Estimation of exogenous drivers to predict COVID-19 pandemic using a method from nonlinear control theory

The currently ongoing COVID-19 pandemic confronts governments and their health systems with great challenges for disease management. Epidemiological models play a crucial role, thereby assisting policymakers to predict the future course of infections and hospitalizations. One difficulty with current models is the existence of exogenous and unmeasurable variables and their significant effect on the infection dynamics. In this paper, we show how a method from nonlinear control theory can complement common compartmental epidemiological models. As a result, one can estimate and predict these exogenous variables requiring the reported infection cases as the only data source. The method allows to investigate how the estimates of exogenous variables are influenced by non-pharmaceutical interventions and how imminent epidemic waves could already be predicted at an early stage. In this way, the concept can serve as an “epidemometer” and guide the optimal timing of interventions. Analyses of the COVID-19 epidemic in various countries demonstrate the feasibility and potential of the proposed approach. The generic character of the method allows for straightforward extension to different epidemiological models.

Embodiment and Its Influence on Informational Costs of Decision Density—Atomic Actions vs. Scripted Sequences

The importance of embodiment for effective robot performance has been postulated for a long time. Despite this, only relatively recently concrete quantitative models were put forward to characterize the advantages provided by a well-chosen embodiment. We here use one of these models, based on the concept of relevant information, to identify in a minimalistic scenario how and when embodiment affects the decision density. Concretely, we study how embodiment affects information costs when, instead of atomic actions, scripts are introduced, that is, predefined action sequences. Their inclusion can be treated as a straightforward extension of the basic action space. We will demonstrate the effect on informational decision cost of utilizing scripts vs. basic actions using a simple navigation task. Importantly, we will also employ a world with “mislabeled” actions, which we will call a “twisted” world. This is a model which had been used in an earlier study of the influence of embodiment on decision costs. It will turn out that twisted scenarios, as opposed to well-labeled (“embodied”) ones, are significantly more costly in terms of relevant information. This cost is further worsened when the agent is forced to lower the decision density by employing scripts (once a script is triggered, no decisions are taken until the script has run to its end). This adds to our understanding why well-embodied (interpreted in our model as well-labeled) agents should be preferable, in a quantifiable, objective sense.

Symmetric spectral synthesis

According to the famous and pioneering result of Laurent Schwartz, any closed translation invariant linear space of continuous functions on the reals is synthesizable from its exponential monomials. Due to a result of D. I. Gurevič there is no straightforward extension of this result to higher dimensions. Following Székelyhidi (Acta Math Hungar 153(1):120–142, 2017), with the aid of Gelfand pairs and K-spherical functions, K-synthesizability of K-varieties can be described. In this paper we contribute to this direction in the special case when K is the symmetric group of order d.

Founded semantics and constraint semantics of logic rules

Logic rules and inference are fundamental in computer science and have been studied extensively. However, prior semantics of logic languages can have subtle implications and can disagree significantly, on even very simple programs, including in attempting to solve the well-known Russell’s paradox. These semantics are often non-intuitive and hard-to-understand when unrestricted negation is used in recursion. This paper describes a simple new semantics for logic rules, founded semantics, and its straightforward extension to another simple new semantics, constraint semantics, that unify the core of different prior semantics. The new semantics support unrestricted negation, as well as unrestricted existential and universal quantifications. They are uniquely expressive and intuitive by allowing assumptions about the predicates, rules and reasoning to be specified explicitly, as simple and precise binary choices. They are completely declarative and relate cleanly to prior semantics. In addition, founded semantics can be computed in linear time in the size of the ground program.

On The Quotient of a Centralized and a Non-centralized Complex Gaussian Random Variable

A detailed investigation of the quotient of two independent complex random variables is presented. The numerator has a zero mean, and the denominator has a non-zero mean. A normalization step is taken prior to the theoretical developments in order to simplify the formulation. Next, an indirect approach is taken to derive the statistics of the modulus and phase angle of the quotient. That in turn enables a straightforward extension of the statistical results to real and imaginary parts. After the normalization procedure, the probability density function of the quotient is found as a function of only the mean of the random variable that corresponds to the denominator term. Asymptotic analysis shows that the quotient closely resembles a normally-distributed complex random variable as the mean becomes large. In addition, the first and second moments, as well as the approximate of the second moment of the clipped random variable, are derived, which are closely related to practical applications in complex-signal processing such as microwave metrology of scattering-parameters. Tolerance intervals associated with the ratio of complex random variables are presented.

Dualism

Dualism is a metaphysical view about the nature of consciousness, driven largely by epistemic concerns. Dualism’s chief rival, physicalism about consciousness, is also a metaphysical view driven largely by epistemic concerns. A primary goal of this chapter is to correct a widespread misunderstanding about how epistemic issues shape the debate between dualists and physicalists. According to a familiar picture, dualism is motivated by armchair reflection, and dualists accord special significance to our ways of conceptualizing consciousness and the physical. In contrast, physicalists favor empirical data over armchair reflection, and physicalism is a relatively straightforward extension of scientific theorizing. This familiar picture is inaccurate. Both dualist and physicalist arguments employ a combination of empirical data and armchair reflection; both rely on considerations of how we conceptualize certain phenomena; and both aim to establish views that are compatible with scientific results but go well beyond the deliverances of empirical science. The discussion highlights these neglected epistemic parallels between dualism and physicalism.

Empirical Analysis of Duality Spaces Connecting Distinct Optical form Transforms

This paper presents a novel technique of construction a precise functional frame in presence of the new proposed constraints during the planning straightforward extension of excessive considerable dimensional generalizations using a empirical relationship of two absolutely distinct transforms having diverse kernels transform for the Laplace Stieltjes spaces consisting of analytical signals from two dimensions at any point heavily affecting the successful development for the view of the Gelfand Shilov techniques a subspace of a Schwartz space simple objective function along with their duals implies continuity having functional analyst approach under many classical conventional transforms arise naturally as Laplace Stieltjes transform of certain distributions extensively used in many applications like magnetic field theory follows from the belongings of strong continuity at origin lean heavily in constructing multidimensional S type spaces based on the testing function spaces upto some desired order for infinitely differentiable functions t, x with Gelfand Shilov concept under one umbrella.

Robust Multi-View Representation Learning (Student Abstract)

Multi-view data has become ubiquitous, especially with multi-sensor systems like self-driving cars or medical patient-side monitors. We propose two methods to approach robust multi-view representation learning with the aim of leveraging local relationships between views.The first is an extension of Canonical Correlation Analysis (CCA) where we consider multiple one-vs-rest CCA problems, one for each view. We use a group-sparsity penalty to encourage finding local relationships. The second method is a straightforward extension of a multi-view AutoEncoder with view-level drop-out.We demonstrate the effectiveness of these methods in simple synthetic experiments. We also describe heuristics and extensions to improve and/or expand on these methods.

General Linear Recurrence Sequences and Their Convolution Formulas

We extend a technique recently introduced by Chen Zhuoyu and Qi Lan in order to find convolution formulas for second order linear recurrence polynomials generated by 1 1 + a t + b t 2 x . The case of generating functions containing parameters, even in the numerator is considered. Convolution formulas and general recurrence relations are derived. Many illustrative examples and a straightforward extension to the case of matrix polynomials are shown.

Centrality in hadron collisions

In hadron interactions at the LHC energies, the reflective scattering mode starts to play a noticeable role which is expected to be even a more significant beyond the energies of the LHC. This new but still arguable phenomenon implies a peripheral dependence of the inelastic probability distribution in the impact parameter space and asymptotically evolving to the black ring. As a consequence, the straightforward extension to hadrons of the centrality definition adopted for nuclei needs to be modified.