112 research outputs found
The silicon Multiplicity Detector for the NA50 experiment
Abstract The operation and performance of the silicon strip Multiplicity Detector in the heavy-ion experiment NA50 at CERN are presented together with a selection of physics results. The main features of the detector are high speed (50 MHz sampling frequency), high granularity (more than 13,000 strips), and good radiation resistance. The detector provided a measurement of event centrality in Pb–Pb collisions, as well as target identification and the measurement of charged particle pseudorapidity distributions as a function of centrality
Silicon strip detectors for two-dimensional soft X-ray imaging at normal incidence
A simple prototype system for static two-dimensional soft X-ray imaging using silicon microstrip detectors irradiated at normal incidence is presented. Radiation sensors consist of single-sided silicon detectors made from 300 mum thick wafers, read by RX64 ASICs. Data acquisition and control is performed by a Windows PC workstation running dedicated LabVIEW routines, connected to the sensors through a PCI-DIO-96 interface. Two-dimensional images are obtained by scanning a lead collimator with a thin slit perpendicular to the strip axis, along the whole detector size; the several strip profiles (slices) taken at each position are then put together to form a planar image. Preliminary results are presented, illustrating the high-resolution imaging capabilities of the system with soft X-rays. (C) 2003 Elsevier B.V. All rights reserved.info:eu-repo/semantics/publishedVersio
The silicon multiplicity detector for the NA50 experiment at CERN
The design, operation and performance of the silicon strip Multiplicity Detector for the heavy-ion experiment NA50 at CERN are presented. The main features of the detector are high speed (50 MHz sampling frequency), high granularity (more than 13,000 strips), and good radiation resistance. The detector provided a measurement ofevent centrality in Pb–Pb collisions, as well as target identification and the measurement ofcharged particle pseudorapidity distributions as a function of centrality. r 2002 Elsevier Science B.V. All rights reserved. PACS: 29.4
Analysis of radiation effects on silicon strip detectors in the NA50 experiment
Abstract During the operation of the Multiplicity Detector in the NA50 experiment the single sided AC-coupled p-on-n silicon strip detectors were exposed to charged particle fluences resulting in an equivalent 1 MeV neutron fluence up to 10 14 eq. n/cm 2 and a total ionising dose up to 20 Mrad, with a very non-uniform radiation spatial distribution. In this paper detailed analysis of radiation effects observed on the detectors during the 1996 lead ion run as well as results of measurements performed after the run are presented
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
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