Identification of the dominant precession damping mechanism in Fe, Co, and Ni by first-principles calculations

The Landau-Lifshitz equation reliably describes magnetization dynamics using a phenomenological treatment of damping. This paper presents first-principles calculations of the damping parameters for Fe, Co, and Ni that quantitatively agree with existing ferromagnetic resonance measurements. This agreement establishes the dominant damping mechanism for these systems and takes a significant step toward predicting and tailoring the damping constants of new materials.Comment: 4 pages, 1 figur

To Learn or Not to Learn Features for Deformable Registration?

Feature-based registration has been popular with a variety of features ranging from voxel intensity to Self-Similarity Context (SSC). In this paper, we examine the question on how features learnt using various Deep Learning (DL) frameworks can be used for deformable registration and whether this feature learning is necessary or not. We investigate the use of features learned by different DL methods in the current state-of-the-art discrete registration framework and analyze its performance on 2 publicly available datasets. We draw insights into the type of DL framework useful for feature learning and the impact, if any, of the complexity of different DL models and brain parcellation methods on the performance of discrete registration. Our results indicate that the registration performance with DL features and SSC are comparable and stable across datasets whereas this does not hold for low level features.Comment: 9 pages, 4 figure

Long-term high fat feeding of rats results in increased numbers of circulating microvesicles with pro-inflammatory effects on endothelial cells

Obesity and type 2 diabetes lead to dramatically increased risks of atherosclerosis and CHD. Multiple mechanisms converge to promote atherosclerosis by increasing endothelial oxidative stress and up-regulating expression of pro-inflammatory molecules. Microvesicles (MV) are small ( < 1 μm) circulating particles that transport proteins and genetic material, through which they are able to mediate cell–cell communication and influence gene expression. Since MV are increased in plasma of obese, insulin-resistant and diabetic individuals, who often exhibit chronic vascular inflammation, and long-term feeding of a high-fat diet (HFD) to rats is a well-described model of obesity and insulin resistance, we hypothesised that this may be a useful model to study the impact of MV on endothelial inflammation. The number and cellular origin of MV from HFD-fed obese rats were characterised by flow cytometry. Total MV were significantly increased after feeding HFD compared to feeding chow (P< 0·001), with significantly elevated numbers of MV derived from leucocyte, endothelial and platelet compartments (P< 0·01 for each cell type). MV were isolated from plasma and their ability to induce reactive oxygen species (ROS) formation and vascular cell adhesion molecule (VCAM)-1 expression was measured in primary rat cardiac endothelial cells in vitro. MV from HFD-fed rats induced significant ROS (P< 0·001) and VCAM-1 expression (P= 0·0275), indicative of a pro-inflammatory MV phenotype in this model of obesity. These findings confirm that this is a useful model to further study the mechanisms by which diet can influence MV release and subsequent effects on cardio-metabolic health

Percolating through networks of random thresholds: Finite temperature electron tunneling in metal nanocrystal arrays

We investigate how temperature affects transport through large networks of nonlinear conductances with distributed thresholds. In monolayers of weakly-coupled gold nanocrystals, quenched charge disorder produces a range of local thresholds for the onset of electron tunneling. Our measurements delineate two regimes separated by a cross-over temperature $T^*$. Up to $T^*$ the nonlinear zero-temperature shape of the current-voltage curves survives, but with a threshold voltage for conduction that decreases linearly with temperature. Above $T^*$ the threshold vanishes and the low-bias conductance increases rapidly with temperature. We develop a model that accounts for these findings and predicts $T^*$.Comment: 5 pages including 3 figures; replaced 3/30/04: minor changes; final versio

Unblocking high-value botanical value chains: Is there a role for blockchain systems?

Blockchain systems are a fast emerging and a currently widely discussed novel strategy for a decentralised cryptographically-enhanced digital ledger recording transactions among stakeholders. This perspective paper looks at its potential uses in the context of high value and mostly low volume botanical material traded globally and used as medicines, health foods, in cosmetics and other applications. We offer a perspective on key areas in the supply of such products globally and how blockchain systems may help in sustainable sourcing, quality assurance, and in tackling supply problems in cases of complex multiherbal preparations. Both open and closed blockchain systems are feasible, and it seems likely that, at least in the initial development, closed ones are the main ones to be utilized. While blockchain’s potential is not yet clear, the examples presented here highlight the opportunities of this new technology

Geometric potential and transport in photonic topological crystals

We report on the experimental realization of an optical analogue of a quantum geometric potential for light wave packets constrained on thin dielectric guiding layers fabricated in silica by the femtosecond laser writing technology. We further demonstrate the optical version of a topological crystal, with the observation of Bloch oscillations and Zener tunneling of purely geometric nature