Predicting the anticancer activity of indole derivatives: A novel GP-tree-based QSAR model optimized by ALO with insights from molecular docking and decision-making methods.

Indole derivatives have demonstrated significant potential as anticancer agents; however, the complexity of their structure-activity relationships and the high dimensionality of molecular descriptors present challenges in the drug discovery process. This study addresses these challenges by introducing a modified GP-Tree feature selection algorithm specifically designed for regression tasks and high-dimensional feature spaces. The algorithm effectively identifies relevant descriptors for predicting LogIC values, the target variable.

Maximizing chitin and chitosan recovery yields from Fusarium verticillioides using a many-factors-at-a-time approach.

The extraction of chitin and chitosan presents challenges due to the complexity of the process and the influence of many variables. This study aimed to optimize chitin and chitosan extraction from Fusarium verticillioides by analyzing many additives and processing variables and modeling their yields using multiple linear regression (MLR) and evolutionary algorithms. FT-IR analysis confirmed the presence of characteristic bands in the extracted samples, and SEM analysis further revealed the microfibrillar appearance of the chitin and the dense, non-porous structure of the chitosan.

Modeling Predictors of Medication Waste Reduction Intention in Algeria: Extending the Theory of Planned Behavior.

COVID-19 caused an increase in the demand for medications, which led to an increase in pharmaceutical waste and there is no doubt that this contributes to environmental pollution. Hence, it became necessary to search for how to protect and improve the environment by encouraging the behavior of medication waste reduction. Accordingly, this study aims to investigate the factors affecting intentions to reduce medication waste.

Experimental Analysis and Neural Network Modeling of the Rheological Behavior of Xanthan Gum and Its Derivatives.

The main objective of this study was to create a mathematical tool that could be used with experimental data to predict the rheological flow behavior of functionalized xanthan gum according to the types of chemical groups grafted onto its backbone. Different rheological and physicochemical analyses were applied to assess six derivatives synthesized via the etherification of xanthan gum by hydrophobic benzylation with benzyl chloride and carboxymethylation with monochloroacetic acid at three (regent/polymer) ratios R equal to 2.4 and 6.

Green synthesis of copper oxide nanoparticles using plant extract and a study of their antifungal, antibacterial activity and photocatalytic performance under sunlight.

In the present work, copper oxide (CuO NPs) was synthesized by an eco-friendly, simple, low-cost, and economical synthesis method using aqueous plant extract as a reducing and capping agent. The biosynthesized CuO-NPs were compared with chemically obtained CuO-NPs to investigate the effect of the preparation method on the structural, optical, morphological, antibacterial, antifungal, and photocatalytic properties under solar irradiation. The CuO NPs were characterized using X-ray diffraction (XRD), UV-VIS spectroscopy, Fourier transform infrared spectrometer (FTIR) analysis, and field emission scanning electron microscopy with energy dispersive X-ray spectroscopy (FESEM-EDX).

The first evidence of a new genotype of nephropathogenic infectious bronchitis virus circulating in vaccinated and unvaccinated broiler flocks in Algeria.

Background And Aim: Avian infectious bronchitis virus (IBV) frequently infects broilers and is responsible for severe economic losses to the poultry industry worldwide. It has also been associated with kidney damage in the broiler flocks. The aim of the present study is to determine the presence of IBV and its possible involvement in kidney damage of broiler chicks.

Knowledge base system (KBS) applied on corrosion damage assessment on metallic structure pipes.

This paper aims to outline a proposed knowledge base system (KBS) for the assessment of corrosive damage on metallic pipe conduits. KBS is developed by using two information sources available for assessing the corrosive damage of pipes which are mainly: expert knowledge and field data. In our knowledge, it's a new method that assists the engineer in his task for assessing the degree of damage on metallic pipes, yielding therefore to a rational evaluation of the corrosive damage (hence the ECOR system) on metallic structures of pipeline, and permits to assign the damage degree on the structure qualitatively while using a ladder of indications representing the severity of each damage type (pitting, crater, weight loss and crack), regarding the priority of either repairing or replacing the metal piece.