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bsj-2291
Association of Cestoda Raillietina echinobothrida in Rock Pigeon Columba livia from Baghdad city of Iraq
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The parasite tapeworm (Raillietina echinobothrida) belonges to the class Cestoda, it is responsible for nodular tapeworm disease in poultry .The aim of this study was to determine tapeworm parasites infections in Columba livia from two markets in the province of Baghdad for the period from May to December 2014. From a total of thirty five sample of Columba livia were randomly selected and then examined the elementary canal of these samples. The present study showed that the collected rock pigeon were found six infected with the cestode Raillietina echinobothrida with infection rate (17.14%). The statistical analysis for the characters of the cestode showed significant differences in all recipes, but there were no significant differences in the length character of rostellum hooks.

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Publication Date
Wed Jan 10 2024
Journal Name
Journal Of Optics
Pulsed laser deposition of Pd/WO3 nanoparticles on Si nanostructure for highly sensitive room-temperature gas sensors
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Publication Date
Wed May 01 2024
Journal Name
Journal Of Water Process Engineering
Rational assembly of Z-scheme FeTiO3/Fe-doped g-C3N4 photocatalytic heterojunctions: Photodegradation behavior and mechanism insight
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Expanded use of antibiotics may increase the ability of pathogenic bacteria to develop antimicrobial resistance. Greater attention must be paid to applying more sustainable techniques for treating wastewater contaminated with antibiotics. Semiconductor photocatalytic processes have proven to be the most effective methods for the degradation of antibiotics. Thus, constructing durable and highly active photocatalytic hybrid materials for the photodegradation of antibiotic pollutants is challenging. Herein, FeTiO3/Fe-doped g-C3N4 (FTO/FCN) heterojunctions were designed with different FTO to FCN ratios by matching the energy level of semiconductors, thereby developing effective direct Z-type heterojunctions. The photodegradation behaviors of th

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
Patient Monitoring System Based on Internet of Things: A Review and Related Challenges With Open Research Issues
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Publication Date
Mon Apr 01 2024
Journal Name
Baghdad Science Journal
Simultaneous spectrophotometric method for determination of both ciprofloxacin and cephalexin by using H-point standard addition method
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طريقة سهلة وبسيطة ودقيقة لتقدير السبروفلوكساسين  في وجود السيفاليكسين او العكس بالعكس في خليط منهما. طبقت الطريقة المقترحة بطريقة الاضافة القياسية لنقطة بنجاح في تقدير السبروفلوكساسين بوجود السيفاليكسين كمتداخل عند الاطوال الموجية 240-272.3 نانوميتر وبتراكيز مختلفة من  السبروفلوكساسين 4-18 مايكروغرام . مل-1 وكذلك تقدير السيفاليكسين بوجود السبروفلوكساسين الذي يتداخل باطوال موجية 262-285.7 نانوميتر وبتراكيز مخ

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Publication Date
Fri Jul 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
A study Some Technical Indicators Under Impact Tillage Depth and Disk harrow Angle of the Compound Machine
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Abstract<p>The research included studying the effect of different plowing depths (10,20and30) cm and three angles of the disc harrows (18,20and25) when they were combined in one compound machine consisting of a triple plow and disc harrows tied within one structure. Draft force, fuel consumption, practical productivity, and resistance to soil penetration. The results indicated that the plowing depth and disc angle had a significant effect on all studied parameters. The results showed that when the plowing depth increased and the disc angle increased, leads to increased pull force ratio, fuel consumption, resistance to soil penetration, and reduce the machine practical productivity.</p>
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Mon Apr 08 2024
Journal Name
Biomed Research International
Evaluation of High-Performance Polyether Ether Ketone Polymer Treated with Piranha Solution and Epigallocatechin-3-Gallate Coating
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Background. Dental implantation has become a standard procedure with high success rates, relying on achieving osseointegration between the implant surface and surrounding bone tissue. Polyether ether ketone (PEEK) is a promising alternative to traditional dental implant materials like titanium, but its osseointegration capabilities are limited due to its hydrophobic nature and reduced surface roughness. Objective. The aim of the study is to increase the surface roughness and hydrophilicity of PEEK by treating the surface with piranha solution and then coating the surface with epigallocatechin-3-gallate (EGCG) by electrospraying technique. Materials and Methods. The study includes four groups intended to investigate the effect of pir

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Publication Date
Fri Jul 04 2025
Journal Name
Analytical Chemistry Letters
Green synthesis, characterization, and broad-spectrum anti-bacterial applications of metallic nanoparticles mediated by natural extracted materials
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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Molecular Docking, Synthesis, characterization and preliminary cytotoxic evaluation of new 1, 3,4-Thiadiazole derivatives as EGFR inhibitors
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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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