The aim of this study is to determine serum IL-33 levels and atherogenic index of plasma (AIP) .Forty patients with moderate activity of rheumatoid arthritis (RA) and forty healthy individuals as control group were enrolled in this study, age (25-45) years. Disease activity was assessed in patients by erythrocyte sedimentation rate (ESR),C-reactive protein (CRP) and rheumatoid factor(RF) .Also lipid profile(cholesterol TC, triglyceride TG, low density lipoprotein LDL-C, very low density lipoprotein VLDL and high density lipoprotein HDL-C), AIP, and IL-33 were determined in all subjects. The results revealed a significant increase in ESR,CRP and RF , TG, VLDL,AIP and IL-33,while is a significant decrease in HDL concentration in patients group compared to control group was found. No significant increase in TC and LDL-C levels were noticed between patients and control groups. Positive correlation was found between CRP and IL-33 in patients group. The conclusion could be drawn from this study that the patients presented with cardiovascular disease as concomitant of RA, which predicted by elevated of AIP value that can be calculated easily.IL-33 used as a novel parameter for assessing disease activity in patients with RA more than CRP dose alone.
The 2011 Iraqi Measles Control Campaign had as its aim to improve immunization coverage among young adults' 17-24years and, in the longer term, prevention of measles epidemics. The aim of the study is estimation measles vaccination and revaccination efficacy by evaluate the seroprevalence of antibody and response to reimmunization in young adults. A previously vaccinated 189 young adult medical students were tested for measles specific IgG &IgM pre and post catch-up revaccination by using commercially available ELISA. To assess the seroprevalence of antibody response pre measles reimmunization in previously vaccinated young adults; 45 were found to be seronegative. To differentiate between primary and secondary vaccine failure, anti- mea
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Twitter is becoming an increasingly popular platform used by financial analysts to monitor and forecast financial markets. In this paper we investigate the impact of the sentiments expressed in Twitter on the subsequent market movement, specifically the bitcoin exchange rate. This study is divided into two phases, the first phase is sentiment analysis, and the second phase is correlation and regression. We analyzed tweets associated with the Bitcoin in order to determine if the user’s sentiment contained within those tweets reflects the exchange rate of the currency. The sentiment of users over a 2-month period is classified as having a positive or negative sentiment of the digital currency using the proposed CNN-LSTM
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The research aims at Identifying family dialogue of kindergarten’s parents. 2) Exploring the fears that kindergarteners suffer from. 3) Identifying family dialogue of kindergarteners’ parents and the fears of their children. To achieve the aim of the research, the researcher designed two scales: one for the family dialogue of kindergarteners’ parents, and the other for the fears of the kindergarten’s child. To identify the relationship between these two elements, the scale subjected to the consultation of a group of specialized expertise in educational and psychological sciences to certify the propriety of the items. The reliability of the scale of the family dialogue recorded (0.85). As for the scale of children’
... Show MoreTraditionally, path selection within routing is formulated as a shortest path optimization problem. The objective function for optimization could be any one variety of parameters such as number of hops, delay, cost...etc. The problem of least cost delay constraint routing is studied in this paper since delay constraint is very common requirement of many multimedia applications and cost minimization captures the need to
distribute the network. So an iterative algorithm is proposed in this paper to solve this problem. It is appeared from the results of applying this algorithm that it gave the optimal path (optimal solution) from among multiple feasible paths (feasible solutions).
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Abstract
The research aims to study the problem of high production costs and low quality and the use of total quality management tools to detect problems of the high cost of failure and low quality products, diagnosis, and developing appropriate solutions.
To achieve the goal, we studied the overall quality tools and its relationship with the costs and the possibility of improving quality through the use of these tools.
Was limited to these tools and study the relation to the reduction of costs and improving quality have been studied serially by the possibility of the reduction.
To achieve the goal, the study of the concept of total quality management
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Traditional accounting takes only one dimension (economic) in calculating the value added of the company, and all other aspects (including environmental and social) are neglected, and despite the emergence of Sustainability Accounting and the interest of companies in preparing sustainability reports, these reports are suffering from many problems, including multiple metrics used in measuring companies (cash, quantity and lavish). In addition, these reports may reach dozens of pages in some companies and this causes the problem (information overload) which affects the qualitative properties of accounting information such as appropriate and relative, which requires the need to find a tool that can measure the Sustainability Unit of
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This study examined the correlation between binder-level fatigue properties and mixture-level cracking resistance in asphalt binders modified with five Nanomaterials (NMs): Nano-Silica (NS), Nano-Alumina (NA), and Nano-Titanium dioxide (NT) at 2%, 4%, and 6% as well as Nano-Zinc oxide (NZ) and Carbon Nanotubes (CNTs) at 1%, 2%, and 3%. Modified binders were subjected to Rolling Thin-Film Oven Test (RTFOT) and Pressure Aging Vessel (PAV) aging and tested at 25 °C using the Linear Amplitude Sweep (LAS) test to determine fatigue life (Nf) and the fatigue parameter G*.sin δ. The corresponding asphalt mixtures were evaluated using the IDEAL-CT test. The results indicated strong correlations between binder and mixture performance for
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Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin
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Human beings are starting to benefit from the technology revolution that witness in our time. Where most researchers are trying to apply modern sciences in different areas of life to catch up on the benefits of these technologies. The field of artificial intelligence is one of the sciences that simulate the human mind, and its applications have invaded human life. The sports field is one of the areas that artificial intelligence has been introduced. In this paper, artificial intelligence technology Fast-DTW (Fast-Dynamic Time Warping) algorithm was used to assess the skill performance of some karate skills. The results were shown that the percentage of improvement in the skill performance of Mai Geri is 100%.
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