IOCCG Ocean Optics and Biogeochemistry Protocols for Satellite Ocean Colour Sensor Validation Volume 7.0. Aquatic Primary Productivity Field Protocols for Satellite Validation and Model Synthesis. (IOCCG Protocols Series, Volume 7.0). DOI: http://dx.doi.org/10.25607/OBP-1835

In 2018, a working group sponsored by the NASA Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) project, in conjunction with the International Ocean Colour Coordinating Group (IOCCG), European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), and Japan Aerospace Exploration Agency (JAXA), was assembled with the aim to develop community consensus on multiple methods for measuring aquatic primary productivity used for satellite validation and model synthesis. A workshop to commence the working group efforts was held December 5–7, 2018, at the University Space Research Association headquarters in Columbia, MD, USA, bringing together 26 active researchers from 16 institutions. In this document, we discuss and develop the workshop findings as they pertain to primary productivity measurements, including the essential issues, nuances, definitions, scales, uncertainties, and ultimately best practices for data collection across multiple methodologies

Model-independent measurement of t\boldsymbol{t}-channel single top quark production in ppˉ\boldsymbol{p\bar{p}} collisions at s=1.96\boldsymbol{\sqrt{s}=1.96} TeV

We present a model-independent measurement of $t$-channel electroweak production of single top quarks in \ppbar collisions at $\sqrt{s}=1.96\;\rm TeV$. Using $5.4\;\rm fb^{-1}$ of integrated luminosity collected by the D0 detector at the Fermilab Tevatron Collider, and selecting events containing an isolated electron or muon, missing transverse energy and one or two jets originating from the fragmentation of $b$ quarks, we measure a cross section \sigma({\ppbar}{\rargap}tqb+X) = 2.90 \pm 0.59\;\rm (stat+syst)\; pb for a top quark mass of $172.5\;\rm GeV$. The probability of the background to fluctuate and produce a signal as large as the one observed is $1.6\times10^{-8}$, corresponding to a significance of 5.5 standard deviations.Comment: 8 pages, 4 figures, submitted to Phys. Lett.

Evolving A Single Scalable Controller For An Octopus Arm With A Variable Number Of Segments

While traditional approaches to machine learning are sensitive to high-dimensional state and action spaces, this paper demonstrates how an indirectly encoded neurocontroller for a simulated octopus arm leverages regularities and domain geometry to capture underlying motion principles and sidestep the superficial trap of dimensionality. In particular, controllers are evolved for arms with 8, 10, 12, 14, and 16 segments in equivalent time. Furthermore, when transferred without further training, solutions evolved on smaller arms retain the fundamental motion model because they simply extend the general kinematic concepts discovered at the original size. Thus this work demonstrates that dimensionality can be a false measure of domain complexity and that indirect encoding makes it possible to shift the focus to the underlying conceptual challenge. © 2010 Springer-Verlag