pwc-archive/papers-with-abstracts huggingface dataset:
Role of Resultant Dipole Moment in Mechanical Dissociation of Biological Complexes
Date: 2018-08-10 00:00:00

Protein-peptide interactions play essential roles in many cellular processes
and their structural characterization is the major focus of current
experimental and theoretical research. Two decades ago, it was proposed to
employ the steered molecular dynamics to assess the strength of protein-peptide
interactions. The idea behind using steered molecular dynamics simulations is
that the mechanical stability can be used as a promising and an efficient
alternative to computationally highly demanding estimation of binding affinity.
However, mechanical stability defined as a peak in force-extension profile
depends on the choice of the pulling direction. Here we propose an uncommon
choice of the pulling direction along resultant dipole moment vector, which has
not been explored in simulations so far. Using explicit solvent all-atom MD
simulations, we apply steered molecular dynamics technique to probe mechanical
resistance of protein-peptide system pulled along two different vectors. A
novel pulling direction, along the resultant dipole moment vector, results in
stronger forces compared to commonly used peptide unbinding along center of
masses vector. Our results demonstrate that resultant dipole moment is one of
the factors influencing the mechanical stability of protein-peptide complex.
Small-time moderate deviations for the randomised Heston model
Date: 2018-08-10 00:00:00

We extend previous large deviations results for the randomised Heston model
to the case of moderate deviations. The proofs involve the G\"artner-Ellis
theorem and sharp large deviations tools.
"Quantum Equilibrium-Disequilibrium": Asset Price Dynamics, Symmetry Breaking, and Defaults as Dissipative Instantons
Date: 2019-05-28 00:00:00
Tasks: Friction

We propose a simple non-equilibrium model of a financial market as an open
system with a possible exchange of money with an outside world and market
frictions (trade impacts) incorporated into asset price dynamics via a feedback
mechanism. Using a linear market impact model, this produces a non-linear
two-parametric extension of the classical Geometric Brownian Motion (GBM)
model, that we call the "Quantum Equilibrium-Disequilibrium" (QED) model. The
QED model gives rise to non-linear mean-reverting dynamics, broken scale
invariance, and corporate defaults. In the simplest one-stock (1D) formulation,
our parsimonious model has only one degree of freedom, yet calibrates to both
equity returns and credit default swap spreads. Defaults and market crashes are
associated with dissipative tunneling events, and correspond to instanton
(saddle-point) solutions of the model. When market frictions and
inflows/outflows of money are neglected altogether, "classical" GBM
scale-invariant dynamics with an exponential asset growth and without defaults
are formally recovered from the QED dynamics. However, we argue that this is
only a formal mathematical limit, and in reality the GBM limit is non-analytic
due to non-linear effects that produce both defaults and divergence of
perturbation theory in a small market friction parameter.
On smile properties of volatility derivatives and exotic products: understanding the VIX skew
Date: 2018-08-10 00:00:00

We develop a method to study the implied volatility for exotic options and
volatility derivatives with European payoffs such as VIX options. Our approach,
based on Malliavin calculus techniques, allows us to describe the properties of
the at-the-money implied volatility (ATMI) in terms of the Malliavin
derivatives of the underlying process. More precisely, we study the short-time
behaviour of the ATMI level and skew. As an application, we describe the
short-term behavior of the ATMI of VIX and realized variance options in terms
of the Hurst parameter of the model, and most importantly we describe the class
of volatility processes that generate a positive skew for the VIX implied
volatility. In addition, we find that our ATMI asymptotic formulae perform very
well even for large maturities. Several numerical examples are provided to
support our theoretical results.
A Novel Method for Epileptic Seizure Detection Using Coupled Hidden Markov Models
Date: 2018-08-10 00:00:00
Tasks: EEG, Electroencephalogram (EEG), Seizure Detection, Variational Inference

We propose a novel Coupled Hidden Markov Model to detect epileptic seizures
in multichannel electroencephalography (EEG) data. Our model defines a network
of seizure propagation paths to capture both the temporal and spatial evolution
of epileptic activity. To address the intractability introduced by the coupled
interactions, we derive a variational inference procedure to efficiently infer
the seizure evolution from spectral patterns in the EEG data. We validate our
model on EEG aquired under clinical conditions in the Epilepsy Monitoring Unit
of the Johns Hopkins Hospital. Using 5-fold cross validation, we demonstrate
that our model outperforms three baseline approaches which rely on a classical
detection framework. Our model also demonstrates the potential to localize
seizure onset zones in focal epilepsy.
Same but not alike: Structure, flexibility and energetics of domains in multi-domain proteins are influenced by the presence of other domains
Date: 2018-08-10 00:00:00

The majority of the proteins encoded in the genomes of eukaryotes contain
more than one domain. Reasons for high prevalence of multi-domain proteins in
various organisms have been attributed to higher stability and functional and
folding advantages over single-domain proteins. Despite these advantages, many
proteins are composed of only one domain while their homologous domains are
part of multi-domain proteins. In the study presented here, differences in the
properties of protein domains in single-domain and multi-domain systems and
their influence on functions are discussed. We studied 20 pairs of identical
protein domains, which were crystallized in two forms (a) tethered to other
proteins domains and (b) tethered to fewer protein domains than (a) or not
tethered to any protein domain. Results suggest that tethering of domains in
multi-domain proteins influences the structural, dynamic and energetic
properties of the constituent protein domains. 50% of the protein domain pairs
show significant structural deviations while 90% of the protein domain pairs
show differences in dynamics and 12% of the residues show differences in the
energetics. To gain further insights on the influence of tethering on the
function of the domains, 4 pairs of homologous protein domains, where one of
them is a full-length single-domain protein and the other protein domain is a
part of a multi-domain protein, were studied. Analyses showed that identical
and structurally equivalent functional residues show differential dynamics in
homologous protein domains, though comparable dynamics between in-silico
generated chimera protein and multi-domain proteins were observed. From these
observations, the differences observed in the functions of homologous proteins
could be attributed to the presence of tethered domain. Overall, we conclude
that tethered domains in multi-domain proteins not only provide stability or
folding advantages but also influence pathways resulting in differences in
function or regulatory properties.
Metrics for describing dyadic movement: a review
Date: 2018-08-15 00:00:00

In movement ecology, the few works that have taken collective behaviour into
account are data-driven and rely on simplistic theoretical assumptions, relying
in metrics that may or may not be measuring what is intended. In the present
paper, we focus on pairwise joint-movement behaviour, where individuals move
together during at least a segment of their path. We investigate the adequacy
of twelve metrics introduced in previous works for assessing joint movement by
analysing their theoretical properties and confronting them with contrasting
case scenarios. Three criteria are taken into account for review of those
metrics: 1) practical use, 2) dependence on parameters and underlying
assumptions, and 3) computational cost. When analysing the similarities between
the metrics as defined, we show how some of them can be expressed using general
mathematical forms. In addition, we evaluate the ability of each metric to
assess specific aspects of joint-movement behaviour: proximity (closeness in
space-time) and coordination (synchrony) in direction and speed. We found that
some metrics are better suited to assess proximity and others are more
sensitive to coordination. To help readers choose metrics, we elaborate a
graphical representation of the metrics in the coordination and proximity space
based on our results, and give a few examples of proximity and coordination
focus in different movement studies.
RNAmountAlign: efficient software for local, global, semiglobal pairwise and multiple RNA sequence/structure alignment
Date: 2018-08-10 00:00:00
Tasks: Benchmarking

Alignment of structural RNAs is an important problem with a wide range of
applications. Since function is often determined by molecular structure, RNA
alignment programs should take into account both sequence and base-pairing
information for structural homology identi^Lcation. A number of successful
alignment programs are heuristic versions of Sanko^K's optimal algorithm. Most
of them require O(n4) run time. This paper describes C++ software,
RNAmountAlign, for RNA sequence/structure alignment that runs in O(n3) time and
O(n2) space; moreover, our software returns a p-value (transformable to expect
value E) based on Karlin-Altschul statistics for local alignment, as well as
parameter ^Ltting for local and global alignment. Using incremental mountain
height, a representation of structural information computable in cubic time,
RNAmountAlign implements quadratic time pairwise local, global and
global/semiglobal (query search) alignment using a weighted combination of
sequence and structural similarity. RNAmountAlign is capable of performing
progressive multiple alignment as well. Benchmarking of RNAmountAlign against
LocARNA, LARA, FOLDALIGN, DYNALIGN and STRAL shows that RNAmountAlign has
reasonably good accuracy and much faster run time supporting all alignment
types.
Development of an 8 channel sEMG wireless device based on ADS1299 with Virtual Instrumentation
Date: 2018-08-10 00:00:00

In this paper, a different approach on the use of the ADS1299 (an analog
front-end with features for electroencephalogram and electrocardiography signal
acquisition) is considered, proposing the development of a surface
electromyography (sEMG) device. The main features of the device include
simultaneous recordings of eight muscular channels, wireless transmission and
virtual instrumentation with the use of LabVIEWTM software. The proposed sEMG
device contains a specifically designed protocol to accommodate data
transmission by reducing the data size while still delivering adequate
resolution (34.33 uV), amplitude range (17.57 mV) and sampling rate (1000 Hz)
for sEMG signals. For the validation methods, a generated sine wave and a known
sEMG data were evaluated. Moreover, the muscular recordings for all the eight
channels of a human arm were successful and the results expose the isolated
contractions of the triceps and the biceps with their amplitude range and
frequency spectrum.
GL-BLSTM: a novel structure of bidirectional long-short term memory for disulfide bonding state prediction
Date: 2018-08-11 00:00:00

Background: Disulfide bonds are crucial to protein structural formation.
Developing an effective method topredict disulfide bonding formation is
important for protein structural modeling and functional study. Mostcurrent
methods still have shortcomings, including low accuracy and strict requirements
for the selection ofdiscriminative features. Results: In this study, we
introduced a nested structure of Bidirectional Long-short Term
Memory(BLSTM)neural network called Global-Local-BLSTM (GL-BLSTM) for disulfide
bonding state prediction. Based on thepatterns of disulfide bond formation, a
BLSTM network called Local-BLSTM is used to extract context-basedfeatures
around every Cys residue. Another BLSTM network called Global-BLSTM is
introduced aboveLocal-BLSTM layer to integrate context-based features of all
Cys residues in the same protein chain, therebyinvolving inter-residue
relationships in the training process. According to our experimental
results,GL-BLSTMnetwork performs much better than other methods, GL-BLSTM
reached 90.26% accuracy at residue-level and 83.66% at protein-level. This
model has reached the state of the art in this field. Conclusion: GL-BLSTMs
special structure and mechanisms are beneficial to disulfide bonding state
prediction.By applying bidirectional LSTM, it can extract context based
features by processing protein sequences, therebyobtain more discriminative
information than traditional machine learning methods. Whats more,
GL-BLSTMsspecial two-layer structure enables it to extract both local and
global features, in which global features areplaying important roles in
improving prediction accuracy, especially at protein-level. Keywords: Disulfide
bonds; Prediction; Deep learning; Bidirectional long short term memory
The Impact of Age on Nationality Bias: Evidence from Ski Jumping
Date: 2018-08-11 00:00:00

This empirical research explores the impact of age on nationality bias. World
Cup competition data suggest that judges of professional ski jumping
competitions prefer jumpers of their own nationality and exhibit this
preference by rewarding them with better marks. Furthermore, the current study
reveals that this nationality bias is diminished among younger judges, in
accordance with the reported lower levels of national discrimination among
younger generations. Globalisation and its effect in reducing class-based
thinking may explain this reduced bias in judgment of others.
A single coordinate framework for optic flow and binocular disparity
Date: 2018-08-11 00:00:00

Optic flow is two dimensional, but no special qualities are attached to one
or other of these dimensions. For binocular disparity, on the other hand, the
terms 'horizontal' and 'vertical' disparities are commonly used. This is odd,
since binocular disparity and optic flow describe essentially the same thing.
The difference is that, generally, people tend to fixate relatively close to
the direction of heading as they move, meaning that fixation is close to the
optic flow epipole, whereas, for binocular vision, fixation is close to the
head-centric midline, i.e. approximately 90 degrees from the binocular epipole.
For fixating animals, some separations of flow may lead to simple algorithms
for the judgement of surface structure and the control of action. We consider
the following canonical flow patterns that sum to produce overall flow: (i)
'towards' flow, the component of translational flow produced by approaching (or
retreating from) the fixated object, which produces pure radial flow on the
retina; (ii) 'sideways' flow, the remaining component of translational flow,
which is produced by translation of the optic centre orthogonal to the
cyclopean line of sight and (iii) 'vergence' flow, rotational flow produced by
a counter-rotation of the eye in order to maintain fixation. A general flow
pattern could also include (iv) 'cyclovergence' flow, produced by rotation of
one eye relative to the other about the line of sight. We consider some
practical advantages of dividing up flow in this way when an observer fixates
as they move. As in some previous treatments, we suggest that there are certain
tasks for which it is sensible to consider 'towards' flow as one component and
'sideways' + 'vergence' flow as another.
Multi-Cell Massive MIMO in LoS
Date: 2018-08-12 00:00:00

We consider a multi-cell Massive MIMO system in a line-of-sight (LoS)
propagation environment, for which each user is served by one base station,
with no cooperation among the base stations. Each base station knows the
channel between its service antennas and its users, and uses these channels for
precoding and decoding. Under these assumptions we derive explicit downlink and
uplink effective SINR formulas for maximum-ratio (MR) processing and
zero-forcing (ZF) processing. We also derive formulas for power control to meet
pre-determined SINR targets. A numerical example demonstrating the usage of the
derived formulas is provided.
Mechanism Design with News Utility
Date: 2018-08-12 00:00:00

News utility is the idea that the utility of an agent depends on changes in
her beliefs over consumption and money. We introduce news utility into
otherwise classical static Bayesian mechanism design models. We show that a key
role is played by the timeline of the mechanism, i.e. whether there are delays
between the announcement stage, the participation stage, the play stage and the
realization stage of a mechanism. Depending on the timing, agents with news
utility can experience two additional news utility effects: a surprise effect
derived from comparing to pre-mechanism beliefs, as well as a realization
effect derived from comparing post-play beliefs with the actual outcome of the
mechanism.
  We look at two distinct mechanism design settings reflecting the two main
strands of the classical literature. In the first model, a monopolist screens
an agent according to the magnitude of her loss aversion. In the second model,
we consider a general multi-agent Bayesian mechanism design setting where the
uncertainty of each player stems from not knowing the intrinsic types of the
other agents. We give applications to auctions and public good provision which
illustrate how news utility changes classical results.
  For both models we characterize the optimal design of the timeline. A
timeline featuring no delay between participation and play but a delay in
realization is never optimal in either model. In the screening model the
optimal timeline is one without delays. In auction settings, under fairly
natural assumptions the optimal timeline has delays between all three stages of
the mechanism.
Modeling and Simulation of Regenerative Braking Energy in DC Electric Rail Systems
Date: 2018-08-13 00:00:00

Regenerative braking energy is the energy produced by a train during
deceleration. When a train decelerates, the motors act as generators and
produce electricity. This energy can be fed back to the third rail and consumed
by other trains accelerating nearby. If there are no nearby trains, this energy
is dumped as heat to avoid over voltage. Regenerative braking energy can be
saved by installing energy storage systems (ESS) and reused later when it is
needed. To find a suitable design, size and placement of energy storage, a good
understanding of this energy is required. The aim of this paper is to model and
simulate regenerative braking energy. The dc electric rail transit system model
introduced in this paper includes trains, substations and rail systems.
Quantification of the underlying mechanisms and relationship among cancer, metastasis and differentiation/development
Date: 2018-08-13 00:00:00

Recurrence and metastasis have been regarded as two of the greatest obstacles
for curing cancer. Cancer stem cell (CSC) have been found. They contribute to
cancer development with the distinct feature of recurrence and resistance to
the popular treatments such as drugs and chemotherapy. In addition, recent
discoveries suggest that the epithelial mesenchymal transition (EMT) is an
essential process in normal embryogenesis and tissue repair, which is a
required step in cancer metastasis. Although there are many indications showing
the connections between metastasis and stem cell, researches often studied them
separately or at most bi-laterally, not in an integrated way. In this study, we
aim at exploring the global mechanisms and interrelationship among cancer,
development and metastasis which are currently poorly understood. To start, we
constructed a core gene regulatory network motif which contain specific genes
and microRNAs of CSC, EMT and cancer. We uncovered seven distinct states
emerged from the underlying landscape. They are identified as Normal,
Premalignant, Cancer, stem cell (SC), cancer stem cell (CSC), Lesion and
Hyperlasia state. Given the biological definition of each state, we also
discussed the metastasis ability of each state. We show how and which types of
cells can be transformed to a cancer state and the connections among cancer,
CSC and EMT. The barrier height and flux of the kinetic paths are explored to
quantify how and which cells switch stochastically between the states. Our
landscape model provides a quantitative way which reveals the global mechanisms
of cancer, development and metastasis.
Random field theory-based p-values: A review of the SPM implementation
Authors: Dirk Ostwald, Sebastian Schneider, Rasmus Bruckner, Lilla Horvath
Date: 2018-08-13 00:00:00

P-values and null-hypothesis significance testing are popular data-analytical tools in functional neuroimaging. Sparked by the analysis of resting-state fMRI data, there has been a resurgence of interest in the validity of some of the p-values evaluated with the widely used software SPM in recent years. The default parametric p-values reported in SPM are based on the application of results from random field theory to statistical parametric maps, a framework commonly referred to as RFT. While RFT was established two decades ago and has since been applied in a plethora of fMRI studies, there does not exist a unified documentation of the mathematical and computational underpinnings of RFT as implemented in current versions of SPM. Here, we provide such a documentation with the aim of contributing to contemporary efforts towards higher levels of computational transparency in functional neuroimaging.
Quantitative and functional post-translational modification proteomics reveals that TREPH1 plays a role in plant thigmomorphogenesis
Date: 2018-08-13 00:00:00

Plants can sense both intracellular and extracellular mechanical forces and
can respond through morphological changes. The signaling components responsible
for mechanotransduction of the touch response are largely unknown. Here, we
performed a high-throughput SILIA (stable isotope labeling in
Arabidopsis)-based quantitative phosphoproteomics analysis to profile changes
in protein phosphorylation resulting from 40 seconds of force stimulation in
Arabidopsis thaliana. Of the 24 touch-responsive phosphopeptides identified,
many were derived from kinases, phosphatases, cytoskeleton proteins, membrane
proteins and ion transporters. TOUCH-REGULATED PHOSPHOPROTEIN1 (TREPH1) and MAP
KINASE KINASE 2 (MKK2) and/or MKK1 became rapidly phosphorylated in
touch-stimulated plants. Both TREPH1 and MKK2 are required for touch-induced
delayed flowering, a major component of thigmomorphogenesis. The treph1-1 and
mkk2 mutants also exhibited defects in touch-inducible gene expression. A
non-phosphorylatable site-specific isoform of TREPH1 (S625A) failed to restore
touch-induced flowering delay of treph1-1, indicating the necessity of S625 for
TREPH1 function and providing evidence consistent with the possible functional
relevance of the touch-regulated TREPH1 phosphorylation. Bioinformatic analysis
and biochemical subcellular fractionation of TREPH1 protein indicate that it is
a soluble protein. Altogether, these findings identify new protein players in
Arabidopsis thigmomorphogenesis regulation, suggesting that protein
phosphorylation may play a critical role in plant force responses.