pwc-archive/papers-with-abstracts huggingface dataset:
Graph Curvature and the Robustness of Cancer Networks
Date: 2015-03-25 00:00:00

The importance of studying properties of networks is manifest in diverse
fields ranging from biology, engineering, physics, chemistry, neuroscience, and
medicine. The functionality of networks with regard to performance, throughput,
reliability and robustness is strongly linked to the underlying geometric and
topological properties of the network and this is the focus of this paper,
especially as applied to certain biological networks. The fundamental
mathematical abstraction of a network as a weighted graph brings to bear the
tools of graph theory--a highly developed subject of mathematical research. But
more importantly, recently proposed geometric notions of curvature on very
general metric measure spaces allow us to utilize a whole new set of tools and
ideas that help quantify functionality and robustness of graphs. In particular,
robustness is closely connected to network entropy which, in turn, is very
closely related to curvature. We will see that there are a number of
alternative notions of discrete curvature that are compatible with the
classical Riemannian definition, each having its own advantages and
disadvantages, and are relevant to networks of interest. We will concentrate on
the role of curvature for certain key cancer networks in order to
quantitatively indicate their apparent functional robustness relative to their
normal counterparts.
A dynamic optimal execution strategy under stochastic price recovery
Date: 2015-02-16 00:00:00

In the present paper, we study the optimal execution problem under stochastic
price recovery based on limit order book dynamics. We model price recovery
after execution of a large order by accelerating the arrival of the refilling
order, which is defined as a Cox process whose intensity increases by the
degree of the market impact. We include not only the market order but also the
limit order in our strategy in a restricted fashion. We formulate the problem
as a combined stochastic control problem over a finite time horizon. The
corresponding Hamilton-Jacobi-Bellman quasi-variational inequality is solved
numerically. The optimal strategy obtained consists of three components: (i)
the initial large trade; (ii) the unscheduled small trades during the period;
(iii) the terminal large trade. The size and timing of the trade is governed by
the tolerance for market impact depending on the state at each time step, and
hence the strategy behaves dynamically. We also provide competitive results due
to inclusion of the limit order, even though a limit order is allowed under
conservative evaluation of the execution price.
Real-Time Stochastic Optimal Control for Multi-agent Quadrotor Systems
Date: 2020-05-12 00:00:00

This paper presents a novel method for controlling teams of unmanned aerial
vehicles using Stochastic Optimal Control (SOC) theory. The approach consists
of a centralized high-level planner that computes optimal state trajectories as
velocity sequences, and a platform-specific low-level controller which ensures
that these velocity sequences are met. The planning task is expressed as a
centralized path-integral control problem, for which optimal control
computation corresponds to a probabilistic inference problem that can be solved
by efficient sampling methods. Through simulation we show that our SOC approach
(a) has significant benefits compared to deterministic control and other SOC
methods in multimodal problems with noise-dependent optimal solutions, (b) is
capable of controlling a large number of platforms in real-time, and (c) yields
collective emergent behaviour in the form of flight formations. Finally, we
show that our approach works for real platforms, by controlling a team of three
quadrotors in outdoor conditions.
Photostimulation activates restorable fragmentation of single mitochondrion by initiating oxide flashes
Date: 2015-02-17 00:00:00

Mitochondrial research is important to ageing, apoptosis, and mitochondrial
diseases. In previous works, mitochondria are usually stimulated indirectly by
proapoptotic drugs to study mitochondrial development, which is in lack of
controllability, or spatial and temporal resolution. These chemicals or even
gene techniques regulating mitochondrial dynamics may also activate other
inter- or intra-cellular processes simultaneously. Here we demonstrate a
photostimulation method on single-mitochondrion level by tightly-focused
femtosecond laser that can precisely activate restorable fragmentation of
mitochondria which soon recover their original tubular structure after tens of
seconds. In this process, series of mitochondrial reactive oxygen species
(mROS) flashes are observed and found very critical to mitochondrial
fragmentation. Meanwhile, transient openings of mitochondrial permeability
transition pores (mPTP), suggested by oscillations of mitochondrial membrane
potential, contribute to the scavenging of redundant mROS and recovery of
fragmented mitochondria. Those results demonstrate photostimulation as an
active, precise and controllable method for the study of mitochondrial
oxidative and morphological dynamics or related fields.
Enhancing Information Awareness Through Directed Qualification of Semantic Relevancy Scoring Operations
Authors: Bryant Jason, Hasseler Gregory, Lebo Timothy, Paulini Matthew
Date: 2015-02-15 00:00:00

Successfully managing analytics-based semantic relationships and their
provenance enables determinations of document importance and priority,
furthering capabilities for machine-based relevancy scoring operations.
Semantic technologies are well suited for modeling explicit and fully qualified
relationships but struggle with modeling relationships that are qualified in
nature, or resultant from applied analytics. Our work seeks to implement the
autonomous Directed Qualification of analytic-based relationships by pairing
the Prov-O Ontology (W3C Recommendation) with a relevancy ontology supporting
analytics terminology. This work results in the capability for any semantically
referenced document, concept, or named graph to be associated with the results
of applied analytics as Direct Qualification (DQ) modeled relational nodes.
This new capability will enable role, identity, or any other content-based
measures of relevancy and analytics-based metrics for semantically described
documents.
Adaptive Synchronization and Anticipatory Dynamical System
Date: 2015-08-15 00:00:00

Many biological systems can sense periodical variations in a stimulus input
and produce well-timed, anticipatory responses after the input is removed. Such
systems show memory effects for retaining timing information in the stimulus
and cannot be understood from traditional synchronization consideration of
passive oscillatory systems. To understand this anticipatory phenomena, we
consider oscillators built from excitable systems with the addition of an
adaptive dynamics. With such systems, well-timed post-stimulus responses
similar to those from experiments can be obtained. Furthermore, a well-known
model of working memory is shown to possess similar anticipatory dynamics when
the adaptive mechanism is identified with synaptic facilitation. The last
finding suggests that this type of oscillators can be common in neuronal
systems with plasticity.
Topic Level Disambiguation for Weak Queries
Authors: Zhang Hui, Yang Kiduk, Jacob Elin
Date: 2015-02-17 00:00:00
Tasks: Information Retrieval, Language Modeling, Language Modelling, Retrieval, Word Sense Disambiguation

Despite limited success, information retrieval (IR) systems today are not
intelligent or reliable. IR systems return poor search results when users
formulate their information needs into incomplete or ambiguous queries (i.e.,
weak queries). Therefore, one of the main challenges in modern IR research is
to provide consistent results across all queries by improving the performance
on weak queries. However, existing IR approaches such as query expansion are
not overly effective because they make little effort to analyze and exploit the
meanings of the queries. Furthermore, word sense disambiguation approaches,
which rely on textual context, are ineffective against weak queries that are
typically short. Motivated by the demand for a robust IR system that can
consistently provide highly accurate results, the proposed study implemented a
novel topic detection that leveraged both the language model and structural
knowledge of Wikipedia and systematically evaluated the effect of query
disambiguation and topic-based retrieval approaches on TREC collections. The
results not only confirm the effectiveness of the proposed topic detection and
topic-based retrieval approaches but also demonstrate that query disambiguation
does not improve IR as expected.
Identification of Atlas models
Date: 2015-02-14 00:00:00

Atlas models are systems of Ito processes with parameters that depend on
rank. We show that the parameters of a simple Atlas model can be identified by
measuring the variance of the top-ranked process for different sampling
intervals.
A Brief Comparison Between Available Bio-printing Methods
Date: 2015-02-17 00:00:00

The scarcity of organs for transplant has led to large waiting lists of very
sick patients. In drug development, the time required for human trials greatly
increases the time to market. Drug companies are searching for alternative
environments where the in-vivo conditions can be closely replicated. Both these
problems could be addressed by manufacturing artificial human tissue. Recently,
researchers in tissue engineering have developed tissue generation methods
based on 3-D printing to fabricate artificial human tissue. Broadly, these
methods could be classified as laser-assisted and laser free. The former have
very fine spatial resolutions (10s of $\mu$m) but suffer from slow speed ( $<
10^2$ drops per second). The later have lower spatial resolutions (100s of
$\mu$ m) but are very fast (up to $5\times 10^3$ drops per second). In this
paper we review state-of-the-art methods in each of these classes and provide a
comparison based on reported resolution, printing speed, cell density and cell
viability.
The role of packaging sites in efficient and specific virus assembly
Date: 2015-02-17 00:00:00
Tasks: Genome Understanding, Specificity, Virology

During the lifecycle of many single-stranded RNA viruses, including many
human pathogens, a protein shell called the capsid spontaneously assembles
around the viral genome. Understanding the mechanisms by which capsid proteins
selectively assemble around the viral RNA amidst diverse host RNAs is a key
question in virology. In one proposed mechanism, sequence elements (packaging
sites) within the genomic RNA promote rapid and efficient assembly through
specific interactions with the capsid proteins. In this work we develop a
coarse-grained particle-based computational model for capsid proteins and RNA
which represents protein-RNA interactions arising both from non-specific
electrostatics and specific packaging sites interactions. Using Brownian
dynamics simulations, we explore how the efficiency and specificity of assembly
depend on solution conditions (which control protein-protein and nonspecific
protein-RNA interactions) as well as the strength and number of packaging
sites. We identify distinct regions in parameter space in which packaging sites
lead to highly specific assembly via different mechanisms, and others in which
packaging sites lead to kinetic traps. We relate these computational
predictions to in vitro assays for specificity in which cognate viral RNAs are
compete against non-cognate RNAs for assembly by capsid proteins.
AMAS: optimizing the partition and filtration of adaptive seeds to speed up read mapping
Date: 2015-02-18 00:00:00

Background: Identifying all possible mapping locations of next-generation
sequencing (NGS) reads is highly essential in several applications such as
prediction of genomic variants or protein binding motifs located in repeat
regions, isoform expression quantification, metagenomics analysis, etc.
However, this task is very time-consuming and majority of mapping tools only
focus on one or a few best mapping locations. Results: We propose AMAS, an
alignment tool specialized in identifying all possible mapping locations of NGS
reads in a reference sequence. AMAS features an effective use of adaptive seeds
to speed up read mapping while preserving sensitivity. Specifically, an index
is designed to pre-store the locations of adaptive seeds in the reference
sequence, efficiently reducing the time for seed matching and partitioning. An
accurate filtration of adaptive seeds is further applied to substantially
tighten the candidate alignment space. As a result, AMAS runs several times
faster than other state-of-the-art read mappers while achieving similar
accuracy. Conclusions: AMAS provides a valuable resource to speed up the
important yet time-consuming task of identifying all mapping locations of NGS
reads. AMAS is implemented in C++ based on the SeqAn library and is freely
available at https://sourceforge.net/projects/ngsamas/. Keywords:
next-generation sequencing, read mapping, sequence alignment, adaptive seeds,
seed partition, filtration
Whether relative respiration in trees can be constant: a discussion of a scaling hypothesis
Date: 2015-02-18 00:00:00

Respiration measurements of whole tree plants have been reported that give
evidence that the relative per volume/mass unit respiration decreases with
increase of tree body size. In this study, based on the available data
published a question was explored if the relative per area unit respiration in
trees can be a constant, independent of the surface area size. There is a
definite gap in the published data when the allometric studies of tree body
structure do not intercept with studies on trees respiration. Thus the question
was studied with the help of indirect comparison between various data. The
comparison showed that the scaling exponents, volume vs. surface area and
respiration vs. stem volume, are slightly larger than they should be for the
hypothesis of the relative respiration constancy to hold. The data studied give
evidence that the relative per area unit respiration slightly increases with
the increase in tree surface area. Possible explanations of the relationship
include a different distribution of metabolically active parts of stem and
higher nitrogen content in larger trees. Also, the published datasets might
include large fast growing trees, which imply that larger trees grow faster and
hence have higher per unit surface area growth respiration. A crucial
experiment is required in which the respiration measurements were performed for
the same data as the measurements of scaling between stem volume and surface
area.
Humans can discriminate trillions of olfactory stimuli, or more, or fewer
Date: 2015-02-18 00:00:00

A recent Science paper (Bushdid et al, 2014)[1] proposed that humans can
discriminate between at least a trillion olfactory stimuli. Here we show that
this claim is the result of a fragile estimation framework capable of producing
nearly any result from the reported data, including values tens of orders of
magnitude larger or smaller than the one originally reported in [1]. We
conclude that there is no evidence for the original claim.
Affective Music Information Retrieval
Authors: Wang Ju-Chiang, Yang Yi-Hsuan, Wang Hsin-Min
Date: 2015-02-18 00:00:00
Tasks: Emotion Recognition, Information Retrieval, Music Information Retrieval, Retrieval

Much of the appeal of music lies in its power to convey emotions/moods and to
evoke them in listeners. In consequence, the past decade witnessed a growing
interest in modeling emotions from musical signals in the music information
retrieval (MIR) community. In this article, we present a novel generative
approach to music emotion modeling, with a specific focus on the
valence-arousal (VA) dimension model of emotion. The presented generative
model, called \emph{acoustic emotion Gaussians} (AEG), better accounts for the
subjectivity of emotion perception by the use of probability distributions.
Specifically, it learns from the emotion annotations of multiple subjects a
Gaussian mixture model in the VA space with prior constraints on the
corresponding acoustic features of the training music pieces. Such a
computational framework is technically sound, capable of learning in an online
fashion, and thus applicable to a variety of applications, including
user-independent (general) and user-dependent (personalized) emotion
recognition and emotion-based music retrieval. We report evaluations of the
aforementioned applications of AEG on a larger-scale emotion-annotated corpora,
AMG1608, to demonstrate the effectiveness of AEG and to showcase how
evaluations are conducted for research on emotion-based MIR. Directions of
future work are also discussed.
Query Expansion Strategy based on Pseudo Relevance Feedback and Term Weight Scheme for Monolingual Retrieval
Authors: Vaidyanathan Rekha, Das Sujoy, Srivastava Namita
Date: 2015-02-18 00:00:00
Tasks: Retrieval

Query Expansion using Pseudo Relevance Feedback is a useful and a popular
technique for reformulating the query. In our proposed query expansion method,
we assume that relevant information can be found within a document near the
central idea. The document is normally divided into sections, paragraphs and
lines. The proposed method tries to extract keywords that are closer to the
central theme of the document. The expansion terms are obtained by
equi-frequency partition of the documents obtained from pseudo relevance
feedback and by using tf-idf scores. The idf factor is calculated for number of
partitions in documents. The group of words for query expansion is selected
using the following approaches: the highest score, average score and a group of
words that has maximum number of keywords. As each query behaved differently
for different methods, the effect of these methods in selecting the words for
query expansion is investigated. From this initial study, we extend the
experiment to develop a rule-based statistical model that automatically selects
the best group of words incorporating the tf-idf scoring and the 3 approaches
explained here, in the future. The experiments were performed on FIRE 2011
Adhoc Hindi and English test collections on 50 queries each, using Terrier as
retrieval engine.
Network events on multiple space and time scales in cultured neural networks and in a stochastic rate model
Date: 2015-11-26 00:00:00

Cortical networks, in-vitro as well as in-vivo, can spontaneously generate a
variety of collective dynamical events such as network spikes, UP and DOWN
states, global oscillations, and avalanches. Though each of them have been
variously recognized in previous works as expressions of the excitability of
the cortical tissue and the associated nonlinear dynamics, a unified picture of
their determinant factors (dynamical and architectural) is desirable and not
yet available. Progress has also been partially hindered by the use of a
variety of statistical measures to define the network events of interest. We
propose here a common probabilistic definition of network events that, applied
to the firing activity of cultured neural networks, highlights the
co-occurrence of network spikes, power-law distributed avalanches, and
exponentially distributed `quasi-orbits', which offer a third type of
collective behavior. A rate model, including synaptic excitation and inhibition
with no imposed topology, synaptic short-term depression, and finite-size
noise, accounts for all these different, coexisting phenomena. We find that
their emergence is largely regulated by the proximity to an oscillatory
instability of the dynamics, where the non-linear excitable behavior leads to a
self-amplification of activity fluctuations over a wide range of scales in
space and time. In this sense, the cultured network dynamics is compatible with
an excitation-inhibition balance corresponding to a slightly sub-critical
regime. Finally, we propose and test a method to infer the characteristic time
of the fatigue process, from the observed time course of the network's firing
rate. Unlike the model, possessing a single fatigue mechanism, the cultured
network appears to show multiple time scales, signalling the possible
coexistence of different fatigue mechanisms.
Some complications of the elementary forms of competition in a source/sink and metacommunity context: the role of intranstive loops
Date: 2015-02-18 00:00:00

Dynamic interspecific interactions are thought to contribute to fundamental
structures of ecological communities. Using the Yodzis framework of dominance
control versus founder control versus niche control, the importance of
intransitive loops in sub-communities in a source/sink or metacommunity
competition context is examined. It is found that a three-species sub-community
sampled from a species pool composed of nothing but dominance controlled
species pairs can result in a stable three species coexistence. It is shown
that if effect and response competition are balanced, the overall sub-community
will be persistent, anchored by one or more intransitive loops. It is proposed
that such an arrangement be referred to as an intransitive structure. It is
concluded that persistence of a sub-community (when species pairs in the
species pool are all dominance controlled) of more than three species is
possible only if it has an intransitive structure.
How predictable is technological progress?
Date: 2015-11-25 00:00:00

Recently it has become clear that many technologies follow a generalized
version of Moore's law, i.e. costs tend to drop exponentially, at different
rates that depend on the technology. Here we formulate Moore's law as a
correlated geometric random walk with drift, and apply it to historical data on
53 technologies. We derive a closed form expression approximating the
distribution of forecast errors as a function of time. Based on hind-casting
experiments we show that this works well, making it possible to collapse the
forecast errors for many different technologies at different time horizons onto
the same universal distribution. This is valuable because it allows us to make
forecasts for any given technology with a clear understanding of the quality of
the forecasts. As a practical demonstration we make distributional forecasts at
different time horizons for solar photovoltaic modules, and show how our method
can be used to estimate the probability that a given technology will outperform
another technology at a given point in the future.
Complexity and self-organization in Turing
Date: 2015-02-18 00:00:00

We comment on Alan Turing's celebrated paper "The Chemical Basis of
Morphogenesis" published in 1952 in the "Philosophical Transactions of the
Royal Society of London". It is a typical example of a pioneering and inspired
work in the domain of mathematical modelling.
Chromosome-scale shotgun assembly using an in vitro method for long-range linkage
Date: 2015-02-18 00:00:00

Long-range and highly accurate de novo assembly from short-read data is one
of the most pressing challenges in genomics. Recently, it has been shown that
read pairs generated by proximity ligation of DNA in chromatin of living tissue
can address this problem. These data dramatically increase the scaffold
contiguity of assemblies and provide haplotype phasing information. Here, we
describe a simpler approach ("Chicago") based on in vitro reconstituted
chromatin. We generated two Chicago datasets with human DNA and used a new
software pipeline ("HiRise") to construct a highly accurate de novo assembly
and scaffolding of a human genome with scaffold N50 of 30 Mb. We also
demonstrated the utility of Chicago for improving existing assemblies by
re-assembling and scaffolding the genome of the American alligator. With a
single library and one lane of Illumina HiSeq sequencing, we increased the
scaffold N50 of the American alligator from 508 kb to 10 Mb. Our method uses
established molecular biology procedures and can be used to analyze any genome,
as it requires only about 5 micrograms of DNA as the starting material.