Growth of confined cancer spheroids : a combined experimental marker, critical modelling approach

A critical step in the dissemination of ovarian cancer is the formation of multicellular spheroids from cells shed from the primary tumour. The objectives of this study were to apply bioengineered three-dimensional (3D) microenvironments for culturing ovarian cancer spheroids in vitro and simultaneously to build on a mathematical model describing the growth of multicellular spheroids in these biomimetic matrices. Cancer cells derived from human epithelial ovarian carcinoma were embedded within biomimetic hydrogels of varying stiffness and grown for up to 4 weeks. Immunohistochemistry, imaging and growth analyses were used to quantify the dependence of cell proliferation and apoptosis on matrix stiffness, long-term culture and treatment with the anti-cancer drug paclitaxel. The mathematical model was formulated as a free boundary problem in which each spheroid was treated as an incompressible porous medium. The functional forms used to describe the rates of cell proliferation and apoptosis were motivated by the experimental work and predictions of the mathematical model compared with the experimental output. This work aimed to establish whether it is possible to simulate solid tumour growth on the basis of data on spheroid size, cell proliferation and cell death within these spheroids. The mathematical model predictions were in agreement with the experimental data set and simulated how the growth of cancer spheroids was influenced by mechanical and biochemical stimuli including matrix stiffness, culture duration and administration of a chemotherapeutic drug. Our computational model provides new perspectives on experimental results and has informed the design of new 3D studies of chemoresistance of multicellular cancer spheroids.

Morphology-based model for predicting osteocyte-like cell line (MLO-Y4) growth process

This work has led to the development of empirical mathematical models to quantitatively predicate the changes of morphology in osteocyte-like cell lines (MLO-Y4) in culture. MLO-Y4 cells were cultured at low density and the changes in morphology recorded over 11 hours. Cell area and three dimensional shape features including aspect ratio, circularity and solidity were then determined using widely accepted image analysis software (ImageJTM). Based on the data obtained from the imaging analysis, mathematical models were developed using the non-linear regression method. The developed mathematical models accurately predict the morphology of MLO-Y4 cells for different culture times and can, therefore, be used as a reference model for analyzing MLO-Y4 cell morphology changes within various biological/mechanical studies, as necessary.

Posttraumatic growth and posttraumatic depreciation as predictors of psychological adjustment

Informed by current trauma literature, this study explored the relationships between Posttraumatic Growth (PTG; Tedeschi & Calhoun, 1995), Posttraumatic Depreciation (PTD; Cann et al., 2010) and other post-trauma outcomes including well-being, psychological flourishing, and psychological distress. The predictive utility of PTG and PTD was also examined. The sample comprised 104 trauma survivors who completed the Posttraumatic Growth Inventory – 42 (Baker et al., 2008) and several outcome measures. As expected, PTD showed strong linear correlations with well-being, flourishing and distress, and emerged as a significant predictor of scores on such measures. However, PTG showed negligible correlations with well-being, flourishing and distress. This reaffirms that PTG and PTD measure conceptually distinct and independent dimensions of experience, which has implications for therapeutic practice.

Working with refugee survivors of torture and trauma : an opportunity for vicarious posttraumatic growth

Clinical work with people who have survived trauma carries a risk of vicarious traumatisation for the service provider, but also the potential for vicarious posttraumatic growth. Despite growing interest in this area, the effects of working with survivors of refugee-related trauma have remained relatively unexplored. The aim of the current study was to examine the lived experiences of people working on a daily basis with survivors of torture and trauma who had sought refuge in Australia. Seventeen clinical, administrative, and managerial staff from a not-for-profit organisation participated in a semi-structured interview that was later analysed using interpretive phenomenological analysis. Analysis of the data demonstrated that the entire sample reported symptoms of vicarious trauma (e.g., strong emotional reactions, intrusive images, shattering of existing beliefs) as well as vicarious posttraumatic growth (e.g., forming new relationships, increased self-understanding, greater appreciation of life). Moreover, effortful meaning making processes appeared to facilitate such positive changes. Reduction in the risks associated with this work, enhancement of clinician well-being, and improvement of therapeutic outcomes is a shared responsibility of the organisation and clinician. Without negating the distress of trauma work, clinicians are encouraged to more deeply consider the unique positive outcomes that supporting survivors can provide.

Mentoring as professional development: ‘growth for both’ mentor and mentee

Teachers need professional development to keep current with teaching practices, although costs for extensive professional development can be prohibitive across an education system. Mentoring provides one way for embedding cost-effective professional development. This mixed-method study includes surveying mentor teachers (n = 101) on a five-part Likert scale and interviews with experienced mentors (n = 10) to investigate professional development for mentors as a result of the mentoring process. Quantitative data were analysed through a pedagogical knowledge framework and qualitative data were collated into themes. Survey data showed that although mentoring of pedagogical knowledge was variable, mentoring pedagogical knowledge practices occurs with the majority of mentors, which requires mentors to evaluate and articulate teaching practices. Qualitative data showed that mentoring acted as professional development and led towards enhancing communication skills, developing leadership roles (problem-solving and building capacity) and advancing pedagogical knowledge. Providing professional development to teachers on mentoring can help to build capacity in two ways: quality mentoring of preservice teachers through explicit mentoring practices, and reflecting and deconstructing teaching practices for mentors’ own pedagogical advancements.

Contribution of knowledge management activities to organisational business performance

Purpose – Within the construction industry there is a growing awareness of the need for linking knowledge management (KM) to business strategy, organisational objectives and existing performance measures. This study was undertaken within the context of construction organisations, and attempts to provide the empirical evidence about the relationships between KM activities and organisational business performance. Design/methodology/approach – A questionnaire survey was administered to a sample of construction contractors operating in Hong Kong to investigate the opinions of construction professionals regarding the intensity of KM activities and business performance within their organisations. In parallel to the survey, semi-structured interviews were undertaken to provide qualitative insights that helped to clarify and deepen understanding of the KM process within the context of the research target. Findings – The investigation shows that knowledge utilisation is the strongest contributor to general business performance. In addition, the impact of KM activities on the lagging performance indicators of the Balanced Scorecard (BSC), such as “financial performance”, is in an indirect manner, and through the leading indicators such as performance from “internal process” as well as “learning and growth” perspectives. Originality/value – The study empirically establishes the linkage between intensity of KM activities and business performance, and demonstrates that KM strategies need to be explicitly formulated and measured according to organisational business objectives.

Designing a new robust on-line secondary path modeling technique for feedforward active noise control systems

Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.

An efficient online secondary path estimation for feedback active noise control systems

In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.

New Perspectives On Firm Growth

This insightful volume presents a collection of innovative works by two of the leading researchers of firm growth: Per Davidsson, Director, Australian Centre for Entrepreneurship Research and Professor of Entrepreneurship, Queensland University of Technology, Australia and Jönköping International Business School, Sweden and Johan Wiklund, Professor of Entrepreneurship, Syracuse University, US and Jönköping International Business School, Sweden. The studies extend previous research by providing stronger theoretical underpinnings and using longitudinal databases that can separate in time the firms’ growth from its presumed causes. They also break new ground by examining different modes of growth, such as sales growth vs. employment growth, and organic growth vs. acquisition-based expansion. Further, the studies investigate the drivers of firm growth and take a critical look at the effects, such as under what circumstances high growth is associated with high profitability. The issue of how firm growth is achieved and managed, and what consequences it has for different stakeholders is both theoretically interesting and practically important. The book will strongly appeal to academics of entrepreneurship, small business management and strategy.

Sensitivity of peak positions to flight-path parameters in a deep-inelastic scattering neutron TOF spectrometer

The effects of small changes in flight-path parameters (primary and secondary flight paths, detector angles), and of displacement of the sample along the beam axis away from its ideal position, are examined for an inelastic time-of-flight (TOF) neutron spectrometer, emphasising the deep-inelastic regime. The aim was to develop a rational basis for deciding what measured shifts in the positions of spectral peaks could be regarded as reliable in the light of the uncertainties in the calibrated flight-path parameters. Uncertainty in the length of the primary or secondary flight path has the least effect on the positions of the peaks of H, D and He, which are dominated by the accuracy of the calibration of the detector angles. This aspect of the calibration of a TOF spectrometer therefore demands close attention to achieve reliable outcomes where the position of the peaks is of significant scientific interest and is discussed in detail. The corresponding sensitivities of the position of peak of the Compton profile, J(y), to flight-path parameters and sample position are also examined, focusing on the comparability across experiments of results for H, D and He. We show that positioning the sample to within a few mm of the ideal position is required to ensure good comparability between experiments if data from detectors at high forward angles are to be reliably interpreted.

Coordination of UAV path planning in 2D and 3D in environmental/bio sensing applications

This paper is concerned with the optimal path planning and initialization interval of one or two UAVs in presence of a constant wind. The method compares previous literature results on synchronization of UAVs along convex curves, path planning and sampling in 2D and extends it to 3D. This method can be applied to observe gas/particle emissions inside a control volume during sampling loops. The flight pattern is composed of two phases: a start-up interval and a sampling interval which is represented by a semi-circular path. The methods were tested in four complex model test cases in 2D and 3D as well as one simulated real world scenario in 2D and one in 3D.

Adaptive dynamic path re-planning RRT algorithms with game theory for UAVs

The main aim of this paper is to describe an adaptive re-planning algorithm based on a RRT and Game Theory to produce an efficient collision free obstacle adaptive Mission Path Planner for Search and Rescue (SAR) missions. This will provide UAV autopilots and flight computers with the capability to autonomously avoid static obstacles and No Fly Zones (NFZs) through dynamic adaptive path replanning. The methods and algorithms produce optimal collision free paths and can be integrated on a decision aid tool and UAV autopilots.

From outpost to outback : project career paths in Australia

With the growth in project management as a form of work organisation in many sectors of the economy has come the significant rise in the number of project managers and project team members. This change in work organisation brings issues in forging career paths and determining career support in work situations that are often dynamic, short lived and intense. In the relatively small but substantially robust Australian economy, a unique labour market and the tyranny of distance bring their own difficulties. Innovative and collaborative project structures and increasing prevalence of contract work provide both challenges and opportunities for new career pathways in many industries. A growing percentage of Australia's workforce is employed in project-based or project-oriented organisations, leading to the claim that Australia is a project-based economy. This provided a context for our research into the career paths and the issues of career management for project managers working in a project based economy. Using in-depth interviews with project managers from three industry areas we found generational and gender differences in experiences of work, workplace support and mentoring for career development. For a continued strong performance in this economy,organisations that employ project personnel will need to consider how they will ensure the supply of high quality project professionals into the future.

A variable step-size FxLMS algorithm for feedforward active noise control systems based on a new online secondary path modelling technique

Several approaches have been introduced in literature for active noise control (ANC) systems. Since FxLMS algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANC applications an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. This paper also proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Benefiting new version of FxLMS algorithm and not continually injection of white noise makes the system more desirable and improves the noise attenuation performance. Comparative simulation results indicate effectiveness of the proposed approach.

A new online secondary path modelling method for feedforward active noise control systems

An online secondary path modelling method using a white noise as a training signal is required in many applications of active noise control (ANC) to ensure convergence of the system. Not continually injection of white noise during system operation makes the system more desirable. The purposes of the proposed method are two folds: controlling white noise by preventing continually injection, and benefiting white noise with a larger variance. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. This paper proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. Comparative simulation results shown in this paper indicate effectiveness of the proposed approach in controlling active noise.