Perfluorooctanoic acid (PFOA) is a synthetic fluor-surfactant chemical used widely in ‎products that resist oil, heat, grease, stains, and water. It is also used in producing other ‎fluoropolymers. The main sources of exposure to PFOA are water, soil, and animal-‎origin food (meat, fish, and dairy products). The aim of this study to evaluate the renal ‎function following oral gavage of sub-lethal dose of PFOA in diabetic and non-diabetic ‎guinea pigs. The experiment run for 4 weeks, total of 40 male guinea pigs, ‎‎(Cavia porcellus), were randomly selected and grouped into four equal groups. The first ‎group (G1) served as the negative control; 2nd group (G2) alloxan induced diabetic, 3rd ‎group (G3) non-diabeti

Electric Quadrupole transitions are calculated for beryllium isotopes (9, 10, 12 and 14). Calculations with configuration mixing shell model usually under estimate the measured E2 transition strength. Although the consideration of a large basis no core shell model with 2ℏtruncations for 9,10,12 and14 where all major shells s, p, sd are used, fail to describe the measured reduced transition strength without normalizing the matrix elements with effective charges to compensate for the discarded space. Instead of using constant effective charges, excitations out of major shell space are taken into account through a microscopic theory which allows particle–hole excitations from the core and model space orbits to all higher orbits

       In recent years, the attention of researchers has increased of semi-parametric regression models, because it is possible to integrate the parametric and non-parametric regression models in one and then form a regression model has the potential to deal with the cruse of dimensionality in non-parametric models that occurs through the increasing of explanatory variables. Involved in the analysis and then decreasing the accuracy of the estimation. As well as the privilege of this type of model with flexibility in the application field compared to the parametric models which comply with certain conditions such as knowledge of the distribution of errors or the parametric models may

The purpose of this article is to improve and minimize noise from the signal by studying wavelet transforms and showing how to use the most effective ones for processing and analysis. As both the Discrete Wavelet Transformation method was used, we will outline some transformation techniques along with the methodology for applying them to remove noise from the signal. Proceeds based on the threshold value and the threshold functions Lifting Transformation, Wavelet Transformation, and Packet Discrete Wavelet Transformation. Using AMSE, A comparison was made between them , and the best was selected. When the aforementioned techniques were applied to actual data that was represented by each of the prices, it became evident that the lift

    The cinematic costume is a qualitative element that transcends the direct function of it. It is an active personality that can become a brand of publicity and transformative signs that dismantle the intellectual system of acts, characters and events and reconstructs them aesthetically. For this reason, the researcher identified the subject of his research with the following address: (cinematic costumes between the function of publicity and Semiotics Significance). The researcher divided the research into the following: The methodological framework. The theoretical framework: The researcher divided it into three topics: the first topic: publicity. Function and concept. The second topic: fashion text and significance. Th

    This article aims to explore the importance of estimating the a semiparametric regression function ,where we suggest a new estimator beside the other combined estimators and then we make a comparison among them by using simulation technique . Through the simulation results we find  that the suggest estimator is the best with the first and second models ,wherealse for the third model we find Burman and Chaudhuri (B&C) is best.

Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

    This research aims to review the importance of estimating the nonparametric regression function using so-called Canonical Kernel which depends on re-scale the smoothing parameter, which has a large and important role in Kernel  and give the sound amount of smoothing .

We has been shown the importance of this method through the application of these concepts on real data refer to international exchange rates to the U.S. dollar against the Japanese yen for the period from January 2007 to March 2010. The results demonstrated preference the nonparametric estimator with Gaussian on the other nonparametric and parametric regression estima

Since the nineties of the last century, Iraqi youth have been exposed to Mexican soap operas dubbed into classical Arabic, and the stories and ideas presented by these series were almost new to all the minds of the youth at that time, a culture completely different from the culture we have of social relations, and since the number of episodes was more than Of the 100 episodes, exposure to these series has left young people confused by the addiction to all their ideas and stories. They differ from the foreign films (mostly American) that we used to watch, and they only take two hours (at most). These films contain diverse stories and may be forgotten. Memory includes events and characters in their entirety at times, and you may remember th