Iowa State University

About: Iowa State University is a(n) education organization based out in Ames, Iowa, United States. It is known for research contribution in the topic(s): Population & Gene. The organization has 50151 authors who have published 107716 publication(s) receiving 3355909 citation(s). The organization is also known as: Iowa State University of Science and Technology & Iowa State College.

Distribution of the Estimators for Autoregressive Time Series with a Unit Root

Abstract: Let n observations Y 1, Y 2, ···, Y n be generated by the model Y t = pY t−1 + e t , where Y 0 is a fixed constant and {e t } t-1 n is a sequence of independent normal random variables with mean 0 and variance σ2. Properties of the regression estimator of p are obtained under the assumption that p = ±1. Representations for the limit distributions of the estimator of p and of the regression t test are derived. The estimator of p and the regression t test furnish methods of testing the hypothesis that p = 1.

General atomic and molecular electronic structure system

Abstract: A description of the ab initio quantum chemistry package GAMESS is presented. Chemical systems containing atoms through radon can be treated with wave functions ranging from the simplest closed-shell case up to a general MCSCF case, permitting calculations at the necessary level of sophistication. Emphasis is given to novel features of the program. The parallelization strategy used in the RHF, ROHF, UHF, and GVB sections of the program is described, and detailed speecup results are given. Parallel calculations can be run on ordinary workstations as well as dedicated parallel machines. © John Wiley & Sons, Inc.

Neural Networks for Pattern Recognition

Abstract: Publisher Summary This chapter provides an account of different neural network architectures for pattern recognition. A neural network consists of several simple processing elements called neurons. Each neuron is connected to some other neurons and possibly to the input nodes. Neural networks provide a simple computing paradigm to perform complex recognition tasks in real time. The chapter categorizes neural networks into three types: single-layer networks, multilayer feedforward networks, and feedback networks. It discusses the gradient descent and the relaxation method as the two underlying mathematical themes for deriving learning algorithms. A lot of research activity is centered on learning algorithms because of their fundamental importance in neural networks. The chapter discusses two important directions of research to improve learning algorithms: the dynamic node generation, which is used by the cascade correlation algorithm; and designing learning algorithms where the choice of parameters is not an issue. It closes with the discussion of performance and implementation issues.

A series of normal stages in the development of the chick embryo

Abstract: FORTY-FIVE FIGURES The preparation of a series of normal stages of the chick embryo does not need justification at a time when chick ernbryos are not only widely used in descriptive and experimental embryology but are proving to be increasingly valuable in medical research, as in work on viruses and cancer. The present series was planned in connection with the preparation of a new edition of Lillie’s DeueZopmerzt of the Chick by the junior author. It is being published separately to make it accessible immediately to a large group of workers. Ever since Aristotle “discovered” the chick embryo as the ideal, object for embryological studies, the embryos have been described in terms of the length of time of incubation, and this arbitrary method is still in general use, except for the first three days of incubation during which more detailed characteristics such as the numbers of somites are applied. The shortcomings of a classification based on chronological age are obvious to every worker in this field, for enormous variations may occur in embryos even though all eggs in a setting are plmaced in the incubator at the same time. Many factors are responsible for the lack of correlation between chronological and structural age. Among these are : genetic differences in the rate of development of different breccls (eg., the embryo of the White Leghorn breed develops more 49

Review of Particle Physics

Abstract: This biennial Review summarizes much of particle physics. Using data from previous editions., plus 2778 new measurements from 645 papers, we list, evaluate, and average measured properties of gauge bosons, leptons, quarks, mesons, and baryons. We also summarize searches for hypothetical particles such as Higgs bosons, heavy neutrinos, and supersymmetric particles. All the particle properties and search limits are listed in Summary Tables. We also give numerous tables, figures, formulae, and reviews of topics such as the Standard Model, particle detectors., probability, and statistics. Among the 108 reviews are many that are new or heavily revised including those on CKM quark-mixing matrix, V-ud & V-us, V-cb & V-ub, top quark, muon anomalous magnetic moment, extra dimensions, particle detectors, cosmic background radiation, dark matter, cosmological parameters, and big bang cosmology.