Recent changes to US research funding are having far-reaching consequences that imperil the integrity of science and the provision of care to vulnerable populations. Resisting these changes, the BJPsych Portfolio reaffirms its commitment to publishing mental science and advancing psychiatric knowledge that improves the mental health of one and all.

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.

An important component of post-release monitoring of biological control of invasive plants is the tracking of species interactions. During post-release monitoring following the initial releases of the weevil Ceutorhynchus scrobicollis Nerenscheimer and Wagner (Coleoptera: Curculionidae) on garlic mustard, Alliaria petiolata (Marschall von Bieberstein) Cavara and Grande (Brassicaceae), in Ontario, Canada, we identified the presence of larvae of the tumbling flower beetle, Mordellina ancilla Leconte (Coleoptera: Mordellidae), in garlic mustard stems. This study documents the life history of M. ancilla on garlic mustard to assess for potential interactions between M. ancilla and C. scrobicollis as a biological control agent. Garlic mustard stems were sampled at eight sites across southern Ontario and throughout the course of one year to record the prevalence of this association and to observe its life cycle on the plant. We found M. ancilla to be a widespread stem-borer of late second–year and dead garlic mustard plants across sampling locations. This is the first host record for M. ancilla on garlic mustard. The observed life cycle of M. ancilla indicates that it is unlikely to negatively impact the growth and reproduction of garlic mustard and that it is unlikely to affect the use of C. scrobicollis as a biological control agent.

While from an instrumental perspective stakeholder relations can promote sustained competitive advantage, normative arguments underscore the importance of morally informed principles, especially when relational strategies have uncertain future outcomes and are prone to imitation. This study investigates how such instrumental and normative views can be complementary based on the case study of Natura, a cosmetics company procuring natural inputs from the Amazon rainforest via supplier relations that are open to multiple parties, including competitors. The research shows that Natura developed and reinforced a morally informed normative core specifying how the company and its managers should act. This resulted in a long-term commitment to the open relational strategy, especially when future outcomes were largely uncertain, which in turn promoted emergent instrumental gains via deepened relational attachments and substantive stakeholder engagement. Importantly, the company’s controlling shareholders strongly influenced the normative core, thus underscoring the importance of identifying key shareholders and their values.

Aerosol-cloud interactions contribute significant uncertainty to modern climate model predictions. Analysis of complex observed aerosol-cloud parameter relationships is a crucial piece of reducing this uncertainty. Here, we apply two machine learning methods to explore variability in in-situ observations from the NASA ACTIVATE mission. These observations consist of flights over the Western North Atlantic Ocean, providing a large repository of data including aerosol, meteorological, and microphysical conditions in and out of clouds. We investigate this dataset using principal component analysis (PCA), a linear dimensionality reduction technique, and an autoencoder, a deep learning non-linear dimensionality reduction technique. We find that we can reduce the dimensionality of the parameter space by more than a factor of 2 and verify that the deep learning method outperforms a PCA baseline by two orders of magnitude. Analysis in the low dimensional space of both these techniques reveals two consistent physically interpretable regimes—a low pollution regime and an in-cloud regime. Through this work, we show that unsupervised machine learning techniques can learn useful information from in-situ atmospheric observations and provide interpretable results of low-dimensional variability.

We conducted an international survey of stroke physicians to assess practices and attitudes toward cardiac monitoring and early rhythm control. A 20-question survey was completed by 241 clinicians representing 61 countries. The minimum duration of actionable atrial fibrillation varied widely, and more than 90% (223/241) of respondents indicated a willingness to enroll patients in a trial assessing the ideal duration of cardiac monitoring. Only a quarter of respondents (62/241) offered early rhythm control for patients with atrial fibrillation, with the majority (209/241, 87%) expressing an opinion that there was equipoise about the benefit of rhythm control in the post-stroke population.