Gyroid cuticular structures in butterfly wing scales: biological photonic crystals

We present a systematic study of the cuticular structure in the butterfly wing scales of some papilionids (Parides sesostris and Teinopalpus imperialis) and lycaenids (Callophrys rubi, Cyanophrys remus, Mitoura gryneus and Callophrys dumetorum). Using published scanning and transmission electron microscopy (TEM) images, analytical modelling and computer-generated TEM micrographs, we find that the three-dimensional cuticular structures can be modelled by gyroid structures with various filling fractions and lattice parameters. We give a brief discussion of the formation of cubic gyroid membranes from the smooth endoplasmic reticulum in the scale's cell, which dry and harden to leave the cuticular structure behind when the cell dies. The scales of C. rubi are a potentially attractive biotemplate for producing three-dimensional optical photonic crystals since for these scales the cuticle-filling fraction is nearly optimal for obtaining the largest photonic band gap in a gyroid structure

Fast Searching in Packed Strings

Given strings $P$ and $Q$ the (exact) string matching problem is to find all positions of substrings in $Q$ matching $P$. The classical Knuth-Morris-Pratt algorithm [SIAM J. Comput., 1977] solves the string matching problem in linear time which is optimal if we can only read one character at the time. However, most strings are stored in a computer in a packed representation with several characters in a single word, giving us the opportunity to read multiple characters simultaneously. In this paper we study the worst-case complexity of string matching on strings given in packed representation. Let $m \leq n$ be the lengths $P$ and $Q$, respectively, and let $\sigma$ denote the size of the alphabet. On a standard unit-cost word-RAM with logarithmic word size we present an algorithm using time O\left(\frac{n}{\log_\sigma n} + m + \occ\right). Here \occ is the number of occurrences of $P$ in $Q$. For $m = o(n)$ this improves the $O(n)$ bound of the Knuth-Morris-Pratt algorithm. Furthermore, if $m = O(n/\log_\sigma n)$ our algorithm is optimal since any algorithm must spend at least \Omega(\frac{(n+m)\log \sigma}{\log n} + \occ) = \Omega(\frac{n}{\log_\sigma n} + \occ) time to read the input and report all occurrences. The result is obtained by a novel automaton construction based on the Knuth-Morris-Pratt algorithm combined with a new compact representation of subautomata allowing an optimal tabulation-based simulation.Comment: To appear in Journal of Discrete Algorithms. Special Issue on CPM 200

Molecular cloning and transcriptional regulation of ompT , a ToxR-repressed gene in Vibrio cholerae

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72189/1/j.1365-2958.2000.01699.x.pd

Can attention select only a fixed number of objects at a time?

Several previous studies have suggested that we may attend only a fixed number of `objects' at a time. However, whereas findings from two-target experiments suggest that we can attend only one object at a time, other results from object-tracking and enumeration paradigms point instead to a four-object limit. Here, we note that in these previous studies the number of objects covaried with the overall size and complexity of the stimulus, such that apparent one-object or four-object limits in those tasks may reflect changes in the complexity of attended stimuli, rather than the number of objects per se. Accordingly, in the current experiments we employ stimuli in which the number of objects varies, while overall size and complexity are held constant. Using these refined measures of object-based effects, we find no evidence for a one-object or four-object limit on attention. Indeed, we conclude that the number of attended objects does not affect how efficiently we can attend a given stimulus. We propose and test an alternative approach to objectbased attention limitations based on within-object and between-object feature-binding mechanisms in human vision