We derive the exact asymptotics of $\mathbb{P} {\{\sup\nolimits_{\boldsymbol{t}\in {\mathcal{A}}}X(\boldsymbol{t})>u \}} \textrm{ as}\ u\to\infty,$ for a centered Gaussian field $X({\boldsymbol{t}}),\ {\boldsymbol{t}}\in \mathcal{A}\subset\mathbb{R}^n$, $n>1$ with continuous sample paths almost surely, for which $\arg \max_{\boldsymbol{t}\in {\mathcal{A}}} {\mathrm{Var}}(X(\boldsymbol{t}))$ is a Jordan set with a finite and positive Lebesgue measure of dimension $k\le n$ and its dependence structure is not necessarily locally stationary. Our findings are applied to derive the asymptotics of tail probabilities related to performance tables and chi processes, particularly when the covariance structure is not locally stationary.

Particle suspensions at the interface of turbulent liquids are governed by the balance of capillary attraction, strain-induced drag and lubrication. Here, we extend previous findings, obtained for small particles whose capillary interactions are dominated by quadrupolar-mode deformation of the interface, to larger spherical and disc-shaped particles experiencing monopole-dominant capillarity. By combining pair-approach experiments, two-dimensional turbulent flow realizations and particle imaging, we demonstrate that particles experiencing monopole-dominant attraction exhibit enhanced clustering compared with their quadrupole-dominant counterparts. We introduce an interaction scale defined by balancing viscous drag and capillary attraction, which is compared with the particle size and interparticle distance. This allows us to map the clustering behaviour onto a parameter space solely defined by those characteristic length scales. This yields a unified framework able to predict the tendency to cluster (and the concentration threshold for those clusters to percolate) in a vast array of fluid–particle systems.

This work proposes an optimization approach for the time-consuming parts of Light Detection and Ranging (LiDAR) data processing and IMU-LiDAR data fusion in the LiDAR-inertial odometry (LIO) method. Two key novelties enable faster and more accurate navigation in complex, noisy environments. Firstly, to improve map update and point cloud registration efficiency, we employ a sparse voxel maps with a new update function to construct a local map around the mobile robot and utilize an improved Generalized Iterative Closest Point algorithm based on sparse voxels to achieve LiDAR point clouds association, thereby boosting both map updating and computational speed. Secondly, to enhance real-time accuracy, this paper analyzes the residuals and covariances of both IMU and LiDAR data in a tightly coupled manner, and achieves system state estimation by fusing sensor information through Gauss-Newton method, effectively mitigating localization deviations by appropriately weighting the LiDAR covariances. The performance of our method is evaluated against advanced LIO algorithms using eight open datasets and five self-collected campus datasets. Results show a 24.7–60.1% reduction in average processing time per point cloud frame, along with improved robustness and higher precision motion trajectory estimation in most cluttered and complex indoor and outdoor environments.

This article argues that contemporary Indian law is animated by two intertwined imaginings of law: as a rational, rule-bound process and as a power that makes decisions as a normless act of prerogative. Through ethnographic fieldwork in Delhi’s terrorism courts, the paper examines petitions written by individuals accused under anti-terror laws, revealing how these texts invoke the dual legal imaginaries. Petitions—ranging from formal legal documents to handwritten pleas—are analysed through the idea of epistolarity, to pay attention to both the form and content of these petitions. The article argues that these letters are affective and rhetorical performances that simultaneously invoke imaginings of the law as both rule and prerogative. In doing so, the subjectivity of the petitioners oscillates between rights-bearing citizens and humble supplicants praying for the law’s intervention.

Images are ubiquitous in the alchemical arts. From diagrams of laboratory equipment, through fantastical images of mythical beasts, to elaborate metaphorical descriptors, images flourished in chymical environs. Such images were more than merely decorative; they offered vital clues which could be used to decode complex and often deliberately obscure treatises, revealing the signs – or tokens – that an alchemist should expect to encounter if their work proceeded successfully. Following recent calls to view the term ‘image’ in its broadest sense, this introduction argues that we must consider both visual and textual imagery in alchemical contexts, as images conjured with pigments and with words alike were essential means of understanding alchemical theories and ideas. It is argued that it is vital that the scope of ‘the image’ is extended to also include linguistic imagery formed through allegory and metaphor, as these were as vital a part of the broader corpus of alchemical imagery as its pictorial counterparts.

This small project was initiated to create a broader understanding of the working properties of sarsen and its challenges. This notoriously durable coarse-grained sandstone is most familiarly associated with the Phase 3 monument at Stonehenge, Wiltshire, although its exploitation persisted into the twentieth century. Discussion has focused on the probable methods employed in prehistory to work the stone: splitting, flaking and pecking. These techniques have rarely been applied in practice, but have been considered broadly in this project. The preliminary results, obtained from a single block of saccharoidal sarsen, have reawakened understanding and appreciation of the potential provided by shock waves to split and shape this intractable silicate successfully and repeatedly using direct percussion, techniques that were familiar to Neolithic communities to work flint. The flaking properties of the stone are considered together with attributes of hammer mode in comparison with data from prehistoric stone assemblages at Stonehenge. The discussion questions to what extent flaking could be controlled repeatedly to form a major part of monolith production. Results derived from the laborious nature of pecking supplement previous attempts to recreate dressed surfaces at Stonehenge. Efficiency was not improved by applying heat to the surface of the stone; indeed, it confirmed that uncontrolled, excessive heat shatters the structure of sarsen, rendering it unworkable.

Peer Refugee Helpers (PRHs) support peers in humanitarian settings, which may influence their own mental health. This longitudinal study examined anxiety and depression trajectories among Afghan, Iranian and Syrian refugees and asylum seekers in Greece, focusing on how PRH status (paid/unpaid) and sense of coherence influence trajectory membership. The study included 176 adult, PRHs and non-helpers. The following scales were administered three times at ~4-month intervals: Patient Health Questionnaire (PHQ-9), Generalized Anxiety Disorder (GAD-7), Social Provisions Scale (SPS-24), Sense of Coherence (SOC-13), Perceived Ability to Cope With Trauma (PACT) and Brief Trauma Questionnaire (BTQ). Using latent growth mixture modeling, we identified two depression (high and low) and three anxiety (high, moderate and low) trajectories. The adjusted logistic and multinomial regression models indicated that unpaid PRHs were significantly less likely to follow a low depression trajectory (odds ratio [OR] = 0.55, p = 0.037), while paid PRHs were more likely to follow a low anxiety trajectory (OR = 3.17, p = 0.009). Higher SOC was associated with low depression (OR = 1.03, p = 0.012) and low anxiety trajectories (OR = 1.06, p = 0.002). Our findings suggest PRH mental health may be associated with working conditions, including financial compensation.

Drug use among young women has severe consequences for their mental health, increases their developmental vulnerability and highlights the global problem of drug addiction. The purpose of this study was to investigate the socioeconomic and psychological factors influencing drug use among young women in Khyber Pakhtunkhwa, Pakistan. The study used a qualitative research design. We collected data from 12 women aged 18–21 years via in-depth qualitative interviews conducted in Mardan and Peshawar from March to June 2022. Research shows that young women frequently use drugs due to peer pressure, emotional challenges and financial concerns, which significantly impact their lives. The study emphasizes the value of cultural intervention programs for young women, concentrating on the region’s mental health services, economic empowerment and gender-specific peer support networks.

This short research article interrogates the rise of digital platforms that enable ‘synthetic afterlives’, with a focus on how deathbots – AI-driven avatar interactions grounded in personal data and recordings – reshape memory practices. Drawing on socio-technical walkthroughs of four platforms – Almaya, HereAfter, Séance AI, and You, Only Virtual – we analyse how they frame, archive, and algorithmically regenerate memories. Our findings reveal a central tension: between preserving the past as a fixed archive and continually reanimating it through generative AI. Our walkthroughs demonstrate how these services commodify remembrance, reducing memory to consumer-driven interactions designed for affective engagement while obscuring the ethical, epistemological and emotional complexities of digital commemoration. In doing so, they enact reductive forms of memory that are embedded within platform economies and algorithmic imaginaries.

How has caste influenced entrepreneurship in India in the past and how does it do so in the present? Using the Industrial Census of 1911, this paper provides the first detailed caste-level mapping of firms in Indian business history and links it to the present by an analysis of the Economic Census of 2013–2014. It finds that while trading castes were dominant, there were significant regional variations and nontrading castes were far more important than usually posited in the literature. Over the course of a century, the social base of entrepreneurship has widened slowly but significant barriers remain. The paper argues that “caste embeddedness” through the nature of wealth distribution, social capital, and ritual purity affects entrepreneurial choices and presents a typology of “caste,” “caste-advantage,” “caste-restricted,” and “noncaste” businesses that characterize the economic life of India.

We define a family of discontinuous maps on the circle, called Bowen–Series-like maps, for geometric presentations of surface groups. The family has $2N$ parameters, where $2N$ is the number of generators of the presentation. We prove that all maps in the family have the same topological entropy, which coincides with the volume entropy of the group presentation. This approach allows a simple algorithmic computation of the volume entropy from the presentation only, using the Milnor–Thurston theory for one-dimensional maps.

With the growing amount of historical infrastructure data available to engineers, data-driven techniques have been increasingly employed to forecast infrastructure performance. In addition to algorithm selection, data preprocessing strategies for machine learning implementations plays an equally important role in ensuring accuracy and reliability. The present study focuses on pavement infrastructure and identifies four categories of strategies to preprocess data for training machine-learning-based forecasting models. The Long-Term Pavement Performance (LTPP) dataset is employed to benchmark these categories. Employing random forest as the machine learning algorithm, the comparative study examines the impact of data preprocessing strategies, the volume of historical data, and forecast horizon on the accuracy and reliability of performance forecasts. The strengths and limitations of each implementation strategy are summarized. Multiple pavement performance indicators are also analysed to assess the generalizability of the findings. Based on the results, several findings and recommendations are provided for short-to medium-term infrastructure management and decision-making: (i) in data-scarce scenarios, strategies that incorporate both explanatory variables and historical performance data provides better accuracy and reliability, (ii) to achieve accurate forecasts, the volume of historical data should at least span a time duration comparable to the intended forecast horizon, and (iii) for International Roughness Index and transverse crack length, a forecast horizon up to 5 years is generally achievable, but forecasts beyond a three-year horizon are not recommended for longitudinal crack length. These quantitative guidelines ultimately support more effective and reliable application of data-driven techniques in infrastructure performance forecasting.

This retrospective cohort study examined the relationship between a continuous measurement of bilingual engagement (operationalized as language entropy) and cognitive aging in regional minority language speakers. We drew Frisian–Dutch bilinguals (n = 7,448) and Low Saxon–Dutch bilinguals (n = 10,114) from the Lifelines Cohort Study and included participants aged 20–80, enabling an adult lifespan perspective. Cognitive functioning was measured using the Cogstate Brief Battery, which assesses processing speed, attention, working memory and recognition memory. We did not observe a robust relationship between bilingual engagement and cognitive functioning. Our results suggest that bilingual engagement does not play a key role in processing speed, attention, working memory and recognition memory performance in Frisian–Dutch and Low Saxon–Dutch bilinguals. Implications for the bilingual engagement measurement and potential investigations into regional minority language bilingualism and cognition are discussed.