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

The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

As the reservoir conditions are in continuous changing during its life, well production rateand its performance will change and it needs to re-model according to the current situationsand to keep the production rate as high as possible.Well productivity is affected by changing in reservoir pressure, water cut, tubing size andwellhead pressure. For electrical submersible pump (ESP), it will also affected by numberof stages and operating frequency.In general, the production rate increases when reservoir pressure increases and/or water cutdecreases. Also the flow rate increase when tubing size increases and/or wellhead pressuredecreases. For ESP well, production rate increases when number of stages is increasedand/or pump frequency is

Ensuring reliable data transmission in Network on Chip (NoC) is one of the most challenging tasks, especially in noisy environments. As crosstalk, interference, and radiation were increased with manufacturers' increasing tendency to reduce the area, increase the frequencies, and reduce the voltages.  So many Error Control Codes (ECC) were proposed with different error detection and correction capacities and various degrees of complexity. Code with Crosstalk Avoidance and Error Correction (CCAEC) for network-on-chip interconnects uses simple parity check bits as the main technique to get high error correction capacity. Per this work, this coding scheme corrects up to 12 random errors, representing a high correction capac

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

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 a

Efficacy of Several Forms of Storage Medium on Avulsed Teeth's Enamel Surface Roughness (An in Vitro Study), Rawaa Sadiq Obeid1*, Muna Saleem Khalaf2

A study of Zooplankton community has been carried out at four selected sites on Dukan Lake. Samples of water and zooplankton were collected monthly for the period from July 2015 to February 2016. Some physical and chemical properties of water were studied and the results showed that the air temperature were ranged from 0 to 36.16 °C, water temperature ranged from 2.83 to 34.66 °C, hydrogen ion concentration of studied sites were found to lie in alkaline side, it was ranged between 6.87 to 8.57, electrical conductivity ranged from 190.79 to 850.08 µs.cm­¹, turbidity ranged from 0.9-7.7 NTU, and dissolved oxygen from 3.3 to 6.8 mg.l-¹ while BOD5 were ranged from 0.53 to 34.66 mg.l-¹. Concerning to the zooplankton, 37 species were ident