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A critical review of real-time modelling of flood forecasting in urban drainage systems
Get PDFThere has been a strong tendency in recent decades to develop real-time urban flood prediction models for early warning to the public due to a large number of worldwide urban flood occurrences and their disastrous consequences. While a significant breakthrough has been made so far, there are still some potential knowledge gaps that need further investigation. This paper presents a comprehensive review of the current state-of-the-art and future trends of real-time modelling of flood forecasting in urban drainage systems. Findings showed that the combination of various real-time sources of rainfall measurement and the inclusion of other real-time data such as soil moisture, wind flow patterns, evaporation, fluvial flow and infiltration should be more investigated in real-time flood forecasting models. Additionally, artificial intelligence is also present in most of the new RTFF models in UDS and consequently further developments of this technique are expected to appear in future works
Achieving quality and effectiveness in dementia using crisis teams (aqueduct): a study protocol for a randomised controlled trial of a resource kit
Get PDFBackground
Improving care at home for people with dementia is a core policy goal in the dementia strategies of many European countries. A challenge to effective home support is the occurrence of crises in the care of people with dementia which arise from changes in their health and social circumstances. Improving the management of these crises may prevent hospital admissions and facilitate better and longer care at home. This trial is part of a National Institute for Health Research funded programme, AQUEDUCT, which aims to improve the quality and effectiveness of teams working to manage crises in dementia.
Methods/design
It is a pragmatic randomised controlled trial of an online Resource Kit to enhance practice in teams managing crises in dementia care. Thirty teams managing mental health crises in dementia in community settings will be randomised between the Resource Kit intervention and treatment as usual. The primary outcome measure is psychiatric admissions to hospital for people with dementia in the teams’ catchment area recorded 6 months after randomisation. Other outcomes include quality of life measures for people with dementia and their carers, practitioner impact measures, acute hospital admissions and costs. To enhance understanding of the Resource Kit intervention, qualitative work will explore staff, patient and carers’ experience.
Discussion
The Resource Kit intervention reflects current policy to enable home-based care for people with dementia by addressing the management of crises which threaten the viability of care at home. It is based upon a model of best practice for managing crises in dementia designed to enhance the quality of care, developed in partnership with people with dementia, carers and practitioners. If the Resource Kit is shown to be clinically and cost-effective in this study, this will enhance the probability of its incorporation into mainstream practice.
Trial registration
ISRCTN 42855694; Registered on 04/03/2021; Protocol number: 127686/2020v9; Research Ethics Committee, 09/03/2021, Ref 21/WM/0004; IRAS ID: 28998
An Enhanced Multifactor Multiobjective Approach for Software Modularization
Get PDFComplex software systems, meant to facilitate organizations, undergo frequent upgrades that can erode the system architectures. Such erosion makes understandability and maintenance a challenging task. To this end, software modularization provides an architectural-level view that helps to understand system architecture from its source code. For modularization, nondeterministic search-based optimization uses single-factor single-objective, multifactor single-objective, and single-factor multiobjective, which have been shown to outperform deterministic approaches. The proposed MFMO approach, which uses both a heuristic (Hill Climbing and Genetic) and a meta-heuristic (nondominated sorting genetic algorithms NSGA-II and III), was evaluated using five data sets of different sizes and complexity. In comparison to leading software modularization techniques, the results show an improvement of 4.13% in Move and Join operations (MoJo, MoJoFM, and NED)
Researching vulnerable multilinguals: developing an inclusive research practice
Get PDF1. Introduction
The BAAL-CUP seminar ‘Researching vulnerable multilinguals: Developing an inclusive research practice’ was organised by Dr. Alexandra Georgiou, University of West London and Dr. Sara Ganassin, Newcastle University. It brought together 25 academics from different fields (e.g., applied linguistics, intercultural communication, education, linguistics) who engaged in discussions about the theoretical and methodological challenges they face in their work.
The seminar organisers are members of BAAL Multilingualism Special Interest Group (SIG), which aims to develop a broad-based community of researchers in applied and sociolinguistics with expertise in multilingualism and linguistic diversity. The BAAL-CUP seminar builds on a previous event organised by the SIG in June 2021, ‘Success stories of refugees in Europe: Celebrating the contributions of children and highly skilled adults’. The 2021 event aimed to promote the linguistic and cultural contributions of refugees in Europe with a focus on social, educational, and professional inclusion. After its successful completion, we thought that an in-person event that further explores issues of multilingualism and vulnerability through the lens of ‘researching multilingually’ would be beneficial to early career researchers, including postgraduate students and established academics from different disciplines
Singing for wellbeing: formulating a model for community group singing interventions
Get PDFResearch into the benefits of community-based group singing, pertaining to positive wellbeing and Quality of Life is lacking. Additionally, no preferred theoretical framework exists for community singing-based interventions. For the present study, six members of a UK community choir were interviewed using a semi-structured interview approach. Interpretative phenomenological analysis (IPA) was employed. Analysis produced superordinate themes of: Social Factors with key elements such as social bonds and group identity; Psychological Factors, highlighting self-efficacy, self-identity and positive emotions and Psychological Motivations for Joining the Group, including autonomy, change of life circumstance and seeking a new challenge. The style/method of the group, teaching, music and group leader, were shown to have an influence on perceived benefits of the singing group. A key product of this study beyond the evidenced benefits of group singing is the development of an intervention model that optimises wellbeing outcomes in community singing groups underpinned by psychological theory, findings from the wider literature and the results of this study
A point-of-care device for fully automated, fast and sensitive protein quantification via qPCR
Get PDFThis paper presents a fully automated point-of-care device for protein quantification using short-DNA aptamers, where no manual sample preparation is needed. The device is based on our novel aptamer-based methodology combined with real-time polymerase chain reaction (qPCR), which we employ for very sensitive protein quantification. DNA amplification through qPCR, sensing and real-time data processing are seamlessly integrated into a point-of-care device equipped with a disposable cartridge for automated sample preparation. The system’s modular nature allows for easy assembly, adjustment and expansion towards a variety of biomarkers for applications in disease diagnostics and personalised medicine. Alongside the device description, we also present a new algorithm, which we named PeakFluo, to perform automated and real-time quantification of proteins. PeakFluo achieves better linearity than proprietary software from a commercially available qPCR machine, and it allows for early detection of the amplification signal. Additionally, we propose an alternative way to use the proposed device beyond the quantitative reading, which can provide clinically relevant advice. We demonstrate how a convolutional neural network algorithm trained on qPCR images can classify samples into high/low concentration classes. This method can help classify obese patients from their leptin values to optimise weight loss therapies in clinical settings
Past caring: episode 6: learning disability
No full textEpisode 6 delves more deeply into the themes from our exhibition, "A History of Care or Control?" on the history of learning disability nursing.
Content warning: This episode contains a number of terms from learning disability history that are offensive today, especially in the interview with Simon who discusses them as an important part of understanding the history and attitudes towards disabled people.
First, hear from writer and performer Emily Curtis and her sister Sophie Potter, who has Down's Syndrome. Emily recently performed her play "Sophie", at the RCN, which explores the sisters' shared experiences growing up together in Hull, including the stigma and the joy Down's Syndrome brought to their lives.
Next, historian Dr Simon Jarrett tells us about the often surprising history of learning disability, including how it was understood in the eighteenth century and what the phrase "to live in the community" really means. Simon's book, "Those They Called Idiots" was published by Reaktion in 2020.
Finally, retired learning disability nurse Professor Bob Gates tells us about his oral history project collecting the untold stories of nurses who had spent decades working with people with learning disabilities in the large residential hospitals of the nineteenth and twentieth centuries
Elderly care model in rural Bangladesh: the case of YPSA initiative
Get PDFThere are around 13 million people in Bangladesh over the age of 60 which is about 8 per cent of the population. The proportion of older people is expected to double by 2050. Previously, families would have taken care of their older relatives but this situation is changing due to social, psychological and economic reasons. Older people are increasingly being left alone and living separately from their families making them vulnerable, a situation that is more prevalent in rural areas than in the cities. In rural
areas, there is a lack of proper health care services, economic services and decent opportunities leaving older people living in such areas even more vulnerable. This research aims to understand ageing in Bangladesh in the rural setting with a focus on how an effective health care service could be established to support older people living there. The YPSA health care model for older people in Bangladesh can provide a way forward for many other countries in the world to follow
Free and open source software as free culture
No full textThis presentation links and contrasts free and open source software (FOSS) including Koha, with open access (OA) publishing. Library workers broadly accept the values and principles of OA, with many of us both advocating and practically facilitating OA in our work; however the same is however not true of FOSS where we see reticence and a relative lack of bold and ambitious action. The reasons for this, and practical routes to overcome these challenges will be explored. The experience of University of West London Library Services will provide a case study in how our strategic planning can reflect free culture beyond OA, and strategically link OA and FOSS in professional practice
A new vision of a simple 1D Convolutional Neural Networks (1D-CNN) with Leaky-ReLU function for ECG abnormalities classification
Get PDFArtificial Intelligence (AI) is increasingly impacting the healthcare field, due to its computational power that reduces time, cost and efforts for both healthcare professionals and patients. Diagnosing cardiac abnormalities using AI represents a very attractive subject for both medical and technical professionals. Cardiac abnormalities are characterized by the ECG signal, which is known by its variable morphology and intense affection by noises and artifacts. In this context, the presented study aims to propose a simple yet efficient version of Convolutional Neural Networks (CNN) to classify those abnormalities. This version increases the ability to detect several heart rate arrhythmias and severe cardiac abnormalities based only on the original 1D format of the ECG signal, which reserve the main feature of this signal and can be very suitable for ready-to-use and real-time applications. The main used training datasets are the MIT-BIH arrhythmias and the PTB databases. The proposed architectures are mainly inspired by the most recent CNN models and introduce several modifications on functions and layers, such as the use of the Leaky-ReLU instead of the ReLU activation function. The results of the proposed model are varying from an accuracy of 97%–99% in classifying Normal (n), Supraventricular (s), Ventricular (v), Fusion of ventricular and normal (f), and noisy (q) beats, in addition to the Myocardial Infarction (MI) case. A continuous performance was achieved while testing the model on real data, and after its migration to real mobile devices