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Bioinspiration-using insights into the function of biological systems for the development of new engineering concepts-is already a successful and rapidly growing field. However, only a small portion of the world's biodiversity has thus far been considered as a potential source for engineering inspiration. This means that vast numbers of biological systems of potentially high value to engineering have likely gone unnoticed. Even more important, insights into form and function that reside in the evolutionary relationships across the tree of life have not yet received attention by engineers. These insights could soon become accessible through recent developments in disparate areas of research; in particular, advancements in digitization of museum specimens, methods to describe and analyze complex biological shapes, quantitative prediction of biological function from form, and analysis of large digital data sets. Taken together, these emerging capabilities should make it possible to mine the world's known biodiversity as a natural resource for knowledge relevant to engineering. This transformation of bioinspiration would be very timely in the development of engineering, because it could yield exactly the kind of insights that are needed to make technology more autonomous, adaptive, and capable of operation in complex environments.

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We analyze the hypothesis that some individuals on the autism spectrum may use visual mental representations and processes to perform certain tasks that typically developing individuals perform verbally. We present a framework for interpreting empirical evidence related to this "Thinking in Pictures" hypothesis and then provide comprehensive reviews of data from several different cognitive tasks, including the n-back task, serial recall, dual task studies, Raven's Progressive Matrices, semantic processing, false belief tasks, visual search, spatial recall, and visual recall. We also discuss the relationships between the Thinking in Pictures hypothesis and other cognitive theories of autism including Mindblindness, Executive Dysfunction, Weak Central Coherence, and Enhanced Perceptual Functioning.

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Electrical transport in metallic carbon nanotubes, especially the ones with diameters of the order of a few nanometers can be best described using the Tomanaga Luttinger liquid (TL) model. Recently, the TL model has been used to create a convenient transmission line like phenomenological model for carbon nanotubes. In this paper, we have characterized metallic nanotubes based on that model, quantifying the quantum capacitances of individual metallic single walled carbon nanotubes and crystalline bundles of single walled tubes of different diameters. Our calculations show that the quantum capacitances for both individual tubes and the bundles show a weak dependence on the diameters of their constituent tubes. The nanotube bundles exhibit a significantly large quantum capacitance due to enhancement of density of states at the Fermi level.