Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

The 3-parameter Weibull distribution is used as a model for failure since this distribution is proper when the failure rate somewhat high in starting operation and these rates will be decreased with increasing time .

In practical side a comparison was made between (Shrinkage and Maximum likelihood) Estimators for parameter and reliability function using simulation , we conclude that the Shrinkage estimators for parameters are better than maximum likelihood estimators but the maximum likelihood estimator for reliability function is the better using statistical measures (MAPE)and (MSE) and for different sample sizes.

Note:- n_s : small sample ; n_m=median sample

Twelve species from Brassicaceae family were studied using two different molecular techniques: RAPD and ISSR; both of these techniques were used to detect some molecular markers associated with the genotype identification. RAPD results, from using five random primers, revealed 241 amplified fragments, 62 of them were polymorphic (26%).

    ISSR results showed that out of seven primers, three (ISSR3, UBC807, UBC811) could not amplify the genomic DNA; other primers revealed 183 amplified fragments, 36 of them were polymorphic (20%). The similarity evidence and dendrogram for the genetic distances of the incorporation between the two techniques showed that the highest similarity was 0.897 between the va

     In this article, the lattice Boltzmann method with two relaxation time  (TRT)  for the  D2Q9 model is used to investigate numerical results for 2D flow. The problem is performed to show the dissipation of the kinetic energy rate and its relationship with the enstrophy growth for 2D dipole wall collision. The investigation is carried out for normal collision and oblique incidents at an angle of . We prove the accuracy of moment -based boundary conditions with slip and Navier-Maxwell slip conditions to simulate this flow. These conditions are under the effect of Burnett-order stress conditions that are consistent with the discrete Boltzmann equation. Stable results are found by using this kind of boundary condition where d

Mn₂O₃ was coated onto reduced titania nanotubes by reverse pulse electrodeposition, showing smooth and homogenous deposits without covering the opening of the nanotubes.

KE Sharquie, JR Al-Rawi, AA Noaimi, RA Al-Khammasi, Iraqi Journal of Community Medicine, 2018

Two-dimensional unsteady mixed convection in a porous cavity with heated bottom wall is numerically studied in the present paper. The forced flow conditions are imposed by providing a hydrostatic pressure head at the inlet port that is located at the bottom of one of the vertical side walls and an open vent at the top of the other vertical side wall. The Darcy model is adopted to model the fluid flow in the porous medium and the combination effects of hydrostatic pressure head and the heat flux quantity parameters are carefully investigated. These governing parameters are varied over wide ranges and their effect on the heat transfer characteristics is studied in detail. It is found that the time required to reach a desired temperature at th

Background: Coronavirus disease 2019 (COVID-19) is an emerging zoonotic disease caused by the new respiratory virus SARS-CoV2. It has a tropism in the lung tissues where excess target receptors exist. Periostin plays a role in subepithelial fibrosis associated with bronchial asthma. Since the Coronavirus's target is the human respiratory system, Periostin has been recently described as a valuable new biomarker in the diagnosis and evaluation of disease in patients with COVID-19 lung involvement. Objectives: To assess the level of Periostin in the serum of COVID-19 patients and to correlate its role in disease severity and prognosis. Subjects and Methods: Periostin serum levels were measured for 63 patients attending three main COVID