3,406 research outputs found
AWF Edwards and the origin of Bayesian phylogenetics
No full textIn the early 1960s, Anthony Edwards and Luca Cavalli-Sforza made an effort to apply R.A. Fisher’s maximum likelihood (ML) method to estimate genealogical trees of human populations using gene frequency data. They used the Yule branching process to describe the probabilities of the trees and branching times and the Brownian motion process to model the drift of gene frequencies (after a suitable transformation) over time along the branches. They experienced considerable difficulties, including “singularities” in the likelihood surface, mainly because a distinction between parameters and random variables was not clearly made. In the process they invented the distance (additive-tree) and parsimony (minimum-evolution) methods, both of which they viewed as heuristic approximations to ML. The statistical nature of the inference problem was not clarified until Edwards 1, which pointed out that the trees should be estimated from their conditional distribution given the genetic data, rather than from the “likelihood function”. In modern terminology, this is the Bayesian approach to phylogeny estimation: the Yule process specifies a prior on trees, while the conditional distribution of the trees given the data is the posterior. This article discusses the connections of the remarkable paper of Edwards 1 to modern Bayesian phylogenetics, and briefly comments on some modelling decisions Edwards made then that still concern us today in modern Bayesian phylogenetics. The reader I have in mind is familiar with modern phylogenetic methods but may not have read Edwards, which is published in a statistics journal
Lamotrigine — Interactions matter! (Editorial)
No full text1. Introduction
The diagnosis and treatment of epilepsy demands a tailored approach. Important therapeutic considerations include patient characteristics, drug attributes, etiology, and type of epilepsy [1]. It is imperative to prescribe the optimal antiepileptic medication (AEM), at the lowest dosage, which minimizes adverse effects (AEs) and maximizes seizure control [2]. In managing the person with epilepsy (PWE), clinicians must consider the patient's needs and expectations. An illustrative case that highlights the many facets of the decision-making process is described.No Full Tex
PROJECTIVE MULTIGRID FOR WILSON FERMIONS
No full textWe propose a multi-level algorithm for Wilson fermions in a background gauge field by the application of the projective multigrid method. A variational wave function is placed on blocks of 2d sites which gives an effective Dirac equation for coarser lattices with new effective gauge links. Renormalization group arguments are given to motivate our Ansatz. Finally we test the multi-level algorithm on a 2d U(1) lattice gauge theory and show that critical slowing down is eliminated for distances less than the confinement scale l-sigma defined by the string tension. As the quark mass vanishes convergence is accelerated by a factor of this length l-sigma measured in lattice units
Meeting with the Hebrew author Elias Hurwitz
No full textWhite paper; handpainted; on the reverse of Luftwaffe uniform pattern. Digitized posters are related to the activities of Jewish displaced persons drawn from the Records of Displaced Persons Camps and Centers in Germany (RG 294.2) Italy (RG 294.3) and Austria (RG 294.4) held by YIVO Archives. Please consult the historical note for those record groups for further information.Digital ImageDigital finding aid available
Obituary announcement about author and labor activist Sh. Mendelson
No full textBrown paper; handpainted. Digitized posters are related to the activities of Jewish displaced persons drawn from the Records of Displaced Persons Camps and Centers in Germany (RG 294.2) Italy (RG 294.3) and Austria (RG 294.4) held by YIVO Archives. Please consult the historical note for those record groups for further information.Digital ImageDigital finding aid available
Sweeping has no effect on renormalized turbulent viscosity
No full textWe perform renormalization group analysis (RG) of the Navier-Stokes equation in the presence of constant mean velocity field , and show that the renormalized viscosity is unaffected by , thus negating the ``sweeping effect", proposed by Kraichnan [Phys. Fluids {\bf 7}, 1723 (1964)] using random Galilean invariance. Using direct numerical simulation, we show that the correlation functions for and differ from each other, but the renormalized viscosity for the two cases are the same. Our numerical results are consistent with the RG calculations
- …
