ABSTRACT Background: work-related musculoskeletal disorders represent an important occupational health issues among dentists especially neck and low back complaints. Biomarkers of tissue damage as results of occupational physical demands could be used for detection of work related musculoskeletal disorders. Aim: The aim of this study was to assess work- related musculoskeletal disorders, physical work load index, selected salivary biomarkers (Creatine kinase and C - reactive protein) and to find the relation among them. Subjects and Methods: Study participants are consisted of 112 dentists. They were selected from college of dentistry /Baghdad University, health care center in Bagdad city. They were of both gender and aged between 40-45 yea

Objective:To Evaluate of Estradiol and Prolactin hormones levels for Breast Cancer women in
Baghdad City.
Methodology: The current study was conducted on 60 breast cancer women and 40 apparently
healthy subjects to evaluate the levels of estradiol and prolactin "hormones in the serum" of
({premenopausal & postmenopausal}) breast cancer and healthy controle women. Estradiol and
prolactin hormones estimated for all cases by using the IMMULITE 2000 instrument that performs
chemiluminescent immunoassays results are calculated for each sample.Data were analysed using
SPSS-18.data of two groups was comparison by the student's t-test.
Results: The results showed a non significant""(P>0.05) elevation in the –mean

Nearly, in the middle of 1970s the split-brain theory became the only theory that explains human creativity used in all fine art and art education schools. In fact, this theory- which appeared for first time in the middle of 1940s – faced many radical changes including its concepts and structures, and these changes affected both teaching art and art criticism. To update people awareness within art field of study, this paper reviews the split-brain theory and its relationship with teaching art from its appearance to its decay in 2013 and after.

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost, loss etc. while maintaining an acceptable system performance in terms of limits on generators real and reactive powers, line flow limits etc. The OPF solution includes an objective function. A common objective function concerns the active power generation cost. A Linear programming method is proposed to solve the OPF problem. The Linear Programming (LP) approach transforms the nonlinear optimization problem into an iterative algorithm that in each iteration solves a linear optimization problem resulting from linearization both the objective function and constrains. A computer program, written in MATLAB environme

The interest of application of liquid membrane (pertraction) processes for recovery of medicinal compounds from dilute ammoniacal leach solutions is demonstrated. Selectivity of the liquid membrane ensures a preferential transport of the desired solute from the native extract into the strip solution, vinblastine was successfully extracted from basic media (pH 9.2) and stripped by acidic media of sulfuric acid (pH= 1.3) applying continuous pertraction in a rotating discs contactor and using n-decane as liquid membrane. Transport of vinblastine in three-liquid-phase system was studied and performed by means of a kinetic model involving two consecutive irreversible first-order reactions. The kinetic parameters (apparent rate constants of th

A nano-sensor for nitrotyrosine (NT) molecule was found by studying the interactions of NT molecule with new B24N24 nanocages. It was calculated using density functionals in this case. The predicted adsorption mechanisms included physical and chemical adsorption with the adsorption energy of −2.76 to −4.60 and −11.28 to −15.65 kcal mol−1, respectively. The findings show that an NT molecule greatly increases the electrical conductivity of a nanocage by creating electronic noise. Moreover, NT adsorption in the most stable complexes significantly affects the Fermi level and the work function. This means the B24N24 nanocage can detect NT as a Φ–type sensor. The recovery time was determined to be 0.3 s. The sensitivity of pure BN na