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Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States
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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Synthesis, Characterization, Antibacterial study and Efficiency of Inhibition of New di-β-enaminone Ligand and its Complexes
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Abstract<p>The new ligand [3,3’-(1,2-phenylenebis(azanediyl))bis(5,5-dimethylcyclohex-2-en-1-one)] (L) derived from 5,5-Dimethylcyclohexane-1,3-dione with 1,2-phenylenediamine was used to prepare a new chain of metal complexes of Mn(ii), Co(ii), Ni(ii), Cu(ii), Cd(ii) and Zn(ii) by inclusive formula [M(L)]Cl2. Characterized compounds on the basis of <sup>1</sup>H, <sup>13</sup>CNMR (for ligand (L)), FT-IR and U.V spectrum, melting point, molar conduct, %C, %H and %N, the percentage of the metal in complexes %M, Magnetic susceptibility, thermal studies (TGA), while its corrosion inhibition for (plain steel) in tap water is studied by weight loss. These measurements proved th</p> ... Show More
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Publication Date
Thu Dec 01 2022
Journal Name
Russian Journal Of Bioorganic Chemistry
Synthesis, Identification and Study of Antioxidant and Anticancer Activities of New 2-Substituted-1,3,4-Thiadiazole from Creatinine
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Publication Date
Fri Aug 06 2021
Journal Name
Research Journal Of Pharmacy And Technology
Synthesis, Antimicrobial evaluation and Docking study of new Schiff bases of benzo[d]oxazol-5-amine derivatives.
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Objective: Benzoxazole derivatives have antifungal, anticancer, antibacterial, and anticonvulsant function. Encouraged by this comment, we agreed to synthesize new Benzoxazole compounds connected to the bases of Schiff's. Methods: 2,4-diaminophenol (1) was prepared by the reaction of 2,4-dinitrophenol and sodium dithionate. Compound (1) reacted with either acetic acid to afford compound (2) or with formic acid to afford compound (3). The Schiff bases were preparation from the reaction condensing reaction of compound (2) or (3) and aromatic aldehydes or ketone; [p-nitrobenzaldehyde, p-hydroxybenzaldehyde, p-chlorobenzaldehyde, p-bromoacetophenone and terephthaldehyde]. Results: FTIR and 1H-NMR spectroscopy characterized all of the pr

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Publication Date
Mon Jun 24 2024
Journal Name
Tropical Journal Of Pharmaceutical Research
Preparation of new Schiff base derivatives from chitosan grafted with polyvinylpyrrolidone and study of their antimicrobial activity
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Purpose: To synthesize and characterize novel Schiff base-chitosan composites and determine their antimicrobial activity. Methods: Novel Schiff-base chitosan composites were synthesized by grafting polyvinylpyrrolidone and then replacing it with different aldehydes. The resulting composites were characterized using advanced analytical techniques, including thermogravimetric analysis (TGA), x-ray diffraction (XRD) studies and Fourier transform infrared spectroscopy (FT-IR). Results: The FT-IR results revealed that the Schiff-base chitosan was successfully produced during mixing and the crystallinity change of the samples was explained by the XRD patterns. Thermogravimetric analysis (TGA) of compounds A1, A3 and A4 showed weight loss

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Publication Date
Thu Feb 08 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
The Feasibility Study Report as an Effective Tool to Evaluate Investment Projects: A Solid Waste Treatment Project as a Case Study
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Hundreds of infrastructure investment projects are inserted into the Iraqi government budget annually. Many of these projects suffer from suspension, delay in completion, corruption, or other negative issues known in Iraqi construction projects. This may harm the country's economic recovery due to allocating funds to useless projects from one or more feasibility studies' components. Therefore, the best solution is to pay attention to the feasibility study reports. This study highlights the importance of feasibility studies reports for investment projects and their effective role in evaluating project ideas to ensure an equitable distribution of a country's financial resources to the most feasible investment projects. This importance

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Publication Date
Sun Jul 23 2023
Journal Name
University Of Samarra
Synthesis, spectral characterization and thermal ‎study of complexes of ions of some metallic ‎elements with new cyclic ligands
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The purpose of my thesis is to prepare four new ligands (L1-L4) that have been ‎used to prepare a series of metal complexes by reacting them with metal ions:‎ ‎ M=(Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II), Hg(II) ‎ ‎ Where succinyl chloride was used as a raw material for the preparation of ‎bi-dented ligands (L1-L4) by reacting it with potassium thiocyanate as a first ‎step and then reacting with (2-aminobenzothiazole, Benzylamine, 4-‎aminoantipyrine, Sulfamethoxazole) respectively as a second step with the use ‎of dry acetone as a solvent, the chemical formula of the four ligands prepared in ‎succession:‎ N1,N4-bis(benzo[d]thiazol-2-ylcarbamothioyl)succinamide (L1)‎ N1,N4-bis(benzylcarbamothioyl)succinami

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Publication Date
Fri Oct 31 2025
Journal Name
The Iraqi Geological Journal
Improving Carbonate Reservoir Development Decision: A Study of Controlling Factors Based on Geological and Engineering Objectives, Halfaya Oil Field
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Detecting the optimum layer for well placement, which requires a diverse assortment of tools and techniques, represents a significant challenge in petroleum studies due to its critical impact on minimizing drilling costs and time. This study aims to evaluate integrated geological, petrophysical, seismic, and geomechanical data to identify the optimum zones for well placement. Three different reservoirs were analyzed to account for lateral and vertical variations in reservoir properties. The integrated data from these reservoirs provides many tools for reservoir development, especially to detect appropriate well placement zones based on evaluations of reservoir and geomechanical quality. The Mechanical Earth Model (MEM) was construct

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Publication Date
Fri Oct 31 2025
Journal Name
The Iraqi Geological Journal
Improving Carbonate Reservoir Development Decision: A Study of Controlling Factors Based on Geological and Engineering Objectives, Halfaya Oil Field
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Detecting the optimum layer for well placement, which requires a diverse assortment of tools and techniques, represents a significant challenge in petroleum studies due to its critical impact on minimizing drilling costs and time. This study aims to evaluate integrated geological, petrophysical, seismic, and geomechanical data to identify the optimum zones for well placement. Three different reservoirs were analyzed to account for lateral and vertical variations in reservoir properties. The integrated data from these reservoirs provides many tools for reservoir development, especially to detect appropriate well placement zones based on evaluations of reservoir and geomechanical quality. The Mechanical Earth Model (MEM) was construct

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Publication Date
Mon Apr 20 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
A Robust Base-layer Design for Hierarchical IoT Intrusion Detection Using Hybrid Deep Learning
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The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

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Scopus
Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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