Effects of tidal volume and positive end-expiratory pressure during resuscitation of very premature lambs

Background: Guidelines recommend neonatal resuscitation without controlling tidal volume or positive end-expiratory pressure (PEEP). However, these may improve gas exchange, lung volume and outcome. Aim: To investigate resuscitation of very premature lambs with a Laerdal bag without PEEP versus volume guarantee ventilation with PEEP. Methods: Anaesthetized lambs (n = 20) delivered at 125 d gestation were randomized to three groups receiving 15 min resuscitation: (1) Laerdal bag and no PEEP; (2) ventilation with a tidal volume of 5 ml/kg and 8 cm H2O PEEP; (3) ventilation with 10 ml/kg and 8 cm H2O PEEP. They were then all ventilated for 2 h with tidal volumes of 5 or 10 ml/kg, and 8 cm H2O PEEP. Ventilation parameters and blood gases were recorded. Results: Different tidal volumes affected PaCO2 within minutes, with 10 ml/kg causing severe hypocarbia. PEEP had little effect on PaCO2. Oxygenation improved significantly with PEEP of 8 cm H2O, irrespective of tidal volume. Conclusion: Very premature lambs can be resuscitated effectively using volume-guarantee ventilation and PEEP. Tidal volumes affected PaCO2 within minutes but had little effect on oxygenation. PEEP halved the oxygen requirement compared with no PEEP. Resuscitating premature babies with controlled tidal volumes and PEEP might improve their outcome.

A two-dimensional fuzzy random model of soil pore structure

A new conceptual model for soil pore-solid structure is formalized. Soil pore-solid structure is proposed to comprise spatially abutting elements each with a value which is its membership to the fuzzy set ''pore,'' termed porosity. These values have a range between zero (all solid) and unity (all pore). Images are used to represent structures in which the elements are pixels and the value of each is a porosity. Two-dimensional random fields are generated by allocating each pixel a porosity by independently sampling a statistical distribution. These random fields are reorganized into other pore-solid structural types by selecting parent points which have a specified local region of influence. Pixels of larger or smaller porosity are aggregated about the parent points and within the region of interest by controlled swapping of pixels in the image. This creates local regions of homogeneity within the random field. This is similar to the process known as simulated annealing. The resulting structures are characterized using one-and two-dimensional variograms and functions describing their connectivity. A variety of examples of structures created by the model is presented and compared. Extension to three dimensions presents no theoretical difficulties and is currently under development.

The end of the public sector debate

In the first of the special essays, John Quiggin revisits the debate over the appropriate size of the public sector and canvasses the issues associated with the distribution of government responsibilities within the Australian federation, with a sweeping perspective and surprising conclusions.

A fuzzy max-flow min-cut theorem

Interval-valued versions of the max-flow min-cut theorem and Karp-Edmonds algorithm are developed and provide robustness estimates for flows in networks in an imprecise or uncertain environment. These results are extended to networks with fuzzy capacities and flows. (C) 2001 Elsevier Science B.V. All rights reserved.

The effects of normalisation on the ability of business end-users to detect data anomalies: An experimental evaluation

With the proliferation of relational database programs for PC's and other platforms, many business end-users are creating, maintaining, and querying their own databases. More importantly, business end-users use the output of these queries as the basis for operational, tactical, and strategic decisions. Inaccurate data reduce the expected quality of these decisions. Implementing various input validation controls, including higher levels of normalisation, can reduce the number of data anomalies entering the databases. Even in well-maintained databases, however, data anomalies will still accumulate. To improve the quality of data, databases can be queried periodically to locate and correct anomalies. This paper reports the results of two experiments that investigated the effects of different data structures on business end-users' abilities to detect data anomalies in a relational database. The results demonstrate that both unnormalised and higher levels of normalisation lower the effectiveness and efficiency of queries relative to the first normal form. First normal form databases appear to provide the most effective and efficient data structure for business end-users formulating queries to detect data anomalies.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.