Habitat complexity, spatial interference, and "minimum risk distribution": a framework for population stability

In the past century, the debate over whether or not density-dependent factors regulate populations has generally focused on changes in mean population density, ignoring the spatial variance around the mean as unimportant noise. In an attempt to provide a different framework for understanding population dynamics based on individual fitness, this paper discusses the crucial role of spatial variability itself on the stability of insect populations. The advantages of this method are the following: (1) it is founded on evolutionary principles rather than post hoc assumptions; (2) it erects hypotheses that can be tested; and (3) it links disparate ecological schools, including spatial dynamics, behavioral ecology, preference-performance, and plant apparency into an overall framework. At the core of this framework, habitat complexity governs insect spatial variance. which in turn determines population stability. First, the minimum risk distribution (MRD) is defined as the spatial distribution of individuals that results in the minimum number of premature deaths in a population given the distribution of mortality risk in the habitat (and, therefore, leading to maximized population growth). The greater the divergence of actual spatial patterns of individuals from the MRD, the greater the reduction of population growth and size from high, unstable levels. Then, based on extensive data from 29 populations of the processionary caterpillar, Ochrogaster lunifer, four steps are used to test the effect of habitat interference on population growth rates. (1) The costs (increasing the risk of scramble competition) and benefits (decreasing the risk of inverse density-dependent predation) of egg and larval aggregation are quantified. (2) These costs and benefits, along with the distribution of resources, are used to construct the MRD for each habitat. (3) The MRD is used as a benchmark against which the actual spatial pattern of individuals is compared. The degree of divergence of the actual spatial pattern from the MRD is quantified for each of the 29 habitats. (4) Finally, indices of habitat complexity are used to provide highly accurate predictions of spatial divergence from the MRD, showing that habitat interference reduces population growth rates from high, unstable levels. The reason for the divergence appears to be that high levels of background vegetation (vegetation other than host plants) interfere with female host-searching behavior. This leads to a spatial distribution of egg batches with high mortality risk, and therefore lower population growth. Knowledge of the MRD in other species should be a highly effective means of predicting trends in population dynamics. Species with high divergence between their actual spatial distribution and their MRD may display relatively stable dynamics at low population levels. In contrast, species with low divergence should experience high levels of intragenerational population growth leading to frequent habitat-wide outbreaks and unstable dynamics in the long term. Six hypotheses, erected under the framework of spatial interference, are discussed, and future tests are suggested.

The application of statistical process control charts to the detection and monitoring of hospital-acquired infections

The monitoring of infection control indicators including hospital-acquired infections is an established part of quality maintenance programmes in many health-care facilities. However, surveillance data use can be frustrated by the infrequent nature of many infections. Traditional methods of analysis often provide delayed identification of increasing infection occurrence, placing patients at preventable risk. The application of Shewhart, Cumulative Sum (CUSUM) and Exponentially Weighted Moving Average (EWMA) statistical process control charts to the monitoring of indicator infections allows continuous real-time assessment. The Shewhart chart will detect large changes, while CUSUM and EWMA methods are more suited to recognition of small to moderate sustained change. When used together, Shewhart and EWMA methods are ideal for monitoring bacteraemia and multiresistant organism rates. Shewhart and CUSUM charts are suitable for surgical infection surveillance.

Monitoring tissue oxygenation during resuscitation of major burns

BACKGROUND: Because subcutaneous and splanchnic oxygenation indices are sensitive indicators of evolving hemorrhagic shock and adequacy of resuscitation, we postulated that these indices might have an equivalent role in the monitoring of severely burned patients. This observational study was undertaken to examine changes in tissue oxygenation indices during burn resuscitation. METHODS: Seven patients with major burns (54 +/- 21% total body surface area) were studied during the first 36 hours of fluid resuscitation. Silastic tubing was placed in the subcutaneous tissue just beneath both normal skin and deep partial thickness burn. Fiberoptic sensors inserted into the tubing measured subcutaneous oxygen and carbon dioxide tensions in the burnt skin (PO2scb and PCO2scb) and normal skin (PO2scn and PCO2scn) continuously. Gastric intramucosal pH (pHi) and the mucosal CO2 (PCO2m) gap were calculated using gastric tonometers. Mean arterial pressure, arterial pH, lactate, and pHi measurements were obtained for 36 hours. RESULTS: There were no significant differences in mean arterial pressure, arterial pH, or lactate concentrations throughout the study period, whereas indices of tissue oxygenation showed deterioration: pHi decreased from 7.2 +/- 0.1 to 6.7 +/- 0.3 (p = 0.06), the PCO2m gap increased from 12 +/- 17 to 108 +/- 123 mm Hg (p < 0.01), PO2scn decreased from 112 +/- 18 to 50 +/- 11 mm Hg (p < 0.01), PO2scb decreased from 62 +/- 23 to 29 +/- 16 mm Hg (p < 0.01), PCO2scn increased from 42 +/- 4 to 46 +/- 10 mm Hg (p = 0.2), and PCO2scb increased from 42 +/- 10 to 52 +/- 5 mm Hg (p = 0.05). CONCLUSION: Despite adequate global indices of tissue perfusion after 36 hours of resuscitation, tissue monitoring indicated significant deterioration in the splanchnic circulation and in the normal and burnt skin.

Transient mesenteric ischaemic episodes tracked by continuous jejunal PCO2 monitoring during liquid feeding

Objective: To test the effect of liquid feeds on the responses to splanchnic ischaemia of a continuous rapid response PCO2 sensor inserted in the jejunum. Design: Prospective experimental animal study in a university research laboratory. Subjects: Adult male Wistar rats. Interventions: Adult male Wistar rats (285-425 g) were anaethetised with sodium pentobarbitone 60 mg/ kg i.p. and ventilated with 100 % oxygen and isoflurane via tracheostomy to a PaCO2 of 30-40 mmHg. A sensor was inserted into the mid-jejunum to record PCO2 every second. Distal aortic pressure was transduced. Four control rats received no feeds whilst in another four rats liquid feed was infused into the proximal jejunum at 3 ml/h. In each rat five episodes of splanchnic ischaemia were induced by 2-min elevations of an aortic sling to a mean distal aortic pressure of 30 mmHg. Measurements and main results: PCO2 elevations were always detectable, usually less than a minute from the onset of splanchnic ischaemia in both fed and unfed rats, with no difference in mean times to detectable response. In the fed rats there was a small but significant increase in the time to peak sensor response (196 +/- 16 vs. 180 +/- 12 s) and a trend towards an elevated mean baseline luminal PCO2 (67 +/- 9 vs. 55 +/- 4 mmHg). Conclusions: Brief episodes of splanchnic ischaemia were tracked successfully by a rapid response jejunal continuous PCO2 sensor during the infusion of a proprietary liquid feed preparation despite minor changes in PCO2 response characteristics and a possible elevation in baseline luminal PCO2.

On the relation between ownership structure and capital structure

The agency relationship between managers and shareholders has the potential to influence decision-making in the firm which in turn potentially impacts on firm characteristics such as value and leverage. Prior evidence has demonstrated an association between ownership structure and firm value. This paper extends the literature by examining a further link between ownership structure and capital structure. Using an agency framework, it is argued that the distribution of equity ownership among corporate managers and external blockholders may have a significant relation with leverage. The empirical results provide support for a positive relation between external blockholders and leverage, and non-linear relation between the level of managerial share ownership and leverage. The results also suggest that the relation between external block ownership and leverage varies across the level of managerial share ownership. These results are consistent with active monitoring by blockholders, and the effects of convergence-of-interests and management entrenchment.

Monitoring hotel performance

There is a pressing need to address productivity analysis in the hospitality industry if hotels are to exist as sustainable business entities in rapidly maturing markets. Unfortunately, productivity ratios commonly used by managers are narrowly defined. This study illustrates data envelopment analysis of cross-sectional data that benchmark hotels on observed best performances. Data envelopment analysis enables management to integrate unlike multiple inputs and outputs to make simultaneous comparisons. Findings from the cross-sectional data suggest that some of the hotels have the potential to reduce number of beds and number of part-time staff while increasing revenue.

Saving, productivity and national income: a discrete-time geometric framework

This paper proposes an alternative geometric framework for analysing the inter-relationship between domestic saving, productivity and income determination in discrete time. The framework provides a means of understanding how low saving economies like the United States sustained high growth rates in the 1990s whereas high saving Japan did not. It also illustrates how the causality between saving and economic activity runs both ways and that discrete changes in national output and income depend on both current and previous accumulation behaviour. The open economy analogue reveals how international capital movements can create external account imbalances that enhance income growth for both borrower and lender economies. (C) 2002 Elsevier Science B.V. All rights reserved.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

A framework for extreme-event control in wastewater treatment

In this paper an approach to extreme event control in wastewater treatment plant operation by use of automatic supervisory control is discussed. The framework presented is based on the fact that different operational conditions manifest themselves as clusters in a multivariate measurement space. These clusters are identified and linked to specific and corresponding events by use of principal component analysis and fuzzy c-means clustering. A reduced system model is assigned to each type of extreme event and used to calculate appropriate local controller set points. In earlier work we have shown that this approach is applicable to wastewater treatment control using look-up tables to determine current set points. In this work we focus on the automatic determination of appropriate set points by use of steady state and dynamic predictions. The performance of a relatively simple steady-state supervisory controller is compared with that of a model predictive supervisory controller. Also, a look-up table approach is included in the comparison, as it provides a simple and robust alternative to the steady-state and model predictive controllers, The methodology is illustrated in a simulation study.

Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques

The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.

A framework for table driven testing of Java classes

With the advent of object-oriented languages and the portability of Java, the development and use of class libraries has become widespread. Effective class reuse depends on class reliability which in turn depends on thorough testing. This paper describes a class testing approach based on modeling each test case with a tuple and then generating large numbers of tuples to thoroughly cover an input space with many interesting combinations of values. The testing approach is supported by the Roast framework for the testing of Java classes. Roast provides automated tuple generation based on boundary values, unit operations that support driver standardization, and test case templates used for code generation. Roast produces thorough, compact test drivers with low development and maintenance cost. The framework and tool support are illustrated on a number of non-trivial classes, including a graphical user interface policy manager. Quantitative results are presented to substantiate the practicality and effectiveness of the approach. Copyright (C) 2002 John Wiley Sons, Ltd.