École Polytechnique Fédérale de Lausanne

About: École Polytechnique Fédérale de Lausanne is a facility organization based out in Lausanne, Switzerland. It is known for research contribution in the topics: Population & Catalysis. The organization has 44041 authors who have published 98296 publications receiving 4372092 citations. The organization is also known as: EPFL & ETHL.

Quantized vortices in an exciton–polariton condensate

Abstract: When a superfluid—such as liquid helium—is set in rotation, vortices appear in which circulation around a closed loop can take only discrete values. Such quantized vortices have now been observed in a solid-state system—a Bose–Einstein condensate made of exciton polaritons. One of the most striking quantum effects in an interacting Bose gas at low temperature is superfluidity. First observed in liquid 4He, this phenomenon has been intensively studied in a variety of systems for its remarkable features such as the persistence of superflows and the proliferation of quantized vortices1. The achievement of Bose–Einstein condensation in dilute atomic gases2 provided the opportunity to observe and study superfluidity in an extremely clean and well-controlled environment. In the solid state, Bose–Einstein condensation of exciton polaritons has been reported recently3,4,5,6. Polaritons are strongly interacting light–matter quasiparticles that occur naturally in semiconductor microcavities in the strong-coupling regime and constitute an interesting example of composite bosons. Here, we report the observation of spontaneous formation of pinned quantized vortices in the Bose-condensed phase of a polariton fluid. Theoretical insight into the possible origin of such vortices is presented in terms of a generalized Gross–Pitaevskii equation. Whereas the observation of quantized vortices is, in itself, not sufficient for establishing the superfluid nature of the non-equilibrium polariton condensate, it suggests parallels between our system and conventional superfluids.

Reduction of Abeta amyloid pathology in APPPS1 transgenic mice in the absence of gut microbiota.

Abstract: Alzheimer's disease is the most common form of dementia in the western world, however there is no cure available for this devastating neurodegenerative disorder. Despite clinical and experimental evidence implicating the intestinal microbiota in a number of brain disorders, its impact on Alzheimer's disease is not known. To this end we sequenced bacterial 16S rRNA from fecal samples of Aβ precursor protein (APP) transgenic mouse model and found a remarkable shift in the gut microbiota as compared to non-transgenic wild-type mice. Subsequently we generated germ-free APP transgenic mice and found a drastic reduction of cerebral Aβ amyloid pathology when compared to control mice with intestinal microbiota. Importantly, colonization of germ-free APP transgenic mice with microbiota from conventionally-raised APP transgenic mice increased cerebral Aβ pathology, while colonization with microbiota from wild-type mice was less effective in increasing cerebral Aβ levels. Our results indicate a microbial involvement in the development of Abeta amyloid pathology, and suggest that microbiota may contribute to the development of neurodegenerative diseases.

Neuromorphic computing with multi-memristive synapses

Abstract: Neuromorphic computing has emerged as a promising avenue towards building the next generation of intelligent computing systems. It has been proposed that memristive devices, which exhibit history-dependent conductivity modulation, could efficiently represent the synaptic weights in artificial neural networks. However, precise modulation of the device conductance over a wide dynamic range, necessary to maintain high network accuracy, is proving to be challenging. To address this, we present a multi-memristive synaptic architecture with an efficient global counter-based arbitration scheme. We focus on phase change memory devices, develop a comprehensive model and demonstrate via simulations the effectiveness of the concept for both spiking and non-spiking neural networks. Moreover, we present experimental results involving over a million phase change memory devices for unsupervised learning of temporal correlations using a spiking neural network. The work presents a significant step towards the realization of large-scale and energy-efficient neuromorphic computing systems.

The Evolution of Research on Computer-Supported Collaborative Learning

Abstract: This chapter summarizes two decades of research on computer-supported collaborative learning (CSCL). We first review the key idea that has emerged, namely the fact that collaboration among peers can be “designed”, that is, directly or indirectly shaped by the CSCL environment. Second, we stress the fact that affective and motivational aspects that influence collaborative learning have been neglected by experimental CSCL researchers. Finally, we point out the emergence of a new trend or new challenge: integration of CSCL activities into larger pedagogical scenarios that include multiple activities and must be orchestrated in real time by the teacher.