Kongolandsbyen was an ‘ethnographic village’ staged in Oslo as part of Norway’s Jubilee Exhibition of 1914. The ‘village’ housed and displayed a troupe of eighty Senegalese performers including musicians playing kora, balafon, and other instruments. Examining music’s performance and reception in Kongolandsbyen demonstrates how colonialist practices and beliefs influenced even European nations, such as Norway, that were nominally non-imperialist. Kongolandsbyen’s promoters mimicked exhibitions common in France and Germany at which audiences sought both to learn about unfamiliar societies and to be entertained by sensationalized, ostensibly ‘primitive’, performances. By demonstrating fluency in the tired but familiar genre of the ‘ethnographic village’, Norwegians emulated the prestige of European imperial powers to challenge Norway’s marginal status as a newly independent, small country with limited geopolitical influence. Kongolandsbyen’s Senegalese performers pushed back against colonialist, racist representations through both thoughtful presentations of their musical traditions and an insistence on their own modernity.

This study presents a comparative evaluation of sentiment analysis models applied to a large corpus of expert wine reviews from Wine Spectator, with the goal of classifying reviews into binary sentiment categories based on expert ratings. We assess six models: logistic regression, XGBoost, LSTM, BERT, the interpretable Attention-based Multiple Instance Classification (AMIC) model, and the generative language model LLAMA 3.1, highlighting their differences in accuracy, interpretability, and computational efficiency. While LLAMA 3.1 achieves the highest accuracy, its marginal improvement over AMIC and BERT comes at a significantly higher computational cost. Notably, AMIC matches the performance of pretrained large language models while offering superior interpretability, making it particularly effective for domain-specific tasks such as wine sentiment analysis. Through qualitative analysis of sentiment-bearing words, we demonstrate AMIC’s ability to uncover nuanced, context-dependent language patterns unique to wine reviews. These findings challenge the assumption of generative models’ universal superiority and underscore the importance of aligning model selection with domain-specific requirements, especially in applications where transparency and linguistic nuance are critical.

This comment is the personal reflection of an early career historian on the challenges of working on Russian history during a time of geopolitical change and declining access. As libraries and archives in the Russian Federation become increasingly difficult to use following the invasion of Ukraine, early-career and younger historians are being forced to adopt remote or indirect methods of research due to formal and informal barriers. I reflect on some of the ethical, practical and epistemological dilemmas of conducting historical investigations at a distance, drawing chiefly on my own experiences working on the tsarist secret police during the First World War. I argue that this is not a return to Cold War constraints, but a new era that demands fresh strategies and a redefinition of expertise.

We construct a model for the (non-unital) S1-framed little 2d-dimensional disks operad for any positive integer d using logarithmic geometry. We also show that the unframed little 2d-dimensional disks operad has a model which can be constructed using log schemes with virtual morphisms.

There is limited analysis of the adoption of luxury tourism strategies in Africa. Such strategies promise lower ecological impact and higher tourism revenues. Through an analysis of economic data and secondary literature, as well as interviews conducted in Mauritius, Botswana, and Rwanda, this article examines why once luxury tourism strategies are adopted and do not deliver expected results, some countries reverse these strategies while others do not. Contrary to recent African political economy literature, this paper shows that “democratic” governments (Mauritius, Botswana) with shorter-term horizons have more flexibility in adapting their strategies compared to “authoritarian” governments with longer-term horizons (Rwanda).

We study new properties of generalised Harish-Chandra theory aiming at explaining the inductive local-global conditions for finite groups of Lie type in nondefining characteristic. In particular, we consider a parametrisation of generalised Harish-Chandra series that is compatible with Clifford theory and with the action of automorphisms on irreducible characters and we reduce it to the verification of certain requirements on stabilisers and extendibility of characters. This parametrisation is used by the author in a separate paper to obtain new conjectures for finite reductive groups that can be seen as geometric realisations of the local-global counting conjectures and their inductive conditions. As a by-product, we extend the parametrisation of generalised Harish-Chandra series given by Broué–Malle–Michel to the nonunipotent case by assuming maximal extendibility.

India, as the world’s most populous country, and with a substantial urban population, requires strategic development to mitigate the risks of urban pluvial flooding in the context of a changing climate. Rapid urbanization increases the presence of impervious surfaces, and climate change effects bring intense, frequent and long-duration rainfall events in India, which magnify urban flooding. Implementing sustainable urban drainage solutions (SUDSs) would mitigate stormwater flood risks, but India has yet to adopt this approach; instead, it relies on traditional drainage infrastructure, despite increasing population indices and an extended yearly rainfall season. Here, we highlight the existing scenario, the challenges and the way forward towards implementing SUDSs in India. To attain SUDSs, city-specific drainage-related challenges need to be identified through problem tree analysis, co-creation with stakeholders of a shared vision for sustainable urban drainage and the design of actionable pathways and experimental approaches for implementing interventions and refining practical indicators. These actions could collectively provide a roadmap for achieving resilient SUDSs.

Butachlor is a herbicide extensively employed in rice (Oryza sativa L.) cultivation but historically under-investigated for its toxicological impacts on terrestrial vegetation. This study examines the dose-dependent effects of butachlor on the germination and antioxidant defense mechanisms in the seeds of Asian tape grass [Vallisneria natans (Lour.) H. Hara], an important submerged plant species widely distributed in the agricultural ponds. In a hydroponic setup, seeds were exposed to four concentrations of butachlor (0, 20, 200, and 2,000 μg ai L−1), and cultivated under controlled light conditions to quantify germination rates and assess oxidative stress responses. Our findings showed that butachlor concentrations up to 20 μg L−1 had no effect on the germination rate of V. natans seeds, while germination rates decreased by 6.0% and 8.7% at 200 and 2,000 μg L−1, respectively. At 2,000 μg L−1, malondialdehyde (MDA) content increased by 5.7 nmol g−1 FW, and catalase (CAT) activity declined by 21%, indicating oxidative damage. Additionally, the antioxidants proline (Pro) and glutathione (GSH) were upregulated under 20 μg L−1 butachlor treatment after 12 h, contributing to reactive oxygen species (ROS) scavenging and cellular stability. This study highlights the nuanced interactions between butachlor exposure and the antioxidant defenses in V. natans, providing valuable insights into the ecological impacts of herbicide pollution. Understanding these interactions is crucial for development of sustainable agricultural practices and management of herbicide resistance in aquatic systems.

Autistic high school students overwhelmingly have a poor experience of school. Research into this stage of life is limited, and researchers have tended not to talk to autistic students directly, instead hearing from non-autistic observers such as teachers and parents. This study aimed to address this gap in our knowledge by interviewing autistic students in mainstream high schools about their experience of school and their ideas for how this could be improved. Ten autistic students (13 to 20 years old) in Australian high schools were interviewed. Students overwhelmingly reported a negative experience. Most said their ideal school would be one where teachers and peers had greater understanding about autism and teachers had training in autism. By including the student voice, this research makes a valuable contribution to our understanding of autistic students’ school experience, adding depth and detail, and including what they would like to see changed. Importantly, the interview data also challenged misconceptions about what autistic students prioritised. The voice of autistic teens can make an important contribution to policies and practices aimed at improving their experience of school.

The growth of small perturbations in isotropic turbulence is studied using massive ensembles of direct numerical simulations. These ensembles capture the evolution of the ensemble-averaged flow field and the ensemble variance in the fully nonlinear regime of perturbation growth. Evolution equations for these two fields are constructed by applying the ensemble average operator to the Navier–Stokes equations and used to study uncertainty growth in scale and physical space. It is shown that uncertainty growth is described by a flux of energy from the ensemble-averaged flow to the ensemble variance. This flux is formally equivalent to the subgrid scale (SGS) energy fluxes of the turbulence cascade, and can be interpreted as an inverse uncertainty cascade from small to large scales. In the absence of information sources (measurements), the uncertainty cascade is unsteady and leads to the progressive filtering of the small scales in the ensemble-averaged flow, a process that represents the loss of predictability due to chaos. Similar to the kinetic energy cascade, the uncertainty cascade displays an inertial range with a constant average uncertainty flux, which is bounded from below by the average kinetic energy dissipation. Locally in space, uncertainty fluxes differ from the SGS energy fluxes at the same scale, but both have similar statistics and are significantly correlated with each other in space. This suggests that uncertainty propagation is partly connected to the energy cascade and that they share similar mechanisms. These findings open avenues to model uncertainty propagation in turbulence following an approach similar to the SGS models in large-eddy simulations. This is relevant not only to efficiently assess the reliability and accuracy of turbulence forecasts, but also to design uncertainty-robust reconstruction techniques for data assimilation or SGS modelling.

Each year, over 100,000 dogs are imported into Germany from other EU countries by animal welfare organisations, mainly from Romania. This study conducted a systematic content analysis of websites belonging to 241 animal welfare organisations that rehome dogs from southern and eastern Europe to Germany. Assessment included transparency, legal compliance, and availability of educational and medical information for adopters. The study shows that many organisations lacked information regarding dogs’ origins, transport methods, or health status which sometimes makes it difficult to distinguish between dog rescue and illegal dog trade. Photos were mainly used in adoption advertisements and behavioural descriptions were only included in two-thirds of the dog advertisements which poses a risk of increased dog relinquishment post-adoption due to behavioural unsuitability. Information on vector-borne diseases and typical behaviour of imported rescue dogs was not provided comprehensively. Few organisations violated legal standards, offering underage or banned breeds and failing to use the TRACES transport system. Most organisations relied upon private foster homes, while few had no temporary housing available in Germany. Although most claimed to conduct pre-adoption checks, comprehensive contract details were rarely published. The number of existing animal welfare organisations that rehome dogs from southern and eastern Europe to Germany is unable to be determined due to high fluctuation and the lack of central registry. Inadequate health disclosures and behavioural descriptions risk poor adoption matches and increased returns. Lack of legal compliance may endanger both animal and public welfare and opens the door to illegal dog trade. Sustainable animal protection requires better adopter education, reliable medical testing, and local engagement in source countries to reduce reliance upon transnational rehoming.

The simulation of turbulent flow requires many degrees of freedom to resolve all the relevant time and length scales. However, due to the dissipative nature of the Navier–Stokes equations, the long-term dynamics is expected to lie on a finite-dimensional invariant manifold with fewer degrees of freedom. In this study, we build low-dimensional data-driven models of pressure-driven flow through a circular pipe. We impose the ‘shift-and-reflect’ symmetry to study the system in a minimal computational cell (e.g. the smallest domain size that sustains turbulence) at a Reynolds number of 2500. We build these models by using autoencoders to parametrise the manifold coordinates and neural ordinary differential equation to describe their time evolution. Direct numerical simulations (DNSs) typically require of the order of $\mathcal{O}(10^5)$ degrees of freedom, while our data-driven framework enables the construction of models with fewer than 20 degrees of freedom. Remarkably, these reduced-order models effectively capture crucial features of the flow, including the streak breakdown. In short-time tracking, these models accurately track the true trajectory for one Lyapunov time, as well as the leading Lyapunov exponent, while at long-times, they successfully capture key aspects of the dynamics such as Reynolds stresses and energy balance. The model can quantitatively capture key characteristics of the flow, including the streak breakdown and regeneration cycle. Additionally, we report new exact coherent states found in the DNS with the aid of these low-dimensional models. This approach leads to the discovery of seventeen previously unknown solutions within the turbulent pipe flow system, notably featuring relative periodic orbits characterised by the longest reported periods for such flow conditions.