Prenatally diagnosed cardiac mass in a newborn caused cardiac tamponade. Cardiac MRI and histopathology confirmed a rare right ventricular mesenchymal hamartoma, previously reported only in the left ventricle.

In sign languages, aspects of event structure have been shown to be systematically reflected in the phonological structure of verb signs, as proposed by the Event Visibility Hypothesis (EVH). This study investigates the relationship between verb semantics and phonology in 119 verbs from Austrian Sign Language (ÖGS). Four Deaf signers evaluated the usability of these verbs in specific contexts to assess event structure, and then their responses were correlated with the phonological structure of the signs. For the majority of signs (N = 109), the semantics of event structure was reflected in their phonological form, mapping to end-state semantics as expected. For a few signs (with inchoativity), phonological forms correlated instead with event onset. Additionally, some signs allowed for argument structure alternations, which have been previously only rarely reported for sign languages. The findings support the claim that event structure is systematically mapped to verb sign phonology using physical properties of articulator motion, and further indicate the need to extend the taxonomy of event/argument structures inventory to encompass the variability across (sign) languages.

While the late Llandovery brachiopod faunas of South China are well documented, they are known almost exclusively from shallow-water settings. Here, we present a detailed study of a brachiopod fauna from the Ningqiang Formation (early to middle Telychian) at the Bifengguan section in Sichuan Province, South China. Quantitative analyses, including non-metric multidimensional scaling (NMDS) and network analysis, reveal three successive brachiopod associations. Significantly, the basal Aegiria–Epitomyonia association was characterized by the abundance of the deep-water indicator Epitomyonia. This represents the first definitive record of a deep-water (BA4) community within the Telychian Xiushan Fauna, which was previously thought to be restricted to shallower environments. This basal association is succeeded by the Aegiria–Megaspinochonetes and Fardenia–Striispirifer associations, and this complete succession indicates a shallowing-upward environmental trend from a BA4 to an upper BA3 setting. We interpret this shallowing trend as a response to regional uplift. The initial existence of this deep-water association was likely facilitated by the unique paleogeographical position of the locality, which likely provided a stable habitat for this deep-water community. This study expands the known ecological range of the Xiushan Fauna and underscores the critical role of local paleogeography in shaping benthic community structures during the early Silurian.

Research was conducted to evaluate the influence of adjuvants on hexazinone efficacy for smut grass control in greenhouse and field conditions. The greenhouse experiment was established in 2023 with two runs, comprising hexazinone at 1.12 kg ai ha-1, applied alone or with adjuvants (Grounded, NanoPro, and Sorbyx), and six simulated rainfall accumulation volumes (0, 6, 12, 25, 50, and 100 mm). In field trials, hexazinone was applied at 1.12 kg ai ha-1 with different adjuvants (BREAK-THRU, Grounded, NanoPro, and Sorbyx), and a non-treated control to small smut grass at Marianna, FL, in 2022 and 2023, and giant smut grass at Ona, FL, in 2022 and 2023. In the greenhouse experiment, the addition of all adjuvants to hexazinone improved efficacy, resulting in >78% control (30 DAT), <50% biomass (% of the non-treated control 30 DAT), and little to no regrowth by 60 DAT; applying hexazinone without an adjuvant resulted in <70% control (30 DAT), >52% biomass, and regrowth by 60 DAT. Similarly, adding Grounded, NanoPro, and Sorbyx to hexazinone in the field resulted in >63% smut grass density reduction. However, adding BREAK-THRU to hexazinone did not enhance its efficacy. Adjuvants Grounded, NanoPro, and Sorbyx enhanced the effectiveness of hexazinone in both the greenhouse and the field, indicating their potential for effective smut grass management.

Invasive, non-native plants frequently restructure ecosystems by homogenizing vegetation and altering trophic interactions, but the ecological consequences of invader removal are less predictable. Removal can redistribute light, nutrients and detrital resources, initiating community reassembly that extends beyond vegetation recovery and may facilitate secondary invasions. We used a single-site invasive-removal field study to examine how management of European buckthorn (Rhamnus cathartica L.) reshaped vegetation structure, litter accumulation and faunal communities in a post-industrial forest preserve in western New York, USA. Across 18 plots representing managed, not-treated and regrown buckthorn conditions, we quantified herbaceous vegetation, leaf litter biomass and the abundance of arthropods, pollinators and small mammals. Rhamnus cathartica removal was associated with a tenfold increase in herbaceous plant cover and species richness, producing structurally complex understories and higher arthropod and pollinator abundance. However, managed plots also supported three- to fivefold higher densities of the invasive European fire ant (Myrmica rubra [Linnaeus, 1758]) – corresponding with increased leaf litter in managed plots. Ant abundance was positively associated with thicker, more persistent litter layers rather than canopy openness, and increasing M. rubra density, in turn, corresponded with reduced pollinator abundance. Detritivore and rodent responses were more closely linked to vegetation structure and litter conditions than to ant abundance.

Effective weed management is critical to the long-term productivity of organic grain cropping systems. The Cornell Organic Cropping Systems Experiment was initiated in 2005 at the Musgrave Research Farm in Aurora, NY to compare four organic cropping systems that differed primarily in intensity of mechanical weed management and soil nutrient inputs. A three-year rotation of corn (Zea mays L.), soybean [Glycine max (L.) Merr.], and spelt (Triticum spelta L.)/red clover (Trifolium pratense L.) was grown in all systems. The four systems were characterized by High Fertility (red clover green manure, composted poultry manure, and commercial organic fertilizer to reach recommended fertility levels), Low Fertility (no fertility inputs other than the red clover and starter fertilizer for corn), Enhanced Weed Management (fertility management as in Low Fertility with additional tillage and cultivation and a higher spelt seeding density), and Reduced Tillage (primarily ridge tillage with different green manure crops). The experiment included two crop rotation entry points, enabling two of the three crops in the rotation to be grown every year. Results from the first two rotation cycles show that, in most cases, weed abundance and diversity increased during the transition to organic production, especially in the Reduced Tillage system. Perennial weeds increased in corn and soybean in the Reduced Tillage system in the second rotation cycle, which contributed to its poor performance relative to the three other systems. Our results suggest that increased soil disturbance, including tillage and cultivation in corn and soybean, plays an important role in reducing weed populations, whereas high fertility levels may exacerbate weed problems. These findings underscore the importance of balancing weed and nutrient management in enabling sustainable organic grain crop production.

In this editorial, three technological laggards reflect on the potential promises and pitfalls of artificial intelligence in psychiatry, as explored in recent BJPsych publications. We argue that the rapid changes driven by artificial intelligence are revealing underlying vulnerabilities within our profession. More importantly, we believe these shifts pose a fundamental challenge to our specialty: can we, as psychiatrists, evolve beyond mere intelligence to practice with genuine wisdom?

Understanding how political information is transmitted requires tools that can reliably and scalably capture complex signals in text. While existing studies highlight interest groups as strategic information providers, empirical analysis has been constrained by reliance on expert annotation. Using policy documents released by interest groups, this study shows that fine-tuned large language models (LLMs) outperform lightly trained workers, crowdworkers, and zero-shot LLMs in distinguishing two difficult-to-separate categories: informative signals that help improve political decision-making and associative signals that shape preferences but lack substantive relevance. We further demonstrate that the classifier generalizes out of distribution across two applications. Although the empirical setting is domain-specific, the approach offers a scalable method for expert-driven text coding applicable to other areas of political inquiry.

Recently, there have been several histories of the British Empire written through the lens of a single family. These works – which this review refers to as imperial family biographies – trace the activities, ideas, and/or connections of a group of individuals from the same family, usually spanning more than one generation, as they roved across the time and space of empire. They facilitate an understanding of a networked, informal British Empire, held together by personal bonds and material goods, and an imperial politics shaped by emotions, affections, and identities. Currently, imperial family biographies tend to prioritize asking what families can reveal about empire, rather than what empire can reveal about families; family networks are used as case studies, dictating the bounds of study and illustrating wider imperial themes. This review argues that this genre of history writing is most successful when families are interpreted as imperial agents that drove historical change, rather than merely conduits for individual action or means by which individuals were connected across empire. This can be achieved through a thorough engagement with the historiography on families and through centralizing concepts such as family identity, family culture, family structure, and family function.

Jabłonowski [‘On biquandle-based invariant of immersed surface-links, Yoshikawa oriented fifth move, and ribbon 2-knots’, Preprint, 2025, arXiv:2505.14724] proved that the knot quandles of Suciu’s n-knots, which share isomorphic knot groups, are mutually nonisomorphic, and Yasuda [‘Knot quandles distinguish Suciu’s ribbon knots’, Preprint, 2025, arXiv:2508.15129] later gave a different proof. We present yet another proof of this result by analysing the conjugacy classes of certain automorphisms of the free group of rank two.

This article examines the ethnic and gender quotas that have been applied to Burundi’s Constitutional Court since 2019. It shows that while gender quotas aim to make the court reflective or to remedy past injustices, ethnic quotas serve multiple roles: securing ethnic peace, de-escalating conflict or confirming power balances. Our analysis challenges scepticism about judicial quotas and independence, arguing that quotas do not inherently undermine legal merit, particularly when constitutional values are at stake. However, the position-sharing model poses risks to judicial independence, potentially diminishing court legitimacy. We highlight the complexities of combining ethnic and gender quotas, and we develop a typology of courts with such quotas, categorizing Burundi’s Constitutional Court as a blend of reflective, affirmative action, position-sharing and power-sharing. By examining Burundi’s experience, the article contributes to the debate on judicial quotas in segmented societies and the impact of identity-based representation on constitutional design, post-conflict governance and judicial independence.

In unstructured environments, Delta robots face challenges in achieving high vision-guided grasping precision due to dynamic lighting conditions and workpiece diversity. This paper designs an integrated solution that combines RGB-D multimodal learning with an enhanced Mask R-CNN framework. Initially, a dual-stream ResNet50-FPN backbone network is designed to achieve cross-modal adaptive alignment via hierarchical feature fusion. Subsequently, a depth-guided attention module is incorporated to bolster robustness against material ambiguity and reflective interference. Moreover, a dynamic depth estimation algorithm is employed to significantly improve target localization accuracy and stability. Finally, real-time trajectory tracking is realized by integrating PD control with Jacobian mapping. Experimental results validate the efficacy of the proposed method, offering an efficient and reliable approach for industrial robotic applications.