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Effect of Radiation on Blood Component and Hormones on Male Patient and Breast Cancer
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Background: The study's objective was to estimate the effects of radiation on testosterone-related hormones and blood components in prostate cancer patients. N Materials and Method: This study aims to investigate the effects of radiation on 20 male prostate cancer patients at the Middle Euphrates Oncology Centre. Blood samples were collected before and after radiation treatment, with a total dose of 60- 70 Gy, The blood parameters were analyzed. The hospital laboratory conducted the blood analysis using an analyzer (Diagon D-cell5D) to test blood components before and after radiation. Hormonal examinations included testosterone levels, using the VIDASR 30 for Multiparametric immunoassay system Results: The study assessed the socio-demography of prostate cancer male patients, revealing that the majority were aged 69.55 t 10.76 years, with a weight of 75.3 t 10.84 Kg and height of 170.50 t 8.70 cm. The stage of cancer was assessed, with 25% of patients being IV and IIV, followed by II, IB, and V. Only one patient was at stage III. The Gleason Score (GS) was used to classify patients, with 40% being given a score of 7, followed by 6, 8, and 9 equally (20%). Total Prostate-specific Antigen (PSA) had a mean value of 12.87 t 2.78. Hematological analysis showed a significant decrease in random blood sugar levels, white blood cells, lymphocytes platelets, and hemoglobin levels after radiotherapy. Testosterone levels also declined after radiotherapy fractions. However, kidney functions like urea and creatinine levels increased after pelvic irradiation Conclusion: The study found that radiation treatment for prostate cancer significantly impacted blood components and hormones associated with testosterone. It led to reduced levels of random blood sugar, white blood cells, lymphocytes, platelets, haemoglobin, and testosterone. Additionally, high-energy therapeutic x-rays increased_ levels of urea and creatinine, indicating the need for strict monitoring and management of adverse effects.

Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Sun Jun 30 2019
Journal Name
Journal Of Engineering
Numerical Study of Fluid Flow and Heat Transfer Characteristics in Solid and Perforated Finned Heat Sinks Utilizing a Piezoelectric Fan
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Numerical study is adapted to combine between piezoelectric fan as a turbulent air flow generator and perforated finned heat sinks. A single piezoelectric fan with different tip amplitudes placed eccentrically at the duct entrance. The problem of solid and perforated finned heat sinks is solved and analyzed numerically by using Ansys 17.2 fluent, and solving three dimensional energy and Navier–Stokes equations that set with RNG based k−ε scalable wall function turbulent model. Finite volume algorithm is used to solve both phases of solid and fluid. Calculations are done for three values of piezoelectric fan amplitudes 25 mm, 30 mm, and 40 mm, respectively. Results of this numerical study are compared with previous b

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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Eco-Friendly Synthesis of Ag-ZnO Nanocomposite Using Aloe-vera, Hibiscus Sabdariffa Plants and Their Antibacterial and Anti-fungi Activities
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The current study used extracts from the aloe vera (AV) plant and the hibiscus sabdariffa flower to make Ag-ZnO nanoparticles (NPs) and Ag-ZnO nanocomposites (NCs). Ag/ZnO NCs were compared to Ag NPs and ZnO NPs. They exhibited unique properties against bacteria and fungi that aren't present in either of the individual parts. The Ag-ZnO NCs from AV showed the best performance against E. coli, with an inhibition zone of up to 27 mm, compared to the other samples. The maximum absorbance peaks were observed at 431 nm and 410 nm for Ag NPs, at 374 nm and 377 nm for ZnO NPs and at 384 nm and 391 nm for Ag-ZnO NCs using AV leaf extract and hibiscus sabdariffa flower extract, respectively. Using field emission-scanning electron microscopes (FE-

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Publication Date
Mon Mar 15 2021
Journal Name
Al-academy
Anthropology and Representations of Magic in Arab Theatrical Text Harut and Marut's Play as a Model: وصال خلفة كاظم البكري
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The research (Anthropology and Representations of magic in Arab Theatrical Text, Harut and Marut's play as a Model) is concerned with studying magic and the forms of its presence in the theatrical text in different human cultures where it belongs. The research consists of four chapters.
The first chapter includes the research problem that revolves around the following questions: (what is the mechanism of employing magic anthropology and its representations in the Arab theatrical text Harut and Marut's play as a model?), and the research importance which is attributed to the necessity of studying (magic) in the Arab theatrical text as it is considered the inauguration of one of the social phenomena that many researchers in the field o

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Publication Date
Sun Mar 20 2016
Journal Name
Al-academy
The mechanism of addition and subtraction in the industrial product and its relation to employment pressure: بـــان محمد شـاكر الطائي
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The Significance of this research comes as a result of the development occurring in various life fields including the field of technical and technological development in the domain of industrial products which are in direct touch with the receiver, and because the study of deletion and addition mechanism didn't Find the Scientific space through researches and Studies. On this basis , the aim of this study is defining the forms of deletion and addition mechanism in designing the industrial product in a way that fits the functional presser . As to the limitations of this study, they involve examples of readymade Turkish House furniture, which is available in Iraqi local markets in Baghdad city 2013. The study included four chapters. The fi

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Publication Date
Fri Jul 01 2022
Journal Name
Operative Dentistry
Interfacial Bond Strength and Morphology of Sound and Caries-affected Dentin Surfaces Bonded to Two Resin-modified Glass Ionomer Cements
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SUMMARY<sec> <title>Objective

To evaluate the shear bond strength and interfacial morphology of sound and caries-affected dentin (CAD) bonded to two resin-modified glass ionomer cements (RMGICs) after 24 hours and two months of storage in simulated body fluid at 37°C.

Methods and Materials

Sixty-four permanent human mandibular first molars (32 sound and 32 with occlusal caries, following the International Caries Detection and Assessment System) were selected. Each prepared substrate (sound and CAD) was co

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Publication Date
Sun Apr 30 2023
Journal Name
Al-kindy College Medical Journal
Prevalence of Burnout Syndrome and its Association with Job Title and Violence among Physicians in Baghdad: A Triangulated Methodology Study
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Background: Economic Globalization affects work condition by increasing work stress. Chronic work stress ended with burnout syndrome. Objectives: To estimate the prevalence of burnout syndrome and the association of job title, and violence with it among physicians in Baghdad, and to assess the burnout syndrome at patient and work levels by structured interviews. Subjects and Methods: A cross section study was conducted on Physicians in Baghdad. Sampling was a multistage, stratified sampling to control the confounders in the design phase. A mixed qualitative and quantitative approach (triangulation) was used. Quantitative method used self-administered questionnaires of Maslach Burn out Inventory. Qualitative approach used an open-end

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Publication Date
Tue Jun 30 2020
Journal Name
Membranes
Experimental and Theoretical Analysis of Lead Pb2+ and Cd2+ Retention from a Single Salt Using a Hollow Fiber PES Membrane
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The present work reports the performance of three types of polyethersulfone (PES) membrane in the removal of highly polluting and toxic lead Pb2+ and cadmium Cd2+ ions from a single salt. This study investigated the effect of operating variables, including pH, types of PES membrane, and feed concentration, on the separation process. The transport parameters and mass transfer coefficient (k) of the membranes were estimated using the combined film theory-solution-diffusion (CFSD), combined film theory-Spiegler-Kedem (CFSK), and combined film theory-finely-porous (CFFP) membrane transport models. Various parameters were used to estimate the enrichment factors, concentration polarization modulus, and Péclet number. The pH values signif

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Publication Date
Fri Nov 01 2024
Journal Name
Heliyon
Strength and Deformation of Encased Concrete Columns by I- Section Steel and I- Section GFRP Subjected to Different Load Conditions
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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Permeability Prediction and Facies Distribution for Yamama Reservoir in Faihaa Oil Field: Role of Machine Learning and Cluster Analysis Approach
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

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