On the mathematical modeling of wound healing angiogenesis in skin as a reaction-transport process

Over the last 30 years, numerous research groups have attempted to provide mathematical descriptions of the skin wound healing process. The development of theoretical models of the interlinked processes that underlie the healing mechanism has yielded considerable insight into aspects of this critical phenomenon that remain difficult to investigate empirically. In particular, the mathematical modeling of angiogenesis, i.e., capillary sprout growth, has offered new paradigms for the understanding of this highly complex and crucial step in the healing pathway. With the recent advances in imaging and cell tracking, the time is now ripe for an appraisal of the utility and importance of mathematical modeling in wound healing angiogenesis research. The purpose of this review is to pedagogically elucidate the conceptual principles that have underpinned the development of mathematical descriptions of wound healing angiogenesis, specifically those that have utilized a continuum reaction-transport framework, and highlight the contribution that such models have made toward the advancement of research in this field. We aim to draw attention to the common assumptions made when developing models of this nature, thereby bringing into focus the advantages and limitations of this approach. A deeper integration of mathematical modeling techniques into the practice of wound healing angiogenesis research promises new perspectives for advancing our knowledge in this area. To this end we detail several open problems related to the understanding of wound healing angiogenesis, and outline how these issues could be addressed through closer cross-disciplinary collaboration.

Viewing systematic reviews and meta-analysis in social research through different lenses

Systematic reviews and meta-analyses are used to combine results across studies to determine an overall effect. Meta-analysis is especially useful for combining evidence to inform social policy, but meta-analyses of applied social science research may encounter practical issues arising from the nature of the research domain. The current paper identifies potential resolutions to four issues that may be encountered in systematic reviews and meta-analyses in social research. The four issues are: scoping and targeting research questions appropriate for meta-analysis; selecting eligibility criteria where primary studies vary in research design and choice of outcome measures; dealing with inconsistent reporting in primary studies; and identifying sources of heterogeneity with multiple confounded moderators. The paper presents an overview of each issue with a review of potential resolutions, identified from similar issues encountered in meta-analysis in medical and biological sciences. The discussion aims to share and improve methodology in systematic reviews and meta-analysis by promoting cross-disciplinary communication, that is, to encourage 'viewing through different lenses'.

Mathematical modeling for improved greenhouse gas balances, agro-ecosystems, and policy development: Lessons from the Australian experience

If the land sector is to make significant contributions to mitigating anthropogenic greenhouse gas (GHG) emissions in coming decades, it must do so while concurrently expanding production of food and fiber. In our view, mathematical modeling will be required to provide scientific guidance to meet this challenge. In order to be useful in GHG mitigation policy measures, models must simultaneously meet scientific, software engineering, and human capacity requirements. They can be used to understand GHG fluxes, to evaluate proposed GHG mitigation actions, and to predict and monitor the effects of specific actions; the latter applications require a change in mindset that has parallels with the shift from research modeling to decision support. We compare and contrast 6 agro-ecosystem models (FullCAM, DayCent, DNDC, APSIM, WNMM, and AgMod), chosen because they are used in Australian agriculture and forestry. Underlying structural similarities in the representations of carbon flows though plants and soils in these models are complemented by a diverse range of emphases and approaches to the subprocesses within the agro-ecosystem. None of these agro-ecosystem models handles all land sector GHG fluxes, and considerable model-based uncertainty exists for soil C fluxes and enteric methane emissions. The models also show diverse approaches to the initialisation of model simulations, software implementation, distribution, licensing, and software quality assurance; each of these will differentially affect their usefulness for policy-driven GHG mitigation prediction and monitoring. Specific requirements imposed on the use of models by Australian mitigation policy settings are discussed, and areas for further scientific development of agro-ecosystem models for use in GHG mitigation policy are proposed.

5-year Chlamydia vaccination programme could reverse disease-related koala population decline: Predictions from a mathematical model using field data

BACKGROUND Many koala populations around Australia are in serious decline, with a substantial component of this decline in some Southeast Queensland populations attributed to the impact of Chlamydia. A Chlamydia vaccine for koalas is in development and has shown promise in early trials. This study contributes to implementation preparedness by simulating vaccination strategies designed to reverse population decline and by identifying which age and sex category it would be most effective to target. METHODS We used field data to inform the development and parameterisation of an individual-based stochastic simulation model of a koala population endemic with Chlamydia. The model took into account transmission, morbidity and mortality caused by Chlamydia infections. We calibrated the model to characteristics of typical Southeast Queensland koala populations. As there is uncertainty about the effectiveness of the vaccine in real-world settings, a variety of potential vaccine efficacies, half-lives and dosing schedules were simulated. RESULTS Assuming other threats remain constant, it is expected that current population declines could be reversed in around 5-6 years if female koalas aged 1-2 years are targeted, average vaccine protective efficacy is 75%, and vaccine coverage is around 10% per year. At lower vaccine efficacies the immunological effects of boosting become important: at 45% vaccine efficacy population decline is predicted to reverse in 6 years under optimistic boosting assumptions but in 9 years under pessimistic boosting assumptions. Terminating a successful vaccination programme at 5 years would lead to a rise in Chlamydia prevalence towards pre-vaccination levels. CONCLUSION For a range of vaccine efficacy levels it is projected that population decline due to endemic Chlamydia can be reversed under realistic dosing schedules, potentially in just 5 years. However, a vaccination programme might need to continue indefinitely in order to maintain Chlamydia prevalence at a sufficiently low level for population growth to continue.

Response to: Electronic health records and healthcare identifiers : legislation discussion paper

Public submission # 029 to a Australian federal parliamentary committee considering proposed legislative changes to the Commonwealth's Healthcare Identifiers Act 2010 and the Personally Controlled Electronic Health Records Act 2012.

Submission on NSW Attorney-General's Discussion Paper on Amendment of Limitation of Actions Act 1969 to remove time limit for civil claims for child abuse

The New South Wales Attorney-General and Justice Policy Division released a Discussion Paper about reform of the Limitation of Actions Act 1969. The key question was whether and how to amend the statute to better provide access to justice for civil claimants in child abuse cases. This submission draws on published literature and multidisciplinary research to support the Discussion Paper's Option A, namely, to abolish the time limit for civil claims for injuries in criminal child abuse cases, and for this to be made retrospective.

A mathematical framework for expanding a railway’s theoretical capacity

Analytical techniques for measuring and planning railway capacity expansion activities have been considered in this article. A preliminary mathematical framework involving track duplication and section sub divisions is proposed for this task. In railways these features have a great effect on network performance and for this reason they have been considered. Additional motivations have also arisen from the limitations of prior models that have not included them.

An integrated mathematical approach to measure the capacity of MMTS

This article focusses upon multi-modal transportation systems (MMTS) and the issues surrounding the determination of system capacity. For that purpose a multi-objective framework is advocated that integrates all the different modes and many different competing capacity objectives. This framework is analytical in nature and facilitates a variety of capacity querying and capacity expansion planning.

Discussion of “Generalized estimating equations: Notes on the choice of the working correlation matrix”

Objective To discuss generalized estimating equations as an extension of generalized linear models by commenting on the paper of Ziegler and Vens "Generalized Estimating Equations. Notes on the Choice of the Working Correlation Matrix". Methods Inviting an international group of experts to comment on this paper. Results Several perspectives have been taken by the discussants. Econometricians have established parallels to the generalized method of moments (GMM). Statisticians discussed model assumptions and the aspect of missing data Applied statisticians; commented on practical aspects in data analysis. Conclusions In general, careful modeling correlation is encouraged when considering estimation efficiency and other implications, and a comparison of choosing instruments in GMM and generalized estimating equations, (GEE) would be worthwhile. Some theoretical drawbacks of GEE need to be further addressed and require careful analysis of data This particularly applies to the situation when data are missing at random.

On the order of the fractional Laplacian in determining the spatio-temporal evolution of a space-fractional model of cardiac electrophysiology

Space-fractional operators have been used with success in a variety of practical applications to describe transport processes in media characterised by spatial connectivity properties and high structural heterogeneity altering the classical laws of diffusion. This study provides a systematic investigation of the spatio-temporal effects of a space-fractional model in cardiac electrophysiology. We consider a simplified model of electrical pulse propagation through cardiac tissue, namely the monodomain formulation of the Beeler-Reuter cell model on insulated tissue fibres, and obtain a space-fractional modification of the model by using the spectral definition of the one-dimensional continuous fractional Laplacian. The spectral decomposition of the fractional operator allows us to develop an efficient numerical method for the space-fractional problem. Particular attention is paid to the role played by the fractional operator in determining the solution behaviour and to the identification of crucial differences between the non-fractional and the fractional cases. We find a positive linear dependence of the depolarization peak height and a power law decay of notch and dome peak amplitudes for decreasing orders of the fractional operator. Furthermore, we establish a quadratic relationship in conduction velocity, and quantify the increasingly wider action potential foot and more pronounced dispersion of action potential duration, as the fractional order is decreased. A discussion of the physiological interpretation of the presented findings is made.

Mathematical modelling of the impaction and spreading of spray droplets on leaves

This thesis concerns the development of mathematical models to describe the interactions that occur between spray droplets and leaves. Models are presented that not only provide a contribution to mathematical knowledge in the field of fluid dynamics, but are also of utility within the agrichemical industry. The thesis is presented in two parts. First, thin film models are implemented with efficient numerical schemes in order to simulate droplets on virtual leaf surfaces. Then the interception event is considered, whereby energy balance techniques are employed to instantaneously predict whether an impacting droplet will bounce, splash, or adhere to a leaf.

Why are students choosing STEM and when do they make their choice?

BACKGROUND OR CONTEXT The higher education sector plays an important role in encouraging students into the STEM pipeline through fostering partnerships with schools, building on universities long tradition in engagement and outreach to secondary schools. Numerous activities focus on integrated STEM learning experiences aimed at developing conceptual scientific and mathematical knowledge with opportunities for students to show and develop skills in working with each other and actively engaging in discussion, decision making and collaborative problem solving. (NAS, 2013; AIG, 2015; OCS, 2014). This highlights the importance of the development and delivery of engaging integrated STEM activities connected to the curriculum to inspire the next generation of scientists and engineers and generally preparing students for post-secondary success. The broad research objective is to gain insight into which engagement activities and to what level they influence secondary school students’ selection of STEM-related career choices at universities. PURPOSE OR GOAL To evaluate and determine the effectiveness of STEM engagement activities impacting student decision making in choosing a STEM-related degree choice at university. APPROACH A survey was conducted with first-year domestic students studying STEM-related fieldswithin the Science and Engineering Faculty at Queensland University of Technology. Of the domestic students commencing in 2015, 29% responded to the survey. The survey was conducted using Survey Monkey and included a variety of questions ranging from academic performance at school to inspiration for choosing a STEM degree. Responses were analysed on a range of factors to evaluate the influence on students’ decisions to study STEM and whether STEM high school engagement activities impacted these decisions. To achieve this the timing of decision making for students choice in study area, degree, and university is compared with the timing of STEM engagement activities. DISCUSSION Statistical analysis using SPSS was carried out on survey data looking at reasons for choosing STEM degrees in terms of gender, academic performance and major influencers in their decision making. It was found that students choose their university courses based on what subjects they enjoyed and exceled at in school. These results found a high correlation between enjoyment of a school subject and their interest in pursuing this subject at university and beyond. Survey results indicated students are heavily influenced by their subject teachers and parents in their choice of STEM-related disciplines. In terms of career choice and when students make their decision, 60% have decided on a broad area of study by year 10, whilst only 15% had decided on a specific course and 10% had decided on which university. The timing of secondary STEM engagement activities is seen as a critical influence on choosing STEM disciplines or selection of senior school subjects with 80% deciding on specific degree between year 11 and 12 and 73% making a decision on which university in year 12. RECOMMENDATIONS/IMPLICATIONS/CONCLUSION Although the data does not support that STEM engagement activities increase the likelihood of STEM-related degree choice, the evidence suggests the students who have participated in STEM activities associate their experiences with their choice to pursue a STEM-related course. It is important for universities to continue to provide quality engaging and inspirational learning experiences in STEM, to identify and build on students’ early interest and engagement, increase STEM knowledge and awareness, engage them in interdisciplinary project-based STEM practices, and provide them with real-world application experiences to sustain their interest.

Mathematical models of calcium and tight junctions in normal and reconstructed epidermis

This project investigated the calcium distributions of the skin, and the growth patterns of skin substitutes grown in the laboratory, using mathematical models. The research found that the calcium distribution in the upper layer of the skin is controlled by three different mechanisms, not one as previously thought. The research also suggests that tight junctions, which are adhesions between neighbouring skin cells, cannot be solely responsible for the differences in the growth patterns of skin substitutes and normal skin.

The importance of a precise definition, comprehensive model, and critical discussion of successful aging at work

It is crucial to advance understanding of the concept of successful aging at work to guide rigorous future research and effective practice. Drawing on the gerontology and life-span developmental literatures, I recently proposed a definition and theoretical framework of successful aging at work that revolve around employees increasingly deviating from average developmental trajectories across the working life span. Based on sustainability, person–job fit, and proactivity theories, Kooij suggested an alternative perspective that emphasizes the active role of employees for successful aging at work. In this article, I compare the 2 approaches and attempt a partial integration. I highlight the importance of a precise definition, comprehensive model, and critical discussion of successful aging at work. Furthermore, I suggest that person–environment fit variables other than person–job fit (e.g., person–organization fit) and adapting to person–environment misfit may also contribute to successful aging at work. Finally, I argue that proactive behaviors must have age-differential effects on work outcomes to be considered personal resources for successful aging at work.

Towards automated content analysis of discussion transcripts: A cognitive presence case

In this paper, we present the results of an exploratory study that examined the problem of automating content analysis of student online discussion transcripts. We looked at the problem of coding discussion transcripts for the levels of cognitive presence, one of the three main constructs in the Community of Inquiry (CoI) model of distance education. Using Coh-Metrix and LIWC features, together with a set of custom features developed to capture discussion context, we developed a random forest classification system that achieved 70.3% classification accuracy and 0.63 Cohen's kappa, which is significantly higher than values reported in the previous studies. Besides improvement in classification accuracy, the developed system is also less sensitive to overfitting as it uses only 205 classification features, which is around 100 times less features than in similar systems based on bag-of-words features. We also provide an overview of the classification features most indicative of the different phases of cognitive presence that gives an additional insights into the nature of cognitive presence learning cycle. Overall, our results show great potential of the proposed approach, with an added benefit of providing further characterization of the cognitive presence coding scheme.