The status of taxonomic knowledge varies across the Globe. Quantifying and mapping the geographic patterns of taxonomic status is essential to prioritise regions that require greater attention from the taxonomic community. Here, we compiled all valid orthopteran species names and their synonyms, extracted from the Catalogue of Life (CoL) and allocated them geographically, based on data from the Global Biodiversity Information Facility (GBIF) and the Orthoptera Species File (OSF). This allowed us to create measures of taxonomic effort, based on the date of species descriptions and the number of associated synonyms and combine them across space. Our analyses show that the descriptions of currently valid species increased exponentially since the 19th century, with a temporary decline following World War II, while synonyms outpaced the number of valid species until the 1980s. The number of taxonomists also increased over time, with declines after World Wars, followed by a significant rise from the 1950s onwards, continuing through the 21st century (with > 100 taxonomists currently active). Per-taxonomist description rates transitioned from highly variable before the 20th century to consistent rates of 5–10 species annually with collaborative efforts. Tropical regions and the Southern Hemisphere hold the majority of recently described species names with fewer associated synonyms, indicating a predominance of alpha taxonomy and highlighting the need for greater taxonomic efforts. In contrast, temperate regions, particularly in Europe and south-western Asia, contain the majority of older names and synonyms, indicating a predominance of beta taxonomy and regions that have been more thoroughly studied. Our findings are discussed in the context of sociopolitical factors, scientific investments and the history of taxonomy. Finally, we propose a framework that makes the links between taxonomy and macroecology accessible for biodiversity in the era of Big Data. Alpha taxonomy (i.e. the description of new species) and Beta taxonomy (i.e. the revision of the taxonomic status and relationships of already described taxa) vary across space and time. We present a framework that connects taxonomy and macroecology, allowing us to assess taxonomic trends to provide information for biodiversity studies in the era of Big Data. We mapped alpha taxonomy rates using the date of species descriptions across space and beta taxonomy rates using the number of synonyms associated with each species. We combined alpha and beta taxonomy rates to understand the global taxonomic status of Orthoptera (Arthropoda, Insecta), the sixth most species-rich insect order, which includes grasshoppers, crickets, katydids and relatives. In tropical regions, orthopteran taxonomy is recent and has few revisions, while in temperate regions, it is older and more consolidated.

Abstract Background: Large Language Models´ (LLMs) potential for psychological diagnostics requires systematic evaluation. Objective: To investigate conditions for reliable and valid psychological assessments, focusing on suicide risk evaluation in clinical data by comparing LLM-generated ratings with human expert ratings across across configurations. Methods: We analyzed 100 youth crisis conversation transcripts rated by four experts using the Nurses Global Assessment of Suicide Scale (NGASR). Using Mixtral-7x8b-Instruct, we generated ratings across three temperature settings and prompting styles (zero-shot, few-shot, chain-of-thought). Across configurations we compared a) inter-rating-reliability for AI-generated NGASR risk and sum scores, b) LLM-to-human observer agreement regarding sum score, risk category, and item, using Krippendorff´s α, c) classification metrics of risk categories and individual items against human ratings. Results: LLM configuration strongly influenced assessment reliability. Zero-shot prompting at temperature 0 yielded perfect inter-rating reliability (α=1.00, 95% CI: [1-1] for high & very high risk), while few-shot prompting showed best human-AI agreement for very high risk (α=0.78, 95% CI: [0.67-0.89]) and strongest classification performance (balanced accuracy 0.54-0.71). Lower temperatures consistently improved reliability and accuracy. However, critical clinical items showed poor validity. Discussion: Our findings establish optimal conditions (zero temperature, task-specific prompting) for LLM-based psychological assessment. However, inconsistent clinical item performance and only moderate to-human agreement limit LLMs to initial screening rather than detailed assessment, requiring careful parameter control and validation.

ABSTRACT Carceral geography has critiqued the notion of a clear binary between the inside and outside of prisons, revealing that the prison boundary is porous and that the prison materializes in multiple forms outside of its apparent margins. However, extant scholarship focusing on (formerly-)incarcerated individuals and others whose engagement with the prison is involuntary has tended to elude prison staff experiences of these porous and permeable borders. In this article, drawing on a large ESRC-funded study of the Victorian-era prison estate in the UK, and focusing on prison staff living accommodation, we consider the implications of a porous prison boundary for prison staff, and trace the ways in which the prison can also reach beyond its formal perimeter walls into their social and domestic lives. We suggest that unlike for (formerly-)incarcerated persons and communities involuntarily engaged with the prison, the staff experience of this permeability may be less clear-cut and more equivocal.

Abstract The increasing reliance on data-driven technologies such as Artificial Intelligence (AI) and Process Mining has transformed various sectors. Yet, access to real-world data is often restricted by privacy concerns. Synthetic data offers a promising solution by enabling secure data sharing while preserving key characteristics for analysis. This paper introduces the Private Autoregressive Log Synthesizer (PALSYN), a novel approach for generating synthetic event logs with differential privacy guarantees. It employs advanced deep learning techniques to capture the complexity of event data while ensuring privacy. In contrast to existing methods, PALSYN can synthesize private multi-perspective event logs. The evaluation demonstrates the approach's ability to generate synthetic event logs that closely resemble the original data across key metrics. However, the results highlight the inherent privacy-utility tradeoff, with stricter privacy settings introducing noise that strongly impacts utility. By enabling the generation of synthetic event logs with formal privacy guarantees, PALSYN demonstrates significant potential for securely sharing event data in privacy-sensitive domains.

The way we perceive the movement of two intersecting discs can be influenced by auditory information. When a brief tone is played while these discs overlap, people tend to report that the discs bounce off each other instead of streaming past each other. This is known as the auditory-induced bouncing/streaming illusion. Both perceptual/attentional and decisional processes have been discussed as explanations for the bouncing/streaming illusion. In four experiments, we study how the abruptness of tone onsets and offsets affects the bouncing/streaming illusion. We found that tones with more abrupt onsets and offsets resulted in a higher proportion of bouncing impressions than those with smoother ones (Experiment 1). This effect was not due to differences in loudness between the tones (Experiment 2). Additionally, we found that the abruptness of the tone onset, rather than the offset, caused the increase in bouncing impressions (Experiment 3). This effect was observed regardless of the temporal alignment of the tones with the moment of visual overlap (onset-aligned vs. centered vs. offset-aligned; Experiment 4). In sum, our results revealed evidence in favor of a chain of perceptual as well as decisional processes contributing to the reported bouncing/streaming impressions, and we discuss how both might interact during the resolution of the ambiguous bouncing/streaming display. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Gilles de la Tourette Syndrome (GTS) is a multi-faceted neuro-psychiatric disorder. While novel conceptions overcoming the criticized categorization of GTS as a movement disorder are on the rise, little is known about their neural implementation and whether there are links to known pathophysiological processes in GTS. This is the case for conceptions suggesting that aberrant perception-action processes reflect a key feature of GTS. Building on the concept that overly strong perception-action associations are pivotal to understanding GTS pathophysiology, we examined how these associations influence response inhibition and used EEG methods to examine the importance of theta, alpha and beta band activity due to their known relevance for GTS pathophysiology. In this case-control study, behavioural analyses revealed that adult patients with GTS experienced greater difficulty during motor response inhibition when perceptual features of Nogo stimuli overlapped with perceptual features of Go stimuli, indicating impaired reconfiguration of perception-action associations. Neurophysiological findings showed robust differential patterns of modulation in theta and alpha band activity between neurotypical (NT) individuals and GTS patients. Specifically, GTS patients exhibited stronger and more extended theta band modulation but weaker and more restricted alpha band modulation during overlapping Nogo trials than NT individuals. Unlike NT individuals, GTS patients did not exhibit beta band modulations necessary for dynamically handling perception-action codes. The findings highlight increased theta band modulation in GTS patients' significant stronger perception-action bindings and a lack of compensatory alpha band modulation. The robust differential modulation observed provides novel insights, emphasizing theta and alpha oscillations as key elements in GTS pathophysiology and offering potential implications for targeted cognitive-behavioural interventions.

Zusammenfassung Nach vierzig Jahren intensiver kontrastiv-linguistischer Forschung in der chinesischen Germanistik erscheint es sinnvoll und notwendig, über einige grundlegende Fragen des deutsch-chinesischen Sprachvergleichs nachzudenken. Der vorliegende Beitrag analysiert exemplarisch Forschungsbeiträge chinesischer Germanistinnen und Germanisten der letzten Jahrzehnte mit dem Ziel, bestehende Probleme zu identifizieren, überholte Modelle zu hinterfragen und neue Erkenntnismöglichkeiten auszuloten. Im Mittelpunkt der Diskussion steht die Erörterung einer interkulturellen Perspektive für die sprachvergleichende Forschung.

Variance parameter estimation in linear mixed models is a challenge for many classical nonlinear optimization algorithms due to the positive-definiteness constraint of the random effects covariance matrix. Many existing algorithms may get stuck on the boundary of the feasible space. In this paper, we address this problem by exploiting the intrinsic geometry of the parameter space, pulling iterates away from the boundary. In this novel approach, we formulate the problem of residual maximum likelihood estimation as an optimization problem on a Riemannian manifold. Based on the introduced formulation, we give geometric higher-order information on the problem via the Riemannian gradient and the Riemannian Hessian, making the algorithm more robust against singularities. We test our approach with Riemannian optimization algorithms numerically. Our approach yields a much better quality of the variance parameter estimates compared to existing approaches.