Proteomic Profiling and Pre-Clinical Efficacy of Antimicrobial Lithium Complex and Colistin Combination against Multi-drug Resistant Acinetobacter baumannii.

Multi-drug resistant (MDR) Acinetobacter baumannii accounts for high mortality rates in hospital-acquired infections. Colistin is the last resort treatment despite nephrotoxic effects and the emergence of colistin resistant A. baumannii.

Awareness and Implementation of Sports Injury Prevention Programs Among Physical Therapists in Saudi Arabia: A Cross-Sectional Study.

: Sports injury prevention programs (SIPPs) are crucial for mitigating sports injuries and enhancing athletes' performance. In Saudi Arabia, the sports sector is growing, and the awareness and implementation of sports injury prevention programs (SIPPs) among physical therapists require examination. This study aims to evaluate physiotherapists' awareness of and the implementation of sports injury prevention programs (SIPPs) in the Saudi Arabian region with findings that could enhance rehabilitation and sports injury prevention practices.

ELW-CNN: An extremely lightweight convolutional neural network for enhancing interoperability in colon and lung cancer identification using explainable AI.

Cancer is a condition in which cells in the body grow uncontrollably, often forming tumours and potentially spreading to various areas of the body. Cancer is a hazardous medical case in medical history analysis. Every year, many people die of cancer at an early stage.

E-waste recycling in an optimized way for copper recovery by leaching and a case study on E-waste generation and management in Dhaka city.

The widespread adoption of electronic devices has enhanced living standards but has also led to a surge in electronic waste (e-waste), creating serious environmental and health challenges. Although various methods exist to recover valuable metals from e-waste, each has notable drawbacks. Among these, chemical leaching with aqua regia is widely used but is both highly corrosive and hazardous.

Inverse Gini indexed averaging: A multi-leveled ensemble approach for skin lesion classification using attention-integrated customized ResNet variants.

Objective: To improve the accuracy and explainability of skin lesion detection and classification, particularly for several types of skin cancers, through a novel approach based on the convolutional neural networks with attention-integrated customized ResNet variants (CRVs) and an optimized ensemble learning (EL) strategy.

Methods: Our approach utilizes all ResNet variants combined with three attention mechanisms: channel attention, soft attention, and squeeze-excitation attention. These attention-integrated ResNet variants are aggregated through a unique multi-level EL strategy.