Fabrication and characteristic detection of graphene nanoelectrodes

Graphene has the advantages of high electrical conductivity, high heat conductivity, and low noise, which makes it a potential option for integrated circuits interconnection and nanoelectrodes. In this paper, we present a novel fabrication method for graphene nanoeletrodes with nanogap. First, graphene grown by chemical vapor deposition (CVD) is assembled to a chip with microelectrodes. Second, an atomic force microscopy (AFM) based mechanical cutting method is developed to cut the graphene into nanoribbons and nanoeletrodes with nanogap. Then the electronic property of a single nanodot is characterized using the garphene nanoelectrodes, demonstrating the effectiveness of the graphene nanoelectrodes. The fabricated graphene nanoeletrode pairs can be used as probes to detect single molecule in micro-environment, and show an attractive prospect for future molecular electronics applications.     

北美最知名的石油天然气流量标定与研究机构——美国科罗拉多工程实验室简介

科罗拉多工程实验室的历史 美国科罗拉多工程实验室(以下简称CEESI)运营始于1951年,作为工程实验室,是科罗拉多大学工程学院的一项计划,用于研究、开发和测试军用火箭.1966年,这个非盈利机构从大学分离出来并迁址到现在的地址,改名为科罗拉多工程试验室(有限)公司.CEESI一直保持非商业性研究机构的状态,直到1986年两位知名计量权威Walt Seidl和Steve Caldwell收购了实验室,将它作为独立的商业性实验室开始运营.在其创立后的50多年间,CEESI一直是北美最知名的石油天然气流量标定和研究机构之一.     

Predicting change for individual psychotherapy clients on the basis of their nearest neighbors.

This study extended client-focused research by using the nearest neighbor (NN) approach, a client-specific sampling and prediction strategy derived from research on alpine avalanches. Psychotherapy clients (N = 203) seen in routine practice settings in the United Kingdom completed a battery of intake measures and then completed symptom intensity ratings before each session. Forecasts of each client's rate of change and session-by-session variability were computed on the basis of that client's NNs (n = 10-50 in different comparisons). Alternative forecasts used linear or log-linear slopes and were compared with an alternative prediction strategy. Results showed that the NN approach was superior to the alternative model in predicting rate of change, though the advantage was less clear for predicting variability. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Scaling Gross Primary Production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation

The Moderate Resolution Imaging Radiometer (MODIS) is the primary instrument in the NASA Earth Observing System for monitoring the seasonality of global terrestrial vegetation. Estimates of 8-day mean daily gross primary production (GPP) at the 1 km spatial resolution are now operationally produced by the MODIS Land Science Team for the global terrestrial surface using a production efficiency approach. In this study, the 2001 MODIS GPP product was compared with scaled GPP estimates (25 km²) based on ground measurements at two forested sites. The ground-based GPP scaling approach relied on a carbon cycle process model run in a spatially distributed mode. Land cover classification and maximum annual leaf area index, as derived from Landsat ETM+ imagery, were used in model initiation. The model was driven by daily meteorological observations from an eddy covariance flux tower situated at the center of each site. Model simulated GPPs were corroborated with daily GPP estimates from the flux tower. At the hardwood forest site, the MODIS GPP phenology started earlier than was indicated by the scaled GPP, and the summertime GPP from MODIS was generally lower than the scaled GPP values. The fall-off in production at the end of the growing season was similar to the validation data. At the boreal forest site, the GPP phenologies generally agreed because both responded to the strong signal associated with minimum temperature. The midsummer MODIS GPP there was generally higher than the ground-based GPP. The differences between the MODIS GPP products and the ground-based GPPs were driven by differences in the timing of FPAR and the magnitude of light use efficiency as well as by differences in other inputs to the MODIS GPP algorithm—daily incident PAR, minimum temperature, and vapor pressure deficit. Ground-based scaling of GPP has the potential to improve the parameterization of light use efficiency in satellite-based GPP monitoring algorithms.     

Violet

Violet is an easy-to-use theorem prover based on locking resolution, with integrated equality extensions that use term rewriting and Knuth–Bendix completion. Violet participated in the CADE-13 ATP System Competition.     

Boundary cell-based acceleration for volume ray casting

Several effective acceleration techniques for volume rendering offer efficient means to skip over empty space, providing significant speedup without affecting image quality. The effectiveness of such an approach depends on its ability to accurately estimate the object boundary inside a volume with minimal computational overhead. We propose a novel boundary cell-based acceleration technique for ray casting which skips over empty space by accurately calculating the intersection distance for each ray. Very short distance estimation time is achieved by exploiting a projection template to calculate the parallel-projection values of each boundary cell and the coherency of adjacent cells. Since no hardware acceleration is used, the projection procedure can also be efficiently parallelized. Experimental results are provided to demonstrate the performance of our new algorithm.     

An Autonomous Spacecraft Agent Prototype

This paper describes the New Millennium Remote Agent (NMRA) architecture for autonomous spacecraft control systems. The architecture supports challenging requirements of the autonomous spacecraft domain not usually addressed in mobile robot architectures, including highly reliable autonomous operations over extended time periods in the presence of tight resource constraints, hard deadlines, limited observability, and concurrent activity. A hybrid architecture, NMRA integrates traditional real-time monitoring and control with heterogeneous components for constraint-based planning and scheduling, robust multi-threaded execution, and model-based diagnosis and reconfiguration. Novel features of this integrated architecture include support for robust closed-loop generation and execution of concurrent temporal plans and a hybrid procedural/deductive executive.We implemented a prototype autonomous spacecraft agent within the architecture and successfully demonstrated the prototype in the context of a challenging autonomous mission scenario on a simulated spacecraft. As a result of this success, the integrated architecture has been selected to fly as an autonomy experiment on Deep Space One (DS-1), the first flight of NASA';s New Millennium Program (NMP), which will launch in 1998. It will be the first AI system to autonomously control an actual spacecraft.     

The Managerial Implications of Real-Time New Product Development in Financial Services

A review of the various models of New Product Development (NPD) process shows that although different approaches have been proposed, they are in fact all variants on a linear theme: some may include feedback loops, but they all essentially advocate that certain steps precede, or are preceded by, others. An inevitable consequence on the Internet/World Wide Web (WWW or Web) is that such models are no longer applicable. Based on the lessons learned from the development of a new financial service offered via the Internet, we show how such assumptions of linearity need no longer be a constraint. In addition, innovativeness is not related to firm size. But the fact that the Web allows for the real-time development of new financial services based on on-going feedback from potential and current customers raises a new set of managerial issues that have to be tackled. The objective of this paper is to use the context of the recent launch of an innovative financial service product via the Web to explore the managerial changes that are starting to affect the banking industry.     

Goal-driven automation of a deep space communications station: a case study in knowledge engineering for plan generation and execution

Abstract: This paper describes the application of Artificial Intelligence techniques for plan generation, plan execution, and plan monitoring to automate a Deep Space Communication Station. This automation allows a communication station to respond to a set of tracking goals by appropriately reconfiguring the communications hardware and software to provide the requested communications services. In particular this paper describes: (1) the overall automation architecture, (2) the plan generation and execution monitoring AI technologies used and implemented software components, and (3) the knowledge engineering process and effort required for automation. This automation was demonstrated in February 1995, at the DSS13 Antenna Station in Goldstone, CA on a series of Voyager tracks and the technologies demonstrated are being transferred to the operational Deep Space Network stations.     

用于去除单张图像高光的光照约束补色

在计算机视觉研究领域,如何检测和消除图像中的高光(specular)一直是个热点问题,有关的研究结果对于提高计算机视觉算法性能有着重要的影响.针对这一问题,提出了一种检测和消除高光的方法.首先,通过比较高光和漫反射光(diffuse)的色度特性的不同,给出了一种交互检测单色物体表面高光区域的方法;然后,引入补色(inpainting)方法并结合光照约束条件,设计了一种去除单张图像中高光并还原出漫反射分量的新的补色算法.与一般补色方法不同,该算法充分利用了高光区域含有的信息来指导补色过程.通过综合利用观测到的像素值、光源的色度分析(illumination chromaticity analysis)、光源颜色的平滑性等来约束补色过程,保证了算法能够克服一般的补色方法无法保持物体表面细微明暗变化的缺点.实验结果表明,与以往的去除单张图像高光的方法相比,该算法能够提供更好的光源色度估计,从而得到更准确的结果.