2,094 research outputs found

    Towards Mott design by δ\delta-doping of strongly correlated titanates

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    Doping the distorted-perovskite Mott insulators LaTiO3_3 and GdTiO3_3 with a single SrO layer along the [001] direction gives rise to a rich correlated electronic structure. A realistic superlattice study by means of the charge self-consistent combination of density functional theory with dynamical mean-field theory reveals layer- and temperature-dependent multi-orbital metal-insulator transitions. An orbital-selective metallic layer at the interface dissolves via an orbital-polarized doped-Mott state into an orbital-ordered insulating regime beyond the two conducting TiO2_2 layers. We find large differences in the scattering behavior within the latter. Breaking the spin symmetry in δ\delta-doped GdTiO3_3 results in blocks of ferromagnetic itinerant and ferromagnetic Mott-insulating layers which are coupled antiferromagnetically.Comment: 17 pages, 9 figures, final versio

    Billiard knots in a cylinder

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    We define cylinder knots as billiard knots in a cylinder. We present a necessary condition for cylinder knots: after dividing cylinder knots by possible rotational symmetries we obtain ribbon knots. We obtain an upper bound for the number of cylinder knots with two fixed parameters (out of three). In addition we prove that rosette knots are cylinder knots.Comment: 14 pages, 10 figures, to appear in the Journal of Knot Theor

    N-terminal modification of proteins with o-aminophenols.

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    The synthetic modification of proteins plays an important role in chemical biology and biomaterials science. These fields provide a constant need for chemical tools that can introduce new functionality in specific locations on protein surfaces. In this work, an oxidative strategy is demonstrated for the efficient modification of N-terminal residues on peptides and N-terminal proline residues on proteins. The strategy uses o-aminophenols or o-catechols that are oxidized to active coupling species in situ using potassium ferricyanide. Peptide screening results have revealed that many N-terminal amino acids can participate in this reaction, and that proline residues are particularly reactive. When applied to protein substrates, the reaction shows a stronger requirement for the proline group. Key advantages of the reaction include its fast second-order kinetics and ability to achieve site-selective modification in a single step using low concentrations of reagent. Although free cysteines are also modified by the coupling reaction, they can be protected through disulfide formation and then liberated after N-terminal coupling is complete. This allows access to doubly functionalized bioconjugates that can be difficult to access using other methods

    Scaling Nonparametric Bayesian Inference via Subsample-Annealing

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    We describe an adaptation of the simulated annealing algorithm to nonparametric clustering and related probabilistic models. This new algorithm learns nonparametric latent structure over a growing and constantly churning subsample of training data, where the portion of data subsampled can be interpreted as the inverse temperature beta(t) in an annealing schedule. Gibbs sampling at high temperature (i.e., with a very small subsample) can more quickly explore sketches of the final latent state by (a) making longer jumps around latent space (as in block Gibbs) and (b) lowering energy barriers (as in simulated annealing). We prove subsample annealing speeds up mixing time N^2 -> N in a simple clustering model and exp(N) -> N in another class of models, where N is data size. Empirically subsample-annealing outperforms naive Gibbs sampling in accuracy-per-wallclock time, and can scale to larger datasets and deeper hierarchical models. We demonstrate improved inference on million-row subsamples of US Census data and network log data and a 307-row hospital rating dataset, using a Pitman-Yor generalization of the Cross Categorization model.Comment: To appear in AISTATS 201

    Multi-Agent Deployment for Visibility Coverage in Polygonal Environments with Holes

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    This article presents a distributed algorithm for a group of robotic agents with omnidirectional vision to deploy into nonconvex polygonal environments with holes. Agents begin deployment from a common point, possess no prior knowledge of the environment, and operate only under line-of-sight sensing and communication. The objective of the deployment is for the agents to achieve full visibility coverage of the environment while maintaining line-of-sight connectivity with each other. This is achieved by incrementally partitioning the environment into distinct regions, each completely visible from some agent. Proofs are given of (i) convergence, (ii) upper bounds on the time and number of agents required, and (iii) bounds on the memory and communication complexity. Simulation results and description of robust extensions are also included

    Sustainable Prairie

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    Tallgrass prairie once blanketed approximately 170 million acres of North America, from Texas up into Canada and from Kentucky west into Kansas. Only about 4 percent of this once vast sea of grass remains, making tallgrass prairie the most altered ecosystem on the continent in terms of acres lost
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