[ Objective] This study aimed to explore a Tricine-SDS-PAGE method for separation and purification of Periplaneta Americana small peptides. [ Method] By comparing the separation effects of three types of gels with dif...[ Objective] This study aimed to explore a Tricine-SDS-PAGE method for separation and purification of Periplaneta Americana small peptides. [ Method] By comparing the separation effects of three types of gels with different ratios on P. Americana small peptides, an appropriate Tricine-SDS-PAGE method for separation of small peptides was established. [ Result] Standard low molecular weight Marker was preliminarily separated to a certain extent with polyacrylamide gel electraphoresis, while the sample mixture was not separated due to the different levels of aggregation in separating gel, spacer gel and stacking gel. [Condusion] More appropriate polyacrylamide gel electrephoresis separation method or other better separation methods were to be further explored for separating peptide mixture with smaller molecular weight.展开更多
As data grows in size,search engines face new challenges in extracting more relevant content for users’searches.As a result,a number of retrieval and ranking algorithms have been employed to ensure that the results a...As data grows in size,search engines face new challenges in extracting more relevant content for users’searches.As a result,a number of retrieval and ranking algorithms have been employed to ensure that the results are relevant to the user’s requirements.Unfortunately,most existing indexes and ranking algo-rithms crawl documents and web pages based on a limited set of criteria designed to meet user expectations,making it impossible to deliver exceptionally accurate results.As a result,this study investigates and analyses how search engines work,as well as the elements that contribute to higher ranks.This paper addresses the issue of bias by proposing a new ranking algorithm based on the PageRank(PR)algorithm,which is one of the most widely used page ranking algorithms We pro-pose weighted PageRank(WPR)algorithms to test the relationship between these various measures.The Weighted Page Rank(WPR)model was used in three dis-tinct trials to compare the rankings of documents and pages based on one or more user preferences criteria.Thefindings of utilizing the Weighted Page Rank model showed that using multiple criteria to rankfinal pages is better than using only one,and that some criteria had a greater impact on ranking results than others.展开更多
目的建立一种定量检测人体泪液中溶菌酶含量的方法。方法通过改进的Tricine-SDS-PAGE电泳,分析正常人体天然泪液中分子量在3~30 k Da的蛋白质分布,使泪液溶菌酶与其它泪液蛋白有效分离,用Image J软件对溶菌酶电泳条带进行灰度分析,定量...目的建立一种定量检测人体泪液中溶菌酶含量的方法。方法通过改进的Tricine-SDS-PAGE电泳,分析正常人体天然泪液中分子量在3~30 k Da的蛋白质分布,使泪液溶菌酶与其它泪液蛋白有效分离,用Image J软件对溶菌酶电泳条带进行灰度分析,定量测定其中溶菌酶的含量。结果泪液溶菌酶和其它小分子蛋白可用改进的Tricine-SDS-PAGE电泳有效分离,对于人体泪液中的溶菌酶检测专属性良好;上样量10~30μg范围内,溶菌酶含量和电泳条带灰度面积线性关系良好(r=0.9934);分析17例人体泪液的样本,其中溶菌酶的含量在1.38~3.07 mg/m L。结论改进的Tricine-SDS-PAGE电泳法简单直观,并能批量性的一次分析多个样本,可用于科研及临床上人体泪液中溶菌酶的含量检测。展开更多
The basic idea behind a personalized web search is to deliver search results that are tailored to meet user needs, which is one of the growing concepts in web technologies. The personalized web search presented in thi...The basic idea behind a personalized web search is to deliver search results that are tailored to meet user needs, which is one of the growing concepts in web technologies. The personalized web search presented in this paper is based on exploiting the implicit feedbacks of user satisfaction during her web browsing history to construct a user profile storing the web pages the user is highly interested in. A weight is assigned to each page stored in the user’s profile;this weight reflects the user’s interest in this page. We name this weight the relative rank of the page, since it depends on the user issuing the query. Therefore, the ranking algorithm provided in this paper is based on the principle that;the rank assigned to a page is the addition of two rank values R_rank and A_rank. A_rank is an absolute rank, since it is fixed for all users issuing the same query, it only depends on the link structures of the web and on the keywords of the query. Thus, it could be calculated by the PageRank algorithm suggested by Brin and Page in 1998 and used by the google search engine. While, R_rank is the relative rank, it is calculated by the methods given in this paper which depends mainly on recording implicit measures of user satisfaction during her previous browsing history.展开更多
基金Supported by National Natural Science Foundation of China ( 30560181)Key Industry Innovation Project of Yunnan Province ( 2008IF012)
文摘[ Objective] This study aimed to explore a Tricine-SDS-PAGE method for separation and purification of Periplaneta Americana small peptides. [ Method] By comparing the separation effects of three types of gels with different ratios on P. Americana small peptides, an appropriate Tricine-SDS-PAGE method for separation of small peptides was established. [ Result] Standard low molecular weight Marker was preliminarily separated to a certain extent with polyacrylamide gel electraphoresis, while the sample mixture was not separated due to the different levels of aggregation in separating gel, spacer gel and stacking gel. [Condusion] More appropriate polyacrylamide gel electrephoresis separation method or other better separation methods were to be further explored for separating peptide mixture with smaller molecular weight.
文摘As data grows in size,search engines face new challenges in extracting more relevant content for users’searches.As a result,a number of retrieval and ranking algorithms have been employed to ensure that the results are relevant to the user’s requirements.Unfortunately,most existing indexes and ranking algo-rithms crawl documents and web pages based on a limited set of criteria designed to meet user expectations,making it impossible to deliver exceptionally accurate results.As a result,this study investigates and analyses how search engines work,as well as the elements that contribute to higher ranks.This paper addresses the issue of bias by proposing a new ranking algorithm based on the PageRank(PR)algorithm,which is one of the most widely used page ranking algorithms We pro-pose weighted PageRank(WPR)algorithms to test the relationship between these various measures.The Weighted Page Rank(WPR)model was used in three dis-tinct trials to compare the rankings of documents and pages based on one or more user preferences criteria.Thefindings of utilizing the Weighted Page Rank model showed that using multiple criteria to rankfinal pages is better than using only one,and that some criteria had a greater impact on ranking results than others.
文摘The basic idea behind a personalized web search is to deliver search results that are tailored to meet user needs, which is one of the growing concepts in web technologies. The personalized web search presented in this paper is based on exploiting the implicit feedbacks of user satisfaction during her web browsing history to construct a user profile storing the web pages the user is highly interested in. A weight is assigned to each page stored in the user’s profile;this weight reflects the user’s interest in this page. We name this weight the relative rank of the page, since it depends on the user issuing the query. Therefore, the ranking algorithm provided in this paper is based on the principle that;the rank assigned to a page is the addition of two rank values R_rank and A_rank. A_rank is an absolute rank, since it is fixed for all users issuing the same query, it only depends on the link structures of the web and on the keywords of the query. Thus, it could be calculated by the PageRank algorithm suggested by Brin and Page in 1998 and used by the google search engine. While, R_rank is the relative rank, it is calculated by the methods given in this paper which depends mainly on recording implicit measures of user satisfaction during her previous browsing history.