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New Polymeric Coii, Niii And Cdii Complexes With Tetrazole Schiff-Base Ligands; Synthesis, Spectral Characterisation And Biological Activity
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New Schiff-base ligands bearing tetrazole moiety and their polymeric metal complexes with Co(II), Ni(II) and Cd(II) ions are reported. Ligands were prepared in a multiple-step reaction. The reaction of sodium 2,6- diformylphenolate and cyclohexane-1,3-dione with 5-amino-2-fluorobenzonitrile resulted in the isolation of two precursors sodium 2,6-bis((E)-(3-cyano-4-fluorophenylimino)methyl)-4-methylphenolate 1 and 5,5'- (1E,1'E)-cyclohexane-1,3-diylidenebis- (azan-1-yl-1-ylidene)bis(2-fluorobenzonitrile) 2, respectively. The reaction of precursors with azide gave the required ligands; sodium 2,6-bis((E)-(4-fluoro-3-(1H-tetrazol-5- yl)phenylimino)methyl)-4-methylphenolate (NaL) and (N, N'E, N, N'E)-N, N'-(cyclohexane-1,3-diylidene)bis(4- fluoro-3-(1H-tetrazol-5-yl)aniline) (L1). The reaction of these ligands with the appropriate metal ions gave polymeric metal complexes of the formulae {[M2(L)]Cl}n and [M(L1)Cl2]n (where M = Co(II), Ni(II) and Cd(II)). A range of techniques were used to confirm the entity of ligands and their complexes. The formation of ligands and mode of complexation and geometrical structure of the title polymeric complexes were verified using FTIR, electronic spectra, NMR, ESMS, magnetic susceptibility, micro-elemental analysis, metal content, chloride content and conductance. The analytical and spectroscopic data indicated the formation of four-coordinate complexes, with a tetrahedral geometry for Co(II) and Cd(II), and square planer for Ni(II) in L- and L1 complexes. Biological evaluation of ligands and their polymeric complexes against gram-positive bacteria (G+), Bacillus stubtili, Staphylococcus aureus, and gram-negative bacteria (G-), Escherichia coli and Pseudomonas aeruginosa, showed ligands and their polymeric metal complexes have a good effect on the screened bacteria.

Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Wed Nov 27 2019
Journal Name
Environmental Science And Pollution Research
Application of emulsion and Pickering emulsion liquid membrane technique for wastewater treatment: an overview
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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Design and Analysis of Electro-Hydraulic Servo System for Speed Control of Hydraulic Motor
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In this study, the electro-hydraulic servo system for speed control of fixed displacement hydraulic motor using proportional valve and (PID) controller is investigated theoretically ,experimentally and simulation . The theoretical part includes the derivation of the nonlinear mathematical model equation of (valve – motor ) combination system and the derivation of the transfer function for the complete hydraulic system , the stability test of the system during the operation through the transfer function using MATLAB package
V7.1 have been done. An experimental part includes design and built hydraulic test rig and simple PID controller .The best PID gains have been calculated experimentally and simulation, speed control performance te

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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

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Publication Date
Fri Nov 03 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences( P-issn 1683 - 3597 E-issn 2521 - 3512)
Diacerein Loaded Novasome for Transdermal Delivery: Prepartion , In-Vitro Characterization and Factors Affecting Formulation
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Diacerein (DCN) is a semi-synthetic anthraquinone derivative of Rhein that is indicated for the management of osteoarthritis. Diacerein exhibits poor dissolution in the GIT fluids and suffers from low bioavailability upon oral administration in addition to the laxative effect of Rhein metabolites. The aim of the present study was to develop novasomal vesicles with optimized entrapment efficiency and size to serve as a carrier for transdermal delivery of diacerein. Novasomal vesicles were prepared by thin film hydration method thin film hydration. The prepared vesicles were optimized utilizing different surfactant to cholesterol molar ration, sonication type, different sonication times and varying fatty acid level. The prepared vesicles were

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Publication Date
Mon Apr 01 2024
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Classification of grapevine leaves images using VGG-16 and VGG-19 deep learning nets
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The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

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Publication Date
Wed May 08 2024
Journal Name
Applied Sciences
Nano-Additives in Asphalt Binder: Bridging the Gap between Traditional Materials and Modern Requirements
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This research delves into the realm of asphalt technology, exploring the potential of nano-additives to enhance traditional asphalt binder properties. Focusing on Nano-Titanium Dioxide (NT), Nano-Aluminum Oxide (NA), and Nano-Silica Oxide (NS), this study investigates the effects of incorporating these nanomaterials at varying dosages, ranging from 0% to 8%, on the asphalt binder’s performance. This study employs a series of experimental tests, including consistency, storage stability, rotational viscosity, mass loss due to aging, and rheological properties, to assess the impact of nano-additives on asphalt binder characteristics. The findings indicate a substantial improvement in the consistency of the asphalt binder with the add

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Publication Date
Thu Apr 21 2016
Journal Name
Iraqi Journal Of Agricultural Sciences
EFFECT OF SHEEP MANURE EXTRACT ON THE GROWTH AND NUTRIENTS CONTENT OF TOMATO SEEDLINGS
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The experiment was conducted under shading (with the aid of Saran) condition on a nursery managed by the Baghdad Mayoralty during the season of 2014-2015 to study the effect of composed sheep manure extract on the growth and leaf nutrients content of tomato seedlings var. Wijdan. The experiment was composed of 6 treatments included the extract of sheep manure by hot (425C)and lmbient(205C) temperature water .The extract was diluted to the half by water and foliar applied to seedlings (multible application) or to the soil . Treatments also included the application of NPK chemical fertilizers as recommended and a control treatment through applying distilled water as foliar .The experiment was designed according to the randomized compl

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Control Pepper Fusarium Wilting by biocontrol agent Trichoderma harzianum and Chelated Iron Fe-EDDHA
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Sweet pepper (Capsicum annuum L.) is an economically important vegetable crop. Wilt disease caused by Fusarium oxysporum f. sp. capsici is a specific pathogen that affects the pepper. Four isolates of F. oxysporum f. sp. capsici Fo3, Fo6, Fo7 and Fo8 were obtained from diseased pepper plants that were collected from different pepper fields in Baghdad. Fo6 isolate that has high pathogenicity to pepper seeds, Trichoderma harzianum (Th) was tested in vitro against F. oxysporum f. sp. capsici showed a high inhibition rate for the isolate Fo6, the concentration of chelated iron Fe-EDDHA 0.5% reduced the radial growth of Fo6 whi

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Ecological Engineering
Chlorpyrifos Removal from Aqueous Solutions by Emulsion Liquid Membrane – Stability, Extraction, and Stripping Studies
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