Machine learning methods for detecting urinary tract infection and analysing daily living activities in people with dementia

Dementia is a neurological and cognitive condition that affects millions of people around the world. At any given time in the United Kingdom, 1 in 4 hospital beds are occupied by a person with dementia, while about 22% of these hospital admissions are due to preventable causes. In this paper we discuss using Internet of Things (IoT) technologies and in-home sensory devices in combination with machine learning techniques to monitor health and well-being of people with dementia. This will allow us to provide more effective and preventative care and reduce preventable hospital admissions. One of the unique aspects of this work is combining environmental data with physiological data collected via low cost in-home sensory devices to extract actionable information regarding the health and well-being of people with dementia in their own home environment. We have worked with clinicians to design our machine learning algorithms where we focused on developing solutions for real-world settings. In our solutions, we avoid generating too many alerts/alarms to prevent increasing the monitoring and support workload. We have designed an algorithm to detect Urinary Tract Infections (UTI) which is one of the top five reasons of hospital admissions for people with dementia (around 9% of hospital admissions for people with dementia in the UK). To develop the UTI detection algorithm, we have used a Non-negative Matrix Factorisation (NMF) technique to extract latent factors from raw observation and use them for clustering and identifying the possible UTI cases. In addition, we have designed an algorithm for detecting changes in activity patterns to identify early symptoms of cognitive decline or health decline in order to provide personalised and preventative care services. For this purpose, we have used an Isolation Forest (iForest) technique to create a holistic view of the daily activity patterns. This paper describes the algorithms and discusses the evaluation of the work using a large set of real-world data collected from a trial with people with dementia and their caregivers

Progress and prospects of thermo-mechanical energy storage—a critical review

Abstract: The share of electricity generated by intermittent renewable energy sources is increasing (now at 26% of global electricity generation) and the requirements of affordable, reliable and secure energy supply designate grid-scale storage as an imperative component of most energy transition pathways. The most widely deployed bulk energy storage solution is pumped-hydro energy storage (PHES), however, this technology is geographically constrained. Alternatively, flow batteries are location independent and have higher energy densities than PHES, but remain associated with high costs and short lifetimes, which highlights the importance of developing and utilizing additional larger-scale, longer-duration and long-lifetime energy storage alternatives. In this paper, we review a class of promising bulk energy storage technologies based on thermo-mechanical principles, which includes: compressed-air energy storage, liquid-air energy storage and pumped-thermal electricity storage. The thermodynamic principles upon which these thermo-mechanical energy storage (TMES) technologies are based are discussed and a synopsis of recent progress in their development is presented, assessing their ability to provide reliable and cost-effective solutions. The current performance and future prospects of TMES systems are examined within a unified framework and a thermo-economic analysis is conducted to explore their competitiveness relative to each other as well as when compared to PHES and battery systems. This includes carefully selected thermodynamic and economic methodologies for estimating the component costs of each configuration in order to provide a detailed and fair comparison at various system sizes. The analysis reveals that the technical and economic characteristics of TMES systems are such that, especially at higher discharge power ratings and longer discharge durations, they can offer promising performance (round-trip efficiencies higher than 60%) along with long lifetimes (>30 years), low specific costs (often below 100 $ kWh−1), low ecological footprints and unique sector-coupling features compared to other storage options. TMES systems have significant potential for further progress and the thermo-economic comparisons in this paper can be used as a benchmark for their future evolution

Progress and prospects of thermo-mechanical energy storage—a critical review

Abstract: The share of electricity generated by intermittent renewable energy sources is increasing (now at 26% of global electricity generation) and the requirements of affordable, reliable and secure energy supply designate grid-scale storage as an imperative component of most energy transition pathways. The most widely deployed bulk energy storage solution is pumped-hydro energy storage (PHES), however, this technology is geographically constrained. Alternatively, flow batteries are location independent and have higher energy densities than PHES, but remain associated with high costs and short lifetimes, which highlights the importance of developing and utilizing additional larger-scale, longer-duration and long-lifetime energy storage alternatives. In this paper, we review a class of promising bulk energy storage technologies based on thermo-mechanical principles, which includes: compressed-air energy storage, liquid-air energy storage and pumped-thermal electricity storage. The thermodynamic principles upon which these thermo-mechanical energy storage (TMES) technologies are based are discussed and a synopsis of recent progress in their development is presented, assessing their ability to provide reliable and cost-effective solutions. The current performance and future prospects of TMES systems are examined within a unified framework and a thermo-economic analysis is conducted to explore their competitiveness relative to each other as well as when compared to PHES and battery systems. This includes carefully selected thermodynamic and economic methodologies for estimating the component costs of each configuration in order to provide a detailed and fair comparison at various system sizes. The analysis reveals that the technical and economic characteristics of TMES systems are such that, especially at higher discharge power ratings and longer discharge durations, they can offer promising performance (round-trip efficiencies higher than 60%) along with long lifetimes (>30 years), low specific costs (often below 100 $ kWh−1), low ecological footprints and unique sector-coupling features compared to other storage options. TMES systems have significant potential for further progress and the thermo-economic comparisons in this paper can be used as a benchmark for their future evolution

Enhanced microdialysis of neuropeptides.

An enhanced microdialysis method for neuropeptides is described and some preliminary results of this novel approach are presented. The enhancement is achieved by adding a vehicle (solid support) to the perfusion fluid in order to increase the diffusion coefficient across the membrane and efficiently transport the analytes towards the detector. The microdialysis samples are desalted and then analyzed on an electrospray ionization orthogonal time-of-flight mass spectrometer. The preliminary results show major increase in signal when comparing this new approach of microdialysis with ordinary microdialysis