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.     

高阶系统次优控制集结设计方法

针对现有集结降阶方法计算量大，或者不能保证精确集结，本文给出一种新的精确集结降阶算法，提出一种基于精确集结模型，设计高阶系统的低阶次优线性调节器和集结状态降维观测器的方法。     

A bi-criteria model for the inventory aggregation problem under risk pooling

Inventory aggregation, also called Risk Pooling, is one of the most efficient ways to reduce the level of safety stocks thereby reducing inventory across the supply chain. Determining the best level of aggregation is a difficult problem and needs extensive study of all the possible scenarios that can affect this decision. Minimizing costs in a supply chain is no longer the sole priority of businesses. Maintaining a high level of responsiveness is also considered equally important. The conflicting nature of these two criteria makes the solution of the problem difficult. In this paper, we develop a bi-criteria nonlinear stochastic integer programming model to determine the best supply chain distribution network to meet customer demands, where minimizing costs while maintaining high levels of responsiveness is important. We develop a two-stage optimization algorithm to solve this problem.     

高可用性舰船网络系统研究

随着舰船信息系统网络化应用的不断增加,信息系统对舰船网络的依赖性也在不断增强,这对网络持续提供服务的高可用能力提出了更高的要求。鉴于目前舰船网络系统的可用性不能满足舰船信息业务对数据中断恢复时间所提出的要求,将最新的商用高可用性IRF2技术引入舰船网络系统,提出了一种新的舰船网络系统方案。该方案采用双交换机堆叠及跨交换机链路聚合的方式实现网络的网关冗余和路径冗余,简化了网络的逻辑结构,提高了整网的故障恢复时间。通过搭建的原型系统对方案的重要参数进行了测试,结果表明：相比于目前的舰船网络,该方案提升了网络效率,并将故障倒换时间从秒级缩短到了50ms级。     

无线传感器网络在温室环境监测中的应用研究

以温室环境监测为应用背景,分析温室环境监控的特点,给出温室环境监控的系统体系结构,并结合温室监控的具体应用提出节能的数据融合算法,仿真实验表明该算法能有效提高节点能量的利用率和延长网络生命周期。     

基于Ajax的智能RSS聚合系统研究

RSS存在信息过载问题,为了解决该问题,设计了一个基于Ajax的智能聚合系统,使用户可以高效、及时、准确地获取到自己感兴趣的新闻。综合了内容过滤和协作过滤的优缺点,提出了一个改进的过滤算法,提高了过滤性能和准确度。对用户的行为和特征进行建模,系统可以依据用户模型过滤掉用户可能不感兴趣的信息。并将信息过滤技术与RSS聚合技术结合,使用户可以通过RSS聚合系统获取到自己感兴趣的内容,降低信息冗余。     

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

     

Amyloidogenic Properties of Peptides Derived from the VHL Tumor Suppressor Protein

The von Hippel-Lindau tumor suppressor protein (pVHL) is involved in maintaining cellular oxygen homeostasis through the regulated degradation of HIF-α. The intrinsically disordered nature of pVHL makes it prone to aggregation that impairs its function, and this is further aggravated in mutant versions of the protein, thus promoting tumor development. By using in silico analysis, we predicted six peptide fragments from pVHL to be amyloidogenic. This was verified for two of the peptides by biophysical approaches, which demonstrated self-assembly and formation of β-sheet-rich aggregates, which, under transmission electron microscopy, atomic force microscopy, and X-ray diffraction, displayed typical fibrillar amyloid characteristics. These motifs may serve as proxies for exploring the nature of pVHL aggregation.