pwc-archive/papers-with-abstracts huggingface dataset:
Optimal Resource Extraction in Regime Switching L\'evy Markets
Date: 2016-11-25 00:00:00

This paper studies the problem of optimally extracting nonrenewable natural
resource in light of various financial and economic restrictions and
constraints. Taking into account the fact that the market values of the main
natural resources i.e. oil, natural gas, copper,...,etc, fluctuate randomly
following global and seasonal macroeconomic parameters, these values are
modeled using Markov switching L\'evy processes. We formulate this problem as
finite-time horizon combined optimal stopping and optimal control problem. We
prove that the value function is the unique viscosity solution of the
corresponding Hamilton-Jacobi-Bellman equations. Moreover, we prove the
convergence of a finite difference approximation of the value function.
Numerical examples are presented to illustrate these results.
The impact of surface area, volume, curvature and Lennard-Jones potential to solvation modeling
Date: 2016-06-10 00:00:00

This paper explores the impact of surface area, volume, curvature and
Lennard-Jones potential on solvation free energy predictions. Rigidity surfaces
are utilized to generate robust analytical expressions for maximum, minimum,
mean and Gaussian curvatures of solvent-solute interfaces, and define a
generalized Poisson-Boltzmann (GPB) equation with a smooth dielectric profile.
Extensive correlation analysis is performed to examine the linear dependence of
surface area, surface enclosed volume, maximum curvature, minimum curvature,
mean curvature and Gaussian curvature for solvation modeling. It is found that
surface area and surfaces enclosed volumes are highly correlated to each
others, and poorly correlated to various curvatures for six test sets of
molecules. Different curvatures are weakly correlated to each other for six
test sets of molecules, but are strongly correlated to each other within each
test set of molecules. Based on correlation analysis, we construct twenty six
nontrivial nonpolar solvation models. Our numerical results reveal that the
Lennard-Jones (LJ) potential plays a vital role in nonpolar solvation modeling,
especially for molecules involving strong van der Waals interactions. It is
found that curvatures are at least as important as surface area or surface
enclosed volume in nonpolar solvation modeling. In conjugation with the GPB
model, various curvature based nonpolar solvation models are shown to offer
some of the best solvation free energy predictions for a wide range of test
sets. For example, root mean square errors from a model constituting surface
area, volume, mean curvature and LJ potential are less than 0.42 kcal/mol for
all test sets.
Study of human accessibility: physical tests versus numerical simulation
Date: 2015-12-22 00:00:00

Consideration of physical dimensions of the user population is essential to
design adapted environment. This variability in body dimensions (called
"anthropometry") is involved in design tools commonly used today to assess
user's accommodation (physical mock-ups, population models, database, boundary
manikins, hybrid methods or digital human modeling). Databases are created from
campaigns of measurement. Besides the fact that such measures are costly in
time and money, they give more "static" measures of man. They do not take into
account possible stretching limbs that could allow increased accessibility.
This paper presents a methodology for human body modeling, in a dynamic way,
not static. The methodology allows to highlight influences of design and human
behaviour on reach skills, directly induced by the interaction with real
prototypes and not just considered by human physical dimensions. The first part
of the method is to create a database of measurements (arms length, hip
breadth, etc.). From these data, a model of accessibility is proposed. The
accessibility field is determined purely numerically. In parallel, an
experiment is set up to measure the extension of the accessibility field, with
the same people. A comparison of the results is then performed and a new model
of the human body is proposed.
Sub-Story Detection in Twitter with Hierarchical Dirichlet Processes
Authors: Srijith P. K., Hepple Mark, Bontcheva Kalina, Preotiuc-Pietro Daniel
Date: 2016-06-11 00:00:00
Tasks: Clustering

Social media has now become the de facto information source on real world
events. The challenge, however, due to the high volume and velocity nature of
social media streams, is in how to follow all posts pertaining to a given event
over time, a task referred to as story detection. Moreover, there are often
several different stories pertaining to a given event, which we refer to as
sub-stories and the corresponding task of their automatic detection as
sub-story detection. This paper proposes hierarchical Dirichlet processes
(HDP), a probabilistic topic model, as an effective method for automatic
sub-story detection. HDP can learn sub-topics associated with sub-stories which
enables it to handle subtle variations in sub-stories. It is compared with
state- of-the-art story detection approaches based on locality sensitive
hashing and spectral clustering. We demonstrate the superior performance of HDP
for sub-story detection on real world Twitter data sets using various
evaluation measures. The ability of HDP to learn sub-topics helps it to recall
the sub- stories with high precision. Another contribution of this paper is in
demonstrating that the conversational structures within the Twitter stream can
be used to improve sub-story detection performance significantly.
Flexibility of short DNA helices under mechanical stretching
Date: 2016-06-11 00:00:00

The flexibility of short DNA fragments is studied by a Hamiltonian model
which treats the inter-strand and intra-strand forces at the level of the base
pair. The elastic response of a set of homogeneous helices to externally
applied forces is obtained by computing the average bending angles between
adjacent base pairs along the molecule axis. The ensemble averages are
performed over a room temperature equilibrium distribution of base pair
separations and bending fluctuations. The analysis of the end-to-end distances
and persistence lengths shows that even short sequences with less than $100$
base pairs maintain a significant bendability ascribed to thermal fluctuational
effects and kinks with large bending angles. The discrepancies between the
outcomes of the discrete model and those of the worm-like-chain model are
examined pointing out the inadequacy of the latter on short length scales.
Market Microstructure During Financial Crisis: Dynamics of Informed and Heuristic-Driven Trading
Date: 2016-06-11 00:00:00

We implement a market microstructure model including informed, uninformed and
heuristic-driven investors, which latter behave in line with loss-aversion and
mental accounting. We show that the probability of informed trading (PIN)
varies significantly during 2008. In contrast, the probability of
heuristic-driven trading (PH) remains constant both before and after the
collapse of Lehman Brothers. Cross-sectional analysis yields that, unlike PIN,
PH is not sensitive to size and volume effects. We show that heuristic-driven
traders are universally present in all market segments and their presence is
constant over time. Furthermore, we find that heuristic-driven investors and
informed traders are disjoint sets.
Balanced activation in a simple embodied neural simulation
Date: 2016-08-18 00:00:00

In recent years, there have been many computational simulations of
spontaneous neural dynamics. Here, we explore a model of spontaneous neural
dynamics and allow it to control a virtual agent moving in a simple
environment. This setup generates interesting brain-environment feedback
interactions that rapidly destabilize neural and behavioral dynamics and
suggest the need for homeostatic mechanisms. We investigate roles for both
local homeostatic plasticity (local inhibition adjusting over time to balance
excitatory input) as well as macroscopic task negative activity (that
compensates for task positive, sensory input) in regulating both neural
activity and resulting behavior (trajectories through the environment). Our
results suggest complementary functional roles for both local homeostatic
plasticity and balanced activity across brain regions in maintaining neural and
behavioral dynamics. These findings suggest important functional roles for
homeostatic systems in maintaining neural and behavioral dynamics and suggest a
novel functional role for frequently reported macroscopic task-negative
patterns of activity (e.g., the default mode network).
Incentivizing Resilience in Financial Networks
Date: 2017-06-23 00:00:00

When banks extend loans to each other, they generate a negative externality
in the form of systemic risk. They create a network of interbank exposures by
which they expose other banks to potential insolvency cascades. In this paper,
we show how a regulator can use information about the financial network to
devise a transaction-specific tax based on a network centrality measure that
captures systemic importance. Since different transactions have different
impact on creating systemic risk, they are taxed differently. We call this tax
a Systemic Risk Tax (SRT). We use an equilibrium concept inspired by the
matching markets literature to show analytically that this SRT induces a unique
equilibrium matching of lenders and borrowers that is systemic-risk efficient,
i.e. it minimizes systemic risk given a certain transaction volume. On the
other hand, we show that without this SRT multiple equilibrium matchings exist,
which are generally inefficient. This allows the regulator to effectively
stimulate a `rewiring' of the equilibrium interbank network so as to make it
more resilient to insolvency cascades, without sacrificing transaction volume.
Moreover, we show that a standard financial transaction tax (e.g. a Tobin-like
tax) has no impact on reshaping the equilibrium financial network because it
taxes all transactions indiscriminately. A Tobin-like tax is indeed shown to
have a limited effect on reducing systemic risk while it decreases transaction
volume.
Unravelling the Asymmetric Volatility Puzzle: A Novel Explanation of Volatility Through Anchoring
Date: 2016-06-11 00:00:00

This paper discusses a novel explanation for asymmetric volatility based on
the anchoring behavioral pattern. Anchoring as a heuristic bias causes
investors focusing on recent price changes and price levels, which two lead to
a belief in continuing trend and mean-reversion respectively. The empirical
results support our theoretical explanation through an analysis of large price
fluctuations in the S&P 500 and the resulting effects on implied and realized
volatility. These results indicate that asymmetry (a negative relationship)
between shocks and volatility in the subsequent period indeed exists. Moreover,
contrary to previous research, our empirical tests also suggest that implied
volatility is not simply an upward biased predictor of future deviation
compensating for the variance of the volatility but rather, due to investors
systematic anchoring to losses and gains in their volatility forecasts, it is a
co-integrated yet asymmetric over/under estimated financial instrument. We also
provide results indicating that the medium-term implied volatility (measured by
the VIX Index) is an unbiased though inefficient estimation of realized
volatility, while in contrast, the short-term volatility (measured by the
recently introduced VXST Index representing the 9-day implied volatility) is
also unbiased and yet efficient.
Modelling Early Transitions Toward Autonomous Protocells
Date: 2016-06-11 00:00:00

This thesis broadly concerns the origins of life problem, pursuing a joint
approach that combines general philosophical/conceptual reflection on the
problem along with more detailed and formal scientific modelling work oriented
in the conceptual perspective developed. The central subject matter addressed
is the emergence and maintenance of compartmentalised chemistries as precursors
of more complex systems with a proper cellular organization. Whereas an
evolutionary conception of life dominates prebiotic chemistry research and
overflows into the protocells field, this thesis defends that the 'autonomous
systems perspective' of living phenomena is a suitable - arguably the most
suitable - conceptual framework to serve as a backdrop for protocell research.
The autonomy approach allows a careful and thorough reformulation of the
origins of cellular life problem as the problem of how integrated autopoietic
chemical organisation, present in all full-fledged cells, originated and
developed from more simple far-from-equilibrium chemical aggregate systems.
The Structures, Functions, and Evolution of Sm-like Archaeal Proteins (SmAPs)
Date: 2016-06-11 00:00:00

Sm proteins were discovered nearly 20 years ago as a group of small antigenic
proteins ($\approx$ 90-120 residues). Since then, an extensive amount of
biochemical and genetic data have illuminated the crucial roles of these
proteins in forming ribonucleoprotein (RNP) complexes that are used in RNA
processing, e.g., spliceosomal removal of introns from pre-mRNAs. Spliceosomes
are large macromolecular machines that are comparable to ribosomes in size and
complexity, and are composed of uridine-rich small nuclear RNPs (U snRNPs).
Various sets of seven different Sm proteins form the cores of most snRNPs.
Despite their importance, very little is known about the atomic-resolution
structure of snRNPs or their Sm cores. As a first step towards a
high-resolution image of snRNPs and their hierarchic assembly, we have
determined the crystal structures of archaeal homologs of Sm proteins, which we
term Sm-like archaeal proteins (SmAPs).
Understanding the Results of Electrostatics Calculations: Visualizing Molecular 'Isopotential' Surfaces
Date: 2016-06-13 00:00:00

This document attempts to clarify potential confusion regarding
electrostatics calculations, specifically in the context of biomolecular
structure and specifically as regards the units typically used to
contour/visualize isopotential surfaces, potentials mapped onto molecular
solvent-accessible surfaces, etc.
A Mathematical Model of Cell Reprogramming due to Intermediate Differential Regulator's Regulations
Date: 2016-06-13 00:00:00

In this paper I have given a mathematical model of Cell reprogramming from a
different contexts. Here I considered there is a delay in differential
regulator rate equations due to intermediate regulator's regulations. At first
I gave some basic mathematical models by Ferell Jr.[2] of reprogramming and
after that I gave mathematical model of cell reprogramming by Mithun Mitra[4].
In the last section I contributed a mathematical model of cell reprogramming
from intermediate steps regulations and tried to find the critical point of
pluripotent cell.
Kolmogorov Space in Time Series Data
Date: 2016-06-10 00:00:00
Tasks: Time Series, Time Series Analysis

We provide the proof that the space of time series data is a Kolmogorov space
with $T_{0}$-separation axiom using the loop space of time series data. In our
approach we define a cyclic coordinate of intrinsic time scale of time series
data after empirical mode decomposition. A spinor field of time series data
comes from the rotation of data around price and time axis by defining a new
extradimension to time series data. We show that there exist hidden eight
dimensions in Kolmogorov space for time series data. Our concept is realized as
the algorithm of empirical mode decomposition and intrinsic time scale
decomposition and it is subsequently used for preliminary analysis on the real
time series data.
Myocardial Architecture and Patient Variability in Clinical Patterns of Atrial Fibrillation
Date: 2016-06-13 00:00:00
Tasks: Rhythm

Atrial fibrillation (AF) increases the risk of stroke by a factor of four to
five and is the most common abnormal heart rhythm. The progression of AF with
age, from short self-terminating episodes to persistence, varies between
individuals and is poorly understood. An inability to understand and predict
variation in AF progression has resulted in less patient-specific therapy.
Likewise, it has been a challenge to relate the microstructural features of
heart muscle tissue (myocardial architecture) with the emergent temporal
clinical patterns of AF. We use a simple model of activation wavefront
propagation on an anisotropic structure, mimicking heart muscle tissue, to show
how variation in AF behaviour arises naturally from microstructural differences
between individuals. We show that the stochastic nature of progressive
transversal uncoupling of muscle strands (e.g., due to fibrosis or gap
junctional remodelling), as occurs with age, results in variability in AF
episode onset time, frequency, duration, burden and progression between
individuals. This is consistent with clinical observations. The uncoupling of
muscle strands can cause critical architectural patterns in the myocardium.
These critical patterns anchor micro-re-entrant wavefronts and thereby trigger
AF. It is the number of local critical patterns of uncoupling as opposed to
global uncoupling that determines AF progression. This insight may eventually
lead to patient specific therapy when it becomes possible to observe the
cellular structure of a patient's heart.
The Sound of Silence: equilibrium filtering and optimal censoring in financial markets
Date: 2016-06-13 00:00:00

Following the approach of standard filtering theory, we analyse
investor-valuation of firms, when these are modelled as geometric-Brownian
state processes that are privately and partially observed, at random (Poisson)
times, by agents. Tasked with disclosing forecast values, agents are able
purposefully to withhold their observations; explicit filtering formulas are
derived for downgrading the valuations in the absence of disclosures. The
analysis is conducted for both a solitary firm and m co-dependent firms.
Birth-death processes with quenched uncertainty and intrinsic noise
Date: 2016-06-13 00:00:00

The dynamics of populations is frequently subject to intrinsic noise. At the
same time unknown interaction networks or rate constants can present quenched
uncertainty. Existing approaches often involve repeated sampling of the
quenched disorder and then running the stochastic birth-death dynamics on these
samples. In this paper we take a different view, and formulate an effective
jump process, representative of the ensemble of quenched interactions as a
whole. Using evolutionary games with random payoff matrices as an example, we
develop an algorithm to simulate this process, and we discuss diffusion
approximations in the limit of weak intrinsic noise.
Weak universality in sensory tradeoffs
Date: 2016-06-13 00:00:00

For many organisms, the number of sensory neurons is largely determined
during development, before strong environmental cues are present. This is
despite the fact that environments can fluctuate drastically both from
generation to generation and within an organism's lifetime. How can organisms
get by by hard-coding the number of sensory neurons? We approach this question
using rate-distortion theory. A combination of simulation and theory suggests
that when environments are large, the rate-distortion function---a proxy for
material costs, timing delays, and energy requirements---depends only on
coarse-grained environmental statistics that are expected to change on
evolutionary, rather than ontogenetic, timescales.
A revised model of fluid transport optimization in Physarum polycephalum
Date: 2016-06-14 00:00:00
Tasks: valid

Optimization of fluid transport in the slime mold Physarum polycephalum has
been the subject of several modeling efforts in recent literature. Existing
models assume that the tube adaptation mechanism in P. polycephalum's tubular
network is controlled by the sheer amount of fluid flow through the tubes. We
put forward the hypothesis that the controlling variable may instead be the
flow's pressure gradient along the tube. We carry out the stability analysis of
such a revised mathematical model for a parallel-edge network, proving that the
revised model supports the global flow-optimizing behavior of the slime mold
for a substantially wider class of response functions compared to previous
models. Simulations also suggest that the same conclusion may be valid for
arbitrary network topologies.
Characterization of protein complexes using chemical cross-linking coupled electrospray mass spectrometry
Date: 2016-06-14 00:00:00
Tasks: Cultural Vocal Bursts Intensity Prediction

Identification and characterization of large protein complexes is a mainstay
of biochemical toolboxes. Utilization of cross-linking chemicals can facilitate
the capture and identification of transient or weak interactions of a transient
nature. Here we describe a detailed methodology for cell culture based
proteomic approach. We describe the generation of cells stably expressing green
fluorescent protein (GFP)- tagged proteins under the tetracycline-inducible
promoter and subsequent proteomic analysis of GFP-interacting proteins. We
include a list of proteins that were identified as interactors of GFP.
Solving Backward Stochastic Differential Equations with quadratic-growth drivers by Connecting the Short-term Expansions
Date: 2018-05-23 00:00:00

This article proposes a new approximation scheme for quadratic-growth BSDEs
in a Markovian setting by connecting a series of semi-analytic asymptotic
expansions applied to short-time intervals. Although there remains a condition
which needs to be checked a posteriori, one can avoid altogether time-consuming
Monte Carlo simulation and other numerical integrations for estimating
conditional expectations at each space-time node. Numerical examples of
quadratic-growth as well as Lipschitz BSDEs suggest that the scheme works well
even for large quadratic coefficients, and a fortiori for large Lipschitz
constants.
Binding equilibrium and kinetics of membrane-anchored receptors and ligands in cell adhesion: insights from computational model systems and theory
Date: 2016-06-14 00:00:00

The adhesion of cell membranes is mediated by the binding of
membrane-anchored receptor and ligand proteins. In this article, we review
recent results from simulations and theory that lead to novel insights on how
the binding equilibrium and kinetics of these proteins is affected by the
membranes and by the membrane anchoring and molecular properties of the
proteins. Simulations and theory both indicate that the binding equilibrium
constant K2D and the on- and off-rate constants of anchored receptors and
ligands in their 'two-dimensional' (2D) membrane environment strongly depend on
the membrane roughness from thermally excited shape fluctuations on nanoscales.
Recent theory corroborated by simulations provides a general relation between
K2D} and the binding constant K3D of soluble variants of the receptors and
ligands that lack the membrane anchors and are free to diffuse in three
dimensions (3D).