Understanding treatment characteristics of constructed stormwater wetlands

Constructed wetlands are a common structural treatment measure employed to remove stormwater pollutants and forms an important part of the Water Sensitive Urban Design (WSUD) treatment suite. In a constructed wetland, a range of processes such as settling, filtration, adsorption, and biological uptake play a role in stormwater treatment. Occurrence and effectiveness of these processes are variable and influenced by hydraulic, chemical and biological factors. The influence of hydraulic factors on treatment processes are of particular concern. This paper presents outcomes of a comprehensive study undertaken to define the treatment performance of a constructed wetland highlighting the influence of hydraulic factors. The study included field monitoring of a well established constructed wetland for quantity and quality factors, development of a conceptual hydraulic model to simulate water movement within the wetland and multivariate analysis of quantity and quality data to investigate correlations and to define linkages between treatment performance and influential hydraulic factors. Total Suspended Solids (TSS), Total Nitrogen (TN) and Total Phosphorus (TP) concentrations formed the primary pollutant parameters investigated in the data analysis. The outcomes of the analysis revealed significant reduction in event mean concentrations of all three pollutants species. Treatment performance of the wetland was significantly different for storm events above and below the prescribed design event. For events below design event, TSS and TN load reduction was comparatively high and strongly influenced by high retention time. For events above design event, TP load reduction was comparatively high and was found to be influenced by the characteristics of TP wash-off from catchment surfaces.

The relationship between fundamental movement skills and self-reported physical activity during Finnish junior high school

Background: Previous studies have shown that fundamental movement skills (FMS) and physical activity are related. Specifically, earlier studies have demonstrated that the ability to perform a variety of FMS increases the likelihood of children participating in a range of physical activities throughout their lives. To date, however, there have not been studies focused on the development of, or the relationship between, these variables through junior high school (that is, between the ages of 13 and 15). Such studies might provide important insights into the relationships between FMS and physical activity during adolescence, and suggest ways to design more effective physical education programmes for adolescents. Purpose: The main purposes of the study are: (1) to investigate the development of the students' self-reported physical activity and FMS from Grade 7 to Grade 9, (2) to analyse the associations among the students' FMS and self-reported physical activity through junior high school, (3) to analyse whether there are gender differences in research tasks one and/or two. Participants and setting: The participants in the study were 152 Finnish students, aged 13 and enrolled in Grade 7 at the commencement of the study. The sample included 66 girls and 86 boys who were drawn from three junior high schools in Middle Finland. Research design and data collection: Both the FMS tests and questionnaires pertaining to self-reported physical activity were completed annually during a 3 year period: in August (when the participants were in Grade 7), January (Grade 8), and in May (Grade 9). Data analysis: Repeated measures multivariate analysis of variances (MANOVAs) were used to analyse the interaction between gender and time (three measurement points) in FMS test sumscores and self-reported physical activity scores. The relationships between self-reported physical activity scores and fundamental movement skill sumscores through junior high school were analysed using Structural Equation Modelling (SEM) with LISREL 8.80 software. Findings: The MANOVA for self-reported physical activity demonstrated that both genders' physical activity decreased through junior high school. The MANOVA for the FMS revealed that the boys' FMS sumscore increased whereas the girls' skills decreased through junior high school. The SEM and squared multiple correlations revealed FMS in Grades 7 and 8 as well as physical activity in Grade 9 explained FMS in Grade 9. The portion of prediction was 69% for the girls and 55% for the boys. Additionally, physical activity measured in Grade 7 and FMS measured in Grade 9 explained physical activity in Grade 9. The portion of prediction was 12% for the girls and 29% for the boys. In the boys' group, three additional paths were found; FMS in Grade 7 explained physical activity in Grade 9, physical activity in Grade 7 explained FMS in Grade 8, and physical activity in Grade 7 explained physical activity in Grade 8. Conclusions: The study suggests that supporting and encouraging FMS and physical activity are co-related and when considering combined scores there is a greater likelihood of healthy lifelong outcomes. Therefore, the conclusion can be drawn that FMS curriculum in school-based PE is a plausible way to ensure good lifelong outcomes. Earlier studies support that school physical education plays an important role in developing students FMS and is in a position to thwart the typical decline of physical activity in adolescence. These concepts are particularly important for adolescent girls as this group reflects the greatest decline in physical activity during the adolescent period.

Surviving an avalanche of data

Open the sports or business section of your daily newspaper, and you are immediately bombarded with an array of graphs, tables, diagrams, and statistical reports that require interpretation. Across all walks of life, the need to understand statistics is fundamental. Given that our youngsters’ future world will be increasingly data laden, scaffolding their statistical understanding and reasoning is imperative, from the early grades on. The National Council of Teachers of Mathematics (NCTM) continues to emphasize the importance of early statistical learning; data analysis and probability was the Council’s professional development “Focus of the Year” for 2007–2008. We need such a focus, especially given the results of the statistics items from the 2003 NAEP. As Shaughnessy (2007) noted, students’ performance was weak on more complex items involving interpretation or application of items of information in graphs and tables. Furthermore, little or no gains were made between the 2000 NAEP and the 2003 NAEP studies. One approach I have taken to promote young children’s statistical reasoning is through data modeling. Having implemented in grades 3 –9 a number of model-eliciting activities involving working with data (e.g., English 2010), I observed how competently children could create their own mathematical ideas and representations—before being instructed how to do so. I thus wished to introduce data-modeling activities to younger children, confi dent that they would likewise generate their own mathematics. I recently implemented data-modeling activities in a cohort of three first-grade classrooms of six year- olds. I report on some of the children’s responses and discuss the components of data modeling the children engaged in.

Modeling and multiway analysis of chatroom tensors

This work identifies the limitations of n-way data analysis techniques in multidimensional stream data, such as Internet chat room communications data, and establishes a link between data collection and performance of these techniques. Its contributions are twofold. First, it extends data analysis to multiple dimensions by constructing n-way data arrays known as high order tensors. Chat room tensors are generated by a simulator which collects and models actual communication data. The accuracy of the model is determined by the Kolmogorov-Smirnov goodness-of-fit test which compares the simulation data with the observed (real) data. Second, a detailed computational comparison is performed to test several data analysis techniques including svd [1], and multi-way techniques including Tucker1, Tucker3 [2], and Parafac [3].

Collective sampling and analysis of high order tensors for chatroom communications

This work investigates the accuracy and efficiency tradeoffs between centralized and collective (distributed) algorithms for (i) sampling, and (ii) n-way data analysis techniques in multidimensional stream data, such as Internet chatroom communications. Its contributions are threefold. First, we use the Kolmogorov-Smirnov goodness-of-fit test to show that statistical differences between real data obtained by collective sampling in time dimension from multiple servers and that of obtained from a single server are insignificant. Second, we show using the real data that collective data analysis of 3-way data arrays (users x keywords x time) known as high order tensors is more efficient than centralized algorithms with respect to both space and computational cost. Furthermore, we show that this gain is obtained without loss of accuracy. Third, we examine the sensitivity of collective constructions and analysis of high order data tensors to the choice of server selection and sampling window size. We construct 4-way tensors (users x keywords x time x servers) and analyze them to show the impact of server and window size selections on the results.

Critical Factors for Sustainable Post Natural Disaster Reconstruction : Chinese Data

While scientists continue to explore the level of climate change impact to new weather patterns and our environment in general, there have been some devastating natural disasters worldwide in the last two decades. Indeed natural disasters are becoming a major concern in our society. Yet in many previous examples, our reconstruction efforts only focused on providing short-term necessities. How to develop resilience in the long run is now a highlight for research and industry practice. This paper introduces a research project aimed at exploring the relationship between resilience building and sustainability in order to identify key factors during reconstruction efforts. From extensive literature study, the authors considered the inherent linkage between the two issues as evidenced from past research. They found that sustainability considerations can improve the level of resilience but are not currently given due attention. Reconstruction efforts need to focus on resilience factors but as part of urban development, they must also respond to the sustainability challenge. Sustainability issues in reconstruction projects need to be amplified, identified, processed, and managed properly. On-going research through empirical study aims to establish critical factors (CFs) for stakeholders in disaster prone areas to plan for and develop new building infrastructure through holistic considerations and balanced approaches to sustainability. A questionnaire survey examined a range of potential factors and the subsequent data analysis revealed six critical factors for sustainable Post Natural Disaster Reconstruction that include: considerable building materials and construction methods, good governance, multilateral coordination, appropriate land-use planning and policies, consideration of different social needs, and balanced combination of long-term and short-term needs. Findings from this study should have an influence on policy development towards Post Natural Disaster Reconstruction and help with the achievement of sustainable objectives.

An analysis of the KEEP CLEAR pavement markings effects on queuing vehicles dynamic performance at urban signalised intersections

KEEP CLEAR pavement markings are widely used at urban signalised intersections to indicate to drivers to avoid entering blocked intersections. For example, ‘Box junctions’ are most widely used in the United Kingdom and other European countries. However, in Australia, KEEP CLEAR markings are mostly used to improve access from side roads onto a main road, especially when the side road is very close to a signalised intersection. This paper aims to reveal how the KEEP CLEAR markings affect the dynamic performance of the queuing vehicles on the main road, where the side road access is near a signalised intersection. Raw traffic field data was collected from an intersection at the Gold Coast, Australia, and the Kanade–Lucas–Tomasi (KLT) feature tracker approach was used to extract dynamic vehicle data from the raw video footage. The data analysis reveals that the KEEP CLEAR markings generate positive effects on the queuing vehicles in discharge on the main road. This finding refutes the traditional viewpoint that the KEEP CLEAR pavement markings will cause delay for the queuing vehicles’ departure due to the enlarged queue spacing. Further studies are suggested in this paper as well.

Urinary biomolecular indicators of exercise-induced over exertion injury

Poor health and injury represent major obstacles to the future economic security of Australia. The national economic cost of work-related injury is estimated at $57.5 billion p/a. Since exposure to high physical demands is a major risk factor for musculoskeletal injury, monitoring and managing such physical activity levels in workers is a potentially important injury prevention strategy. Current injury monitoring practices are inadequate for the provision of clinically valuable information about the tissue specific responses to physical exertion. Injury of various soft tissue structures can manifest over time through accumulation of micro-trauma. Such micro-trauma has a propensity to increase the risk of acute injuries to soft-tissue structures such as muscle or tendon. As such, the capacity to monitor biomarkers that result from the disruption of these tissues offers a means of assisting the pre-emptive management of subclinical injury prior to acute failure or for evaluation of recovery processes. Here we have adopted an in-vivo exercise induced muscle damage model allowing the application of laboratory controlled conditions to assist in uncovering biochemical indicators associated with soft-tissue trauma and recovery. Importantly, urine was utilised as the diagnostic medium since it is non-invasive to collect, more acceptable to workers and less costly to employers. Moreover, it is our hypothesis that exercise induced tissue degradation products enter the circulation and are subsequently filtered by the kidney and pass through to the urine. To test this hypothesis a range of metabolomic and proteomic discovery-phase techniques were used, along with targeted approaches. Several small molecules relating to tissue damage were identified along with a series of skeletal muscle-specific protein fragments resulting from exercise induced soft-tissue damage. Each of the potential biomolecular markers appeared to be temporally present within urine. Moreover, the regulation of abundance seemed to be associated with functional recovery following the injury. This discovery may have important clinical applications for monitoring of a variety of inflammatory myopathies as well as novel applications in monitoring of the musculoskeletal health status of workers, professional athletes and/or military personnel to reduce the onset of potentially debilitating musculoskeletal injuries within these professions.

Development and validation of a ultra performance LC-ESI/MS method for analysis of metabolic phenotypes of healthy men in day and night urine samples

Ultra-performance LC coupled to quadrupole TOF/MS (UPLC-QTOF/MS) in positive and negative ESI was developed and validated to analyze metabolite profiles for urine from healthy men during the day and at night. Data analysis using principal components analysis (PCA) revealed differences between metabolic phenotypes of urine in healthy men during the day and at night. Positive ions with mass-to-charge ratio (m/z) 310.24 (5.35 min), 286.24 (4.74 min) and 310.24 (5.63 min) were elevated in the urine from healthy men at night compared to that during the day. Negative ions elevated in day urine samples of healthy men included m/z 167.02 (0.66 min), 263.12 (2.55 min) and 191.03 (0.73 min), whilst ions m/z 212.01 (4.77 min) were at a lower concentration in urine of healthy men during the day compared to that at night. The ions m/z 212.01 (4.77 min), 191.03 (0.73 min) and 310.24 (5.35 min) preliminarily correspond to indoxyl sulfate, citric acid and N-acetylneuraminic acid, providing further support for an involvement of phenotypic difference in urine of healthy men in day and night samples, which may be associated with notably different activities of gut microbiota, velocity of tricarboxylic acid cycle and activity of sialic acid biosynthesis in healthy men as regulated by circadian rhythm of the mammalian bioclock.

Response to chemotherapy is predictive in relation to longer overall survival in an individual patient combined-analysis with pleural mesothelioma

Background: There is currently no early predictive marker of survival for patients receiving chemotherapy for malignant pleural mesothelioma (MPM). Tumour response may be predictive for overall survival (OS), though this has not been explored. We have thus undertaken a combined-analysis of OS, from a 42 day landmark, of 526 patients receiving systemic therapy for MPM. We also validate published progression-free survival rates (PFSRs) and a progression-free survival (PFS) prognostic-index model. Methods: Analyses included nine MPM clinical trials incorporating six European Organisation for Research and Treatment of Cancer (EORTC) studies. Analysis of OS from landmark (from day 42 post-treatment) was considered regarding tumour response. PFSR analysis data included six non-EORTC MPM clinical trials. Prognostic index validation was performed on one non-EORTC data-set, with available survival data. Results: Median OS, from landmark, of patients with partial response (PR) was 12·8 months, stable disease (SD), 9·4 months and progressive disease (PD), 3·4 months. Both PR and SD were associated with longer OS from landmark compared with disease progression (both p < 0·0001). PFSRs for platinum-based combination therapies were consistent with published significant clinical activity ranges. Effective separation between PFS and OS curves provided a validation of the EORTC prognostic model, based on histology, stage and performance status. Conclusion: Response to chemotherapy is associated with significantly longer OS from landmark in patients with MPM. © 2012 Elsevier Ltd. All rights reserved.

The multi-platform user engagement and data visualisation tool

The ability to identify and assess user engagement with transmedia productions is vital to the success of individual projects and the sustainability of this mode of media production as a whole. It is essential that industry players have access to tools and methodologies that offer the most complete and accurate picture of how audiences/users engage with their productions and which assets generate the most valuable returns of investment. Drawing upon research conducted with Hoodlum Entertainment, a Brisbane-based transmedia producer, this project involved an initial assessment of the way engagement tends to be understood, why standard web analytics tools are ill-suited to measuring it, how a customised tool could offer solutions, and why this question of measuring engagement is so vital to the future of transmedia as a sustainable industry. Working with data provided by Hoodlum Entertainment and Foxtel Marketing, the outcome of the study was a prototype for a custom data visualisation tool that allowed access, manipulation and presentation of user engagement data, both historic and predictive. The prototyped interfaces demonstrate how the visualization tool would collect and organise data specific to multiplatform projects by aggregating data across a number of platform reporting tools. Such a tool is designed to encompass not only platforms developed by the transmedia producer but also sites developed by fans. This visualisation tool accounted for multiplatform experience projects whose top level is comprised of people, platforms and content. People include characters, actors, audience, distributors and creators. Platforms include television, Facebook and other relevant social networks, literature, cinema and other media that might be included in the multiplatform experience. Content refers to discreet media texts employed within the platform, such as tweet, a You Tube video, a Facebook post, an email, a television episode, etc. Core content is produced by the creators’ multiplatform experiences to advance the narrative, while complimentary content generated by audience members offers further contributions to the experience. Equally important is the timing with which the components of the experience are introduced and how they interact with and impact upon each other. Being able to combine, filter and sort these elements in multiple ways we can better understand the value of certain components of a project. It also offers insights into the relationship between the timing of the release of components and user activity associated with them, which further highlights the efficacy (or, indeed, failure) of assets as catalysts for engagement. In collaboration with Hoodlum we have developed a number of design scenarios experimenting with the ways in which data can be visualised and manipulated to tell a more refined story about the value of user engagement with certain project components and activities. This experimentation will serve as the basis for future research.

Utilising hospital data to inform product safety prioritisation : the application of RAPEX severity rankings in ICD-coded burn data

Background The implementation of the Australian Consumer Law in 2011 highlighted the need for better use of injury data to improve the effectiveness and responsiveness of product safety (PS) initiatives. In the PS system, resources are allocated to different priority issues using risk assessment tools. The rapid exchange of information (RAPEX) tool to prioritise hazards, developed by the European Commission, is currently being adopted in Australia. Injury data is required as a basic input to the RAPEX tool in the risk assessment process. One of the challenges in utilising injury data in the PS system is the complexity of translating detailed clinical coded data into broad categories such as those used in the RAPEX tool. Aims This study aims to translate hospital burns data into a simplified format by mapping the International Statistical Classification of Disease and Related Health Problems (Tenth Revision) Australian Modification (ICD-10-AM) burn codes into RAPEX severity rankings, using these rankings to identify priority areas in childhood product-related burns data. Methods ICD-10-AM burn codes were mapped into four levels of severity using the RAPEX guide table by assigning rankings from 1-4, in order of increasing severity. RAPEX rankings were determined by the thickness and surface area of the burn (BSA) with information extracted from the fourth character of T20-T30 codes for burn thickness, and the fourth and fifth characters of T31 codes for the BSA. Following the mapping process, secondary data analysis of 2008-2010 Queensland Hospital Admitted Patient Data Collection (QHAPDC) paediatric data was conducted to identify priority areas in product-related burns. Results The application of RAPEX rankings in QHAPDC burn data showed approximately 70% of paediatric burns in Queensland hospitals were categorised under RAPEX levels 1 and 2, 25% under RAPEX 3 and 4, with the remaining 5% unclassifiable. In the PS system, prioritisations are made to issues categorised under RAPEX levels 3 and 4. Analysis of external cause codes within these levels showed that flammable materials (for children aged 10-15yo) and hot substances (for children aged <2yo) were the most frequently identified products. Discussion and conclusions The mapping of ICD-10-AM burn codes into RAPEX rankings showed a favourable degree of compatibility between both classification systems, suggesting that ICD-10-AM coded burn data can be simplified to more effectively support PS initiatives. Additionally, the secondary data analysis showed that only 25% of all admitted burn cases in Queensland were severe enough to trigger a PS response.

Retaining the thin blue line : What shapes workers' intentions not to quit the current work environment

Purpose – The purpose of this paper is to investigate the relationship between workplace factors and the intentions of police officers to quit their current department. Design/methodology/approach – Data from a survey of Baltimore officers, designed to examine the relationship between police stress and domestic violence in police families were used. Using multivariate regression analysis, the authors focus on the officers' stated intentions to look for alternative employment, with proxies for social and workplace factors. Findings – Higher levels of cooperation (trust), interactional justice and work-life-balance reduce police officers' intentions to quit. While high levels of physical and psychological strain and trauma are not correlated with intentions to quit. Research limitations/implications – A discernible limitation of this study is the age of the data analyzed and that many changes have occurred in recent times (policing and social). It would be of great interest to repeat this study to gauge the true effect. Practical implications – There are policy implications for retention and recruitment: it may possible to decrease the ethnic and gender gaps, through identifying officers at risk and creating programs to hold existing minorities, recruit more, whilst maintaining a strong, happy and healthy department. Originality/value – This study examines the impact of workplace factors on quitting intention for police officers. It is demonstrated that social capital, fairness and work-life balance are moderators for quitting, adding to the literature on worker retention, as little research has been done using multivariate analysis on quitting intentions.

Utilising hospital data to inform product safety prioritisation : the application of RAPEX severity rankings in ICD-coded Burn Data

Background The implementation of the Australian Consumer Law in 2011 highlighted the need for better use of injury data to improve the effectiveness and responsiveness of product safety (PS) initiatives. In the PS system, resources are allocated to different priority issues using risk assessment tools. The rapid exchange of information (RAPEX) tool to prioritise hazards, developed by the European Commission, is currently being adopted in Australia. Injury data is required as a basic input to the RAPEX tool in the risk assessment process. One of the challenges in utilising injury data in the PS system is the complexity of translating detailed clinical coded data into broad categories such as those used in the RAPEX tool. Aims This study aims to translate hospital burns data into a simplified format by mapping the International Statistical Classification of Disease and Related Health Problems (Tenth Revision) Australian Modification (ICD-10-AM) burn codes into RAPEX severity rankings, using these rankings to identify priority areas in childhood product-related burns data. Methods ICD-10-AM burn codes were mapped into four levels of severity using the RAPEX guide table by assigning rankings from 1-4, in order of increasing severity. RAPEX rankings were determined by the thickness and surface area of the burn (BSA) with information extracted from the fourth character of T20-T30 codes for burn thickness, and the fourth and fifth characters of T31 codes for the BSA. Following the mapping process, secondary data analysis of 2008-2010 Queensland Hospital Admitted Patient Data Collection (QHAPDC) paediatric data was conducted to identify priority areas in product-related burns. Results The application of RAPEX rankings in QHAPDC burn data showed approximately 70% of paediatric burns in Queensland hospitals were categorised under RAPEX levels 1 and 2, 25% under RAPEX 3 and 4, with the remaining 5% unclassifiable. In the PS system, prioritisations are made to issues categorised under RAPEX levels 3 and 4. Analysis of external cause codes within these levels showed that flammable materials (for children aged 10-15yo) and hot substances (for children aged <2yo) were the most frequently identified products. Discussion and conclusions The mapping of ICD-10-AM burn codes into RAPEX rankings showed a favourable degree of compatibility between both classification systems, suggesting that ICD-10-AM coded burn data can be simplified to more effectively support PS initiatives. Additionally, the secondary data analysis showed that only 25% of all admitted burn cases in Queensland were severe enough to trigger a PS response.

Rapid scanning of spectrograms for efficient identification of bioacoustic events in big data

Acoustic sensing is a promising approach to scaling faunal biodiversity monitoring. Scaling the analysis of audio collected by acoustic sensors is a big data problem. Standard approaches for dealing with big acoustic data include automated recognition and crowd based analysis. Automatic methods are fast at processing but hard to rigorously design, whilst manual methods are accurate but slow at processing. In particular, manual methods of acoustic data analysis are constrained by a 1:1 time relationship between the data and its analysts. This constraint is the inherent need to listen to the audio data. This paper demonstrates how the efficiency of crowd sourced sound analysis can be increased by an order of magnitude through the visual inspection of audio visualized as spectrograms. Experimental data suggests that an analysis speedup of 12× is obtainable for suitable types of acoustic analysis, given that only spectrograms are shown.