Optical Response of Solid CO2_2 as a Tool for the Determination of the High Pressure Phase

We report first-principles calculations of the frequency dependent linear and second-order optical properties of the two probable extended-solid phases of CO$_2$--V, i.e. $I\bar42d$ and $P2_12_12_1$. Compared to the parent $Cmca$ phase the linear optical susceptibility of both phases is much smaller. We find that $I\bar42d$ and $P2_12_12_1$ differ substantially in their linear optical response in the higher energy regime. The nonlinear optical responses of the two possible crystal structures differ by roughly a factor of five. Since the differences in the nonlinear optical spectra are pronounced in the low energy regime, i.e. below the band gap of diamond, measurements with the sample inside the diamond anvil cell are feasible. We therefore suggest optical experiments in comparison with our calculated data as a tool for the unambiguous identification of the high pressure phase of CO$_2$.Comment: 4 pages 2 fig

Brain amyloid in preclinical Alzheimer\u27s disease is associated with increased driving risk

INTRODUCTION: Postmortem studies suggest that fibrillar brain amyloid places people at higher risk for hazardous driving in the preclinical stage of Alzheimer's disease (AD). METHODS: We administered driving questionnaires to 104 older drivers (19 AD, 24 mild cognitive impairment, and 61 cognitive normal) who had a recent (18)F-florbetapir positron emission tomography scan. We examined associations of amyloid standardized uptake value ratios with driving behaviors: traffic violations or accidents in the past 3 years. RESULTS: The frequency of violations or accidents was curvilinear with respect to standardized uptake value ratios, peaking around a value of 1.1 (model r(2) = 0.10, P = .002); moreover, this relationship was evident for the cognitively normal participants. DISCUSSION: We found that driving risk is strongly related to accumulating amyloid on positron emission tomography, and that this trend is evident in the preclinical stage of AD. Brain amyloid burden may in part explain the increased crash risk reported in older adults

Active perception for plume source localisation with underwater gliders

© 2018 Australasian Robotics and Automation Association. All rights reserved. We consider the problem of localising an unknown underwater plume source in an energy-optimal manner. We first develop a specialised Gaussian process (GP) regression technique for estimating the source location given concentration measurements and an ambient flow field. Then, we use the GP upper confidence bound (GP-UCB) for active perception to choose sampling locations that both improve the estimate of the source and lead the glider to the correct source location. A trim-based FMT∗planner is then used to find the sequence of controls that minimise the energy consumption. We provide a theoretical guarantee on the performance of the algorithm, and demonstrate the algorithm using both artificial and experimental datasets

Magnetic levitation force between a superconducting bulk magnet and a permanent magnet

The current density in a disk-shaped superconducting bulk magnet and the magnetic levitation force exerted on the superconducting bulk magnet by a cylindrical permanent magnet are calculated from first principles. The effect of the superconducting parameters of the superconducting bulk is taken into account by assuming the voltage-current law and the material law. The magnetic levitation force is dominated by the remnant current density, which is induced by switching off the applied magnetizing field. High critical current density and flux creep exponent may increase the magnetic levitation force. Large volume and high aspect ratio of the superconducting bulk can enhance the magnetic levitation force further.Comment: 18 pages and 8 figure

Performance studies of evolutionary transfer learning for end-to-end QoT estimation in multi-domain optical networks [Invited]

This paper proposes an evolutionary transfer learning approach (Evol-TL) for scalable quality-of-transmission (QoT) estimation in multi-domain elastic optical networks (MD-EONs). Evol-TL exploits a broker-based MD-EON architecture that enables cooperative learning between the broker plane (end-to-end) and domain-level (local) machine learning functions while securing the autonomy of each domain. We designed a genetic algorithm to optimize the neural network architectures and the sets of weights to be transferred between the source and destination tasks. We evaluated the performance of Evol-TL with three case studies considering the QoT estimation task for lightpaths with (i) different path lengths (in terms of the numbers of fiber links traversed), (ii) different modulation formats, and (iii) different device conditions (emulated by introducing different levels of wavelength-specific attenuation to the amplifiers). The results show that the proposed approach can reduce the average amount of required training data by up to 13× while achieving an estimation accuracy above 95%

A Multi-level Algorithm for Quantum-impurity Models

A continuous-time path integral Quantum Monte Carlo method using the directed-loop algorithm is developed to simulate the Anderson single-impurity model in the occupation number basis. Although the method suffers from a sign problem at low temperatures, the new algorithm has many advantages over conventional algorithms. For example, the model can be easily simulated in the Kondo limit without time discretization errors. Further, many observables including the impurity susceptibility and a variety of fermionic observables can be calculated efficiently. Finally the new approach allows us to explore a general technique, called the multi-level algorithm, to solve the sign problem. We find that the multi-level algorithm is able to generate an exponentially large number of configurations with an effort that grows as a polynomial in inverse temperature such that configurations with a positive sign dominate over those with negative signs. Our algorithm can be easily generalized to other multi-impurity problems.Comment: 9 pages, 8 figure

Gut-seeded α-synuclein fibrils promote gut dysfunction and brain pathology specifically in aged mice

Parkinson’s disease is a synucleinopathy that is characterized by motor dysfunction, death of midbrain dopaminergic neurons and accumulation of α-synuclein (α-Syn) aggregates. Evidence suggests that α-Syn aggregation can originate in peripheral tissues and progress to the brain via autonomic fibers. We tested this by inoculating the duodenal wall of mice with α-Syn preformed fibrils. Following inoculation, we observed gastrointestinal deficits and physiological changes to the enteric nervous system. Using the AAV-PHP.S capsid to target the lysosomal enzyme glucocerebrosidase for peripheral gene transfer, we found that α-Syn pathology is reduced due to the increased expression of this protein. Lastly, inoculation of α-Syn fibrils in aged mice, but not younger mice, resulted in progression of α-Syn histopathology to the midbrain and subsequent motor defects. Our results characterize peripheral synucleinopathy in prodromal Parkinson’s disease and explore cellular mechanisms for the gut-to-brain progression of α-Syn pathology