pwc-archive/papers-with-abstracts huggingface dataset:
Ecological invasion in competition-diffusion systems when the exotic species is either very strong or very weak
Date: 2018-01-30 00:00:00

Reaction-diffusion systems with a Lotka-Volterra-type reaction term, also
known as competition-diffusion systems, have been used to investigate the
dynamics of the competition among $m$ ecological species for a limited resource
necessary to their survival and growth. Notwithstanding their rather simple
mathematical structure, such systems may display quite interesting behaviours.
In particular, while for $m=2$ no coexistence of the two species is usually
possible, if $m \ge 3$ we may observe coexistence of all or a subset of the
species, sensitively depending on the parameter values. Such coexistence can
take the form of very complex spatio-temporal patterns and oscillations.
  Unfortunately, at the moment there are no known tools for a complete
analytical study of such systems for $m \ge 3$. This means that establishing
general criteria for the occurrence of coexistence appears to be very hard. In
this paper we will instead give some criteria for the non-coexistence of
species, motivated by the ecological problem of the invasion of an ecosystem by
an exotic species. We will show that when the environment is very favourable to
the invading species the invasion will always be successful and the native
species will be driven to extinction. On the other hand, if the environment is
not favourable enough, the invasion will always fail.
On the Secure and Reconfigurable Multi-Layer Network Design for Critical Information Dissemination in the Internet of Battlefield Things (IoBT)
Date: 2018-01-26 00:00:00
Tasks: Decision Making, Epidemiology, Management

The Internet of things (IoT) is revolutionizing the management and control of
automated systems leading to a paradigm shift in areas such as smart homes,
smart cities, health care, transportation, etc. The IoT technology is also
envisioned to play an important role in improving the effectiveness of military
operations in battlefields. The interconnection of combat equipment and other
battlefield resources for coordinated automated decisions is referred to as the
Internet of battlefield things (IoBT). IoBT networks are significantly
different from traditional IoT networks due to battlefield specific challenges
such as the absence of communication infrastructure, heterogeneity of devices,
and susceptibility to cyber-physical attacks. The combat efficiency and
coordinated decision-making in war scenarios depends highly on real-time data
collection, which in turn relies on the connectivity of the network and
information dissemination in the presence of adversaries. This work aims to
build the theoretical foundations of designing secure and reconfigurable IoBT
networks. Leveraging the theories of stochastic geometry and mathematical
epidemiology, we develop an integrated framework to quantify the information
dissemination among heterogeneous network devices. Consequently, a tractable
optimization problem is formulated that can assist commanders in cost
effectively planning the network and reconfiguring it according to the changing
mission requirements.
Chaos in Homeostatically Regulated Neural Systems
Date: 2018-01-30 00:00:00

Low-dimensional yet rich dynamics often emerge in the brain. Examples include
oscillations and chaotic dynamics during sleep, epilepsy, and voluntary
movement. However, a general mechanism for the emergence of low dimensional
dynamics remains elusive. Here, we consider Wilson-Cowan networks and
demonstrate through numerical and analytical work that a type of homeostatic
regulation of the network firing rates can paradoxically lead to a rich
dynamical repertoire. The dynamics include mixed-mode oscillations, mixed-mode
chaos, and chaotic synchronization. This is true for single recurrently coupled
node, pairs of reciprocally coupled nodes without self-coupling, and networks
coupled through experimentally determined weights derived from functional
magnetic resonance imaging data. In all cases, the stability of the homeostatic
set point is analytically determined or approximated. The dynamics at the
network level are directly determined by the behavior of a single node system
through synchronization in both oscillatory and non-oscillatory states. Our
results demonstrate that rich dynamics can be preserved under homeostatic
regulation or even be caused by homeostatic regulation.
Creative Exploration Using Topic Based Bisociative Networks
Authors: Ahmed Faez, Fuge Mark
Date: 2018-01-30 00:00:00
Tasks: Topic Models

Bisociative knowledge discovery is an approach that combines elements from
two or more "incompatible" domains to generate creative solutions and insight.
Inspired by Koestler's notion of bisociation, in this paper we propose a
computational framework for the discovery of new connections between domains to
promote creative discovery and inspiration in design. Specifically, we propose
using topic models on a large collection of unstructured text ideas from
multiple domains to discover creative sources of inspiration. We use these
topics to generate a Bisociative Information Network--- a graph that captures
conceptual similarity between ideas--- that helps designers find creative links
within that network. Using a dataset of thousands of ideas from OpenIDEO, an
online collaborative community, our results show usefulness of representing
conceptual bridges through collections of words (topics) in finding
cross-domain inspiration. We show that the discovered links between domains,
whether presented on their own or via ideas they inspired, are perceived to be
more novel and can also be used as creative stimuli for new idea generation.
How adaptive immunity constrains the composition and fate of large bacterial populations
Date: 2018-07-17 00:00:00

Features of the CRISPR-Cas system, in which bacteria integrate small segments
of phage genome (spacers) into their DNA to neutralize future attacks, suggest
that its effect is not limited to individual bacteria but may control the fate
and structure of whole populations. Emphasizing the population-level impact of
the CRISPR-Cas system, recent experiments show that some bacteria regulate
CRISPR-associated genes via the quorum sensing (QS) pathway. Here we present a
model that shows that from the highly stochastic dynamics of individual spacers
under QS control emerges a rank-abundance distribution of spacers that is
time-invariant, a surprising prediction that we test with dynamic
spacer-tracking data from literature. This distribution depends on the state of
the competing phage-bacteria population, which due to QS-based regulation may
coexist in multiple stable states that vary significantly in their
phage-to-bacterium ratio, a widely used ecological measure to characterize
microbial systems.
Multilayer flows in molecular networks identify biological modules in the human proteome
Date: 2018-01-30 00:00:00

A variety of complex systems exhibit different types of relationships
simultaneously that can be modeled by multiplex networks. A typical problem is
to determine the community structure of such systems that, in general, depend
on one or more parameters to be tuned. In this study we propose one measure,
grounded on information theory, to find the optimal value of the relax rate
characterizing Multiplex Infomap, the generalization of the Infomap algorithm
to the realm of multilayer networks. We evaluate our methodology on synthetic
networks, to show that the most representative community structure can be
reliably identified when the most appropriate relax rate is used. Capitalizing
on these results, we use this measure to identify the most reliable meso-scale
functional organization in the human protein-protein interaction multiplex
network and compare the observed clusters against a collection of independently
annotated gene sets from the Molecular Signatures Database (MSigDB). Our
analysis reveals that modules obtained with the optimal value of the relax rate
are biologically significant and, remarkably, with higher functional content
than the ones obtained from the aggregate representation of the human proteome.
Our framework allows us to characterize the meso-scale structure of those
multilayer systems whose layers are not explicitly interconnected each other --
as in the case of edge-colored models -- the ones describing most biological
networks, from proteomes to connectomes.
Public archives for biological image data
Date: 2018-01-30 00:00:00

Public data archives are the backbone of modern biological and biomedical
research. While archives for biological molecules and structures are
well-established, resources for imaging data do not yet cover the full range of
spatial and temporal scales or application domains used by the scientific
community. In the last few years, the technical barriers to building such
resources have been solved and the first examples of scientific outputs from
public image data resources, often through linkage to existing molecular
resources, have been published. Using the successes of existing biomolecular
resources as a guide, we present the rationale and principles for the
construction of image data archives and databases that will be the foundation
of the next revolution in biological and biomedical informatics and discovery.
FoodRepo: An Open Food Repository of Barcoded Food Products
Date: 2018-01-25 00:00:00
Tasks: Epidemiology, Nutrition

In the past decade, digital technologies have started to profoundly influence
healthcare systems. Digital self-tracking has facilitated more precise
epidemiological studies, and in the field of nutritional epidemiology, mobile
apps have the potential to alleviate a significant part of the journaling
burden by, for example, allowing users to record their food intake via a simple
scan of packaged products barcodes. Such studies thus rely on databases of
commercialized products, their barcodes, ingredients, and nutritional values,
which are not yet openly available with sufficient geographical and product
coverage. In this paper, we present FoodRepo (https://www.foodrepo.org), an
open food repository of barcoded food items, whose database is programmatically
accessible through an application programming interface (API). Furthermore, an
open source license gives the appropriate rights to anyone to share and reuse
FoodRepo data, including for commercial purposes. With currently more than
21,000 items available on the Swiss market, our database represents a solid
starting point for large-scale studies in the field of digital nutrition, with
the aim to lead to a better understanding of the intricate connections between
diets and health in general, and metabolic disorders in particular.
Generalizing Gillespie's direct method to enable network-free simulations
Date: 2018-01-30 00:00:00

Gillespie's direct method for stochastic simulation of chemical kinetics is a
staple of computational systems biology research. However, the algorithm
requires explicit enumeration of all reactions and all chemical species that
may arise in the system. In many cases, this is not feasible due to the
combinatorial explosion of reactions and species in biological networks.
Rule-based modeling frameworks provide a way to exactly represent networks
containing such combinatorial complexity, and generalizations of Gillespie's
direct method have been developed as simulation engines for rule-based modeling
languages. Here, we provide both a high-level description of the algorithms
underlying the simulation engines, termed network-free simulation algorithms,
and how they have been applied in systems biology research. We also define a
generic rule-based modeling framework and describe a number of technical
details required for adapting Gillespie's direct method for network-free
simulation. Finally, we briefly discuss potential avenues for advancing
network-free simulation and the role they continue to play in modeling
dynamical systems in biology.
Non-local tensor completion for multitemporal remotely sensed images inpainting
Date: 2018-01-30 00:00:00

Remotely sensed images may contain some missing areas because of poor weather
conditions and sensor failure. Information of those areas may play an important
role in the interpretation of multitemporal remotely sensed data. The paper
aims at reconstructing the missing information by a non-local low-rank tensor
completion method (NL-LRTC). First, nonlocal correlations in the spatial domain
are taken into account by searching and grouping similar image patches in a
large search window. Then low-rankness of the identified 4-order tensor groups
is promoted to consider their correlations in spatial, spectral, and temporal
domains, while reconstructing the underlying patterns. Experimental results on
simulated and real data demonstrate that the proposed method is effective both
qualitatively and quantitatively. In addition, the proposed method is
computationally efficient compared to other patch based methods such as the
recent proposed PM-MTGSR method.
Histological insight into the hepatic tissue of the Nile monitor (Varanus niloticus)
Date: 2018-01-31 00:00:00

The liver of reptiles is considered an important study model for the
interaction between environment and hepatic tissue. Little is known about the
histology of the liver of reptiles. The aim of the current study was to
elucidate the histological architecture of the liver of the Nile monitor
(Varanus niloticus). Liver fragments from the Nile monitor were collected in
the summer season and processed for the light and electron microscopy. The
liver of the Nile monitor was bi-lobed and the right lobe was found to be
larger than the left lobe. Histological examination revealed indistinct
lobulation of the liver, and the central vein, sinusoids and portal area were
haphazardly organized. The hepatic parenchyma consisted of hepatocytes arranged
in glandular-like alveoli or tubules separated by a network of twisted
capillary sinusoids. The hepatocytes were polyhedral in shape with vacuolated
cytoplasm and the nucleus was single rounded, eccentric, large and vesicular
with a distinct nucleolus. The hepatocytes contained numerous lipid droplets,
abundant glycogen granules and well-developed RER and mitochondria. The
hepatocytes appeared to secrete into the bile canaliculi through the
disintegration of their dark cytoplasm into the bile canaliculi. The space of
Disse separating between the hepatocytes and sinusoids contained many recesses.
The portal area contained branches of the portal vein, hepatic artery, bile
duct and lymphatic vessels embedded in a connective tissue. Some
non-parenchymal cells were described such as Kupffer cells, heterophils,
melano-macrophages, intercalated cells, myofibroblasts in addition to the
endothelium of the sinusoids. This is the first report about the histological
structure of the liver of the Egyptian Nile monitor. The result presented here
should be considered a baseline knowledge to compare with the pathological
affections of the liver in this species.
Landau-Ginzburg theory of cortex dynamics: Scale-free avalanches emerge at the edge of synchronization
Date: 2018-01-31 00:00:00

Understanding the origin, nature, and functional significance of complex
patterns of neural activity, as recorded by diverse electrophysiological and
neuroimaging techniques, is a central challenge in neuroscience. Such patterns
include collective oscillations emerging out of neural synchronization as well
as highly heterogeneous outbursts of activity interspersed by periods of
quiescence, called "neuronal avalanches." Much debate has been generated about
the possible scale invariance or criticality of such avalanches and its
relevance for brain function. Aimed at shedding light onto this, here we
analyze the large-scale collective properties of the cortex by using a
mesoscopic approach following the principle of parsimony of Landau-Ginzburg.
Our model is similar to that of Wilson-Cowan for neural dynamics but crucially,
includes stochasticity and space; synaptic plasticity and inhibition are
considered as possible regulatory mechanisms. Detailed analyses uncover a phase
diagram including down-state, synchronous, asynchronous, and up-state phases
and reveal that empirical findings for neuronal avalanches are consistently
reproduced by tuning our model to the edge of synchronization. This reveals
that the putative criticality of cortical dynamics does not correspond to a
quiescent-to-active phase transition as usually assumed in theoretical
approaches but to a synchronization phase transition, at which incipient
oscillations and scale-free avalanches coexist. Furthermore, our model also
accounts for up and down states as they occur (e.g., during deep sleep). This
approach constitutes a framework to rationalize the possible collective phases
and phase transitions of cortical networks in simple terms, thus helping to
shed light on basic aspects of brain functioning from a very broad perspective.
Identifying systemically important companies in the entire liability network of a small open economy
Date: 2018-01-31 00:00:00

To a large extent, the systemic importance of financial institutions is
related to the topology of financial liability networks. In this work we
reconstruct and analyze the - to our knowledge - largest financial network that
has been studied up to now. This financial liability network consists of 51,980
firms and 796 banks. It represents 80.2% of total liabilities towards banks by
firms and all interbank liabilities from the entire Austrian banking system. We
find that firms contribute to systemic risk in similar ways as banks do. In
particular, we identify several medium-sized banks and firms with total assets
below 1 bln. EUR that are systemically important in the entire financial
network. We show that the notion of systemically important financial
institutions (SIFIs) or global and domestic systemically important banks
(G-SIBs or D-SIBs) can be straightforwardly extended to firms. We find that
firms introduce slightly more systemic risk than banks. In Austria in 2008, the
total systemic risk of the interbank network amounts to only 29% of the total
systemic risk of the entire financial network, consisting of firms and banks.
Ambiguity in defaultable term structure models
Date: 2018-04-24 00:00:00

We introduce the concept of no-arbitrage in a credit risk market under
ambiguity considering an intensity-based framework. We assume the default
intensity is not exactly known but lies between an upper and lower bound. By
means of the Girsanov theorem, we start from the reference measure where the
intensity is equal to $1$ and construct the set of equivalent martingale
measures. From this viewpoint, the credit risky case turns out to be similar to
the case of drift uncertainty in the $G$-expectation framework. Finally, we
derive the interval of no-arbitrage prices for general bond prices in a
Markovian setting.
Systemic-risk-efficient asset allocation: Minimization of systemic risk as a network optimization problem
Date: 2018-03-12 00:00:00

Systemic risk arises as a multi-layer network phenomenon. Layers represent
direct financial exposures of various types, including interbank liabilities,
derivative- or foreign exchange exposures. Another network layer of systemic
risk emerges through common asset holdings of financial institutions. Strongly
overlapping portfolios lead to similar exposures that are caused by price
movements of the underlying financial assets. Based on the knowledge of
portfolio holdings of financial agents we quantify systemic risk of overlapping
portfolios. We present an optimization procedure, where we minimize the
systemic risk in a given financial market by optimally rearranging overlapping
portfolio networks, under the constraints that the expected returns and risks
of the individual portfolios are unchanged. We explicitly demonstrate the power
of the method on the overlapping portfolio network of sovereign exposure
between major European banks by using data from the European Banking Authority
stress test of 2016. We show that systemic-risk-efficient allocations are
accessible by the optimization. In the case of sovereign exposure, systemic
risk can be reduced by more than a factor of two, with- out any detrimental
effects for the individual banks. These results are confirmed by a simple
simulation of fire sales in the government bond market. In particular we show
that the contagion probability is reduced dramatically in the optimized
network.
Are `Water Smart Landscapes' Contagious? An epidemic approach on networks to study peer effects
Date: 2018-01-29 00:00:00

We test the existence of a neighborhood based peer effect around
participation in an incentive based conservation program called `Water Smart
Landscapes' (WSL) in the city of Las Vegas, Nevada. We use 15 years of
geo-coded daily records of WSL program applications and approvals compiled by
the Southern Nevada Water Authority and Clark County Tax Assessors rolls for
home characteristics. We use this data to test whether a spatially mediated
peer effect can be observed in WSL participation likelihood at the household
level. We show that epidemic spreading models provide more flexibility in
modeling assumptions, and also provide one mechanism for addressing problems
associated with correlated unobservables than hazards models which can also be
applied to address the same questions. We build networks of neighborhood based
peers for 16 randomly selected neighborhoods in Las Vegas and test for the
existence of a peer based influence on WSL participation by using a
Susceptible-Exposed-Infected-Recovered epidemic spreading model (SEIR), in
which a home can become infected via autoinfection or through contagion from
its infected neighbors. We show that this type of epidemic model can be
directly recast to an additive-multiplicative hazard model, but not to purely
multiplicative one. Using both inference and prediction approaches we find
evidence of peer effects in several Las Vegas neighborhoods.
How Can We Induce More Women to Competitions?
Date: 2018-01-27 00:00:00

Why women avoid participating in a competition and how can we encourage them
to participate in it? In this paper, we investigate how social image concerns
affect women's decision to compete. We first construct a theoretical model and
show that participating in a competition, even under affirmative action
policies favoring women, is costly for women under public observability since
it deviates from traditional female gender norms, resulting in women's low
appearance in competitive environments. We propose and theoretically show that
introducing prosocial incentives in the competitive environment is effective
and robust to public observability since (i) it induces women who are
intrinsically motivated by prosocial incentives to the competitive environment
and (ii) it makes participating in a competition not costly for women from
social image point of view. We conduct a laboratory experiment where we
randomly manipulate the public observability of decisions to compete and test
our theoretical predictions. The results of the experiment are fairly
consistent with our theoretical predictions. We suggest that when designing
policies to promote gender equality in competitive environments, using
prosocial incentives through company philanthropy or other social
responsibility policies, either as substitutes or as complements to traditional
affirmative action policies, could be promising.