Exposure Factor 2: Road Environment

2015 ◽  
pp. 226-235
Keyword(s):  
Exposure Factor

scholarly journals Optimasi Faktor Eksposi pada Pemeriksaan Radiografi Thorax menggunakan Computed Radiography

2020 ◽  
Vol 6 (1) ◽  
pp. 52-56
Author(s):  
Sri Sugiarti ◽  
Surip Surip ◽  
Merrytiana Fadila
Keyword(s):  
Radiation Dose ◽  
Nuclear Power ◽  
Radiation Safety ◽  
Computed Radiography ◽  
Reference Level ◽  
Radiographic Examination ◽  
Exposure Level ◽  
Exposure Factor ◽  
Chest Examination ◽  
Correlational Method

Concerning radiation safety must meet several radiation protection requirements which include justification or utilization of nuclear power, dose limitation, optimization of protection, and radiation safety. The purpose of this study was to determine the optimization of the exposure factor selection and determine the radiation dose received by the patient based on the selection of exposure factors on the thorax examination. The author observed the use of exposure factors on chest radiographic examination with a sample of 60 people. The design of this study uses the correlational method. The independent variables in this study are age, body weight, object thickness, kV, and mAs. Dependent variable exposure to radiation dose on chest examination. The conclusion of this study is the dose exposure level is influenced by age, object thickness, weight, and use of exposure factors which will then be obtained by the DRL (Diagnostic Reference Level) value.

EVALUATION OF TRANSPORT CONDITIONS OF TROOPS IN HIGH-MOBILITY MULTIPURPOSE MILITARY VEHICLES ON THE BASIS OF ACCELEROMETRIC DATA

2011 ◽  
Vol 159 (1) ◽  
pp. 253-260
Author(s):  
Tadeusz SMOLNICKI ◽  
Krzysztof JAMROZIAK ◽  
Mirosław BOCIAN ◽  
Mariusz KOSOBUDZKI
Keyword(s):  
High Mobility ◽  
Daily Exposure ◽  
Military Vehicles ◽  
Exposure Factor

The issues of driving comfort with regard to military vehicles transporting troops with their equipment are relatively new in available articles and published studies. This paper contains some information related to the driving comfort in high-mobility multipurpose military vehicles operated by the Polish Army. The authors used a daily exposure factor A(8) to evaluate the driving comfort.

Monte Carlo simulation of the exposure factor

2009 ◽  
Vol 18 (6) ◽  
pp. 2217-2222 ◽  
Author(s):  
Zhang Tao ◽  
Liu Yi-Bao ◽  
Yang Bo ◽  
Wu He-Xi ◽  
Gu Jin-Hu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Exposure Factor

scholarly journals Mining the Selective Remodeling of DNA Methylation in Promoter Regions to Identify Robust Gene-Level Associations With Phenotype

2021 ◽  
Vol 8 ◽  
Author(s):  
Yuan Quan ◽  
Fengji Liang ◽  
Si-Min Deng ◽  
Yuexing Zhu ◽  
Ying Chen ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Promoter Region ◽  
Biological Significance ◽  
Biological Efficiency ◽  
Body Region ◽  
Promoter Regions ◽  
Exposure Factor ◽  
Epigenetic Events ◽  
Gene Level ◽  
Disease Related Gene

Epigenetics is an essential biological frontier linking genetics to the environment, where DNA methylation is one of the most studied epigenetic events. In recent years, through the epigenome-wide association study (EWAS), researchers have identified thousands of phenotype-related methylation sites. However, the overlaps of identified phenotype-related DNA methylation sites between various studies are often quite small, and it might be due to the fact that methylation remodeling has a certain degree of randomness within the genome. Thus, the identification of robust gene-phenotype associations is crucial to interpreting pathogenesis. How to integrate the methylation values of different sites on the same gene and to mine the DNA methylation at the gene level remains a challenge. A recent study found that the DNA methylation difference of the gene body and promoter region has a strong correlation with gene expression. In this study, we proposed a Statistical difference of DNA Methylation between Promoter and Other Body Region (SIMPO) algorithm to extract DNA methylation values at the gene level. First, by choosing to smoke as an environmental exposure factor, our method led to significant improvements in gene overlaps (from 5 to 17%) between different datasets. In addition, the biological significance of phenotype-related genes identified by SIMPO algorithm is comparable to that of the traditional probe-based methods. Then, we selected two disease contents (e.g., insulin resistance and Parkinson’s disease) to show that the biological efficiency of disease-related gene identification increased from 15.43 to 44.44% (p-value = 1.20e–28). In summary, our results declare that mining the selective remodeling of DNA methylation in promoter regions can identify robust gene-level associations with phenotype, and the characteristic remodeling of a given gene’s promoter region can reflect the essence of disease.

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