This paper addresses the challenge of obtaining accurate finite element model updating (FEMU) results for complex flexible aircraft structures without relying on prohibitively large numbers of direct finite element evaluations. An adaptive two-stage framework is proposed by integrating Bayesian regularisation neural networks (BR-ANN) with trust-region resampling. In the global stage, a coarse-grained surrogate model is constructed via Latin hypercube sampling (LHS) and Bayesian inference, enabling the non-dominated sorting genetic algorithm II (NSGA-II) to identify the Pareto-front region containing promising candidate solutions. Subsequently, a trust-region strategy performs high-fidelity resampling within the local neighbourhood of the knee-point solution, establishing a refined surrogate model that reduces local surrogate bias and improves parameter convergence. Validation using the GARTEUR SM-AG19 benchmark aircraft demonstrates that the proposed method effectively mitigates the smoothing effect inherent in conventional global surrogate models while maintaining computational efficiency. The average modal frequency error was reduced from 4.56% to 2.39%, and the method supports physically interpretable updating of material and equivalent beam parameters, providing a reliable baseline for subsequent aeroelastic predictions.

Banco do Brasil played a central role in Brazil’s macroeconomic management during the Military Regime (1964–1985), a period marked by ambitious development strategies and heightened monetary instability. While previous research has emphasized its involvement with the Treasury and balance-of-payments financing, the broader scope of its functions has remained underexplored. Drawing on newly digitized balance-sheet data, this article reconstructs and classifies Banco do Brasil’s operations across its main areas of activity. It shows that Banco do Brasil acted as a multipurpose policymaking institution, mediating between competing objectives of growth, stabilization, and external adjustment. By tracing changes over time, the article highlights how Banco do Brasil’s functions evolved with shifting policy priorities across military governments, revealing a more complex and adaptive role in shaping Brazil’s macroeconomic outputs.

Śrīvidyā is a Tantric tradition which includes a form of religious initiation into an esoteric practice. Descriptions of initiation allude to and often describe the initiator sharing an experience with the initiand. In this article, we will suggest that such experiences can be understood in terms of a ‘shared token experience’. To make a case for taking such an experience into account, we use an argument for the epistemic value of religious experience. Our defence of the sharing of token experience across subjects also opens up questions as to the limits of consciousness or subjecthood. The phenomenon of Śrīvidyā initiatory experience also undermines two assumptions regarding what it means to be a subject. The first assumption is that each conscious subject is a unified whole insofar as its different experiential parts are mereologically connected to one subject. The second assumption is that each subject’s experiential field is bounded to one subject such that no two subjects can share the same experiential field. We argue that these assumptions do not necessarily preclude the possibility of a shared token experience.

Black constituents often receive lower-quality responsiveness from elected officials, particularly white representatives. This issue is exacerbated by partisan gerrymandering, which packs Black voters into districts with high majority populations. This trend has led to heightened concerns about increased vote dilution for minority and Democratic voters. This poses an important question: do legislators respond to shifts in their district’s racial demographics? Using data from before and after the 2010 redistricting cycle, we examine whether MCs engaged in policy responsiveness to Black constituents. Consistent with prior research, MCs did not sponsor or cosponsor more civil rights bills in response to increases in their Black constituency. However, Democratic MCs are more likely to mention civil rights in floor speeches, and Republican MCs are more likely to vote on bills in a manner consistent with LCCR priorities. These findings provide new insight into the representation Black Americans receive in Congress.

Natural language processing (NLP) has moved from a specialized research field into the everyday infrastructure of writing, search, translation, education, journalism, public administration, and scientific work. This transition changes what counts as progress. Accuracy, fluency, and benchmark performance remain important, but they are no longer sufficient when language technologies shape knowledge, decisions, identities, and public trust. This column introduces Responsible NLP as a research orientation that integrates fairness, transparency, privacy, safety, cultural diversity, environmental awareness, and human agency across the full life cycle of language technologies. It argues that responsibility is not an external constraint on innovation, but a condition for meaningful and trustworthy innovation. Future research must therefore ask not only whether an NLP system works but also for whom it works, under which assumptions, with what risks, and with what forms of accountability.

Across 13 surveys of 590 residents in seven ventilator-capable SNFs, residents in ventilator-designated beds had markedly higher ESBL (48.1% vs 28.2%; aOR = 1.64) and C. auris (38.6% vs 15.2%, aOR = 2.89), but lower MRSA colonization (35.2% vs 45.5%; aOR = 0.47), supporting the need for MDRO prevention beyond current Enhanced Barrier Precautions.

This article considers how European mountaineers, Bolivian elites, and Aymara communities perceived mountains, glaciers, and one another in the final years of the nineteenth century at the height of a campaign to dispossess Indigenous communities’ land and determined Aymara resistance. To do so, it takes a microhistorical approach, focusing on the interactions among Aymara community members, members of the Sociedad Geográfica de La Paz, and British mountaineer Martin Conway and his Swiss guides during Conway’s 1898 climbs in the Cordillera Real. Each of these groups was devoted to glaciated mountains, but in different ways and for diverging purposes. While Aymaras revered mountains as powerful ancestral deities, paceño geographers valued them as sites of marketable resources. For foreign mountaineers, glaciated peaks were sites for adventure, conquest, and profit. Divergent approaches to mountains and glaciers led to conflicts between foreign mountaineers and Aymara community members rooted in deeper disputes over race, gender, and nature.

Force/motion transmissibility serves as an essential performance metric in the kinematic analysis of parallel mechanisms. The initial step in evaluating force/motion transmissibility involves identifying the basis elements of twist and wrench spaces. In parallel mechanisms consisting of PRS, RPS, SPR, and PU limbs, the identification of the basis elements of a given limb is relatively straightforward, as the limb constraints can be evaluated as pure forces and torques. However, in limbs where the axes of the joints are offset, determining these basis elements becomes quite complex. Typically, the constraints of these limbs involve the interconversion between general screws and line vectors or couples. This paper focuses on a 3-PRRU parallel mechanism. Procedures for identifying the basis elements are investigated. Screw theory is used to elucidate the relationships between the variations in the basis elements and the configurations of the mechanism. Moreover, the influence of an offset between two revolute joint axes on the force/motion transmissibility is systematically analyzed. The results indicate that, compared to the case without offsets, the introduction of offsets enhances the force transmissibility of the mechanism.

We possess a limited understanding of Indigenous electoral behavior, partisanship, and political attitudes. Previous research has mainly focused on explaining Indigenous electoral abstention and has faced constraints, mainly because of small sample sizes. Drawing on data from both the 2019 and 2021 Canadian Election Studies, which encompass an unprecedented number of First Nations, Inuit, and Métis respondents, we explore Indigenous electoral behavior, partisanship, and attitudes toward public spending at the federal level in Canada. We show that while Indigenous respondents remain more likely to consider abstention, they can also be more supportive of third parties than their non-Indigenous counterparts and adopt views spanning the traditional left–right ideological spectrum. These findings encourage a redefinition of the expectations regarding the political behaviors and attitudes of Indigenous Peoples in order to fully engage with diverse political cultures.

In this paper, we explore the concept of modularity in first-order answer set programming (ASP). We introduce a new formalism called parametric modular logic programs, which allows defining subprograms with parameters and intensionality statements. We demonstrate how this formalism can capture the semantics of clingo-programs with collective control, a feature that enables structuring and instantiating subprograms. We provide theoretical foundations for modular ASP, illustrate its usefulness, and connect to traditional non-modular ASP.

Functional neurosurgery can modulate the pathological brain circuits that underlie psychiatric symptoms. For select disorders it is safe, precise and evidence-based; for others, it holds real promise. Nevertheless, referrals remain strikingly low relative to the burden of refractory illness – a gap that could be meaningfully addressed by closer psychiatry–neurosurgery collaboration.

Artificial Intelligence (AI) systems are increasingly supporting targeting, intelligence analysis and operational planning across military domains, reshaping how commanders use force through human–machine teaming (HMT). HMT offers operational advantages, but risks such as automation bias, adversarial manipulation and degraded performance pose challenges for the ability of deployers to use AI systems in compliance with international humanitarian law (IHL). This article argues that adherence to IHL cannot be deferred until hostilities arise; system design, testing, governance and training must be structured in advance to establish the conditions under which AI-enabled human–machine teams can exercise appropriate human judgement consistent with IHL obligations. The paper proposes an HMT Assurance Card, a cross-disciplinary life-cycle instrument integrating IHL obligations, civilian harm pattern analysis and AI governance frameworks into measurable standards applicable across the AI system life cycle, defence institutions and coalition environments.