Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

A simple setup of random number generator is proposed. The random number generation is based on the shot-noise fluctuations in a p-i-n photodiode. These fluctuations that are defined as shot noise are based on a stationary random process whose statistical properties reflect Poisson statistics associated with photon streams. It has its origin in the quantum nature of light and it is related to vacuum fluctuations. Two photodiodes were used and their shot noise fluctuations were subtracted. The difference was applied to a comparator to obtain the random sequence.

The cervical cancer considered as the fourth female prevalent disease worldwide, it was once the most extensively recognized female cancer two in many low-income countries. Human Cytomegalovirus (HCMV) exhibits broader tropism and can cause infection in most of the human body organs. Although, human cytomegalovirus HCMV is not yet considered an oncogenic virus, there is increased evidences of HCMV infection implication in malignant diseases of different cancer types. The present study aims to evaluate the effect of CMV infection on the development of HPV16 positive cervical cancinoma. The current retrospective study enrolled a number of paraffinized cervical cancer tissues .included 30 cervical carcinomatous tissues and 10 biopsies from an

The current research deals with the argument of delusion and interpretation in the direction structure and its reflected impact in the reception activity and the amount of conceptual displacement it is subjected to in an aesthetic approach to abstract conceptual definitions of the reception activity , by the effect of this dialectic in the direction structure, which can be summed up by the following question: (What are the characteristics of the direction structure of the imaginary and what is the argument of interpretation in the theatre reception activity?) in order to stand on the aesthetic framework and conceptual definition of the direction structure in the controversy of interpretation and imagination, and its impact on the concept

This study proposes a mathematical approach and numerical experiment for a simple solution of cardiac blood flow to the heart's blood vessels. A mathematical model of human blood flow through arterial branches was studied and calculated using the Navier-Stokes partial differential equation with finite element analysis (FEA) approach. Furthermore, FEA is applied to the steady flow of two-dimensional viscous liquids through different geometries. The validity of the computational method is determined by comparing numerical experiments with the results of the analysis of different functions. Numerical analysis showed that the highest blood flow velocity of 1.22 cm/s occurred in the center of the vessel which tends to be laminar and is influe