pwc-archive/papers-with-abstracts huggingface dataset:
A Quasi-Doppler Method for Doubling Transmission Efficiency Through Two Orthogonal Directions
Authors: Bingli Jiao
Date: 2020-07-14 00:00:00

Inspired by the anisotropy of Doppler effect with wave propagations, we propose a new method to leverage one information symbol serving two users located in two geometrically orthogonal directions. Specifically in broadband wireless communication, we use multiple antennas with the proposed signal switching method to emulate a moving emission source and yield the frequency shift, referred to as Quasi Doppler effect, which is converted to the discrete phase modulation. Further, using this discrete modulated phase can adjust the phase of one transmit symbol in achieving two different phases in different directions. The modulation mechanism is explained through theoretical derivations with the analysis on the performance robustness in the application-scenarios of crossroads having small geometric deviations. In contrast to the use of conventional symbols, this approach can double the transmission efficiency which is confirmed by our simulations results.
The role of vascular complexity on optimal junction exponents
Authors: Jonathan Keelan, James P. Hague
Date: 2020-07-14 00:00:00

We examine the role of complexity on arterial tree structures, determining globally optimal vessel arrangements using the Simulated AnneaLing Vascular Optimization (SALVO) algorithm, which we have previously used to reproduce features of cardiac and cerebral vasculatures. Fundamental biophysical understanding of complex vascular structure has applications to modelling of cardiovascular diseases, and for improved representations of vasculatures in large artificial tissues. In order to progress in-silico methods for growing arterial networks, we need to understand the stability of computational arterial growth algorithms to complexity, variations in physiological parameters such as tissue demand, and underlying assumptions regarding the value of junction exponents. We determine the globally optimal structure of two-dimensional arterial trees; analysing sensitivity of tree morphology and optimal bifurcation exponent to physiological parameters. We find that, for physiologically relevant simulation parameters, arterial structure is stable, whereas optimal junction exponents vary. We conclude that the full complexity of arterial trees is essential for determining the fundamental properties of vasculatures. These results are important for establishing that optimisation-based arterial growth algorithms are stable against uncertainties in physiological parameters, while identifying that optimal bifurcation exponents (a key parameter for many arterial growth algorithms) are sensitive to complexity and the boundary conditions dictated by organs.
Nonlinear Adaptive Cruise Control of Vehicular Platoons
Date: 2020-07-14 00:00:00
Tasks: Collision Avoidance

The paper deals with the design of nonlinear adaptive cruise controllers for
vehicular platoons operating on an open road or a ring-road. The constructed
feedback controllers are nonlinear functions of the distance between successive
vehicles and their speeds. It is shown that the proposed novel controllers
guarantee safety (collision avoidance) and bounded vehicle speeds by explicitly
characterizing the set of allowable inputs. Moreover, we guarantee global
asymptotic stability of the platoon to a desired configuration as well as
string stability. Certain macroscopic properties are also investigated. The
efficiency of the nonlinear adaptive cruise controllers is demonstrated by
means of a numerical example.
Polarization in Networks: Identification-alienation Framework
Date: 2020-07-14 00:00:00

We introduce a model of polarization in networks as a unifying framework for the measurement of polarization that covers a wide range of applications. We consider a sufficiently general setup for this purpose: node- and edge-weighted, undirected, and connected networks. We generalize the axiomatic characterization of Esteban and Ray (1994) and show that only a particular instance within this class can be used justifiably to measure polarization in networks.
Modeling and measuring incurred claims risk liabilities for a multi-line property and casualty insurer
Authors: Carlos Andrés Araiza Iturria, Frédéric Godin, Mélina Mailhot
Date: 2020-07-14 00:00:00

We propose a stochastic model allowing property and casualty insurers with multiple business lines to measure their liabilities for incurred claims risk and calculate associated capital requirements. Our model includes many desirable features which enable reproducing empirical properties of loss ratio dynamics. For instance, our model integrates a double generalized linear model relying on accident semester and development lag effects to represent both the mean and dispersion of loss ratio distributions, an autocorrelation structure between loss ratios of the various development lags, and a hierarchical copula model driving the dependence across the various business lines. The model allows for a joint simulation of loss triangles and the quantification of the overall portfolio risk through risk measures. Consequently, a diversification benefit associated to the economic capital requirements can be measured, in accordance with IFRS 17 standards which allow for the recognition of such benefit. The allocation of capital across business lines based on the Euler allocation principle is then illustrated. The implementation of our model is performed by estimating its parameters based on a car insurance data obtained from the General Insurance Statistical Agency (GISA), and by conducting numerical simulations whose results are then presented.
Accuracy vs. Complexity for mmWave Ray-Tracing: A Full Stack Perspective
Authors: Mattia Lecci, Paolo Testolina, Michele Polese, Marco Giordani, Michele Zorzi
Date: 2020-07-14 00:00:00

The millimeter wave (mmWave) band will provide multi-gigabits-per-second connectivity in the radio access of future wireless systems. The high propagation loss in this portion of the spectrum calls for the deployment of large antenna arrays to compensate for the loss through high directional gain, thus introducing a spatial dimension in the channel model to accurately represent the performance of a mmWave network. In this perspective, ray-tracing can characterize the channel in terms of Multi Path Components (MPCs) to provide a highly accurate model, at the price of extreme computational complexity (e.g., for processing detailed environment information about the propagation), which limits the scalability of the simulations. In this paper, we present possible simplifications to improve the trade-off between accuracy and complexity in ray-tracing simulations at mmWaves by reducing the total number of MPCs. The effect of such simplifications is evaluated from a full-stack perspective through end-to-end simulations, testing different configuration parameters, propagation scenarios, and higher-layer protocol implementations. We then provide guidelines on the optimal degree of simplification, for which it is possible to reduce the complexity of simulations with a minimal reduction in accuracy for different deployment scenarios.
Stochastic MPC with Dynamic Feedback Gain Selection and Discounted Probabilistic Constraints
Authors: Shuhao Yan, Paul J. Goulart, Mark Cannon
Date: 2020-07-14 00:00:00
Tasks: Model Predictive Control

This paper considers linear discrete-time systems with additive disturbances, and designs a Model Predictive Control (MPC) law incorporating a dynamic feedback gain to minimise a quadratic cost function subject to a single chance constraint. The feedback gain is selected online and we provide two selection methods based on minimising upper bounds on predicted costs. The chance constraint is defined as a discounted sum of violation probabilities on an infinite horizon. By penalising violation probabilities close to the initial time and assigning violation probabilities in the far future with vanishingly small weights, this form of constraints allows for an MPC law with guarantees of recursive feasibility without a boundedness assumption on the disturbance. A computationally convenient MPC optimisation problem is formulated using Chebyshev's inequality and we introduce an online constraint-tightening technique to ensure recursive feasibility. The closed loop system is guaranteed to satisfy the chance constraint and a quadratic stability condition. With dynamic feedback gain selection, the closed loop cost is reduced and conservativeness of Chebyshev's inequality is mitigated. Also, a larger feasible set of initial conditions can be obtained. Numerical simulations are given to show these results.
Outage Probability Analysis of THz Relaying Systems
Authors: Alexandros-Apostolos A. Boulogeorgos, Angeliki Alexiou
Date: 2020-07-14 00:00:00

This paper focuses on quantifying the outage performance of terahertz (THz) relaying systems. In this direction, novel closed-form expressions for the outage probability of a dual-hop relaying system, in which both the source-relay and relay-destination links suffer from fading and stochastic beam misalignment, are extracted. Our results reveal the importance of taking into account the impact of beam misalignment when characterizing the outage performance of the system as well as when selecting the transmission frequencies.
Evaluating Incidence and Impact Estimates of the COVID-19 Outbreak from Wuhan before Lockdown
Date: 2020-07-10 00:00:00

Background: Wuhan, China was the epicenter of COVID-19 pandemic. The goal of
current study is to understand the infection transmission dynamics before
intervention measures were taken. Methods: Data and key events were searched
through pubmed and internet. Epidemiological data were calculated using data
extracted from a variety of data sources. Results: We established a timeline
showing by January 1, 2020, Chinese authorities had been presented convincing
evidence of human-to-human transmission; however, it was not until January 20,
2020 that this information was shared with the public. Our study estimated that
there would have been 10989 total infected cases if interventions were taken on
January 2, 2020, versus 239875 cases when lockdown was put in place on January
23, 2020. Conclusions: China's withholding of key information about the 2020
COVID-19 outbreak and its delayed response ultimately led to the largest public
health crisis of this century and could have been avoided with earlier
countermeasures.
Allpass Feedback Delay Networks
Authors: Sebastian J. Schlecht
Date: 2020-07-14 00:00:00
Tasks: Computational Efficiency

In the 1960s, Schroeder and Logan introduced delay line-based allpass filters, which are still popular due to their computational efficiency and versatile applicability in artificial reverberation, decorrelation, and dispersive system design. In this work, we extend the theory of allpass systems to any arbitrary connection of delay lines, namely feedback delay networks (FDNs). We present a characterization of uniallpass FDNs, i.e., FDNs, which are allpass for an arbitrary choice of delays. Further, we develop a solution to the completion problem, i.e., given an FDN feedback matrix to determine the remaining gain parameters such that the FDN is allpass. Particularly useful for the completion problem are feedback matrices, which yield a homogeneous decay of all system modes. Finally, we apply the uniallpass characterization to previous FDN designs, namely, Schroeder's series allpass and Gardner's nested allpass for single-input, single-output systems, and, Poletti's unitary reverberator for multi-input, multi-output systems and demonstrate the significant extension of the design space.
Molecular mechanisms behind anti SARS-CoV-2 action of lactoferrin
Authors: Mattia Miotto, Lorenzo Di Rienzo, Leonardo Bò, Alberto Boffi, Giancarlo Ruocco, Edoardo Milanetti
Date: 2020-07-14 00:00:00

Despite the huge effort to contain the infection, the novel SARS-CoV-2 coronavirus has rapidly become pandemics, mainly due to its extremely high human-to-human transmission capability, and a surprisingly high viral charge of symptom-less people. While the seek of a vaccine is still ongoing, promising results have been obtained with antiviral compounds. In particular, lactoferrin is found to have beneficial effects both in preventing and soothing the infection. Here, we explore the possible molecular mechanisms with which lactoferrin interferes with SARS-CoV-2 cell invasion, preventing attachment and/or entry of the virus. To this aim, we search for possible interactions lactoferrin may have with virus structural proteins and host receptors. Representing the molecular iso-electron surface of proteins in terms of 2D-Zernike descriptors, we (i) identified putative regions on the lactoferrin surface able to bind sialic acid receptors on the host cell membrane, sheltering the cell from the virus attachment; (ii) showed that no significant shape complementarity is present between lactoferrin and the ACE2 receptor, while (iii) two high complementarity regions are found on the N- and C-terminal domains of the SARS-CoV-2 spike protein, hinting at a possible competition between lactoferrin and ACE2 for the binding to the spike protein.
Keynesian models of depression. Supply shocks and the COVID-19 Crisis
Date: 2020-07-17 00:00:00

The objective of this work is twofold: to expand the depression models
proposed by Tobin and analyse a supply shock, such as the Covid-19 pandemic, in
this Keynesian conceptual environment. The expansion allows us to propose the
evolution of all endogenous macroeconomic variables. The result obtained is
relevant due to its theoretical and practical implications. A quantity or
Keynesian adjustment to the shock produces a depression through the effect on
aggregate demand. This depression worsens in the medium/long-term. It is
accompanied by increases in inflation, inflation expectations and the real
interest rate. A stimulus tax policy is also recommended, as well as an active
monetary policy to reduce real interest rates. On the other hand, the pricing
or Marshallian adjustment foresees a more severe and rapid depression in the
short-term. There would be a reduction in inflation and inflation expectations,
and an increase in the real interest rates. The tax or monetary stimulus
measures would only impact inflation. This result makes it possible to clarify
and assess the resulting depression, as well as propose policies. Finally, it
offers conflicting predictions that allow one of the two models to be
falsified.
Localization, epidemic transitions, and unpredictability of multistrain epidemics with an underlying genotype network
Authors: Blake J. M. Williams, Guillaume St-Onge, Laurent Hébert-Dufresne
Date: 2020-07-15 00:00:00
Tasks: Diversity

Mathematical disease modelling has long operated under the assumption that any one infectious disease is caused by one transmissible pathogen spreading among a population. This paradigm has been useful in simplifying the biological reality of epidemics and has allowed the modelling community to focus on the complexity of other factors such as population structure and interventions. However, there is an increasing amount of evidence that the strain diversity of pathogens, and their interplay with the host immune system, can play a large role in shaping the dynamics of epidemics. Here, we introduce a disease model with an underlying genotype network to account for two important mechanisms. One, the disease can mutate along network pathways as it spreads in a host population. Two, the genotype network allows us to define a genetic distance across strains and therefore to model the transcendence of immunity often observed in real world pathogens. We study the emergence of epidemics in this model, through its epidemic phase transitions, and highlight the role of the genotype network in driving cyclicity of diseases, large scale fluctuations, sequential epidemic transitions, as well as localization around specific strains of the associated pathogen. More generally, our model illustrates the richness of behaviours that are possible even in well-mixed host populations once we consider strain diversity and go beyond the "one disease equals one pathogen" paradigm.
Modelling remote epidemic transmission in Western Australia and implications for pandemic response
Date: 2020-07-15 00:00:00

We develop an agent-based model of disease transmission in remote communities
in Western Australia. Despite extreme isolation, we show that the movement of
people amongst a large number of small but isolated communities has the effect
of causing transmission to spread quickly. Significant movement between remote
communities, and regional and urban centres allows for infection to quickly
spread to and then among these remote communities. Our conclusions are based on
two characteristic features of remote communities in Western Australia: (1)
high mobility of people amongst these communities, and (2) relatively high
proportion of travellers from very small communities to major population
centres. In models of infection initiated in the state capital, Perth, these
remote communities are collectively and uniquely vulnerable. Our model and
analysis does not account for possibly heightened impact due to preexisting
conditions, such additional assumptions would only make the projections of this
model more dire. We advocate stringent monitoring and control of movement to
prevent significant impact on the indigenous population of Western Australia.
Simplified Performance Analysis of OWC System Over Atmospheric Turbulence with Pointing Error
Authors: Kartik Wardhan, S. M. Zafaruddin
Date: 2020-07-15 00:00:00

Optical wireless communication (OWC) is highly vulnerable to the atmospheric turbulence and pointing error. Performance analysis of the OWC system under the combined channel effects of pointing errors and atmospheric turbulence is desirable for its efficient deployment. The widely used Gamma- Gamma statistical model for atmospheric turbulence, which consists of Bessel function, generally leads to complicated analytical expressions. In this paper, we consider the three-parameter exponentiated Weibull model for the atmospheric turbulence to analyze the ergodic rate and average signal-to-noise ratio (SNR) performance of a single-link OWC system. We derive simplified analytical expressions on the performance under the combined effect of atmospheric turbulence and pointing errors in terms of system parameters. We also derive approximate expressions on the performance under the atmospheric turbulence by considering negligible pointing error. In order to evaluate the performance at high SNR, we also develop asymptotic bounds on the average SNR and ergodic rate for the considered system. We demonstrate the tightness of derived expressions through numerical and simulation analysis along with a comparison to the performance obtained using the Gamma-Gamma model.
How does stock market reflect the change in economic demand? A study on the industry-specific volatility spillover networks of China's stock market during the outbreak of COVID-19
Authors: Fu Qiao, Yan Yan
Date: 2020-07-15 00:00:00

Using the carefully selected industry classification standard, we divide 102 industry securities indices in China's stock market into four demand-oriented sector groups and identify demand-oriented industry-specific volatility spillover networks. The "deman-oriented" is a new idea of reconstructing the structure of the networks considering the relationship between industry sectors and the economic demand their outputs meeting. Networks with the new structure help us improve the understanding of the economic demand change, especially when the macroeconomic is dramatically influenced by exogenous shocks like the outbreak of COVID-19. At the beginning of the outbreak of COVID-19, in China's stock market, spillover effects from industry indices of sectors meeting the investment demand to those meeting the consumption demands rose significantly. However, these spillover effects fell after the outbreak containment in China appeared to be effective. Besides, some services sectors including utility, transportation and information services have played increasingly important roles in the networks of industry-specific volatility spillovers as of the COVID-19 out broke. By implication, firstly, being led by Chinese government, the COVID-19 is successfully contained and the work resumption is organized with a high efficiency in China. The risk of the investment demand therefore was controlled and eliminated relatively fast. Secondly, the intensive using of non-pharmaceutical interventions (NPIs) led to supply restriction in services in China. It will still be a potential threat for the Chinese economic recovery in the next stage.
Understanding fluctuations through Multivariate Circulant Singular Spectrum Analysis
Authors: Juan Bógalo, Pilar Poncela, Eva Senra
Date: 2020-07-15 00:00:00
Tasks: Time Series, Time Series Analysis

We introduce Multivariate Circulant Singular Spectrum Analysis (M-CiSSA) to provide a comprehensive framework to analyze fluctuations, extracting the underlying components of a set of time series, disentangling their sources of variation and assessing their relative phase or cyclical position at each frequency. Our novel method is non-parametric and can be applied to series out of phase, highly nonlinear and modulated both in frequency and amplitude. We prove a uniqueness theorem that in the case of common information and without the need of fitting a factor model, allows us to identify common sources of variation. This technique can be quite useful in several fields such as climatology, biometrics, engineering or economics among others. We show the performance of M-CiSSA through a synthetic example of latent signals modulated both in amplitude and frequency and through the real data analysis of energy prices to understand the main drivers and co-movements of primary energy commodity prices at various frequencies that are key to assess energy policy at different time horizons.
Prophylaxis of Epidemic Spreading with Transient Dynamics
Date: 2020-07-15 00:00:00

We investigate the containment of epidemic spreading in networks from a
normative point of view. We consider a susceptible/infected model in which
agents can invest in order to reduce the contagiousness of network links. In
this setting, we study the relationships between social efficiency, individual
behaviours and network structure. First, we exhibit an upper bound on the Price
of Anarchy and prove that the level of inefficiency can scale up to linearly
with the number of agents. Second, we prove that policies of uniform reduction
of interactions satisfy some optimality conditions in a vast range of networks.
In setting where no central authority can enforce such stringent policies, we
consider as a type of second-best policy the shift from a local to a global
game by allowing agents to subsidise investments in contagiousness reduction in
the global rather than in the local network. We then characterise the scope for
Pareto improvement opened by such policies through a notion of Price of
Autarky, measuring the ratio between social welfare at a global and a local
equilibrium. Overall, our results show that individual behaviours can be
extremely inefficient in the face of epidemic propagation but that policy can
take advantage of the network structure to design efficient containment
policies.