Type 1 diabetes (T1D) is an autoimmune disease with chronic nature resulting from a combination of both factors genetic and environmental. The genetic contributors of T1D among Iraqis are unexplored enough. The study aimed to shed a light on the contribution between genetic variation of interleukin2 (IL2) gene to T1D as a risk influencer in a sample of Iraqi patients. The association between IL2−330 polymorphism (rs2069762) was investigated in 322 Iraqis (78 T1D patients and 244 volunteers as controls). Genotyping for the haplotypes using polymerase chain reaction test – specific sequence primer (PCR-SSP) for (GG, GT, and TT) genotypes corresponding to (G and T) alleles were performed. A significant association revealed a decreased freq

Abstract

   The extremes effects in parameters readings which are BOD (Biological Oxygen Demands) and DO(Dissolved Oxygen) can caused error estimating of the model’s parameters which used to determine the ratio of de oxygenation and re oxygenation of the dissolved oxygen(DO),then that will caused launch big amounts of the sewage pollution  water to the rivers and it’s turn is effect in negative form on the ecosystem life and the different types of the water wealth.

   As result of what mention before this research came to employees Streeter-Phleps model parameters estimation which are (K_d,K_r) the de oxygenation and re oxygenation ratios on respect

The purpose of this research was to investigate the beneficial effects of phosphatidylcholine in reducing changes in both lipid and protein profiles in addition to atherogenic index in adult rats with fructose-induced metabolic syndrome. Thirty-six mature Wistar Albino female rats (Rattus norvegicus) (aged 12-15 weeks and weighing 200±10 g) were divided randomly into four groups (G1, G2, G3, and G4); then variable treatments were orally administered for 62 days as follows: G1 (Control group), received distilled water; G2, treated with phosphatidylcholine (PC) orally (1 g/kg BW); G3 (Fr), orally dosed with 40% fructose and 25% fructose mixed with drinking water; G4 (Fr+PC), were also intubated with 40% fr

The demand for single photon sources in quantum key distribution (QKD) systems has necessitated the use of weak coherent pulses (WCPs) characterized by a Poissonian distribution. Ensuring security against eavesdropping attacks requires keeping the mean photon number (µ) small and known to legitimate partners. However, accurately determining µ poses challenges due to discrepancies between theoretical calculations and practical implementation. This paper introduces two experiments. The first experiment involves theoretical calculations of µ using several filters to generate the WCPs. The second experiment utilizes a variable attenuator to generate the WCPs, and the value of µ was estimated from the photons detected by the BB

. 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

In this paper, an ecological model with stage-structure in prey population, fear, anti-predator and harvesting are suggested. Lotka-Volterra and Holling type II functional responses have been assumed to describe the feeding processes . The local and global stability of steady points of this model are established. Finally, the global dynamics are studied numerically to investigate the influence of the parameters on the solutions of the system, especially the effect of fear and anti-predation.

Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro