Non-contact under-mattress sleep monitoring

Sleep quality and duration are increasingly recognised as being important prognostic parameters in the assessment of an individual's health. However, reliable non-invasive long-term monitoring of sleep in a non-clinical setting remains a challenging problem. This paper describes the validation of a novel under mattress pressure sensing sleep monitoring modality that can be seamlessly integrated into existing home environments and provides a pervasive and distributed solution for monitoring long-term changes in sleep patterns and sleep disorders in adults. 410 minutes of concomitant Under Mattress Bed Sensor (UMBS) and strain gauge data were analysed from eight healthy adults lying passively. In this analysis, customised respirations rate detection algorithms yielded a mean difference of −0.12 breaths per five minutes and a mean percentage error (MPE) of 0.16% when the sensor was placed beneath the mattress. 1,491 minutes of UMBS and video data were recorded simultaneously from four participants in order to assess the movement detection efficacy of customised UMBS algorithms. These algorithms yielded accuracies, sensitivities and specificities of over 90% when compared to a video-based movement detection gold standard. A reduced data set (267 minutes) of wrist actigraphy, the gold standard ambulatory sleep monitor, was recorded. The UMBS was shown to outperform the movement detection ability of wrist actigraphy and has the added advantage of not requiring active subject participation.

Automated versus non-automated weaning for reducing the duration of mechanical ventilation in critically ill adults & children (Review)

Background Automated closed loop systems may improve adaptation of mechanical support for a patient's ventilatory needs and facilitate systematic and early recognition of their ability to breathe spontaneously and the potential for discontinuation of ventilation. This review was originally published in 2013 with an update published in 2014. Objectives The primary objective for this review was to compare the total duration of weaning from mechanical ventilation, defined as the time from study randomization to successful extubation (as defined by study authors), for critically ill ventilated patients managed with an automated weaning system versus no automated weaning system (usual care). Secondary objectives for this review were to determine differences in the duration of ventilation, intensive care unit (ICU) and hospital lengths of stay (LOS), mortality, and adverse events related to early or delayed extubation with the use of automated weaning systems compared to weaning in the absence of an automated weaning system. Search methods We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2013, Issue 8); MEDLINE (OvidSP) (1948 to September 2013); EMBASE (OvidSP) (1980 to September 2013); CINAHL (EBSCOhost) (1982 to September 2013); and the Latin American and Caribbean Health Sciences Literature (LILACS). Relevant published reviews were sought using the Database of Abstracts of Reviews of Effects (DARE) and the Health Technology Assessment Database (HTA Database). We also searched the Web of Science Proceedings; conference proceedings; trial registration websites; and reference lists of relevant articles. The original search was run in August 2011, with database auto-alerts up to August 2012. Selection criteria We included randomized controlled trials comparing automated closed loop ventilator applications to non-automated weaning strategies including non-protocolized usual care and protocolized weaning in patients over four weeks of age receiving invasive mechanical ventilation in an ICU. Data collection and analysis Two authors independently extracted study data and assessed risk of bias. We combined data in forest plots using random-effects modelling. Subgroup and sensitivity analyses were conducted according to a priori criteria. Main results We included 21 trials (19 adult, two paediatric) totaling 1676 participants (1628 adults, 48 children) in this updated review. Pooled data from 16 eligible trials reporting weaning duration indicated that automated closed loop systems reduced the geometric mean duration of weaning by 30% (95% confidence interval (CI) 13% to 45%), however heterogeneity was substantial (I2 = 87%, P < 0.00001). Reduced weaning duration was found with mixed or medical ICU populations (42%, 95% CI 10% to 63%) and Smartcare/PS™ (28%, 95% CI 7% to 49%) but not in surgical populations or using other systems. Automated closed loop systems reduced the duration of ventilation (10%, 95% CI 3% to 16%) and ICU LOS (8%, 95% CI 0% to 15%). There was no strong evidence of an effect on mortality rates, hospital LOS, reintubation rates, self-extubation and use of non-invasive ventilation following extubation. Prolonged mechanical ventilation > 21 days and tracheostomy were reduced in favour of automated systems (relative risk (RR) 0.51, 95% CI 0.27 to 0.95 and RR 0.67, 95% CI 0.50 to 0.90 respectively). Overall the quality of the evidence was high with the majority of trials rated as low risk. Authors' conclusions Automated closed loop systems may result in reduced duration of weaning, ventilation and ICU stay. Reductions are more likely to occur in mixed or medical ICU populations. Due to the lack of, or limited, evidence on automated systems other than Smartcare/PS™ and Adaptive Support Ventilation no conclusions can be drawn regarding their influence on these outcomes. Due to substantial heterogeneity in trials there is a need for an adequately powered, high quality, multi-centre randomized controlled trial in adults that excludes 'simple to wean' patients. There is a pressing need for further technological development and research in the paediatric population.

Non-pharmacological interventions for cognitive impairment due to systemic cancer treatment

This is the protocol for a review and there is no abstract. The objectives are as follows:

The primary objective of this review is to evaluate the effects of non-pharmacological interventions among cancer patients targeted at maintaining cognitive function or ameliorating cognitive impairment as a result of cancer or receipt of systemic cancer treatment (i.e. chemotherapy or hormonal therapies in isolation or combination with other treatments). Patients who have received treatments such as cranial radiation for central nervous system tumours or metastases are not the focus of this review and will be excluded.

A second objective is to evaluate the effectiveness of non-pharmacological interventions for improving non-cognitive outcomes e.g. quality of life among this population.

Thirdly, we will extract and analyse data regarding the duration of intervention effects.

Fourthly, we will examine each study to identify safety as an outcome and incorporate information on intervention safety where possible. Evidence for the review will be based on data from randomised trials.

Conventional in vivo irradiation procedures are insufficient to accurately determine tumor responses to non-uniform radiation fields

Purpose: To determine differences in overall tumor responses measured by volumetric assessment and bioluminescence imaging (BLI) following exposure to uniform and non-uniform radiation fields in an ectopic prostate tumor model.

Materials and methods: Bioluminescent human prostate tumor xenografts were established by subcutaneous implantation into male mice. Tumors were irradiated with uniform or non-uniform field configurations using conventional in vivo irradiation procedures performed using a 225 kVp generator with custom lead shielding. Tumor responses were measured using Vernier calipers and by BLI using an in vivo imaging system. Survival was defined as the time to quadroupling of pre-treatment tumor volume. 

Results: The correlation between BLI and tumor volume measurements was found to be different for un-irradiated (R = 0.61), uniformly irradiated (R = 0.34) and partially irradiated (R = 0.30) tumors. Uniformly irradiated tumors resulted in an average tumor growth delay of 60 days with median survival of 75 days, compared to partially irradiated tumors which showed an average growth delay of 24 days and median survival of 38 days. 

Conclusions: Correlation between BLI and tumor volume measurements is lower for partially irradiated tumors than those exposed to uniform dose distributions. The response of partially irradiated tumors suggests non-uniformity in response beyond physical dose distribution within the target volume. Dosimetric uncertainty associated with conventional in vivo irradiation procedures prohibits their ability to accurately determine tumor response to non-uniform radiation fields and stresses the need for image guided small animal radiation research platforms.

ZIL: An Energy-Efficient Indoor Localization System Using ZigBee Radio to Detect WiFi Fingerprints

In existing WiFi-based localization methods, smart mobile devices consume quite a lot of power as WiFi interfaces need to be used for frequent AP scanning during the localization process. In this work, we design an energy-efficient indoor localization system called ZigBee assisted indoor localization (ZIL) based on WiFi fingerprints via ZigBee interference signatures. ZIL uses ZigBee interfaces to collect mixed WiFi signals, which include non-periodic WiFi data and periodic beacon signals. However, WiFi APs cannot be identified from these WiFi signals by ZigBee interfaces directly. To address this issue, we propose a method for detecting WiFi APs to form WiFi fingerprints from the signals collected by ZigBee interfaces. We propose a novel fingerprint matching algorithm to align a pair of fingerprints effectively. To improve the localization accuracy, we design the K-nearest neighbor (KNN) method with three different weighted distances and find that the KNN algorithm with the Manhattan distance performs best. Experiments show that ZIL can achieve the localization accuracy of 87%, which is competitive compared to state-of-the-art WiFi fingerprint-based approaches, and save energy by 68% on average compared to the approach based on WiFi interface.

More nonlocality with less entanglement in a tripartite atom-optomechanical system

Quantum effects in hybrid atomic optomechanics in a system comprising a cloud of atoms and a mobile mirror mediated by a single-mode cavity are studied. Tripartite non-locality is observed in the atom-light-mirror system, as demonstrated by the violation of the Mermin-Klyshko (MK) inequality. It has been shown [C. Genes, et al., PRA 77, 050307 (R) (2008)] that tripartite entanglement is optimized when the cavity is resonant with the anti-Stokes sideband of the driving laser and the atomic frequency matches the Stokes one. However, we show that this is not the case for the nonlocality. The MK function achieves minima when the atoms are resonant with both the Stokes and anti-Stokes sidebands, and unexpectedly, we find violation of the MK inequality only in a parameter region where entanglement is far from being maximum. A negative relation exists between nonlocality and entanglement with consideration of the possibility of bipartite nonlocality in the violation of the MK inequality. We also study the non-classicality of the mirror by post-selected measurements, e.g. Geiger-like detection, on the cavity and/or the atoms. We show that with feasible parameters Geiger-like detection on the atoms can effectively induce mechanical non-classicality.

Dynamical symmetries and crossovers in a three-spin system with collective dissipation

We consider the non-equilibrium dynamics of a simple system consisting of interacting spin-1/2 particles subjected to a collective damping. The model is close to situations that can be engineered in hybrid electro/opto-mechanical settings. Making use of large-deviation theory, we find a Gallavotti-Cohen symmetry in the dynamics of the system as well as evidence for the coexistence of two dynamical phases with different activity levels. We show that additional damping processes smooth out this behavior. Our analytical results are backed up by Monte Carlo simulations that reveal the nature of the trajectories contributing to the different dynamical phases.

Non-Markovian qubit dynamics in a circuit-QED setup

We consider a circuit-QED setup that allows the induction and control of non-Markovian dynamics of a qubit. Non-Markovianity is enforced over the qubit by means of its direct coupling to a bosonic mode which is controllably coupled to another qubit-mode system. We show that this configuration can be achieved in a circuit-QED setup consisting of two initially independent superconducting circuits, each formed by one charge qubit and one transmission-line resonator, which are put in interaction by coupling the resonators to a current-biased Josephson junction. We solve this problem exactly and then proceed with a thorough investigation of the emergent non-Markovianity in the dynamics of the qubits. Our study might serve the context for the first experimental assessment of non-Markovianity in a multielement solid-state device.

Non-convex dynamic economic/environmental dispatch with plug-in electric vehicle loads

Electric vehicles are a key prospect for future transportation. A large penetration of electric vehicles has the potential to reduce the global fossil fuel consumption and hence the greenhouse gas emissions and air pollution. However, the additional stochastic loads imposed by plug-in electric vehicles will possibly introduce significant changes to existing load profiles. In his paper, electric vehicles loads are integrated into an 5-unit system using a non-convex dynamic dispatch model. The actual infrastructure characteristics including valve-point effects, load balance constrains and transmission loss have been included in the model. Multiple load profiles are comparatively studied and compared in terms of economic and environmental impacts in order o identify patterns to charge properly. The study as expected shows ha off-peak charging is the best scenario with respect to using less fuels and producing less emissions.

Experiment of Digital Directional Modulation Transmitters

A digital directional modulation (DM) transmitter structure is proposed from a practical implementation point of view in this paper. This digital DM architecture is built with the help of several off-the-shelf physical layer wireless experiment platform hardware boards. When compared with previous analogue DM transmitter architectures, the digital means offers more precise and fast control on the updates of the array excitations. More importantly, it is an ideal physical arrangement to implement the most universal DM synthesis algorithm, i.e., the orthogonal vector approach. The practical issues in digital DM system calibrations are described and solved. The bit error rates (BERs) are measured via real-time data transmissions to illustrate the DM advantages, in terms of secrecy performance, over conventional non-DM beam-steering transmitters.

Optimal Scheduling Methods to Integrate Plug-In Electric Vehicles with the Power System: A Review

The introduction of the Tesla in 2008 has demonstrated to the public of the potential of electric vehicles in terms of reducing fuel consumption and green-house gas from the transport sector. It has brought electric vehicles back into the spotlight worldwide at a moment when fossil fuel prices were reaching unexpected high due to increased demand and strong economic growth. The energy storage capabilities from of fleets of electric vehicles as well as the potentially random discharging and charging offers challenges to the grid in terms of operation and control. Optimal scheduling strategies are key to integrating large numbers of electric vehicles and the smart grid. In this paper, state-of-the-art optimization methods are reviewed on scheduling strategies for the grid integration with electric vehicles. The paper starts with a concise introduction to analytical charging strategies, followed by a review of a number of classical numerical optimization methods, including linear programming, non-linear programming, dynamic programming as well as some other means such as queuing theory. Meta-heuristic techniques are then discussed to deal with the complex, high-dimensional and multi-objective scheduling problem associated with stochastic charging and discharging of electric vehicles. Finally, future research directions are suggested.

PET/CT imaging for target volume delineation in curative intent radiotherapy of non-small cell lung cancer: IAEA consensus report 2014

This document describes best practice and evidence based recommendations for the use of FDG-PET/CT for the purposes of radiotherapy target volume delineation (TVD) for curative intent treatment of non-small cell lung cancer (NSCLC). These recommendations have been written by an expert advisory group, convened by the International Atomic Energy Agency (IAEA) to facilitate a Coordinated Research Project (CRP) aiming to improve the applications of PET based radiation treatment planning (RTP) in low and middle income countries. These guidelines can be applied in routine clinical practice of radiotherapy TVD, for NSCLC patients treated with concurrent chemoradiation or radiotherapy alone, where FDG is used, and where a calibrated PET camera system equipped for RTP patient positioning is available. Recommendations are provided for PET and CT image visualization and interpretation, and for tumor delineation using planning CT with and without breathing motion compensation.

HpMC: An Energy- Aware Management System for Multi-Level Memory Architectures

DRAM technology faces density and power challenges to increase capacity because of limitations of physical cell design. To overcome these limitations, system designers are exploring alternative solutions that combine DRAM and emerging NVRAM technologies. Previous work on heterogeneous memories focuses, mainly, on two system designs: PCache, a hierarchical, inclusive memory system, and HRank, a flat, non-inclusive memory system. We demonstrate that neither of these designs can universally achieve high performance and energy efficiency across a suite of HPC workloads. In this work, we investigate the impact of a number of multilevel memory designs on the performance, power, and energy consumption of applications. To achieve this goal and overcome the limited number of available tools to study heterogeneous memories, we created HMsim, an infrastructure that enables n-level, heterogeneous memory studies by leveraging existing memory simulators. We, then, propose HpMC, a new memory controller design that combines the best aspects of existing management policies to improve performance and energy. Our energy-aware memory management system dynamically switches between PCache and HRank based on the temporal locality of applications. Our results show that HpMC reduces energy consumption from 13% to 45% compared to PCache and HRank, while providing the same bandwidth and higher capacity than a conventional DRAM system.

Performance assessment of cascade control loopswith non-Gaussian disturbances using entropy information

Cascade control is one of the routinely used control strategies in industrial processes because it can dramatically improve the performance of single-loop control, reducing both the maximum deviation and the integral error of the disturbance response. Currently, many control performance assessment methods of cascade control loops are developed based on the assumption that all the disturbances are subject to Gaussian distribution. However, in the practical condition, several disturbance sources occur in the manipulated variable or the upstream exhibits nonlinear behaviors. In this paper, a general and effective index of the performance assessment of the cascade control system subjected to the unknown disturbance distribution is proposed. Like the minimum variance control (MVC) design, the output variances of the primary and the secondary loops are decomposed into a cascade-invariant and a cascade-dependent term, but the estimated ARMA model for the cascade control loop based on the minimum entropy, instead of the minimum mean squares error, is developed for non-Gaussian disturbances. Unlike the MVC index, an innovative control performance index is given based on the information theory and the minimum entropy criterion. The index is informative and in agreement with the expected control knowledge. To elucidate wide applicability and effectiveness of the minimum entropy cascade control index, a simulation problem and a cascade control case of an oil refinery are applied. The comparison with MVC based cascade control is also included.

A novel radial basis function neural network principal component analysis scheme for PMU-based wide-area power system monitoring

A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.