An almost sure limit theorem for super-Brownian motion

We establish an almost sure scaling limit theorem for super-Brownian motion on $\mathbb{R}^d$ associated with the semi-linear equation $u_t = {1/2}\Delta u +\beta u-\alpha u^2$, where $\alpha$ and $\beta$ are positive constants. In this case, the spectral theoretical assumptions that required in Chen et al (2008) are not satisfied. An example is given to show that the main results also hold for some sub-domains in $\mathbb{R}^d$.Comment: 14 page

Machine learning-based investigation of the association between CMEs and filaments

YesIn this work we study the association between eruptive filaments/prominences and coronal mass ejections (CMEs) using machine learning-based algorithms that analyse the solar data available between January 1996 and December 2001. The Support Vector Machine (SVM) learning algorithm is used for the purpose of knowledge extraction from the association results. The aim is to identify patterns of associations that can be represented using SVM learning rules for the subsequent use in near real-time and reliable CME prediction systems. Timing and location data in the NGDC filament catalogue and the SOHO/LASCO CME catalogue are processed to associate filaments with CMEs. In the previous studies which classified CMEs into gradual and impulsive CMEs, the associations were refined based on CME speed and acceleration. Then the associated pairs were refined manually to increase the accuracy of the training dataset. In the current study, a data- mining system has been created to process and associate filament and CME data, which are arranged in numerical training vectors. Then the data are fed to SVMs to extract the embedded knowledge and provide the learning rules that could have the potential, in the future, to provide automated predictions of CMEs. The features representing the event time (average of the start and end times), duration, type and extent of the filaments are extracted from all the associated and not-associated filaments and converted to a numerical format that is suitable for SVM use. Several validation and verification methods are used on the extracted dataset to determine if CMEs can be predicted solely and efficiently based on the associated filaments. More than 14000 experiments are carried out to optimise the SVM and determine the input features that provide the best performance

Single and double electron capture in collisions of highly ionized, decelerated Ge ions with Ne

SIGLEAvailable from TIB Hannover: RO 801(92-16) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

Scaling behavior of nucleotide cluster in DNA sequences

In this paper we study the scaling behavior of nucleotide cluster in 11 chromosomes of Encephalitozoon cuniculi Genome. The statistical distribution of nucleotide clusters for 11 chromosomes is characterized by the scaling behavior of P(S)∝e(−αS), where S represents nucleotide cluster size. The cluster-size distribution P(S (1)+S (2)) with the total size of sequential C-G cluster and A-T cluster S (1)+S (2) were also studied. P(S (1)+S (2)) follows exponential decay. There does not exist the case of large C-G cluster following large A-T cluster or large A-T cluster following large C-G cluster. We also discuss the relatively random walk length function L(n) and the local compositional complexity of nucleotide sequences based on a new model. These investigations may provide some insight into nucleotide cluster of DNA sequence

Collective motion in nucleus-nucleus collisions at 800 MeV/nucleon

SIGLEAvailable from Gesellschaft fuer Schwerionenforschung m.b.H. (GSI), Darmstadt (DE) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman