The aim of this investigation is to study the rote of alkaline phosphatase in mammogenesis and lactogenesis. A total of fortyfemalealbino rats were used and divided according to their physiological states into four groups [ten rats each]. From each deeply ether anesthetized rat, the mammary gland was removed, fixed, quenched in liquid nitrogen and sectioned using SLEE cryostat. The sections were employed for routine haematoxylin and eosin stain and alkaline phosphatase demonstration using the calcium–cobalt method. The obvious finding in the mammary glands of pregnant rat was the presence of thick black rings indicating strong alkaline phosphatase activityaround the basal part of the secretory epithelium of the alveoli. In lactating mamma

Purpose: Studying the activity of acid phosphatase, which is the marker of lysosomal activity in the mammary glands of rats at different stages of the physiological maturation [virgih, pregnancy, lactation and Post lactation] Methods: Forty, female, albino rats were used in this study. They were divided into four groups according to their physiological states [virgin, pregnancy, lactation and post lactation]. The mammary glands, after suitable fixation and sectioning, were employed for routine haematoxylin and eosin stain and for acid phosphatase demonstration Results: Acid phosphatase activity was weakly diffuse in the secretory tubules of virgin rats, the diffuse and granular activity of this enzyme was increased during pregnancy in the s

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

Electrochemical machining is one of the widely used non-conventional machining processes to machine complex and difficult shapes for electrically conducting materials, such as super alloys, Ti-alloys, alloy steel, tool steel and stainless steel.  Use of optimal ECM process conditions can significantly reduce the ECM operating, tooling, and maintenance cost and can produce components with higher accuracy. This paper studies the effect of process parameters on surface roughness (Ra) and material removal rate (MRR), and the optimization of process conditions in ECM. Experiments were conducted based on Taguchi’s L9 orthogonal array (OA) with three process parameters viz. current, electrolyte concentration, and inter-electrode gap. Sig

Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predi

Background: This study aimed to use the combined mesio-distal crowns widths of maxillary incisors and first molars as predictors to the combined mesio-distal crowns widths of maxillary and mandibular canines and premolars. Materials and methods: The sample included 110 Iraqi Arab subjects with an age ranged between 17-25 years and class I skeletal and dental relations. The crown widths of maxillary teeth and mandibular canines and premolars were measured at the largest mesio-distal dimension on the study casts using digital electronic caliper with 0.01 mm sensitivity. Pearson’s correlation coefficient was used to determine the relation between the combined mesio-distal crowns widths of maxillary incisors and first molars and the combined

Eugenol is found in essential oils of many plants. It belongs to a class of naturally occurring phenolic monoterpenoids, chemically it is an allyl chain-substituted guaiacol. A study was conducted on the compound of Eugenol, which included different studies. The first study was the determination of eugenol in body fluid, which includes serum, saliva and urine has been found the highest concentration was in urine then serum and saliva. The second study was the hematological study. Complete blood count was accomplished on the volunteers alredy administrated with eugenol contained mouthwash the analysis was accomplished before and after the mouth wash use. The result observed a slightly negative results and was not that significant, wh

There is substantial data supporting the importance of both endogenous and exogenous estrogen in maintaining reproductive health and preventing chronic disease, androgens in women's health are rarely discussed. This is one of the first researches to investigate correlates of blood testosterone concentrations in women with osteopenia, in anticipation of the growing interest in the role of androgens in women's health. A 65 volunteer women were enrolled in the current study, they were divided into two groups, 35 postmenopausal women with osteopenia were in the first group, and the second group contained 30 postmenopausal women without osteopenia as a control. Blood samples were collected from all participants and analyzed for testosterone l