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bsj-6272
The Immunohistochemically Estimation of CD63 in Iraqi Patients with Gastric Cancer
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CD63 is -one of the tetraspanin family proteins, which are regarded as: hallmark exosomal markers because it is absent from other types of vesicles. It is expressed in the cell membrane of cancer cells, and cytoplasm of stromal cells. Objective: To assess CD63 expression in gastric cancer (GC) patients, and detected if it could be used as a predictive marker. Furthermore, the current study aimed to find the correlation between CD63 expression and clinicopathological parameters as: gender, age, invasion depth, histopathological type, involvement of lymph nodes, grade and stages of GC (TNM). The current study is a retrospective study in the period time from (2018 to-2020); 50 randomly patients formalin-fixed paraffin embedded blocks (FFPE) of stomach tissue (10 cases normal tissue without GC as control, and 40 patients with GC) with its reports and diagnosis were collected from Pathology Department of the Gastroenterology and Hepatology Teaching Hospital and some private hospitals. The histological sections were stained by hematoxylin and eosin stain (H&E), and immunohistochemistry (IHC) stain for CD63. Statistical analysis accomplished by SPSS system at (P ≤ 0.05). This study indicated that there were  significant differences between control group, and patients group in the expression of CD63, also there was a significant correlation between CD63 expression, and histopathological subtype, invasion depth, involvement of lymph node, and stages in patients, whereas there was a non- significant association between the age, grade, and gender of patients, and the expression of CD63.This result indicates that CD63 could be a good prospective marker in Iraqi cancer patients.

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Publication Date
Thu Jun 16 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Optimization algorithms for transportation problems with stochastic demand
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The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m

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Publication Date
Sat May 28 2022
Journal Name
Abstract And Applied Analysis
Discretization Fractional-Order Biological Model with Optimal Harvesting
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In this paper, a discretization of a three-dimensional fractional-order prey-predator model has been investigated with Holling type III functional response. All its fixed points are determined; also, their local stability is investigated. We extend the discretized system to an optimal control problem to get the optimal harvesting amount. For this, the discrete-time Pontryagin’s maximum principle is used. Finally, numerical simulation results are given to confirm the theoretical outputs as well as to solve the optimality problem.

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Publication Date
Wed Oct 07 2020
Journal Name
Journal Of Interdisciplinary Mathematics
Discrete an SIS model with immigrants and treatment
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In this paper, a discrete SIS epidemic model with immigrant and treatment effects is proposed. Stability analysis of the endemic equilibria and disease-free is presented. Numerical simulations are conformed the theoretical results, and it is illustrated how the immigrants, as well as treatment effects, change current model behavior

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Publication Date
Thu Nov 01 2012
Journal Name
Journal Of Craniofacial Surgery
Inferior Alveolar Nerve Injuries Associated With Mandibular Fractures
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The study evaluates the incidence of inferior alveolar nerve injuries in mandibular fractures, the duration of their recovery, and the factors associated with them. Fifty-two patients with mandibular fractures involving the ramus, angle, and body regions were included in this study; the inferior alveolar nerve was examined for neurological deficit posttraumatically using sharp/blunt differentiation method, and during the follow-up period the progression of neural recovery was assessed. The incidence of neural injury of the inferior alveolar nerve was 42.3%, comminuted and displaced linear fractures were associated with higher incidence of inferior alveolar nerve injury and prolonged recovery time, and recovery of inferior alveolar nerve fun

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
On New Weibull Inverse Lomax Distribution with Applications
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In this paper, simulation studies and applications of the New Weibull-Inverse Lomax (NWIL) distribution were presented. In the simulation studies, different sample sizes ranging from 30, 50, 100, 200, 300, to 500 were considered. Also, 1,000 replications were considered for the experiment. NWIL is a fat tail distribution. Higher moments are not easily derived except with some approximations. However, the estimates have higher precisions with low variances. Finally, the usefulness of the NWIL distribution was illustrated by fitting two data  sets

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Craniofacial Surgery
Is Orbital Floor Reconstruction With Titanium Mesh Safe?
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Publication Date
Fri Mar 18 2022
Journal Name
Aro-the Scientific Journal Of Koya University
Detecting Deepfakes with Deep Learning and Gabor Filters
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The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

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Publication Date
Sat Jan 01 2022
Journal Name
Intelligent Automation & Soft Computing
A Novel Classification Method with Cubic Spline Interpolation
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Publication Date
Sat Jan 01 2022
Journal Name
Food Science And Technology
Analyzing food production risk with Monte Carlo simulation
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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
System Identification Algorithm for Systems with Interval Coefficients
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In this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.

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