Probabilistic Analysis of Temporal and Sequential Aspects of Activities of Daily Living for Abnormal Behaviour Detection

This paper presents a probabilistic approach for the identification of abnormal behaviour in Activities of Daily Living (ADLs) from dense sensor data collected from 30 participants. The ADLs considered are related to preparing and drinking (i) tea, and (ii) coffee. Abnormal behaviour identified in the context of these activities can be an indicator of a progressive health problem or the occurrence of a hazardous incident. The approach presented considers the temporal and sequential aspects of the actions that are part of each ADL and that vary between participants. The average and standard deviation for the duration and number of steps of each activity are calculated to define the average time and steps and a range within which a behaviour could be considered as normal for each stage and activity. The Cumulative Distribution Function (CDF) is used to obtain the probabilities of abnormal behaviours related to the early and late completion of activities and stages within an activity in terms of time and steps. Analysis shows that CDF can provide precise and reliable results regarding the presence of abnormal behaviour in stages and activities that last over a minute or consist of many steps. Finally, this approach could be used to train machine learning algorithms for abnormal behaviour detection.status: publishe

Probabilistic Analysis of Abnormal Behaviour Detection in Activities of Daily Living

This paper presents a probabilistic approach for the identification of abnormal behaviour in Activities of Daily Living (ADLs) from sensor data collected from 30 participants. The ADLs considered are: (i) preparing and drinking tea, and (ii) preparing and drinking coffee. Abnormal behaviour identified in the context of these activities can be an indicator of a progressive health problem or the occurrence of a hazardous incident. The approach presented considers the temporal aspect of the sequences of actions that are part of each ADL and that vary between participants. The average and standard deviation for the durations of each action were calculated to define an average time and a range in which a behaviour could be considered as normal for each stage and activity. The Cumulative Distribution Function (CDF) was used to obtain the probabilities of abnormal behaviours related to the early and late completion of activities and stages within an activity. The data analysis show that CDF can provide accurate and reliable results regarding the presence of abnormal behaviour in stages and activities that last over a minute. Finally, this approach could be used to train machine learning algorithms for the abnormal behaviour detection

Protection associated with a TB vaccine is linked to increased frequency of Ag85A-specific CD4⁺ T cells but no increase in avidity for Ag85A

AbstractThere is a need to improve the efficacy of Bacille Calmette-Guérin (BCG) vaccination against tuberculosis in humans and cattle. Previously, we found boosting BCG-primed cows with recombinant human type 5 adenovirus expressing antigen 85A (Ad5-85A) increased protection against Mycobacterium bovis infection compared to BCG vaccination alone. The aim of this study was to decipher aspects of the immune response associated with this enhanced protection. We compared BCG-primed Ad5-85A-boosted cattle with BCG-vaccinated cattle. Polyclonal CD4+ T cell libraries were generated from pre-boost and post-boost peripheral blood mononuclear cells – using a method adapted from Geiger et al. (2009) – and screened for antigen 85A (Ag85A) specificity. Ag85A-specific CD4+ T cell lines were analysed for their avidity for Ag85A and their Ag85A epitope specificity was defined. Boosting BCG with Ad5-85A increased the frequencies of post-boost Ag85A-specific CD4+ T cells which correlated with protection (reduced pathology). Boosting Ag85A-specific CD4+ T cell responses did not increase their avidity. The epitope specificity was variable between animals and we found no clear evidence for a post-boost epitope spreading. In conclusion, the protection associated with boosting BCG with Ad5-85A is linked with increased frequencies of Ag85A-specific CD4+ T cells without increasing avidity or widening of the Ag85A-specific CD4+ T cell repertoire

The diet-derived short chain fatty acid propionate improves beta-cell function in humans and stimulates insulin secretion from human islets in vitro

Aims: Diet-derived short chain fatty acids (SCFAs) improve glucose homeostasis in vivo, but the role of individual SCFAs and their mechanisms of action have not been defined. This study evaluated the effects of increasing colonic delivery of the SCFA propionate on β-cell function in humans and the direct effects of propionate on isolated human islets in vitro. Materials and Methods: For 24 weeks human subjects ingested an inulin-propionate ester that delivers propionate to the colon. Acute insulin, GLP-1 and non-esterified fatty acid (NEFA) levels were quantified pre- and post-supplementation in response to a mixed meal test. Expression of the SCFA receptor FFAR2 in human islets was determined by western blotting and immunohistochemistry. Dynamic insulin secretion from perifused human islets was quantified by radioimmunoassay and islet apoptosis was determined by quantification of caspase 3/7 activities. Results: Colonic propionate delivery in vivo was associated with improved β-cell function with increased insulin secretion that was independent of changes in GLP-1 levels. Human islet β-cells expressed FFAR2 and propionate potentiated dynamic glucose-stimulated insulin secretion in vitro, an effect that was dependent on signalling via protein kinase C. Propionate also protected human islets from apoptosis induced by the NEFA sodium palmitate and inflammatory cytokines. Conclusions: Our results indicate that propionate has beneficial effects on β-cell function in vivo, and in vitro analyses demonstrated that it has direct effects to potentiate glucose-stimulated insulin release and maintain β-cell mass through inhibition of apoptosis. These observations support ingestion of propiogenic dietary fibres to maintain healthy glucose homeostasis

The effect of polymer end-group on the formation of styrene – maleic acid lipid particles (SMALPs)

A series of block copolymers comprising styrene and maleic acid (SMA) has been prepared using RAFT polymerisation. RAFT often results in a large hydrophobic alkylthiocarbonylthio end group and this work examines its effect on the solution behaviour of the copolymers. SMA variants with, and without, this end group were synthesised and their behaviour compared with a commercially-available random copolymer of similar molecular weight. Dynamic light scattering and surface tension measurements found the RAFT-copolymers preferentially self-assembled into higher-order aggregates in aqueous solution. Small angle neutron scattering using deuterated styrene varients add support to the accepted model that these agreggates comprise a solvent-protected styrenic core with an acid-rich shell. Replacing the hydrophobic RAFT end group with a more hydrophilic nitrile caused differences in the resulting surface activity, attributed to the ability of the adjoining styrene homoblock to drive aggregation. Each of the copolymers formed SMALP nanodiscs with DMPC lipids, which were found to encapsulate a model membrane protein, gramicidin. However, end group variation affected solubilisition of DPPC, a lipid with a higher phase transition temperature. When using RAFT-copolymers terminated with a hydrophobic group, swelling of the bilayer and greater penetration of the homoblock into the nanodisc core occurred with increasing homoblock length. Conversely, commercial and nitrile-terminated RAFT-copolymers produced nanodisc sizes that stayed constant, instead indicating interaction at the edge of the lipid patch. The results highlight how even minor changes to the copolymer can modify the amphiphilic balance between regions, knowledge useful towards optimising copolymer structure to enhance and control nanodisc formation

Safe Beacon: A Bluetooth Based Solution to Monitor Egress of Dementia Sufferers within a Residential Setting

The global population is ageing, as a consequence of this there will be a greater incidence of ageing related illnesses which cause cognitive impairment–such as Alzheimer’s disease. Within residential care homes, such cognitive impairment can lead to wandering of individuals beyond the boundaries of safety provided. This wandering, particularly in urban areas can be life threatening. This study introduces a novel solution to detect, and alert caregivers of, egress of at-risk inhabitants of a care home. This solution operates through a combination of wearable Bluetooth beacons and beam-formed listening devices. In an evaluation process involving 275 egress events, this solution proved to offer accurate operation with no incidence of false positives. Notably, this solution has been deployed within a real residential care home environment for over 12 months. Proposed future work discusses improvements to this solution