pwc-archive/papers-with-abstracts huggingface dataset:
On the survival of poor peasants
Date: 2016-04-14 00:00:00

Previously, in underdeveloped countries, people tried to keep the prices of
food products artificially low, in order to help the poor to buy their food.
But it became soon clear that such system, although helpful for the city poor,
was disastrous for the peasants (who usually are even poorer), so that hunger
increased, instead of decreasing. More recently, thus, higher prices have been
imposed. But a high-price system does not solve the problems. It helps, indeed,
a peasant to buy in the city non-edible products, but not to buy (more
expensive) food products from other peasants. The question is discussed here in
more detail starting from the simplest conceivable case of two peasants
producing each a different food product (bread and cheese, say), then
generalizing to several food items and to any number of peasants producing a
given food item j. Like in every economic system which wants to be sustainable,
or able to reproduce itself in a stationary state at least, prices are
determined by the necessity of exchanging "means of production" among
"industries", except that here industriesare replaced by working peasants and
means of production are replaced by food. It is found that prices must obey
certain inequalities related to the minimal amount of each food item necessary
for survival. Inequalities may be rewritten as equations and, in an important
special case, such equations give rise to a simple version of the matrix
equation used by famous authors to describe the economy.
Convergence of Economic Growth and the Great Recession as Seen From a Celestial Observatory
Date: 2016-08-26 00:00:00

Macroeconomic theories of growth and wealth distribution have an outsized
influence on national and international social and economic policies. Yet, due
to a relative lack of reliable, system wide data, many such theories remain, at
best, unvalidated and, at worst, misleading. In this paper, we introduce a
novel economic observatory and framework enabling high resolution comparisons
and assessments of the distributional impact of economic development through
the remote sensing of planet earth's surface. Striking visual and empirical
validation is observed for a broad, global macroeconomic sigma-convergence in
the period immediately following the end of the Cold War. What is more, we
observe strong empirical evidence that the mechanisms driving sigma-convergence
failed immediately after the financial crisis and the start of the Great
Recession. Nevertheless, analysis of both cross-country and cross-state samples
indicates that, globally, disproportionately high growth levels and excessively
high decay levels have become rarer over time. We also see that urban areas,
especially concentrated within short distances of major capital cities were
more likely than rural or suburban areas to see relatively high growth in the
aftermath of the financial crisis. Observed changes in growth polarity can be
attributed plausibly to post-crisis government intervention and subsidy
policies introduced around the world. Overall, the data and techniques we
present here make economic evidence for the rise of China, the decline of U.S.
manufacturing, the euro crisis, the Arab Spring, and various, recent, Middle
East conflicts visually evident for the first time.
Chloroplast Genome Yields Unusual Seven-Cluster Structure C
Date: 2016-04-15 00:00:00

We studied the structuredness in a chloroplast genome of Siberian larch. The
clusters in 63-dimensional space were identified with elastic map technique,
where the objects to be clusterized are the different fragments of the genome.
A seven-cluster structure in the distribution of those fragments reported
previously has been found. Unlike the previous results, we have found the
drastically other composition of the clusters comprising the fragments
extracted from coding and non-coding regions of the genome.
Enabling Privacy-Preserving GWAS in Heterogeneous Human Populations
Date: 2016-04-15 00:00:00
Tasks: Privacy Preserving

The projected increase of genotyping in the clinic and the rise of large
genomic databases has led to the possibility of using patient medical data to
perform genomewide association studies (GWAS) on a larger scale and at a lower
cost than ever before. Due to privacy concerns, however, access to this data is
limited to a few trusted individuals, greatly reducing its impact on biomedical
research. Privacy preserving methods have been suggested as a way of allowing
more people access to this precious data while protecting patients. In
particular, there has been growing interest in applying the concept of
differential privacy to GWAS results. Unfortunately, previous approaches for
performing differentially private GWAS are based on rather simple statistics
that have some major limitations. In particular, they do not correct for
population stratification, a major issue when dealing with the genetically
diverse populations present in modern GWAS. To address this concern we
introduce a novel computational framework for performing GWAS that tailors
ideas from differential privacy to protect private phenotype information, while
at the same time correcting for population stratification. This framework
allows us to produce privacy preserving GWAS results based on two of the most
commonly used GWAS statistics: EIGENSTRAT and linear mixed model (LMM) based
statistics. We test our differentially private statistics, PrivSTRAT and
PrivLMM, on both simulated and real GWAS datasets and find that they are able
to protect privacy while returning meaningful GWAS results.
Inferring $R_0$ in emerging epidemics - the effect of common population structure is small
Date: 2016-04-15 00:00:00

When controlling an emerging outbreak of an infectious disease it is
essential to know the key epidemiological parameters, such as the basic
reproduction number $R_0$ and the control effort required to prevent a large
outbreak. These parameters are estimated from the observed incidence of new
cases and information about the infectious contact structures of the population
in which the disease spreads. However, the relevant infectious contact
structures for new, emerging infections are often unknown or hard to obtain.
Here we show that for many common true underlying heterogeneous contact
structures, the simplification to neglect such structures and instead assume
that all contacts are made homogeneously in the whole population, results in
conservative estimates for $R_0$ and the required control effort. This means
that robust control policies can be planned during the early stages of an
outbreak, using such conservative estimates of the required control effort.
Super-hedging American Options with Semi-static Trading Strategies under Model Uncertainty
Date: 2017-06-26 00:00:00

We consider the super-hedging price of an American option in a discrete-time
market in which stocks are available for dynamic trading and European options
are available for static trading. We show that the super-hedging price $\pi$ is
given by the supremum over the prices of the American option under randomized
models. That is, $\pi=\sup_{(c_i,Q_i)_i}\sum_ic_i\phi^{Q_i}$, where $c_i \in
\mathbb{R}_+$ and the martingale measure $Q^i$ are chosen such that $\sum_i
c_i=1$ and $\sum_i c_iQ_i$ prices the European options correctly, and
$\phi^{Q_i}$ is the price of the American option under the model $Q_i$. Our
result generalizes the example given in ArXiv:1604.02274 that the highest model
based price can be considered as a randomization over models.
Spatio-temporal Models of Lymphangiogenesis in Wound Healing
Date: 2016-04-15 00:00:00

Several studies suggest that one possible cause of impaired wound healing is
failed or insufficient lymphangiogenesis, that is the formation of new
lymphatic capillaries. Although many mathematical models have been developed to
describe the formation of blood capillaries (angiogenesis), very few have been
proposed for the regeneration of the lymphatic network. Lymphangiogenesis is a
markedly different process from angiogenesis, occurring at different times and
in response to different chemical stimuli. Two main hypotheses have been
proposed: 1) lymphatic capillaries sprout from existing interrupted ones at the
edge of the wound in analogy to the blood angiogenesis case; 2) lymphatic
endothelial cells first pool in the wound region following the lymph flow and
then, once sufficiently populated, start to form a network. Here we present two
PDE models describing lymphangiogenesis according to these two different
hypotheses. Further, we include the effect of advection due to interstitial
flow and lymph flow coming from open capillaries. The variables represent
different cell densities and growth factor concentrations, and where possible
the parameters are estimated from biological data. The models are then solved
numerically and the results are compared with the available biological
literature.
Brain and Cognitive Reserve: Translation via Network Control Theory
Date: 2017-01-17 00:00:00
Tasks: Translation

Traditional approaches to understanding the brain's resilience to
neuropathology have identified neurophysiological variables, often described as
brain or cognitive 'reserve,' associated with better outcomes. However,
mechanisms of function and resilience in large-scale brain networks remain
poorly understood. Dynamic network theory may provide a basis for substantive
advances in understanding functional resilience in the human brain. In this
perspective, we describe recent theoretical approaches from network control
theory as a framework for investigating network level mechanisms underlying
cognitive function and the dynamics of neuroplasticity in the human brain. We
describe the theoretical opportunities offered by the application of network
control theory at the level of the human connectome to understand cognitive
resilience and inform translational intervention.
On the Asymmetry of Vibrational Energy Flow
Date: 2016-04-16 00:00:00

A simple model to predict the directionality of vibrational energy flow at
molecular level is presented. This model is based on a vibrational energy
propagation analysis using ab intio molecular dynamics and the Fukui function
and local softness reactivity indexes derived from DFT. By using this simple
conceptual model we are giving a cogent rationale to previous theoretical and
experimental reports of asymmetrical vibrational energy diffusion in proteins
and energetic materials. We proposed here three basic rules for the Vibrational
Energy Relaxation in molecules: (i) the vibrational energy flows form a soft
site to a hard site but not in the opposite direction, (ii) when vibrational
energy is injected directly to a hard site, it is trapped in this site, and
(iii) if the vibrational energy is pump in a polarizable site and two sites
with different softness are available, the energy will propagate to the softest
one.
The space-clamped Hodgkin-Huxley system with random synaptic input: inhibition of spiking by weak noise and analysis with moment equations
Date: 2016-04-16 00:00:00

We consider a classical space-clamped Hodgkin-Huxley model neuron stimulated
by synaptic excitation and inhibition with conductances represented by
Ornstein-Uhlenbeck processes. Using numerical solutions of the stochastic model
system obtained by an Euler method, it is found that with excitation only there
is a critical value of the steady state excitatory conductance for repetitive
spiking without noise and for values of the conductance near the critical value
small noise has a powerfully inhibitory effect. For a given level of inhibition
there is also a critical value of the steady state excitatory conductance for
repetitive firing and it is demonstrated that noise either in the excitatory or
inhibitory processes or both can powerfully inhibit spiking. Furthermore, near
the critical value, inverse stochastic resonance was observed when noise was
present only in the inhibitory input process.
  The system of 27 coupled deterministic differential equations for the
approximate first and second order moments of the 6-dimensional model is
derived. The moment differential equations are solved using Runge-Kutta methods
and the solutions are compared with the results obtained by simulation for
various sets of parameters including some with conductances obtained by
experiment on pyramidal cells of rat prefrontal cortex. The mean and variance
obtained from simulation are in good agreement when there is spiking induced by
strong stimulation and relatively small noise or when the voltage is
fluctuating at subthreshold levels. In the occasional spike mode sometimes
exhibited by spinal motoneurons and cortical pyramidal cells the assunptions
underlying the moment equation approach are not satisfied.
Exploration of Contextuality in a Psychophysical Double-Detection Experiment
Date: 2016-08-24 00:00:00

The Contextuality-by-Default (CbD) theory allows one to separate
contextuality from context-dependent errors and violations of selective
influences (aka "no-signaling" or "no-disturbance" principles). This makes the
theory especially applicable to behavioral systems, where violations of
selective influences are ubiquitous. For cyclic systems with binary random
variables, CbD provides necessary and sufficient conditions for
noncontextuality, and these conditions are known to be breached in certain
quantum systems. We apply the theory of cyclic systems to a psychophysical
double-detection experiment, in which observers were asked to determine
presence or absence of a signal property in each of two simultaneously
presented stimuli. The results, as in all other behavioral and social systems
previous analyzed, indicate lack of contextuality. The role of context in
double-detection is confined to lack of selectiveness: the distribution of
responses to one of the stimuli is influenced by the state of the other
stimulus.
Testing Contextuality in Cyclic Psychophysical Systems of High Ranks
Date: 2016-08-24 00:00:00
Tasks: Vocal Bursts Intensity Prediction

The Contextuality-by-Default (CbD) theory allows one to separate
contextuality from context-dependent errors and violations of selective
influences (aka "no-signaling" or "no-disturbance" principles). This makes the
theory especially applicable to behavioral systems, where violations of
selective influences are ubiquitous. For cyclic systems with binary random
variables, CbD provides necessary and sufficient conditions for
noncontextuality, and these conditions are known to be breached in certain
quantum systems. We apply the theory of cyclic systems to a psychophysical
double-detection experiment, in which observers were asked to determine
presence or absence of a signal property in each of two simultaneously
presented stimuli. The results, as in all other behavioral and social systems
previous analyzed, indicate lack of contextuality. The role of context in
double-detection is confined to lack of selectiveness: the distribution of
responses to one of the stimuli is influenced by the state of the other
stimulus.
Solving the Equity Risk Premium Puzzle and Inching Towards a Theory of Everything
Date: 2019-09-17 00:00:00

The equity risk premium puzzle is that the return on equities has far
exceeded the average return on short-term risk-free debt and cannot be
explained by conventional representative-agent consumption based equilibrium
models. We review a few attempts done over the years to explain this anomaly:
1. Inclusion of highly unlikely events with low probability (Ugly state along
with Good and Bad), or market crashes / Black Swans. 2. Slow moving habit, or
time-varying subsistence level, added to the basic power utility function. 3. A
separation of the inter-temporal elasticity of substitution and risk aversion,
combined with long run risks which captures time varying economic uncertainty.
We explore whether a fusion of the above approaches supplemented with better
methods to handle the below reservations would provide a more realistic and yet
tractable framework to tackle the various conundrums in the social sciences: 1.
Unlimited ability of individuals to invest as compared to their ability to
consume. 2. Lack of an objective measuring stick of value 3. Unintended
consequences due to the dynamic nature of social systems 4. Relaxation of the
transversality condition to avoid the formation of asset price bubbles 5. How
durable is durable? Accounting for durable goods since nothing lasts forever
The world we live in produces fascinating phenomenon despite (or perhaps, due
to) being a hotchpotch of varying doses of the above elements. The rationale
for a unified theory is that beauty can emerge from chaos since the best test
for a stew is its taste. Many long standing puzzles seem to have been resolved
using different techniques. The various explanations need to stand the test of
time before acceptance; but then unexpected outcomes set in and new puzzles
emerge. As real analysis and limits tell us: We are getting Closer and Closer;
Yet it seems we are still Far Far Away...
Path integral approach to theories of diffusion-influenced reactions
Date: 2016-04-17 00:00:00

The path decomposition expansion represents the propagator of the
irreversible reaction as a convolution of the first-passage, last-passage and
rebinding time probability densities. Using path integral technique, we give an
elementary, yet rigorous, proof of the path decomposition expansion of the
Green's functions describing the non-reactive case and the irreversible
reaction of an isolated pair of molecules. To this end, we exploit the
connection between boundary value problems and interaction potential problems
with $\delta$- and $\delta'$-function perturbation. In particular, we employ a
known exact summation of a perturbation series to derive exact relations
between the Green's functions of the perturbed and unperturbed problem. Along
the way, we are able to derive a number of additional exact identities that
relate the propagators describing the free-space, the non-reactive as well as
the completely and partially reactive case.
Optimized Treatment Schedules for Chronic Myeloid Leukemia
Date: 2016-04-17 00:00:00

Over the past decade, several targeted therapies (e.g. imatinib, dasatinib,
nilotinib) have been developed to treat Chronic Myeloid Leukemia (CML). Despite
an initial response to therapy, drug resistance remains a problem for some CML
patients. Recent studies have shown that resistance mutations that preexist
treatment can be detected in a substan- tial number of patients, and that this
may be associated with eventual treatment failure. One proposed method to
extend treatment efficacy is to use a combination of multiple targeted
therapies. However, the design of such combination therapies (timing, sequence,
etc.) remains an open challenge. In this work we mathematically model the
dynamics of CML response to combination therapy and analyze the impact of
combination treatment schedules on treatment efficacy in patients with
preexisting resistance. We then propose an optimization problem to find the
best schedule of multiple therapies based on the evolution of CML according to
our ordinary differential equation model. This resulting optimiza- tion problem
is nontrivial due to the presence of ordinary different equation constraints
and integer variables. Our model also incorporates realistic drug toxicity
constraints by tracking the dynamics of patient neutrophil counts in response
to therapy. Using realis- tic parameter estimates, we determine optimal
combination strategies that maximize time until treatment failure.
Why Mutant Allele Frequencies in Oncogenes Peak Around 0.40 and Rapidly Decrease?
Date: 2016-04-25 00:00:00

The mutant allele frequencies in oncogenes peak around 0.40 and rapidly
decrease. In this article, we explain why this is the case. Invoking a key
result from mathematical analysis in our model, namely, the inverse function
theorem, we estimate the selection pressures of the mutations as a function of
germline allele frequencies. Under complete dominance of oncogenic mutations,
this selection function is expected to be linearly correlated with the
distribution of the mutant alleles. We demonstrate that this is the case by
investigating the allele frequencies of mutations in oncogenes across various
cancer types, validating our model for mean effective selection. Consistent
with the population genetics model of fitness, the selection function fits a
gamma distribution curve that accurately describes the trend of the mutant
allele frequencies. While existing equations for selection explain evolution at
low allele frequencies, our equations are general formulas for natural
selection under complete dominance operating at all frequencies. We show that
selection exhibits linear behavior at all times, favoring dominant alleles with
respect to the change in recessive allele frequency. Also, these equations
show, selection behaves like power-law against the recessive alleles at low
dominant allele frequency.
Universal asymptotic clone size distribution for general population growth
Date: 2016-10-26 00:00:00

Deterministically growing (wild-type) populations which seed stochastically
developing mutant clones have found an expanding number of applications from
microbial populations to cancer. The special case of exponential wild-type
population growth, usually termed the Luria-Delbr\"uck or Lea-Coulson model, is
often assumed but seldom realistic. In this article we generalise this model to
different types of wild-type population growth, with mutants evolving as a
birth-death branching process. Our focus is on the size distribution of clones
- that is the number of progeny of a founder mutant - which can be mapped to
the total number of mutants. Exact expressions are derived for exponential,
power-law and logistic population growth. Additionally for a large class of
population growth we prove that the long time limit of the clone size
distribution has a general two-parameter form, whose tail decays as a
power-law. Considering metastases in cancer as the mutant clones, upon
analysing a data-set of their size distribution, we indeed find that a
power-law tail is more likely than an exponential one.
Optimal Execution of Limit and Market Orders with Trade Director, Speed Limiter, and Fill Uncertainty
Date: 2017-04-12 00:00:00

We study the optimal execution of market and limit orders with permanent and
temporary price impacts as well as uncertainty in the filling of limit orders.
Our continuous-time model incorporates a trade speed limiter and a trader
director to provide better control on the trading rates. We formulate a
stochastic control problem to determine the optimal dynamic strategy for trade
execution, with a quadratic terminal penalty to ensure complete liquidation. In
addition, we identify conditions on the model parameters to ensure optimality
of the controls and finiteness of the associated value functions. For
comparison, we also solve the schedule-following optimal execution problem that
penalizes deviations from an order schedule. Numerical results are provided to
illustrate the optimal market and limit orders over time.