The purpose of this study was to understand the overall level of key competencies of medical students and explore the potential profile of key competencies, promoting quality education, and improving the quality talen...The purpose of this study was to understand the overall level of key competencies of medical students and explore the potential profile of key competencies, promoting quality education, and improving the quality talent cultivation in medical colleges. A stratified random sampling method selected 734 medical students from four medical colleges in Chongqing Province of China. A general information questionnaire and a key competencies survey questionnaire were used to conduct the survey. The overall score and scores of each dimension of key competencies were analyzed. Latent profile analysis was conducted to classify the key competencies of medical students and compare the distribution differences of demographic variables among different categories. The results showed that 26% of medical students have never heard of the concept of key competencies, and 59% of them are not familiar with the content related to key competencies. The score of key competencies is 3.66 ± 0.60, with the highest score in the dimension of responsibility and the lowest score in the dimension of humanistic accomplishment. The latent profile analysis classified them into three categories: “low key competencies group (14.71%)”, “medium key competencies group (36.79%)”, and “high key competencies group (48.50%)”. The R3STEP regression analysis results showed statistically significant differences in educational level and whether they served as student cadres among different key competencies categories of medical students. This paper discusses three different potential key competencies categories among medical students, and the overall level of key competencies is relatively good. However, medical students lack a comprehensive and systematic understanding of key competencies. Humanistic accomplishment, healthy living, and practical innovation are the three dimensions with lower scores and should be given more attention. Medical colleges should integrate the concept of key competencies into teaching and implement it in medical practice to cultivate more high-quality medical talents for society.展开更多
Older adults’social participation and social relationship may be affected by their partners’cognitive function.In 3,722 cognitively intact married/partnered Health and Retirement Study respondents,latent profile ana...Older adults’social participation and social relationship may be affected by their partners’cognitive function.In 3,722 cognitively intact married/partnered Health and Retirement Study respondents,latent profile analysis identified three social participation profiles(Limited overall social participation(prevalence:69%);Frequent volunteer participation(10%);Frequent non-volunteer participation(21%)),and three social relationship profiles(Social support from all relationships(68%);Mixed social support and strain from all relationships(18%);Social strain from partner with support from other relationships(14%)).Spouse/partner’s cognition was not significantly associated with social participation profiles.Impaired cognition in spouses/partners increased older adults’likelihood of perceiving social strain from their partners with support from other relationships.Frequent volunteer and non-volunteer participation and perceiving social support from all relationships predicted better self-rated health and lower odds of depressive symptoms.These findings highlight the need of community programs that promote social connectedness for older adults living with cognitively impaired spouses/partners.展开更多
This study aimed to perform a systematic review and meta-analysis to determine the LTBI prevalence in prison officers worldwide. A systematic search was performed in PubMed, WoS, Embase, and BVS, including all article...This study aimed to perform a systematic review and meta-analysis to determine the LTBI prevalence in prison officers worldwide. A systematic search was performed in PubMed, WoS, Embase, and BVS, including all articles related to LTBI prevalence and risk factors. After critical evaluation and qualitative synthesis of the identified articles, a meta-analysis was used. Five studies carried out between 2012 and 2022 were included, with a total sample size of 1718 prison officers. The overall LTBI prevalence was 50% [95% confidence interval [CI]: 48% - 52%;n = 816], with high heterogeneity between studies. Smoking [OR = 1.76;CI 95% = 1.26 - 2.46] and males [OR = 2.08;CI 95% = 1.31 - 3.31] were positively related to a higher LTBI prevalence among prison officers. Thus, preventive measures and the rapid and accurate diagnosis of new cases should be emphasized to ensure tuberculosis control, especially among risk groups such as prison officers.展开更多
This study undertakes a thorough analysis of the sentiment within the r/Corona-virus subreddit community regarding COVID-19 vaccines on Reddit. We meticulously collected and processed 34,768 comments, spanning from No...This study undertakes a thorough analysis of the sentiment within the r/Corona-virus subreddit community regarding COVID-19 vaccines on Reddit. We meticulously collected and processed 34,768 comments, spanning from November 20, 2020, to January 17, 2021, using sentiment calculation methods such as TextBlob and Twitter-RoBERTa-Base-sentiment to categorize comments into positive, negative, or neutral sentiments. The methodology involved the use of Count Vectorizer as a vectorization technique and the implementation of advanced ensemble algorithms like XGBoost and Random Forest, achieving an accuracy of approximately 80%. Furthermore, through the Dirichlet latent allocation, we identified 23 distinct reasons for vaccine distrust among negative comments. These findings are crucial for understanding the community’s attitudes towards vaccination and can guide targeted public health messaging. Our study not only provides insights into public opinion during a critical health crisis, but also demonstrates the effectiveness of combining natural language processing tools and ensemble algorithms in sentiment analysis.展开更多
Background:Depressive disorders have become a major risk factor that influences people’s health worldwide,but few studies have focused on the prevalence of depressive disorders among the Chinese elderly and their cha...Background:Depressive disorders have become a major risk factor that influences people’s health worldwide,but few studies have focused on the prevalence of depressive disorders among the Chinese elderly and their characteristics of depressive disorders.The current study is a secondary data analysis designed to explore the profiles of depressive disorders in the Chinese elderly by latent profile analysis.Methods:The China Health and Retirement Longitudinal Study(CHARLS 2018)database will be used for analysis.Latent profile analysis will be employed to identify the profiles of depressive disorders using data from the subsection“CESD Depression”in the section“Cognition and Depression”.Stepwise multinomial logistic regression will be used to explore the influencing factors of different profiles of depressive disorders among the Chinese elderly.Discussion:The prevalence of depressive disorders among the Chinese elderly and their profiles of depressive disorders will be reported.Possible influencing factors may include some demographic characteristics and associated psychological elements,which will provide a reference for further research and precise intervention.展开更多
With the wide application of Web 2.0 and social software, there are more and more tag-related studies and applications. Because of the randomness and the personalization in users' tagging, tag research continues t...With the wide application of Web 2.0 and social software, there are more and more tag-related studies and applications. Because of the randomness and the personalization in users' tagging, tag research continues to encounter data space and semantics obstacles. With the min-max similarity(MMS) to establish the initial centroids, the traditional K-means clustering algorithm is firstly improved to the MMSK-means clustering algorithm, the superiority of which has been tested; based on MMSK-means and combined with latent semantic analysis(LSA), here secondly emerges a new tag clustering algorithm, LMMSK. Finally, three algorithms for tag clustering, MMSK-means, tag clustering based on LSA(LSA-based algorithm) and LMMSK, have been run on Matlab, using a real tag-resource dataset obtained from the Delicious Social Bookmarking System from 2004 to 2009. LMMSK's clustering result turns out to be the most effective and the most accurate.Thus, a better tag-clustering algorithm is found for greater application of social tags in personalized search, topic identification or knowledge community discovery. In addition, for a better comparison of the clustering results, the clustering corresponding results matrix(CCR matrix) is proposed, which is promisingly expected to be an effective tool to capture the evolutions of the social tagging system.展开更多
Body misperception plays an important role in the development of weight and dietary disorders among children and adolescents.A school-based health promotion program(2014-2015)was conducted to promote the school health...Body misperception plays an important role in the development of weight and dietary disorders among children and adolescents.A school-based health promotion program(2014-2015)was conducted to promote the school health education and improve the teenagers'physical health among Chinese children and adolescents.Based on this program,we intended to examine weight status and weight misperception among Chinese children and adolescents and to explore the relationship between weight misperception and lifestyle behaviors.A total of 10708 Chinese children and adolescents in 3rd and 7th grade from Shandong and Qinghai province participated in the program.The participants,dietary and activity patterns were clustered by latent class analysis(LCA).Logistic regression analysis was undertaken to explore the relationship between weight perception and demographic factors or dietary and activity patterns.Given the gender-specific difference of children and adolescents,analyses were separately conducted among boys and girls.The total prevalence of weight misperception was 44.50%.Boys,especially those in higher grade and living in wealthier district,were more likely to misperceive body weight.Girls were more likely to overestimate their weight(26.10%)while boys tended to underestimate the weight(28.32%).Three latent dietary and activity patterns including obesogenic pattern,malnourished pattern and healthy pattern were derived.The participants who had weight misperception were more likely to choose unhealthy dietary and exercise activities.The high prevalence of weight misperception was closely related to the unhealthy weight pattern and unhealthy dietary or exercise patterns.Our research found that most children and adolescents failed to perceive their weight correctly and boys tended to underestimate their weight while girls were subjected to overestimation.So,comprehensive intervention programs should focus on improving self-weight awareness,and appropriate guidance should be made to lead the adolescents to more healthy weight pattern.展开更多
In recent years,multimedia annotation problem has been attracting significant research attention in multimedia and computer vision areas,especially for automatic image annotation,whose purpose is to provide an efficie...In recent years,multimedia annotation problem has been attracting significant research attention in multimedia and computer vision areas,especially for automatic image annotation,whose purpose is to provide an efficient and effective searching environment for users to query their images more easily. In this paper,a semi-supervised learning based probabilistic latent semantic analysis( PLSA) model for automatic image annotation is presenred. Since it's often hard to obtain or create labeled images in large quantities while unlabeled ones are easier to collect,a transductive support vector machine( TSVM) is exploited to enhance the quality of the training image data. Then,different image features with different magnitudes will result in different performance for automatic image annotation. To this end,a Gaussian normalization method is utilized to normalize different features extracted from effective image regions segmented by the normalized cuts algorithm so as to reserve the intrinsic content of images as complete as possible. Finally,a PLSA model with asymmetric modalities is constructed based on the expectation maximization( EM) algorithm to predict a candidate set of annotations with confidence scores. Extensive experiments on the general-purpose Corel5k dataset demonstrate that the proposed model can significantly improve performance of traditional PLSA for the task of automatic image annotation.展开更多
Emotions of users do not converge in a single application but are scattered across diverse applications.Mobile devices are the closest media for handling user data and these devices have the advantage of integrating p...Emotions of users do not converge in a single application but are scattered across diverse applications.Mobile devices are the closest media for handling user data and these devices have the advantage of integrating private user information and emotions spread over different applications.In this paper,we first analyze user profile on a mobile device by describing the problem of the user sentiment profile system in terms of data granularity,media diversity,and server-side solution.Fine-grained data requires additional data and structural analysis in mobile devices.Media diversity requires standard parameters to integrate user data from various applications.A server-side solution presents a potential risk when handling individual privacy information.Therefore,in order to overcome these problems,we propose a general-purposed user profile system based on sentiment analysis that extracts individual emotional preferences by comparing the difference between public and individual data based on particular features.The proposed system is built based on a sentiment hierarchy,which is created by using unstructured data on mobile devices.It can compensate for the concentration of single media,and analyze individual private data without the invasion of privacy on mobile devices.展开更多
This paper discusses the utilization of latent variable modeling related to occupational health and safety in the mining industry.Latent variable modeling,which is a statistical model that relates observable and laten...This paper discusses the utilization of latent variable modeling related to occupational health and safety in the mining industry.Latent variable modeling,which is a statistical model that relates observable and latent variables,could be used to facilitate researchers’understandings of the underlying constructs or hypothetical factors and their magnitude of effect that constitute a complex system.This enhanced understanding,in turn,can help emphasize the important factors to improve mine safety.The most commonly used techniques include the exploratory factor analysis(EFA),the confirmatory factor analysis(CFA)and the structural equation model with latent variables(SEM).A critical comparison of the three techniques regarding mine safety is provided.Possible applications of latent variable modeling in mining engineering are explored.In this scope,relevant research papers were reviewed.They suggest that the application of such methods could prove useful in mine accident and safety research.Application of latent variables analysis in cognitive work analysis was proposed to improve the understanding of human-work relationships in mining operations.展开更多
In order to detect the molecular mechanism of heterosis in pigs, the mRNA differential display technique was performed to investigate the differences of gene expression in the Longissimus dorsi tissue from Meishan, Me...In order to detect the molecular mechanism of heterosis in pigs, the mRNA differential display technique was performed to investigate the differences of gene expression in the Longissimus dorsi tissue from Meishan, Meishan × Large White hybrid and Large White pigs with nine 3’-end anchored primers in combination with ten 5’-end arbitrary primers and nearly 3000 reproducible bands were examined. One novel expressed sequence tag (EST4, GenBank accession number: AY553914) that was differentially expressed in Meishan, Meishan× Large White hybrid and Large White pigs was isolated from the Longissimus dorsi muscle tissue and identified through semi-quantitative RT-PCR. BLAST analysis revealed that the 350 bp long EST (EST4) was not homologous to any of the known porcine genes. Tissue expression profile analyses showed that the EST4 was expressed in most of tissues.LIU Yong-gang, Ph D展开更多
Latent class analysis (LCA) is a widely used statistical technique for identifying subgroups in the population based upon multiple indicator variables. It has a number of advantages over other unsupervised grouping pr...Latent class analysis (LCA) is a widely used statistical technique for identifying subgroups in the population based upon multiple indicator variables. It has a number of advantages over other unsupervised grouping procedures such as cluster analysis, including stronger theoretical underpinnings, more clearly defined measures of model fit, and the ability to conduct confirmatory analyses. In addition, it is possible to ascertain whether an LCA solution is equally applicable to multiple known groups, using invariance assessment techniques. This study compared the effectiveness of multiple statistics for detecting group LCA invariance, including a chi-square difference test, a bootstrap likelihood ratio test, and several information indices. Results of the simulation study found that the bootstrap likelihood ratio test was the optimal invariance assessment statistic. In addition to the simulation, LCA group invariance assessment was demonstrated in an application with the Youth Risk Behavior Survey (YRBS). Implications of the simulation results for practice are discussed.展开更多
The abundance of social networking platforms has increased the frequency and the availability for which individuals communicate with one another. The feasibility and accessibility to go online to find sexual partners ...The abundance of social networking platforms has increased the frequency and the availability for which individuals communicate with one another. The feasibility and accessibility to go online to find sexual partners pose opportunity for contracting sexually transmitted infections (STI) in the absence of safe sexual practices. Low condom use has been reported among young adults who seek sexual partners online. African American young adults have some of the highest rates of infection for certain STIs. In order to mitigate the incidence and prevalence of STIs in at-risk populations, sexually active young adults must use condoms consistently and correctly during sexual activities. The present study sought to uncover the heterogeneity within African American young adults regarding their online networking utilization, STI knowledge, and sexual risk behavior. African American young adults (N = 236), ages 18 - 23, completed private online survey administration. Using latent class analysis, three classes were identified: Social Network Communicators (43%;N = 101), Social Networking Daters (36%;N = 83), and Media Sharers (21%;N = 52). Social Networking Daters exhibited the highest probability of using online dating sites daily, low STI knowledge, and a zero probability of consistent condom use. All three groups exhibited relatively low STI knowledge. Furthermore, having a history of STI increased the likelihood of being classified into the Social Networking Daters class relative to the other classes. Findings highlight the need to capitalize upon online platforms for African American young adults who utilize online dating sites and other online environments.展开更多
We analyzed profiles of IgG autoantibodies to 16 cardiac specific proteins and their main immunogenic region B-epitopes, in the groups of already verified cardiac pathology: acute and chronic lymphocytic myocarditis, ...We analyzed profiles of IgG autoantibodies to 16 cardiac specific proteins and their main immunogenic region B-epitopes, in the groups of already verified cardiac pathology: acute and chronic lymphocytic myocarditis, ST elevation myocardial infarction, postinfarction remodeling of myocardium, dilated cardiomyopathy and in healthy controls along with patients, suffered from gastritis (to evaluate immune response against cross-reactive B-epitopes). AAB specific patterns allowed us to distinguish cases among themselves by means of multiparametrical canonical discriminant analysis in approximately 95% of cases. Positive predictive value in the group of MYO reached 95%, in the STEMI—89%, in the PIR—99%, in the DCM—99%, in the group of gastritis—88%. Principal component analysis of mentioned cardiac pathologies extended current clinical knowledge of their immunopathogenesis. Obtained data markedly proved a usability of serum AAB profiling for non invasive screening, differential diagnostics and working hypothesis composition.展开更多
ncRNAs have been identified as potential regulatory molecules and have multiple biological roles. Aberrant expression of specific ncRNAs contributes to multiple biological processes and many human diseases. Herein, we...ncRNAs have been identified as potential regulatory molecules and have multiple biological roles. Aberrant expression of specific ncRNAs contributes to multiple biological processes and many human diseases. Herein, we simultaneously profiled miRNA, lncRNA and mRNA in human HepG2 and L02 cells applying high-throughput sequencing and micro-array technologies. Abnormal miRNA, lncRNA and mRNA profiles were assessed through fold change filtering. A cross-platform integrated analysis method was developed to analyze differentially expressed miRNA, lncRNA and mRNA profiles. miRNA-mRNA interaction was analyzed according to their functional relationships. Target mRNAs of aberrantly expressed miRNAs were obtained from experimentally validated datasets or predicted using some programs. Generally, multiple target mRNAs were involved, and they have versatile roles by functional enrichment analysis. Ac-cording to actual expression datasets in the study, compared to deregulated miRNAs, these theoretical target mRNAs showed various expression patterns. The consistent or inconsistent expression was mainly derived from complex, mul-tiple, flexible and alternative regulatory relationships between miRNA and mRNA. Further, miRNA/mRNA and lncRNA were completely surveyed based on their location distributions on human chromosomes. Many miRNA-lncRNA and mRNA-lncRNA pairs always were located on the same strand or different strands in the specific genomic region. Due to the location distributions, they might have partly or completely overlapped regions or they could be reverse complementarily binding. These miRNA/mRNA-lncRNA pairs showed consistent or inconsistent expression pat-terns, although they might have functional relationships through reverse complementarily binding events. Moreover, we also detected and analyzed various isomiRs from a given miRNA locus, including those isomiRs with 3’ additional non-template nucleotides. These isomiRs, especially for those 5’ isomiRs with the new “seed sequences” through “seed shifting” events, maybe have potential biological roles as well as isomiR repertoire and their expression patterns. The integrative analysis provides potential functional relationships between miRNA, lncRNA and mRNA across different datasets. The complex and various expression patterns suggest a robust regulatory network across different regulatory molecules and their targets.展开更多
Current research on metaphor analysis is generally knowledge-based and corpus-based,which calls for methods of automatic feature extraction and weight calculation.Combining natural language processing(NLP),latent sema...Current research on metaphor analysis is generally knowledge-based and corpus-based,which calls for methods of automatic feature extraction and weight calculation.Combining natural language processing(NLP),latent semantic analysis(LSA),and Pearson correlation coefficient,this paper proposes a metaphor analysis method for extracting the content words from both literal and metaphorical corpus,calculating correlation degree,and analyzing their relationships.The value of the proposed method was demonstrated through a case study by using a corpus with keyword“飞翔(fly)”.When compared with the method of Pearson correlation coefficient,the experiment shows that the LSA can produce better results with greater significance in correlation degree.It is also found that the number of common words that appeared in both literal and metaphorical word bags decreased with the correlation degree.The case study also revealed that there are more nouns appear in literal corpus,and more adjectives and adverbs appear in metaphorical corpus.The method proposed will benefit NLP researchers to develop the required step-by-step calculation tools for accurate quantitative analysis.展开更多
Cotton(Gossypium hirsutum L.) is the leading fiber crop and one of the mainstays of the economy in the world.Cotton fibers,as the main product of cotton plants,are unicellular,linear
The validity of the concept of coastal equilibritun depends upon a pnd of the ekistence of equilibrium. In addition, the methods of calculating the actual equilibrium profile and the response time are rempred. This st...The validity of the concept of coastal equilibritun depends upon a pnd of the ekistence of equilibrium. In addition, the methods of calculating the actual equilibrium profile and the response time are rempred. This study evaluates equilibriuzn conditions using evidence from EOF (empirical orthogonal function) analysis of the coased profile data (bed slopes and associated elevations) obtained from Poole and Christchurch Bays, southem England. The preliminary results show tha the larges eigenvalue is much greater than the other eigenvalues and the temporally-related eigenfunction is staionary;thes observation implies the existence of wilibrium. Further, the spatially-related eigenfunction associated with the largest eigenvalue is used to calculate the actual beach profile at equilibrium. Although the temporal eigenfopction may nuctuate, it recovers rapidly, indicating tha the response time is short. However, further studies are required to determine the response hme accurately.展开更多
With the development of globalization and information technology,online company profile has been an effective commu-nication channel between companies and their target customers or clients.Online company profile,as a ...With the development of globalization and information technology,online company profile has been an effective commu-nication channel between companies and their target customers or clients.Online company profile,as a specific genre,has the dis-tinct features and functions in commercial activities.This study aims to do linguistic study of the constitution and the role of thesecompany profiles about sporting goods for communication on the Internet.To realize it,six company profiles have been selectedfrom the official websites of each sports company.The genre analysis of these samples is conducted from the perspective ofHasan’s Contextual Configuration(CC)and Generic Structure Potential(GSP).This thesis attempts to give the suggestions on howto compose a company profile for readers and sporting companies and the reference for the related researches in the future.展开更多
文摘The purpose of this study was to understand the overall level of key competencies of medical students and explore the potential profile of key competencies, promoting quality education, and improving the quality talent cultivation in medical colleges. A stratified random sampling method selected 734 medical students from four medical colleges in Chongqing Province of China. A general information questionnaire and a key competencies survey questionnaire were used to conduct the survey. The overall score and scores of each dimension of key competencies were analyzed. Latent profile analysis was conducted to classify the key competencies of medical students and compare the distribution differences of demographic variables among different categories. The results showed that 26% of medical students have never heard of the concept of key competencies, and 59% of them are not familiar with the content related to key competencies. The score of key competencies is 3.66 ± 0.60, with the highest score in the dimension of responsibility and the lowest score in the dimension of humanistic accomplishment. The latent profile analysis classified them into three categories: “low key competencies group (14.71%)”, “medium key competencies group (36.79%)”, and “high key competencies group (48.50%)”. The R3STEP regression analysis results showed statistically significant differences in educational level and whether they served as student cadres among different key competencies categories of medical students. This paper discusses three different potential key competencies categories among medical students, and the overall level of key competencies is relatively good. However, medical students lack a comprehensive and systematic understanding of key competencies. Humanistic accomplishment, healthy living, and practical innovation are the three dimensions with lower scores and should be given more attention. Medical colleges should integrate the concept of key competencies into teaching and implement it in medical practice to cultivate more high-quality medical talents for society.
文摘Older adults’social participation and social relationship may be affected by their partners’cognitive function.In 3,722 cognitively intact married/partnered Health and Retirement Study respondents,latent profile analysis identified three social participation profiles(Limited overall social participation(prevalence:69%);Frequent volunteer participation(10%);Frequent non-volunteer participation(21%)),and three social relationship profiles(Social support from all relationships(68%);Mixed social support and strain from all relationships(18%);Social strain from partner with support from other relationships(14%)).Spouse/partner’s cognition was not significantly associated with social participation profiles.Impaired cognition in spouses/partners increased older adults’likelihood of perceiving social strain from their partners with support from other relationships.Frequent volunteer and non-volunteer participation and perceiving social support from all relationships predicted better self-rated health and lower odds of depressive symptoms.These findings highlight the need of community programs that promote social connectedness for older adults living with cognitively impaired spouses/partners.
文摘This study aimed to perform a systematic review and meta-analysis to determine the LTBI prevalence in prison officers worldwide. A systematic search was performed in PubMed, WoS, Embase, and BVS, including all articles related to LTBI prevalence and risk factors. After critical evaluation and qualitative synthesis of the identified articles, a meta-analysis was used. Five studies carried out between 2012 and 2022 were included, with a total sample size of 1718 prison officers. The overall LTBI prevalence was 50% [95% confidence interval [CI]: 48% - 52%;n = 816], with high heterogeneity between studies. Smoking [OR = 1.76;CI 95% = 1.26 - 2.46] and males [OR = 2.08;CI 95% = 1.31 - 3.31] were positively related to a higher LTBI prevalence among prison officers. Thus, preventive measures and the rapid and accurate diagnosis of new cases should be emphasized to ensure tuberculosis control, especially among risk groups such as prison officers.
文摘This study undertakes a thorough analysis of the sentiment within the r/Corona-virus subreddit community regarding COVID-19 vaccines on Reddit. We meticulously collected and processed 34,768 comments, spanning from November 20, 2020, to January 17, 2021, using sentiment calculation methods such as TextBlob and Twitter-RoBERTa-Base-sentiment to categorize comments into positive, negative, or neutral sentiments. The methodology involved the use of Count Vectorizer as a vectorization technique and the implementation of advanced ensemble algorithms like XGBoost and Random Forest, achieving an accuracy of approximately 80%. Furthermore, through the Dirichlet latent allocation, we identified 23 distinct reasons for vaccine distrust among negative comments. These findings are crucial for understanding the community’s attitudes towards vaccination and can guide targeted public health messaging. Our study not only provides insights into public opinion during a critical health crisis, but also demonstrates the effectiveness of combining natural language processing tools and ensemble algorithms in sentiment analysis.
文摘Background:Depressive disorders have become a major risk factor that influences people’s health worldwide,but few studies have focused on the prevalence of depressive disorders among the Chinese elderly and their characteristics of depressive disorders.The current study is a secondary data analysis designed to explore the profiles of depressive disorders in the Chinese elderly by latent profile analysis.Methods:The China Health and Retirement Longitudinal Study(CHARLS 2018)database will be used for analysis.Latent profile analysis will be employed to identify the profiles of depressive disorders using data from the subsection“CESD Depression”in the section“Cognition and Depression”.Stepwise multinomial logistic regression will be used to explore the influencing factors of different profiles of depressive disorders among the Chinese elderly.Discussion:The prevalence of depressive disorders among the Chinese elderly and their profiles of depressive disorders will be reported.Possible influencing factors may include some demographic characteristics and associated psychological elements,which will provide a reference for further research and precise intervention.
基金supported by the National Natural Science Foundation of China(7127101871531001)
文摘With the wide application of Web 2.0 and social software, there are more and more tag-related studies and applications. Because of the randomness and the personalization in users' tagging, tag research continues to encounter data space and semantics obstacles. With the min-max similarity(MMS) to establish the initial centroids, the traditional K-means clustering algorithm is firstly improved to the MMSK-means clustering algorithm, the superiority of which has been tested; based on MMSK-means and combined with latent semantic analysis(LSA), here secondly emerges a new tag clustering algorithm, LMMSK. Finally, three algorithms for tag clustering, MMSK-means, tag clustering based on LSA(LSA-based algorithm) and LMMSK, have been run on Matlab, using a real tag-resource dataset obtained from the Delicious Social Bookmarking System from 2004 to 2009. LMMSK's clustering result turns out to be the most effective and the most accurate.Thus, a better tag-clustering algorithm is found for greater application of social tags in personalized search, topic identification or knowledge community discovery. In addition, for a better comparison of the clustering results, the clustering corresponding results matrix(CCR matrix) is proposed, which is promisingly expected to be an effective tool to capture the evolutions of the social tagging system.
基金This study was supported by grants from the National Natural Science Foundation of China(No.81573262)the Fundamental Research Funds for the Central Universities,HUST(No.2016YXZD042).
文摘Body misperception plays an important role in the development of weight and dietary disorders among children and adolescents.A school-based health promotion program(2014-2015)was conducted to promote the school health education and improve the teenagers'physical health among Chinese children and adolescents.Based on this program,we intended to examine weight status and weight misperception among Chinese children and adolescents and to explore the relationship between weight misperception and lifestyle behaviors.A total of 10708 Chinese children and adolescents in 3rd and 7th grade from Shandong and Qinghai province participated in the program.The participants,dietary and activity patterns were clustered by latent class analysis(LCA).Logistic regression analysis was undertaken to explore the relationship between weight perception and demographic factors or dietary and activity patterns.Given the gender-specific difference of children and adolescents,analyses were separately conducted among boys and girls.The total prevalence of weight misperception was 44.50%.Boys,especially those in higher grade and living in wealthier district,were more likely to misperceive body weight.Girls were more likely to overestimate their weight(26.10%)while boys tended to underestimate the weight(28.32%).Three latent dietary and activity patterns including obesogenic pattern,malnourished pattern and healthy pattern were derived.The participants who had weight misperception were more likely to choose unhealthy dietary and exercise activities.The high prevalence of weight misperception was closely related to the unhealthy weight pattern and unhealthy dietary or exercise patterns.Our research found that most children and adolescents failed to perceive their weight correctly and boys tended to underestimate their weight while girls were subjected to overestimation.So,comprehensive intervention programs should focus on improving self-weight awareness,and appropriate guidance should be made to lead the adolescents to more healthy weight pattern.
基金Supported by the National Program on Key Basic Research Project(No.2013CB329502)the National Natural Science Foundation of China(No.61202212)+1 种基金the Special Research Project of the Educational Department of Shaanxi Province of China(No.15JK1038)the Key Research Project of Baoji University of Arts and Sciences(No.ZK16047)
文摘In recent years,multimedia annotation problem has been attracting significant research attention in multimedia and computer vision areas,especially for automatic image annotation,whose purpose is to provide an efficient and effective searching environment for users to query their images more easily. In this paper,a semi-supervised learning based probabilistic latent semantic analysis( PLSA) model for automatic image annotation is presenred. Since it's often hard to obtain or create labeled images in large quantities while unlabeled ones are easier to collect,a transductive support vector machine( TSVM) is exploited to enhance the quality of the training image data. Then,different image features with different magnitudes will result in different performance for automatic image annotation. To this end,a Gaussian normalization method is utilized to normalize different features extracted from effective image regions segmented by the normalized cuts algorithm so as to reserve the intrinsic content of images as complete as possible. Finally,a PLSA model with asymmetric modalities is constructed based on the expectation maximization( EM) algorithm to predict a candidate set of annotations with confidence scores. Extensive experiments on the general-purpose Corel5k dataset demonstrate that the proposed model can significantly improve performance of traditional PLSA for the task of automatic image annotation.
基金This work was supported by Institute of Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2019-0-00231,Development of artificial intelligence based video security technology and systems for public infrastructure safety).
文摘Emotions of users do not converge in a single application but are scattered across diverse applications.Mobile devices are the closest media for handling user data and these devices have the advantage of integrating private user information and emotions spread over different applications.In this paper,we first analyze user profile on a mobile device by describing the problem of the user sentiment profile system in terms of data granularity,media diversity,and server-side solution.Fine-grained data requires additional data and structural analysis in mobile devices.Media diversity requires standard parameters to integrate user data from various applications.A server-side solution presents a potential risk when handling individual privacy information.Therefore,in order to overcome these problems,we propose a general-purposed user profile system based on sentiment analysis that extracts individual emotional preferences by comparing the difference between public and individual data based on particular features.The proposed system is built based on a sentiment hierarchy,which is created by using unstructured data on mobile devices.It can compensate for the concentration of single media,and analyze individual private data without the invasion of privacy on mobile devices.
基金Natural Sciences and Engineering Research Council of Canada(NSERC)(ID:236482)for supporting this research
文摘This paper discusses the utilization of latent variable modeling related to occupational health and safety in the mining industry.Latent variable modeling,which is a statistical model that relates observable and latent variables,could be used to facilitate researchers’understandings of the underlying constructs or hypothetical factors and their magnitude of effect that constitute a complex system.This enhanced understanding,in turn,can help emphasize the important factors to improve mine safety.The most commonly used techniques include the exploratory factor analysis(EFA),the confirmatory factor analysis(CFA)and the structural equation model with latent variables(SEM).A critical comparison of the three techniques regarding mine safety is provided.Possible applications of latent variable modeling in mining engineering are explored.In this scope,relevant research papers were reviewed.They suggest that the application of such methods could prove useful in mine accident and safety research.Application of latent variables analysis in cognitive work analysis was proposed to improve the understanding of human-work relationships in mining operations.
文摘In order to detect the molecular mechanism of heterosis in pigs, the mRNA differential display technique was performed to investigate the differences of gene expression in the Longissimus dorsi tissue from Meishan, Meishan × Large White hybrid and Large White pigs with nine 3’-end anchored primers in combination with ten 5’-end arbitrary primers and nearly 3000 reproducible bands were examined. One novel expressed sequence tag (EST4, GenBank accession number: AY553914) that was differentially expressed in Meishan, Meishan× Large White hybrid and Large White pigs was isolated from the Longissimus dorsi muscle tissue and identified through semi-quantitative RT-PCR. BLAST analysis revealed that the 350 bp long EST (EST4) was not homologous to any of the known porcine genes. Tissue expression profile analyses showed that the EST4 was expressed in most of tissues.LIU Yong-gang, Ph D
文摘Latent class analysis (LCA) is a widely used statistical technique for identifying subgroups in the population based upon multiple indicator variables. It has a number of advantages over other unsupervised grouping procedures such as cluster analysis, including stronger theoretical underpinnings, more clearly defined measures of model fit, and the ability to conduct confirmatory analyses. In addition, it is possible to ascertain whether an LCA solution is equally applicable to multiple known groups, using invariance assessment techniques. This study compared the effectiveness of multiple statistics for detecting group LCA invariance, including a chi-square difference test, a bootstrap likelihood ratio test, and several information indices. Results of the simulation study found that the bootstrap likelihood ratio test was the optimal invariance assessment statistic. In addition to the simulation, LCA group invariance assessment was demonstrated in an application with the Youth Risk Behavior Survey (YRBS). Implications of the simulation results for practice are discussed.
文摘The abundance of social networking platforms has increased the frequency and the availability for which individuals communicate with one another. The feasibility and accessibility to go online to find sexual partners pose opportunity for contracting sexually transmitted infections (STI) in the absence of safe sexual practices. Low condom use has been reported among young adults who seek sexual partners online. African American young adults have some of the highest rates of infection for certain STIs. In order to mitigate the incidence and prevalence of STIs in at-risk populations, sexually active young adults must use condoms consistently and correctly during sexual activities. The present study sought to uncover the heterogeneity within African American young adults regarding their online networking utilization, STI knowledge, and sexual risk behavior. African American young adults (N = 236), ages 18 - 23, completed private online survey administration. Using latent class analysis, three classes were identified: Social Network Communicators (43%;N = 101), Social Networking Daters (36%;N = 83), and Media Sharers (21%;N = 52). Social Networking Daters exhibited the highest probability of using online dating sites daily, low STI knowledge, and a zero probability of consistent condom use. All three groups exhibited relatively low STI knowledge. Furthermore, having a history of STI increased the likelihood of being classified into the Social Networking Daters class relative to the other classes. Findings highlight the need to capitalize upon online platforms for African American young adults who utilize online dating sites and other online environments.
文摘We analyzed profiles of IgG autoantibodies to 16 cardiac specific proteins and their main immunogenic region B-epitopes, in the groups of already verified cardiac pathology: acute and chronic lymphocytic myocarditis, ST elevation myocardial infarction, postinfarction remodeling of myocardium, dilated cardiomyopathy and in healthy controls along with patients, suffered from gastritis (to evaluate immune response against cross-reactive B-epitopes). AAB specific patterns allowed us to distinguish cases among themselves by means of multiparametrical canonical discriminant analysis in approximately 95% of cases. Positive predictive value in the group of MYO reached 95%, in the STEMI—89%, in the PIR—99%, in the DCM—99%, in the group of gastritis—88%. Principal component analysis of mentioned cardiac pathologies extended current clinical knowledge of their immunopathogenesis. Obtained data markedly proved a usability of serum AAB profiling for non invasive screening, differential diagnostics and working hypothesis composition.
文摘ncRNAs have been identified as potential regulatory molecules and have multiple biological roles. Aberrant expression of specific ncRNAs contributes to multiple biological processes and many human diseases. Herein, we simultaneously profiled miRNA, lncRNA and mRNA in human HepG2 and L02 cells applying high-throughput sequencing and micro-array technologies. Abnormal miRNA, lncRNA and mRNA profiles were assessed through fold change filtering. A cross-platform integrated analysis method was developed to analyze differentially expressed miRNA, lncRNA and mRNA profiles. miRNA-mRNA interaction was analyzed according to their functional relationships. Target mRNAs of aberrantly expressed miRNAs were obtained from experimentally validated datasets or predicted using some programs. Generally, multiple target mRNAs were involved, and they have versatile roles by functional enrichment analysis. Ac-cording to actual expression datasets in the study, compared to deregulated miRNAs, these theoretical target mRNAs showed various expression patterns. The consistent or inconsistent expression was mainly derived from complex, mul-tiple, flexible and alternative regulatory relationships between miRNA and mRNA. Further, miRNA/mRNA and lncRNA were completely surveyed based on their location distributions on human chromosomes. Many miRNA-lncRNA and mRNA-lncRNA pairs always were located on the same strand or different strands in the specific genomic region. Due to the location distributions, they might have partly or completely overlapped regions or they could be reverse complementarily binding. These miRNA/mRNA-lncRNA pairs showed consistent or inconsistent expression pat-terns, although they might have functional relationships through reverse complementarily binding events. Moreover, we also detected and analyzed various isomiRs from a given miRNA locus, including those isomiRs with 3’ additional non-template nucleotides. These isomiRs, especially for those 5’ isomiRs with the new “seed sequences” through “seed shifting” events, maybe have potential biological roles as well as isomiR repertoire and their expression patterns. The integrative analysis provides potential functional relationships between miRNA, lncRNA and mRNA across different datasets. The complex and various expression patterns suggest a robust regulatory network across different regulatory molecules and their targets.
基金Fundamental Research Funds for the Central Universities of Ministry of Education of China(No.19D111201)。
文摘Current research on metaphor analysis is generally knowledge-based and corpus-based,which calls for methods of automatic feature extraction and weight calculation.Combining natural language processing(NLP),latent semantic analysis(LSA),and Pearson correlation coefficient,this paper proposes a metaphor analysis method for extracting the content words from both literal and metaphorical corpus,calculating correlation degree,and analyzing their relationships.The value of the proposed method was demonstrated through a case study by using a corpus with keyword“飞翔(fly)”.When compared with the method of Pearson correlation coefficient,the experiment shows that the LSA can produce better results with greater significance in correlation degree.It is also found that the number of common words that appeared in both literal and metaphorical word bags decreased with the correlation degree.The case study also revealed that there are more nouns appear in literal corpus,and more adjectives and adverbs appear in metaphorical corpus.The method proposed will benefit NLP researchers to develop the required step-by-step calculation tools for accurate quantitative analysis.
基金This work was supported by the National Natural Science Foundation of China (No 30370904and No 30671258)the National High Technology Research and Development Program(863 project)of China (No 2006AA10Z121)the Program for New Century Excellent Talents in University(No NCET-07-0712)
文摘Cotton(Gossypium hirsutum L.) is the leading fiber crop and one of the mainstays of the economy in the world.Cotton fibers,as the main product of cotton plants,are unicellular,linear
文摘The validity of the concept of coastal equilibritun depends upon a pnd of the ekistence of equilibrium. In addition, the methods of calculating the actual equilibrium profile and the response time are rempred. This study evaluates equilibriuzn conditions using evidence from EOF (empirical orthogonal function) analysis of the coased profile data (bed slopes and associated elevations) obtained from Poole and Christchurch Bays, southem England. The preliminary results show tha the larges eigenvalue is much greater than the other eigenvalues and the temporally-related eigenfunction is staionary;thes observation implies the existence of wilibrium. Further, the spatially-related eigenfunction associated with the largest eigenvalue is used to calculate the actual beach profile at equilibrium. Although the temporal eigenfopction may nuctuate, it recovers rapidly, indicating tha the response time is short. However, further studies are required to determine the response hme accurately.
文摘With the development of globalization and information technology,online company profile has been an effective commu-nication channel between companies and their target customers or clients.Online company profile,as a specific genre,has the dis-tinct features and functions in commercial activities.This study aims to do linguistic study of the constitution and the role of thesecompany profiles about sporting goods for communication on the Internet.To realize it,six company profiles have been selectedfrom the official websites of each sports company.The genre analysis of these samples is conducted from the perspective ofHasan’s Contextual Configuration(CC)and Generic Structure Potential(GSP).This thesis attempts to give the suggestions on howto compose a company profile for readers and sporting companies and the reference for the related researches in the future.
