pwc-archive/papers-with-abstracts huggingface dataset:
A topological perspective into the sequence and conformational space of proteins
Date: 2015-03-27 00:00:00

The precise sequence of aminoacids plays a central role in the tertiary
structure of proteins and their functional properties. The Hydrophobic-Polar
lattice models have provided valuable insights regarding the energy landscape.
We demonstrate here the isomorphism between the protein sequences and
designable structures for two and three dimensional lattice proteins of very
long aminoacid chains using exact enumerations and intuitive considerations.We
emphasize that the topological arrangement of the aminoacid residues alone is
adequate to deduce the designable and non-designable sequences without explicit
recourse to energetics and degeneracies. The results indicate the computational
feasibility of realistic lattice models for proteins in two and three
dimensions and imply that the fundamental principle underlying the designing of
structures is the connectivity of the hydrophobic and polar residues.
A Robust Statistics Approach to Minimum Variance Portfolio Optimization
Date: 2015-03-27 00:00:00
Tasks: Portfolio Optimization

We study the design of portfolios under a minimum risk criterion. The
performance of the optimized portfolio relies on the accuracy of the estimated
covariance matrix of the portfolio asset returns. For large portfolios, the
number of available market returns is often of similar order to the number of
assets, so that the sample covariance matrix performs poorly as a covariance
estimator. Additionally, financial market data often contain outliers which, if
not correctly handled, may further corrupt the covariance estimation. We
address these shortcomings by studying the performance of a hybrid covariance
matrix estimator based on Tyler's robust M-estimator and on Ledoit-Wolf's
shrinkage estimator while assuming samples with heavy-tailed distribution.
Employing recent results from random matrix theory, we develop a consistent
estimator of (a scaled version of) the realized portfolio risk, which is
minimized by optimizing online the shrinkage intensity. Our portfolio
optimization method is shown via simulations to outperform existing methods
both for synthetic and real market data.
Can visual information encoded in cortical columns be decoded from magnetoencephalography data in humans?
Date: 2015-03-27 00:00:00
Tasks: Open-Ended Question Answering

It is a principal open question whether noninvasive imaging methods in humans
can decode information encoded at a spatial scale as fine as the basic
functional unit of cortex: cortical columns. We addressed this question in five
magnetoencephalography (MEG) experiments by investigating the encoding of a
columnar-level encoded visual feature: contrast edge orientation. We found that
MEG signals contained orientation-specific information as early as ~50ms after
stimulus onset even when controlling for confounds, such as overrepresentation
of particular orientations, stimulus edge interactions, and global form-related
signals. Theoretical modeling confirmed the plausibility of this empirical
result. An essential consequence of our results is that information encoded in
the human brain at the level of cortical columns should in general be
accessible by multivariate analysis of electrophysiological signals.
Observability of Market Daily Volatility
Date: 2015-03-27 00:00:00

We study the price dynamics of 65 stocks from the Dow Jones Composite Average
from 1973 until 2014. We show that it is possible to define a Daily Market
Volatility $\sigma(t)$ which is directly observable from data. This quantity is
usually indirectly defined by $r(t)=\sigma(t) \omega(t)$ where the $r(t)$ are
the daily returns of the market index and the $\omega(t)$ are i.i.d. random
variables with vanishing average and unitary variance. The relation
$r(t)=\sigma(t) \omega(t)$ alone is unable to give an operative definition of
the index volatility, which remains unobservable. On the contrary, we show that
using the whole information available in the market, the index volatility can
be operatively defined and detected.
Gonosomal Algebra
Date: 2015-03-22 00:00:00

We introduce the gonosomal algebra. Gonosomal algebra extend the evolution
algebra of the bisexual population (EABP) defined by Ladra and Rozikov. We show
that gonosomal algebras can represent algebraically a wide variety of sex
determination systems observed in bisexual populations. We illustrate this by
about twenty genetic examples, most of these examples cannot be represented by
an EABP. We give seven algebraic constructions of gonosomal algebras, each is
illustrated by genetic examples. We show that unlike the EABP gonosomal
algebras are not dibaric. We approach the existence of dibaric function and
idempotent in gonosomal algebras.
Black-Scholes in a CEV random environment
Date: 2017-11-28 00:00:00

Classical (It\^o diffusions) stochastic volatility models are not able to
capture the steepness of small-maturity implied volatility smiles. Jumps, in
particular exponential L\'evy and affine models, which exhibit small-maturity
exploding smiles, have historically been proposed to remedy this (see
\cite{Tank} for an overview), and more recently rough volatility models
\cite{AlosLeon, Fukasawa}. We suggest here a different route, randomising the
Black-Scholes variance by a CEV-generated distribution, which allows us to
modulate the rate of explosion (through the CEV exponent) of the implied
volatility for small maturities. The range of rates includes behaviours similar
to exponential L\'evy models and fractional stochastic volatility models.
About the decomposition of pricing formulas under stochastic volatility models
Date: 2015-03-27 00:00:00

We obtain a decomposition of the call option price for a very general
stochastic volatility diffusion model extending the decomposition obtained by
E. Al\`os in [2] for the Heston model. We realize that a new term arises when
the stock price does not follow an exponential model. The techniques used are
non anticipative. In particular, we see also that equivalent results can be
obtained using Functional It\^o Calculus. Using the same generalizing ideas we
also extend to non exponential models the alternative call option price
decompostion formula obtained in [1] and [3] written in terms of the Malliavin
derivative of the volatility process. Finally, we give a general expression for
the derivative of the implied volatility under both, the anticipative and the
non anticipative case.
New Routes to Phylogeography
Date: 2015-03-27 00:00:00
Tasks: Computational Efficiency

Phylogeographic methods aim to infer migration trends and the history of
sampled lineages from genetic data. Applications of phylogeography are broad,
and in the context of pathogens include the reconstruction of transmission
histories and the origin and emergence of outbreaks. Phylogeographic inference
based on bottom-up population genetics models is computationally expensive, and
as a result faster alternatives based on the evolution of discrete traits have
become popular. In this paper, we show that inference of migration rates and
root locations based on discrete trait models is extremely unreliable and
sensitive to biased sampling. To address this problem, we introduce BASTA
(BAyesian STructured coalescent Approximation), a new approach implemented in
BEAST2 that combines the accuracy of methods based on the structured coalescent
with the computational efficiency required to handle more than just few
populations. We illustrate the potentially severe implications of poor model
choice for phylogeographic analyses by investigating the zoonotic transmission
of Ebola virus. Whereas the structured coalescent analysis correctly infers
that successive human Ebola outbreaks have been seeded by a large unsampled
non-human reservoir population, the discrete trait analysis implausibly
concludes that undetected human-to-human transmission has allowed the virus to
persist over the past four decades. As genomics takes on an increasingly
prominent role informing the control and prevention of infectious diseases, it
will be vital that phylogeographic inference provides robust insights into
transmission history.
Metapopulation dynamics in a complex ecological landscape
Date: 2015-03-27 00:00:00

We propose a general model to study the interplay between spatial dispersal
and environment spatiotemporal fluctuations in metapopulation dynamics. An
ecological landscape of favorable patches is generated like a L\'{e}vy dust,
which allows to build a range of patterns, from dispersed to clustered ones.
Locally, the dynamics is driven by a canonical model for the evolution of the
population density, consisting of a logistic expression plus multiplicative
noises. Spatial coupling is introduced by means of two spreading mechanisms:
diffusive dispersion and selective migration driven by patch suitability. We
focus on the long-time population size as a function of habitat configurations,
environment fluctuations and coupling schemes. We obtain the conditions, that
the spatial distribution of favorable patches and the coupling mechanisms must
fulfill, to grant population survival. The fundamental phenomenon that we
observe is the positive feedback between environment fluctuations and spatial
spread preventing extinction.
CoMEt: A Statistical Approach to Identify Combinations of Mutually Exclusive Alterations in Cancer
Date: 2015-03-27 00:00:00

Cancer is a heterogeneous disease with different combinations of genetic and
epigenetic alterations driving the development of cancer in different
individuals. While these alterations are believed to converge on genes in key
cellular signaling and regulatory pathways, our knowledge of these pathways
remains incomplete, making it difficult to identify driver alterations by their
recurrence across genes or known pathways. We introduce Combinations of
Mutually Exclusive Alterations (CoMEt), an algorithm to identify combinations
of alterations de novo, without any prior biological knowledge (e.g. pathways
or protein interactions). CoMEt searches for combinations of mutations that
exhibit mutual exclusivity, a pattern expected for mutations in pathways. CoMEt
has several important feature that distinguish it from existing approaches to
analyze mutual exclusivity among alterations. These include: an exact
statistical test for mutual exclusivity that is more sensitive in detecting
combinations containing rare alterations; simultaneous identification of
collections of one or more combinations of mutually exclusive alterations;
simultaneous analysis of subtype-specific mutations; and summarization over an
ensemble of collections of mutually exclusive alterations. These features
enable CoMEt to robustly identify alterations affecting multiple pathways, or
hallmarks of cancer. We show that CoMEt outperforms existing approaches on
simulated and real data. Application of CoMEt to hundreds of samples from four
different cancer types from TCGA reveals multiple mutually exclusive sets
within each cancer type. Many of these overlap known pathways, but others
reveal novel putative cancer genes. *Equal contribution.
Bifurcation analysis and potential landscape of the p53-Mdm2 oscillator regulated by the co-activator PDCD5
Date: 2015-03-28 00:00:00

Dynamics of p53 is known to play important roles in the regulation of cell
fate decisions in response to various stresses, and PDCD5 functions as a
co-activator of p53 to modulate the p53 dynamics. In the present paper, we
investigate how p53 dynamics are modulated by PDCD5 during the DNA damage
response using methods of bifurcation analysis and potential landscape. Our
results reveal that p53 activities can display rich dynamics under different
PDCD5 levels, including monostability, bistability with two stable steady
states, oscillations, and co-existence of a stable steady state and an
oscillatory state. Physical properties of the p53 oscillations are further
shown by the potential landscape, in which the potential force attracts the
system state to the limit cycle attractor, and the curl flux force drives the
coherent oscillation along the cyclic. We also investigate the effect of PDCD5
efficiency on inducing the p53 oscillations. We show that Hopf bifurcation is
induced by increasing the PDCD5 efficiency, and the system dynamics show clear
transition features in both barrier height and energy dissipation when the
efficiency is close to the bifurcation point. This study provides a global
picture of how PDCD5 regulates p53 dynamics via the interaction with the
p53-Mdm2 oscillator and can be helpful in understanding the complicate p53
dynamics in a more complete p53 pathway.
PDCD5 interacts with p53 and functions as a regulator of p53 dynamics in the DNA damage response
Date: 2015-03-28 00:00:00

The tumor suppressor p53 plays a central role in cell fate decisions after
DNA damage. Programmed Cell Death 5 (PDCD5) is known to interact with the p53
pathway to promote cell apoptosis. Recombinant human PDCD5 can significantly
sensitize different cancers to chemotherapies. In the present paper, we
construct a computational model that includes PDCD5 interactions in the p53
signaling network and study the effects of PDCD5 on p53-mediated cell fate
decisions during the DNA damage response. Our results revealed that PDCD5
functions as a co-activator of p53 that regulates p53-dependent cell fate
decisions via the mediation of p53 dynamics. The effects of PDCD5 are
dose-dependent such that p53 can display either sustained or pulsed dynamics at
different PDCD5 levels. Moreover, PDCD5 regulates caspase-3 activation via two
mechanisms during the two phases of sustained and pulsed p53 dynamics. This
study provides insights regarding how PDCD5 functions as a regulator of the p53
pathway and might be helpful for increasing our understanding of the molecular
mechanisms by which PDCD5 can be used to treat cancers.
Outcome prediction in mathematical models of immune response to infection
Date: 2015-03-28 00:00:00
Tasks: Prediction, Prognosis

Clinicians need to predict patient outcomes with high accuracy as early as
possible after disease inception. In this manuscript, we show that
patient-to-patient variability sets a fundamental limit on outcome prediction
accuracy for a general class of mathematical models for the immune response to
infection. However, accuracy can be increased at the expense of delayed
prognosis. We investigate several systems of ordinary differential equations
(ODEs) that model the host immune response to a pathogen load. Advantages of
systems of ODEs for investigating the immune response to infection include the
ability to collect data on large numbers of `virtual patients', each with a
given set of model parameters, and obtain many time points during the course of
the infection. We implement patient-to-patient variability $v$ in the ODE
models by randomly selecting the model parameters from Gaussian distributions
with variance $v$ that are centered on physiological values. We use logistic
regression with one-versus-all classification to predict the discrete
steady-state outcomes of the system. We find that the prediction algorithm
achieves near $100\%$ accuracy for $v=0$, and the accuracy decreases with
increasing $v$ for all ODE models studied. The fact that multiple steady-state
outcomes can be obtained for a given initial condition, i.e. the basins of
attraction overlap in the space of initial conditions, limits the prediction
accuracy for $v>0$. Increasing the elapsed time of the variables used to train
and test the classifier, increases the prediction accuracy, while adding
explicit external noise to the ODE models decreases the prediction accuracy.
Our results quantify the competition between early prognosis and high
prediction accuracy that is frequently encountered by clinicians.
East africa in the Malthusian trap? A statistical analysis of financial, economic, and demographic indicators
Date: 2015-03-29 00:00:00

A statistical analysis of financial, economic, and demographic indicators
performed by the authors demonstrates (1) that the main countries of East
Africa (Uganda, Kenya, and Tanzania) have not escaped the Malthusian Trap yet;
(2) that this countries are not likely to follow the "North African path" and
to achieve this escape before they achieve serious successes in their fertility
transition; (3) that East Africa is unlikely to achieve this escape if it does
not follow the "Bangladeshi path" and does not achieve really substantial
fertility declines in the foreseeable future, which would imply the
introduction of compulsory universal secondary education, serious family
planning programs of the Rwandan type, and the rise of legal age of marriage
with parental consent. Such measures should of course be accompanied by the
substantial increases in the agricultural labor productivity and the decline of
the percentage of population employed in agriculture.
A Novel Modified Apriori Approach for Web Document Clustering
Authors: Roul Rajendra Kumar, Varshneya Saransh, Kalra Ashu, Sahay Sanjay Kumar
Date: 2015-03-29 00:00:00
Tasks: Clustering

The traditional apriori algorithm can be used for clustering the web
documents based on the association technique of data mining. But this algorithm
has several limitations due to repeated database scans and its weak association
rule analysis. In modern world of large databases, efficiency of traditional
apriori algorithm would reduce manifolds. In this paper, we proposed a new
modified apriori approach by cutting down the repeated database scans and
improving association analysis of traditional apriori algorithm to cluster the
web documents. Further we improve those clusters by applying Fuzzy C-Means
(FCM), K-Means and Vector Space Model (VSM) techniques separately. For
experimental purpose, we use Classic3 and Classic4 datasets of Cornell
University having more than 10,000 documents and run both traditional apriori
and our modified apriori approach on it. Experimental results show that our
approach outperforms the traditional apriori algorithm in terms of database
scan and improvement on association of analysis. We found out that FCM is
better than K-Means and VSM in terms of F-measure of clusters of different
sizes.
Anomalous volatility scaling in high frequency financial data
Date: 2015-12-16 00:00:00
Tasks: Time Series, Time Series Analysis, Vocal Bursts Intensity Prediction

Volatility of intra-day stock market indices computed at various time
horizons exhibits a scaling behaviour that differs from what would be expected
from fractional Brownian motion (fBm). We investigate this anomalous scaling by
using empirical mode decomposition (EMD), a method which separates time series
into a set of cyclical components at different time-scales. By applying the EMD
to fBm, we retrieve a scaling law that relates the variance of the components
to a power law of the oscillating period. In contrast, when analysing 22
different stock market indices, we observe deviations from the fBm and Brownian
motion scaling behaviour. We discuss and quantify these deviations, associating
them to the characteristics of financial markets, with larger deviations
corresponding to less developed markets.
The ecological impact of flooding: a study of tree damage
Date: 2015-03-30 00:00:00

The objective of this research was to identify factors affecting tree damage
in the historical Minot flood of 2011. We hypothesized that tree height,
identity, origin, and maximum water height affect in the severity of damage
sustained by a tree in a flood event. All these factors were significant but
highly interactive. The results from this research can influence planting
practices in valleys and other flood prone areas to mitigate future damage.
Whittle Index Policy for Crawling Ephemeral Content
Authors: Avrachenkov Konstantin  INRIA Sophia Antipolis, Borkar Vivek  EE-IIT
Date: 2015-03-30 00:00:00
Tasks: Problem Decomposition, Scheduling

We consider a task of scheduling a crawler to retrieve content from several
sites with ephemeral content. A user typically loses interest in ephemeral
content, like news or posts at social network groups, after several days or
hours. Thus, development of timely crawling policy for such ephemeral
information sources is very important. We first formulate this problem as an
optimal control problem with average reward. The reward can be measured in the
number of clicks or relevant search requests. The problem in its initial
formulation suffers from the curse of dimensionality and quickly becomes
intractable even with moderate number of information sources. Fortunately, this
problem admits a Whittle index, which leads to problem decomposition and to a
very simple and efficient crawling policy. We derive the Whittle index and
provide its theoretical justification.
New class of distortion risk measures and their tail asymptotics with emphasis on VaR
Date: 2016-03-26 00:00:00

Distortion risk measures are extensively used in finance and insurance
applications because of their appealing properties. We present three methods to
construct new class of distortion functions and measures. The approach involves
the composting methods, the mixing methods and the approach that based on the
theory of copula. Subadditivity is an important property when aggregating risks
in order to preserve the benefits of diversification. However, Value at risk
(VaR), as the most well-known example of distortion risk measure is not always
globally subadditive, except of elliptically distributed risks. In this paper,
instead of study subadditivity we investigate the tail subadditivity for VaR
and other distortion risk measures. In particular, we demonstrate that VaR is
tail subadditive for the case where the support of risk is bounded. Various
examples are also presented to illustrate the results.
Local risk-minimization for Barndorff-Nielsen and Shephard models
Date: 2016-01-27 00:00:00

We obtain explicit representations of locally risk-minimizing strategies of
call and put options for the Barndorff-Nielsen and Shephard models, which are
Ornstein--Uhlenbeck-type stochastic volatility models. Using Malliavin calculus
for Levy processes, Arai and Suzuki (2015) obtained a formula for locally
risk-minimizing strategies for Levy markets under many additional conditions.
Supposing mild conditions, we make sure that the Barndorff-Nielsen and Shephard
models satisfy all the conditions imposed in Arai and Suzuki (2015). Among
others, we investigate the Malliavin differentiability of the density of the
minimal martingale measure. Moreover, some numerical experiments for locally
risk-minimizing strategies are introduced.
Liquid FM: Recommending Music through Viscous Democracy
Authors: Boldi Paolo, Monti Corrado, Santini Massimo, Vigna Sebastiano
Date: 2015-03-30 00:00:00
Tasks: Collaborative Filtering, Music Recommendation, Recommendation Systems

Most modern recommendation systems use the approach of collaborative
filtering: users that are believed to behave alike are used to produce
recommendations. In this work we describe an application (Liquid FM) taking a
completely different approach. Liquid FM is a music recommendation system that
makes the user responsible for the recommended items. Suggestions are the
result of a voting scheme, employing the idea of viscous democracy. Liquid FM
can also be thought of as the first testbed for this voting system. In this
paper we outline the design and architecture of the application, both from the
theoretical and from the implementation viewpoints.
Dynamic indifference pricing via the G-expectation
Authors: Qian Lin
Date: 2015-03-30 00:00:00

We study the dynamic indifference pricing with ambiguity preferences. For this, we introduce the dynamic expected utility with ambiguity via the nonlinear expectation--G-expectation, introduced by Peng (2007). We also study the risk aversion and certainty equivalent for the agents with ambiguity. We obtain the dynamic consistency of indifference pricing with ambiguity preferences. Finally, we obtain comparative statics.