pwc-archive/papers-with-abstracts huggingface dataset:
A quantitative definition of organismality and its application to lichen
Date: 2016-11-30 00:00:00

The organism is a fundamental concept in biology. However there is no
universally accepted, formal, and yet broadly applicable definition of what an
organism is. Here we introduce a candidate definition. We adopt the view that
the "organism" is a functional concept, used by scientists to address
particular questions concerning the future state of a biological system, rather
than something wholly defined by that system. In this approach organisms are a
coarse-graining of a fine-grained dynamical model of a biological system.
Crucially, the coarse-graining of the system into organisms is chosen so that
their dynamics can be used by scientists to make accurate predictions of those
features of the biological system that interests them, and do so with minimal
computational burden. To illustrate our framework we apply it to a dynamic
model of lichen symbiosis---a system where either the lichen or its constituent
fungi and algae could reasonably be considered "organisms." We find that the
best choice for what organisms are in this scenario are complex mixtures of
many entities that do not resemble standard notions of organisms. When we
restrict our allowed coarse-grainings to more traditional types of organisms,
we find that ecological conditions, such as niche competition and predation
pressure, play a significant role in determining the best choice for organisms.
Assessing the impacts of time to detection distribution assumptions on detection probability estimation
Date: 2017-05-19 00:00:00

Abundance estimates from animal point-count surveys require accurate
estimates of detection probabilities. The standard model for estimating
detection from removal-sampled point-count surveys assumes that organisms at a
survey site are detected at a constant rate; however, this assumption is often
not justified. We consider a class of N-mixture models that allows for
detection heterogeneity over time through a flexibly defined time-to-detection
distribution (TTDD) and allows for fixed and random effects for both abundance
and detection. Our model is thus a combination of survival time-to-event
analysis with unknown-N, unknown-p abundance estimation. We specifically
explore two-parameter families of TTDDs, e.g. gamma, that can additionally
include a mixture component to model increased probability of detection in the
initial observation period. We find that modeling a TTDD by using a
two-parameter family is necessary when data have a chance of arising from a
distribution of this nature. In addition, models with a mixture component can
outperform non-mixture models even when the truth is non-mixture. Finally, we
analyze an Overbird data set from the Chippewa National Forest using mixed
effect models for both abundance and detection. We demonstrate that the effects
of explanatory variables on abundance and detection are consistent across
mixture TTDDs but that flexible TTDDs result in lower estimated probabilities
of detection and therefore higher estimates of abundance.
Factory of realities: on the emergence of virtual spatiotemporal structures
Authors: Zapatrin Roman
Date: 2016-11-30 00:00:00
Tasks: Information Retrieval, Retrieval

The ubiquitous nature of modern Information Retrieval and Virtual World give
rise to new realities. To what extent are these "realities" real? Which
"physics" should be applied to quantitatively describe them? In this essay I
dwell on few examples. The first is Adaptive neural networks, which are not
networks and not neural, but still provide service similar to classical ANNs in
extended fashion. The second is the emergence of objects looking like
Einsteinian spacetime, which describe the behavior of an Internet surfer like
geodesic motion. The third is the demonstration of nonclassical and even
stronger-than-quantum probabilities in Information Retrieval, their use.
  Immense operable datasets provide new operationalistic environments, which
become to greater and greater extent "realities". In this essay, I consider the
overall Information Retrieval process as an objective physical process,
representing it according to Melucci metaphor in terms of physical-like
experiments. Various semantic environments are treated as analogs of various
realities. The readers' attention is drawn to topos approach to physical
theories, which provides a natural conceptual and technical framework to cope
with the new emerging realities.
EEG-assisted Modulation of Sound Sources in the Auditory Scene
Date: 2017-11-28 00:00:00
Tasks: Brain Computer Interface, EEG, Electroencephalogram (EEG)

Noninvasive EEG (electroencephalography) based auditory attention detection
could be useful for improved hearing aids in the future. This work is a novel
attempt to investigate the feasibility of online modulation of sound sources by
probabilistic detection of auditory attention, using a noninvasive EEG-based
brain computer interface. Proposed online system modulates the upcoming sound
sources through gain adaptation which employs probabilistic decisions (soft
decisions) from a classifier trained on offline calibration data. In this work,
calibration EEG data were collected in sessions where the participants listened
to two sound sources (one attended and one unattended). Cross-correlation
coefficients between the EEG measurements and the attended and unattended sound
source envelope (estimates) are used to show differences in sharpness and
delays of neural responses for attended versus unattended sound source. Salient
features to distinguish attended sources from the unattended ones in the
correlation patterns have been identified, and later they have been used to
train an auditory attention classifier. Compared to the existing results in the
literature, in this paper we have two main contributions. First, using the
auditory attention classifier, we have shown high offline detection performance
with single channel EEG measurements of shorter duration compared to the
existing approaches in the literature which employ large number of channels
with longer EEG measurements. Second, using the classifier trained offline in
the calibration session, we have shown the performance of the online sound
source modulation system. We observe that online sound source modulation system
is able to keep the level of attended sound source higher than the unattended
source.
  Keywords: auditory BCI, cocktail party problem, auditory attention
classification
How much market making does a market need?
Date: 2018-06-25 00:00:00

We consider a simple model for the evolution of a limit order book in which
limit orders of unit size arrive according to independent Poisson processes.
The frequencies of buy limit orders below a given price level, respectively
sell limit orders above a given level are described by fixed demand and supply
functions. Buy (resp. sell) limit orders that arrive above (resp. below) the
current ask (resp. bid) price are converted into market orders. There is no
cancellation of limit orders. This model has independently been reinvented by
several authors, including Stigler in 1964 and Luckock in 2003, who was able to
calculate the equilibrium distribution of the bid and ask prices. We extend the
model by introducing market makers that simultaneously place both a buy and
sell limit order at the current bid and ask price. We show how the introduction
of market makers reduces the spread, which in the original model is
unrealistically large. In particular, we are able to calculate the exact rate
at which market makers need to place orders in order to close the spread
completely. If this rate is exceeded, we show that the price settles at a
random level that in general does not correspond the Walrasian equilibrium
price.
A Primer on Portfolio Choice with Small Transaction Costs
Date: 2017-05-23 00:00:00
Tasks: Survey

This survey is an introduction to asymptotic methods for portfolio-choice
problems with small transaction costs. We outline how to derive the
corresponding dynamic programming equations and simplify them in the small-cost
limit. This allows to obtain explicit solutions in a wide range of settings,
which we illustrate for a model with mean-reverting expected returns and
proportional transaction costs. For even more complex models, we present a
policy iteration scheme that allows to compute the solution numerically.
Probabilistic Broken-Stick Model: A Regression Algorithm for Irregularly Sampled Data with Application to eGFR
Date: 2016-11-30 00:00:00
Tasks: regression, Scheduling, Time Series, Time Series Analysis

In order for clinicians to manage disease progression and make effective
decisions about drug dosage, treatment regimens or scheduling follow up
appointments, it is necessary to be able to identify both short and long-term
trends in repeated biomedical measurements. However, this is complicated by the
fact that these measurements are irregularly sampled and influenced by both
genuine physiological changes and external factors. In their current forms,
existing regression algorithms often do not fulfil all of a clinician's
requirements for identifying short-term events while still being able to
identify long-term trends in disease progression. Therefore, in order to
balance both short term interpretability and long term flexibility, an
extension to broken-stick regression models is proposed in order to make them
more suitable for modelling clinical time series. The proposed probabilistic
broken-stick model can robustly estimate both short-term and long-term trends
simultaneously, while also accommodating the unequal length and irregularly
sampled nature of clinical time series. Moreover, since the model is parametric
and completely generative, its first derivative provides a long-term non-linear
estimate of the annual rate of change in the measurements more reliably than
linear regression. The benefits of the proposed model are illustrated using
estimated glomerular filtration rate as a case study for managing patients with
chronic kidney disease.
Exponential Structure of Income Inequality: Evidence from 67 Countries
Date: 2017-12-16 00:00:00
Tasks: Fairness

Economic competition between humans leads to income inequality, but, so far,
there has been little understanding of underlying quantitative mechanisms
governing such a collective behavior. We analyze datasets of household income
from 67 countries, ranging from Europe to Latin America, North America and
Asia. For all of the countries, we find a surprisingly uniform rule: Income
distribution for the great majority of populations (low and middle income
classes) follows an exponential law. To explain this empirical observation, we
propose a theoretical model within the standard framework of modern economics
and show that free competition and Rawls' fairness are the underlying
mechanisms producing the exponential pattern. The free parameters of the
exponential distribution in our model have an explicit economic interpretation
and direct relevance to policy measures intended to alleviate income
inequality.
Are Chinese transport policies effective? A new perspective from direct pollution rebound effect, and empirical evidence from road transport sector
Date: 2016-10-25 00:00:00
Tasks: Time Series, Time Series Analysis

The air pollution has become a serious challenge in China. Emissions from
motor vehicles have been found as one main source of air pollution. Although
the Chinese government has taken numerous policies to mitigate the harmful
emissions from road transport sector, it is still uncertain for both policy
makers and researchers to know to what extent the policies are effective in the
short and long terms. Inspired by the concept and empirical results from
current literature on energy rebound effect (ERE), we first propose a new
concept of pollution rebound effect (PRE). Then, we estimate direct air PRE as
a measure for the effectiveness of the policies of reducing air pollution from
transport sector based on time-series data from the period 1986-2014. We find
that the short-term direct air PRE is -1.4105, and the corresponding long-run
PRE is -1.246. The negative results indicate that the direct air PRE does not
exist in road passenger transport sector in China, either in the short term or
in the long term during the period 1986-2014. This implies that the Chinese
transport policies are effective in terms of harmful emissions reduction in the
transport sector. This research, to the best of our knowledge, is the first
attempt to quantify the effectiveness of the transport policies in the
transitional China.
China building energy consumption: definitions and measures from an operational perspective
Date: 2016-10-25 00:00:00

There is an increasing awareness of the significance of Chinese building
energy consumption(BEC). However, something worth discussing is that estimate
the building energy consumption adopting the definition of life cycle or
operation. In the existing studies with various evaluation methods, the issue
about the amount of energy consumed by China buildings has not been understood.
In order to settle the disputes over the calculation of BEC, this paper
establish an appropriate accounting method of building energy to present BEC
situation in China and lay the foundation for building energy efficiency.
Adopting the conception of building operational energy consumption, we find
that the energy consumption of buildings just accounts for 15% - 16% of the
final total energy consumption in China; by contrast, the previous calculations
usually have double accounting through top-down approach if central heat-supply
of buildings was given into additional consideration.
The demand for road transport in China: imposing theoretical regularity and flexible functional forms selection
Date: 2016-10-24 00:00:00

Road transport sector is found to be one of the major emitters, and
responsible for serious air pollution and huge pubic health losses. One
important parameter for determining the consequences of transport demand shocks
for the macroeconomy, air pollution and public health is the elasticity of the
demand for transport. Most published studies that use flexible functional forms
have ignored the theoretical regularity conditions implied by microeconomic
theories. Moreover, even a few studies have checked and/or imposed regularity
conditions, most of them equate curvature alone with regularity, thus ignoring
or minimizing the importance of other regularities. And then, the results
appear biased and may in fact be biased. Therefore, we select three of the most
widely used flexible functional forms, the Rotterdam model, the Almost Ideal
Demand System (AIDS), and the quadratic AIDS (QUAIDS) to investigate the demand
for road transport in China using recent annual expenditure data, over a 13
year period from 2002 to 2014, on three expenditure categories in the
transportation sector: private transportation, local transportation and
intercity transportation. Estimation shows that the AIDS model is the only
model that is able to provide theoretically consistent estimates of the
residents demand for road transport in China. Our estimates show that the
private transportation is a luxury among the transportation goods, and is
elastic in price changes relatively. The empirical results imply that the
private and the local transportation, the local and intercity transportation
are gross complements. And, the private transportation is a substitute for the
inter-city transportation, while the intercity transportation is a complement
of the private transportation.
How do Chinese cities grow? A distribution dynamics approach
Date: 2016-10-25 00:00:00

This paper examines the dynamic behavior of city size using a distribution
dynamics approach with Chinese city data for the period 1984-2010. Instead of
convergence, divergence or paralleled growth, multimodality and persistence are
the dominant characteristics in the distribution dynamics of Chinese
prefectural cities. Moreover, initial city size matters, initially small and
medium-sized cities exhibit strong tendency of convergence, while large cities
show significant persistence and multimodality in the sample period.
Examination on the regional city groups shows that locational fundamentals have
important impact on the distribution dynamics of city size.
The distribution dynamics of Carbon Dioxide Emission intensity across Chinese provinces: A weighted Approach
Date: 2016-10-25 00:00:00

This paper examines the distribution dynamics of carbon dioxide (CO2)
emission intensity across 30 Chinese provinces using a weighted distribution
dynamics approach. The results show that CO2 emission intensity tends to
diverge during the sample period of 1995-2014. However, convergence clubs are
found in the ergodic distributions of the full sample and two sub-sample
periods. Divergence, polarization and stratification are the dominant
characteristics in the distribution dynamics. Weightings with economic and
population sizes have important impacts on current distributions and hence long
run steady distributions. Neglecting economic size may under-estimate the
deterioration in the long run steady state. The result also shows that
conditioning on space and income cannot eliminate the multimodality in the long
run distribution. However, capital intensity has important impact on the
formation of convergence clubs. Our findings have contributions in the
understanding of the spatial dynamic behaviours of CO2 emissions across Chinese
provinces, and have important policy implications for CO2 emissions reduction
in China.
Autocatalytic Sets and RNA Secondary Structure
Date: 2017-01-28 00:00:00
Tasks: Diversity

The dominant paradigm in origin of life research is that of an RNA world.
However, despite experimental progress towards the spontaneous formation of
RNA, the RNA world hypothesis still has its problems. Here, we introduce a
novel computational model of chemical reaction networks based on RNA secondary
structure and analyze the existence of autocatalytic sub-networks in random
instances of this model, by combining two well-established computational tools.
Our main results are that (i) autocatalytic sets are highly likely to exist,
even for very small reaction networks and short RNA sequences, and (ii)
sequence diversity seems to be a more important factor in the formation of
autocatalytic sets than sequence length. These findings could shed new light on
the probability of the spontaneous emergence of an RNA world as a network of
mutually collaborative ribozymes.
Hebbian Plasticity for Improving Perceptual Decisions
Date: 2016-12-10 00:00:00

Shibata et al. reported that humans could learn to repeatedly evoke a
stimulus-associated functional magnetic resonance imaging (fMRI) activity
pattern in visual areas V1/V2 through which visual perceptual learning was
achieved without stimulus presentation. Contrary to their attribution of visual
improvements to neuroplasticity in adult V1/V2, our Hebbian learning
interpretation of these data explains the attainment of better perceptual
decisions without plastic V1/V2.
Label Visualization and Exploration in IR
Authors: Alonso Omar
Date: 2016-12-10 00:00:00

There is a renaissance in visual analytics systems for data analysis and
sharing, in particular, in the current wave of big data applications. We
introduce RAVE, a prototype that automates the generation of an interface that
uses facets and visualization techniques for exploring and analyzing relevance
assessments data sets collected via crowdsourcing. We present a technical
description of the main components and demonstrate its use.
Mechanisms of stochastic onset and termination of atrial fibrillation episodes: Insights using a cellular automaton model
Date: 2016-12-11 00:00:00
Tasks: Rhythm

Mathematical models of cardiac electrical excitation are increasingly
complex, with multiscale models seeking to represent and bridge physiological
behaviours across temporal and spatial scales. The increasing complexity of
these models makes it computationally expensive to both evaluate long term (>60
seconds) behaviour and determine sensitivity of model outputs to inputs. This
is particularly relevant in models of atrial fibrillation (AF), where
individual episodes last from seconds to days, and inter-episode waiting times
can be minutes to months. Potential mechanisms of transition between sinus
rhythm and AF have been identified but are not well understood, and it is
difficult to simulate AF for long periods of time using state-of-the-art
models. In this study, we implemented a Moe-type cellular automaton on a novel,
topologically correct surface geometry of the left atrium. We used the model to
simulate stochastic initiation and spontaneous termination of AF, arising from
bursts of spontaneous activation near pulmonary veins. The simplified
representation of atrial electrical activity reduced computational cost, and so
permitted us to investigate AF mechanisms in a probabilistic setting. We
computed large numbers (~10^5) of sample paths of the model, to infer
stochastic initiation and termination rates of AF episodes using different
model parameters. By generating statistical distributions of model outputs, we
demonstrated how to propagate uncertainties of inputs within our microscopic
level model up to a macroscopic level. Lastly, we investigated spontaneous
termination in the model and found a complex dependence on its past AF
trajectory, the mechanism of which merits future investigation.
Do retinal ganglion cells project natural scenes to their principal subspace and whiten them?
Date: 2016-12-11 00:00:00

Several theories of early sensory processing suggest that it whitens sensory
stimuli. Here, we test three key predictions of the whitening theory using
recordings from 152 ganglion cells in salamander retina responding to natural
movies. We confirm the previous finding that firing rates of ganglion cells are
less correlated compared to natural scenes, although significant correlations
remain. We show that while the power spectrum of ganglion cells decays less
steeply than that of natural scenes, it is not completely flattened. Finally,
we find evidence that only the top principal components of the visual stimulus
are transmitted.
A biological model of scabies infection dynamics and treatment explains why mass drug administration does not lead to elimination
Date: 2016-12-12 00:00:00

Despite a low global prevalence, infections with Sarcoptes scabiei, or
scabies, are still common in remote communities such as in northern Australia
and the Solomon Islands. Mass drug administration (MDA) has been utilised in
these communities, and although prevalence drops substantially initially, these
reductions have not been sustained. We develop a compartmental model of scabies
infection dynamics and incorporate both ovicidal and non-ovicidal treatment
regimes. By including the dynamics of mass drug administration, we are able to
reproduce the phenomena of an initial reduction in prevalence, followed by the
recrudescence of infection levels in the population. We show that even under a
`perfect' two-round MDA, eradication of scabies under a non-ovicidal treatment
scheme is almost impossible. We then go on to consider how the probability of
elimination varies with the number of treatment rounds delivered in an MDA. We
find that even with infeasibly large numbers of treatment rounds, elimination
remains challenging.