pwc-archive/papers-with-abstracts huggingface dataset:
Asporin expression is highly regulated in human chondrocytes
Date: 2015-05-26 00:00:00
Tasks: Cultural Vocal Bursts Intensity Prediction

A significant association between a polymorphism in the D repeat of the gene
encoding asporin and osteoarthritis, the most frequent of articular diseases,
has been recently reported. The goal of the present study was to investigate
the expression of this new class I small leucine-rich proteoglycan (SLRP) in
human articular chondrocytes. First, we studied the modulation of asporin
(ASPN) expression by cytokines by Western blot and reverse
transcription-polymerase chain reaction. Interleukin-1$\beta$ and tumor
necrosis factor-$\alpha$ downregulated ASPN, whereas transforming growth
factor-$\beta$1 (when incubated in a serum-free medium) upregulated it.
Similarly to proinflammatory cytokines, chondrocyte dedifferentiation induced
by a successive passages of cells was accompanied by a decreased asporin
expression, whereas their redifferentiation by three-dimensional culture
restored its expression. Finally, we found an important role of the
transcription factor Sp1 in the regulation of ASPN expression. Sp1 ectopic
expression increased ASPN mRNA level and promoter activity. In addition, using
gene reporter assay and electrophoretic mobility shift assay, we showed that
Sp1 mediated its effect through a region located between -473 and -140 bp
upstream of the transcription start site in ASPN gene. In conclusion, this
report is the first study on the regulation of asporin expression by different
cytokines in human articular chondrocytes. Our data indicate that the
expression of this gene is finely regulated in cartilage and suggest a major
role of Sp1.
Conditional Asian Options
Date: 2015-05-26 00:00:00
Tasks: Management

Conditional Asian options are recent market innovations, which offer cheaper
and long-dated alternatives to regular Asian options. In contrast with payoffs
from regular Asian options which are based on average asset prices, the payoffs
from conditional Asian options are determined only by average prices above
certain threshold. Due to the limited inclusion of prices, conditional Asian
options further reduce the volatility in the payoffs than their regular
counterparts and have been promoted in the market as viable hedging and risk
management instruments for equity-linked life insurance products. There has
been no previous academic literature on this subject and practitioners have
only been known to price these products by simulations. We propose the first
analytical approach to computing prices and deltas of conditional Asian options
in comparison with regular Asian options. In the numerical examples, we put to
the test some cost-benefit claims by practitioners. As a by-product, the work
also presents some distributional properties of the occupation time and the
time-integral of geometric Brownian motion during the occupation time.
Motif analysis in directed ordered networks and applications to food webs
Date: 2015-05-26 00:00:00

The analysis of small recurrent substructures, so called network motifs, has
become a standard tool of complex network science to unveil the design
principles underlying the structure of empirical networks. In many natural
systems network nodes are associated with an intrinsic property according to
which they can be ordered and compared against each other. Here, we expand
standard motif analysis to be able to capture the hierarchical structure in
such ordered networks. Our new approach is based on the identification of all
ordered 3-node substructures and the visualization of their significance
profile. We present a technique to calculate the fine grained motif spectrum by
resolving the individual members of isomorphism classes (sets of substructures
formed by permuting node-order). We apply this technique to computer generated
ensembles of ordered networks and to empirical food web data, demonstrating the
importance of considering node order for food-web analysis. Our approach may
not only be helpful to identify hierarchical patterns in empirical food webs
and other natural networks, it may also provide the base for extending motif
analysis to other types of multi-layered networks.
Chromosomal rearrangements as barriers to genetic homogenization between archaic and modern humans
Date: 2015-09-14 00:00:00

Chromosomal rearrangements, which shuffle DNA throughout the genome, are an
important source of divergence across taxa. Using a paired-end read approach
with Illumina sequence data for archaic humans, I identify changes in genome
structure that occurred recently in human evolution. Hundreds of rearrangements
indicate genomic trafficking between the sex chromosomes and autosomes, raising
the possibility of sex-specific changes. Additionally, genes adjacent to genome
structure changes in Neanderthals are associated with testis-specific
expression, consistent with evolutionary theory that new genes commonly form
with expression in the testes. I identify one case of new-gene creation through
transposition from the Y chromosome to chromosome 10 that combines the 5' end
of the testis-specific gene Fank1 with previously untranscribed sequence. This
new transcript experienced copy number expansion in archaic genomes, indicating
rapid genomic change. Among rearrangements identified in Neanderthals, 13% are
transposition of selfish genetic elements, while 32% appear to be ectopic
exchange between repeats. In Denisovan, the pattern is similar but numbers are
significantly higher with 18% of rearrangements reflecting transposition and
40% ectopic exchange between distantly related repeats. There is an excess of
divergent rearrangements relative to polymorphism in Denisovan, which might
result from non-uniform rates of mutation, possibly reflecting a burst of TE
activity in the lineage that led to Denisovan. Finally, loci containing genome
structure changes show diminished rates of introgression from Neanderthals into
modern humans, consistent with the hypothesis that rearrangements serve as
barriers to gene flow during hybridization. Together, these results suggest
that this previously unidentified source of genomic variation has important
biological consequences in human evolution.
Interest-based RDF Update Propagation
Authors: Endris Kemele M., Faisal Sidra, Orlandi Fabrizio, Auer Sören, Scerri Simon
Date: 2015-05-26 00:00:00

Many LOD datasets, such as DBpedia and LinkedGeoData, are voluminous and
process large amounts of requests from diverse applications. Many data products
and services rely on full or partial local LOD replications to ensure faster
querying and processing. While such replicas enhance the flexibility of
information sharing and integration infrastructures, they also introduce data
duplication with all the associated undesirable consequences. Given the
evolving nature of the original and authoritative datasets, to ensure
consistent and up-to-date replicas frequent replacements are required at a
great cost. In this paper, we introduce an approach for interest-based RDF
update propagation, which propagates only interesting parts of updates from the
source to the target dataset. Effectively, this enables remote applications to
`subscribe' to relevant datasets and consistently reflect the necessary changes
locally without the need to frequently replace the entire dataset (or a
relevant subset). Our approach is based on a formal definition for
graph-pattern-based interest expressions that is used to filter interesting
parts of updates from the source. We implement the approach in the iRap
framework and perform a comprehensive evaluation based on DBpedia Live updates,
to confirm the validity and value of our approach.
SWEEPFINDER2: Increased sensitivity, robustness, and flexibility
Date: 2015-05-26 00:00:00
Tasks: Sensitivity

SweepFinder is a popular program that implements a powerful likelihood-based
method for detecting recent positive selection, or selective sweeps. Here, we
present SweepFinder2, an extension of SweepFinder with increased sensitivity
and robustness to the confounding effects of mutation rate variation and
background selection, as well as increased flexibility that enables the user to
examine genomic regions in greater detail and to specify a fixed distance
between test sites. Moreover, SweepFinder2 enables the use of invariant sites
for sweep detection, increasing both its power and precision relative to
SweepFinder.
Optimal Multiple Stopping with Negative Discount Rate and Random Refraction Times under Levy Models
Date: 2015-05-27 00:00:00

This paper studies a class of optimal multiple stopping problems driven by
L\'evy processes. Our model allows for a negative effective discount rate,
which arises in a number of financial applications, including stock loans and
real options, where the strike price can potentially grow at a higher rate than
the original discount factor. Moreover, successive exercise opportunities are
separated by i.i.d. random refraction times. Under a wide class of two-sided
L\'evy models with a general random refraction time, we rigorously show that
the optimal strategy to exercise successive call options is uniquely
characterized by a sequence of up-crossing times. The corresponding optimal
thresholds are determined explicitly in the single stopping case and
recursively in the multiple stopping case.
A Novel Algorithm for the Maximal Fit Problem in Boolean Networks
Date: 2016-06-20 00:00:00
Tasks: Time Series, Time Series Analysis

Gene regulatory networks (GRNs) are increasingly used for explaining
biological processes with complex transcriptional regulation. A GRN links the
expression levels of a set of genes via regulatory controls that gene products
exert on one another. Boolean networks are a common modeling choice since they
balance between detail and ease of analysis. However, even for Boolean networks
the problem of fitting a given network model to an expression dataset is
NP-Complete. Previous methods have addressed this issue heuristically or by
focusing on acyclic networks and specific classes of regulation functions. In
this paper we introduce a novel algorithm for this problem that makes use of
sampling in order to handle large datasets. Our algorithm can handle time
series data for any network type and steady state data for acyclic networks.
Using in-silico time series data we demonstrate good performance on large
datasets with a significant level of noise.
Retrieval of multimedia stimuli with semantic and emotional cues: Suggestions from a controlled study
Authors: Horvat Marko, Kukolja Davor, Ivanec Dragutin
Date: 2017-06-30 00:00:00
Tasks: Retrieval

The ability to efficiently search pictures with annotated semantics and
emotion is an important problem for Human-Computer Interaction with
considerable interdisciplinary significance. Accuracy and speed of the
multimedia retrieval process depends on the chosen metadata annotation model.
The quality of such multifaceted retrieval is opposed to the potential
complexity of data setup procedures and development of multimedia annotations.
Additionally, a recent study has shown that databases of emotionally annotated
multimedia are still being predominately searched manually which highlights the
need to study this retrieval modality. To this regard we present a study with N
= 75 participants aimed to evaluate the influence of keywords and dimensional
emotions in manual retrieval of pictures. The study showed that if the
multimedia database is comparatively small emotional annotations are sufficient
to achieve a fast retrieval despite comparatively lesser overall accuracy. In a
larger dataset semantic annotations became necessary for efficient retrieval
although they contributed to a slower beginning of the search process. The
experiment was performed in a controlled environment with a team of psychology
experts. The results were statistically consistent with validates measures of
the participants' perceptual speed.
Fitting a distribution to Value-at-Risk and Expected Shortfall, with an application to covered bonds
Date: 2015-11-12 00:00:00
Tasks: Management

Covered bonds are a specific example of senior secured debt. If the issuer of
the bonds defaults the proceeds of the assets in the cover pool are used for
their debt service. If in this situation the cover pool proceeds do not suffice
for the debt service, the creditors of the bonds have recourse to the issuer's
assets and their claims are pari passu with the claims of the creditors of
senior unsecured debt. Historically, covered bonds have been very safe
investments. During their more than two hundred years of existence, investors
never suffered losses due to missed payments from covered bonds. From a risk
management perspective, therefore modelling covered bonds losses is mainly of
interest for estimating the impact that the asset encumbrance by the cover pool
has on the loss characteristics of the issuer's senior unsecured debt. We
explore one-period structural modelling approaches for covered bonds and senior
unsecured debt losses with one and two asset value variables respectively.
Obviously, two-assets models with separate values of the cover pool and the
issuer's remaining portfolio allow for more realistic modelling. However, we
demonstrate that exact calibration of such models may be impossible. We also
investigate a one-asset model in which the riskiness of the cover pool is
reflected by a risk-based adjustment of the encumbrance ratio of the issuer's
assets.
Implications of the hybrid epithelial/mesenchymal phenotype in metastasis
Date: 2015-05-27 00:00:00

Understanding cell-fate decisions during tumorigenesis and metastasis is a
major challenge in modern cancer biology. One canonical cell-fate decision that
cancer cells undergo is Epithelial-to-Mesenchymal Transition (EMT) and its
reverse Mesenchymal-to-Epithelial Transition (MET). While transitioning between
these two phenotypes - epithelial and mesenchymal - cells can also attain a
hybrid epithelial/mesenchymal (i.e. partial or intermediate EMT) phenotype.
Cells in this phenotype have mixed epithelial (e.g. adhesion) and mesenchymal
(e.g. migration) properties, thereby allowing them to move collectively as
clusters of Circulating Tumor Cells (CTCs). If these clusters enter the
circulation, they can be more apoptosis-resistant and more capable of
initiating metastatic lesions than cancer cells moving individually with wholly
mesenchymal phenotypes, having undergo a complete EMT. Here, we review the
operating principles of the core regulatory network for EMT/MET that acts as a
three-way switch giving rise to three distinct phenotypes - epithelial,
mesenchymal and hybrid epithelial/mesenchymal. We further characterize this
hybrid E/M phenotype in terms of its capabilities in terms of collective cell
migration, tumor-initiation, cell-cell communication, and drug resistance. We
elucidate how the highly interconnected coupling between these modules
coordinates cell-fate decisions among a population of cancer cells in the
dynamic tumor, hence facilitating tumor-stoma interactions, formation of CTC
clusters, and consequently cancer metastasis. Finally, we discuss the multiple
advantages that the hybrid epithelial/mesenchymal phenotype have as compared to
a complete EMT phenotype and argue that these collectively migrating cells are
the primary 'bad actors' of metastasis.
A Report on the Workshop on Biobanking Informatics
Date: 2015-05-27 00:00:00

The Workshop on Biobanking Informatics in NSW 2013 (WBIN13) was held on
Friday, 10 May 2013 at The Wallace Wurth Building in the University of New
South Wales. This report summarises the keynotes, presentations and discussions
in WBIN13 which discusses current research in the field of Biobanking
Informatics in Australia and internationally.
Energy dissipation in an adaptive molecular circuit
Date: 2015-05-28 00:00:00
Tasks: Relation, Sensitivity

The ability to monitor nutrient and other environmental conditions with high
sensitivity is crucial for cell growth and survival. Sensory adaptation allows
a cell to recover its sensitivity after a transient response to a shift in the
strength of extracellular stimulus. The working principles of adaptation have
been established previously based on rate equations which do not consider
fluctuations in a thermal environment. Recently, G. Lan et al. (Nature Phys.,
8:422-8, 2012) performed a detailed analysis of a stochastic model for the E.
coli sensory network. They showed that accurate adaptation is possible only
when the system operates in a nonequilibrium steady-state (NESS). They further
proposed an energy-speed-accuracy (ESA) trade-off relation. We present here
analytic results on the NESS of the model through a mapping to a
one-dimensional birth-death process. An exact expression for the entropy
production rate is also derived. Based on these results, we are able to discuss
the ESA relation in a more general setting. Our study suggests that the
adaptation error can be reduced exponentially as the methylation range
increases. Finally, we show that a nonequilibrium phase transition exists in
the infinite methylation range limit, despite the fact that the model contains
only two discrete variables.
High-order compact schemes for Black-Scholes basket options
Date: 2015-05-28 00:00:00
Tasks: Vocal Bursts Intensity Prediction

We present a new high-order compact scheme for the multi-dimensional
Black-Scholes model with application to European Put options on a basket of two
underlying assets. The scheme is second-order accurate in time and fourth-order
accurate in space. Numerical examples confirm that a standard second-order
finite difference scheme is significantly outperformed.
An analytic recursive method for optimal multiple stopping: Canadization and phase-type fitting
Date: 2015-05-28 00:00:00

We study an optimal multiple stopping problem for call-type payoff driven by
a spectrally negative Levy process. The stopping times are separated by
constant refraction times, and the discount rate can be positive or negative.
The computation involves a distribution of the Levy process at a constant
horizon and hence the solutions in general cannot be attained analytically.
Motivated by the maturity randomization (Canadization) technique by Carr
(1998), we approximate the refraction times by independent, identically
distributed Erlang random variables. In addition, fitting random jumps to
phase-type distributions, our method involves repeated integrations with
respect to the resolvent measure written in terms of the scale function of the
underlying Levy process. We derive a recursive algorithm to compute the value
function in closed form, and sequentially determine the optimal exercise
thresholds. A series of numerical examples are provided to compare our analytic
formula to results from Monte Carlo simulation.
Genetically Improved BarraCUDA
Date: 2015-05-28 00:00:00
Tasks: CPU, GPU

BarraCUDA is a C program which uses the BWA algorithm in parallel with nVidia
CUDA to align short next generation DNA sequences against a reference genome.
The genetically improved (GI) code is up to three times faster on short paired
end reads from The 1000 Genomes Project and 60percent more accurate on a short
BioPlanet.com GCAT alignment benchmark. GPGPU Barracuda running on a single K80
Tesla GPU can align short paired end nextgen sequences up to ten times faster
than bwa on a 12 core CPU.
Learning universal computations with spikes
Date: 2016-06-29 00:00:00

Providing the neurobiological basis of information processing in higher
animals, spiking neural networks must be able to learn a variety of complicated
computations, including the generation of appropriate, possibly delayed
reactions to inputs and the self-sustained generation of complex activity
patterns, e.g.~for locomotion. Many such computations require previous building
of intrinsic world models. Here we show how spiking neural networks may solve
these different tasks. Firstly, we derive constraints under which classes of
spiking neural networks lend themselves to substrates of powerful general
purpose computing. The networks contain dendritic or synaptic nonlinearities
and have a constrained connectivity. We then combine such networks with
learning rules for outputs or recurrent connections. We show that this allows
to learn even difficult benchmark tasks such as the self-sustained generation
of desired low-dimensional chaotic dynamics or memory-dependent computations.
Furthermore, we show how spiking networks can build models of external world
systems and use the acquired knowledge to control them.
A Faster Algorithm to Build New Users Similarity List in Neighbourhood-based Collaborative Filtering
Authors: Lu Zhigang, Shen Hong
Date: 2015-05-29 00:00:00
Tasks: Collaborative Filtering

Neighbourhood-based Collaborative Filtering (CF) has been applied in the
industry for several decades, because of the easy implementation and high
recommendation accuracy. As the core of neighbourhood-based CF, the task of
dynamically maintaining users' similarity list is challenged by cold-start
problem and scalability problem. Recently, several methods are presented on
solving the two problems. However, these methods applied an $O(n^2)$ algorithm
to compute the similarity list in a special case, where the new users, with
enough recommendation data, have the same rating list. To address the problem
of large computational cost caused by the special case, we design a faster
($O(\frac{1}{125}n^2)$) algorithm, TwinSearch Algorithm, to avoid computing and
sorting the similarity list for the new users repeatedly to save the
computational resources. Both theoretical and experimental results show that
the TwinSearch Algorithm achieves better running time than the traditional
method.
The effect of non-reversibility on inferring rooted phylogenies
Date: 2017-02-20 00:00:00
Tasks: Position

Most phylogenetic models assume that the evolutionary process is stationary
and reversible. As a result, the root of the tree cannot be inferred as part of
the analysis because the likelihood of the data does not depend on the position
of the root. Yet defining the root of a phylogenetic tree is a key component of
phylogenetic inference because it provides a point of reference for polarising
ancestor/descendant relationships and therefore interpreting the tree. In this
paper we investigate the effect of relaxing the reversibility assumption and
allowing the position of the root to be another unknown in the model. We
propose two hierarchical models that are centred on a reversible model but
perturbed to allow non-reversibility. The models differ in the degree of
structure imposed on the perturbations. The analysis is performed in the
Bayesian framework using Markov chain Monte Carlo methods. We illustrate the
performance of the two non-reversible models in analyses of simulated data sets
using two types of topological priors. We then apply the models to a real
biological data set, the radiation of polyploid yeasts, for which there is a
robust biological opinion about the root position. Finally we apply the models
to a second biological data set for which the rooted tree is controversial: the
ribosomal tree of life. We compare the two non-reversible models and conclude
that both are useful in inferring the position of the root from real biological
data sets.
Exploitation of the genomic double-strand breaks to reduce the reproductive power of microorganisms
Date: 2015-05-29 00:00:00

It is shown how to take advantage of the frequent occurrence of double-strand
breaks in the genome of prokaryotic cells, in order to reduce their high
efficient reproductive capability. The analysis examines the physical status of
the free ends of each break and considers how this status can interfere with an
external physical apparatus, with the aim of undermining the repair processes.
We indicate the biological consequences of this interaction and we give an
approximate evaluation of the topological and dynamical effects that arise on
the genomic material involved. The overall result suggests a significant
reduction of the dynamics of the repair.