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Whether voluntary GHG disclosure could help improve subsequent GHG performance-new global evidence
No full textIn light of the Conference of Parties 26, carbon information reporting has become ever-increasingly important. Prior studies presented much evidence on whether environmental disclosure could reliably reflect environmental performance. However, very limited evidence has been provided on if environmental disclosure could drive firms to improve future environmental performance. Based on the competing theoretical predictions from the legitimacy theory and the “outside-in” management perspectives, this study provides new international insight into if carbon disclosure improvements could motivate future carbon performance improvement based on a change analysis. Particularly, the investigation uses a recently available carbon data set of both developed economies and developing economies from the Carbon Disclosure Project and other publicly available media platforms. We find that an improvement in carbon disclosure indicates a future carbon performance deterioration in developed economies, however, carbon disclosure changes are not related to future carbon performance changes in developing economies when using performance data from the Carbon Disclosure Project. When using performance data from other publicly available media platforms, carbon disclosure changes are not related to future carbon performance changes at all internationally. This indicates that the carbon information disclosed on other public media platforms has been intentionally beautified. Thus, firms' carbon performance changes from these platforms lose track of the prior changes in firms' carbon disclosure.</p
A methodological exploration of the P-frame approach: implications for developing phrase lists
No full textThe widespread availability of corpora and corpus tools has led to considerable advances in our understanding of phraseology and how it can be investigated. An increasingly influential approach to investigating phraseology is the retrieval and analysis of phrase frames (p-frames), recurrent word sequences with a variable slot. Although the p-frame approach is quite well-established, pedagogically oriented research in this area is still quite new, in particular the application of phrase frames to generate useful lists of phrases. This paper aims to contribute to methodological efforts in this direction by presenting a case study to illustrate decision-making throughout the process from corpus compilation to the generation of a final pedagogical list of phrases. Using a corpus of research article (RA) introductions in Health Sciences, this study shows how key decisions including p-frame length, frequency and range thresholds were arrived at. It also discusses exclusion criteria focusing on variability and predictability of p-frame fillers, and the fine-tuning of the resulting list, focusing on semantic coherence and pedagogical usefulness. Finally, we present the results of an initial evaluation of the list by stakeholders. The main contributions of the study to p-frame research methodology lie in the clarification of threshold settings, the potential contribution of variability and predictability to decision-making and the proposal of more in-depth concordance analysis of co-text to aid in the identification of phrases
An ultra-precise fast fourier transform – part 2
Full text linkAn earlier paper [1] describes the application of Prism Signal Processing to the Fast Fourier Transform (FFT), which generates high precision estimates of the frequency, amplitude and phase of spectral peaks. The current paper describes improvements to the Prism FFT. These include: a simplified calculation; applicability to shorter FFT window lengths (e.g. 1024 samples); improved performance against the Cramer Rao Lower Bound (CRLB), typically delivering root mean square errors of 2.2σ for frequency and 1.5σ, for amplitude and phase, where σ is defined as the square root of the corresponding CRLB. The method also delivers significantly reduced spectral leakage. MATLAB code implementing the Prism FFT is provided as an appendix
Exploring the training, implementation and utilisation experiences of lung ultrasound accredited physiotherapists in the United Kingdom:A national survey
No full textBackground: With 10-years’ worth of growth in the use of LUS by physiotherapists within the U.K., this survey explores their training, implementation and clinical practice experiences. Methods: A cross-sectional survey was delivered to U.K. Physiotherapists accredited in LUS. The 50-question survey was administered via JISC online and was open for 4-weeks in January 2025. Closed questions were presented descriptively; open questions underwent inductive conceptual content analysis and descriptive coding. Results: Of the 223 invitations, 168 surveys were returned (75% response rate). Responses were highest from four U.K. regions which correlated with a higher number of regional mentors. Most respondents were in band 7 static roles, accredited via FUSIC® and worked on the ICU with respiratory or surgical patients. The primary indication to perform a LUS was an increase in the fraction of inspired oxygen, average scanning frequency was 1–2 per week and common pathological findings were consolidation (pneumonia and atelectasis) plus pleural effusion (transudative and exudative). The most common negative factors experienced overall were limited time to scan and access to an US machine. Additional negative factors were limited access to a mentor during training, limited support from other professions during implementation, limited access to an appropriate patient population to scan during clinical practice. Conclusion: This is the largest survey to investigate the experiences of physiotherapists using lung ultrasound in the U.K. and provides important insights during training, implementation and clinical use. The specific details of these findings will support both current and future LUS users to plan and develop robust physiotherapy LUS service.</p
Co‑designing a research agenda for UK agroforestry using a multi‑actor approach
Full text linkThere is growing recognition of agroforestry’s potential to help mitigate and provide resilience to the climate and biodiversity crises. Beyond its environmental benefits, agroforestry can also enhance production and profits, making it a sustainable farming solution that is scalable. Despite this, uptake within Europe is low, and many knowledge gaps remain that need to beaddressed to promote adoption and optimize the management and implementation of agroforestry systems. We co-developed a research agenda for agroforestry using a multi-actor approach and a modified Delphi method in 2023. 156 UK-based stakeholders contributed to this process, including farmers, advisors, policy makers, NGOs, and researchers. An initial list of 238 research priorities (high-priority research questions) was submitted via a survey and a workshop. This was shortened during a second workshop with 48 participants. The final list included 40 research priorities across the themes “environmentand production,” “human livelihoods, knowledge, and perceptions,” and “policy, financing, and markets.” There was high agreement about which priorities to include, with questions on policy incentives, knowledge-exchange, agroforestry design (e.g., tree/crop selection), biodiversity, ecosystem functioning, well-being, markets, and food security. We identified a need for landscape-scale and longer-term research. Our agenda is a rare example of a research-prioritization process that includes farmers and other agricultural stakeholders throughout the research process. The value of this approach can be seen in the inclusion of research priorities that are grounded in the real world and relevant to different actors. Our agenda goes beyond existing evidence syntheses in scope, and should be used alongside them to identify stakeholder-relevant gaps for future primary research and evidence synthesis. By guiding researchers and funding bodies to impactful areas of enquiry, it can promote evidence-based agroforestry practice and policy. Addressing this research agenda requires better support for longterm, transdisciplinary, multi-stakeholder research, and funded demonstration sites or living labs
Enhancing ecosystem services to mitigate agro-environmental pressures:integrating participatory mapping and land suitability analysis for crop-livestock mixed farming and agroforestry systems
Full text linkStakeholders from six European pilot sites engaged in participatory mapping and land suitability assessments to co-design climate-smart strategies for sustainable land management. The mixed methodology applied combined GIS based landscape vulnerability analysis, stakeholder knowledge, and assessments of ecosystem services. Key phases included preliminary assessment of environmental pressures, participatory SWOT analysis, and collaborative mapping exercises to identify suitable mixed farming (MF) and agroforestry (AF) practices. This approach empowered local communities, enhanced knowledge exchange, and integrated socio-ecological dimensions into land-use planning. Participatory mapping proved effective in capturing spatial perceptions, guiding context-specific transitions, and building consensus on landscape-scale interventions. Based on environmental pressure indicators, the scaling-up analysis showed that, depending on local conditions, the proportion of areas suitable for MF and AF ranged from 2 to 61% of the total area analysed across the six pilot sites. All the stakeholders agreed on the introduction of MF and AF and expressed differing views on their potential to reduce the environmental pressures of agricultural practices and enhance ecosystem services. Practitioners, such as farmers and advisors, emphasised the need for greater knowledge and stronger policy support to implement the transition toward more agroecological farming systems. While results highlight the large potential for MF and AF (up to 61% of the land use, in certain cases), it also showed the importance of participatory tools in bridging scientific research and practice, reinforcing the role of stakeholder engagement in designing resilient and multifunctional agricultural systems. While this might help to bridge the gap between planning and the implementation of agroecological practices across diverse European contexts, further research on the implementations and the socio-economic assessment of MF and AF at landscape scale is needed.</p
Animism and the transmission of ecological knowledge in African children’s books:a close look at Ken Wilson-Max’s Eco Girl and Helvi Itenge’s Nekwa and the Baobab Tree
Full text linkThis article considers how African children’s picture books depict animist cosmologies and transmit ecological knowledge across generations. With a close reading of Ken Wilson-Max’s Eco Girl (2022) and Helvi Itenge’s Nekwa and the Baobab Tree (2023), it argues that these texts construct relational ontologies in which trees, animals, ancestors, and children participate in a shared moral ecology. Drawing on African philosophies of ubuntu, ukama, and eniyan, and Harry Garuba’s “animist unconscious” and Fikret Berkes’ theory of Traditional Ecological Knowledge (TEK), the article provides an analysis on oral esthetics, taboo logic, and intergenerational practices. Nekwa and the Baobab Tree foregrounds the baobab as elder and moral agent, using taboo, song, and multispecies cooperation to stage ecological correction as cosmological rebalancing. Eco Girl presents a quieter ecological becoming grounded in diasporic memory, familial tree-planting rituals, and imaginative kinship with the baobab. These books frame the baobab as an ecological “Tree of Life” and ancestral archive, mediating ethical relations between humans and the more-than-human world. The focus on early-childhood picture books rather than adult fiction extends African ecocriticism into the domain of children’s literature, showing how animist ethics and intergenerational storytelling shape ecological subjectivities and model environmentally embedded forms of African childhood
Cavity collapse associated with oil entry of steel spheres
No full textThe collapse of air cavity towards the liquid surface that occurred immediately after deep seal following vertical entry of steel spheres into a pool of oil, was experimentally investigated. The vertical displacement between the pinch-off depth and the cavity base during the time when the cavity was collapsing towards the surface, was regularly measured and analysed using images taken from a high-speed camera. Furthermore, some phenomena associated with the upward oil jet generated during cavity collapse were also described and briefly studied. The results suggested that the rate of cavity collapse towards the surface, and the time taken for the lower part of the oil jet to reach surface level, were dependent on both the inertial and gravitational forces of the spheres
A probabilistic multi-variable hybrid approach to window operations and indoor comfort in residential dorms
No full textOccupant window interaction is a critical component in optimizing energy consumption and indoor environmental quality (IEQ). Understanding the influence of environmental and behavioral factors on window state decisions remains a significant challenge in building management systems (BMS). We present a hybrid probabilistic model to assess thermal comfort and predict the probability of the occupant opening or closing the window. The data was acquired from an open-source platform that provided yearly university dormitory window interactions. Bayesian networks (BNs) and logistic regression (LR) models were applied to predict the window-opening behavior of the occupants. An average accuracy of 92% for Bayesian and 94% for LR were obtained. The results were further enhanced by combining these models through weighted methods, with weights extrapolated through generative recursive iterations generating an average accuracy of 95% and Area Under the Curve (AUC) of 98%. The proposed hybrid approach significantly improves over existing predictive models in thermal comfort and window state prediction. Practical Application This research provides a practical tool for building engineers, facility managers, and smart system developers to significantly improve energy efficiency and occupant comfort. The developed hybrid model predicts window-opening behavior with high accuracy (95%). This enables the creation of next generation BMS that can anticipate occupant needs, proactively adjust heating, ventilation, and air conditioning (HVAC) operations, and reduce unnecessary energy consumption. For building designers, the model offers data-driven understandings into realistic occupant behavior (OB), leading to better-performing natural ventilation approaches