Implicitly Weighted Methods in Robust Image Analysis

This paper is devoted to highly robust statistical methods with applications to image analysis. The methods of the paper exploit the idea of implicit weighting, which is inspired by the highly robust least weighted squares regression estimator. We use a correlation coefficient based on implicit weighting of individual pixels as a highly robust similarity measure between two images. The reweighted least weighted squares estimator is considered as an alternative regression estimator with a clear interpretation. We apply implicit weighting to dimension reduction by means of robust principal component analysis. Highly robust methods are exploited in tasks of face localization and face detection in a database of 2D images. In this context we investigate a method for outlier detection and a filter for image denoising based on implicit weighting.     

The Role of the Prefrontal Cortex in the Maintenance of Verbal Working Memory: An Event-Related fMRI Analysis.

Neuroimaging studies have been inconclusive in characterizing the role of the prefrontal cortex (PFC) for maintaining increasingly larger amounts of information in working memory (WM). To address this question, the authors collected event-related functional MRI data while participants performed an item-recognition task in which the number of to-be-remembered letters was parametrically modulated. During maintenance of information in WM, the dorsolateral and the ventrolateral PFC exhibited linearly increasing activation in response to increasing WM load. Prefrontal regions could not be distinguished from one another on the basis of load sensitivity, but the dorsolateral PFC had stronger functional connectivity with the parietal and motor cortex than the ventrolateral PFC. These results suggest an increasingly important role for the PFC in actively maintaining information as the amount of that information increases. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Multipose Binding in Molecular Docking

Molecular docking has been extensively applied in virtual screening of small molecule libraries for lead identification and optimization. A necessary prerequisite for successful differentiation between active and non-active ligands is the accurate prediction of their binding affinities in the complex by use of docking scoring functions. However, many studies have shown rather poor correlations between docking scores and experimental binding affinities. Our work aimed to improve this correlation by implementing a multipose binding concept in the docking scoring scheme. Multipose binding, i.e., the property of certain protein-ligand complexes to exhibit different ligand binding modes, has been shown to occur in nature for a variety of molecules. We conducted a high-throughput docking study and implemented multipose binding in the scoring procedure by considering multiple docking solutions in binding affinity prediction. In general, improvement of the agreement between docking scores and experimental data was observed, and this was most pronounced in complexes with large and flexible ligands and high binding affinities. Further developments of the selection criteria for docking solutions for each individual complex are still necessary for a general utilization of the multipose binding concept for accurate binding affinity prediction by molecular docking.     

Chromium ― Copper System: Adhesion Characteristics,Doping, the Structure of Phase Boundary and Composites

The adhesive characteristics and the formation of phase boundaries in the Cr Cu system in a vacuum of (2-4)·10^–3 Pa in the temperature range 1100-1300°C have been studied. The microstructure of composites (50:50 by mass) made by copper impregnation of porous samples of Cr electrolytic powders and Cr obtained by calcium hydride reduction. The effect of Cr, Fe, Co, Ni, Si additions on above characteristics has been investigated.     

Fluorescence correlation spectroscopy at 100 nM concentrations using near-field scanning optical microscopic (NSOM) geometries and highly diffracting force sensing fiber probes

A tapered cantilevered optical fiber probe is introduced for fluorescence correlation spectroscopy (FCS). The probe has an aperture that is coated with metal and its dimension can be very well defined. Its design is based on cantilevered near-field optical fiber probes that allow for on-line atomic force feedback. This permits unprecedented stability in FCS measurements. Even such probes that have large diameters are below the cutoff wavelength of light propagation in optical fibers. Such large diameter probes produce bright spots of light that are highly diffracting. Therefore, only the fluence of light very close to the surface of the glass probe aperture is sufficient to exhibit a high probability of fluorescence excitation. From the results presented in this paper the z extent of such probes seems comparable to what can be obtained from prism-based evanescent wave methods, but with much more flexibility and including force sensing capability. In agreement with theoretical results on prism evanescent field-based excitation, it is shown that even with large xy dimensions for the fiber probes in this paper, fluorescence correlation spectra from 100 nM fluorophore concentrations can be recorded. This is 10 times larger than the concentrations generally required for conventional confocal FCS. The results suggest that such an approach has considerable potential for applications of FCS in membrane, near-membrane, solution, and even within-cell environments. The latter is achieved through atomic force feedback controlled penetration of tapered cantilevered metal-coated glass fibers into cells, and this is also reported in this paper.