Response of seasonal vegetation development to climatic variations in eastern central Asia

Meteorological records show that central Asia has experienced one of the strongest warming signals in the world over the last 30 years. The objective of this study was to examine the seasonal vegetation response to the recent climatic variation on the Mongolian steppes, the third largest grassland in the world. The onset date of green-up for central Asia was estimated using time-series analysis of advanced very high resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) biweekly composite data collected between January 1982 and December 1991. Monthly precipitation and mean temperature data (1982-1990) were acquired from 19 meteorological stations throughout the grasslands of the eastern Mongolian steppes in China. Our results showed that while the taiga forest north of the Mongolian steppes (>50°N) experienced an earlier onset of green-up during the study period, a later onset was observed at the eastern and northern edges of the Gobi Desert (40°N-50°N). Responses of different vegetation types to climatic variability appeared to vary with vegetation characteristics and spring soil moisture availability of specific sites. Plant stress caused by drought was the most significant contributor to later vegetation green-up as observed from satellite imagery over the desert steppe. Areas with greater seasonal soil moisture greened up earlier in the growing season. Our results suggested that water budget limitations determine the pattern of vegetation responses to atmospheric warming.     

星际争霸——狗狗

“狗狗?这是什么意思?“ 　　很明显嘟嘟对这句话已经麻木不仁,连转头都懒得转一下,就自顾自的靠在潮湿的洞壁上Zzzzzzzzzzzz去了,触须带着一点不满轻轻晃动着. 　　……     

Combined Petri net modelling and AI-based heuristic hybrid search for flexible manufacturing systems—part II. Heuristic hybrid search

This two-part paper presents modelling and scheduling approaches of flexible manufacturing systems using Petri nets (PNs) and artificial intelligence (AI)-based heuristic search methods. In Part I, PN-based modelling approaches and basic AI-based heuristic search algorithms were presented. In Part II, a new heuristic function that exploits PN information is proposed. Heuristic information obtained from the PN model is used to dramatically reduce the search space. This heuristic is derived from a new concept, the resource cost reachability matrix, which builds on the properties of B-nets proposed in Part I. Two hybrid search algorithms, (1) an approach to model dispatching rules using analysis information provided by the PN simulation and (2) an approach of the modified stage-search algorithm, are proposed to reduce the complexity of large systems. A random problem generator is developed to test the proposed methods. The experimental results show promising results.     

基于服务器转发的支持多种通信方式的通信协议

提出了一种基于服务器转发的通信协议，其能够支持广播、组播、单播这几种通信方式，支持多种类型消息的通信。介绍了该协议的功能、报文格式以及实现方法。     

狄利克雷积分的几种计算方法

利用含参量非正常积分的一些性质,给出了狄利克雷积分integral from n=0 to +∞(sinx)的几种计算方法。     

Effects of Deposition Temperature on the Properties of Fluorinated Amorphous Carbon Films

Fluorinated amorphous carbon films (a-C:F) were prepared at different temperatures using a microwave electron cyclotron resonance chemical vapor deposition (ECR-CVD) reactor with CHF3 and C2H2 as source gases. Films were annealed at 500℃ in vacuum ambience inorder to investigate the relationship of their thermal stability, optical and electrical propertieswith deposition temperature. Results indicate that the films deposited at high temperature have a less CFx bonding and a more cross-linking structure thus a better thermal stability. They also have a lower bandgap, higher dielectric constant and higher leakage current.     

应用于回归神经网络的基于梯度的典型算法的归纳与分析

首先给出了分层全回归神经网络的一个综合形式及其状态方程,然后归纳了几种典型的基于梯度的回归神经网络训练算法,描述了算法的具体步骤,并分析比较了算法特点及相互联系,最后指出对回归神经网络尤其是其训练算法研究存在的难点及研究重点。     

三相电压型低谐波PWM整流器主电路参数间的关系

三相电压型低谐波PWM整流器主电路的多个参数之间的关系较为复杂，在仿真和实验中，若给出的参数不合理，则变换器不能正常工作，从而给仿真和实验带来一定困难。文章在考虑了输入电阻的情况下，给出了功率因数角为任意值时，主电路各参数和控制参数间的稳态关系及一些参数的约束关系。上述关系对于分析和设计被研究电路具有很好的指导意义，文中的公式通过了仿真验证。     

A Quantum Correction Model for Nanoscale Double-Gate MOS Devices Under Inversion Conditions

A quantum correction model for nanoscale double-gate MOSFETs under inversion conditions is proposed. Based on the solution of Schrödinger-Poisson equations, the developed quantum correction model is optimized with respect to (i) the left and right positions of the charge concentration peak, (ii) the maximum of the charge concentration, (iii) the total inversion charge sheet density, and (iv) the average inversion charge depth, respectively. This model can predict inversion layer electron density for various oxide thicknesses, silicon film thicknesses, and applied voltages. Compared to the Schrödinger-Poisson results, our model prediction is within 3.0% of accuracy. This quantum correction model has continuous derivatives and is therefore amenable to a device simulator.