基于多角度偏振特性的云相态识别及验证

云相态识别是云参数研究的重要组成部分,为了有效识别水云和冰云,根据水云和冰云微物理性质的差别,研究了水云和冰云的单次散射特性,采用基丁倍加累加法的,人量辐射传输方程模拟了水云和冰云的多角度偏振特件.模拟结果表明,光谱的多角度偏振特件能够体现山水云粒子和冰云粒子微物理性质的差异,云在特定方向反射的偏振辐射强度对云相态非常敏感,可以用米进行云相念的识别,在模拟的基础上进行了云相态识别算法的研究,并利用多角度偏振卫星数据--POLDER 0.865μm通道数据进行了实例分析.识别结果与MODIS云相态产品及其1.38μm卷云榆测结果进行了比较.分析结果表明,基于多角度偏振特性云相态识别算法可以有效地进行云相态识别.     

Translating Molecular Recognition into a Pressure Signal to enable Rapid,Sensitive, and Portable Biomedical Analysis

Herein, we demonstrate that a very familiar, yet underutilized, physical parameter—gas pressure—can serve as signal readout for highly sensitive bioanalysis. Integration of a catalyzed gas‐generation reaction with a molecular recognition component leads to significant pressure changes, which can be measured with high sensitivity using a low‐cost and portable pressure meter. This new signaling strategy opens up a new way for simple, portable, yet highly sensitive biomedical analysis in a variety of settings.     

辐射增强PP／BR共混体系的力学性能

研究了在多官能团单体－三烯丙基异氰酸酯存在下，共混体系聚丙烯／１．４－聚丁二烯橡胶的辐射效应，用ＤＳＣ，动态粘弹谱对其进行表征。结果显示，三烯丙基异氰酸酯主要分布于聚丙烯／１．４－聚丁二烯橡胶共混物的界面自高能射线作用下，被引发参与界面反应，从而改善了共混体系的相容性，增强也界面粘接，提高了共混物的力学性能。     

Spatial Correlation Network and Regional Differences for the Development of Digital Economy in China

The rapid development of the digital economy is a powerful driving force to promote high-quality economic growth all over the world. Although a number of studies have been conducted to investigate the development of the digital economy in China, these studies pay little attention to the spatial linkages between the 30 provinces in China and the developmental differences between northern and southern China. Using Chinese digital economic data from 2004 to 2019, we propose an index system to measure the developmental levels of the digital economy and obtain the annual developmental levels of these provinces by using the factor analysis method. We analyze the regional differences of developmental levels by using the Theil index and kernel density estimation method. More importantly, the network method is used to analyze the correlations between the developmental levels of the digital economy in all provinces of China. By decomposing regional differences, our study shows that polarized and uncoordinated development is prominent. The development level of the digital economy in the southern region is higher than that in the northern region. In terms of regional correlations, the network study suggests that there are beneficial and spillover effects of the digital economy development between provinces. Based on the analysis results, we propose policies for improving the development of the digital economy in China.     

Inference of Molecular Regulatory Systems Using Statistical Path-Consistency Algorithm

One of the key challenges in systems biology and molecular sciences is how to infer regulatory relationships between genes and proteins using high-throughout omics datasets. Although a wide range of methods have been designed to reverse engineer the regulatory networks, recent studies show that the inferred network may depend on the variable order in the dataset. In this work, we develop a new algorithm, called the statistical path-consistency algorithm (SPCA), to solve the problem of the dependence of variable order. This method generates a number of different variable orders using random samples, and then infers a network by using the path-consistent algorithm based on each variable order. We propose measures to determine the edge weights using the corresponding edge weights in the inferred networks, and choose the edges with the largest weights as the putative regulations between genes or proteins. The developed method is rigorously assessed by the six benchmark networks in DREAM challenges, the mitogen-activated protein (MAP) kinase pathway, and a cancer-specific gene regulatory network. The inferred networks are compared with those obtained by using two up-to-date inference methods. The accuracy of the inferred networks shows that the developed method is effective for discovering molecular regulatory systems.     

Divide-and-conquer calculations for clean surfaces and surface adsorption

The divide-and-conquer density-functional approach is implemented for electronic structure calculations of clean surfaces and surface adsorption. The method divides a semi-infinite solid-state system into subsystems and determines each subsystem density separately. We have applied the method to study two low index Li surfaces and the chemisorption of a monolayer of atomic hydrogen on the Li(100) surface. Surface and adsorption energies converge well with respect to the number of buffer atoms and surface layers. Our converged energies are in very good agreement with accurate theoretical and available experimental results. Received: 8 January 1997 / Accepted: 14 January 1997     

Binomial leap methods for simulating stochastic chemical kinetics

This paper discusses efficient simulation methods for stochastic chemical kinetics. Based on the tau-leap and midpoint tau-leap methods of Gillespie [D. T. Gillespie, J. Chem. Phys. 115, 1716 (2001)], binomial random variables are used in these leap methods rather than Poisson random variables. The motivation for this approach is to improve the efficiency of the Poisson leap methods by using larger stepsizes. Unlike Poisson random variables whose range of sample values is from zero to infinity, binomial random variables have a finite range of sample values. This probabilistic property has been used to restrict possible reaction numbers and to avoid negative molecular numbers in stochastic simulations when larger stepsize is used. In this approach a binomial random variable is defined for a single reaction channel in order to keep the reaction number of this channel below the numbers of molecules that undergo this reaction channel. A sampling technique is also designed for the total reaction number of a reactant species that undergoes two or more reaction channels. Samples for the total reaction number are not greater than the molecular number of this species. In addition, probability properties of the binomial random variables provide stepsize conditions for restricting reaction numbers in a chosen time interval. These stepsize conditions are important properties of robust leap control strategies. Numerical results indicate that the proposed binomial leap methods can be applied to a wide range of chemical reaction systems with very good accuracy and significant improvement on efficiency over existing approaches.     

Portable detection of serum HER-2 in breast cancer by a pressure-based platform

Analytical and Bioanalytical Chemistry - A high serum HER-2 extracellular domain (sHER-2 ECD) level has a reverse association with tumor behaviors. In this study, a portable platform for the...     

Translating Molecular Recognition into a Pressure Signal to enable Rapid,Sensitive, and Portable Biomedical Analysis

Herein, we demonstrate that a very familiar, yet underutilized, physical parameter—gas pressure—can serve as signal readout for highly sensitive bioanalysis. Integration of a catalyzed gas‐generation reaction with a molecular recognition component leads to significant pressure changes, which can be measured with high sensitivity using a low‐cost and portable pressure meter. This new signaling strategy opens up a new way for simple, portable, yet highly sensitive biomedical analysis in a variety of settings.