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Rheumatoid arthritis (RA) is a chronic inflammatory disease characterized by synovial hyperplasia and progressive joint destruction. Rheumatoid arthritis synovial fibroblasts (RASFs) are leading cells in joint erosion and contribute actively to inflammation. RASFs show an activated phenotype that is independent of the inflammatory environment and requires(More)
Predicting driver behavior is a key component for Advanced Driver Assistance Systems (ADAS). In this paper, a novel approach based on Support Vector Machine and Bayesian filtering is proposed for online lane change intention prediction. The approach uses the multiclass probabilistic outputs of the Support Vector Machine as an input to the Bayesian filter,(More)
Active rheumatoid arthritis originates from few joints but subsequently affects the majority of joints. Thus far, the pathways of the progression of the disease are largely unknown. As rheumatoid arthritis synovial fibroblasts (RASFs) which can be found in RA synovium are key players in joint destruction and are able to migrate in vitro, we evaluated the(More)
With the objective to improve road safety, the automotive industry is moving toward more " intelligent " vehicles. One of the major challenges is to detect dangerous situations and react accordingly in order to avoid or mitigate accidents. This requires predicting the likely evolution of the current traffic situation, and assessing how dangerous that future(More)
Understanding dynamic scenes at road intersections is both crucial and challenging for intelligent vehicles. In order to detect potentially dangerous situations, algorithms are needed that can interpret the behaviour of the actors in the scene and predict its likely evolution. The diculty of this task arises from the large number of possible scenarios. The(More)
We propose a learning-based method for the longitudinal control of an autonomous vehicle on the highway. We use a driver model to generate acceleration inputs which are used as a reference by a model predictive controller. The driver model is trained using real driving data, so that it can reproduce the driver's behavior. We show the system's ability to(More)
We present a framework for autonomous driving which can learn from human demonstrations, and we apply it to the longitudinal control of an autonomous car. Offline, we model car-following strategies from a set of example driving sequences. Online, the model is used to compute accelerations which replicate what a human driver would do in the same situation.(More)
Extracellular RNA (exRNA) has been characterized as a molecular alarm signal upon cellular stress or tissue injury and to exert biological functions as a proinflammatory, prothrombotic, and vessel permeability-regulating factor. In this study, we investigated the contribution of exRNA and its antagonist RNase1 in a chronic inflammatory joint disease,(More)
INTRODUCTION Rheumatoid arthritis synovial fibroblasts (RASF) are key players in synovial pathophysiology and are therefore examined extensively in various experimental approaches. We evaluated, whether passaging during culture and freezing has effects on gene expression and cell proliferation. METHODS RASF were passaged for up to 8 passages. RNA was(More)
Intersections are the most complex and hazardous areas of the road network, and 89% of accidents at intersection are caused by driver error. We focus on these accidents and propose a novel approach to risk assessment: in this work dangerous situations are identified by detecting conflicts between intention and expectation, i.e. between what drivers intend(More)