Classification of the Stance in Online Debates Using the Dependency Relations Feature

Online discussion forums offer Internet users a medium for discussions about current political debates. The debate is a system of claims regarding interactivity and representation. Users make claims in an online discussion with superior content to support their position. Factual accuracy and emotional appeal are critical attributes used to convince readers. A key challenge in debate forums is to identify the participants’ stance, each of which is inter-dependent and inter-connected. This research work aims to construct a classifier that takes the linguistic features of the posts as input and outputs predictions for the stance label of each post. Three types of features which include Lexical, Dependency, and Morphology are used to detect the stance of the posts. Lexical features such as cue words are employed as surface features, and deep features include dependency and morphology features. Multinomial Naïve Bayes classifier is used to build a model for classifying stance and the Chi-Square method is used to select the good feature set. The performance of the stance classification system is evaluated in terms of accuracy. The result of stance labels for this proposed research represents as for and against by analyzing the surface and deep features that capture the content of a post

Cost-Effectiveness of Long-Acting Injectable Paliperidone Palmitate Versus Haloperidol Decanoate in Maintenance Treatment of Schizophrenia

This study assessed the relative cost-effectiveness of a first generation and a second generation long-acting injectable antipsychotic: haloperidol decanoate (HD) and paliperidone palmitate (PP), respectively

Cost-Effectiveness of Comprehensive, Integrated Care for First Episode Psychosis in the NIMH RAISE Early Treatment Program

This study compares the cost-effectiveness of Navigate (NAV), a comprehensive, multidisciplinary, team-based treatment approach for first episode psychosis (FEP) and usual Community Care (CC) in a cluster randomization trial. Patients at 34 community treatment clinics were randomly assigned to either NAV (N = 223) or CC (N = 181) for 2 years. Effectiveness was measured as a one standard deviation change on the Quality of Life Scale (QLS-SD). Incremental cost effectiveness ratios were evaluated with bootstrap distributions. The Net Health Benefits Approach was used to evaluate the probability that the value of NAV benefits exceeded its costs relative to CC from the perspective of the health care system. The NAV group improved significantly more on the QLS and had higher outpatient mental health and antipsychotic medication costs. The incremental cost-effectiveness ratio was $12 081/QLS-SD, with a .94 probability that NAV was more cost-effective than CC at$40 000/QLS-SD. When converted to monetized Quality Adjusted Life Years, NAV benefits exceeded costs, especially at future generic drug prices

Comprehensive Versus Usual Community Care for First-Episode Psychosis: 2-Year Outcomes From the NIMH RAISE Early Treatment Program

The primary aim was to compare the impact of NAVIGATE, a comprehensive, multidisciplinary, team-based treatment approach for first episode psychosis designed for implementation in the U.S. healthcare system, to Community Care on quality of life

Students Allocation System Based on Fuzzy C-means Algorithms

Cluster is refers to identifying the number ofsubclasses of c-clusters (2d” cd” n). There are two kinds of cpartition of data: hard (or crisp) and soft (or fuzzy) . Twoimportant issues are to consider how to measure the similaritybetween pairs of observations and how to evaluate thepartitions how they are performed. Fuzzy c-means clustering isan extremely powerful classification method to accommodatefuzzy data. The application of Fuzzy set in a classificationfunction causes the class membership to become a relative oneand an project can belong to several classes at the same timebut with different degree. Fuzzy c-means clustering algorithm isused in the system. It is a common practice to allocate studentsof certain subject into number of classes just b their ID number.In this system, allocation activity which applies the Fuzzyclustering bases on each student’s achievement. Students withsimilar achievement are pooled in the same class. On the otherhand , students with significantly different level of achievementwill be in different class. And then, it will be selected suitablelectures according to their subjects. This paper focuses onimprovement of the daily learning process for students

Seroprevalence and associated risk factors of Toxoplasma gondii infection among slaughterhouse workers in Yangon Region, Myanmar: A cross-sectional study

Background Toxoplasmosis, having the significant consequences affecting mortality and quality of life, is still prevalent in various places throughout the world. The major gap in surveillance for Toxoplasma gondii infection among high-risk population, slaughterhouse workers, is an obstacle for the effective policies formulation to reduce the burden of toxoplasmosis in Myanmar. Therefore, this study aimed to assess the seroprevalence of toxoplasmosis and associated factors of seropositivity among slaughterhouse workers in Yangon Region, Myanmar. Methods A cross-sectional study that was conducted from June to November 2020 included 139 slaughterhouse workers involving at five main slaughterhouses under Yangon City Development Committee, Myanmar. The presence of IgG and IgM anti-T. gondii antibodies in serum was detected using the OnSite Toxo IgG/IgM Combo Rapid Test. A face-to-face interview was also performed using pretested structured questionnaires to obtain the detail histories: sociodemographic characteristics, level of knowledge, occupational factors, and environmental factors related to T. gondii infection. Bivariate logistic regression was used to determine the factors associated with T. gondii infection. Results Of all participants, the overall seroprevalence of anti-T. gondii was 43.9% (95% CI: 35.5–52.5%), of whom 98.4% (95% CI: 91.2–100.0%) were reactive only for IgG antibody and 1.6% (95% CI: 0.0–8.8%) were reactive for IgG and IgM antibodies. The significant factors associated with the seropositivity of T. gondii antibodies were blood transfusion history (OR: 5.74, 95% CI: 1.17–28.09), low level of knowledge (OR: 2.91, 95% CI: 1.46–5.83), contact with animal organs, muscles or blood (OR: 14.29, 95% CI: 1.83–111.51), and animals most frequently slaughtered (cattle) (OR: 3.22, 95% CI: 1.16–8.93). Conclusions A high seroprevalence of toxoplasmosis was detected among slaughterhouse workers in Yangon Region and it raises a significant public health concern. Therefore, providing health education regarding toxoplasmosis, enforcement of personal hygiene practices in workplaces, the establishment of training for occupational hygiene, and commencement of the risk assessment and serological screening for toxoplasmosis are crucial to curtail the prevalence of T. gondii infection among slaughterhouse workers