211 research outputs found
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 multiâscale 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 overâ or underâ twist of DNA double helix, can compact DNA in both
bacteria and eukaryotes, yielding transcriptional overâexpression or repression.
Post-translational modifications of histone tails demarcate the âepigeneticâ
domains, which are therefore vital to establish the correct chromatin environment.
Chromatinâbinding proteins can form biological âcondensatesâ via
phase separation mechanisms. Recently, liquidâliquid phase separation (LLPS)
has much been touted to motivate the formation of protein clusters in vivo,
often referred to as ânuclear bodiesâ. 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 thesisâ 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 infectionâlike 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, solidâlike, glassy and fractal protein condensates can coâlocalise
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
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