Rheumatoid arthritis (RA) is one of the autoimmune diseases characterized by the synovial inflammation which causes organs and tissues damage especially synovial tissues and joints. The study included 50 serum samples from patients with rheumatoid arthritis (RA) when compared with 50 serum samples from healthy individuals as control with age range 35 – 60 years (41.3 ± 2.4 years vs. 41.0 ± 2.0 years, respectively). ELISA technique was used to assess the Anti-cyclic citrullinated peptide IgG antibody (anti-CCP IgG Ab) level, anti-rheumatoid factor IgG antibody (anti-RF IgG) and anti-Cytomegalovirus (anti-CMV IgG) antibodies frequencies in the studied groups. The present findings demonstrated that all RA patients have 100% seropositive fr

Objectives: Many medication errors occur in the hospital, and these can endanger patients. The purpose of this study was to evaluate the incidence of medication errors in hospitalized patients, and to categorize the most frequent types of errors, and to asses the possible measures that may prevent the occurrence of such errors.
Methods: A prospective, exploratory, and evaluative study, using direct observation method to detect medication errors in adult hospitalized patients in medical and surgical units in Baquba Teaching Hospital- Diyala-Iraq.. The files of 299 patients had been reviewed from July 2009 to September 2009, including medication orders and treatment sheets to detect existing errors. The detected errors were recorded and

This paper presents comprehensive analysis and investigation for 1550nm and 1310nm ring optical modulators employing an electro-optic polymer infiltrated silicon-plasmonic hybrid phase shifter. The paper falls into two parts which introduce a theoretical modeling framework and performance assessment of these advanced modulators, respectively. In this part, analytical expressions are derived to characterize the coupling effect in the hybrid phase shifter, transmission function of the modulator, and modulator performance parameters. The results can be used as a guideline to design compact and wideband optical modulators using plasmonic technology

Portland cement concrete is the most commonly used construction material in the world for decades. However, the searches in concrete technology are remaining growing to meet particular properties related to its strength, durability, and sustainability issue. Thus, several types of concrete have been developed to enhance concrete performance. Most of the modern concrete types have to contain supplementary cementitious materials (SCMs) as a partial replacement of cement. These materials are either by-products of waste such as fly ash, slag, rice husk ash, and silica fume or from a geological resource like natural pozzolans and metakaolin (MK). Ideally, the utilization of SCMs will enhance the concrete performance, minimize

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Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f

Face recognition is required in various applications, and major progress has been witnessed in this area. Many face recognition algorithms have been proposed thus far; however, achieving high recognition accuracy and low execution time remains a challenge. In this work, a new scheme for face recognition is presented using hybrid orthogonal polynomials to extract features. The embedded image kernel technique is used to decrease the complexity of feature extraction, then a support vector machine is adopted to classify these features. Moreover, a fast-overlapping block processing algorithm for feature extraction is used to reduce the computation time. Extensive evaluation of the proposed method was carried out on two different face ima

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

Visceral leishmaniasis(VL) or kala-azar is one of the world most neglected tropical diseases in mortality and fourth in morbidity, rK39 dipstick was used to diagnose the suspected infected patients as easiest and rapid technique for VL diagnostic, the disease out-coming required to the differentiation of cell mediated immunity either T-helper 1(Th-1) or (Th-2). One of main pointers that may be considered as one of immune evasion strategy in the host-parasite interplay is HLA-G level alteration. HLA-G Known as a special proteins (non-classical HLA class I) molecules which can suppress the immune system by T-cell functions impaired in the aid with target receptors as LILRB4. The development of the cell mediated immunity initiated with Interle