Claiming Land, Claiming Water: Borders and the People Who Crossed Them in the Early Modern Atlantic

Claiming Land, Claiming Water shares what historians and geographers wish readers knew about maps and borders before, during, and after the founding of the United States. The essays collected in this volume model how people can learn to interpret maps as arguments, rather than as historical facts, and to read maps for evidence of people and places that were elided, renamed, or destroyed. Contributors travel through the sixteenth, seventeenth, eighteenth, and nineteenth centuries in the place known by many names: the Atlantic World; the North American continent; borderlands; and homelands. Onto this place where people exercised power over space by forging relationships, colonizers came and imagined borders onto maps. Featuring reproductions of twenty historical maps, the book takes readers through this era of immense disruption to teach them strategies for reading and interpreting these maps critically. Essays attend carefully to water alongside land and land alongside water in search of new interpretive avenues that reframe what we know about space, control, and sovereignty. By using historical examples of people--farmers, fishers, hunters, religious leaders, colonial projectors, traders, sailors, soldiers, diplomats, and cartographers, it becomes possible to resist the temptation to impose modern geographical constructs backwards onto the histories we read, teach, and write. Claiming Land, Claiming Water investigates why some of these people imagined and made claims to bounded space, and how and why other people confounded and challenged those claims. Contributors: Sarah Chute, Edward G. Gray, Kim M. Gruenwald, Rachel B. Herrmann, Christian J. Koot, Chad McCutchen, Jennifer Monroe McCutchen, John Morton, Paul Musselwhite, Charles Prior, Karen Rann, Jessica Choppin Roney, Samuel Truett, Harvey Amani Whitfield, Alex Zukas

MedAide: information fusion and anatomy of medical intents via LLM-based agent collaboration

In healthcare intelligence, the ability to fuse heterogeneous, multi-intent information from diverse clinical sources is fundamental to building reliable decision-making systems. Large Language Model (LLM)-driven information interaction systems currently showing potential promise in the healthcare domain. Nevertheless, they often suffer from information redundancy and coupling when dealing with complex medical intents, leading to severe hallucinations and performance bottlenecks. To this end, we propose MedAide, an LLM-based medical multi-agent collaboration framework designed to enable intent-aware information fusion and coordinated reasoning across specialized healthcare domains. Specifically, we introduce a regularization-guided module that combines syntactic constraints with retrieval-augmented generation to decompose complex queries into structured representations, facilitating fine-grained clinical information fusion and intent resolution. Additionally, a dynamic intent prototype matching module is proposed to utilize dynamic prototype representation with a semantic similarity matching mechanism to achieve adaptive recognition and updating of the agent’s intent in multi-round healthcare dialogues. Ultimately, we design a rotation agent collaboration mechanism that introduces dynamic role rotation and decision-level information fusion across specialized medical agents. Extensive experiments are conducted on four medical benchmarks with composite intents. Experimental results from automated metrics and expert doctor evaluations show that MedAide outperforms current LLMs and improves their medical proficiency and strategic reasoning

Attitude strength as a novel predictor of willful ignorance

Willful ignorance is a pervasive phenomenon with significant consequences for decision-making, belief maintenance, and social polarization. While past research has identified various motivational and contextual factors underlying this behavior, less attention has been paid to attitude characteristics that shape the likelihood of engaging in willful ignorance. Addressing this gap, this paper introduces attitude strength as a critical and heretofore unexplored psychological factor that should affect when and why individuals engage in willful ignorance. We argue that strong attitudes, such as those held with certainty, highly accessible, or perceived as morally relevant, are particularly likely to elicit willful ignorance. Drawing on cognitive dissonance theory and motivated reasoning, we synthesize findings across domains, from political partisanship to responses to misinformation and AI-mediated communication

Quality assurance in multi-modality oesophago-gastric cancer clinical trials: past, present and future perspectives

Clinical trials must ensure the quality of both standard and interventional treatments to rigorously evaluate potential benefits, avoid adverse outcomes, and maintain integrity of results. Quality assurance (QA) endeavours to achieve this and is fundamental to all clinical trial elements, though variation exists between specialties. For radiotherapy (RT) in the UK, the NIHR-funded national Radiotherapy Trials Quality Assurance (RTTQA) group has centralised trial RTQA processes across the RT pathway enabling a robust, consistent, efficient and multidisciplinary approach, replacing piecemeal, trial-by-trial application for QA funding. Meanwhile, the surgical community are moving towards standardised QA processes but are yet to achieve this universally. For SACT, though the importance of QA is recognised, under-reporting persists, and the increasing number and diversity of agents used poses challenges. QA in pathology and radiology is also growing as the complexity of clinical trials increases. Internationally, the EORTC have developed QA processes across domains, but uncertainty and challenge in QA implementation remain. Additionally, while the benefits of trial QA are now recognised, the potential negative effects of QA need to be recognised. Using illustrative examples from contemporary oesophago-gastric cancer studies, we further explore the current status of clinical trial QA cross these specialties

Psychological and contextual drivers of indoor air quality behaviours in a deprived urban community: Evidence from participatory research

Indoor air pollution poses significant health risks, disproportionately affecting deprived communities that often face higher levels of exposure. This study, conducted as part of the WellHome project, employed a longitudinal design and a participatory research approach, directly involving 110 residents of a deprived urban area in West London in indoor air quality research. It tested an adapted Health Belief Model (HBM), tailored to indoor air quality behaviours, to examine how perceived vulnerability, perceived severity, self-efficacy, perceptions of indoor and outdoor air quality, and contextual cues to action relate to behavioural changes aimed at improving indoor air quality. It also assessed whether these factors predicted behaviour change over time, and explored patterns across various household behaviours, such as cooking, cleaning, heating, smoking, personal care, home fragrance use, window opening, and air purifier use. Results show that self-efficacy, perceived severity, perceptions of indoor and outdoor air quality, and cues to action were significantly associated with behaviour change, while perceived vulnerability was not. Notably, the influence of self-efficacy on behaviour increased over time, underscoring its role in sustaining long-term change. Visible cues, such as mould and damp, emerged as strong contextual triggers for action. Among the behaviours assessed, changes were most frequently reported in window opening, cooking, and cleaning, although a clear increase in change over time was only observed for cooking and heating. These findings suggest that a participatory approach can be effective in promoting healthier indoor environments in vulnerable communities

Public good or public bad? Nation-building and Indigenous institutions

While existing evidence shows that nation-building policies unify societies, little is known about how and what makes some societal groups to resist them. We examine this in the context of the post-Mexican Revolution (1920s–1950s), when the new state implemented a nation-building policy to eliminate Indigenous cultures and identities by increasing connectivity via transport infrastructure. In a difference-in-differences design, we leverage heterogeneity in the exposure to pre-colonial political centralisation as a proxy for the ability of Indigenous populations in mobilising to resist national integration. We find that the expansion of transport infrastructure was lower in municipalities with a stronger efficacy of Indigenous mobilisation. We demonstrate that this underprovision of public goods can be partly explained by Indigenous identity preservation and high abilities for collective actions

Paleo extreme storm waves in the North Atlantic: geological evidence from Sal Island, Cape Verde Archipelago

The northwestern coast of Sal Island (Cape Verde Archipelago) is characterized by a rocky shoreline that is regularly impacted by Atlantic swells exceeding 4 m in height and 20 s in period. Yet, the only significant geomorphic expression of wave action is an extensive boulder ridge situated atop a rocky cliff, up to 80–100 m inland and between 10 and 15 m above present sea level. The presence of meter-scale boulders within this ridge raises a key question: is it actively shaped by modern storm waves, or is it a relic of paleo storms, impacting the shoreline during an interglacial period when sea level was significantly higher than today? To test this hypothesis, we apply a multidisciplinary approach combining satellite and drone imagery, topographic analysis, hydrodynamic modelling, and empirical boulder transport thresholds. Our results show that under current conditions, storm waves do not reach the ridge and cannot generate sufficient flow to mobilize its largest boulders. However, under modeled higher sea-level scenarios exceeding +5 m, wave runup reaches the ridge, and flow velocities are sufficient to initiate boulder transport by sliding and overturning. We therefore conclude that the ridge is a relict feature, most likely emplaced during Marine Isotope Stage 5e, when relative sea level in Sal Island was 5–7 m higher than today

The influence of viscoelasticity on the dynamics of encapsulated microbubbles near a rigid surface forced by ultrasound

The dynamics of thin-shell encapsulated microbubbles (EMBs) in viscoelastic fluids forced by ultrasound are investigated in this paper. EMBs, which are gas-filled microbubbles encased in a stiff albumin or flexible lipid shell, have been shown to improve the performance of biomedical procedures such as ultrasound contrast imaging and sonoporation. To gain computationally efficient initial insights, the flow is assumed irrotational and axisymmetric, and is solved via the boundary element method. The viscoelastic fluid is modelled using the Oldroyd B model with both the fluid and the properties of the shell accounted for through the dynamic boundary condition at the bubble surface. A large bubble shell thickness is found to have a significant stabilising effect on the bubble, markedly reducing bubble deformation and response to the ultrasound pulse. For realistic ultrasound and biological fluid parameters, shell properties appear to dominate over fluid rheology. Although at lower shell thicknesses the dynamics are governed by a competition between viscous, elastic and inertial forces. A larger response is observed for lower frequency ultrasound and for pressure amplitudes typical to sonoporation, large translational movement in the direction of the pulse is predicted as well as deformation and the potential for bubble fragmentation. The model and quantitative insights herein have the potential to form the basis of a low-cost computational tool useful for EMB design, fabrication and characterisation in the near future

Exploiting independent query information for few-shot image segmentation

This work addresses the challenging task of few-shot segmentation. Previous few-shot segmentation methods mainly employ the information of support images as guidance for query image segmentation. Although some works propose to build a cross-reference between support and query images, their extraction of query information still depends on the support images. In this paper, we propose to extract the information from the query itself independently to benefit the few-shot segmentation task. To this end, we first propose a prior extractor to learn the query information from the unlabeled images with our proposed global–local contrastive learning. Then, we extract a set of predetermined priors via this prior extractor. With the obtained priors, we generate the prior region maps for query images, which locate the objects, as guidance to perform cross-interaction with support features. In such a way, the extraction of query information is detached from the support branch, overcoming the limitation by support, and could obtain more informative query clues to achieve better interaction. Without bells and whistles, the proposed approach achieves new state-of-the-art performance for the few-shot segmentation task on public datasets

Local energy community with a power-to-gas system: A feasibility case study and performance analysis

The transition to local renewable energy communities offers a promising route to decarbonisation, energy security, and system decentralisation. Achieving high renewable shares necessitates highly integrated flexibility through combining multiple energy carriers and storage systems to manage variability and ensure reliability. This study explores the technical, economic, and environmental performance of a hybrid power-to-gas (P2G) system in a UK rural community, incorporating wind and solar generation, battery storage, and hydrogen production. A machine learning-based framework was developed for forecasting key energy system determinants. Among four approaches tested, artificial neural networks (ANN) and random forest (RF) demonstrated high accuracy, with ANN elected for real-time operation due to lower computational requirements. System simulations indicated that 92 % of the community’s annual electricity demand could be supplied by renewables, yielding average electricity cost savings of 54.3 %. Hydrogen blending at a 20 % volume-based scenario reduced gas demand by 6.3 %, while surplus hydrogen produced offered additional revenue potential. Over a 25-year lifetime, total revenues were approximately equal to the capital investment, with a 15-year payback period. These findings highlight the potential of hybrid P2G systems to support net-zero targets at the community level, considering supportive policy and system integration