The research illustrated that the theory of constraints is   "A group of concepts and basics that aim at helping the management in order to determine the difficulties and how to overcome these difficulties through determining the necessary change and how these change can be done efficiently and effectively ".

       The research showed that the theory of constraint including its tools calls for magnifying throughput, constricting the product cycle , determining  the optimal production mix , utilization of scare resources and canceling the idle time , that achieving  throughput  increasing  then  increasing  profit .

      Moreov

This study deals with knowing the types of research in public relations studies at the Faculty of Mass Communication for the period from 1989 to 2007 and knowing the methods that researchers used in their studies, as well as knowing the methods and tools of scientific research that were used, and whether one method or tool is used more than others, and knowing Samples used in the analysis. As well as the contents and types of this research The institutions that were subjected to the study, and the preparation of the respondents This research aims to answer the following questions:. A- What are the types of research and methods that were used in university theses that dealt with the topic? Public Relations at the Faculty of Media from 1989

The objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <

Purpose: Current denture liner materials suffer from low tear strength, poor abrasion resistance, weak bond strength to denture material, and increasing risk of denture stomatitis due to adherence. The aim of this study was to evaluate the effects of the addition of cellulose nanofibers (CNFs) to commercial soft denture liner material on the adherence of and physical and mechanical properties. Materials and Methods: CNFs at concentrations of 0.0, 0.5, and 1.0 wt.% were incorporated into a soft liner material. Antifungal effects were assessed by quantifying the adherence of . The Shore A hardness, tensile strength, peel bond strength, and surface roughness tests were employed to assess the properties of the denture liner materials. Chemica

High-sensitive cardiac troponin I (hs-cTnI) is a recognized marker of myocardial injury in acute coronary syndromes, but its utility in chronic coronary syndromes (CCS) remains unclear. Midkine (MK), a heparin-binding growth factor, plays a role in inflammation and vascular remodeling in atherosclerosis. This cross-sectional study aimed to evaluate the predictive value of serum hs-cTnI and MK in determining the severity of coronary artery obstruction in patients with CCS. The study included 125 subjects undergoing coronary angiography (CAG) at the Iraqi Center of Heart Disease/ Medical City/Baghdad, from March to December 2024. Subjects were classified into three groups based on CAG findings: no CAD, 1- or 2-vessel disease, and 3-ve

Periodontitis is a chronic inflammatory disease initiated by dysbiotic biofilms and sustained by an altered host response, resulting in progressive destruction of the tooth-supporting tissues. Alongside immune-mediated damage, epithelial–mesenchymal transition has been proposed as a contributing mechanism in gingival barrier disruption and periodontal tissue remodeling. This narrative review examines the roles of the EMT-related transcription factors Snail1 and Twist1 in periodontitis, with particular focus on their involvement in epithelial junction loss, mesenchymal activation, and disease-associated tissue change. Relevant literature was identified through targeted searches of PubMed/MEDLINE and Google Scholar using terms relat

Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne