pwc-archive/papers-with-abstracts huggingface dataset:
Nested species interactions promote feasibility over stability during the assembly of a pollinator community
Date: 2016-01-20 00:00:00

The foundational concepts behind the persistence of ecological communities
have been based on two ecological properties: dynamical stability and
feasibility. The former is typically regarded as the capacity of a community to
return to an original equilibrium state after a perturbation in species
abundances, and is usually linked to the strength of interspecific
interactions. The latter is the capacity to sustain positive abundances on all
its constituent species, and is linked to both interspecific interactions and
species demographic characteristics. Over the last 40 years, theoretical
research in ecology has emphasized the search for conditions leading to the
dynamical stability of ecological communities, while the conditions leading to
feasibility have been overlooked. However, thus far, we have no evidence of
whether species interactions are more conditioned by the community's need to be
stable or feasible. Here, we introduce novel quantitative methods and use
empirical data to investigate the consequences of species interactions on the
dynamical stability and feasibility of mutualistic communities. First, we
demonstrate that the more nested the species interactions in a community are,
the lower the mutualistic strength that the community can tolerate without
losing dynamical stability. Second, we show that high feasibility in a
community can be reached either with high mutualistic strength or with highly
nested species interactions. Third, we find that during the assembly process of
a seasonal pollinator community located at The Zackenberg Research Station (NE
Greenland), a high feasibility is reached through the nested species
interactions established between newcomer and resident species. Our findings
imply that nested mutualistic communities promote feasibility over stability,
which may suggest that the former can be key for community persistence.
Bayesian inference of natural selection from allele frequency time series
Date: 2016-01-20 00:00:00
Tasks: Bayesian Inference, Time Series, Time Series Analysis

The advent of accessible ancient DNA technology now allows the direct
ascertainment of allele frequencies in ancestral populations, thereby enabling
the use of allele frequency time series to detect and estimate natural
selection. Such direct observations of allele frequency dynamics are expected
to be more powerful than inferences made using patterns of linked neutral
variation obtained from modern individuals. We develop a Bayesian method to
make use of allele frequency time series data and infer the parameters of
general diploid selection, along with allele age, in non-equilibrium
populations. We introduce a novel path augmentation approach, in which we use
Markov chain Monte Carlo to integrate over the space of allele frequency
trajectories consistent with the observed data. Using simulations, we show that
this approach has good power to estimate selection coefficients and allele age.
Moreover, when applying our approach to data on horse coat color, we find that
ignoring a relevant demographic history can significantly bias the results of
inference. Our approach is made available in a C++ software package.
An RBF-PSO Based Approach for Modeling Prostate Cancer
Date: 2015-12-12 00:00:00

Prostate cancer is one of the most common cancers in men. It is characterized
by a slow growth and it can be diagnosed in an early stage by observing the
Prostate Specific Antigen (PSA). However, a relapse after the primary therapy
could arise and different growth characteristics of the new tumor are observed.
In order to get a better understanding of the phenomenon, a mathematical model
involving several parameters is considered. To estimate the values of the
parameters identifying the disease risk level a novel approach, based on
combining Particle Swarm Optimization (PSO) with a meshfree interpolation
method, is proposed.
Detailed temporal structure of communication networks in groups of songbirds
Date: 2016-01-20 00:00:00

Animals in groups often exchange calls, in patterns whose temporal structure
may be influenced by contextual factors such as physical location and the
social network structure of the group. We introduce a model-based analysis for
temporal patterns of animal call timing, originally developed for networks of
firing neurons. This has advantages over cross-correlation analysis in that it
can correctly handle common-cause confounds and provides a generative model of
call patterns with explicit parameters for the influences between individuals.
It also has advantages over standard Markovian analysis in that it incorporates
detailed temporal interactions which affect timing as well as sequencing of
calls. Further, a fitted model can be used to generate novel synthetic call
sequences. We apply the method to calls recorded from groups of domesticated
zebra finch (Taenopyggia guttata) individuals. We find that the communication
network in these groups has stable structure that persists from one day to the
next, and that "kernels" reflecting the temporal range of influence have a
characteristic structure for a calling individual's effect on itself, its
partner, and on others in the group. We further find characteristic patterns of
influences by call type as well as by individual.
Redundancy in the information transmission in a two-step cascade
Date: 2016-05-13 00:00:00
Tasks: Vocal Bursts Valence Prediction

We present a stochastic framework to study signal transmission in a generic
two-step cascade $\text{S} \rightarrow \text{X} \rightarrow \text{Y}$. Starting
from a set of Langevin equations obeying Gaussian noise processes we calculate
the variance and covariance while considering both linear and nonlinear
production terms for different biochemical species of the cascade. These
quantities are then used to calculate the net synergy within the purview of
partial information decomposition. We show that redundancy in information
transmission is essentially an important consequence of Markovian property of
the two-step cascade motif. We also show that redundancy increases fidelity of
the signalling pathway.
The Critical Domain Size of Stochastic Population Models
Date: 2016-01-21 00:00:00

Identifying the critical domain size necessary for a population to persist is
an important question in ecology. Both demographic and environmental
stochasticity impact a population's ability to persist. Here we explore ways of
including this variability. We study populations which have traditionally been
modelled using a deterministic integrodifference equation (IDE) framework, with
distinct dispersal and sedentary stages. Individual based models (IBMs) are the
most intuitive stochastic analogues to IDEs but yield few analytic insights. We
explore two alternate approaches; one is a scaling up to the population level
using the Central Limit Theorem, and the other a variation on both
Galton-Watson branching processes and branching processes in random
environments. These branching process models closely approximate the IBM and
yield insight into the factors determining the critical domain size for a given
population subject to stochasticity.
Semantic Place Descriptors for Classification and Map Discovery
Authors: Sarda Siddharth, Eickhoff Carsten, Hofmann Thomas
Date: 2016-01-22 00:00:00
Tasks: Classification, Density Estimation, Form, General Classification

Urban environments develop complex, non-obvious structures that are often
hard to represent in the form of maps or guides. Finding the right place to go
often requires intimate familiarity with the location in question and cannot
easily be deduced by visitors. In this work, we exploit large-scale samples of
usage information, in the form of mobile phone traces and geo-tagged Twitter
messages in order to automatically explore and annotate city maps via kernel
density estimation. Our experiments are based on one year's worth of mobile
phone activity collected by Nokia's Mobile Data Challenge (MDC). We show that
usage information can be a strong predictor of semantic place categories,
allowing us to automatically annotate maps based on the behavior of the local
user base.
Rubbish DNA: The functionless fraction of the human genome
Date: 2016-01-22 00:00:00

Because genomes are products of natural processes rather than intelligent
design, all genomes contain functional and nonfunctional parts. The fraction of
the genome that has no biological function is called rubbish DNA. Rubbish DNA
consists of junk DNA, i.e., the fraction of the genome on which selection does
not operate, and garbage DNA, i.e., sequences that lower the fitness of the
organism, but exist in the genome because purifying selection is neither
omnipotent nor instantaneous. In this chapter, I (1) review the concepts of
genomic function and functionlessness from an evolutionary perspective, (2)
present a precise nomenclature of genomic function, (3) discuss the evidence
for the existence of vast quantities of junk DNA within the human genome, (4)
discuss the mutational mechanisms responsible for generating junk DNA, (5)
spell out the necessary evolutionary conditions for maintaining junk DNA, (6)
outline various methodologies for estimating the functional fraction within the
genome, and (7) present a recent estimate for the functional fraction of our
genome.
Analiza regenerarii padurii: perspective statistice si informatice
Date: 2016-01-21 00:00:00
Tasks: Management

The regeneration of forest resources is one of the main objectives of modern
forest management. The present book is based on my personal PhD thesis and aims
to identify detailed features of the regeneration process and the
characteristics of sapling interaction. The research involved evaluation of
regeneration structure, dimensional differentiation of saplings, spatial
pattern analysis - sapling aggregation and species association, and sapling
competition using distance-dependent methods. A new distance-dependent
dimensional differentiation index (IDIV) and a new geometrical criterion for
selecting neighbouring competitor saplings were created and applied.
Appropriate methods and techniques were identified for investigating
regeneration and computer technology was used intensively. Nine stand-alone
software programs were produced in order to achieve the objectives of the
thesis.
RiskRank: Measuring interconnected risk
Date: 2016-01-22 00:00:00

This paper proposes RiskRank as a joint measure of cyclical and
cross-sectional systemic risk. RiskRank is a general-purpose aggregation
operator that concurrently accounts for risk levels for individual entities and
their interconnectedness. The measure relies on the decomposition of systemic
risk into sub-components that are in turn assessed using a set of risk measures
and their relationships. For this purpose, motivated by the development of the
Choquet integral, we employ the RiskRank function to aggregate risk measures,
allowing for the integration of the interrelation of different factors in the
aggregation process. The use of RiskRank is illustrated through a real-world
case in a European setting, in which we show that it performs well in
out-of-sample analysis. In the example, we provide an estimation of systemic
risk from country-level risk and cross-border linkages.
On the Dynamics of Dengue Virus type 2 with Residence Times and Vertical Transmission
Date: 2016-01-23 00:00:00

A two-patch mathematical model of Dengue virus type 2 (DENV-2) that accounts
for vectors' vertical transmission and between patches human dispersal is
introduced. Dispersal is modeled via a Lagrangian approach. A host-patch
residence-times basic reproduction number is derived and conditions under which
the disease dies out or persists are established. Analytical and numerical
results highlight the role of hosts' dispersal in mitigating or exacerbating
disease dynamics. The framework is used to explore dengue dynamics using, as a
starting point, the 2002 outbreak in the state of Colima, Mexico.
Explicit moments of decision times for single- and double-threshold drift-diffusion processes
Date: 2016-01-24 00:00:00

We derive expressions for the first three moments of the decision time (DT)
distribution produced via first threshold crossings by sample paths of a
drift-diffusion equation. The "pure" and "extended" diffusion processes are
widely used to model two-alternative forced choice decisions, and, while simple
formulae for accuracy, mean DT and coefficient of variation are readily
available, third and higher moments and conditioned moments are not generally
available. We provide explicit formulae for these, describe their behaviors as
drift rates and starting points approach interesting limits, and, with the
support of numerical simulations, discuss how trial-to-trial variability of
drift rates, starting points, and non-decision times affect these behaviors in
the extended diffusion model. Both unconditioned moments and those conditioned
on correct and erroneous responses are treated. We argue that the results will
assist in exploring mechanisms of evidence accumulation and in fitting
parameters to experimental data.
Who Ordered This?: Exploiting Implicit User Tag Order Preferences for Personalized Image Tagging
Authors: Nwana Amandianeze O., Chen Tsuhan
Date: 2016-01-20 00:00:00
Tasks: TAG

What makes a person pick certain tags over others when tagging an image? Does
the order that a person presents tags for a given image follow an implicit bias
that is personal? Can these biases be used to improve existing automated image
tagging systems? We show that tag ordering, which has been largely overlooked
by the image tagging community, is an important cue in understanding user
tagging behavior and can be used to improve auto-tagging systems. Inspired by
the assumption that people order their tags, we propose a new way of measuring
tag preferences, and also propose a new personalized tagging objective function
that explicitly considers a user's preferred tag orderings. We also provide a
(partially) greedy algorithm that produces good solutions to our new objective
and under certain conditions produces an optimal solution. We validate our
method on a subset of Flickr images that spans 5000 users, over 5200 tags, and
over 90,000 images. Our experiments show that exploiting personalized tag
orders improves the average performance of state-of-art approaches both on
per-image and per-user bases.
Long Forward Probabilities, Recovery and the Term Structure of Bond Risk Premiums
Date: 2016-01-25 00:00:00

We show that the martingale component in the long-term factorization of the
stochastic discount factor due to Alvarez and Jermann (2005) and Hansen and
Scheinkman (2009) is highly volatile, produces a downward-sloping term
structure of bond Sharpe ratios, and implies that the long bond is far from
growth optimality. In contrast, the long forward probabilities forecast an
upward sloping term structure of bond Sharpe ratios that starts from zero for
short-term bonds and implies that the long bond is growth optimal. Thus,
transition independence and degeneracy of the martingale component are
implausible assumptions in the bond market.
FreeSASA: An open source C library for solvent accessible surface area calculations
Date: 2016-01-25 00:00:00

Calculating solvent accessible surface areas (SASA) is a run-of-the-mill
calculation in structural biology. Although there are many programs available
for this calculation, there are no free-standing, open-source tools designed
for easy tool-chain integration. FreeSASA is an open source C library for SASA
calculations that provides both command-line and Python interfaces in addition
to its C API. The library implements both Lee and Richards' and Shrake and
Rupley's approximations, and is highly configurable to allow the user to
control molecular parameters, accuracy and output granularity. It only depends
on standard C libraries and should therefore be easy to compile and install on
any platform. The source code is freely available from
http://freesasa.github.io/. The library is well-documented, stable and
efficient. The command-line interface can easily replace closed source legacy
programs, with comparable or better accuracy and speed, and with some added
functionality.
Stochasticity and the limits to confidence when estimating R_0 of Ebola and other emerging infectious diseases
Date: 2016-01-21 00:00:00

Dynamic models - often deterministic in nature - were used to estimate the
basic reproductive number, R_0, of the 2014-5 Ebola virus disease (EVD)
epidemic outbreak in West Africa. Estimates of R_0 were then used to project
the likelihood for large outbreak sizes, e.g., exceeding hundreds of thousands
of cases. Yet fitting deterministic models can lead to over-confidence in the
confidence intervals of the fitted R_0, and, in turn, the type and scope of
necessary interventions. In this manuscript we propose a hybrid
stochastic-deterministic method to estimate R_0 and associated confidence
intervals (CIs). The core idea is that stochastic realizations of an underlying
deterministic model can be used to evaluate the compatibility of candidate
values of R_0 with observed epidemic curves. The compatibility is based on
comparing the distribution of expected epidemic growth rates with the observed
epidemic growth rate given "process noise", i.e., arising due to stochastic
transmission, recovery and death events. By applying our method to reported EVD
case counts from Guinea, Liberia and Sierra Leone, we show that prior estimates
of R_0 based on deterministic fits appear to be more confident than analysis of
stochastic trajectories suggests should be possible. Moving forward, we
recommend including a hybrid stochastic-deterministic fitting procedure when
quantifying the full R_0 CI at the onset of an epidemic due to multiple sources
of noise.
BUbiNG: Massive Crawling for the Masses
Authors: Boldi Paolo, Marino Andrea, Santini Massimo, Vigna Sebastiano
Date: 2016-01-26 00:00:00

Although web crawlers have been around for twenty years by now, there is
virtually no freely available, opensource crawling software that guarantees
high throughput, overcomes the limits of single-machine systems and at the same
time scales linearly with the amount of resources available. This paper aims at
filling this gap, through the description of BUbiNG, our next-generation web
crawler built upon the authors' experience with UbiCrawler [Boldi et al. 2004]
and on the last ten years of research on the topic. BUbiNG is an opensource
Java fully distributed crawler; a single BUbiNG agent, using sizeable hardware,
can crawl several thousands pages per second respecting strict politeness
constraints, both host- and IP-based. Unlike existing open-source distributed
crawlers that rely on batch techniques (like MapReduce), BUbiNG job
distribution is based on modern high-speed protocols so to achieve very high
throughput.
Optimized green fluorescent protein fused to FoF1-ATP synthase for single-molecule FRET using a fast anti-Brownian electrokinetic trap
Date: 2016-01-26 00:00:00

Observation times of freely diffusing single molecules in solution are
limited by the photophysics of the attached fluorescence markers and by a small
observation volume in the femtolitre range that is required for a sufficient
signal-to-background ratio. To extend diffusion-limited observation times
through a confocal detection volume, A. E. Cohen and W. E. Moerner have
invented and built the ABELtrap - a microfluidic device to actively counteract
Brownian motion of single nanoparticles with an electrokinetic trap. Here we
present a version of an ABELtrap with a laser focus pattern generated by
electro-optical beam deflectors and controlled by a programmable FPGA chip.
This ABELtrap holds single fluorescent nanoparticles for more than 100 seconds,
increasing the observation time of fluorescent nanoparticles compared to free
diffusion by a factor of 10000. To monitor conformational changes of individual
membrane proteins in real time, we record sequential distance changes between
two specifically attached dyes using F\"orster resonance energy transfer
(smFRET). Fusing the a-subunit of the FoF1-ATP synthase with mNeonGreen results
in an improved signal-to-background ratio at lower laser excitation powers.
This increases our measured trap duration of proteoliposomes beyond 2 s.
Additionally, we observe different smFRET levels attributed to varying
distances between the FRET donor (mNeonGreen) and acceptor (Alexa568)
fluorophore attached at the a- and c-subunit of the FoF1-ATP synthase
respectively.
Competition between fast- and slow-diffusing species in non-homogeneous environments
Date: 2016-01-26 00:00:00

We study an individual-based model in which two spatially-distributed
species, characterized by different diffusivities, compete for resources. We
consider three different ecological settings. In the first, diffusing faster
has a cost in terms of reproduction rate. In the second case, resources are not
uniformly distributed in space. In the third case, the two species are
transported by a fluid flow. In all these cases, at varying the parameters, we
observe a transition from a regime in which diffusing faster confers an
effective selective advantage to one in which it constitutes a disadvantage. We
analytically estimate the magnitude of this advantage (or disadvantage) and
test it by measuring fixation probabilities in simulations of the
individual-based model. Our results provide a framework to quantify
evolutionary pressure for increased or decreased dispersal in a given
environment.
Towards a Theory for Bio - Cyber Physical Systems Modelling
Date: 2016-01-26 00:00:00

Currently, CyberPhysical Systems (CPS) represents a great challenge for
automatic control and smart systems engineering on both theoretical and
practical levels. Designing CPS requires approaches involving multidisciplinary
competences. However they are designed to be autonomous, the CPS present a part
of uncertainty, which requires interaction with human for engineering,
monitoring, controlling, performing operational maintenance, etc. This
human-CPS interaction led naturally to the human in-the-loop (HITL) concept.
Nevertheless, this HITL concept , which stems from a reductionist point of
view, exhibits limitations due to the different natures of the systems
involved. As opposed to this classical approach, we propose, in this paper, a
model of Bio-CPS (i.e. systems based on an integration of computational
elements within biological systems) grounded on theoretical biology, physics
and computer sciences and based on the key concept of human systems
integration.
Suppression of neuronal phase synchronisation in cat cerebral cortex
Date: 2016-01-26 00:00:00

We have studied effects of perturbations on the cat cerebral cortex.
According to the literature, this cortex structure can be described by a
clustered network. This way, we construct a clustered network with the same
number of areas as in the cat matrix, where each area is described as a
sub-network with small-world property. We focus on the suppression of neuronal
phase synchronisation considering different kinds of perturbations. Among the
various controlling interventions, we choose three methods: delayed feedback
control, external time-periodic driving, and activation of selected neurons. We
simulate these interventions to provide a procedure to suppress undesired and
pathological abnormal rhythms that can be associated with many forms of
synchronisation. In our simulations, we have verified that the efficiency of
synchronisation suppression by delayed feedback control is higher than external
time-periodic driving and activation of selected neurons for the cat cerebral
cortex with the same coupling strengths.