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出典(authority):フリー百科事典『ウィキペディア（Wikipedia）』「2016/01/10 23:58:22」(JST)

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Microbial and sensorial models for head-on and gutted (HOG) Atlantic Salmon (Salmo salar) stored from 0 to 15 °C.

Churchill OJ1, Fernandez-Piquer J1, Powell SM1, Tamplin ML2.
Food microbiology.Food Microbiol.2016 Aug;57:144-50. doi: 10.1016/j.fm.2016.02.006. Epub 2016 Feb 26.
Predictive models offer efficient means to manage the quality and safety of highly perishable seafood. Salmon is an increasingly popular seafood, and relies on well managed domestic and international supply chains to minimize growth of spoilage and pathogenic bacteria. While the literature describes
PMID 27052713

Development of a HOG-based real-time PCR method to detect stress response changes in mycotoxigenic moulds.

Rodríguez A1, Medina Á2, Córdoba JJ3, Magan N2.
Food microbiology.Food Microbiol.2016 Aug;57:109-15. doi: 10.1016/j.fm.2016.01.008. Epub 2016 Feb 16.
There is a need to understand the mechanism of adaptation of toxigenic fungal species which are able to colonise highly specialised foods such as cured meats where there is a high osmotic stress due to the presence up to 20-22% NaCl during the ripening process. A new tool able to detect changes in s
PMID 27052709

Photoreactivation and dark repair of environmental E. coli strains following 24 kHz continuous ultrasound and UV-C irradiation.

Kaur J1, Karthikeyan R1, Pillai SD2.
Journal of environmental science and health. Part A, Toxic/hazardous substances & environmental engineering.J Environ Sci Health A Tox Hazard Subst Environ Eng.2016 Apr 6:1-7. [Epub ahead of print]
In this study, effects of 24 kHz continuous ultrasound and UV-C on inactivation and potential repair of environmental E. coli strains were studied through a culture based method and a metabolic activity assay. Three environmental E. coli strains isolated from fecal samples of feral hog and deer and
PMID 27050143

Representation learning for mammography mass lesion classification with convolutional neural networks.

Arevalo J1, González FA2, Ramos-Pollán R3, Oliveira JL4, Guevara Lopez MA5.
Computer methods and programs in biomedicine.Comput Methods Programs Biomed.2016 Apr;127:248-57. doi: 10.1016/j.cmpb.2015.12.014. Epub 2016 Jan 7.
BACKGROUND AND OBJECTIVE: The automatic classification of breast imaging lesions is currently an unsolved problem. This paper describes an innovative representation learning framework for breast cancer diagnosis in mammography that integrates deep learning techniques to automatically learn discrimin
PMID 26826901