The research aims to determine the mix of production optimization in the case of several conflicting objectives to be achieved at the same time, therefore, discussions dealt with the concept of programming goals and entrances to be resolved and dealt with the general formula for the programming model the goals and finally determine the mix of production optimization using a programming model targets to the default case.

In this research a computational simulation  has been carried out on the design and properties of the electrostatic mirror and a mathematical expression has been suggested  to represent the axial potential of an electrostatic mirror. The electron beam path using the Bimurzaev  technique had been investigated as mirror trajectory with the aid of Runge – Kutta  method. The spherical and chromatic aberration coefficients of mirror has computed and normalized in terms of the focal length. The choice of the mirror depends on the operational requirements. The Electrode shape of mirror two electrodes has been determined by using package SIMION computer program. Computations have shown that the suggested potentials giv

Voting is an important procedure in democratic societies in different countries, including Iraq. Electronic voting (E-voting) is becoming more prevalent due to reducing administrative costs and burdens. E-voting systems have many restrictions that affect the electoral process. For example, fraud, tampering with ballot boxes, taking many hours to announce results, and the difficulty of reaching polling stations. Over the last decade, blockchain and smart contract technologies have gained widespread adoption in various sectors, such as cryptocurrencies, finance, banking, and most notably in e-voting systems. If utilized properly, the developer demonstrates properties that are promising for their properties, such as security, privacy, trans

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

STAG3 is the meiotic component of cohesin and a member of the Cancer Testis Antigen (CTA) family. This gene has been found to be overexpressed in many types of cancer, and recently, its variants have been implicated in other disorders and many human diseases. Therefore, this study aimed to analyze the major variants of STAG3. Western blot (WB) and immunoprecipitation (IP) assays were performed using two different anti-STAG3 antibodies that targeted the relevant protein in MCF-7, T-47D, MDA-MB-468, and MDA-MB-231 breast cancer cells with Jurkat and MCF-10A cells as positive and negative controls, respectively. In silico analyses were searched to study the major isoforms. WB and IP assays revealed two abundant polypeptides < 191 kDa and