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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
Fri Nov 01 2019
Journal Name
Journal Of Environmental Quality
Effects of Conservation Practices on Soil Quality Compared with a Corn–Soybean Rotation on a Claypan Soil
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Restoration of degraded lands by adoption of recommended conservation management practices can rehabilitate watersheds and lead to improving soil and water quality. The objective was to evaluate the effects of grass buffers (GBs), biomass crops (BCs), grass waterways (GWWs), agroforestry buffers (ABs), landscape positions, and distance from tree base for AB treatment on soil quality compared with row crop (RC) (corn [Zea mays L.]–soybean [Glycine max (L.) Merr.] rotation) on claypan soils. Soil samples were taken from 10‐cm‐depth increments from the soil surface to 30 cm for GB, BC, GWW, and RC with three replicates. Soil samples were collected from

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Publication Date
Tue Oct 15 2024
Journal Name
Civileng
Structural Performance of a Hollow-Core Square Concrete Column Longitudinally Reinforced with GFRP Bars under Concentric Load
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Concrete columns with hollow-core sections find widespread application owing to their excellent structural efficiency and efficient material utilization. However, corrosion poses a challenge in concrete buildings with steel reinforcement. This paper explores the possibility of using glass fiber-reinforced polymer (GFRP) reinforcement as a non-corrosive and economically viable substitute for steel reinforcement in short square hollow concrete columns. Twelve hollow short columns were meticulously prepared in the laboratory experiments and subjected to pure axial compressive loads until failure. All columns featured a hollow square section with exterior dimensions of (180 × 180) mm and 900 mm height. The columns were categorized into

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Publication Date
Mon Mar 15 2021
Journal Name
Egyptian Journal Of Chemistry
Antimicrobial Activity of New Synthesized Aza -Beta Lactam and Tetrazole Derivatives Bearing Imidazo[2,1-B]Benzothiazole Moiety
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Publication Date
Wed Jan 01 2025
Journal Name
International Journal Of Hydrogen Energy
A comprehensive review of battery thermal management systems for electric vehicles: Enhancing performance, sustainability, and future trends
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Publication Date
Sun Sep 08 2019
Journal Name
Applied Organometallic Chemistry
Phosphorus‐based Schiff bases and their complexes as nontoxic antioxidants: Structure–activity relationship and mechanism of action
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Phosphorus‐based Schiff base were synthesized by treating bis{3‐[2‐(4‐amino‐1.5‐dimethyl‐2‐phenyl‐pyrazol‐3‐ylideneamino)ethyl]‐indol‐1‐ylmethyl}‐phosphinic acid with paraformaldehyde and characterized as a novel antioxidant. Its corresponding complexes [(VO)2L(SO4)2], [Ni2LCl4], [Co2LCl4], [Cu2LCl4], [Zn2LCl4], [Cd2LCl4], [Hg2LCl4], [Pd2LCl4], and [PtL

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Publication Date
Mon Jan 01 2024
Journal Name
International Journal Of Advanced Community Medicine
Knowledge and attitude of breast self-examination toward breast cancer among nonmedical female students at Diyala University
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Abstract Background: Women in developed and poor nations more often get breast cancer. BSE involves women frequently checking their breasts for lumps or swelling to seek medical assistance. BSE lets women know how their breasts appear and feel so they can notify their doctors of any changes. Objectives: To determine the knowledge and attitude of breast self-examination among nonmedical female student. Method: A descriptive cross-sectional research was conducted at Diyala University/Governorate-Iraq on fourth-grade non-medical female students. A 700-student online questionnaire was employed. We got official agreements. Fisher's exact or chi-square test was employed. Statistical significance was set at p<0.05. Results: The mean age of partici

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Publication Date
Mon Nov 05 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Aqueous and Ethanolic Extraction for Coriander Seeds, Leaves and Stems and Studying their Antibacterial Activity
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Objective: To evaluate two kinds of extraction (aqueous and ethanolic) for coriander using seeds, leaves and stems and
studying their antibacterial activity against nine different microorganisms.
Methodology: Coriander was selected to carry out this study. Seeds, leaves and stems were collected from local markets in
Baghdad then dried in shade for at least 10 days and grinded to fine powder. Aqueous hot extracts for 1hr. at (50
c) and
cold extracts for 24 hrs at (4
c) were performed by using seeds, leaves and stems then studied antibacterial effect against
nine different microorganisms by using well diffusion technique. Cold aqueous extracts of coriander seeds for 48 hrs. and
72 hrs and ethanolic extraction

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Publication Date
Fri Dec 01 2023
Journal Name
Case Studies In Chemical And Environmental Engineering
Treatment of petroleum refinery wastewater by an innovative electro-Fenton system: Performance and specific energy consumption evaluation
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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Design and Synthesis of New Non-Steroidal Anti-inflammatory Agents with Expected Selectivity toward Cyclooxygenase-2 Inhibition
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This study includes design and synthesis of new non-steroidal anti-inflammatory agents (NSAIDs) with expected cyclooxygenase-2 (COX-2) selective inhibition to achieve better activity and low gastric side effects. Two series of compounds have been designed and synthesized as potential NSAIDs,these  are:     Salicylamide derivatives (compounds 3,4,5 ) and Diflunisal derivatives (compounds 10&11). In vivo acute anti-inflammatory effect of one of the synthesized agents (compound 3)  was evaluated in the rat using egg-white induced paw edema model of inflammation. Preliminary pharmacological study revealed that compound 3 exhibited less anti-inflammatory effect  compared to that of aspirin after

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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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