3 resultados para diffractive methodology,

em Duke University


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We demonstrate a diffractive maskless lithographic system that is capable of rapidly performing both serial and single-shot micropatterning. Utilizing the diffractive properties of phase holograms displayed on a spatial light modulator, arbitrary intensity distributions were produced to form two and three dimensional micropatterns/structures in a variety of substrates. A straightforward graphical user interface was implemented to allow users to load templates and change patterning modes within the span of a few minutes. A minimum resolution of approximately 700 nm is demonstrated for both patterning modes, which compares favorably to the 232 nm resolution limit predicted by the Rayleigh criterion. The presented method is rapid and adaptable, allowing for the parallel fabrication of microstructures in photoresist as well as the fabrication of protein microstructures that retain functional activity.

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A shearing quotient (SQ) is a way of quantitatively representing the Phase I shearing edges on a molar tooth. Ordinary or phylogenetic least squares regression is fit to data on log molar length (independent variable) and log sum of measured shearing crests (dependent variable). The derived linear equation is used to generate an 'expected' shearing crest length from molar length of included individuals or taxa. Following conversion of all variables to real space, the expected value is subtracted from the observed value for each individual or taxon. The result is then divided by the expected value and multiplied by 100. SQs have long been the metric of choice for assessing dietary adaptations in fossil primates. Not all studies using SQ have used the same tooth position or crests, nor have all computed regression equations using the same approach. Here we focus on re-analyzing the data of one recent study to investigate the magnitude of effects of variation in 1) shearing crest inclusion, and 2) details of the regression setup. We assess the significance of these effects by the degree to which they improve or degrade the association between computed SQs and diet categories. Though altering regression parameters for SQ calculation has a visible effect on plots, numerous iterations of statistical analyses vary surprisingly little in the success of the resulting variables for assigning taxa to dietary preference. This is promising for the comparability of patterns (if not casewise values) in SQ between studies. We suggest that differences in apparent dietary fidelity of recent studies are attributable principally to tooth position examined.