英国政府

The purpose of the 5th International Atomic Energy Agency technical meeting on fusion data processing, validation and analysis (FDPVA) (Ghent University, Ghent, Belgium, 12–15 June 2023) was to provide a platform during which a set of topics relevant to FDPVA were discussed with the view of meeting the needs of next step fusion devices such as ITER. The validation and analysis of experimental data obtained from diagnostics used to characterize fusion plasmas are crucial for a knowledge-based understanding of the physical processes governing the dynamics of these plasmas. This paper presents the recent progress and achievements in the domain of plasma diagnostics data analysis and synthetic diagnostics reported at the meeting, including concept description of new devices; fusion databases; integrated data analysis; inverse problems; uncertainty propagation, verification and validation; probabilistic methods and machine learning. The relevant results underline trends observed in the current major fusion confinement devices.

The larvae of the greater wax moth, Galleria mellonella, are gaining prominence as a versatile nonmammalian in vivo model to study host-pathogen interactions. Their ability to be maintained at 37 °C, coupled with a broad susceptibility to human pathogens and a distinct melanization response that serves as a visual indicator for larval health, positions G. mellonella as a powerful resource for infection research. Despite these advantages, the lack of genetic tools, such as those available for zebrafish and Drosophila melanogaster, has hindered development of the full potential of G. mellonella as a model organism. Here we describe a robust methodology for generating transgenic G. mellonella using the PiggyBac transposon system and for precise gene knockouts via CRISPR-Cas9 technology. These advances significantly enhance the utility of G. mellonella in molecular research, paving the way for its widespread use as an inexpensive and ethically compatible animal model in infection biology and beyond.

We study a novel approach to formative education developed by the public upper secondary school Anna Whitlock’s Gymnasium in Stockholm, Sweden. The school’s educational philosophy, which is based on the concepts of Bildung and assidēre (“to sit beside”), entails a significant focus on formative teaching. We describe the school’s approach to formative education and evaluate it by studying its effects on the students’ growth mindsets and attitudes regarding academic achievement. We use a mixed-methods approach utilizing both survey data and focus group data. Our results show several expected positive results on the school-wide level, but also significant variation between different classes. We select four classes for further study and by analysing the focus group data from these classes we tentatively explore the causal impact of the school’s formative education approach on the students’ growth mindset and achievement attitudes.

Random forest-based source attribution models were developed from a ‘One Health’ resource comprising 4,230 high-quality whole-genome assemblies from Escherichia coli . These were isolated from a wide range of sources, predominantly originating in Scotland, including wastewater, livestock, food and clinical infections of humans and dogs. Using these models, we derived a probabilistic assignment of E. coli isolates from food, shellfish and water samples to potential livestock and human sources of contamination. The incorporation of E. coli sequences from wastewater alongside those from human clinical infections enabled us to capture a wide diversity of human strains in our analyses. The sequence types (STs) of isolates from human bacteraemia and urinary tract infection (UTI) were compared with livestock and food isolates. While only 2.3% of the E. coli isolated from food samples in the study were from STs primarily associated with human bacteraemia and UTI, the models found a livestock signal associated with 15% of the human clinical isolates. In the food and private water samples, livestock-human co-attribution of E. coli isolates was common and consistent with routine human exposure to specific subsets of livestock E. coli , potentially a result of selection during food and water processing. Overall, this research demonstrates the potential value of including source attribution models in national surveillance programmes to understand the transmission of E. coli through the agri-food chain and support risk management to protect public health.

Sampling coatings are a developing technology for detection and quantification of contaminants in porous materials (PM). The sampling coating is a substance of high contaminant affinity that is applied onto the PM and left to absorb contaminant. Upon removal, it is analysed to determine the amount of contaminant absorbed. Whilst sampling coatings have been shown to recover more contaminant from PM than traditional methods, the role of transport kinetics has not been recognized, hindering the quantitative interpretation of the measurements. We present a mathematical modeling framework for sampling coatings, incorporating coupled vaporisation and transport within the PM and absorption into the coating. We show that, on practical time scales (hours to days), only a fraction of the contaminant present in the PM enters the sampling coating and chemical equilibrium is not reached. The sampling efficiency, which we define to be the fraction of the contaminant in the coating, thus depends on the sampling time. We find an analytical solution of the model, valid for feasible sampling times in the physical parameter regime, along with an explicit expression for the sampling efficiency as a function of time. Dependence on the physical system parameters is investigated numerically: the height, diffusivity, and structure of the PM, and the type of chemical contaminant, are identified as key factors affecting sampling efficiency. We further propose a method to quantify contamination in the field using sampling-coating measurements. Our model and results enable practitioners to determine important properties when designing coatings and will inform future experimental work.