Majmaah University

Dietary manipulations are crucial for enhancing rabbit behavior and performanceAddn. of Berberine-loaded chitosan nanoparticles BER-CNPs to fattened rabbit diets has been shown to alleviate the adverse effects of heat stress.BER-CNPs have been found to improve growth performance, feed efficiency, liver functions, immunity and redox balanceBER-CNPs have been observed to reduce the levels of IL-4, TNF-α, IFN-γ, Amyloid A, and NF-κ B while increasing the levels of NO and LZM

Hydrogen is a clean energy source that is commonly available in the natural world.As an alternative energy option, hydrogen proves exceptionally valuable as green fuel.Hydrogen fuel cells further contribute to unprecedented vehicle efficiencies.One of the main obstacles to hydrogen′s widespread use as an energy source is its safe and effective storage.Because of their intrinsic characteristics, COF-MTF stands out as a new family exhibit notable flexibility and a porous structure making them versatile for hydrogen storage and clean energy applications.This study aimed to develop an innovative Covalent Organic Framework based on melamine-terephthalaldehyde (COF-MTF) for efficient and sustainable hydrogen storage.The COF-MTF was prepared by directly reacting melamine with terephthalaldehyde through a schiff base reaction.Characterization of the sample was conducted using various techniques, including thermogravimetric anal. (TGA), Fourier-transform IR spectroscopy (FTIR), SEM (SEM), and Brunauer-Emmett-Teller (BET) surface area anal.The synthesized COF-MTF networks demonstrated a significant BET surface area of 1986 m².g^-1.It demonstrated notable isosteric heat of adsorption values between 28.7 and 33.5 kJ/mol and achieved a maximum N₂ uptake of 171 mg (N₂)/g at 298 K and 25 atm.Subjected to repeated cycles of H₂ gas adsorption, COF-MTF highlighted exceptional adsorbent stability, maintaining over 99.9 % of its adsorption capacity after 10 cycles.The calculated isosteric heat of hydrogen adsorption by the COF-MTF compound equals 8.447 KJ.mol^-1.With relatively high H₂ uptake, this study highlighted COF-MTF as a promising candidate for advancing green hydrogen storage technologies to achieve sustainable development goals (SDGs).

The viruses has spread globally and have been impacted lives of people socially and economically, which causes immense suffering throughout the world. Thousands of people died and millions of illnesses were brought, by the outbreak worldwide. In order to control the coronavirus pandemic, mathematical modeling proved to be an invaluable tool for analyzing and determining the potential and severity of the illness. This work proposed and assessed a deterministic six-compartment model with a novel stochastic neural network. The significance of the proposed model was demonstrated by numerical simulation in which the results are agreed with sensitivity analysis. Furthermore, the efficacy of stochastic neural network has been proven with the help of numerical simulations. Some investigations have been conducted through graphs and tables that how the vaccination process is helpful to minimize stress in society. The numerical simulations also focused on preventing the community-wide spread of the disease. The lowest residual errors have been achieved by our proposed stochastic neural network and compared with numerical solvers to assess the accuracy and robustness of the proposed approach.