pwc-archive/papers-with-abstracts huggingface dataset:
ReconMap: An interactive visualisation of human metabolism
Date: 2016-05-31 00:00:00

A genome-scale reconstruction of human metabolism, Recon 2, is available but
no interface exists to interactively visualise its content integrated with
omics data and simulation results. We manually drew a comprehensive map,
ReconMap 2.0, that is consistent with the content of Recon 2. We present it
within a web interface that allows content query, visualization of custom
datasets and submission of feedback to manual curators. ReconMap can be
accessed via http://vmh.uni.lu, with network export in a Systems Biology
Graphical Notation compliant format. A Constraint-Based Reconstruction and
Analysis (COBRA) Toolbox extension to interact with ReconMap is available via
https://github.com/opencobra/cobratoolbox.
Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression
Date: 2016-09-26 00:00:00

Constraint-Based Reconstruction and Analysis (COBRA) is currently the only
methodology that permits integrated modeling of Metabolism and macromolecular
Expression (ME) at genome-scale. Linear optimization computes steady-state flux
solutions to ME models, but flux values are spread over many orders of
magnitude. Standard double-precision solvers may return inaccurate solutions or
report that no solution exists. Exact simplex solvers are extremely slow and
hence not practical for ME models that currently have 70,000 constraints and
variables and will grow larger. We have developed a quadruple-precision version
of our linear and nonlinear optimizer MINOS, and a solution procedure (DQQ)
involving Double and Quad MINOS that achieves efficiency and reliability for ME
models. DQQ enables extensive use of large, multiscale, linear and nonlinear
models in systems biology and many other applications.
Exploratory Adaptation in Large Random Networks
Date: 2017-01-29 00:00:00

The capacity of cells and organisms to respond to challenging conditions in a
repeatable manner is limited by a finite repertoire of pre-evolved adaptive
responses. Beyond this capacity, cells can use exploratory dynamics to cope
with a much broader array of conditions. However, the process of adaptation by
exploratory dynamics within the lifetime of a cell is not well understood. Here
we demonstrate the feasibility of exploratory adaptation in a high-dimensional
network model of gene regulation. Exploration is initiated by failure to comply
with a constraint and is implemented by random sampling of network
configurations. It ceases if and when the network reaches a stable state
satisfying the constraint. We find that successful convergence (adaptation) in
high dimensions requires outgoing network hubs and is enhanced by their
auto-regulation. The ability of these empirically-validated features of gene
regulatory networks to support exploratory adaptation without fine-tuning,
makes it plausible for biological implementation.
Estimating the EMG response exclusively to fatigue during sustained static maximum voluntary contraction
Date: 2016-05-24 00:00:00

The increase of surface electromyography (sEMG) root-mean-square (RMS) is
very frequently used to determine fatigue. However, as RMS is also influenced
by muscle force,its effective usage as indicator of fatigue is mainly limited
to isometric, constant force tasks.This research develops a simple me-thodto
preclude the effect of muscle force, hereby estimates the EMG amplitude
response exclusively to fatigue with RMS. Experiment was carried out on the
biceps brachiis of 15 subjects (7males, 8 females) during sustained static
maximum voluntary contractions (sMVC).Result shows that the sEMG RMS response
to fatigue increasesto 21.27% while muscle force decreasing to 50%MVC, which
implies that more and more extra effort is needed as muscle fatigue
intensifies. It would be promising to use the RMS response exclusively to
fatigue as an indicator of muscle fatigue.
Quantum consciousness in warm, wet, and noisy brain
Date: 2016-07-14 00:00:00

The emergence of quantum consciousness stems from dynamic flows of hydrogen
ions in brain liquid. This liquid contains vast areas of the fourth phase of
water with hexagonal packing of its molecules, the so-called exclusion zone
(EZ) of water. The hydrogen ion motion on such hexagonal lattices shows as the
hopping of the ions forward and the holes (vacant places) backward, caused by
the Grotthuss mechanism. By supporting this motion using external infrasound
sources, one may achieve the appearance of the superfluid state of the EZ
water. Flows of the hydrogen ions are described by the modified Navier-Stokes
equation. It, along with the continuity equation, yields the nonlinear
Schrodinger equation, which describes the quantum effects of these flows, such
as the tunneling at long distances or the interference on gap junctions.
Applying Adomian Decomposition Method to Solve Burgess Equation with a Non-linear Source
Date: 2016-01-14 00:00:00

In the present work we consider the mathematical model that describes brain
tumour growth (glioblastomas) under medical treatment. Based on the medical
study presented by R. Stupp et al. (New Engl Journal of Med 352: 987-996, 2005)
which evidence that, combined therapies such as, radiotherapy and chemotherapy,
produces negative tumour-growth, and using the mathematical model of P. K.
Burgess et al. (J Neuropath and Exp Neur 56: 704-713, 1997) as an starting
point, we present a model for tumour growth under medical treatment represented
by a non-linear partial differential equation that is solved using the Adomian
Decomposition Method (ADM). It is also shown that the non-linear term
efficiently models the effects of the combined therapies. By means of a proper
use of parameters, this model could be used for calculating doses in
radiotherapy and chemotherapy.
Residential income segregation: A behavioral model of the housing market
Date: 2018-10-20 00:00:00

We represent the functioning of the housing market and study the relation
between income segregation, income inequality and house prices by introducing a
spatial Agent-Based Model (ABM). Differently from traditional models in urban
economics, we explicitly specify the behavior of buyers and sellers and the
price formation mechanism. Buyers who differ by income select among
heterogeneous neighborhoods using a probabilistic model of residential choice;
sellers employ an aspiration level heuristic to set their reservation offer
price; prices are determined through a continuous double auction. We first
provide an approximate analytical solution of the ABM, shedding light on the
structure of the model and on the effect of the parameters. We then simulate
the ABM and find that: (i) a more unequal income distribution lowers the prices
globally, but implies stronger segregation; (ii) a spike of the demand in one
part of the city increases the prices all over the city; (iii) subsidies are
more efficient than taxes in fostering social mixing.
Modelling cross-reactivity and memory in the cellular adaptive immune response to influenza infection in the host
Date: 2016-11-22 00:00:00

The cellular adaptive immune response plays a key role in resolving influenza
infection. Experiments where individuals are successively infected with
different strains within a short timeframe provide insight into the underlying
viral dynamics and the role of a cross-reactive immune response in resolving an
acute infection. We construct a mathematical model of within-host influenza
viral dynamics including three possible factors which determine the strength of
the cross-reactive cellular adaptive immune response: the initial naive T cell
number, the avidity of the interaction between T cells and the epitopes
presented by infected cells, and the epitope abundance per infected cell. Our
model explains the experimentally observed shortening of a second infection
when cross-reactivity is present, and shows that memory in the cellular
adaptive immune response is necessary to protect against a second infection.
On American VIX options under the generalized 3/2 and 1/2 models
Date: 2017-07-17 00:00:00

In this paper, we extend the 3/2-model for VIX studied by Goard and Mazur
(2013) and introduce the generalized 3/2 and 1/2 classes of volatility
processes. Under these models, we study the pricing of European and American
VIX options and, for the latter, we obtain an early exercise premium
representation using a free-boundary approach and local time-space calculus.
The optimal exercise boundary for the volatility is obtained as the unique
solution to an integral equation of Volterra type.
  We also consider a model mixing these two classes and formulate the
corresponding optimal stopping problem in terms of the observed factor process.
The price of an American VIX call is then represented by an early exercise
premium formula. We show the existence of a pair of optimal exercise boundaries
for the factor process and characterize them as the unique solution to a system
of integral equations.
Low-dimensional Query Projection based on Divergence Minimization Feedback Model for Ad-hoc Retrieval
Authors: Dadashkarimi Javid, Sabet Masoud Jalili, Faili Heshaam, Shakery Azadeh
Date: 2016-12-22 00:00:00
Tasks: Language Modeling, Language Modelling, Retrieval

Low-dimensional word vectors have long been used in a wide range of
applications in natural language processing. In this paper we shed light on
estimating query vectors in ad-hoc retrieval where a limited information is
available in the original query. Pseudo-relevance feedback (PRF) is a
well-known technique for updating query language models and expanding the
queries with a number of relevant terms. We formulate the query updating in
low-dimensional spaces first with rotating the query vector and then with
scaling. These consequential steps are embedded in a query-specific projection
matrix capturing both angle and scaling. In this paper we propose a new but not
the most effective technique necessarily for PRF in language modeling, based on
the query projection algorithm. We learn an embedded coefficient matrix for
each query, whose aim is to improve the vector representation of the query by
transforming it to a more reliable space, and then update the query language
model. The proposed embedded coefficient divergence minimization model (ECDMM)
takes top-ranked documents retrieved by the query and obtains a couple of
positive and negative sample sets; these samples are used for learning the
coefficient matrix which will be used for projecting the query vector and
updating the query language model using a softmax function. Experimental
results on several TREC and CLEF data sets in several languages demonstrate
effectiveness of ECDMM. The experimental results reveal that the new
formulation for the query works as well as state-of-the-art PRF techniques and
outperforms state-of-the-art PRF techniques in a TREC collection in terms of
MAP,P@5, and P@10 significantly.
Hemoglobin Strain Field Waves and Allometric Functionality
Date: 2016-05-30 00:00:00

Hemoglobin (Hgb) forms tetramers (dimerized dimers), which enhance its
globular stability and may also facilitate small gas molecule transport, as
shown by recent all-atom Newtonian solvated simulations. Hydropathic
bioinformatic scaling reveals many wave-like features of strained Hgb
structures at the coarse-grained amino acid level, while distinguishing between
these features thermodynamically. Strain fields localized near hemes interfere
with extended strain fields associated with dimer interfacial misfit, resulting
in wave-length dependent dimer correlation function antiresonances.
The load-response of the flagellar beat
Date: 2016-11-21 00:00:00

Cilia and flagella exhibit regular bending waves that perform mechanical work
on the surrounding fluid, to propel cellular swimmers and pump fluids inside
organisms. Here, we quantify a force-velocity relationship of the beating
flagellum, by exposing flagellated \emph{Chlamydomonas} cells to controlled
microfluidic flows. A simple theory of flagellar limit-cycle oscillations,
calibrated by measurements in the absence of flow, reproduces this relationship
quantitatively. We derive a link between the chemo-mechanical efficiency of the
flagellar beat and its ability to synchronize to oscillatory flows.
Estimate of the reproduction number of the 2015 Zika virus outbreak in Barranquilla, Colombia, and estimation of the relative role of sexual transmission
Date: 2017-01-15 00:00:00

Background: In 2015, the Zika arbovirus (ZIKV) began circulating in the
Americas, rapidly expanding its global geographic range in explosive outbreaks.
Unusual among mosquito-borne diseases, ZIKV has been shown to also be sexually
transmitted, although sustained autochthonous transmission due to sexual
transmission alone has not been observed, indicating the reproduction number
(R0) for sexual transmission alone is less than 1. Critical to the assessment
of outbreak risk, estimation of the potential attack rates, and assessment of
control measures, are estimates of the basic reproduction number, R0. Methods:
We estimated the R0 of the 2015 ZIKV outbreak in Barranquilla, Colombia,
through an analysis of the exponential rise in clinically identified ZIKV cases
(n = 359 to the end of November, 2015). Findings: The rate of exponential rise
in cases was rho=0.076 days-1, with 95 percent CI [0.066,0.087] days-1. We used
a vector-borne disease model with additional direct transmission to estimate
the R0; assuming the R0 of sexual transmission alone is less than 1, we
estimated the total R0 = 3.8 [2.4,5.6], and that the fraction of cases due to
sexual transmission was 0.23 [0.01,0.47] with 95 percent confidence.
Interpretation: This is among the first estimates of R0 for a ZIKV outbreak in
the Americas, and also among the first quantifications of the relative impact
of sexual transmission.
The Problem of Calibrating an Agent-Based Model of High-Frequency Trading
Date: 2017-03-23 00:00:00
Tasks: Time Series, Time Series Analysis

Agent-based models, particularly those applied to financial markets,
demonstrate the ability to produce realistic, simulated system dynamics,
comparable to those observed in empirical investigations. Despite this, they
remain fairly difficult to calibrate due to their tendency to be
computationally expensive, even with recent advances in technology. For this
reason, financial agent-based models are frequently validated by demonstrating
an ability to reproduce well-known log return time series and central limit
order book stylized facts, as opposed to being rigorously calibrated to
transaction data. We thus apply an established financial agent-based model
calibration framework to a simple model of high- and low-frequency trader
interaction and demonstrate possible inadequacies of a stylized fact-centric
approach to model validation. We further argue for the centrality of
calibration to the validation of financial agent-based models and possible
pitfalls of current approaches to financial agent-based modeling.
Image-Based Modeling of Blood Flow and Oxygen Transfer in Feto-Placental Capillaries
Date: 2016-10-27 00:00:00

During pregnancy, oxygen diffuses from maternal to fetal blood through
villous trees in the placenta. In this paper, we simulate blood flow and oxygen
transfer in feto-placental capillaries by converting three-dimensional
representations of villous and capillary surfaces, reconstructed from confocal
laser scanning microscopy, to finite-element meshes, and calculating values of
vascular flow resistance and total oxygen transfer. The relationship between
the total oxygen transfer rate and the pressure drop through the capillary is
shown to be captured across a wide range of pressure drops by physical scaling
laws and an upper bound on the oxygen transfer rate. A regression equation is
introduced that can be used to estimate the oxygen transfer in a capillary
using the vascular resistance. Two techniques for quantifying the effects of
statistical variability, experimental uncertainty and pathological placental
structure on the calculated properties are then introduced. First, scaling
arguments are used to quantify the sensitivity of the model to uncertainties in
the geometry and the parameters. Second, the effects of localized dilations in
fetal capillaries are investigated using an idealized axisymmetric model, to
quantify the possible effect of pathological placental structure on oxygen
transfer. The model predicts how, for a fixed pressure drop through a
capillary, oxygen transfer is maximized by an optimal width of the dilation.
The results could explain the prevalence of fetal hypoxia in cases of delayed
villous maturation, a pathology characterized by a lack of the
vasculo-syncytial membranes often seen in conjunction with localized capillary
dilations.
Inference of Causal Information Flow in Collective Animal Behavior
Date: 2016-12-29 00:00:00
Tasks: Time Series, Time Series Analysis

Understanding and even defining what constitutes animal interactions remains
a challenging problem. Correlational tools may be inappropriate for detecting
communication between a set of many agents exhibiting nonlinear behavior. A
different approach is to define coordinated motions in terms of an information
theoretic channel of direct causal information flow. In this work, we consider
time series data obtained by an experimental protocol of optical tracking of
the insect species Chironomus riparius. The data constitute reconstructed 3-D
spatial trajectories of the insects' flight trajectories and kinematics. We
present an application of the optimal causation entropy (oCSE) principle to
identify direct causal relationships or information channels among the insects.
The collection of channels inferred by oCSE describes a network of information
flow within the swarm. We find that information channels with a long spatial
range are more common than expected under the assumption that causal
information flows should be spatially localized. The tools developed herein are
general and applicable to the inference and study of intercommunication
networks in a wide variety of natural settings.
Trends for isolated amino acids and dipeptides: Conformation, divalent ion binding, and remarkable similarity of binding to calcium and lead
Date: 2016-09-14 00:00:00

We derive structural and binding energy trends for twenty amino acids, their
dipeptides, and their interactions with the divalent cations Ca$^{2+}$,
Ba$^{2+}$, Sr$^{2+}$, Cd$^{2+}$, Pb$^{2+}$, and Hg$^{2+}$. The underlying data
set consists of 45,892 first-principles predicted conformers with relative
energies up to about 4 eV (about 400kJ/mol). We show that only very few
distinct backbone structures of isolated amino acids and their dipeptides
emerge as lowest-energy conformers. The isolated amino acids predominantly
adopt structures that involve an acidic proton shared between the carboxy and
amino function. Dipeptides adopt one of two intramolecular-hydrogen bonded
conformations C$_5$ or equatorial C$_7$. Upon complexation with a divalent
cation, the accessible conformational space shrinks and intramolecular hydrogen
bonding is prevented due to strong electrostatic interaction of backbone and
side chain functional groups with cations. Clear correlations emerge from the
binding energies of the six divalent ions with amino acids and dipeptides.
Cd$^{2+}$ and Hg$^{2+}$ show the largest binding energies - a potential
correlation with their known high acute toxicities. Ca$^{2+}$ and Pb$^{2+}$
reveal almost identical binding energies across the entire series of amino
acids and dipeptides. This observation validates past indications that
ion-mimicry of calcium and lead should play an important role in a
toxicological context.
Decoding dynamic brain patterns from evoked responses: A tutorial on multivariate pattern analysis applied to time-series neuroimaging data
Date: 2016-09-30 00:00:00
Tasks: Brain Decoding, Dimensionality Reduction, EEG, Electroencephalogram (EEG), Time Series, Time Series Analysis

Multivariate pattern analysis (MVPA) or brain decoding methods have become
standard practice in analysing fMRI data. Although decoding methods have been
extensively applied in Brain Computing Interfaces (BCI), these methods have
only recently been applied to time-series neuroimaging data such as MEG and EEG
to address experimental questions in Cognitive Neuroscience. In a
tutorial-style review, we describe a broad set of options to inform future
time-series decoding studies from a Cognitive Neuroscience perspective. Using
example MEG data, we illustrate the effects that different options in the
decoding analysis pipeline can have on experimental results where the aim is to
'decode' different perceptual stimuli or cognitive states over time from
dynamic brain activation patterns. We show that decisions made at both
preprocessing (e.g., dimensionality reduction, subsampling, trial averaging)
and decoding (e.g., classifier selection, cross-validation design) stages of
the analysis can significantly affect the results. In addition to standard
decoding, we describe extensions to MVPA for time-varying neuroimaging data
including representational similarity analysis, temporal generalisation, and
the interpretation of classifier weight maps. Finally, we outline important
caveats in the design and interpretation of time-series decoding experiments.
A Minimum Spanning Tree Representation of Anime Similarities
Authors: Wibowo Canggih Puspo
Date: 2017-12-11 00:00:00

In this work, a new way to represent Japanese animation (anime) is presented.
We applied a minimum spanning tree to show the relation between anime. The
distance between anime is calculated through three similarity measurements,
namely crew, score histogram, and topic similarities. Finally, the centralities
are also computed to reveal the most significance anime. The result shows that
the minimum spanning tree can be used to determine the similarity anime.
Furthermore, by using centralities calculation, we found some anime that are
significant to others.
Intrinsic noise and deviations from criticality in Boolean gene-regulatory networks
Date: 2016-06-10 00:00:00

Gene regulatory networks can be successfully modeled as Boolean networks. A
much discussed hypothesis says that such model networks reproduce empirical
findings the best if they are tuned to operate at criticality, i.e. at the
borderline between their ordered and disordered phases. Critical networks have
been argued to lead to a number of functional advantages such as maximal
dynamical range, maximal sensitivity to environmental changes, as well as to an
excellent trade off between stability and flexibility. Here, we study the
effect of noise within the context of Boolean networks trained to learn complex
tasks under supervision. We verify that quasi-critical networks are the ones
learning in the fastest possible way --even for asynchronous updating rules--
and that the larger the task complexity the smaller the distance to
criticality. On the other hand, when additional sources of intrinsic noise in
the network states and/or in its wiring pattern are introduced, the optimally
performing networks become clearly subcritical. These results suggest that in
order to compensate for inherent stochasticity, regulatory and other type of
biological networks might become subcritical rather than being critical, all
the most if the task to be performed has limited complexity.
Model-free portfolio theory and its functional master formula
Date: 2018-05-24 00:00:00

We use pathwise It\^o calculus to prove two strictly pathwise versions of the
master formula in Fernholz' stochastic portfolio theory. Our first version is
set within the framework of F\"ollmer's pathwise It\^o calculus and works for
portfolios generated from functions that may depend on the current states of
the market portfolio and an additional path of finite variation. The second
version is formulated within the functional pathwise It\^o calculus of Dupire
(2009) and Cont \& Fourni\'e (2010) and allows for portfolio-generating
functionals that may depend additionally on the entire path of the market
portfolio. Our results are illustrated by several examples and shown to work on
empirical market data.