The present study aimed to investigate the histological changes of heart, lung, liver and kidney which caused by different concentrations (10, 20 and 40 mg/kg) of Ivabradine. Results of the study revealed some histological changes represented by aggregation of the lymphocytes around respiratory bronchioles of the lung. In the liver, the drug caused hepatocyte necrosis and infiltration of the lymphocytes. In Kidney, there are no histopathological modifications in the tissue after the animals treated with 10 mg\kg of Ivabradine. When the animals treated with Ivabradine drug at 20mg/kg of bw, dose showed vascular congestion between myocardial fibers of heart. Emphysematous c

Breast cancer is the most commonly diagnosed cancer and remains one of the main reasons of cancer-related mortality in women worldwide. KRAS variant rs61764370 (T>G) is associated with an increased risk of occurrence of many cancers, Here The case-control study was accomplished on 135 women including 45 women with breast cancer patients, 45 women with benign breast lesions and 45 healthy women to analyze the association of KRAS variant rs (61764370 T>G) with breast cancer. LCS 6 variant in KRAS gene was amplified by using specific primers, then genotype was detected after sequencing the PCR products. The results showed that the genotype and allele frequency of TT and GT allele of  KRAS

A Ligand (ECA) methyl 2-((1-cyano-2-ethoxy-2-oxoethyl)diazenyl)benzoate with metals of (Co²⁺, Ni²⁺, Cu²⁺) were prepared and characterization using H-NMR, atomic absorption spectroscopy, ultra violet (UV) visible, magnetic moments measurements, bioactivity, and Molar conductivity measurements in soluble ethanol. Complexes have been prepared using a general formula which was suggested as [M (ECA)₂] Cl₂, where M = (Cobalt(II), Nickel(II) and Copper(II), the geometry shape of the complexes is octahedral.

The individual average income is considered one of the most used criteria for the distinguishing between the developed and the developing countries, for this reason the efforts of economic development has been construed on increasing the average national income, the investment expenditures is considered one of the basic foundations for economic development operation which lead to the expanding the prodection power of the economy, and increasing the level of national income in an averages greaten than the primary expenditures due to the work and interaction between the multiplier and the accelerator. But the ability of the economic sectors in the generation of national income as a result of the primary expenditures is different fr

The estimation of the parameters of Two Parameters Gamma Distribution in case of missing data has been made by using two important methods: the Maximum Likelihood Method and the Shrinkage Method. The former one consists of three methods to solve the MLE non-linear equation by which the estimators of the maximum likelihood can be obtained: Newton-Raphson, Thom and Sinha methods. Thom and Sinha methods are developed by the researcher to be suitable in case of missing data. Furthermore, the Bowman, Shenton and Lam Method, which depends on the Three Parameters Gamma Distribution to get the maximum likelihood estimators, has been developed. A comparison has been made between the methods in the experimental aspect to find the best meth

The purpose of this work was to study the effects of the Nd:YAG laser on exposed dentinal
tubules of human extracted teeth using a scanning electron microscope (SEM). Eighty 2.5mm-thick
slices were cut at the cementoenamel junction from 20 extracted human teeth with an electric saw. A
diamond bur was used to remove the cementum layer to expose the dentinal tubules. Each slice was
sectioned into four equal quadrants and the specimens were randomly divided into four groups (A to D ).
Groups B to D were lased for 2 mins using an Nd:YAG laser at 6 pulses per second at energy outputs of
80 , 100 and 120 mJ. Group A served as control. Under SEM observation, nonlased specimens showed
numerous exposed dentinal tubules. SEM o

This research work involves the preparation of nano activated carbonand macro activated carbon from corn seeds with a various mixing ratio ofpotassium hydroxide (1:0, 1:0.2, 1:0.4, 1:0.6, 1:0.8 and 1:1) % using thermaland micro radiation carbonization to identify the best mixing ratio. At studyto confirmed that the efficiency and effectiveness of the prepared of activatedcarbon samples increase when ratio potassium hydroxide increase with athermal and micro radiation carbonization was used. The study of samplesexternal surface area was performed via studying the adsorption of methyleneblue from their aqueous solution, also measured the internal surface area wasperformed via studying the adsorption of iodine from their aqueous solution.Measu

The no parity problem causes determining is the most interesting case by doctors and researchers in this filed, because it helps them to pre-discovering of it, from this point the important of this paper is came, which tries to determine the priority causes and its fluency, thus it helps doctors and researchers to determine the problem and it’s fluency of increase or decrease the active sperm which fluencies of peregrinating. We use the censored regression (Tobit) model to analyze the data that contains 150 observations may by useful to whom it concern.         

Shadow detection and removal is an important task when dealing with color outdoor images. Shadows are generated by a local and relative absence of light. Shadows are, first of all, a local decrease in the amount of light that reaches a surface. Secondly, they are a local change in the amount of light rejected by a surface toward the observer. Most shadow detection and segmentation methods are based on image analysis. However, some factors will affect the detection result due to the complexity of the circumstances. In this paper a method of segmentation test present to detect shadows from an image and a function concept is used to remove the shadow from an image.

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att