Clinical staging versus laparotomy and combined modality with MOPP versus ABVD in early-stage hodgkin's disease: the H6 twin randomized trials from the european organization for research and treatment of cancer lymphoma cooperative group

info:eu-repo/semantics/published

Sorting under partial information (without the ellipsoid algorithm)

We revisit the well-known problem of sorting under partial information: sort a finite set given the outcomes of comparisons between some pairs of elements. The input is a partially ordered set P, and solving the problem amounts to discovering an unknown linear extension of P, using pairwise comparisons. The information-theoretic lower bound on the number of comparisons needed in the worst case is log e(P), the binary logarithm of the number of linear extensions of P. In a breakthrough paper, Jeff Kahn and Jeong Han Kim (STOC 1992) showed that there exists a polynomial-time algorithm for the problem achieving this bound up to a constant factor. Their algorithm invokes the ellipsoid algorithm at each iteration for determining the next comparison, making it impractical. We develop efficient algorithms for sorting under partial information. Like Kahn and Kim, our approach relies on graph entropy. However, our algorithms differ in essential ways from theirs. Rather than resorting to convex programming for computing the entropy, we approximate the entropy, or make sure it is computed only once in a restricted class of graphs, permitting the use of a simpler algorithm. Specifically, we present: an O(n2) algorithm performing O(log n·log e(P)) comparisons; an O(n2.5) algorithm performing at most (1+ε) log e(P) + Oε(n) comparisons; an O(n2.5) algorithm performing O(log e(P)) comparisons. All our algorithms are simple to implement. © 2010 ACM.

Development and standardization of solid phase assays for the detection of anti-neutrophil cytoplasmic antibodies (ANCA). A report on the second phase of an international cooperative study on the standardization of ANCA assays

Anti-neutrophil cytoplasmic antibodies (ANCA) are diagnostic markers for systemic vasculitis. They are classically I detected by an indirect immunofluorescence test using normal donor neutrophils as substrate. This assay lacks antigenic specificity and is not quantitative. The 'EC/BCR Project for ANCA Assay Standardization' is an international collaboration study with the aim to develop and standardize solid phase assays for ANCA detection. In this part of the study the isolation and characterization of proteinase-3 and myeloperoxidase, the two main target molecules for ANCA, and the development and standardization of ELISAs with these antigens are described. Six laboratories successfully isolated purified proteinase-3 preparations that could be used. Three of these preparations, together with one myeloperoxidase preparation, were subsequently used for ANCA testing by ELISA. The ELISA technique was standardized in two rounds of testing in the 14 participating laboratories. The coefficient of variation of these new assays decreased from values of approx. 50% in the first round to approx. 20% in the second round. We conclude that purified proteinase-3 and myeloperoxidase can be used in standardized ELISAs for ANCA detection. Whether such procedures offer advantages over the IIF test will be determined in a prospective clinical study.

A regularized iterative algorithm for limited-angle inverse Radon transform

The tomography problem is investigated when the available projections are restricted to a limited angular domain. It is shown that a previous algorithm proposed for extrapolating the data to the missing cone in Fourier space is unstable in the presence of noise because of the ill-posedness of the problem. A regularized algorithm is proposed, which converges to stable solutions. The efficiency of both algorithms is tested by means of numerical simulations. © 1983 Taylor and Francis Group, LLC.

Regularization of an iterative algorithm for the extrapolation of bandlimited signals

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