A Flux-Limited Sample of z~1 Ly-alpha Emitting Galaxies in the CDFS

We describe a method for obtaining a flux-limited sample of Ly-alpha emitters from GALEX grism data. We show that the multiple GALEX grism images can be converted into a three-dimensional (two spatial axes and one wavelength axis) data cube. The wavelength slices may then be treated as narrowband images and searched for emission-line galaxies. For the GALEX NUV grism data, the method provides a Ly-alpha flux-limited sample over the redshift range z=0.67-1.16. We test the method on the Chandra Deep Field South field, where we find 28 Ly-alpha emitters with faint continuum magnitudes (NUV>22) that are not present in the GALEX pipeline sample. We measure the completeness by adding artificial emitters and measuring the fraction recovered. We find that we have an 80% completeness above a Ly-alpha flux of 10^-15 erg/cm^2/s. We use the UV spectra and the available X-ray data and optical spectra to estimate the fraction of active galactic nuclei in the selection. We report the first detection of a giant Ly-alpha blob at z<1, though we find that these objects are much less common at z=1 than at z=3. Finally, we compute limits on the z~1 Ly-alpha luminosity function and confirm that there is a dramatic evolution in the luminosity function over the redshift range z=0-1.Comment: 18 pages, in press at The Astrophysical Journa

Conceptual Frameworks for Multimodal Social Signal Processing

This special issue is about a research area which is developing rapidly. Pentland gave it a name which has become widely used, ‘Social Signal Processing’ (SSP for short), and his phrase provides the title of a European project, SSPnet, which has a brief to consolidate the area. The challenge that Pentland highlighted was understanding the nonlinguistic signals that serve as the basis for “subconscious discussions between humans about relationships, resources, risks, and rewards”. He identified it as an area where computational research had made interesting progress, and could usefully make more

Ly alpha emitting galaxies as early stages in galaxy formation

We present optical spectroscopy of two samples of GALEX grism selected Ly alpha emitters (LAEs): one at z=0.195-0.44 and the other at z=0.65-1.25. We have also observed a comparison sample of galaxies in the same redshift intervals with the same UV magnitude distributions but with no detected Ly alpha. We use the optical spectroscopy to eliminate active galactic nuclei (AGNs) and to obtain the optical emission-line properties of the samples. We compare the luminosities of the LAEs in the two redshift intervals and show that there is dramatic evolution in the maximum Ly alpha luminosity over z=0-1. Focusing on the z=0.195-0.44 samples alone, we show that there are tightly defined relations between all of the galaxy parameters and the rest-frame equivalent width (EW) of H alpha. The higher EW(H alpha) sources all have lower metallicities, bluer colors, smaller sizes, and less extinction, consistent with their being in the early stages of the galaxy formation process. We find that 75 +- 12% of the LAEs have EW(H alpha)>100 Angstrom, and, conversely, that 31 +/- 3% of galaxies with EW(H alpha)>100 Angstrom are LAEs. We correct the broadband magnitudes for the emission-line contributions and use spectral synthesis fits to estimate the ages of the galaxies. We find a median age of 1.1x10^{8} yr for the LAE sample and 1.4x10^{9} yr for the UV-continuum sample without detected Ly alpha. The median metallicity of the LAE sample is 12+log(O/H)=8.24, or about 0.4 dex lower than the UV-continuum sample.Comment: to be published in the Astrophysical Journa

UK stroke incidence, mortality and cardiovascular risk management 1999–2008: time-trend analysis from the General Practice Research Database

Objectives Stroke is a major cause of morbidity and mortality. This study aimed to investigate secular trends in stroke across the UK. Design This study aimed to investigate recent trends in the epidemiology of stroke in the UK. The study was a time-trend analysis from 1999 to 2008 within the UK General Practice Research Database. Outcome measures were incidence and prevalence of stroke, stroke mortality, rate of secondary cardiovascular events, and prescribing of pharmacological therapy for primary and secondary prevention of cardiovascular disease. Results The study cohort included 32 151 patients with a first stroke. Stroke incidence fell by 30%, from 1.48/1000 person-years in 1999 to 1.04/1000 person-years in 2008 (p<0.001). Stroke prevalence increased by 12.5%, from 6.40/1000 in 1999 to 7.20/1000 in 2008 (p<0.001). 56-day mortality after first stroke reduced from 21% in 1999 to 12% in 2008 (p<0.0001). Prescribing of drugs to control cardiovascular risk factors increased consistently over the study period, particularly for lipid lowering agents and antihypertensive agents. In patients with atrial fibrillation, use of anticoagulants prior to first stroke did not increase with increasing stroke risk. Conclusion Stroke incidence in the UK has decreased and survival after stroke has improved in the past 10 years. Improved drug treatment in primary care is likely to be a major contributor to this, with better control of risk factors both before and after incident stroke. There is, however, scope for further improvement in risk factor reduction in high-risk patients with atrial fibrillation

Developing SASSA: a Soil Analysis Support System for Archaeologists

A constant problem for field archaeologists is the need for familiarity with the core concepts of a diverse range of specialist disciplines. Soils and sediments are an integral part of archaeological sites, yet the teaching of soils in archaeology degrees is variable and many archaeologists complain they are lacking in the confidence and skills required to describe and interpret the deposits they excavate. SASSA (Soil Analysis Support System for Archaeologists) is a free-to-use, internet based system designed to familiarise archaeologists with the concepts and possibilities offered by geoarchaeology (the scientific study of soils and sediments). SASSA consists of two core components: the knowledge base and field tool. The &lsquo;front-end&rsquo; of the website is the knowledge base; this uses Wiki technology to allow users to add their own content and encourage dialogue between archaeologists and geoarchaeologists. Whilst the field tool uses an XML data structure and decision tree, decision support system to guide the user through the process of describing and interpreting soils and sediments. SASSA is designed for use on both &lsquo;static&rsquo; (PC) and &lsquo;mobile&rsquo; (PDA and laptop) hardware in order to provide in-situ field support as well as offering office-based &lsquo;reference book style&rsquo; help. This article introduces the aims of SASSA, presents SASSA as a user might experience it, and discusses the computing technology used to construct the system

Framework-Based Qualitative Analysis of Free Responses of Large Language Models: Algorithmic Fidelity

Today, using Large-scale generative Language Models (LLMs) it is possible to simulate free responses to interview questions like those traditionally analyzed using qualitative research methods. Qualitative methodology encompasses a broad family of techniques involving manual analysis of open-ended interviews or conversations conducted freely in natural language. Here we consider whether artificial "silicon participants" generated by LLMs may be productively studied using qualitative methods aiming to produce insights that could generalize to real human populations. The key concept in our analysis is algorithmic fidelity, a term introduced by Argyle et al. (2023) capturing the degree to which LLM-generated outputs mirror human sub-populations' beliefs and attitudes. By definition, high algorithmic fidelity suggests latent beliefs elicited from LLMs may generalize to real humans, whereas low algorithmic fidelity renders such research invalid. Here we used an LLM to generate interviews with silicon participants matching specific demographic characteristics one-for-one with a set of human participants. Using framework-based qualitative analysis, we showed the key themes obtained from both human and silicon participants were strikingly similar. However, when we analyzed the structure and tone of the interviews we found even more striking differences. We also found evidence of the hyper-accuracy distortion described by Aher et al. (2023). We conclude that the LLM we tested (GPT-3.5) does not have sufficient algorithmic fidelity to expect research on it to generalize to human populations. However, the rapid pace of LLM research makes it plausible this could change in the future. Thus we stress the need to establish epistemic norms now around how to assess validity of LLM-based qualitative research, especially concerning the need to ensure representation of heterogeneous lived experiences.Comment: 46 pages, 5 tables, 5 figure

The COVID-19 pandemic and heart failure: lessons from GUIDE-HF

No abstract available

Digital Health: Implications for Heart Failure Management

Digital health encompasses the use of information and communications technology and the use of advanced computing sciences in healthcare. This review covers the application of digital health in heart failure patients, focusing on teleconsultation, remote monitoring and apps and wearables, looking at how these technologies can be used to support care and improve outcomes. Interest in and use of these technologies, particularly teleconsultation, have been accelerated by the coronavirus disease 2019 pandemic. Remote monitoring of heart failure patients, to identify those patients at high risk of hospitalisation and to support clinical stability, has been studied with mixed results. Remote monitoring of pulmonary artery pressure has a consistent effect on reducing hospitalisation rates for patients with moderately severe symptoms and multiparameter monitoring shows promise for the future. Wearable devices and apps are increasingly used by patients for health and lifestyle support. Some wearable technologies have shown promise in AF detection, and others may be useful in supporting self-care and guiding prognosis, but more evidence is required to guide their optimal use. Support for patients and clinicians wishing to use these technologies is important, along with consideration of data validity and privacy and appropriate recording of decision-making