水稻花药培养技术在新品种选育中的利用

该文综述了花培技术在培育新品种中的利用途径，认为其利用途径一方面是快速获得纯系，培育新品种，缩短育种年限，另一方面可以对花药（花粉）诱变或与其它先进技术相结合，快速获得纯系目标材料，达到创新种质的目的。     

水稻泛素连接酶功能研究进展

泛素广泛调控真核细胞的生命活动,泛素连接酶（E3）在泛素-蛋白酶体降解系统中特异性地识别目标底物。本文综述了水稻E3在激素信号传导、生长发育、生物胁迫和非生物胁迫等方面所起的作用。将来的研究重点是剖析水稻E3及目标底物互作方式,为水稻品质改良和抗逆育种提供借鉴与指导。     

调零天线中的空域极化域联合抗干扰算法

在期望信号功率较小情况下,强同频干扰容易造成系统灵敏度下降,比如卫星导航和卫星通信。采用一个4阵元正交极化阵列,可以通过空域和极化域联合方式对干扰进行抑制。阵列参考阵元位于圆心,其余3个阵元均匀分布在圆周上。自适应滤波采用功率倒置准则下的LMS算法,该方法调整每个正交极化阵元权系数,使得阵列在干扰极化下等效的极化匹配因子接近为0,实现干扰抑制。算法无需信号空间信息,实现简单,同时使阵列自由度达到6,从而增加抗干扰个数。计算机仿真证明了4个阵元阵列可以有效抑制最多6个干扰,而且,通过极化域处理,即使干扰信号与期望信号入射角度相同,只要极化不同,也可以抑制干扰而保持对期望信号增益。     

非线性方程最优拟合的缩张算法

本文提出一种可实现非线性方程最优拟合的新方法－缩张算法（Ｃ－Ｅ算法）。该算法由若干循环组成,每一循环都包含收缩和扩张两个步骤。因而,可以在多维起始空间的内、外漫游搜索目标函数,并利用搜索过程所反馈的信息调整搜索中心和步长;通过较少次Ｃ－Ｅ循环的搜索,便能逼近给定非线性方程的最适参数值。该算法不需要给出方程的导数或偏导数,减少了计算的复杂性,也可能推广应用于解决其它目标函数的最优化问题。     

机动车尾气排放测算行驶周期的自动建立方法

为了建立用于机动车尾气排放测算的行驶周期,利用便携车载尾气采集装置(PEMS)系统和GPS装置进行了大量的机动车尾气排放和驾驶活动数据采集,并对数据进行了预处理,提出了短行程的评价标准,给出了最优短行程自动搜索的2种启发式算法(遗传算法(GA)和离散同步扰动随机逼近(DSPSA)),对建立的行驶周期进行了预测尾气排放总量的有效性验证。结果表明：2种启发式算法均能有效地解决行驶周期自动建立问题,GA算法优化得到的行驶周期更有代表性,该行驶周期能以相对较小的误差预测尾气排放总量。建议将GA算法作为开发其他城市的行驶周期的算法工具。     

电源分配网络阻抗分析及去耦电容优化

高速印制板电源分配网络（power delivery networks,PDN）受电电源端口具有瞬时电流大、目标阻抗小的特点。针对任意形状电源板的阻抗问题,提出一种基于解析式与有限差分法的互补模型,并在此基础上结合粒子群算法实现多个受电电源端口的阻抗优化。通过Matlab仿真,发现互补模型的结果与全波有限元法的基本吻合,计算时间则大幅缩短。测量结果表明,优化后实验板的多个受电电源端口阻抗均满足各自的目标值要求。     

近红外透射光谱技术测定黍稷蛋白含量的研究

为了探索快速测定完整黍稷籽粒蛋白含量的方法,采用近红外光谱分析技术建立数学模型并进行预测,比较原始透射光谱经导数处理结合不同回归算法对模型的影响。结果表明,分别经一阶和二阶导数处理后利用偏最小二乘法和改进的偏最小二乘法,4种方法的分析效果相近,最优的是一阶导数结合改进的偏最小二乘回归法,黍稷蛋白定标模型的定标相关系数（RSQ）为0.8806,定标标准误差（SEC）为0.3424,交互验证相关系数（1-VR）为0.8570,交互验证标准误差（SECV）为0.3751,外部预测标准偏差（SEP）为0.454。最终以完整黍稷籽粒为样品所建立的蛋白NITS模型,可以用于黍稷蛋白含量的快速检测。     

中科院遗传发育所在植物激素调控花分生组织维持及分化的分子机制研究中获进展

<正>高等植物中,植物体所有胚后发育的组织和器官都来源于各级分生组织。花分生组织产生及维持是花器官生成及发育的前提,而FM活性的程序性终止导致的细胞分化是后续的生殖生长及世代交替的保证,在实际应用中能够保证农作物的产量。分生组织的维持及分化由特定的蛋白组分如转录因子,多肽信号和受体及植物激素如生长素和细胞分裂素共同调控,但植物激素间以及激素与蛋白间互作调控FM维持及分化的机制未有系统研究。中国科学院遗传与发育生物学研究所农业资源研究中心刘西岗研究组     

基于HJ-1数据的冬小麦种植面积、长势与收割进度遥感监测

及时、准确地获取冬小麦种植面积、长势、收割进度等信息对冬小麦产量预报和农田精细管理具有重要意义。本研究采用HJ-1A/B CCD1/CCD2影像,结合S-G滤波算法、波段最大化的光谱角目标探测器、阈值分割等方法进行新乡市冬小麦种植面积、小麦长势和收割进度等遥感监测。结果表明：（1）利用HJ卫星NDVI时间序列数据结合波段最大化的光谱角度目标探测器方法,可以进行冬小麦种植面积提取,各县市冬小麦种植面积提取相对误差在10%以内;（2）单景影像NDVI值阈值分割可以反映冬小麦长势在时空差异;（3）冬小麦达到抽穗期的时间不一致,NDVI值在4月15日和21日附近达到最大值;（4）利用成熟期和收割期不同时间的NDVI影像,可监测各县市冬小麦收割进度的时空差异。各县市冬小麦在6月4日前开始收割与6月15日左右完成收割工作。HJ卫星时间序列遥感数据可以进行冬小麦种植面积、长势、收割进度等遥感监测。     

SEEIP核心企业局域智慧能源网络框架及优化配置方法

智慧节能工业园区（SEEIP）的核心企业能源配置对产业集群的循环经济节能降耗具有重要作用。针对SEEIP建设与既有工业园区核心企业能源系统的智慧化改造,提出一种基于信息和通信技术（ICT）的局域智慧能源网络框架,并给出了能源生产模块、能源转换模块与能源蓄存模块中各种能源介质及品位的能量计算数学模型。以经济成本与环境影响为目标的函数,给出了SEEIP企业能源网络系统配置的优化模型,并采用改进的差异演化算法（DE）结合数据库查询技术求解该混合整数非线性规划（MINLP）优化问题,给出企业能源系统最佳配置方案,以满足用户冷、热、电需求。     

State of charge estimation of lithium iron phosphate batteriesbased on adaptive Kalman filters

The Kalman filter algorithm can be used to estimate the state of charge (SOC) of power batteries, however, it easily causes divergence due to uncertain of system noise and its estimation performance is affected by model. An adaptive Kalman filter algorithm is adopted to dynamically estimate SOC of lithium iron phosphate batteries for application in electric vehicles. At first, an equivalent circuit model, appropriate for SOC estimation is built after studying battery models. Then some charging and discharging experiments are carried out for parameter identification and the results are verified. At last, the adaptive Kalman filter algorithm is used on this model for on-line SOC estimation under unknown interfering noise. Simulation results show that adaptive Kalman filter method can correct SOC estimation error caused by tiny model error online, and the estimate accuracy is higher than Kalman filter method. Adaptive Kalman filter algorithm can also correct the initial error. Full-cycle test in electric vehicles proves that the algorithm is appropriate for SOC estimation of lithium iron phosphate battery.     

A blind channel estimation algorithm for UltraWide band channel based on compressive sensing

The sampling speed for the ultra wide band (UWB) channel is too high to realize with the existing sampling technology. To solve the problem, a novel blind channel estimation algorithm was presented based on the theory of compressive sensing. Firstly, some measurements are obtained which are linear combinations of the received signals multiplied by a random incoherent measurement matrix. Then, the mathematical model is established by exploiting the first statistics of the measurements. Finally, the orthogonal matching pursuit (OMP) algorithm is utilized to get the estimating channel parameters. With the proposed algorithm, the number of the measurements need for channel estimation is much smaller than that of the samples needed for the existing algorithms, which reduces the ADC resources greatly. The simulation result shows that the estimation performance of the algorithm is good, while the bit error rate (BER) is only 2~3dB higher than that of the exact channel.     

OBS网络的拥塞控制汇聚算法分析

传统OBS网络汇聚算法没有综合考虑边缘节点汇聚算法和核心节点的数据调度算法二者之间的相互联系,其通信性能受限。在分析OBS网络边缘节点汇聚算法对核心节点数据调度的影响后,提出了一种新的边缘节点汇聚算法——基于OBS网络的拥塞控制汇聚算法（CCAA）。该算法通过分析边缘节点汇聚参数对数据调度的影响,调整汇聚算法实现对核心节点调度成功率的影响,最终实现了提高核心节点数据调度的成功概率。     

Novel channel estimation algorithm for OFDM/TDM over fast fading channels

For the shortage of tracking ability against fast fading channel of the existing pilot structures and channel estimation algorithms in OFDM combined with time division multiplexing (OFDM/TDM) system, an improved channel estimation algorithm is proposed. The channel transfer functions are obtained by estimating the channel properties with two adjacent time domain multiplexing (TDM) pilot sequences, while the channel state information of the OFDM/TDM symbols is obtained with interpolation Combined with frequency domain equalization based on minimum mean square error (MMSE-FDE), the proposed algorithm can significantly compensate the path loss over fast fading channels. Simulation results show that, compared with the existing channel estimation algorithms, the proposed algorithm can achieve better performance, which is not only capable of dealing with slow fading channels, but also has a better tracking ability against fast fading channels with the same data transmission efficiency.     

A charge balance control algorithm of dual-transistors forward converter

An algorithm is proposed for dual-transistors forward converter (DTFC) by using the principle of charge balance control during a transient process to improve their dynamic performance. Combined with response curve,the theoretical analysis and some key equations are presented to improve the dynamic performance of the DTFC by minimizing the over/under shoot and the recovery time. In order to avoid the magnetic saturation of the transformer,an approximate method is introduced in the calculation of the optimal switching time,which can also be applied to other isolated converters when the maximum duty cycle is limited. Finally,the simulation results and the experimental results of the prototype show that,compared with the traditional voltage mode control,the proposed algorithm can significantly improve the dynamic performance of DTFCs.     

A Kind of Robust Identification Algorithm Research

A new robust identification algorithm which is based on the estimation of parameter model,i.e.,Optimal Volume Ellipsoid parameter set identification algorithm is presented in this paper.It identifies not only a parameter point(the center of the ellipsoid) but also the error bounds of each parameter.It employs noise bounds in identification algorithm and dynamically modifies coefficients of identification convergent speed and direction in order to attain satisfactory perfomance.Digital simulation results show that is possesses high accuracy,dramatic convergent speed,excellent performance against noise and strong robustness as well as uniform convergent,which is obviously superior to traditional identification schemes.     

Channel estimation for MB OFDM UWB system based on tap detecting

A novel channel estimation algorithm is proposed for MB OFDM Ultra Wide Band systems based on tap detecting by exploiting the sparse property of channel impulse response. The channel parameters are estimated using the DFT algorithm based on cyclic convolution property of the receive signals. The nonzero taps are detected by exploiting the matching pursuit(MP) algorithm. The new estimated channel parameters are obtained by forcing the zero taps to zeros. Simulation results demonstrate that it has better MSE (mean square error) performance for the four channels proposed by IEEE. Especially for CM1 and CM2 channels, the performance of the algorithm has been greatly improved.     

Parameter Modifiability Based Transformer Substation State Estimation

The accuracy of transformer substation state estimation is widely low,and one reason of that is inaccurate(parameter) of model.Recently,most of papers about state estimation(SE) focus on improving algorithm.Based on classic SE and parameter estimation(PE),this paper takes advantage of the methods that putting parameters into state vector and putting parameters both into state vector and measurement vector in discussing the influence of parameter on transformer substation SE via simulation.The result of simulation shows: First,the error of parameters will be too high if only putting them into state vector,although the result of SE will be much better.Second,putting parameters both into state vector and measurement vector and giving them appropriate coefficient will lead a better result that can be used by engineering.     

MPPT control of photovoltaic grid connected system

The high cost of grid connected photovoltaic (PV) system is an important reason that hinders its market application. The control cost can be partly cut down by using sensorless Maximum Power Point Tracking (MPPT). However, the sensorless MPPT control proposed by previous literatures has drawbacks of poor estimation accuracy, bad real time performance, and poor dynamic responses, which has great impact on the MPPT and the output performance of the whole system. Aiming at these problems, an Adaptive Sliding Mode Observer (ASMO) for estimation of photovoltaic array voltage is proposed. The external disturbance and modeling errors are suppressed while the real time performance and the estimation accuracy are improved greatly by the proposed method. The favorable performance of the output performance and MPPT performance of the PV system based on the ASMO are validated by simulation and experimental results.     

A method for considering parameter errors in power system harmonic state estimation

Total least squares (TLS) is proposed to complete harmonic state estimation when parameter and measurement errors are both taken into consideration. The buses are partitioned into subsets of non source buses and suspicious buses, thereby reducing the number of unknown state variables. The validity and practicability of this approach is validated using the IEEE 14bus harmonic testing system. The estimation precision is analyzed by random sampling 10 000 times in Matlab when measurement errors and parameter errors followed a Gaussian distribution. The results show that an accurate estimate can be obtained using TLS if parameter and measurement errors are considered.