Group-structured and independent subspace based dictionary learning

Thanks to the several successful applications, sparse signal representation has become one of the most actively studied research areas in mathematics. However, in the traditional sparse coding problem the dictionary used for representation is assumed to be known. In spite of the popularity of sparsity and its recently emerged structured sparse extension, interestingly, very few works focused on the learning problem of dictionaries to these codes. In the first part of the paper, we develop a dictionary learning method which is (i) online, (ii) enables overlapping group structures with (iii) non-convex sparsity-inducing regularization and (iv) handles the partially observable case. To the best of our knowledge, current methods can exhibit two of these four desirable properties at most. We also investigate several interesting special cases of our framework and demonstrate its applicability in inpainting of natural signals, structured sparse non-negative matrix factorization of faces and collaborative filtering. Complementing the sparse direction we formulate a novel component-wise acting, epsilon-sparse coding scheme in reproducing kernel Hilbert spaces and show its equivalence to a generalized class of support vector machines. Moreover, we embed support vector machines to multilayer perceptrons and show that for this novel kernel based approximation approach the backpropagation procedure of multilayer perceptrons can be generalized. In the second part of the paper, we focus on dictionary learning making use of independent subspace assumption instead of structured sparsity. The corresponding problem is called independent subspace analysis (ISA), or independent component analysis (ICA) if all the hidden, independent sources are one-dimensional. One of the most fundamental results of this research field is the ISA separation principle, which states that the ISA problem can be solved by traditional ICA up to permutation. This principle (i) forms the basis of the state-of-the-art ISA solvers and (ii) enables one to estimate the unknown number and the dimensions of the sources efficiently. We (i) extend the ISA problem to several new directions including the controlled, the partially observed, the complex valued and the nonparametric case and (ii) derive separation principle based solution techniques for the generalizations. This solution approach (i) makes it possible to apply state-of-the-art algorithms for the obtained subproblems (in the ISA example ICA and clustering) and (ii) handles the case of unknown dimensional sources. Our extensive numerical experiments demonstrate the robustness and efficiency of our approach

Development and characterization of a new measurement technique for monitoring changes in acceleration during hippotherapy

Background: The benefi cial effects of hippotherapy lie in the transmission of the horse’s movements to the patient. The aim of our work was to create a measurement method for objective evaluation that can be used in natural settings without interfering with therapy. Methodology/Principal fi ndings: Our measurement system consists of three treble axis accelerometers connected to a data logger. Software was developed for data analysis and post processing. A commercial DVD recording camera was used to document the hippotherapy session. In this paper we present the results obtained in pilot measurements on ten children with cerebral palsy. For reference, a skilled rider was measured on the same horse using a passive following seat. Conclusions: The acceleration diagrams show common characteristics useful to the interpretation of the movement transfer during hippotherapy as well as individual patterns indicating alterations in the movement reactions of different patients

Nucleosome stability measured in situ by automated quantitative imaging

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The risk of fracture and prevalence of osteoporosis is elevated in patients with idiopathic inflammatory myopathies: cross-sectional study from a single Hungarian center

Background: The prevalence of osteoporosis and risk of fractures is elevated in rheumatoid arthritis (RA), but we have limited information about the bone mineral density (BMD) and fracture risk in patients with inflammatory myopathies. We intended to ascertain and compare fracture risk, bone mineral density and the prevalence of vertebral fractures in patients with inflammatory myositis and rheumatoid arthritis and to assess the effect of prevalent fractures on the quality of life and functional capacity. Methods: Fifty-two patients with myositis and 43 patients with rheumatoid arthritis were included in the study. Fracture Risk was determined using FRAX® Calculation Tool developed by the University of Sheffield. Dual energy Xray absorptiometry and bidirectional thoracolumbar radiographs were performed to assess BMD and vertebral fractures. Quality of life was measured with Short Form-36 (SF-36) and physical function assessment was performed using Health Assessment Questionnaire (HAQ). Results: We found a significantly elevated fracture risk in RA as compared to myositis patients if the risk assessment was performed without the inclusion of the BMD results. If BMD results and glucocorticoid dose adjustment were taken into account, the differences in fracture risk were no longer significant. The prevalence of osteoporosis was found to be significantly higher in the myositis group (7% vs. 13.5%, p: 0.045), but the fracture prevalence was similar in the two groups (75% vs. 68%). The fracture rates were independently associated with age in the myositis group, and with lower BMD results in the RA patients. The number of prevalent fractures was significantly correlated to poorer physical function in both groups, and poorer health status in the myositis group, but not in the RA groupConclusions: Our findings suggest that inflammatory myopathies carry significantly elevated risks for osteoporosis and fractures. These higher risks are comparable to ones detected with RA in studies and strongly affect the physical function and quality of life of patients. Therefore further efforts are required to make the fracture risk assessment reliable and to facilitate the use of early preventive treatmentsL

Lithocholic acid, a bacterial metabolite reduces breast cancer cell proliferation and aggressiveness

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