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Learning the Universe: cosmological and astrophysical parameter inference with galaxy luminosity functions and colours
Get PDFABSTRACT We perform the first direct cosmological and astrophysical parameter inference from the combination of galaxy luminosity functions and colours using a simulation-based inference approach. Using the synthesizer code, we simulate the dust attenuated ultraviolet (UV)–near-infrared stellar emission from galaxies in thousands of cosmological hydrodynamic simulations from the CAMELS suite, including the swift-eagle, IllustrisTNG, simba, and astrid galaxy formation models. For each galaxy, we calculate the rest-frame luminosity in a number of photometric bands, including the SDSS ugriz and GALEX far- and near-UV filters; this data set represents the largest catalogue of synthetic photometry based on hydrodynamic galaxy formation simulations produced to date, totalling 200 million sources. From these, we compile luminosity functions and colour distributions, and find clear dependencies on both cosmology and feedback. We then perform simulation-based (likelihood-free) inference using these distributions to obtain constraints on , , and four parameters controlling the strength of stellar and active galactic nucleus feedback. Both colour distributions and luminosity functions provide complementary information on certain parameters when performing inference. We achieve constraints on the stellar feedback parameters, as well as and . The latter is attributable to the fact that the photometry encodes the star formation–metal enrichment history of each galaxy; galaxies in a universe with a higher tend to form earlier and have higher metallicities, which leads to redder colours. We find that a model trained on one galaxy formation simulation generalizes poorly when applied to another, and attribute this to differences in the subgrid prescriptions, and lack of flexibility in our emission modelling. The photometric catalogues are publicly available
The Global Governance of Education through the OECD’S PISA and TALIS Programme: The Case of England
No full textThis thesis explores the interactions between global governance mechanisms and national policy by examining the impacts of one international body, the Organisation for Economic Co-operation and Development (OECD), on education policy in England. The OECD’s comparative statistics have established the organisation as a key international actor in education governance, its Programme for International Student Assessment (PISA) and Teaching and Learning International Survey (TALIS) collecting data from teachers and students that are then published for use in a variety of policy environments. The decontextualised, ordinalised nature of this data provides seemingly generic, ‘universal’ standards that can facilitate easy uptake by international policymakers, yet raises questions as to the data’s rigour and use. These questions are particularly evident in the case of England, where OECD data have been used to strengthen the nation’s already robust array of educational accountability structures. England’s reticence to fully adopt the OECD’s recommended educational ‘best practices’, despite the UK being a founding member of the organisation, is just one way that England is an ‘outlier’ within the overall global governance landscape. Nevertheless, few studies have examined the concrete impacts of OECD data on classroom practices in England, particularly on teachers, who are arguably the stakeholders most directly affected by education system reforms. This study therefore addresses this gap by analysing OECD publications and conducting semi-structured interviews with secondary school teachers to explore how PISA and TALIS shape teachers’ work and professional experience.
Document analyses show that data in OECD publications are presented in ways that encourage progress through sustainability and self-regulation, rather than political participation, on the part of teachers. This is especially true in the case of the TALIS report, which highlights teachers’ care towards students and multicultural sensitivity, as well as classroom ICT use, rather than teachers’ more direct concerns such as workload and burnout. Teacher interviews, meanwhile, reveal little-to-no knowledge of PISA or TALIS, despite their use by English policymaking bodies on tightening teacher accountability measures and, perhaps more significantly, creating ‘common-sense’ media discourses around England’s education system. Overall, the OECD exerts significant but largely indirect influence on England’s education policy, one that is mediated by the Department for Education’s authority in England, government’s more direct influence, yet nevertheless contributes to the dominant discourses structuring teacher expectations with minimal awareness of teachers themselves. This disparity calls for further investigation prior to future educational policy changes.
Keywords: OECD, PISA, TALIS, England, Global governance ,Teacher
Catalytic Deracemization of 1,2-Aminoalcohols through Enantioselective Hydrogen Atom Abstraction
Get PDFCatalytic deracemization appears a superficially simple way to obtain enantioenriched chiral compounds but is deceptively challenging. The popularization of photochemical methods which utilize excited state pathways have permitted breakthroughs, but application to simple functional motifs that constitute common chiral building blocks is still rare. We report the catalytic deracemization of N-acyl-1,2-aminoalcohols using a cinchona alkaloid-derived catalyst that operates through enantioselective hydrogen atom abstraction, once oxidized by an excited photocatalyst. In combination with an achiral thiol to return the hydrogen atom, accumulation of the unreactive enantiomer occurs. Our catalyst exhibits extremely high chemoselectivity for abstraction adjacent to alcohols and permits a range of useful functionality to be incorporated into the substrates for deracemization. The method generates versatile small molecule building blocks with very high levels of enantioenrichment and demonstrates the synthetic potential of catalysts able to perform hydrogen atom abstraction in a stereoselective manner
High-throughput defect detection and coverage quantification of graphene grids via a dual-stage deep learning framework
Get PDFGraphene grids exhibit exceptional loading capacity for macromolecules, single atoms, and nanoparticles, offering significant potential for exploring the structure and properties of various materials at the nanoscale. However, challenges such as carbon film rupture, contamination, and uneven graphene film coverage frequently occur during grid fabrication. Here we propose a dual-stage deep learning model integrating U-Net and an enhanced YOLO11 architecture, enabling efficient and accurate defect detection and graphene coverage quantification. A tailored data augmentation strategy expanded the initial defect dataset by more than an order of magnitude, which directly contributed to an overall 11.72% improvement across the model’s performance metrics. With the integration of the multi-scale convolutional attention (MSCA) module and the slicing-aided hyper inference (SAHI) method, the model achieved a 0.67% mean absolute percentage error (MAPE), while reducing the average detection time from 26.6 to 0.1 min per image. The proposed model holds strong potential for extension to various material characterization image analysis tasks, providing a scalable strategy for high-throughput image processing that bridges fundamental research with industrial-scale applications
STEM-PD trial protocol: a multi-centre, single-arm, first-in-human, dose-escalation trial, investigating the safety and tolerability of intraputamenal transplantation of human embryonic stem cell-derived dopaminergic cells for Parkinson’s disease
Get PDFIntroduction: Parkinson’s disease (PD) is a common neurodegenerative disease, which has extensive pathology that critically includes the loss of midbrain dopaminergic neurons. This loss leads to debilitating motor features such as bradykinesia and rigidity, as well as some non-motor symptoms. Intracerebral dopamine cell transplants have been explored for many years as a new approach to treating PD and initially used human fetal ventral mesencephalic tissue with inconsistent results, related in part to major logistical challenges in sourcing enough tissue of the right quality and the limited possibilities for quality control and standardisation. Dopaminergic neurons can now be derived reliably from human stem cell sources, which may overcome some of the challenges associated with fetal tissue transplantations. Methods and analysis: STEM-PD is a multi-centre, single-arm, dose-escalation, first-in-human advanced therapy investigational medicinal product (ATIMP) trial in Europe using a cell product that consists of dopaminergic neural progenitors derived from the RC17 human embryonic stem cell line. The aim of the study is to assess the safety, tolerability and feasibility of intraputamenal transplantation of this cell product in patients with moderately advanced PD. Eight participants will be recruited from two sites, Skånes University Hospital (Lund, Sweden) and Cambridge University Hospital (Cambridge, UK). The primary outcome of the trial is safety and tolerability, assessed by the number and nature of adverse events and serious adverse events, and the absence of space-occupying lesions on cranial MRI, in the first 12 months following transplantation. Secondary and exploratory outcomes, including clinical measures, changes in anti-Parkinson’s medication and measures of graft survival using positron emission tomography imaging, will be assessed at both 12 and 36 months post-grafting. Ethics and dissemination: Ethical approval was obtained from the Swedish Ethical Review Authority (EPM dnr 2021-06945-01) and South Central - Oxford A Research Ethics Committee (reference 23/SC/0243). Clinical Trial Authorisation was given by the Swedish Medical Products Agency (Dnr: 5.1-2022-57953) and the Medicines and Healthcare products Regulatory Agency for clinical trials authorisation (reference CTA 40773/0001/001-0001). Authorisation for transfer to Clinical Trial Regulation (EU) 536/2014 was given by the Swedish Medical Products Agency (Dnr: 5.1.1-2024-100773). Potential participants will receive verbal and written information about the trial and written informed consent will be obtained prior to enrolment. A lay summary of the results of the trial will be uploaded to the trial website which is publicly accessible. Trial results will be published in peer-reviewed journals. Trial registration numbers: NCT05635409
Determinants of Early-stage User Involvement (EUI) in User Need Identification for Health Apps: An Exploratory Study
No full textPromising digital health innovations, such as health apps, often fail to improve healthcare outcomes: approximately 80% of health apps are considered unreliable and 53% of them are reportedly uninstalled within 30 days of being downloaded, limiting their adoption and ability to deliver intended impact. Research shows that low user adherence — a primary barrier to successful adoption — is linked to insufficient perceived value, which stems from a mismatch between the app’s usefulness envisaged by developers and that experienced by users (patients, caregivers, and clinicians). This mismatch is largely attributed to developers’ insufficient understanding of users’ multifaceted needs (e.g. physical, psychological, and social) and contextual complexities.
To address this issue, research acknowledges the benefits of involving users upstream during need identification in the fuzzy front-end (FFE) of the innovation process. However, academic literature characterising such early-stage user involvement (EUI) is sparse, highly fragmented, and unspecific regarding factors that facilitate, inhibit, and shape this involvement, as well as how these factors vary by organisational context, pointing to the need for empirical investigation into this area. This thesis addresses this gap by providing an initial response to the overarching research question: What influences the implementation of EUI in pre-design need identification in health app development? To do so, it has examined the determinants (enablers, barriers, and contextual factors) influencing EUI in the FFE of health app development in start-ups and multinational corporations (MNCs) and illustrated how organisational context influences EUI implementation.
Guided by a relativist–interpretivist philosophy and a user-centred design (UCD) conceptual lens, this study used a sequential exploratory mixed-methods design. Phase 1 comprised semi-structured interviews across 28 industry case instances (17 start-ups; 11 MNCs). Abductive analysis helped integrate thematic coding with comparisons within and across organisational contexts to identify EUI determinants (25 in start-ups; 33 in MNCs), dimensions, and dimensional relationships and conceptualise initial EUI implementation frameworks. Phase 2 — a scoring survey administered to a purposively selected respondent group (Phase 1 interviewees) — informed the refinement of the initial EUI conceptual frameworks for start-ups and MNCs.
The findings indicate that while EUI is practiced in both organisational settings, it can be enabled, constrained, and shaped by overlapping and distinct determinants. The study contributes to the academic literature at the intersection of innovation management in the fuzzy front-end, user involvement, and digital health intervention development in three ways. Firstly, it addresses the identified research gap by illuminating EUI determinants in the FFE and by elucidating how organisational context shapes EUI implementation. Secondly, the proposed EUI implementation frameworks augment established DHI development frameworks (e.g. CeHRes roadmap) by conceptualising EUI as a preliminary phase that can inform pre-design need identification and provide an initial response to recurrent calls in the literature for clearer guidance on effectively involving users in the health app development process. Thirdly, the results extend open innovation and UCD theory in the health app development context to better account for the interplay between user-centred considerations, organisational structures, and organisation-user tensions in healthcare’s complex and stringently regulated environment. The study also contributes to practice by providing innovation practitioners with an evidence-based starting point for key considerations as well as implications for integrating EUI into the early phases of digital health innovation to better identify user needs which can help improve the relevance and inclusivity of these solutions
Beyond the reporting of disturbed areas: the use of Deter to analyze the spatiotemporal patterns of forest degradation in the Amazon
Get PDFThe Brazilian Amazon, a critical component of Earth’s climate regulation and biodiversity, has been increasingly affected by forest degradation, a process less monitored than deforestation. This study examines the recurrence and spatiotemporal patterns of forest degradation in the Legal Amazon from 2016 to 2024 using data from the Daily Monitoring of Suppression and Degradation of Native Vegetation (Deter) monitoring system. We first review methodological advances in Deter, highlighting its role in near real-time monitoring and enforcement. Subsequently, we applied a pixel-level recurrence analysis to map degradation frequency and analysis of spatiotemporal patterns, allied to statistical tests to assess monotonic trends. Results show that although most affected pixels had only one detection of degradation, critical hotspots, particularly in Pará and Mato Grosso, had up to five detections. Burn scars were the most frequent type of degradation, with a marked surge in 2024 corresponding to a 271% increase in the degradation rate. No significant overall trend was observed across the time series. Spatiotemporal patterns revealed a shift of degradation toward the eastern Amazon forest edge in 2016–2018, a concentration in southern and northern Mato Grosso in 2019–2021, and widespread degradation across the Legal Amazon in 2022–2024, with a pronounced hotspot in southern Pará. These findings emphasize the growing significance of forest degradation in Brazil, highlighting the need for integrated conservation strategies that extend beyond deforestation to include early detection and response. Strengthening monitoring systems such as Deter remains essential to support environmental governance, enforcement, and sustainable land management in the Amazon
Proactive and retroactive effects of novelty and rest on memory.
Get PDFNovel experiences appear to benefit memory for unrelated information encoded shortly before or after. Other research suggests that memory is impaired by effortful tasks following encoding, compared to simply resting. This registered report explicitly tested the proactive and retroactive effects of novel exploration and wakeful rest. Four groups of participants explored a novel or familiarised virtual environment, either shortly before or shortly after encoding a list of unrelated words. A fifth 'wakeful rest' group performed a low-effort attention task before and after encoding. Memory was tested with immediate free recall, delayed (next day) free recall and delayed recognition with confidence judgements (from which recollection and familiarity were estimated). Bayes factors provided evidence against both proactive and retroactive benefits of novelty across all measures of memory, but provided evidence for a retroactive benefit of rest for immediate recall. In exploratory analysis, we also found evidence for a proactive benefit of rest on immediate recall. We argue that the bidirectional benefits of wakeful rest are more easily explained by Temporal Distinctiveness theory than Consolidation theory. Overall, wakeful rest surrounding learning may represent a useful intervention for improving memory, while novel exploration may not
Spinocerebellar Ataxia 27 A with Episodic Ataxia: Case Series of Fibroblast Growth Factor 14 (FGF14) Microdeletions
No full textSpinocerebellar ataxia 27 A (SCA27A) is a form of progressive cerebellar ataxia due to pathogenic variants in the Fibroblast Growth Factor 14 (FGF14) gene. The objective of this paper is to characterise the clinical spectrum of SCA27A microdeletions (> 50 bp, <2Mbp), and report two novel cases. Literature searches of PubMed, OMIM and ClinVar were carried out. We identified SCA27A microdeletions in 32 cases across 11 families. The phenotypic presentation is: 75% (24/32) nystagmus, 46% (15/32) ataxia, 21% (7/32) episodic ataxia, 21% (7/32) tremor, 15% (5/32) dysarthria, 34% (11/32) learning disability, 28% (8/32) neuropsychiatric disease. The presentation is variable within and between families. Episodic symptoms, nystagmus, learning disability and neuropsychiatric symptoms occur at an earlier age. Patient 1 represents the first case with a 58 kb FGF14 deletion who presented with a paroxysmal movement disorder. Patient 2 carries a 545 kb deletion and developed episodic ataxia and trigeminal neuralgia, a novel feature not previously described in this cohort. We report two cases of heterozygous FGF14 microdeletions: Patient 1 (58 kb) and Patient 2 (545 kb), expanding the phenotypic spectrum of FGF14 structural variants to 32 cases across 11 families. We review potential mechanism from pre-clinical studies relating FGF14 haploinsufficiency to cerebellar, cognitive, neuropsychiatric symptoms, as well as trigeminal neuralgia. We propose the hypothesis that the episodic symptoms in SCA27A align with the molecular pathology of a channelopathy and propose management strategies based on this insight
