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Automated breast ultrasound: A comparison study with handheld ultrasound in detection and characterization of lesions in mammographically dense breast
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Background: Although mammography is a powerful screening tool in detection of early breast cancer, it is imperfect, particularly for women with dense breast, which have a higher risk to develop cancer and decrease the sensitivity of mammogram, Automated breast ultrasound is a recently introduced ultrasonography technique, developed with the purpose to standardize breast ultrasonography and overcome some limitations of handheld ultrasound, this study aims to evaluate the diagnostic efficacy of Automated breast ultrasound and compare it with handheld ultrasound in the detection and characterization of breast lesions in women with dense breasts.

Objectives: To evaluate the diagnostic efficacy of Automated breast ultrasound and compare it with hand held ultrasound in detection and characterization of breast lesions in women with dense breast.

Subjects and Methods: A prospective observational study conducted at Oncology Teaching Hospital during the period of ten months from 1st of February till 1st of December 2020.  Included 62 women with dense breasts on diagnostic mammograms. All women underwent technician performed automated breast ultrasound and radiologist performed handheld ultrasound for both breasts. All suspicious lesions with selected probably benign lesions underwent biopsy, handheld ultrasound detected 48 masses (67.6%), 15 of them (21.1%) were cystic, automated breast ultrasound detected 54 masses (76.1%); 20 of them (28.2%) were cystic. The sensitivity of handheld ultrasound was=87.5%, Specificity=58.8%, the sensitivity of automated breast ultrasound was=93.8%, Specificity=70.6%.

Conclusion: Automated breast ultrasound is an effective modality to detect occult breast lesion in women with dense breasts, automated breast ultrasound and handheld ultrasound have a reliable agreement in detection and characterization of breast lesions with higher accuracy of automated breast ultrasound in the evaluation of malignant lesions.

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Publication Date
Sun Mar 04 2012
Journal Name
Baghdad Science Journal
The use of laurylamine hydrocholoride CH3(CH2)11 NH3 –Cl for secondary oil recovery
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Laurylamine hydrochloride CH3(CH2)11 NH3 – Cl has been chosen from cationic surfactants to produce secondary oil using lab. model shown in fig. (1). The relationship between interfacial tension and (temperature, salinity and solution concentration) have been studied as shown in fig. (2, 3, 4) respectively. The optimum values of these three variables are taken (those values that give the lowest interfacial tension). Saturation, permeability and porosity are measured in the lab. The primary oil recovery was displaced by water injection until no more oil can be obtained, then laurylamine chloride is injected as a secondary oil recovery. The total oil recovery is 96.6% or 88.8% of the residual oil has been recovered by this technique as shown

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Publication Date
Sat Nov 10 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Effect of Long Term Exposure to Sodium Nitrite on Gene Responsible for DNA Repair
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Objective: The aim of this study is to detect the effect of continuous exposure to Sodium Nitrite on 8-oxoguanine
DNA glycosylase (OGG1) gene which responsible on DNA repairs. DNA repair play a major role in maintaining
genomic stability when DNA exposure to damage. Genomic stability is very important for keeping body cells
healthy and to prevent many types of tumor development. Many genes are responsible for this job; one of them is
OGG1 gene.
Methodology: In current study two groups of mice were chronically exposed to sodium nitrite for six months and
eighteen months while third group was used as a control. Then sizes of OGG1 were estimated.
Results: The results exhibited in the unexposed (control) mice had two dif

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Publication Date
Tue Jul 30 2019
Journal Name
Sn Applied Sciences
Removal of oil emulsion from aqueous solution by using Ricinus communis leaves as adsorbent
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Publication Date
Sat Apr 25 2020
Journal Name
Asian Journal Of Agriculture And Biology
Biodegradation of plastic wastes by confused flour beetle Tribolium confusum Jacquelin du Val larvae
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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Development of Regression Models for Predicting Pavement Condition Index from the International Roughness Index
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Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac

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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of Water Process Engineering
Antibiotics adsorption from contaminated water by composites of ZSM-5 zeolite nanocrystals coated carbon
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The presence of antibiotic residues such as ciprofloxacin (CIPR) in an aqueous environment is dangerous when their concentrations exceed the allowable. Therefore, eliminating these residues from the wastewater becomes an essential issue to prevent their harm. In this work, the potential of efficient adsorption of ciprofloxacin antibiotics was studied using eco-friendly ZSM-5 nanocrystals‑carbon composite (NZC). An inexpensive effective natural binder made of the sucrose-citric acid mixture was used for preparing NZC. The characterization methods revealed the successful preparation of NZC with a favorable surface area of 103.739 m2/g, and unique morphology and functional groups. Investigating the ability of NZC for adsorbing CIPR antibioti

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Publication Date
Sat Mar 26 2016
Journal Name
Journal Of Materials Science: Materials In Electronics
Hydrothermal deposition of CdS on vertically aligned ZnO nanorods for photoelectrochemical solar cell application
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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Wed Dec 28 2022
Journal Name
Structural Concrete
Enhancement of RC T‐beams toughness using laced stirrups reinforcement for blast response predictions
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Abstract<p>The dynamic behavior of laced reinforced concrete (LRC) T‐beams could give high‐energy absorption capabilities without significantly affecting the cost, which was offered through a combination of high strength and ductile response. In this paper, LRC T‐beams, composed of inclined continuous reinforcement on each side of the beam, were investigated to maintain high deformations as predicted in blast resistance. The beams were tested under four‐point loading to create pure bending zones and obtain the ultimate flexural capacities. Transverse reinforcement using lacing reinforcement and conventional vertical stirrups were compared in terms of deformation, strain, and toughness changes of the tes</p> ... Show More
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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN
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Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

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