We measure the other-regarding behavior in samples from three related populations in the upper Midwest of the United States: college students, non-student adults from the community surrounding the college, and adult trainee truckers in a residential training program. The use of typical experimental economics recruitment procedures made the first two groups substantially self-selected. Because the context reduced the opportunity cost of participating dramatically, 91 % of the adult trainees solicited participated, leaving little scope for self-selection in this sample. We find no differences in the elicited other-regarding preferences between the self-selected adults and the adult trainees, suggesting that selection is unlikely to bias inferences about the prevalence of other-regarding preferences among non-student adult subjects. Our data also reject the more specific hypothesis that approval-seeking subjects are the ones most likely to select into experiments. Finally, we observe a large difference between self-selected college students and self-selected adults: the students appear considerably less pro-social.

When we open a random political science journal, we have a roughly two-to-one chance that the article is written by a man. Beyond this general finding, we know little about the gender gaps within political science knowledge production: Are women more represented in lower- or higher-ranked journals? Do they publish more single-authored or multiauthored papers? Do they publish more content in some fields than in others? This article answers these questions by analyzing an original dataset based on the International Political Science Abstracts (a peer-reviewed academic journal) from 2022 consisting of more than 7,000 articles and more than 13,000 authors in political science from around the world. We find no difference in the percentage of female authors between higher- and lower-ranked journals. We find a slightly higher propensity among women to publish in teams. Regarding subfields of study, women are particularly underrepresented in political theory, in which they publish only 21.6% of all published articles—which is an approximate 12-percentage-point deviation from the overall average.

This essay celebrates the BU Health Law Program upon its 70th anniversary, offering reflections on the founders of the program, Fran Miller, George Annas, and Wendy Mariner (“FGW,” endearingly), and their contributions to the field.

Current faculty offer reflections, including: Several speak to scholarly research, including Elizabeth McCuskey on health care finance, Aziza Ahmed on human rights, Dionne Lomax on antitrust, Christopher Robertson on trust, and Kathy Zeiler on the marketplace. Other contributors speak to the student experience, with Dianne McCarthy on mentorship, Laura Stephens on demanding excellence, Michael Ulrich on teaching, and Larry Vernaglia on merging law and public health. On FGW’s broader impacts, Nicole Huberfeld speaks to the translation of research to reach new audiences, and Kevin Outterson writes about FGW’s pivotal roles in establishing the health law field and the institutions that now define it.

Together these pieces testify to the astounding contributions of these scholar-teacher-leaders across many domains and dimensions of health law. While their contributions are countless and immeasurable, these reflections offer a start.

Discussions of George Berkeley often dismiss his Notebooks remarks that (1) bodies are powers that cause perceivers to have thoughts, and (2) bodies exist even when they are not perceived. I have previously noted these claims but have not explained how bodies are infinitely linked as thoughts (vs. ideas), and Melissa Frankel treats bodies as archetypes perceived individually by God but does not explain how they are individuated. I argue that because bodies identify objects only for finite minds, they are derivative powers by which individuated objects are related to one another infinitely.

The use of face masks has been widely promoted and at times mandated to prevent coronavirus disease 2019 (COVID-19). The 2023 publication of an updated Cochrane review on mask effectiveness for respiratory viruses as well as the unfolding epidemiology of COVID-19 underscore the need for an unbiased assessment of the current scientific evidence. It appears that the widespread promotion, adoption, and mandating of masking for COVID-19 were based not primarily on the strength of evidence for effectiveness but more on the imperative of decision-makers to act in the face of a novel public health emergency, with seemingly few good alternatives. Randomized clinical trials of masking for prevention of COVID-19 and other respiratory viruses have so far shown no evidence of benefit (with the possible exception of continuous use of N95 respirators by hospital workers). Observational studies provide lower-quality evidence and do not convincingly demonstrate benefit from masking or mask mandates. Unless robust new evidence emerges showing the effectiveness of masks in reducing infection or transmission risks in either trials or real-world conditions, mandates are not warranted for future epidemics of respiratory viral infections.

A high-charge smectite from Arizona [cation-exchange capacity (CEC) = 120 meq/100 g] and a low-charge smectite from Wyoming (CEC = 90 meq/100 g) were used to prepare homoionic tetra-methylammonium (TMA)-clay complexes. The adsorption of benzene, toluene, and o-xylene as vapors by the dry TMA-clays and as solutes from water by the wet TMA-clays was studied. The adsorption of the organic vapors by the dry TMA-smectite samples was strong and apparently consisted of interactions with both the aluminosilicate mineral surfaces and the TMA exchange ions in the interlayers. In the adsorption of organic vapors, the closer packing of TMA ions in the dry high-charge TMA-smectite, compared with the dry low-charge TMA-smectite, resulted in a somewhat higher degree of shape-selective adsorption of benzene, toluene, and xylene. In the presence of water, the adsorption capacities of both samples for the aromatic compounds were significantly reduced, although the uptake of benzene from water by the low-charge TMA-smectite was still substantial. This lower sorption capacity was accompanied by increased shape-selectivity for the aromatic compounds. The reduction in uptake and increased selectivity was much more pronounced for the water-saturated, high-charge TMA-smectite than for the low-charge TMA-smectite. Hydration of the TMA exchange ions and/or the mineral surfaces apparently reduced the accessibility of the aromatic molecules to interlamellar regions. The resulting water-induced sieving effect was greater for the high-charge TMA-smectite due to the higher density of exchanged TMA-ions. The low-charge Wyoming TMA-smectite was a highly effective adsorbent for removing benzene from water and may be useful for purifying benzene-contaminated water.

OpenAI is a research organization founded by, among others, Elon Musk, and supported by Microsoft. In November 2022, it released ChatGPT, an incredibly sophisticated chatbot, that is, a computer system with which humans can converse. The capability of this chatbot is astonishing: as well as conversing with human interlocutors, it can answer questions about history, explain almost anything you might think to ask it, and write poetry. This level of achievement has provoked interest in questions about whether a chatbot might have something similar to human intelligence and even whether one could be conscious. Given that the function of a chatbot is to process linguistic input and produce linguistic output, we consider that the most interesting question in this direction is whether a sophisticated chatbot might have inner speech. That is: might it talk to itself, internally? We explored this via a conversation with ‘Playground’, a chatbot which is very similar to ChatGPT but more flexible in certain respects. We put to it questions which, plausibly, can only be answered if one first produces some inner speech. Here, we present our findings and discuss their philosophical significance.

We introduce an original dataset of formal political participation for over 2,000 individuals included in the Forbes Billionaires List. We find that billionaire politicians are a surprisingly common phenomenon: Over 11% of the world’s billionaires have held or sought political office. Even compared to other elite groups known for producing politicians from their ranks, this is a high rate of political participation. Moreover, billionaires focus their political ambitions on influential positions, have a strong track record of winning elections, and lean to the right ideologically. We also document substantial cross-national variation: a country’s number of billionaire politicians is not simply a product of its total number of billionaires, but is instead related to regime type. Specifically, billionaires formally enter the political sphere at a much higher rate in autocracies than in democracies. We conclude by discussing the normative implications of our findings and outlining a new research agenda on billionaire politicians.

The U.S. Department of Agriculture–Agricultural Research Service (USDA-ARS) has been a leader in weed science research covering topics ranging from the development and use of integrated weed management (IWM) tactics to basic mechanistic studies, including biotic resistance of desirable plant communities and herbicide resistance. ARS weed scientists have worked in agricultural and natural ecosystems, including agronomic and horticultural crops, pastures, forests, wild lands, aquatic habitats, wetlands, and riparian areas. Through strong partnerships with academia, state agencies, private industry, and numerous federal programs, ARS weed scientists have made contributions to discoveries in the newest fields of robotics and genetics, as well as the traditional and fundamental subjects of weed–crop competition and physiology and integration of weed control tactics and practices. Weed science at ARS is often overshadowed by other research topics; thus, few are aware of the long history of ARS weed science and its important contributions. This review is the result of a symposium held at the Weed Science Society of America’s 62nd Annual Meeting in 2022 that included 10 separate presentations in a virtual Weed Science Webinar Series. The overarching themes of management tactics (IWM, biological control, and automation), basic mechanisms (competition, invasive plant genetics, and herbicide resistance), and ecosystem impacts (invasive plant spread, climate change, conservation, and restoration) represent core ARS weed science research that is dynamic and efficacious and has been a significant component of the agency’s national and international efforts. This review highlights current studies and future directions that exemplify the science and collaborative relationships both within and outside ARS. Given the constraints of weeds and invasive plants on all aspects of food, feed, and fiber systems, there is an acknowledged need to face new challenges, including agriculture and natural resources sustainability, economic resilience and reliability, and societal health and well-being.

Mass loss from the Amundsen Sea Embayment of the West Antarctic Ice Sheet is a major contributor to global sea-level rise (SLR) and has been increasing over recent decades. Predictions of future SLR are increasingly modelled using ensembles of simulations within which model parameters and external forcings are varied within credible ranges. Accurately reporting the uncertainty associated with these predictions is crucial in enabling effective planning for, and construction of defences against, rising sea levels. Calibrating model simulations against current observations of ice-sheet behaviour enables the uncertainty to be reduced. Here we calibrate an ensemble of BISICLES ice-sheet model simulations of ice loss from the Amundsen Sea Embayment using remotely sensed observations of surface elevation and ice speed. Each calibration type is shown to be capable of reducing the 90% credibility bounds of predicted contributions to SLR by 34 and 43% respectively.

Microscopy is a widely used method in biological research to observe the morphology and structure of cells. Amongst the plethora of microscopy techniques, fluorescent labeling with dyes or antibodies is the most popular method for revealing specific cellular organelles. However, fluorescent labeling also introduces new challenges to cellular observation, as it increases the workload, and the process may result in nonspecific labeling. Recent advances in deep visual learning have shown that there are systematic relationships between fluorescent and bright-field images, thus facilitating image translation between the two. In this article, we propose the cross-attention conditional generative adversarial network (XAcGAN) model. It employs state-of-the-art GANs (GANs) to solve the image translation task. The model uses supervised learning and combines attention-based networks to explore spatial information during translation. In addition, we demonstrate the successful application of XAcGAN to infer the health state of translated nuclei from bright-field microscopy images. The results show that our approach achieves excellent performance both in terms of image translation and nuclei state inference.

Digital psychiatry could empower individuals to navigate their context-specific experiences outside healthcare visits. This editorial discusses how leveraging digital health technologies could dramatically transform how we conceptualise mental health and the mental health professional's day-day practice, and how patients could be enabled to navigate their mental health with greater agency.

This article reviews existing state laws related to autonomous vehicle (AV) safety, equity, and automobile insurance. Thirty states were identified with relevant legislation. Of these, most states had one or two relevant laws in place. Many of these laws were related to safety and insurance requirements. Data are needed to evaluate the effectiveness of these laws in order to guide further policy development.