Rabbi

Obesity and type 2 diabetes (DM) are risk factors for severe COVID-19 outcomes, which disproportionately affect South Asian populations. This study aims to investigate the humoral and cellular immune responses to SARS-CoV-2 in adult COVID-19 survivors with obesity and DM in Bangladesh. In this cross-sectional study, SARS-CoV-2-specific antibody and T cell responses were investigated in 63 healthy and 75 PCR-confirmed COVID-19 recovered individuals in Bangladesh, during the pre-vaccination first wave of the COVID-19 pandemic in 2020...

This study investigated cyclic magneto-hydrodynamic radiative effects in Casson and Maxwell fluids, including nonlinear radiation and Arrhenius activation energy. It promotes non-Newtonian fluid use in diverse fields like industry, manufacturing, sciences, medicine, and engineering. Using boundary layer approximations, non-dimensional equations are formulated. For numerical solutions, widely recognized explicit finite difference method (EFDM) has been utilized. To ensure the robustness of EFDM results, stability and convergence tests are performed...

The RHMCD-20 dataset offers a thorough investigation of the dynamics of mental health in Bangladesh while under quarantine. The structured survey that was distributed to different demographic groups yielded a dataset that included a wide range of variables, such as age, gender, occupation, and stress levels. Predictive modelling, understanding the effects of quarantine on the workplace and society, and intergenerational insights are all greatly enhanced by this dataset. The dataset allows intelligent algorithms to be developed by bridging the gap between machine learning and healthcare...

Studies focusing on the safety and common side effects of vaccines play a crucial role in enhancing public acceptance of vaccination. Research is scarce regarding the usage of COVID-19 vaccines and the side effects experienced by health professions students in India and other countries. This study aimed to document self-reported side effects associated with COVID-19 vaccination among medical and dental students of six medical and dental colleges and teaching hospitals in four states (Tamil Nadu, Madhya Pradesh, Gujarat, and West Bengal) of India...

Learning from point sets is an essential component in many computer vision and machine learning applications. Native, unordered, and permutation invariant set structure space is challenging to model, particularly for point set classification under spatial deformations. Here we propose a framework for classifying point sets experiencing certain types of spatial deformations, with a particular emphasis on datasets featuring affine deformations. Our approach employs the Linear Optimal Transport (LOT) transform to obtain a linear embedding of set-structured data...

With the increasing interest in microplastics (MPs) pollutants, quantitative analysis of MPs in water environment is an important issue. Vibrational spectroscopy, represented by Raman spectroscopy, is widely used in MP detection because they can provide unique fingerprint characteristics of chemical components of MPs, but it is difficult to provide quantitative information. In this paper, an ingenious method for quantitative analysis of MPs in water environment by combining Raman spectroscopy and convolutional neural network (CNN) is proposed...

Women in coastal areas are particularly vulnerable to climate change impacts due to existing gender inequality and socio-cultural norms in Bangladesh. This research aims to explore the vulnerability of women to climate change-induced natural hazards, the challenges they face due to the chain impacts of climate change, and the resulting violation of women's rights. Quantitative and qualitative data were used in this study, where 260 structured questionnaire surveys and 15 Focus Group Discussions were performed at Mongla and Shyamnagar Upazilas in Bagerhat and Satkhira districts, respectively...

Drinking water disinfection can result in the formation disinfection byproducts (DBPs, > 700 have been identified to date), many of them are reportedly cytotoxic, genotoxic, or developmentally toxic. Analyzing the toxicity levels of these contaminants experimentally is challenging, however, a predictive model could rapidly and effectively assess their toxicity. In this study, machine learning models were developed to predict DBP cytotoxicity based on their chemical information and exposure experiments. The Random Forest model achieved the best performance (coefficient of determination of 0...

Cerebral palsy (CP) includes a group of neurological conditions caused by damage to the developing brain, resulting in maladaptive alterations of muscle coordination and movement. Estimates of joint moments and contact forces during locomotion are important to establish the trajectory of disease progression and plan appropriate surgical interventions in children with CP. Joint moments and contact forces can be estimated using electromyogram (EMG)-informed neuromusculoskeletal models, but a reduced number of EMG sensors would facilitate translation of these computational methods to clinics...

BACKGROUND: Africa is blessed with vast arable land and enriched with valuable natural resources encompassing both renewable (like water, forests, and fisheries) and non-renewable (such as minerals, coal, gas, and oil). Under the right conditions, a natural resource boom should serve as an important driver for growth, development, and the transition from cottage industry to factory output. However, despite its wealth, Africa is often associated with the notion of a resource curse. Negative outcomes are often linked with mineral wealth...

This paper presents a new end-to-end signal classification method using the signed cumulative distribution transform (SCDT). We adopt a transport generative model to define the classification problem. We then make use of mathematical properties of the SCDT to render the problem easier in transform domain, and solve for the class of an unknown sample using a nearest local subspace (NLS) search algorithm in SCDT domain. Experiments show that the proposed method provides high accuracy classification results while being computationally cheap, data efficient, and robust to out-of-distribution samples with respect to the existing end-to-end classification methods...

We examine relationships among ultra-Orthodox Israeli Jews, their doctors, and rabbis when medical decisions are made. Analyzing excerpts from sixteen focus groups with 128 ultra-Orthodox Jews, we determine how their belief system affects their decisions about whom to trust and follow when the doctor's instructions contradict the rabbi's advice. We argue that the strict behaviors described here with regard to relations among doctors, rabbis, and patients, function as social capital that raises the status of ultra-Orthodox Jews as members of an exclusive club that balances health decisions with the social demand to obey their religious leaders...

OBJECTIVES: This research was conducted to explore the patterns and behavior of panic purchasing, stockpiling, and use of drugs during COVID-19 in the Sylhet city, Bangladesh. STUDY DESIGN: The study adopted qualitative exploratory research design. METHODS: 25 in-depth interviews with drug sellers and clients and 7 key informant interviews were conducted with pharmacists and medical representatives of pharmaceutical companies in Sylhet city in Bangladesh from October 2020 to March 2021...

In modern psychiatry, drug addiction is considered as mainly a mental disorder and a brain disease problem, of complex aetiology. In addition, drug addiction has been characterized as a loss of willpower or akrasia, and even a sin. In this essay, I analyse Maimonides' (Rambam's) treatises More Ha-Nevuchim ( Guide for the Perplexed ) and Shemona Perakim ( The Eight Chapters ). He asserts that the soul is one, but has many different faculties (functions) and is intrinsically linked to the body. I argue that drug addiction is a psychological, social-moral deviance, as well as straying from God's path...

Type 2 diabetes mellitus is a major risk factor for hepatocellular carcinoma (HCC). Changes in extracellular matrix (ECM) mechanics contribute to cancer development1,2 , and increased stiffness is known to promote HCC progression in cirrhotic conditions3,4 . Type 2 diabetes mellitus is characterized by an accumulation of advanced glycation end-products (AGEs) in the ECM; however, how this affects HCC in non-cirrhotic conditions is unclear. Here we find that, in patients and animal models, AGEs promote changes in collagen architecture and enhance ECM viscoelasticity, with greater viscous dissipation and faster stress relaxation, but not changes in stiffness...

The present research explores linear as well as nonlinear radiation patterns based on the MHD non-Newtonian (Maxwell) nanofluid flow having Arrhenius activation energy. This study's core focus is MHD properties in non-Newtonian fluid dynamics and boundary layer phenomena analysis. It initiates with time-dependent equations, employing boundary layer approximations. Extensive numerical computations, executed with custom Compact Visual Fortran code and the EFD method, provide profound insights into non-Newtonian fluid behavior, revealing intricate force interactions and fluid patterns...

Making sense of the social world is an intricate process heavily influenced by cultural elements. Gambling is a prevalent leisure-time activity characterized by risk-taking conduct. While some individuals who engage in it do so without experiencing any harm, others will develop gambling problems. Judaism tends to perceive gambling negatively since it contradicts fundamental Jewish principles. The current study focuses on the Jewish Ultra-Orthodox community in Israel which is characterized as a cultural enclave with minimal interaction with the secular world...

Stercularin is a coumarin, isolated from the ethyl acetate fraction of stem bark and leaves of S. diversifolia. Pharmacologically it is active against cancer, diabetes, and inflammation etc. The molecule is further screened for in vitro pharmacological activities. In addition, a detailed description on its drug likeness and pharmacokinetic profile has been established to further explore its fate as a drug candidate. Stercularin exhibited antiglycation, immunomodulatory, and leishmanicidal activity in three different in vitro models...

Type 2 diabetes (T2D) is one of the major metabolic disorders in humans caused by hyperglycemia and insulin resistance syndrome. Although significant genetic effects on T2D pathogenesis are experimentally proved, the molecular mechanism of T2D in South Asian Populations (SAPs) is still limited. Hence, the current research analyzed two Gene Expression Omnibus (GEO) and 17 Genome-Wide Association Studies (GWAS) datasets associated with T2D in SAP to identify DEGs (differentially expressed genes). The identified DEGs were further analyzed to explore the molecular mechanism of T2D pathogenesis following a series of bioinformatics approaches...

BACKGROUND AND OBJECTIVE: Diabetic retinopathy (DR) is a global health concern among diabetic patients. The objective of this study was to propose an explainable machine learning (ML)-based system for predicting the risk of DR. MATERIALS AND METHODS: This study utilized publicly available cross-sectional data in a Chinese cohort of 6374 respondents. We employed boruta and least absolute shrinkage and selection operator (LASSO) based feature selection methods to identify the common predictors of DR...