Background: The COVID-19 virus outbreak had a massive effect on many parts of people's lives, as they were advised to quarantine and lockdown to prevent the virus from spreading, which had a big impact on people's mental health, anxiety, and stress. Many internal and external factors lead to stress. This negatively influences the body's homeostasis. As a result, stress may affect the body's capacity to use energy to defend against pathogens. Many recent investigations have found substantial links between human mental stress and the production of hormones, prohormones, and/or immunological chemicals. some of these researches have verified the link between stress and salivary cortisol levels. The aim of this study is to measure salivary corti

In this study the thermal conductivity of the epoxy composites were characterized as function of volume fraction, particle size of fillers and the time of immersion(30,60,90)days in water .Composites plates were prepared by incorporating (bi-directional) (0º-90º) glass fiber and silicon carbide (SiC) particles of (0.1,0.5,1)mm as particle size at (10%,20%,30%,40%) percent volume in epoxy matrix.
The composites shows slightly increase of the thermal conductivity with increasing volume fraction, particle size and increase with increasing the days of immersion in water. The maximum thermal conductivity (0.51W/m.K) was obtained before the immersion in water at 90 days for epoxy reinforcement by bi-directional glass fiber and SiC particl

Denture bases are fabricated routinely using Poly(methyl methacrylate) (PMMA) acrylic resin. Yet, it is commonly known for its major drawbacks such as insufficient strength and ductility. The purpose of this study was to improve the performance of PMMA acrylic resin as a denture base material by reinforcement with surface treated lithium disilicate glass ceramic powder. The ceramic powder was prepared by grinding and sieving IPS e.max CAD MT blocks. Then, the powder was surface treated with an organosilane coupling agent (TMSPM) and added to PMMA in amount of 1%, 3%, 5% and 7% by weight. Characterizations of the powder was done by particle size analysis, XRD and FTIR. Transverse strength, Impact strength, Shore D hardness and surface roughn

In the present study, multi-walled carbon nanotubes (MWCNTs) with outside diameters of< 8 nm and 20−30 nm were covalently functionalized with β-Alanine using a novel synthesis procedure. The functionalization process was proved successful using Raman spectroscopy, FTIR, and TEM. Utilizing the two-step method with ultrasonication, the MWCNTs treated with β-Alanine (Ala-MWCNTs) with weight concentrations of 0.025%, 0.05%, 0.075%, and 0.1% were dispersed in distilled water to prepare water-based nanofluids. The aqueous colloidal dispersions of pristine MWCNTs were unstable. While for Ala-MWCNTs and after> 50 days from preparation, higher colloidal stability was obtained up to relative concentration of 0.955 and 0.939 for the 0.075-wt% samp

Liquid – liquid interface reaction is the method for
preparation nanoparticles (NP'S) which depend on the super
saturation of ions that provide by using the system that consist from
toluene and water, the first one is above the second to obtain
nanoparticles (NP's) CdS at the interface separated between these
two immiscible liquid. The structure properties were characterized by
XRD-diffraction and transmission electron microscopy.
The crystalline size estimate from X-ray diffraction pattern
using Scherer equation to be about 7nm,and by TEM analysis give us
that ananosize is about 5 nm which give a strong comparable with
Bohr radius. Photoluminescence analysis give two emission peak,
the first one around

Abstract

Characterized by the Ordinary Least Squares (OLS) on Maximum Likelihood for the greatest possible way that the exact moments are known , which means that it can be found, while the other method they are unknown, but approximations to their biases correct to 0(n^-1) can be obtained by standard methods. In our research expressions for approximations to the biases of the ML estimators (the regression coefficients and scale parameter) for linear (type 1) Extreme Value Regression Model for Largest Values are presented by using the advanced approach depends on finding the first derivative, second and third.