Sentiment analysis in multilingual context: Comparative analysis of machine learning and hybrid deep learning models.

This research paper investigates the efficacy of various machine learning models, including deep learning and hybrid models, for text classification in the English and Bangla languages. The study focuses on sentiment analysis of comments from a popular Bengali e-commerce site, "DARAZ," which comprises both Bangla and translated English reviews. The primary objective of this study is to conduct a comparative analysis of various models, evaluating their efficacy in the domain of sentiment analysis. The research methodology includes implementing seven machine learning models and deep learning models, such as Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Convolutional 1D (Conv1D), and a combined Conv1D-LSTM. Preprocessing techniques are applied to a modified text set to enhance model accuracy. The major conclusion of the study is that Support Vector Machine (SVM) models exhibit superior performance compared to other models, achieving an accuracy of 82.56% for English text sentiment analysis and 86.43% for Bangla text sentiment analysis using the porter stemming algorithm. Additionally, the Bi-LSTM Based Model demonstrates the best performance among the deep learning models, achieving an accuracy of 78.10% for English text and 83.72% for Bangla text using porter stemming. This study signifies significant progress in natural language processing research, particularly for Bangla, by enhancing improved text classification models and methodologies. The results of this research make a significant contribution to the field of sentiment analysis and offer valuable insights for future research and practical applications.

BTSD: A curated transformation of sentence dataset for text classification in Bangla language.

The Bangla Transformation of Sentence Classification dataset addresses the resource gap in natural language processing (NLP) for the Bangla language by providing a curated resource for Bangla sentence classification. With 3,793 annotated sentences, the dataset focuses on categorizing Bangla sentences into Simple, Complex, and Compound classes. It serves as a benchmark for evaluating NLP models on Bangla sentence classification, promoting linguistic diversity and inclusive language models. Collected from publicly accessible Facebook pages, the dataset ensures balanced representation across the categories. Preprocessing steps, including anonymization and duplicate removal, were applied. Three native Bangla speakers independently assessed the Transformation of Sentence labels, enhancing the dataset's reliability. The dataset empowers researchers, practitioners, and developers to build accurate and robust NLP models tailored to the Bangla language. It offers insights into Bangla syntax and structure, benefiting linguistic research. The dataset can be used to train models, uncover patterns in Bangla language usage, and develop effective NLP applications across domains.

Changes in prevalence and risk factors of hypertension among adults in Bangladesh: An analysis of two waves of nationally representative surveys.

INTRODUCTION: Bangladesh is one of the countries where the prevalence of non-communicable diseases (NCDs) such as hypertension is rising due to rising living standards, sedentary lifestyles, and epidemiological transition. Among the NCDs, hypertension is a major risk factor for CVD, accounting for half of all coronary heart disease worldwide. However, detailed research in this area has been limited in Bangladesh. The objective of the study was to estimate changes in the prevalence and risk factors of hypertension among Bangladeshi adult population. The study also sought to identify socioeconomic status-related inequality of hypertension prevalence in Bangladesh. METHODS: Cross-sectional analysis was conducted using nationally representative two waves of the Bangladesh Demographic and Health Survey (BDHS) in 2011 and 2017-18. Survey participants were adults 18 years or older- which included detailed biomarker and anthropometric measurements of 23539 participants. The change in prevalence of hypertension was estimated, and adjusted odds ratios were obtained using multivariable survey logistic regression models. Further, Wagstaff decomposition method was also used to analyze the relative contributions of factors to hypertension. RESULTS: From 2011 to 2018, the hypertension prevalence among adults aged ≥35 years increased from 25.84% to 39.40% (p<0.001), with the largest relative increase (97%) among obese individuals. The prevalence among women remained higher than men whereas the relative increase among men and women were 75% and 39%, respectively. Regression analysis identified age and BMI as the independent risk factors of hypertension. Other risk factors of hypertension were sex, marital status, education, geographic region, wealth index, and diabetes status in both survey years. Female adults had significantly higher hypertension risk in both survey years in the overall analysis in, however, in the subgroup analysis, the gender difference in hypertension risk was not significant in rural 2011 and urban 2018 samples. Decomposition analysis revealed that the contributions of socio-economic status related inequality of hypertension in 2011 were46.58% and 20.85% for wealth index and BMI, respectively. However, the contributions of wealth index and BMI have shifted to 12.60% and 55.29%, respectively in 2018. CONCLUSION: The prevalence of hypertension among Bangladeshi adults has increased significantly, and there is no subgroup where it is decreasing. Population-level approaches directed at high-risk groups (overweight, obese) should be implemented thoroughly. We underscore prevention strategies by following strong collaboration with stakeholders in the health system of the country to adopt healthy lifestyle choices.

Genotypic and phenotypic characterization of Streptococcus mutans strains isolated from patients with dental caries.

BACKGROUND AND OBJECTIVES: The oral cavity harbors numerous Streptococcus mutans strains which display remarkable genotypic and phenotypic diversity. This study evaluated the genotypic and phenotypic diversity of 209 S. mutans strains isolated from 336 patients with dental caries and compared with the universal reference strain, UA159. MATERIALS AND METHODS: Selective cultivation on mitis-salivaries-bacitracin agar and species-specific polymerase chain reaction (PCR) was carried out to isolate and identify the 209 S. mutans isolates from 336 patients with dental caries. Arbitrarily primed polymerase chain reaction (AP-PCR), PCR amplification of specific gene, acid production and biofilm formation capacity were performed to evaluate the genotypic and phenotypic variation. Student's t-test and Chi-square test were used for analysis of variables and a probability (P) of <0.05 was considered as significant. RESULTS: Our study revealed a high degree of genotypic and phenotypic variability among the clinical strains. We observed significant differences in colony morphology, generation time, biofilm formation, and acid production while growing in culture medium. All the clinical isolates were able to lower pH while growing in Todd-Hewitt broth. Consistent with phenotypic variations, we also observed genotypic variation by AP-PCR and gene specific PCR. AP-PCR analysis suggested that most of the patients with dental caries have distinct type of S. mutans strains. Genes related to various two component systems were highly conserved among the isolated strains, however, bacteriocin encoding genes such as nlmAB, nlmC were absent in nearly half of the clinical isolates. CONCLUSION: Our results support that S. mutans clinical isolates have wide genotypic diversity and show variation in growth kinetics, acid production, acid tolerance and biofilm formation capacity and indicates the presence of diverse mechanism to initiate and establish the biofilm lifestyle which leads to tooth decay.

Risk factors for pregnancy related complications among urban slum and non-slum women in Bangladesh.

BACKGROUND: Bangladesh is facing a higher maternal mortality and morbidity than many other developing countries in the world. The majority of these maternal deaths occur due to pregnancy related complications. Although health facilities in urban areas in Bangladesh are widely available, women living in underprivileged urban areas are least likely to receive the maternal health services and as a result, they face more pregnancy related complications. Unfortunately, there are only a few studies on complications during maternal and delivery period in these areas. We aim to investigate the factors responsible for pregnancy related complications in urban slum and non-slum areas. METHODS: Data from the Urban Health Survey (UHS), 2013 were analyzed applying mixed logistic regression model. The response variable was complications during pregnancy, during/after delivery at the last birth and the total sample size was 6137. The adjusted odds ratios (AORs) along with their 95% confidence intervals (CIs) were also calculated to compare the magnitude of different risk factors for the pregnancy related complications. RESULTS: Younger mothers (age < 18 years) at the birth of their children had 24% (OR = 1.24, 95% CI: 1.01, 1.54) more odds to experience complications during pregnancy/delivery or after delivery compared to older mothers aged 18 to 35 years. The increased risk of complications was found among primiparous women. Women living in urban slum areas had higher pregnancy related complications than women living elsewhere. Migrant mothers faced more complications than women-who were not migrants. Women had greater pregnancy related complications when they delivered boy child than girl child, presumably from an increased size of the baby and resultant birth obstruction, assisted delivery and post partum haemorrhage. Moreover, a wanted pregnancy had fewer significant complications during pregnancy/delivery or after delivery than an unwanted pregnancy. CONCLUSIONS: The study associates early maternal age, primiparity, unwanted pregnancy, women living in slum areas, women migrating from other cities or non-urban areas and NGO membership with increased risk of pregnancy related complications among urban women in Bangladesh. It is likely that addressing these risk factors for complications to the policymakers may help to reduce the maternal mortality and morbidity in Bangladesh.