pwc-archive/papers-with-abstracts huggingface dataset:
img2net: Automated network-based analysis of imaged phenotypes
Date: 2015-07-10 00:00:00

Automated analysis of imaged phenotypes enables fast and reproducible
quantification of biologically relevant features. Despite recent developments,
recordings of complex, networked structures, such as: leaf venation patterns,
cytoskeletal structures, or traffic networks, remain challenging to analyze.
Here we illustrate the applicability of img2net to automatedly analyze such
structures by reconstructing the underlying network, computing relevant network
properties, and statistically comparing networks of different types or under
different conditions. The software can be readily used for analyzing image data
of arbitrary 2D and 3D network-like structures. img2net is open-source software
under the GPL and can be downloaded from
http://mathbiol.mpimp-golm.mpg.de/img2net/, where supplementary information and
data sets for testing are provided.
Memetic evolution of art to distinct aesthetics
Date: 2015-07-11 00:00:00

Humans have been using symbolic representation (i.e. art) as a creative
cultural form indisputably for at least 80,000 years. A description of the
processes central to the evolution of art from sculpted earthen forms early in
human existence to paintings in museums of the modern world is absent in
scholarly literature. The present manuscript offers a memetic theory of art
evolution demonstrating typological transitions of art in the period post the
3-dimensional to 2-dimensional transition occurring in the early Aurignacian
period. The process of art evolution in the 2-dimensional form central to the
typological transitions post this period was propelled by material and/or
structure chosen to display the artistic message. Symbolic representational
tinkering whether collectively or individually creates artistic typologies of
display deemed aesthetic and non-aesthetic by the current cultural milieu.
Contemporary forms of graffiti underscore the aesthetic/nonaesthetic dichotomy.
Intransitivity in Theory and in the Real World
Date: 2015-07-11 00:00:00

This work considers reasons for and implications of discarding the assumption
of transitivity, which (transitivity) is the fundamental postulate in the
utility theory of Von Neumann and Morgenstern, the adiabatic accessibility
principle of Caratheodory and most other theories related to preferences or
competition. The examples of intransitivity are drawn from different fields,
such as law, biology, game theory, economics and competitive evolutionary
dynamic. This work is intended as a common platform that allows us to discuss
intransitivity in the context of different disciplines. The basic concepts and
terms that are needed for consistent treatment of intransitivity in various
applications are presented and analysed in a unified manner. The analysis
points out conditions that necessitate appearance of intransitivity, such as
multiplicity of preference criteria and imperfect (i.e. approximate)
discrimination of different cases. The present work observes that with
increasing presence and strength of intransitivity, thermodynamics gradually
fades away leaving space for more general kinetic considerations.
Intransitivity in competitive systems is linked to complex phenomena that would
be difficult or impossible to explain on the basis of transitive assumptions.
Human preferences that seem irrational from the perspective of the conventional
utility theory, become perfectly logical in the intransitive and relativistic
framework suggested here. The example of competitive simulations for the
risk/benefit dilemma demonstrates the significance of intransitivity in cyclic
behaviour and abrupt changes in the system. The evolutionary intransitivity
parameter, which is introduced in the Appendix, is a general measure of
intransitivity, which is particularly useful in evolving competitive systems.
Quantum preferences are also considered in the Appendix.
TOPO: Improving remote homologue recognition via identifying common protein structure framework
Date: 2015-07-12 00:00:00
Tasks: Prediction, Protein Structure Prediction

Protein structure prediction remains a challenge in the field of
computational biology. Traditional protein structure prediction approaches
include template-based modelling (say, homology modelling, and threading), and
ab initio. A threading algorithm takes a query protein sequence as input,
recognizes the most likely fold, and finally reports the alignments of the
query sequence to structure-known templates as output. The existing threading
approaches mainly utilizes the information of protein sequence profile, solvent
accessibility, contact probability, etc., and correctly recognize folds for
some proteins. However, the existing threading approaches show poorly
performance for remote homology proteins. How to improve the fold recognition
for remote homology proteins remains to be a difficult task for protein
structure prediction.
Contagion effects in the world network of economic activities
Date: 2015-07-12 00:00:00

Using the new data from the OECD-WTO world network of economic activities we
construct the Google matrix $G$ of this directed network and perform its
detailed analysis. The network contains 58 countries and 37 activity sectors
for years 1995, 2000, 2005, 2008, 2009. The construction of $G$, based on
Markov chain transitions, treats all countries on equal democratic grounds
while the contribution of activity sectors is proportional to their exchange
monetary volume. The Google matrix analysis allows to obtain reliable ranking
of countries and activity sectors and to determine the sensitivity of
CheiRank-PageRank commercial balance of countries in respect to price
variations and labor cost in various countries. We demonstrate that the
developed approach takes into account multiplicity of network links with
economy interactions between countries and activity sectors thus being more
efficient compared to the usual export-import analysis. Our results highlight
the striking increase of the influence of German economic activity on other
countries during the period 1995 to 2009 while the influence of Eurozone
decreases during the same period. We compare our results with the similar
analysis of the world trade network from the UN COMTRADE database. We argue
that the knowledge of network structure allows to analyze the effects of
economic influence and contagion propagation over the world economy.
Effect of Inter-Modular Connection on Fast Sparse Synchronization in Clustered Small-World Neural Networks
Date: 2015-09-22 00:00:00

We consider a clustered network with small-world sub-networks of inhibitory
fast spiking interneurons, and investigate the effect of inter-modular
connection on emergence of fast sparsely synchronized rhythms by varying both
the inter-modular coupling strength $J_{inter}$ and the average number of
inter-modular links per interneuron $M_{syn}^{(inter)}$. In contrast to the
case of non-clustered networks, two kinds of sparsely synchronized states such
as modular and global synchronization are found. For the case of modular sparse
synchronization, the population behavior reveals the modular structure, because
the intra-modular dynamics of sub-networks make some mismatching. On the other
hand, in the case of global sparse synchronization, the population behavior is
globally identical, independently of the cluster structure, because the
intra-modular dynamics of sub-networks make perfect matching. We introduce a
realistic cross-correlation modularity measure, representing the
matching-degree between the instantaneous sub-population spike rates of the
sub-networks, and examine whether the sparse synchronization is global or
modular. Furthermore, we characterize the modular and global sparse
synchronization by employing the realistic sub- and whole-population order
parameters and statistical-mechanical measures. The roles of $J_{inter}$ and
$M_{syn}^{(inter)}$ are thus found as follows. For large $J_{inter}$, due to
strong inhibition it plays a destructive role to "spoil" the pacing between
spikes, while for small $J_{inter}$ it plays a constructive role to "favor" the
pacing between spikes. In contrast, $M_{syn}^{(inter)}$ seems to play a role
just to favor the pacing between spikes. With increasing $M_{syn}^{(inter)}$,
the pacing degree between spikes increases monotonically thanks to the increase
in the degree of effectiveness of global communication between spikes.
Analysis of cyclical behavior in time series of stock market returns
Date: 2017-06-12 00:00:00
Tasks: Time Series, Time Series Analysis

In this paper we have analyzed scaling properties and cyclical behavior of
the three types of stock market indexes (SMI) time series: data belonging to
stock markets of developed economies, emerging economies, and of the
underdeveloped or transitional economies. We have used two techniques of data
analysis to obtain and verify our findings: the wavelet spectral analysis to
study SMI returns data, and the Hurst exponent formalism to study local
behavior around market cycles and trends. We have found cyclical behavior in
all SMI data sets that we have analyzed. Moreover, the positions and the
boundaries of cyclical intervals that we have found seam to be common for all
markets in our dataset. We list and illustrate the presence of nine such
periods in our SMI data. We also report on the possibilities to differentiate
between the level of growth of the analyzed markets by way of statistical
analysis of the properties of wavelet spectra that characterize particular peak
behaviors. Our results show that measures like the relative WT energy content
and the relative WT amplitude for the peaks in the small scales region could be
used for partial differentiation between market economies. Finally, we propose
a way to quantify the level of development of a stock market based on the Hurst
scaling exponent approach. From the local scaling exponents calculated for our
nine peak regions we have defined what we named the Development Index, which
proved, at least in the case of our dataset, to be suitable to rank the SMI
series that we have analyzed in three distinct groups.
The shape of the one-dimensional phylogenetic likelihood function
Date: 2016-07-21 00:00:00
Tasks: All

By fixing all parameters in a phylogenetic likelihood model except for one
branch length, one obtains a one-dimensional likelihood function. In this work,
we introduce a mathematical framework to characterize the shapes of such
one-dimensional phylogenetic likelihood functions. This framework is based on
analyses of algebraic structures on the space of all frequency patterns with
respect to a polynomial representation of the likelihood functions. Using this
framework, we provide conditions under which the one-dimensional phylogenetic
likelihood functions are guaranteed to have at most one stationary point, and
this point is the maximum likelihood branch length. These conditions are
satisfied by common simple models including all binary models, the Jukes-Cantor
model and the Felsenstein 1981 model.
  We then prove that for the simplest model that does not satisfy our
conditions, namely, the Kimura 2-parameter model, the one-dimensional
likelihood functions may have multiple stationary points. As a proof of
concept, we construct a non-degenerate example in which the phylogenetic
likelihood function has two local maxima and a local minimum. To construct such
examples, we derive a general method of constructing a tree and sequence data
with a specified frequency pattern at the root. We then extend the result to
prove that the space of all rescaled and translated one-dimensional
phylogenetic likelihood functions under the Kimura 2-parameter model is dense
in the space of all non-negative continuous functions on $[0, \infty)$ with
finite limits. These results indicate that one-dimensional likelihood functions
under advanced evolutionary models can be more complex than it is typically
assumed by phylogenetic inference algorithms; however, these complexities can
be effectively captured by the Kimura 2-parameter model.
S-index: Towards Better Metrics for Quantifying Research Impact
Authors: Shah Neil, Song Yang
Date: 2015-07-13 00:00:00

The ongoing growth in the volume of scientific literature available today
precludes researchers from efficiently discerning the relevant from irrelevant
content. Researchers are constantly interested in impactful papers, authors and
venues in their respective fields. Moreover, they are interested in the
so-called recent "rising stars" of these contexts which may lead to attractive
directions for future work, collaborations or impactful publication venues. In
this work, we address the problem of quantifying research impact in each of
these contexts, in order to better direct attention of researchers and
streamline the processes of comparison, ranking and evaluation of contribution.
Specifically, we begin by outlining intuitive underlying assumptions that
impact quantification methods should obey and evaluate when current
state-of-the-art methods fail to satisfy these properties. To this end, we
introduce the s-index metric which quantifies research impact through influence
propagation over a heterogeneous citation network. s-index is tailored from
these intuitive assumptions and offers a number of desirable qualities
including robustness, natural temporality and straightforward extensibility
from the paper impact to broader author and venue impact contexts. We evaluate
its effectiveness on the publicly available Microsoft Academic Search citation
graph with over 119 million papers and 1 billion citation edges with 103
million and 21 thousand associated authors and venues respectively.
Mechanosensitivity of the IInd kind: TGFb mechanism of cell sensing the substrate stiffness
Date: 2015-07-14 00:00:00

Cells can sense forces applied to them, but also the stiffness of their
environment. These are two different phenomena, and here we investigate the
mechanosensitivity of the IInd kind: how the cell can measure an elastic
modulus at a single point of adhesion -- and how the cell can receive and
interpret the chemical signal released from the sensor. Our model uses the
example of large latent complex of TGFb as a sensor. Stochastic theory gives
the rate of breaking of latent complex, which initiates the signaling feedback
loop after the active TGFb release and leads to a change of cell phenotype
driven by the smooth muscle actin. We investigate the dynamic and steady-state
behaviours of the model, comparing them with experiments. In particular, we
analyse the timescale of approach to the steady state, the stability of the
non-linear dynamical system, and how the steady-state concentrations of the key
markers vary depending on the elasticity of the substrate. We discover a
crossover region for values of substrate elasticity closely corresponding to
that of the fibroblast to myofibroblast transition. We suggest that the cell
could actively vary the parameters of its dynamic feedback loop to `choose' the
position of the transition region and the range of substrate elasticity that it
can detect. In this way, the theory offers the unifying mechanism for a variety
of phenomena, such as the myofibroblast conversion in fibrosis of wounds and
lungs and smooth muscle cell dysfunction in cardiac disease.
Pseudo-Query Reformulation
Authors: Diaz Fernando
Date: 2015-07-14 00:00:00
Tasks: Retrieval

Automatic query reformulation refers to rewriting a user's original query in
order to improve the ranking of retrieval results compared to the original
query. We present a general framework for automatic query reformulation based
on discrete optimization. Our approach, referred to as pseudo-query
reformulation, treats automatic query reformulation as a search problem over
the graph of unweighted queries linked by minimal transformations (e.g. term
additions, deletions). This framework allows us to test existing performance
prediction methods as heuristics for the graph search process. We demonstrate
the effectiveness of the approach on several publicly available datasets.
Recombinant transfer in the basic genome of E. coli
Date: 2015-07-14 00:00:00

An approximation to the ~4 Mbp basic genome shared by 32 strains of E. coli
representing six evolutionary groups has been derived and analyzed
computationally. A multiple-alignment of the 32 complete genome sequences was
filtered to remove mobile elements and identify the most reliable ~90% of the
aligned length of each of the resulting 496 basic-genome pairs. Patterns of
single-bp mutations (SNPs) in aligned pairs distinguish clonally inherited
regions from regions where either genome has acquired DNA fragments from
diverged genomes by homologous recombination since their last common ancestor.
Such recombinant transfer is pervasive across the basic genome, mostly between
genomes in the same evolutionary group, and generates many unique mosaic
patterns. The six least-diverged genome-pairs have one or two recombinant
transfers of length ~40-115 kbp (and few if any other transfers), each
containing one or more gene clusters known to confer strong selective advantage
in some environments. Moderately diverged genome-pairs (0.4-1% SNPs ) show
mosaic patterns of interspersed clonal and recombinant regions of varying
lengths throughout the basic genome, whereas more highly diverged pairs within
an evolutionary group or pairs between evolutionary groups having >1.3% SNPs
have few clonal matches longer than a few kbp. Many recombinant transfers
appear to incorporate fragments of the entering DNA produced by restriction
systems of the recipient cell. A simple computational model can closely fit the
data. Most recombinant transfers seem likely to be due to generalized
transduction by co-evolving populations of phages, which could efficiently
distribute variability throughout bacterial genomes.
Coexistence of two dengue virus serotypes and forecasting for Madeira island
Date: 2015-07-15 00:00:00
Tasks: Vocal Bursts Valence Prediction

The first outbreak of dengue occurred in Madeira Island on 2012, featuring
one virus serotype. Aedes aegypti was the vector of the disease and it is
unlikely that it will be eliminated from the island. Therefore, a new outbreak
of dengue fever can occur and, if it happens, risk to the population increases
if two serotypes coexist. In this paper, mathematical modeling and numerical
simulations are carried out to forecast what may happen in Madeira Island in
such scenario.
Spectral Detection on Sparse Hypergraphs
Authors: Angelini Maria Chiara, Caltagirone Francesco, Krzakala Florent, Zdeborová Lenka
Date: 2015-07-15 00:00:00

We consider the problem of the assignment of nodes into communities from a
set of hyperedges, where every hyperedge is a noisy observation of the
community assignment of the adjacent nodes. We focus in particular on the
sparse regime where the number of edges is of the same order as the number of
vertices. We propose a spectral method based on a generalization of the
non-backtracking Hashimoto matrix into hypergraphs. We analyze its performance
on a planted generative model and compare it with other spectral methods and
with Bayesian belief propagation (which was conjectured to be asymptotically
optimal for this model). We conclude that the proposed spectral method detects
communities whenever belief propagation does, while having the important
advantages to be simpler, entirely nonparametric, and to be able to learn the
rule according to which the hyperedges were generated without prior
information.
Taming the Basel Leverage Cycle
Date: 2015-07-15 00:00:00

Effective risk control must make a tradeoff between the microprudential risk
of exogenous shocks to individual institutions and the macroprudential risks
caused by their systemic interactions. We investigate a simple dynamical model
for understanding this tradeoff, consisting of a bank with a leverage target
and an unleveraged fundamental investor subject to exogenous noise with
clustered volatility. The parameter space has three regions: (i) a stable
region, where the system always reaches a fixed point equilibrium; (ii) a
locally unstable region, characterized by cycles and chaotic behavior; and
(iii) a globally unstable region. A crude calibration of parameters to data
puts the model in region (ii). In this region there is a slowly building price
bubble, resembling a "Great Moderation", followed by a crash, with a period of
approximately 10-15 years, which we dub the "Basel leverage cycle". We propose
a criterion for rating macroprudential policies based on their ability to
minimize risk for a given average leverage. We construct a one parameter family
of leverage policies that allows us to vary from the procyclical policies of
Basel II or III, in which leverage decreases when volatility increases, to
countercyclical policies in which leverage increases when volatility increases.
We find the best policy depends critically on three parameters: The average
leverage used by the bank; the relative size of the bank and the
fundamentalist, and the amplitude of the exogenous noise. Basel II is optimal
when the exogenous noise is high, the bank is small and leverage is low; in the
opposite limit where the bank is large or leverage is high the optimal policy
is closer to constant leverage. We also find that systemic risk can be
dramatically decreased by lowering the leverage target adjustment speed of the
banks.
Axiomatization of the Choquet integral for 2-dimensional heterogeneous product sets
Date: 2016-03-26 00:00:00
Tasks: Decision Making, Decision Making Under Uncertainty

We prove a representation theorem for the Choquet integral model. The
preference relation is defined on a two-dimensional heterogeneous product set
$X = X_1 \times X_2$ where elements of $X_1$ and $X_2$ are not necessarily
comparable with each other. However, making such comparisons in a meaningful
way is necessary for the construction of the Choquet integral (and any
rank-dependent model). We construct the representation, study its uniqueness
properties, and look at applications in multicriteria decision analysis,
state-dependent utility theory, and social choice. Previous axiomatizations of
this model, developed for decision making under uncertainty, relied heavily on
the notion of comonotocity and that of a "constant act". However, that requires
$X$ to have a special structure, namely, all factors of this set must be
identical. Our characterization does not assume commensurateness of criteria a
priori, so defining comonotonicity becomes impossible.
Sensory feedback in a bump attractor model of path integration
Date: 2015-07-15 00:00:00
Tasks: Position

The mammalian spatial navigation system makes use of several different
sensory information channels. This information is then converted into a neural
code that represents the animal's current position in space by engaging place
cell, grid cell, and head direction cell networks. In particular, sensory
landmark (allothetic) cues can be utilized in concert with an animal's
knowledge of its own velocity (idiothetic) cues to generate a more accurate
representation of position than (idiothetic) path integration provides on its
own (Battaglia et al, 2004). We develop a computational model that merges path
integration with information from external sensory cues that provide a reliable
representation of spatial position along an annular track. Starting with a
continuous bump attractor model, we allow for the possibility of synaptic
spatial heterogeneity that would break the translation symmetry of space. We
use asymptotic analysis to reduce the bump attractor model to a single scalar
equation whose potential represents the impact of heterogeneity. Such
heterogeneity causes errors to build up when the network performs path
integration, but these errors can be corrected by an external control signal
representing the effects of sensory cues. We demonstrate that there is an
optimal strength and decay rate of the control signal when cues are placed both
periodically and randomly. A similar analysis is performed when errors in path
integration arise from dynamic noise fluctuations. Again, there is an optimal
strength and decay of discrete control that minimizes the path integration
error.