pwc-archive/papers-with-abstracts huggingface dataset:
Oblivion: Mitigating Privacy Leaks by Controlling the Discoverability of Online Information
Authors: Simeonovski Milivoj, Bendun Fabian, Asghar Muhammad Rizwan, Backes Michael, Marnau Ninja, Druschel Peter
Date: 2015-06-19 00:00:00
Tasks: Privacy Preserving, TAG

Search engines are the prevalently used tools to collect information about
individuals on the Internet. Search results typically comprise a variety of
sources that contain personal information -- either intentionally released by
the person herself, or unintentionally leaked or published by third parties,
often with detrimental effects on the individual's privacy. To grant
individuals the ability to regain control over their disseminated personal
information, the European Court of Justice recently ruled that EU citizens have
a right to be forgotten in the sense that indexing systems, must offer them
technical means to request removal of links from search results that point to
sources violating their data protection rights. As of now, these technical
means consist of a web form that requires a user to manually identify all
relevant links upfront and to insert them into the web form, followed by a
manual evaluation by employees of the indexing system to assess if the request
is eligible and lawful.
  We propose a universal framework Oblivion to support the automation of the
right to be forgotten in a scalable, provable and privacy-preserving manner.
First, Oblivion enables a user to automatically find and tag her disseminated
personal information using natural language processing and image recognition
techniques and file a request in a privacy-preserving manner. Second, Oblivion
provides indexing systems with an automated and provable eligibility mechanism,
asserting that the author of a request is indeed affected by an online
resource. The automated ligibility proof ensures censorship-resistance so that
only legitimately affected individuals can request the removal of corresponding
links from search results. We have conducted comprehensive evaluations, showing
that Oblivion is capable of handling 278 removal requests per second, and is
hence suitable for large-scale deployment.
Diagnosing ADHD from fMRI Scans Using Hidden Markov Models
Date: 2015-06-19 00:00:00
Tasks: Dimensionality Reduction

This paper applies a hidden Markov model to the problem of Attention Deficit
Hyperactivity Disorder (ADHD) diagnosis from resting-state functional Magnetic
Resonance Image (fMRI) scans of subjects. The proposed model considers the
temporal evolution of fMRI voxel activations in the cortex, cingulate gyrus,
and thalamus regions of the brain in order to make a diagnosis. Four feature
dimen- sionality reduction methods are applied to the fMRI scan: voxel means,
voxel weighted means, principal components analysis, and kernel principal
components analysis. Using principal components analysis and kernel principal
components analysis for dimensionality reduction, the proposed algorithm
yielded an accu- racy of 63.01% and 62.06%, respectively, on the ADHD-200
competition dataset when differentiating between healthy control, ADHD
innattentive, and ADHD combined types.
Low PMEPR OFDM radar waveform design using the iterative least squares algorithm
Date: 2015-06-19 00:00:00
Tasks: Radar waveform design

This letter considers waveform design of orthogonal frequency division
multiplexing (OFDM) signal for radar applications, and aims at mitigating the
envelope fluctuation in OFDM. A novel method is proposed to reduce the
peak-to-mean envelope power ratio (PMEPR), which is commonly used to evaluate
the fluctuation. The proposed method is based on the tone reservation approach,
in which some bits or subcarriers of OFDM are allocated for decreasing PMEPR.
We introduce the coefficient of variation of envelopes (CVE) as the cost
function for waveform optimization, and develop an iterative least squares
algorithm. Minimizing CVE leads to distinct PMEPR reduction, and it is
guaranteed that the cost function monotonically decreases by applying the
iterative algorithm. Simulations demonstrate that the envelope is significantly
smoothed by the proposed method.
SIR model with local and global infective contacts: A deterministic approach and applications
Date: 2015-06-19 00:00:00

An epidemic model with births and deaths is considered on a two dimensional
LxL lattice. Each individual can have global infective contacts according to
the standard SIR model rules or local infective contacts with its nearest
neighbors. We propose a deterministic approach to this model and verified that
there is a good agreement with the stochastic simulations for different
situations of the disease transmission and parameters corresponding to
pertussis and rubella in the prevaccine era.
The evolution of lossy compression
Date: 2015-06-19 00:00:00

In complex environments, there are costs to both ignorance and perception. An
organism needs to track fitness-relevant information about its world, but the
more information it tracks, the more resources it must devote to memory and
processing. Rate-distortion theory shows that, when errors are allowed,
remarkably efficient internal representations can be found by
biologically-plausible hill-climbing mechanisms. We identify two regimes: a
high-fidelity regime where perceptual costs scale logarithmically with
environmental complexity, and a low-fidelity regime where perceptual costs are,
remarkably, independent of the environment. When environmental complexity is
rising, Darwinian evolution should drive organisms to the threshold between the
high- and low-fidelity regimes. Organisms that code efficiently will find
themselves able to make, just barely, the most subtle distinctions in their
environment.
Portfolio Optimization under Local-Stochastic Volatility: Coefficient Taylor Series Approximations & Implied Sharpe Ratio
Date: 2015-06-19 00:00:00
Tasks: Portfolio Optimization

We study the finite horizon Merton portfolio optimization problem in a
general local-stochastic volatility setting. Using model coefficient expansion
techniques, we derive approximations for the both the value function and the
optimal investment strategy. We also analyze the `implied Sharpe ratio' and
derive a series approximation for this quantity. The zeroth-order approximation
of the value function and optimal investment strategy correspond to those
obtained by Merton (1969) when the risky asset follows a geometric Brownian
motion. The first-order correction of the value function can, for general
utility functions, be expressed as a differential operator acting on the
zeroth-order term. For power utility functions, higher order terms can also be
computed as a differential operator acting on the zeroth-order term. We give a
rigorous accuracy bound for the higher order approximations in this case in
pure stochastic volatility models. A number of examples are provided in order
to demonstrate numerically the accuracy of our approximations.
A guide through a family of phylogenetic dissimilarity measures among sites
Date: 2015-06-21 00:00:00
Tasks: Diversity

Ecological studies have now gone beyond measures of species turnover towards
measures of phylogenetic and functional dissimilarity with a main objective:
disentangling the processes that drive species distributions from local to
broad scales. A fundamental difference between phylogenetic and functional
analyses is that phylogeny is intrinsically dependent on a tree-like structure.
When the branches of a phylogenetic tree have lengths, then each evolutionary
unit on these branches can be considered as a basic entity on which
dissimilarities among sites should be measured. Several of the recent measures
of phylogenetic dissimilarities among sites thus are traditional dissimilarity
indices where species are replaced by evolutionary units. The resulting indices
were named PD-dissimilarity indices. Here I review and compare indices and
ordination approaches that, although first developed to analyse the differences
in the species compositions of sites, can be adapted to describe
PD-dissimilarities among sites, thus revealing how lineages are distributed
along environmental gradients, or among habitats or regions. As an
illustration, I show that the amount of PD-dissimilarities among the main
habitats of a disturbance gradient in Selva Lacandona of Chiapas, Mexico is
strongly dependent on whether species are weighted by their abundance or not,
and on the index used to measure PD-dissimilarity. Overall, the family of
PD-dissimilarity indices has a critical potential for future analyses of
phylogenetic diversity as it benefits from decades of research on the measure
of species dissimilarity. I provide clues to help to choose among many
potential indices, identifying which indices satisfy minimal basis properties,
and analysing their sensitivity to abundance, size, diversity, and joint
absences.
What can ecosystems learn? Expanding evolutionary ecology with learning theory
Date: 2015-06-21 00:00:00
Tasks: Learning Theory, Open-Ended Question Answering

Understanding how the structure of community interactions is modified by
coevolution is vital for understanding system responses to change at all
scales. However, in absence of a group selection process, collective community
behaviours cannot be organised or adapted in a Darwinian sense. An open
question thus persists: are there alternative organising principles that enable
us to understand how coevolution of component species creates complex
collective behaviours exhibited at the community level? We address this issue
using principles from connectionist learning, a discipline with well-developed
theories of emergent behaviours in simple networks. We identify conditions
where selection on ecological interactions is equivalent to 'unsupervised
learning' (a simple type of connectionist learning) and observe that this
enables communities to self organize without community-level selection. Despite
not being a Darwinian unit, ecological communities can behave like
connectionist learning systems, creating internal organisation that habituates
to past environmental conditions and actively recalling those conditions.
A linear bound on the number of states in optimal convex characters for maximum parsimony distance
Date: 2015-06-21 00:00:00

Given two phylogenetic trees on the same set of taxa X, the maximum parsimony
distance d_MP is defined as the maximum, ranging over all characters c on X, of
the absolute difference in parsimony score induced by c on the two trees. In
this note we prove that for binary trees there exists a character achieving
this maximum that is convex on one of the trees (i.e. the parsimony score
induced on that tree is equal to the number of states in the character minus 1)
and such that the number of states in the character is at most 7d_MP - 5. This
is the first non-trivial bound on the number of states required by optimal
characters, convex or otherwise. The result potentially has algorithmic
significance because, unlike general characters, convex characters with a
bounded number of states can be enumerated in polynomial time.
New class of compounds - variators - are reprogramming substrate specificity of H3K4me3 epigenetic marks reading PHD domain of BPTF protein
Date: 2015-06-22 00:00:00
Tasks: Specificity

In lymphoma, mutations in genes of histone modifying proteins are frequently
observed. Notably, somatic mutations in the activatory histone modification
writing protein MLL2 and the repressive modification writer EZH2 are the most
frequent. Gain of function mutations are typically detected in EZH2 whilst MLL2
mutations are usually observed as conferring a homozygous loss of function. The
gain-of-function mutations in EZH2 provide an obvious target for the
development of inhibitors with therapeutic potential. To counter the loss of
functional MLL2 protein, we computationally predicted compounds that are able
to modulate the reader of the corresponding modifications, BPTF, to recognize
other forms of the histone H3 lysine 4, instead of the tri-methylated form
normally produced by MLL2. By forming a synthetic triple-complex of a compound,
the histone H3 tail and BPTF we potentially circumvent the requirement for
functional MLL2 methyl-transferase through the modulation of BPTF activity.
Here we show a proof-of-principle that special compounds, named variators, can
reprogram selectivity of protein binding and thus create artificial regulatory
pathways which can have a potential therapeutic role. A therapeutic role of
BPTF variators may extend to other diseases that involve loss of MLL2 function,
such as Kabuki syndrome or the aberrant functioning of H3K4 modification as
observed in Huntington disease and in memory formation.
Stochastic evolutionary games in dynamic populations
Date: 2015-06-22 00:00:00

Frequency dependent selection and demographic fluctuations play important
roles in evolutionary and ecological processes. Under frequency dependent
selection, the average fitness of the population may increase or decrease based
on interactions between individuals within the population. This should be
reflected in fluctuations of the population size even in constant environments.
Here, we propose a stochastic model, which naturally combines these two
evolutionary ingredients by assuming frequency dependent competition between
different types in an individual-based model. In contrast to previous game
theoretic models, the carrying capacity of the population and thus the
population size is determined by pairwise competition of individuals mediated
by evolutionary games and demographic stochasticity. In the limit of infinite
population size, the averaged stochastic dynamics is captured by the
deterministic competitive Lotka-Volterra equations. In small populations,
demographic stochasticity may instead lead to the extinction of the entire
population. As the population size is driven by the fitness in evolutionary
games, a population of cooperators is less prone to go extinct than a
population of defectors, whereas in the usual systems of fixed size, the
population would thrive regardless of its average payoff.
Macroscopic description for networks of spiking neurons
Date: 2015-06-22 00:00:00

A major goal of neuroscience, statistical physics and nonlinear dynamics is
to understand how brain function arises from the collective dynamics of
networks of spiking neurons. This challenge has been chiefly addressed through
large-scale numerical simulations. Alternatively, researchers have formulated
mean-field theories to gain insight into macroscopic states of large neuronal
networks in terms of the collective firing activity of the neurons, or the
firing rate. However, these theories have not succeeded in establishing an
exact correspondence between the firing rate of the network and the underlying
microscopic state of the spiking neurons. This has largely constrained the
range of applicability of such macroscopic descriptions, particularly when
trying to describe neuronal synchronization. Here we provide the derivation of
a set of exact macroscopic equations for a network of spiking neurons. Our
results reveal that the spike generation mechanism of individual neurons
introduces an effective coupling between two biophysically relevant macroscopic
quantities, the firing rate and the mean membrane potential, which together
govern the evolution of the neuronal network. The resulting equations exactly
describe all possible macroscopic dynamical states of the network, including
states of synchronous spiking activity. Finally we show that the firing rate
description is related, via a conformal map, with a low-dimensional description
in terms of the Kuramoto order parameter, called Ott-Antonsen theory. We
anticipate our results will be an important tool in investigating how large
networks of spiking neurons self-organize in time to process and encode
information in the brain.
Fast assessment of structural models of ion channels based on their predicted current-voltage characteristics
Date: 2015-06-22 00:00:00

Computational prediction of protein structures is a difficult task, which
involves fast and accurate evaluation of candidate model structures. We propose
to enhance single model quality assessment with a functionality evaluation
phase for proteins whose quantitative functional characteristics are known. In
particular, this idea can be applied to evaluation of structural models of ion
channels, whose main function - conducting ions - can be quantitatively
measured with the patch-clamp technique providing the current-voltage
characteristics. The study was performed on a set of KcsA channel models
obtained from complete and incomplete contact maps. A fast continuous
electrodiffusion model was used for calculating the current-voltage
characteristics of structural models. We found that the computed charge
selectivity and total current were sensitive to structural and electrostatic
quality of models. In practical terms, we show that evaluating predicted
conductance values is an appropriate method to eliminate modes with an occluded
pore or with multiple erroneously created pores. Moreover, filtering models on
the basis of their predicted charge selectivity results in a substantial
enrichment of the candidate set in highly accurate models. In addition to being
a proof of the concept, our function-oriented single model quality assessment
tool can be directly applied for evaluation of structural models of
strongly-selective protein channels. Finally, our work raises an important
question whether a computational validation of functionality should not be
included in the evaluation process of structural models, whenever possible.
Understanding the Impact of Microcredit Expansions: A Bayesian Hierarchical Analysis of 7 Randomised Experiments
Date: 2016-07-12 00:00:00
Tasks: valid

Bayesian hierarchical models are a methodology for aggregation and synthesis
of data from heterogeneous settings, used widely in statistics and other
disciplines. I apply this framework to the evidence from 7 randomized
experiments of expanding access to microcredit to assess the general impact of
the intervention on household outcomes and the heterogeneity in this impact
across sites. The results suggest that the effect of microcredit is likely to
be positive but small relative to control group average levels, and the
possibility of a negative impact cannot be ruled out. By contrast, common
meta-analytic methods that pool all the data without assessing the
heterogeneity misleadingly produce "statistically significant" results in 2 of
the 6 household outcomes. Standard pooling metrics for the studies indicate on
average 60% pooling on the treatment effects, suggesting that the site-specific
effects are reasonably externally valid, and thus informative for each other
and for the general case. The cross-study heterogeneity is almost entirely
generated by heterogeneous effects for the 27% households who previously
operated businesses before microcredit expansion, although this group is likely
to see much larger impacts overall. A Ridge regression procedure to assess the
correlations between site-specific covariates and treatment effects indicates
that the remaining heterogeneity is strongly correlated with differences in
economic variables, but not with differences in study design protocols. The
average interest rate and the average loan size have the strongest correlation
with the treatment effects, and both are negative.
How we move is universal: scaling in the average shape of human activity
Date: 2015-11-22 00:00:00

Human motor activity is constrained by the rhythmicity of the 24 hours
circadian cycle, including the usual 12-15 hours sleep-wake cycle. However,
activity fluctuations also appear over a wide range of temporal scales, from
days to a few seconds, resulting from the concatenation of a myriad of
individual smaller motor events. Furthermore, individuals present different
propensity to wakefulness and thus to motor activity throughout the circadian
cycle. Are activity fluctuations across temporal scales intrinsically
different, or is there a universal description encompassing them? Is this
description also universal across individuals, considering the aforementioned
variability? Here we establish the presence of universality in motor activity
fluctuations based on the empirical study of a month of continuous wristwatch
accelerometer recordings. We study the scaling of average fluctuations across
temporal scales and determine a universal law characterized by critical
exponents $\alpha$, $\tau$ and $1/{\mu}$. Results are highly reminiscent of the
universality described for the average shape of avalanches in systems
exhibiting crackling noise. Beyond its theoretical relevance, the present
results can be important for developing objective markers of healthy as well as
pathological human motor behavior.
Generative models of the human connectome
Date: 2015-09-19 00:00:00

The human connectome represents a network map of the brain's wiring diagram
and the pattern into which its connections are organized is thought to play an
important role in cognitive function. The generative rules that shape the
topology of the human connectome remain incompletely understood. Earlier work
in model organisms has suggested that wiring rules based on geometric
relationships (distance) can account for many but likely not all topological
features. Here we systematically explore a family of generative models of the
human connectome that yield synthetic networks designed according to different
wiring rules combining geometric and a broad range of topological factors. We
find that a combination of geometric constraints with a homophilic attachment
mechanism can create synthetic networks that closely match many topological
characteristics of individual human connectomes, including features that were
not included in the optimization of the generative model itself. We use these
models to investigate a lifespan dataset and show that, with age, the model
parameters undergo progressive changes, suggesting a rebalancing of the
generative factors underlying the connectome across the lifespan.
New class of compounds - variators - are reprogramming substrate specificity of H4K12Ac, H4K16Ac and H4K20Ac epigenetic marks reading bromodomain of BPTF protein
Date: 2015-06-23 00:00:00
Tasks: Specificity

Previously reported [http://arxiv.org/abs/1506.06433] reprogramming of
substrate specificity of H3K4Me3 epigenetic marks reading PHD domain of BPTF
protein illustrates therapeutic potential of a new class of non-inhibitor small
organic compounds - variators. Here we address the question about
reproducibility of rational design of variators by reprogramming of the second
epigenetic marks reading domain of BPTF protein - bromodomain. Bromodomain of
BPTF binds to epigenetic marks in form of acetylated lysine of histone H4
(H4K12Ac, H4K16Ac and H4K20Ac), which physicochemical properties and binding
mode differs considerably from those of methylated H3K4 marks. Thus, detailed
description of computational approach for reprogramming of bromodomain
substrate specificity illustrates both general and target specific attributes
of computer aided variators design.