We address the anti-trans/queer panic integral to the ascendance of authoritarian politics in America and respond by calling on all political scientists to “queer” political science by undoing the cisheteronormativity of the discipline. We contend that this is not the special obligation of LGBTQ scholars but all political scientists. In this we follow Eve Sedgwick’s orientation away from a “minoritizing” to a “universalizing” epistemological perspective that situates this responsibility relative to resisting democratic decline.

The Supreme Court issued its first decision on affirmative action in Regents of the University of California v. Bakke in 1978. Like most conflicts about civil rights in this era, the fight over affirmative action is presumed to involve primarily Black and White Americans. But Bakke cannot be understood without including Latino participants in the origin story. During the 1970s, Latinos’ rates of university enrollment increased more than those of any other group, especially in California, where the case originated. So when Bakke’s legal challenge threatened that access, Latino lawyers, students, and higher education advocates collaborated on a strategic defense of affirmative action. They drafted legal briefs, formed regional and national committees, and took to the streets. First in California and then in the East and Midwest, Latinos worked to shape the national discussion over the value of affirmative action and to protect their hard-won gains in higher education.

Although nudges have been shown to influence many choices, it is possible that nudging may also result in undesirable consequences compared to other choice architectures (e.g., educational boosts). Here, we present evidence of one such case involving recycled water acceptance. In two experiments, we compared the effects of a popular nudge (i.e., defaults designed to increase acceptance) with an educational boost (e.g., a brief video designed to support informed decision making). Results revealed that both defaults and educational boosts substantially increased choices related to recycled water acceptance (e.g., >60% increase in enrollment in a hypothetical recycled water program across experiments). However, the educational boost also promoted choice-consistent effects on attitudes, intentions, and knowledge, while default nudges resulted in attitude inconsistency (e.g., expressing worry about recycled water; intending to protest and avoid water recycling). Results add to research on practical and ethical risks of nudging and the potential benefits of comparing the costs of nudges with other options.

Integrating trees and shrubs into agroecosystems increases soil nutrients and organic matter, which helps in the recovery of degraded tropical soils. However, selecting the most appropriate tree and shrub species as sources of nutrients and organic matter requires knowledge of their productive potential. The study aimed to evaluate litter productivity and nutrient input to the soil of three tropical silvopastoral fodder bank species. Litter input from Tithonia diversifolia, Leucaena leucocephala, and Moringa oleifera was quantified monthly for one year. We found that the litterfall amount was greatest (p < 0.05) from T. diversifolia (1.81 t ha–1 yr–1) compared to L. leucocephala (1.26 t ha–1 yr–1) and M. oleifera (118 t ha–1 yr–1). Indeed, T. diversifolia had a greater (p < 0.05) input of biomass from leaves (1.36 t ha–1 yr–1) compared to L. leucocephala (0.901 t ha–1 yr–1) and M. oleifera (0.869 t ha–1 yr–1). The highest biomass input (p < 0.05) occurred in September to the three species, T. diversifolia (0.516 t ha–1), L. leucocephala (0.243 t ha–1), and M. oleifera (0.233 t ha–1), and the lowest biomass input occurred in March. Furthermore, the greatest annual input of carbon (0.687 t ha–1 yr–1), nitrogen (0.030 t ha–1 yr–1), and phosphorus (0.006 t ha–1 yr–1) to the soil originated from T. diversifolia. Our study showed that T. diversifolia had the greatest capacity to produce biomass that potentially can reintroduce nutrients and contribute to the recovery process of degraded soil due to its high litter productivity, besides, a combination of these three species also improves soil nutrients in fodder banks when do not hauling forage for livestock, contributing to sustainability of system.

We consider families of special cycles, as introduced by Kudla, on Shimura varieties attached to anisotropic quadratic spaces over totally real fields. By augmenting these cycles with Green currents, we obtain classes in the arithmetic Chow groups of the canonical models of these Shimura varieties (viewed as arithmetic varieties over their reflex fields). The main result of this paper asserts that generating series built from these cycles can be identified with the Fourier expansions of non-holomorphic Hilbert-Jacobi modular forms. This result provides evidence for an arithmetic analogue of Kudla’s conjecture relating these cycles to Siegel modular forms.

Scholars have identified several temporal challenges in foreign policymaking, such as variable time horizons and maintaining commitment or resolve over time. While the behavioural turn has emphasised leaders and their subjective perceptions, research often relies on rationalist conceptions of objective and linear time and struggles to assess leaders’ subjective perceptions of it. This paper theorises time as an intrinsic aspect of narrative reasoning in foreign policy, introducing a ‘temporal definition of the situation’ (TDoS) framework to capture leaders’ situation-specific subjective time perceptions. I then operationalise the TDoS framework’s key temporal features and show how it can be empirically examined. The value of the TDoS is illustrated by assessing the temporal perceptions of Bush and Obama regarding Iran’s nuclear programme, showing how their distinct definitions of the foreign policy situation shaped their subjective time perceptions and their corresponding responses. I conclude by discussing how this advancement can enhance behavioural research, provide insights into the ‘why now?’ questions surrounding leaders’ actions, and challenge existing understandings of time’s impact on foreign policymaking.

This paper documents the details of the design, verification, and certification of a novel technology: a remote monitoring system (digital twin) for a voyage data recorder, referred to as the HermAce Gateway. The electronic components, data transfer, and storage principle explain how the HermAce Gateway communicates and records safety-critical messages. Various prospective benefits to the industry are provided, primarily regarding the opportunities for remote support and testing that the digital twin facilitates. The HermAce Gateway was independently verified through a combination of semi-automated software in the loop and selected complimentary hardware in the loop tests. Different types of communication were simulated in multiple ways, including approximating real-world scenarios. Alarms contained in correctly formed messages were found to be detected and recorded by the HermAce Gateway, and a discussion of how this evidence can be quantified in the context of reducing uncertainty in the reliability of a digital twin. Certification of a digital system is a new concept in the maritime industry. The identification of functional requirements, which informed the verification testing, and the development of an AI register for what is expected to be an increasing number of such systems are also documented.

This article examines the impact of generative artificial intelligence (GAI) on higher education, emphasizing its effects in the broader educational contexts. As AI continues to reshape the landscape of teaching and learning, it is imperative for higher education institutions to adapt rapidly to equip graduates for the challenges of a progressively automated global workforce. However, a critical question emerges: will GAI lead to a more inclusive future of learning, or will it deepen existing divides and create a future where educational access and success are increasingly unequal? This study employs both theoretical and empirical approaches to explore the transformative potential of GAI. Drawing upon the literature on AI and education, we establish a framework that categorizes the essential knowledge and skills needed by graduates in the GAI era. This framework includes four key capability sets: AI ethics, AI literacy (focusing on human-replacement technologies), human–AI collaboration (emphasizing human augmentation), and human-distinctive capacities (highlighting unique human intelligence). Our empirical analysis involves scrutinizing GAI policy documents and the core curricula mandated for all graduates across leading Asian universities. Contrary to expectations of a uniform AI-driven educational transformation, our findings expose significant disparities in AI readiness and implementation among these institutions. These disparities, shaped by national and institutional specifics, are likely to exacerbate existing inequalities in educational outcomes, leading to divergent futures for individuals and universities alike in the age of GAI. Thus, this article not only maps the current landscape but also forecasts the widening educational gaps that GAI might engender.

Variation between general practices in the rate of consultations for musculoskeletal pain conditions may signal important differences in access to primary care, perceived usefulness, or available alternative sources of care; however, it might also just reflect differences in underlying ‘need’ between practices’ registered populations. In a study of 30 general practices in Staffordshire, we calculated the proportion of adults consulting for a musculoskeletal pain condition, then examined this in relation to selected practice and population characteristics, including the estimated prevalence of self-reported musculoskeletal problems and chronic pain in each practices’ registered population. Between September 2021 and July 2022, 18,388 adults were consulted for a musculoskeletal pain condition. After controlling for length of recruitment, time of year, and age-sex structure, the proportion consulting varied up to two-fold between practices but was not strongly associated with the prevalence of self-reported long-term musculoskeletal problems, chronic pain, and high-impact chronic pain.

Composer-Performer Collaboration (CPC) has become a distinct research field in the last twenty years. This article explores a long letter written by Justin Connolly to Neil Heyde in place of final workshops for Collana, for solo cello. The letter sheds forensic light on Connolly’s musical vision and approach to collaboration, revealing a distinctive combination of pedantic concern for details (with concomitant precision of notation) and great flexibility. Connolly encourages the performer as an active participant, with responsibility for a ‘parallel universe of discourse’. Heyde responds directly to extracts from the letter and outlines the shared working context. Connolly’s letter confirms the significance of the dimensions of notation, gesture and instrumental choreography that have emerged in the CPC literature but affords a perspective not shaped by academic demand characteristics. It presents an especially sophisticated approach to what recent writing has called empathetic embodiment.

Research on the political consequences of terrorism often finds a rally around the flag effect: terrorist attacks, as other types of threats, tend to produce spikes in popularity and support for the incumbent, as citizens turn to those in power seeking protection. Most research, however, is based on single case studies that analyze very salient attacks from international terrorist organizations. Even if these studies are well identified, the question of generalizability remains, as the studied attacks are often very idiosyncratic. In this paper, we explore the rally around the flag effect in an arguably difficult context: a sustained terrorist campaign held by domestic terrorist groups in a parliamentary democracy (Spain). To overcome the limitations of the single-attack studies, we use a multiple unexpected event approach: we developed a systematic process of matching the occurrence of terror attacks during the fieldwork of official public opinion surveys in Spain, through which we identified 142 valid attack-survey pairs. We find that in the attacked region support for the incumbent increases, on average, around 4 percentage points right after an attack, while support for the opposition decreases in a similar amount. These effects seem to occur mostly for the conservative incumbent and are especially relevant for the attacks that target civilians. We use a survey experiment to provide additional evidence in support for our interpretation of the findings.

Automatic precision herbicide application offers significant potential for reducing herbicide use in turfgrass weed management. However, developing accurate and reliable neural network models is crucial for achieving optimal precision weed control. The reported neural network models in previous research have been limited by specific geographic regions, weed species, and turfgrass management practices, restricting their broader applicability. The objective of this research was to evaluate the feasibility of deploying a single, robust model for weed classification across a diverse range of weed species, considering variations in species, ecotypes, densities, and growth stages in bermudagrass turfgrass systems across different regions in both China and the United States. Among the models tested, ResNeXt152 emerged as the top performer, demonstrating strong weed detection capabilities across 24 geographic locations and effectively identifying 14 weed species under varied conditions. Notably, the ResNeXt152 model achieved an F1 score and recall exceeding 0.99 across multiple testing scenarios, with a Matthews correlation coefficient (MCC) value surpassing 0.98, indicating its high effectiveness and reliability. These findings suggest that a single neural network model can reliably detect a wide range of weed species in diverse turf regimes, significantly reducing the costs associated with model training and confirming the feasibility of using one model for precision weed control across different turf settings and broad geographic regions.