云南国家级自然保护区存在问题研究

云南是我国生物多样性丰富的地区, 在生物多样性保护中扮演着重要角色而云南国家 级自然保护区在云南省自然保护区中又拥有较大比重, 分布在云南生物多样性关键地区, 对多 种生态系统和大量动植物的保护起到了至关重要的作用。经过多年的努力, 一些重要珍稀濒危 动物种群数量有所增加。但这些保护区仍然存在一系列问题, 主要包括三方面, 一是客观因 素, 大多数保护区地处边远落后山区二是来自于周边村寨巨大的人口压力三是来自于当地 政府和保护区, 主要是缺乏长远规划、大力投资等问题。保护区资源受到如此多种因素的威 胁, 保护效果得不到充分发挥。只有采取强有力的保护措施, 如加强社区共管、拓宽投资渠 道、进行科学规划管理等, 才能使保护区走上可持续发展的轨道。

进化中的选择原理

该文简要介绍了在过去几十年中非平衡统计物理研究有序现象的新概念及其在探讨进化问题中的应用和意义。

滇金丝猴(Rhinopithecus bieti)现状及其保护对策研究

滇金丝猴生活在海拔3800-4300m的原始冷杉林中, 但有时也会在4300-4700m的低矮灌丛、草甸和流石滩上活动达数小时之久, 甚至能跨越近千米的无林高海拔地带。松萝是它们的主要食物, 取食松萝的时间占总取食时间的91%。猴群活动范围可达近百平方公里。笔者在历时8年的野外考察中, 已查明这一物种的全部现存自然种群只有13个, 分布在云南的德钦、兰坪、潍西、丽江和西藏的芒康这五县境内, 其现存种群数量为1000-1500只; 所有现存自然种群几乎均处在相互隔离的状态, 群间已不可能进行基因交流, 充分表明它们已到达灭绝边缘。

Optimal control with stochastic PDE constraints and uncertain controls

The optimal control of problems that are constrained by partial differential equations with uncertainties and with uncertain controls is addressed. The Lagrangian that defines the problem is postulated in terms of stochastic functions, with the control function possibly decomposed into an unknown deterministic component and a known zero-mean stochastic component. The extra freedom provided by the stochastic dimension in defining cost functionals is explored, demonstrating the scope for controlling statistical aspects of the system response. One-shot stochastic finite element methods are used to find approximate solutions to control problems. It is shown that applying the stochastic collocation finite element method to the formulated problem leads to a coupling between stochastic collocation points when a deterministic optimal control is considered or when moments are included in the cost functional, thereby forgoing the primary advantage of the collocation method over the stochastic Galerkin method for the considered problem. The application of the presented methods is demonstrated through a number of numerical examples. The presented framework is sufficiently general to also consider a class of inverse problems, and numerical examples of this type are also presented. © 2011 Elsevier B.V.

A new distance for scale-invariant 3D shape recognition and registration

This paper presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transforms for the first time. We introduce a new distance between poses in this spacethe SRT distance. It is left-invariant, unlike Euclidean distance, and has a unique, closed-form mean, in contrast to Riemannian distance, so is fast to compute. We demonstrate improved performance over the state of the art in both recognition and registration on a real and challenging dataset, by comparing our distance with others in a mean shift framework, as well as with the commonly used Hough voting approach. © 2011 IEEE.