57 resultados para Bull riding
Resumo:
Of the three classes of true phosphoinositide (PI) 3-kinases, the class II subdivision, which consists of three isoforms, PI3K-C2alpha, PI3K-C2beta and PI3K-C2gamma, is the least well understood. There are a number of reasons for this. This class of PI 3-kinase was identified exclusively by PCR and homology cloning approaches and not on the basis of cellular function. Like class I PI 3-kinases, class II PI 3-kinases are activated by diverse receptor types. To complicate the elucidation of class II PI 3-kinase function further, their in vitro substrate specificity is intermediate between the receptor activated class I PI 3-kinases and the housekeeping class III PI 3-kinase. The class II PI 3-kinases are inhibited by the two commonly used PI 3-kinase family selective inhibitors, wortmannin and LY294002, and there are no widely available, specific inhibitors for the individual classes or isoforms. Here the current state of understanding of class II PI 3-kinase function is reviewed, followed by an appraisal as to whether there is enough evidence to suggest that pharmaceutical companies, who are currently targeting the class I PI 3-kinases in an attempt to generate anticancer agents, should also consider targeting the class II PI 3-kinases.
Resumo:
Inelastic neutron scattering spectroscopy has been used to observe and characterise hydrogen on the carbon component of a Pt/C catalyst. INS provides the complete vibration spectrum of coronene, regarded as a molecular model of a graphite layer. The vibrational modes are assigned with the aid of ab initio density functional theory calculations and the INS spectra by the a-CLIMAX program. A spectrum for which the H modes of coronene have been computationally suppressed, a carbon-only coronene spectrum, is a better representation of the spectrum of a graphite layer than is coronene itself. Dihydrogen dosing of a Pt/C catalyst caused amplification of the surface modes of carbon, an effect described as H riding on carbon. From the enhancement of the low energy carbon modes (100-600 cm(-1)) it is concluded that spillover hydrogen becomes attached to dangling bonds at the edges of graphitic regions of the carbon support. (C) 2003 Elsevier Science B.V. All rights reserved.
Resumo:
Motorcyclists and a matched group of non-motorcycling car drivers were assessed on behavioral measures known to relate to accident involvement. Using a range of laboratory measures, we found that motorcyclists chose faster speeds than the car drivers, overtook more, and pulled into smaller gaps in traffic, though they did not travel any closer to the vehicle in front. The speed and following distance findings were replicated by two further studies involving unobtrusive roadside observation. We suggest that the increased risk-taking behavior of motorcyclists was only likely to account for a small proportion of the difference in accident risk between motorcyclists and car drivers. A second group of motorcyclists was asked to complete the simulator tests as if driving a car. They did not differ from the non-motorcycling car drivers on the risk-taking measures but were better at hazard perception. There were also no differences for sensation seeking, mild social deviance, and attitudes to riding/driving, indicating that the risk-taking tendencies of motorcyclists did not transfer beyond motorcycling, while their hazard perception skill did. (C) 2002 Elsevier Science Ltd. All rights reserved.
Resumo:
Purpose – Construction sector competitiveness has been a subject of interest for many years. Research too often focuses on the means of overcoming the “barriers to change” as if such barriers were static entities. There has been little attempt to understand the dynamic inter-relationship between the differing factors which impinge upon construction sector competitiveness. The purpose of this paper is to outline the benefits of taking a systems approach to construction competitiveness research. Design/methodology/approach – The system dynamics (SD) modelling methodology is described. This can provide practitioners with “microworlds” within which they can explore the dynamic effects of different policy decisions. The data underpinning the use of SD was provided by interviews and case study research which allowed an understanding of the context within which practitioners operate. Findings – The over-riding conclusion is that the SD methodology has been shown to be capable of providing a means to assess the forces which shape the sustained competitiveness of construction firms. As such, it takes the assessment of strategic policy analysis in the construction sector onto a higher plane. The need to collect data and make retrospective assessments of competitiveness and strategic performance at the statistical level is not now the only modus operandi available. Originality/value – The paper describes a novel research methodology which points towards an alternative research agenda for construction competitiveness research.
Resumo:
Observations of a chemical at a point in the atmosphere typically show sudden transitions between episodes of high and low concentration. Often these are associated with a rapid change in the origin of air arriving at the site. Lagrangian chemical models riding along trajectories can reproduce such transitions, but small timing errors from trajectory phase errors dramatically reduce the correlation between modeled concentrations and observations. Here the origin averaging technique is introduced to obtain maps of average concentration as a function of air mass origin for the East Atlantic Summer Experiment 1996 (EASE96, a ground-based chemistry campaign). These maps are used to construct origin averaged time series which enable comparison between a chemistry model and observations with phase errors factored out. The amount of the observed signal explained by trajectory changes can be quantified, as can the systematic model errors as a function of air mass origin. The Cambridge Tropospheric Trajectory model of Chemistry and Transport (CiTTyCAT) can account for over 70% of the observed ozone signal variance during EASE96 when phase errors are side-stepped by origin averaging. The dramatic increase in correlation (from 23% without averaging) cannot be achieved by time averaging. The success of the model is attributed to the strong relationship between changes in ozone along trajectories and their origin and its ability to simulate those changes. The model performs less well for longer-lived chemical constituents because the initial conditions 5 days before arrival are insufficiently well known.