pwc-archive/papers-with-abstracts huggingface dataset:
Nonparametric modeling cash flows of insurance company
Date: 2019-08-14 00:00:00
Tasks: Optical Character Recognition (OCR)

The paper proposes an original methodology for constructing quantitative
statistical models based on multidimensional distribution functions constructed
on the basis of the insurance companies' data on inshurance policies (including
policies with deductible) and claims incurred. Real data of some Russian
insurance companies on non-life insurance contracts illustrate some
opportunities of the proposed approach. The point and interval estimates of net
premium, claims frequency, claims reserves including IBNR and OCR, are thus
obtained. The resulting estimate of claims reserves falls in the range of
reasonable estimates calculated on the basis of traditional reserving methods
(the chain-ladder method, the frequency-severity method and the
Bornhuetter-Ferguson method).
  The proposed methodology is based on additive estimates of a company's
financial indicators, in the sense that they are calculated as a sum of
estimates built separately for each element of the sample (claim). This allows
using the proposed methodology to model insurance companies' financial flows
and, in particular, to solve the problems of reserve redistribution between
particular segments of insurance portfolio and/or time intervals; to adjust
risk as part of financial reporting under IAS 17 Insurance Contracts; and to
deal with many other tasks.
  The accuracy of insurance companies' financial parameters estimate based on
the proposed methods was tested by statistical modeling. IBNR was used as the
test parameter. The modeling results showed a satisfactory accuracy of the
proposed reserve estimates.
Stability Analysis of a Bulk-Surface Reaction Model for Membrane-Protein Clustering
Authors: L. M. Stolerman, M. Getz, S. G. Llewellyn Smith, M. Holst, P. Rangamani
Date: 2019-08-14 00:00:00
Tasks: Clustering

Protein aggregation on the plasma membrane (PM) is of critical importance to many cellular processes such as cell adhesion, endocytosis, fibrillar conformation, and vesicle transport. Lateral diffusion of protein aggregates or clusters on the surface of the PM plays an important role in governing their heterogeneous surface distribution. However, the stability behavior of the surface distribution of protein aggregates remains poorly understood. Therefore, understanding the spatial patterns that can emerge on the PM solely through protein-protein interaction, lateral diffusion, and feedback is an important step towards a complete description of the mechanisms behind protein clustering on the cell surface. In this work, we investigate the pattern formation of a reaction-diffusion model that describes the dynamics of a system of ligand-receptor complexes. The purely diffusive ligand in the cytosol can bind receptors in the PM, and the resultant ligand-receptor complexes not only diffuse laterally but can also form clusters resulting in different oligomers. Finally, the largest oligomers recruit ligands from the cytosol in a positive feedback. From a methodological viewpoint, we provide theoretical estimates for diffusion-driven instabilities of the protein aggregates based on the Turing mechanism. Our main result is a threshold phenomenon, in which a sufficiently high recruitment of ligands promotes the input of new monomeric components and consequently drives the formation of a single-patch spatially heterogeneous steady-state.
PMU Data Feature Considerations for Realistic, Synthetic Data Generation
Date: 2019-08-14 00:00:00
Tasks: Synthetic Data Generation

It is critical that the qualities and features of synthetically-generated,
PMU measurements used for grid analysis matches those of measurements obtained
from field-based PMUs. This ensures that analysis results generated by
researchers during grid studies replicate those outcomes typically expected by
engineers in real-life situations. In this paper, essential features associated
with industry PMU-derived data measurements are analyzed for input
considerations in the generation of vast amounts of synthetic power system
data. Inherent variabilities in PMU data as a result of the random dynamics in
power system operations, oscillatory contents, and the prevalence of bad data
are presented. Statistical results show that in the generation of large
datasets of synthetic, grid measurements, an inclusion of different data
anomalies, ambient oscillation contents, and random cases of missing data
samples due to packet drops helps to improve the realism of experimental data
used in power systems analysis.
Mobility restrictions for the control of epidemics: When do they work?
Date: 2019-08-14 00:00:00

Mobility restrictions - travel advisories, trade and travel bans, border
closures and, in extreme cases, area quarantines or cordons sanitaires - are
among the most widely used measures to control infectious diseases.
Restrictions of this kind were important in the response to epidemics of SARS
(2003), H1N1 influenza (2009), and Ebola (2014). However, they do not always
work as expected. The imposition of a cordon sanitaire to control the 2014 West
African Ebola outbreak, for example, is argued to have led to a
higher-than-expected number of cases in the quarantined area. To determine when
mobility restrictions reduce the size of an epidemic, we use a model of disease
transmission within and between economically heterogeneous locally connected
communities. One community comprises a low-risk, resource-rich, low-density
population with access to effective medical resources. The other comprises a
high-risk, resource-poor, high-density population without access to effective
medical resources. We find that the overall size of an epidemic centered in the
high-risk community is sensitive to the stringency of mobility restrictions
between the two communities. Unrestricted mobility between the two risk
communities increases the number of secondary cases in the low-risk community
but reduces the overall epidemic size. By contrast, the imposition of a cordon
sanitaire around the high-risk community reduces the number of secondary
infections in the low-risk community but increases the overall epidemic size.
The degree to which mobility restrictions increase or decrease the overall
epidemic size depends on the level of risk in each community and the
characteristics of the disease.
Joint phase reconstruction and magnitude segmentation from velocity-encoded MRI data
Date: 2019-08-14 00:00:00
Tasks: Segmentation

Velocity-encoded MRI is an imaging technique used in different areas to
assess flow motion. Some applications include medical imaging such as
cardiovascular blood flow studies, and industrial settings in the areas of
rheology, pipe flows, and reactor hydrodynamics, where the goal is to
characterise dynamic components of some quantity of interest. The problem of
estimating velocities from such measurements is a nonlinear dynamic inverse
problem. To retrieve time-dependent velocity information, careful mathematical
modelling and appropriate regularisation is required. In this work, we propose
an optimisation algorithm based on non-convex Bregman iteration to jointly
estimate velocity-, magnitude- and segmentation-information for the application
of bubbly flow imaging. Furthermore, we demonstrate through numerical
experiments on synthetic and real data that the joint model improves velocity,
magnitude and segmentation over a classical sequential approach.
Cooperative metabolic resource allocation in spatially-structured systems
Authors: David S. Tourigny
Date: 2019-08-14 00:00:00

Natural selection has shaped the evolution of cells and multi-cellular organisms such that social cooperation can often be preferred over an individualistic approach to metabolic regulation. This paper extends a framework for dynamic metabolic resource allocation based on the maximum entropy principle to spatiotemporal models of metabolism with cooperation. Much like the maximum entropy principle encapsulates `bet-hedging' behaviour displayed by organisms dealing with future uncertainty in a fluctuating environment, its cooperative extension describes how individuals adapt their metabolic resource allocation strategy to further accommodate limited knowledge about the welfare of others within a community. The resulting theory explains why local regulation of metabolic cross-feeding can fulfil a community-wide metabolic objective if individuals take into consideration an ensemble measure of total population performance as the only form of global information. The latter is likely supplied by quorum sensing in microbial systems or signalling molecules such as hormones in multi-cellular eukaryotic organisms.
Angular Resolution of Closely-Spaced Targets with Antenna Arrays
Date: 2019-08-14 00:00:00
Tasks: Translation

This is an English translation of Ulrich Nickel's PhD dissertation with the
original title "Winkelaufl\"osung eng benachbarter Ziele mit Gruppenantennen."
It describes maximum-likelihood angular superresolution of closely-spaced
targets. It also discusses estimating the number of targets present.
Laboratory biases hinder Eco-Evo-Devo integration: hints from the microworld
Date: 2019-08-14 00:00:00

How specific environmental contexts contribute to the robustness and
variation of developmental trajectories and evolutionary transitions is a
central point in Eco-Evo-Devo. However, the articulation of ecological,
evolutionary and developmental processes into integrative frameworks has been
elusive, partly because standard experimental designs neglect or oversimplify
ecologically meaningful contexts. Microbial models are useful to expose and
discuss two possible sources of bias associated with gene-centered experimental
designs: the use of laboratory strains and laboratory environmental conditions.
We illustrate our point by showing how contrasting developmental phenotypes in
Myxococcus xanthus depend on the joint variation of temperature and substrate
stiffness. Microorganismal development can provide key information for better
understanding the role of environmental conditions in the evolution of
developmental variation, and to overcome some of the limitations associated
with current experimental approaches.
Analysis of Various Transformer Structures for High Frequency Isolation Applications
Date: 2019-08-15 00:00:00
Tasks: Vocal Bursts Intensity Prediction

High frequency transformers are an integral part of power electronics devices
and their parasitic parameters influence the performance and efficiency of the
overall system. In this paper, transformer leakage inductances and parasitic
capacitances are analyzed using finite element method (FEM) for different
structures and windings arrangements of high frequency transformers. Also,
magnetic field, electric field, and voltage distribution within the transformer
is simulated and analyzed. Six different high frequency transformers with
toroidal, EE, and UU cores with different windings are investigated for a
400(V)/400(V), 8 kVA transformer operating at 10 kHz. Additionally, interleaved
windings for EE core are simulated and results compared with previous outcomes.
Analysis results will help categorize each structure, based on its balance
between leakage inductances and series parasitic capacitance. This information
can later be used for optimal selection of transformers as a function of their
operating frequency and enable designers to compromise between various
parameters in different applications, especially new fast switches such as SiC
and GaN.
Risk-neutral option pricing under GARCH intensity model
Authors: Kyungsub Lee
Date: 2019-08-15 00:00:00
Tasks: Clustering, model

The risk-neutral option pricing method under GARCH intensity model is examined. The GARCH intensity model incorporates the characteristics of financial return series such as volatility clustering, leverage effect and conditional asymmetry. The GARCH intensity option pricing model has flexibility in changing the volatility according to the probability measure change.
Why Finnish polytechnics reject top applicants
Date: 2019-08-15 00:00:00

I use a panel of higher education clearinghouse data to study the centralized
assignment of applicants to Finnish polytechnics. I show that on a yearly
basis, large numbers of top applicants unnecessarily remain unassigned to any
program. There are programs which rejected applicants would find acceptable,
but the assignment mechanism both discourages applicants from applying, and
stops programs from admitting those who do. A mechanism which would admit each
year's most eligible applicants has the potential to substantially reduce
re-applications, thereby shortening the long queues into Finnish higher
education.
Nonparametric Identification of First-Price Auction with Unobserved Competition: A Density Discontinuity Framework
Authors: Emmanuel Guerre, Yao Luo
Date: 2019-08-15 00:00:00

We consider nonparametric identification of independent private value first-price auction models, in which the analyst only observes winning bids. Our benchmark model assumes an exogenous number of bidders $N$. We show that, if the bidders observe $N$, the resulting discontinuities in the winning bid density can be used to identify the distribution of $N$. The private value distribution can be nonparametrically identified in a second step. This extends, under testable identification conditions, to the case where $N$ is a number of potential buyers, who bid with some unknown probability. Identification also holds in presence of additive unobserved heterogeneity drawn from some parametric distributions. A parametric Bayesian estimation procedure is proposed. An application to Shanghai Government IT procurements finds that the imposed three bidders participation rule is not effective. This generates loss in the range of as large as $10\%$ of the appraisal budget for small IT contracts.
When very slow is too fast -- collapse of a predator-prey system
Date: 2019-08-15 00:00:00

Critical transitions or regime shifts are sudden and unexpected changes in
the state of an ecosystem, that are usually associated with dangerous levels of
environmental change. However, recent studies show that critical transitions
can also be triggered by dangerous rates of environmental change. In contrast
to classical regime shifts, such rate-induced critical transitions do not
involve any obvious loss of stability, or a bifurcation, and thus cannot be
explained by the linear stability analysis. In this work, we demonstrate that
the well-known Rosenzweig-MacArthur predator-prey model can undergo a
rate-induced critical transition in response to a continuous decline in the
habitat quality, resulting in a collapse of the predator and prey populations.
Rather surprisingly, the collapse occurs even if the environmental change is
slower than the slowest process in the model. To explain this counterintuitive
phenomenon, we combine methods from geometric singular perturbation theory with
the concept of a moving equilibrium, and study critical rates of environmental
change with dependence on the initial state and the system parameters.
Moreover, for a fixed rate of environmental change, we determine the set of
initial states that undergo a rate-induced population collapse. Our results
suggest that ecosystems may be more sensitive to how fast environmental
conditions change than previously assumed. In particular, unexpected critical
transitions with dramatic ecological consequences can be triggered by
environmental changes that (i) do not exceed any dangerous levels, and (ii) are
slower than the natural timescales of the ecosystem. This poses an interesting
research question whether regime shifts observed in the natural world are
predominantly rate-induced or bifurcation-induced.
The inverted U-shaped effect of urban hotspots spatial compactness on urban economic growth
Date: 2019-08-15 00:00:00

The compact city, as a sustainable concept, is intended to augment the
efficiency of urban function. However, previous studies have concentrated more
on morphology than on structure. The present study focuses on urban structural
elements, i.e., urban hotspots consisting of high-density and high-intensity
socioeconomic zones, and explores the economic performance associated with
their spatial structure. We use nighttime luminosity (NTL) data and the Loubar
method to identify and extract the hotspot and ultimately draw two conclusions.
First, with population increasing, the hotspot number scales sublinearly with
an exponent of approximately 0.50~0.55, regardless of the location in China,
the EU or the US, while the intersect values are totally different, which is
mainly due to different economic developmental level. Secondly, we demonstrate
that the compactness of hotspots imposes an inverted U-shaped influence on
economic growth, which implies that an optimal compactness coefficient does
exist. These findings are helpful for urban planning.
Mean-variance hedging of unit linked life insurance contracts in a jump-diffusion model
Authors: Frank Bosserhoff, Mitja Stadje
Date: 2019-08-15 00:00:00

We consider a time-consistent mean-variance portfolio selection problem of an insurer and allow for the incorporation of basis (mortality) risk. The optimal solution is identified with a Nash subgame perfect equilibrium. We characterize an optimal strategy as solution of a system of partial integro-differential equations (PIDEs), a so called extended Hamilton-Jacobi-Bellman (HJB) system. We prove that the equilibrium is necessarily a solution of the extended HJB system. Under certain conditions we obtain an explicit solution to the extended HJB system and provide the optimal trading strategies in closed-form. A simulation shows that the previously found strategies yield payoffs whose expectations and variances are robust regarding the distribution of jump sizes of the stock. The same phenomenon is observed when the variance is correctly estimated, but erroneously ascribed to the diffusion components solely. Further, we show that differences in the insurance horizon and the time to maturity of a longevity asset do not add to the variance of the terminal wealth.
Probabilistic Verification in Mechanism Design
Authors: Ian Ball, Deniz Kattwinkel
Date: 2019-08-15 00:00:00
Tasks: Form

We introduce a model of probabilistic verification in mechanism design. The principal elicits a message from the agent and then selects a test to give the agent. The agent's true type determines the probability with which he can pass each test. We characterize whether each type has an associated test that best screens out all other types. If this condition holds, then the testing technology can be represented in a tractable reduced form. We use this reduced form to solve for profit-maximizing mechanisms with verification. As the verification technology varies, the solution continuously interpolates between the no-verification solution and full surplus extraction.
Using schematic models to understand the microscopic basis for inverted solubility in $\gamma$D-crystallin
Date: 2019-08-15 00:00:00

Inverted solubility--a crystal melting upon cooling--is observed in a handful
of proteins, such as carbomonoxy hemoglobin and $\gamma$D-crystallin. In human
$\gamma$D-crystallin, the phenomenon is associated with the mutation of the
23$^\mathrm{rd}$ residue, a proline, to a threonine, serine or valine. One
proposed microscopic mechanism for this effect entails an increase in
hydrophobicity upon mutagenesis. Recent crystal structures of a double mutant
that includes the P23T mutation allows for a more careful investigation of this
proposal. Here, we first measure the surface hydrophobicity of various mutant
structures of this protein and determine that it does not discernibly increase
upon the mutating the 23$^\mathrm{rd}$ residue. We then investigate the
solubility inversion regime with a schematic patchy particle model that
includes one of three models for temperature-dependent patch energies: two of
the hydrophobic effect, and a more generic description. We conclude that while
solubility inversion due to the hydrophobic effect may be possible, microscopic
evidence to support it in $\gamma$D-crystallin is weak. More generally, we find
that solubility inversion requires a fine balance between patch strengths and
the temperature-dependent contribution, which may explain why inverted
solubility is not commonly observed in proteins. In any event, we also find
that the temperature-dependent interaction has only a negligible impact on the
critical properties of the $\gamma$D-crystallin, in line with previous
experimental observations.
Fast Sub-millimeter Diffusion MRI using gSlider-SMS and SNR-Enhancing Joint Reconstruction
Date: 2019-08-15 00:00:00
Tasks: Denoising, Diffusion  MRI

We evaluate a new approach for achieving diffusion MRI data with high spatial
resolution, large volume coverage, and fast acquisition speed.
  A recent method called gSlider-SMS enables whole-brain sub-millimeter
diffusion MRI with high signal-to-noise ratio (SNR) efficiency. However,
despite the efficient acquisition, the resulting images can still suffer from
low SNR due to the small size of the imaging voxels. This work proposes to
mitigate the SNR problem by combining gSlider-SMS with a regularized
SNR-enhancing reconstruction approach.
  Illustrative results show that, from gSlider-SMS data acquired over a span of
only 25 minutes on a 3T scanner, the proposed method is able to produce 71 MRI
images (64 diffusion encoding orientations with $b=$1500 s/mm$^2$, and 7 images
without diffusion weighting) of the entire \emph{in vivo} human brain with
nominal 0.66 mm spatial resolution. Using data acquired from 75 minutes of
acquisition as a gold standard reference, we demonstrate that the proposed
SNR-ehancement procedure leads to substantial improvements in estimated
diffusion parameters compared to conventional gSlider reconstruction. Results
also demonstrate that the proposed method has advantages relative to denoising
methods based on low-rank matrix modeling. A theoretical analysis of the
trade-off between spatial resolution and SNR suggests that the proposed
approach has high efficiency.
  The combination of gSlider-SMS with advanced regularized reconstruction
enables high-resolution quantitative diffusion MRI from a relatively fast
acquisition.
Persistent Surveillance With Energy-Constrained UAVs and Mobile Charging Stations
Date: 2019-08-15 00:00:00

We address the problem of achieving persistent surveillance over an
environment by using energy-constrained unmanned aerial vehicles (UAVs), which
are supported by unmanned ground vehicles (UGVs) serving as mobile charging
stations. Specifically, we plan the trajectories of all vehicles and the
charging schedule of UAVs to minimize the long-term maximum age, where age is
defined as the time between two consecutive visits to regions of interest in a
partitioned environment. We introduce a scalable planning strategy based on 1)
creating UAV- UGV teams, 2) decomposing the environment into optimal partitions
that can be covered by any of the teams in a single fuel cycle, 3) uniformly
distributing the teams over a cyclic path traversing those partitions, and 4)
having the UAVs in each team cover their current partition and be transported
to the next partition while being recharged by the UGV. We show some results
related to the safety and performance of the proposed strategy.