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A Comparison Between Some Estimator Methods of Linear Regression Model With Auto-Correlated Errors With Application Data for the Wheat in Iraq
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This research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012), (2013), (2014).

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Publication Date
Sun Feb 10 2019
Journal Name
Iraqi National Journal Of Nursing Specialties
Self-Evaluation of Nurses and Midwives Practices Using SBAR (Situation, Background, Assessment, Recommendation) Communication Tool on Maternal Health Documentation
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Abstract:
Objective: To self-evaluate the effect of SBAR (Situation, Background, Assessment, and Recommendation) educational program on nurse and midwives practices in maternal health report documentation accuracy.
Methods: A quasi- experimental design was carried with the application of pre- post test for nurses and midwives’ knowledge and practices regarding SBAR communication tool. The study was held in Al-Elwia maternity teaching hospital, Al –Karckh maternity hospital and Al-Yarmouk teaching Hospital. purposive sample as it was convenient with inclusion criteria consisted of (84) nurse and midwives. The questionnaire comprised of demographic data, nurses- midwives practices of SBAR using (5) level Likert scale for assessme

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Publication Date
Tue May 27 2025
Journal Name
Bulletin Of The Chemical Society Of Ethiopia
Preparation, kinetics, and thermodynamic investigation of Janus green dye removal from aqueous solutions using MnO2 nanoparticles as an adsorbent
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In this study, manganese dioxide (MnO₂) nanoparticles (NPs) were synthesized via the hydrothermal method and utilized for the adsorption of Janus green dye (JG) from aqueous solutions. The effects of MnO₂ NPs on kinetics and diffusion were also analyzed. The synthesized NPs were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), energy-dispersive X-ray analysis (EDX), and Fourier-transform infrared spectroscopy (FT-IR), with XRD confirming the nanoparticle size of 6.23 nm. The adsorption kinetics were investigated using three models: pseudo-first-order (PFO), pseudo-second-order (PSO), and the intraparticle diffusion model. The PSO model provided the best fit (R² = 0.999), indicating that the adsorpti

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Publication Date
Tue Jan 21 2025
Journal Name
Applied Biochemistry And Biotechnology
Synthesis and characterization of new (Au, Ru, and Rh) ion complexes and evaluating their activity as anticancer and antioxidants
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Publication Date
Mon Aug 01 2022
Journal Name
Journal Of Engineering
Production of Load Bearing Concrete Masonry Units (blocks) From Green Concrete Containing Plastic Waste and Nano Silica Sand Powder
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Industrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m3 (B-400) to 300 kg/m3 (B-300) then to 200 kg/m3 (B-200). While (B-380) was produced using 380 kg/m3 cement and 20 kg/m3 nano-sil

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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
Tue Nov 01 2022
Journal Name
Inorganic Chemistry Communications
Sustainable adsorptive removal of high concentration organic contaminants from water using biodegradable Gum-Acacia integrated magnetite nanoparticles hydrogel adsorbent
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Release of industrial effluents comprising dyes in water bodies is one of the foremost causes of water pollution. Therefore, the proper and proficient treatment of these dyes contaminated left-over material before their release is crucial. Herein, an eco-friendly biological macromolecule Gum-Acacia (GA) integrated Fe3O4 nanoparticles composite hydrogel was manufactured via co-precipitation technique for effective adsorption of Congo red (CR) dye existing in water bodies. The as-prepared magnetic GA/Fe3O4 composite hydrogel was characterized by FTIR, XRD, EDX, VSM, SEM, and BET techniques. These studies discovered the fruitful fabrication of biodegradable magnetic GA/Fe3O4 composite hydrogel possessing porous structure with large surface are

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Publication Date
Tue Jun 16 2020
Journal Name
Frontiers In Pharmacology
Administration of Δ9‐Tetrahydrocannabinol (THC) Post‐Staphylococcal Enterotoxin B Exposure Protects Mice From Acute Respiratory Distress Syndrome and Toxicity
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Publication Date
Wed Dec 24 2025
Journal Name
Baghdad Science Journal
Synthesis, Characterization, Antioxidant Content and Antibacterial Study of New Ligand and Its Complexes from Sulfonic Acid and 2-Phthalaldehyde
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The research includes preparation of a new Schiff base from the condensation of sulfonic acid with 2-phthalaldehyde by dissolving (0.2 g, 0.346 mmole) of the ligand (L) in (10 ml) of absolute ethanol, then 0.06 g of potassium hydroxide (KOH) dissolved in 10 ml of distilled water added to it and reacting the product with some binary metal salts (Mn, Co, Ni, Cu, Cd, Zn, Pt, Hg). The biological study was conducted against two types of gram-positive and gram-negative bacteria, Staphylococcus. aureus and Escherichia coli, and the fungus Candida albicans was also used. All the prepared complexes showed higher activity against bacteria and fungi than the ligand for the free Schiff base. The total antioxidant content of the ligand and the c

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Publication Date
Wed Oct 01 2025
Journal Name
Journal Of Materials Science: Materials In Electronics
Comprehensive study of Cu2⁺-ion conducting PVA/PVP/glycerin-based gel polymer electrolytes: structural, electrical, dielectric, and optical properties
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This study investigates the impact of copper sulfate (CuSO4) doping and glycerin plasticization on the structural, electrical, dielectric, and optical properties of poly(vinyl alcohol) (PVA), polyvinyl pyrrolidone (PVP), and glycerin gel polymer electrolytes (GPEs). The GPEs were prepared using a solution casting method with varying CuSO4 concentrations (5 and 10 wt.%). X-ray diffraction analysis revealed the semi-crystalline nature of the polymer blend and also confirmed the presence of CuSO4. Fourier transform infrared spectroscopy confirmed the miscibility of PVA, PVP, and glycerin through interchain hydrogen bonding and indicated the successful incorporation of Cu2+ ions into the polymer blend matrix. The PVA/PVP/glycerin blend containi

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Publication Date
Sun Aug 16 2026
Journal Name
Journal Of Esthetic And Restorative Dentistry
Effectiveness of Cellulose Nanofibers Addition to Soft Denture Lining Material on Candida albicans Adherence and Physical and Mechanical Properties
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Purpose: Current denture liner materials suffer from low tear strength, poor abrasion resistance, weak bond strength to denture material, and increasing risk of denture stomatitis due to adherence. The aim of this study was to evaluate the effects of the addition of cellulose nanofibers (CNFs) to commercial soft denture liner material on the adherence of and physical and mechanical properties. Materials and Methods: CNFs at concentrations of 0.0, 0.5, and 1.0 wt.% were incorporated into a soft liner material. Antifungal effects were assessed by quantifying the adherence of . The Shore A hardness, tensile strength, peel bond strength, and surface roughness tests were employed to assess the properties of the denture liner materials. Chemica

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