pwc-archive/papers-with-abstracts huggingface dataset:
Comparing the rankings obtained from two biodiversity indices: the Fair Proportion Index and the Shapley Value
Date: 2017-07-27 00:00:00

The Shapley Value and the Fair Proportion Index of phylogenetic trees have
been frequently discussed as prioritization tools in conservation biology. Both
indices rank species according to their contribution to total phylogenetic
diversity, allowing for a simple conservation criterion. While both indices
have their specific advantages and drawbacks, it has recently been shown that
both values are closely related. However, as different authors use different
definitions of the Shapley Value, the specific degree of relatedness depends on
the specific version of the Shapley Value - it ranges from a high correlation
index to equality of the indices. In this note, we first give an overview of
the different indices. Then we turn our attention to the mere ranking order
provided by either of the indices. We compare the rankings obtained from
different versions of the Shapley Value for a phylogenetic tree of European
amphibians and illustrate their differences. We then undertake further analyses
on simulated data and show that even though the chance of two rankings being
exactly identical (when obtained from different versions of the Shapley Value)
decreases with an increasing number of taxa, the distance between the two
rankings converges to zero, i.e., the rankings are becoming more and more
alike. Moreover, we introduce our freely available software package
FairShapley, which was implemented in Perl and with which all calculations have
been performed.
Minimizing the Probability of Lifetime Drawdown under Constant Consumption
Date: 2016-05-19 00:00:00

We assume that an individual invests in a financial market with one riskless
and one risky asset, with the latter's price following geometric Brownian
motion as in the Black-Scholes model. Under a constant rate of consumption, we
find the optimal investment strategy for the individual who wishes to minimize
the probability that her wealth drops below some fixed proportion of her
maximum wealth to date, the so-called probability of {\it lifetime drawdown}.
If maximum wealth is less than a particular value, $m^*$, then the individual
optimally invests in such a way that maximum wealth never increases above its
current value. By contrast, if maximum wealth is greater than $m^*$ but less
than the safe level, then the individual optimally allows the maximum to
increase to the safe level.
Inverse Relationship Between Molecular Diversity And Resource Abundances
Date: 2015-07-31 00:00:00
Tasks: Diversity

Cell reproduction involves replication of diverse molecule species, in
contrast to simple replication system with fewer components. Here, we address
why such diversity is sustained despite the efficiency of simple replication
systems, using a cell model with catalytic reaction dynamics that grew by
uptake of environmental resources. Limited resources led to increased diversity
of components within the system, and the number of coexisting species increased
with a negative power of the resource abundances. The diversity was explained
from the optimum growth speed of the cell, determined by a tradeoff between the
utility of diverse resources and the concentration onto fewer components to
increase the reaction rate.
Does normal pupil diameter differences in population underlie the color selection of the #dress?
Date: 2015-11-25 00:00:00

The fundamental question that arises from the color composition of the #dress
is: 'What are the phenomena that underlie the individual differences in colors
reported given all other conditions like light and device for display being
identical?'. The main color camps are blue/black (b/b) and white/gold (w/g) and
a survey of 384 participants showed near equal distribution. We looked at pupil
size differences in the sample population of 53 from the two groups plus a
group who switched (w/g to b/b). Our results show that w/g and switch
population had significantly ( w/g <b/b, p-value = 0.0086) lower pupil size
than b/b camp. A standard infinity focus experiment was then conducted on 18
participants from each group to check if there is bimodality in the population
and we again found statistically significant difference (w/g < b/b , p-value =
0.0132). Six participants, half from the w/g camp, were administered dilation
drops that increased the pupil size by 3-4mm to check if increase in retinal
illuminance will trigger a change in color in the w/g group, but the
participants did not report a switch. The results suggest a population
difference in normal pupil-size in the three groups.
Impact of Multiple Curve Dynamics in Credit Valuation Adjustments under Collateralization
Date: 2015-09-13 00:00:00

We present a detailed analysis of interest rate derivatives valuation under
credit risk and collateral modeling. We show how the credit and collateral
extended valuation framework in Pallavicini et al (2011), and the related
collateralized valuation measure, can be helpful in defining the key market
rates underlying the multiple interest rate curves that characterize current
interest rate markets. A key point is that spot Libor rates are to be treated
as market primitives rather than being defined by no-arbitrage relationships.
We formulate a consistent realistic dynamics for the different rates emerging
from our analysis and compare the resulting model performances to simpler
models used in the industry. We include the often neglected margin period of
risk, showing how this feature may increase the impact of different rates
dynamics on valuation. We point out limitations of multiple curve models with
deterministic basis considering valuation of particularly sensitive products
such as basis swaps. We stress that a proper wrong way risk analysis for such
products requires a model with a stochastic basis and we show numerical results
confirming this fact.
Seeking for a fingerprint: analysis of point processes in actigraphy recording
Date: 2016-02-26 00:00:00
Tasks: Point Processes, Time Series, Time Series Analysis

Motor activity of humans displays complex temporal fluctuations which can be
characterized by scale-invariant statistics, thus documenting that structure
and fluctuations of such kinetics remain similar over a broad range of time
scales. Former studies on humans regularly deprived of sleep or suffering from
sleep disorders predicted change in the invariant scale parameters with respect
to those representative for healthy subjects. In this study we investigate the
signal patterns from actigraphy recordings by means of characteristic measures
of fractional point processes. We analyse spontaneous locomotor activity of
healthy individuals recorded during a week of regular sleep and a week of
chronic partial sleep deprivation. Behavioural symptoms of lack of sleep can be
evaluated by analysing statistics of duration times during active and resting
states, and alteration of behavioural organization can be assessed by analysis
of power laws detected in the event count distribution, distribution of waiting
times between consecutive movements and detrended fluctuation analysis of
recorded time series. We claim that among different measures characterizing
complexity of the actigraphy recordings and their variations implied by chronic
sleep distress, the exponents characterizing slopes of survival functions in
resting states are the most effective biomarkers distinguishing between healthy
and sleep-deprived groups.
pyBioSig: optimizing group discrimination using genetic algorithms for biosignature discovery
Date: 2015-07-30 00:00:00

In medical sciences, a biomarker is "a characteristic that is objectively
measured and evaluated as an indicator of normal biological processes,
pathogenic processes, or pharmacologic responses to a therapeutic
intervention". Molecular experiments are providing rapid and systematic
approaches to search for biomarkers, but because single-molecule biomarkers
have shown a disappointing lack of robustness for clinical diagnosis,
researchers have begun searching for distinctive sets of molecules, called
"biosignatures". However, the most popular statistics are not appropriate for
their identification, and the number of possible biosignatures to be tested is
frequently intractable. In the present work, we developed a "multivariate
filter" using genetic algorithms (GA) as a feature (gene) selector to optimize
a measure of intra-group cohesion and inter-group dispersion. This method was
implemented using Python and R (pyBioSig, available at
https://github.com/fredgca/pybiosig under LGPL) and can be manipulated via
graphical interface or Python scripts. Using it, we were able to identify
putative biosignatures composed by just a few genes and capable of recovering
multiple groups simultaneously in a hierarchical clustering, even ones that
were not recovered using the whole transcriptome, within a feasible length of
time using a personal computer. Our results allowed us to conclude that using
GA to optimize our new intra-group cohesion and inter-group dispersion measure
is a clear, effective, and computationally feasible strategy for the
identification of putative "omical" biosignatures that could support
discrimination among multiple groups simultaneously.
A Study and Preliminary Model of Cross-Domain Influences on Creativity
Date: 2019-07-15 00:00:00

This paper takes a two-pronged approach to investigate the phenomenon of
cross-domain influence on creativity. We present a study in which creative
individuals were asked to list influences on their creative work. More than
half the listed influences were unrelated to their creative domain, thus
demonstrating empirically that cross-domain influence is widespread. We then
present a preliminary model of exaptation, a form of cross-domain influence on
creativity in which a different context suggests a new use for an existing
item, using an example from the study.
What makes a neural code convex?
Date: 2016-12-21 00:00:00
Tasks: Hippocampus

Neural codes allow the brain to represent, process, and store information
about the world. Combinatorial codes, comprised of binary patterns of neural
activity, encode information via the collective behavior of populations of
neurons. A code is called convex if its codewords correspond to regions defined
by an arrangement of convex open sets in Euclidean space. Convex codes have
been observed experimentally in many brain areas, including sensory cortices
and the hippocampus, where neurons exhibit convex receptive fields. What makes
a neural code convex? That is, how can we tell from the intrinsic structure of
a code if there exists a corresponding arrangement of convex open sets? In this
work, we provide a complete characterization of local obstructions to
convexity. This motivates us to define max intersection-complete codes, a
family guaranteed to have no local obstructions. We then show how our
characterization enables one to use free resolutions of Stanley-Reisner ideals
in order to detect violations of convexity. Taken together, these results
provide a significant advance in understanding the intrinsic combinatorial
properties of convex codes.
Dynamics of multi-stable states during ongoing and evoked cortical activity
Date: 2016-03-22 00:00:00
Tasks: Decision Making, Temporal Sequences

Single trial analyses of ensemble activity in alert animals demonstrate that
cortical circuits dynamics evolve through temporal sequences of metastable
states. Metastability has been studied for its potential role in sensory
coding, memory and decision-making. Yet, very little is known about the network
mechanisms responsible for its genesis. It is often assumed that the onset of
state sequences is triggered by an external stimulus. Here we show that state
sequences can be observed also in the absence of overt sensory stimulation.
Analysis of multielectrode recordings from the gustatory cortex of alert rats
revealed ongoing sequences of states, where single neurons spontaneously attain
several firing rates across different states. This single neuron
multi-stability represents a challenge to existing spiking network models,
where typically each neuron is at most bi-stable. We present a recurrent
spiking network model that accounts for both the spontaneous generation of
state sequences and the multi-stability in single neuron firing rates. Each
state results from the activation of neural clusters with potentiated
intra-cluster connections, with the firing rate in each cluster depending on
the number of active clusters. Simulations show that the models ensemble
activity hops among the different states, reproducing the ongoing dynamics
observed in the data. When probed with external stimuli, the model predicts the
quenching of single neuron multi-stability into bi-stability and the reduction
of trial-by-trial variability. Both predictions were confirmed in the data.
Altogether, these results provide a theoretical framework that captures both
ongoing and evoked network dynamics in a single mechanistic model.
On growth-optimal tax rates and the issue of wealth inequalities
Date: 2015-08-25 00:00:00

We introduce a highly stylized, yet non trivial model of the economy, with a
public and private sector coupled through a wealth tax and a redistribution
policy. The model can be fully solved analytically, and allows one to address
the question of optimal taxation and of wealth inequalities. We find that
according to the assumption made on the relative performance of public and
private sectors, three situations are possible. Not surprisingly, the optimal
wealth tax rate is either 0% for a deeply dysfunctional government and/or
highly productive private sector, or 100 % for a highly efficient public sector
and/or debilitated/risk averse private investors. If the gap between the
public/private performance is moderate, there is an optimal positive wealth tax
rate maximizing economic growth, even -- counter-intuitively -- when the
private sector generates more growth. The compromise between profitable private
investments and taxation however leads to a residual level of inequalities. The
mechanism leading to an optimal growth rate is related the well-known
explore/exploit trade-off.
Statistical Emulators for Pricing and Hedging Longevity Risk Products
Date: 2015-09-14 00:00:00

We propose the use of statistical emulators for the purpose of valuing
mortality-linked contracts in stochastic mortality models. Such models
typically require (nested) evaluation of expected values of nonlinear
functionals of multi-dimensional stochastic processes. Except in the simplest
cases, no closed-form expressions are available, necessitating numerical
approximation. Rather than building ad hoc analytic approximations, we advocate
the use of modern statistical tools from machine learning to generate a
flexible, non-parametric surrogate for the true mappings. This method allows
performance guarantees regarding approximation accuracy and removes the need
for nested simulation. We illustrate our approach with case studies involving
(i) a Lee-Carter model with mortality shocks, (ii) index-based static hedging
with longevity basis risk; (iii) a Cairns-Blake-Dowd stochastic survival
probability model.
Mod\'{e}lisation spatiale de la formation des agglom\'{e}rations dans la zone alg\'{e}roise
Date: 2015-07-24 00:00:00

The goal of this study is to analyze the dynamics underlying Algiers urban
area formation with reference to The New Economic Geography (NEG) theories and
more precisely to the paper of Paul Krugman (1991), "Increasing returns and
economic geography" which explains the mechanisms of economic activities
concentration through two types of forces: centripetal forces enhancing the
economic activities concentration and centrifugal forces hindering the
agglomeration process. In fact, these mechanisms are translated into a system
of nonlinear equations which is very hard to solve analytically. As a
consequence, the use of numerical methods is highly advocated. We present some
numerical simulations using real Algerian data.
Active Tension Network model reveals an exotic mechanical state realized in epithelial tissues
Date: 2017-01-18 00:00:00

It is now widely recognized that mechanical interactions between cells play a
crucial role in epithelial morphogenesis, yet understanding the mechanisms
through which stress and deformation affect cell behavior remains an open
problem due to the complexity inherent in the mechanical behavior of cells and
the difficulty of direct measurement of forces within tissues. Theoretical
models can help by focusing experimental studies and by providing the framework
for interpreting measurements. To that end, "vertex models" have introduced an
approximation of epithelial cell mechanics based on a polygonal tiling
representation of planar tissue. Here we formulate and analyze an Active
Tension Network (ATN) model, which is based on the same polygonal
representation of epithelial tissue geometry, but in addition i) assumes that
mechanical balance is dominated by cortical tension and ii) introduces tension
dependent local remodeling of the cortex, representing the active nature of
cytoskeletal mechanics. The tension-dominance assumption has immediate
implications for the geometry of cells, which we demonstrate to hold in certain
types of Drosophila epithelial tissues. We demonstrate that stationary
configurations of an ATN form a manifold with one degree of freedom per cell,
corresponding to "isogonal" - i.e. angle preserving - deformations of cells,
which dominate the dynamic response to perturbations. We show that isogonal
modes account for approximately 90% of experimentally observed deformation of
cells during the process of ventral furrow formation in Drosophila. Other
interesting properties of our model include the exponential screening of
mechanical stress and a negative Poisson ratio response to external uniaxial
stress. We also provide a new approach to the problem of inferring local
cortical tensions from the observed geometry of epithelial cells in a tissue
Using skewness and the first-digit phenomenon to identify dynamical transitions in cardiac models
Date: 2016-01-20 00:00:00

Disruptions in the normal rhythmic functioning of the heart, termed as
arrhythmia, often result from qualitative changes in the excitation dynamics of
the organ. The transitions between different types of arrhythmia are
accompanied by alterations in the spatiotemporal pattern of electrical activity
that can be measured by observing the time-intervals between successive
excitations of different regions of the cardiac tissue. Using biophysically
detailed models of cardiac activity we show that the distribution of these
time-intervals exhibit a systematic change in their skewness during such
dynamical transitions. Further, the leading digits of the normalized intervals
appear to fit Benford's law better at these transition points. This raises the
possibility of using these observations to design a clinical indicator for
identifying changes in the nature of arrhythmia. More importantly, our results
reveal an intriguing relation between the changing skewness of a distribution
and its agreement with Benford's law, both of which have been independently
proposed earlier as indicators of regime shift in dynamical systems.
Symmetry restoration by pricing in a duopoly of perishable goods
Date: 2015-09-29 00:00:00

Competition is a main tenet of economics, and the reason is that a perfectly
competitive equilibrium is Pareto-efficient in the absence of externalities and
public goods. Whether a product is selected in a market crucially relates to
its competitiveness, but the selection in turn affects the landscape of
competition. Such a feedback mechanism has been illustrated in a duopoly model
by Lambert et al., in which a buyer's satisfaction is updated depending on the
{\em freshness} of a purchased product. The probability for buyer $n$ to select
seller $i$ is assumed to be $p_{n,i} \propto e^{ S_{n,i}/T}$, where $S_{n,i}$
is the buyer's satisfaction and $T$ is an effective temperature to introduce
stochasticity. If $T$ decreases below a critical point $T_c$, the system
undergoes a transition from a symmetric phase to an asymmetric one, in which
only one of the two sellers is selected. In this work, we extend the model by
incorporating a simple price system. By considering a greed factor $g$ to
control how the satisfaction depends on the price, we argue the existence of an
oscillatory phase in addition to the symmetric and asymmetric ones in the
$(T,g)$ plane, and estimate the phase boundaries through mean-field
approximations. The analytic results show that the market preserves the
inherent symmetry between the sellers for lower $T$ in the presence of the
price system, which is confirmed by our numerical simulations.
Minimizing the Expected Lifetime Spent in Drawdown under Proportional Consumption
Date: 2015-08-23 00:00:00

We determine the optimal amount to invest in a Black-Scholes financial market
for an individual who consumes at a rate equal to a constant proportion of her
wealth and who wishes to minimize the expected time that her wealth spends in
drawdown during her lifetime. Drawdown occurs when wealth is less than some
fixed proportion of maximum wealth. We compare the optimal investment strategy
with those for three related goal-seeking problems and learn that the
individual is myopic in her investing behavior, as expected from other
goal-seeking research.
CCA Fuzzy Land Cover: a new method for classifying vegetation types and coverages and its implications for deforestation analysis
Date: 2016-06-19 00:00:00

Land cover has been evaluated and classified on the basis of general features
using reflectance or digital levels of photographic or satellite data. One of
the most common methodologies based on CORINE land cover (Coordination of
Information on the Environment) data, which classifies natural cover according
to a small number of categories. This method produces generalizations about the
inventoried areas, resulting in the loss of important floristic and structural
information about vegetation types present (such as palm groves, tall dense
mangroves, and dense forests). This classification forfeits relevant
information on sites with high heterogeneity and diversity. Especially in the
tropics, simplification of coverage types reaches its maximum level with the
use of deforestation analysis, particularly when it is reduced to the two
classes of forests and nonforests. As this paper demonstrates, these results
have considerable consequences for political efforts to conserve the
biodiversity of megadiverse countries. We designed a new methodological
approach that incorporates biological distinctiveness combined with
phytosociological classification of vegetation and its relation to physical
features. This approach is based on parameters obtained through canonical
correspondence analysis on a fuzzy logic model, which are used to construct
multiple coverage maps. This tool is useful for monitoring and analyzing
vegetation dynamics, since it maintains the typological integrity of a
cartographic series. The methodology creates cartographic series congruent in
time and scale, can be applied to multiple and varied satellite inputs, and
always evaluates the same model parameters. We tested this new method in the
southwestern Colombian Caribbean region and compared our results with those
from what we believe are outdated tools used in other analyses of deforestation
around the world.