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Design and optimization of a TensorFlow Lite deep learning neural network for human activity recognition on a smartphone
No full textHuman Activity Recognition (HAR), using machine learning to identify times spent (for example) walking, sitting, and standing, is widely used in health and wellness wearable devices, in ambient assistant living devices, and in rehabilitation. In this paper, a stacked Long Short-Term Memory (LSTM) structure is designed for HAR to be implemented on a smartphone. The use of an edge device for the processing means that the raw collected data does not need to be passed to the cloud for processing, mitigating potential bandwidth, power consumption, and privacy concerns. Our offline prototype model achieves 92.8% classification accuracy when classifying 6 activities using a public dataset. Quantization techniques are shown to reduce the model’s weight representations to achieve a >30x model size reduction for improved use on a smartphone. The end result is an on-phone HAR model with accuracy of 92.7% and a memory footprint of 27 KB
Hybridization as practice: clinical engagement with performance metrics and accounting technologies in the English NHS
No full textPurpose: This study aims to investigate the hybridization practices which medical managers engage with to promote accounting and performance measurement in the hybrid setting of healthcare. In doing so, the authors explore how medical managers enact and become practitioners of hybridity.Design/methodology/approach: The authors adopt a practice lens to conceptualize hybridization as an emergent, situated practice and capture the micro-activities that medical managers engage with when they enact hybridity. The authors conducted semi-structured interviews with medical managers, business managers and coding professionals and collected documents at an English NHS hospital over the course of five years.Findings: The findings accentuate two emergent practices through which medical managers instil hybridity to individuals who are hesitant or resistant to hybridization. Medical managers engage in equivocalizing and destigmatizing practices to broaden the understandings, further diversify or reconcile the teleologies of clinicians in non-managerial roles. In doing so, they signal the merits of accounting in improving care outcomes and remove the stigma associated to clinical engagement with costs.Originality/value: The study contributes to hybridization and practice theory literature via capturing how hybridity is enacted in practice in a healthcare setting. As medical managers engage with and promote accounting information and performance measurement technologies in their practice environment, they transcend professional boundaries and hybridize the professional spaces that surround them
Unravelling the Impact of Graphene Addition to Thermoelectric SrTiO3 and Ladoped SrTiO3 Materials: A Density Functional Theory Study
No full textWe present a detailed theoretical investigation of the interaction of graphene with the SrO terminated (001) surface of pristine and La-doped SrTiO3. The adsorption of graphene is thermodynamically favourable with interfacial adsorption energies of -0.08 Jm-2 and -0.32 Jm-2 to pristine SrTiO3 and La- doped SrTiO3 surfaces respectively. We find that graphene introduces C 2p states at the Fermi level, rendering the composite semi-metallic, and thus the electrical properties are predicted to be highly sensitive to the amount and quality of the graphene in the composites. An investigation of the lattice dynamics predicts that graphene adsorption may lead to a 60-90 % reduction in the thermal conductivity due to a reduction in the phonon group velocities, accounting for the reduced thermal conductivity of the composite materials observed experimentally. This effect is enhanced by La doping. We also find evidence that both La dopant ions and adsorbed graphene introduce low-frequency modes that may scatter the heat-carrying acoustic phonons, and that, if present, these effects likely arise from stronger phonon-phonon interactions
Individual and community social capital, mobility restrictions, and psychological distress during the COVID-19 pandemic: a multilevel analysis of a representative US survey
No full textThis paper explores the role of social capital in mitigating the mental health harms of social/mobility restrictions instigated in the wake of the COVID-19 pandemic. We test whether: (a) social capital continued to predict lower mental distress during the pandemic; and (b) whether social capital buffered (moderated) the harm of social/mobility restrictions on psychological distress. In addition, we test the level at which social capital mitigation effects operated, i.e., at the individual- and/or contextual-level. To do so, we apply multilevel models to three waves of the COVID-19 Household Impact Survey consisting of probability samples of U.S. adults (with the average interview completion rate of 93%). In a novel approach, we explore two modes of capturing contextual social capital: aggregated individual-level survey responses and independently measured social capital indices (SCIs). Findings show that at the individual level social capital was associated with lower psychological distress. It also buffered the harm of restrictions: increasing restrictions had a weaker effect on distress among individuals interacting with neighbors more frequently. Importantly, mitigating processes of contextual social capital appeared conditional on how it was measured. Using aggregated survey responses, contextual social capital had no direct effect on distress but exerted an additional buffering role: individuals in counties with higher average neighbor-interaction experienced a weaker impact of restrictions. Using the independent SCI measures, we found county social capital reduced distress. However, its negative effect on distress becomes increasingly weaker the more restrictions an individual reported: where individuals reported lower restrictions, higher county SCI reduced distress; however, where individuals reported higher restrictions, higher county SCI had no effect on distress. More restrictive environments thus cut individuals off from the benefits of higher county social capital as measured using the SCI
Decision-Making under Uncertainty on Preventive Actions Boosting Power Grid Resilience
No full textThe growing impact of weather-related power outages on economy and society in the last decades underlines the rising need for power system resilience. Power system resilience can be boosted through adoption of probabilistic approaches and preventive actions building on smart grid capabilities. Decisions on the best-performing preventive action, however, are non-trivial and must consider the expected impact of an upcoming event, weather forecasts, fault probabilities and their corresponding uncertainties. This paper presents a three-stage decision-making methodology that is based on assessing weighted pre-event and post-event performance loss and considers spatial uncertainty of fault probabilities, modeled by probability distributions. The methodology is demonstrated using preventive actions, such as additional network constraints and islanding, aiming to mitigate cascading failures in transmission networks. Their performance loss is compared to the traditional N-1 criterion. Simultaneous faults of up to three lines are considered as initiating cause in the IEEE 30-bus network and the 489-bus German transmission network to verify potential and scalability of the methodology. Results show that the decision-making methodology effectively identifies the best-performing action to reduce the risk of cascading failures for any level of uncertainty
Are differences in dysphagia assessment, oral care provision or nasogastric tube insertion associated with stroke-associated pneumonia? A nationwide survey linked to national stroke registry data.
No full textIntroductionStroke-associated pneumonia (SAP) is a common complication associated with poor outcomes. Early dysphagia screening and specialist assessment is associated with reduced risk of SAP. Evidence about oral care and nasogastric tube (NGT) placement is equivocal. This study aimed to expose variations in dysphagia management practices and explore their associations with SAP.Participants and methodsSpeech Pathologists from 166 stroke units in England and Wales were surveyed about dysphagia assessment and management, oral care and NGT placement. Survey data were then linked to the Sentinel Stroke National Audit Programme (SSNAP), the national register of stroke. Univariable and multivariable linear regression models were fitted to estimate the association between dysphagia management practices and SAP incidence.Results113 hospitals completed the survey (68%). Variation was evident in dysphagia screening protocols (DSPs), oral care and NGT practice while specialist swallow assessment data patterns were more consistent. Multivariable analysis showed no evidence of an association in incidence of SAP when using a water-only hospital DSP compared to a multi-consistency DSP (B -.688, 95% CI –2.912-1.536), when using written swallow assessment guidelines compared to not using written guidelines (B .671, 95% CI –1.567-2.908), when teams inserted NGTs overnight compared to teams which did not (B –.505, 95% CI –2.759-1.749) and when teams had a written oral care protocol compared to those which did not (B –1.339, 95% CI –3.551 - .873).Discussion and ConclusionVariation exists in dysphagia screening and management but there was no evidence of an association between clinical practice patterns and incidence of SAP. Further research with larger sample sizes is needed to examine association with SAP
Prognostic factors for relapse in resected gastroenteropancreatic neuroendocrine neoplasms: A systematic review and meta-analysis
No full textBackground: Gastroenteropancreatic neoplasms (GEP-NENs) can potentially be cured through surgical resection, but only 42-57% achieve 5-year disease-free survival. There is a lack of consensus regarding the factors associated with relapse following resection of GEP-NENs. Methods: A systematic review identified studies reporting factors associated with relapse in patients with GEP-NENs following resection of a primary tumour. Meta-analysis was performed to identify the factors prognostic for relapse-free survival (RFS) or overall survival (OS). Results: 63 studies comprising 13,715 patients were included; 56 studies reported on pancreatic NENs (12,418 patients), 24 reported on patients with grade 1-2 tumours (4,735 patients). Median follow-up was 44.2 months, median RFS was 32 months. Pooling of multivariable analyses of GEP-NENs (all sites and grades) found the following factors predicted worse RFS (all p values <0.05): vascular resection performed, metastatic disease resected, grade 2 disease, grade 3 disease, tumour size >20mm, R1 resection, microvascular invasion, perineural invasion, Ki-67>5% and any lymph node positivity. In a subgroup of studies comprising exclusively of grade 1-2 GEP-NENs, R1 resection, perineural invasion, grade 2 disease, any lymph node positivity and tumour size >20mm predicted worse RFS (all p values <0.05). Few OS data were available for pooling; in univariable analysis (entire cohort), grade 2 predicted worse OS (p=0.007), while R1 resection did not (p=0.14). Conclusions: The factors prognostic for worse RFS following resection of a GEP-NEN identified in this meta-analysis could be included in post-curative treatment surveillance clinical guidelines and inform the stratification and inclusion criteria of future adjuvant trials
Striving for evidence-based management of food allergies
No full textThis Issue of the Journal highlights several advances in Food Allergy diagnosis and management. It comes seven years after Du Toit et al’s seminal randomized, double-blinded, clinical trial Learning Early About Peanut (LEAP) that has led to a revolution in our thinking about food allergy prevention.1 The LEAP study clearly demonstrated that at least in high-risk infants and young children with eczema and egg allergy, food avoidance increases the prevalence of peanut allergy. The aim of this theme editorial is to highlight key take home messages and ongoing challenges presented in this Issue’s Rostrum and Review articles that clinicians currently face regarding the diagnosis and management of patients with suspected food allergies
Adaptive lead weighted ResNet trained with different duration signals for classifying 12-lead ECGs
No full textIntroduction: We describe the creation of a ensemble deep neural network architecture to classify cardiac abnormality from 12 lead ECGs. The model was created by the team between a ROC and a heart place for the PhysioNet/Computing in Cardiology Challenge 2020.Methods: ECGs were downsampled to 257 Hz and then set to a consistent duration by randomly clipping or zeropadding the signal to 4096 samples. To learn effective features, we created a modified ResNet with larger kernel sizes that models long-term dependencies. We embeddeda Squeeze-And-Excitation layer into the modified ResNet to learn the importance of each lead, adaptively. A simple constrained grid-search method was applied to deal with class imbalance.Results: Using the bespoke weighted accuracy metric, We achieved a 5-fold cross-validation score of 0.684, sensitivity and specificity of 0.758 and 0.969, respectively. The corresponding result for the hidden test set was 0.672.Conclusion: The proposed prediction model performed well on the validation and hidden test data. Such modelsmay be potentially used for ECG screening or diagnosis
Tropoelastin and Elastin Assembly
No full textElastic fibers are an important component of the extracellular matrix, providing stretch, resilience and cell interactivity to a broad range of elastic tissues. Elastin makes up the majority of elastic fibers and is formed by the hierarchical assembly of its monomer, tropoelastin. Our understanding of key aspects of the assembly process have been unclear due to the intrinsic properties of elastin and tropoelastin that render them difficult to study. This review focuses on recent developments that have shaped our current knowledge of elastin assembly through understanding the relationship between tropoelastin’s structure and function