pwc-archive/papers-with-abstracts huggingface dataset:
Response and noise correlations to complex natural sounds in the auditory midbrain
Date: 2016-06-29 00:00:00

How natural communication sounds are spatially represented across the
inferior colliculus, the main center of convergence for auditory information in
the midbrain, is not known. The neural representation of the acoustic stimuli
results from the interplay of locally differing input and the organization of
spectral and temporal neural preferences that change gradually across the
nucleus. This raises the question how similar the neural representation of the
communication sounds is across these gradients of neural preferences, and
whether it also changes gradually. Multi-unit cluster spike trains were
recorded from guinea pigs presented with a spectrotemporally rich set of eleven
species-specific communication sounds. Using cross-correlation, we analyzed the
response similarity of spiking activity across a broad frequency range for
similarly and differently frequency-tuned neurons. Furthermore, we separated
the contribution of the stimulus to the correlations to investigate whether
similarity is only attributable to the stimulus, or, whether interactions exist
between the multi-unit clusters that lead to correlations and whether these
follow the same representation as the response similarity. We found that
similarity of responses is dependent on the neurons' spatial distance for
similarly and differently frequency-tuned neurons, and that similarity
decreases gradually with spatial distance. Significant neural correlations
exist, and contribute to the response similarity. Our findings suggest that for
multi-unit clusters in the mammalian inferior colliculus, the gradual response
similarity with spatial distance to natural complex sounds is shaped by neural
interactions and the gradual organization of neural preferences.
Relevant parameters in models of cell division control
Date: 2016-06-29 00:00:00

A recent burst of dynamic single-cell growth-division data makes it possible
to characterize the stochastic dynamics of cell division control in bacteria.
Different modeling frameworks were used to infer specific mechanisms from such
data, but the links between frameworks are poorly explored, with relevant
consequences for how well any particular mechanism can be supported by the
data. Here, we describe a simple and generic framework in which two common
formalisms can be used interchangeably: (i) a continuous-time division process
described by a hazard function and (ii) a discrete-time equation describing
cell size across generations (where the unit of time is a cell cycle). In our
framework, this second process is a discrete-time Langevin equation with a
simple physical analogue. By perturbative expansion around the mean initial
size (or inter-division time), we show explicitly how this framework describes
a wide range of division control mechanisms, including combinations of time and
size control, as well as the constant added size mechanism recently found to
capture several aspects of the cell division behavior of different bacteria. As
we show by analytical estimates and numerical simulation, the available data
are characterized with great precision by the first-order approximation of this
expansion. Hence, a single dimensionless parameter defines the strength and the
action of the division control. However, this parameter may emerge from several
mechanisms, which are distinguished only by higher-order terms in our
perturbative expansion. An analytical estimate of the sample size needed to
distinguish between second-order effects shows that this is larger than what is
available in the current datasets. These results provide a unified framework
for future studies and clarify the relevant parameters at play in the control
of cell division.
Phylogenomic Analyses of Large-scale Nuclear Genes Provide New Insights into the Evolutionary Relationships within the Rosids
Date: 2016-06-30 00:00:00

The Rosids is one of the largest groups of flowering plants, with 140
families and ~70,000 species. Previous phylogenetic studies of the rosids have
primarily utilized organelle genes that likely differ in evolutionary histories
from nuclear genes. To better understand the evolutionary history of rosids, it
is necessary to investigate their phylogenetic relationships using nuclear
genes. Here, we employed large-scale phylogenomic datasets composed of nuclear
genes, including 891 clusters of putative orthologous genes. Combined with
comprehensive taxon sampling covering 63 species representing 14 out of the 17
orders, we reconstructed the rosids phylogeny with coalescence and
concatenation methods, yielding similar tree topologies from all datasets.
However, these topologies did not agree on the placement of Zygophyllales.
Through comprehensive analyses, we found that missing data and gene tree
heterogeneity were potential factors that may mislead concatenation methods, in
particular, large amounts of missing data under high gene tree heterogeneity.
Our results provided new insights into the deep phylogenetic relationships of
the rosids, and demonstrated that coalescence methods may effectively resolve
the phylogenetic relationships of the rosids with missing data under high gene
tree heterogeneity.
Stride variability measures derived from wrist- and hip-worn accelerometers
Date: 2016-06-30 00:00:00

Many epidemiological and clinical studies use accelerometry to objectively
measure physical activity using the activity counts, vector magnitude, or
number of steps. These measures use just a fraction of the information in the
raw accelerometry data as they are typically summarized at the minute level. To
address this problem we define and estimate two gait measures of temporal
stride-to-stride variability based on raw accelerometry data: Amplitude
Deviation (AD) and Phase Deviation (PD). We explore the sensitivity of our
approach to on-body placement of the accelerometer by comparing hip, left and
right wrist placements. We illustrate the approach by estimating AD and PD in
46 elderly participants in the Developmental Epidemiologic Cohort Study (DECOS)
who worn accelerometers during a 400 meter walk test. We also show that AD and
PD have a statistically significant association with the gait speed and
sit-to-stand test performance
Individual Differences in Dynamic Functional Brain Connectivity Across the Human Lifespan
Date: 2016-06-30 00:00:00

Individual differences in brain functional networks may be related to complex
personal identifiers, including health, age, and ability. Understanding and
quantifying these differences is a necessary first step towards developing
predictive methods derived from network topology. Here, we present a method to
quantify individual differences in brain functional dynamics by applying
hypergraph analysis, a method from dynamic network theory. Using a summary
metric derived from the hypergraph formalism---hypergraph cardinality---we
investigate individual variations in two separate and complementary data sets.
The first data set ("multi-task") consists of 77 individuals engaging in four
consecutive cognitive tasks. We observed that hypergraph cardinality exhibits
variation across individuals while remaining consistent within individuals
between tasks; moreover, one of the memory tasks evinced a marginally
significant correspondence between hypergraph cardinality and age. This finding
motivated a similar analysis of the second data set ("age-memory"), in which 95
individuals of varying ages performed a memory task with a similar structure to
the multi-task memory task. With the increased age range in the age-memory data
set, the correlation between hypergraph cardinality and age correspondence
becomes significant. We discuss these results in the context of the well-known
finding linking age with network structure, and suggest that age-related
changes in brain function can be better understood by taking an integrative
approach that incorporates information about the dynamics of functional
interactions.
Stock Market Insider Trading in Continuous Time with Imperfect Dynamic Information
Date: 2016-06-30 00:00:00

This paper studies the equilibrium pricing of asset shares in the presence of
dynamic private information. The market consists of a risk-neutral informed
agent who observes the firm value, noise traders, and competitive market makers
who set share prices using the total order flow as a noisy signal of the
insider's information. I provide a characterization of all optimal strategies,
and prove existence of both Markovian and non Markovian equilibria by deriving
closed form solutions for the optimal order process of the informed trader and
the optimal pricing rule of the market maker. The consideration of non
Markovian equilibrium is relevant since the market maker might decide to
re-weight past information after receiving a new signal. Also, I show that a)
there is a unique Markovian equilibrium price process which allows the insider
to trade undetected, and that b) the presence of an insider increases the
market informational efficiency, in particular for times close to dividend
payment.
Analysis of Chromosome 20 - A Study
Date: 2016-06-30 00:00:00

Since the arrival of next-generation sequencing technologies the amount of
genetic sequencing data has increased dramatically. This has has fueled an
increase in human genetics research. At the same time, with the recent advent
of technologies in processing large data sets, lot of these technologies are
proving valuable and efficient in analyzing these huge datasets. In this paper
we use some of these technologies to analyze genetic sequencing data of 1000
Genomes Project,produce and evaluate a framework to process the sequencing data
thereof and look into structural variations with respect to population groups.
Automated pulse discrimination of two freely-swimming weakly electric fish and analysis of their electrical behavior during a dominance contest
Date: 2017-03-22 00:00:00

Electric fishes modulate their electric organ discharges with a remarkable
variability. Some patterns can be easily identified, such as pulse rate
changes, offs and chirps, which are often associated with important behavioral
contexts, including aggression, hiding and mating. However, these behaviors are
only observed when at least two fish are freely interacting. Although their
electrical pulses can be easily recorded by non-invasive techniques,
discriminating the emitter of each pulse is challenging when physically similar
fish are allowed to freely move and interact. Here we optimized a custom-made
software recently designed to identify the emitter of pulses by using automated
chirp detection, adaptive threshold for pulse detection and slightly changing
how the recorded signals are integrated. With these optimizations, we performed
a quantitative analysis of the statistical changes throughout the dominance
contest with respect to Inter Pulse Intervals, Chirps and Offs dyads of freely
moving Gymnotus carapo. In all dyads, chirps were signatures of subsequent
submission, even when they occurred early in the contest. Although offs were
observed in both dominant and submissive fish, they were substantially more
frequent in submissive individuals, in agreement with the idea from previous
studies that offs are electric cues of submission. In general, after the
dominance is established the submissive fish significantly changes its average
pulse rate, while the pulse rate of the dominant remained unchanged.
Additionally, no chirps or offs were observed when two fish were manually kept
in direct physical contact, suggesting that these electric behaviors are not
automatic responses to physical contact.
Estimation and prediction of credit risk based on rating transition systems
Date: 2018-03-27 00:00:00
Tasks: Management

Risk management is an important practice in the banking industry. In this
paper we develop a new methodology to estimate and predict the probability of
default (PD) based on the rating transition matrices, which relates the rating
transition matrices to the macroeconomic variables. Our method can overcome the
shortcomings of the framework of Belkin et al. (1998), and is especially useful
in predicting the PD and doing stress testing. Simulation is conducted at the
end, which shows that our method can provide more accurate estimate than that
obtained by the method of Belkin et al. (1998).
Limit order trading with a mean reverting reference price
Date: 2016-11-14 00:00:00

Optimal control models for limit order trading often assume that the
underlying asset price is a Brownian motion since they deal with relatively
short time scales. The resulting optimal bid and ask limit order prices tend to
track the underlying price as one might expect. This is indeed the case with
the model of Avellaneda and Stoikov (2008), which has been studied extensively.
We consider here this model under the condition when the underlying price is
mean reverting. Our main result is that when time is far from the terminal, the
optimal price for bid and ask limit orders is constant, which means that it
does not track the underlying price. Numerical simulations confirm this
behavior. When the underlying price is mean reverting, then for times
sufficiently far from terminal, it is more advantageous to focus on the mean
price and ignore fluctuations around it. Mean reversion suggests that limit
orders will be executed with some regularity, and this is why they are optimal.
We also explore intermediate time regimes where limit order prices are
influenced by the inventory of outstanding orders. The duration of this
intermediate regime depends on the liquidity of the market as measured by
specific parameters in the model.
The Host-Pathogen Game: an evolutionary approach to biological competitions
Date: 2018-08-31 00:00:00

We introduce a model called Host-Pathogen game for studying biological
competitions. Notably, we focus on the invasive dynamics of external agents,
like bacteria, within a host organism. The former are mapped to a population of
defectors that aim to spread in the extracellular medium of the host. In turn,
the latter is composed of cells, mapped to a population of cooperators, that
aim to kill pathogens. The cooperative behavior of cells is fundamental for the
emergence of the living functions of the whole organism, since each one
contributes to a specific set of tasks. So, broadly speaking, their
contribution can be viewed as a form of energy. When bacteria are spatially
close to a cell, the latter can use a fraction of its energy to remove them. On
the other hand, when bacteria survive an attack, they absorb the received
energy, becoming stronger and more resistant to further attacks. In addition,
since bacteria play as defectors, their unique target is to increase their
wealth, without supporting their own kind. As in many living organisms, the
host temperature plays a relevant role in the host-pathogen equilibrium. For
instance, in animals like human beings, a neural mechanism triggers the
increasing of the body temperature in order to activate the immune system.
Here, cooperators succeed once bacteria are completely removed while, in the
opposite scenario, the host undergoes a deep invasive process, like a blood
poisoning. Results of numerical simulations show that the dynamics of the
proposed model allow to reach a variety of states. At a very high level of
abstraction, some of these states seem to be similar to those that can be
observed in some living systems. Therefore, to conclude, we deem that our model
might be exploited for studying further biological phenomena.
Natural gas-fired power plants valuation and optimisation under Levy copulas and regime-switching
Date: 2016-07-30 00:00:00

In this work we analyse a stochastic control problem for the valuation of a
natural gas power station while taking into account operating characteristics.
Both electricity and gas spot price processes exhibit mean-reverting spikes and
Markov regime-switches. The Levy regime-switching model incorporates the
effects of demand-supply fluctuations in energy markets and abrupt economic
disruptions or business cycles. We make use of skewed Levy copulas to model the
dependence risk of electricity and gas jumps.
  The corresponding HJB equation is the non-linear PIDE which is solved by an
explicit finite difference method. The numerical approach gives us both the
value of the plant and its optimal operating strategy depending on the gas and
electricity prices, current temperature of the boiler and time. The surfaces of
control strategies and contract values are obtained by implementing the
numerical method for a particular example.
Evolutionary Model of Stock Markets
Date: 2015-05-15 00:00:00
Tasks: model

The paper presents an evolutionary economic model for the price evolution of
stocks. Treating a stock market as a self-organized system governed by a fast
purchase process and slow variations of demand and supply the model suggests
that the short term price distribution has the form a logistic (Laplace)
distribution. The long term return can be described by Laplace-Gaussian mixture
distributions. The long term mean price evolution is governed by a Walrus
equation, which can be transformed into a replicator equation. This allows
quantifying the evolutionary price competition between stocks. The theory
suggests that stock prices scaled by the price over all stocks can be used to
investigate long-term trends in a Fisher-Pry plot. The price competition that
follows from the model is illustrated by examining the empirical long-term
price trends of two stocks.
SMISS: A protein function prediction server by integrating multiple sources
Date: 2016-03-22 00:00:00
Tasks: Prediction, Protein Function Prediction

SMISS is a novel web server for protein function prediction. Three different
predictors can be selected for different usage. It integrates different sources
to improve the protein function prediction accuracy, including the query
protein sequence, protein-protein interaction network, gene-gene interaction
network, and the rules mined from protein function associations. SMISS
automatically switch to ab initio protein function prediction based on the
query sequence when there is no homologs in the database. It takes fasta format
sequences as input, and several sequences can submit together without
influencing the computation speed too much. PHP and Perl are two primary
programming language used in the server. The CodeIgniter MVC PHP web framework
and Bootstrap front-end framework are used for building the server. It can be
used in different platforms in standard web browser, such as Windows, Mac OS X,
Linux, and iOS. No plugins are needed for our website. Availability:
http://tulip.rnet.missouri.edu/profunc/.
Swaption Prices in HJM model. Nonparametric fit
Date: 2017-04-10 00:00:00
Tasks: model

Closed form formulas for swaption prices in HJM model are derived. These
formulas are used for nonparametric fit of deterministic forward volatility. It
is demonstrated that this formula and non-parametric fit works very well and
can be used to identify arbitrage opportunities
Optimal Trajectories of Brain State Transitions
Date: 2017-01-10 00:00:00
Tasks: Anatomy, Specificity

The complexity of neural dynamics stems in part from the complexity of the
underlying anatomy. Yet how the organization of white matter architecture
constrains how the brain transitions from one cognitive state to another
remains unknown. Here we address this question from a computational perspective
by defining a brain state as a pattern of activity across brain regions.
Drawing on recent advances in network control theory, we model the underlying
mechanisms of brain state transitions as elicited by the collective control of
region sets. Specifically, we examine how the brain moves from a specified
initial state (characterized by high activity in the default mode) to a
specified target state (characterized by high activity in primary sensorimotor
cortex) in finite time. Across all state transitions, we observe that the
supramarginal gyrus and the inferior parietal lobule consistently acted as
efficient, low energy control hubs, consistent with their strong anatomical
connections to key input areas of sensorimotor cortex. Importantly, both these
and other regions in the fronto-parietal, cingulo-opercular, and attention
systems are poised to affect a broad array of state transitions that cannot
easily be classified by traditional notions of control common in the
engineering literature. This theoretical versatility comes with a vulnerability
to injury. In patients with mild traumatic brain injury, we observe a loss of
specificity in putative control processes, suggesting greater susceptibility to
damage-induced noise in neurophysiological activity. These results offer
fundamentally new insights into the mechanisms driving brain state transitions
in healthy cognition and their alteration following injury.
Using Perturbations to Probe the Neural Control of Rhythmic Movements
Date: 2016-10-27 00:00:00

Small continuous sensory and mechanical perturbations have often been used to
identify properties of the closed-loop neural control of posture and other
systems that are approximately linear time invariant. Here we extend this
approach to study the neural control of rhythmic behaviors such as walking. Our
method is based on the theory of linear time periodic systems, with
modifications to account for ability of perturbations to reset the phase of a
rhythmic behavior. We characterize responses to perturbations in the frequency
domain using harmonic transfer functions and then convert to the time domain to
obtain phase-dependent impulse response functions (IRFs) that describe the
response to a small brief perturbation at any phase of the rhythmic behavior.
IRFs describing responses of kinematic variables and muscle activations
(measured by EMG) to sensory and mechanical perturbations can be used to infer
properties of the plant, the mapping from muscle activation to movement, and of
neural feedback, the mapping from movement to muscle activation. We illustrate
our method by applying it to simulated data from a model and experimental data
of subjects walking on a treadmill perturbed by movement of the visual scene.
Derivative pricing as a transport problem: MPDATA solutions to Black-Scholes-type equations
Date: 2018-12-31 00:00:00

We discuss in this note applications of the Multidimensional Positive
Definite Advection Transport Algorithm (MPDATA) to numerical solutions of
partial differential equations arising from stochastic models in quantitative
finance. In particular, we develop a framework for solving Black-Scholes-type
equations by first transforming them into advection-diffusion problems, and
numerically integrating using an iterative explicit finite-difference approach,
in which the Fickian term is represented as an additional advective term. We
discuss the correspondence between transport phenomena and financial models,
uncovering the possibility of expressing the no-arbitrage principle as a
conservation law. We depict second-order accuracy in time and space of the
embraced numerical scheme. This is done in a convergence analysis comparing
MPDATA numerical solutions with classic Black-Scholes analytical formulae for
the valuation of European options. We demonstrate in addition a way of applying
MPDATA to solve the free boundary problem (leading to a linear complementarity
problem) for the valuation of American options. We finally comment on the
potential the MPDATA framework has with respect to being applied in tandem with
more complex models typically used in quantitive finance.