[ Objective] This study was conducted to investigate the mechanism of Echinacea polysaccharide （EPS） in treatment of various bacterial infection and reduction of inflammation, so as to provide a theoretical basis fo...[ Objective] This study was conducted to investigate the mechanism of Echinacea polysaccharide （EPS） in treatment of various bacterial infection and reduction of inflammation, so as to provide a theoretical basis for clinic application of EPS. [ Method ] Nuclear protein extracted from six groups, the normal control group, the simple lipopolysaccharide （LPS） group and the EPS （ with concentrations of 50,100,200 and 500 μg/ml, respectively） ＋ LPS groups was subjected to SDS-PAGE electrophoresis, and pIkB-α protein contents in the extracts were analyzed by Coomassie brilliant blue （CBB） staining and Western-Blot method. [ Result] The simple LPS group showed the highest pIkB-α protein level, and in the EPS concentration range of 0 -200 μg/ml, the expression level of pIkB-α pro- tein was improved with the increase of EPS concentration. [ Conclusion The expression level of pIkB-α protein was improved under the simulation of IEC-6 by LPS, while EPS could effectively inhibit the expression of pIkB-α protein. The expression level of pIkB-α was the lowest in the LPS ＋500 μg/ml EPS group.展开更多
In this study, histopathological changes in the heart, liver, spleen, lung, kidney, intestine, brain and other organs of foxes died of parvovims infection were observed. According to the results, multiple organs of in...In this study, histopathological changes in the heart, liver, spleen, lung, kidney, intestine, brain and other organs of foxes died of parvovims infection were observed. According to the results, multiple organs of infected foxes were congested and hemorrhaged with tissue damage, inflammatory cell infiltration and a series of pathological changes, mainly exhibiting hepatic cell cord rupture, liver cell granular degeneration and fatty degeneration, small intestinal mucous mem- brane shedding, intestinal villi necrosis and shedding, severe hemorrhage of lamina pmpria with inflammatory cell infiltration, and severe small intestinal bleeding. This study laid a solid foundation for clinical diagnosis, prevention and treatment of parvovirus infection in foxes.展开更多
Knowledge tracing aims to track students’knowledge status over time to predict students’future performance accurately.In a real environment,teachers expect knowledge tracing models to provide the interpretable resul...Knowledge tracing aims to track students’knowledge status over time to predict students’future performance accurately.In a real environment,teachers expect knowledge tracing models to provide the interpretable result of knowledge status.Markov chain-based knowledge tracing(MCKT)models,such as Bayesian Knowledge Tracing,can track knowledge concept mastery probability over time.However,as the number of tracked knowledge concepts increases,the time complexity of MCKT predicting student performance increases exponentially(also called explaining away problem).When the number of tracked knowledge concepts is large,we cannot utilize MCKT to track knowledge concept mastery probability over time.In addition,the existing MCKT models only consider the relationship between students’knowledge status and problems when modeling students’responses but ignore the relationship between knowledge concepts in the same problem.To address these challenges,we propose an inTerpretable pRobAbilistiC gEnerative moDel(TRACED),which can track students’numerous knowledge concepts mastery probabilities over time.To solve explain away problem,we design long and short-term memory(LSTM)-based networks to approximate the posterior distribution,predict students’future performance,and propose a heuristic algorithm to train LSTMs and probabilistic graphical model jointly.To better model students’exercise responses,we proposed a logarithmic linear model with three interactive strategies,which models students’exercise responses by considering the relationship among students’knowledge status,knowledge concept,and problems.We conduct experiments with four real-world datasets in three knowledge-driven tasks.The experimental results show that TRACED outperforms existing knowledge tracing methods in predicting students’future performance and can learn the relationship among students,knowledge concepts,and problems from students’exercise sequences.We also conduct several case studies.The case studies show that TRACED exhibits excellent interpretability and thus has the potential for personalized automatic feedback in the real-world educational environment.展开更多
String similarity search and join are two impor- tant operations in data cleaning and integration, which ex- tend traditional exact search and exact join operations in databases by tolerating the errors and inconsiste...String similarity search and join are two impor- tant operations in data cleaning and integration, which ex- tend traditional exact search and exact join operations in databases by tolerating the errors and inconsistencies in the data. They have many real-world applications, such as spell checking, duplicate detection, entity resolution, and webpage clustering. Although these two problems have been exten- sively studied in the recent decade, there is no thorough sur- vey. In this paper, we present a comprehensive survey on string similarity search and join. We first give the problem definitions and introduce widely-used similarity functions to quantify the similarity. We then present an extensive set of algorithms for siring similarity search and join. We also dis- cuss their variants, including approximate entity extraction, type-ahead search, and approximate substring matching. Fi- nally, we provide some open datasets and summarize some research challenges and open problems.展开更多
基金Supported by Natural Science Foundation of China(31472230)Natural Science Foundation of Hebei Province(C2014407068)Fund from Science and Technology Department of Hebei Province(NO.14966610D)
文摘[ Objective] This study was conducted to investigate the mechanism of Echinacea polysaccharide （EPS） in treatment of various bacterial infection and reduction of inflammation, so as to provide a theoretical basis for clinic application of EPS. [ Method ] Nuclear protein extracted from six groups, the normal control group, the simple lipopolysaccharide （LPS） group and the EPS （ with concentrations of 50,100,200 and 500 μg/ml, respectively） ＋ LPS groups was subjected to SDS-PAGE electrophoresis, and pIkB-α protein contents in the extracts were analyzed by Coomassie brilliant blue （CBB） staining and Western-Blot method. [ Result] The simple LPS group showed the highest pIkB-α protein level, and in the EPS concentration range of 0 -200 μg/ml, the expression level of pIkB-α pro- tein was improved with the increase of EPS concentration. [ Conclusion The expression level of pIkB-α protein was improved under the simulation of IEC-6 by LPS, while EPS could effectively inhibit the expression of pIkB-α protein. The expression level of pIkB-α was the lowest in the LPS ＋500 μg/ml EPS group.
基金Supported by Science and Technology Support Program of Science and Technology Department of Hebei Province(14826613D)Project of Qinhuangdao Academy of Agricultural Sciences(2014-04)Project of Qinghuangdao Municipal Science and Technology Bureau(201502A054)
文摘In this study, histopathological changes in the heart, liver, spleen, lung, kidney, intestine, brain and other organs of foxes died of parvovims infection were observed. According to the results, multiple organs of infected foxes were congested and hemorrhaged with tissue damage, inflammatory cell infiltration and a series of pathological changes, mainly exhibiting hepatic cell cord rupture, liver cell granular degeneration and fatty degeneration, small intestinal mucous mem- brane shedding, intestinal villi necrosis and shedding, severe hemorrhage of lamina pmpria with inflammatory cell infiltration, and severe small intestinal bleeding. This study laid a solid foundation for clinical diagnosis, prevention and treatment of parvovirus infection in foxes.
基金supported by the National Natural Science Foundation of China(Grant Nos.62272093,62137001,U1811261,and 61902055).
文摘Knowledge tracing aims to track students’knowledge status over time to predict students’future performance accurately.In a real environment,teachers expect knowledge tracing models to provide the interpretable result of knowledge status.Markov chain-based knowledge tracing(MCKT)models,such as Bayesian Knowledge Tracing,can track knowledge concept mastery probability over time.However,as the number of tracked knowledge concepts increases,the time complexity of MCKT predicting student performance increases exponentially(also called explaining away problem).When the number of tracked knowledge concepts is large,we cannot utilize MCKT to track knowledge concept mastery probability over time.In addition,the existing MCKT models only consider the relationship between students’knowledge status and problems when modeling students’responses but ignore the relationship between knowledge concepts in the same problem.To address these challenges,we propose an inTerpretable pRobAbilistiC gEnerative moDel(TRACED),which can track students’numerous knowledge concepts mastery probabilities over time.To solve explain away problem,we design long and short-term memory(LSTM)-based networks to approximate the posterior distribution,predict students’future performance,and propose a heuristic algorithm to train LSTMs and probabilistic graphical model jointly.To better model students’exercise responses,we proposed a logarithmic linear model with three interactive strategies,which models students’exercise responses by considering the relationship among students’knowledge status,knowledge concept,and problems.We conduct experiments with four real-world datasets in three knowledge-driven tasks.The experimental results show that TRACED outperforms existing knowledge tracing methods in predicting students’future performance and can learn the relationship among students,knowledge concepts,and problems from students’exercise sequences.We also conduct several case studies.The case studies show that TRACED exhibits excellent interpretability and thus has the potential for personalized automatic feedback in the real-world educational environment.
基金This work was partly supported by the National Grand Fundamental Research 973 Program of China （2015CB358700）, the National Natural Science Foundation of China （Grant Nos. 61422205, 61472198）, Beijing Higher Education Young Elite Teacher Project（YETP0105）, Tsinghua-Tencent Joint Laboratory for Internet In- novation Technology, ＂NEXT Research Center＂, Singapore （WBS：R-252- 300-001-490）, Huawei, Shenzhou, FDCT/ll6/2013/A3, MYRG105（Y1- L3）-FST13-GZ, National High-Tech R＆D （863） Program of China （2012AA012600）, and the Chinese Special Project of Science and Tech- nology （2013zx01039-002-002）.
文摘String similarity search and join are two impor- tant operations in data cleaning and integration, which ex- tend traditional exact search and exact join operations in databases by tolerating the errors and inconsistencies in the data. They have many real-world applications, such as spell checking, duplicate detection, entity resolution, and webpage clustering. Although these two problems have been exten- sively studied in the recent decade, there is no thorough sur- vey. In this paper, we present a comprehensive survey on string similarity search and join. We first give the problem definitions and introduce widely-used similarity functions to quantify the similarity. We then present an extensive set of algorithms for siring similarity search and join. We also dis- cuss their variants, including approximate entity extraction, type-ahead search, and approximate substring matching. Fi- nally, we provide some open datasets and summarize some research challenges and open problems.
