Physiological status and litter size can indeed have a significant impact on ewes' ‎hematological parameters, which are essential indicators of their health. Therefore, this study ‎examined the hematological profiles of ewes during pregnancy with single and twins in the ‎Awassi ewes. The present study involved 232 ewes in good health and at sexual maturity. ‎Among them, 123 ewes had single pregnancies, while 109 ewes had twin pregnancies. The age ‎range of the ewes included in the study was between 3.5 and 4.5 years. Hematological tests ‎were conducted on the sheep's blood samples promptly following collection. The findings ‎demonstrated variations in hematological parameters among pregnant

Mercifulness is a trait of civilization, humanity, and a moral value in society, because it has an impact on social life and its role in spreading interdependence, joint liability, and solidarity among people. Mercifulness means spreading mercy, synergy, sympathy, and cooperation. Generally, a society that enjoys strong ties tends to have a kind of stability and development, as well as, is able to face the economic, political, and security crises. Conversely, a weak society leads to weak social cohesion and weak community infrastructure that is more vulnerable to social, economic, and political instability. Thus, this is the aim of the research that has used a social survey method applied to a sample of respondents who have reached (300)

KE Sharquie, AA Noaimi, MS Abass, American Journal of Dermatology and Venereology, 2019 - Cited by 4

In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

   Lithology identification plays a crucial role in reservoir characteristics, as it directly influences petrophysical evaluations and informs decisions on permeable zone detection, hydrocarbon reserve estimation, and production optimization. This paper aims to identify lithology and minerals composition within the Mishrif Formation of the Ratawi Oilfield using well log data from five open hole logs of wells RT-2, RT-4, RT-5, RT-6, and RT-42. At this step, the logging lithology identification tasks often involve constructing a lithology identification model based on the assumption that the log data are interconnected. Lithology and minerals were identified using three empirical methods: Neutron-Density cross plots for lithology id

Abstract

This research  aims to reform the Iraqi public budget through going into the challenges the budget faces in applying item-line budget in its preparation, implementation and control; which encourage extravagance and waste instead of rationalizing expenditures. This  is shown in the data analysis of Federal public budget laws in Iraq for the years from 2005 till 2013; there was a continuous increase in the aggregate public expenditures in the public budget for the years previously mentioned, as the public expenditures growth has reached into the percent 284.71% in 2013. In addition the public budget for these years (2005-2013) is being prepared with planned deficit without confirming that

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

To perform a secure evaluation of Indoor Design data, the research introduces a Cyber-Neutrosophic Model, which utilizes AES-256 encryption, Role-Based Access Control, and real-time anomaly detection. It measures the percentage of unpredictability, insecurity, and variance present within model features. Also, it provides reliable data security. Similar features have been identified between the final results of the study, corresponding to the Cyber-Neutrosophic Model analysis, and the cybersecurity layer helped mitigate attacks. It is worth noting that Anomaly Detection successfully achieved response times of less than 2.5 seconds, demonstrating that the model can maintain its integrity while providing privacy. Using neutrosophic sim