Search

The ground state half-lives of 69Ge, 73Se, 83Sr, 63Zn, and the half-life of the 1/2- isomer in 85Sr have been measured with high precision using the photoactivation technique at an unconventional bremsstrahlung facility that features a repurposed medical electron linear accelerator. The g-ray activity was counted over about 6 half-lives with a high-purity Germanium detector, enclosed into an ultra low-background lead shield. The measured half-lives are: T1/2(69Ge) = 38.82 +/- 0.07 (stat) +/- 0.06 (sys) h; T1/2(73Se) = 7.18 +/- 0.02 (stat) +/- 0.004 (sys) h; T1/2(83Sr) = 31.87 +/- 1.16 (stat) +/- 0.42 (sys) h; T1/2(85mSr) = 68.24 +/- 0.84 (stat) +/- 0.11 (sys) min; T1/2(63Zn) = 38.71 +/- 0.25 (stat) +/- 0.10 (sys) min. These high-precision half-life measurements will contribute to a more accurate determination of corresponding ground-state photoneutron reaction rates, which are part of a broader effort of constraining statistical nuclear models needed to calculate stellar nuclear reaction rates relevant for the astrophysical p-process nucleosynthesis., Comment: Accepted for publication in Journal of Radioanalytical and Nuclear Chemistry (JRNC)

The AMI Meeting Corpus is a multi-modal data set consisting of 100 hours of meeting recordings. It is being created in the context of a project that is developing meeting browsing technology and will eventually be released publicly. Some of the meetings it contains are naturally occurring, and some are elicited, particularly using a scenario in which the participants play different roles in a design team, taking a design project from kick-o' to completion over the course of a day. The corpus is being recorded using a wide range of devices including close-talking and far-field microphones, individual and room-view video cameras, projection, a whiteboard, and individual pens, all of which produce output signals that are synchronized with each other. It is also being hand-annotated for many different phenomena, including orthographic transcription, discourse properties such as named entities and dialogue acts, summaries, emotions, and some head and hand gestures. We describe the data set, including the rationale behind using elicited material, and explain how the material is being recorded, transcribed and annotated.

This paper describes some recent results of our collaborative work on developing a speech recognition system for the automatic transcription or media archives from the British Broadcasting Corporation (BBC). The material includes a wide diversity of shows with their associated metadata. The latter are highly diverse in terms of completeness, reliability and accuracy. First, we investigate how to improve lightly supervised acoustic training, when timestamp information is inaccurate and when speech deviates significantly from the transcription, and how to perform evaluations when no reference transcripts are available. An automatic timestamp correction method as well as a word and segment level combination approaches between the lightly supervised transcripts and the original programme scripts are presented which yield improved metadata. Experimental results show that systems trained using the improved metadata consistently outperform those trained with only the original lightly supervised decoding hypotheses. Secondly, we show that the recognition task may benefit from systems trained on a combination of in-domain and out-of-domain data. Working with tandem HMMs, we describe Multi-level Adaptive Networks, a novel technique for incorporating information from out-of domain posterior features using deep neural network. We show that it provides a substantial reduction in WER over other systems including a PLP-based baseline, in-domain tandem features, and the best out-of-domain tandem features.

Building bioinformatic facilities for a university hospital is pretty similar to using standardized building blocks to construct a house. Starting with the intention to built a dwelling house, a factory or just a shelter the architect draws a construction plan and determines the material to be used. In general, the building is then constructed by the workmen following exactly the plan. However, for particular reasons, minor alterations may be needed to improve the construction of the building. Here we use the metaphor of constructing a "bio-informatics building" to describe the steps needed to support the daily tasks of a university hospital medical microbiology department which uses genomic methods quite extensively for pathogen identification. Today the Giessen "bioinformatics building" is not yet complete but we have been able to lay solid foundations and erect the ground floor which is functional already. Using a combination of standard tools, internet accessible genomic databases and some own software tools we can support genome sequencing from the raw sequence to pathogen identification.