A density functional theory study on CO2 capture and activation by graphene-like boron nitride with boron vacancy

First principle calculations for a hexagonal (graphene-like) boron nitride (g-BN) monolayer sheet in the presence of a boron-atom vacancy show promising properties for capture and activation of carbon dioxide. CO2 is found to decompose to produce an oxygen molecule via an intermediate chemisorption state on the defect g-BN sheet. The three stationary states and two transition states in the reaction pathway are confirmed by minimum energy pathway search and frequency analysis. The values computed for the two energy barriers involved in this catalytic reaction after enthalpy correction indicate that the catalytic reaction should proceed readily at room temperature.

Adsorption of carbon dioxide and nitrogen on single-layer aluminum nitride nanostructures studied by density functional theory

The adsorption of carbon dioxide and nitrogen molecules on aluminum nitride (AlN) nanostructures has been explored using first-principle computational methods. Optimized configurations corresponding to physisorption and, subsequentially, chemisorption of CO2 are identified, in contrast to N2, for which only a physisorption structure is found. Transition-state searches imply a low energy barrier between the physisorption and chemisorption states for CO2 such that the latter is accessible and thermodynamically favored at room temperature. The effective binding energy of the optimized chemisorption structure is apparently larger than those for other CO2 adsorptive materials, suggesting the potential for application of aluminum nitride nanostructures for carbon dioxide capture and storage.

Cometary evolution : clues on physical properties from chondritic interplanetary dust particles

The degree of diversity or similarity detected in comets depends primarily on the lifetimes of the individual cometary nuclei at the time of analysis. It is inherent in our understanding of cometary orbital dynamics and the seminal model of comet origins that cometary evolution is the natural order of events in our Solar System. Thus, predictions of cometary behaviour in terms of bulk physical, mineralogical or chemical parameters should contain an appreciation of temporal variation(s). Previously, Rietmeijer and Mackinnon [1987] developed mineralogical bases for the chemical evolution of cometary nuclei primarily with regard to the predominantly silicate fraction of comet nuclei. We suggested that alteration of solids in cometary nuclei should be expected and that indications of likely reactants and products can be derived from judicious comparison with terrestrial diagenetic environments which include hydrocryogenic and low-temperature aqueous alterations. In a further development of this concept, Rietmeijer [1988] provides indirect evidence for the formation of sulfides and oxides in comet nuclei. Furthermore, Rietmeijer [1988] noted that timescales for hydrocryogenic and low-temperature reactions involving liquid water are probably adequate for relatively mature comets, e.g. P/comet Halley. In this paper, we will address the evolution of comet nuclei physical parameters such as solid particle grain size, porosity and density. In natural environments, chemical evolution (e.g. mineral reactions) is often accompanied by changes in physical properties. These concurrent changes are well-documented in the terrestrial geological literature, especially in studies of sediment diagenesis and we suggest that similar basic principles apply within the upper few meters of active comet nuclei. The database for prediction of comet nuclei physical parameters is, in principle, the same as used for the proposition of chemical evolution. We use detailed mineralogical studies of chondritic interplanetary dust particles (IDPS) as a guide to the likely constitution of mature comets traversing the inner Solar System. While there is, as yet, no direct proof that a specific sub-group or type of chondritic IDP is derived from a specific comet, it is clear that these particles are extraterrestrial in origin and that a certain portion of the interplanetary flux received by the Earth is cometary in origin. Two chondritic porous (CP) IDPS, sample numbers W701OA2 and W7029CI, from the Johnson Space Center Cosmic Dust Collection have been selected for this study of putative cometary physical parameters. This particular type of particle is considered a likely candidate for a cometary origin on the basis of mineralogy, bulk composition and morphology. While many IDPs have been subjected to intensive study over the past decade, we can develop a physical parameter model on only these two CP IDPs because few others have been studied in sufficient detail.

Assessing the suitability of existing spatial data for disaster planning and mitigation in Queensland

The Council of Australian Governments (COAG) in 2003 gave in-principle approval to a best-practice report recommending a holistic approach to managing natural disasters in Australia incorporating a move from a traditional response-centric approach to a greater focus on mitigation, recovery and resilience with community well-being at the core. Since that time, there have been a range of complementary developments that have supported the COAG recommended approach. Developments have been administrative, legislative and technological, both, in reaction to the COAG initiative and resulting from regular natural disasters. This paper reviews the characteristics of the spatial data that is becoming increasingly available at Federal, state and regional jurisdictions with respect to their being fit for the purpose for disaster planning and mitigation and strengthening community resilience. In particular, Queensland foundation spatial data, which is increasingly accessible by the public under the provisions of the Right to Information Act 2009, Information Privacy Act 2009, and recent open data reform initiatives are evaluated. The Fitzroy River catchment and floodplain is used as a case study for the review undertaken. The catchment covers an area of 142,545 km2, the largest river catchment flowing to the eastern coast of Australia. The Fitzroy River basin experienced extensive flooding during the 2010–2011 Queensland floods. The basin is an area of important economic, environmental and heritage values and contains significant infrastructure critical for the mining and agricultural sectors, the two most important economic sectors for Queensland State. Consequently, the spatial datasets for this area play a critical role in disaster management and for protecting critical infrastructure essential for economic and community well-being. The foundation spatial datasets are assessed for disaster planning and mitigation purposes using data quality indicators such as resolution, accuracy, integrity, validity and audit trail.

Automated marine mammal detection from aerial imagery

This paper presents two algorithms to automate the detection of marine species in aerial imagery. An algorithm from an initial pilot study is presented in which morphology operations and colour analysis formed the basis of its working principle. A second approach is presented in which saturation channel and histogram-based shape profiling were used. We report on performance for both algorithms using datasets collected from an unmanned aerial system at an altitude of 1000 ft. Early results have demonstrated recall values of 48.57% and 51.4%, and precision values of 4.01% and 4.97%.

Molecular dynamics simulation of fracture strength and morphology of defective graphene

Different types of defects can be introduced into graphene during material synthesis, and significantly influence the properties of graphene. In this work, we investigated the effects of structural defects, edge functionalisation and reconstruction on the fracture strength and morphology of graphene by molecular dynamics simulations. The minimum energy path analysis was conducted to investigate the formation of Stone-Wales defects. We also employed out-of-plane perturbation and energy minimization principle to study the possible morphology of graphene nanoribbons with edge-termination. Our numerical results show that the fracture strength of graphene is dependent on defects and environmental temperature. However, pre-existing defects may be healed, resulting in strength recovery. Edge functionalization can induce compressive stress and ripples in the edge areas of graphene nanoribbons. On the other hand, edge reconstruction contributed to the tensile stress and curved shape in the graphene nanoribbons.

Modelling the information seeking user by the decision they make

The article focuses on how the information seeker makes decisions about relevance. It will employ a novel decision theory based on quantum probabilities. This direction derives from mounting research within the field of cognitive science showing that decision theory based on quantum probabilities is superior to modelling human judgements than standard probability models [2, 1]. By quantum probabilities, we mean decision event space is modelled as vector space rather than the usual Boolean algebra of sets. In this way,incompatible perspectives around a decision can be modelled leading to an interference term which modifies the law of total probability. The interference term is crucial in modifying the probability judgements made by current probabilistic systems so they align better with human judgement. The goal of this article is thus to model the information seeker user as a decision maker. For this purpose, signal detection models will be sketched which are in principle applicable in a wide variety of information seeking scenarios.

Displacement motion prediction of a landing deck for recovery operations of rotary UAVs

This paper proposes a practical prediction procedure for vertical displacement of a Rotarywing Unmanned Aerial Vehicle (RUAV) landing deck in the presence of stochastic sea state disturbances. A proper time series model tending to capture characteristics of the dynamic relationship between an observer and a landing deck is constructed, with model orders determined by a novel principle based on Bayes Information Criterion (BIC) and coefficients identified using the Forgetting Factor Recursive Least Square (FFRLS) method. In addition, a fast-converging online multi-step predictor is developed, which can be implemented more rapidly than the Auto-Regressive (AR) predictor as it requires less memory allocations when updating coefficients. Simulation results demonstrate that the proposed prediction approach exhibits satisfactory prediction performance, making it suitable for integration into ship-helicopter approach and landing guidance systems in consideration of computational capacity of the flight computer.

Evolution and innovation in guardianship laws: Assisted decision-making

Guardianship laws in most Western societies provide decision-making mechanisms for adults with impaired capacity. Since the inception of these laws, the principle of autonomy and recognition of human rights for those coming within guardianship regimes has gained prominence. A new legal model has emerged, which seeks to incorporate ‘assisted decision-making’ models into guardianship laws. Such models legally recognise that an adult’s capacity may be maintained through assistance or support provided by another person, and provide formal recognition of the person in that ‘assisting’ role. This article situates this latest legal innovation within a historical context, examining the social and legal evolution of guardianship laws and determining whether modern assisted decision-making models remain consistent with guardianship reform thus far. It identifies and critically analyses the different assisted decision-making models which exist internationally. Finally, it discusses a number of conceptual, legal and practical concerns that remain unresolved. These issues require serious consideration before assisted decisionmaking models are adopted in guardianship regimes in Australia.

Responding to a transformative stressor : climate change and the institutional governance of Australian cities

This paper understands climate change as a transformative stressor that will prompt responses from institutional governance frameworks in Australian cities. A transformative stressor is characterised as a chronic large-scale phenomenon which triggers a process of institutional change whereby institutions seek to reorientate their activities to better manage the social, economic and environmental impacts created by the transformative dynamic. It is posited that institutional change will be required as Australian metropolitan institutional governance frameworks seek to manage climate change effects in urban environments. It is argued that improved operationalisation of adaptation is required as part of a comprehensive urban response to the transformative stresses climate change and its effects are predicted to create in Australian cities. The operationalisation of adaptation refers to adaptation becoming incorporated, codified and implemented as a central principle of metro-regional planning governance. This paper has three key purposes. First, it examines theoretical and conceptual understandings of the role of transformative stressors in compelling institutional change within urban settings. Second, it establishes a conceptual approach that understands climate change as a transformative stressor requiring institutional change within the metropolitan planning frameworks of Australia's cities. Third, it offers early results and conclusions from an empirical investigation into the current prospects for operationalisation of climate adaptation in planning programs within Southeast Queensland (SEQ) via changes to institutional governance. A significant emerging conclusion is that early climate stresses appear not to be leading to episodic institutional change in the metropolitan planning frameworks of SEQ.

Operationalising climate adaptation through institutional change : conceptual and empirical insights

Adaptation is increasingly understood as a necessary response in respect of climate change impacts on urban settlements. Australia is heavily urbanised and climate change is likely to impact severely on its urban environments. Accordingly, climate adaptation must become a key component of urban management. This paper is part of a wider project and reports early insights into the problem of how adaptation may be institutionally operationalised within a planning regime. In this instance, the operationalisation of adaptation refers to adaptation becoming incorporated, codified and implemented as a central principle of planning governance. This paper has three key purposes: first, to set out a conceptual approach to climate adaptation as an institutional challenge; second, to identify the intersection of this problem with planning; third, to report on an on-going empirical investigation in Southeast Queensland (SEQ). Informed by key social scientific theories of institutionalism, this paper develops a conceptual framework that understands the metro-regional planning system of SEQ as an institutional regime capable of undergoing a process of change to respond to the adaptation imperative. It is posited that the success or failure of the SEQ regime’s response to the adaptation imperative is contingent on its ability to undergo institutional change. A capacity for change in this regard is understood to be subject to the influence of various internal and external barriers and pathways that promote or hinder processes of institutional change. Specific attention is paid to the role of ‘storylines’ in facilitating or blocking institutional change.

Communicating personal amnesty : a model for health promotion in an Australian disability context

Currently pathological and illness-centric policy surrounds the evaluation of the health status of a person experiencing disability. In this research partnerships were built between disability service providers, community development organizations and disability arts organizations to build a translational evaluative methodology prior to implementation of an arts-based workshop that was embedded in a strengths-based approach to health and well-being. The model consisted of three foci: participation in a pre-designed drama-based workshop program; individualized assessment and evaluation of changing health status; and longitudinal analysis of participants changing health status in their public lives following the culmination of the workshop series. Participants (n = 15) were recruited through disability service providers and disability arts organizations to complete a 13-week workshop series and public performance. The study developed accumulative qualitative analysis tools and member-checking methods specific to the communication systems used by individual participants. Principle findings included increased confidence for verbal and non-verbal communicators; increased personal drive, ambition and goal-setting; increased arts-based skills including professional engagements as artists; demonstrated skills in communicating perceptions of health status to private and public spheres. Tangential positive observations were evident in the changing recreational, vocational and educational activities participants engaged with pre- and post- the workshop series; participants advocating for autonomous accommodation and health provision and changes in the disability service staff's culture. The research is an example of translational health methodologies in disability studies.

Econometric Modelling with Time Series : Specification, Estimation and Testing

This book provides a general framework for specifying, estimating, and testing time series econometric models. Special emphasis is given to estimation by maximum likelihood, but other methods are also discussed, including quasi-maximum likelihood estimation, generalized method of moments estimation, nonparametric estimation, and estimation by simulation. An important advantage of adopting the principle of maximum likelihood as the unifying framework for the book is that many of the estimators and test statistics proposed in econometrics can be derived within a likelihood framework, thereby providing a coherent vehicle for understanding their properties and interrelationships. In contrast to many existing econometric textbooks, which deal mainly with the theoretical properties of estimators and test statistics through a theorem-proof presentation, this book squarely addresses implementation to provide direct conduits between the theory and applied work.

Scene invariant multi camera crowd counting

Automated crowd counting has become an active field of computer vision research in recent years. Existing approaches are scene-specific, as they are designed to operate in the single camera viewpoint that was used to train the system. Real world camera networks often span multiple viewpoints within a facility, including many regions of overlap. This paper proposes a novel scene invariant crowd counting algorithm that is designed to operate across multiple cameras. The approach uses camera calibration to normalise features between viewpoints and to compensate for regions of overlap. This compensation is performed by constructing an 'overlap map' which provides a measure of how much an object at one location is visible within other viewpoints. An investigation into the suitability of various feature types and regression models for scene invariant crowd counting is also conducted. The features investigated include object size, shape, edges and keypoints. The regression models evaluated include neural networks, K-nearest neighbours, linear and Gaussian process regresion. Our experiments demonstrate that accurate crowd counting was achieved across seven benchmark datasets, with optimal performance observed when all features were used and when Gaussian process regression was used. The combination of scene invariance and multi camera crowd counting is evaluated by training the system on footage obtained from the QUT camera network and testing it on three cameras from the PETS 2009 database. Highly accurate crowd counting was observed with a mean relative error of less than 10%. Our approach enables a pre-trained system to be deployed on a new environment without any additional training, bringing the field one step closer toward a 'plug and play' system.

Separable and non-separable discrete wavelet transform based texture features and image classification of breast thermograms

Highly sensitive infrared cameras can produce high-resolution diagnostic images of the temperature and vascular changes of breasts. Wavelet transform based features are suitable in extracting the texture difference information of these images due to their scale-space decomposition. The objective of this study is to investigate the potential of extracted features in differentiating between breast lesions by comparing the two corresponding pectoral regions of two breast thermograms. The pectoral regions of breastsare important because near 50% of all breast cancer is located in this region. In this study, the pectoral region of the left breast is selected. Then the corresponding pectoral region of the right breast is identified. Texture features based on the first and the second sets of statistics are extracted from wavelet decomposed images of the pectoral regions of two breast thermograms. Principal component analysis is used to reduce dimension and an Adaboost classifier to evaluate classification performance. A number of different wavelet features are compared and it is shown that complex non-separable 2D discrete wavelet transform features perform better than their real separable counterparts.