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Barriers to Baseline Needs for Early Detection of Breast Cancer among Iraqi Female Patients
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Background: Breast Cancer is the most common malignancy among the Iraqi population; the majority of cases are still diagnosed at advanced stages with poor prospects of cure. Early detection through promoting public awareness is one of the promising tools in its control. Objectives: To evaluate the baseline needs for breast cancer awareness in Iraq through exploring level of knowledge, beliefs and behavior towards the disease and highlighting barriers to screening among a sample of Iraqi women complaining of breast cancer. Methodology: Two-hundred samples were enrolled in this study; gathered from the National Cancer Research Center of Baghdad University and the Oncology Teaching Hospital of the Medical City throughout the year 2015. The study population comprised two groups: the first included 100 female patients who were receiving treatment for breast cancer (Group A), while another 100 randomly selected apparently healthy women served as Control (Group B). Those were asked to complete a structured questionnaire which was designed to explore the level of knowledge, beliefs, behavior towards breast cancer and the barriers to early diagnosis. The studied variables included the socio demographic and clinical data, women needs and beliefs regarding breast health and cancer care, and the barriers to screening. Results: Ninety percent of patients with breast cancer in Group I recorded a minimum score of Good; they have answered confidently that the disease is common among women, can be curable when detected at early stages and is not contagious. They also display a significantly higher attitude regarding performing BSE, receiving routine CBE check up and having the courage to be informed about the diagnosis of cancer. Although both groups believe that early detection of cancer should be promoted culturally, Group I displayed a stronger reaction to place this approach as a priority in the community. Overall, both groups do not believe that the disease is usually fatal, could bring disgrace to the family leading to divorce, and did not consider mammography as an embarrassing procedure against religious beliefs. Nevertheless, the majority refuse to be examined by a male doctor and to undergo screening mammography if they have no complaints. Recommendations: Feasible strategies should be more promptly adopted to overcome barriers to early detection of breast cancer among the Iraqi patients; focusing on promoting public health education and ensuring the availability of accessible well equipped diagnostic facilities.

 
 

 

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Publication Date
Wed Jan 01 2020
Journal Name
Materials Research Express
Heavy metal free thermal stabilizing-flame retarding modifier for plasticized poly(vinyl chloride)
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Abstract<p>Our research aimed to find a new material that can be an efficient heavy metal free flame retardant for plasticized poly(vinyl chloride) comparable to the conventional flame retardants. One of these extraordinary materials is Oxydtron using as an admixture for concrete. Oxydtron showed unexpected efficiency as a flame retardant agent and an excellent heat stabilizer as well. Limiting oxygen index (LOI), static heat stability, Congo-red, and differential scanning calorimetry (DSC) were carried out. The thermal tests proved that Oxydtron is suitable to improve plasticized poly(vinyl chloride) performance at high temperatures applications in terms of flame retarding and thermal stability</p> ... Show More
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Publication Date
Mon Jan 29 2024
Journal Name
Advances In Systems Analysis, Software Engineering, And High Performance Computing
Evaluating Antivirus Effectiveness Against Malware in Ascending Order for Increasing Blockchain Endpoint Protection
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Blockchain represents a new promising technology with a huge economic impact resulting from its uses in various fields such as digital currency and banking; malware represents a serious threat to users, and there are many differences in the effectiveness of antivirus software used to deal with the problem of malware. This chapter has developed a coefficient for measuring the effectiveness of antivirus software. This chapter evaluates the effectiveness of antivirus software by conducting tests on a group of protection programs using a folder containing an amount of data. These programs are applied to combat viruses contained in this folder. The study revealed that the effectiveness of antivirus software is as follows: AVG scored 0%,

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Ant Colony Optimization Based Force-Position Control for Human Lower Limb Rehabilitation Robot
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The aim of human lower limb rehabilitation robot is to regain the ability of motion and to strengthen the weak muscles. This paper proposes the design of a force-position control for a four Degree Of Freedom (4-DOF) lower limb wearable rehabilitation robot. This robot consists of a hip, knee and ankle joints to enable the patient for motion and turn in both directions. The joints are actuated by Pneumatic Muscles Actuators (PMAs). The PMAs have very great potential in medical applications because the similarity to biological muscles. Force-Position control incorporating a Takagi-Sugeno-Kang- three- Proportional-Derivative like Fuzzy Logic (TSK-3-PD) Controllers for position control and three-Proportional (3-P) controllers for force contr

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Planner And Development
Urban sustainability assessment for the urban renewal project in Al Shawaka a rea
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Sustainability is a major demand and need pursued by cities in all areas of life due to the environmental, social and economic gains they provide, especially in the field of city planning and urban renewal projects that aim to integrate the past, present and future.

 

The research aims to evaluate the Haifa Street renewal project, and Al-Shawaka district, one of the Baghdad districts located next to Al-Karkh, was elected by comparing the sustainability indicators of urban renewal with the reality of the situation through a field survey and questionnaire form and focusing on the social and economic impacts and environmental for the project on the study area. To reach the most important conclusions and recommendations

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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Fri Nov 01 2019
Journal Name
American Journal Of Dermatology And Venereology
Sesame and Pumpkin Seed Oil are New Effective Topical Therapies for Alopecia Areata
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KE Sharquie, AA Noaimi, MS Abass, American Journal of Dermatology and Venereology, 2019 - Cited by 4

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Synthesis, Characterization and Antimicrobial activity Study Via some new Schiff bases for Trimethoprim
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This search reports the synthesis of some new series of Schiff base compounds for trimetheprim derivatives which known high been known as a medicinal effectiveness. Trimetheprim was condensed with several substituted aldehydes compounds.(4-dimethyl amine benzaldehyde , propanal , salicaldehyde, 2.4 dimethoxy benzaldehyde and 4- methyl benzaldehyde) to obtain Schiff base products(1a-5a) and several substituted ketones compound (4-aminoacetophenone,4-chloroacetophenone, isobutyleketone, acetylacetone and acetophenone) to obtain Schiff base products(6b-10b) in ethanol in the presence of concentrated sulphuric acid as a catalyst to yield the Schiff base. The structure of synthesized compounds has been established on the basis of their Chemical

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Publication Date
Sun Mar 30 2025
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Lithology and minerals identification from well logs for Mishrif Formation in Ratawi oilfield
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   Lithology identification plays a crucial role in reservoir characteristics, as it directly influences petrophysical evaluations and informs decisions on permeable zone detection, hydrocarbon reserve estimation, and production optimization. This paper aims to identify lithology and minerals composition within the Mishrif Formation of the Ratawi Oilfield using well log data from five open hole logs of wells RT-2, RT-4, RT-5, RT-6, and RT-42. At this step, the logging lithology identification tasks often involve constructing a lithology identification model based on the assumption that the log data are interconnected. Lithology and minerals were identified using three empirical methods: Neutron-Density cross plots for lithology id

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Publication Date
Thu Jun 20 2024
Journal Name
Ingénierie Des Systèmes D Information
Enabling Technologies for Ultra-Low Latency and High-Reliability Communication in 6G Networks
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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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