Magnetization reversal in AFC media

In this paper, we report on a study of magnetization reversal processes in antiferromagnetically coupled media. We describe the reversal in terms of the reversible and irreversible susceptibility that has been measured for the CoCrPtB system of fixed-recording layer thickness and variable-stabilization layer thickness. We rind that very thin stabilization layers do not couple strongly to the recording layer, and that for Mrt greater than 0.11 memu/cm(2), some of the change in magnetization becomes irreversible

Charge pumping in monolayer graphene driven by a series of time-periodic potentials

We applied the Floquet scattering-matrix formalism to studying the electronic transport properties in a mesoscopic Dirac system. Using the method, we investigate theoretically quantum pumping driven by a series of time-periodic potentials in graphene monolayer both in the adiabatic and non-adiabatic regimes. Our numerical results demonstrate that adding harmonic modulated potentials can break the time reversal symmetry when no voltage bias is applied to the graphene monolayer. Thus, when the system is pumped with proper dynamic parameters, these scatterers can produce a nonzero dc pumped current. We also find that the transmission is anisotropic as the incident angle is changed.Comment: 8 pages, 6 figure

The influence of initial and surface boundary conditions on a model-generated January climatology

The influence on a model-generated January climate of various surface boundary conditions, as well as initial conditions, was studied by using the GISS coarse-mesh climate model. Four experiments - two with water planets, one with flat continents, and one with mountains - were used to investigate the effects of initial conditions, and the thermal and dynamical effects of the surface on the model generated-climate. However, climatological mean zonal-symmetric sea surface temperature is used in all four runs over the model oceans. Moreover, zero ground wetness and uniform ground albedo except for snow are used in the last experiments

X-ray Polarization Signatures of Compton Scattering in Magnetic Cataclysmic Variables

Compton scattering within the accretion column of magnetic cataclysmic variables (mCVs) can induce a net polarization in the X-ray emission. We investigate this process using Monte Carlo simulations and find that significant polarization can arise as a result of the stratified flow structure in the shock-ionized column. We find that the degree of linear polarization can reach levels up to ~8% for systems with high accretion rates and low white-dwarf masses, when viewed at large inclination angles with respect to the accretion column axis. These levels are substantially higher than previously predicted estimates using an accretion column model with uniform density and temperature. We also find that for systems with a relatively low-mass white dwarf accreting at a high accretion rate, the polarization properties may be insensitive to the magnetic field, since most of the scattering occurs at the base of the accretion column where the density structure is determined mainly by bremsstrahlung cooling instead of cyclotron cooling.Comment: 7 pages, 8 figures, accepted by MNRA

Application of Cryogenic Treatment to Extend the Life of the TiAlN-Coated Tungsten Carbide Milling Cutter

Cutting tools are important to the manufacturing industry since they will affect production efficiency and product quality. Cryogenic treatment can improve the material properties by decreasing residual stress, stabilizing dimensional accuracy, and increasing wear resistance. The purpose of this study is to investigate the feasibility and effect of cryogenic treatment on the performance of TiAlN-coated tungsten carbide milling cutters for machining the Inconel alloy 625 in terms of different testing methods (e.g., hardness, wear resistance, residual stress, microstructure, and tool life test). Experimental results indicate that after cryogenic treatment there is less wear, the microstructure is denser, residual stress is decreased, the adhesion of coating and tungsten carbide is improved, and the tool life is effectively improved

Convolutional Networks for Object Category and 3D Pose Estimation from 2D Images

Current CNN-based algorithms for recovering the 3D pose of an object in an image assume knowledge about both the object category and its 2D localization in the image. In this paper, we relax one of these constraints and propose to solve the task of joint object category and 3D pose estimation from an image assuming known 2D localization. We design a new architecture for this task composed of a feature network that is shared between subtasks, an object categorization network built on top of the feature network, and a collection of category dependent pose regression networks. We also introduce suitable loss functions and a training method for the new architecture. Experiments on the challenging PASCAL3D+ dataset show state-of-the-art performance in the joint categorization and pose estimation task. Moreover, our performance on the joint task is comparable to the performance of state-of-the-art methods on the simpler 3D pose estimation with known object category task