We conducted an analysis of a nationwide survey of US physician offices between 2016 and 2019 and calculated annualized prevalence rates of urinary tract infections (UTIs). During the 3-year study period, UTI was the most common infection in US physician offices, accounting for approximately 10 million annualized encounters.

This article examines the development of colonial public culture in Batavia, the capital of the Dutch East Indies, over the second half of the nineteenth century, focusing on two moments of extended colonial ceremony: the city’s 250th anniversary in 1869 and the inauguration of Queen Wilhelmina in 1898. The analysis shows that over the course of the century, colonial ceremonial increasingly sought to assimilate facets of local cultural practices, while also expanding spatially into a more diverse set of neighbourhoods. Nevertheless, this new and superficially more representative order still maintained a strict internal hierarchy embedded in spatial and socio-cultural boundaries.

Thermal integrity profiling (TIP) is a nondestructive testing technique that takes advantage of the concrete heat of hydration (HoH) to detect inclusions during the casting process. This method is becoming more popular due to its ease of application, as it can be used to predict defects in most concrete foundation structures requiring only the monitoring of temperatures. Despite its advantages, challenges remain with regard to data interpretation and analysis, as temperature is only known at discrete points within a given cross-section. This study introduces a novel method for the interpretation of TIP readings using neural networks. Training data are obtained through numerical finite element simulation spanning an extensive range of soil, concrete, and geometrical parameters. The developed algorithm first classifies concrete piles, establishing the presence or absence of defects. This is followed by a regression algorithm that predicts the defect size and its location within the cross-section. In addition, the regression model provides reliable estimates for the reinforcement cage misalignment and concrete hydration parameters. To make these predictions, the proposed methodology only requires temperature data in the form standard in TIP, so it can be seamlessly incorporated within the TIP workflows. This work demonstrates the applicability and robustness of machine learning algorithms in enhancing nondestructive TIP testing of concrete foundations, thereby improving the safety and efficiency of civil engineering projects.

I reconfigure Hegel’s distinction between Tat (deed) and Handlung (action) to illuminate Oedipus’s enigmatic formula: ‘I suffered my deeds more than I acted them’. Most interpreters hold that Oedipus mistook his Tat for a Handlung and wrongly took responsibility for parricide and incest. I argue against the merely causal reading of Tat presupposed by this view that the tragic Tat also has an intentional structure. On the Restrictive Intentionalism about Action (RIA) which underlies Handlung, what counts as my action is only the realization of a conscious intention, accomplished with reasonable knowledge of the relevant circumstances and foreseeable consequences of realizing my intention. On RIA, Oedipus killed the charioteer and married Iocasta: parricide and incest happened to him. By contrast, on the Inclusive Intentionalism about Action (IIA) which underlies the tragic Tat, what counts as my action is everything I bring about in realizing a conscious intention, regardless of reasonable expectations about knowledge of the circumstances or foreseeable consequences of realizing my intention. On IIA, parricide and incest are part of the ‘whole compass’ of Oedipus’s deeds. I argue that Oedipus is right to take responsibility for his deeds and draw on Tony Honoré’s conception of ‘outcome responsibility’ to characterize the responsibility at stake as blameless liability. Where Oedipus errs is in taking ethical responsibility for his deeds. I show that in Oedipus at Colonus the older Oedipus reverses his position and holds, somewhat surprisingly, that he is innocent and ‘did nothing’. I argue that this reversal presupposes an implicit shift from IIA to RIA, and that this shift helps to finally make sense of Oedipus’s enigmatic formula: Oedipus suffered his deeds (on RIA) more than he acted them (on IIA). I conclude by widening the perspective beyond ancient Greece and engage with Bernard Williams’s interpretation of the same formula.

SIGIRR, also known as the single immunoglobulin interleukin-1 receptor (IL-1R)-related molecule, is a member of the IL-1 receptor superfamily and is believed to play a pivotal role in inflammation and anti-inflammatory regulation within the body. Studies have shown that SIGIRR expression is associated with autoimmunity, inflammatory disorders, graft rejection, viral infection, thrombosis and tumour progression. Due to its unique structure and function, SIGIRR is commonly referred to as an ‘orphan receptor’, with IL-37 being the only confirmed ligand molecule for SIGIRR to date. The primary mechanism through which SIGIRR exerts its anti-inflammatory regulatory effect involves the negative modulation of the Toll-like receptor-IL-1R (TLR-IL-1R) signalling pathway. TLR-IL-1R signalling plays critical roles in immune responses triggered by microbial invasion and alterations in the tumour immune microenvironment. This article provides an overview of research findings on SIGIRR as an orphan receptor and its regulatory role in maintaining a delicate balance between natural immune activation and uncontrolled inflammatory processes under pathological conditions.

Enlist E3® soybean is resistant to 2,4-D, glyphosate, and glufosinate, allowing postemergence applications of these herbicides sequentially or as tank mixes. The objectives of this experiment were to evaluate the effect of postemergence herbicide application timing and sequence with or without a preemergence application of micro-encapsulated acetochlor on waterhemp and common lambsquarters control, soybean yield, and economic returns. Field experiments were conducted in Rosemount and Franklin, Minnesota, in 2021 and 2022. Site, herbicide application timing, and sequence influenced weed control, yield, and profitability. In Rosemount, preemergence followed by (fb) two-pass postemergence programs, including 2,4-D + glyphosate applied at mid-postemergence with or without S-metolachlor, resulted in ≥95% waterhemp control at 28 d after late postemergence application. In Franklin, where weed density was lower, two-pass postemergence programs, regardless of preemergence application that included at least one application of 2,4-D + glyphosate (with or without S-metolachlor), provided ≥97% control of waterhemp and common lambsquarters at 28 d after late postemergence. The level of control was comparable to that of a preemergence herbicide fb a mid-postemergence application of 2,4-D + glyphosate + S-metolachlor at that site. In Rosemount, including acetochlor as the preemergence herbicide in the preemergence fb postemergence programs improved soybean yield by 32% and partial returns by US$384.50 ha−1 compared to postemergence herbicides–only programs. In contrast, the preemergence application did not affect yield or profitability in Franklin. The highest soybean yield (2,925.7 kg ha−1) in Rosemount resulted after glufosinate was applied early postemergence fb 2,4-D + glyphosate applied mid-postemergence. This yield was comparable to that of glufosinate applied early postemergence fb 2,4-D + glyphosate + S-metolachlor applied mid-postemergence and the two-pass glufosinate (early postemergence fb mid-postemergence) program, highlighting the importance of early season weed control. In Franklin, 2,4-D + glyphosate + S-metolachlor (applied mid-postemergence) fb glufosinate (applied late postemergence) provided a yield that was similar to the aforementioned programs at that site.

Our quasi-experimental pilot study between July to September 2024 showed that real-time audit/feedback for antibiotic discharge prescriptions improved appropriateness from 50% to 83%, while decreasing median antibiotic duration compared to preintervention period. Hospital discharges are an important transition point for antimicrobial stewardship interventions at discharge.

Technology neutrality is a guiding principle of the European Union’s technology regulation, stating that legislation should not favour or discriminate against any particular technology, but rather focus on the effects or functions of technologies broadly. This article examines the principle as a way to future-proof regulation by allowing legislation to adapt to the changes in technology over time. Effects of technology neutrality have not been sufficiently analysed in the novel context of regulation of artificial intelligence, which arguably poses more significant societal risks than telecommunications, where the principle first evolved. To address this gap in research, this article analyses whether the technology neutral nature of the EU’s Artificial Intelligence Act (AI Act) renders it more future-proof. It identifies three main factors that affect future-proofness of the AI Act in light of technology neutrality: definition of AI, the risk-based approach and its enforcement mechanisms. The findings indicate that the AI Act’s deviations from technology neutrality, including specific provisions for general-purpose AI models significantly improved its scope and future-proofness. Thus, technology neutrality and future-proof regulation should not be treated synonymously, and strict adherence to neutrality may even obscure the political choices and democratic agency essential for AI regulation.

The assessment of soil–structure interaction (SSI) under dynamic loading conditions remains a challenging task due to the complexities of modeling this system and the interplay of SSI effects, which is also characterized by uncertainties across varying loading scenarios. This field of research encompasses a wide range of engineering structures, including underground tunnels. In this study, a surrogate model based on a regression ensemble model has been developed for real-time assessment of underground tunnels under dynamic loads. The surrogate model utilizes synthetic data generated using Latin hypercube sampling, significantly reducing the required dataset size while maintaining accuracy. The synthetic dataset is constructed using an accurate numerical model that integrates the two-and-a-half-dimensional singular boundary method for modeling wave propagation in the soil with the finite element method for structural modeling. This hybrid approach allows for a precise representation of the dynamic interaction between tunnels and the surrounding soil. The validation and optimization algorithms are evaluated for two problems: underground railway tunnels with circular and rectangular cross-sections, both embedded in a homogenous full-space medium. Both geometrical and material characteristics of the underground tunnel are incorporated into the optimization process. The optimization target is to minimize elastic wave propagation in the surrounding soil. The results demonstrate that the proposed optimization framework, which combines the Bayesian optimization algorithm with surrogate models, effectively explores trade-offs among multiple design parameters. This enables the design of underground railway tunnels that achieve an optimal balance between elastic wave propagation performance, material properties, and geometric constraints.