Introducing the discussion paper by Sz\'{e}kely and Rizzo

Introducing the discussion paper by Sz\'{e}kely and RizzoComment: Published in at http://dx.doi.org/10.1214/09-AOAS34INTRO the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

The Optimum Distance at which to Determine the Size of a Giant Air Shower

To determine the size of an extensive air shower it is not necessary to have knowledge of the function that describes the fall-off of signal size from the shower core (the lateral distribution function). In this paper an analysis with a simple Monte Carlo model is used to show that an optimum ground parameter can be identified for each individual shower. At this optimal core distance, $r_\mathrm{opt}$, the fluctuations in the expected signal, $S(r_\mathrm{opt})$, due to a lack of knowledge of the lateral distribution function are minimised. Furthermore it is shown that the optimum ground parameter is determined primarily by the array geometry, with little dependence on the energy or zenith angle of the shower or choice of lateral distribution function. For an array such as the Pierre Auger Southern Observatory, with detectors separated by 1500 m in a triangular configuration, the optimum distance at which to measure this characteristic signal is close to 1000 m

Evolving macro-actions for planning

Domain re-engineering through macro-actions (i.e. macros) provides one potential avenue for research into learning for planning. However, most existing work learns macros that are reusable plan fragments and so observable from planner behaviours online or plan characteristics offline. Also, there are learning methods that learn macros from domain analysis. Nevertheless, most of these methods explore restricted macro spaces and exploit specific features of planners or domains. But, the learning examples, especially that are used to acquire previous experiences, might not cover many aspects of the system, or might not always reflect that better choices have been made during the search. Moreover, any specific properties are not likely to be common with many planners or domains. This paper presents an offline evolutionary method that learns macros for arbitrary planners and domains. Our method explores a wider macro space and learns macros that are somehow not observable from the examples. Our method also represents a generalised macro learning framework as it does not discover or utilise any specific structural properties of planners or domains

CD28 and T cell antigen receptor signal transduction coordinately regulate interleukin 2 gene expression in response to superantigen stimulation.

Activation of an immune response requires intercellular contact between T lymphocytes and antigen-presenting cells (APC). Interaction of the T cell antigen receptor (TCR) with antigen in the context of major histocompatibility molecules mediates signal transduction, but T cell activation appears to require the induction of a second costimulatory signal transduction pathway. Recent studies suggest that interaction of CD28 with B7 on APC might deliver such a costimulatory signal. To investigate the role of CD28 signal transduction during APC-dependent T cell activation, we have used Staphylococcal enterotoxins (SEs) presented by a B7-positive APC. We used anti-B7 monoclonal antibodies and a mutant interleukin 2 (IL-2) promoter construct, unresponsive to CD28-generated signals, in transient transfection assays to examine the contribution of the CD28-B7 interaction to IL-2 gene activation. These studies indicate that the CD28-regulated signal transduction pathway is activated during SE stimulation of T cells and plays an important role in SE induction of IL-2 gene expression through its influence upon the CD28-responsive element contained within the IL-2 gene promoter. This effect is particularly profound in the activation of the IL-2 gene in peripheral blood T cells

Gamma-based clustering via ordered means with application to gene-expression analysis

Discrete mixture models provide a well-known basis for effective clustering algorithms, although technical challenges have limited their scope. In the context of gene-expression data analysis, a model is presented that mixes over a finite catalog of structures, each one representing equality and inequality constraints among latent expected values. Computations depend on the probability that independent gamma-distributed variables attain each of their possible orderings. Each ordering event is equivalent to an event in independent negative-binomial random variables, and this finding guides a dynamic-programming calculation. The structuring of mixture-model components according to constraints among latent means leads to strict concavity of the mixture log likelihood. In addition to its beneficial numerical properties, the clustering method shows promising results in an empirical study.Comment: Published in at http://dx.doi.org/10.1214/10-AOS805 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Magnetic cylindrical colloids at liquid interfaces exhibit non-volatile switching of their orientation in an external field

We study the orientation of magnetic cylindrical particles adsorbed at a liquid interface in an external field using analytical theory and high resolution finite element simulations. Cylindrical particles are interesting since they possess multiple locally stable orientations at the liquid interface so that the orientational transitions induced by an external field will not disappear when the external field is removed, i.e., the switching effect is \emph{non-volatile}. We show that, in the absence of an external field, as we reduce the aspect ratio $\alpha$ of the cylinders below a critical value ($\alpha_c \approx 2$) the particles undergo spontaneous symmetry breaking from a stable side-on state to one of two equivalent stable tilted states, similar to the spontaneous magnetisation of a ferromagnet going through the Curie point. By tuning both the aspect ratio and contact angle of the cylinders, we show that it is possible to engineer particles that have one, two, three or four locally stable orientations. We also find that the magnetic responses of cylinders with one or two stable states are similar to that of paramagnets and ferromagnets respectively, while the magnetic response of systems with three or four stable states are even more complex and have no analogs in simple magnetic systems. Magnetic cylinders at liquid interfaces therefore provide a facile method for creating switchable functional monolayers where we can use an external field to induce multiple non-volatile changes in particle orientation and self-assembled structure

My word is my bond ; reputation as collateral in nineteenth century English provincial banking

There are few real-world economic transactions that do not involve an element of trust, yet in textbook economics trust is not prominently discussed. In that world, perfectly informed and computationally endowed agents reach optimal, enforceable decisions in continuously harmonizing exchanges. Trust is therefore linked to deviations from the textbook ideal: incomplete information, costly enforcement, and computational limitations faced by agents. Trust can then be thought of as an algorithm, in other words, a way of resolving uncertainty in a complex world. In this sense trust may be seen as a form of expectation concerning the behavior of other agents whose actions and intentions cannot be (fully) observed. This paper pursues this approach by “running the algorithm backwards” and trying to establish what factors led a 19th century provincial English bank to trust different loan applicants. Using a data-set of some 200 loan decisions, and knowing the size of collateral (if any) requested, we develop a method to estimate the probability that the bank attached to each borrower’s promise to repay (i.e., the trust the bank had towards the borrower), adjusting for stages in the business cycle. We then regress this estimated probability on a variety of observable borrower characteristics. We find that trust is not correlated with a priori expected variables, such as borrower’s assets or frequency of interaction. This suggests that trust was built up in other interactions, possibly through social or religious networks, and that the banking relationship reflected information available to bank directors other than what was purely pertinent to the borrowers’ economic conditions. This has strong implications for the allocation of credit to industry in 19th century England.