The Analysis of Electrode Roughness of Medical Electromagnetic Flowmeter on the Measurement of the Impact

Electromagnetic flowmeter is used in medical devices such as dialysis machine, or a liquid flow rate of oxygen is detected, high accuracy is required. The electrode and the insulation lining used for a period of time, because of erosion by the fluid is worn, they will produce a surface roughness. And the surface roughness will be larger with the increase of the use of time, the sensor pipe flow field will be affected. According to the weight function theory, the change of the flow field near the electrode will greatly affect the measurement signal of the electromagnetic flowmeter, this will make electromagnetic flowmeter measurement error. In this paper, through the simulation calculation for the roughness of the electrode change caused by the result of the measurement error. The conclusion is that in order to keep the accuracy of measurement, after a period of use the flowmeter, the electrode must be replaced

Locally-Enriched Cross-Reconstruction for Few-Shot Fine-Grained Image Classification

Few-shot fine-grained image classification has attracted considerable attention in recent years for its realistic setting to imitate how humans conduct recognition tasks. Metric-based few-shot classifiers have achieved high accuracies. However, their metric function usually requires two arguments of vectors, while transforming or reshaping three-dimensional feature maps to vectors can result in loss of spatial information. Image reconstruction is thus involved to retain more appearance details: the test images are reconstructed by different classes and then classified to the one with the smallest reconstruction error. However, discriminative local information, vital to distinguish sub-categories in fine-grained images with high similarities, is not well elaborated when only the base features from a usual embedding module are adopted for reconstruction. Hence, we propose the novel local content-enriched cross-reconstruction network (LCCRN) for few-shot fine-grained classification. In LCCRN, we design two new modules: the local content-enriched module (LCEM) to learn the discriminative local features, and the cross-reconstruction module (CRM) to fully engage the local features with the appearance details obtained from a separate embedding module. The classification score is calculated based on the weighted sum of reconstruction errors of the cross-reconstruction tasks, with weights learnt from the training process. Extensive experiments on four fine-grained datasets showcase the superior classification performance of LCCRN compared with the state-of-the-art few-shot classification methods. Codes are available at: https://github.com/lutsong/LCCRN

Power-Law Decay of Standing Waves on the Surface of Topological Insulators

We propose a general theory on the standing waves (quasiparticle interference pattern) caused by the scattering of surface states off step edges in topological insulators, in which the extremal points on the constant energy contour of surface band play the dominant role. Experimentally we image the interference patterns on both Bi$_2$Te$_3$ and Bi$_2$Se$_3$ films by measuring the local density of states using a scanning tunneling microscope. The observed decay indices of the standing waves agree excellently with the theoretical prediction: In Bi$_2$Se$_3$, only a single decay index of -3/2 exists; while in Bi$_2$Te$_3$ with strongly warped surface band, it varies from -3/2 to -1/2 and finally to -1 as the energy increases. The -1/2 decay indicates that the suppression of backscattering due to time-reversal symmetry does not necessarily lead to a spatial decay rate faster than that in the conventional two-dimensional electron system. Our formalism can also explain the characteristic scattering wave vectors of the standing wave caused by non-magnetic impurities on Bi$_2$Te$_3$.Comment: 4 pages, 3 figure

Limits to sustained energy intake. XXX : Constraint or restraint? Manipulations of food supply show peak food intake in lactation is constrained

This work was partly supported by grants (No. 31670417, 31870388) from the National Natural Science Foundation of China and the Chinese Academy of Sciences Strategic program (XDB13030100). All data is available in the main text or the supplementary materials. Additional data related to this paper may be requested from the authors. Requests should be addressed to Z.J.Z. and J.R.SPeer reviewedPublisher PD