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Mechanisms of human color vision are characterized by two phenomenological aspects: the system is nonlinear and adaptive to changing environments. Conventional attempts to derive these features from statistics use separate arguments for each aspect. The few statistical explanations that do consider both phenomena simultaneously follow parametric(More)
This paper presents a new framework for manifold learning based on a sequence of principal polynomials that capture the possibly nonlinear nature of the data. The proposed Principal Polynomial Analysis (PPA) generalizes PCA by modeling the directions of maximal variance by means of curves, instead of straight lines. Contrarily to previous approaches, PPA(More)
Principal Component Analysis (PCA) has been widely used for manifold description and dimensionality reduction. Performance of PCA is however hampered when data exhibits nonlinear feature relations. In this work, we propose a new framework for manifold learning based on the use of a sequence of Principal Polynomials that capture the eventually nonlinear(More)
The in vitro antiproliferative and antioxidant effects of different fractions of Rosa canina hips on human colon cancer cell lines (Caco-2) was studied. The compounds tested were total extract (fraction 1), vitamin C (fraction 2), neutral polyphenols (fraction 3) and acidic polyphenols (fraction 4). All the extracts showed high cytotoxicity after 72 h, both(More)
See Aubourg (doi:10.1093/awv271) for a scientific commentary on this article.X-linked adrenoleukodystrophy is caused by mutations in the ABCD1 gene leading to accumulation of very long chain fatty acids. Its most severe neurological manifestation is cerebral adrenoleukodystrophy. Here we demonstrate that progressive inflammatory demyelination in cerebral(More)