BACKGROUND: The degree of the development of coronary collaterals is long considered an alternate – that is, a collateral – source of blood supply to an area of the myocardium threatened with vascular ischemia or insufficiency. Hence, the coronary collaterals are beneficial but can also promote harmful (adverse) effects. For instance, the coronary steal effect during the myocardial hyperemia phase and that of restenosis following coronary angioplasty. OBJECTIVES: Our study explores the contribution of coronary collaterals – if any exist – while considering other potential predictors, including demographics and medical history, toward the left ventricular (LV) dysfunction measured through the LV ejection fraction (LVEF). METH

n this research, some thermophysical properties of ethylene glycol with water (H2O) and two solvent mixtures dimethylformamide/ water (DMF + H2O) were studied. The densities (ρ) and viscosities (η) of ethylene glycol in water and a mixed solvent dimethylformamide (DMF + H2O) were determined at 298.15 K, t and a range of concentrations from 0.1 to1.0 molar. The ρ and η values were subsequently used to calculate the thermodynamics of mixing including the apparent molar volume (ϕv), partial molar volume (ϕvo) at infinite dilution. The solute-solute interaction is presented by Sv results from the equation ∅_v=ϕ_v^o+S_v √m. The values of viscosity (B) coefficients and Falkenhagen coefficient(A) of the Jone-Dole equation and Gibbs free

Complexes of 1-phenyl-3-(2(-5-(phenyl amino)-1,3,4-thiadiazole-2-yl)phenyl) thiourea have been prepared and characteizedby elemental analysis, Ff-[R, and u.v./ visible spectra moreover,determination of metal content M%o by flame atomic absorptionspectroscopy, molar conductance in DMSO solution and magneticmoments (peffl.The result showed that the ligand (L) was coordinated to Mn+2, Ni+2,Ct+2,2n+2,Cd+2, and Hg+2 ions through the nitrogen atoms and sulpheratoms.From the result obtained, rhe following general formula [MLCl2] hasbeen given for the prepared complexes with an octahedral geometryaround the metal ions for all complexes.where M= Mn+2, Ni+2, cu+2, zn+2, cd+2, and Hg+2 l= l-phenyl-3-(2-(5-(phenyl amino

Artificial intelligence has quickly invaded the realms of both creative and information-based writing, raising new questions about human originality, authorship and style. Despite its ability to produce writings that are coherent and stylistically varied, there are still concerns over the uniqueness and cultural neutrality of AI programs such as ChatGPT. This review covers significant recent advancements with artificial intelligence applications in both the literary and non-literary fields. It analyzes 35 recent studies contrasting authorship and creativity, or stylistic considerations and impressions, between human and AI texts. These studies range from poetic and fictional writing through essay, news article and academic publicati

Five derivatives of thiadiazole were prepared with aldehydes and alkyl halides, compoundA: 2-amino-5-thiol-1,3,4- thiadiazole, compound B :2-(o-hydroxybenzylidine)amino-5-thiol-1,3,4-thiadiazole, compoundC: 2(2-butan-lidine)amino-5-thiol-1,3,4-thiadiazole, compound E: 2- amino-5-(2-Propanylthio)-1,3,4-thiadiazol) and compound F:2(o-chlorobenzylamino)-5-(2-propanyl thio)-1,3,4 thiadiazol. All prepared compounds were diagnosed by (IR) and (UV) Spectroscopy. All of those compounds were screened for their anti-microbial activity in vitro. The results show that most of the compounds A, B, C exhibited moderate to good activity against Gram-positive bacteria and the same compound exhibit low to moderate activity on most gram-negative bacte

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

In this work, prepared new ligand[3- (1H-indol-3-yl) -2- (3-(4- methoxybenzoyl)thiouereido) propanoic acid](MTP) has been synthesized by reaction of 4-Methoxybenzoyl isothiocyanate with tryptophane(1:1), The ligand was characterized by elemental microanalysis C.H.N.S, FT-IR, UV-Vis and 1H,13C NMR spectra, Some transition metals complexes of this ligand were prepared and characterized by FT-IR, UV-Vis spectra, conductivity measurements, magnetic susceptibility and atomic absorption, From obtained results the molecular formula of all prepared complexes were [M(MTP)2] (M+2 =Mn, Co, Ni, Cu, Zn, Cd and Hg), the proposed geometrical structure for all complexes were tetrahedral except copper complex has a square planer geometry around metallic ion

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD