The activation of hydrogen by excited mercury atoms

That mercury atoms excited by absorption of the line 2537Å are able to activate various kinds of atoms by collisions of the second kind has been shown in several different ways. Using pressure measurements to follow the reaction, Cario and Franck (1) showed that hydrogen, in the presence of excited mercury vapor, can be activated and made to reduce copper oxide or tungsten oxide, while Dickinson (2) repeated the experiment using gaseous oxygen instead of solid oxide. Employing spectroscopic methods of detection, Cario (3) activated thallium vapor by collisions with excited mercury atoms and observed the radiation of the green thallium line 5351 Å and indeed all the thallium lines which would theoretically be expected

The analysis of nonstationary vibration data

The general methodology for the analysis of arbitrary nonstationary random data is reviewed. A specific parametric model, called the product model, that has applications to space vehicle launch vibration data analysis is discussed. Illustrations are given using the nonstationary launch vibration data measured on the Space Shuttle orbiter vehicle

Optimum data analysis procedures for Titan 4 and Space Shuttle payload acoustic measurements during lift-off

Analytical expressions have been derived to describe the mean square error in the estimation of the maximum rms value computed from a step-wise (or running) time average of a nonstationary random signal. These analytical expressions have been applied to the problem of selecting the optimum averaging times that will minimize the total mean square errors in estimates of the maximum sound pressure levels measured inside the Titan IV payload fairing (PLF) and the Space Shuttle payload bay (PLB) during lift-off. Based on evaluations of typical Titan IV and Space Shuttle launch data, it has been determined that the optimum averaging times for computing the maximum levels are (1) T (sub o) = 1.14 sec for the maximum overall level, and T(sub oi) = 4.88 f (sub i) (exp -0.2) sec for the maximum 1/3 octave band levels inside the Titan IV PLF, and (2) T (sub o) = 1.65 sec for the maximum overall level, and T (sub oi) = 7.10 f (sub i) (exp -0.2) sec for the maximum 1/3 octave band levels inside the Space Shuttle PLB, where f (sub i) is the 1/3 octave band center frequency. However, the results for both vehicles indicate that the total rms error in the maximum level estimates will be within 25 percent the minimum error for all averaging times within plus or minus 50 percent of the optimum averaging time, so a precise selection of the exact optimum averaging time is not critical. Based on these results, linear averaging times (T) are recommended for computing the maximum sound pressure level during lift-off

Modelling and simulation framework for reactive transport of organic contaminants in bed-sediments using a pure java object - oriented paradigm

Numerical modelling and simulation of organic contaminant reactive transport in the environment is being increasingly relied upon for a wide range of tasks associated with risk-based decision-making, such as prediction of contaminant profiles, optimisation of remediation methods, and monitoring of changes resulting from an implemented remediation scheme. The lack of integration of multiple mechanistic models to a single modelling framework, however, has prevented the field of reactive transport modelling in bed-sediments from developing a cohesive understanding of contaminant fate and behaviour in the aquatic sediment environment. This paper will investigate the problems involved in the model integration process, discuss modelling and software development approaches, and present preliminary results from use of CORETRANS, a predictive modelling framework that simulates 1-dimensional organic contaminant reaction and transport in bed-sediments

Nanoelectronics

In this chapter we intend to discuss the major trends in the evolution of microelectronics and its eventual transition to nanoelectronics. As it is well known, there is a continuous exponential tendency of microelectronics towards miniaturization summarized in G. Moore's empirical law. There is consensus that the corresponding decrease in size must end in 10 to 15 years due to physical as well as economical limits. It is thus necessary to prepare new solutions if one wants to pursue this trend further. One approach is to start from the ultimate limit, i.e. the atomic level, and design new materials and components which will replace the present day MOS (metal-oxide-semi- conductor) based technology. This is exactly the essence of nanotechnology, i.e. the ability to work at the molecular level, atom by atom or molecule by molecule, to create larger structures with fundamentally new molecular orga- nization. This should lead to novel materials with improved physical, chemi- cal and biological properties. These properties can be exploited in new devices. Such a goal would have been thought out of reach 15 years ago but the advent of new tools and new fabrication methods have boosted the field. We want to give here an overview of two different subfields of nano- electronics. The first part is centered on inorganic materials and describes two aspects: i) the physical and economical limits of the tendency to miniaturiza- tion; ii) some attempts which have already been made to realize devices with nanometric size. The second part deals with molecular electronics, where the basic quantities are now molecules, which might offer new and quite interest- ing possibilities for the future of nanoelectronicsComment: HAL : hal-00710039, version 2. This version corrects some aspect concerning the metal-insulator-metal without dot

A distinctive energy policy for Scotland?

This paper explores the emergence of a distinctive energy policy for Scotland and raises the issue of the desirability of any differentiation from UK energy policy. This requires an examination of both UK and Scottish energy policies, although we adopt a rather broad-brush overview rather than a very detailed analysis

Three and Four Region Multi-sector Linear Modelling Using UK Data : Some Preliminary Results

Scotland and Wales have relatively up-to-date, independently generated, IO tables. These can be separated out from a UK national IO table to construct an inter-regional table. We therefore undertake the detailed analysis at this three-region (Scotland, Wales and the Rest of the UK (RUK)) level, where the Rest of the UK is England and Northern Ireland. However, we also construct a more rudimentary four-region (Scotland, Wales, England and Ireland) set of IO and SAM accounts by constructing a separate Northern Ireland accounts. The inter-regional IO and SAM models are produced for the year 1999. This was determined by the availability of consistent data. In Section II we describe the construction of a three-region Input-Output model for the United Kingdom, which includes the regions of Scotland, Wales and the Rest of the UK (RUK). In Section III we extend the three-region model to construct an inter-regional Social Accounting Matrix. Section IV reports some results using the three-region IO and SAM models. In Section V, we generate a four-region IO and SAM model for the UK, which disaggregates Northern Ireland from the Rest of the UK, and provide some results using the four-region IO and SAM models. Section VI offers our conclusions

Construction of a multi-sectoral inter-regional IO and SAM database for the UK

The purpose of this paper is to explain the construction of the input-output (IO) and social accounting matrix (SAM) databases for the inter-regional computable general equilibrium (CGE) model of the UK developed as part of the project 'An Analysis of National and Devolved Economic Policies' undertaken as part of the ESRC Devolution and Constitutional Change research programme. We identify four main regions of the UK: Scotland, Wales, Northern Ireland and England. However, in Section 2, we begin by constructing a set of two-region accounts where we focus on Scotland, Wales or Northern Ireland with the other aggregate 'region' labelled 'rest of the UK' or RUK. Then, in Section 3, we extend to a three-region framework where we identify Scotland, Wales and RUK. Finally, in Section 4, we extend further to construct the full 4-region IO and SAM