Validation of a generalized transfer function to noninvasively derive central blood pressure during exercise

Exercise brachial blood pressure ( BP) predicts mortality, but because of wave reflection, central ( ascending aortic) pressure differs from brachial pressure. Exercise central BP may be clinically important, and a noninvasive means to derive it would be useful. The purpose of this study was to test the validity of a noninvasive technique to derive exercise central BP. Ascending aortic pressure waveforms were recorded using a micromanometer-tipped 6F Millar catheter in 30 patients (56 +/- 9 years; 21 men) undergoing diagnostic coronary angiography. Simultaneous recordings of the derived central pressure waveform were acquired using servocontrolled radial tonometry at rest and during supine cycling. Pulse wave analysis of the direct and derived pressure signals was performed offline (SphygmoCor 7.01). From rest to exercise, mean arterial pressure and heart rate were increased by 20 +/- 10 mm Hg and 15 +/- 7 bpm, respectively, and central systolic BP ranged from 77 to 229 mm Hg. There was good agreement and high correlation between invasive and noninvasive techniques with a mean difference (+/- SD) for central systolic BP of -1.3 +/- 3.2 mm Hg at rest and -4.7 +/- 3.3 mm Hg at peak exercise ( for both r=0.995; P < 0.001). Conversely, systolic BP was significantly higher peripherally than centrally at rest (155 +/- 33 versus 138 +/- 32mm Hg; mean difference, -16.3 +/- 9.4mm Hg) and during exercise (180 +/- 34 versus 164 +/- 33 mm Hg; mean difference, -15.5 +/- 10.4 mm Hg; for both P < 0.001). True myocardial afterload is not reliably estimated by peripheral systolic BP. Radial tonometry and pulse wave analysis is an accurate technique for the noninvasive determination of central BP at rest and during exercise.

Evaluation of resynchronization of contractile function following biventricular pacing using colour tissue Doppler imaging

Biventdcular (BV) pacing is evaluated as an alternative treatment for patients with dilated cardiomyppathy (both ischemic and non-ischemic) and end-stage heart failure. Colour tissue Doppler imaging using echocardiography allows noninvasive, quantitative assessment of radial motion in the long-axis with measurement of peak systolic velocity timing. The aim of the present study was to evaluate quantitatively, the systolic performance of the left ventricle and the resynchrenization of contraction (before vs after implantation). Patients and methods: 25 patients with dilated cardiomyopathy (11 ischemic), NYHA class III or IV, QRS duration >120 ms received a biventricular pacemaker. Routine 2D echo and colour tissue Doppler imaging were performed before and within 1 week following implantation. LVEF was assessed using the biplane Sampson's method.Peak systolic velocity (PSV) and time to PSV (TPV) were assessed in 4 regions (basal anterior, inferior, lateral and septal). By averaging the TPV from all 4 regions, a synchronization index was dedved from these measurements. Reaults: LVEF improved by 9±9% following pacing; 17 patients improved LVEF 5% or more. The change in PSV in the septal and lateral regions related significantly to the change in LVEF (r=0.74, r=0.62).The change in synchronization index before vs after pacing (as a measurement of REsynchronization) was related to the change in LVEF (y=120x+5.6, r=0.79, P

Radial artery pulse upstroke is not a good marker of left ventricular dysfunction: A comparison of radial tonometry, angiographic and echocardiographic measures of dP/dt

The first derivative of pressure over time (dP/dt) is a marker of left ventricular (LV) systolic function that can be assessed during cardiac catheterization and echocardiography. Radial artery dP/dt (Radial-dP/dt) has been proposed as a possible marker of LV systolic function (Nichols & O’Rourke, McDonald’s Blood Flow in Arteries) and we sought to test this hypothesis. Methods:We compared simultaneously recorded RadialdP/ dt (by high-fidelity tonometry) with LV-dP/dt (by highfidelity catheter and echocardiography parameters analogous to LV-dP/dt) in patients without aortic valve disease. In study 1, beat to beat Radial-dP/dt and LV-dP/dt were recorded at rest and during supine exercise in 12 males (aged 61±12 years) undergoing cardiac catheterization. In study 2, 2D-echocardiography and Radial-dP/dt were recorded in 59 patients (43 men; aged 64±10 years) at baseline and peak dobutamine-induced stress. Three measures at the basal septum were taken as being analogous to LV-dP/dt: (1) peak systolic strain rate, (2) strain rate (SR-dP/dt), and (3) tissue velocity during isovolumic contraction. Results: Study 1; there was a significant difference between resting LV-dP/dt (1461±383 mmHg/s) and Radial-dP/dt (1182±319 mmHg/s; P < 0.001), and a poor, but statistically significant, correlation between the variables (R2 = 0.006; P < 0.001) due to the high number of data points compared (n = 681). Similar results were observed during exercise. Study 2; there was a moderate association between baseline Radial-dP/dt and SRdP/ dt (R2 =−0.17; P < 0.01), but no significant relationship between Radial-dP/dt and all other echocardiographic measures analogous to LV-dP/dt at rest or peak stress (P > 0.05). Conclusion: The radial pressurewaveform is not a reliable marker of LV contractility.

Mixture density network training by computation in parameter space

Training Mixture Density Network (MDN) configurations within the NETLAB framework takes time due to the nature of the computation of the error function and the gradient of the error function. By optimising the computation of these functions, so that gradient information is computed in parameter space, training time is decreased by at least a factor of sixty for the example given. Decreased training time increases the spectrum of problems to which MDNs can be practically applied making the MDN framework an attractive method to the applied problem solver.

Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

Neural network-based wind vector retrieval from satellite scatterometer data

Obtaining wind vectors over the ocean is important for weather forecasting and ocean modelling. Several satellite systems used operationally by meteorological agencies utilise scatterometers to infer wind vectors over the oceans. In this paper we present the results of using novel neural network based techniques to estimate wind vectors from such data. The problem is partitioned into estimating wind speed and wind direction. Wind speed is modelled using a multi-layer perceptron (MLP) and a sum of squares error function. Wind direction is a periodic variable and a multi-valued function for a given set of inputs; a conventional MLP fails at this task, and so we model the full periodic probability density of direction conditioned on the satellite derived inputs using a Mixture Density Network (MDN) with periodic kernel functions. A committee of the resulting MDNs is shown to improve the results.

Structured neural network modelling of multi-valued functions for wind retrieval from scatterometer measurements

A conventional neural network approach to regression problems approximates the conditional mean of the output vector. For mappings which are multi-valued this approach breaks down, since the average of two solutions is not necessarily a valid solution. In this article mixture density networks, a principled method to model conditional probability density functions, are applied to retrieving Cartesian wind vector components from satellite scatterometer data. A hybrid mixture density network is implemented to incorporate prior knowledge of the predominantly bimodal function branches. An advantage of a fully probabilistic model is that more sophisticated and principled methods can be used to resolve ambiguities.

Neural network-based wind vector retrieval from satellite scatterometer data

Obtaining wind vectors over the ocean is important for weather forecasting and ocean modelling. Several satellite systems used operationally by meteorological agencies utilise scatterometers to infer wind vectors over the oceans. In this paper we present the results of using novel neural network based techniques to estimate wind vectors from such data. The problem is partitioned into estimating wind speed and wind direction. Wind speed is modelled using a multi-layer perceptron (MLP) and a sum of squares error function. Wind direction is a periodic variable and a multi-valued function for a given set of inputs; a conventional MLP fails at this task, and so we model the full periodic probability density of direction conditioned on the satellite derived inputs using a Mixture Density Network (MDN) with periodic kernel functions. A committee of the resulting MDNs is shown to improve the results.

The missing ingredient:inter-municipal cooperation and central-local relations in the UK

The thrust of the argument presented in this chapter is that inter-municipal cooperation (IMC) in the United Kingdom reflects local government's constitutional position and its exposure to the exigencies of Westminster (elected central government) and Whitehall (centre of the professional civil service that services central government). For the most part councils are without general powers of competence and are restricted in what they can do by Parliament. This suggests that the capacity for locally driven IMC is restricted and operates principally within a framework constructed by central government's policy objectives and legislation and the political expediencies of the governing political party. In practice, however, recent examples of IMC demonstrate that the practices are more complex than this initial analysis suggests. Central government may exert top-down pressures and impose hierarchical directives, but there are important countervailing forces. Constitutional changes in Scotland and Wales have shifted the locus of central- local relations away from Westminster and Whitehall. In England, the seeding of English government regional offices in 1994 has evolved into an important structural arrangement that encourages councils to work together. Within the local government community there is now widespread acknowledgement that to achieve the ambitious targets set by central government, councils are, by necessity, bound to cooperate and work with other agencies. In recent years, the fragmentation of public service delivery has affected the scope of IMC. Elected local government in the UK is now only one piece of a complex jigsaw of agencies that provides services to the public; whether it is with non-elected bodies, such as health authorities, public protection authorities (police and fire), voluntary nonprofit organisations or for-profit bodies, councils are expected to cooperate widely with agencies in their localities. Indeed, for projects such as regeneration and community renewal, councils may act as the coordinating agency but the success of such projects is measured by collaboration and partnership working (Davies 2002). To place these developments in context, IMC is an example of how, in spite of the fragmentation of traditional forms of government, councils work with other public service agencies and other councils through the medium of interagency partnerships, collaboration between organisations and a mixed economy of service providers. Such an analysis suggests that, following changes to the system of local government, contemporary forms of IMC are less dependent on vertical arrangements (top-down direction from central government) as they are replaced by horizontal modes (expansion of networks and partnership arrangements). Evidence suggests, however that central government continues to steer local authorities through the agency of inspectorates and regulatory bodies, and through policy initiatives, such as local strategic partnerships and local area agreements (Kelly 2006), thus questioning whether, in the case of UK local government, the shift from hierarchy to network and market solutions is less differentiated and transformation less complete than some literature suggests. Vertical or horizontal pressures may promote IMC, yet similar drivers may deter collaboration between local authorities. An example of negative vertical pressure was central government's change of the systems of local taxation during the 1980s. The new taxation regime replaced a tax on property with a tax on individual residency. Although the community charge lasted only a few years, it was a highpoint of the then Conservative government policy that encouraged councils to compete with each other on the basis of the level of local taxation. In practice, however, the complexity of local government funding in the UK rendered worthless any meaningful ambition of councils competing with each other, especially as central government granting to local authorities is predicated (however imperfectly) on at least notional equalisation between those areas with lower tax yields and the more prosperous locations. Horizontal pressures comprise factors such as planning decisions. Over the last quarter century, councils have competed on the granting of permission to out-of-town retail and leisure complexes, now recognised as detrimental to neighbouring authorities because economic forces prevail and local, independent shops are unable to compete with multiple companies. These examples illustrate tensions at the core of the UK polity of whether IMC is feasible when competition between local authorities heightened by local differences reduces opportunities for collaboration. An alternative perspective on IMC is to explore whether specific purposes or functions promote or restrict it. Whether in the principle areas of local government responsibilities relating to social welfare, development and maintenance of the local infrastructure or environmental matters, there are examples of IMC. But opportunities have diminished considerably as councils lost responsibility for services provision as a result of privatisation and transfer of powers to new government agencies or to central government. Over the last twenty years councils have lost their role in the provision of further-or higher-education, public transport and water/sewage. Councils have commissioning power but only a limited presence in providing housing needs, social care and waste management. In other words, as a result of central government policy, there are, in practice, currently far fewer opportunities for councils to cooperate. Since 1997, the New Labour government has promoted IMC through vertical drivers and the development; the operation of these policy initiatives is discussed following the framework of the editors. Current examples of IMC are notable for being driven by higher tiers of government, working with subordinate authorities in principal-agent relations. Collaboration between local authorities and intra-interand cross-sectoral partnerships are initiated by central government. In other words, IMC is shaped by hierarchical drivers from higher levels of government but, in practice, is locally varied and determined less by formula than by necessity and function. © 2007 Springer.

Malmquist indexes using a geometric distance function (GDF)

Traditional approaches to calculate total factor productivity change through Malmquist indexes rely on distance functions. In this paper we show that the use of distance functions as a means to calculate total factor productivity change may introduce some bias in the analysis, and therefore we propose a procedure that calculates total factor productivity change through observed values only. Our total factor productivity change is then decomposed into efficiency change, technological change, and a residual effect. This decomposition makes use of a non-oriented measure in order to avoid problems associated with the traditional use of radial oriented measures, especially when variable returns to scale technologies are to be compared.

Malmquist indexes using a geometric distance function (GDF):application to a sample of Portuguese bank branches

Traditional approaches to calculate total factor productivity (TFP) change through Malmquist indexes rely on distance functions. In this paper we show that the use of distance functions as a means to calculate TFP change may introduce some bias in the analysis, and therefore we propose a procedure that calculates TFP change through observed values only. Our total TFP change is then decomposed into efficiency change, technological change, and a residual effect. This decomposition makes use of a non-oriented measure in order to avoid problems associated with the traditional use of radial oriented measures, especially when variable returns to scale technologies are to be compared. The proposed approach is applied in this paper to a sample of Portuguese bank branches.

Robust automatic mapping algorithms in a network monitoring scenario

Automatically generating maps of a measured variable of interest can be problematic. In this work we focus on the monitoring network context where observations are collected and reported by a network of sensors, and are then transformed into interpolated maps for use in decision making. Using traditional geostatistical methods, estimating the covariance structure of data collected in an emergency situation can be difficult. Variogram determination, whether by method-of-moment estimators or by maximum likelihood, is very sensitive to extreme values. Even when a monitoring network is in a routine mode of operation, sensors can sporadically malfunction and report extreme values. If this extreme data destabilises the model, causing the covariance structure of the observed data to be incorrectly estimated, the generated maps will be of little value, and the uncertainty estimates in particular will be misleading. Marchant and Lark [2007] propose a REML estimator for the covariance, which is shown to work on small data sets with a manual selection of the damping parameter in the robust likelihood. We show how this can be extended to allow treatment of large data sets together with an automated approach to all parameter estimation. The projected process kriging framework of Ingram et al. [2007] is extended to allow the use of robust likelihood functions, including the two component Gaussian and the Huber function. We show how our algorithm is further refined to reduce the computational complexity while at the same time minimising any loss of information. To show the benefits of this method, we use data collected from radiation monitoring networks across Europe. We compare our results to those obtained from traditional kriging methodologies and include comparisons with Box-Cox transformations of the data. We discuss the issue of whether to treat or ignore extreme values, making the distinction between the robust methods which ignore outliers and transformation methods which treat them as part of the (transformed) process. Using a case study, based on an extreme radiological events over a large area, we show how radiation data collected from monitoring networks can be analysed automatically and then used to generate reliable maps to inform decision making. We show the limitations of the methods and discuss potential extensions to remedy these.

Distributed processing, reconfigurable processes and active network

The fast spread of the Internet and the increasing demands of the service are leading to radical changes in the structure and management of underlying telecommunications systems. Active networks (ANs) offer the ability to program the network on a per-router, per-user, or even per-packet basis, thus promise greater flexibility than current networks. To make this new network paradigm of active network being widely accepted, a lot of issues need to be solved. Management of the active network is one of the challenges. This thesis investigates an adaptive management solution based on genetic algorithm (GA). The solution uses a distributed GA inspired by bacterium on the active nodes within an active network, to provide adaptive management for the network, especially the service provision problems associated with future network. The thesis also reviews the concepts, theories and technologies associated with the management solution. By exploring the implementation of these active nodes in hardware, this thesis demonstrates the possibility of implementing a GA based adaptive management in the real network that being used today. The concurrent programming language, Handel-C, is used for the description of the design system and a re-configurable computer platform based on a FPGA process element is used for the hardware implementation. The experiment results demonstrate both the availability of the hardware implementation and the efficiency of the proposed management solution.

A three dimensional surface measurement and reconstruction system for respiratory function analysis

Respiration is a complex activity. If the relationship between all neurological and skeletomuscular interactions was perfectly understood, an accurate dynamic model of the respiratory system could be developed and the interaction between different inputs and outputs could be investigated in a straightforward fashion. Unfortunately, this is not the case and does not appear to be viable at this time. In addition, the provision of appropriate sensor signals for such a model would be a considerable invasive task. Useful quantitative information with respect to respiratory performance can be gained from non-invasive monitoring of chest and abdomen motion. Currently available devices are not well suited in application for spirometric measurement for ambulatory monitoring. A sensor matrix measurement technique is investigated to identify suitable sensing elements with which to base an upper body surface measurement device that monitors respiration. This thesis is divided into two main areas of investigation; model based and geometrical based surface plethysmography. In the first instance, chapter 2 deals with an array of tactile sensors that are used as progression of existing and previously investigated volumetric measurement schemes based on models of respiration. Chapter 3 details a non-model based geometrical approach to surface (and hence volumetric) profile measurement. Later sections of the thesis concentrate upon the development of a functioning prototype sensor array. To broaden the application area the study has been conducted as it would be fore a generically configured sensor array. In experimental form the system performance on group estimation compares favourably with existing system on volumetric performance. In addition provides continuous transient measurement of respiratory motion within an acceptable accuracy using approximately 20 sensing elements. Because of the potential size and complexity of the system it is possible to deploy it as a fully mobile ambulatory monitoring device, which may be used outside of the laboratory. It provides a means by which to isolate coupled physiological functions and thus allows individual contributions to be analysed separately. Thus facilitating greater understanding of respiratory physiology and diagnostic capabilities. The outcome of the study is the basis for a three-dimensional surface contour sensing system that is suitable for respiratory function monitoring and has the prospect with future development to be incorporated into a garment based clinical tool.