Sharp L^p bounds on spectral clusters for Lipschitz metrics

We establish L^p bounds on L^2 normalized spectral clusters for self-adjoint elliptic Dirichlet forms with Lipschitz coefficients. In two dimensions we obtain best possible bounds for all p between $2 and infinity, up to logarithmic losses for$6<p\leq 8$. In higher dimensions we obtain best possible bounds for a limited range of p.Comment: 28 page

Subcritical Lp bounds on spectral clusters for Lipschitz metrics

We establish asymptotic bounds on the L^p norms of spectrally localized functions in the case of two-dimensional Dirichlet forms with coefficients of Lipschitz regularity. These bounds are new for the range p>6. A key step in the proof is bounding the rate at which energy spreads for solutions to hyperbolic equations with Lipschitz coefficients.Comment: 10 page

Subcritical Lp bounds on spectral clusters for Lipschitz metrics

We establish asymptotic bounds on the L^p norms of spectrally localized functions in the case of two-dimensional Dirichlet forms with coefficients of Lipschitz regularity. These bounds are new for the range p>6. A key step in the proof is bounding the rate at which energy spreads for solutions to hyperbolic equations with Lipschitz coefficients.Comment: 10 page

A multi-INT semantic reasoning framework for intelligence analysis support

Lockheed Martin Corp. has funded research to generate a framework and methodology for developing semantic reasoning applications to support the discipline oflntelligence Analysis. This chapter outlines that framework, discusses how it may be used to advance the information sharing and integrated analytic needs of the Intelligence Community, and suggests a system I software architecture for such applications

Alien Registration- Smith, Herbert (Belfast, Waldo County)

https://digitalmaine.com/alien_docs/4128/thumbnail.jp

Application de l’analyse des séries chronologiques à la projection d’effectifs de population scolaire par la méthode des composantes

Cet article veut montrer qu’on peut réécrire des modèles démographiques en vue de réaliser des projections par cohorte, en les transposant dans un modèle économétrique vecteur autorégressif (VAR). De cette façon, la méthode des composantes se dote d’un cadre stochastique qui étend son envergure. Le potentiel de cette perspective est illustré à travers l’exemple d’une projection d’effectifs de population scolaire. Il met en valeur une série d’équations qui permet de vérifier la validité de plusieurs choix de modélisations habituellement utilisées dans le domaine de la prévision.This article shows that we can re-write several demographic models for cohort projections as transpositions of the econometric vector auto-regression (VAR) model. In so doing, we give the method of cohort projection a stochastic framework that extends its applicability. This is demonstrated via an example involving the projection of school enrollments. We emphasize a series of equations that allow us to check the validity of several modeling choices that are otherwise made on the basis of habit alone

On the limited utility of KAP-style survey data in the practical epidemiology of AIDS, with reference to the AIDS epidemic in Chile

Population surveys concerning ‘risk behaviours’ thought to be related to the AIDS epidemic are many. Nevertheless, unfocused inquiry into diffuse behaviours in undifferentiated populations is not productive in low-seroprevalence populations, especially when the point is to design some form of intervention that might actually avert further infection. This is because of a failure to distinguish conceptually between the relevance of AIDS-related behavioural data for individuals and for populations. An illustration is drawn from the AIDS epidemic in Santiago, Chile, and an alternative perspective, based on extensive interviews with persons with AIDS and a survey of current HIV-surveillance and blood-screening programs, is described

Age-Period-Cohort Analysis: What Is It Good For?

If you know when someone was born, and you know what time it is, you know how old they are. If you know how old someone is and when they were born, you know the date on which they are being observed. If you know someone’s age as of a given time, you know when they were born. These are ineluctable features of algebra (age ≡ period – cohort) and geometry, as reflected in the Lexis diagram (Chauvel 2014, 384-389). There are many ways that one can turn the problem (e.g., cohort ≡ period – age) and thus many alternative forms of observation, classification, and depiction. However, there is a strong statistical sense in which there are only two pieces of information, not three