Volume I. Introduction to DUNE

The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay—these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. This TDR is intended to justify the technical choices for the far detector that flow down from the high-level physics goals through requirements at all levels of the Project. Volume I contains an executive summary that introduces the DUNE science program, the far detector and the strategy for its modular designs, and the organization and management of the Project. The remainder of Volume I provides more detail on the science program that drives the choice of detector technologies and on the technologies themselves. It also introduces the designs for the DUNE near detector and the DUNE computing model, for which DUNE is planning design reports. Volume II of this TDR describes DUNE\u27s physics program in detail. Volume III describes the technical coordination required for the far detector design, construction, installation, and integration, and its organizational structure. Volume IV describes the single-phase far detector technology. A planned Volume V will describe the dual-phase technology

Evolving the narrative for protecting a rapidly changing ocean, post‐COVID‐19

The ocean is the linchpin supporting life on Earth, but it is in declining health due to an increasing footprint of human use and climate change. Despite notable successes in helping to protect the ocean, the scale of actions is simply not now meeting the overriding scale and nature of the ocean's problems that confront us. Moving into a post-COVID-19 world, new policy decisions will need to be made. Some, especially those developed prior to the pandemic, will require changes to their trajectories; others will emerge as a response to this global event. Reconnecting with nature, and specifically with the ocean, will take more than good intent and wishful thinking. Words, and how we express our connection to the ocean, clearly matter now more than ever before. The evolution of the ocean narrative, aimed at preserving and expanding options and opportunities for future generations and a healthier planet, is articulated around six themes: (1) all life is dependent on the ocean; (2) by harming the ocean, we harm ourselves; (3) by protecting the ocean, we protect ourselves; (4) humans, the ocean, biodiversity, and climate are inextricably linked; (5) ocean and climate action must be undertaken together; and (6) reversing ocean change needs action now. This narrative adopts a ‘One Health’ approach to protecting the ocean, addressing the whole Earth ocean system for better and more equitable social, cultural, economic, and environmental outcomes at its core. Speaking with one voice through a narrative that captures the latest science, concerns, and linkages to humanity is a precondition to action, by elevating humankind's understanding of our relationship with ‘planet Ocean’ and why it needs to become a central theme to everyone's lives. We have only one ocean, we must protect it, now. There is no ‘Ocean B’

Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

A growing number of artificial intelligence (AI)-based clinical decision support systems are showing promising performance in preclinical, in silico, evaluation, but few have yet demonstrated real benefit to patient care. Early stage clinical evaluation is important to assess an AI system’s actual clinical performance at small scale, ensure its safety, evaluate the human factors surrounding its use, and pave the way to further large scale trials. However, the reporting of these early studies remains inadequate. The present statement provides a multistakeholder, consensus-based reporting guideline for the Developmental and Exploratory Clinical Investigations of DEcision support systems driven by Artificial Intelligence (DECIDE-AI). We conducted a two round, modified Delphi process to collect and analyse expert opinion on the reporting of early clinical evaluation of AI systems. Experts were recruited from 20 predefined stakeholder categories. The final composition and wording of the guideline was determined at a virtual consensus meeting. The checklist and the Explanation & Elaboration (E&E) sections were refined based on feedback from a qualitative evaluation process. 123 experts participated in the first round of Delphi, 138 in the second, 16 in the consensus meeting, and 16 in the qualitative evaluation. The DECIDE-AI reporting guideline comprises 17 AI specific reporting items (made of 28 subitems) and 10 generic reporting items, with an E&E paragraph provided for each. Through consultation and consensus with a range of stakeholders, we have developed a guideline comprising key items that should be reported in early stage clinical studies of AI-based decision support systems in healthcare. By providing an actionable checklist of minimal reporting items, the DECIDE-AI guideline will facilitate the appraisal of these studies and replicability of their findings

Deep Underground Neutrino Experiment (DUNE), far detector technical design report, volume III: DUNE far detector technical coordination

The preponderance of matter over antimatter in the early universe, the dynamics of the supernovae that produced the heavy elements necessary for life, and whether protons eventually decay—these mysteries at the forefront of particle physics and astrophysics are key to understanding the early evolution of our universe, its current state, and its eventual fate. The Deep Underground Neutrino Experiment (DUNE) is an international world-class experiment dedicated to addressing these questions as it searches for leptonic charge-parity symmetry violation, stands ready to capture supernova neutrino bursts, and seeks to observe nucleon decay as a signature of a grand unified theory underlying the standard model. The DUNE far detector technical design report (TDR) describes the DUNE physics program and the technical designs of the single- and dual-phase DUNE liquid argon TPC far detector modules. Volume III of this TDR describes how the activities required to design, construct, fabricate, install, and commission the DUNE far detector modules are organized and managed. This volume details the organizational structures that will carry out and/or oversee the planned far detector activities safely, successfully, on time, and on budget. It presents overviews of the facilities, supporting infrastructure, and detectors for context, and it outlines the project-related functions and methodologies used by the DUNE technical coordination organization, focusing on the areas of integration engineering, technical reviews, quality assurance and control, and safety oversight. Because of its more advanced stage of development, functional examples presented in this volume focus primarily on the single-phase (SP) detector module

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Using photographs to study animal social cognition and behaviour: Do capuchins' responses to photos reflect reality?

© 2015 Elsevier B.V. Behavioural responses to photos are often used to infer what animals understand about their social environment, but are rarely validated against the same stimuli in real life. If subjects' responses to photos do not reflect responses to the same live stimuli, it is difficult to conclude what happens in reality based on photo responses alone. We compared capuchins' responses to photos versus live stimuli in an identical scenario within research cubicles. Subjects had the opportunity to approach food placed in front of an alpha group member and, in a separate condition, photos depicting the same individual. Subjects' latencies to approach food when placed in front of the real alpha negatively correlated with time subjects spent in close proximity to the alpha in their main enclosure. We therefore predicted subjects' latencies to approach food in the presence of photos would positively correlate with their latencies to approach food in the presence of the real alpha inside the cubicles, but negatively correlate with time they spent in proximity to the alpha in their enclosure. Neither prediction was supported. While not necessarily surprising, we explain why these results should be an important reminder that care is needed when interpreting results from photo studies

Disentangling the role of photosynthesis and stomatal conductance on rising forest water-use efficiency

Multiple lines of evidence suggest that plant water-use efficiency (WUE)-the ratio of carbon assimilation to water loss-has increased in recent decades. Although rising atmospheric CO2 has been proposed as the principal cause, the underlying physiological mechanisms are still being debated, and implications for the global water cycle remain uncertain. Here, we addressed this gap using 30-y tree ring records of carbon and oxygen isotope measurements and basal area increment from 12 species in 8 North American mature temperate forests. Our goal was to separate the contributions of enhanced photosynthesis and reduced stomatal conductance to WUE trends and to assess consistency between multiple commonly used methods for estimating WUE. Our results show that tree ring-derived estimates of increases in WUE are consistent with estimates from atmospheric measurements and predictions based on an optimal balancing of carbon gains and water costs, but are lower than those based on ecosystem scale flux observations. Although both physiological mechanisms contributed to rising WUE, enhanced photosynthesis was widespread, while reductions in stomatal conductance were modest and restricted to species that experienced moisture limitations. This finding challenges the hypothesis that rising WUE in forests is primarily the result of widespread, CO2-induced reductions in stomatal conductance