Dynamic Bayesian network inferencing for non-homogeneous complex systems

Dynamic Bayesian Networks (DBNs) provide a versatile platform for predicting and analysing the behaviour of complex systems. As such, they are well suited to the prediction of complex ecosystem population trajectories under anthropogenic disturbances such as the dredging of marine seagrass ecosystems. However, DBNs assume a homogeneous Markov chain whereas a key characteristics of complex ecosystems is the presence of feedback loops, path dependencies and regime changes whereby the behaviour of the system can vary based on past states. This paper develops a method based on the small world structure of complex systems networks to modularise a non-homogeneous DBN and enable the computation of posterior marginal probabilities given evidence in forwards inference. It also provides an approach for an approximate solution for backwards inference as convergence is not guaranteed for a path dependent system. When applied to the seagrass dredging problem, the incorporation of path dependency can implement conditional absorption and allows release from the zero state in line with environmental and ecological observations. As dredging has a marked global impact on seagrass and other marine ecosystems of high environmental and economic value, using such a complex systems model to develop practical ways to meet the needs of conservation and industry through enhancing resistance and/or recovery is of paramount importance.

The navigation and visualisation of environmental audio using zooming spectrograms

Acoustic recordings play an increasingly important role in monitoring terrestrial and aquatic environments. However, rapid advances in technology make it possible to accumulate thousands of hours of recordings, more than ecologists can ever listen to. Our approach to this big-data challenge is to visualize the content of long-duration audio recordings on multiple scales, from minutes, hours, days to years. The visualization should facilitate navigation and yield ecologically meaningful information prior to listening to the audio. To construct images, we calculate acoustic indices, statistics that describe the distribution of acoustic energy and reflect content of ecological interest. We combine various indices to produce false-color spectrogram images that reveal acoustic content and facilitate navigation. The technical challenge we investigate in this work is how to navigate recordings that are days or even months in duration. We introduce a method of zooming through multiple temporal scales, analogous to Google Maps. However, the “landscape” to be navigated is not geographical and not therefore intrinsically visual, but rather a graphical representation of the underlying audio. We describe solutions to navigating spectrograms that range over three orders of magnitude of temporal scale. We make three sets of observations: 1. We determine that at least ten intermediate scale steps are required to zoom over three orders of magnitude of temporal scale; 2. We determine that three different visual representations are required to cover the range of temporal scales; 3. We present a solution to the problem of maintaining visual continuity when stepping between different visual representations. Finally, we demonstrate the utility of the approach with four case studies.

Regenerative sustainability for the built environment – from vision to reality: An introductory chapter

Regenerative sustainability is emerging as an alternative discourse around the transition from a ‘mechanistic’ to an ‘ecological’ or living systems worldview. This view helps us to re-conceptualize relationships among humans’ technological, ecological, economic, social and political systems. Through exploration of ‘net positive’ or ‘regenerative’ development lenses and the traditional sustainability literature, the conceptualization and approaches to achieve sustainable development and ecological modernization are expanded to articulate and to explore the evolving sustainability discourse, ‘regenerative sustainability’. This Special Volume of Journal of Cleaner Production (SV) is focused upon various dimensions of regenerative sustainability (e.g. regenerative design, regenerative development, and positive development) applied to the urban built environment at scales, which range from individual buildings, neighborhoods, and urban developments to integrated regional sustainable development. The main focus is on how these approaches and developments are evolving, how they can help us to prevent or adapt to climate change and how these approaches are likely to evolve in the next two to three decades. These approaches are addressed in four themes: (1) reviewing the theoretical development of the discourse of regenerative sustainability, its emerging principles and practices, (2) explaining how it can be measured and monitored, (3) providing encouraging practical pathways and examples of its implementation in multiple cultural and climatic contexts, and (4) mapping obstacles and enablers that must be addressed to help to ensure that more rapid progress is made in implementing the transitions towards an urban built environment that supports genuinely sustainable societies.

Information sharing in distance collaboration: A software engineering perspective

Information sharing in distance collaboration: A software engineering perspective, QueenslandFactors in software engineering workgroups such as geographical dispersion and background discipline can be conceptually characterized as "distances", and they are obstructive to team collaboration and information sharing. This thesis focuses on information sharing across multidimensional distances and develops an information sharing distance model, with six core dimensions: geography, time zone, organization, multi-discipline, heterogeneous roles, and varying project tenure. The research suggests that the effectiveness of workgroups may be improved through mindful conducts of information sharing, especially proactive consideration of, and explicit adjustment for, the distances of the recipient when sharing information.

Monitoring healing progression and characterizing the mechanical environment in preclinical models for bone tissue engineering

The treatment of large segmental bone defects remains a significant clinical challenge. Due to limitations surrounding the use of bone grafts, tissue-engineered constructs for the repair of large bone defects could offer an alternative. Before translation of any newly developed tissue engineering (TE) approach to the clinic, efficacy of the treatment must be shown in a validated preclinical large animal model. Currently, biomechanical testing, histology, and microcomputed tomography are performed to assess the quality and quantity of the regenerated bone. However, in vivo monitoring of the progression of healing is seldom performed, which could reveal important information regarding time to restoration of mechanical function and acceleration of regeneration. Furthermore, since the mechanical environment is known to influence bone regeneration, and limb loading of the animals can poorly be controlled, characterizing activity and load history could provide the ability to explain variability in the acquired data sets and potentially outliers based on abnormal loading. Many approaches have been devised to monitor the progression of healing and characterize the mechanical environment in fracture healing studies. In this article, we review previous methods and share results of recent work of our group toward developing and implementing a comprehensive biomechanical monitoring system to study bone regeneration in preclinical TE studies.

Adaptive frequency scaled wavelet packet decomposition for frog call classification

Environmental changes have put great pressure on biological systems leading to the rapid decline of biodiversity. To monitor this change and protect biodiversity, animal vocalizations have been widely explored by the aid of deploying acoustic sensors in the field. Consequently, large volumes of acoustic data are collected. However, traditional manual methods that require ecologists to physically visit sites to collect biodiversity data are both costly and time consuming. Therefore it is essential to develop new semi-automated and automated methods to identify species in automated audio recordings. In this study, a novel feature extraction method based on wavelet packet decomposition is proposed for frog call classification. After syllable segmentation, the advertisement call of each frog syllable is represented by a spectral peak track, from which track duration, dominant frequency and oscillation rate are calculated. Then, a k-means clustering algorithm is applied to the dominant frequency, and the centroids of clustering results are used to generate the frequency scale for wavelet packet decomposition (WPD). Next, a new feature set named adaptive frequency scaled wavelet packet decomposition sub-band cepstral coefficients is extracted by performing WPD on the windowed frog calls. Furthermore, the statistics of all feature vectors over each windowed signal are calculated for producing the final feature set. Finally, two well-known classifiers, a k-nearest neighbour classifier and a support vector machine classifier, are used for classification. In our experiments, we use two different datasets from Queensland, Australia (18 frog species from commercial recordings and field recordings of 8 frog species from James Cook University recordings). The weighted classification accuracy with our proposed method is 99.5% and 97.4% for 18 frog species and 8 frog species respectively, which outperforms all other comparable methods.

Developing an evolutionary/ecological approach in enterprise education

This paper presents an ecological/evolutionary approach to enterprise education. Ecological approaches are used at the University of Tasmania to heighten the awareness of students to a raft of difficult to observe environmental factors associated with developing enterprising ideas. At Sheffield University, the discovery and exploitation of entrepreneurial opportunities is viewed as a co-evolving system of emerging business ideas, and routines/heuristics respectively. It is argued that using both approaches enables students to develop a greater awareness of their situated environment, and ultimately the degree of fit between their learning process and a changing external world. The authors argue that in order to improve the chances of longer-term survival what is needed is a new level of organisation where the individual is capable of developing a representation of the external world that he or she can use to sense the appropriateness of local decisions. This reinterpretation of events allows individuals to step back and examine the broader consequences of their actions through the interpretation and anticipation of feedback from the environment. These approaches thus seek to develop practice-based heuristics which individuals can use to make sense of their lived experiences, as they learn to evolve in an increasingly complex world.

Plasma polymer and biomolecule modification of 3-D scaffolds for tissue engineering

Plasma polymerization was used to coat a melt electrospun polycaprolactone scaffold to improve cell attachment and organization. Plasma polymerization was performed using an amine containing monomer, allylamine, which then allowed for the subsequent immobilization of biomolecules i.e. heparin and fibroblast growth factor-2. The stability of the plasma polymerized amine-coating was demonstrated by X-ray photoelectron spectroscopy analysis and imaging time-of-flight secondary ion mass spectrometry revealed that a uniform plasma amine-coating was deposited throughout the scaffold. Based upon comparison with controls it was evident that the combination scaffold aided cell ingress and the formation of distinct fibroblast and keratinocyte layers.

Assessing the integrated sustainability of a public rental housing project from the perspective of complex eco-system

Public rental housing (PRH) projects are the mainstream of China's new affordable housing policies, and their integrated sustainability has a far-reaching effect on medium-low income families' well-being and social stability. However, there are few quantitative researches on the integrated sustainability of PRH projects. Our study tries to fill this gap through proposing an assessment model of the integrated sustainability for PRH projects. First, this paper defines what the sustainability of a PRH project is. Second, after constructing the sustainable system of a PRH project from the perspective of complex eco-system, the paper explores the internal operation mechanism and the coupling mechanism among the ecological, economic and social subsystems. Third, it identifies fourteen indices to represent the sustainability system of a PRH project, including six indices of ecological subsystem, five of economic subsystem and three of social subsystem. Fourth, it qualifies the weights of three subsystems and their internal representative indices. In addition, an assessment model is established through expert surveys and analytic network process (ANP). Finally, the paper carries out an empirical research on a PRH project in Nanjing city of China, followed by suggestions to enhance the integrated sustainability. The sustainability system and its evaluation model proposed in this paper are concise and easy to understand and can provide a theoretical foundation and a scientific basis for the evaluation and optimization of PRH projects.

Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Learning style and digital activity: An ecological study

In order to understand student engagement in higher education through the use of digital technologies, it is necessary to appreciate the broader use of differing technologies. Forty-eight first-year university students completed an online survey that queried patterns of digital activity across home, school and community contexts and that included rating scale items that measured learning style (i.e., active-reflective, sensing-intuitive, visual-verbal, sequential-global). Results suggest that students vary widely in digital activities and that such variation is related to differences in learning style. For example, active learners were more likely than reflective learners to engage in digital activities in the community and users of some specific application, as opposed to non-users, were more likely to be verbal than visual learners. Implications for instructional applications of digital technology in higher education are presented.

Quarantine and surveillance strategies for plant pathogen detection and control

Incursions of plant pests and diseases pose serious threats to food security, agricultural productivity and the natural environment. One of the challenges in confidently delimiting and eradicating incursions is how to choose from an arsenal of surveillance and quarantine approaches in order to best control multiple dispersal pathways. Anthropogenic spread (propagules carried on humans or transported on produce or equipment) can be controlled with quarantine measures, which in turn can vary in intensity. In contrast, environmental spread processes are more difficult to control, but often have a temporal signal (e.g. seasonality) which can introduce both challenges and opportunities for surveillance and control. This leads to complex decisions regarding when, where and how to search. Recent modelling investigations of surveillance performance have optimised the output of simulation models, and found that a risk-weighted randomised search can perform close to optimally. However, exactly how quarantine and surveillance strategies should change to reflect different dispersal modes remains largely unaddressed. Here we develop a spatial simulation model of a plant fungal-pathogen incursion into an agricultural region, and its subsequent surveillance and control. We include structural differences in dispersal via the interplay of biological, environmental and anthropogenic connectivity between host sites (farms). Our objective was to gain broad insights into the relative roles played by different spread modes in propagating an invasion, and how incorporating knowledge of these spread risks may improve approaches to quarantine restrictions and surveillance. We find that broad heuristic rules for quarantine restrictions fail to contain the pathogen due to residual connectivity between sites, but surveillance measures enable early detection and successfully lead to suppression of the pathogen in all farms. Alternative surveillance strategies attain similar levels of performance by incorporating environmental or anthropogenic dispersal risk in the prioritisation of sites. Our model provides the basis to develop essential insights into the effectiveness of different surveillance and quarantine decisions for fungal pathogen control. Parameterised for authentic settings it will aid our understanding of how the extent and resolution of interventions should suitably reflect the spatial structure of dispersal processes.

An engineering or behavioural approach? A study into employee’s perceptions regarding the effectiveness of occupational road safety initiatives

Background and Aims Considerable variation has been documented with fleet safety interventions’ abilities to create lasting behavioural change, and research has neglected to consider employees’ perceptions regarding the effectiveness of fleet interventions. This is a critical oversight as employees’ beliefs and acceptance levels (as well as the perceived organisational commitment to safety) can ultimately influence levels of effectiveness, and this study aimed to examine such perceptions in Australian fleet settings. Method 679 employees sourced from four Australian organisations completed a safety climate questionnaire as well as provided perspectives about the effectiveness of 35 different safety initiatives. Results Countermeasures that were perceived as most effective were a mix of human and engineering-based approaches: - (a) purchasing safer vehicles; - (b) investigating serious vehicle incidents, and; - (c) practical driver skills training. In contrast, least effective countermeasures were considered to be: - (a) signing a promise card; - (b) advertising a company’s phone number on the back of cars for complaints and compliments, and; - (c) communicating cost benefits of road safety to employees. No significant differences in employee perceptions were identified based on age, gender, employees’ self-reported crash involvement or employees’ self-reported traffic infringement history. Perceptions of safety climate were identified to be “moderate” but were not linked to self-reported crash or traffic infringement history. However, higher levels of safety climate were positively correlated with perceived effectiveness of some interventions. Conclusion Taken together, employees believed occupational road safety risks could best be managed by the employer by implementing a combination of engineering and human resource initiatives to enhance road safety. This paper will further outline the key findings in regards to practice as well as provide direction for future research.

User centred design for engineering e-government web usability

E-government provides a platform for governments to implement web enabled services that facilitate communication between citizens and the government. However, technology driven design approach and limited understanding of citizens' requirements, have led to a number of critical usability problems on the government websites. Hitherto, there has been no systematic attempt to analyse the way in which theory of User Centred Design (UCD) can contribute to address the usability issues of government websites. This research seeks to fill this gap by synthesising perspectives drawn from the study of User Centred Design and examining them based on the empirical data derived from case study of the Scottish Executive website. The research employs a qualitative approach in the collection and analysis of data. The triangulated analysis of the findings reveals that e-government web designers take commercial development approach and focus only on technical implementations which lead to websites that do not meet citizens' expectations. The research identifies that e-government practitioners can overcome web usability issues by transferring the theory of UCD to practice.

Growth factor-loaded microparticles for tissue engineering: The discrepancies of in vitro characterization assays

Efficient and effective growth factor (GF) delivery is an ongoing challenge for tissue regeneration therapies. The accurate quantification of complex molecules such as GFs, encapsulated in polymeric delivery devices, is equally critical and just as complex as achieving efficient delivery of active GFs. In this study, GFs relevant to bone tissue formation, vascular endothelial growth factor (VEGF) and bone morphogenetic protein 7 (BMP-7), were encapsulated, using the technique of electrospraying, into poly(lactic-co-glycolic acid) microparticles that contained poly(ethylene glycol) and trehalose to assist GF bioactivity. Typical quantification procedures, such as extraction and release assays using saline buffer, generated a significant degree of GF interactions, which impaired accurate assessment by enzyme-linked immunosorbent assay (ELISA). When both dry BMP-7 and VEGF were processed with chloroform, as is the case during the electrospraying process, reduced concentrations of the GFs were detected by ELISA; however, the biological effect on myoblast cells (C2C12) or endothelial cells (HUVECs) was unaffected. When electrosprayed particles containing BMP-7 were cultured with preosteoblasts (MC3T3-E1), significant cell differentiation into osteoblasts was observed up to 3 weeks in culture, as assessed by measuring alkaline phosphatase. In conclusion, this study showed how electrosprayed microparticles ensured efficient delivery of fully active GFs relevant to bone tissue engineering. Critically, it also highlights major discrepancies in quantifying GFs in polymeric microparticle systems when comparing ELISA with cell-based assays.