pwc-archive/papers-with-abstracts huggingface dataset:
Exact Parallelization of the Stochastic Simulation Algorithm for Scalable Simulation of Large Biochemical Networks
Authors: Arthur P. Goldberg, David R. Jefferson, John A. P. Sekar, Jonathan R. Karr
Date: 2020-05-11 00:00:00

Comprehensive simulations of the entire biochemistry of cells have great potential to help physicians treat disease and help engineers design biological machines. But such simulations must model networks of millions of molecular species and reactions. The Stochastic Simulation Algorithm (SSA) is widely used for simulating biochemistry, especially systems with species populations small enough that discreteness and stochasticity play important roles. However, existing serial SSA methods are prohibitively slow for comprehensive networks, and existing parallel SSA methods, which use periodic synchronization, sacrifice accuracy. To enable fast, accurate, and scalable simulations of biochemistry, we present an exact parallel algorithm for SSA that partitions a biochemical network into many SSA processes that simulate in parallel. Our parallel SSA algorithm exactly coordinates the interactions among these SSA processes and the species state they share by structuring the algorithm as a parallel discrete event simulation (DES) application and using an optimistic parallel DES simulator to synchronize the interactions. We anticipate that our method will enable unprecedented biochemical simulations.
Rational Finance Approach to Behavioral Option Pricing
Authors: Jiexin Dai, Abootaleb Shirvani, Frank J. Fabozzi
Date: 2020-05-10 00:00:00

When pricing options, there may be different views on the instantaneous mean return of the underlying price process. According to Black (1972), where there exist heterogeneous views on the instantaneous mean return, this will result in arbitrage opportunities. Behavioral finance proponents argue that such heterogenous views are likely to occur and this will not impact option pricing models proposed by rational dynamic asset pricing theory and will not give rise to volatility smiles. To rectify this, a leading advocate of behavioral finance has proposed a behavioral option pricing model. As there may be unexplored links between the behavioral and rational approaches to option pricing, in this paper we revisit Shefrin (2008) option pricing model as an example and suggest one approach to modify this behavioral finance option pricing formula to be consistent with rational dynamic asset pricing theory by introducing arbitrage transaction costs which offset the gains from arbitrage trades.
Audio and Contact Microphones for Cough Detection
Date: 2020-05-10 00:00:00
Tasks: feature selection, Specificity

In the framework of assessing the pathology severity in chronic cough
diseases, medical literature underlines the lack of tools for allowing the
automatic, objective and reliable detection of cough events. This paper
describes a system based on two microphones which we developed for this
purpose. The proposed approach relies on a large variety of audio descriptors,
an efficient algorithm of feature selection based on their mutual information
and the use of artificial neural networks. First, the possible use of a contact
microphone (placed on the patient's thorax or trachea) in complement to the
audio signal is investigated. This study underlines that this contact
microphone suffers from reliability issues, and conveys little new relevant
information compared to the audio modality. Secondly, the proposed audio-only
approach is compared to a commercially available system using four sensors on a
database with different sound categories often misdetected as coughs, and
produced in various conditions. With average sensitivity and specificity of
94.7% and 95% respectively, the proposed method achieves better cough detection
performance than the commercial system.
A Repo Model of Fire Sales with VWAP and LOB Pricing Mechanisms
Authors: Maxim Bichuch, Zachary Feinstein
Date: 2020-05-11 00:00:00

We consider a network of banks that optimally choose a strategy of asset liquidations and borrowing in order to cover short term obligations. The borrowing is done in the form of collateralized repurchase agreements, the haircut level of which depends on the total liquidations of all the banks. Similarly the fire-sale price of the asset obtained by each of the banks depends on the amount of assets liquidated by the bank itself and by other banks. By nature of this setup, banks' behavior is considered as a Nash equilibrium. This paper provides two forms for market clearing to occur: through a common closing price and through an application of the limit order book. The main results of this work are providing the existence of maximal and minimal clearing solutions (i.e., liquidations, borrowing, fire sale prices, and haircut levels) as well as sufficient conditions for uniqueness of the clearing solutions.
Electro-Quasistatic Animal Body Communication for Chronic Untethered Rodent Biopotential Recording
Authors: Shreeya Sriram, Shitij Avlani, Matthew P Ward, Shreyas Sen
Date: 2020-05-11 00:00:00

Continuous multi-channel monitoring of biopotential signals is vital in understanding the body as a whole, facilitating accurate models and predictions in neural research. The current state of the art in wireless technologies for untethered biopotential recordings rely on radiative electromagnetic (EM) fields. In such transmissions, only a small fraction of this energy is received since the EM fields are widely radiated resulting in lossy inefficient systems. Using the body as a communication medium (similar to a 'wire') allows for the containment of the energy within the body, yielding order(s) of magnitude lower loss than radiative EM communication. In this work, we introduce Animal Body Communication (ABC), which utilizes the concept of using the body as a medium into the domain of chronic animal biopotential recording. This work, for the first time, develops the theory and models for animal body communication circuitry and channel loss. Using this theoretical model, a sub-inch$^3$, custom-designed sensor node is built using off the shelf components which is capable of sensing and transmitting biopotential signals, through the body of the rat at significantly lower powers compared to traditional wireless transmissions. In-vivo experimental analysis proves that ABC successfully transmits acquired electrocardiogram (EKG) signals through the body with correlation accuracy >99% when compared to traditional wireless communication modalities, with a 50x reduction in power consumption.
Roles of Dynamic State Estimation in Power System Modeling, Monitoring and Operation
Authors: Junbo Zhao, Marcos Netto, Zhenyu Huang, Samson Shenglong Yu, Antonio Gomez-Exposito, Shaobu Wang, Innocent Kamwa, Shahrokh Akhlaghi, Lamine Mili, Vladimir Terzija, A. P. Sakis Meliopoulos, Bikash Pal, Abhinav Kumar Singh, Ali Abur, Tianshu Bi, Alireza Rouhani
Date: 2020-05-11 00:00:00
Tasks: energy management, Management, State Estimation

Power system dynamic state estimation (DSE) remains an active research area. This is driven by the absence of accurate models, the increasing availability of fast-sampled, time-synchronized measurements, and the advances in the capability, scalability, and affordability of computing and communications. This paper discusses the advantages of DSE as compared to static state estimation, and the implementation differences between the two, including the measurement configuration, modeling framework and support software features. The important roles of DSE are discussed from modeling, monitoring and operation aspects for today's synchronous machine dominated systems and the future power electronics-interfaced generation systems. Several examples are presented to demonstrate the benefits of DSE on enhancing the operational robustness and resilience of 21st century power system through time critical applications. Future research directions are identified and discussed, paving the way for developing the next generation of energy management systems.
Workspace Partitioning and Topology Discovery Algorithms for Heterogeneous Multi-Agent Networks
Date: 2020-05-11 00:00:00

In this paper, we consider a class of workspace partitioning problems that
arise in the context of area coverage and spatial load balancing for spatially
distributed heterogeneous multi-agent networks. It is assumed that each agent
has certain directions of motion or directions for sensing and exploration that
are more preferable than others. These preferences are measured by means of
convex and anisotropic (direction-dependent) quadratic proximity metrics which
are, in general, different for each agent. These proximity metrics induce
Voronoi-like partitions of the network's workspace that are comprised of cells
which may not always be convex (or even connected) sets but are necessarily
contained in ellipsoids that are known to their corresponding agents. The main
contributions of this work are 1) a distributed algorithm for the computation
of a Voronoi-like partition of the workspace of a heterogeneous multi-agent
network and 2) a systematic process to discover the network topology induced by
the latter Voronoi-like partition. Numerical simulations that illustrate the
efficacy of the proposed algorithms are also presented.
Towards a Decentralized Digital Engineering Assets Marketplace: Empowered by Model-based Systems Engineering and Distributed Ledger Technology
Date: 2020-05-11 00:00:00

Model-based Systems Engineering (MBSE) has been widely utilized to formalize
system artifacts and facilitate their development throughout the entire
lifecycle. During complex system development, MBSE models need to be frequently
exchanged across stakeholders. Concerns about data security and tampering using
traditional data exchange approaches obstruct the construction of a reliable
marketplace for digital assets. The emerging Distributed Ledger Technology
(DLT), represented by blockchain, provides a novel solution for this purpose
owing to its unique advantages such as tamper-resistant and decentralization.
In this paper, we integrate MBSE approaches with DLT aiming to create a
decentralized marketplace to facilitate the exchange of digital engineering
assets (DEAs). We first define DEAs from perspectives of digital engineering
objects, development processes and system architectures. Based on this
definition, the Graph-Object-Property-Point-Role-Relationship (GOPPRR) approach
is used to formalize the DEAs. Then we propose a framework of a decentralized
DEAs marketplace and specify the requirements, based on which we select a
Directed Acyclic Graph (DAG) structured DLT solution. As a proof-of-concept, a
prototype of the proposed DEAs marketplace is developed and a case study is
conducted to verify its feasibility. The experiment results demonstrate that
the proposed marketplace facilitates free DEAs exchange with a high level of
security, efficiency and decentralization.
Value-at-Risk substitute for non-ruin capital is fallacious and redundant
Authors: Vsevolod Malinovskii
Date: 2020-05-11 00:00:00

This seemed impossible to use a theoretically adequate but too sophisticated risk measure called non-ruin capital, whence its widespread (including regulatory documents) replacement with an inadequate, but simple risk measure called Value-at-Risk. Conflicting with the idea by Albert Einstein that "everything should be made as simple as possible, but not simpler", this led to fallacious, and even deceitful (but generally accepted) standards and recommendations. Arguing from the standpoint of mathematical theory of risk, we aim to break this impasse.
On the Modeling and Simulation of Anti-Windup Proportional-Integral Controller
Date: 2020-05-11 00:00:00
Tasks: Numerical Integration

This paper investigates the chattering and deadlock behaviors of the
proportional-integral (PI) controller with an anti-windup (AW) limiter
recommended by the IEEE Standard 421.5-2016. Depending on the simulation
method, the controller may enter a chattering or deadlock state in some
combinations of parameters and inputs. Chattering and deadlock are analyzed in
the context of three numerical integration approaches: explicit partitioned
method (EPM), execution-list based method (ELM), and implicit trapezoidal
method (ITM). This paper derives the chattering stop condition for EPM and ELP,
and analyzes the impacts of step size and convergence tolerance for
simultaneous method. The deduced chattering stop conditions and deadlock
behavior is verified with numerical simulations.
Semi-closed form prices of barrier options in the time-dependent CEV and CIR models
Authors: Peter Carr, Andrey Itkin, Dmitry Muravey
Date: 2020-05-11 00:00:00
Tasks: Form

We continue a series of papers where prices of the barrier options written on the underlying, which dynamics follows some one factor stochastic model with time-dependent coefficients and the barrier, are obtained in semi-closed form, see (Carr and Itkin, 2020, Itkin and Muravey, 2020). This paper extends this methodology to the CIR model for zero-coupon bonds, and to the CEV model for stocks which are used as the corresponding underlying for the barrier options. We describe two approaches. One is generalization of the method of heat potentials for the heat equation to the Bessel process, so we call it the method of Bessel potentials. We also propose a general scheme how to construct the potential method for any linear differential operator with time-independent coefficients. The second one is the method of generalized integral transform, which is also extended to the Bessel process. In all cases, a semi-closed solution means that first, we need to solve numerically a linear Volterra equation of the second kind, and then the option price is represented as a one-dimensional integral. We demonstrate that computationally our method is more efficient than both the backward and forward finite difference methods while providing better accuracy and stability. Also, it is shown that both method don't duplicate but rather compliment each other, as one provides very accurate results at small maturities, and the other one - at high maturities.
Site-specific online compressive beam codebook learning in mmWave vehicular communication
Authors: Yuyang Wang, Nitin Jonathan Myers, Nuria González-Prelcic, Robert W. Heath Jr
Date: 2020-05-11 00:00:00
Tasks: Compressive Sensing

Millimeter wave (mmWave) communication is one viable solution to support Gbps sensor data sharing in vehicular networks. The use of large antenna arrays at mmWave and high mobility in vehicular communication make it challenging to design fast beam alignment solutions. In this paper, we propose a novel framework that learns the channel angle-of-departure (AoD) statistics at a base station (BS) and uses this information to efficiently acquire channel measurements. Our framework integrates online learning for compressive sensing (CS) codebook learning and the optimized codebook is used for CS-based beam alignment. We formulate a CS matrix optimization problem based on the AoD statistics available at the BS. Furthermore, based on the CS channel measurements, we develop techniques to update and learn such channel AoD statistics at the BS. We use the upper confidence bound (UCB) algorithm to learn the AoD statistics and the CS matrix. Numerical results show that the CS matrix in the proposed framework provides faster beam alignment than standard CS matrix designs. Simulation results indicate that the proposed beam training technique can reduce overhead by 80% compared to exhaustive beam search, and 70% compared to standard CS solutions that do not exploit any AoD statistics.
Extensions of Dupire Formula: Stochastic Interest Rates and Stochastic Local Volatility
Authors: Orcan Ogetbil, Bernhard Hientzsch
Date: 2020-05-12 00:00:00

We derive generalizations of Dupire formula to the cases of general stochastic drift and/or stochastic local volatility. First, we handle a case in which the drift is given as difference of two stochastic short rates. Such a setting is natural in foreign exchange context where the short rates correspond to the short rates of the two currencies, equity single-currency context with stochastic dividend yield, or commodity context with stochastic convenience yield. We present the formula both in a call surface formulation as well as total implied variance formulation where the latter avoids calendar spread arbitrage by construction. We provide derivations for the case where both short rates are given as single factor processes and present the limits for a single stochastic rate or all deterministic short rates. The limits agree with published results. Then we derive a formulation that allows a more general stochastic drift and diffusion including one or more stochastic local volatility terms. In the general setting, our derivation allows the computation and calibration of the leverage function for stochastic local volatility models. Despite being implicit, the generalized Dupire formulae can be used numerically in a fixed-point iterative scheme.
Phase-retrieval exact solution based on window modulation
Date: 2020-05-12 00:00:00
Tasks: Retrieval, Transparent objects

Quantitative phase imaging (QPI) is a promising tool for imaging complex
objects. By Combining self-reference interferometry and phase retrieval, this
paper proposes a general exact QPI for arbitrary complex-objects as well as a
one-shot exact QPI for transparent objects with small phase range (i.e., weak
scattering object). The optical configuration is similar to the Zernike phase
contrast, while the phase-shifting area is a little smaller. With three frames
of phase-shift, the algebraic relationship between the phase and the measured
intensity is built, providing an excellent approximate phase recovery. Then, an
efficient iterative optimization strategy is reported to turn that approximate
solution into an exact one. The iteration exhibits linear convergence property.
Thus exact phase map is achieved with a sufficient number of iterations. When
the object is a pure phase sample with a small phase ranges of [0,{\pi}], a
single intensity measurement will be enough for exact phase recovery by
selecting a tiny phase shifting value, based on a similar linear-convergence
iterative algorithm. The feasibility and accuracy of our method are verified by
both numerical simulations and experiments on diverse phase objects.
No arbitrage and multiplicative special semimartingales
Authors: Eckhard Platen, Stefan Tappe
Date: 2020-05-12 00:00:00

Consider a financial market with nonnegative semimartingales which does not need to have a num\'{e}raire. We are interested in the absence of arbitrage in the sense that no self-financing portfolio gives rise to arbitrage opportunities, where we are allowed to add a savings account to the market. We will prove that in this sense the market is free of arbitrage if and only if there exists an equivalent local martingale deflator which is a multiplicative special semimartingale. In this case, the additional savings account relates to the finite variation part of the multiplicative decomposition of the deflator.
Multi-criteria Analysis for Evaluation of Adaptive Radar Resource Management algorithms on a Naval setting with and without clutter
Authors: Christophe Labreuche, Cédric Buron, Peter Moo, Frédéric Barbaresco
Date: 2020-05-12 00:00:00
Tasks: Management

Multifunction radars (MFR) are met with complex capability requirements, involving various kinds of targets and saturating scenarios. In order to achieve these goals, radar systems use Active Electronically Scanned Array (AESA) to switch between their functions. This complexity makes it difficult to assess their performance both taking into account their functional requirements and the induces cost. In this paper, we first introduce Figures of Merit for phased array radar operation and performance. We compute these metrics on a set of test scenarios of varying complexity, involving different kinds of targets, and we aggregate them into a global notation of MFR radar performances. To achieve our purpose, we rely on the domain of Multi Criteria Decision Analysis (MCDA), and more precisely 2-additive Choquet integral.
The Intermittent Nature of Leaf Growth Fields
Authors: S. Armon, M. Moshe, E. Sharon
Date: 2020-05-12 00:00:00

What are the general principles that allow proper growth of a tissue or an organ? A growing leaf is an example of such a system: it increases its area by orders of magnitude, maintaining a proper (usually flat) shape. How can this be achieved without a central control unit? One would think that a combination of uniform growth with viscoelastic rheology would allow that. Here we show that that the exact opposite process is in action: the natural growth of the leaf surface strongly fluctuates in time and position. By combining high resolution measurements and multi-scale statistical analysis, we suggest a paradigm-change in the way leaf growth is viewed. We measure the in-plane tissue growth of Tobacco leaves in Lagrangian coordinates in 3D and study the statistics of three scalar fields associated with the tensorial growth field: The growth rate, its isotropy and directionality. We identify the governing time and length scales of the fluctuations in the growth rate, and capture abundant switching between local area swelling and shrinking, when measured in high resolution. At lower spatio-temporal resolution the growth rate field becomes smooth. In contrast, the anisotropy field increases over time. Finally, we find significant differences between growth measured during day and night. The growth at night is found to be more intermittent, with shorter correlation lengths and no global directionality. Despite its fluctuative nature, growth fields are not random, thus carry information about growth regulation. Indeed, mechanical analysis shows that a growing leaf can stay flat only if the measured fluctuations are regulated/correlated. Our measurements suggest that the entire statistics of growth fields, and not just their means, should be studied. In particular, the regulation of such fields and the link between their characteristics and the global geometry of a leaf should be studied.
On the usefulness of a minimalistic model to study tree-grass biomass distributions along biogeographic gradients in the savanna biome
Date: 2020-05-12 00:00:00

We present and analyze a model aiming at recovering as dynamical outcomes of
tree-grass interactions the wide range of vegetation physiognomies observable
in the savanna biome along rainfall gradients at regional/continental scales.
The model is based on two ordinary differential equations (ODE), for woody and
grass biomass. It is parameterized from literature and retains mathematical
tractability, since we restricted it to the main processes, notably tree-grass
asym-metric interactions (either facilitative or competitive) and the
grass-fire feedback. We used a fully qualitative analysis to derive all
possible long term dynamics and express them in a bifur-cation diagram in
relation to mean annual rainfall and fire frequency. We delineated domains of
monostability (forest, grassland, savanna), of bistability (e.g.
forest-grassland or forest-savanna) and even tristability. Notably, we
highlighted regions in which two savanna equilibria may be jointly stable
(possibly in addition to forest or grassland). We verified that common
knowledge about decreasing woody biomass with increasing fire frequency is
recovered for all levels of rainfall, contrary to previous attempts using
analogous ODE frameworks. Thus, this framework appears able to render more
realistic and diversified outcomes than often thought of. Our model can help
figure out the ongoing dynamics of savanna vegetation in large territories for
which local data are sparse or absent. To explore the bifurcation diagram with
different combinations of the model parameters, we have developed a
user-friendly R-Shiny application freely available at :
https://gitlab.com/cirad-apps/tree-grass.