It is now generally accepted that human rights law applies at sea, yet uncertainty remains as to how it operates within the maritime domain. The United Nations Convention on the Law of the Sea contains few references to the treatment of individuals and many of the central concepts of the law of the sea that are reflected in it—such as functional zones of maritime jurisdiction, flag State jurisdiction and the freedoms of the seas—present challenges to the effective application of human rights law. Moreover, human rights law was developed with a terrestrial focus, making its application at sea equally problematic. This article argues that before practical solutions can be proposed to address this conflict of regimes, it needs to be recognised that human rights law does not apply at sea in the same way that it applies on land: the practical realities of the maritime environment shape the scope and content of rights. It argues that there is a need to clarify what constitutes a genuine human rights issue in the maritime domain, distinguishing these from other forms of poor treatment or regulatory non-compliance. It examines how the law of the sea and human rights law might interact more effectively, considering both conceptual and contextual adjustments necessary for realistic and enforceable protection of human rights in the maritime domain.

The history of the laws of war is an increasingly popular research field of international law. Claire Vergerio’s book War, States, and International Order: Alberico Gentili and the Foundational Myth of the Laws of War is a good-read in this regard. It provides a critical analysis of how 19th-century international lawyers misread and reinterpreted the writings of the 16th-century Italian jurist Alberico Gentili to establish the modern sovereign state as the sole legitimate subject of the laws of war. In this review essay, I offer a critical reading of War, States and International Order, positioning its intervention in the context of broader scholarly debates.

A pervasive approach in scientific computing is to express the solution to a given problem as the limit of a sequence of vectors or other mathematical objects. In many situations these sequences are generated by slowly converging iterative procedures, and this led practitioners to seek faster alternatives to reach the limit. ‘Acceleration techniques’ comprise a broad array of methods specifically designed with this goal in mind. They started as a means of improving the convergence of general scalar sequences by various forms of ‘extrapolation to the limit’, i.e. by extrapolating the most recent iterates to the limit via linear combinations. Extrapolation methods of this type, the best-known of which is Aitken’s delta-squared process, require only the sequence of vectors as input.

However, limiting methods to use only the iterates is too restrictive. Accelerating sequences generated by fixed-point iterations by utilizing both the iterates and the fixed-point mapping itself has proved highly successful across various areas of physics. A notable example of these fixed-point accelerators (FP-accelerators) is a method developed by Donald Anderson in 1965 and now widely known as Anderson acceleration (AA). Furthermore, quasi-Newton and inexact Newton methods can also be placed in this category since they can be invoked to find limits of fixed-point iteration sequences by employing exactly the same ingredients as those of the FP-accelerators.

This paper presents an overview of these methods – with an emphasis on those, such as AA, that are geared toward accelerating fixed-point iterations. We will navigate through existing variants of accelerators, their implementations and their applications, to unravel the close connections between them. These connections were often not recognized by the originators of certain methods, who sometimes stumbled on slight variations of already established ideas. Furthermore, even though new accelerators were invented in different corners of science, the underlying principles behind them are strikingly similar or identical.

The plan of this article will approximately follow the historical trajectory of extrapolation and acceleration methods, beginning with a brief description of extrapolation ideas, followed by the special case of linear systems, the application to self-consistent field (SCF) iterations, and a detailed view of Anderson acceleration. The last part of the paper is concerned with more recent developments, including theoretical aspects, and a few thoughts on accelerating machine learning algorithms.

This work introduces GalProTE, a proof-of-concept Machine Learning model, leveraging Transformer Encoder architecture to efficiently determine the stellar age, metallicity, and dust attenuation of galaxies from optical spectra. Designed to address the challenges posed by the vast datasets produced by modern astronomical surveys, GalProTE offers a significant improvement in processing speed while maintaining accuracy. Using the E-MILES spectral library, we generate a dataset of 111936 diverse templates by expanding the original 636 simple stellar population models with varying extinction levels, combinations of multiple spectra, and noise modifications. This ensures robust training over the spectral range of 4750–7100 Å at a resolution of 2.5 Å. GalProTE architecture employs four parallel attention-based encoders with varying kernel sizes to capture diverse spectral features. The model demonstrates a mean squared error (MSE) of 0.27% with a standard deviation of 0.10% between the input spectra and the GalProTE-generated spectra for the synthetic test dataset. Performance evaluation against real data from two galaxies in the PHANGS-MUSE survey (NGC4254 and NGC5068) demonstrates its ability to extract physical parameters efficiently, with spectral fit residuals showing a mean of -0.02% and 0.28%, and standard deviations of 4.3% and 5.3%, respectively. To contextualize these results, we compare age, metallicity and dust attenuation maps generated by GalProTE with those of pPXF, a state-of-the-art spectral fitting tool. While pPXF achieves robust results, it requires approximately 11 sec per spectrum. In contrast, GalProTE processes a spectrum in less than 4 ms – a speedup factor exceeding 2750, while also consuming 68 times less power per spectrum. The comparison with pPXF maps from PHANGS-MUSE underscores GalProTE’s capacity to enhance traditional methods through machine learning, paving the way for faster, more energy-efficient, and more comprehensive analyses of galactic properties. This study demonstrates the potential of GalProTE as an efficient, scalable, and sustainable solution for processing large astronomical surveys.

The article argues that the reference to the fig tree under which Jesus claims to have seen Nathanael (John 1.48) has not been satisfactorily discussed by previous critical interpreters. Instead, the tree should be understood against the backdrop of Second Temple and later Jewish and Christian exegetical discussions about what species the Tree of Knowledge of Good and Evil exactly was. After tracing these debates in ancient and early medieval sources, including iconography, the argument moves on to show the interpretative possibilities created by this proposal. The conclusion makes a case for understanding the Fourth Gospel as an inherently open work which invites the audience to actively participate in a variety of exegetical discourses, and whose author function builds its authority through polysemy.

Begonia larorum is a threatened plant species endemic to Alcatrazes Island, south-east Brazil, which had not been recorded since its discovery in the 1920s. Here we report its rediscovery after more than a century since the first and only collection. In February 2024, we found a single individual in the forest understorey and successfully propagated it ex situ. Later that year we located a population of 19 individuals in an open area of vegetation prone to fires and invasive grasses and we obtained the first colour photographs of the species. Given its restricted range and the threats to its survival, we recommend the species be assessed for inclusion on the global IUCN Red List in addition to maintaining its Critically Endangered status at national level on the Red List of Brazilian Flora. We also propose in situ and ex situ conservation actions.

Ethiopia aspired to become Africa’s “light manufacturing hub” and a “lower middle-income country” by 2025 (National Planning Commission 2016, 143, 169). Successive Ethiopian governments launched long-term plans and pursued industrial policies in line with a declared “developmental state” approach inspired by Japanese, South Korean, and Chinese models (Aberg and Becker 2020; Cheru and Oqubay 2019; Clapham 2018; Fourie 2015; Gebreeyesus 2013; Oqubay 2018). The intention was to build on the country’s comparative advantages of cheap land and labor to develop manufacturing with backward linkages to the domestic economy, focus on labor-intensive light manufacturing, build special economic zones (SEZs) to attract foreign direct investment (FDI), and promote exports for global markets to create jobs, enhance skills, expand the private sector, and kickstart wider industrialization.

A significant impetus for the negotiation of the United Nations Convention on the Law of the Sea (UNCLOS) was the impact of new technological and scientific developments on the law of the sea. Such developments have continued apace, raising the question of how UNCLOS continues to respond to new uses of, and threats to, the oceans. This article focuses on marine geoengineering as an emerging technological response to the climate emergency and its regulation by the specialised global dumping regime of the Convention on the Prevention of Marine Pollution by Dumping of Wastes and Other Matter and its Protocol within the general normative framework provided by UNCLOS. It demonstrates how responding to technological developments is hard-wired into the DNA of the law of the sea, and into UNCLOS in particular, which remains the foundation for the governance and management of new maritime technologies.

We present Evolutionary Map of the Universe Search Engine (EMUSE), a tool designed for searching specific radio sources within the extensive datasets of the Evolutionary Map of the Universe (EMU) survey, with potential applications to other Big Data challenges in astronomy. Built on a multimodal approach to radio source classification and retrieval, EMUSE fine-tunes the OpenCLIP model on curated radio galaxy datasets. Leveraging the power of foundation models, our work integrates visual and textual embeddings to enable efficient and flexible searches within large radio astronomical datasets. We fine-tune OpenCLIP using a dataset of 2 900 radio galaxies, encompassing various morphological classes, including FR-I, FR-II, FR-x, R-type, and other rare and peculiar sources. The model is optimised using adapter-based fine-tuning, ensuring computational efficiency while capturing the unique characteristics of radio sources. The fine-tuned model is then deployed in the EMUSE, allowing for seamless image and text-based queries over the EMU survey dataset. Our results demonstrate the model’s effectiveness in retrieving and classifying radio sources, particularly in recognising distinct morphological features. However, challenges remain in identifying rare or previously unseen radio sources, highlighting the need for expanded datasets and continuous refinement. This study showcases the potential of multimodal machine learning in radio astronomy, paving the way for more scalable and accurate search tools in the field. The search engine is accessible at https://askap-emuse.streamlit.app/ and can be used locally by cloning the repository at https://github.com/Nikhel1/EMUSE.