Significant risks to human health are posed by the 2019 coronavirus illness (COVID-19). SARS coronavirus type 2 receptor, also known as the major enzyme in the renin-angiotensin system (RAS), angiotensin-converting enzyme 2 (ACE-2), connects COVID-19 and RAS. This study was conducted with the intention of determining whether or not RAS gene polymorphisms and ACE-2 (G8790A) play a part in the process of predicting susceptibility to infection with COVID-19. In this study 127 participants, 67 of whom were deemed by a physician to be in a severe state of illness, and 60 of whom were categorized as "healthy controls" .The genetic study included an extraction of genomic DNA from blood samples of each covid 19 patients and healthy control

Throughout what mentioned above, It is obvious that the aware narrator in these biography models was the strongest tool in presenting the content, especially the biographies under study were written by feminine hands, striving to prove her identity by all means and ways. In addition, we can suppose that the hiding of she writer behind the character is no more than a mask, by which she want to mask herself so that she can express herself frankly and freely, especially when she talks about subjects that are inconsistent with the society, customs and traditions. It is important to refer that the existence of the participant narrator in the biographies under study does not prevent the presence of another narrator such as external or aware na

In order to advance the education process and raise the educational level of the players, it became necessary to introduce new educational aids, programmed education in the education process, through which the basic skills to be learned are explained and clarified, and immediate feedback is provided that would enhance the information of the learner, and Reaching the goal to be achieved, taking into account the individual differences between the players, and thus it is possible to move away from the educational methods used in learning skills, which requires great effort and time, in addition to that the open playground may not perform the skill accurately and the player looks from one side, while when using the computer you look from severa

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation)  structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of  these procedures and compare them using generated data.

The subject of dumping is considering today one of the subjects in which form an obstruction arise in front of the cycle of growth for some countries , such as the study of dumping is capturing a large attention by the competent because either a big  role and effect in growing the economies of nations then the subject of dumping became a field turn around its sides many measures and laws … and may be done resorting to by many states of the world to anti-dumping as approach of determent weapon delimit  the impact of dumping and gives the national agriculture sector the opportunity for rising and growing so this section of international economics is capturing a special importance and represent in same time an important

With the increasing demands to use remote sensing approaches, such as aerial photography, satellite imagery, and LiDAR in archaeological applications, there is still a limited number of studies assessing the differences between remote sensing methods in extracting new archaeological finds. Therefore, this work aims to critically compare two types of fine-scale remotely sensed data: LiDAR and an Unmanned Aerial Vehicle (UAV) derived Structure from Motion (SfM) photogrammetry. To achieve this, aerial imagery and airborne LiDAR datasets of Chun Castle were acquired, processed, analyzed, and interpreted. Chun Castle is one of the most remarkable ancient sites in Cornwall County (Southwest England) that had not been surveyed and explored

In this study, the spreading of the pandemic coronavirus disease (COVID-19) is formulated mathematically. The objective of this study is to stop or slow the spread of COVID-19. In fact, to stop the spread of COVID-19, the vaccine of the disease is needed. However, in the absence of the vaccine, people must have to obey curfew and social distancing and follow the media alert coverage rule. In order to maintain these alternative factors, we must obey the modeling rule. Therefore, the impact of curfew, media alert coverage, and social distance between the individuals on the outbreak of disease is considered. Five ordinary differential equations of the first-order are used to represent the model. The solution properties of the system ar

Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem

This paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.