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Artificial Intelligence Based Deep Bayesian Neural Network (DBNN) Toward Personalized Treatment of Leukemia with Stem Cells
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The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of Deep Bayesian Neural Network (DBNN) for the personalized treatment of leukemia cancer has shown a significant tested accuracy for the model. DBNNs used in this study was able to classify images with accuracy exceeding 98.73%. This study depicts that the DBNN can classify cell cultures only based on unstained light microscope images which allow their further use. Therefore, building a bayesian‐based model to great help during commercial cell culturing, and possibly a first step in the process of creating an automated/semiautomated neural network‐based model for classification of good and bad quality cultures when images of such will be available.

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Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
Evaluation of cellular immune response in Golden Hamsters experimentally infected with Leishmania donovani comparing with cellular immune response against chicken Red Blood Cells.
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The Evaluation of the immune response in Golden Hamsters experimentally infected with Leishmania donovani was determined in this study, particularly, the cellular immune response. Follow up has maintained to determine the Delayed Type of Hypersensitivity using skin test both in infected and control lab animals. Chicken red blood cells were used as a parameter to evaluate the immune system; they are dull and have the ability of immunization. Two concentrations of chicken R.B.C were examined to determine which gives the higher titration in Hamsters and those were 1.5 X 109 cell/ml and 3 X 109 cell/ml , the second concentration gave the maximum titration where then used in this work. After sensitization with Chicken R.B.C for both infected a

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Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
Evaluation of cellular immune response in Golden Hamsters experimentally infected with Leishmania donovani comparing with cellular immune response against chicken Red Blood Cells.
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The Evaluation of the immune response in Golden Hamsters experimentally infected with Leishmania donovani was determined in this study, particularly, the cellular immune response. Follow up has maintained to determine the Delayed Type of Hypersensitivity using skin test both in infected and control lab animals. Chicken red blood cells were used as a parameter to evaluate the immune system; they are dull and have the ability of immunization. Two concentrations of chicken R.B.C were examined to determine which gives the higher titration in Hamsters and those were 1.5 X 109 cell/ml and 3 X 109 cell/ml , the second concentration gave the maximum titration where then used in this work. After sensitization with Chicken R.B.C for both in

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
E4An Ultrastructural Study by Transmission Electron Microscope of Exocrine Pancreatic Cells in Diabetic Rats Treated with Herbal Combination
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     The current study was designed to investigate the alterations in the ultrastructure of orgenelles and cellular activity of exocrine pancreatic acini of experimentally induced-diabetic rats and to assess the usefulness of herbal combination supplementation in improving the ultrastructure and cellular activity of exocrine pancreas. The number of albino male rats used were 24 which divided into equally 4 groups; group I: control group, group II: alloxan-induced diabetes mellitus (single intraperitoneal dose of alloxan 120 mg/kg for 3 days), group III: herbal combination treatment composed from the extracts of fenugreek seeds (Trigonella foenum-graecum), black cumin (Nigella sativa) seeds, rhizomes

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Publication Date
Fri Jul 01 2016
Journal Name
Infection And Immunity
The Periodontal Pathogen Porphyromonas gingivalis Preferentially Interacts with Oral Epithelial Cells in S Phase of the Cell Cycle
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ABSTRACT<p> <named-content content-type="genus-species">Porphyromonas gingivalis</named-content> , a key periodontal pathogen, is capable of invading a variety of cells, including oral keratinocytes, by exploiting host cell receptors, including alpha-5 beta-1 (α5β1) integrin. Previous studies have shown that <named-content content-type="genus-species">P. gingivalis</named-content> accelerates the cell cycle and prevents apoptosis of host cells, but it is not known whether the cell cycle phases influence bacterium-cell interactions. The cell cycle distribution of oral keratinocytes was characterized by flow cytometry and BrdU (5-bro</p> ... Show More
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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
The relation between some of phenotype characteristics of corn and infection by corn stem borer Sesamia cretica.
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This study was conducted to know the effect of some phenotype characteristics of corn plant on infection by (CSB), using 13 genotypes of corn plant, planting during autumn season 1997 and 1998. The result revealed that the mean of plant height (with male flowering) was (183-219) cm, the mean of leaf No./ plant in all genotypes was (16-18) leaf but the leaf area of plant was (4350-6249) cm2, there were significant differences of phenotype characteristics between genotypes ,the percentage of infection by (CSB) was (5.9-35.9),% the result showed that the phenotype characteristics had non effect on the infection percentage by (CSB) and the correlation coefficient was not significant.

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Publication Date
Tue Jul 01 2014
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
VARIATIONS OF WOOD ELEMENTS IN MAIN STEM OF ALBIZIA LEBBECK (L.) BENTH. GROWING IN BAGHDAD CITY, IRAQ
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    As Albizia lebbeck is one of the important species in Iraq and the region, its wood has subjected to investigation through the assessment of differences in its element dimensions and specific gravity under Baghdad conditions. Variations of fiber length, fiber width, cell wall thickness, vessel diameter, and density of wood were examined along the stem and horizontally.  Results showed that fiber lengths were within the normal range, but their widths were narrower than common range of hardwoods. There were little increase in fiber length, width, wall thickness as the height position increased. Vessel diameter has been affected contrarily. No significant effects of  height on specific gravity could be

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Publication Date
Sun Mar 01 2020
Journal Name
Al-mustansiriyah Journal Of Science
Evaluation the activity of Petroselinum crispum aqueous extract as promoter rooting for stem cuttings of some plants
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This study was conducted in the botanical garden, Department of biology, College of Science/ Mustansiriyah University in from (15 February to 15 March, 2019) under the natural environmental conditions in the greenhouse in order to evaluate the effectiveness of parsley aqueous extract as a promoter for rooting. The study included the use of aqueous extract of a plant Parsley (Petroselinum crispum) extract was used in concentrations (1.25, 2.5 g / l), compare with IBA in concentration (100 mg / L) with dipping time 24 hour for all treatments. The cutting stems were included Rosmarinus officinalis, Nerium oleander, Olea europaea, Plumeria alba, Hibiscus rosa, Pelargonium graveolens, and Myrtus communis. The following measurements were

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Publication Date
Fri May 01 2015
Journal Name
Journal Of Engineering
Brackish Water Desalination Coupled With Wastewater Treatment and Electricity Generation
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A new bio-electrochemical system was proposed for simultaneous removal of organic matters and salinity from actual domestic wastewater and synthetically prepared saline water, respectively. The performance of a three-chambered microbial osmotic fuel cell (MOFC) provided with forward osmosis (FO) membrane and cation exchange membrane (CEM) was evaluated with respect to the chemical oxygen demand (COD) removal from wastewater, electricity generation, and desalination of saline water. The MOFC wasinoculated with activated sludge and fueled with actual domestic wastewater. Results revealed that maximum removal efficiency of COD from wastewater, TDS removal efficiency from saline water, power density, and current density were

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Comparing Weibull Stress – Strength Reliability Bayesian Estimators for Singly Type II Censored Data under Different loss Functions
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     The stress(Y) – strength(X) model reliability Bayesian estimation which defines life of a component with strength X and stress Y (the component fails if and only if at any time the applied stress is greater than its strength) has been studied, then the reliability; R=P(Y<X), can be considered as a measure of the component performance. In this paper, a Bayesian analysis has been considered for R when the two variables X and Y are independent Weibull random variables with common parameter α in order to study the effect of each of the two different scale parameters β and λ; respectively, using three different [weighted, quadratic and entropy] loss functions under two different prior functions [Gamma and extension of Jeffery

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Publication Date
Mon Mar 02 2026
Journal Name
International Journal Of Inventions In Engineering &amp; Science Technology
A Review: Campus Violence Detection Using Deep Learning Models
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This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark

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