pwc-archive/papers-with-abstracts huggingface dataset:
The role of physiological complexity changes in resting-state EEG in clinical effectiveness of rTMS and tDCS in treatments of resistant depression
Date: 2019-03-25 00:00:00
Tasks: EEG, Electroencephalogram (EEG)

The present literature about possible mechanisms behind the effectivity of
noninvasive electromagnetic stimulation in major depressive disorder (MDD) is
not very rich. Despite extensive research in applications for clinical
practice, the exact effects are yet not clear. We are comparing our previous
results about the complexity changes induced by repetitive Transcranial
Magnetic Stimulation (rTMS), and transcranial direct current stimulation (tDCS)
which are known to modulate neural dynamics. Also, we are reviewing different
biomarkers of complexity changes connected to depression, and how they change
with the stimulation. TDCS is low-intensity TES, known to have polarity
specific effects (neuromodulatory effects), and rTMS is inducing an electric
field in the tissue circumstantially via Faraday's law. Both nonlinear
modalities of electromagnetic stimulation may affect the levels of
physiological complexity in the brain. We also compare the changes of
complexity in electroencephalogram (EEG) and electrocardiogram (ECG), as
potential future predictors of therapy outcome.
Stacked Monte Carlo for option pricing
Date: 2019-03-26 00:00:00

We introduce a stacking version of the Monte Carlo algorithm in the context
of option pricing. Introduced recently for aeronautic computations, this simple
technique, in the spirit of current machine learning ideas, learns control
variates by approximating Monte Carlo draws with some specified function. We
describe the method from first principles and suggest appropriate fits, and
show its efficiency to evaluate European and Asian Call options in constant and
stochastic volatility models.
Asynchronous Ad Hoc Networks with Wireless Powered Cognitive Communications
Date: 2019-03-26 00:00:00
Tasks: Point Processes

Over the recent years, the proliferation of smart devices and their
applications has led to a rapid evolution of the concept of the Internet of
Things (IoT), advancing large scale machine type networks which are
characterized by sporadic transmissions of short packets. In contrast to
typical communication models and in order to capture a realistic IoT
environment, we study an asynchronous channel access performed by a primary ad
hoc network underlaid with a cognitive secondary wireless-powered ad hoc
network. Specifically, we consider that the primary transmitters are connected
to the power grid and employ asynchronous transmissions. On the other hand, the
cognitive secondary transmitters have radio frequency energy harvesting
capabilities, and their asynchronous channel access is established based on
certain energy and interference based criteria. We model this sporadic channel
traffic with time-space Poisson point processes and by using tools from
stochastic geometry, we provide an analytical framework for the performance of
this asynchronous system. In particular, we provide closed-form expressions for
the information coverage probability and the spatial throughput for both
networks and we derive the meta distribution of the
signal-to-interference-plus-noise ratio. Finally, we present numerical results
and provide important insights behind the main system parameters.
R\'eint\'egration des refus\'es en Credit Scoring
Date: 2019-03-21 00:00:00
Tasks: Credit score, es-en

The granting process of all credit institutions rejects applicants who seem
risky regarding the repayment of their debt. A credit score is calculated and
associated with a cut-off value beneath which an applicant is rejected.
Developing a new score implies having a learning dataset in which the response
variable good/bad borrower is known, so that rejects are de facto excluded from
the learning process. We first introduce the context and some useful notations.
Then we formalize if this particular sampling has consequences on the score's
relevance. Finally, we elaborate on methods that use not-financed clients'
characteristics and conclude that none of these methods are satisfactory in
practice using data from Cr\'edit Agricole Consumer Finance.
  -----
  Un syst\`eme d'octroi de cr\'edit peut refuser des demandes de pr\^et
jug\'ees trop risqu\'ees. Au sein de ce syst\`eme, le score de cr\'edit fournit
une valeur mesurant un risque de d\'efaut, valeur qui est compar\'ee \`a un
seuil d'acceptabilit\'e. Ce score est construit exclusivement sur des donn\'ees
de clients financ\'es, contenant en particulier l'information `bon ou mauvais
payeur', alors qu'il est par la suite appliqu\'e \`a l'ensemble des demandes.
Un tel score est-il statistiquement pertinent ? Dans cette note, nous
pr\'ecisons et formalisons cette question et \'etudions l'effet de l'absence
des non-financ\'es sur les scores \'elabor\'es. Nous pr\'esentons ensuite des
m\'ethodes pour r\'eint\'egrer les non-financ\'es et concluons sur leur
inefficacit\'e en pratique, \`a partir de donn\'ees issues de Cr\'edit Agricole
Consumer Finance.
Transmitter Diversity with Beam Steering
Date: 2019-10-15 00:00:00
Tasks: Diversity

Providing high data rates is one of the drivers in visible light
communication (VLC) systems. This paper introduces a VLC system that employs
transmitters diversity with beam steering to provide high data rates. In this
work, red, yellow, green, and blue (RYGB) laser diodes (LD) are used as
transmitters to obtain a high modulation bandwidth. Two types of RYGB LDs units
are used in this paper: transmitters diversity (TD) RYGB LDs light unit (for
illumination and communication) and RYGB LDs light unit (for illumination). In
addition, a seven branch angle diversity receiver (ADR) is used where we study
the delay spread and SNR. The proposed system was compared to the normal VLC
system. A data rate up to 22.8 Gb/s was achieved using simple on-off-keying
(OOK) modulation.
Visible Light Optical Data Centre Links
Date: 2019-03-26 00:00:00
Tasks: Diversity

Providing high data rates is one of the big concerns in visible light
communication (VLC) systems. This paper introduces a data centre design that
use a VLC system for downlink communication. In this work, RYGB laser diodes
(LD) are used as transmitters to obtain a high modulation bandwidth. Three
types of receivers, wide field of view receiver (WFOVR), 3 branches angle
diversity receiver (ADR) and 50 pixels imaging receiver (ImR) are used to
examine delay spread and SNR. The proposed system achieved data rates up to
14.2 Gbps using simple on-off-keying (OOK) modulation.
Label-free cell signaling pathway deconvolution of Angiotensin type 1 receptor reveals time-resolved G-protein activity and distinct AngII and AngIII\IV responses
Date: 2019-03-26 00:00:00

Angiotensin II (AngII) type 1 receptor (AT1R) is a G protein-coupled receptor
known for its role in numerous physiological processes and its implication in
many vascular diseases. Its functions are mediated through G protein dependent
and independent signaling pathways. AT1R has several endogenous peptidic
agonists, all derived from angiotensinogen, as well as several synthetic
ligands known to elicit biased signaling responses. Here, surface plasmon
resonance (SPR) was used as a cell- based and label-free technique to quantify,
in real time, the response of HEK293 cells stably expressing the human AT1R.
The goal was to take advantage of the integrative nature of this assay to
identify specific signaling pathways in the features of the response profiles
generated by numerous endogenous and synthetic ligands of AT1R. First, we
assessed the contributions of Gq, G12/13, Gi, Gbg, ERK1/2 and \b{eta}-
arrestins pathways in the cellular responses measured by SPR where Gq,
G12/Rho/ROCK together with \b{eta}-arrestins and ERK1/2 were found to play
significant roles. More specifically, we established a major role for G12 in
the early events of the AT1R-dependent response, which was followed by a robust
ERK1/2 component associated to the later phase of the signal. Interestingly,
endogenous AT1R ligands (AngII, AngIII and AngIV) exhibited distinct responses
signatures with a significant increase of the ERK1/2-like components for both
AngIII and AngIV, which points toward possibly distinct physiological roles for
the later. We also tested AT1R biased ligands, all of which affected both the
early and later events. Our results support SPR-based integrative cellular
assays as a powerful approach to delineate the contribution of specific
signaling pathways for a given cell response and reveal response differences
associated with ligands with distinct pharmacological properties.
Angiotensin II cyclic analogs as tools to investigate AT1R biased signaling mechanisms
Date: 2019-03-26 00:00:00

G protein coupled receptors (GPCRs) produce pleiotropic effects by their
capacity to engage numerous signaling pathways once activated. Functional
selectivity (also called biased signaling), where specific compounds can bring
GPCRs to adopt conformations that enable selective receptor coupling to
distinct signaling pathways, continues to be significantly investigated.
However, an important but often overlooked aspect of functional selectivity is
the capability of ligands such as angiotensin II (AngII) to adopt specific
conformations that may preferentially bind to selective GPCRs structures.
Understanding both receptor and ligand conformation is of the utmost importance
for the design of new drugs targeting GPCRs. In this study, we examined the
properties of AngII cyclic analogs to impart biased agonism on the angiotensin
type 1 receptor (AT1R). Positions 3 and 5 of AngII were substituted for
cysteine and homocysteine residues ([Sar1Hcy3,5]AngII, [Sar1Cys3Hcy5]AngII and
[Sar1Cys3,5]AngII) and the resulting analogs were evaluated for their capacity
to activate the Gq/11, G12, Gi2, Gi3, Gz, ERK and \b{eta}-arrestin (\b{eta}arr)
signaling pathways via AT1R. Interestingly, [Sar1Hcy3,5]AngII exhibited potency
and full efficacy on all pathways tested with the exception of the Gq pathway.
Molecular dynamic simulations showed that the energy barrier associated with
the insertion of residue Phe8 of AngII within the hydrophobic core of AT1R,
associated with Gq/11 activation, is increased with [Sar1Hcy3,5]AngII. These
results suggest that constraining the movements of molecular determinants
within a given ligand by introducing cyclic structures may lead to the
generation of novel ligands providing more efficient biased agonism.
Atom-specific persistent homology and its application to protein flexibility analysis
Date: 2019-03-26 00:00:00

Recently, persistent homology has had tremendous success in biomolecular data
analysis. It works by examining the topological relationship or connectivity of
a group of atoms in a molecule at a variety of scales, then rendering a family
of topological representations of the molecule. However, persistent homology is
rarely {employed} for the analysis of atomic properties, such as biomolecular
flexibility analysis or B factor prediction. This work introduces atom-specific
persistent homology to provide a local atomic level representation of a
molecule via a global topological tool. This is achieved through the
construction of a pair of conjugated sets of atoms and corresponding conjugated
simplicial complexes, as well as conjugated topological spaces. The difference
between the topological invariants of the pair of conjugated sets is measured
by Bottleneck and Wasserstein metrics and leads to an atom-specific topological
representation of individual atomic properties in a molecule. Atom-specific
topological features are integrated with various machine learning algorithms,
including gradient boosting trees and convolutional neural network for protein
thermal fluctuation analysis and B factor prediction. Extensive numerical
results indicate the proposed method provides a powerful topological tool for
analyzing and predicting localized information.
Practical Accuracy Limits of Radiation-Aware Magneto-Inductive 3D Localization
Date: 2019-03-28 00:00:00

The key motivation for the low-frequency magnetic localization approach is
that magnetic near-fields are well predictable by a free-space model, which
should enable accurate localization. Yet, limited accuracy has been reported
for practical systems and it is unclear whether the inaccuracies are caused by
field distortion due to nearby conductors, unconsidered radiative propagation,
or measurement noise. Hence, we investigate the practical performance limits by
means of a calibrated magnetoinductive system which localizes an active
single-coil agent with arbitrary orientation, using 4 mW transmit power at 500
kHz. The system uses eight single-coil anchors around a 3m x 3m area in an
office room. We base the location estimation on a complex baseband model which
comprises both reactive and radiative propagation. The link coefficients, which
serve as input data for location estimation, are measured with a multiport
network analyzer while the agent is moved with a positioner device. This
establishes a reliable ground truth for calibration and evaluation. The system
achieves a median position error of 3.2 cm and a 90th percentile of 8.3 cm.
After investigating the model error we conjecture that field distortion due to
conducting building structures is the main cause of the performance bottleneck.
The results are complemented with predictions on the achievable accuracy in
more suitable circumstances using the Cram\'er-Rao lower bound.
Waveguide-Fed Lens Based Beam-Steering Antenna For 5G Wireless Communications
Date: 2019-03-26 00:00:00

In this paper, a two-dimensional cylindrical Lens antenna based on the
parallel plate technique is designed. It supports beam-steering capability of
58 degree at 28 GHz. The antenna is composed of low loss rectangular waveguide
antennas, which are positioned around a homogeneous cylindrical Teflon lens in
the air region of two conducting parallel plates. The Beam scanning can be
achieved by switching between the antenna elements. The main advantages of our
design include its relative simplicity, ease of fabrication, and high-power
handling capability. Compared to previous works including a curvature
optimization for the plate separation of the parallel plates, the proposed
antenna has a constant distance between plates. At the 28 GHz, the maximum
simulated gain value is about 19 dB. Furthermore, the designed antenna only
deviates about 0.4 dB over the 58 degree scan range.
Dictionary Learning for Two-Dimensional Kendall Shapes
Date: 2020-01-11 00:00:00
Tasks: Dictionary Learning, Vocal Bursts Valence Prediction

We propose a novel sparse dictionary learning method for planar shapes in the
sense of Kendall, namely configurations of landmarks in the plane considered up
to similitudes. Our shape dictionary method provides a good trade-off between
algorithmic simplicity and faithfulness with respect to the nonlinear geometric
structure of Kendall's shape space. Remarkably, it boils down to a classical
dictionary learning formulation modified using complex weights. Existing
dictionary learning methods extended to nonlinear spaces either map the
manifold to a reproducing kernel Hilbert space or to a tangent space. The first
approach is unnecessarily heavy in the case of Kendall's shape space and causes
the geometrical understanding of shapes to be lost, while the second one
induces distortions and theoretical complexity. Our approach does not suffer
from these drawbacks. Instead of embedding the shape space into a linear space,
we rely on the hyperplane of centered configurations, including pre-shapes from
which shapes are defined as rotation orbits. In this linear space, the
dictionary atoms are scaled and rotated using complex weights before summation.
Furthermore, our formulation is more general than Kendall's original one: it
applies to discretely-defined configurations of landmarks as well as
continuously-defined interpolating curves. We implemented our algorithm by
adapting the method of optimal directions combined to a Cholesky-optimized
order recursive matching pursuit. An interesting feature of our shape
dictionary is that it produces visually realistic atoms, while guaranteeing
reconstruction accuracy. Its efficiency can mostly be attributed to a clear
formulation of the framework with complex numbers. We illustrate the strong
potential of our approach for the characterization of datasets of shapes up to
similitudes and the analysis of patterns in deforming 2D shapes.
Single-pixel imaging with origami pattern construction
Date: 2019-03-27 00:00:00
Tasks: Image Reconstruction

Single-pixel compressive imaging can recover images from a small amount of
measurements, offering many benefits especially for the scenes where the array
detection is unavailable. However, the widely used random patterns fail to
explore internal relations between the patterns and the image reconstruction.
Here we propose a single-pixel imaging method based on origami pattern
construction with a better imaging quality, but with less uncertainty of the
pattern sequence. It can decrease the sampling ratio even to 0.5\%, really
realizing super sub-Nyquist sampling. The experimental realization of this
approach is a big step forward toward the real-time compressive video
applications.
A general mathematical framework for understanding the behavior of heterogeneous stem cell regeneration
Authors: Jinzhi Lei
Date: 2019-03-27 00:00:00

Stem cell heterogeneity is essential for the homeostasis in tissue development. This paper established a general formulation for understanding the dynamics of stem cell regeneration with cell heterogeneity and random transitions of epigenetic states. The model generalizes the classical G0 cell cycle model, and incorporates the epigenetic states of stem cells that are represented by a continuous multidimensional variable and the kinetic rates of cell behaviors, including proliferation, differentiation, and apoptosis, that are dependent on their epigenetic states. Moreover, the random transition of epigenetic states is represented by an inheritance probability that can be described as a conditional beta distribution. This model can be extended to investigate gene mutation-induced tumor development. The proposed formula is a generalized formula that helps us to understand various dynamic processes of stem cell regeneration, including tissue development, degeneration, and abnormal growth.
Energy-efficient techniques for combating the influence of reactive jamming using Non-Orthogonal Multiple Access and Distributed Antenna Systems
Date: 2019-03-27 00:00:00

The aim of this work is to propose new approaches for maximizing the energy
efficiency of downlink 5G mobile communication systems, in the presence of a
reactive jammer. The concepts of non-orthogonal multiple access (NOMA) and
distributed antenna systems (DAS) are exploited to devise joint subband, power
and antenna assignment techniques, so as to guarantee a certain quality of
service (QoS) to users. Also, the scheduler relies on jamming statistics,
observed at the end of each timeslot, to perform resource allocation based on
the prediction of the jammer behavior over the next timeslot. A particular care
is given, in the proposed techniques, to maintain a moderate complexity at the
receiver level, and to limit the number of active RRHs (remote radio heads) in
the cell. Simulation results show that a proper combination of NOMA with DAS
can allow a significant enhancement of the system robustness to jamming, with
respect to centralized antenna systems and orthogonal multiple access.
PCL enzymatic hydrolysis: a mechanistic study
Date: 2019-03-27 00:00:00

Accumulation of plastic waste is a major environmental problem. Enzymes,
particularly esterases, play an important role in the biodegradation of
polyesters. These enzymes are usually only active on aliphatic polyesters, but
a few have showed catalytic activity for semi-aromatic polyesters. Due to the
importance of these processes, an atomic level characterization of how common
polyesters are degraded by esterases is necessary. Hereby, we present a
Molecular dynamics (MD) and Quantum Mechanics/Molecular Mechanics (QM/MM) MD
study of the hydrolysis of a model of polycaprolactone (PCL), one of the most
widely used biomaterials, by the thermophilic esterase from the archaeon
Archaeoglobus fulgidus (AfEST). This enzyme is particularly interesting because
it can withstand temperatures well above the glass transition of many
polyesters. Our insights about the reaction mechanism are important for the
design of customized enzymes able to degrade different synthetic polyesters.
Genetic drift in range expansions is very sensitive to density feedback in dispersal and growth
Date: 2019-03-27 00:00:00
Tasks: Diversity

Theory predicts rapid genetic drift during invasions, yet many expanding
populations maintain high genetic diversity. We find that genetic drift is
dramatically suppressed when dispersal rates increase with the population
density because many more migrants from the diverse, high-density regions
arrive at the expansion edge. When density-dependence is weak or negative, the
effective population size of the front scales only logarithmically with the
carrying capacity. The dependence, however, switches to a sublinear power law
and then to a linear increase as the density-dependence becomes strongly
positive. We develop a unified framework revealing that the transitions between
different regimes of diversity loss are controlled by a single, universal
parameter: the ratio of the expansion velocity to the geometric mean of
dispersal and growth rates at expansion edge. Our results suggest that positive
density-dependence could dramatically alter evolution in expanding populations
even when its contributions to the expansion velocity is small.
The minimum value of the Colless index
Date: 2019-07-23 00:00:00

The Colless index is one of the oldest and most widely used balance indices
for rooted bifurcating trees. Despite its popularity, its minimum value on the
space $\mathcal{T}_n$ of rooted bifurcating trees with $n$ leaves is only known
when $n$ is a power of 2. In this paper we fill this gap in the literature, by
providing a formula that computes, for each $n$, the minimum Colless index on
$\mathcal{T}_n$, and characterizing those trees where this minimum value is
reached.
Discounted optimal stopping of a Brownian bridge, with application to American options under pinning
Authors: Bernardo D'Auria, Eduardo García-Portugués, Abel Guada
Date: 2019-03-09 00:00:00

Mathematically, the execution of an American-style financial derivative is commonly reduced to solving an optimal stopping problem. Breaking the general assumption that the knowledge of the holder is restricted to the price history of the underlying asset, we allow for the disclosure of future information about the terminal price of the asset by modeling it as a Brownian bridge. This model may be used under special market conditions, in particular we focus on what in the literature is known as the "pinning effect", that is, when the price of the asset approaches the strike price of a highly-traded option close to its expiration date. Our main mathematical contribution is in characterizing the solution to the optimal stopping problem when the gain function includes the discount factor. We show how to numerically compute the solution and we analyze the effect of the volatility estimation on the strategy by computing the confidence curves around the optimal stopping boundary. Finally, we compare our method with the optimal exercise time based on a geometric Brownian motion by using real data exhibiting pinning.