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Sign language is the predominant mode of communication for individuals with auditory impairment. In Bangladesh, BdSL or Bangla Sign Language is widely used among the hearing-impaired population. However, because of the general public's limited awareness of sign language, communicating with them using BdSL can be challenging. Consequently, there is a growing demand for an automated system capable of efficiently understanding BdSL. For automation, various Deep Learning (DL) architectures can be employed to translate Bangla Sign Language into readable digital text. The automation system incorporates live cameras that continuously capture images, which a DL model then processes. However, factors such as lighting, background noise, skin tone, hand orientations, and other aspects of the image circumstances may introduce uncertainty variables. To address this, we propose a procedure that reduces these uncertainties by considering three modalities: spatial information, skeleton awareness, and edge awareness. We introduce three image pre-processing techniques alongside three CNN models. The CNN models are combined using nine distinct ensemble meta-learning algorithms, with five of them being modifications of averaging and voting techniques. In the result analysis, our individual CNN models achieved higher training accuracy at 99.77%, 98.11%, and 99.30%, respectively, than most of the other state-of-the-art image classification architectures, except for ResNet50, which achieved 99.87%. Meanwhile, the ensemble model attained the highest accuracy of 95.13% on the testing set, outperforming all individual CNN models. This analysis demonstrates that considering multiple modalities can significantly improve the system's overall performance in hand pattern recognition.

Electricity generation and consumption must undergo a substantial transformation as part of the global energy transition towards decarbonization. Hydrogen-based hybrid energy storage systems (HESS) have the potential to replace the existing fossil fuel-based energy generation due to their high energy density and long storage capacity. This study has introduced a novel indicator “usage count” instead of “citation analysis” to obtain the top 100 articles in the field of hydrogen-based HESS because of the factors such as reduction of time lag, recentness and domain independency. After the filtration process, the top 100 articles with the highest usage count are obtained by providing an extensive search in the Scopus database from the year 2012–2021. An extensive comparative study between “usage count” and “citation analysis” among the selected top 100 articles is provided. Moreover, a detailed keyword co-occurrence network (KCN) analysis along with comprehensive reviews concerning HESS modelling, optimization objectives, algorithms, system constraints, and research gaps are presented. The review emphasizes the benefits and drawbacks of hydrogen-based HESS and analyzes the obstacles associated with their application, such as the system's high cost, technical complexity, socio-economic and environmental impact and safety concerns, which can provide the researchers with a clearer picture for future research and development. Finally, the article conveys some suggestions and directions, which can act as a roadmap toward achieving reliable and sustainable next-generation hydrogen-based HESS.

The exploration and development of natural biopolymer-based hydrogels can be traced back to the 18th century. The rising interest in these hydrogels is largely due to their soaring demand in diverse applications such as tissue engineering, bio-separation, drug delivery, smart bioelectronics, and eco-friendly agriculture. However, one major drawback of these naturally derived biopolymer-based hydrogels is their subpar mechanical properties characterized by limited stretchability, modulus, and resilience, along with inadequate water adsorption capability. This restricts their broad-spectrum applicability. These biopolymers are typically crosslinked through different strategies to rectify these issues and functional groups present in polymer chains play crucial roles in crosslinking strategies. Consequently, the understanding of the chemical structure-function relationship in the crosslinked polymeric network is paramount for the design of an effective natural biopolymer-based hydrogel. A profound comprehension of the behavior of functional groups during crosslinking is therefore essential. This review provides a comprehensive overview of the chemistries of functional group interactions in natural biopolymers that are utilized in the development of functional hydrogels. Various categories of functional group interaction chemistries are examined and discussed in terms of crosslinking strategies (e.g., hydrogen bonding, ionic interaction, hydrophobic interaction) for hydrogel formation. Furthermore, the types, properties, and cutting-edge applications of resultant natural biopolymer-based hydrogels are outlined along with a discussion of the future prospects in this field of research.

Current evidence indicates that more than half of all antimicrobials are used in the animal food-producing sector, which is considered a significant risk factor for the development, spread, and existence of antimicrobial resistance (AMR) pathogens in animals, humans, and the environment. Among other factors, clinical etiology and the level of knowledge, attitudes, and practices (KAP) of veterinarians are thought to be responsible for inappropriate prescriptions in the animal-source protein production sector in lower-resource settings like Bangladesh. We performed this cross-sectional study to assess factors associated with veterinarians’ antimicrobial prescription behavior and their KAP on antimicrobial use (AMU) and AMR in Bangladesh. Exploratory and multivariate logistic models were used to describe an association between knowledge, attitudes, and practices of AMU and AMR and demographic characteristics of veterinarians. The results demonstrated that when selecting an antimicrobial, there was no to minimal influence of culture and susceptibility tests and patients’ AMU history but moderate to high influence of the farmer’s economic condition and drug instructions among the veterinarians. The results also demonstrated that more than half of the veterinarians had correct KAP regarding AMU and AMR, while the rest had moderate or lower levels of KAP. The factor score analysis revealed that age, level of education, years of experience, gender, and previous training on AMU and AMR were the key influencing factors in their level of KAP. Adjusted logistic regression analysis showed that respondents’ age, current workplace, and previous training on AMU and AMR had a positive association with increased KAP. Considering the results, it is imperative to include AMR issues on vet curricula, and to provide post-education training, awareness campaigns, easy access to, and dissemination of AMR resources. Increasing the veterinary services to the outreach areas of the country and

Aims: Mortality in children aged under two years is a severe public health problem in many developing countries. The aims of the study were to reveal the prevalence and factors associated with mortality in children under two years in Bangladesh. Methods: Data were analyzed using the Bangladesh Demographic and Health Survey 2014. A total of 7886 participant data used in this study. The chi-square test of association was performed with dependent and independent variables to measure the prevalence rate, while the final model binary logistic and log-binomial regressions were used to identify the potential risk factors for under-two mortalities. Results: The prevalence of under-2 mortalities in Bangladesh was 3.9%. Regression analysis revealed that a lower level of paternal education, succeeding birth interval less than 24 months, multiple birth babies, and smaller than the average size at birth were significantly associated with children’s mortality under two years in Bangladesh. Conclusions: Despite improvements in the reduction of child mortality in Bangladesh, many children died within the first 24 months of life, mostly preventable. Programs towards increasing education levels and pregnancy intervals might help in preventing infant mortality in Bangladesh. Bangladesh Journal of Medical Science Vol. 21 No. 02 April’22 Page : 413-421

Global climatic changes are contaminating ground and surface water sources around the world, resulting in increased salinity. Knowing the animals' typical physiological capability for salinity tolerance without compromising their health is a necessity. The research was undertaken to determine the impacts of drinking water salinity on hemato-biochemical parameters of Black Bengal goats. A total of 40 Black Bengal goats (20 male and 20 female), age ranging from 1 to 5 years, were randomly selected and divided into 2 groups. The animals of group 1 received higher saline water (12 ppt) and those in group 2 received lower saline water (1 ppt) as regular drinking water. Blood parameters of all selected goats were measured. Serum creatinine, uric acid, urea, potassium, sodium, and chloride were significantly higher (P< 0.05) in the animals of group 1 compared with group 2, although serum phosphorous was significantly lower (P < 0.05) in group 1 compared with group 2. There were no significant differences in serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), glucose, magnesium, and calcium between the animals of group 1 and 2. AST and magnesium differed significantly (P < 0.05) between young and adult goats in group 1. Glucose and urea levels were slightly higher (P < 0.05) in young goats. In both groups, male goats had significantly higher (P < 0.05) serum potassium and urea levels than female goats. The results suggest that Black Bengal goats of the coastal areas have different salt tolerance capacities based on their age and sex, and adapt to higher salinity by changing kidney functions.

The COVID-19 pandemic has affected every sector in the world, ranging from the education sector to the health sector, administration sector, economic sector and others in different ways. Multiple kinds of research have been performed by research centres, education institutions and research groups to determine the extent of how huge of a threat the COVID-19 pandemic poses to each sector. However, detailed analysis and assessment of its impact on every single target within the 17 Sustainable Development Goals (SDGs) have not been discussed so far. We report an assessment of the impact of COVID-19 effect towards achieving the United Nations SDGs. In assessing the pandemic effects, an expert elicitation model is used to show how the COVID-19 severity affects the positive and negative impact on the 169 targets of 17 SDGs under environment, society and economy groups. We found that the COVID-19 pandemic has a low positive impact in achieving only 34 (20.12%) targets across the available SDGs and a high negative impact of 54 targets (31.95%) in which the most affected group is the economy and society. The environmental group is affected less; rather it helps to achieve a few targets within this group. Our elicitation model indicates that the assessment process effectively measures the mapping of the COVID-19 pandemic impact on achieving the SDGs. This assessment identifies that the COVID-19 pandemic acts mostly as a threat in enabling the targets of the SDGs.

INTRODUCTION: Self-management is generally considered a dynamic and collaborative process by individuals and caregivers to manage a chronic condition. Self-management has recently emerged as a promising strategy for stroke rehabilitation. This scoping review aims to examine and summarize self-management strategies utilized by stroke survivors for stroke rehabilitation. METHODS: PubMed, Scopus, CINAHL (EBSCO), Embase, and ProQuest were searched for articles published between January 2010 and December 2021. Studies were selected if they were published in English in a peer-reviewed journal, utilized a non-experimental research design, and focused on adult stroke survivors. All relevant information from the included articles was extracted in a systematic way using a pre-developed data extraction form. Two authors performed data extraction and quality evaluation independently. All issues were resolved through discussion among the authors. RESULTS: We narratively summarized the findings of 15 quantitative, qualitative, and mixed-method studies, including a total of 1,494 stroke survivors. The stroke survivors used a range of self-management strategies for their stroke rehabilitation, including domains related to lifestyle, social support, communication, knowledge and information, and goal-setting. Gender, age, stroke-related disability, fatigue, self-management education, social support, and communication with others were found to be associated with self-management use in stroke rehabilitation. CONCLUSIONS: This scoping review provides an important overview on stroke survivors' use of self-management strategies and their experience. Their use of self-management strategies is complicated and multifaceted, comprising several domains and involving a diverse range of approaches and personal experiences. However, we identified several gaps in the literature and more research is required.