GENETIC DIVERSITY BY RAPD IN FOUR POPULATIONS OF ROHU Labeo rohita

Genetička raznolikost među četiri geografski udaljene populacije indijskog šarana (Labeo rohita) - rohu Khulna, rohu India, rohu Faridpur i rohu Barisal - određena je pomoću RAPD markera. Uzorak na gelu je pokazao da je populacija rohu India genetski različita od triju ostalih. Ukupno je pronađeno 87 crtica u četiri rohu populacije pri čemu je 35 crtica bilo polimorfno, što ukazuje na 48,38% polimorfizma s prosjekom od 12 crtica po početnici. Dužina amplificiranih fragmenata DNK kretala se u rasponu od 400 do 1250 bp. Osam jedinstvenih crtica je uočeno u četiri populacije od kojih je šest pronađeno u rohu India populaciji. Genetska udaljenost je bila najviša (0,7221) i genetska identičnost je bila najniža (0,4857) između populacija rohu India i rohu Barisal. Među tri lokalne populacije najniža genetska udaljenost i najviša genetska identičnost utvrđena je između populacija rohu Khulna i rohu Faridpur. UPGMA filogenetsko stablo odijelilo je četiri populacije indijskog šarana u tri glavna odjeljka - C1, C2 i C3. Rohu Indija nalazi se na potpuno drugačijem odjeljku C3, rohu Khulna je smještena u C2, a ostale dvije populacije u C1 odjeljak.Genetic diversity in four geographically distinct rohu (Labeo rohita) populations such as rohu Khulna, rohu India, rohu Faridpur and rohu Barisal was determined by RAPD. The banding pattern showed that rohu India was genetically different from the rest three. A total of 87 bands were found in four rohu populations where 35 bands were polymorphic, indicating 48.38% polymorphisms with an average of 12 bands per primer. The molecular size of amplified DNA fragments ranged from 400 to 1250 bp. Eight unique bands were observed in the four populations of which six were found in rohu Indian population. The genetic distance was highest (0.7221) and genetic identity was lowest (0.4857) between rohu India and rohu Barisal populations. Among three local varieties, the lowest genetic distance and highest genetic identity were found between rohu Khulna and rohu Faridpur populations. The UPGMA dendrogram segregated four populations of rohu into three major clusters - C1, C2 and C3. Rohu India was positioned at a fully different cluster - C3, rohu Khulna was placed in C2 and the rest two populations in C1

Performance Analysis of YOLO-based Architectures for Vehicle Detection from Traffic Images in Bangladesh

The task of locating and classifying different types of vehicles has become a vital element in numerous applications of automation and intelligent systems ranging from traffic surveillance to vehicle identification and many more. In recent times, Deep Learning models have been dominating the field of vehicle detection. Yet, Bangladeshi vehicle detection has remained a relatively unexplored area. One of the main goals of vehicle detection is its real-time application, where `You Only Look Once' (YOLO) models have proven to be the most effective architecture. In this work, intending to find the best-suited YOLO architecture for fast and accurate vehicle detection from traffic images in Bangladesh, we have conducted a performance analysis of different variants of the YOLO-based architectures such as YOLOV3, YOLOV5s, and YOLOV5x. The models were trained on a dataset containing 7390 images belonging to 21 types of vehicles comprising samples from the DhakaAI dataset, the Poribohon-BD dataset, and our self-collected images. After thorough quantitative and qualitative analysis, we found the YOLOV5x variant to be the best-suited model, performing better than YOLOv3 and YOLOv5s models respectively by 7 & 4 percent in mAP, and 12 & 8.5 percent in terms of Accuracy.Comment: Accepted in 25th ICCIT (6 pages, 5 figures, 1 table

The PreQuine Platform: a novel diagnostic tool for measuring glucose-6-phosphate dehydrogenase (G6PD) activity and hemoglobin concentration

Quantitative diagnosis of glucose-6-phosphate dehydrogenase (G6PD) deficiency is essential for the safe administration of 8-aminoquinoline based radical cure for the treatment of Plasmodium vivax infections. Here, we present the PreQuine Platform (IVDS, USA), a quantitative biosensor that uses a dual-analyte assay for the simultaneous measurement of Hemoglobin (Hgb) levels and G6PD enzyme activity within the same sample. The platform relies on a downloadable mobile application. The device requires 10μl of whole blood and works with a reflectance-based meter. Comparing the G6PD measurement normalized by Hgb of 12 samples from the PreQuine Platform with reference measurements methods (spectrophotometry, Pointe Scientific, USA and hemoglobin meter, HemoCue, Sweden) showed a positive and significant agreement with a slope of 1.0091 and an intercept of -0.0379 under laboratory conditions. Next steps will be to conduct field trials in Bangladesh, Cambodia, and the USA to assess diagnostic performance, user friendliness and acceptance

A new estimate of carbon for Bangladesh forest ecosystems with their spatial distribution and REDD+ implications

In tropical developing countries, reducing emissions from deforestation and forest degradation (REDD+) is becoming an important mechanism for conserving forests and protecting biodiversity. A key prerequisite for any successful REDD+ project, however, is obtaining baseline estimates of carbon in forest ecosystems. Using available published data, we provide here a new and more reliable estimate of carbon in Bangladesh forest ecosystems, along with their geo-spatial distribution. Our study reveals great variability in carbon density in different forests and higher carbon stock in the mangrove ecosystems, followed by in hill forests and in inland Sal (Shorea robusta) forests in the country. Due to its coverage, degraded nature, and diverse stakeholder engagement, the hill forests of Bangladesh can be used to obtain maximum REDD+ benefits. Further research on carbon and biodiversity in under-represented forest ecosystems using a commonly accepted protocol is essential for the establishment of successful REDD+ projects and for the protection of the country’s degraded forests and for addressing declining levels of biodiversity

Classification and regression tree for characterising smoking patterns among adults: evidence from global adult tobacco survey, Bangladesh

Background Tobacco consumption is a preventable public health problem. Many tobacco related studies have employed logistic regression in their analysis and they mostly analyzed categorical variables with dichotomous outcomes. In comparison to logistic regressions, classification and regression tree (CART), a data mining technique have not been widely applied for tobacco related research though this technique has enormous benefits over other methods. Therefore, this study examines the smoking patterns among adults by CART method and to compare findings with other traditional techniques. Methods Dataset covered a nationally representative sample of 9,629 respondents extracted from Global Adult Tobacco Survey, Bangladesh and used CART techniques for its suitability than others such as, binary logistic regression, multinomial logistic regression, chi-squared automatic interaction detector, quick unbiased statistical test. Results CART was used to characterize the cigarette smoking behaviour among adults aged 15 years and above in Bangladesh. The algorithm builds a tree model to classify "average number of cigarettes smoked per day" using some attributes as predictors. CART was found easy to understand compared to other data mining techniques. Logistic regression model requires the parametric assumption (PA) of the dependent variable. However, this PA often restricts when data "A mixture of categorical and continuous variables". Therefore, CART is appropriate because: (i) Purely non-parametric and is independent of distribution assumptions (ii) Can handle both continuous and categorical data (iii) Can use skewed or multi-modal data without requiring the independent variables to be normally distributed (iv) Can handle missing data (v) Relatively automatic 'machine learning (vi) Less input is needed for analysis and (vii) Visualization character and its results are simple to interpret even for non-statisticians. Conclusions Among the different techniques so far used in characterizing smoking patterns among adults, CART is the best in terms of all aspects and suggested for future research

Tobacco consumption, environmental tobacco smoke exposure and illicit drug use: A study on selected south Asian countries / Mohammad Alamgir Kabir

The trend of tobacco consumption (TC) is on the increase in the developing and under-developed countries including South Asian region. TC and the closely related problems of environmental tobacco smoke (ETS) exposure and illicit drug use (IDU) are increasingly alarming in South Asian countries. This study aims to explore the prevalence, patterns and determinants of (i) TC among youths and adults, (ii) ETS exposure among adults at home, workplace and public places, and (iii) IDU among males in selected South Asian countries. The associations between TC and ETS, and TC and IDU were also examined. This study utilized data from (i) Global Youth Tobacco Survey-2007 that covered 2,242 Bangladeshi, 1,444 Nepalese and 1,377 Sri Lankan youths aged 13–15 years, (ii) Global Adult Tobacco Survey-2010 that covered 9,629 Bangladeshi and 69,296 Indian adults aged 15 years or more, (iii) Bangladesh Demographic and Health Survey-2007 that covered 3,771 males aged 15-54 years, and (iv) Bangladesh Urban Health Survey-2007 that covered 1,576 males aged 15-24 years that lived in urban slums. Univariate, bivariate, and multivariate (binary, ordinal, and multinomial logistic regressions) and classification and regression tree (CART) analyses and diamond-shaped equiponderant graphs were used for analysis. Prevalence of youth TC was 6.9% in Bangladesh, 9.4% in Nepal and 9.1% in Sri Lanka with higher rates among males. Common significant predictors include TC among friends, exposure to smoking at home and other places, and teaching of smoking hazards in schools. Availability of free tobacco products from vendors significantly influenced Bangladeshi and Sri Lankan youths. Prevalence of adult TC was 43.3% in Bangladesh and 34.6% in India. Males and those older had a higher tendency to use tobacco products. Adults with no education were more likely to use tobacco products in Bangladesh (odds ratio, OR=4.9) and India (OR=3.0) compared to others with tertiary iv education. Adults with the poorest wealth status were more likely to consume tobacco products in Bangladesh (OR=2.3) and India (OR=3.0) compared to those from the richest wealth status. Better knowledge, attitude and perception towards TC significantly reduced the TC rates in both countries. CART analysis had the highest classification accuracy for characterizing smoking patterns. Age of TC initiation, wealth status and gender were important variables for classifying smoking behavior. Other classifying variables include place of residence, educational attainment, and warnings printed on packaging of tobacco products. Older adults and females had significantly less exposure to ETS in Bangladesh and India. Larger family size increased the chance of exposure at home. Those with higher education and knowledge on ETS had lower chance of exposure at home and workplaces, but they had higher exposure at public places. Smoking ban at home and workplaces significantly reduced the chances of being exposed to ETS. The results also suggested that TC increased the likelihood of exposure to ETS, and a higher frequency of TC tend to worsen the problem. Prevalence of IDU among young males in urban slums and the general male population in Bangladesh were 9.1% and 3.4%, respectively. Significant predictors of IDU include education, duration of living in slums, and sexually transmitted infections. The logistic regression analysis revealed that those who used tobacco products daily had significantly higher likelihood of IDU. This likelihood also increased significantly with frequency of tobacco use. The impact of TC on IDU was remarkably higher among males in slums compared to the general male population. Understanding of the influencing factors of TC, ETS and IDU provides helpful insights for tobacco control policy formulation in South Asian region, as well as policy lessons for other low and low-middle income countries

Genetic Diversity by Rapd in Four Populations of Rohu Labeo Rohita

Genetic diversity in four geographically distinct rohu (Labeo rohita) populations such as rohu Khulna, rohu India, rohu Faridpur and rohu Barisal was determined by RAPD. The banding pattern showed that rohu India was genetically different from the rest three. A total of 87 bands were found in four rohu populations where 35 bands were polymorphic, indicating 48.38% polymorphisms with an average of 12 bands per primer. The molecular size of amplified DNA fragments ranged from 400 to 1250 bp. Eight unique bands were observed in the four populations of which six were found in rohu Indian population. The genetic distance was highest (0.7221) and genetic identity was lowest (0.4857) between rohu India and rohu Barisal populations. Among three local varieties, the lowest genetic distance and highest genetic identity were found between rohu Khulna and rohu Faridpur populations. The UPGMA dendrogram segregated four populations of rohu into three major clusters - C1, C2 and C3. Rohu India was positioned at a fully different cluster - C3, rohu Khulna was placed in C2 and the rest two populations in C1

Patterns, prevalence and determinants of environmental tobacco smoke exposure among adults in Bangladesh

Background: Exposure to environmental tobacco smoke (ETS) has been suggested as a risk factor for various health problems. Thus, this study examines the patterns and predictors of ETS exposure among adults at home, workplace and public places. Methods: The dataset covered a nationally representative sample of 9629 respondents extracted from the Global Adult Tobacco Survey. Diamond-shaped equiponderant graphs were used to exhibit the prevalence of ETS. In Logistic regressions, ETS exposure at home, workplace and public places were used as response variables. Demographic and socioeconomic variables, health knowledge about ETS, attitude towards ETS, perception of smoking restrictions were considered as predictors. Results: Adults in higher age groups and females were less exposed to ETS. Better education, high wealth status, better health knowledge on ETS, practice of no smoking at home, and support smoking restrictions were significantly associated with lower ETS exposure at home. Those residing in rural areas and living with many people together were more likely to be exposed to ETS at home. In contrast with home and workplace exposure, adults with higher education, better wealth status, good knowledge on ETS, and support smoking restrictions experienced a high level of exposure at public places. Interestingly, results suggest that those with high levels of ETS exposure at home and workplace had lower exposure to ETS in public places. Conclusions: ETS control should not be overlooked in public health policy. Protection from ETS at home is particularly important, given its impact on the attitude towards and awareness about ETS exposure at all places. Keywords: Environmental tobacco smoke exposure, Equiponderant graphs, Public health, Banglades