Effects of Age and Task Load on Drivers’ Response Accuracy and Reaction Time When Responding to Traffic Lights

International audienceDue to population aging, elderly drivers represent an increasing proportion of car drivers. Yet, how aging alters sensorimotor functions and impacts driving safety remains poorly understood. This paper aimed at assessing to which extent elderly drivers are sensitive to various task loads and how this affects the reaction time (RT) in a driving context. Old and middle-aged people completed RT tasks which reproduced cognitive demands encountered while driving. Participants had to detect and respond to traffic lights or traffic light arrows as quickly as possible, under three experimental conditions of incremental difficulty. In both groups, we hypothesized that decision-making would be impacted by the number of cues to be processed. The first test was a simple measure of RT. The second and third tests were choice RT tasks requiring the processing of 3 and 5 cues, respectively. Responses were collected within a 2 s time-window. Otherwise, the trial was considered a no-response. In both groups, the data revealed that RT, error rate (incorrect answers), and no-response rate increased along with task difficulty. However, the middle-aged group outperformed the elderly group. The RT difference between the two groups increased drastically along with task difficulty. In the third test, the rate of no-response suggested that elderly drivers needed more than 2 s to process complex information and respond accurately. Both prolonged RT and increased no-response rate, especially for difficult tasks, might attest an impairment of cognitive abilities in relation to aging. Accordingly, casual driving conditions for young drivers may be particularly complex and stressful for elderly people who should thus be informed about the effects of normal aging upon driving

Fuzzy hidden Markov chains segmentation for volume determination and quantitation in PET.

International audienceAccurate volume of interest (VOI) estimation in PET is crucial in different oncology applications such as response to therapy evaluation and radiotherapy treatment planning. The objective of our study was to evaluate the performance of the proposed algorithm for automatic lesion volume delineation; namely the fuzzy hidden Markov chains (FHMC), with that of current state of the art in clinical practice threshold based techniques. As the classical hidden Markov chain (HMC) algorithm, FHMC takes into account noise, voxel intensity and spatial correlation, in order to classify a voxel as background or functional VOI. However the novelty of the fuzzy model consists of the inclusion of an estimation of imprecision, which should subsequently lead to a better modelling of the 'fuzzy' nature of the object of interest boundaries in emission tomography data. The performance of the algorithms has been assessed on both simulated and acquired datasets of the IEC phantom, covering a large range of spherical lesion sizes (from 10 to 37 mm), contrast ratios (4:1 and 8:1) and image noise levels. Both lesion activity recovery and VOI determination tasks were assessed in reconstructed images using two different voxel sizes (8 mm3 and 64 mm3). In order to account for both the functional volume location and its size, the concept of % classification errors was introduced in the evaluation of volume segmentation using the simulated datasets. Results reveal that FHMC performs substantially better than the threshold based methodology for functional volume determination or activity concentration recovery considering a contrast ratio of 4:1 and lesion sizes of <28 mm. Furthermore differences between classification and volume estimation errors evaluated were smaller for the segmented volumes provided by the FHMC algorithm. Finally, the performance of the automatic algorithms was less susceptible to image noise levels in comparison to the threshold based techniques. The analysis of both simulated and acquired datasets led to similar results and conclusions as far as the performance of segmentation algorithms under evaluation is concerned

Multilevel Contracts for Trusted Components

This article contributes to the design and the verification of trusted components and services. The contracts are declined at several levels to cover then different facets, such as component consistency, compatibility or correctness. The article introduces multilevel contracts and a design+verification process for handling and analysing these contracts in component models. The approach is implemented with the COSTO platform that supports the Kmelia component model. A case study illustrates the overall approach.Comment: In Proceedings WCSI 2010, arXiv:1010.233

Limiting distributions for explosive PAR(1) time series with strongly mixing innovation

This work deals with the limiting distribution of the least squares estimators of the coefficients a r of an explosive periodic autoregressive of order 1 (PAR(1)) time series X r = a r X r--1 +u r when the innovation {u k } is strongly mixing. More precisely {a r } is a periodic sequence of real numbers with period P \textgreater{} 0 and such that P r=1 |a r | \textgreater{} 1. The time series {u r } is periodically distributed with the same period P and satisfies the strong mixing property, so the random variables u r can be correlated

The Significance of Madison Nguyen and the Rise of Vietnamese American Politics in San José, California: Analysis and Commentary

研究ノート(Research Note)application/pdfdepartmental bulletin pape

Associating Vehicles Automation With Drivers Functional State Assessment Systems: A Challenge for Road Safety in the Future

In the near future, vehicles will gradually gain more autonomous functionalities. Drivers’ activity will be less about driving than about monitoring intelligent systems to which driving action will be delegated. Road safety, therefore, remains dependent on the human factor and we should identify the limits beyond which driver’s functional state (DFS) may no longer be able to ensure safety. Depending on the level of automation, estimating the DFS may have different targets, e.g., assessing driver’s situation awareness in lower levels of automation and his ability to respond to emerging hazard or assessing driver’s ability to monitor the vehicle performing operational tasks in higher levels of automation. Unfitted DFS (e.g., drowsiness) may impact the driver ability respond to taking over abilities. This paper reviews the most appropriate psychophysiological indices in naturalistic driving while considering the DFS through exogenous sensors, providing the more efficient trade-off between reliability and intrusiveness. The DFS also originates from kinematic data of the vehicle, thus providing information that indirectly relates to drivers behavior. The whole data should be synchronously processed, providing a diagnosis on the DFS, and bringing it to the attention of the decision maker in real time. Next, making the information available can be permanent or intermittent (or even undelivered), and may also depend on the automation level. Such interface can include recommendations for decision support or simply give neutral instruction. Mapping of relevant psychophysiological and behavioral indicators for DFS will enable practitioners and researchers provide reliable estimates, fitted to the level of automation

Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks

International audienceIncreasing amounts of sequence data are becoming available for a wide range of non-model organisms. Investigating and modelling the metabolic behaviour of those organisms is highly relevant to understand their biology and ecology. As sequences are often incomplete and poorly annotated, draft networks of their metabolism largely suffer from incompleteness. Appropriate gap-filling methods to identify and add missing reactions are therefore required to address this issue. However, current tools rely on phenotypic or taxonomic information, or are very sensitive to the stoichiometric balance of metabolic reactions, especially concerning the co-factors. This type of information is often not available or at least prone to errors for newly-explored organisms. Here we introduce Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks. Meneco reformulates gap-filling as a qualitative combinatorial optimization problem, omitting constraints raised by the stoichiometry of a metabolic network considered in other methods, and solves this problem using Answer Set Programming. Run on several artificial test sets gathering 10,800 degraded Escherichia coli networks Meneco was able to efficiently identify essential reactions missing in networks at high degradation rates, outperforming the stoichiometry-based tools in scalability. To demonstrate the utility of Meneco we applied it to two case studies. Its application to recent metabolic networks reconstructed for the brown algal model Ectocarpus siliculosus and an associated bacterium Candidatus Phaeomarinobacter ectocarpi revealed several candidate metabolic pathways for algal-bacterial interactions. Then Meneco was used to reconstruct, from transcriptomic and metabolomic data, the first metabolic network for the microalga Euglena mutabilis. These two case studies show that Meneco is a versatile tool to complete draft genome-scale metabolic networks produced from heterogeneous data, and to suggest relevant reactions that explain the metabolic capacity of a biological system

Prehospital ticagrelor in ST-segment elevation myocardial infarction

Background:The direct-acting platelet P2Y receptor antagonist ticagrelor can reduce the incidence of major adverse cardiovascular events when administered at hospital admission to patients with ST-segment elevation myocardial infarction (STEMI). Whether prehospital administration of ticagrelor can improve coronary reperfusion and the clinical outcome is unknown. Methods: We conducted an international, multicenter, randomized, double-blind study involving 1862 patients with ongoing STEMI of less than 6 hours' duration, comparing prehospital (in the ambulance) versus in-hospital (in the catheterization laboratory) treatment with ticagrelor. The coprimary end points were the proportion of patients who did not have a 70% or greater resolution of ST-segment elevation before percutaneous coronary intervention (PCI) and the proportion of patients who did not have Thrombolysis in Myocardial Infarction flow grade 3 in the infarct-related artery at initial angiography. Secondary end points included the rates of major adverse cardiovascular events and definite stent thrombosis at 30 days. Results: The median time from randomization to angiography was 48 minutes, and the median time difference between the two treatment strategies was 31 minutes. The two coprimary end points did not differ significantly between the prehospital and in-hospital groups. The absence of ST-segment elevation resolution of 70% or greater after PCI (a secondary end point) was reported for 42.5% and 47.5% of the patients, respectively. The rates of major adverse cardiovascular events did not differ significantly between the two study groups. The rates of definite stent thrombosis were lower in the prehospital group than in the in-hospital group (0% vs. 0.8% in the first 24 hours; 0.2% vs. 1.2% at 30 days). Rates of major bleeding events were low and virtually identical in the two groups, regardless of the bleeding definition use

Sur la réponse transitoire d'une structure en alliage à mémoire de forme soumise à un impact

National audienceDans cet article sont présentées des évolutions du modèle RL nécessaires pour la résolution de problèmes de dynamique rapide. Le modèle initial, basé sur le comportement thermomécanique de l'alliage couplé à l'équation de la chaleur, a été implémenté dans le cadre de la dynamique basses fréquences dans des travaux antérieurs. L'utilisation de ce modèle non linéaire dans le cadre de la dynamique rapide (réponse de la structure à un impact) conduit à des solutions non physiques ou à des divergences des algorithmes d'intégration temporelle. Ces comportements sont principalement dus aux fortes non-linéarités des équations régissant les cinétiques de transformation entre les deux phases du matériau (austénite/martensite). L'adjonction d'un terme lissant dans les équations différentielles permet de faire converger les algorithmes sans perturber le comportement du modèle initial. Ce terme, d'un point de vue physique, traduit le fait que la transformation de phase ne se fait pas de façon instantanée, mais à une vitesse de propagation donnée. Les résultats issus d'un calcul éléments finis considérant une structure bidimensionnelle soumise à un impact sont présentés