HEADING INCIDENCE AND CHARACTERISTICS IN ELITE WOMEN’S FOOTBALL OVER THE 2020/2021 SEASON

The purpose of the study was to analyse the magnitude of head impact incidence and heading characteristics in elite women’s football across a season. Football players (matches n=25, training n=18) had their headers and head impacts quantified and characterised for the 2020/2021 season. Video recordings from a single elevated camera on the halfway line was used to analyse for 22 matches and 98 training sessions. Overall, 5063 headers and 9 non-ball to head impacts were collected and analysed. This study shows more headers occurred in training than matches for the team of interest across the season (training, 2976; matches, 974). However, the nature of the headers was more submaximal in training than matches, the rate of headers was lower (training, 15.9 headers per hour; matches 29.5 headers per hour), and non-ball to head impacts were much lower (training, 0; matches 9). The longitudinal study presents differences between headers and head impacts in matches and training and provides novel data to further develop our understanding of heading in women’s football

The evolution of inverted magnetic fields through the inner heliosphere

Local inversions are often observed in the heliospheric magnetic field (HMF), but their origins and evolution are not yet fully understood.Parker Solar Probe has recently observed rapid, Alfvénic, HMF inversions in the inner heliosphere, known as ‘switchbacks’, which have been interpreted as the possible remnants of coronal jets. It has also been suggested that inverted HMF may be produced by near-Sun interchange reconnection; a key process in mechanisms proposed for slow solar wind release. These cases suggest that the source of inverted HMF is near the Sun, and it follows that these inversions would gradually decay and straighten as they propagate out through the heliosphere. Alternatively, HMF inversions could form during solar wind transit, through phenomena such velocity shears, draping over ejecta, or waves and turbulence. Such processes are expected to lead to a qualitatively radial evolution of inverted HMF structures. Using Helios measurements spanning 0.3–1 AU, we examine the occurrence rate of inverted HMF, as well as other magnetic field morphologies, as a function of radial distance r, and find that it continually increases. This trend may be explained by inverted HMF observed between 0.3–1 AU being primarily driven by one or more of the above in-transit processes, rather than created at the Sun. We make suggestions as to the relative importance of these different processes based on the evolution of the magnetic field properties associated with inverted HMF. We also explore alternative explanations outside of our suggested driving processes which may lead to the observed trend

Electrochemical reduction of CO2 with an oxide-derived lead nano-coralline electrode in dimcarb

Electroreduction of CO2 in the distillable ionic liquid dimethylammonium dimethylcarbamate (dimcarb) has been investigated with an oxide‐derived lead (od‐Pb) electrode. Compared with unmodified polycrystalline Pb, where H2 is the dominant electrolysis product, od‐Pb possesses impressive catalytic properties for the reduction of CO2 in dimcarb (mixing molar ratio of CO2 and dimethylamine (DMA) >1 : 1.8), with faradaic efficiencies for the generation of H2, CO, and [HCOO]− of approximately 15, 10, and 75 %, respectively. These efficiencies are independent of the applied potential in the range of −1.34 to −3.34 V vs. Cc0/+ (where Cc+=cobaltocenium). Thorough analysis of the properties of od‐Pb, we demonstrate that its intrinsically high catalytic activity towards CO2 reduction compared to bulk Pb is attributable to an increased surface roughness and greater surface area (ca. 10 times higher), rather than the existence of residual metal oxides that are known to suppress the hydrogen evolution reaction, preferred crystal orientation, or the existence of metastable active sites

On the origins and timescales of geoeffective IMF

Southward Interplanetary Magnetic Field (IMF) in the Geocentric Solar Magnetospheric (GSM) reference frame is the key element that controls the level of space-weather disturbance in Earth’s magnetosphere, ionosphere and thermosphere. We discuss the relation of this geoeffective IMF component to the IMF in the Geocentric Solar Ecliptic (GSE) frame and, using the almost continuous interplanetary data for 1996-2015 (inclusive), we show that large geomagnetic storms are always associated with strong southward, out-of-ecliptic field in the GSE frame: dipole tilt effects, that cause the difference between the southward field in the GSM and GSE frames, generally make only a minor contribution to these strongest storms. The time-of-day/time-of-year response patterns of geomagnetic indices and the optimum solar wind coupling function are both influenced by the timescale of the index response. We also study the occurrence spectrum of large out-of-ecliptic field and show that for one-hour averages it is, surprisingly, almost identical in ICMEs (Interplanetary Coronal Mass Ejections), around CIRs/SIRs (Corotating and Stream Interaction Regions) and in the “quiet” solar wind (which is shown to be consistent with the effect of weak SIRs). However, differences emerge when the timescale over which the field remains southward is considered: for longer averaging timescales the spectrum is broader inside ICMEs, showing that these events generate longer intervals of strongly southward average IMF and consequently stronger geomagnetic storms. The behavior of out-of-ecliptic field with timescale is shown to be very similar to that of deviations from the predicted Parker spiral orientation, suggesting the two share common origins

Clean subglacial access:Prospects for future deep hot-water drilling

Accessing and sampling subglacial environments deep beneath the Antarctic Ice Sheet presents several challenges to existing drilling technologies. With over half of the ice sheet believed to be resting on a wet bed, drilling down to this environment must conform to international agreements on environmental stewardship and protection, making clean hot-water drilling the most viable option. Such a drill, and its water recovery system, must be capable of accessing significantly greater ice depths than previous hot-water drills, and remain fully operational after connecting with the basal hydrological system. The Subglacial Lake Ellsworth (SLE) project developed a comprehensive plan for deep (greater than 3000 m) subglacial lake research, involving the design and development of a clean deep-ice hot-water drill. However, during fieldwork in December 2012 drilling was halted after a succession of equipment issues culminated in a failure to link with a subsurface cavity and abandonment of the access holes. The lessons learned from this experience are presented here. Combining knowledge gained from these lessons with experience from other hot-water drilling programmes, and recent field testing, we describe the most viable technical options and operational procedures for future clean entry into SLE and other deep subglacial access targets.</p

The development of a space climatology: 3. Models of the evolution of distributions of space weather variables with timescale

We study how the probability distribution functions of power input to the magnetosphere Pα and of the geomagnetic ap and Dst indices vary with averaging timescale, , between 3 hours and 1 year. From this we develop and present algorithms to empirically model the distributions for a given and a given annual mean value. We show that lognormal distributions work well for ap, but because of the spread of Dst for low activity conditions, the optimum formulation for Dst leads to distributions better described by something like the Weibull formulation. Annual means can be estimated using telescope observations of sunspots and modelling, and so this allows the distributions to be estimated at any given between 3 hour and 1 year for any of the past 400 years, which is another important step towards a useful space weather climatology. The algorithms apply to the core of the distributions and can be used to predict the occurrence rate of “large” events (in the top 5% of activity levels): they may contain some, albeit limited, information relevant to characterizing the much rarer “superstorm” events with extreme value statistics. The algorithm for the Dst index is the more complex one because, unlike ap, Dst can take on either sign and future improvements to it are suggested

The development of a space climatology: 1. solar-wind magnetosphere coupling as a function of timescale and the effect of data gaps

Different terrestrial space weather indicators (such as geomagnetic indices, transpolar voltage, and ring current particle content) depend on different “coupling functions” (combinations of near-Earth solar wind parameters) and previous studies also reported a dependence on the averaging timescale, {\tau}. We study the relationships of the am and SME geomagnetic indices to the power input into the magnetosphere P_{\alpha}, estimated using the optimum coupling exponent {\alpha} for a range of {\tau} between 1 min and 1 year. The effect of missing data is investigated by introducing synthetic gaps into near-continuous data and the best method for dealing with them when deriving the coupling function, is formally defined. Using P_{\alpha}, we show that gaps in data recorded before 1995 have introduced considerable errors into coupling functions. From the near-continuous solar wind data for 1996-2016, we find {\alpha} = 0.44 plus/minus 0.02 and no significant evidence that {\alpha} depends on {\tau}, yielding P_{\alpha} = B^0.88 Vsw^1.90 (mswNsw)^0.23 sin4({\theta}/2), where B is the Interplanetary Magnetic Field (IMF), Nsw the solar wind number density, msw its mean ion mass, Vsw its velocity and {\theta} is the IMF clock angle in the Geocentric Solar Magnetospheric reference frame. Values of P_{\alpha} that are accurate to within plus/minus 5% for 1996-2016 have an availability of 83.8% and the correlation between P_{\alpha} and am for these data is shown to be 0.990 (between 0.972 and 0.997 at the 2{\sigma} uncertainty level), 0.897 plus/minus 0.004, and 0.790 plus/minus 0.03, for {\tau} of 1 year, 1 day and 3 hours, respectively, and that between P_{alpha} and SME at {\tau} of 1 min. is 0.7046 plus/minus 0.0004

Past Antarctic ice sheet dynamics (PAIS) and implications for future sea-level change

Coauthors from the PAIS community Aisling M. Dolan, University of Leeds, Leeds, UK Alan K. Cooper, U.S. Geological Survey Emeritus, Menlo Park, USA Alessandra Venuti, Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy Amy Leventer, Colgate University, Hamilton, NY, USA Andrea Bergamasco, C.N.R. (National Research Council) ISMAR, Venice, Italy Carolina Acosta Hospitaleche, CONICET, División Paleontología Vertebrados, Museo de La Plata (Facultad de Ciencias Naturales y Museo, UNLP) La Plata, Argentina Carolina Acosta Hospitaleche, CONICET – División Paleontología Vertebrados, Museo de La Plata, Facultad de Ciencias Naturales y Museo, UNLP; La Plata, Argentina Catalina Gebhardt, Alfred Wegener Institute Helmholtz Centre of Polar and Marine Research, Bremerhaven, Germany Christine S. Siddoway, Colorado College, Colorado Springs, USA Christopher C. Sorlien, Earth Research Institute, University of California, Santa Barbara, Santa Barbara, California, USA David Harwood, University of Nebraska-Lincoln, Lincoln, Nebraska, USA David Pollard, Pennsylvania State University, University Park, Pennsylvania, USA David J. Wilson, Department of Earth Sciences, University College London, London, UK Denise K. Kulhanek, Texas A&M University, College Station, TX, United States Dominic A. Hodgson, British Antarctic Survey, Cambridge, UK Edward G.W. Gasson, University of Bristol, UK Fausto Ferraccioli, NERC/British Antarctic Survey, Cambridge, UK Fernando Bohoyo, Instituto Geológico y Minero de España, Madrid, Spain Francesca Battaglia, University of Venice Cá Foscari, Italy Frank O. Nitsche, Lamont-Doherty Earth Observatory of Columbia University, Palisades, USA Georgia R. Grant, GNS Science Wellington, New Zealand Gerhard Kuhn, Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany Guy J.G. Paxman, Lamont-Doherty Earth Observatory, Columbia University, New York, USA Ian D. Goodwin, Climate Change Research Centre, University of New South Wales, Sydney, Australia Isabel Sauermilch, University of Tasmania, Institute for Marine and Antarctic Studies, Australia Jamey Stutz, Antarctic Research Centre at Victoria University of Wellington, New Zealand Jan Sverre Laberg, Department of Geosciences, UiT The Arctic University of Norway, NO-9037 Tromsø, Norway Javier N. Gelfo, CONICET – UNLP, División Paleontología Vertebrados, Museo de La Plata, Argentina Johann P. Klages, Alfred Wegener Institute Helmholtz Center for Polar and Marine Research, Bremerhaven, Germany Julia S. Wellner, University of Houston, Houston, USA Karsten Gohl, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany Laura Crispini, University of Genova (DISTAV, Genova, Italy) Leanne K. Armand, Australian National University, Canberra, Australia. Marcelo A. Reguero, Instituto Antártico Argentino, B1650HMK, San Martín, Buenos Aires, Argentina Marcelo A. Reguero, Instituto Antártico Argentino, Buenos Aires, Argentina Marco Taviani, Institute of Marine Sciences (ISMAR), National Research Council (CNR), 40129, Bologna, Italy and Biology Department, Woods Hole Oceanographic Institution, 02543, Woods Hole, USA Martin J. Siegert, Imperial College London, London, UK Marvin A. Speece, Montana Technological University, Butte, USA Mathieu Casado, Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research, Potsdam, Germany Michele Rebesco, OGS, Trieste, Italy Mike Weber, University of Bonn, Institute for Geosciences, Department of Geochemistry and Petrology, 53115 Bonn, Germany Minoru Ikehara, Kochi University, Japan Nicholas R. Golledge, Antarctic Research Centre Victoria University of Wellington, Wellington 6140, New Zealand Nigel Wardell, OGS, Trieste, Italy Paolo Montagna, Institute of Polar Sciences, National Research Council, Bologna, Italy Peter J. Barrett, Antarctic Research Centre, Victoria University of Wellington, Wellington, New Zealand. Peter K. Bijl, Utrecht University, Utrecht, The Netherlands Philip E. O’Brien, Macquarie University, Sydney, Australia Philip J. Bart, Louisiana State University, Baton Rouge, USA Raffaella Tolotti, University of Genoa, Genoa, Italy Reed P. Scherer, Northern Illinois University, DeKalb, IL, USA Renata G. Lucchi, National Institute of Oceanography and Applied Geophysics (OGS), Sgonico-Trieste, Italy Riccardo Geletti, National Institute of Oceanography and Applied Geophysics – OGS, Trieste, Italy Richard C.A. Hindmarsh, British Antarctic Survey & Durham University, Cambridge & Durham, United Kingdom Richard H. Levy, GNS Science and Victoria University of Wellington, Lower Hutt and Wellington, New Zealand Robert B. Dunbar, Stanford University, Stanford, California, USA Robert D. Larter, British Antarctic Survey, Cambridge, UK Robert M. Mckay, Antarctic Research Centre, Victoria University of Wellington, Wellington, New Zealand R. Selwyn Jones, Monash University (Melbourne, Australia) Sandra Passchier, Montclair State University, Montclair, USA Sean P.S. Gulick, University of Texas at Austin, Austin, Texas Sidney R. Hemming, Columbia University, New York, USA Stefanie Brachfeld, Montclair State University, New Jersey, USA Suzanne OConnell, Wesleyan University, Middletown, CT, USA Trevor Williams, International Ocean Discovery Program, Texas A&M University, College Station, USA Ursula Röhl, MARUM, University of Bremen, Bremen, Germany Yasmina M. Martos, NASA Goddard Space Flight Center, Greenbelt, MD, USA & University of Maryland College Park, MD, USAThe legacy of the Scientific Committee on Antarctic Research’s (SCAR) PAIS strategic research programme includes not only breakthrough scientific discoveries, but it is also the story of a long-standing deep collaboration amongst different multi-disciplinary researchers from many nations, to share scientific infrastructure and data, facilities, and numerical models, in order to address high priority questions regarding the evolution and behaviour of the Antarctic ice sheets (AIS). The PAIS research philosophy is based on data-data and data-model integration and intercomparison, and the development of ‘ice-to-abyss’ data transects and paleo-environmental, extending from the ice sheet interior to the deep sea. PAIS strives to improve understanding of AIS dynamics and to reduce uncertainty in model simulations of future ice loss and global sea level change, by studying warm periods of the geological past that are relevant to future climate scenarios. The multi-disciplinary approach fostered by PAIS represents its greatest strength. Eight years after the start of this programme, PAIS achievements have been high-profile and impactful, both in terms of field campaigns that collected unique data sets and samples, and in terms of scientific advances concerning past AIS dynamics, that have measurably improved understanding of ice sheet sensitivity in response to global warming. Here we provide an overview and synthesis of the new knowledge generated by the PAIS Programme and its implications for anticipating and managing the impacts of global sea-level rise.TN acknowledges support from MBIE Antarctic Science Platform contract ANTA1801

MTR: taxonomic annotation of short metagenomic reads using clustering at multiple taxonomic ranks

Motivation: Metagenomics is a recent field of biology that studies microbial communities by analyzing their genomic content directly sequenced from the environment. A metagenomic dataset consists of many short DNA or RNA fragments called reads. One interesting problem in metagenomic data analysis is the discovery of the taxonomic composition of a given dataset. A simple method for this task, called the Lowest Common Ancestor (LCA), is employed in state-of-the-art computational tools for metagenomic data analysis of very short reads (about 100 bp). However LCA has two main drawbacks: it possibly assigns many reads to high taxonomic ranks and it discards a high number of reads