pwc-archive/papers-with-abstracts huggingface dataset:
Noise-plasticity correlations of gene expression in the multicellular organism Arabidopsis thaliana
Date: 2015-11-12 00:00:00
Tasks: Rhythm

Gene expression levels exhibit stochastic variations among genetically
identical organisms under the same environmental conditions (called gene
expression "noise" or phenotype "fluctuation"). In yeast and Escherichia coli,
positive correlations have been found between such gene expression noise and
"plasticity" with environmental variations. To determine the universality of
such correlations in both unicellular and multicellular organisms, we focused
on the relationships between gene expression "noise" and "plasticity" in
Arabidopsis thaliana, a multicellular model organism. In recent studies on
yeast and E. coli, only some gene groups with specific properties of promoter
architecture, average expression levels, and functions exhibited strong
noise-plasticity correlations. However, we found strong noise-plasticity
correlations for most gene groups in Arabidopsis; additionally, promoter
architecture, functional essentiality of genes, and circadian rhythm appeared
to have only a weak influence on the correlation strength. The differences in
the characteristics of noise-plasticity correlations may result from
three-dimensional chromosomal structures and/or circadian rhythm.
Preemptive Investment under Uncertainty
Date: 2016-05-31 00:00:00
Tasks: State Space Models

This paper provides a general characterization of subgame perfect equilibria
for strategic timing problems, where two firms have the (real) option to make
an irreversible investment. Profit streams are uncertain and depend on the
market structure. The analysis is based directly on the inherent economic
structure of the model. In particular, the determination of equilibria with
preemptive investment is reduced to solving a single class of constrained
optimal stopping problems. The general results are applied to typical
state-space models, completing commonly insufficient equilibrium arguments,
showing when uncertainty leads to qualitatively different behavior, and
establishing additional equilibria that are Pareto improvements.
A stochastic model for gene transcription on Drosophila melanogaster embryos
Date: 2015-11-12 00:00:00
Tasks: Position

We examine immunostaining experimental data for the formation of the strip 2
of $even-skipped$ ($eve$) transcripts on $D.$ $melanogaster$ embryos. An
estimate of the factor converting immunofluorescence intensity units into
molecular numbers is given. The analysis of the $eve$ mRNA's dynamics at the
region of the stripe 2 suggests that the promoter site of the gene has two
distinct regimes: an earlier phase when it is predominantly activated until a
critical time when it becomes mainly repressed. That suggests proposing a
stochastic binary model for gene transcription on $D.$ $melanogaster$ embryos.
Our model has two random variables: the transcripts number and the state of the
source of mRNAs given as active or repressed. We are able to reproduce
available experimental data for the average number of transcripts. An analysis
of the random fluctuations on the number of $eve$ mRNA's and their consequences
on the spatial precision of the stripe 2 is presented. We show that the
position of the anterior/posterior borders fluctuate around their average
position by $\sim 1 \%$ of the embryo length which is similar to what is found
experimentally. The fitting of data by such a simple model suggests that it can
be useful to understand the functions of randomness during developmental
processes.
RasBhari: optimizing spaced seeds for database searching, read mapping and alignment-free sequence comparison
Date: 2016-07-20 00:00:00
Tasks: Sensitivity

Many algorithms for sequence analysis rely on word matching or word
statistics. Often, these approaches can be improved if binary patterns
representing match and don't-care positions are used as a filter, such that
only those positions of words are considered that correspond to the match
positions of the patterns. The performance of these approaches, however,
depends on the underlying patterns. Herein, we show that the overlap complexity
of a pattern set that was introduced by Ilie and Ilie is closely related to the
variance of the number of matches between two evolutionarily related sequences
with respect to this pattern set. We propose a modified hill-climbing algorithm
to optimize pattern sets for database searching, read mapping and
alignment-free sequence comparison of nucleic-acid sequences; our
implementation of this algorithm is called rasbhari. Depending on the
application at hand, rasbhari can either minimize the overlap complexity of
pattern sets, maximize their sensitivity in database searching or minimize the
variance of the number of pattern-based matches in alignment-free sequence
comparison. We show that, for database searching, rasbhari generates pattern
sets with slightly higher sensitivity than existing approaches. In our Spaced
Words approach to alignment-free sequence comparison, pattern sets calculated
with rasbhari led to more accurate estimates of phylogenetic distances than the
randomly generated pattern sets that we previously used. Finally, we used
rasbhari to generate patterns for short read classification with CLARK-S. Here
too, the sensitivity of the results could be improved, compared to the default
patterns of the program. We integrated rasbhari into Spaced Words; the source
code of rasbhari is freely available at http://rasbhari.gobics.de/
A Stochastic Model of Order Book Dynamics using Bouncing Geometric Brownian Motions
Date: 2016-03-25 00:00:00

We consider a limit order book, where buyers and sellers register to trade a
security at specific prices. The largest price buyers on the book are willing
to offer is called the market bid price, and the smallest price sellers on the
book are willing to accept is called the market ask price. Market ask price is
always greater than market bid price, and these prices move upwards and
downwards due to new arrivals, market trades, and cancellations. We model these
two price processes as "bouncing geometric Brownian motions (GBMs)", which are
defined as exponentials of two mutually reflected Brownian motions. We then
modify these bouncing GBMs to construct a discrete time stochastic process of
trading times and trading prices, which is parameterized by a positive
parameter $\delta$. Under this model, it is shown that the inter-trading times
are inverse Gaussian distributed, and the logarithmic returns between
consecutive trading times follow a normal inverse Gaussian distribution. Our
main results show that the logarithmic trading price process is a renewal
reward process, and under a suitable scaling, this process converges to a
standard Brownian motion as $\delta\to 0$. We also prove that the modified ask
and bid processes approach the original bouncing GBMs as $\delta\to0$. Finally,
we derive a simple and effective prediction formula for trading prices, and
illustrate the effectiveness of the prediction formula with an example using
real stock price data.
Latency and liquidity provision in a limit order book
Date: 2016-06-24 00:00:00

We use a recent, high-quality data set from Nasdaq to perform an empirical
analysis of order flow in a limit order book (LOB) before and after the arrival
of a market order. For each of the stocks that we study, we identify a sequence
of distinct phases across which the net flow of orders differs considerably. We
note some of our results are consist with the widely reported phenomenon of
stimulated refill, but that others are not. We therefore propose alternative
mechanical and strategic motivations for the behaviour that we observe. Based
on our findings, we argue that strategic liquidity providers consider both
adverse selection and expected waiting costs when deciding how to act.
Spatial frequency processing in the central and peripheral visual field during scene viewing
Date: 2016-10-20 00:00:00

Visuospatial attention and gaze control depend on the interaction of foveal
and peripheral processing. The foveal and peripheral regions of the visual
field are differentially sensitive to parts of the spatial-frequency spectrum.
In two experiments, we investigated how the selective attenuation of spatial
frequencies in the central or the peripheral visual field affects eye-movement
behavior during real-world scene viewing. Gaze-contingent low-pass or high-pass
filters with varying filter levels (i.e., cutoff frequencies; Experiment 1) or
filter sizes (Experiment 2) were applied. Compared to unfiltered control
conditions, mean fixation durations increased most with central high-pass and
peripheral low-pass filtering. Increasing filter size prolonged fixation
durations with peripheral filtering, but not with central filtering. Increasing
filter level prolonged fixation durations with low-pass filtering, but not with
high-pass filtering. These effects indicate that fixation durations are not
always longer under conditions of increased processing difficulty. Saccade
amplitudes largely adapted to processing difficulty: amplitudes increased with
central filtering and decreased with peripheral filtering; the effects
strengthened with increasing filter size and filter level. In addition, we
observed a trade-off between saccade timing and saccadic selection, since
saccade amplitudes were modulated when fixation durations were unaffected by
the experimental manipulations. We conclude that interactions of perception and
gaze control are highly sensitive to experimental manipulations of input images
as long as the residual information can still be accessed for gaze control.
Equilibrium pricing under relative performance concerns
Date: 2017-02-10 00:00:00

We investigate the effects of the social interactions of a finite set of
agents on an equilibrium pricing mechanism. A derivative written on
non-tradable underlyings is introduced to the market and priced in an
equilibrium framework by agents who assess risk using convex dynamic risk
measures expressed by Backward Stochastic Differential Equations (BSDE). Each
agent is not only exposed to financial and non-financial risk factors, but she
also faces performance concerns with respect to the other agents.
  Within our proposed model we prove the existence and uniqueness of an
equilibrium whose analysis involves systems of fully coupled multi-dimensional
quadratic BSDEs. We extend the theory of the representative agent by showing
that a non-standard aggregation of risk measures is possible via
weighted-dilated infimal convolution. We analyze the impact of the problem's
parameters on the pricing mechanism, in particular how the agents' performance
concern rates affect prices and risk perceptions. In extreme situations, we
find that the concern rates destroy the equilibrium while the risk measures
themselves remain stable.
Requirements for efficient cell-type proportioning: regulatory timescales, stochasticity and lateral inhibition
Date: 2015-11-13 00:00:00
Tasks: Diversity

The proper functioning of multicellular organisms requires the robust
establishment of precise proportions between distinct cell-types. This
developmental differentiation process typically involves intracellular
regulatory and stochastic mechanisms to generate cell-fate diversity as well as
intercellular mechanisms to coordinate cell-fate decisions at tissue level. We
thus surmise that key insights about the developmental regulation of cell-type
proportion can be captured by the modeling study of clustering dynamics in
population of inhibitory-coupled noisy bistable systems. This general class of
dynamical system is shown to exhibit a very stable two-cluster state, but also
frustrated relaxation, collective oscillations or steady-state hopping which
prevents from timely and reliably reaching a robust and well-proportioned
clustered state. To circumvent these obstacles or to avoid fine-tuning, we
highlight a general strategy based on dual-time positive feedback loops, such
as mediated through transcriptional versus epigenetic mechanisms, which
improves proportion regulation by coordinating early and flexible lineage
priming with late and firm commitment. This result sheds new light on the
respective and cooperative roles of multiple regulatory feedback, stochasticity
and lateral inhibition in developmental dynamics.
Financial Models with Defaultable Num\'eraires
Date: 2017-10-18 00:00:00

Financial models are studied where each asset may potentially lose value
relative to any other. Conditioning on non-devaluation, each asset can serve as
proper num\'eraire and classical valuation rules can be formulated. It is shown
when and how these local valuation rules can be aggregated to obtain global
arbitrage-free valuation formulas.
The sensorimotor loop as a dynamical system: How regular motion primitives may emerge from self-organized limit cycles
Date: 2018-03-14 00:00:00

We investigate the sensorimotor loop of simple robots simulated within the
LPZRobots environment from the point of view of dynamical systems theory. For a
robot with a cylindrical shaped body and an actuator controlled by a single
proprioceptual neuron we find various types of periodic motions in terms of
stable limit cycles. These are self-organized in the sense, that the dynamics
of the actuator kicks in only, for a certain range of parameters, when the
barrel is already rolling, stopping otherwise. The stability of the resulting
rolling motions terminates generally, as a function of the control parameters,
at points where fold bifurcations of limit cycles occur. We find that several
branches of motion types exist for the same parameters, in terms of the
relative frequencies of the barrel and of the actuator, having each their
respective basins of attractions in terms of initial conditions. For low
drivings stable limit cycles describing periodic and drifting back-and-forth
motions are found additionally. These modes allow to generate symmetry breaking
explorative behavior purely by the timing of an otherwise neutral signal with
respect to the cyclic back-and-forth motion of the robot.
Universality in survivor distributions: Characterising the winners of competitive dynamics
Date: 2015-11-13 00:00:00

We investigate the survivor distributions of a spatially extended model of
competitive dynamics in different geometries. The model consists of a
deterministic dynamical system of individual agents at specified nodes, which
might or might not survive the predatory dynamics: all stochasticity is brought
in by the initial state. Every such initial state leads to a unique and
extended pattern of survivors and non-survivors, which is known as an attractor
of the dynamics. We show that the number of such attractors grows exponentially
with system size, so that their exact characterisation is limited to only very
small systems. Given this, we construct an analytical approach based on
inhomogeneous mean-field theory to calculate survival probabilities for
arbitrary networks. This powerful (albeit approximate) approach shows how
universality arises in survivor distributions via a key concept -- the {\it
dynamical fugacity}. Remarkably, in the large-mass limit, the survival
probability of a node becomes independent of network geometry, and assumes a
simple form which depends only on its mass and degree.
Signal Fluctuation Sensitivity: an improved metric for optimizing detection of resting-state fMRI networks
Date: 2015-11-13 00:00:00
Tasks: Sensitivity, Time Series, Time Series Analysis

Task-free connectivity analyses have emerged as a powerful tool in functional
neuroimaging. Because the cross-correlations that underlie connectivity
measures are sensitive to distortion of time-series, here we used a novel
dynamic phantom to provide a ground truth for dynamic fidelity between blood
oxygen level dependent (BOLD)-like inputs and fMRI outputs. We found that the
de facto quality-metric for task-free fMRI, temporal signal to noise ratio
(tSNR), correlated inversely with dynamic fidelity; thus, studies optimized for
tSNR actually produced time-series that showed the greatest distortion of
signal dynamics. Instead, the phantom showed that dynamic fidelity is
reasonably approximated by a measure that, unlike tSNR, dissociates signal
dynamics from scanner artifact. We then tested this measure, signal fluctuation
sensitivity (SFS), against human resting-state data. As predicted by the
phantom, SFS--and not tSNR--is associated with enhanced sensitivity to both
local and long-range connectivity within the brain's default mode network.
The Multilayer Nature of Ecological Networks
Date: 2016-11-25 00:00:00

Although networks provide a powerful approach to study a large variety of
ecological systems, their formulation does not typically account for multiple
interaction types, interactions that vary in space and time, and interconnected
systems such as networks of networks. The emergent field of `multilayer
networks' provides a natural framework for extending analyses of ecological
systems to include such multiple layers of complexity, as it specifically
allows one to differentiate and model `intralayer' and `interlayer'
connectivity. The framework provides a set of concepts and tools that can be
adapted and applied to ecology, facilitating research on high-dimensional,
heterogeneous systems in nature. Here, we formally define ecological multilayer
networks based on a review of previous and related approaches, illustrate their
application and potential with analyses of existing data, and discuss
limitations, challenges, and future applications. The integration of multilayer
network theory into ecology offers largely untapped potential to further
address ecological complexity, to ultimately provide new theoretical and
empirical insights into the architecture and dynamics of ecological systems.
Cellular replication limits in the Luria-Delbr\"uck mutation model
Date: 2015-11-14 00:00:00

Originally developed to elucidate the mechanisms of natural selection in
bacteria, the Luria-Delbr\"uck model assumed that cells are intrinsically
capable of dividing an unlimited number of times. This assumption however, is
not true for human somatic cells which undergo replicative senescence.
Replicative senescence is thought to act as a mechanism to protect against
cancer and the escape from it is a rate-limiting step in cancer progression.
Here we introduce a Luria-Delbr\"uck model that explicitly takes into account
cellular replication limits in the wild type cell population and models the
emergence of mutants that escape replicative senescence. We present results on
the mean, variance, distribution, and asymptotic behavior of the mutant
population in terms of three classical formulations of the problem. More
broadly the paper introduces the concept of incorporating replicative limits as
part of the Luria-Delbr\"uck mutational framework. Guidelines to extend the
theory to include other types of mutations and possible applications to the
modeling of telomere crisis and fluctuation analysis are also discussed.
Using Text Mining To Analyze Real Estate Classifieds
Authors: Abdallah Sherief
Date: 2015-11-15 00:00:00
Tasks: regression

Many brokers have adapted their operation to exploit the potential of the
web. Despite the importance of the real estate classifieds, there has been
little work in analyzing such data. In this paper we propose a two-stage
regression model that exploits the textual data in real estate classifieds. We
show how our model can be used to predict the price of a real estate
classified. We also show how our model can be used to highlight keywords that
affect the price positively or negatively. To assess our contributions, we
analyze four real world data sets, which we gathered from three different
property websites. The analysis shows that our model (which exploits textual
features) achieves significantly lower root mean squared error across the
different data sets and against variety of regression models.
Applying Semantic Web Technologies for Improving the Visibility of Tourism Data
Authors: Soualah-Alila Fayrouz  L3I, Faucher Cyril  L3I, Bertrand Frédéric  L3I, Coustaty Mickaël  L3I, Doucet Antoine  L3I
Date: 2015-11-15 00:00:00
Tasks: Management

Tourism industry is an extremely information-intensive, complex and dynamic
activity. It can benefit from semantic Web technologies, due to the significant
heterogeneity of information sources and the high volume of on-line data. The
management of semantically diverse annotated tourism data is facilitated by
ontologies that provide methods and standards, which allow flexibility and more
intelligent access to on-line data. This paper provides a description of some
of the early results of the Tourinflux project which aims to apply semantic Web
technologies to support tourist actors in effectively finding and publishing
information on the Web.
Optimal Investment with Transaction Costs under Cumulative Prospect Theory in Discrete Time
Date: 2016-11-13 00:00:00

We study optimal investment problems under the framework of cumulative
prospect theory (CPT). A CPT investor makes investment decisions in a
single-period financial market with transaction costs. The objective is to seek
the optimal investment strategy that maximizes the prospect value of the
investor's final wealth. We obtain the optimal investment strategy explicitly
in two examples. An economic analysis is conducted to investigate the impact of
the transaction costs and risk aversion on the optimal investment strategy.
Dynamical models of task organization in social insect colonies
Date: 2015-11-15 00:00:00

The organizations of insect societies, such as division of labor, task
allocation, collective regulation, mass action responses, have been considered
as main reasons for the ecological success. In this article, we propose and
study a general modeling framework that includes the following three features:
(a) the average internal response threshold for each task (the internal
factor); (b) social network communications that could lead to task switching
(the environmental factor); and (c) dynamical changes of task demands (the
external factor). Since workers in many social insect species exhibit \emph{age
polyethism}, we also extend our model to incorporate \emph{age polyethism} in
which worker task preferences change with age. We apply our general modeling
framework to the cases of two task groups: the inside colony task versus the
outside colony task. Our analytical study of the models provides important
insights and predictions on the effects of colony size, social communication,
and age related task preferences on task allocation and division of labor in
the adaptive dynamical environment. Our study implies that the smaller size
colony invests its resource for the colony growth and allocates more workers in
the risky tasks such as foraging while the larger colony shifts more workers to
perform the safer tasks inside the colony. Social interactions among different
task groups play an important role in shaping task allocation depending on the
relative cost and demands of the tasks.