A Statistical Analysis of the Solar Phenomena Associated with Global EUV Waves

Solar eruptions are the most spectacular events in our solar system and are associated with many different signatures of energy release including solar flares, coronal mass ejections, global waves, radio emission and accelerated particles. Here, we apply the Coronal Pulse Identification and Tracking Algorithm (CorPITA) to the high cadence synoptic data provided by the Solar Dynamic Observatory (SDO) to identify and track global waves observed by SDO. 164 of the 362 solar flare events studied (45%) are found to have associated global waves with no waves found for the remaining 198 (55%). A clear linear relationship was found between the median initial velocity and the acceleration of the waves, with faster waves exhibiting a stronger deceleration (consistent with previous results). No clear relationship was found between global waves and type II radio bursts, electrons or protons detected in-situ near Earth. While no relationship was found between the wave properties and the associated flare size (with waves produced by flares from B to X-class), more than a quarter of the active regions studied were found to produce more than one wave event. These results suggest that the presence of a global wave in a solar eruption is most likely determined by the structure and connectivity of the erupting active region and the surrounding quiet solar corona rather than by the amount of free energy available within the active region.Comment: 33 pages, 6 figures, 1 table. Accepted for publication in Solar Physic

Informal task-sharing practices in inpatient newborn settings in a low-income setting: A task analysis approach

Aim: To describe the complexity and criticality of neonatal nursing tasks and existing task-sharing practices to identify tasks that might be safely shared in inpatient neonatal settings. Design: We conducted a cross-sectional study in a large geographically dispersed sample using the STROBE guidelines. Methods: We used a task analysis approach to describe the complexity/criticality of neonatal nursing tasks and to explore the nature of task sharing using data from structured, self-administered questionnaires. Data was collected between 26th April and 22nd August 2017. Results: Thirty-two facilities were surveyed between 26th April and 22nd August, 2017. Nearly half (42%, 6/14) of the “moderately critical” and “not critical” (41%, 5/11) tasks were ranked as consuming most of the nurses' time and reported as shared with mothers respectively. Most tasks were reported as shared in the public sector than in the private-not-for-profit facilities. This may largely be a response to inadequate nurse staffing, as such, there may be space for considering the future role of health care assistants

Experiments in terabyte searching, genomic retrieval and novelty detection for TREC 2004

In TREC2004, Dublin City University took part in three tracks, Terabyte (in collaboration with University College Dublin), Genomic and Novelty. In this paper we will discuss each track separately and present separate conclusions from this work. In addition, we present a general description of a text retrieval engine that we have developed in the last year to support our experiments into large scale, distributed information retrieval, which underlies all of the track experiments described in this document

Informal task-sharing practices in inpatient newborn settings in a low-income setting-A task analysis approach.

Aim: To describe the complexity and criticality of neonatal nursing tasks and existing task-sharing practices to identify tasks that might be safely shared in inpatient neonatal settings. Design: We conducted a cross-sectional study in a large geographically dispersed sample using the STROBE guidelines. Methods: We used a task analysis approach to describe the complexity/criticality of neonatal nursing tasks and to explore the nature of task sharing using data from structured, self-administered questionnaires. Data was collected between 26th April and 22nd August 2017. Results: Thirty-two facilities were surveyed between 26th April and 22nd August, 2017. Nearly half (42%, 6/14) of the "moderately critical" and "not critical" (41%, 5/11) tasks were ranked as consuming most of the nurses' time and reported as shared with mothers respectively. Most tasks were reported as shared in the public sector than in the private-not-for-profit facilities. This may largely be a response to inadequate nurse staffing, as such, there may be space for considering the future role of health care assistants

Dublin City University video track experiments for TREC 2003

In this paper, we describe our experiments for both the News Story Segmentation task and Interactive Search task for TRECVID 2003. Our News Story Segmentation task involved the use of a Support Vector Machine (SVM) to combine evidence from audio-visual analysis tools in order to generate a listing of news stories from a given news programme. Our Search task experiment compared a video retrieval system based on text, image and relevance feedback with a text-only video retrieval system in order to identify which was more effective. In order to do so we developed two variations of our Físchlár video retrieval system and conducted user testing in a controlled lab environment. In this paper we outline our work on both of these two tasks

Estimating the need for inpatient neonatal services: an iterative approach employing evidence and expert consensus to guide local policy in Kenya.

Universal access to quality newborn health services will be essential to meeting specific Sustainable Development Goals to reduce neonatal and overall child mortality. Data for decision making are crucial for planning services and monitoring progress in these endeavours. However, gaps in local population-level and facility-based data hinder estimation of health service requirements for effective planning in many low-income and middle-income settings. We worked with local policy makers and experts in Nairobi City County, an area with a population of four million and the highest neonatal mortality rate amongst counties in Kenya, to address this gap, and developed a systematic approach to use available data to support policy and planning. We developed a framework to identify major neonatal conditions likely to require inpatient neonatal care and identified estimates of incidence through literature review and expert consultation, to give an overall estimate for the year 2017 of the need for inpatient neonatal care, taking account of potential comorbidities. Our estimates suggest that almost 1 in 5 newborns (183/1000 live births) in Nairobi City County may need inpatient care, resulting in an estimated 24 161 newborns expected to require care in 2017. Our approach has been well received by local experts, who showed a willingness to work together and engage in the use of evidence in healthcare planning. The process highlighted the need for co-ordinated thinking on admission policy and referral care especially in a pluralistic provider environment helping build further appetite for data-informed decision making

TRECVID 2004 experiments in Dublin City University

In this paper, we describe our experiments for TRECVID 2004 for the Search task. In the interactive search task, we developed two versions of a video search/browse system based on the Físchlár Digital Video System: one with text- and image-based searching (System A); the other with only image (System B). These two systems produced eight interactive runs. In addition we submitted ten fully automatic supplemental runs and two manual runs. A.1, Submitted Runs: • DCUTREC13a_{1,3,5,7} for System A, four interactive runs based on text and image evidence. • DCUTREC13b_{2,4,6,8} for System B, also four interactive runs based on image evidence alone. • DCUTV2004_9, a manual run based on filtering faces from an underlying text search engine for certain queries. • DCUTV2004_10, a manual run based on manually generated queries processed automatically. • DCU_AUTOLM{1,2,3,4,5,6,7}, seven fully automatic runs based on language models operating over ASR text transcripts and visual features. • DCUauto_{01,02,03}, three fully automatic runs based on exploring the benefits of multiple sources of text evidence and automatic query expansion. A.2, In the interactive experiment it was confirmed that text and image based retrieval outperforms an image-only system. In the fully automatic runs, DCUauto_{01,02,03}, it was found that integrating ASR, CC and OCR text into the text ranking outperforms using ASR text alone. Furthermore, applying automatic query expansion to the initial results of ASR, CC, OCR text further increases performance (MAP), though not at high rank positions. For the language model-based fully automatic runs, DCU_AUTOLM{1,2,3,4,5,6,7}, we found that interpolated language models perform marginally better than other tested language models and that combining image and textual (ASR) evidence was found to marginally increase performance (MAP) over textual models alone. For our two manual runs we found that employing a face filter disimproved MAP when compared to employing textual evidence alone and that manually generated textual queries improved MAP over fully automatic runs, though the improvement was marginal. A.3, Our conclusions from our fully automatic text based runs suggest that integrating ASR, CC and OCR text into the retrieval mechanism boost retrieval performance over ASR alone. In addition, a text-only Language Modelling approach such as DCU_AUTOLM1 will outperform our best conventional text search system. From our interactive runs we conclude that textual evidence is an important lever for locating relevant content quickly, but that image evidence, if used by experienced users can aid retrieval performance. A.4, We learned that incorporating multiple text sources improves over ASR alone and that an LM approach which integrates shot text, neighbouring shots and entire video contents provides even better retrieval performance. These findings will influence how we integrate textual evidence into future Video IR systems. It was also found that a system based on image evidence alone can perform reasonably and given good query images can aid retrieval performance

Dairy foods and dairy protein consumption is inversely related to markers of adiposity in obese men and women

A number of intervention studies have reported that the prevalence of obesity may be in part inversely related to dairy food consumption while others report no association. We sought to examine relationships between energy, protein and calcium consumption from dairy foods (milk, yoghurt, cheese, dairy spreads, ice-cream) and adiposity including body mass index (BMI), waist (WC) and hip circumference (HC), and direct measures of body composition using dual energy X-ray absorptiometry (% body fat and abdominal fat) in an opportunistic sample of 720 overweight/obese Australian men and women. Mean (SD) age, weight and BMI of the population were 51 ± 10 year, 94 ± 18 kg and 32.4 ± 5.7 kg/m2, respectively. Reduced fat milk was the most commonly consumed dairy product (235 ± 200 g/day), followed by whole milk (63 ± 128 g/day) and yoghurt (53 ± 66 g/day). Overall dairy food consumption (g/day) was inversely associated with BMI, % body fat and WC (all p < 0.05). Dairy protein and dairy calcium (g/day) were both inversely associated with all adiposity measures (all p < 0.05). Yoghurt consumption (g/day) was inversely associated with % body fat, abdominal fat, WC and HC (all p < 0.05), while reduced fat milk consumption was inversely associated with BMI, WC, HC and % body fat (all p < 0.05). Within a sample of obese adults, consumption of dairy products, dairy protein, and calcium was associated with more favourable body composition