The aim of this research is to construct a cognitive behavior program based on the theory of Meichenbaum in reducing the emotional sensitivity among Intermediate school students. To achieve the aims of the research, two hypotheses were formulated and the experimental design with equal groups was chosen. The population of research and its sample are determined. The test of negative emotional sensitivity, which is constructed by the researcher, was adopted. The test contains (20) items proved validity and reliability as a reliable test by presenting it to a group of arbitrators and experts in education and psychology. An educational program is constructed based on the theory of Meichenbaum. The test was applied to a sample of (60) second i

Cumulative lifetime lead (Pb) exposure has been associated with accelerated declines in cognition through the free radical generation and epigenetic effects. Several pieces of literature have identified a correlation between exposure to lead and neurodegenerative disorders. Harwich strain Drosophila melanogaster was exposed to lead acetate for two weeks, and changes in pulse transmission by acetylcholinesterase and systemic redox were evaluated. Besides, molecular docking studies of acetylcholinesterase against Quercetin and its most common derivatives contained in food have been performed. Pharmacokinetic studies on Quercetin and its derivatives have also been performed in silico toxicity. The data obtained showed alterations in antioxi

Ganciclovir (GCV) is a drug included in BCS-Class III, having high solubility and low permeability. It is a synthetic acyclic nucleoside analog of 2′-deoxyguanosine, considered a potent inhibitor of herpes viruses and cytomegalovirus (CMV) infection. Herpes simplex virus (HSV) infections are very common and are also considered a major cause of corneal blindness. This study intended to advance a pioneering nanostructured lipid carriers (NLCs) system for improving the ocular permeability of GCV. Several procedures were used for the preparation. Cold homogenization, solvent injection, and emulsifi cationultrasonication methods. A mixture of palmitic acid (PA) and oleic acid (OA) as a lipid matrix, cremophore EL, and transcutol HP wer

In drilling processes, the rheological properties pointed to the nature of the run-off and the composition of the drilling mud. Drilling mud performance can be assessed for solving the problems of the hole cleaning, fluid management, and hydraulics controls. The rheology factors are typically termed through the following parameters: Yield Point (Yp) and Plastic Viscosity (μp). The relation of (YP/ μp) is used for measuring of levelling for flow. High YP/ μp percentages are responsible for well cuttings transportation through laminar flow. The adequate values of (YP/ μp) are between 0 to 1 for the rheological models which used in drilling. This is what appeared in most of the models that were used in this study. The pressure loss

Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d