pwc-archive/papers-with-abstracts huggingface dataset:
SEIRS epidemics in growing populations
Date: 2017-03-28 00:00:00

An SEIRS epidemic with disease fatalities is introduced in a growing
population (modelled as a super-critical linear birth and death process). The
study of the initial phase of the epidemic is stochastic, while the analysis of
the major outbreaks is deterministic. Depending on the values of the
parameters, the following scenarios are possible. i) The disease dies out
quickly, only infecting few; ii) the epidemic takes off, the \textit{number} of
infected individuals grows exponentially, but the \textit{fraction} of infected
individuals remains negligible; iii) the epidemic takes off, the
\textit{number} of infected grows initially quicker than the population, the
disease fatalities diminish the growth rate of the population, but it remains
super critical, and the \emph{fraction} of infected go to an endemic
equilibrium; iv) the epidemic takes off, the \textit{number} of infected
individuals grows initially quicker than the population, the diseases
fatalities turn the exponential growth of the population to an exponential
decay.
Control of a hair bundle's mechanosensory function by its mechanical load
Date: 2017-03-28 00:00:00

Hair cells, the sensory receptors of the internal ear, subserve different
functions in various receptor organs: they detect oscillatory stimuli in the
auditory system, but transduce constant and step stimuli in the vestibular and
lateral-line systems. We show that a hair cell's function can be controlled
experimentally by adjusting its mechanical load. By making bundles from a
single organ operate as any of four distinct types of signal detector, we
demonstrate that altering only a few key parameters can fundamentally change a
sensory cell's role. The motions of a single hair bundle can resemble those of
a bundle from the amphibian vestibular system, the reptilian auditory system,
or the mammalian auditory system, demonstrating an essential similarity of
bundles across species and receptor organs.
Categorizing User Sessions at Pinterest
Authors: Bandari Dorna, Xiang Shuo, Leskovec Jure
Date: 2017-10-25 00:00:00
Tasks: Clustering

Different users can use a given Internet application in many different ways.
The ability to record detailed event logs of user in-application activity
allows us to discover ways in which the application is being used. This enables
personalization and also leads to important insights with actionable business
and product outcomes.
  Here we study the problem of user session categorization, where the goal is
to automatically discover categories/classes of user in-session behavior using
event logs, and then consistently categorize each user session into the
discovered classes. We develop a three stage approach which uses clustering to
discover categories of sessions, then builds classifiers to classify new
sessions into the discovered categories, and finally performs daily
classification in a distributed pipeline. An important innovation of our
approach is selecting a set of events as long-tail features, and replacing them
with a new feature that is less sensitive to product experimentation and
logging changes. This allows for robust and stable identification of session
types even though the underlying application is constantly changing. We deploy
the approach to Pinterest and demonstrate its effectiveness. We discover
insights that have consequences for product monetization, growth, and design.
Our solution classifies millions of user sessions daily and leads to actionable
insights.
Biased Risk Parity with Fractal Model of Risk
Date: 2017-04-15 00:00:00
Tasks: model

For the past two decades investors have observed long memory and highly
correlated behavior of asset classes that does not fit into the framework of
Modern Portfolio Theory. Custom correlation and standard deviation estimators
consider normal distribution of returns and market efficiency hypothesis. It
forced investors to search more universal instruments of tail risk protection.
One of the possible solutions is a naive risk parity strategy, which avoids
estimation of expected returns and correlations. The authors develop the idea
further and propose a fractal distribution of returns as a core. This class of
distributions is more general as it does not imply strict limitations on risk
evolution. The proposed model allows for modifying a rule for volatility
estimation, thus, enhancing its explanatory power. It turns out that the latter
improves the performance metrics of an investment portfolio over the ten year
period. The fractal model of volatility plays a significant protective role
during the periods of market abnormal drawdowns. Consequently, it may be useful
for a wide range of asset managers which incorporate innovative risk models
into globally allocated portfolios.
Self-organized mechano-chemical dynamics in amoeboid locomotion of Physarum fragments
Date: 2017-03-28 00:00:00

The aim of this work is to quantify the spatio-temporal dynamics of
flow-driven amoeboid locomotion in small ($\sim$100 $\mu$m) fragments of the
true slime mold \phys {\it polycephalum}. In this model organism, cellular
contraction drives intracellular flows, and these flows transport the chemical
signals that regulate contraction in the first place. As a consequence of these
non-linear interactions, a diversity of migratory behaviors can be observed in
migrating \phys fragments. To study these dynamics, we measure the
spatio-temporal distributions of the velocities of the endoplasm and ectoplasm
of each migrating fragment, the traction stresses it generates on the
substratum, and the concentration of free intracellular calcium. Using these
unprecedented experimental data, we classify migrating \phys fragments
according to their dynamics, finding that they often exhibit spontaneously
coordinated waves of flow, contractility and chemical signaling. We show that
\phys fragments exhibiting symmetric spatio-temporal patterns of endoplasmic
flow migrate significantly slower than fragments with asymmetric patterns. In
addition, our joint measurements of ectoplasm velocity and traction stress at
the substratum suggest that forward motion of the ectoplasm is enabled by a
succession of stick-slip transitions, which we conjecture are also organized in
the form of waves. Combining our experiments with a simplified
convection-diffusion model, we show that the convective transport of calcium
ions may be key for establishing and maintaining the spatio-temporal patterns
of calcium concentration that regulate the generation of contractile forces.
Family-specific scaling laws in bacterial genomes
Date: 2017-03-28 00:00:00

Among several quantitative invariants found in evolutionary genomics, one of
the most striking is the scaling of the overall abundance of proteins, or
protein domains, sharing a specific functional annotation across genomes of
given size. The size of these functional categories change, on average, as
power-laws in the total number of protein-coding genes. Here, we show that such
regularities are not restricted to the overall behavior of high-level
functional categories, but also exist systematically at the level of single
evolutionary families of protein domains. Specifically, the number of proteins
within each family follows family-specific scaling laws with genome size.
Functionally similar sets of families tend to follow similar scaling laws, but
this is not always the case. To understand this systematically, we provide a
comprehensive classification of families based on their scaling properties.
Additionally, we develop a quantitative score for the heterogeneity of the
scaling of families belonging to a given category or predefined group. Under
the common reasonable assumption that selection is driven solely or mainly by
biological function, these findings point to fine-tuned and interdependent
functional roles of specific protein domains, beyond our current functional
annotations. This analysis provides a deeper view on the links between
evolutionary expansion of protein families and the functional constraints
shaping the gene repertoire of bacterial genomes.
Meraculous-2D: Haplotype-sensitive Assembly of Highly Heterozygous genomes
Date: 2017-03-29 00:00:00

While many short read assemblers attempt to simplify the de Brujin graph by
identifying and resolving variant-induced bubbles to produce a haploid mosaic
result, this approach is only viable when variants are relatively rare and the
bubbles are well defined in a graph context. We observed that diploid genomes
with very high levels of heterozygosity fail to display well-resolved bubble
structures in a typical assembly graph and thus result in highly fragmented and
incomplete assemblies. Here we present an enhancement of Meraculous2 algorithm,
called Meraculous-2D, which preserves haplotypes across variant sites and
generates accurate assembly of highly heterozygous diploid genomes. Preserving
and taking advantage of the allelic variation throughout the assembly process
allows reconstructing both haplomes at once, without the need to pick arbitrary
paths through bubble structures. We also enhanced the original diploidy
resolution method of Meraculous2 to maintain and report phased haplotype
variant information.
Angiogenesis regulators as a possible key to accelerated growth of secondary tumors following primary tumor resection
Date: 2017-03-29 00:00:00

Resection of primary tumors is often followed by accelerated growth of
metastases. Here we propose that this effect may be due to the fact that
resection of primary tumor results in a decrease in the total systemic amount
of angiogenesis stimulators, such as VEGF and bFGF. This in turn causes
decrease in the systemic level of angiogenesis inhibitors, such as PF-4 and
TSP-1, which at least temporarily relieves inhibition of secondary tumors,
allowing them to grow. This construct is predicated on the notion that systemic
level of angiogenesis inhibitors is regulated by the systemic level of
angiogenesis stimulators, as the host is trying to maintain the homeostatic
balance of stimulators to inhibitors in the body. We evaluate this hypothesis
using a conceptual mathematical model and show that indeed, this mechanism can
explain accelerated growth of secondary tumors following resection of a primary
tumor. We also show that there exists a tradeoff between time of surgery and
time to onset of metastatic growth. We conclude with a discussion of possible
therapeutic approaches that may counteract this effect and reduce metastatic
recurrences after surgery.
Biological timekeeping in the presence of stochasticity
Date: 2017-03-28 00:00:00
Tasks: Specificity

Causal ordering of key events in the cell cycle is essential for proper
functioning of an organism. Yet, it remains a mystery how a specific temporal
program of events is maintained despite ineluctable stochasticity in the
biochemical dynamics which dictate timing of cellular events. We propose that
if a change of cell fate is triggered by the {\em time-integral} of the
underlying stochastic biochemical signal, rather than the original signal, then
a dramatic improvement in temporal specificity results. Exact analytical
results for stochastic models of hourglass-timers and pendulum-clocks, two
important paradigms for biological timekeeping, elucidate how temporal
specificity is achieved through time-integration. En route, we introduce a
natural representation for time-integrals of stochastic processes, provide an
analytical prescription for evaluating corresponding first-passage-time
distributions, and uncover a mechanism by which a population of identical cells
can spontaneously bifurcate into subpopulations of early and late responders,
depending on hierarchy of timescales in the dynamics. Moreover, our approach
reveals how time-integration of stochastic signals may be realized
biochemically, through a simple chemical reaction scheme.
Is Climate Change Controversial? Modeling Controversy as Contention Within Populations
Authors: Dori-Hacohen Shiri, Jang Myungha, Allan James
Date: 2017-03-29 00:00:00

A growing body of research focuses on computationally detecting controversial
topics and understanding the stances people hold on them. Yet gaps remain in
our theoretical and practical understanding of how to define controversy, how
it manifests, and how to measure it. In this paper, we introduce a novel
measure we call "contention", defined with respect to a topic and a population.
We model contention from a mathematical standpoint. We validate our model by
examining a diverse set of sources: real-world polling data sets, actual voter
data, and Twitter coverage on several topics. In our publicly-released Twitter
data set of nearly 100M tweets, we examine several topics such as Brexit, the
2016 U.S. Elections, and "The Dress", and cross-reference them with other
sources. We demonstrate that the contention measure holds explanatory power for
a wide variety of observed phenomena, such as controversies over climate change
and other topics that are well within scientific consensus. Finally, we
re-examine the notion of controversy, and present a theoretical framework that
defines it in terms of population. We present preliminary evidence suggesting
that contention is one dimension of controversy, along with others, such as
"importance". Our new contention measure, along with the hypothesized model of
controversy, suggest several avenues for future work in this emerging
interdisciplinary research area.
Molecular dynamics simulations and in vitro analysis of the CRMP2 thiol switch
Date: 2017-03-29 00:00:00

Collapsin response mediator protein CRMP2 (gene: DPYSL2) is crucial for
neuronal development. The homotetrameric CRMP2 complex is regulated via two
mechanisms, first by phosphorylation at, and second by reduction and oxidation
of the Cys504 residues of two adjacent subunits. Here, we analyzed the effects
of this redox switch on the protein in vitro combined with force field
molecular dynamics (MD). Earlier X-ray data contain the structure of the rigid
body of the molecule but lack the flexible C-terminus with the important sites
for phosphorylation and redox regulation. An in silico model for this part was
established by replica exchange simulations and homology modelling, which is
consistent with results gained from CD spectroscopy with recombinant protein.
Thermofluor data indicated that the protein aggregates at bivalent ion
concentrations below 200 mM. In simulations the protein surface was covered at
these conditions by large amounts of ions, which most likely prevent
aggregation. A tryptophan residue (Trp295) in close proximity to the forming
disulfide allowed the measurement of the structural relaxation of the rigid
body upon reduction by fluorescent quenching. We were also able to determine
the second order rate constant of CRMP2 oxidation by H2O2. The simulated
solvent accessible surface of the hydroxyl group of Ser518 significantly
increased upon reduction of the disulfide bond. Our results give first detailed
insight in the profound structural changes of the tetrameric CRMP2 due to
oxidation and indicate a tightly connected regulation by phosphorylation and
redox modification.
A $4,000 Workstation for Mammalian Genome Assembly with Long Reads
Date: 2017-03-20 00:00:00

Long-read sequencing has enabled the de novo assembly of several mammalian
genomes, but with high cost in computing. Here, we demonstrated de novo
assembly of mammalian genome using long reads in an efficient and inexpensive
workstation.
How much is Wikipedia Lagging Behind News?
Authors: Fetahu Besnik, Anand Abhijit, Anand Avishek
Date: 2017-03-30 00:00:00
Tasks: Articles

Wikipedia, rich in entities and events, is an invaluable resource for various
knowledge harvesting, extraction and mining tasks. Numerous resources like
DBpedia, YAGO and other knowledge bases are based on extracting entity and
event based knowledge from it. Online news, on the other hand, is an
authoritative and rich source for emerging entities, events and facts relating
to existing entities. In this work, we study the creation of entities in
Wikipedia with respect to news by studying how entity and event based
information flows from news to Wikipedia.
  We analyze the lag of Wikipedia (based on the revision history of the English
Wikipedia) with 20 years of \emph{The New York Times} dataset (NYT). We model
and analyze the lag of entities and events, namely their first appearance in
Wikipedia and in NYT, respectively. In our extensive experimental analysis, we
find that almost 20\% of the external references in entity pages are news
articles encoding the importance of news to Wikipedia. Second, we observe that
the entity-based lag follows a normal distribution with a high standard
deviation, whereas the lag for news-based events is typically very low.
Finally, we find that events are responsible for creation of emergent entities
with as many as 12\% of the entities mentioned in the event page are created
after the creation of the event page.
Improving Entity Retrieval on Structured Data
Authors: Fetahu Besnik, Gadiraju Ujwal, Dietze Stefan
Date: 2017-03-30 00:00:00
Tasks: Clustering, Entity Retrieval, Retrieval

The increasing amount of data on the Web, in particular of Linked Data, has
led to a diverse landscape of datasets, which make entity retrieval a
challenging task. Explicit cross-dataset links, for instance to indicate
co-references or related entities can significantly improve entity retrieval.
However, only a small fraction of entities are interlinked through explicit
statements. In this paper, we propose a two-fold entity retrieval approach. In
a first, offline preprocessing step, we cluster entities based on the
\emph{x--means} and \emph{spectral} clustering algorithms. In the second step,
we propose an optimized retrieval model which takes advantage of our
precomputed clusters. For a given set of entities retrieved by the BM25F
retrieval approach and a given user query, we further expand the result set
with relevant entities by considering features of the queries, entities and the
precomputed clusters. Finally, we re-rank the expanded result set with respect
to the relevance to the query. We perform a thorough experimental evaluation on
the Billions Triple Challenge (BTC12) dataset. The proposed approach shows
significant improvements compared to the baseline and state of the art
approaches.
Walking behavior in a circular arena modified by pulsed light stimulation in Drosophila melanogaster w1118 line
Date: 2017-11-18 00:00:00

The Drosophila melanogaster white-eyed w1118 line serves as a blank control,
allowing genetic recombination of any gene of interest along with a readily
recognizable marker. w1118 flies display behavioral susceptibility to
environmental stimulation such as light. It is of great importance to
characterize the behavioral performance of w1118 flies because this would
provide a baseline from which the effect of the gene of interest could be
differentiated. Little work has been performed to characterize the walking
behavior in adult w1118 flies. Here we show that pulsed light stimulation
increased the regularity of walking trajectories of w1118 flies in circular
arenas. We statistically modeled the distribution of distances to center and
extracted the walking structures of w1118 flies. Pulsed light stimulation
redistributed the time proportions for individual walking structures.
Specifically, pulsed light stimulation reduced the episodes of crossing over
the central region of the arena. An addition of four genomic copies of
mini-white, a common marker gene for eye color, mimicked the effect of pulsed
light stimulation in reducing crossing in a circular arena. The reducing effect
of mini-white was copy-number-dependent. These findings highlight the rhythmic
light stimulation-evoked modifications of walking behavior in w1118 flies and
an unexpected behavioral consequence of mini-white in transgenic flies carrying
w1118 isogenic background.
DNA Tweezers Based on Semantics of DNA Strand Graph
Date: 2017-03-29 00:00:00
Tasks: Form

Because of the limitations of classical silicon based computational
technology, several alternatives to traditional method in form of
unconventional computing have been proposed. In this paper we will focus on DNA
computing which is showing the possibility of excellence for its massive
parallelism, potential for information storage, speed and energy efficiency. In
this paper we will describe how syllogistic reasoning by DNA tweezers can be
presented by the semantics of process calculus and DNA strand graph. Syllogism
is an essential ingredient for commonsense reasoning of an individual. This
paper enlightens the procedure to deduce a precise conclusion from a set of
propositions by using formal language theory in form of process calculus and
the expressive power of DNA strand graph.
Comparative genomic analysis of the human gut microbiome reveals a broad distribution of metabolic pathways for the degradation of host-synthetized mucin glycans
Date: 2017-03-30 00:00:00

The colonic mucus layer is a dynamic and complex structure formed by secreted
and transmembrane mucins, which are high-molecular-weight and heavily
glycosylated proteins. Colonic mucus consists of a loose outer layer and a
dense epithelium-attached layer. The outer layer is inhabited by various
representatives of the human gut microbiota (HGM). Glycans of the colonic mucus
can be used by the HGM as a source of carbon and energy when dietary fibers are
not sufficiently available. Here, we analyzed 397 individual HGM genomes to
identify pathways for the cleavage of host-synthetized mucin glycans to
monosaccharides as well as for the catabolism of the derived monosaccharides.
Our key results are as follows: (i) Genes for the cleavage of mucin glycans
were found in 86% of the analyzed genomes, whereas genes for the catabolism of
derived monosaccharides were found in 89% of the analyzed genomes. (ii)
Comparative genomic analysis identified four alternative forms of the
monosaccharide-catabolizing enzymes and four alternative forms of
monosaccharide transporters. (iii) Eighty-five percent of the analyzed genomes
may be involved in exchange pathways for the monosaccharides derived from
cleaved mucin glycans. (iv) The analyzed genomes demonstrated different
abilities to degrade known mucin glycans. Generally, the ability to degrade at
least one type of mucin glycan was predicted for 81% of the analyzed genomes.
(v) Eighty-two percent of the analyzed genomes can form mutualistic pairs that
are able to degrade mucin glycans and are not degradable by any of the paired
organisms alone. Taken together, these findings provide further insight into
the inter-microbial communications of the HGM as well as into host-HGM
interactions.
Analysis and Modelling of Subthreshold Neural Multi-electrode Array Data by Statistical Field Theory
Date: 2017-03-30 00:00:00

Multi-electrode arrays (MEA) are increasingly used to investigate spontaneous
neuronal network activity. The recorded signals comprise several distinct
components: Apart from artefacts without biological significance, one can
distinguish between spikes (action potentials) and subthreshold fluctuations
(local fields potentials). Here we aim to develop a theoretical model that
allows for a compact and robust characterization of subthreshold fluctuations
in terms of a Gaussian statistical field theory in two spatial and one temporal
dimension. What is usually referred to as the driving noise in the context of
statistical physics is here interpreted as a representation of the neural
activity. Spatial and temporal correlations of this activity give valuable
information about the connectivity in the neural tissue. We apply our methods
on a dataset obtained from MEA-measurements in an acute hippocampal brain slice
from a rat. Our main finding is that the empirical correlation functions indeed
obey the logarithmic behaviour that is a general feature of theoretical models
of this kind. We also find a clear correlation between the activity and the
occurence of spikes. Another important insight is the importance of correcly
separating out certain artefacts from the data before proceeding with the
analysis.