pwc-archive/papers-with-abstracts huggingface dataset:
Depreciation and the Time Value of Money
Date: 2018-01-18 00:00:00

Generally accepted depreciation methods do not compute the intrinsic value of
an asset, as they do not factor for the Time Value of Money, a key principle
within financial theory. This is disadvantageous, as knowing the intrinsic
value of an asset can assist with making effective purchase and sale decisions.
  By applying the Time Value of Money principle to deprecation and book
valuation, methods can be formulated to approximate the intrinsic valuation of
a depreciable asset, which improves the capacity for buyers and sellers of
assets to make rational decisions.
  A deprecation method is formulated within, which aims to better match book
value with intrinsic value. While this method makes many assumptions and thus
has limitations, more complex formulas, which factor for a greater number of
variables, can be created using a similar approach, to produce better
approximations for intrinsic value.
Robustness of mathematical models and technical analysis strategies
Date: 2016-04-30 00:00:00

The aim of this paper is to compare the performances of the optimal strategy
under parameters mis-specification and of a technical analysis trading
strategy. The setting we consider is that of a stochastic asset price model
where the trend follows an unobservable Ornstein-Uhlenbeck process. For both
strategies, we provide the asymptotic expectation of the logarithmic return as
a function of the model parameters. Finally, numerical examples find that an
investment strategy using the cross moving averages rule is more robust than
the optimal strategy under parameters mis-specification.
An attempted replication of Hackl, Koster-Hale, Varvoutis (2012)
Date: 2016-04-30 00:00:00
Tasks: Object, Position

Hackl, Koster-Hale & Varvoutis (2012; Journal of Semantics, 29, 145-206; HKV)
provide data that suggested that in a null context,
antecedent-contained-deletion (ACD) relative clause structures modifying a
quantified object noun phrase are easier to process than those modifying a
definite object NP. HKV argue that this pattern of results supports a
quantifier-raising (QR) analysis of both ACD structures and quantified NPs in
object position: under the account that they advocate, both ACD resolution and
quantified NPs in object position require movement of the object NP to a higher
syntactic position. The processing advantage for quantified object NPs in ACD
is hypothesized to derive from the fact that - at the point where ACD
resolution must take place - the quantified NP has already undergone QR whereas
this is not the case for definite NPs. Here, we report attempted replications
of their self-paced reading Experiments 1 and 2. We do not replicate the
critical interactions in any of the words immediately following the
disambiguating verb in either experiment. Putting these observations together
with the observation that it was only post-hoc analysis decisions that were
responsible for HKV's observed effects in the first place (Gibson et al.,
submitted), we conclude that the experiments reported by HKV should not be
viewed as providing evidence for the ACD quantifier raising processing effect.
Effects of human dynamics on epidemic spreading in C\^{o}te d'Ivoire
Date: 2016-04-30 00:00:00
Tasks: Human Dynamics, Unity

Understanding and predicting outbreaks of contagious diseases are crucial to
the development of society and public health, especially for underdeveloped
countries. However, challenging problems are encountered because of complex
epidemic spreading dynamics influenced by spatial structure and human dynamics
(including both human mobility and human interaction intensity). We propose a
systematical model to depict nationwide epidemic spreading in C\^{o}te
d'Ivoire, which integrates multiple factors, such as human mobility, human
interaction intensity, and demographic features. We provide insights to aid in
modeling and predicting the epidemic spreading process by data-driven
simulation and theoretical analysis, which is otherwise beyond the scope of
local evaluation and geometrical views. We show that the requirement that the
average local basic reproductive number to be greater than unity is not
necessary for outbreaks of epidemics. The observed spreading phenomenon can be
roughly explained as a heterogeneous diffusion-reaction process by redefining
mobility distance according to the human mobility volume between nodes, which
is beyond the geometrical viewpoint. However, the heterogeneity of human
dynamics still poses challenges to precise prediction.
Permanence and Stability of a Kill the Winner Model in Marine Ecology
Date: 2016-07-21 00:00:00

We focus on the long term dynamics of "killing the winner" Lotka-Volterra
models of marine communities consisting of bacteria, virus, and zooplankton.
Under suitable conditions, it is shown that there is a unique equilibrium with
all populations present which is stable, the system is permanent, and the
limiting behavior of its solutions is strongly constrained.
Uniform asymptotic approximation of diffusion to a small target: generalized reaction models
Date: 2016-09-16 00:00:00

The diffusion of a reactant to a binding target plays a key role in many
biological processes. The reaction-radius at which the reactant and target may
interact is often a small parameter relative to the diameter of the domain in
which the reactant diffuses. We develop uniform in time asymptotic expansions
in the reaction-radius of the full solution to the corresponding diffusion
equations for two separate reactant-target interaction mechanisms: the Doi or
volume reactivity model, and the Smoluchowski-Collins-Kimball partial
absorption surface reactivity model. In the former, the reactant and target
react with a fixed probability per unit time when within a specified
separation. In the latter, upon reaching a fixed separation, they
probabilistically react or the reactant reflects away from the target.
Expansions of the solution to each model are constructed by projecting out the
contribution of the first eigenvalue and eigenfunction to the solution of the
diffusion equation, and then developing matched asymptotic expansions in
Laplace-transform space. Our approach offers an equivalent, but alternative,
method to the pseudo-potential approach we previously employed in [Isaacson and
Newby 2013] for the simpler Smoluchowski pure absorption reaction mechanism. We
find that the resulting asymptotic expansions of the diffusion equation
solutions are identical with the exception of one parameter: the diffusion
limited reaction rates of the Doi and partial absorption models. This
demonstrates that for biological systems in which the reaction-radius is a
small parameter, properly calibrated Doi and partial absorption models may be
functionally equivalent.
No-arbitrage and hedging with liquid American options
Date: 2018-01-25 00:00:00

Since most of the traded options on individual stocks is of American type it
is of interest to generalize the results obtained in semi-static trading to the
case when one is allowed to statically trade American options. However, this
problem has proved to be elusive so far because of the asymmetric nature of the
positions of holding versus shorting such options. Here we provide a unified
framework and generalize the fundamental theorem of asset pricing (FTAP) and
hedging dualities in arXiv:1502.06681 (to appear in Annals of Applied
Probability) to the case where the investor can also short American options.
Following arXiv:1502.06681, we assume that the longed American options are
divisible. As for the shorted American options, we show that the divisibility
plays no role regarding arbitrage property and hedging prices. Then using the
method of enlarging probability spaces proposed in arXiv:1604.05517, we convert
the shorted American options to European options, and establish the FTAP and
sub- and super-hedging dualities in the enlarged space both with and without
model uncertainty.
Electoral Systems Used around the World
Date: 2016-10-21 00:00:00

We give an overview of the diverse electoral systems used in local, national,
or super-national elections around the world. We discuss existing methods for
selecting single and multiple winners and give real-world examples for some
more elaborate systems. Eventually, we elaborate on some of the better known
strengths and weaknesses of various methods from both the theoretical and
practical points of view.
Flux-dependent graphs for metabolic networks
Date: 2018-03-28 00:00:00

Cells adapt their metabolic fluxes in response to changes in the environment.
We present a framework for the systematic construction of flux-based graphs
derived from organism-wide metabolic networks. Our graphs encode the
directionality of metabolic fluxes via edges that represent the flow of
metabolites from source to target reactions. The methodology can be applied in
the absence of a specific biological context by modelling fluxes
probabilistically, or can be tailored to different environmental conditions by
incorporating flux distributions computed through constraint-based approaches
such as Flux Balance Analysis. We illustrate our approach on the central carbon
metabolism of Escherichia coli and on a metabolic model of human hepatocytes.
The flux-dependent graphs under various environmental conditions and genetic
perturbations exhibit systemic changes in their topological and community
structure, which capture the re-routing of metabolic fluxes and the varying
importance of specific reactions and pathways. By integrating constraint-based
models and tools from network science, our framework allows the study of
context-specific metabolic responses at a system level beyond standard pathway
descriptions.
Is it "natural" to expect Economics to become a part of the Natural Sciences?
Date: 2016-05-13 00:00:00

We are in the middle of a complex debate as to whether Economics is really a
proper natural science. The 'Discussion & Debate' issue of this Euro. Phys. J.
Special Topic volume is: 'Can economics be a Physical Science?' I discuss some
aspects here.
Blink Rate Variability during resting and reading sessions
Date: 2016-04-13 00:00:00
Tasks: EEG, Electroencephalogram (EEG), Memorization

It has been shown that blinks occur not only to moisturize eyes and as a
defensive response to the environment, but are also caused by mental processes.
In this paper, we investigate statistical characteristics of blinks and blink
rate variability of 11 subjects. The subjects are presented with a
reading/memorization session preceded and followed by a resting session. EEG
signals were recorded during these sessions. The signals from the two front
electrodes were then analyzed, and times of the blinks were detected. We
discovered that compared to the resting sessions, reading session is
characterized by a lower number of blinks. However, there was no significant
difference in standard deviation in the blink rate variability. We also noticed
that in terms of complexity measures, the blink rate variability is located
somewhere in between white and pink noises, being closer to the white noise
during reading. We also found that the average of inter-blink intervals
increases during reading/memorization, thus longer inter-blink intervals could
be associated with a mental workload.
Rescaling of spatio-temporal sensing in eukaryotic chemotaxis
Date: 2016-10-25 00:00:00

Eukaryotic cells respond to a chemoattractant gradient by forming
intracellular gradients of signaling molecules that reflect the extracellular
chemical gradient - an ability called directional sensing. Quantitative
experiments have revealed two characteristic input-output relations of the
system: First, in a static chemoattractant gradient, the shapes of the
intracellular gradients of the signaling molecules are determined by the
relative steepness, rather than the absolute concentration, of the
chemoattractant gradient along the cell body. Second, upon a spatially
homogeneous temporal increase in the input stimulus, the intracellular
signaling molecules are transiently activated such that the response magnitudes
are dependent on fold changes of the stimulus, not on absolute levels. However,
the underlying mechanism that endows the system with these response properties
remains elusive. Here, by adopting a widely used modeling framework of
directional sensing, local excitation and global inhibition (LEGI), we propose
a hypothesis that the two rescaling behaviors stem from a single design
principle, namely, invariance of the governing equations to a scale
transformation of the input level. Analyses of the LEGI-based model reveal that
the invariance can be divided into two parts, each of which is responsible for
the respective response properties. Our hypothesis leads to an experimentally
testable prediction that a system with the invariance detects relative
steepness even in dynamic gradient stimuli as well as in static gradients.
Furthermore, we show that the relation between the response properties and the
scale invariance is general in that it can be implemented by models with
different network topologies.
Robust framework for quantifying the value of information in pricing and hedging
Date: 2018-03-30 00:00:00

We investigate asymmetry of information in the context of robust approach to
pricing and hedging of financial derivatives. We consider two agents, one who
only observes the stock prices and another with some additional information,
and investigate when the pricing--hedging duality for the former extends to the
latter. We introduce a general framework to express the superhedging and market
model prices for an informed agent. Our key insight is that an informed agent
can be seen as a regular agent who can restrict her attention to a certain
subset of possible paths. We use results of Hou & Ob\l\'oj on robust approach
with beliefs to establish the pricing--hedging duality for an informed agent.
Our results cover number of scenarios, including information arriving before
trading starts, arriving after static position in European options is formed
but before dynamic trading starts or arriving at some point before the
maturity. For the latter we show that the superhedging value satisfies a
suitable dynamic programming principle, which is of independent interest.
The large graph limit of a stochastic epidemic model on a dynamic multilayer network
Date: 2018-08-20 00:00:00

We consider an SIR-type (Susceptible $\to$ Infected $\to$ Recovered)
stochastic epidemic process with multiple modes of transmission on a contact
network. The network is given by a random graph following a multilayer
configuration model where edges in different layers correspond to potentially
infectious contacts of different types. We assume that the graph structure
evolves in response to the epidemic via activation or deactivation of edges. We
derive a large graph limit theorem that gives a system of ordinary differential
equations (ODEs) describing the evolution of quantities of interest, such as
the proportions of infected and susceptible vertices, as the number of nodes
tends to infinity. Analysis of the limiting system elucidates how the coupling
of edge activation and deactivation to infection status affects disease
dynamics, as illustrated by a two-layer network example with edge types
corresponding to community and healthcare contacts. Our theorem extends some
earlier results deriving the deterministic limit of stochastic SIR processes on
static, single-layer configuration model graphs. We also describe precisely the
conditions for equivalence between our limiting ODEs and the systems obtained
via pair approximation, which are widely used in the epidemiological and
ecological literature to approximate disease dynamics on networks. Potential
applications include modeling Ebola dynamics in West Africa, which was the
motivation for this study.
Feedback Between Motion and Sensation Provides Nonlinear Boost in Run-and-tumble Navigation
Date: 2017-02-22 00:00:00
Tasks: Navigate

Many organisms navigate gradients by alternating straight motions (runs) with
random reorientations (tumbles), transiently suppressing tumbles whenever
attractant signal increases. This induces a functional coupling between
movement and sensation, since tumbling probability is controlled by the
internal state of the organism which, in turn, depends on previous signal
levels. Although a negative feedback tends to maintain this internal state
close to adapted levels, positive feedback can arise when motion up the
gradient reduces tumbling probability, further boosting drift up the gradient.
Importantly, such positive feedback can drive large fluctuations in the
internal state, complicating analytical approaches. Previous studies focused on
what happens when the negative feedback dominates the dynamics. By contrast, we
show here that there is a large portion of physiologically-relevant parameter
space where the positive feedback can dominate, even when gradients are
relatively shallow. We demonstrate how large transients emerge because of
non-normal dynamics (non-orthogonal eigenvectors near a stable fixed point)
inherent in the positive feedback, and further identify a fundamental
nonlinearity that strongly amplifies their effect. Most importantly, this
amplification is asymmetric, elongating runs in favorable directions and
abbreviating others. The result is a "ratchet-like" gradient climbing behavior
with drift speeds that can approach half the maximum run speed of the organism.
Our results thus show that the classical drawback of run-and-tumble navigation
--- wasteful runs in the wrong direction --- can be mitigated by exploiting the
non-normal dynamics implicit in the run-and-tumble strategy.
Target shape dependence in a simple model of receptor-mediated endocytosis and phagocytosis
Date: 2016-05-10 00:00:00

Phagocytosis and receptor-mediated endocytosis are vitally important particle
uptake mechanisms in many cell types, ranging from single-cell organisms to
immune cells. In both processes, engulfment by the cell depends critically on
both particle shape and orientation. However, most previous theoretical work
has focused only on spherical particles and hence disregards the wide-ranging
particle shapes occurring in nature, such as those of bacteria. Here, by
implementing a simple model in one and two dimensions, we compare and contrast
receptor-mediated endocytosis and phagocytosis for a range of biologically
relevant shapes, including spheres, ellipsoids, capped cylinders, and
hourglasses. We find a whole range of different engulfment behaviors with some
ellipsoids engulfing faster than spheres, and that phagocytosis is able to
engulf a greater range of target shapes than other types of endocytosis.
Further, the 2D model can explain why some nonspherical particles engulf
fastest (not at all) when presented to the membrane tip-first (lying flat). Our
work reveals how some bacteria may avoid being internalized simply because of
their shape, and suggests shapes for optimal drug delivery.
A Passage-of-time Model of the Cerebellar Purkinje Cell
Date: 2016-05-12 00:00:00

The cerebellar Purkinje cell controlling eyeblinks can learn, remember and
reproduce the interstimulus interval in a classical conditioning paradigm.
Given temporally separated inputs, the cerebellar Purkinje cell learns to pause
its tonic inhibition of a motor pathway with high temporal precision so that an
overt blink occurs at the right time. Most models relegate the Purkinje cell's
passage-of-time representation to afferent granule cells, a subpopulation of
which is supposedly selected for synaptic depression in order to make the
Purkinje cell pause. However, granule cell models have recently faced two
crucial challenges: 1) bypassing granule cells and directly stimulating the
Purkinje cell's pre-synaptic fibers during training still produces a well-timed
pause, and 2) the Purkinje cell can reproduce the learned pause, invariant to
the temporal structure of probe stimulation. Here, we present a passage-of-time
model which is internal to the Purkinje cell and is invariant to probe
structure. The model accurately simulates the Purkinje cell learning mechanism
and makes testable electrophysiological predictions. Importantly, the model is
a numerical proof-of-principle for a biological learning mechanism which does
not rely on changes of synaptic strength.
Metabolite transport through glial networks stabilizes the dynamics of learning
Date: 2016-05-10 00:00:00

Learning and memory are acquired through long-lasting changes in synapses. In
the simplest models, such synaptic potentiation typically leads to runaway
excitation, but in reality there must exist processes that robustly preserve
overall stability of the neural system dynamics. How is this accomplished?
Various approaches to this basic question have been considered. Here we propose
a particularly compelling and natural mechanism for preserving stability of
learning neural systems. This mechanism is based on the global processes by
which metabolic resources are distributed to the neurons by glial cells.
Specifically, we introduce and study a model comprised of two interacting
networks: a model neural network interconnected by synapses which undergo
spike-timing dependent plasticity (STDP); and a model glial network
interconnected by gap junctions which diffusively transport metabolic resources
among the glia and, ultimately, to neural synapses where they are consumed. Our
main result is that the biophysical constraints imposed by diffusive transport
of metabolic resources through the glial network can prevent runaway growth of
synaptic strength, both during ongoing activity and during learning. Our
findings suggest a previously unappreciated role for glial transport of
metabolites in the feedback control stabilization of neural network dynamics
during learning.
Steric effects induce geometric remodeling of actin bundles in filopodia
Date: 2016-05-10 00:00:00

Filopodia are ubiquitous fingerlike protrusions, spawned by many eukaryotic
cells, to probe and interact with their environments. Polymerization dynamics
of actin filaments, comprising the structural core of filopodia, largely
determine their instantaneous lengths and overall lifetimes. The polymerization
reactions at the filopodial tip require transport of G-actin, which enter the
filopodial tube from the filopodial base and diffuse toward the filament barbed
ends near the tip. Actin filaments are mechanically coupled into a tight bundle
by cross-linker proteins. Interestingly, many of these proteins are relatively
short, restricting the free diffusion of cytosolic G-actin throughout the
bundle and, in particular, its penetration into the bundle core. To investigate
the effect of steric restrictions on G-actin diffusion by the porous structure
of filopodial actin filament bundle, we used a particle-based stochastic
simulation approach. We discovered that excluded volume interactions result in
partial and then full collapse of central filaments in the bundle, leading to a
hollowed-out structure. The latter may further collapse radially due to the
activity of cross-linking proteins, hence producing conical-shaped filament
bundles. Interestingly, electron microscopy experiments on mature filopodia
indeed frequently reveal actin bundles that are narrow at the tip and wider at
the base. Overall, our work demonstrates that excluded volume effects in the
context of reaction-diffusion processes in porous networks may lead to
unexpected geometric growth patterns and complicated, history-dependent
dynamics of intermediate metastable configurations.