闽江口表层沉积物中碎屑矿物的研究

研究闽江口表层沉积物中碎屑矿物的组成，含量及其分布特征，探讨泥沙的来源及重矿物与沉积环境的关系，结果表明，碎屑矿物共有４６种，其中轻矿物１２种，重矿物３４种。矿物组份的种类示出闽江口的碎屑物质主要来源于闽江流域的基岩风化、侵蚀产物，而重矿物的含量分布则与其所处的水力学条件和地形地貌关系密切。     

The neuronal sortilin-related receptor SORL1 is genetically associated with Alzheimer disease

The recycling of the amyloid precursor protein (APP) from the cell surface via the endocytic pathways plays a key role in the generation of amyloid beta peptide (Abeta) in Alzheimer disease. We report here that inherited variants in the SORL1 neuronal sorting receptor are associated with late-onset Alzheimer disease. These variants, which occur in at least two different clusters of intronic sequences within the SORL1 gene (also known as LR11 or SORLA) may regulate tissue-specific expression of SORL1. We also show that SORL1 directs trafficking of APP into recycling pathways and that when SORL1 is underexpressed, APP is sorted into Abeta-generating compartments. These data suggest that inherited or acquired changes in SORL1 expression or function are mechanistically involved in causing Alzheimer disease.     

非最小相位系统传递函数的演化模型降阶

针对非最小相位系统传递函数的模型降阶工作,通过对频域误差平方和加权的形式,提出了同时考虑频域幅值与相位因素的多目标参数优化指标。针对传统的求解多目标优化方法的不足,提出应用演化算法对此复杂的目标函数进行优化的策略。计算实例说明,使用演化优化方法可以获得幅值与相位特性均较好的降阶模型。     

适于大斜视角星载SAR系统的改进距离-多普勒算法

分析了当天线斜视角增大时,导致传统距离-多普勒成像算法性能下降的主要误差来源.提出了一种适合大斜视角星载SAR系统的改进距离-多普勒算法,并给出了处理仿真点目标数据得到图像质量的比较.结果表明,在大斜视角情况下,改进算法的性能远大于传统的距离\|多普勒成像算法.     

An Adaptive Identification and Control Scheme Using Radial Basis Function Networks

1.INTaODUCTIONThemultilayerfeedforwardneuralnetworks(MFNN)hasbeenwidelyappliedinmanyfieldssuchaspatternrecognition,nonlinearoptimization,systemidentificationandcontrol.Thesimpleback-propagation(BP)learningalgorithmisusuallyadoptedtoupdateitsweights.TheBPalgorithm,however,suffersdrawbacksofslowconvergenceandunpredictablesolutionsduringlearning.Althoughmailyapproachessuchasvariablestepsize,conjugategradient,pseudo-Newtonmethods[4]andothermethods[3,10],havebeendevelopedtoovercometheproble…     

MetaOJ: A Massive Distributed Online Judge System

Online Judge(OJ) systems are a basic and important component of computer education. Here, we present MetaOJ, an OJ system that can be used for holding massive programming tests online. MetaOJ is designed to create a distributed, fault-tolerant, and easy-to-scale OJ system from an existing ordinary OJ system by adding several interfaces into it and creating multiple instances of it. Our case on modifying the TUOJ system shows that the modification adds no more than 3% lines of code and the performance loss on a single OJ instance is no more than 12%. We also introduce mechanisms to integrate the system with cloud infrastructure to automate the deployment process. MetaOJ provides a solution for those OJ systems that are designed for a specific programming contest and are now facing performance bottlenecks.     

Single-Index Quantile Regression with Left Truncated Data

The purpose of this paper is two fold. First, the authors investigate quantile regression(QR) estimation for single-index QR models when the response is subject to random left truncation.The random weights are introduced to deal with left truncated data and the associated iteration estimation method is proposed. The asymptotic properties for the proposed QR estimates of the index parameter and unknown link function are both obtained. Further, by combining the QR loss function and the adaptive LA...     

Model Averaging Multistep Prediction in an Infinite Order Autoregressive Process

The key issue in the frequentist model averaging is the choice of weights. In this paper, the authors advocate an asymptotic framework of mean-squared prediction error(MSPE) and develop a model averaging criterion for multistep prediction in an infinite order autoregressive(AR(∞)) process.Under the assumption that the order of the candidate model is bounded, this criterion is proved to be asymptotically optimal, in the sense of achieving the lowest out of sample MSPE for the samerealization pred...     

A new method for uniform local heating deep in body using ultrasound phased-array system

A new method for targeted heating of deep tissue was developed by using an ultrasound phased-array system which can generate various multiple foci patterns by electronically changing its amplitude or phase pattern. This method involves using a technique of combining switching and rotating of multiple foci patterns to create a uniform temperature over tissue volumes in various size. Using this method, the target tissue deep in the body can be heated to a specified temperature, which gives conditions for thermo-sensitive liposomes release. A simulation study for a 108-element, spherically sectioned array was performed to determine an optimal heating scheme from a set of multiple focus fields which were produced by inputting different combinations of phases and amplitudes. Comparisons of a static multiple foci field, the switched fields and the switched-rotated fields indicated that the technique of combining switching and rotating of multiple foci patterns has advantages of both lowering the peak temperature and evening the temperature distribution. The simulation results also show that the therapeutic heating zones in various size employing the combined method. These results offer significant data for designing thermotherapy equipment for tumor-specific drug release with thermo-sensitive liposomes.