A microscopic model for spiral ordering along (110) on the MnSi lattice

We study an extended Heisenberg model on the MnSi lattice. In the cubic B20 crystal structure of MnSi, Mn atoms form lattices of of corner-shared equilateral triangles. We find an ubiquitous spiral ordering along (110) for J1 0, where J1, J2, and J3 are 1st, 2nd and 3rd nearest neighbor Heisenberg interactions, respectively. While the ordering direction of (110) is reasonably robust to the presence of the Dzyaloshinskii-Moriya interaction, it can be shifted to the (111) direction with the introduction of a magnetic anisotropy term for small J2/|J1|. We discuss the possible relevance of these results to the partially ordered state recently reported in MnSi.Comment: 5 pages, 4 figure

Concentration dependent interdiffusion in InGaAs/GaAs as evidenced by high resolution x-ray diffraction and photoluminescence spectroscopy

Article copyright 2005 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The article appeared in Journal of Applied Physics 97, 013536 (2005) and may be found at

Use and abuse of statistics in tobacco industry-funded research on standardised packaging

In this commentary we consider the validity of tobacco industry-funded research on the effects of standardised packaging in Australia. As the first country to introduce standardised packs, Australia is closely watched, and Philip Morris International has recently funded two studies into the impact of the measure on smoking prevalence. Both of these papers are flawed in conception as well as design but have nonetheless been widely publicised as cautionary tales against standardised pack legislation. Specifically, we focus on the low statistical significance of the analytical methods used and the assumption that standardised packaging should have an immediate large impact on smoking prevalence

Fabrication of X-Graded H13 and Cu Powder Mix Using High Power Pulsed Nd:YAG Laser

The manufacturing of Functionally Graded Material (FGM) parts using Solid Free Form manufacturing technologies has been carried out since early 1980. At present, most of the powder manufacturing techniques are being focused on layering powder with different powder blend compositions with Z gradients (graded in direction of layer build). Although, there are a few researchers working on multi powder feeder and deposition system, the study of laser fusion of the deposited powder (by a powder deposition system) is minimum or not known to date. Consequently, the manufacturing of functionally graded structures is still geometry limited. This work was focused on the manufacturing of X-graded (graded along the powder bed plane) specimens with H13 tool steel and Cu mix. Five bimodal powder blends were used with a multi-container feed hopper to spread powder layers for the selective laser fusion of the powder. The powder was fused using a high power Nd:YAG pulsed laser using a specific scanning strategy to reduce porosity. Specimens were produced with graded Cu within the H13 matrix. The specimens were analysed for dimensional accuracy, microstructure, porosity, cracks and micro hardness of the FGM.Mechanical Engineerin

N‐heterocyclic carbene catalyzed photoenolization/Diels–Alder reaction of acid fluorides

The combination of light activation and N‐heterocyclic carbene (NHC) organocatalysis has enabled the use of acid fluorides as substrates in a UVA‐light‐mediated photochemical transformation previously observed only with aromatic aldehydes and ketones. Stoichiometric studies and TD‐DFT calculations support a mechanism involving the photoactivation of an ortho‐toluoyl azolium intermediate, which exhibits “ketone‐like” photochemical reactivity under UVA irradiation. Using this photo‐NHC catalysis approach, a novel photoenolization/Diels–Alder (PEDA) process was developed that leads to diverse isochroman‐1‐one derivatives

On the diffusion of lattice matched InGaAs/InP microstructures

Copyright (2003) American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. The following article appeared in F. Bollet et al., J. Appl. Phys. 93, 3881 (2003) and may be found at http://link.aip.org/link/?jap/93/388

Quantum state preparation in semiconductor dots by adiabatic rapid passage

Preparation of a specific quantum state is a required step for a variety of proposed practical uses of quantum dynamics. We report an experimental demonstration of optical quantum state preparation in a semiconductor quantum dot with electrical readout, which contrasts with earlier work based on Rabi flopping in that the method is robust with respect to variation in the optical coupling. We use adiabatic rapid passage, which is capable of inverting single dots to a specified upper level. We demonstrate that when the pulse power exceeds a threshold for inversion, the final state is independent of power. This provides a new tool for preparing quantum states in semiconductor dots and has a wide range of potential uses.Comment: 4 pages, 4 figure

Automated classification of three-dimensional reconstructions of coral reefs using convolutional neural networks

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hopkinson, B. M., King, A. C., Owen, D. P., Johnson-Roberson, M., Long, M. H., & Bhandarkar, S. M. Automated classification of three-dimensional reconstructions of coral reefs using convolutional neural networks. PLoS One, 15(3), (2020): e0230671, doi: 10.1371/journal.pone.0230671.Coral reefs are biologically diverse and structurally complex ecosystems, which have been severally affected by human actions. Consequently, there is a need for rapid ecological assessment of coral reefs, but current approaches require time consuming manual analysis, either during a dive survey or on images collected during a survey. Reef structural complexity is essential for ecological function but is challenging to measure and often relegated to simple metrics such as rugosity. Recent advances in computer vision and machine learning offer the potential to alleviate some of these limitations. We developed an approach to automatically classify 3D reconstructions of reef sections and assessed the accuracy of this approach. 3D reconstructions of reef sections were generated using commercial Structure-from-Motion software with images extracted from video surveys. To generate a 3D classified map, locations on the 3D reconstruction were mapped back into the original images to extract multiple views of the location. Several approaches were tested to merge information from multiple views of a point into a single classification, all of which used convolutional neural networks to classify or extract features from the images, but differ in the strategy employed for merging information. Approaches to merging information entailed voting, probability averaging, and a learned neural-network layer. All approaches performed similarly achieving overall classification accuracies of ~96% and >90% accuracy on most classes. With this high classification accuracy, these approaches are suitable for many ecological applications.This study was funded by grants from the Alfred P. Sloan Foundation (BMH, BR2014-049; https://sloan.org), and the National Science Foundation (MHL, OCE-1657727; https://www.nsf.gov). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript