Objectives: The purpose of this study was to refine a commercial car driving simulation for occupational research. As the effects of ethanol on driving behavior are well established, we choose alcohol as a test compound to investigate the performance of subjects during simulation.
Materials And Methods: We programmed a night driving scenario consisting of monotonous highway and a rural road on a Foerst F10-P driving simulator. Twenty healthy men, 19-30 years, participated in a pilot study. Subjects were screened for simulator sickness, followed by training on the simulator one hour in total. Experiments were performed in the morning on a separate day. Participants were randomized into either an alcoholized or a control group. All subjects drove two courses consisting of highway and rural road and were sober for the first course. During a 1 h break the ethanol group drank an alcoholic beverage to yield 0.06% blood alcohol concentration (BAC). Generalized linear mixed models were used to analyze the influence of alcohol on driving performance. Among others, independent variables were Simulator Sickness Questionnaire scores and subjective sleepiness.
Results: Subjects did not experience simulator sickness during the experiments. Mean BAC before the second test drive was 0.065% in the mildly intoxicated group. There was no clear-cut difference in the number of crashes between 2 groups. BAC of 0.1% would deteriorate mean braking reaction time by 237 ms (SE = 112, p < 0.05). Ethanol slightly impaired the tracking in the right-hand curves (p = 0.058). Braking reaction time improved by 86 ms (SE = 36, p < 0.05) for the second test drive, indicating a learning effect.
Conclusions: In sum, a clear ethanol effect was observed in the driving simulation. This simulation seems suitable for occupational research and produces little simulator sickness. Controlling for possible learning effects is recommended in driving simulation studies.
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http://dx.doi.org/10.2478/s13382-013-0164-5 | DOI Listing |
Mar Pollut Bull
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Departamento de Biología, Facultad de Ciencias del Mar y Ambientales, Instituto Universitario de Investigación Marina (INMAR), Campus de Excelencia Internacional del Mar (CEI·MAR), Universidad de Cádiz, 11510 Puerto Real, Cádiz, Spain.
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College of Intelligent systems Science and Engineering, Harbin Engineering University, Harbin, 150006, China.
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January 2025
School of Spatial Planning and Design, Hangzhou City University, Hangzhou, 310015, China.
Analysis of the spatiotemporal trends of urban scale and urban vitality on ecosystem services balance provides an essential basis for regional sustainable development. This study employs the Spatial Durbin Model (SDM), Spatial Autoregressive Model (SAR), and Geographically and Temporally Weighted Regression (GTWR) to effectively capture spatiotemporal associations between urban scale, urban vitality, and ecosystem services supply-demand balance, providing a detailed view of regional variations. The integrated framework combines spatiotemporal analysis, predictive scenario simulation, and importance-performance analysis to quantify and strategize urban impacts on ESs.
View Article and Find Full Text PDFThe increasing availability of coarse-scale climate simulations and the need for ready-to-use high-resolution variables drive the climate community to the challenge of reducing computational resources and time for downscaling purposes. To this end, statistical downscaling is gaining interest as a potential strategy for integrating high-resolution climate information obtained through dynamical downscaling over limited years, providing a clear understanding of the gains and losses in combining dynamical and statistical downscaling. In this regard, several questions can be raised: (i) what is the performance of statistical downscaling, assuming dynamical downscaling as a reference over a shared time window; (ii) how much the performance of statistical downscaling is affected by changes in the number of years available for training; (iii) how does the climate normal considered for the training affect the predictions.
View Article and Find Full Text PDFJ Nucl Med
January 2025
Center for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts;
Radionuclides used for imaging and therapy can show high molecular specificity in the body with appropriate targeting ligands. We hypothesized that local energy delivered by molecularly targeted radionuclides could chemically activate prodrugs at disease sites while avoiding activation in off-target sites of toxicity. As proof of principle, we tested whether this strategy of radionuclide-induced drug engagement for release (RAiDER) could locally deliver combined radiation and chemotherapy to maximize tumor cytotoxicity while minimizing off-target exposure to activated chemotherapy.
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