Observation of a Geometric Hall Effect in a Spinor Bose-Einstein Condensate with a Skyrmion Spin Texture

For a spin-carrying particle moving in a spatially varying magnetic field, effective electromagnetic forces can arise due to the geometric phase associated with adiabatic spin rotation of the particle. We report the observation of a geometric Hall effect in a spinor Bose-Einstein condensate with a skyrmion spin texture. Under translational oscillations of the spin texture, the condensate resonantly develops a circular motion in a harmonic trap, demonstrating the existence of an effective Lorentz force. When the condensate circulates, quantized vortices are nucleated in the boundary region of the condensate and the vortex number increases over 100 without significant heating. We attribute the vortex nucleation to the shearing effect of the effective Lorentz force from the inhomogeneous effective magnetic field.Comment: 9 pages, 11 figure

Circuit Structure and Control Method to Reduce Size and Harmonic Distortion of Interleaved Dual Buck Inverter

A new circuit structure and control method for a high power interleaved dual-buck inverter are proposed. The proposed inverter consists of six switches, four diodes and two inductors, uses a dual-buck structure to eliminate zero-cross distortion, and operates in an interleaved mode to reduce the current stress of switch. To reduce the total harmonic distortion at low output power, the inverter is controlled using discontinuous-current-mode control combined with continuous-current-mode control. The experimental inverter had a power-conversion efficiency of 98.5% at output power = 1300 W and 98.3% at output power = 2 kW, when the inverter was operated at an input voltage of 400 V-DC, output voltage of 220 V-AC/60 Hz, and switching frequency of 20 kHz. The total harmonic distortion was < 0.66%, which demonstrates that the inverter is suitable for high-power dc-ac power conversion.11Ysciescopu

Return and Volatility Transmission Between Oil Prices and Emerging Asian Markets

We investigated return and volatility transmission between oil futures prices and ten Asian emerging indices using a VAR-bivariate GARCH model. We also analyzed the optimal weights and hedge ratios for optimizing portfolios to minimize the exposure to risk associated with oil futures price changes. We found no significant influence of oil futures price returns on Asian stock returns. However, strong volatility spillover was observed from oil futures price shocks and volatility to counterpart volatilities. In addition, optimal weights and hedge ratios suggested that incorporating the oil asset in a well-diversified portfolio effectively hedged the risks associated with oil price volatility

MOF-Derived Cu@Cu2O Nanocatalyst for Oxygen Reduction Reaction and Cycloaddition Reaction

Research on the synthesis of nanomaterials using metal-organic frameworks (MOFs), which are characterized by multi-functionality and porosity, as precursors have been accomplished through various synthetic approaches. In this study, copper and copper oxide nanoparticles were fabricated within 30 min by a simple and rapid method involving the reduction of a copper(II)-containing MOF with sodium borohydride solution at room temperature. The obtained nanoparticles consist of a copper core and a copper oxide shell exhibited catalytic activity in the oxygen reduction reaction. The as-synthesized Cu@Cu2O core-shell nanocatalyst exhibited an enhanced limit current density as well as onset potential in the electrocatalytic oxygen reduction reaction (ORR). Moreover, the nanoparticles exhibited good catalytic activity in the Huisgen cycloaddition of various substituted azides and alkynes under mild reaction conditions

Rheology of Dense Bubble Suspensions

The rheological behavior of rapidly sheared bubble suspensions is examined through numerical simulations and kinetic theory. The limiting case of spherical bubbles at large Reynolds number Re and small Weber number We is examined in detail. Here, Re = p y a^2 / u and We = p y^2 a^3 / s, a being the bubble radius, g the imposed shear, s the interfacial tension, and m and r , respectively, the viscosity and density of the liquid. The bubbles are assumed to undergo elastic bounces when they come into contact; coalescence can be prevented in practice by addition of salt or surface-active impurities. The numerical simulations account for the interactions among bubbles which are assumed to be dominated by the potential flow of the liquid caused by the motion of the bubbles and the shear-induced collision of the bubbles. A kinetic theory based on Grad’s moment method is used to predict the distribution function for the bubble velocities and the stress in the suspension. The hydrodynamic interactions are incorporated in this theory only through their influence on the virtual mass and viscous dissipation in the suspension. It is shown that this theory provides reasonable predictions for the bubble-phase pressure and viscosity determined from simulations including the detailed potential flow interactions. A striking result of this study is that the variance of the bubble velocity can become large compared with (y a)^2 in the limit of large Reynolds number. This implies that the disperse-phase pressure and viscosity associated with the fluctuating motion of the bubbles is quite significant. To determine whether this prediction is reasonable even in the presence of nonlinear drag forces induced by bubble deformation, we perform simulations in which the bubbles are subject to an empirical drag law and show that the bubble velocity variance can be as large as 15 y^2 a^2

Detection and monitoring of forest fires using Himawari-8 geostationary satellite data in South Korea

Geostationary satellite remote sensing systems are a useful tool for forest fire detection and monitoring because of their high temporal resolution over large areas. In this study, we propose a combined 3-step forest fire detection algorithm (i.e., thresholding, machine learning-based modeling, and post processing) using Himawari-8 geostationary satellite data over South Korea. This threshold-based algorithm filtered the forest fire candidate pixels using adaptive threshold values considering the diurnal cycle and seasonality of forest fires while allowing a high rate of false alarms. The random forest (RF) machine learning model then effectively removed the false alarms from the results of the threshold-based algorithm (overall accuracy ~99.16%, probability of detection (POD) ~93.08%, probability of false detection (POFD) ~0.07%, and 96% reduction of the false alarmed pixels for validation), and the remaining false alarms were removed through post-processing using the forest map. The proposed algorithm was compared to the two existing methods. The proposed algorithm (POD ~ 93%) successfully detected most forest fires, while the others missed many small-scale forest fires (POD ~ 50-60%). More than half of the detected forest fires were detected within 10 min, which is a promising result when the operational real-time monitoring of forest fires using more advanced geostationary satellite sensor data (i.e., with higher spatial and temporal resolutions) is used for rapid response and management of forest fires