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Immunological and molecular detection of Helicobacter pylori in patients clinically diagnosed with chronic urticarial and atopic dermatitis
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To determine the relationship between Helicobacter pylori infection and skin disorders, sixty six patients who suffering from skin diseases include chronic urticarial (CU) and atopic dermatitis (AD) who attended at Dermatological Clinic/ Al-Numan Teaching Hospital from the beginning of October 2015 to the end of January 2016 with age (6-62) have been investigated and compared to twenty two samples of apparently healthy individuals were studied as control group. All the studied groups were subjected to measurement of antiHelicobacter pylori IgG antibodies by enzyme linked immuno sorbent assay (ELISA) and detection of 16S rRNA and CagA genes by using singleplex and multiplex PCR methods. The results of current study revealed that there was a highly significant elevation (P<0.01) in concentration of H. pylori IgG antibodies in sera of the CU and AD patients compared with control group, also the results revealed that there was a significant elevation (P<0.05) in concentration of H. pylori IgG antibodies in sera of the CU patients compared with control group, and significant elevation (P<0.05) in concentration of H. pylori IgG antibodies in sera of AD patients compared with control group. The results of present study indicated that 26(66.67%) patients out of 39 CU patients were positive for both of 16S rRNA and CagA genes, while 13(33.33%) patients out of 39 CU patients were negative for those genes. Also, the results revealed that 19(70.37%) patients out of 27 AD patients were positive for both of 16S rRNA and CagA genes, whereas only 8(29.62%) were negative for both those genes comparing with control group which showed 1(4.54%) individuals out of 22 apparently healthy individuals were positive for both 16S rRNA and CagA genes, the statistical analysis was highly significant (P<0.01).

Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach
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Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
Facial deepfake performance evaluation based on three detection tools: MTCNN, Dlib, and MediaPipe
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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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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

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Publication Date
Mon Jan 01 2018
Journal Name
Journal Of Global Pharma Technology
Molecular Investigation of Curli Fimbriae Genes in Enterobacter cloacae Isolated from Various Clinical Sources in Baghdad, Iraq
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Thirteen isolates were collected from various clinical sources during the periodfrom 22/10/2017 to 22/12/2017. All the isolates were diagnosed based on the microscopic and biochemical propertiesby Vitek-2 Compact system. All isolates formed biofilm 100%, with 30% of isolatesbiofilm produced strongly and 70% on medium. The results of the present study have shown the presence of Curli fimbriae genes in E. cloacae bacteria from cases of urinary tract infections, infected patient with blood bacteremia and inflammation of wounds. Curli fimbriae is considered to be an important factor in the virulence of E.cloacae bacteria, which plays an important role in adhering and combining cells on solid surfaces to form the biofilmand helps in the adhesion

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Publication Date
Sun Jan 01 2023
Journal Name
Inorganic Chemistry Communications
Detection of nitrotyrosine (Alzheimer's agent) by B24N24 nano cluster: A comparative DFT and QTAIM insight
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A 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

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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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Publication Date
Sun Feb 01 2026
Journal Name
Agricultural Engineering
DEVELOPMENT AND EVALUATION OF A YOLO ALGORITHM-BASED ROBOTIC SPRAYER FOR REAL-TIME WEED DETECTION
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Abstract<p> Weed control with chemicals is a challenging process that should be performed in a rational way to reduce their negative impact on the surrounding environment. The growth of artificial intelligence algorithms encourages researchers to develop smart spraying robots that detect and spray weeds and distinguish them from the main crop which leads to sustainable use of these chemicals and achieves some of the sustainable development goals. However, few studies are available to comprehensively compare different versions of YOLO algorithm to detect weed. In this research, seven versions of YOLO algorithms were evaluated for their performance to detect and spray four t</p> ... Show More
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Publication Date
Tue Sep 30 2025
Journal Name
Gsc Advanced Research And Reviews
A comprehensive review of metal-organic framework based biosensors for detection of reactive oxygen species and hydrogen peroxide in biomedical applications
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Metal-organic frameworks (MOFs) have emerged as revolutionary materials for developing advanced biosensors, especially for detecting reactive oxygen species (ROS) and hydrogen peroxide (H₂O₂) in biomedical applications. This comprehensive review explores the current state-of-the-art in MOF-based biosensors, covering fundamental principles, design strategies, performance features, and clinical uses. MOFs offer unique benefits, including exceptional porosity (up to 10,400 m²/g), tunable structures, biocompatibility, and natural enzyme-mimicking properties, making them ideal platforms for sensitive and selective detection of ROS and H₂O₂. Recent advances have shown significant improvements in detection capabilities, with limit

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Publication Date
Thu Nov 08 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Macrovascular and microvascular complications in type 2 diabetic Iraqi patients treated by metformin and glibenclamide versus metformin and sitagliptin
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Background: In type 2 diabetes mellitus there is a progressive loss of beta cell function. One new
approach yielding promising results is the use of the orally active dipeptidyl peptidase-4 (DPP-4)
inhibitors for type 2 diabetes mellitus.
Objective: This study aims at comparing the possible occurrence of macrovascular & microvascular
complications in Iraqis patients with type 2 diabetes mellitus using two combinations of drugs
metformin + glibenclamide and metformin + sitagliptin.
Methodology: Sixty eight T2DM patients and 34 normal healthy individuals as control group were
enrolled in this study and categorized in to two treatment groups. The group 1 (34 patients ) received
metformin 500 mg three times daily

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Levels of Glucose-6-phosphate Dehydrogenase in Type 1 Diabetes Mellitus patients with Nephropathy and Cardiovascular disease complication: Perry H. Saifullah|Saad M. Nida|Israa B. Raoof
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The aim of this study is to evaluate oxidative stress in diabetes mellitus (DM) Type1 by the measurement of Glucose-6-phosphate Dehydrogenase (G-6-PD), an enzyme expressed in human RBCs, is important in the generation of reduced glutathione which is the key product in oxidative stress controls. The Study was carried on 80 samples of blood and serum of National Diabetes Center (NDC). The study groups under fasting conditions and they divided as:20 samples of diabetes mellitus patients without complications and 20 samples of diabetes mellitus with cardiovascular (CV) complications and 20 samples of diabetes mellitus with Nephropathy (Neph) complications compared with 20 control group with average age (13-67) years.. The results sh

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