Spontaneous fourfold-symmetry breaking driven by electron-lattice coupling and strong correlations in high-TcT_c cuprates

Using dynamical-mean-field theory for clusters, we study the two-dimensional Hubbard model in which electrons are coupled with the orthorhombic lattice distortions through the modulation in the hopping matrix. Instability towards spontaneous symmetry breaking from a tetragonal symmetric phase to an orthorhombic distorted phase is examined as a function of doping and interaction strength. A very strong instability is found in the underdoped pseudogap regime when the interaction strength is large enough to yield the Mott insulating phase at half filling. The symmetry breaking accompanies the recovery of quasiparticle weights along one of the two antinodal directions, leading to the characteristic Fermi arc reconnection. We discuss the implications of our results to the fourfold symmetry breaking reported in systems where the underlying crystal does not have any structural anisotropy.Comment: 6 pages with 4 figure

Temporal shape super-resolution by intra-frame motion encoding using high-fps structured light

One of the solutions of depth imaging of moving scene is to project a static pattern on the object and use just a single image for reconstruction. However, if the motion of the object is too fast with respect to the exposure time of the image sensor, patterns on the captured image are blurred and reconstruction fails. In this paper, we impose multiple projection patterns into each single captured image to realize temporal super resolution of the depth image sequences. With our method, multiple patterns are projected onto the object with higher fps than possible with a camera. In this case, the observed pattern varies depending on the depth and motion of the object, so we can extract temporal information of the scene from each single image. The decoding process is realized using a learning-based approach where no geometric calibration is needed. Experiments confirm the effectiveness of our method where sequential shapes are reconstructed from a single image. Both quantitative evaluations and comparisons with recent techniques were also conducted.Comment: 9 pages, Published at the International Conference on Computer Vision (ICCV 2017

Confidence intervals of prediction accuracy measures for multivariable prediction models based on the bootstrap-based optimism correction methods

In assessing prediction accuracy of multivariable prediction models, optimism corrections are essential for preventing biased results. However, in most published papers of clinical prediction models, the point estimates of the prediction accuracy measures are corrected by adequate bootstrap-based correction methods, but their confidence intervals are not corrected, e.g., the DeLong's confidence interval is usually used for assessing the C-statistic. These naive methods do not adjust for the optimism bias and do not account for statistical variability in the estimation of parameters in the prediction models. Therefore, their coverage probabilities of the true value of the prediction accuracy measure can be seriously below the nominal level (e.g., 95%). In this article, we provide two generic bootstrap methods, namely (1) location-shifted bootstrap confidence intervals and (2) two-stage bootstrap confidence intervals, that can be generally applied to the bootstrap-based optimism correction methods, i.e., the Harrell's bias correction, 0.632, and 0.632+ methods. In addition, they can be widely applied to various methods for prediction model development involving modern shrinkage methods such as the ridge and lasso regressions. Through numerical evaluations by simulations, the proposed confidence intervals showed favourable coverage performances. Besides, the current standard practices based on the optimism-uncorrected methods showed serious undercoverage properties. To avoid erroneous results, the optimism-uncorrected confidence intervals should not be used in practice, and the adjusted methods are recommended instead. We also developed the R package predboot for implementing these methods (https://github.com/nomahi/predboot). The effectiveness of the proposed methods are illustrated via applications to the GUSTO-I clinical trial

Analytical investigations of thermodynamic effect on cavitation characteristics of sheet and tip leakage vortex cavitation

Vapor production in cavitation extracts the latent heat of evaporation from the surrounding liquid, which decreases the local temperature, and hence the local vapor pressure in the vicinity of cavity. This is called thermodynamic/thermal effect of cavitation. In the present study, the thermodynamic effect on cavitation characteristics such as cavitation compliance and mass flow gain factor, which are known to be important parameters for cavitation instabilities appearing in turbopumps, were studied. Main cavitations in turbopumps, blade and tip leakage vortex cavitations were separately analyzed by simple analytical methods developed based on the potential flow theory, taking account of the latent heat extraction and heat transfer between the cavity and the surrounding fluid. The cavitation characteristics were estimated for the partial cavity and the tip leakage vortex cavity, and the thermodynamic effects on those characteristics were discussed.http://deepblue.lib.umich.edu/bitstream/2027.42/84240/1/CAV2009-final40.pd

Royal Jelly Facilitates Restoration of the Cognitive Ability in Trimethyltin-Intoxicated Mice

Trimethyltin (TMT) is a toxic organotin compound that induces acute neuronal death selectively in the hippocampal dentate gyrus (DG) followed by cognition impairment; however the TMT-injured hippocampal DG itself is reported to regenerate the neuronal cell layer through rapid enhancement of neurogenesis. Neural stem/progenitor cells (NS/NPCs) are present in the adult hippocampal DG, and generate neurons that can function for the cognition ability. Therefore, we investigated whether royal jelly (RJ) stimulates the regenerating processes of the TMT-injured hippocampal DG, and found that orally administered RJ significantly increased the number of DG granule cells and simultaneously improved the cognitive impairment. Furthermore, we have already shown that RJ facilitates neurogenesis of cultured NS/NPCs. These present results, taken together with previous observations, suggest that the orally administered RJ may be a promising avenue for ameliorating neuronal function by regenerating hippocampal granule cells that function in the cognition process