Revolutionizing Systematic Reviews and Meta-analyses: The Role of Artificial Intelligence in Evidence Synthesis
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Actinomycetes are free, spore-forming, high (G+C) ratio (>55%) saprophytic microorganisms that are widely distributed in most soils, colonize plants, and are prevalent in water. This is frequently accompanied by the production of filament airborne mycelium. Actinomycetes are well-known microcolonies for creating antibiotics and other critical bioactive components that are beneficial to humans. Approximately 70% to 80% of commercially available medications and antiviral active compounds have been synthesized so far. Secondary metabolites produced by microbes have the potential to be used in a variety of sectors, including antimicrobial agents, enzyme technology, pigment manufacture, antitumor agents against cancer cells, and toxin pr
... Show Moreتسعى المحاسبة الى مسايرة القفزات الهائلة والمتسارعة في تطور العلوم الصرفة والتطبيقية والتقدم التكنولوجي، والتي ادت على ظهور مفاهيم جديدة الغت مسلمات وبديهيات كانت سائدة لمدة طويلة، فعلى سبيل المثال: كان مخزون المواد الاولية والبضاعة التامة في المؤسسات الصناعية او التجارية يشكل العمود الفقري لها بتكاليفه ومشاكله، حتى اذا ما جاء نظام (JIT) الغى بتطبيقاته هذه المفاهيم واعتمد م
... Show MoreBackground: The styloid process is a cylindrical bone (protrusion). It situated above the common carotid artery between the external and internal branches immediately proximal to the internal jugular vein and facial nerves. The styloid process varies in length also it may be absent as well as elongated. Classically, an elongated styloid process and calcified of stylohyoid ligament causes Eagle’s syndrome. The aim of this study was to examine the styloid process using 3 dimensional multi-detector computed tomography (3D-MDCT) to detect the presence of Eagle’s syndrome that causes severe headache and migraine. Materials and methods: One hundred patients with severe headache and migraine were exposed to 3D- multi-detector CT with special
... Show MoreThis study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur
... Show MoreNovel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
This study measures the indicators of social and environmental performance of the contents of the administration's prepared reports on its social and environmental performance by comparing the actual performance with the indicators set within the standards of the Global Reports Initiative (GRI), In preparing this research, the researchers relied on studying the criteria of the Global Reporting Initiative, which aims to achieve a high level of performance disclosure under sustainability, In light of contemporary global trends towards achieving sustainable development and its disclosure and the orientations of economic institutions and units in different countries towards emphasizing the extent of commitment during practicing its a
... Show MoreAbstract:
The aim of the present research is to evaluate the child’s nutritional
method (2-5 years old) which is based on his resistance of the food highly rich
with nutritional elements and his acceptance of the food of a low nutritional
value in addition to his having forbidden food with other mates and making
use of all mates when having food, in establishing the sound social values and
affection since child hood. The required statistical equation have been used
by the researcher namely (Z test).
The sample of the present study consists of (26) children who were selected
intentionally and randomly from the kindergartens of Al-Bayaa region and the
college of Education for women. The questionnaires were d
The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the