5,178 research outputs found
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
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