Science.gov

Sample records for advanced regional prediction

  1. COLLABORATIVE RESEARCH: TOWARDS ADVANCED UNDERSTANDING AND PREDICTIVE CAPABILITY OF CLIMATE CHANGE IN THE ARCTIC USING A HIGH-RESOLUTION REGIONAL ARCTIC CLIMATE SYSTEM MODEL

    SciTech Connect

    Gutowski, William J.

    2013-02-07

    The motivation for this project was to advance the science of climate change and prediction in the Arctic region. Its primary goals were to (i) develop a state-of-the-art Regional Arctic Climate system Model (RACM) including high-resolution atmosphere, land, ocean, sea ice and land hydrology components and (ii) to perform extended numerical experiments using high performance computers to minimize uncertainties and fundamentally improve current predictions of climate change in the northern polar regions. These goals were realized first through evaluation studies of climate system components via one-way coupling experiments. Simulations were then used to examine the effects of advancements in climate component systems on their representation of main physics, time-mean fields and to understand variability signals at scales over many years. As such this research directly addressed some of the major science objectives of the BER Climate Change Research Division (CCRD) regarding the advancement of long-term climate prediction.

  2. Advanced hydrologic prediction system

    NASA Astrophysics Data System (ADS)

    Connelly, Brian A.; Braatz, Dean T.; Halquist, John B.; Deweese, Michael M.; Larson, Lee; Ingram, John J.

    1999-08-01

    As our Nation's population and infrastructure grow, natural disasters are becoming a greater threat to our society's stability. In an average year, inland flooding claims 133 lives and resulting property losses exceed 4.0 billion. Last year, 1997, these losses totaled 8.7 billion. Because of this blossoming threat, the National Weather Service (NWS) has requested funding within its 2000 budget to begin national implementation of the Advanced Hydrologic Prediction System (AHPS). With this system in place the NWS will be able to utilize precipitation and climate predictions to provide extended probabilistic river forecasts for risk-based decisions. In addition to flood and drought mitigation benefits, extended river forecasts will benefit water resource managers in decision making regarding water supply, agriculture, navigation, hydropower, and ecosystems. It's estimated that AHPS, if implemented nationwide, would save lives and provide $677 million per year in economic benefits. AHPS is used currently on the Des Moines River basin in Iowa and will be implemented soon on the Minnesota River basin in Minnesota. Experience gained from user interaction is leading to refined and enhanced product formats and displays. This discussion will elaborate on the technical requirements associated with AHPS implementation, its enhanced products and informational displays, and further refinements based on customer feedback.

  3. Requirements for an Advanced Low Earth Orbit (LEO) Sounder (ALS) for Improved Regional Weather Prediction and Monitoring of Greenhouse Gases

    NASA Technical Reports Server (NTRS)

    Pagano, Thomas S.; Chahine, Moustafa T.; Susskind, Joel

    2008-01-01

    Hyperspectral infrared atmospheric sounders (e.g., the Atmospheric Infrared Sounder (AIRS) on Aqua and the Infrared Atmospheric Sounding Interferometer (IASI) on Met Op) provide highly accurate temperature and water vapor profiles in the lower to upper troposphere. These systems are vital operational components of our National Weather Prediction system and the AIRS has demonstrated over 6 hrs of forecast improvement on the 5 day operational forecast. Despite the success in the mid troposphere to lower stratosphere, a reduction in sensitivity and accuracy has been seen in these systems in the boundary layer over land. In this paper we demonstrate the potential improvement associated with higher spatial resolution (1 km vs currently 13.5 km) on the accuracy of boundary layer products with an added consequence of higher yield of cloud free scenes. This latter feature is related to the number of samples that can be assimilated and has also shown to have a significant impact on improving forecast accuracy. We also present a set of frequencies and resolutions that will improve vertical resolution of temperature and water vapor and trace gas species throughout the atmosphere. Development of an Advanced Low Earth Orbit (LEO) Sounder (ALS) with these improvements will improve weather forecast at the regional scale and of tropical storms and hurricanes. Improvements are also expected in the accuracy of the water vapor and cloud properties products, enhancing process studies and providing a better match to the resolution of future climate models. The improvements of technology required for the ALS are consistent with the current state of technology as demonstrated in NASA Instrument Incubator Program and NOAA's Hyperspectral Environmental Suite (HES) formulation phase development programs.

  4. Predicting Epileptic Seizures in Advance

    PubMed Central

    Moghim, Negin; Corne, David W.

    2014-01-01

    Epilepsy is the second most common neurological disorder, affecting 0.6–0.8% of the world's population. In this neurological disorder, abnormal activity of the brain causes seizures, the nature of which tend to be sudden. Antiepileptic Drugs (AEDs) are used as long-term therapeutic solutions that control the condition. Of those treated with AEDs, 35% become resistant to medication. The unpredictable nature of seizures poses risks for the individual with epilepsy. It is clearly desirable to find more effective ways of preventing seizures for such patients. The automatic detection of oncoming seizures, before their actual onset, can facilitate timely intervention and hence minimize these risks. In addition, advance prediction of seizures can enrich our understanding of the epileptic brain. In this study, drawing on the body of work behind automatic seizure detection and prediction from digitised Invasive Electroencephalography (EEG) data, a prediction algorithm, ASPPR (Advance Seizure Prediction via Pre-ictal Relabeling), is described. ASPPR facilitates the learning of predictive models targeted at recognizing patterns in EEG activity that are in a specific time window in advance of a seizure. It then exploits advanced machine learning coupled with the design and selection of appropriate features from EEG signals. Results, from evaluating ASPPR independently on 21 different patients, suggest that seizures for many patients can be predicted up to 20 minutes in advance of their onset. Compared to benchmark performance represented by a mean S1-Score (harmonic mean of Sensitivity and Specificity) of 90.6% for predicting seizure onset between 0 and 5 minutes in advance, ASPPR achieves mean S1-Scores of: 96.30% for prediction between 1 and 6 minutes in advance, 96.13% for prediction between 8 and 13 minutes in advance, 94.5% for prediction between 14 and 19 minutes in advance, and 94.2% for prediction between 20 and 25 minutes in advance. PMID:24911316

  5. The GEO Water Strategy: Advances in Monitoring, Modeling, and Predicting Groundwater Variations at Regional to Local Scales

    NASA Astrophysics Data System (ADS)

    Miller, N. L.; Heinrich, L.; Kukuri, N.; Plag, H.; Famiglietti, J. S.; Rodell, M.

    2012-12-01

    Groundwater remains one of the most important freshwater resources, especially during droughts and as global warming increases. For informed decisions on managing these resources sustainably, it is important to have sound assessments of the current state of groundwater resources as well as future predictions. This requires reliable groundwater quantity and quality data. However global access to this data is limited. As part of the GEOSS Water Strategy, the International Groundwater Assessment Centre (IGRAC) is therefore implementing the Global Groundwater Monitoring Network (GGMN). The GGMN facilitates periodic assessments of changes in groundwater quantity and quality by aggregating data and information from existing groundwater monitoring networks and regional hydrogeological knowledge (Fig. 1). The GGMN is a participatory process that relies upon contributions from regional and national networks of groundwater experts. Such observation data, along with local well data, surface displacements observed by and GPS data and InSAR, and local in situ gravity data, are necessary for evaluation and simulation of groundwater, leading to improved understanding and prediction of groundwater variations. In conjunction with these observations, regional scale groundwater variations are derived as a residual from land surface-groundwater models through extraction of the total mass of water using geo-rectified Gravity Recovery and Climate Experiment (GRACE) data. Such model-based studies have quantified overdraft and regions at risk of groundwater depletion in parts of Asia, US, and Africa (Fig. 2).We provide an overview of these systems, planned missions, and new model-based approaches toward local-scale methods for assimilation of well data for several regions.igure 1. Example of GGMN (Example of Botswana with fictitious data, with local precipitation map) igure 2. GRACE-derived groundwater storage in northwestern India for 2002 - 2008, relative to the mean. Deviations from

  6. Advanced Regional and Decadal Predictions of Coastal Inundation for the U.S. Atlantic and Gulf Coasts (Invited)

    NASA Astrophysics Data System (ADS)

    Horton, B.; Corbett, D. R.; Donnelly, J. P.; Kemp, A.; Lin, N.; Lindeman, K.; Mann, M. E.; Peltier, W. R.; Rahmstorf, S.

    2013-12-01

    Future inundation of the U.S. Atlantic and Gulf coasts will depend upon sea-level rise and the intensity and frequency of tropical cyclones, each of which will be affected by climate change. Through ongoing, collaborative research we are employing new interdisciplinary approaches to bring about a step change in the reliability of predictions of such inundation. The rate of sea level rise along the U.S. Atlantic and Gulf coasts increased throughout the 20th century. Whilst there is widespread agreement that it continue to accelerate during the 21st century, great uncertainty surrounds its magnitude and geographic variability. Key uncertainties include the role of continental ice sheets, mountain glaciers, and ocean density changes. Insufficient understanding of these complex physical processes precludes accurate prediction of sea-level rise. New approaches using semi-empirical models that relate instrumental records of climate and sea-level rise have projected up to 2 m of sea-level rise by AD 2100. But the time span of instrumental sea-level records is insufficient to adequately constrain the climate:sea-level relationship. We produced new, high-resolution proxy sea-level reconstructions to provide crucial additional constraints to such semi-empirical models. Our dataset spans the alternation between the 'Medieval Climate Anomaly' and 'Little Ice Age'. Before the models can provide appropriate data for coastal management and planning, they must be complemented with regional estimates of sea-level rise. Therefore, the proxy sea-level data has been collected from four study areas (Connecticut, New Jersey, North Carolina and Florida) to accommodate the required extent of regional variability. In the case of inundation arising from tropical cyclones, the historical and observational records are insufficient for predicting their nature and recurrence, because they are such extreme and rare events. Moreover, future storm surges will be superimposed on background sea

  7. Regional Arctic System Model (RASM): A Tool to Address the U.S. Priorities and Advance Capabilities for Arctic Climate Modeling and Prediction

    NASA Astrophysics Data System (ADS)

    Maslowski, W.; Roberts, A.; Cassano, J. J.; Gutowski, W. J., Jr.; Nijssen, B.; Osinski, R.; Zeng, X.; Brunke, M.; Duvivier, A.; Hamman, J.; Hossainzadeh, S.; Hughes, M.; Seefeldt, M. W.

    2015-12-01

    The Arctic is undergoing some of the most coordinated rapid climatic changes currently occurring anywhere on Earth, including the retreat of the perennial sea ice cover, which integrates forcing by, exchanges with and feedbacks between atmosphere, ocean and land. While historical reconstructions from Earth System Models (ESMs) are in broad agreement with these changes, the rate of change in ESMs generally remains outpaced by observations. Reasons for that relate to a combination of coarse resolution, inadequate parameterizations, under-represented processes and a limited knowledge of physical interactions. We demonstrate the capability of the Regional Arctic System Model (RASM) in addressing some of the ESM limitations in simulating observed variability and trends in arctic surface climate. RASM is a high resolution, pan-Arctic coupled climate model with the sea ice and ocean model components configured at an eddy-permitting resolution of 1/12o and the atmosphere and land hydrology model components at 50 km resolution, which are all coupled at 20-minute intervals. RASM is an example of limited-area, process-resolving, fully coupled ESM, which due to the constraints from boundary conditions facilitates detailed comparisons with observational statistics that are not possible with ESMs. The overall goal of RASM is to address key requirements published in the Navy Arctic Roadmap: 2014-2030 and in the Implementation Plan for the National Strategy for the Arctic Region, regarding the need for advanced modeling capabilities for operational forecasting and strategic climate predictions through 2030. The main science objectives of RASM are to advance understanding and model representation of critical physical processes and feedbacks of importance to sea ice thickness and area distribution. RASM results are presented to quantify relative contributions by (i) resolved processes and feedbacks as well as (ii) sensitivity to space dependent sub-grid parameterizations to better

  8. 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

  9. Predicting Career Advancement with Structural Equation Modelling

    ERIC Educational Resources Information Center

    Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia

    2012-01-01

    Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…

  10. Predictive Dynamic Security Assessment through Advanced Computing

    SciTech Connect

    Huang, Zhenyu; Diao, Ruisheng; Jin, Shuangshuang; Chen, Yousu

    2014-11-30

    Abstract— Traditional dynamic security assessment is limited by several factors and thus falls short in providing real-time information to be predictive for power system operation. These factors include the steady-state assumption of current operating points, static transfer limits, and low computational speed. This addresses these factors and frames predictive dynamic security assessment. The primary objective of predictive dynamic security assessment is to enhance the functionality and computational process of dynamic security assessment through the use of high-speed phasor measurements and the application of advanced computing technologies for faster-than-real-time simulation. This paper presents algorithms, computing platforms, and simulation frameworks that constitute the predictive dynamic security assessment capability. Examples of phasor application and fast computation for dynamic security assessment are included to demonstrate the feasibility and speed enhancement for real-time applications.

  11. Predictive markers in advanced renal cell carcinoma.

    PubMed

    Michaelson, M Dror; Stadler, Walter M

    2013-08-01

    Predictive markers of response to therapy are increasingly important in advanced renal cell carcinoma (RCC) due to the proliferation of treatment options in recent years. Different types of potential predictive markers may include clinical, toxicity-based, serum, tissue, and radiologic biomarkers. Clinical factors are commonly used in overall prognostic models of RCC but have limited utility in predicting response to therapy. Correlation between development of particular toxicities and response to therapy has been noted, such as the correlation between hypertension and response to angiogenesis-targeted therapy. Serum and tissue biomarkers will be covered in detail elsewhere, but factors such as serum lactate dehydrogenase (LDH) and circulating cytokines show promise in this regard. Finally, baseline or early treatment radiology studies may have predictive ability for longer term efficacy, with most studies to date focusing on functional imaging modalities such as positron emission tomography (PET) scans, dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), and DCE ultrasound (US). The ultimate goal of developing predictive biomarkers is to enable rational and personalized treatment strategies for patients with advanced RCC. PMID:23972709

  12. Regional Lymph Node Uptake of [18F]Fluorodeoxyglucose After Definitive Chemoradiation Therapy Predicts Local-Regional Failure of Locally Advanced Non-Small Cell Lung Cancer: Results of ACRIN 6668/RTOG 0235

    PubMed Central

    Markovina, Stephanie; Duan, Fenghai; Snyder, Bradley S.; Siegel, Barry A.; Machtay, Mitchell; Bradley, Jeffrey

    2015-01-01

    Purpose/Objective(s) ACRIN 6668/RTOG 0235 demonstrated that standardized uptake value (SUV) on post-treatment [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) correlates with survival in locally advanced non-small cell lung cancer (NSCLC). This secondary analysis determines if SUV of regional lymph nodes (RLNs) on post-treatment FDG-PET correlates with patient outcomes. Methods and Materials Included for analysis were patients treated with concurrent chemoradiation therapy using radiation doses ≥60 Gy, with identifiable FDG-avid RLNs (distinct from primary tumor) on pre-treatment FDG-PET, and post-treatment FDG-PET data. ACRIN Core Laboratory SUV measurements were used. Event time was calculated from the date of post-treatment FDG-PET. Local-regional failure was defined as failure within the treated RT volume and reported by the treating institution. Statistical analyses included Wilcoxon signed-rank test, Kaplan-Meier curves (log rank test), and Cox proportional hazards regression modeling. Results Of 234 trial-eligible patients, 139 (59%) had uptake in both primary tumor and RLNs on pre-treatment FDG-PET, and had SUV data from post-treatment FDG-PET. Maximum SUV was greater for primary tumor than for RLNs before treatment (p<0.001), but not different post-treatment (p=0.320). Post-treatment SUV of RLNs was not associated with overall survival. However, elevated post-treatment SUV of RLNs, both the absolute value and the percent residual activity compared to the pre-treatment SUV, were associated with inferior local-regional control (p<0.001). Conclusions High residual metabolic activity in RLNs on post-treatment FDG-PET is associated with worse local-regional control. Based on these data, future trials evaluating a radiotherapy boost should consider inclusion of both primary tumor and FDG-avid RLNs in the boost volume to maximize local-regional control. PMID:26461002

  13. Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic using a High-Resolution Regional Arctic Climate System Model

    SciTech Connect

    Lettenmaier, Dennis P

    2013-04-08

    Primary activities are reported in these areas: climate system component studies via one-way coupling experiments; development of the Regional Arctic Climate System Model (RACM); and physical feedback studies focusing on changes in Arctic sea ice using the fully coupled model.

  14. Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic Using a High-Resolution Regional Arctic Climate Model

    SciTech Connect

    Cassano, John

    2013-06-30

    The primary research task completed for this project was the development of the Regional Arctic Climate Model (RACM). This involved coupling existing atmosphere, ocean, sea ice, and land models using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM) coupler (CPL7). RACM is based on the Weather Research and Forecasting (WRF) atmospheric model, the Parallel Ocean Program (POP) ocean model, the CICE sea ice model, and the Variable Infiltration Capacity (VIC) land model. A secondary research task for this project was testing and evaluation of WRF for climate-scale simulations on the large pan-Arctic model domain used in RACM. This involved identification of a preferred set of model physical parameterizations for use in our coupled RACM simulations and documenting any atmospheric biases present in RACM.

  15. Towards predictive understanding of regional climate change

    NASA Astrophysics Data System (ADS)

    Xie, Shang-Ping; Deser, Clara; Vecchi, Gabriel A.; Collins, Matthew; Delworth, Thomas L.; Hall, Alex; Hawkins, Ed; Johnson, Nathaniel C.; Cassou, Christophe; Giannini, Alessandra; Watanabe, Masahiro

    2015-10-01

    Regional information on climate change is urgently needed but often deemed unreliable. To achieve credible regional climate projections, it is essential to understand underlying physical processes, reduce model biases and evaluate their impact on projections, and adequately account for internal variability. In the tropics, where atmospheric internal variability is small compared with the forced change, advancing our understanding of the coupling between long-term changes in upper-ocean temperature and the atmospheric circulation will help most to narrow the uncertainty. In the extratropics, relatively large internal variability introduces substantial uncertainty, while exacerbating risks associated with extreme events. Large ensemble simulations are essential to estimate the probabilistic distribution of climate change on regional scales. Regional models inherit atmospheric circulation uncertainty from global models and do not automatically solve the problem of regional climate change. We conclude that the current priority is to understand and reduce uncertainties on scales greater than 100 km to aid assessments at finer scales.

  16. D region predictions. [effects on radio propagation

    NASA Technical Reports Server (NTRS)

    Thrane, E. V.; Chakrabarty, D. K.; Deshpande, S. D.; Doherty, R. H.; Gregory, J. B.; Hargreaves, J. K.; Lastovicka, J.; Morris, P.; Piggott, W. R.; Reagan, J. B.

    1979-01-01

    Present knowledge of D region phenomena is briefly reviewed and the status of current methods of predicting their effects on radio propagation considered. The ELF, VLF and LF navigational and timing systems depend on the stability of the lower part of the D layer where these waves are reflected, whereas MF and HF waves are absorbed as they penetrate the region, in most cases mainly in the upper part of the layer. Possible methods of improving predictions, warnings, and real time operations are considered with particular stress on those which can be implemented in the near future.

  17. Statistical regional calibration of subsidence prediction models

    SciTech Connect

    Cleaver, D.N.; Reddish, D.J.; Dunham, R.K.; Shadbolt, C.H.

    1995-11-01

    Like other influence function methods, the SWIFT subsidence prediction program, developed within the Mineral Resources Engineering Department at the University of Nottingham, requires calibration to regional data in order to produce accurate predictions of ground movements. Previously, this software had been solely calibrated to give results consistent with the Subsidence Engineer`s Handbook (NCB, 1975). This approach was satisfactory for the majority of cases based in the United Kingdom, upon which the calibration was based. However, in certain circumstances within the UK and, almost always, in overseas case studies, the predictions die no correspond to observed patterns of ground movement. Therefore, in order that SWIFT, and other subsidence prediction packages, can be considered more universal, an improved and adaptable method of regional calibration must be incorporated. This paper describes the analysis of a large database of case histories from the UK industry and international publications. Observed maximum subsidence, mining geometry and Geological Index for several hundred cases have been statistically analyzed in terms of developing prediction models. The models developed can more accurately predict maximum subsidence than previously used systems but also, are capable of indicating the likely range of prediction error to a certain degree of probability. Finally, the paper illustrates how this statistical approach can be incorporated as a calibration system for the influence function program, SWIFT.

  18. Advances in tilt rotor noise prediction

    NASA Technical Reports Server (NTRS)

    George, A. R.; Coffen, C. D.; Ringler, T. D.

    1992-01-01

    The two most serious tilt rotor external noise problems, hover noise and blade-vortex interaction noise, are studied. The results of flow visualization and inflow velocity measurements document a complex, recirculating highly unsteady and turbulent flow due to the rotor-wing-body interactions characteristic of tilt rotors. The wing under the rotor is found to obstruct the inflow, causing a deficit in the inflow velocities over the inboard region of the rotor. Discrete frequency harmonic thickness and loading noise mechanisms in hover are examined by first modeling tilt rotor hover aerodynamics and then applying various noise prediction methods using the WOPWOP code. The analysis indicates that the partial ground plane created by the wing below the rotor results in a primary sound source for hover.

  19. Advances in tilt rotor noise prediction

    NASA Astrophysics Data System (ADS)

    George, A. R.; Coffen, C. D.; Ringler, T. D.

    The two most serious tilt rotor external noise problems, hover noise and blade-vortex interaction noise, are studied. The results of flow visualization and inflow velocity measurements document a complex, recirculating highly unsteady and turbulent flow due to the rotor-wing-body interactions characteristic of tilt rotors. The wing under the rotor is found to obstruct the inflow, causing a deficit in the inflow velocities over the inboard region of the rotor. Discrete frequency harmonic thickness and loading noise mechanisms in hover are examined by first modeling tilt rotor hover aerodynamics and then applying various noise prediction methods using the WOPWOP code. The analysis indicates that the partial ground plane created by the wing below the rotor results in a primary sound source for hover.

  20. Prediction of tropical systems over Indian region using mesoscale model

    NASA Astrophysics Data System (ADS)

    Vaidya, S. S.; Mukhopadhyay, P.; Trivedi, D. K.; Sanjay, J.; Singh, S. S.

    The Advanced Regional Prediction System (ARPS) model developed at Center for Analysis and Prediction of Storms at Oklahoma State University, USA is used for simulation of monsoon depression and tropical cyclone over Indian region. The radiosonde data are included in the initial analyses and subsequently; the simulations are performed with 50km and 25km grid resolutions. Two sets of forecast experiments produced by two types of analyses (with radiosonde and without radiosonde data) are compared. It is found that predicted mean sea-level pressure of the depression becomes closer to mean sea level pressure reported in Indian Daily Weather Reports when initialized with analyses containing radiosonde data. The precipitation forecast also is improved when initialized with the analyses containing radiosonde data. The simulation of tropical cyclone with 25km grid resolution is able to simulate some subsynoptic scale features of the system.

  1. Regional price targets appropriate for advanced coal extraction

    NASA Technical Reports Server (NTRS)

    Terasawa, K. L.; Whipple, D. M.

    1980-01-01

    A methodology is presented for predicting coal prices in regional markets for the target time frames 1985 and 2000 that could subsequently be used to guide the development of an advanced coal extraction system. The model constructed is a supply and demand model that focuses on underground mining since the advanced technology is expected to be developed for these reserves by the target years. Coal reserve data and the cost of operating a mine are used to obtain the minimum acceptable selling price that would induce the producer to bring the mine into production. Based on this information, market supply curves can be generated. Demand by region is calculated based on an EEA methodology that emphasizes demand by electric utilities and demand by industry. The demand and supply curves are then used to obtain the price targets. The results show a growth in the size of the markets for compliance and low sulphur coal regions. A significant rise in the real price of coal is not expected even by the year 2000. The model predicts heavy reliance on mines with thick seams, larger block size and deep overburden.

  2. Advanced technology wind shear prediction system evaluation

    NASA Technical Reports Server (NTRS)

    Gering, Greg

    1992-01-01

    The program overviews: (1) American Airline (AA)/Turbulence Prediction Systems (TPS), which have installed forward looking infrared predictive windshear system on 3 MD-80 aircraft; (2) AA/TPS AWAS III evaluation, which is a joint effort and is installed in the noise landing gear (NLG) area and a data recorder installed in the E/E compartment.

  3. Substrate Deformation Predicts Neuronal Growth Cone Advance

    PubMed Central

    Athamneh, Ahmad I.M.; Cartagena-Rivera, Alexander X.; Raman, Arvind; Suter, Daniel M.

    2015-01-01

    Although pulling forces have been observed in axonal growth for several decades, their underlying mechanisms, absolute magnitudes, and exact roles are not well understood. In this study, using two different experimental approaches, we quantified retrograde traction force in Aplysia californica neuronal growth cones as they develop over time in response to a new adhesion substrate. In the first approach, we developed a novel method, to our knowledge, for measuring traction forces using an atomic force microscope (AFM) with a cantilever that was modified with an Aplysia cell adhesion molecule (apCAM)-coated microbead. In the second approach, we used force-calibrated glass microneedles coated with apCAM ligands to guide growth cone advance. The traction force exerted by the growth cone was measured by monitoring the microneedle deflection using an optical microscope. Both approaches showed that Aplysia growth cones can develop traction forces in the 100–102 nN range during adhesion-mediated advance. Moreover, our results suggest that the level of traction force is directly correlated to the stiffness of the microneedle, which is consistent with a reinforcement mechanism previously observed in other cell types. Interestingly, the absolute level of traction force did not correlate with growth cone advance toward the adhesion site, but the amount of microneedle deflection did. In cases of adhesion-mediated growth cone advance, the mean needle deflection was 1.05 ± 0.07 μm. By contrast, the mean deflection was significantly lower (0.48 ± 0.06 μm) when the growth cones did not advance. Our data support a hypothesis that adhesion complexes, which can undergo micron-scale elastic deformation, regulate the coupling between the retrogradely flowing actin cytoskeleton and apCAM substrates, stimulating growth cone advance if sufficiently abundant. PMID:26445437

  4. Predicting impact factor one year in advance.

    PubMed

    Ketcham, Catherine M

    2007-06-01

    The first impact factor (IF) to reflect the sole efforts of a new editorial team occurs 4 years into what is usually a 5-year editorship, owing to the lag times of: paper accrual and publication, accumulation of citations in derivative literature, and compiling of such citations by the Thomson ISI Web of Knowledge service. Through weekly collection of citation data from the Web of Science over the past 2 years, we now demonstrate that the evolution of IF can be tracked weekly over the course of a calendar year, enabling prediction of the next year's IF beginning at the middle of the previous year. The methodology used to track the developing IF for Lab Invest is presented in this study and a prediction made for the 2006 IF, along with IF predictions for other general pathology journals (American Journal of Pathology, Journal of Pathology, Modern Pathology, American Journal of Surgical Pathology, and Human Pathology). Despite the fact that the 2006 IF for Lab Invest will not be issued until June 2007, it became apparent as early as July 2006 that the Lab Invest IF would be greatly improved over 2004 and 2005 by a predicted 0.5 units. However, as important as IF can be to a journal, it is vital not to let IF considerations influence every aspect of the editors' decisions. Rather, the significance of early prediction lies in earlier validation of editorial policies for journal management as a whole, and reassurance that the philosophy for journal operations is on track.

  5. Fast prediction unit selection method for HEVC intra prediction based on salient regions

    NASA Astrophysics Data System (ADS)

    Feng, Lei; Dai, Ming; Zhao, Chun-lei; Xiong, Jing-ying

    2016-07-01

    In order to reduce the computational complexity of the high efficiency video coding (HEVC) standard, a new algorithm for HEVC intra prediction, namely, fast prediction unit (PU) size selection method for HEVC based on salient regions is proposed in this paper. We first build a saliency map for each largest coding unit (LCU) to reduce its texture complexity. Secondly, the optimal PU size is determined via a scheme that implements an information entropy comparison among sub-blocks of saliency maps. Finally, we apply the partitioning result of saliency map on the original LCUs, obtaining the optimal partitioning result. Our algorithm can determine the PU size in advance to the angular prediction in intra coding, reducing computational complexity of HEVC. The experimental results show that our algorithm achieves a 37.9% reduction in encoding time, while producing a negligible loss in Bjontegaard delta bit rate ( BDBR) of 0.62%.

  6. Predicting Production Costs for Advanced Aerospace Vehicles

    NASA Technical Reports Server (NTRS)

    Bao, Han P.; Samareh, J. A.; Weston, R. P.

    2002-01-01

    For early design concepts, the conventional approach to cost is normally some kind of parametric weight-based cost model. There is now ample evidence that this approach can be misleading and inaccurate. By the nature of its development, a parametric cost model requires historical data and is valid only if the new design is analogous to those for which the model was derived. Advanced aerospace vehicles have no historical production data and are nowhere near the vehicles of the past. Using an existing weight-based cost model would only lead to errors and distortions of the true production cost. This paper outlines the development of a process-based cost model in which the physical elements of the vehicle are soared according to a first-order dynamics model. This theoretical cost model, first advocated by early work at MIT, has been expanded to cover the basic structures of an advanced aerospace vehicle. Elemental costs based on the geometry of the design can be summed up to provide an overall estimation of the total production cost for a design configuration. This capability to directly link any design configuration to realistic cost estimation is a key requirement for high payoff MDO problems. Another important consideration in this paper is the handling of part or product complexity. Here the concept of cost modulus is introduced to take into account variability due to different materials, sizes, shapes, precision of fabrication, and equipment requirements. The most important implication of the development of the proposed process-based cost model is that different design configurations can now be quickly related to their cost estimates in a seamless calculation process easily implemented on any spreadsheet tool.

  7. Predicting Malignancy in Thyroid Nodules: Molecular Advances

    PubMed Central

    Melck, Adrienne L.; Yip, Linwah

    2016-01-01

    Over the last several years, a clearer understanding of the genetic alterations underlying thyroid carcinogenesis has developed. This knowledge can be utilized to tackle one of the greatest challenges facing thyroidologists: management of the indeterminate thyroid nodule. Despite the accuracy of fine needle aspiration cytology, many patients undergo invasive surgery in order to determine if a follicular or Hurthle cell neoplasm is malignant, and better diagnostic tools are required. A number of biomarkers have recently been studied and show promise in this setting. In particular, BRAF, RAS, PAX8-PPARγ, microRNAs and loss of heterozygosity have each been demonstrated as useful molecular tools for predicting malignancy and can thereby guide decisions regarding surgical management of nodular thyroid disease. This review summarizes the current literature surrounding each of these markers and highlights our institution’s prospective analysis of these markers and their subsequent incorporation into our management algorithms for thyroid nodules. PMID:21818817

  8. A Primer In Advanced Fatigue Life Prediction Methods

    NASA Technical Reports Server (NTRS)

    Halford, Gary R.

    2000-01-01

    Metal fatigue has plagued structural components for centuries, and it remains a critical durability issue in today's aerospace hardware. This is true despite vastly improved and advanced materials, increased mechanistic understanding, and development of accurate structural analysis and advanced fatigue life prediction tools. Each advance is quickly taken advantage of to produce safer, more reliable more cost effective, and better performing products. In other words, as the envelop is expanded, components are then designed to operate just as close to the newly expanded envelop as they were to the initial one. The problem is perennial. The economic importance of addressing structural durability issues early in the design process is emphasized. Tradeoffs with performance, cost, and legislated restrictions are pointed out. Several aspects of structural durability of advanced systems, advanced materials and advanced fatigue life prediction methods are presented. Specific items include the basic elements of durability analysis, conventional designs, barriers to be overcome for advanced systems, high-temperature life prediction for both creep-fatigue and thermomechanical fatigue, mean stress effects, multiaxial stress-strain states, and cumulative fatigue damage accumulation assessment.

  9. Regional characteristics relevant to advanced technology cogeneration development. [industrial energy

    NASA Technical Reports Server (NTRS)

    Manvi, R.

    1981-01-01

    To assist DOE in establishing research and development funding priorities in the area of advanced energy conversion technoloy, researchers at the Jet Propulsion Laboratory studied those specific factors within various regions of the country that may influence cogeneration with advanced energy conversion systems. Regional characteristics of advanced technology cogeneration possibilities are discussed, with primary emphasis given to coal derived fuels. Factors considered for the study were regional industry concentration, purchased fuel and electricity prices, environmental constraints, and other data of interest to industrial cogeneration.

  10. Regional characteristics relevant to advanced technology cogeneration development

    NASA Astrophysics Data System (ADS)

    Manvi, R.

    1981-07-01

    To assist DOE in establishing research and development funding priorities in the area of advanced energy conversion technoloy, researchers at the Jet Propulsion Laboratory studied those specific factors within various regions of the country that may influence cogeneration with advanced energy conversion systems. Regional characteristics of advanced technology cogeneration possibilities are discussed, with primary emphasis given to coal derived fuels. Factors considered for the study were regional industry concentration, purchased fuel and electricity prices, environmental constraints, and other data of interest to industrial cogeneration.

  11. Design of the advanced regional aircraft, the DART-75

    NASA Technical Reports Server (NTRS)

    Elliott, Steve; Gislason, Jason; Huffstetler, Mark; Mann, Jon; Withers, Ashley; Zimmerman, Mark

    1992-01-01

    This design analysis is intended to show the capabilities of the DART-75, a 75 passenger medium-range regional transport. Included are the detailed descriptions of the structures, performance, stability and control, weight and balance, and engine design. The design should allow for the DART to become the premier regional aircraft of the future due to some advanced features like the canard, semi-composite construction, and advanced engines.

  12. Advanced propeller noise prediction in the time domain

    NASA Technical Reports Server (NTRS)

    Farassat, F.; Dunn, M. H.; Spence, P. L.

    1992-01-01

    The time domain code ASSPIN gives acousticians a powerful technique of advanced propeller noise prediction. Except for nonlinear effects, the code uses exact solutions of the Ffowcs Williams-Hawkings equation with exact blade geometry and kinematics. By including nonaxial inflow, periodic loading noise, and adaptive time steps to accelerate computer execution, the development of this code becomes complete.

  13. Regional price targets appropriate for advanced coal extraction. [Forecasting to 1985 and 2000; USA; Regional analysis

    SciTech Connect

    Terasawa, K.L.; Whipple, D.W.

    1980-12-01

    The object of the study is to provide a methodology for predicting coal prices in regional markets for the target time frames 1985 and 2000 that could subsequently be used to guide the development of an advanced coal extraction system. The model constructed for the study is a supply and demand model that focuses on underground mining, since the advanced technology is expected to be developed for these reserves by the target years. The supply side of the model is based on coal reserve data generated by Energy and Environmental Analysis, Inc. (EEA). Given this data and the cost of operating a mine (data from US Department of Energy and Bureau of Mines), the Minimum Acceptable Selling Price (MASP) is obtained. The MASP is defined as the smallest price that would induce the producer to bring the mine into production, and is sensitive to the current technology and to assumptions concerning miner productivity. Based on this information, market supply curves can then be generated. On the demand side of the model, demand by region is calculated based on an EEA methodology that emphasizes demand by electric utilities and demand by industry. The demand and supply curves are then used to obtain the price targets. This last step is accomplished by allocating the demands among the suppliers so that the combined cost of producing and transporting coal is minimized.

  14. Regional Climate Predictability in the Extratropics

    SciTech Connect

    Robertson,A.W.:Ghil,M.

    2001-08-09

    The goal of this project was to develop a dynamical framework for extratropical climate predictability on decade-to-century timescales and subcontinental spatial scales,besed on the intraseasonal dynamics of the midlatitude atmosphere and their interaction with the ocean's longer timescales.A two-pronged approach was taken,based on (a)idealized,quasi-geostrophic,coupled models of the midlatitude ocean-atmosphere system,and(b)analysis of GCM results.

  15. Ground Motion Prediction Models for Caucasus Region

    NASA Astrophysics Data System (ADS)

    Jorjiashvili, Nato; Godoladze, Tea; Tvaradze, Nino; Tumanova, Nino

    2016-04-01

    Ground motion prediction models (GMPMs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration or spectral acceleration because this parameter gives useful information for Seismic Hazard Assessment. Since 2003 development of Georgian Digital Seismic Network has started. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models is obtained by classical, statistical way, regression analysis. In this study site ground conditions are additionally considered because the same earthquake recorded at the same distance may cause different damage according to ground conditions. Empirical ground-motion prediction models (GMPMs) require adjustment to make them appropriate for site-specific scenarios. However, the process of making such adjustments remains a challenge. This work presents a holistic framework for the development of a peak ground acceleration (PGA) or spectral acceleration (SA) GMPE that is easily adjustable to different seismological conditions and does not suffer from the practical problems associated with adjustments in the response spectral domain.

  16. Ensemble-based Regional Climate Prediction: Political Impacts

    NASA Astrophysics Data System (ADS)

    Miguel, E.; Dykema, J.; Satyanath, S.; Anderson, J. G.

    2008-12-01

    Accurate forecasts of regional climate, including temperature and precipitation, have significant implications for human activities, not just economically but socially. Sub Saharan Africa is a region that has displayed an exceptional propensity for devastating civil wars. Recent research in political economy has revealed a strong statistical relationship between year to year fluctuations in precipitation and civil conflict in this region in the 1980s and 1990s. To investigate how climate change may modify the regional risk of civil conflict in the future requires a probabilistic regional forecast that explicitly accounts for the community's uncertainty in the evolution of rainfall under anthropogenic forcing. We approach the regional climate prediction aspect of this question through the application of a recently demonstrated method called generalized scalar prediction (Leroy et al. 2009), which predicts arbitrary scalar quantities of the climate system. This prediction method can predict change in any variable or linear combination of variables of the climate system averaged over a wide range spatial scales, from regional to hemispheric to global. Generalized scalar prediction utilizes an ensemble of model predictions to represent the community's uncertainty range in climate modeling in combination with a timeseries of any type of observational data that exhibits sensitivity to the scalar of interest. It is not necessary to prioritize models in deriving with the final prediction. We present the results of the application of generalized scalar prediction for regional forecasts of temperature and precipitation and Sub Saharan Africa. We utilize the climate predictions along with the established statistical relationship between year-to-year rainfall variability in Sub Saharan Africa to investigate the potential impact of climate change on civil conflict within that region.

  17. The regional prediction model of PM10 concentrations for Turkey

    NASA Astrophysics Data System (ADS)

    Güler, Nevin; Güneri İşçi, Öznur

    2016-11-01

    This study is aimed to predict a regional model for weekly PM10 concentrations measured air pollution monitoring stations in Turkey. There are seven geographical regions in Turkey and numerous monitoring stations at each region. Predicting a model conventionally for each monitoring station requires a lot of labor and time and it may lead to degradation in quality of prediction when the number of measurements obtained from any õmonitoring station is small. Besides, prediction models obtained by this way only reflect the air pollutant behavior of a small area. This study uses Fuzzy C-Auto Regressive Model (FCARM) in order to find a prediction model to be reflected the regional behavior of weekly PM10 concentrations. The superiority of FCARM is to have the ability of considering simultaneously PM10 concentrations measured monitoring stations in the specified region. Besides, it also works even if the number of measurements obtained from the monitoring stations is different or small. In order to evaluate the performance of FCARM, FCARM is executed for all regions in Turkey and prediction results are compared to statistical Autoregressive (AR) Models predicted for each station separately. According to Mean Absolute Percentage Error (MAPE) criteria, it is observed that FCARM provides the better predictions with a less number of models.

  18. Predicting the acceptance of advanced rider assistance systems.

    PubMed

    Huth, Véronique; Gelau, Christhard

    2013-01-01

    The strong prevalence of human error as a crash causation factor in motorcycle accidents calls for countermeasures that help tackling this issue. Advanced rider assistance systems pursue this goal, providing the riders with support and thus contributing to the prevention of crashes. However, the systems can only enhance riding safety if the riders use them. For this reason, acceptance is a decisive aspect to be considered in the development process of such systems. In order to be able to improve behavioural acceptance, the factors that influence the intention to use the system need to be identified. This paper examines the particularities of motorcycle riding and the characteristics of this user group that should be considered when predicting the acceptance of advanced rider assistance systems. Founded on theories predicting behavioural intention, the acceptance of technologies and the acceptance of driver support systems, a model on the acceptance of advanced rider assistance systems is proposed, including the perceived safety when riding without support, the interface design and the social norm as determinants of the usage intention. Since actual usage cannot be measured in the development stage of the systems, the willingness to have the system installed on the own motorcycle and the willingness to pay for the system are analyzed, constituting relevant conditions that allow for actual usage at a later stage. Its validation with the results from user tests on four advanced rider assistance systems allows confirming the social norm and the interface design as powerful predictors of the acceptance of ARAS, while the extent of perceived safety when riding without support did not have any predictive value in the present study.

  19. Design of the advanced regional aircraft, the DART-75

    NASA Technical Reports Server (NTRS)

    Elliot, Steve; Gislason, Jason; Huffstetler, Mark; Mann, Jon; Withers, Ashley; Zimmerman, Mark

    1992-01-01

    The need for regional aircraft stems from the problem of hub airport congestion. Regional travel will allow a passenger to commute from one spoke city to another spoke city without entering the congested hub airport. In addition, those people traveling longer routes may begin the flight at home instead of traveling to the hub airport. At this time, there is no American aerospace company that produces a regional transport for under 100 passengers. The intention of the Developmental Advanced Regional Transport (DART-75) is to fill this void with a modern, efficient regional aircraft. This design achieves the efficiency through a number of advanced features including three lifting surfaces, partial composite construction, and an advanced engine design. Efficiency is not the only consideration. Structural integrity, fatigue life, ease of maintenance, passenger comfort and convenience, and environmental aspects must all be considered. These factors force the design team to face many tradeoffs that are studied to find the best solution. The final consideration that cannot be overlooked is that of cost. The DART-75 is a 75-passenger medium-range regional transport intended for spoke-to-spoke, spoke-to-hub, and some hub-to-hub operations. Included are the general descriptions of the structures, weight and balance, stability and control, performance, and engine design.

  20. 76 FR 52954 - Workshop: Advancing Research on Mixtures; New Perspectives and Approaches for Predicting Adverse...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-24

    ... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF HEALTH AND HUMAN SERVICES Workshop: Advancing Research on Mixtures; New Perspectives and Approaches for Predicting... ``Advancing Research on Mixtures: New Perspectives and Approaches for Predicting Adverse Human Health...

  1. Predicting binary merger event rates for advanced LIGO/Virgo

    NASA Astrophysics Data System (ADS)

    Holz, Daniel; Belczynski, Chris; O'Shaughnessy, Richard; Bulik, Tomek; LIGO Collaboration

    2016-03-01

    We discuss estimates of the rates of mergers of binary systems composed of neutron stars and/or stellar mass black holes. We use the StarTrack population synthesis code, and make predictions for the detection rate of compact binary coalescences with the advanced LIGO/Virgo gravitational wave detectors. Because these instruments are sensitive to massive (M > 20M⊙) stellar-mass binary black holes mergers out to high redshift (z > 1), we discuss the cosmological effects which must be taken into account when calculating LIGO detection rates, including a generalization of the calculation of the ``peanut factor'' and the sensitive time-volume.

  2. Predicting human age using regional morphometry and inter-regional morphological similarity

    NASA Astrophysics Data System (ADS)

    Wang, Xun-Heng; Li, Lihua

    2016-03-01

    The goal of this study is predicting human age using neuro-metrics derived from structural MRI, as well as investigating the relationships between age and predictive neuro-metrics. To this end, a cohort of healthy subjects were recruited from 1000 Functional Connectomes Project. The ages of the participations were ranging from 7 to 83 (36.17+/-20.46). The structural MRI for each subject was preprocessed using FreeSurfer, resulting in regional cortical thickness, mean curvature, regional volume and regional surface area for 148 anatomical parcellations. The individual age was predicted from the combination of regional and inter-regional neuro-metrics. The prediction accuracy is r = 0.835, p < 0.00001, evaluated by Pearson correlation coefficient between predicted ages and actual ages. Moreover, the LASSO linear regression also found certain predictive features, most of which were inter-regional features. The turning-point of the developmental trajectories in human brain was around 40 years old based on regional cortical thickness. In conclusion, structural MRI could be potential biomarkers for the aging in human brain. The human age could be successfully predicted from the combination of regional morphometry and inter-regional morphological similarity. The inter-regional measures could be beneficial to investigating human brain connectome.

  3. Comparison of two imaging programs in predicting the soft tissue changes with mandibular advancement surgery.

    PubMed

    Ravindranath, Sneha; Krishnaswamy, Nathamuni Rengarajan; Sundaram, Venkateswaran

    2011-01-01

    Establishing common objectives and expectations concerning the outcome of proposed surgical orthodontic therapy is a crucial part of the treatment planning process, which has been greatly simplified by imaging software. The purpose of this study was to investigate the reliability of two surgical imaging programs--Dolphin Imaging 10 and Vistadent OC--in simulating the actual outcome of mandibular advancement surgery by using a visual analog scale (VAS) judged by a panel of orthodontists, oral surgeons, and laypersons. The predictions were also analyzed with soft tissue cephalometric evaluation. The results of the study showed that in predicting the surgical outcome evaluated by the VAS, both programs received a mean rating of fair. One was marginally superior for the overall assessment among all three panelist groups. Region-wise, rating indicated the lower lip region to be the least accurate, and the submental region received the highest scores. The soft tissue cephalometric parameters showed minimal differences except for the lower lip parameters. Thus, Dolphin Imaging 10 and Vistadent OC are reliable in predicting mandibular advancement surgical outcomes with inaccuracies chiefly in the lower lip region. PMID:22299108

  4. ASRM radiation and flowfield prediction status. [Advanced Solid Rocket Motor plume radiation prediction

    NASA Technical Reports Server (NTRS)

    Reardon, J. E.; Everson, J.; Smith, S. D.; Sulyma, P. R.

    1991-01-01

    Existing and proposed methods for the prediction of plume radiation are discussed in terms of their application to the NASA Advanced Solid Rocket Motor (ASRM) and Space Shuttle Main Engine (SSME) projects. Extrapolations of the Solid Rocket Motor (SRM) are discussed with respect to preliminary predictions of the primary and secondary radiation environments. The methodology for radiation and initial plume property predictions are set forth, including a new code for scattering media and independent secondary source models based on flight data. The Monte Carlo code employs a reverse-evaluation approach which traces rays back to their point of absorption in the plume. The SRM sea-level plume model is modified to account for the increased radiation in the ASRM plume due to the ASRM's propellant chemistry. The ASRM cycle-1 environment predictions are shown to identify a potential reason for the shutdown spike identified with pre-SRM staging.

  5. Regional Earth System Prediction for Policy Decision-Making

    NASA Astrophysics Data System (ADS)

    Murtugudde, R. G.; Cbfs Team

    2010-12-01

    While the IPCC will continue to lead Earth System projections for global issues such as greenhouse gas levels and global temperature increase, high-resolution regional Earth System predictions will be crucial for producing effective decision-making tools for day-to-day, sustainable Earth System management and adaptive management of resources. Regional Earth System predictions and projections at the order of a few meters resolution from days to decades must be validated and provide uncertainties and skill scores to be usable. While the task is daunting, it would be criminally negligent of the global human not to embark on this task immediately. The observational needs for the integrated natural-human system for the regional Earth System are distinct from the global needs even though there are many overlaps. The process understanding of the Earth System at the micro-scale can be translated into predictive understanding and skillful predictions for sustainable management and adaptation by merging these observations with Earth System models to go from global scale predictions and projections to regional environmental manifestations and mechanistic depiction of human interactions with the Earth System and exploitation of its resources. Regional Earth System monitoring and predictions thus will continuously take the pulse of the planet to prescribe appropriate actions for participatory decision-making for sustainable and adaptive management of the Earth System and to avoid catastrophic domains of potential outcomes. An example of a regional Earth System prediction system over the Chesapeake Bay with detailed interactions with users is discussed. Routine forecasts of atmospheric and hydrodynamic forecasts are used to produce linked prediction products for water quality, hypoxia, sea nettles, harmful algal blooms, striped bass, pathogens, etc.

  6. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    NASA Technical Reports Server (NTRS)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This paper presents recent thermal model results of the Advanced Stirling Radioisotope Generator (ASRG). The three-dimensional (3D) ASRG thermal power model was built using the Thermal Desktop(trademark) thermal analyzer. The model was correlated with ASRG engineering unit test data and ASRG flight unit predictions from Lockheed Martin's (LM's) I-deas(trademark) TMG thermal model. The auxiliary cooling system (ACS) of the ASRG is also included in the ASRG thermal model. The ACS is designed to remove waste heat from the ASRG so that it can be used to heat spacecraft components. The performance of the ACS is reported under nominal conditions and during a Venus flyby scenario. The results for the nominal case are validated with data from Lockheed Martin. Transient thermal analysis results of ASRG for a Venus flyby with a representative trajectory are also presented. In addition, model results of an ASRG mounted on a Cassini-like spacecraft with a sunshade are presented to show a way to mitigate the high temperatures of a Venus flyby. It was predicted that the sunshade can lower the temperature of the ASRG alternator by 20 C for the representative Venus flyby trajectory. The 3D model also was modified to predict generator performance after a single Advanced Stirling Convertor failure. The geometry of the Microtherm HT insulation block on the outboard side was modified to match deformation and shrinkage observed during testing of a prototypic ASRG test fixture by LM. Test conditions and test data were used to correlate the model by adjusting the thermal conductivity of the deformed insulation to match the post-heat-dump steady state temperatures. Results for these conditions showed that the performance of the still-functioning inboard ACS was unaffected.

  7. Advancements in decadal climate predictability: The role of nonoceanic drivers

    NASA Astrophysics Data System (ADS)

    Bellucci, A.; Haarsma, R.; Bellouin, N.; Booth, B.; Cagnazzo, C.; Hurk, B.; Keenlyside, N.; Koenigk, T.; Massonnet, F.; Materia, S.; Weiss, M.

    2015-06-01

    We review recent progress in understanding the role of sea ice, land surface, stratosphere, and aerosols in decadal-scale predictability and discuss the perspectives for improving the predictive capabilities of current Earth system models (ESMs). These constituents have received relatively little attention because their contribution to the slow climatic manifold is controversial in comparison to that of the large heat capacity of the oceans. Furthermore, their initialization as well as their representation in state-of-the-art climate models remains a challenge. Numerous extraoceanic processes that could be active over the decadal range are proposed. Potential predictability associated with the aforementioned, poorly represented, and scarcely observed constituents of the climate system has been primarily inspected through numerical simulations performed under idealized experimental settings. The impact, however, on practical decadal predictions, conducted with realistically initialized full-fledged climate models, is still largely unexploited. Enhancing initial-value predictability through an improved model initialization appears to be a viable option for land surface, sea ice, and, marginally, the stratosphere. Similarly, capturing future aerosol emission storylines might lead to an improved representation of both global and regional short-term climatic changes. In addition to these factors, a key role on the overall predictive ability of ESMs is expected to be played by an accurate representation of processes associated with specific components of the climate system. These act as "signal carriers," transferring across the climatic phase space the information associated with the initial state and boundary forcings, and dynamically bridging different (otherwise unconnected) subsystems. Through this mechanism, Earth system components trigger low-frequency variability modes, thus extending the predictability beyond the seasonal scale.

  8. Computational methods in the prediction of advanced subsonic and supersonic propeller induced noise: ASSPIN users' manual

    NASA Technical Reports Server (NTRS)

    Dunn, M. H.; Tarkenton, G. M.

    1992-01-01

    This document describes the computational aspects of propeller noise prediction in the time domain and the use of high speed propeller noise prediction program ASSPIN (Advanced Subsonic and Supersonic Propeller Induced Noise). These formulations are valid in both the near and far fields. Two formulations are utilized by ASSPIN: (1) one is used for subsonic portions of the propeller blade; and (2) the second is used for transonic and supersonic regions on the blade. Switching between the two formulations is done automatically. ASSPIN incorporates advanced blade geometry and surface pressure modelling, adaptive observer time grid strategies, and contains enhanced numerical algorithms that result in reduced computational time. In addition, the ability to treat the nonaxial inflow case has been included.

  9. Random Forests for Global and Regional Crop Yield Predictions

    PubMed Central

    Jeong, Jig Han; Resop, Jonathan P.; Mueller, Nathaniel D.; Fleisher, David H.; Yun, Kyungdahm; Butler, Ethan E.; Timlin, Dennis J.; Shim, Kyo-Moon; Gerber, James S.; Reddy, Vangimalla R.

    2016-01-01

    Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data. PMID:27257967

  10. Random Forests for Global and Regional Crop Yield Predictions.

    PubMed

    Jeong, Jig Han; Resop, Jonathan P; Mueller, Nathaniel D; Fleisher, David H; Yun, Kyungdahm; Butler, Ethan E; Timlin, Dennis J; Shim, Kyo-Moon; Gerber, James S; Reddy, Vangimalla R; Kim, Soo-Hyung

    2016-01-01

    Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data. PMID:27257967

  11. Random Forests for Global and Regional Crop Yield Predictions.

    PubMed

    Jeong, Jig Han; Resop, Jonathan P; Mueller, Nathaniel D; Fleisher, David H; Yun, Kyungdahm; Butler, Ethan E; Timlin, Dennis J; Shim, Kyo-Moon; Gerber, James S; Reddy, Vangimalla R; Kim, Soo-Hyung

    2016-01-01

    Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data.

  12. Prediction of Corrosion of Advanced Materials and Fabricated Components

    SciTech Connect

    A. Anderko; G. Engelhardt; M.M. Lencka; M.A. Jakab; G. Tormoen; N. Sridhar

    2007-09-29

    The goal of this project is to provide materials engineers, chemical engineers and plant operators with a software tool that will enable them to predict localized corrosion of process equipment including fabricated components as well as base alloys. For design and revamp purposes, the software predicts the occurrence of localized corrosion as a function of environment chemistry and assists the user in selecting the optimum alloy for a given environment. For the operation of existing plants, the software enables the users to predict the remaining life of equipment and help in scheduling maintenance activities. This project combined fundamental understanding of mechanisms of corrosion with focused experimental results to predict the corrosion of advanced, base or fabricated, alloys in real-world environments encountered in the chemical industry. At the heart of this approach is the development of models that predict the fundamental parameters that control the occurrence of localized corrosion as a function of environmental conditions and alloy composition. The fundamental parameters that dictate the occurrence of localized corrosion are the corrosion and repassivation potentials. The program team, OLI Systems and Southwest Research Institute, has developed theoretical models for these parameters. These theoretical models have been applied to predict the occurrence of localized corrosion of base materials and heat-treated components in a variety of environments containing aggressive and non-aggressive species. As a result of this project, a comprehensive model has been established and extensively verified for predicting the occurrence of localized corrosion as a function of environment chemistry and temperature by calculating the corrosion and repassivation potentials.To support and calibrate the model, an experimental database has been developed to elucidate (1) the effects of various inhibiting species as well as aggressive species on localized corrosion of nickel

  13. Regional Travel-Time Predictions, Uncertainty and Location Improvement

    SciTech Connect

    Flanagan, M; Myers, S

    2004-07-15

    We investigate our ability to improve regional travel-time prediction and seismic event location using an a priori three-dimensional (3D) velocity model of Western Eurasia and North Africa (WENA 1.0). Three principal results are presented. First, the 3D WENA 1.0 velocity model improves travel-time prediction over the IASPI91 model, as measured by variance reduction, for regional phases recorded at 22 stations throughout the modeled region, including aseismic areas. Second, a distance-dependent uncertainty model is developed and tested for the WENA 1.0 model. Third, relocation using WENA 1.0 and the associated uncertainty model provides an end-to-end validation test. Model validation is based on a comparison of approximately 10,000 Pg, Pn, and P travel-time predictions and empirical observations from ground truth (GT) events. Ray coverage for the validation dataset provides representative, regional-distances sampling across Eurasia and North Africa. The WENA 1.0 model markedly improves travel-time predictions for most stations with an average variance reduction of 14% for all ray paths. We find that improvement is station dependent, with some stations benefiting greatly from WENA predictions (25% at OBN, and 16% at BKR), some stations showing moderate improvement (12% at ARU, and 17% at NIL), and some stations benefiting only slightly (7% at AAE, and 8% at TOL). We further test WENA 1.0 by relocating five calibration events. Again, relocation of these events is dependent on ray paths that evenly sample WENA 1.0 and therefore provide an unbiased assessment of location performance. These results highlight the importance of accurate GT datasets in assessing regional travel-time models and demonstrate that an a priori 3D model can markedly improve our ability to locate small magnitude events in a regional monitoring context.

  14. Prediction of the becalmed region for LP turbine profile design

    SciTech Connect

    Schulte, V.; Hodson, H.P.

    1998-10-01

    Recent attention has focused on the so-called ``becalmed region`` that is observed inside the boundary layers of turbomachinery blading and is associated with the process of wake-induced transition. Significant reductions of profile loss have been shown for high lift LP turbine blades at low Reynolds numbers due to the effects of the becalmed region on the diffusing flow at the rear of the suction surface. In this paper the nature and the significance of the becalmed region are examined using experimental observations and computational studies. It is shown that the becalmed region may be modeled using the unsteady laminar boundary layer equations. Therefore, it is predictable independent of the transition or turbulence models employed. The effect of the becalmed region on the transition process is modeled using a spot-based intermittency transition model. An unsteady differential boundary layer code was used to simulate a deterministic experiment involving an isolated turbulent spot numerically. The predictability of the becalmed region means that the rate of entropy production can be calculated in that region. It is found to be of the order of that in a laminar boundary layer. It is for this reason and because the becalmed region may be encroached upon by pursuing turbulent flows that for attached boundary layers, wake-induced transition cannot significantly reduce the profile loss. However, the becalmed region is less prone to separation than a conventional laminar boundary layer. Therefore, the becalmed region may be exploited in order to prevent boundary layer separation and the increase in loss that this entails. It is shown that it should now be possible to design efficient high lift LP turbine blades.

  15. Prediction of concurrent chemoradiotherapy outcome in advanced oropharyngeal cancer

    PubMed Central

    HASEGAWA, MASAHIRO; MAEDA, HIROYUKI; DENG, ZEYI; KIYUNA, ASANORI; GANAHA, AKIRA; YAMASHITA, YUKASHI; MATAYOSHI, SEN; AGENA, SHINYA; TOITA, TAKAFUMI; UEHARA, TAKAYUKI; SUZUKI, MIKIO

    2014-01-01

    The aim of this study was to investigate human papillomavirus (HPV) infection as a predictor of concurrent chemoradiotherapy (CCRT) response and indicator of planned neck dissection (PND) for patients with advanced oropharyngeal squamous cell carcinoma (OPSCC; stage III/IV). Overall, 39 OPSCC patients (32 men, 7 women; median age 61 years, range 39–79 years) were enrolled. The primary lesion and whole neck were irradiated up to 50.4 Gy, and subsequently the primary site and metastatic lymph nodes were boosted with a further 16.2 Gy. Although several chemotherapy regimens were employed, 82.1% of OPSCC patients received the combination of nedaplatin and 5-fluorouracil. HPV-related OPSCC (16 cases) was defined as both HPV DNA-positive status by polymerase chain reaction and p16INK4a overexpression by immunohistochemistry. Patients with N2 and N3 disease received PND 2–3 months after CCRT completion. Compared to non-responders, CCRT responders showed significantly lower nodal stage (N0 to N2b) and HPV-positive status in univariate analysis. Patients with HPV-related OPSCC had longer time to treatment failure (TTF) than those with HPV-unrelated OPSCC (p=0.040). Three-year TTF was 81.3 and 47.8% in the HPV-related and HPV-unrelated groups, respectively. There were also significant differences in disease-free survival (DFS) between the two OPSCC patient groups (p=0.042). Three-year DFS was 93.8 and 66.7% in patients with HPV-related and HPV-unrelated OPSCC, respectively. Multivariate logistic analysis showed a lower risk of TTF event occurrence in HPV-related OPSCC (p=0.041) than in HPV-unrelated OPSCC. Thus, HPV testing in addition to nodal stage was useful for predicting CCRT response, especially in advanced OPSCC. Because patients who received PND showed moderate locoregional control, PND is an effective surgical procedure for controlling neck lesions in patients with advanced HPV-unrelated disease. PMID:24969413

  16. Prediction of regional streamflow frequency using model tree ensembles

    NASA Astrophysics Data System (ADS)

    Schnier, Spencer; Cai, Ximing

    2014-09-01

    This study introduces a novel data-driven method called model tree ensembles (MTEs) to predict streamflow frequency statistics based on known drainage area characteristics, which yields insights into the dominant controls of regional streamflow. The database used to induce the models contains both natural and anthropogenic drainage area characteristics for 294 USGS stream gages (164 in Texas and 130 in Illinois). MTEs were used to predict complete flow duration curves (FDCs) of ungaged streams by developing 17 models corresponding to 17 points along the FDC. Model accuracy was evaluated using ten-fold cross-validation and the coefficient of determination (R2). During the validation, the gages withheld from the analysis represent ungaged watersheds. MTEs are shown to outperform global multiple-linear regression models for predictions in ungaged watersheds. The accuracy of models for low flow is enhanced by explicit consideration of variables that capture human interference in watershed hydrology (e.g., population). Human factors (e.g., population and groundwater use) appear in the regionalizations for low flows, while annual and seasonal precipitation and drainage area are important for regionalizations of all flows. The results of this study have important implications for predictions in ungaged watersheds as well as gaged watersheds subject to anthropogenically-driven hydrologic changes.

  17. Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care

    Cancer.gov

    Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care, a 2010 workshop sponsored by the Epidemiology and Genomics Research Program.

  18. Quantitative Earthquake Prediction on Global and Regional Scales

    SciTech Connect

    Kossobokov, Vladimir G.

    2006-03-23

    for mega-earthquakes of M9.0+. The monitoring at regional scales may require application of a recently proposed scheme for the spatial stabilization of the intermediate-term middle-range predictions. The scheme guarantees a more objective and reliable diagnosis of times of increased probability and is less restrictive to input seismic data. It makes feasible reestablishment of seismic monitoring aimed at prediction of large magnitude earthquakes in Caucasus and Central Asia, which to our regret, has been discontinued in 1991. The first results of the monitoring (1986-1990) were encouraging, at least for M6.5+.

  19. Life prediction methodology for ceramic components of advanced heat engines. Phase 1: Volume 1, Final report

    SciTech Connect

    Cuccio, J.C.; Brehm, P.; Fang, H.T.

    1995-03-01

    Emphasis of this program is to develop and demonstrate ceramics life prediction methods, including fast fracture, stress rupture, creep, oxidation, and nondestructive evaluation. Significant advancements were made in these methods and their predictive capabilities successfully demonstrated.

  20. Defining and predicting structurally conserved regions in protein superfamilies

    PubMed Central

    Huang, Ivan K.; Grishin, Nick V.

    2013-01-01

    Motivation: The structures of homologous proteins are generally better conserved than their sequences. This phenomenon is demonstrated by the prevalence of structurally conserved regions (SCRs) even in highly divergent protein families. Defining SCRs requires the comparison of two or more homologous structures and is affected by their availability and divergence, and our ability to deduce structurally equivalent positions among them. In the absence of multiple homologous structures, it is necessary to predict SCRs of a protein using information from only a set of homologous sequences and (if available) a single structure. Accurate SCR predictions can benefit homology modelling and sequence alignment. Results: Using pairwise DaliLite alignments among a set of homologous structures, we devised a simple measure of structural conservation, termed structural conservation index (SCI). SCI was used to distinguish SCRs from non-SCRs. A database of SCRs was compiled from 386 SCOP superfamilies containing 6489 protein domains. Artificial neural networks were then trained to predict SCRs with various features deduced from a single structure and homologous sequences. Assessment of the predictions via a 5-fold cross-validation method revealed that predictions based on features derived from a single structure perform similarly to ones based on homologous sequences, while combining sequence and structural features was optimal in terms of accuracy (0.755) and Matthews correlation coefficient (0.476). These results suggest that even without information from multiple structures, it is still possible to effectively predict SCRs for a protein. Finally, inspection of the structures with the worst predictions pinpoints difficulties in SCR definitions. Availability: The SCR database and the prediction server can be found at http://prodata.swmed.edu/SCR. Contact: 91huangi@gmail.com or grishin@chop.swmed.edu Supplementary information: Supplementary data are available at Bioinformatics

  1. Regional Earth System Prediction for the Chesapeake Bay

    NASA Astrophysics Data System (ADS)

    Murtugudde, R. G.

    2009-12-01

    While the IPCC will continue to lead Earth System projections for global issues such as greenhouse gas levels and global temperature increase, high-resolution regional Earth System predictions will be crucial for producing effective decision-making tools for day-to-day, sustainable Earth System management and adaptive management of resources. Regional Earth System predictions and projections at the order of a few meters resolution from days to decades must be validated and provide uncertainties and skill scores to be usable. While the task is daunting, it would be criminally negligent of the global human not to embark on this task immediately. The observational needs for the integrated natural-human system for the regional Earth System are distinct from the global needs even though there are many overlaps. A prototype has been built for the Chesapeake Bay which issues routine seasonal outlooks and decadal projections for the air and watershed with linked products that include forecasts of pathogens, harmful algal blooms, sea nettles, fisheries, etc. A decision-making tool has been developed to allow the users to explore what-if scenarios and see the impact on the health of the Bay. Environmental indicators are being developed using mortality and morbidity data to generate predictive, pre-emptive, and personalized health forecasts. Skill of the forecasts and future plans will be discussed.

  2. Prediction of Active-Region CME Productivity from Magnetograms

    NASA Technical Reports Server (NTRS)

    Falconer, D. A.; Moore, R. L.; Gary, G. A.

    2004-01-01

    We report results of an expanded evaluation of whole-active-region magnetic measures as predictors of active-region coronal mass ejection (CME) productivity. Previously, in a sample of 17 vector magnetograms of 12 bipolar active regions observed by the Marshall Space Flight Center (MSFC) vector magnetograph, from each magnetogram we extracted a measure of the size of the active region (the active region s total magnetic flux a) and four measures of the nonpotentiality of the active region: the strong-shear length L(sub SS), the strong-gradient length L(sub SG), the net vertical electric current I(sub N), and the net-current magnetic twist parameter alpha (sub IN). This sample size allowed us to show that each of the four nonpotentiality measures was statistically significantly correlated with active-region CME productivity in time windows of a few days centered on the day of the magnetogram. We have now added a fifth measure of active-region nonpotentiality (the best-constant-alpha magnetic twist parameter (alpha sub BC)), and have expanded the sample to 36 MSFC vector magnetograms of 31 bipolar active regions. This larger sample allows us to demonstrate statistically significant correlations of each of the five nonpotentiality measures with future CME productivity, in time windows of a few days starting from the day of the magnetogram. The two magnetic twist parameters (alpha (sub 1N) and alpha (sub BC)) are normalized measures of an active region s nonpotentially in that they do not depend directly on the size of the active region, while the other three nonpotentiality measures (L(sub SS), L(sub SG), and I(sub N)) are non-normalized measures in that they do depend directly on active-region size. We find (1) Each of the five nonpotentiality measures is statistically significantly correlated (correlation confidence level greater than 95%) with future CME productivity and has a CME prediction success rate of approximately 80%. (2) None of the nonpotentiality

  3. Congenital heart disease in Mexico: advances of the regionalization project.

    PubMed

    Calderón-Colmenero, Juan; Cervantes-Salazar, Jorge; Curi-Curi, Pedro; Ramírez-Marroquín, Samuel

    2013-04-01

    Consistent with the mission of the World Society for Pediatric and Congenital Heart Surgery to promote health care for children with congenital heart disease all around the world, a Mexican Association of Specialists in Congenital Heart Disease (abbreviated in Spanish as AMECC) was created in Mexico in 2008. Our efforts were coordinated with those of the National Health Secretary with the objective being implementation of a national plan for regionalization of care for patients with congenital heart disease. To improve our knowledge related to technologic and human resources for management of congenital heart disease, we developed a national survey. Finally, a national database was created for collecting all Mexican centers' information related to congenital heart disease care in order to quantify the advances related to the proposed plans. The database utilized international consensus nomenclature. The aim of this article is to show the sequence of our actions in relation to direct accomplishments and the current status of congenital heart disease care in Mexico. This article emphasizes the main aspects of these actions: regionalization project implementation, national survey results, and cardiovascular pediatric surgical database creation. Knowledge of outcomes related to successful actions would be useful for those countries that face similar challenges and may lead them to consider adoption of similar measures with the respective adjustments to their own reality.

  4. Understanding and predicting the regional sun-hurricane count relationship

    NASA Astrophysics Data System (ADS)

    Hodges, Robert Edward

    North Atlantic hurricanes constitute a threat to both life and property. The warm seas found in tropical low-latitudes provide a breeding ground for hurricanes, with nearly continuous heat and moisture fluxes into near-surface air. Traditionally, the sun's role in hurricane climate studies is acknowledged as a time-marker for ocean heat content, with calendar date predicting hurricane frequency and intensity. However, a series of investigations into a different type of sun-hurricane relationship has uncovered a link between solar activity and hurricane intensity and frequency. High solar activity at a daily timescale is understood to weaken hurricanes in the southwest Atlantic yet correspond to increased hurricane intensity in the southeast Atlantic. At a seasonal timescale, high solar activity is shown to correspond with fewer U.S.-landfalling hurricanes. A gap in the knowledge exists on how and where solar activity influences seasonal hurricane frequency over and within the North Atlantic basin. This study is quantitative featuring exploratory analysis and inferential modeling, with diagnosis and prediction of the sun-hurricane count relationship over space being the primary contribution to science and society. It is carried out via exploratory data analysis and statistical modeling. Hurricane and climate data are binned in equal-area hexagon regions. Count differences for periods of high solar activity (i.e, high sunspot number) feature fewer hurricanes across the Caribbean, Gulf of Mexico, and along the eastern seaboard of the United States when sunspots are numerous. In contrast, fewer hurricanes are observed in the central North Atlantic when sunspots are few. The sun-hurricane connection is as important as the El Nino Southern Oscillation toward statistically explaining regional hurricane occurrences. Regression results indicate a 30% reduction in probability of annual hurricane occurrence for southeastern Cuba, the southern Bahama islands, Haiti, and

  5. Predictability and prediction of summer rainfall in the arid and semi-arid regions of China

    NASA Astrophysics Data System (ADS)

    Xing, Wen; Wang, Bin

    2016-09-01

    Northwest China (NWC) is an arid and semi-arid region where climate variability and environmental changes are sensitive to precipitation. The present study explores sources and limits of predictability of summer precipitation over NWC using the predictable mode analysis (PMA) of percentage of rainfall anomaly data. Two major modes of NWC summer rainfall variability are identified which are tied to Eurasian continental scale precipitation variations. The first mode features wet northern China corresponding to dry central Siberia and wet Mongolia, which is mainly driven by tropical Pacific sea surface temperature anomalies (SSTA). The second mode features wet western China reflecting wet Central Asia and dry Ural-western Siberia, which strongly links to Indian Ocean SSTA. Anomalous land warming over Eurasia also provides important precursors for the two modes. The cross-validated hindcast results demonstrate these modes can be predicted with significant correlation skills, suggesting that they may be considered as predictable modes. The domain averaged temporal correlation coefficient (TCC) skill during 1979 to 2015 using 0-month (1-month) lead models is 0.39 (0.35), which is considerably higher than dynamical models' multi-model ensemble mean skill (-0.02). Maximum potential attainable prediction skills are also estimated and discussed. The result illustrates advantage of PMA in predicting rainfall over dry land areas and large room for dynamical model improvement. However, secular changes of predictors need to be detected continuously in order to make practical useful prediction.

  6. Predicting regional lung deposition of environmental tobacco smoke particles

    SciTech Connect

    Nazaroff, W.W.; Hung, W.Y.; Sasse, A.G.B.M.; Gadgil, A.J.

    1993-10-01

    Inhalation exposure of environmental tobacco smoke (ETS) particles may increase health risks, but only to the extent that the particles deposit in the respiratory tract. We describe a technique to predict regional lung deposition of environmental tobacco smoke particles. Interpretation of particle size distribution measurements after cigarette combustion by a smoking machine in a test room yields an effective emissions profile. An aerosol dynamics model is used to predict indoor particle concentrations resulting from a specified combination of smoking frequency and building factors. By utilizing a lung deposition model, the rate of ETS mass accumulation in human lungs is then determined as a function of particle size and lung airway generation. Considering emissions of sidestream smoke only, residential exposures of nonsmokers to ETS are predicted to cause rates of total respiratory tract particle deposition in the range of 0.4-0.7 {mu}g/day per kg of body weight for light smoking in a well-ventilated residence and 8-13 {mu}g/day per kg for moderately heavy smoking in a poorly ventilated residence. Emissions of sidestream plus mainstream smoke lead to predicted deposition rates about a factor of 4 higher. This technique should be useful for evaluating health risks and control techniques associated with exposure to ETS particles. 36 refs., 6 figs., 3 tabs.

  7. Application of NASA's Advanced Life Support Technologies in Polar Regions

    NASA Technical Reports Server (NTRS)

    Bubenheim, David L.

    1997-01-01

    The problems of obtaining adequate pure drinking water and disposing of liquid and solid waste in the U.S Arctic, a region where virtually all water is frozen solid for much of the year, has led to unsanitary solutions. Sanitation and a safe water supply are particularly problems in rural villages. These villages are without running water and use plastic buckets for toilets. The outbreak of diseases is believed to be partially attributable to exposure to human waste and lack of sanitation. Villages with the most frequent outbreaks of disease are those in which running water is difficult to obtain. Waste is emptied into open lagoons, rivers, or onto the sea coast. It does not degrade rapidly and in addition to affecting human health, can be harmful to the fragile ecology of the Arctic and the indigenous wildlife and fish populations. Current practices for waste management and sanitation pose serious human hazards as well as threaten the environment. NASA's unique knowledge of water/wastewater treatment systems for extreme environments, identified in the Congressional Office of Technology Assessment report entitled An Alaskan Challenge: Native Villagt Sanitation, may offer practical solutions addressing the issues of safe drinking water and effective sanitation practices in rural villages. NASA's advanced life support technologies are being combined with Arctic science and engineering knowledge to address the unique needs of the remote communities of Alaska through the Advanced Life Systems for Extreme Environments (ALSEE) project. ALSEE is a collaborative effort involving the NASA, the State of Alaska, the University of Alaska, the North Slope Borough of Alaska, Ilisagvik College in Barrow and the National Science Foundation (NSF). The focus is a major issue in the State of Alaska and other areas of the Circumpolar North; the health and welfare of its people, their lives and the subsistence lifestyle in remote communities, economic opportunity, and care for the

  8. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    NASA Technical Reports Server (NTRS)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This presentation describes the capabilities of three-dimensional thermal power model of advanced stirling radioisotope generator (ASRG). The performance of the ASRG is presented for different scenario, such as Venus flyby with or without the auxiliary cooling system.

  9. Change in avian abundance predicted from regional forest inventory data

    USGS Publications Warehouse

    Twedt, Daniel J.; Tirpak, John M.; Jones-Farrand, D. Todd; Thompson, Frank R.; Uihlein, William B.; Fitzgerald, Jane A.

    2010-01-01

    An inability to predict population response to future habitat projections is a shortcoming in bird conservation planning. We sought to predict avian response to projections of future forest conditions that were developed from nationwide forest surveys within the Forest Inventory and Analysis (FIA) program. To accomplish this, we evaluated the historical relationship between silvicolous bird populations and FIA-derived forest conditions within 25 ecoregions that comprise the southeastern United States. We aggregated forest area by forest ownership, forest type, and tree size-class categories in county-based ecoregions for 5 time periods spanning 1963-2008. We assessed the relationship of forest data with contemporaneous indices of abundance for 24 silvicolous bird species that were obtained from Breeding Bird Surveys. Relationships between bird abundance and forest inventory data for 18 species were deemed sufficient as predictive models. We used these empirically derived relationships between regional forest conditions and bird populations to predict relative changes in abundance of these species within ecoregions that are anticipated to coincide with projected changes in forest variables through 2040. Predicted abundances of these 18 species are expected to remain relatively stable in over a quarter (27%) of the ecoregions. However, change in forest area and redistribution of forest types will likely result in changed abundance of some species within many ecosystems. For example, abundances of 11 species, including pine warbler (Dendroica pinus), brown-headed nuthatch (Sitta pusilla), and chuckwills- widow (Caprimulgus carolinensis), are projected to increase within more ecoregions than ecoregions where they will decrease. For 6 other species, such as blue-winged warbler (Vermivora pinus), Carolina wren (Thryothorus ludovicianus), and indigo bunting (Passerina cyanea), we projected abundances will decrease within more ecoregions than ecoregions where they will

  10. The role of radiation-dynamics interaction in regional numerical weather prediction

    NASA Technical Reports Server (NTRS)

    Chang, Chia-Bo

    1988-01-01

    The role of radiation-dynamics interaction in regional numerical weather prediction of severe storm environment and mesoscale convective systems over the United States is researched. Based upon the earlier numerical model simulation experiments, it is believed that such interaction can have a profound impact on the dynamics and thermodynamics of regional weather systems. The research will be carried out using real-data model forecast experiments performed on the Cray-X/MP computer. The forecasting system to be used is a comprehensive mesoscale prediction system which includes analysis and initialization, the dynamic model, and the post-forecast diagnosis codes. The model physics are currently undergoing many improvements in parameterizing radiation processes in the model atmosphere. The forecast experiments in conjunction with in-depth model verification and diagnosis are aimed at a quantitative understanding of the interaction between atmospheric radiation and regional dynamical processes in mesoscale models as well as in nature. Thus, significant advances in regional numerical weather prediction can be made. Results shall also provide valuable information for observational designs in the area of remote sensing techniques to study the characteristics of air-land thermal interaction and moist processes under various atmospheric conditions.

  11. Predicting redox conditions in groundwater at a regional scale

    USGS Publications Warehouse

    Tesoriero, Anthony J.; Terziotti, Silvia; Abrams, Daniel B.

    2015-01-01

    Defining the oxic-suboxic interface is often critical for determining pathways for nitrate transport in groundwater and to streams at the local scale. Defining this interface on a regional scale is complicated by the spatial variability of reaction rates. The probability of oxic groundwater in the Chesapeake Bay watershed was predicted by relating dissolved O2 concentrations in groundwater samples to indicators of residence time and/or electron donor availability using logistic regression. Variables that describe surficial geology, position in the flow system, and soil drainage were important predictors of oxic water. The probability of encountering oxic groundwater at a 30 m depth and the depth to the bottom of the oxic layer were predicted for the Chesapeake Bay watershed. The influence of depth to the bottom of the oxic layer on stream nitrate concentrations and time lags (i.e., time period between land application of nitrogen and its effect on streams) are illustrated using model simulations for hypothetical basins. Regional maps of the probability of oxic groundwater should prove useful as indicators of groundwater susceptibility and stream susceptibility to contaminant sources derived from groundwater.

  12. Predicting Redox Conditions in Groundwater at a Regional Scale.

    PubMed

    Tesoriero, Anthony J; Terziotti, Silvia; Abrams, Daniel B

    2015-08-18

    Defining the oxic-suboxic interface is often critical for determining pathways for nitrate transport in groundwater and to streams at the local scale. Defining this interface on a regional scale is complicated by the spatial variability of reaction rates. The probability of oxic groundwater in the Chesapeake Bay watershed was predicted by relating dissolved O2 concentrations in groundwater samples to indicators of residence time and/or electron donor availability using logistic regression. Variables that describe surficial geology, position in the flow system, and soil drainage were important predictors of oxic water. The probability of encountering oxic groundwater at a 30 m depth and the depth to the bottom of the oxic layer were predicted for the Chesapeake Bay watershed. The influence of depth to the bottom of the oxic layer on stream nitrate concentrations and time lags (i.e., time period between land application of nitrogen and its effect on streams) are illustrated using model simulations for hypothetical basins. Regional maps of the probability of oxic groundwater should prove useful as indicators of groundwater susceptibility and stream susceptibility to contaminant sources derived from groundwater. PMID:26230618

  13. Predicting Redox Conditions in Groundwater at a Regional Scale.

    PubMed

    Tesoriero, Anthony J; Terziotti, Silvia; Abrams, Daniel B

    2015-08-18

    Defining the oxic-suboxic interface is often critical for determining pathways for nitrate transport in groundwater and to streams at the local scale. Defining this interface on a regional scale is complicated by the spatial variability of reaction rates. The probability of oxic groundwater in the Chesapeake Bay watershed was predicted by relating dissolved O2 concentrations in groundwater samples to indicators of residence time and/or electron donor availability using logistic regression. Variables that describe surficial geology, position in the flow system, and soil drainage were important predictors of oxic water. The probability of encountering oxic groundwater at a 30 m depth and the depth to the bottom of the oxic layer were predicted for the Chesapeake Bay watershed. The influence of depth to the bottom of the oxic layer on stream nitrate concentrations and time lags (i.e., time period between land application of nitrogen and its effect on streams) are illustrated using model simulations for hypothetical basins. Regional maps of the probability of oxic groundwater should prove useful as indicators of groundwater susceptibility and stream susceptibility to contaminant sources derived from groundwater.

  14. Advances and computational tools towards predictable design in biological engineering.

    PubMed

    Pasotti, Lorenzo; Zucca, Susanna

    2014-01-01

    The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated.

  15. Advancing Satellite-Based Flood Prediction in Complex Terrain Using High-Resolution Numerical Weather Prediction

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Anagnostou, E. N.; Nikolopoulos, E. I.; Bartsotas, N. S.

    2015-12-01

    Floods constitute one of the most significant and frequent natural hazard in mountainous regions. Satellite-based precipitation products offer in many cases the only available source of QPE. However, satellite-based QPE over complex terrain suffer from significant bias that limits their applicability for hydrologic modeling. In this work we investigate the potential of a new correction procedure, which involves the use of high-resolution numerical weather prediction (NWP) model simulations to adjust satellite QPE. Adjustment is based on the pdf matching of satellite and NWP (used as reference) precipitation distribution. The impact of correction procedure on simulating the hydrologic response is examined for 15 storm events that generated floods over the mountainous Upper Adige region of Northern Italy. Atmospheric simulations were performed at 1-km resolution from a state-of-the-art atmospheric model (RAMS/ICLAMS). The proposed error correction procedure was then applied on the widely used TRMM 3B42 satellite precipitation product and the evaluation of the correction was based on independent in situ precipitation measurements from a dense rain gauge network (1 gauge / 70 km2) available in the study area. Satellite QPE, before and after correction, are used to simulate flood response using ARFFS (Adige River Flood Forecasting System), a semi-distributed hydrologic model, which is used for operational flood forecasting in the region. Results showed that bias in satellite QPE before correction was significant and had a tremendous impact on the simulation of flood peak, however the correction procedure was able to reduce bias in QPE and therefore improve considerably the simulated flood hydrograph.

  16. Advanced GIS Exercise: Predicting Rainfall Erosivity Index Using Regression Analysis

    ERIC Educational Resources Information Center

    Post, Christopher J.; Goddard, Megan A.; Mikhailova, Elena A.; Hall, Steven T.

    2006-01-01

    Graduate students from a variety of agricultural and natural resource fields are incorporating geographic information systems (GIS) analysis into their graduate research, creating a need for teaching methodologies that help students understand advanced GIS topics for use in their own research. Graduate-level GIS exercises help students understand…

  17. Factors that Predict Who Takes Advanced Courses in Cognitive Therapy

    ERIC Educational Resources Information Center

    Pehlivanidis, Artemios

    2007-01-01

    Training in Cognitive Therapy (CT) includes theoretical and didactic components combined with clinical supervision. An introductory course in CT might satisfy training needs in psychotherapy and help in the selection of those trainees who wish to continue to an advanced training level. Predictors of success at such an introductory course have been…

  18. Perceptions and Predictions of Expertise in Advanced Musical Learners

    ERIC Educational Resources Information Center

    Papageorgi, Ioulia; Creech, Andrea; Haddon, Elizabeth; Morton, Frances; De Bezenac, Christophe; Himonides, Evangelos; Potter, John; Duffy, Celia; Whyton, Tony; Welch, Graham

    2010-01-01

    The aim of this article was to compare musicians' views on (a) the importance of musical skills and (b) the nature of expertise. Data were obtained from a specially devised web-based questionnaire completed by advanced musicians representing four musical genres (classical, popular, jazz, Scottish traditional) and varying degrees of professional…

  19. Evaluation of precipitation predictions in a regional climate simulation

    SciTech Connect

    Costigan, K.R.; Bossert, J.E.; Langely, D.L.

    1998-12-01

    The research reported here is part of a larger project that is coupling a suite of environmental models to simulate the hydrologic cycle within river basins (Bossert et al., 1999). These models include the Regional Atmospheric Modeling System (RAMS), which provides meteorological variables and precipitation to the Simulator for Processes of Landscapes, Surface/Subsurface Hydrology (SPLASH). SPLASH partitions precipitation into evaporation, transpiration, soil water storage, surface runoff, and subsurface recharge. The runoff is collected within a simple river channel model and the Finite element Heat and Mass (FEHM) subsurface model is linked to the land surface and river flow model components to simulate saturated and unsaturated flow and changes in aquifer levels. The goal is to produce a fully interactive system of atmospheric, surface hydrology, river and groundwater models to allow water and energy feedbacks throughout the system. This paper focuses on the evaluation of the precipitation fields predicted by the RAMS model at different times during the 1992--1993 water year in the Rio Grande basin. The evaluation includes comparing the model predictions to the observed precipitation as reported by Cooperative Summary of the Day and SNOTEL reporting stations.

  20. New space technology advances knowledge of the remote polar regions. [Arctic and Antarctic regions

    NASA Technical Reports Server (NTRS)

    Macdonald, W. R.

    1974-01-01

    The application of ERTS-1 imagery is rapidly increasing man's knowledge of polar regions. Products compiled from this imagery at scales of 1:250,000, 1:500,000 and 1:1,000,000 are already providing valuable information to earth scientists working in Antarctica. Significant finds detected by these bench mark products were glaciological changes, advancement in ice fronts, discovery of new geographic features, and the repositioning of nunataks, islands, and ice tongues. Tests conducted in Antarctica have proven the feasibility of tracking Navy navigation satellites to establish ground control for positioning ERTS-1 imagery in remote areas. ERTS imagery coupled with satellite geodesy shows great promise and may prove to be the most practical and cost effective way to meet the small-scale cartographic requirements of the polar science community.

  1. Accuracy of three-dimensional soft tissue predictions in orthognathic surgery after Le Fort I advancement osteotomies.

    PubMed

    Ullah, R; Turner, P J; Khambay, B S

    2015-02-01

    Prediction of postoperative facial appearance after orthognathic surgery can be used for communication, managing patients' expectations,avoiding postoperative dissatisfaction and exploring different treatment options. We have assessed the accuracy of 3dMD Vultus in predicting the final 3-dimensional soft tissue facial morphology after Le Fort I advancement osteotomy. We retrospectively studied 13 patients who were treated with a Le Fort I advancement osteotomy alone. We used routine cone-beam computed tomographic (CT) images taken immediately before and a minimum of 6 months after operation, and 3dMD Vultus to virtually reposition the preoperative maxilla and mandible in their post operative positions to generate a prediction of what the soft tissue would look like. Segmented anatomical areas of the predicted mesh were then compared with the actual soft tissue. The means of the absolute distance between the 90th percentile of the mesh points for each region were calculated, and a one-sample Student's t test was used to calculate if the difference differed significantly from 3 mm.The differences in the mean absolute distances between the actual soft tissue and the prediction were significantly below 3 mm for all segmented anatomical areas (p < 0.001), and ranged from 0.65 mm (chin) to 1.17 mm (upper lip). 3dMD Vultus produces clinically satisfactory 3-dimensional facial soft tissue predictions after Le Fort I advancement osteotomy. The mass-spring model for prediction seems to be able to predict the position of the lip and chin, but its ability to predict nasal and paranasal areas could be improved.

  2. Predictions of the Impacts of Future Marcellus Shale Natural Gas Development on Regional Ozone

    NASA Astrophysics Data System (ADS)

    Roy, A.; Adams, P. J.; Robinson, A. L.

    2012-12-01

    Recent discovery of shale gas reserves, combined with advances in drilling and fracturing technology, are leading to extensive development of natural gas in the Marcellus Shale formation which underlies parts of Pennsylvania, West Virginia, Ohio and New York. To assess the impacts of this development on regional air quality, we have constructed a VOC, NOx and PM2.5 emissions inventory for the development and production of gas from the Marcellus formation. In 2020, we estimate that Marcellus activities will contribute about 12% to both regional NOx and VOC emissions. These numbers were obtained as a best estimate (mean) from a distribution obtained through several Monte Carlo runs. We speciated these emissions for use in a 3-D chemical transport model (PMCAMx) to simulate their effects on regional ozone. The projected Marcellus emissions for 2020 were added to a 2007 base inventory developed from the NEI. We have performed multiple simulations to investigate the effects of Marcellus development on regional air quality. The model predicts significant ozone changes in the Marcellus region with a uniform increase of few ppb across a wide region of the Northeast. Sensitivity studies are being performed to investigate the effects of emissions controls and sensitivity to VOC and NOx emissions.

  3. Climatic Instability and Regional Glacial Advances in the Late Ediacaran

    NASA Astrophysics Data System (ADS)

    Hannah, J. L.; Stein, H. J.; Marolf, N.; Bingen, B.

    2014-12-01

    "snowball Earth" event; rather, there may have been multiple Ediacaran glacial advances - perhaps only at high latitudes - marked by tillites of regional, but not global extent. [1] Bowring et al. 2002, Astrobiology 2: 457-458. [2] Shen et al. 2010, Prec. Res. 177: 241-252. [3] Hannah et al. 2007, Geochim. Cosmochim. Acta 71: A378.

  4. Evolution of the Canadian regional ensemble prediction system

    NASA Astrophysics Data System (ADS)

    Frenette, R.; Charron, M.; Li, X.; Gagnon, N.; Lavaysse, C.; Belair, S.; Carrera, M.; Yau, P.; Candille, G.

    2010-09-01

    A regional ensemble prediction system (REPS) over North America is expected to become operational at the Canadian Meteorological Centre (CMC) in late 2010 or early 2011. Different configurations of the REPS have already been tested and verified at different locations and time periods. The system was used during the Beijing 2008 summer Olympics and for the North American domain with a focus over southern British Columbia, Canada, during the 2010 Vancouver Olympics. It will also provide forecasts for tropical storms and hurricanes for the Haïti area during the summer and autumn of 2010. The Canadian Global Environmental Multiscale (GEM) model has been designed with the possibility to be run as a limited area model (GEM-LAM). The Canadian REPS is composed of 20 members running the GEM-LAM at a near 33 km grid spacing and with the same physical parameterizations as those present in the operational global deterministic prediction system at CMC. Two initial perturbation strategies (moist targeted singular vectors [SV] and the ensemble Kalman filter [EnKF]), as well as two stochastic methods for perturbations of parameterizations were verified against surface and upper air (rawinsondes) observations during summer and winter periods to determine which system has the best forecast abilities. For the SV-based REPS, 20 initial conditions (IC) are generated using a targeted SV perturbation method. These ICs are then used to run 20 global GEMs that will provide the lateral boundary conditions (LBCs) for each GEM-LAM. For the EnKF-based REPS, the 20 LBCs are built by downscaling the 20 members of the Canadian global ensemble prediction system (GEPS) to the resolution of the REPS. Verifications indicate that the EnKF approach gives better skill for summer and winter periods. The skill difference between the two systems comes mainly from the reliability attribute (smaller bias and reduced under-dispersion). Stochastic perturbations on model physical tendencies and on physical

  5. Life prediction of advanced materials for gas turbine application

    SciTech Connect

    Zamrik, S.Y.; Ray, A.; Koss, D.A.

    1995-10-01

    Most of the studies on the low cycle fatigue life prediction have been reported under isothermal conditions where the deformation of the material is strain dependent. In the development of gas turbines, components such as blades and vanes are exposed to temperature variations in addition to strain cycling. As a result, the deformation process becomes temperature and strain dependent. Therefore, the life of the component becomes sensitive to temperature-strain cycling which produces a process known as {open_quotes}thermomechanical fatigue, or TMF{close_quotes}. The TMF fatigue failure phenomenon has been modeled using conventional fatigue life prediction methods, which are not sufficiently accurate to quantitatively establish an allowable design procedure. To add to the complexity of TMF life prediction, blade and vane substrates are normally coated with aluminide, overlay or thermal barrier type coatings (TBC) where the durability of the component is dominated by the coating/substrate constitutive response and by the fatigue behavior of the coating. A number of issues arise from TMF depending on the type of temperature/strain phase cycle: (1) time-dependent inelastic behavior can significantly affect the stress response. For example, creep relaxation during a tensile or compressive loading at elevated temperatures leads to a progressive increase in the mean stress level under cyclic loading. (2) the mismatch in elastic and thermal expansion properties between the coating and the substrate can lead to significant deviations in the coating stress levels due to changes in the elastic modulii. (3) the {open_quotes}dry{close_quotes} corrosion resistance coatings applied to the substrate may act as primary crack initiation sites. Crack initiation in the coating is a function of the coating composition, its mechanical properties, creep relaxation behavior, thermal strain range and the strain/temperature phase relationship.

  6. Massive global ozone loss predicted following regional nuclear conflict.

    PubMed

    Mills, Michael J; Toon, Owen B; Turco, Richard P; Kinnison, Douglas E; Garcia, Rolando R

    2008-04-01

    We use a chemistry-climate model and new estimates of smoke produced by fires in contemporary cities to calculate the impact on stratospheric ozone of a regional nuclear war between developing nuclear states involving 100 Hiroshima-size bombs exploded in cities in the northern subtropics. We find column ozone losses in excess of 20% globally, 25-45% at midlatitudes, and 50-70% at northern high latitudes persisting for 5 years, with substantial losses continuing for 5 additional years. Column ozone amounts remain near or <220 Dobson units at all latitudes even after three years, constituting an extratropical "ozone hole." The resulting increases in UV radiation could impact the biota significantly, including serious consequences for human health. The primary cause for the dramatic and persistent ozone depletion is heating of the stratosphere by smoke, which strongly absorbs solar radiation. The smoke-laden air rises to the upper stratosphere, where removal mechanisms are slow, so that much of the stratosphere is ultimately heated by the localized smoke injections. Higher stratospheric temperatures accelerate catalytic reaction cycles, particularly those of odd-nitrogen, which destroy ozone. In addition, the strong convection created by rising smoke plumes alters the stratospheric circulation, redistributing ozone and the sources of ozone-depleting gases, including N(2)O and chlorofluorocarbons. The ozone losses predicted here are significantly greater than previous "nuclear winter/UV spring" calculations, which did not adequately represent stratospheric plume rise. Our results point to previously unrecognized mechanisms for stratospheric ozone depletion. PMID:18391218

  7. 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.

  8. Toward improved durability in advanced combustors and turbines: Progress in the prediction of thermomechanical loads

    NASA Technical Reports Server (NTRS)

    Sokolowski, Daniel E.; Ensign, C. Robert

    1986-01-01

    NASA is sponsoring the Turbine Engine Hot Section Technology (HOST) Project to address the need for improved durability in advanced combustors and turbines. Analytical and experimental activities aimed at more accurate prediction of the aerothermal environment, the thermomechanical loads, the material behavior and structural responses to such loading, and life predictions for high temperature cyclic operation have been underway for several years and are showing promising results. Progress is reported in the development of advanced instrumentation and in the improvement of combustor aerothermal and turbine heat transfer models that will lead to more accurate prediction of thermomechanical loads.

  9. Modelling Aerodynamically Generated Sound: Recent Advances in Rotor Noise Prediction

    NASA Technical Reports Server (NTRS)

    Brentner, Kenneth S.

    2000-01-01

    A great deal of progress has been made in the modeling of aerodynamically generated sound for rotors over the past decade. The Ffowcs Williams-Hawkings (FW-H ) equation has been the foundation for much of the development. Both subsonic and supersonic quadrupole noise formulations have been developed for the prediction of high-speed impulsive noise. In an effort to eliminate the need to compute the quadrupole contribution, the FW-H has also been utilized on permeable surfaces surrounding all physical noise sources. Comparison of the Kirchhoff formulation for moving surfaces with the FW-H equation have shown that the Kirchhoff formulation for moving surfaces can give erroneous results for aeroacoustic problems.

  10. Recent advances using rodent models for predicting human allergenicity

    SciTech Connect

    Knippels, Leon M.J. . E-mail: Knippels@voeding.tno.nl; Penninks, Andre H.

    2005-09-01

    The potential allergenicity of newly introduced proteins in genetically engineered foods has become an important safety evaluation issue. However, to evaluate the potential allergenicity and the potency of new proteins in our food, there are still no widely accepted and reliable test systems. The best-known allergy assessment proposal for foods derived from genetically engineered plants was the careful stepwise process presented in the so-called ILSI/IFBC decision tree. A revision of this decision tree strategy was proposed by a FAO/WHO expert consultation. As prediction of the sensitizing potential of the novel introduced protein based on animal testing was considered to be very important, animal models were introduced as one of the new test items, despite the fact that non of the currently studied models has been widely accepted and validated yet. In this paper, recent results are summarized of promising models developed in rat and mouse.

  11. Investigation of advanced UQ for CRUD prediction with VIPRE.

    SciTech Connect

    Eldred, Michael Scott

    2011-09-01

    This document summarizes the results from a level 3 milestone study within the CASL VUQ effort. It demonstrates the application of 'advanced UQ,' in particular dimension-adaptive p-refinement for polynomial chaos and stochastic collocation. The study calculates statistics for several quantities of interest that are indicators for the formation of CRUD (Chalk River unidentified deposit), which can lead to CIPS (CRUD induced power shift). Stochastic expansion methods are attractive methods for uncertainty quantification due to their fast convergence properties. For smooth functions (i.e., analytic, infinitely-differentiable) in L{sup 2} (i.e., possessing finite variance), exponential convergence rates can be obtained under order refinement for integrated statistical quantities of interest such as mean, variance, and probability. Two stochastic expansion methods are of interest: nonintrusive polynomial chaos expansion (PCE), which computes coefficients for a known basis of multivariate orthogonal polynomials, and stochastic collocation (SC), which forms multivariate interpolation polynomials for known coefficients. Within the DAKOTA project, recent research in stochastic expansion methods has focused on automated polynomial order refinement ('p-refinement') of expansions to support scalability to higher dimensional random input spaces [4, 3]. By preferentially refining only in the most important dimensions of the input space, the applicability of these methods can be extended from O(10{sup 0})-O(10{sup 1}) random variables to O(10{sup 2}) and beyond, depending on the degree of anisotropy (i.e., the extent to which randominput variables have differing degrees of influence on the statistical quantities of interest (QOIs)). Thus, the purpose of this study is to investigate the application of these adaptive stochastic expansion methods to the analysis of CRUD using the VIPRE simulation tools for two different plant models of differing random dimension, anisotropy, and

  12. Advance prediction of hypotension at cesarean delivery under spinal anesthesia.

    PubMed

    Kinsella, S M; Norris, M C

    1996-01-01

    Cardiovascular responses to supine inferior vena cava compression might predict hypotension risk during elective cesarean delivery using spinal anesthesia. In this pilot study we investigated 27 women before operation by taking blood pressure and heart rate measurements for 5 min in the left lateral position, 5 min supine, and then performed one further reading in the left lateral position and one sitting. Anesthesia with hyperbaric bupivacaine was rigorously standardised. A pre-operative 'supine stress test', combining an increase in maternal heart rate of greater than 10 beats/min or leg flexion movements while supine, was analysed. A positive supine stress test (SST) was 4.1 times more frequent in those with severe systolic hypotension below 70% of baseline (12 out of 16 women) than in those without (2 out of 11 women), with a sensitivity of 75% (95% C.I. 48% to 93%) and specificity of 82% (95% C.I. 48% to 98%). A positive test was associated with twice as much vasopressor use as a negative test (30.7 +/-/14.5 mg versus 13.5 +/-/ 9.9 mg; P = 0.0014). Unlike the SST, cardiovascular responses to the change from recumbent to sitting (tilt test) were not useful as a predictor of hypotension.

  13. Advance prediction of hypotension at cesarean delivery under spinal anesthesia.

    PubMed

    Kinsella, S M; Norris, M C

    1996-01-01

    Cardiovascular responses to supine inferior vena cava compression might predict hypotension risk during elective cesarean delivery using spinal anesthesia. In this pilot study we investigated 27 women before operation by taking blood pressure and heart rate measurements for 5 min in the left lateral position, 5 min supine, and then performed one further reading in the left lateral position and one sitting. Anesthesia with hyperbaric bupivacaine was rigorously standardised. A pre-operative 'supine stress test', combining an increase in maternal heart rate of greater than 10 beats/min or leg flexion movements while supine, was analysed. A positive supine stress test (SST) was 4.1 times more frequent in those with severe systolic hypotension below 70% of baseline (12 out of 16 women) than in those without (2 out of 11 women), with a sensitivity of 75% (95% C.I. 48% to 93%) and specificity of 82% (95% C.I. 48% to 98%). A positive test was associated with twice as much vasopressor use as a negative test (30.7 +/-/14.5 mg versus 13.5 +/-/ 9.9 mg; P = 0.0014). Unlike the SST, cardiovascular responses to the change from recumbent to sitting (tilt test) were not useful as a predictor of hypotension. PMID:15321375

  14. Hourly Wind Speed Interval Prediction in Arid Regions

    NASA Astrophysics Data System (ADS)

    Chaouch, M.; Ouarda, T.

    2013-12-01

    The long and extended warm and dry summers, the low rate of rain and humidity are the main factors that explain the increase of electricity consumption in hot arid regions. In such regions, the ventilating and air-conditioning installations, that are typically the most energy-intensive among energy consumption activities, are essential for securing healthy, safe and suitable indoor thermal conditions for building occupants and stored materials. The use of renewable energy resources such as solar and wind represents one of the most relevant solutions to overcome the increase of the electricity demand challenge. In the recent years, wind energy is gaining more importance among the researchers worldwide. Wind energy is intermittent in nature and hence the power system scheduling and dynamic control of wind turbine requires an estimate of wind energy. Accurate forecast of wind speed is a challenging task for the wind energy research field. In fact, due to the large variability of wind speed caused by the unpredictable and dynamic nature of the earth's atmosphere, there are many fluctuations in wind power production. This inherent variability of wind speed is the main cause of the uncertainty observed in wind power generation. Furthermore, producing wind power forecasts might be obtained indirectly by modeling the wind speed series and then transforming the forecasts through a power curve. Wind speed forecasting techniques have received substantial attention recently and several models have been developed. Basically two main approaches have been proposed in the literature: (1) physical models such as Numerical Weather Forecast and (2) statistical models such as Autoregressive integrated moving average (ARIMA) models, Neural Networks. While the initial focus in the literature has been on point forecasts, the need to quantify forecast uncertainty and communicate the risk of extreme ramp events has led to an interest in producing probabilistic forecasts. In short term

  15. Application of NASA's advanced life support technologies in polar regions

    NASA Astrophysics Data System (ADS)

    Bubenheim, D. L.; Lewis, C.

    1997-01-01

    NASA's advanced life support technologies are being combined with Arctic science and engineering knowledge in the Advanced Life Systems for Extreme Environments (ALSEE) project. This project addresses treatment and reduction of waste, purification and recycling of water, and production of food in remote communities of Alaska. The project focus is a major issue in the state of Alaska and other areas of the Circumpolar North; the health and welfare of people, their lives and the subsistence lifestyle in remote communities, care for the environment, and economic opportunity through technology transfer. The challenge is to implement the technologies in a manner compatible with the social and economic structures of native communities, the state, and the commercial sector. NASA goals are technology selection, system design and methods development of regenerative life support systems for planetary and Lunar bases and other space exploration missions. The ALSEE project will provide similar advanced technologies to address the multiple problems facing the remote communities of Alaska and provide an extreme environment testbed for future space applications. These technologies have never been assembled for this purpose. They offer an integrated approach to solving pressing problems in remote communities.

  16. Application of NASA's advanced life support technologies in polar regions.

    PubMed

    Bubenheim, D L; Lewis, C

    1997-01-01

    NASA's advanced life support technologies are being combined with Arctic science and engineering knowledge in the Advanced Life Systems for Extreme Environments (ALSEE) project. This project addresses treatment and reduction of waste, purification and recycling of water, and production of food in remote communities of Alaska. The project focus is a major issue in the state of Alaska and other areas of the Circumpolar North; the health and welfare of people, their lives and the subsistence lifestyle in remote communities, care for the environment, and economic opportunity through technology transfer. The challenge is to implement the technologies in a manner compatible with the social and economic structures of native communities, the state, and the commercial sector. NASA goals are technology selection, system design and methods development of regenerative life support systems for planetary and Lunar bases and other space exploration missions. The ALSEE project will provide similar advanced technologies to address the multiple problems facing the remote communities of Alaska and provide an extreme environment testbed for future space applications. These technologies have never been assembled for this purpose. They offer an integrated approach to solving pressing problems in remote communities.

  17. Regional Advanced Manufacturing Academy: An Agent of Change

    ERIC Educational Resources Information Center

    Schmeling, Daniel M.; Rose, Kevin

    2010-01-01

    Three Northeast Texas community colleges put aside service delivery areas and matters of "turf" to create Centers of Excellence that provided training throughout a nine county area. This consortium; along with 14 manufacturers, seven economic development corporations, and the regional workforce board, led the change in training a highly skilled…

  18. Advancing Tobacco Dependence Treatment Services in the Eastern Mediterranean Region

    PubMed Central

    Hawari, Feras I.; Bader, Rasha K.

    2014-01-01

    Tobacco use negatively affects health and is a major risk factor for non-communicable diseases (NCDs). Today, tobacco use ranks third among risk factors in North Africa and the Middle East in terms of disease burden. Despite the established need for these services, tobacco dependence treatment (TDT) services are still inadequate in the Eastern Mediterranean region (EMR). Among the main challenges hindering their expansion is the current lack of training opportunities. The provision of training and capacity-building—a key enabler of TDT—offers an excellent catalyst to launch TDT services in the region. This review discusses the need for TDT training in the EMR and describes a model for providing regional evidence-based training in line with international standards. The King Hussein Cancer Center in Amman, Jordan, is the regional host for Global Bridges, a worldwide TDT initiative. Using this model, they have trained 1,500 professionals and advocates from the EMR over the past three years. PMID:25364544

  19. Assimilation of thermodynamic information from advanced infrared sounders under partially cloudy skies for regional NWP

    NASA Astrophysics Data System (ADS)

    Wang, Pei; Li, Jun; Goldberg, Mitchell D.; Schmit, Timothy J.; Lim, Agnes H. N.; Li, Zhenglong; Han, Hyojin; Li, Jinlong; Ackerman, Steve A.

    2015-06-01

    Generally, only clear-infrared spectral radiances (not affected by clouds) are assimilated in weather analysis systems. This is due to difficulties in modeling cloudy radiances as well as in observing their vertical structure from space. To take full advantage of the thermodynamic information in advanced infrared (IR) sounder observations requires assimilating radiances from cloud-contaminated regions. An optimal imager/sounder cloud-clearing technique has been developed by the Cooperative Institute for Meteorological Satellite Studies at the University of Wisconsin-Madison. This technique can be used to retrieve clear column radiances through combining collocated multiband imager IR clear radiances and the sounder cloudy radiances; no background information is needed in this method. The imager/sounder cloud-clearing technique is similar to that of the microwave/IR cloud clearing in the derivation of the clear-sky equivalent radiances. However, it retains the original IR sounder resolution, which is critical for regional numerical weather prediction applications. In this study, we have investigated the assimilation of cloud-cleared IR sounder radiances using Atmospheric Infrared Sounder (AIRS)/Moderate Resolution Imaging Spectroradiometer for three hurricanes, Sandy (2012), Irene (2011), and Ike (2008). Results show that assimilating additional cloud-cleared AIRS radiances reduces the 48 and 72 h temperature forecast root-mean-square error by 0.1-0.3 K between 300 and 850 hPa. Substantial improvement in reducing track forecasts errors in the range of 10 km to 50 km was achieved.

  20. Development and Application of Advanced Weather Prediction Technologies for the Wind Energy Industry (Invited)

    NASA Astrophysics Data System (ADS)

    Mahoney, W. P.; Wiener, G.; Liu, Y.; Myers, W.; Johnson, D.

    2010-12-01

    Wind energy decision makers are required to make critical judgments on a daily basis with regard to energy generation, distribution, demand, storage, and integration. Accurate knowledge of the present and future state of the atmosphere is vital in making these decisions. As wind energy portfolios expand, this forecast problem is taking on new urgency because wind forecast inaccuracies frequently lead to substantial economic losses and constrain the national expansion of renewable energy. Improved weather prediction and precise spatial analysis of small-scale weather events are crucial for renewable energy management. In early 2009, the National Center for Atmospheric Research (NCAR) began a collaborative project with Xcel Energy Services, Inc. to perform research and develop technologies to improve Xcel Energy's ability to increase the amount of wind energy in their generation portfolio. The agreement and scope of work was designed to provide highly detailed, localized wind energy forecasts to enable Xcel Energy to more efficiently integrate electricity generated from wind into the power grid. The wind prediction technologies are designed to help Xcel Energy operators make critical decisions about powering down traditional coal and natural gas-powered plants when sufficient wind energy is predicted. The wind prediction technologies have been designed to cover Xcel Energy wind resources spanning a region from Wisconsin to New Mexico. The goal of the project is not only to improve Xcel Energy’s wind energy prediction capabilities, but also to make technological advancements in wind and wind energy prediction, expand our knowledge of boundary layer meteorology, and share the results across the renewable energy industry. To generate wind energy forecasts, NCAR is incorporating observations of current atmospheric conditions from a variety of sources including satellites, aircraft, weather radars, ground-based weather stations, wind profilers, and even wind sensors on

  1. Using Daily GCM Rainfall for Crop Yield Predictions: Advances and Challenges

    NASA Astrophysics Data System (ADS)

    Ines, A. M.; Hansen, J. W.; Robertson, A. W.; Baethgen, W.; Sun, L.; Indeje, M.

    2010-12-01

    Global climate models (GCMs) are promising for crop yield predictions not only because of their ability to simulate seasonal climate in advance of the growing season but also of their ability to simulate long-term climate changes. Despite this potential, a lot of challenges exist in using directly raw GCM data to crop models. First, because of the spatial scale mismatch between GCMs and crop models (10^2 km vs. 10^1 m), and second, due to biases and temporal structure mismatches in daily GCM rainfall relative to station observations. Crop growth is very sensitive to daily variations of rainfall thus any mismatch in daily rainfall statistics could adversely impact simulation of crop yields. In view of this, a lot of efforts have been made to correct biases in daily GCM rainfall relative to the climatology of a station or set of stations, and recently on some attempts to correct time structure in climate model rainfall. Here, we will present some advances in tailoring daily GCM rainfall for crop yield predictions and discuss some challenges underlying those methods. Specifically, we will present an improved nested GCM bias correction-stochastic disaggregation (BC-DisAg) method for improving the use of daily GCM rainfall for crop simulations and show some testing and evaluation results in different regions (Northeastern Kenya, Uruguay, Southern and Northeast Brazil). We also examined several ways of weighting GCM grid cells to better summarize their information contents for the nested approach, including inverse-distance weighting, arithmetic averaging, multiple linear regression and genetic algorithms. Finally, we will show a comparison between the GCM bias correction and Model Output Statistics (MOS)-correction downscaling in one of the selected sites at Katumani, Kenya. Our results showed that there is a significant improvement in the simulation of yields if the GCM bias correction (BC) is nested with stochastic disaggregation than just BC alone because of the

  2. Advancement into the Arctic region for bioactive sponge secondary metabolites.

    PubMed

    Abbas, Samuel; Kelly, Michelle; Bowling, John; Sims, James; Waters, Amanda; Hamann, Mark

    2011-01-01

    Porifera have long been a reservoir for the discovery of bioactive compounds and drug discovery. Most research in the area has focused on sponges from tropical and temperate waters, but more recently the focus has shifted to the less accessible colder waters of the Antarctic and, to a lesser extent, the Arctic. The Antarctic region in particular has been a more popular location for natural products discovery and has provided promising candidates for drug development. This article reviews groups of bioactive compounds that have been isolated and reported from the southern reaches of the Arctic Circle, surveys the known sponge diversity present in the Arctic waters, and details a recent sponge collection by our group in the Aleutian Islands, Alaska. The collection has yielded previously undescribed sponge species along with primary activity against opportunistic infectious diseases, malaria, and HCV. The discovery of new sponge species and bioactive crude extracts gives optimism for the isolation of new bioactive compounds from a relatively unexplored source.

  3. Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines

    PubMed Central

    Nielsen, Nanna Hellum; Jahoor, Ahmed; Jensen, Jens Due; Orabi, Jihad; Cericola, Fabio; Edriss, Vahid; Jensen, Just

    2016-01-01

    Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines) are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families. PMID:27783639

  4. Advancement into the Arctic Region for Bioactive Sponge Secondary Metabolites

    PubMed Central

    Abbas, Samuel; Kelly, Michelle; Bowling, John; Sims, James; Waters, Amanda; Hamann, Mark

    2011-01-01

    Porifera have long been a reservoir for the discovery of bioactive compounds and drug discovery. Most research in the area has focused on sponges from tropical and temperate waters, but more recently the focus has shifted to the less accessible colder waters of the Antarctic and, to a lesser extent, the Arctic. The Antarctic region in particular has been a more popular location for natural products discovery and has provided promising candidates for drug development. This article reviews groups of bioactive compounds that have been isolated and reported from the southern reaches of the Arctic Circle, surveys the known sponge diversity present in the Arctic waters, and details a recent sponge collection by our group in the Aleutian Islands, Alaska. The collection has yielded previously undescribed sponge species along with primary activity against opportunistic infectious diseases, malaria, and HCV. The discovery of new sponge species and bioactive crude extracts gives optimism for the isolation of new bioactive compounds from a relatively unexplored source. PMID:22163194

  5. New Ground Motion Prediction Models for Caucasus Region

    NASA Astrophysics Data System (ADS)

    Jorjiashvili, N.

    2012-12-01

    The Caucasus is a region of numerous natural hazards and ensuing disasters. Analysis of the losses due to past disasters indicates the those most catastrophic in the region have historically been due to strong earthquakes. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration because this parameter gives useful information for Seismic Hazard Assessment. Because of this, many peak ground acceleration attenuation relations have been developed by different authors. Besides, a few attenuation relations were developed for Caucasus region: Ambraseys et al. (1996,2005) which were based on entire European region and they were not focused locally on Caucasus Region; Smit et.al. (2000) that was based on a small amount of acceleration data that really is not enough. Since 2003 construction of Georgian Digital Seismic Network has started with the help of number of International organizations, Projects and Private companies. The works conducted involved scientific as well as organizational activities: Resolving technical problems concerning communication and data transmission. Thus, today we have a possibility to get real time data and make scientific research based on digital seismic data. Generally, ground motion and damage are influenced by the magnitude of the earthquake, the distance from the seismic source to site, the local ground conditions and the characteristics of buildings. Estimation of expected ground motion is a fundamental earthquake hazard assessment. This is the reason why this topic is emphasized in this study. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models are obtained by classical, statistical way, regression analysis. Also site ground conditions are considered because the same earthquake recorded at the same distance may cause different damage

  6. Predicting Regional Self-identification from Spatial Network Models

    PubMed Central

    Almquist, Zack W.; Butts, Carter T.

    2014-01-01

    Social scientists characterize social life as a hierarchy of environments, from the micro level of an individual’s knowledge and perceptions to the macro level of large-scale social networks. In accordance with this typology, individuals are typically thought to reside in micro- and macro-level structures, composed of multifaceted relations (e.g., acquaintanceship, friendship, and kinship). This article analyzes the effects of social structure on micro outcomes through the case of regional identification. Self identification occurs in many different domains, one of which is regional; i.e., the identification of oneself with a locationally-associated group (e.g., a “New Yorker” or “Parisian”). Here, regional self-identification is posited to result from an influence process based on the location of an individual’s alters (e.g., friends, kin or coworkers), such that one tends to identify with regions in which many of his or her alters reside. The structure of this paper is laid out as follows: initially, we begin with a discussion of the relevant social science literature for both social networks and identification. This discussion is followed with one about competing mechanisms for regional identification that are motivated first from the social network literature, and second by the social psychological and cognitive literature of decision making and heuristics. Next, the paper covers the data and methods employed to test the proposed mechanisms. Finally, the paper concludes with a discussion of its findings and further implications for the larger social science literature. PMID:25684791

  7. Urinary π-glutathione S-transferase Predicts Advanced Acute Kidney Injury Following Cardiovascular Surgery

    PubMed Central

    Shu, Kai-Hsiang; Wang, Chih-Hsien; Wu, Che-Hsiung; Huang, Tao-Min; Wu, Pei-Chen; Lai, Chien-Heng; Tseng, Li-Jung; Tsai, Pi-Ru; Connolly, Rory; Wu, Vin-Cent

    2016-01-01

    Urinary biomarkers augment the diagnosis of acute kidney injury (AKI), with AKI after cardiovascular surgeries being a prototype of prognosis scenario. Glutathione S-transferases (GST) were evaluated as biomarkers of AKI. Urine samples were collected in 141 cardiovascular surgical patients and analyzed for urinary alpha-(α-) and pi-(π-) GSTs. The outcomes of advanced AKI (KDIGO stage 2, 3) and all-cause in-patient mortality, as composite outcome, were recorded. Areas under the receiver operator characteristic (ROC) curves and multivariate generalized additive model (GAM) were applied to predict outcomes. Thirty-eight (26.9%) patients had AKI, while 12 (8.5%) were with advanced AKI. Urinary π-GST differentiated patients with/without advanced AKI or composite outcome after surgery (p < 0.05 by generalized estimating equation). Urinary π-GST predicted advanced AKI at 3 hrs post-surgery (p = 0.033) and composite outcome (p = 0.009), while the corresponding ROC curve had AUC of 0.784 and 0.783. Using GAM, the cutoff value of 14.7 μg/L for π-GST showed the best performance to predict composite outcome. The addition of π-GST to the SOFA score improved risk stratification (total net reclassification index = 0.47). Thus, urinary π-GST levels predict advanced AKI or hospital mortality after cardiovascular surgery and improve in SOFA outcome assessment specific to AKI. PMID:27527370

  8. Advancing monthly streamflow prediction accuracy of CART models using ensemble learning paradigms

    NASA Astrophysics Data System (ADS)

    Erdal, Halil Ibrahim; Karakurt, Onur

    2013-01-01

    SummaryStreamflow forecasting is one of the most important steps in the water resources planning and management. Ensemble techniques such as bagging, boosting and stacking have gained popularity in hydrological forecasting in the recent years. The study investigates the potential usage of two ensemble learning paradigms (i.e., bagging; stochastic gradient boosting) in building classification and regression trees (CARTs) ensembles to advance the streamflow prediction accuracy. The study, initially, investigates the use of classification and regression trees for monthly streamflow forecasting and employs a support vector regression (SVR) model as the benchmark model. The analytic results indicate that CART outperforms SVR in both training and testing phases. Although the obtained results of CART model in training phase are considerable, it is not in testing phase. Thus, to optimize the prediction accuracy of CART for monthly streamflow forecasting, we incorporate bagging and stochastic gradient boosting which are rooted in same philosophy, advancing the prediction accuracy of weak learners. Comparing with the results of bagged regression trees (BRTs) and stochastic gradient boosted regression trees (GBRTs) models possess satisfactory monthly streamflow forecasting performance than CART and SVR models. Overall, it is found that ensemble learning paradigms can remarkably advance the prediction accuracy of CART models in monthly streamflow forecasting.

  9. Predicting the Electron Diffusion Region in Asymmetric Magnetic Reconnection

    NASA Astrophysics Data System (ADS)

    Hesse, Michael; Liu, Yi-Hsin; Chen, Li-Jen; Bessho, Naoki; Kuznetsova, Masha; Burch, James; Birn, Joachim

    2016-04-01

    The launch of the Magnetospheric Multiscale mission is leading to a revolution in our understanding of the way magnetic reconnection works. During the first orbit phases, MMS science focuses on asymmetric reconnection, as is commonly found at the Earth's magnetopause. MMS observations have begun to support the view that reconnection operates primarily as a quasi-laminar process, supporting one class of theoretical precitions and a number of concurrent simulations. In this presentation, we present a brief overview of these theoretical and modeling predictions, and we present a comparison to recent MMS observations.

  10. Evaluation of the NMC regional ensemble prediction system during the Beijing 2008 Olympic Games

    NASA Astrophysics Data System (ADS)

    Li, Xiaoli; Tian, Hua; Deng, Guo

    2011-10-01

    Based on the B08RDP (Beijing 2008 Olympic Games Mesoscale Ensemble Prediction Research and Development Project) that was launched by the World Weather Research Programme (WWRP) in 2004, a regional ensemble prediction system (REPS) at a 15-km horizontal resolution was developed at the National Meteorological Center (NMC) of the China Meteorological Administration (CMA). Supplementing to the forecasters' subjective affirmation on the promising performance of the REPS during the 2008 Beijing Olympic Games (BOG), this paper focuses on the objective verification of the REPS for precipitation forecasts during the BOG period. By use of a set of advanced probabilistic verification scores, the value of the REPS compared to the quasi-operational global ensemble prediction system (GEPS) is assessed for a 36-day period (21 July-24 August 2008). The evaluation here involves different aspects of the REPS and GEPS, including their general forecast skills, specific attributes (reliability and resolution), and related economic values. The results indicate that the REPS generally performs significantly better for the short-range precipitation forecasts than the GEPS, and for light to heavy rainfall events, the REPS provides more skillful forecasts for accumulated 6- and 24-h precipitation. By further identifying the performance of the REPS through the attribute-focused measures, it is found that the advantages of the REPS over the GEPS come from better reliability (smaller biases and better dispersion) and increased resolution. Also, evaluation of a decision-making score reveals that a much larger group of users benefits from using the REPS forecasts than using the single model (the control run) forecasts, especially for the heavy rainfall events.

  11. Empirical relation between carbonate porosity and thermal maturity: an approach to regional porosity prediction.

    USGS Publications Warehouse

    Schmoker, J.W.

    1984-01-01

    Carbonate porosity can be predicted approximately on a regional scale as a function of thermal maturity. Thus: theta = a (TTI) b, where theta = regional porosity, a = a constant for a given region and varies by an order of magnitude, TTI = Lopatin's time-T index of thermal maturity and b approx -0.372. -K.A.R.

  12. Improved NASA-ANOPP Noise Prediction Computer Code for Advanced Subsonic Propulsion Systems

    NASA Technical Reports Server (NTRS)

    Kontos, K. B.; Janardan, B. A.; Gliebe, P. R.

    1996-01-01

    Recent experience using ANOPP to predict turbofan engine flyover noise suggests that it over-predicts overall EPNL by a significant amount. An improvement in this prediction method is desired for system optimization and assessment studies of advanced UHB engines. An assessment of the ANOPP fan inlet, fan exhaust, jet, combustor, and turbine noise prediction methods is made using static engine component noise data from the CF6-8OC2, E(3), and QCSEE turbofan engines. It is shown that the ANOPP prediction results are generally higher than the measured GE data, and that the inlet noise prediction method (Heidmann method) is the most significant source of this overprediction. Fan noise spectral comparisons show that improvements to the fan tone, broadband, and combination tone noise models are required to yield results that more closely simulate the GE data. Suggested changes that yield improved fan noise predictions but preserve the Heidmann model structure are identified and described. These changes are based on the sets of engine data mentioned, as well as some CFM56 engine data that was used to expand the combination tone noise database. It should be noted that the recommended changes are based on an analysis of engines that are limited to single stage fans with design tip relative Mach numbers greater than one.

  13. Measured and predicted rotor performance for the SERI advanced wind turbine blades

    NASA Astrophysics Data System (ADS)

    Tangler, J.; Smith, B.; Kelley, N.; Jager, D.

    1992-02-01

    Measured and predicted rotor performance for the Solar Energy Research Institute (SERI) advanced wind turbine blades were compared to assess the accuracy of predictions and to identify the sources of error affecting both predictions and measurements. An awareness of these sources of error contributes to improved prediction and measurement methods that will ultimately benefit future rotor design efforts. Propeller/vane anemometers were found to underestimate the wind speed in turbulent environments such as the San Gorgonio Pass wind farm area. Using sonic or cup anemometers, good agreement was achieved between predicted and measured power output for wind speeds up to 8 m/sec. At higher wind speeds an optimistic predicted power output and the occurrence of peak power at wind speeds lower than measurements resulted from the omission of turbulence and yaw error. In addition, accurate two-dimensional (2-D) airfoil data prior to stall and a post stall airfoil data synthesization method that reflects three-dimensional (3-D) effects were found to be essential for accurate performance prediction.

  14. Comparison of Advection–Diffusion Models and Neural Networks for Prediction of Advanced Water Treatment Effluent

    PubMed Central

    Mortula, Mohammed Maruf; Abdalla, Jamal; Ghadban, Ahmad A.

    2012-01-01

    Abstract An artificial neural network (ANN) can help in the prediction of advanced water treatment effluent and thus facilitate design practices. In this study, sets of 225 experimental data were obtained from a wastewater treatment process for the removal of phosphorus using oven-dried alum residuals in fixed-bed adsorbers. Five input variables (pH, initial phosphorus concentration, wastewater flow rate, porosity, and time) were used to test the efficiency of phosphorus removal at different times, and ANNs were then used to predict the effluent phosphorus concentration. Results of experiments that were conducted for different values of the input parameters made up the data used to train and test a multilayer perceptron using the back-propagation algorithm of the ANN. Values predicted by the ANN and the experimentally measured values were compared, and the accuracy of the ANN was evaluated. When ANN results were compared to the experimental results, it was concluded that the ANN results were accurate, especially during conditions of high phosphorus concentration. While the ANN model was able to predict the breakthrough point with good accuracy, the conventional advection–diffusion equation was not as accurate. A parametric study conducted to examine the effect of the initial pH and initial phosphorus concentration on the effluent phosphorus concentration at different times showed that lower influent pH values are the most suitable for this advanced treatment system. PMID:22783063

  15. Unsteady blade surface pressures on a large-scale advanced propeller - Prediction and data

    NASA Technical Reports Server (NTRS)

    Nallasamy, M.; Groeneweg, J. F.

    1990-01-01

    An unsteady three dimensional Euler analysis technique is employed to compute the flowfield of an advanced propeller operating at an angle of attack. The predicted blade pressure waveforms are compared with wind tunnel data at two Mach numbers, 0.5 and 0.2. The inflow angle is three degrees. For an inflow Mach number of 0.5, the predicted pressure response is in fair agreement with data: the predicted phases of the waveforms are in close agreement with data while the magnitudes are underpredicted. At the low Mach number of 0.2 (take-off) the numerical solution shows the formation of a leading edge vortex which is in qualitative agreement with measurements. However, the highly nonlinear pressure response measured on the blade suction surface is not captured in the present inviscid analysis.

  16. Unsteady blade-surface pressures on a large-scale advanced propeller: Prediction and data

    NASA Technical Reports Server (NTRS)

    Nallasamy, M.; Groeneweg, J. F.

    1990-01-01

    An unsteady 3-D Euler analysis technique is employed to compute the flow field of an advanced propeller operating at an angle of attack. The predicted blade pressure waveforms are compared with wind tunnel data at two Mach numbers, 0.5 and 0.2. The inflow angle is three degrees. For an inflow Mach number of 0.5, the predicted pressure response is in fair agreement with data: the predicted phases of the waveforms are in close agreement with data while the magnitudes are underpredicted. At the low Mach number of 0.2 (takeoff), the numerical solution shows the formation of a leading edge vortex which is in qualitative agreement with measurements. However, the highly nonlinear pressure response measured on the blade suction surface is not captured in the present inviscid analysis.

  17. Correlating CCM upper atmosphere parameters to surface observations for regional climate change predictions

    SciTech Connect

    Li, Xiangshang; Sailor, D.J.

    1997-11-01

    This paper explores the use of statistical downscaling of General Circulation Model (GCM) results for the purpose of regional climate change analysis. The strong correlation between surface observations and GCM upper air predictions is used in an approach very similar to the Model Output Statistics approach used in numerical weather prediction. The primary assumption in this analysis is that the statistical relationships remain unchanged under conditions of climatic change. These relations are applied to GCM upper atmosphere predictions for future (2*CO{sub 2}) climate predictions. The result is a set of regional climate change predictions conceptually valid at the scale of cities. The downscaling for specific cities within a GCM grid cell reveals some of the anticipated variability within the grid cell. In addition, multiple linear regression analysis may indicate warming that is significantly higher or lower for a particular region than the raw data from the GCM runs. 3 refs., 3 figs., 2 tabs.

  18. Advanced Technology Tech Prep Partnership for Northern Kane Regional Delivery System. Final Report.

    ERIC Educational Resources Information Center

    Elgin Community Coll., IL.

    A 1-year project was undertaken to continue implementation, evaluation, and revision of a model advanced technology partnership between Elgin Community College (ECC) and the Northern Kane Regional Delivery System in Illinois. The model program, which originally included three high schools, was expanded to include five additional high schools in…

  19. ArcRegionalization: a GIS-based Toolkit to Predict Streamflow in Ungauged Basins

    NASA Astrophysics Data System (ADS)

    Yuan, Y.; Cheng, Q.

    2005-12-01

    Regionalization, which aims to estimate the model parameters for the ungauged basins from the model parameters for the gauged basins within the same region, provides a method to predict the streamflow in the ungauged basins. However, most of regionalization researches have to calibrate model parameters and derive basin descriptors using two isolated software tools: hydrological modelling software and GIS. In order to facilitate model regionalization research, an ArcGIS extension: ArcRegionalization is developed with C# language to integrate basin descriptor derivation and hydrological models. ArcRegionalization not only provides basin descriptors derivation methods, widely used hydrological models, and regionalization methods, but also provides the interfaces to incorporate new basin descriptors, new hydrological models, and new regionalization methods. Finally, a case study of model regionalization in Oak Ridges Moraine area, southern Ontario, Canada is used to demonstrate the functions of ArcRegionalization.

  20. Effects of semantic predictability and regional dialect on vowel space reduction.

    PubMed

    Clopper, Cynthia G; Pierrehumbert, Janet B

    2008-09-01

    This study explored the interaction between semantic predictability and regional dialect variation in an analysis of speech produced by college-aged female talkers from the Northern, Midland, and Southern dialects of American English. Previous research on the effects of semantic predictability has shown that vowels in high semantic predictability contexts are temporally and spectrally reduced compared to vowels in low semantic predictability contexts. In the current study, an analysis of vowel duration confirmed temporal reduction in the high predictability condition. An analysis of vowel formant structure and vowel space dispersion revealed overall spectral reduction for the Southern talkers. For the Northern talkers, more extreme Northern Cities shifting occurred in the high predictability condition than in the low predictability condition. No effects of semantic predictability were observed for the Midland talkers. These findings suggest an interaction between semantic and indexical factors in vowel reduction processes.

  1. Sexual selection predicts advancement of avian spring migration in response to climate change

    PubMed Central

    Spottiswoode, Claire N; Tøttrup, Anders P; Coppack, Timothy

    2006-01-01

    Global warming has led to earlier spring arrival of migratory birds, but the extent of this advancement varies greatly among species, and it remains uncertain to what degree these changes are phenotypically plastic responses or microevolutionary adaptations to changing environmental conditions. We suggest that sexual selection could help to understand this variation, since early spring arrival of males is favoured by female choice. Climate change could weaken the strength of natural selection opposing sexual selection for early migration, which would predict greatest advancement in species with stronger female choice. We test this hypothesis comparatively by investigating the degree of long-term change in spring passage at two ringing stations in northern Europe in relation to a synthetic estimate of the strength of female choice, composed of degree of extra-pair paternity, relative testes size and degree of sexually dichromatic plumage colouration. We found that species with a stronger index of sexual selection have indeed advanced their date of spring passage to a greater extent. This relationship was stronger for the changes in the median passage date of the whole population than for changes in the timing of first-arriving individuals, suggesting that selection has not only acted on protandrous males. These results suggest that sexual selection may have an impact on the responses of organisms to climate change, and knowledge of a species' mating system might help to inform attempts at predicting these. PMID:17015341

  2. Regional Characterization of the Crust in Metropolitan Areas for Prediction of Strong Ground Motion

    NASA Astrophysics Data System (ADS)

    Hirata, N.; Sato, H.; Koketsu, K.; Umeda, Y.; Iwata, T.; Kasahara, K.

    2003-12-01

    Introduction: After the 1995 Kobe earthquake, the Japanese government increased its focus and funding of earthquake hazards evaluation, studies of man-made structures integrity, and emergency response planning in the major urban centers. A new agency, the Ministry of Education, Science, Sports and Culture (MEXT) has started a five-year program titled as Special Project for Earthquake Disaster Mitigation in Urban Areas (abbreviated to Dai-dai-toku in Japanese) since 2002. The project includes four programs: I. Regional characterization of the crust in metropolitan areas for prediction of strong ground motion. II. Significant improvement of seismic performance of structure. III. Advanced disaster management system. IV. Investigation of earthquake disaster mitigation research results. We will present the results from the first program conducted in 2002 and 2003. Regional Characterization of the Crust in Metropolitan Areas for Prediction of Strong Ground Motion: A long-term goal is to produce map of reliable estimations of strong ground motion. This requires accurate determination of ground motion response, which includes a source process, an effect of propagation path, and near surface response. The new five-year project was aimed to characterize the "source" and "propagation path" in the Kanto (Tokyo) region and Kinki (Osaka) region. The 1923 Kanto Earthquake is one of the important targets to be addressed in the project. The proximity of the Pacific and Philippine Sea subducting plates requires study of the relationship between earthquakes and regional tectonics. This project focuses on identification and geometry of: 1) Source faults, 2) Subducting plates and mega-thrust faults, 3) Crustal structure, 4) Seismogenic zone, 5) Sedimentary basins, 6) 3D velocity properties We have conducted a series of seismic reflection and refraction experiment in the Kanto region. In 2002 we have completed to deploy seismic profiling lines in the Boso peninsula (112 km) and the

  3. Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

    NASA Technical Reports Server (NTRS)

    Wilson, Scott D.; Reid, Terry V.; Schifer, Nicholas A.; Briggs, Maxwell H.

    2012-01-01

    The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two high-efficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical power output for a given net heat input. Microporous bulk insulation is used in the ground support test hardware to minimize the loss of thermal energy from the electric heat source to the environment. The insulation package is characterized before operation to predict how much heat will be absorbed by the convertor and how much will be lost to the environment during operation. In an effort to validate these predictions, numerous tasks have been performed, which provided a more accurate value for net heat input into the ASCs. This test and modeling effort included: (a) making thermophysical property measurements of test setup materials to provide inputs to the numerical models, (b) acquiring additional test data that was collected during convertor tests to provide numerical models with temperature profiles of the test setup via thermocouple and infrared measurements, (c) using multidimensional numerical models (computational fluid dynamics code) to predict net heat input of an operating convertor, and (d) using validation test hardware to provide direct comparison of numerical results and validate the multidimensional numerical models used to predict convertor net heat input. This effort produced high fidelity ASC net heat input predictions, which were successfully validated using

  4. Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

    PubMed Central

    Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

    2015-01-01

    Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC. PMID:26420960

  5. Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

    PubMed

    Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

    2015-09-28

    Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC.

  6. Interannual variability and predictability over the Arabian Penuinsula Winter monsoon region

    NASA Astrophysics Data System (ADS)

    Adnan Abid, Muhammad; Kucharski, Fred; Almazroui, Mansour; Kang, In-Sik

    2016-04-01

    Interannual winter rainfall variability and its predictability are analysed over the Arabian Peninsula region by using observed and hindcast datasets from the state-of-the-art European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal prediction System 4 for the period 1981-2010. An Arabian winter monsoon index (AWMI) is defined to highlight the Arabian Peninsula as the most representative region for the Northern Hemispheric winter dominating the summer rainfall. The observations show that the rainfall variability is relatively large over the northeast of the Arabian Peninsula. The correlation coefficient between the Nino3.4 index and rainfall in this region is 0.33, suggesting potentially some modest predictability, and indicating that El Nino increases and La Nina decreases the rainfall. Regression analysis shows that upper-level cyclonic circulation anomalies that are forced by El Nino Southern Oscillation (ENSO) are responsible for the winter rainfall anomalies over the Arabian region. The stronger (weaker) mean transient-eddy activity related to the upper-level trough induced by the warm (cold) sea-surface temperatures during El Nino (La Nina) tends to increase (decrease) the rainfall in the region. The model hindcast dataset reproduces the ENSO-rainfall connection. The seasonal mean predictability of the northeast Arabian rainfall index is 0.35. It is shown that the noise variance is larger than the signal over the Arabian Peninsula region, which tends to limit the prediction skill. The potential predictability is generally increased in ENSO years and is, in particular, larger during La Nina compared to El Nino years in the region. Furthermore, central Pacific ENSO events and ENSO events with weak signals in the Indian Ocean tend to increase predictability over the Arabian region.

  7. Prediction of Potential Cancer-Risk Regions Based on Transcriptome Data: Towards a Comprehensive View

    PubMed Central

    Alisoltani, Arghavan; Fallahi, Hossein; Ebrahimi, Mahdi; Ebrahimi, Mansour; Ebrahimie, Esmaeil

    2014-01-01

    A novel integrative pipeline is presented for discovery of potential cancer-susceptibility regions (PCSRs) by calculating the number of altered genes at each chromosomal region, using expression microarray datasets of different human cancers (HCs). Our novel approach comprises primarily predicting PCSRs followed by identification of key genes in these regions to obtain potential regions harboring new cancer-associated variants. In addition to finding new cancer causal variants, another advantage in prediction of such risk regions is simultaneous study of different types of genomic variants in line with focusing on specific chromosomal regions. Using this pipeline we extracted numbers of regions with highly altered expression levels in cancer condition. Regulatory networks were also constructed for different types of cancers following the identification of altered mRNA and microRNAs. Interestingly, results showed that GAPDH, LIFR, ZEB2, mir-21, mir-30a, mir-141 and mir-200c, all located at PCSRs, are common altered factors in constructed networks. We found a number of clusters of altered mRNAs and miRNAs on predicted PCSRs (e.g.12p13.31) and their common regulators including KLF4 and SOX10. Large scale prediction of risk regions based on transcriptome data can open a window in comprehensive study of cancer risk factors and the other human diseases. PMID:24796549

  8. High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder.

    PubMed

    Peng, Zhenling; Kurgan, Lukasz

    2015-10-15

    Intrinsically disordered proteins and regions (IDPs and IDRs) lack stable 3D structure under physiological conditions in-vitro, are common in eukaryotes, and facilitate interactions with RNA, DNA and proteins. Current methods for prediction of IDPs and IDRs do not provide insights into their functions, except for a handful of methods that address predictions of protein-binding regions. We report first-of-its-kind computational method DisoRDPbind for high-throughput prediction of RNA, DNA and protein binding residues located in IDRs from protein sequences. DisoRDPbind is implemented using a runtime-efficient multi-layered design that utilizes information extracted from physiochemical properties of amino acids, sequence complexity, putative secondary structure and disorder and sequence alignment. Empirical tests demonstrate that it provides accurate predictions that are competitive with other predictors of disorder-mediated protein binding regions and complementary to the methods that predict RNA- and DNA-binding residues annotated based on crystal structures. Application in Homo sapiens, Mus musculus, Caenorhabditis elegans and Drosophila melanogaster proteomes reveals that RNA- and DNA-binding proteins predicted by DisoRDPbind complement and overlap with the corresponding known binding proteins collected from several sources. Also, the number of the putative protein-binding regions predicted with DisoRDPbind correlates with the promiscuity of proteins in the corresponding protein-protein interaction networks. Webserver: http://biomine.ece.ualberta.ca/DisoRDPbind/.

  9. Long-term predictability of regions and dates of strong earthquakes

    NASA Astrophysics Data System (ADS)

    Kubyshen, Alexander; Doda, Leonid; Shopin, Sergey

    2016-04-01

    Results on the long-term predictability of strong earthquakes are discussed. It is shown that dates of earthquakes with M>5.5 could be determined in advance of several months before the event. The magnitude and the region of approaching earthquake could be specified in the time-frame of a month before the event. Determination of number of M6+ earthquakes, which are expected to occur during the analyzed year, is performed using the special sequence diagram of seismic activity for the century time frame. Date analysis could be performed with advance of 15-20 years. Data is verified by a monthly sequence diagram of seismic activity. The number of strong earthquakes expected to occur in the analyzed month is determined by several methods having a different prediction horizon. Determination of days of potential earthquakes with M5.5+ is performed using astronomical data. Earthquakes occur on days of oppositions of Solar System planets (arranged in a single line). At that, the strongest earthquakes occur under the location of vector "Sun-Solar System barycenter" in the ecliptic plane. Details of this astronomical multivariate indicator still require further research, but it's practical significant is confirmed by practice. Another one empirical indicator of approaching earthquake M6+ is a synchronous variation of meteorological parameters: abrupt decreasing of minimal daily temperature, increasing of relative humidity, abrupt change of atmospheric pressure (RAMES method). Time difference of predicted and actual date is no more than one day. This indicator is registered 104 days before the earthquake, so it was called as Harmonic 104 or H-104. This fact looks paradoxical, but the works of A. Sytinskiy and V. Bokov on the correlation of global atmospheric circulation and seismic events give a physical basis for this empirical fact. Also, 104 days is a quarter of a Chandler period so this fact gives insight on the correlation between the anomalies of Earth orientation

  10. Simulation studies of the impact of advanced observing systems on numerical weather prediction

    NASA Technical Reports Server (NTRS)

    Atlas, R.; Kalnay, E.; Susskind, J.; Reuter, D.; Baker, W. E.; Halem, M.

    1984-01-01

    To study the potential impact of advanced passive sounders and lidar temperature, pressure, humidity, and wind observing systems on large-scale numerical weather prediction, a series of realistic simulation studies between the European Center for medium-range weather forecasts, the National Meteorological Center, and the Goddard Laboratory for Atmospheric Sciences is conducted. The project attempts to avoid the unrealistic character of earlier simulation studies. The previous simulation studies and real-data impact tests are reviewed and the design of the current simulation system is described. Consideration is given to the simulation of observations of space-based sounding systems.

  11. A proposed predictive model for advanced fibrosis in patients with chronic hepatitis B and its validation.

    PubMed

    Nishikawa, Hiroki; Hasegawa, Kunihiro; Ishii, Akio; Takata, Ryo; Enomoto, Hirayuki; Yoh, Kazunori; Kishino, Kyohei; Shimono, Yoshihiro; Iwata, Yoshinori; Nakano, Chikage; Nishimura, Takashi; Aizawa, Nobuhiro; Sakai, Yoshiyuki; Ikeda, Naoto; Takashima, Tomoyuki; Iijima, Hiroko; Nishiguchi, Shuhei

    2016-08-01

    We created a predictive model using serum-based biomarkers for advanced fibrosis (F3 or more) in patients with chronic hepatitis B (CHB) and to confirm the accuracy in an independent cohort.A total of 249 CHB patients were analyzed. To achieve our study aim, a training group (n = 125) and a validation group (n = 124) were formed. In the training group, parameters related to the presence of advanced fibrosis in univariate and multivariate analyses were examined, and a formula for advanced fibrosis was created. Next, we verified the applicability of the predictive model in the validation group.Multivariate analysis identified that gamma-glutamyl transpeptidase (GGT, P = 0.0343) and platelet count (P = 0.0034) were significant predictors of the presence of advanced fibrosis, while Wisteria floribunda agglutinin-positive Mac-2-binding protein (WFA-M2BP, P = 0.0741) and hyaluronic acid (P = 0.0916) tended to be significant factors. Using these 4 parameters, we created the following formula: GMPH score = -0.755 - (0.015 × GGT) - (0.268 × WFA-M2BP) + (0.167 × platelet count) + (0.003 × hyaluronic acid). In 8 analyzed variables (WFA-M2BP, aspartate aminotransferase-to-platelet ratio index, FIB-4 index, prothrombin time, platelet count, hyaluronic acid, Forns index, and GMPH score), GMPH score had the highest area under the receiver operating characteristic (AUROC) curve for advanced fibrosis with a value of 0.8064 in the training group and in the validation group, GMPH score also had the highest AUROC (0.7782). In all subgroup analyses of the hepatitis B virus (HBV) status (HB surface antigen quantification, HBV-DNA quantification, and HBe antigen seropositivity), GMPH score in F3 or F4 was significantly lower than that in F0 to F2. In the above mentioned 8 variables, differences between the liver fibrosis stages (F0 to F1 vs F2, F2 vs F3, F3 vs F4, F0 to F1 vs F3, F0 to F1 vs F4, and F2 vs F4) for the entire

  12. A proposed predictive model for advanced fibrosis in patients with chronic hepatitis B and its validation

    PubMed Central

    Nishikawa, Hiroki; Hasegawa, Kunihiro; Ishii, Akio; Takata, Ryo; Enomoto, Hirayuki; Yoh, Kazunori; Kishino, Kyohei; Shimono, Yoshihiro; Iwata, Yoshinori; Nakano, Chikage; Nishimura, Takashi; Aizawa, Nobuhiro; Sakai, Yoshiyuki; Ikeda, Naoto; Takashima, Tomoyuki; Iijima, Hiroko; Nishiguchi, Shuhei

    2016-01-01

    Abstract We created a predictive model using serum-based biomarkers for advanced fibrosis (F3 or more) in patients with chronic hepatitis B (CHB) and to confirm the accuracy in an independent cohort. A total of 249 CHB patients were analyzed. To achieve our study aim, a training group (n = 125) and a validation group (n = 124) were formed. In the training group, parameters related to the presence of advanced fibrosis in univariate and multivariate analyses were examined, and a formula for advanced fibrosis was created. Next, we verified the applicability of the predictive model in the validation group. Multivariate analysis identified that gamma-glutamyl transpeptidase (GGT, P = 0.0343) and platelet count (P = 0.0034) were significant predictors of the presence of advanced fibrosis, while Wisteria floribunda agglutinin-positive Mac-2-binding protein (WFA+-M2BP, P = 0.0741) and hyaluronic acid (P = 0.0916) tended to be significant factors. Using these 4 parameters, we created the following formula: GMPH score = −0.755 − (0.015 × GGT) − (0.268 × WFA+-M2BP) + (0.167 × platelet count) + (0.003 × hyaluronic acid). In 8 analyzed variables (WFA+-M2BP, aspartate aminotransferase-to-platelet ratio index, FIB-4 index, prothrombin time, platelet count, hyaluronic acid, Forns index, and GMPH score), GMPH score had the highest area under the receiver operating characteristic (AUROC) curve for advanced fibrosis with a value of 0.8064 in the training group and in the validation group, GMPH score also had the highest AUROC (0.7782). In all subgroup analyses of the hepatitis B virus (HBV) status (HB surface antigen quantification, HBV-DNA quantification, and HBe antigen seropositivity), GMPH score in F3 or F4 was significantly lower than that in F0 to F2. In the above mentioned 8 variables, differences between the liver fibrosis stages (F0 to F1 vs F2, F2 vs F3, F3 vs F4, F0 to F1 vs F3, F0 to F1 vs F4, and F2 vs

  13. Predictive and preventive strategies to advance the treatments of cardiovascular and cerebrovascular diseases: the Ukrainian context

    PubMed Central

    2012-01-01

    Despite great efforts in treatments of cardiovascular diseases, the field requires innovative strategies because of high rates of morbidity, mortality and disability, indicating evident deficits in predictive vascular diagnosis and individualized treatment approaches. Talking about the vascular system, currently, physicians are not provided with integrated medical approaches to diagnose and treat vascular diseases. Only an individual global approach to the analysis of all segments in the vascular system of a patient allows finding the optimal way for vascular disease treatment. As for the existing methodology, there is a dominance of static methods such as X-ray contrast angiography and magnetic resonance imaging in angiomode. Taking into account the world experience, this article deals with innovative strategies, aiming at predictive diagnosis in vascular system, personalization of the biomedical treatment approaches, and targeted prevention of individual patient cohorts. Clinical examples illustrate the advances in corresponding healthcare sectors. Recommendations are provided to promote the field. PMID:23083430

  14. Strong topographic sheltering effects lead to spatially complex treeline advance and increased forest density in a subtropical mountain region.

    PubMed

    Greenwood, Sarah; Chen, Jan-Chang; Chen, Chaur-Tzuhn; Jump, Alistair S

    2014-12-01

    Altitudinal treelines are typically temperature limited such that increasing temperatures linked to global climate change are causing upslope shifts of treelines worldwide. While such elevational increases are readily predicted based on shifting isotherms, at the regional level the realized response is often much more complex, with topography and local environmental conditions playing an important modifying role. Here, we used repeated aerial photographs in combination with forest inventory data to investigate changes in treeline position in the Central Mountain Range of Taiwan over the last 60 years. A highly spatially variable upslope advance of treeline was identified in which topography is a major driver of both treeline form and advance. The changes in treeline position that we observed occurred alongside substantial increases in forest density, and lead to a large increase in overall forest area. These changes will have a significant impact on carbon stocking in the high altitude zone, while the concomitant decrease in alpine grassland area is likely to have negative implications for alpine species. The complex and spatially variable changes that we report highlight the necessity for considering local factors such as topography when attempting to predict species distributional responses to warming climate. PMID:25141823

  15. Strong topographic sheltering effects lead to spatially complex treeline advance and increased forest density in a subtropical mountain region.

    PubMed

    Greenwood, Sarah; Chen, Jan-Chang; Chen, Chaur-Tzuhn; Jump, Alistair S

    2014-12-01

    Altitudinal treelines are typically temperature limited such that increasing temperatures linked to global climate change are causing upslope shifts of treelines worldwide. While such elevational increases are readily predicted based on shifting isotherms, at the regional level the realized response is often much more complex, with topography and local environmental conditions playing an important modifying role. Here, we used repeated aerial photographs in combination with forest inventory data to investigate changes in treeline position in the Central Mountain Range of Taiwan over the last 60 years. A highly spatially variable upslope advance of treeline was identified in which topography is a major driver of both treeline form and advance. The changes in treeline position that we observed occurred alongside substantial increases in forest density, and lead to a large increase in overall forest area. These changes will have a significant impact on carbon stocking in the high altitude zone, while the concomitant decrease in alpine grassland area is likely to have negative implications for alpine species. The complex and spatially variable changes that we report highlight the necessity for considering local factors such as topography when attempting to predict species distributional responses to warming climate.

  16. 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

  17. A Model to Predict Nitrogen Losses in Advanced Soil-Based Wastewater Treatment Systems

    NASA Astrophysics Data System (ADS)

    Morales, I.; Cooper, J.; Loomis, G.; Kalen, D.; Amador, J.; Boving, T. B.

    2014-12-01

    Most of the non-point source Nitrogen (N) load in rural areas is attributed to onsite wastewater treatment systems (OWTS). Nitrogen compounds are considered environmental pollutants because they deplete the oxygen availability in water bodies and produce eutrophication. The objective of this study was to simulate the fate and transport of Nitrogen in OWTS. The commercially-available 2D/3D HYDRUS software was used to develop a transport and fate model. Experimental data from a laboratory meso-cosm study included the soil moisture content, NH4 and NO3- data. That data set was used to calibrate the model. Three types of OWTS were simulated: (1) pipe-and-stone (P&S), (2) advanced soil drainfields, pressurized shallow narrow drainfield (SND) and (3) Geomat (GEO), a variation of SND. To better understand the nitrogen removal mechanism and the performance of OWTS technologies, replicate (n = 3) intact soil mesocosms were used with 15N-labelled nitrogen inputs. As a result, it was estimated that N removal by denitrification was predominant in P&S. However, it is suggested that N was removed by nitrification in SND and GEO. The calibrated model was used to estimate Nitrogen fluxes for both conventional and advanced OWTS. Also, the model predicted the N losses from nitrification and denitrification in all OWTS. These findings help to provide practitioners with guidelines to estimate N removal efficiencies for OWTS, and predict N loads and spatial distribution for identifying non-point sources.

  18. Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer

    PubMed Central

    Du, Meijun; Dittmar, Rachel L.; Lee, Adam; Nandy, Debashis; Yuan, Tiezheng; Guo, Yongchen; Wang, Yuan; Tschannen, Michael R.; Worthey, Elizabeth; Jacob, Howard; See, William; Kilari, Deepak; Wang, Xuexia; Hovey, Raymond L.; Huang, Chiang-Ching; Wang, Liang

    2015-01-01

    Liquid biopsies, examinations of tumor components in body fluids, have shown promise for predicting clinical outcomes. To evaluate tumor-associated genomic and genetic variations in plasma cell-free DNA (cfDNA) and their associations with treatment response and overall survival, we applied whole genome and targeted sequencing to examine the plasma cfDNAs derived from 20 patients with advanced prostate cancer. Sequencing-based genomic abnormality analysis revealed locus-specific gains or losses that were common in prostate cancer, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. To estimate tumor burden in cfDNA, we developed a Plasma Genomic Abnormality (PGA) score by summing the most significant copy number variations. Cox regression analysis showed that PGA scores were significantly associated with overall survival (p < 0.04). After androgen deprivation therapy or chemotherapy, targeted sequencing showed significant mutational profile changes in genes involved in androgen biosynthesis, AR activation, DNA repair, and chemotherapy resistance. These changes may reflect the dynamic evolution of heterozygous tumor populations in response to these treatments. These results strongly support the feasibility of using non-invasive liquid biopsies as potential tools to study biological mechanisms underlying therapy-specific resistance and to predict disease progression in advanced prostate cancer. PMID:25915538

  19. Can primary optimal cytoreduction be predicted in advanced epithelial ovarian cancer preoperatively?

    PubMed Central

    2010-01-01

    Introduction Prediction of optimal cytoreduction in patients with advanced epithelial ovarian caner preoperatively. Methods Patients with advanced epithelial ovarian cancer who underwent surgery for the first time from Jan. to June 2008 at gynecologic oncology ward of TUMS (Tehran University of Medical Sciences) were eligible for this study. The possibility of predicting primary optimal cytoreduction considering multiple variables was evaluated. Variables were peritoneal carcinomatosis, serum CA125, ascites, pleural effusion, physical status and imaging findings. Univariate comparisons of patients underwent suboptimal cytoreduction carried out using Fisher's exact test for each of the potential predictors. The wilcoxon rank sum test was used to compare variables between patients with optimal versus suboptimal cytoreduction. Results 41 patients met study inclusion criteria. Statistically significant association was noted between peritoneal carcinomatosis and suboptimal cytoreduction. There were no statistically significant differences between physical status, pleural effusion, imaging findings, serum CA125 and ascites of individuals with optimal cytoreduction compared to those with suboptimal cytoreduction. Conclusions Because of small populations in our study the results are not reproducible in alternate populations. Only the patient who is most unlikely to undergo optimal cytoreduction should be offered neoadjuvant chemotherapy, unless her medical condition renders her unsuitable for primary surgery. PMID:20170515

  20. Isolated limb perfusion with hyperthermia and chemotherapy: predictive factors for regional toxicity

    PubMed Central

    Neto, João Pedreira Duprat; Oliveira, Fernanda; Bertolli, Eduardo; Molina, Andre Sapata; Nishinari, Kenji; Facure, Luciana; Fregnani, Jose Humberto

    2012-01-01

    OBJECTIVE: Isolated limb perfusion combined with melphalan is an accepted treatment for obtaining locoregional control in advanced melanoma of the extremities and other malignant neoplasias restricted to the limb. This study aims to examine the factors associated with toxicity caused by the regional method. We considered the technical aspects of severe complications associated with the procedure in an attempt to diminish the patient morbidity that occurs during the learning curve. METHODS: We conducted a retrospective analysis of the records of patients who underwent perfusion at the AC Camargo Hospital in São Paulo, Brazil between January 2000 and January 2009. The Wieberdink scale was applied to classify local toxicity and its relation to clinical and laboratory variables. RESULTS: Fifty-eight perfusions were performed in 55 patients. Most patients (86.2%) presented a toxicity level between I and III. Grade V toxicity was seen in five cases (8.6%), four of which occurred in the first 2 years. Creatine phosphokinase, an important predictive factor for toxicity, had an average value of 231.8 for toxicity grades I-III and 1286.2 for toxicity grades IV-V (p = 0.001). There was a relationship between the melphalan dose and toxicity, which was 77 mg (25 to 130 mg) for toxicity grades I-II and 93.5 mg (45 to 120 mg) for toxicity grades IV-V (p = 0.0204). CONCLUSION: It is possible to prevent the toxicity associated with melphalan by adjusting the dose according to the patient's body weight (especially for women and obese patients) and the creatine phosphokinase values in the postoperative period. PMID:22473404

  1. Advanced validation of CFD-FDTD combined method using highly applicable solver for reentry blackout prediction

    NASA Astrophysics Data System (ADS)

    Takahashi, Yusuke

    2016-01-01

    An analysis model of plasma flow and electromagnetic waves around a reentry vehicle for radio frequency blackout prediction during aerodynamic heating was developed in this study. The model was validated based on experimental results from the radio attenuation measurement program. The plasma flow properties, such as electron number density, in the shock layer and wake region were obtained using a newly developed unstructured grid solver that incorporated real gas effect models and could treat thermochemically non-equilibrium flow. To predict the electromagnetic waves in plasma, a frequency-dependent finite-difference time-domain method was used. Moreover, the complicated behaviour of electromagnetic waves in the plasma layer during atmospheric reentry was clarified at several altitudes. The prediction performance of the combined model was evaluated with profiles and peak values of the electron number density in the plasma layer. In addition, to validate the models, the signal losses measured during communication with the reentry vehicle were directly compared with the predicted results. Based on the study, it was suggested that the present analysis model accurately predicts the radio frequency blackout and plasma attenuation of electromagnetic waves in plasma in communication.

  2. Advancing decadal-scale climate prediction in the North Atlantic sector.

    PubMed

    Keenlyside, N S; Latif, M; Jungclaus, J; Kornblueh, L; Roeckner, E

    2008-05-01

    The climate of the North Atlantic region exhibits fluctuations on decadal timescales that have large societal consequences. Prominent examples include hurricane activity in the Atlantic, and surface-temperature and rainfall variations over North America, Europe and northern Africa. Although these multidecadal variations are potentially predictable if the current state of the ocean is known, the lack of subsurface ocean observations that constrain this state has been a limiting factor for realizing the full skill potential of such predictions. Here we apply a simple approach-that uses only sea surface temperature (SST) observations-to partly overcome this difficulty and perform retrospective decadal predictions with a climate model. Skill is improved significantly relative to predictions made with incomplete knowledge of the ocean state, particularly in the North Atlantic and tropical Pacific oceans. Thus these results point towards the possibility of routine decadal climate predictions. Using this method, and by considering both internal natural climate variations and projected future anthropogenic forcing, we make the following forecast: over the next decade, the current Atlantic meridional overturning circulation will weaken to its long-term mean; moreover, North Atlantic SST and European and North American surface temperatures will cool slightly, whereas tropical Pacific SST will remain almost unchanged. Our results suggest that global surface temperature may not increase over the next decade, as natural climate variations in the North Atlantic and tropical Pacific temporarily offset the projected anthropogenic warming.

  3. DeepCNF-D: Predicting Protein Order/Disorder Regions by Weighted Deep Convolutional Neural Fields.

    PubMed

    Wang, Sheng; Weng, Shunyan; Ma, Jianzhu; Tang, Qingming

    2015-01-01

    Intrinsically disordered proteins or protein regions are involved in key biological processes including regulation of transcription, signal transduction, and alternative splicing. Accurately predicting order/disorder regions ab initio from the protein sequence is a prerequisite step for further analysis of functions and mechanisms for these disordered regions. This work presents a learning method, weighted DeepCNF (Deep Convolutional Neural Fields), to improve the accuracy of order/disorder prediction by exploiting the long-range sequential information and the interdependency between adjacent order/disorder labels and by assigning different weights for each label during training and prediction to solve the label imbalance issue. Evaluated by the CASP9 and CASP10 targets, our method obtains 0.855 and 0.898 AUC values, which are higher than the state-of-the-art single ab initio predictors.

  4. Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data

    PubMed Central

    Ribay, Kathryn; Kim, Marlene T.; Wang, Wenyi; Pinolini, Daniel; Zhu, Hao

    2016-01-01

    Estrogen receptors (ERα) are a critical target for drug design as well as a potential source of toxicity when activated unintentionally. Thus, evaluating potential ERα binding agents is critical in both drug discovery and chemical toxicity areas. Using computational tools, e.g., Quantitative Structure-Activity Relationship (QSAR) models, can predict potential ERα binding agents before chemical synthesis. The purpose of this project was to develop enhanced predictive models of ERα binding agents by utilizing advanced cheminformatics tools that can integrate publicly available bioassay data. The initial ERα binding agent data set, consisting of 446 binders and 8307 non-binders, was obtained from the Tox21 Challenge project organized by the NIH Chemical Genomics Center (NCGC). After removing the duplicates and inorganic compounds, this data set was used to create a training set (259 binders and 259 non-binders). This training set was used to develop QSAR models using chemical descriptors. The resulting models were then used to predict the binding activity of 264 external compounds, which were available to us after the models were developed. The cross-validation results of training set [Correct Classification Rate (CCR) = 0.72] were much higher than the external predictivity of the unknown compounds (CCR = 0.59). To improve the conventional QSAR models, all compounds in the training set were used to search PubChem and generate a profile of their biological responses across thousands of bioassays. The most important bioassays were prioritized to generate a similarity index that was used to calculate the biosimilarity score between each two compounds. The nearest neighbors for each compound within the set were then identified and its ERα binding potential was predicted by its nearest neighbors in the training set. The hybrid model performance (CCR = 0.94 for cross validation; CCR = 0.68 for external prediction) showed significant improvement over the original QSAR

  5. Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data

    PubMed Central

    Ribay, Kathryn; Kim, Marlene T.; Wang, Wenyi; Pinolini, Daniel; Zhu, Hao

    2016-01-01

    Estrogen receptors (ERα) are a critical target for drug design as well as a potential source of toxicity when activated unintentionally. Thus, evaluating potential ERα binding agents is critical in both drug discovery and chemical toxicity areas. Using computational tools, e.g., Quantitative Structure-Activity Relationship (QSAR) models, can predict potential ERα binding agents before chemical synthesis. The purpose of this project was to develop enhanced predictive models of ERα binding agents by utilizing advanced cheminformatics tools that can integrate publicly available bioassay data. The initial ERα binding agent data set, consisting of 446 binders and 8307 non-binders, was obtained from the Tox21 Challenge project organized by the NIH Chemical Genomics Center (NCGC). After removing the duplicates and inorganic compounds, this data set was used to create a training set (259 binders and 259 non-binders). This training set was used to develop QSAR models using chemical descriptors. The resulting models were then used to predict the binding activity of 264 external compounds, which were available to us after the models were developed. The cross-validation results of training set [Correct Classification Rate (CCR) = 0.72] were much higher than the external predictivity of the unknown compounds (CCR = 0.59). To improve the conventional QSAR models, all compounds in the training set were used to search PubChem and generate a profile of their biological responses across thousands of bioassays. The most important bioassays were prioritized to generate a similarity index that was used to calculate the biosimilarity score between each two compounds. The nearest neighbors for each compound within the set were then identified and its ERα binding potential was predicted by its nearest neighbors in the training set. The hybrid model performance (CCR = 0.94 for cross validation; CCR = 0.68 for external prediction) showed significant improvement over the original QSAR

  6. A research program for improving heat transfer prediction for the laminar to turbulent transition region of turbine vanes/blades

    NASA Technical Reports Server (NTRS)

    Simon, Frederick F.

    1993-01-01

    A program sponsored by NASA for the investigation of the heat transfer in the transition region of turbine vanes and blades with the objective of improving the capability for predicting heat transfer is described. The accurate prediction of gas-side heat transfer is important to the determination of turbine longevity, engine performance, and developmental costs. The need for accurate predictions will become greater as the operating temperatures and stage loading levels of advanced turbine engines increase. The present methods for predicting transition shear stress and heat transfer on turbine blades are based on incomplete knowledge and are largely empirical. To meet the objective of the NASA program, a team approach consisting of researchers from government, universities, a research institute, and a small business is presented. The research is divided into the areas of experiments, direct numerical simulations (DNS), and turbulence modeling. A summary of the results to date is given for the above research areas in a high-disturbance environment (bypass transition) with a discussion of the model development necessary for use in numerical codes.

  7. A research program for improving heat transfer prediction for the laminar to turbulent transition region of turbine vanes/blades

    NASA Astrophysics Data System (ADS)

    Simon, Frederick F.

    1993-08-01

    A program sponsored by NASA for the investigation of the heat transfer in the transition region of turbine vanes and blades with the objective of improving the capability for predicting heat transfer is described. The accurate prediction of gas-side heat transfer is important to the determination of turbine longevity, engine performance, and developmental costs. The need for accurate predictions will become greater as the operating temperatures and stage loading levels of advanced turbine engines increase. The present methods for predicting transition shear stress and heat transfer on turbine blades are based on incomplete knowledge and are largely empirical. To meet the objective of the NASA program, a team approach consisting of researchers from government, universities, a research institute, and a small business is presented. The research is divided into the areas of experiments, direct numerical simulations (DNS), and turbulence modeling. A summary of the results to date is given for the above research areas in a high-disturbance environment (bypass transition) with a discussion of the model development necessary for use in numerical codes.

  8. Predicting groundwater redox status on a regional scale using linear discriminant analysis

    NASA Astrophysics Data System (ADS)

    Close, M. E.; Abraham, P.; Humphries, B.; Lilburne, L.; Cuthill, T.; Wilson, S.

    2016-08-01

    Reducing conditions are necessary for denitrification, thus the groundwater redox status can be used to identify subsurface zones where potentially significant nitrate reduction can occur. Groundwater chemistry in two contrasting regions of New Zealand was classified with respect to redox status and related to mappable factors, such as geology, topography and soil characteristics using discriminant analysis. Redox assignment was carried out for water sampled from 568 and 2223 wells in the Waikato and Canterbury regions, respectively. For the Waikato region 64% of wells sampled indicated oxic conditions in the water; 18% indicated reduced conditions and 18% had attributes indicating both reducing and oxic conditions termed "mixed". In Canterbury 84% of wells indicated oxic conditions; 10% were mixed; and only 5% indicated reduced conditions. The analysis was performed over three different well depths, < 25 m, 25 to 100 and > 100 m. For both regions, the percentage of oxidised groundwater decreased with increasing well depth. Linear discriminant analysis was used to develop models to differentiate between the three redox states. Models were derived for each depth and region using 67% of the data, and then subsequently validated on the remaining 33%. The average agreement between predicted and measured redox status was 63% and 70% for the Waikato and Canterbury regions, respectively. The models were incorporated into GIS and the prediction of redox status was extended over the whole region, excluding mountainous land. This knowledge improves spatial prediction of reduced groundwater zones, and therefore, when combined with groundwater flow paths, improves estimates of denitrification.

  9. Predicting groundwater redox status on a regional scale using linear discriminant analysis.

    PubMed

    Close, M E; Abraham, P; Humphries, B; Lilburne, L; Cuthill, T; Wilson, S

    2016-08-01

    Reducing conditions are necessary for denitrification, thus the groundwater redox status can be used to identify subsurface zones where potentially significant nitrate reduction can occur. Groundwater chemistry in two contrasting regions of New Zealand was classified with respect to redox status and related to mappable factors, such as geology, topography and soil characteristics using discriminant analysis. Redox assignment was carried out for water sampled from 568 and 2223 wells in the Waikato and Canterbury regions, respectively. For the Waikato region 64% of wells sampled indicated oxic conditions in the water; 18% indicated reduced conditions and 18% had attributes indicating both reducing and oxic conditions termed "mixed". In Canterbury 84% of wells indicated oxic conditions; 10% were mixed; and only 5% indicated reduced conditions. The analysis was performed over three different well depths, <25m, 25 to 100 and >100m. For both regions, the percentage of oxidised groundwater decreased with increasing well depth. Linear discriminant analysis was used to develop models to differentiate between the three redox states. Models were derived for each depth and region using 67% of the data, and then subsequently validated on the remaining 33%. The average agreement between predicted and measured redox status was 63% and 70% for the Waikato and Canterbury regions, respectively. The models were incorporated into GIS and the prediction of redox status was extended over the whole region, excluding mountainous land. This knowledge improves spatial prediction of reduced groundwater zones, and therefore, when combined with groundwater flow paths, improves estimates of denitrification. PMID:27182792

  10. Predicting groundwater redox status on a regional scale using linear discriminant analysis.

    PubMed

    Close, M E; Abraham, P; Humphries, B; Lilburne, L; Cuthill, T; Wilson, S

    2016-08-01

    Reducing conditions are necessary for denitrification, thus the groundwater redox status can be used to identify subsurface zones where potentially significant nitrate reduction can occur. Groundwater chemistry in two contrasting regions of New Zealand was classified with respect to redox status and related to mappable factors, such as geology, topography and soil characteristics using discriminant analysis. Redox assignment was carried out for water sampled from 568 and 2223 wells in the Waikato and Canterbury regions, respectively. For the Waikato region 64% of wells sampled indicated oxic conditions in the water; 18% indicated reduced conditions and 18% had attributes indicating both reducing and oxic conditions termed "mixed". In Canterbury 84% of wells indicated oxic conditions; 10% were mixed; and only 5% indicated reduced conditions. The analysis was performed over three different well depths, <25m, 25 to 100 and >100m. For both regions, the percentage of oxidised groundwater decreased with increasing well depth. Linear discriminant analysis was used to develop models to differentiate between the three redox states. Models were derived for each depth and region using 67% of the data, and then subsequently validated on the remaining 33%. The average agreement between predicted and measured redox status was 63% and 70% for the Waikato and Canterbury regions, respectively. The models were incorporated into GIS and the prediction of redox status was extended over the whole region, excluding mountainous land. This knowledge improves spatial prediction of reduced groundwater zones, and therefore, when combined with groundwater flow paths, improves estimates of denitrification.

  11. Bias reduction in decadal predictions of West African monsoon rainfall using regional climate models

    NASA Astrophysics Data System (ADS)

    Paxian, A.; Sein, D.; Panitz, H.-J.; Warscher, M.; Breil, M.; Engel, T.; Tödter, J.; Krause, A.; Cabos Narvaez, W. D.; Fink, A. H.; Ahrens, B.; Kunstmann, H.; Jacob, D.; Paeth, H.

    2016-02-01

    The West African monsoon rainfall is essential for regional food production, and decadal predictions are necessary for policy makers and farmers. However, predictions with global climate models reveal precipitation biases. This study addresses the hypotheses that global prediction biases can be reduced by dynamical downscaling with a multimodel ensemble of three regional climate models (RCMs), a RCM coupled to a global ocean model and a RCM applying more realistic soil initialization and boundary conditions, i.e., aerosols, sea surface temperatures (SSTs), vegetation, and land cover. Numerous RCM predictions have been performed with REMO, COSMO-CLM (CCLM), and Weather Research and Forecasting (WRF) in various versions and for different decades. Global predictions reveal typical positive and negative biases over the Guinea Coast and the Sahel, respectively, related to a southward shifted Intertropical Convergence Zone (ITCZ) and a positive tropical Atlantic SST bias. These rainfall biases are reduced by some regional predictions in the Sahel but aggravated by all RCMs over the Guinea Coast, resulting from the inherited SST bias, increased westerlies and evaporation over the tropical Atlantic and shifted African easterly waves. The coupled regional predictions simulate high-resolution atmosphere-ocean interactions strongly improving the SST bias, the ITCZ shift and the Guinea Coast and Central Sahel precipitation biases. Some added values in rainfall bias are found for more realistic SST and land cover boundary conditions over the Guinea Coast and improved vegetation in the Central Sahel. Thus, the ability of RCMs and improved boundary conditions to reduce rainfall biases for climate impact research depends on the considered West African region.

  12. Early Identification of Students Predicted to Enroll in Advanced, Upper-Level High School Courses: An Examination of Validity

    ERIC Educational Resources Information Center

    DeRose, Diego S.; Clement, Russell W.

    2011-01-01

    Broward County Public Schools' Research Services department uses logistic regression analysis to compute an indicator to predict student enrollment in advanced high school courses, for students entering ninth grade for the first time. This prediction indicator, along with other student characteristics, supports high school guidance staffs in…

  13. Assessing Decadal Predictability of the Regional MiKlip Forecast Ensemble for Europe (1961-2010)

    NASA Astrophysics Data System (ADS)

    Mieruch-Schnuelle, S.; Schädler, G.; Feldmann, H.; Lenz, C.; Kothe, S.; Kottmeier, C.

    2013-12-01

    The aim of the large German Ministry for Education and Research (BMBF) project MiKlip (Mittelfristige Klimaprognose, Decadal Climate Prediction) is to develop a decadal forecast system. To explore the feasability and prospects of global and regional predictions on decadal time scales, global as well as regional predictive ensemble hindcasts have been generated. The focus of this contribution lies on the description of the 10 member regional hindcast ensemble for Europe (1961-2010) at 25 km resolution. The regional model COSMO-CLM has been driven by CMIP5 MPI-ESM simulations, which have been generated by 1-day time-lagged initialization of the atmosphere and an anomaly initialization for the ocean. The study aims at the assessment of the decadal variability and predictability against observations. After removing the long term bias as well as the long term linear trend from the data, we applied low pass filters to the original data to separate the decadal climate signal from high frequency noise. The decadal variability and predictability assessment is applied to temperature and precipitation data for the summer and winter half-year averages/sums. The best results have been found for the prediction of decadal temperature anomalies, i.e.~we have detected a distinct predictive skill and reasonable reliability. Hence it is possible to predict temperature variability on decadal timescales, However, the situation is less satisfactory for precipitation. Here we have found regions showing good predictability, but also regions without any predictive skill. Summer half-year temperature anomalies of E-OBS observations (lilac) and CCLM (orange) at a single grid point near Lodz (Poland). The original data are shown as thin lines, whereas the 9 year moving average filters are plotted as thick lines. The gray shaded area depicts the CCLM ensemble spread, i.e. the standard deviation over the ensemble. Additionally, because of the decadal initialization, the decades have been

  14. Advances in Rosetta structure prediction for difficult molecular-replacement problems

    SciTech Connect

    DiMaio, Frank

    2013-11-01

    Modeling advances using Rosetta structure prediction to aid in solving difficult molecular-replacement problems are discussed. Recent work has shown the effectiveness of structure-prediction methods in solving difficult molecular-replacement problems. The Rosetta protein structure modeling suite can aid in the solution of difficult molecular-replacement problems using templates from 15 to 25% sequence identity; Rosetta refinement guided by noisy density has consistently led to solved structures where other methods fail. In this paper, an overview of the use of Rosetta for these difficult molecular-replacement problems is provided and new modeling developments that further improve model quality are described. Several variations to the method are introduced that significantly reduce the time needed to generate a model and the sampling required to improve the starting template. The improvements are benchmarked on a set of nine difficult cases and it is shown that this improved method obtains consistently better models in less running time. Finally, strategies for best using Rosetta to solve difficult molecular-replacement problems are presented and future directions for the role of structure-prediction methods in crystallography are discussed.

  15. The prediction of the building precision in the Laser Engineered Net Shaping process using advanced networks

    NASA Astrophysics Data System (ADS)

    Lu, Z. L.; Li, D. C.; Lu, B. H.; Zhang, A. F.; Zhu, G. X.; Pi, G.

    2010-05-01

    Laser Engineered Net Shaping (LENS) is an advanced manufacturing technology, but it is difficult to control the depositing height (DH) of the prototype because there are many technology parameters influencing the forming process. The effect of main parameters (laser power, scanning speed and powder feeding rate) on the DH of single track is firstly analyzed, and then it shows that there is the complex nonlinear intrinsic relationship between them. In order to predict the DH, the back propagation (BP) based network improved with Adaptive learning rate and Momentum coefficient (AM) algorithm, and the least square support vector machine (LS-SVM) network are both adopted. The mapping relationship between above parameters and the DH is constructed according to training samples collected by LENS experiments, and then their generalization ability, function-approximating ability and real-time are contrastively investigated. The results show that although the predicted result by the BP-AM approximates the experimental result, above performance index of the LS-SVM are better than those of the BP-AM. Finally, high-definition thin-walled parts of AISI316L are successfully fabricated. Hence, the LS-SVM network is more suitable for the prediction of the DH.

  16. Skill and predictability in multimodel ensemble forecasts for Northern Hemisphere regions with dominant winter precipitation

    NASA Astrophysics Data System (ADS)

    Ehsan, Muhammad Azhar; Tippett, Michael K.; Almazroui, Mansour; Ismail, Muhammad; Yousef, Ahmed; Kucharski, Fred; Omar, Mohamed; Hussein, Mahmoud; Alkhalaf, Abdulrahman A.

    2016-07-01

    Northern Hemisphere winter precipitation reforecasts from the European Centre for Medium Range Weather Forecast System-4 and six of the models in the North American Multi-Model Ensemble are evaluated, focusing on two regions (Region-A: 20°N-45°N, 10°E-65°E and Region-B: 20°N-55°N, 205°E-255°E) where winter precipitation is a dominant fraction of the annual total and where precipitation from mid-latitude storms is important. Predictability and skill (deterministic and probabilistic) are assessed for 1983-2013 by the multimodel composite (MME) of seven prediction models. The MME climatological mean and variability over the two regions is comparable to observation with some regional differences. The statistically significant decreasing trend observed in Region-B precipitation is captured well by the MME and most of the individual models. El Niño Southern Oscillation is a source of forecast skill, and the correlation coefficient between the Niño3.4 index and precipitation over region A and B is 0.46 and 0.35, statistically significant at the 95 % level. The MME reforecasts weakly reproduce the observed teleconnection. Signal, noise and signal to noise ratio analysis show that the signal variance over two regions is very small as compared to noise variance which tends to reduce the prediction skill. The MME ranked probability skill score is higher than that of individual models, showing the advantage of a multimodel ensemble. Observed Region-A rainfall anomalies are strongly associated with the North Atlantic Oscillation, but none of the models reproduce this relation, which may explain the low skill over Region-A. The superior quality of multimodel ensemble compared with individual models is mainly due to larger ensemble size.

  17. Science and Technology to Advance Regional Security in the Middle East and Central Asia

    SciTech Connect

    Tompson, A F B; Richardson, J H; Ragaini, R C; Knapp, R B; Rosenberg, N D; Smith, D K; Ball, D Y

    2002-10-09

    This paper is concerned with the promotion and advancement of regional security in the Middle East and Central Asia through the development of bilateral and multilateral cooperation on targeted scientific and technical projects. It is widely recognized that increasing tensions and instability in many parts of the world emphasize--or reemphasize--a need to seek and promote regional security in these areas. At the Lawrence Livermore National Laboratory (LLNL), a national security research facility operated for the US Department of Energy, we are pursuing an effort to use science and technology as a ''low risk'' means of engagement in regions of strategic importance to the United States. In particular, we are developing collaborations and cooperative projects among (and between) national laboratory scientists in the US and our various counterparts in the countries of interest.

  18. DFLpred: High-throughput prediction of disordered flexible linker regions in protein sequences

    PubMed Central

    Meng, Fanchi; Kurgan, Lukasz

    2016-01-01

    Motivation: Disordered flexible linkers (DFLs) are disordered regions that serve as flexible linkers/spacers in multi-domain proteins or between structured constituents in domains. They are different from flexible linkers/residues because they are disordered and longer. Availability of experimentally annotated DFLs provides an opportunity to build high-throughput computational predictors of these regions from protein sequences. To date, there are no computational methods that directly predict DFLs and they can be found only indirectly by filtering predicted flexible residues with predictions of disorder. Results: We conceptualized, developed and empirically assessed a first-of-its-kind sequence-based predictor of DFLs, DFLpred. This method outputs propensity to form DFLs for each residue in the input sequence. DFLpred uses a small set of empirically selected features that quantify propensities to form certain secondary structures, disordered regions and structured regions, which are processed by a fast linear model. Our high-throughput predictor can be used on the whole-proteome scale; it needs <1 h to predict entire proteome on a single CPU. When assessed on an independent test dataset with low sequence-identity proteins, it secures area under the receiver operating characteristic curve equal 0.715 and outperforms existing alternatives that include methods for the prediction of flexible linkers, flexible residues, intrinsically disordered residues and various combinations of these methods. Prediction on the complete human proteome reveals that about 10% of proteins have a large content of over 30% DFL residues. We also estimate that about 6000 DFL regions are long with ≥30 consecutive residues. Availability and implementation: http://biomine.ece.ualberta.ca/DFLpred/. Contact: lkurgan@vcu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307636

  19. RCWIM - an improved global water isotope pattern prediction model using fuzzy climatic clustering regionalization

    NASA Astrophysics Data System (ADS)

    Terzer, Stefan; Araguás-Araguás, Luis; Wassenaar, Leonard I.; Aggarwal, Pradeep K.

    2013-04-01

    Prediction of geospatial H and O isotopic patterns in precipitation has become increasingly important to diverse disciplines beyond hydrology, such as climatology, ecology, food authenticity, and criminal forensics, because these two isotopes of rainwater often control the terrestrial isotopic spatial patterns that facilitate the linkage of products (food, wildlife, water) to origin or movement (food, criminalistics). Currently, spatial water isotopic pattern prediction relies on combined regression and interpolation techniques to create gridded datasets by using data obtained from the Global Network of Isotopes In Precipitation (GNIP). However, current models suffer from two shortcomings: (a) models may have limited covariates and/or parameterization fitted to a global domain, which results in poor predictive outcomes at regional scales, or (b) the spatial domain is intentionally restricted to regional settings, and thereby of little use in providing information at global geospatial scales. Here we present a new global climatically regionalized isotope prediction model which overcomes these limitations through the use of fuzzy clustering of climatic data subsets, allowing us to better identify and customize appropriate covariates and their multiple regression coefficients instead of aiming for a one-size-fits-all global fit (RCWIM - Regionalized Climate Cluster Water Isotope Model). The new model significantly reduces the point-based regression residuals and results in much lower overall isotopic prediction uncertainty, since residuals are interpolated onto the regression surface. The new precipitation δ2H and δ18O isoscape model is available on a global scale at 10 arc-minutes spatial and at monthly, seasonal and annual temporal resolution, and will provide improved predicted stable isotope values used for a growing number of applications. The model further provides a flexible framework for future improvements using regional climatic clustering.

  20. Edge Fracture Prediction ofTraditional and Advanced Trimming Processes for AA6111-T4 Sheets

    SciTech Connect

    Hu, Xiaohua; Choi, Kyoo Sil; Sun, Xin; Golovashchenko, Segey F.

    2014-02-15

    This work examines the traditional and advanced trimming of AA6111-T4 aluminum sheets with finite element simulations. The Rice-Tracy damage model is used for the simulation with damage parameters estimated from experimental observation of grain aspect ratio near the fracture surface of trimmed parts. Fine meshes at the shearing zone, adaptive meshing, and adaptive contact techniques are used to accurately capture the contact interactions between the sharp corner of the trimming tools and the blank to be trimmed. To the knowledge of the authors, these are the first trimming simulations that can predict the effects of shearing clearance on burr heights with quantitative accuracy for AA6111-T4 aluminum sheets. In addition, the models have also accurately reproduced the crack initiation site as well as burr and sliver formation mechanisms observed experimentally.

  1. Prediction of response to preoperative chemoradiotherapy and establishment of individualized therapy in advanced rectal cancer.

    PubMed

    Nakao, Toshihiro; Iwata, Takashi; Hotchi, Masanori; Yoshikawa, Kozo; Higashijima, Jun; Nishi, Masaaki; Takasu, Chie; Eto, Shohei; Teraoku, Hiroki; Shimada, Mitsuo

    2015-10-01

    Preoperative chemoradiotherapy (CRT) has become the standard treatment for patients with locally advanced rectal cancer. However, no specific biomarker has been identified to predict a response to preoperative CRT. The aim of the present study was to assess the gene expression patterns of patients with advanced rectal cancer to predict their responses to preoperative CRT. Fifty-nine rectal cancer patients were subjected to preoperative CRT. Patients were randomly assigned to receive CRT with tegafur/gimeracil/oteracil (S-1 group, n=30) or tegafur-uracil (UFT group, n=29). Gene expression changes were studied with cDNA and miRNA microarray. The association between gene expression and response to CRT was evaluated. cDNA microarray showed that 184 genes were significantly differentially expressed between the responders and the non‑responders in the S-1 group. Comparatively, 193 genes were significantly differentially expressed in the responders in the UFT group. TBX18 upregulation was common to both groups whereas BTNL8, LOC375010, ADH1B, HRASLS2, LOC284232, GCNT3 and ALDH1A2 were significantly differentially lower in both groups when compared with the non-responders. Using miRNA microarray, we found that 7 and 16 genes were significantly differentially expressed between the responders and non-responders in the S-1 and UFT groups, respectively. miR-223 was significantly higher in the responders in the S-1 group and tended to be higher in the responders in the UFT group. The present study identified several genes likely to be useful for establishing individualized therapies for patients with rectal cancer.

  2. Surprise Questions for Survival Prediction in Patients With Advanced Cancer: A Multicenter Prospective Cohort Study

    PubMed Central

    Hamano, Jun; Morita, Tatsuya; Inoue, Satoshi; Ikenaga, Masayuki; Matsumoto, Yoshihisa; Sekine, Ryuichi; Yamaguchi, Takashi; Hirohashi, Takeshi; Tajima, Tsukasa; Tatara, Ryohei; Watanabe, Hiroaki; Otani, Hiroyuki; Takigawa, Chizuko; Matsuda, Yoshinobu; Nagaoka, Hiroka; Mori, Masanori; Yamamoto, Naoki; Shimizu, Mie; Sasara, Takeshi

    2015-01-01

    Background. Predicting the short-term survival in cancer patients is an important issue for patients, family, and oncologists. Although the prognostic accuracy of the surprise question has value in 1-year mortality for cancer patients, the prognostic value for short-term survival has not been formally assessed. The primary aim of the present study was to assess the prognostic value of the surprise question for 7-day and 30-day survival in patients with advanced cancer. Patients and Methods. The present multicenter prospective cohort study was conducted in Japan from September 2012 through April 2014, involving 16 palliative care units, 19 hospital-based palliative care teams, and 23 home-based palliative care services. Results. We recruited 2,425 patients and included 2,361 for analysis: 912 from hospital-based palliative care teams, 895 from hospital palliative care units, and 554 from home-based palliative care services. The sensitivity, specificity, positive predictive value, and negative predictive value of the 7-day survival surprise question were 84.7% (95% confidence interval [CI], 80.7%–88.0%), 68.0% (95% CI, 67.3%–68.5%), 30.3% (95% CI, 28.9%–31.5%), and 96.4% (95% CI, 95.5%–97.2%), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value for the 30-day surprise question were 95.6% (95% CI, 94.4%–96.6%), 37.0% (95% CI, 35.9%–37.9%), 57.6% (95% CI, 56.8%–58.2%), and 90.4% (95% CI, 87.7%–92.6%), respectively. Conclusion. Surprise questions are useful for screening patients for short survival. However, the high false-positive rates do not allow clinicians to provide definitive prognosis prediction. Implications for Practice: The findings of this study indicate that clinicians can screen patients for 7- or 30-day survival using surprise questions with 90% or more sensitivity. Clinicians cannot provide accurate prognosis estimation, and all patients will not always die within the defined periods. The

  3. Numerical prediction of three-dimensional juncture region flow using the parabolic Navier-Stokes equations

    NASA Technical Reports Server (NTRS)

    Baker, A. J.; Manhardt, P. D.; Orzechowski, J. A.

    1979-01-01

    A numerical solution algorithm is established for prediction of subsonic turbulent three-dimensional flows in aerodynamic configuration juncture regions. A turbulence closure model is established using the complete Reynolds stress. Pressure coupling is accomplished using the concepts of complementary and particular solutions to a Poisson equation. Specifications for data input juncture geometry modification are presented.

  4. Ductile damage prediction in metal forming processes: Advanced modeling and numerical simulation

    NASA Astrophysics Data System (ADS)

    Saanouni, K.

    2013-05-01

    This paper describes the needs required in modern virtual metal forming including both sheet and bulk metal forming of mechanical components. These concern the advanced modeling of thermo-mechanical behavior including the multiphysical phenomena and their interaction or strong coupling, as well as the associated numerical aspects using fully adaptive simulation strategies. First a survey of advanced constitutive equations accounting for the main thermomechanical phenomena as the thermo-elasto-plastic finite strains with isotropic and kinematic hardenings fully coupled with ductile damage will be presented. Only the macroscopic phenomenological approach with state variables (monoscale approach) will be discussed in the general framework of the rational thermodynamics for generalized micromorphic continua. The micro-macro (multi-scales approach) in the framework of polycrystalline inelasticity is not presented here for the sake of shortness but will be presented during the oral presentation. The main numerical aspects related to the resolution of the associated initial and boundary value problem will be outlined. A fully adaptive numerical methodology will be briefly described and some numerical examples will be given in order to show the high predictive capabilities of this adaptive methodology for virtual metal forming simulations.

  5. Immunogenetic mechanisms leading to thyroid autoimmunity: recent advances in identifying susceptibility genes and regions.

    PubMed

    Brand, Oliver J; Gough, Stephen C L

    2011-12-01

    The autoimmune thyroid diseases (AITD) include Graves' disease (GD) and Hashimoto's thyroiditis (HT), which are characterised by a breakdown in immune tolerance to thyroid antigens. Unravelling the genetic architecture of AITD is vital to better understanding of AITD pathogenesis, required to advance therapeutic options in both disease management and prevention. The early whole-genome linkage and candidate gene association studies provided the first evidence that the HLA region and CTLA-4 represented AITD risk loci. Recent improvements in; high throughput genotyping technologies, collection of larger disease cohorts and cataloguing of genome-scale variation have facilitated genome-wide association studies and more thorough screening of candidate gene regions. This has allowed identification of many novel AITD risk genes and more detailed association mapping. The growing number of confirmed AITD susceptibility loci, implicates a number of putative disease mechanisms most of which are tightly linked with aspects of immune system function. The unprecedented advances in genetic study will allow future studies to identify further novel disease risk genes and to identify aetiological variants within specific gene regions, which will undoubtedly lead to a better understanding of AITD patho-physiology.

  6. Warship detection in smoke screen interference based on region of interest for CMAC-prediction

    NASA Astrophysics Data System (ADS)

    Yan, Xiaoke; Shi, Caicheng

    2015-10-01

    Warship detection in smoke screen interference background belongs to the field of object extraction from image with low contrast and low signal/noise ratio. Aimed at the specialty of the complex background, a novel algorithm of warship detection in smoke screen interference based on region of interest for CMAC-prediction is proposed in the article. The regions-of-interest (ROI) must be predicted in target tracking of IR image for increasing capture probability. CMAC estimator can effectually resolve conflict between operational counts and predicting precision. The local fractal dimension is used to differentiate the warship from the ROI. The experimental results show that CMAC can accurately estimate the ROI and a similar performance in a low-noise environment and superiority of the fractal operators in a high noise, the algorithms are effectively for smoke screen interference and are easy to be implemented by parallel processing hardware.

  7. Modeling of rain attenuation and site diversity predictions for tropical regions

    NASA Astrophysics Data System (ADS)

    Semire, F. A.; Mohd-Mokhtar, R.; Ismail, W.; Mohamad, N.; Mandeep, J. S.

    2015-03-01

    Presented in this paper is an empirical model for long-term rain attenuation prediction and statistical prediction of site diversity gain on a slant path. Rain attenuation prediction on a slant path is derived using data collected from tropical regions, and the formula proposed is based on Gaussian distribution. The proposed rain attenuation model shows a considerable reduction in prediction error in terms of standard deviation and root-mean-square (rms) error. The site diversity prediction model is derived as a function of site separation distance, frequency of operation, elevation angle and baseline orientation angle. The novelty of the model is the inclusion of low elevation angles and a high link frequency up to 70 GHz in the model derivation. The results of comparison with Hodge, Panagopoulos and Nagaraja empirical predictions show that the proposed model provides a better performance for site separation distance and elevation angle. The overall performance of the proposed site diversity model is good, and the percentage error is within the allowable error limit approved by International Telecommunication Union - Region (ITU-R).

  8. The effects of regional insolation differences upon advanced solar thermal electric power plant performance and energy costs

    NASA Technical Reports Server (NTRS)

    Latta, A. F.; Bowyer, J. M.; Fujita, T.; Richter, P. H.

    1979-01-01

    The performance and cost of the 10 MWe advanced solar thermal electric power plants sited in various regions of the continental United States were determined. The regional insolation data base is discussed. A range for the forecast cost of conventional electricity by region and nationally over the next several cades are presented.

  9. Intra- and interseasonal autoregressive prediction of dengue outbreaks using local weather and regional climate for a tropical environment in Colombia.

    PubMed

    Eastin, Matthew D; Delmelle, Eric; Casas, Irene; Wexler, Joshua; Self, Cameron

    2014-09-01

    Dengue fever transmission results from complex interactions between the virus, human hosts, and mosquito vectors-all of which are influenced by environmental factors. Predictive models of dengue incidence rate, based on local weather and regional climate parameters, could benefit disease mitigation efforts. Time series of epidemiological and meteorological data for the urban environment of Cali, Colombia are analyzed from January of 2000 to December of 2011. Significant dengue outbreaks generally occur during warm-dry periods with extreme daily temperatures confined between 18°C and 32°C--the optimal range for mosquito survival and viral transmission. Two environment-based, multivariate, autoregressive forecast models are developed that allow dengue outbreaks to be anticipated from 2 weeks to 6 months in advance. These models have the potential to enhance existing dengue early warning systems, ultimately supporting public health decisions on the timing and scale of vector control efforts.

  10. Intra- and Interseasonal Autoregressive Prediction of Dengue Outbreaks Using Local Weather and Regional Climate for a Tropical Environment in Colombia

    PubMed Central

    Eastin, Matthew D.; Delmelle, Eric; Casas, Irene; Wexler, Joshua; Self, Cameron

    2014-01-01

    Dengue fever transmission results from complex interactions between the virus, human hosts, and mosquito vectors—all of which are influenced by environmental factors. Predictive models of dengue incidence rate, based on local weather and regional climate parameters, could benefit disease mitigation efforts. Time series of epidemiological and meteorological data for the urban environment of Cali, Colombia are analyzed from January of 2000 to December of 2011. Significant dengue outbreaks generally occur during warm-dry periods with extreme daily temperatures confined between 18°C and 32°C—the optimal range for mosquito survival and viral transmission. Two environment-based, multivariate, autoregressive forecast models are developed that allow dengue outbreaks to be anticipated from 2 weeks to 6 months in advance. These models have the potential to enhance existing dengue early warning systems, ultimately supporting public health decisions on the timing and scale of vector control efforts. PMID:24957546

  11. RNA secondary structure prediction based on SHAPE data in helix regions.

    PubMed

    Lotfi, Mohadeseh; Zare-Mirakabad, Fatemeh; Montaseri, Soheila

    2015-09-01

    RNA molecules play important and fundamental roles in biological processes. Frequently, the functional form of single-stranded RNA molecules requires a specific tertiary structure. Classically, RNA structure determination has mostly been accomplished by X-Ray crystallography or Nuclear Magnetic Resonance approaches. These experimental methods are time consuming and expensive. In the past two decades, some computational methods and algorithms have been developed for RNA secondary structure prediction. In these algorithms, minimum free energy is known as the best criterion. However, the results of algorithms show that minimum free energy is not a sufficient criterion to predict RNA secondary structure. These algorithms need some additional knowledge about the structure, which has to be added in the methods. Recently, the information obtained from some experimental data, called SHAPE, can greatly improve the consistency between the native and predicted RNA secondary structure. In this paper, we investigate the influence of SHAPE data on four types of RNA substructures, helices, loops, base pairs from the start and end of helices and two base pairs from the start and end of helices. The results show that SHAPE data in helix regions can improve the prediction. We represent a new method to apply SHAPE data in helix regions for finding RNA secondary structure. Finally, we compare the results of the method on a set of RNAs to predict minimum free energy structure based on considering all SHAPE data and only SHAPE data in helix regions as pseudo free energy and without SHAPE data (without any pseudo free energy). The results show that RNA secondary structure prediction based on considering only SHAPE data in helix regions is more successful than not considering SHAPE data and it provides competitive results in comparison with considering all SHAPE data.

  12. Interleukin 10 promoter region polymorphisms and susceptibility to advanced alcoholic liver disease

    PubMed Central

    Grove, J; Daly, A; Bassendine, M; Gilvarry, E; Day, C

    2000-01-01

    BACKGROUND—The factors determining why less than 10% of heavy drinkers develop advanced alcoholic liver disease (ALD) remain elusive, although genetic factors may be important. Interleukin 10 (IL-10) is an important cytokine with anti-inflammatory, anti-immune, and antifibrotic functions. Several polymorphisms have been identified in the IL-10 promoter and recent evidence suggests that some of these may have functional effects on IL-10 secretion.
AIMS—To test the hypothesis that IL-10 promoter region polymorphisms are associated with susceptibility to ALD.
METHODS—The allele frequencies for the two single base pair substitutions at positions −627 (C→A) and −1117 (A→G) in the IL-10 promoter were determined in 287 heavy drinkers with biopsy proved advanced ALD, 107 heavy drinkers with no evidence of liver disease or steatosis only on biopsy, and 227 local healthy volunteers.
RESULTS—At position −627, 50% of patients with advanced ALD had a least one A allele compared with 33% of controls (p<0.0001) and 34% of drinkers with no or mild disease (p=0.017). At position −1117, the slight excess of the A allele in drinkers with advanced disease was because of linkage disequilibrium between the A alleles at the two sites.
CONCLUSIONS—Among heavy drinkers, possession of the A allele at position −627 in the IL-10 promoter is associated with an increased risk of advanced liver disease. This is consistent with recent functional data that the −627*A allele is associated with low IL-10 expression which will favour inflammatory, immune mediated, and profibrotic mechanisms of alcohol related liver injury.


Keywords: ethyl alcohol; cirrhosis; interleukin 10; genetic polymorphism PMID:10716685

  13. Regional white matter hyperintensity volume, not hippocampal atrophy, predicts incident Alzheimer disease in the community.

    PubMed

    Brickman, Adam M; Provenzano, Frank A; Muraskin, Jordan; Manly, Jennifer J; Blum, Sonja; Apa, Zoltan; Stern, Yaakov; Brown, Truman R; Luchsinger, José A; Mayeux, Richard

    2012-12-01

    BACKGROUND New-onset Alzheimer disease (AD) is often attributed to degenerative changes in the hippocampus. However, the contribution of regionally distributed small vessel cerebrovascular disease, visualized as white matter hyperintensities (WMHs) on magnetic resonance imaging, remains unclear. OBJECTIVE To determine whether regional WMHs and hippocampal volume predict incident AD in an epidemiological study. DESIGN A longitudinal community-based epidemiological study of older adults from northern Manhattan, New York. SETTING The Washington Heights/Inwood Columbia Aging Project. PARTICIPANTS Between 2005 and 2007, 717 participants without dementia received magnetic resonance imaging scans. A mean (SD) of 40.28 (9.77) months later, 503 returned for follow-up clinical examination and 46 met criteria for incident dementia (45 with AD). Regional WMHs and relative hippocampal volumes were derived. Three Cox proportional hazards models were run to predict incident dementia, controlling for relevant variables. The first included all WMH measurements; the second included relative hippocampal volume; and the third combined the 2 measurements. MAIN OUTCOME MEASURE Incident AD. RESULTS White matter hyperintensity volume in the parietal lobe predicted time to incident dementia (hazard ratio [HR] = 1.194; P = .03). Relative hippocampal volume did not predict incident dementia when considered alone (HR = 0.419; P = .77) or with the WMH measures included in the model (HR = 0.302; P = .70). Including hippocampal volume in the model did not notably alter the predictive utility of parietal lobe WMHs (HR = 1.197; P = .049). CONCLUSIONS The findings highlight the regional specificity of the association of WMHs with AD. It is not clear whether parietal WMHs solely represent a marker for cerebrovascular burden or point to distinct injury compared with other regions. Future work should elucidate pathogenic mechanisms linking WMHs and AD pathology.

  14. Broca's region and Visual Word Form Area activation differ during a predictive Stroop task.

    PubMed

    Wallentin, Mikkel; Gravholt, Claus Højbjerg; Skakkebæk, Anne

    2015-12-01

    Competing theories attempt to explain the function of Broca's area in single word processing. Studies have found the region to be more active during processing of pseudo words than real words and during infrequent words relative to frequent words and during Stroop (incongruent) color words compared to Non-Stroop (congruent) words. Two related theories explain these findings as reflecting either "cognitive control" processing in the face of conflicting input or a linguistic prediction error signal, based on a predictive coding approach. The latter implies that processing cost refers to violations of expectations based on the statistical distributions of input. In this fMRI experiment we attempted to disentangle single word processing cost originating from cognitive conflict and that stemming from predictive expectation violation. Participants (N = 49) responded to whether the words "GREEN" or "RED" were displayed in green or red (incongruent vs congruent colors). One of the colors, however, was presented three times as often as the other, making it possible to study both congruency and frequency effects independently. Auditory stimuli saying "GREEN" or "RED" had the same distribution, making it possible to study frequency effects across modalities. We found significant behavioral effects of both incongruency and frequency. A significant effect (p < .05 FWE) of incongruency was found in Broca's region, but no effect of frequency was observed and no interaction. Conjoined effects of incongruency and frequency were found in parietal regions as well as in the Visual Word Form Area (VWFA). No interaction between perceptual modality and frequency was found in VWFA suggesting that the region is not strictly visual. These findings speak against a strong version of the prediction error processing hypothesis in Broca's region. They support the idea that prediction error processes in the intermediate timeframe are allocated to more posterior parts of the brain. PMID:26478962

  15. Broca's region and Visual Word Form Area activation differ during a predictive Stroop task.

    PubMed

    Wallentin, Mikkel; Gravholt, Claus Højbjerg; Skakkebæk, Anne

    2015-12-01

    Competing theories attempt to explain the function of Broca's area in single word processing. Studies have found the region to be more active during processing of pseudo words than real words and during infrequent words relative to frequent words and during Stroop (incongruent) color words compared to Non-Stroop (congruent) words. Two related theories explain these findings as reflecting either "cognitive control" processing in the face of conflicting input or a linguistic prediction error signal, based on a predictive coding approach. The latter implies that processing cost refers to violations of expectations based on the statistical distributions of input. In this fMRI experiment we attempted to disentangle single word processing cost originating from cognitive conflict and that stemming from predictive expectation violation. Participants (N = 49) responded to whether the words "GREEN" or "RED" were displayed in green or red (incongruent vs congruent colors). One of the colors, however, was presented three times as often as the other, making it possible to study both congruency and frequency effects independently. Auditory stimuli saying "GREEN" or "RED" had the same distribution, making it possible to study frequency effects across modalities. We found significant behavioral effects of both incongruency and frequency. A significant effect (p < .05 FWE) of incongruency was found in Broca's region, but no effect of frequency was observed and no interaction. Conjoined effects of incongruency and frequency were found in parietal regions as well as in the Visual Word Form Area (VWFA). No interaction between perceptual modality and frequency was found in VWFA suggesting that the region is not strictly visual. These findings speak against a strong version of the prediction error processing hypothesis in Broca's region. They support the idea that prediction error processes in the intermediate timeframe are allocated to more posterior parts of the brain.

  16. Disparities in the Use of Radiation Therapy in Patients With Local-Regionally Advanced Breast Cancer

    SciTech Connect

    Martinez, Steve R.; Beal, Shannon H.; Chen, Steven L.; Canter, Robert J.; Khatri, Vijay P.; Chen, Allen; Bold, Richard J.

    2010-11-01

    Background: Radiation therapy (RT) is indicated for the treatment of local-regionally advanced breast cancer (BCa). Hypothesis: We hypothesized that black and Hispanic patients with local-regionally advanced BCa would receive lower rates of RT than their white counterparts. Methods: The Surveillance Epidemiology and End Results database was used to identify white, black, Hispanic, and Asian patients with invasive BCa and {>=}10 metastatic lymph nodes diagnosed between 1988 and 2005. Univariate and multivariate logistic regression evaluated the relationship of race/ethnicity with use of RT. Multivariate models stratified for those undergoing mastectomy or lumpectomy. Results: Entry criteria were met by 12,653 patients. Approximately half of the patients did not receive RT. Most patients were white (72%); the remainder were Hispanic (10.4%), black (10.3%), and Asian (7.3%). On univariate analysis, Hispanics (odd ratio [OR] 0.89; 95% confidence interval [CI], 0.79-1.00) and blacks (OR 0.79; 95% CI, 0.70-0.89) were less likely to receive RT than whites. On multivariate analysis, blacks (OR 0.76; 95% CI, 0.67-0.86) and Hispanics (OR 0.80; 95% CI, 0.70-0.90) were less likely than whites to receive RT. Disparities persisted for blacks (OR 0.74; 95% CI, 0.64-0.85) and Hispanics (OR 0.77; 95% CI, 0.67-0.89) who received mastectomy, but not for those who received lumpectomy. Conclusions: Many patients with local-regionally advanced BCa do not receive RT. Blacks and Hispanics were less likely than whites to receive RT. This disparity was noted predominately in patients who received mastectomy. Future efforts at improving rates of RT are warranted. Efforts at eliminating racial/ethnic disparities should focus on black and Hispanic candidates for postmastectomy RT.

  17. [Plasma Biomarkers as Predictive Factors for Advanced Hepatocellular Carcinoma with Sorafenib].

    PubMed

    Shiozawa, Kazue; Watanabe, Manabu; Ikehara, Takashi; Matsukiyo, Yasushi; Kogame, Michio; Shinohara, Mie; Kikuchi, Yoshinori; Igarashi, Yoshinori; Sumino, Yasukiyo

    2016-07-01

    We examined plasma biomarkers as predictive factors for advanced hepatocellular carcinoma(ad-HCC)patients treated with sorafenib. We analyzed a-fetoprotein(AFP), AFP-L3, des-g-carboxy prothrombin(DCP), neutrophil-to-lymphocyte ratio(NLR), platelet-to-lymphocyte ratio(PLR), and vascular endothelial growth factor(VEGF)before sorafenib therapy, and changes in AFP-L3, NLR, PLR, and VEGF 1 month after sorafenib therapy in 16 patients. High AFP-L3(hazard ratio: 1.058, 95%CI: 1.019-1.098, p=0.003)and high NLR(hazard ratio: 1.475, 95%CI: 1.045-2.082, p=0.027)were significantly associated with poor prognosis in ad-HCC patients treated with sorafenib. There were no significant differences in changes in AFP-L3, NLR, PLR, and VEGF 1 month after sorafenib therapy. We suggest that AFP-L3 and NLR levels before sorafenib therapy in patients with ad-HCC are an important predictive factor for the therapeutic effect of sorafenib and patient survival. PMID:27431630

  18. Longitudinal Temporal and Probabilistic Prediction of Survival in a Cohort of Patients With Advanced Cancer

    PubMed Central

    Perez-Cruz, Pedro E.; dos Santos, Renata; Silva, Thiago Buosi; Crovador, Camila Souza; Nascimento, Maria Salete de Angelis; Hall, Stacy; Fajardo, Julieta; Bruera, Eduardo; Hui, David

    2014-01-01

    Context Survival prognostication is important during end-of-life. The accuracy of clinician prediction of survival (CPS) over time has not been well characterized. Objectives To examine changes in prognostication accuracy during the last 14 days of life in a cohort of patients with advanced cancer admitted to two acute palliative care units and to compare the accuracy between the temporal and probabilistic approaches. Methods Physicians and nurses prognosticated survival daily for cancer patients in two hospitals until death/discharge using two prognostic approaches: temporal and probabilistic. We assessed accuracy for each method daily during the last 14 days of life comparing accuracy at day −14 (baseline) with accuracy at each time point using a test of proportions. Results 6718 temporal and 6621 probabilistic estimations were provided by physicians and nurses for 311 patients, respectively. Median (interquartile range) survival was 8 (4, 20) days. Temporal CPS had low accuracy (10–40%) and did not change over time. In contrast, probabilistic CPS was significantly more accurate (p<.05 at each time point) but decreased close to death. Conclusion Probabilistic CPS was consistently more accurate than temporal CPS over the last 14 days of life; however, its accuracy decreased as patients approached death. Our findings suggest that better tools to predict impending death are necessary. PMID:24746583

  19. Advanced error-prediction LDPC with temperature compensation for highly reliable SSDs

    NASA Astrophysics Data System (ADS)

    Tokutomi, Tsukasa; Tanakamaru, Shuhei; Iwasaki, Tomoko Ogura; Takeuchi, Ken

    2015-09-01

    To improve the reliability of NAND Flash memory based solid-state drives (SSDs), error-prediction LDPC (EP-LDPC) has been proposed for multi-level-cell (MLC) NAND Flash memory (Tanakamaru et al., 2012, 2013), which is effective for long retention times. However, EP-LDPC is not as effective for triple-level cell (TLC) NAND Flash memory, because TLC NAND Flash has higher error rates and is more sensitive to program-disturb error. Therefore, advanced error-prediction LDPC (AEP-LDPC) has been proposed for TLC NAND Flash memory (Tokutomi et al., 2014). AEP-LDPC can correct errors more accurately by precisely describing the error phenomena. In this paper, the effects of AEP-LDPC are investigated in a 2×nm TLC NAND Flash memory with temperature characterization. Compared with LDPC-with-BER-only, the SSD's data-retention time is increased by 3.4× and 9.5× at room-temperature (RT) and 85 °C, respectively. Similarly, the acceptable BER is increased by 1.8× and 2.3×, respectively. Moreover, AEP-LDPC can correct errors with pre-determined tables made at higher temperatures to shorten the measurement time before shipping. Furthermore, it is found that one table can cover behavior over a range of temperatures in AEP-LDPC. As a result, the total table size can be reduced to 777 kBytes, which makes this approach more practical.

  20. Investigation to advance prediction techniques of the low-speed aerodynamics of V/STOL aircraft

    NASA Technical Reports Server (NTRS)

    Maskew, B.; Strash, D.; Nathman, J.; Dvorak, F. A.

    1985-01-01

    A computer program, VSAERO, has been applied to a number of V/STOL configurations with a view to advancing prediction techniques for the low-speed aerodynamic characteristics. The program couples a low-order panel method with surface streamline calculation and integral boundary layer procedures. The panel method--which uses piecewise constant source and doublet panels-includes an iterative procedure for wake shape and models boundary layer displacement effect using the source transpiration technique. Certain improvements to a basic vortex tube jet model were installed in the code prior to evaluation. Very promising results were obtained for surface pressures near a jet issuing at 90 deg from a flat plate. A solid core model was used in the initial part of the jet with a simple entrainment model. Preliminary representation of the downstream separation zone significantly improve the correlation. The program accurately predicted the pressure distribution inside the inlet on the Grumman 698-411 design at a range of flight conditions. Furthermore, coupled viscous/potential flow calculations gave very close correlation with experimentally determined operational boundaries dictated by the onset of separation inside the inlet. Experimentally observed degradation of these operational boundaries between nacelle-alone tests and tests on the full configuration were also indicated by the calculation. Application of the program to the General Dynamics STOL fighter design were equally encouraging. Very close agreement was observed between experiment and calculation for the effects of power on pressure distribution, lift and lift curve slope.

  1. Advances and applications of binding affinity prediction methods in drug discovery.

    PubMed

    Parenti, Marco Daniele; Rastelli, Giulio

    2012-01-01

    Nowadays, the improvement of R&D productivity is the primary commitment in pharmaceutical research, both in big pharma and smaller biotech companies. To reduce costs, to speed up the discovery process and to increase the chance of success, advanced methods of rational drug design are very helpful, as demonstrated by several successful applications. Among these, computational methods able to predict the binding affinity of small molecules to specific biological targets are of special interest because they can accelerate the discovery of new hit compounds. Here we provide an overview of the most widely used methods in the field of binding affinity prediction, as well as of our own work in developing BEAR, an innovative methodology specifically devised to overtake some limitations in existing approaches. The BEAR method was successfully validated against different biological targets, and proved its efficacy in retrieving active compounds from virtual screening campaigns. The results obtained so far indicate that BEAR may become a leading tool in the drug discovery pipeline. We primarily discuss advantages and drawbacks of each technique and show relevant examples and applications in drug discovery.

  2. Predicting Regional Drought on Sub-Seasonal to Decadal Time Scales

    NASA Technical Reports Server (NTRS)

    Schubert, Siegfried; Wang, Hailan; Suarez, Max; Koster, Randal

    2011-01-01

    Drought occurs on a wide range of time scales, and within a variety of different types of regional climates. It is driven foremost by an extended period of reduced precipitation, but it is the impacts on such quantities as soil moisture, streamflow and crop yields that are often most important from a users perspective. While recognizing that different users have different needs for drought information, it is nevertheless important to understand that progress in predicting drought and satisfying such user needs, largely hinges on our ability to improve predictions of precipitation. This talk reviews our current understanding of the physical mechanisms that drive precipitation variations on subseasonal to decadal time scales, and the implications for predictability and prediction skill. Examples are given highlighting the phenomena and mechanisms controlling precipitation on monthly (e.g., stationary Rossby waves, soil moisture), seasonal (ENSO) and decadal time scales (PD and AMO).

  3. Parameter estimation method and updating of regional prediction equations for ungaged sites in the desert region of California

    USGS Publications Warehouse

    Barth, Nancy A.; Veilleux, Andrea G.

    2012-01-01

    The U.S. Geological Survey (USGS) is currently updating at-site flood frequency estimates for USGS streamflow-gaging stations in the desert region of California. The at-site flood-frequency analysis is complicated by short record lengths (less than 20 years is common) and numerous zero flows/low outliers at many sites. Estimates of the three parameters (mean, standard deviation, and skew) required for fitting the log Pearson Type 3 (LP3) distribution are likely to be highly unreliable based on the limited and heavily censored at-site data. In a generalization of the recommendations in Bulletin 17B, a regional analysis was used to develop regional estimates of all three parameters (mean, standard deviation, and skew) of the LP3 distribution. A regional skew value of zero from a previously published report was used with a new estimated mean squared error (MSE) of 0.20. A weighted least squares (WLS) regression method was used to develop both a regional standard deviation and a mean model based on annual peak-discharge data for 33 USGS stations throughout California’s desert region. At-site standard deviation and mean values were determined by using an expected moments algorithm (EMA) method for fitting the LP3 distribution to the logarithms of annual peak-discharge data. Additionally, a multiple Grubbs-Beck (MGB) test, a generalization of the test recommended in Bulletin 17B, was used for detecting multiple potentially influential low outliers in a flood series. The WLS regression found that no basin characteristics could explain the variability of standard deviation. Consequently, a constant regional standard deviation model was selected, resulting in a log-space value of 0.91 with a MSE of 0.03 log units. Yet drainage area was found to be statistically significant at explaining the site-to-site variability in mean. The linear WLS regional mean model based on drainage area had a Pseudo- 2 R of 51 percent and a MSE of 0.32 log units. The regional parameter

  4. Protein-ligand binding region prediction (PLB-SAVE) based on geometric features and CUDA acceleration

    PubMed Central

    2013-01-01

    Background Protein-ligand interactions are key processes in triggering and controlling biological functions within cells. Prediction of protein binding regions on the protein surface assists in understanding the mechanisms and principles of molecular recognition. In silico geometrical shape analysis plays a primary step in analyzing the spatial characteristics of protein binding regions and facilitates applications of bioinformatics in drug discovery and design. Here, we describe the novel software, PLB-SAVE, which uses parallel processing technology and is ideally suited to extract the geometrical construct of solid angles from surface atoms. Representative clusters and corresponding anchors were identified from all surface elements and were assigned according to the ranking of their solid angles. In addition, cavity depth indicators were obtained by proportional transformation of solid angles and cavity volumes were calculated by scanning multiple directional vectors within each selected cavity. Both depth and volume characteristics were combined with various weighting coefficients to rank predicted potential binding regions. Results Two test datasets from LigASite, each containing 388 bound and unbound structures, were used to predict binding regions using PLB-SAVE and two well-known prediction systems, SiteHound and MetaPocket2.0 (MPK2). PLB-SAVE outperformed the other programs with accuracy rates of 94.3% for unbound proteins and 95.5% for bound proteins via a tenfold cross-validation process. Additionally, because the parallel processing architecture was designed to enhance the computational efficiency, we obtained an average of 160-fold increase in computational time. Conclusions In silico binding region prediction is considered the initial stage in structure-based drug design. To improve the efficacy of biological experiments for drug development, we developed PLB-SAVE, which uses only geometrical features of proteins and achieves a good overall performance

  5. Regional boreal summer intraseasonal oscillation over Indian Ocean and Western Pacific: comparison and predictability study

    NASA Astrophysics Data System (ADS)

    Lee, Sun-Seon; Wang, Bin

    2016-04-01

    The boreal summer intraseasonal oscillation (BSISO) has two major activity centers, the northern Indian Ocean and tropical Western North Pacific, which dominate the monsoon intraseasonal variability over South Asia and East Asia, respectively. The spatial-temporal structures of BSISO over the Indian Ocean (10°S-30°N, 60°-105°E) (IOISO) and Western Pacific (10°S-30°N, 105°-150°E) (WPISO) are examined by corresponding the leading modes of daily OLR and 850-hPa zonal wind (U850). The IOISO features a northeastward propagation with a 30-45 days energy peak and the first principal component (PC1) has maximum variance in May, while the WPISO propagates northward with a broad spectral peak on 10-60 days and the PC1 has maximum variance in August. Because of the large regional differences, two regional indices, the IOISO index and WPISO index, are defined by their corresponding first two leading PCs. The combined IOISO-WPISO index captures about 30 % (10 %) of U850 (OLR) daily variance over the entire IO-WP region (10°S-30°N, 60°-150°E), which doubles that captured by the Madden-Julian Oscillation (MJO) index (Wheeler and Hendon 2004) and is 50 % higher than that captured by the BSISO index (Lee et al. 2013). The combined index also shows superior performance in representing biweekly and pentad-mean variations in the Asian-Pacific summer monsoon region (north of 10°N). The predictability/prediction skill and simulated principal modes of two regional BSISO indices are explored by using data derived from the Intraseasonal Variability Hindcast Experiment project. The major regional modes are reasonably well captured, but the forecasted fractional variances of the leading modes and variability center's locations exhibit significant deficiencies. The multi-model mean estimate of the predictability is 40-45 days for the IOISO index, whereas 33-37 days for the WPISO index. The less predictable WPISO is likely due to the existence of its significant biweekly component

  6. The Climate Variability & Predictability (CVP) Program at NOAA - DYNAMO Recent Project Advancements

    NASA Astrophysics Data System (ADS)

    Lucas, S. E.; Todd, J. F.; Higgins, W.

    2013-12-01

    The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International Geosphere-Biosphere Programme (IGBP), and the U.S. Global Change Research Program (USGCRP). The CVP program sits within the Earth System Science (ESS) Division at NOAA's Climate Program Office. Dynamics of the Madden-Julian Oscillation (DYNAMO): The Indian Ocean is one of Earth's most sensitive regions because the interactions between ocean and atmosphere there have a discernable effect on global climate patterns. The tropical weather that brews in that region can move eastward along the equator and reverberate around the globe, shaping weather and climate in far-off places. The vehicle for this variability is a phenomenon called the Madden-Julian Oscillation, or MJO. The MJO, which originates over the Indian Ocean roughly every 30 to 90 days, is known to influence the Asian and Australian monsoons. It can also enhance hurricane activity in the northeast Pacific and Gulf of Mexico, trigger torrential rainfall along the west coast of North America, and affect the onset of El Niño. CVP-funded scientists participated in the DYNAMO field campaign in 2011-12. Results from this international campaign are expected to improve researcher's insights into this influential phenomenon. A better understanding of the processes governing MJO is an essential step toward

  7. Advances in Landslide Nowcasting: Evaluation of a Global and Regional Modeling Approach

    NASA Technical Reports Server (NTRS)

    Kirschbaum, Dalia Bach; Peters-Lidard, Christa; Adler, Robert; Hong, Yang; Kumar, Sujay; Lerner-Lam, Arthur

    2011-01-01

    represents an important step forward in advancing regional and global-scale landslide hazard assessment.

  8. Toward a unified system for understanding, predicting and projecting regional hurricane activity

    NASA Astrophysics Data System (ADS)

    Vecchi, G. A.; Delworth, T. L.; Yang, X.; Murakami, H.; Zhang, W.; Underwood, S.; Zeng, F. J.; Jia, L.; Kapnick, S. B.; Paffendorf, K.; Krishnamurthy, L.; Wittenberg, A. T.; Msadek, R.; Villarini, G.; Chen, J. H.; Lin, S. J.; Harris, L.; Gudgel, R.; Stern, B.; Zhang, S.

    2015-12-01

    A family of high-resolution (50km and 25km atmospheric/land resolution) global coupled climate models provide a unified framework towards the understanding, intraseasonal-to-decadal prediction and decadal to multi-decadal projection of regional and extreme climate, including tropical cyclones. Initialized predictions of global hurricane activity show skill on regional scales, comparable to the skill on basin-wide scales, suggesting that regional seasonal TC predictions may be a feasible forecast target. The 25km version of the model shows skill at seasonal predictions of the frequency of the most intense hurricanes (Cat. 3-4-5 and Cat. 4-5). It is shown that large-scale systematic errors in the mean-state are a key constraint on the simulation and prediction of variations of regional climate and extremes, and methodologies for overcoming model biases are explored. Improvements in predictions of regional climate are due both to improved representation of local processes, and to improvements in the large-scale climate and variability from improved process representation. These models are used to explore the the response of tropical cyclones, both globally and regionally, to increasing greenhouse gases and to internal climate variations. The 25km model in generally shows a more faithful representation of the impact of climate variability on hurricane activity than the 50km model. The response of the total number and the total power dissipation index of tropical cyclones to increasing greenhouse gases can differ substantially between models of two atmospheric resolutions, 50km and 25km - with the 25km version of the model showing a larger increase in power dissipation from increasing greenhouse gases, principally because - in contrast to that of the 50km model - its global hurricane frequency does not decrease with increasing CO2. Some thoughts on the reasons behind those differences will be offered. The 25km model shows an increase in the frequency of intense tropical

  9. Reward Region Responsivity Predicts Future Weight Gain and Moderating Effects of the TaqIA Allele

    PubMed Central

    Burger, Kyle S.; Yokum, Sonja

    2015-01-01

    Because no large prospective study has investigated neural vulnerability factors that predict future weight gain, we tested whether neural response to receipt and anticipated receipt of palatable food and monetary reward predicted body fat gain over a 3-year follow-up in healthy-weight adolescent humans and whether the TaqIA polymorphism moderates these relations. A total of 153 adolescents completed fMRI paradigms assessing response to these events; body fat was assessed annually over follow-up. Elevated orbitofrontal cortex response to cues signaling impending milkshake receipt predicted future body fat gain (r = 0.32), which is a novel finding that provides support for the incentive sensitization theory of obesity. Neural response to receipt and anticipated receipt of monetary reward did not predict body fat gain, which has not been tested previously. Replicating an earlier finding (Stice et al., 2008a), elevated caudate response to milkshake receipt predicted body fat gain for adolescents with a genetic propensity for greater dopamine signaling by virtue of possessing the TaqIA A2/A2 allele, but lower caudate response predicted body fat gain for adolescents with a genetic propensity for less dopamine signaling by virtue of possessing a TaqIA A1 allele, though this interaction was only marginal [p-value <0.05 corrected using voxel-level familywise error rate (pFWE) = 0.06]. Parental obesity, which correlated with TaqIA allele status (odds ratio = 2.7), similarly moderated the relation of caudate response to milkshake receipt to future body fat gain, which is another novel finding. The former interaction implies that too much or too little dopamine signaling and reward region responsivity increases risk for overeating, suggesting qualitatively distinct reward surfeit and reward deficit pathways to obesity. SIGNIFICANCE STATEMENT Because no large prospective study has investigated neural vulnerability factors that predict future weight gain we tested whether

  10. Compression of regions in the global advanced very high resolution radiometer 1-km data set

    NASA Technical Reports Server (NTRS)

    Kess, Barbara L.; Steinwand, Daniel R.; Reichenbach, Stephen E.

    1994-01-01

    The global advanced very high resolution radiometer (AVHRR) 1-km data set is a 10-band image produced at USGS' EROS Data Center for the study of the world's land surfaces. The image contains masked regions for non-land areas which are identical in each band but vary between data sets. They comprise over 75 percent of this 9.7 gigabyte image. The mask is compressed once and stored separately from the land data which is compressed for each of the 10 bands. The mask is stored in a hierarchical format for multi-resolution decompression of geographic subwindows of the image. The land for each band is compressed by modifying a method that ignores fill values. This multi-spectral region compression efficiently compresses the region data and precludes fill values from interfering with land compression statistics. Results show that the masked regions in a one-byte test image (6.5 Gigabytes) compress to 0.2 percent of the 557,756,146 bytes they occupy in the original image, resulting in a compression ratio of 89.9 percent for the entire image.

  11. Proposed parameters of specific rain attenuation prediction for Free Space Optics link operating in tropical region

    NASA Astrophysics Data System (ADS)

    Suriza, A. Z.; Md Rafiqul, Islam; Wajdi, A. K.; Naji, A. W.

    2013-03-01

    As the demand for higher and unlimited bandwidth for communication channel is increased, Free Space Optics (FSO) is a good alternative solution. As it is protocol transparent, easy to install, cost effective and have capabilities like fiber optics, its demand rises very fast. Weather condition, however is the limiting factor for FSO link. In the temperate region the major blockage for FSO link feasibility is fog. In the tropical region high rainfall rate is expected to be the major drawback of FSO link availability. Rain attenuation is the most significant to influence FSO link availability in tropical region. As for now the available k and α values are developed using data from temperate regions. Therefore, the objective of this paper is to propose new parameters for specific rain attenuation prediction model that represents tropical weather condition. The proposed values are derived from data measured in Malaysia and using methods recommended by ITU-R.

  12. Development of Crop Yield Estimation Method by Applying Seasonal Climate Prediction in Asia-Pacific Region

    NASA Astrophysics Data System (ADS)

    Shin, Y.; Lee, E.

    2015-12-01

    Under the influence of recent climate change, abnormal weather condition such as floods and droughts has issued frequently all over the world. The occurrence of abnormal weather in major crop production areas leads to soaring world grain prices because it influence the reduction of crop yield. Development of crop yield estimation method is important means to accommodate the global food crisis caused by abnormal weather. However, due to problems with the reliability of the seasonal climate prediction, application research on agricultural productivity has not been much progress yet. In this study, it is an object to develop long-term crop yield estimation method in major crop production countries worldwide using multi seasonal climate prediction data collected by APEC Climate Center. There are 6-month lead seasonal predictions produced by six state-of-the-art global coupled ocean-atmosphere models(MSC_CANCM3, MSC_CANCM4, NASA, NCEP, PNU, POAMA). First of all, we produce a customized climate data through temporal and spatial downscaling methods for use as a climatic input data to the global scale crop model. Next, we evaluate the uncertainty of climate prediction by applying multi seasonal climate prediction in the crop model. Because rice is the most important staple food crop in the Asia-Pacific region, we assess the reliability of the rice yields using seasonal climate prediction for main rice production countries. RMSE(Root Mean Squire Error) and TCC(Temporal Correlation Coefficient) analysis is performed in Asia-Pacific countries, major 14 rice production countries, to evaluate the reliability of the rice yield according to the climate prediction models. We compare the rice yield data obtained from FAOSTAT and estimated using the seasonal climate prediction data in Asia-Pacific countries. In addition, we show that the reliability of seasonal climate prediction according to the climate models in Asia-Pacific countries where rice cultivation is being carried out.

  13. Hydrology of the North Cascades region, Washington: 2. A proposed hydrometeorological streamflow prediction method

    USGS Publications Warehouse

    Tangborn, Wendell V.; Rasmussen, Lowell A.

    1976-01-01

    On the basis of a linear relationship between winter (October-April) precipitation and annual runoff from a drainage basin (Rasmussen and Tangborn, 1976) a physically reasonable model for predicting summer (May-September) streamflow from drainages in the North Cascades region was developed. This hydrometeorological prediction method relates streamflow for a season beginning on the day of prediction to the storage (including snow, ice, soil moisture, and groundwater) on that day. The spring storage is inferred from an input-output relationship based on the principle of conservation of mass: spring storage equals winter precipitation on the basin less winter runoff from the basin and less winter evapotranspiration, which is presumed to be small. The method of prediction is based on data only from the years previous to the one for which the prediction is made, and the system is revised each year as data for the previous year become available. To improve the basin storage estimate made in late winter or early spring, a short-season runoff prediction is made. The errors resulting from this short-term prediction are used to revise the storage estimate and improve the later prediction. This considerably improves the accuracy of the later prediction, especially for periods early in the summer runoff season. The optimum length for the test period appears to be generally less than a month for east side basins and between 1 and 2 months for those on the west side of the Cascade Range. The time distribution of the total summer runoff can be predicted when this test season is used so that on May 1 monthly streamflow for the May-September season can be predicted. It was found that summer precipitation and the time of minimum storage are two error sources that were amenable to analysis. For streamflow predictions in seasons beginning in early spring the deviation of the subsequent summer precipitation from a long-period average will contribute up to 53% of the prediction error

  14. Global warming and climate change - predictive models for temperate and tropical regions

    SciTech Connect

    Malini, B.H.

    1997-12-31

    Based on the assumption of 4{degree}C increase of global temperature by the turn of 21st century due to the accumulation of greenhouse gases an attempt is made to study the possible variations in different climatic regimes. The predictive climatic water balance model for Hokkaido island of Japan (a temperate zone) indicates the possible occurrence of water deficit for two to three months, which is a unknown phenomenon in this region at present. Similarly, India which represents tropical region also will experience much drier climates with increased water deficit conditions. As a consequence, the thermal region of Hokkaido which at present is mostly Tundra and Micro thermal will change into a Meso thermal category. Similarly, the moisture regime which at present supports per humid (A2, A3 and A4) and Humid (B4) climates can support A1, B4, B3, B2 and B1 climates indicating a shift towards drier side of the climatic spectrum. Further, the predictive modes of both the regions have indicated increased evapotranspiration rates. Although there is not much of change in the overall thermal characteristics of the Indian region the moisture regime indicates a clear shift towards the aridity in the country.

  15. Regional Scale High Resolution δ18O Prediction in Precipitation Using MODIS EVI

    PubMed Central

    Huang, Cho-Ying; Wang, Chung-Ho; Lin, Shou-De; Lo, Yi-Chen; Huang, Bo-Wen; Hatch, Kent A.; Shiu, Hau-Jie; You, Cheng-Feng; Chang, Yuan-Mou; Shen, Sheng-Feng

    2012-01-01

    The natural variation in stable water isotope ratio data, also known as water isoscape, is a spatiotemporal fingerprint and a powerful natural tracer that has been widely applied in disciplines as diverse as hydrology, paleoclimatology, ecology and forensic investigation. Although much effort has been devoted to developing a predictive water isoscape model, it remains a central challenge for scientists to generate high accuracy, fine scale spatiotemporal water isoscape prediction. Here we develop a novel approach of using the MODIS-EVI (the Moderate Resolution Imagining Spectroradiometer-Enhanced Vegetation Index), to predict δ18O in precipitation at the regional scale. Using a structural equation model, we show that the EVI and precipitated δ18O are highly correlated and thus the EVI is a good predictor of precipitated δ18O. We then test the predictability of our EVI-δ18O model and demonstrate that our approach can provide high accuracy with fine spatial (250×250 m) and temporal (16 days) scale δ18O predictions (annual and monthly predictabilities [r] are 0.96 and 0.80, respectively). We conclude the merging of the EVI and δ18O in precipitation can greatly extend the spatial and temporal data availability and thus enhance the applicability for both the EVI and water isoscape. PMID:23029053

  16. A Comparison of Dynamical Seasonal Tropical Cyclone Predictions for the Australian and Western Pacific Regions

    NASA Astrophysics Data System (ADS)

    Shelton, Kay; Charles, Andrew; Nakaegawa, Toshiyuki; Hendon, Harry; Kuleshov, Yuriy

    2013-04-01

    The Australian Bureau of Meteorology (BoM) issues predictions of tropical cyclone (TC) activity in the Australian and South Pacific regions in the October before the TC season (November to April). Currently, these predictions utilise a statistical model based on the historical relationship between tropical cyclone activity and (i) sea surface temperature anomalies in the Equatorial Pacific (NINO3.4 region) and (ii) the Southern Oscillation Index over the past few decades. Variations in the El Niño-Southern Oscillation (ENSO)-TC relationship that are not contained within the historical record can lead to deficiencies in future predictions. The use of dynamical (physics-based) climate models (GCMs) offers an alternative to statistical TC prediction schemes. Any changes to the environment (whatever their character or cause) are incorporated in the analyses used to initialise a dynamical model. As part of the Pacific-Australia Climate Change Science and Adaptation Planning (PACCSAP) Program, BoM is developing dynamically-based seasonal TC predictions for the Australian, South Pacific and North-West Pacific regions. The seasonal TC predictions from two fully-coupled GCMs are evaluated and compared. These models are BoM's Predictive Ocean-Atmosphere Model for Australia (POAMA) and the Japan Meteorological Agency/Meteorological Research Institute Coupled GCM (JMA/MRI-CGCM). The resolution of POAMA's atmospheric component is T42 (~2.5° x 2.5°), while JMA/MRI-CGCM is T95 (~1.8° x 1.8°). Two TC tracking methods are employed and applied to both models to evaluate the influence of model composition and tracking technique on seasonal TC predictions. In the more traditional TC detection scheme TCs are identified where 850-hPa relative vorticity is a maximum (minimum in the Southern Hemisphere) and exceeds a certain threshold. Additionally, the 500-200-hPa thickness and the difference in maximum winds at 850 and 200 hPa are used to differentiate tropical from extratropical

  17. Advances in Landslide Hazard Forecasting: Evaluation of Global and Regional Modeling Approach

    NASA Technical Reports Server (NTRS)

    Kirschbaum, Dalia B.; Adler, Robert; Hone, Yang; Kumar, Sujay; Peters-Lidard, Christa; Lerner-Lam, Arthur

    2010-01-01

    algorithm performance accuracy include incorporating additional triggering factors such as tectonic activity, anthropogenic impacts and soil moisture into the algorithm calculation. Despite these limitations, the methodology presented in this regional evaluation is both straightforward to calculate and easy to interpret, making results transferable between regions and allowing findings to be placed within an inter-comparison framework. The regional algorithm scenario represents an important step in advancing regional and global-scale landslide hazard assessment and forecasting.

  18. In-Service Design & Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation

    SciTech Connect

    G. R. Odette; G. E. Lucas

    2005-11-15

    This final report on "In-Service Design & Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation" (DE-FG03-01ER54632) consists of a series of summaries of work that has been published, or presented at meetings, or both. It briefly describes results on the following topics: 1) A Transport and Fate Model for Helium and Helium Management; 2) Atomistic Studies of Point Defect Energetics, Dynamics and Interactions; 3) Multiscale Modeling of Fracture consisting of: 3a) A Micromechanical Model of the Master Curve (MC) Universal Fracture Toughness-Temperature Curve Relation, KJc(T - To), 3b) An Embrittlement DTo Prediction Model for the Irradiation Hardening Dominated Regime, 3c) Non-hardening Irradiation Assisted Thermal and Helium Embrittlement of 8Cr Tempered Martensitic Steels: Compilation and Analysis of Existing Data, 3d) A Model for the KJc(T) of a High Strength NFA MA957, 3e) Cracked Body Size and Geometry Effects of Measured and Effective Fracture Toughness-Model Based MC and To Evaluations of F82H and Eurofer 97, 3-f) Size and Geometry Effects on the Effective Toughness of Cracked Fusion Structures; 4) Modeling the Multiscale Mechanics of Flow Localization-Ductility Loss in Irradiation Damaged BCC Alloys; and 5) A Universal Relation Between Indentation Hardness and True Stress-Strain Constitutive Behavior. Further details can be found in the cited references or presentations that generally can be accessed on the internet, or provided upon request to the authors. Finally, it is noted that this effort was integrated with our base program in fusion materials, also funded by the DOE OFES.

  19. Complex Networks Reveal Persistent Global / Regional Structure and Predictive Information Content in Climate Data

    NASA Astrophysics Data System (ADS)

    Steinhaeuser, K.; Chawla, N. V.; Ganguly, A. R.

    2010-12-01

    Recent articles have posited that the skills of climate model projections, particularly for variables and scales of interest to decision makers, may need to be significantly improved. Here we hypothesize that there is information content in variables that are projected more reliably, for example, sea surface temperatures, which is relevant for improving predictions of other variables at scales which may be more crucial, for example, regional land temperature and precipitation anomalies. While this hypothesis may be partially supported based on conceptual understanding, a key question to explore is whether the relevant information content can be meaningfully extracted from observations and model simulations. Here we use climate reconstructions from reanalysis datasets to examine the question in detail. Our tool of choice is complex networks, which have provided useful insights in the context of descriptive analysis and change detection for climate in the recent literature. We describe a new adaptation of complex networks based on computational approaches which provide additional descriptive insights at both global and regional scales, specifically sea surface variables, and provide a unified framework for data-guided predictive modeling, specifically for regional temperature and precipitation over land. Complex networks were constructed from historical data to study the properties of the global climate system and characterize behavior at the global scale. Clusters based on community detection, which leverage the network distance, were used to identify regional structures. Persistence and stability of these features over time were evaluated. Predictive information content of ocean indicators with respect to land climate was extracted using a suite of regression models and validated on held-out data. Our results suggest that the new adaptation of complex networks may be well-suited to provide a unified framework for exploring climate teleconnections or long

  20. The predicted circulation response to global warming and implications for regional hydroclimate.

    NASA Astrophysics Data System (ADS)

    Simpson, Isla; Seager, Richard; Ting, Mingfang; Shaw, Tiffany

    2016-04-01

    A critical aspect of human-induced climate change is how it will affect regional hydroclimate around the world. To leading order, the increased ability of the atmosphere to hold moisture as it warms, intensifies moisture transports, making sub-tropical dry regions drier and mid- to high latitude wet regions wetter. But regional changes in hydroclimate will also depend on how the atmospheric circulation responds to warming. Here, the predictions of the future of the mid-latitude circulation by the current generation of global climate models will be discussed, with a particular focus on circulation changes that impact on regional hydroclimate. In the Northern Hemisphere winter, stationary wave changes are a leading order effect and impact on both North American and European hydroclimate. However, in certain regions, models exhibit considerable diversity in this response, motivating the need for improved understanding of the mechanisms involved and the reasons behind such a model spread. This is particularly true in the Pacific-North American sector during winter and so the mechanisms involved in circulation changes in this region and the reason for the inter-model spread will be discussed in detail.

  1. Advances in the regionalization approach: geostatistical techniques for estimating flood quantiles

    NASA Astrophysics Data System (ADS)

    Chiarello, Valentina; Caporali, Enrica; Matthies, Hermann G.

    2015-04-01

    The knowledge of peak flow discharges and associated floods is of primary importance in engineering practice for planning of water resources and risk assessment. Streamflow characteristics are usually estimated starting from measurements of river discharges at stream gauging stations. However, the lack of observations at site of interest as well as the measurement inaccuracies, bring inevitably to the necessity of developing predictive models. Regional analysis is a classical approach to estimate river flow characteristics at sites where little or no data exists. Specific techniques are needed to regionalize the hydrological variables over the considered area. Top-kriging or topological kriging, is a kriging interpolation procedure that takes into account the geometric organization and structure of hydrographic network, the catchment area and the nested nature of catchments. The continuous processes in space defined for the point variables are represented by a variogram. In Top-kriging, the measurements are not point values but are defined over a non-zero catchment area. Top-kriging is applied here over the geographical space of Tuscany Region, in Central Italy. The analysis is carried out on the discharge data of 57 consistent runoff gauges, recorded from 1923 to 2014. Top-kriging give also an estimation of the prediction uncertainty in addition to the prediction itself. The results are validated using a cross-validation procedure implemented in the package rtop of the open source statistical environment R The results are compared through different error measurement methods. Top-kriging seems to perform better in nested catchments and larger scale catchments but no for headwater or where there is a high variability for neighbouring catchments.

  2. Evaluating observations in the context of predictions for the death valley regional groundwater system

    USGS Publications Warehouse

    Ely, D.M.; Hill, M.C.; Tiedeman, C.R.; O'Brien, G. M.

    2004-01-01

    When a model is calibrated by nonlinear regression, calculated diagnostic and inferential statistics provide a wealth of information about many aspects of the system. This work uses linear inferential statistics that are measures of prediction uncertainty to investigate the likely importance of continued monitoring of hydraulic head to the accuracy of model predictions. The measurements evaluated are hydraulic heads; the predictions of interest are subsurface transport from 15 locations. The advective component of transport is considered because it is the component most affected by the system dynamics represented by the regional-scale model being used. The problem is addressed using the capabilities of the U.S. Geological Survey computer program MODFLOW-2000, with its Advective Travel Observation (ADV) Package. Copyright ASCE 2004.

  3. Models to Predict Flowering Time in the Main Saffron Production Regions of Khorasan Province

    NASA Astrophysics Data System (ADS)

    Behdani, M. A.; Koocheki, A.; Nassiri, M.; Rezvani, P.

    The objective of this study was to develop a thermal model that can be used for prediction of saffron flowering time. For this purpose, existing data on saffron flower emergence time were collected in a wide range of temperature regimes over the saffron production regions of Khorasan province, Iran. Linear second-order polynomial and 5-parameter beta models were used and statistically compared for their ability in predicting saffron flowering time as a function of temperature. The results showed a significant delay in flowering date across the temperature gradient. While beta model had a better statistical performance but the simple linear model also showed a good predicting ability and therefore, can be used as a reliable model.

  4. A design and an application of a regional coupled atmosphere-ocean model for tropical cyclone prediction

    NASA Astrophysics Data System (ADS)

    Winterbottom, Henry R.; Uhlhorn, Eric W.; Chassignet, Eric P.

    2012-04-01

    The prediction of tropical cyclone (TC) track has improved greatly in recent decades due in part to the implementation and improvement of numerical weather prediction (NWP) models. However, the prediction of TC intensity using NWP models remains difficult. Several hypotheses have been proposed to explain the factors contributing to the TC intensity prediction errors and one of the leading candidates is the implication of an evolving sea-surface temperature (SST) boundary condition beneath the TC. In this study, a regional scale coupled atmosphere-ocean model is developed using the Advanced Research Weather Research and Forecasting (ARW) model and the HYbrid Coordinate Ocean Model (HYCOM). A coupling algorithm and a methodology to define appropriate ocean initial conditions are provided. Experiments are conducted, during the lifecycle of TC Ike (2008), using both the coupled-model and static (e.g., temporally fixed) SST to illustrate the impacts of the coupled-model for the TC track, intensity, and structure, as well as upon the larger (synoptic) scale. The results from this study suggest that the impact of the evolving SST (e.g., from a coupled atmosphere-ocean model) begin to impact the intensity, size, and thermodynamic structure for TC Ike (2008) at forecast lead-times beyond 48-hours. Further, the forecast trajectories (i.e., tracks) do not illustrate large differences between the non-coupled and coupled-models. Finally, the impact of the SST boundary condition upon TC Ike (2008) appears to be a function of the strength of the atmospheric forcing - in particular the size and intensity of the TC wind field.

  5. Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM

    NASA Technical Reports Server (NTRS)

    Crane, Robert G.; Hewitson, Bruce

    1990-01-01

    Model simulations of global climate change are seen as an essential component of any program aimed at understanding human impact on the global environment. A major weakness of current general circulation models (GCMs), however, is their inability to predict reliably the regional consequences of a global scale change, and it is these regional scale predictions that are necessary for studies of human/environmental response. This research is directed toward the development of a methodology for the validation of the synoptic scale climatology of GCMs. This is developed with regard to the Goddard Institute for Space Studies (GISS) GCM Model 2, with the specific objective of using the synoptic circulation form a doubles CO2 simulation to estimate regional climate change over North America, south of Hudson Bay. This progress report is specifically concerned with validating the synoptic climatology of the GISS GCM, and developing the transfer function to derive grid-point temperatures from the synoptic circulation. Principal Components Analysis is used to characterize the primary modes of the spatial and temporal variability in the observed and simulated climate, and the model validation is based on correlations between component loadings, and power spectral analysis of the component scores. The results show that the high resolution GISS model does an excellent job of simulating the synoptic circulation over the U.S., and that grid-point temperatures can be predicted with reasonable accuracy from the circulation patterns.

  6. A Regional Model for Seasonal Sea Ice Prediction in the Pacific Sector of the Arctic

    NASA Astrophysics Data System (ADS)

    Yuan, X.; Li, Y.; Chen, D.; Zhang, Q.; Li, C.; Niu, F.; Sun, Y.

    2015-12-01

    The recent results from a linear Markov model for seasonal prediction of pan-Arctic sea ice concentration (SIC) show that sea ice in the Pacific sector has the lowest predictability compared to other regions. One reason could be that the climate variability in the Atlantic sector is so dominant that other signals in the Arctic climate system do not appear in the leading modes used for model construction. This study develops a regional Markov model to improve seasonal forecasting of SIC in the Pacific sector. The model climate system consists of various combinations of the monthly mean series of SIC, sea surface temperature (SST), surface air temperature (SAT), pressure/geopotential height fields and winds at pressure levels. Multivariate empirical orthogonal functions (MEOF) and rotated MEOF are applied to each set of data to reduce the model dimensions. After a series of experiments, the final model configuration selects 23 rotated MEOF modes from a data matrix of three variables (SIC, SST and SAT). This regional model shows considerable improvement in the prediction skill in the Pacific sector in all seasons. The anomaly correlation skill increases by 0.2 at 1- to 4-month leads in the Bering Sea, and by 0.1 at 1- to 10-month leads in the Sea of Okhotsk. In general, the model performs better in summer and fall than in winter and spring. On average, the correlation skill can reach 0.6 at a 2-month (4-month) lead in the Bering Sea (the Sea of Okhotsk).

  7. Elevated Reward Region Responsivity Predicts Future Substance Use Onset But Not Overweight/Obesity Onset

    PubMed Central

    Stice, Eric; Yokum, Sonja; Burger, Kyle S.

    2013-01-01

    Background We tested the hypotheses that adolescents who show elevated reward region responsivity are at increased risk for initial onset of overweight/obesity and substance use, which is important because there have been no such prospective tests of the reward surfeit model of these motivated behaviors. Methods One hundred sixty-two adolescents (mean age = 15.3 ± 1.06 years) with healthy weights (mean body mass index = 20.8 ± 1.90) completed functional magnetic resonance imaging paradigms that assessed neural activation in response to receipt and anticipated receipt of palatable food and monetary reward; body fat and substance use were assessed at baseline and 1-year follow-up. Results Elevated caudate (r = .31, p < .001) and putamen (r = .28, p < .001) response to monetary reward predicted substance use onset over 1-year follow-up, but reward circuitry responsivity did not predict future overweight/obesity onset. Adolescents who reported substance use versus abstinence at baseline also showed less caudate (r = –.31, p < .001) response to monetary reward. Discussion Results show that hyper-responsivity of reward circuitry increases risk for future substance use onset, providing novel support for the reward surfeit model. Results also imply that even a limited substance use history was associated with reduced reward region responsivity, extending results from studies that compared substance-dependent individuals with healthy control subjects and suggesting that substance use downregulates reward circuitry. However, aberrant reward region responsivity did not predict initial unhealthy weight gain. PMID:23312561

  8. Sensitivity of soil moisture initialization for decadal predictions under different regional climatic conditions in Europe

    NASA Astrophysics Data System (ADS)

    Khodayar, S.; Sehlinger, A.; Feldmann, H.; Kottmeier, C.

    2015-12-01

    The impact of soil initialization is investigated through perturbation simulations with the regional climate model COSMO-CLM. The focus of the investigation is to assess the sensitivity of simulated extreme periods, dry and wet, to soil moisture initialization in different climatic regions over Europe and to establish the necessary spin up time within the framework of decadal predictions for these regions. Sensitivity experiments consisted of a reference simulation from 1968 to 1999 and 5 simulations from 1972 to 1983. The Effective Drought Index (EDI) is used to select and quantify drought status in the reference run to establish the simulation time period for the sensitivity experiments. Different soil initialization procedures are investigated. The sensitivity of the decadal predictions to soil moisture initial conditions is investigated through the analysis of water cycle components' (WCC) variability. In an episodic time scale the local effects of soil moisture on the boundary-layer and the propagated effects on the large-scale dynamics are analysed. The results show: (a) COSMO-CLM reproduces the observed features of the drought index. (b) Soil moisture initialization exerts a relevant impact on WCC, e.g., precipitation distribution and intensity. (c) Regional characteristics strongly impact the response of the WCC. Precipitation and evapotranspiration deviations are larger for humid regions. (d) The initial soil conditions (wet/dry), the regional characteristics (humid/dry) and the annual period (wet/dry) play a key role in the time that soil needs to restore quasi-equilibrium and the impact on the atmospheric conditions. Humid areas, and for all regions, a humid initialization, exhibit shorter spin up times, also soil reacts more sensitive when initialised during dry periods. (e) The initial soil perturbation may markedly modify atmospheric pressure field, wind circulation systems and atmospheric water vapour distribution affecting atmospheric stability

  9. Development of Regional Models that Use Meteorological Variables for Predicting Stripe Rust Disease on Winter Wheat.

    NASA Astrophysics Data System (ADS)

    Melugin Coakley, Stella; Boyd, William S.; Line, Roland F.

    1984-08-01

    Meteorological variables can be used to predict stripe rust, a disease of wheat caused by Puccinia striiformis West., at Lind, Pullman, and Walla Walla, Washington and Pendleton, Oregon in the Pacific Northwest of the United States. Regional models developed using different methodologies are described and evaluated for accuracy. Disease intensity data, collected from 1968 to 1981, were converted to a 0-9 disease index (DI) and were used as the dependent variable in regression analysis. Meteorological data were expressed as standardized negative degree days (NDDZ) accumulated during December and January, the Julian date of spring (JDS) [defined as the date when 40 or more positive degree days (PDD) accumulated during the subsequent 14 days] and PDD for the 80-day period after the JDS. In one of the regional models, NDDZ was accumulated for adjusted time periods at sites other than Pullman. Mallow's Cp criterion was used to evaluate the regression equations with different numbers of independent variables. The most accurate model uses NDDZ and JDS as the independent variables. The models were cross-validated by randomly removing 2 years' data and reformulating the model based on the remaining data; the new model was then used to compare actual and predicted DI. Predicted DI was within one standard error of the actual DI 60% of the time. Incorrect predictions occurred during years when spring was unusually favorable or unfavorable for disease development. The methodology described is applicable to developing statistical models relating other pest occurrences to meteorological conditions.

  10. Prediction of Low Community Sanitation Coverage Using Environmental and Sociodemographic Factors in Amhara Region, Ethiopia.

    PubMed

    Oswald, William E; Stewart, Aisha E P; Flanders, W Dana; Kramer, Michael R; Endeshaw, Tekola; Zerihun, Mulat; Melaku, Birhanu; Sata, Eshetu; Gessesse, Demelash; Teferi, Tesfaye; Tadesse, Zerihun; Guadie, Birhan; King, Jonathan D; Emerson, Paul M; Callahan, Elizabeth K; Moe, Christine L; Clasen, Thomas F

    2016-09-01

    This study developed and validated a model for predicting the probability that communities in Amhara Region, Ethiopia, have low sanitation coverage, based on environmental and sociodemographic conditions. Community sanitation coverage was measured between 2011 and 2014 through trachoma control program evaluation surveys. Information on environmental and sociodemographic conditions was obtained from available data sources and linked with community data using a geographic information system. Logistic regression was used to identify predictors of low community sanitation coverage (< 20% versus ≥ 20%). The selected model was geographically and temporally validated. Model-predicted probabilities of low community sanitation coverage were mapped. Among 1,502 communities, 344 (22.90%) had coverage below 20%. The selected model included measures for high topsoil gravel content, an indicator for low-lying land, population density, altitude, and rainfall and had reasonable predictive discrimination (area under the curve = 0.75, 95% confidence interval = 0.72, 0.78). Measures of soil stability were strongly associated with low community sanitation coverage, controlling for community wealth, and other factors. A model using available environmental and sociodemographic data predicted low community sanitation coverage for areas across Amhara Region with fair discrimination. This approach could assist sanitation programs and trachoma control programs, scaling up or in hyperendemic areas, to target vulnerable areas with additional activities or alternate technologies. PMID:27430547

  11. Predicting compliance for mandible advancement splint therapy in 96 obstructive sleep apnea patients.

    PubMed

    Ingman, Tuula; Arte, Sirpa; Bachour, Adel; Bäck, Leif; Mäkitie, Antti

    2013-12-01

    The treatment of choice in obstructive sleep apnea (OSA) is continuous positive airway pressure (CPAP). Mandible advancement splint (MAS) offers an option for patients with mild or moderate OSA, who refuse or are unable to tolerate CPAP. The aim of the study was to find predictive factors in OSA for MAS therapy. The study group comprised 96 consecutive OSA patients who were sent for MAS therapy during 2008. Data were collected on the patients' general and dental condition, diagnosis, and treatment for OSA. Panoramic and cephalometric radiographs were analysed. The treatment compliance rate and problems with the use of the MAS were recorded. This rate was 57% and the significant affecting factors were protrusion of the mandible with MAS during the adaptation to the appliance as well as shorter maxillary and mandible lengths. The compliance of the MAS therapy was best in patients with short maxilla and mandible, which should be taken into consideration when planning MAS therapy for OSA patients. Finally, a sleep study should be part of the follow-up in this patient population. PMID:23159421

  12. A Priori Attitudes Predict Amniocentesis Uptake in Women of Advanced Maternal Age: A Pilot Study.

    PubMed

    Grinshpun-Cohen, Julia; Miron-Shatz, Talya; Rhee-Morris, Laila; Briscoe, Barbara; Pras, Elon; Towner, Dena

    2015-01-01

    Amniocentesis is an invasive procedure performed during pregnancy to determine, among other things, whether the fetus has Down syndrome. It is often preceded by screening, which gives a probabilistic risk assessment. Thus, ample information is conveyed to women with the goal to inform their decisions. This study examined the factors that predict amniocentesis uptake among pregnant women of advanced maternal age (older than 35 years old at the time of childbirth). Participants filled out a questionnaire regarding risk estimates, demographics, and attitudes on screening and pregnancy termination before their first genetic counseling appointment and were followed up to 24 weeks of gestation. Findings show that women's decisions are not always informed by screening results or having a medical indication. Psychological factors measured at the beginning of pregnancy: amniocentesis risk tolerance, pregnancy termination tolerance, and age risk perception affected amniocentesis uptake. Although most women thought that screening for Down syndrome risk would inform their decision, they later stated other reasons for screening, such as preparing for the possibility of a child with special needs. Findings suggest that women's decisions regarding amniocentesis are driven not only by medical factors, but also by a priori attitudes. The authors believe that these should be addressed in the dialogue on women's informed use of prenatal tests. PMID:26065331

  13. Methodological advances in predicting flow-induced dynamics of plants using mechanical-engineering theory.

    PubMed

    de Langre, Emmanuel

    2012-03-15

    The modeling of fluid-structure interactions, such as flow-induced vibrations, is a well-developed field of mechanical engineering. Many methods exist, and it seems natural to apply them to model the behavior of plants, and potentially other cantilever-like biological structures, under flow. Overcoming this disciplinary divide, and the application of such models to biological systems, will significantly advance our understanding of ecological patterns and processes and improve our predictive capabilities. Nonetheless, several methodological issues must first be addressed, which I describe here using two practical examples that have strong similarities: one from agricultural sciences and the other from nuclear engineering. Very similar issues arise in both: individual and collective behavior, small and large space and time scales, porous modeling, standard and extreme events, trade-off between the surface of exchange and individual or collective risk of damage, variability, hostile environments and, in some aspects, evolution. The conclusion is that, although similar issues do exist, which need to be exploited in some detail, there is a significant gap that requires new developments. It is obvious that living plants grow in and adapt to their environment, which certainly makes plant biomechanics fundamentally distinct from classical mechanical engineering. Moreover, the selection processes in biology and in human engineering are truly different, making the issue of safety different as well. A thorough understanding of these similarities and differences is needed to work efficiently in the application of a mechanistic approach to ecology.

  14. Predicting compliance for mandible advancement splint therapy in 96 obstructive sleep apnea patients.

    PubMed

    Ingman, Tuula; Arte, Sirpa; Bachour, Adel; Bäck, Leif; Mäkitie, Antti

    2013-12-01

    The treatment of choice in obstructive sleep apnea (OSA) is continuous positive airway pressure (CPAP). Mandible advancement splint (MAS) offers an option for patients with mild or moderate OSA, who refuse or are unable to tolerate CPAP. The aim of the study was to find predictive factors in OSA for MAS therapy. The study group comprised 96 consecutive OSA patients who were sent for MAS therapy during 2008. Data were collected on the patients' general and dental condition, diagnosis, and treatment for OSA. Panoramic and cephalometric radiographs were analysed. The treatment compliance rate and problems with the use of the MAS were recorded. This rate was 57% and the significant affecting factors were protrusion of the mandible with MAS during the adaptation to the appliance as well as shorter maxillary and mandible lengths. The compliance of the MAS therapy was best in patients with short maxilla and mandible, which should be taken into consideration when planning MAS therapy for OSA patients. Finally, a sleep study should be part of the follow-up in this patient population.

  15. A regional neural network model for predicting mean daily river water temperature

    USGS Publications Warehouse

    Wagner, Tyler; DeWeber, Jefferson Tyrell

    2014-01-01

    Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May–October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover attributes, and used the median prediction from an ensemble of 100 ANNs as our final prediction for each model. The final model included air temperature, landform attributes and forested land cover and predicted mean daily water temperatures with moderate accuracy as determined by root mean squared error (RMSE) at 886 training sites with data from 1980 to 2009 (RMSE = 1.91 °C). Based on validation at 96 sites (RMSE = 1.82) and separately for data from 2010 (RMSE = 1.93), a year with relatively warmer conditions, the model was able to generalize to new stream reaches and years. The most important predictors were mean daily air temperature, prior 7 day mean air temperature, and network catchment area according to sensitivity analyses. Forest land cover at both riparian and catchment extents had relatively weak but clear negative effects. Predicted daily water temperature averaged for the month of July matched expected spatial trends with cooler temperatures in headwaters and at higher elevations and latitudes. Our ANN ensemble is unique in predicting daily temperatures throughout a large region, while other regional efforts have predicted at relatively coarse time steps. The model may prove a useful tool for predicting water temperatures in sampled and unsampled rivers under current conditions and future projections of climate

  16. Derivation and validation of a prediction rule for estimating advanced colorectal neoplasm risk in average-risk Chinese.

    PubMed

    Cai, Quan-Cai; Yu, En-Da; Xiao, Yi; Bai, Wen-Yuan; Chen, Xing; He, Li-Ping; Yang, Yu-Xiu; Zhou, Ping-Hong; Jiang, Xue-Liang; Xu, Hui-Min; Fan, Hong; Ge, Zhi-Zheng; Lv, Nong-Hua; Huang, Zhi-Gang; Li, You-Ming; Ma, Shu-Ren; Chen, Jie; Li, Yan-Qing; Xu, Jian-Ming; Xiang, Ping; Yang, Li; Lin, Fu-Lin; Li, Zhao-Shen

    2012-03-15

    No prediction rule is currently available for advanced colorectal neoplasms, defined as invasive cancer, an adenoma of 10 mm or more, a villous adenoma, or an adenoma with high-grade dysplasia, in average-risk Chinese. In this study between 2006 and 2008, a total of 7,541 average-risk Chinese persons aged 40 years or older who had complete colonoscopy were included. The derivation and validation cohorts consisted of 5,229 and 2,312 persons, respectively. A prediction rule was developed from a logistic regression model and then internally and externally validated. The prediction rule comprised 8 variables (age, sex, smoking, diabetes mellitus, green vegetables, pickled food, fried food, and white meat), with scores ranging from 0 to 14. Among the participants with low-risk (≤3) or high-risk (>3) scores in the validation cohort, the risks of advanced neoplasms were 2.6% and 10.0% (P < 0.001), respectively. If colonoscopy was used only for persons with high risk, 80.3% of persons with advanced neoplasms would be detected while the number of colonoscopies would be reduced by 49.2%. The prediction rule had good discrimination (area under the receiver operating characteristic curve = 0.74, 95% confidence interval: 0.70, 0.78) and calibration (P = 0.77) and, thus, provides accurate risk stratification for advanced neoplasms in average-risk Chinese. PMID:22328705

  17. APPLICATION OF ADVANCED IN VITRO TECHNIQUES TO MEASURE, UNDERSTAND AND PREDICT THE KINETICS AND MECHANISMS OF XENOBIOTIC METABOLISM

    EPA Science Inventory

    We have developed a research program in metabolism that involves numerous collaborators across EPA as well as other federal and academic labs. A primary goal is to develop and apply advanced in vitro techniques to measure, understand and predict the kinetics and mechanisms of xen...

  18. Development of a Measure for Predicting Learning Advancement through Cooperative Education: Reliability and Validity of the PLACE Scale.

    ERIC Educational Resources Information Center

    Parks, Donald K.; Onwuegbuzie, Anthony J.; Cash, Shannon H.

    2001-01-01

    Exploratory factor analysis of data from 2,309 cooperative education students tested a measure of co-op outcomes. Three factors were identified: work skills development, career development, and academic functions. The Predicting Learner Advancement through Cooperative Education Scale appeared to have good psychometric properties. (Contains 27…

  19. Development of Computational Capabilities to Predict the Corrosion Wastage of Boiler Tubes in Advanced Combustion Systems

    SciTech Connect

    Kung, Steven; Rapp, Robert

    2014-08-31

    coal-fired boilers resulting from the coexistence of sulfur and chlorine in the fuel. A new corrosion mechanism, i.e., “Active Sulfidation Corrosion Mechanism,” has been proposed to account for the accelerated corrosion wastage observed on the furnace walls of utility boilers burning coals containing sulfur and chlorine. In addition, a second corrosion mechanism, i.e., “Active Sulfide-to-Oxide Corrosion Mechanism,” has been identified to account for the rapid corrosion attack on superheaters and reheaters. Both of the newly discovered corrosion mechanisms involve the formation of iron chloride (FeCl2) vapor from iron sulfide (FeS) and HCl, followed by the decomposition of FeCl2 via self-sustaining cycling reactions. For higher alloys containing sufficient chromium, the attack on superheaters and reheaters is dominated by Hot Corrosion in the presence of a fused salt. Furthermore, two stages of the hot corrosion mechanism have been identified and characterized in detail. The initiation of hot corrosion attack induced by molten sulfate leads to Stage 1 “acidic” fluxing and re-precipitation of the protective scale formed initially on the deposit-covered alloy surfaces. Once the protective scale is penetrated, Stage 2 Hot Corrosion is initiated, which is dominated by “basic” fluxing and re-precipitation of the scale in the fused salt. Based on the extensive corrosion information generated from this project, corrosion modeling was performed using non-linear regression analysis. As a result of the modeling efforts, two predictive equations have been formulated, one for furnace walls and the other for superheaters and reheaters. These first-of-the-kind equations can be used to estimate the corrosion rates of boiler tubes based on coal chemistry, alloy compositions, and boiler operating conditions for advanced boiler systems.

  20. Predicting success on conditional release for insanity acquittees: regionalized versus nonregionalized hospital patients.

    PubMed

    Tellefsen, C; Cohen, M I; Silver, S B; Dougherty, C

    1992-01-01

    This research compared the outcomes of two cohorts of insanity acquittees: one group was treated solely in the maximum security state forensic hospital before their release to the community (nonregionalized) and the other group was treated at the state forensic hospital and transferred for further treatment at less secure state regional hospitals (regionalized). This research describes the outcome of a group of insanity acquittees (regionalized patients) never previously studied. The applicability of a prediction model based on earlier research of insanity acquittees was tested on the patients. Findings on four outcome indicators are reported: rearrests within five years after release, overall functioning in the community five years after release, rehospitalizations for mental illness, and successful completion of the terms of the five-year conditional release (nonrevocation). Discriminant analysis was performed on the four outcome variables. The model was found to accurately predict the four types of outcome from 69 percent to 94 percent accurately for the nonregionalized insanity acquittees and from 87.5 percent to 95.8 percent for the regionalized patients. This model is currently being adapted to classify patients into potential high- and low-risk groups at the time of conditional release for the purpose of determining the intensity of outpatient supervision.

  1. Decadal predictability of regional scale wind speed and wind energy potentials over Central Europe

    NASA Astrophysics Data System (ADS)

    Moemken, Julia; Reyers, Mark; Buldmann, Benjamin; Pinto, Joaquim G.

    2016-04-01

    Regional climate predictions on timescales from one year to one decade are gaining importance since this time frame falls within the planning horizon of politics, economy, and society. In this context, decadal predictions are of particular interest for the development of renewable energies such as wind energy. The present study examines the decadal predictability of regional scale wind speed and wind energy potentials in the framework of the MiKlip consortium ("Mittelfristige Klimaprognosen"; www.fona-miklip.de). This consortium aims to develop a model system based on the Max-Planck-Institute Earth System Model (MPI-ESM) that can provide skilful decadal predictions on regional and global scales. Three generations of the decadal prediction system, which differ primarily in their ocean initialisation, are analysed here. Ensembles of uninitialised historical and yearly initialised hindcast experiments are used to assess different skill scores for 10m wind speeds and wind energy output (Eout) over Central Europe, with special focus given to Germany. With this aim, a statistical-dynamical downscaling (SDD) approach is used for the regionalisation of the global datasets. Its added value is evaluated by comparison of skill scores for MPI-ESM large-scale wind speeds and SDD simulated regional wind speeds. All three MPI-ESM ensemble generations show some forecast skill for annual mean wind speed and Eout over Central Europe on yearly and multi-yearly time scales. The forecast skill is mostly limited to the first years after initialisation. Differences between the three ensemble generations are generally small. The regionalisation preserves and sometimes increases the forecast skill of the global runs but results depend on lead time and ensemble generation. Moreover, regionalisation often improves the ensemble spread. Seasonal Eout skills are generally lower than for annual means. Skill scores are lowest during summer, and persist longest in autumn. A large-scale westerly

  2. Prediction of response to chemoradiation in rectal cancer by a gene polymorphism in the epidermal growth factor receptor promoter region

    SciTech Connect

    Spindler, Karen-Lise Garm . E-mail: kalgsp@vgs.vejleamt.dk; Nielsen, Jens Nederby; Lindebjerg, Jan; Brandslund, Ivan; Jakobsen, Anders

    2006-10-01

    Purpose: Epidermal growth factor receptor (EGFR) has been associated with radioresistance in solid tumors. Recently a polymorphism in the Sp1 recognition site of the EGFR promoter region was identified. The present study investigated the predictive value of this polymorphism for the outcome of chemoradiation in locally advanced rectal cancer. Methods and Materials: The study included 77 patients with locally advanced T3 rectal tumors. Treatment consisted of preoperative radiation therapy at a total tumor dose of 65 Gy and concomitant chemotherapy with Uftoral. Blood samples from 63 patients were evaluated for Sp1 -216 G/T polymorphism by polymerase chain reaction analysis. Forty-eight primary tumor biopsies were available for EGFR immunostaining. Patients underwent surgery 8 weeks after treatment. Pathologic response evaluation was performed according to the tumor regression grade (TRG) system. Results: Forty-nine percent had major response (TRG1-2) and 51% moderate response (TRG 3-4) to chemoradiation. The rates of major response were 34% (10/29) in GG homozygote patients compared with 65% (22/34) in patients with T containing variants (p = 0.023). Fifty-eight percent of biopsies were positive for EGFR expression (28/48). The major response rates with regard to EGFR immunostaining were not significantly different. EGFR-positive tumors were found in 83% of the GG homozygote patients compared with 38% of patients with TT or GT variants (p = 0.008). Conclusions: There was a significant correlation between EGFR Sp1 -216 G/T polymorphism and treatment response to chemoradiation in locally advanced rectal cancer. Further investigations of a second set of patient and other treatment schedules are warranted.

  3. Mathematical model to predict regions of chromatin attachment to the nuclear matrix.

    PubMed Central

    Singh, G B; Kramer, J A; Krawetz, S A

    1997-01-01

    The potentiation and subsequent initiation of transcription are complex biological phenomena. The region of attachment of the chromatin fiber to the nuclear matrix, known as the matrix attachment region or scaffold attachment region (MAR or SAR), are thought to be requisite for the transcriptional regulation of the eukaryotic genome. As expressed sequences should be contained in these regions, it becomes significant to answer the following question: can these regions be identified from the primary sequence data alone and subsequently used as markers for expressed sequences? This paper represents an effort toward achieving this goal and describes a mathematical model for the detection of MARs. The location of matrix associated regions has been linked to a variety of sequence patterns. Consequently, a list of these patterns is compiled and represented as a set of decision rules using an AND-OR formulation. The DNA sequence was then searched for the presence of these patterns and a statistical significance was associated with the frequency of occurrence of the various patterns. Subsequently, a mathematical potential value,MAR-Potential, was assigned to a sequence region as the inverse proportion to the probability that the observed pattern population occurred at random. Such a MAR detection process was applied to the analysis of a variety of known MAR containing sequences. Regions of matrix association predicted by the software essentially correspond to those determined experimentally. The human T-cell receptor and the DNA sequence from the Drosophila bithorax region were also analyzed. This demonstrates the usefulness of the approach described as a means to direct experimental resources. PMID:9060438

  4. Regional Scale Meteorological Analysis and Prediction Using GPS Occultation and EOS Data

    NASA Technical Reports Server (NTRS)

    Bromwich, David H.; Shum, C. K.; Zhao, Changyin; Kuo, Bill; Rocken, Chris

    2004-01-01

    The main objective of the research under this award is to improve regional meteorological analysis and prediction for traditionally data limited regions, particularly over the Southern Ocean and Antarctica, using the remote sensing observations from current and upcoming GPS radio occultation missions and the EOS instrument suite. The major components of this project are: 1.Develop and improve the methods for retrieving temperature, moisture, and pressure profiles from GPS radio occultation data and EOS radiometer data. 2. Develop and improve a regional scale data assimilation system (MM5 4DVAR). 3. Perform case studies involving data analysis and numerical modeling to investigate the impact of different data for regional meteorological analysis and the importance of data assimilation for regional meteorological simulation over the Antarctic region. 4. Apply the findings and improvements from the above studies to weather forecasting experiments. 5. In the third year of the award we made significant progress toward the remaining goals of the project. The work included carefully evaluating the performance of an atmospheric mesoscale model, the Polar MM5 in Antarctic applications and improving the upper boundary condition.

  5. Testing earthquake prediction algorithms: Statistically significant advance prediction of the largest earthquakes in the Circum-Pacific, 1992-1997

    USGS Publications Warehouse

    Kossobokov, V.G.; Romashkova, L.L.; Keilis-Borok, V. I.; Healy, J.H.

    1999-01-01

    Algorithms M8 and MSc (i.e., the Mendocino Scenario) were used in a real-time intermediate-term research prediction of the strongest earthquakes in the Circum-Pacific seismic belt. Predictions are made by M8 first. Then, the areas of alarm are reduced by MSc at the cost that some earthquakes are missed in the second approximation of prediction. In 1992-1997, five earthquakes of magnitude 8 and above occurred in the test area: all of them were predicted by M8 and MSc identified correctly the locations of four of them. The space-time volume of the alarms is 36% and 18%, correspondingly, when estimated with a normalized product measure of empirical distribution of epicenters and uniform time. The statistical significance of the achieved results is beyond 99% both for M8 and MSc. For magnitude 7.5 + , 10 out of 19 earthquakes were predicted by M8 in 40% and five were predicted by M8-MSc in 13% of the total volume considered. This implies a significance level of 81% for M8 and 92% for M8-MSc. The lower significance levels might result from a global change in seismic regime in 1993-1996, when the rate of the largest events has doubled and all of them become exclusively normal or reversed faults. The predictions are fully reproducible; the algorithms M8 and MSc in complete formal definitions were published before we started our experiment [Keilis-Borok, V.I., Kossobokov, V.G., 1990. Premonitory activation of seismic flow: Algorithm M8, Phys. Earth and Planet. Inter. 61, 73-83; Kossobokov, V.G., Keilis-Borok, V.I., Smith, S.W., 1990. Localization of intermediate-term earthquake prediction, J. Geophys. Res., 95, 19763-19772; Healy, J.H., Kossobokov, V.G., Dewey, J.W., 1992. A test to evaluate the earthquake prediction algorithm, M8. U.S. Geol. Surv. OFR 92-401]. M8 is available from the IASPEI Software Library [Healy, J.H., Keilis-Borok, V.I., Lee, W.H.K. (Eds.), 1997. Algorithms for Earthquake Statistics and Prediction, Vol. 6. IASPEI Software Library]. ?? 1999 Elsevier

  6. Quantification of the uncertainties in soil and vegetation parameterizations for regional climate predictions

    NASA Astrophysics Data System (ADS)

    Breil, Marcus; Schädler, Gerd

    2016-04-01

    The aim of the german research program MiKlip II is the development of an operational climate prediction system that can provide reliable forecasts on a decadal time scale. Thereby, one goal of MiKlip II is to investigate the feasibility of regional climate predictions. Results of recent studies indicate that the regional climate is significantly affected by the interactions between the soil, the vegetation and the atmosphere. Thus, within the framework of MiKlip II a workpackage was established to assess the impact of these interactions on the regional decadal climate predictability. In a Regional Climate Model (RCM) the soil-vegetation-atmosphere interactions are represented in a Land Surface Model (LSM). Thereby, the LSM describes the current state of the land surface by calculating the soil temperature, the soil water content and the turbulent heat fluxes, serving the RCM as lower boundary condition. To be able to solve the corresponding equations, soil and vegetation processes are parameterized within the LSM. Such parameterizations are mainly derived from observations. But in most cases observations are temporally and spatially limited and consequently not able to represent the diversity of nature completely. Thus, soil and vegetation parameterizations always exhibit a certain degree of uncertainty. In the presented study, the uncertainties within a LSM are assessed by stochastic variations of the relevant parameterizations in VEG3D, a LSM developed at the Karlsruhe Institute of Technology (KIT). In a first step, stand-alone simulations of VEG3D are realized with varying soil and vegetation parameters, to identify sensitive model parameters. In a second step, VEG3D is coupled to the RCM COSMO-CLM. With this new model system regional decadal hindcast simulations, driven by global simulations of the Max-Planck-Institute for Meteorology Earth System Model (MPI-ESM), are performed for the CORDEX-EU domain in a resolution of 0.22°. The identified sensitive model

  7. Linkage disequilibrium predicts physical distance in the adenomatous polyposis coli region

    SciTech Connect

    Jorde, L.B.; Watkins, W.S.; Carlson, M.; Albertsen, H.; Thliveris, A.; Leppert, M. )

    1994-05-01

    To test the reliability of linkage-disequilibrium analysis for gene mapping, the authors compared physical distance and linkage disequilibrium among seven polymorphisms in the adenomatous polyposis coli (APC) region on chromosome 5. Three of them lie within the APC gene, and two lie within the nearby MCC (mutated in colon cancer) gene. One polymorphism lies between the two genes, and one is likely to be 5' of MCC. Five of these polymorphisms are newly reported. All polymorphisms were typed in the CEPH kindreds, yielding 179-205 unrelated two-locus haplotypes. Linkage disequilibrium between each pair of polymorphisms is highly correlated with physical distance in this 550-kb region (correlation coefficient [minus].80, P < .006). This result is replicated in both the Utah and non-Utah CEPH kindreds. There is a tendency for greater disequilibrium among pairs of polymorphisms located within the same gene than among other pairs of polymorphisms. Trigenic, quadrigenic, three-locus, and four-locus disequilibrium measures were also estimated, but these measures revealed much less disequilibrium than did the two-locus disequilibrium measures. A review of 19 published disequilibrium studies, including this one, shows that linkage disequilibrium nearly always correlates significantly with physical distance in genomic regions >50-60 kb but that it does not do so in smaller genomic regions. The authors show that this agrees with theoretical predictions. This finding helps to resolve controversies regarding the use of disequilibrium for inferring gene order. Disequilibrium mapping is unlikely to predict gene order correctly in regions <50-60 kb in size but can often be applied successfully in regions of 50-500 kb or so in size. It is convenient that this is the range in which other mapping techniques, including chromosome walking and linkage mapping, become difficult. 81 refs., 3 figs., 5 tabs.

  8. Saudi Arabia: A future regional hub for advanced education, research, science and technology.

    PubMed

    Meo, Sultan Ayoub

    2015-10-01

    Saudi Arabia is the largest country of the Arabian Peninsula, blessed with significant natural resources, including oil, gas and minerals. Saudi Arabia has recognised the importance of education in social and economic transformation, and has established a large number of universities, research and advanced technical institutes which have broken the metropolitan boundaries and have been extended to the far-flung areas of the country. There are 68 universities and degree-awarding institutes. The educational budget reached its highest-ever level of $56.56 billion for the year 2014. About 124,000 Saudi students are pursuing higher education in about 500 universities around the world. Saudi Arabia produced 177826 research papers in Institute for Scientific Information (ISI) database and in the year 2014 alone, 26168 research papers were published in indexed science journals with a rising h-index of 144. The country is turning into a regional hub for advanced education, research, science and technology while swiftly shifting from an oil-based to a knowledge-based economy.

  9. Regional aspects of the North American land surface: Atmosphere interactions and their contributions to the variability and predictability of the regional hydrologic cycle

    NASA Astrophysics Data System (ADS)

    Luo, Yan

    In this study, we investigate the pathways responsible for soil moisture-precipitation interactions and the mechanisms for soil moisture memory at regional scales through analysis of NCEP's North American Regional Reanalysis dataset, which is derived from a system using the mesoscale Eta model coupled with Noah land surface model. The consideration of the relative availability of water and energy leads to the relative strengths of land-atmosphere interaction and soil moisture memory, which are related to the predictability of the regional hydrologic cycle. The seasonal and geographical variations in estimated interaction and memory may establish the relative predictability among the North American basins. The potential for seasonal predictability of the regional hydrologic cycle is conditioned by the foreknowledge of the land surface soil state, which contributes significantly to summer precipitation: (i) The precipitation variability and predictability by strong land-atmosphere interactions are most important in the monsoon regions of Mexico; (ii) Although strong in interactions, the poor soil moisture memory in the Colorado basin and the western part of the Mississippi basin lowers the predictability; (iii) The Columbia basin and the eastern part of the Mississippi basin also stand out as low predictability basins, in that they have good soil moisture memory, but weak strength in interactions, limiting their predictabilities. Our analysis has revealed a highly physically and statistically consistent picture, providing solid support to studies of predictability based on model simulations.

  10. Evaluating the ability of regional models to predict local avian abundance

    USGS Publications Warehouse

    LeBrun, Jaymi J.; Thogmartin, Wayne E.; Miller, James R.

    2012-01-01

    Spatial modeling over broad scales can potentially direct conservation efforts to areas with high species-specific abundances. We examined the performance of regional models for predicting bird abundance at spatial scales typically addressed in conservation planning. Specifically, we used point count data on wood thrush (Hylocichla mustelina) and blue-winged warbler (Vermivora cyanoptera) from 2 time periods (1995-1998 and 2006-2007) to evaluate the ability of regional models derived via Bayesian hierarchical techniques to predict bird abundance. We developed models for each species within Bird Conservation Region (BCR) 23 in the upper midwestern United States at 800-ha, 8,000-ha, and approximately 80,000-ha scales. We obtained count data from the Breeding Bird Survey and land cover data from the National Land Cover Dataset (1992). We evaluated predictions from the best models, as defined by an information-theoretic criterion, using point count data collected within an ecological subregion of BCR 23 at 131 count stations in the 1990s and again in 2006-2007. Competing (Deviance Information Criteria rs = 0.57; P = 0.14), the survey period that most closely aligned with the time period of data used for regional model construction. Wood thrush models exhibited positive correlations with point count data for all survey areas and years combined (rs = 0.58, P ≤ 0.001). In comparison, blue-winged warbler models performed worse as time increased between the point count surveys and vintage of the model building data (rs = 0.03, P = 0.92 for Iowa and rs = 0.13, P = 0.51 for all areas, 2006-2007), likely related to the ephemeral nature of their preferred early successional habitat. Species abundance and sensitivity to changing habitat conditions seems to be an important factor in determining the predictive ability of regional models. Hierarchical models can be a useful tool for concentrating efforts at the scale of management units and should be one of many tools used by

  11. Abs-initio, Predictive Calculations for Optoelectronic and Advanced Materials Research

    NASA Astrophysics Data System (ADS)

    Bagayoko, Diola

    2010-10-01

    Most density functional theory (DFT) calculations find band gaps that are 30-50 percent smaller than the experimental ones. Some explanations of this serious underestimation by theory include self-interaction and the derivative discontinuity of the exchange correlation energy. Several approaches have been developed in the search for a solution to this problem. Most of them entail some modification of DFT potentials. The Green function and screened Coulomb approximation (GWA) is a non-DFT formalism that has led to some improvements. Despite these efforts, the underestimation problem has mostly persisted in the literature. Using the Rayleigh theorem, we describe a basis set and variational effect inherently associated with calculations that employ a linear combination of atomic orbitals (LCAO) in a variational approach of the Rayleigh-Ritz type. This description concomitantly shows a source of large underestimation errors in calculated band gaps, i.e., an often dramatic lowering of some unoccupied energies on account of the Rayleigh theorem as opposed to a physical interaction. We present the Bagayoko, Zhao, and Williams (BZW) method [Phys. Rev. B 60, 1563 (1999); PRB 74, 245214 (2006); and J. Appl. Phys. 103, 096101 (2008)] that systematically avoids this effect and leads (a) to DFT and LDA calculated band gaps of semiconductors in agreement with experiment and (b) theoretical predictions of band gaps that are confirmed by experiment. Unlike most calculations, BZW computations solve, self-consistently, a system of two coupled equations. DFT-BZW calculated effective masses and optical properties (dielectric functions) also agree with measurements. We illustrate ten years of success of the BZW method with its results for GaN, C, Si, 3C-SIC, 4H-SiC, ZnO, AlAs, Ge, ZnSe, w-InN, c-InN, InAs, CdS, AlN and nanostructures. We conclude with potential applications of the BZW method in optoelectronic and advanced materials research.

  12. The Niño1+2 region and the Niño4 region predictability.

    NASA Astrophysics Data System (ADS)

    Miguel, Tasambay-Salazar; Jose, Ortizbevia Maria; Francisco Jose, Alvarez-Garcia; Antonio, Ruizdeelvira

    2016-04-01

    The El Niño-Southern Oscillation variability is monitored basically by the the Niño3.4 Index. In addition, the Niño1+2 and the Niño4 Indexes are also used to characterise ENSO variability, by reason of their relationships with some of the variability of the neighboring regions, like the air temperature in South America or Australia. However, with the increased length of the available instrumental ENSO records, the need of considering the two different ENSO types identified, Eastern Pacific (EP) or Central Pacific (CP), has become more evident. (Yu and Kim 2013). While the Nino3.4 Index is used to monitor the EP events, the CP events are currently identified by removing from the Niño4 Index the variability associated to the Niño1+2 Index (Kao and Yu 2009). Therefore there is a renewed interest on the predictability of both Indexes. In this study we focus on the predictability of the Niño1+2 region variability and those of the Niño4 region, in the recent post-satellital period. We develop a methodology to identify potential predictors among climate modes, represented by their respective indexes. Among the tropical predictors tested we include the most commonly used,like the Southern Oscillation Index or the Warm Water Volume in the equatorial Pacific (WWV) Index, but also some whose part in the ENSO generation and evolution has been pointed only recently, like the Pacific Meridional Mode (PMM) Index or the North Tropical Zonal Gradient and South Tropical Zonal Gradient Indexes.We also include in our study some other tropical Indexes outside the Pacific basin, like the Tropical North Atlantic, the Tropical South Atlantic and the Indian Ocean Dipole Indexes. We use a seasonal approach, based in a linear statistical relationship and focus on leads going from one season to one year. In the case of the Niño1+2 Index, the number of potential predictors is much higher in spring, followed by winter and summer and last of all autumn. The potential predictor most

  13. Comparison between IRI-2007 model predictions and ionospheric observations at European region during extended solar minimum

    NASA Astrophysics Data System (ADS)

    Zakharenkova, Irina; Krankowski, Andrzej; Bilitza, Dieter; Cherniak, Iurii; Shagimuratov, Irk; Krypiak-Gregorczyk, Anna

    The solar minimum began around March 2006 and many predictions of the start and size of Solar Cycle 24 were given since then. In 2007 the Solar Cycle 24 Prediction Panel anticipates the solar minimum marking the onset of Cycle 24 will occur in March 2008 (6 months). Then this date was shifted to the August 2008, after that -to the December 2008. At least solar minimum is extended to the end of 2009. This unusually deep and extended solar minimum makes corrections to the predicted values of solar cycle progression. With every update the predicted values of sunspot number is decreased. It leads to the significant discrepancies in IRI model results in depend on the predicted indices. To calculate the ionospheric parameters the IRI model uses indices file with ionospheric index IG12 and solar sunspot number (12-months running median) Rz12. This IRI file is regularly updated with the newest available indices and predictions. It was considered the IRI model results obtained with use of different predicted and observed IG and Rz indices during 2007-2009 years. For the given study it was done the comparison of the IRI-2007 predicted values of F2 layer critical frequency (foF2) with those observed at several mid-latitude ionospheric stations in European region. Values of foF2 have been scaled manually from ionograms to avoid the evident risks related with using of the autoscaled data that have ionosonde-related errors and uncertainties. It was the ionograms and foF2 values provided by European Digital Upper Atmosphere Server (DIAS). The DIAS bases on real-time and historical data provided by most operating ionospheric stations in Europe. This server collects information from stations located in Rome, Pruhonice, Juliusruh, Athens, Chilton, Ebre and El Arenosillo. For each station it was calculated monthly median of foF2 variation on the base of full month data analysis. We have considered observations taken in the months of January, April, July and October for 2007

  14. Toward prediction of L band scintillations in the equatorial ionization anomaly region

    NASA Astrophysics Data System (ADS)

    Manju, G.; Sreeja, V.; Ravindran, Sudha; Thampi, Smitha V.

    2011-02-01

    The first observations of the duration and spread of equatorial spread F (ESF) at the magnetic equator and their relationship with the L band scintillations in the equatorial ionization anomaly (EIA) region have been presented here. The analysis is done for the equinoctial months of low solar activity period 2005-2006 and the moderate solar activity year 2004. Ionosonde and CRABEX data from Trivandrum and GPS data from four stations in the EIA region centered around 77°E meridian have been used for the study. The results show that the maximum scintillation index (s4) in the EIA region is linearly dependent on the spread of ESF traces for both the equinoxes. The corresponding duration of L band scintillations is also found to be linearly dependent on the duration of ESF at the magnetic equator. Further, the study for the first time reveals the plausible use of the ESF prediction parameter during 1600-1845 IST period for predicting L band scintillations and its inverse relationship with F10.7 cm flux.

  15. Evaluation of GCMs in the context of regional predictive climate impact studies.

    NASA Astrophysics Data System (ADS)

    Kokorev, Vasily; Anisimov, Oleg

    2016-04-01

    Significant improvements in the structure, complexity, and general performance of earth system models (ESMs) have been made in the recent decade. Despite these efforts, the range of uncertainty in predicting regional climate impacts remains large. The problem is two-fold. Firstly, there is an intrinsic conflict between the local and regional scales of climate impacts and adaptation strategies, on one hand, and larger scales, at which ESMs demonstrate better performance, on the other. Secondly, there is a growing understanding that majority of the impacts involve thresholds, and are thus driven by extreme climate events, whereas accent in climate projections is conventionally made on gradual changes in means. In this study we assess the uncertainty in projecting extreme climatic events within a region-specific and process-oriented context by examining the skills and ranking of ESMs. We developed a synthetic regionalization of Northern Eurasia that accounts for the spatial features of modern climatic changes and major environmental and socio-economical impacts. Elements of such fragmentation could be considered as natural focus regions that bridge the gap between the spatial scales adopted in climate-impacts studies and patterns of climate change simulated by ESMs. In each focus region we selected several target meteorological variables that govern the key regional impacts, and examined the ability of the models to replicate their seasonal and annual means and trends by testing them against observations. We performed a similar evaluation with regard to extremes and statistics of the target variables. And lastly, we used the results of these analyses to select sets of models that demonstrate the best performance at selected focus regions with regard to selected sets of target meteorological parameters. Ultimately, we ranked the models according to their skills, identified top-end models that "better than average" reproduce the behavior of climatic parameters, and

  16. Seasonal forecasts in the Sahel region: the use of rainfall-based predictive variables

    NASA Astrophysics Data System (ADS)

    Lodoun, Tiganadaba; Sanon, Moussa; Giannini, Alessandra; Traoré, Pierre Sibiry; Somé, Léopold; Rasolodimby, Jeanne Millogo

    2014-08-01

    In the Sahel region, seasonal predictions are crucial to alleviate the impacts of climate variability on populations' livelihoods. Agricultural planning (e.g., decisions about sowing date, fertilizer application date, and choice of crop or cultivar) is based on empirical predictive indices whose accuracy to date has not been scientifically proven. This paper attempts to statistically test whether the pattern of rainfall distribution over the May-July period contributes to predicting the real onset date and the nature (wet or dry) of the rainy season, as farmers believe. To that end, we considered historical records of daily rainfall from 51 stations spanning the period 1920-2008 and the different agro-climatic zones in Burkina Faso. We performed (1) principal component analysis to identify climatic zones, based on the patterns of intra-seasonal rainfall, (2) and linear discriminant analysis to find the best rainfall-based variables to distinguish between real and false onset dates of the rainy season, and between wet and dry seasons in each climatic zone. A total of nine climatic zones were identified in each of which, based on rainfall records from May to July, we derived linear discriminant functions to correctly predict the nature of a potential onset date of the rainy season (real or false) and that of the rainy season (dry or wet) in at least three cases out of five. These functions should contribute to alleviating the negative impacts of climate variability in the different climatic zones of Burkina Faso.

  17. Regional prediction of carbon isotopes in soil carbonates for Asian dust source tracer

    NASA Astrophysics Data System (ADS)

    Chen, Bing; Cui, Xinjuan; Wang, Yaqiang

    2016-10-01

    Dust particles emitted from deserts and semi-arid lands in northern China cause particulate pollution that increases the burden of disease particularly for urban population in East Asia. The stable carbon isotopes (δ13C) of carbonates in soils and dust aerosols in northern China were investigated. We found that the δ13C of carbonates in surface soils in northern China showed clearly the negative correlation (R2 = 0.73) with Normalized Difference Vegetation Index (NDVI). Using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-derived NDVI, we predicted the regional distribution of δ13C of soil carbonates in deserts, sandy lands, and steppe areas. The predictions show the mean δ13C of -0.4 ± 0.7‰ in soil carbonates in Taklimakan Desert and Gobi Deserts, and the isotope values decrease to -3.3 ± 1.1‰ in sandy lands. The increase in vegetation coverage depletes 13C in soil carbonates, thus the steppe areas are predicted by the lowest δ13C levels (-8.1 ± 1.7‰). The measurements of atmospheric dust samples at eight sites showed that the Asian dust sources were well assigned by the 13C mapping in surface soils. Predicting 13C in large geographical areas with fine resolution offers a cost-effective tracer to monitor dust emissions from sandy lands and steppe areas which show an increasing role in Asian dust loading driven by climate change and human activities.

  18. Genome-scale prediction of proteins with long intrinsically disordered regions.

    PubMed

    Peng, Zhenling; Mizianty, Marcin J; Kurgan, Lukasz

    2014-01-01

    Proteins with long disordered regions (LDRs), defined as having 30 or more consecutive disordered residues, are abundant in eukaryotes, and these regions are recognized as a distinct class of biologically functional domains. LDRs facilitate various cellular functions and are important for target selection in structural genomics. Motivated by the lack of methods that directly predict proteins with LDRs, we designed Super-fast predictor of proteins with Long Intrinsically DisordERed regions (SLIDER). SLIDER utilizes logistic regression that takes an empirically chosen set of numerical features, which consider selected physicochemical properties of amino acids, sequence complexity, and amino acid composition, as its inputs. Empirical tests show that SLIDER offers competitive predictive performance combined with low computational cost. It outperforms, by at least a modest margin, a comprehensive set of modern disorder predictors (that can indirectly predict LDRs) and is 16 times faster compared to the best currently available disorder predictor. Utilizing our time-efficient predictor, we characterized abundance and functional roles of proteins with LDRs over 110 eukaryotic proteomes. Similar to related studies, we found that eukaryotes have many (on average 30.3%) proteins with LDRs with majority of proteomes having between 25 and 40%, where higher abundance is characteristic to proteomes that have larger proteins. Our first-of-its-kind large-scale functional analysis shows that these proteins are enriched in a number of cellular functions and processes including certain binding events, regulation of catalytic activities, cellular component organization, biogenesis, biological regulation, and some metabolic and developmental processes. A webserver that implements SLIDER is available at http://biomine.ece.ualberta.ca/SLIDER/.

  19. A PBL-radiation model for application to regional numerical weather prediction

    NASA Technical Reports Server (NTRS)

    Chang, Chia-Bo

    1989-01-01

    Often in the short-range limited-area numerical weather prediction (NWP) of extratropical weather systems the effects of planetary boundary layer (PBL) processes are considered secondarily important. However, it may not be the case for the regional NWP of mesoscale convective systems over the arid and semi-arid highlands of the southwestern and south-central United States in late spring and summer. Over these dry regions, the PBL can grow quite high up into the lower middle troposphere (600 mb) due to very effective solar heating and hence a vigorous air-land thermal interaction can occur. The interaction representing a major heat source for regional dynamical systems can not be ignored. A one-dimensional PBL-radiation model was developed. The model PBL consists of a constant-flux surface layer superposed with a well-mixed (Ekman) layer. The vertical eddy mixing coefficients for heat and momentum in the surface layer are determined according to the surface similarity theory, while their vertical profiles in the Ekman layer are specified with a cubic polynomial. Prognostic equations are used for predicting the height of the nonneutral PBL. The atmospheric radiation is parameterized to define the surface heat source/sink for the growth and decay of the PBL. A series of real-data numerical experiments has been carried out to obtain a physical understanding how the model performs under various atmospheric and surface conditions. This one-dimensional model will eventually be incorporated into a mesoscale prediction system. The ultimate goal of this research is to improve the NWP of mesoscale convective storms over land.

  20. A methodology for probabilistic predictions of regional climate change from perturbed physics ensembles.

    PubMed

    Murphy, J M; Booth, B B B; Collins, M; Harris, G R; Sexton, D M H; Webb, M J

    2007-08-15

    A methodology is described for probabilistic predictions of future climate. This is based on a set of ensemble simulations of equilibrium and time-dependent changes, carried out by perturbing poorly constrained parameters controlling key physical and biogeochemical processes in the HadCM3 coupled ocean-atmosphere global climate model. These (ongoing) experiments allow quantification of the effects of earth system modelling uncertainties and internal climate variability on feedbacks likely to exert a significant influence on twenty-first century climate at large regional scales. A further ensemble of regional climate simulations at 25km resolution is being produced for Europe, allowing the specification of probabilistic predictions at spatial scales required for studies of climate impacts. The ensemble simulations are processed using a set of statistical procedures, the centrepiece of which is a Bayesian statistical framework designed for use with complex but imperfect models. This supports the generation of probabilities constrained by a wide range of observational metrics, and also by expert-specified prior distributions defining the model parameter space. The Bayesian framework also accounts for additional uncertainty introduced by structural modelling errors, which are estimated using our ensembles to predict the results of alternative climate models containing different structural assumptions. This facilitates the generation of probabilistic predictions combining information from perturbed physics and multi-model ensemble simulations. The methodology makes extensive use of emulation and scaling techniques trained on climate model results. These are used to sample the equilibrium response to doubled carbon dioxide at any required point in the parameter space of surface and atmospheric processes, to sample time-dependent changes by combining this information with ensembles sampling uncertainties in the transient response of a wider set of earth system processes

  1. Risk prediction of Critical Infrastructures against extreme natural hazards: local and regional scale analysis

    NASA Astrophysics Data System (ADS)

    Rosato, Vittorio; Hounjet, Micheline; Burzel, Andreas; Di Pietro, Antonio; Tofani, Alberto; Pollino, Maurizio; Giovinazzi, Sonia

    2016-04-01

    Natural hazard events can induce severe impacts on the built environment; they can hit wide and densely populated areas, where there is a large number of (inter)dependent technological systems whose damages could cause the failure or malfunctioning of further different services, spreading the impacts on wider geographical areas. The EU project CIPRNet (Critical Infrastructures Preparedness and Resilience Research Network) is realizing an unprecedented Decision Support System (DSS) which enables to operationally perform risk prediction on Critical Infrastructures (CI) by predicting the occurrence of natural events (from long term weather to short nowcast predictions, correlating intrinsic vulnerabilities of CI elements with the different events' manifestation strengths, and analysing the resulting Damage Scenario. The Damage Scenario is then transformed into an Impact Scenario, where punctual CI element damages are transformed into micro (local area) or meso (regional) scale Services Outages. At the smaller scale, the DSS simulates detailed city models (where CI dependencies are explicitly accounted for) that are of important input for crisis management organizations whereas, at the regional scale by using approximate System-of-Systems model describing systemic interactions, the focus is on raising awareness. The DSS has allowed to develop a novel simulation framework for predicting earthquakes shake maps originating from a given seismic event, considering the shock wave propagation in inhomogeneous media and the subsequent produced damages by estimating building vulnerabilities on the basis of a phenomenological model [1, 2]. Moreover, in presence of areas containing river basins, when abundant precipitations are expected, the DSS solves the hydrodynamic 1D/2D models of the river basins for predicting the flux runoff and the corresponding flood dynamics. This calculation allows the estimation of the Damage Scenario and triggers the evaluation of the Impact Scenario

  2. Early skin toxicity predicts better outcomes, and early tumor shrinkage predicts better response after cetuximab treatment in advanced colorectal cancer.

    PubMed

    Kogawa, T; Doi, A; Shimokawa, M; Fouad, T M; Osuga, T; Tamura, F; Mizushima, T; Kimura, T; Abe, S; Ihara, H; Kukitsu, T; Sumiyoshi, T; Yoshizaki, N; Hirayama, M; Sasaki, T; Kawarada, Y; Kitashiro, S; Okushiba, S; Kondo, H; Tsuji, Y

    2015-03-01

    Cetuximab-containing treatments for metastatic colorectal cancer have been shown to have higher overall response rates and longer progression-free and overall survival than other systemic therapies. Cetuximab-related manifestations, including severe skin toxicity and early tumor shrinkage, have been shown to be predictors of response to cetuximab. We hypothesized that early skin toxicity is a predictor of response and better outcomes in patients with advanced colorectal carcinoma. We retrospectively evaluated 62 patients with colorectal adenocarcinoma who had unresectable tumors and were treated with cetuximab in our institution. Skin toxicity grade was evaluated on each treatment day. Tumor size was evaluated using computed tomography prior to treatment and 4-8 weeks after the start of treatment with cetuximab.Patients with early tumor shrinkage after starting treatment with cetuximab had a significantly higher overall response rate (P = 0.0001). Patients with early skin toxicity showed significantly longer overall survival (P = 0.0305), and patients with higher skin toxicity grades had longer progression-free survival (P = 0.0168).We have shown that early tumor shrinkage, early onset of skin toxicity, and high skin toxicity grade are predictors of treatment efficacy and/or outcome in patients with advanced colorectal carcinoma treated with cetuximab.

  3. Scale-dependent regional climate predictability over North America inferred from CMIP3 and CMIP5 ensemble simulations

    NASA Astrophysics Data System (ADS)

    Zhang, Fuqing; Li, Wei; Mann, Michael E.

    2016-08-01

    Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty (noise) in surface temperature predictions (represented by the spread among an ensemble of global climate model simulations) generally exceeds the ensemble mean (signal) at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness.

  4. Predicting regional abundance of rare grassland birds with a hierarchical spatial count model

    USGS Publications Warehouse

    Thogmartin, W.E.; Knutson, M.G.; Sauer, J.R.

    2006-01-01

    Grassland birds are among the most imperiled groups of birds in North America. Unfortunately, little is known about the location of regional concentrations of these birds, thus regional or statewide conservation efforts may be inappropriately applied, reducing their effectiveness. We identified environmental covariates associated with the abundance of five grassland birds in the upper midwestern United States (Bobolink [Dolichonyx oryzivorus], Grasshopper Sparrow [Ammodramus savannarum], Henslow's Sparrow [A. henslowii], Sedge Wren [Cistothorus platensis], and Upland Sandpiper [Bartramia longicauda]) with a hierarchical spatial count model fitted with Markov chain Monte Carlo methods. Markov chain Monte Carlo methods are well suited to this task because they are able to incorporate effects associated with autocorrelated counts and nuisance effects associated with years and observers, and the resulting models can be used to map predicted abundance at a landscape scale. Environmental covariates were derived from five suites of variables: landscape composition, landscape configuration, terrain heterogeneity and physiognomy, climate, and human influence. The final models largely conformed to our a priori expectations. Bobolinks and Henslow's Sparrows were strongly sensitive to grassland patch area. All of the species except Henslow's Sparrows exhibited substantial negative relations with forest composition, often at multiple spatial scales. Climate was found to be important for all species, and was the most important factor influencing abundance of Grasshopper Sparrows. After mapping predicted abundance, we found no obvious correspondence in the regional patterns of the five species. Thus, no clearly defined areas exist within the upper midwestern United States where management plans can be developed for a whole suite of grassland birds. Instead, a larger, region-wide initiative setting different goals for different species is recommended.

  5. Application of Genetic Algorithm to Predict Optimal Sowing Region and Timing for Kentucky Bluegrass in China.

    PubMed

    Pi, Erxu; Qu, Liqun; Tang, Xi; Peng, Tingting; Jiang, Bo; Guo, Jiangfeng; Lu, Hongfei; Du, Liqun

    2015-01-01

    Temperature is a predominant environmental factor affecting grass germination and distribution. Various thermal-germination models for prediction of grass seed germination have been reported, in which the relationship between temperature and germination were defined with kernel functions, such as quadratic or quintic function. However, their prediction accuracies warrant further improvements. The purpose of this study is to evaluate the relative prediction accuracies of genetic algorithm (GA) models, which are automatically parameterized with observed germination data. The seeds of five P. pratensis (Kentucky bluegrass, KB) cultivars were germinated under 36 day/night temperature regimes ranging from 5/5 to 40/40 °C with 5 °C increments. Results showed that optimal germination percentages of all five tested KB cultivars were observed under a fluctuating temperature regime of 20/25 °C. Meanwhile, the constant temperature regimes (e.g., 5/5, 10/10, 15/15 °C, etc.) suppressed the germination of all five cultivars. Furthermore, the back propagation artificial neural network (BP-ANN) algorithm was integrated to optimize temperature-germination response models from these observed germination data. It was found that integrations of GA-BP-ANN (back propagation aided genetic algorithm artificial neural network) significantly reduced the Root Mean Square Error (RMSE) values from 0.21~0.23 to 0.02~0.09. In an effort to provide a more reliable prediction of optimum sowing time for the tested KB cultivars in various regions in the country, the optimized GA-BP-ANN models were applied to map spatial and temporal germination percentages of blue grass cultivars in China. Our results demonstrate that the GA-BP-ANN model is a convenient and reliable option for constructing thermal-germination response models since it automates model parameterization and has excellent prediction accuracy. PMID:26154163

  6. Data-driven methods to improve baseflow prediction of a regional groundwater model

    NASA Astrophysics Data System (ADS)

    Xu, Tianfang; Valocchi, Albert J.

    2015-12-01

    Physically-based models of groundwater flow are powerful tools for water resources assessment under varying hydrologic, climate and human development conditions. One of the most important topics of investigation is how these conditions will affect the discharge of groundwater to rivers and streams (i.e. baseflow). Groundwater flow models are based upon discretized solution of mass balance equations, and contain important hydrogeological parameters that vary in space and cannot be measured. Common practice is to use least squares regression to estimate parameters and to infer prediction and associated uncertainty. Nevertheless, the unavoidable uncertainty associated with physically-based groundwater models often results in both aleatoric and epistemic model calibration errors, thus violating a key assumption for regression-based parameter estimation and uncertainty quantification. We present a complementary data-driven modeling and uncertainty quantification (DDM-UQ) framework to improve predictive accuracy of physically-based groundwater models and to provide more robust prediction intervals. First, we develop data-driven models (DDMs) based on statistical learning techniques to correct the bias of the calibrated groundwater model. Second, we characterize the aleatoric component of groundwater model residual using both parametric and non-parametric distribution estimation methods. We test the complementary data-driven framework on a real-world case study of the Republican River Basin, where a regional groundwater flow model was developed to assess the impact of groundwater pumping for irrigation. Compared to using only the flow model, DDM-UQ provides more accurate monthly baseflow predictions. In addition, DDM-UQ yields prediction intervals with coverage probability consistent with validation data. The DDM-UQ framework is computationally efficient and is expected to be applicable to many geoscience models for which model structural error is not negligible.

  7. Application of Genetic Algorithm to Predict Optimal Sowing Region and Timing for Kentucky Bluegrass in China

    PubMed Central

    Peng, Tingting; Jiang, Bo; Guo, Jiangfeng; Lu, Hongfei; Du, Liqun

    2015-01-01

    Temperature is a predominant environmental factor affecting grass germination and distribution. Various thermal-germination models for prediction of grass seed germination have been reported, in which the relationship between temperature and germination were defined with kernel functions, such as quadratic or quintic function. However, their prediction accuracies warrant further improvements. The purpose of this study is to evaluate the relative prediction accuracies of genetic algorithm (GA) models, which are automatically parameterized with observed germination data. The seeds of five P. pratensis (Kentucky bluegrass, KB) cultivars were germinated under 36 day/night temperature regimes ranging from 5/5 to 40/40°C with 5°C increments. Results showed that optimal germination percentages of all five tested KB cultivars were observed under a fluctuating temperature regime of 20/25°C. Meanwhile, the constant temperature regimes (e.g., 5/5, 10/10, 15/15°C, etc.) suppressed the germination of all five cultivars. Furthermore, the back propagation artificial neural network (BP-ANN) algorithm was integrated to optimize temperature-germination response models from these observed germination data. It was found that integrations of GA-BP-ANN (back propagation aided genetic algorithm artificial neural network) significantly reduced the Root Mean Square Error (RMSE) values from 0.21~0.23 to 0.02~0.09. In an effort to provide a more reliable prediction of optimum sowing time for the tested KB cultivars in various regions in the country, the optimized GA-BP-ANN models were applied to map spatial and temporal germination percentages of blue grass cultivars in China. Our results demonstrate that the GA-BP-ANN model is a convenient and reliable option for constructing thermal-germination response models since it automates model parameterization and has excellent prediction accuracy. PMID:26154163

  8. Prediction interval evaluation in modelling of soil texture for regional mapping: methodology and a case study

    NASA Astrophysics Data System (ADS)

    Ciampalini, Rossano; Martin, Manuel; Saby, Nicolas P. A.; Richer de Forges, Anne C.; Nehlig, Pierre; Martelet, Guillaume; Arrouays, Dominique

    2015-04-01

    Model uncertainty mapping represents a practical way to describe efficiency and limits of models prediction and can be calculated using different techniques. The object of this study is to determine and apply a procedure for the prediction interval (PI) evaluation for extended maps of soil granulometric fractions (i.e. clay, silt, sand) in the region "Centre" of France. Among the various methodologies for PI determination, a recent approach is the use of a non-parametric procedure evaluating the prediction interval. The PI is defined as a conventional bound of the predicted values (i.e. 95th percentile) and can be calculated as follows. Assuming a relationship between the inputs of the model and the resulting prediction error (Shrestha et al., 2006, Malone et al., 2011), the input variables-space is classified into different clusters having similar errors with a fuzzy c-means clustering technique. Then, a prediction interval (PI) is calculated for each cluster on the basis of the associated empirical distributions of the errors and considering the degree of membership belonging to each cluster. A relationship between the input variables and the computed prediction intervals is founded using a modelling procedure (calibration), then; the relationship is applied to estimate the prediction interval for the out-of-sample data (validation) (e.g. Solomatine et al., 2008, 2009, Malone et al., 2011). This approach requires the assumption of a relationships between the input variables and the errors, and, obviously the relevancy and accuracy of such approach depends on the validity of the assumption. These assumptions have been accepted in all the studies quoted above. In this work we adopted a similar procedure to the third approach. Our hypothesis is, if a correspondence is supposed and identified between confidence interval and predictors (i.e., 2.5-97.5% values, respectively), a model between predictors and PI may be used to extrapolate it to the whole map. This

  9. Predicting Advanced Placement Examination Success from FCAT Scores. Research Brief. Volume 0709

    ERIC Educational Resources Information Center

    Froman, Terry; Brown, Shelly; Tirado, Arleti

    2008-01-01

    Advanced Placement courses are offered at M-DCPS for students to acquire college credit or advanced college academic standing. A system has been developed in the past by the College Board to use the PSAT for 10th grade students to estimate their potential for AP Examination success. The same test has recently been applied in this district to 9th…

  10. Effects of lateral boundary condition resolution and update frequency on regional climate model predictions

    NASA Astrophysics Data System (ADS)

    Pankatz, Klaus; Kerkweg, Astrid

    2015-04-01

    The work presented is part of the joint project "DecReg" ("Regional decadal predictability") which is in turn part of the project "MiKlip" ("Decadal predictions"), an effort funded by the German Federal Ministry of Education and Research to improve decadal predictions on a global and regional scale. In MiKlip, one big question is if regional climate modeling shows "added value", i.e. to evaluate, if regional climate models (RCM) produce better results than the driving models. However, the scope of this study is to look more closely at the setup specific details of regional climate modeling. As regional models only simulate a small domain, they have to inherit information about the state of the atmosphere at their lateral boundaries from external data sets. There are many unresolved questions concerning the setup of lateral boundary conditions (LBC). External data sets come from global models or from global reanalysis data-sets. A temporal resolution of six hours is common for this kind of data. This is mainly due to the fact, that storage space is a limiting factor, especially for climate simulations. However, theoretically, the coupling frequency could be as high as the time step of the driving model. Meanwhile, it is unclear if a more frequent update of the LBCs has a significant effect on the climate in the domain of the RCM. The first study examines how the RCM reacts to a higher update frequency. The study is based on a 30 year time slice experiment for three update frequencies of the LBC, namely six hours, one hour and six minutes. The evaluation of means, standard deviations and statistics of the climate in the regional domain shows only small deviations, some statistically significant though, of 2m temperature, sea level pressure and precipitation. The second part of the first study assesses parameters linked to cyclone activity, which is affected by the LBC update frequency. Differences in track density and strength are found when comparing the simulations

  11. Predicted reliability of aerospace electronics: Application of two advanced probabilistic concepts

    NASA Astrophysics Data System (ADS)

    Suhir, E.

    Two advanced probabilistic design-for-reliability (PDfR) concepts are addressed and discussed in application to the prediction, quantification and assurance of the aerospace electronics reliability: 1) Boltzmann-Arrhenius-Zhurkov (BAZ) model, which is an extension of the currently widely used Arrhenius model and, in combination with the exponential law of reliability, enables one to obtain a simple, easy-to-use and physically meaningful formula for the evaluation of the probability of failure (PoF) of a material or a device after the given time in operation at the given temperature and under the given stress (not necessarily mechanical), and 2) Extreme Value Distribution (EVD) technique that can be used to assess the number of repetitive loadings that result in the material/device degradation and eventually lead to its failure by closing, in a step-wise fashion, the gap between the bearing capacity (stress-free activation energy) of the material or the device and the demand (loading). It is shown that the material degradation (aging, damage accumulation, flaw propagation, etc.) can be viewed, when BAZ model is considered, as a Markovian process, and that the BAZ model can be obtained as the ultimate steady-state solution to the well-known Fokker-Planck equation in the theory of Markovian processes. It is shown also that the BAZ model addresses the worst, but a reasonably conservative, situation. It is suggested therefore that the transient period preceding the condition addressed by the steady-state BAZ model need not be accounted for in engineering evaluations. However, when there is an interest in understanding the transient degradation process, the obtained solution to the Fokker-Planck equation can be used for this purpose. As to the EVD concept, it attributes the degradation process to the accumulation of damages caused by a train of repetitive high-level loadings, while loadings of levels that are considerably lower than their extreme values do not contribute

  12. Preparatory delay activity in the monkey parietal reach region predicts reach reaction times.

    PubMed

    Snyder, Lawrence H; Dickinson, Anthony R; Calton, Jeffrey L

    2006-10-01

    To acquire something that we see, visual spatial information must ultimately result in the activation of the appropriate set of muscles. This sensory to motor transformation requires an interaction between information coding target location and information coding which effector will be moved. Activity in the monkey parietal reach region (PRR) reflects both spatial information and the effector (arm or eye) that will be used in an upcoming reach or saccade task. To further elucidate the functional role of PRR in visually guided movement tasks and to obtain evidence that PRR signals are used to drive arm movements, we tested the hypothesis that increased neuronal activity during a preparatory delay period would lead to faster reach reaction times but would not be correlated with saccade reaction times. This proved to be the case only when the type of movement and not the spatial goal of that movement was known in advance. The correlation was strongest in cells that showed significantly more activity on arm reach compared with saccade trials. No significant correlations were found during delay periods in which spatial information was provided in advance. These data support the idea that PRR constitutes a bottleneck in the processing of spatial information for an upcoming arm reach. The lack of a correlation with saccadic reaction time also supports the idea that PRR processing is effector specific, that is, it is involved in specifying targets for arm movements but not targets for eye movements.

  13. Artificial neural network analysis for reliability prediction of regional runoff utilization.

    PubMed

    Lee, S C; Lin, H T; Yang, T Y

    2010-02-01

    Many factors in the reliability analysis of planning the regional rainwater utilization tank capacity need to be considered. Based on the historical daily rainfall data, the following four analyzing procedures will be conducted: the regional daily rainfall frequency, the amount of runoff, the water continuity, and the reliability. Thereafter, the suggested designed storage capacity can be obtained according to the conditions with the demand and supply reliability. By using the output data, two different types of artificial neural network models are used to build up small area rainfall-runoff supply systems for the simulation of reliability and the prediction model. They are also used for the testing of stability and learning speed assessment. Based on the result of this research, the radial basis function neural network (RBFNN) model, using the Gaussian function that has a similar trend as the nature as basic function, has better stability than using the back-propagation neural network (BPNN) model. Despite the fact that RBFNN was more reliable than BPNN, it still made a conservative estimate for the actual monitoring data. The error rate of RBFNN was still higher than the correction of BPNN 4-3-1-1. This should have significant benefit in the future application of the instantaneous prediction or the development of related intelligent instantaneous control equipment.

  14. Dynamical Downscaling NCEP Global Climate Forecast System (CFS) Seasonal Predictions Using Regional Atmospheric Modeling System (RAMS)

    NASA Astrophysics Data System (ADS)

    Lu, L.; Zheng, Y.; Pielke, R. A.

    2009-12-01

    As part of the NOAA CPPA-sponsored MRED project, the state-of-the-art Regional Atmospheric Modeling System (RAMS) version 6.0 is used to dynamically and progressively downscale NCEP global Climate Forecast System (CFS, at 100s-km grid increment) seasonal predictions to a regional domain that covers the conterminous United States at 30-km grid increment. The first set of RCM prediction experiment focuses on the winter seasons, during which the precipitation is largely dependent on synoptic-scale mid-latitude storms and orographic dominant mesoscale processes. Our first suite of numerical experiment includes one ensemble member for each year from 1982 through 2008, with all the simulations starting on December 1 and ending on April 30. Driven by the same atmospheric and SST forcings, RAMS will be compared with other RCMs, and evaluated against observations and reanalysis (NARR) to see if the simulations capture the climatology and interannual variability of temperature and precipitation distributions. The overall strengths and weaknesses of the modeling systems will be identified, as well as the consistent model biases. In addition, we will analyze the changes in kinetic energy spectra before and after the spectral nudging algorithm is implemented. The results show that with the spectral nudging scheme, RAMS can better preserve large-scale kinetic energy than standard boundary forcing method, and allow more large-scale energy to cascade to smaller scales.

  15. Heavy metal contents, distribution, and prediction in a regional soil-wheat system.

    PubMed

    Ran, Jing; Wang, Dejian; Wang, Can; Zhang, Gang; Zhang, Hailin

    2016-02-15

    The entry of heavy metals into the food chain is of concern for potential health risks. To investigate the spatial relationships of heavy metals in a regional soil-wheat system, 99 pairs of surface soil (0-15 cm) and wheat grain samples were collected from Changshu, China, a typical county in the Yangtze Delta region. Both soil and wheat grain samples were analyzed for total Cd, Cu, Ni, Pb, and Zn. DTPA-extractable metals and major physico-chemical properties were also determined for soil samples. Moderate accumulation of heavy metals was found in soils and wheat grains, especially Cd. However, the levels were within the target hazard quotients (THQ) safe values with respect to non-carcinogenic risks, but more attention should be paid to Cd. Spatially, Cd, Cu, Ni, and Zn in wheat grains and soils had similar geographical patterns, whereas Pb showed opposite trends. Cross-correlograms further quantitatively confirmed the spatial relationships of heavy metals in wheat grains and soils. In addition, heavy metals in wheat grains were significantly spatially correlated with most soil physio-chemical properties. Particularly, a set of regression models for Cd in wheat grains were established with a maximum predictive success of 65%. These models can be used to predict Cd in wheat grains, and thus allows farmers to decrease the threat by certain framing practices such as ameliorating soil pH or growing a less metal-accumulating cultivar. PMID:26657387

  16. Prediction of transmembrane regions of beta-barrel proteins using ANN- and SVM-based methods.

    PubMed

    Natt, Navjyot K; Kaur, Harpreet; Raghava, G P S

    2004-07-01

    This article describes a method developed for predicting transmembrane beta-barrel regions in membrane proteins using machine learning techniques: artificial neural network (ANN) and support vector machine (SVM). The ANN used in this study is a feed-forward neural network with a standard back-propagation training algorithm. The accuracy of the ANN-based method improved significantly, from 70.4% to 80.5%, when evolutionary information was added to a single sequence as a multiple sequence alignment obtained from PSI-BLAST. We have also developed an SVM-based method using a primary sequence as input and achieved an accuracy of 77.4%. The SVM model was modified by adding 36 physicochemical parameters to the amino acid sequence information. Finally, ANN- and SVM-based methods were combined to utilize the full potential of both techniques. The accuracy and Matthews correlation coefficient (MCC) value of SVM, ANN, and combined method are 78.5%, 80.5%, and 81.8%, and 0.55, 0.63, and 0.64, respectively. These methods were trained and tested on a nonredundant data set of 16 proteins, and performance was evaluated using "leave one out cross-validation" (LOOCV). Based on this study, we have developed a Web server, TBBPred, for predicting transmembrane beta-barrel regions in proteins (available at http://www.imtech.res.in/raghava/tbbpred).

  17. From field to region yield predictions in response to pedo-climatic variations in Eastern Canada

    NASA Astrophysics Data System (ADS)

    JÉGO, G.; Pattey, E.; Liu, J.

    2013-12-01

    The increase in global population coupled with new pressures to produce energy and bioproducts from agricultural land requires an increase in crop productivity. However, the influence of climate and soil variations on crop production and environmental performance is not fully understood and accounted for to define more sustainable and economical management strategies. Regional crop modeling can be a great tool for understanding the impact of climate variations on crop production, for planning grain handling and for assessing the impact of agriculture on the environment, but it is often limited by the availability of input data. The STICS ("Simulateur mulTIdisciplinaire pour les Cultures Standard") crop model, developed by INRA (France) is a functional crop model which has a built-in module to optimize several input parameters by minimizing the difference between calculated and measured output variables, such as Leaf Area Index (LAI). STICS crop model was adapted to the short growing season of the Mixedwood Plains Ecozone using field experiments results, to predict biomass and yield of soybean, spring wheat and corn. To minimize the numbers of inference required for regional applications, 'generic' cultivars rather than specific ones have been calibrated in STICS. After the calibration of several model parameters, the root mean square error (RMSE) of yield and biomass predictions ranged from 10% to 30% for the three crops. A bit more scattering was obtained for LAI (20%prediction to climate variations. Using RS data to re-initialize input parameters that are not readily available (e.g. seeding date) is considered an effective way

  18. Can occupancy patterns be used to predict distributions in widely separated geographic regions?

    PubMed

    Menéndez, Rosa; Thomas, Chris D

    2006-09-01

    Occupancy models, that describe the presence and absence patterns of a species in a given area, are increasingly being used to predict the occurrence of the species in unsurveyed sites, as an aid to conservation planning. In this paper, we consider whether conclusions about local distributions derived from one landscape can be extrapolated to others. We found that habitat patchiness influenced the distribution and abundance of the host-specific moth Wheeleria spilodactylus in a similar way in two landscapes widely separated geographically. In both geographic regions, the spatial location (positive effect of connectivity), and quantity of resource (positive effect of host plant density) increased the likelihood that the moth would be present, consistent with the expectations of metapopulation dynamics. Though some biological attributes of the species appeared to be slightly different, including population density and the timing of the life cycle (phenology), occupancy patterns in one landscape accurately predict occupancy in the other landscape. Our results suggest that it maybe possible to make predictions from one landscape to another, even when the landscapes are widely separated.

  19. Absence of Q waves after thrombolysis predicts more rapid improvement of regional left ventricular dysfunction.

    PubMed

    Isselbacher, E M; Siu, S C; Weyman, A E; Picard, M H

    1996-04-01

    Although the natural history of regional left ventricular (LV) dysfunction after Q-wave and non-Q-wave myocardial infarction (MI) was well defined in the prethrombolytic era, the functional and structural implications of the absence of Q waves after thrombolysis are less clear. Echocardiography was performed within 48 hours of admission (entry) in 86 patients treated with thrombolysis for their first MI. The extent of abnormal wall motion (AWM; square centimeters) and LV endocardial surface area index (ESA; square centimeters per square meters) were quantified by using a previously validated echocardiographic endocardial surface-mapping technique. Electrocardiography (ECG) performed at 48 hours after thrombolysis was used to classify patients into groups with (Q; n=70) and without (non-Q; n=16) Q waves. All patients in the Q group had regional LV dysfunction on initial echocardiogram compared with 69 percent of those in the non-Q group (p<0.001). When the patients in the non-Q group without AWM were excluded from analysis, there was no significant difference in the extent of AWM between the Q and non-Q groups. Among those patients with AWM on entry, follow-up echocardiography at 6 to 12 weeks demonstrated a significant reduction in extent of AWM for both the Q and non-Q groups. However, the fractional change in AWM was significantly greater in the non-Q than in the Q group (-0.74 +/- 0.28 vs -0.29 +/- 0.44; p<0.02), with a trend toward less AWM at follow-up in the non-Q than in the Q group. The mean ESAi was not significantly different between the two groups at entry or at follow-up. In conclusion, failure to develop Q waves after thrombolysis predicts a lower likelihood of developing regional LV dysfunction and, when such dysfunction is present, predicts a greater degree of recovery. PMID:8721634

  20. Spatial prediction of soil texture in region Centre (France) from summary data

    NASA Astrophysics Data System (ADS)

    Dobarco, Mercedes Roman; Saby, Nicolas; Paroissien, Jean-Baptiste; Orton, Tom G.

    2015-04-01

    Soil texture is a key controlling factor of important soil functions like water and nutrient holding capacity, retention of pollutants, drainage, soil biodiversity, and C cycling. High resolution soil texture maps enhance our understanding of the spatial distribution of soil properties and provide valuable information for decision making and crop management, environmental protection, and hydrological planning. We predicted the soil texture of agricultural topsoils in the Region Centre (France) combining regression and area-to-point kriging. Soil texture data was collected from the French soil-test database (BDAT), which is populated with soil analysis performed by farmers' demand. To protect the anonymity of the farms the data was treated by commune. In a first step, summary statistics of environmental covariates by commune were used to develop prediction models with Cubist, boosted regression trees, and random forests. In a second step the residuals of each individual observation were summarized by commune and kriged following the method developed by Orton et al. (2012). This approach allowed to include non-linear relationships among covariates and soil texture while accounting for the uncertainty on areal means in the area-to-point kriging step. Independent validation of the models was done using data from the systematic soil monitoring network of French soils. Future work will compare the performance of these models with a non-stationary variance geostatistical model using the most important covariates and summary statistics of texture data. The results will inform on whether the later and statistically more-challenging approach improves significantly texture predictions or whether the more simple area-to-point regression kriging can offer satisfactory results. The application of area-to-point regression kriging at national level using BDAT data has the potential to improve soil texture predictions for agricultural topsoils, especially when combined with

  1. Accounting for dependencies in regionalized signatures for predictions in ungauged catchments

    NASA Astrophysics Data System (ADS)

    Almeida, S.; Le Vine, N.; McIntyre, N.; Wagener, T.; Buytaert, W.

    2015-06-01

    A recurrent problem in hydrology is the absence of streamflow data to calibrate rainfall-runoff models. A commonly used approach in such circumstances conditions model parameters on regionalized response signatures. While several different signatures are often available to be included in this process, an outstanding challenge is the selection of signatures that provide useful and complementary information. Different signatures do not necessarily provide independent information, and this has led to signatures being omitted or included on a subjective basis. This paper presents a method that accounts for the inter-signature error correlation structure so that regional information is neither neglected nor double-counted when multiple signatures are included. Using 84 catchments from the MOPEX database, observed signatures are regressed against physical and climatic catchment attributes. The derived relationships are then utilized to assess the joint probability distribution of the signature regionalization errors that is subsequently used in a Bayesian procedure to condition a rainfall-runoff model. The results show that the consideration of the inter-signature error structure may improve predictions when the error correlations are strong. However, other uncertainties such as model structure and observational error may outweigh the importance of these correlations. Further, these other uncertainties cause some signatures to appear repeatedly to be disinformative.

  2. Accounting for dependencies in regionalized signatures for predictions in ungauged catchments

    NASA Astrophysics Data System (ADS)

    Almeida, Susana; Le Vine, Nataliya; McIntyre, Neil; Wagener, Thorsten; Buytaert, Wouter

    2016-02-01

    A recurrent problem in hydrology is the absence of streamflow data to calibrate rainfall-runoff models. A commonly used approach in such circumstances conditions model parameters on regionalized response signatures. While several different signatures are often available to be included in this process, an outstanding challenge is the selection of signatures that provide useful and complementary information. Different signatures do not necessarily provide independent information and this has led to signatures being omitted or included on a subjective basis. This paper presents a method that accounts for the inter-signature error correlation structure so that regional information is neither neglected nor double-counted when multiple signatures are included. Using 84 catchments from the MOPEX database, observed signatures are regressed against physical and climatic catchment attributes. The derived relationships are then utilized to assess the joint probability distribution of the signature regionalization errors that is subsequently used in a Bayesian procedure to condition a rainfall-runoff model. The results show that the consideration of the inter-signature error structure may improve predictions when the error correlations are strong. However, other uncertainties such as model structure and observational error may outweigh the importance of these correlations. Further, these other uncertainties cause some signatures to appear repeatedly to be misinformative.

  3. Source regional contributions to PM2.5 in a megacity in China using an advanced source regional apportionment method.

    PubMed

    Tian, Ying-Ze; Chen, Gang; Wang, Hai-Ting; Huang-Fu, Yan-Qi; Shi, Guo-Liang; Han, Bo; Feng, Yin-Chang

    2016-03-01

    To quantify contributions of individual source categories from diverse regions to PM2.5, PM2.5 samples were collected in a megacity in China and analyzed through a newly developed source regional apportionment (SRA) method. Levels, compositions and seasonal variations of speciated PM2.5 dataset were investigated. Sources were determined by Multilinear Engine 2 (ME2) model, and results showed that the PM2.5 in Tianjin was mainly influenced by secondary sulphate & secondary organic carbon SOC (percent contribution of 26.2%), coal combustion (24.6%), crustal dust & cement dust (20.3%), secondary nitrate (14.9%) and traffic emissions (14.0%). The SRA method showed that northwest region R2 was the highest regional contributor to secondary sources, with percent contributions to PM2.5 being 9.7% for secondary sulphate & SOC and 6.0% for secondary nitrates; the highest coal combustion was from local region R1 (6.2%) and northwest R2 (8.0%); the maximum contributing region to crustal & cement dust was southeast region R4 (5.0%); and contributions of traffic emissions were relatively spatial homogeneous. The seasonal variation of regional source contributions was observed: in spring, the crustal and cement dust contributed a higher percentage and the R4 was an important contributor; the secondary process attributed an increase fraction in summer; the mixed coal combustion from southwest R5 enhanced in autumn.

  4. Source regional contributions to PM2.5 in a megacity in China using an advanced source regional apportionment method.

    PubMed

    Tian, Ying-Ze; Chen, Gang; Wang, Hai-Ting; Huang-Fu, Yan-Qi; Shi, Guo-Liang; Han, Bo; Feng, Yin-Chang

    2016-03-01

    To quantify contributions of individual source categories from diverse regions to PM2.5, PM2.5 samples were collected in a megacity in China and analyzed through a newly developed source regional apportionment (SRA) method. Levels, compositions and seasonal variations of speciated PM2.5 dataset were investigated. Sources were determined by Multilinear Engine 2 (ME2) model, and results showed that the PM2.5 in Tianjin was mainly influenced by secondary sulphate & secondary organic carbon SOC (percent contribution of 26.2%), coal combustion (24.6%), crustal dust & cement dust (20.3%), secondary nitrate (14.9%) and traffic emissions (14.0%). The SRA method showed that northwest region R2 was the highest regional contributor to secondary sources, with percent contributions to PM2.5 being 9.7% for secondary sulphate & SOC and 6.0% for secondary nitrates; the highest coal combustion was from local region R1 (6.2%) and northwest R2 (8.0%); the maximum contributing region to crustal & cement dust was southeast region R4 (5.0%); and contributions of traffic emissions were relatively spatial homogeneous. The seasonal variation of regional source contributions was observed: in spring, the crustal and cement dust contributed a higher percentage and the R4 was an important contributor; the secondary process attributed an increase fraction in summer; the mixed coal combustion from southwest R5 enhanced in autumn. PMID:26766363

  5. 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.

  6. A Novel Risk Stratification to Predict Local-Regional Failures in Urothelial Carcinoma of the Bladder After Radical Cystectomy

    SciTech Connect

    Baumann, Brian C.; Guzzo, Thomas J.; He Jiwei; Keefe, Stephen M.; Tucker, Kai; Bekelman, Justin E.; Hwang, Wei-Ting; Vaughn, David J.; Malkowicz, S. Bruce; Christodouleas, John P.

    2013-01-01

    Purpose: Local-regional failures (LF) following radical cystectomy (RC) plus pelvic lymph node dissection (PLND) with or without chemotherapy for invasive urothelial bladder carcinoma are more common than previously reported. Adjuvant radiation therapy (RT) could reduce LF but currently has no defined role because of previously reported morbidity. Modern techniques with improved normal tissue sparing have rekindled interest in RT. We assessed the risk of LF and determined those factors that predict recurrence to facilitate patient selection for future adjuvant RT trials. Methods and Materials: From 1990-2008, 442 patients with urothelial bladder carcinoma at University of Pennsylvania were prospectively followed after RC plus PLND with or without chemotherapy with routine pelvic computed tomography (CT) or magnetic resonance imaging (MRI). One hundred thirty (29%) patients received chemotherapy. LF was any pelvic failure detected before or within 3 months of distant failure. Competing risk analyses identified factors predicting increased LF risk. Results: On univariate analysis, pathologic stage {>=}pT3, <10 nodes removed, positive margins, positive nodes, hydronephrosis, lymphovascular invasion, and mixed histology significantly predicted LF; node density was marginally predictive, but use of chemotherapy, number of positive nodes, type of surgical diversion, age, gender, race, smoking history, and body mass index were not. On multivariate analysis, only stage {>=}pT3 and <10 nodes removed were significant independent LF predictors with hazard ratios of 3.17 and 2.37, respectively (P<.01). Analysis identified 3 patient subgroups with significantly different LF risks: low-risk ({<=}pT2), intermediate-risk ({>=}pT3 and {>=}10 nodes removed), and high-risk ({>=}pT3 and <10 nodes) with 5-year LF rates of 8%, 23%, and 42%, respectively (P<.01). Conclusions: This series using routine CT and MRI surveillance to detect LF confirms that such failures are relatively common

  7. Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

    NASA Technical Reports Server (NTRS)

    Wilson, Scott D.; Reid, Terry; Schifer, Nicholas; Briggs, Maxwell

    2011-01-01

    Past methods of predicting net heat input needed to be validated. Validation effort pursued with several paths including improving model inputs, using test hardware to provide validation data, and validating high fidelity models. Validation test hardware provided direct measurement of net heat input for comparison to predicted values. Predicted value of net heat input was 1.7 percent less than measured value and initial calculations of measurement uncertainty were 2.1 percent (under review). Lessons learned during validation effort were incorporated into convertor modeling approach which improved predictions of convertor efficiency.

  8. African Regional Seminar for Advanced Training In Systematic Curriculum Development and Evaluation. (Achimota, Ghana, 14 July--15 August 1975). Report.

    ERIC Educational Resources Information Center

    Swedish International Development Authority (SIDA).

    This report summarizes the African Regional Seminar for Advanced Training in Systematic Curriculum Development and Evaluation that was held at Achimota, Ghana, July 14-August 15 1975. Attending the seminar were 67 participants from 12 African countries, including Cameroon, Gambia, Ghana, Kenya, Liberia, Malawi, Nigeria, Sierra Leone, Swaziland,…

  9. 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.

  10. 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.

  11. The effects of regional insolation differences upon advanced solar thermal electric power plant performance and energy costs

    NASA Technical Reports Server (NTRS)

    Latta, A. F.; Bowyer, J. M.; Fujita, T.; Richter, P. H.

    1980-01-01

    The performance and cost of four 10 MWe advanced solar thermal electric power plants sited in various regions of the continental United States was studied. Each region has different insolation characteristics which result in varying collector field areas, plant performance, capital costs and energy costs. The regional variation in solar plant performance was assessed in relation to the expected rise in the future cost of residential and commercial electricity supplied by conventional utility power systems in the same regions. A discussion of the regional insolation data base is presented along with a description of the solar systems performance and costs. A range for the forecast cost of conventional electricity by region and nationally over the next several decades is given.

  12. Analysis and Prediction of the Critical Regions of Antimicrobial Peptides Based on Conditional Random Fields

    PubMed Central

    Chang, Kuan Y.; Lin, Tung-pei; Shih, Ling-Yi; Wang, Chien-Kuo

    2015-01-01

    Antimicrobial peptides (AMPs) are potent drug candidates against microbes such as bacteria, fungi, parasites, and viruses. The size of AMPs ranges from less than ten to hundreds of amino acids. Often only a few amino acids or the critical regions of antimicrobial proteins matter the functionality. Accurately predicting the AMP critical regions could benefit the experimental designs. However, no extensive analyses have been done specifically on the AMP critical regions and computational modeling on them is either non-existent or settled to other problems. With a focus on the AMP critical regions, we thus develop a computational model AMPcore by introducing a state-of-the-art machine learning method, conditional random fields. We generate a comprehensive dataset of 798 AMPs cores and a low similarity dataset of 510 representative AMP cores. AMPcore could reach a maximal accuracy of 90% and 0.79 Matthew’s correlation coefficient on the comprehensive dataset and a maximal accuracy of 83% and 0.66 MCC on the low similarity dataset. Our analyses of AMP cores follow what we know about AMPs: High in glycine and lysine, but low in aspartic acid, glutamic acid, and methionine; the abundance of α-helical structures; the dominance of positive net charges; the peculiarity of amphipathicity. Two amphipathic sequence motifs within the AMP cores, an amphipathic α-helix and an amphipathic π-helix, are revealed. In addition, a short sequence motif at the N-terminal boundary of AMP cores is reported for the first time: arginine at the P(-1) coupling with glycine at the P1 of AMP cores occurs the most, which might link to microbial cell adhesion. PMID:25803302

  13. Midlife measurements of white matter microstructure predict subsequent regional white matter atrophy in healthy adults

    PubMed Central

    Ly, Martina; Canu, Elisa; Xu, Guofan; Oh, Jennifer; McLaren, Donald G; Dowling, N. Maritza; Alexander, Andrew L; Sager, Mark A; Johnson, Sterling C; Bendlin, Barbara B

    2013-01-01

    Objectives While age-related brain changes are becoming better understood, midlife patterns of change are still in need of characterization, and longitudinal studies are lacking. The aim of this study was to determine if baseline fractional anisotropy (FA), obtained from diffusion tensor imaging (DTI) predicts volume change over a four-year interval. Experimental design Forty-four cognitively healthy middle-age adults underwent baseline DTI and longitudinal T1-weighted magnetic resonance imaging. Tensor Based Morphometry methods were used to evaluate volume change over time. FA values were extracted from regions of interest that included the cingulum, entorhinal white matter, and the genu and splenium of the corpus callosum. Baseline FA was used as a predictor variable, while gray and white matter atrophy rates as indexed by Tensor Based Morphometry were the dependent variables. Principal observations Over a four-year period, participants showed significant contraction of white matter, especially in frontal, temporal, and cerebellar regions (p<0.05, corrected for multiple comparisons). Baseline FA in entorhinal white matter, genu, and splenium, was associated with longitudinal rates of atrophy in regions that included the superior longitudinal fasciculus, anterior corona radiata, temporal stem, and white matter of the inferior temporal gyrus (p<0.001, uncorrected for multiple comparisons). Conclusions Brain change with aging is characterized by extensive shrinkage of white matter. Baseline white matter microstructure as indexed by DTI was associated with some of the observed regional volume loss. The findings suggest that both white matter volume loss and microstructural alterations should be considered more prominently in models of aging and neurodegenerative diseases. PMID:23861348

  14. A radar-based hydrological model for flash flood prediction in the dry regions of Israel

    NASA Astrophysics Data System (ADS)

    Ronen, Alon; Peleg, Nadav; Morin, Efrat

    2014-05-01

    Flash floods are floods which follow shortly after rainfall events, and are among the most destructive natural disasters that strike people and infrastructures in humid and arid regions alike. Using a hydrological model for the prediction of flash floods in gauged and ungauged basins can help mitigate the risk and damage they cause. The sparsity of rain gauges in arid regions requires the use of radar measurements in order to get reliable quantitative precipitation estimations (QPE). While many hydrological models use radar data, only a handful do so in dry climate. This research presents a robust radar-based hydro-meteorological model built specifically for dry climate. Using this model we examine the governing factors of flash floods in the arid and semi-arid regions of Israel in particular and in dry regions in general. The hydrological model built is a semi-distributed, physically-based model, which represents the main hydrological processes in the area, namely infiltration, flow routing and transmission losses. Three infiltration functions were examined - Initial & Constant, SCS-CN and Green&Ampt. The parameters for each function were found by calibration based on 53 flood events in three catchments, and validation was performed using 55 flood events in six catchments. QPE were obtained from a C-band weather radar and adjusted using a weighted multiple regression method based on a rain gauge network. Antecedent moisture conditions were calculated using a daily recharge assessment model (DREAM). We found that the SCS-CN infiltration function performed better than the other two, with reasonable agreement between calculated and measured peak discharge. Effects of storm characteristics were studied using synthetic storms from a high resolution weather generator (HiReS-WG), and showed a strong correlation between storm speed, storm direction and rain depth over desert soils to flood volume and peak discharge.

  15. EVALUATING THE PERFORMANCE OF REGIONAL-SCALE PHOTOCHEMICAL MODELING SYSTEMS: PART II--OZONE PREDICTIONS. (R825260)

    EPA Science Inventory

    In this paper, the concept of scale analysis is applied to evaluate ozone predictions from two regional-scale air quality models. To this end, seasonal time series of observations and predictions from the RAMS3b/UAM-V and MM5/MAQSIP (SMRAQ) modeling systems for ozone were spectra...

  16. Prediction of plasma-induced damage distribution during silicon nitride etching using advanced three-dimensional voxel model

    SciTech Connect

    Kuboi, Nobuyuki Tatsumi, Tetsuya; Kinoshita, Takashi; Shigetoshi, Takushi; Fukasawa, Masanaga; Komachi, Jun; Ansai, Hisahiro

    2015-11-15

    The authors modeled SiN film etching with hydrofluorocarbon (CH{sub x}F{sub y}/Ar/O{sub 2}) plasma considering physical (ion bombardment) and chemical reactions in detail, including the reactivity of radicals (C, F, O, N, and H), the area ratio of Si dangling bonds, the outflux of N and H, the dependence of the H/N ratio on the polymer layer, and generation of by-products (HCN, C{sub 2}N{sub 2}, NH, HF, OH, and CH, in addition to CO, CF{sub 2}, SiF{sub 2}, and SiF{sub 4}) as ion assistance process parameters for the first time. The model was consistent with the measured C-F polymer layer thickness, etch rate, and selectivity dependence on process variation for SiN, SiO{sub 2}, and Si film etching. To analyze the three-dimensional (3D) damage distribution affected by the etched profile, the authors developed an advanced 3D voxel model that can predict the time-evolution of the etched profile and damage distribution. The model includes some new concepts for gas transportation in the pattern using a fluid model and the property of voxels called “smart voxels,” which contain details of the history of the etching situation. Using this 3D model, the authors demonstrated metal–oxide–semiconductor field-effect transistor SiN side-wall etching that consisted of the main-etch step with CF{sub 4}/Ar/O{sub 2} plasma and an over-etch step with CH{sub 3}F/Ar/O{sub 2} plasma under the assumption of a realistic process and pattern size. A large amount of Si damage induced by irradiated hydrogen occurred in the source/drain region, a Si recess depth of 5 nm was generated, and the dislocated Si was distributed in a 10 nm deeper region than the Si recess, which was consistent with experimental data for a capacitively coupled plasma. An especially large amount of Si damage was also found at the bottom edge region of the metal–oxide–semiconductor field-effect transistors. Furthermore, our simulation results for bulk fin-type field-effect transistor side-wall etching

  17. Polar predictability: exploring the influence of GCM and regional model uncertainty on future ice sheet climates

    NASA Astrophysics Data System (ADS)

    Reusch, D. B.

    2015-12-01

    Evaluating uncertainty in GCMs and regional-scale forecast models is an essential step in the development of climate change predictions. Polar-region skill is particularly important due to the potential for changes affecting both local (ice sheet) and global (sea level) environments through more frequent/intense surface melting and changes in precipitation type/amount. High-resolution, regional-scale models also use GCMs as a source of boundary/initial conditions in future scenarios, thus inheriting a measure of GCM-derived externally-driven uncertainty. We examine inter- and intramodel uncertainty through statistics from decadal climatologies and analyses of variability based on self-organizing maps (SOMs), a nonlinear data analysis tool. We evaluate a 19-member CMIP5 subset and the 30-member CESM1.0-CAM5-BGC Large Ensemble (CESMLE) during polar melt seasons (boreal/austral summer) for recent (1981-2000) and future (2081-2100, RCP 8.5) decades. Regional-model uncertainty is examined with a subset of these GCMs driving Polar WRF simulations. Decadal climatologies relative to a reference (recent: the ERA-Interim reanalysis; future: a skillful modern GCM) identify model uncertainty in bulk, e.g., BNU-ESM is too warm, CMCC-CM too cold. While quite useful for model screening, diagnostic benefit is often indirect. SOMs extend our diagnostics by providing a concise, objective summary of model variability as a set of generalized patterns. Joint analysis of reference and test models summarizes the variability of multiple realizations of climate (all the models), benchmarks each model versus the reference (frequency analysis helps identify the patterns behind GCM bias), and places each GCM in a common context. Joint SOM analysis of CESMLE members shows how initial conditions contribute to differences in modeled climates, providing useful information about internal variability, such as contributions from each member to overall uncertainty using pattern frequencies. In the

  18. Using Climate Variability to Predict Annual Precipitation and Estimate the Persistence of Climate Extremes for Major Urban Areas and Regions within the United States

    NASA Astrophysics Data System (ADS)

    Giovannettone, J. P.

    2015-12-01

    Relationships between climate variability and precipitation in several urban areas throughout the United States are developed using various global climate indices. Precipitation data for over 1200 stations are obtained from the United States Historical Climatology Network maintained by the National Climate Data Center, NOAA. All data are averaged over an extended period (up to five years) and correlated to several climate indices averaged over a period of equal length using lag times also up to five years. The period length and lag time are optimized in order to produce the highest correlation. The index that best correlates with precipitation for each urban area analyzed in the current study is identified and used to create regions within the United States that are predominantly affected by a particular index; strong correlations (r2 values > 0.70) were found in all regions. The final result is a map of the United States that displays the spatial distribution of each region. These results, which include the specific relationships developed for each region and urban area, will not only allow a greater understanding of the major mechanisms that are responsible for rainfall variability throughout the United States, but will also result in improved predictability of precipitation over multiple time scales, including seasonal and annual. In addition, the ability to predict total rainfall for periods greater than one year will allow an estimate of the persistence of trends and extreme events, such as periods of drought or above-average rainfall, to be made in advance; how far these projections can be made in advance depends on the lag times used to create each site-specific and regional correlation. An example related to the California Drought is given.

  19. Advanced Methods for Determining Prediction Uncertainty in Model-Based Prognostics with Application to Planetary Rovers

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew J.; Sankararaman, Shankar

    2013-01-01

    Prognostics is centered on predicting the time of and time until adverse events in components, subsystems, and systems. It typically involves both a state estimation phase, in which the current health state of a system is identified, and a prediction phase, in which the state is projected forward in time. Since prognostics is mainly a prediction problem, prognostic approaches cannot avoid uncertainty, which arises due to several sources. Prognostics algorithms must both characterize this uncertainty and incorporate it into the predictions so that informed decisions can be made about the system. In this paper, we describe three methods to solve these problems, including Monte Carlo-, unscented transform-, and first-order reliability-based methods. Using a planetary rover as a case study, we demonstrate and compare the different methods in simulation for battery end-of-discharge prediction.

  20. Expression, fermentation and purification of a predicted intrinsically disordered region of the transcription factor, NFAT5.

    PubMed

    DuMond, Jenna F; He, Yi; Burg, Maurice B; Ferraris, Joan D

    2015-11-01

    Hypertonicity stimulates Nuclear Factor of Activated T-cells 5 (NFAT5) nuclear localization and transactivating activity. Many transcription factors are known to contain intrinsically disordered regions (IDRs) which become more structured with local environmental changes such as osmolality, temperature and tonicity. The transactivating domain of NFAT5 is predicted to be intrinsically disordered under normal tonicity, and under high NaCl, the activity of this domain is increased. To study the binding of co-regulatory proteins at IDRs a cDNA construct expressing the NFAT5 TAD was created and transformed into Escherichia coli cells. Transformed E. coli cells were mass produced by fermentation and extracted by cell lysis to release the NFAT5 TAD. The NFAT5 TAD was subsequently purified using a His-tag column, cation exchange chromatography as well as hydrophobic interaction chromatography and then characterized by mass spectrometry (MS). PMID:26256058

  1. Ozone phytotoxicity evaluation and prediction of crops production in tropical regions

    NASA Astrophysics Data System (ADS)

    Mohammed, Nurul Izma; Ramli, Nor Azam; Yahya, Ahmad Shukri

    2013-04-01

    Increasing ozone concentration in the atmosphere can threaten food security due to its effects on crop production. Since the 1980s, ozone has been believed to be the most damaging air pollutant to crops. In Malaysia, there is no index to indicate the reduction of crops due to the exposure of ozone. Therefore, this study aimed to identify the accumulated exposure over a threshold of X ppb (AOTX) indexes in assessing crop reduction in Malaysia. In European countries, crop response to ozone exposure is mostly expressed as AOT40. This study was designed to evaluate and predict crop reduction in tropical regions and in particular, the Malaysian climate, by adopting the AOT40 index method and modifying it based on Malaysian air quality and crop data. Nine AOTX indexes (AOT0, AOT5, AOT10, AOT15, AOT20, AOT25, AOT30, AOT40, and AOT50) were analyzed, crop responses tested and reduction in crops predicted. The results showed that the AOT50 resulted in the highest reduction in crops and the highest R2 value between the AOT50 and the crops reduction from the linear regression analysis. Hence, this study suggests that the AOT50 index is the most suitable index to estimate the potential ozone impact on crops in tropical regions. The result showed that the critical level for AOT50 index if the estimated crop reduction is 5% was 1336 ppb h. Additionally, the results indicated that the AOT40 index in Malaysia gave a minimum percentage of 6% crop reduction; as contrasted with the European guideline of 5% (due to differences in the climate e.g., average amount of sunshine).

  2. Prediction of water content at different potentials from soil property data in Jazan region

    NASA Astrophysics Data System (ADS)

    Alturki, Ali; Ibrahim, Hesham

    2016-04-01

    In dry regions effective irrigation management is crucial to maintain crop production and sustain limited water resources. Effective irrigation requires good knowledge of soil water content in the root zone. However, measurement of soil water in the root zone over time is extremely expensive and time consuming. On the other hand, weather and basic soil property data are more available, either from existing databases or by direct measurement in the field. Simulation models can be used to efficiently and accurately estimate soil water content and subsequent irrigation requirements based on the available weather and soil data. In this study we investigated three hierarchical approaches to predict water content at variable potentials (0, 10, 33, 60, 100, 300, 500, 800, 1000, and 1500 kPa) using the Rosetta model: soil texture class (STC); percent of sand, silt, and clay (SSC); bulk density, percent of sand, silt, and clay, and water content measurements at 33 and 1500 kPa (SSC+WC). Estimation of soil water content at 43 locations in Jazan region using the three hierarchical approaches was compared with gravimetric water content. Results showed that the three approaches failed to describe water content accurately at saturation conditions (<10kPa). At water potentials lower than 10 kPa, good agreement was obtained, in general, between measured and simulated soil water content indicating that soil property data can be used to provide adequate estimates of the average soil water content in the root zone. The third approach gave the best results as indicated by an average NSCE value of 0.75 as compared to 0.16 and 0.18 for the first and second approaches, respectively. The ability to predict the amount of available water in the soil profile will facilitate the accurate estimate of irrigation requirements and achieve effective irrigation scheduling especially in locations where only limited weather and soil date are available.

  3. Advances in modelling the coevolving soils, landforms and vegetation in semiarid regions: a multidisciplinary approach.

    NASA Astrophysics Data System (ADS)

    Saco, Patricia M.; Moreno-de las Heras, Mariano; Willgoose, Garry R.

    2014-05-01

    Semiarid landscapes exhibit highly nonlinear interactions between coevolving physical and biological processes. Coevolution in these systems leads to the emergence of remarkable soil, landform and vegetation patterns. Growing concern over ecosystem resilience to climate and land use perturbations that could result in irreversible degradation imposes a pressing need for research, aiming at elucidating the processes, feedbacks, and dynamics leading to these coevolving patterns. This is particularly important since degradation in drylands has been frequently linked to feedback effects between soils, biota and erosion processes. In many dryland regions, feedbacks are responsible for the emergence of areas with low infiltration in unvegetated soil patches (due to surface crusting) and high infiltration rates in the vegetated soil patches (due to improved soil aggregation and macroporosity). This variable infiltration field gives rise to runoff-runon redistribution which determines areas of soil erosion and deposition. We have combined a coupled landform-soil-vegetation model with remote sensing and field data to capture these feedbacks and improve our knowledge of these coevolving biotic-abiotic processes. We discuss and present results showing that the dynamics of the individual processes and their response to climatic and anthropic disturbances cannot be fully understood or predicted if nonlinear feedbacks and coevolution are not considered. Implications for management and restoration efforts are illustrated using data and observations from agricultural sites in central Australia and reclaimed mining sites in Spain.

  4. Advances in regional crop yield estimation over the United States using satellite remote sensing data

    NASA Astrophysics Data System (ADS)

    Johnson, D. M.; Dorn, M. F.; Crawford, C.

    2015-12-01

    Since the dawn of earth observation imagery, particularly from systems like Landsat and the Advanced Very High Resolution Radiometer, there has been an overarching desire to regionally estimate crop production remotely. Research efforts integrating space-based imagery into yield models to achieve this need have indeed paralleled these systems through the years, yet development of a truly useful crop production monitoring system has been arguably mediocre in coming. As a result, relatively few organizations have yet to operationalize the concept, and this is most acute in regions of the globe where there are not even alternative sources of crop production data being collected. However, the National Agricultural Statistics Service (NASS) has continued to push for this type of data source as a means to complement its long-standing, traditional crop production survey efforts which are financially costly to the government and create undue respondent burden on farmers. Corn and soybeans, the two largest field crops in the United States, have been the focus of satellite-based production monitoring by NASS for the past decade. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) has been seen as the most pragmatic input source for modeling yields primarily based on its daily revisit capabilities and reasonable ground sample resolution. The research methods presented here will be broad but provides a summary of what is useful and adoptable with satellite imagery in terms of crop yield estimation. Corn and soybeans will be of particular focus but other major staple crops like wheat and rice will also be presented. NASS will demonstrate that while MODIS provides a slew of vegetation related products, the traditional normalized difference vegetation index (NDVI) is still ideal. Results using land surface temperature products, also generated from MODIS, will also be shown. Beyond the MODIS data itself, NASS research has also focused efforts on understanding a

  5. Impacts of the surface conditions uncertainties in the Canadian Regional Ensemble Prediction System

    NASA Astrophysics Data System (ADS)

    Lavaysse, C.; Carrera, M. L.; Belair, S.; Charron, M.; Yau, P. M.; Frenette, R.; Gagnon, N.

    2010-12-01

    The aim of this study is to quantify the impacts of surface condition uncertainties and the various surface parameters on the atmosphere of the Canadian Regional Ensemble Prediction System (REPS). In this study, the Canadian version of the ISBA land-surface scheme has been coupled to Environment Canada's Numerical Weather Prediction model (GEM) within the REPS. For twenty summer days in 2009, stochastic perturbations have been generated in 18 experiments. Each experiment corresponds to twenty simulations differing by the perturbations at the initial time of one or several surface parameters (e.g., vegetation fraction, leaf area index, sea-ice fraction) or prognostic variables (e.g., soil moisture, soil temperature at different layers). To better isolate these impacts, atmospheric perturbations are not added and all members of the REPS are driven by the same initial atmospheric conditions and large-scale forcing. The impact of these perturbations has been quantified especially for 2-m temperature, 10-m wind speed, and precipitation up to 48-h lead time. Spatial variability and diurnal evolution of these sensitivities over the North American continent will be discussed.

  6. Spatial heterogeneity of parasite co-infection: Determinants and geostatistical prediction at regional scales

    PubMed Central

    Brooker, Simon; Clements, Archie C.A.

    2009-01-01

    Multiple parasite infections are widespread in the developing world and understanding their geographical distribution is important for spatial targeting of differing intervention packages. We investigated the spatial epidemiology of mono- and co-infection with helminth parasites in East Africa and developed a geostatistical model to predict infection risk. The data used for the analysis were taken from standardised school surveys of Schistosoma mansoni and hookworm (Ancylostoma duodenale/Necator americanus) carried out between 1999 and 2005 in East Africa. Prevalence of mono- and co-infection was modelled using satellite-derived environmental and demographic variables as potential predictors. A Bayesian multi-nominal geostatistical model was developed for each infection category for producing maps of predicted co-infection risk. We show that heterogeneities in co-infection with S. mansoni and hookworm are influenced primarily by the distribution of S. mansoni, rather than the distribution of hookworm, and that temperature, elevation and distance to large water bodies are reliable predictors of the spatial large-scale distribution of co-infection. On the basis of these results, we developed a validated geostatistical model of the distribution of co-infection at a scale that is relevant for planning regional disease control efforts that simultaneously target multiple parasite species. PMID:19073189

  7. Evaluation of machine learning algorithms for prediction of regions of high Reynolds averaged Navier Stokes uncertainty

    DOE PAGES

    Ling, Julia; Templeton, Jeremy Alan

    2015-08-04

    Reynolds Averaged Navier Stokes (RANS) models are widely used in industry to predict fluid flows, despite their acknowledged deficiencies. Not only do RANS models often produce inaccurate flow predictions, but there are very limited diagnostics available to assess RANS accuracy for a given flow configuration. If experimental or higher fidelity simulation results are not available for RANS validation, there is no reliable method to evaluate RANS accuracy. This paper explores the potential of utilizing machine learning algorithms to identify regions of high RANS uncertainty. Three different machine learning algorithms were evaluated: support vector machines, Adaboost decision trees, and random forests.more » The algorithms were trained on a database of canonical flow configurations for which validated direct numerical simulation or large eddy simulation results were available, and were used to classify RANS results on a point-by-point basis as having either high or low uncertainty, based on the breakdown of specific RANS modeling assumptions. Classifiers were developed for three different basic RANS eddy viscosity model assumptions: the isotropy of the eddy viscosity, the linearity of the Boussinesq hypothesis, and the non-negativity of the eddy viscosity. It is shown that these classifiers are able to generalize to flows substantially different from those on which they were trained. As a result, feature selection techniques, model evaluation, and extrapolation detection are discussed in the context of turbulence modeling applications.« less

  8. Evaluation of machine learning algorithms for prediction of regions of high Reynolds averaged Navier Stokes uncertainty

    SciTech Connect

    Ling, Julia; Templeton, Jeremy Alan

    2015-08-04

    Reynolds Averaged Navier Stokes (RANS) models are widely used in industry to predict fluid flows, despite their acknowledged deficiencies. Not only do RANS models often produce inaccurate flow predictions, but there are very limited diagnostics available to assess RANS accuracy for a given flow configuration. If experimental or higher fidelity simulation results are not available for RANS validation, there is no reliable method to evaluate RANS accuracy. This paper explores the potential of utilizing machine learning algorithms to identify regions of high RANS uncertainty. Three different machine learning algorithms were evaluated: support vector machines, Adaboost decision trees, and random forests. The algorithms were trained on a database of canonical flow configurations for which validated direct numerical simulation or large eddy simulation results were available, and were used to classify RANS results on a point-by-point basis as having either high or low uncertainty, based on the breakdown of specific RANS modeling assumptions. Classifiers were developed for three different basic RANS eddy viscosity model assumptions: the isotropy of the eddy viscosity, the linearity of the Boussinesq hypothesis, and the non-negativity of the eddy viscosity. It is shown that these classifiers are able to generalize to flows substantially different from those on which they were trained. As a result, feature selection techniques, model evaluation, and extrapolation detection are discussed in the context of turbulence modeling applications.

  9. Novel Pretreatment Scoring Incorporating C-reactive Protein to Predict Overall Survival in Advanced Hepatocellular Carcinoma with Sorafenib Treatment

    PubMed Central

    Nakanishi, Hiroyuki; Kurosaki, Masayuki; Tsuchiya, Kaoru; Yasui, Yutaka; Higuchi, Mayu; Yoshida, Tsubasa; Komiyama, Yasuyuki; Takaura, Kenta; Hayashi, Tsuguru; Kuwabara, Konomi; Nakakuki, Natsuko; Takada, Hitomi; Ueda, Masako; Tamaki, Nobuharu; Suzuki, Shoko; Itakura, Jun; Takahashi, Yuka; Izumi, Namiki

    2016-01-01

    Objectives This study aimed to build a prediction score of prognosis for patients with advanced hepatocellular carcinoma (HCC) after sorafenib treatment. Methods A total of 165 patients with advanced HCC who were treated with sorafenib were analyzed. Readily available baseline factors were used to establish a scoring system for the prediction of survival. Results The median survival time (MST) was 14.2 months. The independent prognostic factors were C-reactive protein (CRP) <1.0 mg/dL [hazard ratio (HR) =0.51], albumin >3.5 g/dL (HR =0.55), alpha-fetoprotein <200 ng/mL (HR =0.45), and a lack of major vascular invasion (HR =0.39). Each of these factors had a score of 1, and after classifying the patients into five groups, the total scores ranged from 0 to 4. Higher scores were linked to significantly longer survival (p<0.0001). Twenty-nine patients (17.6%) with a score of 4 had a MST as long as 36.5 months, whereas MST was as short as 2.4 and 3.7 months for seven (4.2%) and 22 (13.3%) patients with scores of 0 and 1, respectively. Conclusions A novel prognostic scoring system, which includes the CRP level, has the ability to stratify the prognosis of patients with advanced stage HCC after treatment with sorafenib. PMID:27781198

  10. An Integrated Theory for Predicting the Hydrothermomechanical Response of Advanced Composite Structural Components

    NASA Technical Reports Server (NTRS)

    Chamis, C. C.; Lark, R. F.; Sinclair, J. H.

    1977-01-01

    An integrated theory is developed for predicting the hydrothermomechanical (HDTM) response of fiber composite components. The integrated theory is based on a combined theoretical and experimental investigation. In addition to predicting the HDTM response of components, the theory is structured to assess the combined hydrothermal effects on the mechanical properties of unidirectional composites loaded along the material axis and off-axis, and those of angleplied laminates. The theory developed predicts values which are in good agreement with measured data at the micromechanics, macromechanics, laminate analysis and structural analysis levels.

  11. Toward the predictability of meteotsunamis in the Balearic Sea using regional nested atmosphere and ocean models

    NASA Astrophysics Data System (ADS)

    Renault, Lionel; Vizoso, Guillermo; Jansá, Agustin; Wilkin, John; Tintoré, Joaquin

    2011-05-01

    Meteotsunamis are oceanic waves that possess tsunami-like characteristics but are meteorological in origin. In the western Mediterranean, travelling atmospheric pressure oscillations generate these long oceanic surface waves that can become amplified and produce strong seiche oscillations inside harbors. We analyze a June 2006 meteotsunami event in Ciutadella harbor (Menorca Island, Spain), studying numerically the phenomenon during its full life cycle, from the early atmospheric stages to the atmosphere-ocean resonant phase and the final highly amplified harbor oscillation. The Weather Research Forecast (WRF) atmospheric model adequately reproduces the development of a convective nucleus and also reproduces the induced atmospheric pressure oscillations moving at a speed of 27 m/s. The oceanic response is studied using the Regional Ocean Modeling System (ROMS), forced by the WRF pressure field. It shows an inverse barometer wave front in the open ocean progressively amplified through resonant interactions in the different shelf and coastal regions. The predictive capability of this new WRF/ROMS modeling approach is then discussed.

  12. Structure-Based Prediction of Unstable Regions in Proteins: Applications to Protein Misfolding Diseases

    NASA Astrophysics Data System (ADS)

    Guest, Will; Cashman, Neil; Plotkin, Steven

    2009-03-01

    Protein misfolding is a necessary step in the pathogenesis of many diseases, including Creutzfeldt-Jakob disease (CJD) and familial amyotrophic lateral sclerosis (fALS). Identifying unstable structural elements in their causative proteins elucidates the early events of misfolding and presents targets for inhibition of the disease process. An algorithm was developed to calculate the Gibbs free energy of unfolding for all sequence-contiguous regions of a protein using three methods to parameterize energy changes: a modified G=o model, changes in solvent-accessible surface area, and solution of the Poisson-Boltzmann equation. The entropic effects of disulfide bonds and post-translational modifications are treated analytically. It incorporates a novel method for finding local dielectric constants inside a protein to accurately handle charge effects. We have predicted the unstable parts of prion protein and superoxide dismutase 1, the proteins involved in CJD and fALS respectively, and have used these regions as epitopes to prepare antibodies that are specific to the misfolded conformation and show promise as therapeutic agents.

  13. Predicting wetland contamination from atmospheric deposition measurements of pesticides in the Canadian Prairie Pothole region

    NASA Astrophysics Data System (ADS)

    Messing, Paul G.; Farenhorst, Annemieke; Waite, Don T.; McQueen, D. A. Ross; Sproull, James F.; Humphries, David A.; Thompson, Laura L.

    2011-12-01

    Although it has been suggested that atmospheric deposition alone can result in detectable levels of pesticides in wetlands of the Pairie Pothole Region of Canada, this is the first field study to compare the masses of pesticides entering wetlands by atmospheric deposition with those concentrations of pesticides detected in the water-column of prairie wetlands. Weekly air and bulk deposition samples were collected from May 26th to Sept. 15th, 2008 at the Manitoba Zero Tillage Research Association (MZTRA) Farm, Brandon, Manitoba, with four on-site wetlands (approximate sizes 0.15-0.45 ha) monitored every second week. Twelve pesticides were detected in the air, with MCPA (one of the three pesticides applied on the farm in 2008 in addition to clopyralid and glyphosate), triallate, and γ-HCH being detected every week. Calculations were performed to predict wetland pesticide concentrations based on bulk deposits alone for those pesticides that had detectable concentrations in the bulk deposition samples (in order of the highest total seasonal deposition mass to the lowest): MCPA, glyphosate, 2,4-D, clopyralid, bromoxynil, atrazine, dicamba, metolachlor, and mecoprop. The estimated concentrations were closest to actual concentrations for MCPA (Pearson correlation coefficient's = 0.91 to 0.98; p-values < 0.001) and predictions were also reasonable for a range of other herbicides, but a source other than atmospheric deposition was clearly relevant to detections of clopyralid in the wetland water-column. Although the types and levels of pesticides detected in the wetlands of the current study suggest that regional pesticide applications can contribute to pesticide surface water contamination following atmospheric transport and deposition, the greater frequency and concentrations of clopyralid, MCPA, and glyphosate detections in wetlands confirm that on-farm pesticide applications have a greater impact on on-site water quality. Beneficial management practices that reduce

  14. Isoscapes of tree-ring carbon-13 perform like meteorological networks in predicting regional precipitation patterns

    NASA Astrophysics Data System (ADS)

    Castillo, Jorge; Aguilera, Mònica; Voltas, Jordi; Ferrio, Juan Pedro

    2013-03-01

    isotopes in tree rings provide climatic information with annual resolution dating back for centuries or even millennia. However, deriving spatially explicit climate models from isotope networks remains challenging. Here we propose a methodology to model regional precipitation from carbon isotope discrimination (Δ13C) in tree rings by (1) building regional spatial models of Δ13C (isoscapes) and (2) deriving precipitation maps from Δ13C-isoscapes, taking advantage of the response of Δ13C to precipitation in seasonally dry climates. As a case study, we modeled the spatial distribution of mean annual precipitation (MAP) in the northeastern Iberian Peninsula, a region with complex topography and climate (MAP = 303-1086 mm). We compiled wood Δ13C data for two Mediterranean species that exhibit complementary responses to seasonal precipitation (Pinus halepensis Mill., N = 38; Quercus ilex L.; N = 44; pooling period: 1975-2008). By combining multiple regression and geostatistical interpolation, we generated one Δ13 C-isoscape for each species. A spatial model of MAP was then built as the sum of two complementary maps of seasonal precipitation, each one derived from the corresponding Δ13C-isoscape (September-November from Q. ilex; December-August from P. halepensis). Our approach showed a predictive power for MAP (RMSE = 84 mm) nearly identical to that obtained by interpolating data directly from a similarly dense network of meteorological stations (RMSE = 80-83 mm, N = 65), being only outperformed when using a much denser meteorological network (RMSE = 56-57 mm, N = 340). This method offers new avenues for modeling spatial variability of past precipitation, exploiting the large amount of information currently available from tree-ring networks.

  15. Isoscapes of tree-ring carbon-13 perform like meteorological networks in predicting regional precipitation patterns

    NASA Astrophysics Data System (ADS)

    del Castillo, Jorge; Aguilera, Mònica; Voltas, Jordi; Ferrio, Juan Pedro

    2013-04-01

    Stable isotopes in tree rings provide climatic information with annual resolution dating back for centuries or even millennia. However, deriving spatially explicit climate models from isotope networks remains challenging. Here we propose a methodology to model regional precipitation from carbon isotope discrimination (Δ13C) in tree rings by (1) building regional spatial models of Δ13C (isoscapes), and (2) deriving precipitation maps from 13C-isoscapes, taking advantage of the response of Δ13C to precipitation in seasonally-dry climates. As a case study, we modeled the spatial distribution of mean annual precipitation (MAP) in the northeastern Iberian Peninsula, a region with complex orography and climate (MAP=303-1086 mm). We compiled wood Δ13C data for two Mediterranean species that exhibit complementary responses to seasonal precipitation (Pinus halepensis Mill., N=38; Quercus ilex L.; N=44; pooling period: 1975-2008). By combining multiple regression and geostatistical interpolation, we generated one 13C-isoscape for each species. A spatial model of MAP was then built as the sum of two complementary maps of seasonal precipitation, each one derived from the corresponding 13C-isoscape (September-November from Q. ilex; December-August from P. halepensis). Our approach showed a predictive power for MAP (RMSE=84 mm) nearly identical to that obtained by interpolating data directly from a similarly dense network of meteorological stations (RMSE=80-83 mm, N=65), being only outperformed when using a much denser meteorological network (RMSE=56-57 mm, N=340). This method offers new avenues for modeling spatial variability of past precipitation, exploiting the large amount of information currently available from tree-ring networks. Acknowledgements: This work was funded by MC-ERG-246725 (FP7, EU) and AGL 2012-40039-C02-02 (MINECO, Spain). JdC and JPF are supported by FPI fellowship (MCINN) and Ramón y Cajal programme (RYC-2008-02050, MINECO), respectively.

  16. How Prognostic and Predictive Biomarkers Are Transforming Our Understanding and Management of Advanced Gastric Cancer

    PubMed Central

    Mulder, Karen; Spratlin, Jennifer

    2014-01-01

    Background. Gastric cancer (GC) is the second leading cause of cancer death worldwide. GC is a heterogeneous disease in terms of histology, anatomy, and epidemiology. There is also wide variability in how GC is treated in both the resectable and unresectable settings. Identification of prognostic and predictive biomarkers is critical to help direct and tailor therapy for this deadly disease. Methods. A literature search was done using Medline and MeSH terms for GC and predictive biomarkers and prognostic biomarkers. The search was limited to human subjects and the English language. There was no limit on dates. Published data and unpublished abstracts with clinical relevance were included. Results. Many potential prognostic and predictive biomarkers have been assessed for GC, some of which are becoming practice changing. This review is focused on clinically relevant biomarkers, including EGFR, HER2, various markers of angiogenesis, proto-oncogene MET, and the mammalian target of rapamycin. Conclusion. GC is a deadly and heterogeneous disease for which biomarkers are beginning to change our understanding of prognosis and management. The recognition of predictive biomarkers, such as HER2 and vascular endothelial growth factor, has been an exciting development in the management of GC, validating the use of targeted drugs trastuzumab and ramucirumab. MET is another potential predictive marker that may be targeted in GC with drugs such as rilotumumab, foretinib, and crizotinib. Further identification and validation of prognostic and predictive biomarkers has the potential transform how this deadly disease is managed. PMID:25142842

  17. Recent advances in analysis and prediction of Rock Falls, Rock Slides, and Rock Avalanches using 3D point clouds

    NASA Astrophysics Data System (ADS)

    Abellan, A.; Carrea, D.; Jaboyedoff, M.; Riquelme, A.; Tomas, R.; Royan, M. J.; Vilaplana, J. M.; Gauvin, N.

    2014-12-01

    The acquisition of dense terrain information using well-established 3D techniques (e.g. LiDAR, photogrammetry) and the use of new mobile platforms (e.g. Unmanned Aerial Vehicles) together with the increasingly efficient post-processing workflows for image treatment (e.g. Structure From Motion) are opening up new possibilities for analysing, modeling and predicting rock slope failures. Examples of applications at different scales ranging from the monitoring of small changes at unprecedented level of detail (e.g. sub millimeter-scale deformation under lab-scale conditions) to the detection of slope deformation at regional scale. In this communication we will show the main accomplishments of the Swiss National Foundation project "Characterizing and analysing 3D temporal slope evolution" carried out at Risk Analysis group (Univ. of Lausanne) in close collaboration with the RISKNAT and INTERES groups (Univ. of Barcelona and Univ. of Alicante, respectively). We have recently developed a series of innovative approaches for rock slope analysis using 3D point clouds, some examples include: the development of semi-automatic methodologies for the identification and extraction of rock-slope features such as discontinuities, type of material, rockfalls occurrence and deformation. Moreover, we have been improving our knowledge in progressive rupture characterization thanks to several algorithms, some examples include the computing of 3D deformation, the use of filtering techniques on permanently based TLS, the use of rock slope failure analogies at different scales (laboratory simulations, monitoring at glacier's front, etc.), the modelling of the influence of external forces such as precipitation on the acceleration of the deformation rate, etc. We have also been interested on the analysis of rock slope deformation prior to the occurrence of fragmental rockfalls and the interaction of this deformation with the spatial location of future events. In spite of these recent advances

  18. One-Way Coupling of an Advanced CFD Multi-Physics Model to FEA for Predicting Stress-Strain in the Solidifying Shell during Continuous Casting of Steel

    NASA Astrophysics Data System (ADS)

    Svensson, Johan; Ramírez López, Pavel E.; Jalali, Pooria N.; Cervantes, Michel

    2015-06-01

    One of the main targets for Continuous Casting (CC) modelling is the actual prediction of defects during transient events. However, the majority of CC models are based on a statistical approach towards flow and powder performance, which is unable to capture the subtleties of small variations in casting conditions during real industrial operation or the combined effects of such changes leading eventually to defects. An advanced Computational Fluid Dynamics (CFD) model; which accounts for transient changes on lubrication during casting due to turbulent flow dynamics and mould oscillation has been presented on MCWASP XIV (Austria) to address these issues. The model has been successfully applied to the industrial environment to tackle typical problems such as lack of lubrication or unstable flows. However, a direct application to cracking had proven elusive. The present paper describes how results from this advanced CFD-CC model have been successfully coupled to structural Finite Element Analysis (FEA) for prediction of stress-strains as a function of irregular lubrication conditions in the mould. The main challenge for coupling was the extraction of the solidified shell from CFD calculations (carried out with a hybrid structured mesh) and creating a geometry by using iso-surfaces, re-meshing and mapping loads (e.g. temperature, pressure and external body forces), which served as input to mechanical stress-strain calculations. Preliminary results for CC of slabs show that the temperature distribution within the shell causes shrinkage and thermal deformation; which are in turn, the main source of stress. Results also show reasonable stress levels of 10-20 MPa in regions, where the shell is thin and exposed to large temperature gradients. Finally, predictions are in good agreement with prior works where stresses indicate compression at the slab surface, while tension is observed at the interior; generating a characteristic stress-strain state during solidification in CC.

  19. Life prediction methodology for ceramic components of advanced vehicular heat engines: Volume 1. Final report

    SciTech Connect

    Khandelwal, P.K.; Provenzano, N.J.; Schneider, W.E.

    1996-02-01

    One of the major challenges involved in the use of ceramic materials is ensuring adequate strength and durability. This activity has developed methodology which can be used during the design phase to predict the structural behavior of ceramic components. The effort involved the characterization of injection molded and hot isostatic pressed (HIPed) PY-6 silicon nitride, the development of nondestructive evaluation (NDE) technology, and the development of analytical life prediction methodology. Four failure modes are addressed: fast fracture, slow crack growth, creep, and oxidation. The techniques deal with failures initiating at the surface as well as internal to the component. The life prediction methodology for fast fracture and slow crack growth have been verified using a variety of confirmatory tests. The verification tests were conducted at room and elevated temperatures up to a maximum of 1371 {degrees}C. The tests involved (1) flat circular disks subjected to bending stresses and (2) high speed rotating spin disks. Reasonable correlation was achieved for a variety of test conditions and failure mechanisms. The predictions associated with surface failures proved to be optimistic, requiring re-evaluation of the components` initial fast fracture strengths. Correlation was achieved for the spin disks which failed in fast fracture from internal flaws. Time dependent elevated temperature slow crack growth spin disk failures were also successfully predicted.

  20. Ideal MHD Stability Prediction and Required Power for EAST Advanced Scenario

    NASA Astrophysics Data System (ADS)

    Chen, Junjie; Li, Guoqiang; Qian, Jinping; Liu, Zixi

    2012-11-01

    The Experimental Advanced Superconducting Tokamak (EAST) is the first fully superconducting tokamak with a D-shaped cross-sectional plasma presently in operation. The ideal magnetohydrodynamic (MHD) stability and required power for the EAST advanced tokamak (AT) scenario with negative central shear and double transport barrier (DTB) are investigated. With the equilibrium code TOQ and stability code GATO, the ideal MHD stability is analyzed. It is shown that a moderate ratio of edge transport barriers' (ETB) height to internal transport barriers' (ITBs) height is beneficial to ideal MHD stability. The normalized beta βN limit is about 2.20 (without wall) and 3.70 (with ideal wall). With the scaling law of energy confinement time, the required heating power for EAST AT scenario is calculated. The total heating power Pt increases as the toroidal magnetic field BT or the normalized beta βN is increased.

  1. Development of Predictive Models of Advanced Propulsion Concepts for Low Cost Space Transportation

    NASA Technical Reports Server (NTRS)

    Morrell, Michael Randy

    2002-01-01

    This final report presents the Graduate Student Research Program (GSRP) work Mr. Morrell was able to complete as a summer intern at NASA MSFS during the summer of 2001, and represents work completed from inception through project termination. The topics include: 1) NASA TD40 Organization; 2) Combustion Physics Lab; 3) Advanced Hydrocarbon Fuels; 4) GSRP Summer Tasks; 5) High Pressure Facility Installation; 6) High Pressure Combustion Issues; 7) High Energy Density Matter (HEDM) Hydrocarbons; and 8) GSRP Summer Intern Summary.

  2. Life prediction methodology for ceramic components of advanced heat engines. Phase 1: Volume 2, Appendices

    SciTech Connect

    1995-03-01

    This volume presents the following appendices: ceramic test specimen drawings and schematics, mixed-mode and biaxial stress fracture of structural ceramics for advanced vehicular heat engines (U. Utah), mode I/mode II fracture toughness and tension/torsion fracture strength of NT154 Si nitride (Brown U.), summary of strength test results and fractography, fractography photographs, derivations of statistical models, Weibull strength plots for fast fracture test specimens, and size functions.

  3. An accelerated non-Gaussianity based multichannel predictive deconvolution method with the limited supporting region of filters

    NASA Astrophysics Data System (ADS)

    Li, Zhong-xiao; Li, Zhen-chun

    2016-09-01

    The multichannel predictive deconvolution can be conducted in overlapping temporal and spatial data windows to solve the 2D predictive filter for multiple removal. Generally, the 2D predictive filter can better remove multiples at the cost of more computation time compared with the 1D predictive filter. In this paper we first use the cross-correlation strategy to determine the limited supporting region of filters where the coefficients play a major role for multiple removal in the filter coefficient space. To solve the 2D predictive filter the traditional multichannel predictive deconvolution uses the least squares (LS) algorithm, which requires primaries and multiples are orthogonal. To relax the orthogonality assumption the iterative reweighted least squares (IRLS) algorithm and the fast iterative shrinkage thresholding (FIST) algorithm have been used to solve the 2D predictive filter in the multichannel predictive deconvolution with the non-Gaussian maximization (L1 norm minimization) constraint of primaries. The FIST algorithm has been demonstrated as a faster alternative to the IRLS algorithm. In this paper we introduce the FIST algorithm to solve the filter coefficients in the limited supporting region of filters. Compared with the FIST based multichannel predictive deconvolution without the limited supporting region of filters the proposed method can reduce the computation burden effectively while achieving a similar accuracy. Additionally, the proposed method can better balance multiple removal and primary preservation than the traditional LS based multichannel predictive deconvolution and FIST based single channel predictive deconvolution. Synthetic and field data sets demonstrate the effectiveness of the proposed method.

  4. Advances and Challenges In Uncertainty Quantification with Application to Climate Prediction, ICF design and Science Stockpile Stewardship

    NASA Astrophysics Data System (ADS)

    Klein, R.; Woodward, C. S.; Johannesson, G.; Domyancic, D.; Covey, C. C.; Lucas, D. D.

    2012-12-01

    Uncertainty Quantification (UQ) is a critical field within 21st century simulation science that resides at the very center of the web of emerging predictive capabilities. The science of UQ holds the promise of giving much greater meaning to the results of complex large-scale simulations, allowing for quantifying and bounding uncertainties. This powerful capability will yield new insights into scientific predictions (e.g. Climate) of great impact on both national and international arenas, allow informed decisions on the design of critical experiments (e.g. ICF capsule design, MFE, NE) in many scientific fields, and assign confidence bounds to scientifically predictable outcomes (e.g. nuclear weapons design). In this talk I will discuss a major new strategic initiative (SI) we have developed at Lawrence Livermore National Laboratory to advance the science of Uncertainty Quantification at LLNL focusing in particular on (a) the research and development of new algorithms and methodologies of UQ as applied to multi-physics multi-scale codes, (b) incorporation of these advancements into a global UQ Pipeline (i.e. a computational superstructure) that will simplify user access to sophisticated tools for UQ studies as well as act as a self-guided, self-adapting UQ engine for UQ studies on extreme computing platforms and (c) use laboratory applications as a test bed for new algorithms and methodologies. The initial SI focus has been on applications for the quantification of uncertainty associated with Climate prediction, but the validated UQ methodologies we have developed are now being fed back into Science Based Stockpile Stewardship (SSS) and ICF UQ efforts. To make advancements in several of these UQ grand challenges, I will focus in talk on the following three research areas in our Strategic Initiative: Error Estimation in multi-physics and multi-scale codes ; Tackling the "Curse of High Dimensionality"; and development of an advanced UQ Computational Pipeline to enable

  5. Predicted and measured boundary layer refraction for advanced turboprop propeller noise

    NASA Technical Reports Server (NTRS)

    Dittmar, James H.; Krejsa, Eugene A.

    1990-01-01

    Currently, boundary layer refraction presents a limitation to the measurement of forward arc propeller noise measured on an acoustic plate in the NASA Lewis 8- by 6-Foot Supersonic Wind Tunnel. The use of a validated boundary layer refraction model to adjust the data could remove this limitation. An existing boundary layer refraction model is used to predict the refraction for cases where boundary layer refraction was measured. In general, the model exhibits the same qualitative behavior as the measured refraction. However, the prediction method does not show quantitative agreement with the data. In general, it overpredicts the amount of refraction for the far forward angles at axial Mach number of 0.85 and 0.80 and underpredicts the refraction at axial Mach numbers of 0.75 and 0.70. A more complete propeller source description is suggested as a way to improve the prediction method.

  6. Structural classification and prediction of reentrant regions in alpha-helical transmembrane proteins: application to complete genomes.

    PubMed

    Viklund, Håkan; Granseth, Erik; Elofsson, Arne

    2006-08-18

    Alongside the well-studied membrane spanning helices, alpha-helical transmembrane (TM) proteins contain several functionally and structurally important types of substructures. Here, existing 3D structures of transmembrane proteins have been used to define and study the concept of reentrant regions, i.e. membrane penetrating regions that enter and exit the membrane on the same side. We find that these regions can be divided into three distinct categories based on secondary structure motifs, namely long regions with a helix-coil-helix motif, regions of medium length with the structure helix-coil or coil-helix and regions of short to medium length consisting entirely of irregular secondary structure. The residues situated in reentrant regions are significantly smaller on average compared to other regions and reentrant regions can be detected in the inter-transmembrane loops with an accuracy of approximately 70% based on their amino acid composition. Using TOP-MOD, a novel method for predicting reentrant regions, we have scanned the genomes of Escherichia coli, Saccharomyces cerevisiae and Homo sapiens. The results suggest that more than 10% of transmembrane proteins contain reentrant regions and that the occurrence of reentrant regions increases linearly with the number of transmembrane regions. Reentrant regions seem to be most commonly found in channel proteins and least commonly in signal receptors.

  7. Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances

    PubMed Central

    Abut, Fatih; Akay, Mehmet Fatih

    2015-01-01

    Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R) and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance. PMID:26346869

  8. Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances.

    PubMed

    Abut, Fatih; Akay, Mehmet Fatih

    2015-01-01

    Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R) and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance.

  9. A hybrid approach to advancing quantitative prediction of tissue distribution of basic drugs in human

    SciTech Connect

    Poulin, Patrick; Ekins, Sean; Theil, Frank-Peter

    2011-01-15

    A general toxicity of basic drugs is related to phospholipidosis in tissues. Therefore, it is essential to predict the tissue distribution of basic drugs to facilitate an initial estimate of that toxicity. The objective of the present study was to further assess the original prediction method that consisted of using the binding to red blood cells measured in vitro for the unbound drug (RBCu) as a surrogate for tissue distribution, by correlating it to unbound tissue:plasma partition coefficients (Kpu) of several tissues, and finally to predict volume of distribution at steady-state (V{sub ss}) in humans under in vivo conditions. This correlation method demonstrated inaccurate predictions of V{sub ss} for particular basic drugs that did not follow the original correlation principle. Therefore, the novelty of this study is to provide clarity on the actual hypotheses to identify i) the impact of pharmacological mode of action on the generic correlation of RBCu-Kpu, ii) additional mechanisms of tissue distribution for the outlier drugs, iii) molecular features and properties that differentiate compounds as outliers in the original correlation analysis in order to facilitate its applicability domain alongside the properties already used so far, and finally iv) to present a novel and refined correlation method that is superior to what has been previously published for the prediction of human V{sub ss} of basic drugs. Applying a refined correlation method after identifying outliers would facilitate the prediction of more accurate distribution parameters as key inputs used in physiologically based pharmacokinetic (PBPK) and phospholipidosis models.

  10. Multiaxial deformation and life prediction model and experimental data for advanced silicon nitride ceramics

    SciTech Connect

    Ding, J.L.; Liu, K.C.; Brinkman, C.R.

    1993-06-01

    This paper summarizes recent experimental results on creep and creep rupture behavior of a commercial grade of Si{sub 3}N{sub 4} ceramic in the temperature range of 1150 to 1300C obtained at ORNL; and introduces a tentative multiaxial deformation and life prediction model for ceramic materials under general thermomechanical loadings. Issues related to the possible standardization of the data analysis methodology and possible future research needs for high temperature structural ceramics in the area of development of data base and life prediction methodology are also discussed.

  11. Advanced turboprop noise prediction: Development of a code at NASA Langley based on recent theoretical results

    NASA Technical Reports Server (NTRS)

    Farassat, F.; Dunn, M. H.; Padula, S. L.

    1986-01-01

    The development of a high speed propeller noise prediction code at Langley Research Center is described. The code utilizes two recent acoustic formulations in the time domain for subsonic and supersonic sources. The structure and capabilities of the code are discussed. Grid size study for accuracy and speed of execution on a computer is also presented. The code is tested against an earlier Langley code. Considerable increase in accuracy and speed of execution are observed. Some examples of noise prediction of a high speed propeller for which acoustic test data are available are given. A brisk derivation of formulations used is given in an appendix.

  12. LiverTox: Advanced QSAR and Toxicogeomic Software for Hepatotoxicity Prediction

    SciTech Connect

    Lu, P-Y.; Yuracko, K.

    2011-02-25

    YAHSGS LLC and Oak Ridge National Laboratory (ORNL) established a CRADA in an attempt to develop a predictive system using a pre-existing ORNL computational neural network and wavelets format. This was in the interest of addressing national needs for toxicity prediction system to help overcome the significant drain of resources (money and time) being directed toward developing chemical agents for commerce. The research project has been supported through an STTR mechanism and funded by the National Institute of Environmental Health Sciences beginning Phase I in 2004 (CRADA No. ORNL-04-0688) and extending Phase II through 2007 (ORNL NFE-06-00020). To attempt the research objectives and aims outlined under this CRADA, state-of-the-art computational neural network and wavelet methods were used in an effort to design a predictive toxicity system that used two independent areas on which to base the system’s predictions. These two areas were quantitative structure-activity relationships and gene-expression data obtained from microarrays. A third area, using the new Massively Parallel Signature Sequencing (MPSS) technology to assess gene expression, also was attempted but had to be dropped because the company holding the rights to this promising MPSS technology went out of business. A research-scale predictive toxicity database system called Multi-Intelligent System for Toxicogenomic Applications (MISTA) was developed and its feasibility for use as a predictor of toxicological activity was tested. The fundamental focus of the CRADA was an attempt and effort to operate the MISTA database using the ORNL neural network. This effort indicated the potential that such a fully developed system might be used to assist in predicting such biological endpoints as hepatotoxcity and neurotoxicity. The MISTA/LiverTox approach if eventually fully developed might also be useful for automatic processing of microarray data to predict modes of action. A technical paper describing the

  13. Advanced Models and Controls for Prediction and Extension of Battery Lifetime (Presentation)

    SciTech Connect

    Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Pesaran, A.

    2014-02-01

    Predictive models of capacity and power fade must consider a multiplicity of degradation modes experienced by Li-ion batteries in the automotive environment. Lacking accurate models and tests, lifetime uncertainty must presently be absorbed by overdesign and excess warranty costs. To reduce these costs and extend life, degradation models are under development that predict lifetime more accurately and with less test data. The lifetime models provide engineering feedback for cell, pack and system designs and are being incorporated into real-time control strategies.

  14. Predicting Cost/Reliability/Maintainability of Advanced General Aviation Avionics Equipment

    NASA Technical Reports Server (NTRS)

    Davis, M. R.; Kamins, M.; Mooz, W. E.

    1978-01-01

    A methodology is provided for assisting NASA in estimating the cost, reliability, and maintenance (CRM) requirements for general avionics equipment operating in the 1980's. Practical problems of predicting these factors are examined. The usefulness and short comings of different approaches for modeling coast and reliability estimates are discussed together with special problems caused by the lack of historical data on the cost of maintaining general aviation avionics. Suggestions are offered on how NASA might proceed in assessing cost reliability CRM implications in the absence of reliable generalized predictive models.

  15. Predicting plant vulnerability to drought in biodiverse regions using functional traits

    PubMed Central

    Skelton, Robert Paul; West, Adam G.; Dawson, Todd E.

    2015-01-01

    Attempts to understand mechanisms underlying plant mortality during drought have led to the emergence of a hydraulic framework describing distinct hydraulic strategies among coexisting species. This framework distinguishes species that rapidly decrease stomatal conductance (gs), thereby maintaining high water potential (Px; isohydric), from those species that maintain relatively high gs at low Px, thereby maintaining carbon assimilation, albeit at the cost of loss of hydraulic conductivity (anisohydric). This framework is yet to be tested in biodiverse communities, potentially due to a lack of standardized reference values upon which hydraulic strategies can be defined. We developed a system of quantifying hydraulic strategy using indices from vulnerability curves and stomatal dehydration response curves and tested it in a speciose community from South Africa’s Cape Floristic Region. Degree of stomatal regulation over cavitation was defined as the margin between Px at stomatal closure (Pg12) and Px at 50% loss of conductivity. To assess relationships between hydraulic strategy and mortality mechanisms, we developed proxies for carbon limitation and hydraulic failure using time since Pg12 and loss of conductivity at minimum seasonal Px, respectively. Our approach captured continuous variation along an isohydry/anisohydry axis and showed that this variation was linearly related to xylem safety margin. Degree of isohydry/anisohydry was associated with contrasting predictions for mortality during drought. Merging stomatal regulation strategies that represent an index of water use behavior with xylem vulnerability facilitates a more comprehensive framework with which to characterize plant response to drought, thus opening up an avenue for predicting the response of diverse communities to future droughts. PMID:25902534

  16. Predicting plant vulnerability to drought in biodiverse regions using functional traits.

    PubMed

    Skelton, Robert Paul; West, Adam G; Dawson, Todd E

    2015-05-01

    Attempts to understand mechanisms underlying plant mortality during drought have led to the emergence of a hydraulic framework describing distinct hydraulic strategies among coexisting species. This framework distinguishes species that rapidly decrease stomatal conductance (gs), thereby maintaining high water potential (Px; isohydric), from those species that maintain relatively high gs at low Px, thereby maintaining carbon assimilation, albeit at the cost of loss of hydraulic conductivity (anisohydric). This framework is yet to be tested in biodiverse communities, potentially due to a lack of standardized reference values upon which hydraulic strategies can be defined. We developed a system of quantifying hydraulic strategy using indices from vulnerability curves and stomatal dehydration response curves and tested it in a speciose community from South Africa's Cape Floristic Region. Degree of stomatal regulation over cavitation was defined as the margin between Px at stomatal closure (Pg12) and Px at 50% loss of conductivity. To assess relationships between hydraulic strategy and mortality mechanisms, we developed proxies for carbon limitation and hydraulic failure using time since Pg12 and loss of conductivity at minimum seasonal Px, respectively. Our approach captured continuous variation along an isohydry/anisohydry axis and showed that this variation was linearly related to xylem safety margin. Degree of isohydry/anisohydry was associated with contrasting predictions for mortality during drought. Merging stomatal regulation strategies that represent an index of water use behavior with xylem vulnerability facilitates a more comprehensive framework with which to characterize plant response to drought, thus opening up an avenue for predicting the response of diverse communities to future droughts.

  17. Some Techniques for the Objective Analysis of Humidity for Regional Scale Numerical Weather Prediction.

    NASA Astrophysics Data System (ADS)

    Rasmussen, Robert Gary

    Several topics relating to the objective analysis of humidity for regional scale numerical weather prediction are investigated. These include: (1) sampling the humidity field; (2) choosing an analysis scheme; (3) choosing an analysis variable; (4) using surface data to diagnose upper -air humidity (SFC-DIAG); (5) using cloud analysis data to diagnose surface and upper-air humidities (3DNEPH-DIAG); and (6) modeling the humidity lateral autocorrelation function. Regression equations for the diagnosed humidities and several correlation models are developed and validated. Four types of data are used in a preliminary demonstration: observations (radiosonde and surface), SFC-DIAG data, 3DNEPH-DIAG data, and forecast data from the Drexel/NCAR Limited-Area and Mesoscale Prediction System (LAMPS). The major conclusions are: (1) independent samples of relative humidity can be obtained by sampling at intervals of two days and 1750 km, on the average; (2) Gandin's optimum interpolation (OI) is preferable to Cressman's successive correction and Panofsky's surface fitting schemes; (3) relative humidity (RH) is a better analysis variable than dew-point depression; (4) RH*, the square root of (1-RH), is better than RH; (5) both surface and cloud analysis data can be used to diagnose the upper-air humidity; (6) pooling dense data prior to OI analysis can improve the quality of the analysis and reduce its computational burden; (7) iteratively pooling data is economical; (8) for the types of data considered, use of more than about eight data in an OI point analysis cannot be justified by expectations of further reducing the analysis error variance; and (9) the statistical model in OI is faulty in that an analyzed humidity can be biased too much toward the first guess.

  18. Regional intercomparisons of General Circulation Model predictions and historical climate data: CO/sub 2/

    SciTech Connect

    Grotch, S.L.

    1988-04-01

    This study is a detailed intercomparsion of the results produced by four different General Circulation Models (GCMs) that have been used to project the climatic consequences of a doubling of the atmospheric CO/sub 2/ concentration. The results for the models developed by groups at the National Center for Atmospheric Research (NCARCCM, Washington and Meehl, 1984), the Geophysical Fluid Dynamics Laboratory of NOAA (GFDL, Manable and Wetherald, 1987), and the Goddard Institute for Space Studies of NASA (GISS, Hansen, et al., 1984) have been described by Schlesinger and Mitchell (1985) in the DOE state-of-art (SOA) report, ''Projecting the Climatic Effects of Increasing Carbon Dioxide''. The fourth model examined here is the Oregon State University GCM (OSU, Schlesinger, 1986), results for which did not become available until after publication of the SOA. We have chosen to examine only two model variables here: (1) surface air temperature, and (2) precipation. We consider these variables for both seasonally and annually averaged periods, for both the current climatic conditions and the predicted equilibrium changes after a doubling of the CO/sub 2/ concentration. The major conclusion of this study is that, although the models often agree well comparing seasonal or annual averages over the large areas, substanial disagreements become apparent as the spatial extent is reduced, particularly when detailed regional distributions are examined. At scales below continental, the correlations observed between different model predictions are often very poor, particularly for land gridpoints during the Northern Hemisphere (NH) summer, with differences of as much as 5/degree/C between models and observations and between one model and another over relatively large areas.

  19. 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.

  20. 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.

  1. Advance of the Monitor of Drought for the Northern Region of Mexico

    NASA Astrophysics Data System (ADS)

    Reyes Gomez, V. M.; Nunez Lopez, D.

    2007-05-01

    In the last 13 years, the State of Chihuahua suffered a lingering drought that caused social, economical and environmental impacts hardly quantifiable. Since 2002, a monitoring system was implemented to watch the evolution of the meteorological drought in Chihuahua, recently being broadened for the states in the North of Mexico. Evaluation of the Meteorological Drought The Monitoring System on the Drought in Chihuahua includes the following steps: missing data gaps were completed basing on the statistical procedures described by Young (1992); the source code, was compiled to create a computer program, with which it can be derived a level of climatic station, historical series of values for the SPI in time scales of 1 to 48 months; under this classification scheme, it is considered that a drought event begins when the values of the SPI are inferior to -0.7 (McKee et al. 1995). The spatial distribution of the SPI was determined through spatial interpolation techniques using a reverse method of the distance between stations included in Arc/Info©. This same procedure was applied for the States of Sonora, Sinaloa, Durango and Zacatecas with the purpose of implementing this tool for the north of Mexico. Advances on the Monitoring System The monitoring system allows an analysis of the frequency, duration and intensity of the drought events that took place in several climatic regions (Núñez-López et al., 2005); un map of spatial distribution of the SPI for the northern region of Mexico, in the States of Sonora, Sinaloa, Durango and Chihuahua. The generated map will be published in a section on the CEISS web page (www.sequia.edu.mx), together with the monthly bulletin available to the public in general; it is monitoring to an annual scale, the tendencies of the deficits or surplus of the runoff volumes on three of the main dams in the State of Chihuahua Conclusions The Drought Monitoring System in Chihuahua complies with the following international rules for the

  2. Predicting nitrate contamination in recently recharged groundwater: High Plains regional aquifer

    NASA Astrophysics Data System (ADS)

    Gurdak, J. J.; Qi, S. L.

    2004-12-01

    The High Plains regional aquifer, a nationally important groundwater resource, has widespread elevated nitrate concentrations in recently recharged groundwater. This condition has created a potential health concern for nearly 2 million people who rely on the aquifer for drinking water. Concentrations and spatial distribution of nitrate are influenced by anthropogenic activity, particularly from non-point source contamination. A novel groundwater vulnerability assessment encompassing the entire High Plains aquifer is presented that predicts areas of the aquifer where nitrate concentrations are expected to exceed a background value of 4 mg/L as N in recently recharged groundwater, defined as less than 50-years old. This model couples particle-tracking simulations and multivariate logistic regression analysis within a GIS framework, thereby incorporating site-specific hydrogeologic parameters and the groundwater flow regime. Contributing areas, delineated by a 90-degree sector, represented the capture zone up gradient from the well location and defined the area for GIS-based extraction of explanatory variables for statistical modeling. Particle-tracking simulations identified the appropriate radial length for the sector and well screen depths corresponding to recently recharged groundwater. Horizontal and vertical particle movements were most sensitive to hydraulic conductivity and estimates of recharge, respectively. The final multivariate logistic regression model demonstrated statistical significance (p < 0.001), produced an excellent model fit (R2 = 0.912), and was validated with an independent nitrate data set (R2 = 0.856). Statistically significant explanatory variables in the contributing areas included percent agricultural land (p < 0.001), depth to water table (p = 0.001), soil infiltration score (p = 0.013), nitrogen applied as fertilizer on irrigated agricultural land (p = 0.050), and percent clay in the unsaturated zone (p = 0.040). Predicted groundwater

  3. Ground motion prediction and earthquake scenarios in the volcanic region of Mt. Etna (Southern Italy

    NASA Astrophysics Data System (ADS)

    Langer, Horst; Tusa, Giuseppina; Luciano, Scarfi; Azzaro, Raffaela

    2013-04-01

    One of the principal issues in the assessment of seismic hazard is the prediction of relevant ground motion parameters, e. g., peak ground acceleration, radiated seismic energy, response spectra, at some distance from the source. Here we first present ground motion prediction equations (GMPE) for horizontal components for the area of Mt. Etna and adjacent zones. Our analysis is based on 4878 three component seismograms related to 129 seismic events with local magnitudes ranging from 3.0 to 4.8, hypocentral distances up to 200 km, and focal depth shallower than 30 km. Accounting for the specific seismotectonic and geological conditions of the considered area we have divided our data set into three sub-groups: (i) Shallow Mt. Etna Events (SEE), i.e., typically volcano-tectonic events in the area of Mt. Etna having a focal depth less than 5 km; (ii) Deep Mt. Etna Events (DEE), i.e., events in the volcanic region, but with a depth greater than 5 km; (iii) Extra Mt. Etna Events (EEE), i.e., purely tectonic events falling outside the area of Mt. Etna. The predicted PGAs for the SEE are lower than those predicted for the DEE and the EEE, reflecting their lower high-frequency energy content. We explain this observation as due to the lower stress drops. The attenuation relationships are compared to the ones most commonly used, such as by Sabetta and Pugliese (1987)for Italy, or Ambraseys et al. (1996) for Europe. Whereas our GMPEs are based on small earthquakes, the magnitudes covered by the two above mentioned attenuation relationships regard moderate to large magnitudes (up to 6.8 and 7.9, respectively). We show that the extrapolation of our GMPEs to magnitues beyond the range covered by the data is misleading; at the same time also the afore mentioned relationships fail to predict ground motion parameters for our data set. Despite of these discrepancies, we can exploit our data for setting up scenarios for strong earthquakes for which no instrumental recordings are

  4. The Use of Fluid Mechanics to Predict Regions of Microscopic Thrombus Formation in Pulsatile VADs.

    PubMed

    Topper, Stephen R; Navitsky, Michael A; Medvitz, Richard B; Paterson, Eric G; Siedlecki, Christopher A; Slattery, Margaret J; Deutsch, Steven; Rosenberg, Gerson; Manning, Keefe B

    2014-03-01

    We compare the velocity and shear obtained from particle image velocimetry (PIV) and computational fluid dynamics (CFD) in a pulsatile ventricular assist device (VAD) to further test our thrombus predictive methodology using microscopy data from an explanted VAD. To mimic physiological conditions in vitro, a mock circulatory loop is used with a blood analog that matched blood's viscoelastic behavior at 40% hematocrit. Under normal physiologic pressures and for a heart rate of 75 bpm, PIV data is acquired and wall shear maps are produced. The resolution of the PIV shear rate calculations are tested using the CFD and found to be in the same range. A bovine study, using a model of the 50 cc Penn State V-2 VAD, for 30 days at a constant beat rate of 75 beats per minute (bpm) provides the microscopic data whereby after the 30 days, the device is explanted and the sac surface analyzed using scanning electron microscopy (SEM) and, after immunofluorescent labeling for platelets and fibrin, confocal microscopy. Areas are examined based on PIV measurements and CFD, with special attention to low shear regions where platelet and fibrin deposition are most likely to occur. Data collected within the outlet port in a direction normal to the front wall of the VAD shows that some regions experience wall shear rates less than 500 s(-1), which increases the likelihood of platelet and fibrin deposition. Despite only one animal study, correlations between PIV, CFD, and in vivo data show promise. Deposition probability is quantified by the thrombus susceptibility potential, a calculation to correlate low shear and time of shear with deposition.

  5. Advances in Toxico-Cheminformatics: Supporting a New Paradigm for Predictive Toxicology

    EPA Science Inventory

    EPA’s National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction through the harnessing of legacy toxicity data, creation of data linkages, and generation of new high-throughput screening (HTS) data. The D...

  6. The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements

    NASA Astrophysics Data System (ADS)

    Lucas, S. E.; Todd, J. F.

    2015-12-01

    The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). The CVP Program currently supports multiple projects in areas that are aimed at improved representation of physical processes in global models. Some of the topics that are currently funded include: i) Improved Understanding of Intraseasonal Tropical Variability - DYNAMO field campaign and post -field projects, and the new climate model improvement teams focused on MJO processes; ii) Climate Process Teams (CPTs, co-funded with NSF) with projects focused on Cloud macrophysical parameterization and its application to aerosol indirect effects, and Internal-Wave Driven Mixing in Global Ocean Models; iii) Improved Understanding of Tropical Pacific Processes, Biases, and Climatology; iv) Understanding Arctic Sea Ice Mechanism and Predictability;v) AMOC Mechanisms and Decadal Predictability Recent results from CVP-funded projects will be summarized. Additional information can be found at http://cpo.noaa.gov/CVP.

  7. In silico assessment of the acute toxicity of chemicals: recent advances and new model for multitasking prediction of toxic effect.

    PubMed

    Kleandrova, Valeria V; Luan, Feng; Speck-Planche, Alejandro; Cordeiro, M Natália D S

    2015-01-01

    The assessment of acute toxicity is one of the most important stages to ensure the safety of chemicals with potential applications in pharmaceutical sciences, biomedical research, or any other industrial branch. A huge and indiscriminate number of toxicity assays have been carried out on laboratory animals. In this sense, computational approaches involving models based on quantitative-structure activity/toxicity relationships (QSAR/QSTR) can help to rationalize time and financial costs. Here, we discuss the most significant advances in the last 6 years focused on the use of QSAR/QSTR models to predict acute toxicity of drugs/chemicals in laboratory animals, employing large and heterogeneous datasets. The advantages and drawbacks of the different QSAR/QSTR models are analyzed. As a contribution to the field, we introduce the first multitasking (mtk) QSTR model for simultaneous prediction of acute toxicity of compounds by considering different routes of administration, diverse breeds of laboratory animals, and the reliability of the experimental conditions. The mtk-QSTR model was based on artificial neural networks (ANN), allowing the classification of compounds as toxic or non-toxic. This model correctly classified more than 94% of the 1646 cases present in the whole dataset, and its applicability was demonstrated by performing predictions of different chemicals such as drugs, dietary supplements, and molecules which could serve as nanocarriers for drug delivery. The predictions given by the mtk-QSTR model are in very good agreement with the experimental results. PMID:25694074

  8. In silico assessment of the acute toxicity of chemicals: recent advances and new model for multitasking prediction of toxic effect.

    PubMed

    Kleandrova, Valeria V; Luan, Feng; Speck-Planche, Alejandro; Cordeiro, M Natália D S

    2015-01-01

    The assessment of acute toxicity is one of the most important stages to ensure the safety of chemicals with potential applications in pharmaceutical sciences, biomedical research, or any other industrial branch. A huge and indiscriminate number of toxicity assays have been carried out on laboratory animals. In this sense, computational approaches involving models based on quantitative-structure activity/toxicity relationships (QSAR/QSTR) can help to rationalize time and financial costs. Here, we discuss the most significant advances in the last 6 years focused on the use of QSAR/QSTR models to predict acute toxicity of drugs/chemicals in laboratory animals, employing large and heterogeneous datasets. The advantages and drawbacks of the different QSAR/QSTR models are analyzed. As a contribution to the field, we introduce the first multitasking (mtk) QSTR model for simultaneous prediction of acute toxicity of compounds by considering different routes of administration, diverse breeds of laboratory animals, and the reliability of the experimental conditions. The mtk-QSTR model was based on artificial neural networks (ANN), allowing the classification of compounds as toxic or non-toxic. This model correctly classified more than 94% of the 1646 cases present in the whole dataset, and its applicability was demonstrated by performing predictions of different chemicals such as drugs, dietary supplements, and molecules which could serve as nanocarriers for drug delivery. The predictions given by the mtk-QSTR model are in very good agreement with the experimental results.

  9. Predicting Stroop Effect from Spontaneous Neuronal Activity: A Study of Regional Homogeneity

    PubMed Central

    Liu, Congcong; Chen, Zhencai; Wang, Ting; Tang, Dandan; Hitchman, Glenn; Sun, Jiangzhou; Zhao, Xiaoyue; Wang, Lijun; Chen, Antao

    2015-01-01

    The Stroop effect is one of the most robust and well-studied phenomena in cognitive psychology and cognitive neuroscience. However, little is known about the relationship between intrinsic brain activity and the individual differences of this effect. In the present study, we explored this issue by examining whether resting-state functional magnetic resonance imaging (rs-fMRI) signals could predict individual differences in the Stroop effect of healthy individuals. A partial correlation analysis was calculated to examine the relationship between regional homogeneity (ReHo) and Stroop effect size, while controlling for age, sex, and framewise displacement (FD). The results showed positive correlations in the left inferior frontal gyrus (LIFG), the left insula, the ventral anterior cingulate cortex (vACC), and the medial frontal gyrus (MFG), and negative correlation in the left precentral gyrus (LPG). These results indicate the possible influences of the LIFG, the left insula, and the LPG on the efficiency of cognitive control, and demonstrate that the key nodes of default mode network (DMN) may be important in goal-directed behavior and/or mental effort during cognitive control tasks. PMID:25938442

  10. Brain activity in valuation regions while thinking about the future predicts individual discount rates.

    PubMed

    Cooper, Nicole; Kable, Joseph W; Kim, B Kyu; Zauberman, Gal

    2013-08-01

    People vary widely in how much they discount delayed rewards, yet little is known about the sources of these differences. Here we demonstrate that neural activity in ventromedial prefrontal cortex (VMPFC) and ventral striatum (VS) when human subjects are asked to merely think about the future--specifically, to judge the subjective length of future time intervals--predicts delay discounting. High discounters showed lower activity for longer time delays, while low discounters showed the opposite pattern. Our results demonstrate that the correlation between VMPFC and VS activity and discounting occurs even in the absence of choices about future rewards, and does not depend on a person explicitly evaluating future outcomes or judging their self-relevance. This suggests a link between discounting and basic processes involved in thinking about the future, such as temporal perception. Our results also suggest that reducing impatience requires not suppression of VMPFC and VS activity altogether, but rather modulation of how these regions respond to the present versus the future.

  11. Brain Activity in Valuation Regions while Thinking about the Future Predicts Individual Discount Rates

    PubMed Central

    Cooper, Nicole; Kim, B. Kyu; Zauberman, Gal

    2013-01-01

    People vary widely in how much they discount delayed rewards, yet little is known about the sources of these differences. Here we demonstrate that neural activity in ventromedial prefrontal cortex (VMPFC) and ventral striatum (VS) when human subjects are asked to merely think about the future—specifically, to judge the subjective length of future time intervals—predicts delay discounting. High discounters showed lower activity for longer time delays, while low discounters showed the opposite pattern. Our results demonstrate that the correlation between VMPFC and VS activity and discounting occurs even in the absence of choices about future rewards, and does not depend on a person explicitly evaluating future outcomes or judging their self-relevance. This suggests a link between discounting and basic processes involved in thinking about the future, such as temporal perception. Our results also suggest that reducing impatience requires not suppression of VMPFC and VS activity altogether, but rather modulation of how these regions respond to the present versus the future. PMID:23926268

  12. Brain activity in valuation regions while thinking about the future predicts individual discount rates.

    PubMed

    Cooper, Nicole; Kable, Joseph W; Kim, B Kyu; Zauberman, Gal

    2013-08-01

    People vary widely in how much they discount delayed rewards, yet little is known about the sources of these differences. Here we demonstrate that neural activity in ventromedial prefrontal cortex (VMPFC) and ventral striatum (VS) when human subjects are asked to merely think about the future--specifically, to judge the subjective length of future time intervals--predicts delay discounting. High discounters showed lower activity for longer time delays, while low discounters showed the opposite pattern. Our results demonstrate that the correlation between VMPFC and VS activity and discounting occurs even in the absence of choices about future rewards, and does not depend on a person explicitly evaluating future outcomes or judging their self-relevance. This suggests a link between discounting and basic processes involved in thinking about the future, such as temporal perception. Our results also suggest that reducing impatience requires not suppression of VMPFC and VS activity altogether, but rather modulation of how these regions respond to the present versus the future. PMID:23926268

  13. Predicting stroop effect from spontaneous neuronal activity: a study of regional homogeneity.

    PubMed

    Liu, Congcong; Chen, Zhencai; Wang, Ting; Tang, Dandan; Hitchman, Glenn; Sun, Jiangzhou; Zhao, Xiaoyue; Wang, Lijun; Chen, Antao

    2015-01-01

    The Stroop effect is one of the most robust and well-studied phenomena in cognitive psychology and cognitive neuroscience. However, little is known about the relationship between intrinsic brain activity and the individual differences of this effect. In the present study, we explored this issue by examining whether resting-state functional magnetic resonance imaging (rs-fMRI) signals could predict individual differences in the Stroop effect of healthy individuals. A partial correlation analysis was calculated to examine the relationship between regional homogeneity (ReHo) and Stroop effect size, while controlling for age, sex, and framewise displacement (FD). The results showed positive correlations in the left inferior frontal gyrus (LIFG), the left insula, the ventral anterior cingulate cortex (vACC), and the medial frontal gyrus (MFG), and negative correlation in the left precentral gyrus (LPG). These results indicate the possible influences of the LIFG, the left insula, and the LPG on the efficiency of cognitive control, and demonstrate that the key nodes of default mode network (DMN) may be important in goal-directed behavior and/or mental effort during cognitive control tasks.

  14. [The use of information processes indices for prediction of sympathectomy efficiency in complex regional pain syndrome].

    PubMed

    Kuropatkin, A I

    2010-01-01

    Key significance of information processes for ensuring optimal sanogenesis was shown by wavelet-analysis of skin microvascular blood flow oscillations at 64 patients with complex regional pain syndrome after sympathectomy Early reorganization of information in trophotropic direction at the level of microvascular tissue systems, its predomination and conservation all along the microvascular networks facilitate optimal realization of adaptive reactions and, as a result, are conductive to maximum treatment efficiency. In these cases complete elimination of disease and achievement of excellent treatment results were possible. Maximum treatment efficiency could not be reached without the above-mentioned information changing. On the contrary predomination and conservation of ergotropic information at the early periods after surgery were unfavourable to prediction of clinical results of sympathectomy Tissue desympathisation is not required to formation of information trophotropic purposefulness in microvascular networks; it is enough to achieve certain threshold of sympathetic activity decrease. The results of this work may be useful for investigation of physiological mechanisms of information treatment technologies (homeopathy etc.).

  15. A statistical framework to predict functional non-coding regions in the human genome through integrated analysis of annotation data.

    PubMed

    Lu, Qiongshi; Hu, Yiming; Sun, Jiehuan; Cheng, Yuwei; Cheung, Kei-Hoi; Zhao, Hongyu

    2015-05-27

    Identifying functional regions in the human genome is a major goal in human genetics. Great efforts have been made to functionally annotate the human genome either through computational predictions, such as genomic conservation, or high-throughput experiments, such as the ENCODE project. These efforts have resulted in a rich collection of functional annotation data of diverse types that need to be jointly analyzed for integrated interpretation and annotation. Here we present GenoCanyon, a whole-genome annotation method that performs unsupervised statistical learning using 22 computational and experimental annotations thereby inferring the functional potential of each position in the human genome. With GenoCanyon, we are able to predict many of the known functional regions. The ability of predicting functional regions as well as its generalizable statistical framework makes GenoCanyon a unique and powerful tool for whole-genome annotation. The GenoCanyon web server is available at http://genocanyon.med.yale.edu.

  16. Prediction of postoperative loss of lung function in patients with malignant lung mass. Quantitative regional ventilation-perfusion scanning

    SciTech Connect

    Ryo, U.Y. )

    1990-05-01

    The quantitative measurement of regional ventilation and perfusion distribution is simply and reliably accomplished by using routinely available radioactive gas and perfusion lung scanning agents, and a large field-of-view gamma camera with an on-line computer. The preoperative prediction of postsurgical loss in lung function can be made accurately by using the quantitative ventilation-perfusion lung scan technique. Either a regional ventilation study or perfusion study may be used for the prediction, but analysis of regional ventilation distribution appears to be a better parameter than that of perfusion distribution for the prediction of postoperative loss of FEV1. In the rare case of a patient with a marked ventilation-perfusion deficit, quantitative distribution of both ventilation and perfusion may be needed for an accurate assessment of postsurgical lung function. 18 references.

  17. A Research Program for Improving Heat Transfer Prediction Capability for the Laminar to Turbulent Transition Region of Turbine Vanes/Blades

    NASA Technical Reports Server (NTRS)

    Simon, Frederick F.

    2007-01-01

    A program sponsored by the National Aeronautics and Space Administration (NASA) for the investigation of the heat transfer in the transition region of turbine vanes and blades with the object of improving the capability for predicting heat transfer is described,. The accurate prediction of gas-side heat transfer is important to the determination of turbine longevity, engine performance and developmental costs. The need for accurate predictions will become greater as the operating temperatures and stage loading levels of advanced turbine engines increase. The present methods for predicting transition shear stress and heat transfer on turbine blades are based on incomplete knowledge and are largely empirical. To meet the objectives of the NASA program, a team approach consisting of researchers from government, universities, a research institute, and a small business is presented. The research is divided into areas of experimentation, direct numerical simulation (DNS) and turbulence modeling. A summary of the results to date is given for the above research areas in a high-disturbance environment (bypass transition) with a discussion of the model development necessary for use in numerical codes.

  18. Advanced Predictive Model and Real-World Results for Medium Concentration CPV

    NASA Astrophysics Data System (ADS)

    Karney, Bruce; Finot, Marc

    2011-12-01

    Skyline Solar has developed a novel medium concentration PV product. The system is a linear concentrator that tracks the sun with a 1-axis horizontal tracker. Reflectors are used to concentrate sunlight 7-50x using non-imaging optics. The receivers use Silicon cells and passive cooling. The product's design has been guided by a detailed Performance Prediction Tool (PPT) that relates component characteristics and climate data to the overall energy production. In contrast with other tools, the PPT captures the non-linearity of conditions such as weather, system architecture (stringing, shadow management) and the value of energy as a function of time of day and season. This paper describes the key elements of the PPT and compares its predictions to real-world results from different locations with significantly different DNI. Moderate DNI sites are San Jose, California and Kona, Hawaii. The higher DNI site is Nipton, California (DNI ˜7.2). Skyline's PPT accurately predicts the energy harvest for two Skyline Solar systems including the HGS 1000 and the new Skyline Solar X14 System.

  19. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

    PubMed

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets. PMID:27532883

  20. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science

    PubMed Central

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets. PMID:27532883

  1. Louisiana: a model for advancing regional e-Research through cyberinfrastructure

    PubMed Central

    Katz, Daniel S.; Allen, Gabrielle; Cortez, Ricardo; Cruz-Neira, Carolina; Gottumukkala, Raju; Greenwood, Zeno D.; Guice, Les; Jha, Shantenu; Kolluru, Ramesh; Kosar, Tevfik; Leger, Lonnie; Liu, Honggao; McMahon, Charlie; Nabrzyski, Jarek; Rodriguez-Milla, Bety; Seidel, Ed; Speyrer, Greg; Stubblefield, Michael; Voss, Brian; Whittenburg, Scott

    2009-01-01

    Louisiana researchers and universities are leading a concentrated, collaborative effort to advance statewide e-Research through a new cyberinfrastructure: computing systems, data storage systems, advanced instruments and data repositories, visualization environments and people, all linked together by software programs and high-performance networks. This effort has led to a set of interlinked projects that have started making a significant difference in the state, and has created an environment that encourages increased collaboration, leading to new e-Research. This paper describes the overall effort, the new projects and environment and the results to date. PMID:19451102

  2. Thermodynamic calculation and interatomic potential to predict the favored composition region for the Cu-Zr-Al metallic glass formation.

    PubMed

    Cui, Y Y; Wang, T L; Li, J H; Dai, Y; Liu, B X

    2011-03-01

    For the Cu-Zr-Al system, the glass forming compositions were firstly calculated based on the extended Miedema's model, suggesting that the amorphous phase could be thermodynamically favored over a large composition region. An n-body potential was then constructed under the smoothed and long-range second-moment-approximation of tight-binding formulism. Applying the constructed Cu-Zr-Al potential, molecular dynamics simulations were conducted using solid solution models to compare relative stability of crystalline solid solution versus its disordered counterpart. Simulations reveal that the physical origin of metallic glass formation is crystalline lattice collapsing while solute concentration exceeding the critical value, thus predicting a hexagonal composition region, within which the Cu-Zr-Al ternary metallic glass formation is energetically favored. The molecular dynamics simulations predicted composition region is defined as the quantitative glass-forming-ability or glass-forming-region of the Cu-Zr-Al system. PMID:21229150

  3. [Research advances in simulating regional crop growth under water stress by remote sensing].

    PubMed

    Zhang, Li; Wang, Shili; Ma, Yuping

    2005-06-01

    It is of practical significance to simulate the regional crop growth under water stress, especially at regional scale. Combined with remote sensing information, crop growth simulation model could provide an effective way to estimate the regional crop growth, development and yield formation under water stress. In this paper, related research methods and results were summarized, and some problems needed to be further studied and resolved were discussed.

  4. Prediction of Unsteady Blade Surface Pressures on an Advanced Propeller at an Angle of Attack

    NASA Technical Reports Server (NTRS)

    Nallasamy, M.; Groeneweg, J. F.

    1989-01-01

    The numerical solution of the unsteady, three-dimensional, Euler equations is considered in order to obtain the blade surface pressures of an advanced propeller at an angle of attack. The specific configuration considered is the SR7L propeller at cruise conditions with a 4.6 deg inflow angle corresponding to the plus 2 deg nacelle tilt of the Propeller Test Assessment (PTA) flight test condition. The results indicate nearly sinusoidal response of the blade loading, with angle of attack. For the first time, detailed variations of the chordwise loading as a function of azimuthal angle are presented. It is observed that the blade is lightly loaded for part of the revolution and shocks appear from hub to about 80 percent radial station for the highly loaded portion of the revolution.

  5. Predictive and prognostic biomarkers for neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

    PubMed

    Lim, S H; Chua, W; Henderson, C; Ng, W; Shin, J-S; Chantrill, L; Asghari, R; Lee, C S; Spring, K J; de Souza, P

    2015-10-01

    Locally advanced rectal cancer is regularly treated with trimodality therapy consisting of neoadjuvant chemoradiation, surgery and adjuvant chemotherapy. There is a need for biomarkers to assess treatment response, and aid in stratification of patient risk to adapt and personalise components of the therapy. Currently, pathological stage and tumour regression grade are used to assess response. Experimental markers include proteins involved in cell proliferation, apoptosis, angiogenesis, the epithelial to mesenchymal transition and microsatellite instability. As yet, no single marker is sufficiently robust to have clinical utility. Microarrays that screen a tumour for multiple promising candidate markers, gene expression and microRNA profiling will likely have higher yield and it is expected that a combination or panel of markers would prove most useful. Moving forward, utilising serial samples of circulating tumour cells or circulating nucleic acids can potentially allow us to demonstrate tumour heterogeneity, document mutational changes and subsequently measure treatment response. PMID:26032919

  6. Performance Prediction for a Hockey-Puck Silicon Crystal Monochromator at the Advanced Photon Source

    NASA Astrophysics Data System (ADS)

    Liu, Zunping; Rosenbaum, Gerd; Navrotski, Gary

    2014-03-01

    One of the Key Performance Parameters of the upgrade of the Advanced Photon Source (APS) is the increase of the storage ring current from 100 to 150 mA. In order to anticipate the impact of this increased heat load on the X-ray optics of the beamlines, the APS has implemented a systematic review, by means of finite element analysis and computational fluid dynamics, of the thermal performance of the different types of monochromators installed at the highest-heat-load insertion device beamlines. We present here simulations of the performance of a directly liquid nitrogen-cooled silicon crystal, the hockey-puck design. Calculations of the temperature and slope error at multiple ring currents under multiple operational conditions, including the influence of power, cooling, and diffraction surface thickness are included.

  7. Regional prediction of soil organic carbon content over croplands using airborne hyperspectral data

    NASA Astrophysics Data System (ADS)

    Vaudour, Emmanuelle; Gilliot, Jean-Marc; Bel, Liliane; Lefebvre, Josias; Chehdi, Kacem

    2015-04-01

    This study was carried out in the framework of the Prostock-Gessol3 and the BASC-SOCSENSIT projects, dedicated to the spatial monitoring of the effects of exogenous organic matter land application on soil organic carbon storage. It aims at identifying the potential of airborne hyperspectral AISA-Eagle data for predicting the topsoil organic carbon (SOC) content of bare cultivated soils over a large peri-urban area (221 km2) with both contrasted soils and SOC contents, located in the western region of Paris, France. Soils comprise hortic or glossic luvisols, calcaric, rendzic cambisols and colluvic cambisols. Airborne AISA-Eagle data (400-1000 nm, 126 bands) with 1 m-resolution were acquired on 17 April 2013 over 13 tracks which were georeferenced. Tracks were atmospherically corrected using a set of 22 synchronous field spectra of both bare soils, black and white targets and impervious surfaces. Atmospherically corrected track tiles were mosaicked at a 2 m-resolution resulting in a 66 Gb image. A SPOT4 satellite image was acquired the same day in the framework of the SPOT4-Take Five program of the French Space Agency (CNES) which provided it with atmospheric correction. The land use identification system layer (RPG) of 2012 was used to mask non-agricultural areas, then NDVI calculation and thresholding enabled to map agricultural fields with bare soil. All 18 sampled sites known to be bare at this very date were correctly included in this map. A total of 85 sites sampled in 2013 or in the 3 previous years were identified as bare by means of this map. Predictions were made from the mosaic spectra which were related to topsoil SOC contents by means of partial least squares regression (PLSR). Regression robustness was evaluated through a series of 1000 bootstrap data sets of calibration-validation samples. The use of the total sample including 27 sites under cloud shadows led to non-significant results. Considering 43 sites outside cloud shadows only, median

  8. Improving the Gap between Model Predictions and Observations of Formaldehyde over the Remote Marine Regions

    NASA Astrophysics Data System (ADS)

    Trueblood, J.; Meskhidze, N.

    2013-05-01

    Formaldehyde (HCHO) is a ubiquitous oxidation product that exists in polluted rural and urban areas, as well as remote background sites where it is an important photochemical intermediate. HCHO levels of up to six times above what is typically predicted by photochemical models have been reported over the Marine Boundary Layer (MBL). As proposed mechanisms for HCHO production remain to be insufficient to explain such large discrepancies between model predictions and measured values, the role of marine regions in the creation of HCHO continues to be one of the largest sources of uncertainty in current global chemistry-transport models. Here we examine the viability of a proposed mechanism for the photochemical production of formaldehyde involving aerosols enriched with biologically produced organic matter. In this study, the phytoplankton Emiliania Huxleyi was incubated in autoclaved seawater contained within a 9 liter Pyrex glass bottle. Quantitative analysis of the enrichment of transparent exopolymer particles (TEP) and other biologically produced organic matter (dissolved and particulate) in the surface microlayer was carried out by employing Alldredge's alcian blue staining technique. To produce organic aerosols, enriched seawater was bubbled with hydrocarbon free air using a sintered glass filter placed 5 cm below the surface. Utilizing a mixed flow reaction scheme, produced aerosols were then pushed through stainless steel flow tubes into a separate 9-liter Pyrex glass container acting as a residence chamber. The container was surrounded with six Ushio 9W Midrange UVB lights to allow for the irradiation of aerosols at 306 nm. A flow rate of approximately 0.1 l/min allowed for an average aerosol residence time of 90 minutes inside the residence chamber. All air from the chamber was then passed through a 5" long Pyrex desorber tube packed with 60/80 Tenax that had been soaked in the derivatizing agent pentafluorophenyl hydrazine (PFPH). Subsequent thermal

  9. Acute hospital care is the chief driver of regional spending variation in Medicare patients with advanced cancer.

    PubMed

    Brooks, Gabriel A; Li, Ling; Uno, Hajime; Hassett, Michael J; Landon, Bruce E; Schrag, Deborah

    2014-10-01

    The root causes of regional variation in medical spending are poorly understood and vary by clinical condition. To identify drivers of regional spending variation for Medicare patients with advanced cancer, we used linked Surveillance, Epidemiology, and End Results program (SEER)-Medicare data from the period 2004-10. We broke down Medicare spending into thirteen cancer-relevant service categories. We then calculated the contribution of each category to spending and regional spending variation. Acute hospital care was the largest component of spending and the chief driver of regional spending variation, accounting for 48 percent of spending and 67 percent of variation. In contrast, chemotherapy accounted for 16 percent of spending and 10 percent of variation. Hospice care constituted 5 percent of spending. However, variation in hospice spending was fully offset by opposing variation in other categories. Our analysis suggests that the strategy with the greatest potential to improve the value of care for patients with advanced cancer is to reduce reliance on acute hospital care for this patient population.

  10. Application of Suomi-NPP Green Vegetation Fraction and NUCAPS for Improving Regional Numerical Weather Prediction

    NASA Technical Reports Server (NTRS)

    Case, Jonathan L.; Berndt, Emily B.; Srikishen, Jayanthi; Zavodsky, Bradley T.

    2014-01-01

    The NASA SPoRT Center is working to incorporate Suomi-NPP products into its research and transition activities to improve regional numerical weather prediction (NWP). Specifically, SPoRT seeks to utilize two data products from NOAA/NESDIS: (1) daily global VIIRS green vegetation fraction (GVF), and (2) NOAA Unique CrIS and ATMS Processing System (NUCAPS) temperature and moisture retrieved profiles. The goal of (1) is to improve the representation of vegetation in the Noah land surface model (LSM) over existing climatological GVF datasets in order to improve the land-atmosphere energy exchanges in NWP models and produce better temperature, moisture, and precipitation forecasts. The goal of (2) is to assimilate NUCAPS retrieved profiles into the Gridpoint Statistical Interpolation (GSI) data assimilation system to assess the impact on a summer pre-frontal convection case. Most regional NWP applications make use of a monthly GVF climatology for use in the Noah LSM within the Weather Research and Forecasting (WRF) model. The GVF partitions incoming energy into direct surface heating/evaporation over bare soil versus evapotranspiration processes over vegetated surfaces. Misrepresentations of the fractional coverage of vegetation during anomalous weather/climate regimes (e.g., early/late bloom or freeze; drought) can lead to poor NWP model results when land-atmosphere feedback is important. SPoRT has been producing a daily MODIS GVF product based on the University of Wisconsin Direct Broadcast swaths of Normalized Difference Vegetation Index (NDVI). While positive impacts have been demonstrated in the WRF model for some cases, the reflectances composing these NDVI do not correct for atmospheric aerosols nor satellite view angle, resulting in temporal noisiness at certain locations (especially heavy vegetation). The method behind the NESDIS VIIRS GVF is expected to alleviate the issues seen in the MODIS GVF real-time product, thereby offering a higher-quality dataset for

  11. Predicting the number and sizes of IBD regions among family members and evaluating the family size requirement for linkage studies.

    PubMed

    Yang, Wanling; Wang, Zhanyong; Wang, Lusheng; Sham, Pak-Chung; Huang, Peng; Lau, Yu Lung

    2008-12-01

    With genotyping of high-density single nucleotide polymorphisms (SNPs) replacing that of microsatellite markers in linkage studies, it becomes possible to accurately determine the genomic regions shared identity by descent (IBD) by family members. In addition to evaluating the likelihood of linkage for a region with the underlining disease (the LOD score approach), an appropriate question to ask is what would be the expected number and sizes of IBD regions among the affecteds, as there could be more than one region reaching the maximum achievable LOD score for a given family. Here, we introduce a computer program to allow the prediction of the total number of IBD regions among family members and their sizes. Reversely, it can be used to predict the portion of the genome that can be excluded from consideration according to the family size and user-defined inheritance mode and penetrance. Such information has implications on the feasibility of conducting linkage analysis on a given family of certain size and structure or on a few small families when interfamily homogeneity can be assumed. It can also help determine the most relevant members to be genotyped for such a study. Simulation results showed that the IBD regions containing true mutations are usually larger than regions IBD due to random chance. We have made use of this feature in our program to allow evaluation of the identified IBD regions based on Bayesian probability calculation and simulation results.

  12. MicroRNA-31 Emerges as a Predictive Biomarker of Pathological Response and Outcome in Locally Advanced Rectal Cancer.

    PubMed

    Caramés, Cristina; Cristobal, Ion; Moreno, Víctor; Marín, Juan P; González-Alonso, Paula; Torrejón, Blanca; Minguez, Pablo; Leon, Ana; Martín, José I; Hernández, Roberto; Pedregal, Manuel; Martín, María J; Cortés, Delia; García-Olmo, Damian; Fernández, María J; Rojo, Federico; García-Foncillas, Jesús

    2016-01-01

    Neoadjuvant chemoradiotherapy (CRT) followed by total mesorectal excision has emerged as the standard treatment for locally advanced rectal cancer (LARC) patients. However, many cases do not respond to neoadjuvant CRT, suffering unnecessary toxicities and surgery delays. Thus, identification of predictive biomarkers for neoadjuvant CRT is a current clinical need. In the present study, microRNA-31 expression was measured in formalin-fixed paraffin-embedded (FFPE) biopsies from 78 patients diagnosed with LARC who were treated with neoadjuvant CRT. Then, the obtained results were correlated with clinical and pathological characteristics and outcome. High microRNA-31 (miR-31) levels were found overexpressed in 34.2% of cases. Its overexpression significantly predicted poor pathological response (p = 0.018) and worse overall survival (OS) (p = 0.008). The odds ratio for no pathological response among patients with miR-31 overexpression was 0.18 (Confidence Interval = 0.06 to 0.57; p = 0.003). Multivariate analysis corroborated the clinical impact of miR-31 in determining pathological response to neoadjuvant CRT as well as OS. Altogether, miR-31 quantification emerges as a novel valuable clinical tool to predict both pathological response and outcome in LARC patients. PMID:27271609

  13. MicroRNA-31 Emerges as a Predictive Biomarker of Pathological Response and Outcome in Locally Advanced Rectal Cancer

    PubMed Central

    Caramés, Cristina; Cristobal, Ion; Moreno, Víctor; Marín, Juan P.; González-Alonso, Paula; Torrejón, Blanca; Minguez, Pablo; Leon, Ana; Martín, José I.; Hernández, Roberto; Pedregal, Manuel; Martín, María J.; Cortés, Delia; García-Olmo, Damian; Fernández, María J.; Rojo, Federico; García-Foncillas, Jesús

    2016-01-01

    Neoadjuvant chemoradiotherapy (CRT) followed by total mesorectal excision has emerged as the standard treatment for locally advanced rectal cancer (LARC) patients. However, many cases do not respond to neoadjuvant CRT, suffering unnecessary toxicities and surgery delays. Thus, identification of predictive biomarkers for neoadjuvant CRT is a current clinical need. In the present study, microRNA-31 expression was measured in formalin-fixed paraffin-embedded (FFPE) biopsies from 78 patients diagnosed with LARC who were treated with neoadjuvant CRT. Then, the obtained results were correlated with clinical and pathological characteristics and outcome. High microRNA-31 (miR-31) levels were found overexpressed in 34.2% of cases. Its overexpression significantly predicted poor pathological response (p = 0.018) and worse overall survival (OS) (p = 0.008). The odds ratio for no pathological response among patients with miR-31 overexpression was 0.18 (Confidence Interval = 0.06 to 0.57; p = 0.003). Multivariate analysis corroborated the clinical impact of miR-31 in determining pathological response to neoadjuvant CRT as well as OS. Altogether, miR-31 quantification emerges as a novel valuable clinical tool to predict both pathological response and outcome in LARC patients. PMID:27271609

  14. MicroRNA-31 Emerges as a Predictive Biomarker of Pathological Response and Outcome in Locally Advanced Rectal Cancer.

    PubMed

    Caramés, Cristina; Cristobal, Ion; Moreno, Víctor; Marín, Juan P; González-Alonso, Paula; Torrejón, Blanca; Minguez, Pablo; Leon, Ana; Martín, José I; Hernández, Roberto; Pedregal, Manuel; Martín, María J; Cortés, Delia; García-Olmo, Damian; Fernández, María J; Rojo, Federico; García-Foncillas, Jesús

    2016-06-03

    Neoadjuvant chemoradiotherapy (CRT) followed by total mesorectal excision has emerged as the standard treatment for locally advanced rectal cancer (LARC) patients. However, many cases do not respond to neoadjuvant CRT, suffering unnecessary toxicities and surgery delays. Thus, identification of predictive biomarkers for neoadjuvant CRT is a current clinical need. In the present study, microRNA-31 expression was measured in formalin-fixed paraffin-embedded (FFPE) biopsies from 78 patients diagnosed with LARC who were treated with neoadjuvant CRT. Then, the obtained results were correlated with clinical and pathological characteristics and outcome. High microRNA-31 (miR-31) levels were found overexpressed in 34.2% of cases. Its overexpression significantly predicted poor pathological response (p = 0.018) and worse overall survival (OS) (p = 0.008). The odds ratio for no pathological response among patients with miR-31 overexpression was 0.18 (Confidence Interval = 0.06 to 0.57; p = 0.003). Multivariate analysis corroborated the clinical impact of miR-31 in determining pathological response to neoadjuvant CRT as well as OS. Altogether, miR-31 quantification emerges as a novel valuable clinical tool to predict both pathological response and outcome in LARC patients.

  15. Towards a unified modeling system of predicting the transport of radionuclides in coastal sea regions

    NASA Astrophysics Data System (ADS)

    Jung, Kyung Tae; Brovchenko, Igor; Maderich, Vladimir; Kim, Kyeong Ok; Qiao, Fangli

    2016-04-01

    We present in this talk a recent progress in developing a unified modeling system of predicting three-dimensional transport of radionuclides coupled with multiple-scale circulation, wave and suspended sediment modules, keeping in mind the application to coastal sea regions with non-uniform distribution of suspended and bed sediments of both cohesive and non-cohesive types. The model calculates the concentration fields of dissolved and particulate radionuclides in bottom sediment as well as in water column. The transfer of radioactivity between the water column and the pore water in the upper layer of the bottom sediment is governed by diffusion processes. The phase change between dissolved and particulate radionuclides is written in terms of absorption/desorption rates and distribution coefficients. The dependence of distribution coefficients is inversely proportional to the sediment particle size. The hydrodynamic numerical model SELFE that solves equations for the multiple-scale circulation, the wave action and sand transport on the unstructured grids has been used as a base model. We have extended the non-cohesive sediment module of SELFE to the form applicable to mixture of cohesive and non-cohesive sedimentary regimes by implementing an extended form of erosional rate and a flocculation model for the determination of settling velocity of cohesive flocs. Issues related to the calibration of the sediment transport model in the Yellow Sea are described. The radionuclide transport model with one-step transfer kinetics and single bed layer has been initially developed and then applied to Fukushima Daiichi nuclear accident. The model has been in this study verified through the comparison with measurements of 137Cs concentration in bed sediments. Preliminary application to the Yellow and East China Seas with a hypothetical release scenario are described. On-going development of the radionuclide transport model using two-step transfer kinetics and multiple bed layers

  16. The human endogenous retrovirus K Rev response element coincides with a predicted RNA folding region.

    PubMed Central

    Yang, J; Bogerd, H; Le, S Y; Cullen, B R

    2000-01-01

    Human endogenous retrovirus K (HERV-K) is the name given to an approximately 30-million-year-old family of endogenous retroviruses present at >50 copies per haploid human genome. Previously, the HERV-K were shown to encode a nuclear RNA export factor, termed K-Rev, that is the functional equivalent of the H-Rev protein encoded by human immunodeficiency virus type 1. HERV-K was also shown to contain a cis-acting target element, the HERV-K Rev response element (K-RRE), that allowed the nuclear export of linked RNA transcripts in the presence of either K-Rev or H-Rev. Here, we demonstrate that the functionally defined K-RRE coincides with a statistically highly significant unusual RNA folding region and present a potential RNA secondary structure for the approximately 416-nt K-RRE. Both in vitro and in vivo assays of sequence specific RNA binding were used to map two primary binding sites for K-Rev, and one primary binding site for H-Rev, within the K-RRE. Of note, all three binding sites map to discrete predicted RNA stem-loop subdomains within the larger K-RRE structure. Although almost the entire 416-nt K-RRE was required for the activation of nuclear RNA export in cells expressing K-Rev, mutational inactivation of the binding sites for K-Rev resulted in the selective loss of the K-RRE response to K-Rev but not to H-Rev. Together, these data strongly suggest that the K-RRE, like the H-RRE, coincides with an extensive RNA secondary structure and identify specific sites within the K-RRE that can recruit either K-Rev or H-Rev to HERV-K RNA transcripts. PMID:11105755

  17. Chesapeake Inundation Prediction System (CIPS): A regional prototype for a national problem

    USGS Publications Warehouse

    Stamey, B.; Smith, W.; Carey, K.; Garbin, D.; Klein, F.; Wang, Hongfang; Shen, J.; Gong, W.; Cho, J.; Forrest, D.; Friedrichs, C.; Boicourt, W.; Li, M.; Koterba, M.; King, D.; Titlow, J.; Smith, E.; Siebers, A.; Billet, J.; Lee, J.; Manning, Douglas R.; Szatkowski, G.; Wilson, D.; Ahnert, P.; Ostrowski, J.

    2007-01-01

    Recent Hurricanes Katrina and Isabel, among others, not only demonstrated their immense destructive power, but also revealed the obvious, crucial need for improved storm surge forecasting and information delivery to save lives and property in future storms. Current operational methods and the storm surge and inundation products do not adequately meet requirements needed by Emergency Managers (EMs) at local, state, and federal levels to protect and inform our citizens. The Chesapeake Bay Inundation Prediction System (CIPS) is being developed to improve the accuracy, reliability, and capability of flooding forecasts for tropical cyclones and non-tropical wind systems such as nor'easters by modeling and visualizing expected on-land storm-surge inundation along the Chesapeake Bay and its tributaries. An initial prototype has been developed by a team of government, academic and industry partners through the Chesapeake Bay Observing System (CBOS) of the Mid-Atlantic Coastal Ocean Observing Regional Association (MACOORA) within the Integrated Ocean Observing System (IOOS). For demonstration purposes, this initial prototype was developed for the tidal Potomac River in the Washington, DC metropolitan area. The preliminary information from this prototype shows great potential as a mechanism by which NOAA National Weather Service (NWS) Forecast Offices (WFOs) can provide more specific and timely forecasts of likely inundation in individual localities from significant storm surge events. This prototype system has shown the potential to indicate flooding at the street level, at time intervals of an hour or less, and with vertical resolution of one foot or less. This information will significantly improve the ability of EMs and first responders to mitigate life and property loss and improve evacuation capabilities in individual communities. This paper provides an update and expansion of the initial prototype that was presented at the Oceans 2006 MTS/IEEE Conference in Boston, MA

  18. Detailed regional predictions of N2O and NO emissions from a tropical highland rainforest

    NASA Astrophysics Data System (ADS)

    Gharahi Ghehi, N.; Werner, C.; Hufkens, K.; Kiese, R.; Van Ranst, E.; Nsabimana, D.; Wallin, G.; Klemedtsson, L.; Butterbach-Bahl, K.; Boeckx, P.

    2013-01-01

    Tropical forest soils are a significant source for the greenhouse gas N2O as well as for NO, a precursor of tropospheric ozone. However, current estimates are uncertain due to the limited number of field measurements. Furthermore, there is considerable spatial and temporal variability of N2O and NO emissions due to the variation of environmental conditions such as soil properties, vegetation characteristics and meteorology. In this study we used a process-based model (ForestDNDC-tropica) to estimate N2O and NO emissions from tropical highland forest (Nyungwe) soils in southwestern Rwanda. To extend the model inputs to regional scale, ForestDNDC-tropica was linked to an exceptionally large legacy soil dataset. There was agreement between N2O and NO measurements and the model predictions though the ForestDNDC-tropica resulted in considerable lower emissions for few sites. Low similarity was specifically found for acidic soil with high clay content and reduced metals, indicating that chemo-denitrification processes on acidic soils might be under-represented in the current ForestDNDC-tropica model. The results showed that soil bulk density and pH are the most influential factors driving spatial variations in soil N2O and NO emissions for tropical forest soils. The area investigated (1113 km2) was estimated to emit ca. 439 ± 50 t N2O-N yr-1 (2.8-5.5 kg N2O-N ha-1 yr-1) and 244 ± 16 t NO-N yr-1 (0.8-5.1 kg N ha-1 yr-1). Consistent with less detailed studies, we confirm that tropical highland rainforest soils are a major source of atmospheric N2O and NO.

  19. Application of NCEP Land Data Assimilation Systems for Global and Regional Drought Analysis, Monitoring and Prediction

    NASA Astrophysics Data System (ADS)

    Ek, M. B.; Xia, Y.; Meng, C. J.; Dong, J.

    2012-12-01

    Currently, NCEP/EMC includes three Land Data Assimilation Systems (LDASs): (1) Global LDAS (GLDAS), (2) North American LDAS (NLDAS), and (3) high resolution NLDAS on the Hydrologic Rainfall Analysis Project (HRAP) grid (HRAP-NLDAS). GLDAS was developed to provide initial conditions for NCEP coupled global weather and climate models, NLDAS to provide hydrometeorological products to support the National Integrated Drought Information System (NIDIS), and HRAP-NLDAS for long-term and near real-time high-resolution (~4 km) hydrometeorological products to support hydrological research and application at National Weather Service (NWS) River Forecast Centers and the Office of Hydrologic Development (OHD). These three systems are independent but closely related. The core model of the three systems is the NCEP operational land surface model (Noah) and the OHD operational hydrological model (SAC-HT); two additional land surface/hydrological models are used in NLDAS. The three systems are all moving towards being used for global and regional drought analysis, monitoring and prediction. The uncoupled GLDAS used the Noah land model in the Climate Forecast System Reanalysis (CFSR), with blended atmospheric model and observed precipitation forcing used to generate long-term (1979-present) global hydrometeorological products (at ~38 km) as part of the proposed Global Drought Information System (GDIS) in association with the NOAA Climate Program Office (CPO) Modeling, Analysis, Predictions and Projection (MAPP) Drought Task Force; use of GLDAS/Noah continues in the operational Climate Forecast System version 2 (CFSv2). NLDAS is a quasi-operational system that supports U.S. operational drought monitoring and seasonal hydrological prediction, in particular for NIDIS. One key application of the near real-time updates is drought monitoring over the Continental United States (CONUS), shown at the "NLDAS Drought" tab of the NLDAS website (www.emc.ncep.noaa.gov/mmb/nldas). NLDAS is mature

  20. LMethyR-SVM: Predict Human Enhancers Using Low Methylated Regions based on Weighted Support Vector Machines

    PubMed Central

    Xu, Jingting; Hu, Hong; Dai, Yang

    2016-01-01

    Background The identification of enhancers is a challenging task. Various types of epigenetic information including histone modification have been utilized in the construction of enhancer prediction models based on a diverse panel of machine learning schemes. However, DNA methylation profiles generated from the whole genome bisulfite sequencing (WGBS) have not been fully explored for their potential in enhancer prediction despite the fact that low methylated regions (LMRs) have been implied to be distal active regulatory regions. Method In this work, we propose a prediction framework, LMethyR-SVM, using LMRs identified from cell-type-specific WGBS DNA methylation profiles and a weighted support vector machine learning framework. In LMethyR-SVM, the set of cell-type-specific LMRs is further divided into three sets: reliable positive, like positive and likely negative, according to their resemblance to a small set of experimentally validated enhancers in the VISTA database based on an estimated non-parametric density distribution. Then, the prediction model is obtained by solving a weighted support vector machine. Results We demonstrate the performance of LMethyR-SVM by using the WGBS DNA methylation profiles derived from the human embryonic stem cell type (H1) and the fetal lung fibroblast cell type (IMR90). The predicted enhancers are highly conserved with a reasonable validation rate based on a set of commonly used positive markers including transcription factors, p300 binding and DNase-I hypersensitive sites. In addition, we show evidence that the large fraction of the LMethyR-SVM predicted enhancers are not predicted by ChromHMM in H1 cell type and they are more enriched for the FANTOM5 enhancers. Conclusion Our work suggests that low methylated regions detected from the WGBS data are useful as complementary resources to histone modification marks in developing models for the prediction of cell-type-specific enhancers. PMID:27662487

  1. "Well-determined" regions in RNA secondary structure prediction: analysis of small subunit ribosomal RNA.

    PubMed Central

    Zuker, M; Jacobson, A B

    1995-01-01

    Recent structural analyses of genomic RNAs from RNA coliphages suggest that both well-determined base paired helices and well-determined structural domains that are identified by "energy dot plot" analysis using the RNA folding package mfold, are likely to be predicted correctly. To test these observations with another group of large RNAs, we have analyzed 15 ribosomal RNAs. Published secondary structure models that were derived by comparative sequence analysis were used to evaluate the predicted structures. Both the optimal predicted fold and the predicted "energy dot plot" of each sequence were examined. Each prediction was obtained from a single computer run on an entire ribosomal RNA sequence. All predicted base pairs in optimal foldings were examined for agreement with proven base pairs in the comparative models. Our analyses show that the overall correspondence between the predicted and comparative models varied for different RNAs and ranges from a low of 27% to high of 70%, with a mean value of 49%. The correspondence improves to a mean value of 81% when the analysis is limited to well-determined helices. In addition to well-determined helices, large well-determined structural domains can be observed in "energy dot plots" of some 16S ribosomal RNAs. The predicted domains correspond closely with structural domains that are found by the comparative method in the same RNAs. Our analyses also show that measuring the agreement between predicted and comparative secondary structure models underestimates the reliability of structural prediction by mfold. PMID:7544463

  2. Next generation aerosol-cloud microphysics for advanced high-resolution climate predictions

    SciTech Connect

    Bennartz, Ralf; Hamilton, Kevin P; Phillips, Vaughan T.J.; Wang, Yuqing; Brenguier, Jean-Louis

    2013-01-14

    The three top-level project goals are: -We proposed to develop, test, and run a new, physically based, scale-independent microphysical scheme for those cloud processes that most strongly affect greenhouse gas scenarios, i.e. warm cloud microphysics. In particular, we propsed to address cloud droplet activation, autoconversion, and accretion. -The new, unified scheme was proposed to be derived and tested using the University of Hawaii's IPRC Regional Atmospheric Model (iRAM). -The impact of the new parameterizations on climate change scenarios will be studied. In particular, the sensitivity of cloud response to climate forcing from increased greenhouse gas concentrations will be assessed.

  3. Recovery Act. Development and Validation of an Advanced Stimulation Prediction Model for Enhanced Geothermal Systems

    SciTech Connect

    Gutierrez, Marte

    2013-12-31

    This research project aims to develop and validate an advanced computer model that can be used in the planning and design of stimulation techniques to create engineered reservoirs for Enhanced Geothermal Systems. The specific objectives of the proposal are to; Develop a true three-dimensional hydro-thermal fracturing simulator that is particularly suited for EGS reservoir creation; Perform laboratory scale model tests of hydraulic fracturing and proppant flow/transport using a polyaxial loading device, and use the laboratory results to test and validate the 3D simulator; Perform discrete element/particulate modeling of proppant transport in hydraulic fractures, and use the results to improve understand of proppant flow and transport; Test and validate the 3D hydro-thermal fracturing simulator against case histories of EGS energy production; and Develop a plan to commercialize the 3D fracturing and proppant flow/transport simulator. The project is expected to yield several specific results and benefits. Major technical products from the proposal include; A true-3D hydro-thermal fracturing computer code that is particularly suited to EGS; Documented results of scale model tests on hydro-thermal fracturing and fracture propping in an analogue crystalline rock; Documented procedures and results of discrete element/particulate modeling of flow and transport of proppants for EGS applications; and Database of monitoring data, with focus of Acoustic Emissions (AE) from lab scale modeling and field case histories of EGS reservoir creation.

  4. Correlation of predicted and measured thermal stresses on an advanced aircraft structure with similar materials

    NASA Technical Reports Server (NTRS)

    Jenkins, J. M.

    1979-01-01

    A laboratory heating test simulating hypersonic heating was conducted on a heat-sink type structure to provide basic thermal stress measurements. Six NASTRAN models utilizing various combinations of bar, shear panel, membrane, and plate elements were used to develop calculated thermal stresses. Thermal stresses were also calculated using a beam model. For a given temperature distribution there was very little variation in NASTRAN calculated thermal stresses when element types were interchanged for a given grid system. Thermal stresses calculated for the beam model compared similarly to the values obtained for the NASTRAN models. Calculated thermal stresses compared generally well to laboratory measured thermal stresses. A discrepancy of signifiance occurred between the measured and predicted thermal stresses in the skin areas. A minor anomaly in the laboratory skin heating uniformity resulted in inadequate temperature input data for the structural models.

  5. [Advance in researches on vegetation cover and management factor in the soil erosion prediction model].

    PubMed

    Zhang, Yan; Yuan, Jianping; Liu, Baoyuan

    2002-08-01

    Vegetation cover and land management are the main limiting factors of soil erosion, and quantitative evaluation on the effect of different vegetation on soil erosion is essential to land use and soil conservation planning. The vegetation cover and management factor (C) in the universal soil loss equation (USLE) is an index to evaluate this effect, which has been studied deeply and used widely. However, the C factor study is insufficient in China. In order to strengthen the research of C factor, this paper reviewed the developing progress of C factor, and compared the methods of estimating C value in different USLE versions. The relative studies in China were also summarized from the aspects of vegetation canopy coverage, soil surface cover, and root density. Three problems in C factor study were pointed out. The authors suggested that cropland C factor research should be furthered, and its methodology should be unified in China to represent reliable C values for soil loss prediction and conservation planning.

  6. Application of neural networks to prediction of advanced composite structures mechanical response and behavior

    NASA Technical Reports Server (NTRS)

    Cios, K. J.; Vary, A.; Berke, L.; Kautz, H. E.

    1992-01-01

    Two types of neural networks were used to evaluate acousto-ultrasonic (AU) data for material characterization and mechanical reponse prediction. The neural networks included a simple feedforward network (backpropagation) and a radial basis functions network. Comparisons of results in terms of accuracy and training time are given. Acousto-ultrasonic (AU) measurements were performed on a series of tensile specimens composed of eight laminated layers of continuous, SiC fiber reinforced Ti-15-3 matrix. The frequency spectrum was dominated by frequencies of longitudinal wave resonance through the thickness of the specimen at the sending transducer. The magnitude of the frequency spectrum of the AU signal was used for calculating a stress-wave factor based on integrating the spectral distribution function and used for comparison with neural networks results.

  7. Advanced Prediction of Tool Wear by Taking the Load History into Consideration

    NASA Astrophysics Data System (ADS)

    Ersoy, K.; Nuernberg, G.; Herrmann, G.; Hoffmann, H.

    2007-04-01

    A disadvantage of the conventional methods of simulating the wear occurring in deep drawing processes is that the wear coefficient, and thus wear too, is considered to be constant along loading duration, which, in case of deep drawing, corresponds to sliding distance and number of punch strokes. However, in reality, it is a known fact that wear development is not constant over time. In former studies, the authors presented a method, which makes it possible to consider the number of punch strokes in the simulation of wear. Another enhancement of this method is introduced in this paper. It is proposed to consider wear as a function of wear work instead of the number of punch strokes. Using this approach, the wear coefficients are implemented as a function of wear work and fully take into account the load history of the respective node. This enhancement makes it possible to apply the variable wear coefficients to completely different geometries, where one punch stroke involves different sliding distance or pressure values than the experiments with which the wear coefficients were determined. In this study, deep drawing experiments with a cylindrical cup geometry were carried out, in which the characteristic wear coefficient values as well as their gradients along the life cycle were determined. In this case, the die was produced via rapid tooling techniques. The prediction of tool wear is carried out with REDSY, a wear simulation software which was developed at the Institute of Metal Forming and Casting, TU-Muenchen. The wear predictions made by this software are based on the results of a conventional deep drawing simulation. For the wear modelling a modified Archard model was used.

  8. Forecasting phenological responses to climate change: Using hierarchical models to bridge local processes and regional predictions (Invited)

    NASA Astrophysics Data System (ADS)

    Diez, J.; Ibanez, I.

    2010-12-01

    Species’ phenological responses to climate change have large implications for future species distributions, trophic interactions, and ecosystem processes. Analyses of historical databases have shown that these responses are often species-specific and spatially variable. This variability makes predicting future responses more challenging. At the root of this challenge is the fundamental problem in ecology of how locally variable processes scale up to yield regional patterns. In this study, we show how hierarchical models of species phenological responses to climate may help address this challenge. Using long-term datasets (1953-2005) from the Japanese Meteorological Service for Morus bombysis (mulberry) at 100 sites distributed across Japan, we developed models using both monthly and daily climate data to predict bud burst dates. In both cases, hierarchical models were used to translate the different local responses among sites into more realistic predictions across the region and at unmeasured locations. The daily models represent a new approach to predicting phenology that is flexible enough to incorporate different mechanisms that may be important for some species, including forcing, chilling, photoperiod, and extreme events such as frosts. We use the daily models to show how spatial variability in bud burst dates results in part from different mechanisms being more important in different parts of the country. We compare these results to the monthly models to contrast the predictive value of the more detailed models. Our results emphasize the general utility of hierarchical models for understanding and forecasting regional changes in phenology, regardless of the specific model employed.

  9. EVALUATING THE PERFORMANCE OF REGIONAL-SCALE PHOTOCHEMICAL MODELING SYSTEMS: PART I--METEOROLOGICAL PREDICTIONS. (R825260)

    EPA Science Inventory

    In this study, the concept of scale analysis is applied to evaluate two state-of-science meteorological models, namely MM5 and RAMS3b, currently being used to drive regional-scale air quality models. To this end, seasonal time series of observations and predictions for temperatur...

  10. Regional Differences in Brain Volume Predict the Acquisition of Skill in a Complex Real-Time Strategy Videogame

    ERIC Educational Resources Information Center

    Basak, Chandramallika; Voss, Michelle W.; Erickson, Kirk I.; Boot, Walter R.; Kramer, Arthur F.

    2011-01-01

    Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also…

  11. Advancements in near real time mapping of earthquake and rainfall induced landslides in the Avcilar Peninsula, Marmara Region

    NASA Astrophysics Data System (ADS)

    Coccia, Stella

    2014-05-01

    Stella COCCIA (1), Fiona THEOLEYRE (1), Pascal BIGARRE(1) , Semih ERGINTAV(2), Oguz OZEL(3) and Serdar ÖZALAYBEY(4) (1) National Institute of Industrial Environment and Risks (INERIS) Nancy, France, (2) Kandilli Observatory and Earthquake Research Institute (KOERI), Istanbul, Turkey, (3) Istanbul University (IU), Istanbul, Turkey, (4) TUBITAK MAM, Istanbul, Turkey The European Project MARsite (http://marsite.eu/), started in 2012 and leaded by the KOERI, aims to improve seismic risk evaluation and preparedness to face the next dreadful large event expected for the next three decades. MARsite is thus expected to move a "step forward" the most advanced monitoring technologies, and offering promising open databases to the worldwide scientific community in the frame of other European environmental large-scale infrastructures, such as EPOS (http://www.epos-eu.org/ ). Among the 11 work packages (WP), the main aim of the WP6 is to study seismically-induced landslide hazard, by using and improving observing and monitoring systems in geological, hydrogeotechnical and seismic onshore and offshore areas. One of the WP6 specific study area is the Avcilar Peninsula, situated between Kucukcekmece and Buyukcekmece Lakes in the north-west of the region of Marmara. There, more than 400 landslides are located. According to geological and geotechnical investigations and studies, soil movements of this area are related to underground water and pore pressure changes, seismic forces arising after earthquakes and decreasing sliding strength in fissured and heavily consolidated clays. The WP6 includes various tasks and one of these works on a methodology to develop a dynamic system to create combined earthquake and rainfall induced landslides hazard maps at near real time and automatically. This innovative system could be used to improve the prevention strategy as well as in disaster management and relief operations. Base on literature review a dynamic GIS platform is used to combine

  12. Ionospheric Variations in the Region of the Equatorial Ionization Anomaly Crest: Comparison Between Observations and IRI-2012 Model Predictions.

    NASA Astrophysics Data System (ADS)

    Oyeyemi, E. O.; Bolaji, S.; Adewale, A. O.; Akala, A. O.; Oladipo, O. A.; Olugbon, B.; Olawepo, O. A.; Adeniyi, J. O.; Adimula, I.

    2015-12-01

    The objective of this work is to study the variations of the F2-layer critical frequency (foF2) in the region of equatorial ionization anomaly crest and check the accuracy of International Reference Ionosphere (IRI-2012) model predictions using ionosonde measurements from a number of stations in this region. We have used data, based on availability, corresponding to different seasonal and solar activity periods from each station considered to carry out our investigations. Details of the statistical analysis using percentage deviation (PD), upper and lower inter-quartile range (IQR) and relative deviation module mean (RDMM) for the evaluation of the IRI model performance are presented. The results show that, generally, the IRI model predictions have agreement with the observed values in terms of the pattern of variations but there are number of cases where IRI model overestimates and underestimates the observed values. Results from this study will be of help to improving prediction ability of the IRI models.

  13. When Local Extinction and Colonization of River Fishes Can Be Predicted by Regional Occupancy: the Role of Spatial Scales

    PubMed Central

    Bergerot, Benjamin; Hugueny, Bernard; Belliard, Jérôme

    2013-01-01

    Background Predicting which species are likely to go extinct is perhaps one of the most fundamental yet challenging tasks for conservation biologists. This is particularly relevant for freshwater ecosystems which tend to have the highest proportion of species threatened with extinction. According to metapopulation theories, local extinction and colonization rates of freshwater subpopulations can depend on the degree of regional occupancy, notably due to rescue effects. However, relationships between extinction, colonization, regional occupancy and the spatial scales at which they operate are currently poorly known. Methods And Findings: We used a large dataset of freshwater fish annual censuses in 325 stream reaches to analyse how annual extinction/colonization rates of subpopulations depend on the regional occupancy of species. For this purpose, we modelled the regional occupancy of 34 fish species over the whole French river network and we tested how extinction/colonization rates could be predicted by regional occupancy described at five nested spatial scales. Results show that extinction and colonization rates depend on regional occupancy, revealing existence a rescue effect. We also find that these effects are scale dependent and their absolute contribution to colonization and extinction tends to decrease from river section to larger basin scales. Conclusions In terms of management, we show that regional occupancy quantification allows the evaluation of local species extinction/colonization dynamics and reduction of local extinction risks for freshwater fish species implies the preservation of suitable habitats at both local and drainage basin scales. PMID:24367636

  14. Fresnel-region fields and antenna noise-temperature calculations for advanced microwave sounding units

    NASA Technical Reports Server (NTRS)

    Schmidt, R. F.

    1982-01-01

    A transition from the antenna noise temperature formulation for extended noise sources in the far-field or Fraunhofer-region of an antenna to one of the intermediate near field or Fresnel-region is discussed. The effort is directed toward microwave antenna simulations and high-speed digital computer analysis of radiometric sounding units used to obtain water vapor and temperature profiles of the atmosphere. Fresnel-region fields are compared at various distances from the aperture. The antenna noise temperature contribution of an annular noise source is computed in the Fresnel-region (D squared/16 lambda) for a 13.2 cm diameter offset-paraboloid aperture at 60 GHz. The time-average Poynting vector is used to effect the computation.

  15. Global isoscapes for δ18O and δ2H in precipitation: improved prediction using regionalized climatic regression models

    NASA Astrophysics Data System (ADS)

    Terzer, S.; Wassenaar, L. I.; Araguás-Araguás, L. J.; Aggarwal, P. K.

    2013-11-01

    A regionalized cluster-based water isotope prediction (RCWIP) approach, based on the Global Network of Isotopes in Precipitation (GNIP), was demonstrated for the purposes of predicting point- and large-scale spatio-temporal patterns of the stable isotope composition (δ2H, δ18O) of precipitation around the world. Unlike earlier global domain and fixed regressor models, RCWIP predefined 36 climatic cluster domains and tested all model combinations from an array of climatic and spatial regressor variables to obtain the best predictive approach to each cluster domain, as indicated by root-mean-squared error (RMSE) and variogram analysis. Fuzzy membership fractions were thereafter used as the weights to seamlessly amalgamate results of the optimized climatic zone prediction models into a single predictive mapping product, such as global or regional amount-weighted mean annual, mean monthly, or growing-season δ18O/δ2H in precipitation. Comparative tests revealed the RCWIP approach outperformed classical global-fixed regression-interpolation-based models more than 67% of the time, and clearly improved upon predictive accuracy and precision. All RCWIP isotope mapping products are available as gridded GeoTIFF files from the IAEA website (www.iaea.org/water) and are for use in hydrology, climatology, food authenticity, ecology, and forensics.

  16. Global isoscapes for δ18O and δ2H in precipitation: improved prediction using regionalized climatic regression models

    NASA Astrophysics Data System (ADS)

    Terzer, S.; Wassenaar, L. I.; Araguás-Araguás, L. J.; Aggarwal, P. K.

    2013-06-01

    A Regionalized Climatic Water Isotope Prediction (RCWIP) approach, based on the Global Network for Isotopes in Precipitation (GNIP), was demonstrated for the purposes of predicting point- and large-scale spatiotemporal patterns of the stable isotope compositions of water (δ2H, δ18O) in precipitation around the world. Unlike earlier global domain and fixed regressor models, RCWIP pre-defined thirty-six climatic cluster domains, and tested all model combinations from an array of climatic and spatial regressor variables to obtain the best predictive approach to each cluster domain, as indicated by RMSE and variogram analysis. Fuzzy membership fractions were thereafter used as the weights to seamlessly amalgamate results of the optimized climatic zone prediction models into a single predictive mapping product, such as global or regional amount-weighted mean annual, mean monthly or growing-season δ18O/δ2H in precipitation. Comparative tests revealed the RCWIP approach outperformed classical global-fixed regression-interpolation based models more than 67% of the time, and significantly improved upon predictive accuracy and precision. All RCWIP isotope mapping products are available as gridded GeoTIFF files from the IAEA website (www.iaea.org/water) and are for use in hydrology, climatology, food authenticity, ecology, and forensics.

  17. Prediction of household and commercial BMW generation according to socio-economic and other factors for the Dublin region.

    PubMed

    Purcell, M; Magette, W L

    2009-04-01

    Both planning and design of integrated municipal solid waste management systems require accurate prediction of waste generation. This research predicted the quantity and distribution of biodegradable municipal waste (BMW) generation within a diverse 'landscape' of residential areas, as well as from a variety of commercial establishments (restaurants, hotels, hospitals, etc.) in the Dublin (Ireland) region. Socio-economic variables, housing types, and the sizes and main activities of commercial establishments were hypothesized as the key determinants contributing to the spatial variability of BMW generation. A geographical information system (GIS) 'model' of BMW generation was created using ArcMap, a component of ArcGIS 9. Statistical data including socio-economic status and household size were mapped on an electoral district basis. Historical research and data from scientific literature were used to assign BMW generation rates to residential and commercial establishments. These predictions were combined to give overall BMW estimates for the region, which can aid waste planning and policy decisions. This technique will also aid the design of future waste management strategies, leading to policy and practice alterations as a function of demographic changes and development. The household prediction technique gave a more accurate overall estimate of household waste generation than did the social class technique. Both techniques produced estimates that differed from the reported local authority data; however, given that local authority reported figures for the region are below the national average, with some of the waste generated from apartment complexes being reported as commercial waste, predictions arising from this research are believed to be closer to actual waste generation than a comparison to reported data would suggest. By changing the input data, this estimation tool can be adapted for use in other locations. Although focusing on waste in the Dublin region

  18. Prediction of household and commercial BMW generation according to socio-economic and other factors for the Dublin region.

    PubMed

    Purcell, M; Magette, W L

    2009-04-01

    Both planning and design of integrated municipal solid waste management systems require accurate prediction of waste generation. This research predicted the quantity and distribution of biodegradable municipal waste (BMW) generation within a diverse 'landscape' of residential areas, as well as from a variety of commercial establishments (restaurants, hotels, hospitals, etc.) in the Dublin (Ireland) region. Socio-economic variables, housing types, and the sizes and main activities of commercial establishments were hypothesized as the key determinants contributing to the spatial variability of BMW generation. A geographical information system (GIS) 'model' of BMW generation was created using ArcMap, a component of ArcGIS 9. Statistical data including socio-economic status and household size were mapped on an electoral district basis. Historical research and data from scientific literature were used to assign BMW generation rates to residential and commercial establishments. These predictions were combined to give overall BMW estimates for the region, which can aid waste planning and policy decisions. This technique will also aid the design of future waste management strategies, leading to policy and practice alterations as a function of demographic changes and development. The household prediction technique gave a more accurate overall estimate of household waste generation than did the social class technique. Both techniques produced estimates that differed from the reported local authority data; however, given that local authority reported figures for the region are below the national average, with some of the waste generated from apartment complexes being reported as commercial waste, predictions arising from this research are believed to be closer to actual waste generation than a comparison to reported data would suggest. By changing the input data, this estimation tool can be adapted for use in other locations. Although focusing on waste in the Dublin region

  19. Godunov-Based Model of Swash Zone Dynamics to Advance Coastal Flood Prediction

    NASA Astrophysics Data System (ADS)

    Shakeri Majd, M.; Sanders, B. F.

    2012-12-01

    Urbanized lowlands in southern California are defended against coastal flooding by sandy beaches that dynamically adjust to changes in water level and wave conditions, particularly during storm events. Recent research has shown that coastal flood impacts are scaled by the volume of beach overtopping flows, and an improved characterization of dynamic overtopping rates is needed to improve coastal flood forecasting (Gallien et al. 2012). However, uncertainty in the beach slope and height makes it difficult to predict the onset of overtopping and the magnitude of resulting flooding. That is, beaches may evolve significantly over a storm event. Sallenger (Sallenger, 2000) describes Impact Levels to distinguish different impact regimes (swash, collision, overwash and inundation) on dunes and barrier islands. Our goal is to model processes in different regimes as was described by him. Godunov-based models adopt a depth-integrated, two-phase approach and the shallow-water hypothesis to resolve flow and sediment transport in a tightly coupled manner that resolves shocks in the air/fluid and fluid/sediment interface. These models are best known in the context of debris flow modeling where the ability to predict the flow of highly concentrated sediment/fluid mixtures is required. Here, the approach is directed at the swash zone. Existing Godunov-based models are reviewed and shown to have drawbacks relative to wetting and drying and "avalanching"—important processes in the swash zone. This nonphysical erosion can be described as the natural tendency of the schemes to smear out steep bed slopes. To denote and reduce these numerical errors, new numerical methods are presented to address these limitations and the resulting model is applied to a set of laboratory-scale test problems. The shallow-water hypothesis limits the applicability of the model to the swash zone, so it is forced by a time series of water level and cross-shore velocity that accounts for surf zone wave

  20. The impact of transition training on adapting to Technically Advanced Aircraft at regional airlines: Perceptions of pilots and instructor pilots

    NASA Astrophysics Data System (ADS)

    di Renzo, John Carl, Jr.

    Scope and method of study. The purpose of this study was to test a hypothesis about pilot and instructor pilot perceptions of how effectively pilots learn and use new technology, found in Technically Advanced Aircraft (TAA), given initial type of instrumentation training. New aviation technologies such as Glass Cockpits in technically advanced aircraft are complex and can be difficult to learn and use. The research questions focused on the type of initial instrumentation training to determine the differences among pilots trained using various types of instrumentation ranging from aircraft equipped with traditional analog instrumentation to aircraft equipped with glass cockpits. A convenience sample of Pilots in Training (PT) and Instructor Pilots (IP) was selected from a regional airline. The research design used a mixed methodology. Pilots in training completed a thirty-two question quantitative questionnaire and instructor pilots completed a five question qualitative questionnaire. Findings and conclusions. This investigation failed to disprove the null hypothesis. The type of instrumentation training has no significant effect on newly trained regional airline pilot perceived ability to adapt to advanced technology cockpits. Therefore, no evidence exists from this investigation to support the early introduction and training of TAA. While the results of this investigation were surprising, they are nonetheless, instructive. Even though it would seem that there would be a relationship between exposure to and use of technically advanced instrumentation, apparently there was no perceived relationship for this group of airline transport pilots. However, a point of interest is that these pilots were almost evenly divided in their opinion of whether or not their previous training had prepared them for transition to TAA. The majority also believed that the type of initial instrumentation training received does make a difference when transitioning to TAA. Pilots believed

  1. Recent advances in computational predictions of NMR parameters for the structure elucidation of carbohydrates: methods and limitations.

    PubMed

    Toukach, Filip V; Ananikov, Valentine P

    2013-11-01

    All living systems are comprised of four fundamental classes of macromolecules--nucleic acids, proteins, lipids, and carbohydrates (glycans). Glycans play a unique role of joining three principal hierarchical levels of the living world: (1) the molecular level (pathogenic agents and vaccine recognition by the immune system, metabolic pathways involving saccharides that provide cells with energy, and energy accumulation via photosynthesis); (2) the nanoscale level (cell membrane mechanics, structural support of biomolecules, and the glycosylation of macromolecules); (3) the microscale and macroscale levels (polymeric materials, such as cellulose, starch, glycogen, and biomass). NMR spectroscopy is the most powerful research approach for getting insight into the solution structure and function of carbohydrates at all hierarchical levels, from monosaccharides to oligo- and polysaccharides. Recent progress in computational procedures has opened up novel opportunities to reveal the structural information available in the NMR spectra of saccharides and to advance our understanding of the corresponding biochemical processes. The ability to predict the molecular geometry and NMR parameters is crucial for the elucidation of carbohydrate structures. In the present paper, we review the major NMR spectrum simulation techniques with regard to chemical shifts, coupling constants, relaxation rates and nuclear Overhauser effect prediction applied to the three levels of glycomics. Outstanding development in the related fields of genomics and proteomics has clearly shown that it is the advancement of research tools (automated spectrum analysis, structure elucidation, synthesis, sequencing and amplification) that drives the large challenges in modern science. Combining NMR spectroscopy and the computational analysis of structural information encoded in the NMR spectra reveals a way to the automated elucidation of the structure of carbohydrates.

  2. Predictive biomarkers in advance of a companion drug: ahead of their time?

    PubMed

    Kelley, Robin K; Atreya, Chloe; Venook, Alan P; Febbo, Phillip G

    2012-03-01

    Because of a surge in molecular testing capabilities concurrent with the rising numbers of targeted therapies in clinical development, the commercial use of predictive biomarkers before clinical validation is available is a topic of growing relevance to medical oncologists. Increasingly, patients will present questions about, requests for, and results from commercial biomarker tests for their oncologists to address. The sheer numbers of tests reaching the market, along with forecasted American Medical Association reforms in current procedural terminology coding and increasing FDA oversight of in vitro companion diagnostic device development, are likely to draw intense scrutiny to the regulation of commercial molecular testing in the near future, which will also require clinicians to remain abreast of the level of clinical validation of the biomarker tests available in practice. In addition to the direct risks of novel biomarker testing, including financial cost and ethical issues, the indirect risks encompass those associated with any clinical decision based on the biomarker test results. A great need exists for comprehensive and dynamic practice guidelines for all types of biomarker testing according to tumor type. PMID:22393192

  3. The Fitness Landscape of HIV-1 Gag: Advanced Modeling Approaches and Validation of Model Predictions by In Vitro Testing

    PubMed Central

    Omarjee, Saleha; Walker, Bruce D.; Chakraborty, Arup; Ndung'u, Thumbi

    2014-01-01

    Viral immune evasion by sequence variation is a major hindrance to HIV-1 vaccine design. To address this challenge, our group has developed a computational model, rooted in physics, that aims to predict the fitness landscape of HIV-1 proteins in order to design vaccine immunogens that lead to impaired viral fitness, thus blocking viable escape routes. Here, we advance the computational models to address previous limitations, and directly test model predictions against in vitro fitness measurements of HIV-1 strains containing multiple Gag mutations. We incorporated regularization into the model fitting procedure to address finite sampling. Further, we developed a model that accounts for the specific identity of mutant amino acids (Potts model), generalizing our previous approach (Ising model) that is unable to distinguish between different mutant amino acids. Gag mutation combinations (17 pairs, 1 triple and 25 single mutations within these) predicted to be either harmful to HIV-1 viability or fitness-neutral were introduced into HIV-1 NL4-3 by site-directed mutagenesis and replication capacities of these mutants were assayed in vitro. The predicted and measured fitness of the corresponding mutants for the original Ising model (r = −0.74, p = 3.6×10−6) are strongly correlated, and this was further strengthened in the regularized Ising model (r = −0.83, p = 3.7×10−12). Performance of the Potts model (r = −0.73, p = 9.7×10−9) was similar to that of the Ising model, indicating that the binary approximation is sufficient for capturing fitness effects of common mutants at sites of low amino acid diversity. However, we show that the Potts model is expected to improve predictive power for more variable proteins. Overall, our results support the ability of the computational models to robustly predict the relative fitness of mutant viral strains, and indicate the potential value of this approach for understanding viral immune evasion

  4. Executive Summary of the 2015 ISCD Position Development Conference on Advanced Measures From DXA and QCT: Fracture Prediction Beyond BMD.

    PubMed

    Shepherd, John A; Schousboe, John T; Broy, Susan B; Engelke, Klaus; Leslie, William D

    2015-01-01

    There have been many scientific advances in fracture risk prediction beyond bone density. The International Society for Clinical Densitometry (ISCD) convened a Position Development Conference (PDC) on the use of dual-energy X-ray absorptiometry beyond measurement of bone mineral density for fracture risk assessment, including trabecular bone score and hip geometry measures. Previously, no guidelines for nonbone mineral density DXA measures existed. Furthermore, there have been advances in the analysis of quantitative computed tomography (QCT) including finite element analysis, QCT of the hip, DXA-equivalent hip measurements, and opportunistic screening that were not included in the previous ISCD positions. The topics and questions for consideration were developed by the ISCD Board of Directors and the Scientific Advisory Committee and were designed to address the needs of clinical practitioners. Three task forces were created and asked to conduct comprehensive literature reviews to address specific questions. The task forces included participants from many countries and a variety of interests including academic institutions and private health care delivery organizations. Representatives from industry participated as consultants to the task forces. Task force reports with proposed position statements were then presented to an international panel of experts with backgrounds in bone densitometry. The PDC was held in Chicago, Illinois, USA, contemporaneously with the Annual Meeting of the ISCD, February 26 through February 28, 2015. This Executive Summary describes the methodology of the 2015 PDC on advanced measures from DXA and QCT and summarizes the approved official positions. Six separate articles in this issue will detail the rationale, discussion, and additional research topics for each question the task forces addressed.

  5. HPV Genotypes Predict Survival Benefits From Concurrent Chemotherapy and Radiation Therapy in Advanced Squamous Cell Carcinoma of the Cervix

    SciTech Connect

    Wang, Chun-Chieh; Lai, Chyong-Huey; Huang, Yi-Ting; Chao, Angel; Chou, Hung-Hsueh; Hong, Ji-Hong

    2012-11-15

    Purpose: To study the prognostic value of human papillomavirus (HPV) genotypes in patients with advanced cervical cancer treated with radiation therapy (RT) alone or concurrent chemoradiation therapy (CCRT). Methods and Materials: Between August 1993 and May 2000, 327 patients with advanced squamous cell carcinoma of the cervix (International Federation of Gynecology and Obstetrics stage III/IVA or stage IIB with positive lymph nodes) were eligible for this study. HPV genotypes were determined using the Easychip Registered-Sign HPV genechip. Outcomes were analyzed using Kaplan-Meier survival analysis and the Cox proportional hazards model. Results: We detected 22 HPV genotypes in 323 (98.8%) patients. The leading 4 types were HPV16, 58, 18, and 33. The 5-year overall and disease-specific survival estimates for the entire cohort were 41.9% and 51.4%, respectively. CCRT improved the 5-year disease-specific survival by an absolute 9.8%, but this was not statistically significant (P=.089). There was a significant improvement in disease-specific survival in the CCRT group for HPV18-positive (60.9% vs 30.4%, P=.019) and HPV58-positive (69.3% vs 48.9%, P=.026) patients compared with the RT alone group. In contrast, the differences in survival with CCRT compared with RT alone in the HPV16-positive and HPV-33 positive subgroups were not statistically significant (P=.86 and P=.53, respectively). An improved disease-specific survival was observed for CCRT treated patients infected with both HPV16 and HPV18, but these differenced also were not statistically significant. Conclusions: The HPV genotype may be a useful predictive factor for the effect of CCRT in patients with advanced squamous cell carcinoma of the cervix. Verifying these results in prospective trials could have an impact on tailoring future treatment based on HPV genotype.

  6. The value of lactate dehydrogenase serum levels as a prognostic and predictive factor for advanced pancreatic cancer patients receiving sorafenib

    PubMed Central

    Faloppi, Luca; Bianconi, Maristella; Giampieri, Riccardo; Sobrero, Alberto; Labianca, Roberto; Ferrari, Daris; Barni, Sandro; Aitini, Enrico; Zaniboni, Alberto; Boni, Corrado; Caprioni, Francesco; Mosconi, Stefania; Fanello, Silvia; Berardi, Rossana; Bittoni, Alessandro; Andrikou, Kalliopi; Cinquini, Michela; Torri, Valter; Scartozzi, Mario; Cascinu, Stefano

    2015-01-01

    Although lactate dehydrogenase (LDH) serum levels, indirect markers of angiogenesis, are associated with a worse outcome in several tumours, their prognostic value is not defined in pancreatic cancer. Moreover, high levels are associated even with a lack of efficacy of tyrosine kinase inhibitors, contributing to explain negative results in clinical trials. We assessed the role of LDH in advanced pancreatic cancer receiving sorafenib. Seventy-one of 114 patients included in the randomised phase II trial MAPS (chemotherapy plus or not sorafenib) and with available serum LDH levels, were included in this analysis. Patients were categorized according to serum LDH levels (LDH ≤vs.> upper normal rate). A significant difference was found in progression free survival (PFS) and in overall survival (OS) between patients with LDH values under or above the cut-off (PFS: 5.2 vs. 2.7 months, p = 0.0287; OS: 10.7 vs. 5.9 months, p = 0.0021). After stratification according to LDH serum levels and sorafenib treatment, patients with low LDH serum levels treated with sorafenib showed an advantage in PFS (p = 0.05) and OS (p = 0.0012). LDH appears to be a reliable parameter to assess the prognosis of advanced pancreatic cancer patients, and it may be a predictive parameter to select patients candidate to receive sorafenib. PMID:26397228

  7. The value of lactate dehydrogenase serum levels as a prognostic and predictive factor for advanced pancreatic cancer patients receiving sorafenib.

    PubMed

    Faloppi, Luca; Bianconi, Maristella; Giampieri, Riccardo; Sobrero, Alberto; Labianca, Roberto; Ferrari, Daris; Barni, Sandro; Aitini, Enrico; Zaniboni, Alberto; Boni, Corrado; Caprioni, Francesco; Mosconi, Stefania; Fanello, Silvia; Berardi, Rossana; Bittoni, Alessandro; Andrikou, Kalliopi; Cinquini, Michela; Torri, Valter; Scartozzi, Mario; Cascinu, Stefano

    2015-10-27

    Although lactate dehydrogenase (LDH) serum levels, indirect markers of angiogenesis, are associated with a worse outcome in several tumours, their prognostic value is not defined in pancreatic cancer. Moreover, high levels are associated even with a lack of efficacy of tyrosine kinase inhibitors, contributing to explain negative results in clinical trials. We assessed the role of LDH in advanced pancreatic cancer receiving sorafenib. Seventy-one of 114 patients included in the randomised phase II trial MAPS (chemotherapy plus or not sorafenib) and with available serum LDH levels, were included in this analysis. Patients were categorized according to serum LDH levels (LDH ≤ vs.> upper normal rate). A significant difference was found in progression free survival (PFS) and in overall survival (OS) between patients with LDH values under or above the cut-off (PFS: 5.2 vs. 2.7 months, p = 0.0287; OS: 10.7 vs. 5.9 months, p = 0.0021). After stratification according to LDH serum levels and sorafenib treatment, patients with low LDH serum levels treated with sorafenib showed an advantage in PFS (p = 0.05) and OS (p = 0.0012). LDH appears to be a reliable parameter to assess the prognosis of advanced pancreatic cancer patients, and it may be a predictive parameter to select patients candidate to receive sorafenib. PMID:26397228

  8. Advanced prediction technique for the low speed aerodynamics of V/STOL aircraft. Volume 2: User's manual

    NASA Technical Reports Server (NTRS)

    Beatty, T. D.; Worthey, M. K.

    1984-01-01

    A computerized prediction method known as the Vought V/STOL Aircraft Propulsive Effects computer program (VAPE) for propulsive induced forces and moments in transition and Short TakeOff and Landing (STOL) flight is improved and evaluated. The VAPE program is capable of evaluating: (1) effects of relative wind about an aircraft, (2) effects of propulsive lift jet entrainment, vorticity and flow blockage, (3) effects of engine inlet flow on the aircraft flow field, (4) engine inlet forces and moments including inlet separation, (5) ground effects in the STOL region of flight, and (6) viscous effects on lifting surfaces.

  9. Immunohistochemical prediction of lapatinib efficacy in advanced HER2-positive breast cancer patients

    PubMed Central

    Duchnowska, Renata; Wysocki, Piotr J.; Korski, Konstanty; Czartoryska-Arłukowicz, Bogumiła; Niwińska, Anna; Orlikowska, Marlena; Radecka, Barbara; Studziński, Maciej; Demlova, Regina; Ziółkowska, Barbara; Merdalska, Monika; Hajac, Łukasz; Myśliwiec, Paulina; Zuziak, Dorota; Dębska-Szmich, Sylwia; Lang, Istvan; Foszczyńska-Kłoda, Małgorzata; Karczmarek-Borowska, Bożenna; Żawrocki, Anton; Kowalczyk, Anna; Biernat, Wojciech; Jassem, Jacek

    2016-01-01

    Molecular mechanisms of lapatinib resistance in breast cancer are not well understood. The aim of this study was to correlate expression of selected proteins involved in ErbB family signaling pathways with clinical efficacy of lapatinib. Study group included 270 HER2-positive advanced breast cancer patients treated with lapatinib and capecitabine. Immunohistochemical expression of phosphorylated adenosine monophosphate-activated protein (p-AMPK), mitogen-activated protein kinase (p-MAPK), phospho (p)-p70S6K, cyclin E, phosphatase and tensin homolog were analyzed in primary breast cancer samples. The best discriminative value for progression-free survival (PFS) was established for each biomarker and subjected to multivariate analysis. At least one biomarker was determined in 199 patients. Expression of p-p70S6K was independently associated with longer (HR 0.45; 95% CI: 0.25–0.81; p = 0.009), and cyclin E with shorter PFS (HR 1.83; 95% CI: 1.06–3.14; p = 0.029). Expression of p-MAPK (HR 1.61; 95% CI 1.13–2.29; p = 0.009) and cyclin E (HR 2.99; 95% CI: 1.29–6.94; p = 0.011) was correlated with shorter, and expression of estrogen receptor (HR 0.65; 95% CI 0.43–0.98; p = 0.041) with longer overall survival. Expression of p-AMPK negatively impacted response to treatment (HR 3.31; 95% CI 1.48–7.44; p = 0.004) and disease control (HR 3.07; 95% CI 1.25–7.58; p = 0.015). In conclusion: the efficacy of lapatinib seems to be associated with the activity of downstream signaling pathways – AMPK/mTOR and Ras/Raf/MAPK. Further research is warranted to assess the clinical utility of these data and to determine a potential role of combining lapatinib with MAPK pathway inhibitors. PMID:26623720

  10. The role of prophylactic cranial irradiation in regionally advanced non-small cell lung cancer. A Southwest Oncology Group Study

    SciTech Connect

    Rusch, V.W.; Griffin, B.R.; Livingston, R.B. )

    1989-10-01

    Lung cancer is the most common malignant disease in the United States. Only the few tumors detected very early are curable, but there has been some progress in the management of more advanced non-small cell lung cancer, particularly in regionally inoperable disease. Prevention of central nervous system relapse is an important issue in this group of patients because brain metastases ultimately develop in 20% to 25% of them. Seventy-three patients with regionally advanced non-small cell lung cancer were entered into a Phase II trial of neutron chest radiotherapy sandwiched between four cycles of chemotherapy including cisplatin, vinblastine, and mitomycin C. Prophylactic cranial irradiation was administered concurrently with chest radiotherapy (3000 cGy in 10 fractions in 15 patients; 3600 cGy in 18 fractions in the remaining 50 patients). Patients underwent computed tomographic scan of the brain before treatment and every 3 months after treatment. The initial overall response rate was 79%, but 65 of the 73 patients have subsequently died of recurrent disease. Median follow-up is 9 months for all 73 patients and 26 months for eight long-term survivors. No patient who completed the prophylactic cranial irradiation program had clinical or radiologic brain metastases. Toxic reactions to prophylactic cranial irradiation included reversible alopecia in all patients, progressive dementia in one patient, and possible optic neuritis in one patient. Both of these patients received 300 cGy per fraction of irradiation. The use of prophylactic cranial irradiation has been controversial, but its safety and efficacy in this trial supports its application in a group of patients at high risk for central nervous system relapse. Further evaluation of prophylactic cranial irradiation in clinical trials for regionally advanced non-small cell lung cancer is warranted.

  11. Selecting statistical or machine learning techniques for regional landslide susceptibility modelling by evaluating spatial prediction

    NASA Astrophysics Data System (ADS)

    Goetz, Jason; Brenning, Alexander; Petschko, Helene; Leopold, Philip

    2015-04-01

    With so many techniques now available for landslide susceptibility modelling, it can be challenging to decide on which technique to apply. Generally speaking, the criteria for model selection should be tied closely to end users' purpose, which could be spatial prediction, spatial analysis or both. In our research, we focus on comparing the spatial predictive abilities of landslide susceptibility models. We illustrate how spatial cross-validation, a statistical approach for assessing spatial prediction performance, can be applied with the area under the receiver operating characteristic curve (AUROC) as a prediction measure for model comparison. Several machine learning and statistical techniques are evaluated for prediction in Lower Austria: support vector machine, random forest, bundling with penalized linear discriminant analysis, logistic regression, weights of evidence, and the generalized additive model. In addition to predictive performance, the importance of predictor variables in each model was estimated using spatial cross-validation by calculating the change in AUROC performance when variables are randomly permuted. The susceptibility modelling techniques were tested in three areas of interest in Lower Austria, which have unique geologic conditions associated with landslide occurrence. Overall, we found for the majority of comparisons that there were little practical or even statistically significant differences in AUROCs. That is the models' prediction performances were very similar. Therefore, in addition to prediction, the ability to interpret models for spatial analysis and the qualitative qualities of the prediction surface (map) are considered and discussed. The measure of variable importance provided some insight into the model behaviour for prediction, in particular for "black-box" models. However, there were no clear patterns in all areas of interest to why certain variables were given more importance over others.

  12. GFDL's unified regional-global weather-climate modeling system with variable resolution capability for severe weather predictions and regional climate simulations

    NASA Astrophysics Data System (ADS)

    Lin, S. J.

    2015-12-01

    The NOAA/Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions (e.g., tornado outbreak events and cat-5 hurricanes) and ultra-high-resolution (1-km) regional climate simulations within a consistent global modeling framework. The fundation of this flexible regional-global modeling system is the non-hydrostatic extension of the vertically Lagrangian dynamical core (Lin 2004, Monthly Weather Review) known in the community as FV3 (finite-volume on the cubed-sphere). Because of its flexability and computational efficiency, the FV3 is one of the final candidates of NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched (single) grid capability, a two-way (regional-global) multiple nested grid capability, and the combination of the stretched and two-way nests, so as to make convection-resolving regional climate simulation within a consistent global modeling system feasible using today's High Performance Computing System. One of our main scientific goals is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornadoes using a global model that was originally designed for century long climate simulations. As a unified weather-climate modeling system, we evaluated the performance of the model with horizontal resolution ranging from 1 km to as low as 200 km. In particular, for downscaling studies, we have developed various tests to ensure that the large-scale circulation within the global varaible resolution system is well simulated while at the same time the small-scale can be accurately captured

  13. Recent Advances in Regional Climate System Modeling and ClimateChange Analyses of Extreme Heat

    SciTech Connect

    Miller, Norman L.

    2004-09-24

    During the period May 2003 to May 2004, there were two CEC/PIER funded primary research activities by the Atmosphere and Ocean Sciences Group/Earth Science Division at LBNL. These activities are the implementation and testing of the National Center for Atmospheric Research Community Land Model (CLM) into MM5, and the analysis of extreme heat days under a new set of climate simulations. The new version of MM5,MM5-CLM, has been tested for a 90 day snowmelt period in the northwestern U.S. Results show that this new code upgrade, as compared to the MM5-NOAH, has improved snowmelt, temperature, and precipitation when compared to observations. These are due in part to a subgrid scheme,advanced snow processes, and advanced vegetation. The climate change analysis is the upper and lower IPCC Special Report on Emission Scenarios, representing fossil fuel intensive and energy conserving future emission scenarios, and medium and low sensitivity Global Climate Models. Results indicate that California cities will see increases in the number of heat wave and temperature threshold days from two to six times.These results may be viewed as potential outcomes based on today's decisions on emissions.

  14. Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies

    PubMed Central

    Kolch, Walter; Kholodenko, Boris N.; Ambrosi, Cristina De; Barla, Annalisa; Biganzoli, Elia M.; Nencioni, Alessio; Patrone, Franco; Ballestrero, Alberto; Zoppoli, Gabriele; Verri, Alessandro; Parodi, Silvio

    2015-01-01

    The interconnected network of pathways downstream of the TGFβ, WNT and EGF-families of receptor ligands play an important role in colorectal cancer pathogenesis. We studied and implemented dynamic simulations of multiple downstream pathways and described the section of the signaling network considered as a Molecular Interaction Map (MIM). Our simulations used Ordinary Differential Equations (ODEs), which involved 447 reactants and their interactions. Starting from an initial “physiologic condition”, the model can be adapted to simulate individual pathologic cancer conditions implementing alterations/mutations in relevant onco-proteins. We verified some salient model predictions using the mutated colorectal cancer lines HCT116 and HT29. We measured the amount of MYC and CCND1 mRNAs and AKT and ERK phosphorylated proteins, in response to individual or combination onco-protein inhibitor treatments. Experimental and simulation results were well correlated. Recent independently published results were also predicted by our model. Even in the presence of an approximate and incomplete signaling network information, a predictive dynamic modeling seems already possible. An important long term road seems to be open and can be pursued further, by incremental steps, toward even larger and better parameterized MIMs. Personalized treatment strategies with rational associations of signaling-proteins inhibitors, could become a realistic goal. PMID:25671297

  15. Using regional broccoli trial data to select experimental hybrids for input into advanced yield trials

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A large amount of phenotypic trait data are being generated in regional trials that are implemented as part of the Specialty Crop Research Initiative (SCRI) project entitled “Establishing an Eastern Broccoli Industry”. These data are used to identify the best entries in the trials for inclusion in ...

  16. Career Pathways: Aligning Public Resources to Support Individual and Regional Economic Advancement in the Knowledge Economy

    ERIC Educational Resources Information Center

    Jenkins, Davis

    2006-01-01

    This paper describes career pathways, a framework or approach by which regions can better align publicly supported systems and programs to build a knowledge-economy workforce customized to the needs of local labor markets. A career pathway is a series of connected education and training programs and support services that enable individuals to…

  17. Prediction of hot regions in protein-protein interaction by combining density-based incremental clustering with feature-based classification.

    PubMed

    Hu, Jing; Zhang, Xiaolong; Liu, Xiaoming; Tang, Jinshan

    2015-06-01

    Discovering hot regions in protein-protein interaction is important for drug and protein design, while experimental identification of hot regions is a time-consuming and labor-intensive effort; thus, the development of predictive models can be very helpful. In hot region prediction research, some models are based on structure information, and others are based on a protein interaction network. However, the prediction accuracy of these methods can still be improved. In this paper, a new method is proposed for hot region prediction, which combines density-based incremental clustering with feature-based classification. The method uses density-based incremental clustering to obtain rough hot regions, and uses feature-based classification to remove the non-hot spot residues from the rough hot regions. Experimental results show that the proposed method significantly improves the prediction performance of hot regions.

  18. Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America

    PubMed Central

    Medvigy, David; Moorcroft, Paul R.

    2012-01-01

    Terrestrial biosphere models are important tools for diagnosing both the current state of the terrestrial carbon cycle and forecasting terrestrial ecosystem responses to global change. While there are a number of ongoing assessments of the short-term predictive capabilities of terrestrial biosphere models using flux-tower measurements, to date there have been relatively few assessments of their ability to predict longer term, decadal-scale biomass dynamics. Here, we present the results of a regional-scale evaluation of the Ecosystem Demography version 2 (ED2)-structured terrestrial biosphere model, evaluating the model's predictions against forest inventory measurements for the northeast USA and Quebec from 1985 to 1995. Simulations were conducted using a default parametrization, which used parameter values from the literature, and a constrained model parametrization, which had been developed by constraining the model's predictions against 2 years of measurements from a single site, Harvard Forest (42.5° N, 72.1° W). The analysis shows that the constrained model parametrization offered marked improvements over the default model formulation, capturing large-scale variation in patterns of biomass dynamics despite marked differences in climate forcing, land-use history and species-composition across the region. These results imply that data-constrained parametrizations of structured biosphere models such as ED2 can be successfully used for regional-scale ecosystem prediction and forecasting. We also assess the model's ability to capture sub-grid scale heterogeneity in the dynamics of biomass growth and mortality of different sizes and types of trees, and then discuss the implications of these analyses for further reducing the remaining biases in the model's predictions. PMID:22144385

  19. Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America.

    PubMed

    Medvigy, David; Moorcroft, Paul R

    2012-01-19

    Terrestrial biosphere models are important tools for diagnosing both the current state of the terrestrial carbon cycle and forecasting terrestrial ecosystem responses to global change. While there are a number of ongoing assessments of the short-term predictive capabilities of terrestrial biosphere models using flux-tower measurements, to date there have been relatively few assessments of their ability to predict longer term, decadal-scale biomass dynamics. Here, we present the results of a regional-scale evaluation of the Ecosystem Demography version 2 (ED2)-structured terrestrial biosphere model, evaluating the model's predictions against forest inventory measurements for the northeast USA and Quebec from 1985 to 1995. Simulations were conducted using a default parametrization, which used parameter values from the literature, and a constrained model parametrization, which had been developed by constraining the model's predictions against 2 years of measurements from a single site, Harvard Forest (42.5° N, 72.1° W). The analysis shows that the constrained model parametrization offered marked improvements over the default model formulation, capturing large-scale variation in patterns of biomass dynamics despite marked differences in climate forcing, land-use history and species-composition across the region. These results imply that data-constrained parametrizations of structured biosphere models such as ED2 can be successfully used for regional-scale ecosystem prediction and forecasting. We also assess the model's ability to capture sub-grid scale heterogeneity in the dynamics of biomass growth and mortality of different sizes and types of trees, and then discuss the implications of these analyses for further reducing the remaining biases in the model's predictions.

  20. Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

    NASA Astrophysics Data System (ADS)

    Ter Maat, H. W.; Hutjes, R. W. A.; Miglietta, F.; Gioli, B.; Bosveld, F. C.; Vermeulen, A. T.; Fritsch, H.

    2010-08-01

    This paper is a case study to investigate what the main controlling factors are that determine atmospheric carbon dioxide content for a region in the centre of The Netherlands. We use the Regional Atmospheric Modelling System (RAMS), coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C), and including also submodels for urban and marine fluxes, which in principle should include the dominant mechanisms and should be able to capture the relevant dynamics of the system. To validate the model, observations are used that were taken during an intensive observational campaign in central Netherlands in summer 2002. These include flux-tower observations and aircraft observations of vertical profiles and spatial fluxes of various variables. The simulations performed with the coupled regional model (RAMS-SWAPS-C) are in good qualitative agreement with the observations. The station validation of the model demonstrates that the incoming shortwave radiation and surface fluxes of water and CO2 are well simulated. The comparison against aircraft data shows that the regional meteorology (i.e. wind, temperature) is captured well by the model. Comparing spatially explicitly simulated fluxes with aircraft observed fluxes we conclude that in general latent heat fluxes are underestimated by the model compared to the observations but that the latter exhibit large variability within all flights. Sensitivity experiments demonstrate the relevance of the urban emissions of carbon dioxide for the carbon balance in this particular region. The same tests also show the relation between uncertainties in surface fluxes and those in atmospheric concentrations.

  1. An empirical model for probabilistic decadal prediction: global attribution and regional hindcasts

    NASA Astrophysics Data System (ADS)

    Suckling, Emma B.; van Oldenborgh, Geert Jan; Eden, Jonathan M.; Hawkins, Ed

    2016-07-01

    Empirical models, designed to predict surface variables over seasons to decades ahead, provide useful benchmarks for comparison against the performance of dynamical forecast systems; they may also be employable as predictive tools for use by climate services in their own right. A new global empirical decadal prediction system is presented, based on a multiple linear regression approach designed to produce probabilistic output for comparison against dynamical models. A global attribution is performed initially to identify the important forcing and predictor components of the model . Ensemble hindcasts of surface air temperature anomaly fields are then generated, based on the forcings and predictors identified as important, under a series of different prediction `modes' and their performance is evaluated. The modes include a real-time setting, a scenario in which future volcanic forcings are prescribed during the hindcasts, and an approach which exploits knowledge of the forced trend. A two-tier prediction system, which uses knowledge of future sea surface temperatures in the Pacific and Atlantic Oceans, is also tested, but within a perfect knowledge framework. Each mode is designed to identify sources of predictability and uncertainty, as well as investigate different approaches to the design of decadal prediction systems for operational use. It is found that the empirical model shows skill above that of persistence hindcasts for annual means at lead times of up to 10 years ahead in all of the prediction modes investigated. It is suggested that hindcasts which exploit full knowledge of the forced trend due to increasing greenhouse gases throughout the hindcast period can provide more robust estimates of model bias for the calibration of the empirical model in an operational setting. The two-tier system shows potential for improved real-time prediction, given the assumption that skilful predictions of large-scale modes of variability are available. The empirical

  2. Numerical Simulations of Optical Turbulence Using an Advanced Atmospheric Prediction Model: Implications for Adaptive Optics Design

    NASA Astrophysics Data System (ADS)

    Alliss, R.

    2014-09-01

    Optical turbulence (OT) acts to distort light in the atmosphere, degrading imagery from astronomical telescopes and reducing the data quality of optical imaging and communication links. Some of the degradation due to turbulence can be corrected by adaptive optics. However, the severity of optical turbulence, and thus the amount of correction required, is largely dependent upon the turbulence at the location of interest. Therefore, it is vital to understand the climatology of optical turbulence at such locations. In many cases, it is impractical and expensive to setup instrumentation to characterize the climatology of OT, so numerical simulations become a less expensive and convenient alternative. The strength of OT is characterized by the refractive index structure function Cn2, which in turn is used to calculate atmospheric seeing parameters. While attempts have been made to characterize Cn2 using empirical models, Cn2 can be calculated more directly from Numerical Weather Prediction (NWP) simulations using pressure, temperature, thermal stability, vertical wind shear, turbulent Prandtl number, and turbulence kinetic energy (TKE). In this work we use the Weather Research and Forecast (WRF) NWP model to generate Cn2 climatologies in the planetary boundary layer and free atmosphere, allowing for both point-to-point and ground-to-space seeing estimates of the Fried Coherence length (ro) and other seeing parameters. Simulations are performed using a multi-node linux cluster using the Intel chip architecture. The WRF model is configured to run at 1km horizontal resolution and centered on the Mauna Loa Observatory (MLO) of the Big Island. The vertical resolution varies from 25 meters in the boundary layer to 500 meters in the stratosphere. The model top is 20 km. The Mellor-Yamada-Janjic (MYJ) TKE scheme has been modified to diagnose the turbulent Prandtl number as a function of the Richardson number, following observations by Kondo and others. This modification

  3. Advances in high-order interaction region nonlinear optics correction at RHIC

    SciTech Connect

    Zimmer, C.; Binello, S.; Minty, M.; Pilat, F.

    2011-03-28

    A method to indirectly measure and deterministically correct the higher order magnetic errors of the final focusing magnets in the Relativistic Heavy Ion Collider has been in place for several years at BNL. This method yields control over the effects of multi-pole errors through application of closed orbit bumps followed by analysis and correction of the resulting betatron tune shifts using multi-pole correctors. The process has recently been automated in order to provide more efficient and effective corrections. The tune resolution along with the reliability of measurements has also been improved significantly due to advances/upgrades in the betatron tune measurement system employed at RHIC (BBQ). Here we describe the foundation of the IR bump method, followed by recent improvements along with experimental data.

  4. Measurement of cell volume loss in the liquid region preceding an advancing phase change interface.

    PubMed

    Harmison, H R; Diller, K R; Walsh, J R; Neils, C M; Brand, J J

    1998-09-11

    It is well understood that the solidification of a solution results in a redistribution of solute in the liquid zone. For the freezing of suspensions of cells it is anticipated that accumulation of solute in the region leading a growing ice phase will cause an osmotic response in cells before the ice phase reaches the cells. To measure this phenomenon in a specific algal species, the volume changes in Chlorococcum texanum during freezing were studied using directional solidification cryomicroscopy. The relative cell volume was tracked continuously as a function of temperature and position as cells encountered the moving phase front. The loss of cell volume was measured in the liquid region containing concentrated solute ahead of the growing solid phase.

  5. The use of regional advance mitigation planning (RAMP) to integrate transportation infrastructure impacts with sustainability; a perspective from the USA

    NASA Astrophysics Data System (ADS)

    Thorne, James H.; Huber, Patrick R.; O'Donoghue, Elizabeth; Santos, Maria J.

    2014-05-01

    Globally, urban areas are expanding, and their regional, spatially cumulative, environmental impacts from transportation projects are not typically assessed. However, incorporation of a Regional Advance Mitigation Planning (RAMP) framework can promote more effective, ecologically sound, and less expensive environmental mitigation. As a demonstration of the first phase of the RAMP framework, we assessed environmental impacts from 181 planned transportation projects in the 19 368 km2 San Francisco Bay Area. We found that 107 road and railroad projects will impact 2411-3490 ha of habitat supporting 30-43 threatened or endangered species. In addition, 1175 ha of impacts to agriculture and native vegetation are expected, as well as 125 crossings of waterways supporting anadromous fish species. The extent of these spatially cumulative impacts shows the need for a regional approach to associated environmental offsets. Many of the impacts were comprised of numerous small projects, where project-by-project mitigation would result in increased transaction costs, land costs, and lost project time. Ecological gains can be made if a regional approach is taken through the avoidance of small-sized reserves and the ability to target parcels for acquisition that fit within conservation planning designs. The methods are straightforward, and can be used in other metropolitan areas.

  6. Advanced glycation end products and their circulating receptors predict cardiovascular disease mortality in older community-dwelling women

    PubMed Central

    Semba, Richard D.; Ferrucci, Luigi; Sun, Kai; Beck, Justine; Dalal, Mansi; Varadhan, Ravi; Walston, Jeremy; Guralnik, Jack M.; Fried, Linda P.

    2008-01-01

    Objective To characterize the relationship between advanced glycation end products (AGEs) and circulating receptors for AGEs (RAGE) with cardiovascular disease mortality. Methods The relationships between serum AGEs, total RAGE (sRAGE), and endogenous secretory RAGE (esRAGE), and mortality were characterized in 559 community-dwelling women, ≥65 years, in Baltimore, Maryland. Results During 4.5 years of follow-up, 123 (22%) women died, of whom 54 died with cardiovascular disease. The measure of serum AGEs was carboxymethyl-lysine (CML), a dominant AGE. Serum CML predicted cardiovascular disease mortality (Hazards Ratio [H.R.] for highest versus lower three quartiles 1.94, 95% Confidence Interval [C.I.] 1.08-3.48, P = 0.026), after adjusting for age, race, body mass index, and renal insufficiency. Serum sRAGE (ng/mL) and esRAGE (ng/mL) predicted cardiovascular disease mortality (H.R. per 1 Standard Deviation [S.D.] 1.27, 95% C.I. 0.98-1.65, P = 0.07; H.R. 1.28, 95% C.I. 1.02-1.63, P = 0.03), after adjusting for the same covariates. Among non-diabetic women, serum CML, sRAGE, and esRAGE, respectively, predicted cardiovascular disease mortality (H.R. for highest versus lower three quartiles, 2.29, 95% C.I. 1.21-4.34, P = 0.01; H.R. per 1 S.D., 1.24, 95% C.I. 0.92-1.65, P = 0.16; H.R. per 1 S.D. 1.45, 95% C.I. 1.08-1.93, P = 0.01), after adjusting for the same covariates. Conclusions High circulating AGEs and RAGE predict cardiovascular disease mortality among older community-dwelling women. AGEs are a potential target for interventions, as serum AGEs can be lowered by change in dietary pattern and pharmacological treatment. PMID:19448391

  7. Recent Advances in Understanding Radiation Belt Dynamics in the Earth's Inner Zone and Slot Region

    NASA Astrophysics Data System (ADS)

    Li, X.

    2015-12-01

    Comprehensive measurements of the inner belt protons from the Relativistic Electron and Proton Telescope (REPT) onboard Van Allen Probes, in a geo-transfer-like orbit, revealed new features of inner belt protons in terms of their spectrum distribution, spatial distribution, pitch angle distribution, and their different source populations. Concurrent measurements from the Relativistic Electron and Proton Telescope integrated little experiment (REPTile) on board Colorado Student Space Weather Experiment (CSSWE) CubeSat, in a highly inclined low Earth orbit, and REPT demonstrated that there exist sub-MeV electrons in the inner belt and their flux level is orders of magnitude higher than the background associated with the inner belt protons, while higher energy electron (>1.6 MeV) measurements cannot be distinguished from the background. Analysis on sub-MeV electrons data in the inner belt and slot region from the Magnetic Electron Ion Spectrometer (MagEIS) on board Van Allen Probes revealed rather complicated pitch angle distribution of these energetic electrons, with the 90 deg-minimum (butterfly) pitch angle distribution dominating near the magnetic equator. Furthermore, it is clearly shown from MagEIS measurements that 10s - 100s keV electrons are commonly seen penetrating into the inner belt region during geomagnetic active times while protons of similar energies are hardly seen there. These are part of a summary of the most recent measurements and understanding of the dynamics of energetic particles in the inner zone and slot region to be exhibited and discussed in this presentation.

  8. Prediction and validation of total and regional skeletal muscle volume using B-mode ultrasonography in Japanese prepubertal children.

    PubMed

    Midorikawa, Taishi; Ohta, Megumi; Hikihara, Yuki; Torii, Suguru; Sakamoto, Shizuo

    2015-10-28

    Very few effective field methods are available for accurate, non-invasive estimation of skeletal muscle volume (SMV) and mass in children. We aimed to develop regression-based prediction equations for SMV, using ultrasonography, in Japanese prepubertal children, and to assess the validity of these equations. In total, 145 healthy Japanese prepubertal children aged 6-12 years were randomly divided into two groups: the model development group (sixty boys, thirty-seven girls) and the validation group (twenty-nine boys, nineteen girls). Reference data in the form of contiguous MRI with 1-cm slice thickness were obtained from the first cervical vertebra to the ankle joints. The SMV was calculated by the summation of digitised cross-sectional areas. Muscle thickness was measured using B-mode ultrasonography at nine sites in different regions. In the model development group, strong, statistically significant correlations were observed between the site-matched SMV (total, arms, trunk, thigh and lower legs) measured by MRI and the muscle thickness×height measures obtained by ultrasonography, for both boys and girls. When these SMV prediction equations were applied to the validation groups, the measured total and regional SMV were also very similar to the values predicted for boys and girls, respectively. With the exception of the trunk region in girls, the Bland-Altman analysis for the validation group did not indicate any bias for either boys or girls. These results suggest that ultrasonography-derived prediction equations for boys and girls are useful for the estimation of total and regional SMV.

  9. Prognostic and Predictive Value of Baseline and Posttreatment Molecular Marker Expression in Locally Advanced Rectal Cancer Treated With Neoadjuvant Chemoradiotherapy

    SciTech Connect

    Bertolini, Federica . E-mail: bertolini.federica@policlinico.mo.it; Bengala, Carmelo; Losi, Luisa; Pagano, Maria; Iachetta, Francesco; Dealis, Cristina; Jovic, Gordana; Depenni, Roberta; Zironi, Sandra; Falchi, Anna Maria; Luppi, Gabriele; Conte, Pier Franco

    2007-08-01

    Purpose: To evaluate expression of a panel of molecular markers, including p53, p21, MLH1, MSH2, MIB-1, thymidylate synthase, epidermal growth factor receptor (EGFR), and tissue vascular endothelial growth factor (VEGF), before and after treatment in patients treated with neoadjuvant chemoradiotherapy for locally advanced rectal cancer, to correlate the constitutive profile and dynamics of expression with pathologic response and outcome. Methods and Materials: Expression of biomarkers was evaluated by immunohistochemistry in tumor samples from 91 patients with clinical Stage II and III rectal cancer treated with preoperative pelvic radiotherapy (50 Gy) plus concurrent 5-fluorouracil by continuous intravenous infusion. Results: A pathologic complete remission was observed in 14 patients (15.4%). Patients with MLH1-positive tumors had a higher pathologic complete response rate (24.3% vs. 9.4%; p = 0.055). Low expression of constitutive p21, absence of EGFR expression after chemoradiotherapy, and high Dworak's tumor regression grade (TRG) were significantly associated with improved disease-free survival and overall survival. A high MIB-1 value after chemoradiotherapy was significantly associated with worse overall survival. Multivariate analysis confirmed the prognostic value of constitutive p21 expression as well as EGFR expression and MIB-1 value after chemoradiotherapy among patients not achieving TRG 3-4. Conclusions: In our study, we observed the independent prognostic value of EGFR expression after chemoradiotherapy on disease-free survival. Moreover, our study suggests that a constitutive high p21 expression and a high MIB-1 value after neoadjuvant chemoradiotherapy treatment could predict worse outcome in locally advanced rectal cancer.

  10. Primary Tumor Necrosis Predicts Distant Control in Locally Advanced Soft-Tissue Sarcomas After Preoperative Concurrent Chemoradiotherapy

    SciTech Connect

    MacDermed, Dhara M.; Miller, Luke L.; Peabody, Terrance D.; Simon, Michael A.; Luu, Hue H.; Haydon, Rex C.; Montag, Anthony G.; Undevia, Samir D.

    2010-03-15

    Purpose: Various neoadjuvant approaches have been evaluated for the treatment of locally advanced soft-tissue sarcomas. This retrospective study describes a uniquely modified version of the Eilber regimen developed at the University of Chicago. Methods and Materials: We treated 34 patients (28 Stage III and 6 Stage IV) with locally advanced soft-tissue sarcomas of an extremity between 1995 and 2008. All patients received preoperative therapy including ifosfamide (2.5 g/m2 per day for 5 days) with concurrent radiation (28 Gy in 3.5-Gy daily fractions), sandwiched between various chemotherapy regimens. Postoperatively, 47% received further adjuvant chemotherapy. Results: Most tumors (94%) were Grade 3, and all were T2b, with a median size of 10.3 cm. Wide excision was performed in 29 patients (85%), and 5 required amputation. Of the resected tumor specimens, 50% exhibited high (>=90%) treatment-induced necrosis and 11.8% had a complete pathologic response. Surgical margins were negative in all patients. The 5-year survival rate was 42.3% for all patients and 45.2% for Stage III patients. For limb-preservation patients, the 5-year local control rate was 89.0% and reoperation was required for wound complications in 17.2%. The 5-year freedom-from-distant metastasis rate was 53.4% (Stage IV patients excluded), and freedom from distant metastasis was superior if treatment-induced tumor necrosis was 90% or greater (84.6% vs. 19.9%, p = 0.02). Conclusions: This well-tolerated concurrent chemoradiotherapy approach yields excellent rates of limb preservation and local control. The resulting treatment-induced necrosis rates are predictive of subsequent metastatic risk, and this information may provide an opportunity to guide postoperative systemic therapies.

  11. Development of an advanced regional climate-ecosystem model for Arctic applications

    NASA Astrophysics Data System (ADS)

    Chaudhary, Nitin; Smith, Benjamin; Miller, Paul

    2013-04-01

    Cryospheric processes together with their feedbacks play a crucial role in determining rates and patterns of future warming over high-latitude regions. Cryospheric processes including permafrost as well as peatland and associated vegetation, hydrological and biogeochemical dynamics are not well represented in land surface schemes (LSS) of most climate models. As a step in this direction, we describe a scheme to include the coupled dynamics of vegetation, hydrology and peat accumulation under climate forcing within a detailed vegetation dynamics-biogeochemistry model, LPJ GUESS (Smith et al. 2001; Miller et al., in preparation). In the first step, a one-dimensional (1D) landscape scale peat accumulation and two dimensional (2D) micro-topographical models have been developed. For the parameterisation and validation of these models, good quality datasets are being used which are collected at various locations around the Arctic. Building on these, a three-dimensional (3D) scheme will be incorporated in a version of LPJ-GUESS that already includes patch-scale vegetation dynamics and soil carbon cycling, as well as a one-dimensional hydrology scheme. The patches in the 3D model will be treated as adjacent micro-patches in a grid and depending on underlying micro-topography water will flow from higher to lower patches. The 2D and 3D models will help in simulating hummock and hollow structure which is typical for Northern peatlands based on the cyclic regeneration theory (von Post and Sernander, 1910). The resulting models will be incorporated within the biospheric component of a regional climate-ecosystem model, RCA-GUESS (Smith et al., 2010) and used to investigate feedbacks related to the dynamics of peatlands, permafrost and emissions of the greenhouse gases, mainly CO2 and CH4 across the Arctic region. References- Smith B, Prentice IC, and Skyes MT. 2001. Representation of vegetation dynamics in modelling of European ecosystems: comparison of two contrasting

  12. Generation of coronavirus spike deletion variants by high-frequency recombination at regions of predicted RNA secondary structure.

    PubMed Central

    Rowe, C L; Fleming, J O; Nathan, M J; Sgro, J Y; Palmenberg, A C; Baker, S C

    1997-01-01

    Coronavirus RNA evolves in the central nervous systems (CNS) of mice during persistent infection. This evolution can be monitored by detection of a viral quasispecies of spike deletion variants (SDVs) (C. L. Rowe, S. C. Baker, M. J. Nathan, and J. O. Fleming, J. Virol. 71:2959-2969, 1997). We and others have found that the deletions cluster in the region from 1,200 to 1,800 nucleotides from the 5' end of the spike gene sequence, termed the "hypervariable" region. To address how SDVs might arise, we generated the predicted folding structures of the positive- and negative-strand senses of the entire 4,139-nt spike RNA sequence. We found that a prominent, isolated stem-loop structure is coincident with the hypervariable region in each structure. To determine if this predicted stem-loop is a "hot spot" for RNA recombination, we assessed whether this region of the spike is more frequently deleted than three other selected regions of the spike sequence in a population of viral sequences isolated from the CNS of acutely and persistently infected mice. Using differential colony hybridization of cloned spike reverse transcription-PCR products, we detected SDVs in which the hot spot was deleted but did not detect SDVs in which other regions of the spike sequence were exclusively deleted. Furthermore, sequence analysis and mapping of the crossover sites of 25 distinct patterns of SDVs showed that the majority of crossover sites clustered to two regions at the base of the isolated stem-loop, which we designated as high-frequency recombination sites 1 and 2. Interestingly, the majority of the left and right crossover sites of the SDVs were directly across from or proximal to one another, suggesting that these SDVs are likely generated by intramolecular recombination. Overall, our results are consistent with there being an important role for the spike RNA secondary structure as a contributing factor in the generation of SDVs during persistent infection. PMID:9223514

  13. Advanced Strategies for Outdoor LED Lighting Applications and Technologies to Curtail Regional Light Pollution Effects

    NASA Astrophysics Data System (ADS)

    Monrad, Christian Karl; Benya, James R.

    2015-08-01

    LED lighting systems for outdoor lighting applications continue to evolve as do strategies to mitigate related effects upon regional astronomical and ecological assets. The improving availability and relative lumen-per-watt efficiencies of blue-suppressed low correlated color temperature emitters, narrow band amber, phosphor converted amber, and various combinations of broadband emitters and sub-550NM and sub-500NM filters allow for a wide palette of choices to be assessed to suit site-specific and task-specific lighting needs. In addition to static spectral content options, readily available luminaire designs also include precise geometric beam shape selections and adaptive controls to include dimming, dynamic spectral shifting, motion detection, and dynamic beam shaping to minimize total environmental lumen emissions throughout the course of the nighttime hours.Regional and international light pollution mitigation regulations will also be briefly addressed in the context of luminaire shielding and spectral content control efforts to better protect human quality of life issues as well as astronomical and ecological interests.The presentation will include numerous spectral content graphs for various luminaire options as well as project-specific case studies to document comparisons of legacy lighting systems versus high-performance LED systems with regard to total lumen emissions, skyglow contributions, energy efficiency, and end-user satisfaction with the installed LED lighting systems. Physical samples of various luminaires will also be available for hands-on assessments.

  14. 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

  15. North polar region of Mars: Advances in stratigraphy, structure, and erosional modification

    USGS Publications Warehouse

    Tanaka, K.L.; Rodriguez, J.A.P.; Skinner, J.A.; Bourke, M.C.; Fortezzo, C.M.; Herkenhoff, K. E.; Kolb, E.J.; Okubo, C.H.

    2008-01-01

    We have remapped the geology of the north polar plateau on Mars, Planum Boreum, and the surrounding plains of Vastitas Borealis using altimetry and image data along with thematic maps resulting from observations made by the Mars Global Surveyor, Mars Odyssey, Mars Express, and Mars Reconnaissance Orbiter spacecraft. New and revised geographic and geologic terminologies assist with effectively discussing the various features of this region. We identify 7 geologic units making up Planum Boreum and at least 3 for the circumpolar plains, which collectively span the entire Amazonian Period. The Planum Boreum units resolve at least 6 distinct depositional and 5 erosional episodes. The first major stage of activity includes the Early Amazonian (???3 to 1 Ga) deposition (and subsequent erosion) of the thick (locally exceeding 1000 m) and evenly-layered Rupes Tenuis unit (Abrt), which ultimately formed approximately half of the base of Planum Boreum. As previously suggested, this unit may be sourced by materials derived from the nearby Scandia region, and we interpret that it may correlate with the deposits that regionally underlie pedestal craters in the surrounding lowland plains. The second major episode of activity during the Middle to Late Amazonian (??? <1 Ga) began with a section of dark, sand-rich and light-toned ice-rich irregularly-bedded sequences (Planum Boreum cavi unit, Abbc) along with deposition of evenly-bedded light-toned ice- and moderate-toned dust-rich layers (Planum Boreum 1 unit, Abb1). These units have transgressive and gradational stratigraphic relationships. Materials in Olympia Planum underlying the dunes of Olympia Undae are interpreted to consist mostly of the Planum Boreum cavi unit (Abbc). Planum Boreum materials were then deeply eroded to form spiral troughs, Chasma Boreale, and marginal scarps that define the major aspects of the polar plateau's current regional topography. Locally- to regionally-extensive (though vertically minor) episodes

  16. Scaling from Field to Region for Wind Erosion prediction Using WEPS and GIS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Wind Erosion Prediction System (WEPS) simulates soil erosion and dust emissions from agricultural soils. Due to the severe risk of wind erosion in Adams County, Washington, WEPS and ArcGIS were used to simulate soil loss and PM10 (particulate matter <10µm in diameter) emissions. On a county-wide...

  17. Seasonal Prediction of Regional Surface Air Temperature and First-flowering Date in South Korea using Dynamical Downscaling

    NASA Astrophysics Data System (ADS)

    Ahn, J. B.; Hur, J.

    2015-12-01

    The seasonal prediction of both the surface air temperature and the first-flowering date (FFD) over South Korea are produced using dynamical downscaling (Hur and Ahn, 2015). Dynamical downscaling is performed using Weather Research and Forecast (WRF) v3.0 with the lateral forcing from hourly outputs of Pusan National University (PNU) coupled general circulation model (CGCM) v1.1. Gridded surface air temperature data with high spatial (3km) and temporal (daily) resolution are obtained using the physically-based dynamical models. To reduce systematic bias, simple statistical correction method is then applied to the model output. The FFDs of cherry, peach and pear in South Korea are predicted for the decade of 1999-2008 by applying the corrected daily temperature predictions to the phenological thermal-time model. The WRF v3.0 results reflect the detailed topographical effect, despite having cold and warm biases for warm and cold seasons, respectively. After applying the correction, the mean temperature for early spring (February to April) well represents the general pattern of observation, while preserving the advantages of dynamical downscaling. The FFD predictabilities for the three species of trees are evaluated in terms of qualitative, quantitative and categorical estimations. Although FFDs derived from the corrected WRF results well predict the spatial distribution and the variation of observation, the prediction performance has no statistical significance or appropriate predictability. The approach used in the study may be helpful in obtaining detailed and useful information about FFD and regional temperature by accounting for physically-based atmospheric dynamics, although the seasonal predictability of flowering phenology is not high enough. Acknowledgements This work was carried out with the support of the Rural Development Administration Cooperative Research Program for Agriculture Science and Technology Development under Grant Project No. PJ009953 and

  18. Temperature and Material Flow Prediction in Friction-Stir Spot Welding of Advanced High-Strength Steel

    SciTech Connect

    Miles, Michael; Karki, U.; Hovanski, Yuri

    2014-10-01

    Friction-stir spot welding (FSSW) has been shown to be capable of joining advanced high-strength steel, with its flexibility in controlling the heat of welding and the resulting microstructure of the joint. This makes FSSW a potential alternative to resistance spot welding if tool life is sufficiently high, and if machine spindle loads are sufficiently low that the process can be implemented on an industrial robot. Robots for spot welding can typically sustain vertical loads of about 8 kN, but FSSW at tool speeds of less than 3000 rpm cause loads that are too high, in the range of 11–14 kN. Therefore, in the current work, tool speeds of 5000 rpm were employed to generate heat more quickly and to reduce welding loads to acceptable levels. Si3N4 tools were used for the welding experiments on 1.2-mm DP 980 steel. The FSSW process was modeled with a finite element approach using the Forge* software. An updated Lagrangian scheme with explicit time integration was employed to predict the flow of the sheet material, subjected to boundary conditions of a rotating tool and a fixed backing plate. Material flow was calculated from a velocity field that is two-dimensional, but heat generated by friction was computed by a novel approach, where the rotational velocity component imparted to the sheet by the tool surface was included in the thermal boundary conditions. An isotropic, viscoplastic Norton-Hoff law was used to compute the material flow stress as a function of strain, strain rate, and temperature. The model predicted welding temperatures to within percent, and the position of the joint interface to within 10 percent, of the experimental results.

  19. Evaluating Aggregate Terrestrial Impacts of Road Construction Projects for Advanced Regional Mitigation

    NASA Astrophysics Data System (ADS)

    Thorne, James H.; Girvetz, Evan H.; McCoy, Michael C.

    2009-05-01

    This study presents a GIS-based database framework used to assess aggregate terrestrial habitat impacts from multiple highway construction projects in California, USA. Transportation planners need such impact assessment tools to effectively address additive biological mitigation obligations. Such assessments can reduce costly delays due to protracted environmental review. This project incorporated the best available statewide natural resource data into early project planning and preliminary environmental assessments for single and multiple highway construction projects, and provides an assessment of the 10-year state-wide mitigation obligations for the California Department of Transportation. Incorporation of these assessments will facilitate early and more strategic identification of mitigation opportunities, for single-project and regional mitigation efforts. The data architecture format uses eight spatial scales: six nested watersheds, counties, and transportation planning districts, which were intersected. This resulted in 8058 map planning units statewide, which were used to summarize all subsequent analyses. Range maps and georeferenced locations of federally and state-listed plants and animals and a 55-class landcover map were spatially intersected with the planning units and the buffered spatial footprint of 967 funded projects. Projected impacts were summarized and output to the database. Queries written in the database can sum expected impacts and provide summaries by individual construction project, or by watershed, county, transportation district or highway. The data architecture allows easy incorporation of new information and results in a tool usable without GIS by a wide variety of agency biologists and planners. The data architecture format would be useful for other types of regional planning.

  20. Evaluating aggregate terrestrial impacts of road construction projects for advanced regional mitigation.

    PubMed

    Thorne, James H; Girvetz, Evan H; McCoy, Michael C

    2009-05-01

    This study presents a GIS-based database framework used to assess aggregate terrestrial habitat impacts from multiple highway construction projects in California, USA. Transportation planners need such impact assessment tools to effectively address additive biological mitigation obligations. Such assessments can reduce costly delays due to protracted environmental review. This project incorporated the best available statewide natural resource data into early project planning and preliminary environmental assessments for single and multiple highway construction projects, and provides an assessment of the 10-year state-wide mitigation obligations for the California Department of Transportation. Incorporation of these assessments will facilitate early and more strategic identification of mitigation opportunities, for single-project and regional mitigation efforts. The data architecture format uses eight spatial scales: six nested watersheds, counties, and transportation planning districts, which were intersected. This resulted in 8058 map planning units statewide, which were used to summarize all subsequent analyses. Range maps and georeferenced locations of federally and state-listed plants and animals and a 55-class landcover map were spatially intersected with the planning units and the buffered spatial footprint of 967 funded projects. Projected impacts were summarized and output to the database. Queries written in the database can sum expected impacts and provide summaries by individual construction project, or by watershed, county, transportation district or highway. The data architecture allows easy incorporation of new information and results in a tool usable without GIS by a wide variety of agency biologists and planners. The data architecture format would be useful for other types of regional planning.

  1. Terrestrial Carbon Fluxes from Deforestation in the Brazilian Amazon and Cerrado Regions Predicted from MODIS Satellite Data and Ecosystem Modeling

    NASA Astrophysics Data System (ADS)

    Klooster, S.; Potter, C.; Genovese, V.

    2008-12-01

    The NASA-CASA (Carnegie Ames Stanford Approach) simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate tropical forest and savanna (Cerrado) carbon pools for the Brazilian Amazon region over the period 2000-2004. Adjustments for mean age of forest stands were carried out across the region, resulting in a new mapping of aboveground biomass pools based on MODIS satellite data. Yearly maps of newly deforested lands from the Brazilian PRODES (Programa de calculo do desflorestamento da Amazonia ) project were combined with these NASA-CASA biomass predictions to generate seasonal budgets of potential carbon and nitrogen trace gas losses from biomass burning events. Simulations of plant residue and soil carbon decomposition were conducted in the NASA-CASA model during and following deforestation events to track the fate of aboveground biomass pools that were cut and burned each year across the region.

  2. Full-coverage film cooling: 3-dimensional measurements of turbulence structure and prediction of recovery region hydrodynamics

    NASA Technical Reports Server (NTRS)

    Yavuzkurt, S.; Moffat, R. J.; Kays, W. M.

    1979-01-01

    Hydrodynamic measurements were made with a triaxial hot-wire in the full-coverage region and the recovery region following an array of injection holes inclined downstream, at 30 degrees to the surface. The data were taken under isothermal conditions at ambient temperature and pressure for two blowing ratios: M = 0.9 and M = 0.4. Profiles of the three main velocity components and the six Reynolds stresses were obtained at several spanwise positions at each of the five locations down the test plate. A one-equation model of turbulence (using turbulent kinetic energy with an algebraic mixing length) was used in a two-dimensional computer program to predict the mean velocity and turbulent kinetic energy profiles in the recovery region. A new real-time hotwire scheme was developed to make measurements in the three-dimensional turbulent boundary layer over the full-coverage surface.

  3. Regional study of the Archean to Proterozoic crust at the Sudbury Neutrino Observatory (SNO+), Ontario: Predicting the geoneutrino flux

    NASA Astrophysics Data System (ADS)

    Huang, Yu; Strati, Virginia; Mantovani, Fabio; Shirey, Steven B.; McDonough, William F.

    2014-10-01

    SNO+ detector that is currently under construction in Ontario, Canada, will be a new kiloton-scale liquid scintillation detector with the capability of recording geoneutrino events that can be used to constrain the strength of the Earth's radiogenic power, and in turn, to test compositional models of the bulk silicate Earth (BSE). We constructed a detailed 3-D model of the regional crust centered at SNO+ from compiled geological, geophysical, and geochemical information. Crustal cross sections obtained from refraction and reflection seismic surveys were used to characterize the crust and assign uncertainties to its structure. The average Moho depth in the study area is 42.3 ± 2.6 km. The upper crust was divided into seven dominant lithologic units on the basis of regional geology. The abundances of U and Th and their uncertainties in each upper crustal lithologic unit were determined from analyses of representative outcrop samples. The average chemical compositions of the middle and lower crust beneath the SNO+ region were determined by coupling local seismic velocity profiles with a global compilation of the chemical compositions of amphibolite and granulite facies rocks. Monte Carlo simulations were used to predict the geoneutrino signal originating from the regional crust at SNO+ and to track asymmetrical uncertainties of U and Th abundances. The total regional crust contribution of the geoneutrino signal at SNO+ is predicted to be 15.6-3.4+5.3 TNU (a Terrestrial Neutrino Unit is one geoneutrino event per 1032 target protons per year), with the Huronian Supergroup near SNO+ dominantly contributing 7.3-3.0+5.0 TNU to this total. Future systematically sampling of this regional unit and denser seismic surveys will better model its composition and structure, and thus reduce the uncertainty on geoneutrino signal at SNO+. The bulk crustal geoneutrino signal at SNO+ is estimated to be 30.7-4.2+6.0 TNU, which is lower than that predicted in a global-scale reference

  4. UNESCO-UNEVOC Regional Forum Asia and Pacific: Advancing TVET for Youth Employability and Sustainable Development (Seoul, Republic of Korea, September 4-6, 2013). Meeting Report

    ERIC Educational Resources Information Center

    UNESCO-UNEVOC International Centre for Technical and Vocational Education and Training, 2013

    2013-01-01

    To strengthen global and regional harmonization for the advancement of TVET transformation through the capacities of UNEVOC's unique global Network of specialized TVET institutions and affiliated partners, the UNESCO-UNEVOC International Centre organized a series of meetings to be held in all regions of the world. The meetings are organized…

  5. Improved sea level anomaly prediction through combination of data relationship analysis and genetic programming in Singapore Regional Waters

    NASA Astrophysics Data System (ADS)

    Kurniawan, Alamsyah; Ooi, Seng Keat; Babovic, Vladan

    2014-11-01

    With recent advances in measurement and information technology, there is an abundance of data available for analysis and modelling of hydrodynamic systems. Spatial and temporal data coverage, better quality and reliability of data modelling and data driven techniques have resulted in more favourable acceptance by the hydrodynamic community. The data mining tools and techniques are being applied in variety of hydro-informatics applications ranging from data mining for pattern discovery to data driven models and numerical model error correction. The present study explores the feasibility of applying mutual information theory by evaluating the amount of information contained in observed and prediction errors of non-tidal barotropic numerical modelling (i.e. assuming that the hydrodynamic model, available at this point, is best representation of the physics in the domain of interest) by relating them to variables that reflect the state at which the predictions are made such as input data, state variables and model output. In addition, the present study explores the possibility of employing ‘genetic programming' (GP) as an offline data driven modelling tool to capture the sea level anomaly (SLA) dynamics and then using them for updating the numerical model prediction in real time applications. These results suggest that combination of data relationship analysis and GP models helps to improve the forecasting ability by providing information of significant predicative parameters. It is found that GP based SLA prediction error forecast model can provide significant improvement when applied as data assimilation schemes for updating the SLA prediction obtained from primary hydrodynamic models.

  6. Clinical Dementia Rating Performed Several Years prior to Death Predicts Regional Alzheimer’s Neuropathology

    PubMed Central

    Beeri, Michal Schnaider; Silverman, Jeremy M.; Schmeidler, James; Wysocki, Michael; Grossman, Hillel Z.; Purohit, Dushyant P.; Perl, Daniel P.; Haroutunian, Vahram

    2011-01-01

    Aims To assess the relationships between early and late antemortem measures of dementia severity and Alzheimer disease (AD) neuropathology severity. Methods 40 residents of a nursing home, average age at death 82.0, participated in this longitudinal cohort study with postmortem assessment. Severity of dementia was measured by Clinical Dementia Rating (CDR) at two time points, averaging 4.5 and 1.0 years before death. Densities of postmortem neuritic plaques (NPs) and neurofibrillary tangles (NFTs) were measured in the cerebral cortex, hippocampus, and entorhinal cortex. Results For most brain areas, both early and late CDRs were significantly associated with NPs and NFTs. CDRs assessed proximal to death predicted NFTs beyond the contribution of early CDRs. NPs were predicted by both early and late CDRs. NPs were predictive of both early and late CDRs after controlling for NFTs. NFTs were only associated significantly with late CDR in the cerebral cortex after controlling for NPs. Conclusions Even if assessed several years before death, dementia severity is associated with AD neuropathology. NPs are more strongly associated with dementia severity than NFTs. NFTs consistently associate better with late than early CDR, suggesting that these neuropathological changes may occur relatively later in the course of the disease. PMID:18367838

  7. Classification and flow prediction in a data-scarce watershed of the Equatorial Nile region

    NASA Astrophysics Data System (ADS)

    Kileshye Onema, J.-M.; Taigbenu, A.; Ndiritu, J.

    2011-04-01

    Continuous developments and investigations in flow prediction are of interest in watershed hydrology especially where watercourses are poorly gauged and data are scarce like in most parts of Africa. Thus, this paper reports on two approaches to generate local monthly runoff of the data-scarce Semliki watershed. The Semliki River is part of the upper drainage of the Albert Nile. With an average annual local runoff of 4.622 km3, the Semliki watershed contributes up to 20% of the flows of the White Nile. The watershed was sub-divided in 21 subcatchments (S3 to S23); eight physiographic attributes from remotely sensed acquired datasets and limited ground information were generated for each subcatchments and used to forecast monthly volumes. One ordination technique, the Principal Component Analysis (PCA) and the tree clustering analysis of the landform attributes was performed to study the data structure and spot physiographic similarities between subcatchments. The PCA revealed the existence of two major groups of subcatchments. Multi-linear and polynomial regressions were the two modeling approaches used to predict the long-term monthly mean of discharges for the two types of subcatchments identified in the Semliki watershed. The ranges of multiple R, the multiple R2, and the adjusted R2 for the multi-linear and the polynomial models were, respectively 0.96-0.99; 0.93-0.99 and 0.92-0.99. The linearity assumption provided less accurate predictions.

  8. Application of the Wind Erosion Prediction System in the AIRPACT regional air quality modeling framework

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Wind erosion of soil is a major concern of the agricultural community as it removes the most fertile part of the soil and thus degrades soil productivity. Furthermore, dust emissions due to wind erosion contribute to poor air quality, reduce visibility, and cause perturbations to regional radiation ...

  9. Pre-season prediction of regional rainfed wheat yield in Northern Greece with CERES-Wheat

    NASA Astrophysics Data System (ADS)

    Mavromatis, T.

    2014-08-01

    The present study aims at forecasting hard wheat ( Triticum turgidum L. var. durum) yield in northern Greece, a season prior to harvest. It is based on (a) crop simulated, with CERES-Wheat indicators at four planting dates and (b) reported crop yields at two regional levels (three NUTS2 [ Nomenclature of Units for Territorial Statistics] and 16 NUTS3 regions), for the years 1979-2006. Principal component analysis (PCA) was applied to explore major patterns of joint variability in 20 crop simulated agroclimatic indicators of the growing season before harvest. Stepwise regression and hindcast were employed for the selection of the modes identified by PCA as predictors in multivariate linear regression models used for forecasting yield a season ahead of harvest. Forecasting skill varied to a large extent by spatial scale and planting date. When the simulation results aggregated to the larger spatial level (NUTS2), the yield forecasting skill, in terms of R2, was rated as high (ranging from 0.48 to 0.73) in three out of four planting dates for Central Macedonia and in one planting ( R 2 = 0.57) for Thrace. Harvest index, nitrogen leaching and related soil water crop simulated output of the previous season, were the most important predictors. No forecasting skill was found in the third NUTS2 region. The performance of the regression models substantially deteriorated at the higher resolution spatial level (NUTS3). In four regions only (including the one where CERES-Wheat was calibrated) yield forecasting skill was moderate ( R 2 > 0.25). The results demonstrate the potential of this approach for regional crop yield forecasting before the beginning of the cropping season. However, crop model calibration is required before its application.

  10. Advancing hydrometeorological prediction capabilities through standards-based cyberinfrastructure development: The community WRF-Hydro modeling system

    NASA Astrophysics Data System (ADS)

    gochis, David; Parodi, Antonio; Hooper, Rick; Jha, Shantenu; Zaslavsky, Ilya

    2013-04-01

    The need for improved assessments and predictions of many key environmental variables is driving a multitude of model development efforts in the geosciences. The proliferation of weather and climate impacts research is driving a host of new environmental prediction model development efforts as society seeks to understand how climate does and will impact key societal activities and resources and, in turn, how human activities influence climate and the environment. This surge in model development has highlighted the role of model coupling as a fundamental activity itself and, at times, a significant bottleneck in weather and climate impacts research. This talk explores some of the recent activities and progress that has been made in assessing the attributes of various approaches to the coupling of physics-based process models for hydrometeorology. One example modeling system that is emerging from these efforts is the community 'WRF-Hydro' modeling system which is based on the modeling architecture of the Weather Research and Forecasting (WRF). An overview of the structural components of WRF-Hydro will be presented as will results from several recent applications which include the prediction of flash flooding events in the Rocky Mountain Front Range region of the U.S. and along the Ligurian coastline in the northern Mediterranean. Efficient integration of the coupled modeling system with distributed infrastructure for collecting and sharing hydrometeorological observations is one of core themes of the work. Specifically, we aim to demonstrate how data management infrastructures used in the US and Europe, in particular data sharing technologies developed within the CUAHSI Hydrologic Information System and UNIDATA, can interoperate based on international standards for data discovery and exchange, such as standards developed by the Open Geospatial Consortium and adopted by GEOSS. The data system we envision will help manage WRF-Hydro prediction model data flows, enabling

  11. Predicting Clear-Sky Reflectance Over Snow/Ice in Polar Regions

    NASA Technical Reports Server (NTRS)

    Chen, Yan; Sun-Mack, Sunny; Arduini, Robert F.; Hong, Gang; Minnis, Patrick

    2015-01-01

    Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the nearinfrared (NIR; 1.24, 1.6 or 2.13 micrometers), visible (VIS; 0.63 micrometers) and vegetation (VEG; 0.86 micrometers) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) to help identify clouds and retrieve their properties in both snow-free and snow-covered conditions. Thus, it is critical to have reliable distributions of clear-sky albedo for all of these channels. In CERES Edition 4 (Ed4), the 1.24-micrometer channel is used to retrieve cloud optical depth over snow/ice-covered surfaces. Thus, it is especially critical to accurately predict the 1.24-micrometer clear-sky albedo alpha and reflectance rho for a given location and time. Snow albedo and reflectance patterns are very complex due to surface texture, particle shapes and sizes, melt water, and vegetation protrusions from the snow surface. To minimize those effects, this study focuses on the permanent snow cover of Antarctica where vegetation is absent and melt water is minimal. Clear-sky albedos are determined as a function of solar zenith angle (SZA) from observations over all scenes determined to be cloud-free to produce a normalized directional albedo model (DRM). The DRM is used to develop alpha(SZA=0 degrees) on 10 foot grid for each season. These values provide the basis for predicting r at any location and set of viewing & illumination conditions. This paper examines the accuracy of this approach for two theoretical snow surface reflectance models.

  12. Predicting the susceptibility to gully initiation in data-poor regions

    NASA Astrophysics Data System (ADS)

    Dewitte, Olivier; Daoudi, Mohamed; Bosco, Claudio; Van Den Eeckhaut, Miet

    2015-01-01

    Permanent gullies are common features in many landscapes and quite often they represent the dominant soil erosion process. Once a gully has initiated, field evidence shows that gully channel formation and headcut migration rapidly occur. In order to prevent the undesired effects of gullying, there is a need to predict the places where new gullies might initiate. From detailed field measurements, studies have demonstrated strong inverse relationships between slope gradient of the soil surface (S) and drainage area (A) at the point of channel initiation across catchments in different climatic and morphological environments. Such slope-area thresholds (S-A) can be used to predict locations in the landscape where gullies might initiate. However, acquiring S-A requires detailed field investigations and accurate high resolution digital elevation data, which are usually difficult to acquire. To circumvent this issue, we propose a two-step method that uses published S-A thresholds and a logistic regression analysis (LR). S-A thresholds from the literature are used as proxies of field measurement. The method is calibrated and validated on a watershed, close to the town of Algiers, northern Algeria, where gully erosion affects most of the slopes. The gullies extend up to several kilometres in length and cover 16% of the study area. First we reconstruct the initiation areas of the existing gullies by applying S-A thresholds for similar environments. Then, using the initiation area map as the dependent variable with combinations of topographic and lithological predictor variables, we calibrate several LR models. It provides relevant results in terms of statistical reliability, prediction performance, and geomorphological significance. This method using S-A thresholds with data-driven assessment methods like LR proves to be efficient when applied to common spatial data and establishes a methodology that will allow similar studies to be undertaken elsewhere.

  13. Initialization of soil-water content in regional-scale atmospheric prediction models

    NASA Technical Reports Server (NTRS)

    Smith, Christopher B.; Lakhtakia, Mercedes; Capehart, William J.; Carlson, Toby N.

    1994-01-01

    The purpose of this study is to demonstrate the feasibility of determining the soil-water content fields required as initial conditions for land surface components within atmospheric prediction models. This is done using a model of the hydrologic balance and conventional meteorological observations, land cover, and soils information. A discussion is presented of the subgrid-scale effects, the integration time, and the choice of vegetation type on the soil-water content patterns. Finally, comparisons are made between two The Pennsylvania State University/National Center for Atmospheric Research mesoscale model simulations, one using climatological fields and the other one using the soil-moisture fields produced by this new method.

  14. Surface impedance method applied to the prediction of eddy currents in hydrogenerator stator end regions

    SciTech Connect

    Silva, V.C.; Marechal, Y.; Foggia, A.

    1995-05-01

    A three-dimensional finite-element analysis is employed to investigate the losses of hydrogenerator stator end regions by using surface-impedance boundary conditions. The three-dimensional complexity of the end-winding geometry is fully taken into account by the model. The purpose of this work is also to evaluate the eddy-current paths allowing for slits in the stator teeth and their effectiveness in reducing stator core-end losses. The methodology was applied to the stator core of a 52-pole 300-MVA hydrogenerator in two different cases: (1) with non-slit teeth; (2) with fully slit teeth. It may also be extended to large turbogenerators end regions.

  15. Learning to predict where human gaze is using quaternion DCT based regional saliency detection

    NASA Astrophysics Data System (ADS)

    Li, Ting; Xu, Yi; Zhang, Chongyang

    2014-09-01

    Many current visual attention approaches used semantic features to accurately capture human gaze. However, these approaches demand high computational cost and can hardly be applied to daily use. Recently, some quaternion-based saliency detection models, such as PQFT (phase spectrum of Quaternion Fourier Transform), QDCT (Quaternion Discrete Cosine Transform), have been proposed to meet real-time requirement of human gaze tracking tasks. However, current saliency detection methods used global PQFT and QDCT to locate jump edges of the input, which can hardly detect the object boundaries accurately. To address the problem, we improved QDCT-based saliency detection model by introducing superpixel-wised regional saliency detection mechanism. The local smoothness of saliency value distribution is emphasized to distinguish noises of background from salient regions. Our algorithm called saliency confidence can distinguish the patches belonging to the salient object and those of the background. It decides whether the image patches belong to the same region. When an image patch belongs to a region consisting of other salient patches, this patch should be salient as well. Therefore, we use saliency confidence map to get background weight and foreground weight to do the optimization on saliency map obtained by QDCT. The optimization is accomplished by least square method. The optimization approach we proposed unifies local and global saliency by combination of QDCT and measuring the similarity between each image superpixel. We evaluate our model on four commonly-used datasets (Toronto, MIT, OSIE and ASD) using standard precision-recall curves (PR curves), the mean absolute error (MAE) and area under curve (AUC) measures. In comparison with most state-of-art models, our approach can achieve higher consistency with human perception without training. It can get accurate human gaze even in cluttered background. Furthermore, it achieves better compromise between speed and accuracy.

  16. Role of Haematological Changes in Predicting Occurrence of Leishmaniasis- A Study in Kumaon Region of Uttarakhand

    PubMed Central

    Pant, Prabhat; Chachra, Upasna; Singh, Paramjeet; Thapliyal, Naveen; Rawat, Vinita

    2016-01-01

    Introduction A number of cases of Leishmaniasis have been reported from non-endemic sub-himalayan regions of India. Due to low clinical suspicion and atypical presentation, cases may go undetected or there may be a delay in diagnosis. Aim The aim of the study was to evaluate clinico-haematological parameters and bone marrow findings so that a high degree of suspicion could be made in unsuspected cases of Visceral Leishmaniasis (VL) and Leishman Donovan (LD) body negative bone marrow smears. Materials and Methods A retrospective study was conducted at a tertiary care centre serving the kumaon region of Uttarakhand from 2010 to 2014. Forty bone marrow aspirates were included, which were sent on clinical suspicion of VL. Twenty cases were positive for LD bodies. Their clinico-haematological features including bone marrow findings were studied in detail and compared with rest of the 20 LD negative cases. Five LD negative cases were also positive for rk39. Results Twenty LD positive cases were evaluated. Splenomegaly was the most common sign present in 17 cases (85%). Anaemia, leucopenia and lymphocytosis were present in all the cases (100%). Pancytopenia was seen in 17 cases (85%). Microcytic hypochromic blood picture was the most common finding in 11 cases (55%). Bone marrow was normocellular in 7 cases (35%), hypercellular in 7 cases (35%). Erythropoesis was micro-normoblastic in 11 cases (55%). Overall, there were 25 cases of VL (20 LD positive, 5 LD negative). Increased plasma cells, lymphocytes and histiocytes were seen in 17 cases (68%) of VL. Conclusion In non-endemic region where clinical suspicion is low, bone marrow findings can be a strong indicator for VL even though marrow is negative for LD bodies. If required other ancillary investigations can also be ordered. This study also emphasizes the need for epidemiological work up in this region. PMID:27437230

  17. Regional cerebellar volumes predict functional outcome in children with cerebellar malformations.

    PubMed

    Bolduc, Marie-Eve; du Plessis, Adre J; Sullivan, Nancy; Guizard, Nicolas; Zhang, Xun; Robertson, Richard L; Limperopoulos, Catherine

    2012-06-01

    The cerebellum has recently been recognized for its role in high-order functions, including cognition, language, and behavior. Recent studies have also begun to describe a functional topography of the mature cerebellum that includes organization on a mediolateral axis. However, no study to date has examined the relationship between regional cerebellar volume and developmental disabilities in children with cerebellar malformations. The objective of this study was to estimate the extent to which total and regional cerebellar volumes are associated with developmental disabilities in a cohort of children with cerebellar malformations. Children aged 1 to 6 years with a diagnosis of cerebellar malformation underwent standardized outcome measures and quantitative magnetic resonance scanning. The cerebellum was parcellated into seven mediolateral zones (three for each hemisphere plus the vermis) for regional volume analysis. In children with cerebellar malformations, decreased total cerebellar volume was associated with delays in global development, expressive language, cognition, as well as gross and fine motor function. Decreased volume in the right lateral cerebellar hemisphere was related to impaired cognition, expressive language, and gross motor function. Additionally, reduced vermis volume was associated with impaired global development, cognition, expressive language, and gross and fine motor skills, as well as behavior problems and a higher rate of positive autism spectrum screening test. These results begin to define the structural topography of functional outcome in children with cerebellar malformations and should lead to greater accuracy of prognostication as well as timely early developmental interventions.

  18. Does ecosystem sensitivity to precipitation at the site-level conform to regional-scale predictions?.

    PubMed

    Wilcox, Kevin R; Blair, John M; Smith, Melinda D; Knapp, Alan K

    2016-03-01

    Central to understanding global C cycle dynamics is the functional relationship between precipitation and net primary production (NPP). At large spatial (regional) scales, the responsiveness of aboveground NPP (ANPP) to interannual variation in annual precipitation (AP; ANPPsens) is inversely related to site-level ANPP, coinciding with turnover of plant communities along precipitation gradients. Within ecosystems experiencing chronic alterations in water availability, plant community change will also occur with unknown consequences for ANPPsens. To examine the role plant community shifts may play in determining alterations in site-level ANPPPsens, we experimentally increased precipitation by approximately 35% for two decades in a native Central U.S. grassland. Consistent with regional models, ANPPsens decreased initially as water availability and ANPP increased. However, ANPPsens shifted back to ambient levels when mesic species increased in abundance in the plant community. Similarly, in grassland sites with distinct mesic and xeric plant communities and corresponding 50% differences in ANPP, ANPPsens did not differ over almost three decades. We conclude that responses in ANPPsens to chronic alterations in water availability within an ecosystem may not conform to regional AP-ANPP patterns, despite expected changes in ANPP and plant communities. The result is unanticipated functional resistance to climate change at the site scale. PMID:27197383

  19. Regional amplitude of the low-frequency fluctuations at rest predicts word-reading skill.

    PubMed

    Xu, M; De Beuckelaer, A; Wang, X; Liu, L; Song, Y; Liu, J

    2015-07-01

    Individuals' reading skills are critical for their educational development, but variation in reading skills is known to be large. The present study used functional magnetic resonance imaging (fMRI) to examine the role of spontaneous brain activity at rest in individual differences in reading skills in a large sample of participants (N=263). Specifically, we correlated individuals' word-reading skill with their fractional amplitude of low-frequency fluctuation (fALFF) of the whole brain at rest and found that the fALFFs of both the bilateral precentral gyrus (PCG) and superior temporal plane (STP) were positively associated with reading skills. The fALFF-reading association observed in these two regions remained after controlling for general cognitive abilities and in-scanner head motion. A cross-validation confirmed that the individual differences in word-reading skills were reliably correlated with the fALFF values of the bilateral PCG and STP. A follow-up task-based fMRI experiment revealed that the reading-related regions overlapped with regions showing a higher response to sentences than to pseudo-sentences (strings of pseudo-words), suggesting the resting-state brain activity partly captures the characteristics of task-based brain activity. In short, our study provides one of the first pieces of evidence that links spontaneous brain activity to reading behavior and offers an easy-to-access neural marker for evaluating reading skill.

  20. Regional amplitude of the low-frequency fluctuations at rest predicts word-reading skill.

    PubMed

    Xu, M; De Beuckelaer, A; Wang, X; Liu, L; Song, Y; Liu, J

    2015-07-01

    Individuals' reading skills are critical for their educational development, but variation in reading skills is known to be large. The present study used functional magnetic resonance imaging (fMRI) to examine the role of spontaneous brain activity at rest in individual differences in reading skills in a large sample of participants (N=263). Specifically, we correlated individuals' word-reading skill with their fractional amplitude of low-frequency fluctuation (fALFF) of the whole brain at rest and found that the fALFFs of both the bilateral precentral gyrus (PCG) and superior temporal plane (STP) were positively associated with reading skills. The fALFF-reading association observed in these two regions remained after controlling for general cognitive abilities and in-scanner head motion. A cross-validation confirmed that the individual differences in word-reading skills were reliably correlated with the fALFF values of the bilateral PCG and STP. A follow-up task-based fMRI experiment revealed that the reading-related regions overlapped with regions showing a higher response to sentences than to pseudo-sentences (strings of pseudo-words), suggesting the resting-state brain activity partly captures the characteristics of task-based brain activity. In short, our study provides one of the first pieces of evidence that links spontaneous brain activity to reading behavior and offers an easy-to-access neural marker for evaluating reading skill. PMID:25896801

  1. Impaired Activation in Cognitive Control Regions Predicts Reversal Learning in Schizophrenia.

    PubMed

    Culbreth, Adam J; Gold, James M; Cools, Roshan; Barch, Deanna M

    2016-03-01

    Reinforcement learning deficits have been associated with schizophrenia (SZ). However, the pathophysiology that gives rise to these abnormalities remains unclear. To address this question, SZ patients (N = 58) and controls (CN; N = 36) completed a probabilistic reversal-learning paradigm during functional magnetic resonance imaging scanning. During the task, participants choose between 2 stimuli. Initially, 1 stimulus was frequently rewarded (80%); the other was infrequently rewarded (20%). The reward contingencies reversed periodically because the participant learned the more rewarded stimulus. The results indicated that SZ patients achieved fewer reversals than CN, and demonstrated decreased winstay-loseshift decision-making behavior. On loseshift compared to winstay trials, SZ patients showed reduced Blood Oxygen Level Dependent activation compared to CN in a network of brain regions widely associated with cognitive control, and striatal regions. Importantly, relationships between group membership and behavior were mediated by alterations in the activity of cognitive control regions, but not striatum. These findings indicate an important role for the cognitive control network in mediating the use and updating of value representations in SZ. Such results provide biological targets for further inquiry because researchers attempt to better characterize decision-making neural circuitry in SZ as a means to discover new pathways for interventions. PMID:26049083

  2. Body regional distribution and stratification of fatty acids in the blubber of New Zealand sea lions: implications for diet predictions.

    PubMed

    Lambert, Antoine; Meynier, Laureline; Donaldson, Laura C; Roe, Wendi D; Morel, Patrick C H

    2013-01-01

    Fatty acids (FAs) from blubber are often analysed to assess the diet of marine mammals. However, distribution of blubber FAs is not necessarily uniform along the body. It is therefore important to understand the deposition of dietary fat to be able to estimate the diet. We analysed the FA compositions of the thoracic ventral (T region) blubber of 28 New Zealand (NZ) sea lions Phocarctos hookeri by-caught by the southern arrow squid Nototodarus sloani fishery. Each blubber sample was divided into an inner and an outer layer. For 16 of these 28 animals, the pelvic dorsal (P) region was also sampled. The influence of body region and layer was statistically tested on the distribution of blubber FAs. We found minimal differences between the P and T regions (3 out of 29 FAs). The outer blubber layer was more concentrated in short-chain monounsaturated FAs, and less concentrated in saturated FAs, but the degree of stratification was small. Diet predictions from quantitative FA signature analysis (QFASA) applied on different body regions were similar. When applied to different blubber layers, QFASA gave some variation in the contribution of rattails (~25 % in outer blubber vs. ~12 % in inner blubber). Nonetheless, diet predicted from both layers was dominated by similar prey species: octopus, hoki and rattails. Hoki and rattails shared a similar ecological niche. Therefore, feeding ecology of NZ sea lions inferred from the inner or the outer blubber would lead to the same conclusions. In the case of NZ sea lions, the outer layer of blubber, if the only sample accessible, could be a useful tissue for diet inference from FAs.

  3. 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.

  4. 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

  5. Predictive combinatorial design of mRNA translation initiation regions for systematic optimization of gene expression levels

    PubMed Central

    Seo, Sang Woo; Yang, Jae-Seong; Cho, Han-Saem; Yang, Jina; Kim, Seong Cheol; Park, Jong Moon; Kim, Sanguk; Jung, Gyoo Yeol

    2014-01-01

    Balancing the amounts of enzymes is one of the important factors to achieve optimum performance of a designed metabolic pathway. However, the random mutagenesis approach is impractical since it requires searching an unnecessarily large number of variants and often results in searching a narrow range of expression levels which are out of optimal level. Here, we developed a predictive combinatorial design method, called UTR Library Designer, which systematically searches a large combinatorial space of expression levels. It accomplishes this by designing synthetic translation initiation region of mRNAs in a predictive way based on a thermodynamic model and genetic algorithm. Using this approach, we successfully enhanced lysine and hydrogen production in Escherichia coli. Our method significantly reduced the number of variants to be explored for covering large combinatorial space and efficiently enhanced pathway efficiency, thereby facilitating future efforts in metabolic engineering and synthetic biology. PMID:24682040

  6. Regional Myocardial Sympathetic Denervation Predicts the Risk of Sudden Cardiac Arrest in Ischemic Cardiomyopathy

    PubMed Central

    Fallavollita, James A.; Heavey, Brendan M.; Luisi, Andrew J.; Michalek, Suzanne M.; Baldwa, Sunil; Mashtare, Terry L.; Hutson, Alan D.; deKemp, Robert A.; Haka, Michael S.; Sajjad, Munawwar; Cimato, Thomas R.; Curtis, Anne B.; Cain, Michael E.; Canty, John M.

    2014-01-01

    Objectives The PAREPET (Prediction of ARrhythmic Events with Positron Emission Tomography) study sought to test the hypothesis that quantifying inhomogeneity in myocardial sympathetic innervation could identify patients at highest risk for sudden cardiac arrest (SCA). Background Left ventricular ejection fraction (LVEF) is the only parameter identifying patients at risk of SCA who benefit from an implantable cardiac defibrillator (ICD). Methods We prospectively enrolled 204 subjects with ischemic cardiomyopathy (LVEF ≤35%) eligible for primary prevention ICDs. Positron emission tomography (PET) was used to quantify myocardial sympathetic denervation (11C-meta-hydroxyephedrine [11C-HED]), perfusion (13N-ammonia) and viability (insulin-stimulated 18F-2-deoxyglucose). The primary endpoint was SCA defined as arrhythmic death or ICD discharge for ventricular fibrillation or ventricular tachycardia >240 beats/min. Results After 4.1 years follow-up, cause-specific SCA was 16.2%. Infarct volume (22 ± 7% vs. 19 ± 9% of left ventricle [LV]) and LVEF (24 ± 8% vs. 28 ± 9%) were not predictors of SCA. In contrast, patients developing SCA had greater amounts of sympathetic denervation (33 ± 10% vs. 26 ± 11% of LV; p = 0.001) reflecting viable, denervated myocardium. The lower tertiles of sympathetic denervation had SCA rates of 1.2%/year and 2.2%/year, whereas the highest tertile had a rate of 6.7%/year. Multivariate predictors of SCA were PET sympathetic denervation, left ventricular end-diastolic volume index, creatinine, and no angiotensin inhibition. With optimized cut-points, the absence of all 4 risk factors identified low risk (44% of cohort; SCA <1%/year); whereas ≥2 factors identified high risk (20% of cohort; SCA ~12%/year). Conclusions In ischemic cardiomyopathy, sympathetic denervation assessed using 11C-HED PET predicts cause-specific mortality from SCA independently of LVEF and infarct volume. This may provide an improved approach for the identification

  7. Predictive models of autism spectrum disorder based on brain regional cortical thickness.

    PubMed

    Jiao, Yun; Chen, Rong; Ke, Xiaoyan; Chu, Kangkang; Lu, Zuhong; Herskovits, Edward H

    2010-04-01

    Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a wide phenotypic range, often affecting personality and communication. Previous voxel-based morphometry (VBM) studies of ASD have identified both gray- and white-matter volume changes. However, the cerebral cortex is a 2-D sheet with a highly folded and curved geometry, which VBM cannot directly measure. Surface-based morphometry (SBM) has the advantage of being able to measure cortical surface features, such as thickness. The goals of this study were twofold: to construct diagnostic models for ASD, based on regional thickness measurements extracted from SBM, and to compare these models to diagnostic models based on volumetric morphometry. Our study included 22 subjects with ASD (mean age 9.2+/-2.1 years) and 16 volunteer controls (mean age 10.0+/-1.9 years). Using SBM, we obtained regional cortical thicknesses for 66 brain structures for each subject. In addition, we obtained volumes for the same 66 structures for these subjects. To generate diagnostic models, we employed four machine-learning techniques: support vector machines (SVMs), multilayer perceptrons (MLPs), functional trees (FTs), and logistic model trees (LMTs). We found that thickness-based diagnostic models were superior to those based on regional volumes. For thickness-based classification, LMT achieved the best classification performance, with accuracy=87%, area under the receiver operating characteristic (ROC) curve (AUC)=0.93, sensitivity=95%, and specificity=75%. For volume-based classification, LMT achieved the highest accuracy, with accuracy=74%, AUC=0.77, sensitivity=77%, and specificity=69%. The thickness-based diagnostic model generated by LMT included 7 structures. Relative to controls, children with ASD had decreased cortical thickness in the left and right pars triangularis, left medial orbitofrontal gyrus, left parahippocampal gyrus, and left frontal pole, and increased cortical thickness in the left caudal anterior

  8. Final Report on Hierarchical Coupled Modeling and Prediction of Regional Climate Change in the Atlantic Sector

    SciTech Connect

    Saravanan, Ramalingam

    2011-10-30

    During the course of this project, we have accomplished the following: a) Carried out studies of climate changes in the past using a hierarchy of intermediate coupled models (Chang et al., 2008; Wan et al 2009; Wen et al., 2010a,b) b) Completed the development of a Coupled Regional Climate Model (CRCM; Patricola et al., 2011a,b) c) Carried out studies testing hypotheses testing the origin of systematic errors in the CRCM (Patricola et al., 2011a,b) d) Carried out studies of the impact of air-sea interaction on hurricanes, in the context of barrier layer interactions (Balaguru et al)

  9. Brachytherapy boost in loco-regionally advanced nasopharyngeal carcinoma: a prospective randomized trial of the International Atomic Energy Agency

    PubMed Central

    2014-01-01

    Abstact Background The purpose was to determine whether a brachytherapy boost improves outcomes in patients with advanced nasopharyngeal carcinoma treated with standard chemo-radiotherapy. Methods Patients with nasopharyngeal carcinoma WHO grades I-III and TNM stages III or non-metastatic stage IV were eligible for this phase III study. Patients were randomized to either arm (A) induction chemotherapy, followed by external beam radiotherapy (EBRT) with concomitant cisplatin (n = 139) or arm (B), the same schedule plus a brachytherapy boost to the nasopharynx (n = 135). The EBRT doses given were 70 Gy to the primary tumour and positive lymph nodes and 46 Gy to the negative neck. The additional brachytherapy boost in arm (B) was given by either low dose-rate (LDR – 11 Gy) or high dose-rate (HDR – 3 fractions of 3.0 Gy) brachytherapy. The primary endpoint was 3-year overall survival (OS) and secondary endpoints were: local control, regional control, distant metastasis and grade 3–4 adverse events. Results 274 patients were randomized between September 2004 and December 2008. The two arms were comparable with regard to age, gender, stage and grade. 273 patients completed treatment. Median follow-up was 29 months (0.2-67 months). The effect of treatment arm, country, age, gender, WHO pathology, stage (T3-4, N2-3 versus other) and chemotherapy on overall survival (OS), disease-free survival (DFS) and local recurrence-free survival (LRFS) was studied. Stage significantly affected OS (p = 0.024) and DFS (p = 0.018) while age significantly affected OS (p = 0.014). None of the other factors studied were significant. The 3-year LRFS was 60.5% and 54.4% in arms A and B respectively (p = 0.647). The 3-year regional control rate in the neck was 59.7% and 54.3% respectively (p = 0.7). Distant metastasis developed in 59.7% of patients in arm A and 55.4% in arm B (p = 0.377). Patients with T1/T2 N + had a 3 year LRFS of 51.8% in Arm A (62 patients) versus 57.9% in Arm B (67

  10. Postirradiation evaluations of capsules HANS-1 and HANS-2 irradiated in the HFIR target region in support of fuel development for the advanced neutron source

    SciTech Connect

    Hofman, G.L.; Snelgrove, J.L.; Copeland, G.L.

    1995-08-01

    This report describes the design, fabrication, irradiation, and evaluation of two capsule tests containing U{sub 3}Si{sub 2} fuel particles in contact with aluminum. The tests were in support of fuel qualification for the Advanced Neutron Source (ANS) reactor, a high-powered research reactor that was planned for the Oak Ridge National Laboratory. At the time of these tests, the fuel consisted of U{sub 3}Si{sub 2}, containing highly enriched uranium dispersed in aluminum at a volume fraction of {approximately}0.15. The extremely high thermal flux in the target region of the High Flux Isotope Reactor provided up to 90% burnup in one 23-d cycle. Temperatures up to 450{degrees}C were maintained by gamma heating. Passive SiC temperature monitors were employed. The very small specimen size allowed only microstructural examination of the fuel particles but also allowed many specimens to be tested at a range of temperatures. The determination of fission gas bubble morphology by microstructural examination has been beneficial in developing a fuel performance model that allows prediction of fuel performance under these extreme conditions. The results indicate that performance of the reference fuel would be satisfactory under the ANS conditions. In addition to U{sub 3}Si{sub 2}, particles of U{sub 3}Si, UAl{sub 2}, UAl{sub x}, and U{sub 3}O{sub 8} were tested.

  11. Prognostic index score and clinical prediction model of local regional recurrence after mastectomy in breast cancer patients

    SciTech Connect

    Cheng, Skye Hongiun . E-mail: skye@mail.kfcc.org.tw; Horng, C.-F.; Clarke, Jennifer L.; Tsou, M.-H.; Tsai, Stella Y.; Chen, C.-M.; Jian, James J.; Liu, M.-C.; West, Mike; Huang, Andrew T.; Prosnitz, Leonard R.

    2006-04-01

    Purpose: To develop clinical prediction models for local regional recurrence (Lr) of breast carcinoma after mastectomy that will be superior to the conventional measures of tumor size and nodal status. Methods and Materials: Clinical information from 1,010 invasive breast cancer patients who had primary modified radical mastectomy formed the database of the training and testing of clinical prognostic and prediction models of LRR. Cox proportional hazards analysis and Bayesian tree analysis were the core methodologies from which these models were built. To generate a prognostic index model, 15 clinical variables were examined for their impact on LRR. Patients were stratified by lymph node involvement (<4 vs. {>=}4) and local regional status (recurrent vs. control) and then, within strata, randomly split into training and test data sets of equal size. To establish prediction tree models, 255 patients were selected by the criteria of having had LRR (53 patients) or no evidence of LRR without postmastectomy radiotherapy (PMRT) (202 patients). Results: With these models, patients can be divided into low-, intermediate-, and high-risk groups on the basis of axillary nodal status, estrogen receptor status, lymphovascular invasion, and age at diagnosis. In the low-risk group, there is no influence of PMRT on either LRR or survival. For intermediate-risk patients, PMRT improves LR control but not metastases-free or overall survival. For the high-risk patients, however, PMRT improves both LR control and metastasis-free and overall survival. Conclusion: The prognostic score and predictive index are useful methods to estimate the risk of LRR in breast cancer patients after mastectomy and for estimating the potential benefits of PMRT. These models provide additional information criteria for selection of patients for PMRT, compared with the traditional selection criteria of nodal status and tumor size.

  12. The prediction of radiation-induced liver dysfunction using a local dose and regional venous perfusion model

    SciTech Connect

    Cao Yue; Platt, Joel F.; Francis, Isaac R; Balter, James M.; Pan, Charlie; Normolle, Daniel; Ben-Josef, Edgar; Haken, Randall K. ten; Lawrence, Theodore S.

    2007-02-15

    We have shown that high dose conformal radiation combined with chemotherapy appears to prolong the survival of patients with unresectable intrahepatic cancers. The ability to safely deliver higher doses is primarily limited by the development of radiation-induced liver disease, characterized by venous occlusion. In this study, we investigated whether portal venous perfusion measured prior to the end of radiation therapy (RT) together with dose could predict liver venous perfusion dysfunction after treatment. Ten patients with unresectable intrahepatic cancer participated in an IRB-approved computer tomography (CT) perfusion study. Hepatic arterial and portal vein perfusion distributions were estimated by using dynamic contrast enhanced CT and the single compartmental model. Scans were obtained at four time points: prior to t