一种新型极性脲丙基-C30固定相的制备和性能评价

以3-脲丙基三甲氧基硅烷为偶联剂，制备了一种新型极性脲丙基-C30（TPU-C30）反相色谱固定相。采用扫描电子显微镜、元素分析、红外光谱和热分析等对该固定相进行表征。结果表明，TPU-C30固定相已成功制备，连续制备3次固定相，其元素含量的相对偏差均小于5%，说明该合成工艺重复性良好。以不同极性、位置异构、碱性化合物为溶质探针，以传统的C18色谱柱与C30色谱柱为参比，对制备的固定相的色谱性能进行了研究。研究结果表明，TPU-C30固定相具有不同于传统C18柱、C30柱的选择性和更优的择形性，明显改善了碱性物质的峰形，其具有广阔的应用空间。     

一种不同地面分辨率图像的拼接算法

航空遥感监测中变焦镜头的广泛应用以及飞行高度的变化会获得不同地面分辨率的航空影像,因此为了实时监控到飞行区域的整体情况,需要对不同地面分辨率的图像进行拼接。提出了针对不同地面分辨率图像进行拼接的方法。首先用四分法对图像进行分割,检测变化倍率,选择配准策略;然后用基于加速鲁棒性特征(Speeded-Up Robust Features,SURF)的算法对相邻图像进行拼接。获得了焦距变化从高倍过渡到低倍,或从低倍过渡到高倍的拼接图像。通过航空变焦模拟影像的拼接实验和地面变焦影像的拼接实验表明,该方法能够对不同地面分辨率的图像进行拼接,且拼接结果均以高分辨率为基准。     

Single-Round DNA Aptamer Selection by Combined Use of Capillary Electrophoresis and Next Generation Sequencing: An Aptaomics Approach for Identifying Unique Functional Protein-Binding DNA Aptamers

In DNA aptamer selection, existing methods do not discriminate aptamer sequences based on their binding affinity and function and the reproducibility of the selection is often poor, even for the selection of well-known aptamers like those that bind the commonly used model protein thrombin. In the present study, a novel single-round selection method (SR-CE selection) was developed by combining capillary electrophoresis (CE) with next generation sequencing. Using SR-CE selection, a successful semi-quantitative and semi-comprehensive aptamer selection for thrombin was demonstrated with high reproducibility for the first time. Selection rules based on dissociation equilibria and kinetics were devised to obtain families of analogous sequences. Selected sequences of the same family were shown to bind thrombin with high affinity. Furthermore, data acquired from SR-CE selection was mined by creating sub-libraries that were categorized by the functionality of the aptamers (e. g., pre-organized aptamers versus structure-induced aptamers). Using this approach, a novel fluorescent molecular recognition sensor for thrombin with nanomolar detection limits was discovered. Thus, in this proof-of-concept report, we have demonstrated the potential of a “DNA Aptaomics” approach to systematically design functional aptamers as well as to obtain high affinity aptamers.     

Random frog: An efficient reversible jump Markov Chain Monte Carlo-like approach for variable selection with applications to gene selection and disease classification

The identification of disease-relevant genes represents a challenge in microarray-based disease diagnosis where the sample size is often limited. Among established methods, reversible jump Markov Chain Monte Carlo (RJMCMC) methods have proven to be quite promising for variable selection. However, the design and application of an RJMCMC algorithm requires, for example, special criteria for prior distributions. Also, the simulation from joint posterior distributions of models is computationally extensive, and may even be mathematically intractable. These disadvantages may limit the applications of RJMCMC algorithms. Therefore, the development of algorithms that possess the advantages of RJMCMC methods and are also efficient and easy to follow for selecting disease-associated genes is required. Here we report a RJMCMC-like method, called random frog that possesses the advantages of RJMCMC methods and is much easier to implement. Using the colon and the estrogen gene expression datasets, we show that random frog is effective in identifying discriminating genes. The top 2 ranked genes for colon and estrogen are Z50753, U00968, and Y10871_at, Z22536_at, respectively. (The source codes with GNU General Public License Version 2.0 are freely available to non-commercial users at: http://code.google.com/p/randomfrog/.)     

A maximum-efficiency-first multi-path route selection strategy for optical burst switching networks

In this paper, the impact of a path selection on other existing paths in optical burst switching (OBS) networks is studied by analyzing the contention among different traffic streams and the interaction between the route selection and traffic load balance. The results show that there exists a mutual reinforcement interaction among the traffic load of a path, the path burst loss ratio and the contention ability of the path when burst loss ratio based multi-path selection strategies are adopted, which may increase the unbalance of traffic and lead to severe congestion further. A maximum-efficiency-first multi-path selection strategy, which considers the performance of the burst flows and the impact of a path selection on existing OBS paths at the same time by a combined metric of route efficiency, is proposed to maximize the utility of the burst flows and minimize the increment of lost throughput on the path. The performance of the proposed multi-path selection strategy is evaluated through simulation. The results show that the presented strategy obviously outperforms the least burst loss ratio strategy and shortest path first strategy in terms of the burst loss ratio in the practical unbalanced background traffic, especially when the network is heavily loaded.     

Monotonicity of certain integrals involving gamma distributions and their applications in multiple comparisons

Barlow and Gupta (1969) and Alam (1970) studied the monotonicity of two integrals, involving gamma distributions, that arise in certain ranking and selection problems. In this paper, we shall unify their results by studying the monotonicity of two generalized versions of integrals considered by them. We will also provide applications of derived results in study of certain multiple comparison procedures.     

基于图像特征检测和匹配的无人船航行姿态角提取方法

计算机视觉的飞速发展, 使得采用视觉技术辅助无人船航行成为可能. 在无人船巡航过程中, 获取船体航向是航行控制的必备基础. 特征匹配是无人船相关视觉技术中的重要部分, 是目标识别和定位等功能的关键步骤. 获取无人船运动姿态的基本步骤是对图像前后帧进行有效的特征提取和匹配. 针对水域环境中的图像静态特征提取速度慢、精度低的问题, 本文提出一种图像匹配方法以求取无人船的航行姿态角. 首先对图像预处理, 并对有效区域进行特征提取. 其次, 设计一种基于描述子相似度的初始特征匹配策略. 再其次, 筛选特征匹配对, 优化模型参数. 最后, 通过前后帧旋转矩阵计算航行姿态角. 实验表明, 该方法能有效提取无人船的航行姿态角.     

有效因子综合偏好强度与CVaR整合优化模型

本文从股票多维特征因子中选择有效因子,融合形成最大化有效因子综合偏好强度(IPS)的附加理性,构建并验证IPS-均值-CVaR投资组合优化模型。基于沪深300股2006~2015年数据分析显示:(1)有效因子IPS投资组合优越于单因子投资组合;(2)IPS方法相较于因子打分法,具有更优的多维数据整合功效;(3)IPS-均值-CVaR投资组合优化模型相对于均值-CVaR模型具有更优越的资产选择能力,也拓展了投资组合模型的多维数据处理能力和适用性。     

On generalized Nash equilibrium problems with linear coupling constraints and mixed-integer variables

ABSTRACT

We define and discuss different enumerative methods to compute solutions of generalized Nash equilibrium problems with linear coupling constraints and mixed-integer variables. We propose both branch-and-bound methods based on merit functions for the mixed-integer game, and branch-and-prune methods that exploit the concept of dominance to make effective cuts. We show that under mild assumptions the equilibrium set of the game is finite and we define an enumerative method to compute the whole of it. We show that our branch-and-prune method can be suitably modified in order to make a general equilibrium selection over the solution set of the mixed-integer game. We define an application in economics that can be modelled as a Nash game with linear coupling constraints and mixed-integer variables, and we adapt the branch-and-prune method to efficiently solve it.