Convenient Labelling Technique for Mass Spectrometry - Acid Catalyzed Deuterium and Oxygen-18 Exchange via Gas-liquid Chromatography

Mass spectrometry labelling technique - acid catalyzed deuterium and oxygen 18 exchange by gas-liquid chromatograph

The Impact of the Internet Tax Freedom Act on State Revenues

The Internet Tax Freedom Act, passed by the U.S. Congress, is both a result of and a potentially important influence on the growth of electronic commerce. This paper examines the impact of the moratorium imposed by the legislation prohibiting the collection of taxes on Internet commerce. Its significance with respect to business-to-business and business-to-consumer commerce is documented by analysis of current sales activities. The paper also explores the potential impact on a variety of sales categories if the moratorium is extended beyond the current three-year period of effect. The discussion illustrates how continuing the force of the legislation will have an increasingly significant effect on both states, which depend on sales tax revenue, and participants in Internet commerce

Emergence of long-range order in BaTiO3 from local symmetry-breaking distortions

By using a symmetry motivated basis to evaluate local distortions against pair distribution function data (PDF), we show without prior bias, that the off-centre Ti displacements in the archetypal ferroelectric BaTiO3 are zone centred and rhombohedral-like in nature across its known ferroelectric and paraelectric phases. With our newly-gained insight we construct a simple Monte Carlo (MC) model which captures our main experimental findings and demonstrate how the rich crystallographic phase diagram of BaTiO3 emerges from correlations of local symmetry-breaking distortions alone. Our results strongly support the order-disorder picture for these phase transitions, but can also be reconciled with the soft-mode theory of BaTiO3 that is supported by some spectroscopic techniques.Comment: 5 pages, 3 figure

Overstating the evidence - double counting in meta-analysis and related problems

Background: The problem of missing studies in meta-analysis has received much attention. Less attention has been paid to the more serious problem of double counting of evidence. Methods: Various problems in overstating the precision of results from meta-analyses are described and illustrated with examples, including papers from leading medical journals. These problems include, but are not limited to, simple double-counting of the same studies, double counting of some aspects of the studies, inappropriate imputation of results, and assigning spurious precision to individual studies. Results: Some suggestions are made as to how the quality and reliability of meta-analysis can be improved. It is proposed that the key to quality in meta-analysis lies in the results being transparent and checkable. Conclusions: Existing quality check lists for meta-analysis do little to encourage an appropriate attitude to combining evidence and to statistical analysis. Journals and other relevant organisations should encourage authors to make data available and make methods explicit. They should also act promptly to withdraw meta-analyses when mistakes are found

INFORMATION SYSTEMS SUPPORT FOR ASSESSMENT OF MANAGEMENT PERFORMANCE: AN EXPERIMENTAL EVALUATION

This paper reports the results of a study to determine how individual managers assemble information from automated systems when the task is evaluating organization performance. An experiment was conducted in which managers were given varying forms of information over a period of time and required to accumulate the information they would need for a later evaluation decision. As the results show, there are differences in the way individuals select and assemble reported information system design practices

Harold Jeffreys's Theory of Probability Revisited

Published exactly seventy years ago, Jeffreys's Theory of Probability (1939) has had a unique impact on the Bayesian community and is now considered to be one of the main classics in Bayesian Statistics as well as the initiator of the objective Bayes school. In particular, its advances on the derivation of noninformative priors as well as on the scaling of Bayes factors have had a lasting impact on the field. However, the book reflects the characteristics of the time, especially in terms of mathematical rigor. In this paper we point out the fundamental aspects of this reference work, especially the thorough coverage of testing problems and the construction of both estimation and testing noninformative priors based on functional divergences. Our major aim here is to help modern readers in navigating in this difficult text and in concentrating on passages that are still relevant today.Comment: This paper commented in: [arXiv:1001.2967], [arXiv:1001.2968], [arXiv:1001.2970], [arXiv:1001.2975], [arXiv:1001.2985], [arXiv:1001.3073]. Rejoinder in [arXiv:0909.1008]. Published in at http://dx.doi.org/10.1214/09-STS284 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Spiking neurons with short-term synaptic plasticity form superior generative networks

Spiking networks that perform probabilistic inference have been proposed both as models of cortical computation and as candidates for solving problems in machine learning. However, the evidence for spike-based computation being in any way superior to non-spiking alternatives remains scarce. We propose that short-term plasticity can provide spiking networks with distinct computational advantages compared to their classical counterparts. In this work, we use networks of leaky integrate-and-fire neurons that are trained to perform both discriminative and generative tasks in their forward and backward information processing paths, respectively. During training, the energy landscape associated with their dynamics becomes highly diverse, with deep attractor basins separated by high barriers. Classical algorithms solve this problem by employing various tempering techniques, which are both computationally demanding and require global state updates. We demonstrate how similar results can be achieved in spiking networks endowed with local short-term synaptic plasticity. Additionally, we discuss how these networks can even outperform tempering-based approaches when the training data is imbalanced. We thereby show how biologically inspired, local, spike-triggered synaptic dynamics based simply on a limited pool of synaptic resources can allow spiking networks to outperform their non-spiking relatives.Comment: corrected typo in abstrac

Comparison of Forward, Backward, and Conventional Training in the Learning of a List of CVC Trigrams

Ss were instructed to learn a list of 10 CVC trigrams by either the conventional serial anticipation method, backward conditioning or forward conditioning. The F ratio failed to show a significant difference between the three experimental groups. The results contradict previous results which shown that forward training is more efficient than the other two methods