Background: Oxidative stress may contribute to the etiology of hypertension in humans. Oxidative stress is an imbalance between reactive oxygen species (ROS) and antioxidant defense mechanisms, causing damage to biological macromolecules and dysregulation of normal metabolism and physiology. Amlodipine as an antihypertensive agent is a long-acting calcium channel blocker that dilates blood vessels and improves blood flow. The aim of this study was to assess the oxidative stress in hypertensive patients on Amlodipine treatment through the assessment of salivary Malondialdehyde (MDA) and superoxide dismutase (SOD) as a marker of oxidative stress.

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In this paper, preliminary test Shrinkage estimator have been considered for estimating the shape parameter α of pareto distribution when the scale parameter equal to the smallest loss and when a prior estimate α0 of α is available as initial value from the past experiences or from quaintance cases. The proposed estimator is shown to have a smaller mean squared error in a region around α0 when comparison with usual and existing estimators.

Leishmaniasis is a widespread parasitic disease caused by Leishmania parasite, this disease considers a major health problem among worldwide. Treatments available are expensive or with cytotoxic side effect. This study was aimed to investigate the effect of an herbal new compound, called artemisinin, derived from a Chinese plant called Artemisia annua. Various concentrations were studied in vitro against L. tropica amastigotes by chamber counting to investigate its effect on the proliferation of promastigotes. Three incubation periods were adopted (24, 48, 72) hours. The results showed a significant decrease in surviving promastigotes, in parallel with the normal parasite count of untreated promastigotes, along the periods studied. This stu

The efforts in designing and developing lightweight cryptography (LWC) started a decade ago. Many scholarly studies in literature report the enhancement of conventional cryptographic algorithms and the development of new algorithms. This significant number of studies resulted in the rise of many review studies on LWC in IoT. Due to the vast number of review studies on LWC in IoT, it is not known what the studies cover and how extensive the review studies are. Therefore, this article aimed to bridge the gap in the review studies by conducting a systematic scoping study. It analyzed the existing review articles on LWC in IoT to discover the extensiveness of the reviews and the topics covered. The results of the study suggested that many re

Leishmaniasis is a widespread parasitic disease caused by Leishmania parasite, this disease considers a major health problem among worldwide. Treatments available are expensive or with cytotoxic side effect. This study was aimed to investigate the effect of an herbal new compound, called artemisinin, derived from a Chinese plant called Artemisia annua. Various concentrations were studied in vitro against L. tropica amastigotes by chamber counting to investigate its effect on the proliferation of promastigotes. Three incubation periods were adopted (24, 48, 72) hours. The results showed a significant decrease in surviving promastigotes, in parallel with the normal parasite count of untreated promastigotes, along the periods studied. Th

Dust samples have been collected from three areas in Baghdad during dust storm occurred in 18th of June 2009 to characterize elemental particle size and composition by different techniques. The x-ray diffraction detected six minerals those are calcite, and quartz, present as a major components, dolomite, kaolinite, gypsum and plagioclase present as miner components .EDX detected some normal elements presented in local soil except traces of lead , nickel, and chromium. The particle size analysis by a set of sieves have revealed that the majority particle distribution was between (32 and 45)μm . To isolate the aerosol size, PM10 buoyancy method of powder in water showed a signifying amounts of particulate size .Scheerer’s method was app

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