Understanding and Modeling the Effect of Surfactants in Enhanced Particle Removal from Surfaces in Aqueous Media

The removal of particulate contamination is a critical issue for many manufacturing processes. It is particularly critical to the electronics industry in which small pieces of microscopic debris remaining after chemical mechanical planarization (cmp) using submicron polishing particles can cause device failure. One way to enhance particle removal following the cmp process is to utilize surfactants. Recent research has shown ways to model the effect of surfactants on enhanced particle removal. However, previous research has not demonstrated the effect of ionic strength on enhanced particle removal associated with surfactant use. Past research has also not shown the combined effects of ionic strength and surfactant concentration on enhanced particle removal using surfactants. This article summarizes the parameters affecting particle removal, and it provides data and analysis on the effect of ionic strength as well as the combined effects of ionic strength and surfactant concentration on particle removal following cmp processing.     

ERCM与数据库设计

本文介绍了一种实用的数据库设计方法，它以实体分析法为理论基础，通过对我们日常使用的表进行聚集和归类，完成数据库的逻辑设计，所设计的数据库满足ＢＮＯＦ范式。同时该方法可操作性较强，本文还介绍了自行设计的ＥＲＣＭ数据库辅助设计工具。     

Calendar maintenance of arbitrarily structured systems

A semi-Markov model is constructed that describes an arbitrarily structured multicomponent technological system and takes into account its calendar maintenance. Using an aggregation algorithm, approximate values of stationary reliability characteristics and an optimal term of maintenance work are determined for the system. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 69–86, March–April 2006.     

节理岩体的代表单元集合体模型及弹性参数预测

本文明确提出了节理岩体“代表单元集合体”的概念和模型，通过对节理岩体的“代表单元集合体”进行数值模拟，研究了节理岩体的“代表单元集合体”的变形特性，建立了节理岩体的弹性模型，提出了预测节理岩体宏观等效弹性参数的计算机模拟方法，并将其应用于岩体工程稳定性分析中。     

A time aggregation approach to Markov decision processes

We propose a time aggregation approach for the solution of infinite horizon average cost Markov decision processes via policy iteration. In this approach, policy update is only carried out when the process visits a subset of the state space. As in state aggregation, this approach leads to a reduced state space, which may lead to a substantial reduction in computational and storage requirements, especially for problems with certain structural properties. However, in contrast to state aggregation, which generally results in an approximate model due to the loss of Markov property, time aggregation suffers no loss of accuracy, because the Markov property is preserved. Single sample path-based estimation algorithms are developed that allow the time aggregation approach to be implemented on-line for practical systems. Some numerical and simulation examples are presented to illustrate the ideas and potential computational savings.     

Calorimetric determination of the enthalpy change for the binding of methyl orange to poly(vinylpyrrolidone) in aqueous solution

Thermodynamic parameters have been determined for the interaction of methyl orange and poly(vinylpyrrolidone) in aqueous solutions containing tris, tris and hydrochloric acid, or water only. Enthalpy changes were determined by use of a flow microcalorimeter. Free energy changes were calculated from the results of equilbrium dialysis studies. The results are interpreted in terms of the behaviour of poly(vinylpyrrolidone) in these systems. Analysis of data shows that the hydrophobic interactions in the systems are in the order: tris > wateronly > tris-HC1.     

Biflavonoid-Induced Disruption of Hydrogen Bonds Leads to Amyloid-β Disaggregation

Deposition of amyloid β (Aβ) fibrils in the brain is a key pathologic hallmark of Alzheimer’s disease. A class of polyphenolic biflavonoids is known to have anti-amyloidogenic effects by inhibiting aggregation of Aβ and promoting disaggregation of Aβ fibrils. In the present study, we further sought to investigate the structural basis of the Aβ disaggregating activity of biflavonoids and their interactions at the atomic level. A thioflavin T (ThT) fluorescence assay revealed that amentoflavone-type biflavonoids promote disaggregation of Aβ fibrils with varying potency due to specific structural differences. The computational analysis herein provides the first atomistic details for the mechanism of Aβ disaggregation by biflavonoids. Molecular docking analysis showed that biflavonoids preferentially bind to the aromatic-rich, partially ordered N-termini of Aβ fibril via the π–π interactions. Moreover, docking scores correlate well with the ThT EC₅₀ values. Molecular dynamic simulations revealed that biflavonoids decrease the content of β-sheet in Aβ fibril in a structure-dependent manner. Hydrogen bond analysis further supported that the substitution of hydroxyl groups capable of hydrogen bond formation at two positions on the biflavonoid scaffold leads to significantly disaggregation of Aβ fibrils. Taken together, our data indicate that biflavonoids promote disaggregation of Aβ fibrils due to their ability to disrupt the fibril structure, suggesting biflavonoids as a lead class of compounds to develop a therapeutic agent for Alzheimer’s disease.     

Multi-Scale Dilated Convolutional Neural Network for Hyperspectral Image Classification

基于多尺度空洞卷积神经网络的高光谱图像分类

郑姗姗¹,刘文¹,单锐¹,赵静一²,江国乾³,张智⁴

（1. 燕山大学理学院,河北 秦皇岛 066004;2. 燕山大学机械工程学院,河北 秦皇岛 066004;3. 燕山大学电气工程学院,河北 秦皇岛 066004;4. 北京航天研究所,北京 100094）

创新点说明：

1）将图像分割方法——空洞卷积用于卷积神经网络进行高光谱图像分类,提取更加广泛、抽象的图像特征。

2）构建基于多尺度空洞卷积神经网络的高光谱图像分类方法。搭建多尺度聚合结构,在每个通道中使用快捷连接和空洞卷积结构,有效提取图像特征,避免信息丢失。

研究目的：

针对图像信息丢失问题,得到高精度的高光谱图像分类方法。

研究方法：

在Indian Pines和Pavia University数据集上,与4个已有的高光谱图像分类方法进行对比实验,比较OA, AA和Kappa值。

研究结果：

多尺度空洞卷积神经网络在Indian Pines和Pavia University数据集上OA值分别达到了99.58%,99.92%。AA值分别达到了99.57%,99.90%。Kappa分别达到了99.52%,99.89%。

结论：

1）在卷积神经网络中引入空洞卷积,可以有效避免图像信息丢失。

2）多尺度空洞卷积神经网络能提取更佳的判别性特征,实现高分类性能。

关键词：多尺度聚合;空洞卷积;高光谱图像分类;快捷连接

     

The Antithrombotic Agent Pterostilbene Interferes with Integrin αIIbβ3-Mediated Inside-Out and Outside-In Signals in Human Platelets

Platelets play a crucial role in the physiology of primary hemostasis and pathological processes such as arterial thrombosis; thus, developing a therapeutic target that prevents platelet activation can reduce arterial thrombosis. Pterostilbene (PTE) has remarkable pharmacological activities, including anticancer and neuroprotection. Few studies have reported the effects of pterostilbene on platelet activation. Thus, we examined the inhibitory mechanisms of pterostilbene in human platelets and its role in vascular thrombosis prevention in mice. At low concentrations (2–8 μM), pterostilbene strongly inhibited collagen-induced platelet aggregation. Furthermore, pterostilbene markedly diminished Lyn, Fyn, and Syk phosphorylation and hydroxyl radical formation stimulated by collagen. Moreover, PTE directly hindered integrin α_IIbβ₃ activation through interfering with PAC-1 binding stimulated by collagen. In addition, pterostilbene affected integrin α_IIbβ₃-mediated outside-in signaling, such as integrin β₃, Src, and FAK phosphorylation, and reduced the number of adherent platelets and the single platelet spreading area on immobilized fibrinogen as well as thrombin-stimulated fibrin clot retraction. Furthermore, pterostilbene substantially prolonged the occlusion time of thrombotic platelet plug formation in mice. This study demonstrated that pterostilbene exhibits a strong activity against platelet activation through the inhibition of integrin α_IIbβ₃-mediated inside-out and outside-in signaling, suggesting that pterostilbene can serve as a therapeutic agent for thromboembolic disorders.     

Solubility and Aggregation of Selected Proteins Interpreted on the Basis of Hydrophobicity Distribution

Protein solubility is based on the compatibility of the specific protein surface with the polar aquatic environment. The exposure of polar residues to the protein surface promotes the protein’s solubility in the polar environment. The aquatic environment also influences the folding process by favoring the centralization of hydrophobic residues with the simultaneous exposure to polar residues. The degree of compatibility of the residue distribution, with the model of the concentration of hydrophobic residues in the center of the molecule, with the simultaneous exposure of polar residues is determined by the sequence of amino acids in the chain. The fuzzy oil drop model enables the quantification of the degree of compatibility of the hydrophobicity distribution observed in the protein to a form fully consistent with the Gaussian 3D function, which expresses an idealized distribution that meets the preferences of the polar water environment. The varied degrees of compatibility of the distribution observed with the idealized one allow the prediction of preferences to interactions with molecules of different polarity, including water molecules in particular. This paper analyzes a set of proteins with different levels of hydrophobicity distribution in the context of the solubility of a given protein and the possibility of complex formation.