Fingerprints of global warming on wild animals and plants

Over the past 100 years, the global average temperature has increased by approximately 0.6 degrees C and is projected to continue to rise at a rapid rate. Although species have responded to climatic changes throughout their evolutionary history, a primary concern for wild species and their ecosystems is this rapid rate of change. We gathered information on species and global warming from 143 studies for our meta-analyses. These analyses reveal a consistent temperature-related shift, or 'fingerprint', in species ranging from molluscs to mammals and from grasses to trees. Indeed, more than 80% of the species that show changes are shifting in the direction expected on the basis of known physiological constraints of species. Consequently, the balance of evidence from these studies strongly suggests that a significant impact of global warming is already discernible in animal and plant populations. The synergism of rapid temperature rise and other stresses, in particular habitat destruction, could easily disrupt the connectedness among species and lead to a reformulation of species communities, reflecting differential changes in species, and to numerous extirpations and possibly extinctions.     

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。     

Tilman's predicted productivity-diversity relationship shown by desert rodents

Tilman has developed a model to predict the number of plant species that can coexist competitively on a limited resource base. Species diversity first increases over low resource supplies, then declines as the environment becomes richer. Although Tilman 's model was developed to describe interspecific interactions between plant species, it may also apply to animal species. Tilman questions whether animals specialize on particular proportions of nutrients. However, we believe animals probably specialize on relatively subtle microhabitat differences, especially in a multispecies competitive regime. Thus, microhabitats may act like nutrients. We hypothesize that animal species, too, show a peaked curve of diversity over productivity. The present data provide a confirmation of the hypothesis using rodent species. We have investigated the number of rodent species along a geographical gradient of increasing rainfall. The gradient extends from extremely poor desert habitats to those with annual rainfall over 300 mm. Because of the aridity , precipitation reflects productivity. The diversity pattern in desert rodents agrees with that predicted by Tilman for plants. It even possesses similar asymmetry, rising steeply then falling slowly. The pattern is duplicated in rocky and sandy habitats, each of which has a distinct and almost nonoverlapping assemblage of species. As mean precipitation is closely correlated with the variability of precipitation, the diversity pattern might also be caused by a decline in the frequency of disturbances, models for which have been proposed by several investigators.     

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.     

Crystal structure of a membrane-bound metalloenzyme that catalyses the biological oxidation of methane

Particulate methane monooxygenase (pMMO) is an integral membrane metalloenzyme that catalyses the conversion of methane to methanol. Knowledge of how pMMO performs this extremely challenging chemistry may have an impact on the use of methane as an alternative energy source by facilitating the development of new synthetic catalysts. We have determined the structure of pMMO from the methanotroph Methylococcus capsulatus (Bath) to a resolution of 2.8 A. The enzyme is a trimer with an alpha3beta3gamma3 polypeptide arrangement. Two metal centres, modelled as mononuclear copper and dinuclear copper, are located in soluble regions of each pmoB subunit, which resembles cytochrome c oxidase subunit II. A third metal centre, occupied by zinc in the crystal, is located within the membrane. The structure provides new insight into the molecular details of biological methane oxidation.     

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。