An Investigation on the Potential of Utilizing Aluminum Alloys in the Production and Storage of Hydrogen Gas.

The interest in hydrogen is rapidly expanding because of rising greenhouse gas emissions and the depletion of fossil resources. The current work focuses on employing affordable Al alloys for hydrogen production and storage to identify the most efficient alloy that performs best in each situation. In the first part of this work, hydrogen was generated from water electrolysis.

Evaluation of an ergonomically designed schoolbag: Heart rate variability and body discomfort rating.

Background: Unsuitable schoolbags may stress the spine and promote poor body posture, particularly for school students. Global recommendations have suggested that schoolbag weight must not exceed 10% of a healthy student's body mass, which would need continuous monitoring and enforcement.

Objectives: The present study presents a comparison between an ergonomically designed schoolbag, which helps reduce the potential effects of carrying a load, and a commercial one.

Insight into chitosan/zeolite-A nanocomposite as an advanced carrier for levofloxacin and its anti-inflammatory properties; loading, release, and anti-inflammatory studies.

Chitosan/zeolite-A nanocomposite (CH/ZA) was synthesized as a potential carrier for levofloxacin (LVOX) of enhanced technical properties. The CH/ZA composite displayed enhanced loading capacity (425 mg/g) as compared to chitosan (188.8 mg/g) and zeolite-A (234.

Insight into chitosan/mesoporous silica nanocomposites as eco-friendly adsorbent for enhanced retention of U (VI) and Sr (II) from aqueous solutions and real water.

The chitosan chains were integrated with MCM-48 mesoporous silica in an eco-friendly composite (CH/MCM-48) of enhanced adsorption capacity. The prepared CH/MCM-48 composite was applied in systematic retention of U (VI) as well as Sr (II) ions from water as the commonly detected radioactive pollutants. It displayed promising retention capacities of 261.

Driver Missense Mutation Identification Using Feature Selection and Model Fusion.

Driver mutations propel oncogenesis and occur much less frequently than passenger mutations. The need for automatic and accurate identification of driver mutations has increased dramatically with the exponential growth of mutation data. Current computational solutions to identify driver mutations rely on sequence homology.

Wavelet analysis in current cancer genome research: a survey.

With the rapid development of next generation sequencing technology, the amount of biological sequence data of the cancer genome increases exponentially, which calls for efficient and effective algorithms that may identify patterns hidden underneath the raw data that may distinguish cancer Achilles' heels. From a signal processing point of view, biological units of information, including DNA and protein sequences, have been viewed as one-dimensional signals. Therefore, researchers have been applying signal processing techniques to mine the potentially significant patterns within these sequences.