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Sample records for australia monitoring prediction

  1. Using a multi-parameter monitoring methodology to predict failures in the cryogenic plant of the cold neutron source at Australia's OPAL reactor

    NASA Astrophysics Data System (ADS)

    Lu, Weijian; Thiering, Russell

    2012-06-01

    A 5 kW Brayton-cycle helium refrigeration plant provides cooling at 20 K to the Cold Neutron Source (CNS) at Australia's OPAL Reactor. During several years of operation to the present day, the plant has experienced an unusually high number of turbine and compressor failures. The root cause for some of the failures is known, but for others remains to be determined. All of the failures were catastrophic without any prior warning from standard industrial monitoring based on singular process variables such as temperature, pressure and vibration. The failures and the down time they caused have been very costly. As the operator of the plant, we have developed a multi-parameter monitoring (MPM) methodology to track the performance of the plant. The methodology utilises indicators obtained from a combination of process variables based on their thermodynamic relations. By studying the historical trends of appropriate indicators, especially during the past failures, we have found some indicators that would be able to improve our predictive capability so that we can avoid similar failures in the future.

  2. Predicting the course of AIDS in Australia.

    PubMed

    Solomon, P J; Wilson, S R; Swanson, C E; Cooper, D A

    1990-10-01

    There have been urgent demands for knowledge about the epidemic of the acquired immunodeficiency syndrome (AIDS) in Australia. Accurate predictions are important for efficient allocation and planning of limited health-care resources. Ideal data for this purpose would be reliable knowledge of the past and present incidence of human immunodeficiency virus (HIV) infection. However, since the incidence of the infection is unknown predictions can only be based on historical data of the incidence of AIDS. In this article, we show the limitations of such predictions by examining a broad range of mathematical models that successfully track the observed data (1187 cases diagnosed to December 31, 1988). In addition, we describe a simple method for prediction in subgroups where the numbers of cases observed so far are small. Four models representing different forms of departure from the simple exponential model provide the best fits to the Australian AIDS data. Regional variability and a possible effect resulting from the introduction of zidovudine were incorporated into the models. Significant regional variability in the course of the epidemic was observed between New South Wales, Victoria and the rest of the country. For Australia as a whole, the doubling time changed from less than one year before mid 1987 to more than two years after this time. Model fits were improved by fitting the models to just the four years of data from 1985. The models give comparable predictions for the first year (1989) of around 600 new cases. However, by 1993 the predictions vary considerably, ranging from 500 to 2300 new cases. It is predicted that between 3100 and 6700 cases are likely to be diagnosed in Australia between 1989 and 1993. The results from the subgroup prediction demonstrate that when the observed number of cases is small, then the range of predictions for a future time interval is very wide. For reliable long-term predictions that are necessary for public health planning, basic

  3. Building a Continental Scale Land Cover Monitoring Framework for Australia

    NASA Astrophysics Data System (ADS)

    Thankappan, Medhavy; Lymburner, Leo; Tan, Peter; McIntyre, Alexis; Curnow, Steven; Lewis, Adam

    2012-04-01

    Land cover information is critical for national reporting and decision making in Australia. A review of information requirements for reporting on national environmental indicators identified the need for consistent land cover information to be compared against a baseline. A Dynamic Land Cover Dataset (DLCD) for Australia has been developed by Geoscience Australia and the Australian Bureau of Agriculture and Resource Economics and Sciences (ABARES) recently, to provide a comprehensive and consistent land cover information baseline to enable monitoring and reporting for sustainable farming practices, water resource management, soil erosion, and forests at national and regional scales. The DLCD was produced from the analysis of Enhanced Vegetation Index (EVI) data at 250-metre resolution derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the period from 2000 to 2008. The EVI time series data for each pixel was modelled as 12 coefficients based on the statistical, phenological and seasonal characteristics. The time series were then clustered in coefficients spaces and labelled using ancillary information on vegetation and land use at the catchment scale. The accuracy of the DLCD was assessed using field survey data over 25,000 locations provided by vegetation and land management agencies in State and Territory jurisdictions, and by ABARES. The DLCD is seen as the first in a series of steps to build a framework for national land cover monitoring in Australia. A robust methodology to provide annual updates to the DLCD is currently being developed at Geoscience Australia. There is also a growing demand from the user community for land cover information at better spatial resolution than currently available through the DLCD. Global land cover mapping initiatives that rely on Earth observation data offer many opportunities for national and international programs to work in concert and deliver better outcomes by streamlining efforts on development and

  4. ECLSS predictive monitoring

    NASA Technical Reports Server (NTRS)

    Doyle, Richard J.; Chien, Steve A.

    1991-01-01

    On Space Station Freedom (SSF), design iterations have made clear the need to keep the sensor complement small. Along with the unprecendented duration of the mission, it is imperative that decisions regarding placement of sensors be carefully examined and justified during the design phase. In the ECLSS Predictive Monitoring task, we are developing AI-based software to enable design engineers to evaluate alternate sensor configurations. Based on techniques from model-based reasoning and information theory, the software tool makes explicit the quantitative tradeoffs among competing sensor placements, and helps designers explore and justify placement decisions. This work is being applied to the Environmental Control and Life Support System (ECLSS) testbed at MSFC to assist design personnel in placing sensors for test purposes to evaluate baseline configurations and ultimately to select advanced life support system technologies for evolutionary SSF.

  5. Australia.

    PubMed

    1984-05-01

    This discussion of Australia covers the following: the people, geography, history, government, political conditions, economy, foreign relations and defense, and relations between the US and Australia. In 1983 the population of Australia totaled 15.3 million with an annual growth rate of 1.3%. The infant mortality rate is 9.9/1000 live births with a life expectancy of 74 years. The people of Australia are predominantly of British origin, and their culture and outlook are similar to those of the US. The aboriginal population is estimated to be 1% of the total. Much of Australia's culture is derived from European roots, but distinctive Australian trends have evolved from the environment, aboriginal culture, and the influence of Australia's neighbors. Australia, the world's smallest continent but 1 of the largest nations, is located below the Southeast Asian archipelago and is bounded on the east by the Pacific Ocean and on the west by the Indian Ocean. Most of the continent is a low, irregular plateau. Little is known of Australia before its discovery by Dutch explorers in the 17th century. On January 26, 1788 the Colony of New South Wales was founded and formal proclamation on the site of Sydney followed on February 7. Many of the 1st settlers were convicts. The mid-19th century began a policy of emancipation of convicts and assisted immigration of free people. The 1st federal Parliament was opened at Melbourne in May 1901. Australia passed the Statute of Westminster Adoption Act in 1942, which officially established Australia's complete autonomy in both internal and external affairs. The Commonwealth government was created with a constitution patterned partly on the US constitution. Australia is a fully independent nation within the Commonwealth. The federal Parliament is bicameral, consisting of a Senate and a House of Representatives. At the apex of the court system is the High Court of Australia. The 3 main political groups in Australia are the Liberal Party, the

  6. On predicting monitoring system effectiveness

    NASA Astrophysics Data System (ADS)

    Cappello, Carlo; Sigurdardottir, Dorotea; Glisic, Branko; Zonta, Daniele; Pozzi, Matteo

    2015-03-01

    While the objective of structural design is to achieve stability with an appropriate level of reliability, the design of systems for structural health monitoring is performed to identify a configuration that enables acquisition of data with an appropriate level of accuracy in order to understand the performance of a structure or its condition state. However, a rational standardized approach for monitoring system design is not fully available. Hence, when engineers design a monitoring system, their approach is often heuristic with performance evaluation based on experience, rather than on quantitative analysis. In this contribution, we propose a probabilistic model for the estimation of monitoring system effectiveness based on information available in prior condition, i.e. before acquiring empirical data. The presented model is developed considering the analogy between structural design and monitoring system design. We assume that the effectiveness can be evaluated based on the prediction of the posterior variance or covariance matrix of the state parameters, which we assume to be defined in a continuous space. Since the empirical measurements are not available in prior condition, the estimation of the posterior variance or covariance matrix is performed considering the measurements as a stochastic variable. Moreover, the model takes into account the effects of nuisance parameters, which are stochastic parameters that affect the observations but cannot be estimated using monitoring data. Finally, we present an application of the proposed model to a real structure. The results show how the model enables engineers to predict whether a sensor configuration satisfies the required performance.

  7. Predicting milk yield in sheep used for dairying in Australia.

    PubMed

    Morrissey, A D; Cameron, A W N; Caddy, D J; Tilbrook, A J

    2007-11-01

    It is necessary to identify traits that are simple to measure and correlated with milk yield to select ewes for dairying from existing populations of sheep in Australia. We studied 217 primiparous and 113 multiparous (second parity, n = 51; third parity, n = 40; and fourth parity, n = 22) East Friesian crossbred ewes, for 2 consecutive lactations, that were milked by machine following a period of suckling (24 to 28 d). We measured lamb growth, milk production, milk yield, and residual milk during early lactation (predicts milk yield. Milk production at weaning, or the amount of residual milk, or both, predict milk yield within lactations. These measures also predict milk yield between lactations. Lambs were weighed at birth and weaning and milk production in ewes was measured using a 4-h milk production test at d 5 of lactation and at weaning. Following weaning, ewes were milked twice daily and milk yield was recorded weekly for 8 wk and once a month thereafter. Milk production (using a 16-h milk production test) and residual milk were measured at weaning, and again 1 wk and 4 wk later. Milk yield to 120 d was correlated (r2 = 0.39) between lactations, and 120-d milk yield (primiparous 82.7 +/- 2.0 L; multiparous 107.1 +/- 4.2 L; second lactation 146 +/- 3.7 L) can be predicted after 4 wk of machine milking using a single measurement of either daily milk yield (primiparous 770 +/- 25 mL/d; multiparous 940 +/- 44 mL/d; second lactation 1,372 +/- 46 mL/d, r2 = 0.60 to 0.65) or daily milk production (primiparous 1,197 +/- 27 mL/d; multiparous 1,396 +/- 62 mL/d; second lactation 1,707 +/- 45 mL/d, r2 = 0.50 to 0.53). Residual milk in primiparous ewes (38%) and multiparous ewes (34%) was high (292 +/- 11 and 321 +/- 20 mL, respectively) in the first lactation, but lower (17%) in the second lactation (238 +/- 17 mL). Residual milk and 120-d milk yield were not

  8. Australia

    ERIC Educational Resources Information Center

    Inglis, Christine

    1986-01-01

    Examines educational provisions for ethnic and racial groups in Australia, comprised primarily of the aborigines and the migrants or non-English speaking immigrants. Discussion of the official policies of "self determination" and "multiculturalism" emphasizes the important differences between the two and the considerations given them by the…

  9. Australia.

    PubMed

    1989-03-01

    The smallest continent and one of the largest countries, Australia is a country of diverse geographical conditions and differing cultures of people unified by one predominant language and political system. Mountains, desert and rivers are some of the varying landscape features of Australia, although the climate and condition for most of the country is tropical. Original Australians, a hunting-gathering people called Aborigines, came to Australia over 38,000 years ago. Today the Aborigines compose about 1% of the population and live in traditional tribal areas as well as cities. The 1st European settlement came in 1788 from Great Britain. After World War II, the population doubled. Although the population is primarily composed of British and Irish immigrants, immigrants from other European countries such as Italy and Greece as well as refugees from Indochina, Vietnam, Cambodia and Laos are a significant factor to the growing Australian population. Australian and Aboriginal culture has took hold and took notice in the areas of opera, art, literature and film. The Australian Commonwealth is based on a constitution similar to that of the United States government. The National Parliament is bicameral with both the Senate and the House of Representatives having a select number of elected officials from each state and territory. The Australian economy is predominantly reliant on the sale of mineral and agricultural exports. History, economic changes, defense, international relations and notes to the traveler are also discussed in this overview of Australia. PMID:12177993

  10. Monitoring the Galactic Centre with the Australia Telescope Compact Array

    NASA Astrophysics Data System (ADS)

    Borkar, A.; Eckart, A.; Straubmeier, C.; Kunneriath, D.; Jalali, B.; Sabha, N.; Shahzamanian, B.; García-Marín, M.; Valencia-S, M.; Sjouwerman, L.; Britzen, S.; Karas, V.; Dovčiak, M.; Donea, A.; Zensus, A.

    2016-05-01

    The supermassive black hole, Sagittarius A* (Sgr A*), at the centre of the Milky Way undergoes regular flaring activity, which is thought to arise from the innermost region of the accretion flow. Between 2010 and 2014, we performed monitoring observations of the Galactic Centre to study the flux-density variations at 3 mm using the Australia Telescope Compact Array (ATCA). We obtain light curves of Sgr A* by subtracting the contributions from the extended emission around it, and the elevation and time-dependent gains of the telescope. We perform structure function analysis and the Bayesian blocks representation to detect flare events. The observations detect six instances of significant variability in the flux density of Sgr A* in three observations, with variations between 0.5 and 1.0 Jy, which last for 1.5-3 h. We use the adiabatically expanding plasmon model to explain the short time-scale variations in the flux density. We derive the physical quantities of the modelled flare emission, such as the source expansion speed vexp, source sizes, spectral indices and the turnover frequency. These parameters imply that the expanding source components are either confined to the immediate vicinity of Sgr A* by contributing to the corona or the disc, or have a bulk motion greater than vexp. No exceptional flux-density variation on short flare time-scales was observed during the approach and the flyby of the dusty S-cluster object (DSO/G2). This is consistent with its compactness and the absence of a large bow shock.

  11. Seasonal Dynamical Prediction of Coral Bleaching in the Great Barrier Reef, Australia

    NASA Astrophysics Data System (ADS)

    Spillman, C. M.; Alves, O.

    2009-05-01

    Sea surface temperature (SST) is now recognised as the primary cause of mass coral bleaching events. Coral bleaching occurs during times of stress, particularly when SSTs exceed the coral colony's tolerance level. Global warming is potentially a serious threat to the future of the world's reef systems with predictions by the international community that bleaching will increase in both frequency and severity. Advance warning of anomalous sea surface temperatures, and thus potential bleaching events, would allow for the implementation of management strategies to minimise reef damage. Seasonal SST forecasts from the coupled ocean-atmosphere model POAMA (Bureau of Meteorology) have skill in the Great Barrier Reef (Australia) several months into the future. We will present model forecasts and probabilistic products for use in reef management, and assess model skill in the region. These products will revolutionise the way in which coral bleaching events are monitored and assessed in the Great Barrier Reef and Australian region.

  12. Monitoring International Interest in Transnational Academic Mobility to Australia

    ERIC Educational Resources Information Center

    Hopkins, John L.

    2011-01-01

    This research examines the issue of transnational academic mobility of academic staff looking at potential moves to higher education institutions in Australia. By establishing a web-based portal, attracting interested parties from around the world with information about Australian universities and subsequent career opportunities, web analytics are…

  13. The appropriateness of opt-out consent for monitoring childhood obesity in Australia.

    PubMed

    Lacy, K; Kremer, P; de Silva-Sanigorski, A; Allender, S; Leslie, E; Jones, L; Fornaro, S; Swinburn, B

    2012-10-01

    Childhood obesity monitoring is a fundamental component of obesity prevention but is poorly done in Australia. Monitoring obesity prevalence in children provides important population health data that can be used to track trends over time, identify areas at greatest risk of obesity, determine the effectiveness of interventions and policies, raise awareness and stimulate action. High participation rates are essential for effective monitoring because these provide more representative data. Passive ('opt-out') consent has been shown to provide high participation rates in international childhood obesity monitoring programs and in a recent Australian federal initiative monitoring early child development. A federal initiative structured like existing child development monitoring programs, but with the authority to collect height and weight measurements using opt-out consent, is recommended to monitor rates of childhood obesity in Australia. PMID:22888020

  14. Prediction and monitoring of volcanic activities

    SciTech Connect

    Sudradjat, A.

    1986-07-01

    This paper summarizes the state of the art for predicting and monitoring volcanic activities, and it emphasizes the experience obtained by the Volcanological Survey Indonesia for active volcanoes. The limited available funds, the large number of active volcanoes to monitor, and the high population density of the volcanic area are the main problems encountered. Seven methods of volcano monitoring are applied to the active volcanoes of Indonesia: seismicity, ground deformation, gravity and magnetic studies, self-potential studies, petrochemistry, gas monitoring, and visual observation. Seismic monitoring augmented by gas monitoring has proven to be effective, particularly for predicting individual eruptions at the after-initial phase. However, the success of the prediction depends on the characteristics of each volcano. In general, the initial eruption phase is the most difficult phenomenon to predict. The preparation of hazard maps and the continuous awareness of the volcanic eruption are the most practical ways to mitigate volcanic danger.

  15. Designing optimal greenhouse gas monitoring networks for Australia

    NASA Astrophysics Data System (ADS)

    Ziehn, T.; Law, R. M.; Rayner, P. J.; Roff, G.

    2016-01-01

    Atmospheric transport inversion is commonly used to infer greenhouse gas (GHG) flux estimates from concentration measurements. The optimal location of ground-based observing stations that supply these measurements can be determined by network design. Here, we use a Lagrangian particle dispersion model (LPDM) in reverse mode together with a Bayesian inverse modelling framework to derive optimal GHG observing networks for Australia. This extends the network design for carbon dioxide (CO2) performed by Ziehn et al. (2014) to also minimise the uncertainty on the flux estimates for methane (CH4) and nitrous oxide (N2O), both individually and in a combined network using multiple objectives. Optimal networks are generated by adding up to five new stations to the base network, which is defined as two existing stations, Cape Grim and Gunn Point, in southern and northern Australia respectively. The individual networks for CO2, CH4 and N2O and the combined observing network show large similarities because the flux uncertainties for each GHG are dominated by regions of biologically productive land. There is little penalty, in terms of flux uncertainty reduction, for the combined network compared to individually designed networks. The location of the stations in the combined network is sensitive to variations in the assumed data uncertainty across locations. A simple assessment of economic costs has been included in our network design approach, considering both establishment and maintenance costs. Our results suggest that, while site logistics change the optimal network, there is only a small impact on the flux uncertainty reductions achieved with increasing network size.

  16. Perceived coping & concern predict terrorism preparedness in Australia

    PubMed Central

    2012-01-01

    Background In the aftermath of major terrorist incidents research shows population shifts towards protective behaviours, including specific preparedness and avoidance responses. Less is known about individual preparedness in populations with high assumed threat but limited direct exposure, such as Australia. In this study we aimed to determine whether individuals with high perceived coping and higher concern would show greater preparedness to respond to terrorism threats. Methods Adults in New South Wales (NSW) completed terrorism perception and response questions as part of computer assisted telephone interviews (CATI) in 2010 (N=2038). Responses were weighted against the NSW population. Multiple logistic regression analyses were conducted to evaluate the relationship between personal coping/concern factors and terrorism-related preparedness and avoidance behaviours, and to control for potential confounders such as socio-demographic and threat perception factors. Results Increased vigilance for suspicious behaviours was the most commonly reported behavioural response to perceived terrorism threat. Multivariate analyses showed that the factor combination of high perceived coping and higher concern was the most consistent predictor of terrorism preparedness behaviours and evacuation intentions, including increased vigilance (Adjusted Odd Ratios (AOR)=2.07, p=0.001) learning evacuation plans (AOR=1.61, p=0.05), establishing emergency contact plans (AOR=2.73, p<0.001), willingness to evacuate homes (AOR=2.20, p=0.039), and willingness to evacuate workplaces or public facilities (AOR=6.19, p=0.015) during potential future incidents. Conclusion The findings of this study suggest that terrorism preparedness behaviours are strongly associated with perceived high coping but that this relationship is also mediated by personal concerns relating to this threat. Cognitive variables such as coping self-efficacy are increasingly targeted as part of natural hazard preparedness

  17. Predicting adolescent breakfast consumption in the UK and Australia using an extended theory of planned behaviour.

    PubMed

    Mullan, Barbara; Wong, Cara; Kothe, Emily

    2013-03-01

    The aim of this study was to investigate whether the theory of planned behaviour (TPB) with the addition of risk awareness could predict breakfast consumption in a sample of adolescents from the UK and Australia. It was hypothesised that the TPB variables of attitudes, subjective norm and perceived behavioural control (PBC) would significantly predict intentions, and that inclusion of risk perception would increase the proportion of variance explained. Secondly it was hypothesised that intention and PBC would predict behaviour. Participants were recruited from secondary schools in Australia and the UK. A total of 613 participants completed the study (448 females, 165 males; mean=14years ±1.1). The TPB predicted 42.2% of the variance in intentions to eat breakfast. All variables significantly predicted intention with PBC as the strongest component. The addition of risk made a small but significant contribution to the prediction of intention. Together intention and PBC predicted 57.8% of the variance in breakfast consumption. PMID:23219456

  18. Improving Climate Prediction By Climate Monitoring

    NASA Astrophysics Data System (ADS)

    Leroy, S. S.; Redaelli, G.; Grassi, B.

    2014-12-01

    Various climate agencies are pursuing concepts of space-based atmospheric monitoring based on ideas of empirically verifiable accuracy in observations. Anticipating that atmospheric monitoring systems based in observing the emitted longwave spectrum, the reflected shortwave spectrum, and radio occultation are implemented, we seek to discover how long-term records in these quantities might be used to improve our ability to predict climate change. This is a follow-up to a previous study that found that climate monitoring by remote sensing better informs climate prediction than does climate monitoring in situ. We have used the output of a CMIP5 historical scenario to hind-cast observation types being considered for space-based atmospheric monitoring to modify ensemble prediction of multi-decadal climate change produced by a CMIP5 future scenario. Specifically, we have considered spatial fingerprints of 1970­-2005 averages and trends in hind-cast observations to improve global average surface air temperature change from 2005 to 2100. Correlations between hind-cast observations at individual locations on the globe and multi-decadal change are generally consistent with a null-correlation distribution. We have found that the modes in inter-model differences in hind-casts are clearly identified with tropical clouds, but only Arctic warming as can be identified in radio occultation observations correlates with multi-decadal change, but only with 80% confidence. Understanding how long-term monitoring can be used to improve climate prediction remains an unsolved problem, but it is anticipated that improving climate prediction will depend strongly on an ability to distinguish between climate forcing and climate response in remotely sensed observables.

  19. Long-term marine litter monitoring in the remote Great Australian Bight, South Australia.

    PubMed

    Edyvane, K S; Dalgetty, A; Hone, P W; Higham, J S; Wace, N M

    2004-06-01

    The Anxious Bay beach litter clearance is the longest running annual survey of ocean-based litter in Australia. It's remoteness from centres of human population and location (with respect to prevailing winds and currents) make it an ideal place for monitoring ocean or ship-based litter in Australia's southern oceans and particularly, the Great Australian Bight. Over the 1991-1999 period, a large but gradual decline in the amount of beach washed litter was recorded (with minor peaks recorded during the 1992 and 1994 surveys). Beach washed litter decreased by approximately 86%, from 344 kg recorded in 1991 (13.2 kg/km) to 49 kg in 1999 (i.e. 1.9 kg/km), reaching a maximum of 390 kg in 1992 (or 15 kg/km of beach). However, a sharp increase in litter was recorded in 2000 (i.e. 252 kg or 9.7 kg/km). This increase in litter yield in 2000 is probably due to stronger than average onshore surface flow (or Ekman Transport) in the western Eyre Peninsula and Bight region. Prior to the survey in 2000, the results appeared to indicate that ocean litter on Anxious Bay beach was beginning to level out at around 50-70 kg/year (i.e. 2-3 kg/km). As the beach surveys involve the assumption that the beach is completely cleared of litter, this may represent a baseline level for ocean-based litter in the region. The yields and type of litter collected from the annual survey indicates that the majority of litter washed ashore originates from commercial fishing activities within the Great Australian Bight. Most of the fishing-related litter was directly sourced to the Southern Rock Lobster Fishery (i.e. bait buckets, baskets, pots), the Great Australian Bight Trawl Fishery (i.e. codends, trawl nets) and the Southern Shark Fishery (i.e. monofilament gillnets and longlines). Between 1994 and 1999, large reductions were observed in the amount of bait straps (77% reduction), lobster bait baskets/buckets (86% reduction), nets/ropes (62% reduction) and floats/buoys (83% reduction). Significantly

  20. Monitoring and adaptive resistance management in Australia for Bt-cotton: current status and future challenges.

    PubMed

    Downes, Sharon; Mahon, Rod; Olsen, Karen

    2007-07-01

    In the mid-1990 s the Australian Cotton industry adopted an insect-resistant variety of cotton (Ingard) which expresses the Bt toxin Cry1Ac that is specific to a group of insects including the target Helicoverpa armigera. A conservative resistance management plan (RMP), that restricted the area planted to Ingard, was implemented to preserve the efficacy of Cry1Ac until two-gene transgenic cotton was available. In 2004/05 Bollgard II replaced Ingard as the transgenic cotton available in Australia. It improves on Ingard by incorporating an additional insecticidal protein (Cry2Ab). If an appropriate refuge is grown, there is no restriction on the area planted to Bollgard II. In 2004/05 and 2005/06 the Bollgard II acreage represented approximately 80 of the total area planted to cotton in Australia. The sensitivity of field-collected populations of H. armigera to Bt products was assayed before and subsequent to the widespread deployment of Ingard cotton. In 2002 screens against Cry2Ab were developed in preparation for replacement of Ingard with Bollgard II. There have been no reported field failures of Bollgard II due to resistance. However, while alleles that confer resistance to H. armigera in the field are rare for Cry1Ac, they are surprisingly common for Cry2Ab. We present an overview of the current approach adopted in Australia to monitor and adaptively manage resistance to Bt-cotton in field populations of H. armigera and discuss the implications of our findings to date. We also highlight future challenges for resistance management in Australia, many of which extend to other Bt-crop and pest systems. PMID:17470372

  1. Global integrated drought monitoring and prediction system

    PubMed Central

    Hao, Zengchao; AghaKouchak, Amir; Nakhjiri, Navid; Farahmand, Alireza

    2014-01-01

    Drought is by far the most costly natural disaster that can lead to widespread impacts, including water and food crises. Here we present data sets available from the Global Integrated Drought Monitoring and Prediction System (GIDMaPS), which provides drought information based on multiple drought indicators. The system provides meteorological and agricultural drought information based on multiple satellite-, and model-based precipitation and soil moisture data sets. GIDMaPS includes a near real-time monitoring component and a seasonal probabilistic prediction module. The data sets include historical drought severity data from the monitoring component, and probabilistic seasonal forecasts from the prediction module. The probabilistic forecasts provide essential information for early warning, taking preventive measures, and planning mitigation strategies. GIDMaPS data sets are a significant extension to current capabilities and data sets for global drought assessment and early warning. The presented data sets would be instrumental in reducing drought impacts especially in developing countries. Our results indicate that GIDMaPS data sets reliably captured several major droughts from across the globe. PMID:25977759

  2. Global integrated drought monitoring and prediction system.

    PubMed

    Hao, Zengchao; AghaKouchak, Amir; Nakhjiri, Navid; Farahmand, Alireza

    2014-01-01

    Drought is by far the most costly natural disaster that can lead to widespread impacts, including water and food crises. Here we present data sets available from the Global Integrated Drought Monitoring and Prediction System (GIDMaPS), which provides drought information based on multiple drought indicators. The system provides meteorological and agricultural drought information based on multiple satellite-, and model-based precipitation and soil moisture data sets. GIDMaPS includes a near real-time monitoring component and a seasonal probabilistic prediction module. The data sets include historical drought severity data from the monitoring component, and probabilistic seasonal forecasts from the prediction module. The probabilistic forecasts provide essential information for early warning, taking preventive measures, and planning mitigation strategies. GIDMaPS data sets are a significant extension to current capabilities and data sets for global drought assessment and early warning. The presented data sets would be instrumental in reducing drought impacts especially in developing countries. Our results indicate that GIDMaPS data sets reliably captured several major droughts from across the globe. PMID:25977759

  3. Predicting asthma exacerbations employing remotely monitored adherence.

    PubMed

    Killane, Isabelle; Sulaiman, Imran; MacHale, Elaine; Breathnach, Aoife; Taylor, Terence E; Holmes, Martin S; Reilly, Richard B; Costello, Richard W

    2016-03-01

    This Letter investigated the efficacy of a decision-support system, designed for respiratory medicine, at predicting asthma exacerbations in a multi-site longitudinal randomised control trial. Adherence to inhaler medication was acquired over 3 months from patients with asthma employing a dose counter and a remote monitoring adherence device which recorded participant's inhaler use: n = 184 (23,656 audio files), 61% women, age (mean ± sd) 49.3 ± 16.4. Data on occurrence of exacerbations was collected at three clinical visits, 1 month apart. The relative risk of an asthma exacerbation for those with good and poor adherence was examined employing a univariate and multivariate modified Poisson regression approach; adjusting for age, gender and body mass index. For all months dose counter adherence was significantly (p < 0.01) higher than remote monitoring adherence. Overall, those with poor adherence had a 1.38 ± 0.34 and 1.42 ± 0.39 (remotely monitored) and 1.25 ± 0.32 and 1.18 ± 0.31 (dose counter) higher relative risk of an exacerbation in model 1 and model 2, respectively. However, this was not found to be statistically significantly different. Remotely monitored adherence holds important clinical information and future research should focus on refining adherence and exacerbation measures. Decision-support systems based on remote monitoring may enhance patient-physician communication, possibly reducing preventable adverse events. PMID:27222733

  4. Advancing Drought Understanding, Monitoring and Prediction

    NASA Technical Reports Server (NTRS)

    Mariotti, Annarita; Schubert, Siegfried D.; Mo, Kingtse; Peters-Lidard, Christa; Wood, Andy; Pulwarty, Roger; Huang, Jin; Barrie, Dan

    2013-01-01

    Having the capacity to monitor droughts in near-real time and providing accurate drought prediction from weeks to seasons in advance can greatly reduce the severity of social and economic damage caused by drought, a leading natural hazard for North America. The congressional mandate to establish the National Integrated Drought Information System (NIDIS; Public Law 109-430) in 2006 was a major impulse to develop, integrate, and provide drought information to meet the challenges posed by this hazard. Significant progress has been made on many fronts. On the research front, efforts by the broad scientific community have resulted in improved understanding of North American droughts and improved monitoring and forecasting tools. We now have a better understanding of the droughts of the twentieth century including the 1930s "Dust Bowl"; we have developed a broader array of tools and datasets that enhance the official North American Drought Monitor based on different methodologies such as state-of-the-art land surface modeling (e.g., the North American Land Data Assimilation System) and remote sensing (e.g., the evaporative stress index) to better characterize the occurrence and severity of drought in its multiple manifestations. In addition, we have new tools for drought prediction [including the new National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2, for operational prediction and an experimental National Multimodel Ensemble] and have explored diverse methodologies including ensemble hydrologic prediction approaches. Broad NIDIS-inspired progress is influencing the development of a Global Drought Information System (GDIS) under the auspices of the World Climate Research Program. Despite these advances, current drought monitoring and forecasting capabilities still fall short of users' needs, especially the need for skillful and reliable drought forecasts at regional and local scales. To tackle this outstanding challenging problem

  5. Predictive risk modelling in health: options for New Zealand and Australia.

    PubMed

    Panattoni, Laura E; Vaithianathan, Rhema; Ashton, Toni; Lewis, Geraint H

    2011-02-01

    Predictive risk models (PRMs) are case-finding tools that enable health care systems to identify patients at risk of expensive and potentially avoidable events such as emergency hospitalisation. Examples include the PARR (Patients-at-Risk-of-Rehospitalisation) tool and Combined Predictive Model used by the National Health Service in England. When such models are coupled with an appropriate preventive intervention designed to avert the adverse event, they represent a useful strategy for improving the cost-effectiveness of preventive health care. This article reviews the current knowledge about PRMs and explores some of the issues surrounding the potential introduction of a PRM to a public health system. We make a particular case for New Zealand, but also consider issues that are relevant to Australia. PMID:21367330

  6. Monitoring temporal changes in use of two cathinones in a large urban catchment in Queensland, Australia.

    PubMed

    Thai, Phong K; Lai, Foon Yin; Edirisinghe, Methsiri; Hall, Wayne; Bruno, Raimondo; O'Brien, Jake W; Prichard, Jeremy; Kirkbride, K Paul; Mueller, Jochen F

    2016-03-01

    Wastewater analysis was used to examine prevalence and temporal trends in the use of two cathinones, methylone and mephedrone, in an urban population (>200,000 people) in South East Queensland, Australia. Wastewater samples were collected from the inlet of the sewage treatment plant that serviced the catchment from 2011 to 2013. Liquid chromatography coupled with tandem mass spectrometry was used to measure mephedrone and methylone in wastewater sample using direct injection mode. Mephedrone was not detected in any samples while methylone was detected in 45% of the samples. Daily mass loads of methylone were normalized to the population and used to evaluate methylone use in the catchment. Methylone mass loads peaked in 2012 but there was no clear temporal trend over the monitoring period. The prevalence of methylone use in the catchment was associated with the use of MDMA, the more popular analogue of methylone, as indicated by other complementary sources. Methylone use was stable in the study catchment during the monitoring period whereas mephedrone use has been declining after its peak in 2010. More research is needed on the pharmacokinetics of emerging illicit drugs to improve the applicability of wastewater analysis in monitoring their use in the population. PMID:26747989

  7. Monthly prediction of air temperature in Australia and New Zealand with machine learning algorithms

    NASA Astrophysics Data System (ADS)

    Salcedo-Sanz, S.; Deo, R. C.; Carro-Calvo, L.; Saavedra-Moreno, B.

    2016-07-01

    Long-term air temperature prediction is of major importance in a large number of applications, including climate-related studies, energy, agricultural, or medical. This paper examines the performance of two Machine Learning algorithms (Support Vector Regression (SVR) and Multi-layer Perceptron (MLP)) in a problem of monthly mean air temperature prediction, from the previous measured values in observational stations of Australia and New Zealand, and climate indices of importance in the region. The performance of the two considered algorithms is discussed in the paper and compared to alternative approaches. The results indicate that the SVR algorithm is able to obtain the best prediction performance among all the algorithms compared in the paper. Moreover, the results obtained have shown that the mean absolute error made by the two algorithms considered is significantly larger for the last 20 years than in the previous decades, in what can be interpreted as a change in the relationship among the prediction variables involved in the training of the algorithms.

  8. Monthly prediction of air temperature in Australia and New Zealand with machine learning algorithms

    NASA Astrophysics Data System (ADS)

    Salcedo-Sanz, S.; Deo, R. C.; Carro-Calvo, L.; Saavedra-Moreno, B.

    2015-05-01

    Long-term air temperature prediction is of major importance in a large number of applications, including climate-related studies, energy, agricultural, or medical. This paper examines the performance of two Machine Learning algorithms (Support Vector Regression (SVR) and Multi-layer Perceptron (MLP)) in a problem of monthly mean air temperature prediction, from the previous measured values in observational stations of Australia and New Zealand, and climate indices of importance in the region. The performance of the two considered algorithms is discussed in the paper and compared to alternative approaches. The results indicate that the SVR algorithm is able to obtain the best prediction performance among all the algorithms compared in the paper. Moreover, the results obtained have shown that the mean absolute error made by the two algorithms considered is significantly larger for the last 20 years than in the previous decades, in what can be interpreted as a change in the relationship among the prediction variables involved in the training of the algorithms.

  9. A future geodetic monitoring system for vertical land motion in the Perth basin, Australia

    NASA Astrophysics Data System (ADS)

    Filmer, Mick; Featherstone, Will; Morgan, Linda; Schenk, Andreas

    2013-04-01

    SAR imagery. The InSAR component is necessary to avoid reliance on discrete monitoring stations and to provide larger scale mapping of the subsidence. As the framework for an ongoing monitoring programme, images are being acquired from the German Aerospace Centre's (DLR's) TerraSAR-X satellite mission under a collaborative science project among Geoscience Australia, Curtin University of Technology, Landgate and Karlsruhe Institute of Technology. This programme initially covers ~13 months (up to 30 images) and will provide sufficient data to lay the foundation for ongoing monitoring. This monitoring programme will be used to determine linear and non-linear VLM in Perth at time scales ranging from seasonal to long term over multiple years.

  10. Are High-Impact Species Predictable? An Analysis of Naturalised Grasses in Northern Australia

    PubMed Central

    van Klinken, Rieks D.; Panetta, F. Dane; Coutts, Shaun R.

    2013-01-01

    Predicting which species are likely to cause serious impacts in the future is crucial for targeting management efforts, but the characteristics of such species remain largely unconfirmed. We use data and expert opinion on tropical and subtropical grasses naturalised in Australia since European settlement to identify naturalised and high-impact species and subsequently to test whether high-impact species are predictable. High-impact species for the three main affected sectors (environment, pastoral and agriculture) were determined by assessing evidence against pre-defined criteria. Twenty-one of the 155 naturalised species (14%) were classified as high-impact, including four that affected more than one sector. High-impact species were more likely to have faster spread rates (regions invaded per decade) and to be semi-aquatic. Spread rate was best explained by whether species had been actively spread (as pasture), and time since naturalisation, but may not be explanatory as it was tightly correlated with range size and incidence rate. Giving more weight to minimising the chance of overlooking high-impact species, a priority for biosecurity, meant a wider range of predictors was required to identify high-impact species, and the predictive power of the models was reduced. By-sector analysis of predictors of high impact species was limited by their relative rarity, but showed sector differences, including to the universal predictors (spread rate and habitat) and life history. Furthermore, species causing high impact to agriculture have changed in the past 10 years with changes in farming practice, highlighting the importance of context in determining impact. A rationale for invasion ecology is to improve the prediction and response to future threats. Although our study identifies some universal predictors, it suggests improved prediction will require a far greater emphasis on impact rather than invasiveness, and will need to account for the individual circumstances of

  11. Validation of satellite-based operational flood monitoring in Southern Queensland, Australia

    NASA Astrophysics Data System (ADS)

    Gouweleeuw, Ben; Ticehurst, Catherine; Lerat, Julien; Thew, Peter

    2010-05-01

    The integration of remote sensing observations with stage data and flood modeling has the potential to provide improved support to a number of disciplines, such as flood warning emergency response and operational water resources management. The ability of remote sensing technology to monitor the dynamics of hydrological events lies in its capacity to map surface water. For flood monitoring, remote sensing imagery needs to be available sufficiently frequently to capture subsequent inundation stages. MODIS optical data are available at a moderately high spatial and temporal resolution (250m-1km, twice daily), but are affected by cloud cover. AMSR-E passive microwave observations are available at comparable temporal resolution, but coarse spatial resolution (5-70km), where the smaller footprints corresponds with the higher frequency bands, which are affected by precipitating clouds. A novel operational technique to monitor flood extent combines MODIS reflectance and AMSR-E passive microwave imagery to optimize data continuity. Flood extent is subsequently combined with a DEM to obtain total flood water volume. The flood extent and volume product is operational for the lower-Balonne floodplain in Southern Queensland, Australia. For validation purposes, two moderate flood events coinciding with the MODIS and AMSR-E sensor lifetime are evaluated. The flood volume estimated from MODIS/AMSR-E images gives an accurate indication of both the timing and the magnitude of the flood peak compared to the net volume from recorded flow. In the flood recession, however, satellite-derived water volume declines rapidly, while the net flow volume remains level. This may be explained by a combination of ungauged outflows, soil infiltration, evaporation and diversion of flood water into many large open reservoirs for irrigation purposes. The open water storage extent unchanged, the water volume product is not sensitive enough to capture the change in storage water level. Additional

  12. Predicting the Benefits of Banana Bunchy Top Virus Exclusion from Commercial Plantations in Australia

    PubMed Central

    Cook, David C.; Liu, Shuang; Edwards, Jacqueline; Villalta, Oscar N.; Aurambout, Jean-Philippe; Kriticos, Darren J.; Drenth, Andre; De Barro, Paul J.

    2012-01-01

    Benefit cost analysis is a tried and tested analytical framework that can clearly communicate likely net changes in producer welfare from investment decisions to diverse stakeholder audiences. However, in a plant biosecurity context, it is often difficult to predict policy benefits over time due to complex biophysical interactions between invasive species, their hosts, and the environment. In this paper, we demonstrate how a break-even style benefit cost analysis remains highly relevant to biosecurity decision-makers using the example of banana bunchy top virus, a plant pathogen targeted for eradication from banana growing regions of Australia. We develop an analytical approach using a stratified diffusion spread model to simulate the likely benefits of exclusion of this virus from commercial banana plantations over time relative to a nil management scenario in which no surveillance or containment activities take place. Using Monte Carlo simulation to generate a range of possible future incursion scenarios, we predict the exclusion benefits of the disease will avoid Aus$15.9-27.0 million in annual losses for the banana industry. For these exclusion benefits to be reduced to zero would require a bunchy top re-establishment event in commercial banana plantations three years in every four. Sensitivity analysis indicates that exclusion benefits can be greatly enhanced through improvements in disease surveillance and incursion response. PMID:22879960

  13. Radon monitoring and hazard prediction in Ireland

    NASA Astrophysics Data System (ADS)

    Elio, Javier; Crowley, Quentin; Scanlon, Ray; Hodgson, Jim; Cooper, Mark; Long, Stephanie

    2016-04-01

    Radon is a naturally occurring radioactive gas which forms as a decay product from uranium. It is the largest source of natural ionizing radiation affecting the global population. When radon is inhaled, its short-lived decay products can interact with lung tissue leading to DNA damage and development of lung cancer. Ireland has among the highest levels of radon in Europe and eighth highest of an OECD survey of 29 countries. Every year some two hundred and fifty cases of lung cancer in Ireland are linked to radon exposure. This new research project will build upon previous efforts of radon monitoring in Ireland to construct a high-resolution radon hazard map. This will be achieved using recently available high-resolution airborne gamma-ray spectrometry (radiometric) and soil geochemistry data (http://www.tellus.ie/), indoor radon concentrations (http://www.epa.ie/radiation), and new direct measurement of soil radon. In this regard, legacy indoor radon concentrations will be correlated with soil U and Th concentrations and other geogenic data. This is a new approach since the vast majority of countries with a national radon monitoring programme rely on indoor radon measurements, or have a spatially limited dataset of soil radon measurements. Careful attention will be given to areas where an indicative high radon hazard based on geogenic factors does not match high indoor radon concentrations. Where such areas exist, it may imply that some parameter(s) in the predictive model does not match that of the environment. These areas will be subjected to measurement of radon soil gas using a combination of time averaged (passive) and time dependant (active) measurements in order to better understand factors affecting production, transport and accumulation of radon in the natural environment. Such mapping of radon-prone areas will ultimately help to inform when prevention and remediation measures are necessary, reducing the radon exposure of the population. Therefore, given

  14. Monitoring Contrasting Land Management in the Savanna Landscapes of Northern Australia

    NASA Astrophysics Data System (ADS)

    Franklin, Donald C.; Petty, Aaron M.; Williamson, Grant J.; Brook, Barry W.; Bowman, David M. J. S.

    2008-04-01

    We compared measures of ecosystem state across six adjacent land-tenure groups in the intact tropical savanna landscapes of northern Australia. Tenure groups include two managed by Aboriginal owners, two national parks, a cluster of pastoral leases, and a military training area. This information is of relevance to the debate about the role of indigenous lands in the Australian conservation estate. The timing and frequency of fire was determined by satellite imagery; the biomass and composition of the herb-layer and the abundance of large feral herbivores by field surveys; and weediness by analysis of a Herbarium database. European tenures varied greatly in fire frequencies but were consistently burnt earlier in the dry season than the two Aboriginal tenures, the latter having intermediate fire frequencies. Weeds were more frequent in the European tenures, whilst feral animals were most abundant in the Aboriginal tenures. This variation strongly implies a signature of current management and/or recent environmental history. We identify indices suitable for monitoring of management outcomes in an extensive and sparsely populated landscape. Aboriginal land offers a unique opportunity for the conservation of biodiversity through the maintenance of traditional fire regimes. However, without financial support, traditional practices may prove unsustainable both economically and because exotic weeds and feral animals will alter fire regimes. An additional return on investment in Aboriginal land management is likely to be improved livelihoods and health outcomes for these disadvantaged communities.

  15. Real Time Monitoring of an Injection Test for an Enhanced Geothermal Reservoir, Paralana, South Australia

    NASA Astrophysics Data System (ADS)

    Peacock, J.; Thiel, S.; Heinson, G. S.; Reid, P.

    2011-12-01

    Real-time monitoring of changes in subsurface material properties proves valuable in many geophysical aplications where fluids are present, including ground water, geothermal, CO2 sequestration, unconventional gas, and more. Reservoir stimulation typically includes pumping high pressure fluids into tight lithology with the intention of creating or extending the reservior. Unfortunately, the fracturing process and reservoir extension is not always predictable. Therefore, real time monitoring needs to be employed to better understand the system. Electromagnetic methods can exploit the large dynamic range of electrical conductivity from the surface, specifically the magnetotelluric (MT) can measure conductivity contrasts as a function of depth and time. Presented is an example of real-time monitoring of an enhanced geothermal system injection test at around 4~km depth using 11 MT stations with a remote reference. Its found that changes in the MT response are small, on the order of a few percent, but correlate with earthquake clusters measured by a micro-seismic array.

  16. Post Processing Numerical Weather Prediction Model Rainfall Forecasts for Use in Ensemble Streamflow Forecasting in Australia

    NASA Astrophysics Data System (ADS)

    Shrestha, D. L.; Robertson, D.; Bennett, J.; Ward, P.; Wang, Q. J.

    2012-12-01

    Through the water information research and development alliance (WIRADA) project, CSIRO is conducting research to improve flood and short-term streamflow forecasting services delivered by the Australian Bureau of Meteorology. WIRADA aims to build and test systems to generate ensemble flood and short-term streamflow forecasts with lead times of up to 10 days by integrating rainfall forecasts from Numerical Weather Prediction (NWP) models and hydrological modelling. Here we present an overview of the latest progress towards developing this system. Rainfall during the forecast period is a major source of uncertainty in streamflow forecasting. Ensemble rainfall forecasts are used in streamflow forecasting to characterise the rainfall uncertainty. In Australia, NWP models provide forecasts of rainfall and other weather conditions for lead times of up to 10 days. However, rainfall forecasts from Australian NWP models are deterministic and often contain systematic errors. We use a simplified Bayesian joint probability (BJP) method to post-process rainfall forecasts from the latest generation of Australian NWP models. The BJP method generates reliable and skilful ensemble rainfall forecasts. The post-processed rainfall ensembles are then used to force a semi-distributed conceptual rainfall runoff model to produce ensemble streamflow forecasts. The performance of the ensemble streamflow forecasts is evaluated on a number of Australian catchments and the benefits of using post processed rainfall forecasts are demonstrated.

  17. Predicting Cereal Root Disease in Western Australia Using Soil DNA and Environmental Parameters.

    PubMed

    Poole, Grant J; Harries, Martin; Hüberli, D; Miyan, S; MacLeod, W J; Lawes, Roger; McKay, A

    2015-08-01

    Root diseases have long been prevalent in Australian grain-growing regions, and most management decisions to reduce the risk of yield loss need to be implemented before the crop is sown. The levels of pathogens that cause the major root diseases can be measured using DNA-based services such as PreDicta B. Although these pathogens are often studied individually, in the field they often occur as mixed populations and their combined effect on crop production is likely to vary across diverse cropping environments. A 3-year survey was conducted covering most cropping regions in Western Australia, utilizing PreDicta B to determine soilborne pathogen levels and visual assessments to score root health and incidence of individual crop root diseases caused by the major root pathogens, including Rhizoctonia solani (anastomosis group [AG]-8), Gaeumannomyces graminis var. tritici (take-all), Fusarium pseudograminearum, and Pratylenchus spp. (root-lesion nematodes) on wheat roots for 115, 50, and 94 fields during 2010, 2011, and 2012, respectively. A predictive model was developed for root health utilizing autumn and summer rainfall and soil temperature parameters. The model showed that pathogen DNA explained 16, 5, and 2% of the variation in root health whereas environmental parameters explained 22, 11, and 1% of the variation in 2010, 2011, and 2012, respectively. Results showed that R. solani AG-8 soil pathogen DNA, environmental soil temperature, and rainfall parameters explained most of the variation in the root health. This research shows that interactions between environment and pathogen levels before seeding can be utilized in predictive models to improve assessment of risk from root diseases to assist growers to plan more profitable cropping programs. PMID:25822184

  18. Atmospheric CO{sub 2} concentrations the CSIRO (Australia) monitoring program from aircraft 1972 - 1981

    SciTech Connect

    Beardsmore, D.J.; Pearman, G.I.

    1984-09-01

    Atmospheric CO{sub 2} concentrations were measured in the troposphere and lower stratosphere over the Australia-New Zealand region and as far south as Antarctica for the period 1972-1981. The samples were collected from aircraft over a large range of latitudes and altitudes. The sampling program has been based on the cooperation of the Australia Department of Transport, Quantas Airways, Trans Australia Airlines, the United States, New Zealand and Australian Air Forces and occasional chartering of light aircraft for special purposes.

  19. A model to predict CWD residence times in tropical forests along an altitudinal gradient in Australia

    NASA Astrophysics Data System (ADS)

    Torello-Raventos, Mireia; Ford, Andrew; Saiz, Gus; Bloomfield, Keith; Lloyd, Jon; Bird, Michael

    2014-05-01

    More reliable knowledge on the complex responses of vegetation to climate change is one of the most urgent needs for tropical forest preservation and recent data models indicate an increase of tree mortality in tropical forests as a consequence of climate change1. Coarse woody debris dynamics in tropical forests remain poorly understood2. Tropical forests are known for possessing a wide range of wood densities- with different wood traits and secondary wood chemical components-, adding complexity to the accurate estimations of coarse woody debris residence times (τ). Quantifying τ in these ecosystems along an altitudinal gradient provides a way to improve our understanding of carbon dynamics in the face of climate change. This study examines τ from different tree tropical forest species -ranging from soft to hardwoods- and under different decay status, to understand the effects of climate on the chemical and physical decay of CWD on an elevation gradient from 102 m above sea level (MAT = 23.7° C) to 1500 m above sea level (MAT = 16.7° C) in Australia. Wood density together with Carbon:Nitrogen ratio enabled prediction of the variation in τ between decay classes within tree species, between tree species and along the elevation gradient. τ increased with decreasing the decay status, increasing wood density and temperature also played an important role as τ increased with increasing site elevation. The study also highlighted the importance of including seasonal variation of climate in short term field studies, as a single wet season reduced the τ of the CWD compared to τ after a year of exposure. Intraspecific variation of plant traits and secondary wood chemicals explained the observed range in τ for species with similar wood densities, decreasing with increasing decayed status of the samples. This study will aid in the development of predictive relationships between wood density and environmental variables to infer carbon dynamics at local and global scale

  20. Sensitivity analysis of numerical weather prediction radiative schemes to forecast direct solar radiation over Australia

    NASA Astrophysics Data System (ADS)

    Mukkavilli, S. K.; Kay, M. J.; Taylor, R.; Prasad, A. A.; Troccoli, A.

    2014-12-01

    The Australian Solar Energy Forecasting System (ASEFS) project requires forecasting timeframes which range from nowcasting to long-term forecasts (minutes to two years). As concentrating solar power (CSP) plant operators are one of the key stakeholders in the national energy market, research and development enhancements for direct normal irradiance (DNI) forecasts is a major subtask. This project involves comparing different radiative scheme codes to improve day ahead DNI forecasts on the national supercomputing infrastructure running mesoscale simulations on NOAA's Weather Research & Forecast (WRF) model. ASEFS also requires aerosol data fusion for improving accurate representation of spatio-temporally variable atmospheric aerosols to reduce DNI bias error in clear sky conditions over southern Queensland & New South Wales where solar power is vulnerable to uncertainities from frequent aerosol radiative events such as bush fires and desert dust. Initial results from thirteen years of Bureau of Meteorology's (BOM) deseasonalised DNI and MODIS NASA-Terra aerosol optical depth (AOD) anomalies demonstrated strong negative correlations in north and southeast Australia along with strong variability in AOD (~0.03-0.05). Radiative transfer schemes, DNI and AOD anomaly correlations will be discussed for the population and transmission grid centric regions where current and planned CSP plants dispatch electricity to capture peak prices in the market. Aerosol and solar irradiance datasets include satellite and ground based assimilations from the national BOM, regional aerosol researchers and agencies. The presentation will provide an overview of this ASEFS project task on WRF and results to date. The overall goal of this ASEFS subtask is to develop a hybrid numerical weather prediction (NWP) and statistical/machine learning multi-model ensemble strategy that meets future operational requirements of CSP plant operators.

  1. Developing a new Predictive Ocean Atmosphere Model for Australia (POAMA-3.0)

    NASA Astrophysics Data System (ADS)

    Zhou, Xiaobing; Alves, Oscar; Okely, Patricia; Tseitkin, Faina; Marshall, Andrew; Luo, Jing-Jia; Hudson, Debra; Zhao, Maggie; Yin, Yonghong; Hendon, Harry

    2013-04-01

    The Predictive Ocean Atmosphere Model for Australia (POAMA) is a state-of-the-art intra-seasonal to seasonal forecast system based on a coupled climate model and ocean/atmosphere/land observations assimilation system. Several versions of the POAMA system have been developed over the past decade, including 1.0, 1.5, 2.0 and 2.4. The development of a new POAMA system, POAMA-3.0, is currently underway. The model components in POAMA-3.0 are totally different from its previous versions. The POAMA-3.0 model is based on ACCESS-1.3 coupled model (Australian Community Climate and Earth-System Simulator) developed at the Centre for Australian Weather and Climate Research (CAWCR). The ACCESS-1.3 model is comprised of the UK Met Office atmospheric model UM7.3, GFDL ocean model MOM4p1, Los Alamos sea ice model CICE4.1, the Australian land model CABLE1.8 and the CERFACS coupler OASIS3.25. The model configuration used for seasonal forecasting has some different configurations compared to the model used for the IPCC AR5 contributions in several aspects, such as an improved shortwave penetration scheme in the ocean model, enhanced entrainment and detrainment rates in deep convection, an improved cloud overlap scheme and better representation of the boundary layer in the atmospheric model. A 100-yr run is conducted and the model's biases and interannual variability are validated. At the current stage of POAMA-3.0 development, a simple data assimilation approach is applied to produce initial conditions for intra-seasonal/seasonal forecasts during the period of 1980-2010. The atmospheric model is nudged to ECMWF ERA-interim data and the ocean model is driven by the surface fluxes while the atmosphere is being nudged. Seasonal hindcasts are performed during the period 1982-2010 and each hindcast goes out to lead time of 5 months. The prediction skill for El Nino indices, Indian Ocean dipole, Madden-Julian Oscillation and Australian rainfall are evaluated. The retrospective results of

  2. Time-lapse Geophysical Monitoring of the Subsurface Hydrology at Kings Park, Western Australia

    NASA Astrophysics Data System (ADS)

    Adekoya, Tunde; McGrath, Gavan; Leopold, Matthias; Shragge, Jeffrey; Challis, Anthea; Stevens, Jason; Miller, Ben

    2015-04-01

    The increasing occurrence of drought stress throughout Southwestern Western Australia is postulated to have contributed to the decline of Banksia populations both in Kings Park, Perth, and in the Banksia woodlands in the greater Swan Coastal Plain region. To help quantify these assertions, there is an urgent need to better understand the base levels of soil moisture content - as well as seasonal variations thereof - in these geographical regions. We conducted time-lapse (TL) electrical resistivity tomography (ERT) and ground penetrating radar (GPR) methods on a monthly basis (May-August 2014). In addition, at each site we hand-augured test holes to a depth of 3-4 m and collected samples at 20-cm intervals to enable grain-size analysis, soil moisture content and water retention tests. PR2 capacitance probe measurements were also acquired when augering to enable a moisture content comparison study. The acquired TL ERT datasets were inverted using 2D EarthImager software and the temporal variations in resistivity were interpreted in terms of changes in moisture content. The TL ERT data reveal significant calendar variations in the spatial distribution of moisture content. The TL ERT inversions also detected isolated less resistive lithologies and the depth to groundwater. Processed TL GPR data were interpreted to show vertical variations in the vadose zone moisture content. The water content variations were consistent with the rainfall data. The grain-size distributions of the samples were analysed statistically. The apparent resistivity values from the analysed samples and observed volumetric water content are strongly correlated (R2=0.84) as may be expected from Archie's law. Soil moisture content analysis results including the PR2 probe measurements were plotted as a function of depth, the result shows vertical variations in moisture content with depth. The hydrological tests indicated the properties of the subsurface lithologies and confirm the responses of the

  3. Monitoring International Interest in Transnational Academic Mobility to Australia: A Mixed-Method Approach

    ERIC Educational Resources Information Center

    Hopkins, John L.

    2013-01-01

    In a recent study, the issue of transnational academic mobility of academic staff, considering moves to higher education institutions in Australia, was examined using a web-based portal that attracted interested parties from around the world with information about Australian academic career opportunities. Web analytics were used as the research…

  4. Monitoring and modelling walking track impacts in the Tasmanian Wilderness World Heritage Area, Australia.

    PubMed

    Dixon, Grant; Hawes, Martin; McPherson, Glen

    2004-07-01

    A program has been developed for monitoring the condition of unimproved walking tracks on a 1000-km track system in Western Tasmania, and it has been used as the basis of an eight-year study of track-impact development. The monitoring technique involves measuring track depth and two track-width indicators at permanently marked and widely dispersed sites, each site comprising ten transects located at 2-m intervals. Sites have been 'typed' on the basis of track slope, drainage and substrate characteristics, and the typing scheme has been tested and refined by assessing the relationship between type-usage groups and observed impacts. Analysis reveals that track depth and rates of erosion are strongly influenced by track type and to a lesser extent by usage, while track width is influenced mainly by usage and track bogginess. The time-invariant variable 'usage gradient' was introduced to compensate for the fact that usage levels on most walking tracks in Western Tasmania have varied over time. Data derived from multiple inspections at 2-3 year intervals since 1994 from over 250 sites have been used to derive impact/time curves for different type-'usage gradient' groups. Each of the impact variables can be approximated by the formula m = alphatBeta, where m is the expected value of the impact variable, t is chronological time, and alpha and Beta are constants characteristic of the impact variable and type-'usage gradient' group in question. The typing scheme and impact-development model have the potential to be used for systematically describing and predicting impacts over extensive systems of 'typed' tracks. The implications of these findings for the ongoing monitoring, sitting and management of walking tracks are discussed. PMID:15217719

  5. Micro-Seismic Monitoring During Stimulation at Paralana-2 South Australia

    NASA Astrophysics Data System (ADS)

    Hasting, M. A.; Albaric, J.; Oye, V.; Reid, P.; Messeiller, M.; Llanos, E.

    2011-12-01

    In 2009 the Paralana JV, drilled the Paralana-2 (P2) Enhanced Geothermal System (EGS) borehole east of the Flinders Range in South Australia. Drilling started on 30 Jun and reached a total depth of 4,003m (G.L AHD) on 9 Nov. A 7- inch casing was set and cemented to a depth of 3,725m and P2 was officially completed on the 9th Dec 2009. On 2 Jan 2011 a six meter zone was perforated between 3,679 and 3,685mRT. A stimulation of P2 was carried out on 3 Jan by injecting approximately 14,668l of fluid at pressure of up to 8.7kpsi and various rates up to 2bpm. During the stimulation 125 micro-earthquakes (MEQ) were triggered in the formation. Most MEQ events occurred in an area about 100m wide and 220m deep at an average depth of 3,850m. The largest event, ML1.4, occurred after the shut-in. Between 11 and 15 July 2011, the main fracture stimulation was carried out with ~3M litres injected at pressures up to 9kpsi and rates up to 10bpm. Over 10,000 MEQ were detected by the seismic monitoring network. This network consisted of 12 surface and 8 borehole stations with sensor depths of 40m, 200m and 1,800m. Four accelerometers were also installed to record ground motions near key facilities in the case of a larger seismic event. MEQ were automatically triggered and located in near-real-time with the software MIMO provided by NORSAR. A traffic light system was in operation and none of the detected events came close to the threshold value. More than 1/2 of the detected events could be processed and located reliably in the full automatic mode. Selected MEQ events were manually picked on site in order to improve the location accuracy. A total of 1,875 events were located to form the final picture of the stimulation fracture. Results show that fracturing occurred in three swarms. The 1st swarm occurs near the well and deepened with time from 3.7km to over 4.1km. The 2nd swarm occurred a few days in and shows as a circular patch extending a few hundred meters east of the 1st one. The

  6. Epsilon Aur monitoring during predicted pulsation phase

    NASA Astrophysics Data System (ADS)

    Waagen, Elizabeth O.; Templeton, Matthew R.

    2014-09-01

    Dr. Robert Stencel (University of Denver Astronomy Program) has requested that AAVSO observers monitor epsilon Aurigae from now through the end of the observing season. "Studies of the long-term, out-of-eclipse photometry of this enigmatic binary suggest that intervals of coherent pulsation occur at roughly 1/3 of the 27.1-year orbital period. Kloppenborg, et al. noted that stable variation patterns develop at 3,200-day intervals' implying that 'the next span of dates when such events might happen are circa JD ~2457000 (2014 December)'. "These out-of-eclipse light variations often have amplitudes of ~0.1 magnitude in U, and ~0.05 in V, with characteristic timescales of 60-100 days. The AAVSO light curve data to the present may indicate that this coherent phenomenon has begun, but we encourage renewed efforts by observers...to help deduce whether these events are internal to the F star, or externally-driven by tidal interaction with the companion star." Nightly observations or one observation every few days (CCD/PEP/DSLR, VUBR (amplitude too small for visual)) are requested. Finder charts with sequence may be created using the AAVSO Variable Star Plotter (http://www.aavso.org/vsp). Observations should be submitted to the AAVSO International Database. Epsilon Aur was the subject of major international campaigns and the AAVSO's Citizen Sky project as it went through its 27.1-year eclipse in 2009-2011. Over 700 observers worldwide submitted over 20,000 multicolor observations to the AAVSO International Database for this project. Much information on eps Aur is available from the AAVSO, including material on the Citizen Sky website (http://www.aavso.org/epsilon-aurigae and http://www.citizensky.org/content/star-our-project). The Journal of the AAVSO, Volume 40, No. 2 (2012) was devoted to discussion of and research results from this event. See full Alert Notice for more details and observations.

  7. The Murrumbidgee Monitoring Network: Supporting CEOP, GEWEX and Hydrological Research in the Murray-Darling Basin, Australia

    NASA Astrophysics Data System (ADS)

    Ellett, K. M.; Western, A. W.; Walker, J. P.; Sirawardena, L.; Young, R. I.; Smith, A. B.; Flint, A. L.; Summerell, G.

    2006-12-01

    In 2001 a network of 18 soil moisture monitoring sites were installed across the 80,000 square km Murrumbidgee River catchment in Australia with the aim of evaluating the land surface component of the Australian Bureau of Meteorology's operational weather forecasting model. Since that time the Murrumbidgee Monitoring Network (MMN) has evolved to include 46 sites for continuous measurement of root-zone soil moisture, soil temperature and precipitation, as well as observations of deep soil moisture and ground water variability. Much of these data will soon be incorporated into the World Climate Research Programme's Coordinated Enhanced Observing Period (CEOP) database (www.ceop.net) marking a substantial new contribution from the Australian continent. This paper provides an overview of the MMN and presents current results from applications in a number of regional-scale research projects including the Murray-Darling Basin GEWEX study and the National Airborne Field Experiment 2006 (NAFE'06) aimed at improving the retrieval of soil moisture and vegetation parameters from airborne and satellite platforms. The MMN also plays an integral role in the HYDROGRACE project with the objectives of (1) providing the first in-situ based validation of terrestrial water storage observations from the GRACE (Gravity Recovery and Climate Experiment) mission and (2) improving regional-scale model simulations through data assimilation of GRACE observations. The MMN is part of the broader OzNet hydrological monitoring network throughout eastern Australia. Details on OzNet and the projects mentioned above are provided at www.oznet.unimelb.edu.au.

  8. Predicting the Location and Spatial Extent of Submerged Coral Reef Habitat in the Great Barrier Reef World Heritage Area, Australia

    PubMed Central

    Bridge, Tom; Beaman, Robin; Done, Terry; Webster, Jody

    2012-01-01

    Aim Coral reef communities occurring in deeper waters have received little research effort compared to their shallow-water counterparts, and even such basic information as their location and extent are currently unknown throughout most of the world. Using the Great Barrier Reef as a case study, habitat suitability modelling is used to predict the distribution of deep-water coral reef communities on the Great Barrier Reef, Australia. We test the effectiveness of a range of geophysical and environmental variables for predicting the location of deep-water coral reef communities on the Great Barrier Reef. Location Great Barrier Reef, Australia. Methods Maximum entropy modelling is used to identify the spatial extent of two broad communities of habitat-forming megabenthos phototrophs and heterotrophs. Models were generated using combinations of geophysical substrate properties derived from multibeam bathymetry and environmental data derived from Bio-ORACLE, combined with georeferenced occurrence records of mesophotic coral communities from autonomous underwater vehicle, remotely operated vehicle and SCUBA surveys. Model results are used to estimate the total amount of mesophotic coral reef habitat on the GBR. Results Our models predict extensive but previously undocumented coral communities occurring both along the continental shelf-edge of the Great Barrier Reef and also on submerged reefs inside the lagoon. Habitat suitability for phototrophs is highest on submerged reefs along the outer-shelf and the deeper flanks of emergent reefs inside the GBR lagoon, while suitability for heterotrophs is highest in the deep waters along the shelf-edge. Models using only geophysical variables consistently outperformed models incorporating environmental data for both phototrophs and heterotrophs. Main Conclusion Extensive submerged coral reef communities that are currently undocumented are likely to occur throughout the Great Barrier Reef. High-quality bathymetry data can be used

  9. Social/Ethical Issues in Predictive Insider Threat Monitoring

    SciTech Connect

    Greitzer, Frank L.; Frincke, Deborah A.; Zabriskie, Mariah

    2011-01-01

    Combining traditionally monitored cybersecurity data with other kinds of organizational data is one option for inferring the motivations of individuals, which may in turn allow early prediction and mitigation of insider threats. While unproven, some researchers believe that this combination of data may yield better results than either cybersecurity or organizational data would in isolation. However, this nontraditional approach creates a potential conflict between goals, such as conflicts between organizational security improvements and individual privacy considerations. There are many facets to debate. Should warning signs of a potential malicious insider be addressed before a malicious event has occurred to prevent harm to the organization and discourage the insider from violating the organization’s rules? Would intervention violate employee trust or legal guidelines? What about the possibilities of misuse? Predictive approaches cannot be validated a priori; false accusations can affect the career of the accused; and collection/monitoring of certain types of data may affect employee morale. In this chapter, we explore some of the social and ethical issues stemming from predictive insider threat monitoring and discuss ways that a predictive modeling approach brings to the forefront social and ethical issues that should be considered and resolved by stakeholders and communities of interest.

  10. A Seamless Framework for Global Water Cycle Monitoring and Prediction

    NASA Astrophysics Data System (ADS)

    Sheffield, J.; Wood, E. F.; Chaney, N.; Fisher, C. K.; Caylor, K. K.

    2013-12-01

    The Global Earth Observation System of Systems (GEOSS) Water Strategy ('From Observations to Decisions') recognizes that 'water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity', and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the development of a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions

  11. Application of the extreme learning machine algorithm for the prediction of monthly Effective Drought Index in eastern Australia

    NASA Astrophysics Data System (ADS)

    Deo, Ravinesh C.; Şahin, Mehmet

    2015-02-01

    The prediction of future drought is an effective mitigation tool for assessing adverse consequences of drought events on vital water resources, agriculture, ecosystems and hydrology. Data-driven model predictions using machine learning algorithms are promising tenets for these purposes as they require less developmental time, minimal inputs and are relatively less complex than the dynamic or physical model. This paper authenticates a computationally simple, fast and efficient non-linear algorithm known as extreme learning machine (ELM) for the prediction of Effective Drought Index (EDI) in eastern Australia using input data trained from 1957-2008 and the monthly EDI predicted over the period 2009-2011. The predictive variables for the ELM model were the rainfall and mean, minimum and maximum air temperatures, supplemented by the large-scale climate mode indices of interest as regression covariates, namely the Southern Oscillation Index, Pacific Decadal Oscillation, Southern Annular Mode and the Indian Ocean Dipole moment. To demonstrate the effectiveness of the proposed data-driven model a performance comparison in terms of the prediction capabilities and learning speeds was conducted between the proposed ELM algorithm and the conventional artificial neural network (ANN) algorithm trained with Levenberg-Marquardt back propagation. The prediction metrics certified an excellent performance of the ELM over the ANN model for the overall test sites, thus yielding Mean Absolute Errors, Root-Mean Square Errors, Coefficients of Determination and Willmott's Indices of Agreement of 0.277, 0.008, 0.892 and 0.93 (for ELM) and 0.602, 0.172, 0.578 and 0.92 (for ANN) models. Moreover, the ELM model was executed with learning speed 32 times faster and training speed 6.1 times faster than the ANN model. An improvement in the prediction capability of the drought duration and severity by the ELM model was achieved. Based on these results we aver that out of the two machine learning

  12. Water utilization, evapotranspiration and soil moisture monitoring in the south east region of south Australia

    NASA Technical Reports Server (NTRS)

    Mccloy, K. R.; Shepherd, K. J.; Mcintosh, G. F. (Principal Investigator)

    1977-01-01

    The author has identified the following significant results. It was established that reliable estimates of sand and coastal scrub areas can be determined from LANDSAT image classification by the Vec classifier more economically than by conventional means from a map of the coastal zone produced by photointerpretation using 1:10,000 aerial photography. Current LANDSAT imagery is also suitable for monitoring for large scale storm damage to the zone, but the normal change in sand areas extent due to man's activity or other reasons, is about 5 to 10 m per year, occasionally being as great as 30 m per year, so that it is considered that LANDSAT D will have the resolution necessary to monitor these changes but not current imagery.

  13. Field Validation of a Transcriptional Assay for the Prediction of Age of Uncaged Aedes aegypti Mosquitoes in Northern Australia

    PubMed Central

    Hugo, Leon E.; Cook, Peter E.; Johnson, Petrina H.; Rapley, Luke P.; Kay, Brian H.; Ryan, Peter A.; Ritchie, Scott A.; O'Neill, Scott L.

    2010-01-01

    Background New strategies to eliminate dengue have been proposed that specifically target older Aedes aegypti mosquitoes, the proportion of the vector population that is potentially capable of transmitting dengue viruses. Evaluation of these strategies will require accurate and high-throughput methods of predicting mosquito age. We previously developed an age prediction assay for individual Ae. aegypti females based on the transcriptional profiles of a selection of age responsive genes. Here we conducted field testing of the method on Ae. aegypti that were entirely uncaged and free to engage in natural behavior. Methodology/Principal Findings We produced “free-range” test specimens by releasing 8007 adult Ae. aegypti inside and around an isolated homestead in north Queensland, Australia, and recapturing females at two day intervals. We applied a TaqMan probe-based assay design that enabled high-throughput quantitative RT-PCR of four transcripts from three age-responsive genes and a reference gene. An age prediction model was calibrated on mosquitoes maintained in small sentinel cages, in which 68.8% of the variance in gene transcription measures was explained by age. The model was then used to predict the ages of the free-range females. The relationship between the predicted and actual ages achieved an R2 value of 0.62 for predictions of females up to 29 days old. Transcriptional profiles and age predictions were not affected by physiological variation associated with the blood feeding/egg development cycle and we show that the age grading method could be applied to differentiate between two populations of mosquitoes having a two-fold difference in mean life expectancy. Conclusions/Significance The transcriptional profiles of age responsive genes facilitated age estimates of near-wild Ae. aegypti females. Our age prediction assay for Ae. aegypti provides a useful tool for the evaluation of mosquito control interventions against dengue where mosquito

  14. Imaging proteomics for diagnosis, monitoring and prediction of Alzheimer's disease.

    PubMed

    Nazeri, Arash; Ganjgahi, Habib; Roostaei, Tina; Nichols, Thomas; Zarei, Mojtaba

    2014-11-15

    Proteomic and imaging markers have been widely studied as potential biomarkers for diagnosis, monitoring and prognosis of Alzheimer's disease. In this study, we used Alzheimer Disease Neuroimaging Initiative dataset and performed parallel independent component analysis on cross sectional and longitudinal proteomic and imaging data in order to identify the best proteomic model for diagnosis, monitoring and prediction of Alzheimer disease (AD). We used plasma proteins measurement and imaging data from AD and healthy controls (HC) at the baseline and 1 year follow-up. Group comparisons at baseline and changes over 1 year were calculated for proteomic and imaging data. The results were fed into parallel independent component analysis in order to identify proteins that were associated with structural brain changes cross sectionally and longitudinally. Regression model was used to find the best model that can discriminate AD from HC, monitor AD and to predict MCI converters from non-converters. We showed that five proteins are associated with structural brain changes in the brain. These proteins could discriminate AD from HC with 57% specificity and 89% sensitivity. Four proteins whose change over 1 year were associated with brain structural changes could discriminate AD from HC with sensitivity of 93%, and specificity of 92%. This model predicted MCI conversion to AD in 2 years with 94% accuracy. This model has the highest accuracy in prediction of MCI conversion to AD within the ADNI-1 dataset. This study shows that combination of selected plasma protein levels and MR imaging is a useful method in identifying potential biomarker. PMID:25173418

  15. Climate Predictions Accelerate Decline for Threatened Macrozamia Cycads from Queensland, Australia

    PubMed Central

    Laidlaw, Melinda J.; Forster, Paul I.

    2012-01-01

    Changes in the potential habitat of five allopatric species of threatened Macrozamia cycads under scenarios of increased ambient temperature were examined. A lack of seed dispersal, poor recruitment, low seedling survival, obligate pollinator mutualisms and continued habitat loss have led to extant populations being largely restricted to refugia. Models predict that the area of suitable habitat will further contract and move upslope, resulting in a reduced incidence within protected areas with increasing annual mean temperature. Areas of potential habitat for all five species are also predicted to become increasingly isolated from one another, further reducing the exchange between metapopulations and subpopulations, exacerbating existing threatening processes. PMID:24832522

  16. Using subseasonal-to-seasonal (S2S) extreme rainfall forecasts for extended-range flood prediction in Australia

    NASA Astrophysics Data System (ADS)

    White, C. J.; Franks, S. W.; McEvoy, D.

    2015-06-01

    Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal). Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S) forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR) activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

  17. Monitoring of wild birds for Newcastle disease virus in north Queensland, Australia.

    PubMed

    Hoque, M A; Burgess, G W; Karo-Karo, D; Cheam, A L; Skerratt, L F

    2012-01-01

    surveillance programs for NDVs in northern Australia. PMID:21945812

  18. Mortality of Inshore Marine Mammals in Eastern Australia Is Predicted by Freshwater Discharge and Air Temperature

    PubMed Central

    Meager, Justin J.; Limpus, Colin

    2014-01-01

    Understanding environmental and climatic drivers of natural mortality of marine mammals is critical for managing populations effectively and for predicting responses to climate change. Here we use a 17-year dataset to demonstrate a clear relationship between environmental forcing and natural mortality of inshore marine mammals across a subtropical-tropical coastline spanning a latitudinal gradient of 13° (>2000 km of coastline). Peak mortality of inshore dolphins and dugongs followed sustained periods of elevated freshwater discharge (9 months) and low air temperature (3 months). At a regional scale, these results translated into a strong relationship between annual mortality and an index of El Niño-Southern Oscillation. The number of cyclones crossing the coastline had a comparatively weak effect on inshore marine mammal mortality, and only in the tropics. Natural mortality of offshore/migratory cetaceans was not predicted by freshwater discharge, but was related to lagged air temperature. These results represent the first quantitative link between environmental forcing and marine mammal mortality in the tropics, and form the basis of a predictive tool for managers to prepare responses to periods of elevated marine mammal mortality. PMID:24740149

  19. Mortality of inshore marine mammals in eastern Australia is predicted by freshwater discharge and air temperature.

    PubMed

    Meager, Justin J; Limpus, Colin

    2014-01-01

    Understanding environmental and climatic drivers of natural mortality of marine mammals is critical for managing populations effectively and for predicting responses to climate change. Here we use a 17-year dataset to demonstrate a clear relationship between environmental forcing and natural mortality of inshore marine mammals across a subtropical-tropical coastline spanning a latitudinal gradient of 13° (>2000 km of coastline). Peak mortality of inshore dolphins and dugongs followed sustained periods of elevated freshwater discharge (9 months) and low air temperature (3 months). At a regional scale, these results translated into a strong relationship between annual mortality and an index of El Niño-Southern Oscillation. The number of cyclones crossing the coastline had a comparatively weak effect on inshore marine mammal mortality, and only in the tropics. Natural mortality of offshore/migratory cetaceans was not predicted by freshwater discharge, but was related to lagged air temperature. These results represent the first quantitative link between environmental forcing and marine mammal mortality in the tropics, and form the basis of a predictive tool for managers to prepare responses to periods of elevated marine mammal mortality. PMID:24740149

  20. USING CONDITION MONITORING TO PREDICT REMAINING LIFE OF ELECTRIC CABLES.

    SciTech Connect

    LOFARO,R.; SOO,P.; VILLARAN,M.; GROVE,E.

    2001-03-29

    Electric cables are passive components used extensively throughout nuclear power stations to perform numerous safety and non-safety functions. It is known that the polymers commonly used to insulate the conductors on these cables can degrade with time; the rate of degradation being dependent on the severity of the conditions in which the cables operate. Cables do not receive routine maintenance and, since it can be very costly, they are not replaced on a regular basis. Therefore, to ensure their continued functional performance, it would be beneficial if condition monitoring techniques could be used to estimate the remaining useful life of these components. A great deal of research has been performed on various condition monitoring techniques for use on electric cables. In a research program sponsored by the U.S. Nuclear Regulatory Commission, several promising techniques were evaluated and found to provide trendable information on the condition of low-voltage electric cables. These techniques may be useful for predicting remaining life if well defined limiting values for the aging properties being measured can be determined. However, each technique has advantages and limitations that must be addressed in order to use it effectively, and the necessary limiting values are not always easy to obtain. This paper discusses how condition monitoring measurements can be used to predict the remaining useful life of electric cables. The attributes of an appropriate condition monitoring technique are presented, and the process to be used in estimating the remaining useful life of a cable is discussed along with the difficulties that must be addressed.

  1. Causal simulation and sensor planning in predictive monitoring

    NASA Technical Reports Server (NTRS)

    Doyle, Richard J.

    1989-01-01

    Two issues are addressed which arise in the task of detecting anomalous behavior in complex systems with numerous sensor channels: how to adjust alarm thresholds dynamically, within the changing operating context of the system, and how to utilize sensors selectively, so that nominal operation can be verified reliably without processing a prohibitive amount of sensor data. The approach involves simulation of a causal model of the system, which provides information on expected sensor values, and on dependencies between predicted events, useful in assessing the relative importance of events so that sensor resources can be allocated effectively. The potential applicability of this work to the execution monitoring of robot task plans is briefly discussed.

  2. Models for predicting enteric methane emissions from dairy cows in North America, Europe, and Australia and New Zealand.

    PubMed

    Appuhamy, Jayasooriya A D R N; France, James; Kebreab, Ermias

    2016-09-01

    There are several models in the literature for predicting enteric methane (CH4 ) emissions. These models were often developed on region or country-specific data and may not be able to predict the emissions successfully in every region. The majority of extant models require dry matter intake (DMI) of individual animals, which is not routinely measured. The objectives of this study were to (i) evaluate performance of extant models in predicting enteric CH4 emissions from dairy cows in North America (NA), Europe (EU), and Australia and New Zealand (AUNZ) and (ii) explore the performance using estimated DMI. Forty extant models were challenged on 55, 105, and 52 enteric CH4 measurements (g per lactating cow per day) from NA, EU, and AUNZ, respectively. The models were ranked using root mean square prediction error as a percentage of the average observed value (RMSPE) and concordance correlation coefficient (CCC). A modified model of Nielsen et al. (Acta Agriculturae Scand Section A, 63, 2013 and 126) using DMI, and dietary digestible neutral detergent fiber and fatty acid contents as predictor variables, were ranked highest in NA (RMSPE = 13.1% and CCC = 0.78). The gross energy intake-based model of Yan et al. (Livestock Production Science, 64, 2000 and 253) and the updated IPCC Tier 2 model were ranked highest in EU (RMSPE = 11.0% and CCC = 0.66) and AUNZ (RMSPE = 15.6% and CCC = 0.75), respectively. DMI of cows in NA and EU was estimated satisfactorily with body weight and fat-corrected milk yield data (RMSPE < 12.0% and CCC > 0.60). Using estimated DMI, the Nielsen et al. (2013) (RMSPE = 12.7 and CCC = 0.79) and Yan et al. (2000) (RMSPE = 13.7 and CCC = 0.50) models still predicted emissions in respective regions well. Enteric CH4 emissions from dairy cows can be predicted successfully (i.e., RMSPE < 15%), if DMI can be estimated with reasonable accuracy (i.e., RMSPE < 10%). PMID:27148862

  3. Predicting career development in hard-of-hearing adolescents in Australia.

    PubMed

    Punch, Renée; Creed, Peter A; Hyde, Merv

    2005-01-01

    This article reports on a study investigating the career development of hard-of-hearing high school students attending regular classes with itinerant teacher support. We compared 65 hard-of-hearing students with a matched group of normally hearing peers on measures of career maturity, career indecision, perceived career barriers, and three variables associated with social cognitive career theory career decision-making self-efficacy, outcome expectations, and goals. In addition, the predictors of career maturity and career indecision were tested in both groups. Results indicated that (a) the two groups did not differ on measures of career maturity, (b) the SCCT variables were less predictive of career behaviors for the hard-of-hearing students than for the normally hearing students, and (c) perceived career barriers related to hearing loss predicted lower scores on career maturity attitude for the hard-of-hearing students. These findings are discussed in the context of career education and counseling interventions that may benefit young people who are hard of hearing. PMID:15778211

  4. Remotely Monitoring Change in Vegetation Cover on the Montebello Islands, Western Australia, in Response to Introduced Rodent Eradication

    PubMed Central

    Lohr, Cheryl; Van Dongen, Ricky; Huntley, Bart; Gibson, Lesley; Morris, Keith

    2014-01-01

    The Montebello archipelago consists of 218 islands; 80 km from the north-west coast of Western Australia. Before 1912 the islands had a diverse terrestrial fauna. By 1952 several species were locally extinct. Between 1996 and 2011 rodents and cats were eradicated, and 5 mammal and 2 bird species were translocated to the islands. Monitoring of the broader terrestrial ecosystem over time has been limited. We used 20 dry-season Landsat images from 1988 to 2013 and estimation of green fraction cover in nadir photographs taken at 27 sites within the Montebello islands and six sites on Thevenard Island to assess change in vegetation density over time. Analysis of data averaged across the 26-year period suggests that 719 ha out of 2169 ha have increased in vegetation cover by up to 32%, 955 ha have remained stable and 0.6 ha have declined in vegetation cover. Over 492 ha (22%) had no vegetation cover at any time during the period analysed. Chronological clustering analysis identified two breakpoints in the average vegetation cover data occurring in 1997 and 2003, near the beginning and end of the rodent eradication activities. On many islands vegetation cover was declining prior to 1996 but increased after rodents were eradicated from the islands. Data for North West and Trimouille islands were analysed independently because of the potential confounding effect of native fauna being introduced to these islands. Mala (Lagorchestes hirsutus) and Shark Bay mice (Pseudomys fieldi) both appear to suppress native plant recruitment but not to the same degree as introduced rodents. Future research should assess whether the increase in vegetation cover on the Montebello islands is due to an increase in native or introduced plants. PMID:25436454

  5. Improving Flood Prediction By the Assimilation of Satellite Soil Moisture in Poorly Monitored Catchments.

    NASA Astrophysics Data System (ADS)

    Alvarez-Garreton, C. D.; Ryu, D.; Western, A. W.; Crow, W. T.; Su, C. H.; Robertson, D. E.

    2014-12-01

    Flood prediction in poorly monitored catchments is among the greatest challenges faced by hydrologists. To address this challenge, an increasing number of studies in the last decade have explored methods to integrate various existing observations from ground and satellites. One approach in particular, is the assimilation of satellite soil moisture (SM-DA) into rainfall-runoff models. The rationale is that satellite soil moisture (SSM) can be used to correct model soil water states, enabling more accurate prediction of catchment response to precipitation and thus better streamflow. However, there is still no consensus on the most effective SM-DA scheme and how this might depend on catchment scale, climate characteristics, runoff mechanisms, model and SSM products used, etc. In this work, an operational SM-DA scheme was set up in the poorly monitored, large (>40,000 km2), semi-arid Warrego catchment situated in eastern Australia. We assimilated passive and active SSM products into the probability distributed model (PDM) using an ensemble Kalman filter. We explored factors influencing the SM-DA framework, including relatively new techniques to remove model-observation bias, estimate observation errors and represent model errors. Furthermore, we explored the advantages of accounting for the spatial distribution of forcing and channel routing processes within the catchment by implementing and comparing lumped and semi-distributed model setups. Flood prediction is improved by SM-DA (Figure), with a 30% reduction of the average root-mean-squared difference of the ensemble prediction, a 20% reduction of the false alarm ratio and a 40% increase of the ensemble mean Nash-Sutcliffe efficiency. SM-DA skill does not significantly change with different observation error assumptions, but the skill strongly depends on the observational bias correction technique used, and more importantly, on the performance of the open-loop model before assimilation. Our findings imply that proper

  6. Assessing the repeatability of terrestrial laser scanning for monitoring gully topography: A case study from Aratula, Queensland, Australia

    NASA Astrophysics Data System (ADS)

    Goodwin, Nicholas Robert; Armston, John; Stiller, Isaac; Muir, Jasmine

    2016-06-01

    Terrestrial laser scanning (TLS) technology is a powerful tool for quantifying gully morphology and monitoring change over time. This is due to the high sampling density, sub-centimetre positional accuracies (x, y, z), flexibility of survey configurations and ability to link multiple TLS scans together. However, to ensure correct interpretation of results, research is needed to test the repeatability of TLS derived products to quantify the accuracy and separate 'false' from 'true' geomorphic change. In this study, we use the RIEGL VZ400 scanner to test the repeatability of TLS datasets for mapping gully morphology. We then quantify change following a rainfall event of approximately 100 mm. Our study site, located in south-east Queensland, Australia was chosen to be challenging from a repeatability perspective with high topographic variability. The TLS data capture involved three sets of linked scans: one survey pre-rainfall, to be compared to two surveys post-rainfall acquired on consecutive days. Change is considered negligible in the two post-rainfall scans to test survey repeatability. To verify TLS accuracy, an independent dataset of gully extent and spot heights were acquired using traditional total station techniques. Results confirm that the TLS datasets can be registered multi-temporally at sub-centimetre levels of accuracy in three dimensions. Total station and TLS elevation samples showed strong agreement with a mean error and standard deviation (SD) of residuals equal to 0.052 and 0.047 m, respectively (n = 889). Significantly, our repeatability tests found that return type and pulse deviation influence the accuracy and repeatability of DEMs in gully environments. Analysis of consecutive day datasets showed that DEMs derived from first return data recorded 40% higher SD of residual error than DEMs using multiple return data. A significant empirical relationship between pulse deviation and the variance of residuals for repeat DEMs is also shown (r2 = 0

  7. Ischemic placental syndrome - prediction and new disease monitoring.

    PubMed

    Kwiatkowski, Sebastian; Kwiatkowska, Ewa; Rzepka, Rafał; Torbe, Andrzej; Dolegowska, Barbara

    2016-06-01

    The last decade has seen an improved understanding of the cause of the development of pathologies such as gestational hypertension, preeclampsia, intrauterine growth restriction, intrauterine fetal death or placental abruption. Nowadays, we know that most conditions within this group share the same pathogenesis, the cause of which is placental ischemia. The following review is an attempt to propose a new method for prediction, diagnosis and - above all - appropriate monitoring of pregnant women and fetuses developing the ischemic placental syndrome with the use of tests that are new but yet widely available in clinical diagnosis. They are closely related to the condition's pathogenesis, therefore their elevated levels may predate clinical symptoms, and - most importantly - they correlate with syndrome aggravation and the occurrence of complications. Perhaps, the new look will allow us to improve perinatal results by reducing mortality and severe complications in pregnant women and fetal deaths resulting from sudden intrauterine fetal death or placental abruption. PMID:26444581

  8. A novel bridge scour monitoring and prediction system

    NASA Astrophysics Data System (ADS)

    Valyrakis, Manousos; Michalis, Panagiotis; Zhang, Hanqing

    2015-04-01

    obtaining real time data, via novel electromagnetic sensors monitoring scour depth. Once the model is trained with data representative of the new system, bridge scour prediction can be performed for high/design flows or floods.

  9. Effectiveness of impedance monitoring during radiofrequency ablation for predicting popping

    PubMed Central

    Iida, Hiroya; Aihara, Tsukasa; Ikuta, Shinichi; Yamanaka, Naoki

    2012-01-01

    AIM: To retrospectively evaluate the effectiveness of impedance monitoring for predicting popping during radiofrequency ablation (RFA) using internally cooled electrodes. METHODS: We reviewed 140 patients (94 males, 46 females; age range 73.0 ± 11.1 year) who underwent RFA between February 2006 and November 2008 with a modified protocol using a limited power delivery rather than a conventional one to avoid popping. All the patients provided their written informed consent, and the study was approved by the institutional review board. Intraprocedural impedances were measured for the study subjects, and the tumors were classified into three types according to the characteristics of their impedance curves: increasing, flat, or decreasing. The tumors were further sorted into seven subtypes (A-G) depending on the curvature of the impedance curve’s increase or decrease. Relative popping rates were determined for the three types and seven subtypes. A chi-square test was performed to estimate statistical significance. RESULTS: A total of 148 nodules treated by RFA were analyzed. The study samples included 132 nodules of hepatocellular carcinoma, 14 nodules of metastatic liver cancer, and two nodules of intrahepatic cholangiocarcinoma. The numbers of nodules with each impedance curve type were as follows: 37 increasing-type nodules, 43 flat-type nodules, and 68 decreasing-type nodules. Popping occurrence rates were 24.3%, 46.5% and 64.7%, respectively. Flat-type nodules exhibited a significantly higher rate of popping compared to increasing-type nodules (P = 0.039). Decreasing-type nodules exhibited a significantly higher rate of popping compared to increasing-type nodules (P < 0.0001). Notably, nodules that showed a sharp decrease in impedance in the latter ablation period (subtype E) exhibited a significantly higher rate of popping compared to other subtypes. CONCLUSION: Intraprocedural impedance monitoring can be a useful tool to predict the occurrence of popping

  10. The SupraThermal Ion Monitor for space weather predictions.

    PubMed

    Allegrini, F; Desai, M I; Livi, S; McComas, D J; Ho, G C

    2014-05-01

    Measurement of suprathermal energy ions in the heliosphere has always been challenging because (1) these ions are situated in the energy regime only a few times higher than the solar wind plasma, where intensities are orders of magnitude higher and (2) ion energies are below or close to the threshold of state-of-art solid-state detectors. Suprathermal ions accelerated at coronal mass ejection-driven shocks propagate out ahead of the shocks. These shocks can cause geomagnetic storms in the Earth's magnetosphere that can affect spacecraft and ground-based power and communication systems. An instrument with sufficient sensitivity to measure these ions can be used to predict the arrival of the shocks and provide an advance warning for potentially geo-effective space weather. In this paper, we present a novel energy analyzer concept, the Suprathermal Ion Monitor (STIM) that is designed to measure suprathermal ions with high sensitivity. We show results from a laboratory prototype and demonstrate the feasibility of the concept. A list of key performances is given, as well as a discussion of various possible detectors at the back end. STIM is an ideal candidate for a future space weather monitor in orbit upstream of the near-earth environment, for example, around L1. A scaled-down version is suitable for a CubeSat mission. Such a platform allows proofing the concept and demonstrating its performance in the space environment. PMID:24880387

  11. Predictive NO x emission monitoring on board a passenger ferry

    NASA Astrophysics Data System (ADS)

    Cooper, D. A.; Andreasson, K.

    NO x emissions from a medium speed diesel engine on board a servicing passenger ferry have been indirectly measured using a predictive emission monitoring system (PEMS) over a 1-yr period. Conventional NO x measurements were carried out with a continuous emission monitoring system (CEMS) at the start of the study to provide historical data for the empirical PEMS function. On three other occasions during the year the CEMS was also used to verify the PEMS and follow any changes in emission signature of the engine. The PEMS consisted of monitoring exhaust O 2 concentrations (in situ electrochemical probe), engine load, combustion air temperature and humidity, and barometric pressure. Practical experiences with the PEMS equipment were positive and measurement data were transferred to a land-based office by using a modem data communication system. The initial PEMS function (PEMS1) gave systematic differences of 1.1-6.9% of the calibration domain (0-1725 ppm) and a relative accuracy of 6.7% when compared with CEMS for whole journeys and varying load situations. Further improvements on the performance could be obtained by updating this function. The calculated yearly emission for a total engine running time of 4618 h was 316 t NO x±38 t and the average NO x emission corrected for ambient conditions 14.3 g kWh corr-1. The exhaust profile of the engine in terms of NO x, CO and CO 2 emissions as determined by CEMS was similar for most of the year. Towards the end of the study period, a significantly lower NO x emission was detected which was probably caused by replacement of fuel injector nozzles. The study suggests that PEMS can be a viable option for continuous, long-term NO x measurements on board ships.

  12. Potential wildlife sentinels for monitoring the endemic spread of human buruli ulcer in South-East australia.

    PubMed

    Carson, Connor; Lavender, Caroline J; Handasyde, Kathrine A; O'Brien, Carolyn R; Hewitt, Nick; Johnson, Paul D R; Fyfe, Janet A M

    2014-01-01

    The last 20 years has seen a significant series of outbreaks of Buruli/Bairnsdale Ulcer (BU), caused by Mycobacterium ulcerans, in temperate south-eastern Australia (state of Victoria). Here, the prevailing view of M. ulcerans as an aquatic pathogen has been questioned by recent research identifying native wildlife as potential terrestrial reservoirs of infection; specifically, tree-dwelling common ringtail and brushtail possums. In that previous work, sampling of environmental possum faeces detected a high prevalence of M. ulcerans DNA in established endemic areas for human BU on the Bellarine Peninsula, compared with non-endemic areas. Here, we report research from an emergent BU focus recently identified on the Mornington Peninsula, confirming associations between human BU and the presence of the aetiological agent in possum faeces, detected by real-time PCR targeting M. ulcerans IS2404, IS2606 and KR. Mycobacterium ulcerans DNA was detected in 20/216 (9.3%) ground collected ringtail possum faecal samples and 4/6 (66.6%) brushtail possum faecal samples. The distribution of the PCR positive possum faecal samples and human BU cases was highly focal: there was a significant non-random cluster of 16 M. ulcerans positive possum faecal sample points detected by spatial scan statistics (P<0.0001) within a circle of radius 0.42 km, within which were located the addresses of 6/12 human cases reported from the area to date; moreover, the highest sample PCR signal strength (equivalent to ≥10(6) organisms per gram of faeces) was found in a sample point located within this cluster radius. Corresponding faecal samples collected from closely adjacent BU-free areas were predominantly negative. Possums may be useful sentinels to predict endemic spread of human BU in Victoria, for public health planning. Further research is needed to establish whether spatial associations represent evidence of direct or indirect transmission between possums and humans, and the mechanism by

  13. Potential Wildlife Sentinels for Monitoring the Endemic Spread of Human Buruli Ulcer in South-East Australia

    PubMed Central

    Carson, Connor; Lavender, Caroline J.; Handasyde, Kathrine A.; O'Brien, Carolyn R.; Hewitt, Nick; Johnson, Paul D. R.; Fyfe, Janet A. M.

    2014-01-01

    The last 20 years has seen a significant series of outbreaks of Buruli/Bairnsdale Ulcer (BU), caused by Mycobacterium ulcerans, in temperate south-eastern Australia (state of Victoria). Here, the prevailing view of M. ulcerans as an aquatic pathogen has been questioned by recent research identifying native wildlife as potential terrestrial reservoirs of infection; specifically, tree-dwelling common ringtail and brushtail possums. In that previous work, sampling of environmental possum faeces detected a high prevalence of M. ulcerans DNA in established endemic areas for human BU on the Bellarine Peninsula, compared with non-endemic areas. Here, we report research from an emergent BU focus recently identified on the Mornington Peninsula, confirming associations between human BU and the presence of the aetiological agent in possum faeces, detected by real-time PCR targeting M. ulcerans IS2404, IS2606 and KR. Mycobacterium ulcerans DNA was detected in 20/216 (9.3%) ground collected ringtail possum faecal samples and 4/6 (66.6%) brushtail possum faecal samples. The distribution of the PCR positive possum faecal samples and human BU cases was highly focal: there was a significant non-random cluster of 16 M. ulcerans positive possum faecal sample points detected by spatial scan statistics (P<0.0001) within a circle of radius 0.42 km, within which were located the addresses of 6/12 human cases reported from the area to date; moreover, the highest sample PCR signal strength (equivalent to ≥106 organisms per gram of faeces) was found in a sample point located within this cluster radius. Corresponding faecal samples collected from closely adjacent BU-free areas were predominantly negative. Possums may be useful sentinels to predict endemic spread of human BU in Victoria, for public health planning. Further research is needed to establish whether spatial associations represent evidence of direct or indirect transmission between possums and humans, and the mechanism by which

  14. Is predictive emission monitoring an acceptable low cost alternative to continuous emission monitoring for complying with enhanced monitoring requirements?

    SciTech Connect

    Jernigan, J.R.

    1995-12-01

    Title VII of the 1990 Clean Air Act Amendments (the {open_quotes}Act{close_quotes}) expanded and clarified the Environmental Protection Agency`s (EPA) enforcement capabilities under the Act. Section 702 of the 1990 Amendments clarified EPA`s ability to require sources to provide information. Additionally, Section 702(b) required EPA to promulgate rules on enhanced monitoring and compliance certifications by adding a new section 114(a)(3) of the Act which states in part: {open_quotes}The Administrator shall in the case of any person which is the owner or operator of a major stationary source, and any in the case of any other person, require enhanced monitoring and submission of compliance certifications. Compliance certifications shall include (A) identification of the applicable requirement that is the basis of the certification, (B) the method used for determining the compliance status of the source, (C) the compliance status, (D) whether compliance is continuous or intermittent, (E) such other facts as the Administrator may require...{close_quotes} The 1990 Amendments contained several other changes that either relate directly to section 114(a)(3) or provide additional indications of the intent behind the new section. First, section 504(b) of the Amendments permits the Administrator to promulgate appropriate tests methods and monitoring requirements for determining compliance. That section states that {open_quotes}continuous emissions monitoring need not be required if alternative methods are available that provide sufficiently reliable and timely information for determining compliance.{close_quotes} This paper will describe Predictive Emission Systems (PEMS) and how the applications of PEMS may be a low cost, accurate, and acceptable alternative to Continuous Emission Monitoring Systems (CEMS) for complying with Enhanced Monitoring requirements.

  15. Short range prediction and monitoring of downbursts over Indian region

    NASA Astrophysics Data System (ADS)

    Johny, C. J.; Prasad, V. S.; Singh, S. K.; Basu, Swati

    2016-05-01

    Convective downdraft motions and related outflow wind considered as an eventual source of potential damage which can be more severe in the aviation sector. A great variety of atmospheric environments can produce these downdraft motions. These events are not easily detectable using conventional weather radar or wind shear alert systems, while Doppler radars are useful for identifying these Downbursts. In order to identify the situations that can cause these downdraft events different diagnostic tools are designed. Recently launched Indian satellite INSAT-3D, with atmospheric sounder and imager on board, is capable of identifying regions of downburst occurrence and can help in monitoring them in real time. Some Downburst events reported over different parts of India, during January-April period is investigated using Microburst Wind Speed Potential Index (MWPI) and thermodynamic characteristics derived from the NCMRWF GFS (NGFS) model. An attempt is made to make a short range prediction of these events using MWPI computed from NGFS model forecasts. The results are validated with in-situ observations and also by employing INSAT-3D data and it is shown that the method has a reasonable success. All the investigated downdraft events are associated with the hybrid Microburst environment.

  16. Optimal characterization of pollutant sources in contaminated aquifers by integrating sequential-monitoring-network design and source identification: methodology and an application in Australia

    NASA Astrophysics Data System (ADS)

    Prakash, Om; Datta, Bithin

    2015-09-01

    Often, when pollution is first detected in groundwater, very few spatiotemporal pollutant concentration measurements are available. The contaminant concentration measurement data initially available are generally sparse and insufficient for accurate source characterization. This requires development of a contaminant monitoring plan and its field implementation to collect more data. The location of scientifically chosen monitoring points and the number of measurements are important considerations in improving the source-characterization process, especially in a complex contamination scenario. In order to improve the efficiency of source characterization, a feedback-based methodology is implemented, integrating sequential-monitoring-network design and a source identification method. The simulated annealing (SA) optimization algorithm is used to solve the models for optimal source identification and the monitoring-network-design optimization. This sequence is repeated a few times to improve the accuracy of source characterization. The methodology is based on the premise that concentration measurements from a sequence of implemented monitoring networks provide feedback information on the actual concentration in the site. This additional information, obtained as feedback from monitoring networks designed and implemented based on intermediate source characterization, can result in sequential improvement in the resulting source characterization. The performance of this methodology is evaluated by application to a contaminated aquifer site in New South Wales, Australia, where source location, source-activity initiation time and source-flux (mass per unit time) release history are considered as unknown variables. The performance evaluation results demonstrate potential applicability of the proposed sequential methodology.

  17. A summary of fault modelling and predictive health monitoring of rolling element bearings

    NASA Astrophysics Data System (ADS)

    El-Thalji, Idriss; Jantunen, Erkki

    2015-08-01

    The rolling element bearing is one of the most critical components that determine the machinery health and its remaining lifetime in modern production machinery. Robust Predictive Health Monitoring tools are needed to guarantee the healthy state of rolling element bearing s during the operation. A Predictive Health Monitoring tool indicates the upcoming failures which provide sufficient lead time for maintenance planning. The Predictive Health Monitoring tool aims to monitor the deterioration i.e. wear evolution rather than just detecting the defects. The Predictive Health Monitoring procedures contain detection, diagnosis and prognosis analysis, which are required to extract the features related to the faulty rolling element bearing and estimate the remaining useful lifetime. The purpose of this study is to review the Predictive Health Monitoring methods and explore their capabilities, advantages and disadvantage in monitoring rolling element bearings. Therefore, the study provides a critical review of the Predictive Health Monitoring methods of the entire defect evolution process i.e. over the whole lifetime and suggests enhancements for rolling element bearing monitoring.

  18. Tectonic events, sequence stratigraphy and prediction of petroleum play elements in the Cretaceous and Tertiary of the northern Carnarvon Basin, north west shelf, Australia

    SciTech Connect

    Romine, K.K.; Durrant, J.D.

    1996-12-31

    The Carnarvon Basin is one of Australia`s most prolific oil and gas provinces. A recent Paleocene discovery has initiated a shift in exploration interest from traditional Jurassic/Triassic plays to the younger Cretaceous and Tertiary section. To improve play element prediction, a sequence stratigraphic study has been completed, utilizing newly acquired, regional high-resolution seismic data and 80 wells. The occurrence and distribution of the key play elements, reservoir, source and seal, is controlled by the interaction of tectonic subsidence, eustasy and paleogeography, with traps and migration pathways set up and modified by regional tectonic events. For example, a major rifting event commenced in the latest Kimmeridgian-Tithonian that resulted in structuring of older Jurassic sediments and initiation of seafloor spreading in the adjacent Cuvier-Gascoyne Abyssal Plain in the Valanginian. This event was accompanied by a dramatic fall in eustasy that initiated the deposition of high-quality reservoir sandstones of the Tithonian-Valanginian age Barrow Delta. The post-rift phase of thermal cooling and rapid subsidence resulted in transgression, accompanied by deposition of backstepping parasequences of the Mardie Greensand, a potential thief zone and reservoir, and culminated in maximum transgression and deposition of seal and source facies of the Muclerong Shale. The improved sequence stratigraphic framework established in this study provides a predictive tool for the development and assessment of new plays.

  19. Application of GNSS-RTK derived topographical maps for rapid environmental monitoring: a case study of Jack Finnery Lake (Perth, Australia).

    PubMed

    Schloderer, Glen; Bingham, Matthew; Awange, Joseph L; Fleming, Kevin M

    2011-09-01

    In environmental monitoring, environmental impact assessments and environmental audits, topographical maps play an essential role in providing a means by which the locations of sampling sites may be selected, in assisting with the interpretation of physical features, and in indicating the impact or potential impact on an area due to changes in the system being monitored (e.g., spatially changing features such as wetlands). Global Navigation Satellite Systems (GNSS) are hereby presented as a rapid method for monitoring spatial changes to support environmental monitoring decisions and policies. To validate the GNSS-based method, a comparison is made of results from a small-scale topographic survey using radio-based real-time kinematic GNSS (GNSS-RTK) and total station survey methods at Jack Finnery Lake, Perth, Australia. The accuracies achieved by the total station in this study were 2 cm horizontally and 6 cm vertically, while the GNSS-RTK also achieved an accuracy of 2 cm horizontally, but only 28 cm vertically. While the GNSS-RTK measurements were less accurate in the height component compared to those from the total station method, it is still capable of achieving accuracies sufficient for a topographic map at a scale of 1:1,750 that could support environmental monitoring tasks such as identifying spatial changes in small water bodies or wetlands. The time taken to perform the survey using GNSS-RTK, however, was much shorter compared to the total station method, thereby making it quite suitable for monitoring spatial changes within an environmental context, e.g., dynamic mining activities that require rapid surveys and the updating of the monitored data at regular intervals. PMID:21136293

  20. Privatizing Australia

    SciTech Connect

    Burr, M.T.

    1995-07-01

    The sun is setting on Australia`s long tradition of state involvement in business. As part of efforts begun in the late-1980`s to stem the tide of debt rising within Australian federal and state treasuries, government-owned entities are being corporatized and privatized, and private companies are sponsoring a large share of the country`s new infrastructure projects.

  1. The monitoring and prediction of solar particle events--an experience report.

    PubMed

    Heckman, G; Hirman, J; Kunches, J; Balch, C

    1984-01-01

    The routine monitoring and prediction of solar proton events that may be a hazard to personnel and materials in space are a routine service of the Space Environment Services Center in Boulder, Colorado, U.S.A. The services provided are made available to the space centers in the United States for use in their operations. The real time monitoring consists primarily of Space Environment Monitors on both geosynchronous and polar orbiting weather satellites. The monitoring emphasizes proton fluxes but alpha particles, electrons, and in one case, heavier particles, are included. The predictions are of two types; a general outlook made 1 to 3 days in advance, and specific prediction of event size and probability of occurrence made after a solar flare occurs. The accuracy of the prediction made for solar cycle 21 are assessed. PMID:11539624

  2. FUSE - Australia

    ERIC Educational Resources Information Center

    South Australian Science Teachers Journal, 1974

    1974-01-01

    Announces the establishment of a division of FUSE in Australia, at Sturt College of Advanced Education, for the purpose of disseminating the concept of unified science and to facilitate the development of unified science programs. (BR)

  3. EPA perspective - exposure and effects prediction and monitoring

    EPA Science Inventory

    Risk-based decisions for environmental chemicals often rely on estimates of human exposure and biological response. Biomarkers have proven a useful empirical tool for evaluating exposure and hazard predictions. In the United States, the Centers for Disease Control and Preventio...

  4. Interactions of Team Mental Models and Monitoring Behaviors Predict Team Performance in Simulated Anesthesia Inductions

    ERIC Educational Resources Information Center

    Burtscher, Michael J.; Kolbe, Michaela; Wacker, Johannes; Manser, Tanja

    2011-01-01

    In the present study, we investigated how two team mental model properties (similarity vs. accuracy) and two forms of monitoring behavior (team vs. systems) interacted to predict team performance in anesthesia. In particular, we were interested in whether the relationship between monitoring behavior and team performance was moderated by team…

  5. Predicting Activity Energy Expenditure Using the Actical[R] Activity Monitor

    ERIC Educational Resources Information Center

    Heil, Daniel P.

    2006-01-01

    This study developed algorithms for predicting activity energy expenditure (AEE) in children (n = 24) and adults (n = 24) from the Actical[R] activity monitor. Each participant performed 10 activities (supine resting, three sitting, three house cleaning, and three locomotion) while wearing monitors on the ankle, hip, and wrist; AEE was computed…

  6. Predictive monitoring research: Summary of the PREMON system

    NASA Technical Reports Server (NTRS)

    Doyle, Richard J.; Sellers, Suzanne M.; Atkinson, David J.

    1987-01-01

    Traditional approaches to monitoring are proving inadequate in the face of two important issues: the dynamic adjustment of expectations about sensor values when the behavior of the device is too complex to enumerate beforehand, and the selective but effective interpretation of sensor readings when the number of sensors becomes overwhelming. This system addresses these issues by building an explicit model of a device and applying common-sense theories of physics to model causality in the device. The resulting causal simulation of the device supports planning decisions about how to efficiently yet reliably utilize a limited number of sensors to verify correct operation of the device.

  7. Accelerometry-based prediction of movement dynamics for balance monitoring.

    PubMed

    Fuschillo, Valeria Lucia; Bagalà, Fabio; Chiari, Lorenzo; Cappello, Angelo

    2012-09-01

    This paper proposes a 2D functional evaluation tool for estimating subject-specific body segment parameters, which uses a simple motor task (repeated sit-to-stand, rSTS), recorded with one single-axis accelerometer (SAA) per segment and a force plate (FP). After this preliminary estimation, the accelerometer alone is used to make quasi-real-time predictions of ground reaction force (anterior/posterior, F ( X ), and vertical, F ( Z ), components), center of pressure (CoP) and center of mass (CoM), during rSTS and postural oscillation in the sagittal plane. These predicted dynamic variables, as well as those obtained using anthropometric parameters derived from De Leva, were compared to actual FP outputs in terms of root mean-squared errors (RMSEs). Using De Leva's parameters in place of those estimated, RMSEs increase from 12 to 21 N (F ( X )), from 21 to 24 N (F ( Z )), and from 21.1 to 55.6 mm (CoP) in rSTS; similarly, RMSEs increase from 3.1 to 3.3 N (F ( X )) and from 5.5 to 6.6 mm (CoP) in oscillatory trials. A telescopic inverted pendulum model was adopted to analyze the balance control in rSTS using only predicted CoP and CoM. Results suggest that one SAA per segment is sufficient to predict the dynamics of a biomechanical model of any degrees of freedom. PMID:22802142

  8. Evaluation of Wheat Growth Monitoring Methods Based on Hyperspectral Data of Later Grain Filling and Heading Stages in Western Australia

    NASA Astrophysics Data System (ADS)

    Nakanishi, T.; Imai, Y.; Morita, T.; Akamatsu, Y.; Odagawa, S.; Takeda, T.; Kashimura, O.

    2012-07-01

    This study estimated the wheat yield, quality, and growth conditions using hyperspectral data of the later grain filling and heading stages. The study area is located in the suburbs of Mullewa, Western Australia. Various data used included spectral reflectance of wheat measured from the ground and those measured using airborne sensors, wheat growth conditions data, such as LAI, SPAD values, and wheat height, and sample analysis data, including biomass, grain nitrogen content rate, leaf nitrogen content rate, and ash content, of the later grain filling and heading stages. This study consisted of (1) selection of estimation items regarding the wheat yield, quality, and growth conditions by correlation analysis of sample data, (2) definition of estimate equations for selected items, (3) verification of estimation accuracy, and (4) development of estimation maps. As a result, head moisture, which is related to the wheat growth conditions, was well estimated using hyperspectral data of the later grain filling stage. At the same time, grain weight, which is related to the wheat yield, and grain nitrogen content rate and ash content, which are related to the wheat quality, were well estimated using hyperspectral data of the heading stage. This study implies that it is possible to visualize the wheat yield, quality, and growth conditions on a regional scale using hyperspectral data.

  9. Effect of broadcast baiting on abundance patterns of red imported fire ants (Hymenoptera: Formicidae) and key local ant genera at long-term monitoring sites in Brisbane, Australia.

    PubMed

    McNaught, Melinda K; Wylie, F Ross; Harris, Evan J; Alston, Clair L; Burwell, Chris J; Jennings, Craig

    2014-08-01

    In 2001, the red imported fire ant (Solenopsis invicta Buren) was identified in Brisbane, Australia. An eradication program involving broadcast bait treatment with two insect growth regulators and a metabolic inhibitor began in September of that year and is currently ongoing. To gauge the impacts of these treatments on local ant populations, we examined long-term monitoring data and quantified abundance patterns of S. invicta and common local ant genera using a linear mixed-effects model. For S. invicta, presence in pitfalls reduced over time to zero on every site. Significantly higher numbers of S. invicta workers were collected on high-density polygyne sites, which took longer to disinfest compared with monogyne and low-density polygyne sites. For local ants, nine genus groups of the 10 most common genera analyzed either increased in abundance or showed no significant trend. Five of these genus groups were significantly less abundant at the start of monitoring on high-density polygyne sites compared with monogyne and low-density polygyne sites. The genus Pheidole significantly reduced in abundance over time, suggesting that it was affected by treatment efforts. These results demonstrate that the treatment regime used at the time successfully removed S. invicta from these sites in Brisbane, and that most local ant genera were not seriously impacted by the treatment. These results have important implications for current and future prophylactic treatment efforts, and suggest that native ants remain in treated areas to provide some biological resistance to S. invicta. PMID:25195416

  10. In Brief: Unlocking Australia's oil and gas reserves

    NASA Astrophysics Data System (ADS)

    Showstack, Randy

    2007-11-01

    A collaboration to unlock stranded offshore oil and gas reserves through improved underwater pipeline design was launched in Perth, Australia, on 31 October. Called the Wealth From Oceans National Research Flagship's Collaboration Cluster on Subsea Pipelines, the A$11 million program brings together the research capabilities of Australia's Commonwealth Scientific and Industrial Research Organisation (CSIRO) and six universities. With more than 80% of Australia's gas resources likely lying as far as 300 kilometers offshore at a depth greater than 1 kilometer, Flagship director Kate Wilson said that realizing the full potential of these resources requires developing economically viable and environmentally sound transportation technologies. ``Projects will investigate seabed characterization and morphology, structural integrity, pipeline monitoring, geohazards, and full-life reliability. This will involve everything from sophisticated computer modeling and seafloor movement prediction to understanding tsunami effects and exploring the use of autonomous underwater and remotely operated vehicles.''

  11. Continuous metabolic monitoring based on multi-analyte biomarkers to predict exhaustion.

    PubMed

    Kastellorizios, Michail; Burgess, Diane J

    2015-01-01

    This work introduces the concept of multi-analyte biomarkers for continuous metabolic monitoring. The importance of using more than one marker lies in the ability to obtain a holistic understanding of the metabolism. This is showcased for the detection and prediction of exhaustion during intense physical exercise. The findings presented here indicate that when glucose and lactate changes over time are combined into multi-analyte biomarkers, their monitoring trends are more sensitive in the subcutaneous tissue, an implantation-friendly peripheral tissue, compared to the blood. This unexpected observation was confirmed in normal as well as type 1 diabetic rats. This study was designed to be of direct value to continuous monitoring biosensor research, where single analytes are typically monitored. These findings can be implemented in new multi-analyte continuous monitoring technologies for more accurate insulin dosing, as well as for exhaustion prediction studies based on objective data rather than the subject's perception. PMID:26028477

  12. Continuous Metabolic Monitoring Based on Multi-Analyte Biomarkers to Predict Exhaustion

    PubMed Central

    Kastellorizios, Michail; Burgess, Diane J.

    2015-01-01

    This work introduces the concept of multi-analyte biomarkers for continuous metabolic monitoring. The importance of using more than one marker lies in the ability to obtain a holistic understanding of the metabolism. This is showcased for the detection and prediction of exhaustion during intense physical exercise. The findings presented here indicate that when glucose and lactate changes over time are combined into multi-analyte biomarkers, their monitoring trends are more sensitive in the subcutaneous tissue, an implantation-friendly peripheral tissue, compared to the blood. This unexpected observation was confirmed in normal as well as type 1 diabetic rats. This study was designed to be of direct value to continuous monitoring biosensor research, where single analytes are typically monitored. These findings can be implemented in new multi-analyte continuous monitoring technologies for more accurate insulin dosing, as well as for exhaustion prediction studies based on objective data rather than the subject’s perception. PMID:26028477

  13. Predicting and Monitoring Cancer Treatment Response with DW-MRI

    PubMed Central

    Thoeny, Harriet C.; Ross, Brian D.

    2010-01-01

    An imaging biomarker that would provide for an early quantitative metric of clinical treatment response in cancer patients would provide for a paradigm shift in cancer care. Currently, non-image based clinical outcome metrics include morphology, clinical and laboratory parameters however, these are obtained relatively late following treatment. Diffusion-weighted MRI (DW-MRI) holds promise for use as a cancer treatment response biomarker as it is sensitive to macromolecular and microstructural changes which can occur at the cellular level earlier than anatomical changes during therapy. Studies have shown that successful treatment of a many tumor types can be detected using DW-MRI as an early increase in the apparent diffusion coefficient (ADC) values. Additionally, low pre-treatment ADC values of various tumors are often predictive of better outcome. These capabilities, once validated, could provide for an important opportunity to individualize therapy thereby minimizing unnecessary systemic toxicity associated with ineffective therapies with the additional advantage of improving overall patient health care and associated costs. In this report, we provide a brief technical overview of DW-MRI acquisition protocols, quantitative image analysis approaches and review studies which have implemented DW-MRI for the purpose of early prediction of cancer treatment response. PMID:20575076

  14. Coronas-F Orbit Monitoring and Re-Entry Prediction

    NASA Technical Reports Server (NTRS)

    Ivanov, N. M.; Kolyuka, Yu. F.; Afanasieva, T. I.; Gridchina, T. A.

    2007-01-01

    Russian scientific satellite CORONAS-F was launched on July, 31, 2001. The object was inserted in near-circular orbit with the inclination 82.5deg and a mean altitude approx. 520 km. Due to the upper atmosphere drag CORONAS-F was permanently descended and as a result on December, 6, 2005 it has finished the earth-orbital flight, having lifetime in space approx. 4.5 years. The satellite structural features and its flight attitude control led to the significant variations of its ballistic coefficient during the flight. It was a cause of some specific difficulties in the fulfillment of the ballistic and navigation support of this space vehicle flight. Besides the main mission objective CORONAS-F also has been selected by the Inter-Agency Space Debris Coordination Committee (IADC) as a target object for the next regular international re-entry test campaign on a program of surveillance and re-entry prediction for the hazard space objects within their de-orbiting phases. Spacecraft (S/C) CORONAS-F kept its working state right up to the end of the flight - down to the atmosphere entry. This fact enabled to realization of the additional research experiments, concerning with an estimation of the atmospheric density within the low earth orbits (LEO) of the artificial satellites, and made possible to continue track the S/C during final phase of its flight by means of Russian regular command & tracking system, used for it control. Thus there appeared a unique possibility of using for tracking S/C at its de-orbiting phase not only passive radar facilities, belonging to the space surveillance systems and traditionally used for support of the IADC re-entry test campaigns, but also more precise active trajectory radio-tracking facilities from the ground control complex (GCC) applied for this object. Under the corresponding decision of the Russian side such capability of additional high-precise tracking control of the CORONAS-F flight in this period of time has been implemented

  15. Reducing the predictive uncertainty associated with groundwater management decision-making in the Perth regional aquifer system of Western Australia

    NASA Astrophysics Data System (ADS)

    Siade, A. J.

    2015-12-01

    The Perth Regional Aquifer Model (PRAMS) framework has been used for about a decade now to evaluate the potential anthropogenic impacts associated with management decisions that affect Perth's groundwater resources. A great wealth of data, expertise and numerical analysis have gone into the development of PRAMS over the years. However, there has been little quantitative work conducted on systemically addressing the uncertainty in the model's structure and predictions. PRAMS is designed to make a variety of regional and local-scale predictions and, both the nature and magnitude of the uncertainty associated with these predictions can vary significantly. A primary prediction to be addressed using the PRAMS framework, will be the effects of various deep-aquifer groundwater management scenarios on both the environmental and social concerns surrounding the superficial aquifer, which supports sensitive wetlands, and the negative impacts of seawater intrusion into the deep aquifers. A particular model-structure component that greatly affects the predictions associated with deep-aquifer groundwater extraction is the characterization of the local fault structure, i.e., whether or not faults are acting as barriers to groundwater flow. Therefore, uncertainty in fault characterization can subsequently lead to significant predictive uncertainty. However, new observation data can be obtained to reduce this uncertainty. In this study, an experimental design methodology is employed to optimally acquire new observations of state in such a way as to maximize the information obtained about the hydraulic properties of faults. Various information criteria are employed to develop optimal locations of new observation wells. The A-optimality criterion was found to be the most effective for comparing sampling strategies given the design assumptions, which include the parameter sets employed, hydraulic forcing, temporal considerations, and the use of the existing observation network. A

  16. Tectonic events, sequence stratigraphy and prediction of petroleum play elements in the Cretaceous and Tertiary of the northern Carnarvon Basin, north west shelf, Australia

    SciTech Connect

    Romine, K.K. ); Durrant, J.D. )

    1996-01-01

    The Carnarvon Basin is one of Australia's most prolific oil and gas provinces. A recent Paleocene discovery has initiated a shift in exploration interest from traditional Jurassic/Triassic plays to the younger Cretaceous and Tertiary section. To improve play element prediction, a sequence stratigraphic study has been completed, utilizing newly acquired, regional high-resolution seismic data and 80 wells. The occurrence and distribution of the key play elements, reservoir, source and seal, is controlled by the interaction of tectonic subsidence, eustasy and paleogeography, with traps and migration pathways set up and modified by regional tectonic events. For example, a major rifting event commenced in the latest Kimmeridgian-Tithonian that resulted in structuring of older Jurassic sediments and initiation of seafloor spreading in the adjacent Cuvier-Gascoyne Abyssal Plain in the Valanginian. This event was accompanied by a dramatic fall in eustasy that initiated the deposition of high-quality reservoir sandstones of the Tithonian-Valanginian age Barrow Delta. The post-rift phase of thermal cooling and rapid subsidence resulted in transgression, accompanied by deposition of backstepping parasequences of the Mardie Greensand, a potential thief zone and reservoir, and culminated in maximum transgression and deposition of seal and source facies of the Muclerong Shale. The improved sequence stratigraphic framework established in this study provides a predictive tool for the development and assessment of new plays.

  17. Prediction of coronary heart disease mortality in Busselton, Western Australia: an evaluation of the Framingham, national health epidemiologic follow up study, and WHO ERICA risk scores.

    PubMed Central

    Knuiman, M W; Vu, H T

    1997-01-01

    STUDY OBJECTIVES: To evaluate the performance of the Framingham, national health epidemiologic follow up study, and the WHO ERICA risk scores in predicting death from coronary heart disease (CHD) in an Australian population. DESIGN: Cohort follow up study. SETTING AND PARTICIPANTS: The cohort consisted of 1923 men and 1968 women who participated in health surveys in the town of Busselton in Western Australia over the period 1966-81. Baseline assessment included cardiovascular risk factor measurement. Mortality follow up to 31 December 1994 was used. MAIN RESULTS: Risk scores for death from CHD within 10 years based on age, systolic blood pressure, cholesterol, smoking, and BMI were derived from the Busselton study data using logistic regression analysis. Similar risk scores developed from the Framingham, the national health epidemiologic follow up study, and the WHO ERICA cohorts were found to perform just as well in Busselton as the Busselton-derived scores, both before and after controlling the effect of age. There was considerable overlap across the different risk scores in the identification of individuals in the highest quintile of risk. Those in the top 20% of scores included about 41% of deaths from CHD among men and about 63% of deaths from CHD among women. CONCLUSION: Although there is variation in risk score coefficients across the studies, the relative risk predictive performance of the scores is similar. The use of Framingham and other similar risk scores will not be misleading in white Australian populations. PMID:9425461

  18. Predicting reading outcomes with progress monitoring slopes among middle grade students.

    PubMed

    Tolar, Tammy D; Barth, Amy E; Fletcher, Jack M; Francis, David J; Vaughn, Sharon

    2014-02-01

    Effective implementation of response-to-intervention (RTI) frameworks depends on efficient tools for monitoring progress. Evaluations of growth (i.e., slope) may be less efficient than evaluations of status at a single time point, especially if slopes do not add to predictions of outcomes over status. We examined progress monitoring slope validity for predicting reading outcomes among middle school students by evaluating latent growth models for different progress monitoring measure-outcome combinations. We used multi-group modeling to evaluate the effects of reading ability, reading intervention, and progress monitoring administration condition on slope validity. Slope validity was greatest when progress monitoring was aligned with the outcome (i.e., word reading fluency slope was used to predict fluency outcomes in contrast to comprehension outcomes), but effects varied across administration conditions (viz., repeated reading of familiar vs. novel passages). Unless the progress monitoring measure is highly aligned with outcome, slope may be an inefficient method for evaluating progress in an RTI context. PMID:24659899

  19. Monitoring Central Venous Catheter Resistance to Predict Imminent Occlusion: A Prospective Pilot Study

    PubMed Central

    Wolf, Joshua; Tang, Li; Rubnitz, Jeffrey E.; Brennan, Rachel C.; Shook, David R.; Stokes, Dennis C.; Monagle, Paul; Curtis, Nigel; Worth, Leon J.; Allison, Kim; Sun, Yilun; Flynn, Patricia M.

    2015-01-01

    Background Long-term central venous catheters are essential for the management of chronic medical conditions, including childhood cancer. Catheter occlusion is associated with an increased risk of subsequent complications, including bloodstream infection, venous thrombosis, and catheter fracture. Therefore, predicting and pre-emptively treating occlusions should prevent complications, but no method for predicting such occlusions has been developed. Methods We conducted a prospective trial to determine the feasibility, acceptability, and efficacy of catheter-resistance monitoring, a novel approach to predicting central venous catheter occlusion in pediatric patients. Participants who had tunneled catheters and were receiving treatment for cancer or undergoing hematopoietic stem cell transplantation underwent weekly catheter-resistance monitoring for up to 12 weeks. Resistance was assessed by measuring the inline pressure at multiple flow-rates via a syringe pump system fitted with a pressure-sensing transducer. When turbulent flow through the device was evident, resistance was not estimated, and the result was noted as “non-laminar.” Results Ten patients attended 113 catheter-resistance monitoring visits. Elevated catheter resistance (>8.8% increase) was strongly associated with the subsequent development of acute catheter occlusion within 10 days (odds ratio = 6.2; 95% confidence interval, 1.8–21.5; p <0.01; sensitivity, 75%; specificity, 67%). A combined prediction model comprising either change in resistance greater than 8.8% or a non-laminar result predicted subsequent occlusion (odds ratio = 6.8; 95% confidence interval, 2.0–22.8; p = 0.002; sensitivity, 80%; specificity, 63%). Participants rated catheter-resistance monitoring as highly acceptable. Conclusions In this pediatric hematology and oncology population, catheter-resistance monitoring is feasible, acceptable, and predicts imminent catheter occlusion. Larger studies are required to validate

  20. Improving Multi-Sensor Drought Monitoring, Prediction and Recovery Assessment Using Gravimetry Information

    NASA Astrophysics Data System (ADS)

    Aghakouchak, Amir; Tourian, Mohammad J.

    2015-04-01

    Development of reliable drought monitoring, prediction and recovery assessment tools are fundamental to water resources management. This presentation focuses on how gravimetry information can improve drought assessment. First, we provide an overview of the Global Integrated Drought Monitoring and Prediction System (GIDMaPS) which offers near real-time drought information using remote sensing observations and model simulations. Then, we present a framework for integration of satellite gravimetry information for improving drought prediction and recovery assessment. The input data include satellite-based and model-based precipitation, soil moisture estimates and equivalent water height. Previous studies show that drought assessment based on one single indicator may not be sufficient. For this reason, GIDMaPS provides drought information based on multiple drought indicators including Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI) and the Multivariate Standardized Drought Index (MSDI) which combines SPI and SSI probabilistically. MSDI incorporates the meteorological and agricultural drought conditions and provides composite multi-index drought information for overall characterization of droughts. GIDMaPS includes a seasonal prediction component based on a statistical persistence-based approach. The prediction component of GIDMaPS provides the empirical probability of drought for different severity levels. In this presentation we present a new component in which the drought prediction information based on SPI, SSI and MSDI are conditioned on equivalent water height obtained from the Gravity Recovery and Climate Experiment (GRACE). Using a Bayesian approach, GRACE information is used to evaluate persistence of drought. Finally, the deficit equivalent water height based on GRACE is used for assessing drought recovery. In this presentation, both monitoring and prediction components of GIDMaPS will be discussed, and the results from 2014

  1. Efficacy of monitoring and empirical predictive modeling at improving public health protection at Chicago beaches

    USGS Publications Warehouse

    Nevers, Meredith B.; Whitman, Richard L.

    2011-01-01

    Efforts to improve public health protection in recreational swimming waters have focused on obtaining real-time estimates of water quality. Current monitoring techniques rely on the time-intensive culturing of fecal indicator bacteria (FIB) from water samples, but rapidly changing FIB concentrations result in management errors that lead to the public being exposed to high FIB concentrations (type II error) or beaches being closed despite acceptable water quality (type I error). Empirical predictive models may provide a rapid solution, but their effectiveness at improving health protection has not been adequately assessed. We sought to determine if emerging monitoring approaches could effectively reduce risk of illness exposure by minimizing management errors. We examined four monitoring approaches (inactive, current protocol, a single predictive model for all beaches, and individual models for each beach) with increasing refinement at 14 Chicago beaches using historical monitoring and hydrometeorological data and compared management outcomes using different standards for decision-making. Predictability (R2) of FIB concentration improved with model refinement at all beaches but one. Predictive models did not always reduce the number of management errors and therefore the overall illness burden. Use of a Chicago-specific single-sample standard-rather than the default 235 E. coli CFU/100 ml widely used-together with predictive modeling resulted in the greatest number of open beach days without any increase in public health risk. These results emphasize that emerging monitoring approaches such as empirical models are not equally applicable at all beaches, and combining monitoring approaches may expand beach access.

  2. Drought: A comprehensive R package for drought monitoring, prediction and analysis

    NASA Astrophysics Data System (ADS)

    Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.; Cheng, Hongguang

    2015-04-01

    Drought may impose serious challenges to human societies and ecosystems. Due to complicated causing effects and wide impacts, a universally accepted definition of drought does not exist. The drought indicator is commonly used to characterize drought properties such as duration or severity. Various drought indicators have been developed in the past few decades for the monitoring of a certain aspect of drought condition along with the development of multivariate drought indices for drought characterizations from multiple sources or hydro-climatic variables. Reliable drought prediction with suitable drought indicators is critical to the drought preparedness plan to reduce potential drought impacts. In addition, drought analysis to quantify the risk of drought properties would provide useful information for operation drought managements. The drought monitoring, prediction and risk analysis are important components in drought modeling and assessments. In this study, a comprehensive R package "drought" is developed to aid the drought monitoring, prediction and risk analysis (available from R-Forge and CRAN soon). The computation of a suite of univariate and multivariate drought indices that integrate drought information from various sources such as precipitation, temperature, soil moisture, and runoff is available in the drought monitoring component in the package. The drought prediction/forecasting component consists of statistical drought predictions to enhance the drought early warning for decision makings. Analysis of drought properties such as duration and severity is also provided in this package for drought risk assessments. Based on this package, a drought monitoring and prediction/forecasting system is under development as a decision supporting tool. The package will be provided freely to the public to aid the drought modeling and assessment for researchers and practitioners.

  3. MINErosion 3: A user friendly hillslope model for predicting erosion from steep post-mining landscapes in Central Queensland, Australia.

    NASA Astrophysics Data System (ADS)

    So, Hwat-Bing; Khalifa, Ashraf; Carroll, Chris; Yu, Bofu

    2010-05-01

    Open-cut coal mining in Central Queensland involves the breaking up of overburden that overlies the coal seams using explosives, followed by removal with draglines which results in the formation of extensive overburden spoil-piles with steep slopes at the angle of repose (approximately 75 % or 37o). These spoil-piles are found in long multiple rows, with heights of up to 60 or 70 m above the original landscapes. They are generally highly saline and dispersive and hence highly erosive. Legislation requires that these spoil-piles be rehabilitated into a stable self sustaining ecosystem with no off-site pollution. The first stage in the rehabilitation of these landscapes is the lowering of slopes to create a landscape that is stable against geotechnical failure and erosion. This is followed by revegetation generally with grasses as pioneer vegetation to further reduce erosion and a mixture of native shrubs and trees. Minimizing erosion and excessive on-site discharges of sediment into the working areas may result in the temporary cessation of mining operation with significant financial consequences, while off site discharges may breach the mining lease conditions. The average cost of rehabilitation is around 22,000 per ha. With more than 50,000 ha of such spoil-piles in Queensland at present, the total cost of rehabilitation facing the industry is very high. Most of this comprised the cost of reshaping the landscape, largely associated with the amount of material movement necessary to achieve the desired landscape. Since soil and spoil-piles vary greatly in their erodibilities, a reliable and accurate method is required to determine a cost effective combination of slope length, slope gradient and vegetation that will result in acceptable rates of erosion. A user friendly hillslope computer package MINErosion 3, was developed to predict potential erosion to select suitable combinations of landscape design parameters (slope gradient, slope length and vegetation cover

  4. Improving flood prediction by the assimilation of satellite soil moisture in poorly monitored catchments

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Flood prediction in poorly monitored catchments is among the greatest challenges faced by hydrologists. To address this challenge, an increasing number of studies in the last decade have explored methods to integrate various existing observations from ground and satellites. One approach in particula...

  5. Predicting Kindergarteners' Response to Early Reading Intervention: An Examination of Progress-Monitoring Measures

    ERIC Educational Resources Information Center

    Oslund, Eric L.; Hagan-Burke, Shanna; Taylor, Aaron B.; Simmons, Deborah C.; Simmons, Leslie; Kwok, Oi-Man; Johnson, Caitlin; Coyne, Michael D.

    2012-01-01

    This study examined the predictive validity of combinations of progress-monitoring measures: (a) curriculum-embedded phonemic awareness and alphabetic/decoding measures, and (b) Dynamic Indicators of Basic Early Literacy Skills (DIBELS; Good & Kaminski, 2002) nonsense word fluency and phoneme segmentation fluency on reading outcomes of…

  6. Predicting High Risk Adolescents' Substance Use over Time: The Role of Parental Monitoring

    ERIC Educational Resources Information Center

    Clark, Heddy Kovach; Shamblen, Stephen R.; Ringwalt, Chris L.; Hanley, Sean

    2012-01-01

    We examined whether parental monitoring at baseline predicted subsequent substance use in a high-risk youth population. Students in 14 alternative high schools in Washington State completed self-report surveys at three time points over the course of 2 years. Primary analyses included 1,423 students aged 14-20 who lived with at least one parent or…

  7. Development of a catchment/landscape erosion prediction model (MINErosion 4) for post-mining landscapes in Central Queensland, Australia.

    NASA Astrophysics Data System (ADS)

    Khalifa, Ashraf; Yu, Bofu; Ghadiri, Hossain; Carroll, Chris; So, Hwat-Bing

    2010-05-01

    industry further require a tool that enables them to predict and manage the impact of on-site and offsite discharges from storm events and to identify the areas of high erosion risk. Work is in progress to develop a user friendly package MINErosion 4 by combining the hillslope model MINErosion 3 with ARC-GIS 9, which allows the prediction of sediment losses and deposition from proposed post-mining landscapes (designed based on criteria derived from MINErosion3) subjected to rainstorms with known recurrence intervals for selected locations. An option is provided to derive mean annual soil loss from these catchments and landscapes. Soil samples were collected from various locations on 6 minesites to provide a measure of variability in erodibilities across a minesite. The model was validated against 9 years of catchment data collected from previous projects and the agreement between predicted (Y) and measured (X) soil losses are good with regression equations of Y = 0.919 X (R2 = 0.81) for individual rainstorms, and Y= 1.473 X (R2 = 0.726) for average annual soil loss.

  8. Research Progress of Farmland Drought Monitoring and Prediction Based on Multi-Source Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Yang, Guijun; Yang, Hao; Jin, Xiuliang; Pignatti, Stefano; Casa, Raffaele; Pascucci, Simone; Silvesrtro, Paolo Cosmo

    2014-11-01

    Since the Kick-off of the Dragon-3 project Farmland Drought Monitoring and Prediction Based on Multi-source Remote Sensing Data (ID: 10448), our research focuses on three points including 1) the monitoring of key biophysical variables of crop and soil in farmland drought by optical and radar remote sensing data, 2) the risk assessment of farmland drought by time series remote sensing and meteorological data, and 3) the crop loss evaluation under farmland drought mainly based on AquaCrop crop model. Our study area is mainly located in Beijing, and Shaanxi Province (semi-arid region), China. Experiment campaign and data analysis were carried out and some new methods aiming at farmland drought monitoring and prediction were developed, which highlighting the importance of ESA-NRSCC Dragon cooperation.

  9. Predictive based monitoring of nuclear plant component degradation using support vector regression

    SciTech Connect

    Agarwal, Vivek; Alamaniotis, Miltiadis; Tsoukalas, Lefteri H.

    2015-02-01

    Nuclear power plants (NPPs) are large installations comprised of many active and passive assets. Degradation monitoring of all these assets is expensive (labor cost) and highly demanding task. In this paper a framework based on Support Vector Regression (SVR) for online surveillance of critical parameter degradation of NPP components is proposed. In this case, on time replacement or maintenance of components will prevent potential plant malfunctions, and reduce the overall operational cost. In the current work, we apply SVR equipped with a Gaussian kernel function to monitor components. Monitoring includes the one-step-ahead prediction of the component’s respective operational quantity using the SVR model, while the SVR model is trained using a set of previous recorded degradation histories of similar components. Predictive capability of the model is evaluated upon arrival of a sensor measurement, which is compared to the component failure threshold. A maintenance decision is based on a fuzzy inference system that utilizes three parameters: (i) prediction evaluation in the previous steps, (ii) predicted value of the current step, (iii) and difference of current predicted value with components failure thresholds. The proposed framework will be tested on turbine blade degradation data.

  10. Application of the Artificial Neural Network model for prediction of monthly Standardized Precipitation and Evapotranspiration Index using hydrometeorological parameters and climate indices in eastern Australia

    NASA Astrophysics Data System (ADS)

    Deo, Ravinesh C.; Şahin, Mehmet

    2015-07-01

    The forecasting of drought based on cumulative influence of rainfall, temperature and evaporation is greatly beneficial for mitigating adverse consequences on water-sensitive sectors such as agriculture, ecosystems, wildlife, tourism, recreation, crop health and hydrologic engineering. Predictive models of drought indices help in assessing water scarcity situations, drought identification and severity characterization. In this paper, we tested the feasibility of the Artificial Neural Network (ANN) as a data-driven model for predicting the monthly Standardized Precipitation and Evapotranspiration Index (SPEI) for eight candidate stations in eastern Australia using predictive variable data from 1915 to 2005 (training) and simulated data for the period 2006-2012. The predictive variables were: monthly rainfall totals, mean temperature, minimum temperature, maximum temperature and evapotranspiration, which were supplemented by large-scale climate indices (Southern Oscillation Index, Pacific Decadal Oscillation, Southern Annular Mode and Indian Ocean Dipole) and the Sea Surface Temperatures (Nino 3.0, 3.4 and 4.0). A total of 30 ANN models were developed with 3-layer ANN networks. To determine the best combination of learning algorithms, hidden transfer and output functions of the optimum model, the Levenberg-Marquardt and Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton backpropagation algorithms were utilized to train the network, tangent and logarithmic sigmoid equations used as the activation functions and the linear, logarithmic and tangent sigmoid equations used as the output function. The best ANN architecture had 18 input neurons, 43 hidden neurons and 1 output neuron, trained using the Levenberg-Marquardt learning algorithm using tangent sigmoid equation as the activation and output functions. An evaluation of the model performance based on statistical rules yielded time-averaged Coefficient of Determination, Root Mean Squared Error and the Mean Absolute

  11. A Study Protocol for the Australasian Oncofertility Registry: Monitoring Referral Patterns and the Uptake, Quality, and Complications of Fertility Preservation Strategies in Australia and New Zealand.

    PubMed

    Anazodo, Antoinette C; Stern, Catharyn J; McLachlan, Robert I; Gerstl, Brigitte; Agresta, Franca; Cohn, Richard J; Jayasinghe, Yasmin; Wakefield, Claire E; Daly, Genevieve; Chan, Daisy; Gilbert, Lorrae; Kemertzis, Matthew; Orme, Lisa M; Wand, Handan; Viney, Rosalie; Gillam, Lynn; Deans, Rebecca; Jetti, Murali; Wu, John; Chapman, Michael; Ledger, William; Sullivan, Elizabeth A

    2016-09-01

    Improvements in cancer diagnosis and treatment in patients of a reproductive age have led to significant improvements in survival rates; however, a patient's fertility can be affected by both cancer and its treatment. As survival rates improve, there is an expectation by clinicians and patients that patient's reproductive potential should be considered and protected as much as possible. However, there is a lack of data about current fertility preservation (FP) uptake as well as accurate data on the acute or permanent reproductive risks of cancer treatment, complications of FP in cancer patients, and the use and success of assisted reproductive technology by cancer survivors. FP remains a major gap in acute cancer management with lifelong implications for cancer survivors. The FUTuRE Fertility research team has established the first binational multisite Australasian Oncofertility Registry, which is collecting a complete oncofertility data set from cancer and fertility centers in Australia and New Zealand. Outcomes from the research study will monitor referral, uptake, and complications of FP, document patient's reproductive potential after treatment, and collect data on the use of assisted reproductive technology following cancer treatment. The data will be linked to other routine health and administrative data sets to allow for other research projects to be carried out. The changes in oncofertility care will be benchmarked against the Australasian Oncofertility Charter. The data will be used to develop evidence-based guidelines and resources, including development of accurate risk projections for patients' risk of infertility, allowing clinicians to make recommendations for FP or assisted reproductive technology. Australian New Zealand Clinical Trials Number-12615000221550. PMID:26981848

  12. Computational studies of a strain-based deformation shape prediction algorithm for control and monitoring applications

    NASA Astrophysics Data System (ADS)

    Derkevorkian, Armen; Alvarenga, Jessica; Masri, Sami F.; Boussalis, Helen; Richards, W. Lance

    2012-04-01

    A modal approach is investigated for real-time deformation shape prediction of lightweight unmanned flying aerospace structures, for the purposes of Structural Health Monitoring (SHM) and condition assessment. The deformation prediction algorithm depends on the modal properties of the structure and uses high-resolution fiber-optic sensors to obtain strain data from a representative aerospace structure (e.g., flying wing) in order to predict the associated real-time deflection shape. The method is based on the use of fiber-optic sensors such as optical Fiber Bragg Gratings (FBGs) which are known for their accuracy and light weight. In this study, the modal method is examined through computational models involving Finite-Element Analysis (FEA). Furthermore, sensitivity analyses are performed to investigate the effects of several external factors such as sensor locations and noise pollution on the performance of the algorithm. This work analyzes the numerous complications and difficulties that might potentially arise from combining the state-of-the-art advancements in sensing technology, deformation shape prediction, and structural health monitoring, to achieve a robust way of monitoring ultra lightweight flying wings or next-generation commercial airplanes.

  13. Quantifying the prediction accuracy of a 1-D SVAT model at a range of ecosystems in the USA and Australia: evidence towards its use as a tool to study Earth's system interactions

    NASA Astrophysics Data System (ADS)

    Petropoulos, G. P.; North, M. R.; Ireland, G.; Srivastava, P. K.; Rendall, D. V.

    2015-10-01

    This paper describes the validation of the SimSphere SVAT (Soil-Vegetation-Atmosphere Transfer) model conducted at a range of US and Australian ecosystem types. Specific focus was given to examining the models' ability in predicting shortwave incoming solar radiation (Rg), net radiation (Rnet), latent heat (LE), sensible heat (H), air temperature at 1.3 m (Tair 1.3 m) and air temperature at 50 m (Tair 50 m). Model predictions were compared against corresponding in situ measurements acquired for a total of 72 selected days of the year 2011 obtained from eight sites belonging to the AmeriFlux (USA) and OzFlux (Australia) monitoring networks. Selected sites were representative of a variety of environmental, biome and climatic conditions, to allow for the inclusion of contrasting conditions in the model evaluation. Overall, results showed a good agreement between the model predictions and the in situ measurements, particularly so for the Rg, Rnet, Tair 1.3 m and Tair 50 m parameters. The simulated Rg parameter exhibited a root mean square deviation (RMSD) within 25 % of the observed fluxes for 58 of the 72 selected days, whereas an RMSD within ~ 24 % of the observed fluxes was reported for the Rnet parameter for all days of study (RMSD = 58.69 W m-2). A systematic underestimation of Rg and Rnet (mean bias error (MBE) = -19.48 and -16.46 W m-2) was also found. Simulations for the Tair 1.3 m and Tair 50 m showed good agreement with the in situ observations, exhibiting RMSDs of 3.23 and 3.77 °C (within ~ 15 and ~ 18 % of the observed) for all days of analysis, respectively. Comparable, yet slightly less satisfactory simulation accuracies were exhibited for the H and LE parameters (RMSDs = 38.47 and 55.06 W m-2, ~ 34 and ~ 28 % of the observed). Highest simulation accuracies were obtained for the open woodland savannah and mulga woodland sites for most of the compared parameters. The Nash-Sutcliffe efficiency index for all parameters ranges from 0.720 to 0.998, suggesting

  14. Evaluation of the predicted error of the soil moisture retrieval from C-band SAR by comparison against modelled soil moisture estimates over Australia.

    PubMed

    Doubková, Marcela; Van Dijk, Albert I J M; Sabel, Daniel; Wagner, Wolfgang; Blöschl, Günter

    2012-05-15

    The Sentinel-1 will carry onboard a C-band radar instrument that will map the European continent once every four days and the global land surface at least once every twelve days with finest 5 × 20 m spatial resolution. The high temporal sampling rate and operational configuration make Sentinel-1 of interest for operational soil moisture monitoring. Currently, updated soil moisture data are made available at 1 km spatial resolution as a demonstration service using Global Mode (GM) measurements from the Advanced Synthetic Aperture Radar (ASAR) onboard ENVISAT. The service demonstrates the potential of the C-band observations to monitor variations in soil moisture. Importantly, a retrieval error estimate is also available; these are needed to assimilate observations into models. The retrieval error is estimated by propagating sensor errors through the retrieval model. In this work, the existing ASAR GM retrieval error product is evaluated using independent top soil moisture estimates produced by the grid-based landscape hydrological model (AWRA-L) developed within the Australian Water Resources Assessment system (AWRA). The ASAR GM retrieval error estimate, an assumed prior AWRA-L error estimate and the variance in the respective datasets were used to spatially predict the root mean square error (RMSE) and the Pearson's correlation coefficient R between the two datasets. These were compared with the RMSE calculated directly from the two datasets. The predicted and computed RMSE showed a very high level of agreement in spatial patterns as well as good quantitative agreement; the RMSE was predicted within accuracy of 4% of saturated soil moisture over 89% of the Australian land mass. Predicted and calculated R maps corresponded within accuracy of 10% over 61% of the continent. The strong correspondence between the predicted and calculated RMSE and R builds confidence in the retrieval error model and derived ASAR GM error estimates. The ASAR GM and Sentinel-1 have

  15. Evaluation of the predicted error of the soil moisture retrieval from C-band SAR by comparison against modelled soil moisture estimates over Australia

    PubMed Central

    Doubková, Marcela; Van Dijk, Albert I.J.M.; Sabel, Daniel; Wagner, Wolfgang; Blöschl, Günter

    2012-01-01

    The Sentinel-1 will carry onboard a C-band radar instrument that will map the European continent once every four days and the global land surface at least once every twelve days with finest 5 × 20 m spatial resolution. The high temporal sampling rate and operational configuration make Sentinel-1 of interest for operational soil moisture monitoring. Currently, updated soil moisture data are made available at 1 km spatial resolution as a demonstration service using Global Mode (GM) measurements from the Advanced Synthetic Aperture Radar (ASAR) onboard ENVISAT. The service demonstrates the potential of the C-band observations to monitor variations in soil moisture. Importantly, a retrieval error estimate is also available; these are needed to assimilate observations into models. The retrieval error is estimated by propagating sensor errors through the retrieval model. In this work, the existing ASAR GM retrieval error product is evaluated using independent top soil moisture estimates produced by the grid-based landscape hydrological model (AWRA-L) developed within the Australian Water Resources Assessment system (AWRA). The ASAR GM retrieval error estimate, an assumed prior AWRA-L error estimate and the variance in the respective datasets were used to spatially predict the root mean square error (RMSE) and the Pearson's correlation coefficient R between the two datasets. These were compared with the RMSE calculated directly from the two datasets. The predicted and computed RMSE showed a very high level of agreement in spatial patterns as well as good quantitative agreement; the RMSE was predicted within accuracy of 4% of saturated soil moisture over 89% of the Australian land mass. Predicted and calculated R maps corresponded within accuracy of 10% over 61% of the continent. The strong correspondence between the predicted and calculated RMSE and R builds confidence in the retrieval error model and derived ASAR GM error estimates. The ASAR GM and Sentinel-1 have

  16. Southern Australia

    NASA Technical Reports Server (NTRS)

    2002-01-01

    South-central Australia is home to several deserts, including the Simpson Desert, whose reddish-orange sands are seen in the upper left quadrant of this Moderate Resolution Imaging Spectroradiometer (MODIS) image from July 1, 2002. Several impermanent, salty, lakes stand whitely out against the arid terrain. The largest is North Lake Eyre, southwest of center. At bottom center, Spencer Gulf separates the triangular Eyre Peninsula from the Yorke Peninsula. The Gulf of St. Vincent separates Yorke Peninsula from the mainland. In Spencer Gulf, colorful blue-green swirls indicate the presence of a bloom of marine plants called phytoplankton, whose brightly colored photosynthetic pigments stain the water. Water quality in the Gulf is an ongoing problem for Australia, as irrigation projects have diverted the already small flow of freshwater that empties into the Gulf. Other problems include contamination with pesticides and agricultural and residential fertilizer. On both the Eyre Peninsula and in the Victoria Territory to the east of Spencer Gulf, dark-colored rectangles show the boundaries of parks and nature preserves where the natural, drought-tolerant vegetation thrives.

  17. Integrating monitor alarms with laboratory test results to enhance patient deterioration prediction.

    PubMed

    Bai, Yong; Do, Duc H; Harris, Patricia Rae Eileen; Schindler, Daniel; Boyle, Noel G; Drew, Barbara J; Hu, Xiao

    2015-02-01

    Patient monitors in modern hospitals have become ubiquitous but they generate an excessive number of false alarms causing alarm fatigue. Our previous work showed that combinations of frequently co-occurring monitor alarms, called SuperAlarm patterns, were capable of predicting in-hospital code blue events at a lower alarm frequency. In the present study, we extend the conceptual domain of a SuperAlarm to incorporate laboratory test results along with monitor alarms so as to build an integrated data set to mine SuperAlarm patterns. We propose two approaches to integrate monitor alarms with laboratory test results and use a maximal frequent itemsets mining algorithm to find SuperAlarm patterns. Under an acceptable false positive rate FPRmax, optimal parameters including the minimum support threshold and the length of time window for the algorithm to find the combinations of monitor alarms and laboratory test results are determined based on a 10-fold cross-validation set. SuperAlarm candidates are generated under these optimal parameters. The final SuperAlarm patterns are obtained by further removing the candidates with false positive rate>FPRmax. The performance of SuperAlarm patterns are assessed using an independent test data set. First, we calculate the sensitivity with respect to prediction window and the sensitivity with respect to lead time. Second, we calculate the false SuperAlarm ratio (ratio of the hourly number of SuperAlarm triggers for control patients to that of the monitor alarms, or that of regular monitor alarms plus laboratory test results if the SuperAlarm patterns contain laboratory test results) and the work-up to detection ratio, WDR (ratio of the number of patients triggering any SuperAlarm patterns to that of code blue patients triggering any SuperAlarm patterns). The experiment results demonstrate that when varying FPRmax between 0.02 and 0.15, the SuperAlarm patterns composed of monitor alarms along with the last two laboratory test results

  18. Considerations on the Use of 3-D Geophysical Models to Predict Test Ban Monitoring Observables

    SciTech Connect

    Harris, D B; Zucca, J J; McCallen, D B; Pasyanos, M E; Flanagan, M P; Myers, S C; Walter, W R; Rodgers, A J; Harben, P E

    2007-07-09

    The use of 3-D geophysical models to predict nuclear test ban monitoring observables (phase travel times, amplitudes, dispersion, etc.) is widely anticipated to provide improvements in the basic seismic monitoring functions of detection, association, location, discrimination and yield estimation. A number of questions arise when contemplating a transition from 1-D, 2-D and 2.5-D models to constructing and using 3-D models, among them: (1) Can a 3-D geophysical model or a collection of 3-D models provide measurably improved predictions of seismic monitoring observables over existing 1-D models, or 2-D and 2 1/2-D models currently under development? (2) Is a single model that can predict all observables achievable, or must separate models be devised for each observable? How should joint inversion of disparate observable data be performed, if required? (3) What are the options for model representation? Are multi-resolution models essential? How does representation affect the accuracy and speed of observable predictions? (4) How should model uncertainty be estimated, represented and how should it be used? Are stochastic models desirable? (5) What data types should be used to construct the models? What quality control regime should be established? (6) How will 3-D models be used in operations? Will significant improvements in the basic monitoring functions result from the use of 3-D models? Will the calculation of observables through 3-D models be fast enough for real-time use or must a strategy of pre-computation be employed? (7) What are the theoretical limits to 3-D model development (resolution, uncertainty) and performance in predicting monitoring observables? How closely can those limits be approached with projected data availability, station distribution and inverse methods? (8) What priorities should be placed on the acquisition of event ground truth information, deployment of new stations, development of new inverse techniques, exploitation of large

  19. Optimization of monitoring networks based on uncertainty quantification of model predictions of contaminant transport

    NASA Astrophysics Data System (ADS)

    Vesselinov, V. V.; Harp, D.

    2010-12-01

    The process of decision making to protect groundwater resources requires a detailed estimation of uncertainties in model predictions. Various uncertainties associated with modeling a natural system, such as: (1) measurement and computational errors; (2) uncertainties in the conceptual model and model-parameter estimates; (3) simplifications in model setup and numerical representation of governing processes, contribute to the uncertainties in the model predictions. Due to this combination of factors, the sources of predictive uncertainties are generally difficult to quantify individually. Decision support related to optimal design of monitoring networks requires (1) detailed analyses of existing uncertainties related to model predictions of groundwater flow and contaminant transport, (2) optimization of the proposed monitoring network locations in terms of their efficiency to detect contaminants and provide early warning. We apply existing and newly-proposed methods to quantify predictive uncertainties and to optimize well locations. An important aspect of the analysis is the application of newly-developed optimization technique based on coupling of Particle Swarm and Levenberg-Marquardt optimization methods which proved to be robust and computationally efficient. These techniques and algorithms are bundled in a software package called MADS. MADS (Model Analyses for Decision Support) is an object-oriented code that is capable of performing various types of model analyses and supporting model-based decision making. The code can be executed under different computational modes, which include (1) sensitivity analyses (global and local), (2) Monte Carlo analysis, (3) model calibration, (4) parameter estimation, (5) uncertainty quantification, and (6) model selection. The code can be externally coupled with any existing model simulator through integrated modules that read/write input and output files using a set of template and instruction files (consistent with the PEST

  20. Interactions of team mental models and monitoring behaviors predict team performance in simulated anesthesia inductions.

    PubMed

    Burtscher, Michael J; Kolbe, Michaela; Wacker, Johannes; Manser, Tanja

    2011-09-01

    In the present study, we investigated how two team mental model properties (similarity vs. accuracy) and two forms of monitoring behavior (team vs. systems) interacted to predict team performance in anesthesia. In particular, we were interested in whether the relationship between monitoring behavior and team performance was moderated by team mental model properties. Thirty-one two-person teams consisting of anesthesia resident and anesthesia nurse were videotaped during a simulated anesthesia induction of general anesthesia. Team mental models were assessed with a newly developed measurement tool based on the concept-mapping technique. Monitoring behavior was coded by two organizational psychologists using a structured observation system. Team performance was rated by two expert anesthetists using a performance-checklist. Moderated multiple regression analysis revealed that team mental model similarity moderated the relationship between team monitoring and performance; a higher level of team monitoring in the absence of a similar team mental model had a negative effect on performance. Furthermore, team mental model similarity and accuracy interacted to predict team performance. Our findings provide new insights on factors influencing the relationship between team processes and team performance in health care. When investigating the effectiveness of a specific team coordination behavior, team cognition has to be taken into account. This represents a necessary and compelling extension of the popular process-outcome relationship on which previous teamwork research in health care has focused. Moreover, the current study adds further external validity to the concept of team mental models by highlighting its usefulness in health care. PMID:21942315

  1. Absent otoacoustic emissions predict otitis media in young Aboriginal children: A birth cohort study in Aboriginal and non-Aboriginal children in an arid zone of Western Australia

    PubMed Central

    Lehmann, Deborah; Weeks, Sharon; Jacoby, Peter; Elsbury, Dimity; Finucane, Janine; Stokes, Annette; Monck, Ruth; Coates, Harvey

    2008-01-01

    Background Otitis media (OM) is the most common paediatric illness for which antibiotics are prescribed. In Australian Aboriginal children OM is frequently asymptomatic and starts at a younger age, is more common and more likely to result in hearing loss than in non-Aboriginal children. Absent transient evoked otoacoustic emissions (TEOAEs) may predict subsequent risk of OM. Methods 100 Aboriginal and 180 non-Aboriginal children in a semi-arid zone of Western Australia were followed regularly from birth to age 2 years. Tympanometry was conducted at routine field follow-up from age 3 months. Routine clinical examination by an ENT specialist was to be done 3 times and hearing assessment by an audiologist twice. TEOAEs were measured at ages <1 and 1–2 months. Cox proportional hazards model was used to investigate the association between absent TEOAEs and subsequent risk of OM. Results At routine ENT specialist clinics, OM was detected in 55% of 184 examinations in Aboriginal children and 26% of 392 examinations in non-Aboriginal children; peak prevalence was 72% at age 5–9 months in Aboriginal children and 40% at 10–14 months in non-Aboriginal children. Moderate-severe hearing loss was present in 32% of 47 Aboriginal children and 7% of 120 non-Aboriginal children aged 12 months or more. TEOAE responses were present in 90% (46/51) of Aboriginal children and 99% (120/121) of non-Aboriginal children aged <1 month and in 62% (21/34) and 93% (108/116), respectively, in Aboriginal and non-Aboriginal children at age 1–2 months. Aboriginal children who failed TEOAE at age 1–2 months were 2.6 times more likely to develop OM subsequently than those who passed. Overall prevalence of type B tympanograms at field follow-up was 50% (n = 78) in Aboriginal children and 20% (n = 95) in non-Aboriginal children. Conclusion The burden of middle ear disease is high in all children, but particularly in Aboriginal children, one-third of whom suffer from moderate-severe hearing

  2. Accuracy of continuous noninvasive hemoglobin monitoring for the prediction of blood transfusions in trauma patients.

    PubMed

    Galvagno, Samuel M; Hu, Peter; Yang, Shiming; Gao, Cheng; Hanna, David; Shackelford, Stacy; Mackenzie, Colin

    2015-12-01

    Early detection of hemorrhagic shock is required to facilitate prompt coordination of blood component therapy delivery to the bedside and to expedite performance of lifesaving interventions. Standard physical findings and vital signs are difficult to measure during the acute resuscitation stage, and these measures are often inaccurate until patients deteriorate to a state of decompensated shock. The aim of this study is to examine a severely injured trauma patient population to determine whether a noninvasive SpHb monitor can predict the need for urgent blood transfusion (universal donor or additional urgent blood transfusion) during the first 12 h of trauma patient resuscitation. We hypothesize that trends in continuous SpHb, combined with easily derived patient-specific factors, can identify the immediate need for transfusion in trauma patients. Subjects were enrolled if directly admitted to the trauma center, >17 years of age, and with a shock index (heart rate/systolic blood pressure) >0.62. Upon admission, a Masimo Radical-7 co-oximeter sensor (Masimo Corporation, Irvine, CA) was applied, providing measurement of continuous non-invasive hemoglobin (SpHb) levels. Blood was drawn and hemoglobin concentration analyzed and conventional pulse oximetry photopletysmograph signals were continuously recorded. Demographic information and both prehospital and admission vital signs were collected. The primary outcome was transfusion of at least one unit of packed red blood cells within 24 h of admission. Eight regression models (C1-C8) were evaluated for the prediction of blood use by comparing area under receiver operating curve (AUROC) at different time intervals after admission. 711 subjects had continuous vital signs waveforms available, to include heart rate (HR), SpHb and SpO2 trends. When SpHb was monitored for 15 min, SpHb did not increase AUROC for prediction of transfusion. The highest ROC was recorded for model C8 (age, sex, prehospital shock index, admission

  3. Becoming a Woman Teacher: Memories of Learning to Be a Monitor in Western Australia in the 1920s and 1930s

    ERIC Educational Resources Information Center

    Trotman, Janina; O'Donoghue, Tom

    2010-01-01

    Oral testimonies generated in a research project involving a group of women graduates of Western Australia's state teachers' college indicate that contradictions existed between competing discourses of femininity and teaching in the State in the early decades of the twentieth century, and that these opened up new possibilities for women teachers.…

  4. NOAA Drought Task Force: A Coordinated Research Initiative to Advance Drought Understanding, Monitoring and Prediction

    NASA Astrophysics Data System (ADS)

    Mariotti, A.; Barrie, D.

    2014-12-01

    The NOAA's Drought Task Force was first established in October 2011 and renewed in October 2014 with the goal of achieving significant new advances in the ability to understand, monitor and predict drought over North America. The Task Force is an initiative of NOAA's Climate Program Office Modeling, Analysis, Predictions, and Projections (MAPP) program in support of the National Integrated Drought Information System NIDIS. The Drought Task Force also represents an important research contribution to efforts to develop an international Global Drought Information System (GDIS). The Drought Task Force brings together leading drought scientists research laboratories and/or operational centers from NOAA, other U.S. agencies laboratories and academia. Their concerted research effort builds on individual MAPP research projects and related drought-research sector developments. The projects span the wide spectrum of drought research needed to make fundamental advances, from those aimed at the basic understanding of drought mechanisms to those evaluating new drought monitoring and prediction tools for operational and service purposes. This contribution will present an overview of Drought Task Force activities and plans to date, including highlights of research activities and how the group has been working in partnership with NIDIS and synergy with GDIS to advance the science underpinning the development, assessment and provision of drought information.

  5. Advancing the understanding, monitoring and prediction of North American drought in support of NIDIS

    NASA Astrophysics Data System (ADS)

    Mariotti, Annarita; Pulwarty, Roger

    2014-05-01

    The NOAA's Drought Task Force was established in October 2011 with the goal of achieving significant new advances in the ability to understand, monitor and predict drought over North America. The Task Force is an initiative of NOAA's Climate Program Office Modeling, Analysis, Predictions, and Projections (MAPP) program in support of the National Integrated Drought Information System NIDIS. It brings together over thirty-five leading drought scientists research laboratories and/or operational centers from NOAA, other U.S. agencies laboratories and academia. Their concerted research effort builds on individual MAPP research projects and related drought-research sector developments. The projects span the wide spectrum of drought research needed to make fundamental advances, from those aimed at the basic understanding of drought mechanisms to those evaluating new drought monitoring and prediction tools for operational and service purposes. In this presentation we will show how a coordinated, sustained multidisciplinary effort to assess understanding of both past droughts and emergent events contributes to the effectiveness of early warning systems. This contribution will present an overview of Drought Task Force activities to date, including highlights of research activities and how the group has been working in partnership with NIDIS to advance the science underpinning the development, assessment and provision of drought information.

  6. Real-Time Safety Monitoring and Prediction for the National Airspace System

    NASA Technical Reports Server (NTRS)

    Roychoudhury, Indranil

    2016-01-01

    As new operational paradigms and additional aircraft are being introduced into the National Airspace System (NAS), maintaining safety in such a rapidly growing environment becomes more challenging. It is therefore desirable to have both an overview of the current safety of the airspace at different levels of granularity, as well an understanding of how the state of the safety will evolve into the future given the anticipated flight plans, weather forecasts, predicted health of assets in the airspace, and so on. To this end, we have developed a Real-Time Safety Monitoring (RTSM) that first, estimates the state of the NAS using the dynamic models. Then, given the state estimate and a probability distribution of future inputs to the NAS, the framework predicts the evolution of the NAS, i.e., the future state, and analyzes these future states to predict the occurrence of unsafe events. The entire probability distribution of airspace safety metrics is computed, not just point estimates, without significant assumptions regarding the distribution type and or parameters. We demonstrate our overall approach by predicting the occurrence of some unsafe events and show how these predictions evolve in time as flight operations progress.

  7. Comparison of tunnel ventilation emissions monitoring data against predicted modeling results

    SciTech Connect

    Kasprak, A.; Schattanek, G.

    1997-12-31

    On December 15, 1995, the new Ted Williams Tunnel (TWT) opened for commercial and taxi traffic between South and East Boston. This opening of the TWT constitutes the Early Opening Phase which will extend until the completion of the Central Artery/Tunnel (CA/T) Project, when the connection between the TWT, the Massachusetts Turnpike (I-90), and the Central Artery (I-93) will be completed and fully opened for general public use. The ventilation system for the TWT is a fully transverse ventilation system that is comprised of numerous supply and exhaust fans and ancillary equipment housed in two separate ventilation buildings. Emissions from vehicles are ventilated to the outside atmosphere through a series of exhaust stacks, housed on each ventilation building. During the Early Opening Phase of the TWT, a monitoring program is being conducted to determine if the emissions from each ventilation building are within the ranges of the projected emissions used in the design of the tunnel`s ventilation system. This paper presents the results of the emissions monitoring program and compares projected emissions data with the actual emissions data recorded during the monitoring program. In addition, a comparison is made regarding monitoring emissions data within the tunnel with predicted emission data using the current Mobile 5a Emission Factor Model.

  8. Research-Based Monitoring, Prediction, and Analysis Tools of the Spacecraft Charging Environment for Spacecraft Users

    NASA Technical Reports Server (NTRS)

    Zheng, Yihua; Kuznetsova, Maria M.; Pulkkinen, Antti A.; Maddox, Marlo M.; Mays, Mona Leila

    2015-01-01

    The Space Weather Research Center (http://swrc. gsfc.nasa.gov) at NASA Goddard, part of the Community Coordinated Modeling Center (http://ccmc.gsfc.nasa.gov), is committed to providing research-based forecasts and notifications to address NASA's space weather needs, in addition to its critical role in space weather education. It provides a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, tailored space weather alerts and products, and weekly summaries and reports. In this paper, we focus on how (near) real-time data (both in space and on ground), in combination with modeling capabilities and an innovative dissemination system called the integrated Space Weather Analysis system (http://iswa.gsfc.nasa.gov), enable monitoring, analyzing, and predicting the spacecraft charging environment for spacecraft users. Relevant tools and resources are discussed.

  9. Sydney, Australia

    NASA Technical Reports Server (NTRS)

    2002-01-01

    This image was acquired on October 12, 2002 by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA's Terra satellite. With its 14 spectral bands from the visible to the thermal infrared wavelength region, and its high spatial resolution of 15 to 90 meters (about 50 to 300 feet), ASTER will image Earth for the next 6 years to map and monitor the changing surface of our planet.

    ASTER is one of five Earth-observing instruments launched December 18,1999, on NASA's Terra satellite. The instrument was built by Japan's Ministry of Economy, Trade and Industry. A joint U.S./Japan science team is responsible for validation and calibration of the instrument and the data products. Dr. Anne Kahle at NASA's Jet Propulsion Laboratory, Pasadena, California, is the U.S. Science team leader; Bjorn Eng of JPL is the project manager. ASTER is the only high resolution imaging sensor on Terra. The Terra mission is part of NASA's Earth Science Enterprise, along-term research and technology program designed to examine Earth's land, oceans, atmosphere, ice and life as a total integrated system.

    The broad spectral coverage and high spectral resolution of ASTER will provide scientists in numerous disciplines with critical information for surface mapping, and monitoring dynamic conditions and temporal change. Example applications are: monitoring glacial advances and retreats; monitoring potentially active volcanoes; identifying crop stress; determining cloud morphology and physical properties; wetlands evaluation; thermal pollution monitoring; coral reef degradation; surface temperature mapping of soils and geology; and measuring surface heat balance.

    Size: 42 x 32 km (25.1 x 19.2 miles) Location: 33.7 deg. South lat., 151.4 deg. East long. Orientation: North at top Image Data: ASTER bands 1,2, and 3. Original Data Resolution: 15 m Date Acquired: October 12, 2001

  10. Individual Differences in Fifth Graders' Literacy and Academic Language Predict Comprehension Monitoring Development: An Eye-Movement Study

    ERIC Educational Resources Information Center

    Connor, Carol McDonald; Radach, Ralph; Vorstius, Christian; Day, Stephanie L.; McLean, Leigh; Morrison, Frederick J.

    2015-01-01

    In this study, we investigated fifth graders' (n = 52) fall literacy, academic language, and motivation and how these skills predicted fall and spring comprehension monitoring on an eye movement task. Comprehension monitoring was defined as the identification and repair of misunderstandings when reading text. In the eye movement task,…

  11. Ocean currents influence the genetic structure of an intertidal mollusc in southeastern Australia – implications for predicting the movement of passive dispersers across a marine biogeographic barrier

    PubMed Central

    Miller, Adam D; Versace, Vincent L; Matthews, Ty G; Montgomery, Steven; Bowie, Kate C

    2013-01-01

    Major disjunctions among marine communities in southeastern Australia have been well documented, although explanations for biogeographic structuring remain uncertain. Converging ocean currents, environmental gradients, and habitat discontinuities have been hypothesized as likely drivers of structuring in many species, although the extent to which species are affected appears largely dependent on specific life histories and ecologies. Understanding these relationships is critical to the management of native and invasive species, and the preservation of evolutionary processes that shape biodiversity in this region. In this study we test the direct influence of ocean currents on the genetic structure of a passive disperser across a major biogeographic barrier. Donax deltoides (Veneroida: Donacidae) is an intertidal, soft-sediment mollusc and an ideal surrogate for testing this relationship, given its lack of habitat constraints in this region, and its immense dispersal potential driven by year-long spawning and long-lived planktonic larvae. We assessed allele frequencies at 10 polymorphic microsatellite loci across 11 sample locations spanning the barrier region and identified genetic structure consistent with the major ocean currents of southeastern Australia. Analysis of mitochondrial DNA sequence data indicated no evidence of genetic structuring, but signatures of a species range expansion corresponding with historical inundations of the Bassian Isthmus. Our results indicate that ocean currents are likely to be the most influential factor affecting the genetic structure of D. deltoides and a likely physical barrier for passive dispersing marine fauna generally in southeastern Australia. PMID:23762511

  12. Predictable and reliable ECG monitoring over IEEE 802.11 WLANs within a hospital.

    PubMed

    Park, Juyoung; Kang, Kyungtae

    2014-09-01

    Telecardiology provides mobility for patients who require constant electrocardiogram (ECG) monitoring. However, its safety is dependent on the predictability and robustness of data delivery, which must overcome errors in the wireless channel through which the ECG data are transmitted. We report here a framework that can be used to gauge the applicability of IEEE 802.11 wireless local area network (WLAN) technology to ECG monitoring systems in terms of delay constraints and transmission reliability. For this purpose, a medical-grade WLAN architecture achieved predictable delay through the combination of a medium access control mechanism based on the point coordination function provided by IEEE 802.11 and an error control scheme based on Reed-Solomon coding and block interleaving. The size of the jitter buffer needed was determined by this architecture to avoid service dropout caused by buffer underrun, through analysis of variations in transmission delay. Finally, we assessed this architecture in terms of service latency and reliability by modeling the transmission of uncompressed two-lead electrocardiogram data from the MIT-BIH Arrhythmia Database and highlight the applicability of this wireless technology to telecardiology. PMID:25083792

  13. Internet-based monitoring and prediction system of coal stockpile behaviors under atmospheric conditions.

    PubMed

    Yilmaz, Nihat; Ozdeniz, A Hadi

    2010-03-01

    Spontaneous combustion on industrial-scale stockpiles causes environmental problems and economic losses for the companies consuming large amounts of coal. In this study, an effective monitoring and prediction system based on internet was developed and implemented to prevent losses and environmental problems. The system was performed in a coal stockpile with 5 m width, 10 m length, 3 m height, and having 120 t of weight. The inner temperature data of the stockpile was recorded by 17 temperature sensors placed inside the stockpile at certain points. Additionally, the data relating to the air temperature, air humidity, atmospheric pressure, wind velocity, and wind direction that are the parameters affecting the coal stockpile were also recorded. The recorded values were analyzed with artificial neural network and Statistical modeling methods for prediction of spontaneous combustion. Real-time measurement values and model outputs were published with a web page on internet. The internet-based system can also provide real-time monitoring (combustion alarms, system status) and tele-controlling (Parameter adjusting, system control) through internet exclusively with a standard web browser without the need of any additional software. PMID:19238568

  14. Network of seismo-geochemical monitoring observatories for earthquake prediction research in India

    NASA Astrophysics Data System (ADS)

    Chaudhuri, Hirok; Barman, Chiranjib; Iyengar, A.; Ghose, Debasis; Sen, Prasanta; Sinha, Bikash

    2013-08-01

    Present paper deals with a brief review of the research carried out to develop multi-parametric gas-geochemical monitoring facilities dedicated to earthquake prediction research in India by installing a network of seismo-geochemical monitoring observatories at different regions of the country. In an attempt to detect earthquake precursors, the concentrations of helium, argon, nitrogen, methane, radon-222 (222Rn), polonium-218 (218Po), and polonium-214 (214Po) emanating from hydrothermal systems are monitored continuously and round the clock at these observatories. In this paper, we make a cross correlation study of a number of geochemical anomalies recorded at these observatories. With the data received from each of the above observatories we attempt to make a time series analysis to relate magnitude and epicentral distance locations through statistical methods, empirical formulations that relate the area of influence to earthquake scale. Application of the linear and nonlinear statistical techniques in the recorded geochemical data sets reveal a clear signature of long-range correlation in the data sets.

  15. Monitor units are not predictive of neutron dose for high-energy IMRT

    PubMed Central

    2012-01-01

    Background Due to the substantial increase in beam-on time of high energy intensity-modulated radiotherapy (>10 MV) techniques to deliver the same target dose compared to conventional treatment techniques, an increased dose of scatter radiation, including neutrons, is delivered to the patient. As a consequence, an increase in second malignancies may be expected in the future with the application of intensity-modulated radiotherapy. It is commonly assumed that the neutron dose equivalent scales with the number of monitor units. Methods Measurements of neutron dose equivalent were performed for an open and an intensity-modulated field at four positions: inside and outside of the treatment field at 0.2 cm and 15 cm depth, respectively. Results It was shown that the neutron dose equivalent, which a patient receives during an intensity-modulated radiotherapy treatment, does not scale with the ratio of applied monitor units relative to an open field irradiation. Outside the treatment volume at larger depth 35% less neutron dose equivalent is delivered than expected. Conclusions The predicted increase of second cancer induction rates from intensity-modulated treatment techniques can be overestimated when the neutron dose is simply scaled with monitor units. PMID:22883384

  16. Prediction of Tumor Recurrence and Therapy Monitoring Using Ultrasound-Guided Photoacoustic Imaging

    PubMed Central

    Mallidi, Srivalleesha; Watanabe, Kohei; Timerman, Dmitriy; Schoenfeld, David; Hasan, Tayyaba

    2015-01-01

    Selection and design of individualized treatments remains a key goal in cancer therapeutics; prediction of response and tumor recurrence following a given therapy provides a basis for subsequent personalized treatment design. We demonstrate an approach towards this goal with the example of photodynamic therapy (PDT) as the treatment modality and photoacoustic imaging (PAI) as a non-invasive, response and disease recurrence monitor in a murine model of glioblastoma (GBM). PDT is a photochemistry-based, clinically-used technique that consumes oxygen to generate cytotoxic species, thus causing changes in blood oxygen saturation (StO2). We hypothesize that this change in StO2 can be a surrogate marker for predicting treatment efficacy and tumor recurrence. PAI is a technique that can provide a 3D atlas of tumor StO2 by measuring oxygenated and deoxygenated hemoglobin. We demonstrate that tumors responding to PDT undergo approximately 85% change in StO2 by 24-hrs post-therapy while there is no significant change in StO2 values in the non-responding group. Furthermore, the 3D tumor StO2 maps predicted whether a tumor was likely to regrow at a later time point post-therapy. Information on the likelihood of tumor regrowth that normally would have been available only upon actual regrowth (10-30 days post treatment) in a xenograft tumor model, was available within 24-hrs of treatment using PAI, thus making early intervention a possibility. Given the advances and push towards availability of PAI in the clinical settings, the results of this study encourage applicability of PAI as an important step to guide and monitor therapies (e.g. PDT, radiation, anti-angiogenic) involving a change in StO2. PMID:25553116

  17. Great Barrier Reef, Queensland, Australia

    NASA Technical Reports Server (NTRS)

    1990-01-01

    This detailed view of the Great Barrier Reef, Queensland, Australia (19.5S, 149.5E) shows several small patch reefs within the overall reef system. The Great Barrier Reef, largest in the world, comprises thousands of individual reefs of great variety and are closely monitored by marine ecologists. These reefs are about 6000 years old and sit on top of much older reefs. The most rapid coral growth occurs on the landward side of the reefs.

  18. Enabling Technology for Monitoring & Predicting Gas Turbine Health & Performance in IGCC Powerplants

    SciTech Connect

    Kenneth A. Yackly

    2005-12-01

    The ''Enabling & Information Technology To Increase RAM for Advanced Powerplants'' program, by DOE request, was re-directed, de-scoped to two tasks, shortened to a 2-year period of performance, and refocused to develop, validate and accelerate the commercial use of enabling materials technologies and sensors for coal/IGCC powerplants. The new program was re-titled ''Enabling Technology for Monitoring & Predicting Gas Turbine Health & Performance in IGCC Powerplants''. This final report summarizes the work accomplished from March 1, 2003 to March 31, 2004 on the four original tasks, and the work accomplished from April 1, 2004 to July 30, 2005 on the two re-directed tasks. The program Tasks are summarized below: Task 1--IGCC Environmental Impact on high Temperature Materials: The first task was refocused to address IGCC environmental impacts on high temperature materials used in gas turbines. This task screened material performance and quantified the effects of high temperature erosion and corrosion of hot gas path materials in coal/IGCC applications. The materials of interest included those in current service as well as advanced, high-performance alloys and coatings. Task 2--Material In-Service Health Monitoring: The second task was reduced in scope to demonstrate new technologies to determine the inservice health of advanced technology coal/IGCC powerplants. The task focused on two critical sensing needs for advanced coal/IGCC gas turbines: (1) Fuel Quality Sensor to rapidly determine the fuel heating value for more precise control of the gas turbine, and detection of fuel impurities that could lead to rapid component degradation. (2) Infra-Red Pyrometer to continuously measure the temperature of gas turbine buckets, nozzles, and combustor hardware. Task 3--Advanced Methods for Combustion Monitoring and Control: The third task was originally to develop and validate advanced monitoring and control methods for coal/IGCC gas turbine combustion systems. This task was

  19. Performance of ANFIS versus MLP-NN dissolved oxygen prediction models in water quality monitoring.

    PubMed

    Najah, A; El-Shafie, A; Karim, O A; El-Shafie, Amr H

    2014-02-01

    We discuss the accuracy and performance of the adaptive neuro-fuzzy inference system (ANFIS) in training and prediction of dissolved oxygen (DO) concentrations. The model was used to analyze historical data generated through continuous monitoring of water quality parameters at several stations on the Johor River to predict DO concentrations. Four water quality parameters were selected for ANFIS modeling, including temperature, pH, nitrate (NO3) concentration, and ammoniacal nitrogen concentration (NH3-NL). Sensitivity analysis was performed to evaluate the effects of the input parameters. The inputs with the greatest effect were those related to oxygen content (NO3) or oxygen demand (NH3-NL). Temperature was the parameter with the least effect, whereas pH provided the lowest contribution to the proposed model. To evaluate the performance of the model, three statistical indices were used: the coefficient of determination (R (2)), the mean absolute prediction error, and the correlation coefficient. The performance of the ANFIS model was compared with an artificial neural network model. The ANFIS model was capable of providing greater accuracy, particularly in the case of extreme events. PMID:23949111

  20. Lumped Parameter Modeling as a Predictive Tool for a Battery Status Monitor

    SciTech Connect

    Jon P. Christophersen; Chester G. Motloch; Chinh D. Ho; John L. Morrison; Ronald C. Fenton; Vincent S. Battaglia; Tien Q. Duong

    2003-10-01

    The Advanced Technology Development Program is currently evaluating the performance of the second generation of lithium-ion cells (i.e., Gen 2 cells). Both the Gen 2 Baseline and Variant C cells are tested in accordance with the cell-specific test plan, and are removed at roughly equal power fade increments and sent for destructive diagnostic analysis. The diagnostic laboratories did not need all test cells for analysis, and returned five spare cells to the Idaho National Engineering and Environmental Laboratory (INEEL). INEEL used these cells for special pulse testing at various duty cycles, amplitudes, and durations to investigate the usefulness of the lumped parameter model (LPM) as a predictive tool in a battery status monitor (BSM). The LPM is a simplified linear model that accurately predicts the voltage response during certain pulse conditions. A database of parameter trends should enable dynamic predictions of state-of-charge and state-of-health conditions during in-vehicle pulsing. This information could be used by the BSM to provide accurate information to the vehicle control system.

  1. Multiscale Modeling of Advanced Materials for Damage Prediction and Structural Health Monitoring

    NASA Astrophysics Data System (ADS)

    Borkowski, Luke

    Advanced aerospace materials, including fiber reinforced polymer and ceramic matrix composites, are increasingly being used in critical and demanding applications, challenging the current damage prediction, detection, and quantification methodologies. Multiscale computational models offer key advantages over traditional analysis techniques and can provide the necessary capabilities for the development of a comprehensive virtual structural health monitoring (SHM) framework. Virtual SHM has the potential to drastically improve the design and analysis of aerospace components through coupling the complementary capabilities of models able to predict the initiation and propagation of damage under a wide range of loading and environmental scenarios, simulate interrogation methods for damage detection and quantification, and assess the health of a structure. A major component of the virtual SHM framework involves having micromechanics-based multiscale composite models that can provide the elastic, inelastic, and damage behavior of composite material systems under mechanical and thermal loading conditions and in the presence of microstructural complexity and variability. Quantification of the role geometric and architectural variability in the composite microstructure plays in the local and global composite behavior is essential to the development of appropriate scale-dependent unit cells and boundary conditions for the multiscale model. Once the composite behavior is predicted and variability effects assessed, wave-based SHM simulation models serve to provide knowledge on the probability of detection and characterization accuracy of damage present in the composite. The research presented in this dissertation provides the foundation for a comprehensive SHM framework for advanced aerospace materials. The developed models enhance the prediction of damage formation as a result of ceramic matrix composite processing, improve the understanding of the effects of architectural and

  2. An integrated Modelling framework to monitor and predict trends of agricultural management (iMSoil)

    NASA Astrophysics Data System (ADS)

    Keller, Armin; Della Peruta, Raneiro; Schaepman, Michael; Gomez, Marta; Mann, Stefan; Schulin, Rainer

    2014-05-01

    Agricultural systems lay at the interface between natural ecosystems and the anthroposphere. Various drivers induce pressures on the agricultural systems, leading to changes in farming practice. The limitation of available land and the socio-economic drivers are likely to result in further intensification of agricultural land management, with implications on fertilization practices, soil and pest management, as well as crop and livestock production. In order to steer the development into desired directions, tools are required by which the effects of these pressures on agricultural management and resulting impacts on soil functioning can be detected as early as possible, future scenarios predicted and suitable management options and policies defined. In this context, the use of integrated models can play a major role in providing long-term predictions of soil quality and assessing the sustainability of agricultural soil management. Significant progress has been made in this field over the last decades. Some of these integrated modelling frameworks include biophysical parameters, but often the inherent characteristics and detailed processes of the soil system have been very simplified. The development of such tools has been hampered in the past by a lack of spatially explicit soil and land management information at regional scale. The iMSoil project, funded by the Swiss National Science Foundation in the national research programme NRP68 "soil as a resource" (www.nrp68.ch) aims at developing and implementing an integrated modeling framework (IMF) which can overcome the limitations mentioned above, by combining socio-economic, agricultural land management, and biophysical models, in order to predict the long-term impacts of different socio-economic scenarios on the soil quality. In our presentation we briefly outline the approach that is based on an interdisciplinary modular framework that builds on already existing monitoring tools and model components that are

  3. Monitoring, mapping and prediction of ionospheric scintillation over the Brazilian equatorial and low latitude regions

    NASA Astrophysics Data System (ADS)

    Becker-Guedes, Fabio; de Paula, E. R.; de Rezende, L. F. C.; Stephany, S.; Kantor, I. J.; Muella, M. T. A. H.; Siqueira, P. M.; Correa, K. S.; Dutra, A. P.; Guedes, C.; Takahashi, H.; Silva, J. D. S.

    It is well known, today, that equatorial ionospheric scintillations affect performance of GPS receivers. Scintillation occurs when a radio wave crosses the ionosphere and suffers distortion in phase and amplitude. It also contributes to loss of lock of GPS receivers, resulting decrease of the number of available satellites and consequently yielding poor satellite geometry. Therefore, the required accuracy and positioning precision for aerial navigation are affected. Among other activities, EMBRACE, the space weather program of INPE, is monitoring and mapping the ionospheric scintillation over the South American equatorial and low latitude region in real time. This mapping is available in the internet by means of computer programs that retrieve data from a network of GPS receivers distributed in Brazil. These data are also being used to survey and predict the occurrence of ionospheric scintillation through data mining techniques.

  4. Monitoring and prediction in early warning systems for rapid mass movements

    NASA Astrophysics Data System (ADS)

    Stähli, M.; Sättele, M.; Huggel, C.; McArdell, B. W.; Lehmann, P.; Van Herwijnen, A.; Berne, A.; Schleiss, M.; Ferrari, A.; Kos, A.; Or, D.; Springman, S. M.

    2015-04-01

    Rapid mass movements (RMM) pose a substantial risk to people and infrastructure. Reliable and cost-efficient measures have to be taken to reduce this risk. One of these measures includes establishing and advancing the state of practice in the application of early warning systems (EWSs). EWSs have been developed during the past decades and are rapidly increasing. In this paper, we focus on the technical part of EWSs, i.e., the prediction and timely recognition of imminent hazards, as well as on monitoring slopes at risk and released mass movements. Recent innovations in assessing spatial precipitation, monitoring and precursors of the triggering and deformation of RMM offer new opportunities for next-generation EWSs. However, technical advancement can only be transferred into more reliable, operational EWSs with an adequate well-instructed dedicated staff. To this end, an intense dialog between scientists, engineers and those in charge of warning, as well as further experience with new comprehensive prototype systems jointly operated by scientists and practitioners, will be essential.

  5. Direct pressure monitoring accurately predicts pulmonary vein occlusion during cryoballoon ablation.

    PubMed

    Kosmidou, Ioanna; Wooden, Shannnon; Jones, Brian; Deering, Thomas; Wickliffe, Andrew; Dan, Dan

    2013-01-01

    Cryoballoon ablation (CBA) is an established therapy for atrial fibrillation (AF). Pulmonary vein (PV) occlusion is essential for achieving antral contact and PV isolation and is typically assessed by contrast injection. We present a novel method of direct pressure monitoring for assessment of PV occlusion. Transcatheter pressure is monitored during balloon advancement to the PV antrum. Pressure is recorded via a single pressure transducer connected to the inner lumen of the cryoballoon. Pressure curve characteristics are used to assess occlusion in conjunction with fluoroscopic or intracardiac echocardiography (ICE) guidance. PV occlusion is confirmed when loss of typical left atrial (LA) pressure waveform is observed with recordings of PA pressure characteristics (no A wave and rapid V wave upstroke). Complete pulmonary vein occlusion as assessed with this technique has been confirmed with concurrent contrast utilization during the initial testing of the technique and has been shown to be highly accurate and readily reproducible. We evaluated the efficacy of this novel technique in 35 patients. A total of 128 veins were assessed for occlusion with the cryoballoon utilizing the pressure monitoring technique; occlusive pressure was demonstrated in 113 veins with resultant successful pulmonary vein isolation in 111 veins (98.2%). Occlusion was confirmed with subsequent contrast injection during the initial ten procedures, after which contrast utilization was rapidly reduced or eliminated given the highly accurate identification of occlusive pressure waveform with limited initial training. Verification of PV occlusive pressure during CBA is a novel approach to assessing effective PV occlusion and it accurately predicts electrical isolation. Utilization of this method results in significant decrease in fluoroscopy time and volume of contrast. PMID:23485956

  6. Usefulness of mycophenolic acid monitoring with PETINIA for prediction of adverse events in kidney transplant recipients.

    PubMed

    Ham, Ji Yeon; Jung, Hee-Yeon; Choi, Ji-Young; Park, Sun-Hee; Kim, Yong-Lim; Kim, Hyung-Kee; Huh, Seung; Kim, Chan-Duck; Won, Dong Il; Song, Kyung Eun; Cho, Jang-Hee

    2016-07-01

    Background Therapeutic drug monitoring of mycophenolic acid (MPA) is required to optimize the immunosuppressive effect and minimize toxicity. We validated a new particle-enhanced turbidimetric inhibition immunoassay (PETINIA) for the determination of MPA levels and evaluated the relationship of MPA trough level with drug-related adverse events. Methods PETENIA and liquid chromatography-mass spectrometry (LC-MS) were used to determine MPA concentrations from 54 kidney transplant recipients (KTRs). Agreement between PETINIA and LC-MS results was assessed by Passing-Bablok regression and the Bland-Altman plot method. The association of adverse events with MPA trough level obtained by PETINIA was analyzed. Results PETINIA revealed a good agreement with the LC-MS; Regression analysis gave an equation of y = 1.27x - 0.12 (r(2) = 0.975, p < 0.001). PETINIA showed a systemic positive bias with a mean difference of 0.66 mg/L compared to LC-MS. However, the magnitude of the positive bias decreased to 0.44 mg/L within the therapeutic range of MPA. Multiple logistic regression showed that MPA trough level determined by PETINIA was an independent risk factor for adverse events (odds ratio 2.28, 95% CI 1.25-4.16, p = 0.007). MPA trough level predicted adverse events with a sensitivity of 77.8% and a specificity of 86.7% using a cut-off level of 5.25 mg/L. Conclusions Good correlation between the two methods indicates that PETINIA is an acceptable method for the monitoring of MPA therapeutic levels. Furthermore, MPA trough level obtained by PETINIA is a useful monitoring tool to minimize toxicity in KTRs. PMID:26981890

  7. Direct Pressure Monitoring Accurately Predicts Pulmonary Vein Occlusion During Cryoballoon Ablation

    PubMed Central

    Kosmidou, Ioanna; Wooden, Shannnon; Jones, Brian; Deering, Thomas; Wickliffe, Andrew; Dan, Dan

    2013-01-01

    Cryoballoon ablation (CBA) is an established therapy for atrial fibrillation (AF). Pulmonary vein (PV) occlusion is essential for achieving antral contact and PV isolation and is typically assessed by contrast injection. We present a novel method of direct pressure monitoring for assessment of PV occlusion. Transcatheter pressure is monitored during balloon advancement to the PV antrum. Pressure is recorded via a single pressure transducer connected to the inner lumen of the cryoballoon. Pressure curve characteristics are used to assess occlusion in conjunction with fluoroscopic or intracardiac echocardiography (ICE) guidance. PV occlusion is confirmed when loss of typical left atrial (LA) pressure waveform is observed with recordings of PA pressure characteristics (no A wave and rapid V wave upstroke). Complete pulmonary vein occlusion as assessed with this technique has been confirmed with concurrent contrast utilization during the initial testing of the technique and has been shown to be highly accurate and readily reproducible. We evaluated the efficacy of this novel technique in 35 patients. A total of 128 veins were assessed for occlusion with the cryoballoon utilizing the pressure monitoring technique; occlusive pressure was demonstrated in 113 veins with resultant successful pulmonary vein isolation in 111 veins (98.2%). Occlusion was confirmed with subsequent contrast injection during the initial ten procedures, after which contrast utilization was rapidly reduced or eliminated given the highly accurate identification of occlusive pressure waveform with limited initial training. Verification of PV occlusive pressure during CBA is a novel approach to assessing effective PV occlusion and it accurately predicts electrical isolation. Utilization of this method results in significant decrease in fluoroscopy time and volume of contrast. PMID:23485956

  8. Global and Regional Real-time Systems for Flood and Drought Monitoring and Prediction

    NASA Astrophysics Data System (ADS)

    Hong, Y.; Gourley, J. J.; Xue, X.; Flamig, Z.

    2015-12-01

    A Hydrometeorological Extreme Mapping and Prediction System (HyXtreme-MaP), initially built upon the Coupled Routing and Excess STorage (CREST) distributed hydrological model, is driven by real-time quasi-global TRMM/GPM satellites and by the US Multi-Radar Multi-Sensor (MRMS) radar network with dual-polarimetric upgrade to simulate streamflow, actual ET, soil moisture and other hydrologic variables at 1/8th degree resolution quasi-globally (http://eos.ou.edu) and at 250-meter 2.5-mintue resolution over the Continental United States (CONUS: http://flash.ou.edu).­ Multifaceted and collaborative by-design, this end-to-end research framework aims to not only integrate data, models, and applications but also brings people together (i.e., NOAA, NASA, University researchers, and end-users). This presentation will review the progresses, challenges and opportunities of such HyXTREME-MaP System used to monitor global floods and droughts, and also to predict flash floods over the CONUS.

  9. Antipsychotic therapeutic drug monitoring: psychiatrists’ attitudes and factors predicting likely future use

    PubMed Central

    Law, Suzanne; Haddad, Peter M.; Chaudhry, Imran B.; Husain, Nusrat; Drake, Richard J.; Flanagan, Robert J.; David, Anthony S.

    2015-01-01

    Background: This study aimed to explore predictive factors for future use of therapeutic drug monitoring (TDM) and to further examine psychiatrists’ current prescribing practices and perspectives regarding antipsychotic TDM using plasma concentrations. Method: A cross-sectional study for consultant psychiatrists using a postal questionnaire was conducted in north-west England. Data were combined with those of a previous London-based study and principal axis factor analysis was conducted to identify predictors of future use of TDM. Results: Most of the 181 participants (82.9%, 95% confidence interval 76.7–87.7%) agreed that ‘if TDM for antipsychotics were readily available, I would use it’. Factor analysis identified five factors from the original 35 items regarding TDM. Four of the factors significantly predicted likely future use of antipsychotic TDM and together explained 40% of the variance in a multivariate linear regression model. Likely future use increased with positive attitudes and expectations, and decreased with potential barriers, negative attitudes and negative expectations. Scientific perspectives of TDM and psychiatrist characteristics were not significant predictors. Conclusion: Most senior psychiatrists indicated that they would use antipsychotic TDM if available. However, psychiatrists’ attitudes and expectations and the potential barriers need to be addressed, in addition to the scientific evidence, before widespread use of antipsychotic TDM is likely in clinical practice. PMID:26301077

  10. FBG Sensor for Contact Level Monitoring and Prediction of Perforation in Cardiac Ablation

    PubMed Central

    Ho, Siu Chun Michael; Razavi, Mehdi; Nazeri, Alireza; Song, Gangbing

    2012-01-01

    Atrial fibrillation (AF) is the most common type of arrhythmia, and is characterized by a disordered contractile activity of the atria (top chambers of the heart). A popular treatment for AF is radiofrequency (RF) ablation. In about 2.4% of cardiac RF ablation procedures, the catheter is accidently pushed through the heart wall due to the application of excessive force. Despite the various capabilities of currently available technology, there has yet to be any data establishing how cardiac perforation can be reliably predicted. Thus, two new FBG based sensor prototypes were developed to monitor contact levels and predict perforation. Two live sheep were utilized during the study. It was observed during operation that peaks appeared in rhythm with the heart rate whenever firm contact was made between the sensor and the endocardial wall. The magnitude of these peaks varied with pressure applied by the operator. Lastly, transmural perforation of the left atrial wall was characterized by a visible loading phase and a rapid signal drop-off correlating to perforation. A possible pre-perforation signal was observed for the epoxy-based sensor in the form of a slight signal reversal (12–26% of loading phase magnitude) prior to perforation (occurring over 8 s). PMID:22368507

  11. Remote health monitoring: predicting outcome success based on contextual features for cardiovascular disease.

    PubMed

    Alshurafa, Nabil; Eastwood, Jo-Ann; Pourhomayoun, Mohammad; Liu, Jason J; Sarrafzadeh, Majid

    2014-01-01

    Current studies have produced a plethora of remote health monitoring (RHM) systems designed to enhance the care of patients with chronic diseases. Many RHM systems are designed to improve patient risk factors for cardiovascular disease, including physiological parameters such as body mass index (BMI) and waist circumference, and lipid profiles such as low density lipoprotein (LDL) and high density lipoprotein (HDL). There are several patient characteristics that could be determining factors for a patient's RHM outcome success, but these characteristics have been largely unidentified. In this paper, we analyze results from an RHM system deployed in a six month Women's Heart Health study of 90 patients, and apply advanced feature selection and machine learning algorithms to identify patients' key baseline contextual features and build effective prediction models that help determine RHM outcome success. We introduce Wanda-CVD, a smartphone-based RHM system designed to help participants with cardiovascular disease risk factors by motivating participants through wireless coaching using feedback and prompts as social support. We analyze key contextual features that secure positive patient outcomes in both physiological parameters and lipid profiles. Results from the Women's Heart Health study show that health threat of heart disease, quality of life, family history, stress factors, social support, and anxiety at baseline all help predict patient RHM outcome success. PMID:25570321

  12. FBG sensor for contact level monitoring and prediction of perforation in cardiac ablation.

    PubMed

    Ho, Siu Chun Michael; Razavi, Mehdi; Nazeri, Alireza; Song, Gangbing

    2012-01-01

    Atrial fibrillation (AF) is the most common type of arrhythmia, and is characterized by a disordered contractile activity of the atria (top chambers of the heart). A popular treatment for AF is radiofrequency (RF) ablation. In about 2.4% of cardiac RF ablation procedures, the catheter is accidently pushed through the heart wall due to the application of excessive force. Despite the various capabilities of currently available technology, there has yet to be any data establishing how cardiac perforation can be reliably predicted. Thus, two new FBG based sensor prototypes were developed to monitor contact levels and predict perforation. Two live sheep were utilized during the study. It was observed during operation that peaks appeared in rhythm with the heart rate whenever firm contact was made between the sensor and the endocardial wall. The magnitude of these peaks varied with pressure applied by the operator. Lastly, transmural perforation of the left atrial wall was characterized by a visible loading phase and a rapid signal drop-off correlating to perforation. A possible pre-perforation signal was observed for the epoxy-based sensor in the form of a slight signal reversal (12-26% of loading phase magnitude) prior to perforation (occurring over 8 s). PMID:22368507

  13. Remote infrasound monitoring of Mount Etna: Observed and predicted network detection capability

    NASA Astrophysics Data System (ADS)

    Tailpied, Dorianne; Le Pichon, Alexis; Marchetti, Emanuele; Ripepe, Maurizio; Kallel, Mohamed; Ceranna, Lars

    2013-04-01

    Volcanic eruptions are unique and valuable calibrating sources of infrasonic waves worldwide detected by the International Monitoring System (IMS) of the Comprehensive nuclear Test Ban Treaty Organization (CTBTO) and other experimental stations. Building a comprehensive database of volcanic signals is likely to help the scientific community to better characterize eruptive sequences and may help to prevent eruption disasters while on a longer term mitigate the impact of ash clouds on aviation. In this study, we assess the detection capability of the existing infrasound network to remotely detect the eruptive activity of Mount Etna with a high level of confidence, and predict the performance of the future ARISE infrastructure network (Atmospheric dynamics InfraStructure in Europe). This well-instrumented volcano offers a unique opportunity to validate attenuation models using multiyear near-and-far field recordings. The seasonal trend in the number of detections of Etna at the IS48 IMS station (Tunisia) is correlated to fine temporal fluctuations of the stratospheric waveguide structure. The modeling results are consistent with the observed detection capability of the existing network. In summer, during the downwind season, a minimum detectable amplitude of ~10 Pa at a reference distance of 1 km from the source is predicted. In winter, when upwind propagation occurs, detection thresholds increase up to ~100 Pa. When adding four experimental arrays to the existing IMS network, thresholds decrease down to ~20 Pa in winter. The simulation results provide here a realistic description of long-range infrasound propagation and allow predicting fine temporal fluctuations in the European infrasound network performance with potential application for civil aviation safety.

  14. Is the incidence of heart attack still decreasing in Australia? Developing reliable methods for monitoring trends in myocardial infarction and coronary heart disease (AUS-MOCHA): a study protocol

    PubMed Central

    Nedkoff, Lee; Knuiman, Matthew; Hobbs, Michael S T; Hung, Joseph; Mathur, Sushma; Beilby, John; Reynolds, Anna; Briffa, Tom G; Lopez, Derrick

    2016-01-01

    Introduction Accurate monitoring of acute coronary heart disease (CHD) is essential for understanding the effects of primary and secondary prevention and for planning of healthcare services. The ability to reliably monitor acute CHD has been affected by new diagnostic tests for myocardial infarction (MI) and changing clinical classifications and management of CHD. Our study will develop new and reliable methods for monitoring population trends in incidence, outcomes and health service usage for acute CHD and chest pain. Methods and analysis The study cohort of all CHD will be identified from the Western Australian Data Linkage System using state-wide data sets for emergency department presentation, hospitalisations and mortality data for 2002–2014. This core linked data set will be supplemented with data from hospital medical record reviews, pathology data and hospital pharmacy dispensing databases. The consistency over time of the coding of the different subgroups of CHD/chest pain (ST-elevation MI, non-ST elevation MI, unstable angina, stable angina, other CHD, non-CHD chest pain) in linked data will be assessed using these data sources, and an algorithm developed detailing groups in which temporal trends can be reliably measured. This algorithm will be used for measurement of trends in incidence and outcomes of acute CHD, and to develop further methods for monitoring acute CHD using unlinked and linked data with varying availability of hospitalisation history. Ethics and dissemination Ethics approval has been obtained from the Human Research Ethics Committees of the WA Department of Health (#2016/23) and The University of Western Australia (RA/4/1/7230). Findings will be disseminated via publication in peer-reviewed journals, and presentation at national and international conferences. There will also be a strong platform for dissemination of new monitoring methods via collaboration with the Australian Institute of Health and Welfare which will assist with

  15. WIFIRE: A Scalable Data-Driven Monitoring, Dynamic Prediction and Resilience Cyberinfrastructure for Wildfires

    NASA Astrophysics Data System (ADS)

    Altintas, I.; Block, J.; Braun, H.; de Callafon, R. A.; Gollner, M. J.; Smarr, L.; Trouve, A.

    2013-12-01

    Recent studies confirm that climate change will cause wildfires to increase in frequency and severity in the coming decades especially for California and in much of the North American West. The most critical sustainability issue in the midst of these ever-changing dynamics is how to achieve a new social-ecological equilibrium of this fire ecology. Wildfire wind speeds and directions change in an instant, and first responders can only be effective when they take action as quickly as the conditions change. To deliver information needed for sustainable policy and management in this dynamically changing fire regime, we must capture these details to understand the environmental processes. We are building an end-to-end cyberinfrastructure (CI), called WIFIRE, for real-time and data-driven simulation, prediction and visualization of wildfire behavior. The WIFIRE integrated CI system supports social-ecological resilience to the changing fire ecology regime in the face of urban dynamics and climate change. Networked observations, e.g., heterogeneous satellite data and real-time remote sensor data is integrated with computational techniques in signal processing, visualization, modeling and data assimilation to provide a scalable, technological, and educational solution to monitor weather patterns to predict a wildfire's Rate of Spread. Our collaborative WIFIRE team of scientists, engineers, technologists, government policy managers, private industry, and firefighters architects implement CI pathways that enable joint innovation for wildfire management. Scientific workflows are used as an integrative distributed programming model and simplify the implementation of engineering modules for data-driven simulation, prediction and visualization while allowing integration with large-scale computing facilities. WIFIRE will be scalable to users with different skill-levels via specialized web interfaces and user-specified alerts for environmental events broadcasted to receivers before

  16. Prediction and monitoring of monsoon intraseasonal oscillations over Indian monsoon region in an ensemble prediction system using CFSv2

    NASA Astrophysics Data System (ADS)

    Abhilash, S.; Sahai, A. K.; Borah, N.; Chattopadhyay, R.; Joseph, S.; Sharmila, S.; De, S.; Goswami, B. N.; Kumar, Arun

    2014-05-01

    An ensemble prediction system (EPS) is devised for the extended range prediction (ERP) of monsoon intraseasonal oscillations (MISO) of Indian summer monsoon (ISM) using National Centers for Environmental Prediction Climate Forecast System model version 2 at T126 horizontal resolution. The EPS is formulated by generating 11 member ensembles through the perturbation of atmospheric initial conditions. The hindcast experiments were conducted at every 5-day interval for 45 days lead time starting from 16th May to 28th September during 2001-2012. The general simulation of ISM characteristics and the ERP skill of the proposed EPS at pentad mean scale are evaluated in the present study. Though the EPS underestimates both the mean and variability of ISM rainfall, it simulates the northward propagation of MISO reasonably well. It is found that the signal-to-noise ratio of the forecasted rainfall becomes unity by about 18 days. The potential predictability error of the forecasted rainfall saturates by about 25 days. Though useful deterministic forecasts could be generated up to 2nd pentad lead, significant correlations are found even up to 4th pentad lead. The skill in predicting large-scale MISO, which is assessed by comparing the predicted and observed MISO indices, is found to be ~17 days. It is noted that the prediction skill of actual rainfall is closely related to the prediction of large-scale MISO amplitude as well as the initial conditions related to the different phases of MISO. An analysis of categorical prediction skills reveals that break is more skillfully predicted, followed by active and then normal. The categorical probability skill scores suggest that useful probabilistic forecasts could be generated even up to 4th pentad lead.

  17. Monitoring and predicting cognitive state and performance via physiological correlates of neuronal signals.

    PubMed

    Russo, Michael B; Stetz, Melba C; Thomas, Maria L

    2005-07-01

    Judgment, decision making, and situational awareness are higher-order mental abilities critically important to operational cognitive performance. Higher-order mental abilities rely on intact functioning of multiple brain regions, including the prefrontal, thalamus, and parietal areas. Real-time monitoring of individuals for cognitive performance capacity via an approach based on sampling multiple neurophysiologic signals and integrating those signals with performance prediction models potentially provides a method of supporting warfighters' and commanders' decision making and other operationally relevant mental processes and is consistent with the goals of augmented cognition. Cognitive neurophysiological assessments that directly measure brain function and subsequent cognition include positron emission tomography, functional magnetic resonance imaging, mass spectroscopy, near-infrared spectroscopy, magnetoencephalography, and electroencephalography (EEG); however, most direct measures are not practical to use in operational environments. More practical, albeit indirect measures that are generated by, but removed from the actual neural sources, are movement activity, oculometrics, heart rate, and voice stress signals. The goal of the papers in this section is to describe advances in selected direct and indirect cognitive neurophysiologic monitoring techniques as applied for the ultimate purpose of preventing operational performance failures. These papers present data acquired in a wide variety of environments, including laboratory, simulator, and clinical arenas. The papers discuss cognitive neurophysiologic measures such as digital signal processing wrist-mounted actigraphy; oculometrics including blinks, saccadic eye movements, pupillary movements, the pupil light reflex; and high-frequency EEG. These neurophysiological indices are related to cognitive performance as measured through standard test batteries and simulators with conditions including sleep loss

  18. Enabling Technology for Monitoring & Predicting Gas Turbine Health & Performance in COAL IGCC Powerplants

    SciTech Connect

    Kenneth A. Yackly

    2004-09-30

    The ''Enabling & Information Technology To Increase RAM for Advanced Powerplants'' program, by DOE request, has been re-directed, de-scoped to two tasks, shortened to a 2-year period of performance, and refocused to develop, validate and accelerate the commercial use of enabling materials technologies and sensors for Coal IGCC powerplants. The new program has been re-titled as ''Enabling Technology for Monitoring & Predicting Gas Turbine Health & Performance in IGCC Powerplants'' to better match the new scope. This technical progress report summarizes the work accomplished in the reporting period April 1, 2004 to August 31, 2004 on the revised Re-Directed and De-Scoped program activity. The program Tasks are: Task 1--IGCC Environmental Impact on high Temperature Materials: This first materials task has been refocused to address Coal IGCC environmental impacts on high temperature materials use in gas turbines and remains in the program. This task will screen material performance and quantify the effects of high temperature erosion and corrosion of hot gas path materials in Coal IGCC applications. The materials of interest will include those in current service as well as advanced, high-performance alloys and coatings. Task 2--Material In-Service Health Monitoring: This second task develops and demonstrates new sensor technologies to determine the in-service health of advanced technology Coal IGCC powerplants, and remains in the program with a reduced scope. Its focus is now on only two critical sensor need areas for advanced Coal IGCC gas turbines: (1) Fuel Quality Sensor for detection of fuel impurities that could lead to rapid component degradation, and a Fuel Heating Value Sensor to rapidly determine the fuel heating value for more precise control of the gas turbine, and (2) Infra-Red Pyrometer to continuously measure the temperature of gas turbine buckets, nozzles, and combustor hardware.

  19. Quantitative electroencephalographic monitoring during myocardial revascularization predicts postoperative disorientation and improves outcome.

    PubMed

    Edmonds, H L; Griffiths, L K; van der Laken, J; Slater, A D; Shields, C B

    1992-03-01

    We evaluated computerized quantitative electroencephalography for the intraoperative detection of cerebral dysfunction. The quantitative electroencephalogram was recorded continuously during 96 myocardial revascularizations involving hypothermic cardiopulmonary bypass using Cerebrovascular Intraoperative MONitor (CIMON) software. CIMON relies on an adaptive statistical approach to detect subtle, but clinically relevant, changes in electroencephalographic activity indicative of cerebrocortical dysfunction. Relative (percent of total) low-frequency (1.5 to 3.5 Hz) power was chosen as the single quantitative electroencephalographic descriptor because it is an established hallmark of cortical dysfunction and is surprisingly insensitive to moderate changes in body temperature and level of opioid anesthesia. Reference values for this measure were established for each patient after anesthetic induction before sternotomy. The large sample variance often seen in low-frequency power was dramatically decreased by using log-transformed data and allowing each patient to serve as his own control. Quantitative electroencephalographic changes in standard deviation units or z-scores were determined from the individualized reference self-norm. Prolonged (greater than 5 minutes) and statistically significant (greater than 3 standard deviation) focal increases in relative low-frequency power were temperature-corrected to determine a standardized cerebrocortical dysfunction time at 37 degrees C. (CDT37). In phase I (n = 48), this objective quantitative electroencephalogram-based numeric descriptor was used to predict neuropsychologic outcome. These CDT37 greater than 5-minute episodes occurred 38 times in 19 patients. The quantitative electroencephalogram-based descriptor predicted the occurrence of such disorientation (n = 14 or 29%) with a 68% false positive rate but only an 8% false negative rate. Since these intraoperative quantitative electroencephalographic episodes were often

  20. A Cloud Based Framework For Monitoring And Predicting Subsurface System Behaviour

    NASA Astrophysics Data System (ADS)

    Versteeg, R. J.; Rodzianko, A.; Johnson, D. V.; Soltanian, M. R.; Dwivedi, D.; Dafflon, B.; Tran, A. P.; Versteeg, O. J.

    2015-12-01

    Subsurface system behavior is driven and controlled by the interplay of physical, chemical, and biological processes which occur at multiple temporal and spatial scales. Capabilities to monitor, understand and predict this behavior in an effective and timely manner are needed for both scientific purposes and for effective subsurface system management. Such capabilities require three elements: Models, Data and an enabling cyberinfrastructure, which allow users to use these models and data in an effective manner. Under a DOE Office of Science funded STTR award Subsurface Insights and LBNL have designed and implemented a cloud based predictive assimilation framework (PAF) which automatically ingests, controls quality and stores heterogeneous physical and chemical subsurface data and processes these data using different inversion and modeling codes to provide information on the current state and evolution of subsurface systems. PAF is implemented as a modular cloud based software application with five components: (1) data acquisition, (2) data management, (3) data assimilation and processing, (4) visualization and result delivery and (5) orchestration. Serverside PAF uses ZF2 (a PHP web application framework) and Python and both open source (ODM2) and in house developed data models. Clientside PAF uses CSS and JS to allow for interactive data visualization and analysis. Client side modularity (which allows for a responsive interface) of the system is achieved by implementing each core capability of PAF (such as data visualization, user configuration and control, electrical geophysical monitoring and email/SMS alerts on data streams) as a SPA (Single Page Application). One of the recent enhancements is the full integration of a number of flow and mass transport and parameter estimation codes (e.g., MODFLOW, MT3DMS, PHT3D, TOUGH, PFLOTRAN) in this framework. This integration allows for autonomous and user controlled modeling of hydrological and geochemical processes. In

  1. Real-time Seismic Amplitude Measurement (RSAM): a volcano monitoring and prediction tool

    USGS Publications Warehouse

    Endo, E.T.; Murray, T.

    1991-01-01

    Seismicity is one of the most commonly monitored phenomena used to determine the state of a volcano and for the prediction of volcanic eruptions. Although several real-time earthquake-detection and data acquisition systems exist, few continuously measure seismic amplitude in circumstances where individual events are difficult to recognize or where volcanic tremor is prevalent. Analog seismic records provide a quick visual overview of activity; however, continuous rapid quantitative analysis to define the intensity of seismic activity for the purpose of predicing volcanic eruptions is not always possible because of clipping that results from the limited dynamic range of analog recorders. At the Cascades Volcano Observatory, an inexpensive 8-bit analog-to-digital system controlled by a laptop computer is used to provide 1-min average-amplitude information from eight telemetered seismic stations. The absolute voltage level for each station is digitized, averaged, and appended in near real-time to a data file on a multiuser computer system. Raw realtime seismic amplitude measurement (RSAM) data or transformed RSAM data are then plotted on a common time base with other available volcano-monitoring information such as tilt. Changes in earthquake activity associated with dome-building episodes, weather, and instrumental difficulties are recognized as distinct patterns in the RSAM data set. RSAM data for domebuilding episodes gradually develop into exponential increases that terminate just before the time of magma extrusion. Mount St. Helens crater earthquakes show up as isolated spikes on amplitude plots for crater seismic stations but seldom for more distant stations. Weather-related noise shows up as low-level, long-term disturbances on all seismic stations, regardless of distance from the volcano. Implemented in mid-1985, the RSAM system has proved valuable in providing up-to-date information on seismic activity for three Mount St. Helens eruptive episodes from 1985 to

  2. Prediction and Monitoring of Monsoon Intraseasonal Oscillations over Indian Monsoon Region in an Ensemble Prediction System using CFSv2

    NASA Astrophysics Data System (ADS)

    Borah, N.; Abhilash, S.; Sahai, A. K.; Chattopadhyay, R.; Joseph, S.; Sharmila, S.; de, S.; Goswami, B.; Kumar, A.

    2013-12-01

    An ensemble prediction system (EPS) is devised for the extended range prediction (ERP) of monsoon intraseasonal oscillations (MISOs) of Indian summer monsoon (ISM) using NCEP Climate Forecast System model version2 at T126 horizontal resolution. The EPS is formulated by producing 11 member ensembles through the perturbation of atmospheric initial conditions. The hindcast experiments were conducted at every 5-day interval for 45 days lead time starting from 16th May to 28th September during 2001-2012. The general simulation of ISM characteristics and the ERP skill of the proposed EPS at pentad mean scale are evaluated in the present study. Though the EPS underestimates both the mean and variability of ISM rainfall, it simulates the northward propagation of MISO reasonably well. It is found that the signal-to-noise ratio becomes unity by about18 days and the predictability error saturates by about 25 days. Though useful deterministic forecasts could be generated up to 2nd pentad lead, significant correlations are observed even up to 4th pentad lead. The skill in predicting large-scale MISO, which is assessed by comparing the predicted and observed MISO indices, is found to be ~17 days. It is noted that the prediction skill of actual rainfall is closely related to the prediction of amplitude of large scale MISO as well as the initial conditions related to the different phases of MISO. Categorical prediction skills reveals that break is more skillfully predicted, followed by active and then normal. The categorical probability skill scores suggest that useful probabilistic forecasts could be generated even up to 4th pentad lead.

  3. Prediction and Monitoring of Monsoon Intraseasonal Oscillations over Indian Monsoon Region in an Ensemble Prediction System using CFSv2

    NASA Astrophysics Data System (ADS)

    Borah, Nabanita; Sukumarpillai, Abhilash; Sahai, Atul Kumar; Chattopadhyay, Rajib; Joseph, Susmitha; De, Soumyendu; Nath Goswami, Bhupendra; Kumar, Arun

    2014-05-01

    An ensemble prediction system (EPS) is devised for the extended range prediction (ERP) of monsoon intraseasonal oscillations (MISO) of Indian summer monsoon (ISM) using NCEP Climate Forecast System model version2 at T126 horizontal resolution. The EPS is formulated by producing 11 member ensembles through the perturbation of atmospheric initial conditions. The hindcast experiments were conducted at every 5-day interval for 45 days lead time starting from 16th May to 28th September during 2001-2012. The general simulation of ISM characteristics and the ERP skill of the proposed EPS at pentad mean scale are evaluated in the present study. Though the EPS underestimates both the mean and variability of ISM rainfall, it simulates the northward propagation of MISO reasonably well. It is found that the signal-to-noise ratio becomes unity by about18 days and the predictability error saturates by about 25 days. Though useful deterministic forecasts could be generated up to 2nd pentad lead, significant correlations are observed even up to 4th pentad lead. The skill in predicting large-scale MISO, which is assessed by comparing the predicted and observed MISO indices, is found to be ~17 days. It is noted that the prediction skill of actual rainfall is closely related to the prediction of amplitude of large scale MISO as well as the initial conditions related to the different phases of MISO. Categorical prediction skills reveals that break is more skillfully predicted, followed by active and then normal. The categorical probability skill scores suggest that useful probabilistic forecasts could be generated even up to 4th pentad lead.

  4. Prediction of self-monitoring compliance: application of the theory of planned behaviour to chronic illness sufferers.

    PubMed

    McGuckin, Conor; Prentice, Garry R; McLaughlin, Christopher G; Harkin, Emma

    2012-01-01

    Chronic obstructive pulmonary disease (COPD), diabetes and asthma are chronic illnesses that affect a substantial number of people. The continued high cost of clinic- and hospital-based care provision in these areas could be reduced by patients self-monitoring their condition more effectively. Such a move requires an understanding of how to predict self-monitoring compliance. Ajzen's theory of planned behaviour (TPB) makes it possible to predict those clients who will comply with medical guidelines, prescription drug intake and self-monitoring behaviours (peak flow or blood sugar levels). Ninety-seven clients attending a medical centre located in a large urbanised area of Northern Ireland completed TPB questionnaires. Significant amounts of variance explained by the TPB model indicated its usefulness as a predictor of self-monitoring behaviour intentions in the sample. The results also highlighted the importance of subjective norm and perceived behavioural control within the TPB in predicting intentions. The utility of the TPB in this study also provides evidence for health promotion professionals that costly clinic/hospital treatment provision can be reduced, whilst also being satisfied with ongoing client self-monitoring of their condition. PMID:22111866

  5. Future clinical uses of neurophysiological biomarkers to predict and monitor treatment response for schizophrenia

    PubMed Central

    Light, Gregory A.; Swerdlow, Neal R.

    2015-01-01

    Advances in psychiatric neuroscience have transformed our understanding of impaired and spared brain functions in psychotic illnesses. Despite substantial progress, few if any laboratory tests have graduated to clinics to inform diagnoses, guide treatments, and monitor treatment response. Providers must rely on careful behavioral observation and interview techniques to make inferences about patients’ inner experiences and then secondary deductions about impacted neural systems. Development of more effective treatments has also been hindered by a lack of translational quantitative biomarkers that can span the brain–behavior–treatment knowledge gap. Here, we describe an example of a simple, low-cost, and translatable electroencephalography (EEG) measure that offers promise for improving our understanding and treatment of psychotic illnesses: mismatch negativity (MMN). MMN is sensitive to and/or predicts response to some pharmacologic and non-pharmacologic interventions and accounts for substantial portions of variance in clinical, cognitive, and psychosocial functioning in schizophrenia. This measure has recently been validated for use in large-scale multisite clinical studies of schizophrenia. Lastly, MMN greatly improves our ability to forecast which individuals at high clinical risk actually develop a psychotic illness. These attributes suggest that MMN can contribute to personalized biomarker-guided treatment strategies aimed at ameliorating or even preventing the onset of psychosis. PMID:25752648

  6. Multi-Scale Monitoring and Prediction of System Responses to Biostimulation

    SciTech Connect

    Hubbard, Susan; Williams, Ken; Steefel, Carl; Long, Phil; Kinsong Chen, Slater, Lee; Banfield, Jill

    2006-04-05

    To advance solutions needed for remediation of DOE contaminated sites, approaches are needed that can elucidate and predict reactions associated with coupled biological, geochemical, and hydrological processes over a variety of spatial scales and in heterogeneous environments. Our laboratory experimental experiments, which were conducted under controlled conditions, suggest that geophysical methods have the potential for elucidating system transformations that often occur during remediation, such as the generation of gases and precipitates. In this new ERSP project, we will Integrate hydrological, biogeochemical, and geophysical expertise and approaches to: (1) Explore the potential of geophysical methods for detecting changes in physical, chemical, and biological properties at the field scale; and (2) Explore the joint use of reactive transport modeling and geophysical monitoring information for improvements in both methods. A brief review of our previously-conducted laboratory results are given in Section II. Section III describes the approach for our new project, which will have both laboratory and field-scale components. The field scale component will be conducted at the Rifle, CO. site, which is described in Section IV.

  7. The Source Physics Experiments and Advances in Seismic Explosion Monitoring Predictive Capabilities

    NASA Astrophysics Data System (ADS)

    Walter, W. R.; Ford, S. R.; Antoun, T.; Pitarka, A.; Xu, H.; Vorobiev, O.; Rodgers, A.; Pyle, M. L.

    2012-12-01

    Despite many years of study, a number of seismic explosion phenomena remain incompletely understood. These include the generation of S-waves, the variation of absolute amplitudes with emplacement media differences, and the occasional generation of reversed Rayleigh waves. Advances in numerical methods and increased computational power have improved the physics contained in the modeling software and it is possible to couple non-linear source-region effects to far-field propagation codes to predict seismic observables, thereby allowing end-to-end modeling. However, despite the many sensor records from prior nuclear tests, the data available to develop and validate the simulation codes remain limited in important ways. This is particularly the case for the range of both scaled depths of burial and of source media, especially where full near-field to far-field records are available along with key quantitative parameter data such as depth, material properties and yield. For example, two of the most widely used seismic source models, both derived from the best empirical data, Mueller and Murphy (1971) and Denny and Johnson (1989), predict very different amplitudes for greatly overburied explosions. To provide new data to advance predictive explosion modeling capabilities, the National Nuclear Security Administration (NNSA) is carrying out a series of seven chemical explosions over a range of depths and sizes in the Source Physics Experiments (SPE). These shots are taking place in the Climax Stock granite at the Nevada National Security Site, the location where reversed Rayleigh waves from a nuclear test were first observed in the 1962 HARDHAT event (e.g. Brune and Pomeroy, 1963). Three of the SPE shots have successfully occurred so far, and were well-recorded by an extensive set of instrumentation including seismic, acoustic, EM, and remote sensing. In parallel, detailed site characterization has been conducted using geologic mapping and sampling, borehole geophysics

  8. DoD-GEIS Rift Valley Fever Monitoring and Prediction System as a Tool for Defense and US Diplomacy

    NASA Technical Reports Server (NTRS)

    Anyamba, Assaf; Tucker, Compton J.; Linthicum, Kenneth J.; Witt, Clara J.; Gaydos, Joel C.; Russell, Kevin L.

    2011-01-01

    Over the last 10 years the Armed Forces Health Surveillance Center's Global Emerging Infections Surveillance and Response System (GEIS) partnering with NASA'S Goddard Space Flight Center and USDA's USDA-Center for Medical, Agricultural & Veterinary Entomology established and have operated the Rift Valley fever Monitoring and Prediction System to monitor, predict and assess the risk of Rift Valley fever outbreaks and other vector-borne diseases over Africa and the Middle East. This system is built on legacy DoD basic research conducted by Walter Reed Army Institute of Research overseas laboratory (US Army Medical Research Unit-Kenya) and the operational satellite environmental monitoring by NASA GSFC. Over the last 10 years of operation the system has predicted outbreaks of Rift Valley fever in the Horn of Africa, Sudan, South Africa and Mauritania. The ability to predict an outbreak several months before it occurs provides early warning to protect deployed forces, enhance public health in concerned countries and is a valuable tool use.d by the State Department in US Diplomacy. At the international level the system has been used by the Food and Agricultural Organization (FAD) and the World Health Organization (WHO) to support their monitoring, surveillance and response programs in the livestock sector and human health. This project is a successful testament of leveraging resources of different federal agencies to achieve objectives of force health protection, health and diplomacy.

  9. Testing a Multi-Stage Screening System: Predicting Performance on Australia's National Achievement Test Using Teachers' Ratings of Academic and Social Behaviors

    ERIC Educational Resources Information Center

    Kettler, Ryan J.; Elliott, Stephen N.; Davies, Michael; Griffin, Patrick

    2012-01-01

    This study addresses the predictive validity of results from a screening system of academic enablers, with a sample of Australian elementary school students, when the criterion variable is end-of-year achievement. The investigation included (a) comparing the predictive validity of a brief criterion-referenced nomination system with more…

  10. Monitoring the spread of myxoma virus in rabbit Oryctolagus cuniculus populations on the southern tablelands of New South Wales, Australia. I. Natural occurrence of myxomatosis.

    PubMed

    Merchant, J C; Kerr, P J; Simms, N G; Robinson, A J

    2003-02-01

    A survey of rabbit populations in the southern tablelands of New South Wales, Australia, was carried out to establish the pattern of occurrence of myxomatosis in preparation for a deliberate release of myxoma virus. Myxomatosis was first detected in December and cases were found on most sites through to May. The serological profiles of rabbit populations suggested that their susceptibility to myxoma virus was generally low in winter and highest in spring and summer reflecting the presence of increasing numbers of susceptible young rabbits. This was consistent with the pattern of rabbit breeding, as determined from the distribution of births and reproductive activity in females and males, which occurred maximally in spring and early summer. The serology and age structure of rabbit populations on sites suggested that some rabbit populations can escape an annual myxomatosis epizootic. Although fleas were present on rabbits throughout the year and therefore not considered to be a limiting factor in the spread of myxomatosis, their numbers peaked at times coincident with peak rabbit breeding. It was concluded that mid to late spring was an optimal time for a deliberate release. PMID:12613753

  11. Plant functional types are more efficient than climate in predicting spectrums of trait variation in evergreen angiosperm trees of tropical Australia and China

    NASA Astrophysics Data System (ADS)

    Togashi, H. F.; Prentice, I. C. C.; Atkin, O. K.; Bloomfield, K. J.; Bradford, M.; Weerasinghe, L. K.; Harrison, S. P.; Evans, B. J.; Liddell, M. J.; Wang, H.; Cao, K. F.; Fan, Z.

    2015-12-01

    The representation of Plant Functional Types (PFTs) in current generation of Dynamic Global Vegetation Models (DGVMs) is excessively simplistically. Key ecophysiological properties, such as photosynthesis biochemistry, are most times merely averaged and trade-off with other plant traits is often neglected. Validation of a PFT framework based in photosynthetic process is crucial to improve reliability of DGVMs. We present 431 leaf-biochemical and wood level measurements in evergreen angiosperm trees of tropical forests in Australia and China that were divided in four spectrums of plant trait variation: metabolic, structural, hydraulic and height dimensions. Plant traits divided in each of these dimensions adopt survival strategies reflected more clearly by trade-off within each spectrum, and in some extent across spectrums. Co-ordination theory (that Rubisco- and electron-transport limited rates of photosynthesis are co-limiting) and least-coast theory (that intercellular to ambient CO2 concentration minimizes the combined costs per unit carbon assimilation, regulating maximum height and wood density) expectations matched PFT (which takes in account canopy position and light access, and life spam) variation. Our findings suggest that climate (air moisture, air temperature, light) has lower power representing these dimensions, in comparison to the PFT framework.

  12. Monitors.

    ERIC Educational Resources Information Center

    Powell, David

    1984-01-01

    Provides guidelines for selecting a monitor to suit specific applications, explains the process by which graphics images are produced on a CRT monitor, and describes four types of flat-panel displays being used in the newest lap-sized portable computers. A comparison chart provides prices and specifications for over 80 monitors. (MBR)

  13. Predictive Value of Somatosensory Evoked Potential Monitoring during Resection of Intraparenchymal and Intraventricular Tumors Using an Endoscopic Port

    PubMed Central

    Lai, Daniel; Engh, Jonathan; Habeych, Miguel; Crammond, Donald; Balzer, Jeffrey

    2013-01-01

    Background and Purpose Intraoperative neurophysiological monitoring (IONM) using upper and lower somatosensory evoked potentials (SSEPs) is an established technique used to predict and prevent neurologic injury during intracranial tumor resections. Endoscopic port surgery (EPS) is a minimally-invasive approach to deep intraparenchymal and intraventricular brain tumors. The authors intended to evaluate the predictive value of SSEP monitoring during resection of intracranial brain tumors using a parallel endoscopic technique. Methods A retrospective review was conducted of patients operated on from 2007-2010 utilizing IONM in whom endoscopic ports were used to remove either intraparenchymal or intraventricular tumors. Cases were eligible for review if an endoscopic port was used to resect an intracranial tumor and the electronic chart included all intraoperative monitoring data as well as pre- and post-operative neurologic exams. Results 139 EPS cases met criteria for inclusion. Eighty five patients (61%) had intraparenchymal and fifty four (39%) had intraventricular tumors or colloid cysts. SSEP changes were seen in eleven cases (7.9%), being irreversible in three (2.2%) and reversible in eight cases (5.8%). Seven patients (5.0%) with intraparenchymal tumors had SSEP changes which met our criterea for significant changes while there were four (2.9%) with intraventricular (p-value=0.25). Five patients suffered post operative deficits, two reversible and two irreversible SSEP changes. Only one case exhibited post operative hemiparesis with no SSEP changes. The positive predictive value of SSEP was 45.4% and the negative predictive value was 99.2%. Conclusions Based on the high negative and low positive predictive values, the utility of SSEP monitoring for cylindrical port resections may be limited. However, the use of SSEP monitoring can be helpful in reducing the impact of endoscopic port manipulation when the tumor is closer to the somatosensory pathway. PMID

  14. An Analysis of Predicted vs. Monitored Space Heat Energy Use in 120 Homes : Residential Construction Demonstration Project Cycle II.

    SciTech Connect

    Douglass, John G.; Young, Marvin; Washington State Energy Office.

    1991-10-01

    The SUNDAY thermal simulation program was used to predict space heat energy consumption for 120 energy efficient homes. The predicted data were found to explain 43.8 percent of the variation in monitored space heat consumption. Using a paired Student's to test, no statistically significant difference could be found between mean predicted space heat and monitored space heat for the entire sample of homes. The homes were grouped into seven classes, sub-samples by total heat loss coefficient. An intermediate class (UA = 300--350 Btu/{degrees}F) was found to significantly over-predict space heat by 25 percent. The same class was over-predicted by 16 percent in the analogous Cycle 1 research, but the sample size was smaller and this was not found to be statistically significant. Several variables that were not directly included as inputs to the simulation were examined with an analysis of covariance model for their ability to improve the simulation's prediction of space heat. The variables having the greatest effect were conditioned floor area, heating system type, and foundation type. The model was able to increase the coefficient of determination from 0.438 to 0.670; a 54 percent increase. While the SUNDAY simulation program to aggregate is able to predict space heat consumption, it should be noted that there is a considerable amount of variation in both the monitored space heat consumption and the SUNDAY predictions. The ability of the program to accurately model an individual house will be constrained by both the quality of input variables and the range of occupant behavior. These constraints apply to any building model.

  15. An Analysis of Predicted vs. Monitored Space Heat Energy Use in 120 Homes :Residential Construction Demonstration Project Cycle II.

    SciTech Connect

    Douglass, John G.; Young, Marvin; Washington State Energy Office.

    1991-10-01

    The SUNDAY thermal simulation program was used to predict space heat energy consumption for 120 energy efficient homes. The predicted data were found to explain 43.8 percent of the variation in monitored space heat consumption. Using a paired Student`s to test, no statistically significant difference could be found between mean predicted space heat and monitored space heat for the entire sample of homes. The homes were grouped into seven classes, sub-samples by total heat loss coefficient. An intermediate class (UA = 300--350 Btu/{degrees}F) was found to significantly over-predict space heat by 25 percent. The same class was over-predicted by 16 percent in the analogous Cycle 1 research, but the sample size was smaller and this was not found to be statistically significant. Several variables that were not directly included as inputs to the simulation were examined with an analysis of covariance model for their ability to improve the simulation`s prediction of space heat. The variables having the greatest effect were conditioned floor area, heating system type, and foundation type. The model was able to increase the coefficient of determination from 0.438 to 0.670; a 54 percent increase. While the SUNDAY simulation program to aggregate is able to predict space heat consumption, it should be noted that there is a considerable amount of variation in both the monitored space heat consumption and the SUNDAY predictions. The ability of the program to accurately model an individual house will be constrained by both the quality of input variables and the range of occupant behavior. These constraints apply to any building model.

  16. Space weather activities in Australia

    NASA Astrophysics Data System (ADS)

    Cole, D.

    Space Weather Plan Australia has a draft space weather plan to drive and focus appropriate research into services that meet future industry and social needs. The Plan has three main platforms, space weather monitoring and service delivery, support for priority research, and outreach to the community. The details of monitoring, service, research and outreach activities are summarised. A ground-based network of 14 monitoring stations from Antarctica to Papua New Guinea is operated by IPS, a government agency. These sites monitor ionospheric and geomagnetic characteristics, while two of them also monitor the sun at radio and optical wavelengths. Services provided through the Australian Space Forecast Centre (ASFC) include real-time information on the solar, space, ionospheric and geomagnetic environments. Data are gathered automatically from monitoring sites and integrated with data exchanged internationally to create snapshots of current space weather conditions and forecasts of conditions up to several days ahead. IPS also hosts the WDC for Solar-Terrestrial Science and specialises in ground-based solar, ionospheric, and geomagnetic data sets, although recent in-situ magnetospheric measurements are also included. Space weather activities A research consortium operates the Tasman International Geospace Environment Radar (TIGER), an HF southward pointing auroral radar operating from Hobart (Tasmania). A second cooperative radar (Unwin radar) is being constructed in the South Island of New Zealand. This will intersect with TIGER over the auroral zone and enhance the ability of the radar to image the surge of currents that herald space environment changes entering the Polar Regions. Launched in November 2002, the micro satellite FEDSAT, operated by the Cooperative Research Centre for Satellite Systems, has led to successful space science programs and data streams. FEDSAT is making measurements of the magnetic field over Australia and higher latitudes. It also carries a

  17. Integrating Real-time and Manual Monitored Soil Moisture Data to Predict Hillslope Soil Moisture Variations with High Temporal Resolutions

    NASA Astrophysics Data System (ADS)

    Zhu, Qing; Lv, Ligang; Zhou, Zhiwen; Liao, Kaihua

    2016-04-01

    Spatial-temporal variability of soil moisture 15 has been remaining an challenge to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time soil moisture monitoring methods. This restricted the comprehensive and intensive examination of soil moisture dynamics. In this study, we aimed to integrate the manual and real-time monitored soil moisture to depict the hillslope dynamics of soil moisture with good spatial coverage and temporal resolution. Linear (stepwise multiple linear regression-SMLR) and non-linear models (support vector machines-SVM) were used to predict soil moisture at 38 manual sites (collected 1-2 times per month) with soil moisture automatically collected at three real-time monitoring sites (collected every 5 mins). By comparing the accuracies of SMLR and SVM for each manual site, optimal soil moisture prediction model of this site was then determined. Results show that soil moisture at these 38 manual sites can be reliably predicted (root mean square errors<0.035 m3 m-3) using this approach. Absence or occurrence of subsurface flow can probably influence the choosing of SMLR or SVM in the prediction, respectively. Depth to bedrock, elevation, topographic wetness index, profile curvature, and relative difference of soil moisture and its standard deviation influenced the selection of prediction model since they related to the dynamics of soil water distribution and movement. By using this approach, hillslope soil moisture spatial distributions at un-sampled times and dates were predicted after a typical rainfall event. Missing information of hillslope soil moisture dynamics was then acquired successfully. This can be benefit for determining the hot spots and moments of soil water movement, as well as designing the proper soil moisture monitoring plan at the field scale.

  18. Coping with drought: A High Resolution Drought Monitoring and Prediction System for the Pacific Northwest

    NASA Astrophysics Data System (ADS)

    Xiao, M.; Nijssen, B.; Shukla, S.; Lettenmaier, D. P.

    2013-12-01

    The Pacific Northwest (PNW) region in North America (defined here as the Columbia and Klamath River basins plus the coastal drainages) is a diverse geographic region with complex topography and a variety of climates. Agriculture (dryland and irrigated), forestry, fisheries, and hydropower provide significant economic benefit to the region and are directly dependent on the availability of sufficient water at the right time. Additional demands are made on water supplies by recreation, ecosystem services and emerging needs such as hydropower generation in support of wind energy integration. Several major droughts have occurred over the region in recent decades (notably 1977, 2001, and 2004), which have had significant consequences for the region's agricultural, hydropower production, and environment. An emerging need for the region is the coordination of existing regional climate activities, including a better awareness of the current water availability conditions across the region. The University of Washington has operated a surface water monitor for the continental United States since 2005, which provides near real-time estimates of surface water conditions at a spatial resolution of 1/2 degree in terms of soil moisture, snow water equivalent, and total moisture based on a suite of land surface models. A higher resolution Drought Monitoring and Prediction System (DMPS) for Washington State was originally implemented at 1/8 degree and later increased to 1/16 degree. This presentation describes the extension of this system to the entire PNW region at 1/16 degree. The expanded system provides daily updates of three primary drought-related indices based on near real-time station observations in the region: Standardized Precipitation Index (SPI), Standardized Runoff Index (SRI), and Soil Moisture Percentiles (SMP). To make the drought measures relevant to water managers, surface water conditions are not only reported on a gridded map, but watershed-level drought summary

  19. Heron Island, Australia

    NASA Technical Reports Server (NTRS)

    2002-01-01

    Heron Island is located at the sourthern end of Australia's 2,050 km-long Great Barrier Reef. Surrounded by coral reef and home to over 1000 species of fish, scuba divers and scientists alike are drawn to the island's resort and research station. The true-color image above was taken by Space Imaging's Ikonos satellite with a resolution of 4 meters per pixel-high enough to see individual boats tied up at the small marina. The narrow channel leading from the marina to the ocean was blasted and dredged decades ago, before the island became a national park. Since then the Australian government has implemented conservation measures, such as limiting the number of tourists and removing or recycling, instead of incinerating, all trash. One of the applications of remote sensing data from Ikonos is environmental monitoring, including studies of coral reef health. For more information about the island, read Heron Island. Image by Robert Simmon, based on data copyright Space Imaging

  20. Model-based evaluation of subsurface monitoring networks for improved efficiency and predictive certainty of regional groundwater models

    NASA Astrophysics Data System (ADS)

    Gosses, M. J.; Wöhling, Th.; Moore, C. R.; Dann, R.; Scott, D. M.; Close, M.

    2012-04-01

    Groundwater resources worldwide are increasingly under pressure. Demands from different local stakeholders add to the challenge of managing this resource. In response, groundwater models have become popular to make predictions about the impact of different management strategies and to estimate possible impacts of changes in climatic conditions. These models can assist to find optimal management strategies that comply with the various stakeholder needs. Observations of the states of the groundwater system are essential for the calibration and evaluation of groundwater flow models, particularly when they are used to guide the decision making process. On the other hand, installation and maintenance of observation networks are costly. Therefore it is important to design monitoring networks carefully and cost-efficiently. In this study, we analyse the Central Plains groundwater aquifer (~ 4000 km2) between the Rakaia and Waimakariri rivers on the Eastern side of the Southern Alps in New Zealand. The large sedimentary groundwater aquifer is fed by the two alpine rivers and by recharge from the land surface. The area is mainly under agricultural land use and large areas of the land are irrigated. The other major water use is the drinking water supply for the city of Christchurch. The local authority in the region, Environment Canterbury, maintains an extensive groundwater quantity and quality monitoring programme to monitor the effects of land use and discharges on groundwater quality, and the suitability of the groundwater for various uses, especially drinking-water supply. Current and projected irrigation water demand has raised concerns about possible impacts on groundwater-dependent lowland streams. We use predictive uncertainty analysis and the Central Plains steady-state groundwater flow model to evaluate the worth of pressure head observations in the existing groundwater well monitoring network. The data worth of particular observations is dependent on the problem

  1. A model for predicting coolant activity behaviour for fuel-failure monitoring analysis

    NASA Astrophysics Data System (ADS)

    El-Jaby, Ali

    A CANDU fuel element becomes defective when the Zircaloy-4 sheath is breached, allowing high pressure heavy water (D2O) coolant to enter the fuel-to-sheath gap, thereby creating a direct path for fission products (mainly volatile species of iodine and noble gases) and fuel debris to escape into the primary heat transport system (PHTS). In addition, the entry of D 2O coolant into the fuel-to-sheath gap may cause the UO2 fuel to oxidize, which in turn can augment the rate of fission product release into the PHTS. The release of fission products and fuel debris into the PHTS will elevate circuit contamination levels, consequently increasing radiation exposure to station personnel during maintenance tasks. Moreover, the continued operation of a defective fuel element may diminish its thermal performance due to fuel oxidation effects. It is therefore desirable to discharge defective fuel as soon as possible. Hence, a better understanding of defective fuel behaviour is required in order to develop an improved methodology for fuel-failure monitoring and PHTS coolant activity prediction. A mathematical model has been developed to predict the release of volatile fission products from operating defective nuclear fuel elements. The fission product activity in both the fuel-to-sheath gap and PHTS coolant as a function of time can be predicted during all reactor operations including steady-state operation as well as reactor shutdown, startup, and bundle-shifting manoeuvres. In addition, an improved ability to predict the PHTS coolant activity of the 135Xe isotope in commercial reactors is discussed. Moreover, a method to approximate both the burnup and the amount of the tramp uranium deposits in-core, as well as the tramp uranium fission rate is proposed. The model has been implemented as the STAR (Steady-state and Transient Activity Release) stand-alone code written in the C++ programming language using a custom developed finite-difference variable-mesh (FDVM) numerical

  2. Monitoring the incidence and causes of diseases potentially transmitted by food in Australia: Annual report of the OzFoodNet network, 2011.

    PubMed

    2015-06-01

    This report summarises the incidence of diseases potentially transmitted by food in Australia and details outbreaks associated with food in 2011. OzFoodNet sites reported 30,957 notifications of 9 diseases or conditions that may be transmitted by food. The most commonly notified infections were Campylobacter (17,733 notifications) followed by Salmonella (12,271 notifications). The most frequently notified Salmonella serotype was Salmonella Typhimurium, accounting for 48% of all Salmonella notifications. OzFoodNet sites also reported 1,719 outbreaks of gastrointestinal illness affecting 29,839 people and resulting in 872 people being hospitalised and 103 associated deaths. The majority of outbreaks (79% 1,352/1,719) were due to person-to-person transmission, 9% (151/1,719) were suspected or confirmed to be foodborne, 11% (192/1,719) were due to an unknown mode of transmission, 19 were due to community based Salmonella clusters, four were due to waterborne or suspected waterborne transmission and 1 outbreak was due to animal-to-person transmission. Foodborne and suspected foodborne outbreaks affected 2,104 persons and included 231 hospitalisations. There were 5 deaths reported during these outbreaks. Salmonella was the most common aetiological agent identified in foodborne outbreaks and restaurants were the most frequently reported food preparation setting. A single food source of infection was identified for 49 outbreaks, 26 of which were associated with the consumption of dishes containing raw or minimally cooked eggs and all of these outbreaks were due to S. Typhimurium. These data assist agencies to document sources of foodborne disease, develop food safety policies, and prevent foodborne illness. PMID:26234259

  3. Three Conservation Applications of Astronaut Photographs of Earth: Tidal Flat Loss (Japan), Elephant Impacts on Vegetation (Botswana), and Seagrass and Mangrove Monitoring (Australia)

    NASA Technical Reports Server (NTRS)

    Lulla, Kamlesh P.; Robinson, Julie A.; Minorukashiwagi; Maggiesuzuki; Duanenellis, M.; Bussing, Charles E.; Leelong, W. J.; McKenzie, Andlen J.

    2000-01-01

    NASA photographs taken from low Earth orbit can provide information relevant to conservation biology. This data source is now more accessible due to improvements in digitizing technology, Internet file transfer, and availability of image processing software. We present three examples of conservation-related projects that benefited from using orbital photographs. (1) A time series of photographs from the Space Shuttle showing wetland conversion in Japan was used as a tool for communicating about the impacts of tidal flat loss. Real-time communication with astronauts about a newsworthy event resulted in acquiring current imagery. These images and the availability of other high resolution digital images from NASA provided timely public information on the observed changes. (2) A Space Shuttle photograph of Chobe National Park in Botswana was digitally classified and analyzed to identify the locations of elephant-impacted woodland. Field validation later confirmed that areas identified on the image showed evidence of elephant impacts. (3) A summary map from intensive field surveys of seagrasses in Shoalwater Bay, Australia was used as reference data for a supervised classification of a digitized photograph taken from orbit. The classification was able to distinguish seagrasses, sediments and mangroves with accuracy approximating that in studies using other satellite remote sensing data. Orbital photographs are in the public domain and the database of nearly 400,000 photographs from the late 1960s to the present is available at a single searchable location on the Internet. These photographs can be used by conservation biologists for general information about the landscape and in quantitative applications.

  4. Monitoring Dolphins in an Urban Marine System: Total and Effective Population Size Estimates of Indo-Pacific Bottlenose Dolphins in Moreton Bay, Australia

    PubMed Central

    Ansmann, Ina C.; Lanyon, Janet M.; Seddon, Jennifer M.; Parra, Guido J.

    2013-01-01

    Moreton Bay, Queensland, Australia is an area of high biodiversity and conservation value and home to two sympatric sub-populations of Indo-Pacific bottlenose dolphins (Tursiops aduncus). These dolphins live in close proximity to major urban developments. Successful management requires information regarding their abundance. Here, we estimate total and effective population sizes of bottlenose dolphins in Moreton Bay using photo-identification and genetic data collected during boat-based surveys in 2008–2010. Abundance (N) was estimated using open population mark-recapture models based on sighting histories of distinctive individuals. Effective population size (Ne) was estimated using the linkage disequilibrium method based on nuclear genetic data at 20 microsatellite markers in skin samples, and corrected for bias caused by overlapping generations (Nec). A total of 174 sightings of dolphin groups were recorded and 365 different individuals identified. Over the whole of Moreton Bay, a population size N of 554±22.2 (SE) (95% CI: 510–598) was estimated. The southern bay sub-population was small at an estimated N = 193±6.4 (SE) (95% CI: 181–207), while the North sub-population was more numerous, with 446±56 (SE) (95% CI: 336–556) individuals. The small estimated effective population size of the southern sub-population (Nec = 56, 95% CI: 33–128) raises conservation concerns. A power analysis suggested that to reliably detect small (5%) declines in size of this population would require substantial survey effort (>4 years of annual mark-recapture surveys) at the precision levels achieved here. To ensure that ecological as well as genetic diversity within this population of bottlenose dolphins is preserved, we consider that North and South sub-populations should be treated as separate management units. Systematic surveys over smaller areas holding locally-adapted sub-populations are suggested as an alternative method for increasing ability to detect

  5. Improving Radar QPE's in Complex Terrain for Improved Flash Flood Monitoring and Prediction

    NASA Astrophysics Data System (ADS)

    Cifelli, R.; Streubel, D. P.; Reynolds, D.

    2010-12-01

    Quantitative Precipitation Estimation (QPE) is extremely challenging in regions of complex terrain due to a combination of issues related to sampling. In particular, radar beams are often blocked or scan above the liquid precipitation zone while rain gauge density is often too low to properly characterize the spatial distribution of precipitation. Due to poor radar coverage, rain gauge networks are used by the National Weather Service (NWS) River Forecast Centers as the principal source for QPE across the western U.S. The California Nevada River Forecast Center (CNRFC) uses point rainfall measurements and historical rainfall runoff relationships to derive river stage forecasts. The point measurements are interpolated to a 4 km grid using Parameter-elevation Regressions on Independent Slopes Model (PRISM) data to develop a gridded 6-hour QPE product (hereafter referred to as RFC QPE). Local forecast offices can utilize the Multi-sensor Precipitation Estimator (MPE) software to improve local QPE’s and thus local flash flood monitoring and prediction. MPE uses radar and rain gauge data to develop a combined QPE product at 1-hour intervals. The rain gauge information is used to bias correct the radar precipitation estimates so that, in situations where the rain gauge density and radar coverage are adequate, MPE can take advantage of the spatial coverage of the radar and the “ground truth” of the rain gauges to provide an accurate QPE. The MPE 1-hour QPE analysis should provide better spatial and temporal resolution for short duration hydrologic events as compared to 6-hour analyses. These hourly QPEs are then used to correct radar derived rain rates used by the Flash Flood Monitoring and Prediction (FFMP) software in forecast offices for issuance of flash flood warnings. Although widely used by forecasters across the eastern U.S., MPE is not used extensively by the NWS in the west. Part of the reason for the lack of use of MPE across the west is that there has

  6. Online Training in Australia

    ERIC Educational Resources Information Center

    Kuzic, Joze

    2013-01-01

    On-line training is becoming an interesting phenomenon in Australia and has attracted a lot of interest across many industries and businesses (Chan and Ngai, 2007). The research reported here looks at the use of online training in corporations in Australia. It focuses on two aspects of online training, the factors that "warrant" its…

  7. Community Music in Australia

    ERIC Educational Resources Information Center

    Harrison, Gillian

    2010-01-01

    This paper presents a historical perspective to the development of community music in Australia. Finding political support in Australia's progressive arts policies of the late 1970s, community music is discussed as embracing the principles of access and equity and supporting the development of musical skills in the context of social change and…

  8. Lake Eyre, Simpson Desert, South Australia, Australia

    NASA Technical Reports Server (NTRS)

    1990-01-01

    Lake Eyre, Simpson Desert, South Australia, Australia (27.0S, 136.0E) is normally a dry lakebed for years on end. However on rare occasions small amounts of rainfall are recorded and ponding can be seen in low parts of the lake, as in this image, where an algae bloom in the water is seen as a dark pink area on the lakebed. The Finke Riverbed intersects Lake Eyre but it is normally a dry wash and seldom contributes water to the lake.

  9. Women Astronomers: Australia: Women astronomers in Australia

    NASA Astrophysics Data System (ADS)

    Bhathal, Ragbir

    2001-08-01

    Ragbir Bhathal summarizes the role played by women astronomers in Australia's astronomy, now and in the past. Australia has a great tradition in astronomy, from the early observations of Aboriginal people through the colonial drive to explore and understand, culminating in the established excellence of research there today. Women have contributed to this achievement in no small way, yet their contribution has been unremarked, if not ignored. Here I summarize the historical and present state of affairs and look forward to a brighter and more equitable future.

  10. Using prediction uncertainty analysis to design hydrologic monitoring networks: Example applications from the Great Lakes water availability pilot project

    USGS Publications Warehouse

    Fienen, Michael N.; Doherty, John E.; Hunt, Randall J.; Reeves, Howard W.

    2010-01-01

    The importance of monitoring networks for resource-management decisions is becoming more recognized, in both theory and application. Quantitative computer models provide a science-based framework to evaluate the efficacy and efficiency of existing and possible future monitoring networks. In the study described herein, two suites of tools were used to evaluate the worth of new data for specific predictions, which in turn can support efficient use of resources needed to construct a monitoring network. The approach evaluates the uncertainty of a model prediction and, by using linear propagation of uncertainty, estimates how much uncertainty could be reduced if the model were calibrated with addition information (increased a priori knowledge of parameter values or new observations). The theoretical underpinnings of the two suites of tools addressing this technique are compared, and their application to a hypothetical model based on a local model inset into the Great Lakes Water Availability Pilot model are described. Results show that meaningful guidance for monitoring network design can be obtained by using the methods explored. The validity of this guidance depends substantially on the parameterization as well; hence, parameterization must be considered not only when designing the parameter-estimation paradigm but also-importantly-when designing the prediction-uncertainty paradigm.

  11. Comparison of model predictions with the data of an urban air quality monitoring network in Izmir, Turkey

    NASA Astrophysics Data System (ADS)

    Elbir, Tolga

    The CALMET meteorological model and its puff dispersion model CALPUFF were used to predict dispersion of the sulfur dioxide emissions from industrial and domestic heating sources in Izmir, the third biggest province in Turkey. The modeling domain covered an area of 80×100 km centered at the metropolitan area of Izmir with grid spacing of 1000 m. Statistical analyses were carried out to evaluate the model performance by comparing the predicted and measured time series of sulfur dioxide concentrations at four monitoring stations using two main methods: root of the mean square error (RMSE) and an index of agreement (d). The index of agreement varied from 0.51 to 0.77 at four monitoring stations and the total RMSE ranged from 0.36 to 0.66 for the year 2000. The overall model performance for four monitoring stations was found good with an accuracy of about 68%. The agreement of model predictions and measurements was better for two urban monitoring stations (Karsiyaka and Bornova), compared with the other urban stations (Alsancak and Konak).

  12. Tritium monitoring in groundwater and evaluation of model predictions for the Hanford Site 200 Area Effluent Treatment Facility

    SciTech Connect

    Barnett, D.B.; Bergeron, M.P.; Cole, C.R.; Freshley, M.D.; Wurstner, S.K.

    1997-08-01

    The Effluent Treatment Facility (ETF) disposal site, also known as the State-Approved Land Disposal Site (SALDS), receives treated effluent containing tritium, which is allowed to infiltrate through the soil column to the water table. Tritium was first detected in groundwater monitoring wells around the facility in July 1996. The SALDS groundwater monitoring plan requires revision of a predictive groundwater model and reevaluation of the monitoring well network one year from the first detection of tritium in groundwater. This document is written primarily to satisfy these requirements and to report on analytical results for tritium in the SALDS groundwater monitoring network through April 1997. The document also recommends an approach to continued groundwater monitoring for tritium at the SALDS. Comparison of numerical groundwater models applied over the last several years indicate that earlier predictions, which show tritium from the SALDS approaching the Columbia River, were too simplified or overly robust in source assumptions. The most recent modeling indicates that concentrations of tritium above 500 pCi/L will extend, at most, no further than {approximately}1.5 km from the facility, using the most reasonable projections of ETF operation. This extent encompasses only the wells in the current SALDS tritium-tracking network.

  13. Sensor-model prediction, monitoring and in-situ control of liquid RTM advanced fiber architecture composite processing

    NASA Astrophysics Data System (ADS)

    Kranbuehl, D.; Kingsley, P.; Hart, S.; Loos, A.; Hasko, G.; Dexter, B.

    In-situ frequency dependent electromagnetic sensors (FDEMS) and the Loos resin transfer model have been used to select and control the processing properties of an epoxy resin during liquid pressure RTM impregnation and cure. Once correlated with viscosity and degree of cure the FDEMS sensor monitors and the RTM processing model predicts the reaction advancement of the resin, viscosity and the impregnation of the fabric. This provides a direct means for predicting, monitoring, and controlling the liquid RTM process in-situ in the mold throughout the fabrication process and the effects of time, temperature, vacuum and pressure. Most importantly, the FDEMS-sensor model system has been developed to make intelligent decisions, thereby automating the liquid RTM process and removing the need for operator direction.

  14. Sensor-model prediction, monitoring and in-situ control of liquid RTM advanced fiber architecture composite processing

    NASA Technical Reports Server (NTRS)

    Kranbuehl, D.; Kingsley, P.; Hart, S.; Loos, A.; Hasko, G.; Dexter, B.

    1992-01-01

    In-situ frequency dependent electromagnetic sensors (FDEMS) and the Loos resin transfer model have been used to select and control the processing properties of an epoxy resin during liquid pressure RTM impregnation and cure. Once correlated with viscosity and degree of cure the FDEMS sensor monitors and the RTM processing model predicts the reaction advancement of the resin, viscosity and the impregnation of the fabric. This provides a direct means for predicting, monitoring, and controlling the liquid RTM process in-situ in the mold throughout the fabrication process and the effects of time, temperature, vacuum and pressure. Most importantly, the FDEMS-sensor model system has been developed to make intelligent decisions, thereby automating the liquid RTM process and removing the need for operator direction.

  15. Predicted decline of protected whales based on molecular genetic monitoring of Japanese and Korean markets.

    PubMed

    Baker, C S; Lento, G M; Cipriano, F; Palumbi, S R

    2000-06-22

    the International Whaling Commission. For the range of exploitation consistent with the market sample, this protected stock was predicted to decline towards extinction over the next few decades. These results confirmed the power of molecular methods in monitoring retail markets and pointed to the inadequacy of the current moratorium for ensuring the recovery of protected species. More importantly, the integration of genetic evidence with a model of population dynamics identified an urgent need for actions to limit undocumented exploitation of a 'protected' stock of whales. PMID:10902685

  16. Predicted decline of protected whales based on molecular genetic monitoring of Japanese and Korean markets.

    PubMed Central

    Baker, C S; Lento, G M; Cipriano, F; Palumbi, S R

    2000-01-01

    the International Whaling Commission. For the range of exploitation consistent with the market sample, this protected stock was predicted to decline towards extinction over the next few decades. These results confirmed the power of molecular methods in monitoring retail markets and pointed to the inadequacy of the current moratorium for ensuring the recovery of protected species. More importantly, the integration of genetic evidence with a model of population dynamics identified an urgent need for actions to limit undocumented exploitation of a 'protected' stock of whales. PMID:10902685

  17. Monitoring and restabilizing structures under external excitations through detection and prediction of changes in structural properties

    NASA Astrophysics Data System (ADS)

    Sebastijanovic, Nebojsa

    The primary goal of this dissertation is the development of methods for prediction and detection of damage in structures under external excitations through the use of sensors and actuators. The first example involves developing an active flutter suppression algorithm for a flat panel in flight and space vehicles using embedded piezoceramic actuators. A basic eigenvector orientation approach is used to evaluate the possibility of controlling the onset of panel flutter. Eigenvectors for two consecutive modes are usually orthogonal and the onset of flutter condition can be observed earlier as they start to lose their orthogonality. Piezoelectric layers are assumed to be bonded to the top and bottom surfaces of the panel in order to provide counter-bending moments at joints between elements. The controllers are designed to modify the stiffness of the structure and re-stabilize the system; as a result, flutter occurrence can be offset to a higher flutter speed. To illustrate the applicability and effectiveness of the developed method, several simple wide beam examples using piezoelectric layers as actuators are studied and presented. Controllers based on different control objectives are considered and the effects of control moment locations are studied. Potential applications of this basic method may be straightforwardly applied to plate and shell structures of laminated composites. The second example includes developing a method for detecting, locating, and quantifying structural damage using acceleration measurements as feedback. This method directly uses time domain structural vibration measurements and the effects of different damages are decoupled in the controller design. The effectiveness of the proposed method is evaluated with illustrative examples of a three and an eight-story model as well as a single story steel frame model with changes in joint flexibility. Finally, the progress on developing a hybrid structural health monitoring system is presented through

  18. On the identification of representative in situ soil moisture monitoring stations for the validation of SMAP soil moisture products in Australia

    NASA Astrophysics Data System (ADS)

    Yee, Mei Sun; Walker, Jeffrey P.; Monerris, Alessandra; Rüdiger, Christoph; Jackson, Thomas J.

    2016-06-01

    The high spatio-temporal variability of soil moisture complicates the validation of remotely sensed soil moisture products using in situ monitoring stations. Therefore, a standard methodology for selecting the most representative stations for the purpose of validating satellites and land surface models is essential. Based on temporal stability and geostatistical studies using long-term soil moisture records, intensive ground measurements and airborne soil moisture products, this study investigates the representativeness of soil moisture monitoring stations within the Yanco study area for the validation of NASA's Soil Moisture Active Passive (SMAP) products at 3 km for radar, 9 km for radar-radiometer and 36 km for radiometer pixels. This resulted in the identification of a number of representative stations according to the different scales. Although the temporal stability method was found to be suitable for identifying representative stations, stations based on the mean relative difference (MRD) were not necessarily the most representative of the areal average. Moreover, those identified from standard deviation of the relative difference (SDRD) may be dry-biased. It was also found that in the presence of heterogeneous land use, stations should be weighted based on proportions of agricultural land. Airborne soil moisture products were also shown to provide useful a priori information for identifying representative locations. Finally, recommendations are made regarding the design of future networks for satellite validation, and specifically the most representative stations for the Yanco area.

  19. Early evidence about the predicted unintended consequences of standardised packaging of tobacco products in Australia: a cross-sectional study of the place of purchase, regular brands and use of illicit tobacco

    PubMed Central

    Scollo, Michelle; Zacher, Meghan; Durkin, Sarah; Wakefield, Melanie

    2014-01-01

    Objectives To test for early evidence whether, following the standardisation of tobacco packaging, smokers in Australia were—as predicted by the tobacco industry—less likely to purchase from small mixed business retailers, more likely to purchase cheap brands imported from Asia and more likely to use illicit tobacco. Design Serial cross-sectional population telephone surveys in November 2011 (a year prior to implementation), 2012 (during roll-out) and 2013 (a year after implementation). Setting/participants Smokers aged 18 years and over identified in an annual population survey in the Australian state of Victoria (2011: n=754; 2012: n=590; 2013: n=601). Main outcome measures Changes between 2011 and 2013 in: proportions of current smokers who purchased their last cigarette from discount outlets such as supermarkets compared with small mixed business retail outlets; prevalence of regular use of low-cost brands imported from Asia and use of unbranded tobacco. Results The proportion of smokers purchasing from supermarkets did not increase between 2011 (65.4%) and 2013 (65.7%; p=0.98), and the percentage purchasing from small mixed business outlets did not decline (2011: 9.2%; 2012: 11.2%; p=0.32). The prevalence of low-cost Asian brands was low and did not increase between 2011 (1.1%) and 2013 (0.9%; p=0.98). The proportion reporting current use of unbranded illicit tobacco was 2.3% in 2011 and 1.9% in 2013 (p=0.46). In 2013, 2.6% of cigarette smokers reported having purchased one or more packets of cigarettes in non-compliant packaging in the past 3 months; 1.7% had purchased one or more packets from an informal seller in the past year. Conclusions One year after implementation, this study found no evidence of the major unintended consequences concerning loss of smoker patrons from small retail outlets, flooding of the market by cheap Asian brands and use of illicit tobacco predicted by opponents of plain packaging in Australia. PMID:25168041

  20. Incorporating remote sensing data in crop model to monitor crop growth and predict yield in regional area

    NASA Astrophysics Data System (ADS)

    Guo, Jianmao; Lu, Weisong; Zhang, Guoping; Qian, Yonglan; Yu, Qiang; Zhang, Jiahua

    2006-12-01

    Accurate crop growth monitoring and yield predicting is very important to food security and agricultural sustainable development. Crop models can be forceful tools for monitoring crop growth status and predicting yield over homogeneous areas, however, their application to a larger spatial domains is hampered by lack of sufficient spatial information about model inputs, such as the value of some of their parameters and initial conditions, which may have great difference between regions even fields. The use of remote sensing data helps to overcome this problem. By incorporating remote sensing data into the WOFOST crop model (through LAI), it is possible to incorporate remote sensing variables (vegetation index) for each point of the spatial domain, and it is possible for this point to re-estimate new values of the parameters or initial conditions, to which the model is particularly sensitive. This paper describes the use of such a method on a local scale, for winter wheat, focusing on the parameters describing emergence and early crop growth. These processes vary greatly depending on the soil, climate and seedbed preparation, and affect yield significantly. The WOFOST crop model is calibrated under standard conditions and then evaluated under test conditions to which the emergence and early growth parameters of the WOFOST model are adjusted by incorporating remote sensing data. The inversion of the combined model allows us to accurately monitoring crop growth status and predicting yield on a regional scale.

  1. Drought monitoring through parallel computing

    SciTech Connect

    Burrage, K.; Belward, J.; Lau, L.; Rezny, M.; Young, R.

    1993-12-31

    One area where high performance computing can make a significant social and economic impact in Australia (especially in view of the recent El-Nino) is in the accurate and efficient monitoring and prediction of drought conditions - both in terms of speed of calculation and in high quality visualization. As a consequence, the Queensland Department of Primary Industries (DPI) is developing a spatial model of pasture growth and utilization for monitoring, assessment and prediction of the future of the state`s rangeloads. This system incorporates soil class, pasture type, tree cover, herbivore density and meterological data. DPI`s drought research program aims to predict the occurrence of feed deficits and land condition alerts on a quarter to half shire basis over Queensland. This will provide a basis for large-scale management decisions by graziers and politicians alike.

  2. MOBILESAT: Australia's own

    NASA Technical Reports Server (NTRS)

    Wagg, Michael

    1990-01-01

    Australia will be introducing a dedicated Mobile Satellite Communications System following the launch of the AUSSAT-B satellites late in 1991. The Mobile Satellite System, MOBILESAT, will provide circuit switched voice/data services and packet-switched data services for land, aeronautical and maritime users. Here, an overview is given of the development program being undertaken within Australia to enable a fully commercial service to be introduced in 1992.

  3. Monitoring and modeling the multi-time-scale seismic hazard of the southern Longmenshan fault: an experimental design of the `monitoring and modeling for prediction' system

    NASA Astrophysics Data System (ADS)

    Wu, Z.; Li, L.; Liu, G.; Jiang, C.; Ma, H.

    2010-12-01

    To the southwest of the WFSD-I and WFSD-II is the southern part of the Longmenshan fault, which has been keeping quiet since the May 12, 2008, Wenchuan earthquake which ruptured the middle and the northern part of the Longmenshan fault zone. The seismic hazard in this reason is one of the concerns not only in the WFSD project but also in the regional sustainability. This presentation tries to discuss the following three major problems related to the seismic hazard of this fault segment: 1) If there were a major earthquake rupturing this fault segment, what would be the ‘scenario rupture’ preparing and occurring; 2) Based on this concept of ‘scenario rupture’, how to design the ‘monitoring and modeling for prediction’ system in this region, for the effective constraint of geodynamic models for earthquake preparation, the effective monitoring of potentially pre-seismic changes of geophysical fields, and the effective test of the predictive models and/or algorithms; and 3) what will be the potential contribution of the WFSD project, in both long-term sense and short-term sense, to the monitoring and modeling of seismic hazard in this region. In considering these three questions, lessons and experiences from the Wenchuan earthquake plays an important role, and the relation between the Xianshuihe fault and the Longmenshan fault is one of the critical issues subject to consideration. Considering the state-of-the-art of earthquake science and social needs, the monitoring and modeling endeavor should be dealing with different time scales considering both scientific issues and decision-making issues. Taking the lessons and experiences of the previously-conducted earthquake prediction experiment sites, we propose a concept ‘seismological engineering’ (which is different from either ‘earthquake engineering’ or ‘engineering seismology’) dealing with the design of the operational multi-disciplinary observation system oriented at the monitoring and

  4. Predictable pollution: an assessment of weather balloons and associated impacts on the marine environment--an example for the Great Barrier Reef, Australia.

    PubMed

    O'Shea, Owen R; Hamann, Mark; Smith, Walter; Taylor, Heidi

    2014-02-15

    Efforts to curb pollution in the marine environment are covered by national and international legislation, yet weather balloons are released into the environment with no salvage agenda. Here, we assess impacts associated with weather balloons in the Great Barrier Reef World Heritage Area (GBRWHA). We use modeling to assess the probability of ocean endpoints for released weather balloons and predict pathways post-release. In addition, we use 21 months of data from beach cleanup events to validate our results and assess the abundance and frequency of weather balloon fragments in the GBRWHA. We found between 65% and 70% of balloons land in the ocean and ocean currents largely determine final endpoints. Beach cleanup data revealed 2460 weather balloon fragments were recovered from 24 sites within the GBRWHA. This is the first attempt to quantify this problem and these data will add support to a much-needed mitigation strategy for weather balloon waste. PMID:24434000

  5. Prediction of landslide activation at locations in Beskidy Mountains using standard and real-time monitoring methods

    NASA Astrophysics Data System (ADS)

    Bednarczyk, Z.

    2012-04-01

    The paper presents landslide monitoring methods used for prediction of landslide activity at locations in the Carpathian Mountains (SE Poland). Different types of monitoring methods included standard and real-time early warning measurement with use of hourly data transfer to the Internet were used. Project financed from the EU funds was carried out for the purpose of public road reconstruction. Landslides with low displacement rates (varying from few mm to over 5cm/year) had size of 0.4-2.2mln m3. Flysch layers involved in mass movements represented mixture of clayey soils and sandstones of high moisture content and plasticity. Core sampling and GPR scanning were used for recognition of landslide size and depths. Laboratory research included index, IL oedometer, triaxial and direct shear laboratory tests. GPS-RTK mapping was employed for actualization of landslide morphology. Instrumentation consisted of standard inclinometers, piezometers and pore pressure transducers. Measurements were carried 2006-2011, every month. In May 2010 the first in Poland real-time monitoring system was installed at landslide complex over the Szymark-Bystra public road. It included in-place uniaxial sensors and 3D continuous inclinometers installed to the depths of 12-16m with tilt sensors every 0.5m. Vibrating wire pore pressure and groundwater level transducers together with automatic meteorological station analyzed groundwater and weather conditions. Obtained monitoring and field investigations data provided parameters for LEM and FEM slope stability analysis. They enabled prediction and control of landslide behaviour before, during and after stabilization or partly stabilization works. In May 2010 after the maximum precipitation (100mm/3hours) the rates of observed displacements accelerated to over 11cm in a few days and damaged few standard inclinometer installations. However permanent control of the road area was possible by continuous inclinometer installations. Comprehensive

  6. Evaluation of the ability of three physical activity monitors to predict weight change and estimate energy expenditure.

    PubMed

    Correa, John B; Apolzan, John W; Shepard, Desti N; Heil, Daniel P; Rood, Jennifer C; Martin, Corby K

    2016-07-01

    Activity monitors such as the Actical accelerometer, the Sensewear armband, and the Intelligent Device for Energy Expenditure and Activity (IDEEA) are commonly validated against gold standards (e.g., doubly labeled water, or DLW) to determine whether they accurately measure total daily energy expenditure (TEE) or activity energy expenditure (AEE). However, little research has assessed whether these parameters or others (e.g., posture allocation) predict body weight change over time. The aims of this study were to (i) test whether estimated energy expenditure or posture allocation from the devices was associated with weight change during and following a low-calorie diet (LCD) and (ii) compare free-living TEE and AEE predictions from the devices against DLW before weight change. Eighty-seven participants from 2 clinical trials wore 2 of the 3 devices simultaneously for 1 week of a 2-week DLW period. Participants then completed an 8-week LCD and were weighed at the start and end of the LCD and 6 and 12 months after the LCD. More time spent walking at baseline, measured by the IDEEA, significantly predicted greater weight loss during the 8-week LCD. Measures of posture allocation demonstrated medium effect sizes in their relationships with weight change. Bland-Altman analyses indicated that the Sensewear and the IDEEA accurately estimated TEE, and the IDEEA accurately measured AEE. The results suggest that the ability of energy expenditure and posture allocation to predict weight change is limited, and the accuracy of TEE and AEE measurements varies across activity monitoring devices, with multi-sensor monitors demonstrating stronger validity. PMID:27270210

  7. Analysis of long-term water quality for effective river health monitoring in peri-urban landscapes--a case study of the Hawkesbury-Nepean river system in NSW, Australia.

    PubMed

    Pinto, U; Maheshwari, B L; Ollerton, R L

    2013-06-01

    The Hawkesbury-Nepean River (HNR) system in South-Eastern Australia is the main source of water supply for the Sydney Metropolitan area and is one of the more complex river systems due to the influence of urbanisation and other activities in the peri-urban landscape through which it flows. The long-term monitoring of river water quality is likely to suffer from data gaps due to funding cuts, changes in priority and related reasons. Nevertheless, we need to assess river health based on the available information. In this study, we demonstrated how the Factor Analysis (FA), Hierarchical Agglomerative Cluster Analysis (HACA) and Trend Analysis (TA) can be applied to evaluate long-term historic data sets. Six water quality parameters, viz., temperature, chlorophyll-a, dissolved oxygen, oxides of nitrogen, suspended solids and reactive silicates, measured at weekly intervals between 1985 and 2008 at 12 monitoring stations located along the 300 km length of the HNR system were evaluated to understand the human and natural influences on the river system in a peri-urban landscape. The application of FA extracted three latent factors which explained more than 70 % of the total variance of the data and related to the 'bio-geographical', 'natural' and 'nutrient pollutant' dimensions of the HNR system. The bio-geographical and nutrient pollution factors more likely related to the direct influence of changes and activities of peri-urban natures and accounted for approximately 50 % of variability in water quality. The application of HACA indicated two major clusters representing clean and polluted zones of the river. On the spatial scale, one cluster was represented by the upper and lower sections of the river (clean zone) and accounted for approximately 158 km of the river. The other cluster was represented by the middle section (polluted zone) with a length of approximately 98 km. Trend Analysis indicated how the point sources influence river water quality on spatio

  8. Autonomous monitoring of control hardware to predict off-normal conditions using NIF automatic Alignment Systems

    SciTech Connect

    Awwal, A; Wilhelmsen, K; Leach, R; Kamm, V M; Burkhart, S; Lowe-Webb, R; Cohen, S

    2011-07-20

    The National Ignition Facility (NIF) is a high power laser system capable of supporting high-energy-density experimentation as a user facility for the next 30 years. In order to maximize the facility availability, preventive maintenance enhancements are being introduced into the system. An example of such an enhancement is a camera-based health monitoring system, integrated into the automated alignment system, which provides an opportunity to monitor trends in measurements such as average beam intensity, size of the beam, and pixel saturation. The monitoring system will generate alerts based on observed trends in measurements to allow scheduled pro-active maintenance before routine off-normal detection stops system operations requiring unscheduled intervention.

  9. Decision analyses for optimization of monitoring networks based on uncertainty quantification of model predictions of contaminant transport

    NASA Astrophysics Data System (ADS)

    Vesselinov, V. V.; Harp, D.

    2011-12-01

    Model-based decision making related to environmental management problems is a challenging problem. There has been substantial theoretical research and practical applications related to this problem. However, there are very few cases in which the actual decision analyses have been tested in the field to evaluate their adequacy. Over the last several years, we have performed a series of decision analyses to support optimization of a monitoring network at the Los Alamos National Laboratory (LANL) site. The problem deals with contaminant transport in the regional aquifer beneath the LANL site. At three separate stages, the existing monitoring network was augmented based on analyses of the existing uncertainties; in total, five new monitoring wells were proposed. At each stage, the data collected at the new monitoring wells demonstrated the adequacy of the prior uncertainty and decision analyses. The decision analyses required a detailed estimation of uncertainties in model predictions. Various uncertainties, including measurement errors and uncertainties in the conceptualization and model parameters, contributed to the uncertainties in the model predictions. The decision analyses were computationally intensive requiring on the order of one million model simulations; computational efficiency is achieved using (1) high-performance computing (LANL multiprocessor clusters), (2) novel computational techniques for model analysis, and (3) a simple analytical 3D simulator to simulate contaminant transport. Decision support related to optimal design of monitoring networks required optimization of the proposed new monitoring well locations in order to reduce existing model-prediction uncertainties and environmental risk. An important aspect of the analysis is the application of novel techniques for optimization (SQUADS based on coupling of Particle Swarm and Levenberg-Marquardt optimization methods; Vesselinov & Harp, 2011) and uncertainty quantification (ABAGUS: Agent

  10. Monitoring

    DOEpatents

    Orr, Christopher Henry; Luff, Craig Janson; Dockray, Thomas; Macarthur, Duncan Whittemore

    2004-11-23

    The invention provides apparatus and methods which facilitate movement of an instrument relative to an item or location being monitored and/or the item or location relative to the instrument, whilst successfully excluding extraneous ions from the detection location. Thus, ions generated by emissions from the item or location can successfully be monitored during movement. The technique employs sealing to exclude such ions, for instance, through an electro-field which attracts and discharges the ions prior to their entering the detecting location and/or using a magnetic field configured to repel the ions away from the detecting location.

  11. Environmental sampling to predict fecal prevalence of Salmonella in an intensively monitored dairy herd

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Although dairy cattle are known reservoirs for salmonellae, cattle that are shedding this organism are often asymptomatic and difficult to identify. A dairy herd that was experiencing an outbreak of Salmonella enterica subsp. enterica Cerro was monitored for two years. Fecal samples from the lacta...

  12. A predictive model for anti-degradation monitoring of the Delaware River mainstem

    EPA Science Inventory

    The non-tidal portion of the Delaware River can be considered to be in minimally disturbed condition, but there is increasing pressure on the watershed. Thus, the primary goal of this research was to develop a monitoring tool that can be used by the Delaware River Basin Commissi...

  13. Monitoring and predicting shrink potential and future processing quality of potato tubers

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Long-term storage of potato tubers increases risks, which are often attributed to shrink and quality loss. To minimize shrink and ensure high quality tubers, producers must closely monitor the condition of the crop during storage and make necessary adjustments to management plans. Evaluation procedu...

  14. Individual Differences in Working Memory Capacity Predict Action Monitoring and the Error-Related Negativity

    ERIC Educational Resources Information Center

    Miller, A. Eve; Watson, Jason M.; Strayer, David L.

    2012-01-01

    Neuroscience suggests that the anterior cingulate cortex (ACC) is responsible for conflict monitoring and the detection of errors in cognitive tasks, thereby contributing to the implementation of attentional control. Though individual differences in frontally mediated goal maintenance have clearly been shown to influence outward behavior in…

  15. Model-Based Hookload Monitoring and Prediction at Drilling Rigs using Neural Networks and Forward-Selection Algorithm

    NASA Astrophysics Data System (ADS)

    Arnaout, A.; Fruhwirth, R.; Winter, M.; Esmael, B.; Thonhauser, G.

    2012-04-01

    The use of neural networks and advanced machine learning techniques in the oil & gas industry is a growing trend in the market. Especially in drilling oil & gas wells, prediction and monitoring different drilling parameters is an essential task to prevent serious problems like "Kick", "Lost Circulation" or "Stuck Pipe" among others. The hookload represents the weight load of the drill string at the crane hook. It is one of the most important parameters. During drilling the parameter "Weight on Bit" is controlled by the driller whereby the hookload is the only measure to monitor how much weight on bit is applied to the bit to generate the hole. Any changes in weight on bit will be directly reflected at the hookload. Furthermore any unwanted contact between the drill string and the wellbore - potentially leading to stuck pipe problem - will appear directly in the measurements of the hookload. Therefore comparison of the measured to the predicted hookload will not only give a clear idea on what is happening down-hole, it also enables the prediction of a number of important events that may cause problems in the borehole and yield in some - fortunately rare - cases in catastrophes like blow-outs. Heuristic models using highly sophisticated neural networks were designed for the hookload prediction; the training data sets were prepared in cooperation with drilling experts. Sensor measurements as well as a set of derived feature channels were used as input to the models. The contents of the final data set can be separated into (1) features based on rig operation states, (2) real-time sensors features and (3) features based on physics. A combination of novel neural network architecture - the Completely Connected Perceptron and parallel learning techniques which avoid trapping into local error minima - was used for building the models. In addition automatic network growing algorithms and highly sophisticated stopping criterions offer robust and efficient estimation of the

  16. Tuberculosis notifications in Australia, 2010.

    PubMed

    Bareja, Christina; Waring, Justin; Stapledon, Richard

    2014-03-01

    The National Notifiable Diseases Surveillance System received 1,353 tuberculosis (TB) notifications in 2010, representing a rate of 6.1 cases per 100,000 population. While rates of 5 to 6 cases per 100,000 population for TB have been maintained in Australia, since first achieved in the mid-1980s, there has been a steady increase in incidence over the past decade. The incidence in the Australian-born Indigenous population was 7.5 per 100,000 population, which is 11 times the incidence reported in the Australian-born non-Indigenous population of 0.7 per 100,000 population. Overseas-born people accounted for 90% of all cases notified in 2010 and represented a rate of 24 per 100,000 population. International students have been recognised as an increasingly important group, representing 25% of all overseas-born cases notified in 2010, and are a focus of this report. Household or other close contact with TB or past residence in a high risk country were the most commonly reported risk factors for TB infection. Outcome data for the 2009 TB cohort indicate that treatment success was attained in more than 95% of cases. As Australia continues to contribute to global TB control it is important to maintain good centralised national reporting of TB to identify populations at risk and monitor trends in TB. PMID:25409354

  17. Routine outcome measurement in Australia.

    PubMed

    Burgess, Philip; Pirkis, Jane; Coombs, Tim

    2015-08-01

    Australia has been implementing routine outcome measurement in its specialized public sector mental health services for over a decade. It uses a range of clinician-rated and consumer-rated measures that are administered at set times during episodes of inpatient, ambulatory and community residential episodes of care. Routine outcome measurement is now embedded in service delivery, and data are made available in a variety of ways to different audiences. These data are used by policy-makers and planners to inform decisions about system-wide reforms, by service managers to monitor quality and effectiveness, and by clinicians to guide clinical decision-making and to promote dialogue with consumers. Consumers, carers and the general community can use these data to ensure that services are accountable for the care they deliver. This paper describes the status quo in Australia with respect to routine outcome measurement, discusses the factors that led to its successful implementation, and considers the steps that are necessary for its continued development. PMID:25768326

  18. Individual differences in fifth graders’ reading and language predict their comprehension monitoring development: An eye-movement study

    PubMed Central

    Connor, Carol McDonald; Radach, Ralph; Vorstius, Christian; Day, Stephanie L.; McLean, Leigh; Morrison, Frederick J.

    2015-01-01

    In this study, we investigated fifth-graders’ (n=52) fall literacy, academic language, and motivation, and how these skills predicted fall and spring comprehension monitoring on an eye movement task. Comprehension monitoring was defined as the identification and repair of misunderstandings when reading text. In the eye movement task, children read two sentences; the second included either a plausible or implausible word in the context of the first sentence. Stronger readers had shorter reading times overall suggesting faster processing of text. Generally fifth-graders reacted to the implausible word (i.e., longer gaze duration on the implausible v. the plausible word, which reflects lexical access). Students with stronger academic language, compared to those with weaker academic language, generally spent more time re-reading the implausible target compared to the plausible target. This difference increased from fall to spring. Results support the centrality of academic language for meaning integration, setting standards of coherence, and utilizing comprehension repair strategies. PMID:27065721

  19. An Integrated System for Vadose Zone Monitoring, Model Calibration, Performance Assessment, and Prediction (MCAP) in Hanford's T Tank Farm

    NASA Astrophysics Data System (ADS)

    Zhang, Z. F.; Keller, J. M.; Myers, D. A.; Sydnor, H. A.

    2006-12-01

    The Hanford Site has 149 underground single-shell tanks that store hazardous radioactive waste. Many of these tanks and their associated infrastructure (e.g., pipelines, diversion boxes) have leaked. Some of the leaked waste is projected to have entered the groundwater. The largest known leak occurred from the T-106 Tank in 1973. Most of the contaminants from that leak still reside within the vadose zone beneath the T Tank Farm. To minimize movement of this residual contaminant plume, an interim infiltration barrier will be constructed on the ground surface. This barrier is expected to prevent infiltrating water from reaching the plume and moving it further towards groundwater. An integrated system will be used for vadose zone moisture monitoring, model calibration, performance assessment, and prediction (MCAP). The system is to be broadly- designed so that the data can be used for multiple purposes. In addition to monitoring soil water movement both under the proposed barrier and adjacent to it, the collected data can also be used to characterize vadose zone hydraulic properties and to calibrate a numerical model. The calibrated model can then be used to assess the performance of the infiltration barrier and to predict water flow and contaminant transport under conditions with and/or without a barrier. A MCAP system is being applied to the Hanford's T Tank Farm. Soil water content is to be monitored using both neutron and capacitance probes; soil water pressure and soil temperature will be monitored with heat dissipation sensors; and water flux will be measured using water fluxmeters. These instruments will be installed in direct push probe holes advanced by a hydraulic hammer unit. Excluding neutron probe measurements, all data collection and data transmittal will be sent to an automated central server. This design allows measurements to be taken continually and reduces the need for personnel to enter the farm thereby increasing worker safety. It is expected that

  20. Epileptic Seizure Detection and Prediction Based on Continuous Cerebral Blood Flow Monitoring--a Review.

    PubMed

    Tewolde, Senay; Oommen, Kalarickal; Lie, Donald Y C; Zhang, Yuanlin; Chyu, Ming-Chien

    2015-01-01

    Epilepsy is the third most common neurological illness, affecting 1% of the world's population. Despite advances in medicine, about 25 to 30% of the patients do not respond to or cannot tolerate the severe side effects of medical treatment, and surgery is not an option for the majority of patients with epilepsy. The objective of this article is to review the current state of research on seizure detection based on cerebral blood flow (CBF) data acquired by thermal diffusion flowmetry (TDF), and CBF-based seizure prediction. A discussion is provided on the applications, advantages, and disadvantages of TDF in detecting and localizing seizure foci, as well as its role in seizure prediction. Also presented are an overview of the present challenges and possible future research directions (along with methodological guidelines) of the CBF-based seizure detection and prediction methods. PMID:26288885

  1. A water marker monitored by satellites to predict seasonal endemic cholera

    PubMed Central

    JUTLA, ANTARPREET; AKANDA, ALI SHAFQAT; HUQ, ANWAR; FARUQUE, ABU SYED GOLAM; COLWELL, RITA; ISLAM, SHAFIQUL

    2013-01-01

    The ability to predict an occurrence of cholera, a water-related disease, offers a significant public health advantage. Satellite based estimates of chlorophyll, a surrogate for plankton abundance, have been linked to cholera incidence. However, cholera bacteria can survive under a variety of coastal ecological conditions, thus constraining the predictive ability of the chlorophyll, since it provides only an estimate of greenness of seawater. Here, a new remote sensing based index is proposed: Satellite Water Marker (SWM), which estimates condition of coastal water, based on observed variability in the difference between blue (412 nm) and green (555 nm) wavelengths that can be related to seasonal cholera incidence. The index is bounded between physically separable wavelengths for relatively clear (blue) and turbid (green) water. Using SWM, prediction of cholera with reasonable accuracy, with at least two month in advance, can potentially be achieved in the endemic coastal regions. PMID:23878762

  2. A general model for predicting coolant activity behaviour for fuel-failure monitoring analysis

    NASA Astrophysics Data System (ADS)

    El-Jaby, A.; Lewis, B. J.; Thompson, W. T.; Iglesias, F.; Ip, M.

    2010-04-01

    A mathematical treatment has been developed to predict the release of volatile fission products from operating defective nuclear fuel elements. The fission product activity in both the fuel-to-sheath gap and primary heat transport system as a function of time can be predicted during all reactor operating conditions, including: startup, steady-state, shutdown, and bundle-shifting manoeuvres. In addition, an improved ability to predict the coolant activity of the 135Xe isotope in commercial reactors is discussed. A method is also proposed to estimate both the burnup and the amount of tramp uranium deposits in-core. The model has been validated against in-reactor experiments conducted with defective fuel elements containing natural and artificial failures at the Chalk River Laboratories. Lastly, the model has been benchmarked against a defective fuel occurrence in a commercial reactor.

  3. Radar monitoring of hydrology in Maryland's forested coastal plain wetlands: Implications for predicted climate change and improved mapping

    NASA Astrophysics Data System (ADS)

    Weiner Lang, Megan

    Wetlands provide important services to society but Mid-Atlantic wetlands are at high risk for loss, with forested wetlands being especially vulnerable. Hydrology (flooding and soil moisture) controls wetland function and extent but it may be altered due to changes in climate and anthropogenic influence. Wetland hydrology must better understood in order to predict and mitigate the impact of these changes. Broad-scale forested wetland hydrology is difficult to monitor using ground-based and traditional remote sensing methods. C-band synthetic aperture radar (SAR) data could improve the capability to monitor forested wetland hydrology but the abilities and limitations of these data need further investigation. This study examined: (1) the link between climate and wetland hydrology; (2) the ability of ENVISAT SAR (C-HH and C-VV) data to monitor inundation and soil moisture in forested wetlands; (3) limitations inherent to C-band data (incidence angle, polarization, and phenology) when monitoring forested wetland hydrology; and (4) the accuracy of forested wetland maps produced using SAR data. The study was primarily conducted near the Patuxent River in Maryland but the influence of incidence angle was considered along the Roanoke River in North Carolina. This study showed: (1) climate was highly correlated with wetland inundation; (2) significant differences in C-VV and C-HH backscatter existed between forested areas of varying hydrology (uplands and wetlands) throughout the year; (3) C-HH backscatter was better correlated to hydrology than C-VV backscatter; (4) correlations were stronger during the leaf-off season; (5) the difference in backscatter between flooded and non-flooded areas did not sharply decline with incidence angle, as predicted; and (6) maps produced using SAR data had relatively high accuracy levels. Based on these findings, I concluded that hydrology is influenced by climate at the study site, and C-HH data should be able to monitor changes in

  4. The Health Behavior Schedule-II for Diabetes Predicts Self-Monitoring of Blood Glucose

    ERIC Educational Resources Information Center

    Frank, Maxwell T.; Cho, Sungkun; Heiby, Elaine M.; Lee, Chun-I; Lahtela, Adrienne L.

    2006-01-01

    The Health Behavior Schedule-II for Diabetes (HBS-IID) is a 27-item questionnaire that was evaluated as a predictor of self-monitoring of blood glucose (SMBG). The HBS-IID was completed by 96 adults with Type 2 diabetes. Recent glycosylated hemoglobin HbA1c and fasting blood glucose results were taken from participants' medical records. Only 31.3%…

  5. The Challenges of Developing a Framework for Global Water Cycle Monitoring and Prediction (Alfred Wegener Medal Lecture)

    NASA Astrophysics Data System (ADS)

    Wood, Eric F.

    2014-05-01

    The Global Earth Observation System of Systems (GEOSS) Water Strategy ("From Observations to Decisions") recognizes that "water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity", and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the developments at Princeton University towards a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict

  6. Intensity of Territorial Marking Predicts Wolf Reproduction: Implications for Wolf Monitoring

    PubMed Central

    García, Emilio J.

    2014-01-01

    Background The implementation of intensive and complex approaches to monitor large carnivores is resource demanding, restricted to endangered species, small populations, or small distribution ranges. Wolf monitoring over large spatial scales is difficult, but the management of such contentious species requires regular estimations of abundance to guide decision-makers. The integration of wolf marking behaviour with simple sign counts may offer a cost-effective alternative to monitor the status of wolf populations over large spatial scales. Methodology/Principal Findings We used a multi-sampling approach, based on the collection of visual and scent wolf marks (faeces and ground scratching) and the assessment of wolf reproduction using howling and observation points, to test whether the intensity of marking behaviour around the pup-rearing period (summer-autumn) could reflect wolf reproduction. Between 1994 and 2007 we collected 1,964 wolf marks in a total of 1,877 km surveyed and we searched for the pups' presence (1,497 howling and 307 observations points) in 42 sampling sites with a regular presence of wolves (120 sampling sites/year). The number of wolf marks was ca. 3 times higher in sites with a confirmed presence of pups (20.3 vs. 7.2 marks). We found a significant relationship between the number of wolf marks (mean and maximum relative abundance index) and the probability of wolf reproduction. Conclusions/Significance This research establishes a real-time relationship between the intensity of wolf marking behaviour and wolf reproduction. We suggest a conservative cutting point of 0.60 for the probability of wolf reproduction to monitor wolves on a regional scale combined with the use of the mean relative abundance index of wolf marks in a given area. We show how the integration of wolf behaviour with simple sampling procedures permit rapid, real-time, and cost-effective assessments of the breeding status of wolf packs with substantial implications to monitor

  7. COMPLEMENTARY CO-KRIGING: SPATIAL PREDICTION USING DATA COMBINED FROM, SEVERAL POLLUTION MONITORING NETWORKS

    EPA Science Inventory

    We consider the problem of optimal spatial prediction of an environmental variable using data from more than one sampling network. A model incorporating spatial dependence and measurement errors with network-specific biases and variances serves as the basis for the analysis of th...

  8. Healthcare in Australia.

    PubMed

    Dalton-Brown, Sally

    2016-07-01

    No single issue has dominated health practitioners' ethical debates in 2014 in Australia, but a controversial decision on gene patenting and the media focus on "Dr. Death," euthanasia campaigner Dr. Philip Nitschke, have given new life to these two familiar (and global) debates. Currently a dying with dignity bill, drafted by the Australian Green Party, is under examination. The Senate inquiry into the bill received more than 663 submissions, with 57% opposed and 43% in support of the bill, which has now been referred to a Senate committee. Will this be another of Australia's failed attempts to legalize euthanasia? The trial of Dr. Nitschke begins on November 10, 2014. PMID:27348826

  9. Surgery in Australia.

    PubMed

    Clunie, G J

    1994-01-01

    More than 4000 surgeons in Australia provide services to 17.6 million people living in the world's driest continent, with a land mass comparable to that of the United States. The problem of distance has been overcome in large part for the 17% of the population who live in remote areas by modern communication systems and by the Flying Doctor and Flying Surgeon services. For the remaining population, largely clustered on the fertile eastern seaboard, surgical services rival the best in the world, and surgical training, under the control of The Royal Australasian College of Surgeons, has set an example for which Australia can be justifiably proud. PMID:8279935

  10. Near-infrared diffuse optical monitoring of cerebral blood flow and oxygenation for the prediction of vasovagal syncope

    NASA Astrophysics Data System (ADS)

    Cheng, Ran; Shang, Yu; Wang, Siqi; Evans, Joyce M.; Rayapati, Abner; Randall, David C.; Yu, Guoqiang

    2014-01-01

    Significant drops in arterial blood pressure and cerebral hemodynamics have been previously observed during vasovagal syncope (VVS). Continuous and simultaneous monitoring of these physiological variables during VVS is rare, but critical for determining which variable is the most sensitive parameter to predict VVS. The present study used a novel custom-designed diffuse correlation spectroscopy flow-oximeter and a finger plethysmograph to simultaneously monitor relative changes of cerebral blood flow (rCBF), cerebral oxygenation (i.e., oxygenated/deoxygenated/total hemoglobin concentration: r[HbO2]/r[Hb]/rTHC), and mean arterial pressure (rMAP) during 70 deg head-up tilt (HUT) in 14 healthy adults. Six subjects developed presyncope during HUT. Two-stage physiological responses during HUT were observed in the presyncopal group: slow and small changes in measured variables (i.e., Stage I), followed by rapid and dramatic decreases in rMAP, rCBF, r[HbO2], and rTHC (i.e., Stage II). Compared to other physiological variables, rCBF reached its breakpoint between the two stages earliest and had the largest decrease (76±8%) during presyncope. Our results suggest that rCBF has the best sensitivity for the assessment of VVS. Most importantly, a threshold of ˜50% rCBF decline completely separated the subjects from those without presyncope, suggesting its potential for predicting VVS.

  11. Near-infrared diffuse optical monitoring of cerebral blood flow and oxygenation for the prediction of vasovagal syncope

    PubMed Central

    Cheng, Ran; Shang, Yu; Wang, Siqi; Evans, Joyce M.; Rayapati, Abner; Randall, David C.; Yu, Guoqiang

    2014-01-01

    Abstract. Significant drops in arterial blood pressure and cerebral hemodynamics have been previously observed during vasovagal syncope (VVS). Continuous and simultaneous monitoring of these physiological variables during VVS is rare, but critical for determining which variable is the most sensitive parameter to predict VVS. The present study used a novel custom-designed diffuse correlation spectroscopy flow-oximeter and a finger plethysmograph to simultaneously monitor relative changes of cerebral blood flow (rCBF), cerebral oxygenation (i.e., oxygenated/deoxygenated/total hemoglobin concentration: r[HbO2]/r[Hb]/rTHC), and mean arterial pressure (rMAP) during 70 deg head-up tilt (HUT) in 14 healthy adults. Six subjects developed presyncope during HUT. Two-stage physiological responses during HUT were observed in the presyncopal group: slow and small changes in measured variables (i.e., Stage I), followed by rapid and dramatic decreases in rMAP, rCBF, r[HbO2], and rTHC (i.e., Stage II). Compared to other physiological variables, rCBF reached its breakpoint between the two stages earliest and had the largest decrease (76±8%) during presyncope. Our results suggest that rCBF has the best sensitivity for the assessment of VVS. Most importantly, a threshold of ∼50% rCBF decline completely separated the subjects from those without presyncope, suggesting its potential for predicting VVS. PMID:24402372

  12. Monitoring the film coating unit operation and predicting drug dissolution using terahertz pulsed imaging.

    PubMed

    Ho, Louise; Müller, Ronny; Gordon, Keith C; Kleinebudde, Peter; Pepper, Michael; Rades, Thomas; Shen, Yaochun; Taday, Philip F; Zeitler, J Axel

    2009-12-01

    Understanding the coating unit operation is imperative to improve product quality and reduce output risks for coated solid dosage forms. Three batches of sustained-release tablets coated with the same process parameters (pan speed, spray rate, etc.) were subjected to terahertz pulsed imaging (TPI) analysis followed by dissolution testing. Mean dissolution times (MDT) from conventional dissolution testing were correlated with terahertz waveforms, which yielded a multivariate, partial least squares regression (PLS) model with an R(2) of 0.92 for the calibration set and 0.91 for the validation set. This two-component, PLS model was built from batch I that was coated in the same environmental conditions (air temperature, humidity, etc.) to that of batch II but at different environmental conditions from batch III. The MDTs of batch II was predicted in a nondestructive manner with the developed PLS model and the accuracy of the predicted values were subsequently validated with conventional dissolution testing and found to be in good agreement. The terahertz PLS model was also shown to be sensitive to changes in the coating conditions, successfully identifying the larger coating variability in batch III. In this study, we demonstrated that TPI in conjunction with PLS analysis could be employed to assist with film coating process understanding and provide predictions on drug dissolution. PMID:19367620

  13. Using remote sensing and grid-based meteorological datasets for regional soybean crop yield prediction and crop monitoring

    NASA Astrophysics Data System (ADS)

    Mali, Preeti

    Regional crop yield estimations using crop models is a national priority due to its contributions to crop security assessment and food pricing policies. Many of these crop yield assessments are performed using time-consuming, intensive field surveys. This research was initiated to test the applicability of remote sensing and grid-based meteorological model data for providing improved and efficient predictive capabilities for crop bio-productivity. The soybean prediction model (Sinclair model) used in this research, requires daily data inputs to simulate yield which are temperature, precipitation, solar radiation, day length initialization of certain soil moisture parameters for each model run. The traditional meteorological datasets were compared with simulated South American Land Data Assimilation System (SALDAS) meteorological datasets for Sinclair model runs and for initializing soil moisture inputs. Considering the fact that grid-based meteorological data has the resolution of 1/8th of a degree, the estimations demonstrated a reasonable accuracy level and showed promise for increase in efficiency for regional level yield predictions. The research tested daily composited Normalized Difference Vegetation Index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (both AQUA and TERRA platform) and simulated Visible/Infrared Imager Radiometer Suite (VIIRS) sensor product (a new sensor planned to be launched in the near future) for crop growth and development based on phenological events. The AQUA and TERRA fusion based daily MODIS NDVI was utilized to develop a planting date estimation method. The results have shown that daily MODIS composited NDVI values have the capability for enhanced monitoring of soybean crop growth and development. The method was able to predict planting date within +/-3.4 days. A geoprocessing framework for extracting data from the grid data sources was developed. Overall, this study was able to demonstrate the utility of

  14. Teaching about Australia. ERIC Digest.

    ERIC Educational Resources Information Center

    Prior, Warren R.

    Many reasons can be offered for teaching about Australia. The field of Australian studies offers many opportunities for U.S. teachers and students to critically analyze aspects of their own culture, for there are many experiences in the history of Australia that parallel the U.S. experience. Australia and the United States have strong ongoing…

  15. Classification in Australia.

    ERIC Educational Resources Information Center

    McKinlay, John

    Despite some inroads by the Library of Congress Classification and short-lived experimentation with Universal Decimal Classification and Bliss Classification, Dewey Decimal Classification, with its ability in recent editions to be hospitable to local needs, remains the most widely used classification system in Australia. Although supplemented at…

  16. Media Matters in Australia.

    ERIC Educational Resources Information Center

    Daniels, Kell

    1998-01-01

    Describes how a teacher helped transform a K-12 Christian school near Sydney, Australia, from a book-bound media studies program into a hands-on learning experience for students. Various projects allow students to operate advanced equipment, evaluate their own and their peers' work, present research results to the class, and produce live media…

  17. Agricultural Education in Australia.

    ERIC Educational Resources Information Center

    Farquhar, R. N.

    This document is an English-language abstract (approximately 1,500 words) of a comprehensive survey of education and training for agriculture in Australia. The present facilities are described, and then set against estimates of present and future needs. Constructive proposals are made as to how these needs can best be met by agricultural…

  18. Children's Books in Australia.

    ERIC Educational Resources Information Center

    Horn, Vida

    This report, given at a special meeting held in Tehran, describes children's literature in Australia, discussing specifically the background of this literature (the country and early children's books); various influences on the literature, such as the Children's Book Council and children's and school libraries; present-day publishing, including…

  19. English in Australia.

    ERIC Educational Resources Information Center

    Jernudd, Bjorn H.

    This paper provides a review of "English Transported: Essays on Australasian English," edited by W. S. Ramson. The book is a collection of articles on the various types of English spoken mainly in Australia and New Zealand. Articles discuss such varieties as nineteenth and twentieth century Australian English, New Zealand English, Pidgin English…

  20. Australia: a continuing genocide?

    PubMed

    Short, Damien

    2010-01-01

    Debates about genocide in Australia have for the most part focussed on past frontier killings and child removal practices. This article, however, focuses on contemporary culturally destructive policies, and the colonial structures that produce them, through the analytical lens of the concept of genocide. The article begins with a discussion of the meaning of cultural genocide, locating the idea firmly in Lemkin's work before moving on to engage with the debates around Lemkin's distinction between genocide and cultural 'diffusion.' In contrast to those scholars who prefer the word 'ethnocide,' the underlying conceptual contention is that the term 'cultural genocide' simply describes a key method of genocide and should be viewed, without the need for qualification, as genocide. While direct physical killing and genocidal child removal practices may have ceased in Australia, some indigenous activists persuasively contend that genocide is a continuing process in an Australia that has failed to decolonise. Concurring with these views the article argues that the contemporary expression of continuing genocidal relations in Australia can be seen principally, and perversely, in the colonial state's official reconciliation process, native title land rights regime and the recent interventionist 'solutions' to indigenous 'problems' in the Northern Territory. PMID:20941881

  1. Networking in Australia

    ERIC Educational Resources Information Center

    Peake, Dorothy G.

    1976-01-01

    The last few years have seen increasing interest in library networking in Australia from a number of different groups. All the projects have concerned networks of similar libraries and no parallel to U.S.A. developments of networks encompassing a variety of types of libraries has yet appeared. (Author)

  2. Evaluation of calving indicators measured by automated monitoring devices to predict the onset of calving in Holstein dairy cows.

    PubMed

    Ouellet, V; Vasseur, E; Heuwieser, W; Burfeind, O; Maldague, X; Charbonneau, É

    2016-02-01

    Dystocias are common in dairy cows and often adversely affect production, reproduction, animal welfare, labor, and economics within the dairy industry. An automated device that accurately predicts the onset of calving could potentially minimize the effect of dystocias by enabling producers to intervene early. Although many well-documented indicators can detect the imminence of calving, research is limited on their effectiveness to predict calving when measured by automated devices. The objective of this experiment was to determine if a decrease in vaginal temperature (VT), rumination (RT), and lying time (LT), or an increase in lying bouts (LB), as measured by 3 automated devices, could accurately predict the onset of calving within 24, 12, and 6 h. The combination of these 4 calving indicators was also evaluated. Forty-two multiparous Holstein cows housed in tie-stalls were fitted with a temperature logger inserted in the vaginal cavity 7±2 d before their expected calving date; VT was recorded at 1-min intervals. An ear-attached sensor recorded rumination time every hour based on ear movement while an accelerometer fitted to the right hind leg recorded cow position at 1-min intervals. On average, VT were 0.3±0.03°C lower, and RT and LT were 41±17 and 52±28 min lower, respectively, on the calving day compared with the previous 4 d. Cows had 2±1 more LB on the calving day. Of the 4 indicators, a decrease in VT≥0.1°C was best able to predict calving within the next 24 h with a sensitivity of 74%, specificity of 74%, positive and negative predictive values of 51 and 89%, and area under the curve of 0.80. Combining the indicators enhanced the performance to predict calving within the next 24, 12, and 6 h with best overall results obtained by combining the 3 devices for prediction within the next 24 h (sensitivity: 77%, specificity: 77%, positive and negative predictive values: 56 and 90%, area under the curve: 0.82). These results indicate that a device that

  3. Australia: a full house.

    PubMed

    Short, R

    1994-01-01

    Australia had a population of 17.6 million in 1991. In 1992, Australia's population grew at the rate of 1.06%, 0.8% due to natural increase and 0.26% from immigration. The recent Australian Bureau of Statistics Report estimates that it will grow to 18.9 million by the end of the century and 23.1 million by 2025, assuming fertility remains at current levels and net migration stabilizes at 70,000 per annum from the year 2000. The World Bank estimates that Australia's population will stabilize at 25 million some time in the future. Since Australia's politicians and economists fail to understand that the country already has a large enough population, no national population policy has been declared. The Department of Immigration and Ethnic Affairs, responsible for all population issues, gives no thought to the long-term environmental consequences of the rapidly growing population and determines the annual migrant intake simply on the basis of the nation's economic needs, demands from new immigrants for admission of their next of kin, and humanitarian considerations with regard to refugees. Population growth in Australia needs to be checked as soon as possible. Reducing the annual migrant intake to below 50,000, Australia could achieve a stable population of approximately 23 million by 2040; the annual intake of 150,000 immigrants will grow the population to 37 million. The total fertility rate (TFR) has been below replacement level since 1976, but the population's skewed age distribution will cause it to continue to grow through natural increase at the current rate of approximately 0.8% per year for some time to come. Improving educational opportunities for women and ensuring that all have ready access to modern contraception could help produce a further decline in TFR. Moreover, education about contraception must be made a part of every school curriculum. Steps taken now may avert any future flood of millions of ecological refugees from Southeast Asia, particularly

  4. In situ damage monitoring in vibration mechanics: diagnostics and predictive maintenance

    NASA Astrophysics Data System (ADS)

    Basseville, M.; Benveniste, A.; Gach-Devauchelle, B.; Goursat, M.; Bonnecase, D.; Dorey, P.; Prevosto, M.; Olagnon, M.

    1993-09-01

    A system identification approach is presented for damage monitoring in vibration mechanics. Identification, detection, and diagnostics are performed using accelerometer measurements from the system at work so that the excitation is not controlled, usually not observed and may involve turbulent phenomena. Targeted applications include power engineering (rotating machines, core and pipes of nuclear power plants), civil engineering (large buildings subject to hurricanes or earthquakes, bridges, dams, offshore structures), aeronautics (wings and other structures subject to strength), automobile, rail transportation etc. The method is illustrated by a laboratory example, and the results of 3 years industrial usage. This paper is a progress report on a 10 year project involving three people almost permanently. We describe here the whole approach but omit the technical details which are available in previous papers.

  5. Investigation of Bearing Fatigue Damage Life Prediction Using Oil Debris Monitoring

    NASA Technical Reports Server (NTRS)

    Dempsey, Paula J.; Bolander, Nathan; Haynes, Chris; Toms, Allison M.

    2011-01-01

    Research was performed to determine if a diagnostic tool for detecting fatigue damage of helicopter tapered roller bearings can be used to determine remaining useful life (RUL). The taper roller bearings under study were installed on the tail gearbox (TGB) output shaft of UH- 60M helicopters, removed from the helicopters and subsequently installed in a bearing spall propagation test rig. The diagnostic tool was developed and evaluated experimentally by collecting oil debris data during spall progression tests on four bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor was monitored and recorded for the occurrence of pitting damage. Results from the four bearings tested indicate that measuring the debris generated when a bearing outer race begins to spall can be used to indicate bearing damage progression and remaining bearing life.

  6. Real Time On-line Space Research Laboratory Environment Monitoring with Off-line Trend and Prediction Analysis

    NASA Technical Reports Server (NTRS)

    Jules, Kenol; Lin, Paul P.

    2006-01-01

    their g-level contribution to the environment. The system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many Increments of the space station for selected disturbance activities. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential system failure as well as for use by research scientists during their science results analysis. Examples of both real time on-line vibratory disturbance detection and off-line trend analysis are presented in this paper. Several soft computing techniques such as Kohonen s Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

  7. Radon exhalation of hardening concrete: monitoring cement hydration and prediction of radon concentration in construction site.

    PubMed

    Kovler, Konstantin

    2006-01-01

    The unique properties of radon as a noble gas are used for monitoring cement hydration and microstructural transformations in cementitious system. It is found that the radon concentration curve for hydrating cement paste enclosed in the chamber increases from zero (more accurately - background) concentrations, similar to unhydrated cement. However, radon concentrations developed within 3 days in the test chamber containing cement paste were approximately 20 times higher than those of unhydrated cement. This fact proves the importance of microstructural transformations taking place in the process of cement hydration, in comparison with cement grain, which is a time-stable material. It is concluded that monitoring cement hydration by means of radon exhalation method makes it possible to distinguish between three main stages, which are readily seen in the time dependence of radon concentration: stage I (dormant period), stage II (setting and intensive microstructural transformations) and stage III (densification of the structure and drying). The information presented improves our understanding of the main physical mechanisms resulting in the characteristic behavior of radon exhalation in the course of cement hydration. The maximum value of radon exhalation rate observed, when cement sets, can reach 0.6 mBq kg(-1) s(-1) and sometimes exceeds 1.0 mBq kg(-1) s(-1). These values exceed significantly to those known before for cementitious materials. At the same time, the minimum ventilation rate accepted in the design practice (0.5 h(-1)), guarantees that the concentrations in most of the cases will not exceed the action level and that they are not of any radiological concern for construction workers employed in concreting in closed spaces. PMID:16356604

  8. Potential of the Thermal Infrared Wavelength Region to predict semi-arid Soil Surface Properties for Remote Sensing Monitoring

    NASA Astrophysics Data System (ADS)

    Eisele, Andreas; Chabrillat, Sabine; Lau, Ian; Hecker, Christoph; Hewson, Robert; Carter, Dan; Wheaton, Buddy; Ong, Cindy; Cudahy, Thomas John; Kaufmann, Hermann

    2014-05-01

    Digital soil mapping with the means of passive remote sensing basically relies on the soils' spectral characteristics and an appropriate atmospheric window, where electromagnetic radiation transmits without significant attenuation. Traditionally the atmospheric window in the solar-reflective wavelength region (visible, VIS: 0.4 - 0.7 μm; near infrared, NIR: 0.7 - 1.1 μm; shortwave infrared, SWIR: 1.1 - 2.5 μm) has been used to quantify soil surface properties. However, spectral characteristics of semi-arid soils, typically have a coarse quartz rich texture and iron coatings that can limit the prediction of soil surface properties. In this study we investigated the potential of the atmospheric window in the thermal wavelength region (long wave infrared, LWIR: 8 - 14 μm) to predict soil surface properties such as the grain size distribution (texture) and the organic carbon content (SOC) for coarse-textured soils from the Australian wheat belt region. This region suffers soil loss due to wind erosion processes and large scale monitoring techniques, such as remote sensing, is urgently required to observe the dynamic changes of such soil properties. The coarse textured sandy soils of the investigated area require methods, which can measure the special spectral response of the quartz dominated mineralogy with iron oxide enriched grain coatings. By comparison, the spectroscopy using the solar-reflective region has limitations to discriminate such arid soil mineralogy and associated coatings. Such monitoring is important for observing potential desertification trends associated with coarsening of topsoil texture and reduction in SOC. In this laboratory study we identified the relevant LWIR wavelengths to predict these soil surface properties. The results showed the ability of multivariate analyses methods (PLSR) to predict these soil properties from the soil's spectral signature, where the texture parameters (clay and sand content) could be predicted well in the models

  9. Presepsin is an early monitoring biomarker for predicting clinical outcome in patients with sepsis.

    PubMed

    Ali, Fahmy T; Ali, Mohamed A M; Elnakeeb, Mostafa M; Bendary, Heba N M

    2016-09-01

    Despite their undoubted helpfulness in diagnosing sepsis, increased blood C-reactive protein (CRP) and procalcitonin (PCT) levels have been described in many noninfectious conditions. Presepsin is a soluble fragment of the cluster of differentiation 14 involved in pathogen recognition by innate immunity. We aimed to investigate the diagnostic and prognostic performance of presepsin in comparison to PCT and CRP in patients presenting with systemic inflammatory response syndrome (SIRS) and suspected sepsis. Seventy-six subjects were enrolled in this study, including 51 patients with SIRS as well as 25 healthy subjects. Plasma presepsin, PCT and CRP levels were serially measured on admission and at days 1, 3, 7 and 15. Presepsin and PCT yielded similar diagnostic accuracy, whereas presepsin performed significantly better than CRP. Presepsin and PCT showed comparable performance for predicting 28-day mortality, and both biomarkers performed significantly better than CRP. In septic patients, presepsin revealed earlier concentration changes over time when compared to PCT and CRP. Presepsin and PCT could differentiate between septic and non-septic patients with comparable accuracy and both biomarkers showed similar performance for predicting 28-day mortality. Early changes in presepsin concentrations might reflect the appropriateness of the therapeutic modality and could be useful for making effective treatment decisions. PMID:27353646

  10. Temporal epilepsy seizures monitoring and prediction using cross-correlation and chaos theory

    PubMed Central

    Ben-Hamida, Naim; Talbi, Larbi; Lakhssassi, Ahmed; Aouini, Sadok

    2014-01-01

    Temporal seizures due to hippocampal origins are very common among epileptic patients. Presented is a novel seizure prediction approach employing correlation and chaos theories. The early identification of seizure signature allows for various preventive measures to be undertaken. Electro-encephalography signals are spectrally broken down into the following sub-bands: delta; theta; alpha; beta; and gamma. The proposed approach consists of observing a high correlation level between any pair of electrodes for the lower frequencies and a decrease in the Lyapunov index (chaos or entropy) for the higher frequencies. Power spectral density and statistical analysis tools were used to determine threshold levels for the lower frequencies. After studying all five sub-bands, the analysis has revealed that the seizure signature can be extracted from the delta band and the high frequencies. High frequencies are defined as both the gamma band and the ripples occurring within the 60–120 Hz sub-band. To validate the proposed approach, six patients from both sexes and various age groups with temporal epilepsies originating from the hippocampal area were studied using the Freiburg database. An average seizure prediction of 30 min, an anticipation accuracy of 72%, and a false-positive rate of 0% were accomplished throughout 200 h of recording time. PMID:26609376