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Biodiversity accounting and accountability: the business of preventing extinction of species
No full textThis chapter examines the paradigm of extinction accounting, designed to hold organisations accountable for their environmental impact and the increasing emphasis on biodiversity conservation. The core tenets of extinction accounting challenge traditional organisational accountability by expanding its scope to encompass environmental and social considerations alongside economic performance. To achieve this, a novel extinction framework is detailed, drawing from existing frameworks and guidance. The framework introduces a model for integrating extinction-related reporting into established business structures, emphasising the vital role of proactive engagement and integrated thinking. Conclusively, the chapter advocates for the adoption of extinction accounting as a pivotal step toward integrating environmental responsibility into the fabric of organisational accountability, urging businesses to embrace a comprehensive approach that appreciates the interconnectedness of economic, environmental, and social imperatives
Adolescents’ food choice patterns at school: A data driven approach
Get PDFDiet quality is critical during adolescence, given the nutritional requirements and developmental changes. Foods that adolescents choose at school can contribute a considerable proportion to their dietary intake. This study's aim was to examine adolescents' food choice patterns in secondary school. Food selection data across an academic year for students (11-18 years) attending a secondary school in England were examined. Food choice profiles for students (n = 857) were derived, and cluster analysis was performed to determine food choice patterns. Associations between cluster membership and characteristics (sex, year group, free school meal status) were examined. Five clusters were differentiated based on adolescents' selection of foods and beverages. Clusters were characterised by dominant items: 'sandwich combo fans' (n = 340), 'break time snackers' (n = 196), 'traybake enthusiasts' (n = 161), 'pizza lovers' (n = 147) and 'healthy lunchers' (n = 13). The preponderance of a few items across clusters, specifically cookies and traybakes was notable, as was the relative size of the clusters. Significant associations were found between cluster membership and year group, free school meal status and sex, all with small effect sizes (φc = 0.19, 0.18 and 0.13, respectively). This study provides important insights into adolescents' food choice patterns during the school day, specifically the general dominance of cookies and traybakes, as well as the very small number of 'healthy lunchers'. Findings point to future work to examine the relative popularity of items, as well as targeted interventions to support adolescents' dietary health
Assessment of SWOT for monitoring ice-marginal lake water levels in Greenland
Get PDFThe Surface Water and Ocean Topography (SWOT) satellite mission provides a powerful data set for monitoring global surface water resources. However, its performance for monitoring ice-marginal lakes in Greenland remains unknown. Due to the scarcity of in situ measurements, this study evaluated the reliability of ice-marginal lake elevations derived from the SWOT Water Mask Raster Product by comparing to ICESat-2 LiDAR altimeter data. Results show that across 204 near-contemporaneous water level points for 110 lakes, the average deviation between SWOT and ICESat-2 was 0.03 m, with a root mean square deviation of 1.43 m, showing a good agreement. The higher temporal resolution of SWOT (<21 days over Greenland) enabled better monitoring of glacial lake outburst floods (GLOFs), with a 100% increase in the number of GLOFs detected compared to ICESat-2 between 2023 and 2024. These advantages make SWOT an excellent data source for monitoring ice-marginal lakes around the Greenland Ice Sheet
Working with underrepresented groups: lessons from the SCHEMA trial
Get PDFThere is a growing focus on ensuring research is accessible and inclusive to individuals traditionally not represented. To be truly inclusive, the broader context needs to be explored, as barriers might not only be linked to population characteristics but also to the complexity of their environment, and limited research opportunity within certain healthcare professions. The SCHEMA trial is a randomised controlled trial evaluating whether interpersonal art psychotherapy is effective at reducing aggressive behaviour in individuals with learning disability or borderline intellectual function in secure care. The trial illustrates the challenges and solutions to conducting research in secure care settings, a challenging environment, with an underrepresented patient population and healthcare professionals unfamiliar with conducting research. To better understand the challenges, a survey was circulated to understand site staff’s general experience with research and their specific experiences of the SCHEMA trial. Difficulty of balancing research with other responsibilities and a fear of making a mistake were the most common barriers. The top two facilitators were working with collaborators and the presence of clear guidelines and protocols. Site setup was identified as the most challenging stage of the trial, while follow-up data collection was identified as the least challenging. In response to these challenges, the central trial team worked closely with site staff to provide tailored support to address the unique needs of the healthcare professionals and participant population
Inferring photospheric horizontal flows from multiple observations with SUVEL models
Get PDFPhotospheric horizontal velocity fields play essential roles in the formation and evolution of numerous solar activities. Various methods for estimating the horizontal velocity field have been proposed in the past. Aiming at the highest available (and future) spatial resolution (10 km pixel−1) observations, a new method, the Shallow U-net models (SUVEL), based on realistic numerical simulation and machine learning techniques, was recently developed to track the photospheric horizontal velocity fields. Although SUVEL has been tested on numerical simulation data, its performance on solar observational data remained unclear. In this work, we apply SUVEL to the photospheric intensity observations from four ground-based solar telescopes (DKIST, GST, NVST, and SST) with the largest available apertures, and compare the results obtained from SUVEL with the Fourier local correlation tracking method (FLCT). Average correlation indices between granular regions and velocity fields inferred by SUVEL (FLCT) are 0.63, 0.81, 0.80, and 0.87 (0.00, 0.11, 0.16, and 0.10) for DKIST, GST, NVST, and SST observations. Higher correlation indices between the velocity fields tracked by SUVEL and granular patterns than FLCT reveal the superior performance of SUVEL, validating its reliability with respect to solar observational data
Long-term representational costs of overloading working memory
Get PDFCan learning too much information at once impair long-term retention of its meaning? Emerging evidence suggests that encoding too many items into working memory (WM) limits subsequent long-term memory (LTM) retrieval of their details and gist. These findings highlight a boundary condition for theories positing relatively automatic gist encoding. But how expansive is this boundary? Experiment 1 shows that it extends to older adults, despite their generally enhanced reliance on gist memory. In two older adult samples (n = 40 each), LTM gist retrieval was reduced for objects encoded in sets exceeding WM capacity. Experiment 2 shows that this boundary holds even when retaining items in LTM is essential. Under intentional long-term learning, young (n = 81) and older (n = 40) adults’ LTM gist retrieval remained affected by overloading WM at encoding. Results invite leading memory theories to reconsider the universality of relatively automatic gist encoding
Changes in HbA1c and diabetes-specific quality of life following structured type 1 diabetes education: Exploratory latent profile analysis of outcomes in the DAFNEplus trial
Get PDFAims
To identify meaningful clusters of participants with shared baseline characteristics (demographic, clinical, and psychological) from a sample of adults with type 1 diabetes (T1D) completing dose adjustment for normal eating (DAFNE) structured T1D education, or the updated DAFNEplus programme. Further, to determine whether those clusters respond differently, at 6- and 12 months, to DAFNE and DAFNEplus on core outcomes: HbA1c and diabetes-specific quality of life (QoL).
Methods
Latent profile analysis was conducted on the DAFNEplus randomised control trial dataset using relevant indicator variables (age; HbA1c; hypoglycaemia awareness; diabetes-specific QoL, distress, and positive well-being; fear of hypoglycaemia; satisfaction with diabetes management). Model fit indices were used to select the optimal number of clusters and multilevel linear regression models to estimate the effect of DAFNEplus (compared with DAFNE) on HbA1c and diabetes-specific QoL in each cluster.
Results
A total of n = 363 participants were included in the analysis (n = 147, 40% randomised to DAFNEplus). The final model included two clusters: the first was consistently worse off on clinical and psychological indicator variables. The multilevel analysis showed a significant adjusted mean difference, at 12 months (first cluster only), between DAFNE and DAFNEplus in diabetes-specific QoL (0.81; 95% CI: 0.19–1.43; p = 0.01), but not at other time points or in HbA1c.
Conclusions
This study suggests that DAFNEplus has significant added benefits in reducing the negative impact of diabetes on QoL for a subgroup of adults with T1D, but not for their HbA1c. This provides important insights for the future real-world implementation of the DAFNEplus programme
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