Dynamical epidemic suppression using stochastic prediction and control

We consider the effects of noise on a model of epidemic outbreaks, where the outbreaks appear. randomly. Using a constructive transition approach that predicts large outbreaks, prior to their occurrence, we derive an adaptive control. scheme that prevents large outbreaks from occurring. The theory inapplicable to a wide range of stochastic processes with underlying deterministic structure.Comment: 14 pages, 6 figure

Parsimonious Kernel Fisher Discrimination

By applying recent results in optimization transfer, a new algorithm for kernel Fisher Discriminant Analysis is provided that makes use of a non-smooth penalty on the coefficients to provide a parsimonious solution. The algorithm is simple, easily programmed and is shown to perform as well as or better than a number of leading machine learning algorithms on a substantial benchmark. It is then applied to a set of extreme small-sample-size problems in virtual screening where it is found to be less accurate than a currently leading approach but is still comparable in a number of cases

A Method for the Study of Human Factors in Aircraft Operations

A method for the study of human factors in the aviation environment is described. A conceptual framework is provided within which pilot and other human errors in aircraft operations may be studied with the intent of finding out how, and why, they occurred. An information processing model of human behavior serves as the basis for the acquisition and interpretation of information relating to occurrences which involve human error. A systematic method of collecting such data is presented and discussed. The classification of the data is outlined

Accurate Noise Projection for Reduced Stochastic Epidemic Models

We consider a stochastic Susceptible-Exposed-Infected-Recovered (SEIR) epidemiological model. Through the use of a normal form coordinate transform, we are able to analytically derive the stochastic center manifold along with the associated, reduced set of stochastic evolution equations. The transformation correctly projects both the dynamics and the noise onto the center manifold. Therefore, the solution of this reduced stochastic dynamical system yields excellent agreement, both in amplitude and phase, with the solution of the original stochastic system for a temporal scale that is orders of magnitude longer than the typical relaxation time. This new method allows for improved time series prediction of the number of infectious cases when modeling the spread of disease in a population. Numerical solutions of the fluctuations of the SEIR model are considered in the infinite population limit using a Langevin equation approach, as well as in a finite population simulated as a Markov process.Comment: 38 pages, 10 figures, new title, Final revision to appear in Chao

Aeroelastic Model Structure Computation for Envelope Expansion

Structure detection is a procedure for selecting a subset of candidate terms, from a full model description, that best describes the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modeling may be of critical importance in the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion that may save significant development time and costs. In this study, a least absolute shrinkage and selection operator (LASSO) technique is investigated for computing efficient model descriptions of non-linear aeroelastic systems. The LASSO minimises the residual sum of squares with the addition of an l(Sub 1) penalty term on the parameter vector of the traditional l(sub 2) minimisation problem. Its use for structure detection is a natural extension of this constrained minimisation approach to pseudo-linear regression problems which produces some model parameters that are exactly zero and, therefore, yields a parsimonious system description. Applicability of this technique for model structure computation for the F/A-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Active Aeroelastic Wing project using flight test data is shown for several flight conditions (Mach numbers) by identifying a parsimonious system description with a high percent fit for cross-validated data

Switching barrier scaling near bifurcation points for non-Gaussian noise

We study noise-induced switching of a system close to bifurcation parameter values where the number of stable states changes. For non-Gaussian noise, the switching exponent, which gives the logarithm of the switching rate, displays a non-power-law dependence on the distance to the bifurcation point. This dependence is found for Poisson noise. Even weak additional Gaussian noise dominates switching sufficiently close to the bifurcation point, leading to a crossover in the behavior of the switching exponent

On guidance and volatility

Survey evidence suggests that managers voluntarily disclose information, particularly earnings guidance, with an aim toward dampening share price volatility. Yet, consultants and influential institutions advise against providing guidance — citing fears of litigation and market penalties associated with missed earnings targets, as well as a lack of evidence that disclosure actually curbs volatility. Furthermore, recent research links guidance to increased volatility and heightened crash risk. Hence, many argue that guidance not only fails to promote tranquility but may actually prompt turbulence. In this paper, we consider the interplay between guidance and volatility. Consistent with the notion that volatility does indeed factor into managers’ decisions to supply earnings guidance, we provide evidence of a link between increased volatility and the likelihood that a manager chooses to "bundle" a forecast with the firm’s earnings announcement in the current quarter. In particular, our findings indicate that firms in more volatile information environments exhibit a general reticence to offer guidance, but given a recent spike in volatility, managers are more likely to jump in with a forecast seemingly in an effort to calm the market. Subsequent tests indicate that managers’ efforts do not go unrewarded, as we document a greater post-announcement run-down in volatility for guiding firms. Taken collectively, this evidence supports the view that managers can and do positively shape their firms’ information environments by an earnings guidance

A Coronal Hole's Effects on CME Shock Morphology in the Inner Heliosphere

We use STEREO imagery to study the morphology of a shock driven by a fast coronal mass ejection (CME) launched from the Sun on 2011 March 7. The source region of the CME is located just to the east of a coronal hole. The CME ejecta is deflected away from the hole, in contrast with the shock, which readily expands into the fast outflow from the coronal hole. The result is a CME with ejecta not well centered within the shock surrounding it. The shock shape inferred from the imaging is compared with in situ data at 1 AU, where the shock is observed near Earth by the Wind spacecraft, and at STEREO-A. Shock normals computed from the in situ data are consistent with the shock morphology inferred from imaging.Comment: to appear in The Astrophysical Journa