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Using Artificial Neural Network to Predict Rate of Penetration from Dynamic Elastic Properties in Nasiriya Oil Field
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   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic properties for the studied wells was determined and listed with depth. Laboratory measurements were conducted on core samples selected from two wells from the studied wells. Ultrasonic device was used to measure the transit time of compressional and shear waves and to compare these results with log records. The reason behind that is to check the accuracy of the Greenberg-Castagna equation that was used to estimate the shear wave in order to calculate dynamic elastic properties. The model was built using Artificial Neural Network (ANN) to predict the rate of penetration in Mishrif formation in the Nasiriya oil field for the selected wells. The results obtained from the model were compared with the provided rate of penetration from the field and the Mean Square Error (MSE) of the model was 3.58 *10-5.

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Publication Date
Mon Nov 05 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Effectiveness of Instruction-oriented Intervention for Primipara Women upon Episiotomy and Self-perineal Care at Ibn Al-Baladi Hospital
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Objective: To identify the effectiveness of instruction oriented intervention for primipara women upon episiotomy and self
perineal care.
Methodology: A quasi-experimental study was carried out to determine the effectiveness of instruction-oriented
intervention for primipara women upon episiotomy and self-perineal care. A purposive "non-probability" sample of (60)
primipara mothers was selected from Ibn AL-Balady Pediatric and Maternity Hospital, Al-russafa, Baghdad. The sample
has been divided into two groups; (30) primipara women who were considered as a study group, and another (30) primipara
women who were considered as a control one. The study group was exposed to an instruction-oriented intervention. While,
the

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Publication Date
Thu Jan 01 2026
Journal Name
Journal Of Nanostructures
Cytotoxic and Antibacterial Activity of Yttrium Oxide Nanoparticle Y2O3 Against Serratia Fonticuli and Citrobacter Kasseri Isolated fFrom Cholangitis Patients
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The rise of antibiotic-resistant bacteria necessitates the exploration of novel antimicrobial agents. Yttrium oxide nanoparticles (Y₂O₃) have shown potential due to their unique physicochemical properties and antibacterial activities against various pathogens. This study investigates the cytotoxic and antibacterial effects of Y₂O₃ nanoparticles against Serratia fonticuli and Citrobacter koseri, bacteria isolated from cholangitis patients. Bacterial strains were isolated from bile specimens and confirmed using standard microbiological techniques. The methods of X-ray diffraction (XRD), (SEM), and Frequency transform-infrared spectroscopic (FT-IR) were used to characterize YO₃ particles. Using a microdilution technique, the minimum

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Publication Date
Fri Dec 20 2024
Journal Name
Baghdad Science Journal
Interference with quorum sensing of Klebsiella pneumoniae by some plant extracts can affect the biofilm formation and antibiotic resistance.
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Quorum sensing (QS) is a perfectly orchestrated molecular communication system. It is a boon for Klebsiella pneumoniae, and bane for the host. This system is believed to make K. pneumoniae a leading cause of multidrug-resistant (MDR) nosocomial infections. This study aimed to investigate the antibacterial and anti-biofilm potential of medicinal plant extracts through interfering with QS of K. pneumoniae. The effect of different concentrations of ethanolic extracts of cinnamon and clove on K. pneumoniae was determined by analyzing the growth curve, survival assay (MTT), Qualitative and quantitative biofilm formation, antibiotic resistance, along with studying gene expression of the genes encoding the above traits, using quantitative real tim

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Publication Date
Mon Oct 16 2023
Journal Name
F1000research
Assessment of general population knowledge, attitude, and practice on safe unused and expired drugs disposal: a cross-sectional study
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Background The appropriate disposal of medication is a well-recognized issue that has convened growing recognition in several contexts. Insufficient awareness relating to appropriate methods for the disposal of unneeded medicine may result in notable consequences. The current research was conducted among the public in Iraq with the aim of examining their knowledge, attitude, and practices regarding the proper disposal of unused and expired medicines. Methods The present study used an observational cross-sectional design that was community-based. The data were obtained from using an online questionnaire. The study sample included people of diverse genders, regardless of their race or occupational status. The study mandated that all pa

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Publication Date
Fri Oct 30 2020
Journal Name
International Journal Of Agronomy
Molybdenum Induces Growth, Yield, and Defence System Mechanisms of the Mung Bean (Vigna radiata L.) under Water Stress Conditions
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Water stress has a negative impact on the yield and growth of crops worldwide and consequently has a global impact on food security. Many biochemical changes occur in plants as a response to water stress, such as activation of antioxidant systems. Molybdenum (Mo) plays an important part in activating the expression of many enzymes, such as CAT, POD, and SOD, as well as increasing the proline content. Mo therefore supports the defence system in plants and plays an important role in the defence system of mung bean plants growing under water stress conditions. Four concentrations of Mo (0, 15, 30, and 45 mg·L−1) were applied to plants, using two approaches: (a) seed soaking and (b) foliar application. Mung bean plants were subject

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Publication Date
Sun Jun 13 2021
Journal Name
International Journal Of Drug Delivery Technology
Synthesis, Characterization and Anticorrosion Studies of New Co(II), Ni(II), Cu(II), and Zn(II) Schiff Base Complexes
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The research included preparation of new Schiff base (L) by two steps: preparation of precursor [bis(2-formyl-6-methoxyphenyl) succinate] (P) by reacting (3-methoxy salicyl aldehyde) with (succinoyl dichloride) as first step then react the prepared precursor (P) with (ethanethioamide) to have the new Schiff base [bis(2-((ethane thioyl imino) methyl)-6-methoxy phenyl) succinate] (L) as second step. Characterized compounds based on Mass spectra, 1 H, 13CNMR (for ligand (L)), FT-IR and UV spectrum, melting point, molar conduct, %C, %H, and %N, the percentage of the metal in complexes %M, magnetic susceptibility, while study corrosion inhibition (mild steel) in acid solution by weight loss. These measurements proved that by (Oxygen, Nitrogen, a

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Publication Date
Mon Feb 01 2021
Journal Name
Meta Gene
Association analysis of FTO gene polymorphisms rs9939609 and obesity risk among the adults: A systematic review and meta-analysis
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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Mon Jan 01 2018
Journal Name
Al-qadisiyah Journal Of Pure Science
Synthesis and Spectroscopic Studies of new ligand N-((4-(phenylamino)phenyl)carbamothioyl)acetamide with some Divalent Metal Ion Complexes
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A new ligand N-((4-(phenylamino) phenyl) carbamothioyl) acetamide (PCA) was synthesized by reaction of (4-amino di phenyl amine) with (acetyl isothiocyante) by using acetone as a solvent. The prepared ligand(PCA) has been characterization by elemental analysis (CHNS), infrared(FT-IR),electronic spectral (UV-Vis)&1H,13C- NMR spectra. Some Divalent Metal ion complexes of ligand (PCA) were prepared and spectroscopic studies by infrared(FT-IR), electronic spectral (UV-Vis), molar conductance, magnetic susceptibility and atomic absorption. The results measured showed the formula ofFall prepared complexes were [M (PCA)2 Cl2] (M+2 = Mn, Co, Ni, CU, Zn, Cd &Hg),the proposed geometrical structure for all complexes wereeoctahedral.

Publication Date
Thu Feb 23 2023
Journal Name
Chalcogenide Letters
Studying the effect of copper on the p-ZnTe/n-AgCuInSe2/p-Si for thin films solar cell applications
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A thin film of AgInSe2 and Ag1-xCuxInSe2 as well as n-Ag1-xCuxInSe2 /p-Si heterojunction with different Cu ratios (0, 0.1, 0.2) has been successfully fabricated by thermal evaporation method as absorbent layer with thickness about 700 nm and ZnTe as window layer with thickness about 100 nm. We made a multi-layer of p-ZnTe/n-AgCuInSe2/p-Si structures, In the present work, the conversion efficiency (η) increased when added the Cu and when used p-ZnTe as a window layer (WL) the bandgap energy of the direct transition decreases from 1.75 eV (Cu=0.0) to 1.48 eV (Cu=0.2 nm) and the bandgap energy for ZnTe=2.35 eV. The measurements of the electrical properties for prepared films showed that the D.C electrical conductivity (σd.c) increase

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