Effect of self-monitoring and national culture on follower perceptions of personal charisma and charismatic message

In this paper, a theory of charismatic relationships is examined with reference to the follower's personal characteristics. It is argued that a leader's charismatic message and personal charisma occupy different roles for individuals who vary in national culture and level of self-monitoring. In an empirical test of the theory, 387 undergraduates of Chinese and Australian cultural backgrounds completed self-monitoring and charismatic leadership instruments. High self-monitors placed more importance on personal charisma than the charismatic message. Chinese participants relied more than the Australians on the charismatic message, although this preference depended on self-monitoring orientation. These results indicate the influence of both individual-and cultural-level variables on leader-member relationships, and the need to consider these effects in future developments of a theory of charismatic leadership.

A proposal for developing a large patient population cohort for longterm safety monitoring in rheumatoid arthritis

This paper proposes the creation of an objectively acquired reference database to more accurately characterize the incidence and longterm risk of relatively infrequent, but serious, adverse events. Such a database would be maintained longitudinally to provide for ongoing comparison with new rheumatologic drug safety databases collecting the occurrences and treatments of rare events, We propose the establishment of product-specific registries to prospectively follow a cohort of patients with rheumatoid arthritis (RA) who receive newly approved therapies. In addition, a database is required of a much larger cohort of RA patients treated with multiple second line agents of sufficient size to enable case-controlled determinations of the relative incidence of rare but serious events in the treated (registry) versus the larger disease population, The number of patients necessary for agent-specific registries and a larger patient population adequate to supply a matched case-control cohort will depend upon estimates of the detectability of an increased incidence over background. We suggest a system to carry out this proposal that will involve an umbrella organization. responsible for establishment of this large patient cohort, envisioned to be drawn from around the world.

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.

Modelling the input-output behaviour of piezoelectric structural health monitoring systems for composite plates

This paper investigates the input-output characteristics of structural health monitoring systems for composite plates based on permanently attached piezoelectric transmitter and sensor elements. Using dynamic piezoelectricity theory and a multiple integral transform method to describe the propagating and scattered flexural waves an electro-mechanical model for simulating the voltage input-output transfer function for circular piezoelectric transmitters and sensors adhesively attached to an orthotropic composite plate is developed. The method enables the characterization of all three physical processes, i.e. wave generation, wave propagation and wave reception. The influence of transducer, plate and attached electrical circuit characteristics on the voltage output behaviour of the system is examined through numerical calculations, both in frequency and the time domain. The results show that the input-output behaviour of the system is not properly predicted by the transducers' properties alone. Coupling effects between the transducers and the tested structure have to be taken into account, and adding backing materials to the piezoelectric elements can significantly improve the sensitivity of the system. It is shown that in order to achieve maximum sensitivity, particular piezoelectric transmitters and sensors need to be designed according to the structure to be monitored and the specific frequency regime of interest.

Introduced mammals in Australian rangelands: Future threats and the role of monitoring programmes in management strategies

In the present paper, we have provided an initial assessment of the current and future threats to biodiversity posed by introduced mammals (predators and herbivores) inhabiting the Australian rangelands, exploring trends in populations and options for management. Notably, rabbits have declined in recent years in the wake of rabbit haemorrhagic disease, populations of feral camels have increased dramatically and foxes appear to have moved northwards, thereby threatening native fauna within an expanded range. Following on, we developed a framework for monitoring the impacts of introduced mammals in the Australian rangelands. In doing so, we considered the key issues that needed to be considered in designing a monitoring programme for this purpose and critically evaluated the role of monitoring in pest animal management. Finally we have provided a brief inventory of current best-practice methods of estimating the abundance of introduced mammal populations in the Australian rangelands with some comments on new approaches and their potential applications.

Multivariate monitoring of a biological wastewater treatment process: a case study at Melbourne Water's Western Treatment Plant

Biological wastewater treatment is a complex, multivariate process, in which a number of physical and biological processes occur simultaneously. In this study, principal component analysis (PCA) and parallel factor analysis (PARAFAC) were used to profile and characterise Lagoon 115E, a multistage biological lagoon treatment system at Melbourne Water's Western Treatment Plant (WTP) in Melbourne, Australia. In this study, the objective was to increase our understanding of the multivariate processes taking place in the lagoon. The data used in the study span a 7-year period during which samples were collected as often as weekly from the ponds of Lagoon 115E and subjected to analysis. The resulting database, involving 19 chemical and physical variables, was studied using the multivariate data analysis methods PCA and PARAFAC. With these methods, alterations in the state of the wastewater due to intrinsic and extrinsic factors could be discerned. The methods were effective in illustrating and visually representing the complex purification stages and cyclic changes occurring along the lagoon system. The two methods proved complementary, with each having its own beneficial features. (C) 2003 Elsevier B.V. All rights reserved.

Improving the efficiency of wildlife monitoring by estimating detectability: a case study of foxes (Vulpes vulpes) on the Eyre Peninsula, South Australia

Demonstrating the existence of trends in monitoring data is of increasing practical importance to conservation managers wishing to preserve threatened species or reduce the impact of pest species. However, the ability to do so can be compromised if the species in question has low detectability and the true occupancy level or abundance of the species is thus obscured. Zero-inflated models that explicitly model detectability improve the ability to make sound ecological inference in such situations. In this paper we apply an occupancy model including detectability to data from the initial stages of a fox-monitoring program on the Eyre Peninsula, South Australia. We find that detectability is extremely low (< 18%) and varies according to season and the presence or absence of roadside vegetation. We show that simple methods of using monitoring data to inform management, such as plotting the raw data or performing logistic regression, fail to accurately diagnose either the status of the fox population or its trajectory over time. We use the results of the detectability model to consider how future monitoring could be redesigned to achieve efficiency gains. A wide range of monitoring programs could benefit from similar analyses, as part of an active adaptive approach to improving monitoring and management.

A contour plot approach that uses data accumulated during routine monitoring to obtain insights into lagoon behaviour

Regular monitoring of wastewater characteristics is undertaken on most wastewater treatment plants. The data acquired during this process are usually filed and forgotten. However, systematic analysis of these data can provide useful insights into plant behaviour. Conventional graphical techniques are inadequate to give a good overall picture of how wastewater characteristics vary, with time and along the lagoon system. An approach based on the use of contour plots was devised that largely overcomes this problem. Superimposition of contour plots for different parameters can be used to gain a qualitative understanding of the nature and strength of relationships between the parameters. This is illustrated in an analysis of monitoring data for lagoon 115 East at the Western Treatment Plant, near Melbourne, Australia. In this illustrative analysis, relationships between ammonia removal rates and parameters such as chlorophyll a level and temperature are explored using a contour plot superimposition approach. It is concluded that this approach can help improve our understanding, not only of lagoon systems, but of other wastewater treatment systems as well.