Cancer statistics, 1998

The Surveillance Research Program of the American Cancer Society's Department of Epidemiology and Surveillance reports its 32nd annual compilation of cancer incidence, mortality, and survival data for the United States and around the world.     

AnyBoard: an FPGA-based, reconfigurable system

AnyBoard, a low-cost, field programmable gate array (FPGA)-based, reconfigurable rapid-prototyping system is described. The system hardware organization and software tools that help users automatically map designs to the FPGAs and manage the design process are discussed. The implementation of a pattern generator design is presented to illustrate the system's effectiveness     

Cancer surveillance in the U.S.: can we have a national system?

Cancer-related services are consuming ever-increasing health resources; along with this trend, health care costs are rising. As health care planners, researchers, and policymakers formulate strategies to meet this challenge, they are looking to cancer registries and the health information system built around them as collectors of the most extensive information regarding cancer treatment in the U.S. Currently, there are multiple programs collecting and reporting data regarding cancer incidence, morbidity, mortality, and survival. This report profiles cancer surveillance efforts in the U.S. and describes the National Coordinating Council for Cancer Surveillance, which was organized in 1995 to facilitate a collaborative approach among the organizations involved.     

Solution of the Three-Parameter Weibull Equations by Constrained Modified Quasilinearization (Progressively Censored Samples)

The location, shape, and scale parameters of the Weibull distribution are estimated from Type I progressively censored samples by the method of maximum likelihood. Nonlinear logarithmic likelihood estimating equations are derived, and the approximate asymptotic variance-covariance matrix for the maximum likelihood parameter estimates is given. The iterative procedure to solve the likelihood equations is a stable and rapidly convergent constrained modified quasilinearization algorithm which is applicable to the general case in which all three parameters are unknown. The numerical results indicate that, in terms of the number of iterations required for convergence and in the accuracy of the solution, the proposed algorithm is a very effective technique for solving systems of logarithmic likelihood equations for which all iterative approximations to the solution vector must satisfy certain intrinsic constraints on the parameters. A FORTRAN IV program implementing the maximum likelihood estimation procedure is included.     

Image-based collision detection for deformable cloth models

Modeling the natural interaction of cloth and garments with objects in a 3D environment is currently one of the most computationally demanding tasks. These highly deformable materials are subject to a very large number of contact points in the proximity of other moving objects. Furthermore, cloth objects often fold, roll, and drape within themselves, generating a large number of self-collision areas. The interactive requirements of 3D games and physically driven virtual environments make the cloth collisions and self-collision computations more challenging. By exploiting mathematically well-defined smoothness conditions over smaller patches of deformable surfaces and resorting to image-based collision detection tests, we developed an efficient collision detection method that achieves interactive rates while tracking self-interactions in highly deformable surfaces consisting of a large number of elements. The method makes use of a novel technique for dynamically generating a hierarchy of cloth bounding boxes in order to perform object-level culling and image-based intersection tests using conventional graphics hardware support. An efficient backward voxel-based AABB hierarchy method is proposed to handle deformable surfaces which are highly compressed.     

Fenton-driven regeneration of MTBE-spent granular activated carbon—Effects of particle size and iron amendment procedures

Fenton-driven regeneration of spent granular activated carbon (GAC) can be used to regenerate organic contaminant-spent GAC. In this study, the effects of GAC particle size (>2 mm to <0.35 mm) and acid pre-treatment of GAC on Fenton-driven oxidation of methyl-tert-butyl ether (MTBE)-spent GAC were evaluated. Iron (Fe) was amended to the GAC using two methods: (1) untreated—where GAC was amended with a concentrated solution of ferrous sulfate and (2) acid pre-treatment—where GAC was amended with acid followed by sequential applications of a dilute ferrous sulfate solution. Subsequently, MTBE was amended to the GAC, followed by oxidative treatments with H₂O₂. H₂O₂ reaction and MTBE oxidation were inversely correlated with GAC particle size and were attributed to shorter intraparticle diffusion transport distances for both H₂O₂ and MTBE. Image analysis of the GAC cross-sections (i.e., prepared thin sections) revealed that the Fe amended to the GAC extended to the center of the GAC particles. Fe accumulated at higher levels on the periphery of the untreated GAC but Fe dispersal was more uniform in the acid pre-treated GAC. In the acid pre-treated GAC, conditions for MTBE oxidation were favorable and greater levels of MTBE oxidation were measured for all particle size fractions tested. Modeling and critical analysis of H₂O₂ diffusive transport and reaction indicated limited H₂O₂ penetration into large GAC particles which contributed to a decline in MTBE removal. Residual MTBE remaining on the GAC limited the quantity of MTBE that could be re-adsorbed, but no reduction in MTBE sorption capacity resulted from oxidative treatments.     

Physical activity, functional limitations, and the risk of fall-related fractures in community-dwelling elderly

The ability of positron emission tomography (PET) to serve as a useful myocardial perfusion indicator is well established. We describe a methodology for obtaining reliable quantitative kinetic parameters from dynamic cardiac PET data. Reconstructed images of the myocardium are subdivided into three-dimensional volumes of interest which are used to obtain quantitative measures of myocardial perfusion over physiologically meaningful anatomical regions. The quantitation technique rigorously models the uncertainty of estimated parameters while compensating for effects such as patient motion and partial volumes to arrive at model parameters with well-established confidence intervals.     

Maximum likelihood estimation of exponential distribution parameters using interval data

This paper addresses the problem of estimating, by the method of maximum likelihood (ML), the location parameter (when present) and scale parameter of the exponential distribution (ED) from interval data. Interval data are defined as two data values that surround an unknown failure observation. Such observations occur naturally, during periodic inspections, for example, when only the time interval during which the failure occurred is known. The appropriate (conditional) log-likelihood functions are derived, as are expressions for the asymptotic variances and covariances of the ML parameter estimates. To illustrate the calculations involved, two numerical examples are discussed.