954 resultados para NON-IDEAL SYSTEM


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The simulation of open quantum dynamics has recently allowed the direct investigation of the features of system-environment interaction and of their consequences on the evolution of a quantum system. Such interaction threatens the quantum properties of the system, spoiling them and causing the phenomenon of decoherence. Sometimes however a coherent exchange of information takes place between system and environment, memory effects arise and the dynamics of the system becomes non-Markovian. Here we report the experimental realisation of a non-Markovian process where system and environment are coupled through a simulated transverse Ising model. By engineering the evolution in a photonic quantum simulator, we demonstrate the role played by system-environment correlations in the emergence of memory effects.

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Physical transceivers have hardware impairments that create distortions which degrade the performance of communication systems. The vast majority of technical contributions in the area of relaying neglect hardware impairments and, thus, assume ideal hardware. Such approximations make sense in low-rate systems, but can lead to very misleading results when analyzing future high-rate systems. This paper quantifies the impact of hardware impairments on dual-hop relaying, for both amplify-and-forward and decode-and-forward protocols. The outage probability (OP) in these practical scenarios is a function of the effective end-to-end signal-to-noise-and-distortion ratio (SNDR). This paper derives new closed-form expressions for the exact and asymptotic OPs, accounting for hardware impairments at the source, relay, and destination. A similar analysis for the ergodic capacity is also pursued, resulting in new upper bounds. We assume that both hops are subject to independent but non-identically distributed Nakagami-m fading. This paper validates that the performance loss is small at low rates, but otherwise can be very substantial. In particular, it is proved that for high signal-to-noise ratio (SNR), the end-to-end SNDR converges to a deterministic constant, coined the SNDR ceiling, which is inversely proportional to the level of impairments. This stands in contrast to the ideal hardware case in which the end-to-end SNDR grows without bound in the high-SNR regime. Finally, we provide fundamental design guidelines for selecting hardware that satisfies the requirements of a practical relaying system.

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Electrostatic solitary waves in plasmas are the focus of many current studies of localized electrostatic disturbances in both laboratory and astrophysical plasmas. Here, an investigation of the nonlinear dynamics of plasma evolving in two dimensions, in the presence of excess superthermal background electrons and positrons, is undertaken. We investigate the effect of a magnetic field on weakly nonlinear ion acoustic waves. Deviation from the Maxwellian distribution is effectively modelled by the kappa model. A linear dispersion relation is derived, and a decrease in frequency and phase speed in both parallel and perpendicular modes can be seen, when the proportion of positrons to electrons increases. We show that ion acoustic solitary waves can be generated during the nonlinear evolution of a plasma fluid, and their nonlinear propagation is governed by a Zakharov-Kuznetsov (ZK) type equation. A multiple scales perturbation technique is used to derive the ZK equation. The solitary wave structures are dependent on the relation between the system parameters, specifically the superthermality of the system, the proportion of positron content, magnetic field strength, and the difference between electron and positron temperature. The parametric effect of these on electrostatic shock structures is investigated. In particular, we find that stronger superthermality leads to narrower excitations with smaller potential amplitudes. Increased positron concentration also suppresses both the amplitude and the width of solitary wave structures. However, the structures are only weakly affected by temperature differentials between electrons and positrons in our model. © 2013 AIP Publishing LLC.

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The pressure and velocity field in a one-dimensional acoustic waveguide can be sensed in a non-intrusive manner using spatially distributed microphones. Experimental characterization with sensor arrangements of this type has many applications in measurement and control. This paper presents a method for measuring the acoustic variables in a duct under fluctuating propagation conditions with specific focus on in-system calibration and tracking of the system parameters of a three-microphone measurement configuration. The tractability of the non-linear optimization problem that results from taking a parametric approach is investigated alongside the influence of extraneous measurement noise on the parameter estimates. The validity and accuracy of the method are experimentally assessed in terms of the ability of the calibrated system to separate the propagating waves under controlled conditions. The tracking performance is tested through measurements with a time-varying mean flow, including an experiment conducted under propagation conditions similar to those in a wind instrument during playing.

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Background: Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) are commonly prescribed to the growing number of cancer patients (more than two million in the UK alone) often to treat hypertension. However, increased fatal cancer in ARB users in a randomized trial and increased breast cancer recurrence rates in ACEI users in a recent observational study have raised concerns about their safety in cancer patients. We investigated whether ACEI or ARB use after breast, colorectal or prostate cancer diagnosis was associated with increased risk of cancer-specific mortality.

Methods: Population-based cohorts of 9,814 breast, 4,762 colorectal and 6,339 prostate cancer patients newly diagnosed from 1998 to 2006 were identified in the UK Clinical Practice Research Datalink and confirmed by cancer registry linkage. Cancer-specific and all-cause mortality were identified from Office of National Statistics mortality data in 2011 (allowing up to 13 years of follow-up). A nested case–control analysis was conducted to compare ACEI/ARB use (from general practitioner prescription records) in cancer patients dying from cancer with up to five controls (not dying from cancer). Conditional logistic regression estimated the risk of cancer-specific, and all-cause, death in ACEI/ARB users compared with non-users.

Results: The main analysis included 1,435 breast, 1,511 colorectal and 1,184 prostate cancer-specific deaths (and 7,106 breast, 7,291 colorectal and 5,849 prostate cancer controls). There was no increase in cancer-specific mortality in patients using ARBs after diagnosis of breast (adjusted odds ratio (OR) = 1.06 95% confidence interval (CI) 0.84, 1.35), colorectal (adjusted OR = 0.82 95% CI 0.64, 1.07) or prostate cancer (adjusted OR = 0.79 95% CI 0.61, 1.03). There was also no evidence of increases in cancer-specific mortality with ACEI use for breast (adjusted OR = 1.06 95% CI 0.89, 1.27), colorectal (adjusted OR = 0.78 95% CI 0.66, 0.92) or prostate cancer (adjusted OR = 0.78 95% CI 0.66, 0.92).

Conclusions: Overall, we found no evidence of increased risks of cancer-specific mortality in breast, colorectal or prostate cancer patients who used ACEI or ARBs after diagnosis. These results provide some reassurance that these medications are safe in patients diagnosed with these cancers.

Keywords: Colorectal cancer; Breast cancer; Prostate cancer; Mortality; Angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers

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We introduce a tool for the quantitative characterization of the departure from Markovianity of a given dynamical process. Our tool can be applied to a generic N-level system and extended straightforwardly to Gaussian continuous-variable systems. It is linked to the change of the volume of physical states that are dynamically accessible to a system and provides qualitative expectations in agreement with some of the analogous tools proposed so far. We illustrate its predictive power by tackling a few canonical examples.

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A maths support system for first-year engineering students with non-traditional entry qualifications has involved students working through practice questions structured to correspond with the maths module which runs in parallel. The setting was informal and there was significant one-to-one assistance. The non-traditional students (who are known to be less well prepared mathematically) were explicitly contacted in the first week of their university studies regarding the maths support and they generally seemed keen to participate. However, attendance at support classes was relatively low, on average, but varied greatly between students. Students appreciated the personal help and having time to ask questions. It seemed that having a small group of friends within the class promoted attendance – perhaps the mutual support or comfort that they all had similar mathematical difficulties was a factor. The classes helped develop confidence. Attendance was hindered by the class being timetabled too soon after the relevant lecture and students were reluctant to come with no work done beforehand. Although students at risk due to their mathematical unpreparedness can easily be identified at an early stage of their university career, encouraging them to partake of the maths support is an ongoing, major problem.

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This paper introduces hybrid address spaces as a fundamental design methodology for implementing scalable runtime systems on many-core architectures without hardware support for cache coherence. We use hybrid address spaces for an implementation of MapReduce, a programming model for large-scale data processing, and the implementation of a remote memory access (RMA) model. Both implementations are available on the Intel SCC and are portable to similar architectures. We present the design and implementation of HyMR, a MapReduce runtime system whereby different stages and the synchronization operations between them alternate between a distributed memory address space and a shared memory address space, to improve performance and scalability. We compare HyMR to a reference implementation and we find that HyMR improves performance by a factor of 1.71× over a set of representative MapReduce benchmarks. We also compare HyMR with Phoenix++, a state-of-art implementation for systems with hardware-managed cache coherence in terms of scalability and sustained to peak data processing bandwidth, where HyMR demon- strates improvements of a factor of 3.1× and 3.2× respectively. We further evaluate our hybrid remote memory access (HyRMA) programming model and assess its performance to be superior of that of message passing.

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Loss-of-mains protection is an important component of the protection systems of embedded generation. The role of loss-of-mains is to disconnect the embedded generator from the utility grid in the event that connection to utility dispatched generation is lost. This is necessary for a number of reasons, including the safety of personnel during fault restoration and the protection of plant against out-of-synchronism reclosure to the mains supply. The incumbent methods of loss-of-mains protection were designed when the installed capacity of embedded generation was low, and known problems with nuisance tripping of the devices were considered acceptable because of the insignificant consequence to system operation. With the dramatic increase in the installed capacity of embedded generation over the last decade, the limitations of current islanding detection methods are no longer acceptable. This study describes a new method of loss-of-mains protection based on phasor measurement unit (PMU) technology, specifically using a low cost PMU device of the authors' design which has been developed for distribution network applications. The proposed method addresses the limitations of the incumbent methods, providing a solution that is free of nuisance tripping and has a zero non-detection zone. This system has been tested experimentally and is shown to be practical, feasible and effective. Threshold settings for the new method are recommended based on data acquired from both the Great Britain and Ireland power systems.

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Non-Volatile Memory (NVM) technology holds promise to replace SRAM and DRAM at various levels of the memory hierarchy. The interest in NVM is motivated by the difficulty faced in scaling DRAM beyond 22 nm and, long-term, lower cost per bit. While offering higher density and negligible static power (leakage and refresh), NVM suffers increased latency and energy per memory access. This paper develops energy and performance models of memory systems and applies them to understand the energy-efficiency of replacing or complementing DRAM with NVM. Our analysis focusses on the application of NVM in main memory. We demonstrate that NVM such as STT-RAM and RRAM is energy-efficient for memory sizes commonly employed in servers and high-end workstations, but PCM is not. Furthermore, the model is well suited to quickly evaluate the impact of changes to the model parameters, which may be achieved through optimization of the memory architecture, and to determine the key parameters that impact system-level energy and performance.

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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.

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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.

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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.

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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.

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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.