The equalization probability of the Polya urn

We consider a Polya urn, started with b black and w white balls, where b>w. We compute the probability that there are ever the same number of black and white balls in the urn, and show that it is twice the probability of getting no more than w-1 heads in b+w-1 tosses of a fair coin

Isotopic ratios at z=0.68 from molecular absorption lines toward B 0218+357

Isotopic ratios of heavy elements are a key signature of the nucleosynthesis processes in stellar interiors. The contribution of successive generations of stars to the metal enrichment of the Universe is imprinted on the evolution of isotopic ratios over time. We investigate the isotopic ratios of carbon, nitrogen, oxygen, and sulfur through millimeter molecular absorption lines arising in the z=0.68 absorber toward the blazar B 0218+357. We find that these ratios differ from those observed in the Galactic interstellar medium, but are remarkably close to those in the only other source at intermediate redshift for which isotopic ratios have been measured to date, the z=0.89 absorber in front of PKS1830-211. The isotopic ratios in these two absorbers should reflect enrichment mostly from massive stars, and they are indeed close to the values observed toward local starburst galaxies. Our measurements set constraints on nucleosynthesis and chemical evolution models.Comment: Accepted for publication in Astronomy & Astrophysics; 10 pages, 9 figure

Stochastic Motion of an Open Bosonic String

We show that the classical stochastic motion of an open bosonic string leads to the same results as the standard first quantization of this system. For this, the diffusion constant governing the process has to be proportional to \alpha ', the Regge slope parameter, which is the only constant, along with the velocity of light, needed to describe the motion of a string.Comment: Submitted to Phys. Rev. D, 9 pages RevTex, reference removed, no picture

An Implementation of Bayesian Adaptive Regression Splines (BARS) in C with S and R Wrappers

BARS (DiMatteo, Genovese, and Kass 2001) uses the powerful reversible-jump MCMC engine to perform spline-based generalized nonparametric regression. It has been shown to work well in terms of having small mean-squared error in many examples (smaller than known competitors), as well as producing visually-appealing fits that are smooth (filtering out high-frequency noise) while adapting to sudden changes (retaining high-frequency signal). However, BARS is computationally intensive. The original implementation in S was too slow to be practical in certain situations, and was found to handle some data sets incorrectly. We have implemented BARS in C for the normal and Poisson cases, the latter being important in neurophysiological and other point-process applications. The C implementation includes all needed subroutines for fitting Poisson regression, manipulating B-splines (using code created by Bates and Venables), and finding starting values for Poisson regression (using code for density estimation created by Kooperberg). The code utilizes only freely-available external libraries (LAPACK and BLAS) and is otherwise self-contained. We have also provided wrappers so that BARS can be used easily within S or R.

An Implementation of Bayesian Adaptive Regression Splines (BARS) in C with S and R Wrappers

BARS (DiMatteo, Genovese, and Kass 2001) uses the powerful reversible-jump MCMC engine to perform spline-based generalized nonparametric regression. It has been shown to work well in terms of having small mean-squared error in many examples (smaller than known competitors), as well as producing visually-appealing fits that are smooth (filtering out high-frequency noise) while adapting to sudden changes (retaining high-frequency signal). However, BARS is computationally intensive. The original implementation in S was too slow to be practical in certain situations, and was found to handle some data sets incorrectly. We have implemented BARS in C for the normal and Poisson cases, the latter being important in neurophysiological and other point-process applications. The C implementation includes all needed subroutines for fitting Poisson regression, manipulating B-splines (using code created by Bates and Venables), and finding starting values for Poisson regression (using code for density estimation created by Kooperberg). The code utilizes only freely-available external libraries (LAPACK and BLAS) and is otherwise self-contained. We have also provided wrappers so that BARS can be used easily within S or R

Statistical Origin of Quantum Mechanics

The one particle quantum mechanics is considered in the frame of a N-body classical kinetics in the phase space. Within this framework, the scenario of a subquantum structure for the quantum particle, emerges naturally, providing an ontological support to the orthodox quantum mechanics. This approach to quantum mechanics, constitutes a deductive and direct method which, in a self-consistent scheme of a classical kinetics, allows us: i) to obtain the probabilistic nature of the quantum description and to interpret the wave function $\psi$ according to the Copenhagen school; ii) to derive the quantum potential and then the Schr\"odinger equation; iii) to calculate the values of the physical observables as mean values of the associated quantum operators; iv) to obtain the Heisenberg uncertainty principle.Comment: Accepted for publication in Physica

Quantum phases in entropic dynamics

In the Entropic Dynamics framework the dynamics is driven by maximizing entropy subject to appropriate constraints. In this work we bring Entropic Dynamics one step closer to full equivalence with quantum theory by identifying constraints that lead to wave functions that remain single-valued even for multi-valued phases by recognizing the intimate relation between quantum phases, gauge symmetry, and charge quantization.Comment: Presented at MaxEnt 2017, the 37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (July 9-14, 2017, Jarinu, Brazil

Features Missing in Action: Knowledge Management Systems in Practice

This paper presents the results from a multiplecase study of knowledge management systems (KM -systems) in practical use. A set of general problem areas concerning the investigated KM -systems has been identified. These problem areas constitute the starting point of the discussion regarding design implications of KM -systems. One conclusion is that significant functions are missing in the KM -systems. Most of them can be described as traditional personnel administration systems, complemented with features that file competencies. A final conclusion is that the KM -systems’ functions have to be developed and improved, if the organizations’ KM-efforts shall ‘survive’