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Compared with traditional models, semi-random epidemic network models may be more reasonable to describe the real dynamics of many epidemics. In this paper, we first investigate the optimal control problem (OCP) of semi-random epidemic networks. By using the Pontryagin’s minimum principle, we obtain the optimal control strategy aimed to minimize the total epidemic incidence and control cost. We then define a centrality index which can measure average control strength of the optimal control. Based on this index, the OCP is converted into a static OCP (SOCP), whose solution is utilized to design a nonidentical constant control (NCC). NCC is suboptimal as it is optimal on a subset of the whole control set, and is determined by only the network’s clustering coefficient and initial condition. We finally propose an effective targeted constant quarantine control by using this centrality index. The results uncover the relationship between the optimal control and the network’s topological structure, provide a convenient method to determine suboptimal control, and present a strategy for targeted constant control. This paper can help to design effective control strategies for more general epidemic networks in the real world. [ABSTRACT FROM AUTHOR]

A stochastic model predictive control scheme is developed within the context of planning water-level references for an automated channel. The references are provided as inputs to decentralized feedback controllers that regulate the capacity for gravity-fed supply of flow at points along the channel. An operational challenge is to comply with constraints on channel-flow and water-level transients in the automatic response to changes in the off-take flow load and water-level references. The proposed approach is to determine the reference inputs using a model of the channel dynamics that includes a forecast of off-take demand. Specifically, a structured probabilistic representation of the forecast is used to formualte a chance-constrained optimal control problem that is solved in a receding horizon fashion. A scenario-based approximation of this difficult optimal control problem is considered. The size of the approximating quadratic program scales with the prediction horizon and the number of water-level regulation points. But importantly, the size does not ultimately depend on the number of scenarios used to construct the approximation. Simulations and experimental results from an operational channel are presented to demonstrate the method. [ABSTRACT FROM AUTHOR]

Frasnian reef complexes along the northern margin of the Canning Basin in northwestern Australia evolved during rifting of the Fitzroy Trough. Geological investigations of the Frasnian Hull platform, which developed on an active tilted fault‐block, reveal significant lateral and vertical facies variations superimposed on prominent metre‐scale cyclicity. This study uses numerical analyses of facies and magnetic susceptibility data from three measured sections along the Hull platform to test whether a tectonic signal can be distinguished from eustatic and other signals. Geostatistical analysis of facies variations reveals an exponential distribution of thin (<3 m) facies, characteristic of stochastic depositional processes. Thick subtidal facies predominate in the Guppy Hills (GH) and southeastern Hull Range (SHR) sections near the hangingwall margin, and thick shallow‐subtidal to intertidal facies dominate the Horse Springs drillcore (HD 14) section near the footwall margin. Power and wavelet spectral analyses indicate a strong periodic component; Average Spectral Misfit and spectral optimisation methods confirm the presence of Milankovitch eccentricity signals and suggest the presence of obliquity and precession signals. However, the results also expose strong temporal and spatial variation providing evidence for tectonic control. Spectral analyses show strongest periodicity is recorded in short intervals that are not correlated across the platform and provide evidence of variations in sedimentation rate and hiatuses. Time series for the neighbouring GH and SHR sections show no overall statistical correlation, and Markov analysis indicates weakly ordered vertical facies transitions that do not correlate across the platform. Subtidal to intertidal facies data from HD 14 core suggest that at least 35% of the section is absent, almost obscuring the Milankovitch signal. The results indicate a complex set of controls on deposition on the Hull platform with local tectonic effects having produced spatio‐temporal moderation of the underlying eustatic signals and autogenic processes adding a localised stochastic response. [ABSTRACT FROM AUTHOR]

The novel coronavirus COVID-19 arrived on Australian shores around 25 January 2020. This paper presents a novel method of dynamically modeling and forecasting the COVID-19 pandemic in Australia with a high degree of accuracy and in a timely manner using limited data; a valuable resource that can be used to guide government decision-making on societal restrictions on a daily and/or weekly basis. The "partially-observable stochastic process" used in this study predicts not only the future actual values with extremely low error, but also the percentage of unobserved COVID-19 cases in the population. The model can further assist policy makers to assess the effectiveness of several possible alternative scenarios in their decision-making processes. [ABSTRACT FROM AUTHOR]

This paper points out that equating the rate of exceedance over threshold to the probability of exceedance in the generalized Pareto distribution, as is often applied in practice, leads to erroneous model parameter estimation, under- or overestimation of hazard, and impairs the duality between the generalized Pareto (GPD) and the generalized extreme-value (GEV) distributions. The problem stems from the fundamental difference in the domain of definition: the rate of exceedance ∈ 0 , ∞ and the probability of exceedance ∈ 0 , 1 . The erroneous parameter estimation is a result of practice in model parameter estimation that uses the concept of 'return period' (the inverse of exceedance probability) for both the GEV and the GPD. By using the concept of 'average recurrence interval' (the inverse of exceedance rate) of extremes in stochastic processes, we illustrate that the erroneous hazard estimation of the GPD is resolved. The use of average recurrence interval along with the duality allows the use of either the GEV or GPD for extreme hazard analysis, regardless of whether the data are collected via block maxima or peaks over a threshold. Some recommendations with regard to the practice of distribution parameter estimation are given. We demonstrate the duality of the two distributions and the impact of using average recurrence interval instead of return period by analysis of wind gust data collected by an automatic weather station at Woomera, South Australia, Australia. [ABSTRACT FROM AUTHOR]

The majority of catch per unit effort (cpue) standardizations use generalized linear models (GLMs) or generalized additive models (GAMs). We develop geostatistical models that model catch locations as continuous Gaussian random fields (GRFs) and apply them to standardizing cpue in Australia's Eastern Tuna and Billfish Fishery (ETBF). The results are compared with the traditional GLMs currently used in ETBF assessments as well as GAMs. Specifically, we compare seven models in three groups: two GLMs, two GAMs, and three GRF models. Within each group, one model treats spatial and temporal variables independently, while the other model(s) treats them together as an interaction term. The two spatio-temporal GRF models differ in treating the spatial–temporal interaction: either as a random process or as an autoregressive process. We simulate catch rate data for five pelagic species based on real fishery catch rates so that the simulated data reflect real fishery patterns while the "true" annual abundance levels are known. The results show that within each group, the model with a spatial–temporal interaction term significantly outperforms the other model treating spatial and temporal variables independently. For spatial–temporal models between the three groups, prediction accuracy tends to improve from GLM to GAM and to the GRF models. Overall, the spatio-temporal GRF autoregressive model reduces mean relative predictive error by 43.4% from the GLM, 33.9% from the GAM, and reduces mean absolute predictive error by 23.5% from the GLM and 3.3% from the GAM, respectively. The comparison suggests a promising direction for further developing the geostatistical models for the ETBF. [ABSTRACT FROM AUTHOR]

This paper formulates a control problem for systems that are affected by uncertain inputs and are vulnerable to risks as a chance-constrained optimization problem (CCP) with two chance-constraints (CCs). The first CC encompasses requirements of the normal operations of the system, whereas the second CC ensures the avoidance of risks associated with rare events. CCPs are in general difficult to solve, and this paper proposes a scenario-based optimization, testing, and improving algorithm to find approximate solutions to such problems within a stochastic model predictive control setting in a computationally cheap manner. The proposed approach is applied to a river control problem with flood avoidance, and the controller performed well in realistic simulations of the upper part of Murray River in Australia. [ABSTRACT FROM AUTHOR]

An ensemble of stochastic daily rainfall projections has been generated for 30 stations across south-eastern Australia using the downscaling nonhomogeneous hidden Markov model, which was driven by atmospheric predictors from four climate models for three IPCC emissions scenarios (A1B, A2, and B1) and for two periods (2046-2065 and 2081-2100). The results indicate that the annual rainfall is projected to decrease for both periods for all scenarios and climate models, with the exception of a few scenarios of no statistically significant changes. However, there is a seasonal difference: two downscaled GCMs consistently project a decline of summer rainfall, and two an increase. In contrast, all four downscaled GCMs show a decrease of winter rainfall. Because winter rainfall accounts for two-thirds of the annual rainfall and produces the majority of streamflow for this region, this decrease in winter rainfall would cause additional water availability concerns in the southern Murray-Darling basin, given that water shortage is already a critical problem in the region. In addition, the annual maximum daily rainfall is projected to intensify in the future, particularly by the end of the 21st century; the maximum length of consecutive dry days is projected to increase, and correspondingly, the maximum length of consecutive wet days is projected to decrease. These changes in daily sequencing, combined with fewer events of reduced amount, could lead to drier catchment soil profiles and further reduce runoff potential and, hence, also have streamflow and water availability implications. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The large-scale integration of wind power into electrical power systems is likely to require significant improvements to transmission infrastructure over coming years. Planning for these developments may involve modeling of power systems using estimates of the time-varying power output of proposed wind farms. Such estimates may be derived from wind measurements, although it is rarely the case that measurements are available simultaneously for all sites of interest. In the present work, a method is developed to produce synthetic time-series of wind power at several locations based on a measured time-series of wind speed from a reference site. The stochastic properties of the modeled time-series are shown to be comparable with those of measured data from south-eastern Australia. It is anticipated that with appropriate tuning for local conditions, the method could be applied in other geographical regions. [ABSTRACT FROM PUBLISHER]

In this article, we propose a new set of multivariate stochastic models that capture time-varying seasonality within the vector innovations structural time-series (VISTS) framework. These models encapsulate exponential smoothing methods in a multivariate setting. The models considered are the local level, local trend, and damped trend VISTS models with an additive multivariate seasonal component. We evaluate the forecasting accuracy of these models against the forecasting accuracy of univariate alternatives using international tourist arrivals from 11 source countries to Australia and New Zealand. In general, the newly proposed multivariate models improve on forecast accuracy over the univariate alternatives. [ABSTRACT FROM PUBLISHER]

Seabed sediment textural parameters such as mud, sand and gravel content can be useful surrogates for predicting patterns of benthic biodiversity. Multibeam sonar mapping can provide near-complete spatial coverage of high-resolution bathymetry and backscatter data that are useful in predicting sediment parameters. Multibeam acoustic data collected across a ∼1000 km2 area of the Carnarvon Shelf, Western Australia, were used in a predictive modelling approach to map eight seabed sediment parameters. Four machine learning models were used for the predictive modelling: boosted decision tree, random forest decision tree, support vector machine and generalised regression neural network. The results indicate overall satisfactory statistical performance, especially for %Mud, %Sand, Sorting, Skewness and Mean Grain Size. The study also demonstrates that predictive modelling using the combination of machine learning models has provided the ability to generate prediction uncertainty maps. However, the single models were shown to have overall better prediction performance than the combined models. Another important finding was that choosing an appropriate set of explanatory variables, through a manual feature selection process, was a critical step for optimising model performance. In addition, machine learning models were able to identify important explanatory variables, which are useful in identifying underlying environmental processes and checking predictions against the existing knowledge of the study area. The sediment prediction maps obtained in this study provide reliable coverage of key physical variables that will be incorporated into the analysis of covariance of physical and biological data for this area. [ABSTRACT FROM AUTHOR]

The article presents a study on the increased use of condoms and reducing rates of partner change in order to reduce syphilis transmission among gay men. The study uses an agent-stochastic model to examine syphilis transmission among gay men in Australia. Results show that simulations of interventions such as condom use has short-term reductions in rates of partner change, and states that maintained changes in the sexual behavior in a long-term, can mitigate syphilis epidemics.

Summary: Six methods of downscaling GCM simulations to multi-site daily precipitation were applied to a set of 30 rain gauges located within South-Eastern Australia. The methods were tested at reproducing a range of statistics important within hydrological studies including inter-annual variability and spatial coherency using both NCEP/NCAR reanalysis and GCM predictors, thus testing the validity of GCM downscaled predictions. The methods evaluated, all having found application in Australia previously, are: (1) the dynamical downscaling Conformal-Cubic Atmospheric Model (CCAM) of ; the historical data based (2) Scaling method applied by and (3) Analogue method of ; and three stochastic methods, (4) the GLIMCLIM (Generalised Linear Model for daily Climate time series) software package (), (5) the Non-homogeneous Hidden Markov Model (NHMM) of Charles et al. (1999), and (6) the modified Markov model–kernel probability density estimation (MMM–KDE) downscaling technique of . The results showed that the simple Scaling approach provided relatively robust results for a range of statistics when GCM forcing data was used, and was therefore recommended for regional water availability and planning studies (subject to certain limitations as mentioned in conclusion section). The stochastic methods better capture changes to a fuller range of rainfall statistics and are recommended for detailed catchment modelling studies. In particular, the stochastic methods show better results for daily extreme rainfall (e.g. flooding/low flow) as the simulations are not based purely on temporal/spatial rainfall patterns observed in the past, and a hybrid GLIMCLIM occurrence-KDE amounts model is recommended based on performance for individual statistics. For GCM downscaled simulations, biases in annual mean and standard deviation of ±5% and −30% were observed typically, and no single model performed well over all timescales/statistics, suggesting that the user beware of model limitations when applying downscaling methods for various purposes. A brief demonstration of predictor biases is presented, highlighting that biases observed in GCM predictors can cause poorer performance during GCM validation, and that investigation of these biases should inform choice of GCMs, GCM predictors, and the downscaling methods that use them. [Copyright &y& Elsevier]

Abstract: Both for mapping and for estimating spatial means of an environmental variable, the accuracy of the result will usually be increased by dispersing the sample locations so that they cover the study area as uniformly as possible. We developed a new R package for designing spatial coverage samples for mapping, and for random sampling from compact geographical strata for estimating spatial means. The mean squared shortest distance (MSSD) was chosen as objective function, which can be minimized by k-means clustering. Two k-means algorithms are described, one for unequal area and one for equal area partitioning. The R package is illustrated with three examples: (1) subsampling of square and circular sampling plots commonly used in surveys of soil, vegetation, forest, etc.; (2) sampling of agricultural fields for soil testing; and (3) infill sampling of climate stations for mainland Australia and Tasmania. The algorithms give satisfactory results within reasonable computing time. [Copyright &y& Elsevier]

Abstract: Synergies are reported for mixed-enterprise farming systems in a benchmarking group in the Wheat-Sheep Zone in New South Wales, Australia. A stochastic input distance function is estimated and a measure of synergies is calculated, based on the second cross partial derivative of output variables in the distance function. Evidence is presented of strong synergies from complementarity between sheep and beef enterprises, sheep and crop enterprises, and beef and crop enterprises. [Copyright &y& Elsevier]

Purpose - This paper aims to reflect on the sources of the technical inefficiency of health care foodservice operations, using a sample of Australian and American hospitals. Design/methodology/approach - The paper applies the stochastic frontier model to reflect on the technical inefficiency and its sources. The advantage of the model is that it allows the simultaneous parameters estimation of technical efficiency as well as the factors that explain variations in technical efficiency. A set of hypotheses are tested to ensure the applicability and suitability of the suggested model. Then the model parameters are estimated, discussed and checked against the theoretical requirements and the literature. Findings - Results show that all the variable coefficients are correctly signed and that the average technical efficiency is around 83 percent for Australia and 80 percent for the USA. Practical implications - The technical efficiency results, according to the introduced model, suggest that health care foodservice operations in both countries are not operating at a full efficient level. The results also reveal that factors such as manager's education, manager's experience, and size have a direct impact on reducing the level of technical inefficiency of these operations. Originality/value - This paper overcomes the limitations of the existing efficiency techniques in the area of health care foodservice and also provides policy implications by emphasizing on the sources of technical inefficiency of health care foodservice operations for Australia and USA. [ABSTRACT FROM AUTHOR]

Summary: The paper conceptualises new environmental derivatives, water options, which can be used as an important leverage to facilitate the growing Australian water market. A model of water option pricing has been developed. This model is based on the theory of stochastic processes with jumps. The developed model is justified by analysis of real price dynamics in water market in northern Victoria, Australia. The price of European call options is modelled as a Brownian motion and compound Poisson process. The numerical simulation for modelled water and option prices is obtained for a set of predefined jumps and hypothetical water price. Potential impacts of the introduction of water options on irrigators and the water market are discussed. [Copyright &y& Elsevier]

Abstract: Spatial variability in community structure of dictyoceratid sponges (class Demospongiae; order Dictyoceratida) was examined on coral reefs in Torres Strait, an archipelago of islands and reefs between northern Queensland, Australia, and Papua New Guinea. Dictyoceratid sponge abundances and environmental factors were recorded at four locations, separated by 50–220km. Each location was subdivided into 5–7 sites, each ⩾2km apart. At each site, four 50×2m belt transects were quantitatively surveyed, recording the dictyoceratid numbers, substrate type (rock, rubble and sand), water clarity, degree of reef slope and depth. Dictyoceratid abundance was similar among locations over large spatial scales, averaging 15.5 individuals per 100m2, but varied significantly among sites within particular locations (i.e. small scale heterogeneity). Twenty-three dictyoceratid species were recorded in Torres Strait, with approximately half (12/23) found in only one location. The canonical correspondence analysis determined that the measured environmental factors explained only 26% of the spatial variation. Cluster analysis revealed a complex dictyoceratid community structure with similarities among neighbouring sites and among sites separated by hundreds of kilometres. Conversely the abundance and composition of dictyoceratids could vary greatly between neighbouring sites 2km apart and on the same reef complex. The results of this study suggest that spatial variability of dictyoceratid sponges in Torres Strait is influenced by a combination of environmental, biological and stochastic processes. [Copyright &y& Elsevier]

As only a very limited number of earthquake strong ground motion records are available in southwest Western Australia (SWWA), it is difficult to derive a reliable and unbiased strong ground motion attenuation model based on these data. To overcome this, in this study a combined approach is used to simulate ground motions. First, the stochastic approach is used to simulate ground motion time histories at various epicentral distances from small earthquake events. Then, the Green's function method, with the stochastically simulated time histories as input, is used to generate large event ground motion time histories. Comparing the Fourier spectra of the simulated motions with the recorded motions of a ML6.2 event in Cadoux in June 1979 and a ML5.5 event in Meckering in January 1990, provides good evidence in support of this method. This approach is then used to simulate a series of ground motion time histories from earthquakes of varying magnitudes and distances. From the regression analyses of these simulated data, the attenuation relations of peak ground acceleration (PGA), peak ground velocity (PGV), and response spectrum of ground motions on rock site in SWWA are derived. [ABSTRACT FROM AUTHOR]

Abstract: This study describes the use of landscape transition analysis as a means for effective basin management. Land cover transitions from 1995 to 2002 were analyzed using a cross-tabulation matrix for an important economic zone in south-west Victoria, Australia. Specifically, the matrix was used to determine whether the transitions were random or systematic. Random landscape transitions occur when a land cover replaces other land covers in proportion to their availability. Systematic landscape transitions occur when there are deviations from random patterns, and land use types ‘target’ other land use types for replacement. The analysis was conducted with 11 land cover categories and showed that dryland pastures have been systematically losing area to dryland crops and blue gum (Eucalyptus globulus) plantations. Dryland crops have systematically expanded in the north-east of the catchment, an area where increasing in-stream salinization has occurred concurrently with this transition. The systematic expansion of the blue gum plantations has been predominantly in the south-west of the catchment and has the potential to reduce stream flows and groundwater recharge in an already water-stressed region, as blue gums use more water than the dryland pastures they are replacing. All other transitions were largely random. These findings have implications for land use planning in the study area for regional water balance and revegetation strategies. Landscape transition analysis is a cost-effective means of contributing to the management of water resources at a regional scale, and is highly recommended for future basin planning. [Copyright &y& Elsevier]

Summary: A robust model for disaggregation of daily rainfall data at a point within a large region to any fine timescale of choice is presented. Limited fine timescale data are required to calibrate only three parameters for the regional model, to establish monthly variation of simulation timescale lag-1 autocorrelations, and also to establish a scaling law between the simulation timescale and the 24-h aggregation levels. Site specific parameters are obtained using the 24-h statistics to disaggregate a long record of daily data by repetition and proportional adjusting techniques with capping. An Australia-wide data set has been used as a case study to illustrate the capability of the model. It has been demonstrated that the disaggregation model predicts very well the gross statistics (including extreme values) of rainfall time series down to 6-min timescale. The possibility of linking the disaggregation model to daily, or global circulation, models that can capture the inter-annual variability of the rainfall process for simulation beyond the number of years of record is being explored. [Copyright &y& Elsevier]

Summary: A stochastic modeling framework for multisite generation of daily rainfall is developed with an aim of representing both short and higher time scale dependence in the generated rainfall sequences. The framework simulates rainfall at individual locations using separate models for rainfall occurrences and rainfall amounts on the simulated wet days. The spatial correlations in the generated occurrences and amounts are induced using spatially correlated yet serially independent random numbers. The rainfall occurrence model is based on a modification of the transition probabilities of the traditional Markov model through an analytically derived factor that represents the influence of rainfall aggregated over long time periods in an attempt to incorporate low-frequency variability in simulations. The rainfall amounts on the wet days are generated using a nonparametric conditional simulation approach. The utility of the proposed method is illustrated by applying the model on a network of 30 raingauge stations around Sydney, Australia, and comparing a range of statistics describing daily and higher time scale distribution and dependence attributes. The analyses of the results show that the method adequately captures daily as well as aggregated higher time scale rainfall characteristics at individual locations including the spatial distribution of rainfall over the region. [Copyright &y& Elsevier]

This article is an economic analysis of reallocating River Murray Basin water from agriculture to the environment with and without the possibility of interregional water trade. Acquiring environmental flows as an equal percentage of water allocations from all irrigation regions in the Basin is estimated to reduce returns to irrigation. When the same volume of water is taken from selected low-value regions only, the net revenue reduction is less. In all scenarios considered, net revenue gains from freeing trade are estimated to outweigh the negative revenue effects of reallocating water for environmental flows. The model accounts for how stochastic weather affects market water demand, supply and requirements for environmental flows. Net irrigation revenue is estimated to be 75 million less than the baseline level for a scenario involving reallocating a constant volume of water for the environment in both wet and dry years. For a more realistic scenario involving more water for the environment in wet and less in dry years, estimated net revenue loss is reduced by 48 per cent to 39 million. Finally, the external salinity-related costs of water trading are estimated at around 1 million per annum, a quite modest amount compared to the direct irrigation benefits of trade. [ABSTRACT FROM AUTHOR]

Human life expectancy has risen in most developed countries over the last century, causing the observed demographic shifts. Babel, Bomsdorf and Schmidt (forthcoming) introduce a stochastic mortality model using panel data procedures which distinguishes between a common time effect and a common age effect of mortality evolvement. Using this mortality model, the present paper provides forecasts of future life expectancy for 17 countries divided into 12 regions: Australia, Alps, Bene, Canada, England and Wales, France, Germany, Italy, Japan, Spain, Scandinavia and the United States of America. We consider (traditional) period life expectancies as well as cohort life expectancies, the latter being a more realistic approach but less common. It turns out that a continuing increase of life expectancy is expected in all considered countries. Further, we show that the probabilistic uncertainty of forecast life expectancies is different if either period life expectancies or cohort life expectancies are considered and, moreover, the uncertainty increases substantially if the error of parameter estimation is included. [ABSTRACT FROM AUTHOR]

Australian unions have adopted new organizing methods to rebuild and develop their organizations. This represents a change in direction from the commitment to partnership and tripartite planning that characterized the Accord period under the Labor governments of the 1980s and 1990s to a new focus on capacity building. A serious decline in union density along with shifts in the labour process has led unions to focus on recruiting and organizing new members. The vitality involved is tempered by a hostile legal climate that supports workplace flexibility, casualization, fragmentation and low-wage work, while curtailing the rights of unions to recruit and organize. This paper explores the common heritage between the new organizing and theories of popular education, radical history and social movement experience. The paper suggests that contemporary efforts to regenerate unions as assertive organizations that rely on developing and educating new activists and leaders can benefit from drawing on emancipatory traditions of popular education, radical history and community organizing, and in so doing avoid an uncritical adoption of what might become simply a new set of organizing techniques. [ABSTRACT FROM AUTHOR]

Quantifying the potential spread and density of an invading organism enables decision-makers to determine the most appropriate response to incursions. We present two linked models that estimate the spread of Solenopsis invicta Buren (red imported fire ant) in Australia based on limited data gathered after its discovery in Brisbane in 2001. A stochastic cellular automaton determines spread within a location (100 km by 100 km) and this is coupled with a model that simulates human-mediated movement of S. invicta to new locations. In the absence of any control measures, the models predict that S. invicta could cover 763 000–4 066 000 km2 by the year 2035 and be found at 200 separate locations around Australia by 2017–2027, depending on the rate of spread. These estimated rates of expansion (assuming no control efforts were in place) are higher than those experienced in the USA in the 1940s during the early invasion phases in that country. Active control efforts and quarantine controls in the USA (including a concerted eradication attempt in the 1960s) may have slowed spread. Further, milder winters, the presence of the polygynous social form, increased trade and human mobility in Australia in 2000s compared with the USA in 1940s could contribute to faster range expansion. [ABSTRACT FROM AUTHOR]

Abstract: Several mill regions within the Australian sugar industry are currently exploring long-term scenarios to reduce costs in the harvesting and rail transport of sugarcane. These efficiencies can be achieved through extending the time window of harvesting, reducing the number of harvesters, and investing in new or upgraded infrastructures. As part of a series of integrated models to conduct the analysis, we developed a capacity planning model for transport to estimate the (1) number of locomotives and shifts required; (2) the number of bins required; and (3) the delays to harvesting operations resulting from harvesters waiting for bin deliveries. The model is based on the principles of stochastic simulation, rather than producing a transport schedule, which gives advantages of flexibility and ease of application. We applied the model in partnership with growing, harvesting and milling representatives at a sugar region in Australia for which one of the scenarios produced by the model was implemented by all harvesters within the region during 2003. The simulation model was also extended to optimise harvester start times, to explore further opportunities for reducing costs. [Copyright &y& Elsevier]

The effect of stochastic variability upon the wake downstream of a real headland is investigated. From observations taken at Bass Point, Australia, three sources of stochastic forcing are identified and quantified, these being variability in the wind stress, in the flow incident on the headland, and that generated in the flow by complex reef topography at the headland's tip. These sources of stochastic forcing are found to induce a significant degree of unsteadiness in a nonlinear numerical model of flow around Bass Point that, in the absence of stochastic forcing, simulates steady recirculating flow. The observed stochastic variability of the flow incident on the headland is found to be larger than is necessary to support unsteadiness in the simulated straining zone. The dynamics of the perturbation growth observed in the model are understood by applying the techniques of generalized stability theory to the associated tangent linear model (TLM). The eigenmodes of the TLM confirm that the system is asymptotically stable, but analysis reveals that these eigenmodes are nonorthogonal and hence that the dynamical system is nonnormal. It is found that the model's response to stochastic forcing is not controlled by the least damped eigenmodes of the TLM, but rather by the least damped of its most nonnormal modes. The pseudospectra of the system suggest that the nonnormal modes are excited and sustained by the process of pseudoresonance. The nonnormality of the system permits transient growth of disturbances, because this allows a linear sum of exponentially decaying nonorthogonal modes to grow for a finite period because of eigenmode interference. Only in the absence of forcing do the least damped modes dictate the character of the flow. It is concluded that the subcritical transition to unsteady flow observed in the model may occur in straining coastal ocean circulations in general because of the ubiquity of environmental noise. As a result, nondimensional... [ABSTRACT FROM AUTHOR]

Cash flow management is a significant issue in the management of a building or construction firm. This paper steps back from the well researched area of poor cash management and its relationship with failure, to focus on the funds which are generated through operations, and the positive benefits which can follow in a well managed organization. A stochastic model is developed which illustrates how an average of 16% of turnover can be available for reinvestment. This is sufficient to allow investment in non-liquid assets, provided that this is managed carefully and precautions are taken against a severe reduction in turnover. This level of funds is sufficient to encourage firms to enter the industry with the motivation of generating funds, rather than a desire to build. This has implications for large clients and for government when dealing with the industry. [ABSTRACT FROM AUTHOR]

This paper reports the results of an examination of the time series properties of a range of accounting numbers and ratios which may be associated with firm valuation. The work extends earlier research, which has concentrated on earnings or its derivatives, and which has found that earnings numbers follow a random walk or similar stochastic process. The tests reported in this paper suggested that, during the 25 year period studied, annual changes in a wide range of accounting variables also were, for the most part, random. Significant departures from randomness occurred only in variables where there were a priori reasons for believing that serial dependence would exist. [ABSTRACT FROM AUTHOR]

In this paper we examine the information on inflation contained in the term spread of the Australian term structure in a model in which we allow the expected real term spread to vary with time. Previously, Mishkin (1990) assumed a constant expected real term spread in a similar inflation forecasting model. We further extend the model by allowing the coefficient of the nominal yield spread also to vary with time. Results show that the model based on the time-varying expected real rate, estimated with the Kalman filter, is more suitable than the model based on the constant real rate. Also, the term spread lagged one period has more information on future inflation than the contemporaneous term. Finally, the forecasting power of a model with a randomly time-varying yield spread is inferior to the other versions examined. [ABSTRACT FROM AUTHOR]

Termite mounds are an important habitat for an enormous diversity of microorganisms. However, the microbial community assembly processes in termite mounds remain unresolved, which impeded our ability to predict the biological functions of these mound-associated microbiota under the global changes. Here we conducted a large-scale investigation in northern Australia to explore biogeographical patterns of microbial community in termite mounds and identify the role of deterministic and stochastic processes in microbial community assembly. Microbial communities in termite mounds exhibited a significant distance-decay pattern, and fungi had a stronger distance-decay relationship than bacteria. The neutral community model and normalized stochasticity ratio index (NST) revealed that the deterministic selection, rather than stochastic forces, predominated the microbial community assembly in termite mounds. Deterministic processes exhibited a significantly weaker impact on bacteria (NST = 45.23%) than on fungi (NST = 33.72%), likely due to the wider habitat niche breadth and higher potential migration rate of bacteria. Random forest model further demonstrated that mean annual temperature was the most important predictor of both bacterial and fungal profiles in termite mounds. These findings improved our understanding of spatial patterns and processes of microbiome in termite mounds, which is critical to decipher the role of termite mounds associated microbes in regulating ecosystem multifunctionality. • Termite mounds associated microbial communities exhibited a significant distance-decay pattern. • Deterministic selection predominated the microbial community assembly in termite mounds. • Mean annual temperature is the most important predictor of microbial profiles in termite mounds. • Deterministic processes exhibited a weaker impact on bacteria than fungi. [ABSTRACT FROM AUTHOR]

Presents a calendar of international conferences related to quantitative finance, scheduled from May to August 2002. Workshop on Interest Rate Models in Kaiserslautern, Germany; Bachelier Finance Society 2nd World Congress in Crete, Greece; Conference on Stochastic Processes and Their Applications in Australia.