A Molecular Brush Approach to Enhance Quantum Yield and Suppress Nonspecific Interactions of Conjugated Polyelectrolyte for Targeted Far‐Red/Near‐Infrared Fluorescence Cell Imaging

A red‐fluorescent conjugated polyelectrolyte (CPE, P2 ) is grafted with dense poly(ethylene glycol) (PEG) chains via click chemistry and subsequently modified with folic acid to form a molecular brush based cellular probe ( P4 ). P4 self‐assembles into a core–shell nanostructure in aqueous medium with an average size of 130 nm measured by laser light scattering. As compared to P2 , P4 possesses not only a substantially higher quantum yield (11%), but also reduced nonspecific interactions with biomolecules in aqueous medium due to the shielding effect of PEG. In conjunction with its high photostability and low cytotoxicity, utilization of P4 as a far‐red/near‐infrared cellular probe allows for effective visualization and discrimination of MCF‐7 cancer cells from NIH‐3T3 normal cells in a high contrast, selective, and nonviral manner. This study thus demonstrates a flexible molecular brush approach to overcome the intrinsic drawbacks of CPEs for advanced bioimaging applications.     

一种可信计算平台及信任链传递验证方法

信任链是可信计算机系统的重要部分,它保证计算机系统从可信源头至系统各组件的可信,但存在信任链建立过程的信任度逐层衰减问题。文中通过可信平台控制模块授权CPU进行链式度量,同时TPCM尾随CPU对信任链进行实时的、随机的和分块的度量,然后在平台信任链中嵌入检查点,统计并检查各块运行时间,从而判断各信任节点是否被篡改。该方法提高了信任链建立和验证的实时性,尤其可以防御针对信任链的时间差攻击。     

针对JPEG格式的数字隐写与隐写分析

数字隐写和隐写分析是信息隐藏技术的重要分支。JPEG图像是隐写术最常见的载体,因而研究以JPEG图像为载体的隐写和隐写分析具有重要意义。剖析了JPEG文件结构,提出了基于JPEG格式的隐写方案;并针对该方案提出了相应的隐写分析方案;然后通过大量统计,建立了两个数据库,并最终构建了一个准实时隐藏信息提取系统。该系统从5万幅互联网上的JPEG图像提出了信息,并有效攻击了11种互联网上的隐写软件。     

Algorithm design for a class of base station location problems in sensor networks

Base station placement has significant impact on sensor network performance. Despite its significance, results on this problem remain limited, particularly theoretical results that can provide performance guarantee. This paper proposes a set of procedure to design (1− ε) approximation algorithms for base station placement problems under any desired small error bound ε > 0. It offers a general framework to transform infinite search space to a finite-element search space with performance guarantee. We apply this procedure to solve two practical problems. In the first problem where the objective is to maximize network lifetime, an approximation algorithm designed through this procedure offers 1/ε² complexity reduction when compared to a state-of-the-art algorithm. This represents the best known result to this problem. In the second problem, we apply the design procedure to address base station placement problem when the optimization objective is to maximize network capacity. Our (1− ε) approximation algorithm is the first theoretical result on this problem. Yi Shi received his B.S. degree from University of Science and Technology of China, Hefei, China, in 1998, a M.S. degree from Institute of Software, Chinese Academy of Science, Beijing, China, in 2001, and a second M.S. degree from Virginia Tech, Blacksburg, VA, in 2003, all in computer science. He is currently working toward his Ph.D. degree in electrical and computer engineering at Virginia Tech. While in undergraduate, he was a recipient of Meritorious Award in International Mathematical Contest in Modeling and 1997 and 1998, respectively. His current research focuses on algorithms and optimizations for wireless sensor networks, wireless ad hoc networks, UWB-based networks, and SDR-based networks. His work has appeared in journals and highly selective international conferences (ACM Mobicom, ACM Mobihoc, and IEEE Infocom). Y. Thomas Hou received the B.E. degree from the City College of New York in 1991, the M.S. degree from Columbia University in 1993, and the Ph.D. degree from Polytechnic University, Brooklyn, New York, in 1998, all in Electrical Engineering. Since Fall 2002, he has been an Assistant Professor at Virginia Tech, the Bradley Department of Electrical and Computer Engineering, Blacksburg, VA. His current research interests are radio resource (spectrum) management and networking for software-defined radio wireless networks, optimization and algorithm design for wireless ad hoc and sensor networks, and video communications over dynamic ad hoc networks. From 1997 to 2002, Dr. Hou was a Researcher at Fujitsu Laboratories of America, Sunnyvale, CA, where he worked on scalable architectures, protocols, and implementations for differentiated services Internet, service overlay networking, video streaming, and network bandwidth allocation policies and distributed flow control algorithms. Prof. Hou is a recipient of an Office of Naval Research (ONR) Young Investigator Award (2003) and a National Science Foundation (NSF) CAREER Award (2004). He is a Co-Chair of Technical Program Committee of the Second International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM 2007), Orlando, FL, August 1–3, 2007. He also was the Chair of the First IEEE Workshop on Networking Technologies for Software Defined Radio Networks, September 25, 2006, Reston, VA. Prof. Hou holds two U.S. patents and has three more pending. Alon Efrat earned his Bachelor in Applied Mathematics from the Technion (Israel’s Institute of Technology) in 1991, his Master in Computer Science from the Technion in 1993, and his Ph.D in Computer Science from Tel-Aviv University in 1998. During 1998–2000 he was a Post Doctorate Research Associate at the Computer Science Department of Stanford University, and at IBM Almaden Research Center. Since 2000, he is an assistant professor at the Computer Science Department of the University of Arizona. His main research areas are Computational Geometry, and its applications to sensor networks and medical imaging.     

Efficient bad equalizer in two-ray multipath fading channels

An efficient bidirectional arbitrated decision feedback (BAD) equalizer is presented in single-carrier block transmission system in the Two-Ray multipath fading channels, where the output from the bidirectional equalizers are combined together directly using maximal ratio combining (MRC) rule to improve the signal-to-noise ratio (SNR) before demodulation. The computational complexity of the BAD equalizer presented is linear with the channel length, which is the same as conventional decision feedback equalizer (DFE) and is significantly lower than that of conventional BAD equalizer as well as the maximum likelihood (ML) algorithm. While the performance of the new scheme depends on the specific channel characteristics, it is shown by simulation results that the performance of the new BAD can surpass the one of DFE dramatically in the minimum or non-minimum phase Two-Ray multipath fading channels.     

基于Nd∶YAG激光器声音辨识的实验探究

为了实现以激光作为载体的声音辨识,提出了一种基于Nd∶YAG激光器的声音辨识测量方法。首先,通过实验验证了采用Nd∶YAG激光器的测量系统能够测量低反射率物体纸片的运动位移;其次,声音信号在通过空气向外传播时,会引起纸片的振动位移,经过滤波、放大处理,实现声音的还原。结果表明,基于Nd∶YAG激光器的激光回馈干涉测量系统通过测量纸片的振动位移,从而实现对测试人员的声音辨识。     

带驻波故障监测功能的AISG塔顶放大器控制单元设计

根据AISG2.0协议对带驻波检测功能的塔顶放大器( TMA)中状态监控、故障告警和数据通信的技术要求,提出了TMA嵌入式控制单元的设计及实现方法。硬件部分首先概述了总体设计方案,然后阐明了OOK( On-Off Keying)模块、可配置式电流告警电路、浪涌电流抑制电路和驻波检测功能的设计思路;软件部分详细介绍了AISG协议栈的设计方法,并给出了低噪声放大器( LNA )及驻波故障的检测流程。测试证明,本系统的电气性能、监控功能以及协议完整性均满足AISG2.0协议的要求,并完成了与主流基站系统厂家的互操作测试。     

新型高隔离度OADM的光谱及传输实验研究

光插分复用器（ｏｐｔｉｃａｌ ａｄｄ／ｄｒｏｐ ｍｕｌｔｉｐｌｅｘｅｒ,ＯＡＤＭ）是波分复用系统的关键器件之一,光纤光栅器件是ＯＡＤＭ一种较为理想的选择。本文提出了一种新型的ＯＡＤＭ,它由两个环形器,一个光隔离器和两个光纤光栅器件构成。针对基本结构的ＯＡＤＭ和该新型ＯＡＤＭ,本文分别进行了一系列相应的性能实验。通过比较两种结构光插分复用器的Ａｄｄ信号对Ｄｒｏｐ信号的相干干扰、以及Ｄｒｏｐ信号对Ａｄ     

自动目标识别(ATR)可靠性研究

对同类目标畸变不变的正确识别率与不同类目标分类误识别率是衡量一个自动目标识别 (ATR)系统的两个最重要性能指标。但在实际应用中 ,ATR系统所获取的外场的目标与背景总是处于随时间不断变化的条件下 ,与系统所存储的参考目标通常都不会一致 ,从而导致相关识别SNR劣化。特别对于多目标识别与不同类目标的区分 ,常规的相关门限判决方法会造成很大的误识别 ,大大影响了ATR系统的识别可靠性。本文采用人工神经网络 (ANN)与模糊逻辑技术 ,对相关信号与噪声进行实时数字后处理 ,通过对信号与噪声强度分布等高线而不仅仅是强度的识别 ,大大提高了ATR系统的识别可靠性 ,改善了识别效率。     

外逸电子传感器8031单片机控制系统设计

基于传感器智能化的设计思想,提出以８０３１单片机为核心传感器计数控制系统。该系统主要由定时／计数同步电路、ＬＣＭ接口电路和光电隔离电路等组成。实验结果表明,系统设计合理,体积小、实时处理速度快和控制精度高,从而为外逸电子传感器的智能化奠定了良好的基础。