pwc-archive/papers-with-abstracts huggingface dataset:
Modeling the Effects of Multiple Myeloma on Kidney Function
Date: 2018-07-17 00:00:00
Tasks: Kidney Function, Prognosis

Multiple myeloma (MM), a plasma cell cancer, is associated with many health
challenges, including damage to the kidney by tubulointerstitial fibrosis. We
develop a mathematical model which captures the qualitative behavior of the
cell and protein populations involved. Specifically, we model the interaction
between cells in the proximal tubule of the kidney, free light chains, renal
fibroblasts, and myeloma cells. We analyze the model for steady-state solutions
to find a mathematically and biologically relevant stable steady-state
solution. This foundational model provides a representation of dynamics between
key populations in tubulointerstitial fibrosis that demonstrates how these
populations interact to affect patient prognosis in patients with MM and renal
impairment.
Valuation of Variable Annuities with Guaranteed Minimum Withdrawal Benefit under Stochastic Interest Rate
Date: 2017-01-15 00:00:00

A variable annuity contract with Guaranteed Minimum Withdrawal Benefit (GMWB)
promises to return the entire initial investment through cash withdrawals
during the contract plus the remaining account balance at maturity, regardless
of the portfolio performance. Under the optimal(dynamic) withdrawal strategy of
a policyholder, GMWB pricing becomes an optimal stochastic control problem that
can be solved by backward recursion of Bellman equation. In this paper we
develop a very efficient new algorithm for pricing these contracts in the case
of stochastic interest rate not considered previously in the literature.
Presently our method is applied to the Vasicek interest rate model, but it is
generally applicable to any model when transition density or moments of the
underlying asset and interest rate are known in closed form or can be evaluated
efficiently. Using bond price as a numeraire the required expectations in the
backward recursion are reduced to two-dimensional integrals calculated through
a high order Gauss-Hermite quadrature applied on a two-dimensional cubic spline
interpolation. Numerical results from the new algorithm for a series of GMWB
contracts for both static and optimal cases are presented. As a validation,
results of the algorithm are compared with the closed form solutions for simple
vanilla options, and with Monte Carlo and finite difference results for the
static GMWB. The comparison demonstrates that the new algorithm is
significantly faster than finite difference or Monte Carlo for all the
two-dimensional problems tested so far. For dynamic GMWB pricing, we found that
for positive correlation between the underlying asset and interest rate, the
GMWB price under the stochastic interest rate is significantly higher compared
to the case of deterministic interest rate, while for negative correlation the
difference is less but still significant.
Development of a Computationally Optimized Model of Cancer-induced Angiogenesis through Specialized Cellular Mechanics
Date: 2016-02-10 00:00:00

Angiogenesis, the development of new vasculature, is a critical process in
the growth of new tumors. Driven by a goal to understand this aspect of cancer
proliferation, I develop a discrete computationally optimized mathematical
model of angiogenesis that specializes in intercellular interactions. I model
vascular endothelial growth factor spread and dynamics of endothelial cell
movement in a competitive environment, with parameters specific to our model
calculated through Dependent Variable Sensitivity Analysis (DVSA) and
experimentally observed data. Through simulation testing, we find the critical
limits of angiogenesis to be 102 m and 153 m respectively, beyond which
angiogenesis will not successfully occur. Cell density in the surrounding
region and the concentration of extracellular matrix fibers are also found to
directly inhibit angiogenesis. Through these three factors, we postulate a
method for establishing criticality of a tumor based upon the likelihood of
angiogenesis completing. This research expands on other work by choosing
factors that are patient-dependent through our specialized Cellular Potts mode,
which serves to optimize and increase accuracy of the model. By doing such, I
establish a theoretical framework for analyzing lesions using angiogenetic
properties, with the ability to potentially compute the criticality of tumors
with the aid of medical imaging technology.
A study of co-movements between oil price, stock index and exchange rate under a cross-bicorrelation perspective: the case of Mexico
Date: 2016-02-10 00:00:00

In this chapter we studied the nonlinear co-movements between the Mexican
Crude Oil price, the Mexican Stock Market Index and the USD/MXN Exchange Rate,
for the sample period from 1994 to date. We used a battery of nonlinear tests,
cf. (Patterson & Ashley, 2000) and one multivariate test, in order to determine
the dynamic co-movement exerted from the oil prices to the stock and exchange
rate markets. Such co-movement and time windows are exposed using the Brooks &
Hinich (1999) cross- bicorrelation statistical test. The effects of oil spills
on other markets have been studied from different angles and on several
financial assets. In this study, we focus our attention on the detection, not
only of the correlations amongst markets but on the epochs in which such
nonlinear dependence might occur. This is important in order to understand
better, how the markets that drive the economy interact with each other. We
hope to contribute to the literature with such findings, filling a gap in the
emerging markets context, in particular, for the Mexican case.
Pricing options on forwards in energy markets: the role of mean reversion's speed
Date: 2016-02-10 00:00:00

Consider the problem of pricing options on forwards in energy markets, when
spot prices follow a geometric multi-factor model in which several rates of
mean reversion appear. In this paper we investigate the role played by slow
mean reversion when pricing and hedging options. In particular, we determine
both upper and lower bounds for the error one makes neglecting low rates of
mean reversion in the spot price dynamics.
Winning versus losing during gambling and its neural correlates
Date: 2016-02-10 00:00:00
Tasks: Decision Making

Humans often make decisions which maximize an internal utility function. For
example, humans often maximize their expected reward when gambling and this is
considered as a "rational" decision. However, humans tend to change their
betting strategies depending on how they "feel". If someone has experienced a
losing streak, they may "feel" that they are more likely to win on the next
hand even though the odds of the game have not changed. That is, their
decisions are driven by their emotional state. In this paper, we investigate
how the human brain responds to wins and losses during gambling. Using a
combination of local field potential recordings in human subjects performing a
financial decision-making task, spectral analyses, and non-parametric cluster
statistics, we investigated whether neural responses in different cognitive and
limbic brain areas differ between wins and losses after decisions are made. In
eleven subjects, the neural activity modulated significantly between win and
loss trials in one brain region: the anterior insula ($p=0.01$). In particular,
gamma activity (30-70 Hz) increased in the anterior insula when subjects just
realized that they won. Modulation of metabolic activity in the anterior insula
has been observed previously in functional magnetic resonance imaging studies
during decision making and when emotions are elicited. However, our study is
able to characterize temporal dynamics of electrical activity in this brain
region at the millisecond resolution while decisions are made and after
outcomes are revealed.
Basel III capital surcharges for G-SIBs fail to control systemic risk and can cause pro-cyclical side effects
Date: 2016-02-10 00:00:00

In addition to constraining bilateral exposures of financial institutions,
there are essentially two options for future financial regulation of systemic
risk (SR): First, financial regulation could attempt to reduce the financial
fragility of global or domestic systemically important financial institutions
(G-SIBs or D-SIBs), as for instance proposed in Basel III. Second, future
financial regulation could attempt strengthening the financial system as a
whole. This can be achieved by re-shaping the topology of financial networks.
We use an agent-based model (ABM) of a financial system and the real economy to
study and compare the consequences of these two options. By conducting three
"computer experiments" with the ABM we find that re-shaping financial networks
is more effective and efficient than reducing leverage. Capital surcharges for
G-SIBs can reduce SR, but must be larger than those specified in Basel III in
order to have a measurable impact. This can cause a loss of efficiency. Basel
III capital surcharges for G-SIBs can have pro-cyclical side effects.
Detecting the Collapse of Cooperation in Evolving Networks
Date: 2016-02-11 00:00:00

The sustainability of structured biological, social, economic and ecological
communities are often determined by the outcome of social conflicts between
cooperative and selfish individuals (cheaters). Cheaters avoid the cost of
contributing to the community and can occasionally spread in the population
leading to the complete collapse of cooperation. Although such a collapse often
unfolds unexpectedly bearing the traits of a critical transition, it is unclear
whether one can detect the rising risk of cheater's invasions and loss of
cooperation in an evolving community. Here, we combine dynamical networks and
evolutionary game theory to study the abrupt loss of cooperation as a critical
transition. We estimate the risk of collapse of cooperation after the
introduction of a single cheater under gradually changing conditions. We
observe a systematic increase in the average time it takes for cheaters to be
eliminated from the community as the risk of collapse increases. We detect this
risk based on changes in community structure and composition. Nonetheless,
reliable detection depends on the mechanism that governs how cheaters evolve in
the community. Our results suggest possible avenues for detecting the loss of
cooperation in evolving communities
Theoretical connections between mathematical neuronal models corresponding to different expressions of noise
Date: 2016-02-10 00:00:00

Identifying the right tools to express the stochastic aspects of neural
activity has proven to be one of the biggest challenges in computational
neuroscience. Even if there is no definitive answer to this issue, the most
common procedure to express this randomness is the use of stochastic models. In
accordance with the origin of variability, the sources of randomness are
classified as intrinsic or extrinsic and give rise to distinct mathematical
frameworks to track down the dynamics of the cell. While the external
variability is generally treated by the use of a Wiener process in models such
as the Integrate-and-Fire model, the internal variability is mostly expressed
via a random firing process. In this paper, we investigate how those distinct
expressions of variability can be related. To do so, we examine the probability
density functions to the corresponding stochastic models and investigate in
what way they can be mapped one to another via integral transforms. Our
theoretical findings offer a new insight view into the particular categories of
variability and it confirms that, despite their contrasting nature, the
mathematical formalization of internal and external variability are strikingly
similar.
Mathematical model of galactose regulation and metabolic consumption in yeast
Date: 2016-02-11 00:00:00

The galactose network is a complex system responsible for galactose
metabolism. It has been extensively studied experimentally and mathematically
at the unicellular level to broaden our understanding of its regulatory
mechanisms at higher order species. Although the key molecular players involved
in the metabolic and regulatory processes underlying this system have been
known for decades, their interactions and chemical kinetics remain incompletely
understood. Mathematical models can provide an alternative method to study the
dynamics of this network from a quantitative and a qualitative perspective.
Here, we employ such approaches to unravel the main properties of the galactose
network, including equilibrium binary and temporal responses, as a way to
decipher its adaptation to actively-changing inputs. We combine the two main
components of the network; namely, the genetic branch which allows for bistable
responses, and a metabolic branch, encompassing the relevant metabolic
processes and glucose repressive reactions. We use both computational tools to
estimate model parameters based on published experimental data, as well as
bifurcation analysis to decipher the properties of the system in various
parameter regimes. Our model analysis reveals that the interplay between the
inducer (galactose) and the repressor (glucose) creates the bistability regime
which dictates the temporal responses of the system. Based on the same
bifurcation techniques, we can also explain why the system is robust to genetic
mutations and molecular instabilities. These findings may provide
experimentalists with a theoretical framework upon which they can determine how
the galactose network functions under various conditions.
Modelling intensities of order flows in a limit order book
Date: 2016-02-12 00:00:00
Tasks: Point Processes

We propose a parametric model for the simulation of limit order books. We
assume that limit orders, market orders and cancellations are submitted
according to point processes with state-dependent intensities. We propose new
functional forms for these intensities, as well as new models for the placement
of limit orders and cancellations. For cancellations, we introduce the concept
of "priority index" to describe the selection of orders to be cancelled in the
order book. Parameters of the model are estimated using likelihood
maximization. We illustrate the performance of the model by providing extensive
simulation results, with a comparison to empirical data and a standard Poisson
reference.
Maximum likelihood estimates of pairwise rearrangement distances
Date: 2017-04-14 00:00:00

Accurate estimation of evolutionary distances between taxa is important for
many phylogenetic reconstruction methods. In the case of bacteria, distances
can be estimated using a range of different evolutionary models, from single
nucleotide polymorphisms to large-scale genome rearrangements. In the case of
sequence evolution models (such as the Jukes-Cantor model and associated
metric) have been used to correct pairwise distances. Similar correction
methods for genome rearrangement processes are required to improve inference.
Current attempts at correction fall into 3 categories: Empirical computational
studies, Bayesian/MCMC approaches, and combinatorial approaches. Here we
introduce a maximum likelihood estimator for the inversion distance between a
pair of genomes, using the group-theoretic approach to modelling inversions
introduced recently. This MLE functions as a corrected distance: in particular,
we show that because of the way sequences of inversions interact with each
other, it is quite possible for minimal distance and MLE distance to
differently order the distances of two genomes from a third. This has obvious
implications for the use of minimal distance in phylogeny reconstruction. The
work also tackles the above problem allowing free rotation of the genome.
Generally a frame of reference is locked, and all computation made accordingly.
This work incorporates the action of the dihedral group so that distance
estimates are free from any a priori frame of reference.
A tool for computing diversity and consideration on differences between diversity indices
Date: 2016-02-12 00:00:00
Tasks: Diversity

Diversity represents a key concept in ecology, and there are various methods
of assessing it. The multitude of diversity indices are quite puzzling and
sometimes difficult to compute for a large volume of data. This paper promotes
a computational tool used to assess the diversity of different entities. The
BIODIV software is a user-friendly tool, developed using Microsoft Visual
Basic. It is capable to compute several diversity indices such as: Shannon,
Simpson, Pielou, Brillouin, Berger-Parker, McIntosh, Margalef, Menhinick and
Gleason. The software tool was tested using real data sets and the results were
analysed in order to make assumption on the indices behaviour. The results
showed a clear segregation of indices in two major groups with similar
expressivity.
Individual area and spatial distribution of saplings
Date: 2016-02-12 00:00:00

Forest regeneration is a spatial multifaceted process with numerous unknown
variables. The individual area or the area potentially available (APA) to an
individual plant embodies an idea widely used in population ecology but it has
fewer applications in forest research. It was used a Voronoi/ Thiessen
tessellation in order to determine the individual area of each sapling. The
study was conducted in a naturally regenerated area; using data collected from
over seven thousands saplings positioned in a network of permanent rectangular
sampling plots. The Voronoi/ Thiessen polygons were used to characterize
spatial pattern of sapling distribution as well as the competition relations
between the individuals. It is obvious that, at least from the mathematically
point of view, the Voronoi tessellation represents one of the best solutions to
determine neighbouring competitors of a tree. There were studied the
correlations between APA values and the main biometrical attributes, height
growth and competition indices. Furthermore, it is shown that APA coefficient
of variation is a straight-forward indicator with positive results as an
indicator of spatial pattern. The statistical significance of this indicator
was evaluated by comparing the results with the values of a 95% confidence
envelope generated by Monte-Carlo simulations. Two practical software tools
were produced using Visual Basic (VORONOI and ARIA VORONOI) in order to
simplify the analyses.
The Conformation of Interfacially Adsorbed Ranaspumin-2 is an Arrested State on the Unfolding Pathway
Date: 2016-02-12 00:00:00

Ranaspumin-2 (Rsn-2) is a surfactant protein found in the foam nests of the
t\'{u}ngara frog. Previous experimental work has led to a proposed model of
adsorption which involves an unusual clam shell-like `unhinging' of the protein
at an interface. Interestingly, there is no concomitant denaturation of the
secondary structural elements of Rsn-2 with the large scale transformation of
its tertiary structure. In this work we use both experiment and simulation to
better understand the driving forces underpinning this unusual process. We
develop a modified G\={o}-model approach where we have included explicit
representation of the side-chains in order to realistically model the
interaction between the secondary structure elements of the protein and the
interface. Doing so allows for the study of the underlying energy landscape
which governs the mechanism of Rsn-2 interfacial adsorption. Experimentally, we
study targeted mutants of Rsn-2, using the Langmuir trough, pendant drop
tensiometry and circular dichroism, to demonstrate that the clam-shell model is
correct. We find that Rsn-2 adsorption is in fact a two-step process: the
hydrophobic N-terminal tail recruits the protein to the interface after which
Rsn-2 undergoes an unfolding transition which maintains its secondary
structure. Intriguingly, our simulations show that the conformation Rsn-2
adopts at an interface is an arrested state along the denaturation pathway.
More generally, our computational model should prove a useful, and
computationally efficient, tool in studying the dynamics and energetics of
protein-interface interactions.
The Magnitude and Frequency Variations of Vector-Borne Infections Outbreaks with the Ross-Macdonald Model: Explaining and Predicting Outbreaks of Dengue Fever
Date: 2016-03-28 00:00:00

It is possible to model vector-borne infection using the classical
Ross-Macdonald model. This attempt, however fails in several respects. First,
using measured (or estimated) parameters, the model predicts a much greater
number of cases than what is usually observed. Second, the model predicts a
single huge outbreaks that is followed after decades of much smaller outbreaks.
This is not what is observed. Usually towns or cities report a number of cases
that recur for many years, even when environmental changes cannot explain the
disappearance of the infection in-between the peaks. In this paper we continue
to examine the pitfalls in modeling this class of infections, and explain that,
in fact, if properly used, the Ross-Macdonald model works, can be used to
understand the patterns of epidemics and even, to some extents, to make some
predictions. We model several outbreaks of dengue fever and show that the
variable pattern of year recurrence (or absence of it) can be understood and
explained by a simple Ross-Macdonald model modified to take into account human
movement across a range of neighborhoods inside a city. In addition, we analyze
the effect of seasonal variations in the parameters determining the number,
longevity and biting behavior of mosquitoes. Based on the size of the first
outbreak, we show that it is possible to estimate the proportion of the
remaining susceptibles and predict the likelihood and magnitude of eventual
subsequent outbreaks. The approach is exemplified by actual dengue outbreaks
with different recurrence patterns from some Brazilian regions.
Observing single FoF1-ATP synthase at work using an improved fluorescent protein mNeonGreen as FRET donor
Date: 2016-02-12 00:00:00

Adenosine triphosphate (ATP) is the universal chemical energy currency for
cellular activities provided mainly by the membrane enzyme FoF1-ATP synthase in
bacteria, chloroplasts and mitochondria. Synthesis of ATP is accompanied by
subunit rotation within the enzyme. Over the past 15 years we have developed a
variety of single-molecule FRET (smFRET) experiments to monitor catalytic
action of individual bacterial enzymes in vitro. By specifically labeling
rotating and static subunits within a single enzyme we were able to observe
three-stepped rotation in the F1 motor, ten-stepped rotation in the Fo motor
and transient elastic deformation of the connected rotor subunits. However, the
spatial and temporal resolution of motor activities measured by smFRET were
limited by the photophysics of the FRET fluorophores. Here we evaluate the
novel FRET donor mNeonGreen as a fusion to FoF1-ATP synthase and compare it to
the previously used fluorophore EGFP. Topics of this manuscript are the
biochemical purification procedures and the activity measurements of the fully
functional mutant enzyme.