This study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

Hepatitis C virus (HCV) is a liver disease that affects14 million people. Feasible research was conducted for identifying the genotypes and allele frequency of some single nucleotide polymorphisms (SNPs) of the IL-28β genes and their predictive role in disease incidence in Iraqi patients. The SNPs (rs28416813, rs4803219, rs11881222, and rs8103142) of IL-28β have been associated with susceptibility to several diseases. Ninety eight (98) HCV patients were included in this research; with average age ± SE (42.28 ± 3.44) years. Also, 80 healthy people (with average age ± SE (29.40 ± 2.84) years) were included as a control group. The SNPs were detected by allele-specific PCR (polymerase chain reaction) using specific primers. The re

Background: since December 2019, China and in particularly Wuhan, faced an unprecedented an outbreak challenge of coronavirus disease 2019, caused by the severe acute respiratory syndrome coronavirus 2. Clinical characteristics of Iraqi patients with COVID-19 and risk factors for mortality needed to be shared with the health care providers to improve the overall disease experience. Methods: prospective, single-center study recruited patients with confirmed SARS-CoV-2 infection who were admitted to Al-Shifaa Isolation Center / Baghdad Medical City between the mid of March and the end of April 2020 until had been discharged or had died. Demographic data, information on clinical signs, symptoms, at presentation, treatment, have been collected

Methotrxate (MTX) has become the standard of care and first-line therapy for patients who have RA and consider as a gold standard of treatment for RA. The role of MTX in the treatment of RA has now been well established. The use of MTX treatment of RA inhibits proliferation of the lymphocytes, reduces signs and symptoms this disease, reduces progression damage of the joints and improves quality of life outcome. Progranulin (PGRN) acts a role in autoimmune inflammatory, has important function in several processes including immune response. Present study has conducted to find the effect of MTX drugs as a therapeutic target for RA patients because of its ability to bind with tumor necrosis factor receptor (TNFR), with progranulin, obestatin an

Background: Myocardial infarction (MI) is distinguished by the necrosis of myocardial cells as a result of substantial and prolonged ischemia. Anxiety, problems sleeping, and feelings of depression are some of the most common psychosocial consequences of having a myocardial infarction. Aim: The purpose of this study is to evaluate the effects of post-myocardial infarction on patients' levels of anxiety, depression, and quality of sleep. Method: The collection of data from 94 individuals with MI was carried out according to a descriptive cross-sectional design. Sleep quality, depression, and anxiety were evaluated using standard questionnaires. Results: 69.1% of the participants reported having trouble getting quality sleep. The perc

Out of 150 different specimens, 67 S. aureus isolate were isolated. However, 16sRNA gene was located only in 60 isolates. Moreover, mecA gene was located in 48 isolates; thereby MRSA covered 80% of all S. aureus isolates. Of considerable interest, pvl gene was detected in only six isolates (10%). Hence, the present work emphasizes the notion suggested that pvl is not an indicative of CA-MRSA.

Background: Asthma is a disease of the airways characterized by chronic inflammation associated with airway hyper-responsiveness and airway wall remodeling. Aims of the study: The aims of this study was to determine the prevalence of oral manifestations , identify different microorganism from oral micro flora and determination of salivary IgA and salivary flow rate in asthmatic patients taking different dose of Prednisolone in comparison with control group. Subjects, materials and methods: The study included 17 patients under treatment with Prednisolone (10-20 mg),15 patients take (20-30 mg) of Prednisolone and other 18 patients take (30 – 40mg) of Prednisolone, and 25 healthy control group (10 male and 15 female). Results : The mo

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an