A multisite validation of brain white matter pathways of resilience to chronic back pain.

Chronic back pain (CBP) is a global health concern with significant societal and economic burden. While various predictors of back pain chronicity have been proposed, including demographic and psychosocial factors, neuroimaging studies have pointed to brain characteristics as predictors of CBP. However, large-scale, multisite validation of these predictors is currently lacking.

Fabrication of PVA-PVC composite membrane for enhanced TDS removal from tannery effluent: sustainable water treatment approach.

The environmental burden of tannery wastewater, characterized by high levels of total dissolved solids (TDS) and other contaminants, presents a significant challenge for sustainable water management. This study addresses this issue by developing a novel polyvinyl alcohol (PVA) and polyvinyl chloride (PVC) composite membrane optimized for efficient TDS removal from tannery effluent. The membrane was fabricated using a solution casting technique, with glutaraldehyde employed as a crosslinking agent to enhance mechanical properties and stability.

Molecular detection and epidemiological distribution of poultry respiratory viral pathogens in commercial chicken flocks in Bangladesh.

Respiratory viral infections have a considerable detrimental impact on animal health as well as significant financial consequences in the poultry industry. The primary aim of this study is to investigate the major pathogens involved in respiratory diseases of poultry, the co-infection rate, and their epidemiological distribution in commercial chicken farms in Bangladesh. From June 2022 to December 2023, 300 pooled samples (swabs from live birds, and respiratory tissues from dead birds) were collected from the selected poultry farms where respiratory outbreaks were noticed.

AqUavplant Dataset: A High-Resolution Aquatic Plant Classification and Segmentation Image Dataset Using UAV.

Aquatic vegetation species are declining gradually, posing a threat to the stability of aquatic ecosystems. The decline can be controlled with proper monitoring and mapping of the species for effective conservation and management. The Unmanned Ariel Vehicle (UAV) aka Drone can be deployed to comprehensively capture large area of water bodies for effective mapping and monitoring.

Optimizing coastal groundwater quality predictions: A novel data mining framework with cross-validation, bootstrapping, and entropy analysis.

Investigating the potential of novel data mining algorithms (DMAs) for modeling groundwater quality in coastal areas is an important requirement for groundwater resource management, especially in the coastal region of Bangladesh where groundwater is highly contaminated. In this work, the applicability of DMA, including Gaussian Process Regression (GPR), Bayesian Ridge Regression (BRR) and Artificial Neural Network (ANN), for predicting groundwater quality in coastal areas was investigated. The optuna-based optimized hyperparameter is proposed to improve the accuracy of the models, including optuna-GPR and optuna-BRR as benchmark models.