This study aims to examine the main features of the new trends in agenda studies using the secondary analytic approach in analyzing the newest studies in agenda-setting issues from 2007 till 2017, in addition to the quantitative approach.
The researcher has analyzed 110 studies -75 foreign and 35 Arabic - to determine, describe and evaluate the key research trends which came in Arabic and foreign agenda-setting studies. The results confirmed that studies of the agenda theory are increasing steadily worldwide with diversity in the theoretical trends and used research tools. In addition, primary studies focus on content analysis and the survey approach (method). Also, most Arabic agenda-setting studies used the traditional methods and known research tools such as content analysis and survey, contrary to the foreign studies conducted in the same field where they were characterized by the different research teams specializing in many scientific branches. The study recommends more cooperation among Arab researchers and the re-survey of the research map in fields of agenda studies. It also recommends giving more attention to comparative studies, revising the used methods and tools and focusing more on interdisciplinary studies through different timespans (periods).
This research studies the development and synthesis of blended nanocomposites filled with Titanium dioxide (TiO2). Blended nanocomposites based on unsaturated polyester resin (UPR) and epoxy resins were synthesized by reactive blending. The optimum quantity from nano partical of titanium dioxide was selected and different weight proportions 1%, 3%, 5%, and 7% ratios of new epoxy are blended with UPR resin. The dielectric breakdown strength and thermal conductivity properties of the blended nanocomposites were compared with those of the basis material (UPR and 3% TiO2).The results show good compatibility epoxy resins with the UPR resin on blending, dielectric breakdown strength values are higher while thermal conductivity values of
... Show MoreFour new copolymers were synthesized from reaction of bis acid monomer 3-((4-carboxyphenyl) diazenyl)-5-chloro-2-hydroxybenzoic acid with five diacidhydrazide in presence of poly phosphoric acid. The resulted monomers and copolymers have been characterized by FT-IR, 1H-NMR, 13C-NMR spectroscopy as well as EIMs technique. The number averages of molecular weights of the copolymers are between 4822 and 9144, and their polydispersity indexes are between 1.02 and 2.15. All the copolymers show good thermal stability with the temperatures higher than 305.86 C when losing 10% weight under nitrogen. The cyclic voltammetry (CV) measurement and the electrochemical band gaps (Eg) of these copolymers are found below 2.00 ev.
Abstract: Chalcones were used to synthesis series of 2-pyrazoline derivatives and evaluated their antimicrobial and anti-inflammatory activities (E)-1,3-diphenylprop-2-en-1-one (1-5) were synthesized by Claisen-Schmidt Condensation method through the reaction of acetophenone with five various para substituted benzaldehyde in presence of KOH, the reaction monitoring by TLC and the result intermediates were checked by melting point and FT-IR Various 2-Pyrazoline derivatives were prepared by one pot reaction that involved the refluxing of (E)-1,3-diphenylprop-2-en-1-one (1–5) and Hydrazine monohydrate in the presence of glacial acetic acid for 24 hours at a temperature of (45–50) °C fo
... Show MoreIn this study, synthesis of polymer Nanocomposites through the blending of prepared polymers with polyvinyl alcohol (a synthetic polymer) or chitosan (a natural polymer) then mixed with nano oxide silica by many steps. The new compound [I] was obtained via reaction of 3,3’-dimethoxybiphenyl-4,4’-diamine as starting material with malic anhydride in DMF then treatment with ammonium persulfate (NH4 )2 S2 O8 (as the initiator) in order to produce polymer [II]. Also, we prepared new polymers [III-V] by using the same starting material (3,3’-dimethoxybiphenyl-4,4’-diamine) with glutaric acid or adipic acid or isophthalic acid in DMF and pyridine. In this study, new polymer blending [VI-IX] and [X-XIII] were synthesized from a prepared pol
... Show MoreThe meteorite with a single total mass of 630 gm as a visible meteorite has fallen on 22 March 2021, at 10:00 a.m. in Al-Sherqat subdistrict within Salah Al-Din, northern Iraq; and therefore, was named Al-Sherqat meteorite by the authors. It is characterized by a uniform structure of coherent and medium degree of malleability. It is of a well-crystalline structure and not homogeneous in composition. The Al-Sherqat meteorite is composed of metallic phases of 7.6 gm/cm3 density exhibiting an oriented intergrowth of kamacite (α-FeNi) with taenite showing a Widmanstätten pattern on an etched polished section with the finest octahedrite kamacite bandwidth of less than 0.2 mm. It is composed of Fe (86.9 wt%), Ni (9.63 wt%), P (1.31 wt%)
... Show MoreSmall ring heterocycles containing nitrogen and sulfur have been under investigation for a long time because of their important medicinal properties. Among the wide range of heterocycles explored to develop pharmaceutically important molecules, thiadiazoles had played an important role in medicinal chemistry. A survey of literature had shown that compounds having thiadiazole nucleus possess a broad range of biological activities such as anti-inflammatory (1), antibacterial (2), and antifungal activities (3). Thiazine-4-one and their derivatives are import classes of compounds in organic and medicinal chemistry. The thiazine-4-one ring system is a core structure in various synthetic pharmaceutical agents, displaying a broad spectrum of biolo
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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