Clozapine remains the only evidence-based treatment for treatment-resistant schizophrenia, supported by guidelines from the National Institute for Health and Care Excellence (NICE) and other authorities. However, clozapine is still underutilised for treatment-resistant schizophrenia, despite its proven benefits, including reduced all-cause mortality. This is attributed mainly to its association with adverse effects, including cardiac adverse effects. This review focuses on the latter, with a detailed exploration of clozapine-induced myocarditis – a potentially fatal acute hypersensitivity reaction – and cardiomyopathy, tachycardia and conduction deficits. Among other things, we discuss their pathophysiology, diagnosis and management, with signposting to international diagnostic criteria and monitoring protocols.

In this article, I explain how peasant communities were affected by fire disasters in North Ostrobothnia in northern Finland during the seventeenth century. Unlike previous research mainly based on dendrochronological data aimed at dating these fire disasters’ scope and occurrence, I focus on the socio-economic consequences of wildfires from both a bottom-up and a top-down perspective in order to establish different factors of resilience and vulnerability. Through the analysis of local district court protocols, tax records and Swedish legislation, the article explains how and why fires occurred and what role peasant common-pool institutions and the early modern Swedish state played in this development. The results show how peasant communities were able to bounce back from recurrent events of fire disasters thanks to close cooperation between them and Swedish officials, the reinvigorated medieval relief institution of fire support (Swe. brandstod), and owing to the robustness of the peasants’ common-pool institutions.

Small-leaf spiderwort (Tradescantia fluminensis Vell.) is a low-growing perennial ground cover that has become increasingly problematic in Florida due to its ability to quickly spread vegetatively over large areas and outcompete native vegetation. Prior research has identified several herbicides that can be used to manage T. fluminensis, but the effect of application timing on herbicidal efficacy is unknown. Therefore, the objective of this study was to evaluate the efficacy of selected postemergence herbicide applications and to understand differences in the efficacy of these timings (i.e., spring and fall), including on the rate of regrowth of target plants. Specific herbicides evaluated in this study included 2,4-D, 2,4-D + triclopyr amine, aminopyralid, glyphosate, and triclopyr (as acid and amine). An additional aspect of this study was to reapply treatments when coverage ratings exceeded 25% to assess the impact of sequential applications when using less efficacious herbicides that might provide greater selectivity to non-target plants. Overall, the data showed that initial treatment timing had little to no impact on efficacy for most of the herbicides evaluated. Triclopyr (acid or amine) tended to provide the highest level of control and required no retreatment over a 12-mo evaluation period. Other effective options included glyphosate and 2,4-D + triclopyr amine, which provided results similar to triclopyr on most evaluation dates. The 2,4-D and aminopyralid treatments were in general the least efficacious options, requiring retreatment at either 3, 6, or 9 mo following the initial application to achieve less than 25% T. fluminensis coverage. Results indicate that practitioners would likely achieve similar levels of T. fluminensis control regardless of application timing. Data also suggest triclopyr would be the most effective option, while a low level of control would be expected with 2,4-D, even following multiple applications.

A wall-modelled large eddy simulation approach is proposed in a discontinuous Galerkin (DG) setting, building on the slip-wall concept of Bae et al. (J. Fluid Mech., vol. 859, 2019, pp. 400–432) and the universal scaling relationship by Pradhan and Duraisamy (J. Fluid Mech., vol. 955, 2023, A6). The effect of the order of the DG approximation is introduced via the length scales in the formulation. The level of under-resolution is represented by a slip Reynolds number and the model attempts to incorporate the effects of the numerical discretization and the subgrid-scale model. The dynamic part of the new model is based on a modified form of the Germano identity -- performed on the universal scaling parameter -- and is coupled with the dynamic Smagorinsky model. A sharp modal cutoff filter is used as the test filter for the dynamic procedure, and the dynamic model can be easily integrated into any DG solver. Numerical experiments on channel flows show that grid independence of the statistics is achievable and predictions for the mean velocity and Reynolds stress profiles agree well with the direct numerical simulation, even with significant under-resolution. When applied to flows with separation and reattachment, the model also consistently predicts one-point statistics in the reverse flow and post-reattachment regions in good agreement with experiments. The performance of the model in accurately predicting equilibrium and separated flows using significantly under-resolved meshes can be attributed to several aspects that work synergistically: the optimal finite-element projection framework, the interplay of the scale separation and numerical discretization within the DG framework, and the consistent dynamic procedures for subgrid and wall modelling.

The European Green Deal (EGD) provides a strategic framework for the European Union’s (EU) transition to climate neutrality by 2050. Yet, limited integration of socio-economic dimensions may hinder its long-term success and fairness. This study investigates the indirect impacts of socio-economic factors on EGD performance by constructing a Green Deal Performance Index (GDPI) using a multi-criteria decision-making approach for 22 EU countries over 2010–2020. We then apply an instrumental variable regression approach to estimate how emissions, shaped by structural socio-economic conditions, affect the GDPI. Our results show that the negative impact of emissions is nearly 47 times larger when socio-economic dynamics are ignored. These findings underscore the necessity of inclusive policymaking for achieving carbon neutrality, contributing to discussions on ensuring a just transition by highlighting the critical role of socio-economic dynamics. We also present implications for policymakers developing fair and equitable strategies promoting sustainability and social justice in this context.

This article offers a view of the prospects of nuclear fusion as a sustainable energy source, with a focus on magnetic confinement fusion and tokamaks. It highlights the key theme of integration and presents the EUROfusion programme as a model for coordinated fusion R&D in Europe while stressing the need for public–private partnerships to bridge the gap between laboratory innovation and industrial implementation. A crucial element is human capital development, i.e. the training of a new, diverse generation of scientists, engineers, and technicians. A broader educational effort is called for, with industry–academia collaboration, hands-on training, and mechanisms to retain and transfer knowledge from legacy projects such as JET.

Carbon credits have become increasingly important for supporting sustainable forest management and mitigating climate change. However, carbon projects can be challenging for local communities and smallholders to implement due to high expenses and complicated protocols. Forest projects often suffer from inefficiency, lack of transparency, and uneven benefit distribution. This study suggests a blockchain-based framework for aggregating forest carbon projects. This framework is the first in the forest sector to provide a reward mechanism for local communities or smallholders with a direct integration into an accredited registry protocol of Monitoring, Reporting, and Verification. The system combines digital identities, smart contracts, and automated incentives to improve transparency, responsibility, and trust among stakeholders. Two types of tokens are introduced: (i) Carbon Coin represents verified carbon credits within the system; and (ii) Forest Coin functions as a security token used to proportionally distribute project revenue among stakeholders. The revenue distribution was demonstrated in scenarios of afforestation, reforestation, and conservation. In addition, a web application was developed so that users can monitor project details. Unlike most blockchain carbon platforms that focus on investment and trading, this framework addresses upstream challenges, prioritising equitable benefit-sharing. The framework supports project aggregation and prioritises community ownership, advancing inclusive access to the carbon market. This study demonstrates how technological advantages can be transferred to community-driven ecological conservation.