pwc-archive/papers-with-abstracts huggingface dataset:
First Principles Attempt to Unify some Population Growth Models
Date: 2016-05-20 00:00:00

In this work, some phenomenological models, those that are based only on the
population information (macroscopic level), are deduced in an intuitive way.
These models, as for instance Verhulst, Gompertz and Bertalanffy models, are
posted in such a manner that all the parameters involved have physical
interpretation. A model based on the interaction (distance dependent) between
the individuals (microscopic level) is also presented. This microscopic model
reachs the phenomenological models presented as particular cases. In this
approach, the Verhulst model represents the situation in which all the
individuals interact in the same way, regardless of the distance between them.
That means Verhulst model is a kind of mean field model. The other
phenomenological models are reaching from the microscopic model according to
two quantities: i) the relation between the way that the interaction decays
with the distance; and ii) the dimension of the spatial structure formed by the
population. This microscopic model allows understanding population growth by
first principles, because it predicts that some phenomenological models can be
seen as a consequence of the same individual level kind of interaction. In this
sense, the microscopic model that will be discussed here paves the way to
finding universal patterns that are common to all types of growth, even in
systems of very different nature.
Criteria for folding in structure-based models of proteins
Date: 2016-05-20 00:00:00

In structure-based models of proteins, one often assumes that folding is
accomplished when all contacts are established. This assumption may frequently
lead to a conceptual problem that folding takes place in a temperature region
of very low thermodynamic stability, especially when the contact map used is
too sparse. We consider six different structure-based models and show that
allowing for a small, but model-dependent, percentage of the native contacts
not being established boosts the folding temperature substantially while
affecting the time scales of folding only in a minor way. We also compare other
properties of the six models. We show that the choice of the description of the
backbone stiffness has a substantial effect on the values of characteristic
temperatures that relate both to equilibrium and kinetic properties. Models
without any backbone stiffness (like the self-organized polymer) are found to
perform similar to those with the stiffness, including in the studies of
stretching.
Hedging with Small Uncertainty Aversion
Date: 2016-05-20 00:00:00

We study the pricing and hedging of derivative securities with uncertainty
about the volatility of the underlying asset. Rather than taking all models
from a prespecified class equally seriously, we penalise less plausible ones
based on their "distance" to a reference local volatility model. In the limit
for small uncertainty aversion, this leads to explicit formulas for prices and
hedging strategies in terms of the security's cash gamma.
Seasonality on the life cycle of Aedes aegypti mosquito and its effects on dengue outbreaks
Date: 2016-05-20 00:00:00

Dengue is a vector-borne disease transmitted by the mosquito Aedes aegypti.
It has been observed that its incidence is strongly influenced by temperature
and other abiotic factors like rainfall and humidity. In this work we compare
the effects of seasonality in temperature that affect the entomological
parameters of the mosquito with precipitation that affects the hatchery
capacity. We also analyze its joint action using a dynamical model for the life
cycle of Aedes aegypti and historical weather data from 8 regions of Mexico. We
found that the joint action of different mechanisms can enhance the prevalence
of the disease, but also inhibit it when they act in an asynchronous way. We
found that for the studied regions, the seasonality of the low temperature
rather than mean temperature is the main driving force of Dengue outbreaks. We
also analyzed the role of the diapause in these kinds of outbreaks. The
methodology developed here can be used to discover the underlying mechanism of
Dengue outbreaks in different regions and thus help to apply targeted control
measures.
Volatility Forecasts Using Nonlinear Leverage Effects
Date: 2017-12-11 00:00:00

The leverage effect-- the correlation between an asset's return and its
volatility-- has played a key role in forecasting and understanding volatility
and risk. While it is a long standing consensus that leverage effects exist and
improve forecasts, empirical evidence paradoxically do not show that most
individual stocks exhibit this phenomena, mischaracterizing risk and therefore
leading to poor predictive performance. We examine this paradox, with the goal
to improve density forecasts, by relaxing the assumption of linearity in the
leverage effect. Nonlinear generalizations of the leverage effect are proposed
within the Bayesian stochastic volatility framework in order to capture
flexible leverage structures, where small fluctuations in prices have a
different effect from large shocks. Efficient Bayesian sequential computation
is developed and implemented to estimate this effect in a practical, on-line
manner. Examining 615 stocks that comprise the S\&P500 and Nikkei 225, we find
that relaxing the linear assumption to our proposed nonlinear leverage effect
function improves predictive performances for 89\% of all stocks compared to
the conventional model assumption.
Bidirectionality From Cargo Thermal Fluctuations in Motor-Mediated Transport
Date: 2016-12-27 00:00:00

Molecular motor proteins serve as an essential component of intracellular
transport by generating forces to haul cargoes along cytoskeletal filaments.
Two species of motors that are directed oppositely (e.g. kinesin, dynein) can
be attached to the same cargo, which is known to produce bidirectional net
motion. Although previous work focuses on the motor number as the driving noise
source for switching, we propose an alternative mechanism: cargo diffusion. A
mean-field mathematical model of mechanical interactions of two populations of
molecular motors with cargo thermal fluctuations (diffusion) is presented to
study this phenomenon. The delayed response of a motor to fluctuations in the
cargo velocity is quantified, allowing for the reduction of the full model a
single "characteristic distance", a proxy for the net force on the cargo. The
system is then found to be metastable, with switching exclusively due to cargo
diffusion between distinct directional transport states. The time to switch
between these states is then investigated using a mean first passage time
analysis. The switching time is found to be non-monotonic in the drag of the
cargo, providing an experimental test of the theory.
Evolutionary dynamics on any population structure
Date: 2016-12-22 00:00:00

Evolution occurs in populations of reproducing individuals. The structure of
a biological population affects which traits evolve. Understanding evolutionary
game dynamics in structured populations is difficult. Precise results have been
absent for a long time, but have recently emerged for special structures where
all individuals have the same number of neighbors. But the problem of
determining which trait is favored by selection in the natural case where the
number of neighbors can vary, has remained open. For arbitrary selection
intensity, the problem is in a computational complexity class which suggests
there is no efficient algorithm. Whether there exists a simple solution for
weak selection was unanswered. Here we provide, surprisingly, a general formula
for weak selection that applies to any graph or social network. Our method uses
coalescent theory and relies on calculating the meeting times of random walks.
We can now evaluate large numbers of diverse and heterogeneous population
structures for their propensity to favor cooperation. We can also study how
small changes in population structure---graph surgery---affect evolutionary
outcomes. We find that cooperation flourishes most in societies that are based
on strong pairwise ties.
On Content-Based Recommendation and User Privacy in Social-Tagging Systems
Authors: Puglisi Silvia, Parra-Arnau Javier, Forné Jordi, Rebollo-Monedero David
Date: 2016-05-20 00:00:00
Tasks: Recommendation Systems, TAG

Recommendation systems and content filtering approaches based on annotations
and ratings, essentially rely on users expressing their preferences and
interests through their actions, in order to provide personalised content. This
activity, in which users engage collectively, has been named social tagging.
Although it has opened a myriad of new possibilities for application
interoperability on the semantic web, it is also posing new privacy threats.
Social tagging consists in describing online or online resources by using
free-text labels (i.e. tags), therefore exposing the user's profile and
activity to privacy attacks. Tag forgery is a privacy enhancing technology
consisting of generating tags for categories or resources that do not reflect
the user's actual preferences. By modifying their profile, tag forgery may have
a negative impact on the quality of the recommendation system, thus protecting
user privacy to a certain extent but at the expenses of utility loss. The
impact of tag forgery on content-based recommendation is, therefore,
investigated in a real-world application scenario where different forgery
strategies are evaluated, and the consequent loss in utility is measured and
compared.
Inference by Reparameterization in Neural Population Codes
Date: 2016-05-20 00:00:00
Proceeding: NeurIPS 2016 12

Behavioral experiments on humans and animals suggest that the brain performs
probabilistic inference to interpret its environment. Here we present a new
general-purpose, biologically-plausible neural implementation of approximate
inference. The neural network represents uncertainty using Probabilistic
Population Codes (PPCs), which are distributed neural representations that
naturally encode probability distributions, and support marginalization and
evidence integration in a biologically-plausible manner. By connecting multiple
PPCs together as a probabilistic graphical model, we represent multivariate
probability distributions. Approximate inference in graphical models can be
accomplished by message-passing algorithms that disseminate local information
throughout the graph. An attractive and often accurate example of such an
algorithm is Loopy Belief Propagation (LBP), which uses local marginalization
and evidence integration operations to perform approximate inference
efficiently even for complex models. Unfortunately, a subtle feature of LBP
renders it neurally implausible. However, LBP can be elegantly reformulated as
a sequence of Tree-based Reparameterizations (TRP) of the graphical model. We
re-express the TRP updates as a nonlinear dynamical system with both fast and
slow timescales, and show that this produces a neurally plausible solution. By
combining all of these ideas, we show that a network of PPCs can represent
multivariate probability distributions and implement the TRP updates to perform
probabilistic inference. Simulations with Gaussian graphical models demonstrate
that the neural network inference quality is comparable to the direct
evaluation of LBP and robust to noise, and thus provides a promising mechanism
for general probabilistic inference in the population codes of the brain.
A model for the clustered distribution of SNPs in the human genome
Date: 2016-05-21 00:00:00
Tasks: Diversity

Motivated by a non-random but clustered distribution of SNPs, we introduce a
phenomenological model to account for the clustering properties of SNPs in the
human genome. The phenomenological model is based on a preferential mutation to
the closer proximity of existing SNPs. With the Hapmap SNP data, we empirically
demonstrate that the preferential model is better for illustrating the
clustered distribution of SNPs than the random model. Moreover, the model is
applicable not only to autosomes but also to the X chromosome, although the X
chromosome has different characteristics from autosomes. The analysis of the
estimated parameters in the model can explain the pronounced population
structure and the low genetic diversity of the X chromosome. In addition,
correlation between the parameters reveals the population-wise difference of
the mutation probability. These results support the mutational non-independence
hypothesis against random mutation.
The impact of the financial crisis on the long-range memory of European corporate bond and stock markets
Date: 2016-05-21 00:00:00

This paper investigates the presence of long memory in corporate bond and
stock indices of six European Union countries from July 1998 to February 2015.
We compute the Hurst exponent by means of the DFA method and using a sliding
window in order to measure long range dependence. We detect that Hurst
exponents behave differently in the stock and bond markets, being smoother in
the stock indices than in the bond indices. We verify that the level of
informational efficiency is time-varying. Moreover we find an asymmetric impact
of the 2008 financial crisis in the fixed income and the stock markets,
affecting the former but not the latter. Similar results are obtained using the
R/S method.
Velvet Worms (Onychophora) in Folklore and Art: Geographic Pattern, Types of Cultural Reference and Public Perception
Date: 2016-05-21 00:00:00
Tasks: Cultural Vocal Bursts Intensity Prediction, Image Retrieval

Aims: To document and preserve folkloric beliefs and art inspired by velvet
worms (Onychophora), rare invertebrates that are considered "living fossils",
have full placental organs and capture prey with a rough "net" built in a
fraction of a second. Study Design: This study is a combination of field
interviews, online surveys and automatic database search. Methods: We asked
open-ended questions to farmers who know the worms, consulted experts and
searched the Internet to document folkloric and artistic instances using all
the names that these animals receive in English, Spanish and Portuguese
(languages of the countries where they occur) as well as other languages, and
automatic image search, in Web of Science, CrossRef, Google Scholar and Google.
Results: We found more than 80 cases of direct references to velvet worms in
folklore and art, mostly from the USA, Australia, Brazil, Costa Rica and New
Zealand. Per capita the countries with more cases are New Zealand (24 cases per
million inhabitants), Costa Rica (16 cases per million inhabitants) and
Australia (3 cases per million inhabitants). The most frequent expressions are
cartoons, followed by tourism agencies using velvet worms in their ads,
products with velvet worm representations, folkloric beliefs, and music bands
or songs named after them. In almost all cases the animals are seen in a
favorable light, inspiring folklore and art that highlight their extraordinary
nature. Conclusion: The unique prey capture mechanism of velvet worms seems to
have inspired an unexpected number of artistic and folkloric expressions,
preserved for the future in the present article, which starts a totally new
line of research: the effect of "living fossils" on human culture.
An unbiased metric of antiproliferative drug effect in vitro
Date: 2016-05-22 00:00:00
Tasks: Drug Discovery

In vitro cell proliferation assays are widely used in pharmacology, molecular
biology, and drug discovery. Using theoretical modeling and experimentation, we
show that current antiproliferative drug effect metrics suffer from
time-dependent bias, leading to inaccurate assessments of parameters such as
drug potency and efficacy. We propose the drug-induced proliferation (DIP)
rate, the slope of the line on a plot of cell population doublings versus time,
as an alternative, time-independent metric.
Asymptotic Eigenvalue Distribution of Wishart Matrices whose Components are not Independently and Identically Distributed
Date: 2016-05-22 00:00:00

In the present work, eigenvalue distributions defined by a random rectangular
matrix whose components are neither independently nor identically distributed
are analyzed using replica analysis and belief propagation. In particular, we
consider the case in which the components are independently but not identically
distributed; for example, only the components in each row or in each column may
be {identically distributed}. We also consider the more general case in which
the components are correlated with one another. We use the replica approach
while making only weak assumptions in order to determine the asymptotic
eigenvalue distribution and to derive an algorithm for doing so, based on
belief propagation. One of our findings supports the results obtained from
Feynman diagrams. We present the results of several numerical experiments that
validate our proposed methods.
Portfolio Optimization Problem with Non-identical Variances of Asset Returns using Statistical Mechanical Informatics
Date: 2016-05-22 00:00:00
Tasks: Portfolio Optimization

The portfolio optimization problem in which the variances of the return rates
of assets are not identical is analyzed in this paper using the methodology of
statistical mechanical informatics, specifically, replica analysis. We define
two characteristic quantities of an optimal portfolio, namely, minimal
investment risk and concentrated investment level, in order to solve the
portfolio optimization problem and analytically determine their asymptotical
behaviors using replica analysis. Moreover, numerical experiments were
performed, and a comparison between the results of our simulation and those
obtained via replica analysis validated our proposed method.
Minimal Investment Risk of Portfolio Optimization Problem with Budget and Investment Concentration Constraints
Date: 2016-05-22 00:00:00
Tasks: Portfolio Optimization

In the present paper, the minimal investment risk for a portfolio
optimization problem with imposed budget and investment concentration
constraints is considered using replica analysis. Since the minimal investment
risk is influenced by the investment concentration constraint (as well as the
budget constraint), it is intuitive that the minimal investment risk for the
problem with an investment concentration constraint be larger than that without
the constraint (that is, with only the budget constraint). Moreover, a
numerical experiment shows the effectiveness of our proposed analysis.
Genetic recombination as DNA repair
Date: 2016-05-23 00:00:00

Maintenance of sexual reproduction and genetic recombination imposes
physiological costs when compared to parthenogenic reproduction, most
prominently: for maintaining the corresponding (molecular) machinery, for
finding a mating partner, and through the decreased fraction of females in a
population, which decreases the reproductive capacity. Based on principles from
information theory, we have previously developed a new population genetic
model, and applying it in simulations, we have recently hypothesized that all
species maintain the maximum genomic complexity that is required by their niche
and allowed by their mutation rate and selection intensity. Applying this idea
to the complexity overhead of recombination maintenance, its costs must be more
than compensated by an additional capacity for complexity in recombining
populations. Here, we show a simple mechanism, where recombination helps to
maintain larger biases of alleles frequencies in a population, so the
advantageous alleles can have increased frequency. This allows recombining
populations to maintain higher fitness and phenotypic efficiency in comparison
with asexual populations with the same parameters. Random mating alone already
significantly increases the ability to maintain genomic and phenotypic
complexity. Sexual selection provides additional capacity for this complexity.
The model can be considered as a unifying synthesis of previous hypotheses
about the roles of recombination in Muller's ratchet, mutation purging and Red
Queen dynamics, because the introduction of recombination both increases
population frequencies of beneficial alleles and decreases detrimental ones. In
addition, we suggest simple explanations for niche-dependent prevalence of
transient asexuality and the exceptional asexual lineage of Bdelloid rotifers.
The mitotic spindle in the one-cell C. elegans embryo is positioned with high precision and stability
Date: 2016-09-13 00:00:00
Tasks: Position

Precise positioning of the mitotic spindle is important for specifying the
plane of cell division, which in turn determines how the cytoplasmic contents
are partitioned into the daughter cells, and how the daughters are positioned
within the tissue. During metaphase in the early C. elegans embryo, the spindle
is aligned and centered on the anterior-posterior axis by a
microtubule-dependent machinery that exerts restoring forces when the spindle
is displaced from the center. To investigate the accuracy and stability of
centering, we tracked the position and orientation of the mitotic spindle
during the first cell division with high temporal and spatial resolution. We
found that the precision is remarkably high: the cell-to-cell variation in the
transverse position of the center of the spindle during metaphase, as measured
by the standard deviation, was only 1.5% of the length of the short axis of the
cell. Spindle position is also very stable: the standard deviation of the
fluctuations in transverse spindle position during metaphase was only 0.5% of
the short axis of the cell. Assuming that stability is limited by fluctuations
in the number of independent motor elements such as microtubules or dyneins
underlying the centering machinery, we infer that the number is on the order of
one thousand, consistent with the several thousand of astral microtubules in
these cells. Astral microtubules grow out from the two spindle poles, make
contact with the cell cortex, and then shrink back shortly thereafter. The high
stability of centering can be accounted for quantitatively if, while making
contact with the cortex, the astral microtubules buckle as they exert
compressive, pushing forces. We thus propose that the large number of
microtubules in the asters provides a highly precise mechanism for positioning
the spindle during metaphase while assembly is completed prior to the onset of
anaphase.
Initial conditions in the neural field model
Date: 2016-05-23 00:00:00
Tasks: model, Time Series, Time Series Analysis

In spite of the large amount of existing neural models in the literature,
there is a lack of a systematic review of the possible effect of choosing
different initial conditions on the dynamic evolution of neural systems. In
this short review we intend to give insights into this topic by discussing some
published examples. First, we briefly introduce the different ingredients of a
neural dynamical model. Secondly, we introduce some concepts used to describe
the dynamic behavior of neural models, namely phase space and its portraits,
time series, spectra, multistability and bifurcations. We end with an analysis
of the irreversibility of processes and its implications on the functioning of
normal and pathological brains.
Functional neuroimaging of psychedelic experience: An overview of psychological and neural effects and their relevance to research on creativity, daydreaming, and dreaming
Date: 2016-05-23 00:00:00

Humans have employed an incredible variety of plant-derived substances over
the millennia in order to alter consciousness and perception. Among the
innumerable narcotics, analgesics, 'ordeal' drugs, and other psychoactive
substances discovered and used in ritualistic contexts by cultures around the
world, one class in particular stands out not only for its radical
psychological effects, but also for the highly charged political and legal
atmosphere that has surrounded it since its widespread adoption about 50 years
ago: so-called psychedelic substances. We review functional neuroimaging
investigations of the neural correlates of the psychedelic experience, and
highlight relationships with the psychological and neural bases of creativity,
daydreaming, and dreaming.