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.

Combined Experimental and DFT-TDDFT Computational Study of Photoelectrochemical Cell Ruthenium Sensitizers

Abstract: We report a combined experimental and computational study of several ruthenium(II) sensitizers originated from the [Ru(dcbpyH2)2(NCS)2], N3, and [Ru(dcbpyH2)(tdbpy)(NCS)2], N621, (dcbpyH2 = 4,4‘-dicarboxy-2,2‘-bipyridine, tdbpy = 4,4‘-tridecyl-2,2‘-bipyridine) complexes. A purification procedure was developed to obtain pure N-bonded isomers of both types of sensitizers. The photovoltaic data of the purified N3 and N621 sensitizers adsorbed on TiO2 films in their monoprotonated and diprotonated state, exhibited remarkable power conversion efficiency at 1 sun, 11.18 and 9.57%, respectively. An extensive Density Functional Theory (DFT)−Time Dependent DFT study of these sensitizers in solution was performed, investigating the effect of protonation of the terminal carboxylic groups and of the counterions on the electronic structure and optical properties of the dyes. The calculated absorption spectra are in good agreement with the experiment, thus allowing a detailed assignment of the UV−vis spectral features ...

AMPK regulates energy expenditure by modulating NAD + metabolism and SIRT1 activity

Abstract: AMP-activated protein kinase (AMPK) is a metabolic fuel gauge conserved along the evolutionary scale in eukaryotes that senses changes in the intracellular AMP/ATP ratio. Recent evidence indicated an important role for AMPK in the therapeutic benefits of metformin, thiazolidinediones and exercise, which form the cornerstones of the clinical management of type 2 diabetes and associated metabolic disorders. In general, activation of AMPK acts to maintain cellular energy stores, switching on catabolic pathways that produce ATP, mostly by enhancing oxidative metabolism and mitochondrial biogenesis, while switching off anabolic pathways that consume ATP. This regulation can take place acutely, through the regulation of fast post-translational events, but also by transcriptionally reprogramming the cell to meet energetic needs. Here we demonstrate that AMPK controls the expression of genes involved in energy metabolism in mouse skeletal muscle by acting in coordination with another metabolic sensor, the NAD+-dependent type III deacetylase SIRT1. AMPK enhances SIRT1 activity by increasing cellular NAD+ levels, resulting in the deacetylation and modulation of the activity of downstream SIRT1 targets that include the peroxisome proliferator-activated receptor-gamma coactivator 1alpha and the forkhead box O1 (FOXO1) and O3 (FOXO3a) transcription factors. The AMPK-induced SIRT1-mediated deacetylation of these targets explains many of the convergent biological effects of AMPK and SIRT1 on energy metabolism.

A hole-conductor-free, fully printable mesoscopic perovskite solar cell with high stability

Abstract: We fabricated a perovskite solar cell that uses a double layer of mesoporous TiO2 and ZrO2 as a scaffold infiltrated with perovskite and does not require a hole-conducting layer. The perovskite was produced by drop-casting a solution of PbI2, methylammonium (MA) iodide, and 5-ammoniumvaleric acid (5-AVA) iodide through a porous carbon film. The 5-AVA templating created mixed-cation perovskite (5-AVA)x(MA)1- xPbI3 crystals with lower defect concentration and better pore filling as well as more complete contact with the TiO2 scaffold, resulting in a longer exciton lifetime and a higher quantum yield for photoinduced charge separation as compared to MAPbI3. The cell achieved a certified power conversion efficiency of 12.8% and was stable for >1000 hours in ambient air under full sunlight.

EPnP: An Accurate O(n) Solution to the PnP Problem

Abstract: We propose a non-iterative solution to the PnP problem--the estimation of the pose of a calibrated camera from n 3D-to-2D point correspondences--whose computational complexity grows linearly with n This is in contrast to state-of-the-art methods that are O(n 5) or even O(n 8), without being more accurate Our method is applicable for all n?4 and handles properly both planar and non-planar configurations Our central idea is to express the n 3D points as a weighted sum of four virtual control points The problem then reduces to estimating the coordinates of these control points in the camera referential, which can be done in O(n) time by expressing these coordinates as weighted sum of the eigenvectors of a 12×12 matrix and solving a small constant number of quadratic equations to pick the right weights Furthermore, if maximal precision is required, the output of the closed-form solution can be used to initialize a Gauss-Newton scheme, which improves accuracy with negligible amount of additional time The advantages of our method are demonstrated by thorough testing on both synthetic and real-data

Geometric Deep Learning: Going beyond Euclidean data

Abstract: Many scientific fields study data with an underlying structure that is non-Euclidean. Some examples include social networks in computational social sciences, sensor networks in communications, functional networks in brain imaging, regulatory networks in genetics, and meshed surfaces in computer graphics. In many applications, such geometric data are large and complex (in the case of social networks, on the scale of billions) and are natural targets for machine-learning techniques. In particular, we would like to use deep neural networks, which have recently proven to be powerful tools for a broad range of problems from computer vision, natural-language processing, and audio analysis. However, these tools have been most successful on data with an underlying Euclidean or grid-like structure and in cases where the invariances of these structures are built into networks used to model them.