China was one of the world's most important areas of growth in wine demand in the 2010s, accounting for 7% of the world's wine consumption and 8% of its value of wine imports by 2017. But China's per capita wine consumption peaked in the mid-2010s, and its wine imports have more than halved since then. As well, the sources of China's imports of wine have fluctuated considerably over the past two decades, making this a risky market for wine exporters. Certainly, the COVID-19 disruption played a role, but between 2019 and 2022, the fall in sales was considerably larger for wine (47%) than for spirits (17%) and beer (9%), such that wine's share of alcohol consumption in China fell by two-fifths over those 3 years alone. The article examines the reasons behind the dramatic gyrations in this globally important market and their impact on wine-exporting countries, and speculates on future trends.

Adaptation to climate change requires robust climate projections, yet the uncertainty in these projections performed by ensembles of Earth system models (ESMs) remains large. This is mainly due to uncertainties in the representation of subgrid-scale processes such as turbulence or convection that are partly alleviated at higher resolution. New developments in machine learning-based hybrid ESMs demonstrate great potential for systematically reduced errors compared to traditional ESMs. Building on the work of hybrid (physics + AI) ESMs, we here discuss the additional potential of further improving and accelerating climate models with quantum computing. We discuss how quantum computers could accelerate climate models by solving the underlying differential equations faster, how quantum machine learning could better represent subgrid-scale phenomena in ESMs even with currently available noisy intermediate-scale quantum devices, how quantum algorithms aimed at solving optimization problems could assist in tuning the many parameters in ESMs, a currently time-consuming and challenging process, and how quantum computers could aid in the analysis of climate models. We also discuss hurdles and obstacles facing current quantum computing paradigms. Strong interdisciplinary collaboration between climate scientists and quantum computing experts could help overcome these hurdles and harness the potential of quantum computing for this urgent topic.

With the passage of the 1935 National Labor Relations Act (NLRA), the American labor movement cemented the right to form unions and engage in collective bargaining. However, the NLRA explicitly excluded the public sector. Government employees did not achieve similar legal protections until decades later, and even then, the laws varied considerably by state. Because of this, scholarly accounts of the development of public-sector unions usually start in the 1960s and emphasize how public- and private-sector unions developed along separate paths. In this article, we analyze a new dataset and show that hundreds of cities had organized workers during the 1920s, 1930s, and 1940s, including firefighters, police, and other public-sector workers (like those in the sanitation and roads departments). By the 1950s, numerous employee unions had engaged in strikes and had achieved written agreements with their city employers. We also present evidence that public- and private-sector employee organization were correlated during this period. Thus, despite very different legal contexts before 1960, our evidence suggests that the timing and location of early public-sector organization may have had more in common with private-sector organization than is often recognized.

Due to the ever-increasing complexity of technical products, the quantity of system requirements, which are typically expressed in natural language, is inevitably rising. Model-based formalization through the application of Model-based Systems Engineering is a common solution to cope with rising complexity. Thereby, grouping requirements to use cases forms the first step towards model-based requirements and allows to improve the understanding of the system. To support this manual and subjective task, automation by artificial intelligence and methods of natural language processing are needed. This contribution proposes a novel pipeline to derive use cases from natural language requirements by considering incomplete manual mappings and the possibility that one requirement contributes to multiple use cases. The approach utilizes semi-supervised requirements graph generation with subsequent overlapping graph clustering. Each identified use case is described by keyphrases to increase accessibility for the user. Industrial requirement sets from the automotive industry are used to evaluate the pipeline in two application scenarios. The proposed pipeline overcomes limitations of prior work in the practical application, which is emphasized by critical discussions with experts from the industry. The proposed pipeline automatically generates proposals for use cases defined in the requirement set, forming the basis for use case diagrams.

A hidden consequence of the cumulative impact of poverty, ‘hygiene poverty’ compels people to make stark choices when allocating household budgets. To increase understanding of this understudied phenomenon, we explored the prevalence of factors leading to, and impacts of, hygiene poverty in Ireland. An online survey was completed by 258 respondents during September 2023 covering a broad range of topics relating to the affordability of hygiene products. The results were analysed to identify key themes of statistical relevance in the data. Our study found 65.1 per cent of respondents had personally experienced difficulty affording essential hygiene items. Whilst lower incomes and the presence of children in the household featured, inability to afford hygiene items was also felt by those in insecure housing, people with disabilities and those from ethnic minorities. Lack of access to basic essentials prevented people from engaging fully in social, work and educational activities with negative impacts on physical and mental health across all income brackets. Drawing on existing literature alongside reporting original research, the substantive argument in this article suggests that ‘hygiene poverty’ is most usefully thought of as an aspect of deprivation, and that hygiene-related needs often sit at the bottom of a range of deprivation types.

Data governance has emerged as a pivotal area of study over the past decade, yet despite its growing importance, a comprehensive analysis of the academic literature on this subject remains notably absent. This paper addresses this gap by presenting a systematic review of all academic publications on data governance from 2007 to 2024. By synthesizing insights from more than 3500 documents authored by more than 9000 researchers across various sources, this study offers a broad yet detailed perspective on the evolution of data governance research.

Mentorship is a vital part of the training provided in the K and T programs funded by the Clinical and Translational Science Awards (CTSA). However, the inputs, indicators, and outcomes associated with a successful mentoring relationship remain poorly understood. In this review, we critically examine the current body of literature on mentorship in a CTSA context. We conducted a comprehensive search of the literature for relevant research articles. We included articles that were contextualized within a CTSA hub, examined a mentorship program, and conducted evaluation research. Through an initial search of online databases and by reviewing reference sections of relevant articles, we identified 141 potentially relevant articles. Twenty-five of these articles met our inclusion criteria. We identified three categories of research: nationwide institutional surveys of CTSA mentorship programs, mentored research training programs, and mentor training programs. While the findings highlighted the effectiveness of mentor training and mentored training programs, there is a notable lack of assessment of mentoring inputs and indicators. Based on our review, we propose a model for the evaluation of CTSA mentorship that includes measurable inputs, indicators, and outcomes. This model provides a holistic framework for evaluators and CTSA program directors to better understand their mentorship programs.

Since the early 2000s, the US Government has made purposeful investments to help ensure medical preparedness should a radiological or nuclear incident occur within its borders. This focused support of products to diagnose, mitigate, and treat radiation-induced bodily injuries that would be anticipated during a radiation public health emergency has involved many departments, ranging from multiple agencies within the Department of Health and Human Services to the Department of Defense. The intent of this manuscript is to convey information both on products that have been approved by the US Food and Drug Administration for radiation injuries during a radiation incident, as well as promising approaches under advanced stages of development. These products impact multiple organ systems (e.g., bone marrow, gastrointestinal tract, lungs, kidneys, skin) and have been tested for efficacy in a number of different small and large preclinical animal models. The successful development of these models, methods, products, and devices discussed herein demonstrate the importance of an intentionally collaborative, “one-government” approach to fostering radiation research, while also showcasing the need for critical public-private partnerships – all to ensure the safety of the public should the unthinkable occur.

The adoption of a feminist foreign policy (FFP) by Mexico took Mexican feminist civil society by surprise. In September 2019, without prior consultations or dialogues with local feminist civil society, the Mexican Foreign Affairs Secretary announced its FFP during the 74th session of the UN General Assembly. While the UN New York City headquarters roared with applause in response to the Mexican Foreign Affairs Secretary’s claim that the “Mexican government is feminist,” many feminists in Mexico interpreted the statement as an effort to pinkwash the government’s poor track record on gender equality within its borders. Moreover, Mexico’s FFP was charged with racial and colonial undertones since its inception, colloquially known as the “first FFP from the Global South” (Thompson 2020; Thompson, Ahmed, and Khokhar 2021).

Designers often rely on their self-evaluations – either independently or using design tools – to make concept selection decisions. When evaluating designs for sustainability, novice designers, given their lack of experience, could demonstrate psychological distance from sustainability-related issues, leading to faulty concept evaluations. We aim to investigate the accuracy of novice designers’ self-evaluations of the sustainability of their solutions and the moderating role of their (1) trait empathy and (2) their beliefs, attitudes and intentions toward sustainability on this accuracy. We conducted an experiment with first-year engineering students comprising a sustainable design activity. In the activity, participants evaluated the sustainability of their own designs, and these self-evaluations were compared against expert evaluations. We see that participants’ self-evaluations were consistent with the expert evaluations on the following sustainable design heuristics: (1) longevity and (2) finding wholesome alternatives. Second, trait empathy moderated the accuracy of self-evaluations, with lower levels of fantasy and perspective-taking relating to more accurate self-evaluations. Finally, beliefs, attitudes and intentions toward sustainability also moderated the accuracy of self-evaluations, and these effects vary based on the sustainable design heuristic. Taken together, these findings suggest that novice designers’ individual differences (e.g., trait empathy) could moderate the accuracy of the evaluation of their designs in the context of sustainability.

This article argues that a relational and trust-based understanding of fides can explain its use and impact in a variety of secular and religious settings, but particularly between members of different religious communities and especially in commercial contracts. The Latin word fides can be translated in a variety of ways, from ‘faith’, ‘trust’ and ‘trustworthiness’, to ‘proof’ and ‘belief’. Within these meanings there are complex religious and legal implications. Most understandings focus on the ways in which the term defines and creates relationships within a community. Contracts from thirteenth- and fourteenth-century Barcelona and Mallorca demonstrate the meaning and significance of the use of the term between merchants and investors from different religious communities. The article provides a new understanding of the place of faith language within the creation of trusting relationships.

The aim of the study is to compare the use of two different particles that are used in Icelandic conversation: the native form ha and the English borrowing what. The research questions are as follows: (1) What are the similarities and differences between the two forms in terms of turn-position, sequential placement, prosody, and functions?, and (2) What can the comparison tell us about the borrowing of discourse particles from one language to another? The data consisted of 28 hours and 36 minutes of conversation. The methodology employed in the study is that of interactional linguistics. The study shows that although ha and what have some similarities in certain environments, there are certain differences between the two forms. What is more limited in use than ha, both in terms of functions and position within a turn.

Cover crops (CCs) are a component of the integrated weed management strategies for controlling herbicide-resistant weed biotypes. A field study was conducted at Kansas State University Agricultural Research Center near Hays, KS, from 2021 to 2024 to determine the effect of spring-planted CCs in combination with residual herbicide on weed suppression during fallow phase and subsequent wheat yield in a no-till winter wheat (Triticum aestivum L.)–grain sorghum [Sorghum bicolor (L.) Moench]–fallow rotation in the semiarid Central Great Plains (CGP). The study site had a natural seedbank of glyphosate-resistant (GR) kochia [Bassia scoparia (L.) A.J. Scott] and Palmer amaranth (Amaranthus palmeri S. Watson). A mixture of CCs (oats [Avena sativa L.]–barley [Hordeum vulgare L.]–spring peas [Pisum sativum L.]) was spring-planted in no-till sorghum stubbles and terminated at the oats heading stage. Four treatments were tested: (1) weedy fallow (no CC and no herbicide), (2) chemical fallow (no CC but glyphosate + flumioxazin/pyroxasulfone + dicamba), (3) CC terminated with glyphosate, and (4) CC terminated with glyphosate + flumioxazin/pyroxasulfone. Across 3 yr, CC at termination reduced total weed density by 78% to 99% and total weed biomass by 93% to 99% compared with weedy fallow. Weed suppression by the CC terminated with glyphosate plus flumioxazin/pyroxasulfone continued for at least 90 d with reduced total weed density of 52% to 80% and total weed biomass reduction by 70% compared with weedy fallow across 3 yr. No differences in subsequent wheat grain yield between CC treatments and chemical fallow were recorded in 2021 to 2022 and 2022 to 2023; however, in 2023 to 2024, chemical fallow and CC terminated with glyphosate + flumioxazin/pyroxasulfone had greater wheat yield than CC terminated with glyphosate only. These results suggest that integration of spring-planted CC with residual herbicide may help suppress GR B. scoparia and A. palmeri in the CGP.