University of Texas at Austin

About: University of Texas at Austin is a education organization based out in Austin, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 94352 authors who have published 206297 publications receiving 9070052 citations. The organization is also known as: UT-Austin & UT Austin.

Observation of Majorana fermions in ferromagnetic atomic chains on a superconductor

Abstract: Majorana fermions are predicted to localize at the edge of a topological superconductor, a state of matter that can form when a ferromagnetic system is placed in proximity to a conventional superconductor with strong spin-orbit interaction. With the goal of realizing a one-dimensional topological superconductor, we have fabricated ferromagnetic iron (Fe) atomic chains on the surface of superconducting lead (Pb). Using high-resolution spectroscopic imaging techniques, we show that the onset of superconductivity, which gaps the electronic density of states in the bulk of the Fe chains, is accompanied by the appearance of zero-energy end-states. This spatially resolved signature provides strong evidence, corroborated by other observations, for the formation of a topological phase and edge-bound Majorana fermions in our atomic chains.

Two-dimensional flexible nanoelectronics.

Abstract: The unique electrical, mechanical and physical properties of two-dimensional materials make them attractive candidates in flexible nanoelectronic systems. Here Akinwande et al. review the literature on two-dimensional materials in flexible nanoelectronics, and highlight barriers to their full implementation.

Explaining Phonetic Variation: A Sketch of the H&H Theory

Abstract: The H&H theory is developed from evidence showing that speaking and listening are shaped by biologically general processes. Speech production is adaptive. Speakers can, and typically do, tune their performance according to communicative and situational demands, controlling the interplay between production-oriented factors on the one hand, and output-oriented constraints on the other. For the ideal speaker, H&H claims that such adaptations reflect his tacit awareness of the listener’s access to sources of information independent of the signal and his judgement of the short-term demands for explicit signal information. Hence speakers are expected to vary their output along a continuum of hyper- and hypospeech. The theory suggests that the lack of invariance that speech signals commonly exhibit (Perkell and Klatt 1986) is a direct consequence of this adaptive organization (cf MacNeilage 1970). Accordingly, in the H&H program the quest for phonetic invariance is replaced by another research task: Explicating the notion of sufficient discriminability and defining the class of speech signals that meet that criterion.

Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria.

Abstract: Maxent, one of the most commonly used methods for inferring species distributions and environmental tolerances from occurrence data, allows users to fit models of arbitrary complexity. Model complexity is typically constrained via a process known as L1 regularization, but at present little guidance is available for setting the appropriate level of regularization, and the effects of inappropriately complex or simple models are largely unknown. In this study, we demonstrate the use of information criterion approaches to setting regularization in Maxent, and we compare models selected using information criteria to models selected using other criteria that are common in the literature. We evaluate model performance using occurrence data generated from a known "true" initial Maxent model, using several different metrics for model quality and transferability. We demonstrate that models that are inappropriately complex or inappropriately simple show reduced ability to infer habitat quality, reduced ability to infer the relative importance of variables in constraining species' distributions, and reduced transferability to other time periods. We also demonstrate that information criteria may offer significant advantages over the methods commonly used in the literature.