百麦外用中药制剂对小鼠乳腺增生的实验研究

目的:观察外用中药制剂对小鼠乳腺增生的预防作用并探讨其机理。方法:采用苯甲酸雌二醇腹腔注射造模,分对照组、模型组与预防组。模型组与预防组腹腔注射苯甲酸雌二醇,隔天1次,并且预防组小鼠乳房涂抹百麦外用中药制剂,每天1次,共30天;对照组小鼠腹腔注射生理盐水,隔天1次,共30 d。测定各组小鼠体重变化,乳晕及乳头直径变化,血清雌激素(E2)、孕激素(P)指标,并取小鼠第二对乳房组织病理切片检查。结果:预防组与模型组小鼠体重、乳晕及乳头直径比较均有显著性差异(P0.05);预防组与模型组比较,E2水平明显降低(P0.05),P水平明显升高(P0.05);预防组小鼠增生的乳腺小叶、腺泡数、腺泡腔直径、导管直径以及胞浆面积较模型组降低。结论:百麦外用中药制剂具有预防乳腺增生的作用,其机理可能是通过抑制血清雌二醇水平而实现。     

摩擦非线性环节的特性、建模与控制补偿综述

首先介绍了机械伺服系统中摩擦非线性环节的动态、静态特性的研究成果和目前常用的几种摩擦模型 ,讨论了摩擦非线性环节对伺服系统的动态性能和静态性能的影响 ,以及摩擦非线性环节导致的极限环振荡、低速爬行等现象。然后对有关摩擦补偿方法方面的研究成果进行了总结 ,介绍了传统的摩擦补偿方法和基于智能控制理论的摩擦补偿方法方面的研究成果。最后 ,展望了该领域今后的发展方向。     

多参考预测链的时域可扩展性和抗错性

网络的带宽抖动和数据传输错误是影响视频传输的重要原因。该文提出了一种新的多参考帧图像预测的视频编码算法,即多参考预测链,使视频具有时域可扩展性和抗错性解决网络的这两个潜在问题。该算法中P帧之间的参考预测关系构成多条链状结构,使视频具有时域可扩展性。链间的不相关性使每个链可独立解码,从而增强了码流抗错性。该算法采用R-D框架动态的管理预测关系链,从而适合网络带宽的变化而获得最佳的终端视觉效果。仿真实验表明,采用多参考预测链编码的码流时域可扩展性的应用非常可行,且表现出较高的抗错性。     

Bit-Depth Scalable Coding Using a Perfect Picture and Adaptive Neighboring Filter

Bit-depth scalability is a new research field in the on-going scalable extension of the H.264/AVC (SVC) video coding standard. The key point is to accurately predict the enhancement layer, whose bit depth is 10 or more, from the 8 bit base layer. An improved inter-layer prediction scheme for bit-depth scalability was developed that ensures compatibility with the standard and improves the encoding efficiency. The scheme uses a “perfect” 8 bit picture with an adaptive neighbor filter whose coefficients are optimized by minimizing the block distortion between the 8 bit reconstructed picture and the “perfect” picture to achieve a more precise 10 bit prediction based on the filtered picture. Double arithmetic precision is used to further improve the encoding efficiency. Experimental results show that the scheme outperforms the recent joint video team (JVT) proposal in the joint scalable video model (JSVM).     

基于神经网络的直流电动机实时跟踪控制

研究了三层对角回归神经网络(DRNN)用于直流电动机实时控制的方法.首先采用动态反传算法训练神经网络以辨识直流电动机的逆模型,然后将这一训练后的网络作为前馈控制器与常规反馈控制器一起输出控制电压,以控制系统跟踪位置或速度指令.该算法简单、计算量小,适于实时控制.仿真结果表明了该方法的有效性.     

Newly identified loci that influence lipid concentrations and risk of coronary artery disease

To identify genetic variants influencing plasma lipid concentrations, we first used genotype imputation and meta-analysis to combine three genome-wide scans totaling 8,816 individuals and comprising 6,068 individuals specific to our study (1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables) and 2,758 individuals from the Diabetes Genetics Initiative, reported in a companion study in this issue. We subsequently examined promising signals in 11,569 additional individuals. Overall, we identify strongly associated variants in eleven loci previously implicated in lipid metabolism (ABCA1, the APOA5-APOA4-APOC3-APOA1 and APOE-APOC clusters, APOB, CETP, GCKR, LDLR, LPL, LIPC, LIPG and PCSK9) and also in several newly identified loci (near MVK-MMAB and GALNT2, with variants primarily associated with high-density lipoprotein (HDL) cholesterol; near SORT1, with variants primarily associated with low-density lipoprotein (LDL) cholesterol; near TRIB1, MLXIPL and ANGPTL3, with variants primarily associated with triglycerides; and a locus encompassing several genes near NCAN, with variants strongly associated with both triglycerides and LDL cholesterol). Notably, the 11 independent variants associated with increased LDL cholesterol concentrations in our study also showed increased frequency in a sample of coronary artery disease cases versus controls.     

ADAMTS5 is the major aggrecanase in mouse cartilage in vivo and in vitro

Aggrecan is the major proteoglycan in cartilage, endowing this tissue with the unique capacity to bear load and resist compression. In arthritic cartilage, aggrecan is degraded by one or more 'aggrecanases' from the ADAMTS (a disintegrin and metalloproteinase with thrombospondin motifs) family of proteinases. ADAMTS1, 8 and 9 have weak aggrecan-degrading activity. However, they are not thought to be the primary aggrecanases because ADAMTS1 null mice are not protected from experimental arthritis, and cleavage by ADAMTS8 and 9 is highly inefficient. Although ADAMTS4 and 5 are expressed in joint tissues, and are known to be efficient aggrecanases in vitro, the exact contribution of these two enzymes to cartilage pathology is unknown. Here we show that ADAMTS5 is the major aggrecanase in mouse cartilage, both in vitro and in a mouse model of inflammatory arthritis. Our data suggest that ADAMTS5 may be a suitable target for the development of new drugs designed to inhibit cartilage destruction in arthritis, although further work will be required to determine whether ADAMTS5 is also the major aggrecanase in human arthritis.     

飞行转台Backstepping与神经网络并行控制

阐述了飞行仿真转台的Backstepping设计方法及步骤。在Backstepping鲁棒控制的基础上,提出了一种Backstepping鲁棒控制和神经网络并行控制的方案,以Backstepping鲁棒控制为主控制器,神经网络进行动态误差补偿。Backstepping鲁棒控制克服了对象的不确定性,保障系统的鲁棒性;神经网络可以进一步提高系统的跟踪精度。仿真表明,这种方法实现了Backstepping鲁棒控制和神经网络控制的完美结合,很适合高精度飞行仿真转台系统的鲁棒控制。     

基于共享内存机制微机实时网的数据传输实时性研究

文章首先介绍了广播式内存及反射内存的特点、功用等,并在试验的基础上研究了二者对不同操作系统的支持程度、所构成网络的实时性、网络运行的稳定性等。得出反射内存网卡在综合性能上优于广播式内存网卡,更适合于半实物仿真系统的集成。最后通过某型号半实物仿真系统的集成及试验,验证了基于反射内存机制的半实物仿真系统的仿真实时性及仿真精度。     

一类高精度伺服系统基于模糊神经网络的复合控制

针对高精度伺服系统中存在的各种非线性及不确定性 ,提出了基于模糊神经网络的复合控制方法。控制器由前馈控制器和闭环反馈控制器组成。前馈控制器由零相差跟踪控制器 (ZPETC)及FIR滤波器构成 ,闭环反馈控制器采用模糊神经网络控制 ,包含一个辨识网络FNNI和控制网络FNNC。该控制方法结合了神经网络和模糊推理的优点 ,可以克服各种非线性和不确定性 ,明显提高跟踪性能 ,具有很好的鲁棒性。提出的模糊神经网络结构简单 ,推理算法易于实现 ,并且可以更合理地选择初始权值 ,加快了网络的收敛速度 ,在一定程度上解决了神经网络的实时性问题