On modifications to the long-term survival mixture model in the presence of competing risks

A mixture model for long-term survivors has been adopted in various fields such as biostatistics and criminology where some individuals may never experience the type of failure under study. It is directly applicable in situations where the only information available from follow-up on individuals who will never experience this type of failure is in the form of censored observations. In this paper, we consider a modification to the model so that it still applies in the case where during the follow-up period it becomes known that an individual will never experience failure from the cause of interest. Unless a model allows for this additional information, a consistent survival analysis will not be obtained. A partial maximum likelihood (ML) approach is proposed that preserves the simplicity of the long-term survival mixture model and provides consistent estimators of the quantities of interest. Some simulation experiments are performed to assess the efficiency of the partial ML approach relative to the full ML approach for survival in the presence of competing risks.

The moderating role of task characteristics in determining responses to a stressful work simulation

Two experimental studies were conducted to examine whether the stress-buffering effects of behavioral control on work task responses varied as a function of procedural information. Study 1 manipulated low and high levels of task demands, behavioral control, and procedural information for 128 introductory psychology students completing an in-basket activity. ANOVA procedures revealed a significant three-way interaction among these variables in the prediction of subjective task performance and task satisfaction. It was found that procedural information buffered the negative effects of task demands on ratings of performance and satisfaction only under conditions of low behavioral control. This pattern of results suggests that procedural information may have a compensatory effect when the work environment is characterized by a combination of high task demands and low behavioral control. Study 2 (N = 256) utilized simple and complex versions of the in-basket activity to examine the extent to which the interactive relationship among task demands, behavioral control, and procedural information varied as a function of task complexity. There was further support for the stress-buffering role of procedural information on work task responses under conditions of low behavioral control. This effect was, however, only present when the in-basket activity was characterized by high task complexity, suggesting that the interactive relationship among these variables may depend on the type of tasks performed at work. Copyright (C) 1999 John Wiley & Sons, Ltd.

A model for adsorption of condensable vapors on nonporous materials

A new isotherm is proposed here for adsorption of condensable vapors and gases on nonporous materials having type II isotherms according to the Brunauer-Deming-Deming-Teller (BDDH) classification. The isotherm combines the recent molecular-continuum model in the multilayer region, with other widely used models for sub-monolayer coverage, some of which satisfy the requirement of a Henry's law asymptote. The model is successfully tested using isotherm data for nitrogen adsorption on nonporous silica, carbon and alumina, as well as benzene and hexane adsorption on nonporous carbon. Based on the data fits, out of several different alternative choices of model for the monolayer region, the Freundlich and the Unilan models are found to be the most successful when combined with the multilayer model to predict the whole isotherm. The hybrid model is consequently applicable over a wide pressure range. (C) 2000 Elsevier Science B.V. All rights reserved.

Monitoring growth in rapidly urbanizing areas using remotely sensed data

Urbanization and the ability to manage for a sustainable future present numerous challenges for geographers and planners in metropolitan regions. Remotely sensed data are inherently suited to provide information on urban land cover characteristics, and their change over time, at various spatial and temporal scales. Data models for establishing the range of urban land cover types and their biophysical composition (vegetation, soil, and impervious surfaces) are integrated to provide a hierarchical approach to classifying land cover within urban environments. These data also provide an essential component for current simulation models of urban growth patterns, as both calibration and validation data. The first stages of the approach have been applied to examine urban growth between 1988 and 1995 for a rapidly developing area in southeast Queensland, Australia. Landsat Thematic Mapper image data provided accurate (83% adjusted overall accuracy) classification of broad land cover types and their change over time. The combination of commonly available remotely sensed data, image processing methods, and emerging urban growth models highlights an important application for current and next generation moderate spatial resolution image data in studies of urban environments.

Anisotropic convection model for the earth's mantle

The paper presents a theory for modeling flow in anisotropic, viscous rock. This theory has originally been developed for the simulation of large deformation processes including the folding and kinking of multi-layered visco-elastic rock (Muhlhaus et al. [1,2]). The orientation of slip planes in the context of crystallographic slip is determined by the normal vector - the director - of these surfaces. The model is applied to simulate anisotropic mantle convection. We compare the evolution of flow patterns, Nusselt number and director orientations for isotropic and anisotropic rheologies. In the simulations we utilize two different finite element methodologies: The Lagrangian Integration Point Method Moresi et al [8] and an Eulerian formulation, which we implemented into the finite element based pde solver Fastflo (www.cmis.csiro.au/Fastflo/). The reason for utilizing two different finite element codes was firstly to study the influence of an anisotropic power law rheology which currently is not implemented into the Lagrangian Integration point scheme [8] and secondly to study the numerical performance of Eulerian (Fastflo)- and Lagrangian integration schemes [8]. It turned out that whereas in the Lagrangian method the Nusselt number vs time plot reached only a quasi steady state where the Nusselt number oscillates around a steady state value the Eulerian scheme reaches exact steady states and produces a high degree of alignment (director orientation locally orthogonal to velocity vector almost everywhere in the computational domain). In the simulations emergent anisotropy was strongest in terms of modulus contrast in the up and down-welling plumes. Mechanisms for anisotropic material behavior in the mantle dynamics context are discussed by Christensen [3]. The dominant mineral phases in the mantle generally do not exhibit strong elastic anisotropy but they still may be oriented by the convective flow. Thus viscous anisotropy (the main focus of this paper) may or may not correlate with elastic or seismic anisotropy.

A 2D numerical model for simulating the physics of fault systems

Simulations provide a powerful means to help gain the understanding of crustal fault system physics required to progress towards the goal of earthquake forecasting. Cellular Automata are efficient enough to probe system dynamics but their simplifications render interpretations questionable. In contrast, sophisticated elasto-dynamic models yield more convincing results but are too computationally demanding to explore phase space. To help bridge this gap, we develop a simple 2D elastodynamic model of parallel fault systems. The model is discretised onto a triangular lattice and faults are specified as split nodes along horizontal rows in the lattice. A simple numerical approach is presented for calculating the forces at medium and split nodes such that general nonlinear frictional constitutive relations can be modeled along faults. Single and multi-fault simulation examples are presented using a nonlinear frictional relation that is slip and slip-rate dependent in order to illustrate the model.

Numerical simulation of double-diffusion driven convective flow and rock alteration in three-dimensional fluid-saturated geological fault zones

Numerical methods are used to simulate the double-diffusion driven convective pore-fluid flow and rock alteration in three-dimensional fluid-saturated geological fault zones. The double diffusion is caused by a combination of both the positive upward temperature gradient and the positive downward salinity concentration gradient within a three-dimensional fluid-saturated geological fault zone, which is assumed to be more permeable than its surrounding rocks. In order to ensure the physical meaningfulness of the obtained numerical solutions, the numerical method used in this study is validated by a benchmark problem, for which the analytical solution to the critical Rayleigh number of the system is available. The theoretical value of the critical Rayleigh number of a three-dimensional fluid-saturated geological fault zone system can be used to judge whether or not the double-diffusion driven convective pore-fluid flow can take place within the system. After the possibility of triggering the double-diffusion driven convective pore-fluid flow is theoretically validated for the numerical model of a three-dimensional fluid-saturated geological fault zone system, the corresponding numerical solutions for the convective flow and temperature are directly coupled with a geochemical system. Through the numerical simulation of the coupled system between the convective fluid flow, heat transfer, mass transport and chemical reactions, we have investigated the effect of the double-diffusion driven convective pore-fluid flow on the rock alteration, which is the direct consequence of mineral redistribution due to its dissolution, transportation and precipitation, within the three-dimensional fluid-saturated geological fault zone system. (c) 2005 Elsevier B.V. All rights reserved.

Numerical simulation of dendrite growth during solidification

A comprehensive probabilistic model for simulating dendrite morphology and investigating dendritic growth kinetics during solidification has been developed, based on a modified Cellular Automaton (mCA) for microscopic modeling of nucleation, growth of crystals and solute diffusion. The mCA model numerically calculated solute redistribution both in the solid and liquid phases, the curvature of dendrite tips and the growth anisotropy. This modeling takes account of thermal, curvature and solute diffusion effects. Therefore, it can simulate microstructure formation both on the scale of the dendrite tip length. This model was then applied for simulating dendritic solidification of an Al-7%Si alloy. Both directional and equiaxed dendritic growth has been performed to investigate the growth anisotropy and cooling rate on dendrite morphology. Furthermore, the competitive growth and selection of dendritic crystals have also investigated.

Three-dimensional model for multi-component reactive transport with variable density groundwater flow

PHWAT is a new model that couples a geochemical reaction model (PHREEQC-2) with a density-dependent groundwater flow and solute transport model (SEAWAT) using the split-operator approach. PHWAT was developed to simulate multi-component reactive transport in variable density groundwater flow. Fluid density in PHWAT depends not on only the concentration of a single species as in SEAWAT, but also the concentrations of other dissolved chemicals that can be subject to reactive processes. Simulation results of PHWAT and PHREEQC-2 were compared in their predictions of effluent concentration from a column experiment. Both models produced identical results, showing that PHWAT has correctly coupled the sub-packages. PHWAT was then applied to the simulation of a tank experiment in which seawater intrusion was accompanied by cation exchange. The density dependence of the intrusion and the snow-plough effect in the breakthrough curves were reflected in the model simulations, which were in good agreement with the measured breakthrough data. Comparison simulations that, in turn, excluded density effects and reactions allowed us to quantify the marked effect of ignoring these processes. Next, we explored numerical issues involved in the practical application of PHWAT using the example of a dense plume flowing into a tank containing fresh water. It was shown that PHWAT could model physically unstable flow and that numerical instabilities were suppressed. Physical instability developed in the model in accordance with the increase of the modified Rayleigh number for density-dependent flow, in agreement with previous research. (c) 2004 Elsevier Ltd. All rights reserved.

Analysis of dynamic process models for structural insight and model reduction .1. Structural identification measures

An important consideration in the development of mathematical models for dynamic simulation, is the identification of the appropriate mathematical structure. By building models with an efficient structure which is devoid of redundancy, it is possible to create simple, accurate and functional models. This leads not only to efficient simulation, but to a deeper understanding of the important dynamic relationships within the process. In this paper, a method is proposed for systematic model development for startup and shutdown simulation which is based on the identification of the essential process structure. The key tool in this analysis is the method of nonlinear perturbations for structural identification and model reduction. Starting from a detailed mathematical process description both singular and regular structural perturbations are detected. These techniques are then used to give insight into the system structure and where appropriate to eliminate superfluous model equations or reduce them to other forms. This process retains the ability to interpret the reduced order model in terms of the physico-chemical phenomena. Using this model reduction technique it is possible to attribute observable dynamics to particular unit operations within the process. This relationship then highlights the unit operations which must be accurately modelled in order to develop a robust plant model. The technique generates detailed insight into the dynamic structure of the models providing a basis for system re-design and dynamic analysis. The technique is illustrated on the modelling for an evaporator startup. Copyright (C) 1996 Elsevier Science Ltd

Improving wheat simulation capabilities in Australia from a cropping systems perspective: water and nitrogen effects on spring wheat in a semi-arid environment

Systems approaches can help to evaluate and improve the agronomic and economic viability of nitrogen application in the frequently water-limited environments. This requires a sound understanding of crop physiological processes and well tested simulation models. Thus, this experiment on spring wheat aimed to better quantify water x nitrogen effects on wheat by deriving some key crop physiological parameters that have proven useful in simulating crop growth. For spring wheat grown in Northern Australia under four levels of nitrogen (0 to 360 kg N ha(-1)) and either entirely on stored soil moisture or under full irrigation, kernel yields ranged from 343 to 719 g m(-2). Yield increases were strongly associated with increases in kernel number (9150-19950 kernels m(-2)), indicating the sensitivity of this parameter to water and N availability. Total water extraction under a rain shelter was 240 mm with a maximum extraction depth of 1.5 m. A substantial amount of mineral nitrogen available deep in the profile (below 0.9 m) was taken up by the crop. This was the source of nitrogen uptake observed after anthesis. Under dry conditions this late uptake accounted for approximately 50% of total nitrogen uptake and resulted in high (>2%) kernel nitrogen percentages even when no nitrogen was applied,Anthesis LAI values under sub-optimal water supply were reduced by 63% and under sub-optimal nitrogen supply by 50%. Radiation use efficiency (RUE) based on total incident short-wave radiation was 1.34 g MJ(-1) and did not differ among treatments. The conservative nature of RUE was the result of the crop reducing leaf area rather than leaf nitrogen content (which would have affected photosynthetic activity) under these moderate levels of nitrogen limitation. The transpiration efficiency coefficient was also conservative and averaged 4.7 Pa in the dry treatments. Kernel nitrogen percentage varied from 2.08 to 2.42%. The study provides a data set and a basis to consider ways to improve simulation capabilities of water and nitrogen effects on spring wheat. (C) 1997 Elsevier Science B.V.

Commercialisation of agriculture in Kenya: Case study of urban bias on food availability in farm households

This study investigates the effect of cash cropping on food availability and examines the determinants of the proportion of income allocated for food expenditures in the Nyeri district in Kenya. Using a Tobit model, the results suggest that in general food expenditure allocations suffer due to cash cropping in Kenya as the lump-sum income flows from this may be used for purchases other than food. Food expenditure also suffers when remittances are irregular. On the other hand, earnings from outside employment for married women living with husbands are positively associated with food expenditure allocations. Amounts of non-cash food output as well as ownership of livestock are negatively associated with food expenditure allocations. These findings indicate that lump sum income may not lead to improved welfare of women and children. Thus, there may be social reasons for increasing non-cash food production especially by women, instead of over emphasizing cash cropping as now seems to be so in public policy.

Long-term survivor mixture model with random effects: application to a multi-centre clinical trial of carcinoma

A mixture model incorporating long-term survivors has been adopted in the field of biostatistics where some individuals may never experience the failure event under study. The surviving fractions may be considered as cured. In most applications, the survival times are assumed to be independent. However, when the survival data are obtained from a multi-centre clinical trial, it is conceived that the environ mental conditions and facilities shared within clinic affects the proportion cured as well as the failure risk for the uncured individuals. It necessitates a long-term survivor mixture model with random effects. In this paper, the long-term survivor mixture model is extended for the analysis of multivariate failure time data using the generalized linear mixed model (GLMM) approach. The proposed model is applied to analyse a numerical data set from a multi-centre clinical trial of carcinoma as an illustration. Some simulation experiments are performed to assess the applicability of the model based on the average biases of the estimates formed. Copyright (C) 2001 John Wiley & Sons, Ltd.

A dynamic model with on-line identification for rotary sugar drying processes

A dynamic modelling methodology, which combines on-line variable estimation and parameter identification with physical laws to form an adaptive model for rotary sugar drying processes, is developed in this paper. In contrast to the conventional rate-based models using empirical transfer coefficients, the heat and mass transfer rates are estimated by using on-line measurements in the new model. Furthermore, a set of improved sectional solid transport equations with localized parameters is developed in this work to reidentified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.place the global correlation for the computation of solid retention time. Since a number of key model variables and parameters are identified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.

Model based procedure for scale-up of wet overflow ball mills Part 1: Outline of the methodology

Bond's method for ball mill scale-up only gives the mill power draw for a given duty. This method is incompatible with computer modelling and simulation techniques. It might not be applicable for the design of fine grinding ball mills and ball mills preceded by autogenous and semi-autogenous grinding mills. Model-based ball mill scale-up methods have not been validated using a wide range of full-scale circuit data. Their accuracy is therefore questionable. Some of these methods also need expensive pilot testing. A new ball mill scale-up procedure is developed which does not have these limitations. This procedure uses data from two laboratory tests to determine the parameters of a ball mill model. A set of scale-up criteria then scales-up these parameters. The procedure uses the scaled-up parameters to simulate the steady state performance of full-scale mill circuits. At the end of the simulation, the scale-up procedure gives the size distribution, the volumetric flowrate and the mass flowrate of all the streams in the circuit, and the mill power draw.