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The Influence of Helicobacter Pylori Infection on Cardiovascular Risk Factors in Patients with Gastritis
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Helicobacter pylori (HP) is the etiopathogenic agent of gastric and duodenal disorders ranging from gastritis to malignancy. It is also associated with many extraintestinal diseases, including cardiovascular disease and its associated risk factors. To evaluate the link between HP infection and some cardiovascular risk factors by studying the effects of HP infection on body mass index, blood pressure, and serum lipid profile among patients having gastritis with and without HP infection. A crosssectional study included 1214 patients who had gastritis diagnosed by gastroscopy examination. Those patients were in the age range of 30-65 years and they were divided according to their gender into 725 females and 489 males depending on the 13C urea breath test, they were divided into HP positive ( +) groups (550 female & 300 male ) and HP negative (-) group (175 female & 189 male). The blood pressure and body mass index (BMI) were measured for each patient and following at least 10-h fasting, a lipid profile test was performed. Our study exhibited a significant difference (p > 0.05) in Body Mass Index (BMI) between HP (+) and HP (–) participants. HP (+) participants were obese (34.29 Kg/m2) while HP (-) participants were leanِ. The mean systolic & diastolic blood pressures were non- significantly higher in HP (+) group than those in HP (-) group. The TC, TG, and LDL parameters scored the highest mean value in HP (+) group (212.47±18.35, 117.17±37.14, and 79.30±15.42) respectively. In contrast, HDL scored the lowest mean value in HP (-) group (40.59±2.38). HP infection significantly alters lipid profile test and may be one of the risk factors for obesity, dyslipidemia and hypertension.

Publication Date
Sun Jan 01 2017
Journal Name
Aip Conference Proceedings
Macro controlling of copper oxide deposition processes and spray mode by using home-made fully computerized spray pyrolysis system
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Synthesis, Characterization and Textural Analysis of Functionalized Mesoporous Silica Using Sodium Silicate as Precursor and Silicone Surfactant as Template
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Three mesoporous silica with different functional group were prepared by one-step synthesis based on the simultaneous hydrolysis and condensation of sodium silicate with organo - silane in the presence of template surfactant polydimethylsiloxane - polyethyleneoxide (PDMS - PEO). The prepared materials were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), atomic force microscopy (AFM) and nitrogen adsorption/desorption experiments. The results indicate that the preparation of methyl and phenyl functionalized silica were successful and the mass of methyl and phenyl groups bonded to the silica structure are 15, 38 mmol per gram silica. The average diameter of the silica particles are 103.51,

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Publication Date
Thu Jul 15 2021
Journal Name
University Of Samarra
Preparation, Diagnosis and Biological ‎Efficacy of new Ligands Derived from ‎Succinyl Chloride and Their Metal ‎Complexes and non metallic
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The purpose of my thesis is to synthesis two new bidentate ligands ‎which were used to prepare series of metal complexes by reacting the ‎ligands with (M+2 = Mn, Co, Ni, Cu, Cd and Hg) ‎ ‎ Succinyl chloride was used as starting material to synthesis two ‎bidentate ligands (L1) and (L2) by reaction it with 4-chloroaniline ‎‎(L1) and ‎ ‎ (4-aminoacetophenone) (L2) in dichloromethane as a solvent, that ‎are:‎ ‎(L1) = N1,N4-bis (4-chloro phenyl ) succinamide ‎(L2) =N1,N4-bis(4-acetylphenyl)succinamide ‎ The new ligands were characterize by using spectroscopic study ‎‎(Fourier-transform infrared spectroscopy (FT-IR), electronic spectra ( ‎UV-Vis) ,nuclear magnetic resonance(1H,13C-NMR), Mass spectra ‎

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Thu Feb 06 2020
Journal Name
Scientific Reports
Waste foundry sand/MgFe-layered double hydroxides composite material for efficient removal of Congo red dye from aqueous solution
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Abstract<p>We aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure</p> ... Show More
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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Public Health Research &amp; Development
Effect of <i>Olea europea</i> L Extraction and TiO<sub>2</sub> Nanoparticles against <i>Pseudomonas aeruginosa</i>
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Publication Date
Fri Oct 01 2010
Journal Name
Iraqi Journal Of Physics
Investigation of Beta and Gamma Rays Total Interaction Cross Section and Effective Atomic Number for CR-39Nuclear Track Detector
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CR-39 is a solid state nuclear track detector (SSNTD) that has been used in many research areas. In spite of the assumption that the CR-39 detectors are insensitive to beta and gamma rays, irradiation with these rays can have significant effects on the detector properties. In this study, beta and gamma rays mass attenuation coefficients μ/ρ (cm2 g-1) for the CR-39 detector have been measured using NaI(Tl) scintillation spectrometer along with a standard geometrical arrangement in the energy region of (0.546-2.274) MeV beta rays and standard gamma sources having energy 0.356, 0.5697, 0.6617 and 1.063 MeV. The total atomic cross-section (σtot), total electronic cross-section (σT E) and the effective atomic number (Zeff) of gamma rays a

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Publication Date
Mon Jan 01 2018
Journal Name
2018 Detroit, Michigan July 29 - August 1, 2018
Design and validation of an electronic data logging systems (CAN Bus) for monitoring machinery performance and management- Planting application
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Publication Date
Wed Nov 23 2022
Journal Name
Dental Hypotheses
Remineralization of Dentine Caries Using Moringa Oleifera Based Nano-Silver Fluoride: A Single-Blinded, Randomized, Active-Controlled Clinical Trial
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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Extraction and estimation of curcumin compounds from turmeric (Curcuma longa) rhizomes by using different variables (solvent, time and temperature).
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The study aimed to investigate the effect of different times as follows 0.5, 1.00, 2.00 and 3.00 hrs, type of solvent (acetone, methanol and ethanol) and temperature (~ 25 and 50)ºc on curcumin percentage yield from turmeric rhizomes. The results showed significant differences (p? 0.05) in all variables. The curcumin content which were determined spectrophotometrically ranged between (0.55-2.90) %. The maximum yield was obtained when temperature, time and solvent were 50ºC, 3 hrs and acetone, respectively.

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