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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
Wed Dec 23 2020
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
Heuristic and Meta-Heuristic Optimization Models for Task Scheduling in Cloud-Fog Systems: A Review
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Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th

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Publication Date
Tue Dec 30 2014
Journal Name
College Of Islamic Sciences
Excuse for ignorance in Islamic law         Financial transactions: (Contemporary Applied Models)
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The researcher highlighted in his research on an important subject that people need, which is the excuse of ignorance in Islamic law. , As the flag of light and ignorance of darkness. Then the researcher lameness of the reasons for research in this subject as it is one of the assets that should be practiced by the ruler and the judge and the mufti and the diligent and jurisprudent, but the public should identify the issues that ignore ignorance and issues that are not excused even if claimed ignorance.
 Then the researcher concluded the most important results, and recommendations that he wanted to set scientific rules for students of science and Muslims in general, to follow the issues of legitimacy and learn its provisions and i

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Publication Date
Mon Nov 09 2020
Journal Name
Construction Research Congress 2020
Alternative Risk Models for Optimal Investment in Portfolio-Based Community Solar
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Publication Date
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
Mon Feb 01 2016
Journal Name
Swarm And Evolutionary Computation
Improving the performance of evolutionary multi-objective co-clustering models for community detection in complex social networks
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Publication Date
Wed Dec 02 2020
Journal Name
International Journal Of Pharmaceutical Research
Therapeutic efficacy of protein compound extraction fromMetapenaeusaffinisagainst glucosamine sulphate-induced nephrotoxicity in male rats
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Publication Date
Wed May 31 2023
Journal Name
Research Journal Of Pharmacy And Technology
Renoprotective effects of Guggulsterone against Cisplatin-Induced Kidney Damage in White Female Albino Rats
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Background: Gugglusterone has been reported to provide protection against inflammatory and oxidative reactions of different pathological conditions. Objectives: The main object of this research work is to evaluate the renoprotective effects of guggulsterone in the prevention of cisplatin-induced nephrotoxicity in rats via assessment of renal function and histological study. Materials and methods: Rats in this study were split into four groups which comprise a control group, an induction group, a third group receiving low-dose guggulsterone, and a fourth group receiving high-dose guggulsterone. Results: a single dose of cisplatin drug has jeopardisedrenal physiology that has been demonstrated in histopathology sections and elevation

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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 Sep 25 2022
Journal Name
Lubricants
Development of Hybrid Intelligent Models for Prediction Machining Performance Measure in End Milling of Ti6Al4V Alloy with PVD Coated Tool under Dry Cutting Conditions
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Ti6Al4V alloy is widely used in aerospace and medical applications. It is classified as a difficult to machine material due to its low thermal conductivity and high chemical reactivity. In this study, hybrid intelligent models have been developed to predict surface roughness when end milling Ti6Al4V alloy with a Physical Vapor Deposition PVD coated tool under dry cutting conditions. Back propagation neural network (BPNN) has been hybridized with two heuristic optimization techniques, namely: gravitational search algorithm (GSA) and genetic algorithm (GA). Taguchi method was used with an L27 orthogonal array to generate 27 experiment runs. Design expert software was used to do analysis of variances (ANOVA). The experimental data were

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