It is important that real time stability in smart grids is ensured as the integration of renewables and the complexity of the systems grows. In this paper, we provide a solid architecture, which combines a Residual CNNLSTM deep neural network predictor, FPGA-accelerated Model Predictive Control (MPC), and SHAP-based explainability. The proposed method predicted with 99.8% accuracy using the Electrical grid Stability Simulated Dataset (UCI) and minimized the instability rates surpassing 85 percent in all operating conditions. Meeting real-time operating needs, FPGA deployment on a Xilinx Zynq UltraScale+ provided 3.1 ms latency and 5 times reduced energy consumption against CPU processing. By emphasizing bus voltage and frequency as major in

Commercial, industrial, and military activity, largely in the 19th and 20th centuries, have led to  environmental pollution that can threaten human health and ecosystem function, liquid gas petroleum (LPG) products are the major sources of energy for industry and daily life that cause environmental contamination during various stages of production, transportation, refining and use. Screening of bacterial isolate by using clear zone techniques and biomass and optical density. Results revealed that isolate Burkholdaria cepatia showed a high ability for hydrocarbons biodegradation and this isolate identified depending on morphological cultural, gram stain, microscopic features, biochemical tests, and VITEK2 compact.   In this study,

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

AlxSb1-x compounds with different aluminum content(x=0.1, 0.3 , 0.5 , 0.7 and 0.9 ) were prepared by mixing the two elements in the appropriate ratios in quartz ampulla which then sealed and put in an oven at 1273 and left 5 hours. The obtained powder were grinded and then pressed in pellets shape which will be the target to prepare thin films samples. AlxSb1-x thin films were synthesized by PLD with ~ 150nm in thickness .The structures of AlxSb1-x powders and thin films were determined using X–ray diffraction. The data revealed that all the prepare AlxSb1-x bulk and thin films have polycrystalline . The results showed that increasing of Al reduced the crystallinity of the prepared samples at the first but then the opposite take pla

Background Green synthesis of silver nanoparticles (AgNPs) using plant extracts has gained increasing attention as an environmentally friendly alternative to conventional chemical methods. Salix alba L contains bioactive phytochemicals that can act as reducing and stabilizing agents during nanoparticle synthesis. This study aimed to synthesize AgNPs using an aqueous bark extract of S. alba and to evaluate their antimicrobial and cytogenetic effects. Methods Silver nanoparticles were synthesized by mixing S. alba aqueous e

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