Using urea dilution to standardise cellular and non-cellular components of pleural and bronchoalveolar lavage (BAL) fluids in the cat

A technique to standardise the analysis of cellular and non-cellular components in epithelial lining fluid (ELF) collected during saline lavage of pulmonary and pleural cavities was developed using the urea dilution method. Bronchoalveolar lavage (BAL) and pleural lavage (PL) fluids were collected from 12 clinically healthy cats. Total and differential cell counts in BAL fluid were within normal ranges for the cat, while cell Counts in PL fluid were assumed to be normal based on clinical health during examination, auscultation and lactate dehydrogenase (LDH) activities being comparable with other species. The major clinical implication of this study was that nucleated cell counts within feline ELF could not be predicted from analysis of lavage fluid which suggests that calculation of the proportion of ELF in lavage fluid by the urea dilution method may be necessary to avoid misdiagnosis of health or disease in pulmonary or pleural cavities. (C) 2005 ESFM and AAFP. Published by Elsevier Ltd. All rights reserved.

Do process modelling techniques get better? A comparative ontological analysis of BPMN

Current initiatives in the field of Business Process Management (BPM) strive for the development of a BPM standard notation by pushing the Business Process Modeling Notation (BPMN). However, such a proposed standard notation needs to be carefully examined. Ontological analysis is an established theoretical approach to evaluating modelling techniques. This paper reports on the outcomes of an ontological analysis of BPMN and explores identified issues by reporting on interviews conducted with BPMN users in Australia. Complementing this analysis we consolidate our findings with previous ontological analyses of process modelling notations to deliver a comprehensive assessment of BPMN.

Applying a Systems Approach to the Analysis of the Benefits of Conversion to Organic Production

Although the current level of organic production in industrialised countries amounts to little more than 1-2 percent, it is recognised that one of the major issues shaping agricultural output over the next several decades will be the demand for organic produce (Dixon et al. 2001). In Australia, the issues of healthy food and environmental concern contribute to increasing demand and market volumes for organic produce. However, in Indonesia, using more economical inputs for organic production is a supply-side factor driving organic production. For individual growers and processors, conversion from conventional to organic agriculture is often a challenging step, entailing a thorough revision of established practices and heightened market insecurity. This paper examines the potential for a systems approach to the analysis of the conversion process, to yield insights for household and community decisions. A framework for applying farming systems research to investigate the benefits of organic production in both Australia and Indonesia is discussed. The framework incorporates scope for farmer participation, crucial to the understanding of farming systems; analysis of production; and relationships to resources, technologies, markets, services, policies and institutions in their local cultural context. A systems approach offers the potential to internalise the external effects that may be constraining decisions to convert to organic production, and for the design of decision-making tools to assist households and the community. Systems models can guide policy design and serve as a mechanism for predicting the impact of changes to the policy and market environments. The increasing emphasis of farming systems research on community and environment in recent years is in keeping with the proposed application to organic production, processing and marketing issues. The approach will also facilitate the analysis of critical aspects of the Australian production, marketing and policy environment, and the investigation of these same features in an Indonesian context.

Comparison of BR and QR Eigenvalue Algorithms for Power System Small Signal Stability Analysis

The BR algorithm is a novel and efficient method to find all eigenvalues of upper Hessenberg matrices and has never been applied to eigenanalysis for power system small signal stability. This paper analyzes differences between the BR and the QR algorithms with performance comparison in terms of CPU time based on stopping criteria and storage requirement. The BR algorithm utilizes accelerating strategies to improve its performance when computing eigenvalues of narrowly banded, nearly tridiagonal upper Hessenberg matrices. These strategies significantly reduce the computation time at a reasonable level of precision. Compared with the QR algorithm, the BR algorithm requires fewer iteration steps and less storage space without depriving of appropriate precision in solving eigenvalue problems of large-scale power systems. Numerical examples demonstrate the efficiency of the BR algorithm in pursuing eigenanalysis tasks of 39-, 68-, 115-, 300-, and 600-bus systems. Experiment results suggest that the BR algorithm is a more efficient algorithm for large-scale power system small signal stability eigenanalysis.

A comparison of segmental and wrist-to-ankle methodologies of bioimpedance analysis

The common approach of bioelectrical impedance analysis to estimate body water uses a wrist-to-ankle methodology which, although not indicated by theory, has the advantage of ease of application particularly for clinical studies involving patients with debilitating diseases. A number of authors have suggested the use of a segmental protocol in which the impedances of the trunk and limbs are measured separately to provide a methodology more in keeping with basic theory. The segmental protocol hits not, however, been generally adopted, partly because of the increased complexity involved in its application, and partly because studies comparing the two methodologies have not clearly demonstrated a significant improvement from the segmental methodology. We have conducted a small pilot study involving ten subjects to investigate the efficacy of the two methodologies in a group of normal subjects. The study did not require the independent measure of body water, by for example isotope dilution, as the subjects were maintained in a state of constant hydration with only the distribution between limbs and trunk changing as a result of change in posture. The results demonstrate a significant difference between the two methodologies in predicting the expected constancy of body water in this study, with the segmental methodology indicating a mean percentage change in extracellular water of -2.2%; which was not significantly different from the expected null result, whereas the wrist-to-ankle methodology indicated a mean percentage change in extracellular water of -6.6%. This is significantly different from the null result, and from the value obtained from the segmental methodology (p = 0.006). Similar results were obtained using estimates of total body water from the two methodologies. (C) 1998 Elsevier Science Ltd. All rights reserved.

Preprocessing and time-frequency analysis of newborn EEG seizures

Neurological disease or dysfunction in newborn infants is often first manifested by seizures. Prolonged seizures can result in impaired neurodevelopment or even death. In adults, the clinical signs of seizures are well defined and easily recognized. In newborns, however, the clinical signs are subtle and may be absent or easily missed without constant close observation. This article describes the use of adaptive signal processing techniques for removing artifacts from newborn electroencephalogram (EEG) signals. Three adaptive algorithms have been designed in the context of EEG signals. This preprocessing is necessary before attempting a fine time-frequency analysis of EEG rhythmical activities, such as electrical seizures, corrupted by high amplitude signals. After an overview of newborn EEG signals, the authors describe the data acquisition set-up. They then introduce the basic physiological concepts related to normal and abnormal newborn EEGs and discuss the three adaptive algorithms for artifact removal. They also present time-frequency representations (TFRs) of seizure signals and discuss the estimation and modeling of the instantaneous frequency related to the main ridge of the TFR.

Analysis of the wind field and heat budget in an alpine lake basin during summertime fair weather conditions

Observational data collected in the Lake Tekapo hydro catchment of the Southern Alps in New Zealand are used to analyse the wind and temperature fields in the alpine lake basin during summertime fair weather conditions. Measurements from surface stations, pilot balloon and tethersonde soundings, Doppler sodar and an instrumented light aircraft provide evidence of multi-scale interacting wind systems, ranging from microscale slope winds to mesoscale coast-to-basin flows. Thermal forcing of the winds occurred due to differential heating as a consequence of orography and heterogeneous surface features, which is quantified by heat budget and pressure field analysis. The daytime vertical temperature structure was characterised by distinct layering. Features of particular interest are the formation of thermal internal boundary layers due to the lake-land discontinuity and the development of elevated mixed layers. The latter were generated by advective heating from the basin and valley sidewalls by slope winds and by a superimposed valley wind blowing from the basin over Lake Tekapo and up the tributary Godley Valley. Daytime heating in the basin and its tributary valleys caused the development of a strong horizontal temperature gradient between the basin atmosphere and that over the surrounding landscape, and hence the development of a mesoscale heat low over the basin. After noon, air from outside the basin started flowing over mountain saddles into the basin causing cooling in the lowest layers, whereas at ridge top height the horizontal air temperature gradient between inside and outside the basin continued to increase. In the early evening, a more massive intrusion of cold air caused rapid cooling and a transition to a rather uniform slightly stable stratification up to about 2000 m agl. The onset time of this rapid cooling varied about 1-2 h between observation sites and was probably triggered by the decay of up-slope winds inside the basin, which previously countered the intrusion of air over the surrounding ridges. The intrusion of air from outside the basin continued until about mid-night, when a northerly mountain wind from the Godley Valley became dominant. The results illustrate the extreme complexity that can be caused by the operation of thermal forcing processes at a wide range of spatial scales.

Functional-structural plant modelling using a combination of architectural analysis, L-systems and a canonical model of function

This paper presents a new method for producing a functional-structural plant model that simulates response to different growth conditions, yet does not require detailed knowledge of underlying physiology. The example used to present this method is the modelling of the mountain birch tree. This new functional-structural modelling approach is based on linking an L-system representation of the dynamic structure of the plant with a canonical mathematical model of plant function. Growth indicated by the canonical model is allocated to the structural model according to probabilistic growth rules, such as rules for the placement and length of new shoots, which were derived from an analysis of architectural data. The main advantage of the approach is that it is relatively simple compared to the prevalent process-based functional-structural plant models and does not require a detailed understanding of underlying physiological processes, yet it is able to capture important aspects of plant function and adaptability, unlike simple empirical models. This approach, combining canonical modelling, architectural analysis and L-systems, thus fills the important role of providing an intermediate level of abstraction between the two extremes of deeply mechanistic process-based modelling and purely empirical modelling. We also investigated the relative importance of various aspects of this integrated modelling approach by analysing the sensitivity of the standard birch model to a number of variations in its parameters, functions and algorithms. The results show that using light as the sole factor determining the structural location of new growth gives satisfactory results. Including the influence of additional regulating factors made little difference to global characteristics of the emergent architecture. Changing the form of the probability functions and using alternative methods for choosing the sites of new growth also had little effect. (c) 2004 Elsevier B.V. All rights reserved.

An analysis of relational complexity in an air traffic control conflict detection task

Theoretical analyses of air traffic complexity were carried out using the Method for the Analysis of Relational Complexity. Twenty-two air traffic controllers examined static air traffic displays and were required to detect and resolve conflicts. Objective measures of performance included conflict detection time and accuracy. Subjective perceptions of mental workload were assessed by a complexity-sorting task and subjective ratings of the difficulty of different aspects of the task. A metric quantifying the complexity of pair-wise relations among aircraft was able to account for a substantial portion of the variance in the perceived complexity and difficulty of conflict detection problems, as well as reaction time. Other variables that influenced performance included the mean minimum separation between aircraft pairs and the amount of time that aircraft spent in conflict.

Investigating the performance analysis of EASI algorithm and EKENS algorithm in nonlinear model

This paper investigates the performance of EASI algorithm and the proposed EKENS algorithm for linear and nonlinear mixtures. The proposed EKENS algorithm is based on the modified equivariant algorithm and kernel density estimation. Theory and characteristic of both the algorithms are discussed for blind source separation model. The separation structure of nonlinear mixtures is based on a nonlinear stage followed by a linear stage. Simulations with artificial and natural data demonstrate the feasibility and good performance of the proposed EKENS algorithm.