The discovery of drugs is recognized as a lengthy, highly costly, and extremely complex process. For example, some traditional drug discovery methods consist of millions of trials to get a druggable compound to the market. Drug discovery based on artificial intelligence can be a prompt, low-cost, and effective way to streamline drug discovery. Although some works have been proposed to use artificial intelligence tools for drug discovery, few people summarize these advances in a systematic way. In this paper, we propose an organized and comprehensive review that outlines a broad range of appliances of artificial intelligence in drug discovery including harnessing virtual screening and molecular docking techniques, utilizing pathway networks for repurposing existing drugs, lead identification, biomarker research, identification of the target, diverse variety of artificial intelligence and their comparison, etc. In addition, we shed light on predicted limitations and challenges in drug discovery based on artificial intelligence, as well as sketch the strategies to harness its potential for upcoming drug design endeavors.
{"title":"A Review: Drug Discovery Methods Based on Artificial Intelligence","authors":"Jinhao Chen","doi":"10.61173/khh85h64","DOIUrl":"https://doi.org/10.61173/khh85h64","url":null,"abstract":"The discovery of drugs is recognized as a lengthy, highly costly, and extremely complex process. For example, some traditional drug discovery methods consist of millions of trials to get a druggable compound to the market. Drug discovery based on artificial intelligence can be a prompt, low-cost, and effective way to streamline drug discovery. Although some works have been proposed to use artificial intelligence tools for drug discovery, few people summarize these advances in a systematic way. In this paper, we propose an organized and comprehensive review that outlines a broad range of appliances of artificial intelligence in drug discovery including harnessing virtual screening and molecular docking techniques, utilizing pathway networks for repurposing existing drugs, lead identification, biomarker research, identification of the target, diverse variety of artificial intelligence and their comparison, etc. In addition, we shed light on predicted limitations and challenges in drug discovery based on artificial intelligence, as well as sketch the strategies to harness its potential for upcoming drug design endeavors.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141376851","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}
Securities trading has always been a high-risk, high-return domain. Investors seek high returns while endeavoring to minimize risks as much as possible. Therefore, stock price prediction has become a popular and immensely valuable research topic. This paper will use the ARMA model to forecast stock prices. Firstly, an analysis was conducted on selected stock, determining that the price sequence exhibits no seasonal effects but does display volatility effects. The trend is essentially linear, and the relationship between volatility effects and trends fits an additive model. Based on this, preprocessing was conducted by taking the three-day moving average sequence of the series to eliminate the volatility effects, yielding a clean sequence trend. Then, the trend was differenced once to obtain a stationary sequence. Subsequently, the appropriate ARIMA model order was determined by the (partial) autocorrelation plot of this stationary sequence, and the model was fitted to the stock for prediction, yielding satisfactory results. This indicates that the model can accurately forecast long-term trends, but the filtering of volatility effects prevents the prediction results from sensitively reflecting short-term fluctuations.
证券交易一直是一个高风险、高回报的领域。投资者在追求高回报的同时，也在尽可能地降低风险。因此，股票价格预测已成为一个热门且极具价值的研究课题。本文将使用 ARMA 模型来预测股票价格。首先，对选定的股票进行分析，确定价格序列没有季节效应，但有波动效应。趋势基本上是线性的，波动效应与趋势之间的关系符合加法模型。在此基础上，通过对序列的三天移动平均序列进行预处理，以消除波动效应，从而得到清晰的序列趋势。然后，对趋势进行一次差分，以获得静态序列。随后，根据该静态序列的（部分）自相关图确定适当的 ARIMA 模型阶数，并将该模型拟合到股票上进行预测，结果令人满意。这表明该模型可以准确预测长期趋势，但由于过滤了波动效应，预测结果无法灵敏反映短期波动。
{"title":"ARIMA Model-Based Research on Stock Price Prediction","authors":"Dong Liang","doi":"10.61173/nq5kv133","DOIUrl":"https://doi.org/10.61173/nq5kv133","url":null,"abstract":"Securities trading has always been a high-risk, high-return domain. Investors seek high returns while endeavoring to minimize risks as much as possible. Therefore, stock price prediction has become a popular and immensely valuable research topic. This paper will use the ARMA model to forecast stock prices. Firstly, an analysis was conducted on selected stock, determining that the price sequence exhibits no seasonal effects but does display volatility effects. The trend is essentially linear, and the relationship between volatility effects and trends fits an additive model. Based on this, preprocessing was conducted by taking the three-day moving average sequence of the series to eliminate the volatility effects, yielding a clean sequence trend. Then, the trend was differenced once to obtain a stationary sequence. Subsequently, the appropriate ARIMA model order was determined by the (partial) autocorrelation plot of this stationary sequence, and the model was fitted to the stock for prediction, yielding satisfactory results. This indicates that the model can accurately forecast long-term trends, but the filtering of volatility effects prevents the prediction results from sensitively reflecting short-term fluctuations.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"21 10‐11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141379855","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}
Through daily life, complex tasks require the neural encoding of spatial location for oneself and others. Previous research studies in rodents have shown that rodents have neural representations of themselves in addition to other rodents. ( Ovchinnikov, 2010) However, there is still a need to understand how the human brain processes spatial location for itself and others. Furthermore, it is important to research which parts of human cognition can affect location encoding mechanisms. The current study uses existing data to determine the correlation between environmental boundaries and human brain activity. Using spatial observation and navigation tasks, the study investigated whether a physical boundary can affect neural encoding using implanted electrodes, representing the participants’ location and others’ location while in a closed environment. Results showed that representations were strengthened when the encoding of location had a greater behavioral significance and was contingent upon the momentary cognitive state of the individual.Together, these findings support the existence of a shared encoding mechanism within the human brain that signifies the whereabouts of both individuals in communal settings. Moreover, they illuminate novel insights into the neural processes that govern spatial navigation and the perception of others in practical situations.
{"title":"Real world ambulatory boundary effect within MTL oscillation during movement in human brains","authors":"Siwei Wu","doi":"10.61173/62mqmr19","DOIUrl":"https://doi.org/10.61173/62mqmr19","url":null,"abstract":"Through daily life, complex tasks require the neural encoding of spatial location for oneself and others. Previous research studies in rodents have shown that rodents have neural representations of themselves in addition to other rodents. ( Ovchinnikov, 2010) However, there is still a need to understand how the human brain processes spatial location for itself and others. Furthermore, it is important to research which parts of human cognition can affect location encoding mechanisms. The current study uses existing data to determine the correlation between environmental boundaries and human brain activity. Using spatial observation and navigation tasks, the study investigated whether a physical boundary can affect neural encoding using implanted electrodes, representing the participants’ location and others’ location while in a closed environment. Results showed that representations were strengthened when the encoding of location had a greater behavioral significance and was contingent upon the momentary cognitive state of the individual.Together, these findings support the existence of a shared encoding mechanism within the human brain that signifies the whereabouts of both individuals in communal settings. Moreover, they illuminate novel insights into the neural processes that govern spatial navigation and the perception of others in practical situations.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"14 13‐14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380154","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}
With the rapid increase in the number of electric vehicles (EVs), vehicle-to-grid (V2G) technology plays a vital role in reducing the burden on the power system. This technology optimizes network load distribution through a two-way charging mechanism and effectively alleviates network load fluctuations. However, potential negative impacts on EV battery life should also be a cause for concern. Furthermore, the technology does not fundamentally change the charging behavior of electric vehicles. Against this background, this study proposes a multi-objective optimization strategy to adapt electricity price policy to network load fluctuations to control charging behavior. This strategy optimizes battery attenuation, charging costs, and network load fluctuations, aiming to alleviate network load fluctuations while completely solving user concerns about charging and battery maintenance costs. Simulation analysis has verified the effectiveness of this model in reducing grid load fluctuations and balancing user costs.
{"title":"Bi-Directional Optimization of V2G Strategy Based on Multi-Objective Optimization: Balancing Grid Load and Reducing Electric Vehicle Charging Costs","authors":"Yilin Liu","doi":"10.61173/75xhcx48","DOIUrl":"https://doi.org/10.61173/75xhcx48","url":null,"abstract":"With the rapid increase in the number of electric vehicles (EVs), vehicle-to-grid (V2G) technology plays a vital role in reducing the burden on the power system. This technology optimizes network load distribution through a two-way charging mechanism and effectively alleviates network load fluctuations. However, potential negative impacts on EV battery life should also be a cause for concern. Furthermore, the technology does not fundamentally change the charging behavior of electric vehicles. Against this background, this study proposes a multi-objective optimization strategy to adapt electricity price policy to network load fluctuations to control charging behavior. This strategy optimizes battery attenuation, charging costs, and network load fluctuations, aiming to alleviate network load fluctuations while completely solving user concerns about charging and battery maintenance costs. Simulation analysis has verified the effectiveness of this model in reducing grid load fluctuations and balancing user costs.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"343 6‐7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141381051","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 application of UAV remote sensing technology in engineering surveying and mapping has gradually become widespread due to its high efficiency and accuracy. It cannot only quickly obtain high-definition mapping data to provide accurate and complete information support for engineering design and construction but also make up for the limitations of traditional engineering surveying and mapping and promote the innovation and development of the surveying and mapping field. Therefore, this paper explores the application of UAV remote sensing technology in engineering mapping. The exploration of UAV remote sensing technology is of great practical significance for achieving the goal of high-quality mapping data and high efficiency of the mapping process. Surveying and mapping staff need to have a correct perception and logic of the workflow of UAV remote sensing technology in the field of engineering surveying and mapping, analyze the needs of engineering surveying and mapping step by step, study the use of the technology and specific scenes, and promote the rapid development of technology and innovation, to give full play to the role of remote sensing technology of UAVs, and to arrive at more accurate measurement results.
{"title":"Exploration of the Application of UAV Remote Sensing Technology in Engineering Surveying and Mapping","authors":"Suqi Liu","doi":"10.61173/f0qwkj60","DOIUrl":"https://doi.org/10.61173/f0qwkj60","url":null,"abstract":"The application of UAV remote sensing technology in engineering surveying and mapping has gradually become widespread due to its high efficiency and accuracy. It cannot only quickly obtain high-definition mapping data to provide accurate and complete information support for engineering design and construction but also make up for the limitations of traditional engineering surveying and mapping and promote the innovation and development of the surveying and mapping field. Therefore, this paper explores the application of UAV remote sensing technology in engineering mapping. The exploration of UAV remote sensing technology is of great practical significance for achieving the goal of high-quality mapping data and high efficiency of the mapping process. Surveying and mapping staff need to have a correct perception and logic of the workflow of UAV remote sensing technology in the field of engineering surveying and mapping, analyze the needs of engineering surveying and mapping step by step, study the use of the technology and specific scenes, and promote the rapid development of technology and innovation, to give full play to the role of remote sensing technology of UAVs, and to arrive at more accurate measurement results.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"199 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141376107","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 the primary cause of global warming, the increase in atmospheric carbon dioxide(CO2) concentration has attracted more and more attention worldwide. With the slogan of “peaking carbon” and “carbon neutrality” in China, the need for quantitative, real-time, and large-scale monitoring of CO2 concentration is becoming more urgent. As an all-weather, high-precision monitoring method for greenhouse gas emissions, satellite remote sensing has great potential in CO2 monitoring. After studying the development and performance of remote sensing satellites for CO2 monitoring, the conclusion drawn by this paper is that the monitoring accuracy of CO2 monitoring sensors is gradually improved with increasing attention to CO2 concentration detection in various countries and that because active remote sensing is not affected by aerosol and solar radiation, the current high-precision CO2 concentration detection has gradually changed from passive remote sensing to a combination of active and passive remote sensing. By reviewing the development process of CO2 monitoring remote sensing satellites and the research and application of CO2 satellite data, this paper finds out the gaps in the current research of CO2 remote sensing satellites. It inspires future scholars who want to carry out research in this field.
{"title":"Progress and Case Study of Satellite Remote Rensing Technology for Carbon Dioxide","authors":"Jinbo Pu","doi":"10.61173/k28nqk82","DOIUrl":"https://doi.org/10.61173/k28nqk82","url":null,"abstract":"As the primary cause of global warming, the increase in atmospheric carbon dioxide(CO2) concentration has attracted more and more attention worldwide. With the slogan of “peaking carbon” and “carbon neutrality” in China, the need for quantitative, real-time, and large-scale monitoring of CO2 concentration is becoming more urgent. As an all-weather, high-precision monitoring method for greenhouse gas emissions, satellite remote sensing has great potential in CO2 monitoring. After studying the development and performance of remote sensing satellites for CO2 monitoring, the conclusion drawn by this paper is that the monitoring accuracy of CO2 monitoring sensors is gradually improved with increasing attention to CO2 concentration detection in various countries and that because active remote sensing is not affected by aerosol and solar radiation, the current high-precision CO2 concentration detection has gradually changed from passive remote sensing to a combination of active and passive remote sensing. By reviewing the development process of CO2 monitoring remote sensing satellites and the research and application of CO2 satellite data, this paper finds out the gaps in the current research of CO2 remote sensing satellites. It inspires future scholars who want to carry out research in this field.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"358 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141381072","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}
In the context of the “double carbon” strategy and the rapid development of deep learning, it provides new ideas for load forecasting of intelligent microgrids. In this study, we choose the Informer model based on the Transformer framework, which improves the self-attention mechanism and reduces the computational cost, to improve load accuracy and to achieve intelligent management of the microgrid system by accurately forecasting power load data.
{"title":"Deepening Intelligent Microgrid Management: A Study on Improving Load Forecasting Accuracy Based on Informer Models","authors":"Yuke Wang","doi":"10.61173/sq6kd003","DOIUrl":"https://doi.org/10.61173/sq6kd003","url":null,"abstract":"In the context of the “double carbon” strategy and the rapid development of deep learning, it provides new ideas for load forecasting of intelligent microgrids. In this study, we choose the Informer model based on the Transformer framework, which improves the self-attention mechanism and reduces the computational cost, to improve load accuracy and to achieve intelligent management of the microgrid system by accurately forecasting power load data.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"5 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380678","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}
In recent years, medical waste has gained attention due to its hazardous nature, complexity, and high cost of manual sorting and management. Therefore, it is crucial to develop classification systems that are accurate and efficient. This study analyzes various deep learning models for medical waste classification, compares their accuracies in image recognition, and provides an in-depth analysis of EfficientNet, a classification model that is well-suited to handle large amounts of waste mixing. EfficientNet’s superior performance can be adapted to numerous potential scenarios in medical waste, and its improved performance is also very promising in the field of medical waste classification. The data demonstrate its significant advantages over other models, indicating broad application prospects and economic benefits.
{"title":"Improvement of EfficientNet in medical waste classification","authors":"Xiaomo Wang","doi":"10.61173/dzxz2j87","DOIUrl":"https://doi.org/10.61173/dzxz2j87","url":null,"abstract":"In recent years, medical waste has gained attention due to its hazardous nature, complexity, and high cost of manual sorting and management. Therefore, it is crucial to develop classification systems that are accurate and efficient. This study analyzes various deep learning models for medical waste classification, compares their accuracies in image recognition, and provides an in-depth analysis of EfficientNet, a classification model that is well-suited to handle large amounts of waste mixing. EfficientNet’s superior performance can be adapted to numerous potential scenarios in medical waste, and its improved performance is also very promising in the field of medical waste classification. The data demonstrate its significant advantages over other models, indicating broad application prospects and economic benefits.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"211 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141375971","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 article aims to identify those factors that have an impact on new energy vehicle prices. The method of multiple linear regression is used to analyze the significant factors using 100 samples from Kaggle. Based on an assumption, 13 variables that were chosen do correlate with new energy car prices. This paper will analyze these following factors: energy type, engine power, reviews count, seating capacity, fuel tank capacity, body type, rating, no cylinder, max power rp, max power bhp, max power rpm, max power nm, transmission type. This article uses multiple linear regression models to analyze these factors’ influence on new energy vehicles. Overall, new energy vehicle prices can be analyzed by the extent to which these factors affect them. By calculation, it is determined that engine power, no cylinder, and max power bhp will have a significant positive impact on the starting price. Max torque rpm and max torque nm will have a significant negative influence on the starting price.
{"title":"Research on the Influencing Factors of New Energy Cars Prices","authors":"Xijun Wang","doi":"10.61173/qbt0bb62","DOIUrl":"https://doi.org/10.61173/qbt0bb62","url":null,"abstract":"This article aims to identify those factors that have an impact on new energy vehicle prices. The method of multiple linear regression is used to analyze the significant factors using 100 samples from Kaggle. Based on an assumption, 13 variables that were chosen do correlate with new energy car prices. This paper will analyze these following factors: energy type, engine power, reviews count, seating capacity, fuel tank capacity, body type, rating, no cylinder, max power rp, max power bhp, max power rpm, max power nm, transmission type. This article uses multiple linear regression models to analyze these factors’ influence on new energy vehicles. Overall, new energy vehicle prices can be analyzed by the extent to which these factors affect them. By calculation, it is determined that engine power, no cylinder, and max power bhp will have a significant positive impact on the starting price. Max torque rpm and max torque nm will have a significant negative influence on the starting price.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"353 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141380656","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 paper presents the design of a fire safety and security network for high-rise buildings based on wireless sensor networks. Utilizing the Zigbee system’s topology and Zigbee technology for wireless sensor network communication, the design enables intercommunication among sensor nodes, forming a multi-network system. This system facilitates the preemptive warning and dissemination of fire-related information, facilitating efficient information transmission. Simulation results affirm the practical effectiveness of this design scheme, underscoring its substantial applicability.
{"title":"Research on Fire Alarm Network for High-rise Buildings Based on Wireless Sensor Networks","authors":"Keyan Wei","doi":"10.61173/8m678b18","DOIUrl":"https://doi.org/10.61173/8m678b18","url":null,"abstract":"This paper presents the design of a fire safety and security network for high-rise buildings based on wireless sensor networks. Utilizing the Zigbee system’s topology and Zigbee technology for wireless sensor network communication, the design enables intercommunication among sensor nodes, forming a multi-network system. This system facilitates the preemptive warning and dissemination of fire-related information, facilitating efficient information transmission. Simulation results affirm the practical effectiveness of this design scheme, underscoring its substantial applicability.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"26 44","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141379258","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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