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Image, screen, projection: conceptualising the urban (imaginary) in digital visual culture
Get PDFThis paper examines the implications for theorising the concept of the 'urban imaginary' in the context of digital visual culture. In digital visual culture, the vast majority of images are designed, circulated and displayed using software, data networks and screens of various kinds. The literature on urban imaginaries has long acknowledged that cities are mediated by images as much as by various kinds of other media, and significant attention has been given to specific visual media including films, documentary photography and maps. This remains the case when visual culture is digital. However, digital images have a particular technocultural materiality which also has implications for their co-constitution of the urban. In digital visual culture, visual imagery is dominated by animations, shaped in part by the affordances of computer graphics software. These images require screens and data networks to become visible, which also mediate the infrastructure of cities both materially and imaginatively. Moreover, onscreen digital visual content materialises as an ambient atmosphere projected across and between screens and gazes (human and not). This networked, screenic projection is now sufficiently pervasive to constitute a significant form of urban spatiality. Hence the paper proposes that in digital visual culture, visual urban imaginaries can no longer be theorised only as representations of an urban reality. Instead, onscreen images must be theorised as enacting a form of the urban itself, in three ways: in their visual content, in the material emplacement of their networked screens, and in their projection into and as urban space
The lengths of conjugators in the model filiform groups
Get PDFThe conjugator length function of a finitely generated group Γ gives the optimal upper bound on the length of a shortest conjugator for any pair of conjugate elements in the ball of radius n in the Cayley graph of Γ. We prove that polynomials of arbitrary degree arise as conjugator length functions of finitely presented groups. To establish this, we analyse the geometry of conjugation in the discrete model filiform groups Γd = Zd ⋊φ Z where φ is the automorphism of Zd that fixes the last element of a basis a1, . . . , ad and sends ai to aiai+1 for i < d. The conjugator length function of Γd is polynomial of degree d
Secure and scalable rerouting in LEO satellite networks
No full textResilient routing in large-scale Low Earth Orbit (LEO) satellite networks remains a key challenge due to frequent and unpredictable link and node failures, potentially in response to cybersecurity breaches. While prior work has explored rerouting strategies with various levels of network awareness, their relative tradeoffs under dynamic failure conditions remain underexplored.In this work, we extend the Deep Space Network Simulator (DSNS) to systematically compare three rerouting paradigms, each differing in the scope of failure knowledge available to each node. We compare local neighbor-based, segment-based and global-knowledge-based rerouting as well as a naive source routing solution that is unaware of failures.Our main goal is to evaluate how the breadth of failure awareness impacts routing performance and resilience under failures, both random and targeted. We measure delivery ratio, latency, rerouting overhead, and loop occurrence. Our findings show the potential of segment-based rerouting to achieve a favorable tradeoff between local responsiveness and global coordination, offering resilience benefits with minimal overhead—insights that can inform future fault-tolerant satellite network design
Challenges and solutions to participation in mental health clinical trials: Count Me In 2.0
Get PDFMental health clinical trials in the UK face significant recruitment barriers, with mental health studies comprising just 3.3% of approved interventional medicinal product trials. Challenges include the limited numbers of trials and clinician gatekeeping-where clinicians decide whether or not to inform patients about research opportunities, limiting patient awareness and recruitment. The 'Count Me In' (CMI) approach, an opt-out recruitment model launched in Oxford in 2021 and then in Liverpool City Region in 2024, aimed to address these issues by directly contacting patients to discuss research opportunities, empower them in the shared decision process and embed participation in research into real-world clinical care. In this paper, we discuss the need for advancing beyond the original CMI model, including the requirement for enhanced data capture, mechanism for patient outreach that prioritises inclusive practices for improving participation and ensuring diverse, representative trial populations
MBRRACE-UK Data Brief: Maternal Mortality 2022-2024
No full textThese are top-level data from the Maternal, Newborn and Infant Clinical Outcome Review Programme, presented as an online Data Brief with key statistics concerning maternal mortality. In depth data are released with the “Saving Lives, Improving Mothers Care” reports each autumn
How Accurately Can Obscured Galaxy Luminosities Be Measured Using Spectral Energy Distribution Fitting of Near- through Far-infrared Observations?
Get PDFInfrared-luminous galaxies are important sites of stellar and black hole mass assembly at most redshifts. Their luminosities are often estimated by fitting spectral energy distribution (SED) models to near- to far-infrared data, but the dependence of these estimates on the data used is not well understood. Here, using observations simulated from a well-studied local sample, we compare the effects of wavelength coverage, signal-to-noise ratio, flux calibration, angular resolution, and redshift on the recovery of starburst, active galactic nucleus (AGN), and host luminosities. We show that the most important factors are wavelength coverage that spans the peak in a SED, and dense wavelength sampling. Such observations recover starburst and AGN infrared luminosities with systematic bias below 20%. Starburst luminosities are best recovered with far-infrared observations, while AGN luminosities are best recovered with near- and mid-infrared observations, though the recovery of both are enhanced with near/mid-infrared and far-infrared observations, respectively. Host luminosities are best recovered with near/far-infrared observations, but are usually biased low, by ≳20%. The recovery of starburst and AGN luminosity is enhanced by observing at high angular resolution. Starburst-dominated systems show more biased recovery of luminosities than do AGN-dominated systems. As redshift increases, far-infrared observations become more capable and mid-infrared observations less capable at recovering luminosities. Our results highlight the transformative power of a far-infrared instrument with dense wavelength coverage, from tens to hundreds of microns, for studying infrared-luminous galaxies. We tabulate estimates of systematic bias and random error for use with JWST and other observatories
Establishing global standards on wearable technology for measuring mobility in ageing populations: an international consensus exercise
Get PDFBackground: Mobility, defined as movement in all its forms, is a hallmark of healthy ageing. As wearable technologies become increasingly integrated into population health surveillance and ageing research, the absence of standardised terminology, measurement protocols and reporting practices presents a major barrier to progress. This consensus exercise aimed to establish minimum standards for measuring mobility with wearable technology in ageing populations and set priorities for future research in the field. Methods: A two-day, in-person consensus meeting was convened with 24 international experts in ageing, mobility and digital health. Using a modified nominal group technique facilitated by a trained moderator, participants engaged in structured small-group brainstorming, followed by iterative large-group discussions. Consensus was achieved through anonymised digital voting on proposed measures, principles and priorities. Findings: Consensus (≥80% agreement) was reached on 20 core device-derived mobility measures and 30 guiding principles for the optimal use of wearable technology in older populations. Experts also identified and ranked 16 priority areas for future research, with the top five including: (i) longitudinal studies and data collection, (ii) digital biomarkers and health outcomes, (iii) contextual data capture, (iv) algorithm development and validation and (v) integration with healthcare systems. Interpretations: These consensus-based standards provide a foundational framework for the consistent and transparent use of wearable devices in ageing research and practice. They can inform the development of regulations and guidelines, support harmonisation across studies and chart a path for future research to enhance the utility and impact of wearable technologies in ageing populations
The role of common cardiac comorbidities and mitochondrial variants as modifiers and/or phenocopies in hypertrophic cardiomyopathy (HCM)
Get PDFHypertrophic cardiomyopathy (HCM) is the most common inherited cardiac condition, typically associated with sarcomeric gene mutations. However, 40% of patients lack identifiable pathogenic variants, suggesting the role of other factors. This thesis investigates the interaction between selected genetic and non-genetic factors in HCM, focusing on the common cardiac comorbidities hypertension and obesity, and rare genetic variants known to mimic the HCM phenotype - the MT-TI:m.4300A>G mitochondrial variant. Through advanced imaging, biomarker analysis, and clinical data, this research aims to clarify the mechanisms influencing HCM phenotypes and improve diagnostic and therapeutic strategies
Time trends in newly recorded diagnoses of 19 long term conditions before, during, and after the covid-19 pandemic: population based cohort study in England using OpenSAFELY
Get PDFObjective: To evaluate temporal changes in rates of newly recorded diagnoses for 19 long term conditions in England in relation to the covid-19 pandemic by disease, age group, sex, socioeconomic status, and ethnicity. Design: Population based cohort study. Setting: Primary care and hospital admission data, with the approval of NHS England. Participants: 29 995 025 individuals registered with general practices in England contributing data to the OpenSAFELY-TPP platform. Main outcome measures: Temporal trends in age and sex standardised incident and prevalent diagnosis rates for 19 long term conditions between 1 April 2016 and 30 November 2024. Differences between expected and observed diagnosis rates after the onset of the covid-19 pandemic were compared using seasonal autoregressive integrated moving-average models, based on modelled projections of expected rates from pre-pandemic patterns. Results: All 19 conditions showed a sharp decline in newly recorded diagnoses during the first year of the pandemic, followed by variable recovery. As of November 2024, cumulative reductions in diagnoses remained evident for conditions such as depression (734 800 (27.7%) fewer diagnoses than expected; 95% prediction interval (PI) 703 100 to 766 400), asthma (152 900 (16.4%) fewer diagnoses; 95% PI 137 500 to 168 300), chronic obstructive pulmonary disease (COPD) (90 100 (15.8%) fewer diagnoses; 95% PI 81 400 to 98 900), psoriasis (54 700 (17.1%) fewer diagnoses; 95% PI 50 100 to 59 200), and osteoporosis (54 100 (11.5%) fewer diagnoses; 95% PI 47 100 to 61 100). Conversely, diagnoses of chronic kidney disease have increased by 34.8% above expected levels during the pandemic recovery period, corresponding to 359 000 additional diagnoses (95% PI 333 500 to 384 500). Unadjusted subgroup analyses stratified by ethnicity and socioeconomic status indicated that, after an initial decrease, dementia diagnosis rates have risen above pre-pandemic levels for people of white ethnicity and in less deprived socioeconomic areas, but not for those from other ethnicities and more deprived areas. Conclusions: Since the covid-19 pandemic, there have been fewer diagnoses than expected for conditions such as depression, asthma, COPD, and osteoporosis, in contrast with a rapid increase in diagnoses of chronic kidney disease since 2022. Unadjusted analyses stratified by ethnicity and socioeconomic status suggest differential patterns of recovery, particularly for individuals with dementia. This study highlights the potential for near real time monitoring of disease epidemiology using routinely collected health data, informing strategies to enhance case detection and investigate inequities in healthcare