pwc-archive/papers-with-abstracts huggingface dataset:
Bridging the time scales of single-cell and population dynamics
Date: 2018-01-20 00:00:00

How are granular details of stochastic growth and division of individual
cells reflected in smooth deterministic growth of population numbers? We
provide an integrated, multiscale perspective of microbial growth dynamics by
formulating a data-validated theoretical framework that accounts for
observables at both single-cell and population scales. We derive exact
analytical complete time-dependent solutions to cell-age distributions and
population growth rates as functionals of the underlying interdivision time
distributions, for symmetric and asymmetric cell division. These results
provide insights into the surprising implications of stochastic single-cell
dynamics for population growth. Using our results for asymmetric division, we
deduce the time to transition from the reproductively quiescent (swarmer) to
replication-competent (stalked) stage of the {\em Caulobacter crescentus}
lifecycle. Remarkably, population numbers can spontaneously oscillate with
time. We elucidate the physics leading to these population oscillations. For
{\em C. crescentus} cells, we show that a simple measurement of the population
growth rate, for a given growth condition, is sufficient to characterize the
condition-specific cellular unit of time, and thus yields the mean
(single-cell) growth and division timescales, fluctuations in cell division
times, the cell age distribution, and the quiescence timescale.
Computation of first-order Greeks for barrier options using chain rules for Wiener path integrals
Date: 2016-12-21 00:00:00

This paper presents a new methodology to compute first-order Greeks for
barrier options under the framework of path-dependent payoff functions with
European, Lookback, or Asian type and with time-dependent trigger levels. In
particular, we develop chain rules for Wiener path integrals between two curves
that arise in the computation of first-order Greeks for barrier options. We
also illustrate the effectiveness of our method through numerical examples.
Simple Yet Effective Methods for Large-Scale Scholarly Publication Ranking
Authors: Herrmannova Drahomira, Knoth Petr
Date: 2016-11-16 00:00:00

With the growing amount of published research, automatic evaluation of
scholarly publications is becoming an important task. In this paper we address
this problem and present a simple and transparent approach for evaluating the
importance of scholarly publications. Our method has been ranked among the top
performers in the WSDM Cup 2016 Challenge. The first part of this paper
describes our method. In the second part we present potential improvements to
the method and analyse the evaluation setup which was provided during the
challenge. Finally, we discuss future challenges in automatic evaluation of
papers including the use of full-texts based evaluation methods.
Toward Economics as a New Complex System
Date: 2016-11-15 00:00:00

The 2015 Nobel Prize in Economic Sciences was awarded to Eugene Fama, Lars
Peter Hansen and Robert Shiller for their contributions to the empirical
analysis of asset prices. Eugene Fama [1] is an advocate of the efficient
market hypothesis. The efficient market hypothesis assumes that asset price is
determined by using all available information and only reacts to new
information not incorporated into the fundamentals. Thus, the movement of stock
prices is unpredictable. Robert Shiller [2] has been studying the existence of
irrational bubbles, which are defined as the long term deviations of asset
price from the fundamentals. This drives us to the unsettled question of how
the market actually works.
  In this paper, I look back at the development of economics and consider the
direction in which we should move in order to truly understand the workings of
an economic society.
Analysis of Price and Income Elasticities of Energy Demand in Ecuador: A Dynamic OLS Approach
Date: 2016-11-16 00:00:00
Tasks: Position

Energy consumption in Ecuador has increased significantly during the last
decades, affecting negatively the financial position of the country since large
energy consumption subsidies are provided in its internal market and Ecuador is
mostly a crude oil exporter and oil derivatives importer country. This research
seeks to state the long run price and income elasticities of energy demand in
Ecuador, by analyzing information spanning the period from 1970 to 2015. A
cointegration analysis and an estimation by using a Dynamic Ordinary Least
Squares approach considering structural breaks is carried out. Results obtained
are robust and suggest that in the long run energy demand in Ecuador is highly
income elastic, has no relationship with its price and has an almost unitary
but inverse relationship with the industrial production level. Conclusions and
economic policy suggestions are also provided.
Bridging the Gap between Individuality and Joint Improvisation in the Mirror Game
Date: 2016-11-16 00:00:00

Extensive experiments in Human Movement Science suggest that solo motions are
characterized by unique features that define the individuality or motor
signature of people. While interacting with others, humans tend to
spontaneously coordinate their movement and unconsciously give rise to joint
improvisation. However, it has yet to be shed light on the relationship between
individuality and joint improvisation. By means of an ad-hoc virtual agent, in
this work we uncover the internal mechanisms of the transition from solo to
joint improvised motion in the mirror game, a simple yet effective paradigm for
studying interpersonal human coordination. According to the analysis of
experimental data, normalized segments of velocity in solo motion are regarded
as individual motor signature, and the existence of velocity segments
possessing a prescribed signature is theoretically guaranteed. In this work, we
first develop a systematic approach based on velocity segments to generate
\emph{in-silico} trajectories of a given human participant playing solo. Then
we present an online algorithm for the virtual player to produce joint
improvised motion with another agent while exhibiting some desired kinematic
characteristics, and to account for movement coordination and mutual adaptation
during joint action tasks. Finally, we demonstrate that the proposed approach
succeeds in revealing the kinematic features transition from solo to joint
improvised motions, thus revealing the existence of a tight relationship
between individuality and joint improvisation.
The Pattern Recognition of Probability Distributions of Amino acids in protein families
Date: 2016-10-13 00:00:00

A pattern Recognition of a probability distribution of amino acids is
obtained for selected families of proteins. The mathematical model is derived
from a theory of protein families formation which is derived from application
of a Pauli's master equation method.
Robust Trading of Implied Skew
Date: 2016-11-17 00:00:00

In this paper, we present a method for constructing a (static) portfolio of
co-maturing European options whose price sign is determined by the skewness
level of the associated implied volatility. This property holds regardless of
the validity of a specific model - i.e. the method is robust. The strategy is
given explicitly and depends only on beliefs about the future values of implied
skewness, which is an observable market indicator. As such, our method allows
to use the existing statistical tools to formulate the beliefs, providing a
practical interpretation of the more abstract mathematical setting, in which
the belies are understood as a family of probability measures. One of the
applications of our results is a method for trading views on the future changes
in implied skew, largely independently of other market factors. Another
application provides a concrete improvement of the existing model-independent
super- and sub- replication strategies for barrier options, which exploits a
given set of beliefs on the implied skew. Our theoretical results are tested
empirically, using the historical prices of SP500 options.
Random matrix approach to estimation of high-dimensional factor models
Date: 2017-11-23 00:00:00
Tasks: Dimensionality Reduction, Time Series, Time Series Analysis, Vocal Bursts Intensity Prediction

In dealing with high-dimensional data sets, factor models are often useful
for dimension reduction. The estimation of factor models has been actively
studied in various fields. In the first part of this paper, we present a new
approach to estimate high-dimensional factor models, using the empirical
spectral density of residuals. The spectrum of covariance matrices from
financial data typically exhibits two characteristic aspects: a few spikes and
bulk. The former represent factors that mainly drive the features and the
latter arises from idiosyncratic noise. Motivated by these two aspects, we
consider a minimum distance between two spectrums; one from a covariance
structure model and the other from real residuals of financial data that are
obtained by subtracting principal components. Our method simultaneously
provides estimators of the number of factors and information about correlation
structures in residuals. Using free random variable techniques, the proposed
algorithm can be implemented and controlled effectively. Monte Carlo
simulations confirm that our method is robust to noise or the presence of weak
factors. Furthermore, the application to financial time-series shows that our
estimators capture essential aspects of market dynamics.
The Tragedy of Your Upstairs Neighbors: Is the Airbnb Negative Externality Internalized?
Date: 2015-12-16 00:00:00

A commonly expressed concern about the rise of the peer-to-peer rental market
Airbnb is that hosts---those renting out their properties---impose costs on
their unwitting neighbors. I consider the question of whether apartment
building owners will, in a competitive rental market, set a building-specific
Airbnb hosting policy that is socially efficient. I find that if tenants can
sort across apartments based on the owners policy then the equilibrium fraction
of buildings allowing Airbnb listing would be socially efficient.
From cells to tissue: A continuum model of epithelial mechanics
Date: 2017-04-23 00:00:00

A continuum model of epithelial tissue mechanics was formulated using
cellular-level mechanical ingredients and cell morphogenetic processes,
including cellular shape changes and cellular rearrangements. This model can
include finite deformation, and incorporates stress and deformation tensors,
which can be compared with experimental data. Using this model, we elucidated
dynamical behavior underlying passive relaxation, active
contraction-elongation, and tissue shear flow. This study provides an
integrated scheme for the understanding of the mechanisms that are involved in
orchestrating the morphogenetic processes in individual cells, in order to
achieve epithelial tissue morphogenesis.
Estimation of reproduction number and non stationary spectral analysis of Dengue epidemic
Date: 2016-11-16 00:00:00

In this work we analyze the post monsoon Dengue outbreaks by analyzing the
transient and long term dynamics of Dengue incidences and its environmental
correlates in Ahmedabad city in western India from 2005-2012. We calculate the
reproduction number $R_p$ using the growth rate of post monsoon Dengue
outbreaks and biological parameters like host and vector incubation periods and
vector mortality rate, and its uncertainties are estimated through Monte-Carlo
simulations by sampling parameters from their respective probability
distributions. Reduction in Female Aedes mosquito density required for an
effective prevention of Dengue outbreaks is also calculated. The non stationary
pattern of Dengue incidences and its climatic correlates like rainfall
temperature is analyzed through Wavelet based methods. We find that the mean
time lag between peak of monsoon and Dengue is 9 weeks. Monsoon and Dengue
cases are phase locked from 2008-2012 in the 16-32 weeks band. The duration of
post monsoon outbreak has been increasing every year, especially post 2008,
even though the intensity and duration of monsoon has been decreasing.
Temperature and Dengue incidences show correlations in the same band, but phase
lock is not stationary.
Phylogenetic trees
Date: 2016-11-17 00:00:00

We introduce the package PhylogeneticTrees for Macaulay2 which allows users
to compute phylogenetic invariants for group-based tree models. We provide some
background information on phylogenetic algebraic geometry and show how the
package PhylogeneticTrees can be used to calculate a generating set for a
phylogenetic ideal as well as a lower bound for its dimension. Finally, we show
how methods within the package can be used to compute a generating set for the
join of any two ideals.
Balancing specificity, sensitivity and speed of ligand discrimination by zero-order ultraspecificity
Date: 2016-11-17 00:00:00
Tasks: Decision Making, Sensitivity, Specificity

Specific interactions between receptors and their target ligands in the
presence of non-target ligands are crucial for biological processes such as T
cell ligand discrimination. To discriminate between the target and non-target
ligands, cells have to increase specificity by amplifying the small differences
in affinity among ligands. In addition, sensitivity to ligand concentration and
quick discrimination are also important to detect low amounts of target ligands
and facilitate fast cellular decision making after ligand recognition. In this
work, we find that ultraspecificity is naturally derived from a well-known
mechanism for zero-order ultrasensitivity to concentration. We also show that
this mechanism can produce an optimal balance of specificity, sensitivity, and
quick discrimination. Furthermore, we show that a model for insensitivity to
large number of non-terget ligands can be naturally derived from the
ultraspecificity model. Zero-order ultraspecificity may provide alternative way
to understand ligand discrimination from the viewpoint of the nonlinear
properties of biochemical reactions.
Biodiversity in models of cyclic dominance is preserved by heterogeneity in site-specific invasion rates
Date: 2016-11-17 00:00:00

Global, population-wide oscillations in models of cyclic dominance may result
in the collapse of biodiversity due to the accidental extinction of one species
in the loop. Previous research has shown that such oscillations can emerge if
the interaction network has small-world properties, and more generally, because
of long-range interactions among individuals or because of mobility. But
although these features are all common in nature, global oscillations are
rarely observed in actual biological systems. This begets the question what is
the missing ingredient that would prevent local oscillations to synchronize
across the population to form global oscillations. Here we show that, although
heterogeneous species-specific invasion rates fail to have a noticeable impact
on species coexistence, randomness in site-specific invasion rates successfully
hinders the emergence of global oscillations and thus preserves biodiversity.
Our model takes into account that the environment is often not uniform but
rather spatially heterogeneous, which may influence the success of microscopic
dynamics locally. This prevents the synchronization of locally emerging
oscillations, and ultimately results in a phenomenon where one type of
randomness is used to mitigate the adverse effects of other types of randomness
in the system.
Morphology of Fly Larval Class IV Dendrites Accords with a Random Branching and Contact Based Branch Deletion Model
Date: 2016-11-17 00:00:00

Dendrites are branched neuronal processes that receive input signals from
other neurons or the outside world [1]. To maintain connectivity as the
organism grows, dendrites must also continue to grow. For example, the
dendrites in the peripheral nervous system continue to grow and branch to
maintain proper coverage of their receptor fields [2, 3, 4, 5]. One such neuron
is the Drosophila melanogaster class IV dendritic arborization neuron [6]. The
dendritic arbors of these neurons tile the larval surface [7], where they
detect localized noxious stimuli, such as jabs from parasitic wasps [8]. In the
present study, we used a novel measure, the hitting probability, to show that
the class IV neuron forms a tight mesh that covers the larval surface.
Furthermore, we found that the mesh size remains largely unchanged during the
larval stages, despite a dramatic increase in overall size of the neuron and
the larva. We also found that the class IV dendrites are dense (assayed with
the fractal dimension) and uniform (assayed with the lacunarity) throughout the
larval stages. To understand how the class IV neuron maintains its morphology
during larval development, we constructed a mathematical model based on random
branching and self-avoidance. We found that if the branching rate is uniform in
space and time and that if all contacting branches are deleted, we can
reproduce the branch length distribution, mesh size and density of the class IV
dendrites throughout the larval stages. Thus, a simple set of statistical rules
can generate and maintain a complex branching morphology during growth.
Burkholderia genome mining for nonribosomal peptide synthetases reveals a great potential for novel siderophores and lipopeptides synthesis
Date: 2016-11-18 00:00:00

Burkholderia is an important genus encompassing a variety of species,
including pathogenic strains as well as strains that promote plant growth. We
have carried out a global strategy, which combined two complementary
approaches. The first one is genome guided with deep analysis of genome
sequences and the second one is assay guided with experiments to support the
predictions obtained in silico. This efficient screening for new secondary
metabolites, performed on 48 gapless genomes of Burkholderia species, revealed
a total of 161 clusters containing nonribosomal peptide synthetases (NRPSs),
with the potential to synthesize at least 11 novel products. Most of them are
siderophores or lipopeptides, two classes of products with potential
application in biocontrol. The strategy led to the identification, for the
first time, of the cluster for cepaciachelin biosynthesis in the genome of
Burkholderia ambifaria AMMD and a cluster corresponding to a new
malleobactin-like siderophore, called phymabactin, was identified in
Burkholderia phymatum STM815 genome. In both cases, the siderophore was
produced when the strain was grown in iron-limited conditions. Elsewhere, the
cluster for the antifungal burkholdin was detected in the genome of B.
ambifaria AMMD and also Burkholderia sp. KJ006. Burkholderia pseudomallei
strains harbor the genetic potential to produce a novel lipopeptide called
burkhomycin, containing a peptidyl moiety of 12 monomers. A mixture of
lipopeptides produced by Burkholderia rhizoxinica lowered the surface tension
of the supernatant from 70 to 27 mN/m. The production of nonribosomal secondary
metabolites seems related to the three phylogenetic groups obtained from 16S
rRNA sequences. Moreover, the genome-mining approach gave new insights into the
nonribosomal synthesis exemplified by the identification of dual C/E domains in
lipopeptide NRPSs, up to now essentially found in Pseudomonas strains.
Variants of intrinsic disorder in the human proteome
Date: 2016-11-18 00:00:00

In this paper we propose a straightforward operational definition of variants
of disordered proteins, taking the human proteome as a case study. The focus is
on a distinction between mostly unstructured proteins and proteins which
contain long unstructured regions accommodated in an overall folded structure.
In particular we distinguish: i) Not disordered proteins (NDPs), that either
have all their residues ordered or do not have disordered segments longer than
30 residues nor more than 30% of disordered residues; ii) Proteins with
intrinsically disordered regions (IDRPs), that have at least one disordered
domain longer than 30 residues, but disordered in less than 30% of their
residues; iii) Proteins that are intrinsically disordered (IDPs), that have
both at least one disordered segment longer than 30 residues and that are
disordered on more than 30% of their residues; iv) Proteins with fragmented
disorder (FRAG_IDPs), that do not have a disordered fragment longer than 30
residues but that, nevertheless, have at least 30% or more of their residues
predicted as disordered. The potential use of these variants is checked over
several groups of disease-related proteins. Our main conclusions point out that
IDRPs are more similar to NDPs than to IDPs. IDRPs and NDPs have a similar
functional repertoire and probably share a lock-and-key mechanism of
interaction with substrates. IDRPs and IDPs are differently present among human
disease-related proteins. IDRPs probably do not play a specific role in the
development of complex diseases, since their frequency is similar in
disease-related proteins and in the entire human proteome. IDPs can play a role
in the emergence of cancer, neurodegenerative, thyroid and liver disease.
Evaluating genetic drift in time-series evolutionary analysis
Date: 2016-11-18 00:00:00
Tasks: Time Series, Time Series Analysis

The Wright-Fisher model is the most popular population model for describing
the behaviour of evolutionary systems with a finite population size.
Approximations to the model have commonly been used for the analysis of
time-resolved genome sequence data, but the model itself has rarely been tested
against genomic data. Here, we evaluate the extent to which it can be inferred
as the correct model given experimental data. Given genome-wide data from an
evolutionary experiment, we validate the Wright-Fisher model as the better
model for variance in a finite population in contrast to a Gaussian model of
allele frequency propagation. However, we note a range of circumstances under
which the Wright-Fisher model cannot be correctly identified. We discuss the
potential for more rapid approximations to the Wright-Fisher model.
Calibration to American Options: Numerical Investigation of the de-Americanization
Date: 2016-11-18 00:00:00

American options are the reference instruments for the model calibration of a
large and important class of single stocks. For this task, a fast and accurate
pricing algorithm is indispensable. The literature mainly discusses pricing
methods for American options that are based on Monte Carlo, tree and partial
differential equation methods. We present an alternative approach that has
become popular under the name de-Americanization in the financial industry. The
method is easy to implement and enjoys fast run-times. Since it is based on ad
hoc simplifications, however, theoretical results guaranteeing reliability are
not available. To quantify the resulting methodological risk, we empirically
test the performance of the de-Americanization method for calibration. We
classify the scenarios in which de-Americanization performs very well. However,
we also identify the cases where de-Americanization oversimplifies and can
result in large errors.