pwc-archive/papers-with-abstracts huggingface dataset:
Modelling correlated marker effects in genome-wide prediction via Gaussian concentration graph models
Date: 2017-09-20 00:00:00

In genome-wide prediction, independence of marker allele substitution effects
is typically assumed; however, since early stages of this technology it has
been known that nature points to correlated effects. In statistics, graphical
models have been identified as a useful and powerful tool for covariance
estimation in high dimensional problems and it is an area that has recently
experienced a great expansion. In particular, Gaussian concentration graph
models (GCGM) have been widely studied. These are models in which the
distribution of a set of random variables, the marker effects in this case, is
assumed to be Markov with respect to an undirected graph G. In this paper,
Bayesian (Bayes G and Bayes G-D) and frequentist (GML-BLUP) methods adapting
the theory of GCGM to genome-wide prediction were developed. Different
approaches to define the graph G based on domain-specific knowledge were
proposed, and two propositions and a corollary establishing conditions to find
decomposable graphs were proven. These methods were implemented in small
simulated and real datasets. In our simulations, scenarios where correlations
among allelic substitution effects were expected to arise due to various causes
were considered, and graphs were defined on the basis of physical marker
positions. Results showed improvements in correlation between phenotypes and
predicted breeding values and accuracies of predicted breeding values when
accounting for partially correlated allele substitution effects. Extensions to
the multiallelic loci case were described and some possible refinements
incorporating more flexible priors in the Bayesian setting were discussed. Our
models are promising because they allow incorporation of biological information
in the prediction process, and because they are more flexible and general than
other models accounting for correlated marker effects that have been proposed
previously.
Measurement of Anticipative Power of a Retina by Predictive Information
Date: 2016-11-10 00:00:00
Tasks: Time Series, Time Series Analysis

The predictive properties of a retina are studied by measuring the mutual
information (MI) between its stimulation and the corresponding firing rates
while it is being probed by a train of short pulses with stochastic intervals.
Features of the measured MI at various time shifts between the stimulation and
the response are used to characterize the predictive properties of the retina.
By varying the statistical properties of the pulse train, our experiments show
that a retina has the ability to predict future events of the stimulation if
the information rate of the stimulation is low enough. Also, this predictive
property of the retina occurs at a time scale similar to the well established
anticipative phenomenon of omitted stimulus response in a retina. Furthermore,
a retina can make use of its predictive ability to distinguish between time
series created by an Ornstein--Uhlenbeck and a hidden Markovian process.
Prevalence of algorithm-based qualitative (ABQ) method osteoporotic vertebral fracture in elderly Chinese men and women with reference to semi-quantitative (SQ) method: Mr. Os and Ms Os. (Hong Kong) studies
Date: 2016-11-10 00:00:00

Introduction: This study evaluated algorithm-based qualitative (ABQ) method
for vertebral fracture (VF) evaluation with reference to semi-quantitative (SQ)
method and bone mineral density (BMD) measurement. Methods: Mr. OS (Hong Kong)
and Ms. OS (Hong Kong) represent the first large-scale cohort studies on bone
health in elderly Chinese men and women. The current study compared Genant's SQ
method and ABQ method in these two cohorts. Based on quantitative measurement,
the severity of ABQ method detected fractures was additionally classified into
grade-1, grad-2, and grade-3 according to SQ's deformity criteria. The
radiographs of 1,954 elderly Chinese men (mean: 72.3 years) and 1,953 elderly
Chinese women (mean: 72.5 years) were evaluated. Results: according to ABQ,
grade-1,-2,-3 VFs accounted for 1.89%, 1.74%, 2.25% in men, and 3.33%, 3.07%,
and 5.53% in women. In men and women, 15.7% (35/223) and 34.5% (48/139) of
vertebrae with SQ grade-1 deformity were ABQ(+, with fracture) respectively. In
men and women, 89.7% (35/39) and 66.7% (48/72) of vertebrae with ABQ grade-1
fracture had SQ grade-1 deformity. For grade-1 change, SQ (-, negative without
fracture) & ABQ (+, positive with vertebral cortex line fracture) subjects tend
to have a lower BMD than the SQ(+)& ABQ(-) subjects. In subjects with SQ
grade-2 deformity, those were also ABQ(+) tended to have a lower BMD than those
were ABQ(-). In all grades, SQ(-)&ABQ(-) subjects tended to have highest BMD,
while SQ(+)&ABQ(+)subjects tended to have lowest BMD. Conclusion: ABQ method
may be more sensitive to VF associated mild lower BMD than SQ method.
A Possible Role for Entropy in Creative Cognition
Date: 2016-11-11 00:00:00

This paper states the case for applying the conceptual and analytic tools
associated with the study of entropy in physical systems to cognition, focusing
on creative cognition. It is proposed that minds modify their contents and
adapt to their environments to minimize psychological entropy:
arousal-provoking uncertainty, which can be experienced negatively as anxiety,
or positively as a wellspring for creativity (or both). Thus, intrinsically
motivated creativity begins with detection of high psychological entropy
material (e.g., a question or inconsistency), which provokes uncertainty and is
arousal-inducing. This material is recursively considering from new contexts
until it is sufficiently restructured that arousal dissipates and entropy
reaches an acceptable level. Restructuring involves neural synchrony and
dynamic binding, and may be facilitated by temporarily shifting to a more
associative mode of thought. The creative outcome may similarly induce
restructuring in others, and thereby contribute to the cultural evolution of
more nuanced understandings. Thus, the concept of entropy could play a unifying
role in cognitive science as a driver of thought and action, and in cultural
studies as the driver of the creative innovations that fuel cultural evolution.
The paper concludes with an invitation for cross-disciplinary exploration of
this potential new arena of entropy studies.
The Neural Basis and Evolution of Divergent and Convergent Thought
Date: 2019-03-13 00:00:00

This chapter takes as its departure point a neural level theory of insight
that arose from studies of the sparse, distributed, content-addressable
architecture of associative memory. It is argued that convergent thought is
most fruitfully characterized in terms of, not the generation of a single
correct solution (as it is conventionally construed), but using concepts in
their most compact form by activating neural cell assemblies that respond to
their most typical properties. This allows them to be deployed in a
conventional manner such that effort is reserved for exploring causal
relationships. Conversely, it is argued that divergent thought is most
fruitfully characterized in terms of, not the generation of multiple solutions
(as it is conventionally construed), but using concepts in a form that is,
albeit expanded, constrained by the situation, by activating neural cell
assemblies that respond to context-specific atypical properties. This allows
them to be deployed in a manner that is conducive to exploring unconventional
yet potentially relevant associations, and unearthing potentially useful
relationships of correlation. Thus, divergent thought can involve as few as one
idea. This proposal is compatible with widespread beliefs that (1) most
creative tasks require not many solutions but one, yet entail both divergent
and convergent thinking, and (2) not all problems with multiple solutions
require creative thinking, and conversely, some problems with single solution
do require creative thought. The chapter discusses how the ability to shift
between convergent and divergent modes of thought may have evolved, and it
concludes with educational and vocational implications.
A model for structured information representation in neural networks
Date: 2019-03-26 00:00:00
Tasks: Information Retrieval, Retrieval, Sentence

Humans possess the capability to reason at an abstract level and to structure
information into abstract categories, but the underlying neural processes have
remained unknown. Experimental evidence has recently emerged for the
organization of an important aspect of abstract reasoning: for assigning words
to semantic roles in a sentence, such as agent (or subject) and patient (or
object). Using minimal assumptions, we show how such a binding of words to
semantic roles emerges in a generic spiking neural network through Hebbian
plasticity. The resulting model is consistent with the experimental data and
enables new computational functionalities such as structured information
retrieval, copying data, and comparisons. It thus provides a basis for the
implementation of more demanding cognitive computations by networks of spiking
neurons.
Properties of the financial break-even point in a simple investment project as a function of the discount rate
Date: 2016-06-29 00:00:00

We consider a simple investment project with the following parameters: I>0:
Initial investment which is amortizable in n years; n: Number of years the
investment allows production with constant output per year; A>0: Annual
amortization (A=I/n); Q>0: Quantity of products sold per year; Cv>0: Variable
cost per unit; p>0: Price of the product with p>Cv; Cf>0: Annual fixed costs;
te: Tax of earnings; r: Annual discount rate. We also assume inflation is
negligible. We derive a closed expression of the financial break-even point Qf
(i.e. the value of Q for which the net present value (NPV) is zero) as a
function of the parameters I, n, Cv, Cf, te, r, p. We study the behavior of Qf
as a function of the discount rate r and we prove that: (i) For r negligible Qf
equals the accounting break-even point Qc (i.e. the earnings before taxes (EBT)
is null) ; (ii) When r is large the graph of the function Qf=Qf(r) has an
asymptotic straight line with positive slope. Moreover, Qf(r) is an strictly
increasing and convex function of the variable r; (iii) From a sensitivity
analysis we conclude that, while the influence of p and Cv on Qf is strong, the
influence of Cf on Qf is weak.
Top-k String Auto-Completion with Synonyms
Authors: Xu Pengfei, Lu Jiaheng
Date: 2016-11-22 00:00:00
Tasks: Management, Retrieval

Auto-completion is one of the most prominent features of modern information
systems. The existing solutions of auto-completion provide the suggestions
based on the beginning of the currently input character sequence (i.e. prefix).
However, in many real applications, one entity often has synonyms or
abbreviations. For example, "DBMS" is an abbreviation of "Database Management
Systems". In this paper, we study a novel type of auto-completion by using
synonyms and abbreviations. We propose three trie-based algorithms to solve the
top-k auto-completion with synonyms; each one with different space and time
complexity trade-offs. Experiments on large-scale datasets show that it is
possible to support effective and efficient synonym-based retrieval of
completions of a million strings with thousands of synonyms rules at about a
microsecond per-completion, while taking small space overhead (i.e. 160-200
bytes per string). The source code of our experiments can be download at:
http://udbms.cs.helsinki.fi/?projects/autocompletion/download .
What do central counterparties default funds really cover? A network-based stress test answer
Date: 2016-11-11 00:00:00

In the last years, increasing efforts have been put into the development of
effective stress tests to quantify the resilience of financial institutions.
Here we propose a stress test methodology for central counterparties based on a
network characterization of clearing members, whose links correspond to direct
credits and debits. This network constitutes the ground for the propagation of
financial distress: equity losses caused by an initial shock with both
exogenous and endogenous components reverberate within the network and are
amplified through credit and liquidity contagion channels. At the end of the
dynamics, we determine the vulnerability of each clearing member, which
represents its potential equity loss. We apply the proposed framework to the
Fixed Income asset class of CC&G, the central counterparty operating in Italy
whose main cleared securities are Italian Government Bonds. We consider two
different scenarios: a distributed, plausible initial shock, as well as a shock
corresponding to the cover 2 regulatory requirement (the simultaneous default
of the two most exposed clearing members). Although the two situations lead to
similar results after an unlimited reverberation of shocks on the network, the
distress propagation is much more hasty in the latter case, with a large number
of additional defaults triggered at early stages of the dynamics. Our results
thus show that setting a default fund to cover insolvencies only on a cover 2
basis may not be adequate for taming systemic events, and only very
conservative default funds, such as CC&G's one, can face total losses due to
the shock propagation. Overall, our network-based stress test represents a
refined tool for calibrating default fund amounts.
Configuration Interaction of Hydropathic Waves Enables Ubiquitin Functionality
Date: 2016-11-11 00:00:00

Ubiquitin, discovered less than 50 years ago, tags thousands of diseased
proteins for destruction. It is small (only 76 amino acids), and is found
unchanged in mammals, birds, fish and even worms. Key features of its
functionality are identified here using critical point thermodynamic scaling
theory. These include Fano interference between first- and second-order
elements of globular surface shape transitions. Comparison with its closest
relative, 76 amino acid Nedd8, shows that the latter lacks these features. A
cracked elastic network model is proposed for the common target shared by many
diseased proteins.
Shared information between residues is sufficient to detect pair-wise epistasis in a protein
Date: 2016-11-12 00:00:00

In a comment on our manuscript "Strong selection significantly increases
epistatic interactions in the long-term evolution of a protein", Dr. Crona
challenges our assertion that shared entropy (that is, information) between two
residues implies epistasis between those residues, by constructing an explicit
example of three loci (say A, B, and C), where A and B are epistatically linked
(leading to shared entropy between A and B), and A and C also depend
epistatically (leading to shared entropy between A and C), so that loci B and C
are correlated (share entropy).
Residual Information of Previous Decision Affects Evidence Accumulation in Current Decision
Date: 2017-10-14 00:00:00
Tasks: Decision Making

Bias in perceptual decisions comes to pass when the advance knowledge
colludes with the current sensory evidence in support of the final choice. The
literature on decision making suggests two main hypotheses to account for this
kind of bias: internal bias signals are derived from (a) the residual of motor
response-related signals, and (b) the sensory information residues of the
decisions that we made in the past. Beside these hypotheses, a credible
hypothesis proposed by this study to explain the cause of decision biasing,
suggests that the decision-related neuron can make use of the residual
information of the previous decision for the current decision. We demonstrate
the validity of this assumption, first by performing behavioral experiments
based on the two-alternative forced-choice (TAFC) discrimination of motion
direction paradigms and then, we modified the pure drift-diffusion model (DDM)
based on accumulation to the bound mechanism to account for the sequential
effect. In both cases, the trace of the previous trial influences the current
decision. Results indicate that the probability of being correct in a current
decision increases if it is in line with the previously made decision. Also,
the model that keeps the previous decision information provides a better fit to
the behavioral data. Our findings suggest that the state of a decision variable
which is represented in the activity of decision-related neurons after crossing
the bound (in the previous decision) can accumulate with the decision variable
for the current decision in consecutive trials.
High-Resolution Structure and Intermolecular Interactions between L-type Straight Flagellar Filaments
Date: 2016-11-12 00:00:00

Bacterial mobility is powered by rotation of helical flagellar filaments
driven by rotary motors. Flagellin isolated from {\it Salmonella Typhimurium}
SJW1660 strain, which differs by a point mutation from the wild-type strain,
assembles into straight filaments in which flagellin monomers are arranged into
left-handed helix. Using small-angle X-ray scattering (SAXS) and osmotic stress
methods, we investigated the high-resolution structure of SJW1660 flagellar
filaments as well as intermolecular forces that govern their assembly into
dense hexagonal bundle. The scattering data were fitted to high-resolution
models, which took into account the atomic structure of the flagellin subunits.
The analysis revealed the exact helical arrangement and the super-helical twist
of the flagellin subunits within the filaments. Under osmotic stress the
filaments formed $2D$ hexagonal bundles. Monte-Carlo simulations and continuum
theories were used to analyze the scattering data from hexagonal arrays,
revealing how bulk modulus, as well as how the deflection length depends on the
applied osmotic stress. Scattering data from aligned flagellar bundles
confirmed the predicated structure-factor scattering peak line-shape.
Quantitative analysis of the measured equation of state of the bundles revealed
the contributions of the electrostatic, hydration, and elastic interactions to
the intermolecular interactions associated with bundling of straight
semi-flexible flagellar filaments.}%1 {Insert Received for publication Date and
in final form Date.
Mean-field models for non-Markovian epidemics on networks: from edge-based compartmental to pairwise models
Date: 2016-11-12 00:00:00

This paper presents a novel extension of the edge-based compartmental model
for epidemics with arbitrary distributions of transmission and recovery times.
Using the message passing approach we also derive a new pairwise-like model for
epidemics with Markovian transmission and an arbitrary recovery period. The new
pairwise-like model allows one to formally prove that the message passing and
edge-based compartmental models are equivalent in the case of Markovian
transmission and arbitrary recovery processes. The edge-based and message
passing models are conjectured to also be equivalent for arbitrary transmission
processes; we show the first step of a full proof of this. The new
pairwise-like model encompasses many existing well-known models that can be
obtained by appropriate reductions. It is also amenable to a relatively
straightforward numerical implementation. We test the theoretical results by
comparing the numerical solutions of the various pairwise-like models to
results based on explicit stochastic network simulations.
The Reasonable Effectiveness of Agent-Based Simulations in Evolutionary Game Theory
Date: 2016-11-13 00:00:00

This is a Reply to comments published in Physics of Life Reviews, on our
article "Evolutionary game theory using agent-based methods" (Physics of Life
Reviews, 2016, arXiv:1404.0994).
Time-varying return predictability in the Chinese stock market
Date: 2016-11-13 00:00:00

China's stock market is the largest emerging market all over the world. It is
widely accepted that the Chinese stock market is far from efficiency and it
possesses possible linear and nonlinear dependence. We study the predictability
of returns in the Chinese stock market by employing the wild bootstrap
automatic variance ratio test and the generalized spectral test. We find that
the return predictability vary over time and significant return predictability
is observed around market turmoils. Our findings are consistent with the
Adaptive Markets Hypothesis and have practical implications for market
participants.
Immediate price impact of a stock and its warrant: Power-law or logarithmic model?
Date: 2016-11-13 00:00:00

Based on the order flow data of a stock and its warrant, the immediate price
impacts of market orders are estimated by two competitive models, the power-law
model (PL model) and the logarithmic model (LG model). We find that the PL
model is overwhelmingly superior to the LG model, regarding the robustness of
the estimated parameters and the accuracy of out-of-sample forecasting. We also
find that the price impacts of ask and bid orders are consistent with each
other for filled trades, since significant positive correlations are observed
between the model parameters of both types of orders. Our findings may provide
valuable insights for optimal trade execution.
Dynamic instabilities in the kinetics of growth and disassembly of microtubules
Date: 2016-11-13 00:00:00

Dynamic instability of microtubules is considered using frameworks of
non-linear thermodynamics and non-equilibrium reaction-diffusion systems.
Stochastic assembly/disassembly phases in the polymerization dynamics of
microtubules are treated as a result of collective clusterization of
microdefects (holes in structure). The model explains experimentally observed
power law dependence of catastrophe frequency from the microtubule growth rate.
Additional reaction-diffusion-precipitation model is developed to account for
kinetic limitations in microtubule dynamics. It is shown that large scale
periodic microtubules length fluctuations are accompanied by concentration
autowaves. We built corresponding parametric diagram mapping areas of
stationary, non-stationary and metastable solutions. The loss of stability for
the stationary solutions happens through bifurcation of Andronov-Hopf. Using
parametric diagram we classify cytostatic effect of microtubule stabilizing
drugs in four major classes and analyze their compatibility and possible
synergistic effect for cancer treatment therapy.
On the Mechanism of Homology Search by RecA Protein Filaments
Date: 2016-11-13 00:00:00

Genetic stability is a key factor in maintaining, survival and reproduction
of biological cells. It relies on many processes, but one of the most important
is a {\it homologous recombination}, in which the repair of breaks in
double-stranded DNA molecules is taking place with a help of several specific
proteins. In bacteria this task is accomplished by RecA proteins that are
active as nucleoprotein filaments formed on single-stranded segments of DNA. A
critical step in the homologous recombination is a search for a corresponding
homologous region on DNA, which is called a {\it homology search}. Recent
single-molecule experiments clarified some aspects of this process, but its
molecular mechanisms remain not well understood. We developed a quantitative
theoretical approach to analyze the homology search. It is based on a
discrete-state stochastic model that takes into account the most relevant
physical-chemical processes in the system. Using a method of first-passage
processes, a full dynamic description of the homology search is presented. It
is found that the search dynamics depends on the degree of extension of DNA
molecules and on the size of RecA nucleoprotein filaments, in agreement with
experimental single-molecule measurements of DNA pairing by RecA proteins. Our
theoretical calculations, supported by extensive Monte Carlo computer
simulations, provide a molecular description of the mechanisms of the homology
search.