Single-Molecule Photoactivation FRET: A General and Easy-To-Implement Approach To Break the Concentration Barrier

Single-molecule fluorescence resonance energy transfer (sm-FRET) has become a widely used tool to reveal dynamic processes and molecule mechanisms hidden under ensemble measurements. However, the upper limit of fluorescent species used in sm-FRET is still orders of magnitude lower than the association affinity of many biological processes under physiological conditions. Herein, we introduce single-molecule photoactivation FRET (sm-PAFRET), a general approach to break the concentration barrier by using photoactivatable fluorophores as donors. We demonstrate sm-PAFRET by capturing transient FRET states and revealing new reaction pathways during translation using μm fluorophore labeled species, which is 2–3 orders of magnitude higher than commonly used in sm-FRET measurements. sm-PAFRET serves as an easy-to-implement tool to lift the concentration barrier and discover new molecular dynamic processes and mechanisms under physiological concentrations.     

A self‐adaptive intelligence gray prediction model with the optimal fractional order accumulating operator and its application

The self‐adaptive intelligence gray predictive model (SAIGM) has an alterable‐flexible model structure, and it can build a dynamic structure to fit different external environments by adjusting the parameter values of SAIGM. However, the order number of the raw SAIGM model is not optimal, which is an integer. For this, a new SAIGM model with the fractional order accumulating operator (SAIGM_FO) was proposed in this paper. Specifically, the final restored expression of SAIGM_FO was deduced in detail, and the parameter estimation method of SAIGM_FO was studied. After that, the Particle Swarm Optimization algorithm was used to optimize the order number of SAIGM_FO, and some steps were provided. Finally, the SAIGM_FO model was applied to simulate China's electricity consumption from 2001 to 2008 and forecast it during 2009 to 2015, and the mean relative simulation and prediction percentage errors of the new model were only 0.860% and 2.661%, in comparison with the ones obtained from the raw SAIGM model, the GM(1, 1) model with the optimal fractional order accumulating operator and the GM(1, 1) model, which were (1.201%, 5.321%), (1.356%, 3.324%), and (2.013%, 23.944%), respectively. The findings showed both the simulation and the prediction performance of the proposed SAIGM_FO model were the best among the 4 models.     

河北省装备制造产业发展的灰色关联分析

基于灰色系统中的关联分析方法,从动态的视角出发,对河北省装备制造产业生产总值与装备制造产业系统内部结构关系进行研究分析,得出河北省装备制造产业的发展具有以下特点:金属制品业等资源加工型产业依旧在装备制造产业中占据主导地位,通用装备业和仪器仪表业等技术密集型产业的贡献率相对不足.因此,应从河北省的实际情况出发,不断优化装备制造的内部产业结构。     

微电子机械系统中转速测量的光学方法

利用显微测量技术和CCD图像传感器的线性积分成像特性,将数字图像处理技术与时间积分成像技术用于微电子机械系统(MEMS)中的转速测量。只需分别摄取被测物体上的标志点在静止状态下的时间积分图像和运动状态下的时间积分图像,即可测得物体在该段曝光时间内的转速。该方法对实验设备及实验条件要求较宽松。实验表明该方法对微系统中近似匀速转动时转速的测量是完全可行的,且具有较高的精度。     

Classification‐Based Approach for Hybridizing Statistical and Rule‐Based Machine Translation

In this paper, we propose a classification‐based approach for hybridizing statistical machine translation and rule‐based machine translation. Both the training dataset used in the learning of our proposed classifier and our feature extraction method affect the hybridization quality. To create one such training dataset, a previous approach used auto‐evaluation metrics to determine from a set of component machine translation (MT) systems which gave the more accurate translation (by a comparative method). Once this had been determined, the most accurate translation was then labelled in such a way so as to indicate the MT system from which it came. In this previous approach, when the metric evaluation scores were low, there existed a high level of uncertainty as to which of the component MT systems was actually producing the better translation. To relax such uncertainty or error in classification, we propose an alternative approach to such labeling; that is, a cut‐off method. In our experiments, using the aforementioned cut‐off method in our proposed classifier, we managed to achieve a translation accuracy of 81.5% — a 5.0% improvement over existing methods.     

一种QPSK-DS信号参数估计方法

基于QPSK-DS信号的结构特征,从直扩通信的基本特征和QPSK-DS信号做平方及延迟相乘处理后所具有的典型特征入手,探寻可实现对QPSK-DS信号参数估计的方法。提出了一种基于时域信号处理与频域特征提取的QPSK-DS通信参数估计方法,该方法通过对接收信号做平方和延迟相乘处理然后搜索特征谱线的方法完成对QPSK-DS扩频参数符号周期和码片时宽的估计。仿真试验表明该方法简单有效,可操作性强。     

基于数字微镜的无掩模数字光刻系统的研制

研究了一种基于数字微镜的无掩模光刻系统.利用数字微镜输出的高精度数字掩模,结合高质量的高倍精缩投影光学系统,理论上完全可实现亚微米级衍射微光学元件的制作.该文从照明系统、数字微镜芯片、精缩物镜设计等方面进行了系统总体设计.利用该系统成功制作了5×5达曼光栅、8台阶闪耀光栅和8台阶菲涅耳透镜,进一步论证了该系统的可行性.     

基于粒子群算法和卡尔曼滤波的运动目标跟踪算法

针对目前一些常用的运动目标跟踪算法存在跟踪精度不高、实时性低、对遮挡问题处理不佳等问题,提出一种粒子群算法与卡尔曼滤波相结合的新的运动目标跟踪方法。利用卡尔曼滤波预测目标中心在下一帧图像中的位置,从而极大减少了搜索范围,并以该位置为中心建立目标搜索区域。然后以目标的灰度统计特征对目标模板和候选区域进行匹配,确保跟踪准确性。为了有效减少搜索匹配次数、提高实时性,利用粒子群算法在搜索区域找到和目标模板最相似的区域,从而找到最优中心位置,并以该位置作为卡尔曼滤波的观测值,进行下一帧跟踪。仿真实验结果表明新算法显著提高了跟踪的实时性、精确性,并对部分遮挡能较好地处理。     

利用红外光纤传像束测量桥丝感应电流

针对传统的桥丝式电点火头中感应电流测量方法在电磁环境测量时会引入电场或者磁场的干扰,本文基于红外光纤传像束耦合CCD红外探测器,提出一种非接触式远程测量的新方法.通过CCD红外探测器得到桥丝式电点火头辐射的热场灰度图像,根据灰度值与温度、温度与电流的关系标定对应的桥丝微弱的感应电流值.实验结果表明,这种方法可以精确测量...     

具有片上多段基准源的14位宽温度范围高SNDR全差分逐次逼近型模数转换器

介绍了一种带有片上多段带隙基准源的14位低功耗自定时全差分逐次逼近型模数转换器。采用一个在-40到120℃温度范围内具有1.3ppm/℃温度系数的片上多段带隙基准电压源来为逐次逼近型模数转换器提供高精度基准电压源。设计中用格雷码代替二进制编码来减少衬底噪声从而增加整个系统的线性度。采用自定时位循环来增加时间利用率。该14位模数转换器利用TSMC 0.13μm CMOS工艺流片。该逐次逼近型模数转换器在室温2M/s 转换速率条件下能够获得81.2dB SNDR (有效位数13.2) 和85.2dB SFDR,并且在2M/s转换速率下在-40到120℃温度范围内能够保持12位以上有效位数。