Forbidden Suckling Decision in Islamic jurisprudence

BACKGROUND: Many genetic factors are known to be related to osteoporosis, and currently the role of the glucagon-like peptide-1 receptor (GLP-1R) gene in bone health has been studied intensively. Some variation of this gene, such as rs1042044 and rs6458093, are known to be linked to metabolic diseases and lower bone mineral density, however their specific contribution to osteoporosis remains largely unexplored. Therefore, this study was conducted to investigate the combined genotypic effect of rs1042044 and rs6458093 as a genetic risk factor for osteoporosis in postmenopausal Iraqi women.METHODS: Blood samples from 75 osteoporosis patients and 75 healthy controls, aged 45-85, were collected. DNA was extracted, and a region of GLP-1R

Background: Dyslipidemia is defined as an abnormally high level of various lipids in the blood. It is considered a major risk for atherosclerosis and coronary artery disease. Genetic susceptibility can have a significant influence on the development and progression of dyslipidemia. ApoB-100 R3500Q mutation and ApoE variants are among those genetic risks for dyslipidemia. This study aims to assess the possible contribution of ApoB and ApoE variants on lipid profile among a group of early-onset ischemic heart disease (IHD) patients in comparison to a group of controls. Methods: Forty patients with dyslipidemia and early-onset IHD without chronic conditions likely to cause derangement of lipid levels were recruited to this case-control study

The aim of this work is to provide an efficient selection technique as a part of planning process to guide the decision makers to decide the preferences of one supplier over another for purchasing lab instruments in education domain. Fuzzy Analytical Hierarchy Process has used as a multi-criteria decision process, as an industrial engineering tool with certain emphasis on the qualitative aspects required to the decision makers. While the concept of degree of possibility for each criterion is used to reach its relative weights, a specific methodology created to reach the final objective decision of supplier selection. A questionnaire form was developed and distributed to five universities located in Baghdad province with a total

Most of the Internet of Things (IoT), cell phones, and Radio Frequency Identification (RFID) applications need high speed in the execution and processing of data. this is done by reducing, system energy consumption, latency, throughput, and processing time. Thus, it will affect against security of such devices and may be attacked by malicious programs. Lightweight cryptographic algorithms are one of the most ideal methods Securing these IoT applications. Cryptography obfuscates and removes the ability to capture all key information patterns ensures that all data transfers occur Safe, accurate, verified, legal and undeniable.  Fortunately, various lightweight encryption algorithms could be used to increase defense against various at

tock markets changed up and down during time. Some companies’ affect others due to dependency on each other . In this work, the network model of the stock market is discribed as a complete weighted graph. This paper aims to investigate the Iraqi stock markets using graph theory tools. The vertices of this graph correspond to the Iraqi markets companies, and the weights of the edges are set ulrametric distance of minimum spanning tree.

With the high usage of computers and networks in the current time, the amount of security threats is increased. The study of intrusion detection systems (IDS) has received much attention throughout the computer science field. The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection. This paper presents an overview of different intrusion detection systems and a detailed analysis of multiple techniques for these systems, including their advantages and disadvantages. These techniques include artificial neural networks, bio-inspired computing, evolutionary techniques, machine learning, and pattern recognition.

Most Internet-tomography problems such as shared congestion detection depend on network measurements. Usually, such measurements are carried out in multiple locations inside the network and relied on local clocks. These clocks usually skewed with time making these measurements unsynchronized and thereby degrading the performance of most techniques. Recently, shared congestion detection has become an important issue in many computer networked applications such as multimedia streaming and
peer-to-peer file sharing. One of the most powerful techniques that employed in literature is based on Discrete Wavelet Transform (DWT) with cross-correlation operation to determine the state of the congestion. Wavelet transform is used as a de-noisin

Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh