pwc-archive/papers-with-abstracts huggingface dataset:
Random mappings designed for commercial search engines
Authors: Donaldson Roger, Gupta Arijit, Plan Yaniv, Reimer Thomas
Date: 2015-07-21 00:00:00
Tasks: Retrieval

We give a practical random mapping that takes any set of documents
represented as vectors in Euclidean space and then maps them to a sparse subset
of the Hamming cube while retaining ordering of inter-vector inner products.
Once represented in the sparse space, it is natural to index documents using
commercial text-based search engines which are specialized to take advantage of
this sparse and discrete structure for large-scale document retrieval. We give
a theoretical analysis of the mapping scheme, characterizing exact asymptotic
behavior and also giving non-asymptotic bounds which we verify through
numerical simulations. We balance the theoretical treatment with several
practical considerations; these allow substantial speed up of the method. We
further illustrate the use of this method on search over two real data sets: a
corpus of images represented by their color histograms, and a corpus of daily
stock market index values.
Chaotic Neuronal Oscillations in Spontaneous Cortical-Subcortical Networks
Date: 2015-07-21 00:00:00
Tasks: Time Series, Time Series Analysis

Oscillatory activities are widely observed in specific frequency bands of
recorded field potentials in different brain regions, and play critical roles
in processing neural information. Understanding the structure of these
oscillatory activities is essential for understanding the brain function. So
far many details remain elusive about their rhythmic structures and how these
oscillations are generated. We show that many oscillatory activities in
spontaneous cortical-subcortical networks, such as delta, spindle, gamma,
high-gamma and sharp wave ripple bands in different brain regions, are genuine
chaotic time series which can be reconstructed as chaotic attractors through
appropriately selected embedding delay and dimension. The reconstructed
attractors are approximated by a simple radial basis function enabling high
precision short-term prediction. Simultaneously recorded oscillatory activities
in multiple brain regions differ greatly in term of temporal phase and
amplitude but can be approximated by the same function. Our results suggest
that neural oscillations are produced by deterministic chaotic systems. The
occurrence of neural oscillation events is predetermined, and the brain
possibly knows when and where the information will be processed and transferred
in the future time as a result of the deterministic dynamic.
Sequence Heterogeneity Accelerates Protein Search for Targets on DNA
Date: 2015-07-21 00:00:00

The process of protein search for specific binding sites on DNA is
fundamentally important since it marks the beginning of all major biological
processes. We present a theoretical investigation that probes the role of DNA
sequence symmetry, heterogeneity and chemical composition in the protein search
dynamics. Using a discrete-state stochastic approach with a first-passage
events analysis, which takes into account the most relevant physical-chemical
processes, a full analytical description of the search dynamics is obtained. It
is found that, contrary to existing views, the protein search is generally
faster on DNA with more heterogeneous sequences. In addition, the search
dynamics might be affected by the chemical composition near the target site.
The physical origins of these phenomena are discussed. Our results suggest that
biological processes might be effectively regulated by modifying chemical
composition, symmetry and heterogeneity of a genome.
Risk Quantification in Stochastic Simulation under Input Uncertainty
Date: 2017-12-18 00:00:00

When simulating a complex stochastic system, the behavior of output response
depends on input parameters estimated from finite real-world data, and the
finiteness of data brings input uncertainty into the system. The quantification
of the impact of input uncertainty on output response has been extensively
studied. Most of the existing literature focuses on providing inferences on the
mean response at the true but unknown input parameter, including point
estimation and confidence interval construction. Risk quantification of mean
response under input uncertainty often plays an important role in system
evaluation and control, because it provides inferences on extreme scenarios of
mean response in all possible input models. To the best of our knowledge, it
has rarely been systematically studied in the literature. In this paper, first
we introduce risk measures of mean response under input uncertainty, and
propose a nested Monte Carlo simulation approach to estimate them. Then we
develop asymptotical properties such as consistency and asymptotic normality
for the proposed nested risk estimators. We further study the associated budget
allocation problem for efficient nested risk simulation, and finally use a
sharing economy example to illustrate the importance of accessing and
controlling risk due to input uncertainty.
Data-driven modelling of the inositol trisphosphate receptor (IPR) and its role in calcium induced calcium release (CICR)
Date: 2015-07-22 00:00:00

We give a review of the current state of the art of data-driven modelling of
the inositol trisphosphate receptor (IPR). After explaining that the IPR plays
a crucial role as a central regulator in calcium dynamics, several sources of
relevant experimental data are introduced. Single ion channels are best studied
by recording single-channel currents under different ligand concentrations via
the patch-clamp technique. The particular relevance of modal gating, the
spontaneous switching between different levels of channel activity that occur
even at constant ligand concentrations, is highlighted. In order to investigate
the interactions of IPRs, calcium release from small clusters of channels,
so-called calcium puffs, can be used. We then present the mathematical
framework common to all models based on single-channel data, aggregated
continuous-time Markov models, and give a short review of statistical
approaches for parameterising these models with experimental data. The process
of building a Markov model that integrates various sources of experimental data
is illustrated using two recent examples, the model by Ullah et al. and the
"Park-Drive" model by Siekmann et al., the only models that account for all
sources of data currently available. Finally, it is demonstrated that the
essential features of the Park-Drive model in different models of calcium
dynamics are preserved after reducing it to a two-state model that only
accounts for the switching between the inactive "park" and the active "drive"
mode. This highlights the fact that modal gating is the most important
mechanism of ligand regulation in the IPR. It also emphasises that data-driven
models of ion channels do not necessarily have to lead to detailed models but
can be constructed so that relevant data is selected to represent ion channels
at the appropriate level of complexity for a given application.
Sustainability of Transient Kinetic Regimes and Origins of Death
Date: 2016-01-12 00:00:00

It is generally recognized that a distinguishing feature of life is its
peculiar capability to avoid equilibration. The origin of this capability and
its evolution along the timeline of abiogenesis is not yet understood. We
propose to study an analog of this phenomenon that could emerge in
non-biological systems. To this end, we introduce the concept of sustainability
of transient kinetic regimes. This concept is illustrated via investigation of
cooperative effects in an extended system of compartmentalized chemical
oscillators under batch and semi-batch conditions. The computational study of a
model system shows robust enhancement of lifetimes of the decaying oscillations
which translates into the evolution of the survival function of the transient
non-equilibrium regime. This model does not rely on any form of replication.
Rather, it explores the role of a structured effective environment as a
contributor to the system-bath interactions that define non-equilibrium
regimes. We implicate the noise produced by the effective environment of a
compartmentalized oscillator as the cause of the lifetime extension.
Multi-scaling of wholesale electricity prices
Date: 2015-07-21 00:00:00
Tasks: Time Series, Time Series Analysis

We empirically analyze the most volatile component of the electricity price
time series from two North-American wholesale electricity markets. We show that
these time series exhibit fluctuations which are not described by a Brownian
Motion, as they show multi-scaling, high Hurst exponents and sharp price
movements. We use the generalized Hurst exponent (GHE, $H(q)$) to show that
although these time-series have strong cyclical components, the fluctuations
exhibit persistent behaviour, i.e., $H(q)>0.5$. We investigate the
effectiveness of the GHE as a predictive tool in a simple linear forecasting
model, and study the forecast error as a function of $H(q)$, with $q=1$ and
$q=2$. Our results suggest that the GHE can be used as prediction tool for
these time series when the Hurst exponent is dynamically evaluated on rolling
time windows of size $\approx 50 - 100$ hours. These results are also compared
to the case in which the cyclical components have been subtracted from the time
series, showing the importance of cyclicality in the prediction power of the
Hurst exponent.
Tip cell overtaking occurs as a side effect of sprouting in computational models of angiogenesis
Date: 2015-11-23 00:00:00
Tasks: Position

During angiogenesis, endothelial cells compete for the tip position during
angiogenesis: a phenomenon named tip cell overtaking. It is still unclear to
what extent tip cell overtaking is a side effect of sprouting or to what extent
a biological function. To address this question, we studied tip cell overtaking
in two existing cellular Potts models of angiogenic sprouting. In these models
angiogenic sprouting-like behavior emerges from a small set of plausible cell
behaviors and the endothelial cells spontaneously migrate forwards and
backwards within sprouts, suggesting that tip cell overtaking might occur as a
side effect of sprouting. In accordance with experimental observations, in our
simulations the cells' tendency to occupy the tip position can be regulated
when two cell lines with different levels of Vegfr2 expression are contributing
to sprouting (mosaic sprouting assay), where cell behavior is regulated by a
simple VEGF-Dll4-Notch signaling network. Our modeling results suggest that tip
cell overtaking occurs spontaneously due to the stochastic motion of cells
during sprouting. Thus, tip cell overtaking and sprouting dynamics may be
interdependent and should be studied and interpreted in combination.
VEGF-Dll4-Notch can regulate the ability of cells to occupy the tip cell
position, but only when cells in the simulation strongly differ in their levels
of Vegfr2. We propose that VEGF-Dll4-Notch signaling might not regulate which
cell ends up at the tip, but assures that the cell that randomly ends up at the
tip position acquires the tip cell phenotype.
The Tangent Search Engine: Improved Similarity Metrics and Scalability for Math Formula Search
Authors: Zanibbi Richard, Davila Kenny, Kane Andrew, Tompa Frank
Date: 2015-07-22 00:00:00
Tasks: Information Retrieval, Math, Retrieval

With the ever-increasing quantity and variety of data worldwide, the Web has
become a rich repository of mathematical formulae. This necessitates the
creation of robust and scalable systems for Mathematical Information Retrieval,
where users search for mathematical information using individual formulae
(query-by-expression) or a combination of keywords and formulae. Often, the
pages that best satisfy users' information needs contain expressions that only
approximately match the query formulae. For users trying to locate or re-find a
specific expression, browse for similar formulae, or who are mathematical
non-experts, the similarity of formulae depends more on the relative positions
of symbols than on deep mathematical semantics.
  We propose the Maximum Subtree Similarity (MSS) metric for
query-by-expression that produces intuitive rankings of formulae based on their
appearance, as represented by the types and relative positions of symbols.
Because it is too expensive to apply the metric against all formulae in large
collections, we first retrieve expressions using an inverted index over tuples
that encode relationships between pairs of symbols, ranking hits using the Dice
coefficient. The top-k formulae are then re-ranked using MSS. Our approach
obtains state-of-the-art performance on the NTCIR-11 Wikipedia formula
retrieval benchmark and is efficient in terms of both index space and overall
retrieval time. Retrieval systems for other graphical forms, including chemical
diagrams, flowcharts, figures, and tables, may also benefit from adopting our
approach.
Lamarckian inheritance following sensorimotor training and its neural basis in Drosophila
Date: 2015-07-22 00:00:00

Jean-Baptiste Lamarck was among first to suggest that certain acquired traits
may be heritable from parents to offspring. In this study, I examine whether
and what aspects of sensorimotor conditioning by parents prior to conception
may influence the behavior of subsequent generations in Drosophila. Using
genetic and anatomic techniques, I find that both first- and second-generation
offspring of parents who underwent prolonged olfactory training over multiple
days displayed a distinct response bias to the same specific trained odors. The
offspring displayed an enhanced anemotactic approach response to the trained
odors, however, and did not differentiate between orders based on whether
parental training was aversive or appetitive. Consequently, disruption of both
olfactory-receptor and dorsal-paired-medial neuron input into the mushroom
bodies abolished this change in offspring response, but disrupting synaptic
output from a/b neurons of the mushroom body themselves had little effect on
behavior even though they remained necessary for enacting newly trained
conditioned responses. These observations identify a unique transgenerational
dissociation between parentally-trained conditioned and unconditioned sensory
stimuli, and provide a putative neural basis for how sensorimotor experiences
in insects may bias the behavior of subsequent generations.
Bond rupture mechanism enables to explain in block asymmetry of elaxation, force-velocity curve and the path of energy dissipation in muscle
Date: 2015-07-22 00:00:00

Bond rupture mechanism enables to explain in block asymmetry of elaxation,
force-velocity curve and the path of energy dissipation in muscle
GMOL: An Interactive Tool for 3D Genome Structure Visualization
Date: 2015-07-23 00:00:00

It has been shown that genome spatial structures largely affect both genome
activity and DNA function. Knowing this, many researchers are currently
attempting to accurately model genome structures. Despite these increased
efforts there still exists a shortage of tools dedicated to visualizing the
genome. Creating a tool that can accurately visualize the genome can aid
researchers by highlighting structural relationships that may not be obvious
when examining the sequence information alone. Here we present a desktop
application, known as GMOL, designed to effectively visualize genome tertiary
structures at multiple scales so that researchers may better analyze their
genomic data. GMOL was developed based upon our multi-scale approach that
allows a user to zoom in and out between six separate levels within the genome.
These six scales are full genome, chromosome, loci, fiber, nucleosome, and
nucleotide. In order to store the data of the different scales, a new file
format, known as GSS, was created. With GMOL, a user can choose any unit at any
scale and scale it up or down to visualize its structure and retrieve
corresponding genome sequences from either Ensembl or a local database. Users
can also interactively manipulate and measure the whole genome structure and
extract static images and machine-readable data files in PDB format from the
multi-scale structure. By using GMOL researchers will be able to better
understand and analyze genome structure models and the impact their structural
relations have on genome activity and DNA function through GMOLs unique
features and functions, which includes the multi-scale method that can satisfy
the users requirement to not only visualize genome tertiary structure, but also
measure it.
A New Local Score Based Method Applied to Behavior-divergent Quail Lines Sequenced in Pools Precisely Detects Selection Signatures on Genes Related to Autism
Date: 2015-07-23 00:00:00

Detecting genomic footprints of selection is an important step in the
understanding of evolution. Accounting for linkage disequilibrium in genome
scans allows increasing the detection power, but haplotype-based methods
require individual genotypes and are not applicable on pool-sequenced samples.
We propose to take advantage of the local score approach to account for linkage
disequilibrium, accumulating (possibly small) signals from single markers over
a genomic segment, to clearly pinpoint a selection signal, avoiding windowing
methods. This method provided results similar to haplotype-based methods on two
benchmark data sets with individual genotypes. Results obtained for a divergent
selection experiment on behavior in quail, where two lines were sequenced in
pools, are precise and biologically coherent, while competing methods failed:
our approach led to the detection of signals involving genes known to act on
social responsiveness or autistic traits. This local score approach is general
and can be applied to other genome-wide analyzes such as GWAS or genome scans
for selection.
Novel and topical business news and their impact on stock market activities
Date: 2015-07-23 00:00:00
Tasks: Articles

We propose an indicator to measure the degree to which a particular news
article is novel, as well as an indicator to measure the degree to which a
particular news item attracts attention from investors. The novelty measure is
obtained by comparing the extent to which a particular news article is similar
to earlier news articles, and an article is regarded as novel if there was no
similar article before it. On the other hand, we say a news item receives a lot
of attention and thus is highly topical if it is simultaneously reported by
many news agencies and read by many investors who receive news from those
agencies. The topicality measure for a news item is obtained by counting the
number of news articles whose content is similar to an original news article
but which are delivered by other news agencies. To check the performance of the
indicators, we empirically examine how these indicators are correlated with
intraday financial market indicators such as the number of transactions and
price volatility. Specifically, we use a dataset consisting of over 90 million
business news articles reported in English and a dataset consisting of
minute-by-minute stock prices on the New York Stock Exchange and the NASDAQ
Stock Market from 2003 to 2014, and show that stock prices and transaction
volumes exhibited a significant response to a news article when it is novel and
topical.
Coherent motion of monolayer sheets under confinement and its pathological implications
Date: 2016-01-22 00:00:00

Coherent angular rotation of epithelial cells is thought to contribute to
many vital physiological processes including tissue morphogenesis and glandular
formation. However, factors regulating this motion, and the implications of
this motion if perturbed remain incompletely understood. In the current study,
we address these questions using a cell-center based model in which cells are
polarized, motile, and interact with the neighboring cells via harmonic forces.
We demonstrate that, a simple evolution rule in which the polarization of any
cell tends to orient with its velocity vector can induce coherent motion in
geometrically confined environments. In addition to recapitulating coherent
rotational motion observed in experiments, our results also show the presence
of radial movements and tissue behavior that can vary between solid-like and
fluid-like. We show that the pattern of coherent motion is dictated by the
combination of different physical parameters including number density, cell
motility, system size, bulk cell stiffness and stiffness of cell-cell
adhesions. We further observe that, perturbations in the form of cell division
can induce a reversal in the direction of motion when cell division occurs
synchronously. Moreover, when the confinement is removed, we see that the
existing coherent motion leads to cell scattering, with bulk cell stiffness and
stiffness of cell-cell contacts dictating the invasion pattern. In summary, our
study provides an in-depth understanding of the origin of coherent rotation in
confined tissues, and extracts useful insights into the influence of various
physical parameters on the pattern of such movements
Optimum Liquidation Problem Associated with the Poisson Cluster Process
Date: 2015-12-25 00:00:00

In this research, we develop a trading strategy for the discrete-time optimal
liquidation problem of large order trading with different market
microstructures in an illiquid market. In this framework, the flow of orders
can be viewed as a point process with stochastic intensity. We model the price
impact as a linear function of a self-exciting dynamic process. We formulate
the liquidation problem as a discrete-time Markov Decision Processes, where the
state process is a Piecewise Deterministic Markov Process (PDMP). The numerical
results indicate that an optimal trading strategy is dependent on
characteristics of the market microstructure. When no orders above certain
value come the optimal solution takes offers in the lower levels of the limit
order book in order to prevent not filling of orders and facing final inventory
costs.
LDAExplore: Visualizing Topic Models Generated Using Latent Dirichlet Allocation
Authors: Ganesan Ashwinkumar, Brantley Kiante, Pan Shimei, Chen Jian
Date: 2015-07-23 00:00:00
Tasks: Topic Models

We present LDAExplore, a tool to visualize topic distributions in a given
document corpus that are generated using Topic Modeling methods. Latent
Dirichlet Allocation (LDA) is one of the basic methods that is predominantly
used to generate topics. One of the problems with methods like LDA is that
users who apply them may not understand the topics that are generated. Also,
users may find it difficult to search correlated topics and correlated
documents. LDAExplore, tries to alleviate these problems by visualizing topic
and word distributions generated from the document corpus and allowing the user
to interact with them. The system is designed for users, who have minimal
knowledge of LDA or Topic Modelling methods. To evaluate our design, we run a
pilot study which uses the abstracts of 322 Information Visualization papers,
where every abstract is considered a document. The topics generated are then
explored by users. The results show that users are able to find correlated
documents and group them based on topics that are similar.