The neutral grounding mode of medium-voltage distribution network decides the reliability, overvoltage, relay protection and electrical safety. Therefore, a comprehensive consideration of the reliability, safety and e...The neutral grounding mode of medium-voltage distribution network decides the reliability, overvoltage, relay protection and electrical safety. Therefore, a comprehensive consideration of the reliability, safety and economy is particularly important for the decision of neutral grounding mode. This paper proposes a new decision method of neutral point grounding mode for mediumvoltage distribution network. The objective function is constructed for the decision according the life cycle cost. The reliability of the neutral point grounding mode is taken into account through treating the outage cost as an operating cost. The safety condition of the neutral point grounding mode is preserved as the constraint condition of decision models, so the decision method can generate the most economical and reliable scheme of neutral point grounding mode within a safe limit. The example is used to verify the feasibility and effectiveness of the decision method.展开更多
To help the government better understand and manage public sentiments,and help the public establish the values of rational participation in online discussions related to COVID-19,it is necessary to explore the themes ...To help the government better understand and manage public sentiments,and help the public establish the values of rational participation in online discussions related to COVID-19,it is necessary to explore the themes and emotions of different subjects discussing the pandemic on social media platforms.The study takes a comprehensive view by combining social media and scholarly outputs data.In particular,WeChat articles are investigated to reveal the public concern and public sentiment towards COVID-19,and WeChat mentions to scholarly papers are identified to show the interaction between the public and researchers.Text analysis is conducted to construct co-occurrence networks and reveal the distribution of themes.VOSviewer is applied to network visualization.Statistical and comparative analysis showed that discussion about COVID-19 keeps hot on WeChat.WeChat offical accounts from the information industry dominate,suggesting a free and flexible discussing environment.Topics on WeChat overlap with that of scholarly papers but have a much broader scope.WeChat mentions to scholarly papers has bridged the public with the research and has a high coverage of 61.7%.Public sentiment in WeChat is positive,demonstrating good confidence in defeating the pandemic.These findings are helpful in understanding the social attitude towards and comprehensive perception of COVID-19 in China.展开更多
The aim of this research was to evaluate doxorubicin(DOX)-loaded zein in situ gels,a new drug delivery system in which a liquid state drug can be transformed into semi-solid after intratumoral injection.In vitro relea...The aim of this research was to evaluate doxorubicin(DOX)-loaded zein in situ gels,a new drug delivery system in which a liquid state drug can be transformed into semi-solid after intratumoral injection.In vitro release of DOX-loaded zein was investigated and the pharmacokinetics,biodistribution and therapeutic efficacy of these DOX-loaded zein formulations were investigated using BAI B/c nude tumor-bearing mice.In vitro release of DOX from the gels extended up to 7 days.Efficient accumulation of DOX in the tumor with lower drug concentration in blood and normal organs was obtained resulting in effective inhibition of tumor growth and fewer off-target side effects.In conclusion,a DOX-loaded in situ gel was developed with sustained release,enhanced anti-cancer efficacy for colorectal cancer in vivo,and especially with reduced off-target side effects.展开更多
[Purpose/Significance]The article investigated the automatic identification of the motivation of Facebook mention to scholarly outputs based on Light GBM algorithm,in order to achieve more in-depth usage of Facebook m...[Purpose/Significance]The article investigated the automatic identification of the motivation of Facebook mention to scholarly outputs based on Light GBM algorithm,in order to achieve more in-depth usage of Facebook mention on a large scale.[Methodology/Procedure]Based on three types of contextual data,including mentioned scholarly outputs,Facebook users who post scholarly outputs,and text of Facebook posts to scholarly outputs,promising relevant features were extracted,and machine learning algorithms were used to automatically identify the motivations.[Results/Conclusions](1)Features significantly correlated to the motivation of Facebook mention are identified in all three types of contextual data.In particular,relevant features are the altmetric attention score,the number of collaborative countries,the number of followers,the number of likes,the identities of Facebook users who post scholarly outputs and the number of comments on Facebook posts;(2)The prediction precision of the Light GBM classification model for motivation of Facebook mention was 0.31.In comparison,the classification precision without the text features of Facebook posts was 0.35,which was higher than the overall feature combination.The classification precision with only the post text features was 0.27.After combining the length and language of posts,the precision was improved to 0.30;(3)The classification precision of Facebook motivation has a positive correlation with users’activity.After combining all features,the classification precision of the first quartile users in terms of productivity reached 1,the classification precision of the second quartile was 0.36,and for the third quartile,the classification precision was 0.32.In conclusion,considering the high complexity of automatic classification of motivation of Facebook mentions,the study has achieved relatively high classification precision and could provide reference for future studies.展开更多
文摘The neutral grounding mode of medium-voltage distribution network decides the reliability, overvoltage, relay protection and electrical safety. Therefore, a comprehensive consideration of the reliability, safety and economy is particularly important for the decision of neutral grounding mode. This paper proposes a new decision method of neutral point grounding mode for mediumvoltage distribution network. The objective function is constructed for the decision according the life cycle cost. The reliability of the neutral point grounding mode is taken into account through treating the outage cost as an operating cost. The safety condition of the neutral point grounding mode is preserved as the constraint condition of decision models, so the decision method can generate the most economical and reliable scheme of neutral point grounding mode within a safe limit. The example is used to verify the feasibility and effectiveness of the decision method.
基金funded by the National Natural Science Foundation of China(72274227)Humanity and Social Science Foundation of the Ministry of Education of China(22YJA870016).
文摘To help the government better understand and manage public sentiments,and help the public establish the values of rational participation in online discussions related to COVID-19,it is necessary to explore the themes and emotions of different subjects discussing the pandemic on social media platforms.The study takes a comprehensive view by combining social media and scholarly outputs data.In particular,WeChat articles are investigated to reveal the public concern and public sentiment towards COVID-19,and WeChat mentions to scholarly papers are identified to show the interaction between the public and researchers.Text analysis is conducted to construct co-occurrence networks and reveal the distribution of themes.VOSviewer is applied to network visualization.Statistical and comparative analysis showed that discussion about COVID-19 keeps hot on WeChat.WeChat offical accounts from the information industry dominate,suggesting a free and flexible discussing environment.Topics on WeChat overlap with that of scholarly papers but have a much broader scope.WeChat mentions to scholarly papers has bridged the public with the research and has a high coverage of 61.7%.Public sentiment in WeChat is positive,demonstrating good confidence in defeating the pandemic.These findings are helpful in understanding the social attitude towards and comprehensive perception of COVID-19 in China.
基金This study was supported by the Natural Science Foundation of China(30801444)the Natural Science Foundation of Hebei Province(H2012208020)the Hebei University of Science and Technology Discipline Construction Office and the State Key Laboratory Breeding Base-Hebei Key Laboratory of Molecular Chemistry For Drug。
文摘The aim of this research was to evaluate doxorubicin(DOX)-loaded zein in situ gels,a new drug delivery system in which a liquid state drug can be transformed into semi-solid after intratumoral injection.In vitro release of DOX-loaded zein was investigated and the pharmacokinetics,biodistribution and therapeutic efficacy of these DOX-loaded zein formulations were investigated using BAI B/c nude tumor-bearing mice.In vitro release of DOX from the gels extended up to 7 days.Efficient accumulation of DOX in the tumor with lower drug concentration in blood and normal organs was obtained resulting in effective inhibition of tumor growth and fewer off-target side effects.In conclusion,a DOX-loaded in situ gel was developed with sustained release,enhanced anti-cancer efficacy for colorectal cancer in vivo,and especially with reduced off-target side effects.
基金supported by Hum anity and Social Science Foundation of Ministry of Education of China(22YJA870016)National Natural Science Foundation of China(NO.72274227)
文摘[Purpose/Significance]The article investigated the automatic identification of the motivation of Facebook mention to scholarly outputs based on Light GBM algorithm,in order to achieve more in-depth usage of Facebook mention on a large scale.[Methodology/Procedure]Based on three types of contextual data,including mentioned scholarly outputs,Facebook users who post scholarly outputs,and text of Facebook posts to scholarly outputs,promising relevant features were extracted,and machine learning algorithms were used to automatically identify the motivations.[Results/Conclusions](1)Features significantly correlated to the motivation of Facebook mention are identified in all three types of contextual data.In particular,relevant features are the altmetric attention score,the number of collaborative countries,the number of followers,the number of likes,the identities of Facebook users who post scholarly outputs and the number of comments on Facebook posts;(2)The prediction precision of the Light GBM classification model for motivation of Facebook mention was 0.31.In comparison,the classification precision without the text features of Facebook posts was 0.35,which was higher than the overall feature combination.The classification precision with only the post text features was 0.27.After combining the length and language of posts,the precision was improved to 0.30;(3)The classification precision of Facebook motivation has a positive correlation with users’activity.After combining all features,the classification precision of the first quartile users in terms of productivity reached 1,the classification precision of the second quartile was 0.36,and for the third quartile,the classification precision was 0.32.In conclusion,considering the high complexity of automatic classification of motivation of Facebook mentions,the study has achieved relatively high classification precision and could provide reference for future studies.
