Systematic description and key to streptomyces isolants from Chile-Atacama Desert, Hawaii, and Oregon soils

Systematic description and key to Streptomycetes isolants from Chile-Atacama Desert, Hawaii, and Oregon soil

Systematic description and key to Streptomyces isolants from Chile, Mexico and Arizona desert soils Progress report

Streptomycetes isolants from Chile, Mexico, and Arizona desert soil

The Ramsey method in high-precision mass spectrometry with Penning traps: Experimental results

The highest precision in direct mass measurements is obtained with Penning trap mass spectrometry. Most experiments use the interconversion of the magnetron and cyclotron motional modes of the stored ion due to excitation by external radiofrequency-quadrupole fields. In this work a new excitation scheme, Ramsey's method of time-separated oscillatory fields, has been successfully tested. It has been shown to reduce significantly the uncertainty in the determination of the cyclotron frequency and thus of the ion mass of interest. The theoretical description of the ion motion excited with Ramsey's method in a Penning trap and subsequently the calculation of the resonance line shapes for different excitation times, pulse structures, and detunings of the quadrupole field has been carried out in a quantum mechanical framework and is discussed in detail in the preceding article in this journal by M. Kretzschmar. Here, the new excitation technique has been applied with the ISOLTRAP mass spectrometer at ISOLDE/CERN for mass measurements on stable as well as short-lived nuclides. The experimental resonances are in agreement with the theoretical predictions and a precision gain close to a factor of four was achieved compared to the use of the conventional excitation technique.Comment: 12 pages, 14 figures, 2 table

Magnetic field stabilization for high-accuracy mass measurements on exotic nuclides

The magnetic-field stability of a mass spectrometer plays a crucial role in precision mass measurements. In the case of mass determination of short-lived nuclides with a Penning trap, major causes of instabilities are temperature fluctuations in the vicinity of the trap and pressure fluctuations in the liquid helium cryostat of the superconducting magnet. Thus systems for the temperature and pressure stabilization of the Penning trap mass spectrometer ISOLTRAP at the ISOLDE facility at CERN have been installed. A reduction of the fluctuations by at least one order of magnitude downto dT=+/-5mK and dp=+/-50mtorr has been achieved, which corresponds to a relative frequency change of 2.7x10^{-9} and 1.5x10^{-10}, respectively. With this stabilization the frequency determination with the Penning trap only shows a linear temporal drift over several hours on the 10 ppb level due to the finite resistance of the superconducting magnet coils.Comment: 23 pages, 13 figure

Finding Scientific Gems with Google

We apply the Google PageRank algorithm to assess the relative importance of all publications in the Physical Review family of journals from 1893--2003. While the Google number and the number of citations for each publication are positively correlated, outliers from this linear relation identify some exceptional papers or "gems" that are universally familiar to physicists.Comment: 6 pages, 4 figures, 2 tables, 2-column revtex4 forma

A linear radiofrequency ion trap for accumulation, bunching, and emittance improvement of radioactive ion beams

An ion beam cooler and buncher has been developed for the manipulation of radioactive ion beams. The gas-filled linear radiofrequency ion trap system is installed at the Penning trap mass spectrometer ISOLTRAP at ISOLDE/CERN. Its purpose is to accumulate the 60-keV continuous ISOLDE ion beam with high efficiency and to convert it into low-energy low-emittance ion pulses. The efficiency was found to exceed 10% in agreement with simulations. A more than 10-fold reduction of the ISOLDE beam emittance can be achieved. The system has been used successfully for first on-line experiments. Its principle, setup and performance will be discussed

How did the discussion go: Discourse act classification in social media conversations

We propose a novel attention based hierarchical LSTM model to classify discourse act sequences in social media conversations, aimed at mining data from online discussion using textual meanings beyond sentence level. The very uniqueness of the task is the complete categorization of possible pragmatic roles in informal textual discussions, contrary to extraction of question-answers, stance detection or sarcasm identification which are very much role specific tasks. Early attempt was made on a Reddit discussion dataset. We train our model on the same data, and present test results on two different datasets, one from Reddit and one from Facebook. Our proposed model outperformed the previous one in terms of domain independence; without using platform-dependent structural features, our hierarchical LSTM with word relevance attention mechanism achieved F1-scores of 71\% and 66\% respectively to predict discourse roles of comments in Reddit and Facebook discussions. Efficiency of recurrent and convolutional architectures in order to learn discursive representation on the same task has been presented and analyzed, with different word and comment embedding schemes. Our attention mechanism enables us to inquire into relevance ordering of text segments according to their roles in discourse. We present a human annotator experiment to unveil important observations about modeling and data annotation. Equipped with our text-based discourse identification model, we inquire into how heterogeneous non-textual features like location, time, leaning of information etc. play their roles in charaterizing online discussions on Facebook

A general multivariate latent growth model with applications in student careers Data warehouses

The evaluation of the formative process in the University system has been assuming an ever increasing importance in the European countries. Within this context the analysis of student performance and capabilities plays a fundamental role. In this work we propose a multivariate latent growth model for studying the performances of a cohort of students of the University of Bologna. The model proposed is innovative since it is composed by: (1) multivariate growth models that allow to capture the different dynamics of student performance indicators over time and (2) a factor model that allows to measure the general latent student capability. The flexibility of the model proposed allows its applications in several fields such as socio-economic settings in which personal behaviours are studied by using panel data.Comment: 20 page

Automatic Metadata Generation using Associative Networks

In spite of its tremendous value, metadata is generally sparse and incomplete, thereby hampering the effectiveness of digital information services. Many of the existing mechanisms for the automated creation of metadata rely primarily on content analysis which can be costly and inefficient. The automatic metadata generation system proposed in this article leverages resource relationships generated from existing metadata as a medium for propagation from metadata-rich to metadata-poor resources. Because of its independence from content analysis, it can be applied to a wide variety of resource media types and is shown to be computationally inexpensive. The proposed method operates through two distinct phases. Occurrence and co-occurrence algorithms first generate an associative network of repository resources leveraging existing repository metadata. Second, using the associative network as a substrate, metadata associated with metadata-rich resources is propagated to metadata-poor resources by means of a discrete-form spreading activation algorithm. This article discusses the general framework for building associative networks, an algorithm for disseminating metadata through such networks, and the results of an experiment and validation of the proposed method using a standard bibliographic dataset