A Bayesian network approach to modelling temporal behaviour of Lyngbya majuscula bloom initiation

Lyngbya majuscula is a cyanobacterium (blue-green algae) occurring naturally in tropical and subtropical coastal areas worldwide. Deception Bay, in Northern Moreton Bay, Queensland, has a history of Lyngbya blooms, and forms a case study for this investigation. The South East Queensland (SEQ) Healthy Waterways Partnership, collaboration between government, industry, research and the community, was formed to address issues affecting the health of the river catchments and waterways of South East Queensland. The Partnership coordinated the Lyngbya Research and Management Program (2005-2007) which culminated in a Coastal Algal Blooms (CAB) Action Plan for harmful and nuisance algal blooms, such as Lyngbya majuscula. This first phase of the project was predominantly of a scientific nature and also facilitated the collection of additional data to better understand Lyngbya blooms. The second phase of this project, SEQ Healthy Waterways Strategy 2007-2012, is now underway to implement the CAB Action Plan and as such is more management focussed. As part of the first phase of the project, a Science model for the initiation of a Lyngbya bloom was built using Bayesian Networks (BN). The structure of the Science Bayesian Network was built by the Lyngbya Science Working Group (LSWG) which was drawn from diverse disciplines. The BN was then quantified with annual data and expert knowledge. Scenario testing confirmed the expected temporal nature of bloom initiation and it was recommended that the next version of the BN be extended to take this into account. Elicitation for this BN thus occurred at three levels: design, quantification and verification. The first level involved construction of the conceptual model itself, definition of the nodes within the model and identification of sources of information to quantify the nodes. The second level included elicitation of expert opinion and representation of this information in a form suitable for inclusion in the BN. The third and final level concerned the specification of scenarios used to verify the model. The second phase of the project provides the opportunity to update the network with the newly collected detailed data obtained during the previous phase of the project. Specifically the temporal nature of Lyngbya blooms is of interest. Management efforts need to be directed to the most vulnerable periods to bloom initiation in the Bay. To model the temporal aspects of Lyngbya we are using Object Oriented Bayesian networks (OOBN) to create ‘time slices’ for each of the periods of interest during the summer. OOBNs provide a framework to simplify knowledge representation and facilitate reuse of nodes and network fragments. An OOBN is more hierarchical than a traditional BN with any sub-network able to contain other sub-networks. Connectivity between OOBNs is an important feature and allows information flow between the time slices. This study demonstrates more sophisticated use of expert information within Bayesian networks, which combine expert knowledge with data (categorized using expert-defined thresholds) within an expert-defined model structure. Based on the results from the verification process the experts are able to target areas requiring greater precision and those exhibiting temporal behaviour. The time slices incorporate the data for that time period for each of the temporal nodes (instead of using the annual data from the previous static Science BN) and include lag effects to allow the effect from one time slice to flow to the next time slice. We demonstrate a concurrent steady increase in the probability of initiation of a Lyngbya bloom and conclude that the inclusion of temporal aspects in the BN model is consistent with the perceptions of Lyngbya behaviour held by the stakeholders. This extended model provides a more accurate representation of the increased risk of algal blooms in the summer months and show that the opinions elicited to inform a static BN can be readily extended to a dynamic OOBN, providing more comprehensive information for decision makers.

What is an expert? A systems perspective on expertise

1. Expert knowledge continues to gain recognition as a valuable source of information in a wide range of research applications. Despite recent advances in defining expert knowledge, comparatively little attention has been given to how to view expertise as a system of interacting contributory factors, and thereby, to quantify an individual’s expertise. 2. We present a systems approach to describing expertise that accounts for many contributing factors and their interrelationships, and allows quantification of an individual’s expertise. A Bayesian network (BN) was chosen for this purpose. For the purpose of illustration, we focused on taxonomic expertise. The model structure was developed in consultation with professional taxonomists. The relative importance of the factors within the network were determined by a second set of senior taxonomists. This second set of experts (i.e. supra-experts) also provided validation of the model structure. Model performance was then assessed by applying the model to hypothetical career states in the discipline of taxonomy. Hypothetical career states were used to incorporate the greatest possible differences in career states and provide an opportunity to test the model against known inputs. 3. The resulting BN model consisted of 18 primary nodes feeding through one to three higher-order nodes before converging on the target node (Taxonomic Expert). There was strong consistency among node weights provided by the supra-experts for some nodes, but not others. The higher order nodes, “Quality of work” and “Total productivity”, had the greatest weights. Sensitivity analysis indicated that although some factors had stronger influence in the outer nodes of the network, there was relatively equal influence of the factors leading directly into the target node. Despite differences in the node weights provided by our supra-experts, there was remarkably good agreement among assessments of our hypothetical experts that accurately reflected differences we had built into them. 4. This systems approach provides a novel way of assessing the overall level of expertise of individuals, accounting for multiple contributory factors, and their interactions. Our approach is adaptable to other situations where it is desirable to understand components of expertise.

Vibrational spectroscopy of the borate mineral gaudefroyite Ca4Mn3+3-x(BO3)3(CO3)(O,OH) from N’Chwaning II mine, Kalahari, Republic of South Africa

Gaudefroyite Ca4Mn3+3-x(BO3)3(CO3)(O,OH)3 is an unusual mineral containing both borate and carbonate groups and is found in the oxidation zones of manganese minerals, and it is black in color. Vibrational spectroscopy has been used to explore the molecular structure of gaudefroyite. Gaudefroyite crystals are short dipyramidal or prismatic with prominent pyramidal terminations, to 5 cm. Two very sharp Raman bands at 927 and 1076 cm-1are assigned to trigonal borate and carbonate respectively. Broad Raman bands at 1194, 1219 and 1281 cm-1 are attributed to BOH in-plane bending modes. Raman bands at 649 and 670 cm-1 are assigned to the bending modes of trigonal and tetrahedral boron. Infrared spectroscopy supports these band assignments. Raman bands in the OH stretching region are of a low intensity. The combination of Raman and infrared spectroscopy enables the assessment of the molecular structure of gaudefroyite to be made.

Infrared and Raman spectroscopic characterization of the borate mineral hydroboracite CaMg[B3O4(OH)3]2⋅3H2O : implications for the molecular structure

We have studied the mineral hydroboracite CaMg[B3O4(OH)3]2∙3H2O using electron microscopy and vibrational spectroscopy. Both tetrahedral and trigonal boron units are observed. The nominal resolution of the Raman spectrometer is of the order of 2 cm-1 and as such is sufficient enough to identify separate bands for the stretching bands of the two boron isotopes. The Raman band at 1039 cm-1 is assigned to BO stretching vibration. Raman bands at 1144, 1157, 1229, 1318 cm-1 are attributed to the BOH in-plane bending modes. Raman bands at 825 and 925 cm-1 are attributed to the antisymmetric stretching modes of tetrahedral boron. The sharp Raman peak at 925 cm-1 is from the 11-B component such a mode, then it should have a smaller 10-B satellite near (1.03)x(925) = 952 cm-1, and indeed a small peak at 955 is observed. Four sharp Raman bands observed at 3371, 3507, 3563 and 3632 cm-1 are attributed to the stretching vibrations of hydroxyl units. The broad Raman bands at 3076, 3138, 3255, 3384 and 3551 cm-1 are assigned to water stretching vibrations. Infrared bands at 3367, 3505, 3559 and 3631 cm-1are assigned to the stretching vibration of the hydroxyl units. Broad infrared bands at 3072 and 3254 cm-1 are assigned to water stretching vibrations. Infrared bands at 1318, 1349, 1371, 1383 cm-1 are assigned to the antisymmetric stretching vibrations of trigonal boron

Vibrational spectroscopy of the borate mineral tunellite SrB6O9(OH)2·3(H2O) : implications for the molecular structure

Tunellite is a strontium borate mineral with formula: SrB6O9(OH)2∙3(H2O) and occurs as colorless crystals in the monoclinic pyramidal crystal system. An intense Raman band at 994 cm-1 was assigned to the BO stretching vibration of the B2O3 units. Raman bands at 1043, 1063, 1082 and 1113 cm-1 are attributed to the in-plane bending vibrations of trigonal boron. Sharp Raman bands observed at 464, 480, 523, 568 and 639 cm-1 are simply defined as trigonal and tetrahedral borate bending modes. The Raman spectrum clearly shows intense Raman bands at 3567 and 3614 cm-1, attributed to OH units. The molecular structure of a natural tunellite has been assessed by using vibrational spectroscopy.

Bayesian networks in environmental and resource management

This overview article for the special series “Bayesian Networks in Environmental and Resource Management” reviews 7 case study articles with the aim to compare Bayesian network (BN) applications to different environmental and resource management problems from around the world. The article discusses advances in the last decade in the use of BNs as applied to environmental and resource management. We highlight progress in computational methods, best-practices for model design and model communication. We review several research challenges to the use of BNs in environmental and resource management that we think may find a solution in the near future with further research attention.

Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific sub-regions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

Infrared and Raman spectroscopic characterization of the Borate mineral Vonsenite

There are a large number of boron-containing minerals, of which vonsenite is one. Some discussion about the molecular structure of vonsenite exists in the literature. Whether water is involved in the structure is ill-determined. The molecular structure of vonsenite has been assessed by the combination of Raman and infrared spectroscopy. The Raman spectrum is characterized by two intense broad bands at 997 and 1059 cm−1 assigned to the BO stretching vibrational mode. A series of Raman bands in the 1200–1500 cm−1 spectral range are attributed to BO antisymmetric stretching modes and in-plane bending modes. The infrared spectrum shows complexity in this spectral range. No Raman spectrum of water in the OH stretching region could be obtained. The infrared spectrum shows a series of overlapping bands with bands identified at 3037, 3245, 3443, 3556, and 3614 cm−1. It is important to understand the structure of vonsenite in order to form nanomaterials based on its structure. Vibrational spectroscopy enables a better understanding of the structure of vonsenite.

Hydrogen evolution by a metal-free electrocatalyst

Electrocatalytic reduction of water to molecular hydrogen via the hydrogen evolution reaction may provide a sustainable energy supply for the future, but its commercial application is hampered by the use of precious platinum catalysts. All alternatives to platinum thus far are based on nonprecious metals, and, to our knowledge, there is no report about a catalyst for electrocatalytic hydrogen evolution beyond metals. Here we couple graphitic-carbon nitride with nitrogen-doped graphene to produce a metal-free hybrid catalyst, which shows an unexpected hydrogen evolution reaction activity with comparable overpotential and Tafel slope to some of well-developed metallic catalysts. Experimental observations in combination with density functional theory calculations reveal that its unusual electrocatalytic properties originate from an intrinsic chemical and electronic coupling that synergistically promotes the proton adsorption and reduction kinetics.

A theoretical study of C4B isomers. The interconversion of CCBCC and CCCCB via cyclic C4B

Theory suggests that CCBCC (1) will rearrange to planar cyclo-C4B (19) if the excess energy of 1 is greater than or equal to16.1 kcal mol(-1) [calculations at the CCSD(T)/aug-cc-pVTZ//B3LYP/6-31G(d) level of theory]. Cyclo-C4B lies only 1.1 kcal mol(-1) above CCBCC. The planar nature of symmetrical cyclo-C4B is attributed to multicentered bonding involving boron. If cyclo-C4B (19) has an excess energy of greater than or equal to24.4 kcal mol-1, it may ring open to form CCCCB (3).

Coal seam gas water : potential hazards and exposure pathways in Queensland

The extraction of coal seam gas (CSG) produces large volumes of potentially contaminated water. It has raised concerns about the environmental health impacts of the co-produced CSG water. In this paper, we review CSG water contaminants and their potential health effects in the context of exposure pathways in Queensland’s CSG basins. The hazardous substances associated with CSG water in Queensland include fluoride, boron, lead and benzene. The exposure pathways for CSG water are: (1) water used for municipal purposes, (2) recreational water activities in rivers, (3) occupational exposures, (4) water extracted from contaminated aquifers, and; (5) indirect exposure through the food chain. We recommend mapping of exposure pathways into communities in CSG regions to determine the potentially exposed populations in Queensland. Future efforts to monitor chemicals of concern and consolidate them into a central database will build the necessary capability to undertake a much needed environmental health impact assessment.

A vibrational spectroscopic study of the borate mineral takedaite Ca3(BO3)2

We have studied the mineral takedaite Ca3(BO3)2, a borate mineral of calcium using SEM with EDX and vibrational spectroscopy. Chemical analysis shows a homogeneous phase, composed of Ca. Boron was not detected. A very intense Raman band at 1087 cm−1 is assigned to the BO stretching vibration of BO3 units. Additional Raman bands may be due to isotopic splitting. In the infrared spectrum, bands at 1218 cm−1 and at 1163, 1262 and 1295 cm−1 are assigned to the trigonal borate stretching modes. Raman bands at 712 and 715 cm−1 are assigned to the in-plane bending modes of the BO3 units. Vibrational spectroscopy enables aspects of the molecular structure of takedaite to be assessed.

Low-temperature plasma processing for Si photovoltaics

There has been a recent rapid expansion of the range of applications of low-temperature plasma processing in Si-based photovoltaic (PV) technologies. The desire to produce Si-based PV materials at an acceptable cost with consistent performance and reproducibility has stimulated a large number of major research and research infrastructure programs, and a rapidly increasing number of publications in the field of low-temperature plasma processing for Si photovoltaics. In this article, we introduce the low-temperature plasma sources for Si photovoltaic applications and discuss the effects of low-temperature plasma dissociation and deposition on the synthesis of Si-based thin films. We also examine the relevant growth mechanisms and plasma diagnostics, Si thin-film solar cells, Si heterojunction solar cells and silicon nitride materials for antireflection and surface passivation. Special attention is paid to the low-temperature plasma interactions with Si materials including hydrogen interaction, wafer cleaning, masked or mask-free surface texturization, the direct formation of p-n junction, and removal of phosphorus silicate glass or parasitic emitters. The chemical and physical interactions in such plasmas with Si surfaces are analyzed. Several examples of the plasma processes and techniques are selected to represent a variety of applications aimed at the improvement of Si-based solar cell performance. © 2014 Elsevier B.V.

New reaction paths for metal diborides at low temperature and pressure

Attention has recently focussed on MgB2 superconductors (Tc~39K) which can be formed into wires with high material density and viable critical current densities (Jc)1. However, broader utilisation of this diboride and many others is likely to occur when facile synthesis for bulk applications is developed. To date, common synthesis methods include high temperature sintering of mixed elemental powders2, combustion synthesis3, mechano-chemical mixing with high temperature sintering4 and high pressure (~GPa region) with high temperature. In this work, we report on a lower temperature, moderate (<4MPa) pressure method to synthesise metal diborides.

Spin polarized DFT calculations of metal borides

The metal borides, in particular the diborides and hexaborides, contain stoichiometric forms that include insulators, semiconductors and superconductors. In addition, their end-member structures have high symmetry and two atoms although, in general, substitution(s) of multi-valent ions into the metal site occurs consistent with Vegard’s law. These characteristics allow for fundamental comparison of important physical properties such as superconductivity and insulation within a relatively simple structure type. Our early work1,2 has demonstrated this for the hexaborides and this work compares similar attributes across a broader suite of boride structures. In all cases, theoretical calculations are referenced to structures determined via high resolution neutron or X-ray diffraction experiments.