Polarimetric multi-offset radio-echo sounding offers improved constraints on englacial thermal conditions, basal properties and ice crystal orientation compared to standard monostatic observations. Nevertheless, such surveys are uncommon in glaciology and are typically limited in offset due to cable losses. In the 2023–24 austral summer, we deployed two radar systems on Eastwind Glacier and the McMurdo Ice Shelf in Antarctica, collecting five polarimetric common-midpoint (CMP) surveys. Using an Autonomous phase-sensitive Radio-Echo Sounder (ApRES), modified with off-the-shelf radio frequency-over-fiber (RFoF) hardware and a low-loss fiber optic link, we detect bed reflections at offsets up to the equivalent of four ice thicknesses, well beyond the theoretical point of total internal reflection. A second, cable-less system built around a software-defined radio (SDR) was deployed simultaneously as an unsynchronized receiver recording the same ApRES transmitter. These co-located datasets demonstrate the potential for cabled radar systems with integrated RFoF technology for extending maximum offsets by overcoming attenuation losses inherent to coaxial cables. Furthermore, we perform polarimetric amplitude-vs-offset analysis to probe glacier dielectric structure. Finally, we present data from deployment of the fiber optic system on Thwaites Glacier, where we detect bed reflections at an offset of 4 km, demonstrating operation on thick ice (~2.2 km).

Timely blood cultures (BCx) are required by SEP-1. The recent BCx bottle shortage necessitated enhanced BCx stewardship. At two hospitals during the shortage, SEP-1 metric compliance declined related to BCx utilization. Review of cases where BCx were not obtained demonstrated most BCx were safely avoided without demonstrable patient harm.

Language models (LMs) have attracted the attention of researchers from the natural language processing (NLP) and machine learning (ML) communities working in specialized domains, including climate change. NLP and ML practitioners have been making efforts to reap the benefits of LMs of various sizes, including large language models, in order to both simplify and accelerate the processing of large collections of text data, and in doing so, help climate change stakeholders to gain a better understanding of past and current climate-related developments, thereby staying on top of both ongoing changes and increasing amounts of data. This paper presents a brief history of language models and ties LMs’ beginnings to them becoming an emerging technology for analysing and interacting with texts in the specialized domain of climate change. The paper reviews existing domain-specific LMs and systems based on general-purpose large language models for analysing climate change data, with special attention being paid to the LMs’ and LM-based systems’ functionalities, intended use and audience, architecture, the data used in their development, the applied evaluation methods, and their accessibility. The paper concludes with a brief overview of potential avenues for future research vis-à-vis the advantages and disadvantages of deploying LMs and LM-based solutions in a high-stakes scenario such as climate change research. For the convenience of readers, explanations of specialized terms used in NLP and ML are provided.

This article argues that the global Business and Human Rights movement demonstrates a push towards a human-rights type of sustainable corporation, reconciling economic development and human rights. It explains the necessity for and significance of a definition of a sustainable corporation at the intersection of traditional international human rights and sustainable development instruments. It argues, inter alia, that an internationally recognised definition of a sustainable corporation can settle fundamental questions and create a minimal framework for meaningful discourse on corporate accountability for human rights, climate change and the environment. It identifies difficulties of defining a sustainable corporation such as the integration problem. It suggests ‘direct human rights obligation’ as a minimally sufficient normative criterion for the definitional correctness of a sustainable corporation. The suggested definition of sustainable corporation requires taking a normative position which makes the term ‘essentially contested’ resulting in discursive and behavioural norm contestation in the search for definitional determinacy and consensus within the divide between international and domestic law.

This article discusses the official discourse that appeared in Macau’s Portuguese-language media and the documentaries that were shot there by Portuguese filmmakers in the 1960s and 1970s, especially focusing on the productions that followed the 123 Incident and which largely functioned as a response to it. These riots occurred in December 1966, when Chinese residents of Macau used Cultural Revolution-like protests to contest what they viewed as an inefficient and unfair Portuguese administration. They had a long-lasting and deep impact, weakening Portuguese colonial rule and increasing the influence of the People’s Republic of China (PRC) and local Maoists in Macau. In an attempt to counter the image-damage caused by the incident and legitimise Portuguese sovereignty in the territory during what was its worst crisis in the post-war period, Portuguese official discourse and these films came to promote Macau as a site of ‘miraculous’ development and modernisation that had as its basis Luso-Chinese partnership. Furthermore, Macau was advocated as an exemplary case of good neighbourhood policy towards the PRC and of coexistence at all levels, particularly ethnically and politically. This, it was suggested, made it a unique place and a model for the world in a time of cold war.

A general way to represent stochastic differential equations (SDEs) on smooth manifolds is based on the Schwartz morphism. In this manuscript, we are interested in SDEs on a smooth manifold $M$ that are driven by p-dimensional Wiener process $W_t \in \mathbb{R}^p$ and time $t$. In terms of the Schwartz morphism, such an SDE is represented by a Schwartz morphism that morphs the semimartingale $(t,W_t)\in\mathbb{R}^{p+1}$ into a semimartingale on the manifold $M$. We show that it is possible to construct such Schwartz morphisms using special maps that we call diffusion generators. We show that one of the ways to construct a diffusion generator is by considering the flow of differential equations. One particular case is the construction of diffusion generators using Lagrangian vector fields. Using the diffusion generator approach, we also give the extended Itô formula (also known as generalized Itô formula or Itô–Wentzell formula) for SDEs on manifolds.

Promoting fruit and vegetable (F&V) consumption is a public health priority. This study assessed compliance with the international recommendation of consuming at least 400g of F&V daily among Mexican adults and analysed its association with the five stages of behaviour change from the Transtheoretical Model (Precontemplation, Contemplation, Preparation for action, Action, and Maintenance). Using data from 5203 adults (ages 20–59) in the 2016 National Health and Nutrition Survey, dietary intake was collected via a food frequency questionnaire. Compliance was defined dichotomously (Yes/No), and readiness to change was assessed using a specific survey module. Multiple logistic regression models examined the association between stages of change and compliance, adjusting for demographic, socioeconomic, and health characteristics, as well as perceived barriers and self-efficacy. Nationally, 26.3% of adults met the F&V recommendation. Compliance was significantly higher among individuals in the Preparation for action (OR 3.62, 95% CI: 1.82–7.19), Action (OR 4.50, 95% CI: 1.8–11.25), and Maintenance (OR 9.54, 95% CI: 4.76–19.13) than those in the Precontemplation stage. Higher compliance was also significantly associated with greater self-efficacy (OR 1.86, 95% CI: 1.4–2.47), being in the highest socioeconomic tertile (OR 1.71, 95% CI: 1.25–2.33), and living in the central region (OR 1.70, 95% CI: 1.18–2.45). Conversely, individuals reporting a dislike for vegetables were less likely to meet recommendations (OR 0.67, 95% CI: 0.48–0.94). These findings highlight the value of developing stage-tailored interventions that consider both psychological and structural barriers to improve F&V consumption.

Fine-grained mortality forecasting has gained momentum in actuarial research due to its ability to capture localized, short-term fluctuations in death rates. This paper introduces MortFCNet, a deep-learning method that predicts weekly death rates using region-specific weather inputs. Unlike traditional Serfling-based methods and gradient-boosting models that rely on predefined fixed Fourier terms and manual feature engineering, MortFCNet automatically learns patterns from raw time-series data without needing explicitly defined Fourier terms or manual feature engineering. Extensive experiments across over 200 NUTS-3 regions in France, Italy, and Switzerland demonstrate that MortFCNet consistently outperforms both a standard Serfling-type baseline and XGBoost in terms of predictive accuracy. Our ablation studies further confirm its ability to uncover complex relationships in the data without feature engineering. Moreover, this work underscores a new perspective on exploring deep learning for advancing fine-grained mortality forecasting.

“The Fate of Ophelia,” the opening track on Taylor Swift’s album The Life of a Showgirl, includes an unsettling Shakespearean allusion. Ophelia was the jilted lover of the melancholy prince in Shakespeare’s Hamlet, a woman whose life ends in suicide. Swift’s song says her fiancé, Travis Kelce, saved her from the fate of Ophelia, positioning her previous boyfriends as moody philosophers and the fun-loving jock Kelce as the anti-Hamlet. This song also recuperates Swift as a reader of Shakespeare after the startingly bad account of Romeo and Juliet in “Love Story,” the song that started Swift’s career.