The aim of the current research to determine the extent of logical intelligence in the book of chemistry for the fifth grade of science and to achieve the goal the researcher has prepared a special criterion in the areas of logical intelligence main and sub-to be included in the book after reviewing the previous literature and studies in this regard may be the final form after presentation to experts and arbitrators in the field of Educational and psychological sciences, curricula and teaching methods from (3) main areas and (21) sub-fields, then the researcher analyzed the book Bibih and applied branches and adopted the idea of ​​both explicit and implicit as a unit of registration and repet

Abstract: E2F6 is a member of the E2F family of transcription factors involved in regulation of a wide variety of genes through both activation and repression. E2F6 has been reported as overexpressed in breast cancers but whether or not this is important for tumor development is unclear. We first checked E2F6 expression in tumor cDNAs and the protein level in a range of breast cancer cell lines. RNA interference-mediated depletion was then used to assess the importance of E2F6 expression in cell lines with regard to cell cycle profile using fluorescence-activated cell sorting and a cell survival assay using (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). The overexpression of E2F6 was confirmed in breast tumor cDNA samp

The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma

Checkpoint inhibitors are a type of immune therapy used to treat different types of cancers. These drugs block different checkpoint proteins, for example, CTLA-4, PD-1, and PD-L1 inhibitors.

They block proteins that stop the immune system from attacking the cancer cells.  Checkpoints are also described as a type of monoclonal antibody that antagonizes binding between B7 to CTLA-4 and PD-L1 to PD-1.

 Immune checkpoint inhibitors are used to treat BARCA mutated triple-negative breast cancer (TNBCS) in patients who do not respond to chemotherapy, and also in the treatment of highly mutated and solid tumors such as brain tumors, liver, and pancreatic cancers.

Immune checkpoint inhibitors exhibit an effect on solid tumo

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with