Chitinase-3-like 1 protein (YKL-40) is a glycoprotein primarily produced in the arthritic joint and plays a crucial role in inflammatory processes. The aim of the study is to establish the role of YKL-40 as a biomarker for rheumatoid arthritis (RA) compared to proinflammatory biomarkers and disease activity. The study included 58 patients and 18 control. Diseases activity score (DAS-28) and clinical disease activity index (CDAI) were measured. Serum level of YKL-40, tumor necrosis factor-α (TNF-α), interleukin-1B (IL-1β), erythrocyte sedimentation (ESR), rheumatoid factor (RF), C-reactive protein (CRP), and anti-citrullinated protein antibody (ACPA) were assessed. The results showed that the median serum YKL-40 level which was 5.42 

بناء على ما تقدم يتضح ان القطاع العام والقطاع الخاص ليسا موقفا ايدولوجيا انتقائيا، وانما هو انبثاق من العمود الفقري للصيرورة الرأسمالية القائمة على تقديس الملكية الخاصة، وان الادوار التي يمكن ان يلعباها ليسا منعزلين عن الحركة العامة للاقتصاد في كليته، وليس هما ابنا السياسات الاقتصادية، والبناء الفوقي بقدر ماهما نتاج الحركة الموضوعية وصيرورة التطور الاجتماعي معبرا عنها في تطور علاقات الانتاج وقوى الانتا

This paper discuses the mindset contribution of the organization Science in organizational effectiveness (OE), and the most valuable thoughts they introduced in this subject, starting from the pre- classical era, through classical era to present time. This paper has identified the main contribution in OE. The concept of OE didn’t arise until what had been introduced by Chester Barnard, although Max Weber mentioned this concept in his bureaucratic theory, but he didn’t explain it as Barnard does. After that no clear focus was pointed to this subject until Peter Drucker did so, which considered as the main participant in OE after Barnard. After that many researchers be interested in OE and they start studying this subject like

In order to a chive the aim of the research the researcher chose the (Nebras kindergarten) to be the search sample .the member of the sampleFrom(males and fameless)and the researcher chose the class of(butterfly) as experimental group to do the pantomime consist of(15)males and fameless, and put(singles, senses ,double senses and communal senses)in the binging of the experiment the researcher applied the measurement of(AL Kaswany and other)as(pre_ test)which prepare to measure, the movement skills for kindergarten, the measurement have the validity and reliability to knowledge the difference between the two experiment. The experiment continue from(20/1/201to 20/2/2014)in the end of experiment the researcher applied the measurement of(AL

Osteoporosis (OP)is one of the most important metabolic disorder also affected by interaction of genetic and environmental factors by almost 70% and 30% respectively. Genetic components are identified to strongly effect bone mineral density, bone building and turnover, so they play an important role in determining risk of OP and fragility fractures. This study consists of patient and control group; Group A: (70) postmenopausal women with OP and osteopenia, Group B: (20) control group.  five milliliters of blood sample were divided into three tubes; one tube (1ml) contain gel for obtain serum to measure glucose level, the others tubes containing ethylene-diamine-tetra-acetic acid (EDTA), in 2 tube 2ml stored in deep freeze at (–40

A superb demonstration of one of the wonders of technology providing the people with great aid is the employment of Artificial Intelligence in the medical field, and mainly the introduction of Clinical Decision Support Systems (CDSS). Nevertheless, non-’black-box’ AI systems have a significant problem, that is, although they are visible and understandable, there is still a considerable issue of trust by healthcare professionals. Explainable AI (XAI) technology is a means to overcome all the obstacles by unveiling more and offering the explanations of the procedures that AI performs in decision making. This study was conducted by examining various widely used approaches to XAI, which illustrate how XAI verifies the trustworthiness of CDS

Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi