Stochastic models and simulation of ion channel dynamics

The behaviour of ion channels within cardiac and neuronal cells is intrinsically stochastic in nature. When the number of channels is small this stochastic noise is large and can have an impact on the dynamics of the system which is potentially an issue when modelling small neurons and drug block in cardiac cells. While exact methods correctly capture the stochastic dynamics of a system they are computationally expensive, restricting their inclusion into tissue level models and so approximations to exact methods are often used instead. The other issue in modelling ion channel dynamics is that the transition rates are voltage dependent, adding a level of complexity as the channel dynamics are coupled to the membrane potential. By assuming that such transition rates are constant over each time step, it is possible to derive a stochastic differential equation (SDE), in the same manner as for biochemical reaction networks, that describes the stochastic dynamics of ion channels. While such a model is more computationally efficient than exact methods we show that there are analytical problems with the resulting SDE as well as issues in using current numerical schemes to solve such an equation. We therefore make two contributions: develop a different model to describe the stochastic ion channel dynamics that analytically behaves in the correct manner and also discuss numerical methods that preserve the analytical properties of the model.

Analyzing real-time video microscopy : the dynamics and geometry of vesicles and tubules in endocytosis

With the advent of live cell imaging microscopy, new types of mathematical analyses and measurements are possible. Many of the real-time movies of cellular processes are visually very compelling, but elementary analysis of changes over time of quantities such as surface area and volume often show that there is more to the data than meets the eye. This unit outlines a geometric modeling methodology and applies it to tubulation of vesicles during endocytosis. Using these principles, it has been possible to build better qualitative and quantitative understandings of the systems observed, as well as to make predictions about quantities such as ligand or solute concentration, vesicle pH, and membrane trafficked. The purpose is to outline a methodology for analyzing real-time movies that has led to a greater appreciation of the changes that are occurring during the time frame of the real-time video microscopy and how additional quantitative measurements allow for further hypotheses to be generated and tested.

Evolving noisy oscillatory dynamics in genetic regulatory networks

We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation of genetic networks is based on a biochemical reaction model including key elements such as transcription, translation and post-translational modifications. The stochastic, reaction-based GP system is similar but not identical with algorithmic chemistries. We evolved genetic networks with noisy oscillatory dynamics. The results show the practicality of evolving particular dynamics in gene regulatory networks when modelled with intrinsic noise.

User-representative feature selection for keystroke dynamics

Continuous user authentication with keystroke dynamics uses characters sequences as features. Since users can type characters in any order, it is imperative to find character sequences (n-graphs) that are representative of user typing behavior. The contemporary feature selection approaches do not guarantee selecting frequently-typed features which may cause less accurate statistical user-representation. Furthermore, the selected features do not inherently reflect user typing behavior. We propose four statistical based feature selection techniques that mitigate limitations of existing approaches. The first technique selects the most frequently occurring features. The other three consider different user typing behaviors by selecting: n-graphs that are typed quickly; n-graphs that are typed with consistent time; and n-graphs that have large time variance among users. We use Gunetti’s keystroke dataset and k-means clustering algorithm for our experiments. The results show that among the proposed techniques, the most-frequent feature selection technique can effectively find user representative features. We further substantiate our results by comparing the most-frequent feature selection technique with three existing approaches (popular Italian words, common n-graphs, and least frequent ngraphs). We find that it performs better than the existing approaches after selecting a certain number of most-frequent n-graphs.

Development of a performance model for international construction joint venture : a system dynamics approach

The uncertain and dynamic nature of International Construction Joint Venture (ICJV) performance is evolved with many critical factors which lead to make partner relationships more complex in respect of making decisions to maintain a cohesive environment. Addressing to the fact, a generic system dynamics performance model for ICJV is developed by integrating a number variables as to get an overall impact on performance of ICJV and to make effective decisions based on that. In order to formulate and validate the model both structurally and behaviourally, both qualitative and quantitative data are gathered by conducting intensive interviews from two ICJVs in Thailand. After conducting intensive simulations of model, three major problems are identified related to negative value gap, low productivity in construction and high rate of ineffective information sharing of both ICJVs. Several policies are suggested and integrated application of these policies provides a maximum improvement to performance of the ICJV.

Compensation of unmodeled aircraft dynamics in airborne inspection of linear infrastructure assets

Fixed-wing aircraft equipped with downward pointing cameras and/or LiDAR can be used for inspecting approximately piecewise linear assets such as oil-gas pipelines, roads and power-lines. Automatic control of such aircraft is important from a productivity and safety point of view (long periods of precision manual flight at low-altitude is not considered reasonable from a safety perspective). This paper investigates the effect of any unwanted coupling between guidance and autopilot loops (typically caused by unmodeled delays in the aircraft’s response), and the specific impact of any unwanted dynamics on the performance of aircraft undertaking inspection of piecewise linear corridor assets (such as powerlines). Simulation studies and experimental flight tests are used to demonstrate the benefits of a simple compensator in mitigating the unwanted lateral oscillatory behaviour (or coupling) that is caused by unmodeled time constants in the aircraft dynamics.

Modelling contractor's and subcontractor's trust : a system dynamics approach

A general mistrust within the contactor and subcontractor companies has identified one of the significant barriers to derive benefits from true downstream supply chain integration. Using the general theory of trust in inter-organizational relations and conducting interviews, this research discusses factors that influence development of trust and cooperation in contractor– subcontractor relationships in construction projects. System dynamics is the simulation method is selected in this theory-building effort, based on qualitative data collected from two projects of a construction company in Thailand. Performance, permeability and system based trust are found to make significant contributions toward parties’ trust level. Three strategic policies such as best value contracting, management of subcontractors as internal team and semi project partnering approach are recommended to stimulate the trust factors as well as cooperative long term relationship.

The Metapopulation Dynamics of an Infectious Disease: Tuberculosis in Possums

An SEI metapopulation model is developed for the spread of an infectious agent by migration. The model portrays two age classes on a number of patches connected by migration routes which are used as host animals mature. A feature of this model is that the basic reproduction ratio may be computed directly, using a scheme that separates topography, demography, and epidemiology. We also provide formulas for individual patch basic reproduction numbers and discuss their connection with the basic reproduction ratio for the system. The model is applied to the problem of spatial spread of bovine tuberculosis in a possum population. The temporal dynamics of infection are investigated for some generic networks of migration links, and the basic reproduction ratio is computed—its value is not greatly different from that for a homogeneous model. Three scenarios are considered for the control of bovine tuberculosis in possums where the spatial aspect is shown to be crucial for the design of disease management operations

It's only temporary: Time frame and the dynamics of creative project teams

The success of many knowledge-intensive industries depends on creative projects that lie at the heart of their logic of production. The temporality of such projects, however, is an issue that is insufficiently understood. To address this, we study the perceived time frame of teams that work on creative projects and its effects on project dynamics. An experiment with 267 managers assigned to creative project teams with varying time frames demonstrates that compared to creative project teams with a relatively longer time frame, project teams with a shorter time frame focus more on the immediate present, are less immersed in their task, and utilize a more heuristic mode of information processing. Furthermore, we find that time frame moderates the negative effect of team conflict on team cohesion. These results are consistent with our theory that the temporary nature of creative projects shapes different time frames among project participants, and that it is this time frame that is an important predictor of task and team processes.

The dynamics of parenting and early feeding - constructs and controversies : a viewpoint

There is increasing evidence that parenting and feeding interact to influence children’s eating behaviour and weight status. Interpretation of existing research is complicated by the lack of consensus in the conceptualisation and measurement of both ‘parenting’ and ‘feeding’, particularly the distinction between ‘styles’, ‘dimensions’ and ‘practices’. In addition, the lack of validated tools to concurrently assess feeding practices in infancy limits the capacity to examine the relationships between parenting and feeding in infancy and their short- and long-term influence on weight status. In this paper we provide an overview of the constructs examined in this emerging area of research, highlight the conceptual, definitional and measurement challenges and propose a unifying model to aid design and the interpretation of intervention studies. Progress on these methodological issues will contribute to the robust evidence required to justify investment in interventions that focus on parenting and feeding in the context of child obesity prevention.

Negotiating group dynamics for better safety performance

Safety psychology and workplace safety Commitment, Motivational and attitudinal components of safety Leadership Group Dynamics and Group Change Case Study from Construction

(Not) the Twitter election: The dynamics of the #ausvotes conversation in relation to the Australian media ecology

This paper draws on a larger study of the uses of Australian user-created content and online social networks to examine the relationships between professional journalists and highly engaged Australian users of political media within the wider media ecology, with a particular focus on Twitter. It uses an analysis of topic based conversation networks using the #ausvotes hashtag on Twitter around the 2010 federal election to explore the key themes and issues addressed by this Twitter community during the campaign, and finds that Twitter users were largely commenting on the performance of mainstream media and politicians rather than engaging in direct political discussion. The often critical attitude of Twitter users towards the political establishment mirrors the approach of news and political bloggers to political actors, nearly a decade earlier, but the increasing adoption of Twitter as a communication tool by politicians, journalists, and everyday users alike makes a repetition of the polarisation experienced at that time appear unlikely.

Modeling ion channel dynamics through reflected stochastic differential equations

Ion channels are membrane proteins that open and close at random and play a vital role in the electrical dynamics of excitable cells. The stochastic nature of the conformational changes these proteins undergo can be significant, however current stochastic modeling methodologies limit the ability to study such systems. Discrete-state Markov chain models are seen as the "gold standard," but are computationally intensive, restricting investigation of stochastic effects to the single-cell level. Continuous stochastic methods that use stochastic differential equations (SDEs) to model the system are more efficient but can lead to simulations that have no biological meaning. In this paper we show that modeling the behavior of ion channel dynamics by a reflected SDE ensures biologically realistic simulations, and we argue that this model follows from the continuous approximation of the discrete-state Markov chain model. Open channel and action potential statistics from simulations of ion channel dynamics using the reflected SDE are compared with those of a discrete-state Markov chain method. Results show that the reflected SDE simulations are in good agreement with the discrete-state approach. The reflected SDE model therefore provides a computationally efficient method to simulate ion channel dynamics while preserving the distributional properties of the discrete-state Markov chain model and also ensuring biologically realistic solutions. This framework could easily be extended to other biochemical reaction networks. © 2012 American Physical Society.