Smoothing Lipschitz functions

This paper describes a new approach to multivariate scattered data smoothing. It is assumed that the data are generated by a Lipschitz continuous function f, and include random noise to be filtered out. The proposed approach uses known, or estimated value of the Lipschitz constant of f, and forces the data to be consistent with the Lipschitz properties of f. Depending on the assumptions about the distribution of the random noise, smoothing is reduced to a standard quadratic or a linear programming problem. We discuss an efficient algorithm which eliminates the redundant inequality constraints. Numerical experiments illustrate applicability and efficiency of the method. This approach provides an efficient new tool of multivariate scattered data approximation.

Standardizing anthropometric measures in children and adolescents with new functions for egen

A new function for egen has been developed to allow transformation of child anthropometric data to z-scores using the LMS method and the reference data available from the 1990 British Growth Reference and the 2000 US CDC Growth Reference. An additional function allows for children to be categorized according to body mass index (weight/height ²) using international cutoff points recommended by the Childhood Obesity Working Group of the International Obesity Taskforce. Copyright 2004 by StataCorp LP.

Multi-wavelets from B-spline super-functions with approximation order

Approximation order is an important feature of all wavelets. It implies that polynomials up to degree p−1 are in the space spanned by the scaling function(s). In the scalar case, the scalar sum rules determine the approximation order or the left eigenvectors of the infinite down-sampled convolution matrix H determine the combinations of scaling functions required to produce the desired polynomial. For multi-wavelets the condition for approximation order is similar to the conditions in the scalar case. Generalized left eigenvectors of the matrix H_f; a finite portion of H determines the combinations of scaling functions that produce the desired superfunction from which polynomials of desired degree can be reproduced. The superfunctions in this work are taken to be B-splines. However, any refinable function can serve as the superfunction. The condition of approximation order is derived and new, symmetric, compactly supported and orthogonal multi-wavelets with approximation orders one, two, three and four are constructed.

Estimating money demand functions for South Asian countries

In this paper, we estimate a money demand function for a panel of five South Asian countries. We find that the money demand and its determinants, namely real income, real exchange rate and short-term domestic and foreign interest rates are cointegrated both for individual countries as well as for the panel, and panel long-run elasticities provide robust evidence of statistically significant relationships between money demand and its determinants. Our test for panel Granger causality suggests short-run causality running from all variables, except foreign interest rate, to money demand, and we find evidence that except for Nepal money demand functions are stable.

Texture recognition by using GLCM and various aggregation functions

We discuss the problem of texture recognition based on the grey level co-occurrence matrix (GLCM). We performed a number of numerical experiments to establish whether the accuracy of classification is optimal when GLCM entries are aggregated into standard metrics like contrast, dissimilarity, homogeneity, entropy, etc., and compared these metrics to several alternative aggregation methods.We conclude that k nearest neighbors classification based on raw GLCM entries typically works better than classification based on the standard metrics for noiseless data, that metrics based on principal component analysis inprove classification, and that a simple change from the arithmetic to quadratic mean in calculating the standard metrics also improves classification.

Suppressors of cytokine signaling : functions in normal biology and roles in disease

Suppressor of cytokine signaling (SaCS) proteins have been identified as key negative regulators of cytokine and growth factor signaling. Therefore, given the diverse roles played by cytokines and growth factors in development and disease, it is not surprising that the sacs proteins themselves possess equally diverse and important functions, such as the control of hematopoiesis, immune function, growth and placental development. Significantly, more recent studies are increaSingly highlighting the crucial roles played by SOCS proteins in disease, particularly their tumor suppressor and anti-infammatory functions. Collectively, this research has served to confirm the importance of this class of proteins and suggests that therapeutic strategies for modulating SOCS proteins might be relevant for a range of diseases.

Gut health immunomodulatory and anti-inflammatory functions of gut enzyme digested high protein micro-nutrient dietary supplement-Enprocal

Background: Enprocal is a high-protein micro-nutrient rich formulated supplementary food designed to meet the nutritional needs of the frail elderly and be delivered to them in every day foods. We studied the potential of Enprocal to improve gut and immune health using simple and robust bioassays for gut cell proliferation, intestinal integrity/permeability, immunomodulatory, anti-inflammatory and anti-oxidative activities. Effects of Enprocal were compared with whey protein concentrate 80 (WPC), heat treated skim milk powder, and other commercially available milk derived products.

Results: Enprocal (undigested) and digested (Enprocal D) selectively enhanced cell proliferation in normal human intestinal epithelial cells (FHs74-Int) and showed no cytotoxicity. In a dose dependent manner Enprocal induced cell death in Caco-2 cells (human colon adencarcinoma epithelial cells). Digested Enprocal (Enprocal D: gut enzyme cocktail treated) maintained the intestinal integrity in transepithelial resistance (TEER) assay, increased the permeability of horseradish peroxidase (HRP) and did not induce oxidative stress to the gut epithelial cells. Enprocal D upregulated the surface expression of co-stimulatory (CD40, CD86, CD80), MHC I and MHC II molecules on PMA differentiated THP-1 macrophages in coculture transwell model, and inhibited the monocyte/lymphocyte (THP-1/Jurkat E6-1 cells)-epithelial cell adhesion. In cytokine secretion analyses, Enprocal D down-regulated the secretion of proinflammatory cytokines (IL-1β and TNF-α) and up-regulated IFN-γ, IL-2 and IL-10.

Conclusion: Our results indicate that Enprocal creates neither oxidative injury nor cytotoxicity, stimulates normal gut cell proliferation, up regulates immune cell activation markers and may aid in the production of antibodies. Furthermore, through downregulation of proinflammatory cytokines, Enprocal appears to be beneficial in reducing the effects of chronic gut inflammatory diseases such as inflammatory bowel disease (IBD). Stimulation of normal human fetal intestinal cell proliferation without cell cytotoxicity indicates it may also be given as infant food particularly for premature babies.

Ornament colour selection, visual contrast and the shape of colour preference functions in great bowerbirds, Chlamydera nuchalis

A male bowerbird visual signal includes his own plumage, a structure he  constructs out of plant material and coloured objects (ornaments) he places on or near the structure to make up the bower. Plumage and bower together are used to attract females for mating. Ornaments are known to contrast with plumage, bower structure and visual backgrounds in seven Australian bowerbird species (Endler et al. 2005, Evolution, 50, 1795-1818). We estimated the colour preferences in a wild population of great bowerbirds using artificially coloured objects widely spaced in bird colour space. We found that these birds prefer colours that contrast with their own plumage, the bower structure and the visual backgrounds adjacent to the bower, and that they have very strong dislikes for colours that are similar to their own plumage and to the visual backgrounds. The range of disliked colour hues was much narrower than the range of preferred hues, suggesting that the word 'preference' may be misleading. Preferences for colour are inherently multidimensional and should be studied in the context of their function.

Convex hulls in concept induction

Classification learning is dominated by systems which induce large numbers of small axis-orthogonal decision surfaces. This strongly biases such systems towards particular hypothesis types but there is reason believe that many domains have underlying concepts which do not involve axis orthogonal surfaces. Further, the multiplicity of small decision regions mitigates against any holistic appreciation of the theories produced by these systems, notwithstanding the fact that many of the small regions are individually comprehensible. This thesis investigates modeling concepts as large geometric structures in n-dimensional space. Convex hulls are a superset of the set of axis orthogonal hyperrectangles into which axis orthogonal systems partition the instance space. In consequence, there is reason to believe that convex hulls might provide a more flexible and general learning bias than axis orthogonal regions. The formation of convex hulls around a group of points of the same class is shown to be a usable generalisation and is more general than generalisations produced by axis-orthogonal based classifiers, without constructive induction, like decision trees, decision lists and rules. The use of a small number of large hulls as a concept representation is shown to provide classification performance which can be better than that of classifiers which use a large number of small fragmentary regions for each concept. A convex hull based classifier, CH1, has been implemented and tested. CH1 can handle categorical and continuous data. Algorithms for two basic generalisation operations on hulls, inflation and facet deletion, are presented. The two operations are shown to improve the accuracy of the classifier and provide moderate classification accuracy over a representative selection of typical, largely or wholly continuous valued machine learning tasks. The classifier exhibits superior performance to well-known axis-orthogonal-based classifiers when presented with domains where the underlying decision surfaces are not axis parallel. The strengths and weaknesses of the system are identified. One particular advantage is the ability of the system to model domains with approximately the same number of structures as there are underlying concepts. This leads to the possibility of extraction of higher level mathematical descriptions of the induced concepts, using the techniques of computational geometry, which is not possible from a multiplicity of small regions.

Thresholds, incidence functions, and species-specific cues : responses of woodland birds to landscape structure in south-eastern Australia

Looking out from a vantage point across a large tract of forest gives a superficial impression of uniformity: the crowns of canopy trees follow the folds and contours of the landscape to provide a continuous cover of wooded vegetation. But this visual appearance belies the truth: forested landscapes are far from uniform. On closer examination, they comprise a complex mosaic of different vegetation types and and stands of different age-classes, differing structural features, and modified to a varying extent by human land-uses. Forests have a critical role in the conservation of biodiversity throughout the world (Peterken 1996; Laurance and Bierregard 1997; Lindenmayer and Franklin 2002) and a key feature contributing to their conservation value is the response of forest biota to the heterogeneity inherent in forested landscapes (Lindenmayer et al. 2006). Consequently, an understanding of the implications of landscape structure for the maintainance of species and ecological processes is an important foundation for forest management and biodiversity conservation.

Reference functions and balanced concessions in bargaining

In bargaining, agents expect their concessions to be reciprocated. Using the 'reference function' concept of Thomson (1981), this paper constructs a class of solutions the outcomes of which lead to balanced concessions by agents as prescribed by the reference function adopted. The Kalai/Smorodinsky solution arises as a special case. Another solution in this class, which depends on the entire feasible set, is generated by using the centre of gravity as the reference function.