84 THE APPLICATIONS AND LIMITATIONS OF TIME/ACTIVITY DATA FOR EXPOSURE ASSESSMENT

Epidemiology ◽  
1995 ◽  
Vol 6 (2) ◽  
pp. S22
Author(s):  
M Sehwab
Keyword(s):  
Exposure Assessment ◽  
Activity Data ◽  
Time Activity

Human Exposure Assessment II: Quantifying and Reducing the Uncertainties

1992 ◽  
Vol 8 (5) ◽  
pp. 321-342 ◽  
Author(s):  
Gary K. Whitmyre ◽  
Jeffrey H. Driver ◽  
Michael E. Ginevan ◽  
Robert G. Tardiff ◽  
Scott R. Baker
Keyword(s):  
Exposure Assessment ◽  
Human Exposure ◽  
Absorbed Dose ◽  
Assessment Process ◽  
Alternative Methods ◽  
Bivariate Analysis ◽  
Activity Data ◽  
Time Activity ◽  
Exposed Individual ◽  
Human Exposure Assessment

Alternative methods of human exposure assessment that reduce and/or allow quantification of the uncertainties associated with exposure estimates are surveyed and illustrated. These alternative approaches include (1) use of more appropriate exposure parameter default values rather than values that result in extreme exposure estimates; (2) incorporation of time-activity data to better define appropriate exposure duration values; (3) the use of reasonable exposure scenarios rather than the traditional Maximally Exposed Individual (MEI) approach; (4) the use of stochastic approaches such as Monte Carlo-based and information analysis-based methods; (5) use of bivariate analysis to identify the extent to which interdependencies between different exposure parameters affect the distribution of exposure estimates; (6) use of less-than-lifetime exposure and risk assessment; and (7) incorporation of physiological considerations relevant to absorbed dose estimation, including route-specific impacts, use of improved absorption factors, and application of pharmacokinetic models. Other ways to improve the exposure assessment process, including assuring statistical equivalency in comparing different exposure estimates and incorporation of sensitive subpopulation considerations are also discussed, as are key research needs.

scholarly journals Using smartphones to collect time–activity data for long-term personal-level air pollution exposure assessment

2014 ◽  
Vol 26 (4) ◽  
pp. 356-364 ◽  
Author(s):  
Mark L Glasgow ◽  
Carole B Rudra ◽  
Eun-Hye Yoo ◽  
Murat Demirbas ◽  
Joel Merriman ◽  
...  
Keyword(s):  
Air Pollution ◽  
Exposure Assessment ◽  
Activity Data ◽  
Time Activity ◽  
Air Pollution Exposure ◽  
Personal Level ◽  
Pollution Exposure

scholarly journals Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1406
Author(s):  
Rok Novak ◽  
David Kocman ◽  
Johanna Amalia Robinson ◽  
Tjaša Kanduč ◽  
Dimosthenis Sarigiannis ◽  
...  
Keyword(s):  
Heart Rate ◽  
Particulate Matter ◽  
Low Cost ◽  
Minute Ventilation ◽  
Dose Assessment ◽  
Sensor Data ◽  
Activity Data ◽  
Time Activity ◽  
Activity Monitors ◽  
Coarse Information

Low-cost sensors can be used to improve the temporal and spatial resolution of an individual’s particulate matter (PM) intake dose assessment. In this work, personal activity monitors were used to measure heart rate (proxy for minute ventilation), and low-cost PM sensors were used to measure concentrations of PM. Intake dose was assessed as a product of PM concentration and minute ventilation, using four models with increasing complexity. The two models that use heart rate as a variable had the most consistent results and showed a good response to variations in PM concentrations and heart rate. On the other hand, the two models using generalized population data of minute ventilation expectably yielded more coarse information on the intake dose. Aggregated weekly intake doses did not vary significantly between the models (6–22%). Propagation of uncertainty was assessed for each model, however, differences in their underlying assumptions made them incomparable. The most complex minute ventilation model, with heart rate as a variable, has shown slightly lower uncertainty than the model using fewer variables. Similarly, among the non-heart rate models, the one using real-time activity data has less uncertainty. Minute ventilation models contribute the most to the overall intake dose model uncertainty, followed closely by the low-cost personal activity monitors. The lack of a common methodology to assess the intake dose and quantifying related uncertainties is evident and should be a subject of further research.

Internal radionuclide therapy

2006 ◽  
Vol 45 (06) ◽  
pp. 269-272 ◽  
Author(s):  
M. Landmann ◽  
A. Wunderlich ◽  
T. Kull ◽  
F. M. Mottaghy ◽  
S. N. Reske ◽  
...  
Keyword(s):  
Scatter Correction ◽  
Maximum Intensity Projection ◽  
Region Growing ◽  
Software Tool ◽  
Good Clinical Practice ◽  
Activity Data ◽  
Time Activity ◽  
Tomographic Data ◽  
Planar Approach ◽  
And Cluster Analysis

SummaryAim: Accurate dosimetry must be performed for each patient before therapy with unsealed radionuclides. Recently, the software tool ULMDOS was developed to facilitate planar dosimetric calculations and to support traceability and documentation as a prerequisite for good clinical practice. Here, the extended version of ULMDOS for processing of tomographic data is presented. Methods: ULMDOS is developed in IDL 6.1 (Interactive Data Language) under Windows XP/2000. Serial tomographic data can be loaded in an ECAT7 or DICOM format, and presented as maximum intensity projection. The definition of volumes of interest is supported by various tools (e.g., freehand, isocontour, polygon), region growing, and cluster analysis. Residence times are calculated from fits of the time activity data to exponential functions. Results, discussion: Quantitative 3-dimensional data allow performing a more individualized dosimetry, as problems due to organ overlay, insufficient attenuation and scatter correction in the planar approach can be avoided. For traceability, documentation, retrospective examination and later processing all data can be saved in binary or ASCII format. Dosimetric calculations can be conducted within a single environment, thus it spares the time-consuming transfer of data between different software tools.

scholarly journals Effects of Individual and Environmental Factors on GPS-Based Time Allocation in Urban Microenvironments Using GIS

2018 ◽  
Vol 8 (10) ◽  
pp. 2007 ◽  
Author(s):  
Audrius Dėdelė ◽  
Auksė Miškinytė ◽  
Irma Česnakaitė ◽  
Regina Gražulevičienė
Keyword(s):  
Environmental Factors ◽  
Exposure Assessment ◽  
Time Allocation ◽  
Activity Patterns ◽  
Personal Exposure ◽  
Health Impact ◽  
Individual Characteristics ◽  
Time Activity ◽  
Study Results ◽  
The Impact

Time-activity patterns are an essential part of personal exposure assessment to various environmental factors. People move through different environments during the day and they have different daily activity patterns which are significantly influenced by individual characteristics and the residential environment. In this study, time spent in different microenvironments (MEs) were assessed for 125 participants for 7 consecutive days to evaluate the impact of individual characteristics on time-activity patterns in Kaunas, Lithuania. The data were collected with personal questionnaires and diaries. The global positioning system (GPS) sensor integrated into a smartphone was used to track daily movements and to assess time-activity patterns. The study results showed that behavioral and residential greenness have a statistically significant impact on time spent indoors. These results underline the high influence of the individual characteristics and environmental factors on time spent indoors, which is an important determinant for exposure assessment and health impact assessment studies.

scholarly journals Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhu Liu ◽  
Philippe Ciais ◽  
Zhu Deng ◽  
Ruixue Lei ◽  
Steven J. Davis ◽  
...  
Keyword(s):  
World War Ii ◽  
Real Time ◽  
Energy Use ◽  
World War ◽  
Economic Activities ◽  
Activity Data ◽  
Time Activity ◽  
Country Level ◽  
Economic Downturns ◽  
Global Emissions

AbstractThe COVID-19 pandemic is impacting human activities, and in turn energy use and carbon dioxide (CO2) emissions. Here we present daily estimates of country-level CO2 emissions for different sectors based on near-real-time activity data. The key result is an abrupt 8.8% decrease in global CO2 emissions (−1551 Mt CO2) in the first half of 2020 compared to the same period in 2019. The magnitude of this decrease is larger than during previous economic downturns or World War II. The timing of emissions decreases corresponds to lockdown measures in each country. By July 1st, the pandemic’s effects on global emissions diminished as lockdown restrictions relaxed and some economic activities restarted, especially in China and several European countries, but substantial differences persist between countries, with continuing emission declines in the U.S. where coronavirus cases are still increasing substantially.

A modeling approach for quantifying tumor hypoxia with [F-18]fluoromisonidazole PET time-activity data

1995 ◽  
Vol 22 (7) ◽  
pp. 1127-1139 ◽  
Author(s):  
J. J. Casciari ◽  
M. M. Graham ◽  
J. S. Rasey
Keyword(s):  
Tumor Hypoxia ◽  
Activity Data ◽  
Time Activity ◽  
Modeling Approach

Evaluating pulmonary vascular permeability with radiolabeled proteins: an error analysis

1990 ◽  
Vol 68 (4) ◽  
pp. 1696-1706 ◽  
Author(s):  
M. A. Mintun ◽  
T. E. Warfel ◽  
D. P. Schuster
Keyword(s):  
Vascular Permeability ◽  
Radiation Detection ◽  
Compartment Model ◽  
Physical Factors ◽  
Activity Data ◽  
Pulmonary Vascular Permeability ◽  
Time Activity ◽  
Positron Emission ◽  
Transcapillary Escape Rate ◽  
Activity Measurements

Using techniques of mathematical simulation, we compared two methods of evaluating pulmonary vascular permeability, i.e., transvascular protein flux. Both methods calculate a transport rate constant [pulmonary transcapillary escape rate (PTCER)] after making external radiation detection measurements of an intravenously administered radiolabeled protein. With one method, lung tissue time-activity data are acquired by positron emission tomography (PET) and are interpreted with a two-compartment model. With the other method, the time-activity data are acquired with simple detector probes and are interpreted by linear regression after normalizing for various physical factors (slope-intercept or SI method). The results show that significant errors in calculating PTCER can result from using the SI method, because it ignores the effects of back-flux on the tissue time-activity measurements. Both methods produce errors if the data analysis includes activity from vascular volumes not involved in tracer exchange with the extravascular compartment. Significant errors can also occur with the PET method, particularly when permeability is nearly normal, if pulmonary vascular volume changes significantly during the period of data collection. On balance, the PET method appears to be the method of choice for accurately evaluating pulmonary vascular permeability by protein flux measurements, although both methods may be useful in clinical applications.

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