Disability and depression among stroke survivors attending rehabilitation facilities at three designated tertiary care hospitals in Bangladesh: A cross-sectional study.

Background: Poststroke depression (PSD) is a highly prevalent and serious mental health condition affecting a significant proportion of stroke survivors worldwide. While its exact causes remain under investigation, managing PSD presents a significant challenge.

Aim: This study aimed to evaluate the prevalence and predictors of depression among Bangladeshi stroke victims.

Recent Advances in Enantiorecognition and Enantioseparation Techniques of Chiral Molecules in the Pharmaceutical Field.

Enantioseparation and enantiorecognition are crucial in the pharmaceutical analysis of chiral substances, impacting safety, efficacy, and regulatory compliance. Enantioseparation refers to the process of separating enantiomers from a mixture, typically achieved through chromatography techniques like HPLC and SFC. In contrast, enantiorecognition involves the identification of enantiomers based on their interaction with a chiral selector without the need for separation.

First report on comprehensive genomic analysis of a multidrug-resistant Enterobacter asburiae isolated from diabetic foot infection from Bangladesh.

Enterobacter asburiae (E. asburiae) is a gram-negative rod-shaped bacterium which has emerging significance as an opportunistic pathogen having high virulence pattern and drug resistant properties. In this study, we present the detailed analysis of the whole genome sequence of a multidrug-resistant (MDR) E.

3D highly isolated 6-port tri-band MIMO antenna system with 360° coverage for 5G IoT applications based machine learning verification.

A multipurpose antenna system that can handle a broad area of frequencies is crucial in the effort to build up widespread 5G Internet-of-Things (IoT) networks. For fifth-generation Internet-of-things applications, this research introduces a new multi-band antenna that can operate in the sub-6 GHz band (2-7 GHz), Ku-band (13-17.5 GHz), and millimeter wave band (25-39 GHz).

Automatic detection, classification, and segmentation of sagittal MR images for diagnosing prolapsed lumbar intervertebral disc.

Magnetic resonance (MR) images are commonly used to diagnose prolapsed lumbar intervertebral disc (PLID). However, for a computer-aided diagnostic (CAD) system, distinguishing between pathological abnormalities of PLID in MR images is a challenging and intricate task. Here, we propose a comprehensive model for the automatic detection and cropping of regions of interest (ROI) from sagittal MR images using the YOLOv8 framework to solve this challenge.