pwc-archive/papers-with-abstracts huggingface dataset:
Near real-time enumeration of live and dead bacteria using a fibre-based spectroscopic device
Date: 2018-09-10 00:00:00
Tasks: regression

A rapid, cost-effective and easy method that allows on-site determination of
the concentration of live and dead bacterial cells using a fibre-based
spectroscopic device (the optrode system) is proposed and demonstrated.
Identification of live and dead bacteria was achieved by using the commercially
available dyes SYTO 9 and propidium iodide, and fluorescence spectra were
measured by the optrode. Three spectral processing methods were evaluated for
their effectiveness in predicting the original bacterial concentration in the
samples: principal components regression (PCR), partial least squares
regression (PLSR) and support vector regression (SVR). Without any sample
pre-concentration, PCR achieved the most reliable results. It was able to
quantify live bacteria from $10^{8}$ down to $10^{6.2}$ bacteria/mL and showed
the potential to detect as low as $10^{5.7}$ bacteria/mL. Meanwhile,
enumeration of dead bacteria using PCR was achieved between $10^{8}$ and
$10^{7}$ bacteria/mL. The general procedures described in this article can be
applied or modified for the enumeration of bacteria within populations stained
with fluorescent dyes. The optrode is a promising device for the enumeration of
live and dead bacterial populations particularly where rapid, on-site
measurement and analysis is required.
Species traits and community properties explain species extinction effects on detritus-based food webs
Date: 2019-02-11 00:00:00

Effects of changes in functional composition of soil communities on nutrient
cycling are still not well understood. Models simulating community dynamics
overcome the technical challenges of conducting species removal experiments in
the field. However, to date, available soil food web models do not adequately
represent the organic matter processing chain which is key for soil dynamics.
Here, we present a new model of soil food web dynamics accounting for
allometric scaling of metabolic rate, ontogeny of organic matter, and explicit
representation of nitrogen and carbon flows. We use this model to investigate
what traits are best predictors of species effects on community productivity
and on nutrient cycling. To do so, we removed 161 tropho-species (groups of
functionally identical species) one at a time from 48 forest soil food webs,
and simulated their dynamics until equilibrium. Simulations revealed that
combinations of traits better determine removal effects than single ones. The
smallest species are the most competitive ones, but carnivores of various body
masses presenting the highest connectivity and resource similarity could be key
stone species in the regulation of competitive forces. Despite this, most
removals had low effects, suggesting functional redundancy provides a high
resistance of soil food webs to single tropho-species extinction. We also
highlight for the first time that food web structure and soil fertility can
drastically change species effects in an unpredictable way. Moreover, the
exclusion of detritus and stoichiometric constraints in past studies lead to
underestimations of indirect effects and retroactions. While additional work is
needed to incorporate complementarity between detritivores, it is essential to
take into account these mechanisms in models in order to improve the
understanding of soil food web functioning.
Non-invasive assessment of the spatial and temporal distributions of interstitial fluid pressure, fluid velocity and fluid flow in cancers in vivo
Date: 2018-09-11 00:00:00

Interstitial fluid pressure (IFP), interstitial fluid velocity (IFV),
interstitial permeability (IP) and vascular permeability (VP) are cancer
mechanopathological parameters of great clinical significance. To date, there
is a lack of non-invasive techniques that can be used to estimate these
parameters in vivo. In this study, we designed and tested new ultrasound
poroelastography methods capable of estimating the magnitude and spatial
distribution of fluid pressure, fluid velocity and fluid flow inside tumors. We
theoretically proved that fluid pressure, velocity and flow estimated using
poroelastography from a tumor under creep compression are directly related to
the underlying IFP, IFV and fluid flow, respectively, differing only in peak
values. We also proved that, from the spatial distribution of the fluid
pressure estimated using poroelastography, it is possible to derive: the
parameter alpha, which quantifies the spatial distribution of the IFP; the
ratio between VP and IP and the ratio between the peak IFP and effective
vascular pressure in the tumor. Finally, we demonstrated that axial strain time
constant (TC) elastograms are directly related to VP and IP in tumors. Our
techniques were validated using finite element and ultrasound simulations,
while experiments on a human breast cancer animal model were used to show the
feasibility of these methods in vivo.
The human longevity record may hold for decades
Date: 2018-09-11 00:00:00

Since 1990 Jeanne Louise Calment has held the record for human longevity. She
was born on 21 February 1875, became the longest-lived human on 12 May 1990
when she was 115.21 and died on 4 August 1997 at age 122.45 years. In this
chapter, we use data available on 25 September 2017 on people who reached age
110, supercentenarians, to address the following questions: 1. How likely is it
that a person has reached age 122.45? 2. How unlikely is it that Calment's
record has not yet been broken? 3. How soon might it be broken? Assuming a
constant annual probability of death of 50% after age 110, we found that the
probability that a person who survived to age 110 would have lived to 122.45 by
25 September 2017 is 17.1%. Furthermore, we calculated that there was only a
20.3% chance that Calment's record would have been broken after 1997 but before
2017. Finally, we estimated that there is less than a 50% chance that someone
will surpass Calment's lifespan before 2045. Jeanne Louise Calment's record is
exceptional but not impossible. It does not provide evidence that her lifespan
is an upper limit to human lifespans.
Stochastic Multipath Model for the In-Room Radio Channel based on Room Electromagnetics
Date: 2018-09-11 00:00:00

We propose a stochastic multipath model for the received signal for the case
where the transmitter and receiver, both with directive antennas, are situated
in the same rectangular room. This scenario is known to produce channel impulse
responses with a gradual specular-to-diffused transition in delay. Mirror
source theory predicts the arrival rate to be quadratic in delay, inversely
proportional to room volume and proportional to the product of the antenna beam
coverage fractions. We approximate the mirror source positions by a homogeneous
spatial Poisson point process and their gain as complex random variables with
the same second moment. The multipath delays in the resulting model form an
inhomogeneous Poisson point process which enables derivation of the
characteristic functional, power/kurtosis delay spectra, and the distribution
of order statistics of the arrival delays in closed form. We find that the
proposed model matches the mirror source model well in terms of power delay
spectrum, kurtosis delay spectrum, order statistics, and prediction of mean
delay and rms delay spread. The constant rate model, assumed in e.g. the
Saleh-Valenzuela model, is unable to reproduce the same effects.
Diversification, Volatility, and Surprising Alpha
Date: 2018-09-11 00:00:00

It has been widely observed that capitalization-weighted indexes can be
beaten by surprisingly simple, systematic investment strategies. Indeed, in the
U.S. stock market, equal-weighted portfolios, random-weighted portfolios, and
other naive, non- optimized portfolios tend to outperform a
capitalization-weighted index over the long term. This outperformance is
generally attributed to beneficial factor exposures. Here, we provide a deeper,
more general explanation of this phenomenon by decomposing portfolio
log-returns into an average growth and an excess growth component. Using a
rank-based empirical study we argue that the excess growth component plays the
major role in explaining the outperformance of naive portfolios. In particular,
individual stock growth rates are not as critical as is traditionally assumed.
Unjamming and nematic flocks in endothelial monolayers during angiogenesis : theoretical and experimental analysis
Date: 2018-09-11 00:00:00

Angiogenesis is the complex process by which new blood vessels develop from
an existing vasculature in order to supply nutrients and/or metabolites to
tissues, playing a fundamental role in many physiological and pathological
conditions such as embryogenesis and tissue repair or tumour growth. Here we
analysed the \textit{in-vitro} angiogenic process from the perspective of the
monolayer to understand the role of the interaction between the surrounding
endothelial monolayer, the sprouting and the mechanics. First we noticed that
the VEGF (Vascular Endothelial Growth Factor) promotes a jamming/unjamming
transition that allows the fluidisation of the monolayer by measuring the shape
index factor. Next, we measured the density field over the monolayer and
realised that the flow of cells manifests strong similarities with the
evacuation process where the flock of cells can flow or stuck, defining a
convergent channel. Based on these novel observations we propose a mathematical
model to describe the effects of unjamming and reorientation of a flock of
cells which flow from the monolayer towards the early capillary structure. This
model is developed into the framework of the continuum mechanics in which we
consider the endothelial monolayer as an active biopolymer film where the
nematic order emerges in the unjammed phase promoted by the VEGF activation. To
test the proposed ideas we implement the developed coupled equations into a
finite element code and describe, with a simplified geometry, the flow effect
and cells orientation from the monolayer to the capillary. In this work, we
propose an interpretation, from the top of the endothelial monolayer, based on
experimental observations and theoretical arguments to think the angiogenesis.
House Price Modeling with Digital Census
Date: 2018-08-29 00:00:00

Urban house prices are strongly associated with local socioeconomic factors.
In literature, house price modeling is based on socioeconomic variables from
traditional census, which is not real-time, dynamic and comprehensive. Inspired
by the emerging concept of "digital census" - using large-scale digital records
of human activities to measure urban population dynamics and socioeconomic
conditions, we introduce three typical datasets, namely 311 complaints, crime
complaints and taxi trips, into house price modeling. Based on the individual
housing sales data in New York City, we provide comprehensive evidence that
these digital census datasets can substantially improve the modeling
performances on both house price levels and changes, regardless whether
traditional census is included or not. Hence, digital census can serve as both
effective alternatives and complements to traditional census for house price
modeling.
Analysis of Sequence Polymorphism of LINEs and SINEs in Entamoeba histolytica
Date: 2018-09-10 00:00:00

The goal of this dissertation is to study the sequence polymorphism in
retrotransposable elements of Entamoeba histolytica. The Quasispecies theory, a
concept of equilibrium (stationary), has been used to understand the behaviour
of these elements. Two datasets of retrotransposons of Entamoeba histolytica
have been used. We present results from both datasets of retrotransposons
(SINE1s) of E. histolytica. We have calculated the mutation rate of EhSINE1s
for both datasets and drawn a phylogenetic tree for newly determined EhSINE1s
(dataset II). We have also discussed the variation in lengths of EhSINE1s for
both datasets. Using the quasispecies model, we have shown how sequences of
SINE1s vary within the population. The outputs of the quasispecies model are
discussed in the presence and the absence of back mutation by taking different
values of fitness. From our study of Non-long terminal repeat retrotransposons
(LINEs and their non-autonomous partner's SINEs) of Entamoeba histolytica, we
can conclude that an active EhSINE can generate very similar copies of itself
by retrotransposition. Due to this reason, it increases mutations which give
the result of sequence polymorphism. We have concluded that the mutation rate
of SINE is very high. This high mutation rate provides an idea for the
existence of SINEs, which may affect the genetic analysis of EhSINE1
ancestries, and calculation of phylogenetic distances.
EXS: Explainable Search Using Local Model Agnostic Interpretability
Authors: Singh Jaspreet, Anand Avishek
Date: 2018-09-11 00:00:00
Tasks: Information Retrieval, model, Retrieval

Retrieval models in information retrieval are used to rank documents for
typically under-specified queries. Today machine learning is used to learn
retrieval models from click logs and/or relevance judgments that maximizes an
objective correlated with user satisfaction. As these models become
increasingly powerful and sophisticated, they also become harder to understand.
Consequently, it is hard for to identify artifacts in training, data specific
biases and intents from a complex trained model like neural rankers even if
trained purely on text features. EXS is a search system designed specifically
to provide its users with insight into the following questions: `What is the
intent of the query according to the ranker?', `Why is this document ranked
higher than another?' and `Why is this document relevant to the query?'. EXS
uses a version of a popular posthoc explanation method for classifiers -- LIME,
adapted specifically to answer these questions. We show how such a system can
effectively help a user understand the results of neural rankers and highlight
areas of improvement.
A comparative stochastic and deterministic study of a class of epidemic dynamic models for malaria: exploring the impacts of noise on eradication and persistence of disease
Date: 2018-09-10 00:00:00

A comparative stochastic and deterministic study of a family of SEIRS
epidemic dynamic models for malaria is presented. The family type is determined
by the qualitative behavior of the nonlinear incidence rates of the disease.
Furthermore, the malaria models exhibit three random delays:- two of the delays
represent the incubation periods of the disease inside the vector and human
hosts, whereas the third delay is the period of effective natural immunity
against the disease. The stochastic malaria models are improved by including
the random environmental fluctuations in the disease transmission and natural
death rates of humans. Insights about the effects of the delays and the noises
on the malaria dynamics are gained via comparative analyses of the family of
stochastic and deterministic models, and further critical examination of the
significance of the intensities of the white noises in the system on (1) the
existence and stability of the equilibria, and also on (2) the eradication and
persistence of malaria in the human population. The basic reproduction numbers
and other threshold values for malaria in the stochastic and deterministic
settings are determined and compared for the cases of constant or random delays
in the system. Numerical simulation results are presented.
Mitigating Confirmation Bias on Twitter by Recommending Opposing Views
Authors: Lex Elisabeth, Wagner Mario, Kowald Dominik
Date: 2018-09-11 00:00:00

In this work, we propose a content-based recommendation approach to increase
exposure to opposing beliefs and opinions. Our aim is to help provide users
with more diverse viewpoints on issues, which are discussed in partisan groups
from different perspectives. Since due to the backfire effect, people's
original beliefs tend to strengthen when challenged with counter evidence, we
need to expose them to opposing viewpoints at the right time. The preliminary
work presented here describes our first step into this direction. As
illustrative showcase, we take the political debate on Twitter around the
presidency of Donald Trump.
Regression Discontinuity Designs Using Covariates
Date: 2018-09-11 00:00:00
Tasks: regression

We study regression discontinuity designs when covariates are included in the
estimation. We examine local polynomial estimators that include discrete or
continuous covariates in an additive separable way, but without imposing any
parametric restrictions on the underlying population regression functions. We
recommend a covariate-adjustment approach that retains consistency under
intuitive conditions, and characterize the potential for estimation and
inference improvements. We also present new covariate-adjusted mean squared
error expansions and robust bias-corrected inference procedures, with
heteroskedasticity-consistent and cluster-robust standard errors. An empirical
illustration and an extensive simulation study is presented. All methods are
implemented in \texttt{R} and \texttt{Stata} software packages.
Localization of Brain Activity from EEG/MEG Using MV-PURE Framework
Authors: Tomasz Piotrowski, Jan Nikadon, Alexander Moiseev
Date: 2018-09-11 00:00:00
Tasks: EEG, Electroencephalogram (EEG)

We consider the problem of localization of sources of brain electrical activity from electroencephalographic (EEG) and magnetoencephalographic (MEG) measurements using spatial filtering techniques. We propose novel reduced-rank activity indices based on the minimum-variance pseudo-unbiased reduced-rank estimation (MV-PURE) framework. The main results of this paper establish the key unbiasedness property of the proposed indices and their higher spatial resolution compared with full-rank indices in challenging task of localizing closely positioned and possibly highly correlated sources, especially in low signal-to-noise regime. Numerical examples are provided to illustrate the practical applicability of the proposed activity indices using both simulated and real data.
Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy
Date: 2018-09-11 00:00:00
Tasks: Anatomy

Focal epilepsy is a devastating neurological disorder that affects an
overwhelming number of patients worldwide, many of whom prove resistant to
medication. The efficacy of current innovative technologies for the treatment
of these patients has been stalled by the lack of accurate and effective
methods to fuse multimodal neuroimaging data to map anatomical targets driving
seizure dynamics. Here we propose a parsimonious model that explains how
large-scale anatomical networks and shared genetic constraints shape
inter-regional communication in focal epilepsy. In extensive ECoG recordings
acquired from a group of patients with medically refractory focal-onset
epilepsy, we find that ictal and preictal functional brain network dynamics can
be accurately predicted from features of brain anatomy and geometry, patterns
of white matter connectivity, and constraints complicit in patterns of gene
coexpression, all of which are conserved across healthy adult populations.
Moreover, we uncover evidence that markers of non-conserved architecture,
potentially driven by idiosyncratic pathology of single subjects, are most
prevalent in high frequency ictal dynamics and low frequency preictal dynamics.
Finally, we find that ictal dynamics are better predicted by white matter
features and more poorly predicted by geometry and genetic constraints than
preictal dynamics, suggesting that the functional brain network dynamics
manifest in seizures rely on - and may directly propagate along - underlying
white matter structure that is largely conserved across humans. Broadly, our
work offers insights into the generic architectural principles of the human
brain that impact seizure dynamics, and could be extended to further our
understanding, models, and predictions of subject-level pathology and response
to intervention.
Virus genome sequence classification using features based on nucleotides, words and compression
Date: 2018-09-11 00:00:00
Tasks: Descriptive

The ICTV develops, refines and maintains a universal virus taxonomy; Order is
the highest taxon in the branching hierarchy of recognised viral taxa.
Historically, ICTV (sub)committees have classified viruses on the basis of
morphological characteristics and various other attributes. Today, virtually
all new viral genomes are assembled from metagenomic datasets and are not
linked directly to biological agents. Thus, placing a virus into a taxonomic
scheme solely from primary genome structure is an increasingly important
problem. Various simple descriptive statistics of a viral genome sequence have
been used successfully for virus classification. Here, we use the NCBI's viral
and viroid reference sequence collection (RefSeq) and a common experimental
framework to compare the performance of different genome sequence-derived
features and classifiers in the task of assigning a virus to one of seven ICTV
Orders. The nucleotide-, word-, and compression-based features we consider
include genome length, the k-mer Natural Vector (k = 1, ..., 6) and its
derivatives, return time distribution, and general-purpose and DNA-specific
compression ratios; the classifiers used are the k-NN and SVM. The combination
of genome length and k-NN has the worst, yet still respectable, performance
(mean error rate of 0.137); the best performance is achieved using 4-mer counts
and SVM (mean error rate of 0.006). We investigate the main causes of
misclassification, explore which viruses are more difficult to classify, and
use the best performing combination to predict the Orders of 1,834 unclassified
viruses. A subsequent version of RefSeq assigned Orders to 17 of these
previously unlabelled viruses. Since 16 of our predictions match these
assignments, our approach could aid virologists dealing with viruses that are
known only from sequence data.
A phenomenological cluster-based model of Ca2+ waves and oscillations for Inositol 1,4,5-trisphosphate receptor (IP3R) channels
Authors: Svitlana Braichenko, Atul Bhaskar, Srinandan Dasmahapatra
Date: 2018-09-11 00:00:00
Tasks: Descriptive

Clusters of IP3 receptor channels in the membranes of the endoplasmic reticulum (ER) of many non-excitable cells release calcium ions in a cooperative manner giving rise to dynamical patterns such as Ca2+ puffs, waves, and oscillations that occur on multiple spatial and temporal scales. We introduce a minimal yet descriptive reaction-diffusion model of IP3 receptors for a saturating concentration of IP3 using a principled reduction of a detailed Markov chain description of individual channels. A dynamical systems analysis reveals the possibility of excitable, bistable and oscillatory dynamics of this model that correspond to three types of observed patterns of calcium release -- puffs, waves, and oscillations respectively. We explain the emergence of these patterns via a bifurcation analysis of a coupled two-cluster model, compute the phase diagram and quantify the speed of the waves and period of oscillations in terms of system parameters. We connect the termination of large-scale Ca2+ release events to IP3 unbinding or stochasticity.