Objective: To conduct a standardized method for cavity preparation on the palatal surface of rat maxillary molars and to introduce a standardized method for tooth correct alignment within the specimen during the wax embedding procedure to better detect cavity position within the examined slides. Materials and methods: Six male Wistar rats, aged 4-6 weeks, were used. The maxillary molars of three animals were sectioned in the frontal plane to identify the thickness of hard tissue on the palatal surface of the first molar which was (250-300µm). The end-cutting bur (with a cutting head diameter of 0.2mm) was suitable for preparing a dentinal cavity (70-80µm) depth. Cavity preparation was then performed using the same bur on the tooth

Background: Colorectal cancer is the third most common cancer-related mortality worldwide, and its prevalence is increasing among many nations.  Aim of the study: Investigate the predictive value of carbohydrate antigen 242 (CA242) in comparison to the CEA biomarker and to estimate the significance of CA242 as prognosis maker in colorectal cancer patients. Methods: a case-control study with a total of 150 individuals, 100 patients (59 males, 41 females) and 50 healthy controls (26 males, 24 females). using an enzyme-linked immunosorbent (ELISA) to determine the serum levels of CA242 and CEA. The study was carried out at the gastroenterology consultation clinic of the oncology teaching hospital between November 2020 and February

BACKGROUND: Polycystic ovary syndrome(PCOS) is one of the most common endocrine disorder affecting women in reproductive age. No single etiologic factor fully accounts for the spectrum of abnormalities in the polycystic ovary syndrome. Different changes in hormonal, metabolism and the inflammatory markers as squealy of PCOS with adverse effect on the women life. OBJECTIVE: To study the relationship between polycystic ovary syndrome and levels of C-reactive protein, human interleukin and hormonal and metabolic alteration in women with PCOS PATIENTS AND METHODS: Thirty women with Polycystic Ovary syndrome (PCOS) and other thirty women without PCOS were included. Venous blood samples were taken in early follicular phase of menstrual cycle [day

The dependence of the energy losses or the stopping power for the ion contribution in D- T hot plasma fuels upon the corresponding energies and the related penetrating factorare arrive by using by a theoretical approximation models. In this work we reach a compatible agreement between our results and the corresponding experimental results.

The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of dat

The aim of the research is to shed light on identifying the extent of the university professor's competencies and their roles in managing and training participants in e-training workshops as a pedagogical point view. The research sample consisted of a group of (30) university professors (lecturers) in the training workshops, in scientific,humanitarian and social disciplines, including (12) a university professor (holding a trainer certificate), , the research methodology is descriptive, and the community is a group of trained participants. (115) participated in (40) e-training workshops organized by the Center for Continuing Education at the University of Baghdad (and the selection of workshops within the researcher's specialization in the

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals