Co-creating an Adventure Playground (CAP): Reading playwork stories, practices and artefacts, Gloucester: University of Gloucestershire

This report draws on findings from an action research project carried out with an adventure playground (AP) over a six-month period during summer/autumn 2013. The overall intention was to explore the ways in which playwork practitioners at the playground make sense of and give meaning to their practice in designing and maintaining an environment for play. Working collaboratively with members of the play and playwork team at the University of Gloucestershire, adventure playground workers explored current articulations of design intentions and practices drawing on a range of conceptual approaches and tools. This brought a critical and reflective lens to the production of the AP, its everyday rhythms, routines and habits, and the ways in which adults and children co-create play spaces

Development of an Expert System Based on the Systematic Approach to Tropical Cyclone Track Forecasting

LONG-TERM GOALS: The long-term goals of this project are to improve the quantitative accuracy and interpretative utility of official tropical cyclone (TC) track forecasts by enabling forecasters to successfully recognize and skillfully compensate for periods when numerical TC track forecast models are likely to be making highly erroneous track forecasts. The conceptual methodology for accomplishing these goals is the Systematic Approach to Tropical Cyclone Track Forecasting (hereafter Systematic Approach) conceived by Carr and Elsberry (1994).Award # N0001499WR3004

Condensed and Updated Version of the Systematic Approach Meteorological Knowledge Base Southern Hemisphere

The meteorological knowledge base for the Systematic and Integrated Approach to Tropical Cyclone Track Forecasting proposed by Carr and Elsberry has evolved as additional research has been completed. As this Systematic Approach has been applied in the Southern Hemisphere, a number of conceptual models have been refined and new terminology has been adopted to reflect global applicability. As a knowledge-based expert system is being developed, it was convenient to condense and update the meteorological knowledge base for the Southern Hemisphere. Thus, the material is presented with text on the left page and the corresponding figure on the facing page as it will appear on the computer screen.Prepared for: Office of Naval Research, Code 322MM, Arlington, VA 22217 SPAWARSYSCOM, Code PMW 185, San Diego, CA 92110http://archive.org/details/condensedupdated00carrSponsored by: Office of Naval Research and SPAWARSYSCOM.Approved for public release; distribution is unlimited

Kir4.1 Potassium Channel Subunit Is Crucial for Oligodendrocyte Development and In Vivo Myelination

To understand the cellular and in vivo functions of specific K^+ channels in glia, we have studied mice with a null mutation in the weakly inwardly rectifying K^+ channel subunit Kir4.1. Kir4.1−/− mice display marked motor impairment, and the cellular basis is hypomyelination in the spinal cord, accompanied by severe spongiform vacuolation, axonal swellings, and degeneration. Immunostaining in the spinal cord of wild-type mice up to postnatal day 18 reveals that Kir4.1 is expressed in myelin-synthesizing oligodendrocytes, but probably not in neurons or glial fibrillary acidic protein-positive (GFAP-positive) astrocytes. Cultured oligodendrocytes from developing spinal cord of Kir4.1−/− mice lack most of the wild-type K^+ conductance, have depolarized membrane potentials, and display immature morphology. By contrast, cultured neurons from spinal cord of Kir4.1−/− mice have normal physiological characteristics. We conclude that Kir4.1 forms the major K^+ conductance of oligodendrocytes and is therefore crucial for myelination. The Kir4.1 knock-out mouse is one of the few CNS dysmyelinating or demyelinating phenotypes that does not involve a gene directly involved in the structure, synthesis, degradation, or immune response to myelin. Therefore, this mouse shows how an ion channel mutation could contribute to the polygenic demyelinating diseases

A Monadic, Functional Implementation of Real Numbers

Large scale real number computation is an essential ingredient in several modern mathematical proofs. Because such lengthy computations cannot be verified by hand, some mathematicians want to use software proof assistants to verify the correctness of these proofs. This paper develops a new implementation of the constructive real numbers and elementary functions for such proofs by using the monad properties of the completion operation on metric spaces. Bishop and Bridges's notion of regular sequences is generalized to, what I call, regular functions which form the completion of any metric space. Using the monad operations, continuous functions on length spaces (a common subclass of metric spaces) are created by lifting continuous functions on the original space. A prototype Haskell implementation has been created. I believe that this approach yields a real number library that is reasonably efficient for computation, and still simple enough to easily verify its correctness.Comment: This paper is to appear in an upcoming issue of Mathematical Structures in Computer Science published by Cambridge University Press. For more information and the latest source code for Few Digits, see <http://r6.ca/FewDigits/

Matching Visual Saliency to Confidence in Plots of Uncertain Data

Conveying data uncertainty in visualizations is crucial for preventing viewers from drawing conclusions based on untrustworthy data points. This paper proposes a methodology for efficiently generating density plots of uncertain multivariate data sets that draws viewers to preattentively identify values of high certainty while not calling attention to uncertain values. We demonstrate how to augment scatter plots and parallel coordinates plots to incorporate statistically modeled uncertainty and show how to integrate them with existing multivariate analysis techniques, including outlier detection and interactive brushing. Computing high quality density plots can be expensive for large data sets, so we also describe a probabilistic plotting technique that summarizes the data without requiring explicit density plot computation. These techniques have been useful for identifying brain tumors in multivariate magnetic resonance spectroscopy data and we describe how to extend them to visualize ensemble data sets