pwc-archive/papers-with-abstracts huggingface dataset:
On the modelling of multivariate counts with Cox processes and dependent shot noise intensities
Authors: Benjamin Avanzi, Gregory Clive Taylor, Bernard Wong, Xinda Yang
Date: 2020-04-23 00:00:00

In this paper, we develop a method to model and estimate several, _dependent_ count processes, using granular data. Specifically, we develop a multivariate Cox process with shot noise intensities to jointly model the arrival process of counts (e.g. insurance claims). The dependency structure is introduced via multivariate shot noise _intensity_ processes which are connected with the help of L\'evy copulas. In aggregate, our approach allows for (i) over-dispersion and auto-correlation within each line of business; (ii) realistic features involving time-varying, known covariates; and (iii) parsimonious dependence between processes without requiring simultaneous primary (e.g. accidents) events. The explicit incorporation of time-varying, known covariates can accommodate characteristics of real data and hence facilitate implementation in practice. In an insurance context, these could be changes in policy volumes over time, as well as seasonality patterns and trends, which may explain some of the relationship (dependence) between multiple claims processes, or at least help tease out those relationships. Finally, we develop a filtering algorithm based on the reversible-jump Markov Chain Monte Carlo (RJMCMC) method to estimate the latent stochastic intensities and illustrate model calibration using real data from the AUSI data set.
The Category of Node-and-Choice Extensive-Form Games
Date: 2020-07-28 00:00:00
Tasks: Form

This paper develops the category $\mathbf{NCG}$. Its objects are
node-and-choice games, which include essentially all extensive-form games. Its
morphisms allow arbitrary transformations of a game's nodes, choices, and
players, as well as monotonic transformations of the utility functions of the
game's players. Among the morphisms are subgame inclusions. Several
characterizations and numerous properties of the isomorphisms are derived. For
example, it is shown that isomorphisms preserve the game-theoretic concepts of
no-absentmindedness, perfect-information, and (pure-strategy) Nash-equilibrium.
Finally, full subcategories are defined for choice-sequence games and
choice-set games, and relationships among these two subcategories and
$\mathbf{NCG}$ itself are expressed and derived via isomorphic inclusions and
equivalences.
Performance Analysis of Uplink NOMA-Relevant Strategy Under Statistical Delay QoS Constraints
Date: 2020-04-23 00:00:00

A new multiple access (MA) strategy, referred to as non orthogonal multiple
access - Relevant (NOMA-R), allows selecting NOMA when this increases all
individual rates, i.e., it is beneficial for both strong(er) and weak(er)
individual users. This letter provides a performance analysis of the NOMA-R
strategy in uplink networks with statistical delay constraints. Closed-form
expressions of the effective capacity (EC) are provided in two-users networks,
showing that the strong user always achieves a higher EC with NOMA-R. Regarding
the network's sum EC, there are distinctive gains with NOMA-R, particularly
under stringent delay constraints.
Maternal education and offspring birthweight for gestational age: the mediating effect of smoking during pregnancy
Date: 2020-04-22 00:00:00

Background Small for gestational age (SGA) birthweight, a risk factor of
infant mortality and delayed child development, is associated with maternal
educational attainment. Maternal tobacco smoking during pregnancy could
contribute to this association. We aimed to quantify the contribution of
maternal smoking during pregnancy to social inequalities in child birthweight
for gestational age (GA). Methods Data come from the French nation-wide ELFE
cohort study, which included 17,155 singletons. Birthweights for GA were
calculated using z-scores. Associations between maternal educational
attainment, tobacco smoking during pregnancy and child birthweight for GA were
ascertained using mediation analysis. Mediation analyses were also stratified
by maternal pre-pregnancy body mass index.Results Low maternal educational
attainment was associated with an increased odd of tobacco smoking during
pregnancy (adjusted OR (ORa)=2.58 [95% CI 2.34, 2.84]) as well as a decrease in
child birthweight for GA (RRa=0.94 [95% 0.91, 0.98]). Tobacco smoking during
pregnancy was associated with a decrease in offspring birthweight for GA
(RRa=0.73 [95% CI 0.70, 0.76]). Mediation analysis suggests that 39% of the
effect of low maternal educational attainment on offspring birthweight for GA
was mediated by smoking during pregnancy. A more important direct effect of
maternal educational attainment on child birthweight for GA was observed among
underweight women (RRa=0.82 [95%CI 0.72, 0.93]).Conclusions The relationship
between maternal educational attainment and child birthweight for GA is
strongly mediated by smoking during pregnancy. Reducing maternal smoking could
lessen the occurrence of infant SGA and decrease socioeconomic inequalities in
birthweight for GA.Keywords Birthweight, educational attainment, tobacco
smoking, pregnancy, mediation analysis, health inequalities
Partner support during pregnancy mediates social inequalities in maternal postpartum depression for non-migrant and first generation migrant women
Date: 2020-04-22 00:00:00
Tasks: Epidemiology

Background An advantaged socioeconomic position (SEP) and satisfying social
support during pregnancy (SSP) have been found to be protective factors of
maternal postpartum depression (PDD). An advantaged SEP is also associated with
satisfying SSP, making SSP a potential mediator of social inequalities in PPD.
SEP, SSP and PPD are associated with migrant status. The aim of this study was
to quantify the mediating role of SSP in social inequalities in PPD regarding
mother's migrant status. Methods A sub-sample of 15,000 mothers from the French
nationally-representative ELFE cohort study was used for the present analyses.
SEP was constructed as a latent variable measured with educational attainment,
occupational grade, employment, financial difficulties and household income.
SSP was characterized as perceived support from partner (good relation,
satisfying support and paternal leave) and actual support from midwives
(psychosocial risk factors assessment and antenatal education). Mediation
analyses with multiple mediators, stratified by migrant status were conducted.
Results Study population included 76% of non-migrant women, 12% of second and
12% of first generation migrant. SEP was positively associated with support
from partner, regardless of migrant status. Satisfying partner support was
associated with a 8 (non-migrant women) to 11% (first generation migrant women)
reduction in PPD score. Limitations History of depression was not
reported.Conclusions Partner support could reduce social inequalities in PPD.
This work supports the need of interventions, longitudinal and qualitative
studies including fathers and adapted to women at risk of PPD to better
understand the role of SSP in social inequalities in PPD. Keywords social
support, postpartum depression, epidemiology, social inequalities, pregnancy,
mediation analysis
Fractional-order susceptible-infected model: definition and applications to the study of COVID-19 main protease
Authors: Luciano Abadias, Gissell Estrada-Rodriguez, Ernesto Estrada
Date: 2020-04-23 00:00:00

We propose a model for the transmission of perturbations across the amino acids of a protein represented as an interaction network. The dynamics consists of a Susceptible-Infected (SI) model based on the Caputo fractional-order derivative. We find an upper bound to the analytical solution of this model which represents the worse-case scenario on the propagation of perturbations across a protein residue network. This upper bound is expressed in terms of Mittag-Leffler functions of the adjacency matrix of the network of inter-amino acids interactions. We then apply this model to the analysis of the propagation of perturbations produced by inhibitors of the main protease of SARS CoV-2. We find that the perturbations produced by strong inhibitors of the protease are propagated far away from the binding site, confirming the long-range nature of intra-protein communication. On the contrary, the weakest inhibitors only transmit their perturbations across a close environment around the binding site. These findings may help to the design of drug candidates against this new coronavirus.
On the multiplicity of the martingale condition: Spontaneous symmetry breaking in Quantum Finance
Authors: Ivan Arraut, Alan Au, Alan Ching-biu Tse
Date: 2020-04-18 00:00:00

We demonstrate that the martingale condition in the stock market can be interpreted as a vacuum condition when we express the financial equations in the Hamiltonian form. We then show that the symmetry under the changes of the prices is spontaneously broken in general and the symmetry under changes in the volatility, for the case of the Merton-Garman (MG) equation, is also spontaneously broken. This reproduces a vacuum degeneracy for the system. In this way, we find the conditions under which, the martingale condition can be considered to be a non-degenerate vacuum. This gives us a surprising connection between spontaneous symmetry breaking and the flow of information through the boundaries for the financial systems. Subsequently, we find an extended martingale condition for the MG equation, depending not only prices but also on the volatility and finally, we show what happens if we include additional non-derivative terms on the Black Scholes and on the MG equations, breaking then some other symmetries of the system spontaneously.
Estimating the Demand Factors and Willingness to Pay for Agricultural Insurance
Authors: Osman Gulseven
Date: 2020-03-12 00:00:00

This article investigates the effect of prices and socio-demographic variables on the farmers decision to purchase agricultural insurance. A survey has been conducted to 200 farmers most of whom are engaged in diversified income-generating activities. The logistic estimation results suggest that education and household income from farming activities positively affect the likelihood of purchasing insurance. The demand for insurance is negatively correlated with the premium paid per insured value, suggesting that insurance is a normal good. Farmers are willing to pay (WTP) increasingly higher premiums for contracts with a higher coverage ratio. According to the valuation model, the WTP declines sharply for coverage ratios under 70%.
Sparse Convolutional Beamforming for 3D Ultrafast Ultrasound Imaging
Date: 2020-04-23 00:00:00

Real-time three dimensional (3D) ultrasound provides complete visualization
of inner body organs and blood vasculature, which is crucial for diagnosis and
treatment of diverse diseases. However, 3D systems require massive hardware due
to the huge number of transducer elements and consequent data size. This
increases cost significantly and limits both frame rate and image quality, thus
preventing 3D ultrasound from being common practice in clinics worldwide. A
recent study proposed a technique, called convolutional beamforming algorithm
(COBA), which obtains improved image quality while allowing notable element
reduction. COBA was developed and tested for 2D focused imaging using full and
sparse arrays. The later was referred to as sparse COBA (SCOBA). In this paper,
we build upon previous work and introduce a nonlinear beamformer for 3D
imaging, called COBA-3D, consisting of 2D spatial convolution of the in-phase
and quadrature received signals. The proposed technique considers
diverging-wave transmission, thus, achieves improved image resolution and
contrast compared with standard delay-and-sum beamforming, while enabling high
frame rate. Incorporating 2D sparse arrays into our method creates SCOBA-3D: a
sparse beamformer which offers significant element reduction and thus allows to
perform 3D imaging with the resources typically available for 2D setups. To
create 2D thinned arrays, we present a scalable and systematic way to design 2D
fractal sparse arrays. The proposed framework paves the way for affordable
ultrafast ultrasound devices that perform high-quality 3D imaging, as
demonstrated using phantom and ex-vivo data.
Assessment of Practical Smart Gateway Diversity Based on Multi-Site Measurements in Q/V band
Date: 2020-04-23 00:00:00
Tasks: Diversity

Next generations of High Throughput Satellite (HTS) systems operating a Q/V
band network of gateways (GWs) for the feeder link, need to apply some form of
Smart Gateway Diversity (SGD) to ensure they meet the demanding availability
targets. However, most of the published research on SGD usually resorts to
ideal assumptions that are not realistic for an operational system. To evaluate
in more depth the performance of practical SGD, this paper exploits for the
first time multi-site propagation measurements for a network of six measurement
sites (GWs) at 40 GHz. Based on this, it studies the performance of SGD in
terms of feeder availability and number of switches between GWs taking into
account the climatic region, the switching processing delay, the clustering of
GWs, and the impact of downlink versus uplink frequency in Q/V band. Along the
course, the interplay between propagation aspects and SGD operational aspects
is highlighted.
Lockhart with a twist: modelling cellulose microfibril deposition and reorientation reveals twisting plant cell growth mechanisms
Authors: Jeevanjyoti Chakraborty, Jingxi Luo, Rosemary J Dyson
Date: 2020-04-23 00:00:00

Plant morphology emerges from cellular growth and structure. The turgor-driven diffuse growth of a cell can be highly anisotropic: significant longitudinally and negligible radially. Such anisotropy is ensured by cellulose microfibrils (CMF) reinforcing the cell wall in the hoop direction. To maintain the cell's integrity during growth, new wall material including CMF must be continually deposited. We develop a mathematical model representing the cell as a cylindrical pressure vessel and the cell wall as a fibre-reinforced viscous sheet, explicitly including the mechano-sensitive angle of CMF deposition. The model incorporates interactions between turgor, external forces, CMF reorientation during wall extension, and matrix stiffening. Using the model, we reinterpret some recent experimental findings, and reexamine the popular hypothesis of CMF/microtubule alignment. We explore how the handedness of twisting cell growth depends on external torque and intrinsic wall properties, and find that cells twist left-handedly `by default' in some suitable sense. Overall, this study provides a unified mechanical framework for understanding left- and right-handed twist-growth as seen in many plants.
Mathematical and Preclinical Investigation of Respiratory Sinus Arrhythmia Effects on Cardiac Output
Authors: Sahar Rahbar
Date: 2020-04-23 00:00:00
Tasks: Heart Rate Variability

Respiratory sinus arrhythmia (RSA) is heart rate variability in synchrony with respiration although its functional significance not clear. The loss of sinus arrhythmia may indicate underlying heart failure or disease; therefore, there would be a great advantage of knowing how it works and affects the cardio-respiratory system, especially by providing a mathematical model. To this end, Windkessel model and cardiovascular partial differential equations are used to obtain cardiac output based on the elasticity of left ventricle, which is related to RSA. By solving the corresponding equations, it would be possible to propose a new model to predict the RSA effects on cardiac output.
Modelos SIR modificados para la evoluci\'on del COVID19
Date: 2020-04-23 00:00:00
Tasks: Unity

We study the SIR epidemiological model, with a variable contagion rate,
applied to the evolution of COVID19 in Cuba. It is highlighted that an increase
in the predictive character depends on understanding the dynamics for the
temporal evolution of the rate of contagion $\beta^*$. A semi-empirical model
for this dynamics is formulated, where reaching $\beta^*\approx0$ due to
isolation is achieved after the mean duration of the disease $\tau=1/\gamma$,
in which the number of infected in the confined families has decreased. It is
considered that $\beta^*(t)$ should have an abrupt decrease on the day of
initiation of confinement and decrease until canceling at the end of the
interval $\tau$. The analysis describes appropriately the infection curve for
Germany. The model is applied to predict an infection curve for Cuba, which
estimates a maximum number of infected as less than 2000 in the middle of May,
depending on the rigor of the isolation. This is suggested by the ratio between
the daily detected cases and the total. We consider the ratio between the
observed and real infected cases (k) less than unity. The low value of k
decreases the maximum obtained when $\beta^*-\gamma>0$. The observed evolution
is independent of k in the linear region. The value of $\beta^*$ is also
studied by time intervals, adjusting to the data of Cuba, Germany and South
Korea. We compare the extrapolation of the evolution of Cuba with the contagion
rate until 16.04.20 with that obtained by a strict quarantine at the end of
April. This model with variable $\beta^*$ correctly describes the observed
infected evolution curves. We emphasize that the desired maximum of the SIR
infected curve is not the maximum standard with constant $\beta^*$, but one
achieved due to quarantine when $\tilde R_0=\beta^*/\gamma<1$. For the
countries controlling the epidemic the maxima are in the region in which SIR
equations are linear.
Rotated spectral principal component analysis (rsPCA) for identifying dynamical modes of variability in climate systems
Date: 2020-04-23 00:00:00
Tasks: Diagnostic, Time Series Analysis

Spectral PCA (sPCA), in contrast to classical PCA, offers the advantage of
identifying organized spatio-temporal patterns within specific frequency bands
and extracting dynamical modes. However, the unavoidable tradeoff between
frequency resolution and robustness of the PCs leads to high sensitivity to
noise and overfitting, which limits the interpretation of the sPCA results. We
propose herein a simple non-parametric implementation of the sPCA using the
continuous analytic Morlet wavelet as a robust estimator of the cross-spectral
matrices with good frequency resolution. To improve the interpretability of the
results when several modes of similar amplitude exist within the same frequency
band, we propose a rotation of eigenvectors that optimizes the spatial
smoothness in the phase domain. The developed method, called rotated spectral
PCA (rsPCA), is tested on synthetic data simulating propagating waves and shows
impressive performance even with high levels of noise in the data. Applied to
historical sea surface temperature (SST) time series over the Pacific Ocean,
the method accurately captures the El Ni\~{n}o-Southern Oscillation (ENSO) at
low frequency (2 to 7 years periodicity). At high frequencies (sub-annual
periodicity), at which several extratropical patterns of similar amplitude are
identified, the rsPCA successfully unmixes the underlying modes, revealing
spatially coherent patterns with robust propagation dynamics. Identification of
higher frequency space-time climate modes holds promise for seasonal to
subseasonal prediction and for diagnostic analysis of climate models.
Does Subjective Well-being Contribute to Our Understanding of Mexican Well-being?
Date: 2020-04-23 00:00:00
Tasks: Descriptive, Econometrics

The article reviews the history of well-being to gauge how subjective
question surveys can improve our understanding of well-being in Mexico. The
research uses data at the level of the 32 federal entities or States, taking
advantage of the heterogeneity in development indicator readings between and
within geographical areas, the product of socioeconomic inequality. The data
come principally from two innovative subjective questionnaires, BIARE and
ENVIPE, which intersect in their fully representative state-wide applications
in 2014, but also from conventional objective indicator sources such as the HDI
and conventional surveys. This study uses two approaches, a descriptive
analysis of a state-by-state landscape of indicators, both subjective and
objective, in an initial search for stand-out well-being patterns, and an
econometric study of a large selection of mainly subjective indicators inspired
by theory and the findings of previous Mexican research. Descriptive analysis
confirms that subjective well-being correlates strongly with and complements
objective data, providing interesting directions for analysis. The econometrics
literature indicates that happiness increases with income and satisfying of
material needs as theory suggests, but also that Mexicans are relatively happy
considering their mediocre incomes and high levels of insecurity, the last of
which, by categorizing according to satisfaction with life, can be shown to
impact poorer people disproportionately. The article suggests that well-being
is a complex, multidimensional construct which can be revealed by using
exploratory multi-regression and partial correlations models which juxtapose
subjective and objective indicators.
StochaLM: a Stochastic alternate Linearization Method for distributed optimization
Authors: Inês Almeida, João Xavier
Date: 2020-04-23 00:00:00
Tasks: Distributed Optimization, Federated Learning

We present the Stochastic alternate Linearization Method (StochaLM), a token-based method for distributed optimization. This algorithm finds the solution of a consensus optimization problem by solving a sequence of subproblems where some components of the cost are linearized around specific anchor points. StochaLM can be interpreted as a dual block coordinate ascent method whose block components are selected using the state of an ergodic Markov chain. This sampling process is neither essentially cyclic nor independent over time, preventing us from using proofs of convergence of dual block coordinate ascent methods done in previous works. The proof of convergence of our method is, therefore, also novel. We show that, if the cost is strongly convex and the network is fully connected, then, with probability one, the primal sequence generated by StochaLM converges to the solution. Our method is application-friendly, as it has no global hyperparameters to tune; any hyperparameters can be tuned locally by the agents, using information regarding their private cost and neighbourhood. Our method is, therefore, decentralized in the truest sense. Numerical experiments evidence that our method converges to the solution faster than other token-based methods, even when these methods' hyperparameters are tuned for optimal performance.
Topological IIR Filters over Simplicial Topologies via Sheaves
Authors: Georg Essl
Date: 2020-04-23 00:00:00
Tasks: Translation

Topology offers a means to formally generalize digital filtering methods based on digital linear translation-invariant (LTI) filters while also, in principle, incorporating translation-variant and nonlinear methods as well as studying large scale (global) properties of filter problems. In this letter we show how the full content of LTI digital filter theory can be incorporated into the formalism of topological filters as introduced by Robinson. In particular, we will give the feedback filter construction associated with infinite impulse responses (IIR). The result allows for direct translation of LTI filters into topological filters, which are sheaves of finite vector spaces and suitably constructed linear maps over simplicial topologies.