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The Maine Department of Marine Resources (MEDMR) is a state agency tasked with developing, conserving, researching, and promoting commercial and recreational marine fisheries across Maine’s vast coastline. Close collaborations with industry members in each of the 30 or more fisheries that support Maine’s coastal economy are central to MEDMR’s efforts to address this suite of tasks. Here we reflect on recent decades of MEDMR's work and demonstrate how MEDMR fisheries research programmes are preparing for an uncertain future through the lens of three broadly applicable climate-driven challenges: (1) a rapidly changing marine ecosystem; (2) recommendations driven by state and federal climate initiatives; and (3) the need to share institutional knowledge with a new generation of marine resource scientists. We do this by highlighting our scientific and co-management approach to coastal Maine fisheries that have prospered, declined, or followed a unique trend over the last 25+ years. We use these examples to illustrate our lessons learned when studying a diverse array of fisheries, highlight the importance of collaborations with academia and the commercial fishing industry, and share our recommendations to marine resource scientists for addressing the climate-driven challenges that motivated this work.

 

Middleware is required to support and interface multi-modal Dynamic Data Driven Application Systems (DDDAS) with back-end and other computing facilities. Middleware is also needed to support distributed simulations and emulations needed in earlier phases of system development. This work describes the Green Runtime Infrastructure (G-RTI), an energy-efficient client server based middleware developed to support distributed DDDAS simulation, emulation and deployment. G-RTI eases and accelerates the development and testing of multi-modal studies, testbeds and DDDAS systems. It serves as a platform for research in energy reduction techniques for middleware services. The services implemented by G-RTI are described and results of benchmarking studies are reported. Its application is demonstrated through a use-case for an end-to-end implementation of a connected vehicle application. G-RTI is open source. 

We presentosprey3.0, a new and greatly improved release of theospreyprotein design software.Osprey3.0 features a convenient new Python interface, which greatly improves its ease of use. It is over two orders of magnitude faster than previous versions ofospreywhen running the same algorithms on the same hardware. Moreover,osprey3.0 includes several new algorithms, which introduce substantial speedups as well as improved biophysical modeling. It also includes GPU support, which provides an additional speedup of over an order of magnitude. Like previous versions ofosprey,osprey3.0 offers a unique package of advantages over other design software, including provable design algorithms that account for continuous flexibility during design and model conformational entropy. Finally, we show here empirically thatosprey3.0 accurately predicts the effect of mutations on protein–protein binding.Osprey3.0 is available athttp://www.cs.duke.edu/donaldlab/osprey.phpas free and open‐source software. © 2018 Wiley Periodicals, Inc.