Ankylosing spondylitis is a complex debilitating disease because its pathogenesis is not clear. This study aims at detecting some pathogenesis factors that lead to induce the disease. Chlamydia pneumoniae is one of these pathogenesis factors which acts as a triggering factor for the disease. The study groups included forty Iraqi Ankylosing spondylitis patients and forty healthy persons as a control group. Immunological and molecular examinations were done to detect Chlamydia. pneumoniae in AS group. The immunological results were performed by Enzyme-Linked Immunosorbent Assay (ELISA) to detect anti-IgG and anti-IgM antibodies of C. pneumoniae revealed that five of forty AS patients' samples (12.5%) were positive for anti-IgG and IgM C. pneumoniae antibodies compared to controls which revealed seronegative. Molecular detection included 16srRNA and HSP-70 genes were to ensure the serological examination for detection of bacteria in the five blood samples which were positive; therefore, these results improved that C. pneumoniae played a role in the pathogenesis of the disease
Introduction: Selenium is an essential trace element involved in different physiological functions of the human body. An inverse relationship between serum selenium levels and cervical intraepithelial neoplasia has been reported. cervical intraepithelial neoplasia is regarded as a potentially premalignant transformation of squamous cells of the cervix. Objectives: To evaluate the relationship between the serum level of selenium and cervical intraepithelial neoplasia. Methods: A case-control study was conducted at Baghdad Teaching Hospital and Iraqi National Cancer Research Center in the University of Baghdad during the period from July 2021 to July 2022. A convenient sample of 100 women was enrolled in the current study and included
... Show MoreObjective; swine flu is known to be caused by influenza A subtypes H1N1,H1N2, H2N3, H3N1, and H3N2, was first proposed to be a disease related to human flu during the 1918 flu pandemic, Iraq face the epidemic of 2009, many patients admitted to the medical word of alkindy teaching hospital, the clinical features were observed and managed according to WHO protocols.
The aim of the study; is to asses some features of morbidity and mortality of swine flu epidemic admitted patients in 2009 in alkindy teaching hospital.
Methods; A total 131 patients with suspected influenza
admitted to Alkindy Teaching Hospital all complain of
fever more than 38c, sore throat with or without cough.
The admitted patients are of two main
groups
Objective; swine flu is known to be caused by influenza A subtypes H1N1,H1N2, H2N3, H3N1, and H3N2, was first proposed to be a disease related to human flu during the 1918 flu pandemic, Iraq face the epidemic of 2009, many patients admitted to the medical word of alkindy teaching hospital, the clinical features were observed and managed according to WHO protocols.
The aim of the study; is to asses some features of morbidity and mortality of swine flu epidemic admitted patients in 2009 in alkindy teaching hospital.
Methods; A total 131 patients with suspected influenza
admitted to Alkindy Teaching Hospital all complain of
fever more than 38c, sore throat with or without cough.
The admitted patients are of two main
groups
The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t
Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show More<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynami
... Show MoreA nano-sensor for nitrotyrosine (NT) molecule was found by studying the interactions of NT molecule with new B24N24 nanocages. It was calculated using density functionals in this case. The predicted adsorption mechanisms included physical and chemical adsorption with the adsorption energy of −2.76 to −4.60 and −11.28 to −15.65 kcal mol−1, respectively. The findings show that an NT molecule greatly increases the electrical conductivity of a nanocage by creating electronic noise. Moreover, NT adsorption in the most stable complexes significantly affects the Fermi level and the work function. This means the B24N24 nanocage can detect NT as a Φ–type sensor. The recovery time was determined to be 0.3 s. The sensitivity of pure BN na
... Show MoreThis study included the isolation and identification of Aspergillus flavus isolates associated with imported American rice grains and local corn grains which collected from local markets, using UV light with 365 nm wave length and different media (PDA, YEA, COA, and CDA ). One hundred and seven fungal isolates were identified in rice and 147 isolates in corn.4 genera and 7 species were associated with grains, the genera were Aspergillus ,Fusarium ,Neurospora ,Penicillium . Aspergillus was dominant with occurrence of 0.47% and frequency of 11.75% in rice grains whereas in corn grains the genus Neurospora was dominant with occurrence of 1.09% and frequency 27.25% ,results revealed that 20 isolates out of 50 A. flavus isolates were able
... Show More