This article explores the intersection of Cold War geopolitics, cultural psychiatry, and migration in Taiwan from the mid-1940s to the 1970s. Building on recent scholarship in cultural psychiatry and Cold War science, it examines how geopolitical tensions shaped psychiatric knowledge production in East Asia. Focusing on the psychological and social impact of the 1949 mass migration, when over a million Chinese immigrants arrived in Taiwan, alongside the clinical and academic work of Taiwanese psychiatrists, the study highlights how migration and societal upheaval became central research concerns. Operating under the authoritarian Kuomintang regime and within the constraints and opportunities of international politics, Taiwanese psychiatrists – most of whom were native-born with colonial backgrounds – drew on intellectual traditions from imperial Japan, fascist Germany, and the Cold War Western bloc. Navigating both global psychiatric discourses and local concerns, they positioned themselves as key contributors to the international development of psychiatric research. While their portrayals of Chinese character structure and family dynamics sometimes reflected essentialist views, their work also demonstrated a nuanced awareness of historical change and contemporary realities during a period of intense political repression and uncertainty. By analysing archival sources and medical texts, this article illuminates the complex interplay between geopolitics and psychiatric knowledge production in Cold War Taiwan.

Machine learning, an artificial intelligence (AI) approach, provides scope for developing predictive modelling in mental health. The ability of machine learning algorithms to analyse vast amounts of data and make predictions about the onset or course of mental health problems makes this approach a valuable tool in mental health research of the future. The right use of this approach could improve personalisation and precision of medical and non-medical treatment approaches. However, ensuring the availability of large, good-quality data-sets that represent the diversity of the population, along with the need for openness and transparency of the AI approaches, are some of the challenges that need to be overcome. This article provides an overview of current machine learning applications in mental health research, synthesising literature identified through targeted searches of key databases and expert knowledge to examine research developments and emerging applications of AI-enabled predictive modelling in psychiatry. The article appraises both the potential applications and current challenges of AI-based predictive modelling in psychiatric practice and research.

The operating room scheduling (ORS) problem deals with the optimization of daily operating room surgery schedules. It is a challenging problem subject to many constraints, like to determine the starting time of different surgeries and allocating the required resources, including the availability of beds in different department units. Recently, solutions to this problem based on answer set programming (ASP) have been delivered. Such solutions are overall satisfying but, when applied to real data, they can currently only verify whether the encoding aligns with the actual data and, at most, suggest alternative schedules that could have been computed. As a consequence, it is not currently possible to generate provisional schedules. Furthermore, the resulting schedules are not always robust. In this paper, we integrate inductive and deductive techniques for solving these issues. We first employ machine learning algorithms to predict the surgery duration, from historical data, to compute provisional schedules. Then, we consider the confidence of such predictions as an additional input to our problem and update the encoding correspondingly in order to compute more robust schedules. Results on historical data from the ASL1 Liguria in Italy confirm the viability of our integration.

The presence of children in eighteenth-century English voluntary hospitals is an area of increasing interest and attention. The Northampton Infirmary admission records detail inpatient and outpatient ages from 1744 to 1804, allowing for longitudinal investigations of children in the institution. The most common distempers affecting children were surgical infections, infectious diseases, and skin diseases; fifty-six per cent of the child patients were male and 43.3 per cent were female. Nearly seventy-five per cent of children left the hospital ‘cured’. This article outlines the Northampton Infirmary Eighteenth Century Child Admission Database, and demonstrates how the patterning of distempers within and among children provides insight into the health journeys of eighteenth-century children through the lens of their bodies, their parents, and their institutional recommenders.

This article contributes to research on pragmatic borrowings through its exploration of their prosodic features in interactional turns. The pragmatic borrowings focused on are actual or enacted responses that demonstrate a stance towards the interlocutor’s previous turn. The data are drawn from podcast conversations in Finland Swedish. The qualitative exploration of the data, which draws on principles from Interactional Linguistics and uses sequential and acoustic analyses, focuses on an in-depth analysis of four examples of response tokens. Our analysis illustrates that borrowed response tokens are not used frequently, but when they are used, they are marked by speakers prosodically, rendering them stylistically salient within the context of the interaction. The borrowed response tokens demonstrate specific interactional meanings, such as affect, humor, farce and upgrading. These findings demonstrate that, like other pragmatic borrowings, responses are integrated into the overall repertoire of the receiving speech community, serving as stylistic variants alongside heritage forms.

Over the past two decades, there have been encouraging achievements in the surgical treatment of children with congenital tracheal stenosis. Slide tracheoplasty has become the standard surgical procedure for the correction of long-segment congenital tracheal stenosis with abnormal bronchial morphology in many medical centres around the world. Identification of the shape and degree of tracheal stenosis before operation is helpful to develop a better surgical strategy. Flexible application of slide tracheoplasty can effectively correct different types of congenital tracheal stenosis. Cardiopulmonary bypass and intraoperative fiberoptic bronchoscopy are helpful to improve the efficiency of surgery. Postoperative multidisciplinary cooperative management can improve the prognosis of children. Biodegradable scaffolds, tissue-engineered trachea, and 3D printing technology are based on a completely different perspective from traditional medicine. The initial attempts in the biomedical field provide a new idea for the treatment of congenital tracheal stenosis. This article reviews the classification, past and current situation, advantages, surgical indications, surgical techniques, prognosis, related risk factors, and prospects of slide tracheoplasty in the treatment of congenital tracheal stenosis in children.

This paper provides an overview of key concepts in evolutionary psychiatry, summarising major evolutionary explanations for mental illness and highlighting the potential of these perspectives to enhance assessment, diagnosis, explanation to the patient, treatment and prevention strategies. Expanding beyond conventional evolutionary approaches, we explore environmental influences on mental health and illness, emphasising the significant areas of convergence between evolutionary and environmental viewpoints. We then propose an integrated framework that combines insights from both perspectives, offering general principles for improving mental health outcomes at both individual and population levels. The discussion includes implications for general practice, public health and broader societal considerations, with particular reference to concepts such as biophilia and the emerging role of ‘green care’ in psychiatric practice.

According to the orthodox comparativist approach in rational choice theory, the ultimate conative basis for an agent’s preference ordering – and thus for their rational choice – is their comparative evaluation among competing options. However, it has been shown extensively in experimental psychology that an agent’s judgments about an option can be distorted by the contrast effects from their contextual reference point, which can sometimes be provided by the very competing option that they compare with. Such contrast effects from competing option, I argue, raise a new problem for comparativism: Sometimes an agent’s comparative evaluation might favor an option A over another option B only because their judgments about A’s appealing intrinsic features are distorted by B’s contrast effects. Such a comparative evaluation from contrast effects, however, is not only epistemically defective but also likely to lead to post-choice disenchantment with option A once the contrast effects from the competing option B are removed. While comparativists can either rationalize the choices made on the basis of comparative evaluations from contrast effects or idealize the type of comparative evaluations they appeal to, I argue that both strategies still face significant problems.

Visible satellite imagery (VIS) is essential for monitoring weather patterns and tracking ground surface changes associated with climate change. However, its availability is limited during nighttime. To address this limitation, we present a discrete variational autoencoder (VQVAE) method for translating infrared satellite imagery to VIS. This method departs from previous efforts that utilize a U-Net architecture. By removing the connections between corresponding layers of the encoder and decoder, the model learns a discrete and rich codebook of latent priors for the translation task. We train and test our model on mesoscale data from the Geostationary Operational Environmental Satellite (GOES) West Advanced Baseline Imager (ABI) sensor, spanning 4 years (2019 to 2022) using the Conditional Generative Adversarial Nets (CGAN) framework. This work demonstrates the practical use of a VQVAE for meteorological satellite image translation. Our approach provides a modular framework for data compression and reconstruction, with a latent representation space specifically designed for handling meteorological satellite imagery.

Clinicians across medical disciplines are intimately familiar with an unusual feature of descriptive diagnoses. The diagnostic terms, despite their non-aetiological nature, seem to offer an explanatory lens to many patients, at times with profound effects. These experiences highlight a striking, neglected and unchristened medical phenomenon: the therapeutic effect of a clinical diagnosis, independent of any other intervention, where clinical diagnosis refers to situating the person’s experiences into a clinical category by either a clinician or the patient. We call this the Rumpelstiltskin effect. This article describes this phenomenon and highlights its importance as a topic of empirical investigation.

A realization is a triple, $(A,b,c)$, consisting of a $d-$tuple, $A= (A_1, \cdots , A_d )$, $d\in \mathbb {N}$, of bounded linear operators on a separable, complex Hilbert space, $\mathcal {H}$, and vectors $b,c \in \mathcal {H}$. Any such realization defines an analytic non-commutative (NC) function in an open neighbourhood of the origin, $0:= (0, \cdots , 0)$, of the NC universe of $d-$tuples of square matrices of any fixed size. For example, a univariate realization, i.e., where A is a single bounded linear operator, defines a holomorphic function of a single complex variable, z, in an open neighbourhood of the origin via the realization formula $b^{*} (I-zA)^{-1} c$.

It is well known that an NC function has a finite-dimensional realization if and only if it is a non-commutative rational function that is defined at $0$. Such finite realizations contain valuable information about the NC rational functions they generate. By extending to infinite-dimensional realizations, we construct, study and characterize more general classes of analytic NC functions. In particular, we show that an NC function is (uniformly) entire if and only if it has a jointly compact and quasinilpotent realization. Restricting our results to one variable shows that a formal Taylor series extends globally to an entire or meromorphic function in the complex plane, $\mathbb {C}$, if and only if it has a realization whose component operator is compact and quasinilpotent, or compact, respectively. This motivates our definition of the field of global (uniformly) meromorphic NC functions as the field of fractions generated by NC rational expressions in the ring of NC functions with jointly compact realizations. This definition recovers the field of meromorphic functions in $\mathbb {C}$ when restricted to one variable.

These excerpts from Inbetweenness, an upcoming hopepunk novel, intertwine eco-social justice narratives and Indigenous education through climate fiction. Inbetweenness challenges Western-centric paradigms by highlighting diverse voices and posthumanist perspectives, focusing on the tension between contemporary environmental crises and Indigenous knowledge systems. It features characters like Joanne Penderwith, a graduate student navigating social justice, ecological connection, and decolonial praxis, inviting readers to reflect on allyship and positionality within activism. The novel also juxtaposes human-centric actions with the voices of other-than-human entities, using multi-species ethnography to embody ecological storytelling. A pivotal segment details Joanne’s transformative experience at a salmon ceremony led by the W̱SÁNEĆ First Nations, showcasing the resilience of Indigenous practices and their potential to guide sustainable futures. Inbetweenness uses fiction-based research methods grounded in 20 years of transdisciplinary research. It critiques performative allyship and advocates for authentic relationships with Indigenous communities, proposing a hopeful approach to environmental education and climate action.

During the last decade, early Neolithic sites with unique flat-bottomed pottery as distinguishing feature were discovered in the southern part of Western Siberia at the Baraba forest-steppe and identified as the Early Neolithic Baraba Culture (briefly, Baraba culture). The culture is represented in settlements and ritual complexes, has households, as well as implements made of stone and bone. Samples of mammal bones, bird bones and bone artifacts were collected from three sites of the Baraba Culture: Vengerovo-2, Tartas-1, and Ust-Tartas mounds, and dated by accelerator mass-spectrometry (AMS) to reconstruct the chronology of the sites. 36 reliable radiocarbon dates were obtained: 12 of them at the Curt-Engelhorn-Centre of Archaeometry (Mannheim, Germany) and 24 at the AMS Golden Valley (Novosibirsk, Russia). Minimal-to-no differences between radiocarbon dates assessed at GV and MAMS facilities were identified by Bayesian analysis of covariance/analysis of variance. Bayesian chronological modeling supports existence of the Baraba culture between the middle of 8th millennium BC till the start of 6th millennium BC. Two stages of sites’ use were identified, separated by the transitory period of uncertain duration lasting since the end of 7th millennium. The end of the first stage was followed by abandonment of the Tartas-1 site, which we suggest coincided with the start of the 8.2k climatic event.1