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jih-3254
Isolation and Identification of Endophytic Fungi from Aloe vera Leaves and Chemical Analysis of the Alcoholic Extract of the Leaves Using HPLC, GC, and GC-Mass Devices
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The study's goals were to separate and identify endophytic fungi from Aloe vera leaves by looking at their morphology and molecules, as well as to find the chemical compounds in the leaf extract by using HPLC, GC, and GC-Mass instruments. The results showed that 53 endophytic fungi were isolated from a total of 120 pieces of A. vera leaves, with a total colonization rate of 44.16%. The fungus Aspergillus terreus had a colonization rate of 14.16%; Aspergillus niger had a colonization rate of 13.33%; Penicillium chermesinum demonstrated a colonization rate of 6.66%; Paecilomyces variotii had a colonization rate of 2.5%; Talaromyces radicus; and Aspergillus flavus achieved a colonization rate of 1.66%. Finally, the fungi Aspergillus quadrilineatus, Talaromyces verruculosus, Neoscytalidium dimidiatum, Alternaria solani, and Aspergillus niveus achieved a colonization rate of 0.83%. The results of examining the alcoholic extract of the leaves using the HPLC device showed the presence of the chemical compounds aloin at a concentration of 125.39 ppm and aloe emodin at a concentration of 66.59 ppm. We looked at the leaf alcoholic extract with a GC machine and found a group of fatty acids. These included linoleic, oleic, palmitic, and stearic. The GC-MS test revealed a group of active compounds, including Heptane, 1-(ethenylthio), Ethanedicarboxamide, N-allyl-N'-(2,5-dimethylphenyl), 2H-Pyran, 2-(3-butynyloxy) tetrahydro, 1,2-Cyclobutanedicarboxylic acid, 3-methyl-dimethyl ester and 4 (1H)-Pyrimidinone, 2-(propylthio). The presence of endophytic fungi from which effective enzymes or compounds can be isolated could probably have an important role in future medical and therapeutic uses. Also, the leaves of the A. vera plant have medicinal and therapeutic uses for many diseases.

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
STATISTICAL ANALYSIS OF PATIENTS INFECTED WITH CORONAVIRUS USING MANOVA
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Investigating the Influence of Precursor Concentration on the Photodegradation of Methylene Blue using Biosynthesized ZnO from Pometia pinnata Leaf Extracts
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The ZnO nanoparticles were synthesized at various precursor concentrations i.e. 0.05, 0.1, and 0.5 M by biosynthesis method based on Pometia pinnata Leaf Extracts. Initial nanoparticle concentration influenced the optical bandgap, shape, and structure of nanoparticles. The photodegradation process was carried out under UV illumination. The efficiency of MB degradation was determined by measuring the decrease in MB concentration and by analyzing the optical absorption at 663 nm recorded by UV-Vis spectroscopy. Results showed that the biosynthesized ZnO nanoparticles exhibited efficient photodegradation of MB, with a maximum degradation rate of 80% after 90 minutes of exposure to UV-C light. The study highlights the potential of Pometia pi

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Publication Date
Mon Oct 17 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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Publication Date
Fri Jun 12 2015
Journal Name
Chemistry And Materials Research
Synthesis, Physico-Chemical and Antimicrobial Activities Co(II),Ni (II) ,Cu(II), Zn(II),Cd(II) and Hg(II) MixedLigand Complexes of L- Alanine and Trimethoprim Antibiotic
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The Co (II), Ni (II) ,Cu(II), Zn(II) ,Cd(II) and Hg(II) complexes of mixed of amino acid (L-Alanine ) and Trimethoprim antibiotic were synthesized. The complexes were characterized using melting point, conductivity measurement and determination the percentage of the metal in the complexes by flame (AAS). Magnetic susceptibility, Spectroscopic Method [FT-IR and UV-Vis]. The general formula have been given for the prepared mixed ligand complexes [M(Ala)2(TMP)(H2O)] where L- alanine (abbreviated as (Ala ) = (C5H9NO2) deprotonated primary ligand, L- Alanine ion .= (C5H8NO2-) Trimethoprim (abbreviated as (TMP ) = C10H11N3O3S M(II) = Co (II),Ni(II) ,Cu(II), Zn(II) ,Cd(II) and Hg(II). The results showed that the deprotonated L- Alanine b

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Publication Date
Wed Nov 13 2019
Journal Name
Al-kindy College Medical Journal
Disturbances of Amino Acid Metabolism in Neurologic Disorders detected by fluorescent high performance liquid chromotograghy (HPLC) in Baghdad - IRAQ
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Background:Amino acid disorders are a major group of inborn error metabolism (IEM) with variable clinical presentation; its diagnosis constitutes a real challenge in a community with high consanguinity rate and no systematic newborn screening.

Objectives: to provide data about amino acid disorders detected in high-risk Iraqi children by using quantitative amino acid fluorescent high performance liquid chromatography (HPLC) analysis.

Type of the study: Cross-sectional study.

Methods: a descriptive cross sectional study from 1st February to 1st December 2014, at Neurological ward and clinic of the Children Welfare teaching Hospital, in Baghdad - Ira

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Publication Date
Tue Jun 01 2010
Journal Name
Al-mustansiriya Journal For Sciences And Education
Synthesis and Identification of metal complexes of 1-phenyl-3,(2-(5-phenyl amine-1,3,4-thiadiazole-2-yl) phenyl thiourea
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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

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Synthesis, Characterization and the Corrosion Inhibition Study of Two Schiff Base Ligands Derived From Urea and Thiourea and Their Complexes with Cu(II) and Hg(II) Ions
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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Publication Date
Sat Aug 24 2024
Journal Name
Mathematics
Identification of Time-Wise Thermal Diffusivity, Advection Velocity on the Free-Boundary Inverse Coefficient Problem
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This paper is concerned with finding solutions to free-boundary inverse coefficient problems. Mathematically, we handle a one-dimensional non-homogeneous heat equation subject to initial and boundary conditions as well as non-localized integral observations of zeroth and first-order heat momentum. The direct problem is solved for the temperature distribution and the non-localized integral measurements using the Crank–Nicolson finite difference method. The inverse problem is solved by simultaneously finding the temperature distribution, the time-dependent free-boundary function indicating the location of the moving interface, and the time-wise thermal diffusivity or advection velocities. We reformulate the inverse problem as a non-

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