Analysis of multiparticle production data on proton-nucleus collisions using a new variable

Multiparticle production data on proton-nucleus collisions have been analyzed taking the number of ‘created’ charged particles instead of the observed number of shower particles as the variable. The mean normalized multiplicity,R _A , has been found to be independent of energy in the energy range (7–8000) GeV and its mass number dependence has been obtained. The modified analysis introduces some more regularities in the experimental results onp-nucleus collisions like the invariance with respect to energy of the relationshipR _A = α + βN _h and the KNO-like scaling of the multiplicity distributions of the created charged particles. The functional form of the scaling function has been calculated.     

Generalized nonlinear master equations for local fluctuations: Dimensionality expansions and augmented mean field theory

By application of a projection operator technique we derive a formally exact generalization of the nonlinear mean field master equation introduced recently for the study of local fluctuations in a reacting medium. Our starting point is a phenomenological cell master equation. The results of our theory are applicable to the theory of a fluctuating hydrodynamic reacting system. The mean field equation is placed on a firm theoretical foundation by showing it to be the lowest order approximation in an expansion in the dimensionality of the physical space keeping the product of the number of nearest neighbors (an increasing function of dimensionality) and the typical diffusion coefficient constant. A more accurate nonlinear master equation that allows for the correlation and fluctuations in the environment of a given volume element is derived in the form of an augmented mean field equation.Work supported in part by a grant from the National Science Foundation.     

Measurement of small spin-spin splittings in the presence of chemical exchange: case of deuteriated water

A new implementation of a described data processing for measuring small scalar coupling constant J is proposed. It is applied particularly to situations where the coupling constant is around the linewidth at half-height, and in the presence of chemical exchange. This modified data processing uses only a simple "one-pulse" experiment instead of a series of spin echoes experiments required by the previous processing. The FID recorded in the one pulse experiment is used by a reconstitution program to generate a set of signals, which are analyzed in the time domain to obtain a spectrum where the scalar coupling constant is apparently multiplied by n+1, where n is positive. The new processing is tested with simulated spectra. The coupling constant between proton and deuterium is measured in the proton spectrum of a solution of 80% of D(2)O and 20% of H(2)O. It was found to be J=1.54+/-0.01 Hz.     

Divergent Cesàro and Riesz means of Jacobi and Laguerre expansions

We show that for below certain critical indices there are functions whose Jacobi or Laguerre expansions have almost everywhere divergent Cesàro and Riesz means of order .

     

ESR spectroscopy as a tool for identifying joining fragments of antique marbles: the example of a pulpit by Donatello and Michelozzo

ESR spectroscopy is one of the physicochemical techniques used to characterize archaeological white marbles and obtain information about their quarries of provenance. This is done by measuring selected spectral features of the Mn(2+) impurity ubiquitously present in marbles and developing a statistical classification rule from the variable vectors measured for a significant number of samples of known provenance (the quarry database). Now we show that the overall variability exhibited by the same spectroscopic features decreases rapidly with the linear dimensions of the sampled block and can be used to distinguish fragments belonging to the same piece of stone from those simply originating from the same quarry. Application of the method to the seven marble panels of the Donatello pulpit in Prato (Tuscany) shows that they have all been cut from the same single block and their different degradation must be ascribed to differential weathering and to the different conservation treatments undergone in the past. The limits and possible drawbacks of the method are also discussed.     

Broad distributions from resource partitioning

We present a model describing a generic process in which a finite resource is partitioned and distributed among agents. Through numerical simulation we show that the model considered is able to originate, within a unifying approach, a variety of broad distributions and provides an interpretation of empirical properties of distributions observed in the real world. In particular it allows to relate the exponent of the power-law part of the distributions to resource abundance and accessibility, while the left-end exponential behavior, observed in many distributions, is related to the presence of dissipative effects.     

与Euler函数有关的误差项均值估计

设ψ(n)是Euler函数,r是正实数.以E(x,r)表示和式的渐近公式中的误差项,本文研究了E(x,r)的算术均值和积分均值.     

On Cesàro Means of Double Trigonometric Fourier Series

Zhizhiashvili studied questions associated with the approximation properties of Cesàro means of trigonometric Fourier series for functions of two variables in the spaces H. It is proved here that the corresponding estimate cannot be improved for p = 1 or p = .     

Asset pricing for an affine jump‐diffusion model using an FD method of lines on nonuniform meshes

We present a novel numerical scheme for the valuation of options under a well‐known jump‐diffusion model. European option pricing for such a case satisfies a 1 + 2 partial integro‐differential equation (PIDE) including a double integral term, which is nonlocal. The proposed approach relies on nonuniform meshes with a focus on the discontinuous and degenerate areas of the model and applying quadratically convergent finite difference (FD) discretizations via the method of lines (MOL). A condition for observing the time stability of the fully discretized problem is given. Also, we report results of numerical experiments.     

A Bootstrap Framework for Aggregating within and between Feature Selection Methods

In the past decade, big data has become increasingly prevalent in a large number of applications. As a result, datasets suffering from noise and redundancy issues have necessitated the use of feature selection across multiple domains. However, a common concern in feature selection is that different approaches can give very different results when applied to similar datasets. Aggregating the results of different selection methods helps to resolve this concern and control the diversity of selected feature subsets. In this work, we implemented a general framework for the ensemble of multiple feature selection methods. Based on diversified datasets generated from the original set of observations, we aggregated the importance scores generated by multiple feature selection techniques using two methods: the Within Aggregation Method (WAM), which refers to aggregating importance scores within a single feature selection; and the Between Aggregation Method (BAM), which refers to aggregating importance scores between multiple feature selection methods. We applied the proposed framework on 13 real datasets with diverse performances and characteristics. The experimental evaluation showed that WAM provides an effective tool for determining the best feature selection method for a given dataset. WAM has also shown greater stability than BAM in terms of identifying important features. The computational demands of the two methods appeared to be comparable. The results of this work suggest that by applying both WAM and BAM, practitioners can gain a deeper understanding of the feature selection process.