Climate change considerations are fundamental to management of deep‐sea resource extraction

Climate change manifestation in the ocean, through warming, oxygen loss, increasing acidification, and changing particulate organic carbon flux (one metric of altered food supply), is projected to affect most deep‐ocean ecosystems concomitantly with increasing direct human disturbance. Climate drivers will alter deep‐sea biodiversity and associated ecosystem services, and may interact with disturbance from resource extraction activities or even climate geoengineering. We suggest that to ensure the effective management of increasing use of the deep ocean (e.g., for bottom fishing, oil and gas extraction, and deep‐seabed mining), environmental management and developing regulations must consider climate change. Strategic planning, impact assessment and monitoring, spatial management, application of the precautionary approach, and full‐cost accounting of extraction activities should embrace climate consciousness. Coupled climate and biological modeling approaches applied in the water and on the seafloor can help accomplish this goal. For example, Earth‐System Model projections of climate‐change parameters at the seafloor reveal heterogeneity in projected climate hazard and time of emergence (beyond natural variability) in regions targeted for deep‐seabed mining. Models that combine climate‐induced changes in ocean circulation with particle tracking predict altered transport of early life stages (larvae) under climate change. Habitat suitability models can help assess the consequences of altered larval dispersal, predict climate refugia, and identify vulnerable regions for multiple species under climate change. Engaging the deep observing community can support the necessary data provisioning to mainstream climate into the development of environmental management plans. To illustrate this approach, we focus on deep‐seabed mining and the International Seabed Authority, whose mandates include regulation of all mineral‐related activities in international waters and protecting the marine environment from the harmful effects of mining. However, achieving deep‐ocean sustainability under the UN Sustainable Development Goals will require integration of climate consideration across all policy sectors.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2020 The Authors. Global Change Biology published by John Wiley & Sons Lt

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Measurement of antiproton production from antihyperon decays in p He collisions at √sNN = 110 GeV

The interpretation of cosmic antiproton flux measurements from space-borne experiments is currently limited by the knowledge of the antiproton production cross-section in collisions between primary cosmic rays and the interstellar medium. Using collisions of protons with an energy of 6.5TeV incident on helium nuclei at rest in the proximity of the interaction region of the LHCb experiment, the ratio of antiprotons originating from antihyperon decays to prompt production is measured for antiproton momenta between 12 and 110GeV. The dominant antihyperon contribution, namely Λ¯→p¯π+ decays from promptly produced Λ¯ particles, is also exclusively measured. The results complement the measurement of prompt antiproton production obtained from the same data sample. At the energy scale of this measurement, the antihyperon contributions to antiproton production are observed to be significantly larger than predictions of commonly used hadronic production models

Direct CP violation in charmless three-body decays of B± mesons

Measurements of C P asymmetries in charmless three-body decays of B ± mesons are reported using proton-proton collision data collected by the LHCb detector, corresponding to an integrated luminosity of 5.9     fb − 1 . The previously observed C P asymmetry in B ± → π ± K + K − decays is confirmed, and C P asymmetries are observed with a significance of more than five standard deviations in the B ± → π ± π + π − and B ± → K ± K + K − decays, while the C P asymmetry of B ± → K ± π + π − decays is confirmed to be compatible with zero. The distributions of these asymmetries are also studied as a function of the three-body phase space and suggest contributions from rescattering and resonance interference processes. An indication of the presence of the decays B ± → π ± χ c 0 ( 1 P ) in both B ± → π ± π + π − and B ± → π ± K + K − decays is observed, as is C P violation involving these amplitudes

Measurement of J/ψ -pair production in pp collisions at √s = 13 TeV and study of gluon transverse-momentum dependent PDFs

The production cross-section of J/ψ pairs in proton-proton collisions at a centre-of-mass energy of √s = 13 TeV is measured using a data sample corresponding to an integrated luminosity of 4.2 fb−1 collected by the LHCb experiment. The measurement is performed with both J/ψ mesons in the transverse momentum range 0 &lt; pT&lt; 14 GeV/c and rapidity range 2.0 &lt; y &lt; 4.5. The cross-section of this process is measured to be 16.36 ± 0.28 (stat) ± 0.88 (syst) nb. The contributions from single-parton scattering and double-parton scattering are separated based on the dependence of the cross-section on the absolute rapidity difference ∆y between the two J/ψ mesons. The effective cross-section of double-parton scattering is measured to be σeff = 13.1 ± 1.8 (stat) ± 2.3 (syst) mb. The distribution of the azimuthal angle ϕCS of one of the J/ψ mesons in the Collins-Soper frame and the pT-spectrum of the J/ψ pairs are also measured for the study of the gluon transverse-momentum dependent distributions inside protons. The extracted values of ⟨cos 2ϕCS⟩ and ⟨cos 4ϕCS⟩ are consistent with zero, but the presence of azimuthal asymmetry at a few percent level is allowed

Fully automated image segmentation for benthic resource assessment of poly-metallic nodules

Highlights • The proposed method automatically assesses the abundance of poly-metallic nodules on the seafloor. • No manually created feature reference set is required. • Large collections of benthic images from a range of acquisition gear can be analysed efficiently. Abstract Underwater image analysis is a new field for computational pattern recognition. In academia as well as in the industry, it is more and more common to use camera-equipped stationary landers, autonomous underwater vehicles, ocean floor observatory systems or remotely operated vehicles for image based monitoring and exploration. The resulting image collections create a bottleneck for manual data interpretation owing to their size. In this paper, the problem of measuring size and abundance of poly-metallic nodules in benthic images is considered. A foreground/background separation (i.e. separating the nodules from the surrounding sediment) is required to determine the targeted quantities. Poly-metallic nodules are compact (convex), but vary in size and appear as composites with different visual features (color, texture, etc.). Methods for automating nodule segmentation have so far relied on manual training data. However, a hand-drawn, ground-truthed segmentation of nodules and sediment is difficult (or even impossible) to achieve for a sufficient number of images. The new ES4C algorithm (Evolutionary tuned Segmentation using Cluster Co-occurrence and a Convexity Criterion) is presented that can be applied to a segmentation task without a reference ground truth. First, a learning vector quantization groups the visual features in the images into clusters. Secondly, a segmentation function is constructed by assigning the clusters to classes automatically according to defined heuristics. Using evolutionary algorithms, a quality criterion is maximized to assign cluster prototypes to classes. This criterion integrates the morphological compactness of the nodules as well as feature similarity in different parts of nodules. To assess its applicability, the ES4C algorithm is tested with two real-world data sets. For one of these data sets, a reference gold standard is available and we report a sensitivity of 0.88 and a specificity of 0.65. Our results show that the applied heuristics, which combine patterns in the feature domain with patterns in the spatial domain, lead to good segmentation results and allow full automation of the resource-abundance assessment for benthic poly-metallic nodules

Insights from the management of offshore energy resources: Toward an ecosystem-services based management approach for deep-ocean industries

The deep ocean comprises complex ecosystems made up of numerous community and habitat types that provide multiple services that benefit humans. As the industrialization of the deep sea proceeds, a standardized and robust set of methods and metrics need to be developed to monitor the baseline conditions and any anthropogenic and climate change-related impacts on biodiversity, ecosystem function, and ecosystem services. Here, we review what we have learned from studies involving offshore-energy industries, including state-of-the-art technologies and strategies for obtaining reliable metrics of deep-sea biodiversity and ecosystem function. An approach that includes the detection and monitoring of ecosystem services, with open access to baseline data from multiple sectors, can help to improve our global capacity for the management of the deep ocean