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.

Using the canonical modelling approach to simplify the simulation of function in functional-structural plant models

Functional-structural plant models that include detailed mechanistic representation of underlying physiological processes can be expensive to construct and the resulting models can also be extremely complicated. On the other hand, purely empirical models are not able to simulate plant adaptability and response to different conditions. In this paper, we present an intermediate approach to modelling plant function that can simulate plant response without requiring detailed knowledge of underlying physiology. Plant function is modelled using a 'canonical' modelling approach, which uses compartment models with flux functions of a standard mathematical form, while plant structure is modelled using L-systems. Two modelling examples are used to demonstrate that canonical modelling can be used in conjunction with L-systems to create functional-structural plant models where function is represented either in an accurate and descriptive way, or in a more mechanistic and explanatory way. We conclude that canonical modelling provides a useful, flexible and relatively simple approach to modelling plant function at an intermediate level of abstraction.

Functional recycling of C2 domains throughout evolution: A comparative study of synaptotagmin, protein kinase C and phospholipase C by sequence, structural and modelling approaches

The C2 domain is one of the most frequent and widely distributed calcium-binding motifs. Its structure comprises an eight-stranded beta-sandwich with two structural types as if the result of a circular permutation. Combining sequence, structural and modelling information, we have explored, at different levels of granularity, the functional characteristics of several families of C2 domains. At the coarsest level,the similarity correlates with key structural determinants of the C2 domain fold and, at the finest level, with the domain architecture of the proteins containing them, highlighting the functional diversity between the various subfamilies. The functional diversity appears as different conserved surface patches throughout this common fold. In some cases, these patches are related to substrate-binding sites whereas in others they correspond to interfaces of presumably permanent interaction between other domains within the same polypeptide chain. For those related to substrate-binding sites, the predictions overlap with biochemical data in addition to providing some novel observations. For those acting as protein-protein interfaces' our modelling analysis suggests that slight variations between families are a result of not only complementary adaptations in the interfaces involved but also different domain architecture. In the light of the sequence and structural genomic projects, the work presented here shows that modelling approaches along with careful sub-typing of protein families will be a powerful combination for a broader coverage in proteomics. (C) 2003 Elsevier Ltd. All rights reserved.

Fitting genetic models to twin data with binary and ordered categorical responses: A comparison of structural equation modelling and Bayesian hierarchical models

We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

Virtual plants - integrating architectural and physiological models

Recent advances in computer technology have made it possible to create virtual plants by simulating the details of structural development of individual plants. Software has been developed that processes plant models expressed in a special purpose mini-language based on the Lindenmayer system formalism. These models can be extended from their architectural basis to capture plant physiology by integrating them with crop models, which estimate biomass production as a consequence of environmental inputs. Through this process, virtual plants will gain the ability to react to broad environmental conditions, while crop models will gain a visualisation component. This integration requires the resolution of the fundamentally different time scales underlying the approaches. Architectural models are usually based on physiological time; each time step encompasses the same amount of development in the plant, without regard to the passage of real time. In contrast, physiological models are based in real time; the amount of development in a time step is dependent on environmental conditions during the period. This paper provides a background on the plant modelling language, then describes how widely-used concepts of thermal time can be implemented to resolve these time scale differences. The process is illustrated using a case study. (C) 1997 Elsevier Science Ltd.

Using the floatability characterisation test rig for industrial flotation plant design

Industrial flotation plant design is a complex process involving many aspects, one of which is the use of pilot-scale plants to test industrial plant flow sheets. Once test work on a pilot-scale has been performed, scale-up of these results to the full-scale plant must be performed. This paper describes scale-up test work performed on the Floatability Characterisation Test Rig (FCTR). The FCTR is a self-contained, highly instrumented mobile pilot plant designed to determine flotation model parameters and to develop and validate flotation plant modelling, scale-up and simulation methodologies.

To learn from one's mistakes: The role of impulsivity in positive workplace behaviours

Recentiy a neuropsychological model of learning has been proposed Qackson, 2002) which argues that Responsibility provides a cognitive re-expression of Impulsivit)' in the prediction of functional and dysfunctional behaviour. Jackson argues that primitive, instinctive impulses lead to antisocial behaviours and socio-cognitive regulators such as Responsibility leads to the re-expression of Impulsivity in terms of pro-social behaviours. Study 1 tests and supports the measurement properties of the assessment methodology associated with the model. Study 2 provides evidence in favour of the instinctive basis of Impulsivity and the conscious basis of Responsibility, which reinforces the underlying neuropsychological basis of the model. Study 3 uses structural equation modelling to determine if Responsibility mediates Impulsivity in the prediction of a latent variable representing work performance, work commitment and team performance, but does not mediate Impulsivit}' in the prediction of a latent variable representing sexual proclivity, workplace deviancy, gambling and beer consumption. Results provide strong support for Jackson's model and suggest that Impulsivity and Responsibility are fundamental to both functional and dysfunctional learning

Goals and reputations amongst young children - The validation of the importance of goals and reputation enhancement scales

The aim of the present research was to provide school psychologists with valid instruments with which to assess the goals and reputations of young children. This was achieved by ascertaining whether the factor structures and the second-order factor models of the high school versions of the Importance of Goals (Carroll, et al., 1997) and Reputation Enhancement Scales (Carroll, et al., 1999) could be replicated with a primary school sample. Eight hundred and eighty-six 10 to 12 year old children were administered modified versions of the two scales, which were combined and renamed the Children's Activity Questionnaire. For the two scales, the factor structure proved replicable and reliable with the primary school sample. A comparison between the factor loadings of the primary school and the high school samples using the coefficient of congruence procedure demonstrated similarity indicating that the scales are replicable and able to be used with a younger primary school sample. Structural equation modelling indicated that the second-order factor structure of the Importance of Goals Scale was acceptable but this was not the case for the second-order factor structure of the Reputation Enhancement Scale.

Determinants of general practitioner use among women in Australia

This study investigates the use of general practitioner services by women in Australia. Although there is a universal health insurance system (Medicare) in Australia, there are variations in access to services and out of pocket costs for services. Survey data from 2350 mid-age (45-50 years) and 2102 older (70-75 years) women participating in the Australian Longitudinal Study on Women's Health were linked with Medicare data to provide a range of individual and contextual variables hypothesised to explain general practitioner use. Structural equation modelling showed that physical health was the most powerful explanatory factor of general practitioner use. However, after adjusting for self-reported health, out of pocket cost per consultation was inversely associated with use of services. The out of pocket cost was generally lower for women with low socioeconomic status but cost was also directly related to geographical remoteness. Women living in more remote areas had higher out of pocket costs and poorer access to services. Women who reported better access to care were more likely to be satisfied with their most recent general practice consultation and less likely to be sceptical of the value of medical care. These results show the need for health policies that improve the equitable use of general practitioner services in Australia. (C) 2001 Elsevier Science Ltd. All rights reserved.

Repeated blood pressure measurements in a sample of Swedish twins: heritabilities and associations with polymorphisms in the renin-angiotensin-aldosterone system Iliadou, Anastasia, Lichtenstein, Paul, Morgenstern, Ralf, Forsberg, Lena, Svensson, Richard, de Faire, Ulf, Martin, Nicholas, Pedersen, Nancy

Background Twin and family studies have shown that genetic effects explain a relatively high amount of the phenotypic variation in blood pressure. However, many studies have not been able to replicate findings of association between specific polymorphisms and diastolic and systolic blood pressure. Methods In a structural equation-modelling framework the authors investigated longitudinal changes in repeated measures of blood pressures in a sample of 298 like-sexed twin pairs from the population-based Swedish Twin Registry. Also examined was the association between blood pressure and polymorphisms in the angiotensin-I converting enzyme and the angiotensin 11 receptor type 1 with the 'Fulker' test Both linkage and association were tested simultaneously revealing whether the polymorphism is a Quantitative Trait Locus (QTL) or in linkage disequilibrium with the QTL. Results Genetic influences explained up to 46% of the phenotypic variance in diastolic and 63% of the phenotypic variance in systolic blood pressure. Genetic influences were stable over time and contributed up to 78% of the phenotypic correlation in both diastolic and systolic blood pressure. Non-shared environmental effects were characterised by time specific influences and little transmission from one time point to the next. There was no significant linkage and association between the polymorphisms and blood pressure. Conclusions There is a considerable genetic stability in both diastolic and systolic blood pressure for a 6-year period of time in adult life. Non-shared environmental influences have a small long-term effect Although associations with the polymorphisms could not be replicated, results should be interpreted with caution due to power considerations. (C) 2002 Lippincott Williams Wilkins.

The validity and heritability of self-report osteoarthritis in an Australian older twin sample

In order to investigate the genetic and environmental antecedents of osteoarthritis (CA), self-report measures of joint pain, stiffness and swelling were obtained from a population-based sample of 1242 twin pairs over 50 years of age. In order to provide validation for these self-report measures, a subsample of 118 twin pairs were examined according to the American College of Rheumatology clinical and radiographic criteria for the classification of osteoarthritis. A variety of statistical methods were employed to identify the model derived from self-report variables which would provide optimal prediction of these standardised assessments, and structural equation modelling was used to determine the relative influences of genetic and environmental influences on the development of osteoarthritis. Significant genetic effects were found to contribute to osteoarthritis of the hands, hips and knees in women, with heritability estimates ranging from 30-46% depending on the site. In addition, the additive genetic effects contributing to osteoarthritis in various parts of the body were confirmed to be the same. Statistically significant familial aggregation of osteoarthritis in men was also observed, but it was not possible to determine whether this was due to genetic or shared environmental effects.

Single-subject research designs and data analyses for assessing elite athletes' conditioning

Research in conditioning (all the processes of preparation for competition) has used group research designs, where multiple athletes are observed at one or more points in time. However, empirical reports of large inter-individual differences in response to conditioning regimens suggest that applied conditioning research would greatly benefit from single-subject research designs. Single-subject research designs allow us to find out the extent to which a specific conditioning regimen works for a specific athlete, as opposed to the average athlete, who is the focal point of group research designs. The aim of the following review is to outline the strategies and procedures of single-subject research as they pertain to.. the assessment of conditioning for individual athletes. The four main experimental designs in single-subject research are: the AB design, reversal (withdrawal) designs and their extensions, multiple baseline designs and alternating treatment designs. Visual and statistical analyses commonly used to analyse single-subject data, and advantages and limitations are discussed. Modelling of multivariate single-subject data using techniques such as dynamic factor analysis and structural equation modelling may identify individualised models of conditioning leading to better prediction of performance. Despite problems associated with data analyses in single-subject research (e.g. serial dependency), sports scientists should use single-subject research designs in applied conditioning research to understand how well an intervention (e.g. a training method) works and to predict performance for a particular athlete.

Are interactions in Gray's Reinforcement Sensitivity Theory proximal or distal in the prediction of religiosity: a test of the joint subsystems hypothesis

Gray's Reinforcement Sensitivity Theory (RST) consists of the Behavioural Activation System (BAS) which is the basis of Impulsivity, and Behavioural Inhibition System (BIS) which is the basis of Anxiety. In this study, Impulsivity and Anxiety were used as distal predictors of attitudes to religion in the prediction of three religious dependent variables (Church attendance, Amount of prayer, and Importance of church). We hypothesised that Impulsivity would independently predict a Rewarding attitude to the Church and that Anxiety would independently predict an Anxious attitude to the church, and that these attitudes would be proximal predictors of our dependent variables. Moreover, we predicted that interactions between predictors would be proximal. Using structural equation modelling, data from 400 participants supported the hypotheses. We also tested Eysenck's personality scales of Extraversion and Neuroticism and found a key path of the structural equation model to be non-significant. (C) 2003 Elsevier Ltd. All rights reserved.