ParisTech

About: ParisTech is a education organization based out in Paris, France. It is known for research contribution in the topics: Finite element method & Residual stress. The organization has 1888 authors who have published 1965 publications receiving 55532 citations. The organization is also known as: Paris Institute of Technology & ParisTech Développement.

A questionnaire to measure the user experience in immersive virtual environments

Abstract: Most of the models of User eXperience (UX) in Immersive Virtual Environment (IVE) are partial due to the components and the measuring methods they suggest. We have presented in a previous work a holistic UX in IVE model, combining key components and influencing factors from the most common fields of Virtual Reality (education, entertainment and edutainment). We do not doubt that the best way to measure the UX in IVEs is to gather and compare results from the appropriate subjective methods with the appropriate objective methods. Nevertheless, in this paper, we chose to focus only on the questionnaire method. Indeed, most of components can be measured through questionnaires. The objective of this paper is to rely on the components of our UX model to select appropriate existing questionnaires and finally choose the more suitable items to create our own mixed questionnaire. First, this paper reviews the questionnaires chosen to create our own. Finally, it proposes an elaboration of the final questionnaire.

Glucose Induces Slow-Wave Sleep by Exciting the Sleep-Promoting Neurons in the Ventrolateral Preoptic Nucleus: A New Link between Sleep and Metabolism

Abstract: Sleep-active neurons located in the ventrolateral preoptic nucleus (VLPO) play a crucial role in the induction and maintenance of slow-wave sleep (SWS). However, the cellular and molecular mechanisms responsible for their activation at sleep onset remain poorly understood. Here, we test the hypothesis that a rise in extracellular glucose concentration in the VLPO can promote sleep by increasing the activity of sleep-promoting VLPO neurons. We find that infusion of a glucose concentration into the VLPO of mice promotes SWS and increases the density of c-Fos-labeled neurons selectively in the VLPO. Moreover, we show in patch-clamp recordings from brain slices that VLPO neurons exhibiting properties of sleep-promoting neurons are selectively excited by glucose within physiological range. This glucose-induced excitation implies the catabolism of glucose, leading to a closure of ATP-sensitive potassium ( K ATP ) channels. The extracellular glucose concentration monitors the gating of K ATP channels of sleep-promoting neurons, highlighting that these neurons can adapt their excitability according to the extracellular energy status. Together, these results provide evidence that glucose may participate in the mechanisms of SWS promotion and/or consolidation. SIGNIFICANCE STATEMENT Although the brain circuitry underlying vigilance states is well described, the molecular mechanisms responsible for sleep onset remain largely unknown. Combining in vitro and in vivo experiments, we demonstrate that glucose likely contributes to sleep onset facilitation by increasing the excitability of sleep-promoting neurons in the ventrolateral preoptic nucleus (VLPO). We find here that these neurons integrate energetic signals such as ambient glucose directly to regulate vigilance states accordingly. Glucose-induced excitation of sleep-promoting VLPO neurons should therefore be involved in the drowsiness that one feels after a high-sugar meal. This novel mechanism regulating the activity of VLPO neurons reinforces the fundamental and intimate link between sleep and metabolism.

A Multidimensional Data-Driven Sparse Identification Technique: The Sparse Proper Generalized Decomposition

Abstract: Sparse model identification by means of data is especially cumbersome if the sought dynamics live in a high dimensional space. This usually involves the need for large amount of data, unfeasible in such a high dimensional settings. This well-known phenomenon, coined as the curse of dimensionality, is here overcome by means of the use of separate representations. We present a technique based on the same principles of the Proper Generalized Decomposition that enables the identification of complex laws in the low-data limit. We provide examples on the performance of the technique in up to ten dimensions.

Drop production and tip-streaming phenomenon in a microfluidic flow-focusing device via an interfacial chemical reaction.

Abstract: Microfluidic flow-focusing technology is used to investigate the effect on drop formation due to the production of a surfactant via an interfacial chemical reaction. The reactants are an aqueous so...