In this paper, the deterministic and the stochastic models are proposed to study the interaction of the Coronavirus (COVID-19) with host cells inside the human body. In the deterministic model, the value of the basic reproduction number   determines the persistence or extinction of the COVID-19. If   , one infected cell will transmit the virus to less than one cell, as a result,  the person carrying the Coronavirus will get rid of the disease .If   the infected cell  will be able to infect  all  cells that contain ACE receptors. The stochastic model proves that if  are sufficiently large then maybe  give  us ultimate disease extinction although ,  and this  facts also proved by computer simulation.

The- role of radiotherapy in immunological and  cytological function of  patients.  with  carcino.ma  of  breast 'tDd   uterus  were  investigared: Using n:>sette forming T lYJi'lphl)Cytes, white  blood  cell's and lymphocytes  count  and  distributiQn  of  micronuclei  as  parameters . After  irradiation . the number  of  peripheral   blood  lymphocytes and vvhite blood  cells  was  reduced  . The  percentage of ro:sette Jorming  T

ly mphocytes   were· alsu  decreased   while  NBT  percentage  Of poly

morpho  nudcocyte

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

Many of the dynamic processes in different sciences are described by models of differential equations. These models explain the change in the behavior of the studied process over time by linking the behavior of the process under study with its derivatives. These models often contain constant and time-varying parameters that vary according to the nature of the process under study in this We will estimate the constant and time-varying parameters in a sequential method in several stages. In the first stage, the state variables and their derivatives are estimated in the method of penalized splines(p- splines) . In the second stage we use pseudo lest square to estimate constant parameters, For the third stage, the rem

Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the

Aim:- to show  that not all survival  curves without shoulder  are not able to repair or have lost the ability for the accumulation of sublethal damage.

Background:-  the shoulder  of the survival  curve  is considered  as a

region of accumulation  of sublethal  damage also as an indicator  for cell capacity to repair. The size can be influenced by the change ofthe slope of the linear portion of the survival curve.

Results:- we have shown  that a survival curve with  shoulder size of

1.5 Gy can be a straight line  when the slope of the  exponential part is changed  so  the

Children who have a health problem need special requirements for their clothes. The purpose of the study is to design functional and aesthetic clothes to meet their needs. The research used the applied descriptive approach. The research sample comprised 120 women whose children suffered from hip dislocation. Designs for injured children presented and submitted to the arbitrators for evaluation regarding the functional and aesthetic aspects. The finding was achieving the design solutions. The most important recommendations are to increase attention to designing clothes to suit all the needs of society.

 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

Color is one of the most important elements involved and contributing mainly to designs and visual works, whether they are fixed or mobile, for internal spaces through what color gives it the possibilities on the physical and intellectual level, if the process is linked to the functional performance or the aesthetic value, which is thus included within the system of processors and basic works in Designing the interior spaces and highlighting the functional and aesthetic aspects of them through the executed designs that are linked to certain techniques and mechanisms. Therefore, they are processed according to the references and pressure structures or the creation and modern dealing with materials and designs to implement operations in hi

This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators