Models of collective cell behaviour with crowding effects : comparing lattice-based and lattice-free approaches

Individual-based models describing the migration and proliferation of a population of cells frequently restrict the cells to a predefined lattice. An implicit assumption of this type of lattice based model is that a proliferative population will always eventually fill the lattice. Here we develop a new lattice-free individual-based model that incorporates cell-to-cell crowding effects. We also derive approximate mean-field descriptions for the lattice-free model in two special cases motivated by commonly used experimental setups. Lattice-free simulation results are compared to these mean-field descriptions and to a corresponding lattice-based model. Data from a proliferation experiment is used to estimate the parameters for the new model, including the cell proliferation rate, showing that the model fits the data well. An important aspect of the lattice-free model is that the confluent cell density is not predefined, as with lattice-based models, but an emergent model property. As a consequence of the more realistic, irregular configuration of cells in the lattice-free model, the population growth rate is much slower at high cell densities and the population cannot reach the same confluent density as an equivalent lattice-based model.

Quantum models of cognition and decision

Much of our understanding of human thinking is based on probabilistic models. This innovative book by Jerome R. Busemeyer and Peter D. Bruza argues that, actually, the underlying mathematical structures from quantum theory provide a much better account of human thinking than traditional models. They introduce the foundations for modelling probabilistic-dynamic systems using two aspects of quantum theory. The first, "contextuality", is a way to understand interference effects found with inferences and decisions under conditions of uncertainty. The second, "entanglement", allows cognitive phenomena to be modelled in non-reductionist ways. Employing these principles drawn from quantum theory allows us to view human cognition and decision in a totally new light...

Book review of Wang, Y., & Pizam, A. (Eds). 2011. Destination Marketing and Management – Theories and Applications.

A contentious issue in the field of destination marketing has been the recent tendency by some authors to refer to destination marketing organisations (DMOs) as destination management organisations. This nomenclature infers control over destination resources, a level of influence that is in reality held by few DMOs. This issue of a lack of control over the destination ‘amalgam’ is acknowledged by a number of the contributors, including the editors and the discussion on destination competitiveness by J.R. Brent Ritchie and Geoffrey Crouch, and is perhaps best summed up by Alan Fyall in the concluding chapter: “...unless all elements are owned by the same body, then the ability to control and influence the direction, quality and development of the destination pose very real challenges’ (p. 343). The title of the text acknowledges both marketing and management, in relation to theories and applications. While there are insightful propositions about ideals of destination management, readers will find there is a lack of coverage of destination management in practise by DMOs. This represents fertile ground for future research.

How do allied health professionals evaluate new models of care? What are we measuring and why?

The aim of this study was to identify what outcome measures or quality indicators are being used to evaluate advanced and new roles in nine allied health professions and whether the measures are evaluating outcomes of interest to the patient, the clinician, or the healthcare provider. A systematic search strategy was used. Medical and allied health databases were searched and relevant articles extracted. Relevant studies with at least 1 outcome measure were evaluated. A total of 106 articles were identified that described advanced roles, however, only 23 of these described an outcome measure in sufficient detail to be included for review. The majority of the reported measures fit into the economic and process categories. The most reported outcome related to patients was satisfaction surveys. Measures of patient health outcomes were infrequently reported. It is unclear from the studies evaluated whether new models of allied healthcare can be shown to be as safe and effective as traditional care for a given procedure. Outcome measures chosen to evaluate these services often reflect organizational need and not patient outcomes. Organizations need to ensure that high-quality performance measures are chosen to evaluate the success of new health service innovations. There needs to be a move away from in-house type surveys that add little or no valid evidence as to the effect of a new innovation. More importance needs to be placed on patient outcomes as a measure of the quality of allied health interventions.

Some extensions to representation and encoding of structure in models of distributional semantics

This thesis makes several contributions towards improved methods for encoding structure in computational models of word meaning. New methods are proposed and evaluated which address the requirement of being able to easily encode linguistic structural features within a computational representation while retaining the ability to scale to large volumes of textual data. Various methods are implemented and evaluated on a range of evaluation tasks to demonstrate the effectiveness of the proposed methods.

Lattice-free models of cell invasion : discrete simulations and travelling waves

Invasion waves of cells play an important role in development, disease and repair. Standard discrete models of such processes typically involve simulating cell motility, cell proliferation and cell-to-cell crowding effects in a lattice-based framework. The continuum-limit description is often given by a reaction–diffusion equation that is related to the Fisher–Kolmogorov equation. One of the limitations of a standard lattice-based approach is that real cells move and proliferate in continuous space and are not restricted to a predefined lattice structure. We present a lattice-free model of cell motility and proliferation, with cell-to-cell crowding effects, and we use the model to replicate invasion wave-type behaviour. The continuum-limit description of the discrete model is a reaction–diffusion equation with a proliferation term that is different from lattice-based models. Comparing lattice based and lattice-free simulations indicates that both models lead to invasion fronts that are similar at the leading edge, where the cell density is low. Conversely, the two models make different predictions in the high density region of the domain, well behind the leading edge. We analyse the continuum-limit description of the lattice based and lattice-free models to show that both give rise to invasion wave type solutions that move with the same speed but have very different shapes. We explore the significance of these differences by calibrating the parameters in the standard Fisher–Kolmogorov equation using data from the lattice-free model. We conclude that estimating parameters using this kind of standard procedure can produce misleading results.

Children and young people using public space : models of rights, optimism and wellbeing

This presentation discusses topics and issues that connect closely with the Conference Themes and themes in the ARACY Report Card. For example, developing models of public space that are safe, welcoming and relevant to children and young people will impact on their overall wellbeing and may help to prevent many of the tensions occurring in Australia and elsewhere around the world. This area is the subject of ongoing international debate, research and policy formation, relevant to concerns in the ARACY Report Card about children and young people’s health and safety, participation, behaviours and risks and peer and family relationships.

Rodent Models of Conditioned Fear: Behavioral Measures of Fear and Memory

Pavlovian fear conditioning is a robust technique for examining behavioral and cellular components of fear learning and memory. In fear conditioning, the subject learns to associate a previously neutral stimulus with an inherently noxious co-stimulus. The learned association is reflected in the subjects' behavior upon subsequent re-exposure to the previously neutral stimulus or the training environment. Using fear conditioning, investigators can obtain a large amount of data that describe multiple aspects of learning and memory. In a single test, researchers can evaluate functional integrity in fear circuitry, which is both well characterized and highly conserved across species. Additionally, the availability of sensitive and reliable automated scoring software makes fear conditioning amenable to high-throughput experimentation in the rodent model; thus, this model of learning and memory is particularly useful for pharmacological and toxicological screening. Due to the conserved nature of fear circuitry across species, data from Pavlovian fear conditioning are highly translatable to human models. We describe equipment and techniques needed to perform and analyze conditioned fear data. We provide two examples of fear conditioning experiments, one in rats and one in mice, and the types of data that can be collected in a single experiment. © 2012 Springer Science+Business Media, LLC.

Pavlovian fear memory circuits and phenotype models of PTSD

Pavlovian fear conditioning, also known as classical fear conditioning is an important model in the study of the neurobiology of normal and pathological fear. Progress in the neurobiology of Pavlovian fear also enhances our understanding of disorders such as posttraumatic stress disorder (PTSD) and with developing effective treatment strategies. Here we describe how Pavlovian fear conditioning is a key tool for understanding both the neurobiology of fear and the mechanisms underlying variations in fear memory strength observed across different phenotypes. First we discuss how Pavlovian fear models aspects of PTSD. Second, we describe the neural circuits of Pavlovian fear and the molecular mechanisms within these circuits that regulate fear memory. Finally, we show how fear memory strength is heritable; and describe genes which are specifically linked to both changes in Pavlovian fear behavior and to its underlying neural circuitry. These emerging data begin to define the essential genes, cells and circuits that contribute to normal and pathological fear.

RatSLAM : using models of rodent hippocampus for robot navigation and beyond

We describe recent biologically-inspired mapping research incorporating brain-based multi-sensor fusion and calibration processes and a new multi-scale, homogeneous mapping framework. We also review the interdisciplinary approach to the development of the RatSLAM robot mapping and navigation system over the past decade and discuss the insights gained from combining pragmatic modelling of biological processes with attempts to close the loop back to biology. Our aim is to encourage the pursuit of truly interdisciplinary approaches to robotics research by providing successful case studies.

A Matlab toolbox for parametric identification of radiation-force models of ships and offshore structures

This article describes a Matlab toolbox for parametric identification of fluid-memory models associated with the radiation forces ships and offshore structures. Radiation forces are a key component of force-to-motion models used in simulators, motion control designs, and also for initial performance evaluation of wave-energy converters. The software described provides tools for preparing non-parmatric data and for identification with automatic model-order detection. The identification problem is considered in the frequency domain.

Joint identification of infinite-frequency added mass and fluid-memory models of marine structures

This paper addresses the problem of joint identification of infinite-frequency added mass and fluid memory models of marine structures from finite frequency data. This problem is relevant for cases where the code used to compute the hydrodynamic coefficients of the marine structure does not give the infinite-frequency added mass. This case is typical of codes based on 2D-potential theory since most 3D-potential-theory codes solve the boundary value associated with the infinite frequency. The method proposed in this paper presents a simpler alternative approach to other methods previously presented in the literature. The advantage of the proposed method is that the same identification procedure can be used to identify the fluid-memory models with or without having access to the infinite-frequency added mass coefficient. Therefore, it provides an extension that puts the two identification problems into the same framework. The method also exploits the constraints related to relative degree and low-frequency asymptotic values of the hydrodynamic coefficients derived from the physics of the problem, which are used as prior information to refine the obtained models.

Probability and story-telling : normative and descriptive models of juridical proof

The operation of the law rests on the selection of an account of the facts. Whether this involves prediction or postdiction, it is not possible to achieve certainty. Any attempt to model the operation of the law completely will therefore raise questions of how to model the process of proof. In the selection of a model a crucial question will be whether the model is to be used normatively or descriptively. Focussing on postdiction, this paper presents and contrasts the mathematical model with the story model. The former carries the normative stamp of scientific approval, whereas the latter has been developed by experimental psychologists to describe how humans reason. Neil Cohen's attempt to use a mathematical model descriptively provides an illustration of the dangers in not clearly setting this parameter of the modelling process. It should be kept in mind that the labels 'normative' and 'descriptive' are not eternal. The mathematical model has its normative limits, beyond which we may need to critically assess models with descriptive origins.

Effect of strong acids on red mud structural and fluoride adsorption properties

The removal of fluoride using red mud has been improved by acidifying red mud with hydrochloric, nitric and sulphuric acid. This investigation shows that the removal of fluoride using red mud is significantly improved if red mud is initially acidified. The acidification of red mud causes sodalite and cancrinite phases to dissociate, confirmed by the release of sodium and aluminium into solution as well as the disappearance of sodalite bands and peaks in infrared and X-ray diffraction data. The dissolution of these mineral phases increases the amount of available iron and aluminium oxide/hydroxide sites that are accessible for the adsorption of fluoride. The removal of fluoride is dependent on the charge of iron and aluminium oxide/hydroxides on the surface of red mud. Acidifying red mud with hydrochloric, nitric and sulphuric acid resulted in surface sites of the form ≡ SOH2+ and ≡ SOH. Optimum removal is obtained when the majority of surface sites are in the form ≡ SOH2+ as the substitution of a fluoride ion doesn’t cause a significant increase in pH. This investigation shows the importance of having a low and consistent pH for the removal of fluoride from aqueous solutions using red mud.