The class of quasi semi -convex functions and pseudo semi -convex functions are presented in this paper by combining the class of -convex functions with the class of quasi semi -convex functions and pseudo semi -convex functions, respectively. Various non-trivial examples are introduced to illustrate the new functions and show their relationships with -convex functions recently introduced in the literature. Different general properties and characteristics of this class of functions are established. In addition, some optimality properties of generalized non-linear optimization problems are discussed. In this generalized optimization problems, we used, as the objective function, quasi semi -convex (respectively, strictly quasi semi -convex

With the increasing prevalence of breast cancer among female internationally, occupies about 25% of all cases of cancer, with a measured 1.57 million up to date cases in 2012. Breast cancer has turn a most warning to health of female in Iraq, where it is the major cause of death among women after cardiovascular diseases, with a mortality rate of 23% related cancer. Recently there is a crucial requirement to include community pharmacists in health elevation activities to support awareness and early diagnosis of cancer, specially breast cancer. The aim of this study is to assess knowledge, attitude and perceived barriers amongst Iraqi community pharmacists towards health promotion of breast cancer. This study is cross sectional research. A

Left ventricular hypertrophy (LVH) caused by high blood pressure is linked to increased mortality and arrhythmia risk. This study aimed to evaluate arrhythmia in hypertensive patients due to left ventricular hypertrophy (LVH). A cross-sectional study was performed, assessing participants' blood pressure, echocardiography and electrocardiography, and Holter monitoring in certain cases. There were 300 hypertensive patients >18 years attending the cardiology unit of Baghdad medical city. The study was conducted between January–June 2022. The electrocardiograms at rest for 300 adults with hypertension were investigated. 130 (43.5%) were females, and 170 (56.5%) were males. The mean age of participants was 58 years. Forty-nine (16.3

Background: Myocardial infarction (MI) is distinguished by the necrosis of myocardial cells as a result of substantial and prolonged ischemia. Anxiety, problems sleeping, and feelings of depression are some of the most common psychosocial consequences of having a myocardial infarction. Aim: The purpose of this study is to evaluate the effects of post-myocardial infarction on patients' levels of anxiety, depression, and quality of sleep. Method: The collection of data from 94 individuals with MI was carried out according to a descriptive cross-sectional design. Sleep quality, depression, and anxiety were evaluated using standard questionnaires. Results: 69.1% of the participants reported having trouble getting quality sleep. The perc

It is recognized that organisms live and interact in groups, exposing them to various elements like disease, fear, hunting cooperation, and others. As a result, in this paper, we adopted the construction of a mathematical model that describes the interaction of the prey with the predator when there is an infectious disease, as well as the predator community's characteristic of cooperation in hunting, which generates great fear in the prey community. Furthermore, the presence of an incubation period for the disease provides a delay in disease transmission from diseased predators to healthy predators. This research aims to examine the proposed mathematical model's solution behavior to better understand these elements' impact on an eco-epidemi

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr