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Novel Candidate Single Nucleotide Polymorphisms of ERCC2 Gene that Influence Colorectal Cancer Susceptibility
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Colorectal cancer (CRC) is the most common gastrointestinal malignancy and one of the top ten common cancers worldwide with approximately 2 million cases. There are multiple risk factors that could lead to CRC emergence; of which are genetic polymorphisms. Excision repair cross-complementing group 2 (ERCC2) gene encodes for ERCC2 enzyme which plays a crucial role in maintaining genomic integrity by removing DNA adducts. Several studies suggested that there could be a link between genetic polymorphisms of ERCC2 gene and the risk of CRC development. Hence the present study aims to validate the relationship between the following ERCC2 single nucleotide polymorphisms (rs13181, rs149943175, rs530662943, and rs1799790) and CRC susceptibility. A total of 121 participants were enrolled in this case control study; 72 CRC patients and 49 apparently healthy individuals. CRC patients aged 56.34 ±11.89 years and 41 (56.9%) were males while control group were 53.20 ± 17.33 years and 26 (53.1%) of them are males. Genotyping was performed using polymerase chain reaction (PCR) followed by Sanger sequencing then the association between genetic polymorphisms and CRC susceptibility was examined. GA genotype and A allele of rs149943175 were associated with lower risk of CRC development [OR 95% (CI)= 0.3 (0.1-0.88); P=0.02 and 0.4 (0.1-0.9); P=0.03 respectively]. However, GA genotype and A allele carriers of rs530662943 had significantly increased risk compared to GG genotype and G allele respectively [OR 95%(CI)= 5.17 (1.1-24.0); P=0.03 and 4.76 (1.0-21.6); P=0.04 respectively]. Additional stratified analyses showed that carriers of heterozygous genotype of rs149943175 who non-smokers, females or BMI figures less than 25 are less likely to develop CRC compared to wild genotype carriers. Taken together, genetic polymorphisms of ERCC2 modulate the susceptibility of CRC malignancy.

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm
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Incremental sheet metal forming is a modern technique of sheet metal forming in which a uniform sheet is locally deformed during the progressive action of a forming tool. The tool movement is governed by a CNC milling machine. The tool locally deforms by this way the sheet with pure deformation stretching. In SPIF process, the research is concentrate on the development of predict models for estimate the product quality. Using simulated annealing algorithm (SAA), Surface quality in SPIF has been modeled. In the development of this predictive model, spindle speed, feed rate and step depth have been considered as model parameters. Maximum peak height (Rz) and Arithmetic mean surface roughness (Ra) are used as response parameter to assess th

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Publication Date
Mon May 27 2019
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Process Parameters That Affecting on Surface Roughness in Multi-Point Forming Process Using ANOVA Algorithm
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Multipoint forming process is an engineering concept which means that the working surface of the punch and die is produced as hemispherical ends of individual active elements (called pins), where each pin can be independently, vertically displaced using a geometrically reconfigurable die. Several different products can be made without changing tools saved precious production time. Also, the manufacturing of very expensive rigid dies is reduced, and a lot of expenses are saved. But the most important aspects of using such types of equipment are the flexibility of the tooling. This paper presents an experimental investigation of the effect of three main parameters which are blank holder, rubber thickness and forming speed th

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Publication Date
Fri Sep 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Real Time Wireless Monitoring and Controlling of 3-D Single Point Incremental Tool
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Maintenance of machine tools can be improved significantly by analyzing the operating of manufacturing process with the real-time monitoring system for 3-D single point deformation measurements. Therefore, the process of manufacturing could be optimized with less cost. Recently, wireless technology and internet of things (IOT) applied on intelligent machine has witnessed a significant advance with augmented virtuality, the analysis and the process certainly would contribute to enhance the intelligence of that machine. This paper presents a group of the wireless sensors and 3D animation technologies for data monitoring and analyzing. Three degree of freedom robotic hand structure has been selected as a prototype to be form the process of the

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Publication Date
Mon Dec 04 2017
Journal Name
Al-qadisiyah Journal For Administrative And Economic Sciences
Survival Function Estimating of Single age Groups for Generalized Gamma Distribution with Simulation.
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The analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the

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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
Single-Phase Grid-Tied Transformerless Inverter of Zero Leakage Current for PV System
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Publication Date
Wed Jan 01 2014
Journal Name
American Journal Of Mathematics And Statistics
Preliminary Test Single Stage Shrinkage Estimator for the Scale Parameter of Gamma Distribution
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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Engineering
Improving the productivity of single effect double slope solar still by modification simple
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The present paper is an experimental study to improve the productivity of the conventional solar still. This done by modifying conventional still in a way that the distilled basin is larger than distillation basin, thus providing an increase in the condensation surface and speeding up the condensation process. Moreover, increase in the dimensions of the distilled base helps coupling reflective panels to the distilled base to reflect incident solar radiation to the distillation basin. For this purpose , two solar stills were made, one conventional designand another made according to the proposed design. The two solar stills were tested during the period from February to July 2009 under varying weather conditions of Basra, Iraq (latitude o

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Publication Date
Wed Mar 01 2023
Journal Name
Journal Of Engineering
Comparative Evaluation of Roundabout Capacities Methods for Single-lane and Multi-lane Roundabout
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A roundabout is a highway engineering concept meant to calm traffic, increase safety, reduce stop-and-go travel, reduce accidents and congestion, and decrease traffic delays. It is circular and facilitates one-way traffic flow around a central point. The first part of this study evaluated the principles and methods used to compare the capacity methods of roundabouts with different traffic conditions and geometric configurations. These methods include gap acceptance, empirical, and simulation software methods. Previous studies mentioned in this research used various methods and other new models developed by several researchers. However, this paper's main aim is to compare different roundabout capacity models for acceptabl

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Publication Date
Sun Dec 01 2019
Journal Name
Saudi Medical Journal
The diagnostic power of circulating micro ribonucleic acid 34a in combination with cancer antigen 15-3 as a potential biomarker of breast cancer
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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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