. 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

Obesity is a risk factor for a number of chronic conditions. Obesity is clinically defined using the body mass index (BMI) as weight in kg divided by (height)² in m² correlated with obesity. Currently, genetic markers of obesity are being studied. This study focused on the association between the angiotensin II receptor AGTR1 gene (A1166C) and fat mass and obesity-associated protein also known as alpha-ketoglutarate-dependent dioxygenase (FTO) (rs9939609) in obese children and adolescents patients in Rostov region, Russia.  Five-hundreds of Russian nationality child and adolescent were recruited for the obesity-control studies. The relationship between the A1166C polymorphism of the AGTR1 gene in

Human action recognition has gained popularity because of its wide applicability, such as in patient monitoring systems, surveillance systems, and a wide diversity of systems that contain interactions between people and electrical devices, including human computer interfaces. The proposed method includes sequential stages of object segmentation, feature extraction, action detection and then action recognition. Effective results of human actions using different features of unconstrained videos was a challenging task due to camera motion, cluttered background, occlusions, complexity of human movements, and variety of same actions performed by distinct subjects. Thus, the proposed method overcomes such problems by using the fusion of featur

The recent studies suggested the possible toxicities or genetic alterations associated with biological and medical applications of silver nanoparticles (AgNPs). The current research is directed to see if AgNPs administration can lead to some changes in expression of BRAF gene in selected body organs tissues. Fifty-six male of musmusculs (Balb/C) mice from the animal house of Al-Nahrain Centre of Biotechnology were used. These animals were divided randomly to seven groups (eight mouse in each group), one of these groups represented the control group, three groups were subjected to different doses of AgNPs (0.25, 0.5and 1 mg/kg of body weight) for one week, and the remaining three groups were subjected to three different doses of AgNP

The aim of this study was to investigate the correlation between GRIN2A rs387906637 polymorphism and susceptibility to epilepsy. Blood samples were collected from 85 volunteers, dividing into 60 epilepsy patients (34 males and 26 females) and 25 healthy subjects (19 males and 6 females).The DNA was extracted and GRIN2A rs387906637 polymorphism was analyzed by Real-time PCR using two probes and primers. The results showed no significant differences between patients and control samples; therefore, there are no allelic and genotypic correlations of this SNP with epilepsy. This study indicated that GRIN2A rs387906637 polymorphism is not a risk factor for epilepsy in the studied set of patients.

     The present study investigates the implementation of machine learning models on crop data to predict crop yield in Rajasthan state, India. The key objective of the study is to identify which machine learning model performs are better to provide the most accurate predictions. For this purpose, two machine learning models (decision tree and random forest regression) were implemented, and gradient boosting regression was used as an optimization algorithm. The result clarifies that using gradient boosting regression can reduce the yield prediction mean square error to 6%. Additionally, for the present data set, random forest regression performed better than other models. We reported the machine learning model's performance using Mea

     Approximately 15% of all couples all over the world suffer from difficulty conceiving their first child. The word "infertility" is used to describe this problem.

When a couple had  regular, unprotected sexual intercourse for a year or longer, it indicates that they have been unsuccessful in their efforts to conceive.

      The current investigation aims to find out if there is a relationship between PROTAMIN-1(PRM-1) and INTERLEUKINE-12 (IL-12) gene expressions and their effect on the development of infertility. The current investigation comprised 100 teratozoospermia patients and 100 healthy fertile controls who had their semen examined. Samples were given by Al-Nahrain University's Biotech

Background: The study was conducted to investigate the association between hyperprolactinaemia and markers of human leukocyte antigen (HLA) system in a sample of Iraqi infertile females, together with the profile anti-nuclear antibodies (ANA).
Objectives: One hundred and seventy five female patients (age range: 20 -40 years) were recruited in this study. They were attending the Institute for Embryo Research and Infertility Treatment (Al-Nahrain University) during the period January 2005 - September 2006.
Results:After clinical and laboratry evaluations, it was found that 100 patients were hyperprolactinaemic, whereas the other 75 patients were euprolactinaemic, therefore, they were considered as a control group. Based on serum le

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