Molecular dynamics (MD) simulations were carried out in order to investigate the binding mode of axillaridine-A at the active site of human acetylcholinesterase (AChE) enzyme. 2.0 nanosecond of MD simulations was made for the protein and the complex to dynamically explore the active site and the behavior of the ligand at the peripheral AChE binding site. These calculations for the enzyme alone showed that the active site of AChE is located at the bottom of a deep and narrow cavity whose surface is lined with rings of aromatic residues and Tyr72 is almost perpendicular to the Trp286 ring and forms a stable - interaction. The size of the active site of the complex decreases with time due to increase the interaction. Axillaridine-A forms

The study aimed at identifying the mental capacity of the research sample and classifying them for the purposes of the study, preparing the scale of cognitive control of the subject of teaching methods of sports education, preparing educational units by establishing the question network for the subject of the teaching methods of sports education, and adopting the experimental method by experimental design workers (2×2) for the two groups The limits of the research community are represented by third-stage students of the Department of Physical Education and Sports Science in the morning study of the College of Knowledge, the Community University, which continues in the regular working hours of the year (2019-2020) adult Their number

The research aimed to prepare a measure of the importance of enlightenment, academic education, and applied skills for third-stage female students, including teaching methods from their point of view/College of Education and Sports Sciences/University of Baghdad/Al-Jadriyah. The researchers used descriptive description in the comprehensive research procedures, an appropriate methodology in achieving the research objectives, sufficient for interpretations, how important is the academic teacher’s knowledge of teaching methods for student learning, what are the roles that the learners have acquired from the academic teacher. The scale of importance and horror consists of 15 items. The research population includes female students of t

The acceptance sampling plans for generalized exponential distribution, when life time experiment is truncated at a pre-determined time are provided in this article. The two parameters (α, λ), (Scale parameters and Shape parameters) are estimated by LSE, WLSE and the Best Estimator’s for various samples sizes are used to find the ratio of true mean time to a pre-determined, and are used to find the smallest possible sample size required to ensure the producer’s risks, with a pre-fixed probability (1 - P^*). The result of estimations and of sampling plans is provided in tables.

Key words: Generalized Exponential Distribution, Acceptance Sampling Plan, and Consumer’s and Producer Risks

The reaction of 1,5-dimethyl-2-phenyl-1H-pyrazol-3(2H)-one with one equivalent of 4-chlorophenol by coupling reaction afforded (E)-4-((5-chloro-2- hydroxyphenyl)diazenyl)-1,5-dimethyl-2-phenyl-1H-pyrazol-3(2H)-one. Then azo ligand was characterize using spectroscopic studies ( FTIR,UV-Vis, 1H and 13CNMR, Mass) also micro-elemental analysiz (C.H.N.O). Transition metal chelation with Co(II), Ni(II), Cu(II), and Zn(II) was investigated, revealing 1:2 metal-to-ligand stoichiometry with octahedral geometry. The biological, and industrial application for the azo ligand and it is complexes were evaluated, demonstrating antimicrobial activity against bacterial and fungal strains, with the Zn(II) complex exhibiting superior inhibition. Additionally,

In this research was conducted to provide a product to analyze the performance sensor fiber optic used to measure and feel the intensity of the electric field results showed obtained that use sensor long gives reactive high electric field strength and a high value for allergic sensor, but that is at the expense of reducing the intensity of the electric field that is detected

Researchers often equate database accounting models in general and the Resources-Events-Agents (REA) accounting model in particular with events accounting as proposed by Sorter (1969). In fact, REA accounting, database accounting, and events accounting are very different. Because REA accounting has become a popular topic in AIS research, it is important to agree on exactly what is meant by certain ideas, both in concept and in historical origin. This article clarifies the analyzing framework of REA accounting model and highlights the differences between the terms events accounting, database accounting, semantically-modeled accounting, and REA accounting. It als

This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,

An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med