pwc-archive/papers-with-abstracts huggingface dataset:
The "Wow! signal" of the terrestrial genetic code
Date: 2017-06-12 00:00:00

It has been repeatedly proposed to expand the scope for SETI, and one of the
suggested alternatives to radio is the biological media. Genomic DNA is already
used on Earth to store non-biological information. Though smaller in capacity,
but stronger in noise immunity is the genetic code. The code is a flexible
mapping between codons and amino acids, and this flexibility allows modifying
the code artificially. But once fixed, the code might stay unchanged over
cosmological timescales. Thus, it represents a reliable storage for an
intelligent signature, if that conforms to biological and thermodynamic
requirements. As the actual scenario for the origin of terrestrial life is far
from being settled, the proposal that it might have been seeded intentionally
cannot be ruled out. A statistically strong signal in the genetic code is then
a testable consequence of such scenario. Here we show that the terrestrial code
displays a thorough precision orderliness matching the criteria to be
considered an informational signal. Simple arrangements of the code reveal an
ensemble of arithmetical and ideographical patterns of the same symbolic
language. Accurate and systematic, these underlying patterns appear as a
product of precision logic and nontrivial computing rather than of stochastic
processes. The patterns are profound to the extent that the code mapping itself
is uniquely deduced from their algebraic representation. The signal displays
readily recognizable hallmarks of artificiality. Besides, extraction of the
signal involves logically straightforward but abstract operations, making the
patterns essentially irreducible to any natural origin. Plausible way of
embedding the signal into the code and possible interpretation of its content
are discussed. Overall, while the code is nearly optimized biologically, its
limited capacity is used extremely efficiently to store non-biological
information.
Directional genetic differentiation and asymmetric migration
Date: 2016-09-26 00:00:00

Understanding the population structure and patterns of gene flow within
species is of fundamental importance to the study of evolution. In the fields
of population and evolutionary genetics, measures of genetic differentiation
are commonly used to gather this information. One potential caveat is that
these measures assume gene flow to be symmetric. However, asymmetric gene flow
is common in nature, especially in systems driven by physical processes such as
wind or water currents. Since information about levels of asymmetric gene flow
among populations is essential for the correct interpretation of the
distribution of contemporary genetic diversity within species, this should not
be overlooked. To obtain information on asymmetric migration patterns from
genetic data, complex models based on maximum likelihood or Bayesian approaches
generally need to be employed, often at great computational cost. Here, a new
simpler and more efficient approach for understanding gene flow patterns is
presented. This approach allows the estimation of directional components of
genetic divergence between pairs of populations at low computational effort,
using any of the classical or modern measures of genetic differentiation. These
directional measures of genetic differentiation can further be used to
calculate directional relative migration and to detect asymmetries in gene flow
patterns. This can be done in a user-friendly web application called
divMigrate-online introduced in this paper. Using simulated data sets with
known gene flow regimes, we demonstrate that the method is capable of resolving
complex migration patterns under a range of study designs.
Neural network spectral robustness under perturbations of the underlying graph
Date: 2015-07-16 00:00:00

Recent studies have been using graph theoretical approaches to model complex
networks (such as social, infrastructural or biological networks), and how
their hardwired circuitry relates to their dynamic evolution in time.
Understanding how configuration reflects on the coupled behavior in a system of
dynamic nodes can be of great importance, for example in the context of how the
brain connectome is affecting brain function. However, the connectivity
patterns that appear in brain networks, and their individual effects on network
dynamics, are far from being fully understood.
  We study the connections between edge configuration and dynamics in a simple
oriented network composed of two interconnected cliques (representative of
brain feedback regulatory circuitry). In this paper, our main goal is to study
the spectra of the graph adjacency and Laplacian matrices, with a focus on
three aspects in particular: (1) the sensitivity/robustness the spectrum in
response to varying the intra and inter-modular edge density, (2) the effects
on the spectrum of perturbing the edge configuration, while keeping the
densities fixed and (3) the effects of increasing the network size. We study
some tractable aspects analytically, then simulate more general results
numerically. This paper aims to clarify, from analytical and modeling
perspectives, the underpinnings of our related work, which further addresses
how graph properties affect the network's temporal dynamics and phase
transitions.
  We propose that this type of results may be helpful when studying small
networks such as macroscopic brain circuits. We suggest potential applications
to understanding synaptic restructuring in learning networks, and the effects
of network configuration to function of emotion-regulatory neural circuits.
Methods to study splicing from high-throughput RNA Sequencing data
Date: 2015-07-30 00:00:00
Tasks: Vocal Bursts Intensity Prediction

The development of novel high-throughput sequencing (HTS) methods for RNA
(RNA-Seq) has provided a very powerful mean to study splicing under multiple
conditions at unprecedented depth. However, the complexity of the information
to be analyzed has turned this into a challenging task. In the last few years,
a plethora of tools have been developed, allowing researchers to process
RNA-Seq data to study the expression of isoforms and splicing events, and their
relative changes under different conditions. We provide an overview of the
methods available to study splicing from short RNA-Seq data. We group the
methods according to the different questions they address: 1) Assignment of the
sequencing reads to their likely gene of origin. This is addressed by methods
that map reads to the genome and/or to the available gene annotations. 2)
Recovering the sequence of splicing events and isoforms. This is addressed by
transcript reconstruction and de novo assembly methods. 3) Quantification of
events and isoforms. Either after reconstructing transcripts or using an
annotation, many methods estimate the expression level or the relative usage of
isoforms and/or events. 4) Providing an isoform or event view of differential
splicing or expression. These include methods that compare relative
event/isoform abundance or isoform expression across two or more conditions. 5)
Visualizing splicing regulation. Various tools facilitate the visualization of
the RNA-Seq data in the context of alternative splicing. In this review, we do
not describe the specific mathematical models behind each method. Our aim is
rather to provide an overview that could serve as an entry point for users who
need to decide on a suitable tool for a specific analysis. We also attempt to
propose a classification of the tools according to the operations they do, to
facilitate the comparison and choice of methods.
Elasticity theory of structuring
Date: 2016-12-12 00:00:00

Financial derivatives have often been criticized as casino-style betting
instruments. It turns out that many naive ways of making them are indeed
equivalent to gambling. Fortunately, this inadvertent effect can be understood
and prevented. We present a theory of product design which achieves that.
A comparison of techniques for dynamic multivariate risk measures
Date: 2015-01-29 00:00:00

This paper contains an overview of results for dynamic multivariate risk
measures. We provide the main results of four different approaches. We will
prove under which assumptions results within these approaches coincide, and how
properties like primal and dual representation and time consistency in the
different approaches compare to each other.
Third-Order Short-Time Expansions for Close-to-the-Money Option Prices under the CGMY Model
Date: 2017-11-22 00:00:00

A third-order approximation for close-to-the-money European option prices
under an infinite-variation CGMY L\'{e}vy model is derived, and is then
extended to a model with an additional independent Brownian component. The
asymptotic regime considered, in which the strike is made to converge to the
spot stock price as the maturity approaches zero, is relevant in applications
since the most liquid options have strikes that are close to the spot price.
Our results shed new light on the connection between both the volatility of the
continuous component and the jump parameters and the behavior of option prices
near expiration when the strike is close to the spot price. In particular, a
new type of transition phenomenon is uncovered in which the third order term
exhibits two distinct asymptotic regimes depending on whether $Y\in(1,3/2)$ or
$Y\in(3/2,2)$. Unlike second order approximations, the expansions herein are
shown to be remarkably accurate so that they can actually be used for
calibrating some model parameters. For illustration, we calibrate the
volatility $\sigma$ of the Brownian component and the jump intensity $C$ of the
CGMY model to actual option prices.
Travelling wave analysis of a mathematical model of glioblastoma growth
Date: 2017-02-17 00:00:00

In this paper we analyse a previously proposed cell-based model of
glioblastoma (brain tumour) growth, which is based on the assumption that the
cancer cells switch phenotypes between a proliferative and motile state (Gerlee
and Nelander, PLoS Comp. Bio., 8(6) 2012). The dynamics of this model can be
described by a system of partial differential equations, which exhibits
travelling wave solutions whose wave speed depends crucially on the rates of
phenotypic switching. We show that under certain conditions on the model
parameters, a closed form expression of the wave speed can be obtained, and
using singular perturbation methods we also derive an approximate expression of
the wave front shape. These new analytical results agree with simulations of
the cell-based model, and importantly show that the inverse relationship
between wave front steepness and speed observed for the Fisher equation no
longer holds when phenotypic switching is considered.
Arbitrage and duality in nondominated discrete-time models
Date: 2015-03-16 00:00:00

We consider a nondominated model of a discrete-time financial market where
stocks are traded dynamically, and options are available for static hedging. In
a general measure-theoretic setting, we show that absence of arbitrage in a
quasi-sure sense is equivalent to the existence of a suitable family of
martingale measures. In the arbitrage-free case, we show that optimal
superhedging strategies exist for general contingent claims, and that the
minimal superhedging price is given by the supremum over the martingale
measures. Moreover, we obtain a nondominated version of the Optional
Decomposition Theorem.
B-spline techniques for volatility modeling
Date: 2015-06-12 00:00:00

This paper is devoted to the application of B-splines to volatility modeling,
specifically the calibration of the leverage function in stochastic local
volatility models and the parameterization of an arbitrage-free implied
volatility surface calibrated to sparse option data. We use an extension of
classical B-splines obtained by including basis functions with infinite
support. We first come back to the application of shape-constrained B-splines
to the estimation of conditional expectations, not merely from a scatter plot
but also from the given marginal distributions. An application is the Monte
Carlo calibration of stochastic local volatility models by Markov projection.
Then we present a new technique for the calibration of an implied volatility
surface to sparse option data. We use a B-spline parameterization of the
Radon-Nikodym derivative of the underlying's risk-neutral probability density
with respect to a roughly calibrated base model. We show that this method
provides smooth arbitrage-free implied volatility surfaces. Finally, we sketch
a Galerkin method with B-spline finite elements to the solution of the partial
differential equation satisfied by the Radon-Nikodym derivative.
Ruin probability of a discrete-time risk process with proportional reinsurance and investment for exponential and Pareto distributions
Date: 2015-03-15 00:00:00

In this paper a quantitative analysis of the ruin probability in finite time
of discrete risk process with proportional reinsurance and investment of
finance surplus is focused on. It is assumed that the total loss on a unit
interval has a light-tailed distribution -- exponential distribution and a
heavy-tailed distribution -- Pareto distribution. The ruin probability for
finite-horizon 5 and 10 was determined from recurrence equations. Moreover for
exponential distribution the upper bound of ruin probability by Lundberg
adjustment coefficient is given. For Pareto distribution the adjustment
coefficient does not exist, hence an asymptotic approximation of the ruin
probability if an initial capital tends to infinity is given. Obtained
numerical results are given as tables and they are illustrated as graphs.
Additive versus multiplicative parameters - applications in economics and finance
Date: 2016-12-12 00:00:00

In this paper, we pay our attention to geometric parameters and their
applications in economics and finance. We discuss the multiplicative models in
which a geometric mean and a geometric standard deviation are more natural than
arithmetic ones. We give two examples from Warsaw Stock Exchange in 1995--2009
and from a bid of 52-week treasury bills in 1992--2009 in Poland as an
illustrative example. For distributions having applications in finance and
insurance we give their multiplicative parameters as well as their estimations.
We consider, among others, heavy-tailed distributions such as lognormal and
Pareto distribution, applied to modelling of large losses.
Composite random search strategies based on non-directional sensory cues
Date: 2015-02-27 00:00:00

Many foraging animals find food using composite random search strategies,
which consist of intensive and extensive search modes. Models of composite
search can generate predictions about how optimal foragers should behave in
each search mode, and how they should determine when to switch between search
modes. Most of these models assume that foragers use resource encounters to
decide when to switch between search modes. Empirical observations indicate
that a variety of organisms use non-directional sensory cues to identify areas
that warrant intensive search. These cues are not precise enough to allow a
forager to directly orient itself to a resource, but can be used as a criterion
to determine the appropriate search mode. As a potential example, a forager
might use olfactory information, which could help it determine if an area is
worth searching carefully. We developed a model of composite search based on
non-directional sensory cues. With simulations, we compared the search
efficiencies of composite foragers that use resource encounters as their
mode-switching criterion with those that use non-directional sensory cues. We
identified optimal search patterns and mode-switching criteria on a variety of
resource distributions, characterized by different levels of resource
aggregation and density. On all resource distributions, foraging strategies
based on the non-directional sensory criterion were more efficient than those
based on the resource encounter criterion. Strategies based on the
non-directional sensory criterion were also more robust to changes in resource
distribution. Our results suggest that current assumptions about the role of
resource encounters in models of optimal composite search should be
re-examined. The search strategies predicted by our model can help bridge the
gap between random search theory and traditional patch-use foraging theory.
Social Discounting and the Long Rate of Interest
Date: 2015-09-28 00:00:00
Tasks: Management

The well-known theorem of Dybvig, Ingersoll and Ross shows that the long
zero-coupon rate can never fall. This result, which, although undoubtedly
correct, has been regarded by many as surprising, stems from the implicit
assumption that the long-term discount function has an exponential tail. We
revisit the problem in the setting of modern interest rate theory, and show
that if the long "simple" interest rate (or Libor rate) is finite, then this
rate (unlike the zero-coupon rate) acts viably as a state variable, the value
of which can fluctuate randomly in line with other economic indicators. New
interest rate models are constructed, under this hypothesis and certain
generalizations thereof, that illustrate explicitly the good asymptotic
behaviour of the resulting discount bond systems. The conditions necessary for
the existence of such "hyperbolic" and "generalized hyperbolic" long rates are
those of so-called social discounting, which allow for long-term cash flows to
be treated as broadly "just as important" as those of the short or medium term.
As a consequence, we are able to provide a consistent arbitrage-free valuation
framework for the cost-benefit analysis and risk management of long-term social
projects, such as those associated with sustainable energy, resource
conservation, and climate change.
A Statistical Test of Walrasian Equilibrium by Means of Complex Networks Theory
Date: 2016-09-14 00:00:00

We represent an exchange economy in terms of statistical ensembles for
complex networks by introducing the concept of market configuration. This is
defined as a sequence of nonnegative discrete random variables $\{w_{ij}\}$
describing the flow of a given commodity from agent $i$ to agent $j$. This
sequence can be arranged in a nonnegative matrix $W$ which we can regard as the
representation of a weighted and directed network or digraph $G$. Our main
result consists in showing that general equilibrium theory imposes highly
restrictive conditions upon market configurations, which are in most cases not
fulfilled by real markets. An explicit example with reference to the e-MID
interbank credit market is provided.
Characteristics of Cost Overruns for Dutch Transport Infrastructure Projects and the Importance of the Decision to Build and Project Phases
Date: 2015-01-24 00:00:00
Tasks: Decision Making

Using a methodology similar to that used the in the worldwide research, the
cost performance of Dutch large-scale transport infrastructure projects is
determined. In the Netherlands, cost overruns are as common as cost underruns
but because cost overruns are larger than cost underruns projects on average
have a cost overrun of 16.5%. The focus on one country further enabled to
consider cost overruns during different project development phases. It turned
out that in the Netherlands the majority of the cost overrun occurs in the
pre-construction phase (the period between the formal decision to build and the
start of construction). The frequency as well as the magnitude of
pre-construction cost overrun is significantly higher than in the construction
phase. The used methodology of calculating cost overruns does however not take
lock-in into account. This phenomenon shows that the real decision to build was
taken much earlier in the decision-making process. Since estimated costs are
usually lower during these earlier stages, the cost overruns based on this real
decision to build are likely to be much higher. Cost overruns presented in
studies are therefore often underestimated and the problem of cost overruns is
much larger than we think.
Different Cost Performance: Different Determinants? The Case of Cost Overruns in Dutch Transportation Infrastructure Projects
Date: 2015-01-24 00:00:00

This paper examines three independent explanatory variables and their
relation with cost overrun in order to decide whether this is different for
Dutch infrastructure projects compared to worldwide findings. The three
independent variables are project type (road, rail, and fixed link projects),
project size (measured in terms of estimated costs) and the length of the
project implementation phase. For Dutch projects, average cost overrun is 10.6%
for rail, 18.6% for roads and 21.7% for fixed links. For project size, small
Dutch projects have the largest average percentage cost overruns but in terms
of total overrun, large projects have a larger share. The length of the
implementation phase and especially the length of the pre-construction phase
are important determinants of cost overruns in the Netherlands. With each
additional year of pre-construction, percentage cost overrun increases by five
percentage points. In contrast, the length of the construction phase has hardly
any influence on cost overruns. This is an important contribution to current
knowledge about cost overruns, because the period in which projects are most
prone to cost overruns is narrowed down considerably, at least in the
Netherlands. This means that period can be focused on to determine the causes
and cures of overruns.
Re-imagining the Hardy-Weinberg Law
Date: 2015-12-16 00:00:00

Under random mating, a progeny's alleles are independently sampled from the
parental gene pools. Here is a new proof which avoids the usual algebraic
complexity, based on a restated Mendel's First Law. Another simplified proof
along the old approach led to the discovery that allelic independence can hold
under random mating and fertility selection. The theoretical existence and
number of such selection coefficients are established.
Relativistic Black-Scholes model
Date: 2018-02-11 00:00:00
Tasks: model

Black-Scholes equation, after a certain coordinate transformation, is
equivalent to the heat equation. On the other hand the relativistic extension
of the latter, the telegraphers equation, can be derived from the Euclidean
version of the Dirac equation. Therefore the relativistic extension of the
Black-Scholes model follows from relativistic quantum mechanics quite
naturally. We investigate this particular model for the case of European
vanilla options. Due to the notion of locality incorporated in this way one
finds that the volatility frown-like effect appears when comparing to the
original Black-Scholes model.
Detecting a trend change in cross-border epidemic transmission
Date: 2015-10-14 00:00:00
Tasks: Time Series, Time Series Analysis

A method for detecting a trend change in cross-border epidemic transmission
is developed for a standard epidemiological SIR compartment model and a
meta-population network model. The method is applicable to investigating the
efficacy of the implemented public health intervention in managing infectious
travelers across borders from a time series of the number of new cases reported
in multiple geographical regions. It is found that the change point of the
probability of travel movements was one week after the WHO worldwide alert on
the SARS outbreak in 2003. The alert was effective in managing infectious
travelers. On the other hand, it is found that the probability of travel
movements did not change at all for the flu pandemic in 2009. The pandemic did
not affect potential travelers despite the WHO alert.