4th International Conference on Medical Imaging with Deep Learning Jul 07, 2021 - Jul 09, 2021 — Virtual Meeting (online)
Medical Image Understanding and Analysis Conference 2021 Jul 12, 2021 - Jul 14, 2021 — Virtual Meeting (online)
Medical Imaging Convention [rescheduled] Sep 15, 2021 - Sep 16, 2021 — National Exhibition Centre, Birmingham, England
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eLearning

SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.


Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

Managing harvesting to minimize the impact of epidemics on wild fish stocks

Author(s): Alexander G. Murray

Abstract:
Epidemic diseases inflict substantial damage to stocks of harvested species. Epidemic waves can be predictable away from their origin. I use a classical epidemiology model to investigate the interaction of harvesting strategy with an epidemic. The effect of reducing populations by harvesting before the epidemic depends upon the nature of the epidemic's survivors. If these have recovered following infection, then pre-epidemic fishing optimizes the harvest, but reduces long-term survival. However, if these survivors avoided infection, then increased pre-epidemic fishing effort can increase post-epidemic populations; survival is maximized by reducing the pre-epidemic population to the threshold required to propagate infection. Post-epidemic harvesting provides poor returns and damages stocks. Optimal stock management strategy in the face of a predicted epidemic depends upon balancing harvesting and conservation of stocks-complimentary or antagonistic goals, depending on the nature of the epidemic.

Full version: Available here

Click the link to go to an external website with the full version of the paper


ISBN: 0890-8575 (ISSN print)
Publication Year: 2004
Periodical: Natural Resource Modeling
Periodical Number: 2
Volume: 17
Pages: 103-121
Author Address: