9,564 research outputs found
Importing Vector Graphics: The grImport Package for R
This article describes an approach to importing vector-based graphical images into statistical software as implemented in a package called grImport for the R statistical computing environment. This approach assumes that an original image can be transformed into a PostScript format (i.e., the original image is in a standard vector graphics format such as PostScript, PDF, or SVG). The grImport package consists of three components: a function for converting PostScript files to an R-specific XML format; a function for reading the XML format into special Picture objects in R; and functions for manipulating and drawing Picture objects. Several examples and applications are presented, including annotating a statistical plot with an imported logo and using imported images as plotting symbols.
Heat shock proteins in tendinopathy: novel molecular regulators
Tendon disorders-tendinopathies-are the primary reason for musculoskeletal consultation in primary care and account for up to 30% of rheumatological consultations. Whilst the molecular pathophysiology of tendinopathy remains difficult to interpret the disease process involving repetitive stress, and cellular load provides important mechanistic insight into the area of heat shock proteins which spans many disease processes in the autoimmune community. Heat shock proteins, also called damage-associated molecular patterns (DAMPs), are rapidly released following nonprogrammed cell death, are key effectors of the innate immune system, and critically restore homeostasis by promoting the reconstruction of the effected tissue. Our investigations have highlighted a key role for HSPs in tendion disease which may ultimately affect tissue rescue mechanisms in tendon pathology. This paper aims to provide an overview of the biology of heat shock proteins in soft tissue and how these mediators may be important regulators of inflammatory mediators and matrix regulation in tendinopathy
Escaping RGBland: Selecting Colors for Statistical Graphics
Statistical graphics are often augmented by the use of color coding information contained in some variable. When this involves the shading of areas (and not only points or lines) - e.g., as in bar plots, pie charts, mosaic displays or heatmaps - it is important that the colors are perceptually based and do not introduce optical illusions or systematic bias. Here, we discuss how the perceptually-based Hue-Chroma-Luminance (HCL) color space can be used for deriving suitable color palettes for coding categorical data (qualitative palettes) and numerical variables (sequential and diverging palettes).Series: Research Report Series / Department of Statistics and Mathematic
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