Spatial temperature gradient capillary electrophoresis for DNA mutation detection

A continuous spatial temperature gradient was established in capillary electrophoresis by using a simple temperature control device. The temperature profile along the capillary was predicted by theoretical calculations. A nearly linear spatial temperature gradient was established and applied to DNA mutation detection. By spanning a wide temperature range, it was possible to perform simultaneous heteroduplex analysis for various mutation types that have different melting temperatures.

知觉组织在拥挤现象中的作用

Crowding, generally defined as the deleterious influence of nearby contours on visual discrimination, is ubiquitous in spatial vision. Specifically, long-range effects of non-overlapping distracters can alter the appearance of an object, making it unrecognizable. Theories in many domains, including vision computation and high-level attention, have been proposed to account for crowding. However, neither compulsory averaging model nor insufficient spatial esolution of attention provides an adequate explanation for crowding. The present study examined the effects of perceptual organization on crowding. We hypothesize that target-distractor segmentation in crowding is analogous to figure-ground segregation in Gestalt. When distractors can be grouped as a whole or when they are similar to each other but different from the target, the target can be distinguished from distractors. However, grouping target and distractors together by Gestalt principles may interfere with target-distractor separation. Six experiments were carried out to assess our theory. In experiments 1, 2, and 3, we manipulated the similarity between target and distractor as well as the configuration of distractors to investigate the effects of stimuli-driven grouping on target-distractor segmentation. In experiments 4, 5, and 6, we focused on the interaction between bottom-up and top-down processes of grouping, and their influences on target-distractor segmentation. Our results demonstrated that: (a) when distractors were similar to each other but different from target, crowding was eased; (b) when distractors formed a subjective contour or were placed regularly, crowding was also reduced; (c) both bottom-up and top-down processes could influence target-distractor grouping, mediating the effects of crowding. These results support our hypothesis that the figure-ground segregation and target-distractor segmentation in crowding may share similar processes. The present study not only provides a novel explanation for crowding, but also examines the processing bottleneck in object recognition. These findings have significant implications on computer vision and interface design as well as on clinical practice in amblyopia and dyslexia.

Spatial Reference Frames for Object Recognition: Tuning for Rotations in Depth

The inferior temporal cortex (IT) of monkeys is thought to play an essential role in visual object recognition. Inferotemporal neurons are known to respond to complex visual stimuli, including patterns like faces, hands, or other body parts. What is the role of such neurons in object recognition? The present study examines this question in combined psychophysical and electrophysiological experiments, in which monkeys learned to classify and recognize novel visual 3D objects. A population of neurons in IT were found to respond selectively to such objects that the monkeys had recently learned to recognize. A large majority of these cells discharged maximally for one view of the object, while their response fell off gradually as the object was rotated away from the neuron"s preferred view. Most neurons exhibited orientation-dependent responses also during view-plane rotations. Some neurons were found tuned around two views of the same object, while a very small number of cells responded in a view- invariant manner. For five different objects that were extensively used during the training of the animals, and for which behavioral performance became view-independent, multiple cells were found that were tuned around different views of the same object. No selective responses were ever encountered for views that the animal systematically failed to recognize. The results of our experiments suggest that neurons in this area can develop a complex receptive field organization as a consequence of extensive training in the discrimination and recognition of objects. Simple geometric features did not appear to account for the neurons" selective responses. These findings support the idea that a population of neurons -- each tuned to a different object aspect, and each showing a certain degree of invariance to image transformations -- may, as an assembly, encode complex 3D objects. In such a system, several neurons may be active for any given vantage point, with a single unit acting like a blurred template for a limited neighborhood of a single view.

Template Matching: Matched Spatial Filters and Beyond

Template matching by means of cross-correlation is common practice in pattern recognition. However, its sensitivity to deformations of the pattern and the broad and unsharp peaks it produces are significant drawbacks. This paper reviews some results on how these shortcomings can be removed. Several techniques (Matched Spatial Filters, Synthetic Discriminant Functions, Principal Components Projections and Reconstruction Residuals) are reviewed and compared on a common task: locating eyes in a database of faces. New variants are also proposed and compared: least squares Discriminant Functions and the combined use of projections on eigenfunctions and the corresponding reconstruction residuals. Finally, approximation networks are introduced in an attempt to improve filter design by the introduction of nonlinearity.

Image Chunking: Defining Spatial Building Blocks for Scene Analysis

Rapid judgments about the properties and spatial relations of objects are the crux of visually guided interaction with the world. Vision begins, however, with essentially pointwise representations of the scene, such as arrays of pixels or small edge fragments. For adequate time-performance in recognition, manipulation, navigation, and reasoning, the processes that extract meaningful entities from the pointwise representations must exploit parallelism. This report develops a framework for the fast extraction of scene entities, based on a simple, local model of parallel computation.sAn image chunk is a subset of an image that can act as a unit in the course of spatial analysis. A parallel preprocessing stage constructs a variety of simple chunks uniformly over the visual array. On the basis of these chunks, subsequent serial processes locate relevant scene components and assemble detailed descriptions of them rapidly. This thesis defines image chunks that facilitate the most potentially time-consuming operations of spatial analysis---boundary tracing, area coloring, and the selection of locations at which to apply detailed analysis. Fast parallel processes for computing these chunks from images, and chunk-based formulations of indexing, tracing, and coloring, are presented. These processes have been simulated and evaluated on the lisp machine and the connection machine.

Biomass?Diversity Responses and Spatial Dependencies in Disturbed Tallgrass Prairies

Javier G. P. Gamarra and Ricard V. Sole (2002). Biomass-diversity responses and spatial dependencies in disturbed tallgrass prairies. Journal of Theoretical Biology, 215 (4) pp.469-480 RAE2008