We define a notion of tracial $\mathcal {Z}$-absorption for simple not necessarily unital C*-algebras, study it systematically and prove its permanence properties. This extends the notion defined by Hirshberg and Orovitz for unital C*-algebras. The Razak-Jacelon algebra, simple nonelementary C*-algebras with tracial rank zero, and simple purely infinite C*-algebras are tracially $\mathcal {Z}$-absorbing. We obtain the first purely infinite examples of tracially $\mathcal {Z}$-absorbing C*-algebras which are not $\mathcal {Z}$-absorbing. We use techniques from reduced free products of von Neumann algebras to construct these examples. A stably finite example was given by Z. Niu and Q. Wang in 2021. We study the Cuntz semigroup of a simple tracially $\mathcal {Z}$-absorbing C*-algebra and prove that it is almost unperforated and the algebra is weakly almost divisible.

A vast amount of clinical data are still stored in unstructured text. Automatic extraction of medical information from these data poses several challenges: high costs of clinical expertise, restricted computational resources, strict privacy regulations, and limited interpretability of model predictions. Recent domain adaptation and prompting methods using lightweight masked language models showed promising results with minimal training data and allow for application of well-established interpretability methods. We are first to present a systematic evaluation of advanced domain-adaptation and prompting methods in a lower-resource medical domain task, performing multi-class section classification on German doctor’s letters. We evaluate a variety of models, model sizes (further-pre)training and task settings, and conduct extensive class-wise evaluations supported by Shapley values to validate the quality of small-scale training data and to ensure interpretability of model predictions. We show that in few-shot learning scenarios, a lightweight, domain-adapted pretrained language model, prompted with just 20 shots per section class, outperforms a traditional classification model, by increasing accuracy from $48.6\%$ to $79.1\%$. By using Shapley values for model selection and training data optimization, we could further increase accuracy up to $84.3\%$. Our analyses reveal that pretraining of masked language models on general-language data is important to support successful domain-transfer to medical language, so that further-pretraining of general-language models on domain-specific documents can outperform models pretrained on domain-specific data only. Our evaluations show that applying prompting based on general-language pretrained masked language models combined with further-pretraining on medical-domain data achieves significant improvements in accuracy beyond traditional models with minimal training data. Further performance improvements and interpretability of results can be achieved, using interpretability methods such as Shapley values. Our findings highlight the feasibility of deploying powerful machine learning methods in clinical settings and can serve as a process-oriented guideline for lower-resource languages and domains such as clinical information extraction projects.

During the past 30 yr an impasse has developed in the discovery and commercialization of synthetic herbicides with new molecular targets and novel chemistries. Similarly, there has been little success with bioherbicides, both microbial and chemical. These bioherbicides are needed to combat fast-growing herbicide resistance and to fulfill the need for more environmentally and toxicologically safe herbicides. In response to this substantial and growing opportunity, numerous start-up companies are utilizing novel approaches to provide new tools for weed management. These diverse new tools broaden the scope of discovery, encompassing advanced computational, bioinformatic, and imaging platforms; plant genome–editing and targeted protein degradation technologies; and machine learning and artificial intelligence (AI)-based strategies. This review contains summaries of the presentations of 10 such companies that took part in a symposium held at the WSSA annual meeting in 2024. Four of the companies are developing microbial bioherbicides or natural product–based herbicides, and the other six are using advanced technologies, such as AI, to accelerate the discovery of herbicides with novel molecular target sites or to develop non-GMO, herbicide-resistant crops.

We hypothesized that the incubation for urethral gonorrhoea would be longer for men with oropharyngeal gonorrhoea than those without oropharyngeal gonorrhoea. We conducted a chart review of men who have sex with men with urethral gonorrhoea symptoms at a sexual health clinic between 2019 and 2021. The incubation period was defined as the number of days between men’s last sexual contact and onset of symptoms. We used a Mann–Whitney U test to compare differences in the median incubation for urethral gonorrhoea between men with and men without oropharyngeal gonorrhoea. There were 338 men with urethral symptoms (median age = 32 years; IQR: 28–39), and of these, 307 (90.1%) were tested for oropharyngeal gonorrhoea, of whom 124 (40.4%, 95% CI: 34.9–46.1) men had oropharyngeal and urethral gonorrhoea. We analyzed incubation data available for 190 (61.9%) of the 307 men, with 38.9% (74/190) testing positive for oropharyngeal gonorrhoea. The incubation for urethral gonorrhoea did not differ between 74 men (39%) with oropharyngeal gonorrhoea (median = 4 days; IQR: 2–6) and 116 men (61%) without oropharyngeal gonorrhoea (median = 2.5 days; IQR: 1–5) (p = 0.092). Research is needed to investigate gonorrhoea transmission from the oropharynx to the urethra.

A growing body of evidence demonstrates that individual differences in declarative memory may be an important predictor of second language (L2) abilities. However, the evidence comes from studies using different declarative memory tasks that vary in their reliance on verbal abilities and task demands, which preclude estimating the size of the relationship between declarative memory and L2 learning. To address these concerns, we examined the relationship between verbal and nonverbal declarative memory abilities within the same task while controlling for task demands and stimulus modality, to estimate the upper bound of the relationship between verbal and nonverbal declarative memory. Results indicate that when task demands and stimulus modality are controlled, verbal and nonverbal declarative memory abilities shared a medium-to-large amount of underlying variance. However, future studies should exercise caution in appraising associations between declarative memory abilities and L2 learning until a more precise understanding of the underlying mechanisms is achieved.

Research articles in the clinical and translational science literature commonly use quantitative data to inform evaluation of interventions, learn about the etiology of disease, or develop methods for diagnostic testing or risk prediction of future events. The peer review process must evaluate the methodology used therein, including use of quantitative statistical methods. In this manuscript, we provide guidance for peer reviewers tasked with assessing quantitative methodology, intended to complement guidelines and recommendations that exist for manuscript authors. We describe components of clinical and translational science research manuscripts that require assessment including study design and hypothesis evaluation, sampling and data acquisition, interventions (for studies that include an intervention), measurement of data, statistical analysis methods, presentation of the study results, and interpretation of the study results. For each component, we describe what reviewers should look for and assess; how reviewers should provide helpful comments for fixable errors or omissions; and how reviewers should communicate uncorrectable and irreparable errors. We then discuss the critical concepts of transparency and acceptance/revision guidelines when communicating with responsible journal editors.

Engineered products have economic, environmental, and social impacts, which comprise the major dimensions of sustainability. This paper seeks to explore interactions between design parameters when social impacts are incorporated into the concept development phase of the systems design process. Social impact evaluation is increasing in importance similar to what has happened in recent years with environmental impact consideration in the design of engineered products. Concurrently, research into new airship design has increased. Airships have yet to be reintroduced at a large scale or for a range of applications in society. Although airships have the potential for positive environmental and economic impacts, the social impacts are still rarely considered. This paper presents a case study of the hypothetical introduction of airships in the Amazon region of Brazil to help local farmers transport their produce to market. It explores the design space in terms of both engineering parameters and social impacts using a discrete-event simulation to model the system. The social impacts are found to be dependent not only on the social factors and airship design parameters but also on the farmer-airship system, suggesting that socio-technical systems design will benefit from integrated social impact metric analysis.

One of our main goals with “Expression unleashed” was to highlight the distinctive, ostensive nature of human communication, and the many roles that ostension can play in human behavior and society. The commentaries we received forced us to be more precise about several aspects of this thesis. At the same time, no commentary challenged the central idea that the manifest diversity of human expression is underpinned by a common cognitive unity. Our reply is organized around six issues: (1) languages and their cultural evolution; (2) the pervasiveness of expression in human behavior; (3) artificial intelligence and ostensive communication; (4) communication in other animals; (5) the ecology and evolution of ostensive communication; and (6) biolinguistics and pragmatics.

Human expression is open-ended, versatile, and diverse, ranging from ordinary language use to painting, from exaggerated displays of affection to micro-movements that aid coordination. Here we present and defend the claim that this expressive diversity is united by an interrelated suite of cognitive capacities, the evolved functions of which are the expression and recognition of informative intentions. We describe how evolutionary dynamics normally leash communication to narrow domains of statistical mutual benefit, and how expression is unleashed in humans. The relevant cognitive capacities are cognitive adaptations to living in a partner choice social ecology; and they are, correspondingly, part of the ordinarily developing human cognitive phenotype, emerging early and reliably in ontogeny. In other words, we identify distinctive features of our species' social ecology to explain how and why humans, and only humans, evolved the cognitive capacities that, in turn, lead to massive diversity and open-endedness in means and modes of expression. Language use is but one of these modes of expression, albeit one of manifestly high importance. We make cross-species comparisons, describe how the relevant cognitive capacities can evolve in a gradual manner, and survey how unleashed expression facilitates not only language use, but also novel behaviour in many other domains too, focusing on the examples of joint action, teaching, punishment, and art, all of which are ubiquitous in human societies but relatively rare in other species. Much of this diversity derives from graded aspects of human expression, which can be used to satisfy informative intentions in creative and new ways. We aim to help reorient cognitive pragmatics, as a phenomenon that is not a supplement to linguistic communication and on the periphery of language science, but rather the foundation of the many of the most distinctive features of human behaviour, society, and culture.

Engineered products have economic, environmental, and social impacts, which comprise the major dimensions of sustainability. This paper seeks to determine the interaction between design parameters when the social impacts are incorporated into the design process. Social impact evaluation is increasing in importance similar to what has happened with environmental impact consideration in recent years in the design of engineered products. Concurrently, research into new airship design has increased, however airships have yet to be reintroduced at a large scale and for a range of applications in society. Although airships have the potential for positive environmental and economic impacts, the social impacts are still rarely considered. This paper presents a case study of the hypothetical introduction of airships in the Amazon to help local farmers transport their produce to market. It explores the design space in terms of the airship's social impacts connected to the design parameters. The social impacts are found to be dependent not only on the social factors and airship design parameters, but also on the farmer-airship system, suggesting that socio-technical systems design will benefit from integrated social impact metric analysis.

Let G be a finite group, let A be an infinite-dimensional stably finite simple unital C*-algebra, and let $\alpha \colon G \to {\operatorname {Aut}} (A)$ be an action of G on A which has the weak tracial Rokhlin property. Let $A^{\alpha }$ be the fixed point algebra. Then the radius of comparison satisfies ${\operatorname {rc}} (A^{\alpha }) \leq {\operatorname {rc}} (A)$ and ${\operatorname {rc}} ( C^* (G, A, \alpha ) ) \leq ({1}/{{{\operatorname{card}}} (G))} \cdot {\operatorname {rc}} (A)$. The inclusion of $A^{\alpha }$ in A induces an isomorphism from the purely positive part of the Cuntz semigroup ${\operatorname {Cu}} (A^{\alpha })$ to the fixed points of the purely positive part of ${\operatorname {Cu}} (A)$, and the purely positive part of ${\operatorname {Cu}} ( C^* (G, A, \alpha ) )$ is isomorphic to this semigroup. We construct an example in which $G \,{=}\, {\mathbb {Z}} / 2 {\mathbb {Z}}$, A is a simple unital AH algebra, $\alpha $ has the Rokhlin property, ${\operatorname {rc}} (A)> 0$, ${\operatorname {rc}} (A^{\alpha }) = {\operatorname {rc}} (A)$, and ${\operatorname {rc}} ({C^* (G, A, \alpha)} ) = ({1}/{2}) {\operatorname {rc}} (A)$.

Are communicators perceived as committed to what they actually say (what is explicit), or to what they mean (including what is implicit)? Some research claims that explicit communication leads to a higher attribution of commitment and more accountability than implicit communication. Here we present theoretical arguments and experimental data to the contrary. We present three studies exploring whether the saying–meaning distinction affects commitment attribution in promises, and, crucially, whether commitment attribution is further modulated by the degree to which the hearer will actually rely on the promise. Our results support the conclusion that people perceive communicators to be committed to ‘what is meant’, and not simply to ‘what is said’. Our findings add to the experimental literature showing that the saying–meaning distinction is not as pivotal to social relations as often assumed, and that its role in commitment attribution might be overestimated. The attribution of commitment is strongly dependent on the (mutually known) relevance of ‘what is meant’.

Ichthyosporean parasites (order Dermocystida) can cause morbidity and mortality in amphibians, but their ecology and epidemiology remain understudied. We investigated the prevalence, gross and histologic appearance, and molecular phylogeny of a novel dermocystid in the state-endangered silvery salamander (Ambystoma platineum) and the co-occurring, non-threatened small-mouthed salamander (Ambystoma texanum) from Illinois. Silvery salamanders (N = 610) were sampled at six ephemeral wetlands from 2016 to 2018. Beginning in 2017, 1–3 mm raised, white skin nodules were identified in 24 silvery salamanders and two small-mouthed salamanders from five wetlands (prevalence = 0–11.1%). Skin biopsy histology (N = 4) was consistent with dermocystid sporangia, and necropsies (N = 3) identified infrequent hepatic sporangia. Parasitic 18S rRNA sequences (N = 5) from both salamander species were identical, and phylogenetic analysis revealed a close relationship to Dermotheca viridescens. Dermocystids were not identified in museum specimens from the same wetlands (N = 125) dating back to 1973. This is the first report of Dermotheca sp. affecting caudates in the Midwestern United States. Future research is needed to determine the effects of this pathogen on individual and population health, and to assess whether this organism poses a threat to the conservation of ambystomatid salamanders.

Organizations all over the world, both national and international, gather demographic data so that the progress of nations and peoples can be tracked. This data is often made available to the public in the form of aggregated national level data or individual responses (microdata). Product designers likewise conduct surveys to better understand their customer and create personas. Personas are archetypes of the individuals who will use, maintain, sell or otherwise be affected by the products created by designers. Personas help designers better understand the person the product is designed for. Unfortunately, the process of collecting customer information and creating personas is often a slow and expensive process. In this paper, we introduce a new method of creating personas, leveraging publicly available databanks of both aggregated national level and information on individuals in the population. A computational persona generator is introduced that creates a population of personas that mirrors a real population in terms of size and statistics. Realistic individual personas are filtered from this population for use in product development.

In this commentary on Borsboom et al.’s target article, we argue that researchers should be aware of the historical development of models in neuroscience. Considering the importance of causality in anatomo-clinical approach and stressing the complexity of mental phenomenon, we provide new insight on reductionism and representation limitation.

We use experimental methods to investigate subsidy incidence, the transfer of subsidy payments from intended recipients to other economic agents, in privately negotiated spot markets. Our results show that market outcomes in treatments with a subsidy given to either buyers or sellers are significantly different from both a no-subsidy treatment and the competitive prediction of a 50% subsidy incidence. The disparity in incidence across treatments relative to predicted levels suggests that incidence equivalence does not hold in this market setting. Moreover, we find no statistical difference in market outcomes when benefits are framed as a “subsidy” versus a schedule shift.