pwc-archive/papers-with-abstracts huggingface dataset:
Experimental design trade-offs for gene regulatory network inference: an in silico study of the yeast Saccharomyces cerevisiae cell cycle
Date: 2017-12-14 00:00:00
Tasks: Experimental Design, Time Series, Time Series Analysis

Time-series of high throughput gene sequencing data intended for gene
regulatory network (GRN) inference are often short due to the high costs of
sampling cell systems. Moreover, experimentalists lack a set of quantitative
guidelines that prescribe the minimal number of samples required to infer a
reliable GRN model. We study the temporal resolution of data vs quality of GRN
inference in order to ultimately overcome this deficit. The evolution of a
Markovian jump process model for the Ras/cAMP/PKA pathway of proteins and
metabolites in the G1 phase of the Saccharomyces cerevisiae cell cycle is
sampled at a number of different rates. For each time-series we infer a linear
regression model of the GRN using the LASSO method. The inferred network
topology is evaluated in terms of the area under the precision-recall curve
AUPR. By plotting the AUPR against the number of samples, we show that the
trade-off has a, roughly speaking, sigmoid shape. An optimal number of samples
corresponds to values on the ridge of the sigmoid.
60 GHz Blockage Study Using Phased Arrays
Date: 2017-12-14 00:00:00
Tasks: Blocking

The millimeter wave (mmWave) frequencies offer the potential for enormous
capacity wireless links. However, designing robust communication systems at
these frequencies requires that we understand the channel dynamics over both
time and space: mmWave signals are extremely vulnerable to blocking and the
channel can thus rapidly appear and disappear with small movement of obstacles
and reflectors. In rich scattering environments, different paths may experience
different blocking trajectories and understanding these multi-path blocking
dynamics is essential for developing and assessing beamforming and
beam-tracking algorithms. This paper presents the design and experimental
results of a novel measurement system which uses phased arrays to perform
mmWave dynamic channel measurements. Specifically, human blockage and its
effects across multiple paths are investigated with only several microseconds
between successive measurements. From these measurements we develop a modeling
technique which uses low-rank tensor factorization to separate the available
paths so that their joint statistics can be understood.
Soft Seeded SSL Graphs for Unsupervised Semantic Similarity-based Retrieval
Authors: Srivastava Avikalp, Datt Madhav
Date: 2017-12-15 00:00:00
Tasks: Question Answering, Retrieval, Semantic Similarity, Semantic Textual Similarity

Semantic similarity based retrieval is playing an increasingly important role
in many IR systems such as modern web search, question-answering, similar
document retrieval etc. Improvements in retrieval of semantically similar
content are very significant to applications like Quora, Stack Overflow, Siri
etc. We propose a novel unsupervised model for semantic similarity based
content retrieval, where we construct semantic flow graphs for each query, and
introduce the concept of "soft seeding" in graph based semi-supervised learning
(SSL) to convert this into an unsupervised model.
  We demonstrate the effectiveness of our model on an equivalent question
retrieval problem on the Stack Exchange QA dataset, where our unsupervised
approach significantly outperforms the state-of-the-art unsupervised models,
and produces comparable results to the best supervised models. Our research
provides a method to tackle semantic similarity based retrieval without any
training data, and allows seamless extension to different domain QA
communities, as well as to other semantic equivalence tasks.
DOA and Polarization Estimation for Non-Circular Signals in 3-D Millimeter Wave Polarized Massive MIMO Systems
Date: 2017-12-15 00:00:00
Tasks: parameter estimation

In this paper, an algorithm of multiple signal classification (MUSIC) is
proposed for two-dimensional (2-D) direction of- arrival (DOA) and polarization
estimation of non-circular signal in three-dimensional (3-D) millimeter wave
polarized largescale/ massive multiple-input-multiple-output (MIMO) systems.
The traditional MUSIC-based algorithms can estimate either the DOA and
polarization for circular signal or the DOA for non-circular signal by using
spectrum search. By contrast, in the proposed algorithm only the DOA estimation
needs spectrum search, and the polarization estimation has a closedform
expression. First, a novel dimension-reduced MUSIC (DRMUSIC) is proposed for
DOA and polarization estimation of circular signal with low computational
complexity. Next, based on the quaternion theory, a novel algorithm named
quaternion non-circular MUSIC (QNC-MUSIC) is proposed for parameter estimation
of non-circular signal with high estimation accuracy. Then based on the DOA
estimation result using QNC-MUSIC, the polarization estimation of non-circular
signal is acquired by using the closed-form expression of the polarization
estimation in DR-MUSIC. In addition, the computational complexity analysis
shows that compared with the conventional DOA and polarization estimation
algorithms, our proposed QNC-MUSIC and DRMUSIC have much lower computational
complexity, especially when the source number is large. The stochastic
Cramer-Rao Bound (CRB) for the estimation of the 2-D DOA and polarization
parameters of the non-circular signals is derived as well. Finally, numerical
examples are provided to demonstrate that the proposed algorithms can improve
the parameter estimation performance when the large-scale/massive MIMO systems
are employed.
Period-Amplitude Co-variation in Biomolecular Oscillators
Date: 2018-04-10 00:00:00

The period and amplitude of biomolecular oscillators are functionally
important properties in multiple contexts. For a biomolecular oscillator, the
overall constraints in how tuning of amplitude affects period, and vice versa,
are generally unclear. Here we investigate this co-variation of the period and
amplitude in mathematical models of biomolecular oscillators using both
simulations and analytical approximations. We computed the amplitude-period
co-variation of eleven benchmark biomolecular oscillators as their parameters
were individually varied around a nominal value, classifying the various
co-variation patterns such as a simultaneous increase/ decrease in period and
amplitude. Next, we repeated the classification using a power norm-based
amplitude metric, to account for the amplitudes of the many biomolecular
species that may be part of the oscillations, finding largely similar trends.
Finally, we calculate "scaling laws" of period-amplitude co-variation for a
subset of these benchmark oscillators finding that as the approximated period
increases, the upper bound of the amplitude increases, or reaches a constant
value. Based on these results, we discuss the effect of different parameters on
the type of period-amplitude co-variation as well as the difficulty in
achieving an oscillation with large amplitude and small period.
Risk Sensitive Portfolio Optimization with Default Contagion and Regime-Switching
Date: 2018-10-24 00:00:00
Tasks: Portfolio Optimization

We study an open problem of risk-sensitive portfolio allocation in a
regime-switching credit market with default contagion. The state space of the
Markovian regime-switching process is assumed to be a countably infinite set.
To characterize the value function, we investigate the corresponding recursive
infinite-dimensional nonlinear dynamical programming equations (DPEs) based on
default states. We propose to work in the following procedure: Applying the
theory of monotone dynamical system, we first establish the existence and
uniqueness of classical solutions to the recursive DPEs by a truncation
argument in the finite state space. The associated optimal feedback strategy is
characterized by developing a rigorous verification theorem. Building upon
results in the first stage, we construct a sequence of approximating risk
sensitive control problems with finite states and prove that the resulting
smooth value functions will converge to the classical solution of the original
system of DPEs. The construction and approximation of the optimal feedback
strategy for the original problem are also thoroughly discussed.
Increased adaptive immune responses and proper feedback regulation protect against clinical dengue
Date: 2017-12-11 00:00:00

Dengue is the most prevalent arthropod-borne viral disease. Clinical symptoms
of dengue virus (DENV) infection range from classical mild dengue fever to
severe, life-threatening dengue shock syndrome. However, most DENV infections
cause few or no symptoms. Asymptomatic DENV-infected patients provide a unique
opportunity to decipher the host immune responses leading to virus elimination
without negative impact on t v 'health. We used an integrated approach of
transcriptional profiling and immunological analysis comparing a Cambodian
population of strictly asymptomatic viremic individuals with clinical dengue
patients. Whereas inflammatory pathways and innate immune responses were
similar between asymptomatic individuals and clinical dengue patients,
expression of proteins related to antigen presentation and subsequent T and B
cell activation pathways were differentially regulated, independent of viral
load or previous DENV infection. Feedback mechanisms controlled the immune
response in asymptomatic viremic individuals as demonstrated by increased
activation of T cell apoptosis-related pathways and Fc$\gamma$RIIB signaling
associated with decreased anti-DENV specific antibody concentrations. Taken
together, our data illustrate that symptom-free DENV infection in children is
determined by increased activation of the adaptive immune compartment and
proper control mechanisms leading to elimination of viral infection without
excessive immune activation, having implications for novel vaccine development
strategies.
Chaos and unpredictability in evolution of cooperation in continuous time
Date: 2017-12-16 00:00:00

Cooperators benefit others with paying costs. Evolution of cooperation
crucially depends on the cost-benefit ratio of cooperation, denoted as $c$. In
this work, we investigate the infinitely repeated prisoner's dilemma for
various values of $c$ with four of the representative memory-one strategies,
i.e., unconditional cooperation, unconditional defection, tit-for-tat, and
win-stay-lose-shift. We consider replicator dynamics which deterministically
describes how the fraction of each strategy evolves over time in an
infinite-sized well-mixed population in the presence of implementation error
and mutation among the four strategies. Our finding is that this
three-dimensional continuous-time dynamics exhibits chaos through a bifurcation
sequence similar to that of a logistic map as $c$ varies. If mutation occurs
with rate $\mu \ll 1$, the position of the bifurcation sequence on the $c$ axis
is numerically found to scale as $\mu^{0.1}$, and such sensitivity to $\mu$
suggests that mutation may have non-perturbative effects on evolutionary paths.
It demonstrates how the microscopic randomness of the mutation process can be
amplified to macroscopic unpredictability by evolutionary dynamics.
Overview of the Wikidata Vandalism Detection Task at WSDM Cup 2017
Authors: Heindorf Stefan, Potthast Martin, Engels Gregor, Stein Benno
Date: 2017-12-16 00:00:00

We report on the Wikidata vandalism detection task at the WSDM Cup 2017. The
task received five submissions for which this paper describes their evaluation
and a comparison to state of the art baselines. Unlike previous work, we recast
Wikidata vandalism detection as an online learning problem, requiring
participant software to predict vandalism in near real-time. The
best-performing approach achieves a ROC-AUC of 0.947 at a PR-AUC of 0.458. In
particular, this task was organized as a software submission task: to maximize
reproducibility as well as to foster future research and development on this
task, the participants were asked to submit their working software to the TIRA
experimentation platform along with the source code for open source release.
A monotonic relationship between the variability of the infectious period and final size in pairwise epidemic modelling
Date: 2018-12-24 00:00:00

For a recently derived pairwise model of network epidemics with non-Markovian
recovery, we prove that under some mild technical conditions on the
distribution of the infectious periods, smaller variance in the recovery time
leads to higher reproduction number, and consequently to a larger epidemic
outbreak, when the mean infectious period is fixed. We discuss how this result
is related to various stochastic orderings of the distributions of infectious
periods. The results are illustrated by a number of explicit stochastic
simulations, suggesting that their validity goes beyond regular networks.
Tracking of plus-ends reveals microtubule functional diversity in different cell types
Date: 2017-12-17 00:00:00
Tasks: Diversity

Many cellular processes are tightly connected to the dynamics of microtubules
(MTs). While in neuronal axons MTs mainly regulate intracellular trafficking,
they participate in cytoskeleton reorganization in many other eukaryotic cells,
enabling the cell to efficiently adapt to changes in the environment. We show
that the functional differences of MTs in different cell types and regions is
reflected in the dynamic properties of MT tips. Using plus-end tracking
proteins EB1 to monitor growing MT plus-ends, we show that MT dynamics and life
cycle in axons of human neurons significantly differ from that of fibroblast
cells. The density of plus-ends, as well as the rescue and catastrophe
frequencies increase while the growth rate decreases toward the fibroblast cell
margin. This results in a rather stable filamentous network structure and
maintains the connection between nucleus and membrane. In contrast, plus-ends
are uniformly distributed along the axons and exhibit diverse polymerization
run times and spatially homogeneous rescue and catastrophe frequencies, leading
to MT segments of various lengths. The probability distributions of the
excursion length of polymerization and the MT length both follow nearly
exponential tails, in agreement with the analytical predictions of a two-state
model of MT dynamics.
Cargo binding promotes KDEL receptor clustering at the mammalian cell surface
Date: 2017-12-17 00:00:00
Tasks: Clustering

Transmembrane receptor clustering is a ubiquitous phenomenon in pro- and
eukaryotic cells to physically sense receptor/ligand interactions and
subsequently translate an exogenous signal into a cellular response. Despite
that receptor cluster formation has been described for a wide variety of
receptors, ranging from chemotactic receptors in bacteria to growth factor and
neurotransmitter receptors in mammalian cells, a mechanistic understanding of
the underlying molecular processes is still puzzling. In an attempt to fill
this gap we followed a combined experimental and theoretical approach by
dissecting and modulating cargo binding, internalization and cellular response
mediated by KDEL receptors (KDELRs) at the mammalian cell surface after
interaction with a model cargo/ligand. Using a fluorescent variant of ricin
toxin A chain as KDELR-ligand, eGFP-RTA (H/KDEL), we demonstrate that cargo
binding induces dose-dependent receptor cluster formation at and subsequent
internalization from the membrane which is associated and counteracted by
anterograde and microtubule-assisted receptor transport to preferred docking
sites at the plasma membrane. By means of analytical arguments and extensive
numerical simulations we show that cargo-synchronized receptor transport from
and to the membrane is causative for KDELR/cargo cluster formation at the
mammalian cell surface.
Adaptive antenna system by ESP32-PICO-D4 and its application to web radio system
Date: 2017-12-18 00:00:00
Tasks: PICO

Adaptive antenna technique has an important role in the IoT environment in
order to establish reliable and stable wireless communication in high
congestion situation. Even if knowing antenna characteristics in advance,
electromagnetic wave propagation in the non-line-of-sight environment is very
complex and unpredictable, therefore, the adjustment the antenna radiation for
the optimum signal reception is important for the better wireless link. This
article presents a simple but effective adaptive antenna system for Wi-Fi
utilizing the function of a highly integrated component, ESP32-PICO-D4. This
chip is a system-in-chip containing all components for Wi-Fi and Bluetooth
application except for antenna. Together with SP3T RF switch and dielectric
antennas and high-resolution audio DAC, completed web-radio system is made in
the size of 50 x 50 mm.
Modules for Automated Validation and Comparison of Models of Neurophysiological and Neurocognitive Biomarkers of Psychiatric Disorders: ASSRUnit - A Case Study
Date: 2017-12-18 00:00:00

The characterisation of biomarkers and endophenotypic measures has been a
central goal of research in psychiatry over the last years. While most of this
research has focused on the identification of biomarkers and endophenotypes,
using various experimental approaches, it has been recognised that their
instantiations, through computational models, have a great potential to help us
understand and interpret these experimental results. However, the enormous
increase in available neurophysiological and neurocognitive as well as
computational data also poses new challenges. How can a researcher stay on top
of the experimental literature? How can computational modelling data be
efficiently compared to experimental data? How can computational modelling most
effectively inform experimentalists? Recently, a general scientific framework
for the generation of executable tests that automatically compare model results
to experimental observations, SciUnit, has been proposed. Here we exploit this
framework for research in psychiatry to address the challenges mentioned above.
We extend the SciUnit framework by adding an experimental database, which
contains a comprehensive collection of relevant experimental observations, and
a prediction database, which contains a collection of predictions generated by
computational models. Together with appropriately designed SciUnit tests and
methods to mine and visualise the databases, model data and test results, this
extended framework has the potential to greatly facilitate the use of
computational models in psychiatry. As an initial example we present ASSRUnit,
a module for auditory steady-state response deficits in psychiatric disorders.
Quantification of sulfated polysaccharides in mouse and rat plasma by the Heparin Red mix-and-read fluorescence assay
Date: 2017-12-15 00:00:00

Sulfated polysaccharides constitute a large and complex group of
macromolecules which possess a wide range of important biological properties.
Many of them hold promise as new therapeutics, but determination of their blood
levels during pharmacokinetic studies can be challenging. Heparin Red, a
commercial mix-and-read fluorescence assay, has recently emerged as a tool in
clinical drug development and pharmacokinetic analysis for the quantification
of sulfated polysaccharides in human plasma. The present study describes the
application of Heparin Red to the detection of heparin, a highly sulfated
polysaccharide, and fucoidan, a less sulfated polysaccharide, in spiked mouse
and rat plasmas. While the standard assay protocol for human plasma matrix gave
less satisfactory results, a modified protocol was developed that provides
within a detection range 0 to 10 micrograms per mL better limits of
quantification, 1.1 to 2.3 micrograms per mL for heparin, and 1.7 to 3.4
micrograms per mL for fucoidan. The required plasma sample volume of only 20
microliters is advantegous in particular when blood samples need to be
collected from mice. Our results suggest that Heparin Red is a promising tool
for the preclinical evaluation of sulfated polysaccharides with varying
sulfation degrees in mouse and rat models.
Back-of-the-envelope swaptions in a very parsimonious multicurve interest rate model
Date: 2017-12-18 00:00:00

We propose an elementary model to price European physical delivery swaptions
in multicurve setting with a simple exact closed formula. The proposed model is
very parsimonious: it is a three-parameter multicurve extension of the
two-parameter Hull-White (1990) model. The model allows also to obtain simple
formulas for all other plain vanilla Interest Rate derivatives. Calibration
issues are discussed in detail.
WiBall: A Time-Reversal Focusing Ball Method for Indoor Tracking
Date: 2017-12-18 00:00:00

With the development of the Internet of Things technology, indoor tracking
has become a popular application nowadays, but most existing solutions can only
work in line-of-sight scenarios, or require regular re-calibration. In this
paper, we propose WiBall, an accurate and calibration-free indoor tracking
system that can work well in non-line-of-sight based on radio signals. WiBall
leverages a stationary and location-independent property of the time-reversal
focusing effect of radio signals for highly accurate moving distance
estimation. Together with the direction estimation based on inertial
measurement unit and location correction using the constraints from the
floorplan, WiBall is shown to be able to track a moving object with
decimeter-level accuracy in different environments. Since WiBall can
accommodate a large number of users with only a single pair of devices, it is
low-cost and easily scalable, and can be a promising candidate for future
indoor tracking applications.
Another Look at the Ho-Lee Bond Option Pricing Model
Date: 2017-12-18 00:00:00

In this paper, we extend the classical Ho-Lee binomial term structure model
to the case of time-dependent parameters and, as a result, resolve a drawback
associated with the model. This is achieved with the introduction of a more
flexible no-arbitrage condition in contrast to the one assumed in the Ho-Lee
model.
Gene regulatory and signalling networks exhibit distinct topological distributions of motifs
Date: 2018-04-12 00:00:00
Tasks: Decision Making

The biological processes of cellular decision making and differentiation
involve a plethora of signalling pathways and gene regulatory circuits. These
networks, in their turn, exhibit a multitude of motifs playing crucial parts in
regulating network activity. Here, we compare the topological placement of
motifs in gene regulatory and signalling networks and find that it suggests
different evolutionary strategies in motif distribution for distinct cellular
subnetworks.