283 resultados para Farkas lemma
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We have identified verotoxin 1 (VT1) as the active component within an antineoplastic bacteriocin preparation from Escherichia coli HSC10 studied over two decades. Recombinant VT1 can simulate the toxicity of anticancer proteins (ACP), and the antineoplastic activity of ACP (and VT1) was abrogated by treatment with anti-VT1 antibody. Similarly, VT1 mimics the protective effect of ACP in a murine metastatic fibrosarcoma model. Prior immunization with VT1 B subunit prevents the effect of VT1 or ACP in this model. The activity of ACP against a variety of human ovarian cell lines was mimicked by VT1, and multidrug-resistant variants were significantly hypersensitive. Primary ovarian tumors and metastases contain elevated levels of globotriaosylceramide compared with normal ovaries, and overlay of frozen tumor sections showed selective VT binding to tumor tissue and the lumen of invading blood vessels. Our contention that VT1 could provide an additional approach to the management of certain human neoplasms is discussed.
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Mode of access: Internet.
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Mode of access: Internet.
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This article discusses the effects of Wisconsin's community notification statute that authorizes officials to alert residents about the release and reintegration of sex offenders in their communities.
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Available on demand as hard copy or computer file from Cornell University Library.
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With reproduction of original title-pages.
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Errata sheet tipped in at end.
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Mode of access: Internet.
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"December 1994"--P.i.
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We establish maximum principles for second order difference equations and apply them to obtain uniqueness for solutions of some boundary value problems.
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We derive necessary and sufficient conditions for the existence of bounded or summable solutions to systems of linear equations associated with Markov chains. This substantially extends a famous result of G. E. H. Reuter, which provides a convenient means of checking various uniqueness criteria for birth-death processes. Our result allows chains with much more general transition structures to be accommodated. One application is to give a new proof of an important result of M. F. Chen concerning upwardly skip-free processes. We then use our generalization of Reuter's lemma to prove new results for downwardly skip-free chains, such as the Markov branching process and several of its many generalizations. This permits us to establish uniqueness criteria for several models, including the general birth, death, and catastrophe process, extended branching processes, and asymptotic birth-death processes, the latter being neither upwardly skip-free nor downwardly skip-free.
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This article studies the comparative statics of output subsidies for firms, with monotonic preferences over costs and returns, that face price and production uncertainty. The modeling of deficiency payments, support-price schemes, and stochastic supply shifts in a state-space framework is discussed. It is shown how these notions can be used, via a simple application of Shephard's lemma, to analyze input-demand shifts once comparative-static results for supply are available. A range of comparative-static results for supply are then developed and discussed.
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The Australian beef industry places the greatest value in bulls, in comparison to cows, for prime beef production. Male carcasses can be sold for a larger profit due to their increased muscle mass. This project aims to demonstrate the feasibility of producing male animals that can sire male only offspring, through a transgenic approach in mice that could later be translated into livestock production systems. The mouse Sry (Sex determining region on the Y) gene has been shown to provide the initiating molecular signal leading to male sex determination in mammals. Sry has also been shown to cause sex reversal in XX mice transgenic for the gene. In this project Sry will be targeted to a locus not subject to X-inactivation on the X chromosome of XY mice. These mice will be bred to determine how the transgene is passed on, to determine expression of the transgene, and to assess its activity in causing XX sex reversal. The male mice transgenic for the Sry gene on their X chromosome will be produced using tetraploid aggregation, which in a single step produces 100% ES cell derived embryos. The same target locus can later be used to introduce the bovine SRY gene onto the X chromosome of bovidae species and using germ cell transplantation produce sex reversed animals. This would bypass the need for expensive chimera crosses and provide farmers with a stud bull capable of producing only sons.
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Based on a simple convexity lemma, we develop bounds for different types of Bayesian prediction errors for regression with Gaussian processes. The basic bounds are formulated for a fixed training set. Simpler expressions are obtained for sampling from an input distribution which equals the weight function of the covariance kernel, yielding asymptotically tight results. The results are compared with numerical experiments.
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Recently there has been an outburst of interest in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, there is no general consensus as to how best to process sequences using topographicmaps, and this topic remains an active focus of neurocomputational research. The representational capabilities and internal representations of the models are not well understood. Here, we rigorously analyze a generalization of the self-organizingmap (SOM) for processing sequential data, recursive SOM (RecSOM) (Voegtlin, 2002), as a nonautonomous dynamical system consisting of a set of fixed input maps. We argue that contractive fixed-input maps are likely to produce Markovian organizations of receptive fields on the RecSOM map. We derive bounds on parameter β (weighting the importance of importing past information when processing sequences) under which contractiveness of the fixed-input maps is guaranteed. Some generalizations of SOM contain a dynamic module responsible for processing temporal contexts as an integral part of the model. We show that Markovian topographic maps of sequential data can be produced using a simple fixed (nonadaptable) dynamic module externally feeding a standard topographic model designed to process static vectorial data of fixed dimensionality (e.g., SOM). However, by allowing trainable feedback connections, one can obtain Markovian maps with superior memory depth and topography preservation. We elaborate on the importance of non-Markovian organizations in topographic maps of sequential data. © 2006 Massachusetts Institute of Technology.