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In The Structure of Scientific Revolutions, Thomas Kuhn uses an analogy with the common law to help explain the nature of scientific progress. He says, ‘In science … a paradigm is rarely an object for replication. Instead, like an accepted judicial decision in the common law, it is an object for further articulation and specification under new or more stringent conditions.’ This chapter argues that this analogy is helpful for three reasons. First, it offers a useful—although non-exhaustive—definition of precedent. Secondly, Kuhn’s account helps to explain when and why precedents must be overturned. This is not because precedents are ‘mistaken’ exactly but rather because, as in science, ‘malfunctions’ arise in the process of solving legal problems. Kuhn’s theory explains the two types of change which are necessary for the common law to progress: cumulative and paradigmatic. Thirdly and finally, Kuhn’s analogy shows that, while progress in the law is not linear, this complexity is to the law’s advantage. Sometimes it is necessary, and even helpful, for the common law to move backwards to move forwards.

Full list of authors: Glowacki, Marcin; Collier, Jordan D.; Kazemi-Moridani, Amir; Frank, Bradley; Roberts, Hayley; Darling, Jeremy; Klöckner, Hans-Rainer; Adams, Nathan; Baker, Andrew J.; Bershady, Matthew; Blecher, Tariq; Blyth, Sarah-Louise; Bowler, Rebecca; Catinella, Barbara; Chemin, Laurent; Crawford, Steven M.; Cress, Catherine; Davé, Romeel; Deane, Roger; de Blok, Erwin; Delhaize, Jacinta; Duncan, Kenneth; Elson, Ed; February, Sean; Gawiser, Eric; Hatfield, Peter; Healy, Julia; Henning, Patricia; Hess, Kelley M.; Heywood, Ian; Holwerda, Benne W.; Hoosain, Munira; Hughes, John P.; Hutchens, Zackary L.; Jarvis, Matt; Kannappan, Sheila; Katz, Neal; Kereš, Dušan; Korsaga, Marie; Kraan-Korteweg, Renée C.; Lah, Philip; Lochner, Michelle; Maddox, Natasha; Makhathini, Sphesihle; Meurer, Gerhardt R.; Meyer, Martin; Obreschkow, Danail; Oh, Se-Heon; Oosterloo, Tom; Oppor, Joshua; Pan, Hengxing; Pisano, D. J.; Randriamiarinarivo, Nandrianina; Ravindranath, Swara; Schröder, Anja C.; Skelton, Rosalind; Smirnov, Oleg; Smith, Mathew; Somerville, Rachel S.; Srianand, Raghunathan; Staveley-Smith, Lister; Tanaka, Masayuki; Vaccari, Mattia; van Driel, Wim; Verheijen, Marc; Walter, Fabian; Wu, John F.; Zwaan, Martin A..--This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited., In the local universe, OH megamasers (OHMs) are detected almost exclusively in infrared-luminous galaxies, with a prevalence that increases with IR luminosity, suggesting that they trace gas-rich galaxy mergers. Given the proximity of the rest frequencies of OH and the hyperfine transition of neutral atomic hydrogen (H i), radio surveys to probe the cosmic evolution of H i in galaxies also offer exciting prospects for exploiting OHMs to probe the cosmic history of gas-rich mergers. Using observations for the Looking At the Distant Universe with the MeerKAT Array (LADUMA) deep H i survey, we report the first untargeted detection of an OHM at z > 0.5, LADUMA J033046.20−275518.1 (nicknamed "Nkalakatha"). The host system, WISEA J033046.26−275518.3, is an infrared-luminous radio galaxy whose optical redshift z ≈ 0.52 confirms the MeerKAT emission-line detection as OH at a redshift zOH = 0.5225 ± 0.0001 rather than H i at lower redshift. The detected spectral line has 18.4σ peak significance, a width of 459 ± 59 km s−1, and an integrated luminosity of (6.31 ± 0.18 [statistical] ± 0.31 [systematic]) × 103 L⊙, placing it among the most luminous OHMs known. The galaxy's far-infrared luminosity LFIR = (1.576 ±0.013) × 1012 L⊙ marks it as an ultraluminous infrared galaxy; its ratio of OH and infrared luminosities is similar to those for lower-redshift OHMs. A comparison between optical and OH redshifts offers a slight indication of an OH outflow. This detection represents the first step toward a systematic exploitation of OHMs as a tracer of galaxy growth at high redshifts. © 2022. The Author(s). Published by the American Astronomical Society., M.G. acknowledges support from IDIA and was partially supported by the Australian Government through the Australian Research Council's Discovery Projects funding scheme (DP210102103). A.K.M. and A.J.B. acknowledge support from NSF grant AST-1814421. A.K.M. also thanks the LSSTC Data Science Fellowship Program, which is funded by the LSST Corporation, NSF grant OAC-1829740, the Brinson Foundation, and the Moore Foundation; his participation in the program has been helpful for this work. H.R. and Je.D. acknowledge support from NSF grant AST-1814648; M.B. and J.O. acknowledge support from NSF grant AST-1814682; R.B. acknowledges support from an STFC Ernest Rutherford Fellowship (grant No. ST/T003596/1); Ja.D. and H.P. acknowledge the financial assistance of SARAO; K.M.H. acknowledges funding from the State Agency for Research of the Spanish Ministry of Science, Innovation and Universities through the "Center of Excellence Severo Ochoa" awarded to the Instituto de Astrofísica de Andalucía (SEV-2017-0709); from grant RTI2018-096228-B-C31 (Ministry of Science, Innovation and Universities/State Agency for Research/European Regional Development Funds, European Union); and from the coordination of the participation in SKA-SPAIN, funded by the Ministry of Science and innovation (MICIN); and Z.L.H. and S.K. acknowledge support from NSF grant AST-1814486. Parts of this research were supported by the Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), through project number CE170100013, and by the South African Research Chairs Initiative of the Department of Science and Technology and the NRF.

The accurate estimation of photometric redshifts is crucial to many upcoming galaxy surveys, for example the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). Almost all Rubin extragalactic and cosmological science requires accurate and precise calculation of photometric redshifts; many diverse approaches to this problem are currently in the process of being developed, validated, and tested. In this work, we use the photometric redshift code GPz to examine two realistically complex training set imperfections scenarios for machine learning based photometric redshift calculation: i) where the spectroscopic training set has a very different distribution in colour-magnitude space to the test set, and ii) where the effect of emission line confusion causes a fraction of the training spectroscopic sample to not have the true redshift. By evaluating the sensitivity of GPz to a range of increasingly severe imperfections, with a range of metrics (both of photo-z point estimates as well as posterior probability distribution functions, PDFs), we quantify the degree to which predictions get worse with higher degrees of degradation. In particular we find that there is a substantial drop-off in photo-z quality when line-confusion goes above ~1%, and sample incompleteness below a redshift of 1.5, for an experimental setup using data from the Buzzard Flock synthetic sky catalogues., 12 pages, 8 figures, accepted in PASP

A simple method of calculating the mean line of sight in solid figures is demonstrated and used in conjunction with the Cauchy theorem for the mean chord. This gives a straightforward expression for the enhancement ratio of a uniform optically thick plasma as four times the ratio of the area of the shadow of the plasma in the line of sight to the full surface area. This is used to deduce that the maximum value this enhancement can take is two. The method is used in the analysis of a sphere and cylinder, and shows that the ratio can be calculated exactly for any angle of observation in these cases. This ratio is linked to its applications in the study of opacity effects in the plasma of distant stars, in particular the use of spectral line intensity ratio enhancement observations to make inferences about plasma geometry.

The Arktos vehicle is an amphibious craft system capable of operation in a wide range of Arctic ice conditions and seastates. It is approved as an evacuation system by various regulators, such as the US Coast Guard, and is currently operational in several marine cold regions as an EER system. As part of a reliability investigation of the ARKTOS EER capability, a series of non-Arctic calm condition fully-manned drills was carried out to focus on ergonomic factors. These drills were carried out at a temperate location in the Fraser River Delta, near Vancouver, B.C. A full complement of evacuees was observed and documented throughout a range of evacuation drills, including escape, boarding, securing, and transport to a location outside of a hypothetical hazard zone. Video, time, and expert observer records were made and analyzed subsequently. Two sets of drills were carried out; namely, full-scale evacuation drills and calm open water operation drills. Both sets of drills focused on the ergonomic interfaces of the subjects and the vehicle. This paper describes the observations, presents the statistical results from the data collected, and compares observed results with predicted results of a probabilistic EER simulation computer model. Conclusions and recommendations for reliability improvements are given.