Contents IJPAM: Volume 116, No. 3 (2017)

Arthropod-borne infections, known as vector-borne diseases, are a significant threat to both humans and animals. These diseases are transmitted to humans and animals through the bites of infected arthropods. In the last half century, there have been a number of unexpected viral outbreaks in Middle Eastern countries. Recently, Iraq has witnessed an outbreak of the Crimean-Congo Hemorrhagic Fever virus with high morbidity and mortality rates in humans. However, very little is known about the prevalence and distribution of CCHFV in Iraq, and therefore, it is impossible to quantify the risk of infection. CCHFV is transmitted to humans through the bite of infected ticks. However, transmission can also occur through contact with the blood or ti

Objective: The goal of this research was to evaluate where selenium nanoparticles impact the activity of antibodies in immunized lambs with foot and mouth vaccines by modulating the immune system. Materials and Methods: Two groups of lambs of 3–4 months of age were injected with 1 ml of ARRIAH-VAC vaccine intramuscularly in the neck, five Lambs were given selenium nanoparticles (size 100 nm) oral administration of selenium nano dose of 0.1 mg/kg of body mass once every day for sixty days considered as group one (G1) while the other five used as control Group 2 (G2). Results: This resulted in the establishment of an immune response, as evidenced by a rise in antibody titer in the blood using the ELISA test for three serotypes A,

A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

One of the most common metabolic illnesses in the world is diabetes mellitus. This metabolic disease is responsible for a large percentage of the burden of kidney damage and dysfunction. The goal of this study was to look into the renal function of diabetic patients using metformin monotherapy who came to Mosul's Al-Wafaa diabetes care and research facility. During the period 1 January 2021 to 30 April 2021, 47 patients with T2DM (age 50.48 7.74 years) were enrolled in this case-control study. These patients' results were compared to a control group of 47 seemingly healthy people (age 45.89 9.06 years). All participants' demographic and medical histories were acquired through the delivery of a questionnaire. Blood samples were collected