Background: Oral squamous cell carcinoma (OSCC) is the most prevalent malignant neoplasm of the oral cavity and constitutes a major health problem in developing. In the last 30 years, the 5-year survival rate of patients with oral SCC has not improved despite advance in diagnostic techniques. To improve early diagnosis for this deadly disease, new biological markers are needed. HOX genes encode homeodomain-containing transcription factors involved in the regulation of cellular proliferation and differentiation during embryogenesis. HOX gene expression has been described in several adult tissues, where they performed important roles in maintaining homeostasis. Few studies have suggested that HOXA1 plays a role in tumorigenesis. Besides bein

The BEK family of flows have many important practical applications such as centrifugal pumps, steam turbines, turbo-machinery and rotor-stator devices. The Bödewadt, Ekman and von Kármán flows are particular cases within this family. The convective instability of the BEK family of rotating boundary-layer flows has been considered for generalised Newtonian fluids, power-law and Carreau fluids. A linear stability analysis is conducted using a Chebyshev collocation method in order to investigate the effect of shear-thinning and shear-thickening fluids for generalised Newtonian fluids on the convective Type I (inviscid crossflow) and Type II (viscous streamline curvature) modes of instability. The results reveal that shear-thinning power-law

Schiff bases of Ceftizoxime sodium were synthesized in an attempt to improve the antimicrobial spectrum of Ceftizoxime. Aminothiazole ring of Ceftizoxime is linked directly through an imino group to different aromatic aldehydes reacted by nucleophilic addition using trimethylamine (TEA), as a catalyst and refluxed in methanol. The antimicrobial activity was evaluated for such Schiff bases using disc diffusion method. Molecular docking was conducted on certain penicillin-binding proteins (PBPs) and carboxypeptidases using 1- click docking software. Schiff bases of Ceftizoxime were prepared with reasonable yields and their chemical structures were confirmed by spectral analysis (FTIR, 1H-NMR) and elemental microanalysis (CHNS). The antibacter

Methods of estimating statistical distribution have attracted many researchers when it comes to fitting a specific distribution to data. However, when the data belong to more than one component, a popular distribution cannot be fitted to such data. To tackle this issue, mixture models are fitted by choosing the correct number of components that represent the data. This can be obvious in lifetime processes that are involved in a wide range of engineering applications as well as biological systems. In this paper, we introduce an application of estimating a finite mixture of Inverse Rayleigh distribution by the use of the Bayesian framework when considering the model as Markov chain Monte Carlo (MCMC). We employed the Gibbs sampler and

Plasma physics and digital image processing technique (DIPT) were utilized in this research to show the effect of the cold plasma (plasma needle) on blood cells. The second order statistical features were used to study this effect. Different samples were used to reach the aim of this paper; the patients have leukemia and their leukocytes number was abnormal. By studying the results of statistical features (mean, variance, energy and entropy), it is concluded that the blood cells of the sample showed a good response to the cold plasma.

This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett