pwc-archive/papers-with-abstracts huggingface dataset:
Assessing Guaranteed Minimum Income Benefits and Rationality of Exercising Reset Options in Variable
Authors: Riley Jones, Adriana Ocejo
Date: 2019-11-14 00:00:00

A variable annuity is an equity-linked financial product typically offered by insurance companies. The policyholder makes an upfront payment to the insurance company and, in return, the insurer is required to make a series of payments starting at an agreed upon date. For a higher premium, many insurance companies offer additional guarantees or options which protect policyholders from various market risks. This research is centered around two of these options: the guaranteed minimum income benefit (GMIB) and the reset option. The sensitivity of various parameters on the value of the GMIB is explored, particularly the guaranteed payment rate set by the insurer. Additionally, a critical value for future interest rates is calculated to determine the rationality of exercising the reset option. This will be able to provide insight to both the policyholder and policy writer on how their future projections on the performance of the stock market and interest rates should guide their respective actions of exercising and pricing variable annuity options. This can help provide details into the value of adding options to a variable annuity for companies that are looking to make variable annuity policies more attractive in a competitive market.
Neutron Ghost Imaging
Date: 2019-11-13 00:00:00
Tasks: Position, Super-Resolution

Ghost imaging is demonstrated using a poly-energetic reactor source of
thermal neutrons. The method presented enables position resolution to be
incorporated, into a variety of neutron instruments that are not position
resolving. In an imaging context, ghost imaging can be beneficial for dose
reduction and resolution enhancement. We also demonstrate a super-resolution
variant of the method, namely a parallel form of neutron ghost imaging, with
the ability to significantly increase the spatial resolution of a pixelated
detector such as a CCD or CMOS camera. Extensions of our neutron ghost-imaging
protocol are discussed in detail and include neutron ghost tomography, neutron
ghost microscopy, dark-field neutron ghost imaging, and isotope-resolved color
neutron ghost imaging via prompt gamma-ray bucket detection.
Nonlinear reserving and multiple contract modifications in life insurance
Date: 2020-03-27 00:00:00

Life insurance cash flows become reserve dependent when contract conditions
are modified during the contract term on condition that actuarial equivalence
is maintained. As a result, insurance cash flows and prospective reserves
depend on each other in a circular way, and it is a non-trivial problem to
solve that circularity and make cash flows and prospective reserves
well-defined. In Markovian models, the (stochastic) Thiele equation and the
Cantelli Theorem are the standard tools for solving the circularity issue and
for maintaining actuarial equivalence. This paper expands the stochastic Thiele
equation and the Cantelli Theorem to non-Markovian frameworks and presents a
recursive scheme for the calculation of multiple contract modifications.
On Excessive Transverse Coordinates for Orbital Stabilization of Periodic Motions
Date: 2020-05-11 00:00:00

This paper explores transverse coordinates for the purpose of orbitally
stabilizing periodic motions of nonlinear, control-affine dynamical systems. It
is shown that the dynamics of any (minimal or excessive) set of transverse
coordinates, which are defined in terms of a particular parameterization of the
motion and a strictly state-dependent projection operator recovering the
parameterizing variable, admits a (transverse) linearization along the target
motion, with explicit expressions stated. Special focus is then placed on a
generic excessive set of orthogonal coordinates, revealing a certain limitation
of the "excessive" transverse linearization for the purpose of control design.
To overcome this limitation, a linear comparison system is introduced, and
conditions are stated for when the asymptotic stability of its origin
corresponds to the asymptotic stability of the origin of linearized transverse
dynamics. This allows for the construction of feedback controllers utilizing
this comparison system which, when implemented on the dynamical system, renders
the desired motion asymptotically stable in the orbital sense.
Resist or perish: fate of a microbial population subjected to a periodic presence of antimicrobial
Date: 2020-03-24 00:00:00

The evolution of antimicrobial resistance can be strongly affected by
variations of antimicrobial concentration. Here, we study the impact of
periodic alternations of absence and presence of antimicrobial on resistance
evolution in a microbial population, using a stochastic model that includes
variations of both population composition and size, and fully incorporates
stochastic population extinctions. We show that fast alternations of presence
and absence of antimicrobial are inefficient to eradicate the microbial
population and strongly favor the establishment of resistance, unless the
antimicrobial increases enough the death rate. We further demonstrate that if
the period of alternations is longer than a threshold value, the microbial
population goes extinct upon the first addition of antimicrobial, if it is not
rescued by resistance. We express the probability that the population is
eradicated upon the first addition of antimicrobial, assuming rare mutations.
Rescue by resistance can happen either if resistant mutants preexist, or if
they appear after antimicrobial is added to the environment. Importantly, the
latter case is fully prevented by perfect biostatic antimicrobials that
completely stop division of sensitive microorganisms. By contrast, we show that
the parameter regime where treatment is efficient is larger for biocidal drugs
than for biostatic drugs. This sheds light on the respective merits of
different antimicrobial modes of action.
Weak Monotone Comparative Statics
Authors: Yeon-Koo Che, Jinwoo Kim, Fuhito Kojima
Date: 2019-11-15 00:00:00

We develop a theory of monotone comparative statics based on weak set order -- in short, weak monotone comparative statics -- and identify the enabling conditions in the context of individual choices, Pareto optimal choices% for a coalition of agents, Nash equilibria of games, and matching theory. Compared with the existing theory based on strong set order, the conditions for weak monotone comparative statics are weaker, sometimes considerably, in terms of the structure of the choice environments and underlying preferences of agents. We apply the theory to establish existence and monotone comparative statics of Nash equilibria in games with strategic complementarities and of stable many-to-one matchings in two-sided matching problems, allowing for general preferences that accommodate indifferences and incompleteness.
Structural Controllability of Networked Relative Coupling Systems
Date: 2020-08-16 00:00:00
Tasks: All

This paper studies controllability of networked systems in which subsystems
are of general high-order linear dynamics and coupled through relative
variables (called networked relative coupling systems, NRCSs in abbreviation)
from a structure perspective. The purpose is to search conditions for subsystem
dynamics and network topologies under which, for almost all weights of the
subsystem interaction links the corresponding numerical NRCSs are controllable,
which is called structurally controllable. Three types of subsystem interaction
fashions are considered, which are 1) each subsystem is
single-input-single-output (SISO), 2) each subsystem is
multiple-input-multiple-output (MIMO), and the weights for all channels between
two subsystems are identical, and 3) each subsystem is MIMO, but different
channels between two subsystems can be weighted differently. We show that under
some necessary connectivity conditions, all parameter-dependent modes of the
NRCSs are generically controllable. We then give necessary and/or sufficient
conditions for structural controllability depending on subsystem dynamics and
the connectivity of network topologies in a decoupled form for all of the three
interaction fashions. We also discuss extending our results to handle certain
subsystem heterogeneities and show their direct applications in some practical
systems, including the mass-spring-damper systems and the power networks.
A Survey of Algorithms for Distributed Charging Control of Electric Vehicles in Smart Grid
Date: 2019-11-15 00:00:00
Tasks: Scheduling

Electric vehicles (EVs) are an eco-friendly alternative to vehicles with
internal combustion engines. Despite their environmental benefits, the massive
electricity demand imposed by the anticipated proliferation of EVs could
jeopardize the secure and economic operation of the power grid. Hence, proper
strategies for charging coordination will be indispensable to the future power
grid. Coordinated EV charging schemes can be implemented as centralized,
decentralized, and hierarchical systems, with the last two, referred to as
distributed charging control systems. This paper reviews the recent literature
of distributed charging control schemes, where the computations are distributed
across multiple EVs and/or aggregators. First, we categorize optimization
problems for EV charging in terms of operational aspects and cost aspects. Then
under each category, we provide a comprehensive discussion on algorithms for
distributed EV charge scheduling, considering the perspectives of the grid
operator, the aggregator, and the EV user. We also discuss how certain
algorithms proposed in the literature cope with various uncertainties inherent
to distributed EV charging control problems. Finally, we outline several
research directions that require further attention.
ANN-assisted CoSaMP Algorithm for Linear Electromagnetic Imaging of Spatially Sparse Domains
Authors: Ali I. Sandhu, Salman A. Shaukat, Abdulla Desmal, Hakan Bagci
Date: 2019-11-15 00:00:00

Greedy pursuit algorithms (GPAs) are widely used to reconstruct sparse signals. Even though many electromagnetic (EM) inverse scattering problems are solved on sparse investigation domains, GPAs have rarely been used for this purpose. This is because (i) they require a priori knowledge of the sparsity level in the investigation domain, which is often not available in EM imaging applications, and (ii) the EM scattering matrix does not satisfy the restricted isometric property. In this work, these challenges are respectively addressed by (i) using an artificial neural network (ANN) to estimate the sparsity level, and (ii) adding a Tikhonov regularization term to the diagonal elements of the scattering matrix. These enhancements permit the compressive sampling matching pursuit (CoSaMP) algorithm to be efficiently used to solve the two-dimensional EM inverse scattering problem, which is linearized using the Born approximation, on spatially sparse investigation domains. Numerical results, which demonstrate the efficiency and applicability of the proposed ANN-enhanced CoSaMP algorithm, are provided.
Longitudinal analysis of fetal MRI in patients with prenatal spina bifida repair
Date: 2019-11-15 00:00:00
Tasks: Super-Resolution

Open spina bifida (SB) is one of the most common congenital defects and can
lead to impaired brain development. Emerging fetal surgery methods have shown
considerable success in the treatment of patients with this severe anomaly.
Afterwards, alterations in the brain development of these fetuses have been
observed. Currently no longitudinal studies exist to show the effect of fetal
surgery on brain development. In this work, we present a fetal MRI
neuro-imaging analysis pipeline for fetuses with SB, including automated fetal
ventricle segmentation and deformation-based morphometry, and demonstrate its
applicability with an analysis of ventricle enlargement in fetuses with SB.
Using a robust super-resolution algorithm, we reconstructed fetal brains at
both pre-operative and post-operative time points and trained a U-Net CNN in
order to automatically segment the ventricles. We investigated the change of
ventricle shape post-operatively, and the impacts of lesion size, type, and GA
at operation on the change in ventricle shape. No impact was found, except for
moderately larger ventriculomegaly progression in myeloschisis patients.
Prenatal ventricle volume growth was also investigated. Our method allows for
the quantification of longitudinal morphological changes to fully quantify the
impact of prenatal SB repair and could be applied to predict postnatal
outcomes.
An approximate solution for the power utility optimization under predictable returns
Authors: Dmytro Ivasiuk
Date: 2019-11-15 00:00:00

This work derives an approximate analytical single period solution of the portfolio choice problem for the power utility function. It is possible to do so if we consider that the asset returns follow a multivariate normal distribution. It is shown in the literature that the log-normal distribution seems to be a good proxy of the normal distribution in case if the standard deviation of the last one is way smaller than its mean. So we can use this property because this happens to be true for gross portfolio returns. In addition, we present a different solution method that relies on the machine learning algorithm called Gradient Descent. It is a powerful tool to solve a wide range of problems, and it was possible to implement this approach to portfolio selection. Besides, the paper provides a simulation study, where we compare the derived results with the well-known solution, which uses a Taylor series expansion of the utility function.
Smart transformer Modelling in Optimal Power Flow Analysis
Date: 2019-11-14 00:00:00
Tasks: STS

The smart transformer (ST) implemented using power electronics converters,
has the capability of independent voltage control and reactive power isolation
between its primary and secondary terminals. This capability provides a
flexibility in the power system to support the voltage at the primary side and
control the demand at the secondary side. Using this flexibility, the system
power flow could, for example, be optimized for lower costs. This paper
proposes an ST model suitable for OPF analysis. The effects of using multiple
STs at different penetration levels, on the daily generation costs in an IEEE
39 bus test system are presented.
Large-Scale Survey of Cell-Differentiation Programs in a Generative Model Reveals Regeneration as an Epiphenomenon of Development
Date: 2019-12-29 00:00:00
Tasks: Diversity

Development combines three basic processes asymmetric --- cell division,
signaling and gene regulation --- in a multitude of ways to create an
overwhelming diversity of multicellular life-forms. Here, we attempt to chart
this diversity using a generative model. We sample millions of biologically
feasible developmental schemes, allowing us to comment on the statistical
properties of cell-differentiation trajectories they produce. Our results
indicate that, in contrast to common views, cell-type lineage graphs are
unlikely to be tree-like. Instead, they are more likely to be directed acyclic
graphs, with multiple lineages converging on the same terminal cell-type.
Additionally, in line with the hypothesis that whole body regeneration is an
epiphenomenon of development, a majority of the `organism' generated by our
model can regenerate using pluripotent cells. The generative framework is
modular and flexible, and can be adapted to test additional hypotheses about
general features of development.
New Approaches in Synthetic Biology: Abiotic Organelles and Artificial Cells Powered and Controlled by Light
Authors: Günther Knör
Date: 2019-11-15 00:00:00

One of the major goals of nanobionics and bottom-up synthetic biology is the development of artificial cell organelles for the creation of cell-like structures operating similar to biological systems with a minimalistic set of building blocks. In the present contribution, versatile strategies to develop artificial reaction centers for novel photoautotrophic processes and to provide fully biocompatible synthetic enzyme counterparts for stepwise sustrate photo-conversion in abiotic organelles are summarized. This unique approach has the potential to create artificial cell-like systems that can be readily manipulated by light providing both energy input and fundamental regulatory functions.
Cyber bonds and their pricing models
Date: 2019-11-15 00:00:00

Motivated by the developments in cyber risk treatment in the finance
industry, we propose a general framework of cyber bond, whose main purpose is
to insure (compensate) losses of a cyber attack. Based on a database of
publicly available cyber events, we determine cyber loss distribution
parameters and use them to numerically simulate cyber bond price, yield, and
other characteristics. We also consider two possible approaches to cyber bond
coupon calculation.
A Gridless Compressive Sensing Based Channel Estimation for Millimeter Wave MIMO OFDM Systems with One-Bit Quantization
Date: 2019-08-19 00:00:00
Tasks: Compressive Sensing, Quantization

This paper considers the problem of estimating the sparse mmWave massive
multiple input - multiple output (MIMO) OFDM channel from one-bit quantized
measurements. Unlike previous grid-based one-bit compressive sensing
approaches, we present a gridless convex method to recover sparse channel form
one-bit measurements via Binary Atomic Norm Minimization (BiANM) and Reweighted
Binary Atomic Norm Minimization (ReBiANM). Simulation results verify the
accuracy of the binary and reweighted binary atomic norm minimization
techniques.
An incremental scenario approach for building energy management with uncertain occupancy
Date: 2019-11-15 00:00:00
Tasks: energy management, Management

We deal with the problem of energy management in buildings subject to
uncertain occupancy. To this end, we formulate this as a finite horizon
optimization program and optimize with respect to the windows' blinds position,
radiator and cooling flux. Aiming at a schedule which is robust with respect to
uncertain occupancy levels while avoiding imposing arbitrary assumptions on the
underlying probability distribution of the uncertainty, we follow a data driven
paradigm. In particular, we apply an incremental scenario approach methodology
that has been recently proposed in the literature to our energy management
formulation. To demonstrate the efficacy of the proposed implementation we
provide a detailed numerical analysis on a stylized building and compare it
with respect to a deterministic design and the standard scenario approach
typically encountered in the literature. We show that our schedule is not
agnostic with respect to uncertainty as deterministic approaches, while it
requires fewer scenarios with respect to the standard scenario approach, thus
resulting in a less conservative performance.
A crossover code for high-dimensional composition
Date: 2019-11-15 00:00:00
Tasks: Vocal Bursts Intensity Prediction

We present a novel way to encode compositional information in
high-dimensional (HD) vectors. Inspired by chromosomal crossover, random HD
vectors are recursively interwoven, with a fraction of one vector's components
masked out and replaced by those from another using a context-dependent mask.
Unlike many HD computing schemes, "crossover" codes highly overlap with their
base elements' and sub-structures' codes without sacrificing relational
information, allowing fast element readout and decoding by greedy
reconstruction. Crossover is mathematically tractable and has several
properties desirable for robust, flexible representation.
X-ray Multimodal Intrinsic-Speckle-Tracking
Date: 2020-09-15 00:00:00
Tasks: Optical Flow Estimation, Position, Retrieval

We develop X-ray Multi-modal Intrinsic-Speckle-Tracking (MIST), a form of
X-ray speckle-tracking that is able to recover both the position-dependent
phase shift and the position-dependent small-angle X-ray scattering (SAXS)
signal of a phase object. MIST is based on combining a Fokker-Planck
description of paraxial X-ray optics, with an optical-flow formalism for X-ray
speckle-tracking. Only two images need to be taken in the presence of the
sample, corresponding to two different transverse positions of the
speckle-generating membrane, in order to recover both the refractive and
local-SAXS properties of the sample. Like the optical-flow X-ray
phase-retrieval method which it generalises, the MIST method implicitly rather
than explicitly tracks both the transverse motion and the diffusion of speckles
that is induced by the presence of a sample. Application to X-ray synchrotron
data shows the method to be efficient, rapid and stable.
Semiparametric Estimation of Correlated Random Coefficient Models without Instrumental Variables
Date: 2019-11-15 00:00:00

We study a linear random coefficient model where slope parameters may be
correlated with some continuous covariates. Such a model specification may
occur in empirical research, for instance, when quantifying the effect of a
continuous treatment observed at two time periods. We show one can carry
identification and estimation without instruments. We propose a semiparametric
estimator of average partial effects and of average treatment effects on the
treated. We showcase the small sample properties of our estimator in an
extensive simulation study. Among other things, we reveal that it compares
favorably with a control function estimator. We conclude with an application to
the effect of malaria eradication on economic development in Colombia.
Precise Spatial Memory in Local Random Networks
Date: 2019-11-16 00:00:00

Self-sustained, elevated neuronal activity persisting on time scales of ten
seconds or longer is thought to be vital for aspects of working memory,
including brain representations of real space. Continuous-attractor neural
networks, one of the most well-known modeling frameworks for persistent
activity, have been able to model crucial aspects of such spatial memory. These
models tend to require highly structured or regular synaptic architectures. In
contrast, we elaborate a geometrically-embedded model with a local but
otherwise random connectivity profile which, combined with a global regulation
of the mean firing rate, produces localized, finely spaced discrete attractors
that effectively span a 2D manifold. We demonstrate how the set of attracting
states can reliably encode a representation of the spatial locations at which
the system receives external input, thereby accomplishing spatial memory via
attractor dynamics without synaptic fine-tuning or regular structure. We
measure the network's storage capacity and find that the statistics of
retrievable positions are also equivalent to a full tiling of the plane,
something hitherto achievable only with (approximately) translationally
invariant synapses, and which may be of interest in modeling such biological
phenomena as visuospatial working memory in two dimensions.
The Creation and Validation of Load Time Series for Synthetic Electric Power Systems
Date: 2019-11-16 00:00:00
Tasks: Time Series, Time Series Analysis

Synthetic power systems that imitate functional and statistical
characteristics of the actual grid have been developed to promote researchers'
access to public system models. Developing time series to represent different
operating conditions of these synthetic systems will expand the potential of
synthetic power systems applications. This paper proposes a methodology to
create synthetic time series of bus-level load using publicly available data.
Comprehensive validation metrics are provided to assure that the quality of
synthetic time series data is sufficiently realistic. This paper also includes
an example application in which the methodology is used to construct load
scenarios for a 10,000-bus synthetic case.