A Strategy for Noise Reduction in Speech Recordings from Smartphones and Tablets

The aim of this work is to analyse the performance of Apple's iPhone and iPad as voice recorders, while at the same time finding algorithms to enhance speech recordings and reduce the noise introduced by the low quality built-in microphone. We perform spectral analysis of silent recordings to acquire the noise print from different device models and propose a MATLAB implementation of a noise reduction filterope

Towards better understanding of gradient-based attribution methods for Deep Neural Networks

Understanding the flow of information in Deep Neural Networks (DNNs) is a challenging problem that has gain increasing attention over the last few years. While several methods have been proposed to explain network predictions, there have been only a few attempts to compare them from a theoretical perspective. What is more, no exhaustive empirical comparison has been performed in the past. In this work, we analyze four gradient-based attribution methods and formally prove conditions of equivalence and approximation between them. By reformulating two of these methods, we construct a unified framework which enables a direct comparison, as well as an easier implementation. Finally, we propose a novel evaluation metric, called Sensitivity-n and test the gradient-based attribution methods alongside with a simple perturbation-based attribution method on several datasets in the domains of image and text classification, using various network architectures.Comment: ICLR 201

Competition between local erasure and long-range spreading of a single biochemical mark leads to epigenetic bistability

The mechanism through which cells determine their fate is intimately related to the spreading of certain biochemical (so-called epigenetic) marks along their genome. The mechanisms behind mark spreading and maintenance are not yet fully understood, and current models often assume a long-range infection-like process for the dynamics of marks, due to the polymeric nature of the chromatin fibre which allows looping between distant sites. While these existing models typically consider antagonising marks, here we propose a qualitatively different scenario which analyses the spreading of a single mark. We define a 1D stochastic model in which mark spreading/infection occurs as a long-range process whereas mark erasure/recovery is a local process, with an enhanced rate at boundaries of infected domains. In the limiting case where our model exhibits absorbing states, we find a first-order-like transition separating the marked/infected phase from the unmarked/recovered phase. This suggests that our model, in this limit, belongs to the long-range compact directed percolation universality class. The abrupt nature of the transition is retained in a more biophysically realistic situation when a basal infection/recovery rate is introduced (thereby removing absorbing states). Close to the transition there is a range of bistability where both the marked/infected and unmarked/recovered states are metastable and long lived, which provides a possible avenue for controlling fate decisions in cells. Increasing the basal infection/recovery rate, we find a second transition between a coherent (marked or unmarked) phase, and a mixed, or random, one.Comment: 11 pages, 7 figures, 2 appendice

A multi–scale study of chromatin organisation and function: DNA topology, epigenetics and chromatin compaction

Understanding chromatin organisation at different length scales is still one of the most puzzling challenges in biophysics. Nowadays, it is clear that DNA or chromatin conformational changes can profoundly affect gene expression. Yet, the mechanisms underlying such conformational changes remain elusive. Several factors can intervene in gene regulation: supercoiling (SC), the extent of over– or under– twist of DNA double helix, can compact DNA in both bacteria and eukaryotes, yielding transcriptional over–expression or repression. Post-translational modifications of histone tails demarcate the “epigenetic” domains, which are therefore vital to establish the correct chromatin environment. Chromatin–binding proteins can form biological “condensates” via phase separation mechanisms. Recently, liquid–liquid phase separation (LLPS) has much been touted to motivate the formation of protein clusters in vivo, often referred to as ‘nuclear bodies’. In addition, the so-called bridging-induced phase separation (BIPS), explains how protein aggregation can be mediated by chromatin only, even in the absence of protein-protein interaction. By using a multi-technique approach, in this thesis’ work I investigate the structural and dynamical properties of DNA and chromatin at different length scales. Monte Carlo algorithms were implemented to simulate SC dynamics in a stochastic model for bacterial transcription. Similar techniques were used to show that an infection–like model can entail epigenetic bistability. Molecular dynamics simulations were employed to study the static and dynamical properties of model protein aggregates; the interplay between LLPS and BIPS was explored, showing properties which go far beyond the liquid state. Depending on the parameters, solid–like, glassy and fractal protein condensates can co–localise with chromatin

Emergence of effective temperatures in an out-of-equilibrium model of biopolymer folding

We investigate the possibility of extending the notion of temperature in a stochastic model for the RNA/protein folding driven out of equilibrium. We simulate the dynamics of a small RNA hairpin subject to an external pulling force, which is time-dependent. First, we consider a fluctuation-dissipation relation (FDR) whereby we verify that various effective temperatures can be obtained for different observables, only when the slowest intrinsic relaxation timescale of the system regulates the dynamics of the system. Then, we introduce a different nonequilibrium temperature, which is defined from the rate of heat exchanged with a weakly-interacting thermal bath. Notably, this 'kinetic' temperature can be defined for any frequency of the external switching force. We also discuss and compare the behavior of these two emerging parameters, by discriminating the time-delayed nature of the FDR temperature from the instantaneous character of the kinetic temperature. The validity of our numerics are corroborated by a simple 4-state Markov model which describes the long-time behaviour of the RNA molecule.Comment: 16 pages, 8 figure