PICES Press, Vol. 21, No. 1, Winter 2013

•2012 PICES Science: A Note from the Science Board Chairman (pp. 1-6) ◾2012 PICES Awards (pp. 7-9) ◾GLOBEC/PICES/ICES ECOFOR Workshop (pp. 10-15) ◾ICES/PICES Symposium on “Forage Fish Interactions” (pp. 16-18) ◾The Yeosu Declaration, the Yeosu Declaration Forum and the Yeosu Project (pp. 19-23) ◾2013 PICES Calendar (p. 23) ◾Why Do We Need Human Dimensions for the FUTURE Program? (pp. 24-25) ◾New PICES MAFF-Sponsored Project on “Marine Ecosystem Health and Human Well-Being” (pp. 26-28) ◾The Bering Sea: Current Status and Recent Trends (pp. 29-31) ◾Continuing Cool in the Northeast Pacific Ocean (pp. 32, 35) ◾The State of the Western North Pacific in the First Half of 2012 (pp. 33-35) ◾New Leadership in PICES (pp. 36-39

Solar System Exploration Research Virtual Institute: Year Three Annual Report 2016

NASA's Solar System Exploration Research Virtual Institute (SSERVI) is pleased to present the 2016 Annual Report. Each year brings new scientific discoveries, technological breakthroughs, and collaborations. The integration of basic research and development, industry and academic partnerships, plus the leveraging of existing technologies, has further opened a scientific window into human exploration. SSERVI sponsorship by the NASA Science Mission Directorate (SMD) and Human Exploration and Operations Mission Directorate (HEOMD) continues to enable the exchange of insights between the human exploration and space science communities, paving a clearer path for future space exploration. SSERVI provides a unique environment for scientists and engineers to interact within multidisciplinary research teams. As a virtual institute, the best teaming arrangements can be made irrespective of the geographical location of individuals or laboratory facilities. The interdisciplinary science that ensues from virtual and in-person interactions, both within the teams and across team lines, provides answers to questions that many times cannot be foreseen. Much of this research would not be accomplished except for the catalyzing, collaborative environment enabled by SSERVI. The SSERVI Central Office, located at NASA Ames Research Center in Silicon Valley, California, provides the leadership, guidance and technical support that steers the virtual institute. At the start of 2016, our institute had nine U.S. teams, each mid-way through their five-year funding cycle, plus nine international partnerships. However, by the end of the year we were well into the selection of four new domestic teams, selected through NASA's Cooperative Agreement Notice (CAN) process, and a new international partnership. Understanding that human and robotic exploration is most successful as an international endeavor, international partnerships collaborate with SSERVI domestic teams on a no-exchange of funds basis, but they bring a richness to the institute that is priceless. The international partner teams interact with the domestic teams in a number of ways, including sharing students, scientific insights, and access to facilities. We are proud to introduce our newest partnership with the Astrophysics and Planetology Research Institute (IRAP) in Toulouse, France. In 2016, Principal Investigator Dr. Patrick Pinet assembled a group of French researchers who will contribute scientific and technological expertise related to SSERVI research. SSERVI's domestic teams compete for five-year funding opportunities through proposals to a NASA CAN every few years. Having overlapping proposal selection cycles allows SSERVI to be more responsive to any change in direction NASA might experience, while providing operational continuity for the institute. Allowing new teams to blend with the more seasoned teams preserves corporate memory and expands the realm of collaborative possibilities. A key component of SSERVI's mission is to grow and maintain an integrated research community focused on questions related to the Moon, Near-Earth asteroids, and the moons of Mars. The strong community response to CAN-2 demonstrated the health of that effort. NASA Headquarters conducted the peer-review of 22 proposals early in 2017 and, based on recommendations from the SSERVI Central Office and NASA SSERVI program officers, the NASA selecting officials determined the new teams in the spring of 2017. We are pleased to welcome the CAN-2 teams into the institute, and look forward to the collaborations that will develop with the current teams. The new teams are: The Network for Exploration and Space Science (NESS) team (Principal Investigator (PI) Prof. Jack Burns/U. Colorado); the Exploration Science Pathfinder Research for Enhancing Solar System Observations (ESPRESSO) team (PI Dr. Alex Parker/Southwest Research Institute); the Toolbox for Research and Exploration (TREX) team (PI Dr. Amanda Hendrix/ Planetary Science Institute); and the Radiation Effects on Volatiles and Exploration of Asteroids & Lunar Surfaces (REVEALS) team (PI Prof. Thomas Orlando/ Georgia Institute of Technology). In this report, you will find an overview of the 2016 leadership activities of the SSERVI Central Office, reports prepared by the U.S. teams from CAN-1, and achievements from several of the SSERVI international partners. Reflecting on the past year's discoveries and advancements serves as a potent reminder that there is still a great deal to learn about NASA's target destinations. Innovation in the way we access, sample, measure, visualize, and assess our target destinations is needed for further discovery. At the same time, let us celebrate how far we have come, and strongly encourage a new generation that will make the most of future opportunities

Advances in Artificial Intelligence: Models, Optimization, and Machine Learning

The present book contains all the articles accepted and published in the Special Issue “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning” of the MDPI Mathematics journal, which covers a wide range of topics connected to the theory and applications of artificial intelligence and its subfields. These topics include, among others, deep learning and classic machine learning algorithms, neural modelling, architectures and learning algorithms, biologically inspired optimization algorithms, algorithms for autonomous driving, probabilistic models and Bayesian reasoning, intelligent agents and multiagent systems. We hope that the scientific results presented in this book will serve as valuable sources of documentation and inspiration for anyone willing to pursue research in artificial intelligence, machine learning and their widespread applications