A propósito de Lancelot, 28°-7°: artealización y pedagogía del espacio

Revista de Filología de la Universidad de La Laguna ◽

10.25145/j.refiull.2021.42.08 ◽

2021 ◽

pp. 115-130

Author(s):

Alicia Llarena ◽

Keyword(s):

The publication of Lancelot, 28°-7°. Guía integral de una isla atlántica in 1929 put into play an artistic project about the islands that revolved around a clear awareness of the power of spatial representation. After reviewing some concepts that support the cultural and anthropological importance of space, and the foundational and symbolic magnitude of spatial images, we highlight the key to the profound teaching that Espinosa’s work has exercised: a pedagogy centered on the art of looking deeply

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Identifying groups of airborne particles by ordination

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100172012 ◽

1994 ◽

Vol 52 ◽

pp. 856-857

Author(s):

M. Shlepr ◽

C. M. Vicroy

Keyword(s):

Elemental Analysis ◽

Energy Dispersive Spectroscopy ◽

Manufacturing Process ◽

Spatial Representation ◽

Airborne Particles ◽

Common Source ◽

Data Set ◽

Microelectronics Industry ◽

Induced Changes ◽

Source Materials

The microelectronics industry is heavily tasked with minimizing contaminates at all steps of the manufacturing process. Particles are generated by physical and/or chemical fragmentation from a mothersource. The tools and macrovolumes of chemicals used for processing, the environment surrounding the process, and the circuits themselves are all potential particle sources. A first step in eliminating these contaminants is to identify their source. Elemental analysis of the particles often proves useful toward this goal, and energy dispersive spectroscopy (EDS) is a commonly used technique. However, the large variety of source materials and process induced changes in the particles often make it difficult to discern if the particles are from a common source.Ordination is commonly used in ecology to understand community relationships. This technique usespair-wise measures of similarity. Separation of the data set is based on discrimination functions. Theend product is a spatial representation of the data with the distance between points equaling the degree of dissimilarity.

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