As the climate crisis intensifies, fossil fuel industry funding of academic research faces increasing scrutiny. This research examines the complex interplay between fossil fuel funding, corporate capture, and academic integrity in higher education, uncovering how public discourse frames industry funding as a mechanism of climate obstruction and delay. Employing a comparative approach, we analyse how fossil fuel funding is addressed in institutional policies versus public discourse across the UK and US, while investigating the emerging Fossil Free Research movement and its parallels with Fossil Fuel Divestment campaigns. Our findings reveal a significant disparity between public discourse and institutional governance approaches to fossil fuel funding, highlighting the pervasive presence of climate delay discourse and disinformation within academia. We identify country-specific differences between the UK and US shaped by their distinct higher education systems, while underscoring the need for policy reforms that protect transparency, research integrity, and academic freedom. The study concludes that these mechanisms of influence transcend fossil fuel funding, revealing how corporate interests across industries - from chemical and pharmaceutical to agriculture and technology sectors - systematically shape academic research to serve the profit-seeking interests of the private sector rather than the interests of the public, particularly in climate-related fields. Thus, we emphasise the imperative for higher education institutions to adopt stronger policies protecting the integrity of climate research and its crucial role in societal decision-making and reclaiming the public mission of higher education.
A recent challenge is how to mix qualitative interpretation with computational techniques to analyze big qualitative data. To this end, we propose “multi-resolution design” for mixed method analysis of the same data: qualitative analysis zooms-in to provide in-depth contextual insight and quantitative analysis zooms-out to provide measures, associations, and statistical models. The raw qualitative data is transformed between excerpts, counts, and measures; with each having unique gains and losses. Multi-resolution designs entail transforming the data back-and-forth between these data types, recursively quantitizing and qualitizing the data. Two empirical studies illustrate how multi-resolution design can support abductive inference and increase validity. This contributes to mixed methods literature a conceptualization of how mixed analysis of the same big qualitative dataset can create tightly integrated synergies.
Restoration of degraded marine and coastal areas is a priority set by European policy makers, as exemplified by the recent adoption of the European Nature Restoration Law (NRL) in June 2024. This legislation-driven approach is expected to expand the European marine restoration community rapidly as the amount of funding and projects grows to meet the targets outlined by the NRL However, it is difficult to assess the success of restoration activities which is vital to ensure the viability of upscaling. Furthermore, best practices are not well established in the marine realm and scientific networks are still in their early stages of development. Here, we outline our development of a digital, online toolbox for marine restoration in collaboration with the European restoration community. The toolbox aims to go beyond simply making data FAIR (Findable, Accessible, Interoperable, and Reusable) through the creation of science-based digital services that allow for use of information for decision-making for marine restoration. The toolbox is constructed in a modular way to fulfil the needs of a diverse range of users across Europe and includes a centralized space to find methodological approaches, relevant networks, funding opportunities, and resources. The digital tools under development will be openly accessible through the Blue-Cloud 2026 platform within the thematic virtual research environment for marine restoration, which allows for the scalable use and reuse of data and code by any interested user. The toolbox aims to provide restoration community members science-based methods from which they can leverage and accelerate their restoration projects. In the pursuit to democratize access to best practices and knowledge, we go beyond providing code or data in static repositories. Based on our experience, we encourage others that are developing toolboxes or knowledge bases for diverse user groups to consider taking advantage of publicly funded infrastructure to promote their work according to open science practices.
Sulfur-driven autotrophic denitrification (SAD), an organic-free biological nitrogen removal process driven by sulfur-based electron donors (SEDs), offered advantages including low energy consumption, low sludge yield, and reduced greenhouse gas emissions. The sulfur-based compounds, with their abundant global reserves and cost-effectiveness, serve as utilizable electron donors for advanced nitrogen removal in wastewater treatment and polluted water remediation. Research on a variety of SEDs and SAD processes had expanded significantly, yet documentation of their large-scale implementation remained scarce in industrial practice. This paper presented a comprehensive review of the research and application of SADs over the past two decades. It summarized and compared the physicochemical properties and nitrogen removal performance of various SEDs, and evaluated their economic and environmental impacts. Moreover, the key factors affecting SAD efficiency were identified, along with feasible solutions to support its large-scale applications. Nitrous oxide (N2O) emissions were considered a critical indicator for evaluating the sustainability of future wastewater treatment technologies. Therefore, this study also examined the N2O emission characteristics from SAD processes, highlighting their potential for low-carbon applications, and further proposed strategies to mitigate N2O emissions. Finally, the review outlined future research directions and prospects of SAD, providing insights to filter material development and guide process design in engineering applications. This study systematically evaluated the merits and constraints of SAD, delineating critical application bottlenecks while identifying potential unresolved scientific challenges demanding further investigation.
To examine the relationships between subjective sleep quality, chronotype and social jetlag with perceived psychological stress in a sample of Irish adults. An observational cross-sectional study of 400 adults. Subjective sleep quality was assessed with the Pittsburgh Sleep Quality Index, chronotype and social jetlag were assessed with the Munich Chronotype Questionnaire, and psychological stress was measured with the Perceived Stress Scale. Correlational, groupwise and path analyses were applied to the data to examine the relationships between perceived stress and sleep variables, age and sex. Bivariate correlation analyses revealed statistically significant associations between both social jetlag and mid-sleep on free days and perceived stress (small effects), and moderate associations between subjective sleep quality and perceived stress. Groupwise analysis revealed that individuals in the high perceived stress group displayed greater social jetlag and poorer sleep quality, but no difference in chronotype, when compared to those with low or moderate stress. Path analysis revealed a moderate reciprocal relationship between subjective sleep quality and perceived stress, no direct effects of chronotype or social jetlag on perceived stress and a small indirect effect of average nightly sleep duration on perceived stress mediated through subjective sleep quality. Chronotype and social jetlag have minimal relationships with perceived stress, whilst subjective sleep quality has a moderate reciprocal relationship with perceived stress.
