The molecular structure of the borate mineral inderite Mg(H4B3O7)(OH)⋅5H2O – A vibrational spectroscopic study

We have undertaken a study of the mineral inderite Mg(H4B3O7)(OH)⋅5H2O a hydrated hydroxy borate mineral of magnesium using scanning electron microscopy, thermogravimetry and vibrational spectroscopic techniques. The structure consists of [B3O3(OH)5]2-[B3O3(OH)5]2- soroborate groups and Mg(OH)2(H2O)4 octahedra interconnected into discrete molecules by the sharing of two OH groups. Thermogravimetry shows a mass loss of 47.2% at 137.5 °C, proving the mineral is thermally unstable. Raman bands at 954, 1047 and 1116 cm−1 are assigned to the trigonal symmetric stretching mode. The two bands at 880 and 916 cm−1 are attributed to the symmetric stretching mode of the tetrahedral boron. Both the Raman and infrared spectra of inderite show complexity. Raman bands are observed at 3052, 3233, 3330, 3392 attributed to water stretching vibrations and 3459 cm−1 with sharper bands at 3459, 3530 and 3562 cm−1 assigned to OH stretching vibrations. Vibrational spectroscopy is used to assess the molecular structure of inderite.

Metal hexaborides with Sc, Ti or Mn

Comparison of well-determined single crystal data for stoichiometric, or near-stoichiometric, metal hexaborides con-firm previously identified lattice parameter trends using powder diffraction. Trends for both divalent and trivalent forms suggest that potential new forms for synthesis include Sc and Mn hexaborides. Density Functional Theory (DFT) calculations for KB6, CaB6, YB6, LaB6, boron octahedral clusters and Sc and Mn forms, show that the shapes of bonding orbitals are defined by the boron framework. Inclusion of metal into the boron framework induces a reduction in energy ranging from 1 eV to 6 eV increasing with ionic charge. For metals with d1 character, such a shift in energy brings a doubly degenerate band section along the G-M reciprocal space direction within the conduction bands tangential to the Fermi surface. ScB6 band structure and density of states calculations show directional and gap characteristics similar to those of YB6 and LaB6. These calculations for ScB6 suggest it may be possible to realize superconductivity in this compound if synthesized.

A Hybrid Queue-based Bayesian Network Framework for passenger facilitation modelling

This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and Exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an $R^2$ goodness of fit of 0.9994 and 0.9982 respectively over a 10 hour test period. The utility of the framework is demonstrated on a number of usage scenarios including real time monitoring and `what-if' analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

Investigation of mediated oxidation of ascorbic acid by ferrocenemethanol using large-amplitude fourier transformed ac voltammetry under quasi-reversible electron-transfer conditions at an indium tin oxide electrode

The ability of the technique of large-amplitude Fourier transformed (FT) ac voltammetry to facilitate the quantitative evaluation of electrode processes involving electron transfer and catalytically coupled chemical reactions has been evaluated. Predictions derived on the basis of detailed simulations imply that the rate of electron transfer is crucial, as confirmed by studies on the ferrocenemethanol (FcMeOH)-mediated electrocatalytic oxidation of ascorbic acid. Thus, at glassy carbon, gold, and boron-doped diamond electrodes, the introduction of the coupled electrocatalytic reaction, while producing significantly enhanced dc currents, does not affect the ac harmonics. This outcome is as expected if the FcMeOH (0/+) process remains fully reversible in the presence of ascorbic acid. In contrast, the ac harmonic components available from FT-ac voltammetry are predicted to be highly sensitive to the homogeneous kinetics when an electrocatalytic reaction is coupled to a quasi-reversible electron-transfer process. The required quasi-reversible scenario is available at an indium tin oxide electrode. Consequently, reversible potential, heterogeneous charge-transfer rate constant, and charge-transfer coefficient values of 0.19 V vs Ag/AgCl, 0.006 cm s (-1) and 0.55, respectively, along with a second-order homogeneous chemical rate constant of 2500 M (-1) s (-1) for the rate-determining step in the catalytic reaction were determined by comparison of simulated responses and experimental voltammograms derived from the dc and first to fourth ac harmonic components generated at an indium tin oxide electrode. The theoretical concepts derived for large-amplitude FT ac voltammetry are believed to be applicable to a wide range of important solution-based mediated electrocatalytic reactions.

Modeling the viability of the free-ranging cheetah population in Namibia : an object-oriented Bayesian network approach

Conservation of free-ranging cheetah (Acinonyx jubatus) populations is multi faceted and needs to be addressed from an ecological, biological and management perspective. There is a wealth of published research, each focusing on a particular aspect of cheetah conservation. Identifying the most important factors, making sense of various (and sometimes contrasting) findings, and taking decisions when little or no empirical data is available, are everyday challenges facing conservationists. Bayesian networks (BN) provide a statistical modeling framework that enables analysis and integration of information addressing different aspects of conservation. There has been an increased interest in the use of BNs to model conservation issues, however the development of more sophisticated BNs, utilizing object-oriented (OO) features, is still at the frontier of ecological research. We describe an integrated, parallel modeling process followed during a BN modeling workshop held in Namibia to combine expert knowledge and data about free-ranging cheetahs. The aim of the workshop was to obtain a more comprehensive view of the current viability of the free-ranging cheetah population in Namibia, and to predict the effect different scenarios may have on the future viability of this free-ranging cheetah population. Furthermore, a complementary aim was to identify influential parameters of the model to more effectively target those parameters having the greatest impact on population viability. The BN was developed by aggregating diverse perspectives from local and independent scientists, agents from the national ministry, conservation agency members and local fieldworkers. This integrated BN approach facilitates OO modeling in a multi-expert context which lends itself to a series of integrated, yet independent, subnetworks describing different scientific and management components. We created three subnetworks in parallel: a biological, ecological and human factors network, which were then combined to create a complete representation of free-ranging cheetah population viability. Such OOBNs have widespread relevance to the effective and targeted conservation management of vulnerable and endangered species.

Tangled Webs : Using Bayesian Networks in the Fight Against Infection

Bayesian networks (BNs) provide a statistical modelling framework which is ideally suited for modelling the many factors and components of complex problems such as healthcare-acquired infections. The methicillin-resistant Staphylococcus aureus (MRSA) organism is particularly troublesome since it is resistant to standard treatments for Staph infections. Overcrowding and understa�ng are believed to increase infection transmission rates and also to inhibit the effectiveness of disease control measures. Clearly the mechanisms behind MRSA transmission and containment are very complicated and control strategies may only be e�ective when used in combination. BNs are growing in popularity in general and in medical sciences in particular. A recent Current Content search of the number of published BN journal articles showed a fi�ve fold increase in general and a six fold increase in medical and veterinary science from 2000 to 2009. This chapter introduces the reader to Bayesian network (BN) modelling and an iterative modelling approach to build and test the BN created to investigate the possible role of high bed occupancy on transmission of MRSA while simultaneously taking into account other risk factors.

Beyond compliance : project on an integrated systems approach for pest risk management in South East Asia

The Beyond Compliance project, which began in July 2011 with funding from the Standards and Trade Development Facility for 2 years, aims to enhance competency and confidence in the South East Asian sub-region by applying a Systems Approach for pest risk management. The Systems Approach involves the use of integrated measures, at least two of which are independent, that cumulatively reduce the risk of introducing exotic pests through trade. Although useful in circumstances where single measures are inappropriate or unavailable, the Systems Approach is inherently more complicated than single-measure approaches, which may inhibit its uptake. The project methodology is to take prototype decision-support tools, such as Control Point-Bayesian Networks (CP-BN), developed in recent plant health initiatives in other regions, including the European PRATIQUE project, and to refine them within this sub-regional context. Case studies of high-priority potential agricultural trade will be conducted by National Plant Protection Organizations of participating South East Asian countries in trials of the tools, before further modifications. Longer term outcomes may include: more robust pest risk management in the region (for exports and imports); greater inclusion of stakeholders in development of pest risk management plans; increased confidence in trade negotiations; and new opportunities for trade.

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.