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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

    Future inundation of the US Atlantic and Gulf coasts will depend upon both sea-level rise and the intensity and frequency of tropical cyclones, each of which will be affected by climate change. In this proposal, we will employ 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 US Atlantic and Gulf coasts has 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 distribution. 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. Here, we produce new high resolution proxy data of sea-level and temperature to provide crucial additional constraints to such semi-empirical models. Our dataset will span 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 six study areas (Massachusetts, New Jersey, North Carolina, Georgia and Atlantic and Gulf coasts of 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, in the future, the resultant

  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. A scoring system basing pathological parameters to predict regional lymph node metastasis after preoperative chemoradiotherapy for locally advanced rectal cancer: implication for local excision

    PubMed Central

    Wang, Xiao-Jie; Chi, Pan; Lin, Hui-Ming; Lu, Xing-Rong; Huang, Ying; Xu, Zong-Bin; Huang, Sheng-Hui; Sun, Yan-Wu; Ye, Dao-Xiong; Yu, Qian

    2016-01-01

    Local excision is an alternative to radical surgery that is indicated in patients with locally advanced rectal cancer (LARC) who have a good response to chemoradiotherapy (CRT). Regional lymph node status is a major uncertainty during local excision of LARC following CRT. We retrospectively reviewed clinicopathologic variables for 244 patients with LARC who were treated at our institute between December 2000 and December 2013 in order to identify independent predictors of regional lymph node metastasis. Multivariate analysis of the training sample demonstrated that histopathologic type, tumor size, and the presence of lymphovascular invasion were significant predictors of regional nodal metastasis. These variables were then incorporated into a scoring system in which the total scores were calculated based on the points assigned for each parameter. The area under the curve in the receiver operating characteristic analysis was 0.750, and the cutoff value for the total score to predict regional nodal metastasis was 7.5. The sensitivity of our system was 73.2% and the specificity was 69.4%. The sensitivity was 77.8% and the specificity was 51.2% when the scoring system was applied to the testing sample. Using this system, we could accurately predict regional nodal metastases in LARC patients following CRT, which may be useful for stratifying patients in clinical trials and selecting potential candidates for organ-sparing surgery following CRT for LARC PMID:27489356

  8. 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

  9. Regional Arctic System Model (RASM): A Tool to Advance Understanding and Prediction of Arctic Climate Change at Process Scales

    NASA Astrophysics Data System (ADS)

    Maslowski, W.; Roberts, A.; Osinski, R.; Brunke, M.; Cassano, J. J.; Clement Kinney, J. L.; Craig, A.; Duvivier, A.; Fisel, B. J.; Gutowski, W. J., Jr.; Hamman, J.; Hughes, M.; Nijssen, B.; Zeng, X.

    2014-12-01

    The Arctic is undergoing rapid climatic changes, which are some of the most coordinated changes currently occurring anywhere on Earth. They are exemplified by 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 Global Climate and Global Earth System Models (GC/ESMs) are in broad agreement with these changes, the rate of change in the GC/ESMs remains outpaced by observations. Reasons for that stem from a combination of coarse model resolution, inadequate parameterizations, unrepresented processes and a limited knowledge of physical and other real world interactions. We demonstrate the capability of the Regional Arctic System Model (RASM) in addressing some of the GC/ESM limitations in simulating observed seasonal to decadal variability and trends in the sea ice cover and climate. RASM is a high resolution, fully coupled, pan-Arctic climate model that uses the Community Earth System Model (CESM) framework. It uses the Los Alamos Sea Ice Model (CICE) and Parallel Ocean Program (POP) configured at an eddy-permitting resolution of 1/12° as well as the Weather Research and Forecasting (WRF) and Variable Infiltration Capacity (VIC) models at 50 km resolution. All RASM components are coupled via the CESM flux coupler (CPL7) at 20-minute intervals. RASM is an example of limited-area, process-resolving, fully coupled earth system model, which due to the additional constraints from lateral boundary conditions and nudging within a regional model domain facilitates detailed comparisons with observational statistics that are not possible with GC/ESMs. In this talk, we will emphasize the utility of RASM to understand sensitivity to variable parameter space, importance of critical processes, coupled feedbacks and ultimately to reduce uncertainty in arctic climate change projections.

  10. ESPC Regional Arctic Prediction System

    DTIC Science & Technology

    2014-09-30

    the Navy the capability to conduct short-term (1 week) to extended (2 weeks) coupled weather forecasts for the Arctic region. APPROACH To...sensitivity of the Arctic weather forecast to key numerical parameters; and 5) conduct extensive validation and verification of the coupled system and...SEP 2014 2. REPORT TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE ESPC Regional Arctic Prediction System 5a. CONTRACT

  11. 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

  12. Observation simulation experiments with regional prediction models

    NASA Technical Reports Server (NTRS)

    Diak, George; Perkey, Donald J.; Kalb, Michael; Robertson, Franklin R.; Jedlovec, Gary

    1990-01-01

    Research efforts in FY 1990 included studies employing regional scale numerical models as aids in evaluating potential contributions of specific satellite observing systems (current and future) to numerical prediction. One study involves Observing System Simulation Experiments (OSSEs) which mimic operational initialization/forecast cycles but incorporate simulated Advanced Microwave Sounding Unit (AMSU) radiances as input data. The objective of this and related studies is to anticipate the potential value of data from these satellite systems, and develop applications of remotely sensed data for the benefit of short range forecasts. Techniques are also being used that rely on numerical model-based synthetic satellite radiances to interpret the information content of various types of remotely sensed image and sounding products. With this approach, evolution of simulated channel radiance image features can be directly interpreted in terms of the atmospheric dynamical processes depicted by a model. Progress is being made in a study using the internal consistency of a regional prediction model to simplify the assessment of forced diabatic heating and moisture initialization in reducing model spinup times. Techniques for model initialization are being examined, with focus on implications for potential applications of remote microwave observations, including AMSU and Special Sensor Microwave Imager (SSM/I), in shortening model spinup time for regional prediction.

  13. 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…

  14. Advanced Computational Techniques in Regional Wave Studies

    DTIC Science & Technology

    1990-01-03

    the new GERESS data. The dissertation work emphasized the development and use of advanced computa- tional techniques for studying regional seismic...hand, the possibility of new data sources at regional distances permits using previously ignored signals. Unfortunately, these regional signals will...the Green’s function around this new reference point is containing the propagation effects, and V is the source Gnk(x,t;r,t) - (2) volume where fJk

  15. 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.

  16. Advanced technology for future regional transport aircraft

    NASA Technical Reports Server (NTRS)

    Williams, L. J.

    1982-01-01

    In connection with a request for a report coming from a U.S. Senate committee, NASA formed a Small Transport Aircraft Technology (STAT) team in 1978. STAT was to obtain information concerning the technical improvements in commuter aircraft that would likely increase their public acceptance. Another area of study was related to questions regarding the help which could be provided by NASA's aeronautical research and development program to commuter aircraft manufacturers with respect to the solution of technical problems. Attention is given to commuter airline growth, current commuter/region aircraft and new aircraft in development, prospects for advanced technology commuter/regional transports, and potential benefits of advanced technology. A list is provided of a number of particular advances appropriate to small transport aircraft, taking into account small gas turbine engine component technology, propeller technology, three-dimensional wing-design technology, airframe aerodynamics/propulsion integration, and composite structure materials.

  17. 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

  18. 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.

  19. Advancements in predictive plasma formation modeling

    NASA Astrophysics Data System (ADS)

    Purvis, Michael A.; Schafgans, Alexander; Brown, Daniel J. W.; Fomenkov, Igor; Rafac, Rob; Brown, Josh; Tao, Yezheng; Rokitski, Slava; Abraham, Mathew; Vargas, Mike; Rich, Spencer; Taylor, Ted; Brandt, David; Pirati, Alberto; Fisher, Aaron; Scott, Howard; Koniges, Alice; Eder, David; Wilks, Scott; Link, Anthony; Langer, Steven

    2016-03-01

    We present highlights from plasma simulations performed in collaboration with Lawrence Livermore National Labs. This modeling is performed to advance the rate of learning about optimal EUV generation for laser produced plasmas and to provide insights where experimental results are not currently available. The goal is to identify key physical processes necessary for an accurate and predictive model capable of simulating a wide range of conditions. This modeling will help to drive source performance scaling in support of the EUV Lithography roadmap. The model simulates pre-pulse laser interaction with the tin droplet and follows the droplet expansion into the main pulse target zone. Next, the interaction of the expanded droplet with the main laser pulse is simulated. We demonstrate the predictive nature of the code and provide comparison with experimental results.

  20. 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.

  1. Predictions of active region flaring probability using subsurface helicity measurements

    NASA Astrophysics Data System (ADS)

    Reinard, A. A.; Komm, R.; Hill, F.

    2010-12-01

    Solar flares are responsible for a number of hazardous effects on the earth such as disabling high-frequency radio communications, interfering with GPS measurements, and disrupting satellites. However, forecasting flare occurrence is currently very difficult. One possible means for predicting flare occurrence lies in helioseismology, i.e. analysis of the region below the active region for signs of an impending flare. Time series helioseismic data collected by the Global Oscillation Network Group (GONG) has been analyzed for a subset of active regions that produce large flares and a subset with very high magnetic field strength that produce no flares. A predictive parameter has been developed and analyzed using discriminant analysis as well as traditional forecasting tools such as the Heidke skill score. Preliminary results show that this parameter predicts the flaring probability of an active region 2-3 days in advance with a relatively high degree of success.

  2. Prediction of seasonal summer monsoon rainfall over homogenous regions of India using dynamical prediction system

    NASA Astrophysics Data System (ADS)

    Ramu, Dandi A.; Rao, Suryachadra A.; Pillai, Prasanth A.; Pradhan, M.; George, G.; Rao, D. Nagarguna; Mahapatra, S.; Pai, D. S.; Rajeevan, M.

    2017-03-01

    Seasonal prediction of Indian summer monsoon rainfall is a challenging task for the modeling community and predicting seasonal mean rainfall at smaller regional scale is much more difficult than predicting all India averaged seasonal mean rainfall. The regional scale prediction of summer monsoon mean rainfall at longer lead time (e.g., predicting 3-4 months in advance) can play a vital role in planning of hydrological and agriculture aspects of the society. Previous attempts for predicting seasonal mean rainfall at regional level (over 5 Homogeneous regions) have resulted with limited success (anomaly correlation coefficient is low, ACC ≈ 0.1-0.4, even at a short lead time of one month). The high resolution Climate Forecast System, version 2 (CFSv2) model, with spectral resolution of T382 (∼38 km), can predict the Indian summer monsoon rainfall (ISMR) at lead time of 3-4 months, with a reasonably good prediction skill (ACC ≈ 0.55). In the present study, we have investigated whether the seasonal mean rainfall over different homogenous regions is predictable using the same model, at 3-4 months lead time? Out of five homogeneous regions of India three regions have shown moderate prediction skill, even at 3 months lead time. Compared to lower resolution model, high resolution model has good skill for all the regions except south peninsular India. High resolution model is able to capture the extreme events and also the teleconnections associated with large scale features at four months lead time and hence shows better skill (ACC ≈ 0.45) in predicting the seasonal mean rainfall over homogeneous regions.

  3. 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.

  4. 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.

  5. 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.

  6. Weather Prediction Improvement Using Advanced Satellite Technology

    NASA Technical Reports Server (NTRS)

    Einaudi, Franco; Uccellini, L.; Purdom, J.; Rogers, D.; Gelaro, R.; Dodge, J.; Atlas, R.; Lord, S.

    2001-01-01

    We discuss in this paper some of the problems that exist today in the fall utilization of satellite data to improve weather forecasts and we propose specific recommendations to solve them. This discussion can be viewed as an aspect of the general debate on how best to organize the transition from research to operational satellites and how to evaluate the impact of a research instrument on numerical weather predictions. A method for providing this transition is offered by the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP). This mission will bridge the time between the present NOAA and Department of Defense (DOD) polar orbiting missions and the initiation of the converged NPOESS series and will evaluate some of the Earth Observing System (EOS) instruments as appropriate for operational missions. Thus, this mission can be viewed as an effort to meet the operational requirements of NOAA and DOD and the research requirements of NASA. More generally, however, it can be said that the process of going from the conception of new, more advanced instruments to their operational implementation and full utilization by the weather forecast communities is not optimal. Instruments developed for research purposes may have insufficient funding to explore their potential operational capabilities. Furthermore, instrument development programs designed for operational satellites typically have insufficient funding for assimilation algorithms needed to transform the satellite observations into data that can be used by sophisticated global weather forecast models. As a result, years often go by before satellite data are efficiently used for operational forecasts. NASA and NOAA each have unique expertise in the design of satellite instruments, their use for basic and applied research and their utilization in weather and climate research. At a time of limited resources, the two agencies must combine their efforts to work toward common

  7. Recent Advances in Predictive (Machine) Learning

    SciTech Connect

    Friedman, J

    2004-01-24

    Prediction involves estimating the unknown value of an attribute of a system under study given the values of other measured attributes. In prediction (machine) learning the prediction rule is derived from data consisting of previously solved cases. Most methods for predictive learning were originated many years ago at the dawn of the computer age. Recently two new techniques have emerged that have revitalized the field. These are support vector machines and boosted decision trees. This paper provides an introduction to these two new methods tracing their respective ancestral roots to standard kernel methods and ordinary decision trees.

  8. 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.

  9. Predicting success on the Advanced Placement Biology Examination

    NASA Astrophysics Data System (ADS)

    Shepherd, Lesa Hanlin

    Four hundred sixty students in four public high schools were used as subjects to determine which of eleven academic and demographic factors studied were significant predictors of success for the Advanced Placement Biology Examination. Factors studied were attendance, class rank, gender, grade level at the time of the examination, grade point average, level of prerequisite biology course, number of Advanced Placement Examinations taken in the year prior to the Advanced Placement Biology Examination, number of Advanced Placement Examinations taken in the same year as the Advanced Placement Biology Examination, proposed major in college, race, and SAT mathematics, verbal, and combined score. Significant relationships were found to exist between the Advanced Placement Biology Examination score and attendance, class rank, gender, grade level at the time of the Advanced Placement Biology Examination, grade point average, number of Advanced Placement Examinations taken in the year prior to the Advanced Placement Biology Examination, number of Advanced Placement Examinations taken in the same year as the Advanced Placement Biology Examination, race, and SAT scores. Significant relationships were not found to exist between Advanced Placement Biology Examination score and level prerequisite biology course and Advanced Placement Biology Examination score and proposed major in college. A multiple regression showed the best combination of predictors to be attendance, SAT verbal score, and SAT mathematics score. Discriminant analysis showed the variables in this study to be good predictors of whether the student would pass the Advanced Placement Biology Examination (score a 3, 4, or 5) or fail the Advanced Placement Biology Examination (score a 1 or 2). These results demonstrated that significant predictors for the Advanced Placement Biology Examination do exist and can be used to assist in the prediction of scores, prediction of passing or failing, the identification of

  10. Predicting RNA structure: advances and limitations.

    PubMed

    Hofacker, Ivo L; Lorenz, Ronny

    2014-01-01

    RNA secondary structures can be predicted using efficient algorithms. A widely used software package implementing a large number of computational methods is the ViennaRNA Package. This chapter describes how to use programs from the ViennaRNA Package to perform common tasks such as prediction of minimum free-energy structures, suboptimal structures, or base pairing probabilities, and generating secondary structure plots with reliability annotation. Moreover, we present recent methods to assess the folding kinetics of an RNA via 2D projections of the energy landscape, identification of local minima and energy barriers, or simulation of RNA folding as a Markov process.

  11. Probabilistic Predictions of Regional Climate Change

    NASA Astrophysics Data System (ADS)

    Harris, G. R.; Sexton, D. M.; Booth, B. B.; Brown, K.; Collins, M.; Murphy, J. M.

    2009-12-01

    We present a methodology for quantifying the leading sources of uncertainty in climate change projections that allows more robust prediction of probability distribution functions (PDFs) for transient regional climate change than is possible, for example, with the multimodel ensemble in the the CMIP3 archive used for the IPCC Fourth Assessment. Uncertainty in equilibrium climate response has been systematically explored by varying uncertain parameters in the atmosphere, sea-ice and surface components in a ensemble of simulations with the third version of the Hadley Centre model coupled to a slab ocean. The ensemble is used to emulate the response for one million parameter combinations, ensuring robust prediction of the prior distributions of equilibrium response for this model. Posterior PDFs are estimated using a weighting scheme that calculates the likelihood for each model version, based upon its ability to reproduce a large set of observed seasonal-mean climate variables. Information from the CMIP3 simulations is used to assess the effect of structural uncertainty, and this is included as an additional variance in the weighting. The posterior distributions of equilibrium response are shown to be relatively robust to variation in key assumptions of the method. A time-scaling technique that maps equilibrium to transient change is then used to predict PDFs for transient regional climate change for specified emissions scenarios. The scaling uses a simple climate model (SCM), with global climate feedbacks and local response sampled from the equilibrium response, and other SCM parameters tuned to the response of other AOGCM ensembles. Use of the SCM allows efficient sampling of uncertainties not fully sampled by expensive GCM simulation, including uncertainty in aerosol radiative forcing, the rate of ocean heat uptake, and the strength of carbon-cycle feedbacks. Uncertainties arising from statistical components of the method, such as emulation or scaling, are

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Predictive Biomarkers to Chemoradiation in Locally Advanced Rectal Cancer

    PubMed Central

    Conde-Muíño, Raquel; Cuadros, Marta; Zambudio, Natalia; Segura-Jiménez, Inmaculada; Cano, Carlos; Palma, Pablo

    2015-01-01

    There has been a high local recurrence rate in rectal cancer. Besides improvements in surgical techniques, both neoadjuvant short-course radiotherapy and long-course chemoradiation improve oncological results. Approximately 40–60% of rectal cancer patients treated with neoadjuvant chemoradiation achieve some degree of pathologic response. However, there is no effective method of predicting which patients will respond to neoadjuvant treatment. Recent studies have evaluated the potential of genetic biomarkers to predict outcome in locally advanced rectal adenocarcinoma treated with neoadjuvant chemoradiation. The articles produced by the PubMed search were reviewed for those specifically addressing a genetic profile's ability to predict response to neoadjuvant treatment in rectal cancer. Although tissue gene microarray profiling has led to promising data in cancer, to date, none of the identified signatures or molecular markers in locally advanced rectal cancer has been successfully validated as a diagnostic or prognostic tool applicable to routine clinical practice. PMID:26504848

  17. Predictive Biomarkers to Chemoradiation in Locally Advanced Rectal Cancer.

    PubMed

    Conde-Muíño, Raquel; Cuadros, Marta; Zambudio, Natalia; Segura-Jiménez, Inmaculada; Cano, Carlos; Palma, Pablo

    2015-01-01

    There has been a high local recurrence rate in rectal cancer. Besides improvements in surgical techniques, both neoadjuvant short-course radiotherapy and long-course chemoradiation improve oncological results. Approximately 40-60% of rectal cancer patients treated with neoadjuvant chemoradiation achieve some degree of pathologic response. However, there is no effective method of predicting which patients will respond to neoadjuvant treatment. Recent studies have evaluated the potential of genetic biomarkers to predict outcome in locally advanced rectal adenocarcinoma treated with neoadjuvant chemoradiation. The articles produced by the PubMed search were reviewed for those specifically addressing a genetic profile's ability to predict response to neoadjuvant treatment in rectal cancer. Although tissue gene microarray profiling has led to promising data in cancer, to date, none of the identified signatures or molecular markers in locally advanced rectal cancer has been successfully validated as a diagnostic or prognostic tool applicable to routine clinical practice.

  18. Predictable elastomeric impressions in advanced fixed prosthodontics: a comprehensive review.

    PubMed

    Lee, E A

    1999-05-01

    Despite advances in dental material technology, the predictable procurement of accurate impressions for the fabrication of complex fixed prosthodontic restorations remains an elusive objective. The technical challenges and potential negative sequelae are exponentially magnified in advanced applications that involve multiple abutments and preparatory phases. A protocol for consistently achieving accurate impressions with the use of polyether impression materials and automatic instrumentation is presented and illustrated with multiple clinical examples. The technique is capable of yielding reliable results in extensive cases and requires minimal support from auxiliary personnel.

  19. Predictable elastomeric impressions in advanced fixed prosthodontics: a comprehensive review.

    PubMed

    Lee, Ernesto A

    2007-10-01

    Despite advances in dental material technology, the predictable procurement of accurate impressions for the fabrication of complex fixed prosthodontic restorations remains an elusive objective. The technical challenges and potential negative sequelae are exponentially magnified in advanced applications that involve multiple abutments and preparatory phases. A protocol for consistently achieving accurate impressions with the use of various impression materials and automatic instrumentation is presented and illustrated with multiple clinical examples. The technique is capable of yielding reliable results in extensive cases and requires minimal support from auxiliary personnel.

  20. Life Prediction of Fretting Fatigue with Advanced Surface Treatments (Preprint)

    DTIC Science & Technology

    2006-05-01

    surfaces and not the fretting pads. The chosen coatings included DLC, Ni-B, Molybdenum, and Nitride. These 4 coatings, their application to the titanium ...Article Preprint 5a. CONTRACT NUMBER In-house 5b. GRANT NUMBER 4 . TITLE AND SUBTITLE LIFE PREDICTION OF FRETTING FATIGUE WITH ADVANCED SURFACE...TREATMENTS (PREPRINT) 5c. PROGRAM ELEMENT NUMBER N/A 5d. PROJECT NUMBER M02R 5e. TASK NUMBER 30 6 . AUTHOR(S) Patrick J. Golden and Michael

  1. 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.

  2. 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.

  3. Advancing climate dynamics toward reliable regional climate projections

    NASA Astrophysics Data System (ADS)

    Xie, Shang-Ping

    2013-06-01

    With a scientific consensus reached regarding the anthropogenic effect on global mean temperature, developing reliable regional climate projections has emerged as a new challenge for climate science. A national project was launched in China in 2012 to study ocean's role in regional climate change. This paper starts with a review of recent advances in the study of regional climate response to global warming, followed by a description of the Chinese project including the rationale, objectives, and plan for field observations. The 15 research articles that follow in the special issue are highlighted, representing some of the initial results from the project.

  4. 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.

  5. Estimating observing locations for advancing beyond the winter predictability barrier of Indian Ocean dipole event predictions

    NASA Astrophysics Data System (ADS)

    Feng, Rong; Duan, Wansuo; Mu, Mu

    2017-02-01

    In this paper, we explored potential observing locations (i.e., the sensitive areas) of positive Indian Ocean dipole (IOD) events to advance beyond the winter predictability barrier (WPB) using the geophysical fluid dynamics laboratory climate model version 2p1 (GFDL CM2p1). The sensitivity analysis is conducted through perfect model predictability experiments, in which the model is assumed to be perfect and so any prediction errors are caused by initial errors. The results show that the initial errors with an east-west dipole pattern are more likely to result in a significant WPB than spatially correlated noises; the areas where the large values of the dipole pattern initial errors are located have great effects on prediction uncertainties in winter and provide useful information regarding the sensitive areas. Further, the prediction uncertainties in winter are more sensitive to the initial errors in the subsurface large value areas than to those in the surface large value areas. The results indicate that the subsurface large value areas are sensitive areas for advancing beyond the WPB of IOD predictions and if we carry out intensive observations across these areas, the prediction errors in winter may be largely reduced. This will lead to large improvements in the skill of wintertime IOD event forecasts.

  6. Lifetime prediction modeling of airfoils for advanced power generation

    NASA Astrophysics Data System (ADS)

    Karaivanov, Ventzislav Gueorguiev

    The use of gases produced from coal as a turbine fuel offers an attractive means for efficiently generating electric power from our Nation's most abundant fossil fuel resource. The oxy-fuel and hydrogen-fired turbine concepts promise increased efficiency and low emissions on the expense of increased turbine inlet temperature (TIT) and different working fluid. Developing the turbine technology and materials is critical to the creation of these near-zero emission power generation technologies. A computational methodology, based on three-dimensional finite element analysis (FEA) and damage mechanics is presented for predicting the evolution of creep and fatigue in airfoils. We took a first look at airfoil thermal distributions in these advanced turbine systems based on CFD analysis. The damage mechanics-based creep and fatigue models were implemented as user modified routine in commercial package ANSYS. This routine was used to visualize the creep and fatigue damage evolution over airfoils for hydrogen-fired and oxy-fuel turbines concepts, and regions most susceptible to failure were indentified. Model allows for interaction between creep and fatigue damage thus damage due to fatigue and creep processes acting separately in one cycle will affect both the fatigue and creep damage rates in the next cycle. Simulation results were presented for various thermal conductivity of the top coat. Surface maps were created on the airfoil showing the development of the TGO scale and the Al depletion of the bond coat. In conjunction with model development, laboratory-scale experimental validation was executed to evaluate the influence of operational compressive stress levels on the performance of the TBC system. TBC coated single crystal coupons were exposed isothermally in air at 900, 1000, 1100oC with and without compressive load. Exposed samples were cross-sectioned and evaluated with scanning electron microscope (SEM). Performance data was collected based on image analysis

  7. 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.

  8. Advances in the assessment and prediction of interpersonal violence.

    PubMed

    Mills, Jeremy F

    2005-02-01

    This article underscores the weakness of clinical judgment as a mechanism for prediction with examples from other areas in the psychological literature. Clinical judgment has as its Achilles'heel the reliance on a person to incorporate multiple pieces of information while overcoming human judgment errors--a feat insurmountable thus far. The actuarial approach to risk assessment has overcome many of the weaknesses of clinical judgment and has been shown to be a much superior method. Nonetheless, the static/historical nature of the risk factors associated with most actuarial approaches is limiting. Advances in risk prediction will be found in part in the development of dynamic actuarial instruments that will measure both static/historical and changeable risk factors. The dynamic risk factors can be reevaluated on an ongoing basis, and it is proposed that the level of change in dynamic factors necessary to represent a significant change in overall risk will be an interactive function with static risk factors.

  9. The prediction of transonic loading on advancing helicopter rotors

    NASA Technical Reports Server (NTRS)

    Strawn, R. C.; Tung, C.

    1986-01-01

    Two different schemes are presented for including the effect of rotor wakes on the finie-difference prediction of rotor loads. The first formulation includes wake effects by means of a blade-surface inflow specification. This approach is sufficiently simple to permit coupling of a full-potential finite-difference rotor code to a comprehensive integral model for the rotor wake and blade motion. The coupling involves a transfer of appropriate loads and inflow data between the two computer codes. Results are compared with experimental data for two advancing rotor cases. The second rotor-wake modeling scheme is a split potential formulation for computing unsteady blade-vortex interactions. Discrete vortex fields are introduced into a three-dimensional, conservative, full-potential rotor code. Computer predictions are compared with two experimental blade-vortex interaction cases.

  10. The prediction of transonic loading advancing helicopter rotors

    NASA Technical Reports Server (NTRS)

    Strawn, R.; Tung, C.

    1986-01-01

    Two different schemes are presented for including the effect of rotor wakes on the finite-difference prediction of rotor loads. The first formulation includes wake effects by means of a blade-surface inflow specification. This approach is sufficiently simple to permit coupling of a full-potential finite-difference rotor code to a comprehensive integral model for the rotor wake and blade motion. The coupling involves a transfer of appropriate loads and inflow data between the two computer codes. Results are compared with experimental data for two advancing rotor cases. The second rotor wake modeling scheme in this paper is a split potential formulation for computing unsteady blade-vortex interactions. Discrete vortex fields are introduced into a three-dimensional, conservative, full-potential rotor code. Computer predictions are compared with two experimental blade-vortex interaction cases.

  11. 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.

  12. 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.

  13. 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.

  14. Assessment of protein disorder region predictions in CASP10

    PubMed Central

    Monastyrskyy, Bohdan; Kryshtafovych, Andriy; Moult, John; Tramontano, Anna; Fidelis, Krzysztof

    2015-01-01

    The article presents the assessment of disorder region predictions submitted to CASP10. The evaluation is based on the three measures tested in previous CASPs: (i) balanced accuracy, (ii) the Matthews correlation coefficient for the binary predictions, and (iii) the area under the curve in the receiver operating characteristic (ROC) analysis of predictions using probability annotation. We also performed new analyses such as comparison of the submitted predictions with those obtained with a Naïve disorder prediction method and with predictions from the disorder prediction databases D2P2 and MobiDB. On average, the methods participating in CASP10 demonstrated slightly better performance than those in CASP9. PMID:23946100

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. Initialized near-term regional climate change prediction

    PubMed Central

    Doblas-Reyes, F. J.; Andreu-Burillo, I.; Chikamoto, Y.; García-Serrano, J.; Guemas, V.; Kimoto, M.; Mochizuki, T.; Rodrigues, L. R. L.; van Oldenborgh, G. J.

    2013-01-01

    Climate models are seen by many to be unverifiable. However, near-term climate predictions up to 10 years into the future carried out recently with these models can be rigorously verified against observations. Near-term climate prediction is a new information tool for the climate adaptation and service communities, which often make decisions on near-term time scales, and for which the most basic information is unfortunately very scarce. The Fifth Coupled Model Intercomparison Project set of co-ordinated climate-model experiments includes a set of near-term predictions in which several modelling groups participated and whose forecast quality we illustrate here. We show that climate forecast systems have skill in predicting the Earth's temperature at regional scales over the past 50 years and illustrate the trustworthiness of their predictions. Most of the skill can be attributed to changes in atmospheric composition, but also partly to the initialization of the predictions. PMID:23591882

  20. Initialized near-term regional climate change prediction.

    PubMed

    Doblas-Reyes, F J; Andreu-Burillo, I; Chikamoto, Y; García-Serrano, J; Guemas, V; Kimoto, M; Mochizuki, T; Rodrigues, L R L; van Oldenborgh, G J

    2013-01-01

    Climate models are seen by many to be unverifiable. However, near-term climate predictions up to 10 years into the future carried out recently with these models can be rigorously verified against observations. Near-term climate prediction is a new information tool for the climate adaptation and service communities, which often make decisions on near-term time scales, and for which the most basic information is unfortunately very scarce. The Fifth Coupled Model Intercomparison Project set of co-ordinated climate-model experiments includes a set of near-term predictions in which several modelling groups participated and whose forecast quality we illustrate here. We show that climate forecast systems have skill in predicting the Earth's temperature at regional scales over the past 50 years and illustrate the trustworthiness of their predictions. Most of the skill can be attributed to changes in atmospheric composition, but also partly to the initialization of the predictions.

  1. Reducing uncertainty in predictions in ungauged basins by combining hydrologic indices regionalization and multiobjective optimization

    NASA Astrophysics Data System (ADS)

    Zhang, Zhenxing; Wagener, Thorsten; Reed, Patrick; Bhushan, Rashi

    2008-12-01

    Approaches to predictions in ungauged basins have so far mainly focused on a priori parameter estimates from physical watershed characteristics or on the regionalization of model parameters. Recent studies suggest that the regionalization of hydrologic indices (e.g., streamflow characteristics) provides an additional way to extrapolate information about the expected watershed response to ungauged locations for use in continuous watershed modeling. This study contributes a novel multiobjective framework for identifying behavioral parameter ensembles for ungauged basins using suites of regionalized hydrologic indices. The new formulation enables the use of multiobjective optimization algorithms for the identification of model ensembles for predictions in ungauged basins for the first time. Application of the new formulation to 30 watersheds located in England and Wales and comparison of the results with a Monte Carlo approach demonstrate that the new formulation will significantly advance our ability to reduce the uncertainty of predictions in ungauged basins.

  2. Advance Prediction of the March 11, 2011 Great East Japan Earthquake: A Missed Opportunity for Disaster Preparedness

    NASA Astrophysics Data System (ADS)

    Davis, C. A.; Keilis-Borok, V. I.; Kossobokov, V. G.; Soloviev, A.

    2012-12-01

    There was a missed opportunity for implementing important disaster preparedness measures following an earthquake prediction that was announced as an alarm in mid-2001. This intermediate-term middle-range prediction was the initiation of a chain of alarms that successfully detected the time, region, and magnitude range for the magnitude 9.0 March 11, 2011 Great East Japan Earthquake. The prediction chains were made using an algorithm called M8 and is the latest of many predictions tested worldwide for more than 25 years, the results of which show at least a 70% success rate. The earthquake detection could have been utilized to implement measures and improve earthquake preparedness in advance; unfortunately this was not done, in part due to the predictions' limited distribution and the lack of applying existing methods for using intermediate-term predictions to make decisions for taking action. The resulting earthquake and induced tsunami caused tremendous devastation to north-east Japan. Methods that were known in advance of the predication and further advanced during the prediction timeframe are presented in a scenario describing some possibilities on how the 2001 prediction may have been utilized to reduce significant damage, including damage to the Fukushima nuclear power plant, and to show prudent cost-effective actions can be taken if the prediction certainty is known, but not necessarily high. The purpose of this presentation is to show how the prediction information can be strategically used to enhance disaster preparedness and reduce future impacts from the world's largest earthquakes.

  3. Numerical Weather Prediction Over Caucasus Region With Nested Grid Models

    NASA Astrophysics Data System (ADS)

    Davitashvili, Dr.; Kutaladze, Dr.; Kvatadze, Dr.

    2010-09-01

    Global atmosphere models, which describe the weather processes, give the general character of the weather but can't catch the smaller scale processes, especially local weather for the territories with compound topography. Small-scale processes such as convection often dominate the local weather, which cannot be explicitly represented in models with grid size more then 10 km. A much finer grid is required to properly simulate frontal structures and represent cumulus convection. Georgia lies to the south of the Major Caucasian Ridge and the Lesser Caucasus mountains occupy the southern part of Georgia. About 85 percent of the total land area occupies complex mountain ranges.Therefore for the territory of Georgia it is necessary to use atmosphere models with a very high resolution nested grid system taking into account main orographic features of the area. We have elaborated and configured Whether Research Forecast - Advanced Researcher Weather (WRF-ARW) model for Caucasus region considering geographical-landscape character, topography height, land use, soil type and temperature in deep layers, vegetation monthly distribution, albedo and others. Porting of WRF-ARW application to the grid was a good opportunity for running model on larger number of CPUs and storing large amount of data on the grid storage elements. On the grid WRF was compiled for both Open MP and MPI (Shared + Distributed memory) environment and WPS was compiled for serial environment using PGI (v7.1.6, MPI- version 1.2.7) on the platform Linux-x86. In searching of optimal execution time for time saving different model directory structures and storage schema was used. Simulations were performed using a set of 2 domains with horizontal grid-point resolutions of 15 and 5 km, both defined as those currently being used for operational forecasts The coarser domain is a grid of 94x102 points which covers the South Caucasus region, while the nested inner domain has a grid size of 70x70 points mainly

  4. HotRegion: a database of predicted hot spot clusters

    PubMed Central

    Cukuroglu, Engin; Keskin, Ozlem

    2012-01-01

    Hot spots are energetically important residues at protein interfaces and they are not randomly distributed across the interface but rather clustered. These clustered hot spots form hot regions. Hot regions are important for the stability of protein complexes, as well as providing specificity to binding sites. We propose a database called HotRegion, which provides the hot region information of the interfaces by using predicted hot spot residues, and structural properties of these interface residues such as pair potentials of interface residues, accessible surface area (ASA) and relative ASA values of interface residues of both monomer and complex forms of proteins. Also, the 3D visualization of the interface and interactions among hot spot residues are provided. HotRegion is accessible at http://prism.ccbb.ku.edu.tr/hotregion. PMID:22080558

  5. Anaesthetic agents for advanced regional anaesthesia: a North American perspective.

    PubMed

    Buckenmaier, Chester C; Bleckner, Lisa L

    2005-01-01

    Interest in the use of regional anaesthesia, particularly peripheral nerve blocks (PNBs) and continuous PNBs, has increased in recent years. Accompanying this resurgence in interest has been the development of new local anaesthetics and additives designed to enhance block duration and quality. This manuscript provides a literature-based review on accepted uses of local anaesthetics and adjuncts for a variety of regional anaesthesia techniques. A brief review of local anaesthetic pharmacodynamics describes the action of these drugs in preventing nerve depolarisation, thus blocking nerve impulses. Toxic adverse effects of local anaesthetics, specifically CNS and cardiac manifestations of excessive local anaesthetic blood concentrations and the direct neurotoxic properties of local anaesthetics, are discussed generally and specifically for many commonly used local anaesthetics. Clinically useful ester and amide local anaesthetics are evaluated individually in terms of their physical properties and toxic potential. How these properties impact on the clinical uses of each local anaesthetic is explored. Particular emphasis is placed on the long-acting local anaesthetic toxic potential of racemic bupivacaine compared with levobupivacaine and ropivacaine, which are both levorotatory stereoisomers. Guidelines for using ropivacaine and mepivacaine, based on the authors' experience using advanced regional anaesthesia in a busy practice, is provided. Finally, epinephrine (adrenaline), clonidine and other local anaesthetic additives and their rationale for use is covered along with other future possibilities.

  6. Advances in Data Assimilation and Weather Prediction Using TRMM Observations

    NASA Technical Reports Server (NTRS)

    Atlas, Robert (Technical Monitor); Hou, Arthur Y.; Zhang, Sara; daSilvia, Arlindo; Li, Jui-Lin; Zhang, Minghua

    2002-01-01

    Understanding the Earth's climate and how it responds to climate perturbations requires knowledge of how atmospheric moisture, clouds, latent heating, the large-scale circulation and energy fluxes vary with changing climatic conditions. The physical process linking these climate elements is precipitation. Accurate knowledge of how precipitation varies in space and time and how it couples with other atmospheric variables is essential for understanding the global water and energy cycle. In recent years, TRMM data products have played a key role in advancing the field of data assimilation to provide better global analyses for climate research and numerical weather prediction. TRMM research has demonstrated the effectiveness of microwave-based rainfall and total precipitable water (TPW) observations in improving the quality of assimilated datasets and upgrading forecast skills. TRMM latent heating products have also stimulated experimentation with innovative techniques to use this type of information to improve global analyses. We discuss strategies of assimilating TRMM observations at NASA s Data Assimilation Office and present results on the impact assimilating TRMM data on the Goddard Earth Observing System (GEOS) analyses and forecast capabilities.

  7. 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.

  8. 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.

  9. 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.

  10. Crystallization of RNA polymerase I subcomplex A14/A43 by iterative prediction, probing and removal of flexible regions

    PubMed Central

    Geiger, Sebastian R.; Kuhn, Claus.-D.; Leidig, Christoph; Renkawitz, Jörg; Cramer, Patrick

    2008-01-01

    The removal of flexible protein regions is generally used to promote crystallization, but advanced strategies to quickly remove multiple flexible regions from proteins or protein complexes are lacking. Here, it is shown how a protein heterodimer with multiple flexibilities, the RNA polymerase I subcomplex A14/A43, could be crystallized with the use of an iterative procedure of predicting flexible regions, experimentally testing and improving these predictions and combining deletions of flexible regions in a stepwise manner. This strategy should enable the crystallization of other proteins and subcomplexes with multiple flexibilities, as required for hybrid structure solution of large macromolecular assemblies. PMID:18453714

  11. 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+.

  12. Prediction of regional functional impairment following experimental stroke via connectome analysis.

    PubMed

    Schmitt, O; Badurek, S; Liu, W; Wang, Y; Rabiller, G; Kanoke, A; Eipert, P; Liu, J

    2017-04-13

    Recent advances in functional connectivity suggest that shared neuronal activation patterns define brain networks linking anatomically separate brain regions. We sought to investigate how cortical stroke disrupts multiple brain regions in processing spatial information. We conducted a connectome investigation at the mesoscale-level using the neuroVIISAS-framework, enabling the analysis of directed and weighted connectivity in bilateral hemispheres of cortical and subcortical brain regions. We found that spatial-exploration induced brain activation mapped by Fos, a proxy of neuronal activity, was differentially affected by stroke in a region-specific manner. The extent of hypoactivation following spatial exploration is inversely correlated with the spatial distance between the region of interest and region damaged by stroke, in particular within the parietal association and the primary somatosensory cortex, suggesting that the closer a region is to a stroke lesion, the more it would be affected during functional activation. Connectome modelling with 43 network parameters failed to reliably predict regions of hypoactivation in stroke rats exploring a novel environment, despite a modest correlation found for the centrality and hubness parameters in the home-caged animals. Further investigation in the inhibitory versus excitatory neuronal networks and microcircuit connectivity is warranted to improve the accuracy of predictability in post-stroke functional impairment.

  13. 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.

  14. 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

  15. 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

    ... 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 Effects....niehs.nih.gov/conferences/dert/mixtures/ . The deadline to register for this workshop is...

  16. Regional predictability and the linearity of climate feedbacks

    NASA Astrophysics Data System (ADS)

    Feldl, N.; Roe, G.

    2011-12-01

    At the global scale, feedback analysis is a powerful tool for constraining climate sensitivity through understanding uncertainty in the component model physics. Our focus here is to evaluate the extent to which this framework can be applied to the question of regional climate predictability. We have developed a clean and clear approach to address these challenges. We employ the GFDL AM2 model in aquaplanet mode, coupled to simple ocean mixed-layer and sea-ice schemes, and run under perpetual equinox conditions. This simplified, aquaplanet simulation enables us to investigate the atmospheric response to carbon dioxide without the effects of a seasonal cycle or land-sea distribution, which can obscure the response. Further, we explicitly calculate radiative kernels (necessary to diagnose the feedbacks) for this precise model set-up, thus removing much of the ambiguity in the feedback approximation. We find that linking regional predictability and individual climate feedbacks depends on the balance between local radiative feedbacks and meridional energy transport in response to changes in climate forcing. An important aspect of this energy budget is the linearity of the kernel-calculated feedbacks, which we evaluate. Spatial patterns of these factors can be related to the basic structure of atmospheric circulation, and our results highlight regional differences in the effect of feedbacks on the regional climate response.

  17. Satellite radiance data assimilation for rainfall prediction in Java Region

    NASA Astrophysics Data System (ADS)

    Sagita, Novvria; Hidayati, Rini; Hidayat, Rahmat; Gustari, Indra

    2017-01-01

    This study examined the influence of satellite radiance data assimilation for predicting two days of heavy rainfall in the Java region. The first case occurred from 22 to 23 on January 2015 while the second case occurred from 1 to 2 on February 2015. The analysis examined before and after data assimilation in the two cases study. The Global Forecast System (GFS) data were used as initial condition which was assimilated with several data such as surface observation data, radiance data from AMSUA sensor, radiance data from HIRS sensor, and radiance data from MHS sensor. Weather Research and Forecasting Data Assimilation (WRFDA) is a tool which is used in this study for assimilating process with Three Dimensional Variation (3D-Var) method. The Quantitative Precipitation Forecast (QPF) skill was used to evaluate influence data assimilation for rainfall prediction. The result of the study obtained different rainfall prediction with different data assimilation. In general, the surface observation data assimilation has lower QPF skill than the satellite radiance data assimilation. Even thought radiance data assimilation has slightly contribution on rainfall prediction, but it gave better accuracy on rainfall prediction for two heavy rainfall cases.

  18. 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

  19. Predicting regional neurodegeneration from the healthy brain functional connectome.

    PubMed

    Zhou, Juan; Gennatas, Efstathios D; Kramer, Joel H; Miller, Bruce L; Seeley, William W

    2012-03-22

    Neurodegenerative diseases target large-scale neural networks. Four competing mechanistic hypotheses have been proposed to explain network-based disease patterning: nodal stress, transneuronal spread, trophic failure, and shared vulnerability. Here, we used task-free fMRI to derive the healthy intrinsic connectivity patterns seeded by brain regions vulnerable to any of five distinct neurodegenerative diseases. These data enabled us to investigate how intrinsic connectivity in health predicts region-by-region vulnerability to disease. For each illness, specific regions emerged as critical network "epicenters" whose normal connectivity profiles most resembled the disease-associated atrophy pattern. Graph theoretical analyses in healthy subjects revealed that regions with higher total connectional flow and, more consistently, shorter functional paths to the epicenters, showed greater disease-related vulnerability. These findings best fit a transneuronal spread model of network-based vulnerability. Molecular pathological approaches may help clarify what makes each epicenter vulnerable to its targeting disease and how toxic protein species travel between networked brain structures.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. Advanced System-Level Reliability Analysis and Prediction with Field Data Integration

    DTIC Science & Technology

    2011-09-01

    innovative life prediction methodologies that incorporate emerging probabilistic lifing techniques as well as advanced physics-of- failure...often based on simplifying assumptions and their predictions may suffer from different sources of uncertainty. For instance, one source of...system level, most modeling approaches focus on life prediction for single components and fail to account for the interdependencies that may result

  5. 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

  6. Predicting Performance in Technical Preclinical Dental Courses Using Advanced Simulation.

    PubMed

    Gottlieb, Riki; Baechle, Mary A; Janus, Charles; Lanning, Sharon K

    2017-01-01

    The aim of this study was to investigate whether advanced simulation parameters, such as simulation exam scores, number of student self-evaluations, time to complete the simulation, and time to complete self-evaluations, served as predictors of dental students' preclinical performance. Students from three consecutive classes (n=282) at one U.S. dental school completed advanced simulation training and exams within the first four months of their dental curriculum. The students then completed conventional preclinical instruction and exams in operative dentistry (OD) and fixed prosthodontics (FP) courses, taken during the first and second years of dental school, respectively. Two advanced simulation exam scores (ASES1 and ASES2) were tested as predictors of performance in the two preclinical courses based on final course grades. ASES1 and ASES2 were found to be predictors of OD and FP preclinical course grades. Other advanced simulation parameters were not significantly related to grades in the preclinical courses. These results highlight the value of an early psychomotor skills assessment in dentistry. Advanced simulation scores may allow early intervention in students' learning process and assist in efficient allocation of resources such as faculty coverage and tutor assignment.

  7. 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.

  8. 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.

  9. Advances and Computational Tools towards Predictable Design in Biological Engineering

    PubMed Central

    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. PMID:25161694

  10. 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.

  11. 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…

  12. 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…

  13. 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…

  14. firestar--advances in the prediction of functionally important residues.

    PubMed

    Lopez, Gonzalo; Maietta, Paolo; Rodriguez, Jose Manuel; Valencia, Alfonso; Tress, Michael L

    2011-07-01

    firestar is a server for predicting catalytic and ligand-binding residues in protein sequences. Here, we present the important developments since the first release of firestar. Previous versions of the server required human interpretation of the results; the server is now fully automatized. firestar has been implemented as a web service and can now be run in high-throughput mode. Prediction coverage has been greatly improved with the extension of the FireDB database and the addition of alignments generated by HHsearch. Ligands in FireDB are now classified for biological relevance. Many of the changes have been motivated by the critical assessment of techniques for protein structure prediction (CASP) ligand-binding prediction experiment, which provided us with a framework to test the performance of firestar. URL: http://firedb.bioinfo.cnio.es/Php/FireStar.php.

  15. 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.

  16. 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.

  17. Advances in fatigue life prediction methodology for metallic materials

    NASA Technical Reports Server (NTRS)

    Newman, J. C., Jr.

    1992-01-01

    The capabilities of a plasticity-induced crack-closure model to predict small- and large-crack growth rates, and in some cases total fatigue life, for four aluminum alloys and three titanium alloys under constant-amplitude, variable-amplitude, and spectrum loading are described. Equations to calculate a cyclic-plastic-zone corrected effective stress-intensity factor range from a cyclic J-integral and crack-closure analysis of large cracks were reviewed. The effective stress-intensity factor range against crack growth rate relations were used in the closure model to predict small- and large-crack growth under variable-amplitude and spectrum loading. Using the closure model and microstructural features, a total fatigue life prediction method is demonstrated for three aluminum alloys under various load histories.

  18. 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.

  19. RNA Structure: Advances and Assessment of 3D Structure Prediction.

    PubMed

    Miao, Zhichao; Westhof, Eric

    2017-03-30

    Biological functions of RNA molecules are dependent upon sustained specific three-dimensional (3D) structures of RNA, with or without the help of proteins. Understanding of RNA structure is frequently based on 2D structures, which describe only the Watson-Crick (WC) base pairs. Here, we hierarchically review the structural elements of RNA and how they contribute to RNA 3D structure. We focus our analysis on the non-WC base pairs and on RNA modules. Several computer programs have now been designed to predict RNA modules. We describe the RNA-Puzzles initiative, which is a community-wide, blind assessment of RNA 3D structure prediction programs to determine the capabilities and bottlenecks of current predictions. The assessment metrics used in RNA-Puzzles are briefly described. The detection of RNA 3D modules from sequence data and their automatic implementation belong to the current challenges in RNA 3D structure prediction. Expected final online publication date for the Annual Review of Biophysics Volume 46 is May 20, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

  20. Validation of High Frequency (HF) Propagation Prediction Models in the Arctic region

    NASA Astrophysics Data System (ADS)

    Athieno, R.; Jayachandran, P. T.

    2014-12-01

    Despite the emergence of modern techniques for long distance communication, Ionospheric communication in the high frequency (HF) band (3-30 MHz) remains significant to both civilian and military users. However, the efficient use of the ever-varying ionosphere as a propagation medium is dependent on the reliability of ionospheric and HF propagation prediction models. Most available models are empirical implying that data collection has to be sufficiently large to provide good intended results. The models we present were developed with little data from the high latitudes which necessitates their validation. This paper presents the validation of three long term High Frequency (HF) propagation prediction models over a path within the Arctic region. Measurements of the Maximum Usable Frequency for a 3000 km range (MUF (3000) F2) for Resolute, Canada (74.75° N, 265.00° E), are obtained from hand-scaled ionograms generated by the Canadian Advanced Digital Ionosonde (CADI). The observations have been compared with predictions obtained from the Ionospheric Communication Enhanced Profile Analysis Program (ICEPAC), Voice of America Coverage Analysis Program (VOACAP) and International Telecommunication Union Recommendation 533 (ITU-REC533) for 2009, 2011, 2012 and 2013. A statistical analysis shows that the monthly predictions seem to reproduce the general features of the observations throughout the year though it is more evident in the winter and equinox months. Both predictions and observations show a diurnal and seasonal variation. The analysed models did not show large differences in their performances. However, there are noticeable differences across seasons for the entire period analysed: REC533 gives a better performance in winter months while VOACAP has a better performance for both equinox and summer months. VOACAP gives a better performance in the daily predictions compared to ICEPAC though, in general, the monthly predictions seem to agree more with the

  1. Broadband noise - Its prediction and likely importance for advanced propfans

    NASA Astrophysics Data System (ADS)

    Knowles, K.

    1986-07-01

    A comparison of published experimental results and analytical results on broadband noise evaluations for rotating many-bladed propellers has been conducted to assess the importance of broadband noise in the perceived noise (PN) level of propfans. It is concluded that, in cruise conditions, the tone noise dominates the broadband noise of typical propfans by 8 dB. As the speed is reduced, and the values of forward Mach number and helical tip Mach number are reduced, the tones fall more rapidly than the broadband component until, at approach conditions, the broadband noise is dominant by 8 to 16 PNdB. A survey of the state-of-the-art of broadband noise prediction suggests that the broadband noise can be predicted to within 5 dB.

  2. Early Prediction of Lupus Nephritis Using Advanced Proteomics

    DTIC Science & Technology

    2009-06-01

    nephritis from non inflammatory nephropathies with similar urinary findings. 1.2: Validation of NGAL as a biomarker for predicting SLE disease...R01-DK-069749, R01-DK-53289, P50-DK-52612, and R21-DK-070163 from the National Institute of Diabetes and Digestive and Kidney Diseases) and by the...significant, and P values less than 0.1 were reported to show trends. RESULTS Baseline patient characteristics and treatments . Table 1 summarizes the

  3. 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.

  4. Early Prediction of Lupus Nephritis Using Advanced Proteomics

    DTIC Science & Technology

    2012-06-01

    non inflammatory nephropathies with similar urinary findings. 1.2: Validation of NGAL as a biomarker for predicting SLE disease activity and course...Devarajan’s work was supported by the NIH (grants R01-DK-069749, R01-DK-53289, P50-DK-52612, and R21-DK-070163 from the National Institute of Diabetes and... treatments . Table 1 summarizes the characteristics of the 111 pa- tients included in the study. Their mean SD age was 15.9 3.4 years, and the

  5. 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.

  6. Predicting the relativistic periastron advance of a binary without curving spacetime

    NASA Astrophysics Data System (ADS)

    Friedman, Y.; Livshitz, S.; Steiner, J. M.

    2017-01-01

    Relativistic Newtonian dynamics, the simple model used previously for predicting accurately the anomalous precession of Mercury, is now applied to predict the periastron advance of a binary. The classical treatment of a binary as a two-body problem is modified to account for the influence of the gravitational potential on spacetime. Without curving spacetime, the model predicts the identical equation for the relativistic periastron advance as the post-Newtonian approximation of the general relativity formalism thereby providing further substantiation of this model.

  7. 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.

  8. Dynamic Regional Viscosity Prediction Model of Blast Furnace Slag Based on the Partial Least-Squares Regression

    NASA Astrophysics Data System (ADS)

    Guo, Hongwei; Zhu, Mengyi; Yan, Bingji; Deng, Shichan; Li, Xinyu; Liu, Feng

    2017-02-01

    Viscosity is considered to be a significant indicator of the metallurgical property of blast furnace (BF) slag. A model for viscosity prediction based on the partial least-squares regression of varietal quantity reference points is presented in this article. The present model proposes a dynamic regional algorithm for reference point selection. The study applied the partial least-squares regression to establish the dynamic regional viscosity prediction model on the basis of limited discrete points data. Then an actual prediction was carried out with a large amount of viscosity data of real and synthesized BF slags that was obtained from a certain steel plant in China. The results show that this advanced method turns out to be satisfactory in the viscosity prediction of BF slags with a low averaging error and mean value deviation.

  9. Dynamic Regional Viscosity Prediction Model of Blast Furnace Slag Based on the Partial Least-Squares Regression

    NASA Astrophysics Data System (ADS)

    Guo, Hongwei; Zhu, Mengyi; Yan, Bingji; Deng, Shichan; Li, Xinyu; Liu, Feng

    2016-11-01

    Viscosity is considered to be a significant indicator of the metallurgical property of blast furnace (BF) slag. A model for viscosity prediction based on the partial least-squares regression of varietal quantity reference points is presented in this article. The present model proposes a dynamic regional algorithm for reference point selection. The study applied the partial least-squares regression to establish the dynamic regional viscosity prediction model on the basis of limited discrete points data. Then an actual prediction was carried out with a large amount of viscosity data of real and synthesized BF slags that was obtained from a certain steel plant in China. The results show that this advanced method turns out to be satisfactory in the viscosity prediction of BF slags with a low averaging error and mean value deviation.

  10. Regional hippocampal volumes and development predict learning and memory.

    PubMed

    Tamnes, Christian K; Walhovd, Kristine B; Engvig, Andreas; Grydeland, Håkon; Krogsrud, Stine K; Østby, Ylva; Holland, Dominic; Dale, Anders M; Fjell, Anders M

    2014-01-01

    The hippocampus is an anatomically and functionally heterogeneous structure, but longitudinal studies of its regional development are scarce and it is not known whether protracted maturation of the hippocampus in adolescence is related to memory development. First, we investigated hippocampal subfield development using 170 longitudinally acquired brain magnetic resonance imaging scans from 85 participants aged 8-21 years. Hippocampal subfield volumes were estimated by the use of automated segmentation of 7 subfields, including the cornu ammonis (CA) sectors and the dentate gyrus (DG), while longitudinal subfield volumetric change was quantified using a nonlinear registration procedure. Second, associations between subfield volumes and change and verbal learning/memory across multiple retention intervals (5 min, 30 min and 1 week) were tested. It was hypothesized that short and intermediate memory would be more closely related to CA2-3/CA4-DG and extended, remote memory to CA1. Change rates were significantly different across hippocampal subfields, but nearly all subfields showed significant volume decreases over time throughout adolescence. Several subfield volumes were larger in the right hemisphere and in males, while for change rates there were no hemisphere or sex differences. Partly in support of the hypotheses, greater volume of CA1 and CA2-3 was related to recall and retention after an extended delay, while longitudinal reduction of CA2-3 and CA4-DG was related to learning. This suggests continued regional development of the hippocampus across adolescence and that volume and volume change in specific subfields differentially predict verbal learning and memory over different retention intervals, but future high-resolution studies are called for.

  11. The accuracy of clinicians' predictions of survival in advanced cancer: a review.

    PubMed

    Cheon, Stephanie; Agarwal, Arnav; Popovic, Marko; Milakovic, Milica; Lam, Michael; Fu, Wayne; DiGiovanni, Julia; Lam, Henry; Lechner, Breanne; Pulenzas, Natalie; Chow, Ronald; Chow, Edward

    2016-01-01

    The process of formulating an accurate survival prediction is often difficult but important, as it influences the decisions of clinicians, patients, and their families. The current article aims to review the accuracy of clinicians' predictions of survival (CPS) in advanced cancer patients. A literature search of Cochrane CENTRAL, EMBASE, and MEDLINE was conducted to identify studies that reported clinicians' prediction of survival in advanced cancer patients. Studies were included if the subjects consisted of advanced cancer patients and the data reported on the ability of clinicians to predict survival, with both estimated and observed survival data present. Studies reporting on the ability of biological and molecular markers to predict survival were excluded. Fifteen studies that met the inclusion and exclusion criteria were identified. Clinicians in five studies underestimated patients' survival (estimated to observed survival ratio between 0.5 and 0.92). In contrast, 12 studies reported clinicians' overestimation of survival (ratio between 1.06 and 6). CPS in advanced cancer patients is often inaccurate and overestimated. Given these findings, clinicians should be aware of their tendency to be overoptimistic. Further investigation of predictive patient and clinician characteristics is warranted to improve clinicians' ability to predict survival.

  12. 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.

  13. 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.

  14. Climate fails to predict wood decomposition at regional scales

    NASA Astrophysics Data System (ADS)

    Bradford, Mark A.; Warren, Robert J., II; Baldrian, Petr; Crowther, Thomas W.; Maynard, Daniel S.; Oldfield, Emily E.; Wieder, William R.; Wood, Stephen A.; King, Joshua R.

    2014-07-01

    Decomposition of organic matter strongly influences ecosystem carbon storage. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on mean responses can be irrelevant and misleading. We test whether climate controls on the decomposition rate of dead wood--a carbon stock estimated to represent 73 +/- 6 Pg carbon globally--are sensitive to the spatial scale from which they are inferred. We show that the common assumption that climate is a predominant control on decomposition is supported only when local-scale variation is aggregated into mean values. Disaggregated data instead reveal that local-scale factors explain 73% of the variation in wood decomposition, and climate only 28%. Further, the temperature sensitivity of decomposition estimated from local versus mean analyses is 1.3-times greater. Fundamental issues with mean correlations were highlighted decades ago, yet mean climate-decomposition relationships are used to generate simulations that inform management and adaptation under environmental change. Our results suggest that to predict accurately how decomposition will respond to climate change, models must account for local-scale factors that control regional dynamics.

  15. 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

    2008-04-08

    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.

  16. 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

  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…

  18. Advancing alternatives analysis: The role of predictive toxicology in selecting safer chemical products and processes.

    PubMed

    Malloy, Timothy; Zaunbrecher, Virginia; Beryt, Elizabeth; Judson, Richard; Tice, Raymond; Allard, Patrick; Blake, Ann; Cote, Ila; Godwin, Hilary; Heine, Lauren; Kerzic, Patrick; Kostal, Jakub; Marchant, Gary; McPartland, Jennifer; Moran, Kelly; Nel, Andre; Oguseitan, Oladele; Rossi, Mark; Thayer, Kristina; Tickner, Joel; Whittaker, Margaret; Zarker, Ken

    2017-03-01

    Alternatives analysis (AA) is a method used in regulation and product design to identify, assess, and evaluate the safety and viability of potential substitutes for hazardous chemicals. It requires toxicological data for the existing chemical and potential alternatives. Predictive toxicology uses in silico and in vitro approaches, computational models, and other tools to expedite toxicological data generation in more cost-effective manner than traditional approaches. This article briefly reviews the challenges associated with using predictive toxicology in regulatory AA, then presents four recommendations for its advancement. It recommends using case studies to advance the integration of predictive toxicology into AA; adopting a stepwise process to employing predicative toxicology in AA beginning with prioritization of chemicals of concern; leveraging existing resources to advance the integration of predictive toxicology into the practice of AA, and supporting trans-disciplinary efforts. The further incorporation of predictive toxicology into AA would advance the ability of companies and regulators to select alternatives to harmful ingredients, and potentially increase the use of predictive toxicology in regulation more broadly. This article is protected by copyright. All rights reserved.

  19. 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

  20. Massive global ozone loss predicted following regional nuclear conflict

    PubMed Central

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

    2008-01-01

    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 N2O 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

  1. 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.

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

    PubMed

    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

    2016-08-16

    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.

  3. Are transit times key process-based tools for regional classification and prediction in ungauged basins?

    NASA Astrophysics Data System (ADS)

    Tetzlaff, D.; Soulsby, C.; Hrachowitz, M.; Speed, M.

    2009-04-01

    In recent years, transit times (TTs) have been increasingly explored as a process-based tools for conceptualising hydrological processes in an integrated manner at a range of scales. Traditionally the identification of the appropriate transit time distribution (TTD) for a hydrological system (e.g. hillslope or catchment), and the derivation of metrics such as the mean transit time (MTT) have required quantitative assessment of input-output relationships for conservative tracers using lumped parameter models. Such work has allowed the main landscape controls on TTs to be identified and facilitated the prediction of MTT in ungauged basins in particular geomorphic provinces. This has shown TT to be a useful diagnostic index of similarity that can be valuable in process-based catchment classification. In this contribution, we used well-constrained MTT estimates (with uncertainty) from 32 experimental catchments (1 to 250km2 in area) with contrasting geologic, topographic, pedologic and climatic characteristics in Scotland. The MTT was highly variable ranging from 30 days to ca. 1200 days for individual catchments. Moreover, MTT was also found to be closely correlated with key hydrometric design statistics such as the Q95, Q5, Mean Annual Flood (MAF) and the slope of the hydrograph recession curve. Analysis of the TT estimates, in conjunction with GIS-based quantitative assessment of key landscape controls, showed that MTT could be predicted to within 25% for ungauged basins from catchment soil cover, drainage density and topographic wetness index. For ungauged basins it was found that the hydrometric design statistics (Q95, Q5, MAF and the recession slope) could be more simply and accurately forecasted from MTT predictions than a single set of catchment characteristics. We demonstrate that TTs - predicted from mapped landscape characteristics - are useful integrating diagnostic metrics for regional classification, prediction and process assessment in ungauged montane

  4. 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.

  5. Characterizing the Hypermutated Subtype of Advanced Prostate Cancer as a Predictive Biomarker for Precision Medicine

    DTIC Science & Technology

    2015-10-01

    hypermutated advanced prostate cancers. Using a targeted deep sequencing assay that includes intronic and flanking regions we discovered DNA mismatch...subtype of advanced prostate cancer, most likely mutations in DNA mismatch repair genes. To test this hypothesis we performed targeted deep ...have adapted the mSINGS method to both the BROCA and UW-OncoPlex genomic deep sequencing platforms to accurately detect both phenotypic MSI and

  6. 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

  7. 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

  8. Application of infinite model predictive control methodology to other advanced controllers.

    PubMed

    Abu-Ayyad, M; Dubay, R; Hernandez, J M

    2009-01-01

    This paper presents an application of most recent developed predictive control algorithm an infinite model predictive control (IMPC) to other advanced control schemes. The IMPC strategy was derived for systems with different degrees of nonlinearity on the process gain and time constant. Also, it was shown that IMPC structure uses nonlinear open-loop modeling which is conducted while closed-loop control is executed every sampling instant. The main objective of this work is to demonstrate that the methodology of IMPC can be applied to other advanced control strategies making the methodology generic. The IMPC strategy was implemented on several advanced controllers such as PI controller using Smith-Predictor, Dahlin controller, simplified predictive control (SPC), dynamic matrix control (DMC), and shifted dynamic matrix (m-DMC). Experimental work using these approaches combined with IMPC was conducted on both single-input-single-output (SISO) and multi-input-multi-output (MIMO) systems and compared with the original forms of these advanced controllers. Computer simulations were performed on nonlinear plants demonstrating that the IMPC strategy can be readily implemented on other advanced control schemes providing improved control performance. Practical work included real-time control applications on a DC motor, plastic injection molding machine and a MIMO three zone thermal system.

  9. High-latitude E and F region ionospheric predictions

    NASA Technical Reports Server (NTRS)

    Hunsucker, R. D.; Allen, R.; Argo, P. E.; Babcock, R.; Bakshi, P.; Lund, D.; Matsushita, S.; Smith, G.; Shirochkov, A. V.; Wortham, G.

    1979-01-01

    The physical processes and morphology of the high latitude E and F layers are discussed. The existence and adequacy of models, and features to be included are examined, as well as reliability of ionospheric predictions.

  10. Data Mining and Predictive Modeling in Institutional Advancement: How Ten Schools Found Success. Technical Report

    ERIC Educational Resources Information Center

    Luperchio, Dan

    2009-01-01

    This technical report, produced in partnership by the Council for Advancement and Support of Education (CASE) and SPSS Inc., explores the promise of data mining alumni records at educational institutions. Working with individual alumni records from The Johns Hopkins Zanvyl Krieger School of Arts and Sciences, a predictive regression model is…

  11. 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

  12. Intermediate-term prediction in advance of the Loma Prieta earthquake

    SciTech Connect

    Keilis-Borok, V.I.; Kossobokov, V.; Rotvain, I. ); Knopoff, L. )

    1990-08-01

    The Loma Prieta earthquake of October 17, 1989 was predicted by the use of two pattern recognition algorithms, CN and M8. The prediction with algorithm CN was that an earthquake with magnitude greater than or equal to 6.4 was expected to occur in a roughly four year interval staring in midsummer 1986 in a polygonal spatial window of approximate average dimensions 600 {times} 450 km, encompassing Northern California and Northern Nevada. The prediction with algorithm M8 was that an earthquake with magnitude greater than or equal to 7.0 was expected to occur within 5 to 7 years after 1985, in a spatial window of approximate average dimensions 800 {times} 560 km. The predictions were communicated in advance of the earthquake. In previous, mainly retrospective applications of these algorithms, successful predictions occurred in about 80% of the cases.

  13. Small Engine Technology (SET) - Task 4, Regional Turboprop/Turbofan Engine Advanced Combustor Study

    NASA Technical Reports Server (NTRS)

    Reynolds, Robert; Srinivasan, Ram; Myers, Geoffrey; Cardenas, Manuel; Penko, Paul F. (Technical Monitor)

    2003-01-01

    Under the SET Program Task 4 - Regional Turboprop/Turbofan Engine Advanced Combustor Study, a total of ten low-emissions combustion system concepts were evaluated analytically for three different gas turbine engine geometries and three different levels of oxides of nitrogen (NOx) reduction technology, using an existing AlliedSignal three-dimensional (3-D) Computational Fluid Dynamics (CFD) code to predict Landing and Takeoff (LTO) engine cycle emission values. A list of potential Barrier Technologies to the successful implementation of these low-NOx combustor designs was created and assessed. A trade study was performed that ranked each of the ten study configurations on the basis of a number of manufacturing and durability factors, in addition to emissions levels. The results of the trade study identified three basic NOx-emissions reduction concepts that could be incorporated in proposed follow-on combustor technology development programs aimed at demonstrating low-NOx combustor hardware. These concepts are: high-flow swirlers and primary orifices, fuel-preparation cans, and double-dome swirlers.

  14. Regionality of disease progression predicts prognosis in amyotrophic lateral sclerosis.

    PubMed

    van der Kleij, Lisa A; Jones, Ashley R; Steen, I Nick; Young, Carolyn A; Shaw, Pamela J; Shaw, Christopher E; Leigh, P Nigel; Turner, Martin R; Al-Chalabi, Ammar

    2015-01-01

    Amyotrophic lateral sclerosis (ALS) is a devastating neurological syndrome in which motor neurons degenerate relentlessly. Although the site of onset and the rate of spread have been studied extensively, little is known about whether focal as opposed to diffuse disease affects prognosis. We therefore tested the hypothesis that regionality of disease burden is a prognostic factor in ALS. We analysed clinical data from two large multicentre, longitudinal trials. Regionality was defined as the difference in progression rates in three domains as measured by the revised ALS Functional Rating Scale, omitting the respiratory domain from analysis. We used death by trial end as the outcome variable and tested this by logistic regression against predictor variables including regionality and overall rate of disease progression. There were 561 patients. Regionality of disease was independently associated with significantly higher chance of death by study end (odds ratio most diffuse against most focal category 0.354 (0.191, 0.657), p = 0.001), with a direct relationship between degree of regionality and odds of death. We have shown using clinical trial data that focal disease is associated with a worse prognosis in ALS. Measures of regionality warrant further independent consideration in the development of future prognostic models.

  15. A Fast Algorithm for Exonic Regions Prediction in DNA Sequences

    PubMed Central

    Saberkari, Hamidreza; Shamsi, Mousa; Heravi, Hamed; Sedaaghi, Mohammad Hossein

    2013-01-01

    The main purpose of this paper is to introduce a fast method for gene prediction in DNA sequences based on the period-3 property in exons. First, the symbolic DNA sequences were converted to digital signal using the electron ion interaction potential method. Then, to reduce the effect of background noise in the period-3 spectrum, we used the discrete wavelet transform at three levels and applied it on the input digital signal. Finally, the Goertzel algorithm was used to extract period-3 components in the filtered DNA sequence. The proposed algorithm leads to decrease the computational complexity and hence, increases the speed of the process. Detection of small size exons in DNA sequences, exactly, is another advantage of the algorithm. The proposed algorithm ability in exon prediction was compared with several existing methods at the nucleotide level using: (i) specificity - sensitivity values; (ii) receiver operating curves (ROC); and (iii) area under ROC curve. Simulation results confirmed that the proposed method can be used as a promising tool for exon prediction in DNA sequences. PMID:24672762

  16. 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

  17. Formability Prediction of Advanced High Strength Steel with a New Ductile Fracture Criterion

    NASA Astrophysics Data System (ADS)

    Lou, Yanshan; Lim, Sungjun; Huh, Jeehyang; Huh, Hoon

    2011-08-01

    A ductile fracture criterion is newly proposed to accurately predict forming limit diagrams (FLD) of sheet metals. The new ductile fracture criterion is based on the effect of the non-dimensional stress triaxiality, the stress concentration factor and the effective plastic strain on the nucleation, growth and coalescence of voids. The new ductile fracture criterion has been applied to estimate the formability of four kind advanced high strength steels (AHSS): DP780, DP980, TRIP590, and TWIP980. FLDs predicted are compared with experimental results and those predicted by other ductile fracture criteria. The comparison demonstrates that FLDs predicted by the new ductile fracture criterion are in better agreement with experimental FLDs than those predicted by other ductile fracture criteria. The better agreement of FLDs predicted by the new ductile fracture criterion is because conventional ductile fracture criteria were proposed for fracture prediction in bulk metal forming while the new one is proposed to predict the onset of fracture in sheet metal forming processes.

  18. MGMT expression levels predict disease stabilisation, progression-free and overall survival in patients with advanced melanomas treated with DTIC.

    PubMed

    Busch, Christian; Geisler, Jürgen; Lillehaug, Johan R; Lønning, Per Eystein

    2010-07-01

    Metastatic melanoma responds poorly to systemic treatment. We report the results of a prospective single institution study evaluating O(6)-methylguanine-DNA methyltransferase (MGMT) status as a potential predictive and/or prognostic marker among patients treated with dacarbazine (DTIC) 800-1000 mg/m(2) monotherapy administered as a 3-weekly schedule for advanced malignant melanomas. The study was approved by the Regional Ethical Committee. Surgical biopsies from metastatic or loco-regional deposits obtained prior to DTIC treatment were snap-frozen immediately upon removal and stored in liquid nitrogen up to processing. Median time from enrolment to end of follow-up was 67 months. MGMT expression levels evaluated by qRT-PCR correlated significantly to DTIC benefit (CR/PR/SD; p=0.005), time to progression (TTP) (p=0.005) and overall survival (OS) (p=0.003). MGMT expression also correlated to Breslow thickness in the primary tumour (p=0.014). While MGMT promoter hypermethylation correlated to MGMT expression, MGMT promoter hypermethylation did not correlate to treatment benefit, TTP or OS, suggesting that other factors may be critical in determining MGMT expression levels in melanomas. In a Cox proportional regression analysis, serum lactate dehydrogenase (LDH, p<0.001), MGMT expression (p=0.022) and p16(INK4a) expression (p=0.037) independently predicted OS, while TTP correlated to DTIC benefit after 6 weeks only (p=0.001). Our data reveal MGMT expression levels to be associated with disease stabilisation and prognosis in patients receiving DTIC monotherapy for advanced melanoma. The role of MGMT expression as a predictor to DTIC sensitivity versus a general prognostic factor in advanced melanomas warrants further evaluation.

  19. Regional Variability and Predictability in the Upper Ocean

    DTIC Science & Technology

    2007-11-02

    for post-exercise analyses. To provide additional operational testing of telemetry components the system was also deployed in support of the ONR...depth-averaged currents in sub-polar and polar regions from known winds. 1) Lagrangian dispersion in the Gulf of Mexico: This work centered on testing ...dynamical systems theory) and turbulence theory. The testing was carried out using various statistical measures. The data consisted of surface drifter

  20. Development of advanced structural analysis methodologies for predicting widespread fatigue damage in aircraft structures

    NASA Technical Reports Server (NTRS)

    Harris, Charles E.; Starnes, James H., Jr.; Newman, James C., Jr.

    1995-01-01

    NASA is developing a 'tool box' that includes a number of advanced structural analysis computer codes which, taken together, represent the comprehensive fracture mechanics capability required to predict the onset of widespread fatigue damage. These structural analysis tools have complementary and specialized capabilities ranging from a finite-element-based stress-analysis code for two- and three-dimensional built-up structures with cracks to a fatigue and fracture analysis code that uses stress-intensity factors and material-property data found in 'look-up' tables or from equations. NASA is conducting critical experiments necessary to verify the predictive capabilities of the codes, and these tests represent a first step in the technology-validation and industry-acceptance processes. NASA has established cooperative programs with aircraft manufacturers to facilitate the comprehensive transfer of this technology by making these advanced structural analysis codes available to industry.

  1. 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.

  2. Advanced Numerical Prediction and Modeling of Tropical Cyclones Using WRF-NMM modeling system

    NASA Astrophysics Data System (ADS)

    Gopalakrishnan, S. G.; Rogers, R. F.; Marks, F. D.; Atlas, R.

    2007-12-01

    Dramatic improvement in tropical cyclone track forecasts have occurred through advancements in high quality observations, high speed computers and improvements in dynamical models. Similar advancements now need to be made for tropical cyclone intensity, structure and rainfall prediction. The Weather Research Forecasting Model (WRF) is a general purpose, multi-institutional mesoscale modeling system. A version of the WRF model called the HWRF/WRF-NMM modeling system, developed at the National Center for Environmental Protection (NCEP) was recently adopted for hurricane forecasting (Gopalakrishnan et al, 2006) by the National Hurricane Center (NHC). At the Hurricane Research Division (HRD/AOML/OAR) we are developing and further advancing a research version of this modeling system. This work is done in collaboration with the Developmental Test bed Center (DTC), Boulder, CO, Global Systems division (GSD/ESRL/OAR), Boulder, CO, The Air Resources Laboratory (ARL/OAR), Washington, D.C., the U.S. university community, the Indian Institute of Technology, IIT.Delhi, India, and the India Meteorological Department, New Delhi, India Our modeling effort includes advancing the WRF system for Ensemble Hurricane Forecasting, advancing our understanding of Ensemble-vs- High Resolution Forecasting of Hurricanes, advancing WRF/WRF-NMM with better analysis techniques (e.g. Four Dimensional Data Assimilation) for improving forecasts and above all, advancing our understanding of hurricane processes using a high resolution numerical modeling approach. Examples of some of these applications will be shown here. Reference: NCEP's Two-way-Interactive-Moving-Nest NMM-WRF modeling system for Hurricane Forecasting, S.G. Gopalakrishnan, N. Surgi, R. Tuleya, and Z. Janjic 27th Conference on Hurricanes and Tropical Meteorology, 24- 28 April 2006, Monterey, California.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. Distinct regions of anterior cingulate cortex signal prediction and outcome evaluation.

    PubMed

    Jahn, Andrew; Nee, Derek Evan; Alexander, William H; Brown, Joshua W

    2014-07-15

    A number of theories have been proposed to account for the role of anterior cingulate cortex (ACC) and the broader medial prefrontal cortex (mPFC) in cognition. The recent Prediction of Response Outcome (PRO) computational model casts the mPFC in part as performing two theoretically distinct functions: learning to predict the various possible outcomes of actions, and then evaluating those predictions against the actual outcomes. Simulations have shown that this new model can account for an unprecedented range of known mPFC effects, but the central theory of distinct prediction and evaluation mechanisms within ACC remains untested. Using combined computational neural modeling and fMRI, we show here that prediction and evaluation signals are indeed each represented in the ACC, and furthermore, they are represented in distinct regions within ACC. Our task independently manipulated both the number of predicted outcomes and the degree to which outcomes violated expectancies, the former providing assessment of regions sensitive to prediction and the latter providing assessment of regions sensitive to evaluation. Using quantitative regressors derived from the PRO computational model, we show that prediction-based model signals load on a network including the posterior and perigenual ACC, but outcome evaluation model signals load on the mid-dorsal ACC. These findings are consistent with distinct prediction and evaluation signals as posited by the PRO model and provide new perspective on a large set of known effects within ACC.

  9. Plasma mRNA as liquid biopsy predicts chemo-sensitivity in advanced gastric cancer patients.

    PubMed

    Shen, Jie; Kong, Weiwei; Wu, Yuanna; Ren, Haozhen; Wei, Jia; Yang, Yang; Yang, Yan; Yu, Lixia; Guan, Wenxian; Liu, Baorui

    2017-01-01

    Predictive biomarkers based individualized chemotherapy can improve efficacy. However, for those advanced patients, it may be impossible to obtain the tissues from operation. Tissues from biopsy may not be always enough for gene detection. Thus, biomarker from blood could be a non-invasive and useful tool to provide real-time information in the procedure of treatment. To further understand the role of plasma mRNA in chemo-efficiency prediction, several mRNA expression levels were assessed in plasma and paired tumor tissues from 133 locally advanced gastric cancer patients (stage III), and mRNA levels were correlated with chemosensitivity to docetaxel, pemetrexed, platinum, and irinotecan. mRNA expression level in 64 advanced gastric cancer patients (stage IV) was also examined (55 in test group, and 9 in control), and chemotherapy in the test group were given according to the plasma gene detection. As a result, in the 133 patients with locally advanced gastric cancer (Stage III), correlations were observed between the mRNA expression of plasma/tumor BRCA1 levels and docetaxel sensitivity (P<0.001), plasma/tumor TS and pemetrexed sensitivity (P<0.001), plasma/tumor BRCA1 and platinum sensitivity (plasma, P=0.016; tumor, P<0.001), and plasma/tumor TOPO1 and irinotecan sensitivity (plasma, P=0.015; tumor, P=0.011). Among another 64 patients with advanced cancer (Stage IV), the median OS of test group was 15.5m (95% CI=10.1 to 20.9m), the PFS was 9.1m (95% CI=8.0 to 10.2m), which were significant longer than the control (P=0.047 for OS, P=0.038 for PFS). The mortality risk was higher in the control than patients treated according to the plasma gene detection (HR in the control=2.34, 95% CI=0.93 to 5.88, P=0.071). Plasma mRNA as liquid biopsy could be ideal recourse for examination to predict chemo-sensitivity in gastric cancer.

  10. Plasma mRNA as liquid biopsy predicts chemo-sensitivity in advanced gastric cancer patients

    PubMed Central

    Shen, Jie; Kong, Weiwei; Wu, Yuanna; Ren, Haozhen; Wei, Jia; Yang, Yang; Yang, Yan; Yu, Lixia; Guan, Wenxian; Liu, Baorui

    2017-01-01

    Predictive biomarkers based individualized chemotherapy can improve efficacy. However, for those advanced patients, it may be impossible to obtain the tissues from operation. Tissues from biopsy may not be always enough for gene detection. Thus, biomarker from blood could be a non-invasive and useful tool to provide real-time information in the procedure of treatment. To further understand the role of plasma mRNA in chemo-efficiency prediction, several mRNA expression levels were assessed in plasma and paired tumor tissues from 133 locally advanced gastric cancer patients (stage III), and mRNA levels were correlated with chemosensitivity to docetaxel, pemetrexed, platinum, and irinotecan. mRNA expression level in 64 advanced gastric cancer patients (stage IV) was also examined (55 in test group, and 9 in control), and chemotherapy in the test group were given according to the plasma gene detection. As a result, in the 133 patients with locally advanced gastric cancer (Stage III), correlations were observed between the mRNA expression of plasma/tumor BRCA1 levels and docetaxel sensitivity (P<0.001), plasma/tumor TS and pemetrexed sensitivity (P<0.001), plasma/tumor BRCA1 and platinum sensitivity (plasma, P=0.016; tumor, P<0.001), and plasma/tumor TOPO1 and irinotecan sensitivity (plasma, P=0.015; tumor, P=0.011). Among another 64 patients with advanced cancer (Stage IV), the median OS of test group was 15.5m (95% CI=10.1 to 20.9m), the PFS was 9.1m (95% CI=8.0 to 10.2m), which were significant longer than the control (P=0.047 for OS, P=0.038 for PFS). The mortality risk was higher in the control than patients treated according to the plasma gene detection (HR in the control=2.34, 95% CI=0.93 to 5.88, P=0.071). Plasma mRNA as liquid biopsy could be ideal recourse for examination to predict chemo-sensitivity in gastric cancer.

  11. 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.

  12. Development of a constitutive model for creep and life prediction of advanced silicon nitride ceramics

    SciTech Connect

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

    1992-12-31

    A constitutive model capable of describing deformation and predicting rupture life was developed for high temperature ceramic materials under general thermal-mechanical loading conditions. The model was developed based on the deformation and fracture behavior observed from a systematic experimental study on an advanced silicon nitride (Si{sub 3}N{sub 4}) ceramic material. Validity of the model was evaluated with reference to creep and creep rupture data obtained under constant and stepwise-varied loading conditions, including the effects of annealing on creep and creep rupture behavior.

  13. 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

  14. Seasonal Predictability of the Regional Climate of the Mississippi River Basin

    NASA Technical Reports Server (NTRS)

    Tribbia, Joseph; Giorgi, Filippo

    2002-01-01

    This is a report on our accomplishments during the previous year and our wrap-up plans for the coming months for our work in studying the seasonal predictability of precipitation over the Mississippi River Basin. The work accomplished during the grant falls into two broad catagories: (1) diagnosis of regional skill of CCM3; and (2) regional and global model development.

  15. The inhabited environment, infrastructure development and advanced urbanization in China’s Yangtze River Delta Region

    NASA Astrophysics Data System (ADS)

    Zhu, Xiaoqing; Gao, Weijun; Zhou, Nan; Kammen, Daniel M.; Wu, Yiqun; Zhang, Yao; Chen, Wei

    2016-12-01

    This paper analyzes the relationship among the inhabited environment, infrastructure development and environmental impacts in China’s heavily urbanized Yangtze River Delta region. Using primary human environment data for the period 2006-2014, we examine factors affecting the inhabited environment and infrastructure development: urban population, GDP, built-up area, energy consumption, waste emission, transportation, real estate and urban greenery. Then we empirically investigate the impact of advanced urbanization with consideration of cities’ differences. Results from this study show that the growth rate of the inhabited environment and infrastructure development is strongly influenced by regional development structure, functional orientations, traffic network and urban size and form. The effect of advanced urbanization is more significant in large and mid-size cities than huge and mega cities. Energy consumption, waste emission and real estate in large and mid-size cities developed at an unprecedented rate with the rapid increase of economy. However, urban development of huge and mega cities gradually tended to be saturated. The transition development in these cities improved the inhabited environment and ecological protection instead of the urban construction simply. To maintain a sustainable advanced urbanization process, policy implications included urban sprawl control polices, ecological development mechanisms and reforming the economic structure for huge and mega cities, and construct major cross-regional infrastructure, enhance the carrying capacity and improvement of energy efficiency and structure for large and mid-size cities.

  16. 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

  17. 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

  18. Diagnostic sea ice predictability in the pan-Arctic and U.S. Arctic regional seas

    NASA Astrophysics Data System (ADS)

    Cheng, Wei; Blanchard-Wrigglesworth, Edward; Bitz, Cecilia M.; Ladd, Carol; Stabeno, Phyllis J.

    2016-11-01

    This study assesses sea ice predictability in the pan-Arctic and U.S. Arctic regional (Bering, Chukchi, and Beaufort) seas with a purpose of understanding regional differences from the pan-Arctic perspective and how predictability might change under changing climate. Lagged correlation is derived using existing output from the Community Earth System Model Large Ensemble (CESM-LE), Pan-Arctic Ice-Ocean Modeling and Assimilation System, and NOAA Coupled Forecast System Reanalysis models. While qualitatively similar, quantitative differences exist in Arctic ice area lagged correlation in models with or without data assimilation. On regional scales, modeled ice area lagged correlations are strongly location and season dependent. A robust feature in the CESM-LE is that the pan-Arctic melt-to-freeze season ice area memory intensifies, whereas the freeze-to-melt season memory weakens as climate warms, but there are across-region variations in the sea ice predictability changes with changing climate.

  19. Prediction of monthly regional groundwater levels through hybrid soft-computing techniques

    NASA Astrophysics Data System (ADS)

    Chang, Fi-John; Chang, Li-Chiu; Huang, Chien-Wei; Kao, I.-Feng

    2016-10-01

    Groundwater systems are intrinsically heterogeneous with dynamic temporal-spatial patterns, which cause great difficulty in quantifying their complex processes, while reliable predictions of regional groundwater levels are commonly needed for managing water resources to ensure proper service of water demands within a region. In this study, we proposed a novel and flexible soft-computing technique that could effectively extract the complex high-dimensional input-output patterns of basin-wide groundwater-aquifer systems in an adaptive manner. The soft-computing models combined the Self Organized Map (SOM) and the Nonlinear Autoregressive with Exogenous Inputs (NARX) network for predicting monthly regional groundwater levels based on hydrologic forcing data. The SOM could effectively classify the temporal-spatial patterns of regional groundwater levels, the NARX could accurately predict the mean of regional groundwater levels for adjusting the selected SOM, the Kriging was used to interpolate the predictions of the adjusted SOM into finer grids of locations, and consequently the prediction of a monthly regional groundwater level map could be obtained. The Zhuoshui River basin in Taiwan was the study case, and its monthly data sets collected from 203 groundwater stations, 32 rainfall stations and 6 flow stations during 2000 and 2013 were used for modelling purpose. The results demonstrated that the hybrid SOM-NARX model could reliably and suitably predict monthly basin-wide groundwater levels with high correlations (R2 > 0.9 in both training and testing cases). The proposed methodology presents a milestone in modelling regional environmental issues and offers an insightful and promising way to predict monthly basin-wide groundwater levels, which is beneficial to authorities for sustainable water resources management.

  20. A hybrid numerical technique for predicting the aerodynamic and acoustic fields of advanced turboprops

    NASA Technical Reports Server (NTRS)

    Homicz, G. F.; Moselle, J. R.

    1985-01-01

    A hybrid numerical procedure is presented for the prediction of the aerodynamic and acoustic performance of advanced turboprops. A hybrid scheme is proposed which in principle leads to a consistent simultaneous prediction of both fields. In the inner flow a finite difference method, the Approximate-Factorization Alternating-Direction-Implicit (ADI) scheme, is used to solve the nonlinear Euler equations. In the outer flow the linearized acoustic equations are solved via a Boundary-Integral Equation (BIE) method. The two solutions are iteratively matched across a fictitious interface in the flow so as to maintain continuity. At convergence the resulting aerodynamic load prediction will automatically satisfy the appropriate free-field boundary conditions at the edge of the finite difference grid, while the acoustic predictions will reflect the back-reaction of the radiated field on the magnitude of the loading source terms, as well as refractive effects in the inner flow. The equations and logic needed to match the two solutions are developed and the computer program implementing the procedure is described. Unfortunately, no converged solutions were obtained, due to unexpectedly large running times. The reasons for this are discussed and several means to alleviate the situation are suggested.

  1. A prospective study of the efficacy of magnetic resonance spectroscopy imaging for predicting locally advanced prostate cancer

    PubMed Central

    Razi, Ali; Parizi, Mehdi Kardoust; Kazemeini, Seid Mohammad; Abedi, Akbar

    2015-01-01

    Objective: To evaluate the efficacy of magnetic resonance spectroscopy imaging (MRSI) for predicting locally advanced prostate cancer (PC). Materials and methods: Between April 2009 and July 2012, 80 consecutive patients with clinically localized PC had undergone endorectal MRSI before radical retropubic prostatectomy. Clinicopathological parameters, including age, preoperative prostate-specific antigen (PSA), Gleason score (GS) at biopsy, perinural invasion at biopsy, prostate weight at surgery, GS of surgical specimen, and pathological staging were recorded. The MRSI findings were compared with the histopathological findings of the radical prostatectomy. The diagnostic accuracy measures consisting of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) of MRSI, and other variables in the diagnosis of locally advanced PC (Pathology Stages pT3a, pT3b, or pT4) were evaluated. Results: Sensitivity, specificity, PPV, and NPV of MRSI in detecting locally advanced PC is 42.4%, 93.6%, 82.3%, and 69.8%, respectively [area under the receiver operating characteristic (ROC) curve=0.658, p value <0.0001]. MRSI, cancer-positive core percentage at biopsy, and GS at biopsy are more accurate factors among all the predictive variables in predicting locally advanced PC. Conclusion: MRSI may be considered as a complementary diagnostic modality with high specificity and moderate sensitivity in predicting locally advanced PC. Combination of this modality with other predictive factors helps the surgeon and patient to select an appropriate treatment strategy. PMID:26328204

  2. Predictive Factors of Tumor Response After Neoadjuvant Chemoradiation for Locally Advanced Rectal Cancer

    SciTech Connect

    Moureau-Zabotto, Laurence; Farnault, Bertrand; de Chaisemartin, Cecile; Esterni, Benjamin; Lelong, Bernard; Viret, Frederic; Giovannini, Marc; Monges, Genevieve; Delpero, Jean-Robert; Bories, Erwan; Turrini, Olivier; Viens, Patrice; Salem, Naji

    2011-06-01

    Purpose: Neoadjuvant chemoradiation followed by surgery is the standard of care for locally advanced rectal cancer. The aim of this study was to correlate tumor response to survival and to identify predictive factors for tumor response after chemoradiation. Methods and Materials: From 1998 to 2008, 168 patients with histologically proven locally advanced adenocarcinoma treated by preoperative chemoradiation before total mesorectal excision were retrospectively studied. They received a radiation dose of 45 Gy with a concomitant 5-fluorouracil (5-FU)-based chemotherapy. Analysis of tumor response was based on lowering of the T stage between pretreatment endorectal ultrasound and pathologic specimens. Overall and progression-free survival rates were correlated with tumor response. Tumor response was analyzed with predictive factors. Results: The median follow-up was 34 months. Five-year disease-free survival and overall survival rates were, of 44.4% and 74.5% in the whole population, 83.4% and 83.4%, respectively, in patients with pathological complete response, 38.6% and 71.9%, respectively, in patients with tumor downstaging, and 29.1and 58.9% respectively, in patients with absence of response. A pretreatment carcinoembryonic antigen (CEA) level of <5 ng/ml was significantly independently associated with pathologic complete tumor response (p = 0.019). Pretreatment small tumor size (p = 0.04), pretreatment CEA level of <5 ng/ml (p = 0.008), and chemotherapy with capecitabine (vs. 5-FU) (p = 0.04) were significantly associated with tumor downstaging. Conclusions: Downstaging and complete response after CRT improved progression-free survival and overall survival of locally advanced rectal adenocarcinoma. In multivariate analysis, a pretreatment CEA level of <5 ng/ml was associated with complete tumor response. Thus, small tumor size, a pretreatment CEA level of < 5ng/ml, and use of capecitabine were associated with tumor downstaging.

  3. Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

    SciTech Connect

    Maslowski, Wieslaw

    2016-10-17

    This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate through polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.

  4. Prediction of flexible/rigid regions from protein sequences using k-spaced amino acid pairs

    PubMed Central

    Chen, Ke; Kurgan, Lukasz A; Ruan, Jishou

    2007-01-01

    Background Traditionally, it is believed that the native structure of a protein corresponds to a global minimum of its free energy. However, with the growing number of known tertiary (3D) protein structures, researchers have discovered that some proteins can alter their structures in response to a change in their surroundings or with the help of other proteins or ligands. Such structural shifts play a crucial role with respect to the protein function. To this end, we propose a machine learning method for the prediction of the flexible/rigid regions of proteins (referred to as FlexRP); the method is based on a novel sequence representation and feature selection. Knowledge of the flexible/rigid regions may provide insights into the protein folding process and the 3D structure prediction. Results The flexible/rigid regions were defined based on a dataset, which includes protein sequences that have multiple experimental structures, and which was previously used to study the structural conservation of proteins. Sequences drawn from this dataset were represented based on feature sets that were proposed in prior research, such as PSI-BLAST profiles, composition vector and binary sequence encoding, and a newly proposed representation based on frequencies of k-spaced amino acid pairs. These representations were processed by feature selection to reduce the dimensionality. Several machine learning methods for the prediction of flexible/rigid regions and two recently proposed methods for the prediction of conformational changes and unstructured regions were compared with the proposed method. The FlexRP method, which applies Logistic Regression and collocation-based representation with 95 features, obtained 79.5% accuracy. The two runner-up methods, which apply the same sequence representation and Support Vector Machines (SVM) and Naïve Bayes classifiers, obtained 79.2% and 78.4% accuracy, respectively. The remaining considered methods are characterized by accuracies below 70

  5. 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.

  6. 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.

  7. Regional cooling caused recent New Zealand glacier advances in a period of global warming.

    PubMed

    Mackintosh, Andrew N; Anderson, Brian M; Lorrey, Andrew M; Renwick, James A; Frei, Prisco; Dean, Sam M

    2017-02-14

    Glaciers experienced worldwide retreat during the twentieth and early twenty first centuries, and the negative trend in global glacier mass balance since the early 1990s is predominantly a response to anthropogenic climate warming. The exceptional terminus advance of some glaciers during recent global warming is thought to relate to locally specific climate conditions, such as increased precipitation. In New Zealand, at least 58 glaciers advanced between 1983 and 2008, and Franz Josef and Fox glaciers advanced nearly continuously during this time. Here we show that the glacier advance phase resulted predominantly from discrete periods of reduced air temperature, rather than increased precipitation. The lower temperatures were associated with anomalous southerly winds and low sea surface temperature in the Tasman Sea region. These conditions result from variability in the structure of the extratropical atmospheric circulation over the South Pacific. While this sequence of climate variability and its effect on New Zealand glaciers is unusual on a global scale, it remains consistent with a climate system that is being modified by humans.

  8. Regional cooling caused recent New Zealand glacier advances in a period of global warming

    NASA Astrophysics Data System (ADS)

    Mackintosh, Andrew N.; Anderson, Brian M.; Lorrey, Andrew M.; Renwick, James A.; Frei, Prisco; Dean, Sam M.

    2017-02-01

    Glaciers experienced worldwide retreat during the twentieth and early twenty first centuries, and the negative trend in global glacier mass balance since the early 1990s is predominantly a response to anthropogenic climate warming. The exceptional terminus advance of some glaciers during recent global warming is thought to relate to locally specific climate conditions, such as increased precipitation. In New Zealand, at least 58 glaciers advanced between 1983 and 2008, and Franz Josef and Fox glaciers advanced nearly continuously during this time. Here we show that the glacier advance phase resulted predominantly from discrete periods of reduced air temperature, rather than increased precipitation. The lower temperatures were associated with anomalous southerly winds and low sea surface temperature in the Tasman Sea region. These conditions result from variability in the structure of the extratropical atmospheric circulation over the South Pacific. While this sequence of climate variability and its effect on New Zealand glaciers is unusual on a global scale, it remains consistent with a climate system that is being modified by humans.

  9. Regional cooling caused recent New Zealand glacier advances in a period of global warming

    PubMed Central

    Mackintosh, Andrew N.; Anderson, Brian M.; Lorrey, Andrew M.; Renwick, James A.; Frei, Prisco; Dean, Sam M.

    2017-01-01

    Glaciers experienced worldwide retreat during the twentieth and early twenty first centuries, and the negative trend in global glacier mass balance since the early 1990s is predominantly a response to anthropogenic climate warming. The exceptional terminus advance of some glaciers during recent global warming is thought to relate to locally specific climate conditions, such as increased precipitation. In New Zealand, at least 58 glaciers advanced between 1983 and 2008, and Franz Josef and Fox glaciers advanced nearly continuously during this time. Here we show that the glacier advance phase resulted predominantly from discrete periods of reduced air temperature, rather than increased precipitation. The lower temperatures were associated with anomalous southerly winds and low sea surface temperature in the Tasman Sea region. These conditions result from variability in the structure of the extratropical atmospheric circulation over the South Pacific. While this sequence of climate variability and its effect on New Zealand glaciers is unusual on a global scale, it remains consistent with a climate system that is being modified by humans. PMID:28195582

  10. 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

  11. 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.

  12. Comparison of the Berg Balance Scale and Fullerton Advanced Balance Scale to predict falls in community-dwelling adults

    PubMed Central

    Jeon, Yong-Jin; Kim, Gyoung-Mo

    2017-01-01

    [Purpose] The purpose of this study was to investigate and compare the predictive properties of Berg Balance Scale and Fullerton Advanced Balance Scales, in a group of independently-functioning community dwelling older adults. [Subjects and Methods] Ninety-seven community-dwelling older adults (male=39, female=58) who were capable of walking independently on assessment were included in this study. A binary logistic regression analysis of the Berg Balance Scale and Fullerton Advanced Balance Scale scores was used to investigate a predictive model for fall risk. A receiver operating characteristic analysis was conducted for each, to determine the cut-off for optimal levels of sensitivity and specificity. [Results] The overall prediction success rate was 89.7%; the total Berg Balance Scale and Fullerton Advanced Balance Scale scores were significant in predicting fall risk. Receiver operating characteristic analysis determined that a cut-off score of 40 out of 56 on the Berg Balance Scale produced the highest sensitivity (0.82) and specificity (0.67), and a cut-off score of 22 out of 40 on the Fullerton Advanced Balance Scale produced the highest sensitivity (0.85) and specificity (0.65) in predicting faller status. [Conclusion] The Berg Balance Scale and Fullerton Advanced Balance Scales can predict fall risk, when used for independently-functioning community-dwelling older adults. PMID:28265146

  13. Comparison of the Berg Balance Scale and Fullerton Advanced Balance Scale to predict falls in community-dwelling adults.

    PubMed

    Jeon, Yong-Jin; Kim, Gyoung-Mo

    2017-02-01

    [Purpose] The purpose of this study was to investigate and compare the predictive properties of Berg Balance Scale and Fullerton Advanced Balance Scales, in a group of independently-functioning community dwelling older adults. [Subjects and Methods] Ninety-seven community-dwelling older adults (male=39, female=58) who were capable of walking independently on assessment were included in this study. A binary logistic regression analysis of the Berg Balance Scale and Fullerton Advanced Balance Scale scores was used to investigate a predictive model for fall risk. A receiver operating characteristic analysis was conducted for each, to determine the cut-off for optimal levels of sensitivity and specificity. [Results] The overall prediction success rate was 89.7%; the total Berg Balance Scale and Fullerton Advanced Balance Scale scores were significant in predicting fall risk. Receiver operating characteristic analysis determined that a cut-off score of 40 out of 56 on the Berg Balance Scale produced the highest sensitivity (0.82) and specificity (0.67), and a cut-off score of 22 out of 40 on the Fullerton Advanced Balance Scale produced the highest sensitivity (0.85) and specificity (0.65) in predicting faller status. [Conclusion] The Berg Balance Scale and Fullerton Advanced Balance Scales can predict fall risk, when used for independently-functioning community-dwelling older adults.

  14. 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.

  15. In silico ADMET prediction: recent advances, current challenges and future trends.

    PubMed

    Cheng, Feixiong; Li, Weihua; Liu, Guixia; Tang, Yun

    2013-01-01

    There are numerous small molecular compounds around us to affect our health, such as drugs, pesticides, food additives, industrial chemicals, and environmental pollutants. Over decades, properties related to absorption, distribution, metabolism, excretion, and toxicity (ADMET) have become one of the most important issues to assess the effects or risks of these compounds on human body. Recent high-rate drug withdrawals increase the pressure on regulators and pharmaceutical industry to improve preclinical safety testing. Since in vivo and in vitro evaluations are costly and laborious, in silico techniques have been widely used to estimate these properties. In this review, we would briefly describe the recent advances of in silico ADMET prediction, with emphasis on substructure pattern recognition method that we developed recently. Challenges and limitations in the area of in silico ADMET prediction were further discussed, such as application domain of models, models validation techniques, and global versus local models. At last, several new promising research directions were provided, such as computational systems toxicology (toxicogenomics), data-integration and meta-decision making systems, which could be used for systemic in silico ADMET prediction in drug discovery and hazard risk assessment.

  16. Creating a framework for clinical nursing practice to advance in the West Midlands region.

    PubMed

    Dunn, L; Morgan, E

    1998-05-01

    The West Midlands Regional Health Authority identified a lack of opportunities for nurses to develop advanced clinical practice through a recognized programme at Postgraduate diploma/Masters degree level. Education for clinical practice must be equally grounded in theory and practice. Advanced clinical practice requires more than just skills acquisition, it has a much wider remit incorporating elements of clinical expertise and higher level decision making, research awareness, teaching and role modelling, informing policy making and leading in the provision of patient care within individual Trusts. This initiative has encouraged universities, trusts and provider units to work together to identify and prepare students and staff for their changes in role, and to review existing boundaries for practice which will enable new approaches to team work and the provision of holistic patient care.

  17. Improving hot region prediction by parameter optimization of density clustering in PPI.

    PubMed

    Hu, Jing; Zhang, Xiaolong

    2016-11-01

    This paper proposed an optimized algorithm which combines density clustering of parameter selection with feature-based classification for hot region prediction. First, all the residues are classified by SVM to remove non-hot spot residues, then density clustering of parameter selection is used to find hot regions. In the density clustering, this paper studies how to select input parameters. There are two parameters radius and density in density-based incremental clustering. We firstly fix density and enumerate radius to find a pair of parameters which leads to maximum number of clusters, and then we fix radius and enumerate density to find another pair of parameters which leads to maximum number of clusters. Experiment results show that the proposed method using both two pairs of parameters provides better prediction performance than the other method, and compare these two predictive results, the result by fixing radius and enumerating density have slightly higher prediction accuracy than that by fixing density and enumerating radius.

  18. 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.

  19. 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.

  20. 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.

  1. Perspective on Advances in Resonance-Region Nuclear Modeling and Opportunities for Future Research

    SciTech Connect

    Dunn, Michael E; Larson, Nancy M; Derrien, Herve; Leal, Luiz C

    2007-01-01

    The advent of high-fidelity radiation-transport modeling capabilities, coupled with the need to analyze complex nuclear systems, has served to emphasize the importance of high-precision cross section data, including the associated covariance information. Due to the complex nature of resonance-region interactions, cross section data cannot be calculated directly from theory; rather, high-precision resonance-region cross section measurements must be made at facilities such as the Oak Ridge Electron Linear Accelerator (ORELA) at Oak Ridge National Laboratory (ORNL), Geel Electron Linear Accelerator (GELINA), Rensselaer Polytechnic Institute (RPI). To extract accurate cross section data from these measurements, detailed nuclear modeling of the measured data is performed to parameterize the cross section behavior in the resonance range. The objective of this paper is to highlight recent advances in resonance-region nuclear modeling with particular emphasis on the covariance analysis capabilities. Opportunities for future research are identified in an effort to stimulate further advances in the state of the art nuclear modeling capabilities.

  2. 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.

  3. 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.

  4. The Ordered Network Structure and Prediction Summary for M≥7 Earthquakes in Xinjiang Region of China

    NASA Astrophysics Data System (ADS)

    Men, Ke-Pei; Zhao, Kai

    2014-12-01

    M ≥7 earthquakes have showed an obvious commensurability and orderliness in Xinjiang of China and its adjacent region since 1800. The main orderly values are 30 a × k (k = 1,2,3), 11 ~ 12 a, 41 ~ 43 a, 18 ~ 19 a, and 5 ~ 6 a. In the guidance of the information forecasting theory of Wen-Bo Weng, based on previous research results, combining ordered network structure analysis with complex network technology, we focus on the prediction summary of M ≥ 7 earthquakes by using the ordered network structure, and add new information to further optimize network, hence construct the 2D- and 3D-ordered network structure of M ≥ 7 earthquakes. In this paper, the network structure revealed fully the regularity of seismic activity of M ≥ 7 earthquakes in the study region during the past 210 years. Based on this, the Karakorum M7.1 earthquake in 1996, the M7.9 earthquake on the frontier of Russia, Mongol, and China in 2003, and two Yutian M7.3 earthquakes in 2008 and 2014 were predicted successfully. At the same time, a new prediction opinion is presented that the future two M ≥ 7 earthquakes will probably occur around 2019 - 2020 and 2025 - 2026 in this region. The results show that large earthquake occurred in defined region can be predicted. The method of ordered network structure analysis produces satisfactory results for the mid-and-long term prediction of M ≥ 7 earthquakes.

  5. Role of dynamic vegetation in regional climate predictions over western Africa

    NASA Astrophysics Data System (ADS)

    Alo, Clement Aga; Wang, Guiling

    2010-10-01

    This study examines the role of vegetation dynamics in regional predictions of future climate change in western Africa using a dynamic vegetation model asynchronously coupled to a regional climate model. Two experiments, one for present day and one for future, are conducted with the linked regional climate-vegetation model, and the third with the regional climate model standing alone that predicts future climate based on present-day vegetation. These simulations are so designed in order to tease out the impact of structural vegetation feedback on simulated climate and hydrological processes. According to future predictions by the regional climate-vegetation model, increase in LAI is widespread, with significant shift in vegetation type. Over the Guinean Coast in 2084-2093, evergreen tree coverage decreases by 49% compared to 1984-1993, while drought deciduous tree coverage increases by 56%. Over the Sahel region in the same period, grass cover increases by 31%. Such vegetation changes are accompanied by a decrease of JJA rainfall by 2% over the Guinean Coast and an increase by 23% over the Sahel. This rather small decrease or large increase of precipitation is largely attributable to the role of vegetation feedback. Without the feedback effect from vegetation, the regional climate model would have predicted a 5% decrease of JJA rainfall in both the Guinean Coast and the Sahel as a result of the radiative and physiological effects of higher atmospheric CO2 concentration. These results demonstrate that climate- and CO2-induced changes in vegetation structure modify hydrological processes and climate at magnitudes comparable to or even higher than the radiative and physiological effects, thus evincing the importance of including vegetation feedback in future climate predictions.

  6. 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.

  7. 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.

  8. Prediction and preliminary standardization of fire debris constituents with the advanced distillation curve method.

    PubMed

    Bruno, Thomas J; Lovestead, Tara M; Huber, Marcia L

    2011-01-01

    The recent National Academy of Sciences report on forensic sciences states that the study of fire patterns and debris in arson fires is in need of additional work and eventual standardization. We discuss a recently introduced method that can provide predicted evaporation patterns for ignitable liquids as a function of temperature. The method is a complex fluid analysis protocol, the advanced distillation curve approach, featuring a composition explicit data channel for each distillate fraction (for qualitative, quantitative, and trace analysis), low uncertainty temperature measurements that are thermodynamic state points that can be modeled with an equation of state, consistency with a century of historical data, and an assessment of the energy content of each distillate fraction. We discuss the application of the method to kerosenes and gasolines and outline how expansion of the scope of fluids to other ignitable liquids can benefit the criminalist in the analysis of fire debris for arson.

  9. 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.

  10. Mutations within enhancer II and BCP regions of hepatitis B virus in relation to advanced liver diseases in patients infected with subgenotype B3 in Indonesia.

    PubMed

    Heriyanto, Didik Setyo; Yano, Yoshihiko; Utsumi, Takako; Anggorowati, Nungki; Rinonce, Hanggoro Tri; Lusida, Maria Inge; Soetjipto; Triwikatmani, Catharina; Ratnasari, Neneng; Maduseno, Sutanto; Purnama, Putut Bayu; Nurdjanah, Siti; Hayashi, Yoshitake

    2012-01-01

    Studies on the characteristics of mutations within the hepatitis B virus (HBV) genome, their roles in the pathogenesis of advanced liver diseases, and the involvement of host properties of HBV-infected individuals have not been conducted in subgenotype B3-infected populations. For addressing this issue, 40 cases with HBV surface antigen (HBsAg)-positive advanced liver diseases, including advanced liver cancer and cirrhosis (male 31, female 9, age 54.4 ± 11.6-year-old), were collected and compared with 109 cases with chronic hepatitis B (male 71, female 38, age 38.0 ± 13.4-year-old). Mutations in enhancer II (Enh II) and basal core promoter (BCP)/precore regions were analyzed by PCR-direct sequencing method. HBV viral load was examined by real-time PCR. For all examined regions, the prevalence of mutation was significantly higher in cases with advanced liver diseases. Multivariate analysis showed that, in patients older than 45 years, C1638T and T1753V mutations constituted independent risk factors for the advancement of liver diseases. The presence of C1638T and T1753V mutations may serve as predictive markers for the progression of liver diseases in Indonesia and other countries, where subgenotype B3 infection is prevalent.

  11. 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.

  12. Simulation of Regional-scale Nucleation Events and Prediction of Aerosol Number Concentration in a Regional Air Quality Model

    NASA Astrophysics Data System (ADS)

    Jung, J.; Adams, P.; Pandis, S.

    2006-12-01

    Nanoparticles can perturb Earth's climate by growing to cloud condensation nuclei sizes and also may be harmful to human health. Accurate simulation of the nucleation, growth, and removal of multicomponent nanoparticles demands enormous computational resources. Most regional-scale three-dimensional chemical transport models do not include nanoparticles and do not conserve number concentrations. A major challenge associated with the simulation of nucleation events is the uncertainty regarding the controlling nucleation mechanism under typical atmospheric conditions. Previous work indicates that nucleation events in the Pittsburgh area are well predicted using ternary (H2O-H2SO4-NH3) nucleation theory, which was successful in predicting on which days nucleation events occurred during summer and winter, as well as the beginning and end of the events. To predict the composition and growth of nanoparticles, we have developed a computationally efficient new approach based on the Two-Moment Aerosol Sectional (TOMAS) microphysics module. This model simulates inorganic and organic components of the nanoparticles describing both the number and the mass distribution of the particulate matter from approximately 1 nm to 10 micrometers. The model explains why nanoparticles were observed to be acidic during nucleation events that appear to involve ammonia. The simulation suggests that nanoparticles produced by ternary nucleation can be acidic due to depletion of ammonia vapor during the growth of the particles out of the nucleation sizes. The low CPU time requirements of the model using TOMAS make it suitable for incorporation in three- dimensional chemical transport models. The nucleation/coagulation/growth model has been added to the PMCAMx regional air quality model and is used for the investigation of nucleation events in the Eastern U.S. We can estimate number budget in the Eastern U.S. and predict frequency/size of nucleation events.

  13. Predicted functional RNAs within coding regions constrain evolutionary rates of yeast proteins.

    PubMed

    Warden, Charles D; Kim, Seong-Ho; Yi, Soojin V

    2008-02-13

    Functional RNAs (fRNAs) are being recognized as an important regulatory component in biological processes. Interestingly, recent computational studies suggest that the number and biological significance of functional RNAs within coding regions (coding fRNAs) may have been underestimated. We hypothesized that such coding fRNAs will impose additional constraint on sequence evolution because the DNA primary sequence has to simultaneously code for functional RNA secondary structures on the messenger RNA in addition to the amino acid codons for the protein sequence. To test this prediction, we first utilized computational methods to predict conserved fRNA secondary structures within multiple species alignments of Saccharomyces sensu strico genomes. We predict that as much as 5% of the genes in the yeast genome contain at least one functional RNA secondary structure within their protein-coding region. We then analyzed the impact of coding fRNAs on the evolutionary rate of protein-coding genes because a decrease in evolutionary rate implies constraint due to biological functionality. We found that our predicted coding fRNAs have a significant influence on evolutionary rates (especially at synonymous sites), independent of other functional measures. Thus, coding fRNA may play a role on sequence evolution. Given that coding regions of humans and flies contain many more predicted coding fRNAs than yeast, the impact of coding fRNAs on sequence evolution may be substantial in genomes of higher eukaryotes.

  14. 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.

  15. 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

  16. 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.

    1979-01-01

    This paper presents the performance and cost of four 10-MWe advanced solar thermal electric power plants sited in various regions of the continental United States. Each region has different insolation characteristics which result in varying collector field areas, plant performance, capital costs, and energy costs. The paraboloidal dish, central receiver, cylindrical parabolic trough, and compound parabolic concentrator (CPC) comprise the advanced concepts studied. This paper contains a discussion of the regional insolation data base, a description of the solar systems' performances and costs, and a presentation of a range for the forecast cost of conventional electricity by region and nationally over the next several decades.

  17. [Prediction of regional soil quality based on mutual information theory integrated with decision tree algorithm].

    PubMed

    Lin, Fen-Fang; Wang, Ke; Yang, Ning; Yan, Shi-Guang; Zheng, Xin-Yu

    2012-02-01

    In this paper, some main factors such as soil type, land use pattern, lithology type, topography, road, and industry type that affect soil quality were used to precisely obtain the spatial distribution characteristics of regional soil quality, mutual information theory was adopted to select the main environmental factors, and decision tree algorithm See 5.0 was applied to predict the grade of regional soil quality. The main factors affecting regional soil quality were soil type, land use, lithology type, distance to town, distance to water area, altitude, distance to road, and distance to industrial land. The prediction accuracy of the decision tree model with the variables selected by mutual information was obviously higher than that of the model with all variables, and, for the former model, whether of decision tree or of decision rule, its prediction accuracy was all higher than 80%. Based on the continuous and categorical data, the method of mutual information theory integrated with decision tree could not only reduce the number of input parameters for decision tree algorithm, but also predict and assess regional soil quality effectively.

  18. Prediction of Daily Flow Duration Curves and Streamflow for Ungauged Catchments Using Regional Flow Duration Curves

    EPA Science Inventory

    This study presents a method to predict flow duration curves (FDCs) and streamflow for ungauged catchments in the Mid-Atlantic Region, USA. We selected 29 catchments from the Appalachian Plateau, Ridge and Valley, and Piedmont physiographic provinces to develop and test the propo...

  19. Predicting Inner Heliospheric Solar Wind Conditions in Advance of Solar Probe Plus

    NASA Astrophysics Data System (ADS)

    Case, A. W.; Kasper, J. C.; Korreck, K. E.; Stevens, M. L.; Cohen, O.; Salem, C. S.; Halekas, J. S.; Larson, D. E.; Maruca, B. A.

    2012-12-01

    In advance of the upcoming inner heliospheric missions (Solar Orbiter and Solar Probe Plus) it is vital to have an accurate prediction of the range of solar wind conditions that occur between 9.5Rs and 0.7AU. These conditions will place constraints on instrument design and the operational modes that are used. In this paper, we discuss and compare different methods of predicting the solar wind bulk plasma parameters. One method uses observed 1AU conditions observed with the Wind spacecraft combined with scaling laws derived from Helios observations. We extend this simple model by using a more realistic solar wind velocity profile in addition to the Wind and Helios observations. Another method uses 3D MHD simulations from which solar wind conditions along a spacecraft trajectory can be extracted. We discuss some implications of these models in the design of the Solar Wind Electrons Alphas and Protons investigation, a suite of solar wind instruments being designed to fly on Solar Probe Plus.

  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. 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.

  2. 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).

  3. 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.

  4. 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.

  5. 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

  6. 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).

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub-continental scales.

    PubMed

    Collins, Sarah M; Oliver, Samantha K; Lapierre, Jean Francois; Stanley, Emily H; Jones, John R; Wagner, Tyler; Soranno, Patricia A

    2017-03-31

    Production in many ecosystems is co-limited by multiple elements. While a known suite of drivers associated with nutrient sources, nutrient transport, and internal processing controls concentrations of phosphorus (P) and nitrogen (N) in lakes, much less is known about whether the drivers of single nutrient concentrations can also explain spatial or temporal variation in lake N:P stoichiometry. Predicting stoichiometry might be more complex than predicting concentrations of individual elements because some drivers have similar relationships with N and P, leading to a weak relationship with their ratio. Further, the dominant controls on elemental concentrations likely vary across regions, resulting in context dependent relationships between drivers, lake nutrients and their ratios. Here, we examine whether known drivers of N and P concentrations can explain variation in N:P stoichiometry, and whether explaining variation in stoichiometry differs across regions. We examined drivers of N:P in ~2,700 lakes at a sub-continental scale and two large regions nested within the sub-continental study area that have contrasting ecological context, including differences in the dominant type of land cover (agriculture vs. forest). At the sub-continental scale, lake nutrient concentrations were correlated with nutrient loading and lake internal processing, but stoichiometry was only weakly correlated to drivers of lake nutrients. At the regional scale, drivers that explained variation in nutrients and stoichiometry differed between regions. In the Midwestern US region, dominated by agricultural land use, lake depth and the percentage of row crop agriculture were strong predictors of stoichiometry because only phosphorus was related to lake depth and only nitrogen was related to the percentage of row crop agriculture. In contrast, all drivers were related to N and P in similar ways in the Northeastern US region, leading to weak relationships between drivers and stoichiometry. Our

  12. Resonance Region Nuclear Data Analysis to Support Advanced Fuel Cycle Development

    SciTech Connect

    Dunn, Michael E; Derrien, Herve; Leal, Luiz C; Gil, Choong-Sup; Kim, D.

    2011-01-01

    The Oak Ridge National Laboratory (ORNL) and the Korean Atomic Energy Research Institute (KAERI) are performing collaborative research as part of a three-year United States (U.S.) / Republic of Korea (ROK) International Nuclear Energy Research Initiative (I-NERI) project to provide improved neutron cross-section data with uncertainty or covariance data important for advanced fuel cycle and nuclear safeguards applications. ORNL and KAERI have initiated efforts to prepare new cross-section evaluations for 240Pu, 237Np, and the stable Cm isotopes. At the current stage of the I-NERI project, ORNL has recently completed a preliminary resonance-region cross-section evaluation with covariance data for 240Pu and initiated resonance evaluation efforts for 237Np and 244Cm. Likewise, KAERI is performing corresponding high-energy cross-section analyses (i.e., above the resonance region) for the noted isotopes. The paper provides results pertaining to the new resonance region evaluation efforts with emphasis on the new 240Pu evaluation.

  13. Improved sequence-based prediction of disordered regions with multilayer fusion of multiple information sources

    PubMed Central

    Mizianty, Marcin J.; Stach, Wojciech; Chen, Ke; Kedarisetti, Kanaka Durga; Disfani, Fatemeh Miri; Kurgan, Lukasz

    2010-01-01

    Motivation: Intrinsically disordered proteins play a crucial role in numerous regulatory processes. Their abundance and ubiquity combined with a relatively low quantity of their annotations motivate research toward the development of computational models that predict disordered regions from protein sequences. Although the prediction quality of these methods continues to rise, novel and improved predictors are urgently needed. Results: We propose a novel method, named MFDp (Multilayered Fusion-based Disorder predictor), that aims to improve over the current disorder predictors. MFDp is as an ensemble of 3 Support Vector Machines specialized for the prediction of short, long and generic disordered regions. It combines three complementary disorder predictors, sequence, sequence profiles, predicted secondary structure, solvent accessibility, backbone dihedral torsion angles, residue flexibility and B-factors. Our method utilizes a custom-designed set of features that are based on raw predictions and aggregated raw values and recognizes various types of disorder. The MFDp is compared at the residue level on two datasets against eight recent disorder predictors and top-performing methods from the most recent CASP8 experiment. In spite of using training chains with ≤25% similarity to the test sequences, our method consistently and significantly outperforms the other methods based on the MCC index. The MFDp outperforms modern disorder predictors for the binary disorder assignment and provides competitive real-valued predictions. The MFDp's outputs are also shown to outperform the other methods in the identification of proteins with long disordered regions. Availability: http://biomine.ece.ualberta.ca/MFDp.html Supplementary information: Supplementary data are available at Bioinformatics online. Contact: lkurgan@ece.ualberta.ca PMID:20823312

  14. Research Area 3 - Mathematical Sciences: Multiscale Modeling of the Mechanics of Advanced Energetic Materials Relevant to Detonation Prediction

    DTIC Science & Technology

    2015-08-24

    new energetic materials with enhanced energy release rates and reduced sensitivity to unintentional detonation . The following results have been...Mechanics of Advanced Energetic Materials Relevant to Detonation Prediction The views, opinions and/or findings contained in this report are those of the...modeling, molecular simulations, detonation prediction REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 10. SPONSOR/MONITOR’S

  15. The role of advanced reactive surface area characterization in improving predictions of mineral reaction rates

    NASA Astrophysics Data System (ADS)

    Beckingham, L. E.; Zhang, S.; Mitnick, E.; Cole, D. R.; Yang, L.; Anovitz, L. M.; Sheets, J.; Swift, A.; Kneafsey, T. J.; Landrot, G.; Mito, S.; Xue, Z.; Steefel, C. I.; DePaolo, D. J.; Ajo Franklin, J. B.

    2014-12-01

    Geologic sequestration of CO2 in deep sedimentary formations is a promising means of mitigating carbon emissions from coal-fired power plants but the long-term fate of injected CO2 is challenging to predict. Reactive transport models are used to gain insight over long times but rely on laboratory determined mineral reaction rates that have been difficult to extrapolate to field systems. This, in part, is due to a lack of understanding of mineral reactive surface area. Many models use an arbitrary approximation of reactive surface area, applying orders of magnitude scaling factors to measured BET or geometric surface areas. Recently, a few more sophisticated approaches have used 2D and 3D image analyses to determine mineral-specific reactive surface areas that account for the accessibility of minerals. However, the ability of these advanced surface area estimates to improve predictions of mineral reaction rates has yet to be determined. In this study, we fuse X-ray microCT, SEM QEMSCAN, XRD, SANS, and SEM-FIB analysis to determine mineral-specific accessible reactive surface areas for a core sample from the Nagaoka pilot CO2 injection site (Japan). This sample is primarily quartz, plagioclase, smectite, K-feldspar, and pyroxene. SEM imaging shows abundant smectite cement and grain coatings that decrease the fluid accessibility of other minerals. However, analysis of FIB-SEM images reveals that smectite nano-pores are well connected such that access to underlying minerals is not occluded by smectite coatings. Mineral-specific accessible surfaces are determined, accounting for the connectivity of the pore space with and without connected smectite nano-pores. The large-scale impact of variations in accessibility and dissolution rates are then determined through continuum scale modeling using grid-cell specific information on accessible surface areas. This approach will be compared with a traditional continuum scale model using mineral abundances and common surface area

  16. Carbon emissions from deforestation in the Brazilian Amazon region predicted from satellite data and ecosystem modeling

    NASA Astrophysics Data System (ADS)

    Potter, C.; Klooster, S.; Genovese, V.

    2009-03-01

    A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2002. The NASA-CASA (Carnegie Ames Stanford Approach) model estimates of annual forest production were used as the basis to generate a prediction for the standing pool of carbon in above-ground biomass (AGB; g C m-2) for forested areas of the Brazilian Amazon region. Plot-level measurements of the residence time of carbon in wood in Amazon forest from Malhi et al. (2006) were interpolated by inverse distance weighting algorithms and used with CASA to generate a new regional map of AGB. Data from the Brazilian PRODES (Estimativa do Desflorestamento da Amazônia) project were used to map deforested areas. Results show that net primary production (NPP) sinks for carbon are highest across the eastern and northern Amazon areas, whereas deforestation sources of CO2 flux from decomposition of residual woody debris are more rapid and less seasonal in the central Amazon than in the eastern and southern areas. Increased woody debris from past deforestation events was predicted to alter the net ecosystem carbon balance of the Amazon region to generate annual CO2 source fluxes at least two times higher than previously predicted by CASA modeling studies. Variations in climate, land cover, and forest burning were predicted to release carbon at rates of 0.5 to 1 Pg C yr-1 from the Brazilian Amazon. When direct carbon emissions from forest burning of between 0.2 and 0.6-1 in the Legal Amazon are overlooked in regional budgets, the year-to-year variations in this net biome flux may appear to be large, whereas our model results implies net biome fluxes had actually been relatively consistent from year to year during the period 2000-2002.

  17. 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

  18. 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.

  19. 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.

  20. Role of salvage radiotherapy for regional lymph node recurrence after radical surgery in advanced gastric cancer

    PubMed Central

    Kim, Byoung Hyuck; Kim, Jae-Sung; Kim, Hyung-Ho; Park, Do Joong

    2013-01-01

    Purpose To evaluate the role of salvage radiotherapy (RT) for the treatment of regional lymph node recurrence (RLNR) after radical surgery in advanced gastric cancer. Materials and Methods We retrospectively analyzed medical records of 26 patients who underwent salvage treatment after diagnosis of RLNR between 2006 and 2011. Patients with peritoneal seeding or distant metastasis were excluded. Eighteen patients received RT with or without chemotherapy and the other 8 did chemotherapy only without RT. A three-dimensional conformal RT was performed with median dose of 56 Gy (range, 44 to 60 Gy). Sixteen patients had fluoropyrimidine-based chemotherapy, 5 did taxane-based chemotherapy, and irinotecan was applied in 4. Results With a median follow-up of 20 months (range, 5 to 57 months), median overall survival (OS) and progression-free survival (PFS) after diagnosis of RLNR were 29 months and 12 months in the entire patients, respectively. Radiotherapy (p = 0.007) and disease-free interval (p = 0.033) were statistically significant factors for OS in multivariate analysis. Median OS was 36 months in patients who received RT and 16 months in those who did not. Furthermore, delivery of RT (p < 0.001), complete remission after salvage treatment (p = 0.040) and performance status (p = 0.023) were associated with a significantly better PFS. Gastrointestinal toxicities from RT were mild in most patients. Conclusion Salvage RT combined with systemic chemotherapy may be an effective treatment managing RLNR from advanced gastric cancer. PMID:24137560

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. Regional scale high resolution δ18O prediction in precipitation using MODIS EVI.

    PubMed

    Chan, Wei-Ping; Yuan, Hsiao-Wei; 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 δ(18)O in precipitation at the regional scale. Using a structural equation model, we show that the EVI and precipitated δ(18)O are highly correlated and thus the EVI is a good predictor of precipitated δ(18)O. We then test the predictability of our EVI-δ(18)O model and demonstrate that our approach can provide high accuracy with fine spatial (250×250 m) and temporal (16 days) scale δ(18)O predictions (annual and monthly predictabilities [r] are 0.96 and 0.80, respectively). We conclude the merging of the EVI and δ(18)O in precipitation can greatly extend the spatial and temporal data availability and thus enhance the applicability for both the EVI and water isoscape.

  6. 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.

  7. 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.

  8. 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.

  9. Soft tissue profile changes following mandibular advancement surgery: predictability and long-term outcome.

    PubMed

    Mobarak, K A; Espeland, L; Krogstad, O; Lyberg, T

    2001-04-01

    The objectives of this cephalometric study were to assess long-term changes in the soft tissue profile following mandibular advancement surgery and to investigate the relationship between soft tissue and hard tissue movements. The sample consisted of 61 patients treated consecutively for mandibular retrognathism with orthodontic therapy combined with bilateral sagittal split osteotomy and rigid fixation. Lateral cephalograms were taken on 6 occasions: immediately before surgery, immediately after surgery, 2 and 6 months after surgery, and 1 and 3 years after surgery. Postsurgical changes in the upper and the lower lips and the mentolabial fold were more pronounced among low-angle cases compared with high-angle cases. In accordance with other studies, the soft tissue chin and the mentolabial fold were generally found to follow their underlying skeletal structures in a 1:1 ratio. Because of the strong influence skeletal relapse has on soft tissue profile changes, alternative ratios of soft tissue-to-hard tissue movement that accounted for mean relapse were also generated. It is suggested that if a more realistic long-term prediction of the postsurgical soft tissue profile is desirable, then ratios incorporating mean relapse should be used rather than estimates based on a 1:1 relationship.

  10. 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

  11. 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...

  12. A risk score for the prediction of advanced age-related macular degeneration: Development and validation in 2 prospective cohorts

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We aimed to develop an eye specific model which used readily available information to predict risk for advanced age-related macular degeneration (AMD). We used the Age-Related Eye Disease Study (AREDS) as our training dataset, which consisted of the 4,507 participants (contributing 1,185 affected v...

  13. A finite Reynolds number approach for the prediction of boundary layer receptivity in localized regions

    NASA Technical Reports Server (NTRS)

    Choudhari, Meelan; Street, Craig L.

    1991-01-01

    Previous theoretical work on the boundary layer receptivity problem has utilized large Reynolds number asymptotic theories, thus being limited to a narrow part of the frequency - Reynolds number domain. An alternative approach is presented for the prediction of localized instability generation which has a general applicability, and also accounts for finite Reynolds number effects. This approach is illustrated for the case of Tollmien-Schlichting wave generation in a Blasius boundary layer due to the interaction of a free stream acoustic wave with a region of short scale variation in the surface boundary condition. The specific types of wall inhomogeneities studied are: regions of short scale variations in wall suction, wall admittance, and wall geometry (roughness). Extensive comparison is made between the results of the finite Reynolds number approach and previous asymptotic predictions, which also suggests an alternative way of using the latter at Reynolds numbers of interest in practice.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

  19. 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).

  20. Predicting natural streamflows in regulated snowmelt-driven watersheds using regionalization methods

    NASA Astrophysics Data System (ADS)

    Kim, D.; Kaluarachchi, J.

    2013-07-01

    Predicting streamflows in snow-fed watersheds in the Western United States is important for water allocation. Since many of these watersheds are heavily regulated through canal networks and reservoirs, predicting expected natural flows and therefore water availability under limited data is always a challenge. This study investigates the applicability of the flow duration curve (FDC) method for predicting natural flows in gauged and ungauged snow-fed watersheds. Point snow observations, air temperature, precipitation, and snow water equivalent, are used to simulate snowmelt process with SNOW-17 model and extended to streamflow generation by a FDC method with modified current precipitation index. For regulated (ungauged) watersheds, a parametric regional FDC method is applied to reconstruct natural flow. For comparison, a simplified Tank Model is used as well. The proximity regionalization method is used to generate streamflow using the Tank Model in ungauged watersheds. The results show that the FDC method can produce acceptable natural flow estimates in both gauged and ungauged watersheds under data limited conditions. The performance of the FDC method is better in watersheds with relatively low evapotranspiration (ET). Multiple donor data sets including current precipitation index are recommended to reduce uncertainty of the regional FDC method for ungauged watersheds. In spite of its simplicity, the FDC method can perform better than the Tank Model under minimal data availability.

  1. 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.

  2. 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

    2016-09-07

    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.

  3. 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.

  4. Surface Tension Prediction Using Characteristics of the Density Profile Through the Interfacial Region

    NASA Astrophysics Data System (ADS)

    Wemhoff, A. P.; Carey, V. P.

    2006-03-01

    A simple surface tension estimation technique is described that is based solely upon the characteristics of the density profile in the interfacial region and the physical properties of the molecules in the fluid. This method, denoted free energy integration (FEI), links interfacial tension to known interfacial region density profile characteristics obtained via experiment or simulation. The general FEI methodology is provided here, and specific relations are derived for a methodology that incorporates the Redlich-Kwong fluid model. The Redlich-Kwong based FEI method was used to predict interfacial tension using the density profile characteristics of molecular dynamics (MD) simulations of argon using the Lennard-Jones potential, diatomic nitrogen using the two-center Lennard-Jones potential, and water using the extended simple point-charge (SPC/E) model. These results for argon compare favorably to values calculated by the traditional virial approach, known values from the literature using the finite-size scaling technique, and ASHRAE recommended values. In addition, the FEI predictions agree well with ASHRAE values and predictions using the virial method for nitrogen for the simulated range of temperatures in this study, and for water for reduced temperatures above 0.7. In addition, the FEI method results agree well with other established theoretical techniques for predictions of the surface tension of sulfur hexafluoride close to the critical point.

  5. A global model of avian influenza prediction in wild birds: the importance of northern regions.

    PubMed

    Herrick, Keiko A; Huettmann, Falk; Lindgren, Michael A

    2013-06-13

    Avian influenza virus (AIV) is enzootic to wild birds, which are its natural reservoir. The virus exhibits a large degree of genetic diversity and most of the isolated strains are of low pathogenicity to poultry. Although AIV is nearly ubiquitous in wild bird populations, highly pathogenic H5N1 subtypes in poultry have been the focus of most modeling efforts. To better understand viral ecology of AIV, a predictive model should 1) include wild birds, 2) include all isolated subtypes, and 3) cover the host's natural range, unbounded by artificial country borders. As of this writing, there are few large-scale predictive models of AIV in wild birds. We used the Random Forests algorithm, an ensemble data-mining machine-learning method, to develop a global-scale predictive map of AIV, identify important predictors, and describe the environmental niche of AIV in wild bird populations. The model has an accuracy of 0.79 and identified northern areas as having the highest relative predicted risk of outbreak. The primary niche was described as regions of low annual rainfall and low temperatures. This study is the first global-scale model of low-pathogenicity avian influenza in wild birds and underscores the importance of largely unstudied northern regions in the persistence of AIV.

  6. 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.

  7. 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

  8. Advancing Ensemble Streamflow Prediction with Stochastic Meteorological Forcings for Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Caraway, N.; Wood, A. W.; Rajagopalan, B.; Zagona, E. A.; Daugherty, L.

    2012-12-01

    River Forecast Centers of National Weather Service (NWS) produce seasonal streamflow forecasts via a method called Ensemble Streamflow Prediction (ESP). NWS ESP forces the temperature index Snow17 and Sacramento Soil Moisture Accounting model (SAC-SMA) models with historical weather sequences for the forecasting period, starting from models' current watershed initial conditions, to produce ensemble streamflow forecasts. There are two major drawbacks of this method: (i) the ensembles are limited to the length of historical, limiting ensemble variability and (ii) incorporating seasonal climate forecasts (e.g., El Nino Southern Oscillation) relies on adjustment or weighting of ESP streamflow sequences. These drawbacks motivate the research presented here, which has two components: (i) a multi-site stochastic weather generator and (ii) generation of ensemble weather forecast inputs to the NWS model to produce ensemble streamflow forecasts. We enhanced the K-nearest neighbor bootstrap based stochastic generator include: (i) clustering the forecast locations into climatologically homogeneous regions to better capture the spatial heterogeneity and, (ii) conditioning the weather forecasts on a probabilistic seasonal climate forecast. This multi-site stochastic weather generator runs in R and the NWS models run within the new Community Hydrologic Prediction System, a forecasting sequence we label WG-ESP. The WG-ESP framework was applied to generate ensemble forecasts of spring season (April-July) streamflow in the San Juan River Basin, one of the major tributaries of the Colorado River, for the period 1981-2010. The hydrologic model requires daily weather sequences at 66 locations in the basin. The enhanced daily weather generator sequences captured the distributional properties and spatial dependence of the climatological ESP, and also generated weather sequences consistent with conditioning on seasonal climate forecasts. Spring season ensemble forecast lead times from

  9. Industrial emission in a coastal region of India: Prediction of impact on air environment

    SciTech Connect

    Gargava, P.; Aggarwal, A.L.

    1996-08-01

    Industrial air pollution has assumed a menacing proportion in the developing countries, including India. Its control should not be delayed any more. The economic reforms and subsequent industrial development and growing urbanization will aggregate the problem in coming years. Poor land use planning for industrial development often results in the high concentrations of air pollutants in urban centers. This paper discusses the impact of industrial activities on the air environment in a coastal region of India, as a case study. A Gaussian-Plume atmospheric dispersion algorithm has been used to predict the ground level concentration of major pollutants released into the atmosphere due to industrial activities in the region. Typical diurnal variation of Pasquill`s stability and mixing height over the Cochin Region were used. Ground level concentrations (CLC) of major pollutants were predicted from as many as 108 point sources from 15 industries located in the region. A roll-back approach was then applied to compute the degree of emission control required to keep pollution level within the permissible limits of ambient air quality. 10 refs., 6 figs.

  10. 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

  11. Interleukin-22 predicts severity and death in advanced liver cirrhosis: a prospective cohort study

    PubMed Central

    2012-01-01

    Background Interleukin-22 (IL-22), recently identified as a crucial parameter of pathology in experimental liver damage, may determine survival in clinical end-stage liver disease. Systematic analysis of serum IL-22 in relation to morbidity and mortality of patients with advanced liver cirrhosis has not been performed so far. Methods This is a prospective cohort study including 120 liver cirrhosis patients and 40 healthy donors to analyze systemic levels of IL-22 in relation to survival and hepatic complications. Results A total of 71% of patients displayed liver cirrhosis-related complications at study inclusion. A total of 23% of the patients died during a mean follow-up of 196 ± 165 days. Systemic IL-22 was detectable in 74% of patients but only in 10% of healthy donors (P < 0.001). Elevated levels of IL-22 were associated with ascites (P = 0.006), hepatorenal syndrome (P < 0.0001), and spontaneous bacterial peritonitis (P = 0.001). Patients with elevated IL-22 (>18 pg/ml, n = 57) showed significantly reduced survival compared to patients with regular (≤18 pg/ml) levels of IL-22 (321 days versus 526 days, P = 0.003). Other factors associated with reduced overall survival were high CRP (≥2.9 mg/dl, P = 0.005, hazard ratio (HR) 0.314, confidence interval (CI) (0.141 to 0.702)), elevated serum creatinine (P = 0.05, HR 0.453, CI (0.203 to 1.012)), presence of liver-related complications (P = 0.028, HR 0.258, CI (0.077 to 0.862)), model of end stage liver disease (MELD) score ≥20 (P = 0.017, HR 0.364, CI (0.159 to 0.835)) and age (P = 0.011, HR 0.955, CI (0.922 to 0.989)). Adjusted multivariate Cox proportional-hazards analysis identified elevated systemic IL-22 levels as independent predictors of reduced survival (P = 0.007, HR 0.218, CI (0.072 to 0.662)). Conclusions In patients with liver cirrhosis, elevated systemic IL-22 levels are predictive for reduced survival independently from age, liver-related complications, CRP, creatinine and the MELD score. Thus

  12. 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

  13. Numerical modeling of the flow in intracranial aneurysms: prediction of regions prone to thrombus formation.

    PubMed

    Rayz, V L; Boussel, L; Lawton, M T; Acevedo-Bolton, G; Ge, L; Young, W L; Higashida, R T; Saloner, D

    2008-11-01

    The deposition of intralumenal thrombus in intracranial aneurysms adds a risk of thrombo-embolism over and above that posed by mass effect and rupture. In addition to biochemical factors, hemodynamic factors that are governed by lumenal geometry and blood flow rates likely play an important role in the thrombus formation and deposition process. In this study, patient-specific computational fluid dynamics (CFD) models of blood flow were constructed from MRA data for three patients who had fusiform basilar aneurysms that were thrombus free and then proceeded to develop intralumenal thrombus. In order to determine whether features of the flow fields could suggest which regions had an elevated potential for thrombus deposition, the flow was modeled in the baseline, thrombus-free geometries. Pulsatile flow simulations were carried out using patient-specific inlet flow conditions measured with MR velocimetry. Newtonian and non-Newtonian blood behavior was considered. A strong similarity was found between the intra-aneurysmal regions with CFD-predicted slow, recirculating flows and the regions of thrombus deposition observed in vivo in the follow-up MR studies. In two cases with larger aneurysms, the agreement between the low velocity zones and clotted-off regions improved when non-Newtonian blood behavior was taken into account. A similarity was also found between the calculated low shear stress regions and the regions that were later observed to clot.

  14. 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.

  15. 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

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

    PubMed Central

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

    1994-01-01

    To test the reliability of linkage-disequilibrium analysis for gene mapping, we 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 -.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. We 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. PMID:8178829

  17. 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.

  18. Investigation into regional climate variability using tree-ring reconstruction, climate diagnostics and prediction

    NASA Astrophysics Data System (ADS)

    Barandiaran, Daniel A.

    This document is a summary of research conducted to develop and apply climate analysis tools toward a better understanding of the past and future of hydroclimate variability in the state of Utah. Two pilot studies developed data management and climate analysis tools subsequently applied to our region of interest. The first investigated the role of natural atmospheric forcing in the inter-annual variability of precipitation of the Sahel region in Africa, and found a previously undocumented link with the East Atlantic mode, which explains 29% of variance in regional precipitation. An analysis of output from an operational seasonal climate forecast model revealed a failure in the model to reproduce this linkage, thus highlighting a shortcoming in model performance. The second pilot study studied long-term trends in the strength of the Great Plains low-level jet, an driver of storm development in the region's wet spring season. Our analysis showed that since 1979 the low-level jet has strengthened as shifted the timing of peak activity, resulting in shifts both in time and location for peak precipitation, possibly the result of anthropogenic forcing. Our third study used a unique tree-ring dataset to create a reconstruction of April 1 snow water equivalent, an important measure of water supply in the Intermountain West, for the state of Utah to 1850. Analysis of the reconstruction shows the majority of snowpack variability occurs monotonically over the whole state at decadal to multidecadal frequencies. The final study evaluated decadal prediction performance of climate models participating in the Coupled Model Intercomparison Project 5. We found that the analyzed models exhibit modest skill in prediction of the Pacific Decadal Oscillation and better skill in prediction of global temperature trends post 1960.

  19. Advancing the predictive capability for pedestal structure through experiment and modeling

    NASA Astrophysics Data System (ADS)

    Hughes, Jerry

    2012-10-01

    Prospects for predictive capability of the edge pedestal in magnetic fusion devices have been dramatically enhanced due to recent research, which was conducted jointly by the US experimental and theory communities. Studies on the C-Mod, DIII-D and NSTX devices have revealed common features, including an upper limit on pedestal pressure in ELMy H-mode determined by instability to peeling-ballooning modes (PBMs), and pedestal width which scales approximately as βpol^1/2. The width dependence is consistent with a pedestal regulated by kinetic ballooning modes (KBMs). Signatures of KBMs have been actively sought both in experimental fluctuation measurements and in gyrokinetic simulations of the pedestal, with encouraging results. Studies of the temporal evolution of the pedestal during the ELM cycle reveal a tendency for the pressure gradient to saturate in advance of the ELM, with a steady growth in the pedestal width occurring prior to the ELM crash, which further supports a model for KBMs and PBMs working together to set the pedestal structure. Such a model, EPED, reproduces the pedestal height and width to better than 20% accuracy on existing devices over a range of more than 20 in pedestal pressure. Additional transport processes are assessed for their impact on pedestal structure, in particular the relative variation of the temperature and density pedestals due, for example, to differences in edge neutral sources. Such differences are observed in dimensionlessly matched discharges on C-Mod and DIII-D, despite their having similar calculated MHD stability and similar edge fluctuations. In certain high performance discharges, such as EDA H-mode, QH-mode and I-mode, pedestal relaxation is accomplished by continuous edge fluctuations, avoiding peeling-ballooning instabilities and associated ELMs. Progress in understanding these regimes will be reported.

  20. Regional Seismic Travel-Time Prediction, Uncertainty, and Location Improvement in Western Eurasia

    NASA Astrophysics Data System (ADS)

    Flanagan, M. P.; Myers, S. C.

    2004-12-01

    We investigate our ability to improve regional travel-time prediction and seismic event location using an a priori, three-dimensional velocity model of Western Eurasia and North Africa: WENA1.0 [Pasyanos et al., 2004]. Our objective is to improve the accuracy of seismic location estimates and calculate representative location uncertainty estimates. As we focus on the geographic region of Western Eurasia, the Middle East, and North Africa, we develop, test, and validate 3D model-based travel-time prediction models for 30 stations in the study region. Three principal results are presented. First, the 3D WENA1.0 velocity model improves travel-time prediction over the iasp91 model, as measured by variance reduction, for regional Pg, Pn, and P phases recorded at the 30 stations. Second, a distance-dependent uncertainty model is developed and tested for the WENA1.0 model. Third, an end-to-end validation test based on 500 event relocations demonstrates improved location performance over the 1-dimensional iasp91 model. Validation of the 3D model is based on a comparison of approximately 11,000 Pg, Pn, and P travel-time predictions and empirical observations from ground truth (GT) events. Ray coverage for the validation dataset is chosen to provide representative, regional-distance sampling across Eurasia and North Africa. The WENA1.0 model markedly improves travel-time predictions for most stations with an average variance reduction of 25% for all ray paths. We find that improvement is station dependent, with some stations benefiting greatly from WENA1.0 predictions (52% at APA, 33% at BKR, and 32% at NIL), some stations showing moderate improvement (12% at KEV, 14% at BOM, and 12% at TAM), some benefiting only slightly (6% at MOX, and 4% at SVE), and some are degraded (-6% at MLR and -18% at QUE). We further test WENA1.0 by comparing location accuracy with results obtained using the iasp91 model. Again, relocation of these events is dependent on ray paths that evenly

  1. 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

  2. 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

  3. Regional prediction of flow-duration curves using a three-dimensional kriging

    NASA Astrophysics Data System (ADS)

    Castellarin, Attilio

    2014-05-01

    The relationship between magnitude and frequency of daily streamflows over a number of years for a given basin is often termed long-term flow-duration curve (FDC). This analysis addresses the problem of predicting FDCs in ungauged basins by means of a three-dimensional (3D) kriging interpolation of empirical FDCs. A three-dimensional xyz space is defined to perform the interpolation, where x and y are functions of physiographic and climatic catchment descriptors, while z represents the streamflow duration in terms of standard-normal variate. The 3D interpolation technique is applied to several catchments located in two broad geographical regions of Northern (Alpine catchments) and Central (Apenninic catchments) Italy, for which several geomorphological and climatic descriptors are available. An extensive cross-validation procedure is used to quantify the accuracy of the proposed technique in both case studies, and to compare it to traditional regionalization procedures. The cross-validation points out that 3D kriging is a reliable and robust approach, which performs as well as or better than traditional regional models. In particular the approach significantly outperforms conventional approaches for the prediction of low-flows (i.e. streamflows associated with high durations) in ungauged basins.

  4. 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

  5. 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.

  6. Regional estimation of design precipitation totals by simple scaling for flood risk prediction in Slovakia

    NASA Astrophysics Data System (ADS)

    Bara, Marta; Kohnova, Silvia; Gaal, Ladislav; Szolgay, Jan; Hlavcova, Kamila

    2010-05-01

    Design values of extreme rainfall are of very great importance in engineering hydrology, such as input data for hydrological modeling, for the prediction of flood events, or for planning and design in water resources management. Precipitation data with sufficient temporal resolution necessary for estimation of design precipitation totals are available from a limited number of raingauges with continuous recording. One of the advantages of the simple scaling method is, that it allows estimating of design precipitation totals for required durations and recurrence intervals using daily data, available from a denser network of non-recording raingauges. In this study the possibility of using the simple scaling method for regional estimation of design short-term precipitation totals for flood risk forecasting was tested. The analysis includes precipitation data from 56 raingauge stations from the whole territory of Slovakia, distributed into three homogeneous regions based on regionalization of the daily maximum precipitation totals in the warm season (April-September). The regional dimensionless growth curve of daily precipitation maxima was derived in the regions, and the local T-year quantiles were estimated by the index value method. In each region three verification stations were selected which were treated as ungauged sites. It was supposed that the only information on the precipitation regime at the verification stations was the index value. Using the regionally averaged scaling exponent, the IDF curves were estimated by downscaling the design daily precipitation totals. The IDF curves were finally compared with those assessed locally in previous studies and their application in engineering practice was discussed.

  7. Regional brain activity change predicts responsiveness to treatment for stuttering in adults.

    PubMed

    Ingham, Roger J; Wang, Yuedong; Ingham, Janis C; Bothe, Anne K; Grafton, Scott T

    2013-12-01

    Developmental stuttering is known to be associated with aberrant brain activity, but there is no evidence that this knowledge has benefited stuttering treatment. This study investigated whether brain activity could predict progress during stuttering treatment for 21 dextral adults who stutter (AWS). They received one of two treatment programs that included periodic H2(15)O PET scanning (during oral reading, monologue, and eyes-closed rest conditions). All participants successfully completed an initial treatment phase and then entered a phase designed to transfer treatment gains; 9/21 failed to complete this latter phase. The 12 pass and 9 fail participants were similar on speech and neural system variables before treatment, and similar in speech performance after the initial phase of their treatment. At the end of the initial treatment phase, however, decreased activation within a single region, L. putamen, in all 3 scanning conditions was highly predictive of successful treatment progress.

  8. 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.

  9. 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

  10. Prediction of Bulk Density of Soils in the Loess Plateau Region of China

    NASA Astrophysics Data System (ADS)

    Wang, Yunqiang; Shao, Ming'an; Liu, Zhipeng; Zhang, Chencheng

    2013-08-01

    Soil bulk density (BD) is a key soil physical property that may affect the transport of water and solutes and is essential to estimate soil carbon/nutrients reserves. However, BD data are often lacking in soil databases due to the challenge of directly measuring BD, which is considered to be labor intensive, time consuming, and expensive especially for the lower layers of deep soils such as those of the Chinese Loess Plateau region. We determined the factors that were closely correlated with BD at the regional scale and developed a robust pedotransfer function (PTF) for BD by measuring BD and potentially related soil and environmental factors at 748 selected sites across the Loess Plateau of China (620,000 km2) at which we collected undisturbed and disturbed soil samples from two soil layers (0-5 and 20-25 cm). Regional BD values were normally distributed and demonstrated weak spatial variation (CV = 12 %). Pearson's correlation and stepwise multiple linear regression analyses identified silt content, slope gradient (SG), soil organic carbon content (SOC), clay content, slope aspect (SA), and altitude as the factors that were closely correlated with BD and that explained 25.8, 6.3, 5.8, 1.4, 0.3, and 0.3 % of the BD variation, respectively. Based on these closely correlated variables, a reasonably robust PTF was developed for BD using multiple linear regression, which performed equally with the artificial neural network method in the current study. The inclusion of topographic factors significantly improved the predictive capability of the BD PTF and in which SG was an important input variable that could be used in place of SA and altitude without compromising its capability for predicting BD. Thus, the developed PTF with only four input variables (clay, silt, SOC, SG), including their common transformations and interactive terms, predicted BD with reasonable accuracy and is thus useful for most applications on the Loess Plateau of China. More attention should be

  11. The predictive value of MRI in detecting thyroid gland invasion in patients with advanced laryngeal or hypopharyngeal carcinoma.

    PubMed

    Lin, Peiliang; Huang, Xiaoming; Zheng, Chushan; Cai, Qian; Guan, Zhong; Liang, Faya; Zheng, Yiqing

    2017-01-01

    The aim of this study was to evaluate the predictive value of magnetic resonance imaging (MRI) in detecting thyroid gland invasion (TGI) in patients with advanced laryngeal or hypopharyngeal carcinoma. In a retrospective chart review, 41 patients with advanced laryngeal or hypopharyngeal carcinoma underwent MRI scan before total laryngectomy and ipsilateral or bilateral thyroidectomy during the past 5 years. The MRI findings were compared with the postoperative pathological results. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Among the 41 patients, 3 had thyroid gland invasion in postoperative pathological results. MRI correctly predicted the absence of TGI in 37 of 38 patients and TGI in all 3 patients. The sensitivity, specificity, PPV, and NPV of MRI were 100.0, 97.4, 75.0, and 100 %, respectively, with the diagnostic accuracy of 97.6 %. In consideration of the high negative predictive value of MRI, it may help surgeons selectively preserve thyroid gland in total laryngectomy and reduce the incidence of hypothyroidism and hypoparathyroidism postoperatively.

  12. 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

  13. Prediction of helicopter rotor discrete frequency noise: A computer program incorporating realistic blade motions and advanced acoustic formulation

    NASA Technical Reports Server (NTRS)

    Brentner, K. S.

    1986-01-01

    A computer program has been developed at the Langley Research Center to predict the discrete frequency noise of conventional and advanced helicopter rotors. The program, called WOPWOP, uses the most advanced subsonic formulation of Farassat that is less sensitive to errors and is valid for nearly all helicopter rotor geometries and flight conditions. A brief derivation of the acoustic formulation is presented along with a discussion of the numerical implementation of the formulation. The computer program uses realistic helicopter blade motion and aerodynamic loadings, input by the user, for noise calculation in the time domain. A detailed definition of all the input variables, default values, and output data is included. A comparison with experimental data shows good agreement between prediction and experiment; however, accurate aerodynamic loading is needed.

  14. Curriculum development for an advanced regional anesthesia education program: one institution's experience from apprenticeship to comprehensive teaching.

    PubMed

    Ouanes, Jean-Pierre P; Schwengel, Deborah; Mathur, Vineesh; Ahmed, Omar I; Hanna, Marie N

    2014-02-01

    Results of recent attitude survey studies suggest that most practicing physicians are inadequately treating postoperative pain. Residents in anesthesia are confident in performing lumbar epidural and spinal anesthesia, but many are not confident in performing the blocks with which they have the least exposure. Changes need to be made in the training processes to a comprehensive model that prepares residents to perform a wider array of blocks in postgraduate practice. Here, we describe one institution's approach to creating a standardized, advanced regional anesthesia curriculum for residents that follows the six core competencies of the ACGME. Residents received training in anatomy dissection, ultrasound-guided regional anesthesia, traditional nerve stimulation techniques, problem-based learning and simulation sessions, oral board presentation sessions, and journal club sessions. Residents kept a detailed log for their use of peripheral nerve block procedures. We have now redesigned and implemented an advanced regional anesthesia program within our institution to provide residents with experience in regional anesthesia at a competent level. Resident's knowledge in regional anesthesia did improve after the first year of implementation as reflected in improvements between the pre- and post-tests. As the advanced regional anesthesia education program continues to improve, we hope to demonstrate levels of validity, reliability, and usability by other programs.

  15. Predicting Violence Among Forensic-Correctional Populations: The Past 2 Decades of Advancements and Future Endeavors

    ERIC Educational Resources Information Center

    Loza, Wagdy; Dhaliwal, Gurmeet K.

    2005-01-01

    Research on violence prediction during the past 2 decades has evolved appreciably in terms of depicting determinants of violence and developing psychometrically sound actuarial measures to predict the probability of future violent behavior. This article provides a brief synopsis of information on predicting violence gained in the past 2 decades,…

  16. 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.

  17. 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.

  18. Delineation of homogenous regions using hydrological variables predicted by projection pursuit regression

    NASA Astrophysics Data System (ADS)

    Durocher, Martin; Chebana, Fateh; Ouarda, Taha B. M. J.

    2016-11-01

    This study investigates the utilization of hydrological information in regional flood frequency analysis (RFFA) to enforce desired properties for a group of gauged stations. Neighbourhoods are particular types of regions that are centred on target locations. A challenge for using neighbourhoods in RFFA is that hydrological information is not available at target locations and cannot be completely replaced by the available physiographical information. Instead of using the available physiographic characteristics to define the centre of a target location, this study proposes to introduce estimates of reference hydrological variables to ensure a better homogeneity. These reference variables represent nonlinear relations with the site characteristics obtained by projection pursuit regression, a nonparametric regression method. The resulting neighbourhoods are investigated in combination with commonly used regional models: the index-flood model and regression-based models. The complete approach is illustrated in a real-world case study with gauged sites from the southern part of the province of Québec, Canada, and is compared with the traditional approaches such as region of influence and canonical correlation analysis. The evaluation focuses on the neighbourhood properties as well as prediction performances, with special attention devoted to problematic stations. Results show clear improvements in neighbourhood definitions and quantile estimates.

  19. Distribution of Misfolded Prion Protein Seeding Activity Alone Does Not Predict Regions of Neurodegeneration

    PubMed Central

    Alibhai, James; Blanco, Richard A.; Barria, Marcelo A.; Piccardo, Pedro; Caughey, Byron; Perry, V. Hugh; Freeman, Tom C.; Manson, Jean C.

    2016-01-01

    Protein misfolding is common across many neurodegenerative diseases, with misfolded proteins acting as seeds for "prion-like" conversion of normally folded protein to abnormal conformations. A central hypothesis is that misfolded protein accumulation, spread, and distribution are restricted to specific neuronal populations of the central nervous system and thus predict regions of neurodegeneration. We examined this hypothesis using a highly sensitive assay system for detection of misfolded protein seeds in a murine model of prion disease. Misfolded prion protein (PrP) seeds were observed widespread throughout the brain, accumulating in all brain regions examined irrespective of neurodegeneration. Importantly, neither time of exposure nor amount of misfolded protein seeds present determined regions of neurodegeneration. We further demonstrate two distinct microglia responses in prion-infected brains: a novel homeostatic response in all regions and an innate immune response restricted to sites of neurodegeneration. Therefore, accumulation of misfolded prion protein alone does not define targeting of neurodegeneration, which instead results only when misfolded prion protein accompanies a specific innate immune response. PMID:27880767

  20. 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

  1. 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.

  2. 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,…

  3. Early Prediction of Outcome in Advanced Head-and-Neck Cancer Based on Tumor Blood Volume Alterations During Therapy: A Prospective Study

    SciTech Connect

    Cao Yue Popovtzer, Aron; Li, Diana; Chepeha, Douglas B.; Moyer, Jeffrey S.; Prince, Mark E.; Worden, Francis; Teknos, Theodoros; Bradford, Carol; Mukherji, Suresh K.; Eisbruch, Avraham

    2008-12-01

    Purpose: To assess whether alterations in tumor blood volume (BV) and blood flow (BF) during the early course of chemo-radiotherapy (chemo-RT) for head-and-neck cancer (HNC) predict treatment outcome. Methods and Materials: Fourteen patients receiving concomitant chemo-RT for nonresectable, locally advanced HNC underwent dynamic contrast-enhanced (DCE) MRI scans before therapy and 2 weeks after initiation of chemo-RT. The BV and BF were quantified from DCE MRI. Preradiotherapy BV and BF, as well as their changes during RT, were evaluated separately in the primary gross tumor volume (GTV) and nodal GTV for association with outcomes. Results: At a median follow-up of 10 months (range, 5-27 months), 9 patients had local-regional controlled disease. One patient had regional failure, 3 had local failures, and 1 had local-regional failure. Reduction in tumor volume after 2 weeks of chemo-RT did not predict for local control. In contrast, the BV in the primary GTV after 2 weeks of chemo-RT was increased significantly in the local control patients compared with the local failure patients (p < 0.03). Conclusions: Our data suggest that an increase in available primary tumor blood for oxygen extraction during the early course of RT is associated with local control, thus yielding a predictor with potential to modify treatment. These findings require validation in larger studies.

  4. 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

  5. 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.

  6. Predicted complementarity determining regions of the T cell antigen receptor determine antigen specificity.

    PubMed Central

    Katayama, C D; Eidelman, F J; Duncan, A; Hooshmand, F; Hedrick, S M

    1995-01-01

    The antigen receptor on T cells (TCR) has been predicted to have a structure similar to a membrane-anchored form of an immunoglobulin F(ab) fragment. Virtually all of the conserved amino acids that are important for inter- and intramolecular interactions in the VH-VL pair are also conserved in the TCR V alpha and V beta chains. A molecular model of the TCR has been constructed by homology and we have used the information from this, as well as the earlier structural predictions of others, to study the basis for specificity. Specifically, regions of a TCR cloned from an antigen-specific T cell were stitched into the corresponding framework of a second TCR. Results indicate that the substitution of amino acid sequences corresponding to the complementarity determining regions (CDRs) of immunoglobulin can convey the specificity for antigen and major histocompatibility complex molecules. These data are consistent with a role, but not an exclusive role, for CDR3 in antigen peptide recognition. Images PMID:7534228

  7. Test-sites for earthquake prediction experiments within the Colli Albani region

    NASA Astrophysics Data System (ADS)

    Quattrocchi, F.; Calcara, M.

    In this paper we discuss some geochemical data gathered by discrete and continuous monitoring during the 1995-1996 period, carried out for earthquake prediction test-experiments throughout the Colli Albani quiescent volcano, seat of seismicity, selecting some gas discharge sites with peri-volcanic composition. In particular we stressed the results obtained at the continuous geochemical monitoring station (GMS I, BAR site), designed by ING for geochemical surveillance of seismic events. The 12/6/1995 (M=3.6-3.8) Roma earthquake together with the 3/11/1995 (M=3.1) Tivoli earthquake was the most energetic events within the Colli Albani - Roma area, after the beginning of the continuous monitoring (1991) up today: strict correlation between these seismic events and fluid geochemical anomalies in groundwater has been discovered (temperature, Eh, 222Rn, CO 2, NH 3). Separation at depth of a vapour phase, rich in reducing-acidic gases (CO 2, H 2S, etc...), from a hyper-saline brine, within the deep geothermal reservoir is hypothesised to explain the geochemical anomalies: probably the transtensional episodes accompanying the seismic sequences caused an increasing and/or triggering of the phase-separation process and fluid migration, on the regional scale of the Western sector of the Colli Albani, beyond the seismogenic depth (2-4 Km) up to surface. We draw the state of art of GMS II monitoring prototype and the selection criteria of test-sites for earthquake prediction experiments in the Colli Albani region.

  8. Groundwater arsenic contamination in Burkina Faso, West Africa: Predicting and verifying regions at risk.

    PubMed

    Bretzler, Anja; Lalanne, Franck; Nikiema, Julien; Podgorski, Joel; Pfenninger, Numa; Berg, Michael; Schirmer, Mario

    2017-04-15

    Arsenic contamination in groundwater from crystalline basement rocks in West Africa has only been documented in isolated areas and presents a serious health threat in a region already facing multiple challenges related to water quality and scarcity. We present a comprehensive dataset of arsenic concentrations from drinking water wells in rural Burkina Faso (n=1498), of which 14.6% are above 10μg/L. Included in this dataset are 269 new samples from regions where no published water quality data existed. We used multivariate logistic regression with arsenic measurements as calibration data and maps of geology and mineral deposits as independent predictor variables to create arsenic prediction models at concentration thresholds of 5, 10 and 50μg/L. These hazard maps delineate areas vulnerable to groundwater arsenic contamination in Burkina Faso. Bedrock composed of schists and volcanic rocks of the Birimian formation, potentially harbouring arsenic-containing sulphide minerals, has the highest probability of yielding groundwater arsenic concentrations >10μg/L. Combined with population density estimates, the arsenic prediction models indicate that ~560,000 people are potentially exposed to arsenic-contaminated groundwater in Burkina Faso. The same arsenic-bearing geological formations that are positive predictors for elevated arsenic concentrations in Burkina Faso also exist in neighbouring countries such as Mali, Ghana and Ivory Coast. This study's results are thus of transboundary relevance and can act as a trigger for targeted water quality surveys and mitigation efforts.

  9. Fog Prediction for Road Traffic Safety in a Coastal Desert Region

    NASA Astrophysics Data System (ADS)

    Bartok, Juraj; Bott, Andreas; Gera, Martin

    2012-12-01

    Modern weather prediction models use relatively high grid resolutions as well as sophisticated parametrization schemes for microphysical and other subgrid-scale atmospheric processes. Nonetheless, with these models it remains a difficult task to perform successful numerical fog forecasts since many factors controlling a particular fog event are not yet sufficiently simulated. Here we describe our efforts to create a mechanism that produces successful predictions of fog in the territory located on the north coast of the Arabian Peninsula. Our approach consists in the coupling of the one-dimensional PAFOG fog model with the three-dimensional WRF 3.0 (Weather Research and Forecast) modelling system. The proposed method allows us to construct an efficient operative road traffic warning system for the occurrence of fog in the investigated region. In total 84 historical situations were studied during the period 2008-2009. Moreover, results of operative day-by-day fog forecasting during January and February 2010 are presented. For the investigated arid and hot climate region the land-sea breeze circulation seems to be the major factor affecting the diurnal variations of the meteorological conditions, frequently resulting in the formation of fog.

  10. Study on multi-scale blending initial condition perturbations for a regional ensemble prediction system

    NASA Astrophysics Data System (ADS)

    Zhang, Hanbin; Chen, Jing; Zhi, Xiefei; Wang, Yi; Wang, Yanan

    2015-08-01

    An initial conditions (ICs) perturbation method was developed with the aim to improve an operational regional ensemble prediction system (REPS). Three issues were identified and investigated: (1) the impacts of perturbation scale on the ensemble spread and forecast skill of the REPS; (2) the scale characteristic of the IC perturbations of the REPS; and (3) whether the REPS's skill could be improved by adding large-scale information to the IC perturbations. Numerical experiments were conducted to reveal the impact of perturbation scale on the ensemble spread and forecast skill. The scales of IC perturbations from the REPS and an operational global ensemble prediction system (GEPS) were analyzed. A "multi-scale blending" (MSB) IC perturbation scheme was developed, and the main findings can be summarized as follows: The growth rates of the ensemble spread of the REPS are sensitive to the scale of the IC perturbations; the ensemble forecast skills can benefit from large-scale perturbations; the global ensemble IC perturbations exhibit more power at larger scales, while the regional ensemble IC perturbations contain more power at smaller scales; the MSB method can generate IC perturbations by combining the small-scale component from the REPS and the large-scale component from the GEPS; the energy norm growth of the MSB-generated perturbations can be appropriate at all forecast lead times; and the MSB-based REPS shows higher skill than the original system, as determined by ensemble forecast verification.

  11. Engagement of Temporal Lobe Regions Predicts Response to Educational Interventions in Adolescent Struggling Readers

    PubMed Central

    Rezaie, Roozbeh; Simos, Panagiotis G.; Fletcher, Jack M.; Cirino, Paul T.; Vaughn, Sharon; Papanicolaou, Andrew C.

    2012-01-01

    Brain activation profiles obtained using magnetoencephalography were compared between middle-school students experiencing reading difficulties and non-reading-impaired students during performance of a continuous printed word recognition task. Struggling readers underwent small–group remedial instruction, and students who showed significant gains in word reading efficiency at a one-year follow-up assessment were classified as Adequate Responders whereas those not demonstrating such gains as Inadequate Responders. At baseline, compared to Inadequate Responders, the activation profiles of Adequate Responders featured increased activity in the left middle, superior temporal, and ventral occipitotemporal regions, as well as in the right mesial temporal cortex. The degree of activity in these regions was a significant predictor of improvement in word reading efficiency beyond the prediction afforded by baseline reading accuracy or fluency measures. The engagement of brain areas that typically serve as key components of the brain circuit for reading may be an important factor in predicting response to intervention in older students who experience reading difficulties. PMID:21978010

  12. 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

  13. In Silico Prediction of Scaffold/Matrix Attachment Regions in Large Genomic Sequences

    PubMed Central

    Frisch, Matthias; Frech, Kornelie; Klingenhoff, Andreas; Cartharius, Kerstin; Liebich, Ines; Werner, Thomas

    2002-01-01

    Scaffold/matrix attachment regions (S/MARs) are essential regulatory DNA elements of eukaryotic cells. They are major determinants of locus control of gene expression and can shield gene expression from position effects. Experimental detection of S/MARs requires substantial effort and is not suitable for large-scale screening of genomic sequences. In silico prediction of S/MARs can provide a crucial first selection step to reduce the number of candidates. We used experimentally defined S/MAR sequences as the training set and generated a library of new S/MAR-associated, AT-rich patterns described as weight matrices. A new tool called SMARTest was developed that identifies potential S/MARs by performing a density analysis based on the S/MAR matrix library (http://www.genomatix.de/cgi-bin/smartest_pd/smartest.pl). S/MAR predictions were evaluated by using six genomic sequences from animal and plant for which S/MARs and non-S/MARs were experimentally mapped. SMARTest reached a sensitivity of 38% and a specificity of 68%. In contrast to previous algorithms, the SMARTest approach does not depend on the sequence context and is suitable to analyze long genomic sequences up to the size of whole chromosomes. To demonstrate the feasibility of large-scale S/MAR prediction, we analyzed the recently published chromosome 22 sequence and found 1198 S/MAR candidates. PMID:11827955

  14. [Feasibility Study of a One-Day Educational Program to Train Advance Care Planning Facilitators(ACPFs)in Regional Areas].

    PubMed

    Nishikawa, Mitsunori; Miura, Hisayuki; Oya, Sanae; Kato, Tomonari; Nagae, Hiroyuki; Osada, Yoshiyuki; Watanabe, Tetsuya; Matsuoka, Sachiko; Otsuka, Yasuro; Yamaguchi, Mie; Watanabe, Kazuko; Kito, Katsutoshi; Ooi, Hatsue; Suzuki, Naoko

    2016-12-01

    Promoting advance care planning in regional areas is important. Education For Implementing End-of-Life Discussion(EFIELD) is a two-day educational program for Advance Care Planning Facilitators(ACPFs)developed by the National Center for Geriatrics and Gerontology. Unfortunately, some trainers experience difficulties implementing the content of the program, and some trainees feel the program is too long for implementation in many regional areas. The purpose of the research is to clarify the feasibility of ACPFs education using a one-day program in regional areas. The methods involved documenting the process of a one-day program from implementation to evaluation from May of 2015 to March of 2016 and then evaluating the effectiveness of the program 3 months after the implementation using meeting minutes from 7 local hospitals. The results indicated a need for 5 steps from program implementation to evaluation as well as 5 categories for final evaluation. The most important finding is that E-FIELD challenged trainers to shorten and simplify their expressions in order to teach the content more efficiently. The second finding is that Group for Promoting Advance Care Planning & End Of Life Discussion in Chita(GACPEL) activities encouraged ACPimplementation within each hospital. The limitations of this research are related to small regional areas. In conclusion, a one-day regional ACPFs educational program is feasible.

  15. 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

  16. Predicting soil fumigant air concentrations under regional and diverse agronomic conditions.

    PubMed

    Cryer, Steven A

    2005-01-01

    SOFEA (SOil Fumigant Exposure Assessment system; Dow AgroSciences, Indianapolis, IN) is a new stochastic numerical modeling tool for evaluating and managing human inhalation exposure potential associated with the use of soil fumigants. SOFEA calculates fumigant concentrations in air arising from volatility losses from treated fields for large agricultural regions using multiple transient source terms (treated fields), geographical information systems (GIS) information, agronomic specific variables, user-specified buffer zones, and field reentry intervals. A modified version of the USEPA Industrial Source Complex Short Term model (ISCST3) is used for air dispersion calculations. Weather information, field size, application date, application rate, application type, soil incorporation depth, pesticide degradation rates in air, tarp presence, field retreatment, and other sensitive parameters are varied stochastically using Monte Carlo techniques to mimic region and crop specific agronomic practices. Regional land cover, elevation, and population information can be used to refine source placement (treated fields), dispersion calculations, and risk assessments. This paper describes the technical algorithms of SOFEA and offers comparisons of simulation predictions for the soil fumigant 1,3-dichloropropene (1,3-D) to actual regional air monitoring measurements from Kern, California. Comparison of simulation results to daily air monitoring observations is remarkable over the entire concentration distribution (average percent deviation of 44% and model efficiency of 0.98), especially considering numerous inputs such as meteorological conditions for SOFEA were unavailable and approximated by neighboring regions. Both current and anticipated and/or forecasted fumigant scenarios can be simulated using SOFEA to provide risk managers and product stewards the necessary information to make sound regulatory decisions regarding the use of soil fumigants in agriculture.

  17. Genome-Wide Analyses of Recombination Prone Regions Predict Role of DNA Structural Motif in Recombination

    PubMed Central

    Das, Swapan Kumar; Chowdhury, Shantanu

    2009-01-01

    HapMap findings reveal surprisingly asymmetric distribution of recombinogenic regions. Short recombinogenic regions (hotspots) are interspersed between large relatively non-recombinogenic regions. This raises the interesting possibility of DNA sequence and/or other cis- elements as determinants of recombination. We hypothesized the involvement of non-canonical sequences that can result in local non-B DNA structures and tested this using the G-quadruplex DNA as a model. G-quadruplex or G4 DNA is a unique form of four-stranded non-B DNA structure that engages certain G-rich sequences, presence of such motifs has been noted within telomeres. In support of this hypothesis, genome-wide computational analyses presented here reveal enrichment of potential G4 (PG4) DNA forming sequences within 25618 human hotspots relative to 9290 coldspots (p<0.0001). Furthermore, co-occurrence of PG4 DNA within several short sequence elements that are associated with recombinogenic regions was found to be significantly more than randomly expected. Interestingly, analyses of more than 50 DNA binding factors revealed that co-occurrence of PG4 DNA with target DNA binding sites of transcription factors c-Rel, NF-kappa B (p50 and p65) and Evi-1 was significantly enriched in recombination-prone regions. These observations support involvement of G4 DNA in recombination, predicting a functional model that is consistent with duplex-strand separation induced by formation of G4 motifs in supercoiled DNA and/or when assisted by other cellular factors. PMID:19198658

  18. 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.

  19. Kinematic earthquake source inversion and tsunami runup prediction with regional geophysical data

    NASA Astrophysics Data System (ADS)

    Melgar, D.; Bock, Y.

    2015-05-01

    Rapid near-source earthquake source modeling relying only on strong motion data is limited by instrumental offsets and magnitude saturation, adversely affecting subsequent tsunami prediction. Seismogeodetic displacement and velocity waveforms estimated from an optimal combination of high-rate GPS and strong motion data overcome these limitations. Supplementing land-based data with offshore wave measurements by seafloor pressure sensors and GPS-equipped buoys can further improve the image of the earthquake source and prediction of tsunami extent, inundation, and runup. We present a kinematic source model obtained from a retrospective real-time analysis of a heterogeneous data set for the 2011 Mw9.0 Tohoku-Oki, Japan, earthquake. Our model is consistent with conceptual models of subduction zones, exhibiting depth dependent behavior that is quantified through frequency domain analysis of slip rate functions. The stress drop distribution is found to be significantly more correlated with aftershock locations and mechanism types when off-shore data are included. The kinematic model parameters are then used as initial conditions in a fully nonlinear tsunami propagation analysis. Notably, we include the horizontal advection of steeply sloping bathymetric features. Comparison with post-event on-land survey measurements demonstrates that the tsunami's inundation and runup are predicted with considerable accuracy, only limited in scale by the resolution of available topography and bathymetry. We conclude that it is possible to produce credible and rapid, kinematic source models and tsunami predictions within minutes of earthquake onset time for near-source coastal regions most susceptible to loss of life and damage to critical infrastructure, regardless of earthquake magnitude.

  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. Prediction of regional flow duration curves: geostatistical techniques versus multivariate regression

    NASA Astrophysics Data System (ADS)

    Pugliese, A.; Farmer, W. H.; Castellarin, A.; Archfield, S. A.; Vogel, R. M.

    2015-12-01

    A period-of-record flow duration curve (FDC) represents the relationship between the magnitude and frequency of daily streamflows. Prediction of FDCs in ungauged basins is of great importance in those locations characterized by sparse, or more often missing, streamflow observations. We present a detailed comparison of two approaches which are capable of predicting an FDC in ungauged basins. An adaptation of the geostatistical method Top-kriging employs a linear weighted average of dimensionless empirical FDCs, standardized for a reference streamflow value. Weights are the result of the application of Top-kriging over a point index which, empirically, expresses the similarity between curves. Dimensional FDCs are then reconstructed developing a similar Top-kriging-based model capable of predicting the reference streamflow in the same sites. The second method is based on regional multiple linear regressions and is one of the most common method for prediction of FDCs in ungauged sites. Comparisons of these two methods are made at 182, mostly unregulated, river catchments in the southeastern U.S. using a three-fold cross-validation algorithm. Our results reveal that the two methods perform very similarly throughout flow-regimes, showing average Nash-Sutcliffe Efficiencies of 0.566 and 0.662 in natural scale, while 0.883 and 0.829 in log-transformed scale, for the geostatistical and the linear regression models, respectively. However, some complementarities are shown in the very low-flow regime, i.e. duration greater than 0.95, where the two models highlight different behaviors whether considering natural or log-transformed streamflows.

  2. 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

  3. Predicting depression based on dynamic regional connectivity: a windowed Granger causality analysis of MEG recordings.

    PubMed

    Lu, Qing; Bi, Kun; Liu, Chu; Luo, Guoping; Tang, Hao; Yao, Zhijian

    2013-10-16

    Abnormal inter-regional causalities can be mapped for the objective diagnosis of various diseases. These inter-regional connectivities are usually calculated over an entire scan and used to characterize the stationary strength of the connections. However, the connectivity within networks may undergo substantial changes during a scan. In this study, we developed an objective depression recognition approach using the dynamic regional interactions that occur in response to sad facial stimuli. The whole time-period magnetoencephalography (MEG) signals from the visual cortex, amygdala, anterior cingulate cortex (ACC) and inferior frontal gyrus (IFG) were separated into sequential time intervals. The Granger causality mapping method was used to identify the pairwise interaction pattern within each time interval. Feature selection was then undertaken within a minimum redundancy-maximum relevance (mRMR) framework. Typical classifiers were utilized to predict those patients who had depression. The overall performances of these classifiers were similar, and the highest classification accuracy rate was 87.5%. The best discriminative performance was obtained when the number of features was within a robust range. The discriminative network pattern obtained through support vector machine (SVM) analyses displayed abnormal causal connectivities that involved the amygdala during the early and late stages. These early and late connections in the amygdala appear to reveal a negative bias to coarse expression information processing and abnormal negative modulation in patients with depression, which may critically affect depression discrimination.

  4. Neural correlates of envy: Regional homogeneity of resting-state brain activity predicts dispositional envy.

    PubMed

    Xiang, Yanhui; Kong, Feng; Wen, Xue; Wu, Qihan; Mo, Lei

    2016-11-15

    Envy differs from common negative emotions across cultures. Although previous studies have explored the neural basis of episodic envy via functional magnetic resonance imaging (fMRI), little is known about the neural processes associated with dispositional envy. In the present study, we used regional homogeneity (ReHo) as an index in resting-state fMRI (rs-fMRI) to identify brain regions involved in individual differences in dispositional envy, as measured by the Dispositional Envy Scale (DES). Results showed that ReHo in the inferior/middle frontal gyrus (IFG/MFG) and dorsomedial prefrontal cortex (DMPFC) positively predicted dispositional envy. Moreover, of all the personality traits measured by the Revised NEO Personality Inventory (NEO-PI-R), only neuroticism was significantly associated with dispositional envy. Furthermore, neuroticism mediated the underlying association between the ReHo of the IFG/MFG and dispositional envy. Hence, to the best of our knowledge, this study provides the first evidence that spontaneous brain activity in multiple regions related to self-evaluation, social perception, and social emotion contributes to dispositional envy. In addition, our findings reveal that neuroticism may play an important role in the cognitive processing of dispositional envy.

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. Seasonal rainfall predictions over the southeast United States using the Florida State University nested regional spectral model

    NASA Astrophysics Data System (ADS)

    Cocke, Steven; Larow, T. E.; Shin, D. W.

    2007-02-01

    Seasonal rainfall predictions over the southeast United States using the recently developed Florida State University (FSU) nested regional spectral model are presented. The regional model is nested within the FSU coupled model, which includes a version of the Max Plank Institute Hamburg Ocean Primitive Equation model. The southeast U.S. winter has a rather strong climatic signal due to teleconnections with tropical Pacific sea surface temperatures and thus provides a good test case scenario for a modeling study. Simulations were done for 12 boreal winter seasons, from 1986 to 1997. Both the regional and global models captured the basic large-scale patterns of precipitation reasonably well when compared to observed station data. The regional model was able to predict the anomaly pattern somewhat better than the global model. The regional model was particularly more skillful at predicting the frequency of significant rainfall events, in part because of the ability to produce heavier rainfall events.

  10. Analysis and prediction of the critical regions of antimicrobial peptides based on conditional random fields.

    PubMed

    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.

  11. Prediction of Frost Risks and Plagues using WRF model: a Port Wine region case study

    NASA Astrophysics Data System (ADS)

    Rodrigues, M. A.; Rocha, A.; Monteiro, A.; Quénol, H.; de Freitas, J. R.

    2012-04-01

    In viticulture where the quality of the wine, the selection of the grapevines or even the characteristics of the farming soil, also depending from local soil features like topography, proximity of a river or water body, will act locally on the weather. Frosts are of significant concern to growers of many cultures crops such as winegrapes. Because of their high latitude and some altitude, the vineyards of the Demarcated Douro Region (DDR) are subjected to the frost, which cause serious damages. But the hazards of vineyard don't confine to the incidents of the fortuitous and meteorological character. The illnesses and plagues affect frequently the vineyards of Demarcated Douro Region due, namely to the weather, to the high power of the regional stocks, to the dense vegetation badly drained and favourable to the setting of numberless fungi, viruses and/or poisonous insects. In the case of DDR it is worth noticing the meteorological conditions due to the weather characteristics. Although there are several illnesses and plagues the most important enemies for the vine in the DDR are the mildew, oidium, grey rottenness, grape moth,. . . , if the climatic conditions favour their appearance and development. For this study, we selected some months for different periods, at the 16 weather stations of the Region of Douro. We use the Weather Research and Forecast Model (WRF) to study and possibly predict the occurrence of risk and plagues (mildew) episodes. The model is first validated with the meteorological data obtained at the weather stations. The knowledge of frost and plagues occurrence allows one to decrease its risks not only by selecting the cultural species and varieties but also the places of growth and the planting and sowing dates.

  12. 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

  13. 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.

  14. 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.

  15. 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

  16. 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).

  17. 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.

  18. Pineal cysts and other pineal region malignancies: determining factors predictive of hydrocephalus and malignancy.

    PubMed

    Starke, Robert M; Cappuzzo, Justin M; Erickson, Nicholas J; Sherman, Jonathan H

    2016-10-21

    OBJECTIVE Cystic lesions of the pineal gland are most often uncomplicated benign lesions with typical MRI characteristics. The authors aimed to study pineal lesion characteristics on MRI to better distinguish benign pineal cysts from other pineal region malignancies as well as to determine which characteristics were predictive of the latter malignancies. They also aimed to study risk factors predictive of hydrocephalus or malignancy in patients harboring these lesions. METHODS The authors performed a retrospective review of a prospectively compiled database documenting the outcomes of patients with suspected pineal cysts on MRI who had presented in the period from 1998 to 2004. Inherent patient and lesion characteristics were assessed in a univariate logistic regression analysis to predict the following dependent variables: development of hydrocephalus, biopsy-confirmed malignancy, and intervention. Possible inherent patient and lesion characteristics included age, sex, T1 and T2 MRI signal pattern, contrast enhancement pattern, presence of cyst, presence of blood, complexity of lesion, presence of calcification, and duration of follow-up. Inherent patient and lesion characteristics that were predictive in the univariate analysis (p < 0.15) were included in the multivariable logistic regression analysis. RESULTS Of the 79 patients with benign-appearing pineal cysts, 26 (33%) were male and 53 (67%) were female, with a median age of 38 years (range 9-86 years). The median cyst radius was 5 mm (range 1-20 mm). Two patients (2.5%) had evidence of calcifications, 7 (9%) had multicystic lesions, and 25 (32%) had some evidence of contrast enhancement. The median follow-up interval was 3 years (range 0.5-13 years). Seven patients (9%) had an increase in the size of their lesion over time. Eight patients (10%) had a hemorrhage, and 11 patients (14%) developed hydrocephalus. Nine (11%) received ventriculoperitoneal shunts for the development of hydrocephalus, and 12 patients

  19. Predicting SAT Performance from Advanced Course Content and Timing of Matriculation

    ERIC Educational Resources Information Center

    Patterson, Jonathan Sparks

    2012-01-01

    As record numbers of students are applying to selective colleges and universities, students are attempting to set themselves apart from their peers by taking rigorous advanced courses in high school. The race for improving a student's academic record has resulted in more and more students taking these courses earlier and earlier in their high…

  20. Regional yield predictions of malting barley by remote sensing and ancillary data

    NASA Astrophysics Data System (ADS)

    Weissteiner, Christof J.; Braun, Matthias; Kuehbauch, Walter

    2004-02-01

    Yield forecasts are of high interest to the malting and brewing industry in order to allow the most convenient purchasing policy of raw materials. Within this investigation, malting barley yield forecasts (Hordeum vulgare L.) were performed for typical growing regions in South-Western Germany. Multisensoral and multitemporal Remote Sensing data on one hand and ancillary meteorological, agrostatistical, topographical and pedological data on the other hand were used as input data for prediction models, which were based on an empirical-statistical modeling approach. Since spring barley production is depending on acreage and on the yield per area, classification is needed, which was performed by a supervised multitemporal classification algorithm, utilizing optical Remote Sensing data (LANDSAT TM/ETM+). Comparison between a pixel-based and an object-oriented classification algorithm was carried out. The basic version of the yield estimation model was conducted by means of linear correlation of Remote Sensing data (NOAA-AVHRR NDVI), CORINE land cover data and agrostatistical data. In an extended version meteorological data (temperature, precipitation, etc.) and soil data was incorporated. Both, basic and extended prediction systems, led to feasible results, depending on the selection of the time span for NDVI accumulation.

  1. Predicting the effects of nanoscale cerium additives in diesel fuel on regional-scale air quality.

    PubMed

    Erdakos, Garnet B; Bhave, Prakash V; Pouliot, George A; Simon, Heather; Mathur, Rohit

    2014-11-04

    Diesel vehicles are a major source of air pollutant emissions. Fuel additives containing nanoparticulate cerium (nCe) are currently being used in some diesel vehicles to improve fuel efficiency. These fuel additives also reduce fine particulate matter (PM2.5) emissions and alter the emissions of carbon monoxide (CO), nitrogen oxides (NOx), and hydrocarbon (HC) species, including several hazardous air pollutants (HAPs). To predict their net effect on regional air quality, we review the emissions literature and develop a multipollutant inventory for a hypothetical scenario in which nCe additives are used in all on-road and nonroad diesel vehicles. We apply the Community Multiscale Air Quality (CMAQ) model to a domain covering the eastern U.S. for a summer and a winter period. Model calculations suggest modest decreases of average PM2.5 concentrations and relatively larger decreases in particulate elemental carbon. The nCe additives also have an effect on 8 h maximum ozone in summer. Variable effects on HAPs are predicted. The total U.S. emissions of fine-particulate cerium are estimated to increase 25-fold and result in elevated levels of airborne cerium (up to 22 ng/m3), which might adversely impact human health and the environment.

  2. Activities of the Climate Forecast Unit (CFU) on regional decadal prediction

    NASA Astrophysics Data System (ADS)

    Guemas, V.; Prodhomme, C.; Doblas-Reyes, F.; Volpi, D.; Caron, L. P.; Davis, M.; Menegoz, M.; Saurral, R. I.; Bellprat, O.

    2014-12-01

    The Climate Forecasting Unit (CFU) is a research unit devoted to develop climate forecast systems to contribute to the creation of climate services that aims to 1) develop climate forecast systems and prediction methodologies, 2) investigate the potential sources of skill and understand the limitation of state-of-the-art forecast systems, 3) formulate reliable climate forecasts that meet specific user needs and 4) contribute to the development of climate services. This presentation will provide an overview of the latest results of this research unit in the field of regional decadal prediction focusing on 1) an assessment of the relative merits of the full-field and the anomaly initialisation techniques, 2) a description of the forecast quality of North Atlantic tropical cyclone activity and South Pacific climate, 3) an evaluation of the impact of volcanic aerosol prescription during decadal forecasts, and 4) the strategy for the development of a climate service to ensure that forecasts are both useful and action-oriented. Results from several European projects, SPECS, PREFACE and EUPORIAS, will be used to illustrate these findings.

  3. [Prediction of winter wheat yield based on crop biomass estimation at regional scale].

    PubMed

    Ren, Jian-Qiang; Liu, Xing-Ren; Chen, Zhong-Xin; Zhou, Qing-Bo; Tang, Hua-Jun

    2009-04-01

    Based on the 2004 in situ data of crop yield, remote sensing inversed photosynthetically active radiation (PAR), fraction of photosynthetically active radiation (f(PAR)), climate, and soil moisture in 83 typical winter wheat sampling field of 45 counties in Shijiazhuang, Hengshui, and Xingtai of Hebei Province, a simplified model for calculating the light use efficiency (epsilon) of winter wheat in Huanghuaihai Plain was established. According to the crop accumulated biomass from March to May and corrected by harvest index, the quantitative relationship between crop biomass and crop yield for winter wheat was set up, and applied in the 235 counties in Huanghuaihai Plain region of Hebei Province and Shandong Province and validated by the official crop statistical data at county level in 2004. The results showed that the root mean square error (RMSE) of predicted winter wheat yield in study area was 238.5 kg x hm(-2), and the relative error was 4.28%, suggesting that it was feasible to predict winter wheat yield by crop biomass estimation based on remote sensing data.

  4. 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

  5. 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.

  6. 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

  7. 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

  8. Forest production predicted from satellite image analysis for the Southeast Asia region

    PubMed Central

    2013-01-01

    Background The objective of this study was to demonstrate a new, cost-effective method to define the sustainable amounts of harvested wood products in Southeast Asian countries case studies, while avoiding degradation (net loss) of total wood carbon stocks. Satellite remote sensing from the MODIS sensor was used in the CASA (Carnegie Ames Stanford Approach) carbon cycle model to map forest production for the Southeast Asia region from 2000 to 2010. These CASA model results have been designed to be spatially detailed enough to support carbon cycle assessments in different wooded land cover classes, e.g., open woodlands, wetlands, and forest areas. Results The country with the highest average forest net primary production (NPP greater than 950 g C m-2 yr-1) over the period was the Philippines, followed by Malaysia and Indonesia. Myanmar and Vietnam had the lowest average forest NPP among the region’s countries at less than 815 g C m-2 yr-1. Case studies from throughout the Southeast Asia region for the maximum harvested wood products amount that could be sustainably extracted per year were generated using the CASA model NPP predictions. Conclusions The method of using CASA model’s estimated annual change in forest carbon on a yearly basis can conservatively define the upper limit for the amount of harvested wood products that can be removed and still avoid degradation (net loss) of the total wood carbon stock over that same time period. PMID:24016254

  9. 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.

  10. 76 FR 23543 - The Jobs and Innovation Accelerator Challenge; a Coordinated Initiative To Advance Regional...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-04-27

    ... approximately 20 industry clusters that exhibit high-growth development potential. These successful clusters... customized solutions for approximately 20 competitively selected industry clusters in urban and rural regions... sustainable economic prosperity. Knowing that regional innovation clusters provide a globally proven...

  11. 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

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. Application of Advanced Methods to Predict Grid to Rod Fretting in PWRs

    SciTech Connect

    Karoutas, Zeses; Roger, Lu Y.; Yan, J.; Krammen, M.A.; Sham, Sam

    2012-01-01

    Advanced modeling and simulation methods are being developed as part of the US Department of Energy sponsored Nuclear Energy Modeling and Simulation Hub called CASL (Consortium for Advanced Simulation of LWRs). The key participants of the CASL team include Oak Ridge National Laboratory (lead), Idaho National Laboratory, Sandia National Laboratories, Los Alamos National Laboratory, Massachusetts Institute of Technology, North Carolina State University, University of Michigan, Electric Power Research Institute, Tennessee Valley Authority and Westinghouse Electric Corporation. One of the key objectives of the CASL program is to develop multi-physics methods and tools which evaluate neutronic, thermal-hydraulic, structural mechanics and nuclear fuel rod performance in rod bundles to support power uprates, increased burnup/cycle length and life extension for US nuclear plants.

  17. Advancing viral RNA structure prediction: measuring the thermodynamics of pyrimidine-rich internal loops.

    PubMed

    Phan, Andy; Mailey, Katherine; Sakai, Jessica; Gu, Xiaobo; Schroeder, Susan J

    2017-02-17

    Accurate thermodynamic parameters improve RNA structure predictions and thus accelerate understanding of RNA function and the identification of RNA drug binding sites. Many viral RNA structures, such as internal ribosome entry sites, have internal loops and bulges that are potential drug target sites. Current models used to predict internal loops are biased towards small, symmetric purine loops, and thus poorly predict asymmetric, pyrimidine-rich loops with more than 6 nucleotides that occur frequently in viral RNA. This paper presents new thermodynamic data for 40 pyrimidine loops, many of which can form UU or protonated CC base pairs. Protonated cytosine and uracil base pairs stabilize asymmetric internal loops. Accurate prediction rules are presented that account for all thermodynamic measurements of RNA asymmetric internal loops. New loop initiation terms for loops with more than 6 nucleotides are presented that do not follow previous assumptions that increasing asymmetry destabilizes loops. Since the last 2004 update, 126 new loops with asymmetry or sizes greater than 2x2 have been measured (Mathews 2004). These new measurements significantly deepen and diversify the thermodynamic database for RNA. These results will help better predict internal loops that are larger, pyrimidine-rich, and occur within viral structures such as internal ribosome entry sites.

  18. 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.

  19. 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.

  20. OSMOSE an experimental program for improving neutronic predictions of advanced nuclear fuels.

    SciTech Connect

    Klann, R. T.; Aliberti, G.; Zhong, Z.; Graczyk, D.; Loussi, A.; Nuclear Engineering Division; Commissariat a l Energie Atomique

    2007-10-18

    This report describes the technical results of tasks and activities conducted in FY07 to support the DOE-CEA collaboration on the OSMOSE program. The activities are divided into five high-level tasks: reactor modeling and pre-experiment analysis, sample fabrication and analysis, reactor experiments, data treatment and analysis, and assessment for relevance to high priority advanced reactor programs (such as GNEP and Gen-IV).

  1. [Clinical application value of prognostic nutritional index for predicting survival in patients with advanced non-small cell lung cancer].

    PubMed

    Xu, W J; Kang, Y M; Zhou, L; Chen, F F; Song, Y H; Zhang, C Q

    2017-02-23

    Objective: To explore the clinical application value of prognostic nutritional index(PNI) for predicting overall survival(OS) in patients with advanced non-small cell lung cancer (NSCLC). Methods: 123 patients with histologically confirmed non-small cell lung cancer were enrolled in this study, and their clinical and laboratory data were reviewed. The PNI was calculated as 10×serum albumin value+ 5×total lymphocyte countin peripheral blood.Univariate and multivariate analyses were used to identify the potential prognostic factors for advanced NSCLC. Results: PNI of the 123 NSCLC patients was 46.24±6.56. PNI was significantly associated with age, weight loss and pleural effusion (P<0.05). However, it showed no relationship with sex, smoking, hemoptysis, chest pain, dyspnea, histological type, clinical stage, and administration of chemotherapy (P>0.05). The median OS of the 123 patients was 19.5 months. The median OS in the higher PNI group (PNI≥46.24) and lower PNI group(PNI<46.24) were 25.2 months and 16.4 months, respectively.The 1-year survival rates were 80.6% and 63.9%, and 2-year survival rates were 54.8% and 19.6%, respectively (P<0.01). Univariate analysis showed that PNI, age, dyspnea, and weight loss were related to the OS of the advanced NSCLC patients (P<0.05). Multivariate analysis identified PNI as an independent prognostic factor for OS of advanced NSCLC (P<0.001). Conclusion: PNI can be easily calculated, and may be used as a relatively new prognostic indicator for advanced NSCLC in clinical practice.

  2. DisoMCS: Accurately Predicting Protein Intrinsically Disordered Regions Using a Multi-Class Conservative Score Approach

    PubMed Central

    Wang, Zhiheng; Yang, Qianqian; Li, Tonghua; Cong, Peisheng

    2015-01-01

    The precise prediction of protein intrinsically disordered regions, which play a crucial role in biological procedures, is a necessary prerequisite to further the understanding of the principles and mechanisms of protein function. Here, we propose a novel predictor, DisoMCS, which is a more accurate predictor of protein intrinsically disordered regions. The DisoMCS bases on an original multi-class conservative score (MCS) obtained by sequence-order/disorder alignment. Initially, near-disorder regions are defined on fragments located at both the terminus of an ordered region connecting a disordered region. Then the multi-class conservative score is generated by sequence alignment against a known structure database and represented as order, near-disorder and disorder conservative scores. The MCS of each amino acid has three elements: order, near-disorder and disorder profiles. Finally, the MCS is exploited as features to identify disordered regions in sequences. DisoMCS utilizes a non-redundant data set as the training set, MCS and predicted secondary structure as features, and a conditional random field as the classification algorithm. In predicted near-disorder regions a residue is determined as an order or a disorder according to the optimized decision threshold. DisoMCS was evaluated by cross-validation, large-scale prediction, independent tests and CASP (Critical Assessment of Techniques for Protein Structure Prediction) tests. All results confirmed that DisoMCS was very competitive in terms of accuracy of prediction when compared with well-established publicly available disordered region predictors. It also indicated our approach was more accurate when a query has higher homologous with the knowledge database. Availability The DisoMCS is available at http://cal.tongji.edu.cn/disorder/. PMID:26090958

  3. Strengthening sociometric prediction: scientific advances in the assessment of children's peer relations.

    PubMed

    DeRosier, Melissa E; Thomas, James M

    2003-01-01

    This study assessed the strength of sociometric classification in the prediction of concurrent sociobehavioral adjustment. Differential adjustment for subgroups of unclassified children were also examined. Participants were 881 fifth graders (ages 9 to 12). Classification strength (CS) and unclassified subgroups were determined through newly developed algorithms. CS added significantly to the prediction of all areas of adjustment. For example, highly rejected children were at extreme risk for victimization whereas highly controversial children were most likely to be bullies and relationally aggressive. Unclassified subgroups were found to exhibit adjustment problems mirroring those of their extreme status group counterparts. Findings support that increasing the sensitivity of sociometric measurement results in both greater predictive strength and enhanced understanding of underlying social processes.

  4. 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.

  5. 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.

  6. 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

  7. 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.

  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. 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.

  10. 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.

  11. 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

  12. 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.

  13. Neoadjuvant treatment for advanced esophageal cancer: response assessment before surgery and how to predict response to chemoradiation before starting treatment

    PubMed Central

    Hölscher, Arnulf H.; Schmidt, Matthias; Warnecke-Eberz, Ute

    2015-01-01

    Patients with advanced esophageal cancer (T3-4, N) have a poor prognosis. Chemoradiation or chemotherapy before esophagectomy with adequate lymphadenectomy is the standard treatment for patients with resectable advanced esophageal carcinoma. However, only patients with major histopathologic response (regression to less than 10% of the primary tumor) after preoperative treatment will have a prognostic benefit of preoperative chemoradiation. Using current therapy regimens about 40% to 50% of the patients show major histopathological response. The remaining cohort does not benefit from this neoadjuvant approach but might benefit from earlier surgical resection. Therefore, it is an aim to develop tools for response prediction before starting the treatment and for early response assessment identifying responders. The current review discusses the different imaging techniques and the most recent studies about molecular markers for early response prediction. The results show that [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET) has a good sensitivity but the specificity is not robust enough for routine clinical use. Newer positron emission tomography detector technology, the combination of FDG-PET with computed tomography, additional evaluation criteria and standardization of evaluation may improve the predictive value. There exist a great number of retrospective studies using molecular markers for prediction of response. Until now the clinical use is missing. But the results of first prospective studies are promising. A future perspective may be the combination of imaging technics and special molecular markers for individualized therapy. Another aspect is the response assessment after finishing neoadjuvant treatment protocol. The different clinical methods are discussed. The results show that until now no non-invasive method is valid enough to assess complete histopathological response. PMID:26157318

  14. 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

  15. 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...

  16. Development of advanced stability theory suction prediction techniques for laminar flow control. [on swept wings

    NASA Technical Reports Server (NTRS)

    Srokowski, A. J.

    1978-01-01

    The problem of obtaining accurate estimates of suction requirements on swept laminar flow control wings was discussed. A fast accurate computer code developed to predict suction requirements by integrating disturbance amplification rates was described. Assumptions and approximations used in the present computer code are examined in light of flow conditions on the swept wing which may limit their validity.

  17. 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.

  18. Predictive risk factors for chronic regional and multisite musculoskeletal pain: a 5-year prospective study in a working population.

    PubMed

    Herin, Fabrice; Vézina, Michel; Thaon, Isabelle; Soulat, Jean-Marc; Paris, Christophe

    2014-05-01

    The role of psychosocial and physical factors in the development of musculoskeletal pain (MSP) has now been clearly demonstrated. However, it is unclear whether these factors contribute to specific regional MSP or to multisite pain. The main goal of this study was to assess the impact of work-related factors according to gender on the development of regional and multisite MSP. A total of 12,591 subjects (65% men and 35% women) who were born in 1938, 1943, 1948, and 1953 and were participating in a French longitudinal prospective epidemiological survey (ESTEV) in 1990 to 1995 were eligible. Personal factors and work exposure were assessed by self-administered questionnaires. Statistical associations between chronic MSP (regional body site or multisite), personal factors, and occupational factors were analyzed using logistic regression modeling. The incidence of regional MSP and multisite pain in 1995 were, respectively, 17% and 25.6%. For women, highly repetitive movements predicted neck/shoulder pain; posture and vibrations predicted arm and low back pain; and effort with tools predicted arm pain. For men, forceful effort and vibrations predicted neck/shoulder pain; posture and forceful effort predicted lower limb and low back pain; and forceful effort and effort with tools predicted arm pain. Physical constraints (ie, forceful effort or vibrations) were associated with multisite pain in both genders. Only for women, psychological factors were risk factors predictive of upper limb pain and in 3 or 4 painful anatomical sites. These results support the hypothesis that some physical and psychological work-related factors are predictive of regional or multisite MSP but differ according to gender. Gender differences and risk factors for work-related musculoskeletal pain should be also taken into account to more effectively target preventive measures.

  19. Short-term predictions by statistical methods in regions of varying dynamical error growth in a chaotic system

    NASA Astrophysics Data System (ADS)

    Mittal, A. K.; Singh, U. P.; Tiwari, A.; Dwivedi, S.; Joshi, M. K.; Tripathi, K. C.

    2015-08-01

    In a nonlinear, chaotic dynamical system, there are typically regions in which an infinitesimal error grows and regions in which it decays. If the observer does not know the evolution law, recourse is taken to non-dynamical methods, which use the past values of the observables to fit an approximate evolution law. This fitting can be local, based on past values in the neighborhood of the present value as in the case of Farmer-Sidorowich (FS) technique, or it can be global, based on all past values, as in the case of Artificial Neural Networks (ANN). Short-term predictions are then made using the approximate local or global mapping so obtained. In this study, the dependence of statistical prediction errors on dynamical error growth rates is explored using the Lorenz-63 model. The regions of dynamical error growth and error decay are identified by the bred vector growth rates or by the eigenvalues of the symmetric Jacobian matrix. The prediction errors by the FS and ANN techniques in these two regions are compared. It is found that the prediction errors by statistical methods do not depend on the dynamical error growth rate. This suggests that errors using statistical methods are independent of the dynamical situation and the statistical methods may be potentially advantageous over dynamical methods in regions of low dynamical predictability.

  20. 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

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

    PubMed

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

    2015-05-05

    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.

  2. [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.

  3. Advanced Information Processing. Volume II. Instructor's Materials. Curriculum Improvement Project. Region II.

    ERIC Educational Resources Information Center

    Stanford, Linda

    This course curriculum is intended for use by community college insructors and administrators in implementing an advanced information processing course. It builds on the skills developed in the previous information processing course but goes one step further by requiring students to perform in a simulated office environment and improve their…

  4. Advanced Information Processing. Volume I. Student's Materials. Curriculum Improvement Project. Region II.

    ERIC Educational Resources Information Center

    Stanford, Linda

    This course curriculum is intended for use in an advanced information processing course. It builds on the skills developed in the previous information processing course but goes one step further by requiring students to perform in a simulated office environment and improve their decision-making skills. This volume contains two parts of the…

  5. Functional imaging using computational fluid dynamics to predict treatment success of mandibular advancement devices in sleep-disordered breathing.

    PubMed

    De Backer, J W; Vanderveken, O M; Vos, W G; Devolder, A; Verhulst, S L; Verbraecken, J A; Parizel, P M; Braem, M J; Van de Heyning, P H; De Backer, W A

    2007-01-01

    Mandibular advancement devices (MADs) have emerged as a popular alternative for the treatment of sleep-disordered breathing. These devices bring the mandibula forward in order to increase upper airway (UA) volume and prevent total UA collapse during sleep. However, the precise mechanism of action appears to be quite complex and is not yet completely understood; this might explain interindividual variation in treatment success. We examined whether an UA model, that combines imaging techniques and computational fluid dynamics (CFD), allows for a prediction of the treatment outcome with MADs. Ten patients that were treated with a custom-made mandibular advancement device (MAD), underwent split-night polysomnography. The morning after the sleep study, a low radiation dose CT scan was scheduled with and without the MAD. The CT examinations allowed for a comparison between the change in UA volume and the anatomical characteristics through the conversion to three-dimensional computer models. Furthermore, the change in UA resistance could be calculated through flow simulations with CFD. Boundary conditions for the model such as mass flow rate and pressure distributions were obtained during the split-night polysomnography. Therefore, the flow modeling was based on a patient specific geometry and patient specific boundary conditions. The results indicated that a decrease in UA resistance and an increase in UA volume correlate with both a clinical and an objective improvement. The results of this pilot study suggest that the outcome of MAD treatment can be predicted using the described UA model.

  6. Application of Multivariable Model Predictive Advanced Control for a 2×310T/H CFB Boiler Unit

    NASA Astrophysics Data System (ADS)

    Weijie, Zhao; Zongllao, Dai; Rong, Gou; Wengan, Gong

    When a CFB boiler is in automatic control, there are strong interactions between various process variables and inverse response characteristics of bed temperature control target. Conventional Pill control strategy cannot deliver satisfactory control demand. Kalman wave filter technology is used to establish a non-linear combustion model, based on the CFB combustion characteristics of bed fuel inventory, heating values, bed lime inventory and consumption. CFB advanced combustion control utilizes multivariable model predictive control technology to optimize primary and secondary air flow, bed temperature, air flow, fuel flow and heat flux. In addition to providing advanced combustion control to 2×310t/h CFB+1×100MW extraction condensing turbine generator unit, the control also provides load allocation optimization and advanced control for main steam pressure, combustion and temperature. After the successful implementation, under 10% load change, main steam pressure varied less than ±0.07MPa, temperature less than ±1°C, bed temperature less than ±4°C, and air flow (O2) less than ±0.4%.

  7. 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

  8. DNase-seq predicts regions of rotational nucleosome stability across diverse human cell types.

    PubMed

    Winter, Deborah R; Song, Lingyun; Mukherjee, Sayan; Furey, Terrence S; Crawford, Gregory E

    2013-07-01

    DNase-seq is primarily used to identify nucleosome-depleted DNase I hypersensitive (DHS) sites genome-wide that correspond to active regulatory elements. However, ≈ 40 yr ago it was demonstrated that DNase I also digests with a ≈ 10-bp periodicity around nucleosomes matching the exposure of the DNA minor groove as it wraps around histones. Here, we use DNase-seq data from 49 samples representing diverse cell types to reveal this digestion pattern at individual loci and predict genomic locations where nucleosome rotational positioning, the orientation of DNA with respect to the histone surface, is stably maintained. We call these regions DNase I annotated regions of nucleosome stability (DARNS). Compared to MNase-seq experiments, we show DARNS correspond well to annotated nucleosomes. Interestingly, many DARNS are positioned over only one side of annotated nucleosomes, suggesting that the periodic digestion pattern attenuates over the nucleosome dyad. DARNS reproduce the arrangement of nucleosomes around transcription start sites and are depleted at ubiquitous DHS sites. We also generated DARNS from multiple lymphoblast cell line (LCL) samples. We found that LCL DARNS were enriched at DHS sites present in most of the original 49 samples but absent in LCLs, while multi-cell-type DARNS were enriched at LCL-specific DHS sites. This indicates that variably open DHS sites are often occupied by rotationally stable nucleosomes in cell types where the DHS site is closed. DARNS provide additional information about precise DNA orientation within individual nucleosomes not available from other nucleosome positioning assays and contribute to understanding the role of chromatin in gene regulation.

  9. Ostwald-Meyers Metastable Region in LiBr Crystallization-Comparison of Measurements with Predictions.

    PubMed

    Duvall, Kristin N.; Dirksen, James A.; Ring, Terry A.

    2001-07-15

    Experiments have been performed to measure the Ostwald-Meyers metastable region during crystallization from concentrated LiBr solutions. Solution thermodynamics shows that several hydrated LiBr salts and ice can crystallize depending upon the concentration of LiBr in aqueous solution. The available solubility data were interpreted to give solubility products of several hydrated LiBr salts using the formulation of Helgeson, which accounts for the activity of water. The crystallization temperature was measured by monitoring to +/-0.01 degrees C the temperature of solutions inside test tubes placed in a cooling bath programmed at a cooling rate of 20 degrees C/h. A release of the heat of crystallization identifies the temperature of crystallization. The equilibrium solubility was verified by crystallization with seed crystals present. The crystallization temperature without seeds present was 10 to 20 degrees C less than the equilibrium solubility temperature corresponding to the Ostwald-Meyers metastable region. This crystallization temperature measured at 20 degrees C/h was shown to correspond to nucleation on the surface of the test tube with an interface energy of 40+/-1.2 erg/cm(2). Homogeneous nucleation from solution data shows the crystallization temperature to be from 40 to 50 degrees C below the equilibrium solubility curve and to be accurately predicted by homogeneous nucleation with an interface energy of 26 erg/cm(2), the literature value of the ice/water interface. Since the hydrated LiBr salts have surfaces that expose structured water molecules to the solution, this value is believed to be an appropriate value of the interface energy of the hydrated LiBr crystals. Crystallization temperature measurements were performed at different cooling rates, showing that slower cooling rates gave a narrower Ostwald-Myers metastable zone as is expected. Induction time measurements showed that the time to spontaneous crystallization increases as the supersaturation

  10. Mapping as a tool for predicting the risk of anthrax outbreaks in Northern Region of Ghana

    PubMed Central

    Nsoh, Ayamdooh Evans; Kenu, Ernest; Forson, Eric Kofi; Afari, Edwin; Sackey, Samuel; Nyarko, Kofi Mensah; Yebuah, Nathaniel

    2016-01-01

    Introduction Anthrax is a febrile soil-born infectious disease that can affect all warm-blooded animals including man. Outbreaks of anthrax have been reported in northern region of Ghana but no concerted effort has been made to implement risk-based surveillance systems to document outbreaks so as to implement policies to address the disease. We generated predictive maps using soil pH, temperature and rainfall as predictor variables to identify hotspot areas for the outbreaks. Methods A 10-year secondary data records on soil pH, temperature and rainfall were used to create climate-based risk maps using ArcGIS 10.2. The monthly mean values of rainfall and temperature for ten years were calculated and anthrax related evidence based constant raster values were created as weights for the three factors. All maps were generated using the Kriging interpolation method. Results There were 43 confirmed outbreaks. The deaths involved were 131 cattle, 44 sheep, 15 goats, 562 pigs with 6 human deaths and 22 developed cutaneous anthrax. We found three strata of well delineated distribution pattern indicating levels of risk due to suitability of area for anthrax spore survival. The likelihood of outbreaks occurrence and reoccurrence was higher in Strata I, Strata II and strata III respectively in descending order, due to the suitability of soil pH, temperature and rainfall for the survival and dispersal of B. anthracis spore. Conclusion The eastern corridor of Northern region is a Hots spot area. Policy makers can develop risk based surveillance system and focus on this area to mitigate anthrax outbreaks and reoccurrence. PMID:28149439

  11. 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.

  12. Advances in CFD Prediction of Shock Wave Turbulent Boundary Layer Interactions

    DTIC Science & Technology

    2006-01-01

    on the Baldwin and Lomax [151] algebraic turbulence model. Fig. 58 from Panaras [150] includes all the critical elements of the swept shock/turbulent...pitot pressure, yaw angle and surface pressure are predictable with reasonable accuracy using algebraic or two-equation turbulence models, however the...calculations they tested algebraic turbulence models and the k−² model, integrated to the wall or employing the wall-function technique. They have found

  13. Advanced Control Filtering and Prediction for Phased Arrays in Directed Energy Systems

    DTIC Science & Technology

    2014-07-31

    SIMULINK model for prediction and feedback control of a phase ramp. Mirror represented by integrator with sample time tsim. The model shown has a...and simulating the closed-loop system in SIMULINK . Approved for public release; distribution unlimited 3 4.0 RESULTS AND DISCUSSION 4.1...although this measurement probably is not necessary. 4.2 Simulation Model There are three differences between the current SIMULINK model and the

  14. Advanced Durability Analysis. Volume 2. Analytical Predictions, Test Results and Analytical Correlations

    DTIC Science & Technology

    1989-02-27

    used for the back-extrapolation. Recommendations for durability analysis are as follows: (1) define the equivalent initial flaw size distribution ...WAFXHR4 Data Set) for Cumulative Distribution of Service Time to Reach Crack Size x1 -0.59" Based on DCGA- DCGA. xiv List of Figures (Continued) Fiaur. ag ...be used to make predictions for the probability bf crack exceedance at any service time, 7’ , and the cumulative distribution of service time to

  15. 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.

  16. 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.

  17. 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

  18. Sequential correction of ensemble regional weather predictions for forecasting reference evapotranspiration

    NASA Astrophysics Data System (ADS)

    Pelosi, Anna; Medina Gonzalez, Hanoi; Villani, Paolo; D'Urso, Guido; Battista Chirico, Giovanni

    2016-04-01

    This study explores the performance of an adaptive procedure for correcting the ensemble numerical weather outputs applied to the probabilistic forecast of reference evapotranspiration (ETo). This procedure is proposed as an effective forecast correction method when the available dataset is not large enough for the calibration of statistical batch procedures. The numerical weather prediction outputs are those provided by COSMO-LEPS, an ensemble-based Limited Area Model, with 16 members and 7.5 km spatial resolution, with forecast lead-time up to 5 days. ETo forecasts are computed according to the FAO Penman-Monteith (FAO-PM) equation, which requires data of five weather variables: air temperature, relative humidity, solar radiation and wind speed. The performance of the proposed procedure is evaluated at eighteen monitoring stations, located in Campania region (Southern Italy), with two alternative strategies: i) correction applied to the raw ensemble forecasts of the five weather variables prior applying the FAO-PM equation; ii) correction applied to the ensemble output of the ETo forecasts obtained with FAO-PM equation after using the raw ensemble weather forecasts as input. In both cases the suggested post-processing procedure was able to significantly increase the accuracy and reduce the uncertainty of the ETo forecasts.

  19. 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.

  20. Prediction of maximum earthquake intensities for the San Francisco Bay region

    USGS Publications Warehouse

    Borcherdt, Roger D.; Gibbs, James F.

    1975-01-01

    The intensity data for the California earthquake of April 18, 1906, are strongly dependent on distance from the zone of surface faulting and the geological character of the ground. Considering only those sites (approximately one square city block in size) for which there is good evidence for the degree of ascribed intensity, the empirical relation derived between 1906 intensities and distance perpendicular to the fault for 917 sites underlain by rocks of the Franciscan Formation is: Intensity = 2.69 - 1.90 log (Distance) (km). For sites on other geologic units intensity increments, derived with respect to this empirical relation, correlate strongly with the Average Horizontal Spectral Amplifications (AHSA) determined from 99 three-component recordings of ground motion generated by nuclear explosions in Nevada. The resulting empirical relation is: Intensity Increment = 0.27 +2.70 log (AHSA), and average intensity increments for the various geologic units are -0.29 for granite, 0.19 for Franciscan Formation, 0.64 for the Great Valley Sequence, 0.82 for Santa Clara Formation, 1.34 for alluvium, 2.43 for bay mud. The maximum intensity map predicted from these empirical relations delineates areas in the San Francisco Bay region of potentially high intensity from future earthquakes on either the San Andreas fault or the Hazard fault.

  1. Regional climate model downscaling may improve the prediction of alien plant species distributions

    NASA Astrophysics Data System (ADS)

    Liu, Shuyan; Liang, Xin-Zhong; Gao, Wei; Stohlgren, Thomas J.

    2014-12-01

    Distributions of invasive species are commonly predicted with species distribution models that build upon the statistical relationships between observed species presence data and climate data. We used field observations, climate station data, and Maximum Entropy species distribution models for 13 invasive plant species in the United States, and then compared the models with inputs from a General Circulation Model (hereafter GCM-based models) and a downscaled Regional Climate Model (hereafter, RCM-based models).We also compared species distributions based on either GCM-based or RCM-based models for the present (1990-1999) to the future (2046-2055). RCM-based species distribution models replicated observed distributions remarkably better than GCM-based models for all invasive species under the current climate. This was shown for the presence locations of the species, and by using four common statistical metrics to compare modeled distributions. For two widespread invasive taxa ( Bromus tectorum or cheatgrass, and Tamarix spp. or tamarisk), GCM-based models failed miserably to reproduce observed species distributions. In contrast, RCM-based species distribution models closely matched observations. Future species distributions may be significantly affected by using GCM-based inputs. Because invasive plants species often show high resilience and low rates of local extinction, RCM-based species distribution models may perform better than GCM-based species distribution models for planning containment programs for invasive species.

  2. 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

    2013-08-07

    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.

  3. 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

  4. 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.

  5. Myopodin methylation is a prognostic biomarker and predicts antiangiogenic response in advanced kidney cancer.

    PubMed

    Pompas-Veganzones, N; Sandonis, V; Perez-Lanzac, Alberto; Beltran, M; Beardo, P; Juárez, A; Vazquez, F; Cozar, J M; Alvarez-Ossorio, J L; Sanchez-Carbayo, Marta

    2016-10-01

    Myopodin is a cytoskeleton protein that shuttles to the nucleus depending on the cellular differentiation and stress. It has shown tumor suppressor functions. Myopodin methylation status was useful for staging bladder and colon tumors and predicting clinical outcome. To our knowledge, myopodin has not been tested in kidney cancer to date. The purpose of this study was to evaluate whether myopodin methylation status could be clinically useful in renal cancer (1) as a prognostic biomarker and 2) as a predictive factor of response to antiangiogenic therapy in patients with metastatic disease. Methylation-specific polymerase chain reactions (MS-PCR) were used to evaluate myopodin methylation in 88 kidney tumors. These belonged to patients with localized disease and no evidence of disease during follow-up (n = 25) (group 1), and 63 patients under antiangiogenic therapy (sunitinib, sorafenib, pazopanib, and temsirolimus), from which group 2 had non-metastatic disease at diagnosis (n = 32), and group 3 showed metastatic disease at diagnosis (n = 31). Univariate and multivariate Cox analyses were utilized to assess outcome and response to antiangiogenic agents taking progression, disease-specific survival, and overall survival as clinical endpoints. Myopodin was methylated in 50 out of the 88 kidney tumors (56.8 %). Among the 88 cases analyzed, 10 of them recurred (11.4 %), 51 progressed (57.9 %), and 40 died of disease (45.4 %). Myopodin methylation status correlated to MSKCC Risk score (p = 0.050) and the presence of distant metastasis (p = 0.039). Taking all patients, an unmethylated myopodin identified patients with shorter progression-free survival, disease-specific survival, and overall survival. Using also in univariate and multivariate models, an unmethylated myopodin predicted response to antiangiogenic therapy (groups 2 and 3) using progression-free survival, disease-specific, and overall survival as clinical endpoints. Myopodin was revealed

  6. Predicting early brain metastases based on clinicopathological factors and gene expression analysis in advanced HER2-positive breast cancer patients.

    PubMed

    Duchnowska, Renata; Jassem, Jacek; Goswami, Chirayu Pankaj; Dundar, Murat; Gökmen-Polar, Yesim; Li, Lang; Woditschka, Stephan; Biernat, Wojciech; Sosińska-Mielcarek, Katarzyna; Czartoryska-Arłukowicz, Bogumiła; Radecka, Barbara; Tomasevic, Zorica; Stępniak, Piotr; Wojdan, Konrad; Sledge, George W; Steeg, Patricia S; Badve, Sunil

    2015-03-01

    The overexpression or amplification of the human epidermal growth factor receptor 2 gene (HER2/neu) is associated with high risk of brain metastasis (BM). The identification of patients at highest immediate risk of BM could optimize screening and facilitate interventional trials. We performed gene expression analysis using complementary deoxyribonucleic acid-mediated annealing, selection, extension and ligation and real-time quantitative reverse transcription PCR (qRT-PCR) in primary tumor samples from two independent cohorts of advanced HER2 positive breast cancer patients. Additionally, we analyzed predictive relevance of clinicopathological factors in this series. Study group included discovery Cohort A (84 patients) and validation Cohort B (75 patients). The only independent variables associated with the development of early BM in both cohorts were the visceral location of first distant relapse [Cohort A: hazard ratio (HR) 7.4, 95 % CI 2.4-22.3; p < 0.001; Cohort B: HR 6.1, 95 % CI 1.5-25.6; p = 0.01] and the lack of trastuzumab administration in the metastatic setting (Cohort A: HR 5.0, 95 % CI 1.4-10.0; p = 0.009; Cohort B: HR 10.0, 95 % CI 2.0-100.0; p = 0.008). A profile including 13 genes was associated with early (≤36 months) symptomatic BM in the discovery cohort. This was refined by qRT-PCR to a 3-gene classifier (RAD51, HDGF, TPR) highly predictive of early BM (HR 5.3, 95 % CI 1.6-16.7; p = 0.005; multivariate analysis). However, predictive value of the classifier was not confirmed in the independent validation Cohort B. The presence of visceral metastases and the lack of trastuzumab administration in the metastatic setting apparently increase the likelihood of early BM in advanced HER2-positive breast cancer.

  7. Tumor size and lymph node status determined by imaging are reliable factors for predicting advanced cervical cancer prognosis.

    PubMed

    Kyung, Min Sun; Kim, Hong Bae; Seoung, Jung Yeob; Choi, In Young; Joo, Young Soo; Lee, Me Yeon; Kang, Jung Bae; Park, Young Han

    2015-05-01

    The aim of the present study was to investigate the prognostic role of a number of clinical factors in advanced cervical cancer patients. Patients (n=157) with stage IIA-IIB cervical cancer treated at four Hallym Medical Centers in South Korea (Hallym University Sacred Heart Hospital; Kangnam Sacred Heart Hospital; Chuncheon Sacred Heart Hospital; and Kangdong Sacred Heart Hospital) between 2006 and 2010 were retrospectively enrolled. Univariate analysis identified significant predictive values in the following eight factors: i) Cancer stage (P<0.0001); ii) tumor size (≤4 vs. 4-6 cm, P=0.0147; and ≤4 vs. >6 cm, P<0.0001); iii) serum squamous cell carcinoma antigen level (≤2 vs. >15 ng/ml; P=0.0291); iv) lower third vaginal involvement (P<0.0001); v) hydronephrosis (P=0.0003); vi) bladder/rectum involvement (P=0.0015); vii) pelvic (P=0.0017) or para-aortic (P=0.0019) lymph node (LN) metastasis detected by imaging vs. no metastasis; and viii) pelvic LN metastasis identified by pathological analysis (P=0.0289). Furthermore, multivariate analysis determined that tumor size (≤4 vs. 4-6 cm, P=0.0371; and ≤4 vs. >6 cm, P=0.0024) and pelvic LN metastasis determined by imaging vs. no metastasis (P=0.0499) were independent predictive variables. Therefore, tumor size and pelvic LN metastasis measured by imaging were independent predictive factors for the prognosis of advanced cervical cancer. These factors may provide more clinically significant prognostic information compared with the currently used International Federation of Gynecology and Obstetrics staging system.

  8. 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.

  9. 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 paper considers the numerical solution of the unsteady, three-dimensional, Euler equations 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 +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.

  10. 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.

  11. CEP55 overexpression predicts poor prognosis in patients with locally advanced esophageal squamous cell carcinoma

    PubMed Central

    Jiang, Wenpeng; Wang, Zhou; Jia, Yang

    2017-01-01

    Development of esophageal squamous cell carcinoma (ESCC) involves alterations in multiple genes with corresponding proteins. Recent studies have demonstrated that centrosomal protein 55 (CEP55) shares certain features with oncogenes, and CEP55 overexpression is associated with the development and progression of malignant tumors. The present study aimed to analyze, for the first time, whether CEP55 expression is related to clinicopothalogic features in the esophageal squamous cell carcinoma (ESCC), as well as patient survival. A total of 110 patients with mid-thoracic ESCC who suffered from Ivor-Lewis were enrolled. The CEP55 expression profile of these patients in tumour tissues and corresponding healthy esophageal mucosa (CHEM) was detected by immunohistochemistry and semi-quantitative reverse transcription-polymerase chain reaction analyses. Correlations between CEP55 expression and clinicopathological factors were analyzed using χ2 test. The log-rank test was employed to calculate survival rate. A Cox regression multivariate analysis was performed to determine independent prognostic factors. The results demonstrated that CEP55 expression in ESCC was significantly higher than that of CHEM (P<0.001). Overexpression of CEP55 was significantly associated with differentiation degree (P=0.022), T stage (P=0.019), lymph node metastasis (P=0.033), clinicopathological staging (P=0.002) and tumor recurrence (P=0.021) in locally advanced ESCC patients. In addition, CEP55 overexpression was significantly associated with reduced overall survival of patients after surgery (P=0.012). The 5-year survival rate of patients without CEP55 overexpression was significantly higher than that of patients with CEP55 overexpression (P=0.012). Therefore, these findings suggest that CEP55 overexpression correlates with poor prognosis in locally advanced ESCC patients. PMID:28123547

  12. An advanced system model for the prediction of the clinical task performance of radiographic systems

    NASA Astrophysics Data System (ADS)

    Töpfer, Karin; Keelan, Brian W.; Sugiro, Francisca

    2007-03-01

    A flexible software tool was developed that combines predictive models for detector noise and blur with image simulation and an improved human observer model to predict the clinical task performance of existing and future radiographic systems. The model starts with high-fidelity images from a database and mathematical models of common disease features, which may be added to the images at desired contrast levels. These images are processed through the entire imaging chain including capture, the detector, image processing, and hardcopy or softcopy display. The simulated images and the viewing conditions are passed to a human observer model, which calculates the detectability index d' of the signal (disease or target feature). The visual model incorporates a channelized Hotelling observer with a luminance-dependent contrast sensitivity function and two types of internal visual system noise (intrinsic and image background-induced). It was optimized based on three independent human observer studies of target detection, and is able to predict d' over a wide range of viewing conditions, background complexities, and target spatial frequency content. A more intuitive metric of system performance, Task-Specific Detective Efficiency (TSDE), is defined to indicate how much detector improvements would translate to better radiologist performance. The TSDE is calculated as the squared ratio of d' for a system with the actual detector and a hypothetical system containing an ideal detector. A low TSDE, e.g., 5% for the detection of 0.1 mm microcalcifications in typical mammography systems, indicates that improvements in the detector characteristics are likely to translate to better detection performance. The TSDE of lung nodule detection is as high as 75% even with the detective quantum efficiency (DQE) of the detector not exceeding 24%. Applications of the model to system optimizations for flat-panel detectors, in mammography and dual energy digital radiography, are discussed.

  13. 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

  14. Advanced Train and Traffic Control Based on Prediction of Train Movement

    NASA Astrophysics Data System (ADS)

    Hiraguri, Shigeto; Hirao, Yuji; Watanabe, Ikuo; Tomii, Norio; Hase, Shinichi

    Trains are often forced to decelerate or stop between stations on commuter lines due to the delay of the preceding train. If a train stops between stations, both the travel time and the interval between trains will increase. This situation has an adverse effect on energy consumption. To solve this problem, we propose a new train control method based on the prediction of train movement and data communications between railway sub-systems. Computer simulations are carried out to verify the effect of the proposed method. As a result, it has been proved that the new method reduces the train stopping time between stations and the electric energy consumption at substations.

  15. Prediction of Dynamic Stall Characteristics Using Advanced Non-Linear Panel Methods.

    DTIC Science & Technology

    1984-04-04

    three- dimensional method , incorporating the techniques that are being examined in the two-dimensional pilot code. r.• - t... . .. -..-. .°.- S °"°"° I...RD-Ai48 453 PREDICTION OF DYNAMIC STRLL CHARACTERISTICS USING 1/1 RDVRNCED NON-LINERR PAN..(U) ANALYTICAL METHODS INC REDMOND WA B MRSKEW ET AL. 84...1 2.0 micROCOPY RESOLUTION TEST CHART hAyl0#dM. @UAU M STAUIOAPOI A VOSR-TR 84.0 97 5 Analytical methods Report 8406 FINAL REPORT Tw. ’ PREDICITON OF

  16. Usefulness of human epididymis protein 4 in predicting cytoreductive surgical outcomes for advanced ovarian tubal and peritoneal carcinoma

    PubMed Central

    Tang, Zhijian; Chang, Xiaohong; Ye, Xue; Li, Yi; Cheng, Hongyan

    2015-01-01

    Objective Human epididymis protein 4 (HE4) is a promising biomarker of epithelial ovarian cancer (EOC). But its role in assessing the primary optimal debulking (OD) of EOC remains unknown. The purpose of this study is to elucidate the ability of preoperative HE4 in predicting the primary cytoreductive outcomes in advanced EOC, tubal or peritoneal carcinoma. Methods We reviewed the records of 90 patients with advanced ovarian, tubal or peritoneal carcinoma who underwent primary cytoreduction at the Department of Obstetrics and Gynecology of Peking University People’s Hospital between November 2005 and October 2010. Preoperative serum HE4 and CA125 levels were detected with EIA kit. A receiver operating characteristic (ROC) curve was used to determine the most useful HE4 cut-off value. Logistic regression analysis was performed to identify significant preoperative clinical characteristics to predict optimal primary cytoreduction. Results OD was achieved in 47.7% (43/48) of patients. The median preoperative HE4 level for patients with OD vs. suboptimal debulking was 423 and 820 pmol/L, respectively (P<0.001). The areas under the ROC curve for HE4 and CA125 were 0.716 and 0.599, respectively (P=0.080). The most useful HE4 cut-off value was 473 pmol/L. Suboptimal cytoreduction was obtained in 66.7% (38/57) of cases with HE4 ≥473 pmol/L compared with only 27.3% (9/33) of cases with HE4 <473 pmol/L. At this threshold, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for diagnosing suboptimal debulking were 81%, 56%, 67%, and 73%, respectively. Logistic regression analysis showed that the patients with HE4 ≥473 pmol/L were less likely to achieve OD (odds ratio =5.044, P=0.002). Conclusions Preoperative serum HE4 may be helpful to predict whether optimal cytoreductive surgery could be obtained or whether extended cytoreduction would be needed by an interdisciplinary team. PMID:26157328

  17. 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.

  18. 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.

  19. 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

  20. A model to predict deflection of bevel-tipped active needle advancing in soft tissue.

    PubMed

    Datla, Naresh V; Konh, Bardia; Honarvar, Mohammad; Podder, Tarun K; Dicker, Adam P; Yu, Yan; Hutapea, Parsaoran

    2014-03-01

    Active needles are recently being developed to improve steerability and placement accuracy for various medical applications. These active needles can bend during insertion by actuators attached to their bodies. The bending of active needles enables them to be steered away from the critical organs on the way to target and accurately reach target locations previously unachievable with conventional rigid needles. These active needles combined with an asymmetric bevel-tip can further improve their steerability. To optimize the design and to develop accurate path planning and control algorithms, there is a need to develop a tissue-needle interaction model. This work presents an energy-based model that predicts needle deflection of active bevel-tipped needles when inserted into the tissue. This current model was based on an existing energy-based model for bevel-tipped needles, to which work of actuation was included in calculating the system energy. The developed model was validated with needle insertion experiments with a phantom material. The model predicts needle deflection reasonably for higher diameter needles (11.6% error), whereas largest error was observed for the smallest needle diameter (24.7% error).

  1. An InP-Based Dual-Depletion-Region Electroabsorption Modulator with Low Capacitance and Predicted High Bandwidth

    NASA Astrophysics Data System (ADS)

    Shao, Yong-Bo; Zhao, Ling-Juan; Yu, Hong-Yan; Qiu, Ji-Fang; Qiu, Ying-Ping; Pan, Jiao-Qing; Wang, Bao-Jun; Zhu, Hong-Liang; Wang, Wei

    2011-11-01

    A novel dual-depletion-region electroabsorption modulator (DDR-EAM) based on InP at 1550 nm is fabricated. The measured capacitance and extinction ratio of the DDR-EAM reveal that the dual depletion region structure can reduce the device capacitance significantly without any degradation of extinction ratio. Moreover, the bandwidth of the DDR-EAM predicted by using an equivalent circuit model is larger than twice the bandwidth of the conventional lumped-electrode EAM (L-EAM).

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. Recovery Act. Development and Validation of an Advanced Stimulation Prediction Model for Enhanced Geothermal System

    SciTech Connect

    Gutierrez, Marte

    2016-12-31

    The 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: 1) Develop a true three-dimensional hydro-thermal fracturing simulator that is particularly suited for EGS reservoir creation. 2) 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. 3) Perform discrete element/particulate modeling of proppant transport in hydraulic fractures, and use the results to improve understand of proppant flow and transport. 4) Test and validate the 3D hydro-thermal fracturing simulator against case histories of EGS energy production. 5) 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: 1) A true-3D hydro-thermal fracturing computer code that is particularly suited to EGS, 2) Documented results of scale model tests on hydro-thermal fracturing and fracture propping in an analogue crystalline rock, 3) Documented procedures and results of discrete element/particulate modeling of flow and transport of proppants for EGS applications, and 4) Database of monitoring data, with focus of Acoustic Emissions (AE) from lab scale modeling and field case histories of EGS reservoir creation.

  7. 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.

  8. Advances and challenges in biomarker development for type 1 diabetes prediction and prevention using omic technologies

    PubMed Central

    Carey, Colleen; Purohit, Sharad; She, Jin-Xiong

    2010-01-01

    Importance of the field Biomarkers are essential for the identification of high risk children as well as monitoring of prevention outcomes for type 1 diabetes (T1D). Areas covered in this review This review discusses progress, opportunities and challenges in biomarker discovery and validation using high throughput genomic, transcriptomic and proteomic technologies. The authors also suggest potential solutions to deal with the current challenges. What the reader will gain Readers will gain an overview of the current status on T1D biomarkers, an integrated review of three omic technologies, their applications and limitations for biomarker discovery and validation, and a critical discussion of the major issues encountered in biomarker development. Take home message Better biomarkers are still urgently needed for T1D prediction and prevention. The high throughput omic technologies offer great opportunities but also face significant challenges that have to be solved before their potential for biomarker development is fully realized. PMID:20885991

  9. 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.

  10. Predictive biomarkers for response to therapy in advanced colorectal/rectal adenocarcinoma.

    PubMed

    Kapur, Payal

    2012-01-01

    Over the past couple of decades, with discovery of novel targeted therapies, and expansion of our understanding of the molecular biology of rectal cancer, there has been an emergence of a wide variety of therapeutic options designed to facilitate a personalized approach for the treatment of this malignancy. A plethora of new prognostic and predictive single genes and proteins are being discovered that may reflect susceptibility and/or resistance to therapy. Pathologic complete response rates occur in 10-16% of patients and have been shown to correlate with both disease-free and overall survival. However, the response to neoadjuvant therapy remains variable and unpredictable. In this review, some of these novel markers are discussed for their potential use as pharmacogenetic predictors for specific therapy, drug toxicity, and disease outcome.

  11. 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.

  12. Voluntary Ethanol Intake Predicts κ-Opioid Receptor Supersensitivity and Regionally Distinct Dopaminergic Adaptations in Macaques

    PubMed Central

    Siciliano, Cody A.; Calipari, Erin S.; Cuzon Carlson, Verginia C.; Helms, Christa M.; Lovinger, David M.; Grant, Kathleen A.

    2015-01-01

    The dopaminergic projections from the ventral midbrain to the striatum have long been implicated in mediating motivated behaviors and addiction. Previously it was demonstrated that κ-opioid receptor (KOR) signaling in the striatum plays a critical role in the increased reinforcing efficacy of ethanol following ethanol vapor exposure in rodent models. Although rodents have been used extensively to determine the neurochemical consequences of chronic ethanol exposure, establishing high levels of voluntary drinking in these models has proven difficult. Conversely, nonhuman primates exhibit similar intake and pattern to humans in regard to drinking. Here we examine the effects of chronic voluntary ethanol self-administration on dopamine neurotransmission and the ability of KORs to regulate dopamine release in the dorsolateral caudate (DLC) and nucleus accumbens (NAc) core. Using voltammetry in brain slices from cynomolgus macaques after 6 months of ad libitum ethanol drinking, we found increased KOR sensitivity in both the DLC and NAc. The magnitude of ethanol intake predicted increases in KOR sensitivity in the NAc core, but not the DLC. Additionally, ethanol drinking increased dopamine release and uptake in the NAc, but decreased both of these measures in the DLC. These data suggest that chronic daily drinking may result in regionally distinct disruptions of striatal outputs. In concert with previous reports showing increased KOR regulation of drinking behaviors induced by ethanol exposure, the strong relationship between KOR activity and voluntary ethanol intake observed here gives further support to the hypothesis that KORs may provide a promising pharmacotherapeutic target in the treatment of alcoholism. PMID:25878269

  13. 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

  14. 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

  15. Comparison of Predicted and Measured Soil Retention Curve in Lombardy Region Northern of Italy

    NASA Astrophysics Data System (ADS)

    Wassar, Fatma; Rienzner, Michele; Chiaradia, Enrico Antonio; Gandolfi, Claudio

    2013-04-01

    Water retention characteristics are crucial input parameters in any modeling study on water flow and solute transport. These properties are difficult to measure and therefore the use of both direct and indirect methods is required in order to adequately describe them with sufficient accuracy. Several field methods, laboratory methods and theoretical models for such determinations exist, each having their own limitations and advantages (Stephens, 1994). Therefore, extensive comparisons between estimated, field and laboratory results to determine it still requires their validity for a range of different soils and specific cases. This study attempts to make a contribution specifically in this connection. The soil water retention characteristics were determined in two representative sites (PMI-1 and PMI-5) located in Landriano field, in Lombardy region, northern Italy. In the laboratory, values of both volumetric water content (θ) and soil water matric potential (h) are measured in the same sample using the tensiometric box and pressure plate apparatus. Field determination of soil water retention involved measurements of soil water content with SENTEK probes, and matric potential with tensiometers. The retention curve characteristics were also determined using some of the most commonly cited and some recently developed PTFs that use soil properties such as particle-size distribution (sand, silt, and clay content), organic matter or organic Carbon content, and dry bulk density. Field methods are considered to be more representative than laboratory and estimation methods for determining water retention characteristics (Marion et al., 1996). Therefore, field retention curves were compared against retention curves obtained from laboratory measurements and PTFs estimations. The performances of laboratory and PTFs in predicting field measured data were evaluated using root mean square error (RMSE) and bias. The comparison showed that laboratory measurements were the most

  16. Are Regional Operational Wind-Waves Models Usable to Predict Coastal and Nearshore Wave Climate?

    NASA Astrophysics Data System (ADS)

    Lambert, A. P.; Neumeier, U.; Jacob, D.; Savard, J.

    2012-12-01

    Estuary and Gulf of Saint-Lawrence (EGSL) shores are subjected to strong erosion linked to storminess. Due to the likely presence of sea ice and to the high tidal range affecting the north shores of the EGSL, it is impossible to measure wave parameters at depth lesser than 10m from November to April, i.e. the storm period. Winter waves can be forecasted by the operational Regional Deterministic Wave Prediction System (RDWPS) from the Canadian Meteorological Center (CMC). However, spatial resolution of the RDWPS in the EGSL is 0.04°x0.06° (5x5km @ 49°N), which theoretically limits its application to areas of low bathymetric gradients and does neither destined it to the prediction of coastal nor nearshore waves. Nevertheless, given the lack of nearshore wave measurements during the late fall and winter period, it might seem wise to use the RDWPS data for operational purposes of warning and coastal structure design. This research thus evaluates the performance of the RDWPS for this period, both in the coastal and nearshore areas of a complex bathymetric domain. Our method is based on: 1. A direct comparison of RDWPS wave parameters time series to those produced from two instruments berthed in front of Sept-Iles, North Shore, Quebec (50° 10.3' N 66° 13.5' W). M1 mooring is deployed permanently throughout the year at -32m MSL, while M2 is deployed from April to November at -8m MSL. These comparisons are made from 01/10/2010 to 31/12/2011 (winter period). 2. A high-resolution (0.2x0.2km) coastal wind-wave model (SWAN v.40.85) is locally nested in the EGSL RDWPS domain in order to propagate waves from quasi-infinite depth to the shore at the site location, including moorings positions. Our implementation uses the same source terms, physics and inputs as in the RDWPS implementation of WAM. This allows producing reference time series for the winter at the M2 location. RDWPS data are thus also compared with these model outputs for the same period as 1. Our results show

  17. 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

  18. 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.

  19. Influence of lateral and top boundary conditions on regional air quality prediction: A multiscale study coupling regional and global chemical transport models

    NASA Astrophysics Data System (ADS)

    Tang, Youhua; Carmichael, Gregory R.; Thongboonchoo, Narisara; Chai, Tianfeng; Horowitz, Larry W.; Pierce, Robert B.; Al-Saadi, Jassim A.; Pfister, Gabriele; Vukovich, Jeffrey M.; Avery, Melody A.; Sachse, Glen W.; Ryerson, Thomas B.; Holloway, John S.; Atlas, Elliot L.; Flocke, Frank M.; Weber, Rodney J.; Huey, L. Gregory; Dibb, Jack E.; Streets, David G.; Brune, William H.

    2007-05-01

    The sensitivity of regional air quality model to various lateral and top boundary conditions is studied at 2 scales: a 60 km domain covering the whole USA and a 12 km domain over northeastern USA. Three global models (MOZART-NCAR, MOZART-GFDL and RAQMS) are used to drive the STEM-2K3 regional model with time-varied lateral and top boundary conditions (BCs). The regional simulations with different global BCs are examined using ICARTT aircraft measurements performed in the summer of 2004, and the simulations are shown to be sensitive to the boundary conditions from the global models, especially for relatively long-lived species, like CO and O3. Differences in the mean CO concentrations from three different global-model boundary conditions are as large as 40 ppbv, and the effects of the BCs on CO are shown to be important throughout the troposphere, even near surface. Top boundary conditions show strong effect on O3 predictions above 4 km. Over certain model grids, the model's sensitivity to BCs is found to depend not only on the distance from the domain's top and lateral boundaries, downwind/upwind situation, but also on regional emissions and species properties. The near-surface prediction over polluted area is usually not as sensitive to the variation of BCs, but to the magnitude of their background concentrations. We also test the sensitivity of model to temporal and spatial variations of the BCs by comparing the simulations with time-varied BCs to the corresponding simulations with time-mean and profile BCs. Removing the time variation of BCs leads to a significant bias on the variation prediction and sometime causes the bias in predicted mean values. The effect of model resolution on the BC sensitivity is also studied.

  20. 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.

  1. 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

  2. Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies.

    PubMed

    Tortolina, Lorenzo; Duffy, David J; Maffei, Massimo; Castagnino, Nicoletta; Carmody, Aimée M; Kolch, Walter; Kholodenko, Boris N; De Ambrosi, Cristina; Barla, Annalisa; Biganzoli, Elia M; Nencioni, Alessio; Patrone, Franco; Ballestrero, Alberto; Zoppoli, Gabriele; Verri, Alessandro; Parodi, Silvio

    2015-03-10

    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.

  3. 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…

  4. Recent advances in computational predictions of NMR parameters for the structure elucidation of carbohydrates: methods and limitations.

    PubMed

    Toukach, Filip V; Ananikov, Valentine P

    2013-11-07

    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.

  5. 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 ...

  6. Pre-adjuvant chemotherapy leukocyte count may predict the outcome for advanced gastric cancer after radical resection.

    PubMed

    Pei, Dong; Zhu, Fang; Chen, Xiaofeng; Qian, Jing; He, Shaohua; Qian, Yingying; Shen, Hua; Liu, Yiqian; Xu, Jiali; Shu, Yongqian

    2014-03-01

    Gastric cancer (GC) has a high morbidity worldwide each year especially in China and advanced GC is well known with poor prognosis, for which surgical resection combine adjuvant chemotherapy is the optimal choice for therapy. Leukocyte is an important index during the treatment for its influence on drugs' dosage and tolerance. Therefore, peripheral blood leukocyte and its subsets during adjuvant chemotherapy may have great clinical value for predicting prognostic. In this retrospective study, we showed the distribution of white blood cell and its subsets in the baseline period before adjuvant chemotherapy in 399 patients who underwent radical resection for advanced GC from January 1, 2008 to August 31, 2012. We investigated the relationship between leukocyte count and overall survival (OS) as well as disease-free survival (DFS). In these patients, females were more likely to have less white blood cells after operation (P=0.016). Patients with pre-chemotherapy leukocyte count less than 4×10(9)/L got worse DFS (P=0.028) and OS (P=0.016). In multivariate analysis, tumor size ≥ 6cm (P=0.033), TNM stage IV (P=0.024), vascular or nerval invasion (P=0.005) and leukocyte count less than 4.0×10(9)/L (P=0.019) was associated with poor DFS. TNM stage IV (P=0.008), vascular or nerval invasion (P=0.001) and lower leukocyte count (P=0.045) were independent risk factors for poor OS. Taken together, our findings suggest that pre-adjuvant chemotherapy peripheral blood leukocyte count correlates with clinical outcome of patients with advanced GC after radical resection.

  7. 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.

  8. Advanced Procedures for Long-Term Creep Data Prediction for 2.25 Chromium Steels

    NASA Astrophysics Data System (ADS)

    Whittaker, Mark T.; Wilshire, Brian

    2013-01-01

    A critical review of recent creep studies concluded that traditional approaches such as steady-state behavior, power law equations, and the view that diffusional creep mechanisms are dominant at low stresses should be seriously reconsidered. Specifically, creep strain rate against time curves show that a decaying primary rate leads into an accelerating tertiary stage, giving a minimum rather than a secondary period. Conventional steady-state mechanisms should therefore be abandoned in favor of an understanding of the processes governing strain accumulation and the damage phenomena causing tertiary creep and fracture. Similarly, creep always takes place by dislocation processes, with no change to diffusional creep mechanisms with decreasing stress, negating the concept of deformation mechanism maps. Alternative descriptions are then provided by normalizing the applied stress through the ultimate tensile stress and yield stress at the creep temperature. In this way, the resulting Wilshire equations allow accurate prediction of 100,00 hours of creep data using only property values from tests lasting 5000 hours for a series of 2.25 chromium steels, namely grades 22, 23, and 24.

  9. Predictive transport simulations of real-time profile control in JET advanced tokamak plasmas

    NASA Astrophysics Data System (ADS)

    Tala, T.; Laborde, L.; Mazon, D.; Moreau, D.; Corrigan, G.; Crisanti, F.; Garbet, X.; Heading, D.; Joffrin, E.; Litaudon, X.; Parail, V.; Salmi, A.; EFDA-JET workprogramme, contributors to the

    2005-09-01

    Predictive, time-dependent transport simulations with a semi-empirical plasma model have been used in closed-loop simulations to control the q-profile and the strength and location of the internal transport barrier (ITB). Five transport equations (Te, Ti, q, ne, vΦ) are solved, and the power levels of lower hybrid current drive, NBI and ICRH are calculated in a feedback loop determined by the feedback controller matrix. The real-time control (RTC) technique and algorithms used in the transport simulations are identical to those implemented and used in JET experiments (Laborde L. et al 2005 Plasma Phys. Control. Fusion 47 155 and Moreau D. et al 2003 Nucl. Fusion 43 870). The closed-loop simulations with RTC demonstrate that varieties of q-profiles and pressure profiles in the ITB can be achieved and controlled simultaneously. The simulations also showed that with the same RTC technique as used in JET experiments, it is possible to sustain the q-profiles and pressure profiles close to their set-point profiles for longer than the current diffusion time. In addition, the importance of being able to handle the multiple time scales to control the location and strength of the ITB is pointed out. Several future improvements and perspectives of the RTC scheme are presented.

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. 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.

  15. Predictive value of advanced glycation end products for the development of post-infarction heart failure: a preliminary report

    PubMed Central

    2012-01-01

    Background Since post-infarction heart failure (HF) determines a great morbidity and mortality, and given the physiopathology implications of advanced glycation end products (AGE) in the genesis of myocardial dysfunction, it was intended to analyze the prognostic value of these molecules in order to predict post-infarction HF development. Methods A prospective clinical study in patients after first acute coronary syndrome was conducted. The follow-up period was consisted in 1 year. In 194 patients consecutively admitted in the coronary unit for myocardial infarct fluorescent AGE levels were measured. The association between glycaemic parameters and the development of post-infarction HF were analyzed in those patients. Finally, we identified the variables with independent predictor value by performing a multivariate analysis of Hazard ratio for Cox regression. Results Eleven out of 194 patients (5.6%) developed HF during follow-up (median: 1.0 years [0.8 - 1.5 years]). Even though basal glucose, fructosamine and glycated haemoglobin were significant predictive factors in the univariate analysis, after being adjusted by confounding variables and AGE they lost their statistical signification. Only AGE (Hazard Ratio 1.016, IC 95%: 1.006-1.026; p<0,001), together with NT-proBNP and the infarct extension were predictors for post-infarction HF development, where AGE levels over the median value 5-fold increased the risk of HF development during follow-up. Conclusions AGE are an independent marker of post-infarction HF development risk. PMID:22909322

  16. Neoadjuvant chemotherapy in women with large and locally advanced breast cancer: chemoresistance and prediction of response to drug therapy.

    PubMed

    Chuthapisith, S; Eremin, J M; El-Sheemy, M; Eremin, O

    2006-08-01

    Patients with large and locally advanced breast cancer (LLABC) present with a therapeutic challenge and undergo multimodality treatment. Many such patients receive neoadjuvant chemotherapy (NAC) prior to surgery. However, a number of these patients do not respond well to NAC and only a percentage (usually less than 30%) obtains a complete or optimal response. A range of mechanisms are believed to be involved in this chemoresistance, including ATP binding cassette (ABC) transporter overexpression, dysregulation of apoptosis and possibly increased numbers of cancer stem cells. The chemoresistant processes may be due to more than one mechanism. The ability to predict a response to NAC would be beneficial, targeting expensive and toxic drug treatment to those likely to respond and providing a therapeutic strategy for further post-operative chemotherapy. Currently, many biomarkers have been studied with a view to establishing a predictor of response. However, no single biomarker appears to be effective. Genomics is a novel biotechnological process which is being used to predict response to drug therapy; this work is currently at an early stage of development

  17. 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.

  18. 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

  19. Prediction of intrinsically disordered regions in proteins using signal processing methods: application to heat-shock proteins.

    PubMed

    Vojisavljevic, Vuk; Pirogova, Elena

    2016-12-01

    Heat-shock protein (HSP)-based immunotherapy is believed to be a promising area of development for cancer treatment as such therapy is characterized by a unique approach to every tumour. It was shown that by inhibition of HSPs it is possible to induce apoptotic cell death in cancer cells. Interestingly, there are a great number of disordered regions in proteins associated with cancer, cardiovascular and neurodegenerative diseases, signalling, and diabetes. HSPs and some specific enzymes were shown to have these disordered regions in their primary structures. The experimental studies of HSPs confirmed that their intrinsically disordered (ID) regions are of functional importance. These ID regions play crucial roles in regulating the specificity of interactions between dimer complexes and their interacting partners. Because HSPs are overexpressed in cancer, predicting the locations of ID regions and binding sites in these proteins will be important for developing novel cancer therapeutics. In our previous studies, signal processing methods have been successfully used for protein structure-function analysis (i.e. for determining functionally important amino acids and the locations of protein active sites). In this paper, we present and discuss a novel approach for predicting the locations of ID regions in the selected cancer-related HSPs.

  20. 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.

  1. 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

  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. Regional differences in brain volume predict the acquisition of skill in a complex real-time strategy videogame.

    PubMed

    Basak, Chandramallika; Voss, Michelle W; Erickson, Kirk I; Boot, Walter R; Kramer, Arthur F

    2011-08-01

    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 be useful in predicting the acquisition of skill in complex tasks, such as strategy-based video games. Twenty older adults were trained for over 20 h to play Rise of Nations, a complex real-time strategy game. These adults showed substantial improvements over the training period in game performance. MRI scans obtained prior to training revealed that the volume of a number of brain regions, which have been previously associated with subsets of the trained skills, predicted a substantial amount of variance in learning on the complex game. Thus, regional differences in brain volume can predict learning in complex tasks that entail the use of a variety of perceptual, cognitive and motor processes.

  4. Influence of Elevation Data Resolution on Spatial Prediction of Colluvial Soils in a Luvisol Region

    PubMed Central

    Penížek, Vít; Zádorová, Tereza; Kodešová, Radka; Vaněk, Aleš

    2016-01-01

    The development of a soil cover is a dynamic process. Soil cover can be altered within a few decades, which requires updating of the legacy soil maps. Soil erosion is one of the most important processes quickly altering soil cover on agriculture land. Colluvial soils develop in concave parts of the landscape as a consequence of sedimentation of eroded material. Colluvial soils are recognised as important soil units because they are a vast sink of soil organic carbon. Terrain derivatives became an important tool in digital soil mapping and are among the most popular auxiliary data used for quantitative spatial prediction. Prediction success rates are often directly dependent on raster resolution. In our study, we tested how raster resolution (1, 2, 3, 5, 10, 20 and 30 meters) influences spatial prediction of colluvial soils. Terrain derivatives (altitude, slope, plane curvature, topographic position index, LS factor and convergence index) were calculated for the given raster resolutions. Four models were applied (boosted tree, neural network, random forest and Classification/Regression Tree) to spatially predict the soil cover over a 77 ha large study plot. Models training and validation was based on 111 soil profiles surveyed on a regular sampling grid. Moreover, the predicted real extent and shape of the colluvial soil area was examined. In general, no clear trend in the accuracy prediction was found without the given raster resolution range. Higher maximum prediction accuracy for colluvial soil, compared to prediction accuracy of total soil cover of the study plot, can be explained by the choice of terrain derivatives that were best for Colluvial soils differentiation from other soil units. Regarding the character of the predicted Colluvial soils area, maps of 2 to 10 m resolution provided reasonable delineation of the colluvial soil as part of the cover over the study area. PMID:27846230

  5. 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.

  6. 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

  7. Regional White Matter Damage Predicts Speech Fluency in Chronic Post-Stroke Aphasia

    PubMed Central

    Basilakos, Alexandra; Fillmore, Paul T.; Rorden, Chris; Guo, Dazhou; Bonilha, Leonardo; Fridriksson, Julius

    2014-01-01

    Recently, two different white matter regions that support speech fluency have been identified: the aslant tract and the anterior segment of the arcuate fasciculus (ASAF). The role of the ASAF was demonstrated in patients with post-stroke aphasia, while the role of the aslant tract shown in primary progressive aphasia. Regional white matter integrity appears to be crucial for speech production; however, the degree that each region exerts an independent influence on speech fluency is unclear. Furthermore, it is not yet defined if damage to both white matter regions influences speech in the context of the same neural mechanism (stroke-induced aphasia). This study assessed the relationship between speech fluency and quantitative integrity of the aslant region and the ASAF. It also explored the relationship between speech fluency and other white matter regions underlying classic cortical language areas such as the uncinate fasciculus and the inferior longitudinal fasciculus (ILF). Damage to these regions, except the ILF, was associated with speech fluency, suggesting synergistic association of these regions with speech fluency in post-stroke aphasia. These observations support the theory that speech fluency requires the complex, orchestrated activity between a network of pre-motor, secondary, and tertiary associative cortices, supported in turn by regional white matter integrity. PMID:25368572

  8. 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.

  9. Regional brain activity and strenuous exercise: predicting affective responses using EEG asymmetry.

    PubMed

    Hall, Eric E; Ekkekakis, Panteleimon; Petruzzello, Steven J

    2007-05-01

    Previous research using the model proposed by Davidson has shown that resting frontal electroencephalographic (EEG) asymmetry can predict affective responses to aerobic exercise at moderate intensities. Specifically, greater relative left frontal activity has been shown to predict positive affect (i.e., energy) following exercise. The purpose of this study was to determine if resting frontal EEG asymmetry would predict affective responses following strenuous exercise. Thirty participants (13 women, 17 men) completed a maximal graded exercise test on a treadmill. EEG was recorded prior to exercise. Affect was measured by the Activation Deactivation Adjective Check List prior to the graded exercise test, immediately following, 10 and 20-min following exercise. Greater relative left frontal activity predicted tiredness and calmness during recovery from exercise, but not tension or energy. Tiredness and calmness following exercise covaried, suggesting that tiredness following exercise might not have been linked with displeasure. These findings offer further support for the link between EEG asymmetry and affective responses to exercise.

  10. 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

  11. 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.

  12. Evaluation of plasma microRNA levels to predict insensitivity of patients with advanced lung adenocarcinomas to pemetrexed and platinum.

    PubMed

    Zhu, Jinghua; Qi, Yuhua; Wu, Jianzhong; Shi, Meiqi; Feng, Jifeng; Chen, Longbang

    2016-12-01

    Pemetrexed combined with platinum is a first-line therapy used to treat patients with advanced non-small cell lung cancer (NSCLC) that exhibit negative or unknown epidermal growth factor receptor (EGFR) mutational status or anaplastic lymphoma kinase (ALK) rearrangements. Lung adenocarcinoma (LAC) is the primary type of NSCLC. In order to prevent overtreatment, it is necessary to identify patients with LAC who may not benefit from certain chemotherapies. Patients recruited in the present study (n=129) were diagnosed with advanced LAC and received first-line pemetrexed and platinum-based chemotherapy. A microRNA (miR) microarray was used to screen the plasma miR expression profiles in a screening set of eight patients prior to and following treatment. Specifically, plasma miR-25, miR-21, miR-27b, miR-326, miR-483-5p and miR-920 were selected for reverse transcription-quantitative polymerase chain reaction analysis in a training set (n=44) prior to treatment. The screening and training set patients were all non-smokers with no prior history of serious or chronic disease. The ∆∆Cq values of these miRs were compared between the group that showed benefit from pemetrexed and platinum treatment and the group that did not. Consequently, the ∆∆Cq values of miR-25, miR-21, miR-27b and miR-326 were further determined in a validation set (n=77). The results of the present study demonstrate that plasma expression levels of miR-25, miR-21, miR-27b and miR-326, in the training and validation sets prior to treatment, were significantly different between the benefit and non-benefit groups (P≤0.001). The expression of miR-25, miR-21, miR-27b and miR-326 was upregulated in the non-benefit group and this elevation was positively correlated with decreased progression-free survival (PFS; P≤0.001). In addition, the predictive power of each miR was evaluated through receiver operating characteristic curves, in which miR-25 exhibited the highest degree of accuracy (area under

  13. Brain size and visual environment predict species differences in paper wasp sensory processing brain regions (hymenoptera: vespidae, polistinae).

    PubMed

    O'Donnell, Sean; Clifford, Marie R; DeLeon, Sara; Papa, Christopher; Zahedi, Nazaneen; Bulova, Susan J

    2013-01-01

    The mosaic brain evolution hypothesis predicts that the relative volumes of functionally distinct brain regions will vary independently and correlate with species' ecology. Paper wasp species (Hymenoptera: Vespidae, Polistinae) differ in light exposure: they construct open versus enclosed nests and one genus (Apoica) is nocturnal. We asked whether light environments were related to species differences in the size of antennal and optic processing brain tissues. Paper wasp brains have anatomically distinct peripheral and central regions that process antennal and optic sensory inputs. We measured the volumes of 4 sensory processing brain regions in paper wasp species from 13 Neotropical genera including open and enclosed nesters, and diurnal and nocturnal species. Species differed in sensory region volumes, but there was no evidence for trade-offs among sensory modalities. All sensory region volumes correlated with brain size. However, peripheral optic processing investment increased with brain size at a higher rate than peripheral antennal processing investment. Our data suggest that mosaic and concerted (size-constrained) brain evolution are not exclusive alternatives. When brain regions increase with brain size at different rates, these distinct allometries can allow for differential investment among sensory modalities. As predicted by mosaic evolution, species ecology was associated with some aspects of brain region investment. Nest architecture variation was not associated with brain investment differences, but the nocturnal genus Apoica had the largest antennal:optic volume ratio in its peripheral sensory lobes. Investment in central processing tissues was not related to nocturnality, a pattern also noted in mammals. The plasticity of neural connections in central regions may accommodate evolutionary shifts in input from the periphery with relatively minor changes in volume.