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The GAMA Microreactor is a low-power nuclear power plant dedicated for remote area with a power output of 300 kWe. The primary characteristics of the GAMA Microreactor are its system compactness, design simplicity, and safe operation without moving parts. The fuel is uranium hydride powder, which works simultaneously as a moderator, contained within a stainless-steel vessel and surrounded by a graphite reflector. Liquid sodium-filled heat pipes are embedded in the fuel powder to extract fission-generated heat via passive coolant flow due to capillary action. As a part of the design process, neutronic parameters of the GAMA Microreactor have been determined using SCALE6.2 and OpenMC codes. Among the analyzed parameters are the excess reactivity as a function of burn-up, shutdown margin, control rod worth, temperature coefficient of reactivity (TCR), fuel density coefficient of reactivity (DCR), and reactivity coefficient due to hydrogen dissociation. From the calculation results, the GAMA Microreactor has a maximum excess reactivity of 0.049 at the operational temperature (700 °C) and 0.0788 at ambient temperature. The TCR value is negative (−2.267 pcm/°C) at the beginning of the cycle (BOL) and −4.9618 pcm/°C at the end of the cycle (EOC). Hydrogen dissociation imposes negative reactivity on the reactor both at the BOL (−0.2631 Δk/k-%dissociation) and EOC (−0.3524 Δk/k-%dissociation). Therefore, the GAMA Microreactor maintains its inherent safety characteristics over a considerably long operation time.

Background: Preventing depression and helping individuals to become more resilient to depression, awareness-related programs have been suggested. To implement such programs, depression literacy (D-Lit) assessment is needed. However, little information is known about it in Bangladesh, and this gap was addressed - in the present study. Methods: An online-based cross-sectional survey was carried out among 404 university students (62.6% male; 69.3% undergraduates, mean age = 22.35 ± 2.69 years). The survey included questions asking about socio-demographics, personal and family depression history, its' stigma and related programs, and the 20-item Bangla Depression Literacy questionnaire. Results: The results showed a mean score of 9.30 (SD = 2.75; out of total 20 scores) on the Bangla D-Lit scale. Participants had very limited knowledge of the psychotic symptoms, impact, and management subscales. Moreover, nine items out of the total twenty-items were answered correctly by at least 50% of the participants. There were no significant D-Lit score differences based on gender and past-year personal history, and family depression history. Structural equation modeling indicated that having knowledge about depression and attending depression seminars were positively related to elevated depression literacy. Limitations: The study has some limitations due to its cross-sectional study nature and modest sample size. In addition, there the assessment of depression did not use a validated psychometric instrument and the D-Lit comprises multiple-choice responses so the real rate of depression literacy may be even lower than that found because participants could have guessed answers that they did not know. Conclusions: Findings from this study suggest that depression literacy was low in the population studied and the findings here will help to facilitate mental health literacy awareness programs in the context of Bangladeshi students as well as those outside the country.

The number of diabetic patients is increasing rapidly who have vulnerable feet and might be easily affected by different adversities. Since there is no available footwear sizing system for diabetic patients, manufacturers produce diabetic footwear of different sizes and fittings based on other available footwear sizing systems, which may result in inappropriate fitting. To get footwear with proper fittings, diabetic patients may go for customized or bespoke footwear based on their foot conditions, which is very costly. This study attempts to explore the foot complications of diabetic patients and categorize their feet to create a new sizing system using foot measurements from 102 male diabetic patients based on three dimensions of human feet, namely foot length, ball girth, and instep circumference. K-means data clustering is followed to categorize the data into three broad groups, namely small, medium, and large groups for footwear sizing. The developed footwear sizing system uses a sizing interval of 8 mm and a fitting interval of 6 mm. This study suggests a total of 11 sizes along with 24 different fittings for the footwear manufacturers for producing diabetic footwear. This newly developed footwear sizing system has a total of 79.41 % coverage where there are 10, 10, and 4 fittings in the small, medium, and large groups, respectively. The proposed footwear sizing system can help footwear manufacturers understand the proper size and fit of diabetic patients’ feet so that they can make appropriate footwear for diabetic patients economically.

This study aims to explore the scopes and challenges, rank the challenges, and provide strategic solutions for adopting Industry Revolution 4.0 (IR 4.0) in Bangladesh's textile and apparel industry. A random survey was administered to a total of 142 factories in Bangladesh. Both quantitative and qualitative methods of analysis were used in this study. The survey includes questions on important study variables, such as big data, smart factories, cyber-physical systems (CPS), the Internet of Things (IoT), interoperability, textile production, and industry performance. The Variable Destination Multiple Access (VDMA) Model has been adopted to design the questionnaire, focusing on qualitative and quantitative questions. The survey dataset was investigated through SmartPLS 4.0 by normality and confirmatory tests. Likert scale data have been analyzed through IBM SPSS software version 26.0 by the exploratory factor analysis method to rank the IR 4.0 adoption variables. Analysis of the survey data indicates the level of adoption of Industry 4.0 in terms of organizational strategy, investment, infrastructure, IT (Information Technology), Ready Made Garments (RMG) skilled workers, smart operations, and smart factories. The study shows that the variable “Review of the strategy using indicators” got the highest ranking in the external factor, 0.791. This clearly indicates that strategy formulation is the topmost priority among other IR 4.0 adoption variables. Consequently, “digital integration” got the lowest loading at 0.620, as IR 4.0 digital technology adoption is very low. The overall maturity level for IR 4.0 adoption in the Bangladesh textile and apparel industry is 1.91 on a 5-point scale, indicating a low adoption level. This study can help concerned policymakers and industrialists who want to implement Industry 4.0 in the textile and RMG sectors to stay competitive in the global market. Alongside this study, it also summarizes the IR 4.0 adoption level in 9 broad categories.

Since the Wright Brothers’ first flight in 1903, extensive research has been dedicated to improving the aerodynamic performance of aircraft. This study investigates the effect of two distinct wing geometric modifications on airfoil performance at high angles of attack (AOAs). These two modifications are slot, specifically the NACA 4412 with only a slot, and groove, specifically the NACA 4412 with both a slot and a groove. The investigation combines numerical simulation using ANSYS fluent with experimental evaluations conducted in the VDAS AF1300 subsonic wind tunnel. Since turbulent airflow often results in early stall, the primary objective of this research is to delay the stall angle of the normal NACA 4412 airfoil by mitigating local separation zones, and boundary layer transitions. Numerical simulations are performed at airspeeds of 20 m/s and 43.9 m/s, while experimental investigations are conducted at a speed of 20 m/s. The results indicate that both modified airfoils have higher lift-to-drag ratio than the normal airfoil at high AOAs. Specifically, the NACA 4412 airfoil with only a slot demonstrates the highest lift-to-drag ratio among the modified airfoils at high AOAs. Moreover, the NACA 4412 airfoil equipped with a slot and a groove demonstrates the highest stall angle, measured at 18°, compared to the normal NACA 4412 airfoil with a stall angle of 14°. At high AOA, the NACA 4412 airfoil with a slot generates a nearly 35 % higher lift coefficient than the normal NACA 4412 airfoil, while the NACA 4412 with a slot and a groove achieves almost a 16 % higher lift coefficient than the normal NACA 4412 airfoil.

Hilsa shad, Tenualosa ilisha, has recently gained momentum due to its taste, nutrition and demand. Imposing ban at peak breeding and setting up a minimum capture size are two of the most effective tools for conservation and management of any fish species. Although, Bangladesh government has been imposing ban on a particular time and set the minimum legal size, there is still contradictory information on these two issues. That is why, a study was carried out to determine peak season of breeding and first maturity of Hilsa collected across the natural habitats in Bangladesh. Variation in fecundity and egg-size at different sizes were also investigated. Peak breeding season was identified observing gonadosomatic index of female Hilsa all the year round. First maturity was estimated with Probit analysis.Based on the gonadosomatic index of gravid females, peak breeding season was identified as late October to early November in this study. However, another minor peak was found in February–March. The highest GSI value (12.1) was observed in October–November, which indicates the peak time of spawning. The size at maturity (M50) of female Hilsa was estimated as 31 cm total length. A significant variation was observed in egg sizes between the left and right lobes of the fish (t (24) = 2.42, p = 0.02), and between the parts of the same lobe (p = 0.03). However, fish length and weight had no effect on egg size(for egg-size vs. fish length, r = -0.009, p = 0.966; and for egg size vs. body weight, r = 0.132 and p = 0.530). The average egg count from left lobe and right lobe were recorded as 0.375 ± 0.16 million, 0.371 ± 0.17 million. Total fecundity was counted as 0.745 ± 0.33 million. A significant positive correlation was noticed between length, weight, and total fecundity (r = 0.7 for total fecundity vs. body weight; r = 0.6 for of total fecundity vs. length). No significant variation was observed in fecundity between the left and right lobe (p = 0.6) and among three parts of a lobe (p = 0.3). The size of eggs varied between two lobes and among different parts of a lobe. The eggs from middle part were bigger in size than the other parts. The findings of our study will help conserve and manage the natural population of Hilsa (T. ilisha) in Bangladesh and contribute to the wider scientific community.

Black tea samples were investigated for theaflavin (TF), thearubigin (TR), highly polymerized substances (HPS), total liquor color (TLC), color index (CI), caffeine (CAF), total polyphenol content (TPC), antioxidant activity (DPPH) and organoleptic evaluation. The objectives of the study was to perform the biochemical analysis and organoleptic test of various black tea and develop a correlation between them. Overall correlation study showed that TF:TR and total liquor color, are significantly (p

Background and aim: Outbreak of COVID-19 seems to have exacerbated across the globe, including Bangladesh. Scientific literature on the clinical data record of COVID-19 patients in Bangladesh is inadequate. Our study analyzes the clinical data of COVID-19 positive patients based on molecular identification and risk factor correlated with three variables (age, sex, residence) and COVID-19 prevalence in the four districts of Chattogram Division (Noakhali, Feni, Lakshmipur and Chandpur) with an aim to understand the trajectory of this pandemic in Chattogram, Southern Bangladesh. Methods: A cross-sectional study is conducted in the context of RT-PCR-based COVID-19 positive 5,589 individuals diagnosed with SARS-CoV-2 infection from the COVID-19 testing laboratory, Abdul Malek Ukil Medical College, Noakhali-3800, Bangladesh. For molecular confirmation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), standard diagnostic protocols through real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) were conducted. Different patient demographics were analyzed using SPSS version 22 for exploring the relationship of three factors – age, sex, and residence with a cumulative number of COVID-19 positive cases and prevalence of COVID-19 in four districts in Chattogram division. The data was recorded between May to July, 2020. Results: Among the three parameters, the present study revealed that 20–40 cohort had the highest incidence of infection rate (51.80%, n = 2895) among the different age groups. Among the infected individuals, 56.8% (n = 3177) were male and 43.2% (n = 2412) were female, denoting males being the most susceptible to this disease. Urban residents (52.7%, n = 2948) were more vulnerable to SARS-CoV-2 infection than those residing in rural areas (47.3%, n = 2641). The prevalence of COVID-19 positive cases among the four districts was recorded highest in the Noakhali district with 36.8% (n = 2057), followed by the Feni, Lakshmipur and Chandpur districts with 25.9% (n = 1448), 20.8% (n = 1163) and 16.5% (n = 921), respectively. Conclusions: This study presents a statistical correlation of certain factors linked to Bangladesh with confirmed COVID-19 patients, which will enable health practitioners and policy makers to take proactive steps to control and mitigate disease transmission.

Background: Intimate Partner Violence (IPV) is a serious violation of women's human rights and a dominant chronic global public health problem. Although it is suspected that epidemic-induced economic downturns have fueled the IPV, enough empirical literature are not available to make a consensus. Against this backdrop, the present study has attempted to explore the prevalence and associated factors of IPV amid the COVID-19 pandemic. Methods: The study has included Bangladesh as the study area and collected data from married women who lived with her intimate partner. Total of 605 women were reached and 84.30% (510) women, aged 16–45 with mean age 30.12 (±6.27) years, provided their consent and required information. The study has employed the translated version of WHO multi-country study tools to screen the IPV. Results: This cross-sectional study has found the prevalence of IPV about 45.29%, where 44.12% are emotionally abused, 15.29% physically, 10.59% sexually, and 19.22% are abused either physically or sexually. The study has found that types of marriage, area of residence, women's employment status, husband's age and level of education, family income status, and pandemic induced economic downturns were the associated factors of intimate partner violence amid the pandemic. Limitations: Self-reported cross-sectional study has some methodological limitations, and the present study is not free from them. Conclusions: The study contributes to the existing literature by highlighting the associated factors of IPV amid the pandemic, which will help to make preventive policy.

The task of drug-target interaction prediction holds significant importance in pharmacology and therapeutic drug design. In this paper, we present FRnet-DTI, an auto-encoder based feature manipulation and a convolutional neural network based classifier for drug target interaction prediction. Two convolutional neural networks are proposed: FRnet-Encode and FRnet-Predict. Here, one model is used for feature manipulation and the other one for classification. Using the first method FRnet-Encode, we generate 4096 features for each of the instances in each of the datasets and use the second method, FRnet-Predict, to identify interaction probability employing those features. We have tested our method on four gold standard datasets extensively used by other researchers. Experimental results shows that our method significantly improves over the state-of-the-art method on three out of four drug-target interaction gold standard datasets on both area under curve for Receiver Operating Characteristic (auROC) and area under Precision Recall curve (auPR) metric. We also introduce twenty new potential drug-target pairs for interaction based on high prediction scores. The source codes and implementation details of our methods are available from https://github.com/farshidrayhanuiu/FRnet-DTI/ and also readily available to use as an web application from http://farshidrayhan.pythonanywhere.com/FRnet-DTI/.