pwc-archive/papers-with-abstracts huggingface dataset:
Missing and spurious interaction in additive, multiplicative and odds ratio models
Authors: Jorge Fernandez-de-Cossio, Jorge Fernandez-de-Cossio-Diaz, Toshifumi Takao, Yasser Perera
Date: 2017-12-12 00:00:00
Tasks: Epidemiology

Additive, multiplicative, and odd ratio neutral models for interactions are for long advocated and controversial in epidemiology. We show here that these commonly advocated models are biased, leading to spurious interactions, and missing true interactions.
Fair valuation of L\'evy-type drawdown-drawup contracts with general insured and penalty functions
Date: 2018-02-19 00:00:00

In this paper, we analyse some equity-linked contracts that are related to
drawdown and drawup events based on assets governed by a geometric spectrally
negative L\'evy process. Drawdown and drawup refer to the differences between
the historical maximum and minimum of the asset price and its current value,
respectively. We consider four contracts. In the first contract, a protection
buyer pays a premium with a constant intensity $p$ until the drawdown of fixed
size occurs. In return, he/she receives a certain insured amount at the
drawdown epoch, which depends on the drawdown level at that moment. Next, the
insurance contract may expire earlier if a certain fixed drawup event occurs
prior to the fixed drawdown. The last two contracts are extensions of the
previous ones but with an additional cancellable feature that allows the
investor to terminate the contracts earlier. In these cases, a fee for early
stopping depends on the drawdown level at the stopping epoch. In this work, we
focus on two problems: calculating the fair premium $p$ for basic contracts and
finding the optimal stopping rule for the polices with a cancellable feature.
To do this, we use a fluctuation theory of L\'evy processes and rely on a
theory of optimal stopping.
Deciphering the 'fuzzy' interaction of FG nucleoporins and transport factors using SANS
Date: 2018-01-10 00:00:00

The largely intrinsically disordered phenylalanine-glycine-rich nucleoporins
(FG Nups) underline a selectivity mechanism, which enables the rapid
translocation of transport factors (TFs) through the nuclear pore complexes
(NPCs). Conflicting models of NPC transport have assumed that FG Nups undergo
different conformational transitions upon interacting with TFs. To selectively
characterize conformational changes in FG Nups induced by TFs we performed
small-angle neutron scattering (SANS) with contrast matching. Conformational
ensembles derived SANS data indicate an increase in the overall size of FG Nups
is associated with TF interaction. Moreover, the organization of the FG motif
in the interacting state is consistent with prior experimental analyses
defining that FG motifs undergo conformational restriction upon interacting
with TFs. These results provide structural insights into a highly dynamic
interaction and illustrate how functional disorder imparts rapid and selective
FG Nup / TF interactions.
Bursting endemic bubbles in an adaptive network
Date: 2018-04-13 00:00:00

The spread of an infectious disease is known to change people's behavior,
which in turn affects the spread of disease. Adaptive network models that
account for both epidemic and behavior change have found oscillations, but in
an extremely narrow region of the parameter space, which contrasts with
intuition and available data. In this paper we propose a simple SIS epidemic
model on an adaptive network with time-delayed rewiring, and show that
oscillatory solutions are now present in a wide region of the parameter space.
Altering the transmission or rewiring rates reveals the presence of an endemic
bubble - an enclosed region of the parameter space where oscillations are
observed.
Analysis and Optimization of Aperture Design in Computational Imaging
Date: 2017-12-12 00:00:00

There is growing interest in the use of coded aperture imaging systems for a
variety of applications. Using an analysis framework based on mutual
information, we examine the fundamental limits of such systems---and the
associated optimum aperture coding---under simple but meaningful propagation
and sensor models. Among other results, we show that when thermal noise
dominates, spectrally-flat masks, which have 50% transmissivity, are optimal,
but that when shot noise dominates, randomly generated masks with lower
transmissivity offer greater performance. We also provide comparisons to
classical pinhole cameras.
Online Nonlinear Estimation via Iterative L2-Space Projections: Reproducing Kernel of Subspace
Date: 2018-09-12 00:00:00

We propose a novel online learning paradigm for nonlinear-function estimation
tasks based on the iterative projections in the L2 space with probability
measure reflecting the stochastic property of input signals. The proposed
learning algorithm exploits the reproducing kernel of the so-called dictionary
subspace, based on the fact that any finite-dimensional space of functions has
a reproducing kernel characterized by the Gram matrix. The L2-space geometry
provides the best decorrelation property in principle. The proposed learning
paradigm is significantly different from the conventional kernel-based learning
paradigm in two senses: (i) the whole space is not a reproducing kernel Hilbert
space and (ii) the minimum mean squared error estimator gives the best
approximation of the desired nonlinear function in the dictionary subspace. It
preserves efficiency in computing the inner product as well as in updating the
Gram matrix when the dictionary grows. Monotone approximation, asymptotic
optimality, and convergence of the proposed algorithm are analyzed based on the
variable-metric version of adaptive projected subgradient method. Numerical
examples show the efficacy of the proposed algorithm for real data over a
variety of methods including the extended Kalman filter and many batch
machine-learning methods such as the multilayer perceptron.
Everything You Always Wanted to Know About TREC RTS* (*But Were Afraid to Ask)
Authors: Hubert Gilles, Moreno Jose G., Pinel-Sauvagnat Karen, Pitarch Yoann
Date: 2017-12-13 00:00:00

The TREC Real-Time Summarization (RTS) track provides a framework for
evaluating systems monitoring the Twitter stream and pushing tweets to users
according to given profiles. It includes metrics, files, settings and
hypothesis provided by the organizers. In this work, we perform a thorough
analysis of each component of the framework used in 2016 and 2017 and found
some limitations for the Scenario A of this track. Our main findings point out
the weakness of the metrics and give clear recommendations to fairly reuse the
collection.
Increased hepatic PDGF-AA signaling mediates liver insulin resistance in obesity associated type 2 diabetes
Date: 2017-12-13 00:00:00
Tasks: Blocking

Type 2 diabetes (T2D) is closely linked with non-alcoholic fatty liver
disease (NAFLD) and hepatic insulin resistance, but the involved mechanisms are
still elusive. Using DNA methylome and transcriptome analyses of livers from
obese individuals, we found that both hypomethylation at a CpG site in PDGFA
(encoding platelet derived growth factor alpha) and PDGFA overexpression are
associated with increased T2D risk, hyperinsulinemia, increased insulin
resistance and increased steatohepatitis risk. Both genetic risk score studies
and human cell modeling pointed to a causative impact of high insulin levels on
PDGFA CpG site hypomethylation, PDGFA overexpression, and increased PDGF-AA
secretion from liver. We found that PDGF-AA secretion further stimulates its
own expression through protein kinase C activity and contributes to insulin
resistance through decreased expression of both insulin receptor substrate 1
and of insulin receptor. Importantly, hepatocyte insulin sensitivity can be
restored by PDGF-AA blocking antibodies, PDGF receptor inhibitors and by
metformin opening therapeutic avenues. Conclusion: Therefore, in the liver of
obese patients with T2D, the increased PDGF-AA signaling contributes to insulin
resistance, opening new therapeutic avenues against T2D and NAFLD.
Localization of multilayer networks by the optimized single-layer rewiring
Date: 2018-02-21 00:00:00

We study localization properties of principal eigenvector (PEV) of multilayer
networks. Starting with a multilayer network corresponding to a delocalized
PEV, we rewire the network edges using an optimization technique such that the
PEV of the rewired multilayer network becomes more localized. The framework
allows us to scrutinize structural and spectral properties of the networks at
various localization points during the rewiring process. We show that rewiring
only one-layer is enough to attain a multilayer network having a highly
localized PEV. Our investigation reveals that a single edge rewiring of the
optimized multilayer network can lead to the complete delocalization of a
highly localized PEV. This sensitivity in the localization behavior of PEV is
accompanied by a pair of almost degenerate eigenvalues. This observation opens
an avenue to gain a deeper insight into the origin of PEV localization of
networks. Furthermore, analysis of multilayer networks constructed using
real-world social and biological data show that the localization properties of
these real-world multilayer networks are in good agreement with the simulation
results for the model multilayer network. The study is relevant to applications
that require understanding propagation of perturbation in multilayer networks.
Optimal Stochastic Decensoring and Applications to Calibration of Market Models
Date: 2017-12-18 00:00:00

Typically flat filling, linear or polynomial interpolation methods to
generate missing historical data. We introduce a novel optimal method for
recreating data generated by a diffusion process. The results are then applied
to recreate historical data for stocks.
Stock market as temporal network
Date: 2017-12-13 00:00:00
Tasks: Management, Portfolio Optimization

Financial networks have become extremely useful in characterizing the
structure of complex financial systems. Meanwhile, the time evolution property
of the stock markets can be described by temporal networks. We utilize the
temporal network framework to characterize the time-evolving correlation-based
networks of stock markets. The market instability can be detected by the
evolution of the topology structure of the financial networks. We employ the
temporal centrality as a portfolio selection tool. Those portfolios, which are
composed of peripheral stocks with low temporal centrality scores, have
consistently better performance under different portfolio optimization schemes,
suggesting that the temporal centrality measure can be used as new portfolio
optimization and risk management tools. Our results reveal the importance of
the temporal attributes of the stock markets, which should be taken serious
consideration in real life applications.
Why early tactile speech aids may have failed: no perceptual integration of tactile and auditory signals
Date: 2017-11-28 00:00:00

Tactile speech aids, though extensively studied in the 1980s and 90s, never
became a commercial success. A hypothesis to explain this failure might be that
it is difficult to obtain true perceptual integration of a tactile signal with
information from auditory speech: exploitation of tactile cues from a tactile
aid might require cognitive effort and so prevent speech understanding at the
high rates typical of everyday speech. To test this hypothesis, we attempted to
create true perceptual integration of tactile with auditory information in what
might be considered the simplest situation encountered by a hearing-impaired
listener. We created an auditory continuum between the syllables BA and VA, and
trained participants to associate BA to one tactile stimulus VA to another
tactile stimulus. After training, we tested if auditory discrimination along
the continuum between the two syllables could be biased by incongruent tactile
stimulation. We found that such a bias occurred only when the tactile stimulus
was above its previously measured tactile discrimination threshold. Such a
pattern is compatible with the idea that the effect is due to a cognitive or
decisional strategy, rather than to truly perceptual integration. We therefore
ran a further study, where we created a tactile version of the McGurk effect.
We extensively trained two Subjects over six days to associate four recorded
auditory syllables with four corresponding apparent motion tactile patterns. In
a subsequent test, we presented stimulation that was either congruent or
incongruent with the learnt association, and asked Subjects to report the
syllable they perceived. We found no analog to the McGurk effect. These
findings strengthen our hypothesis according to which tactile aids failed
because integration of tactile cues with auditory speech occurred at a
cognitive or decisional level, rather than truly at a perceptual level
Series representation of the pricing formula for the European option driven by space-time fractional diffusion
Date: 2018-10-15 00:00:00

In this paper, we show that the price of an European call option, whose
underlying asset price is driven by the space-time fractional diffusion, can be
expressed in terms of rapidly convergent double-series. The series formula can
be obtained from the Mellin-Barnes representation of the option price with help
of residue summation in $\mathbb{C}^2$. We also derive the series
representation for the associated risk-neutral factors, obtained by Esscher
transform of the space-time fractional Green functions.
Language: The missing selection pressure
Date: 2017-12-13 00:00:00

Human beings are talkative. What advantage did their ancestors find in
communicating so much? Numerous authors consider this advantage to be "obvious"
and "enormous". If so, the problem of the evolutionary emergence of language
amounts to explaining why none of the other primate species evolved anything
even remotely similar to language. What I propose here is to reverse the
picture. On closer examination, language resembles a losing strategy. Competing
for providing other individuals with information, sometimes striving to be
heard, makes apparently no sense within a Darwinian framework. At face value,
language as we can observe it should never have existed or should have been
counter-selected. In other words, the selection pressure that led to language
is still missing. The solution I propose consists in regarding language as a
social signaling device that developed in a context of generalized insecurity
that is unique to our species. By talking, individuals advertise their
alertness and their ability to get informed. This hypothesis is shown to be
compatible with many characteristics of language that otherwise are left
unexplained.
The Mathematics of Market Timing
Date: 2017-12-13 00:00:00
Tasks: Math

Market timing is an investment technique that tries to continuously switch
investment into assets forecast to have better returns. What is the likelihood
of having a successful market timing strategy? With an emphasis on modeling
simplicity, I calculate the feasible set of market timing portfolios using
index mutual fund data for perfectly timed (by hindsight) all or nothing
quarterly switching between two asset classes, US stocks and bonds over the
time period 1993--2017. The historical optimal timing path of switches is shown
to be indistinguishable from a random sequence. The key result is that the
probability distribution function of market timing returns is asymetric, that
the highest probability outcome for market timing is a below median return. Put
another way, simple math says market timing is more likely to lose than to
win---even before accounting for costs. The median of the market timing return
probability distribution can be directly calculated as a weighted average of
the returns of the model assets with the weights given by the fraction of time
each asset has a higher return than the other. For the time period of the data
the median return was close to, but not identical with, the return of a static
60:40 stock:bond portfolio. These results are illustrated through Monte Carlo
sampling of timing paths within the feasible set and by the observed return
paths of several market timing mutual funds.
Single gene dynamics under controlled mating
Date: 2017-12-14 00:00:00
Tasks: Management

We seek models for the genotype evolution of agricultural animals, animals
involved in primary production processes. Classical models for genotype
evolution have tended to be very simple in order that analytic methods may be
employed in their study. Unfortunately these models fail to describe processes
in artificially controlled populations including agricultural livestock. It is
particularly important {to describe such processes} in order to make better use
of the massive genotyping data becoming available. We describe an approach to
stochastically modeling the dynamics of a biallelic polymorphism herds under
conditions of controlled mating {and restriction of herds size from above}. The
system of stochastic differential equations that we propose is based on jump
diffusion processes to provide an effective platform for Monte Carlo
simulation. A feature of the model is the division of the {population} into a
{\it main herd} comprised of animals involved in the production process and a
{\it replacement herd} of {animals not currently in the production process,
typically juvenile animals}. This feature allows for exploring different
strategies for adding replacement animals to the main herd without altering the
part of the model concerned with the dynamics of the main herd. A discrete-time
version of the model has been developed which reflects the typical practice of
New Zealand dairy herd management. Our Monte Carlo simulation has demonstrated
that an isolated deme whose size is bounded above demonstrate size
stabilization at a level less than the control limit, it is looks like partial
extinction, the effect being well known in classic models.
Late stages of mineralisation and their signature on the bone mineral density distribution
Date: 2017-12-14 00:00:00

Purpose: Experimental measurements of bone mineral density distributions
(BMDDs) enable a determination of secondary mineralisation kinetics in bone,
but the maximum degree of mineralisation and how this maximum is approached
remain uncertain. We thus test computationally different hypotheses on late
stages of bone mineralisation by simulating BMDDs in low turnover conditions.
Materials and Methods: An established computational model of the BMDD that
accounts for mineralisation and remodelling processes was extended to limit
mineralisation to various maximum calcium capacities of bone. Simulated BMDDs
obtained by reducing turnover rate from the reference trabecular BMDD under
different assumptions on late stage mineralisation kinetics were compared with
experimental BMDDs of low-turnover bone. Results: Simulations show that an
abrupt stopping of mineralisation near a maximum calcium capacity induces a
pile-up of minerals in the BMDD statistics that is not observed experimentally.
With a smooth decrease of mineralisation rate, imposing low maximum calcium
capacities helps to match peak location and width of simulated low turnover
BMDDs with peak location and width of experimental BMDDs, but results in a
distinctive asymmetric peak shape. No tuning of turnover rate and maximum
calcium capacity was able to explain the differences found in experimental
BMDDs between trabecular bone (high turnover) and femoral cortical bone (low
turnover). Conclusions: Secondary mineralisation in human bone does not stop
abruptly, but continues slowly up to a calcium content greater than 30 wt% Ca.
The similar mineral heterogeneity seen in trabecular and femoral cortical bones
at different peak locations was unexplained by turnover differences tested.
The evaluation of geometric Asian power options under time changed mixed fractional Brownian motion
Date: 2017-12-14 00:00:00

The aim of this paper is to evaluate geometric Asian option by a mixed
fractional subdiffusive Black-Scholes model. We derive a pricing formula for
geometric Asian option when the underlying stock follows a time changed mixed
fractional Brownian motion. We then apply the results to price Asian power
options on the stocks that pay constant dividends when the payoff is a power
function. Finally, lower bound of Asian options and some special cases are
provided.
A Data Driven Approach for Resting-state EEG signal Classification of Schizophrenia with Control Participants using Random Matrix Theory
Date: 2018-01-17 00:00:00
Tasks: Classification, EEG, EEG Signal Classification, Electroencephalogram (EEG)

Resting state electroencephalogram (EEG) abnormalities in clinically
high-risk individuals (CHR), clinically stable first-episode patients with
schizophrenia (FES), healthy controls (HC) suggest alterations in neural
oscillatory activity. However, few studies directly compare these anomalies
among each types. Therefore, this study investigated whether these
electrophysiological characteristics differentiate clinical populations from
one another, and from non-psychiatric controls. To address this question,
resting EEG power and coherence were assessed in 40 clinically high-risk
individuals (CHR), 40 first-episode patients with schizophrenia (FES), and 40
healthy controls (HC). These findings suggest that resting EEG can be a
sensitive measure for differentiating between clinical disorders.This paper
proposes a novel data-driven supervised learning method to obtain
identification of the patients mental status in schizophrenia research.
According to Marchenko-Pastur Law, the distribution of the eigenvalues of EEG
data is divided into signal subspace and noise subspace. A test statistic named
LES that embodies the characteristics of all eigenvalues is adopted. different
classifier and different feature(LES test function) are selected for
experiments, we have shown that using von Neumann Entropy as LES test function
combine with SVM classifier could obtain the best average classification
accuracy during three classification among HC, FES and CHR of Schizophrenia
group with EEG signal. It is worth noting that the result of LES feature
extraction with the highest classification accuracy is around 90% in two
classification(HC compare with FES) and around 70% in three classification.
Where the classification accuracy higher than 70% could be used to assist
clinical diagnosis.
Analysis and calibration of a linear model for structured cell populations with unidirectional motion : Application to the morphogenesis of ovarian follicles
Date: 2017-12-14 00:00:00

We analyze a multi-type age dependent model for cell populations subject to
unidirectional motion, in both a stochastic and deterministic framework. Cells
are distributed into successive layers; they may divide and move irreversibly
from one layer to the next. We adapt results on the large-time convergence of
PDE systems and branching processes to our context, where the Perron-Frobenius
or Krein-Rutman theorem can not be applied. We derive explicit analytical
formulas for the asymptotic cell number moments, and the stable age
distribution. We illustrate these results numerically and we apply them to the
study of the morphodynamics of ovarian follicles. We prove the structural
parameter identifiability of our model in the case of age independent division
rates. Using a set of experimental biological data, we estimate the model
parameters to fit the changes in the cell numbers in each layer during the
early stages of follicle development.