Evaluating the Efficacy of Latent Variables in Mitigating Data Poisoning Attacks in the Context of Bayesian Networks:An Empirical Study

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.

Prevalence of Latent Tuberculosis Infection [LTBI] in Prison Officers: A Systematic Review and Meta-Analysis

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.

Current Status of Key Competencies among Medical Students: A Latent Profile Analysis

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.

A semantic and emotion-based dual latent variable generation model for a dialogue system

With the development of intelligent agents pursuing humanisation,artificial intelligence must consider emotion,the most basic spiritual need in human interaction.Traditional emotional dialogue systems usually use an external emotional dictionary to select appropriate emotional words to add to the response or concatenate emotional tags and semantic features in the decoding step to generate appropriate responses.However,selecting emotional words from a fixed emotional dictionary may result in loss of the diversity and consistency of the response.We propose a semantic and emotion-based dual latent variable generation model(Dual-LVG)for dialogue systems,which is able to generate appropriate emotional responses without an emotional dictionary.Different from previous work,the conditional variational autoencoder(CVAE)adopts the standard transformer structure.Then,Dual-LVG regularises the CVAE latent space by introducing a dual latent space of semantics and emotion.The content diversity and emotional accuracy of the generated responses are improved by learning emotion and semantic features respectively.Moreover,the average attention mechanism is adopted to better extract semantic features at the sequence level,and the semi-supervised attention mechanism is used in the decoding step to strengthen the fusion of emotional features of the model.Experimental results show that Dual-LVG can successfully achieve the effect of generating different content by controlling emotional factors.

Mg-3Al-1Zn alloy deformed along different strain paths: Role of latent hardening

The mechanical properties of magnesium alloy AZ31 were investigated experimentally with visco-plastic self-consistent modeling. Tension,compression and plane strain compression(PSC) tests were performed along 3 directions of a hot rolled plate, and the material parameters input in the model were fitted with the uniaxial stress-strain curves. The critical resolved shear stress(CRSS) for tension twinning was modeled with a modified Voce hardening law first decreasing, and then increasing with strain, that could reproduce better the flow stress for twin-predominant deformation. Such CRSS evolution may better model twin nucleation, propagation and growth. Firstly simulations were carried out assuming latent hardening coefficients for slip by other slip systems equal to self-hardening. Then different heterogeneous latent hardening were used, whose values were based on dislocation dynamics simulations from the literature. This study shows that equal self and latent hardening can reproduce the stress strain curves and plastic anisotropy as well as heterogeneous mode on mode latent hardening.Discrepancies between simulations and experimental results from PSC are explained by an under-estimation of twinning for some PSC strain paths.

Maturity-onset diabetes of the young type 9 or latent autoimmune diabetes in adults:A case report and review of literature

BACKGROUND Maturity-onset diabetes of the young(MODY)is a monogenic genetic disease often clinically misdiagnosed as type 1 or type 2 diabetes.MODY type 9(MODY9)is a rare subtype caused by mutations in the PAX4 gene.Currently,there are limited reports on PAX4-MODY,and its clinical characteristics and treatments are still unclear.In this report,we described a Chinese patient with high autoimmune antibodies,hyperglycemia and a site mutation in the PAX4 gene.CASE SUMMARY A 42-year-old obese woman suffered diabetes ketoacidosis after consuming substantial amounts of beverages.She had never had diabetes before,and no one in her family had it.However,her autoantibody tested positive,and she managed her blood glucose within the normal range for 6 mo through lifestyle interventions.Later,her blood glucose gradually increased.Next-generation sequencing and Sanger sequencing were performed on her family.The results revealed that she and her mother had a heterozygous mutation in the PAX4 gene(c.314G>A,p.R105H),but her daughter did not.The patient is currently taking liraglutide(1.8 mg/d),and her blood glucose levels are under control.Previous cases were retrieved from PubMed to investigate the relationship between PAX4 gene mutations and diabetes.CONCLUSION We reported the first case of a PAX4 gene heterozygous mutation site(c.314G>A,p.R105H),which does not appear pathogenic to MODY9 but may facilitate the progression of latent autoimmune diabetes in adults.

Latent tuberculosis infection in health-care workers in the government sector in Brunei Darussalam:A cross-sectional study

Objective:Health-care workers(HCWs)are known to be at high risk for occupational biological hazards,and this includes exposure to mycobacterium tuberculosis(TB)which can result in either active or latent TB infection(LTBI).This study aims to provide an overview of the incidence of LTBI among HCWs in Brunei Darussalam,to examine associated risk factors,and to evaluate LTBI treatment compliance.Materials and Methods:This is a retrospective cross-sectional study which was conducted using data from January 2018 to December 2021,on notified cases of LTBI in HCWs which identified 115 cases.Demographic data,underlying medical conditions,and compliance to treatment were assessed through reviews of their electronic health records.Results:The incidence of LBTI was 14.6/year/1000 HCWs.The incidence rate reached a high of 24.6/1000 in 2020,and majority of cases were in the older age groups.There was good treatment acceptance and compliance(82.6%),and this was observed to be significantly higher in females than males(P=0.02).Conclusion:This study showed an average incidence of LTBI of 14.6/1000 HCWs over 4 years and high LTBI treatment acceptance(82.6%)and compliance.Emphasis on infection prevention and control measures in health-care settings and actions to increase awareness of LTBI are crucial interventions toward reducing the burden of LTBI.

Chronic Spontaneous Urticaria on Omalizumab Therapy and Latent Tuberculosis Infection: A New Case Report

Background: Chronic Spontaneous urticarial (CSU) is a common dermatological problem characterized by recurrent pruritic or burning wheals last less than 24 hours and treated by many modalities of therapy including systemic antihistamines and in refractory cases with Omalizumab anti-IgE antibody biological injection. Latent tuberculosis infection (LTBI) is diagnosed based on a positive tuberculin skin test or QuantiFERON-TB test without evidence of active tuberculosis. Aim: To document a new case report of a patient with a history of CSU and latent tuberculosis on Omalizumab therapy during Isoniazid (INH) prophylaxis. Case Report: A-53-year-old woman with a history of CSU and newly identified LTBI who have been treated with INH monotherapy before starting Omalizumab injection followed up over 24 weeks course of therapy for any sign of tuberculosis reinfection. Conclusion: Omalizumab injection was used effectively for the treatment of CSU in a patient with latent tuberculosis infection with minimal risk of tuberculosis reactivation.

Modelling of Active and Latent Attributes Based on Traveler Perspectives: Case of Port City of Douala

A growing stream of study stresses the relevance of subjective elements in understanding the hierarchy of preferences that underpin individual travel behavior. The purpose of this study is to evaluate the impact of various factors on mode choice. To achieve this, a multinomial logit model (MNL) was used to analyze the relationships between mode choice and three classes of attributes;Combined Active and Latent, Active only and Latent only attributes. The data used are derived from surveys in the port city of Douala, Cameroon as a case study. Results stipulated that, the combined attributes model performed better than both active only attributes and latent only attributes models. Likewise, latent only attributes model performed better than active only attributes model. The advantage of modelling all three groups is for better selection of the most relevant attributes, and this is very relevant in understanding travel behavior of individuals and mode choice decisions.

Accounting for Heterogeneity in Stop Frequency Models of Work Tours Using Latent Class Poisson Models

Stop frequency models, as one of the elements of activity based models, represent an important part of travel behavior. Unobserved heterogeneity across the travelers should be taken into consideration to prevent biasedness and inconsistency in the estimated parameters in the stop frequency models. Additionally, previous studies on the stop frequency have mostly been done in larger metropolitan areas and less attention has been paid to the areas with less population. This study addresses these gaps by using 2012 travel data from a medium sized U.S. urban area using the work tour for the case study. Stop in the work tour were classified into three groups of outbound leg, work based subtour, and inbound leg of the commutes. Latent Class Poisson Regression Models were used to analyze the data. The results indicate the presence of heterogeneity across the commuters. Using latent class models significantly improves the predictive power of the models compared to regular one class Poisson regression models. In contrast to one class Poisson models, gender becomes insignificant in predicting the number of tours when unobserved heterogeneity is accounted for. The commuters are associated with increased stops on their work based subtour when the employment density of service-related occupations increases in their work zone, but employment density of retail employment does not significantly contribute to the stop making likelihood of the commuters. Additionally, an increase in the number of work tours was associated with fewer stops on the inbound leg of the commute. The results of this study suggest the consideration of unobserved heterogeneity in the stop frequency models and help transportation agencies and policy makers make better inferences from such models.

Latent Growth Mixture Modeling to Estimate Differential PTSD Trajectories and Associated Risk Factors in Psychiatric Staff Following Workplace Violence

Background: Workplace violence (WV) towards psychiatric staff has commonly been associated with Posttraumatic Stress Disorder (PTSD). However, prospective studies have shown that not all psychiatric staff who experience workplace violence experience post-traumatic stress. Purpose: We want to examine the longitudinal trajectories of PTSD in this population to identify possible subgroups that might be more at risk. Furthermore, we need to investigate whether certain risk factors of PTSD might identify membership in the subgroups. Method: In a sample of psychiatric staff from 18 psychiatric wards in Denmark who had reported an incident of WV, we used Latent Growth Mixture Modelling (LGMM) and further logistic regression analysis to investigate this. Results: We found three separate PTSD trajectories: a recovering, a delayed-onset, and a moderate-stable trajectory. Higher social support and negative cognitive appraisals about oneself, the world and self-blame predicted membership in the delayed-onset trajectory, while higher social support and lower accept coping predicted membership in the delayed-onset trajectory. Conclusion: Although most psychiatric staff go through a natural recovery, it is important to be aware of and identify staff members who might be struggling long-term. More focus on the factors that might predict these groups should be an important task for psychiatric departments to prevent posttraumatic symptomatology from work.

Multimodal Medical Image Fusion Based on Parameter Adaptive PCNN and Latent Low-rank Representation

Medical image fusion has been developed as an efficient assistive technology in various clinical applications such as medical diagnosis and treatment planning.Aiming at the problem of insufficient protection of image contour and detail information by traditional image fusion methods,a new multimodal medical image fusion method is proposed.This method first uses non-subsampled shearlet transform to decompose the source image to obtain high and low frequency subband coefficients,then uses the latent low rank representation algorithm to fuse the low frequency subband coefficients,and applies the improved PAPCNN algorithm to fuse the high frequency subband coefficients.Finally,based on the automatic setting of parameters,the optimization method configuration of the time decay factorαe is carried out.The experimental results show that the proposed method solves the problems of difficult parameter setting and insufficient detail protection ability in traditional PCNN algorithm fusion images,and at the same time,it has achieved great improvement in visual quality and objective evaluation indicators.

Effect of Individualized Nursing Intervention on Patients with Tuberculosis Latent Infection and Active Tuberculosis

Objective:This paper aims to explore the effect of individualized nursing intervention on patients with active tuberculosis(ATB)and latent tuberculosis infection(LTBI).Methods:The nursing study started in January 2020 and ended in January 2023.A total of 60 patients with ATB and LTBI were included,and they were divided into two groups according to the intervention schemes selected for control testing,each with 30 cases.The intervention program selected for group A was routine care,and for group B was individualized nursing.The proportion of adverse reactions,changes in the level of lung items,self-management outcomes and satisfaction were evaluated and compared.Results:After evaluating the proportion of adverse reactions,the total proportion of ATB and LTBI in group B was lower than that in group A(P<0.05).Based on the evaluation and testing of the expiratory flow(EF),expiratory volume(EV),and vital capacity(VC)after the intervention,these levels in group B showed higher outcomes than those in group A(P<0.05).The scores in terms of living habits,sleep,diet,and compliance in group B were higher than those in group A(P<0.05).The total proportion of the satisfaction of ATB and LTBI patients in group B was higher than that in group A(P<0.05).Conclusion:After the intervention of individualized nursing measures in patients with ATB and LTBI,it was found that it can not only play a positive role in the prevention and control of adverse reactions,but also improve their lung function,and promote their self-management,with good satisfaction level,thus it has high research and clinical application values.

Paraffin–CaCl_(2)·6H_(2)O dosage effects on the strength and heat transfer characteristics of cemented tailings backfill

The challenge of high temperatures in deep mining remains harmful to the health of workers and their production efficiency The addition of phase change materials (PCMs) to filling slurry and the use of the cold storage function of these materials to reduce downhole temperatures is an effective approach to alleviate the aforementioned problem.Paraffin–CaCl_(2)·6H_(2)O composite PCM was prepared in the laboratory.The composition,phase change latent heat,thermal conductivity,and cemented tailing backfill (CTB) compressive strength of the new material were studied.The heat transfer characteristics and endothermic effect of the PCM were simulated using Fluent software.The results showed the following:(1) The new paraffin–CaCl_(2)·6H_(2)O composite PCM improved the thermal conductivity of native paraffin while avoiding the water solubility of CaCl_(2)·6H_(2)O.(2) The calculation formula of the thermal conductivity of CaCl_(2)·6H_(2)O combined with paraffin was deduced,and the reasons were explained in principle.(3) The“enthalpy–mass scale model”was applied to calculate the phase change latent heat of nonreactive composite PCMs.(4)The addition of the paraffin–CaCl_(2)·6H_(2)O composite PCM reduced the CTB strength but increased its heat absorption capacity.This research can give a theoretical foundation for the use of heat storage backfill in green mines.

陈健教授从“伏火”论治儿童周期性发热综合征经验

[目的]总结陈健教授从“伏火”论治儿童周期性发热综合征的临床经验。[方法]通过门诊跟诊学习、病案收集整理及查阅相关文献,探讨儿童周期性发热综合征的病因病机,总结陈教授从“伏火”论治该病的治疗经验,并举验案一则加以验证。[结果]陈教授认为,儿童周期性发热综合征的核心病机为“伏火”,“伏火”为发病之本,痰、毒、瘀既是病理产物,也是贯穿病程始终的重要致病因素,郁为存在于发病全过程的病理状态。治疗上以益气除热或养阴清热与调气之法并行,并以自拟方药为治疗儿童周期性发热综合征的有效验方。所举验案以周期性发热为主要症状,辨为阴虚发热证,投以养阴清热、行气解郁之法,取得了较好的疗效。[结论]陈教授从“伏火”论治儿童周期性发热综合征,疗效显著,具有一定的指导意义,值得临床参考借鉴。

范永升教授从伏邪温病论治全身型幼年特发性关节炎学术经验探析

[目的]总结首届全国名中医范永升教授治疗全身型幼年特发性关节炎的学术经验。[方法]通过跟诊学习,整理分析典型病案,并参阅相关文献,结合范永升教授的著作及临证所述,从病因病机、治疗思路两个层面总结归纳范永升教授治疗全身型幼年特发性关节炎的学术经验,并附验案一则加以佐证。[结果]范永升教授认为,全身型幼年特发性关节炎发病过程与温病卫气营血转变规律相似,致病特点与伏邪温病也有相似之处,多因正气亏虚于内,加之感受外邪,伏藏于里,伺机而发,或外邪引动而发。临床应用火郁发之,透解伏邪;顾护正气,攻伐有度;续贯治疗,增效减毒等治疗思路治疗本病,取得了满意的临床疗效。验案中患者就诊初期表现为邪伏阴分、气营两燔,治以清解和营、祛风通络;药后疹消热退,伏邪出阳,枢机不利,治以和解枢机、清透郁热;待邪气渐去,正气已衰,遂予以疏解透热,佐以和胃健脾。整个治疗过程中辛透伏邪贯穿始终,同时体现了范永升教授用药灵活、顾护正气的治疗思路。[结论]范永升教授以伏邪温病理论为基础,从卫气营血辨治全身型幼年特发性关节炎临床收效甚佳,其学术经验值得借鉴和推广。

Evaluation of Interferon-Gamma Release Assay Testing and Tuberculin Skin Test for Early Diagnosis of Tuberculosis in Children and Adolescents

Background: This study aimed to evaluate the diagnostic value of interferon-γ release assay (IGRA), a sensitive microbiological diagnostic method, in children and adolescents with suspected tuberculosis in a country with a high burden of tuberculosis. Method: This study included 581 children and adolescents aged 4 - 19 years who were suspected of having tuberculosis, were latently infected with Mycobacterium tuberculosis, and had received at least one dose of BCG vaccine between April 17, 2019, and February 24, 2021. The study evaluated the TST results of 106 patients who had a positive Quantiferon test and were suspected of having tuberculosis. Results: The study included 581 patients aged between 4 and 19 years. Of these, 106 patients tested positive for the Quantiferon test, while 19 were indeterminate and 456 were negative. The Quantiferon test positivity rate was 18.24%. Among the 106 QFT-Plus-positive cases, 23 patients also tested positive for TST. The difference in distribution was found to be statistically significant. Conclusion: The QFT-Plus test is considered an alternative to TST and other microbiological diagnostic methods for early tuberculosis diagnosis, particularly in children and adolescents.

Analysis of Public Sentiment regarding COVID-19 Vaccines on the Social Media Platform Reddit

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.

WJD 5^(th) Anniversary Special Issues(3): Type 1 diabetes Distinct clinical and laboratory characteristics of latent autoimmune diabetes in adults in relation to type 1 and type 2 diabetes mellitus

Ever since its first appearance among the multiple forms of diabetes,latent autoimmune diabetes in adults(LADA),has been the focus of endless discussions concerning mainly its existence as a special type of diabetes.In this mini-review,through browsing important peer-reviewed publications,(original articles and reviews),we will attempt to refresh our knowledge regarding LADA hoping to enhance our understanding of this controversial diabetes entity.A unique combination of immunological,clinical and metabolic characteristics has been identified in this group of patients,namely persistent islet cell antibodies,high frequency of thyroid and gastric autoimmunity,DR3 and DR4 human leukocyte antigen haplotypes,progressive loss of beta cells,adult disease onset,normal weight,defective glycaemic control,and without tendency to ketoacidosis.Although anthropomorphic measurements are useful as a first line screening,the detection of C-peptide levels and the presence of glutamic acid decarboxylase(GAD)autoantibodies is undoubtedly the sine qua non condi-tion for a confirmatory LADA diagnosis.In point of fact,GAD autoantibodies are far from being solely a biomarker and the specific role of these autoantibodies in disease pathogenesis is still to be thoroughly studied.Nevertheless,the lack of diagnostic criteria and guidelines still puzzle the physicians,who struggle between early diagnosis and correct timing for insulin treatment.

Numerical Study of Impacts of Soil Moisture on the Diurnal and Seasonal Cycles of Sensible/Latent Heat Fluxes over Semi-arid Region

The semi-arid regions, as climatic and ecosystem transitional zones, are the most vulnerable to global environmental change. Earlier researches indicate that the semi-arid regions are characterized by strong landatmosphere coupling in which soil moisture is the crucial variable in land surface processes. In this paper, we investigate the sensitivity of the sensible/latent heat fluxes to soil moisture during the growing season based on the enhanced observations at Tongyu in the Jilin province of China, a reference site of international Coordinated Energy and Water Cycle Observations Project （CEOP） in the semi-arid regions, by using a sophisticated land surface model （NCAR_CLM3.0）. Comparisons between the observed and simulated sensible/latent heat fluxes indicate that the soil moisture has obvious effects on the sensible/latent heat fluxes in terms of diurnal cycle and seasonal evolution. Better representation of the soil moisture could improve the model performance to a large degree. Therefore, for the purpose of simulating the land-atmosphere interaction and predicting the climate and water resource changes in semi-arid regions, it is necessary to enhance the description of the soil moisture distribution both in the way of observation and its treatment in land surface models.