This paper develops a mathematical model for the physical properties of electrodes suitable for use in electric current computed tomography (ECCT). The model includes the effects of discretization, shunt, and contact impedance. The complete model was validated by experiment. Bath resistivities of 284.0, 139.7, 62.3, 29.5 omega.cm were studied. Values of "effective" contact impedance zeta used in the numerical approximations were 58.0, 35.0, 15.0, and 7.5 omega.cm2, respectively. Agreement between the calculated and experimentally measured values was excellent throughout the range of bath conductivities studied. It is desirable in electrical impedance imaging systems to model the observed voltages to the same precision as they are measured in order to be able to make the highest resolution reconstructions of the internal conductivity that the measurement precision allows. The complete electrode model, which includes the effects of discretization of the current pattern, the shunt effect due to the highly conductive electrode material, and the effect of an "effective" contact impedance, allows calculation of the voltages due to any current pattern applied to a homogeneous resistivity field.

One-dimensional (1D) MoO2 nanorods in the form of a large-area array and nanobranched structure were prepared by hot-filament metal–oxide vapour deposition at low and high pressures in atmospheric argon flows respectively. The x-ray diffraction (XRD) patterns of both as-synthesized samples show that the 1D MoO2 nanorods are monoclinic crystals in space group P 21/c. The Raman spectrum of the large-area array of 1D MoO2 nanorods appears to be the same as that of a two-dimensional (2D) MoO2 thin film. The Raman spectrum of the nanobranched structure of 1D MoO2 nanorods showed a downshift and asymmetric broadening of the Raman first-order TO peak when compared with the bulk (q = 0) mode. The Raman shift and broadening were attributed to phonon confinement effect in the 1D nanorods. The in situ Raman spectra of laser-induced oxidation of the nanobranched structure of 1D MoO2 nanorods demonstrate that they can be oxidized easily and more strongly than the 3D bulk MoO2 powder.

Automatic instrument segmentation in video is an essentially fundamental yet challenging problem for robot-assisted minimally invasive surgery. In this paper, we propose a novel framework to leverage instrument motion information, by incorporating a derived temporal prior to an attention pyramid network for accurate segmentation. Our inferred prior can provide reliable indication of the instrument location and shape, which is propagated from the previous frame to the current frame according to inter-frame motion flow. This prior is injected to the middle of an encoder-decoder segmentation network as an initialization of a pyramid of attention modules, to explicitly guide segmentation output from coarse to fine. In this way, the temporal dynamics and the attention network can effectively complement and benefit each other. As additional usage, our temporal prior enables semi-supervised learning with periodically unlabeled video frames, simply by reverse execution. We extensively validate our method on the public 2017 MICCAI EndoVis Robotic Instrument Segmentation Challenge dataset with three different tasks. Our method consistently exceeds the state-of-the-art results across all three tasks by a large margin. Our semi-supervised variant also demonstrates a promising potential for reducing annotation cost in the clinical practice.

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The synthesis of RuO2 nanorods with reactive sputtering was demonstrated in this work. The synthesis process is very much like the metal organic chemical vapor deposition, except that RuO3 generated with reactive sputtering under high oxygen-to-argon flow ratio (>5SCCM∕15SCCM) (SCCM denotes cubic centimeter per minute at STP) and high substrate temperature (>300°C) is used in place of the metal organic precursor. RuO2 nanorods tend to grow steadily with constant aspect ratio (∼27) and the field-emission characteristics appear very sensitive to their spatial distribution.

The purpose of this study is to characterize the trajectory of a barbell and clarify whether there is a standard pattern in the barbell trajectory for each lifter. Two high-speed cameras (mega-speed MS1000, sampling rate=120 Hz) were used to film the barbell trajectories of male Taiwanese weightlifters under competitive conditions. Twenty-four successful lifts were filmed and classified into 3 groups (n=8 per group) by relative barbell-mass (RBM): the better-performance group (RBM>1.63), the middle group (1.28

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