pwc-archive/papers-with-abstracts huggingface dataset:
Moran-evolution of cooperation: From well-mixed to heterogeneous complex networks
Date: 2018-02-14 00:00:00

Configurational arrangement of network architecture and interaction character
of individuals are two most influential factors on the mechanisms underlying
the evolutionary outcome of cooperation, which is explained by the
well-established framework of evolutionary game theory. In the current study,
not only qualitatively but also quantitatively, we measure Moran-evolution of
cooperation to support an analytical agreement based on the consequences of the
replicator equation in a finite population. The validity of the measurement has
been double-checked in the well-mixed network by the Langevin stochastic
differential equation and the Gillespie-algorithmic version of Moran-evolution,
while in a structured network, the measurement of accuracy is verified by the
standard numerical simulation. Considering the Birth-Death and Death-Birth
updating rules through diffusion of individuals, the investigation is carried
out in the wide range of game environments those relate to the various social
dilemmas where we are able to draw a new rigorous mathematical track to tackle
the heterogeneity of complex networks. The set of modified criteria reveals the
exact fact about the emergence and maintenance of cooperation in the structured
population. We find that in general, nature promotes the environment of
coexistent traits.
On the binomial approximation of the American put
Date: 2018-12-11 00:00:00

We consider the binomial approximation of the American put price in the
Black-Scholes model (with continuous dividend yield). Our main result is that
the error of approximation is $O((ln n) $\alpha$ /n)$ where n is the number of
time periods and the exponent $\alpha$ is a positive number, the value of which
may differ according to the respective levels of the interest rate and the
dividend yield.
Optimal launch states for the measurement of principal modes in optical fibers
Date: 2018-07-26 00:00:00

Modal dispersion characterization of multimode optical fibers can be
performed using the recently-proposed mode-dependent signal delay method. This
method consists of sending optical pulses using different combinations of modes
though the multimode optical fiber and measuring the mode group delay at the
fiber output. From these measurements, it is possible to estimate the modal
dispersion vector, the principal modes, and their corresponding differential
mode group delays. In this paper, we revise and extend the theoretical
framework of the mode-dependent signal delay method to include the impact of
receiver noise and mode-dependent loss. We compute optimal launch modes,
minimizing the noise error in the estimation of the fiber modal dispersion
vector. We show that, for a 40-mode fiber, the electronic signal-to-noise ratio
(SNR) is improved asymptotically by almost 6 dB compared to conventional mode
combinations.
4D blood flow mapping using SPIM-microPIV in the developing zebrafish heart
Date: 2018-02-15 00:00:00

Fluid-structure interaction in the developing heart is an active area of
research in developmental biology. However, investigation of heart dynamics is
mostly limited to computational fluid dynamics simulations using heart wall
structure information only, or single plane blood flow information - so there
is a need for 3D + time resolved data to fully understand cardiac function. We
present an imaging platform combining selective plane illumination microscopy
(SPIM) with micro particle image velocimetry ({\textmu}PIV) to enable
3D-resolved flow mapping in a microscopic environment, free from many of the
sources of error and bias present in traditional epifluorescence-based
{\textmu}PIV systems. By using our new system in conjunction with optical heart
beat synchronisation, we demonstrte the ability obtain non-invasive 3D + time
resolved blood flow measurements in the heart of a living zebrafish embryo.
Persistence-infectivity trade-offs in environmentally transmitted pathogens change population-level disease dynamics
Date: 2018-02-15 00:00:00

Human pathogens transmitted through environmental pathways are subject to
stress and pressures outside of the host. These pressures may cause pathogen
pathovars to diverge in their environmental persistence and their infectivity
on an evolutionary time-scale. On a shorter time-scale, a single-genotype
pathogen population may display wide variation in persistence times and exhibit
biphasic decay. Using an infectious disease transmission modeling framework, we
demonstrate in both cases that fitness-preserving trade-offs have implications
for the dynamics of associated epidemics: less infectious, more persistent
pathogens cause epidemics to progress more slowly than more infectious, less
persistent (labile) pathogens, even when the overall risk is the same. Using
identifiability analysis, we show that the usual disease surveillance data does
not sufficiently inform these underlying pathogen population dynamics, even
with basic environmental monitoring. These results suggest directions for
future microbial research and environmental monitoring. In particular,
determining the relative infectivity of persistent pathogen subpopulations and
the rates of phenotypic conversion will help ascertain how much disease risk is
associated with the long tails of biphasic decay. Alternatively, risk can be
indirectly ascertained by developing methods to separately monitor labile and
persistent subpopulations. A better understanding of persistence--infectivity
trade-offs and associated dynamics can improve risk assessment and disease
control strategies.
Imaging the Developing Heart: Synchronized Timelapse Microscopy During Developmental Changes
Date: 2018-02-15 00:00:00

How do you use imaging to analyse the development of the heart, which not
only changes shape but also undergoes constant, high-speed, quasi-periodic
changes? We have integrated ideas from prospective and retrospective optical
gating to capture long-term, phase-locked developmental time-lapse videos. In
this paper we demonstrate the success of this approach over a key developmental
time period: heart looping, where large changes in heart shape prevent previous
prospective gating approaches from capturing phase-locked videos. We use the
comparison with other approaches to in vivo heart imaging to highlight the
importance of collecting the most appropriate data for the biological question.
Development of Highly Efficient Multi-invariable Wireless Sensor System Design for Energy Harvesting
Date: 2018-02-15 00:00:00
Tasks: Management

Capillary wireless sensor networks devoted to air quality monitoring have
provided vital information on dangerous air conditions. In adopting the
environmentally generated energy as the fundamental energy source the main
challenge is the implementation of capillary networks rather than replacing the
batteries on a set period of times that leads to functional dilemma of devices
management and high costs. In this paper we present a battery-less,
self-governing, multi-parametric sensing platform for air quality monitoring
that harvests environment energy for long run. Furthermore study on sensor
section with their results have also been described in the paper. A customized
process of calibration to check the sensors' sensitivity and a basic portfolio
of variant energy sources over the power recovery section could productively
improve air quality standards tracing in indoor and outdoor application, in a
kind of 'set and forget' scenario.
Growth tradeoffs produce complex microbial communities on a single limiting resource
Date: 2018-05-31 00:00:00

The relationship between the dynamics of a community and its constituent
pairwise interactions is a fundamental problem in ecology. Higher-order
ecological effects beyond pairwise interactions may be key to complex
ecosystems, but mechanisms to produce these effects remain poorly understood.
Here we show that higher-order effects can arise from variation in multiple
microbial growth traits, such as lag times and growth rates, on a single
limiting resource with no other interactions. These effects produce a range of
ecological phenomena: an unlimited number of strains can exhibit multistability
and neutral coexistence, potentially with a single keystone strain; strains
that coexist in pairs do not coexist all together; and the champion of all
pairwise competitions may not dominate in a mixed community. Since variation in
multiple growth traits is ubiquitous in microbial populations due to pleiotropy
and non-genetic variation, our results indicate these higher-order effects may
also be widespread, especially in laboratory ecology and evolution experiments.
Numerical simulation of BOD5 dynamics in Igap\'o I lake, Londrina, Paran\'a, Brazil: Experimental measurement and mathematical modeling
Date: 2018-02-15 00:00:00

The concentration of biochemical oxygen demand, BOD5, was studied in order to
evaluate the water quality of the Igap\'o I Lake, in Londrina, Paran\'a State,
Brazil. The simulation was conducted by means of the discretization in
curvilinear coordinates of the geometry of Igap\'o I Lake, together with finite
difference and finite element methods. The evaluation of the proposed numerical
model for water quality was performed by comparing the experimental values of
BOD5 with the numerical results. The evaluation of the model showed
quantitative results compatible with the actual behavior of Igap\'o I Lake in
relation to the simulated parameter. The qualitative analysis of the numerical
simulations provided a better understanding of the dynamics of the BOD5
concentration at Igap\'o I Lake, showing that such concentrations in the
central regions of the lake have values above those allowed by Brazilian law.
The results can help to guide choices by public officials, as: (i) improve the
identification mechanisms of pollutant emitters on Lake Igap\'o I, (ii)
contribute to the optimal treatment of the recovery of the polluted environment
and (iii) provide a better quality of life for the regulars of the lake as well
as for the residents living on the lakeside.
Phonemic evidence reveals interwoven evolution of Chinese dialects
Date: 2018-02-16 00:00:00
Tasks: Diversity

Han Chinese experienced substantial population migrations and admixture in
history, yet little is known about the evolutionary process of Chinese
dialects. Here, we used phylogenetic approaches and admixture inference to
explicitly decompose the underlying structure of the diversity of Chinese
dialects, based on the total phoneme inventories of 140 dialect samples from
seven traditional dialect groups: Mandarin, Wu, Xiang, Gan, Hakka, Min and Yue.
We found a north-south gradient of phonemic differences in Chinese dialects
induced from historical population migrations. We also quantified extensive
horizontal language transfers among these dialects, corresponding to the
complicated socio-genetic history in China. We finally identified that the
middle latitude dialects of Xiang, Gan and Hakka were formed by admixture with
other four dialects. Accordingly, the middle-latitude areas in China were a
linguistic melting pot of northern and southern Han populations. Our study
provides a detailed phylogenetic and historical context against family-tree
model in China.
Algorithmic Complexity and Reprogrammability of Chemical Structure Networks
Date: 2018-03-18 00:00:00

Here we address the challenge of profiling causal properties and tracking the
transformation of chemical compounds from an algorithmic perspective. We
explore the potential of applying a computational interventional calculus based
on the principles of algorithmic probability to chemical structure networks. We
profile the sensitivity of the elements and covalent bonds in a chemical
structure network algorithmically, asking whether reprogrammability affords
information about thermodynamic and chemical processes involved in the
transformation of different compound classes. We arrive at numerical results
suggesting a correspondence between some physical, structural and functional
properties. Our methods are capable of separating chemical classes that reflect
functional and natural differences without considering any information about
atomic and molecular properties. We conclude that these methods, with their
links to chemoinformatics via algorithmic, probability hold promise for future
research.
The dynamic impact of monetary policy on regional housing prices in the US: Evidence based on factor-augmented vector autoregressions
Date: 2018-02-16 00:00:00

In this study interest centers on regional differences in the response of
housing prices to monetary policy shocks in the US. We address this issue by
analyzing monthly home price data for metropolitan regions using a
factor-augmented vector autoregression (FAVAR) model. Bayesian model estimation
is based on Gibbs sampling with Normal-Gamma shrinkage priors for the
autoregressive coefficients and factor loadings, while monetary policy shocks
are identified using high-frequency surprises around policy announcements as
external instruments. The empirical results indicate that monetary policy
actions typically have sizeable and significant positive effects on regional
housing prices, revealing differences in magnitude and duration. The largest
effects are observed in regions located in states on both the East and West
Coasts, notably California, Arizona and Florida.
Dealing with Uncertainties in User Feedback: Strategies Between Denying and Accepting
Authors: Jasberg Kevin, Sizov Sergej
Date: 2018-02-16 00:00:00
Tasks: Two-sample testing

Latest research revealed a considerable lack of reliability within user
feedback and discussed striking impacts for the assessment of adaptive web
systems and content personalisation approaches, e.g. ranking errors, systematic
biases to accuracy metrics as well as its natural offset (the magic barrier).
In order to perform holistic assessments and to improve web systems, a variety
of strategies have been proposed to deal with this so-called human uncertainty.
In this contribution we discuss the most relevant strategies to handle
uncertain feedback and demonstrate that these approaches are more or less
ineffective to fulfil their objectives. In doing so, we consider human
uncertainty within a purely probabilistic framework and utilise hypothesis
testing as well as a generalisation of the magic barrier to compare the effects
of recently proposed algorithms. On this basis we recommend a novel strategy of
acceptance which turns away from mere filtering and discuss potential benefits
for the community of the WWW.
Degradation rate uniformity determines success of oscillations in repressive feedback regulatory networks
Date: 2018-02-16 00:00:00

Ring oscillators are biochemical circuits consisting of a ring of
interactions capable of sustained oscillations. The non-linear interactions
between genes hinder the analytical insight into their function, usually
requiring computational exploration. Here we show that, despite the apparent
complexity, the stability of the unique steady state in an incoherent feedback
ring depends only on the degradation rates and a single parameter summarizing
the feedback of the circuit. Concretely, we show that the range of regulatory
parameters that yield oscillatory behaviour, is maximized when the degradation
rates are equal. Strikingly, this results holds independently of the regulatory
functions used or number of genes. We also derive properties of the
oscillations as a function of the degradation rates and number of nodes forming
the ring. Finally, we explore the role of mRNA dynamics by applying the generic
results to the specific case with two naturally different degradation time
scales
Analysis of Schema.org Usage in the Tourism Domain
Authors: Balcı Boran Taylan, Şimşek Umutcan, Kärle Elias, Fensel Dieter
Date: 2018-02-16 00:00:00

Schema.org is an initiative founded in 2011 by the four-big search engine
Bing, Google, Yahoo!, and Yandex. The goal of the initiative is to publish and
maintain the schema.org vocabulary, in order to facilitate the publication of
structured data on the web which can enable the implementation of automated
agents like intelligent personal assistants and chatbots. In this paper, the
usage of schema.org in tourism domain between years 2013 and 2016 is analysed.
The analysis shows the adoption of schema.org, which indicates how well the
tourism sector is prepared for the web that targets automated agents. The
results have shown that the adoption of schema.org type and properties is grown
over the years. While the US is dominating the annotation numbers, a drastic
drop is observed for the proportion of the US in 2016. Poorly rated businesses
are encountered more in 2016 results in comparison to previous years.
Grant-less Uplink Transmission for LTE Operated in Unlicensed Spectrum
Date: 2018-02-14 00:00:00

Deployment of Long Term Evolution (LTE) in unlicensed spectrum has been a
candidate feature to meet the explosive growth of traffic demand since 3GPP
release 13. To further explore the advantage of unlicensed bands, in this
context the operation of both uplink and downlink has been supported and
studied in the subsequent releases. However, it has been identified that
scheduled uplink transmission performance in unlicensed spectrum is
significantly degraded due to the double listen-before-talk (LBT) requirements
at both eNB when sending the uplink grant, and at the scheduled UEs before
transmission. In this paper, in order to overcome this issue, a novel uplink
transmission scheme, which does not require any grant, is proposed, and the
details regarding the system design are provided. By modeling the dynamics in
time of the LBT for both a system that employs a conventional uplink scheme, as
well as the proposed scheme, it is verified through analytical evaluation that
the double LBT scheme for uplink transmission greatly reduces the channel
access probability for the UE, and leads consequently to performance loss,
while the proposed scheme is able to alleviate this issue. System level
simulation results, compliant with the LTE standard, show that the proposed
scheme can achieve a significant performance gain in terms of throughput with
negligible performance loss for the downlink, and other technologies operating
in the same spectrum.
Enhancement of Noisy Speech Exploiting an Exponential Model Based Threshold and a Custom Thresholding Function in Perceptual Wavelet Packet Domain
Date: 2018-02-15 00:00:00
Tasks: Speech Enhancement

For enhancement of noisy speech, a method of threshold determination based on
modeling of Teager energy (TE) operated perceptual wavelet packet (PWP)
coefficients of the noisy speech by exponential distribution is presented. A
custom thresholding function based on the combination of mu-law and semisoft
thresholding functions is designed and exploited to apply the statistically
derived threshold upon the PWP coefficients. The effectiveness of the proposed
method is evaluated for car and multi-talker babble noise corrupted speech
signals through performing extensive simulations using the NOIZEUS database.
The proposed method outperforms some of the state-of-the-art speech enhancement
methods both at high and low levels of SNRs in terms of the standard objective
measures and the subjective evaluations including formal listening tests.
Residual-Based Detections and Unified Architecture for Massive MIMO Uplink
Date: 2018-02-15 00:00:00

Massive multiple-input multiple-output (M-MIMO) technique brings better
energy efficiency and coverage but higher computational complexity than
small-scale MIMO. For linear detections such as minimum mean square error
(MMSE), prohibitive complexity lies in solving large-scale linear equations.
For a better trade-off between bit-error-rate (BER) performance and
computational complexity, iterative linear algorithms like conjugate gradient
(CG) have been applied and have shown their feasibility in recent years. In
this paper, residual-based detection (RBD) algorithms are proposed for M-MIMO
detection, including minimal residual (MINRES) algorithm, generalized minimal
residual (GMRES) algorithm, and conjugate residual (CR) algorithm. RBD
algorithms focus on the minimization of residual norm per iteration, whereas
most existing algorithms focus on the approximation of exact signal. Numerical
results have shown that, for $64$-QAM $128\times 8$ MIMO, RBD algorithms are
only $0.13$ dB away from the exact matrix inversion method when BER$=10^{-4}$.
Stability of RBD algorithms has also been verified in various correlation
conditions. Complexity comparison has shown that, CR algorithm require $87\%$
less complexity than the traditional method for $128\times 60$ MIMO. The
unified hardware architecture is proposed with flexibility, which guarantees a
low-complexity implementation for a family of RBD M-MIMO detectors.
Effect of rainfall and fire frequency on tree--grass dynamics: Capturing the forest--savanna distributions along biogeographic gradients
Date: 2018-02-15 00:00:00

In this work, we improve a previous minimalistic tree-grass savanna model by
taking into account water availability, in addition to fire, since both factors
are known to be important for shaping savanna physiognomies along a climatic
gradient. As in our previous models, we consider two nonlinear functions of
grass and tree biomasses to respectively take into account grass-fire
feedbacks, and the response of trees to fire of a given intensity. The novelty
is that rainfall is taken into account in the tree and grass growth functions
and in the biomass carrying capacities. Then, we derive a qualitative analysis
of the ODE model, showing existence of equilibria, and studying their stability
conditions. We also construct a two dimension bifurcation diagram based on
rainfall and fire frequency. This led to summarize different scenarios for the
model including multi-stabilities that are proven possible. Next, to bring more
realism in the model, pulsed fire events are modelled as part of an IDE
(Impulsive differential Equations) system analogous to the ODE system.
Numerical simulations are provided and we discuss some important ecological
outcomes that our ODE and IDE models are able to predict. Notably, the
expansion of forest into tree-poor physiognomies (grassland and savanna) is
systematically predicted when fire return period increases, especially in mesic
and humid climatic areas.
Kinetic Theory for Finance Brownian Motion from Microscopic Dynamics
Date: 2018-02-16 00:00:00

Recent technological development has enabled researchers to study social
phenomena scientifically in detail and financial markets has particularly
attracted physicists since the Brownian motion has played the key role as in
physics. In our previous report (arXiv:1703.06739; to appear in Phys. Rev.
Lett.), we have presented a microscopic model of trend-following high-frequency
traders (HFTs) and its theoretical relation to the dynamics of financial
Brownian motion, directly supported by a data analysis of tracking trajectories
of individual HFTs in a financial market. Here we show the mathematical
foundation for the HFT model paralleling to the traditional kinetic theory in
statistical physics. We first derive the time-evolution equation for the
phase-space distribution for the HFT model exactly, which corresponds to the
Liouville equation in conventional analytical mechanics. By a systematic
reduction of the Liouville equation for the HFT model, the
Bogoliubov-Born-Green-Kirkwood-Yvon hierarchal equations are derived for
financial Brownian motion. We then derive the Boltzmann-like and Langevin-like
equations for the order-book and the price dynamics by making the assumption of
molecular chaos. The qualitative behavior of the model is asymptotically
studied by solving the Boltzmann-like and Langevin-like equations for the large
number of HFTs, which is numerically validated through the Monte-Carlo
simulation. Our kinetic description highlights the parallel mathematical
structure between the financial Brownian motion and the physical Brownian
motion.