The National union catalog, pre-1956 imprints ; a cumulative author list representing Library of Congress printed cards and titles reported by other American libraries /

Vols. 686-754 comprise a supplement.

Three horizontal muscle squint surgery for large angle infantile esotropia

Background: To report the long-term outcome of a series of 49 patients who underwent three horizontal muscle squint surgery for large angle infantile esotropia. Methods: The patient records were retrospectively reviewed of 49 (24 girls [49%], 25 boys) consecutive patients with infantile esotropia of angle greater than or equal to60 Delta, who had undergone three horizontal muscle surgery performed by one surgeon (author GG). Surgery consisted of bilateral medial rectus recession combined with graded unilateral lateral rectus resection. Surgeries were carried out over a 6-year period with a mean follow-up period of 32.9 months (3.7-71.8 months). Results: Using Kaplan-Meier life-table analysis, cumulative surgical success (orthotropia +/-10 Delta) was 93.9% at 1 week, 91.8% at 2 and 6 months, 87.7% at 12 and 18 months, 79.9% at 2 years, 77.1% at 3, 4 and 5 years, and 70.6% at 6 years. The mean preoperative deviation was 68.7 Delta. The mean age at surgery was 12.9 months. The failure rate was independent of preoperative deviation. Prevalence of residual esotropia (>10 Delta) varied from 2.0% at 1 week to 17.0% at 6 years. Similarly the prevalence of consecutive exotropia (>10 Delta) varied from 4.0% at 1 week to 12.4% at 6 years. Conclusion: Operating in a graded fashion on three horizontal muscles in children with large angle infantile esotropia has a high success rate, even over long-term follow up. Based on the study's results, amounts of surgery for a given angle of strabismus are proposed.

Pseudo memory effects, majorization and entropy in quantum random walks

A quantum random walk on the integers exhibits pseudo memory effects, in that its probability distribution after N steps is determined by reshuffling the first N distributions that arise in a classical random walk with the same initial distribution. In a classical walk, entropy increase can be regarded as a consequence of the majorization ordering of successive distributions. The Lorenz curves of successive distributions for a symmetric quantum walk reveal no majorization ordering in general. Nevertheless, entropy can increase, and computer experiments show that it does so on average. Varying the stages at which the quantum coin system is traced out leads to new quantum walks, including a symmetric walk for which majorization ordering is valid but the spreading rate exceeds that of the usual symmetric quantum walk.

Teleonomic entropy: measuring the phase-space of end-directed systems

We introduce a novel way of measuring the entropy of a set of values undergoing changes. Such a measure becomes useful when analyzing the temporal development of an algorithm designed to numerically update a collection of values such as artificial neural network weights undergoing adjustments during learning. We measure the entropy as a function of the phase-space of the values, i.e. their magnitude and velocity of change, using a method based on the abstract measure of entropy introduced by the philosopher Rudolf Carnap. By constructing a time-dynamic two-dimensional Voronoi diagram using Voronoi cell generators with coordinates of value- and value-velocity (change of magnitude), the entropy becomes a function of the cell areas. We term this measure teleonomic entropy since it can be used to describe changes in any end-directed (teleonomic) system. The usefulness of the method is illustrated when comparing the different approaches of two search algorithms, a learning artificial neural network and a population of discovering agents. (C) 2004 Elsevier Inc. All rights reserved.

The psychotogenic effects of cannabis use: challenges in reducing residual uncertainties and communicating the risks

No Abstract

A tutorial on the cross-entropy method

The cross-entropy (CE) method is a new generic approach to combinatorial and multi-extremal optimization and rare event simulation. The purpose of this tutorial is to give a gentle introduction to the CE method. We present the CE methodology, the basic algorithm and its modifications, and discuss applications in combinatorial optimization and machine learning. combinatorial optimization

The cross-entropy method for network reliability estimation

Consider a network of unreliable links, modelling for example a communication network. Estimating the reliability of the network-expressed as the probability that certain nodes in the network are connected-is a computationally difficult task. In this paper we study how the Cross-Entropy method can be used to obtain more efficient network reliability estimation procedures. Three techniques of estimation are considered: Crude Monte Carlo and the more sophisticated Permutation Monte Carlo and Merge Process. We show that the Cross-Entropy method yields a speed-up over all three techniques.

Application of the cross-entropy method to the buffer allocation problem in a simulation-based environment

The buffer allocation problem (BAP) is a well-known difficult problem in the design of production lines. We present a stochastic algorithm for solving the BAP, based on the cross-entropy method, a new paradigm for stochastic optimization. The algorithm involves the following iterative steps: (a) the generation of buffer allocations according to a certain random mechanism, followed by (b) the modification of this mechanism on the basis of cross-entropy minimization. Through various numerical experiments we demonstrate the efficiency of the proposed algorithm and show that the method can quickly generate (near-)optimal buffer allocations for fairly large production lines.

Heavy tails, importance sampling and cross-entropy

We consider the problem of estimating P(Yi + (...) + Y-n > x) by importance sampling when the Yi are i.i.d. and heavy-tailed. The idea is to exploit the cross-entropy method as a toot for choosing good parameters in the importance sampling distribution; in doing so, we use the asymptotic description that given P(Y-1 + (...) + Y-n > x), n - 1 of the Yi have distribution F and one the conditional distribution of Y given Y > x. We show in some specific parametric examples (Pareto and Weibull) how this leads to precise answers which, as demonstrated numerically, are close to being variance minimal within the parametric class under consideration. Related problems for M/G/l and GI/G/l queues are also discussed.

Pathological complete response and residual DCIS following neoadjuvant chemotherapy for breast carcinoma

Patients who have no residual invasive cancer following neoadjuvant chemotherapy for breast carcinoma have a better overall survival than those with residual disease. Many classification systems assessing pathological response to neoadjuvant chemotherapy include residual ductal carcinoma in situ (DCIS) only in the definition of pathological complete response. The purpose of this study was to investigate whether patients with residual DCIS only have the same prognosis as those with no residual invasive or in situ disease. A retrospective analysis of a prospectively maintained database identified 435 patients, who received neoadjuvant chemotherapy for operable breast cancer between February 1985 and February 2003. Of these, 30 (7%; 95% CI 5-9%) had no residual invasive disease or DCIS and 20 (5%; CI 3-7%) had residual DCIS only. With a median follow-up of 61 months, there was no statistical difference in disease-free survival, 80% (95% CI 60-90%) in those with no residual invasive or in situ disease and 61% (95% CI 35-80%) in those with DCIS only (P = 0.4). No significant difference in 5-year overall survival was observed, 93% (95% CI 75-98%) in those with no residual invasive or in situ disease and 82% (95% CI 52-94%) in those with DCIS only (P = 0.3). Due to the small number of patients and limited number of events in each group, it is not possible to draw definitive conclusions from this study. Further analyses of other databases are required to confirm our finding of no difference in disease-free and overall survival between patients with residual DCIS and those with no invasive or in situ disease following neoadjuvant chemotherapy for breast cancer.

The cross-entropy method for continuous multi-extremal optimization

In recent years, the cross-entropy method has been successfully applied to a wide range of discrete optimization tasks. In this paper we consider the cross-entropy method in the context of continuous optimization. We demonstrate the effectiveness of the cross-entropy method for solving difficult continuous multi-extremal optimization problems, including those with non-linear constraints.