes. This study analyses the causal relationship between ‘Foreign Direct Investment and Economic Growth’ and ‘External Commercial Borrowings and Economic Growth’ in India in Renewable Energy sector, also explores the causal relationship between Foreign Direct Investment and External Commercial Borrowings. The study will help in recommending policy changes to increase Foreign Direct Investment and External Commercial Borrowings into Renewable Energy in India.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844587","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}
This study aims to find the impact of leadership on organizational culture and its subsequent effect on employee development. A quantitative research approach was employed, and data were collected through a survey questionnaire from a sample of employees working in various organizations. The study used correlation analysis to examine the relationship between leadership, organizational culture, and employee development. The result of the study revealed a positive and significant relationship between leadership and organizational culture. Also, the study found that organizational culture has a significant impact on employee development.
{"title":"A study on impact of leadership on organizational culture to employee development: An empirical analysis","authors":"Sadaf Khan, Shikha Mishra","doi":"10.47974/jsms-1162","DOIUrl":"https://doi.org/10.47974/jsms-1162","url":null,"abstract":"This study aims to find the impact of leadership on organizational culture and its subsequent effect on employee development. A quantitative research approach was employed, and data were collected through a survey questionnaire from a sample of employees working in various organizations. The study used correlation analysis to examine the relationship between leadership, organizational culture, and employee development. The result of the study revealed a positive and significant relationship between leadership and organizational culture. Also, the study found that organizational culture has a significant impact on employee development.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135844607","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}
Sadhana Tiwari, Nitendra Kumar, Priyanka Agarwal, Mohd Nafees Siddiqui, Arti Malik
Green banking encourage environment-friendly practices and minimizing carbon foot-printing from banking activities. By using latest emerging technologies in Indian banking services, customers reduce using paper such as they used in traditional banking but now they doing banking transactions by digitally instead of paper. Green Banking service is a service that is given by the bank to its customers and done through mainly green phones. So, in this research paper, the researchers’ goal is to gauge the awareness level of millennial working women towards green banking practices in Indian Banking sector. The study is centered on millennial working women, who were born in 1981-96 (22-37age group).The study is descriptive and cross-sectional in nature and it is completely based on primary research and data gathered from 100 millennial working women of India.
{"title":"Indian working women millennials: An assessment of the relevance of green banking practices","authors":"Sadhana Tiwari, Nitendra Kumar, Priyanka Agarwal, Mohd Nafees Siddiqui, Arti Malik","doi":"10.47974/jsms-1190","DOIUrl":"https://doi.org/10.47974/jsms-1190","url":null,"abstract":"Green banking encourage environment-friendly practices and minimizing carbon foot-printing from banking activities. By using latest emerging technologies in Indian banking services, customers reduce using paper such as they used in traditional banking but now they doing banking transactions by digitally instead of paper. Green Banking service is a service that is given by the bank to its customers and done through mainly green phones. So, in this research paper, the researchers’ goal is to gauge the awareness level of millennial working women towards green banking practices in Indian Banking sector. The study is centered on millennial working women, who were born in 1981-96 (22-37age group).The study is descriptive and cross-sectional in nature and it is completely based on primary research and data gathered from 100 millennial working women of India.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135107531","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}
Anthony De Sa, Satya N. Mandal, Deepak Bajaj, N. Sridharan
As a supplier of commercial and residential infrastructure, real estate acts as a fulcrum for growth and enables holistic socio-economic development in India. This paper studies the extent of the impact of Covid-19 on the Indian real estate sector and evaluates the response to the challenges on the part of Real Estate Regulatory Authorities, government and other agencies in the real estate regulatory framework. Using primary data from a survey covering 257 respondents from 16 states, and secondary data from CREDAI and Anarock surveys conducted in two separate waves of Covid-19, notifications issued by RERAs and Ministries, RBI directives, stakeholder association representations, and a focus group discussion of experts, the regulatory response is assessed and evaluated. The data indicate that the measures announced are inadequate; a more robust response, including GST and other fiscal changes, and amendments to the RERA Act are required, as are technology infusion and management innovation for long-term adjustment.
{"title":"Real estate and Covid-19: Impact and regulatory response in India","authors":"Anthony De Sa, Satya N. Mandal, Deepak Bajaj, N. Sridharan","doi":"10.47974/jsms-1156","DOIUrl":"https://doi.org/10.47974/jsms-1156","url":null,"abstract":"As a supplier of commercial and residential infrastructure, real estate acts as a fulcrum for growth and enables holistic socio-economic development in India. This paper studies the extent of the impact of Covid-19 on the Indian real estate sector and evaluates the response to the challenges on the part of Real Estate Regulatory Authorities, government and other agencies in the real estate regulatory framework. Using primary data from a survey covering 257 respondents from 16 states, and secondary data from CREDAI and Anarock surveys conducted in two separate waves of Covid-19, notifications issued by RERAs and Ministries, RBI directives, stakeholder association representations, and a focus group discussion of experts, the regulatory response is assessed and evaluated. The data indicate that the measures announced are inadequate; a more robust response, including GST and other fiscal changes, and amendments to the RERA Act are required, as are technology infusion and management innovation for long-term adjustment.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135838586","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}
Students are impacted by new developments in digital learning tools in various ways, enhancing their learning experience. The transition of the education system towards online education requires scrutiny of the satisfaction of the students with remote learning through the digital platform. This study intends to examine the level of satisfaction of undergraduate and postgraduate students through their experience with online learning. The present study took a sample of 147 students from higher education institutions and the data was collected through a questionnaire based on simple random sampling methods. The present study’s result shows a significant and positive relationship between students’ satisfaction and remote learning. The findings will aid educators and academics in identifying elements that can improve the level of students’ satisfaction with remote learning.
{"title":"A study on students’ satisfaction in remote learning behaviour using digital platforms in Indian higher education institutions","authors":"Shalini Kumari, Balvinder Shukla, Paritosh Mishra","doi":"10.47974/jsms-1175","DOIUrl":"https://doi.org/10.47974/jsms-1175","url":null,"abstract":"Students are impacted by new developments in digital learning tools in various ways, enhancing their learning experience. The transition of the education system towards online education requires scrutiny of the satisfaction of the students with remote learning through the digital platform. This study intends to examine the level of satisfaction of undergraduate and postgraduate students through their experience with online learning. The present study took a sample of 147 students from higher education institutions and the data was collected through a questionnaire based on simple random sampling methods. The present study’s result shows a significant and positive relationship between students’ satisfaction and remote learning. The findings will aid educators and academics in identifying elements that can improve the level of students’ satisfaction with remote learning.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135838524","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}
As access to healthcare has become more central to people’s daily lives, the amount of medical big data has grown exponentially. Wearable Internet of Things (IoT)-reliant technology is gaining popularity in the medical field as a means to improve patient care and reduce wait times. In recent years, billions of sensors, devices, and machines have been hooked up to the web. One such technology, remote patient monitoring, is increasingly used in modern patient care and treatment. In addition, these developments pose substantial security issues about the recording of transaction data and the transmission of information itself, and pose considerable dangers to users’ privacy. Concerns about the privacy of a patient’s medical records have the ability to discontinue treatment, putting the patient’s life in threat. Thus, a system is proposed using machine learning in combination with blockchain technology to allow secure management as well as analysis of large amounts of healthcare data. With the help of machine learning, it is feasible to sort through all of the data and extract out only the most pertinent information. This is accomplished with the help of trained methodologies. After this data has been saved, the next issue will be the exchange of data and ensuring its trustworthiness. The concept of blockchain is introduced at this point. The Blockchain technology relies on consensus to ensure that all data is accurate and that all transactions are conducted in a safe manner. The management of healthcare is one area where blockchain technology offers the ability to have a huge impact by placing patients at the center of the system and improving the privacy and portability of health records. This study is primarily concerned with finding solutions to issues relating to the administration of healthcare data by utilizing Blockchain technology and incorporating some crucial characteristics developed with Machine Learning. The performance evaluation of proposed Support Vector Machine is compared with the other conventional machine learning classifiers. It is observed from the experimental finding that performance accuracy of Support vector machine is 98% which is better as compared to other traditional machine learning classifiers.
{"title":"Securing healthcare data management using machine learning and blockchain technology: A comparative performance evaluation of support vector machine and conventional classifiers","authors":"Vaibhav Nivrutti Patil, Vijay H. Kalmani","doi":"10.47974/jsms-1080","DOIUrl":"https://doi.org/10.47974/jsms-1080","url":null,"abstract":"As access to healthcare has become more central to people’s daily lives, the amount of medical big data has grown exponentially. Wearable Internet of Things (IoT)-reliant technology is gaining popularity in the medical field as a means to improve patient care and reduce wait times. In recent years, billions of sensors, devices, and machines have been hooked up to the web. One such technology, remote patient monitoring, is increasingly used in modern patient care and treatment. In addition, these developments pose substantial security issues about the recording of transaction data and the transmission of information itself, and pose considerable dangers to users’ privacy. Concerns about the privacy of a patient’s medical records have the ability to discontinue treatment, putting the patient’s life in threat. Thus, a system is proposed using machine learning in combination with blockchain technology to allow secure management as well as analysis of large amounts of healthcare data. With the help of machine learning, it is feasible to sort through all of the data and extract out only the most pertinent information. This is accomplished with the help of trained methodologies. After this data has been saved, the next issue will be the exchange of data and ensuring its trustworthiness. The concept of blockchain is introduced at this point. The Blockchain technology relies on consensus to ensure that all data is accurate and that all transactions are conducted in a safe manner. The management of healthcare is one area where blockchain technology offers the ability to have a huge impact by placing patients at the center of the system and improving the privacy and portability of health records. This study is primarily concerned with finding solutions to issues relating to the administration of healthcare data by utilizing Blockchain technology and incorporating some crucial characteristics developed with Machine Learning. The performance evaluation of proposed Support Vector Machine is compared with the other conventional machine learning classifiers. It is observed from the experimental finding that performance accuracy of Support vector machine is 98% which is better as compared to other traditional machine learning classifiers.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135107353","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}
The selection of providers with sustainability considerations is the most significant activity in contemporary supply chain operations. Using the MCDM (Multi-Criteria Decision Making) technique, vendors are chosen. By choosing the right sustainable supplier, the organizations can upgrade their products, decrease costs, and satisfying customers’ requirements. Dodla dairy is a renowned name in dairy companies in Hyderabad and Andhra Pradesh where purchasing managers choose the farmers. The purchasing managers gave their references so that the weights of the identified criterion and the ranking of another possibility on the basis of each criterion are to be determined. Quality and cost of the products are the most prominent criterion in the dairy supply chain. The method called Fuzzy TOPSIS is utilized in this paper to choose the dairy suppliers. The major goal of employing fuzzy logic is to assist purchasing managers in deciding how much importance to give each criterion and how to rank each sustainable dealer. The outcome of the Fuzzy TOPSIS technique, which has been successfully applied, establishes the weights of the criterion and the best and worst sustainable suppliers.
{"title":"Evaluation and selection of sustainable suppliers using fuzzy topsis method in a dairy product company","authors":"Reema Agarwal, Ankur Agrawal, Nitendra Kumar, Samrat Ray, Priyanka Agarwal","doi":"10.47974/jsms-1186","DOIUrl":"https://doi.org/10.47974/jsms-1186","url":null,"abstract":"The selection of providers with sustainability considerations is the most significant activity in contemporary supply chain operations. Using the MCDM (Multi-Criteria Decision Making) technique, vendors are chosen. By choosing the right sustainable supplier, the organizations can upgrade their products, decrease costs, and satisfying customers’ requirements. Dodla dairy is a renowned name in dairy companies in Hyderabad and Andhra Pradesh where purchasing managers choose the farmers. The purchasing managers gave their references so that the weights of the identified criterion and the ranking of another possibility on the basis of each criterion are to be determined. Quality and cost of the products are the most prominent criterion in the dairy supply chain. The method called Fuzzy TOPSIS is utilized in this paper to choose the dairy suppliers. The major goal of employing fuzzy logic is to assist purchasing managers in deciding how much importance to give each criterion and how to rank each sustainable dealer. The outcome of the Fuzzy TOPSIS technique, which has been successfully applied, establishes the weights of the criterion and the best and worst sustainable suppliers.","PeriodicalId":270059,"journal":{"name":"Journal of Statistics and Management Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135107526","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}
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