pwc-archive/papers-with-abstracts huggingface dataset:
Estimating effective population size changes from preferentially sampled genetic sequences
Date: 2019-03-28 00:00:00

Coalescent theory combined with statistical modeling allows us to estimate
effective population size fluctuations from molecular sequences of individuals
sampled from a population of interest. When sequences are sampled serially
through time and the distribution of the sampling times depends on the
effective population size, explicit statistical modeling of sampling times
improves population size estimation. Previous work assumed that the genealogy
relating sampled sequences is known and modeled sampling times as an
inhomogeneous Poisson process with log-intensity equal to a linear function of
the log-transformed effective population size. We improve this approach in two
ways. First, we extend the method to allow for joint Bayesian estimation of the
genealogy, effective population size trajectory, and other model parameters.
Next, we improve the sampling time model by incorporating additional sources of
information in the form of time-varying covariates. We validate our new
modeling framework using a simulation study and apply our new methodology to
analyses of population dynamics of seasonal influenza and to the recent Ebola
virus outbreak in West Africa.
Short Selling with Margin Risk and Recall Risk
Date: 2019-03-28 00:00:00

Short sales are regarded as negative purchases in textbook asset pricing
theory. In reality, however, the symmetry between purchases and short sales is
broken by a variety of costs and risks peculiar to the latter. We formulate an
optimal stopping model in which the decision to cover a short position is
affected by two short sale-specific frictions---margin risk and recall risk.
Margin risk refers to the fact that short sales are collateralised
transactions, which means that short sellers may be forced to close out their
positions involuntarily if they cannot fund margin calls. Recall risk refers to
a peculiarity of the stock lending market, which permits lenders to recall
borrowed stock at any time, once again triggering involuntary close-outs. We
examine the effect of these frictions on the optimal close-out strategy and
quantify the loss of value resulting from each. Our results show that realistic
short selling constraints have a dramatic impact on the optimal behaviour of a
short seller, and are responsible for a substantial loss of value relative to
the first-best situation without them. This has implications for many familiar
no-arbitrage identities, which are predicated on the assumption of unfettered
short selling.
Inertial Sensor Aided mmWave Beam Tracking to Support Cooperative Autonomous Driving
Date: 2019-03-28 00:00:00
Tasks: Autonomous Driving

This paper presents an inertial sensor aided technique for beam alignment and
tracking in massive multiple-input multiple-output (MIMO) vehicle-to-vehicle
(V2V) communications based on millimeter waves (mmWave). Since directional
communications in vehicular scenarios are severely hindered by beam pointing
issues, a beam alignment procedure has to be periodically carried out to
guarantee the communication reliability. When dealing with massive MIMO links,
the beam sweeping approach is known to be time consuming and often unfeasible
due to latency constraints. To speed up the process, we propose a method that
exploits a-priori information on array dynamics provided by an inertial sensor
on transceivers to assist the beam alignment procedure. The proposed inertial
sensor aided technique allows a continuous tracking of the beam while
transmitting, avoiding frequent realignment phases. Numerical results based on
real measurements of on-transceiver accelerometers demonstrate a significant
gain in terms of V2V communication throughput with respect to conventional beam
alignment protocols.
Accessibility percolation in random fitness landscapes
Authors: Joachim Krug
Date: 2019-03-28 00:00:00

The fitness landscape encodes the mapping of genotypes to fitness and provides a succinct representation of possible trajectories followed by an evolving population. Evolutionary accessibility is quantified by the existence of fitness-monotonic paths connecting far away genotypes. Studies of accessibility percolation use probabilistic fitness landscape models to explore the emergence of such paths as a function of the initial fitness, the parameters of the landscape or the structure of the genotype graph. This chapter reviews these studies and discusses their implications for the predictability of evolutionary processes.
Early deafness leads to re-shaping of global functional connectivity beyond the auditory cortex
Date: 2019-03-28 00:00:00
Tasks: Functional Connectivity

Early sensory deprivation such as blindness or deafness shapes brain
development in multiple ways. While it is established that deprived brain areas
start to be engaged in the processing of stimuli from the remaining modalities
and in high-level cognitive tasks, some reports have also suggested the
possibility of structural and functional changes in non-deprived brain areas.
We compared resting-state functional network organization of the brain in
early-deaf adults and hearing controls by examining global network segregation
and integration. Relative to hearing controls, deaf adults exhibited an altered
modular organization, with regions of the salience network coupled with the
fronto-parietal network. They showed weaker connections between auditory and
somatomotor regions, stronger coupling between the fronto-parietal network and
several other large-scale networks (visual, memory, cingulo-opercular and
somatomotor), and an enlargement of the default mode network. Their overall
functional segregation of brain networks was also lower. Our findings suggest
that brain plasticity in deaf adults is not limited to changes in auditory
cortex but additionally alters the coupling between other large-scale networks.
These widespread functional connectivity changes may provide a mechanism for
the superior behavioral performance of the deaf in visual and attentional
tasks.
Developmental trajectory of Caenorhabditis elegans nervous system governs its structural organization
Date: 2019-05-14 00:00:00

A central problem of neuroscience involves uncovering the principles
governing the organization of nervous systems which ensure robustness in brain
development. The nematode Caenorhabditis elegans provides us with a model
organism for studying this question. In this paper, we focus on the invariant
connection structure and spatial arrangement of the neurons comprising the
somatic neuronal network of this organism to understand the key developmental
constraints underlying its design. We observe that neurons with certain shared
characteristics - such as, neural process lengths, birth time cohort, lineage
and bilateral symmetry - exhibit a preference for connecting to each other.
Recognizing the existence of such homophily helps in connecting the physical
location and morphology of neurons with the topological organization of the
network. Further, the functional identities of neurons appear to dictate the
temporal hierarchy of their appearance during the course of development.
Providing crucial insights into principles that may be common across many
organisms, our study shows how the trajectory in the developmental landscape
constrains the eventual spatial and network topological organization of a
nervous system.
Deciphering the underlying mechanisms of the pharyngeal motions in Caenorhabditis elegans
Date: 2019-03-28 00:00:00

The pharynx of the nematode Caenorhabditis elegans is a neuromuscular pump
that exhibits two typical motions: pumping and peristalsis. While the dynamics
of these motions are well characterized, the underlying mechanisms generating
most of them are not known. In this paper, we propose comprehensive and
detailed mechanisms that can explain the various observed dynamics of the
different pharyngeal areas: the dynamics of the pumping muscles - corpus,
anterior isthmus, and terminal bulb - and the peristalsis dynamics of the
posterior isthmus muscles. While the suggested mechanisms are consistent with
all available relevant data, the assumptions on which they are based and the
open questions they raise could point at additional interesting research
directions on the C. elegans pharynx. We are hoping that appropriate
experiments on the nematode will eventually corroborate our results, and
improve our understanding of the functioning of the C. elegans pharynx, and
possibly of the mammalian digestive system.
Multi-agent estimation and filtering for minimizing team mean-squared error
Authors: Mohammad Afshari, Aditya Mahajan
Date: 2019-03-28 00:00:00
Tasks: Autonomous Vehicles

Motivated by estimation problems arising in autonomous vehicles and decentralized control of unmanned aerial vehicles, we consider multi-agent estimation and filtering problems in which multiple agents generate state estimates based on decentralized information and the objective is to minimize a coupled mean-squared error which we call \emph{team mean-square error}. We call the resulting estimates as minimum team mean-squared error (MTMSE) estimates. We show that MTMSE estimates are different from minimum mean-squared error (MMSE) estimates. We derive closed-form expressions for MTMSE estimates, which are linear function of the observations where the corresponding gain depends on the weight matrix that couples the estimation error. We then consider a filtering problem where a linear stochastic process is monitored by multiple agents which can share their observations (with delay) over a communication graph. We derive expressions to recursively compute the MTMSE estimates. To illustrate the effectiveness of the proposed scheme we consider an example of estimating the distances between vehicles in a platoon and show that MTMSE estimates significantly outperform MMSE estimates and consensus Kalman filtering estimates.
Sizing and Placement of Battery Energy Storage Systems and Wind Turbines by Minimizing Costs and System Losses
Date: 2019-03-28 00:00:00

Probabilistic and intermittent output power of wind turbines (WT) is one
major inconsistency of WTs. Battery Energy Storage Systems (BESSs) are a
suitable solution to mitigate this intermittency which use to smoothen the
output power injected to the grid by such intermittent sources. This paper
proposes a new optimization formulation using genetic algorithm to simultaneous
sizing and placement of BESSs and WTs which result in finding best location and
size (capacity) of WTs and BESSs in power system by minimizing total system
loss (active and reactive loss) and Costs of WTs and BESSs which improves
demand bus voltage profiles. The result of optimization problem is best buses
to locate WTs and BESSs and the size (installable active and reactive power) of
them. The case studies performed on IEEE 33 bus system, validates the
suitability of the formulation for loss minimization and bus voltage profiles
improvement in the test system in presence of WT and BESS.
Imaging cytometry without image reconstruction (ghost cytometry)
Date: 2019-03-27 00:00:00
Tasks: Image Reconstruction

Imaging and analysis of many single cells hold great potential in our
understanding of heterogeneous and complex life systems and in enabling
biomedical applications. We here introduce a recently realized image-free
"imaging" cytometry technology, which we call ghost cytometry. While a
compressive ghost imaging technique utilizing object's motion relative to a
projected static light pattern allows recovery of their images, a key of this
ghost cytometry is to achieve ultrafast cell classification by directly
applying machine learning methods to the compressive imaging signals in a
temporal domain. We show the applicability of our method in the analysis of
flowing objects based on the reconstructed images as well as in that based on
the imaging waveform without image production.
Performance and Energy Conservation of 3GPP IFOM Protocol for Dual Connectivity in Heterogeneous LTE-WLAN Network
Date: 2019-03-28 00:00:00

For the 5th Generation (5G) networks, Third Generation Partnership Project
(3GPP) is considering standardization of various solutions for traffic
aggregation using licensed and unlicensed spectrum, to meet the rising data
demands. IP Flow Mobility (IFOM) is a multi access connectivity
solution/protocol standardized by the Internet Engineering Task force (IETF)
and 3GPP in Release 10. It enables concurrent access for an User Equipment (UE)
to Heterogeneous Networks (HetNets) such as Long Term Evolution (LTE) and IEEE
802.11 Wireless Local Area Network (WLAN). IFOM enabled UEs have multiple
interfaces to connect to HetNets. They can have concurrent flows with different
traffic types over these networks and can seamlessly switch the flows from one
network to the other. In this paper, we focus on two objectives. First is to
investigate the performance parameters e.g. throughput, latency, tunnelling
overhead, packet loss, energy cost etc. of IFOM enabled UEs (IeUs) in HetNets
of LTE and WLAN. We have proposed a novel mechanism to maximize the throughput
of IeUs achieving a significant throughput gain with low latency for the IeUs.
We have explored further and observed a throughput energy trade off for low
data rate flows. To address this, we also propose a smart energy efficient and
throughput optimization algorithm for the IeUs, resulting in a substantial
reduction in energy cost, while maintaining the high throughput at lower
latency and satisfying the Quality of Service (QoS) requirements of the IeUs.
Hieroglyph: Hierarchical Glia Graph Skeletonization and Matching
Date: 2019-03-26 00:00:00
Tasks: 3D Reconstruction

Automatic 3D reconstruction of glia morphology is a powerful tool necessary
for investigating the role of microglia in neurological disorders in the
central nervous system. Current glia skeleton reconstruction techniques fail to
capture an accurate tracing of the processes over time, useful for the study of
the microglia motility and morphology in the brain during healthy and diseased
states. We propose Hieroglyph, a fully automatic temporal 3D skeleton
reconstruction algorithm for glia imaged via 3D multiphoton microscopy.
Hieroglyph yielded a 21% performance increase compared to state of the art
automatic skeleton reconstruction methods and outperforms the state of the art
in different measures of consistency on datasets of 3D images of microglia. The
results from this method provide a 3D graph and digital reconstruction of glia
useful for a myriad of morphological analyses that could impact studies in
brain immunology and disease.
Optimal Reinsurance and Investment in a Diffusion Model
Date: 2019-03-29 00:00:00

We consider a diffusion approximation to an insurance risk model where an
external driver models a stochastic environment. The insurer can buy
reinsurance. Moreover, investment in a financial market is possible. The
financial market is also driven by the environmental process. Our goal is to
maximise terminal expected utility. In particular, we consider the case of
SAHARA utility functions. In the case of proportional and excess-of-loss
reinsurance, we obtain explicit results.
An Alternating Direction Algorithm for Hybrid Precoding and Combining in Millimeter Wave MIMO Systems
Date: 2019-03-29 00:00:00

Millimeter-wave (mmWave) technology is one of the most promising candidates
for future wireless communication systems as it can offer large underutilized
bandwidths and eases the implementation of large antenna arrays which are
required to help overcome the severe signal attenuation that occurs at these
frequencies. To reduce the high cost and power consumption of a fully digital
mmWave precoder and combiner, hybrid analog/digital designs based on analog
phase shifters are often adopted. In this work we derive an iterative algorithm
for the hybrid precoding and combining design for spatial multiplexing in
mmWave massive multiple-input multiple-output (MIMO) systems. To cope with the
difficulty of handling the hardware constraint imposed by the analog phase
shifters we use the alternating direction method of the multipliers (ADMM) to
split the hybrid design problem into a sequence of smaller subproblems. This
results in an iterative algorithm where the design of the analog
precoder/combiner consists of a closed form solution followed by a simple
projection over the set of matrices with equal magnitude elements. It is
initially developed for the fully-connected structure and then extended to the
partially-connected architecture which allows simpler hardware implementation.
Furthermore, to cope with the more likely wideband scenarios where the channel
is frequency selective, we also extend the algorithm to an orthogonal frequency
division multiplexing (OFDM) based mmWave system. Simulation results in
different scenarios show that the proposed design algorithms are capable of
achieving performances close to the optimal fully digital solution and can work
with a broad range of configuration of antennas, RF chains and data streams.
Frequency Domain Equalization for Single and Multiuser Generalized Spatial Modulation Systems in Time Dispersive Channels
Date: 2019-04-26 00:00:00

In this letter, a low-complexity iterative detector with frequency domain
equalization is proposed for generalized spatial modulation (GSM) aided single
carrier (SC) transmissions operating in frequency selective channels. The
detector comprises three main separate tasks namely, multiple-input
multiple-output (MIMO) equalization, active antenna detection and symbol wise
demodulation. This approach makes the detector suitable for a broad range of
MIMO configurations, which includes single-user and multiuser scenarios, as
well as arbitrary signal constellations. Simulation results show that the
receiver can cope with the intersymbol interference induced by severe time
dispersive channels and operate in difficult underdetermined scenarios where
the total number of transmitter antennas is substantially larger than the
number of receiver antennas.
Market Manipulation as a Security Problem
Date: 2019-03-29 00:00:00

Order matching systems form the backbone of modern equity exchanges, used by
millions of investors daily. Thus, their operation is strictly controlled
through numerous regulatory directives to ensure that markets are fair and
transparent. Despite these efforts, market manipulation remains an open
problem.
  In this work, we focus on a class of market manipulation techniques that
exploit technical details and glitches in the operation of the exchanges (i.e.,
mechanical arbitrage). Such techniques are used by predatory traders with deep
knowledge of the exchange's structure to gain an advantage over the other
market participants. We argue that technical solutions to the problem of
mechanical arbitrage have the potential to significantly thwart these
practices. Our work provides the first overview of the threat landscape, models
fair markets and their security assumptions, and discusses various mitigation
measures.
Field-portable quantitative lensless microscopy based on translated speckle illumination and sub-sampled ptychographic phase retrieval
Date: 2019-03-28 00:00:00
Tasks: Object, Retrieval

We report a compact, cost-effective and field-portable lensless imaging
platform for quantitative microscopy. In this platform, the object is placed on
top of an image sensor chip without using any lens. We use a low-cost galvo
scanner to rapidly scan an unknown laser speckle pattern on the object. To
address the positioning repeatability and accuracy issues, we directly recover
the positional shifts of the speckle pattern based on the phase correlation of
the captured images. To bypass the resolution limit set by the imager pixel
size, we employ a sub-sampled ptychographic phase retrieval process to recover
the complex object. We validate our approach using a resolution target, a phase
target, and a biological sample. Our results show that accurate, high-quality
complex images can be obtained from a lensless dataset with as few as ~10
images. We also demonstrate the reported approach to achieve a 6.4 mm by 4.6 mm
field of view and a half pitch resolution of 1 miron. The reported approach may
provide a quantitative lensless imaging strategy for addressing point-of-care,
global-health, and telemedicine related challenges.
Physical constraints on accuracy and persistence during breast cancer cell chemotaxis
Date: 2019-03-29 00:00:00

Directed cell motion in response to an external chemical gradient occurs in
many biological phenomena such as wound healing, angiogenesis, and cancer
metastasis. Chemotaxis is often characterized by the accuracy, persistence, and
speed of cell motion, but whether any of these quantities is physically
constrained by the others is poorly understood. Using a combination of theory,
simulations, and 3D chemotaxis assays on single metastatic breast cancer cells,
we investigate the links among these different aspects of chemotactic
performance. In particular, we observe in both experiments and simulations that
the chemotactic accuracy, but not the persistence or speed, increases with the
gradient strength. We use a random walk model to explain this result and to
propose that cells' chemotactic accuracy and persistence are mutually
constrained. Our results suggest that key aspects of chemotactic performance
are inherently limited regardless of how favorable the environmental conditions
are.
Random matrix analysis of Ca$^{2+}$ signals in $\beta$-cell collectives
Date: 2019-03-29 00:00:00

Even within small organs like pancreatic islets, different endocrine cell
types and subtypes form a heterogeneous collective to sense the chemical
composition of the extracellular solution and compute an adequate hormonal
output. Erroneous cellular processing and hormonal output due to challenged
heterogeneity result in various disorders with diabetes mellitus as a flagship
metabolic disease. Here we attempt to address the aforementioned functional
heterogeneity with comparing pairwise cell-cell cross-correlations obtained
from simultaneous measurements of cytosolic calcium responses in hundreds of
islet cells in an optical plane to statistical properties of correlations
predicted by the random matrix theory (RMT). We find that the bulk of the
empirical eigenvalue spectrum is almost completely described by RMT prediction,
however, the deviating eigenvalues that exist below and above RMT spectral
edges suggest that there are local and extended modes driving the correlations.
We show that empirical nearest neighbor spacing of eigenvalues follows
universal RMT properties regardless of glucose stimulation, but that number
variance displays clear separation from RMT prediction and can differentiate
between empirical spectra obtained under non-stimulated and stimulated
conditions. We suggest that RMT approach provides a sensitive tool to assess
the functional cell heterogeneity and its effects on the spatio-temporal
dynamics a collective of beta cells in pancreatic islets in physiological
resting and stimulatory conditions.