pwc-archive/papers-with-abstracts huggingface dataset:
The accuracy of telling time via oscillatory signals
Date: 2016-01-14 00:00:00

Circadian clocks are the central timekeepers of life, allowing cells to
anticipate changes between day and night. Experiments in recent years have
revealed that circadian clocks can be highly stable, raising the question how
reliably they can be read out. Here, we combine mathematical modeling with
information theory to address the question how accurately a cell can infer the
time from an ensemble of protein oscillations, which are driven by a circadian
clock. We show that the precision increases with the number of oscillations and
their amplitude relative to their noise. Our analysis also reveals that their
exists an optimal phase relation that minimizes the error in the estimate of
time, which depends on the relative noise levels of the protein oscillations.
Lastly, our work shows that cross-correlations in the noise of the protein
oscillations can enhance the mutual information, which suggests that
cross-regulatory interactions between the proteins that read out the clock can
be beneficial for temporal information transmission.
Convex duality for stochastic differential utility
Date: 2016-01-14 00:00:00

This paper introduces a dual problem to study a continuous-time consumption
and investment problem with incomplete markets and stochastic differential
utility. For Epstein-Zin utility, duality between the primal and dual problems
is established. Consequently the optimal strategy of the consumption and
investment problem is identified without assuming several technical conditions
on market model, utility specification, and agent's admissible strategy.
Meanwhile the minimizer of the dual problem is identified as the utility
gradient of the primal value and is economically interpreted as the "least
favorable" completion of the market.
Efficient Maximum-Likelihood Inference For The Isolation-With-Initial-Migration Model With Potentially Asymmetric Gene Flow
Date: 2016-01-14 00:00:00

The isolation-with-migration (IM) model is a common tool to make inferences
about the presence of gene flow during speciation, using polymorphism data.
However, Becquet and Przeworski (2009) report that the parameter estimates
obtained by fitting the IM model are very sensitive to the model's assumptions,
including the assumption of constant gene flow until the present. This paper is
concerned with the isolation-with-initial-migration (IIM) model of
Wilkinson-Herbots (2012), which drops precisely this assumption. In the IIM
model, one ancestral population divides into two descendant subpopulations,
between which there is an initial period of gene flow and a subsequent period
of isolation. We derive a fast method of fitting an extended version of the IIM
model, which allows for asymmetric gene flow and unequal subpopulation sizes.
This is a maximum-likelihood method, applicable to observations on the number
of different sites between pairs of DNA sequences from a large number of
independent loci. In addition to obtaining parameter estimates, our method can
also be used to distinguish between alternative models representing different
evolutionary cenarios, by means of likelihood ratio tests. We illustrate the
procedure on pairs of Drosophila sequences from approximately 30,000 loci. The
computing time needed to fit the most complex version of the model to this data
set is only a couple of minutes. The code to fit the IIM model can be found in
the supplementary files of this paper.
Integrating Theory and Experiment to Explain the Breakdown of Population Synchrony in a Complex Microbial Community
Date: 2016-01-15 00:00:00

We consider the extension of the `Moran effect', where correlated noise
generates synchrony between isolated single species populations, to the study
of synchrony between populations embedded in multi-species communities. In
laboratory experiments on complex microbial communities, comprising both
predators (protozoa) and prey (bacteria), we observe synchrony in abundances
between isolated replicates. A breakdown in synchrony occurs for both predator
and prey as the reactor dilution rate increases, which corresponds to both an
increased rate of input of external resources and an increased effective
mortality though washout. The breakdown is more rapid, however, for the lower
trophic level. We can explain this phenomenon using a mathematical framework
for determining synchrony between populations in multi-species communities at
equilibrium. We assume that there are multiple sources of environmental noise
with different degrees of correlation that affect the individual species
population dynamics differently. The deterministic dynamics can then influence
the degree of synchrony between species in different communities. In the case
of a stable equilibrium community synchrony is controlled by the eigenvalue
with smallest negative real part. Intuitively fluctuations are minimally damped
in this direction. We show that the experimental observations are consistent
with this framework but only for multiplicative noise.
Do Mature Economies Grow Exponentially?
Date: 2016-01-15 00:00:00
Tasks: Articles, Time Series, Time Series Analysis

Most models that try to explain economic growth indicate exponential growth
paths. In recent years, however, a lively discussion has emerged considering
the validity of this notion. In the empirical literature dealing with drivers
of economic growth, the majority of articles is based upon an implicit
assumption of exponential growth. Few scholarly articles have addressed this
issue so far. In order to shed light on this issue, we estimate autoregressive
integrated moving average time series models based on Gross Domestic Product
Per Capita data for 18 mature economies from 1960 to 2013. We compare the
adequacy of linear and exponential growth models and conduct several robustness
checks. Our fndings cast doubts on the widespread belief of exponential growth
and suggest a deeper discussion on alternative economic grow theories.
A Statistical Model of Inequality
Date: 2016-01-15 00:00:00
Tasks: model

This paper develops a nonparametric statistical model of wealth distribution
that imposes little structure on the fluctuations of household wealth. In this
setting, we use new techniques to obtain a closed-form household-by-household
characterization of the stable distribution of wealth and show that this
distribution is shaped entirely by two factors - the reversion rates (a measure
of cross-sectional mean reversion) and idiosyncratic volatilities of wealth
across different ranked households. By estimating these factors, our model can
exactly match the U.S. wealth distribution. This provides information about the
current trajectory of inequality as well as estimates of the distributional
effects of progressive capital taxes. We find evidence that the U.S. wealth
distribution might be on a temporarily unstable trajectory, thus suggesting
that further increases in top wealth shares are likely in the near future. For
capital taxes, we find that a small tax levied on just 1% of households
substantially reshapes the distribution of wealth and reduces inequality.
Inherent rhythm of smooth muscle cells in rat mesenteric arterioles: an eigensystem formulation
Date: 2016-03-19 00:00:00
Tasks: Rhythm, valid

On the basis of experimental data and mathematical equations in the
literature, we remodel the ionic dynamics of smooth muscle cells (SMCs) as an
eigensystem formulation, which is valid for investigating finite variations of
variables from the equilibrium like in common experimental operations. This
algorithm provides an alternate viewpoint from frequency-domain analysis and
enables one to probe functionalities of SMC's rhythm by means of a
resonance-related mechanism. Numerical results show three types of calcium
oscillations of SMCs in mesenteric arterioles: spontaneous calcium oscillation,
agonist-dependent calcium oscillation, and agonist-dependent calcium spike. For
simple single and double SMCs, we demonstrate properties of synchronization
among complex signals related to calcium oscillations, and show different
correlation relations between calcium and voltage signals for various
synchronization and resonance conditions. For practical cell clusters, our
analyses indicate that the rhythm of SMCs could (1) benefit enhancements of
signal communications among remote cells, (2) respond to a significant calcium
peaking against transient stimulations for triggering globally-oscillating
modes, and (3) characterize the globally-oscillating modes via frog-leap
(non-molecular-diffusion) calcium waves across inhomogeneous SMCs.
Chiral autocatalysis: reaction noise, micro-reversibility and chiral inhibition in mirror symmetry breaking
Date: 2016-01-16 00:00:00

Applying the constraints dictated by the principle of detailed balance, we
analyze a recent proposal for spontaneous mirror symmetry breaking (SMSB) based
on enantioselective autocatalysis coupled to a linear decay of the enantiomers
and in the presence of reaction noise. We find the racemic state is the final
stable outcome for both deterministic as well as for stochastic dynamics, and
for both well-mixed and small spatially-coupled systems. The racemic outcome
results even when the autocatalytic cycles are driven irreversibly by external
reagents, in manifestly non-equilibrium conditions. Our findings suggest that
first-order autocatalysis coupled to reactions involving \textit{non-linear}
heterochiral dynamics is a necessary pre-condition for any mechanism purporting
to lead to molecular homochirality.
Folding PDZ2 domain using the Molecular Transfer Model
Date: 2016-01-16 00:00:00
Tasks: model

A major challenge in molecular simulations is to describe
denaturant-dependent folding of proteins order to make direct comparisons with
{\it in vitro} experiments. We use the molecular transfer model, which is
currently the only method that accomplishes this goal albeit
phenomenologically, to quantitatively describe urea-dependent folding of PDZ
domain, which plays a significant role in molecular recognition and signaling.
Experiments show that urea-dependent unfolding rates of the PDZ2 domain exhibit
a downward curvature at high urea concentrations, which has been interpreted by
invoking the presence of a sparsely populated high energy intermediate.
Simulations using the MTM and a coarse-grained model of PDZ2 are used to show
that the intermediate, which has some native-like character, is present in
equilibrium both in the presence and absence of urea. The free energy profiles
show that there are two barriers separating the folded and unfolded states.
Structures of the transition state ensembles, ($TSE1$ separating the unfolded
and $I_{EQ}$ and $TSE2$ separating $I_{EQ}$ and the native state), determined
using the $P_{fold}$ method, show that $TSE1$ is expanded; $TSE2$ and
native-like. Folding trajectories reveal that PDZ2 folds by parallel routes. In
one pathway folding occurs exclusively through $I_1$, which resembles $I_{EQ}$.
In a fraction of trajectories, constituting the second pathway, folding occurs
through a combination of $I_{1}$ and a kinetic intermediate. The radius of
gyration ($R_g^{U}$) of the unfolded state is more compact (by $\sim$ 9\%)
under native conditions. Decrease in $R_g^{U}$ occurs on the time scale on the
order of utmost $\sim$ 20 $\mu s$. The modest decrease in $R_g^{U}$ and the
rapid collapse suggest that high spatial and temporal resolution are needed to
detect compaction in finite-sized proteins.
A comparison among some Hurst exponent approaches to predict nascent bubbles in $500$ company stocks
Date: 2016-01-16 00:00:00
Tasks: Time Series, Time Series Analysis

In this paper, three approaches to calculate the self-similarity exponent of
a time series are compared in order to determine which one performs best to
identify the transition from random efficient market behavior (EM) to herding
behavior (HB) and hence, to find out the beginning of a market bubble. In
particular, classical Detrended Fluctuation Analysis (DFA), Generalized Hurst
Exponent (GHE) and GM2 (one of Geometric Method-based algorithms) were applied
for self-similarity exponent calculation purposes. Traditionally, researchers
have been focused on identifying the beginning of a crash. Instead of this, we
are pretty interested in identifying the beginning of the transition process
from EM to a market bubble onset, what we consider could be more interesting.
The relevance of self-similarity index in such a context lies on the fact that
it becomes a suitable indicator which allows to identify the raising of HB in
financial markets. Overall, we could state that the greater the self-similarity
exponent in financial series, the more likely the transition process to HB
could start. This fact is illustrated through actual S\&P500 stocks.
Modelling of immune cells as vectors of HIV spread inside a patient human body
Date: 2016-01-16 00:00:00

The search to understand how the HIV virus spreads inside the human body and
how the immune response works to control it has motivated studies related to
Mathematical Immunology. Actually, researches include the idea of mathematical
models representing the dynamics of healthy and infected cell populations and
focusing on mechanisms used by HIV to invade target-host cells, viral
dissemination (which leads to depletion of the T-cell pool and collapse of the
immune system), and impairment of immune response. In this work, we show the
importance of specific cells of immune response, as infection vectors involved
in the dynamics of viral proliferation within an untreated patient, by using an
ordinary differential equation model in which we considered that the virus
infected target-cells such as macrophages, dendritic cells, and lymphocytes
TCD4 and TCD8 populations. In conclusion, we demonstrate the importance of each
cell-host and the threshold of viral establishment and posterior spread based
on the presence of infected macrophages and dendritic cells in
antigen-presenting processing, which leads to new infections (by wild or mutant
virions) after immune response activation episodes. We presented an $R_0$
expression that provides the major parameters of HIV infection. Additionally,
we suggest some possibilities of new targets for functional vaccines.
Speculative Futures Trading under Mean Reversion
Date: 2016-01-16 00:00:00

This paper studies the problem of trading futures with transaction costs when
the underlying spot price is mean-reverting. Specifically, we model the spot
dynamics by the Ornstein-Uhlenbeck (OU), Cox-Ingersoll-Ross (CIR), or
exponential Ornstein-Uhlenbeck (XOU) model. The futures term structure is
derived and its connection to futures price dynamics is examined. For each
futures contract, we describe the evolution of the roll yield, and compute
explicitly the expected roll yield. For the futures trading problem, we
incorporate the investor's timing option to enter or exit the market, as well
as a chooser option to long or short a futures upon entry. This leads us to
formulate and solve the corresponding optimal double stopping problems to
determine the optimal trading strategies. Numerical results are presented to
illustrate the optimal entry and exit boundaries under different models. We
find that the option to choose between a long or short position induces the
investor to delay market entry, as compared to the case where the investor
pre-commits to go either long or short.
Topological mapping of space in bat hippocampus
Date: 2016-01-17 00:00:00
Tasks: Hippocampus

Mammalian hippocampus plays a key role in spatial learning and memory, but
the exact nature of the hippocampal representation of space is still being
explored. Recently, there has been a fair amount of success in modeling
hippocampal spatial maps in rats, assuming a topological perspective on spatial
information processing. In this paper, we use the topological model to study
$3D$ learning in bats, which produces several insights into neurophysiological
mechanisms of the hippocampal spatial mapping. First, we demonstrate functional
importance of the cell assemblies for producing accurate maps of the $3D$
environments. Second, the model suggests that the readout neurons in these cell
assemblies should function as integrators of synaptic inputs, rather than
detectors of place cells' coactivity and allows estimating the integration time
window. Lastly, the model suggests that, in contrast with relatively slow
moving rats, suppressing $\theta$-precession in bats improves the place cells
capacity to encode spatial maps, which is consistent with the experimental
observations.
Partitioning RNAs into pseudonotted and pseudoknot-free regions modeled as Dual Graphs
Date: 2016-01-17 00:00:00

Dual graphs have been applied to model RNA secondary structures. The purpose
of the paper is two-fold: we present new graph-theoretic properties of dual
graphs to validate the further analysis and classification of RNAs using these
topological representations; we also present a linear-time algorithm to
partition dual graphs into topological components called {\it blocks} and
determine if each block contains a {\it pseudoknot} or not. We show that a
block contains a pseudoknot if and only if the block has a vertex of degree $3$
or more; this characterization allows us to efficiently isolate smaller RNA
fragments and classify them as pseudoknotted or pseudoknot-free regions, while
keeping these sub-structures intact. Even though non-topological techniques to
detect and classify pseudoknots have been efficiently applied, structural
properties of dual graphs provide a unique perspective for the further analysis
of RNAs. Applications to RNA design can be envisioned since modular building
blocks with intact pseudoknots can be combined to form new
constructs.\end{abstract}
Negative oil price bubble is likely to burst in March - May 2016. A forecast on the basis of the law of log-periodical dynamics
Date: 2016-01-17 00:00:00

Data analysis with log-periodical parametrization of the Brent oil price
dynamics has allowed to estimate (very approximately) the date when the dashing
collapse of the Brent oil price will achieve the absolute minimum level
(corresponding to the so-called singularity point), after which there will
occur a rather rapid rebound, whereas the accelerating fall of the oil prices
which started in mid-2014 will come to an end. This is likely to happen in the
period between March, 24th and May, 15th, 2016. An analogous estimate (though a
more exact one) was made for the date of the burst of the nearest negative
"sub-bubble", which is likely to occur between 19.01 and 02.02.2016
(importantly, this estimate will allow to verify the robustness of the
developed forecast in the very nearest days). However, this will not mean a
start of a new uninterrupted global growth - the fall will soon continue,
breaking new "anti-records". The fall will only finally stop after passing the
abovementioned point of the main negative bubble singularity somewhere between
March 24th and May 15th, 2016 (if, of course, the oil market remains at the
disposal of speculators, and no massive interventions of macro actors are
made). Importantly, our calculations have also shown that after mid-2014 we are
dealing not with an antibubble (when price collapse goes on in a damped and
almost unstoppable regime) in the world oil market, but with a negative bubble,
when prices collapse in an accelerated mode, and there can be particularly
powerful collapses with particularly strong destabilizing effect near the
singularity point. On the other hand, negative bubbles can be better
manipulated by the actions of the macro actors.
On bivariate lifetime modelling in life insurance applications
Date: 2016-01-17 00:00:00
Tasks: parameter estimation

Insurance and annuity products covering several lives require the modelling
of the joint distribution of future lifetimes. In the interest of simplifying
calculations, it is common in practice to assume that the future lifetimes
among a group of people are independent. However, extensive research over the
past decades suggests otherwise. In this paper, a copula approach is used to
model the dependence between lifetimes within a married couple \eH{using data
from a large Canadian insurance company}. As a novelty, the age difference and
the \eH{gender} of the elder partner are introduced as an argument of the
dependence parameter. \green{Maximum likelihood techniques are} thus
implemented for the parameter estimation. Not only do the results make clear
that the correlation decreases with age difference, but also the dependence
between the lifetimes is higher when husband is older than wife. A
goodness-of-fit procedure is applied in order to assess the validity of the
model. Finally, considering several products available on the life insurance
market, the paper concludes with practical illustrations.
Dipole density instead of potentials in electrocardiology
Date: 2016-01-18 00:00:00

We discuss the forward and inverse problems between the potential V(x)
measured in a heart chamber and its sources represented by a dipole density
d(y) located on the heart wall. We show that the mapping from d(y) to V(x) is a
compact integral operator. Its inverse is unbounded which makes the inverse
problem ill-posed in the mathematical sense. We investigate methods to solve
the inverse problem approximately in view of the mapping of complicated cardiac
arrhythmias. We point out an analogy between phase mapping and 2-dimensional
hydrodynamics.
Reducing local minima in fitness landscapes of parameter estimation by using piecewise evaluation and state estimation
Date: 2016-01-18 00:00:00
Tasks: Articles, parameter estimation, State Estimation

Ordinary differential equations (ODE) are widely used for modeling in Systems
Biology. As most commonly only some of the kinetic parameters are measurable or
precisely known, parameter estimation techniques are applied to parametrize the
model to experimental data. A main challenge for the parameter estimation is
the complexity of the parameter space, especially its high dimensionality and
local minima.
  Parameter estimation techniques consist of an objective function, measuring
how well a certain parameter set describes the experimental data, and an
optimization algorithm that optimizes this objective function. A lot of effort
has been spent on developing highly sophisticated optimization algorithms to
cope with the complexity in the parameter space, but surprisingly few articles
address the influence of the objective function on the computational complexity
in finding global optima. We extend a recently developed multiple shooting for
stochastic systems (MSS) objective function for parameter estimation of
stochastic models and apply it to parameter estimation of ODE models. This MSS
objective function treats the intervals between measurement points separately.
This separate treatment allows the ODE trajectory to stay closer to the data
and we show that it reduces the complexity of the parameter space.
  We use examples from Systems Biology, namely a Lotka-Volterra model, a
FitzHugh-Nagumo oscillator and a Calcium oscillation model, to demonstrate the
power of the MSS approach for reducing the complexity and the number of local
minima in the parameter space. The approach is fully implemented in the COPASI
software package and, therefore, easily accessible for a wide community of
researchers.