This study investigated the bioethanol production from green algae Chlorella vulgaris depending on its carbohydrate-enriched biomass. Four different phosphorous concentrations were employed to stimulate bioethanol production from Chlorella vulgaris. The impact of various phosphorous values on Chlorella vulgaris growth rate as well as primary product (carbohydrate) were evaluated. High performance liquid chromatography was utilized in this work. The stationary phase was identified as day 14, 12, 10 and 6 in treatments 6, 4, 2 and g/L, respectively. The findings suggest that the treatment without phosphorous addition had the highest record of carbohydrate content (22.64% dry weight) as well as the highest bioethanol yield (20.66% dry weight).

The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of

The present research was conducted to reduce the sulfur content of Iraqi heavy naphtha by adsorption using different metals oxides over Y-Zeolite. The Y-Zeolite was synthesized by a sol-gel technique. The average size of zeolite was 92.39 nm, surface area 558 m2/g, and pore volume 0.231 cm3/g. The metals of nickel, zinc, and copper were dispersed by an impregnation method to prepare Ni/HY, Zn/HY, Cu/HY, and Ni + Zn /HY catalysts for desulfurization. The adsorptive desulfurization was carried out in a batch mode at different operating conditions such as mixing time (10,15,30,60, and 600 min) and catalyst dosage (0.2,0.4,0.6,0.8,1, and 1.2 g). The most of the sulfur compounds were removed at 10 min for all catalyst types. The maximum

An innovative desalination method called electrosorption or capacitive deionization (CDI) has significant benefits for wastewater treatment. This process is performed by using a carbon fiber electrode as a working electrode to remove hexavalent chromium ions from an aqueous solution. The pH, NaCl concentration, and cell voltage were optimized using the Box-Behnken experimental design (BDD) in response surface methodology (RSM) to study the effects and interactions of selected variables. To attain the relationship between the process variables and chromium removal, the experimental data were subjected to an analysis of variance and fitted with a quadratic model. The optimum conditions to remove Cr(VI) ions were: pH of 2, a cell voltage of 4.