pwc-archive/papers-with-abstracts huggingface dataset:
Testing separability and independence of perceptual dimensions with general recognition theory: A tutorial and new R package (grtools)
Date: 2016-10-11 00:00:00
Tasks: Experimental Design

Determining whether perceptual properties are processed independently is an
important goal in perceptual science, and tools to test independence should be
widely available to experimental researchers. The best analytical tools to test
for perceptual independence are provided by General Recognition Theory (GRT), a
multidimensional extension of signal detection theory. Unfortunately, there is
currently a lack of software implementing GRT analyses that is ready-to-use by
experimental psychologists and neuroscientists with little training in
computational modeling. This paper presents grtools, an R package developed
with the explicit aim of providing experimentalists with the ability to perform
full GRT analyses using only a couple of command lines. We describe the
software and provide a practical tutorial on how to perform each of the
analyses available in grtools. We also provide advice to researchers on best
practices for experimental design and interpretation of results.
A Corrected Parsimony Criterion for Reconstructing Phylogenies
Date: 2016-10-11 00:00:00
Tasks: valid

In phylogenetic analysis, for non-molecular data, particularly morphology,
parsimony optimization is the most commonly employed approach. In the past and
present application of the parsimony principle, extra step numbers have been
added across different characters without proper justification. This practice,
however, has caused the impacts of characters to be inflated or deflated
without a valid reason. To resolve this methodological deficiency, here I
present a corrected parsimony criterion for reconstructing phylogenies. In
essence, character rather than step is the most fundamental unit. Accordingly,
the most parsimonious tree should maximize the sum or average of the
phylogenetic signals, quantified by retention index, contributed by each
character. Assigning proper weights to characters is a separate task that
requires information other than the intra-character step number changing range.
Epidemics of Liquidity Shortages in Interbank Markets
Date: 2018-05-16 00:00:00

Financial contagion from liquidity shocks has being recently ascribed as a
prominent driver of systemic risk in interbank lending markets. Building on
standard compartment models used in epidemics, in this work we develop an EDB
(Exposed-Distressed-Bankrupted) model for the dynamics of liquidity shocks
reverberation between banks, and validate it on electronic market for interbank
deposits data. We show that the interbank network was highly susceptible to
liquidity contagion at the beginning of the 2007/2008 global financial crisis,
and that the subsequent micro-prudential and liquidity hoarding policies
adopted by banks increased the network resilience to systemic risk---yet with
the undesired side effect of drying out liquidity from the market. We finally
show that the individual riskiness of a bank is better captured by its network
centrality than by its participation to the market, along with the currently
debated concept of "too interconnected to fail".
An Improved Filtering Algorithm for Big Read Datasets
Date: 2016-10-11 00:00:00

For single-cell or metagenomic sequencing projects, it is necessary to
sequence with a very high mean coverage in order to make sure that all parts of
the sample DNA get covered by the reads produced. This leads to huge datasets
with lots of redundant data. A filtering of this data prior to assembly is
advisable. Titus Brown et al. (2012) presented the algorithm Diginorm for this
purpose, which filters reads based on the abundance of their $k$-mers. We
present Bignorm, a faster and quality-conscious read filtering algorithm. An
important new feature is the use of phred quality scores together with a
detailed analysis of the $k$-mer counts to decide which reads to keep. With
recommended parameters, in terms of median we remove 97.15% of the reads while
keeping the mean phred score of the filtered dataset high. Using the SDAdes
assembler, we produce assemblies of high quality from these filtered datasets
in a fraction of the time needed for an assembly from the datasets filtered
with Diginorm. We conclude that read filtering is a practical method for
reducing read data and for speeding up the assembly process. Our Bignorm
algorithm allows assemblies of competitive quality in comparison to Diginorm,
while being much faster. Bignorm is available for download at
https://git.informatik.uni-kiel.de/axw/Bignorm.git
A Review of Mathematical Models for Muscular Dystrophy: A Systems Biology Approach
Date: 2016-10-28 00:00:00

Muscular dystrophy (MD) describes generalized progressive muscular weakness
due to the wasting of muscle fibers. The progression of the disease is affected
by known immunological and mechanical factors, and possibly other unknown
mechanisms. These dynamics have begun to be elucidated in the last two decades.
This article reviews mathematical models of MD that characterize molecular and
cellular components implicated in MD progression. A biological background for
these processes is also presented. Molecular effectors that contribute to MD
include mitochondrial bioenergetics and genetic factors; both drive cellular
metabolism, communication and signaling. These molecular events leave cells
vulnerable to mechanical stress which can activate an immunological cascade
that weakens cells and surrounding tissues. This review article lays the
foundation for a systems biology approach to study MD progression.
Dynamical Pattern Selection of Growing Cellular Mosaic in Fish Retina
Date: 2017-10-12 00:00:00

A Markovian lattice model for photoreceptor cells is introduced to describe
the growth of mosaic patterns on fish retina. The radial stripe pattern
observed in wild-type zebrafish is shown to be selected naturally during the
retina growth, against the geometrically equivalent, circular stripe pattern.
The mechanism of such dynamical pattern selection is clarified on the basis of
both numerical simulations and theoretical analyses, which find that the
successive emergence of local defects plays a critical role in the realization
of the wild-type pattern.
Dynamic patterns of overexploitation in fisheries
Date: 2016-10-26 00:00:00

Understanding overfishing phenomenon and regulating fishing quotas is a major
global challenge for the 21st Century both in terms of providing food for
humankind and to preserve the oceans ecosystems. However, fishing is a complex
economic activity, affected not just by overfishing but also by such factors as
pollution, technology, financial factors and more. For this reason, it is often
difficult to state with complete certainty that overfishing is the cause of the
decline of a fishery. In this study, we developed a simple dynamic model based
on the earlier, well-known Lotka-Volterra model or Prey-Predator model. To
describe exploitation patterns, we assume that the fish stock and the fishing
industry are coupled stock variables in the model and they dynamically affect
each other, with the fishing yield proportional to both the fishing capital and
the fish stock. The model is based on the concept that the fishing industry
acts as the predator of the resource and that its growth and subsequent decline
is directly related to the abundance of the fish stock. If the model can be fit
historical data relative to specific fisheries, then it is a strong indication
that the fishing industry is strongly affected by the magnitude of the fish
stock and that, in particular, the decline of the yield and the decline of the
stock are linked to each other. The model does not pretend to be a general
description of the fishing industry in all its varied forms; however, the data
reported here show that the model can indeed qualitatively describe several
historical case of the collapse of fisheries. The model can also be used as a
qualitative guide to understand the behavior of several other fisheries. These
result indicate that one of the main factors causing the present crisis of the
world's fisheries is the overexploitation of the fish stocks.
Diet variation in climbing perch populations inhabiting eight different types of ecosystems
Date: 2016-10-12 00:00:00

The present study revealed that populations of climbing perch (Anabas
testudineus) inhabiting river, backwater, shallow water channel, ponds with and
without vegetation cover, marsh, sewage canal and aquaculture tank varied
significantly in the number of food items consumed. Chironomous larvae, organic
debris and filamentous algae were the common ingredients of the menu of this
species across focal ecosystems, whereas sewage canal population was found
surviving solely on insect larvae and organic debris.
Fast, Accurate, Straightforward Extreme Quantiles of Compound Loss Distributions
Date: 2017-07-18 00:00:00

We present an easily implemented, fast, and accurate method for approximating
extreme quantiles of compound loss distributions (frequency+severity) as are
commonly used in insurance and operational risk capital models. The
Interpolated Single Loss Approximation (ISLA) of Opdyke (2014) is based on the
widely used Single Loss Approximation (SLA) of Degen (2010) and maintains two
important advantages over its competitors: first, ISLA correctly accounts for a
discontinuity in SLA that otherwise can systematically and notably bias the
quantile (capital) approximation under conditions of both finite and infinite
mean. Secondly, because it is based on a closed-form approximation, ISLA
maintains the notable speed advantages of SLA over other methods requiring
algorithmic looping (e.g. fast Fourier transform or Panjer recursion). Speed is
important when simulating many quantile (capital) estimates, as is so often
required in practice, and essential when simulations of simulations are needed
(e.g. some power studies). The modified ISLA (MISLA) presented herein increases
the range of application across the severity distributions most commonly used
in these settings, and it is tested against extensive Monte Carlo simulation
(one billion years' worth of losses) and the best competing method (the
perturbative expansion (PE2) of Hernandez et al., 2014) using twelve
heavy-tailed severity distributions, some of which are truncated. MISLA is
shown to be comparable to PE2 in terms of both speed and accuracy, and it is
arguably more straightforward to implement for the majority of Advanced
Measurement Approaches (AMA) banks that are already using SLA (and failing to
take into account its biasing discontinuity).
On Origins of Bubbles
Date: 2017-07-30 00:00:00

We discuss - in what is intended to be a pedagogical fashion - a criterion,
which is a lower bound on a certain ratio, for when a stock (or a similar
instrument) is not a good investment in the long term, which can happen even if
the expected return is positive. The root cause is that prices are positive and
have skewed, long-tailed distributions, which coupled with volatility results
in a long-run asymmetry. This relates to bubbles in stock prices, which we
discuss using a simple binomial tree model, without resorting to the stochastic
calculus machinery. We illustrate empirical properties of the aforesaid ratio.
Log of market cap and sectors appear to be relevant explanatory variables for
this ratio, while price-to-book ratio (or its log) is not. We also discuss a
short-term effect of volatility, to wit, the analog of Heisenberg's uncertainty
principle in finance and a simple derivation thereof using a binary tree.
MI-Sim: A MATLAB Package for the Numerical Analysis of Microbial Ecological Interactions
Date: 2016-10-12 00:00:00

Food-webs and other classes of ecological network motifs, are a means of
describing feeding relationships between consumers and producers in an
ecosystem. They have application across scales where they differ only in the
underlying characteristics of the organisms and substrates describing the
system. Mathematical modelling, using mechanistic approaches to describe the
dynamic behaviour and properties of the system through sets of ordinary
differential equations, has been used extensively in ecology. Models allow
simulation of the dynamics of the various motifs and their numerical analysis
provides a greater understanding of the interplay between the system components
and their intrinsic properties. We have developed the MI-Sim software for use
with MATLAB to allow a rigorous and rapid numerical analysis of several common
ecological motifs. MI-Sim contains a series of the most commonly used motifs
such as cooperation, competition and predation. It does not require detailed
knowledge of mathematical analytical techniques and is offered as a single
graphical user interface containing all input and output options. The tools
available in the current version of MI-Sim include model simulation, steady-
state existence and stability analysis, and basin of attraction analysis. The
software includes seven ecological interaction motifs and seven growth function
models. Unlike other system analysis tools, MI-Sim is designed as a simple and
user-friendly tool specific to ecological population type models, allowing for
rapid assessment of their dynamical and behavioural properties.
Linking structure and activity in nonlinear spiking networks
Date: 2020-02-25 00:00:00

Recent experimental advances are producing an avalanche of data on both
neural connectivity and neural activity. To take full advantage of these two
emerging datasets we need a framework that links them, revealing how collective
neural activity arises from the structure of neural connectivity and intrinsic
neural dynamics. This problem of {\it structure-driven activity} has drawn
major interest in computational neuroscience. Existing methods for relating
activity and architecture in spiking networks rely on linearizing activity
around a central operating point and thus fail to capture the nonlinear
responses of individual neurons that are the hallmark of neural information
processing. Here, we overcome this limitation and present a new relationship
between connectivity and activity in networks of nonlinear spiking neurons by
developing a diagrammatic fluctuation expansion based on statistical field
theory. We explicitly show how recurrent network structure produces pairwise
and higher-order correlated activity, and how nonlinearities impact the
networks' spiking activity. Our findings open new avenues to investigating how
single-neuron nonlinearities---including those of different cell
types---combine with connectivity to shape population activity and function.
Prediction of Influenza B Vaccine Effectiveness from Sequence Data
Date: 2016-10-13 00:00:00

Influenza is a contagious respiratory illness that causes significant human
morbidity and mortality, affecting 5-15% of the population in a typical
epidemic season. Human influenza epidemics are caused by types A and B, with
roughly 25% of human cases due to influenza B. Influenza B is a single-stranded
RNA virus with a high mutation rate, and both prior immune history and
vaccination put significant pressure on the virus to evolve. Due to the high
rate of viral evolution, the influenza B vaccine component of the annual
influenza vaccine is updated, roughly every other year in recent years. To
predict when an update to the vaccine is needed, an estimate of expected
vaccine effectiveness against a range of viral strains is required. We here
introduce a method to measure antigenic distance between the influenza B
vaccine and circulating viral strains. The measure correlates well with
effectiveness of the influenza B component of the annual vaccine in humans
between 1979 and 2014. We discuss how this measure of antigenic distance may be
used in the context of annual influenza vaccine design and prediction of
vaccine effectiveness.
Modeling sexual selection in T\'ungara frog and rationality of mate choice
Date: 2016-10-13 00:00:00

The males of the specie of frogs Engystomops pustulosus produce simple and
com- plex calls to lure females, as a way of Intersexual selection. Complex
calls lead males to a greater reproductive success than simple calls do.
However, the complex calls are also more attractive to the main predator of
these amphibians, the bat Trachops cirrhosus. Therefore, as M. Ryan suggests,
the complexity of the calls let the frogs keep a trade off between reproductive
success and predation. In this paper, we first propose to model the proportion
of simple to complex calls as a symmetric game of two strategies. We also
propose a model with three strategies (simple callers, complex callers and
quiet males), where we assess the effect of a male that keeps quiet and
intercepts females, which would play a role of Intrasexual selection. We
analyze the stable points of the replicator equations of the models that we
propose. Under the assumption that the decision of the males takes into account
this trade off between reproductive success and predation, our model reproduces
the observed behavior reported in the literature with minimal assumption on the
parameters. From the three strategies model, we verify that the quiet strategy
could only coexists with the simple and complex strategies as long as the rate
at which quiet males intercept females is high. We conclude that the
reproductive strategy of the male frog Engystomops pustulosus is rational.
Optimal Consumption and Investment with Fixed and Proportional Transaction Costs
Date: 2016-10-13 00:00:00

The classical optimal investment and consumption problem with infinite
horizon is studied in the presence of transaction costs. Both proportional and
fixed costs as well as general utility functions are considered. Weak dynamic
programming is proved in the general setting and a comparison result for
possibly discontinuous viscosity solutions of the dynamic programming equation
is provided. Detailed numerical experiments illustrate several properties of
the optimal investment strategies.
Geometric stability considerations of the ribosome flow model with pool
Date: 2016-10-13 00:00:00
Tasks: Translation

In order to better understand the process of gene translation, the ribosome
flow model (RFM) with pool was introduced recently. This model describes the
movement of several ribosomes along an mRNA template and simultaneously
captures the dynamics of the finite pool of ribosomes. Studying this system
with respect to the number and stability of its equilibria was so far based on
monotone systems theory (Margaliot and Tuller, 2012). We extend the results
obtained therein by using a geometric approach, showing that the equilibria of
the system constitute a normally hyperbolic invariant submanifold.
Subsequently, we analyze the Jacobi linearization of the system evaluated at
the equilibria in order to show that the equilibria are asymptotically stable
relative to certain affine subspaces. As this approach does not require any
monotonicity features of the system, it may also be applied for more complex
systems of the same kind such as bi-directional ribosome flows or time-varying
template numbers.
Emergency Identification and Analysis with EAIMS
Authors: McCreadie Richard, Macdonald Craig, Ounis Iadh
Date: 2016-10-13 00:00:00
Tasks: Management

Social media platforms are now a key source of information for a large
segment of the public. As such, these platforms have a great potential as a
means to provide real-time information to emergency management agencies.
Moreover, during an emergency, these agencies are very interested in social
media as a means to find public-driven response efforts, as well as to track
how their handling of that emergency is being perceived. However, there is
currently a lack advanced tools designed for monitoring social media during
emergencies. The Emergency Analysis Identification and Management System
(EAIMS) is a prototype service that aims to fill this technology gap by
providing richer analytic and exploration tools than current solutions. In
particular, EAIMS provides real-time detection of emergency events, related
information finding, information access and credibility analysis tools for use
over social media during emergencies.
A resource dependent protein synthesis model for evaluating synthetic circuits
Date: 2016-10-13 00:00:00

Reliable in-silico design of synthetic gene networks necessitates novel
approaches to model the process of protein synthesis under the influence of
limited resources. We present such a novel protein synthesis model which
originates from the Ribosome Flow Model and among other things describes the
movement of RNA-polymerase and Ribosomes on mRNA and DNA templates
respectively. By analyzing the convergence properties of this model based upon
geometric considerations we present additional insights into the dynamic
mechanisms of the process of protein synthesis. Further, we exemplarily show
how this model can be used to evaluate the performance of synthetic gene
circuits under different loading scenarios.
Is state-dependent valuation more adaptive than simpler rules?
Date: 2017-12-23 00:00:00

McNamara, Trimmer, and Houston (2012) claim to provide an explanation of
certain systematic deviations from rational behavior using a mechanism that
could arise through natural selection. We provide an arguably much simpler
mechanism in terms of computational limitations, that performs better in the
environment described by McNamara, Trimmer, and Houston (2012). To argue
convincingly that animals' use of state-dependent valuation is adaptive and is
likely to be selected for by natural selection, one must argue that, in some
sense, it is a better approach than the simple strategies that we propose.
Time value of extra information against its timely value
Date: 2016-10-13 00:00:00

We introduce an interactive market setup with sequential auctions where
agents receive variegated signals with a known deadline. The effects of
differential information and mutual learning on the allocation of overall
profit \& loss (P\&L) and the pace of price discovery are analysed. We
characterise the signal-based expected P\&L of agents based on explicit
formulae for the directional quality of the trading signal, and study the
optimal trading pattern using dynamic programming and provided that there is a
common anticipation by agents of gains from trade. We find evidence in favour
of exploiting new information whenever it arrives, and market efficiency. Brief
extensions of the problem to risk-adjusted gains as well as risk-averse agents
are provided. We then introduce the `information-adjusted risk premium' and
recover the signal-based equilibrium price as the weighted average of the
signal-based individual prices with respect to the risk-aversion levels.