pwc-archive/papers-with-abstracts huggingface dataset:
Analytic and Numerical Models of Oxygen and Nutrient Diffusion, Metabolism Dynamics, and Architecture Optimization in Three-Dimensional Tissue Constructs with Applications and Insights in Cerebral Organoids
Date: 2015-12-21 00:00:00

Diffusion models are important in tissue engineering as they enable an
understanding of molecular delivery to cells in tissue constructs. As
three-dimensional (3D) tissue constructs become larger, more intricate, and
more clinically applicable, it will be essential to understand internal
dynamics and signaling molecule concentrations throughout the tissue. Diffusion
characteristics present a significant limitation in many engineered tissues,
particularly for avascular tissues and for cells whose viability,
differentiation, or function are affected by concentrations of oxygen and
nutrients. This paper seeks to provide novel analytic solutions for certain
cases of steady-state and non-steady-state diffusion and metabolism in 3D
construct designs (planar, cylindrical, and spherical forms), solutions that
otherwise require mathematical approximations achieved through numerical
methods. This model is applied to cerebral organoids, where it is shown that
limitations in diffusion and organoid size can be partially overcome by
localizing metabolically-active cells to an outer layer in a sphere, a
regionalization process that is known to occur through neuroglial precursor
migration both in organoids and in early brain development. The given
prototypical solutions include a review of metabolic information for many cell
types and can be broadly applied to many forms of tissue constructs. This work
enables researchers to model oxygen and nutrient delivery to cells, predict
cell viability, design constructs with improved diffusion capabilities, and
accurately control molecular concentrations in tissue constructs that may be
used in studying models of development and disease or for conditioning cells to
enhance survival after insults like ischemia or implantation into the body,
thereby providing a framework for better understanding and exploring the
characteristics of engineered tissue constructs.
How much diversification potential is there in a single market? Evidence from the Australian Stock Exchange
Date: 2015-12-21 00:00:00

We present four methods of assessing the diversification potential within a
stock market, two of these are based on principal component analysis. They were
applied to the Australian stock exchange for the years 2000 to 2014 and all
show a consistent picture. The potential for diversification declined almost
monotonically in the three years prior to the 2008 financial crisis. On one of
the measures the diversification potential declined even further in the 2011
European debt crisis and the American credit downgrade.
Conversion of the chemical concentration of odorous mixtures into odour concentration and odour intensity: a comparison of methods
Date: 2015-12-21 00:00:00

Continuous odour measurements both of emissions as well as ambient
concentrations are seldom realised, mainly because of their high costs. They
are therefore often substituted by concentration measurements of odorous
substances. Then a conversion of the chemical concentrations C (mg m-3) into
odour concentrations COD (ouE m-3) and odour intensities OI is necessary. Four
methods to convert the concentrations of single substances to the odour
concentrations and odour intensities of an odorous mixture are investigated:
(1) direct use of measured concentrations, (2) the sum of the odour activity
value SOAV, (3) the sum of the odour intensities SOI, and (4) the equivalent
odour concentration EOC, as a new method. The methods are evaluated with
olfactometric measurements of seven substances as well as their mixtures. The
results indicate that the SOI and EOC conversion methods deliver reliable
values. These methods use not only the odour threshold concentration but also
the slope of the Weber-Fechner law to include the sensitivity of the odour
perception of the individual substances. They fulfil the criteria of an
objective conversion without the need of a further calibration by additional
olfactometric measurements.
Asymptotic pricing in large financial markets
Date: 2015-12-21 00:00:00

The problem of hedging and pricing sequences of contingent claims in large
financial markets is studied. Connection between asymptotic arbitrage and
behavior of the $\alpha$~-~quantile price is shown. The large Black-Scholes
model is carefully examined.
Uniform bounds for Black--Scholes implied volatility
Date: 2016-08-31 00:00:00

In this note, Black--Scholes implied volatility is expressed in terms of
various optimisation problems. From these representations, upper and lower
bounds are derived which hold uniformly across moneyness and call price.
Various symmetries of the Black--Scholes formula are exploited to derive new
bounds from old. These bounds are used to reprove asymptotic formulae for
implied volatility at extreme strikes and/or maturities.
A mathematical model of granulopoiesis incorporating the negative feedback dynamics and kinetics of G-CSF/neutrophil binding and internalisation
Date: 2015-12-21 00:00:00

We develop a physiological model of granulopoiesis which includes explicit
modelling of the kinetics of the cytokine granulocyte colony-stimulating factor
(G-CSF) incorporating both the freely circulating concentration and the
concentration of the cytokine bound to mature neutrophils. G-CSF concentrations
are used to directly regulate neutrophil production, with the rate of
differentiation of stem cells to neutrophil precursors, the effective
proliferation rate in mitosis, the maturation time, and the release rate from
the mature marrow reservoir into circulation all dependent on the level of
G-CSF in the system. The dependence of the maturation time on the cytokine
concentration introduces a state-dependent delay into our differential equation
model, and we show how this is derived from an age-structured partial
differential equation model of the mitosis and maturation, and also detail the
derivation of the rest of our model. The model and its estimated parameters are
shown to successfully predict the neutrophil and G-CSF responses to a variety
of treatment scenarios, including the combined administration of chemotherapy
and exogenous G-CSF. This concomitant treatment was reproduced without any
additional fitting to characterise drug-drug interactions.
Sovereign Default Risk and Uncertainty Premia
Date: 2015-12-22 00:00:00

This paper studies how international investors' concerns about model
misspecification affect sovereign bond spreads. We develop a general
equilibrium model of sovereign debt with endogenous default wherein investors
fear that the probability model of the underlying state of the borrowing
economy is misspecified. Consequently, investors demand higher returns on their
bond holdings to compensate for the default risk in the context of uncertainty.
In contrast with the existing literature on sovereign default, we match the
bond spreads dynamics observed in the data together with other business cycle
features for Argentina, while preserving the default frequency at historical
low levels.
Screening Genome Sequences for Known RNA Genes and Motifs
Date: 2015-12-22 00:00:00

This methods paper presents computational protocols for the identification of
non-coding RNA genes or RNA motifs within genomic sequences. An application to
bacterial small RNA is proposed.
A discrete in continuous mathematical model of cardiac progenitor cells formation and growth as spheroid clusters (Cardiospheres)
Date: 2015-12-22 00:00:00

We propose a discrete in continuous mathematical model describing the in
vitro growth process of biophsy-derived mammalian cardiac progenitor cells
growing as clusters in the form of spheres (Cardiospheres). The approach is
hybrid: discrete at cellular scale and continuous at molecular level. In the
present model cells are subject to the self-organizing collective dynamics
mechanism and, additionally, they can proliferate and differentiate, also
depending on stochastic processes. The two latter processes are triggered and
regulated by chemical signals present in the environment. Numerical simulations
show the structure and the development of the clustered progenitors and are in
a good agreement with the results obtained from in vitro experiments.
The Impact of Technical Domain Expertise on Search Behavior and Task Outcome
Authors: Kiseleva Julia, García Alejandro Montes, Kamps Jaap, Spirin Nikita
Date: 2015-12-22 00:00:00
Tasks: Position

Domain expertise is regarded as one of the key factors impacting search
success: experts are known to write more effective queries, to select the right
results on the result page, and to find answers satisfying their information
needs. Search transaction logs play the crucial role in the result ranking. Yet
despite the variety in expertise levels of users, all prior interactions are
treated alike, suggesting that weighting in expertise can improve the ranking
for informational tasks. The main aim of this paper is to investigate the
impact of high levels of technical domain expertise on both search behavior and
task outcome. We conduct an online user study with searchers proficient in
programming languages. We focus on Java and Javascript, yet we believe that our
study and results are applicable for other expertise-sensitive search tasks.
The main findings are three-fold: First, we constructed expertise tests that
effectively measure technical domain expertise and correlate well with the
self-reported expertise. Second, we showed that there is a clear position bias,
but technical domain experts were less affected by position bias. Third, we
found that general expertise helped finding the correct answers, but the domain
experts were more successful as they managed to detect better answers. Our work
is using explicit tests to determine user expertise levels, which is an
important step toward fully automatic detection of expertise levels based on
interaction behavior. A deeper understanding of the impact of expertise on
search behavior and task outcome can enable more effective use of expert
behavior in search logs - essentially make everyone search as an expert.
Multi Currency Credit Default Swaps Quanto effects and FX devaluation jumps
Date: 2018-01-21 00:00:00

Credit Default Swaps (CDS) on a reference entity may be traded in multiple
currencies, in that protection upon default may be offered either in the
domestic currency where the entity resides, or in a more liquid and global
foreign currency. In this situation currency fluctuations clearly introduce a
source of risk on CDS spreads. For emerging markets, but in some cases even in
well developed markets, the risk of dramatic Foreign Exchange (FX) rate
devaluation in conjunction with default events is relevant. We address this
issue by proposing and implementing a model that considers the risk of foreign
currency devaluation that is synchronous with default of the reference entity.
  Preliminary results indicate that perceived risks of devaluation can induce a
significant basis across domestic and foreign CDS quotes. For the Republic of
Italy, a USD CDS spread quote of 440 bps can translate into a EUR quote of 350
bps in the middle of the Euro-debt crisis in the first week of May 2012. More
recently, from June 2013, the basis spreads between the EUR quotes and the USD
quotes are in the range around 40 bps.
  We explain in detail the sources for such discrepancies. Our modeling
approach is based on the reduced form framework for credit risk, where the
default time is modeled in a Cox process setting with explicit diffusion
dynamics for default intensity/hazard rate and exponential jump to default. For
the FX part, we include an explicit default-driven jump in the FX dynamics. As
our results show, such a mechanism provides a further and more effective way to
model credit / FX dependency than the instantaneous correlation that can be
imposed among the driving Brownian motions of default intensity and FX rates,
as it is not possible to explain the observed basis spreads during the
Euro-debt crisis by using the latter mechanism alone.
MVA Transfer Pricing
Date: 2016-07-28 00:00:00

This article prices OTC derivatives with either an exogenously determined
initial margin profile or endogenously approximated initial margin. In the
former case, margin valuation adjustment (MVA) is defined as the liability-side
discounted expected margin profile, while in the latter, an extended partial
differential equation is derived and solved for an all-in fair value,
decomposable into coherent CVA, FVA and MVA. For uncollateralized customer
trades, MVA can be transferred to the customer via an extension of the
liability-side pricing theory. For BCBS-IOSCO covered OTC derivatives, a market
maker has to charge financial counterparties a bid-ask spread to transfer its
funding cost. An IM multiplier is applied to calibrate to external IM models to
allow portfolio incremental pricing. In particular, a link to ISDA SIMM for
equity, commodity and fx risks is established through the PDE with its vega and
curvature IM components captured fully. Numerical examples are given for swaps
and equity portfolios and offer a plausible attribution of recent CME-LCH basis
spread widening to elevated MVA accompanying dealers' hedging of customer
flows.
Liability-side Pricing of Swaps and Coherent CVA and FVA by Regression/Simulation
Date: 2015-12-23 00:00:00
Tasks: regression

An uncollateralized swap hedged back-to-back by a CCP swap is used to
introduce FVA. The open IR01 of FVA, however, is a sure sign of risk not being
fully hedged, a theoretical no-arbitrage pricing concern, and a bait to lure
market risk capital, a practical business concern. By dynamically trading the
CCP swap, with the liability-side counterparty provides counterparty exposure
hedge and swap funding, we find that the uncollateralized swap can be fully
replicated, leaving out no IR01 leakage. The fair value of the swap is obtained
by applying to swap's net cash flows a discount rate switching to
counterparty's bond curve if the swap is a local asset or one's own curve if a
liability, and the total valuation adjustment is the present value of cost of
funding the risk-free price discounted at the same switching rate. FVA is
redefined as a liquidity or funding basis component of total valuation
adjustment, coherent with CVA, the default risk component. A Longstaff-Schwartz
style least-square regression and simulation is introduced to compute the
recursive fair value and adjustments. A separately developed finite difference
scheme is used to test and find regression necessary to decouple the discount
rate switch. Preliminary results show the impact of counterparty risk to swap
hedge ratios, swap bid/ask spreads, and valuation adjustments, and considerable
errors of calculating CVA by discounting cash flow or potential future
exposure.
Musical instrument sound classification with deep convolutional neural network using feature fusion approach
Authors: Park Taejin, Lee Taejin
Date: 2015-12-23 00:00:00
Tasks: General Classification, Sound Classification

A new musical instrument classification method using convolutional neural
networks (CNNs) is presented in this paper. Unlike the traditional methods, we
investigated a scheme for classifying musical instruments using the learned
features from CNNs. To create the learned features from CNNs, we not only used
a conventional spectrogram image, but also proposed multiresolution recurrence
plots (MRPs) that contain the phase information of a raw input signal.
Consequently, we fed the characteristic timbre of the particular instrument
into a neural network, which cannot be extracted using a phase-blinded
representations such as a spectrogram. By combining our proposed MRPs and
spectrogram images with a multi-column network, the performance of our proposed
classifier system improves over a system that uses only a spectrogram.
Furthermore, the proposed classifier also outperforms the baseline result from
traditional handcrafted features and classifiers.
The White Matter Query Language: A Novel Approach for Describing Human White Matter Anatomy
Date: 2015-12-23 00:00:00
Tasks: Anatomy, Diffusion  MRI

We have developed a novel method to describe human white matter anatomy using
an approach that is both intuitive and simple to use, and which automatically
extracts white matter tracts from diffusion MRI volumes. Further, our method
simplifies the quantification and statistical analysis of white matter tracts
on large diffusion MRI databases. This work reflects the careful syntactical
definition of major white matter fiber tracts in the human brain based on a
neuroanatomist's expert knowledge. The framework is based on a novel query
language with a near-to-English textual syntax. This query language makes it
possible to construct a dictionary of anatomical definitions that describe
white matter tracts. The definitions include adjacent gray and white matter
regions, and rules for spatial relations. This novel method makes it possible
to automatically label white matter anatomy across subjects. After describing
this method, we provide an example of its implementation where we encode
anatomical knowledge in human white matter for 10 association and 15 projection
tracts per hemisphere, along with 7 commissural tracts. Importantly, this novel
method is comparable in accuracy to manual labeling. Finally, we present
results applying this method to create a white matter atlas from 77 healthy
subjects, and we use this atlas in a small proof-of-concept study to detect
changes in association tracts that characterize schizophrenia.
QuickProbs 2: towards rapid construction of high-quality alignments of large protein families
Date: 2016-08-30 00:00:00
Tasks: Multiple Sequence Alignment

Increasing size of sequence databases caused by the development of high
throughput sequencing, poses multiple alignment algorithms to face one of the
greatest challenges yet. As we show, well-established techniques employed for
increasing alignment quality, i.e., refinement and consistency, are ineffective
when large protein families are of interest. We present QuickProbs 2, an
algorithm for multiple sequence alignment. Based on probabilistic models,
equipped with novel column-oriented refinement and selective consistency, it
offers outstanding accuracy. When analysing hundreds of sequences, QuickProbs 2
is significantly better than Clustal Omega, the previous leader for processing
numerous protein families. In the case of smaller sets, for which
consistency-based methods are the best performing, QuickProbs 2 is also
superior to the competitors. Due to computational scalability of selective
consistency and utilisation of massively parallel architectures, presented
algorithm is comparable to Clustal Omega in terms of execution time, and orders
of magnitude faster than full consistency approaches, like MSAProbs or PicXAA.
All these make QuickProbs 2 a useful tool for aligning families ranging from
few, to hundreds of proteins. QuickProbs 2 is available at
https://github.com/refresh-bio/QuickProbs.
Exploiting Hierarchy for Ranking-based Recommendation
Authors: Kouneli Marianna
Date: 2015-12-23 00:00:00
Tasks: Collaborative Filtering

The purpose of this master's thesis is to study and develop a new algorithmic
framework for collaborative filtering (CF) to generate recommendations. The
method we propose is based on the exploitation of the hierarchical structure of
the item space and intuitively "stands" on the property of Near Complete
Decomposability (NCD) which is inherent in the structure of the majority of
hierarchical systems. Building on the intuition behind the NCDawareRank
algorithm and its related concept of NCD proximity, we model our system in a
way that illuminates its endemic characteristics and we propose a new
algorithmic framework for recommendations, called HIR. We focus on combining
the direct with the NCD "neighborhoods" of items to achieve better
characterization of the inter-item relations, in order to improve the quality
of recommendations and alleviate sparsity related problems.
Evaluation-as-a-Service: Overview and Outlook
Authors: Hanbury Allan, Müller Henning, Balog Krisztian, Brodt Torben, Cormack Gordon V., Eggel Ivan, Gollub Tim, Hopfgartner Frank, Kalpathy-Cramer Jayashree, Kando Noriko, Krithara Anastasia, Lin Jimmy, Mercer Simon, Potthast Martin
Date: 2015-12-23 00:00:00
Tasks: Information Retrieval, Retrieval

Evaluation in empirical computer science is essential to show progress and
assess technologies developed. Several research domains such as information
retrieval have long relied on systematic evaluation to measure progress: here,
the Cranfield paradigm of creating shared test collections, defining search
tasks, and collecting ground truth for these tasks has persisted up until now.
In recent years, however, several new challenges have emerged that do not fit
this paradigm very well: extremely large data sets, confidential data sets as
found in the medical domain, and rapidly changing data sets as often
encountered in industry. Also, crowdsourcing has changed the way that industry
approaches problem-solving with companies now organizing challenges and handing
out monetary awards to incentivize people to work on their challenges,
particularly in the field of machine learning.
  This white paper is based on discussions at a workshop on
Evaluation-as-a-Service (EaaS). EaaS is the paradigm of not providing data sets
to participants and have them work on the data locally, but keeping the data
central and allowing access via Application Programming Interfaces (API),
Virtual Machines (VM) or other possibilities to ship executables. The objective
of this white paper are to summarize and compare the current approaches and
consolidate the experiences of these approaches to outline the next steps of
EaaS, particularly towards sustainable research infrastructures.
  This white paper summarizes several existing approaches to EaaS and analyzes
their usage scenarios and also the advantages and disadvantages. The many
factors influencing EaaS are overviewed, and the environment in terms of
motivations for the various stakeholders, from funding agencies to challenge
organizers, researchers and participants, to industry interested in supplying
real-world problems for which they require solutions.