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Arsenic Detection Using Surface Plasmon Resonance Sensor With Hydrous Ferric Oxide Layer
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Abstract<p>The lethality of inorganic arsenic (As) and the threat it poses have made the development of efficient As detection systems a vital necessity. This research work demonstrates a sensing layer made of hydrous ferric oxide (Fe<sub>2</sub>H<sub>2</sub>O<sub>4</sub>) to detect As(III) and As(V) ions in a surface plasmon resonance system. The sensor conceptualizes on the strength of Fe<sub>2</sub>H<sub>2</sub>O<sub>4</sub> to absorb As ions and the interaction of plasmon resonance towards the changes occurring on the sensing layer. Detection sensitivity values for As(III) and As(V) were 1.083 °·ppb<sup>−1</sup> and 0.922 °·ppb<sup>−1</sup>, respectively, while the limit of detection for both ions was 0.6 ppb. These findings support the feasibility and potential of the sensor configuration towards paving future advancement in As detection systems.</p>
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Publication Date
Sun Nov 01 2020
Journal Name
2020 2nd Annual International Conference On Information And Sciences (aicis)
An Enhanced Multi-Objective Evolutionary Algorithm with Decomposition for Signed Community Detection Problem
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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
An Evolutionary Algorithm with Gene Ontology-Aware Crossover Operator for Protein Complex Detection
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     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

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Publication Date
Tue Aug 15 2023
Journal Name
Al-academy
Effect of partial substitution of alkaline oxides with lithium oxide (Li2O) on low-temperature ceramic glaze
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The research aims to study the effect of adding (Li2O) to an alkaline glaze containing (K2O, Na2O). Although all the alkaline oxides have common properties, each oxide has something that distinguishes it. The molecular weight of (Li2O) is two times less than that of (Na2O) and three times that of (K2O). Therefore, it is added in small proportions. In addition, it is a very strong flux, so it is not used alone, but rather replaces a part of other alkaline oxides. It was added to an alkali glass that matured at a temperature of 980CO in proportions (2.0,1.4,1.2,0.8,0.4%) instead of (Na2O), using lithium carbonate (Li2CO3) as an oxide source. The glazes mixtures were applied to a white pottery body, and the samples were fired and cooled acc

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Publication Date
Tue Sep 01 2020
Journal Name
Ceramics International
High-performance (K,Na)NbO3-based binary lead-free piezoelectric ceramics modified with acceptor metal oxide
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Publication Date
Sat Oct 10 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Histomorphometric analysis of bone deposition at Ti implant surface dip-coated with hydroxyapatite (In vivo study)
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Background: Synthetic hydroxyapatite,(Ca10(PO4)6(OH2) can directly bond to bones without infection and fibrous encapsulation, thus is regarded as bioactive and biocompatible. The aim of the study was the estimation of microarchitecture bone parameters include bone mass (gm/cm2) cortical bone width (mm), thread width (mm), marrow space star volume analysis (V*m) and osteoblast, osteocyte cell number. Materials and methods: Ninety-six (96) commercially pure titanium CpTi) used in this study, (48) implants were coated with HA by dipping coating and (48) implants were used as control. They were inserted in (32) Newzland white rabbits and followed for 2 & 6 weeks. Mechanical torque removal test and histomorphometric analysis of bone microarchit

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Publication Date
Thu Jan 07 2021
Journal Name
Indian Journal Of Forensic Medicine &amp; Toxicology
Effect of Dentifrices with Different Abrasives on the Surface Roughness of a Nano Composite Resins materials
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Background: to evaluate the effect of different dentifrices on the surface roughness of two composite resins (nanofilled-based and nanoceramic – based composite resins). Materials and methods: Forty specimens (diameter 12 mm and height of 2mm) prepared from different composite resin materials: Z350 (nanofilled composite, and Ceram-X (nanoceramic) .they were subjected to brushing simulation equivalent to the period of 1 year. The groups assessed were a control group brushed with distilled water (G1), Opalescence whitening toothpasteR (G2), Colgate sensitive pro-relief (G3) and Biomed Charcoal Toothpaste (G4). The initial and final roughness of each group was tested by surface roughness tester. The results were statistically analyzed using

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Ecological Engineering
Chromium Ions Removal by Capacitive Deionization Process – Optimization of the Operating Parameters with Response Surface Methodology
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An innovative desalination method called electrosorption or capacitive deionization (CDI) has significant benefits for wastewater treatment. This process is performed by using a carbon fiber electrode as a working electrode to remove hexavalent chromium ions from an aqueous solution. The pH, NaCl concentration, and cell voltage were optimized using the Box-Behnken experimental design (BDD) in response surface methodology (RSM) to study the effects and interactions of selected variables. To attain the relationship between the process variables and chromium removal, the experimental data were subjected to an analysis of variance and fitted with a quadratic model. The optimum conditions to remove Cr(VI) ions were: pH of 2, a cell voltage of 4.

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Publication Date
Sun Jan 14 2018
Journal Name
Journal Of Engineering
The effect of Laser Shock Peening on Fatigue Life Using Pure Water and Hydrofluoric Acid As a Confining Layer of Al – Alloy 7075-T6
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Laser shock peening (LSP) is deemed as a deep-rooted technology for stimulating compressive residual stresses below the surface of metallic elements. As a result, fatigue lifespan is improved, and the substance properties become further resistant to wear and corrosion. The LSP provides more unfailing surface treatment and a potential decrease in microstructural damage. Laser shock peening is a well-organized method measured up to the mechanical shoot peening. This kind of surface handling can be fulfilled via an intense laser pulse focused on a substantial surface in extremely shorter intervals. In this work, Hydrofluoric Acid (HF) and pure water as a coating layer were utilized as a new technique to improve the properti

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Publication Date
Tue Jan 05 2016
Journal Name
Iraqi Journal Of Science
Local Study of blaCTX-M genes detection in Proteus spp. by using PCR technique
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n this study, 25 clinical isolates of Proteus spp. were collected from urine, wounds and burns specimens from different hospitals in Baghdad city, all isolates were identified by using different bacteriological media, biochemical assays and Vitek-2 system. It was found that 15 (60%) isolates were identifies as Proteus mirabilis and 10 (40 %) isolates were Proteus vulgaris. The susceptibility of P. mirabilis and P. vulgaris isolates towards cefotaxime was (66.6 %) and (44.4 %) respectively; while the susceptibility of P. mirabilis and P. vulgaris isolates towards ceftazidime was (20%). Extended spectrum β-lactamses producing Proteus was (30.7 %). DNA of 10 isolates of P. mirabilis and 4 isolates of P. vulgaris were extracted and de

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Publication Date
Sat Oct 04 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced IOT Cyber-Attack Detection Using Grey Wolf Optimized Feature Selection and Adaptive SMOTE
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The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

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