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Study the Effect of Welding Heat Input on the Microstructure, Hardness, and Impact Toughness of AISI 1015 Steel
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In the present study, MIG welding is carried out on low carbon steel type (AISI 1015) by using electrode ER308L of 1.5mm diameter with direct current straight polarity (DCSP). The joint geometry is of a single V-butt joint with one pass welding stroke for different plate thicknesses of 6, 8, and 10 mm. In welding experiments, AISI 1015 plates with dimensions of 200×100mm and edge angle of 60o from both sides are utilized. In this work, three main parameters related to MIG welding process are investigated, which are welding current, welding speed, heat input and plate thickness, and to achieve that three groups of plates are employed each one consists of three plates. The results indicate that increasing the weld heat input (through changing the current and voltage) leads to an increase in widmanstatten ferrite (WF), acicular ferrite (AF) and polygonal ferrite (PF) in FZ region, and a reduction in grain size. It is observed that the micro-hardness of welded AISI 1015 plate increases as the weld heat input decreases. As well as increasing the weld heat input results in an increase in the width of WM and HAZ and a reduction in the impact energy of the weld joint of AISI 1015 at WM region. Also, it is noted the corrosion rate of weld joint increases with increase of Icorr due to increasing in welding current (heat input), corrosion rate increased up to (0.126µm/yr.) with increasing of heat input up to (1.27 KJ/mm).

 

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Publication Date
Tue Jul 09 2024
Journal Name
Diagnostics
A Novel Hybrid Machine Learning-Based System Using Deep Learning Techniques and Meta-Heuristic Algorithms for Various Medical Datatypes Classification
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea

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Publication Date
Sun Sep 01 2024
Journal Name
Baghdad Science Journal
Graphene Oxide Decorated with Nickel Cobaltite Nanoparticles as an Adsorbent for Cationic Methyl Green Dye: Kinetic, Isotherm, and Thermodynamic Studies
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‎تم في هذه الدراسة ، تزيين ‏رقائق أكسيد الجرافين (‏GO‏) بجسيمات ‏كوبلتيت النيكل النانوية ‏NiCo2O4‎‏(‏NC‏) عن طريق الترسيب في ‏الموقع ، وتم استخدام المتراكب ‏المحضر (‏NC: GO‏) كسطح ماز لإزالة ‏صبغة الميثيل الخضراء ( ‏MG‏) من ‏المحاليل المائية. تم التحقق من ‏التغطية الناجحة لأوكسيد الجرافين ‏بجزيئات كوبلتيت النيكل النانوية ‏‏(‏NC‏) باستخدام دراسات ‏FT-IR‏ وحيود ‏الأشعة السينية (‏XRD‏). كانت أحجام  ‏الجسيم

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Automated Stand-alone Surgical Safety Evaluation for Laparoscopic Cholecystectomy (LC) using Convolutional Neural Network and Constrained Local Models (CNN-CLM)
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In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

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Publication Date
Thu Jan 30 2014
Journal Name
Al-kindy College Medical Journal
Managementt o f non traumatic A vascular Necrosis off Femoral Head at precollapse stage with Core Decompression and tibial Bone Grafting
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 Avascular necrosis have always presented great challenges to orthopedic surgeons and patients, remain in many ways today the unsolved dilemma. Varieties of non-vascularized bone grafting techniques preceded by core decompression have been proposed with varying degrees of success. O bb j ee cc t i vv ee ss : The aim of this study is to review the the value of core decompression and non-vascularized tibial bone strip graft treatment for early stages of non-traumatic osteonecrosis stage II & III according to stein burg staging . M ee t hh oo dd ss : prospectively reviewed 26 patients (32 hips) with osteonecrosis of the femoral head between June 2006 and December 2013 at Imam Ali hospital in Sader city & Al-Wasity teaching hosp

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Publication Date
Sun Dec 10 2017
Journal Name
Journal Of Pharmaceutical, Chemical And Biological Sciences
BRCA1 is Overexpressed in Breast Cancer Cell Lines and is Negatively Regulated by E2F6 in Normal but not Cancerous Breast Cells
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This study focused on the expression and regulation of BRCA1 in breast cancer cell lines compared to normal breast. BRCA1 transcript levels were assessed by real time quantitative polymerase chain reaction (RT-qPCR) in the cancer cell lines. Our data show overexpression of BRCA1 mRNA level in all the studied breast cancer cell lines: MCF-7, T47D, MDA-MB-231 and MDA-MB-468 along with Jurkat, leukemia T-lymphocyte, the positive control, relative to normal breast tissue. To investigate whether a positive or negative correlation exists between BRCA1 and the transcription factor E2F6, three different si-RNA specific for E2F6 were used to transfect the normal and cancerous breast cell lines. Interestingly, strong negative relationship was found b

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Publication Date
Wed Jan 01 2025
Journal Name
International Journal Of Advanced Community Medicine
Health-promoting lifestyle profile and associated factors among medical staff working in a primary health care centers in AL-Rusafah 2022
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Abstract Background: The lifestyle of an individual significantly influences health-promoting behaviors. The World Health Organization defines health promotion as a mechanism enabling people to increase control over and improve their health. This study aimed to evaluate the health promoting lifestyle profile of medical staff working in primary health care centers of Al-Rusafa, Baghdad.

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Publication Date
Fri Oct 02 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Caries-Experiences and Dental Treatment Needs among (16-18 Years Old) in High School Girls in Al-Mussayb City, Babylon Governorate
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Background: Numerous epidemiological studies were conducted in Iraq, concerning dental caries and related etiological factors however; most of these studies were concerned with pre-and primary school children and/or those at index ages (12-15years old). At the time studies regarding older ages are very limited. This study was done to determine the prevalence and severity of dental caries and treatment need among high schools girls (16-18 years old) in Al-Mussayb city, Babylon Governorate. Thus, it can be considered as a base line data that allows studying dental caries among permanent dentition, also allows the comparison with other studies in other parts of the world. Material and Method: A total number of 900 high school girls were examin

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Publication Date
Sat Jan 31 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
Low-complexity Deep Learning for Joint Channel-type Identification and SNR Estimation in MIMO-OFDM Using CNN–BRNN with LUT Labels
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Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
Increasing confidence in full field modelling and water flood planning for a giant reservoir under primary depletion through Material Balance modelling
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Abstract<p>One of the principle inputs to project economics and all business decisions is a realistic production forecast and a practical and achievable development plan (i.e. waterflood). Particularly this becomes challenging in supergiant oil fields with medium to low lateral connectivity. The main objectives of the Production Forecast and feasibility study for water injection are:</p><p>1- Provide an overview of the total expected production profile, expected wells potential/spare capacity, water breakthrough timing and water cut development over time</p><p>2- Highlight the requirements to maintain performance, suggest the optimum developmen</p> ... Show More
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Publication Date
Fri Oct 02 2026
Journal Name
Journal Of Physical Education
Specifying Standard Scores and Levels for Some Physical Variables as Indicators for Selecting Youth Soccer Players Aged (17 – 19) years Old
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