Prevalence and predictors of musculoskeletal injuries among gym members in Bangladesh: A nationwide cross-sectional study.

Background: Participating in physical exercise is advantageous for maintaining optimum health, improving physical capacity, decreasing the likelihood of chronic diseases, and promoting overall wellbeing.

Aim: This study aimed to find out the prevalence and factors that contribute to musculoskeletal injuries among individuals who participated in fitness activities at the gym.

Methods: This cross-sectional study included 1123 gym members, both male and female, aged between 18 and 50 years, from selected fitness centers in Bangladesh.

Strategies for deep learning-based attenuation and scatter correction of brain F-FDG PET images in the image domain.

Background: Attenuation and scatter correction is crucial for quantitative positron emission tomography (PET) imaging. Direct attenuation correction (AC) in the image domain using deep learning approaches has been recently proposed for combined PET/MR and standalone PET modalities lacking transmission scanning devices or anatomical imaging.

Purpose: In this study, different input settings were considered in the model training to investigate deep learning-based AC in the image space.

One-Step Synthesis of Ultrasmall Nanoparticles in Glycerol as a Promising Green Solvent at Room Temperature Using Omega-Shaped Microfluidic Micromixers.

Despite innovations in the synthesis protocol of nanoparticles (NPs), the size distribution and uniformity of particles still remain as crucial attributes. Homogeneous and rapid nucleation is a critical phenomenon to obtain monodisperse nanoparticles. Herein, we have carried out the synthesis of metal nanoparticles in a customized microfluidic (MF) chip, with 18 omega-shaped micromixers, by using glycerol as a promising green solvent and reducing agent at various concentrations (10-80%), and simultaneous comparison of the results from batch synthesis.

IoT and Ensemble Long-Short-Term-Memory-Based Evapotranspiration Forecasting for Riyadh.

Evapotranspiration (ET) is the fundamental component of efficient water resource management. Accurate forecasting of ET is essential for efficient water utilization in agriculture. ET forecasting is a complex process due to the requirements of large meteorological variables.

Performances of leading Islamic finance markets prior to and during the COVID-19 pandemic.

The recent COVID-19 pandemic or Global Health Crisis (GFH) has distorted the normal functioning of the global economies and financial markets. Previous research has shown that Islamic equities were relatively more stable than conventional ones during the 2008 Global Financial Crisis (GFC). So, this study aims to assess the effect of the COVID-19 pandemic on the performance and co-movement of the leading Islamic finance markets by employing MGARCH-DCC on daily frequency data spanning from January 01, 2017 to October 22, 2021.