The stars of the Milky Way carry the chemical history of our Galaxy in their atmospheres as they journey through its vast expanse. Like barcodes, we can extract the chemical fingerprints of stars from high-resolution spectroscopy. The fourth data release (DR4) of the Galactic Archaeology with HERMES (GALAH) Survey, based on a decade of observations, provides the chemical abundances of up to 32 elements for 917 588 stars that also have exquisite astrometric data from the Gaia satellite. For the first time, these elements include life-essential nitrogen to complement carbon, and oxygen as well as more measurements of rare-earth elements critical to modern-life electronics, offering unparalleled insights into the chemical composition of the Milky Way. For this release, we use neural networks to simultaneously fit stellar parameters and abundances across the whole wavelength range, leveraging synthetic grids computed with Spectroscopy Made Easy. These grids account for atomic line formation in non-local thermodynamic equilibrium for 14 elements. In a two-iteration process, we first fit stellar labels to all 1 085 520 spectra, then co-add repeated observations and refine these labels using astrometric data from Gaia and 2MASS photometry, improving the accuracy and precision of stellar parameters and abundances. Our validation thoroughly assesses the reliability of spectroscopic measurements and highlights key caveats. GALAH DR4 represents yet another milestone in Galactic archaeology, combining detailed chemical compositions from multiple nucleosynthetic channels with kinematic information and age estimates. The resulting dataset, covering nearly a million stars, opens new avenues for understanding not only the chemical and dynamical history of the Milky Way but also the broader questions of the origin of elements and the evolution of planets, stars, and galaxies.

Current and future surveys rely on machine learning classification to obtain large and complete samples of transients. Many of these algorithms are restricted by training samples that contain a limited number of spectroscopically confirmed events. Here, we present the first real-time application of Active Learning to optimise spectroscopic follow-up with the goal of improving training sets of early type Ia supernovae (SNe Ia) classifiers. Using a photometric classifier for early SN Ia, we apply an Active Learning strategy for follow-up optimisation using the real-time Fink broker processing of the ZTF public stream. We perform follow-up observations at the ANU 2.3m telescope in Australia and obtain 92 spectroscopic classified events that are incorporated in our training set. We show that our follow-up strategy yields a training set that, with 25% less spectra, improves classification metrics when compared to publicly reported spectra. Our strategy selects in average fainter events and, not only supernovae types, but also microlensing events and flaring stars which are usually not incorporated on training sets. Our results confirm the effectiveness of active learning strategies to construct optimal training samples for astronomical classifiers. With the Rubin Observatory LSST soon online, we propose improvements to obtain earlier candidates and optimise follow-up. This work paves the way to the deployment of real-time AL follow-up strategies in the era of large surveys.

Anaemia is characterised by low hemoglobin (Hb) concentration. Despite being a public health concern in Ethiopia, the role of micronutrients and non-nutritional factors as a determinant of Hb concentrations has been inadequately explored. This study focused on the assessment of serum micronutrient and Hb concentrations and a range of non-nutritional factors, to evaluate their associations with the risk of anaemia among the Ethiopian population (n 2046). It also explored the mediation effect of Zn on the relation between se and Hb. Bivariate and multivariate regression analyses were performed to identify the relationship between serum micronutrients concentration, inflammation biomarkers, nutritional status, presence of parasitic infection and socio-demographic factors with Hb concentration (n 2046). Sobel–Goodman test was applied to investigate the mediation of Zn on relations between serum se and Hb. In total, 18·6 % of participants were anaemic, 5·8 % had iron deficiency (ID), 2·6 % had ID anaemia and 0·6 % had tissue ID. Younger age, household head illiteracy and low serum concentrations of ferritin, Co, Cu and folate were associated with anaemia. Serum se had an indirect effect that was mediated by Zn, with a significant effect of se on Zn (P < 0·001) and Zn on Hb (P < 0·001). The findings of this study suggest the need for designing a multi-sectorial intervention to address anaemia based on demographic group.

Despite the recent policy impetus for age-friendly cities, there is still scope for more geographical insights into ageing in low- and middle-income countries (LMICs). Cities in LMICs, such as Bengaluru (India), are witnessing an increase in the size of the older population in their peripheral urban regions, but there is relatively little understanding of the risks of exclusion in later age in these liminal zones. This study, set in a peripheral ward of Bengaluru, focuses on the experiences of exclusion/inclusion of socio-economically marginalised older adults and their access to work, health care and leisure. The research uses a multidimensional old-age exclusion framework to highlight how the domains of neighbourhood, material resources, mobility infrastructure and social relations influence the risks for social exclusion. We use a qualitative approach by combining behavioural mapping and in-depth interviews. Our findings highlight some ways in which institutionalised exclusion from civic infrastructure accentuates the precariousness of ageing. The rigidity of traditional hierarchies in peri-urban regions has meant that older adults who were poor, women and belonged to marginalised castes experience constrained mobilities to access labour markets, health care and social life, compounding their place-based exclusion. Despite social networks and solidarities, older adults on the periphery faced individualisation of risks while trying to access the basic amenities, thereby falling between the gap of the urban–rural milieu and governance. Age-friendly cities need to accommodate such hybrid transitionary urban processes, in the absence of which, active ageing in these rising peripheries can be impeded.