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Evaluation of surface latent heat and sensible heat fluxes from ERA-5,GLDAS,and MODIS on different underlying surfaces in the Tibetan Plateau
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作者 LAN Xincan YIN Yongsheng +4 位作者 TANG Jiale LIAN Yuanyuan ZHAO Fang WANG Yumeng ZHENG Zhixian 《Journal of Mountain Science》 2025年第1期230-245,共16页
Surface-latent heat(LE)and sensible heat(SH)fluxes play a pivotal role in governing hydrological,biological,geochemical,and ecological processes on the land surface in the Tibetan Plateau.However,to accurately assess ... Surface-latent heat(LE)and sensible heat(SH)fluxes play a pivotal role in governing hydrological,biological,geochemical,and ecological processes on the land surface in the Tibetan Plateau.However,to accurately assess and understand the spatial distribution of LE and SH fluxes across different underlying surfaces,it is crucial to verify the validity and reliability of ERA-5,GLDAS,and MODIS data against ground measurements obtained from the Flux Net micrometeorological tower network.This study analyzed the spatial patterns of LE and SH over the Tibetan Plateau using data from ERA-5,GLDAS,and MODIS.The results were compared with ground measurements from Flux Net tower observations on different underlying surfaces,and five statistical parameters(Pearson's r,LR slope,RMSE,MBE,and MAE)were used to validate the data.The results showed that:(1)MODIS LE data and ERA-5 SH data exhibited the closest agreement with ground observations,as indicated by their lowest root mean square error and mean bias area values.(2)The accuracy of ERA-5 SH was the highest in meadows and steppes,while GLDAS SH performed optimally in shrublands.Notably,MODIS LE consistently outperformed the other datasets across all vegetation types.(3)The spatial distribution of LE and SH displayed considerable heterogeneity,contingent upon the specific data sources and underlying surfaces.Notably,there was a contrasting trend between GLDAS and ERA-5,as well as MODIS,in terms of SH distribution in the shrubland.In shrublands and meadows,MODIS SH and LE exhibited more pronounced changes than ERA-5 and GLDAS.Additionally,ERA-5 SH demonstrated the opposite variation in meadow and steppe regions compared to GLDAS and MODIS. 展开更多
关键词 FLUXNET ERA-5 GLDAS MODIS latent and sensible heat flux(LE and SH) Tibetan Plateau
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Determination of Latent Heats of Vaporization and Fusion
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作者 Lahbib Abbas Lahcen Bih +3 位作者 Khalid Yamni Abderrahim Elyahyaouy Abdelmalik El Attaoui Zahra Ramzi 《Advances in Chemical Engineering and Science》 CAS 2024年第3期113-124,共12页
Water is the most abundant liquid on the surface of the earth. It is a liquid whose properties are quite surprising, both as a pure liquid and as a solvent. Water is a very cohesive liquid: its melting and vaporizatio... Water is the most abundant liquid on the surface of the earth. It is a liquid whose properties are quite surprising, both as a pure liquid and as a solvent. Water is a very cohesive liquid: its melting and vaporization temperatures are very high for a liquid that is neither ionic nor metallic, and whose molar mass is low. Thus, water remains liquid at atmospheric pressure up to 100C while similar molecules such as H2S, H2Se, H2Te for example would give a vaporization temperature close to 80C. This cohesion is in fact ensured by hydrogen bonds between water molecules. This type of bonds between neighboring molecules, hydrogen bonds, is quite often found in chemistry [1] [2]. Any change in the state of aggregation of a substance occurs with the absorption or release of a certain amount of latent heat of transformation. Latent heat of fusion, vaporization or sublimation is the ratio of the energy supplied as heat to the mass of the substance that is melted, vaporized or sublimated. As a result of the reversibility of the processes, the fusion heat is equal to the heat released in the reverse process: crystallization and solidification heat. And likewise the heat of vaporization is equal to the heat of condensation. This equality of heat is often used to determine experimentally either of these quantities. There are two main measurement methods: 1) Direct measurement using the calorimeter, 2) Indirect measure based on the use of the VantHoff relationship. The objective of this work is to measure the latent heat of water vaporization and verify the compatibility of the experimental values with the values given by the tables using the indirect method. 展开更多
关键词 latent Heat of Vaporization latent Heat of Fusion CALORIMETRY Relationship of Vant’Hoff
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Discovering Latent Variables for the Tasks With Confounders in Multi-Agent Reinforcement Learning
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作者 Kun Jiang Wenzhang Liu +2 位作者 Yuanda Wang Lu Dong Changyin Sun 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第7期1591-1604,共14页
Efficient exploration in complex coordination tasks has been considered a challenging problem in multi-agent reinforcement learning(MARL). It is significantly more difficult for those tasks with latent variables that ... Efficient exploration in complex coordination tasks has been considered a challenging problem in multi-agent reinforcement learning(MARL). It is significantly more difficult for those tasks with latent variables that agents cannot directly observe. However, most of the existing latent variable discovery methods lack a clear representation of latent variables and an effective evaluation of the influence of latent variables on the agent. In this paper, we propose a new MARL algorithm based on the soft actor-critic method for complex continuous control tasks with confounders. It is called the multi-agent soft actor-critic with latent variable(MASAC-LV) algorithm, which uses variational inference theory to infer the compact latent variables representation space from a large amount of offline experience.Besides, we derive the counterfactual policy whose input has no latent variables and quantify the difference between the actual policy and the counterfactual policy via a distance function. This quantified difference is considered an intrinsic motivation that gives additional rewards based on how much the latent variable affects each agent. The proposed algorithm is evaluated on two collaboration tasks with confounders, and the experimental results demonstrate the effectiveness of MASAC-LV compared to other baseline algorithms. 展开更多
关键词 latent variable model maximum entropy multi-agent reinforcement learning(MARL) multi-agent system
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Latent Categories of Mental Health Literacy in Patients with Coronary Artery Disease and Their Relationship with Quality of Life
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作者 Jing Zhao Qiuju Shan +5 位作者 Panpan Wang Yongxia Mei Zhiguang Ping Zhenzhen Wang Miaoliu Lian Yikai Liu 《Journal of Biosciences and Medicines》 2024年第11期592-604,共13页
Objectives: This study aims to explore the latent categories of mental health literacy among patients with coronary artery disease and examine their associations with quality of life. Design: A cross-sectional quantit... Objectives: This study aims to explore the latent categories of mental health literacy among patients with coronary artery disease and examine their associations with quality of life. Design: A cross-sectional quantitative design was used. Methods: The study sample consisted of 208 patients with coronary artery disease from five wards in the Department of Cardiology at a tertiary hospital. Data were collected using a general information questionnaire, the Chinese version of the Multiple Mental Health Literacy Scale and the Chinese Cardiovascular Patient Quality of Life Assessment Questionnaire. The data were analysed with Mplus (v.8.3) and SPSS (v.25.0). Results: The mental health literacy of the 208 patients was categorised into four latent categories: low literacy (n = 28, 13.5%), high knowledge-low resources (n = 53, 25.5%), low knowledge-high resources (n = 63, 30.2%) and high literacy (n = 64, 30.8%). A significant difference in quality of life was observed according to mental health literacy category (P Conclusion: The quality of life of patients with coronary artery disease is significantly influenced by their levels of mental health literacy. Targeted interventions addressing the various profiles of mental health literacy should be implemented to improve the quality of life for patients with coronary artery disease. 展开更多
关键词 Coronary Artery Disease latent Categories Mental Health Literacy
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Evaluating the Efficacy of Latent Variables in Mitigating Data Poisoning Attacks in the Context of Bayesian Networks:An Empirical Study
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作者 Shahad Alzahrani Hatim Alsuwat Emad Alsuwat 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第5期1635-1654,共20页
Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among variables.However,the reliability and integrity of learned Bayesian network models are highly dependent ... Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among variables.However,the reliability and integrity of learned Bayesian network models are highly dependent on the quality of incoming data streams.One of the primary challenges with Bayesian networks is their vulnerability to adversarial data poisoning attacks,wherein malicious data is injected into the training dataset to negatively influence the Bayesian network models and impair their performance.In this research paper,we propose an efficient framework for detecting data poisoning attacks against Bayesian network structure learning algorithms.Our framework utilizes latent variables to quantify the amount of belief between every two nodes in each causal model over time.We use our innovative methodology to tackle an important issue with data poisoning assaults in the context of Bayesian networks.With regard to four different forms of data poisoning attacks,we specifically aim to strengthen the security and dependability of Bayesian network structure learning techniques,such as the PC algorithm.By doing this,we explore the complexity of this area and offer workablemethods for identifying and reducing these sneaky dangers.Additionally,our research investigates one particular use case,the“Visit to Asia Network.”The practical consequences of using uncertainty as a way to spot cases of data poisoning are explored in this inquiry,which is of utmost relevance.Our results demonstrate the promising efficacy of latent variables in detecting and mitigating the threat of data poisoning attacks.Additionally,our proposed latent-based framework proves to be sensitive in detecting malicious data poisoning attacks in the context of stream data. 展开更多
关键词 Bayesian networks data poisoning attacks latent variables structure learning algorithms adversarial attacks
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Impact of Assimilating FY-4A Lightning Data with a Latent Heat Nudging Method on Short-Term Forecasts of Severe Convective Events in Eastern China
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作者 Yanqing GAO Xiaofeng WANG Wei GUO 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第12期2478-2494,共17页
In this study,a latent heat nudging lightning data assimilation(LDA)method independent of the flash rate was developed and tested with data from the Lightning Mapping Imager(LMI)onboard the Feng-Yun-4A(FY-4A)satellite... In this study,a latent heat nudging lightning data assimilation(LDA)method independent of the flash rate was developed and tested with data from the Lightning Mapping Imager(LMI)onboard the Feng-Yun-4A(FY-4A)satellite based on the Weather Research and Forecasting(WRF)model.In this LDA method,the positive temperature perturbations at the lightning location are first calculated by the difference between the moist adiabatic temperature of a lifted air parcel and the model temperature.The positive temperature perturbations in the mixed-phase region are then assimilated by a nudging method to adjust the latent heat within the convective system.Meanwhile,the water vapor mixing ratio is adapted to the temperature perturbations accordingly to constrain the relative humidity to remain unchanged.This method considers the physical nature of the convective system,in contrast with other LDA methods that establish an empirical or statistical relationship between the lightning flash rates and model variables.The impact of this LDA method on short-term(≤6 h)forecasts was evaluated using two severe convective events in eastern China:a multi-region heavy rainfall event and a thunderstorm high-wind event.The results showed that LDA could add thermodynamic information associated with the convective system to the WRF model during the nudging period,leading to a more reasonable storm environment.In the forecast fields,the simulations with LDA produced more realistic convective structures,resulting in an improvement in forecasts of precipitation and high winds. 展开更多
关键词 FY-4A LMI lightning data assimilation latent heat nudging numerical weather prediction
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Network analysis of adolescent non-suicidal self-injury subgroups identified through latent profile analysis
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作者 Wei Yang Kun Lian +3 位作者 Yu-Qi Cheng Xiu-Feng Xu Xin-Cen Duan Xu You 《World Journal of Psychiatry》 SCIE 2024年第12期1936-1946,共11页
BACKGROUND Non-suicidal self-injury(NSSI)is common among adolescents and frequently cooccurs with depression.Understanding the distinct patterns of NSSI behaviors,along with their associated risk and protective factor... BACKGROUND Non-suicidal self-injury(NSSI)is common among adolescents and frequently cooccurs with depression.Understanding the distinct patterns of NSSI behaviors,along with their associated risk and protective factors,is crucial for developing effective interventions.AIM To classify NSSI behaviors and examine interactions between risk and resilience factors in Chinese adolescents.METHODS A cross-sectional study involving 3967 Chinese students(51.7%female,mean age 13.58±2.24 years)who completed questionnaires on parenting styles,bullying,childhood maltreatment,depression,resilience,and NSSI.Latent profile analysis(LPA)was used to identify NSSI subtypes,and network analysis explored interactions between risk and resilience factors.RESULTS Three NSSI subtypes were identified:NSSI with depression(18.8%),NSSI without depression(12.3%),and neither(68.9%).Bullying was the central risk factor across subtypes,while emotional control and family support were key protective factors.Statistical analyses showed significant differences between groups(P<0.001).CONCLUSION This study identified three NSSI subtypes among Chinese adolescents.Bullying emerged as a central risk factor,while emotional control and family support were key protective factors.Targeting these areas may help reduce NSSI behaviors in this population. 展开更多
关键词 Non-suicidal self-injury ADOLESCENT Network analysis latent profile analysis RESILIENCE
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From immunology to artificial intelligence: revolutionizing latent tuberculosis infection diagnosis with machine learning
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作者 Lin-Sheng Li Ling Yang +3 位作者 Li Zhuang Zhao-Yang Ye Wei-Guo Zhao Wen-Ping Gong 《Military Medical Research》 SCIE CAS CSCD 2024年第5期747-784,共38页
Latent tuberculosis infection(LTBI)has become a major source of active tuberculosis(ATB).Although the tuberculin skin test and interferon-gamma release assay can be used to diagnose LTBI,these methods can only differe... Latent tuberculosis infection(LTBI)has become a major source of active tuberculosis(ATB).Although the tuberculin skin test and interferon-gamma release assay can be used to diagnose LTBI,these methods can only differentiate infected individuals from healthy ones but cannot discriminate between LTBI and ATB.Thus,the diagnosis of LTBI faces many challenges,such as the lack of effective biomarkers from Mycobacterium tuberculosis(MTB)for distinguishing LTBI,the low diagnostic efficacy of biomarkers derived from the human host,and the absence of a gold standard to differentiate between LTBI and ATB.Sputum culture,as the gold standard for diagnosing tuberculosis,is time-consuming and cannot distinguish between ATB and LTBI.In this article,we review the pathogenesis of MTB and the immune mechanisms of the host in LTBI,including the innate and adaptive immune responses,multiple immune evasion mechanisms of MTB,and epigenetic regulation.Based on this knowledge,we summarize the current status and challenges in diagnosing LTBI and present the application of machine learning(ML)in LTBI diagnosis,as well as the advantages and limitations of ML in this context.Finally,we discuss the future development directions of ML applied to LTBI diagnosis. 展开更多
关键词 Tuberculosis(TB) latent tuberculosis infection(LTBI) Machine learning(ML) Biomarkers Differential diagnosis
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A process monitoring method for autoregressive-dynamic inner total latent structure projection
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作者 CHEN Yalin KONG Xiangyu LUO Jiayu 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第5期1326-1336,共11页
As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decompos... As a dynamic projection to latent structures(PLS)method with a good output prediction ability,dynamic inner PLS(DiPLS)is widely used in the prediction of key performance indi-cators.However,due to the oblique decomposition of the input space by DiPLS,there are false alarms in the actual industrial process during fault detection.To address the above problems,a dynamic modeling method based on autoregressive-dynamic inner total PLS(AR-DiTPLS)is proposed.The method first uses the regression relation matrix to decompose the input space orthogonally,which reduces useless information for the predic-tion output in the quality-related dynamic subspace.Then,a vector autoregressive model(VAR)is constructed for the predic-tion score to separate dynamic information and static informa-tion.Based on the VAR model,appropriate statistical indicators are further constructed for online monitoring,which reduces the occurrence of false alarms.The effectiveness of the method is verified by a Tennessee-Eastman industrial simulation process and a three-phase flow system. 展开更多
关键词 dynamic characteristic fault detection feature extraction process monitoring projection to latent structure(PLS) quality-related spatial partitioning
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Internet Gaming Disorder and Mental Health of Children in China:A Latent Profile Analysis
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作者 Md Zahir Ahmed Oli Ahmed +2 位作者 Lingfeng Gao Mary C.Jobe Weijian Li 《International Journal of Mental Health Promotion》 2024年第7期517-529,共13页
In recent years,speculation of an increase in Internet Gaming Disorder(IGD)has surfaced with the growing popularity of internet gaming among Chinese children and adolescents.The detrimental impact of IGD on mental hea... In recent years,speculation of an increase in Internet Gaming Disorder(IGD)has surfaced with the growing popularity of internet gaming among Chinese children and adolescents.The detrimental impact of IGD on mental health cannot be denied,even though only a small portion of the screen-dependent population exhibits psychopathological and behavioral symptoms.The present study aimed to explore a latent profile analysis(LPA)of Internet Gaming Disorder on the mental health of Chinese school students.The data were collected from a sample of 1005 Chinese school students(49.8%male;age M=13.32,SD=1.34 years)using a paper-pencil survey through convenience sampling.LPA explored three latent profiles of internet gamers:regular gamers(62.4%),moderate gamers(28.1%),and probable disordered gamers(9.4%).Results showed that the probable disordered gamers had significantly higher levels of depression,anxiety,emotional and conduct problems,hyperactivity,and peer problem symptoms as well as lower life satisfaction,and pro-social symptoms compared to regular and moderate gamers(p<0.05).This study would be helpful to mental health professionals in designing interventions for gamers who present IGD symptoms.Future longitudinal studies should also be undertaken to assess whether mental health worsens for probable disordered gamers. 展开更多
关键词 Internet gaming disorder latent profile analysis mental health children and adolescents China
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Prevalence of Latent Tuberculosis Infection [LTBI] in Prison Officers: A Systematic Review and Meta-Analysis
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作者 Thiago Poss Moreira Gustavo Henrique Baraca Sanvezzo +5 位作者 Maico Trevisol Renan William Mesquita Luiza Scalcon de Oliveira Lia Beatriz Henke de Azevedo Cleide Viviane Buzanello Martins Lirane Elize Defante Ferreto 《Open Journal of Respiratory Diseases》 2024年第1期12-24,共13页
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
关键词 latent Tuberculosis Mycobacterium tuberculosis META-ANALYSIS PREVALENCE Occupational Exposure
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Current Status of Key Competencies among Medical Students: A Latent Profile Analysis
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作者 Mengyao Xiao Li Yan +1 位作者 Yongping Xia Li Liu 《Open Journal of Applied Sciences》 2024年第2期450-465,共16页
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
关键词 Sustainable Education Medical Students Key Competencies latent Profile Analysis
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A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data
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作者 Jiufang Chen Kechen Liu +4 位作者 Xin Luo Ye Yuan Khaled Sedraoui Yusuf Al-Turki MengChu Zhou 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第11期2220-2235,共16页
High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation lear... High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation learning to an HDI matrix,whose hyper-parameter adaptation can be implemented through a particle swarm optimizer(PSO) to meet scalable requirements.However, conventional PSO is limited by its premature issues,which leads to the accuracy loss of a resultant LFA model. To address this thorny issue, this study merges the information of each particle's state migration into its evolution process following the principle of a generalized momentum method for improving its search ability, thereby building a state-migration particle swarm optimizer(SPSO), whose theoretical convergence is rigorously proved in this study. It is then incorporated into an LFA model for implementing efficient hyper-parameter adaptation without accuracy loss. Experiments on six HDI matrices indicate that an SPSO-incorporated LFA model outperforms state-of-the-art LFA models in terms of prediction accuracy for missing data of an HDI matrix with competitive computational efficiency.Hence, SPSO's use ensures efficient and reliable hyper-parameter adaptation in an LFA model, thus ensuring practicality and accurate representation learning for HDI matrices. 展开更多
关键词 Data science generalized momentum high-dimensional and incomplete(HDI)data hyper-parameter adaptation latent factor analysis(LFA) particle swarm optimization(PSO)
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Characteristics and Influencing Factors of Self- Advocacy in Young and Middle-Aged Patients with Breast Cancer: A Latent Profile Analysis
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作者 Xinyi Wang Shan Zhang +1 位作者 Shaoshun Zhang Yu Bao 《Journal of Clinical and Nursing Research》 2024年第12期147-158,共12页
Objective:To explore the potential categories and influencing factors of self-advocacy in young and middle-aged patients with breast cancer and to provide a theoretical basis for personalized intervention.Methods:From... Objective:To explore the potential categories and influencing factors of self-advocacy in young and middle-aged patients with breast cancer and to provide a theoretical basis for personalized intervention.Methods:From September 2023 to March 2024,314 young and middle-aged breast cancer patients were studied.Female cancer patients were surveyed using the self-advocacy scale,social support rating scale,and chronic health literacy scale.Latent profile analysis was used to investigate the heterogeneity and influencing factors of self-advocacy.Results:Self-advocacy among young and middle-aged breast cancer patients were classified into two potential categories:low advocacy-lack of support(51.7%)and high advocacy-effective communication(48.3%).Binary logistic regression analysis indicated that educational level,per capita monthly income,social support,and health literacy were significant influencing factors of these categories(P<0.05).Conclusion:Self-advocacy in young and middle-aged breast cancer patients demonstrates categorical heterogeneity.Identifying self-advocacy characteristics and implementing targeted intervention strategies—focused on self-efficacy and improving health literacy—can enhance self-advocacy in these patients. 展开更多
关键词 Young and middle-aged Breast cancer SELF-ADVOCACY latent profile analysis
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Temporally Preserving Latent Variable Models:Offline and Online Training for Reconstruction and Interpretation of Fault Data for Gearbox Condition Monitoring
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作者 Ryan Balshaw P.Stephan Heyns +1 位作者 Daniel N.Wilke Stephan Schmidt 《Journal of Dynamics, Monitoring and Diagnostics》 2024年第2期156-177,共22页
Latent variable models can effectively determine the condition of essential rotating machinery without needing labeled data.These models analyze vibration data via an unsupervised learning strategy.Temporal preservati... Latent variable models can effectively determine the condition of essential rotating machinery without needing labeled data.These models analyze vibration data via an unsupervised learning strategy.Temporal preservation is necessary to obtain an informative latent manifold for the fault diagnosis task.In a temporalpreserving context,two approaches exist to develop a condition-monitoring methodology:offline and online.For latent variable models,the available training modes are not different.While many traditional methods use offline training,online training can dynamically adjust the latent manifold,possibly leading to better fault signature extraction from the vibration data.This study explores online training using temporal-preserving latent variable models.Within online training,there are two main methods:one focuses on reconstructing data and the other on interpreting the data components.Both are considered to evaluate how they diagnose faults over time.Using two experimental datasets,the study confirms that models from both training modes can detect changes in machinery health and identify faults even under varying conditions.Importantly,the complementarity of offline and online models is emphasized,reassuring their versatility in fault diagnostics.Understanding the implications of the training approach and the available model formulations is crucial for further research in latent variable modelbased fault diagnostics. 展开更多
关键词 Condition monitoring unsupervised learning latent variable models temporal preservation training approaches
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Latent profile analysis of perceived stress and influencing factors in colorectal cancer patients
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作者 Yu-Yue Tan Yin-Hong Liu +3 位作者 Zhi-Hui Zhang Wei-Rong Huang Man-Lin Yan Xian-Rong Li 《Frontiers of Nursing》 2024年第3期303-312,共10页
Objective:To understand the latent categories of perceived stress in colorectal cancer patients and analyze the characteristics of different categories of patients.Methods:A total of 255 colorectal cancer patients rec... Objective:To understand the latent categories of perceived stress in colorectal cancer patients and analyze the characteristics of different categories of patients.Methods:A total of 255 colorectal cancer patients receiving treatment in the gastrointestinal surgery and oncology depar tments of a ter tiary Grade A hospital in Sichuan Province,from January 2023 to June 2023,were selected as the study subjects.General information questionnaire,Chinese version of the Perceived Stress Scale(CPSS),and Comprehensive Score Table for Patient-Repor ted Outcome Measures of Economic Toxicity(COST-PROM)were used for data collection.Results:Perceived stress in colorectal cancer patients was classified into 3 latent categories:C1“Low stress-stable type”(19.2%),C2“Moderate stress-uncontrolled type”(23.9%),and C3“High stress-anxious type”(56.9%).The average score of perceived stress was(34.07±5.08).Compared with C1 type,patients with a monthly household income of≤3000 RMB were more likely to belong to the C2 and C3 types(P<0.05),and patients without a stoma were less likely to belong to C3 type(P<0.05).Compared with C2 type,male patients were more likely to belong to C3 type(P<0.05),and patients without a stoma were less likely to belong to C3 type(P<0.05).Compared with C3 type,patients with higher economic toxicity scores were more likely to be classified into C1 and C2 types(P<0.05).Conclusions:Perceived stress in colorectal cancer patients exhibits distinct categorical features.Male gender,lower income,presence of a stoma,and higher economic toxicity are associated with higher levels of perceived stress in colorectal cancer patients. 展开更多
关键词 colorectal cancer economic toxicity influence factors latent profile analysis perceived stress
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Multi-Modal Medical Image Fusion Based on Improved Parameter Adaptive PCNN and Latent Low-Rank Representation
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作者 Zirui Tang Xianchun Zhou 《Instrumentation》 2024年第2期53-63,共11页
Multimodal medical image fusion can help physicians provide more accurate treatment plans for patients, as unimodal images provide limited valid information. To address the insufficient ability of traditional medical ... Multimodal medical image fusion can help physicians provide more accurate treatment plans for patients, as unimodal images provide limited valid information. To address the insufficient ability of traditional medical image fusion solutions to protect image details and significant information, a new multimodality medical image fusion method(NSST-PAPCNNLatLRR) is proposed in this paper. Firstly, the high and low-frequency sub-band coefficients are obtained by decomposing the source image using NSST. Then, the latent low-rank representation algorithm is used to process the low-frequency sub-band coefficients;An improved PAPCNN algorithm is also proposed for the fusion of high-frequency sub-band coefficients. The improved PAPCNN model was based on the automatic setting of the parameters, and the optimal method was configured for the time decay factor αe. The experimental results show that, in comparison with the five mainstream fusion algorithms, the new algorithm has significantly improved the visual effect over the comparison algorithm,enhanced the ability to characterize important information in images, and further improved the ability to protect the detailed information;the new algorithm has achieved at least four firsts in six objective indexes. 展开更多
关键词 image fusion improved parameter adaptive pcnn non-subsampled shear-wave transform latent low-rank representation
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一种将中医辨证规则定量化的无监督学习方法:约束隐结构分析
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作者 许玉龙 陈锦华 +3 位作者 陈周荣 朱红磊 吕雅丽 张连文 《中医药信息》 2025年第1期12-18,共7页
目的:通过设计约束隐结构分析方法解决经典隐结构分析得到规则中分值与语义不相符问题,将主症、次症作为约束语义加入分析过程,得到更符合语义的辨证规则。方法:将主症、次症约束语义用条件概率表示,加入隐结构分析的寻优过程,采用块坐... 目的:通过设计约束隐结构分析方法解决经典隐结构分析得到规则中分值与语义不相符问题,将主症、次症作为约束语义加入分析过程,得到更符合语义的辨证规则。方法:将主症、次症约束语义用条件概率表示,加入隐结构分析的寻优过程,采用块坐标梯度上升方法进行寻优,能够得到含有主症、次症约束的辨证规则模型,即约束隐结构分析。结果:通过设计约束隐结构分析方法,并将其用程序实现加入到隐结构分析软件(孔明灯)中,针对胃肠湿热的症状数据,分别使用隐结构和约束隐结构进行对比分析,结果显示,约束隐结构方法得到模型规则能较好地反映主症、次症的特点,不存在分值过大、过小或为负分的情况,较经典隐结构得到的规则更符合中医理论,也更具有真实量化意义。结论:约束隐结构分析是经典隐结构分析方法的改进,能得到符合主症、次症约束语义的辨证规则,有助于中医辨证论治的推广应用。 展开更多
关键词 隐结构 约束隐结构 辨证规则 中医证候
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社区失能老年人家庭照护潜类别分析及与居家照护安全的关系
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作者 曹松梅 肖峰 +3 位作者 梁怡青 黄欢欢 柏素萍 赵庆华 《护理学杂志》 北大核心 2025年第2期90-94,共5页
目的探讨社区失能老人家庭照护类型,分析不同家庭照护类型对居家照护安全结局的影响。方法采用便利抽样法选取镇江市436对社区失能老人及照护者为调查对象,采用一般资料调查表、Katz指数量表、简明精神认知状态问卷、照护者负担简明问... 目的探讨社区失能老人家庭照护类型,分析不同家庭照护类型对居家照护安全结局的影响。方法采用便利抽样法选取镇江市436对社区失能老人及照护者为调查对象,采用一般资料调查表、Katz指数量表、简明精神认知状态问卷、照护者负担简明问卷、中文版家庭照护者照护能力量表和居家照护不良事件发生情况调查表进行调查。对社区失能老人及照护者的家庭照护类型进行潜类别分析,并通过稳健三步法探讨亚群划分的影响因素,采用Lanza方法探讨不同亚群的居家照护不良事件发生概率。结果识别出4种社区失能老人家庭照护类型:轻失能良认知-强照护型(15.1%)、重失能-中照护型(32.8%)、重失能-弱照护型(15.1%)、重失能良认知-中照护型(36.9%)。老人年龄、慢性病种类、子女数量、家庭经济状况及照护者性别、照护者文化程度、照护负担是亚群分类的影响因素(均P<0.05);重失能-弱照护型发生居家照护不良事件的概率最高(P<0.05)。结论社区失能老人家庭照护类型存在异质性,其影响了居家照护安全结局。根据家庭照护类型采取针对性策略是提升居家照护安全的关键。 展开更多
关键词 失能老年人 家庭照护者 居家照护 安全 照护能力 照护负担 不良事件 潜类别分析
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双车道公路超车行为安全研究进展
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作者 戢晓峰 俸才梅 +2 位作者 李武 韩春阳 覃文文 《安全与环境学报》 北大核心 2025年第1期21-40,共20页
双车道公路超车行为作为一项复杂且极为危险的驾驶行为,可能导致严重的交通事故,已成为驾驶行为研究中的热点和难点问题。聚焦双车道公路超车行为安全,运用潜在狄利克雷分配(Latent Dirichlet Allocation,LDA)模型对该领域的潜在研究主... 双车道公路超车行为作为一项复杂且极为危险的驾驶行为,可能导致严重的交通事故,已成为驾驶行为研究中的热点和难点问题。聚焦双车道公路超车行为安全,运用潜在狄利克雷分配(Latent Dirichlet Allocation,LDA)模型对该领域的潜在研究主题进行了归纳总结,梳理了超车视距评估与间隙接受决策行为建模、超车安全影响因素与碰撞风险评估、超车持续时间及交通仿真建模、超车碰撞预警系统安全分析4个主题的研究进展。结果表明:双车道公路超车行为安全研究总体上面临数据获取的难度、模型参数选择的不确定性、实际应用中的复杂性等局限性,主要体现在超车事故数据以及多车结队超车、弯道超车等非常规超车场景下的现场观测数据支撑较为薄弱;影响超车安全的道路、环境、驾驶员等因素难以被全面捕捉,增加了模型参数选择的不确定性;面对现实交通环境的复杂动态变化,超车模型的实时性、敏感性可能不足。在总结现有研究局限性的基础上,认为未来研究应从4个方面重点改进:一是完善超车视距的可靠性分析方法,拓展智能网联背景下的动态超车视距和间隙接受决策研究;二是强化多维因素对超车安全耦合影响机制的挖掘,构建超车风险的动态演化分析方法;三是深入解析异质交通流状态下超车持续时间与超车风险的关系,着力开发针对双车道公路超车的交通仿真软件;四是完善超车碰撞预警系统的微观驾驶行为和宏观交通运行影响分析,提升超车碰撞预警系统的集成应用研究。 展开更多
关键词 安全工程 双车道公路超车行为 研究进展 潜在狄利克雷分配模型 交通仿真
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