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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 limits as low as 0.357 nM for H₂O₂ detection using ZIF-8-based SERS sensors and picomolar sensitivity for various ROS species. The review systematically examines different MOF structures, including pure MOFs, bimetallic systems, and composite materials, emphasizing their mechanisms through electrochemical, optical, and colorimetric methods. Key biomedical applications include cancer diagnosis, cardiovascular disease monitoring, inflammatory condition assessment, and point-of-care testing. Despite notable progress, challenges such as stability under physiological conditions, biocompatibility, manufacturing reproducibility, and regulatory approval remain for clinical translation. Future directions include developing AI-integrated systems, wearable devices, and theranostic platforms that combine sensing with therapeutic functions.

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Wed Mar 01 2023
Journal Name
Journal Of Photochemistry And Photobiology A: Chemistry
Multipurpose properties the Z-scheme dimanganese copper oxide/cadmium sulfide nanocomposites for photo- or photoelectro-catalytic, antibacterial applications, and thiamine detection process
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Publication Date
Sun Sep 30 2001
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Effect of Velocity and Temperature on Mass Transfer of Oxygen in Corrosion Processes
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Publication Date
Sat Apr 12 2025
Journal Name
Mustansiriyah Journal Of Sports Science
A Review of the Use of Artificial Intelligence Algorithms for Predicting Injuries and Performance in Football Players
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The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p

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Publication Date
Wed Jan 01 2020
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees20
Form factor calculations for some light nuclei in the framework of electron scattering
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Publication Date
Thu Jun 01 2023
Journal Name
Cellular, Molecular And Biomedical Reports
Comprehensive analysis of microRNA (miRNA) in cancer cells
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Publication Date
Tue Aug 23 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Face mask detection based on algorithm YOLOv5s
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Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

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Publication Date
Tue Nov 04 2025
Journal Name
Iraqi Journal Of Science
Intrusion Detection Approach Based on DNA Signature
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Publication Date
Thu Feb 28 2019
Journal Name
Multimedia Tools And Applications
Shot boundary detection based on orthogonal polynomial
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Publication Date
Thu Dec 01 2022
Journal Name
Environmental Nanotechnology Monitoring & Management
Green approach for the synthesis of graphene glass hybrid as a reactive barrier for remediation of groundwater contaminated with lead and tetracycline
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