Search results for "Signal"

Implementation of signal-processing functionalities in the Terahertz frequency domain

2020

Three-dimensional dynamic light scattering

1999

Abstract We describe the employment of a novel light-scattering scheme for the decorrelation of multiple scattering in strongly turbid samples. The three-dimensional scheme, which has been proposed already theoretically, shows certain advantages compared with the two-colour apparatus, which is commercially available. We describe our set-up in detail; features are the use of modern semiconductor laser diodes and contemporary single-mode fibre receivers. We show experimentally that the optimal signal-to-noise ratio (or intercept) β opt = 0.20, which is obtainable with our set-up, can be quantitatively calculated from the measured uncertainties in the alignment. In particular, we give a detail…

Deep learning algorithms for gravitational waves core-collapse supernova detection

2021

The detection of gravitational waves from core-collapse supernova (CCSN) explosions is a challenging task, yet to be achieved, in which it is key the connection between multiple messengers, including neutrinos and electromagnetic signals. In this work, we present a method for detecting these kind of signals based on machine learning techniques. We tested its robustness by injecting signals in the real noise data taken by the Advanced LIGO-Virgo network during the second observation run, O2. We trained three newly developed convolutional neural networks using time-frequency images corresponding to injections of simulated phenomenological signals, which mimic the waveforms obtained in 3D nume…

Understanding disease mechanisms with models of signaling pathway activities

2014

Background Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is one of the main challenges in the analysis of genomic data and is on the basis of the future implementation of precision medicine. Results Here we propose a simple probabilistic model in which signaling pathways are separated into elementary sub-pathways or signal transmission circuits (which ultimately trigger cell functions) and then transforms gene expression measurements into probabilities of activation of such signal transmission circuits. Using this model, differential activation of such circuits between biological conditions can be estimated. Thus, circuit activation s…

Functional characterisation of the first HSP110 inhibitors.

2023

Heat shock proteins are molecular chaperones highly expressed in haematological malignancies. My laboratory has shown that the heat shock protein HSP110 is a new and important therapeutic target In colorectal cancer and in non-Hodgkin's lymphoma. As there were no existing inhibitors of HSP110, a screening strategy of a chemical library was carried out and allowed the identification of two molecules capable of specifically inhibiting the chaperone activity of HSP110. My thesis objective was to characterise and functionally validate these newly identified molecules in diffuse large cell B lymphomas. I have shown that one of these molecules limits the interaction of HSP110 with the SYK signall…

Honesty of agonistic signalling and effects of size and motivation asymmetry in contests

1999

Game theoretical models predict that the main function of fighting behaviour is to assess the relative fighting ability of opponents. The sequential assessment game has often been used to investigate contests, while honest signalling theory has received much less attention. With the wolf spider Hygrolycosa rubrofasciata we investigated whether male agonistic signalling can reveal honest information about fighting ability, and how size and motivation asymmetries affect male fighting behaviour. We also determined whether male–male competition affects the courtship behaviour of the males. We found that agonistic drumming activity is an honest indicator of male fighting ability, and that relati…

Extracellular vesicles from neural stem cells transfer the IFN-gamma/IFNGR1 complex to activate Stat1-dependent signalling in target cells

2014

Probing the radio emission from air showers with polarization measurements

2014

The emission of radio waves from air showers has been attributed to the so-called geomagnetic emission process. At frequencies around 50 MHz this process leads to coherent radiation which can be observed with rather simple setups. The direction of the electric field induced by this emission process depends only on the local magnetic field vector and on the incoming direction of the air shower. We report on measurements of the electric field vector where, in addition to this geomagnetic component, another component has been observed which cannot be described by the geomagnetic emission process. The data provide strong evidence that the other electric field component is polarized radially wit…

Background studies for acoustic neutrino detection at the South Pole

2011

The detection of acoustic signals from ultra-high energy neutrino interactions is a promising method to measure the tiny flux of cosmogenic neutrinos expected on Earth. The energy threshold for this process depends strongly on the absolute noise level in the target material. The South Pole Acoustic Test Setup (SPATS), deployed in the upper part of four boreholes of the IceCube Neutrino Observatory, has monitored the noise in Antarctic ice at the geographic South Pole for more than two years down to 500 m depth. The noise is very stable and Gaussian distributed. Lacking an in-situ calibration up to now, laboratory measurements have been used to estimate the absolute noise level in the 10 to …

From optimization to algorithmic differentiation: a graph detour

2021

This manuscript highlights the work of the author since he was nominated as "Chargé de Recherche" (research scientist) at Centre national de la recherche scientifique (CNRS) in 2015. In particular, the author shows a thematic and chronological evolution of his research interests:- The first part, following his post-doctoral work, is concerned with the development of new algorithms for non-smooth optimization.- The second part is the heart of his research in 2020. It is focused on the analysis of machine learning methods for graph (signal) processing.- Finally, the third and last part, oriented towards the future, is concerned with (automatic or not) differentiation of algorithms for learnin…