pwc-archive/papers-with-abstracts huggingface dataset:
Comparing fitness and drift explanations of Neanderthal replacement
Date: 2018-10-29 00:00:00

There is a general consensus among archaeologists that replacement of
Neanderthals by anatomically modern humans in Europe occurred around 40K to 35K
YBP. However, the causal mechanism for this replacement continues to be
debated. Searching for specific fitness advantages in the archaeological record
has proven difficult, as these may be obscured, absent, or subject to
interpretation. Proposed models have therefore featured either fitness
advantages in favor of anatomically modern humans, or invoked neutral drift
under various preconditions. To bridge this gap, we rigorously compare the
system-level properties of fitness- and drift-based explanations of Neanderthal
replacement. Our stochastic simulations and analytical predictions show that,
although both fitness and drift can produce fixation, they present important
differences in 1) required initial conditions, 2) reliability, 3) time to
replacement, and 4) path to replacement (population histories). These results
present useful opportunities for comparison with archaeological and genetic
data. We find far greater agreement between the available empirical evidence
and the system-level properties of replacement by differential fitness, rather
than by neutral drift.
Why Abeta42 Is Much More Toxic Than Abeta40
Authors: J. C. Phillips
Date: 2018-10-25 00:00:00

Amyloid precursor with 770 amino acids dimerizes and aggregates, as do its c terminal 99 amino acids and amyloid 40,42 amino acids fragments. The titled question has been discussed extensively, and here it is addressed further using thermodynamic scaling theory to analyze mutational trends in structural factors and kinetics. Special attention is given to Family Alzheimer's Disease mutations outside amyloid 42. The scaling analysis is connected to extensive docking simulations which included membranes, thereby confirming their results and extending them to Amyloid precursor.
Everything you always wanted to know about a dataset: studies in data summarisation
Authors: Koesten Laura, Simperl Elena, Kacprzak Emilia, Blount Tom, Tennison Jeni
Date: 2018-10-23 00:00:00

Summarising data as text helps people make sense of it. It also improves data
discovery, as search algorithms can match this text against keyword queries. In
this paper, we explore the characteristics of text summaries of data in order
to understand how meaningful summaries look like. We present two complementary
studies: a data-search diary study with 69 students, which offers insight into
the information needs of people searching for data; and a summarisation study,
with a lab and a crowdsourcing component with overall 80 data-literate
participants, which produced summaries for 25 datasets. In each study we
carried out a qualitative analysis to identify key themes and commonly
mentioned dataset attributes, which people consider when searching and making
sense of data. The results helped us design a template to create more
meaningful textual representations of data, alongside guidelines for improving
data-search experience overall.
Partial Shading Detection and Smooth Maximum Power Point Tracking of PV Arrays under PSC
Date: 2018-10-29 00:00:00
Tasks: Point Tracking

One of the most important issues in the operation of a photovoltaic (PV)
system is extracting maximum power from the PV array, especially in partial
shading condition (PSC). Under PSC, P-V characteristic of PV arrays will have
multiple peak points, only one of which is global maximum. Conventional maximum
power point tracking (MPPT) methods are not able to extract maximum power in
this condition. In this paper, a novel two-stage MPPT method is presented to
overcome this drawback. In the first stage, a method is proposed to determine
the occurrence of PSC, and in the second stage, using a new algorithm that is
based on ramp change of the duty cycle and continuous sampling from the P-V
characteristic of the array, global maximum power point of array is reached.
P&O algorithm is then re-activated to trace small changes of the new MPP. Open
loop operation of the proposed method makes its implementation cheap and
simple. The method is robust in the face of changing environmental conditions
and array characteristics, and has minimum negative impact on the connected
power system. Simulations in Matlab/Simulink and experimental results validate
the performance of the proposed methods.
Semiparametrically efficient estimation of the average linear regression function
Date: 2018-10-30 00:00:00
Tasks: regression

Let Y be an outcome of interest, X a vector of treatment measures, and W a
vector of pre-treatment control variables. Here X may include (combinations of)
continuous, discrete, and/or non-mutually exclusive "treatments". Consider the
linear regression of Y onto X in a subpopulation homogenous in W = w (formally
a conditional linear predictor). Let b0(w) be the coefficient vector on X in
this regression. We introduce a semiparametrically efficient estimate of the
average beta0 = E[b0(W)]. When X is binary-valued (multi-valued) our procedure
recovers the (a vector of) average treatment effect(s). When X is
continuously-valued, or consists of multiple non-exclusive treatments, our
estimand coincides with the average partial effect (APE) of X on Y when the
underlying potential response function is linear in X, but otherwise
heterogenous across agents. When the potential response function takes a
general nonlinear/heterogenous form, and X is continuously-valued, our
procedure recovers a weighted average of the gradient of this response across
individuals and values of X. We provide a simple, and semiparametrically
efficient, method of covariate adjustment for settings with complicated
treatment regimes. Our method generalizes familiar methods of covariate
adjustment used for program evaluation as well as methods of semiparametric
regression (e.g., the partially linear regression model).
Phase asymmetry guided adaptive fractional-order total variation and diffusion for feature-preserving ultrasound despeckling
Date: 2018-10-30 00:00:00
Tasks: FAD

It is essential for ultrasound despeckling to remove speckle noise while
simultaneously preserving edge features for accurate diagnosis and analysis in
many applications. To preserve real edges such as ramp edges and low contrast
edges, we first detect edges using a phase-based measure called phase asymmetry
(PAS), which can distinguish small differences in transition border regions and
varies from $0$ to $1$, taking $0$ in ideal smooth regions and taking $1$ at
ideal step edges. We further propose three strategies to properly preserve
edges. First, in observing that fractional-order anisotropic diffusion (FAD)
filter has good performance in smooth regions while the fractional-order TV
(FTV) filter performs better at edges, we leverage the PAS metric to keep a
balance between FAD filter and FTV filter for achieving the best performance of
preserving ramp edges. Second, considering that the FAD filter fails to protect
low contrast edges by solely integrating gradient information into the
diffusion coefficient, we integrate the PAS metric into the diffusion
coefficient to properly preserve low contrast edges. Finally, different from
fixed fractional order diffusion filters neglecting the differences between
smooth regions and transition border regions, an adaptive fractional order is
implemented based on the PAS metric to enhance edges. The experimental results
show that our method outperforms other state-of-the-art ultrasound despeckling
filters in both speckle reduction and feature preservation.
Deep-diving of Atlantic salmon ($\textit{Salmo salar}$) during their marine feeding migrations
Date: 2018-10-30 00:00:00

Data from seven data storage tags recovered from Atlantic salmon marked as
smolts were analyzed for depth movements and patterns of deep diving during the
marine migration. The salmon mostly stayed at the surface and showed diurnal
activity especially from autumn until spring. During the first months at sea
the salmon stayed at shallower depths (< 100 m). The salmon took short deep
dives (> 100 m), that were rare or absent during the first summer at sea but
increased in frequency and duration especially in late winter. The maximum
depth of the dives varied from 419 to 1187 m. Most of dives were short, (< 5
hours) but could last up to 33 hours. The duration of dives increased in late
winter until spring and the overall depth and maximum depth per dive increased
exponentially over time. The initiation of the dives was more common in
evenings and at night, suggesting nocturnal diving. We hypothesized that deep
diving is related to feeding of salmon as mesopelagic fish can be important
food for salmon during winter.
An architecture of open-source tools to combine textual information extraction, faceted search and information visualisation
Authors: Sonntag Daniel, Profitlich Hans-Jürgen
Date: 2018-10-30 00:00:00

This article presents our steps to integrate complex and partly unstructured
medical data into a clinical research database with subsequent decision
support. Our main application is an integrated faceted search tool, accompanied
by the visualisation of results of automatic information extraction from
textual documents. We describe the details of our technical architecture
(open-source tools), to be replicated at other universities, research
institutes, or hospitals. Our exemplary use cases are nephrology and
mammography. The software was first developed in the nephrology domain and then
adapted to the mammography use case. We report on these case studies,
illustrating how the application can be used by a clinician and which questions
can be answered. We show that our architecture and the employed software
modules are suitable for both areas of application with a limited amount of
adaptations. For example, in nephrology we try to answer questions about the
temporal characteristics of event sequences to gain significant insight from
the data for cohort selection. We present a versatile time-line tool that
enables the user to explore relations between a multitude of diagnosis and
laboratory values.
Convolutional Dictionary Regularizers for Tomographic Inversion
Date: 2019-02-18 00:00:00
Tasks: Denoising, Dictionary Learning

There has been a growing interest in the use of data-driven regularizers to
solve inverse problems associated with computational imaging systems. The
convolutional sparse representation model has recently gained attention, driven
by the development of fast algorithms for solving the dictionary learning and
sparse coding problems for sufficiently large images and data sets.
Nevertheless, this model has seen very limited application to tomographic
reconstruction problems. In this paper, we present a model-based tomographic
reconstruction algorithm using a learnt convolutional dictionary as a
regularizer. The key contribution is the use of a data-dependent weighting
scheme for the l1 regularization to construct an effective denoising method
that is integrated into the inversion using the Plug-and-Play reconstruction
framework. Using simulated data sets we demonstrate that our approach can
improve performance over traditional regularizers based on a Markov random
field model and a patch-based sparse representation model for sparse and
limited-view tomographic data sets.
Undirected graphs: is the shift-enabled condition trivial or necessary?
Date: 2019-05-22 00:00:00

It has recently been shown that, contrary to the wide belief that a
shift-enabled condition (necessary for any shift-invariant filter to be
representable by a graph shift matrix) can be ignored because any
non-shift-enabled matrix can be converted to a shift-enabled matrix, such a
conversion in general may not hold for a directed graph with non-symmetric
shift matrix. This letter extends this prior work, focusing on undirected
graphs where the shift matrix is generally symmetric. We show that while, in
this case, the shift matrix can be converted to satisfy the original
shift-enabled condition, the converted matrix is not associated with the
original graph, that is, it does not capture anymore the structure of the graph
signal. We show via a counterexample, that a non-shift-enabled matrix cannot be
converted to a shift-enabled one and still maintain the topological structure
of the underlying graph, which is necessary to facilitate localized signal
processing.
Volterra-assisted Optical Phase Conjugation: a Hybrid Optical-Digital Scheme For Fiber Nonlinearity Compensation
Date: 2018-10-26 00:00:00

Mitigation of optical fiber nonlinearity is an active research field in the
area of optical communications, due to the resulting marked improvement in
transmission performance. Following the resurgence of optical coherent
detection, digital nonlinearity compensation (NLC) schemes such as digital
backpropagation (DBP) and Volterra equalization have received much attention.
Alternatively, optical NLC, and specifically optical phase conjugation (OPC),
has been proposed to relax the digital signal processing complexity. In this
work, a novel hybrid optical-digital NLC scheme combining OPC and a Volterra
equalizer is proposed, termed Volterra-Assisted OPC (VAO). It has a twofold
advantage: it overcomes the OPC limitation in asymmetric links and
substantially enhances the performance of Volterra equalizers. The proposed
scheme is shown to outperform both OPC and Volterra equalization alone by up to
4.2 dB in a 1000 km EDFA-amplified fiber link. Moreover, VAO is also
demonstrated to be very robust when applied to long-transmission distances,
with a 2.5 dB gain over OPC-only systems at 3000 km. VAO combines the
advantages of both optical and digital NLC offering a promising trade-off
between performance and complexity for future high-speed optical communication
systems.
Log-optimal portfolio and numéraire portfolio for market models stopped at a random time
Authors: Tahir Choulli, Sina Yansori
Date: 2018-10-26 00:00:00

This paper focuses on num\'eraire portfolio and log-optimal portfolio (portfolio with finite expected utility that maximizes the expected logarithm utility from terminal wealth), when a market model $(S,\mathbb F)$ -specified by its assets' price $S$ and its flow of information $\mathbb F$- is stopped at a random time $\tau$. This setting covers the areas of credit risk and life insurance, where $\tau$ represents the default time and the death time respectively. Thus, the progressive enlargement of $\mathbb F$ with $\tau$, denoted by $\mathbb G$, sounds tailor-fit for modelling the new flow of information that incorporates both $\mathbb F$ and $\tau$. For the resulting stopped model $(S^{\tau},\mathbb G)$, we study the two portfolios in different manners, and describe their computations in terms of the $\mathbb F$-observable parameters of the pair $(S, \tau)$.
Single-shot image retrieval through a multimode fiber using a genetic algorithm
Date: 2018-10-26 00:00:00
Tasks: Image Retrieval, Retrieval

In this letter, we present a genetic algorithm-based approach for image
retrieval through a multimode fiber in a reference-less system. Due to mode
interference, when an image is illuminated at one side of a multimode fiber,
the transmitted light forms a noise-like speckle pattern at the other end. With
the use of a prior-measured transmission matrix of the fiber, a speckle pattern
is calculated using a random input mask. By optimizing the input mask to
achieve a high correlation coefficient of experimental and calculated patterns,
the input mask is optimized into an image with high similarity to the original
image.
The Replicator Dynamics for Multilevel Selection in Evolutionary Games
Date: 2018-12-16 00:00:00

We consider a stochastic model for evolution of group-structured populations
in which interactions between group members correspond to the Prisoner's
Dilemma or the Hawk-Dove game. Selection operates at two organization levels:
individuals compete with peer group members based on individual payoff, while
groups also compete with other groups based on average payoff of group members.
In the Prisoner's Dilemma, this creates a tension between the two levels of
selection, as defectors are favored at the individual level, whereas groups
with at least some cooperators outperform groups of defectors at the
between-group level. In the limit of infinite group size and infinite number of
groups, we derive a non-local PDE that describes the probability distribution
of group compositions in the population. For special families of payoff
matrices, we characterize the long-time behavior of solutions of our equation,
finding a threshold level of between-group selection required to sustain
density steady states and the survival of cooperation. When all-cooperator
groups are most fit, the average and most abundant group composition at steady
state range from featuring all-defector groups when individual-level selection
dominates to featuring all-cooperator groups when group-level selection
dominates. When the most fit groups have a mix of cooperators and defectors,
then the average and most abundant group compositions always feature a smaller
fraction of cooperators than required for the optimal mix, even in the limit
where group-level selection is infinitely stronger than individual-level
selection. In such cases, the conflict between the two levels of selection
cannot be decoupled, and cooperation cannot be sustained at all in the case
when between-group competition favors an even mix of cooperators and defectors.
Quantitative assessment of changes in cellular morphology at photodynamic treatment in vitro by means of digital holographic microscopy
Authors: A. V. Belashov, A. A. Zhikhoreva, T. N. Belyaeva, E. S. Kornilova, A. V. Salova, I. V. Semenova, O. S. Vasyutinskii
Date: 2018-10-30 00:00:00

Changes in morphological characteristics of cells from two cultured cancer cell lines, HeLa and A549, induced by photodynamic treatment with Radachlorin photosensitizer have been monitored using digital holographic microscopy. The observed dose-dependent post-treatment dynamics of phase shift variations demonstrated several scenarios of cell death. In particular the phase shift increase at low doses can be associated with apoptosis while its decrease at high doses can be associated with necrosis. Two cell types were shown to be differently responsive to treatment at the same doses. Although the sequence of death scenarios with increasing irradiation dose was demonstrated to be the same, each specific scenario was realized at substantially different doses. Results obtained by holographic microscopy were confirmed by confocal fluorescence microscopy with the commonly used test assay.
Path integral approach to generating functions for multistep post-transcription and post-translation processes and arbitrary initial conditions
Date: 2018-10-30 00:00:00
Tasks: Translation

Stochastic fluctuations in the copy number of gene products have perceivable
effects on the functioning of gene regulatory networks (GRN). The Master
equation (ME) provides a theoretical basis for studying such effects. However,
solving the ME can be a task that ranges from simple to difficult to impossible
using conventional methods. Therefore, discovering new techniques for solving
the ME is an important part of research on stochastic GRN. In this paper, we
present a novel approach to obtaining the generating function (GF), which
contains the same information as the ME, for a one gene system that includes
multi-step post-transcription and post-translation processes. The novelty of
the approach lies in the separation of the mRNAs from proteins. The GF for the
mRNAs is obtained using a formalism involving operators and vector states.
Using the same formalism, the GF for the proteins is solved for a particular
path taken by all mRNAs in the time-copy number plane; then, the GF is summed
over all possible paths. We prove a theorem that shows the summation of all
paths to be equivalent to an equation similar to the ME for the mRNAs. On a
system with six gene products in total and randomly selected initial
conditions, we confirm the validity of our results by comparing them with
Gillespie simulations.
Exploring and mapping the universe of evolutionary graphs
Date: 2018-10-30 00:00:00

Population structure can be modelled by evolutionary graphs, which can have a
substantial, but very subtle influence on the fate of the arising mutants.
Individuals are located on the nodes of these graphs, competing with each other
to eventually take over the graph via the links. Many applications for this
framework can be envisioned, from the ecology of river systems and cancer
initiation in colonic crypts to biotechnological search for optimal mutations.
In all these applications, it is not only important where and when novel
variants arise and how likely it is that they ultimately take over, but also
how long this process takes. More concretely, how is the probability to take
over the population related to the associated time? We study this problem for
all possible undirected and unweighted graphs up to a certain size. To move
beyond the graph size where an exhaustive search is possible, we devise a
genetic algorithm to find graphs with either high or low fixation probability
and either short or long fixation time and study their structure in detail
searching for common themes. Our work unravels structural properties that
maximize or minimize fixation probability and time, which allows us to
contribute to a first map of the universe of evolutionary graphs.
Asset Price Distributions and Efficient Markets
Date: 2018-10-30 00:00:00

We explore a decomposition in which returns on a large class of portfolios
relative to the market depend on a smooth non-negative drift and changes in the
asset price distribution. This decomposition is obtained using general
continuous semimartingale price representations, and is thus consistent with
virtually any asset pricing model. Fluctuations in portfolio relative returns
depend on stochastic time-varying dispersion in asset prices. Thus, our
framework uncovers an asset pricing factor whose existence emerges from an
accounting identity universal across different economic and financial
environments, a fact that has deep implications for market efficiency. In
particular, in a closed, dividend-free market in which asset price dispersion
is relatively constant, a large class of portfolios must necessarily outperform
the market portfolio over time. We show that price dispersion in commodity
futures markets has increased only slightly, and confirm the existence of
substantial excess returns that co-vary with changes in price dispersion as
predicted by our theory.
A Comparison of Microbial Genome Web Portals
Date: 2018-10-30 00:00:00

Microbial genome web portals have a broad range of capabilities that address
a number of information-finding and analysis needs for scientists. This article
compares the capabilities of the major microbial genome web portals to aid
researchers in determining which portal(s) are best suited to solving their
information-finding and analytical needs. We assessed both the bioinformatics
tools and the data content of BioCyc, KEGG, Ensembl Bacteria, KBase, IMG, and
PATRIC. For each portal, our assessment compared and tallied the available
capabilities. The strengths of BioCyc include its genomic and metabolic tools,
multi-search capabilities, table-based analysis tools, regulatory network tools
and data, omics data analysis tools, breadth of data content, and large amount
of curated data. The strengths of KEGG include its genomic and metabolic tools.
The strengths of Ensembl Bacteria include its genomic tools and large number of
genomes. The strengths of KBase include its genomic tools and metabolic models.
The strengths of IMG include its genomic tools, multi-search capabilities,
large number of genomes, table-based analysis tools, and breadth of data
content. The strengths of PATRIC include its large number of genomes,
table-based analysis tools, metabolic models, and breadth of data content.