Machine learning’s integration into reliability analysis holds substantial potential to ensure infrastructure safety. Despite the merits of flexible tree structure and formulable expression, random forest (RF) and evolutionary polynomial regression (EPR) cannot contribute to reliability-based design due to absent uncertainty quantification (UQ), thus hampering broader applications. This study introduces quantile regression and variational inference (VI), tailored to RF and EPR for UQ, respectively, and explores their capability in identifying material indices. Specifically, quantile-based RF (QRF) quantifies uncertainty by weighting the distribution of observations in leaf nodes, while VI-based EPR (VIEPR) works by approximating the parametric posterior distribution of coefficients in polynomials. The compression index of clays is taken as an exemplar to develop models, which are compared in terms of accuracy and reliability, and also with deterministic counterparts. The results indicate that QRF outperforms VIEPR, exhibiting higher accuracy and confidence in UQ. In the regions of sparse data, predicted uncertainty becomes larger as errors increase, demonstrating the validity of UQ. The generalization ability of QRF is further verified on a new creep index database. The proposed uncertainty-incorporated modeling approaches are available under diverse preferences and possess significant prospects in broad scientific computing domains.

The increasing popularity of large language models has not only led to widespread use but has also brought various risks, including the potential for systematically spreading fake news. Consequently, the development of classification systems such as DetectGPT has become vital. These detectors are vulnerable to evasion techniques, as demonstrated in an experimental series: Systematic changes of the generative models’ temperature proofed shallow learning—detectors to be the least reliable (Experiment 1). Fine-tuning the generative model via reinforcement learning circumvented BERT-based—detectors (Experiment 2). Finally, rephrasing led to a >90% evasion of zero-shot—detectors like DetectGPT, although texts stayed highly similar to the original (Experiment 3). A comparison with existing work highlights the better performance of the presented methods. Possible implications for society and further research are discussed.

In this study, we investigated the diversity and survival of aestivating snails in dry-season rice paddies, focusing on their role as intermediate hosts for trematodes. A total of 1,159 snails from various families were collected and analysed, revealing nine species, primarily from the Bithyniidae family, with Bithynia siamensis siamensis being the most abundant. Of the nine species collected, the most common species, B. s. siamensis, exhibited a relatively high survival rate of 81.5% throughout the three-month dry period post-harvest, whereas the remaining eight species had survival rates below 24.0% (0–23.1%). Four snail species, B. s. siamensis, Filopaludina martensi martensi, F. sumatrensis polygramma, and F. doliaris, were found infected with larval trematodes, with an overall prevalence of 8.46% (57/674). The larval trematodes identified were categorized into four types: echinostome metacercaria, Thapariella anastomusa metacercaria, unidentified metacercaria, and unidentified rediae. These findings demonstrate that trematode infections can persist in aestivating snails despite the challenging conditions during the dry season, emphasizing the potential of aestivating snails to act as vectors for trematode transmission in agricultural settings. This underscores the need for effective management strategies to mitigate the risks associated with trematode transmission.

Healthcare technologies are often appraised under considerable ambiguity over the size of incremental benefits and costs, and thus how decision-makers combine unclear information to make recommendations is of considerable public interest. This paper provides a conceptual foundation for such decision-making under ambiguity, formalizing and differentiating the decision problems of a representative policy-maker reviewing the results from an economic evaluation. A primary result is that presenting information to regulators in an incremental cost-effectiveness ratio or cost-effectiveness analysis (CEA) format instead of a net monetary benefit or cost–benefit analysis (CBA) framework may induce errors in decision-making when there exists ambiguity in incremental benefits and decision-makers use well-known decision rules to combine information. Ambiguity in incremental costs or the value of the cost-effectiveness threshold does not distort decision-making under these rules. In reasonable contexts, I show that the CEA framing may result in the approval of fewer technologies relative to CBA framing. I interpret these results as predictions on how the presentation of information from economic evaluations to regulators may frame and distort recommendations. All the results extend to non-healthcare contexts.

The ad hominem appears to be the simplest fallacy form—one criticizes speakers instead of their statements or arguments. It is regularly taken to be a fallacy of irrelevance, in that who is speaking does not bear on the truth of what is said. But three puzzles attend this analysis. (1) Given that the fallacy is simple and seemingly obvious, how could it be effective in practice? (2) Are there not cases when who is speaking is relevant? How do we sort those cases from those where it is irrelevant? (3) Isn’t there another level to the ad hominem, one where we observe it, know it is a bad argumentative move, and make inferences about the argumentative circumstances and arguers in light of it? Accusing another of committing the ad hominem, on this line of thought, has broader implications about the reasoner and their reasons. This article is an attempt to tell a coherent story of the ad hominem that makes sense of these three puzzles and shows how the observed preponderance of the argument form should trouble us as reasoners.

Intermittent swimming behaviour is commonly observed in larval zebrafish, often attributed to energy-saving mechanisms. In this study, we utilize a hybrid approach combining deep reinforcement learning and the immersed boundary–lattice Boltzmann method to train a larval zebrafish-like swimmer to reach a target with minimized energy expenditure. We find that when the tail-beat period is fixed, continuous swimming emerges as the optimal strategy. However, when the tail-beat period is allowed to vary, intermittent swimming proves superior in energy performance, achieved through reductions in tail-beat amplitude and frequency. Our detailed analysis reveals that intermittent swimmers employ rapid backward tail flicks to attain high speeds, coupled with slower forward tail flicks and coasting phases to conserve energy. Furthermore, we derive scaling laws governing the swimming performance of trained fish. These results offer valuable insights into the intermittent swimming patterns of fish, with implications for understanding bio-inspired locomotion and informing the design of energy-efficient aquatic systems.

This paper responds to Al-Hoorie, Hiver, and In’nami’s (2024) critique of the second language (L2) Motivational Self System (L2MSS) by advocating for an immediate cessation of its use in the absence of substantial revision and validation. We revisit foundational studies in the tradition, exposing critical methodological flaws that we feel undermine empirical support for the model. Further, we examine systemic factors that contributed to the largely uncritical acceptance of the model. Drawing on our own experiences, we reflect on how these dynamics have obstructed the adoption of more robust motivational theories available in psychology and education. We further caution that without a stronger emphasis on validating measurement instruments, similar distractions may continue to hinder progress in the field.

Historians have long argued that abolitionism, as a distinct political project, never fully took root in the Ottoman Empire. While anti-slavery measures emerged from the mid-nineteenth century onwards, they are often seen as state-imposed responses to diplomatic pressure. From a state-focused perspective, abolition indeed appears to be the result of actions by the Ottoman state and international community, inevitably so, given its entanglement with the emergence and development of the Congress system in the aftermath of the Congress of Vienna. Yet a focus on individuals, organizations, and institutions also suggests a subversive, practical abolitionism concerned with everyday injustices rather than lofty ideals. This paper examines such efforts, reframing abolitionism as a political issue rather than a moral one detached from broader transformations. By situating abolitionist thought within the late Ottoman Empire’s increasingly radical politics, it challenges the conventional state-centered narrative, highlighting the diverse actors who shaped anti-slavery discourse and action.

In this article, I argue that leaders of the U.S. Department of War and U.S. Army developed the organizational form and management practices of the modern corporation, decades before the advent of the railroads. Following Mark R. Wilson’s call to “bring the military in” to organizational analysis, I show how leaders of the U.S. military developed modern management practices and organizational structures as a way of maintaining control over officers, soldiers, and workers over long distances, as they provided the organized violence necessary for domestic imperialist expansion. By the time that elite merchants and real estate interests in the Atlantic port cities of the U.S. became interested in building railroads, in the late 1820s and 1830s, the U.S. Army already evidenced the key characteristics of modern business enterprise as defined by Alfred Chandler: a multi-unit organization coordinated by a hierarchy of professional, salaried, career-oriented middle and top managers. All the characteristic coordination mechanisms of the corporation: staff and line hierarchies, divisional and departmental structure, and bureaucratic systems of information gathering, surveillance, and control, were developed by the state in the course of building a continental empire.

We study how consumer preferences affect the transmission of microeconomic price shocks to consumer price index (CPI) inflation. These preferences give rise to complementarities and substitutions between goods, generating demand-driven cross-price dependencies that either amplify or mitigate the impact of price shocks. Our results demonstrate that while both effects are present, positive spillovers due to complementarities dominate. The magnitude of these cross-price effects is significant, demonstrating their importance in shaping CPI inflation dynamics. Most importantly, demand-driven price linkages decisively shape the impact of producer prices on CPI inflation. These findings underscore the need to take into account demand-driven price dependencies when assessing the impact of price shocks on CPI inflation, rather than relying solely on supply-related ones.

An idée fixe of Great Moderation economic policy was that central banks are only effective macroeconomic managers when they are segregated from electoral politics. That idea made a swift transition from radical heterodoxy to commonsensical orthodoxy during the 1980s and proved remarkably resistant to reality during the 2008 financial crisis. After almost twenty years of ‘unconventional’ monetary policy, scholars, policymakers, and politicians are justifiably searching for more credible ways to conceptualise and use the nation-state’s monetary authority. Two recent books provide vital energy for that intellectual exercise. Éric Monnet’s Balance of Power is a bold re-conceptualisation of monetary authority as a welfare-state support in liberal democracies. In addition to dissipating the illusion that central banks are simply interest-rate-setting inflation-fighters, Monnet presents a systematic argument for integrating them into a web of deliberative institutions (including public development banks and economically empowered parliaments) to bolster the legitimacy and effectiveness of monetary policy. Relatedly, Manuella Moschella’s Unexpected Revolutionaries attacks the idea that central bankers are responsive only to technocratic doctrine and private-market behaviour, showing how monetary authorities sculpt policies to bolster their reputation with political actors. Paying close reference to private-market liquidity guarantees and quantitative easing, Moschella maps the fortunes of unconventional policy in alignment with political support for financial-market backstops and exceptional economic stimulus. Both books provoke readers to jettison the anodyne generalities of central banks’ own glossy pamphlets and think afresh about the possibilities of economic policy’s new normality.

Birth cohort studies provide invaluable data on topics across the lifecourse, including health, education, socioeconomic conditions, and well-being. As a result, they are an important resource for biosocial researchers to answer numerous complex research questions. However, despite being positioned as representative of their national or regional context, cohort studies often fail to capture the experience of marginalised groups.

One such group is sexual and gender minority (or LGBTQ+) people who, until very recently, have been largely invisible in birth cohorts. This is despite huge social and attitudinal changes in the last fifty years and clear evidence of the social, political, economic, and health and well-being disparities experienced compared to heterosexual cisgender people. However, due to small numbers, opportunities for quantitative analysis are limited and result in the neglect of LGBTQ+ data even when it is captured.

This article presents a brief overview of how queer lives have (and have not) been captured by standard data collection and analysis techniques in the British birth cohort studies. Then, using a cohort born in 1970, the authors explore the possibilities of person-centred mixed-method pen portraits to improve understanding of this group’s life trajectories.

The zero suicide approach is based on the belief that all deaths from suicide in healthcare settings are preventable. We caution that the narrow focus on suicide prevention as a key indicator for measuring mental health system performance may have adverse consequences.

The South Asian region, including India, faces an increased prevalence of illicit drug use. Key challenges include rising opioid use, injecting drug use and spread of stimulant use from some pockets to other regions of the country. Challenges faced are poor surveillance, lack of evidence-based and structured prevention programmes, wide treatment gaps and inadequate social capital for reintegration of substance users into society. The drug control efforts in India have resulted in an improved drug offence surveillance system, increased community awareness, a growing network of drug treatment centres and resource-building measures. India has made pioneering efforts in the field of harm reduction in the South Asian region. The steps taken have the potential of applicability across other South Asian, as well as most low- and middle-income, countries around the world.