Determination and evaluation of principal minerals in Negella sativa by atomic absorption technical methods were showed, using wet ashing method. This work was done on Negella sativa because of wide using of this plant in many formulations ( in food or medicine ).two types of atomic absorptions were used : first, flame atomic absorption spectroscopy, for minerals of high concentrations such as, Na, Mg, K, Fe, Ca, Li, Ni, Zn, Mn, Cu. Second, flameless atomic absorption spectroscopy, for minerals of low concentrations such as, Al, Si, V, B, Pb, Co, Cd, Cr ,Si, Hg, Sn .The results showed the existence of many minerals in Negella sativa useful to human sanity with acceptable dietary allowance. On other side, the presence of harmful m

Background: Diabetes mellitus type 2 has been known for many years as the most common endocrine metabolic disorder that affect the oral cavity and cause many oral diseases including candidiasis. In this study, the incidence of Candida spp. in the saliva of controlled and uncontrolled diabetic patients were determined and compared with non diabetic group. Material and method: The sample consists of 200 subjects: 100 diabetic patients [57 (28.5%) uncontrolled diabetes, 43 (21.5%) controlled diabetes] and 100 (50%) non diabetic groups. Saliva samples was obtained from the subjects and cultured on selective media using appropriate microbiological method to observe the presence of Candida spp. Results: The results revealed a significant associat

0

Is in this research review of the way minimum absolute deviations values ​​based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values ​​proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.

this research aims at a number of objectives including Developing the tax examination process and raise its efficiency without relying on comprehensive examination method using some statistical methods in the tax examination and Discussing the most important concepts related to the statistical methods used in the tax examination and showing its importance and how they are applied. the research represents an applied study in the General Commission of taxes. In order to achieve its objectives the research has used in the theoretical side the descriptive approach (analytical), and in the practical side Some statistical methods applied to the sample of the final accounts for the contracting company (limited) and the pharmaceutical industry (

Background: Bone defect healing is a multidimensional procedure with an overlapping timeline that involves the regeneration of bone tissue. Due to bone's ability to regenerate, the vast majority of bone abnormalities can be restored intuitively under the right physiological conditions. The goal of this study is to examine the immunohistochemistry of bone sialoprotein in order to determine the effect of local application of bone sialoprotein on the healing of a rat tibia generated bone defect. Materials and Methods: In this experiment, 48 albino male rats weighing 300-400 grams and aged 6-8 months will be employed under controlled temperature, drinking, and food consumption settings. The animals will be subjected to a surgical procedure o

The aim of this study is to utilize the behavior of a mathematical model consisting of three-species with Lotka Volterra functional response with incorporating of fear and hunting cooperation factors with both juvenile and adult predators. The existence of equilibrium points of the system was discussed the conditions with variables. The behavior of model referred by local stability in nearness of any an equilibrium point and the conditions for the method of approximating the solution has been studied locally. We define a suitable Lyapunov function that covers every element of the nonlinear system and illustrate that it works. The effect of the death factor was observed in some periods, leading to non-stability. To confirm the theore

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise