pwc-archive/papers-with-abstracts huggingface dataset:
The tetrazole analogue of the auxin indole-3-acetic acid binds preferentially to TIR1 and not AFB5
Date: 2018-08-27 00:00:00
Tasks: Molecular Docking

Auxin is considered one of the cardinal hormones in plant growth and
development. It regulates a wide range of processes throughout the plant.
Synthetic auxins exploit the auxin-signalling pathway and are valuable as
herbicidal agrochemicals. Currently, despite a diversity of chemical scaffolds
all synthetic auxins have a carboxylic acid as the active core group. By
applying bio-isosteric replacement we discovered that indole-3-tetrazole was
active by surface plasmon resonance (SPR) spectrometry, showing that the
tetrazole could initiate assembly of the TIR1 auxin co-receptor complex. We
then tested the tetrazole's efficacy in a range of whole plant physiological
assays and in protoplast reporter assays which all confirmed auxin activity,
albeit rather weak. We then tested indole-3-tetrazole against the AFB5
homologue of TIR1, finding that binding was selective against TIR1, absent with
AFB5. The kinetics of binding to TIR1 are contrasted to those for the herbicide
picloram, which shows the opposite receptor preference as it binds to AFB5 with
far greater affinity than to TIR1. The basis of the preference of
indole-3-tetrazole for TIR1 was revealed to be a single residue substitution
using molecular docking, and assays using tir1 and afb5 mutant lines confirmed
selectivity in vivo. Given the potential that a TIR1-selective auxin might have
for unmasking receptor-specific actions, we followed a rational design, lead
optimisation campaign and a set of chlorinated indole-3-tetrazoles was
synthesised. Improved affinity for TIR1 and the preference for binding to TIR1
was maintained for 4- and 6-chloroindole-3-tetrazoles, coupled with improved
efficacy in vivo. This work expands the range of auxin chemistry for the design
of receptor-selective synthetic auxins.
Immigration-induced phase transition in a regulated multispecies birth-death process
Date: 2018-08-27 00:00:00

Power-law-distributed species counts or clone counts arise in many biological
settings such as multispecies cell populations, population genetics, and
ecology. This empirical observation that the number of species $c_{k}$
represented by $k$ individuals scales as negative powers of $k$ is also
supported by a series of theoretical birth-death-immigration (BDI) models that
consistently predict many low-population species, a few intermediate-population
species, and very high-population species. However, we show how a simple global
population-dependent regulation in a neutral BDI model destroys the power law
distributions. Simulation of the regulated BDI model shows a high probability
of observing a high-population species that dominates the total population.
Further analysis reveals that the origin of this breakdown is associated with
the failure of a mean-field approximation for the expected species abundance
distribution. We find an accurate estimate for the expected distribution
$\langle c_k \rangle$ by mapping the problem to a lower-dimensional Moran
process, allowing us to also straightforwardly calculate the covariances
$\langle c_k c_\ell \rangle$. Finally, we exploit the concepts associated with
energy landscapes to explain the failure of the mean-field assumption by
identifying a phase transition in the quasi-steady-state species counts
triggered by a decreasing immigration rate.
Harnessing Historical Corrections to build Test Collections for Named Entity Disambiguation
Authors: Reitz Florian
Date: 2018-08-27 00:00:00
Tasks: Entity Disambiguation

Matching mentions of persons to the actual persons (the name disambiguation
problem) is central for several digital library applications. Scientists have
been working on algorithms to create this matching for decades without finding
a universal solution. One problem is that test collections for this problem are
often small and specific to a certain collection. In this work, we present an
approach that can create large test collections from historical metadata with
minimal extra cost. We apply this approach to the DBLP collection to generate
two freely available test collections. One collection focuses on the properties
of defects and one on the evaluation of disambiguation algorithms.
ParsRec: Meta-Learning Recommendations for Bibliographic Reference Parsing
Authors: Tkaczyk Dominika, Sheridan Paraic, Beel Joeran
Date: 2018-08-27 00:00:00
Tasks: Meta-Learning, Recommendation Systems

Bibliographic reference parsers extract metadata (e.g. author names, title,
year) from bibliographic reference strings. No reference parser consistently
gives the best results in every scenario. For instance, one tool may be best in
extracting titles, and another tool in extracting author names. In this paper,
we address the problem of reference parsing from a recommender-systems
perspective. We propose ParsRec, a meta-learning approach that recommends the
potentially best parser(s) for a given reference string. We evaluate ParsRec on
105k references from chemistry. We propose two approaches to meta-learning
recommendations. The first approach learns the best parser for an entire
reference string. The second approach learns the best parser for each field of
a reference string. The second approach achieved a 2.6% increase in F1 (0.909
vs. 0.886, p < 0.001) over the best single parser (GROBID), reducing the false
positive rate by 20.2% (0.075 vs. 0.094), and the false negative rate by 18.9%
(0.107 vs. 0.132).
In vitro and sensory tests to design easy-to-swallow multi-particulate formulations
Date: 2018-08-27 00:00:00

Flexible dosing and ease of swallowing are key factors when designing oral
drug delivery systems for paediatric and geriatric populations.
Multi-particulate oral dosage forms can offer significant benefits over
conventional capsules and tablets. This study proposes the use of an in vitro
model to quantitatively investigate the swallowing dynamics in presence of
multi-particulates. In vitro results were compared against sensory tests that
considered the attributes of ease of swallowing and post-swallow residues.
Water and hydrocolloids were considered as suspending vehicles, while the
suspended phase consisted of cellulose pellets of two different average sizes.
Both in vivo and in vitro tests reported easier swallow for smaller
multi-particulates. Besides, water thin liquids appeared not optimal for
complete oral clearance of the solids. The sensory study did not highlight
significant differences between the levels of thickness of the hydrocolloids.
Conversely, more discriminant results were obtained from in vitro tests,
suggesting that a minimum critical viscosity is necessary to enable a smooth
swallow, but increasing too much the carrier concentration affects swallowing
negatively. These results highlight the important interplay of particle size
and suspending vehicle rheology and the meaningful contribution that in vitro
methods can provide to pre-screening multi-particulate oral drug delivery
systems before sensory evaluation.
Combining Alchemical Transformation with Physical Pathway to Accurately Compute Absolute Binding Free Energy
Date: 2018-08-28 00:00:00

We present a new method that combines alchemical transformation with physical
pathway to accurately and efficiently compute the absolute binding free energy
of receptor-ligand complex. Currently, the double decoupling method (DDM) and
the potential of mean force approach (PMF) methods are widely used to compute
the absolute binding free energy of biomolecules. The DDM relies on
alchemically decoupling the ligand from its environments, which can be
computationally challenging for large ligands and charged ligands because of
the large magnitude of the decoupling free energies involved. On the other
hand, the PMF approach uses physical pathway to extract the ligand out of the
binding site, thus avoids the alchemical decoupling of the ligand. However, the
PMF method has its own drawback because of the reliance on a ligand
binding/unbinding pathway free of steric obstruction from the receptor atoms.
Therefore, in the presence of deeply buried ligand functional groups the
convergence of the PMF calculation can be very slow leading to large errors in
the computed binding free energy. Here we develop a new method called AlchemPMF
by combining alchemical transformation with physical pathway to overcome the
major drawback in the PMF method. We have tested the new approach on the
binding of a charged ligand to an allosteric site on HIV-1 Integrase. After 20
ns of simulation per umbrella sampling window, the new method yields absolute
binding free energies within ~1 kcal/mol from the experimental result, whereas
the standard PMF approach and the DDM calculations result in errors of ~5
kcal/mol and > 2 kcal/mol, respectively. Furthermore, the binding free energy
computed using the new method is associated with smaller statistical error
compared with those obtained from the existing methods.
Snapshot multispectral imaging using a filter array
Date: 2018-08-28 00:00:00
Tasks: Demosaicking, Sensitivity

A multispectral filter array (MSFA) is one solution for capturing a
multispectral image (MSI) in a single shot at low cost. We introduce our
optimization method of the spectral sensitivity of the MSFAs and demosaicking,
and show a new prototype filter array for snapshot imaging based on a photonic
crystal.
A Residual Bootstrap for Conditional Value-at-Risk
Authors: Eric Beutner, Alexander Heinemann, Stephan Smeekes
Date: 2018-08-28 00:00:00

A fixed-design residual bootstrap method is proposed for the two-step estimator of Francq and Zako\"ian (2015) associated with the conditional Value-at-Risk. The bootstrap's consistency is proven for a general class of volatility models and intervals are constructed for the conditional Value-at-Risk. A simulation study reveals that the equal-tailed percentile bootstrap interval tends to fall short of its nominal value. In contrast, the reversed-tails bootstrap interval yields accurate coverage. We also compare the theoretically analyzed fixed-design bootstrap with the recursive-design bootstrap. It turns out that the fixed-design bootstrap performs equally well in terms of average coverage, yet leads on average to shorter intervals in smaller samples. An empirical application illustrates the interval estimation.
MIaS: Math-Aware Retrieval in Digital Mathematical Libraries
Authors: Sojka Petr  Faculty of Informatics, Masaryk University, Brno, Czech Republic, Růžička Michal  Faculty of Informatics, Masaryk University, Brno, Czech Republic, Novotný Vít  Faculty of Informatics, Masaryk University, Brno, Czech Republic
Date: 2018-08-28 00:00:00
Tasks: Information Retrieval, Math, Math Information Retrieval, Retrieval, Text Retrieval

Digital mathematical libraries (DMLs) such as arXiv, Numdam, and EuDML
contain mainly documents from STEM fields, where mathematical formulae are
often more important than text for understanding. Conventional information
retrieval (IR) systems are unable to represent formulae and they are therefore
ill-suited for math information retrieval (MIR). To fill the gap, we have
developed, and open-sourced the MIaS MIR system. MIaS is based on the full-text
search engine Apache Lucene. On top of text retrieval, MIaS also incorporates a
set of tools for preprocessing mathematical formulae. We describe the design of
the system and present speed, and quality evaluation results. We show that MIaS
is both efficient, and effective, as evidenced by our victory in the NTCIR-11
Math-2 task.
Fully Decentralized Massive MIMO Detection Based on Recursive Methods
Date: 2018-08-28 00:00:00

Algorithms for Massive MIMO uplink detection typically rely on a centralized
approach, by which baseband data from all antennas modules are routed to a
central node in order to be processed. In case of Massive MIMO, where hundreds
or thousands of antennas are expected in the base-station, this architecture
leads to a bottleneck, with critical limitations in terms of interconnection
bandwidth requirements. This paper presents a fully decentralized architecture
and algorithms for Massive MIMO uplink based on recursive methods, which do not
require a central node for the detection process. Through a recursive approach
and very low complexity operations, the proposed algorithms provide a sequence
of estimates that converge asymptotically to the zero-forcing solution, without
the need of specific hardware for matrix inversion. The proposed solution
achieves significantly lower interconnection data-rate than other
architectures, enabling future scalability.
Implementation Notes for the Soft Cosine Measure
Authors: Novotný Vít
Date: 2018-08-28 00:00:00
Tasks: Information Retrieval, Question Answering, Retrieval

The standard bag-of-words vector space model (VSM) is efficient, and
ubiquitous in information retrieval, but it underestimates the similarity of
documents with the same meaning, but different terminology. To overcome this
limitation, Sidorov et al. proposed the Soft Cosine Measure (SCM) that
incorporates term similarity relations. Charlet and Damnati showed that the SCM
is highly effective in question answering (QA) systems. However, the
orthonormalization algorithm proposed by Sidorov et al. has an impractical time
complexity of $\mathcal O(n^4)$, where n is the size of the vocabulary.
  In this paper, we prove a tighter lower worst-case time complexity bound of
$\mathcal O(n^3)$. We also present an algorithm for computing the similarity
between documents and we show that its worst-case time complexity is $\mathcal
O(1)$ given realistic conditions. Lastly, we describe implementation in
general-purpose vector databases such as Annoy, and Faiss and in the inverted
indices of text search engines such as Apache Lucene, and ElasticSearch. Our
results enable the deployment of the SCM in real-world information retrieval
systems.
Pharmacogenomics in the Age of GWAS, Omics Atlases, and PheWAS
Date: 2018-08-28 00:00:00

The search for causative pharmacogenomic loci is being transformed by
integrative omics pipelines, but their outputs have only begun being applied to
test design. We assess the direction of the field in light of Biobanks/PheWAS,
omics atlases, and AI. We first assess the potential of recent epigenome and
spatial genome concepts, datasets, and methods to improve the functionality of
PIP-style pipelines. We then discuss new potential methods of genetic test
design on the basis of the outputs of such pipelines. We conclude with a vision
for a pharmacophenomic atlas, in which omics atlas data, PheWAS associations,
and biobank data would be used with AI to design thousands of genetic tests for
clinical deployment in an automated parallel process.
Tutorial on agent-based models in NetLogo applied to immunology and virology
Date: 2018-08-28 00:00:00
Tasks: Cultural Vocal Bursts Intensity Prediction, Virology

This tutorial introduces participants to the design and implementation of an
agent-based model using NetLogo through one of two different projects:
modelling T cell movement within a lymph node or modelling the progress of a
viral infection in an in vitro cell culture monolayer. Each project is broken
into a series of incremental steps of increasing complexity. Each step is
described in detail and the code to type in is initially provided. However,
each project has room to grow in complexity and biological realism so
participants are encouraged to expand their project beyond the scope of the
tutorial or to develop a project of their own.
Smile Modelling in Commodity Markets
Authors: Emanuele Nastasi, Andrea Pallavicini, Giulio Sartorelli
Date: 2018-08-29 00:00:00

We present a stochastic-local volatility model for derivative contracts on commodity futures able to describe forward-curve and smile dynamics with a fast calibration to liquid market quotes. A parsimonious parametrization is introduced to deal with the limited number of options quoted in the market. Cleared commodity markets for futures and options are analyzed to include in the pricing framework specific trading clauses and margining procedures. Numerical examples for calibration and pricing are provided for different commodity products.
Switching Cost Models as Hypothesis Tests
Date: 2018-08-29 00:00:00

We relate models based on costs of switching beliefs (e.g. due to
inattention) to hypothesis tests. Specifically, for an inference problem with a
penalty for mistakes and for switching the inferred value, a band of inaction
is optimal. We show this band is equivalent to a confidence interval, and
therefore to a two-sided hypothesis test.
Modelling Irregular Spatial Patterns using Graph Convolutional Neural Networks
Authors: Zhu Di, Liu Yu
Date: 2018-08-15 00:00:00

The understanding of geographical reality is a process of data representation
and pattern discovery. Former studies mainly adopted continuous-field models to
represent spatial variables and to investigate the underlying spatial
continuity/heterogeneity in the regular spatial domain. In this article, we
introduce a more generalized model based on graph convolutional neural networks
(GCNs) that can capture the complex parameters of spatial patterns underlying
graph-structured spatial data, which generally contain both Euclidean spatial
information and non-Euclidean feature information. A trainable semi-supervised
prediction framework is proposed to model the spatial distribution patterns of
intra-urban points of interest(POI) check-ins. This work demonstrates the
feasibility of GCNs in complex geographic decision problems and provides a
promising tool to analyze irregular spatial data.
Continuous-time Duality for Super-replication with Transient Price Impact
Authors: Peter Bank, Yan Dolinsky
Date: 2018-08-29 00:00:00

We establish a super-replication duality in a continuous-time financial model where an investor's trades adversely affect bid- and ask-prices for a risky asset and where market resilience drives the resulting spread back towards zero at an exponential rate. Similar to the literature on models with a constant spread, our dual description of super-replication prices involves the construction of suitable absolutely continuous measures with martingales close to the unaffected reference price. A novel feature in our duality is a liquidity weighted $L^2$-norm that enters as a measurement of this closeness and that accounts for strategy dependent spreads. As applications, we establish optimality of buy-and-hold strategies for the super-replication of call options and we prove a verification theorem for utility maximizing investment strategies.
Enforcing Regulation Under Illicit Adaptation
Date: 2018-08-29 00:00:00

Attempts to curb illegal activity by enforcing regulations gets complicated
when agents react to the new regulatory regime in unanticipated ways to
circumvent enforcement. We present a research strategy that uncovers such
reactions, and permits program evaluation net of such adaptive behaviors. Our
interventions were designed to reduce over-fishing of the critically endangered
Pacific hake by either (a) monitoring and penalizing vendors that sell illegal
fish or (b) discouraging consumers from purchasing using an information
campaign. Vendors attempt to circumvent the ban through hidden sales and other
means, which we track using mystery shoppers. Instituting random monitoring
visits are much more effective in reducing true hake availability by limiting
such cheating, compared to visits that occur on a predictable schedule.
Monitoring at higher frequency (designed to limit temporal displacement of
illegal sales) backfires, because targeted agents learn faster, and cheat more
effectively. Sophisticated policy design is therefore crucial for determining
the sustained, longer-term effects of enforcement. Data collected from
fishermen, vendors, and consumers allow us to document the upstream,
downstream, spillover, and equilibrium effects of enforcement on the entire
supply chain. The consumer information campaign generates two-thirds of the
gains compared to random monitoring, but is simpler for the government to
implement and almost as cost-effective.
Coarse-Grained Residue-Based Models of Disordered Protein Condensates: Utility and Limitations of Simple Charge Pattern Parameters
Date: 2018-10-30 00:00:00

Biomolecular condensates undergirded by phase separations of proteins and
nucleic acids serve crucial biological functions. To gain physical insights
into their genetic basis, we study how liquid-liquid phase separation (LLPS) of
intrinsically disordered proteins (IDPs) depends on their sequence charge
patterns using a continuum Langevin chain model wherein each amino acid residue
is represented by a single bead. Charge patterns are characterized by the
`blockiness' measure $\kappa$ and the `sequence charge decoration' (SCD)
parameter. Consistent with random phase approximation (RPA) theory and lattice
simulations, LLPS propensity as characterized by critical temperature $T^*_{\rm
cr}$ increases with increasingly negative SCD for a set of sequences showing a
positive correlation between $\kappa$ and $-$SCD. Relative to RPA, the
simulated sequence-dependent variation in $T^*_{\rm cr}$ is often---though not
always---smaller, whereas the simulated critical volume fractions are higher.
However, for a set of sequences exhibiting an anti-correlation between $\kappa$
and $-$SCD, the simulated $T^*_{\rm cr}$'s are quite insensitive to either
parameters. Additionally, we find that blocky sequences that allow for strong
electrostatic repulsion can lead to coexistence curves with upward concavity as
stipulated by RPA, but the LLPS propensity of a strictly alternating charge
sequence was likely overestimated by RPA and lattice models because interchain
stabilization of this sequence requires spatial alignments that are difficult
to achieve in real space. These results help delineate the utility and
limitations of the charge pattern parameters and of RPA, pointing to further
efforts necessary for rationalizing the newly observed subtleties.
New trends in mechanistic transdermal drug delivery modelling: Towards an accurate description of skin microstructure
Date: 2019-11-22 00:00:00

Interest for in silico modelling of the absorption of xenobiotics into the
skin has been growing in the last years, owing to their lower cost compared to
experimental alternatives, and the desire to avoid animal experimentation. This
review presents an overview of Physiologically-Based Pharmacokinetic (PBPK)
models and focuses on recent, modelling approaches, such as Finite Element and
Lattice Boltzmann. These methods allow for a detailed geometric representation
of the skin microstructure, in contrast to classic QSPR and compartmental
models. Morphological features of the skin such as the bricks and mortar
description of the stratum corneum, hair follicles, and the pilosebaceous unit
can therefore be represented more accurately, allowing a better description of
the interaction of cosmetics with the skin. This review also highlights several
perspectives to further develop these models in directions relevant to
industry.
DCSM Protocol for Content Transfer in Deep Space Network
Date: 2018-08-30 00:00:00
Tasks: Prediction

To maximize file transfer from space vehicles to the Earth, we propose a new
space-to-earth content transfer protocol that combines turbo codes, RaptorQ
codes, real-time channel prediction, and dynamic code-rate selection. The
protocol features a practical signal-to-noise ratio prediction model that
facilitates periodic adjustment of the turbo encoder to achieve adaptive rate
transmission. Our simulation results indicate that an increase of about 20% in
file transfer rate is achievable using the proposed protocol.