Eliminating Redundant Training Data Using Unsupervised Clustering Techniques

Training data for supervised learning neural networks can be clustered such that the input/output pairs in each cluster are redundant. Redundant training data can adversely affect training time. In this paper we apply two clustering algorithms, ART2 -A and the Generalized Equality Classifier, to identify training data clusters and thus reduce the training data and training time. The approach is demonstrated for a high dimensional nonlinear continuous time mapping. The demonstration shows six-fold decrease in training time at little or no loss of accuracy in the handling of evaluation data

Liquid metal magnetohydrodynamics (LMMHD) technology transfer feasibility study. Volume 2: Appendixes

For abstract, see N74-13466

Liquid metal magnetohydrodynamics (LMMHD) technology transfer feasibility study. Volume 1: Summary

The potential application of liquid metal magnetohydrodynamics (LMMHD) to central station utility power generation through the period to 1990 is examined. Included are: (1) a description of LMMHD and a review of its development status, (2) LMMHD preliminary design for application to central station utility power generation, (3) evaluation of LMMHD in comparison with conventional and other advanced power generation systems and (4) a technology development plan. One of the major conclusions found is that the most economic and technically feasible application of LMMHD is a topping cycle to a steam plant, taking advantage of high temperatures available but not usable by the steam cycle

A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae

All authors are with the Department of Chemical Engineering, The University of Texas at Austin, 200 E Dean Keeton St. Stop C0400, Austin, TX 78712, USA -- Hal S. Alper is with the Institute for Cellular and Molecular Biology, The University of Texas at Austin, 2500 Speedway Avenue, Austin, TX 78712, USA -- Amanda M. Lanza Current Address: Bristol-Myers Squibb, Biologics Development, 35 South Street, Hopkinton, MA 01748, USABackground: Heterologous gene expression is an important tool for synthetic biology that enables metabolic engineering and the production of non-natural biologics in a variety of host organisms. The translational efficiency of heterologous genes can often be improved by optimizing synonymous codon usage to better match the host organism. However, traditional approaches for optimization neglect to take into account many factors known to influence synonymous codon distributions. Results: Here we define an alternative approach for codon optimization that utilizes systems level information and codon context for the condition under which heterologous genes are being expressed. Furthermore, we utilize a probabilistic algorithm to generate multiple variants of a given gene. We demonstrate improved translational efficiency using this condition-specific codon optimization approach with two heterologous genes, the fluorescent protein-encoding eGFP and the catechol 1,2-dioxygenase gene CatA, expressed in S. cerevisiae. For the latter case, optimization for stationary phase production resulted in nearly 2.9-fold improvements over commercial gene optimization algorithms. Conclusions: Codon optimization is now often a standard tool for protein expression, and while a variety of tools and approaches have been developed, they do not guarantee improved performance for all hosts of applications. Here, we suggest an alternative method for condition-specific codon optimization and demonstrate its utility in Saccharomyces cerevisiae as a proof of concept. However, this technique should be applicable to any organism for which gene expression data can be generated and is thus of potential interest for a variety of applications in metabolic and cellular engineering.Chemical EngineeringInstitute for Cellular and Molecular [email protected]

Empirical likelihood confidence intervals and significance test for regression parameters under complex sampling designs

Confidence intervals based on ordinary least squares may have poor coverages for regression parameters when the effect of sampling design is ignored. Standard confidence intervals based on design variances may not have the right coverages when the sampling distribution is skewed. Berger and De La Riva Torres (2012) proposed an empirical likelihood approach which can be used for point estimation and to construct confidence intervals under complex sampling designs for a single parameter. We show that this approach can be extended to test the significance of a subset of model parameters and to derive confidence intervals. The proposed approach is not a straightforward extension of Berger and De La Riva Torres (2012) approach, because we consider the situation when the parameter is multidimensional and the parameter of interest is a subset of the parameter. This requires profiling which is not covered by Berger and De La Riva Torres (2012). The proposed approach intrinsically incorporates sampling weights, design variables, and auxiliary information. It may yield to more accurate confidence intervals when the sampling distribution of the regression parameters is not normal, the point estimator is biased, or the regression model is not linear. The proposed approach is simple to implement and less computer intensive than bootstrap. The proposed approach does not rely on re-sampling, linearisation, variance estimation, or design-effect

Stratifying quotient stacks and moduli stacks

Recent results in geometric invariant theory (GIT) for non-reductive linear algebraic group actions allow us to stratify quotient stacks of the form [X/H], where X is a projective scheme and H is a linear algebraic group with internally graded unipotent radical acting linearly on X, in such a way that each stratum [S/H] has a geometric quotient S/H. This leads to stratifications of moduli stacks (for example, sheaves over a projective scheme) such that each stratum has a coarse moduli space.Comment: 25 pages, submitted to the Proceedings of the Abel Symposium 201

Anomalous behavior of pion production in high energy particle collisions

A shape of invariant differential cross section for charged hadron production as function of transverse momentum measured in various collider experiments is analyzed. Contrary to the behavior of produced charged kaons, protons and antiprotons, the pion spectra require an anomalously high contribution of an exponential term to describe the shape.Comment: 4 pages, 6 figure

Rituximab monitoring and redosing in pediatric neuromyelitis optica spectrum disorder.

Abstract OBJECTIVE: To study rituximab in pediatric neuromyelitis optica (NMO)/NMO spectrum disorders (NMOSD) and the relationship between rituximab, B cell repopulation, and relapses in order to improve rituximab monitoring and redosing. METHODS: Multicenter retrospective study of 16 children with NMO/NMOSD receiving 652 rituximab courses. According to CD19 counts, events during rituximab were categorized as "repopulation," "depletion," or "depletion failure" relapses (repopulation threshold CD19 6510 7 10(6) cells/L). RESULTS: The 16 patients (14 girls; mean age 9.6 years, range 1.8-15.3) had a mean of 6.1 events (range 1-11) during a mean follow-up of 6.1 years (range 1.6-13.6) and received a total of 76 rituximab courses (mean 4.7, range 2-9) in 42.6-year cohort treatment. Before rituximab, 62.5% had received azathioprine, mycophenolate mofetil, or cyclophosphamide. Mean time from rituximab to last documented B cell depletion and first repopulation was 4.5 and 6.8 months, respectively, with large interpatient variability. Earliest repopulations occurred with the lowest doses. Significant reduction between pre- and post-rituximab annualized relapse rate (ARR) was observed (p = 0.003). During rituximab, 6 patients were relapse-free, although 21 relapses occurred in 10 patients, including 13 "repopulation," 3 "depletion," and 4 "depletion failure" relapses. Of the 13 "repopulation" relapses, 4 had CD19 10-50 7 10(6) cells/L, 10 had inadequate monitoring ( 641 CD19 in the 4 months before relapses), and 5 had delayed redosing after repopulation detection. CONCLUSION: Rituximab is effective in relapse prevention, but B cell repopulation creates a risk of relapse. Redosing before B cell repopulation could reduce the relapse risk further. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that rituximab significantly reduces ARR in pediatric NMO/NMOSD. This study also demonstrates a relationship between B cell repopulation and relapses

Higher-Order QCD Corrections to Inclusive Particle Production in p anti-p Collisions

Inclusive single-particle production cross sections have been calculated including higher-order QCD corrections. Transverse-momentum and rapidity distributions are presented and the scale dependence is studied. The results are compared with experimental data from the CERN S(p anti-p)S Collider and the Fermilab Tevatron.Comment: 28 pages, [12 uuencoded PS figures, 3 available under request]. Preprint DESY 92-13