A new hetrocyclic liquid crystal compounds containing 1,3,4-oxadiazole with different substituted in para position (Bromo, Chloro, Nitro and Methyl) were synthesized and characterized by melting points, FTIR Spectroscopy and 1HNMR spectroscopy for [Cl-SR6] and [NO2-SR6] compounds. The liquid crystalline properties of the synthesized compounds were studied by using hot-stage polarizing optical microscopy (POM), so they determined the transition enthalpies and entropies by using differential scanning calorimetery (DSC). All of the compounds show mesomorphic properties. The compounds [Br-SR6], [Cl-SR6] and [NO2SR6] exhibit an enantiotropic dimorphism smectic (Sm) phase, while the compounds [MeSR6] showed nematic (N) phase throw cooling only. Continuously, permittivity dielectric properties, electrical conductivity, relaxation times and activation energies have been studied in the range of temperatures (70-150)°C at two frequencies (500) Hz and (1000) Hz. Generally, the results show the dielectric permittivity and relaxation time values increasing when raising temperature, while electrical conductivity values decrease with increasing temperature. The activation energy values were determined in terms of the Arrhenius plot.
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Purpose: To validate a UV-visible spectrophotometric technique for evaluating niclosamide (NIC) concentration in different media across various values of pH. Methods: NIC was investigated using a UV-visible spectrophotometer in acidic buffer solution (ABS) of pH 1.2, deionized water (DW), and phosphate buffer solution (PBS), pH 7.4. The characterization of NIC was done with differential scanning calorimeter (DSC), powder X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The UV analysis was validated for accuracy, precision, linearity, and robustness. Results: The DSC spectra showed a single endothermic peak at 228.43 °C (corresponding to the melting point of NIC), while XRD and FTIR analysis confirmed the identit
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An investigation was conducted effect of addition co- solvent on solvent extraction process for two types of a lubricating oil fraction (spindle) and (SAE-30) obtained from vacuum distillation unit of lube oil plant of Daura Refinery. In this study two types of co-solvents ( formamide and N-methyl, 2, pyrrolidone) were blended with furfural to extract aromatic hydrocarbons which are the undesirable materials in raw lubricating oil, in order to improve the viscosity index, viscosity and yield of produced lubricating oil. The studied operating condition are extraction temperature range from 70 to 110 °C for formamide and 80 to 120 °C for N-methyl, 2, pyrrolidone, solvent to oil ratio range from 1:1 to 2:1 (wt./wt.) for furfural with form
... Show MoreA total of 41 patients with gastro duodenal symptoms (show signs of inflammation with or without duodenal ulcer) . 21 males (51.2%) and 20 female (48.8%) with an average age 0f (20 – 80) years old under going gastrointestinal endoscopy at Baghdad teaching hospital in internal disease clinical laboratory , between (February – June) 2009 . Biopsies specimen of antrum , gastric fundus ,& duodenal bulb were examined by the following methods (rapid urease test , Giemsa stain section to detect bacteria , & Haematoxilin and Eosin stained section for pathological study which are considered the gold standard methods , sera or plasma from these patients were tested by immunochromotography (ICM),serological m
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In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve
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Five rice (Oryza sativa L.) cultivars (N22, Amber, Moroberekan, Kinandang Patong, and Azucena) underwent path coefficient analysis across three plant spacings (15 cm × 15 cm, 20 cm × 20 cm, and 25 cm× 25 cm) in the summer of 2017 at the College of Agricultural Engineering Sciences, University of Baghdad, Al-Jadriya, Iraq. The experiment proceeded in a randomized complete block design (RCBD) with a split-plot arrangement and three replications. The main plots included three planting distances, and the subplot comprised five varieties. The traits studied were plant height, flag leaf area, number of tillers, panicle number, length and branches, grains per panicle, 1000-grain weight, and the percentage of unfilled grains. The results
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Background: Pumpkin seeds are a valuable source of high-quality protein and can be utilized as functional food ingredients due to their properties, such as solubility, foam formation, and stability. This study aims to produce protein isolate and its enzymatic hydrolysates from local pumpkin seeds to study their properties. Methodology: Preparing defatted pumpkin seeds for protein extraction, followed by the enzymes’ hydrolysis using Trypsin and Pepsin enzymes separately and together in two methods. The determination of amino acids and the degree of hydrolysis was conducted; moreover, protein properties were studied, including solubility, emulsifying activity, stability index, foaming capacity, and stability. Results: A protein sample was
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