Random-effects regression analysis of correlated grouped-time survival data

Random-effects regression modelling is proposed for analysis of correlated grouped-time survival data. Two analysis approaches are considered. The first treats survival time as an ordinal outcome, which is either right-censored or not. The second approach treats survival time as a set of dichotomous indicators of whether the event occurred for time periods up to the period of the event or censor. For either approach both proportional hazards and proportional odds versions of the random-effects model are developed, while partial proportional hazards and odds generalizations are described for the latter approach. For estimation, a full-information maximum marginal likelihood solution is implemented using numerical quadrature to integrate over the distribution of multiple random effects. The quadrature solution allows some flexibility in the choice of distributions for the random effects; both normal and rectangular distributions are considered in this article. An analysis of a dataset where students are clustered within schools is used to illustrate features of random-effects analysis of clustered grouped-time survival data.     

Numerical simulations of scattering in a two-photon optical data storage system

Scattering effects in a two-photon optical data storage system are numerically studied. Surface scattering analysis with a scalar, beam propagation model is performed. We analyze the problem by modeling scattering from randomly varying surfaces and also by Fourier surface decomposition. Scattering induced by propagation through multiple pages of randomly recorded data marks is also studied with a hybrid finite-difference-time-domain/angular-spectrum model. Both surface and bulk scattering are shown to influence the spatial properties of the optical beam. Results and some possible implications are presented.     

ManyEyes: a site for visualization at internet scale

We describe the design and deployment of Many Eyes, a public web site where users may upload data, create interactive visualizations, and carry on discussions. The goal of the site is to support collaboration around visualizations at a large scale by fostering a social style of data analysis in which visualizations not only serve as a discovery tool for individuals but also as a medium to spur discussion among users. To support this goal, the site includes novel mechanisms for end-user creation of visualizations and asynchronous collaboration around those visualizations. In addition to describing these technologies, we provide a preliminary report on the activity of our users.     

Intense source of spin-polarized electrons

Spin angular momentum conservation in chemiionization reactions involving optically oriented He(2(3)S) atoms in a flowing helium afterglow has been exploited to yield a source of spin-polarized electrons. Either transversely or longitudinally polarized electrons can be extracted. Polarized electron beam currents of approximately 2 muA have been realized at 40% polarization. The beam has an effective emittance of approximately 2 mrad/cm over the energy range 100-400 eV, an energy spread of less, similar0.15 eV, and the polarization is readily reversible. The source is relatively inexpensive and appears suitable for the majority of low-energy spin-dependent scattering experiments proposed to date.     

Mott electron spin polarization analysis system of novel design

A novel Mott polarization analysis system is described. This system is much simpler than earlier designs and offers improved rejection of electrons inelastically scattered from the gold target foil. In addition the analyzer is capable of 'in-line' polarization measurements.     

'Minimum average risk' as a new peak-detection algorithm applied to myofibrillar dynamics

We present a new peak-detection algorithm based on the method of 'minimum average risk' proposed by Kolmogorov and developed for signal processing in various fields. In this method, translations of features within a signal scan are quantified by minimizing the integrated pointwise product of each scan relative to the first derivative of the immediately previous scan. We have adapted this method for use in a new algorithm to monitor dynamic changes of sarcomere length in single myofibrillar sarcomeres of striated muscles, but the algorithm can also be used more generally for peak localization. We find that this method results in sub-nanometer precision and higher signal-to-noise ratio than current methods. At an equal noise level, the RMS deviation of the minimum average risk algorithm was 1.3 times lower than that of the center of mass method with modeled data and 3-4 times lower with actual data.