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The Prevalence of Aerobic Bacteria Isolated from Horses Fecal Samples
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Dietary components and changes cause shifts in the gastrointestinal microbial ecology that can play a role in animal health and a wide range of diseases. However, most information about the microbial populations in the gut of horses has not been quantitative. The objective of this study was to characterize the fecal bacterial and its prevalence in healthy horses and diarrheal one in a period from September 2010 to July 2013. Out of 100 Fecal samples of horses (from farms in Al-furusyia club) in Baghdad were examined for microbial differentiation founded eighty percent of the fecal samples isolated from healthy horses. The most common pathogen found were Streptococcus spp. (33.7%), Escherichia coli (20.9%), , and Staphylococcus aureus (9.2%). Relatively low frequency of detection was found for serratia marcescens spp. (0.6%), Acintobacter spp.(1.2%), (1.8%) for Enterococcus sp., Micrococcus sp., Proteus vulgaris, Klebsiella pneumoniae and Citrobacter diversus ,Pseudomonas spp (2.5%), Salmonella spp. (3.1%), and Listeria monocytogenes (0.0%)

Publication Date
Thu Feb 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Formulation Variables Effect on Gelation Temperature of Nefopam Hydrochloride intranasal in Situ Gel (Conference Paper) #
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Nefopam (N.F.) HCl is a non-narcotic centrally-acting, non-opioid benzoxazocine analgesic to relieve acute and chronic pain. It exhibits low bioavailability (about 36%) due to its first-pass degradation in the liver.

Intranasal administration has been used as a new route for targeting active brain sites and enhancing the bioavailability of N.F. HCl bypassing hepatic metabolism.

In situ gel of N.F. HCl was prepared by the cold method using different concentrations of Poloxamer 407, Poloxamer 188, HPMC K4M, Carbapol 934, and Hyaluronic acid polymers.

The results show that identification tests are superimposed with references, solubility study shows that N.F. HCl is suitable to be administered intranasally; Compatibi

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Publication Date
Tue Jan 19 2021
Journal Name
Archives Of Civil And Mechanical Engineering
Push-out test of steel–concrete–steel composite sections with various core materials: behavioural study
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Steel–concrete–steel (SCS) structural systems have economic and structural advantages over traditional reinforced concrete; thus, they have been widely used. The performance of concrete made from recycled rubber aggregate from scrap tires has been evaluated since the early 1990s. The use of rubberized concrete in structural construction remains necessary because of its high impact resistance, increases ductility, and produces a lightweight concrete; therefore, it adds such important properties to SCS members. In this research, the use of different concrete core materials in SCS was examined. Twelve SCS specimens were subjected to push-out monotonic loading for inspecting their mechanical performance. One specimen was constructed from co

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Synthesis and Characterization of Magnetic Iron Oxide Nanoparticles by Co-Precipitation Method at Different Conditions
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Magnetic nanoparticles (MNPs) of iron oxide (Fe3O4) represent the most promising materials in many applications. MNPs have been synthesized by co-precipitation of ferric and ferrous ions in alkaline solution. Two methods of synthesis were conducted with different parameters, such as temperature (25 and 80 ̊C), adding a base to the reactants and the opposite process, and using nitrogen as an inert gas. The product of the first method (MNPs-1) and the second method (MNPs-2) were characterized by x-ray diffractometer (XRD), Zeta Potential, atomic force microscope (AFM) and scanning electron microscope (SEM). AFM results showed convergent particle size of (MNPs-1) and (MNPs-2) with (86.01) and (74.14)

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Fri May 05 2023
Journal Name
Environmental Science And Pollution Research
Photocatalytic degradation of ciprofloxacin by MMT/CuFe2O4 nanocomposite: characteristics, response surface methodology, and toxicity analyses
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Publication Date
Tue Mar 21 2023
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Impact of Deep Learning Strategy in Mathematics Achievement and Practical Intelligence among High School Students
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— To identify the effect of deep learning strategy on mathematics achievement and practical intelligence among secondary school students during the 2022/2023 academic year. In the research, the experimental research method with two groups (experimental and control) with a post-test were adopted. The research community is represented by the female students of the fifth scientific grade from the first Karkh Education Directorate. (61) female students were intentionally chosen, and they were divided into two groups: an experimental group (30) students who were taught according to the proposed strategy, and a control group (31) students who were taught according to the usual method. For the purpose of collecting data for the experimen

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Publication Date
Wed Jan 01 2020
Journal Name
Energy Conversion And Management
Improved PCM melting in a thermal energy storage system of double-pipe helical-coil tube
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Publication Date
Tue Mar 12 2019
Journal Name
Lubricants
Absorption Wavebands for Discriminating Oxidation Time of Engine Oil as Detected by FT-IR Spectroscopy
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Fourier Transform-Infrared (FT-IR) spectroscopy was used to analyze gasoline engine oil (SAE 5W20) samples that were exposed to seven different oxidation times (0 h, 24 h, 48 h, 72 h, 96 h, 120 h, and 144 h) to determine the best wavenumbers and wavenumber ranges for the discrimination of the oxidation times. The thermal oxidation process generated oil samples with varying total base number (TBN) levels. Each wavenumber (400–3900 cm−1) and wavenumber ranges identified from the literature and this study were statistically analyzed to determine which wavenumbers and wavenumber ranges could discriminate among all oxidation times. Linear regression was used with the best wavenumbers and wavenumber ranges to predict oxidation time.

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Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Photoinduced interfacial charge transfer processes in solar photocatalysis degradation of methylene blue using nanostructured ZnO
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In this research, design of advanced material for sunlight conversion requires focused research to obtain efficient photocatalytic system. Nanostructured ZnO was synthesized using spin coating technique. The structural, morphological and optical properties of annealed nanostructured ZnO thin film at 390 Co for 3 hours were characterized by x-ray diffraction, atomic force microscope AFM and UV-VIS spectrophotometer. Nanostructured ZnO was applied for removal Methylene Blue (MB) dye from water using sunlight induced photocatalytic process. Overall degradation of MB/ZnO was achieved after 120 minutes of sunlight irradiation while it needs more time for MB alone. The reaction rate constant fit pseudo first order for MB/ZnO degradation was 0.

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Publication Date
Mon May 01 2023
Journal Name
Ain Shams Engineering Journal
Neural network modeling of rutting performance for sustainable asphalt mixtures modified by industrial waste alumina
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