Search for lepton flavor violating decays of a heavy neutral particle in p-pbar collisions at root(s)=1.8 TeV

We report on a search for a high mass, narrow width particle that decays directly to e+mu, e+tau, or mu+tau. We use approximately 110 pb^-1 of data collected with the Collider Detector at Fermilab from 1992 to 1995. No evidence of lepton flavor violating decays is found. Limits are set on the production and decay of sneutrinos with R-parity violating interactions.Comment: Figure 2 fixed. Reference 4 fixed. Minor changes to tex

Decomposition of semigroup algebras

Let A \subseteq B be cancellative abelian semigroups, and let R be an integral domain. We show that the semigroup ring R[B] can be decomposed, as an R[A]-module, into a direct sum of R[A]-submodules of the quotient ring of R[A]. In the case of a finite extension of positive affine semigroup rings we obtain an algorithm computing the decomposition. When R[A] is a polynomial ring over a field we explain how to compute many ring-theoretic properties of R[B] in terms of this decomposition. In particular we obtain a fast algorithm to compute the Castelnuovo-Mumford regularity of homogeneous semigroup rings. As an application we confirm the Eisenbud-Goto conjecture in a range of new cases. Our algorithms are implemented in the Macaulay2 package MonomialAlgebras.Comment: 12 pages, 2 figures, minor revisions. Package may be downloaded at http://www.math.uni-sb.de/ag/schreyer/jb/Macaulay2/MonomialAlgebras/html

Structural Material Property Tailoring Using Deep Neural Networks

Advances in robotics, artificial intelligence, and machine learning are ushering in a new age of automation, as machines match or outperform human performance. Machine intelligence can enable businesses to improve performance by reducing errors, improving sensitivity, quality and speed, and in some cases achieving outcomes that go beyond current resource capabilities. Relevant applications include new product architecture design, rapid material characterization, and life-cycle management tied with a digital strategy that will enable efficient development of products from cradle to grave. In addition, there are also challenges to overcome that must be addressed through a major, sustained research effort that is based solidly on both inferential and computational principles applied to design tailoring of functionally optimized structures. Current applications of structural materials in the aerospace industry demand the highest quality control of material microstructure, especially for advanced rotational turbomachinery in aircraft engines in order to have the best tailored material property. In this paper, deep convolutional neural networks were developed to accurately predict processing-structure-property relations from materials microstructures images, surpassing current best practices and modeling efforts. The models automatically learn critical features, without the need for manual specification and/or subjective and expensive image analysis. Further, in combination with generative deep learning models, a framework is proposed to enable rapid material design space exploration and property identification and optimization. The implementation must take account of real-time decision cycles and the trade-offs between speed and accuracy

MOBILE and the provision of total joint replacement

Modern joint replacements have been available for 45 years, but we still do not have clear indications for these interventions, and we do not know how to optimize the outcome for patients who agree to have them done. The MOBILE programme has been investigating these issues in relation to primary total hip and knee joint replacements, using mixed methods research

Regional innovation and spillover effects of foreign direct investment in China: a threshold approach

Using a data set on twenty-nine Chinese provinces for the period 1985–2008, this paper establishes a threshold model to analyse the relationship between spillover effects of foreign direct investment (FDI) and regional innovation in China. There is clear evidence of double-threshold effects of regional innovation on productivity spillovers from FDI. Specifically, only when the level of regional innovation reaches the minimum innovation threshold will FDI in the region begin to produce positive productivity spillovers. Furthermore, positive productivity spillovers from FDI will be substantial only when the level of regional innovation attains a higher threshold. The double threshold divides Chinese provinces into three super-regions in terms of innovation, with most provinces positioned within the middle-level innovation super-region. Policy implications are discussed

Helicity Modulus and Fluctuating Type II Superconductors: Elastic Approximation and Numerical Simulations

We develop the helicity modulus as a criterion for superconducting order in the mixed phase of a fluctuating type II superconductor. We show that there is a duality relation between this helicity modulus and the superfluid density of a system of analog 2D bosons. We show that the vortex line lattice exhibits a perfect Meissner effect with respect to a shearing perturbation of the applied magnetic field, and this becomes our creterion for "longitudinal superconductivity" parallel to the applied field. We present arguments based on the 2D boson analogy, as well as the results of numerical simulations, that suggest that longitudinal superconductivity can persist into the vortex line liquid state for systems of finite thickness, comparable to those commonly found in experiments.Comment: 63 pages, 22 postscript figure