ALBERT

Description: Fluid-rock interaction has profound effects on the dynamics of the lithosphere. This Perspectives article describes the catalytic effects of water on the kinetics of mineral reactions and on the strength of rocks in terms of coupled dissolution and precipitation mechanisms on a macro- and nano-scale. The length scale of coupling between the dissolution and precipitation steps depends on the fluid composition at the mineral-fluid interface and also on differential stress. Stress-induced mass transport, dependent on the generation of porosity by mineral reactions, results in dissolution-precipitation creep as the principal mechanism of rock deformation in the lithosphere. The heterogeneous distribution of fluid infiltration into dry, strong rocks in the deep crust leads to weak rocks within strong, stressed host rock and the possibility of significant local variations in pressure. Fluid-rock interaction mechanisms are discussed in terms of recrystallisation reactions whereby mass transport and the most favourable nucleation sites determine the distribution and texture of the resultant assemblages. Metamorphic differentiation is a natural consequence of dissolution-precipitation mechanisms under deviatoric stress and similar mechanisms may apply to general pattern formation in rocks.

Description: The continuum emission from radio galaxies can be generally classified into different morphological classes such as FRI, FRII, Bent, or Compact. In this paper, we explore the task of radio galaxy classification based on morphology using deep learning methods with a focus on using a small scale dataset (∼2000 samples). We apply few-shot learning techniques based on Twin Networks and transfer learning techniques using a pre-trained DenseNet model with advanced techniques like cyclical learning rate and discriminative learning to train the model rapidly. We achieve a classification accuracy of over 92% using our best performing model with the biggest source of confusion being between Bent and FRII type galaxies. Our results show that focusing on a small but curated dataset along with the use of best practices to train the neural network can lead to good results. Automated classification techniques will be crucial for upcoming surveys with next generation radio telescopes which are expected to detect hundreds of thousands of new radio galaxies in the near future.

Description: We present VIVACE, the VIrac VAriable Classification Ensemble, a catalogue of variable stars extracted from an automated classification pipeline for the Vista Variables in the Vía Láctea (VVV) infrared survey of the Galactic bar/bulge and southern disc. Our procedure utilises a two-stage hierarchical classifier to first isolate likely variable sources using simple variability summary statistics and training sets of non-variable sources from the Gaia early third data release, and then classify candidate variables using more detailed light curve statistics and training labels primarily from OGLE and VSX. The methodology is applied to point-spread-function photometry for ∼490 million light curves from the VIRAC v2 astrometric and photometric catalogue resulting in a catalogue of ∼1.4 million likely variable stars, of which ∼39, 000 are high-confidence (classification probability 〉0.9) RR Lyrae ab stars, ∼8000 RR Lyrae c/d stars, ∼187, 000 detached/semi-detached eclipsing binaries, ∼18, 000 contact eclipsing binaries, ∼1400 classical Cepheid variables and ∼2200 Type II Cepheid variables. Comparison with OGLE-4 suggests a completeness of around 90  per cent for RRab and ≲ 60 per cent for RRc/d, and a misclassification rate for known RR Lyrae stars of around 1 per cent for the high confidence sample. We close with two science demonstrations of our new VIVACE catalogue: first, a brief investigation of the spatial and kinematic properties of the RR Lyrae stars within the disc/bulge, demonstrating the spatial elongation of bar-bulge RR Lyrae stars is in the same sense as the more metal-rich red giant population whilst having a slower rotation rate of ∼40 km s−1kpc−1; and secondly, an investigation of the Gaia EDR3 parallax zeropoint using contact eclipsing binaries across the Galactic disc plane and bulge.

Description: We investigate the properties of the dark matter (DM) halo surrounding the nearby galaxy group NGC 1600. Through the use of deep (252 ks) Chandra observations and 64.3 ks of XMM–Newton observations, we construct surface brightness profiles in multiple energy bands in order to perform hydrostatic equilibrium analysis of the hot plasma within NGC 1600. Regardless of the DM model profile assumed, we measure a halo concentration (c200) that is an extreme, positive outlier of the ΛCDM c200-M200 relation. For a typical NFW DM profile, we measure c200 = 26.7 ± 1.4 and M200 = (2.0 ± 0.2) × 1013 M⊙; assuming a similar halo mass, the average concentration expected is c200 = 6 − 7 for the theoretical ΛCDM c-M relation. Such a high concentration is similar to that of well-known fossil groups MRK 1216 and NGC 6482. While NGC 1600 exhibits some properties of a fossil group, it fails to meet the X-ray luminosity threshold of LX 〉 5 × 1041 erg s−1. Whether or not it is considered a fossil group, the high concentration value makes it part of a select group of galaxy groups.

Description: In this paper, we report white dwarfs identified in the 5th Data Release of the Large Area Multi-Object fibre Spectroscopic Telescope, including spectral types of DA, DB, DC, DZ, and so on. There are 2 625 DA spectra of 2 281 DA stars, 182 DB spectra of 166 DB stars, 62 DC spectra of 58 DC stars, 36 DZ spectra of 33 DZ stars and many other types identified, in addition to our previous paper (Data Release 2). Among those sources, 393 DA stars and 46 DB stars are new identifications after cross-matching with the literature. In order to select DA candidates, we use the classification result from the LAMOST pipeline, colour-colour cut method and a random forest machine learning method. For DBs, since there is no template for DB in the pipeline model, a random forest machine learning method is chosen to select candidates. All the WD candidates have been visually checked individually. The parameters of effective temperature, surface gravity, mass, and cooling age have been estimated for relatively high signal-to-noise ratio DAs and DBs. The peaks of the DA and DB mass distributions are found to be around 0.62 M⊙ and 0.65 M⊙, respectively. Finally, the data and method we used to select white dwarf candidates for the second phase of LAMOST survey are also addressed in this paper.

Description: Magnetars, the likely sources of Fast Radio Bursts (FRBs), produce both steady highly relativistic magnetized winds, and occasional ejection events. We demonstrate that the requirement of conservation of the magnetic flux dominates the overall dynamics of magnetic explosions. This is missed in conventional hydrodynamic models of the ejections as expanding shell with parametrically added magnetic field, as well as one-dimensional models of magnetic disturbances. Magnetic explosions from magnetars come into force balance with the pre-flare wind close to the light cylinder. They are then advected quietly with the wind, or propagate as electromagnetic disturbances. No powerful shock waves are generated in the wind.

Description: Qualitative Network Models (QNMs), Fuzzy Cognitive Maps (FCMs), and Bayesian Belief Networks (BBNs) have been proposed as methods to formalize conceptual models of social–ecological systems and project system responses to management interventions or environmental change. To explore how these different methods might influence conclusions about system dynamics, we assembled conceptual models representing three different coastal systems, adapted them to the network approaches, and evaluated outcomes under scenarios representing increased fishing effort and environmental warming. The sign of projected change was the same across the three network models for 31–60% of system variables on average. Pairwise agreement between network models was higher, ranging from 33 to 92%; average levels of similarity were comparable between network pairs. Agreement measures based on both the sign and strength of change were substantially worse for all model comparisons. These general patterns were similar across systems and scenarios. Different outcomes between models led to different inferences regarding trade-offs under the scenarios. We recommend deployment of all three methods, when feasible, to better characterize structural uncertainty and leverage insights gained under one framework to inform the others. Improvements in precision will require model refinement through data integration and model validation.

Description: The IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb; www.guidetopharmacology.org) is an open-access, expert-curated database of molecular interactions between ligands and their targets. We describe expansion in content over nine database releases made during the last two years, which has focussed on three main areas of infection. The COVID-19 pandemic continues to have a major impact on health worldwide. GtoPdb has sought to support the wider research community to understand the pharmacology of emerging drug targets for SARS-CoV-2 as well as potential targets in the host to block viral entry and reduce the adverse effects of infection in patients with COVID-19. We describe how the database rapidly evolved to include a new family of Coronavirus proteins. Malaria remains a global threat to half the population of the world. Our database content continues to be enhanced through our collaboration with Medicines for Malaria Venture (MMV) on the IUPHAR/MMV Guide to MALARIA PHARMACOLOGY (www.guidetomalariapharmacology.org). Antibiotic resistance is also a growing threat to global health. In response, we have extended our coverage of antibacterials in partnership with AntibioticDB.

Description: Much has been published on the effects of ocean acidification on plankton since the original Royal Society 2005 report. In addition to direct effects on primary production, it is clear that ocean acidification also has profound consequences for biogeochemistry. Furthermore, although ocean acidification can have direct effects of on grazers such as copepods, acidification induces changes in nutritional value of phytoplankton which can be passed on up the food chain. There has also been recognition of the complexity of the interactions between elevated CO2 and other environmental factors and this has seen an upsurge in climate change research involving multifactorial experiments. In particular, the interaction of ocean acidification with global warming resulting from the increasing greenhouse effect has been investigated. There has also been research on acidification and warming effects in inland water plankton. These, combined with novel experimental techniques and long term studies of genetic adaptation, are providing better insights to plankton biology and communities in a future world.

Description: The health of Corymbia calophylla (marri), a keystone tree species in the native forests of southwest Western Australia, has been in decline for the past few decades. Phytophthora root disease and waterlogging have often been cited as contributing to this decline. Traditional methods (i.e., field surveys and sampling) of mapping Phytophthora root infection in the field are time-consuming and expensive; thus, the potential of reflectance spectroscopy to characterize marri response to Phytophthora and waterlogging stress was investigated. Twelve-month old marri plants were infected with either P. cinnamomi or P. multivora in two glasshouse trials and waterlogged for 24 h each fortnight. Spectral measurements with a portable high-resolution spectroradiometer were taken weekly. Plant biophysical measurements were taken at harvest time. Normalized difference spectral index (NDSI) was calculated for every combination of reflectance values between 400 and 2500 nm for all time points, correlated with the treatment effects and displayed as heat maps. Narrowband vegetation indices (VIs), utilizing different wavelengths of the electromagnetic spectrum, were also calculated from the spectral data. The Phytophthora treatments did not cause significant differences with the biophysical measurements in both trials. In the second trial, the waterlogging treatment significantly lowered plant top dry weight (P = 0.016) and diameter (P = 0.044). Reflectance values plotted against wavelength displayed differences between treatments as well as a seasonal trend. The NDSI heat maps indicated that the Phytophthora and waterlogging treatment effects were strongest correlated with bandwidths in the visible and near-infrared portions of the electromagnetic spectrum (538–558 nm and 701–709 nm). Six of the VIs (normalized difference nitrogen index 2, anthocyanin reflectance index 1, photochemical reflectance index, Carter index 1, Vogelman index 3 and water band index) were able to track the biochemical changes in the leaves over the 10 weeks, confirming the seasonal trend. The interaction effect between P. cinnamomi, waterlogging and elapsed time in the first trial was significant for water band index (P = 0.010). This study demonstrates that reflectance spectroscopy holds promise for characterizing marri response but more work needs to be done to identify the optimum wavelengths for identifying Phytophthora and waterlogging stress with marri.