The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

objective  the research to diagnosis and interpretation of the nature of the correlation between the  basic elements of knowledge management (tecgnology , structure , culture , process , human resource ) and the strategic performance of the Iraqi private banks, the research community and the level dimensions, and  tested this research in the private banking sector represented by (7), especially in Baghdad city, Iraqi banks, and applied on sample consisting of 100 distributors in several administrative levels Director (Director, Director of the department, branch manager), and use questionnaire Head to collect data and information tool, and some private banks annual reports, has sought research to test a number of h

A pure posteriorly posterior communicating artery (PCoA) aneurysm represents a surgical challenge. This is mainly when there is a need for good exposure of the aneurysmal neck, sac, PCoA, and anterior choroidal arteries. Ruptured pure posteriorly directed PCoA aneurysm imposes significantly extra challenge as the surgeon undergoes dissection through a tight brain. Even with measures commonly used to attain brain relaxation like the lumbar drain and cisternal fenestration. Here, we describe a technique for posterior temporal pole mobilization (TPM) as an integrated part of microsurgical clipping of ruptured pure posteriorly directed PCoA aneurysms. This technique is implicated in twenty-three successive cases of ruptured PCoA aneurys

A mathematical model has been introduced to investigate the effect of nuclear reaction constant ( A ), probability of the BEC ground state occupation Ω i, nD is the number density of deuteron (d) and the overall number of nuclei ND on the total nuclear d-d fusion rate (R). Under steady-state of the condensates of Bose-Einstein, the postulate of quantum theory and Bose-Einstein theory were applied to evaluate the total nuclear (d-d) fusion rate trapping in Nickel-metal The total nuclear fusion rate trapping predicts a strong relationship between astrophysical S-factor and masses of Nickel. The reaction rate trapping model was tested on three reaction d(d,p)T, d(d, n)3He and d(d, 4He)Q = 23.8MeV respectively. The reaction rate has described

Epilepsy is considered as one of the common neurological disorders.About 50 million persons have affected by epilepsy .Carbamazepine is one of the common drugs used by pregnant women with epilepsy. The aim of the present study is to investigate the effect of carbamazepine on the process of brain development during day 13 of pregnancy.Fifty pregnant albino mice have been used. They were divided into two groups. The control group that had been orally drenched with normal saline. The other group was treated group that had been given 15 mgKg of Carbamazepine orally. The fetuses have been collected after killing of the mice. Boun’s solution was selected as fixative. 5-8 µm thick sections from the fetuses were cut to be stained with hematoxyli

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