U-Th, 14C and d11B results for Holocene North Atlantic deep sea corals (Lophelia pertusa), 2011

Sediment Core MD01-2454G SW Rockall BANK 747m water depth on Logatechev Mounds (Core was taken during Marion Dufresne Cruise Geosciences 2001 at 55°31'N and 15°39'W) ENAM corals from BoxCores of SW Rockall Bank and Porcupine Bank water depth 725 and 750m (Box cores ENAM 9915 and ENAM 9910 were taken from 725 m bsl on the Southwest Rockall Bank (55,32°N, 15,40°W), and ENAM 9828 from 745 m bsl on the Porcupine Bank (53,48°N, 13,54°W))

Minimally invasive surgical video analysis: a powerful tool for surgical training and navigation

Analysis of minimally invasive surgical videos is a powerful tool to drive new solutions for achieving reproducible training programs, objective and transparent assessment systems and navigation tools to assist surgeons and improve patient safety. This paper presents how video analysis contributes to the development of new cognitive and motor training and assessment programs as well as new paradigms for image-guided surgery.

Selection, training and validation process of a sensory panel for bread analysis: Influence of cultivar on the quality of breads made from common wheat and spelta wheat

A protocol of selection, training and validation of the members of the panel for bread sensory analysis is proposed to assess the influence of wheat cultivar on the sensory quality of bread. Three cultivars of bread wheat and two cultivars of spelt wheat organically-grown under the same edaphoclimatic conditions were milled and baked using the same milling and baking procedure. Through the use of triangle tests, differences were identified between the five breads. Significant differences were found between the spelt breads and those made with bread wheat for the attributes ?crumb cell homogeneity? and ?crumb elasticity?. Significant differences were also found for the odor and flavor attributes, with the bread made with ?Espelta Navarra? being the most complex, from a sensory point of view. Based on the results of this study, we propose that sensory properties should be considered as breeding criteria for future work on genetic improvement.

The role of automated feedback in training and retaining biological recorders for citizen science

© 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Acknowledgments The authors thank H. H. Nguyen for his early development work on the BeeWatch interface; E. O'Mahony, I. Pearce, and R. Comont for identifying numerous photographed bumblebees; B. Darvill, D. Ewing, and G. Perkins for enabling our partnership with the Bumblebee Conservation Trust; and S. Blake for his investments in developing the NLG feedback. The study was part of the Digital Conservation project of dot.rural, the University of Aberdeen's Digital Economy Research Hub, funded by RCUK (grant reference EP/G066051/1).

Non-librarian health professionals becoming librarians and information specialists: results of an Internet survey

Objectives: To obtain basic information about non-librarian health professionals who become librarians and information specialists.

Health care, information needs, and outreach: reaching Ohio's rural citizens

As a rural state, Ohio has a vital interest in addressing rural health and information needs. NetWellness is a Web-based consumer health information service that focuses on the needs of the residents of Ohio. Health sciences faculty from the state's three Carnegie Research I universities—University of Cincinnati, Case Western Reserve University, and The Ohio State University—create and evaluate content and provide Ask an Expert service to all visitors. Through partnerships at the state and local levels, involving public, private, commercial, and noncommercial organizations, NetWellness has grown from a regional demonstration project in 1995 to a key statewide service. Collaboration with public libraries, complemented by alliances with kindergarten through twelfth grade agencies, makes NetWellness Ohio's essential health information resource.

Training and search methods for speech recognition.

Speech recognition involves three processes: extraction of acoustic indices from the speech signal, estimation of the probability that the observed index string was caused by a hypothesized utterance segment, and determination of the recognized utterance via a search among hypothesized alternatives. This paper is not concerned with the first process. Estimation of the probability of an index string involves a model of index production by any given utterance segment (e.g., a word). Hidden Markov models (HMMs) are used for this purpose [Makhoul, J. & Schwartz, R. (1995) Proc. Natl. Acad. Sci. USA 92, 9956-9963]. Their parameters are state transition probabilities and output probability distributions associated with the transitions. The Baum algorithm that obtains the values of these parameters from speech data via their successive reestimation will be described in this paper. The recognizer wishes to find the most probable utterance that could have caused the observed acoustic index string. That probability is the product of two factors: the probability that the utterance will produce the string and the probability that the speaker will wish to produce the utterance (the language model probability). Even if the vocabulary size is moderate, it is impossible to search for the utterance exhaustively. One practical algorithm is described [Viterbi, A. J. (1967) IEEE Trans. Inf. Theory IT-13, 260-267] that, given the index string, has a high likelihood of finding the most probable utterance.