pwc-archive/papers-with-abstracts huggingface dataset:
Corpus COFLA: A research corpus for the Computational study of Flamenco Music
Authors: Kroher Nadine, Díaz-Báñez José-Miguel, Mora Joaquin, Gómez Emilia
Date: 2015-10-14 00:00:00
Tasks: Diversity, Information Retrieval, Music Information Retrieval, Retrieval

Flamenco is a music tradition from Southern Spain which attracts a growing
community of enthusiasts around the world. Its unique melodic and rhythmic
elements, the typically spontaneous and improvised interpretation and its
diversity regarding styles make this still largely undocumented art form a
particularly interesting material for musicological studies. In prior works it
has already been demonstrated that research on computational analysis of
flamenco music, despite it being a relatively new field, can provide powerful
tools for the discovery and diffusion of this genre. In this paper we present
corpusCOFLA, a data framework for the development of such computational tools.
The proposed collection of audio recordings and meta-data serves as a pool for
creating annotated subsets which can be used in development and evaluation of
algorithms for specific music information retrieval tasks. First, we describe
the design criteria for the corpus creation and then provide various examples
of subsets drawn from the corpus. We showcase possible research applications in
the context of computational study of flamenco music and give perspectives
regarding further development of the corpus.
Automatic Transcription of Flamenco Singing from Polyphonic Music Recordings
Authors: Kroher Nadine, Gómez Emilia
Date: 2015-10-14 00:00:00
Tasks: Information Retrieval, Music Information Retrieval, Onset Detection, Retrieval

Automatic note-level transcription is considered one of the most challenging
tasks in music information retrieval. The specific case of flamenco singing
transcription poses a particular challenge due to its complex melodic
progressions, intonation inaccuracies, the use of a high degree of
ornamentation and the presence of guitar accompaniment. In this study, we
explore the limitations of existing state of the art transcription systems for
the case of flamenco singing and propose a specific solution for this genre: We
first extract the predominant melody and apply a novel contour filtering
process to eliminate segments of the pitch contour which originate from the
guitar accompaniment. We formulate a set of onset detection functions based on
volume and pitch characteristics to segment the resulting vocal pitch contour
into discrete note events. A quantised pitch label is assigned to each note
event by combining global pitch class probabilities with local pitch contour
statistics. The proposed system outperforms state of the art singing
transcription systems with respect to voicing accuracy, onset detection and
overall performance when evaluated on flamenco singing datasets.
Cloning and Preliminary Characterization of STY46 from Arabidopsis thaliana, a Candidate Protein Kinase Involved in the Plant Sugar Starvation Response
Date: 2015-10-20 00:00:00

To study how plants respond to conditions under which the carbohydrates
needed for growth and development are exhausted, this project focuses on
cloning and functional characterization of a cytosolic protein kinase, STY46
that may potentially be involved in the sugar starvation response (SSR).
Generating A. thaliana STY46 knockout (KO) and overexpression (OE) lines is the
main method in this project to determine the function of the protein. A SALK
line (SALK116340) was confirmed to contain a TDNA insert in the STY46 gene and
the aim was to prove that this reduced the expression of this gene. Highly
intact RNA was isolated and reverse transcription PCR performed to determine
the level of transcript of STY46 in STY46KO. However the results were
inconclusive. This may be due to not enough amount of RNA use for the cDNA
reverse transcription. To develop an overexpression line, STY46 was cloned from
wild type Arabidopsis genotype. Primers were designed to flank the open read
frame of the STY46. They also contained restriction enzyme recognition sites
and a myctag engineered at their 5' ends to facilitate subsequent synthesis of
a plant transformation construct. A cDNA fragment of the expected size was
successfully amplified by PCR.
Driven diffusion against electrostatic or effective energy barrier across Alpha-Hemolysin
Date: 2015-10-14 00:00:00

We analyze the translocation of a charged particle across an Alpha-Hemolysin
(aHL) pore in the framework of a driven diffusion over an extended energy
barrier generated by the electrical charges of the aHL. A one-dimensional
electrostatic potential is extracted from the full 3D solution of the Poisson's
equation. We characterize the particle transport under the action of a constant
forcing by studying the statistics of the translocation time. We derive an
analytical expression of translocation time average that compares well with the
results from Brownian dynamic simulations of driven particles over the
electrostatic potential. Moreover, we show that the translocation time
distributions can be perfectly described by a simple theory which replaces the
true barrier by an equivalent structureless square barrier. Remarkably our
approach maintains its accuracy also for low-applied voltage regimes where the
usual inverse-Gaussian approximation fails. Finally we discuss how the
comparison between the simulated time distributions and their theoretical
prediction results to be greatly simplified when using the notion of the
empirical Laplace transform technique.
Integral Control Feedback Circuit for the Reactivation of Malfunctioning p53 Pathway
Date: 2015-10-14 00:00:00

We developed a strategy to control p53 levels when the p53 concentration
falls below a desired threshold . Based on an established p53-MDM2 mathematical
model that also incorporates microRNA regulators (p53-MDM2-miRNA), we applied a
control action in closed-loop with respect to this model. In particular, we
employ various architectures of synthetic circuit with integral feedback
control, illustrating varying degree in adaptive response to step-wise
perturbation of p53.
An Entropy-Based Technique for Classifying Bacterial Chromosomes According to Synonymous Codon Usage
Date: 2015-10-14 00:00:00

We present a framework based on conditional entropy and the Dirichlet
distribution for classifying chromosomes based on the degree to which they use
synonymous codons uniformly or preferentially, that is, whether or not codons
that code for an amino acid appear with the same relative frequency. Applying
the approach to a large collection of annotated bacterial chromosomes reveals
three distinct groups of bacteria.
Methods for Characterizing the Epigenetic Attractors Landscape Associated with Boolean Gene Regulatory Networks
Date: 2015-10-14 00:00:00

Gene regulatory network (GRN) modeling is a well-established theoretical
framework for the study of cell-fate specification during developmental
processes. Recently, dynamical models of GRNs have been taken as a basis for
formalizing the metaphorical model of Waddington's epigenetic landscape,
providing a natural extension for the general protocol of GRN modeling. In this
contribution we present in a coherent framework a novel implementation of two
previously proposed general frameworks for modeling the Epigenetic Attractors
Landscape associated with boolean GRNs: the inter-attractor and inter-state
transition approaches. We implement novel algorithms for estimating
inter-attractor transition probabilities without necessarily depending on
intensive single-event simulations. We analyze the performance and sensibility
to parameter choices of the algorithms for estimating inter-attractor
transition probabilities using three real GRN models. Additionally, we present
a side-by-side analysis of downstream analysis tools such as the attractors'
temporal and global ordering in the EAL. Overall, we show how the methods
complement each other using a real case study: a cellular-level GRN model for
epithelial carcinogenesis. We expect the toolkit and comparative analyses put
forward here to be a valuable additional re- source for the systems biology
community interested in modeling cellular differentiation and reprogramming
both in normal and pathological developmental processes.
Modeling response time with power-law distributions
Date: 2015-10-14 00:00:00

Understanding the properties of response time distributions is a
long-standing problem in cognitive science. We provide a tutorial overview of
several contemporary models that assume power law scaling is a plausible
description of the skewed heavy tails that are typically expressed in response
time distributions. We discuss several properties and markers of these
distribution functions that have implications for cognitive and
neurophysiological organization supporting a given cognitive activity. We
illustrate how a power law assumption suggests that collecting larger samples,
and combining individual subjects' data into a single set for a
distribution-function analysis allows for a better comparison of a group of
interest to a control group. We demonstrate our techniques in contrasts of
response time measurements of children with and without dyslexia.
Random close packing in protein cores
Date: 2015-10-14 00:00:00

Shortly after the determination of the first protein x-ray crystal
structures, researchers analyzed their cores and reported packing fractions
$\phi \approx 0.75$, a value that is similar to close packing equal-sized
spheres. A limitation of these analyses was the use of `extended atom' models,
rather than the more physically accurate `explicit hydrogen' model. The
validity of using the explicit hydrogen model is proved by its ability to
predict the side chain dihedral angle distributions observed in proteins. We
employ the explicit hydrogen model to calculate the packing fraction of the
cores of over $200$ high resolution protein structures. We find that these
protein cores have $\phi \approx 0.55$, which is comparable to random
close-packing of non-spherical particles. This result provides a deeper
understanding of the physical basis of protein structure that will enable
predictions of the effects of amino acid mutations and design of new functional
proteins.
Extending the Black-Scholes Option Pricing Theory to Account for an Option Market Maker's Funding Costs
Date: 2015-10-15 00:00:00
Tasks: Position

An option market maker incurs funding costs when carrying and hedging
inventory. To hedge a net long delta inventory, for example, she pays a fee to
borrow stock from the securities lending market. Because of haircuts, she posts
additional cash margin to the lender which needs to be financed at her
unsecured debt rate. This paper incorporates funding asymmetry (borrowed cash
and invested cash earning different interest rates) and realistic stock
financing cost into the classic option pricing theory. It is shown that an
option position can be dynamically replicated and self financed in the presence
of these funding costs. Noting that the funding amounts and costs are different
for long and short positions, we extend Black-Scholes partial differential
equations (PDE) per position side. The PDE's nonlinear funding cost terms
create a free funding boundary and would result in the bid price for a long
position on an option lower than the ask price for a short position. An
iterative Crank-Nicholson finite difference method is developed to compute
European and American vanilla option prices. Numerical results show that
reasonable funding cost parameters can easily produce same magnitude of bid/ask
spread of less liquid, longer term options as observed in the market place.
Portfolio level pricing examples show the netting effect of hedges, which could
moderate impact of funding costs.
A unified framework for information integration based on information geometry
Date: 2015-10-15 00:00:00

We propose a unified theoretical framework for quantifying spatio-temporal
interactions in a stochastic dynamical system based on information geometry. In
the proposed framework, the degree of interactions is quantified by the
divergence between the actual probability distribution of the system and a
constrained probability distribution where the interactions of interest are
disconnected. This framework provides novel geometric interpretations of
various information theoretic measures of interactions, such as mutual
information, transfer entropy, and stochastic interaction in terms of how
interactions are disconnected. The framework therefore provides an intuitive
understanding of the relationships between the various quantities. By extending
the concept of transfer entropy, we propose a novel measure of integrated
information which measures causal interactions between parts of a system.
Integrated information quantifies the extent to which the whole is more than
the sum of the parts and can be potentially used as a biological measure of the
levels of consciousness.
Towards Cleaning-up Open Data Portals: A Metadata Reconciliation Approach
Authors: Tygel Alan, Auer Sören, Debattista Jeremy, Orlandi Fabrizio, Campos Maria Luiza Machado
Date: 2015-10-15 00:00:00
Tasks: TAG

This paper presents an approach for metadata reconciliation, curation and
linking for Open Governamental Data Portals (ODPs). ODPs have been lately the
standard solution for governments willing to put their public data available
for the society. Portal managers use several types of metadata to organize the
datasets, one of the most important ones being the tags. However, the tagging
process is subject to many problems, such as synonyms, ambiguity or
incoherence, among others. As our empiric analysis of ODPs shows, these issues
are currently prevalent in most ODPs and effectively hinders the reuse of Open
Data. In order to address these problems, we develop and implement an approach
for tag reconciliation in Open Data Portals, encompassing local actions related
to individual portals, and global actions for adding a semantic metadata layer
above individual portals. The local part aims to enhance the quality of tags in
a single portal, and the global part is meant to interlink ODPs by establishing
relations between tags.
Dynamics and Stability in Retail Competition
Date: 2016-03-17 00:00:00

Retail competition today can be described by three main features: i)
oligopolistic competition, ii) multi-store settings, and iii) the presence of
large economies of scale. In these markets, firms usually apply a centralized
decisions making process in order to take full advantage of economies of
scales, e.g. retail distribution centers. In this paper, we model and analyze
the stability and chaos of retail competition considering all these issues. In
particular, a dynamic multi-market Cournot-Nash equilibrium with global
economies and diseconomies of scale model is developed. We confirm the
non-intuitive hypothesis that retail multi-store competition is more unstable
that traditional small business that cover the same demand. The main sources of
stability are the scale parameter and the number of markets
Investigating the Selectivity of KcsA Channel by an Image Charge Solvation Method (ICSM) in Molecular Dynamics Simulations
Date: 2015-10-15 00:00:00

In this paper, we study the selectivity of the potassium channel KcsA by a
recently developed image-charge solvation method(ICSM) combined with molecular
dynamics simulations. The hybrid solvation model in the ICSM is able to
demonstrate atomistically the function of the selectivity filter of the KcsA
channel when potassium and sodium ions are considered and their distributions
inside the filter are simulated. Our study also shows that the reaction field
effect, explicitly accounted for through image charge approximation in the ICSM
model, is necessary in reproducing the correct selectivity property of the
potassium channels.
A comparison of heroin epidemic models
Date: 2015-10-15 00:00:00

The use of illicit drugs has been on the rise in United States. It is very
detrimental on society, as fatal overdose is the fourth leading cause of death
in the United States, which is about the same as motor vehicle crashes. Of all
illicit drugs, one drug that has an severe adverse effect on a community as a
whole is heroin. This paper will discuss two mathematical models- the White and
Comiskey model and a newly introduced model proposed by the author, describing
heroin use within a fixed community. We will show the existence of stable
equilibrium from both models, suggesting both a situation where heroin use is
eradicated and one where it remains an endemic.
Quantification of the effect of mutations using a global probability model of natural sequence variation
Date: 2015-10-15 00:00:00
Tasks: Diversity

Modern biomedicine is challenged to predict the effects of genetic variation.
Systematic functional assays of point mutants of proteins have provided
valuable empirical information, but vast regions of sequence space remain
unexplored. Fortunately, the mutation-selection process of natural evolution
has recorded rich information in the diversity of natural protein sequences.
Here, building on probabilistic models for correlated amino-acid substitutions
that have been successfully applied to determine the three-dimensional
structures of proteins, we present a statistical approach for quantifying the
contribution of residues and their interactions to protein function, using a
statistical energy, the evolutionary Hamiltonian. We find that these
probability models predict the experimental effects of mutations with
reasonable accuracy for a number of proteins, especially where the selective
pressure is similar to the evolutionary pressure on the protein, such as
antibiotics.
On Capturing the Spreading Dynamics over Trading Prices in the Market
Date: 2015-10-15 00:00:00

While market is a social field where information flows over the interacting
agents, there have been not so many methods to observe the spreading
information in the prices comprising the market. By incorporating the entropy
transfer in information theory in its relation to the Granger causality, the
paper proposes a tree of weighted directed graph of market to detect the
changes of price might affect other price changes. We compare the proposed
analysis with the similar tree representation built from the correlation
coefficients of stock prices in order to have insight of possibility in seeing
the collective behavior of the market in general.
A geometric method for model reduction of biochemical networks with polynomial rate functions
Date: 2015-10-23 00:00:00

Model reduction of biochemical networks relies on the knowledge of slow and
fast variables. We provide a geometric method, based on the Newton polytope, to
identify slow variables of a biochemical network with polynomial rate
functions. The gist of the method is the notion of tropical equilibration that
provides approximate descriptions of slow invariant manifolds. Compared to
extant numerical algorithms such as the intrinsic low dimensional manifold
method, our approach is symbolic and utilizes orders of magnitude instead of
precise values of the model parameters. Application of this method to a large
collection of biochemical network models supports the idea that the number of
dynamical variables in minimal models of cell physiology can be small, in spite
of the large number of molecular regulatory actors.
First passage times in homogeneous nucleation: dependence on the total number of particles
Date: 2015-10-15 00:00:00

Motivated by nucleation and molecular aggregation in physical, chemical and
biological settings, we present an extension to a thorough analysis of the
stochastic self-assembly of a fixed number of identical particles in a finite
volume. We study the statistic of times it requires for maximal clusters to be
completed, starting from a pure-monomeric particle configuration. For finite
volume, we extend previous analytical approaches to the case of arbitrary
size-dependent aggregation and fragmentation kinetic rates. For larger volume,
we develop a scaling framework to study the behavior of the first assembly time
as a function of the total quantity of particles.
  We find that the mean time to first completion of a maximum-sized cluster may
have surprisingly a very weak dependency on the total number of particles. We
highlight how the higher statistic (variance, distribution) of the first
passage time may still help to infer key parameters (such as the size of the
maximum cluster) from data. And last but not least, we present a framework to
quantify the formation of cluster of macroscopic size, whose formation is
(asymptotically) very unlikely and occurs as a large deviation phenomenon from
the mean-field limit. We argue that this framework is suitable to describe
phase transition phenomena, as inherent infrequent stochastic processes, in
contrast to classical nucleation theory.
Semantic vector space models predict neural responses to complex visual stimuli
Date: 2015-10-15 00:00:00

Encoding models have as their objective to predict neural responses to
naturalistic stimuli with the aim of elucidating how sensory information is
represented in the brain. This prediction is achieved by representing the
stimulus in terms of a suitable feature space and using this feature space to
linearly predict observed neural responses. Here, we investigate to what extent
semantic vector space models can be used to predict neural responses to complex
visual stimuli. We show that these models provide good predictions of neural
responses in downstream visual areas, improving significantly over a low-level
control model based on Gabor wavelet pyramids. The outlined approach provides a
new way to model and map high-level semantic representations across cortex.
Information theoretical study of cross-talk mediated signal transduction in MAPK pathways
Date: 2016-12-30 00:00:00
Tasks: Time Series, Time Series Analysis

Biochemical networks related to similar functional pathways are often
correlated due to cross-talk among the homologous proteins in the different
networks. Using a stochastic framework, we address the functional significance
of the cross-talk between two pathways. Our theoretical analysis on generic
MAPK pathways reveals cross-talk is responsible for developing coordinated
fluctuations between the pathways. The extent of correlation evaluated in terms
of the information theoretic measure provides directionality to net information
propagation. Stochastic time series and scattered plot suggest that the
cross-talk generates synchronization within a cell as well as in a cellular
population. Depending on the number of input and output, we identify signal
integration and signal bifurcation motif that arise due to inter-pathway
connectivity in the composite network. Analysis using partial information
decomposition quantifies the net synergy in the information propagation through
these branched pathways.
How to (Not) Estimate Gini Coefficients for Fat Tailed Variables
Date: 2015-10-16 00:00:00

Direct measurements of Gini coefficients by conventional arithmetic
calculations are a poor estimator, even if paradoxically, they include the
entire population, as because of super-additivity they cannot lend themselves
to comparisons between units of different size, and intertemporal analyses are
vitiated by the population changes. The Gini of aggregated units A and B will
be higher than those of A and B computed separately. This effect becomes more
acute with fatness of tails. When the sample size is smaller than entire
population, the error is extremely high. The conventional literature on Gini
coefficients cannot be trusted and comparing countries of different sizes makes
no sense; nor does it make sense to make claims of "changes in inequality"
based on conventional measures. We compare the standard methodologies to the
indirect methods via maximum likelihood estimation of tail exponent. We compare
to the tail method which is unbiased, with considerably lower error rate. We
also consider measurement errors of the tail exponent and suggest a simple but
efficient methodology to calculate Gini coefficients.