Global well-posedness and optimal time decay rates of solutions to the pressureless Euler-Navier-Stokes system

In this paper, we present a new framework for the global well-posedness and large-time behavior of a two-phase flow system, which consists of the pressureless Euler equations and incompressible Navier-Stokes equations coupled through the drag force. To overcome the difficulties arising from the absence of the pressure term in the Euler equations, we establish the time decay estimates of the high-order derivative of the velocity to obtain uniform estimates of the fluid density. The upper bound decay rates are obtained by designing a new functional and the lower bound decay rates are achieved by selecting specific initial data. Moreover, the upper bound decay rates are the same order as the lower one. Therefore, the time decay rates are optimal. When the fluid density in the pressureless Euler flow vanishes, the system is reduced into an incompressible Navier-Stokes flow. In this case, our works coincide with the classical results by Schonbek \cite{M.S3} [JAMS,1991], which can be regarded as a generalization from a single fluid model to the two-phase fluid one

Balance-approach For Mechanical Properties Test of Micro Fabricated Structure

Copyright 1997 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.A simple and effective method using a balance to measure micro force and corresponding deflection is presented. The method is proved to be very practical in testing the force-deflection behavior of silicon cantilever, in which the Young’s modulus of the material can be calculated, and in investigating the static performance of bulk micromachined capacitive accelerometers. The balance approach for micro force-displacement measurement is very attractive for its easiness in operation, low cost and higher resolution.http://dx.doi.org/10.1117/12.28449

A Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understanding

Multi-intent detection and slot filling joint models are gaining increasing traction since they are closer to complicated real-world scenarios. However, existing approaches (1) focus on identifying implicit correlations between utterances and one-hot encoded labels in both tasks while ignoring explicit label characteristics; (2) directly incorporate multi-intent information for each token, which could lead to incorrect slot prediction due to the introduction of irrelevant intent. In this paper, we propose a framework termed DGIF, which first leverages the semantic information of labels to give the model additional signals and enriched priors. Then, a multi-grain interactive graph is constructed to model correlations between intents and slots. Specifically, we propose a novel approach to construct the interactive graph based on the injection of label semantics, which can automatically update the graph to better alleviate error propagation. Experimental results show that our framework significantly outperforms existing approaches, obtaining a relative improvement of 13.7% over the previous best model on the MixATIS dataset in overall accuracy.Comment: Submitted to ICASSP 202

The initial value problem for the compressible Navier-Stokes equations without heat conductivity

Abstract(#br)In this paper, we are concerned with the global existence and convergence rates of strong solutions for the compressible Navier-Stokes equations without heat conductivity in R 3 . The global existence and uniqueness of strong solutions are established by the delicate energy method under the condition that the initial data are close to the constant equilibrium state in H 2 -framework. Furthermore, if additionally the initial data belong to L 1 , the optimal convergence rates of the solutions in L 2 -norm and convergence rates of their spatial derivatives in L 2 -norm are obtained

Structure Design and Fabrication of Symmetric Force-balance Micromachining Capacitive Accelerometer

Copyright 1997 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.A novel KOH silicon maskless anisotropic etching technology is adopted to fabricate micromachining silicon mass-beam structure accelerometer. Lateral sensitivity effect in normal accelerometer is eliminated because the beams which are thinner than 15 micrometers have been formed in the middle of the seismic mass. Based on the calculation of sensitivity and basic resonance frequency of two kinds of bulk micromachining accelerometers, the structure parameters of cantilever and double-side-supported accelerometer have been optimized by using the sensitivity-frequency product as the figure of merit of a structure. The different etching characteristics of {311} and {100} plane of silicon in KOH maskless anisotropic etching process have been investigated thoroughly and utilized in the fabrication of symmetric mass- beam structure. Special damping design has been proposed to reduce the damping ratio of the device in order to improve the dynamic performance of the accelerometer. Preliminary measurement of the static characteristics of the structure has been performed with a force-deflection balance measurement apparatus.http://dx.doi.org/10.1117/12.28449

The 2011 Survey on Hypertensive Disorders of Pregnancy (HDP) in China:Prevalence, Risk Factors, Complications, Pregnancy and Perinatal Outcomes

Hypertensive disorders of pregnancy (HDP) are a group of medical complications in pregnancy and also a risk factor for severe pregnancy outcomes, but it lacks a large-scale epidemiological investigation in recent years. This survey represents a multicenter cross-sectional retrospective study to estimate the prevalence and analyze the risk factors for HDP among the pregnant women who had referred for delivery between January 1st 2011 and December 31st 2011 in China Mainland. A total of 112,386 pregnant women were investigated from 38 secondary and tertiary specialized or general hospitals randomly selected across the country, of which 5,869 had HDP, accounting for 5.22% of all pregnancies. There were significant differences in the prevalence of HDP between geographical regions, in which the North China showed the highest (7.44%) and Central China showed the lowest (1.23%). Of six subtypes of HDP, severe preeclampsia accounted for 39.96%, gestational hypertension for 31.40%, mild preeclampsia for 15.13%, chronic hypertension in pregnancy for 6.00%, preeclampsia superimposed on chronic hypertension for 3.68% and eclampsia for 0.89%. A number of risk factors for HDP were identified, including twin pregnancy, age of >35 years, overweight and obesity, primipara, history of hypertension as well as family history of hypertension and diabetes. The prevalence of pre-term birth, placental abruption and postpartum hemorrhage were significantly higher in women with HDP than those without HDP. The possible risk factors confirmed in this study may be useful for the development of early diagnosis and appropriate treatment of HDP

FTM: A Frame-Level Timeline Modeling Method for Temporal Graph Representation Learning

Learning representations for graph-structured data is essential for graph analytical tasks. While remarkable progress has been made on static graphs, researches on temporal graphs are still in its beginning stage. The bottleneck of the temporal graph representation learning approach is the neighborhood aggregation strategy, based on which graph attributes share and gather information explicitly. Existing neighborhood aggregation strategies fail to capture either the short-term features or the long-term features of temporal graph attributes, leading to unsatisfactory model performance and even poor robustness and domain generality of the representation learning method. To address this problem, we propose a Frame-level Timeline Modeling (FTM) method that helps to capture both short-term and long-term features and thus learns more informative representations on temporal graphs. In particular, we present a novel link-based framing technique to preserve the short-term features and then incorporate a timeline aggregator module to capture the intrinsic dynamics of graph evolution as long-term features. Our method can be easily assembled with most temporal GNNs. Extensive experiments on common datasets show that our method brings great improvements to the capability, robustness, and domain generality of backbone methods in downstream tasks. Our code can be found at https://github.com/yeeeqichen/FTM

Balance-Approach For Load-Displacement Measurement Of Microstructures

A simple and effective method using a balance to measure micro force and corresponding deflection is presented. The method is proved to be very practical in testing the force–deflection behavior of silicon cantilever, in which the Youngs modulus of the material can be calculated, and in investigating the static performance of bulk micromachined capacitive accelerometers. The same value of the Youngs modulus was obtained on much different microstructures including the single silicon cantilevers and the beam-island structures of capacitive accelerometers. The balance approach for micro force–displacement measurement is very attractive for its easiness in operation, low cost and higher resolution.http://dx.doi.org/10.1016/S0957-4158(98)00018-