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THE EFFECIENCY OF ENTERIC LACTOBACILLUS IN PREVENTING HEMORRHAGIC COLITIS AND BLOCKING SHIGA TOXINS PRODUCTIONS IN RATS MODELS INFECTED WITH ENTEROHEMORRHAGIC ESCHERICHIA COLI (EHEC)
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The objective of this study was to investigate the prophylactic roles of human enteric derived Lactobacillus plantarum L1 (Ll) and Lactobacillus paracasei L2 (L2), on EHEC O157:H7 infection in rodent models (In vivo). The Lactobacillus suspensions (L1 and L2) were individually and orally administered to experimental rats at a daily two consecutives of 100 μl (108 CFU/ ml/rat) for up to two weeks.  Thereafter, on the 8th day of experiment rats were orally challenged with one dose infection of EHEC (105 CFU/ml/rat). Animals mortality and illness symptoms have been monitored. There was no fatal EHEC infection in rats that had been pre‑colonized with the Lactobacillus strains, while most of EHEC infected rats were died (90%).  The Stx1 and Stx2 levels were significantly lower (14 and 12 folds) in the L1and L2 pre-inoculated rates respectively, compared with those in the EHEC colonized group. Histological sections were proven the prophylactic roles of L1 and L2, whereas, no effective histological upsets were detected in Lactobacillus + EHEC- colonized rats. The cytopathic symptoms were predominant in kidney and intestinal sections of EHEC infected rats. The kidney sections cytopathy manifested to lining membrane ulceration, infiltration of mononuclear cells and glomerular and tubular epithelium necrosis.  The striking attaching and effacing (A/E) lesions were prominent in intestinal sections of EHEC infected animal models.

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Publication Date
Tue Jan 01 2013
Journal Name
Iraqi Journal Of Science
Effect of LPS Extracted from Campylobacter coli on Lymphocyte Transformation
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Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Publication Date
Fri Dec 31 2021
Journal Name
Political Sciences Journal
Alternative Perspectives in Explaining the Conduct of US Foreign Policy: A Historical-Critical View of Decision-Making Models
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Receipt date:2/17/2021 acceptance date:3/16/2021 Publishing date:12/31/2021

Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Objective: This paper investigates the contradictions in the decision-making process of the United States, which historically proven to be successful policies in the short term, but in the long term proven to be wanting and failure. Methodology: The paper uses descriptive, historical, comparative method. A

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Publication Date
Tue Jun 23 2020
Journal Name
Annal S Of Tropical Medicine & Public Health
Histological Evaluation of local application of Phyllunthus amarus extracted powder and its combination with fibronectin protein on Wound Healing of rats
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Background: A wound is defined as a break or damage in the skin, resulting from physical or thermal damage or as a result of the presence of an underlying medical or physical condition. Herbal medicine can be called one of the branches of medicine in various forms.Phyllunthus amarus is a small herb well known for its medicinal properties and widely used worldwide. P. amarus is an important plant of Indian Ayurvedic system of medicine. Fibronectin is a major component of the extracellular matrix. It is secreted by various cells, primarily fibroblasts, as a soluble protein dimer and is then assembled into an insoluble matrix in a complex cell-mediated process. Materials and methods: Forty rats will be subjected for a surgical operation

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Publication Date
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Impact of Different Doses of Nicorandil-Induced Ulceration (Oral , Gastrointestinal Tract, and Anal) in Rats: Roles of Leptin and Prostaglandin E2
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Many reports confirm ulcers as an adverse effect of drugs such as nicorandil and aspirin. The exact responsible mechanisms of ulceration have until now not proved. Mucosal ulcers associated with the onset of ulcer are manifested by an increase in proinflammatory cytokine, excessive prostaglandin, and up-regulation of Endothilin-1 level, which directly impacts the release of leptin. These, released locally within mucosal tissues, have played a role in controlling the extent of local inflammatory responses and processes of mucosal repair.
This study was designed to find out the correlation of plasma leptin and prostaglandin levels as a possible mechanism of oral ulcer formation as an adverse effect of nicorandil. The effect of nicorandi

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Spatial Prediction of Monthly Precipitation in Sulaimani Governorate using Artificial Neural Network Models
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ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Multistage and Numerical Discretization Methods for Estimating Parameters in Nonlinear Linear Ordinary Differential Equations Models.
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Many of the dynamic processes in different sciences are described by models of differential equations. These models explain the change in the behavior of the studied process over time by linking the behavior of the process under study with its derivatives. These models often contain constant and time-varying parameters that vary according to the nature of the process under study in this We will estimate the constant and time-varying parameters in a sequential method in several stages. In the first stage, the state variables and their derivatives are estimated in the method of penalized splines(p- splines) . In the second stage we use pseudo lest square to estimate constant parameters, For the third stage, the rem

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Publication Date
Mon Aug 01 2016
Journal Name
Arpn Journal Of Engineering And Applied Sciences
SURVEY ON VANET TECHNOLOGIES AND SIMULATION MODELS
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Vehicular ad hoc network (VANET) is a distinctive form of Mobile Ad hoc Network (MANET) that has attracted increasing research attention recently. The purpose of this study is to comprehensively investigate the elements constituting a VANET system and to address several challenges that have to be overcome to enable a reliable wireless communications within a vehicular environment. Furthermore, the study undertakes a survey of the taxonomy of existing VANET routing protocols, with particular emphasis on the strengths and limitations of these protocols in order to help solve VANET routing issues. Moreover, as mobile users demand constant network access regardless of their location, this study seeks to evaluate various mobility models for vehi

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