The Multiple Facets of ETF Investing: A World-Wide Analysis

The global ETF industry provides more complicated investment vehicles than low-cost index trackers. Instead, we find that the real investments of ETFs that do not fully replicate their benchmarks may deviate from their benchmarks to leverage informational advantages (which leads to a surprising stock-selection ability), to benefit from the securities lending market, to support ETF-affiliated banks’ stock prices, and to help affiliated OEFs through cross-trading. These effects are more prevalent in ETFs domiciled in Europe. Market awareness of such additional risk is reflected in ETF outflows. These results have important normative implications for consumer protection and financial stability.

Analysis of Load Impact on Small-signal Stability based on Load Active Power Sensitivity

While load flow conditions vary with different loads, the small-signal stability of the entire system is closely related with to the locations, capacities and models of loads. In this paper, load impacts with different capacities and models on the small-signal stability are analysed. In the real large-scale power system case, the load sensitivity which denotes the sensitivity of the eigenvalue with respect to the load active power is introduced and applied to rank the loads. The loads with high sensitivity are also considered.

Analysis of Fixed-Speed Wind Farm Low-Frequency Power Pulsations using a Wavelet-Prony Method

The increasing penetration of wind generation on the Island of Ireland has been accompanied by close investigation of low-frequency periodic pulsations contained within the active power flow from different wind farms. A primary concern is excitation of existing low-frequency oscillation modes already present on the system, particularly the 0.75 Hz mode as a consequence of the interconnected Northern and Southern power system networks. Recently grid code requirements on the Northern Ireland power system have been updated stipulating that wind farms connected after 2005 must be able to control the magnitude of oscillations in the range of 0.25 - 1.75 Hz to within 1% of the wind farm's registered output. In order to determine whether wind farm low-frequency oscillations have a negative effect (excite other modes) or possibly a positive impact (damping of existing modes) on the power system, the oscillations at the point of connection must be measured and characterised. Using time - frequency methods, research presented in this paper has been conducted to extract signal features from measured low-frequency active power pulsations produced by wind farms to determine the effective composition of possible oscillatory modes which may have a detrimental effect on system dynamic stability. The paper proposes a combined wavelet-Prony method to extract modal components and determine damping factors. The method is exemplified using real data obtained from wind farm measurements.

Real-Time Face Recognition from Surveillance Video

This chapter describes an experimental system for the recognition of human faces from surveillance video. In surveillance applications, the system must be robust to changes in illumination, scale, pose and expression. The system must also be able to perform detection and recognition rapidly in real time. Our system detects faces using the Viola-Jones face detector, then extracts local features to build a shape-based feature vector. The feature vector is constructed from ratios of lengths and differences in tangents of angles, so as to be robust to changes in scale and rotations in-plane and out-of-plane. Consideration was given to improving the performance and accuracy of both the detection and recognition steps.

Nilotinib 300mg BID as frontline treatment of CML:Prospective analysis of the Xpert BCR-ABL Monitor system and significance of 3-month molecular response

Sixty patients with early chronic phase CML (ECPCML) received Nilotinib on a phase II study which included a comparison of the Xpert BCR-ABL Monitor™ PCR system with standardized (IS) BCR-ABL1 real-time quantitative PCR (RQ-PCR). 88% patients achieved MMR with 45% achieving MR4.5. At 3 months BCR-ABL1/ABL1 IS >1% and

Preliminary analysis of organic Rankine cycles to improve vehicle efficiency

This paper presents the background rationale and key findings for a model-based study of supercritical waste heat recovery organic Rankine cycles. The paper’s objective is to cover the necessary groundwork to facilitate the future operation of a thermodynamic organic Rankine cycle model under realistic thermodynamic boundary conditions for performance optimisation of organic Rankine cycles. This involves determining the type of power cycle for organic Rankine cycles, the circuit configuration and suitable boundary conditions. The study focuses on multiple heat sources from vehicles but the findings are generally applicable, with careful consideration, to any waste heat recovery system. This paper introduces waste heat recovery and discusses the general merits of organic fluids versus water and supercritical operation versus subcritical operation from a theoretical perspective and, where possible, from a practical perspective. The benefits of regeneration are investigated from an efficiency perspective for selected subcritical and supercritical conditions. A simulation model is described with an introduction to some general Rankine cycle boundary conditions. The paper describes the analysis of real hybrid vehicle data from several driving cycles and its manipulation to represent the thermal inertia for model heat input boundary conditions. Basic theory suggests that selecting the operating pressures and temperatures to maximise the Rankine cycle performance is relatively straightforward. However, it was found that this may not be the case for an organic Rankine cycle operating in a vehicle. When operating in a driving cycle, the available heat and its quality can vary with the power output and between heat sources. For example, the available coolant heat does not vary much with the load, whereas the quantity and quality of the exhaust heat varies considerably. The key objective for operation in the vehicle is optimum utilisation of the available heat by delivering the maximum work out. The fluid selection process and the presentation and analysis of the final results of the simulation work on organic Rankine cycles are the subjects of two future publications.

Detection of cardiac arrest using a simplified frequency analysis of the impedance cardiogram recorded from defibrillator pads

An algorithm based only on the impedance cardiogram (ICG) recorded through two defibrillation pads, using the strongest frequency component and amplitude, incorporated into a defibrillator could determine circulatory arrest and reduce delays in starting cardiopulmonary resuscitation (CPR). Frequency analysis of the ICG signal is carried out by integer filters on a sample by sample basis. They are simpler, lighter and more versatile when compared to the FFT. This alternative approach, although less accurate, is preferred due to the limited processing capacity of devices that could compromise real time usability of the FFT. These two techniques were compared across a data set comprising 13 cases of cardiac arrest and 6 normal controls. The best filters were refined on this training set and an algorithm for the detection of cardiac arrest was trained on a wider data set. The algorithm was finally tested on a validation set. The ICG was recorded in 132 cardiac arrest patients (53 training, 79 validation) and 97 controls (47 training, 50 validation): the diagnostic algorithm indicated cardiac arrest with a sensitivity of 81.1% (77.6-84.3) and specificity of 97.1% (96.7-97.4) for the validation set (95% confidence intervals). Automated defibrillators with integrated ICG analysis have the potential to improve emergency care by lay persons enabling more rapid and appropriate initiation of CPR and when combined with ECG analysis they could improve on the detection of cardiac arrest.

Principal Component Analysis of Wide Area Phasor Measurements for Islanding Detection – A Geometric View

This paper presents a new technique for the detectionof islanding conditions in electrical power systems. This problem isespecially prevalent in systems with significant penetrations of distributedrenewable generation. The proposed technique is based onthe application of principal component analysis (PCA) to data setsof wide-area frequency measurements, recorded by phasor measurementunits. The PCA approach was able to detect islandingaccurately and quickly when compared with conventional RoCoFtechniques, as well as with the frequency difference and change-ofangledifference methods recently proposed in the literature. Thereliability and accuracy of the proposed PCA approach is demonstratedby using a number of test cases, which consider islandingand nonislanding events. The test cases are based on real data,recorded from several phasor measurement units located in theU.K. power system.

Public management, Peace-building and Creating Change: Shifting the Lens of Analysis from the Macro to the Micro

Considerable time, research money and expertise has been spent exploring the complex reality of ethno nationalist conflict and the role that public management plays in supporting the transition from violent conflict to stability, order and prosperity (Esman 1999; Guelke and Milton-Edwards 2000; Brinkerhoff 2005; Brinkerhoff, Wetterberg et al. 2012; Rao 2014). However, there seems to be a gap in relation to the practical challenges of managing change within, through and beyond such conflict. This paper aims to begin the process of putting a framework around the real experience of public management in conflict and transition by shifting the lens of analysis from macros concerns about sequencing interventions (Rao 2014) and legitimate requirements of security, stability and service delivery (Brinkerhoff, Wetterberg et al. 2012) to a micro analysis of the attitudes, behaviours, challenges and compromises held and faced by those public servants on the front line of conflict management and conflict transformation processes. Using senior managers as the unit of analysis and Northern Ireland as an embryonic case study, this paper discusses the links between ethno nationalist societal conflict, public sector reform and manager behaviour. In doing so, it highlights some initial data from an early pilot study into the experiences of individuals in significant public service roles at various stages of the NI conflict / peace process and draws some tentative conclusions about the viability of a wider study.

Evolving to the optoelectronic mouse for phycotoxin analysis in shellfish

Despite ethical and technical concerns, the in vivo method, or more commonly referred to mouse bioassay (MBA), is employed globally as a reference method for phycotoxin analysis in shellfish. This is particularly the case for paralytic shellfish poisoning (PSP) and emerging toxin monitoring. A high-performance liquid chromatography method (HPLC-FLD) has been developed for PSP toxin analysis, but due to difficulties and limitations in the method, this procedure has not been fully implemented as a replacement. Detection of the diarrhetic shellfish poisoning (DSP) toxins has moved towards LC-mass spectrometry (MS) analysis, whereas the analysis of the amnesic shellfish poisoning (ASP) toxin domoic acid is performed by HPLC. Although alternative methods of detection to the MBA have been described, each procedure is specific for a particular toxin and its analogues, with each group of toxins requiring separate analysis utilising different extraction procedures and analytical equipment. In addition, consideration towards the detection of unregulated and emerging toxins on the replacement of the MBA must be given. The ideal scenario for the monitoring of phycotoxins in shellfish and seafood would be to evolve to multiple toxin detection on a single bioanalytical sensing platform, i.e. 'an artificial mouse'. Immunologically based techniques and in particular surface plasmon resonance technology have been shown as a highly promising bioanalytical tool offering rapid, real-time detection requiring minimal quantities of toxin standards. A Biacore Q and a prototype multiplex SPR biosensor have been evaluated for their ability to be fit for purpose for the simultaneous detection of key regulated phycotoxin groups and the emerging toxin palytoxin. Deemed more applicable due to the separate flow channels, the prototype performance for domoic acid, okadaic acid, saxitoxin, and palytoxin calibration curves in shellfish achieved detection limits (IC20) of 4,000, 36, 144 and 46 μg/kg of mussel, respectively. A one-step extraction procedure demonstrated recoveries greater than 80 % for all toxins. For validation of the method at the 95 % confidence limit, the decision limits (CCα) determined from an extracted matrix curve were calculated to be 450, 36 and 24 μg/kg, and the detection capability (CCβ) as a screening method is ≤10 mg/kg, ≤160 μg/kg and ≤400 μg/kg for domoic acid, okadaic acid and saxitoxin, respectively.

Analysis of voltage source converter-based high-voltage direct current under DC line-to-earth fault

DC line faults on high-voltage direct current (HVDC) systems utilising voltage source converters (VSCs) are a major issue for multi-terminal HVDC systems in which complete isolation of the faulted system is not a viable option. Of these faults, single line-to-earth faults are the most common fault scenario. To better understand the system under such faults, this study analyses the behaviour of HVDC systems based on both conventional two-level converter and multilevel modular converter technology, experiencing a permanent line-to-earth fault. Operation of the proposed system under two different earthing configurations of converter side AC transformer earthed with converter unearthed, and both converter and AC transformer unearthed, was analysed and simulated, with particular attention paid to the converter operation. It was observed that the development of potential earth loops within the system as a result of DC line-to-earth faults leads to substantial overcurrent and results in oscillations depending on the earthing configuration.

Accuracy of LightCycler SeptiFast for the detection and identification of pathogens in the blood of patients with suspected sepsis: a systematic review and meta-analysis

Purpose: There is an urgent need to develop diagnostic tests to improve the detection of pathogens causing life-threatening infection (sepsis). SeptiFast is a CE-marked multi-pathogen real-time PCR system capable of detecting DNA sequences of bacteria and fungi present in blood samples within a few hours. We report here a systematic review and meta-analysis of diagnostic accuracy studies of SeptiFast in the setting of suspected sepsis.

Methods: A comprehensive search strategy was developed to identify studies that compared SeptiFast with blood culture in suspected sepsis. Methodological quality was assessed using QUADAS. Heterogeneity of studies was investigated using a coupled forest plot of sensitivity and specificity and a scatter plot in receiver operator characteristic space. Bivariate model method was used to estimate summary sensitivity and specificity.

Results: From 41 phase III diagnostic accuracy studies, summary sensitivity and specificity for SeptiFast compared with blood culture were 0.68 (95 % CI 0.63–0.73) and 0.86 (95 % CI 0.84–0.89) respectively. Study quality was judged to be variable with important deficiencies overall in design and reporting that could impact on derived diagnostic accuracy metrics.

Conclusions: SeptiFast appears to have higher specificity than sensitivity, but deficiencies in study quality are likely to render this body of work unreliable. Based on the evidence presented here, it remains difficult to make firm recommendations about the likely clinical utility of SeptiFast in the setting of suspected sepsis.

Global Sensitivity Analysis for MAP Inference in Graphical Models

We study the sensitivity of a MAP configuration of a discrete probabilistic graphical model with respect to perturbations of its parameters. These perturbations are global, in the sense that simultaneous perturbations of all the parameters (or any chosen subset of them) are allowed. Our main contribution is an exact algorithm that can check whether the MAP configuration is robust with respect to given perturbations. Its complexity is essentially the same as that of obtaining the MAP configuration itself, so it can be promptly used with minimal effort. We use our algorithm to identify the largest global perturbation that does not induce a change in the MAP configuration, and we successfully apply this robustness measure in two practical scenarios: the prediction of facial action units with posed images and the classification of multiple real public data sets. A strong correlation between the proposed robustness measure and accuracy is verified in both scenarios.

Bayesian network data imputation with application to survival tree analysis

Retrospective clinical datasets are often characterized by a relatively small sample size and many missing data. In this case, a common way for handling the missingness consists in discarding from the analysis patients with missing covariates, further reducing the sample size. Alternatively, if the mechanism that generated the missing allows, incomplete data can be imputed on the basis of the observed data, avoiding the reduction of the sample size and allowing methods to deal with complete data later on. Moreover, methodologies for data imputation might depend on the particular purpose and might achieve better results by considering specific characteristics of the domain. The problem of missing data treatment is studied in the context of survival tree analysis for the estimation of a prognostic patient stratification. Survival tree methods usually address this problem by using surrogate splits, that is, splitting rules that use other variables yielding similar results to the original ones. Instead, our methodology consists in modeling the dependencies among the clinical variables with a Bayesian network, which is then used to perform data imputation, thus allowing the survival tree to be applied on the completed dataset. The Bayesian network is directly learned from the incomplete data using a structural expectation–maximization (EM) procedure in which the maximization step is performed with an exact anytime method, so that the only source of approximation is due to the EM formulation itself. On both simulated and real data, our proposed methodology usually outperformed several existing methods for data imputation and the imputation so obtained improved the stratification estimated by the survival tree (especially with respect to using surrogate splits).

Rapid detection of health-care-associated bloodstream infection in critical care using multipathogen real-time polymerase chain reaction technology: a diagnostic accuracy study and systematic review

Background: There is growing interest in the potential utility of real-time polymerase chain reaction (PCR) in diagnosing bloodstream infection by detecting pathogen deoxyribonucleic acid (DNA) in blood samples within a few hours. SeptiFast (Roche Diagnostics GmBH, Mannheim, Germany) is a multipathogen probe-based system targeting ribosomal DNA sequences of bacteria and fungi. It detects and identifies the commonest pathogens causing bloodstream infection. As background to this study, we report a systematic review of Phase III diagnostic accuracy studies of SeptiFast, which reveals uncertainty about its likely clinical utility based on widespread evidence of deficiencies in study design and reporting with a high risk of bias. 

Objective: Determine the accuracy of SeptiFast real-time PCR for the detection of health-care-associated bloodstream infection, against standard microbiological culture. 

Design: Prospective multicentre Phase III clinical diagnostic accuracy study using the standards for the reporting of diagnostic accuracy studies criteria. 

Setting: Critical care departments within NHS hospitals in the north-west of England. 

Participants: Adult patients requiring blood culture (BC) when developing new signs of systemic inflammation. 

Main outcome measures: SeptiFast real-time PCR results at species/genus level compared with microbiological culture in association with independent adjudication of infection. Metrics of diagnostic accuracy were derived including sensitivity, specificity, likelihood ratios and predictive values, with their 95% confidence intervals (CIs). Latent class analysis was used to explore the diagnostic performance of culture as a reference standard. 

Results: Of 1006 new patient episodes of systemic inflammation in 853 patients, 922 (92%) met the inclusion criteria and provided sufficient information for analysis. Index test assay failure occurred on 69 (7%) occasions. Adult patients had been exposed to a median of 8 days (interquartile range 4–16 days) of hospital care, had high levels of organ support activities and recent antibiotic exposure. SeptiFast real-time PCR, when compared with culture-proven bloodstream infection at species/genus level, had better specificity (85.8%, 95% CI 83.3% to 88.1%) than sensitivity (50%, 95% CI 39.1% to 60.8%). When compared with pooled diagnostic metrics derived from our systematic review, our clinical study revealed lower test accuracy of SeptiFast real-time PCR, mainly as a result of low diagnostic sensitivity. There was a low prevalence of BC-proven pathogens in these patients (9.2%, 95% CI 7.4% to 11.2%) such that the post-test probabilities of both a positive (26.3%, 95% CI 19.8% to 33.7%) and a negative SeptiFast test (5.6%, 95% CI 4.1% to 7.4%) indicate the potential limitations of this technology in the diagnosis of bloodstream infection. However, latent class analysis indicates that BC has a low sensitivity, questioning its relevance as a reference test in this setting. Using this analysis approach, the sensitivity of the SeptiFast test was low but also appeared significantly better than BC. Blood samples identified as positive by either culture or SeptiFast real-time PCR were associated with a high probability (> 95%) of infection, indicating higher diagnostic rule-in utility than was apparent using conventional analyses of diagnostic accuracy. 

Conclusion: SeptiFast real-time PCR on blood samples may have rapid rule-in utility for the diagnosis of health-care-associated bloodstream infection but the lack of sensitivity is a significant limiting factor. Innovations aimed at improved diagnostic sensitivity of real-time PCR in this setting are urgently required. Future work recommendations include technology developments to improve the efficiency of pathogen DNA extraction and the capacity to detect a much broader range of pathogens and drug resistance genes and the application of new statistical approaches able to more reliably assess test performance in situation where the reference standard (e.g. blood culture in the setting of high antimicrobial use) is prone to error.