This paper reports a fiber Bragg grating (FBG) as a biosensor. The FBGs were etched using a chemical agent,namely,hydrofluoric acid (HF). This implies the removal of some part of the cladding layer. Consequently, the evanescent field propagating out of the core will be closer to the environment and become more sensitive to the change in the surrounding. The proposed FBG sensor was utilized to detect toxic heavy metal ions aqueous medium namely, copper ions (Cu2+). Two FBG sensors were etched with 20 and 40 μm diameters and fabricated. The sensors were studied towards Cu2+ with different concentrations using wavelength shift as a result of the interaction between the evanescent field and copper ions. The FBG sensors showed

In accordance with epidemic COVID-19, the elevated infection rates, disinfectant overuse and antibiotic misuse what led to immune suppression in most of the population in addition to genotypic and phenotypic alterations in the microorganisms, so a great need to reevaluate the genetic determinants that responsible for bacterial community (biofilm) has been raised. A total of 250 clinical specimens were obtained from patients in Baghdad hospitals and streaked on Mannitol salt agar medium. The results revealed that 156 isolates appeared as round yellow colonies, indicating that they were mostly identified as Staphylococcus aureus from 250 specimens. The antibiotic resistance pattern of the isolates for methicillin 37.17% (n=58), Amoxic

Breast cancer is one of the most common cancers in females. In Iraq there are noticeable elevation in incidence rates and prevalence of advanced stages of breast cancer. Ferritin is intracellular iron storage protein abundant in circulation and its main application in differential diagnosis of anemia.

The level of serum ferritin was found raised in various cancers including breast cancer. The aim of this study was to assess whether the serum ferritin concentration would be altered in Iraqi women with breast cancer and it could be related to progression of disease.

Sixty eight females participated in this study. The mean age of these females was 53.25± 9.52 .The level of serum ferritin was measured in 24

Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from

Background:SARS-CoV-2 infection has caused a global pandemic that continues to negatively impact human health. A large group of microbial domains including bacteria co-evolved and interacted in complex molecular pathogenesis along with SARS-CoV-2. Evidence suggests that periodontal disease bacteria are involved in COVID-19, and are associated with chronic inflammatory systemic diseases. This study was performed to investigate the association between bacterial loads of Porphyromonas gingivalis and pathogenesis of SARS-CoV-2 infection. Fifty patients with confirmed COVID-19 by reverse transcriptase-polymerase chain reaction, their age ranges between 20-76 years, and 35 healthy volunteers (matched accordingly with age and sex to th

Tuberculosis status as the second leading causes of significant morbidity and mortality from an infectious disease worldwide, after human immunodeficiency virus (HIV). Sample collection was conducted at the Institute of Chest and Respiratory Diseases/Baghdad Medical City in Baghdad. The collection interval was from August to October 2014, 629 suspected TB patients were examined during this period. The results revealed among total 629 specimens, 56 (8.9%) of the specimens were positive by direct examination and 573 (91.1%) negative specimens by smear microscopy. Fifty six DNA samples were extracted from positive ZN smears of sputum specimens and 40 samples from healthy persons (as control) were subjected to molecular diagnosis by real tim

Background: Hyperlipidemia is an elevated fat (lipids), mostly cholesterol and triglycerides, in the blood. These lipids usually bind to proteins to remain circulated so-called lipoprotein. Aims of the study: To determine taste detection threshold and estimate the trace elements (zinc) in serum and saliva of those patients and compare all of these with healthy control subjects. Methods: Eighty subjects were incorporated in this study, thy were divided into two groups: forty patients on simvastatin treatment age between (35-60) years, and forty healthy control of age range between (35-60) years. Saliva was collected by non-stimulated technique within 10 minutes. Serum was obtained from each subject. Zinc was estimated in serum and saliva