Concepts and dimensionality in modeling unsaturated water flow and solute transport

Many environmental studies require accurate simulation of water and solute fluxes in the unsaturated zone. This paper evaluates one- and multi-dimensional approaches for soil water flow as well as different spreading mechanisms to model solute behavior at different scales. For quantification of soil water fluxes,Richards equation has become the standard. Although current numerical codes show perfect water balances, the calculated soil water fluxes in case of head boundary conditions may depend largely on the method used for spatial averaging of the hydraulic conductivity. Atmospheric boundary conditions, especially in the case of phreatic groundwater levels fluctuating above and below a soil surface, require sophisticated solutions to ensure convergence. Concepts for flow in soils with macro pores and unstable wetting fronts are still in development. One-dimensional flow models are formulated to work with lumped parameters in order to account for the soil heterogeneity and preferential flow. They can be used at temporal and spatial scales that are of interest to water managers and policymakers. Multi-dimensional flow models are hampered by data and computation requirements.Their main strength is detailed analysis of typical multi-dimensional flow problems, including soil heterogeneity and preferential flow. Three physically based solute-transport concepts have been proposed to describe solute spreading during unsaturated flow: The stochastic-convective model (SCM), the convection-dispersion equation (CDE), and the fraction aladvection-dispersion equation (FADE). A less physical concept is the continuous-time random-walk process (CTRW). Of these, the SCM and the CDE are well established, and their strengths and weaknesses are identified. The FADE and the CTRW are more recent,and only a tentative strength weakness opportunity threat (SWOT)analysis can be presented at this time. We discuss the effect of the number of dimensions in a numerical model and the spacing between model nodes on solute spreading and the values of the solute-spreading parameters. In order to meet the increasing complexity of environmental problems, two approaches of model combination are used: Model integration and model coupling. Amain drawback of model integration is the complexity of there sulting code. Model coupling requires a systematic physical domain and model communication analysis. The setup and maintenance of a hydrologic framework for model coupling requires substantial resources, but on the other hand, contributions can be made by many research groups.

Modelling the fate of chromated copper arsenate in a sandy soil

A pulse of chromated copper arsenate (CCA, a timber preservative) was applied in irrigation water to an undisturbed field soil in a laboratory column. Concentrations of various elements in the leachate from the column were measured during the experiment. Also, the remnants within the soil were measured at the end of the experiment. The geochemical modelling package, PHREEQC-2, was used to simulate the experimental data. Processes included in the CCA transport modelling were advection, dispersion, non-specific adsorption (cation exchange) and specific adsorption by clay minerals and organic matter, as well as other possible chemical reactions such as precipitation/dissolution. The modelling effort highlighted the possible complexities in CCA transport and reaction experiments. For example, the uneven dosing of CCA as well as incomplete knowledge of the soil properties resulted in simulations that gave only partial, although reasonable, agreement with the experimental data. Both the experimental data and simulations show that As and Cu are strongly adsorbed and therefore, will mostly remain at the top of the soil profile, with a small proportion appearing in leachate. On the other hand, Cr is more mobile and thus it is present in the soil column leachate. Further simulations show that both the quantity of CCA added to the soil and the pH of the irrigation water will influence CCA transport. Simulations suggest that application of larger doses of CCA to the soil will result in higher leachate concentrations, especially for Cu and As. Irrigation water with a lower pH will dramatically increase leaching of Cu. These results indicate that acidic rainfall or significant accidental spillage of CCA will increase the risk of groundwater pollution.

Quantifying minimum monolith size and solute dilution from multi-compartment percolation sampler data

Preferential flow affects solute transport in natural soils, leading to high spatiotemporal variation of concentration. A multicompartment solute sampler (MCS), yielding multiple breakthrough curves at a given depth, can monitor tracer movement in a heterogeneous soil. We present a technique to estimate from MCS data whether a soil monolith is sufficiently large to capture preferential flow, which is a necessity for tracer breakthrough curves to be representative. For several soils, we estimate that an MCS should be larger than 0.1 to 0.2 m². We also expand dilution theory to analyze the concentration variations of a tracer passing the control plane monitored by the MCS, in addition to the conventional plume spreading analysis. We characterize the set of locally observed breakthrough curves by the entropy-based dilution index. For given first and second-central moment, the spatially uniform log-normal breakthrough curve maximizes the dilution index. The ratio between observed and maximum dilution index is denoted reactor ratio. For a 300-compartment solute sampler, covering an area of 0.75 m², we compute a reactor ratio of 0.665, compared with 0.04 for stochastic-convective and 1 for convective-dispersive transport. With a single, large collector the reactor ratio would be 0.958, severely underestimating concentration variations. Large collector areas are clearly inadequate to estimate dilution. Values of the dilution index and the reactor ratio for individual sampling compartments indicate efficient longitudinal mixing in most but not all cases, and considerable spatial variation of the leaching process.

Safely delegating data mining tasks

Data mining is playing an important role in decision making for business activities and governmental administration. Since many organizations or their divisions do not possess the in-house expertise and infrastructure for data mining, it is beneficial to delegate data mining tasks to external service providers. However, the organizations or divisions may lose of private information during the delegating process. In this paper, we present a Bloom filter based solution to enable organizations or their divisions to delegate the tasks of mining association rules while protecting data privacy. Our approach can achieve high precision in data mining by only trading-off storage requirements, instead of by trading-off the level of privacy preserving.

Workload capacity measures for estimating allied health staffing requirements

Workforce planning methodologies for the allied health professions are acknowledged as rudimentary despite the increasing importance of these professions to health care across the spectrum of health services settings. The objectives of this study were to (i) identify workload capacity measures and methods for profiling allied health workforce requirements from a systematic review of the international literature; (ii) explore the use of these methods in planning workforce requirements; (iii) identify barriers to applying such methods; and (iv) recommend further action. Future approaches to workforce planning were explored through a systematic review of the literature, interviews with key stakeholders and focus group discussions with representatives from the different professional bodies and health agencies in Victoria. Results identified a range of methods used to calculate workload requirements or capacity. In order of increasing data demands and costliness to implement, workload capacity methods can be broadly classified into four groups: ratio-based, procedure-based, categories of care-based and diagnostic or casemix-based. Despite inherent limitations, the procedure-based measurement approach appears to be most widely accepted. Barriers to more rigorous workforce planning methods are discussed and future directions explored through an examination of the potential of casemix and mixed-method approaches.

Taking environmental water requirements and climate change into account in the designation and management of protected areas for floodplain ecosystems

In 2005, the Victorian government asked the Victorian Environmental Assessment Council (VEAC) to 1) identify and evaluate the extent, condition, values, management, resources and uses of riverine red gum forests and associated fauna, wetlands, floodplain ecosystems and vegetation communities in northern Victoria; and 2) make recommendations relating to the conservation, protection and ecological sustainable use of public land. The design of a comprehensive, adequate and representative (CAR) reserve system was a key part of the recommendations made by VEAC. In order to assist in the decision-making for environmental water allocation for protected areas and other public land, a process for identifying flood-dependent natural values on the Victorian floodplains of the River Murray and its tributaries was developed.

Although some areas such as the Barmah forest are very well known, there have been few comprehensive inventories of important natural values along the Murray floodplains. For this project, VEAC sought out and compiled data on flood requirements (natural flood frequency, critical interval between floods, minimum duration of floods) for all flood-dependent ecological vegetation classes (EVCs) and threatened species along the Goulburn, Ovens, King and Murray Rivers in Victoria. The project did not include the Kerang Lakes and floodplains of the Avoca, Loddon and Campaspe Rivers. 186 threatened species and 110 EVCs (covering 224,247 ha) were identified as flood-dependent and therefore at risk from insufficient flooding.

Past environmental water allocations have targeted a variety of different natural assets (e.g. stressed red gum trees, colonial nesting waterbirds, various fish species), but consideration of the water requirements of the full suite of floodplain ecosystems and significant species has been limited. By considering the water requirements of the full range of natural assets, the effectiveness of water delivery for biodiversity can be maximised. This approach highlights the species and ecosystems most in need of water and builds on the icon sites approach to view the Murray floodplains as an interconnected system. This project also identified for the first time the flood-frequency and duration requirements for the full suite of floodplain ecosystems and significant species.

This project is the most comprehensive identification of water requirements for natural values on the floodplain to date, and is able to be used immediately to guide prioritisation of environmental watering. As more information on floodplain EVCs and species becomes available, the water requirements and distribution of values can be refined by ecologists and land and water managers. That is, the project is intended as the start of an adaptive process allowing for the incorporation of monitoring and feedback over time. The project makes it possible to transparently and easily communicate the extent to which manipulated or natural flows benefit various natural values. Quantitative and visual outputs such as maps will enable environmental managers and the public to easily see which values do and do not receive water (see http://www.veac.vic.gov.au/riverredgumfinal.htm for further details).

How welfare-to-work requirements impact on single parents' volunteer activities

This paper seeks to describe the volunteering experiences of female single parents engaged in Australia's welfare-to-work program. Interviews were conducted with 26 single parents who had been required to increase their hours of work as a condition of the Centrelink policy introduced in 2006. To analyse the data, the technique of rich point analysis was employed which identified three key concepts central to the women's experiences.  These concepts included the nature of a decent job, notions of reciprocity, and a seeming hierarchy of suitable jobs promoted within the welfareto- work policy. How volunteer activities fit within these constructs was the focus of the investigation. The analysis revealed that the types of paid jobs women obtained were less fulfilling and flexible than their volunteer activities. and gave them less sense of contributing to society, Further, in most cases prior to welfare reform, these single mothers were volunteering in their children's school and as such, both the school's capacity and intergenerational role modelling of volunteering were depleted.

Flowering ecology of a Box-Ironbark Eucalyptus community

Box-Ironbark forests occur on the inland hills of the Great Dividing Range in Australia, from western Victoria to southern Queensland. These dry, open forests are characteristically dominated by Eucalyptus species such as Red Ironbark E. tricarpa, Mugga Ironbark E. sideroxylon and Grey Box E. microcarpa. Within these forests, several Eucalyptus species are a major source of nectar for the blossom-feeding birds and marsupials that form a distinctive component of the fauna. In Victoria, approximately 83% of the original pre - European forests of the Box-Ironbark region have been cleared, and the remaining fragmented forests have been heavily exploited for gold and timber. This exploitation has lead to a change in the structure of these forests, from one dominated by large 80-100 cm diameter, widely -spaced trees to mostly small (≥40 cm DBH), more densely - spaced trees. This thesis examines the flowering ecology of seven Eucalyptus species within a Box-Ironbark community. These species are characteristic of Victorian Box-Ironbark forests; River Red Gum E. camaldulensis, Yellow Gum E. leucoxylon, Red Stringybark E. macrorhyncha, Yellow Box E. melliodora, Grey Box E. microcarpa, Red Box E. polyanthemos and Red Ironbark E. tricarpa. Specifically, the topics examined in this thesis are: (1) the floral character traits of species, and the extent to which these traits can be associated with syndromes of bird or insect pollination; (2) the timing, frequency, duration, intensity, and synchrony of flowering of populations and individual trees; (3) the factors that may explain variation in flowering patterns of individual trees through examination of the relationships between flowering and tree-specific factors of individually marked trees; (4) the influence of tree size on the flowering patterns of individually marked trees, and (5) the spatial and temporal distribution of the floral resources of a dominant species, E. tricarpa. The results are discussed in relation to the evolutionary processes that may have lead to the flowering patterns, and the likely effects of these flowering patterns on blossom-feeding fauna of the Box-Ironbark region. Flowering observations were made for approximately 100 individually marked trees for each species (a total of 754 trees). The flower cover of each tree was assessed at a mean interval of 22 (+ 0.6) days for three years; 1997, 1998 and 1999. The seven species of eucalypt each had characteristic flowering seasons, the timing of which was similar each year. In particular, the timing of peak flowering intensity was consistent between years. Other spatial and temporal aspects of flowering patterns for each species, including the percentage of trees that flowered, frequency of flowering, intensity of flowering and duration of flowering, displayed significant variation between years, between forest stands (sites) and between individual trees within sites. All seven species displayed similar trends in flowering phenology over the study, such that 1997 was a relatively 'poor' flowering year, 1998 a 'good' year and 1999 an 'average' year in this study area. The floral character traits and flowering seasons of the seven Eucalyptus species suggest that each species has traits that can be broadly associated with particular pollinator types. Differences between species in floral traits were most apparent between 'summer' and 'winter' flowering species. Winter - flowering species displayed pollination syndromes associated with bird pollination and summer -flowering species displayed syndromes more associated with insect pollination. Winter - flowering E. tricarpa and E. leucoxylon flowers, for example, were significantly larger, and contained significantly greater volumes of nectar, than those of the summer flowering species, such as E. camaldulensis and E. melliodom. An examination of environmental and tree-specific factors was undertaken to investigate relationships between flowering patterns of individually marked trees of E. microcarpa and E. tricarpa and a range of measures that may influence the observed patterns. A positive association with tree-size was the most consistent explanatory variable for variation between trees in the frequency and intensity of flowering. Competition from near-neighbours, tree health and the number of shrubs within the canopy area were also explanatory variables. The relationship between tree size and flowering phenology was further examined by using the marked trees of all seven species, selected to represent five size-classes. Larger trees (≥40 cm DBH) flowered more frequently, more intensely, and for a greater duration than smaller trees. Larger trees provide more abundant floral resources than smaller trees because they have more flowers per unit area of canopy, they have larger canopies in which more flowers can be supported, and they provide a greater abundance of floral resources over the duration of the flowering season. Heterogeneity in the distribution of floral resources was further highlighted by the study of flowering patterns of E. tricarpa at several spatial and temporal scales. A total of approximately 5,500 trees of different size classes were sampled for flower cover along transects in major forest blocks at each of five sample dates. The abundance of flowers varied between forest blocks, between transects and among tree size - classes. Nectar volumes in flowers of E. tricarpa were sampled. The volume of nectar varied significantly among flowers, between trees, and between forest stands. Mean nectar volume per flower was similar on each sample date. The study of large numbers of individual trees for each of seven species was useful in obtaining quantitative data on flowering patterns of species' populations and individual trees. The timing of flowering for a species is likely to be a result of evolutionary selective forces tempered by environmental conditions. The seven species' populations showed a similar pattern in the frequency and intensity of flowering between years (e.g. 1998 was a 'good' year for most species) suggesting that there is some underlying environmental influence acting on these aspects of flowering. For individual trees, the timing of flowering may be influenced by tree-specific factors that affect the ability of each tree to access soil moisture and nutrients. In turn, local weather patterns, edaphic and biotic associations are likely to influence the available soil moisture. The relationships between the timing of flowering and environmental conditions are likely to be complex. There was no evidence that competition for pollinators has a strong selective influence on the timing of flowering. However, as there is year-round flowering in this community, particular types of pollinators may be differentiated along a temporal gradient (e.g. insects in summer, birds in winter). This type of differentiation may have resulted in the co-evolution of floral traits and pollinator types, with flowers displaying adaptations that match the morphologies and energy requirements of the most abundant pollinators in any particular season. Spatial variation in flowering patterns was evident at several levels. This is likely to occur because of variation in climate, weather patterns, soil types, degrees of disturbance and biotic associations, which vary across the Box-Ironbark region. There was no consistency among sites between years in flowering patterns suggesting that factors affecting flowering at this level are complex. Blossom-feeding animals are confronted with a highly spatially and temporally patchy resource. This patchiness has been increased with human exploitation of these forests leading to a much greater abundance of small trees and fewer large trees. Blossom-feeding birds are likely to respond to this variation in different ways, depending upon diet-breadth, mobility and morphological and behavioural characteristics. Future conservation of the blossom-feeding fauna of Box-Ironbark forests would benefit from the retention of a greater number of large trees, the protection and enhancement of existing remnants, and revegetation with key species, such as E. leucoxylon, E. microcarpa and E. tricarpa. The selective clearing of summer flowering species, which occur on the more fertile areas, may have negatively affected the year-round abundance and distribution of floral resources. The unpredictability of the spatial distribution of flowering patches within the region means that all remnants are likely to be important foraging areas in some years.

Learning from large data : bias, variance, sampling, and learning curves

One of the fundamental machine learning tasks is that of predictive classification. Given that organisations collect an ever increasing amount of data, predictive classification methods must be able to effectively and efficiently handle large amounts of data. However, it is understood that present requirements push existing algorithms to, and sometimes beyond, their limits since many classification prediction algorithms were designed when currently common data set sizes were beyond imagination. This has led to a significant amount of research into ways of making classification learning algorithms more effective and efficient. Although substantial progress has been made, a number of key questions have not been answered. This dissertation investigates two of these key questions. The first is whether different types of algorithms to those currently employed are required when using large data sets. This is answered by analysis of the way in which the bias plus variance decomposition of predictive classification error changes as training set size is increased. Experiments find that larger training sets require different types of algorithms to those currently used. Some insight into the characteristics of suitable algorithms is provided, and this may provide some direction for the development of future classification prediction algorithms which are specifically designed for use with large data sets. The second question investigated is that of the role of sampling in machine learning with large data sets. Sampling has long been used as a means of avoiding the need to scale up algorithms to suit the size of the data set by scaling down the size of the data sets to suit the algorithm. However, the costs of performing sampling have not been widely explored. Two popular sampling methods are compared with learning from all available data in terms of predictive accuracy, model complexity, and execution time. The comparison shows that sub-sampling generally products models with accuracy close to, and sometimes greater than, that obtainable from learning with all available data. This result suggests that it may be possible to develop algorithms that take advantage of the sub-sampling methodology to reduce the time required to infer a model while sacrificing little if any accuracy. Methods of improving effective and efficient learning via sampling are also investigated, and now sampling methodologies proposed. These methodologies include using a varying-proportion of instances to determine the next inference step and using a statistical calculation at each inference step to determine sufficient sample size. Experiments show that using a statistical calculation of sample size can not only substantially reduce execution time but can do so with only a small loss, and occasional gain, in accuracy. One of the common uses of sampling is in the construction of learning curves. Learning curves are often used to attempt to determine the optimal training size which will maximally reduce execution time while nut being detrimental to accuracy. An analysis of the performance of methods for detection of convergence of learning curves is performed, with the focus of the analysis on methods that calculate the gradient, of the tangent to the curve. Given that such methods can be susceptible to local accuracy plateaus, an investigation into the frequency of local plateaus is also performed. It is shown that local accuracy plateaus are a common occurrence, and that ensuring a small loss of accuracy often results in greater computational cost than learning from all available data. These results cast doubt over the applicability of gradient of tangent methods for detecting convergence, and of the viability of learning curves for reducing execution time in general.

Integrating data to facilitate clinical research : a case study

The integration of routine clinical administrative activities into ongoing rigorous clinical research poses challenges for both clinicians and researchers. This case study describes the development of a responsive database system used to facilitate comprehensive longitudinal research into the outcomes of patients waiting for hip and knee replacement surgery in a large public teaching hospital. The initial research procedure was paper-based, with manual patient matching and data entry. This process was time-consuming and associated with substantial risk of error and omissions, necessitating the design of a better system. An integrated database system was designed to receive daily electronic updates of the orthopaedic waiting-list and scheduled clinic and surgery dates. Using readily available software (Microsoft Access), new patients were identified through specifying inclusion and exclusion criteria which allowed rapid and complete recruitment at time of entry to the waiting-list. The integrated system specified the appropriate timing of multiple follow-up assessments, provided prompt information on recruitment for reporting purposes and integrated multiple linked research projects within one database. Seamless exporting of data to statistical programs for analysis was also enabled. This simple integrated approach facilitated efficient execution of a longitudinal study from recruitment to statistical analysis while maximising confidentiality and minimising resources required. This case study describes the development and design of a simple system which could be easily adapted for database management in hospital or clinic-based settings according to local requirements.

A new approach to determining environmental flow requirements : sustaining the natural values of floodplains of the southern Murray-Darling Basin

Large overbank flood events play an important role in maintaining largescale ecological processes and connectivity along and across the floodplains and between the rivers and their floodplains in the southern Murray-Darling Basin. However, the regulation of rivers means that extensive overbank flooding can only occur in the rare circumstance of extreme flood events. Recent environmental water allocations have focussed on the largest floodplain blocks (‘icon’ sites) and a small set of specific values (e.g. colonial nesting waterbirds), as well as on trialling fine-scale manipulation of infrastructure (e.g. pumping) to water relatively small areas. There has been no comprehensive systematic assessment of the entire floodplain and its wider set of flood-dependent natural assets (such as ecosystems and species; herein referred to as ‘natural values’) to maximise the effectiveness of environmental water use and to catalogue values likely to be lost. This paper describes an assessment of some 220 000 ha found to support flood-dependent natural values in Victoria. We mapped the geographic distribution and estimated components of the flooding requirements (natural flooding frequency, and maximum period without flooding and minimum duration of each flooding event before significant deterioration) for each natural value. Using an example of one stretch of the River Murray, we show how the resultant spatial data can be used with floodplain inundation modelling to compare the outcomes of real or planned environmental watering events; potentially providing tools for management agencies to conserve a wider range of floodplain values than is currently the case. That is, water managers and the public can see what ecosystems and threatened species are intended to be maintained by environmental watering and what values are intended to be abandoned across the whole floodplain, rather than just seeing the small subset of values and ‘icon’ sites that are intended to be maintained. Examples are provided to illustrate how information about the location, water requirements and extent covered by potential floods for specific values can be used to build adaptive watering strategies for areas as large as the whole floodplain.

Quality control of sensor network data

A wireless sensor network (WSN) is a group of sensors that are geographically distributed and interconnected by wireless networks. Sensors gather information about the state of physical world. Then, after processing forward them to the main destination. To be able to provide this service, there are many aspects of communication techniques that need to be explored. Supporting quality of service (QoS) will be of critical importance for pervasive WSNs that serve as the network infrastructure of diverse applications. To illustrate new research and development interests in this field, this paper examines and discusses the requirements, critical challenges, and open research issues on QoS management in WSNs. A brief overview of recent progress is given.

Do toddlers need iron-fortified toddler foods to ensure their dietary iron requirements are met?

Adequate nutrition during toddlerhood is essential for optimal growth and development, yet biochemical data suggest that 12-24-month-old children are at risk of iron deficiency. Mathematical modelling combined with experimental interventions can provide strong evidence regarding the types of foods required to improve toddler iron status.

An efficient one-pass method for discovering bases of recently frequent episodes over online data streams

The knowledge embedded in an online data stream is likely to change over time due to the dynamic evolution of the stream. Consequently, infrequent episode mining over an online stream, frequent episodes should be adaptively extracted from recently generated stream segments instead of the whole stream. However, almost all existing frequent episode mining approaches find episodes frequently occurring over the whole sequence. This paper proposes and investigates a new problem: online mining of recently frequent episodes over data streams. In order to meet strict requirements of stream mining such as one-scan, adaptive result update and instant result return, we choose a novel frequency metric and define a highly condensed set called the base of recently frequent episodes. We then introduce a one-pass method for mining bases of recently frequent episodes. Experimental results show that the proposed method is capable of finding bases of recently frequent episodes quickly and adaptively. The proposed method outperforms the previous approaches with the advantages of one-pass, instant result update and return, more condensed resulting sets and less space usage.

X4 and R5 HIV-1 have distinct post-entry requirements for uracil DNA glycosylase during infection of primary cells

It has been assumed that R5 and X4 HIV utilize similar strategies to support viral cDNA synthesis post viral entry. In this study, we provide evidence to show that R5 and X4 HIV have distinct requirements for host cell uracil DNA glycosylase (UNG2) during the early stage of infection. UNG2 has been previously implicated in HIV infection, but its precise role remains controversial. In this study we show that, although UNG2 is highly expressed in different cell lines, UNG2 levels are low in the natural host cells of HIV. Short interfering RNA knockdown of endogenous UNG2 in primary cells showed that UNG2 is required for R5 but not X4 HIV infection and that this requirement is bypassed when HIV enters the target cell via vesicular stomatitis virus envelope-glycoprotein-mediated endocytosis. We also show that short interfering RNA knockdown of UNG2 in virus-producing primary cells leads to defective R5 HIV virions that are unable to complete viral cDNA synthesis. Quantitative PCR analysis revealed that endogenous UNG2 levels are transiently up-regulated post HIV infection, and this increase in UNG2 mRNA is ∼10–20 times higher in R5 versus X4 HIV-infected cells. Our data show that both virion-associated UNG2 and HIV infection-induced UNG2 expression are critical for reverse transcription during R5 but not X4 HIV infection. More importantly, we have made the novel observation that R5 and X4 HIV have distinct host cell factor requirements and differential capacities to induce gene expression during the early stages of infection. These differences may result from activation of distinct signaling cascades and/or infection of divergent T-lymphocyte subpopulations.