Science.gov

Sample records for advanced predictive activity

  1. 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

  2. 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). PMID:24296105

  3. Advances in predicting acute GVHD

    PubMed Central

    Harris, Andrew C.; Ferrara, James L.M.; Levine, John E.

    2012-01-01

    Summary Acute graft-versus-host disease (GVHD) is a leading cause of non-relapse mortality following allogeneic haematopoietic cell transplantation. Attempts to improve treatment response in clinically-established GVHD have not improved overall survival, often due to the increased risk of infectious complications. Alternative approaches to decrease GVHD-related morbidity and mortality have focused on the ability to predict GVHD prior to clinical manifestation in an effort to provide an opportunity to abort GVHD development, and to gain new insights into GVHD pathophysiology. This review outlines the research efforts to date that have identified clinical and laboratory-based factors that are predictive of acute GVHD and describes future directions in developing algorithms that will improve the ability to predict the development of clinically relevant GVHD. PMID:23205489

  4. Advancing Drought Understanding, Monitoring and Prediction

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

    , focused and coordinated research efforts are needed, drawing from excellence across the broad drought research community. To meet this challenge, National Oceanic and Atmospheric Administration (NOAA)'s Drought Task Force was established in October 2011 with the ambitious goal of achieving significant new advances in the ability to understand, monitor, and predict drought over North America. The Task Force (duration of October 2011-September 2014) is an initiative of NOAA's Climate Program Office Modeling, Analysis, Predictions, and Projections (MAPP) program in partnership with NIDIS. It brings together over 30 leading MAPP-funded drought scientists from multiple academic and federal institutions [involves scientists from NOAA's research laboratories and centers, the National Aeronautics and Space Administration (NASA), U.S. Department of Agriculture, National Center for Atmospheric Research (NCAR), and many universities] in a concerted research effort that builds on individual MAPP research projects. These projects span the wide spectrum of drought research needed to make fundamental advances, from those aimed at the basic understanding of drought mechanisms to those aimed at testing new drought monitoring and prediction tools for operational and service purposes (as part of NCEP's Climate Test Bed). The Drought Task Force provides focus and coordination to MAPP drought research activities and also facilitates synergies with other national and international drought research efforts, including those by the GDIS.

  5. Recent advances in turbulence prediction

    NASA Astrophysics Data System (ADS)

    Bhattacharya, Atreyee

    2012-08-01

    Turbulence in the upper troposphere and the lower stratosphere (8-14 kilometers in altitude) is a well-known aviation hazard; it is the major cause of injuries and occasional fatalities to passengers and crew members on commercial aircraft. Jet streams, thunderstorms, flow over mountains, and even the passage of other aircraft cause turbulence. However, the lack of precise observational data (which is still mainly from pilots reporting turbulence) and a clear understanding of the processes that cause turbulence make it difficult to accurately forecast aviation-scale turbulence. Hence, upper troposphere and lower stratosphere turbulence forecasting is an area of active research.

  6. 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…

  7. Predicting intrinsic brain activity.

    PubMed

    Craddock, R Cameron; Milham, Michael P; LaConte, Stephen M

    2013-11-15

    Multivariate supervised learning methods exhibit a remarkable ability to decode externally driven sensory, behavioral, and cognitive states from functional neuroimaging data. Although they are typically applied to task-based analyses, supervised learning methods are equally applicable to intrinsic effective and functional connectivity analyses. The obtained models of connectivity incorporate the multivariate interactions between all brain regions simultaneously, which will result in a more accurate representation of the connectome than the ones available with standard bivariate methods. Additionally the models can be applied to decode or predict the time series of intrinsic brain activity of a region from an independent dataset. The obtained prediction accuracy provides a measure of the integration between a brain region and other regions in its network, as well as a method for evaluating acquisition and preprocessing pipelines for resting state fMRI data. This article describes a method for learning multivariate models of connectivity. The method is applied in the non-parametric prediction accuracy, influence, and reproducibility-resampling (NPAIRS) framework, to study the regional variation of prediction accuracy and reproducibility (Strother et al., 2002). The resulting spatial distribution of these metrics is consistent with the functional hierarchy proposed by Mesulam (1998). Additionally we illustrate the utility of the multivariate regression connectivity modeling method for optimizing experimental parameters and assessing the quality of functional neuroimaging data. PMID:23707580

  8. 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.

  9. 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.

  10. 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

  11. Improved methodology for temperature predictions in advanced reactors

    SciTech Connect

    Ambrosek, R.G.; Chang, G.S.

    1995-10-01

    Advanced nuclear reactors maximize power and/or flux levels for increased performance levels. One of the challenges is accurate prediction of temperatures in the structural components and experiments. An improved methodology utilizing the computer codes MCNP and ABAQUS has been demonstrated in instrumented experiments at the Advanced Test Reactor. The analytical predictions have shown excellent agreement with the measured results.

  12. 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.

  13. 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.

  14. 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

  15. Predictable nonlinear dynamics: Advances and limitations

    SciTech Connect

    Anosov, L.A.; Butkovskii, O.Y.; Kravtsov, Y.A.; Surovyatkina, E.D.

    1996-06-01

    Methods for reconstruction chaotic dynamical system structure directly from experimental time series are described. Effectiveness of general methods is illustrated with the results of numerical simulation. It is of common interest that from the single time series it is possible to reconstruct a set of interconnected variables. Predictive power of dynamical models, provided by the nonlinear dynamics inverse problem solution, is limited firstly by the noise level in the system under study and is characterized by the horizon of predictability. New physical results are presented, concerning nonstationary and bifurcation nonlinear systems: (1) algorithms for revealing of nonstationarity in random-like chaotic time-series are suggested based on discriminant analysis with nonlinear discriminant function; (2) an opportunity is established to predict the final state in bifurcation system with quickly varying control parameters; (3) hysteresis is founded out in bifurcation system with quickly varying parameters; (4) delayed correlation {l_angle}noise-prediction error{r_angle} in chaotic systems is revealed. {copyright} {ital 1996 American Institute of Physics.}

  16. Development of a numerical scheme to predict geomagnetic storms after intense solar events and geomagnetic activity 27 days in advance. Final report, 6 Aug 86-16 Nov 90

    SciTech Connect

    Akasofu, S.I.; Lee, L.H.

    1991-02-01

    The modern geomagnetic storm prediction scheme should be based on a numerical simulation method, rather than on a statistical result. Furthermore, the scheme should be able to predict the geomagnetic storm indices, such as the Dst and AE indices, as a function of time. By recognizing that geomagnetic storms are powered by the solar wind-magnetosphere generator and that its power is given in terms of the solar wind speed, the interplanetary magnetic field (IMF) magnitude and polar angle, the authors have made a major advance in predicting both flare-induced storms and recurrent storms. Furthermore, it is demonstrated that the prediction scheme can be calibrated using the interplanetary scintillation (IPS) observation, when the solar disturbance advances about half-way to the earth. It is shown, however, that we are still far from a reliable prediction scheme. The prediction of the IMF polar angle requires future advance in understanding characteristics of magnetic clouds.

  17. DNA Methyltransferase Activity Assays: Advances and Challenges

    PubMed Central

    Poh, Wan Jun; Wee, Cayden Pang Pee; Gao, Zhiqiang

    2016-01-01

    DNA methyltransferases (MTases), a family of enzymes that catalyse the methylation of DNA, have a profound effect on gene regulation. A large body of evidence has indicated that DNA MTase is potentially a predictive biomarker closely associated with genetic disorders and genetic diseases like cancer. Given the attention bestowed onto DNA MTases in molecular biology and medicine, highly sensitive detection of DNA MTase activity is essential in determining gene regulation, epigenetic modification, clinical diagnosis and therapeutics. Conventional techniques such as isotope labelling are effective, but they often require laborious sample preparation, isotope labelling, sophisticated equipment and large amounts of DNA, rendering them unsuitable for uses at point-of-care. Simple, portable, highly sensitive and low-cost assays are urgently needed for DNA MTase activity screening. In most recent technological advances, many alternative DNA MTase activity assays such as fluorescent, electrochemical, colorimetric and chemiluminescent assays have been proposed. In addition, many of them are coupled with nanomaterials and/or enzymes to significantly enhance their sensitivity. Herein we review the progress in the development of DNA MTase activity assays with an emphasis on assay mechanism and performance with some discussion on challenges and perspectives. It is hoped that this article will provide a broad coverage of DNA MTase activity assays and their latest developments and open new perspectives toward the development of DNA MTase activity assays with much improved performance for uses in molecular biology and clinical practice. PMID:26909112

  18. 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.

  19. Predicting Malignancy in Thyroid Nodules: Molecular Advances

    PubMed Central

    Melck, Adrienne L.; Yip, Linwah

    2016-01-01

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

  20. 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.

  1. 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

  2. CRAFFT: An Activity Prediction Model based on Bayesian Networks

    PubMed Central

    Nazerfard, Ehsan; Cook, Diane J.

    2014-01-01

    Recent advances in the areas of pervasive computing, data mining, and machine learning offer unique opportunities to provide health monitoring and assistance for individuals facing difficulties to live independently in their homes. Several components have to work together to provide health monitoring for smart home residents including, but not limited to, activity recognition, activity discovery, activity prediction, and prompting system. Compared to the significant research done to discover and recognize activities, less attention has been given to predict the future activities that the resident is likely to perform. Activity prediction components can play a major role in design of a smart home. For instance, by taking advantage of an activity prediction module, a smart home can learn context-aware rules to prompt individuals to initiate important activities. In this paper, we propose an activity prediction model using Bayesian networks together with a novel two-step inference process to predict both the next activity features and the next activity label. We also propose an approach to predict the start time of the next activity which is based on modeling the relative start time of the predicted activity using the continuous normal distribution and outlier detection. To validate our proposed models, we used real data collected from physical smart environments. PMID:25937847

  3. 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.

  4. Advanced Light Source Activity Report 2000

    SciTech Connect

    Greiner, A.; Moxon, L.; Robinson, A.; Tamura, L.

    2001-04-01

    This is an annual report, detailing activities at the Advanced Light Source for the year 2000. It includes highlights of scientific research by users of the facility as well as information about the development of the facility itself.

  5. 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. PMID:26504848

  6. 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

  7. Solar activity predicted with artificial intelligence

    NASA Astrophysics Data System (ADS)

    Lundstedt, Henrik

    The variability of solar activity has been described as a non-linear chaotic dynamic system. AI methods are therefore especially suitable for modelling and predicting solar activity. Many indicators of the solar activity have been used, such as sunspot numbers, F 10.7 cm solar radio flux, X-ray flux, and magnetic field data. Artificial neural networks have also been used by many authors to predict solar cycle activity. Such predictions will be discussed. A new attempt to predict the solar activity using SOHO/MDI high-time resolution solar magnetic field data is discussed. The purpose of this new attempt is to be able to predict episodic events and to predict occurrence of coronal mass ejections. These predictions will be a part of the Lund Space Weather Model.

  8. Advanced Placement Economics. Macroeconomics: Student Activities.

    ERIC Educational Resources Information Center

    Morton, John S.

    This book is designed to help advanced placement students better understand macroeconomic concepts through various activities. The book contains 6 units with 64 activities, sample multiple-choice questions, sample short essay questions, and sample long essay questions. The units are entitled: (1) "Basic Economic Concepts"; (2) "Measuring Economic…

  9. Advanced Placement Economics. Microeconomics: Student Activities.

    ERIC Educational Resources Information Center

    Morton, John S.

    This book is designed to help advanced placement students better understand microeconomic concepts through various activities. The book contains 5 units with 73 activities, sample multiple-choice questions, sample short essay questions, and sample long essay questions. The units are entitled: (1) "The Basic Economic Problem"; (2) "The Nature and…

  10. 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

    2016-04-01

    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.

  11. 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.

  12. Prediction and monitoring of volcanic activities

    SciTech Connect

    Sudradjat, A.

    1986-07-01

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

  13. 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.

  14. A Global and Regional Multi-scale Advanced Prediction System

    NASA Astrophysics Data System (ADS)

    Chen, D.; Xue, J.; Yang, X.; Zhang, H.; Liu, J.; Jin, Z.; Huang, L.; Wu, X.

    With social progress and economic development, the requirement for providing much longer, more detailed and more accurate meteorological forecasting services with higher resolution, including climate, synoptic and meso-scale weather forecasts, and air pollution as well as forest fire warning is increased significantly. On the other hand, to meet all needs of services, the numerical weather prediction models will be- come more and more complicated, and more and more ?huge?. The costs for improve- ment and maintenance will be expensive if several NWP systems are to be developed, improved and maintained at the same time and at the same center! In this paper, a Global and Regional multi-scale Advanced Prediction model System (GRAPS) was designed to meet all needs of short, medium and long range weather forecasts as well as environmental predictions. The main features of the GRAPS model include (1) full latitude-longitude grid points; (2) multi-scale in an unified model; (3) hydrostatic or non hydrostatic hypotheses optionally(4) variable or uniform resolution in option (5) possibility to run in regional or global mode(6) finite difference in the vertical dis- cretization in option (7) semi-implicit and semi-Lagrangian scheme; (8) height terrain- following coordinate; (9) Arakawa-C variable staggering; (10) Cascade-interpolation; (11) quasi-conservation of semi-Lagrangian advection scheme combined Staniforth (1992) and Preistley (1993).

  15. Dynamo theory prediction of solar activity

    NASA Technical Reports Server (NTRS)

    Schatten, Kenneth H.

    1988-01-01

    The dynamo theory technique to predict decadal time scale solar activity variations is introduced. The technique was developed following puzzling correlations involved with geomagnetic precursors of solar activity. Based upon this, a dynamo theory method was developed to predict solar activity. The method was used successfully in solar cycle 21 by Schatten, Scherrer, Svalgaard, and Wilcox, after testing with 8 prior solar cycles. Schatten and Sofia used the technique to predict an exceptionally large cycle, peaking early (in 1990) with a sunspot value near 170, likely the second largest on record. Sunspot numbers are increasing, suggesting that: (1) a large cycle is developing, and (2) that the cycle may even surpass the largest cycle (19). A Sporer Butterfly method shows that the cycle can now be expected to peak in the latter half of 1989, consistent with an amplitude comparable to the value predicted near the last solar minimum.

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

    NASA Astrophysics Data System (ADS)

    Mariotti, A.; Barrie, D.

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Mariotti, Annarita; Pulwarty, Roger

    2014-05-01

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

  18. Advanced Extravehicular Activity Breakout Group Summary

    NASA Technical Reports Server (NTRS)

    Kosmo, Joseph J.; Perka, Alan; Walz, Carl; Cobb, Sharon; Hanford, Anthony; Eppler, Dean

    2005-01-01

    This viewgraph document summarizes the workings of the Advanced Extravehicular Activity (AEVA) Breakout group in a Martian environment. The group was tasked with: identifying potential contaminants and pathways for AEVA systems with respect to forward and backward contamination; identifying plausible mitigation alternatives and obstacles for pertinent missions; identifying topics that require further research and technology development and discuss development strategies with uncertain Planetary Protection (PP) requirements; Identifying PP requirements that impose the greatest mission/development costs; Identifying PP requirements/topics that require further definition;

  19. Advanced Active Thermal Control Systems Architecture Study

    NASA Technical Reports Server (NTRS)

    Hanford, Anthony J.; Ewert, Michael K.

    1996-01-01

    The Johnson Space Center (JSC) initiated a dynamic study to determine possible improvements available through advanced technologies (not used on previous or current human vehicles), identify promising development initiatives for advanced active thermal control systems (ATCS's), and help prioritize funding and personnel distribution among many research projects by providing a common basis to compare several diverse technologies. Some technologies included were two-phase thermal control systems, light-weight radiators, phase-change thermal storage, rotary fluid coupler, and heat pumps. JSC designed the study to estimate potential benefits from these various proposed and under-development thermal control technologies for five possible human missions early in the next century. The study compared all the technologies to a baseline mission using mass as a basis. Each baseline mission assumed an internal thermal control system; an external thermal control system; and aluminum, flow-through radiators. Solar vapor compression heat pumps and light-weight radiators showed the greatest promise as general advanced thermal technologies which can be applied across a range of missions. This initial study identified several other promising ATCS technologies which offer mass savings and other savings compared to traditional thermal control systems. Because the study format compares various architectures with a commonly defined baseline, it is versatile and expandable, and is expected to be updated as needed.

  20. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    PubMed Central

    Mansouri, Kamel; Abdelaziz, Ahmed; Rybacka, Aleksandra; Roncaglioni, Alessandra; Tropsha, Alexander; Varnek, Alexandre; Zakharov, Alexey; Worth, Andrew; Richard, Ann M.; Grulke, Christopher M.; Trisciuzzi, Daniela; Fourches, Denis; Horvath, Dragos; Benfenati, Emilio; Muratov, Eugene; Wedebye, Eva Bay; Grisoni, Francesca; Mangiatordi, Giuseppe F.; Incisivo, Giuseppina M.; Hong, Huixiao; Ng, Hui W.; Tetko, Igor V.; Balabin, Ilya; Kancherla, Jayaram; Shen, Jie; Burton, Julien; Nicklaus, Marc; Cassotti, Matteo; Nikolov, Nikolai G.; Nicolotti, Orazio; Andersson, Patrik L.; Zang, Qingda; Politi, Regina; Beger, Richard D.; Todeschini, Roberto; Huang, Ruili; Farag, Sherif; Rosenberg, Sine A.; Slavov, Svetoslav; Hu, Xin; Judson, Richard S.

    2016-01-01

    Background: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. Objectives: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing. Methods: CERAPP combined multiple models developed in collaboration with 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure–activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were evaluated on a set of 7,522 chemicals curated from the literature. To overcome the limitations of single models, a consensus was built by weighting models on scores based on their evaluated accuracies. Results: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing. Conclusion: This project demonstrated the possibility to screen large libraries of chemicals using a consensus of different in silico approaches. This concept will be applied in future projects related to other

  1. Prediction of concurrent chemoradiotherapy outcome in advanced oropharyngeal cancer

    PubMed Central

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

    2014-01-01

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

  2. 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.

  3. Recent Advances in GEO Water Cycle Activities

    NASA Astrophysics Data System (ADS)

    Lawford, R. G.

    2009-12-01

    Over the past few years GEO (Group on Earth Observations) efforts within the Water Societal Benefit Area (SBA) have been coordinated by the Science Committee of the former Integrated Global Observing Strategy Partnership (IGOS-P) IGWCO (Integrated Global Water Cycle Observations) theme. Within this framework a number of projects related to data system design, product development, and capacity building are being carried out. GEO has recently consolidated the Water SBA activities into three tasks, namely Droughts, Floods and Water Resource Management; Capacity Building for Water Resource Management (in Asia, Africa and the Americas); and Integrated Products for Water Resource Management and Research. In order to strengthen interactions with the GEO and its User Interface Committee, a Water Cycle Community of Practice (COP) was initiated. In addition, within the past year, the IGWCO Science Committee has decided to also function as a Community of Practice in collaboration with the existing Water Cycle COP. This overview will provide background and an update on the GEO Water SBA activities with an emphasis of the way in which these activities are being integrated within the three tasks. It will also describe activities that are planned for 2010 to facilitate this integration. Recent advances related to drought monitoring, capacity and network building, and observational and data systems will be highlighted. New water-related activities arising from collaborations between US GEO and Canada GEO, and through activities within the GEO Architecture and Data Committee, will also be described. This presentation will conclude with a longer-term outlook for water within the GEO framework and provide some guidance for interested experts on how they can become involved in helping to implement these plans.

  4. 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.

  5. Advanced extravehicular activity systems requirements definition study

    NASA Technical Reports Server (NTRS)

    1988-01-01

    A study to define the requirements for advanced extravehicular activities (AEVA) was conducted. The purpose of the study was to develop an understanding of the EVA technology requirements and to map a pathway from existing or developing technologies to an AEVA system capable of supporting long-duration missions on the lunar surface. The parameters of an AEVA system which must sustain the crewmembers and permit productive work for long periods in the lunar environment were examined. A design reference mission (DRM) was formulated and used as a tool to develop and analyze the EVA systems technology aspects. Many operational and infrastructure design issues which have a significant influence on the EVA system are identified.

  6. Advanced Hydrologic Prediction Services (AHPS) Science Infusion Strategy

    NASA Astrophysics Data System (ADS)

    Schaake, J.; Smith, G.; Carter, G.

    2002-05-01

    NWS is implementing an Advanced Hydrologic Prediction Services (AHPS) Science initiative to meet NWS Vision 2005 goals and related hydrologic services requirements, including the goal of being a world leader using state of the art forecast science and technology. AHPS includes a science infusion strategy to meet the following objectives: extend forecast lead time, improve forecast accuracy, and provide better information for user decisions. AHPS will meet these goals by implementing hydrologic forecast models tuned to local conditions and operated to account for uncertainty in hydrologic forecasts. AHPS will use ensemble weather and climate forecasts of precipitation and other conditions, such as air temperature, that affect the forecasts. This ensemble approach to weather, climate and water forecasting will provide a probabilistic basis for AHPS forecast products. Meeting AHPS goals and objectives requires an infusion of new science into the existing forecast system. Three AHPS requirements for science infusion are: 1. Quantify the uncertainty of river forecasts and provide users with a clear view of future hydrologic conditions together with hard evidence that AHPS products are based on valid forecast probability information; 2. Reduce the space and time scale, improve the accuracy, and extend the lead time of hydrologic forecasts. Demonstrate that new improvements to hydrologic forecast procedures add value to the forecasts and meet user requirements; 3. Improve the ability of forecasters to use the tools provided by integrating these into an efficient operational forecast system that includes automatic techniques for data quality control, access to data, model calibration, data assimilation, processing of ensemble forecasts, verification of forecasts and monitoring of all stages of the forecast process.

  7. 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... Research and Training, NIEHS, P.O. Box 12233, MD K3-04, Research Triangle Park, NC 27709, (telephone)...

  8. Early onset of hypertension and serum electrolyte changes as potential predictive factors of activity in advanced HCC patients treated with sorafenib: results from a retrospective analysis of the HCC-AVR group

    PubMed Central

    Gardini, Andrea Casadei; Scarpi, Emanuela; Marisi, Giorgia; Foschi, Francesco Giuseppe; Donati, Gabriele; Giampalma, Emanuela; Faloppi, Luca; Scartozzi, Mario; Silvestris, Nicola; Bisulli, Marcello; Corbelli, Jody; Gardini, Andrea; Barba, Giuliano La; Veneroni, Luigi; Tamberi, Stefano; Cascinu, Stefano; Frassineti, Giovanni Luca

    2016-01-01

    Hypertension (HTN) is frequently associated with the use of angiogenesis inhibitors targeting the vascular endothelial growth factor pathway and appears to be a generalized effect of this class of agent. We investigated the phenomenon in 61 patients with advanced hepatocellular carcinoma (HCC) receiving sorafenib. Blood pressure and plasma electrolytes were measured on days 1 and 15 of the treatment. Patients with sorafenib-induced HTN had a better outcome than those without HTN (disease control rate: 63.4% vs. 17.2% (p=0.001); progression-free survival 6.0 months (95% CI 3.2-10.1) vs. 2.5 months (95% CI 1.9-2.6) (p<0.001) and overall survival 14.6 months (95% CI9.7-19.0) vs. 3.9 months (95% CI 3.1-8.7) (p=0.003). Sodium levels were generally higher on day 15 than at baseline (+2.38, p<0.0001) in the group of responders (+4.95, p <0.0001) compared to patients who progressed (PD) (+0.28, p=0.607). In contrast, potassium was lower on day 14 (−0.30, p=0.0008) in the responder group (−0.58, p=0.003) than in those with progressive disease (−0.06, p=0.500). The early onset of hypertension is associated with improved clinical outcome in HCC patients treated with sorafenib. Our data are suggestive of an activation of the renin-angiotensin system in patients with advanced disease who developed HTN during sorafenib treatment. PMID:26893366

  9. Early onset of hypertension and serum electrolyte changes as potential predictive factors of activity in advanced HCC patients treated with sorafenib: results from a retrospective analysis of the HCC-AVR group.

    PubMed

    Casadei Gardini, Andrea; Scarpi, Emanuela; Marisi, Giorgia; Foschi, Francesco Giuseppe; Donati, Gabriele; Giampalma, Emanuela; Faloppi, Luca; Scartozzi, Mario; Silvestris, Nicola; Bisulli, Marcello; Corbelli, Jody; Gardini, Andrea; La Barba, Giuliano; Veneroni, Luigi; Tamberi, Stefano; Cascinu, Stefano; Frassineti, Giovanni Luca

    2016-03-22

    Hypertension (HTN) is frequently associated with the use of angiogenesis inhibitors targeting the vascular endothelial growth factor pathway and appears to be a generalized effect of this class of agent. We investigated the phenomenon in 61 patients with advanced hepatocellular carcinoma (HCC) receiving sorafenib. Blood pressure and plasma electrolytes were measured on days 1 and 15 of the treatment. Patients with sorafenib-induced HTN had a better outcome than those without HTN (disease control rate: 63.4% vs. 17.2% (p=0.001); progression-free survival 6.0 months (95% CI 3.2-10.1) vs. 2.5 months (95% CI 1.9-2.6) (p<0.001) and overall survival 14.6 months (95% CI9.7-19.0) vs. 3.9 months (95% CI 3.1-8.7) (p=0.003). Sodium levels were generally higher on day 15 than at baseline (+2.38, p<0.0001) in the group of responders (+4.95, p <0.0001) compared to patients who progressed (PD) (+0.28, p=0.607). In contrast, potassium was lower on day 14 (-0.30, p=0.0008) in the responder group (-0.58, p=0.003) than in those with progressive disease (-0.06, p=0.500). The early onset of hypertension is associated with improved clinical outcome in HCC patients treated with sorafenib. Our data are suggestive of an activation of the renin-angiotensin system in patients with advanced disease who developed HTN during sorafenib treatment. PMID:26893366

  10. Recent advances in predictability studies in China (1999-2002)

    NASA Astrophysics Data System (ADS)

    Mu, Mu; Wansuo, Duan; Jifan, Chou

    2004-06-01

    Since the last International Union of Geodesy and Geophysics (IUGG) General Assembly (1999), the predictability studies in China have made further progress during the period of 1999-2002. Firstly, three predictability sub-problems in numerical weather and climate prediction are classified, which are concerned with the maximum predictability time, the maximum prediction error, and the maximum allowable initial error, and then they are reduced into three nonlinear optimization problems. Secondly, the concepts of the nonlinear singular vector (NSV) and conditional nonlinear optimal perturbation (CNOP) are proposed, which have been utilized to study the predictability of numerical weather and climate prediction. The results suggest that the nonlinear characteristics of the motions of atmosphere and oceans can be revealed by NSV and CNOP. Thirdly, attention has also been paid to the relations between the predictability and spatial-temporal scale, and between the model predictability and the machine precision, of which the investigations disclose the importance of the spatial-temporal scale and machine precision in the study of predictability. Also the cell-to-cell mapping is adopted to analyze globally the predictability of climate, which could provide a new subject to the research workers. Furthermore, the predictability of the summer rainfall in China is investigated by using the method of correlation coefficients. The results demonstrate that the predictability of summer rainfall is different in different areas of China. Analysis of variance, which is one of the statistical methods applicable to the study of predictability, is also used to study the potential predictability of monthly mean temperature in China, of which the conclusion is that the monthly mean temperature over China is potentially predictable at a statistical significance level of 0.10. In addition, in the analysis of the predictability of the T106 objective analysis/forecasting field, the variance

  11. [Research advance in the drug target prediction based on chemoinformatics].

    PubMed

    Fang, Jian-song; Liu, Ai-lin; Du, Guan-hua

    2014-10-01

    The emerging of network pharmacology and polypharmacology forces the scientists to recognize and explore new mechanisms of existing drugs. The drug target prediction can play a key significance on the elucidation of the molecular mechanism of drugs and drug reposition. In this paper, we systematically review the existing approaches to the prediction of biological targets of small molecule based on chemoinformatics, including ligand-based prediction, receptor-based prediction and data mining-based prediction. We also depict the strength of these methods as well as their applications, and put forward their developing direction. PMID:25577863

  12. Prediction of primary somatosensory neuron activity during active tactile exploration

    PubMed Central

    Campagner, Dario; Evans, Mathew Hywel; Bale, Michael Ross; Erskine, Andrew; Petersen, Rasmus Strange

    2016-01-01

    Primary sensory neurons form the interface between world and brain. Their function is well-understood during passive stimulation but, under natural behaving conditions, sense organs are under active, motor control. In an attempt to predict primary neuron firing under natural conditions of sensorimotor integration, we recorded from primary mechanosensory neurons of awake, head-fixed mice as they explored a pole with their whiskers, and simultaneously measured both whisker motion and forces with high-speed videography. Using Generalised Linear Models, we found that primary neuron responses were poorly predicted by whisker angle, but well-predicted by rotational forces acting on the whisker: both during touch and free-air whisker motion. These results are in apparent contrast to previous studies of passive stimulation, but could be reconciled by differences in the kinematics-force relationship between active and passive conditions. Thus, simple statistical models can predict rich neural activity elicited by natural, exploratory behaviour involving active movement of sense organs. DOI: http://dx.doi.org/10.7554/eLife.10696.001 PMID:26880559

  13. 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.

  14. 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

  15. 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

  16. Advanced Light Source Activity Report 2002

    SciTech Connect

    Duque, Theresa; Greiner, Annette; Moxon, Elizabeth; Robinson, Arthur; Tamura, Lori

    2003-06-12

    This annual report of the Advanced Light Source details science highlights and facility improvements during the year. It also offers information on events sponsored by the facility, technical specifications, and staff and publication information.

  17. 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. PMID:21672959

  18. 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…

  19. 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…

  20. "Bridging Activities," New Media Literacies, and Advanced Foreign Language Proficiency

    ERIC Educational Resources Information Center

    Thorne, Steven L.; Reinhardt, Jonathon

    2008-01-01

    In this article we propose the pedagogical model "bridging activities" to address advanced foreign language proficiency in the context of existing and emerging internet communication and information tools and communities. The article begins by establishing the need for language and genre-focused activities at the advanced level that attend to the…

  1. Neural predictive control for active buffet alleviation

    NASA Astrophysics Data System (ADS)

    Pado, Lawrence E.; Lichtenwalner, Peter F.; Liguore, Salvatore L.; Drouin, Donald

    1998-06-01

    The adaptive neural control of aeroelastic response (ANCAR) and the affordable loads and dynamics independent research and development (IRAD) programs at the Boeing Company jointly examined using neural network based active control technology for alleviating undesirable vibration and aeroelastic response in a scale model aircraft vertical tail. The potential benefits of adaptive control includes reducing aeroelastic response associated with buffet and atmospheric turbulence, increasing flutter margins, and reducing response associated with nonlinear phenomenon like limit cycle oscillations. By reducing vibration levels and thus loads, aircraft structures can have lower acquisition cost, reduced maintenance, and extended lifetimes. Wind tunnel tests were undertaken on a rigid 15% scale aircraft in Boeing's mini-speed wind tunnel, which is used for testing at very low air speeds up to 80 mph. The model included a dynamically scaled flexible fail consisting of an aluminum spar with balsa wood cross sections with a hydraulically powered rudder. Neural predictive control was used to actuate the vertical tail rudder in response to strain gauge feedback to alleviate buffeting effects. First mode RMS strain reduction of 50% was achieved. The neural predictive control system was developed and implemented by the Boeing Company to provide an intelligent, adaptive control architecture for smart structures applications with automated synthesis, self-optimization, real-time adaptation, nonlinear control, and fault tolerance capabilities. It is designed to solve complex control problems though a process of automated synthesis, eliminating costly control design and surpassing it in many instances by accounting for real world non-linearities.

  2. Limits of Predictability of Solar Activity

    NASA Astrophysics Data System (ADS)

    Kremliovsky, M. N.

    1995-07-01

    The study of a nonlinear chaotic map of 11-year cycle maxima evolution recently derived from observations is presented with the purpose of predicting the features of the long-term variability of solar activity. It is stressed that dynamical forecast is limited by the Lyapunov time and a statistical approach can be justified due to the ergodic properties of the chaotic evolution. The Gleissberg variation is described as a chaotic walk and its distribution over length is shown to be broad. The global minima are identified as laminar slots of temporal intermittency and their typical distribution over length is also given. We note that a long sunspot cycle can be used as a precursor of the global minimum and a close sequence of global minima (once in approximately 1500 2000 years) may be responsible for the climatic changes (Little Ice Ages).

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

    PubMed

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

    2015-06-30

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

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

    PubMed Central

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

    2015-01-01

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

  5. 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.

  6. Solar-terrestrial predictions proceedings. Volume 4: Prediction of terrestrial effects of solar activity

    NASA Technical Reports Server (NTRS)

    Donnelly, R. E. (Editor)

    1980-01-01

    Papers about prediction of ionospheric and radio propagation conditions based primarily on empirical or statistical relations is discussed. Predictions of sporadic E, spread F, and scintillations generally involve statistical or empirical predictions. The correlation between solar-activity and terrestrial seismic activity and the possible relation between solar activity and biological effects is discussed.

  7. Advances in the Assessment and Prediction of Interpersonal Violence

    ERIC Educational Resources Information Center

    Mills, Jeremy F.

    2005-01-01

    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…

  8. 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.

  9. Future missions studies: Combining Schatten's solar activity prediction model with a chaotic prediction model

    NASA Technical Reports Server (NTRS)

    Ashrafi, S.

    1991-01-01

    K. Schatten (1991) recently developed a method for combining his prediction model with our chaotic model. The philosophy behind this combined model and his method of combination is explained. Because the Schatten solar prediction model (KS) uses a dynamo to mimic solar dynamics, accurate prediction is limited to long-term solar behavior (10 to 20 years). The Chaotic prediction model (SA) uses the recently developed techniques of nonlinear dynamics to predict solar activity. It can be used to predict activity only up to the horizon. In theory, the chaotic prediction should be several orders of magnitude better than statistical predictions up to that horizon; beyond the horizon, chaotic predictions would theoretically be just as good as statistical predictions. Therefore, chaos theory puts a fundamental limit on predictability.

  10. Recent and Past Musical Activity Predicts Cognitive Aging Variability: Direct Comparison with General Lifestyle Activities

    PubMed Central

    Hanna-Pladdy, Brenda; Gajewski, Byron

    2012-01-01

    Studies evaluating the impact of modifiable lifestyle factors on cognition offer potential insights into sources of cognitive aging variability. Recently, we reported an association between extent of musical instrumental practice throughout the life span (greater than 10 years) on preserved cognitive functioning in advanced age. These findings raise the question of whether there are training-induced brain changes in musicians that can transfer to non-musical cognitive abilities to allow for compensation of age-related cognitive declines. However, because of the relationship between engagement in general lifestyle activities and preserved cognition, it remains unclear whether these findings are specifically driven by musical training or the types of individuals likely to engage in greater activities in general. The current study controlled for general activity level in evaluating cognition between musicians and nomusicians. Also, the timing of engagement (age of acquisition, past versus recent) was assessed in predictive models of successful cognitive aging. Seventy age and education matched older musicians (>10 years) and non-musicians (ages 59–80) were evaluated on neuropsychological tests and general lifestyle activities. Musicians scored higher on tests of phonemic fluency, verbal working memory, verbal immediate recall, visuospatial judgment, and motor dexterity, but did not differ in other general leisure activities. Partition analyses were conducted on significant cognitive measures to determine aspects of musical training predictive of enhanced cognition. The first partition analysis revealed education best predicted visuospatial functions in musicians, followed by recent musical engagement which offset low education. In the second partition analysis, early age of musical acquisition (<9 years) predicted enhanced verbal working memory in musicians, while analyses for other measures were not predictive. Recent and past musical activity, but not

  11. 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.

  12. 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.

  13. Advanced electric field computation for RF sheaths prediction with TOPICA

    NASA Astrophysics Data System (ADS)

    Milanesio, Daniele; Maggiora, Riccardo

    2012-10-01

    The design of an Ion Cyclotron (IC) launcher is not only driven by its coupling properties, but also by its capability of maintaining low parallel electric fields in front of it, in order to provide good power transfer to plasma and to reduce the impurities production. However, due to the impossibility to verify the antenna performances before the starting of the operations, advanced numerical simulation tools are the only alternative to carry out a proper antenna design. With this in mind, it should be clear that the adoption of a code, such as TOPICA [1], able to precisely take into account a realistic antenna geometry and an accurate plasma description, is extremely important to achieve these goals. Because of the recently introduced features that allow to compute the electric field distribution everywhere inside the antenna enclosure and in the plasma column, the TOPICA code appears to be the only alternative to understand which elements may have a not negligible impact on the antenna design and then to suggest further optimizations in order to mitigate RF potentials. The present work documents the evaluation of the electric field map from actual antennas, like the Tore Supra Q5 and the JET A2 launchers, and the foreseen ITER IC antenna. [4pt] [1] D. Milanesio et al., Nucl. Fusion 49, 115019 (2009).

  14. Predictive value of serum medroxyprogesterone acetate concentration for response in advanced or recurrent breast cancer.

    PubMed

    Nishimura, R; Nagao, K; Matsuda, M; Baba, K; Matsuoka, Y; Yamashita, H; Fukuda, M; Higuchi, A; Ikeda, K

    1997-08-01

    Medroxyprogesterone acetate (MPA) is one of the most commonly prescribed drugs for endocrine therapy of metastatic breast cancer. In this study, the serum MPA concentration was measured by high-performance liquid chromatography (HPLC) and evaluated for its usefulness in predicting the response in 79 cases of advanced or recurrent breast cancers. Overall, 29 patients (37%) achieved an objective response. The response rate correlated significantly with the oestrogen receptor (ER) status (P = 0.03), proliferative activity determined by DNA polymerase alpha (P = 0.04), the disease-free interval (DFI) (P = 0.05) and the serum MPA concentration (P < 0.001). Patients with ER-positive tumours, lower proliferative activity, a longer (DFI) or a higher serum MPA concentration responded more frequently. The mean serum MPA concentration in the responders with ER-positive tumours (P = 0.01) or tumours with a lower proliferative activity (P = 0.008) were significantly lower than in cases with ER-negative tumours or tumours with a higher proliferative activity, respectively. Cases with soft tissue metastases showed responses at significantly lower MPA concentrations (P = 0.003) than those with bone or visceral metastases. Furthermore, there was a dramatic decrease in the MPA concentration when a responder with a high concentration became unresponsive to the therapy. Thus, the serum MPA concentration is a determining factor for the response to treatment. PMID:9337682

  15. 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

  16. Advanced Technology Development for Active Acoustic Liners

    NASA Technical Reports Server (NTRS)

    Sheplak, Mark; Cattafesta, Louis N., III; Nishida, Toshikazu; Kurdila, Andrew J.

    2001-01-01

    Objectives include: (1) Develop electro-mechanical/acoustic models of a Helmholtz resonator possessing a compliant diaphragm coupled to a piezoelectric device; (2) Design and fabricate the energy reclamation module and active Helmholtz resonator; (3) Develop and build appropriate energy reclamation/storage circuit; (4) Develop and fabricate appropriate piezoelectric shunt circuit to tune the compliance of the active Helmholtz resonator via a variable capacitor; (5) Quantify energy reclamation module efficiency in a grazing-flow plane wave tube possessing known acoustic energy input; and (6) Quantify actively tuned Helmholtz resonator performance in grazing-flow plane wave tube for a white-noise input

  17. Overview on NASA's Advanced Electric Propulsion Concepts Activities

    NASA Technical Reports Server (NTRS)

    Frisbee, Robert H.

    1999-01-01

    Advanced electric propulsion research activities are currently underway that seek to addresses feasibility issues of a wide range of advanced concepts, and may result in the development of technologies that will enable exciting new missions within our solar system and beyond. Each research activity is described in terms of the present focus and potential future applications. Topics include micro-electric thrusters, electrodynamic tethers, high power plasma thrusters and related applications in materials processing, variable specific impulse plasma thrusters, pulsed inductive thrusters, computational techniques for thruster modeling, and advanced electric propulsion missions and systems studies.

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

    PubMed

    Kinsella, S M; Norris, M C

    1996-01-01

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

  19. Solar Activity Predictions Based on Solar Dynamo Theories

    NASA Astrophysics Data System (ADS)

    Schatten, Kenneth H.

    2009-05-01

    We review solar activity prediction methods, statistical, precursor, and recently the Dikpati and the Choudhury groups’ use of numerical flux-dynamo methods. Outlining various methods, we compare precursor techniques with weather forecasting. Precursors involve events prior to a solar cycle. First started by the Russian geomagnetician Ohl, and then Brown and Williams; the Earth's field variations near solar minimum was used to predict the next solar cycle, with a correlation of 0.95. From the standpoint of causality, as well as energetically, these relationships were somewhat bizarre. One index used was the "number of anomalous quiet days,” an antiquated, subjective index. Scientific progress cannot be made without some suspension of disbelief; otherwise old paradigms become tautologies. So, with youthful naïveté, Svalgaard, Scherrer, Wilcox and I viewed the results through rose-colored glasses and pressed ahead searching for understanding. We eventually fumbled our way to explaining how the Sun could broadcast the state of its internal dynamo to Earth. We noted one key aspect of the Babcock-Leighton Flux Dynamo theory: the polar field at the end of a cycle serves as a seed for the next cycle's growth. Near solar minimum this field usually bathes the Earth, and thereby affects geomagnetic indices then. We found support by examining 8 previous solar cycles. Using our solar precursor technique we successfully predicted cycles 21, 22 and 23 using WSO and MWSO data. Pesnell and I improved the method using a SODA (SOlar Dynamo Amplitude) Index. In 2005, nearing cycle 23's minimum, Svalgaard and I noted an unusually weak polar field, and forecasted a small cycle 24. We discuss future advances: the flux-dynamo methods. As far as future solar activity, I shall let the Sun decide; it will do so anyhow.

  20. Environmental Monitoring Networks Optimization Using Advanced Active Learning Algorithms

    NASA Astrophysics Data System (ADS)

    Kanevski, Mikhail; Volpi, Michele; Copa, Loris

    2010-05-01

    The problem of environmental monitoring networks optimization (MNO) belongs to one of the basic and fundamental tasks in spatio-temporal data collection, analysis, and modeling. There are several approaches to this problem, which can be considered as a design or redesign of monitoring network by applying some optimization criteria. The most developed and widespread methods are based on geostatistics (family of kriging models, conditional stochastic simulations). In geostatistics the variance is mainly used as an optimization criterion which has some advantages and drawbacks. In the present research we study an application of advanced techniques following from the statistical learning theory (SLT) - support vector machines (SVM) and the optimization of monitoring networks when dealing with a classification problem (data are discrete values/classes: hydrogeological units, soil types, pollution decision levels, etc.) is considered. SVM is a universal nonlinear modeling tool for classification problems in high dimensional spaces. The SVM solution is maximizing the decision boundary between classes and has a good generalization property for noisy data. The sparse solution of SVM is based on support vectors - data which contribute to the solution with nonzero weights. Fundamentally the MNO for classification problems can be considered as a task of selecting new measurement points which increase the quality of spatial classification and reduce the testing error (error on new independent measurements). In SLT this is a typical problem of active learning - a selection of the new unlabelled points which efficiently reduce the testing error. A classical approach (margin sampling) to active learning is to sample the points closest to the classification boundary. This solution is suboptimal when points (or generally the dataset) are redundant for the same class. In the present research we propose and study two new advanced methods of active learning adapted to the solution of

  1. Advanced Extravehicular Activity Pressure Garment Requirements Development

    NASA Technical Reports Server (NTRS)

    Ross, Amy

    2014-01-01

    The NASA Johnson Space Center advanced pressure garment technology development team is addressing requirements development for exploration missions. Lessons learned from the Z-2 high fidelity prototype development have reiterated that clear low-level requirements and verification methods reduce risk to the government, improve efficiency in pressure garment design efforts, and enable the government to be a smart buyer. The expectation is to provide requirements at the specification level that are validated so that their impact on pressure garment design is understood. Additionally, the team will provide defined verification protocols for the requirements. However, in reviewing exploration space suit high level requirements there are several gaps in the team's ability to define and verify related lower level requirements. This paper addresses the efforts in requirement areas such as mobility/fit/comfort and environmental protection (dust, radiation, plasma, secondary impacts) to determine the by what method the requirements can be defined and use of those methods for verification. Gaps exist at various stages. In some cases component level work is underway, but no system level effort has begun, in other cases no effort has been initiated to close the gap. Status of ongoing efforts and potential approaches to open gaps are discussed.

  2. Advanced Light Source: Activity report 1993

    SciTech Connect

    Not Available

    1994-11-01

    The Advanced Light Source (ALS) produces the world`s brightest light in the ultraviolet and soft x-ray regions of the spectrum. The first low-energy third-generation synchrotron source in the world, the ALS provides unprecedented opportunities for research in science and technology not possible anywhere else. This year marked the beginning of operations and the start of the user research program at the ALS, which has already produced numerous high quality results. A national user facility located at Lawrence Berkeley Laboratory of the University of California, the ALS is available to researchers from academia, industry, and government laboratories. This report contains the following: (1) director`s message; (2) operations overview; (3) user program; (4) users` executive committee; (5) industrial outreach; (6) accelerator operations; (7) beamline control system; (8) insertion devices; (9) experimental systems; (10) beamline engineering; (11) first results from user beamlines; (12) beamlines for 1994--1995; (13) special events; (14) publications; (15) advisory panels; and (16) ALS staff.

  3. Predicting eruptions from precursory activity using remote sensing data hybridization

    NASA Astrophysics Data System (ADS)

    Reath, K. A.; Ramsey, M. S.; Dehn, J.; Webley, P. W.

    2016-07-01

    Many volcanoes produce some level of precursory activity prior to an eruption. This activity may or may not be detected depending on the available monitoring technology. In certain cases, precursors such as thermal output can be interpreted to make forecasts about the time and magnitude of the impending eruption. Kamchatka (Russia) provides an ideal natural laboratory to study a wide variety of eruption styles and precursory activity prior to an eruption. At Bezymianny volcano for example, a clear increase in thermal activity commonly occurs before an eruption, which has allowed predictions to be made months ahead of time. Conversely, the eruption of Tolbachik volcano in 2012 produced no discernable thermal precursors before the large scale effusive eruption. However, most volcanoes fall between the extremes of consistently behaved and completely undetectable, which is the case with neighboring Kliuchevskoi volcano. This study tests the effectiveness of using thermal infrared (TIR) remote sensing to track volcanic thermal precursors using data from both the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Advanced Very High Resolution Radiometer (AVHRR) sensors. It focuses on three large eruptions that produced different levels and durations of effusive and explosive behavior at Kliuchevskoi. Before each of these eruptions, TIR spaceborne sensors detected thermal anomalies (i.e., pixels with brightness temperatures > 2 °C above the background temperature). High-temporal, low-spatial resolution (i.e., ~ hours and 1 km) AVHRR data are ideal for detecting large thermal events occurring over shorter time scales, such as the hot material ejected following strombolian eruptions. In contrast, high-spatial, low-temporal resolution (i.e., days to weeks and 90 m) ASTER data enables the detection of much lower thermal activity; however, activity with a shorter duration will commonly be missed. ASTER and AVHRR data are combined to track low

  4. Activity and Language in Advanced Graduate Study

    ERIC Educational Resources Information Center

    Barowy, William; Thormann, Joan

    2008-01-01

    Recent work integrating Cultural-Historical Activity Theory (CHAT) with Systemic Functional Linguistics (SFL) forms a basis for systematizing action research in higher education. This basis strengthens what are often otherwise its methodological weaknesses, namely, the disconnection between analysis and subsequent plans for action and the…

  5. Speaking Activities for the Advanced College-Bound Student.

    ERIC Educational Resources Information Center

    Henderson, Don

    Three activities for developing speaking skills of advanced English as second language students are presented. Impromptu speaking, extemporaneous speaking, and debate activities are designed to train students to organize concepts, develop spontaneous oral skills, and enhance confidence and clarity of thought. Impromptu speaking develops…

  6. Real-time Neural Network predictions of geomagnetic activity indices

    NASA Astrophysics Data System (ADS)

    Bala, R.; Reiff, P. H.

    2009-12-01

    The Boyle potential or the Boyle Index (BI), Φ (kV)=10-4 (V/(km/s))2 + 11.7 (B/nT) sin3(θ/2), is an empirically-derived formula that can characterize the Earth's polar cap potential, which is readily derivable in real time using the solar wind data from ACE (Advanced Composition Explorer). The BI has a simplistic form that utilizes a non-magnetic "viscous" and a magnetic "merging" component to characterize the magnetospheric behavior in response to the solar wind. We have investigated its correlation with two of conventional geomagnetic activity indices in Kp and the AE index. We have shown that the logarithms of both 3-hr and 1-hr averages of the BI correlate well with the subsequent Kp: Kp = 8.93 log10(BI) - 12.55 along with 1-hr BI correlating with the subsequent log10(AE): log10(AE) = 1.78 log10(BI) - 3.6. We have developed a new set of algorithms based on Artificial Neural Networks (ANNs) suitable for short term space weather forecasts with an enhanced lead-time and better accuracy in predicting Kp and AE over some leading models; the algorithms omit the time history of its targets to utilize only the solar wind data. Inputs to our ANN models benefit from the BI and its proven record as a forecasting parameter since its initiation in October, 2003. We have also performed time-sensitivity tests using cross-correlation analysis to demonstrate that our models are as efficient as those that incorporates the time history of the target indices in their inputs. Our algorithms can predict the upcoming full 3-hr Kp, purely from the solar wind data and achieve a linear correlation coefficient of 0.840, which means that it predicts the upcoming Kp value on average to within 1.3 step, which is approximately the resolution of the real-time Kp estimate. Our success in predicting Kp during a recent unexpected event (22 July ’09) is shown in the figure. Also, when predicting an equivalent "one hour Kp'', the correlation coefficient is 0.86, meaning on average a prediction

  7. Advanced light source. Activity report 1995

    SciTech Connect

    1996-07-01

    The ALS Activity Report is designed to share the breadth, variety, and interest of the scientific program and ongoing R&D efforts in a form that is accessible to a broad audience. Recent research results are presented in six sections, each representing an important theme in ALS science. These results are designed to demonstrate the capabilities of the ALS, rather than to give a comprehensive review of 1995 experiments. Although the scientific program and facilities report are separate sections, in practice the achievements and accomplishments of users and ALS staff are interdependent. This user-staff collaboration is essential to help us direct our efforts toward meeting the needs of the user community, and to ensure the continued success of the ALS as a premier facility.

  8. Bi-Directional SIFT Predicts a Subset of Activating Mutations

    PubMed Central

    Lee, William; Lazarus, Robert A.; Zhang, Zemin

    2009-01-01

    Advancements in sequencing technologies have empowered recent efforts to identify polymorphisms and mutations on a global scale. The large number of variations and mutations found in these projects requires high-throughput tools to identify those that are most likely to have an impact on function. Numerous computational tools exist for predicting which mutations are likely to be functional, but none that specifically attempt to identify mutations that result in hyperactivation or gain-of-function. Here we present a modified version of the SIFT (Sorting Intolerant from Tolerant) algorithm that utilizes protein sequence alignments with homologous sequences to identify functional mutations based on evolutionary fitness. We show that this bi-directional SIFT (B-SIFT) is capable of identifying experimentally verified activating mutants from multiple datasets. B-SIFT analysis of large-scale cancer genotyping data identified potential activating mutations, some of which we have provided detailed structural evidence to support. B-SIFT could prove to be a valuable tool for efforts in protein engineering as well as in identification of functional mutations in cancer. PMID:20011534

  9. The Built Environment Predicts Observed Physical Activity

    PubMed Central

    Kelly, Cheryl; Wilson, Jeffrey S.; Schootman, Mario; Clennin, Morgan; Baker, Elizabeth A.; Miller, Douglas K.

    2014-01-01

    Background: In order to improve our understanding of the relationship between the built environment and physical activity, it is important to identify associations between specific geographic characteristics and physical activity behaviors. Purpose: Examine relationships between observed physical activity behavior and measures of the built environment collected on 291 street segments in Indianapolis and St. Louis. Methods: Street segments were selected using a stratified geographic sampling design to ensure representation of neighborhoods with different land use and socioeconomic characteristics. Characteristics of the built environment on-street segments were audited using two methods: in-person field audits and audits based on interpretation of Google Street View imagery with each method blinded to results from the other. Segments were dichotomized as having a particular characteristic (e.g., sidewalk present or not) based on the two auditing methods separately. Counts of individuals engaged in different forms of physical activity on each segment were assessed using direct observation. Non-parametric statistics were used to compare counts of physically active individuals on each segment with built environment characteristic. Results: Counts of individuals engaged in physical activity were significantly higher on segments with mixed land use or all non-residential land use, and on segments with pedestrian infrastructure (e.g., crosswalks and sidewalks) and public transit. Conclusion: Several micro-level built environment characteristics were associated with physical activity. These data provide support for theories that suggest changing the built environment and related policies may encourage more physical activity. PMID:24904916

  10. Selected advanced aerodynamic and active control concepts development

    NASA Technical Reports Server (NTRS)

    1980-01-01

    A summary is presented of results obtained during analysis, design and test activities on six selected technical tasks directed at exploratory improvement of fuel efficiency for new and derivative transports. The work included investigations into the potential offered by natural laminar flow, improved surface coatings and advanced high lift concepts. Similar investigations covering optimum low-energy flight path control, integrated application of active controls and evaluation of primary flight control systems reliability and maintenance are also summarized. Recommendations are included for future work needed to exploit potential advancements.

  11. Prediction models for platinum-based chemotherapy response and toxicity in advanced NSCLC patients.

    PubMed

    Yin, Ji-Ye; Li, Xi; Li, Xiang-Ping; Xiao, Ling; Zheng, Wei; Chen, Juan; Mao, Chen-Xue; Fang, Chao; Cui, Jia-Jia; Guo, Cheng-Xian; Zhang, Wei; Gao, Yang; Zhang, Chun-Fang; Chen, Zi-Hua; Zhou, Hui; Zhou, Hong-Hao; Liu, Zhao-Qian

    2016-07-10

    In this study, we aimed to establish a platinum-based chemotherapy response and toxicity prediction model in advanced non-small cell lung cancer (NSCLC) patients. 416 single nucleotide polymorphisms (SNPs) in 185 genes were genotyped, and their association with drug response and toxicity were estimated using logistic regression. Nine data mining techniques were employed to establish the prediction model; the sensitivity, specificity, overall accuracy and receiver operating characteristic (ROC) curve were used to assess the models' performance. Finally, selected models were validated in an independent cohort. The models established by naïve Bayesian algorithm had the best performance. The response prediction model achieved a sensitivity of 0.90 and a specificity of 0.47 with the ROC area under curve (AUC) of 0.80. The overall toxicity prediction model achieved a sensitivity of 0.86 and a specificity of 0.46 with the ROC AUC of 0.73. The hematological toxicity prediction model achieved a sensitivity of 0.89 and a specificity of 0.39 with the ROC AUC of 0.76. The gastrointestinal toxicity prediction model achieved a sensitivity of 0.93 and a specificity of 0.35 with the ROC AUC of 0.80. In conclusion, we provided platinum-based chemotherapy response and toxicity prediction models for advanced NSCLC patients. PMID:27126360

  12. Prediction Activities at NASA's Global Modeling and Assimilation Office

    NASA Technical Reports Server (NTRS)

    Schubert, Siegfried

    2010-01-01

    The Global Modeling and Assimilation Office (GMAO) is a core NASA resource for the development and use of satellite observations through the integrating tools of models and assimilation systems. Global ocean, atmosphere and land surface models are developed as components of assimilation and forecast systems that are used for addressing the weather and climate research questions identified in NASA's science mission. In fact, the GMAO is actively engaged in addressing one of NASA's science mission s key questions concerning how well transient climate variations can be understood and predicted. At weather time scales the GMAO is developing ultra-high resolution global climate models capable of resolving high impact weather systems such as hurricanes. The ability to resolve the detailed characteristics of weather systems within a global framework greatly facilitates addressing fundamental questions concerning the link between weather and climate variability. At sub-seasonal time scales, the GMAO is engaged in research and development to improve the use of land information (especially soil moisture), and in the improved representation and initialization of various sub-seasonal atmospheric variability (such as the MJO) that evolves on time scales longer than weather and involves exchanges with both the land and ocean The GMAO has a long history of development for advancing the seasonal-to-interannual (S-I) prediction problem using an older version of the coupled atmosphere-ocean general circulation model (AOGCM). This includes the development of an Ensemble Kalman Filter (EnKF) to facilitate the multivariate assimilation of ocean surface altimetry, and an EnKF developed for the highly inhomogeneous nature of the errors in land surface models, as well as the multivariate assimilation needed to take advantage of surface soil moisture and snow observations. The importance of decadal variability, especially that associated with long-term droughts is well recognized by the

  13. Predicting mining activity with parallel genetic algorithms

    USGS Publications Warehouse

    Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.

    2005-01-01

    We explore several different techniques in our quest to improve the overall model performance of a genetic algorithm calibrated probabilistic cellular automata. We use the Kappa statistic to measure correlation between ground truth data and data predicted by the model. Within the genetic algorithm, we introduce a new evaluation function sensitive to spatial correctness and we explore the idea of evolving different rule parameters for different subregions of the land. We reduce the time required to run a simulation from 6 hours to 10 minutes by parallelizing the code and employing a 10-node cluster. Our empirical results suggest that using the spatially sensitive evaluation function does indeed improve the performance of the model and our preliminary results also show that evolving different rule parameters for different regions tends to improve overall model performance. Copyright 2005 ACM.

  14. Measuring Active Learning to Predict Course Quality

    ERIC Educational Resources Information Center

    Taylor, John E.; Ku, Heng-Yu

    2011-01-01

    This study investigated whether active learning within computer-based training courses can be measured and whether it serves as a predictor of learner-perceived course quality. A major corporation participated in this research, providing access to internal employee training courses, training representatives, and historical course evaluation data.…

  15. Motolimod effectively drives immune activation in advanced cancer patients

    PubMed Central

    Dietsch, Gregory N.

    2016-01-01

    ABSTRACT A novel approach to immunotherapy is the activation of toll-like receptor 8 (TLR8). Motolimod, a selective TLR8 agonist can act in concert with approved immunotherapies to sensitize T cells and augment natural killer (NK) cell function. Despite treatment with chemotherapeutic agents and advance disease, cancer patients remain sensitive to motolimod.

  16. Advanced Light Source Activity Report 1997/1998

    SciTech Connect

    Greiner, Annette

    1999-03-01

    This Lawrence Berkeley National Laboratory, Advanced Light Source (ALS) activity report for 1997/98 discusses the following topics: Introduction and Overview; Science Highlights; Facility Report; Special Events; ALS Advisory Panels 1997/98; ALS Staff 1997/98 and Facts and Figures for the year.

  17. 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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Erdal, Halil Ibrahim; Karakurt, Onur

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  1. A prediction of geomagnetic activity for solar cycle 23

    NASA Astrophysics Data System (ADS)

    Cliver, E. W.; Ling, A. G.; Wise, J. E.; Lanzerotti, L. J.

    1999-04-01

    Using a database of 13 solar cycles of geomagnetic aa data, we obtained correlations between cycle averages of geomagnetic activity (and sunspot number) and the numbers of days with disturbance levels above certain aa thresholds. We then used a precursor-type relation to predict an average aa index of 23.1 nT for cycle 23 and inserted this average aa value into the above correlations to forecast the integral size distribution of geomagnetic activity for the new cycle. The predicted size distribution is similar to that observed for cycles 21 and 22 but most closely resembles that of solar cycle 18 (1944-1954), which was slightly smaller than cycles 21 and 22. Our prediction agrees reasonably well with the ``climatology-based'' forecast made by the intergovernmental panel tasked to predict geomagnetic activity for the coming solar cycle and is significantly different from their ``precursor-based'' prediction.

  2. 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.

  3. Cortical activity patterns predict speech discrimination ability

    PubMed Central

    Engineer, Crystal T; Perez, Claudia A; Chen, YeTing H; Carraway, Ryan S; Reed, Amanda C; Shetake, Jai A; Jakkamsetti, Vikram; Chang, Kevin Q; Kilgard, Michael P

    2010-01-01

    Neural activity in the cerebral cortex can explain many aspects of sensory perception. Extensive psychophysical and neurophysiological studies of visual motion and vibrotactile processing show that the firing rate of cortical neurons averaged across 50–500 ms is well correlated with discrimination ability. In this study, we tested the hypothesis that primary auditory cortex (A1) neurons use temporal precision on the order of 1–10 ms to represent speech sounds shifted into the rat hearing range. Neural discrimination was highly correlated with behavioral performance on 11 consonant-discrimination tasks when spike timing was preserved and was not correlated when spike timing was eliminated. This result suggests that spike timing contributes to the auditory cortex representation of consonant sounds. PMID:18425123

  4. New Model Predicts Fire Activity in South America

    NASA Video Gallery

    UC Irvine scientist Jim Randerson discusses a new model that is able to predict fire activity in South America using sea surface temperature observations of the Pacific and Atlantic Ocean. The find...

  5. PREDICTING PREFERENTIAL ADSORPTION OF ORGANICS BY ACTIVATED CARBON

    EPA Science Inventory

    Preferential adsorption of organic compounds onto activated carbon from dilute aqueous solutions was studied to develop a comprehensive theoretical basis for predicting adsorption of multicomponent solutes. The research program investigates why some solutes are strong adsorbers, ...

  6. Prognostication of Survival in Patients With Advanced Cancer: Predicting the Unpredictable?

    PubMed Central

    Hui, David

    2016-01-01

    Background Prognosis is a key driver of clinical decision-making. However, available prognostication tools have limited accuracy and variable levels of validation. Methods Principles of survival prediction and literature on clinician prediction of survival, prognostic factors, and prognostic models were reviewed, with a focus on patients with advanced cancer and a survival rate of a few months or less. Results The 4 principles of survival prediction are (a) prognostication is a process instead of an event, (b) prognostic factors may evolve over the course of the disease, (c) prognostic accuracy for a given prognostic factor/tool varies by the definition of accuracy, the patient population, and the time frame of prediction, and (d) the exact timing of death cannot be predicted with certainty. Clinician prediction of survival rate is the most commonly used approach to formulate prognosis. However, clinicians often overestimate survival rates with the temporal question. Other clinician prediction of survival approaches, such as surprise and probabilistic questions, have higher rates of accuracy. Established prognostic factors in the advanced cancer setting include decreased performance status, delirium, dysphagia, cancer anorexia–cachexia, dyspnea, inflammation, and malnutrition. Novel prognostic factors, such as phase angle, may improve rates of accuracy. Many prognostic models are available, including the Palliative Prognostic Score, the Palliative Prognostic Index, and the Glasgow Prognostic Score. Conclusions Despite the uncertainty in survival prediction, existing prognostic tools can facilitate clinical decision-making by providing approximated time frames (months, weeks, or days). Future research should focus on clarifying and comparing the rates of accuracy for existing prognostic tools, identifying and validating novel prognostic factors, and linking prognostication to decision-making. PMID:26678976

  7. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  9. An integrated theory for predicting the hydrothermomechanical response of advanced composite structural components

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

    A theory is developed for predicting the hydrothermomechanical response of advanced composite structural components. The combined hydrothermal effects on the mechanical properties of unidirectional composites loaded along the material axis and off-axis, and of angleplied laminates are also evaluated. The materials investigated consist of neat PR-288 epoxy matrix resin and an AS-type graphite fiber/PR-288 resin unidirectional composite.

  10. Advanced extravehicular activity systems requirements definition study. Phase 2: Extravehicular activity at a lunar base

    NASA Technical Reports Server (NTRS)

    Neal, Valerie; Shields, Nicholas, Jr.; Carr, Gerald P.; Pogue, William; Schmitt, Harrison H.; Schulze, Arthur E.

    1988-01-01

    The focus is on Extravehicular Activity (EVA) systems requirements definition for an advanced space mission: remote-from-main base EVA on the Moon. The lunar environment, biomedical considerations, appropriate hardware design criteria, hardware and interface requirements, and key technical issues for advanced lunar EVA were examined. Six remote EVA scenarios (three nominal operations and three contingency situations) were developed in considerable detail.

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

    SciTech Connect

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

    1992-02-01

    Measured and predicted rotor performance for the SERI advanced wind turbine blades were compared to assess the accuracy of predictions and to identify the sources of error affecting both predictions and measurements. An awareness of these sources of error contributes to improved prediction and measurement methods that will ultimately benefit future rotor design efforts. Propeller/vane anemometers were found to underestimate the wind speed in turbulent environments such as the San Gorgonio Pass wind farm area. Using sonic or cup anemometers, good agreement was achieved between predicted and measured power output for wind speeds up to 8 m/sec. At higher wind speeds an optimistic predicted power output and the occurrence of peak power at wind speeds lower than measurements resulted from the omission of turbulence and yaw error. In addition, accurate two-dimensional (2-D) airfoil data prior to stall and a post stall airfoil data synthesization method that reflects three-dimensional (3-D) effects were found to be essential for accurate performance prediction. 11 refs.

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

    NASA Technical Reports Server (NTRS)

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

    1996-01-01

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

  13. Advanced deposition model for thermal activated chemical vapor deposition

    NASA Astrophysics Data System (ADS)

    Cai, Dang

    Thermal Activated Chemical Vapor Deposition (TACVD) is defined as the formation of a stable solid product on a heated substrate surface from chemical reactions and/or dissociation of gaseous reactants in an activated environment. It has become an essential process for producing solid film, bulk material, coating, fibers, powders and monolithic components. Global market of CVD products has reached multi billions dollars for each year. In the recent years CVD process has been extensively used to manufacture semiconductors and other electronic components such as polysilicon, AlN and GaN. Extensive research effort has been directed to improve deposition quality and throughput. To obtain fast and high quality deposition, operational conditions such as temperature, pressure, fluid velocity and species concentration and geometry conditions such as source-substrate distance need to be well controlled in a CVD system. This thesis will focus on design of CVD processes through understanding the transport and reaction phenomena in the growth reactor. Since the in situ monitor is almost impossible for CVD reactor, many industrial resources have been expended to determine the optimum design by semi-empirical methods and trial-and-error procedures. This approach has allowed the achievement of improvements in the deposition sequence, but begins to show its limitations, as this method cannot always fulfill the more and more stringent specifications of the industry. To resolve this problem, numerical simulation is widely used in studying the growth techniques. The difficulty of numerical simulation of TACVD crystal growth process lies in the simulation of gas phase and surface reactions, especially the latter one, due to the fact that very limited kinetic information is available in the open literature. In this thesis, an advanced deposition model was developed to study the multi-component fluid flow, homogeneous gas phase reactions inside the reactor chamber, heterogeneous surface

  14. Individualized relapse prediction: personality measures and striatal and insular activity during reward-processing robustly predict relapse*

    PubMed Central

    Gowin, Joshua L.; Ball, Tali M.; Wittmann, Marc; Tapert, Susan F.; Paulus, Martin P.

    2015-01-01

    Background Nearly half of individuals with substance use disorders relapse in the year after treatment. A diagnostic tool to help clinicians make decisions regarding treatment does not exist for psychiatric conditions. Identifying individuals with high risk for relapse to substance use following abstinence has profound clinical consequences. This study aimed to develop neuroimaging as a robust tool to predict relapse. Methods 68 methamphetamine-dependent adults (15 female) were recruited from 28-day inpatient treatment. During treatment, participants completed a functional MRI scan that examined brain activation during reward processing. Patients were followed 1 year later to assess abstinence. We examined brain activation during reward processing between relapsing and abstaining individuals and employed three random forest prediction models (clinical and personality measures, neuroimaging measures, a combined model) to generate predictions for each participant regarding their relapse likelihood. Results 18 individuals relapsed. There were significant group by reward-size interactions for neural activation in the left insula and right striatum for rewards. Abstaining individuals showed increased activation for large, risky relative to small, safe rewards, whereas relapsing individuals failed to show differential activation between reward types. All three random forest models yielded good test characteristics such that a positive test for relapse yielded a likelihood ratio 2.63, whereas a negative test had a likelihood ratio of 0.48. Conclusions These findings suggest that neuroimaging can be developed in combination with other measures as an instrument to predict relapse, advancing tools providers can use to make decisions about individualized treatment of substance use disorders. PMID:25977206

  15. 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

  16. Plastic Instability in Complex Strain Paths Predicted by Advanced Constitutive Equations

    NASA Astrophysics Data System (ADS)

    Butuc, Marilena C.; Barlat, Frédéric; Gracio, José J.; Vincze, Gabriela

    2011-08-01

    The present paper aims at predicting plastic instabilities under complex loading histories using an advanced sheet metal forming limit model. The onset of localized necking is computed using the Marciniak-Kuczinsky (MK) analysis [1] with a physically-based hardening model and the phenomenological anisotropic yield criterion Yld2000-2d [2]. The hardening model accounts for anisotropic work-hardening induced by the microstructural evolution at large strains, which was proposed by Teodosiu and Hu [3]. Simulations are carried out for linear and complex strain paths. Experimentally, two deep-drawing quality sheet metals are selected: a bake-hardening steel (BH) and a DC06 steel sheet. The validity of the model is assessed by comparing the predicted and experimental forming limits. The remarkable accuracy of the developed software to predict the forming limits under linear and non-linear strain path is obviously due to the performance of the advanced constitutive equations to describe with great detail the material behavior. The effect of strain-induced anisotropy on formability evolution under strain path changes, as predicted by the microstructural hardening model, is particularly well captured by the model.

  17. Predicting Physical Activity in Arab American School Children

    ERIC Educational Resources Information Center

    Martin, Jeffrey J.; McCaughtry, Nate; Shen, Bo

    2008-01-01

    Theoretically grounded research on the determinants of Arab American children's physical activity is virtually nonexistent. Thus, the purpose of our investigation was to evaluate the ability of the theory of planned behavior (TPB) and social cognitive theory (SCT) to predict Arab American children's moderate-to-vigorous physical activity (MVPA).…

  18. 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.

  19. 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.

  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. Flutter prediction for a wing with active aileron control

    NASA Technical Reports Server (NTRS)

    Penning, K.; Sandlin, D. R.

    1983-01-01

    A method for predicting the vibrational stability of an aircraft with an analog active aileron flutter suppression system (FSS) is expained. Active aileron refers to the use of an active control system connected to the aileron to damp vibrations. Wing vibrations are sensed by accelerometers and the information is used to deflect the aileron. Aerodynamic force caused by the aileron deflection oppose wing vibrations and effectively add additional damping to the system.

  2. Synthesis, characterization, theoretical prediction of activities and evaluation of biological activities of some sulfacetamide based hydroxytriazenes.

    PubMed

    Agarwal, Shilpa; Baroliya, Prabhat K; Bhargava, Amit; Tripathi, I P; Goswami, A K

    2016-06-15

    Six new N [(4-aminophenyl)sulfonyl]acetamide based hydroxytriazenes have been synthesized and characterized using elemental analysis, IR, 1H NMR, 13C NMR and MASS spectral analysis. Further, their theoretical predictions for probable activities have been taken using PASS (Prediction of Activity Spectra for Substance). Although a number of activities have been predicted but specifically anti-inflammatory, antiradical, anti-diabetic activities have been experimentally validated which proves that theoretical predictions agree with the experimental results. The object of the Letter is to establish Computer Aided Drug Design (CADD) using our compounds. PMID:27136718

  3. Prediction of fine-tuned promoter activity from DNA sequence

    PubMed Central

    Siwo, Geoffrey; Rider, Andrew; Tan, Asako; Pinapati, Richard; Emrich, Scott; Chawla, Nitesh; Ferdig, Michael

    2016-01-01

    The quantitative prediction of transcriptional activity of genes using promoter sequence is fundamental to the engineering of biological systems for industrial purposes and understanding the natural variation in gene expression. To catalyze the development of new algorithms for this purpose, the Dialogue on Reverse Engineering Assessment and Methods (DREAM) organized a community challenge seeking predictive models of promoter activity given normalized promoter activity data for 90 ribosomal protein promoters driving expression of a fluorescent reporter gene. By developing an unbiased modeling approach that performs an iterative search for predictive DNA sequence features using the frequencies of various k-mers, inferred DNA mechanical properties and spatial positions of promoter sequences, we achieved the best performer status in this challenge. The specific predictive features used in the model included the frequency of the nucleotide G, the length of polymeric tracts of T and TA, the frequencies of 6 distinct trinucleotides and 12 tetranucleotides, and the predicted protein deformability of the DNA sequence. Our method accurately predicted the activity of 20 natural variants of ribosomal protein promoters (Spearman correlation r = 0.73) as compared to 33 laboratory-mutated variants of the promoters (r = 0.57) in a test set that was hidden from participants. Notably, our model differed substantially from the rest in 2 main ways: i) it did not explicitly utilize transcription factor binding information implying that subtle DNA sequence features are highly associated with gene expression, and ii) it was entirely based on features extracted exclusively from the 100 bp region upstream from the translational start site demonstrating that this region encodes much of the overall promoter activity. The findings from this study have important implications for the engineering of predictable gene expression systems and the evolution of gene expression in naturally occurring

  4. Advances in Inner Magnetosphere Passive and Active Wave Research

    NASA Technical Reports Server (NTRS)

    Green, James L.; Fung, Shing F.

    2004-01-01

    This review identifies a number of the principal research advancements that have occurred over the last five years in the study of electromagnetic (EM) waves in the Earth's inner magnetosphere. The observations used in this study are from the plasma wave instruments and radio sounders on Cluster, IMAGE, Geotail, Wind, Polar, Interball, and others. The data from passive plasma wave instruments have led to a number of advances such as: determining the origin and importance of whistler mode waves in the plasmasphere, discovery of the source of kilometric continuum radiation, mapping AKR source regions with "pinpoint" accuracy, and correlating the AKR source location with dipole tilt angle. Active magnetospheric wave experiments have shown that long range ducted and direct echoes can be used to obtain the density distribution of electrons in the polar cap and along plasmaspheric field lines, providing key information on plasmaspheric filling rates and polar cap outflows.

  5. A Simple Tool to Predict ESRD Within 1 Year in Elderly Patients with Advanced CKD

    PubMed Central

    Drawz, Paul E.; Goswami, Puja; Azem, Reem; Babineau, Denise C.; Rahman, Mahboob

    2013-01-01

    BACKGROUND/OBJECTIVES Chronic kidney disease (CKD) is common in older patients; currently, no tools are available to predict the risk of end-stage renal disease (ESRD) within 1 year. The goal of this study was to develop and validate a model to predict the 1 year risk for ESRD in elderly subjects with advanced CKD. DESIGN Retrospective study SETTING Veterans Affairs Medical Center PARTICIPANTS Patients over 65 years of age with CKD with an estimated (eGFR) less than 30mL/min/1.73m2. MEASUREMENTS The outcome was ESRD within 1 year of the index eGFR. Cox regression was used to develop a predictive model (VA risk score) which was validated in a separate cohort. RESULTS Of the 1,866 patients in the developmental cohort, 77 developed ESRD. Risk factors for ESRD in the final model were age, congestive heart failure, systolic blood pressure, eGFR, potassium, and albumin. In the validation cohort, the C index for the VA risk score was 0.823. The risk for developing ESRD at 1 year from lowest to highest tertile was 0.08%, 2.7%, and 11.3% (P<0.001). The C-index for the recently published Tangri model in the validation cohort was 0.780. CONCLUSION A new model using commonly available clinical measures shows excellent ability to predict the onset of ESRD within the next year in elderly subjects. Additionally, the Tangri model had very good predictive ability. Patients and physicians can use these risk models to inform decisions regarding preparation for renal replacement therapy in patients with advanced CKD. PMID:23617782

  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. Structure based activity prediction of HIV-1 reverse transcriptase inhibitors.

    PubMed

    de Jonge, Marc R; Koymans, Lucien M H; Vinkers, H Maarten; Daeyaert, Frits F D; Heeres, Jan; Lewi, Paul J; Janssen, Paul A J

    2005-03-24

    We have developed a fast and robust computational method for prediction of antiviral activity in automated de novo design of HIV-1 reverse transcriptase inhibitors. This is a structure-based approach that uses a linear relation between activity and interaction energy with discrete orientation sampling and with localized interaction energy terms. The localization allows for the analysis of mutations of the protein target and for the separation of inhibition and a specific binding to the enzyme. We apply the method to the prediction of pIC(50) of HIV-1 reverse transcriptase inhibitors. The model predicts the activity of an arbitrary compound with a q(2) of 0.681 and an average absolute error of 0.66 log value, and it is fast enough to be used in high-throughput computational applications. PMID:15771460

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2011-01-01

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

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

    PubMed

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

    2015-01-01

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

  11. A neural network model for olfactory glomerular activity prediction

    NASA Astrophysics Data System (ADS)

    Soh, Zu; Tsuji, Toshio; Takiguchi, Noboru; Ohtake, Hisao

    2012-12-01

    Recently, the importance of odors and methods for their evaluation have seen increased emphasis, especially in the fragrance and food industries. Although odors can be characterized by their odorant components, their chemical information cannot be directly related to the flavors we perceive. Biological research has revealed that neuronal activity related to glomeruli (which form part of the olfactory system) is closely connected to odor qualities. Here we report on a neural network model of the olfactory system that can predict glomerular activity from odorant molecule structures. We also report on the learning and prediction ability of the proposed model.

  12. Recent advances in dynamical extra-seasonal to annual climate prediction at IAP/CAS

    NASA Astrophysics Data System (ADS)

    Lin, Zhaohui; Wang, Huijun; Zhou, Guangqing; Chen, Hong; Lang, Xianmei; Zhao, Yan; Zeng, Qingcun

    2004-06-01

    Recent advances in dynamical climate prediction at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS) during the last five years have been briefly described in this paper. Firstly, the second generation of the IAP dynamical climate prediction system (IAP DCP-II) has been described, and two sets of hindcast experiments of the summer rainfall anomalies over China for the periods of 1980 1994 with different versions of the IAP AGCM have been conducted. The comparison results show that the predictive skill of summer rainfall anomalies over China is improved with the improved IAP AGCM in which the surface albedo parameterization is modified. Furthermore, IAP DCP-II has been applied to the real-time prediction of summer rainfall anomalies over China since 1998, and the verification results show that IAP DCP-II can quite well capture the large scale patterns of the summer flood/drought situations over China during the last five years (1998 2002). Meanwhile, an investigation has demonstrated the importance of the atmospheric initial conditions on the seasonal climate prediction, along with studies on the influences from surface boundary conditions (e.g., land surface characteristics, sea surface temperature). Certain conclusions have been reached, such as, the initial atmospheric anomalies in spring may play an important role in the summer climate anomalies, and soil moisture anomalies in spring can also have a significant impact on the summer climate anomalies over East Asia. Finally, several practical techniques (e.g., ensemble technique, correction method, etc.), which lead to the increase of the prediction skill for summer rainfall anomalies over China, have also been illustrated. The paper concludes with a list of critical requirements needed for the further improvement of dynamical seasonal climate prediction.

  13. 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

  14. Solar Activity Forecasting for use in Orbit Prediction

    NASA Technical Reports Server (NTRS)

    Schatten, Kenneth

    2001-01-01

    Orbital prediction for satellites in low Earth orbit (LEO) or low planetary orbit depends strongly on exospheric densities. Solar activity forecasting is important in orbital prediction, as the solar UV and EUV inflate the upper atmospheric layers of the Earth and planets, forming the exosphere in which satellites orbit. Geomagnetic effects also relate to solar activity. Because of the complex and ephemeral nature of solar activity, with different cycles varying in strength by more than 100%, many different forecasting techniques have been utilized. The methods range from purely numerical techniques (essentially curve fitting) to numerous oddball schemes, as well as a small subset, called 'Precursor techniques.' The situation can be puzzling, owing to the numerous methodologies involved, somewhat akin to the numerous ether theories near the turn of the last century. Nevertheless, the Precursor techniques alone have a physical basis, namely dynamo theory, which provides a physical explanation for why this subset seems to work. I discuss this solar cycle's predictions, as well as the Sun's observed activity. I also discuss the SODA (Solar Dynamo Amplitude) index, which provides the user with the ability to track the Sun's hidden, interior dynamo magnetic fields. As a result, one may then update solar activity predictions continuously, by monitoring the solar magnetic fields as they change throughout the solar cycle. This paper ends by providing a glimpse into what the next solar cycle (#24) portends.

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

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

  16. 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.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-08-01

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

  19. Benefits of advanced space suits for supporting routine extravehicular activity

    NASA Technical Reports Server (NTRS)

    Alton, L. R.; Bauer, E. H.; Patrick, J. W.

    1975-01-01

    Technology is available to produce space suits providing a quick-reaction, safe, much more mobile extravehicular activity (EVA) capability than before. Such a capability may be needed during the shuttle era because the great variety of missions and payloads complicates the development of totally automated methods of conducting operations and maintenance and resolving contingencies. Routine EVA now promises to become a cost-effective tool as less complex, serviceable, lower-cost payload designs utilizing this capability become feasible. Adoption of certain advanced space suit technologies is encouraged for reasons of economics as well as performance.

  20. Stock price change rate prediction by utilizing social network activities.

    PubMed

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

  1. Stock Price Change Rate Prediction by Utilizing Social Network Activities

    PubMed Central

    Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

    Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586

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

    PubMed Central

    2012-01-01

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

  3. Solar activity forecast: Spectral analysis and neurofuzzy prediction

    NASA Astrophysics Data System (ADS)

    Gholipour, Ali; Lucas, Caro; Araabi, Babak N.; Shafiee, Masoud

    2005-04-01

    Active research in the last two decades indicates that the physical precursor and solar dynamo techniques are preferred as practical tools for long-term prediction of solar activity. But why should we omit more than 23 cycles of solar activity history, and just use empirical methods or simple autoregressive methods on the basis of observations for the latest eight cycles? In this article, a method based on spectral analysis and neurofuzzy modeling is proposed that is capable of issuing very accurate long-term prediction of sunspot number time series. A locally linear neurofuzzy model is optimized for each of the principal components obtained from singular spectrum analysis, and the multi-step predicted values are recombined to make the sunspot number time series. The proposed method is used for solar cycles 22 and 23 and the results are remarkably good in comparison to the predictions made by solar dynamo and precursor methods. An early prediction of the maximum smoothed international sunspot number for cycle 24 is 145 in 2011 2012.

  4. Prediction of Response to Preoperative Chemoradiotherapy in Rectal Cancer by Multiplex Kinase Activity Profiling

    SciTech Connect

    Folkvord, Sigurd; Flatmark, Kjersti; Dueland, Svein

    2010-10-01

    Purpose: Tumor response of rectal cancer to preoperative chemoradiotherapy (CRT) varies considerably. In experimental tumor models and clinical radiotherapy, activity of particular subsets of kinase signaling pathways seems to predict radiation response. This study aimed to determine whether tumor kinase activity profiles might predict tumor response to preoperative CRT in locally advanced rectal cancer (LARC). Methods and Materials: Sixty-seven LARC patients were treated with a CRT regimen consisting of radiotherapy, fluorouracil, and, where possible, oxaliplatin. Pretreatment tumor biopsy specimens were analyzed using microarrays with kinase substrates, and the resulting substrate phosphorylation patterns were correlated with tumor response to preoperative treatment as assessed by histomorphologic tumor regression grade (TRG). A predictive model for TRG scores from phosphosubstrate signatures was obtained by partial-least-squares discriminant analysis. Prediction performance was evaluated by leave-one-out cross-validation and use of an independent test set. Results: In the patient population, 73% and 15% were scored as good responders (TRG 1-2) or intermediate responders (TRG 3), whereas 12% were assessed as poor responders (TRG 4-5). In a subset of 7 poor responders and 12 good responders, treatment outcome was correctly predicted for 95%. Application of the prediction model on the remaining patient samples resulted in correct prediction for 85%. Phosphosubstrate signatures generated by poor-responding tumors indicated high kinase activity, which was inhibited by the kinase inhibitor sunitinib, and several discriminating phosphosubstrates represented proteins derived from signaling pathways implicated in radioresistance. Conclusions: Multiplex kinase activity profiling may identify functional biomarkers predictive of tumor response to preoperative CRT in LARC.

  5. 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

  6. Application of Avco data analysis and prediction techniques (ADAPT) to prediction of sunspot activity

    NASA Technical Reports Server (NTRS)

    Hunter, H. E.; Amato, R. A.

    1972-01-01

    The results are presented of the application of Avco Data Analysis and Prediction Techniques (ADAPT) to derivation of new algorithms for the prediction of future sunspot activity. The ADAPT derived algorithms show a factor of 2 to 3 reduction in the expected 2-sigma errors in the estimates of the 81-day running average of the Zurich sunspot numbers. The report presents: (1) the best estimates for sunspot cycles 20 and 21, (2) a comparison of the ADAPT performance with conventional techniques, and (3) specific approaches to further reduction in the errors of estimated sunspot activity and to recovery of earlier sunspot historical data. The ADAPT programs are used both to derive regression algorithm for prediction of the entire 11-year sunspot cycle from the preceding two cycles and to derive extrapolation algorithms for extrapolating a given sunspot cycle based on any available portion of the cycle.

  7. Recent advances in active control of aircraft cabin noise

    NASA Astrophysics Data System (ADS)

    Mathur, Gopal; Fuller, Christopher

    2002-11-01

    Active noise control techniques can provide significant reductions in aircraft interior noise levels without the structural modifications or weight penalties usually associated with passive techniques, particularly for low frequency noise. Our main objective in this presentation is to give a review of active control methods and their applications to aircraft cabin noise reduction with an emphasis on recent advances and challenges facing the noise control engineer in the practical application of these techniques. The active noise control method using secondary acoustic sources, e.g., loudspeakers, as control sources for tonal noise reduction is first discussed with results from an active noise control flight test demonstration. An innovative approach of applying control forces directly to the fuselage structure using piezoelectric actuators, known as active structural acoustic control (ASAC), to control cabin noise is then presented. Experimental results from laboratory ASAC tests conducted on a full-scale fuselage and from flight tests on a helicopter will be discussed. Finally, a hybrid active/passive noise control approach for achieving significant broadband noise reduction will be discussed. Experimental results of control of broadband noise transmission through an aircraft structure will be presented.

  8. Aerodynamic Design Study of an Advanced Active Twist Rotor

    NASA Technical Reports Server (NTRS)

    Sekula, Martin K.; Wilbur, Matthew L.; Yeager, William T., Jr.

    2003-01-01

    An Advanced Active Twist Rotor (AATR) is currently being developed by the U.S. Army Vehicle Technology Directorate at NASA Langley Research Center. As a part of this effort, an analytical study was conducted to determine the impact of blade geometry on active-twist performance and, based on those findings, propose a candidate aerodynamic design for the AATR. The process began by creating a baseline design which combined the dynamic design of the original Active Twist Rotor and the aerodynamic design of a high lift rotor concept. The baseline model was used to conduct a series of parametric studies to examine the effect of linear blade twist and blade tip sweep, droop, and taper on active-twist performance. Rotor power requirements and hub vibration were also examined at flight conditions ranging from hover to advance ratio = 0.40. A total of 108 candidate designs were analyzed using the second-generation version of the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics (CAMRAD II) code. The study concluded that the vibration reduction capabilities of a rotor utilizing controlled, strain-induced twisting are enhanced through the incorporation of blade tip sweep, droop, and taper into the blade design, while they are degraded by increasing the nose-down linear blade twist. Based on the analysis of rotor power, hub vibration, and active-twist response, a candidate aerodynamic design for the AATR consisting of a blade with approximately 10 degrees of linear blade twist and a blade tip design with 30 degree sweep, 10 degree droop, and 2.5:1 taper ratio over the outer five percent of the blade is proposed.

  9. A new mathematical solution for predicting char activation reactions

    USGS Publications Warehouse

    Rafsanjani, H.H.; Jamshidi, E.; Rostam-Abadi, M.

    2002-01-01

    The differential conservation equations that describe typical gas-solid reactions, such as activation of coal chars, yield a set of coupled second-order partial differential equations. The solution of these coupled equations by exact analytical methods is impossible. In addition, an approximate or exact solution only provides predictions for either reaction- or diffusion-controlling cases. A new mathematical solution, the quantize method (QM), was applied to predict the gasification rates of coal char when both chemical reaction and diffusion through the porous char are present. Carbon conversion rates predicted by the QM were in closer agreement with the experimental data than those predicted by the random pore model and the simple particle model. ?? 2002 Elsevier Science Ltd. All rights reserved.

  10. 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.

  11. Predicting Physical Activity Promotion in Health Care Settings.

    ERIC Educational Resources Information Center

    Faulkner, Guy; Biddle, Stuart

    2001-01-01

    Tested the theory of planned behavior's (TPB) ability to predict stage of change for physical activity promotion among health professionals. Researchers measured attitudes, subjective norms, intentions, perceived behavioral control, and stage of change, then later reassessed stage of change. TPB variables of attitude, subjective norms, perceived…

  12. Predicting Work Activities with Divergent Thinking Tests: A Longitudinal Study

    ERIC Educational Resources Information Center

    Clapham, Maria M.; Cowdery, Edwina M.; King, Kelly E.; Montang, Melissa A.

    2005-01-01

    This study examined whether divergent thinking test scores obtained from engineering students during college predicted creative work activities fifteen years later. Results showed that a subscore of the "Owens Creativity Test", which assesses divergent thinking about mechanical objects, correlated significantly with self-ratings of creative work…

  13. Prediction of energy expenditure and physical activity in preschoolers

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Accurate, nonintrusive, and feasible methods are needed to predict energy expenditure (EE) and physical activity (PA) levels in preschoolers. Herein, we validated cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on accelerometry and heart rate (HR) ...

  14. FY09 Advanced Instrumentation and Active Interrogation Research for Safeguards

    SciTech Connect

    D. L. Chichester; S. A. Pozzi; E. H. Seabury; J. L. Dolan; M. Flaska; J. T. Johnson; S. M. Watson; J. Wharton

    2009-08-01

    Multiple small-scale projects have been undertaken to investigate advanced instrumentation solutions for safeguard measurement challenges associated with advanced fuel cycle facilities and next-generation fuel reprocessing installations. These activities are in support of the U.S. Department of Energy's Fuel Cycle Research and Development program and its Materials Protection, Accounting, and Control for Transmutation (MPACT) campaign. 1) Work was performed in a collaboration with the University of Michigan (Prof. Sara Pozzi, co-PI) to investigate the use of liquid-scintillator radiation detectors for assaying mixed-oxide (MOX) fuel, to characterize its composition and to develop advanced digital pulse-shape discrimination algorithms for performing time-correlation measurements in the MOX fuel environment. This work included both simulations and experiments and has shown that these techniques may provide a valuable approach for use within advanced safeguard measurement scenarios. 2) Work was conducted in a collaboration with Oak Ridge National Laboratory (Dr. Paul Hausladen, co-PI) to evaluate the strengths and weaknesses of the fast-neutron coded-aperture imaging technique for locating and characterizing fissile material, and as a tool for performing hold-up measurements in fissile material handling facilities. This work involved experiments at Idaho National Laboratory, using MOX fuel and uranium metal, in both passive and active interrogation configurations. A complete analysis has not yet been completed but preliminary results suggest several potential uses for the fast neutron imaging technique. 3) Work was carried out to identify measurement approaches for determining nitric acid concentration in the range of 1 – 4 M and beyond. This work included laboratory measurements to investigate the suitability of prompt-gamma neutron activation analysis for this measurement and product reviews of other commercial solutions. Ultrasonic density analysis appears to be

  15. EarthCube Activities: Community Engagement Advancing Geoscience Research

    NASA Astrophysics Data System (ADS)

    Kinkade, D.

    2015-12-01

    Our ability to advance scientific research in order to better understand complex Earth systems, address emerging geoscience problems, and meet societal challenges is increasingly dependent upon the concept of Open Science and Data. Although these terms are relatively new to the world of research, Open Science and Data in this context may be described as transparency in the scientific process. This includes the discoverability, public accessibility and reusability of scientific data, as well as accessibility and transparency of scientific communication (www.openscience.org). Scientists and the US government alike are realizing the critical need for easy discovery and access to multidisciplinary data to advance research in the geosciences. The NSF-supported EarthCube project was created to meet this need. EarthCube is developing a community-driven common cyberinfrastructure for the purpose of accessing, integrating, analyzing, sharing and visualizing all forms of data and related resources through advanced technological and computational capabilities. Engaging the geoscience community in EarthCube's development is crucial to its success, and EarthCube is providing several opportunities for geoscience involvement. This presentation will provide an overview of the activities EarthCube is employing to entrain the community in the development process, from governance development and strategic planning, to technical needs gathering. Particular focus will be given to the collection of science-driven use cases as a means of capturing scientific and technical requirements. Such activities inform the development of key technical and computational components that collectively will form a cyberinfrastructure to meet the research needs of the geoscience community.

  16. [Advances on chemical constituents and pharmacological activity of genus Scilla].

    PubMed

    Fan, Meng-Yang; Wang, Yan-Min; Wang, Zhi-Min; Gao, Hui-Min

    2014-01-01

    The genus Scilla consists of 90 species widely distributed in Europe, Asia and Africa, one and its variant of which can be found in China Some species of the genus have been used in traditional medicine to treat various diseases related to inflammation and pain. Phytochemical studies have demonstrated the presence of triterpene and tritepenoid saponins derived from eucosterol, bufadienolides, alkaloids, stilbenoids and lignan in the plants of this genus. Various bioactivities such as antimicrobial, anti-inflammatory, antioxidant, anti-tumor and glycosidase inhibitory activities, have been reported. In this review, the advance of chemical constituents and pharmacological activities of the Scilla species are summarized for further development and utilization of the resource. PMID:24761625

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  18. 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

  19. Prediction of adolescents doing physical activity after completing secondary education.

    PubMed

    Moreno-Murcia, Juan Antonio; Huéscar, Elisa; Cervelló, Eduardo

    2012-03-01

    The purpose of this study, based on the self-determination theory (Ryan & Deci, 2000) was to test the prediction power of student's responsibility, psychological mediators, intrinsic motivation and the importance attached to physical education in the intention to continue to practice some form of physical activity and/or sport, and the possible relationships that exist between these variables. We used a sample of 482 adolescent students in physical education classes, with a mean age of 14.3 years, which were measured for responsibility, psychological mediators, sports motivation, the importance of physical education and intention to be physically active. We completed an analysis of structural equations modelling. The results showed that the responsibility positively predicted psychological mediators, and this predicted intrinsic motivation, which positively predicted the importance students attach to physical education, and this, finally, positively predicted the intention of the student to continue doing sport. Results are discussed in relation to the promotion of student's responsibility towards a greater commitment to the practice of physical exercise. PMID:22379700

  20. A community computational challenge to predict the activity of pairs of compounds

    PubMed Central

    Bansal, Mukesh; Yang, Jichen; Karan, Charles; Menden, Michael P; Costello, James C; Tang, Hao; Xiao, Guanghua; Li, Yajuan; Allen, Jeffrey; Zhong, Rui; Chen, Beibei; Kim, Minsoo; Wang, Tao; Heiser, Laura M; Realubit, Ronald; Mattioli, Michela; Alvarez, Mariano J; Shen, Yao; Gallahan, Daniel; Singer, Dinah; Saez-Rodriguez, Julio; Xie, Yang; Stolovitzky, Gustavo; Califano, Andrea

    2015-01-01

    Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction. PMID:25419740

  1. Predicting Active Users' Personality Based on Micro-Blogging Behaviors

    PubMed Central

    Hao, Bibo; Guan, Zengda; Zhu, Tingshao

    2014-01-01

    Because of its richness and availability, micro-blogging has become an ideal platform for conducting psychological research. In this paper, we proposed to predict active users' personality traits through micro-blogging behaviors. 547 Chinese active users of micro-blogging participated in this study. Their personality traits were measured by the Big Five Inventory, and digital records of micro-blogging behaviors were collected via web crawlers. After extracting 845 micro-blogging behavioral features, we first trained classification models utilizing Support Vector Machine (SVM), differentiating participants with high and low scores on each dimension of the Big Five Inventory. The classification accuracy ranged from 84% to 92%. We also built regression models utilizing PaceRegression methods, predicting participants' scores on each dimension of the Big Five Inventory. The Pearson correlation coefficients between predicted scores and actual scores ranged from 0.48 to 0.54. Results indicated that active users' personality traits could be predicted by micro-blogging behaviors. PMID:24465462

  2. Predicting active users' personality based on micro-blogging behaviors.

    PubMed

    Li, Lin; Li, Ang; Hao, Bibo; Guan, Zengda; Zhu, Tingshao

    2014-01-01

    Because of its richness and availability, micro-blogging has become an ideal platform for conducting psychological research. In this paper, we proposed to predict active users' personality traits through micro-blogging behaviors. 547 Chinese active users of micro-blogging participated in this study. Their personality traits were measured by the Big Five Inventory, and digital records of micro-blogging behaviors were collected via web crawlers. After extracting 839 micro-blogging behavioral features, we first trained classification models utilizing Support Vector Machine (SVM), differentiating participants with high and low scores on each dimension of the Big Five Inventory [corrected]. The classification accuracy ranged from 84% to 92%. We also built regression models utilizing PaceRegression methods, predicting participants' scores on each dimension of the Big Five Inventory. The Pearson correlation coefficients between predicted scores and actual scores ranged from 0.48 to 0.54. Results indicated that active users' personality traits could be predicted by micro-blogging behaviors. PMID:24465462

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

    ERIC Educational Resources Information Center

    DeRose, Diego S.; Clement, Russell W.

    2011-01-01

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

  4. 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.

  5. Australian Tropical Cyclone Activity: Interannual Prediction and Climate Change

    NASA Astrophysics Data System (ADS)

    Nicholls, N.

    2014-12-01

    It is 35 years since it was first demonstrated that interannual variations in seasonal Australian region tropical cyclone (TC) activity could be predicted using simple indices of the El Niño - Southern Oscillation (ENSO). That demonstration (Nicholls, 1979), which was surprising and unexpected at the time, relied on only 25 years of data (1950-1975), but its later confirmation eventually led to the introduction of operational seasonal tropical cyclone activity. It is worth examining how well the ENSO-TC relationship has performed, over the period since 1975. Changes in observational technology, and even how a tropical cyclone is defined, have affected the empirical relationships between ENSO and seasonal activity, and ways to overcome this in forecasting seasonal activity will be discussed. Such changes also complicate the investigation of long-term trends in cyclone activity. The early work linked cyclone activity to local sea surface temperature thereby leading to the expectation that global warming would result in an increase in cyclone activity. But studies in the 1990s (eg., Nicholls et al., 1998) suggested that such an increase in activity was not occurring, neither in the Australian region nor elsewhere. Trends in Australian tropical cyclone activity will be discussed, and the confounding influence of factors such as changes in observational technologies will be examined. Nicholls, N. 1979. A possible method for predicting seasonal tropical cyclone activity in the Australian region. Mon. Weath. Rev., 107, 1221-1224 Nicholls, N., Landsea, C., and Gill, J., 1998. Recent trends in Australian region tropical cyclone activity. Meteorology and Atmospheric Physics, 65, 197-205.

  6. 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.

  7. Platelet Serotonin Transporter Function Predicts Default-Mode Network Activity

    PubMed Central

    Kasess, Christian H.; Meyer, Bernhard M.; Hofmaier, Tina; Diers, Kersten; Bartova, Lucie; Pail, Gerald; Huf, Wolfgang; Uzelac, Zeljko; Hartinger, Beate; Kalcher, Klaudius; Perkmann, Thomas; Haslacher, Helmuth; Meyer-Lindenberg, Andreas; Kasper, Siegfried; Freissmuth, Michael; Windischberger, Christian; Willeit, Matthäus; Lanzenberger, Rupert; Esterbauer, Harald; Brocke, Burkhard; Moser, Ewald; Sitte, Harald H.; Pezawas, Lukas

    2014-01-01

    Background The serotonin transporter (5-HTT) is abundantly expressed in humans by the serotonin transporter gene SLC6A4 and removes serotonin (5-HT) from extracellular space. A blood-brain relationship between platelet and synaptosomal 5-HT reuptake has been suggested, but it is unknown today, if platelet 5-HT uptake can predict neural activation of human brain networks that are known to be under serotonergic influence. Methods A functional magnetic resonance study was performed in 48 healthy subjects and maximal 5-HT uptake velocity (Vmax) was assessed in blood platelets. We used a mixed-effects multilevel analysis technique (MEMA) to test for linear relationships between whole-brain, blood-oxygen-level dependent (BOLD) activity and platelet Vmax. Results The present study demonstrates that increases in platelet Vmax significantly predict default-mode network (DMN) suppression in healthy subjects independent of genetic variation within SLC6A4. Furthermore, functional connectivity analyses indicate that platelet Vmax is related to global DMN activation and not intrinsic DMN connectivity. Conclusion This study provides evidence that platelet Vmax predicts global DMN activation changes in healthy subjects. Given previous reports on platelet-synaptosomal Vmax coupling, results further suggest an important role of neuronal 5-HT reuptake in DMN regulation. PMID:24667541

  8. Predicting activity approach based on new atoms similarity kernel function.

    PubMed

    Abu El-Atta, Ahmed H; Moussa, M I; Hassanien, Aboul Ella

    2015-07-01

    Drug design is a high cost and long term process. To reduce time and costs for drugs discoveries, new techniques are needed. Chemoinformatics field implements the informational techniques and computer science like machine learning and graph theory to discover the chemical compounds properties, such as toxicity or biological activity. This is done through analyzing their molecular structure (molecular graph). To overcome this problem there is an increasing need for algorithms to analyze and classify graph data to predict the activity of molecules. Kernels methods provide a powerful framework which combines machine learning with graph theory techniques. These kernels methods have led to impressive performance results in many several chemoinformatics problems like biological activity prediction. This paper presents a new approach based on kernel functions to solve activity prediction problem for chemical compounds. First we encode all atoms depending on their neighbors then we use these codes to find a relationship between those atoms each other. Then we use relation between different atoms to find similarity between chemical compounds. The proposed approach was compared with many other classification methods and the results show competitive accuracy with these methods. PMID:26117822

  9. Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations

    NASA Astrophysics Data System (ADS)

    Marre, O.; El Boustani, S.; Frégnac, Y.; Destexhe, A.

    2009-04-01

    We designed a model-based analysis to predict the occurrence of population patterns in distributed spiking activity. Using a maximum entropy principle with a Markovian assumption, we obtain a model that accounts for both spatial and temporal pairwise correlations among neurons. This model is tested on data generated with a Glauber spin-glass system and is shown to correctly predict the occurrence probabilities of spatiotemporal patterns significantly better than Ising models only based on spatial correlations. This increase of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep. This approach can also be used to generate surrogates that reproduce the spatial and temporal correlations of a given data set.

  10. Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations

    SciTech Connect

    Marre, O.; El Boustani, S.; Fregnac, Y.; Destexhe, A.

    2009-04-03

    We designed a model-based analysis to predict the occurrence of population patterns in distributed spiking activity. Using a maximum entropy principle with a Markovian assumption, we obtain a model that accounts for both spatial and temporal pairwise correlations among neurons. This model is tested on data generated with a Glauber spin-glass system and is shown to correctly predict the occurrence probabilities of spatiotemporal patterns significantly better than Ising models only based on spatial correlations. This increase of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep. This approach can also be used to generate surrogates that reproduce the spatial and temporal correlations of a given data set.

  11. Compulsivity predicts fronto striatal activation in severely anorectic individuals.

    PubMed

    Rothemund, Y; Buchwald, C; Georgiewa, P; Bohner, G; Bauknecht, H-C; Ballmaier, M; Klapp, B F; Klingebiel, R

    2011-12-01

    Anorexia nervosa is a severe illness and shows one of the highest death rates among psychiatric or psychosomatic diseases. However, despite several lines of research, the etiology of this disease is still unknown. One of those features is the rigidity of behaviors, for example, controlling of weight and pursuing of thinness, that often meets the criteria for obsessive-compulsive behavior. In this study, it was investigated whether the clinical feature of compulsivity in anorexia nervosa patients relates to regional brain activation. Using functional magnetic resonance imaging, 12 severely anorectic women were compared to 12 normal-weight female individuals following a cue-reactivity paradigm. Cues comprised food cues of high and low calorie content as well as eating-related utensils. Voxel-based morphometric analysis indicated significantly overall reduced gray matter volume and significantly increased cerebrospinal fluids in anorexia nervosa (AN) patients, which was controlled for in subsequent analyses. Following the high-calorie stimulation, AN patients activated the right caudate body and right precuneus, whereas control subjects did not show significant regional activations. In both other conditions, low-calorie foods and eating utensils, regional brain activations did not survive FDR thresholds. During the high-calorie condition, compulsivity, that is, the subscore "obsessive thoughts," predicted activation of the superior frontal gyrus [Brodmann areas (BA) 10], inferior frontal gyrus, anterior cingulate cortex (BA 32), cingulate gyrus (BA 24), caudate body, cuneus, pre- and postcentral gyrus. The subscore "compulsive acts" correlated with activation of the claustrum during the high-calorie condition and predicted a number of deactivations of frontal and temporal regions. We conclude that in severely anorectic individuals, the degree of compulsivity predicts activation and deactivation of the fronto-striatal pathway. PMID:21952129

  12. [Activities of Research Institute for Advanced Computer Science

    NASA Technical Reports Server (NTRS)

    Gross, Anthony R. (Technical Monitor); Leiner, Barry M.

    2001-01-01

    The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administrations missions. RIACS is located at the NASA Ames Research Center, Moffett Field, California. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1. Automated Reasoning for Autonomous Systems Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. 2. Human-Centered Computing Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities. 3. High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to analysis of large scientific datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  14. Toward the Prediction of FBPase Inhibitory Activity Using Chemoinformatic Methods

    PubMed Central

    Hao, Ming; Zhang, Shuwei; Qiu, Jieshan

    2012-01-01

    Currently, Chemoinformatic methods are used to perform the prediction for FBPase inhibitory activity. A genetic algorithm-random forest coupled method (GA-RF) was proposed to predict fructose 1,6-bisphosphatase (FBPase) inhibitors to treat type 2 diabetes mellitus using the Mold2 molecular descriptors. A data set of 126 oxazole and thiazole analogs was used to derive the GA-RF model, yielding the significant non-cross-validated correlation coefficient r2ncv and cross-validated r2cv values of 0.96 and 0.67 for the training set, respectively. The statistically significant model was validated by a test set of 64 compounds, producing the prediction correlation coefficient r2pred of 0.90. More importantly, the building GA-RF model also passed through various criteria suggested by Tropsha and Roy with r2o and r2m values of 0.90 and 0.83, respectively. In order to compare with the GA-RF model, a pure RF model developed based on the full descriptors was performed as well for the same data set. The resulting GA-RF model with significantly internal and external prediction capacities is beneficial to the prediction of potential oxazole and thiazole series of FBPase inhibitors prior to chemical synthesis in drug discovery programs. PMID:22837677

  15. Statistical analysis and verification of 3-hourly geomagnetic activity probability predictions

    NASA Astrophysics Data System (ADS)

    Wang, Jingjing; Zhong, Qiuzhen; Liu, Siqing; Miao, Juan; Liu, Fanghua; Li, Zhitao; Tang, Weiwei

    2015-12-01

    The Space Environment Prediction Center (SEPC) has classified geomagnetic activity into four levels: quiet to unsettled (Kp < 4), active (Kp = 4), minor to moderate storm (Kp = 5 or 6), and major to severe storm (Kp > 6). The 3-hourly Kp index prediction product provided by the SEPC is updated half hourly. In this study, the statistical conditional forecast models for the 3-hourly geomagnetic activity level were developed based on 10 years of data and applied to more than 3 years of data, using the previous Kp index, interplanetary magnetic field, and solar wind parameters measured by the Advanced Composition Explorer as conditional parameters. The quality of the forecast models was measured and compared against verifications of accuracy, reliability, discrimination capability, and skill of predicting all geomagnetic activity levels, especially the probability of reaching the storm level given a previous "calm" (nonstorm level) or "storm" (storm level) condition. It was found that the conditional models that used the previous Kp index, the peak value of BtV (the product of the total interplanetary magnetic field and speed), the average value of Bz (the southerly component of the interplanetary magnetic field), and BzV (the product of the southerly component of the interplanetary magnetic field and speed) over the last 6 h as conditional parameters provide a relative operating characteristic area of 0.64 and can be an appropriate predictor for the probability forecast of geomagnetic activity level.

  16. Diesel engine emissions and combustion predictions using advanced mixing models applicable to fuel sprays

    NASA Astrophysics Data System (ADS)

    Abani, Neerav; Reitz, Rolf D.

    2010-09-01

    An advanced mixing model was applied to study engine emissions and combustion with different injection strategies ranging from multiple injections, early injection and grouped-hole nozzle injection in light and heavy duty diesel engines. The model was implemented in the KIVA-CHEMKIN engine combustion code and simulations were conducted at different mesh resolutions. The model was compared with the standard KIVA spray model that uses the Lagrangian-Drop and Eulerian-Fluid (LDEF) approach, and a Gas Jet spray model that improves predictions of liquid sprays. A Vapor Particle Method (VPM) is introduced that accounts for sub-grid scale mixing of fuel vapor and more accurately and predicts the mixing of fuel-vapor over a range of mesh resolutions. The fuel vapor is transported as particles until a certain distance from nozzle is reached where the local jet half-width is adequately resolved by the local mesh scale. Within this distance the vapor particle is transported while releasing fuel vapor locally, as determined by a weighting factor. The VPM model more accurately predicts fuel-vapor penetrations for early cycle injections and flame lift-off lengths for late cycle injections. Engine combustion computations show that as compared to the standard KIVA and Gas Jet spray models, the VPM spray model improves predictions of in-cylinder pressure, heat released rate and engine emissions of NOx, CO and soot with coarse mesh resolutions. The VPM spray model is thus a good tool for efficiently investigating diesel engine combustion with practical mesh resolutions, thereby saving computer time.

  17. 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.

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

    PubMed

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

    2008-05-01

    The climate of the North Atlantic region exhibits fluctuations on decadal timescales that have large societal consequences. Prominent examples include hurricane activity in the Atlantic, and surface-temperature and rainfall variations over North America, Europe and northern Africa. Although these multidecadal variations are potentially predictable if the current state of the ocean is known, the lack of subsurface ocean observations that constrain this state has been a limiting factor for realizing the full skill potential of such predictions. Here we apply a simple approach-that uses only sea surface temperature (SST) observations-to partly overcome this difficulty and perform retrospective decadal predictions with a climate model. Skill is improved significantly relative to predictions made with incomplete knowledge of the ocean state, particularly in the North Atlantic and tropical Pacific oceans. Thus these results point towards the possibility of routine decadal climate predictions. Using this method, and by considering both internal natural climate variations and projected future anthropogenic forcing, we make the following forecast: over the next decade, the current Atlantic meridional overturning circulation will weaken to its long-term mean; moreover, North Atlantic SST and European and North American surface temperatures will cool slightly, whereas tropical Pacific SST will remain almost unchanged. Our results suggest that global surface temperature may not increase over the next decade, as natural climate variations in the North Atlantic and tropical Pacific temporarily offset the projected anthropogenic warming. PMID:18451859

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

    ERIC Educational Resources Information Center

    Heil, Daniel P.

    2006-01-01

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

  20. Predictions for Swift Follow-up Observations of Advanced LIGO/Virgo Gravitational Wave Sources

    NASA Astrophysics Data System (ADS)

    Racusin, Judith; Evans, Phil; Connaughton, Valerie

    2015-04-01

    The likely detection of gravitational waves associated with the inspiral of neutron star binaries by the upcoming advanced LIGO/Virgo observatories will be complemented by searches for electromagnetic counterparts over large areas of the sky by Swift and other observatories. As short gamma-ray bursts (GRB) are the most likely electromagnetic counterpart candidates to these sources, we can make predictions based upon the last decade of GRB observations by Swift and Fermi. Swift is uniquely capable of accurately localizing new transients rapidly over large areas of the sky in single and tiled pointings, enabling ground-based follow-up. We describe simulations of the detectability of short GRB afterglows by Swift given existing and hypothetical tiling schemes with realistic observing conditions and delays, which guide the optimal observing strategy and improvements provided by coincident detection with observatories such as Fermi-GBM.

  1. 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.

  2. Prefrontal Activity Predicts Monkeys' Decisions During an Auditory Category Task

    PubMed Central

    Lee, Jung H.; Russ, Brian E.; Orr, Lauren E.; Cohen, Yale E.

    2009-01-01

    The neural correlates that relate auditory categorization to aspects of goal-directed behavior, such as decision-making, are not well understood. Since the prefrontal cortex (PFC) plays an important role in executive function and the categorization of auditory objects, we hypothesized that neural activity in the PFC should predict an animal's behavioral reports (decisions) during a category task. To test this hypothesis, we tested PFC activity that was recorded while monkeys categorized human spoken words (Russ et al., 2008b). We found that activity in the ventrolateral PFC, on average, correlated best with the monkeys' choices than with the auditory stimuli. This finding demonstrates a direct link between PFC activity and behavioral choices during a non-spatial auditory task. PMID:19587846

  3. Predicting above normal wildfire activity in southern Europe as a function of meteorological drought

    NASA Astrophysics Data System (ADS)

    Gudmundsson, L.; Rego, F. C.; Rocha, M.; Seneviratne, S. I.

    2014-08-01

    Wildfires are a recurrent feature of ecosystems in southern Europe, regularly causing large ecological and socio-economic damages. For efficient management of this hazard, long lead time forecasts could be valuable tools. Using logistic regression, we show that the probability of above normal summer wildfire activity in the 1985-2010 time period can be forecasted as a function of meteorological drought with significant predictability (p \\lt 0.05) several months in advance. The results show that long lead time forecasts of this natural hazard are feasible in southern Europe, which could potentially aid decision-makers in the design of strategies for forest management.

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

    PubMed Central

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

    2015-01-01

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

  5. An Advanced Data Assimilation System for Estuary and Coastal Ocean Prediction

    NASA Astrophysics Data System (ADS)

    Hoffman, M. J.; Murtugudde, R.; Brown, C. W.

    2008-12-01

    We are developing an advanced data assimilation system for the Chesapeake Bay Forecast System, a regional Earth System Prediction model. To accomplish this, the Regional Ocean Modeling System (ROMS) implementation on the Chesapeake Bay (ChesROMS) has been interfaced with the Local Ensemble Transform Kalman Filter (LETKF) to create an efficient data assimilation system. The LETKF, an ensemble Kalman filtering scheme developed at the University of Maryland, is among the most advanced data assimilation methods and is very effective for large, non-linear dynamical systems in both sparse and dense data coverage situations. Crucial to the LETKF-ChesROMS assimilation system is having accurate open ocean boundary conditions from GODAE and other large scale products. Currently, the assimilation system is run with prescribed climatological boundary conditions in a relatively coarse resolution. In perfect model experiments using ChesROMS, the filter converges quickly and greatly reduces the analysis and subsequent forecast errors in the temperature, salinity, and velocity fields. This error reduction has proved fairly robust to sensitivity studies such as reduced data coverage. The LETKF also provides an efficient algorithm for error estimation and facilitates the investigation of the spatial distribution of the error. This information will be used to determine areas where more monitoring is needed and to address other issues of the observational impacts on the analyses and observational system simulation experiments, in addition to forecast initialization experiments and regional reanalyses for the past decade.

  6. 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

  7. UTILITY OF MECHANISTIC MODELS FOR DIRECTING ADVANCED SEPARATIONS RESEARCH & DEVELOPMENT ACTIVITIES: Electrochemically Modulated Separation Example

    SciTech Connect

    Schwantes, Jon M.

    2009-06-01

    The objective for this work was to demonstrate the utility of mechanistic computer models designed to simulate actinide behavior for use in efficiently and effectively directing advanced laboratory R&D activities associated with developing advanced separations methods.

  8. Advanced Active-Magnetic-Bearing Thrust-Measurement System

    NASA Technical Reports Server (NTRS)

    Imlach, Joseph; Kasarda, Mary; Blumber, Eric

    2008-01-01

    An advanced thrust-measurement system utilizes active magnetic bearings to both (1) levitate a floating frame in all six degrees of freedom and (2) measure the levitation forces between the floating frame and a grounded frame. This system was developed for original use in measuring the thrust exerted by a rocket engine mounted on the floating frame, but can just as well be used in other force-measurement applications. This system offers several advantages over prior thrust-measurement systems based on mechanical support by flexures and/or load cells: The system includes multiple active magnetic bearings for each degree of freedom, so that by selective use of one, some, or all of these bearings, it is possible to test a given article over a wide force range in the same fixture, eliminating the need to transfer the article to different test fixtures to obtain the benefit of full-scale accuracy of different force-measurement devices for different force ranges. Like other active magnetic bearings, the active magnetic bearings of this system include closed-loop control subsystems, through which the stiffness and damping characteristics of the magnetic bearings can be modified electronically. The design of the system minimizes or eliminates cross-axis force-measurement errors. The active magnetic bearings are configured to provide support against movement along all three orthogonal Cartesian axes, and such that the support along a given axis does not produce force along any other axis. Moreover, by eliminating the need for such mechanical connections as flexures used in prior thrust-measurement systems, magnetic levitation of the floating frame eliminates what would otherwise be major sources of cross-axis forces and the associated measurement errors. Overall, relative to prior mechanical-support thrust-measurement systems, this system offers greater versatility for adaptation to a variety of test conditions and requirements. The basic idea of most prior active

  9. 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.

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

    PubMed

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

    2016-07-01

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

  11. 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.

  12. Improving realtime predictions of magnetospheric activities using STEREO Space Weather Beacon

    NASA Astrophysics Data System (ADS)

    Bala, R.; Reiff, P. H.

    2011-12-01

    The Rice neural network models of geomagnetic activity indices Kp, Dst and AE (available from \\url{http://mms.rice.edu/realtime/forecast.html}), driven by the ACE solar wind data, have been actively running in near-realtime mode to provide short-term predictions of magnetospheric activities; subscribers to our ``spacalrt" system receive email alerts and notices of space weather based on key discriminator levels. Active structures that are likely to erupt on the sun and resulting in solar flares and/or Coronal Mass Ejections (CMEs) are now being well imaged by instruments aboard STEREO, which also provides multipoint, realtime and continuous information of the solar wind, interplanetary magnetic field, solar energetic particles through its Space Weather Beacon IMPACT and PLASTIC. The spacecraft lagging Earth (STEREO-B) and being ahead in the Parker spiral, is well suited to provide longer lead times to predictions of any common measures of geoeffectiveness resulting from solar wind-magnetospheric interactions such as Kp, Dst and AE indices. As our models are constantly evolving, our desire to drive them by indulging these advanced instruments is to provide longer lead times. Furthermore, this paper also investigates the geoeffectiveness of predicting CME-driven storms.

  13. Resource assurance predicts specialist and generalist bee activity in drought

    PubMed Central

    Minckley, Robert L.; Roulston, T'ai H.; Williams, Neal M.

    2013-01-01

    Many short-lived desert organisms remain in diapause during drought. Theoretically, the cues desert species use to continue diapause through drought should differ depending on the availability of critical resources, but the unpredictability and infrequent occurrence of climate extremes and reduced insect activity during such events make empirical tests of this prediction difficult. An intensive study of a diverse bee–plant community through a drought event found that bee specialists of a drought-sensitive host plant were absent in the drought year in contrast to generalist bees and to specialist bees of a drought-insensitive host plant. Different responses of bee species to drought indicate that the diapause cues used by bee species allow them to reliably predict host availability. Species composition of the bee community in drought shifted towards mostly generalist species. However, we predict that more frequent and extended drought, predicted by climate change models for southwest North America, will result in bee communities that are species-poor and dominated by specialist species, as found today in the most arid desert region of North America. PMID:23536593

  14. 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

  15. Overview of Advanced Space Propulsion Activities in the Space Environmental Effects Team at MSFC

    NASA Technical Reports Server (NTRS)

    Edwards, David; Carruth, Ralph; Vaughn, Jason; Schneider, Todd; Kamenetzky, Rachel; Gray, Perry

    2000-01-01

    Exploration of our solar system, and beyond, requires spacecraft velocities beyond our current technological level. Technologies addressing this limitation are numerous. The Space Environmental Effects (SEE) Team at the Marshall Space Flight Center (MSFC) is focused on three discipline areas of advanced propulsion; Tethers, Beamed Energy, and Plasma. This presentation will give an overview of advanced propulsion related activities in the Space Environmental Effects Team at MSFC. Advancements in the application of tethers for spacecraft propulsion were made while developing the Propulsive Small Expendable Deployer System (ProSEDS). New tether materials were developed to meet the specifications of the ProSEDS mission and new techniques had to be developed to test and characterize these tethers. Plasma contactors were developed, tested and modified to meet new requirements. Follow-on activities in tether propulsion include the Air-SEDS activity. Beamed energy activities initiated with an experimental investigation to quantify the momentum transfer subsequent to high power, 5J, ablative laser interaction with materials. The next step with this experimental investigation is to quantify non-ablative photon momentum transfer. This step was started last year and will be used to characterize the efficiency of solar sail materials before and after exposure to Space Environmental Effects (SEE). Our focus with plasma, for propulsion, concentrates on optimizing energy deposition into a magnetically confined plasma and integration of measurement techniques for determining plasma parameters. Plasma confinement is accomplished with the Marshall Magnetic Mirror (M3) device. Initial energy coupling experiments will consist of injecting a 50 amp electron beam into a target plasma. Measurements of plasma temperature and density will be used to determine the effect of changes in magnetic field structure, beam current, and gas species. Experimental observations will be compared to

  16. Prediction of antifungal activity of gemini imidazolium compounds.

    PubMed

    Pałkowski, Łukasz; Błaszczyński, Jerzy; Skrzypczak, Andrzej; Błaszczak, Jan; Nowaczyk, Alicja; Wróblewska, Joanna; Kożuszko, Sylwia; Gospodarek, Eugenia; Słowiński, Roman; Krysiński, Jerzy

    2015-01-01

    The progress of antimicrobial therapy contributes to the development of strains of fungi resistant to antimicrobial drugs. Since cationic surfactants have been described as good antifungals, we present a SAR study of a novel homologous series of 140 bis-quaternary imidazolium chlorides and analyze them with respect to their biological activity against Candida albicans as one of the major opportunistic pathogens causing a wide spectrum of diseases in human beings. We characterize a set of features of these compounds, concerning their structure, molecular descriptors, and surface active properties. SAR study was conducted with the help of the Dominance-Based Rough Set Approach (DRSA), which involves identification of relevant features and relevant combinations of features being in strong relationship with a high antifungal activity of the compounds. The SAR study shows, moreover, that the antifungal activity is dependent on the type of substituents and their position at the chloride moiety, as well as on the surface active properties of the compounds. We also show that molecular descriptors MlogP, HOMO-LUMO gap, total structure connectivity index, and Wiener index may be useful in prediction of antifungal activity of new chemical compounds. PMID:25961015

  17. Prediction of Antifungal Activity of Gemini Imidazolium Compounds

    PubMed Central

    Pałkowski, Łukasz; Błaszczyński, Jerzy; Skrzypczak, Andrzej; Błaszczak, Jan; Nowaczyk, Alicja; Wróblewska, Joanna; Kożuszko, Sylwia; Gospodarek, Eugenia; Słowiński, Roman; Krysiński, Jerzy

    2015-01-01

    The progress of antimicrobial therapy contributes to the development of strains of fungi resistant to antimicrobial drugs. Since cationic surfactants have been described as good antifungals, we present a SAR study of a novel homologous series of 140 bis-quaternary imidazolium chlorides and analyze them with respect to their biological activity against Candida albicans as one of the major opportunistic pathogens causing a wide spectrum of diseases in human beings. We characterize a set of features of these compounds, concerning their structure, molecular descriptors, and surface active properties. SAR study was conducted with the help of the Dominance-Based Rough Set Approach (DRSA), which involves identification of relevant features and relevant combinations of features being in strong relationship with a high antifungal activity of the compounds. The SAR study shows, moreover, that the antifungal activity is dependent on the type of substituents and their position at the chloride moiety, as well as on the surface active properties of the compounds. We also show that molecular descriptors MlogP, HOMO-LUMO gap, total structure connectivity index, and Wiener index may be useful in prediction of antifungal activity of new chemical compounds. PMID:25961015

  18. Baseline Brain Activity Predicts Response to Neuromodulatory Pain Treatment

    PubMed Central

    Jensen, Mark P.; Sherlin, Leslie H.; Fregni, Felipe; Gianas, Ann; Howe, Jon D.; Hakimian, Shahin

    2015-01-01

    Objectives The objective of this study was to examine the associations between baseline electroencephalogram (EEG)-assessed brain oscillations and subsequent response to four neuromodulatory treatments. Based on available research, we hypothesized that baseline theta oscillations would prospectively predict response to hypnotic analgesia. Analyses involving other oscillations and the other treatments (meditation, neurofeedback, and both active and sham transcranial direct current stimulation) were viewed as exploratory, given the lack of previous research examining brain oscillations as predictors of response to these other treatments. Design Randomized controlled study of single sessions of four neuromodulatory pain treatments and a control procedure. Methods Thirty individuals with spinal cord injury and chronic pain had their EEG recorded before each session of four active treatments (hypnosis, meditation, EEG biofeedback, transcranial direct current stimulation) and a control procedure (sham transcranial direct stimulation). Results As hypothesized, more presession theta power was associated with greater response to hypnotic analgesia. In exploratory analyses, we found that less baseline alpha power predicted pain reduction with meditation. Conclusions The findings support the idea that different patients respond to different pain treatments and that between-person treatment response differences are related to brain states as measured by EEG. The results have implications for the possibility of enhancing pain treatment response by either 1) better patient/treatment matching or 2) influencing brain activity before treatment is initiated in order to prepare patients to respond. Research is needed to replicate and confirm the findings in additional samples of individuals with chronic pain. PMID:25287554

  19. 15-PGDH expression as a predictive factor response to neoadjuvant chemotherapy in advanced gastric cancer

    PubMed Central

    Hu, Min; Li, Kai; Maskey, Ninu; Xu, Zhigao; Peng, ChunWei; Tian, Sufang; Li, Yan; Yang, Guifang

    2015-01-01

    Given the various clinical and pathologic responses to neoadjuvant chemotherapy (NACT) in gastric cancer (GC), potential biomarkers that reflecting the efficacy of NACT on GC should be investigated. The aim of this study was to investigate the 15-PGDH expression response to NACT in GC patients and its relationship with prognosis of GC. Immunohistochemical method was used to assess the level of 15-PGDH expression in 56 GC patients who received NACT before surgery and 46 patients who underwent surgical treatment without NACT as well as their corresponding adjacent non-neoplastic tissues. We found that there was no correlation of 15-PGDH expression between non-cancerous gastric tissues and GC tissues (P=0.519), while 15-PGDH expression level in NACT group was higher than that in nNACT group (P=0.015). In patients with NACT, the higher level of 15-PGDH expression was significantly associated with well-moderately differentiated grade (P=0.023), I/II stage (P=0.014) and with no lymph node metastasis (P=0.016). Moreover, statistically significant differences in overall survival (OS) were found among 15-PGDH expression (log-rank test, P<0.001) and TNM stage (log-rank test, P=0.032). Most importantly, expression of 15-PGDH was found to be an independent predictive factor by multivariate analysis (Hazard ratio (HR) 0.315 [0.120-0.827], P=0.019). These findings indicated that NACT could increase 15-PGDH expression in advanced GC patients, and 15-PGDH may serve as a candidate prognostic biomarker of advanced GC response to NACT. PMID:26261578

  20. 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

  1. Selected advanced aerodynamic and active control concepts development

    NASA Technical Reports Server (NTRS)

    1981-01-01

    A task for the Energy Efficient Transport program conducted: (1) The design and wind tunnel development of high-aspect-ratio supercritical wings, investigating the cruise speed regime and also high-lift. (2) The preliminary design and evaluation of an aircraft combining a high-aspect-ratio supercritical wing with a winglet. (3) Active Controls: The determination of criteria, configuration, and flying qualities associated with augmented longitudinal stability of a level likely to be acceptable for the next generation transport; and the design of a practical augmentation system. The baseline against which the work was performed and evaluated was the Douglas DC-X-200 twin engine derivative of the DC-10 transport. The supercritical wing development showed that the cruise and buffet requirements could be achieved and that the wing could be designed to realize a sizable advantage over today's technology. Important advances in high lift performance were shown. The design study of an aircraft with supercritical wing and winglet suggested advantages in weight and fuel economy could be realized. The study of augmented stability, conducted with the aid of a motion base simulator, concluded that a negative static margin was acceptable for the baseline unaugmented aircraft.

  2. Predicting brain activation patterns associated with individual lexical concepts based on five sensory-motor attributes.

    PubMed

    Fernandino, Leonardo; Humphries, Colin J; Seidenberg, Mark S; Gross, William L; Conant, Lisa L; Binder, Jeffrey R

    2015-09-01

    While major advances have been made in uncovering the neural processes underlying perceptual representations, our grasp of how the brain gives rise to conceptual knowledge remains relatively poor. Recent work has provided strong evidence that concepts rely, at least in part, on the same sensory and motor neural systems through which they were acquired, but it is still unclear whether the neural code for concept representation uses information about sensory-motor features to discriminate between concepts. In the present study, we investigate this question by asking whether an encoding model based on five semantic attributes directly related to sensory-motor experience - sound, color, visual motion, shape, and manipulation - can successfully predict patterns of brain activation elicited by individual lexical concepts. We collected ratings on the relevance of these five attributes to the meaning of 820 words, and used these ratings as predictors in a multiple regression model of the fMRI signal associated with the words in a separate group of participants. The five resulting activation maps were then combined by linear summation to predict the distributed activation pattern elicited by a novel set of 80 test words. The encoding model predicted the activation patterns elicited by the test words significantly better than chance. As expected, prediction was successful for concrete but not for abstract concepts. Comparisons between encoding models based on different combinations of attributes indicate that all five attributes contribute to the representation of concrete concepts. Consistent with embodied theories of semantics, these results show, for the first time, that the distributed activation pattern associated with a concept combines information about different sensory-motor attributes according to their respective relevance. Future research should investigate how additional features of phenomenal experience contribute to the neural representation of conceptual

  3. Advanced Light Source activity report 1996/97

    SciTech Connect

    1997-09-01

    Ten years ago, the Advanced Light Source (ALS) existed as a set of drawings, calculations, and ideas. Four years ago, it stored an electron beam for the first time. Today, the ALS has moved from those ideas and beginnings to a robust, third-generation synchrotron user facility, with eighteen beam lines in use, many more in planning or construction phases, and hundreds of users from around the world. Progress from concepts to realities is continuous as the scientific program, already strong in many diverse areas, moves in new directions to meet the needs of researchers into the next century. ALS staff members who develop and maintain the infrastructure for this research are similarly unwilling to rest on their laurels. As a result, the quality of the photon beams the authors deliver, as well as the support they provide to users, continues to improve. The ALS Activity Report is designed to share the results of these efforts in an accessible form for a broad audience. The Scientific Program section, while not comprehensive, shares the breadth, variety, and interest of recent research at the ALS. (The Compendium of User Abstracts and Technical Reports provides a more comprehensive and more technical view.) The Facility Report highlights progress in operations, ongoing accelerator research and development, and beamline instrumentation efforts. Although these Activity Report sections are separate, in practice the achievements of staff and users at the ALS are inseparable. User-staff collaboration is essential as they strive to meet the needs of the user community and to continue the ALS's success as a premier research facility.

  4. 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

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

    SciTech Connect

    G. R. Odette; G. E. Lucas

    2005-11-15

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

  6. Advanced Technological Education Program: 1995 Awards and Activities.

    ERIC Educational Resources Information Center

    National Science Foundation, Washington, DC. Directorate for Education and Human Resources.

    The Advanced Technological Education (ATE) program promotes exemplary improvement in advanced technological education at the national and regional level through support of curriculum development and program improvement at the undergraduate and secondary school levels, especially for technicians being educated for the high performance workplace of…

  7. Mask R&D activities at the Advanced Mask Technology Center

    NASA Astrophysics Data System (ADS)

    Dilger, Markus; Peters, Jan Hendrik

    2004-08-01

    The Advanced Mask Technology Center (AMTC) in Dresden is an equally-owned joint venture of Advanced Micro Devices Inc. (AMD), DuPont Photomasks, Inc. (DPI), and Infineon Technologies AG (Infineon) founded in 2002 to create a world-leading mask R&D center for both DRAM and logic applications. The AMTC's primary focus is research and development of sub-70 nm technologies. While 193 nm lithography will be used for 65 nm design rules and is probable for 45 nm design rules, solutions for sub-45 nm design rules are still being studied. Possible solutions include 193 nm immersion, 157 nm immersion, EUV, and EPL or its variants. The AMTC is actively involved in multiple collaborative projects to develop masks for advanced lithographies. This paper presents a sampling of AMTC's development activities on both conventional and EUV masks. Intensive studies on adequate materials and their properties for the respective technology have been performed with key partners in the field. Masks have been produced and analyzed. New repair processes have been developed for the small structures of future nodes, the printing capabilities have been predicted by AIMS measurements and analyzed with printing experiments at the respective wavelengths. In this talk we will present the latest results of simulations, experiments, handling and tool qualifications performed at the AMTC or with its partners. We will especially focus on our activities for the EUV technology and will present results on material and process development as well as on simulations for soft and hard pellicle induced distortions. For the EUV technology we will present preliminary results from our etching experiment on binary masks. First results on the performance of our new nano-machining RAVE tool will be shown.

  8. Long-Range Solar Activity Predictions: A Reprieve from Cycle #24's Activity

    NASA Technical Reports Server (NTRS)

    Richon, K.; Schatten, K.

    2003-01-01

    We discuss the field of long-range solar activity predictions and provide an outlook into future solar activity. Orbital predictions for satellites in Low Earth Orbit (LEO) depend strongly on exospheric densities. Solar activity forecasting is important in this regard, as the solar ultra-violet (UV) and extreme ultraviolet (EUV) radiations inflate the upper atmospheric layers of the Earth, forming the exosphere in which satellites orbit. Rather than concentrate on statistical, or numerical methods, we utilize a class of techniques (precursor methods) which is founded in physical theory. The geomagnetic precursor method was originally developed by the Russian geophysicist, Ohl, using geomagnetic observations to predict future solar activity. It was later extended to solar observations, and placed within the context of physical theory, namely the workings of the Sun s Babcock dynamo. We later expanded the prediction methods with a SOlar Dynamo Amplitude (SODA) index. The SODA index is a measure of the buried solar magnetic flux, using toroidal and poloidal field components. It allows one to predict future solar activity during any phase of the solar cycle, whereas previously, one was restricted to making predictions only at solar minimum. We are encouraged that solar cycle #23's behavior fell closely along our predicted curve, peaking near 192, comparable to the Schatten, Myers and Sofia (1996) forecast of 182+/-30. Cycle #23 extends from 1996 through approximately 2006 or 2007, with cycle #24 starting thereafter. We discuss the current forecast of solar cycle #24, (2006-2016), with a predicted smoothed F10.7 radio flux of 142+/-28 (1-sigma errors). This, we believe, represents a reprieve, in terms of reduced fuel costs, etc., for new satellites to be launched or old satellites (requiring reboosting) which have been placed in LEO. By monitoring the Sun s most deeply rooted magnetic fields; long-range solar activity can be predicted. Although a degree of uncertainty

  9. Predictive Analysis of Landslide Activity Using Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Markuzon, N.; Regan, J.; Slesnick, C.

    2012-12-01

    Landslides are historically one of the most damaging geohazard phenomena in terms of death tolls and socio-economic losses. Therefore, understanding the underlying causes of landslides and how environmental phenomena affect their frequency and severity is of critical importance. Of specific importance for mitigating future damage is increasing our understanding of how climate change will affect landslide severity, occurrence rates, and damage. We are developing data driven models aimed at predicting landslide activity. The models learn multi-dimensional weather and geophysical patterns associated with historical landslides and estimate location-dependent probabilities for landslides under current or future weather and geophysical conditions. Our approach uses machine learning algorithms capable of determining non-linear associations between dependent variables and landslide occurrence without requiring detailed knowledge of geomorphology. Our primary goal in year one of the project is to evaluate the predictive capabilities of data mining models in application to landslide activity, and to analyze if the approach will discover previously unknown variables and/or relationships important to landslide occurrence, frequency or severity. The models include remote sensing and ground-based data, including weather, landcover, slope, elevation and drainage information as well as urbanization data. The historical landslide dataset we used to build our preliminary models was compiled from City of Seattle landslide files, United States Geological Survey reports, newspaper articles, and a verified subset of the Seattle Landslide Database that consists of all reported landslides within Seattle, WA, between 1948 and 1999. Most of the landslides analyzed to-date are shallow. Using statistical analysis and unsupervised clustering methods we have thus far identified subsets of weather conditions that lead to a significantly higher landslide probability, and have developed

  10. 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. PMID:22357585

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

    PubMed

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

    2015-01-01

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

  12. The sequential structure of brain activation predicts skill.

    PubMed

    Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa

    2016-01-29

    In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. PMID:26707716

  13. Cortical alpha activity predicts the confidence in an impending action

    PubMed Central

    Kubanek, Jan; Hill, N. Jeremy; Snyder, Lawrence H.; Schalk, Gerwin

    2015-01-01

    When we make a decision, we experience a degree of confidence that our choice may lead to a desirable outcome. Recent studies in animals have probed the subjective aspects of the choice confidence using confidence-reporting tasks. These studies showed that estimates of the choice confidence substantially modulate neural activity in multiple regions of the brain. Building on these findings, we investigated the neural representation of the confidence in a choice in humans who explicitly reported the confidence in their choice. Subjects performed a perceptual decision task in which they decided between choosing a button press or a saccade while we recorded EEG activity. Following each choice, subjects indicated whether they were sure or unsure about the choice. We found that alpha activity strongly encodes a subject's confidence level in a forthcoming button press choice. The neural effect of the subjects' confidence was independent of the reaction time and independent of the sensory input modeled as a decision variable. Furthermore, the effect is not due to a general cognitive state, such as reward expectation, because the effect was specifically observed during button press choices and not during saccade choices. The neural effect of the confidence in the ensuing button press choice was strong enough that we could predict, from independent single trial neural signals, whether a subject was going to be sure or unsure of an ensuing button press choice. In sum, alpha activity in human cortex provides a window into the commitment to make a hand movement. PMID:26283892

  14. Prediction of Antibacterial Activity from Physicochemical Properties of Antimicrobial Peptides

    PubMed Central

    Melo, Manuel N.; Ferre, Rafael; Feliu, Lídia; Bardají, Eduard; Planas, Marta; Castanho, Miguel A. R. B.

    2011-01-01

    Consensus is gathering that antimicrobial peptides that exert their antibacterial action at the membrane level must reach a local concentration threshold to become active. Studies of peptide interaction with model membranes do identify such disruptive thresholds but demonstrations of the possible correlation of these with the in vivo onset of activity have only recently been proposed. In addition, such thresholds observed in model membranes occur at local peptide concentrations close to full membrane coverage. In this work we fully develop an interaction model of antimicrobial peptides with biological membranes; by exploring the consequences of the underlying partition formalism we arrive at a relationship that provides antibacterial activity prediction from two biophysical parameters: the affinity of the peptide to the membrane and the critical bound peptide to lipid ratio. A straightforward and robust method to implement this relationship, with potential application to high-throughput screening approaches, is presented and tested. In addition, disruptive thresholds in model membranes and the onset of antibacterial peptide activity are shown to occur over the same range of locally bound peptide concentrations (10 to 100 mM), which conciliates the two types of observations. PMID:22194847

  15. 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...

  16. 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...

  17. Predicting muscle activation patterns from motion and anatomy: modelling the skull of Sphenodon (Diapsida: Rhynchocephalia)

    PubMed Central

    Curtis, Neil; Jones, Marc E. H.; Evans, Susan E.; Shi, JunFen; O'Higgins, Paul; Fagan, Michael J.

    2010-01-01

    The relationship between skull shape and the forces generated during feeding is currently under widespread scrutiny and increasingly involves the use of computer simulations such as finite element analysis. The computer models used to represent skulls are often based on computed tomography data and thus are structurally accurate; however, correctly representing muscular loading during food reduction remains a major problem. Here, we present a novel approach for predicting the forces and activation patterns of muscles and muscle groups based on their known anatomical orientation (line of action). The work was carried out for the lizard-like reptile Sphenodon (Rhynchocephalia) using a sophisticated computer-based model and multi-body dynamics analysis. The model suggests that specific muscle groups control specific motions, and that during certain times in the bite cycle some muscles are highly active whereas others are inactive. The predictions of muscle activity closely correspond to data previously recorded from live Sphenodon using electromyography. Apparent exceptions can be explained by variations in food resistance, food size, food position and lower jaw motions. This approach shows considerable promise in advancing detailed functional models of food acquisition and reduction, and for use in other musculoskeletal systems where no experimental determination of muscle activity is possible, such as in rare, endangered or extinct species. PMID:19474084

  18. Solubility Prediction of Active Pharmaceutical Compounds with the UNIFAC Model

    NASA Astrophysics Data System (ADS)

    Nouar, Abderrahim; Benmessaoud, Ibtissem; Koutchoukali, Ouahiba; Koutchoukali, Mohamed Salah

    2016-03-01

    The crystallization from solution of an active pharmaceutical ingredient requires the knowledge of the solubility in the entire temperature range investigated during the process. However, during the development of a new active ingredient, these data are missing. Its experimental determination is possible, but tedious. UNIFAC Group contribution method Fredenslund et al. (Vapor-liquid equilibria using UNIFAC: a group contribution method, 1977; AIChE J 21:1086, 1975) can be used to predict this physical property. Several modifications on this model have been proposed since its development in 1977, modified UNIFAC of Dortmund Weidlich et al. (Ind Eng Chem Res 26:1372, 1987), Gmehling et al. (Ind Eng Chem Res 32:178, 1993), Pharma-modified UNIFAC Diedrichs et al. (Evaluation und Erweiterung thermodynamischer Modelle zur Vorhersage von Wirkstofflöslichkeiten, PhD Thesis, 2010), KT-UNIFAC Kang et al. (Ind Eng Chem Res 41:3260, 2002), ldots In this study, we used UNIFAC model by considering the linear temperature dependence of interaction parameters as in Pharma-modified UNIFAC and structural groups as defined by KT-UNIFAC first-order model. More than 100 binary datasets were involved in the estimation of interaction parameters. These new parameters were then used to calculate activity coefficient and solubility of some molecules in various solvents at different temperatures. The model gives better results than those from the original UNIFAC and shows good agreement between the experimental solubility and the calculated one.

  19. Autonomic activity during sleep predicts memory consolidation in humans.

    PubMed

    Whitehurst, Lauren N; Cellini, Nicola; McDevitt, Elizabeth A; Duggan, Katherine A; Mednick, Sara C

    2016-06-28

    Throughout history, psychologists and philosophers have proposed that good sleep benefits memory, yet current studies focusing on the relationship between traditionally reported sleep features (e.g., minutes in sleep stages) and changes in memory performance show contradictory findings. This discrepancy suggests that there are events occurring during sleep that have not yet been considered. The autonomic nervous system (ANS) shows strong variation across sleep stages. Also, increases in ANS activity during waking, as measured by heart rate variability (HRV), have been correlated with memory improvement. However, the role of ANS in sleep-dependent memory consolidation has never been examined. Here, we examined whether changes in cardiac ANS activity (HRV) during a daytime nap were related to performance on two memory conditions (Primed and Repeated) and a nonmemory control condition on the Remote Associates Test. In line with prior studies, we found sleep-dependent improvement in the Primed condition compared with the Quiet Wake control condition. Using regression analyses, we compared the proportion of variance in performance associated with traditionally reported sleep features (model 1) vs. sleep features and HRV during sleep (model 2). For both the Primed and Repeated conditions, model 2 (sleep + HRV) predicted performance significantly better (73% and 58% of variance explained, respectively) compared with model 1 (sleep only, 46% and 26% of variance explained, respectively). These findings present the first evidence, to our knowledge, that ANS activity may be one potential mechanism driving sleep-dependent plasticity. PMID:27298366

  20. Decreased dopamine activity predicts relapse in methamphetamine abusers

    SciTech Connect

    Wang G. J.; Wang, G.-J.; Smith, L.; Volkow, N.D.; Telang, F.; Logan, J.; Tomasi, D.; Wong, C.T.; Hoffman, W.; Jayne, M.; Alia-Klein, N.; Thanos, P.; Fowler, J.S.

    2011-01-20

    Studies in methamphetamine (METH) abusers showed that the decreases in brain dopamine (DA) function might recover with protracted detoxification. However, the extent to which striatal DA function in METH predicts recovery has not been evaluated. Here we assessed whether striatal DA activity in METH abusers is associated with clinical outcomes. Brain DA D2 receptor (D2R) availability was measured with positron emission tomography and [{sup 11}C]raclopride in 16 METH abusers, both after placebo and after challenge with 60 mg oral methylphenidate (MPH) (to measure DA release) to assess whether it predicted clinical outcomes. For this purpose, METH abusers were tested within 6 months of last METH use and then followed up for 9 months of abstinence. In parallel, 15 healthy controls were tested. METH abusers had lower D2R availability in caudate than in controls. Both METH abusers and controls showed decreased striatal D2R availability after MPH and these decreases were smaller in METH than in controls in left putamen. The six METH abusers who relapsed during the follow-up period had lower D2R availability in dorsal striatum than in controls, and had no D2R changes after MPH challenge. The 10 METH abusers who completed detoxification did not differ from controls neither in striatal D2R availability nor in MPH-induced striatal DA changes. These results provide preliminary evidence that low striatal DA function in METH abusers is associated with a greater likelihood of relapse during treatment. Detection of the extent of DA dysfunction may be helpful in predicting therapeutic outcomes.

  1. Multiplexed model predictive control for active vehicle suspensions

    NASA Astrophysics Data System (ADS)

    Hu, Yinlong; Chen, Michael Z. Q.; Hou, Zhongsheng

    2015-02-01

    Multiplexed model predictive control (MMPC) is a recently proposed efficient model predictive control (MPC) algorithm, which can effectively reduce the computational burden of the online optimisation in MPC implementation by updating the control inputs in an asynchronous manner. This paper investigates the application of MMPC in active vehicle suspension design. An MMPC controller integrated with soft constraints and a Kalman filter is proposed based on a full-car model. Ride comfort, roadholding and suspension deflection are considered in this paper, where ride comfort and roadholding are formulated as a quadratic cost function in terms of sprung mass accelerations and tyre deflections, while suspension deflection performance is formulated as a hard constraint. The saturation of the actuator force is also considered and formulated as a hard constraint as well. Numerical simulation is performed with respect to different choices of weighting factors, vehicle speeds and control horizons. The results show that the overall performance of ride comfort and roadholding can be improved significantly by employing MMPC and the average time taken by MMPC to solve the individual quadratic programming problem is considerably smaller than that of the conventional MPC, which effectively demonstrate the effectiveness of the proposed method.

  2. Target of rapamycin activation predicts lifespan in fruit flies

    PubMed Central

    Scialò, Filippo; Sriram, Ashwin; Naudí, Alba; Ayala, Victoria; Jové, Mariona; Pamplona, Reinald; Sanz, Alberto

    2015-01-01

    Aging and age-related diseases are one of the most important health issues that the world will confront during the 21st century. Only by understanding the proximal causes will we be able to find treatments to reduce or delay the onset of degenerative diseases associated with aging. Currently, the prevalent paradigm in the field is the accumulation of damage. However, a new theory that proposes an alternative explanation is gaining momentum. The hyperfunction theory proposes that aging is not a consequence of a wear and tear process, but a result of the continuation of developmental programs during adulthood. Here we use Drosophila melanogaster, where evidence supporting both paradigms has been reported, to identify which parameters that have been previously related with lifespan best predict the rate of aging in wild type flies cultured at different temperatures. We find that mitochondrial function and mitochondrial reactive oxygen species (mtROS) generation correlates with metabolic rate, but not with the rate of aging. Importantly, we find that activation of nutrient sensing pathways (i.e. insulin-PI3K/Target of rapamycin (Tor) pathway) correlates with lifespan, but not with metabolic rate. Our results, dissociate metabolic rate and lifespan in wild type flies and instead link nutrient sensing signaling with longevity as predicted by the hyperfunction theory. PMID:26259964

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  4. Advances in CFD prediction of shock wave turbulent boundary layer interactions

    NASA Astrophysics Data System (ADS)

    Knight, Doyle; Yan, Hong; Panaras, Argyris G.; Zheltovodov, Alexander

    2003-04-01

    The paper presents a summary of recent computational fluid dynamics (CFD) simulations of shock wave turbulent boundary layer interactions. This survey was prepared as part of the activity of NATO RTO Working Group 10 which was established in December 1998, and considers results obtained subsequent to the previous survey paper on the same topic by Knight and Degrez (“Shock Wave Boundary Layer Interactions in High Mach Number Flows-A Critical Survey of Current CFD Prediction Capabilities”, AGARD Advisory Report AR-319, Volume II, December 1998). Five configurations are considered: 2-D compression corner, 2-D shock impingement, 2-D expansion-compression corner, 3-D single fin and 3-D double fin. Recent direct numerical simulations (DNS), large eddy simulations (LES) and Reynolds-averaged Navier-Stokes (RANS) simulations are compared with experiment. The capabilities and limitations are described, and future research needs identified.

  5. Advanced MRI may complement histological diagnosis of lower grade gliomas and help in predicting survival.

    PubMed

    Cuccarini, Valeria; Erbetta, A; Farinotti, M; Cuppini, L; Ghielmetti, F; Pollo, B; Di Meco, F; Grisoli, M; Filippini, G; Finocchiaro, G; Bruzzone, M G; Eoli, M

    2016-01-01

    MRI grading of grade II and III gliomas may have an important impact on treatment decisions. Occasionally,both conventional MRI (cMRI) and histology fail to clearly establish the tumour grade. Three cMRI features(no necrosis; no relevant oedema; absent or faint contrast enhancement) previously validated in 196 patients with supratentorial gliomas directed our selection of 68 suspected low-grade gliomas (LGG) that were also investigated by advanced MRI (aMRI), including perfusion weighted imaging (PWI), diffusion weighted imaging(DWI) and spectroscopy. All the gliomas had histopathological diagnoses. Sensitivity and specificity of cMRI preoperative diagnosis were 78.5 and 38.5 %, respectively, and 85.7 and 53.8 % when a MRI was included, respectively. ROC analysis showed that cut-off values of 1.29 for maximum rCBV, 1.69 for minimum rADC, 2.1 for rCho/Cr ratio could differentiate between LGG and HGG with a sensitivity of 61.5, 53.8, and 53.8 % and a specificity of 54.7, 43 and 64.3 %, respectively. A significantly longer OS was observed in patients with a maximum rCBV<1.46 and minimum rADC>1.69 (80 vs 55 months, p = 0.01; 80 vs 51 months, p = 0.002, respectively). This result was also confirmed when cases were stratified according to pathology (LGG vs HGG). The ability of a MRI to differentiate between LGG and HGG and to predict survival improved as the number of a MRI techniques considered increased. In a selected population of suspected LGG,classification by cMRI underestimated the actual fraction of HGG. aMRI slightly increased the diagnostic accuracy compared to histopathology. However, DWI and PWI were prognostic markers independent of histological grade. PMID:26468137

  6. Prediction of Energy Expenditure and Physical Activity in Preschoolers

    PubMed Central

    Butte, Nancy F.; Wong, William W.; Lee, Jong Soo; Adolph, Anne L.; Puyau, Maurice R.; Zakeri, Issa F.

    2013-01-01

    Purpose Accurate, nonintrusive and feasible methods are needed to predict energy expenditure (EE) and physical activity (PA) levels in preschoolers. Herein, we validated cross-sectional time series (CSTS) and multivariate adaptive regression splines (MARS) models based on accelerometry and heart rate (HR) for prediction of EE using room calorimetry and doubly labeled water (DLW), and established accelerometry cut-points for PA levels. Methods Fifty preschoolers, mean±SD age 4.5±0.8 y, participated in room calorimetry for minute-by-minute measurements of EE, accelerometer counts (AC) (Actiheart and ActiGraph GT3X+) and HR (Actiheart). Free-living, 105 children, aged 4.6±0.9 years, completed the 7-d DLW procedure while wearing the devices. AC cut-points for PA levels were established using smoothing splines and receiver operating characteristic curves. Results Based on calorimetry, mean percent errors for EE were -2.9±10.8% and -1.1±7.4% for CSTS models, and -1.9±9.6 and 1.3±8.1% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. Based on DLW, mean percent errors were -0.5±9.7% and 4.1±8.5% for CSTS models and 3.2±10.1% and 7.5±10.0% for MARS models using the Actiheart and ActiGraph+HR devices, respectively. Applying activity EE thresholds, final accelerometer cut-points were determined: 41, 449, and 1,297 cpm for Actiheart x-axis; 820, 3,908, and 6,112 cpm for ActiGraph vector magnitude; and 240, 2,120, and 4,450 cpm for ActiGraph x-axis for sedentary/light, light/moderate, and moderate/vigorous PA (MVPA). Based on confusion matrices, correctly classified rates were 81–83% for sedentary PA, 58–64% for light PA and 62–73% for MVPA. Conclusion The lack of bias and acceptable limits of agreement affirm the validity of the CSTS and MARS models for the prediction of EE in preschool-aged children. Accelerometer cut-points are satisfactory for classification of sedentary, light and moderate-vigorous levels of PA in preschoolers

  7. Brain monoamine oxidase A activity predicts trait aggression.

    PubMed

    Alia-Klein, Nelly; Goldstein, Rita Z; Kriplani, Aarti; Logan, Jean; Tomasi, Dardo; Williams, Benjamin; Telang, Frank; Shumay, Elena; Biegon, Anat; Craig, Ian W; Henn, Fritz; Wang, Gene-Jack; Volkow, Nora D; Fowler, Joanna S

    2008-05-01

    The genetic deletion of monoamine oxidase A (MAO A), an enzyme that breaks down the monoamine neurotransmitters norepinephrine, serotonin, and dopamine, produces aggressive phenotypes across species. Therefore, a common polymorphism in the MAO A gene (MAOA, Mendelian Inheritance in Men database number 309850, referred to as high or low based on transcription in non-neuronal cells) has been investigated in a number of externalizing behavioral and clinical phenotypes. These studies provide evidence linking the low MAOA genotype and violent behavior but only through interaction with severe environmental stressors during childhood. Here, we hypothesized that in healthy adult males the gene product of MAO A in the brain, rather than the gene per se, would be associated with regulating the concentration of brain amines involved in trait aggression. Brain MAO A activity was measured in vivo in healthy nonsmoking men with positron emission tomography using a radioligand specific for MAO A (clorgyline labeled with carbon 11). Trait aggression was measured with the multidimensional personality questionnaire (MPQ). Here we report for the first time that brain MAO A correlates inversely with the MPQ trait measure of aggression (but not with other personality traits) such that the lower the MAO A activity in cortical and subcortical brain regions, the higher the self-reported aggression (in both MAOA genotype groups) contributing to more than one-third of the variability. Because trait aggression is a measure used to predict antisocial behavior, these results underscore the relevance of MAO A as a neurochemical substrate of aberrant aggression. PMID:18463263

  8. Brain Monoamine Oxidase-A Activity Predicts Trait Aggression

    PubMed Central

    Alia-Klein, Nelly; Goldstein, Rita Z.; Kriplani, Aarti; Logan, Jean; Tomasi, Dardo; Williams, Benjamin; Telang, Frank; Shumay, Elena; Biegon, Anat; Craig, Ian W.; Henn, Fritz; Wang, Gene-Jack; Volkow, Nora D.; Fowler, Joanna S.

    2008-01-01

    The genetic deletion of monoamine oxidase A (MAO A, an enzyme which breaks down the monoamine neurotransmitters norepinephrine, serotonin and dopamine) produces aggressive phenotypes across species. Therefore, a common polymorphism in the MAO A gene (MAOA, MIM 309850, referred to as high or low based on transcription in non-neuronal cells) has been investigated in a number of externalizing behavioral and clinical phenotypes. These studies provide evidence linking the low MAOA genotype and violent behavior but only through interaction with severe environmental stressors during childhood. Here, we hypothesized that in healthy adult males the gene product of MAO A in the brain, rather than the gene per se, would be associated with regulating the concentration of brain amines involved in trait aggression. Brain MAO A activity was measured in-vivo in healthy non-smoking men with positron emission tomography using a radioligand specific for MAO A (clorgyline labeled with carbon 11). Trait aggression was measured with the Multidimensional Personality Questionnaire (MPQ). Here we report for the first time that brain MAO A correlates inversely with the MPQ trait measure of aggression (but not with other personality traits) such that the lower the MAO A activity in cortical and subcortical brain regions the higher the self-reported aggression (in both MAOA genotype groups) contributing to more than a third of the variability. Since trait aggression is a measure used to predict antisocial behavior, these results underscore the relevance of MAO A as a neurochemical substrate of aberrant aggression. PMID:18463263

  9. Cortical activity patterns predict robust speech discrimination ability in noise

    PubMed Central

    Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.

    2012-01-01

    The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331

  10. Global cortical activity predicts shape of hand during grasping.

    PubMed

    Agashe, Harshavardhan A; Paek, Andrew Y; Zhang, Yuhang; Contreras-Vidal, José L

    2015-01-01

    Recent studies show that the amplitude of cortical field potentials is modulated in the time domain by grasping kinematics. However, it is unknown if these low frequency modulations persist and contain enough information to decode grasp kinematics in macro-scale activity measured at the scalp via electroencephalography (EEG). Further, it is unclear as to whether joint angle velocities or movement synergies are the optimal kinematics spaces to decode. In this offline decoding study, we infer from human EEG, hand joint angular velocities as well as synergistic trajectories as subjects perform natural reach-to-grasp movements. Decoding accuracy, measured as the correlation coefficient (r) between the predicted and actual movement kinematics, was r = 0.49 ± 0.02 across 15 hand joints. Across the first three kinematic synergies, decoding accuracies were r = 0.59 ± 0.04, 0.47 ± 0.06, and 0.32 ± 0.05. The spatial-temporal pattern of EEG channel recruitment showed early involvement of contralateral frontal-central scalp areas followed by later activation of central electrodes over primary sensorimotor cortical areas. Information content in EEG about the grasp type peaked at 250 ms after movement onset. The high decoding accuracies in this study are significant not only as evidence for time-domain modulation in macro-scale brain activity, but for the field of brain-machine interfaces as well. Our decoding strategy, which harnesses the neural "symphony" as opposed to local members of the neural ensemble (as in intracranial approaches), may provide a means of extracting information about motor intent for grasping without the need for penetrating electrodes and suggests that it may be soon possible to develop non-invasive neural interfaces for the control of prosthetic limbs. PMID:25914616

  11. Predicting Monoamine Oxidase Inhibitory Activity through Ligand-Based Models

    PubMed Central

    Vilar, Santiago; Ferino, Giulio; Quezada, Elias; Santana, Lourdes; Friedman, Carol

    2013-01-01

    The evolution of bio- and cheminformatics associated with the development of specialized software and increasing computer power has produced a great interest in theoretical in silico methods applied in drug rational design. These techniques apply the concept that “similar molecules have similar biological properties” that has been exploited in Medicinal Chemistry for years to design new molecules with desirable pharmacological profiles. Ligand-based methods are not dependent on receptor structural data and take into account two and three-dimensional molecular properties to assess similarity of new compounds in regards to the set of molecules with the biological property under study. Depending on the complexity of the calculation, there are different types of ligand-based methods, such as QSAR (Quantitative Structure-Activity Relationship) with 2D and 3D descriptors, CoMFA (Comparative Molecular Field Analysis) or pharmacophoric approaches. This work provides a description of a series of ligand-based models applied in the prediction of the inhibitory activity of monoamine oxidase (MAO) enzymes. The controlled regulation of the enzymes’ function through the use of MAO inhibitors is used as a treatment in many psychiatric and neurological disorders, such as depression, anxiety, Alzheimer’s and Parkinson’s disease. For this reason, multiple scaffolds, such as substituted coumarins, indolylmethylamine or pyridazine derivatives were synthesized and assayed toward MAO-A and MAO-B inhibition. Our intention is to focus on the description of ligand-based models to provide new insights in the relationship between the MAO inhibitory activity and the molecular structure of the different inhibitors, and further study enzyme selectivity and possible mechanisms of action. PMID:23231398

  12. Global cortical activity predicts shape of hand during grasping

    PubMed Central

    Agashe, Harshavardhan A.; Paek, Andrew Y.; Zhang, Yuhang; Contreras-Vidal, José L.

    2015-01-01

    Recent studies show that the amplitude of cortical field potentials is modulated in the time domain by grasping kinematics. However, it is unknown if these low frequency modulations persist and contain enough information to decode grasp kinematics in macro-scale activity measured at the scalp via electroencephalography (EEG). Further, it is unclear as to whether joint angle velocities or movement synergies are the optimal kinematics spaces to decode. In this offline decoding study, we infer from human EEG, hand joint angular velocities as well as synergistic trajectories as subjects perform natural reach-to-grasp movements. Decoding accuracy, measured as the correlation coefficient (r) between the predicted and actual movement kinematics, was r = 0.49 ± 0.02 across 15 hand joints. Across the first three kinematic synergies, decoding accuracies were r = 0.59 ± 0.04, 0.47 ± 0.06, and 0.32 ± 0.05. The spatial-temporal pattern of EEG channel recruitment showed early involvement of contralateral frontal-central scalp areas followed by later activation of central electrodes over primary sensorimotor cortical areas. Information content in EEG about the grasp type peaked at 250 ms after movement onset. The high decoding accuracies in this study are significant not only as evidence for time-domain modulation in macro-scale brain activity, but for the field of brain-machine interfaces as well. Our decoding strategy, which harnesses the neural “symphony” as opposed to local members of the neural ensemble (as in intracranial approaches), may provide a means of extracting information about motor intent for grasping without the need for penetrating electrodes and suggests that it may be soon possible to develop non-invasive neural interfaces for the control of prosthetic limbs. PMID:25914616

  13. Adding Structure to the Transition Process to Advanced Mathematical Activity

    ERIC Educational Resources Information Center

    Engelbrecht, Johann

    2010-01-01

    The transition process to advanced mathematical thinking is experienced as traumatic by many students. Experiences that students had of school mathematics differ greatly to what is expected from them at university. Success in school mathematics meant application of different methods to get an answer. Students are not familiar with logical…

  14. Strategy to Promote Active Learning of an Advanced Research Method

    ERIC Educational Resources Information Center

    McDermott, Hilary J.; Dovey, Terence M.

    2013-01-01

    Research methods courses aim to equip students with the knowledge and skills required for research yet seldom include practical aspects of assessment. This reflective practitioner report describes and evaluates an innovative approach to teaching and assessing advanced qualitative research methods to final-year psychology undergraduate students. An…

  15. HOTAIR is a predictive and prognostic biomarker for patients with advanced gastric adenocarcinoma receiving fluorouracil and platinum combination chemotherapy

    PubMed Central

    Zhao, Wei; Dong, Shuang; Duan, Bensong; Chen, Ping; Shi, Lei; Gao, Hengjun; Qi, Haizhi

    2015-01-01

    Accumulating evidence suggests that long non-coding RNA (lncRNA) HOTAIR participates in many types of cancer such as gastric cancer and may confer malignant phenotype to tumor cells. Fluorouracil and platinum combination chemotherapy is the first line therapy for gastric cancer. However, it is still unknown whether HOTAIR influences the outcome of cancer patients treated with chemotherapy. This study aimed to evaluate the association of HOTAIR expression with the prognosis of patients with advanced gastric adenocarcinoma (GA) receiving fluorouracil and platinum based chemotherapy. We examined the levels of HOTAIR in 168 GA samples using quantitative real-time PCR and analyzed its relationship with clinical features and prognosis of patients with advanced GA treated with fluorouracil and platinum based chemotherapy. Compared with paracancerous tissues, HOTAIR was significantly upregulated in GA tissues, especially in more advanced cases. High HOTAIR expression was an independent poor prognostic factor for patients with advanced GA. Further stratification analyses revealed that the association between HOTAIR expression and survival in patients with advanced GA remained significant in the subgroup of patients with TNM stages IIIA and IIIB, poorly differentiated, and smaller tumors. In conclusion, our results provide first evidence that HOTAIR may be served as a biomarker that predicts which patient with advanced GA will benefit from fluorouracil and platinum combination chemotherapy. PMID:26328013

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

    ERIC Educational Resources Information Center

    Froman, Terry; Brown, Shelly; Tirado, Arleti

    2008-01-01

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

  17. Gut Epithelial Barrier Dysfunction and Innate Immune Activation Predict Mortality in Treated HIV Infection

    PubMed Central

    Hunt, Peter W.; Sinclair, Elizabeth; Rodriguez, Benigno; Shive, Carey; Clagett, Brian; Funderburg, Nicholas; Robinson, Janet; Huang, Yong; Epling, Lorrie; Martin, Jeffrey N.; Deeks, Steven G.; Meinert, Curtis L.; Van Natta, Mark L.; Jabs, Douglas A.; Lederman, Michael M.

    2014-01-01

    Background. While inflammation predicts mortality in treated human immunodeficiency virus (HIV) infection, the prognostic significance of gut barrier dysfunction and phenotypic T-cell markers remains unclear. Methods. We assessed immunologic predictors of mortality in a case-control study within the Longitudinal Study of the Ocular Complications of AIDS (LSOCA), using conditional logistic regression. Sixty-four case patients who died within 12 months of treatment-mediated viral suppression were each matched to 2 control individuals (total number of controls, 128) by duration of antiretroviral therapy–mediated viral suppression, nadir CD4+ T-cell count, age, sex, and prior cytomegalovirus (CMV) retinitis. A similar secondary analysis was conducted in the SCOPE cohort, which had participants with less advanced immunodeficiency. Results. Plasma gut epithelial barrier integrity markers (intestinal fatty acid binding protein and zonulin-1 levels), soluble CD14 level, kynurenine/tryptophan ratio, soluble tumor necrosis factor receptor 1 level, high-sensitivity C-reactive protein level, and D-dimer level all strongly predicted mortality, even after adjustment for proximal CD4+ T-cell count (all P ≤ .001). A higher percentage of CD38+HLA-DR+ cells in the CD8+ T-cell population was a predictor of mortality before (P = .031) but not after (P = .10) adjustment for proximal CD4+ T-cell count. Frequencies of senescent (defined as CD28−CD57+ cells), exhausted (defined as PD1+ cells), naive, and CMV-specific T cells did not predict mortality. Conclusions. Gut epithelial barrier dysfunction, innate immune activation, inflammation, and coagulation—but not T-cell activation, senescence, and exhaustion—independently predict mortality in individuals with treated HIV infection with a history of AIDS and are viable targets for interventions. PMID:24755434

  18. 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,…

  19. 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

  20. 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.

  1. Gene Expression Profile for Predicting Survival in Advanced-Stage Serous Ovarian Cancer Across Two Independent Datasets

    PubMed Central

    Yoshihara, Kosuke; Tajima, Atsushi; Yahata, Tetsuro; Kodama, Shoji; Fujiwara, Hiroyuki; Suzuki, Mitsuaki; Onishi, Yoshitaka; Hatae, Masayuki; Sueyoshi, Kazunobu; Fujiwara, Hisaya; Kudo, Yoshiki; Kotera, Kohei; Masuzaki, Hideaki; Tashiro, Hironori; Katabuchi, Hidetaka; Inoue, Ituro; Tanaka, Kenichi

    2010-01-01

    Background Advanced-stage ovarian cancer patients are generally treated with platinum/taxane-based chemotherapy after primary debulking surgery. However, there is a wide range of outcomes for individual patients. Therefore, the clinicopathological factors alone are insufficient for predicting prognosis. Our aim is to identify a progression-free survival (PFS)-related molecular profile for predicting survival of patients with advanced-stage serous ovarian cancer. Methodology/Principal Findings Advanced-stage serous ovarian cancer tissues from 110 Japanese patients who underwent primary surgery and platinum/taxane-based chemotherapy were profiled using oligonucleotide microarrays. We selected 88 PFS-related genes by a univariate Cox model (p<0.01) and generated the prognostic index based on 88 PFS-related genes after adjustment of regression coefficients of the respective genes by ridge regression Cox model using 10-fold cross-validation. The prognostic index was independently associated with PFS time compared to other clinical factors in multivariate analysis [hazard ratio (HR), 3.72; 95% confidence interval (CI), 2.66–5.43; p<0.0001]. In an external dataset, multivariate analysis revealed that this prognostic index was significantly correlated with PFS time (HR, 1.54; 95% CI, 1.20–1.98; p = 0.0008). Furthermore, the correlation between the prognostic index and overall survival time was confirmed in the two independent external datasets (log rank test, p = 0.0010 and 0.0008). Conclusions/Significance The prognostic ability of our index based on the 88-gene expression profile in ridge regression Cox hazard model was shown to be independent of other clinical factors in predicting cancer prognosis across two distinct datasets. Further study will be necessary to improve predictive accuracy of the prognostic index toward clinical application for evaluation of the risk of recurrence in patients with advanced-stage serous ovarian cancer. PMID:20300634

  2. The Clinical Significance of MiR-148a as a Predictive Biomarker in Patients with Advanced Colorectal Cancer

    PubMed Central

    Takahashi, Masanobu; Cuatrecasas, Miriam; Balaguer, Francesc; Hur, Keun; Toiyama, Yuji; Castells, Antoni; Boland, C. Richard; Goel, Ajay

    2012-01-01

    Aim Development of robust prognostic and/or predictive biomarkers in patients with colorectal cancer (CRC) is imperative for advancing treatment strategies for this disease. We aimed to determine whether expression status of certain miRNAs might have prognostic/predictive value in CRC patients treated with conventional cytotoxic chemotherapies. Methods We studied a cohort of 273 CRC specimens from stage II/III patients treated with 5-fluorouracil-based adjuvant chemotherapy and stage IV patients subjected to 5-fluorouracil and oxaliplatin-based chemotherapy. In a screening set (n = 44), 13 of 21 candidate miRNAs were successfully quantified by multiplex quantitative RT-PCR. In the validation set comprising of the entire patient cohort, miR-148a expression status was assessed by quantitative RT-PCR, and its promoter methylation was quantified by bisulfite pyrosequencing. Lastly, we analyzed the associations between miR-148a expression and patient survival. Results Among the candidate miRNAs studied, miR-148a expression was most significantly down-regulated in advanced CRC tissues. In stage III and IV CRC, low miR-148a expression was associated with significantly shorter disease free-survival (DFS), a worse therapeutic response, and poor overall survival (OS). Furthermore, miR-148a methylation status correlated inversely with its expression, and was associated with worse survival in stage IV CRC. In multivariate analysis, miR-148a expression was an independent prognostic/predictive biomarker for advanced CRC patients (DFS in stage III, low vs. high expression, HR 2.11; OS in stage IV, HR 1.93). Discussion MiR-148a status has a prognostic/predictive value in advanced CRC patients treated with conventional chemotherapy, which has important clinical implications in improving therapeutic strategies and personalized management of this malignancy. PMID:23056401

  3. Subgenual cingulate cortical activity predicts the efficacy of electroconvulsive therapy.

    PubMed

    Argyelan, M; Lencz, T; Kaliora, S; Sarpal, D K; Weissman, N; Kingsley, P B; Malhotra, A K; Petrides, G

    2016-01-01

    Electroconvulsive therapy (ECT) is the most effective treatment for depression, yet its mechanism of action is unknown. Our goal was to investigate the neurobiological underpinnings of ECT response using longitudinally collected resting-state functional magnetic resonance imaging (rs-fMRI) in 16 patients with treatment-resistant depression and 10 healthy controls. Patients received bifrontal ECT 3 times a week under general anesthesia. We acquired rs-fMRI at three time points: at baseline, after the 1st ECT administration and after the course of the ECT treatment; depression was assessed with the Hamilton Depression Rating Scale (HAM-D). The primary measure derived from rs-fMRI was fractional amplitude of low frequency fluctuation (fALFF), which provides an unbiased voxel-wise estimation of brain activity. We also conducted seed-based functional connectivity analysis based on our primary findings. We compared treatment-related changes in HAM-D scores with pre- and post-treatment fALFF and connectivity measures. Subcallosal cingulate cortex (SCC) demonstrated higher BOLD signal fluctuations (fALFF) at baseline in depressed patients, and SCC fALFF decreased over the course of treatment. The baseline level of fALFF of SCC predicted response to ECT. In addition, connectivity of SCC with bilateral hippocampus, bilateral temporal pole, and ventromedial prefrontal cortex was significantly reduced over the course of treatment. These results suggest that the antidepressant effect of ECT may be mediated by downregulation of SCC activity and connectivity. SCC function may serve as an important biomarker of target engagement in the development of novel therapies for depression that is resistant to treatment with standard medications. PMID:27115120

  4. Subgenual cingulate cortical activity predicts the efficacy of electroconvulsive therapy

    PubMed Central

    Argyelan, M; Lencz, T; Kaliora, S; Sarpal, D K; Weissman, N; Kingsley, P B; Malhotra, A K; Petrides, G

    2016-01-01

    Electroconvulsive therapy (ECT) is the most effective treatment for depression, yet its mechanism of action is unknown. Our goal was to investigate the neurobiological underpinnings of ECT response using longitudinally collected resting-state functional magnetic resonance imaging (rs-fMRI) in 16 patients with treatment-resistant depression and 10 healthy controls. Patients received bifrontal ECT 3 times a week under general anesthesia. We acquired rs-fMRI at three time points: at baseline, after the 1st ECT administration and after the course of the ECT treatment; depression was assessed with the Hamilton Depression Rating Scale (HAM-D). The primary measure derived from rs-fMRI was fractional amplitude of low frequency fluctuation (fALFF), which provides an unbiased voxel-wise estimation of brain activity. We also conducted seed-based functional connectivity analysis based on our primary findings. We compared treatment-related changes in HAM-D scores with pre- and post-treatment fALFF and connectivity measures. Subcallosal cingulate cortex (SCC) demonstrated higher BOLD signal fluctuations (fALFF) at baseline in depressed patients, and SCC fALFF decreased over the course of treatment. The baseline level of fALFF of SCC predicted response to ECT. In addition, connectivity of SCC with bilateral hippocampus, bilateral temporal pole, and ventromedial prefrontal cortex was significantly reduced over the course of treatment. These results suggest that the antidepressant effect of ECT may be mediated by downregulation of SCC activity and connectivity. SCC function may serve as an important biomarker of target engagement in the development of novel therapies for depression that is resistant to treatment with standard medications. PMID:27115120

  5. Predicting Water Activity for Complex Wastes with Solvation Cluster Equilibria (SCE) - 12042

    SciTech Connect

    Agnew, S.F.; Reynolds, J.G.; Johnston, C.T.

    2012-07-01

    Predicting an electrolyte mixture's water activity, i.e. the ratio of water vapor pressure over a solution with that of pure water, in principle reveals both boiling point and solubilities for that mixture. Better predictions of these properties helps support the ongoing missions to concentrate complex nuclear waste mixtures in order to conserve tank space and improved predictions of water activity will help. A new approach for predicting water activity, the solvation cluster equilibria (SCE) model, uses pure electrolyte water activities to predict water activity for a complex mixture of those electrolytes. An SCE function based on electrolyte hydration free energy and a standard Debye- Hueckel (DH) charge compression fits each pure electrolyte's water activity with three parameters. Given these pure electrolyte water activities, the SCE predicts any mixture water activity over a large range of concentration with an additional parameter for each mixture vector, the multinarity. In contrast to ionic strength, which scales with concentration, multinarity is related to the relative proportion of electrolytes in a mixture and can either increase or decrease the water activity prediction over a broad range of concentration for that mixture. The SCE model predicts water activity for complex electrolyte mixtures based on the water activities of pure electrolytes. Three parameter SCE functions fit the water activities of pure electrolytes and along with a single multinarity parameter for each mixture vector then predict the mixture water activity. Predictions of water activity can in principle predict solution electrolyte activity and this relationship will be explored in the future. Predicting electrolyte activities for complex mixtures provides a means of determining solubilities for each electrolyte. Although there are a number of reports [9, 10, 11] of water activity models for pure and binary mixtures of electrolytes, none of them compare measured versus calculated

  6. Predictive active disturbance rejection control for processes with time delay.

    PubMed

    Zheng, Qinling; Gao, Zhiqiang

    2014-07-01

    Active disturbance rejection control (ADRC) has been shown to be an effective tool in dealing with real world problems of dynamic uncertainties, disturbances, nonlinearities, etc. This paper addresses its existing limitations with plants that have a large transport delay. In particular, to overcome the delay, the extended state observer (ESO) in ADRC is modified to form a predictive ADRC, leading to significant improvements in the transient response and stability characteristics, as shown in extensive simulation studies and hardware-in-the-loop tests, as well as in the frequency response analysis. In this research, it is assumed that the amount of delay is approximately known, as is the approximated model of the plant. Even with such uncharacteristic assumptions for ADRC, the proposed method still exhibits significant improvements in both performance and robustness over the existing methods such as the dead-time compensator based on disturbance observer and the Filtered Smith Predictor, in the context of some well-known problems of chemical reactor and boiler control problems. PMID:24182516

  7. Traction force dynamics predict gap formation in activated endothelium.

    PubMed

    Valent, Erik T; van Nieuw Amerongen, Geerten P; van Hinsbergh, Victor W M; Hordijk, Peter L

    2016-09-10

    In many pathological conditions the endothelium becomes activated and dysfunctional, resulting in hyperpermeability and plasma leakage. No specific therapies are available yet to control endothelial barrier function, which is regulated by inter-endothelial junctions and the generation of acto-myosin-based contractile forces in the context of cell-cell and cell-matrix interactions. However, the spatiotemporal distribution and stimulus-induced reorganization of these integral forces remain largely unknown. Traction force microscopy of human endothelial monolayers was used to visualize contractile forces in resting cells and during thrombin-induced hyperpermeability. Simultaneously, information about endothelial monolayer integrity, adherens junctions and cytoskeletal proteins (F-actin) were captured. This revealed a heterogeneous distribution of traction forces, with nuclear areas showing lower and cell-cell junctions higher traction forces than the whole-monolayer average. Moreover, junctional forces were asymmetrically distributed among neighboring cells. Force vector orientation analysis showed a good correlation with the alignment of F-actin and revealed contractile forces in newly formed filopodia and lamellipodia-like protrusions within the monolayer. Finally, unstable areas, showing high force fluctuations within the monolayer were prone to form inter-endothelial gaps upon stimulation with thrombin. To conclude, contractile traction forces are heterogeneously distributed within endothelial monolayers and force instability, rather than force magnitude, predicts the stimulus-induced formation of intercellular gaps. PMID:27498166

  8. Predicting Activation of Experiments Inside the Annular Core Research Reactor

    SciTech Connect

    Greenberg, Joseph Isaac

    2015-11-01

    The objective of this thesis is to create a program to quickly estimate the radioactivity and decay of experiments conducted inside of the Annular Core Research Reactor at Sandia National Laboratories and eliminate the need for users to write code. This is achieved by model the neutron fluxes in the reactor’s central cavity where experiments are conducted for 4 different neutron spectra using MCNP. The desired neutron spectrum, experiment material composition, and reactor power level are then input into CINDER2008 burnup code to obtain activation and decay information for every isotope generated. DREAD creates all of the files required for CINDER2008 through user selected inputs in a graphical user interface and executes the program for the user and displays the resulting estimation for dose rate at various distances. The DREAD program was validated by weighing and measuring various experiments in the different spectra and then collecting dose rate information after they were irradiated and comparing it to the dose rates that DREAD predicted. The program provides results with an average of 17% higher estimates than the actual values and takes seconds to execute.

  9. Accurate Prediction of Advanced Liver Fibrosis Using the Decision Tree Learning Algorithm in Chronic Hepatitis C Egyptian Patients

    PubMed Central

    Hashem, Somaya; Esmat, Gamal; Elakel, Wafaa; Habashy, Shahira; Abdel Raouf, Safaa; Darweesh, Samar; Soliman, Mohamad; Elhefnawi, Mohamed; El-Adawy, Mohamed; ElHefnawi, Mahmoud

    2016-01-01

    Background/Aim. Respectively with the prevalence of chronic hepatitis C in the world, using noninvasive methods as an alternative method in staging chronic liver diseases for avoiding the drawbacks of biopsy is significantly increasing. The aim of this study is to combine the serum biomarkers and clinical information to develop a classification model that can predict advanced liver fibrosis. Methods. 39,567 patients with chronic hepatitis C were included and randomly divided into two separate sets. Liver fibrosis was assessed via METAVIR score; patients were categorized as mild to moderate (F0–F2) or advanced (F3-F4) fibrosis stages. Two models were developed using alternating decision tree algorithm. Model 1 uses six parameters, while model 2 uses four, which are similar to FIB-4 features except alpha-fetoprotein instead of alanine aminotransferase. Sensitivity and receiver operating characteristic curve were performed to evaluate the performance of the proposed models. Results. The best model achieved 86.2% negative predictive value and 0.78 ROC with 84.8% accuracy which is better than FIB-4. Conclusions. The risk of advanced liver fibrosis, due to chronic hepatitis C, could be predicted with high accuracy using decision tree learning algorithm that could be used to reduce the need to assess the liver biopsy. PMID:26880886

  10. Accurate Prediction of Advanced Liver Fibrosis Using the Decision Tree Learning Algorithm in Chronic Hepatitis C Egyptian Patients.

    PubMed

    Hashem, Somaya; Esmat, Gamal; Elakel, Wafaa; Habashy, Shahira; Abdel Raouf, Safaa; Darweesh, Samar; Soliman, Mohamad; Elhefnawi, Mohamed; El-Adawy, Mohamed; ElHefnawi, Mahmoud

    2016-01-01

    Background/Aim. Respectively with the prevalence of chronic hepatitis C in the world, using noninvasive methods as an alternative method in staging chronic liver diseases for avoiding the drawbacks of biopsy is significantly increasing. The aim of this study is to combine the serum biomarkers and clinical information to develop a classification model that can predict advanced liver fibrosis. Methods. 39,567 patients with chronic hepatitis C were included and randomly divided into two separate sets. Liver fibrosis was assessed via METAVIR score; patients were categorized as mild to moderate (F0-F2) or advanced (F3-F4) fibrosis stages. Two models were developed using alternating decision tree algorithm. Model 1 uses six parameters, while model 2 uses four, which are similar to FIB-4 features except alpha-fetoprotein instead of alanine aminotransferase. Sensitivity and receiver operating characteristic curve were performed to evaluate the performance of the proposed models. Results. The best model achieved 86.2% negative predictive value and 0.78 ROC with 84.8% accuracy which is better than FIB-4. Conclusions. The risk of advanced liver fibrosis, due to chronic hepatitis C, could be predicted with high accuracy using decision tree learning algorithm that could be used to reduce the need to assess the liver biopsy. PMID:26880886

  11. Evaluation of Instrumental Activities of Daily Living in Greek Patients with Advanced Cancer

    ERIC Educational Resources Information Center

    Mystakidou, Kyriaki; Parpa, Efi; Tsilika, Eleni; Panagiotoua, Irene; Roumeliotou, Anna; Symeonidi, Matina; Galanos, Antonis; Kouvaris, Ioannis

    2013-01-01

    Translation of the instrumental activities of daily living (IADL) was carried out and its psychometric properties were assessed in a Greek sample of patients with advanced cancer. The scale was translated with the forward-backward procedure into the Greek language. It was initially administered to 136 advanced cancer patients. To assess…

  12. 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.

  13. Prediction Model for Prevalence and Incidence of Advanced Age-Related Macular Degeneration Based on Genetic, Demographic, and Environmental Variables

    PubMed Central

    Seddon, Johanna M.; Reynolds, Robyn; Maller, Julian; Fagerness, Jesen A.; Daly, Mark J.; Rosner, Bernard

    2013-01-01

    Purpose The joint effects of genetic, ocular, and environmental variables were evaluated and predictive models for prevalence and incidence of AMD were assessed. Methods Participants in the multicenter Age-Related Eye Disease Study (AREDS) were included in a prospective evaluation of 1446 individuals, of which 279 progressed to advanced AMD (geographic atrophy or neovascular disease) and 1167 did not progress during 6.3 years of follow-up. For prevalent AMD, 509 advanced cases were compared with 222 controls. Covariates for the incidence analysis included age, sex, education, smoking, body mass index (BMI), baseline AMD grade, and the AREDS vitamin–mineral treatment assignment. DNA specimens were evaluated for six variants in five genes related to AMD. Unconditional logistic regression analyses were performed for prevalent and incident advanced AMD. An algorithm was developed and receiver operating characteristic curves and C statistics were calculated to assess the predictive ability of risk scores to discriminate progressors from nonprogressors. Results All genetic polymorphisms were independently related to prevalence of advanced AMD, controlling for genetic factors, smoking, BMI, and AREDS treatment. Multivariate odds ratios (ORs) were 3.5 (95% confidence interval [CI], 1.7–7.1) for CFH Y402H; 3.7 (95% CI, 1.6 – 8.4) for CFH rs1410996; 25.4 (95% CI, 8.6 –75.1) for LOC387715 A69S (ARMS2); 0.3 (95% CI, 0.1– 0.7) for C2 E318D; 0.3 (95% CI, 0.1– 0.5) for CFB; and 3.6 (95% CI, 1.4 –9.4) for C3 R102G, comparing the homozygous risk/protective genotypes to the referent genotypes. For incident AMD, all these variants except CFB were significantly related to progression to advanced AMD, after controlling for baseline AMD grade and other factors, with ORs from 1.8 to 4.0 for presence of two risk alleles and 0.4 for the protective allele. An interaction was seen between CFH402H and treatment, after controlling for all genotypes. Smoking was independently

  14. STRUCTURE-ACTIVITY RELATIONSHIP STUIDES AND THEIR ROLE IN PREDICTING AND INVESTIGATING CHEMICAL TOXICITY

    EPA Science Inventory

    Structure-Activity Relationship Studies and their Role in Predicting and Investigating Chemical Toxicity

    Structure-activity relationships (SAR) represent attempts to generalize chemical information relative to biological activity for the twin purposes of generating insigh...

  15. CONSIDERATION OF REACTION INTERMEDIATES IN STRUCTURE-ACTIVITY RELATIONSHIPS: A KEY TO UNDERSTANDING AND PREDICTION

    EPA Science Inventory

    Consideration of Reaction Intermediates in Structure- Activity Relationships: A Key to Understanding and Prediction

    A structure-activity relationship (SAR) represents an empirical means for generalizing chemical information relative to biological activity, and is frequent...

  16. Predicting the unpredictable: critical analysis and practical implications of predictive anticipatory activity

    PubMed Central

    Mossbridge, Julia A.; Tressoldi, Patrizio; Utts, Jessica; Ives, John A.; Radin, Dean; Jonas, Wayne B.

    2014-01-01

    A recent meta-analysis of experiments from seven independent laboratories (n = 26) indicates that the human body can apparently detect randomly delivered stimuli occurring 1–10 s in the future (Mossbridge etal., 2012). The key observation in these studies is that human physiology appears to be able to distinguish between unpredictable dichotomous future stimuli, such as emotional vs. neutral images or sound vs. silence. This phenomenon has been called presentiment (as in “feeling the future”). In this paper we call it predictive anticipatory activity (PAA). The phenomenon is “predictive” because it can distinguish between upcoming stimuli; it is “anticipatory” because the physiological changes occur before a future event; and it is an “activity” because it involves changes in the cardiopulmonary, skin, and/or nervous systems. PAA is an unconscious phenomenon that seems to be a time-reversed reflection of the usual physiological response to a stimulus. It appears to resemble precognition (consciously knowing something is going to happen before it does), but PAA specifically refers to unconscious physiological reactions as opposed to conscious premonitions. Though it is possible that PAA underlies the conscious experience of precognition, experiments testing this idea have not produced clear results. The first part of this paper reviews the evidence for PAA and examines the two most difficult challenges for obtaining valid evidence for it: expectation bias and multiple analyses. The second part speculates on possible mechanisms and the theoretical implications of PAA for understanding physiology and consciousness. The third part examines potential practical applications. PMID:24723870

  17. Modified Advanced Crew Escape Suit Intravehicular Activity Suit for Extravehicular Activity Mobility Evaluations

    NASA Technical Reports Server (NTRS)

    Watson, Richard D.

    2014-01-01

    The use of an intravehicular activity (IVA) suit for a spacewalk or extravehicular activity (EVA) was evaluated for mobility and usability in the Neutral Buoyancy Laboratory (NBL) environment at the Sonny Carter Training Facility near NASA Johnson Space Center in Houston, Texas. The Space Shuttle Advanced Crew Escape Suit was modified to integrate with the Orion spacecraft. The first several missions of the Orion Multi-Purpose Crew Vehicle will not have mass available to carry an EVA-specific suit; therefore, any EVA required will have to be performed by the Modified Advanced Crew Escape Suit (MACES). Since the MACES was not designed with EVA in mind, it was unknown what mobility the suit would be able to provide for an EVA or whether a person could perform useful tasks for an extended time inside the pressurized suit. The suit was evaluated in multiple NBL runs by a variety of subjects, including crewmembers with significant EVA experience. Various functional mobility tasks performed included: translation, body positioning, tool carrying, body stabilization, equipment handling, and tool usage. Hardware configurations included with and without Thermal Micrometeoroid Garment, suit with IVA gloves and suit with EVA gloves. Most tasks were completed on International Space Station mock-ups with existing EVA tools. Some limited tasks were completed with prototype tools on a simulated rocky surface. Major findings include: demonstrating the ability to weigh-out the suit, understanding the need to have subjects perform multiple runs prior to getting feedback, determining critical sizing factors, and need for adjusting suit work envelope. Early testing demonstrated the feasibility of EVA's limited duration and limited scope. Further testing is required with more flight-like tasking and constraints to validate these early results. If the suit is used for EVA, it will require mission-specific modifications for umbilical management or Primary Life Support System integration

  18. Activities of the Research Institute for Advanced Computer Science

    NASA Technical Reports Server (NTRS)

    Oliger, Joseph

    1994-01-01

    The Research Institute for Advanced Computer Science (RIACS) was established by the Universities Space Research Association (USRA) at the NASA Ames Research Center (ARC) on June 6, 1983. RIACS is privately operated by USRA, a consortium of universities with research programs in the aerospace sciences, under contract with NASA. The primary mission of RIACS is to provide research and expertise in computer science and scientific computing to support the scientific missions of NASA ARC. The research carried out at RIACS must change its emphasis from year to year in response to NASA ARC's changing needs and technological opportunities. Research at RIACS is currently being done in the following areas: (1) parallel computing; (2) advanced methods for scientific computing; (3) high performance networks; and (4) learning systems. RIACS technical reports are usually preprints of manuscripts that have been submitted to research journals or conference proceedings. A list of these reports for the period January 1, 1994 through December 31, 1994 is in the Reports and Abstracts section of this report.

  19. Advanced planning activity. [for interplanetary flight and space exploration

    NASA Technical Reports Server (NTRS)

    1974-01-01

    Selected mission concepts for interplanetary exploration through 1985 were examined, including: (1) Jupiter orbiter performance characteristics; (2) solar electric propulsion missions to Mercury, Venus, Neptune, and Uranus; (3) space shuttle planetary missions; (4) Pioneer entry probes to Saturn and Uranus; (5) rendezvous with Comet Kohoutek and Comet Encke; (6) space tug capabilities; and (7) a Pioneer mission to Mars in 1979. Mission options, limitations, and performance predictions are assessed, along with probable configurational, boost, and propulsion requirements.

  20. Can vesicle size distributions predict eruption intensity during volcanic activity?

    NASA Astrophysics Data System (ADS)

    LaRue, A.; Baker, D. R.; Polacci, M.; Allard, P.; Sodini, N.

    2013-06-01

    We studied three-dimensional (3-D) vesicle size distributions by X-ray microtomography in scoria collected during the relatively quiescent Phase II of the 2010 eruption at Eyjafjallajökull volcano, Iceland. Our goal was to compare the vesicle size distributions (VSDs) measured in these samples with those found in Stromboli volcano, Italy. Stromboli was chosen because its VSDs are well-characterized and show a correlation with eruption intensity: typical Strombolian activity produces VSDs with power-law exponents near 1, whereas larger and more energetic Vulcanian-type explosions and Plinian eruptions produce VSDs with power-law exponents near 1.5. The hypothesis to be tested was whether or not the samples studied in this work would contain VSDs similar to normal Strombolian products, display higher power-law exponents, or be described by exponential functions. Before making this comparison we tested the hypothesis that the phreatomagmatic nature of the Eyjafjallajökull eruption might have a significant effect on the VSDs. We performed 1 atm bubble-growth experiments in which the samples were inundated with water and compared them to similar, control, experiments without water inundation. No significant differences between the VSDs of the two sets of experiments were found, and the hypothesis is not supported by the experimental evidence; therefore, VSDs of magmatic and phreatomagmatic eruptions can be directly compared. The Phase II Eyjafjallajökull VSDs are described by power law exponents of ~ 0.8, typical of normal Strombolian eruptions. The comparable VSDs and behavior of Phase II of the Eyjafjallajökull 2010 eruption to Stromboli are interpreted to be a reflection of similar conduit systems in both volcanoes that are being constantly fed by the ascent of deep magma that mixes with resident magma at shallow depths. Such behavior implies that continued activity during Phase II of the Eyjafjallajökull eruption could be expected and would have been predicted

  1. Soil erosion predictions from upland areas – a discussion of selected RUSLE2 advances and needs

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Obtaining more accurate soil loss estimates from upland areas is important for improving management practices on agricultural fields. Much of the soil erosion prediction research of the last 25 years has been concerned with this goal. The most widely used predictive relationships have been the Unive...

  2. Advanced Study for Active Noise Control in Aircraft (ASANCA)

    NASA Technical Reports Server (NTRS)

    Borchers, Ingo U.; Emborg, Urban; Sollo, Antonio; Waterman, Elly H.; Paillard, Jacques; Larsen, Peter N.; Venet, Gerard; Goeransson, Peter; Martin, Vincent

    1992-01-01

    Aircraft interior noise and vibration measurements are included in this paper from ground and flight tests. In addition, related initial noise calculations with and without active noise control are conducted. The results obtained to date indicate that active noise control may be an effective means for reducing the critical low frequency aircraft noise.

  3. 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.

  4. Advanced Embedded Active Assemblies for Extreme Space Applications

    NASA Technical Reports Server (NTRS)

    DelCastillo, Linda; Moussessian, Alina; Mojarradi, Mohammad; Kolawa, Elizabeth

    2009-01-01

    This work describes the development and evaluation of advanced technologies for the integration of electronic die within membrane polymers. Specifically, investigators thinned silicon die, electrically connecting them with circuits on flexible liquid crystal polymer (LCP), using gold thermo-compression flip chip bonding, and embedding them within the material. Daisy chain LCP assemblies were thermal cycled from -135 to +85degC (Mars surface conditions for motor control electronics). The LCP assembly method was further utilized to embed an operational amplifier designed for operation within the Mars surface ambient. The embedded op-amp assembly was evaluated with respect to the influence of temperature on the operational characteristics of the device. Applications for this technology range from multifunctional, large area, flexible membrane structures to small-scale, flexible circuits that can be fit into tight spaces for flex to fit applications.

  5. Advanced active health monitoring system of liquid rocket engines

    NASA Astrophysics Data System (ADS)

    Qing, Xinlin P.; Wu, Zhanjun; Beard, Shawn; Chang, Fu-Kuo

    2008-11-01

    An advanced SMART TAPE system has been developed for real-time in-situ monitoring and long term tracking of structural integrity of pressure vessels in liquid rocket engines. The practical implementation of the structural health monitoring (SHM) system including distributed sensor network, portable diagnostic hardware and dedicated data analysis software is addressed based on the harsh operating environment. Extensive tests were conducted on a simulated large booster LOX-H2 engine propellant duct to evaluate the survivability and functionality of the system under the operating conditions of typical liquid rocket engines such as cryogenic temperature, vibration loads. The test results demonstrated that the developed SHM system could survive the combined cryogenic temperature and vibration environments and effectively detect cracks as small as 2 mm.

  6. New advances on glial activation in health and disease

    PubMed Central

    Lee, Kim Mai; MacLean, Andrew G

    2015-01-01

    In addition to being the support cells of the central nervous system (CNS), astrocytes are now recognized as active players in the regulation of synaptic function, neural repair, and CNS immunity. Astrocytes are among the most structurally complex cells in the brain, and activation of these cells has been shown in a wide spectrum of CNS injuries and diseases. Over the past decade, research has begun to elucidate the role of astrocyte activation and changes in astrocyte morphology in the progression of neural pathologies, which has led to glial-specific interventions for drug development. Future therapies for CNS infection, injury, and neurodegenerative disease are now aimed at targeting astrocyte responses to such insults including astrocyte activation, astrogliosis and other morphological changes, and innate and adaptive immune responses. PMID:25964871

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  8. Predicting Classroom Achievement from Active Responding on a Computer-Based Groupware System.

    ERIC Educational Resources Information Center

    Shin, Jongho; Deno, Stanley L.; Robinson, Steven L.; Marston, Douglas

    2000-01-01

    The predictive validity of active responding on a computer-based groupware system was examined with 48 second graders. Results showed that active responding correlated highly with initial and final performance measures and that active responding contributed significantly to predicting final performance when initial performance was controlled.…

  9. An Activity for Predicting Performances in the 1984 Summer Olympics.

    ERIC Educational Resources Information Center

    Henningsen, Jacqueline

    1984-01-01

    Techniques that students can use to make predictions about performances in the Olympics include point estimation. This is used to estimate a single value using a set of data. A worksheet for students is included. (MNS)

  10. Predictive motor control of sensory dynamics in auditory active sensing.

    PubMed

    Morillon, Benjamin; Hackett, Troy A; Kajikawa, Yoshinao; Schroeder, Charles E

    2015-04-01

    Neuronal oscillations present potential physiological substrates for brain operations that require temporal prediction. We review this idea in the context of auditory perception. Using speech as an exemplar, we illustrate how hierarchically organized oscillations can be used to parse and encode complex input streams. We then consider the motor system as a major source of rhythms (temporal priors) in auditory processing, that act in concert with attention to sharpen sensory representations and link them across areas. We discuss the circuits that could mediate this audio-motor interaction, notably the potential role of the somatosensory system. Finally, we reposition temporal predictions in the context of internal models, discussing how they interact with feature-based or spatial predictions. We argue that complementary predictions interact synergistically according to the organizational principles of each sensory system, forming multidimensional filters crucial to perception. PMID:25594376

  11. Advances in synthetic approach to and antifungal activity of triazoles

    PubMed Central

    Kumar, Nitin; Drabu, Sushma; Sharma, Pramod Kumar

    2011-01-01

    Summary Several five membered ring systems, e.g., triazole, oxadiazole dithiazole and thiadiazole with three heteroatoms at symmetrical or asymmetrical positions have been studied because of their interesting pharmacological properties. In this article our emphasis is on synthetic development and pharmacological activity of the triazole moiety which exhibit a broad spectrum of pharmacological activity such as antifungal, antibacterial, anti-inflammatory and anticancer etc. Triazoles have increased our ability to treat many fungal infections, for example, candidiasis, cryptococcal meningitis, aspergillosis etc. However, mortality due to these infections even with antifungal therapy is still unacceptably high. Therefore, the development of new antifungal agents targeting specific fungal structures or functions is being actively pursued. Rapid developments in molecular mycology have led to a concentrated search for more target antifungals. Although we are entering a new era of antifungal therapy in which we will continue to be challenged by systemic fungal diseases, the options for treatment will have greatly expanded. PMID:21804864

  12. Early prediction of pathological response in locally advanced rectal cancer based on sequential 18F-FDG PET

    PubMed Central

    HATT, MATHIEU; VAN STIPHOUT, RUUD; LE POGAM, ADRIEN; LAMMERING, GUIDO; VISVIKIS, DIMITRIS; LAMBIN, PHILIPPE

    2016-01-01

    Background The objectives of this study were to investigate the predictive value of sequential 18F-FDG PET scans for pathological tumor response grade (TRG) after preoperative chemoradiotherapy (PCRT) in locally advanced rectal cancer (LARC) and the impact of partial volume effects correction (PVC). Methods Twenty-eight LARC patients were included. Responders and non-responders status were determined in histopathology. PET indices [SUV max and mean, volume and total lesion glycolysis (TLG)] at baseline and their evolution after one and two weeks of PCRT were extracted by delineation of the PET images, with or without PVC. Their predictive value was investigated using Mann-Whitney-U tests and ROC analysis. Results Within baseline parameters, only SUVmean was correlated with response. No evolution after one week was predictive of the response, whereas after two weeks all the parameters except volume were, the best prediction being obtained with TLG (AUC 0.79, sensitivity 63%, specificity 92%). PVC had no significant impact on these results. Conclusion Several PET indices at baseline and their evolution after two weeks of PCRT are good predictors of response in LARC, with or without PVC, whereas results after one week are suboptimal. Best predictor was TLG reduction after two weeks, although baseline SUVmean had smaller but similar predictive power. PMID:22873767

  13. Drought Prediction Site Specific and Regional up to Three Years in Advance

    NASA Astrophysics Data System (ADS)

    Suhler, G.; O'Brien, D. P.

    2002-12-01

    Dynamic Predictables has developed proprietary software that analyzes and predicts future climatic behavior based on past data. The programs employ both a regional thermodynamic model together with a unique predictive algorithm to achieve a high degree of prediction accuracy up to 36 months. The thermodynamic model was developed initially to explain the results of a study on global circulation models done at SUNY-Stony Brook by S. Hameed, R.G. Currie, and H. LaGrone (Int. Jour. Climatology, 15, pp.852-871, 1995). The authors pointed out that on a time scale of 2-70 months the spectrum of sea level pressure is dominated by the harmonics and subharmonics of the seasonal cycle and their combination tones. These oscillations are fundamental to an understanding of climatic variations on a sub-regional to continental basis. The oscillatory nature of these variations allows them to be used as broad based climate predictors. In addition, they can be subtracted from the data to yield residuals. The residuals are then analyzed to determine components that are predictable. The program then combines both the thermodynamic model results (the primary predictive model) with those from the residual data (the secondary model) to yield an estimate of the future behavior of the climatic variable. Spatial resolution is site specific or aggregated regional based upon appropriate length (45 years or more monthly data) and reasonable quality weather observation records. Most climate analysis has been based on monthly time-step data, but time scales on the order of days can be used. Oregon Climate Division 1 (Coastal) precipitation provides an example relating DynaPred's method to nature's observed elements in the early 2000s. The prediction's leading dynamic factors are the strong seasonal in the primary model combined with high secondary model contributions from planet Earth's Chandler Wobble (near 15 months) and what has been called the Quasi-Triennial Oscillation (QTO, near 36 months

  14. Activities of the Specialized Agencies to Promote the Advancement of Women. Study on UNESCO Activities of Special Interest to Women.

    ERIC Educational Resources Information Center

    United Nations Economic and Social Council, New York, NY.

    There are two emphases of the UNESCO program to promote the advancement of women within the reporting period 1972-1973. They are (1) to involve member states closely in UNESCO activities and (2) to focus on the equality of educational opportunity. Activities include: (1) a report on a five country research program concerning the relationship…

  15. Advanced Extra-Vehicular Activity Pressure Garment Requirements Development

    NASA Technical Reports Server (NTRS)

    Ross, Amy; Aitchison, Lindsay; Rhodes, Richard

    2015-01-01

    The NASA Johnson Space Center advanced pressure garment technology development team is addressing requirements development for exploration missions. Lessons learned from the Z-2 high fidelity prototype development have reiterated that clear low-level requirements and verification methods reduce risk to the government, improve efficiency in pressure garment design efforts, and enable the government to be a smart buyer. The expectation is to provide requirements at the specification level that are validated so that their impact on pressure garment design is understood. Additionally, the team will provide defined verification protocols for the requirements. However, in reviewing exploration space suit high level requirements there are several gaps in the team's ability to define and verify related lower level requirements. This paper addresses the efforts in requirement areas such as mobility/fit/comfort and environmental protection (dust, radiation, plasma, secondary impacts) to determine the method by which the requirements can be defined and use of those methods for verification. Gaps exist at various stages. In some cases component level work is underway, but no system level effort has begun; in other cases no effort has been initiated to close the gap. Status of on-going efforts and potential approaches to open gaps are discussed.

  16. Overview of ASTM standard activities in support of advanced structural ceramics development

    SciTech Connect

    Brinkman, C.R.; Quinn, G.D.; McClung, R.W.

    1995-07-01

    An overview is presented of the activities of ASTM Committee C-28 on Advanced Ceramics. This activity originated in 1986 when it became apparent that advanced ceramics were being considered for extensive use in applications such as advanced heat engines, heat exchangers, combustors, etc. in aerospace and energy conservation activities. These applications require optimum material behavior with physical and mechanical property reproducibility, component reliability, and well defined methods of data treatment and material analysis for both monolithic and composite ceramic materials. As new materials are introduced into the market place, these issues are best dealt with via standard methods. Therefore, a progress report is given describing activities of the five standard writing subcommittees who support the ASTM Committee C-28 effort. Accomplishments to date are given, as well as likely future activities, including a brief summary of joint cooperative efforts with international standard formulating organizations.

  17. Advanced aerodynamics and active controls. Selected NASA research

    NASA Technical Reports Server (NTRS)

    1981-01-01

    Aerodynamic and active control concepts for application to commercial transport aircraft are discussed. Selected topics include in flight direct strike lightning research, triply redundant digital fly by wire control systems, tail configurations, winglets, and the drones for aerodynamic and structural testing (DAST) program.

  18. Advanced Activated Sludge. Training Module 2.117.4.77.

    ERIC Educational Resources Information Center

    Kirkwood Community Coll., Cedar Rapids, IA.

    This document is an instructional module package prepared in objective form for use by an instructor familiar with operation of activated sludge wastewater treatment plants. Included are objectives, instructor guides, student handouts and transparency masters. This is the third level of a three module series and considers design and operation…

  19. Recent advances in researches on physiologically active substances in holothurians

    NASA Astrophysics Data System (ADS)

    Takashi, Hirata; Nobuhiro, Zaima; Kyoko, Yamashita; Ryoko, Noguchi; Xue, Changhu; Tatsuya, Sugawara

    2005-07-01

    In this report, we reviewed recent literature on physiologically active substances from sea cucumbers (SCs) and their activities together with results obtained from our study. Preventive properties against lipid metabolism were reported in rats using a whole SC preparation with no particular constituent specified. Administration of the preparation lowered serum and hepatic cholesterol levels and improved the HDL/LDL ratio. These functions may be attributed to the stimulatory effect of the extract on the secretion of cholesterol in feces. Novel fucosylated chondroitin sulfates (FCSs) from Ludwigothurea grisea significantly induced fibroblast growth factor 2-dependent angiogenesis in human umbilical vein endothelial cells (HU-VECs). The proangiogenetic activity seemed attributable to the action of the sulfated fucose branches on the polysaccharide. SCs contain mycosporine-like amino acids (MAAs) that are capable of absorbing UV. A biogenetic precursor of MAAs was first reported in SCs. The anti-proliferative effects of a branched chain fatty acid from a sea cucumber on prostate cancer cells was reported with the activity of 5-lipoxygenase. Glycosphingolipid constituents in SCs have been systematically analyzed over the past ten years. The results showed that the gangliosides in several SCs differed from those of mammals in that a sialic acid of SC gangliosides directly binded to glucose of cerebroside. Neuritogenic activity of the glycosphingolipids was demonstrated in vitro experiments and may lead to the development of therapeutic products for neurological disorders. Our study also showed that sphingoid bases, the hydrolyzed products of glycosphingolipids from SCs, induced significant apoptosis in several tumor cell lines.

  20. Predictive and prognostic significance of circulating endothelial cells in advanced non-small cell lung cancer patients.

    PubMed

    Yuan, Dong-mei; Zhang, Qin; Lv, Yan-ling; Ma, Xing-qun; Zhang, Yan; Liu, Hong-bing; Song, Yong

    2015-11-01

    The aim of this study was to evaluate the predictive and prognostic values of circulating endothelial cells (CECs) in patients with advanced non-small cell lung cancer (NSCLC). A total of 102 newly diagnosed advanced NSCLC patients were enrolled in this study. The amount of CECs was enumerated by flow cytometry (CD45- CD31+ CD146+) at baseline. CEC counts of 56 patients were detected before and after two cycles of chemotherapy. We correlated the baseline and reduction of CECs after therapy with objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). The CEC level was significantly higher in advanced NSCLC patients, ranging from 57 to 1300 cells/10(5) cells (mean ± SD = 299 ± 221 cells/10(5) cells), than in patients with benign lesions (205 ± 97 cells/10(5) cells) and healthy volunteers (117 ± 33 cells/10(5) cells). When the cutoff value of CEC counts was 210 cells/10(5) cells, there was no significant association between CEC counts and OR/PFS/OS of the enrolled patients. However, patients with CEC response after chemotherapy have more chances to achieve OR (P < 0.001), and such patients showed longer PFS (P = 0.048) and OS (P = 0.018) than those without CEC response. In the multivariate analysis, the independent prognostic roles of brain metastasis (HR 6.165, P = 0.001), and CEC response (HR 0.442, P = 0.044) were found. The CEC counts could be considered as diagnostic biomarker for advanced NSCLC patients. And the reduction of CECs after treatment might be more ideal than the baseline CEC counts as a predictive or prognostic factor in patients treated with chemotherapy or anti-angiogenic therapy. PMID:26084612

  1. Solar activity prediction of sunspot numbers (verification). Predicted solar radio flux; predicted geomagnetic indices Ap and Kp. [space shuttle program: satellite orbital lifetime

    NASA Technical Reports Server (NTRS)

    Newman, S. R.

    1980-01-01

    Efforts to further verify a previously reported technique for predicting monthly sunspot numbers over a period of years (1979 to 1989) involved the application of the technique over the period for the maximum epoch of solar cycle 19. Results obtained are presented. Methods and results for predicting solar flux (F10.7 cm) based on flux/sunspot number models, ascent and descent, and geomagnetic activity indices as a function of sunspot number and solar cycle phase classes are included.

  2. 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.

  3. 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.

  4. 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.

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

    NASA Technical Reports Server (NTRS)

    Morrell, Michael Randy

    2002-01-01

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

  6. Mechanisms of inflammasome activation: recent advances and novel insights

    PubMed Central

    Vanaja, Sivapriya; Rathinam, Vijay K.

    2015-01-01

    Inflammasomes are cytosolic multiprotein platforms assembled in response to invading pathogens and other danger signals. Typically inflammasome complexes contain a sensor protein, an adaptor protein and a zymogen, procaspase-1. Formation of inflammasome assembly results in processing of inactive procasase-1 into an active cysteine protease enzyme, caspase-1, which subsequently activates proinflammatory cytokines, IL-1β and IL-18, and induces pyroptosis, a highly pyrogenic inflammatory form of cell death. Studies over the last year have unveiled exciting new players and regulatory pathways that are involved in traditional inflammasome signaling, some of them even challenging the existing dogma. This review outlines these new insights in inflammasome research and discusses areas that warrant further exploration. PMID:25639489

  7. 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

  8. Comparison of the PLTEMP code flow instability predictions with measurements made with electrically heated channels for the advanced test reactor.

    SciTech Connect

    Feldman, E.

    2011-06-09

    fuel element burnout is due to a form of flow instability. Whittle and Forgan provide a formula that predicts when this flow instability will occur. This formula is included in the PLTEMP/ANL code.Error! Reference source not found. Olson has shown that the PLTEMP/ANL code accurately predicts the powers at which flow instability occurs in the Whittle and Forgan experiments. He also considered the electrically heated tests performed in the ANS Thermal-Hydraulic Test Loop at ORNL and report by M. Siman-Tov et al. The purpose of this memorandum is to demonstrate that the PLTEMP/ANL code accurately predicts the Croft and the Waters tests. This demonstration should provide sufficient confidence that the PLTEMP/ANL code can adequately predict the onset of flow instability for the converted MURR. The MURR core uses light water as a coolant, has a 24-inch active fuel length, downward flow in the core, and an average core velocity of about 7 m/s. The inlet temperature is about 50 C and the peak outlet is about 20 C higher than the inlet for reactor operation at 10 MW. The core pressures range from about 4 to about 5 bar. The peak heat flux is about 110 W/cm{sup 2}. Section 2 describes the mechanism that causes flow instability. Section 3 describes the Whittle and Forgan formula for flow instability. Section 4 briefly describes both the Croft and the Waters experiments. Section 5 describes the PLTEMP/ANL models. Section 6 compares the PLTEMP/ANL predictions based on the Whittle and Forgan formula with the Croft measurements. Section 7 does the same for the Waters measurements. Section 8 provides the range of parameters for the Whittle and Forgan tests. Section 9 discusses the results and provides conclusions. In conclusion, although there is no single test that by itself closely matches the limiting conditions in the MURR, the preponderance of measured data and the ability of the Whittle and Forgan correlation, as implemented in PLTEMP/ANL, to predict the onset of flow

  9. Nestling activity levels during begging behaviour predicts activity level and body mass in adulthood

    PubMed Central

    Griffith, Simon C.

    2014-01-01

    Across a range of species including humans, personality traits, or differences in behaviour between individuals that are consistent over time, have been demonstrated. However, few studies have measured whether these consistent differences are evident in very young animals, and whether they persist over an individual’s entire lifespan. Here we investigated the begging behaviour of very young cross-fostered zebra finch nestlings and the relationship between that and adult activity levels. We found a link between the nestling activity behaviour head movements during begging, measured at just five and seven days after hatching, and adult activity levels, measured when individuals were between three and three and a half years old. Moreover, body mass was found to be negatively correlated with both nestling and adult activity levels, suggesting that individuals which carry less body fat as adults are less active both as adults and during begging as nestlings. Our work suggests that the personality traits identified here in both very young nestlings and adults may be linked to physiological factors such as metabolism or environmental sources of variation. Moreover, our work suggests it may be possible to predict an individual’s future adult personality at a very young age, opening up new avenues for future work to explore the relationship between personality and a number of aspects of individual life history and survival. PMID:25279258

  10. Nestling activity levels during begging behaviour predicts activity level and body mass in adulthood.

    PubMed

    McCowan, Luke S C; Griffith, Simon C

    2014-01-01

    Across a range of species including humans, personality traits, or differences in behaviour between individuals that are consistent over time, have been demonstrated. However, few studies have measured whether these consistent differences are evident in very young animals, and whether they persist over an individual's entire lifespan. Here we investigated the begging behaviour of very young cross-fostered zebra finch nestlings and the relationship between that and adult activity levels. We found a link between the nestling activity behaviour head movements during begging, measured at just five and seven days after hatching, and adult activity levels, measured when individuals were between three and three and a half years old. Moreover, body mass was found to be negatively correlated with both nestling and adult activity levels, suggesting that individuals which carry less body fat as adults are less active both as adults and during begging as nestlings. Our work suggests that the personality traits identified here in both very young nestlings and adults may be linked to physiological factors such as metabolism or environmental sources of variation. Moreover, our work suggests it may be possible to predict an individual's future adult personality at a very young age, opening up new avenues for future work to explore the relationship between personality and a number of aspects of individual life history and survival. PMID:25279258

  11. 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.

  12. 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. PMID:26346869

  13. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1978-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

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

  18. 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.

  19. TURBULENT PUMPING OF MAGNETIC FLUX REDUCES SOLAR CYCLE MEMORY AND THUS IMPACTS PREDICTABILITY OF THE SUN'S ACTIVITY

    SciTech Connect

    Karak, Bidya Binay; Nandy, Dibyendu E-mail: dnandi@iiserkol.ac.in

    2012-12-10

    Prediction of the Sun's magnetic activity is important because of its effect on space environment and climate. However, recent efforts to predict the amplitude of the solar cycle have resulted in diverging forecasts with no consensus. Yeates et al. have shown that the dynamical memory of the solar dynamo mechanism governs predictability, and this memory is different for advection- and diffusion-dominated solar convection zones. By utilizing stochastically forced, kinematic dynamo simulations, we demonstrate that the inclusion of downward turbulent pumping of magnetic flux reduces the memory of both advection- and diffusion-dominated solar dynamos to only one cycle; stronger pumping degrades this memory further. Thus, our results reconcile the diverging dynamo-model-based forecasts for the amplitude of solar cycle 24. We conclude that reliable predictions for the maximum of solar activity can be made only at the preceding minimum-allowing about five years of advance planning for space weather. For more accurate predictions, sequential data assimilation would be necessary in forecasting models to account for the Sun's short memory.

  20. Thrombin activation and liver inflammation in advanced hepatitis C virus infection

    PubMed Central

    González-Reimers, Emilio; Quintero-Platt, Geraldine; Martín-González, Candelaria; Pérez-Hernández, Onán; Romero-Acevedo, Lucía; Santolaria-Fernández, Francisco

    2016-01-01

    Hepatitis C virus (HCV) infection is associated with increased thrombotic risk. Several mechanisms are involved including direct endothelial damage by the HCV virus, with activation of tissue factor, altered fibrinolysis and increased platelet aggregation and activation. In advanced stages, chronic HCV infection may evolve to liver cirrhosis, a condition in which alterations in the portal microcirculation may also ultimately lead to thrombin activation, platelet aggregation, and clot formation. Therefore in advanced HCV liver disease there is an increased prevalence of thrombotic phenomena in portal vein radicles. Increased thrombin formation may activate hepatic stellate cells and promote liver fibrosis. In addition, ischemic changes derived from vascular occlusion by microthrombi favor the so called parenchymal extinction, a process that promotes collapse of hepatocytes and the formation of gross fibrous tracts. These reasons may explain why advanced HCV infection may evolve more rapidly to end-stage liver disease than other forms of cirrhosis. PMID:27182154

  1. Thrombin activation and liver inflammation in advanced hepatitis C virus infection.

    PubMed

    González-Reimers, Emilio; Quintero-Platt, Geraldine; Martín-González, Candelaria; Pérez-Hernández, Onán; Romero-Acevedo, Lucía; Santolaria-Fernández, Francisco

    2016-05-14

    Hepatitis C virus (HCV) infection is associated with increased thrombotic risk. Several mechanisms are involved including direct endothelial damage by the HCV virus, with activation of tissue factor, altered fibrinolysis and increased platelet aggregation and activation. In advanced stages, chronic HCV infection may evolve to liver cirrhosis, a condition in which alterations in the portal microcirculation may also ultimately lead to thrombin activation, platelet aggregation, and clot formation. Therefore in advanced HCV liver disease there is an increased prevalence of thrombotic phenomena in portal vein radicles. Increased thrombin formation may activate hepatic stellate cells and promote liver fibrosis. In addition, ischemic changes derived from vascular occlusion by microthrombi favor the so called parenchymal extinction, a process that promotes collapse of hepatocytes and the formation of gross fibrous tracts. These reasons may explain why advanced HCV infection may evolve more rapidly to end-stage liver disease than other forms of cirrhosis. PMID:27182154

  2. 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.

  3. 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...

  4. Prediction of Pathway Activation by Xenobiotic-Responsive Transcription Factors in the Mouse Liver

    EPA Science Inventory

    Many drugs and environmentally-relevant chemicals activate xenobioticresponsive transcription factors (TF). Identification of target genes of these factors would be useful in predicting pathway activation in in vitro chemical screening. Starting with a large compendium of Affymet...

  5. Reinforcing Constructivist Teaching in Advanced Level Biochemistry through the Introduction of Case-Based Learning Activities

    ERIC Educational Resources Information Center

    Hartfield, Perry J.

    2010-01-01

    In the process of curriculum development, I have integrated a constructivist teaching strategy into an advanced-level biochemistry teaching unit. Specifically, I have introduced case-based learning activities into the teaching/learning framework. These case-based learning activities were designed to develop problem-solving skills, consolidate…

  6. [Advances in studies on chemical constituents and biological activities of Desmodium species].

    PubMed

    Liu, Chao; Wu, Ying; Zhang, Qian-Jun; Kang, Wen-Yi; Zhang, Long; Zhou, Qing-Di

    2013-12-01

    The chemical constituents isolated from Desmodium species (Leguminosae) included terpenoids, flavonoids, steroids, alkaloids compounds. Modem pharmacological studies have showed that the Desmodium species have antioxidant, antibacterial, anti-inflammatory, hepatoprotective, diuretic, antipyretic, analgesic and choleretic activity. This article mainly has reviewed the research advances of chemical constituents and biological activities of Desmodium species since 2003. PMID:24791478

  7. Solar activity and its evolution across the corona: recent advances

    NASA Astrophysics Data System (ADS)

    Zuccarello, Francesca; Balmaceda, Laura; Cessateur, Gael; Cremades, Hebe; Guglielmino, Salvatore L.; Lilensten, Jean; Dudok de Wit, Thierry; Kretzschmar, Matthieu; Lopez, Fernando M.; Mierla, Marilena; Parenti, Susanna; Pomoell, Jens; Romano, Paolo; Rodriguez, Luciano; Srivastava, Nandita; Vainio, Rami; West, Matt; Zuccarello, Francesco P.

    2013-04-01

    Solar magnetism is responsible for the several active phenomena that occur in the solar atmosphere. The consequences of these phenomena on the solar-terrestrial environment and on Space Weather are nowadays clearly recognized, even if not yet fully understood. In order to shed light on the mechanisms that are at the basis of the Space Weather, it is necessary to investigate the sequence of phenomena starting in the solar atmosphere and developing across the outer layers of the Sun and along the path from the Sun to the Earth. This goal can be reached by a combined multi-disciplinary, multi-instrument, multi-wavelength study of these phenomena, starting with the very first manifestation of solar active region formation and evolution, followed by explosive phenomena (i.e., flares, erupting prominences, coronal mass ejections), and ending with the interaction of plasma magnetized clouds expelled from the Sun with the interplanetary magnetic field and medium. This wide field of research constitutes one of the main aims of COST Action ES0803: Developing Space Weather products and services in Europe. In particular, one of the tasks of this COST Action was to investigate the Progress in Scientific Understanding of Space Weather. In this paper we review the state of the art of our comprehension of some phenomena that, in the scenario outlined above, might have a role on Space Weather, focusing on the researches, thematic reviews, and main results obtained during the COST Action ES0803.

  8. Advances in the pharmacological activities and mechanisms of diosgenin.

    PubMed

    Chen, Yan; Tang, You-Mei; Yu, Su-Lan; Han, Yu-Wei; Kou, Jun-Ping; Liu, Bao-Lin; Yu, Bo-Yang

    2015-08-01

    Diosgenin, a well-known steroid sapogenin derived from plants, has been used as a starting material for production of steroidal hormones. The present review will summarize published literature concerning pharmacological potential of diosgenin, and the underlying mechanisms of actions. Diosgenin has shown a vast range of pharmacological activities in preclinical studies. It exhibits anticancer, cardiovascular protective, anti-diabetes, neuroprotective, immunomodulatory, estrogenic, and skin protective effects, mainly by inducing apoptosis, suppressing malignant transformation, decreasing oxidative stress, preventing inflammatory events, promoting cellular differentiation/proliferation, and regulating T-cell immune response, etc. It interferes with cell death pathways and their regulators to induce apoptosis. Diosgenin antagonizes tumor metastasis by modulating epithelial-mesenchymal transition and actin cytoskeleton to change cellular motility, suppressing degradation of matrix barrier, and inhibiting angiogenesis. Additionally, diosgenin improves antioxidant status and inhibits lipid peroxidation. Its anti-inflammatory activity is through inhibiting production of pro-inflammatory cytokines, enzymes and adhesion molecules. Furthermore, diosgenin drives cellular growth/differentiation through the estrogen receptor (ER) cascade and transcriptional factor PPARγ. In summary, these mechanistic studies provide a basis for further development of this compound for pharmacotherapy of various diseases. PMID:26253490

  9. Incorporating an advanced aerosol activation parameterization into WRF-CAM5: Model evaluation and parameterization intercomparison

    SciTech Connect

    Zhang, Yang; Zhang, Xin; Wang, Kai; He, Jian; Leung, Lai-Yung R.; Fan, Jiwen; Nenes, Athanasios

    2015-07-22

    Aerosol activation into cloud droplets is an important process that governs aerosol indirect effects. The advanced treatment of aerosol activation by Fountoukis and Nenes (2005) and its recent updates, collectively called the FN series, have been incorporated into a newly developed regional coupled climate-air quality model based on the Weather Research and Forecasting model with the physics package of the Community Atmosphere Model version 5 (WRF-CAM5) to simulate aerosol-cloud interactions in both resolved and convective clouds. The model is applied to East Asia for two full years of 2005 and 2010. A comprehensive model evaluation is performed for model predictions of meteorological, radiative, and cloud variables, chemical concentrations, and column mass abundances against satellite data and surface observations from air quality monitoring sites across East Asia. The model performs overall well for major meteorological variables including near-surface temperature, specific humidity, wind speed, precipitation, cloud fraction, precipitable water, downward shortwave and longwave radiation, and column mass abundances of CO, SO2, NO2, HCHO, and O3 in terms of both magnitudes and spatial distributions. Larger biases exist in the predictions of surface concentrations of CO and NOx at all sites and SO2, O3, PM2.5, and PM10 concentrations at some sites, aerosol optical depth, cloud condensation nuclei over ocean, cloud droplet number concentration (CDNC), cloud liquid and ice water path, and cloud optical thickness. Compared with the default Abdul-Razzack Ghan (2000) parameterization, simulations with the FN series produce ~107–113% higher CDNC, with half of the difference attributable to the higher aerosol activation fraction by the FN series and the remaining half due to feedbacks in subsequent cloud microphysical processes. With the higher CDNC, the FN series are more skillful in simulating cloud water path, cloud optical thickness, downward shortwave radiation

  10. Low acute hematological toxicity during chemotherapy predicts reduced disease control in advanced Hodgkin's disease.

    PubMed

    Brosteanu, O; Hasenclever, D; Loeffler, M; Diehl, V

    2004-03-01

    Chemotherapy-treated patients with advanced Hodgkin's disease (HD) differ considerably in acute hematotoxicity. Hematotoxicity may be indicative of pharmacological and metabolic heterogeneity. We hypothesized that low hematotoxicity might correlate with reduced systemic dose and thus reduced disease control. A total of 266 patients with advanced HD treated with cyclophosphamide, vincristine, procarbazine, prednisone, doxorubicin, bleomycin, vinblastine, and dacarbazine (COPP-ABVD) were analyzed (HD6 trial of the German Hodgkin's Lymphoma Study Group). The reported WHO grade of leukocytopenia was averaged over chemotherapy cycles given and weighted with the reciprocal dose intensity of the corresponding cycle. The low and high toxicity groups were defined in retrospect as having had an averaged WHO grade of leukocytopenia 2.1, respectively. The independent impact of low hematological toxicity on freedom from treatment failure (FFTF) was assessed multivariately adjusting for the international prognostic score for advanced HD. The results were validated in two independent cohorts [181 patients treated with COPP-ABVD (HD9-trial) and 250 patients treated with COPP-ABV-ifosfamide, methotrexate, etoposide, and prednisone (IMEP) (HD6 trial)]. The 5-year FFTF rates were 68% for patients with high toxicity vs 47% for patients with low toxicity [multivariate relative risk (RR) 2.0, 95% confidence interval (CI) 1.4-3.0, p=0.0002]. Patients with low toxicity received significantly higher nominal dose ( p=0.02) and dose intensity ( p<0.0001). This finding was confirmed in both validation cohorts (multivariate RR 2.1, 95% CI 1.2-3.8, p=0.01 and RR 1.5, 95% CI 1.01-2.26, p=0.04, respectively). Patients with low hematotoxicity have significantly higher failure rates despite higher doses and dose intensity. Hematotoxicity is an independent prognostic factor for treatment outcome. This observation suggests a strategy of individualized dosing adapted to hematotoxicity

  11. Activities and operations of Argonne's Advanced Computing Research Facility: February 1990 through April 1991

    SciTech Connect

    Pieper, G.W.

    1991-05-01

    This report reviews the activities and operations of the Advanced Computing Research Facility (ACRF) from February 1990 through April 1991. The ACRF is operated by the Mathematics and Computer Science Division at Argonne National Laboratory. The facility's principal objective is to foster research in parallel computing. Toward this objective, the ACRF operates experimental advanced computers, supports investigations in parallel computing, and sponsors technology transfer efforts to industry and academia. 5 refs., 1 fig.

  12. Activities and operations of the Advanced Computing Research Facility, January 1989--January 1990

    SciTech Connect

    Pieper, G.W.

    1990-02-01

    This report reviews the activities and operations of the Advanced Computing Research Facility (ACRF) for the period January 1, 1989, through January 31, 1990. The ACRF is operated by the Mathematics and Computer Science Division at Argonne National Laboratory. The facility's principal objective is to foster research in parallel computing. Toward this objective, the ACRF continues to operate experimental advanced computers and to sponsor new technology transfer efforts and new research projects. 4 refs., 8 figs.

  13. New active drugs for the treatment of advanced colorectal cancer

    PubMed Central

    Zaniboni, Alberto

    2015-01-01

    Newer active drugs have been recently added to the pharmacological armamentarium for the treatment of metastatic colorectal cancer. Aflibercept, a recombinant fusion protein composed of the extracellular domains of human vascular endothelial growth factor receptors (VEGFR) 1 and 2 and the Fc portion of human immunoglobulin G1 (IgG1), is an attractive second-line option in combination with folfiri for patients who have failed folfox +/- bevacizumab. Ramucirumab, a human IgG1 monoclonal antibody that targets VEGFR-2, provided similar results in the same setting. Tas-102, an oral fluoropyrimidine, and regorafenib, a multi-tyrosine kinase inhibitor, are both able to control the disease in a considerable proportion of patients when all other available treatments have failed. These new therapeutic options along with the emerging concept that previous therapies may also be reitroduced or rechallenged after regorafenib and Tas-102 failure are bringing new hope for thousands of patients and their families. PMID:26730280

  14. Technology advances in active and passive microwave sensing through 1985

    NASA Technical Reports Server (NTRS)

    Barath, F. T.

    1977-01-01

    As a result of a growing awareness by the remote sensing community of the unique capabilities of passive and active microwave sensors, these instruments are expected to grow in the next decade in numbers, versatility and complexity. The Nimbus-G and Seasat-A Scanning Multichannel Microwave Spectrometer (SMMR), the Seasat-A radar altimeter, scatterometer and synthetic aperture radar represent the first systematic attempt at exploring a wide variety of applications utilizing microwave sensing techniques and are indicators of the directions in which the pertinent technology is likely to evolve. The trend is toward high resolution multi-frequency imagers spanning wide frequency ranges and wide swaths requiring sophisticated receivers, real-time data processors and most importantly, complex antennas.

  15. New active drugs for the treatment of advanced colorectal cancer.

    PubMed

    Zaniboni, Alberto

    2015-12-27

    Newer active drugs have been recently added to the pharmacological armamentarium for the treatment of metastatic colorectal cancer. Aflibercept, a recombinant fusion protein composed of the extracellular domains of human vascular endothelial growth factor receptors (VEGFR) 1 and 2 and the Fc portion of human immunoglobulin G1 (IgG1), is an attractive second-line option in combination with folfiri for patients who have failed folfox +/- bevacizumab. Ramucirumab, a human IgG1 monoclonal antibody that targets VEGFR-2, provided similar results in the same setting. Tas-102, an oral fluoropyrimidine, and regorafenib, a multi-tyrosine kinase inhibitor, are both able to control the disease in a considerable proportion of patients when all other available treatments have failed. These new therapeutic options along with the emerging concept that previous therapies may also be reitroduced or rechallenged after regorafenib and Tas-102 failure are bringing new hope for thousands of patients and their families. PMID:26730280

  16. Fostering Engagement Activities To Advance Adaptation And Resiliency

    NASA Astrophysics Data System (ADS)

    Dissen, J.; Owen, T.; Brewer, M.; Hollingshead, A.; Mecray, E. L.; Werner, K.

    2015-12-01

    As the understanding of climate risks grows for public and private companies, the dissemination of meaningful climate and environmental information becomes important for improved risk management practices and innovation. In a broader effort to build capacity for adaptation and demonstrate the value of investment in resiliency, NCEI and its partners have made several shifts to showcase an improved understanding of uses and applications of climate and environmental data and information. The NOAA NCEI engagement initiative includes actively exploring ways to: 1) identify opportunities in data use and applications and 2) characterize needs and requirements from customers to help inform investment in the relevant science. This presentation will highlight: 1) NCEI's engagement initiative strategy, 2) our regional and national partnerships as agents of engagement in the region, 3) a few examples of uses of climate information with select stakeholders and 4) justification of customer engagement and requirements as a critical component in informing the science agenda.

  17. Advances in preparation, analysis and biological activities of single chitooligosaccharides.

    PubMed

    Li, Kecheng; Xing, Ronge; Liu, Song; Li, Pengcheng

    2016-03-30

    Chitooligosaccharides (COS), as a source of potential bioactive material, has been reported to possess diverse bioactivities. These bioactivities of COS are often tested using relatively poorly characterized oligomer mixtures during past few decades, resulting in difficult identification of COS molecules responsible for biological effects. Therefore, a new interest has recently been emerged on highly purified COS of defined size. Several technological approaches have been used to produce single COS and new improvements were introduced to their characterization in order to understand the unrevealed structure-function relationship. Here we provide an overview of techniques that were used to prepare and analyze reasonably well-defined COS fractions. Based on the latest reports, several applications of single COS for plants and animals, are also presented, including antitumor, immunostimulatory, antioxidant, antimicrobial, elicitors of plant defence and neural activity. PMID:26794961

  18. Advanced active quenching circuits for single-photon avalanche photodiodes

    NASA Astrophysics Data System (ADS)

    Stipčević, M.; Christensen, B. G.; Kwiat, P. G.; Gauthier, D. J.

    2016-05-01

    Commercial photon-counting modules, often based on actively quenched solid-state avalanche photodiode sensors, are used in wide variety of applications. Manufacturers characterize their detectors by specifying a small set of parameters, such as detection efficiency, dead time, dark counts rate, afterpulsing probability and single photon arrival time resolution (jitter), however they usually do not specify the conditions under which these parameters are constant or present a sufficient description. In this work, we present an in-depth analysis of the active quenching process and identify intrinsic limitations and engineering challenges. Based on that, we investigate the range of validity of the typical parameters used by two commercial detectors. We identify an additional set of imperfections that must be specified in order to sufficiently characterize the behavior of single-photon counting detectors in realistic applications. The additional imperfections include rate-dependence of the dead time, jitter, detection delay shift, and "twilighting." Also, the temporal distribution of afterpulsing and various artifacts of the electronics are important. We find that these additional non-ideal behaviors can lead to unexpected effects or strong deterioration of the system's performance. Specifically, we discuss implications of these new findings in a few applications in which single-photon detectors play a major role: the security of a quantum cryptographic protocol, the quality of single-photon-based random number generators and a few other applications. Finally, we describe an example of an optimized avalanche quenching circuit for a high-rate quantum key distribution system based on time-bin entangled photons.

  19. Prediction of geomagnetic activity on time scales of one to ten years

    NASA Technical Reports Server (NTRS)

    Feynman, J.; Gu, X. Y.

    1986-01-01

    The long-term prediction of geomagnetic indices that characterize the state of the magnetosphere is discussed. While a prediction of the yearly average sunspot number is simultaneously a prediction of the yearly number of sudden-commencement storms, it is not a prediction of the number of disturbed or quiet half days. Knowledge of the sunspot cycle phase leads to a good estimate of the correlation expected between activity during one 27-day solar rotation period and the next.

  20. LSD-induced entropic brain activity predicts subsequent personality change.

    PubMed

    Lebedev, A V; Kaelen, M; Lövdén, M; Nilsson, J; Feilding, A; Nutt, D J; Carhart-Harris, R L

    2016-09-01

    Personality is known to be relatively stable throughout adulthood. Nevertheless, it has been shown that major life events with high personal significance, including experiences engendered by psychedelic drugs, can have an enduring impact on some core facets of personality. In the present, balanced-order, placebo-controlled study, we investigated biological predictors of post-lysergic acid diethylamide (LSD) changes in personality. Nineteen healthy adults underwent resting state functional MRI scans under LSD (75µg, I.V.) and placebo (saline I.V.). The Revised NEO Personality Inventory (NEO-PI-R) was completed at screening and 2 weeks after LSD/placebo. Scanning sessions consisted of three 7.5-min eyes-closed resting-state scans, one of which involved music listening. A standardized preprocessing pipeline was used to extract measures of sample entropy, which characterizes the predictability of an fMRI time-series. Mixed-effects models were used to evaluate drug-induced shifts in brain entropy and their relationship with the observed increases in the personality trait openness at the 2-week follow-up. Overall, LSD had a pronounced global effect on brain entropy, increasing it in both sensory and hierarchically higher networks across multiple time scales. These shifts predicted enduring increases in trait openness. Moreover, the predictive power of the entropy increases was greatest for the music-listening scans and when "ego-dissolution" was reported during the acute experience. These results shed new light on how LSD-induced shifts in brain dynamics and concomitant subjective experience can be predictive of lasting changes in personality. Hum Brain Mapp 37:3203-3213, 2016. © 2016 Wiley Periodicals, Inc. PMID:27151536

  1. Prediction of active control of subsonic centrifugal compressor rotating stall

    NASA Technical Reports Server (NTRS)

    Lawless, Patrick B.; Fleeter, Sanford

    1993-01-01

    A mathematical model is developed to predict the suppression of rotating stall in a centrifugal compressor with a vaned diffuser. This model is based on the employment of a control vortical waveform generated upstream of the impeller inlet to damp weak potential disturbances that are the early stages of rotating stall. The control system is analyzed by matching the perturbation pressure in the compressor inlet and exit flow fields with a model for the unsteady behavior of the compressor. The model was effective at predicting the stalling behavior of the Purdue Low Speed Centrifugal Compressor for two distinctly different stall patterns. Predictions made for the effect of a controlled inlet vorticity wave on the stability of the compressor show that for minimum control wave magnitudes, on the order of the total inlet disturbance magnitude, significant damping of the instability can be achieved. For control waves of sufficient amplitude, the control phase angle appears to be the most important factor in maintaining a stable condition in the compressor.

  2. Prediction of Geomagnetic Activity and Key Parameters in High-latitude Ionosphere

    NASA Technical Reports Server (NTRS)

    Khazanov, George V.; Lyatsky, Wladislaw; Tan, Arjun; Ridley, Aaron

    2007-01-01

    Prediction of geomagnetic activity and related events in the Earth's magnetosphere and ionosphere are important tasks of US Space Weather Program. Prediction reliability is dependent on the prediction method, and elements included in the prediction scheme. Two of the main elements of such prediction scheme are: an appropriate geomagnetic activity index, and an appropriate coupling function (the combination of solar wind parameters providing the best correlation between upstream solar wind data and geomagnetic activity). We have developed a new index of geomagnetic activity, the Polar Magnetic (PM) index and an improved version of solar wind coupling function. PM index is similar to the existing polar cap PC index but it shows much better correlation with upstream solar wind/IMF data and other events in the magnetosphere and ionosphere. We investigate the correlation of PM index with upstream solar wind/IMF data for 10 years (1995-2004) that include both low and high solar activity. We also have introduced a new prediction function for the predicting of cross-polar-cap voltage and Joule heating based on using both PM index and upstream solar wind/IMF data. As we show such prediction function significantly increase the reliability of prediction of these important parameters. The correlation coefficients between the actual and predicted values of these parameters are approx. 0.9 and higher.

  3. Intrinsic resistance to EGFR tyrosine kinase inhibitors in advanced non-small-cell lung cancer with activating EGFR mutations

    PubMed Central

    Wang, Jun; Wang, Baocheng; Chu, Huili; Yao, Yunfeng

    2016-01-01

    Identifying activating EGFR mutations is a useful predictive strategy that helps select a population of advanced non-small-cell lung cancer (NSCLC) patients for treatment with EGFR tyrosine kinase inhibitors (TKIs). Patients with sensitizing EGFR mutations (predominantly an in-frame deletion in exon 19 and an L858R substitution) are highly responsive to first-generation EGFR TKIs, such as gefitinib and erlotinib, and show improved progression-free survival without serious side effects. However, all patients with activating EGFR mutations who are initially responsive to EGFR TKIs eventually develop acquired resistance after a median progression-free survival of 10–16 months, followed by disease progression. Moreover, ~20%–30% of NSCLC patients have no objective tumor regression on initial EGFR TKI treatment, although they harbor an activating EGFR mutation. These patients represent an NSCLC subgroup that is defined as having intrinsic or primary resistance to EGFR TKIs. Different mechanisms of acquired EGFR TKI resistance have been identified, and several novel compounds have been developed to reverse acquired resistance, but little is known about EGFR TKI intrinsic resistance. In this review, we summarize the latest findings involving mechanisms of intrinsic resistance to EGFR TKIs in advanced NSCLC with activating EGFR mutations and present possible therapeutic strategies to overcome this resistance. PMID:27382309

  4. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

    PubMed

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets. PMID:27532883

  5. 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

  6. Active osmotic exchanger for advanced filtration at the nano scale

    NASA Astrophysics Data System (ADS)

    Marbach, Sophie; Bocquet, Lyderic

    2015-11-01

    One of the main functions of the kidney is to remove the waste products of an organism, mostly by excreting concentrated urea while reabsorbing water and other molecules. The human kidney is capable of recycling about 200 liters of water per day, at the relatively low cost of 0.5 kJ/L (standard dialysis requiring at least 150 kJ/L). Kidneys are constituted of millions of parallel filtration networks called nephrons. The nephrons of all mammalian kidneys present a specific loop geometry, the Loop of Henle, that is believed to play a key role in the urinary concentrating mechanism. One limb of the loop is permeable to water and the other contains sodium pumps that exchange with a common interstitium. In this work, we take inspiration from this osmotic exchanger design to propose new nanofiltration principles. We first establish simple analytical results to derive general operating principles, based on coupled water permeable pores and osmotic pumps. The best filtration geometry, in terms of power required for a given water recycling ratio, is comparable in many ways to the mammalian nephron. It is not only more efficient than traditional reverse osmosis systems, but can also work at much smaller pressures (of the order of the blood pressure, 0.13 bar, as compared to more than 30 bars for pressure-retarded osmosis systems). We anticipate that our proof of principle will be a starting point for the development of new filtration systems relying on the active osmotic exchanger principle.

  7. Advances in multifocal methods for imaging human brain activity

    NASA Astrophysics Data System (ADS)

    Carney, Thom; Ales, Justin; Klein, Stanley A.

    2006-02-01

    The typical multifocal stimulus used in visual evoked potential (VEP) studies consists of about 60 checkerboard stimulus patches each independently contrast reversed according to an m-sequence. Cross correlation of the response (EEG, MEG, ERG, or fMRI) with the m-sequence results in a series of response kernels for each response channel and each stimulus patch. In the past the number and complexity of stimulus patches has been constrained by graphics hardware, namely the use of look-up-table (LUT) animation methods. To avoid such limitations we replaced the LUTs with true color graphic sprites to present arbitrary spatial patterns. To demonstrate the utility of the method we have recorded simultaneously from 192 cortically scaled stimulus patches each of which activate about 12mm2 of cortex in area V1. Because of the sparseness of cortical folding, very small stimulus patches and robust estimation of dipole source orientation, the method opens a new window on precise spatio-temporal mapping of early visual areas. The use of sprites also enables multiplexing stimuli such that at each patch location multiple stimuli can be presented. We have presented patterns with different orientations (or spatial frequencies) at the same patch locations but independently temporally modulated, effectively doubling the number of stimulus patches, to explore cell population interactions at the same cortical locus. We have also measured nonlinear responses to adjacent pairs of patches, thereby getting an edge response that doubles the spatial sampling density to about 1.8 mm on cortex.

  8. Predicting Earthquake Occurrence at Subduction-Zone Plate Boundaries Through Advanced Computer Simulation

    NASA Astrophysics Data System (ADS)

    Matsu'Ura, M.; Hashimoto, C.; Fukuyama, E.

    2004-12-01

    In general, predicting the occurrence of earthquakes is very difficult, because of the complexity of actual faults and nonlinear interaction between them. From the standpoint of earthquake prediction, however, our target is limited to the large events that completely break down a seismogenic zone. To such large events we may apply the concept of the earthquake cycle. The entire process of earthquake generation cycles generally consists of tectonic loading due to relative plate motion, quasi-static rupture nucleation, dynamic rupture propagation and stop, and restoration of fault strength. This process can be completely described by a coupled nonlinear system, which consists of an elastic/viscoelastic slip-response function that relates fault slip to shear stress change and a fault constitutive law that prescribes change in shear strength with fault slip and contact time. The shear stress and the shear strength are related with each other through boundary conditions on the fault. The driving force of this system is observed relative plate motion. The system to describe the earthquake generation cycle is conceptually quite simple. The complexity in practical modeling mainly comes from complexity in structure of the real earth. Recently, we have developed a physics-based, predictive simulation system for earthquake generation at plate boundaries in and around Japan, where the four plates of Pacific, North American, Philippine Sea and Eurasian are interacting with each other. The simulation system consists of a crust-mantle structure model, a quasi-static tectonic loading model, and a dynamic rupture propagation model. First, we constructed a realistic 3D model of plate interfaces in and around Japan by applying an inversion technique to ISC hypocenter data, and computed viscoelastic slip-response functions for this structure model. Second, we introduced the slip- and time-dependent fault constitutive law with an inherent strength-restoration mechanism as a basic

  9. Transfer Student Success: Educationally Purposeful Activities Predictive of Undergraduate GPA

    ERIC Educational Resources Information Center

    Fauria, Renee M.; Fuller, Matthew B.

    2015-01-01

    Researchers evaluated the effects of Educationally Purposeful Activities (EPAs) on transfer and nontransfer students' cumulative GPAs. Hierarchical, linear, and multiple regression models yielded seven statistically significant educationally purposeful items that influenced undergraduate student GPAs. Statistically significant positive EPAs for…

  10. Predictive and prognostic biomarkers for neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

    PubMed

    Lim, S H; Chua, W; Henderson, C; Ng, W; Shin, J-S; Chantrill, L; Asghari, R; Lee, C S; Spring, K J; de Souza, P

    2015-10-01

    Locally advanced rectal cancer is regularly treated with trimodality therapy consisting of neoadjuvant chemoradiation, surgery and adjuvant chemotherapy. There is a need for biomarkers to assess treatment response, and aid in stratification of patient risk to adapt and personalise components of the therapy. Currently, pathological stage and tumour regression grade are used to assess response. Experimental markers include proteins involved in cell proliferation, apoptosis, angiogenesis, the epithelial to mesenchymal transition and microsatellite instability. As yet, no single marker is sufficiently robust to have clinical utility. Microarrays that screen a tumour for multiple promising candidate markers, gene expression and microRNA profiling will likely have higher yield and it is expected that a combination or panel of markers would prove most useful. Moving forward, utilising serial samples of circulating tumour cells or circulating nucleic acids can potentially allow us to demonstrate tumour heterogeneity, document mutational changes and subsequently measure treatment response. PMID:26032919

  11. 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.

  12. 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.

  13. 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.

  14. Prognostic and Predictive Blood-Based Biomarkers in Patients with Advanced Pancreatic Cancer: Results from CALGB80303 (Alliance)

    PubMed Central

    Nixon, Andrew B.; Pang, Herbert; Starr, Mark D.; Friedman, Paula N.; Bertagnolli, Monica M.; Kindler, Hedy L.; Goldberg, Richard M.; Venook, Alan P.; Hurwitz, Herbert I.

    2014-01-01

    Purpose CALGB80303 was a phase III trial of 602 patients with locally advanced or metastatic pancreatic cancer comparing gemcitabine/bevacizumab versus gemcitabine/placebo. The study found no benefit in any outcome from the addition of bevacizumab to gemcitabine. Blood samples were collected and multiple angiogenic factors were evaluated and then correlated with clinical outcome in general (prognostic markers) and with benefit specifically from bevacizumab treatment (predictive markers). Experimental Design Plasma samples were analyzed via a novel multiplex ELISA platform for 31 factors related to tumor growth, angiogenesis, and inflammation. Baseline values for these factors were correlated with overall survival (OS) using univariate Cox proportional hazard regression models and multivariable Cox regression models with leave-one-out cross validation. Predictive markers were identified using a treatment by marker interaction term in the Cox model. Results Baseline plasma was available from 328 patients. Univariate prognostic markers for OS were identified including: Ang2, CRP, ICAM-1, IGFBP-1, TSP-2 (all P < 0.001). These prognostic factors were found to be highly significant, even after adjustment for known clinical factors. Additional modeling approaches yielded prognostic signatures from multivariable Cox regression. The gemcitabine/bevacizumab signature consisted of IGFBP-1, interleukin-6, PDGF-AA, PDGF-BB, TSP-2; whereas the gemcitabine/ placebo signature consisted of CRP, IGFBP-1, PAI-1, PDGF-AA, P-selectin (both P < 0.0001). Finally, three potential predictive markers of bevacizumab efficacy were identified: VEGF-D (P <0.01), SDF1 (P <0.05), and Ang2 (P < 0.05). Conclusion This study identified strong prognostic markers for pancreatic cancer patients. Predictive marker analysis indicated that plasma levels of VEGF-D, Ang2, and SDF1 significantly predicted for benefit or lack of benefit from bevacizumab in this population. PMID:24097873

  15. 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

  16. Prediction of Geomagnetic Activity and Key Parameters in High-Latitude Ionosphere-Basic Elements

    NASA Technical Reports Server (NTRS)

    Lyatsky, W.; Khazanov, G. V.

    2007-01-01

    Prediction of geomagnetic activity and related events in the Earth's magnetosphere and ionosphere is an important task of the Space Weather program. Prediction reliability is dependent on the prediction method and elements included in the prediction scheme. Two main elements are a suitable geomagnetic activity index and coupling function -- the combination of solar wind parameters providing the best correlation between upstream solar wind data and geomagnetic activity. The appropriate choice of these two elements is imperative for any reliable prediction model. The purpose of this work was to elaborate on these two elements -- the appropriate geomagnetic activity index and the coupling function -- and investigate the opportunity to improve the reliability of the prediction of geomagnetic activity and other events in the Earth's magnetosphere. The new polar magnetic index of geomagnetic activity and the new version of the coupling function lead to a significant increase in the reliability of predicting the geomagnetic activity and some key parameters, such as cross-polar cap voltage and total Joule heating in high-latitude ionosphere, which play a very important role in the development of geomagnetic and other activity in the Earth s magnetosphere, and are widely used as key input parameters in modeling magnetospheric, ionospheric, and thermospheric processes.

  17. 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

  18. A computational framework to advance hydrometeorological prediction capabilities in cold regions

    NASA Astrophysics Data System (ADS)

    Clark, M. P.; Kavetski, D.; Slater, A. G.; Lundquist, J. D.; Wood, A. W.; Gochis, D. J.; Gutmann, E. D.; Rasmussen, R.

    2012-12-01

    Many different modeling groups recognize the need for new computational frameworks for use as both (i) a model development tool to evaluate competing process representations; and (ii) a predictive tool to reliably represent model uncertainty. Here we describe a computational framework to explore different approaches for modeling the hydrology and thermodynamics of snow and partially frozen soils. The framework has two main features: it has a "numerically agile" structural core to support evaluating the impact of different numerical approximations (e.g., vertical discretization, linearizations, etc.), and it has the modularity to support experimenting with different constitutive functions and boundary conditions. The broad flexibility of the framework facilitates constructing multiple equally plausible model realizations - these realizations can be used either as ensembles to represent model uncertainty, or examined in a systematic way to isolate the impact of individual model components on model predictions and hence facilitate a controlled approach to hypothesis testing. Application of the framework in different snow environments emphasizes the impact of (and interactions among) different modeling decisions. The approaches used to parameterize turbulent heat fluxes, parameters controlling the storage of liquid water in the snowpack, and the lower boundary conditions for hydrology were especially important in the case studies examined. More generally, results show that the impacts of differences in model structure are often overwhelmed by uncertainty in a-priori estimates of model parameters, and suggest that careful specification of probability distributions of model parameters can be used to represent model uncertainty.

  19. MicroRNA-31 Emerges as a Predictive Biomarker of Pathological Response and Outcome in Locally Advanced Rectal Cancer.

    PubMed

    Caramés, Cristina; Cristobal, Ion; Moreno, Víctor; Marín, Juan P; González-Alonso, Paula; Torrejón, Blanca; Minguez, Pablo; Leon, Ana; Martín, José I; Hernández, Roberto; Pedregal, Manuel; Martín, María J; Cortés, Delia; García-Olmo, Damian; Fernández, María J; Rojo, Federico; García-Foncillas, Jesús

    2016-01-01

    Neoadjuvant chemoradiotherapy (CRT) followed by total mesorectal excision has emerged as the standard treatment for locally advanced rectal cancer (LARC) patients. However, many cases do not respond to neoadjuvant CRT, suffering unnecessary toxicities and surgery delays. Thus, identification of predictive biomarkers for neoadjuvant CRT is a current clinical need. In the present study, microRNA-31 expression was measured in formalin-fixed paraffin-embedded (FFPE) biopsies from 78 patients diagnosed with LARC who were treated with neoadjuvant CRT. Then, the obtained results were correlated with clinical and pathological characteristics and outcome. High microRNA-31 (miR-31) levels were found overexpressed in 34.2% of cases. Its overexpression significantly predicted poor pathological response (p = 0.018) and worse overall survival (OS) (p = 0.008). The odds ratio for no pathological response among patients with miR-31 overexpression was 0.18 (Confidence Interval = 0.06 to 0.57; p = 0.003). Multivariate analysis corroborated the clinical impact of miR-31 in determining pathological response to neoadjuvant CRT as well as OS. Altogether, miR-31 quantification emerges as a novel valuable clinical tool to predict both pathological response and outcome in LARC patients. PMID:27271609

  20. 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

  1. Predicting Nitrogen Fertilizer Recommendations for Corn using an Active Sensor

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Active sensors, mounted on typical agricultural equipment, can be used to measure N (nitrogen) status in corn (Zea mays L.). This gives a producer the potential to improve N fertilizer recommendations that will reduce nitrate loss to the environment. This study examines the relationship between re...

  2. Worry tendencies predict brain activation during aversive imagery.

    PubMed

    Schienle, Anne; Schäfer, Axel; Pignanelli, Roman; Vaitl, Dieter

    2009-09-25

    Because of its abstract nature, worrying might function as an avoidance response in order to cognitively disengage from fearful imagery. The present functional magnetic resonance imaging study investigated neural correlates of aversive imagery and their association with worry tendencies, as measured by the Penn State Worry Questionnaire (PSWQ). Nineteen healthy women first viewed, and subsequently imagined pictures from two categories, 'threat' and 'happiness'. Worry tendencies were negatively correlated with brain activation in the anterior cingulate cortex, the prefrontal cortex (dorsolateral, dorsomedial, ventrolateral), the parietal cortex and the insula. These negative correlations between PSWQ scores and localized brain activation were specific for aversive imagery. Moreover, activation in the above mentioned regions was positively associated with the experienced vividness of both pleasant and unpleasant mental pictures. As the identified brain regions are involved in emotion regulation, vivid imagery and memory retrieval, a lowered activity in high PSWQ scorers might be associated with cognitive disengagement from aversive imagery as well as insufficient refresh rates of mental pictures. Our preliminary findings encourage future imagery studies on generalized anxiety disorder patients, as one of the main symptoms of this disorder is excessive worrying. PMID:19545612

  3. Spontaneous activity does not predict morphological type in cerebellar interneurons.

    PubMed

    Haar, Shlomi; Givon-Mayo, Ronit; Barmack, Neal H; Yakhnitsa, Vadim; Donchin, Opher

    2015-01-28

    The effort to determine morphological and anatomically defined neuronal characteristics from extracellularly recorded physiological signatures has been attempted with varying success in different brain areas. Recent studies have attempted such classification of cerebellar interneurons (CINs) based on statistical measures of spontaneous activity. Previously, such efforts in different brain areas have used supervised clustering methods based on standard parameterizations of spontaneous interspike interval (ISI) histograms. We worried that this might bias researchers toward positive identification results and decided to take a different approach. We recorded CINs from anesthetized cats. We used unsupervised clustering methods applied to a nonparametric representation of the ISI histograms to identify groups of CINs with similar spontaneous activity and then asked how these groups map onto different cell types. Our approach was a fuzzy C-means clustering algorithm applied to the Kullbach-Leibler distances between ISI histograms. We found that there is, in fact, a natural clustering of the spontaneous activity of CINs into six groups but that there was no relationship between this clustering and the standard morphologically defined cell types. These results proved robust when generalization was tested to completely new datasets, including datasets recorded under different anesthesia conditions and in different laboratories and different species (rats). Our results suggest the importance of an unsupervised approach in categorizing neurons according to their extracellular activity. Indeed, a reexamination of such categorization efforts throughout the brain may be necessary. One important open question is that of functional differences of our six spontaneously defined clusters during actual behavior. PMID:25632121

  4. Baseline brain activity fluctuations predict somatosensory perception in humans

    PubMed Central

    Boly, M.; Balteau, E.; Schnakers, C.; Degueldre, C.; Moonen, G.; Luxen, A.; Phillips, C.; Peigneux, P.; Maquet, P.; Laureys, S.

    2007-01-01

    In perceptual experiments, within-individual fluctuations in perception are observed across multiple presentations of the same stimuli, a phenomenon that remains only partially understood. Here, by means of thulium–yttrium/aluminum–garnet laser and event-related functional MRI, we tested whether variability in perception of identical stimuli relates to differences in prestimulus, baseline brain activity. Results indicate a positive relationship between conscious perception of low-intensity somatosensory stimuli and immediately preceding levels of baseline activity in medial thalamus and the lateral frontoparietal network, respectively, which are thought to relate to vigilance and “external monitoring.” Conversely, there was a negative correlation between subsequent reporting of conscious perception and baseline activity in a set of regions encompassing posterior cingulate/precuneus and temporoparietal cortices, possibly relating to introspection and self-oriented processes. At nociceptive levels of stimulation, pain-intensity ratings positively correlated with baseline fluctuations in anterior cingulate cortex in an area known to be involved in the affective dimension of pain. These results suggest that baseline brain-activity fluctuations may profoundly modify our conscious perception of the external world. PMID:17616583

  5. 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.

  6. Recent advances in squamous non-small cell lung cancer: evidence beyond predictive biomarkers.

    PubMed

    Genova, Carlo; Rijavec, Erika; Grossi, Francesco

    2016-01-01

    Squamous non-small cell lung cancer (NSCLC) has always been characterized by a limited number of therapeutic options and by the lack of actionable biomarkers compared to its non-squamous counterpart. Recent clinical trials have led to the approval of new anti-neoplastic drugs available to both non-squamous and squamous NSCLC, consisting in a vascular-disrupting agent and two immune check-point inhibitors; additionally, a monoclonal antibody targeting the epidermal growth factor receptor (EGFR) is currently under evaluation by the Food and Drug Administration (FDA). While predictive molecular biomarkers have not been identified with consistency and are still highly demanded, these agents proved themselves noteworthy and can be considered a powerful addition to the available treatments for squamous NSCLC. PMID:26567561

  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. Family History Predicts Stress Fracture in Active Female Adolescents

    PubMed Central

    Loud, Keith J.; Micheli, Lyle J.; Bristol, Stephanie; Austin, S. Bryn; Gordon, Catherine M.

    2011-01-01

    OBJECTIVE Increased physical activity and menstrual irregularity have been associated with increased risk for stress fracture among adult women active in athletics. The purposes of this study were to determine whether menstrual irregularity is also a risk factor for stress fracture in active female adolescents and to estimate the quantity of exercise associated with an increased risk for this injury. PATIENTS AND METHODS A case-control study was conducted of 13- to 22-year-old females diagnosed with their first stress fracture, each matched prospectively on age and self-reported ethnicity with 2 controls. Patients with chronic illnesses or use of medications known to affect bone mineral density were excluded, including use of hormonal preparations that could alter menstrual cycles. The primary outcome, stress fracture in any extremity or the spine, was confirmed radiographically. Girls with stress fracture had bone mineral density measured at the lumbar spine by dual-energy x-ray absorptiometry. RESULTS The mean ± SD age of the 168 participants was 15.9 ± 2.1 years; 91.7% were postmenarchal, with a mean age at menarche of 13.1 ± 1.1 years. The prevalence of menstrual irregularity was similar among cases and controls. There was no significant difference in the mean hours per week of total physical activity between girls in this sample with stress fracture (8.2 hours/week) and those without (7.4 hours/week). In multivariate models, case subjects had nearly 3 times the odds of having a family member with osteoporosis or osteopenia. In secondary analyses, participants with stress fracture had a low mean spinal bone mineral density for their age. CONCLUSIONS Among highly active female adolescents, only family history was independently associated with stress fracture. The magnitude of this association suggests that further investigations of inheritable skeletal factors are warranted in this population, along with evaluation of bone mineral density in girls with stress

  9. Predicting Child Physical Activity and Screen Time: Parental Support for Physical Activity and General Parenting Styles

    PubMed Central

    Crain, A. Lauren; Senso, Meghan M.; Levy, Rona L.; Sherwood, Nancy E.

    2014-01-01

    Objective: To examine relationships between parenting styles and practices and child moderate-to-vigorous physical activity (MVPA) and screen time. Methods: Participants were children (6.9 ± 1.8 years) with a body mass index in the 70–95th percentile and their parents (421 dyads). Parent-completed questionnaires assessed parental support for child physical activity (PA), parenting styles and child screen time. Children wore accelerometers to assess MVPA. Results: Parenting style did not predict MVPA, but support for PA did (positive association). The association between support and MVPA, moreover, varied as a function of permissive parenting. For parents high in permissiveness, the association was positive (greater support was related to greater MVPA and therefore protective). For parents low in permissiveness, the association was neutral; support did not matter. Authoritarian and permissive parenting styles were both associated with greater screen time. Conclusions: Parenting practices and styles should be considered jointly, offering implications for tailored interventions. PMID:24812256

  10. Synthesis, antiproliferative activity and molecular properties predictions of galloyl derivatives.

    PubMed

    da Silva, Marciane Maximo; Comin, Marina; Duarte, Thiago Santos; Foglio, Mary Ann; de Carvalho, João Ernesto; do Vieira, Maria Carmo; Formagio, Anelise Samara Nazari

    2015-01-01

    The present study was designed to investigate the in vitro antiproliferative activity against ten human cancer cell lines of a series of galloyl derivatives bearing substituted-1,3,4-oxadiazole and carbohydrazide moieties. The compounds were also assessed in an in silico study of the absorption, distribution, metabolism and excretion (ADME) in the human body using Lipinski's parameters, the topological polar surface area (TPSA) and percentage of absorption (%ABS). In general, the introduction of N'-(substituted)-arylidene galloyl hydrazides 4-8 showed a moderate antitumor activity, while the 2-methylthio- and 2-thioxo-1,3,4-oxadiazol-5-yl derivatives 9 and 10 led to increased inhibition of cancer cell proliferation. The precursor compound methyl gallate 2 and the intermediary galloyl hydrazide 3 showed greater antiproliferative activity with GI50 values < 5.54 µM against all human tumor cell lines tested. A higher inhibition effect against ovarian cancer (OVCAR-3) (GI50 = 0.05-5.98 µM) was also shown, with compounds 2, 3, 9 and 10 with GI50 ≤ 0.89 µM standing out in this respect. The in silico study revealed that the compounds showed good intestinal absorption. PMID:25816079

  11. Low platelet activity predicts 30 days mortality in patients undergoing heart surgery.

    PubMed

    Kuliczkowski, Wiktor; Sliwka, Joanna; Kaczmarski, Jacek; Zysko, Dorota; Zembala, Michal; Steter, Dawid; Zembala, Marian; Gierlotka, Marek; Kim, Moo Hyun; Serebruany, Victor

    2016-03-01

    Despite advanced techniques and improved clinical outcomes, patient survival following coronary artery bypass grafting (CABG) is still a major concern. Therefore, predicting future CABG mortality represents an unmet medical need and should be carefully explored. The objective of this study is to assess whether pre-CABG platelet activity corresponds with 30 days mortality post-CABG. Retrospective analyses of platelet biomarkers and death at 30 days in 478 heart surgery patients withdrawn from aspirin or/and clopidogrel. Platelet activity was assessed prior to CABG for aspirin (ASPI-test) with arachidonic acid and clopidogrel (ADP-test) utilizing Multiplate impedance aggregometer. Most patients (n = 198) underwent conventional CABG, off-pump (n = 162), minimally invasive (n = 30), artificial valve implantation (n = 48) or valves in combination with CABG (n = 40). There were 22 deaths at 30 days, including 10 in-hospital fatalities. With the cut-off value set below 407 area under curve (AUC) for the ASPI-test, the 30-day mortality was 5.90% for the lower cohort and 2.66% for patients with significantly higher platelet reactivity (P = 0.038). For the ADP-test with a cut-off at 400AUC, the 30-day mortality was 9.68% for the lower cohort and 3.66% for patients with higher platelet reactivity, representing a borderline significant difference (P = 0.046). Aside from the platelet indices, patients who received red blood cell (RBC) concentrate had a highly significant (P < 0.0001) risk of death at 30 days. Both aspirin and clopidogrel tests were useful in predicting 30 days mortality following heart surgery, suggesting the danger of diminished platelet activity prior to CABG in such high-risk patients. These preliminary evidence supports early discontinuation of antiplatelet therapy for elective CABG and requires adequately powered randomized trials to test the hypothesis and potentially improve survival. PMID:26366827

  12. TH-A-9A-01: Active Optical Flow Model: Predicting Voxel-Level Dose Prediction in Spine SBRT

    SciTech Connect

    Liu, J; Wu, Q.J.; Yin, F; Kirkpatrick, J; Cabrera, A; Ge, Y

    2014-06-15

    Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH/NCI under grant

  13. Godunov-Based Model of Swash Zone Dynamics to Advance Coastal Flood Prediction

    NASA Astrophysics Data System (ADS)

    Shakeri Majd, M.; Sanders, B. F.

    2012-12-01

    Urbanized lowlands in southern California are defended against coastal flooding by sandy beaches that dynamically adjust to changes in water level and wave conditions, particularly during storm events. Recent research has shown that coastal flood impacts are scaled by the volume of beach overtopping flows, and an improved characterization of dynamic overtopping rates is needed to improve coastal flood forecasting (Gallien et al. 2012). However, uncertainty in the beach slope and height makes it difficult to predict the onset of overtopping and the magnitude of resulting flooding. That is, beaches may evolve significantly over a storm event. Sallenger (Sallenger, 2000) describes Impact Levels to distinguish different impact regimes (swash, collision, overwash and inundation) on dunes and barrier islands. Our goal is to model processes in different regimes as was described by him. Godunov-based models adopt a depth-integrated, two-phase approach and the shallow-water hypothesis to resolve flow and sediment transport in a tightly coupled manner that resolves shocks in the air/fluid and fluid/sediment interface. These models are best known in the context of debris flow modeling where the ability to predict the flow of highly concentrated sediment/fluid mixtures is required. Here, the approach is directed at the swash zone. Existing Godunov-based models are reviewed and shown to have drawbacks relative to wetting and drying and "avalanching"—important processes in the swash zone. This nonphysical erosion can be described as the natural tendency of the schemes to smear out steep bed slopes. To denote and reduce these numerical errors, new numerical methods are presented to address these limitations and the resulting model is applied to a set of laboratory-scale test problems. The shallow-water hypothesis limits the applicability of the model to the swash zone, so it is forced by a time series of water level and cross-shore velocity that accounts for surf zone wave

  14. 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.

  15. 25 CFR 170.615 - Can a tribe receive advance payments for non-construction activities?

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... 25 Indians 1 2012-04-01 2011-04-01 true Can a tribe receive advance payments for non-construction activities? 170.615 Section 170.615 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAND AND WATER INDIAN RESERVATION ROADS PROGRAM Service Delivery for Indian Reservation Roads Contracts...

  16. 25 CFR 170.615 - Can a tribe receive advance payments for non-construction activities?

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... 25 Indians 1 2011-04-01 2011-04-01 false Can a tribe receive advance payments for non-construction activities? 170.615 Section 170.615 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAND AND WATER INDIAN RESERVATION ROADS PROGRAM Service Delivery for Indian Reservation Roads Contracts...

  17. 25 CFR 170.615 - Can a tribe receive advance payments for non-construction activities?

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 25 Indians 1 2010-04-01 2010-04-01 false Can a tribe receive advance payments for non-construction activities? 170.615 Section 170.615 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR LAND AND WATER INDIAN RESERVATION ROADS PROGRAM Service Delivery for Indian Reservation Roads Contracts...

  18. The Transformation of Learning: Advances in Cultural-Historical Activity Theory

    ERIC Educational Resources Information Center

    van Oers, Bert, Ed.; Wardekker, Wim, Ed.; Elbers, Ed, Ed.; van der Veer, Rene, Ed.

    2010-01-01

    Learning is a changing phenomenon, depending on the advances in theory and research. This book presents a relatively new approach to learning, based on meaningful human activities in cultural practices and in collaboration with others. It draws extensively from the ideas of Lev Vygotsky and his recent followers. The book presents ideas that…

  19. Welcome to Lotus 1-2-3 Advanced. Learning Activity Packets.

    ERIC Educational Resources Information Center

    Mills, Steven; And Others

    This learning activity packet (LAP) contains five self-paced study lessons that allow students to study advanced concepts of Lotus 1-2-3 at their own pace. The lessons used in the LAP are organized in the following way: lesson name, lesson number, objectives, completion standard, performance standard, required materials, unit test, and exercises.…

  20. Advanced Marketing 8130. Instructional Areas. Duties and Tasks. Learning Activities. Referenced Resources.

    ERIC Educational Resources Information Center

    Virginia State Dept. of Education, Richmond.

    This resource handbook, which is designed for use by instructors of courses in advanced marketing, consists of a duty/task list with referenced resources, a duty/task list with learning activities, and a list of resources. Included in each list are materials dealing with the following topics: communication in marketing, economics in marketing,…

  1. Identifying correlates and determinants of physical activity in youth: How can we advance the field?

    PubMed

    Atkin, Andrew J; van Sluijs, Esther M F; Dollman, James; Taylor, Wendell C; Stanley, Rebecca M

    2016-06-01

    This commentary provides a critical discussion of current research investigating the correlates and determinants of physical activity in young people, with specific focus on conceptual, theoretical and methodological issues. We draw on current child and adolescent literature and our own collective expertise to illustrate our discussion. We conclude with recommendations that will strengthen future research and help to advance the field. PMID:26940254

  2. Planning and Managing Learning Tasks and Activities. Advances in Research on Teaching. Volume 3.

    ERIC Educational Resources Information Center

    Brophy, Jere, Ed.

    This publication is the third volume in the "Advanced in Research on Teaching" series, which has been established to provide state-of-the-art conceptualization and analysis of the processes involved in functioning as a classroom teacher. This volume focuses on the planning and managing of learning tasks and activities, in particular, what is…

  3. Institutional Advancement Activities at Select Hispanic-Serving Institutions: The Politics of Raising Funds

    ERIC Educational Resources Information Center

    Mulnix, Michael William; Bowden, Randall G.; Lopez, Esther Elena

    2004-01-01

    This article analyzes the current state of institutional advancement activities at Hispanic-serving institutions (HSIs) of higher education. Since the 1980s, a core group of colleges and universities in the United States with significant enrollments of Hispanic students has come to be recognized as primary providers of education to the burgeoning…

  4. The Fitness Landscape of HIV-1 Gag: Advanced Modeling Approaches and Validation of Model Predictions by In Vitro Testing

    PubMed Central

    Omarjee, Saleha; Walker, Bruce D.; Chakraborty, Arup; Ndung'u, Thumbi

    2014-01-01

    Viral immune evasion by sequence variation is a major hindrance to HIV-1 vaccine design. To address this challenge, our group has developed a computational model, rooted in physics, that aims to predict the fitness landscape of HIV-1 proteins in order to design vaccine immunogens that lead to impaired viral fitness, thus blocking viable escape routes. Here, we advance the computational models to address previous limitations, and directly test model predictions against in vitro fitness measurements of HIV-1 strains containing multiple Gag mutations. We incorporated regularization into the model fitting procedure to address finite sampling. Further, we developed a model that accounts for the specific identity of mutant amino acids (Potts model), generalizing our previous approach (Ising model) that is unable to distinguish between different mutant amino acids. Gag mutation combinations (17 pairs, 1 triple and 25 single mutations within these) predicted to be either harmful to HIV-1 viability or fitness-neutral were introduced into HIV-1 NL4-3 by site-directed mutagenesis and replication capacities of these mutants were assayed in vitro. The predicted and measured fitness of the corresponding mutants for the original Ising model (r = −0.74, p = 3.6×10−6) are strongly correlated, and this was further strengthened in the regularized Ising model (r = −0.83, p = 3.7×10−12). Performance of the Potts model (r = −0.73, p = 9.7×10−9) was similar to that of the Ising model, indicating that the binary approximation is sufficient for capturing fitness effects of common mutants at sites of low amino acid diversity. However, we show that the Potts model is expected to improve predictive power for more variable proteins. Overall, our results support the ability of the computational models to robustly predict the relative fitness of mutant viral strains, and indicate the potential value of this approach for understanding viral immune evasion

  5. Executive Summary of the 2015 ISCD Position Development Conference on Advanced Measures From DXA and QCT: Fracture Prediction Beyond BMD.

    PubMed

    Shepherd, John A; Schousboe, John T; Broy, Susan B; Engelke, Klaus; Leslie, William D

    2015-01-01

    There have been many scientific advances in fracture risk prediction beyond bone density. The International Society for Clinical Densitometry (ISCD) convened a Position Development Conference (PDC) on the use of dual-energy X-ray absorptiometry beyond measurement of bone mineral density for fracture risk assessment, including trabecular bone score and hip geometry measures. Previously, no guidelines for nonbone mineral density DXA measures existed. Furthermore, there have been advances in the analysis of quantitative computed tomography (QCT) including finite element analysis, QCT of the hip, DXA-equivalent hip measurements, and opportunistic screening that were not included in the previous ISCD positions. The topics and questions for consideration were developed by the ISCD Board of Directors and the Scientific Advisory Committee and were designed to address the needs of clinical practitioners. Three task forces were created and asked to conduct comprehensive literature reviews to address specific questions. The task forces included participants from many countries and a variety of interests including academic institutions and private health care delivery organizations. Representatives from industry participated as consultants to the task forces. Task force reports with proposed position statements were then presented to an international panel of experts with backgrounds in bone densitometry. The PDC was held in Chicago, Illinois, USA, contemporaneously with the Annual Meeting of the ISCD, February 26 through February 28, 2015. This Executive Summary describes the methodology of the 2015 PDC on advanced measures from DXA and QCT and summarizes the approved official positions. Six separate articles in this issue will detail the rationale, discussion, and additional research topics for each question the task forces addressed. PMID:26277847

  6. 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.

  7. Have We Entered a 21st Century Prolonged Minimum of Solar Activity? Updated Implications of a 1987 Prediction

    NASA Astrophysics Data System (ADS)

    Shirley, James H.

    2009-05-01

    Fairbridge and Shirley (1987) predicted that a new prolonged minimum of solar activity would be underway by the year 2013 (Solar Physics 110, 191). While it is much too early to tell if this prediction will be fully realized, recent observations document a striking reduction in the Sun's general level of activity. While other forecasts of reduced future activity levels on decadal time scales have appeared, the Fairbridge-Shirley (FS) prediction is unique in pinpointing the current epoch. We are unaware of any forecast method that shows a better correspondence with the actual behavior of the Sun to this point. The FS prediction was based on the present-day recurrence of two physical indicators that were correlated in time with the occurrence of the Wolf, Sporer, and Maunder Minima. The amplitude of the inertial revolution of the axis of symmetry of the Sun's orbital motion about the solar system barycenter, and the direction in space of that axis, each bear a relationship to the occurrence of the prolonged minima of the historic record. The FS prediction appeared before the importance of solar meridional flows was generally appreciated, and before the existence and role of the tachocline was suspected. We will update and restate some of the physical implications of the FS results, along with those of some more recent investigations, particularly with reference to orbit-spin coupling hypotheses (Shirley, 2006: M.N.R.A.S. 368, 280). New investigations combining and integrating modern dynamo models with physical solutions describing key aspects of the variability of the solar motion may lead to significant advances in our ability to forecast future changes in the Sun. Acknowledgement: This work was supported by the resources of the author. No part of this work was performed at the Jet Propulsion Laboratory under a contract from NASA.

  8. The value of lactate dehydrogenase serum levels as a prognostic and predictive factor for advanced pancreatic cancer patients receiving sorafenib

    PubMed Central

    Faloppi, Luca; Bianconi, Maristella; Giampieri, Riccardo; Sobrero, Alberto; Labianca, Roberto; Ferrari, Daris; Barni, Sandro; Aitini, Enrico; Zaniboni, Alberto; Boni, Corrado; Caprioni, Francesco; Mosconi, Stefania; Fanello, Silvia; Berardi, Rossana; Bittoni, Alessandro; Andrikou, Kalliopi; Cinquini, Michela; Torri, Valter; Scartozzi, Mario; Cascinu, Stefano

    2015-01-01

    Although lactate dehydrogenase (LDH) serum levels, indirect markers of angiogenesis, are associated with a worse outcome in several tumours, their prognostic value is not defined in pancreatic cancer. Moreover, high levels are associated even with a lack of efficacy of tyrosine kinase inhibitors, contributing to explain negative results in clinical trials. We assessed the role of LDH in advanced pancreatic cancer receiving sorafenib. Seventy-one of 114 patients included in the randomised phase II trial MAPS (chemotherapy plus or not sorafenib) and with available serum LDH levels, were included in this analysis. Patients were categorized according to serum LDH levels (LDH ≤vs.> upper normal rate). A significant difference was found in progression free survival (PFS) and in overall survival (OS) between patients with LDH values under or above the cut-off (PFS: 5.2 vs. 2.7 months, p = 0.0287; OS: 10.7 vs. 5.9 months, p = 0.0021). After stratification according to LDH serum levels and sorafenib treatment, patients with low LDH serum levels treated with sorafenib showed an advantage in PFS (p = 0.05) and OS (p = 0.0012). LDH appears to be a reliable parameter to assess the prognosis of advanced pancreatic cancer patients, and it may be a predictive parameter to select patients candidate to receive sorafenib. PMID:26397228

  9. The value of lactate dehydrogenase serum levels as a prognostic and predictive factor for advanced pancreatic cancer patients receiving sorafenib.

    PubMed

    Faloppi, Luca; Bianconi, Maristella; Giampieri, Riccardo; Sobrero, Alberto; Labianca, Roberto; Ferrari, Daris; Barni, Sandro; Aitini, Enrico; Zaniboni, Alberto; Boni, Corrado; Caprioni, Francesco; Mosconi, Stefania; Fanello, Silvia; Berardi, Rossana; Bittoni, Alessandro; Andrikou, Kalliopi; Cinquini, Michela; Torri, Valter; Scartozzi, Mario; Cascinu, Stefano

    2015-10-27

    Although lactate dehydrogenase (LDH) serum levels, indirect markers of angiogenesis, are associated with a worse outcome in several tumours, their prognostic value is not defined in pancreatic cancer. Moreover, high levels are associated even with a lack of efficacy of tyrosine kinase inhibitors, contributing to explain negative results in clinical trials. We assessed the role of LDH in advanced pancreatic cancer receiving sorafenib. Seventy-one of 114 patients included in the randomised phase II trial MAPS (chemotherapy plus or not sorafenib) and with available serum LDH levels, were included in this analysis. Patients were categorized according to serum LDH levels (LDH ≤ vs.> upper normal rate). A significant difference was found in progression free survival (PFS) and in overall survival (OS) between patients with LDH values under or above the cut-off (PFS: 5.2 vs. 2.7 months, p = 0.0287; OS: 10.7 vs. 5.9 months, p = 0.0021). After stratification according to LDH serum levels and sorafenib treatment, patients with low LDH serum levels treated with sorafenib showed an advantage in PFS (p = 0.05) and OS (p = 0.0012). LDH appears to be a reliable parameter to assess the prognosis of advanced pancreatic cancer patients, and it may be a predictive parameter to select patients candidate to receive sorafenib. PMID:26397228

  10. Advanced Control Strategy for Single-Phase Voltage-Source Active Rectifier with Low Harmonic Emission

    NASA Astrophysics Data System (ADS)

    Blahník, Vojtĕch; Peroutka, Zdenĕk; Talla, Jakub

    2014-03-01

    This paper introduces the advanced control of single-phase voltage-source active rectifier. This control provide direct control of trolley-wire current and active damping of low-frequency disturbances at the converter ac side. Our proposed control strategy combines PR controller with feed-forward model and low-frequency harmonic compensator based on resonant controllers. Achieved experimental results show excellent converter behavior, where converter is fed by strongly distorted supply voltage.

  11. Predicting activities without computing descriptors: graph machines for QSAR.

    PubMed

    Goulon, A; Picot, T; Duprat, A; Dreyfus, G

    2007-01-01

    We describe graph machines, an alternative approach to traditional machine-learning-based QSAR, which circumvents the problem of designing, computing and selecting molecular descriptors. In that approach, which is similar in spirit to recursive networks, molecules are considered as structured data, represented as graphs. For each example of the data set, a mathematical function (graph machine) is built, whose structure reflects the structure of the molecule under consideration; it is the combination of identical parameterised functions, called "node functions" (e.g. a feedforward neural network). The parameters of the node functions, shared both within and across the graph machines, are adjusted during training with the "shared weights" technique. Model selection is then performed by traditional cross-validation. Therefore, the designer's main task consists in finding the optimal complexity for the node function. The efficiency of this new approach has been demonstrated in many QSAR or QSPR tasks, as well as in modelling the activities of complex chemicals (e.g. the toxicity of a family of phenols or the anti-HIV activities of HEPT derivatives). It generally outperforms traditional techniques without requiring the selection and computation of descriptors. PMID:17365965

  12. 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.

  13. Performance on indirect measures of race evaluation predicts amygdala activation.

    PubMed

    Phelps, E A; O'Connor, K J; Cunningham, W A; Funayama, E S; Gatenby, J C; Gore, J C; Banaji, M R

    2000-09-01

    We used fMRI to explore the neural substrates involved in the unconscious evaluation of Black and White social groups. Specifically, we focused on the amygdala, a subcortical structure known to play a role in emotional learning and evaluation. In Experiment 1, White American subjects observed faces of unfamiliar Black and White males. The strength of amygdala activation to Black-versus-White faces was correlated with two indirect (unconscious) measures of race evaluation (Implicit Association Test [IAT] and potentiated startle), but not with the direct (conscious) expression of race attitudes. In Experiment 2, these patterns were not obtained when the stimulus faces belonged to familiar and positively regarded Black and White individuals. Together, these results suggest that amygdala and behavioral responses to Black-versus-White faces in White subjects reflect cultural evaluations of social groups modified by individual experience. PMID:11054916

  14. Predicting earthquakes by analyzing accelerating precursory seismic activity

    USGS Publications Warehouse

    Varnes, D.J.

    1989-01-01

    During 11 sequences of earthquakes that in retrospect can be classed as foreshocks, the accelerating rate at which seismic moment is released follows, at least in part, a simple equation. This equation (1) is {Mathematical expression},where {Mathematical expression} is the cumulative sum until time, t, of the square roots of seismic moments of individual foreshocks computed from reported magnitudes;C and n are constants; and tfis a limiting time at which the rate of seismic moment accumulation becomes infinite. The possible time of a major foreshock or main shock, tf,is found by the best fit of equation (1), or its integral, to step-like plots of {Mathematical expression} versus time using successive estimates of tfin linearized regressions until the maximum coefficient of determination, r2,is obtained. Analyzed examples include sequences preceding earthquakes at Cremasta, Greece, 2/5/66; Haicheng, China 2/4/75; Oaxaca, Mexico, 11/29/78; Petatlan, Mexico, 3/14/79; and Central Chile, 3/3/85. In 29 estimates of main-shock time, made as the sequences developed, the errors in 20 were less than one-half and in 9 less than one tenth the time remaining between the time of the last data used and the main shock. Some precursory sequences, or parts of them, yield no solution. Two sequences appear to include in their first parts the aftershocks of a previous event; plots using the integral of equation (1) show that the sequences are easily separable into aftershock and foreshock segments. Synthetic seismic sequences of shocks at equal time intervals were constructed to follow equation (1), using four values of n. In each series the resulting distributions of magnitudes closely follow the linear Gutenberg-Richter relation log N=a-bM, and the product n times b for each series is the same constant. In various forms and for decades, equation (1) has been used successfully to predict failure times of stressed metals and ceramics, landslides in soil and rock slopes, and volcanic

  15. A Case Study on Using Prediction Markets as a Rich Environment for Active Learning

    ERIC Educational Resources Information Center

    Buckley, Patrick; Garvey, John; McGrath, Fergal

    2011-01-01

    In this paper, prediction markets are presented as an innovative pedagogical tool which can be used to create a Rich Environment for Active Learning (REAL). Prediction markets are designed to make forecasts about specific future events by using a market mechanism to aggregate the information held by a large group of traders about that event into a…

  16. Using Social Cognitive Theory to Predict Physical Activity and Fitness in Underserved Middle School Children

    ERIC Educational Resources Information Center

    Martin, Jeffrey J.; McCaughtry, Nate; Flory, Sara; Murphy, Anne; Wisdom, Kimberlydawn

    2011-01-01

    Few researchers have used social cognitive theory and environment-based constructs to predict physical activity (PA) and fitness in underserved middle-school children. Hence, we evaluated social cognitive variables and perceptions of the school environment to predict PA and fitness in middle school children (N = 506, ages 10-14 years). Using…

  17. Resting amygdala and medial prefrontal metabolism predicts functional activation of the fear extinction circuit

    PubMed Central

    Linnman, Clas; Zeidan, Mohamed A.; Furtak, Sharon C.; Pitman, Roger K.; Quirk, Gregory J.; Milad, Mohammed R.

    2014-01-01

    Objective Individual differences in ability to control fear have been linked to activation of dorsal anterior cingulate cortex, ventromedial prefrontal cortex, and amygdala. This study investigated whether functional variance in this network can be predicted by resting metabolism in these same regions. Methods Healthy subject volunteers were studied with positron emission tomography using [18F]-deoxyglucose to measure resting brain metabolism. This was followed by a two-day fear conditioning and extinction training paradigm in a functional magnetic resonance imaging scanner to measure brain activation during fear extinction and its recall. Skin conductance response was used to index conditioned responding. Resting metabolism in amygdala, dorsal anterior cingulate cortex and ventromedial prefrontal cortex were used to predict responses during fear extinction and extinction recall. Results During extinction training, resting amygdala metabolism positively predicted ventromedial prefrontal cortex, and negatively predicted dorsal anterior cingulate cortex, activation. In contrast, during extinction recall, resting amygdala metabolism negatively predicted ventromedial prefrontal cortex, and positively predicted dorsal anterior cingulate cortex, activation. Resting dorsal anterior cingulate cortex metabolism predicted fear expression (skin conductance response) during extinction recall. Conclusions Brain metabolism at rest predicts neuronal reactivity and skin conductance changes associated with recall of the fear extinction memory. PMID:22318762

  18. Identification of a DNA methylation signature to predict disease-free survival in locally advanced rectal cancer

    PubMed Central

    Claus, Rainer; Weichenhan, Dieter; Jung, Klaus; Kitz, Julia; Grade, Marian; Wolff, Hendrik A.; Jo, Peter; Doyen, Jérôme; Gérard, Jean-Pierre; Johnsen, Steven A.; Plass, Christoph; Beißbarth, Tim; Ghadimi, Michael

    2014-01-01

    In locally advanced rectal cancer a preoperative predictive biomarker is necessary to adjust treatment specifically for those patients expected to suffer relapse. We applied whole genome methylation CpG island array analyses to an initial set of patients (n=11) to identify differentially methylated regions (DMRs) that separate a good from a bad prognosis group. Using a quantitative high-resolution approach, candidate DMRs were first validated in a set of 61 patients (test set) and then confirmed DMRs were further validated in additional independent patient cohorts (n=71, n=42). We identified twenty highly discriminative DMRs and validated them in the test set using the MassARRAY technique. Ten DMRs could be confirmed which allowed separation into prognosis groups (p=0.0207, HR=4.09). The classifier was validated in two additional cohorts (n=71, p=0.0345, HR=3.57 and n=42, p=0.0113, HR=3.78). Interestingly, six of the ten DMRs represented regions close to the transcriptional start sites of genes which are also marked by the Polycomb Repressor Complex component EZH2. In conclusion we present a classifier comprising 10 DMRs which predicts patient prognosis with a high degree of accuracy. These data may now help to discriminate between patients that may respond better to standard treatments from those that may require alternative modalities. PMID:25261372

  19. PREDICTION OF SELECTIVITY FOR ACTIVATED CARBON ADSORPTION OF TRACE ORGANIC (HOMOLOGUE) CONTAMINANTS

    EPA Science Inventory

    Preferential adsorption of organic compounds onto activated carbon from dilute aqueous solutions was studied to develop a comprehensive theoretical basis for predicting adsorption of multicomponent solutes. The authors investigated in this research program a comparison of differe...

  20. PREDICTING TOXICOLOGICAL ENDPOINTS OF CHEMICALS USING QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS (QSARS)

    EPA Science Inventory

    Quantitative structure-activity relationships (QSARs) are being developed to predict the toxicological endpoints for untested chemicals similar in structure to chemicals that have known experimental toxicological data. Based on a very large number of predetermined descriptors, a...

  1. Phase advancement and nucleus-specific timing of thalamocortical activity during slow cortical oscillation

    PubMed Central

    Slézia, Andrea; Hangya, Balázs; Ulbert, István; Acsády, László

    2011-01-01

    The exact timing of cortical afferent activity is instrumental for the correct coding and retrieval of internal and external stimuli. Thalamocortical inputs represent the most significant subcortical pathway to the cortex, but the precise timing and temporal variability of thalamocortical activity is not known. To examine this question, we studied the phase of thalamic action potentials relative to cortical oscillations and established correlations among phase, the nuclear location of the thalamocortical neurons and the frequency of cortical activity. The phase of thalamic action potentials depended on the exact frequency of the slow cortical oscillation both on long (minutes) and short (single wave) time scales. Faster waves were accompanied by phase advancement in both cases. Thalamocortical neurons located in different nuclei fired at significantly different phases of the slow waves but were active at similar phase of spindle oscillations. Different thalamic nuclei displayed distinct burst patterns. Bursts with higher number of action potentials displayed progressive phase advancement in a nucleus-specific manner. Thalamic neurons located along nuclear borders were characterized by mixed burst and phase properties. Our data demonstrate that the temporal relationship between cortical and thalamic activity is not fixed but displays dynamic changes during oscillatory activity. The timing depends on the precise location and exact activity of thalamocortical cells and the ongoing cortical network pattern. This variability of thalamic output and its coupling to cortical activity can enable thalamocortical neurons to actively participate in the coding and retrieval of complex cortical signals. PMID:21228169

  2. Researches on the Nankai trough mega thrust earthquake seismogenic zones using real time observing systems for advanced early warning systems and predictions

    NASA Astrophysics Data System (ADS)

    Kaneda, Yoshiyuki

    2015-04-01

    We recognized the importance of real time monitoring on Earthquakes and Tsunamis Based on lessons learned from 2004 Sumatra Earthquake/Tsunamis and 2011 East Japan Earthquake. We deployed DONET1 and are developing DONET2 as real time monitoring systems which are dense ocean floor networks around the Nankai trough seismogenic zone Southwestern Japan. Total observatories of DONE1 and DONET2 are 51 observatories equipped with multi kinds of sensors such as the accelerometer, broadband seismometer, pressure gauge, difference pressure gauge, hydrophone and thermometer in each observatory. These systems are indispensable for not only early warning of Earthquakes/ Tsunamis, but also researches on broadband crustal activities around the Nankai trough seismogenic zone for predictions. DONET1 detected offshore tsunamis 15 minutes earlier than onshore stations at the 2011 East Japan earthquake/tsunami. Furthermore, DONET1/DONET2 will be expected to monitor slow events such as low frequency tremors and slow earthquakes for the prediction researches. Finally, the integration of observations and simulation researches will contribute to estimate of seismic stage changes from the inter-seismic to pre seismic stage. I will introduce applications of DONET1/DONET2 data and advanced simulation researches.

  3. Asymmetric frontal cortical activity predicts effort expenditure for reward.

    PubMed

    Hughes, David M; Yates, Mark J; Morton, Emma E; Smillie, Luke D

    2015-07-01

    An extensive literature shows that greater left, relative to right, frontal cortical activity (LFA) is involved in approach-motivated affective states and reflects stable individual differences in approach motivation. However, relatively few studies have linked LFA to behavioral indices of approach motivation. In this study, we examine the relation between LFA and effort expenditure for reward, a behavioral index of approach motivation. LFA was calculated for 51 right-handed participants (55% female) using power spectral analysis of electroencephalogram recorded at rest. Participants also completed the effort expenditure for rewards task (EEfRT), which presents a series of trials requiring a choice between a low-reward low-effort task and a high-reward high-effort task. We found that individuals with greater resting LFA were more willing to expend greater effort in the pursuit of larger rewards, particularly when reward delivery was less likely. Our findings offer a more nuanced understanding of the motivational significance of LFA, in terms of processes that mitigate the effort- and uncertainty-related costs of pursuing rewarding goals. PMID:25479792

  4. 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

  5. Physical Activity in Patients With Advanced-Stage Cancer: A Systematic Review of the Literature

    PubMed Central

    Albrecht, Tara A.; Taylor, Ann Gill

    2014-01-01

    The importance of physical activity for chronic disease prevention and management has become generally well accepted. The number of research interventions and publications examining the benefits of physical activity for patients with cancer has been rising steadily. However, much of that research has focused on the impact of physical activity either prior to or early in the cancer diagnosis, treatment, and survivorship process. Research focusing on the effects of physical activity, specifically for patients with advanced-stage cancer and poorer prognostic outcomes, has been addressed only recently. The purpose of this article is to examine the state of the science for physical activity in the advanced-stage disease subset of the cancer population. Exercise in a variety of intensities and forms, including yoga, walking, biking, and swimming, has many health benefits for people, including those diagnosed with cancer. Research has shown that, for people with cancer (including advanced-stage cancer), exercise can decrease anxiety, stress, and depression while improving levels of pain, fatigue, shortness of breath, constipation, and insomnia. People diagnosed with cancer should discuss with their oncologist safe, easy ways they can incorporate exercise into their daily lives. PMID:22641322

  6. Physical activity in patients with advanced-stage cancer: a systematic review of the literature.

    PubMed

    Albrecht, Tara A; Taylor, Ann Gill

    2012-06-01

    The importance of physical activity for chronic disease prevention and management has become generally well accepted. The number of research interventions and publications examining the benefits of physical activity for patients with cancer has been rising steadily. However, much of that research has focused on the impact of physical activity either prior to or early in the cancer diagnosis, treatment, and survivorship process. Research focusing on the effects of physical activity, specifically for patients with advanced-stage cancer and poorer prognostic outcomes, has been addressed only recently. The purpose of this article is to examine the state of the science for physical activity in the advanced-stage disease subset of the cancer population. Exercise in a variety of intensities and forms, including yoga, walking, biking, and swimming, has many health benefits for people, including those diagnosed with cancer. Research has shown that, for people with cancer (including advanced-stage cancer), exercise can decrease anxiety, stress, and depression while improving levels of pain, fatigue, shortness of breath, constipation, and insomnia. People diagnosed with cancer should discuss with their oncologist safe, easy ways they can incorporate exercise into their daily lives. PMID:22641322

  7. 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.

  8. Weighted quantification of ¹⁸F-FDG tumor metabolism activity using fuzzy-thresholding to predict post-treatment tumor recurrence.

    PubMed

    Roman-Jimenez, Geoffrey; Acosta, Oscar; Leseur, Julie; Devillers, Anne; Le Gouestre, Jonathan; Ospina, Juan-David; Simon, Antoine; Terve, Pierre; De Crevoisier, Renaud

    2015-08-01

    Cervical cancer is one of the most common cancer to affect women worldwide. Despite the efficiency of radiotherapy treatment, some patients present post-treatment tumor recurrence which increases the risk of death. Early outcome prediction could help oncologists to adapt the treatment. Several studies suggest that quantification of tumor activity using (18)FFDG PET imaging could be used to predict post-treatment tumor recurrence. In this paper we study the predictive value of weighted quantification of tumor metabolism extracted by fuzzy-thresholding for tumor recurrence of locally advanced cervical cancer. Fifty-three patients with locally advanced cervical cancer treated by chemo-radiotherapy were considered in our study. For each patient, a coregistered (18)F-FDG PET/CT scan was acquired before the treatment and was segmented using different hard and fuzzy segmentations methods. The tumor activity was extracted through the total lesion glycolysis and through a weighted analog of the total lesion glycolysis using the probability maps provided by the fuzzy segmentations. Outcomes prediction was performed using the area under the receiver operating characteristic curve (AUC) and the Harrell's C-index. Results suggest that weighted quantification of tumor activity seems to be strongly informative and could be used to predict post-treatment tumor recurrence in cervical cancer. PMID:26736737

  9. Beta- and gamma-band activity reflect predictive coding in the processing of causal events.

    PubMed

    van Pelt, Stan; Heil, Lieke; Kwisthout, Johan; Ondobaka, Sasha; van Rooij, Iris; Bekkering, Harold

    2016-06-01

    In daily life, complex events are perceived in a causal manner, suggesting that the brain relies on predictive processes to model them. Within predictive coding theory, oscillatory beta-band activity has been linked to top-down predictive signals and gamma-band activity to bottom-up prediction errors. However, neurocognitive evidence for predictive coding outside lower-level sensory areas is scarce. We used magnetoencephalography to investigate neural activity during probability-dependent action perception in three areas pivotal for causal inference, superior temporal sulcus, temporoparietal junction and medial prefrontal cortex, using bowling action animations. Within this network, Granger-causal connectivity in the beta-band was found to be strongest for backward top-down connections and gamma for feed-forward bottom-up connections. Moreover, beta-band power in TPJ increased parametrically with the predictability of the action kinematics-outcome sequences. Conversely, gamma-band power in TPJ and MPFC increased with prediction error. These findings suggest that the brain utilizes predictive-coding-like computations for higher-order cognition such as perception of causal events. PMID:26873806

  10. Anti-glycated activity prediction of polysaccharides from two guava fruits using artificial neural networks.

    PubMed

    Yan, Chunyan; Lee, Jinsheng; Kong, Fansheng; Zhang, Dezhi

    2013-10-15

    High-efficiency ultrasonic treatment was used to extract the polysaccharides of Psidium guajava (PPG) and Psidium littorale (PPL). The aims of this study were to compare polysaccharide activities from these two guavas, as well as to investigate the relationship between ultrasonic conditions and anti-glycated activity. A mathematical model of anti-glycated activity was constructed with the artificial neural network (ANN) toolbox of MATLAB software. Response surface plots showed the correlation between ultrasonic conditions and bioactivity. The optimal ultrasonic conditions of PPL for the highest anti-glycated activity were predicted to be 256 W, 60 °C, and 12 min, and the predicted activity was 42.2%. The predicted highest anti-glycated activity of PPG was 27.2% under its optimal predicted ultrasonic condition. The experimental result showed that PPG and PPL possessed anti-glycated and antioxidant activities, and those of PPL were greater. The experimental data also indicated that ANN had good prediction and optimization capability. PMID:23987324

  11. Individual differences in activation of the parental care motivational system: assessment, prediction, and implications.

    PubMed

    Buckels, Erin E; Beall, Alec T; Hofer, Marlise K; Lin, Eden Y; Zhou, Zenan; Schaller, Mark

    2015-03-01

    We report on the development, validation, and utility of a measure assessing individual differences in activation of the parental care motivational system: The Parental Care and Tenderness (PCAT) questionnaire. Results from 1,608 adults (including parents and nonparents) show that the 25-item PCAT measure has high internal consistency, high test-retest reliability, high construct validity, and unique predictive utility. Among parents, it predicted self-child identity overlap and caring child-rearing attitudes; among nonparents, it predicted desire to have children. PCAT scores predicted the intensity of tender emotions aroused by infants, and also predicted the amount of time individuals chose look at infant (but not adult) faces. PCAT scores uniquely predicted additional outcomes in the realm of social perception, including mate preferences, moral judgments, and trait inferences about baby-faced adults. Practical and conceptual implications are discussed. PMID:25559194

  12. A unified framework for activity recognition-based behavior analysis and action prediction in smart homes.

    PubMed

    Fatima, Iram; Fahim, Muhammad; Lee, Young-Koo; Lee, Sungyoung

    2013-01-01

    In recent years, activity recognition in smart homes is an active research area due to its applicability in many applications, such as assistive living and healthcare. Besides activity recognition, the information collected from smart homes has great potential for other application domains like lifestyle analysis, security and surveillance, and interaction monitoring. Therefore, discovery of users common behaviors and prediction of future actions from past behaviors become an important step towards allowing an environment to provide personalized service. In this paper, we develop a unified framework for activity recognition-based behavior analysis and action prediction. For this purpose, first we propose kernel fusion method for accurate activity recognition and then identify the significant sequential behaviors of inhabitants from recognized activities of their daily routines. Moreover, behaviors patterns are further utilized to predict the future actions from past activities. To evaluate the proposed framework, we performed experiments on two real datasets. The results show a remarkable improvement of 13.82% in the accuracy on average of recognized activities along with the extraction of significant behavioral patterns and precise activity predictions with 6.76% increase in F-measure. All this collectively help in understanding the users" actions to gain knowledge about their habits and preferences. PMID:23435057

  13. A Unified Framework for Activity Recognition-Based Behavior Analysis and Action Prediction in Smart Homes

    PubMed Central

    Fatima, Iram; Fahim, Muhammad; Lee, Young-Koo; Lee, Sungyoung

    2013-01-01

    In recent years, activity recognition in smart homes is an active research area due to its applicability in many applications, such as assistive living and healthcare. Besides activity recognition, the information collected from smart homes has great potential for other application domains like lifestyle analysis, security and surveillance, and interaction monitoring. Therefore, discovery of users common behaviors and prediction of future actions from past behaviors become an important step towards allowing an environment to provide personalized service. In this paper, we develop a unified framework for activity recognition-based behavior analysis and action prediction. For this purpose, first we propose kernel fusion method for accurate activity recognition and then identify the significant sequential behaviors of inhabitants from recognized activities of their daily routines. Moreover, behaviors patterns are further utilized to predict the future actions from past activities. To evaluate the proposed framework, we performed experiments on two real datasets. The results show a remarkable improvement of 13.82% in the accuracy on average of recognized activities along with the extraction of significant behavioral patterns and precise activity predictions with 6.76% increase in F-measure. All this collectively help in understanding the users” actions to gain knowledge about their habits and preferences. PMID:23435057

  14. The use of early summer mosquito surveillance to predict late summer West Nile virus activity

    USGS Publications Warehouse

    Ginsberg, Howard S.; Rochlin, Ilia; Campbell, Scott R.

    2010-01-01

    Utility of early-season mosquito surveillance to predict West Nile virus activity in late summer was assessed in Suffolk County, NY. Dry ice-baited CDC miniature light traps paired with gravid traps were set weekly. Maximum-likelihood estimates of WNV positivity, minimum infection rates, and % positive pools were generally well correlated. However, positivity in gravid traps was not correlated with positivity in CDC light traps. The best early-season predictors of WNV activity in late summer (estimated using maximum-likelihood estimates of Culex positivity in August and September) were early date of first positive pool, low numbers of mosquitoes in July, and low numbers of mosquito species in July. These results suggest that early-season entomological samples can be used to predict WNV activity later in the summer, when most human cases are acquired. Additional research is needed to establish which surveillance variables are most predictive and to characterize the reliability of the predictions.

  15. Advance cueing produces enhanced action-boundary patterns of spike activity in the sensorimotor striatum.

    PubMed

    Barnes, Terra D; Mao, Jian-Bin; Hu, Dan; Kubota, Yasuo; Dreyer, Anna A; Stamoulis, Catherine; Brown, Emery N; Graybiel, Ann M

    2011-04-01

    One of the most characteristic features of habitual behaviors is that they can be evoked by a single cue. In the experiments reported here, we tested for the effects of such advance cueing on the firing patterns of striatal neurons in the sensorimotor striatum. Rats ran in a T-maze with instruction cues about the location of reward given at the start of the runs. This advance cueing about reward produced a highly augmented task-bracketing pattern of activity at the beginning and end of procedural task performance relative to the patterns found previously with midtask cueing. Remarkably, the largest increase in activity early during the T-maze runs was not associated with the instruction cues themselves, the earliest predictors of reward; instead, the highest peak of early activity was associated with the beginning of the motor period of the task. We suggest that the advance cueing, reducing midrun demands for decision making but adding a working-memory load, facilitated chunking of the maze runs as executable scripts anchored to sensorimotor aspects of the task and unencumbered by midtask decision-making demands. Our findings suggest that the acquisition of stronger task-bracketing patterns of striatal activity in the sensorimotor striatum could reflect this enhancement of behavioral chunking. Deficits in such representations of learned sequential behaviors could contribute to motor and cognitive problems in a range of neurological disorders affecting the basal ganglia, including Parkinson's disease. PMID:21307317

  16. Advance cueing produces enhanced action-boundary patterns of spike activity in the sensorimotor striatum

    PubMed Central

    Barnes, Terra D.; Mao, Jian-Bin; Hu, Dan; Kubota, Yasuo; Dreyer, Anna A.; Stamoulis, Catherine; Brown, Emery N.

    2011-01-01

    One of the most characteristic features of habitual behaviors is that they can be evoked by a single cue. In the experiments reported here, we tested for the effects of such advance cueing on the firing patterns of striatal neurons in the sensorimotor striatum. Rats ran in a T-maze with instruction cues about the location of reward given at the start of the runs. This advance cueing about reward produced a highly augmented task-bracketing pattern of activity at the beginning and end of procedural task performance relative to the patterns found previously with midtask cueing. Remarkably, the largest increase in activity early during the T-maze runs was not associated with the instruction cues themselves, the earliest predictors of reward; instead, the highest peak of early activity was associated with the beginning of the motor period of the task. We suggest that the advance cueing, reducing midrun demands for decision making but adding a working-memory load, facilitated chunking of the maze runs as executable scripts anchored to sensorimotor aspects of the task and unencumbered by midtask decision-making demands. Our findings suggest that the acquisition of stronger task-bracketing patterns of striatal activity in the sensorimotor striatum could reflect this enhancement of behavioral chunking. Deficits in such representations of learned sequential behaviors could contribute to motor and cognitive problems in a range of neurological disorders affecting the basal ganglia, including Parkinson's disease. PMID:21307317

  17. Advanced fire-resistant forms of activated carbon and methods of adsorbing and separating gases using same

    DOEpatents

    Xiong, Yongliang; Wang, Yifeng

    2016-04-19

    A method of removing a target gas from a gas stream is disclosed. The method uses advanced, fire-resistant activated carbon compositions having vastly improved fire resistance. Methods for synthesizing the compositions are also provided. The advanced compositions have high gas adsorption capacities and rapid adsorption kinetics (comparable to commercially-available activated carbon), without having any intrinsic fire hazard.

  18. Prognostic and Predictive Value of Baseline and Posttreatment Molecular Marker Expression in Locally Advanced Rectal Cancer Treated With Neoadjuvant Chemoradiotherapy

    SciTech Connect

    Bertolini, Federica . E-mail: bertolini.federica@policlinico.mo.it; Bengala, Carmelo; Losi, Luisa; Pagano, Maria; Iachetta, Francesco; Dealis, Cristina; Jovic, Gordana; Depenni, Roberta; Zironi, Sandra; Falchi, Anna Maria; Luppi, Gabriele; Conte, Pier Franco

    2007-08-01

    Purpose: To evaluate expression of a panel of molecular markers, including p53, p21, MLH1, MSH2, MIB-1, thymidylate synthase, epidermal growth factor receptor (EGFR), and tissue vascular endothelial growth factor (VEGF), before and after treatment in patients treated with neoadjuvant chemoradiotherapy for locally advanced rectal cancer, to correlate the constitutive profile and dynamics of expression with pathologic response and outcome. Methods and Materials: Expression of biomarkers was evaluated by immunohistochemistry in tumor samples from 91 patients with clinical Stage II and III rectal cancer treated with preoperative pelvic radiotherapy (50 Gy) plus concurrent 5-fluorouracil by continuous intravenous infusion. Results: A pathologic complete remission was observed in 14 patients (15.4%). Patients with MLH1-positive tumors had a higher pathologic complete response rate (24.3% vs. 9.4%; p = 0.055). Low expression of constitutive p21, absence of EGFR expression after chemoradiotherapy, and high Dworak's tumor regression grade (TRG) were significantly associated with improved disease-free survival and overall survival. A high MIB-1 value after chemoradiotherapy was significantly associated with worse overall survival. Multivariate analysis confirmed the prognostic value of constitutive p21 expression as well as EGFR expression and MIB-1 value after chemoradiotherapy among patients not achieving TRG 3-4. Conclusions: In our study, we observed the independent prognostic value of EGFR expression after chemoradiotherapy on disease-free survival. Moreover, our study suggests that a constitutive high p21 expression and a high MIB-1 value after neoadjuvant chemoradiotherapy treatment could predict worse outcome in locally advanced rectal cancer.

  19. Primary Tumor Necrosis Predicts Distant Control in Locally Advanced Soft-Tissue Sarcomas After Preoperative Concurrent Chemoradiotherapy

    SciTech Connect

    MacDermed, Dhara M.; Miller, Luke L.; Peabody, Terrance D.; Simon, Michael A.; Luu, Hue H.; Haydon, Rex C.; Montag, Anthony G.; Undevia, Samir D.

    2010-03-15

    Purpose: Various neoadjuvant approaches have been evaluated for the treatment of locally advanced soft-tissue sarcomas. This retrospective study describes a uniquely modified version of the Eilber regimen developed at the University of Chicago. Methods and Materials: We treated 34 patients (28 Stage III and 6 Stage IV) with locally advanced soft-tissue sarcomas of an extremity between 1995 and 2008. All patients received preoperative therapy including ifosfamide (2.5 g/m2 per day for 5 days) with concurrent radiation (28 Gy in 3.5-Gy daily fractions), sandwiched between various chemotherapy regimens. Postoperatively, 47% received further adjuvant chemotherapy. Results: Most tumors (94%) were Grade 3, and all were T2b, with a median size of 10.3 cm. Wide excision was performed in 29 patients (85%), and 5 required amputation. Of the resected tumor specimens, 50% exhibited high (>=90%) treatment-induced necrosis and 11.8% had a complete pathologic response. Surgical margins were negative in all patients. The 5-year survival rate was 42.3% for all patients and 45.2% for Stage III patients. For limb-preservation patients, the 5-year local control rate was 89.0% and reoperation was required for wound complications in 17.2%. The 5-year freedom-from-distant metastasis rate was 53.4% (Stage IV patients excluded), and freedom from distant metastasis was superior if treatment-induced tumor necrosis was 90% or greater (84.6% vs. 19.9%, p = 0.02). Conclusions: This well-tolerated concurrent chemoradiotherapy approach yields excellent rates of limb preservation and local control. The resulting treatment-induced necrosis rates are predictive of subsequent metastatic risk, and this information may provide an opportunity to guide postoperative systemic therapies.

  20. Advancing hydrometeorological prediction capabilities through standards-based cyberinfrastructure development: The community WRF-Hydro modeling system

    NASA Astrophysics Data System (ADS)

    gochis, David; Parodi, Antonio; Hooper, Rick; Jha, Shantenu; Zaslavsky, Ilya

    2013-04-01

    The need for improved assessments and predictions of many key environmental variables is driving a multitude of model development efforts in the geosciences. The proliferation of weather and climate impacts research is driving a host of new environmental prediction model development efforts as society seeks to understand how climate does and will impact key societal activities and resources and, in turn, how human activities influence climate and the environment. This surge in model development has highlighted the role of model coupling as a fundamental activity itself and, at times, a significant bottleneck in weather and climate impacts research. This talk explores some of the recent activities and progress that has been made in assessing the attributes of various approaches to the coupling of physics-based process models for hydrometeorology. One example modeling system that is emerging from these efforts is the community 'WRF-Hydro' modeling system which is based on the modeling architecture of the Weather Research and Forecasting (WRF). An overview of the structural components of WRF-Hydro will be presented as will results from several recent applications which include the prediction of flash flooding events in the Rocky Mountain Front Range region of the U.S. and along the Ligurian coastline in the northern Mediterranean. Efficient integration of the coupled modeling system with distributed infrastructure for collecting and sharing hydrometeorological observations is one of core themes of the work. Specifically, we aim to demonstrate how data management infrastructures used in the US and Europe, in particular data sharing technologies developed within the CUAHSI Hydrologic Information System and UNIDATA, can interoperate based on international standards for data discovery and exchange, such as standards developed by the Open Geospatial Consortium and adopted by GEOSS. The data system we envision will help manage WRF-Hydro prediction model data flows, enabling

  1. CEA serum level as early predictive marker of outcome during EGFR-TKI therapy in advanced NSCLC patients.

    PubMed

    Facchinetti, Francesco; Aldigeri, Raffaella; Aloe, Rosalia; Bortesi, Beatrice; Ardizzoni, Andrea; Tiseo, Marcello

    2015-08-01

    Considering the role of carcinoembryonic antigen (CEA) serum levels as potential useful predictive marker during chemotherapy treatment, we studied its applicability in advanced non-small cell lung cancer (NSCLC) patients treated with epidermal growth factor receptor (EGFR) tyrosine-kinase inhibitors (TKIs). Our retrospective cohort consists of 79 patients (33 EGFR mutated and 46 EGFR wild type or unknown) affected by advanced NSCLC, for whom CEA serum values at the beginning of TKI therapy and after the first month of treatment were available, regardless of treatment line. Baseline CEA value, percentage of CEA reduction after 1 month, and percentage of patients with ≥20 % CEA decrease after 1 month (CEA response) were correlated with disease control rate (DCR), progression-free (PFS), and overall (OS) survival, according to EGFR mutational status. Median baseline CEA levels were significantly higher in EGFR mutated (40.9 ng/ml; interquartile range (IQR) 8.9-197.6) than in wild-type cases (6.2 ng/ml; IQR 2.8-12.8; p = 0.003). Both percentage reduction in CEA levels (-10.7 vs. +13.4 %) and percentage of cases with CEA response (42 vs. 20 %) were significantly higher in mutated vs. wild-type/unknown patients (p = 0.007 and p = 0.027, respectively). In wild-type/unknown patients, CEA response was significantly correlated with DCR (p = 0.001) and resulted as a significant predictor of PFS both in univariate (p = 0.002) and in multivariate analyses (hazard ratio (HR) 0.27; 95 % confidence interval (CI) 0.11-0.66; p = 0.004); only a trend was found for OS prediction (p = 0.082). In EGFR-mutated group, CEA reduction did not show any correlation either with PFS or OS. CEA response after 1 month of EGFR-TKI therapy could be a useful marker, worthy to further studies, as early predictor of treatment outcome in EGFR wild-type/unknown unselected NSCLC cases for which no molecular predictor is yet available. PMID:25731731

  2. Baseline MELD Score Predicts Hepatic Decompensation during Antiviral Therapy in Patients with Chronic Hepatitis C and Advanced Cirrhosis

    PubMed Central

    Dultz, Georg; Seelhof, Martin; Herrmann, Eva; Welker, Martin-Walter; Friedrich-Rust, Mireen; Teuber, Gerlinde; Kronenberger, Bernd; von Wagner, Michael; Vermehren, Johannes; Sarrazin, Christoph; Zeuzem, Stefan; Hofmann, Wolf Peter

    2013-01-01

    Background and Aims In patients with advanced liver cirrhosis due to chronic hepatitis C virus (HCV) infection antiviral therapy with peginterferon and ribavirin is feasible in selected cases only due to potentially life-threatening side effects. However, predictive factors associated with hepatic decompensation during antiviral therapy are poorly defined. Methods In a retrospective cohort study, 68 patients with HCV-associated liver cirrhosis (mean MELD score 9.18±2.72) were treated with peginterferon and ribavirin. Clinical events indicating hepatic decompensation (onset of ascites, hepatic encephalopathy, upper gastrointestinal bleeding, hospitalization) as well as laboratory data were recorded at baseline and during a follow up period of 72 weeks after initiation of antiviral therapy. To monitor long term sequelae of end stage liver disease an extended follow up for HCC development, transplantation and death was applied (240weeks, ±SD 136weeks). Results Eighteen patients (26.5%) achieved a sustained virologic response. During the observational period a hepatic decompensation was observed in 36.8%. Patients with hepatic decompensation had higher MELD scores (10.84 vs. 8.23, p<0.001) and higher mean bilirubin levels (26.74 vs. 14.63 µmol/l, p<0.001), as well as lower serum albumin levels (38.2 vs. 41.1 g/l, p = 0.015), mean platelets (102.64 vs. 138.95/nl, p = 0.014) and mean leukocytes (4.02 vs. 5.68/nl, p = 0.002) at baseline as compared to those without decompensation. In the multivariate analysis the MELD score remained independently associated with hepatic decompensation (OR 1.56, 1.18–2.07; p = 0.002). When the patients were grouped according to their baseline MELD scores, hepatic decompensation occurred in 22%, 59%, and 83% of patients with MELD scores of 6–9, 10–13, and >14, respectively. Baseline MELD score was significantly associated with the risk for transplantation/death (p<0.001). Conclusions Our data suggest that the

  3. Understanding the impact of deep brain stimulation on ambulatory activity in advanced Parkinson's disease.

    PubMed

    Rochester, Lynn; Chastin, Sebastien Francois Martin; Lord, Sue; Baker, Katherine; Burn, David John

    2012-06-01

    Whilst deep brain stimulation of the subthalamic nucleus (DBS-STN) improves the motor symptoms of Parkinson's disease (PD), its effect on daily activity is unknown. We aimed to quantify changes in ambulatory activity following DBS-STN in advanced PD using novel accelerometry based measures that describe changes to the volume and pattern of walking. Seventeen participants with advanced PD were measured over a 7-day period using an activPAL (™) activity monitor. Data were collected 6 weeks before and 6 months after surgery and included measures that describe the volume and pattern of ambulatory activity (number of steps per day, accumulation, diversity and variability of walking time), alongside standard measures for disease severity, freezing of gait, gait speed, and extended activities of daily living. Activity outcomes were compared pre- and 6 months post-surgery using linear mixed models and correlated with standard outcomes. The results of this study are despite significant improvements in motor symptoms after surgery, the volume of ambulatory activity (total number of steps per day) did not change (P = 0.468). However, significant increases in length and variability of walking bouts emerged, suggesting improvements in diversity and flexibility of walking patterns. Motor severity and extended activities of daily living scores were significantly correlated with walking bout variability but not with volume of walking. Thus, the conclusions are reduction in motor symptom severity after DBS-STN translated into selective improvements in daily activity. Novel measures derived from accelerometry provide a discrete measure of performance and allow closer interpretation of the impact of DBS-STN on real-world activity. PMID:22086738

  4. Prediction of in vitro and in vivo oestrogen receptor activity using hierarchical clustering

    EPA Science Inventory

    In this study, hierarchical clustering classification models were developed to predict in vitro and in vivo oestrogen receptor (ER) activity. Classification models were developed for binding, agonist, and antagonist in vitro ER activity and for mouse in vivo uterotrophic ER bindi...

  5. Predicting Antitumor Activity of Peptides by Consensus of Regression Models Trained on a Small Data Sample

    PubMed Central

    Radman, Andreja; Gredičak, Matija; Kopriva, Ivica; Jerić, Ivanka

    2011-01-01

    Predicting antitumor activity of compounds using regression models trained on a small number of compounds with measured biological activity is an ill-posed inverse problem. Yet, it occurs very often within the academic community. To counteract, up to some extent, overfitting problems caused by a small training data, we propose to use consensus of six regression models for prediction of biological activity of virtual library of compounds. The QSAR descriptors of 22 compounds related to the opioid growth factor (OGF, Tyr-Gly-Gly-Phe-Met) with known antitumor activity were used to train regression models: the feed-forward artificial neural network, the k-nearest neighbor, sparseness constrained linear regression, the linear and nonlinear (with polynomial and Gaussian kernel) support vector machine. Regression models were applied on a virtual library of 429 compounds that resulted in six lists with candidate compounds ranked by predicted antitumor activity. The highly ranked candidate compounds were synthesized, characterized and tested for an antiproliferative activity. Some of prepared peptides showed more pronounced activity compared with the native OGF; however, they were less active than highly ranked compounds selected previously by the radial basis function support vector machine (RBF SVM) regression model. The ill-posedness of the related inverse problem causes unstable behavior of trained regression models on test data. These results point to high complexity of prediction based on the regression models trained on a small data sample. PMID:22272081

  6. Can Gymnastic Teacher Predict Leisure Activity Preference among Children with Developmental Coordination Disorders (DCD)?

    ERIC Educational Resources Information Center

    Engel-Yeger, Batya; Hanna-Kassis, Amany; Rosenblum, Sara

    2012-01-01

    The aims of the study were to analyze: (1) whether significant differences exist between children with typical development and children with developmental coordination disorders (DCD) in their preference to participate in leisure activities (2) whether the teacher estimation of activity form (TEAF) evaluation predicts participation preference.…

  7. Predicting antitumor activity of peptides by consensus of regression models trained on a small data sample.

    PubMed

    Radman, Andreja; Gredičak, Matija; Kopriva, Ivica; Jerić, Ivanka

    2011-01-01

    Predicting antitumor activity of compounds using regression models trained on a small number of compounds with measured biological activity is an ill-posed inverse problem. Yet, it occurs very often within the academic community. To counteract, up to some extent, overfitting problems caused by a small training data, we propose to use consensus of six regression models for prediction of biological activity of virtual library of compounds. The QSAR descriptors of 22 compounds related to the opioid growth factor (OGF, Tyr-Gly-Gly-Phe-Met) with known antitumor activity were used to train regression models: the feed-forward artificial neural network, the k-nearest neighbor, sparseness constrained linear regression, the linear and nonlinear (with polynomial and Gaussian kernel) support vector machine. Regression models were applied on a virtual library of 429 compounds that resulted in six lists with candidate compounds ranked by predicted antitumor activity. The highly ranked candidate compounds were synthesized, characterized and tested for an antiproliferative activity. Some of prepared peptides showed more pronounced activity compared with the native OGF; however, they were less active than highly ranked compounds selected previously by the radial basis function support vector machine (RBF SVM) regression model. The ill-posedness of the related inverse problem causes unstable behavior of trained regression models on test data. These results point to high complexity of prediction based on the regression models trained on a small data sample. PMID:22272081

  8. Office of River Protection Advanced Low-Activity Waste Glass Research and Development Plan

    SciTech Connect

    Kruger, A. A.; Peeler, D. K.; Kim, D. S.; Vienna, J. D.; Piepel, G. F.; Schweiger, M. J.

    2015-11-23

    The U.S. Department of Energy Office of River Protection (ORP) has initiated and leads an integrated Advanced Waste Glass (AWG) program to increase the loading of Hanford tank wastes in glass while meeting melter lifetime expectancies and process, regulatory, and product performance requirements. The integrated ORP program is focused on providing a technical, science-based foundation for making key decisions regarding the successful operation of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) facilities in the context of an optimized River Protection Project (RPP) flowsheet. The fundamental data stemming from this program will support development of advanced glass formulations, key product performance and process control models, and tactical processing strategies to ensure safe and successful operations for both the low-activity waste (LAW) and high-level waste vitrification facilities. These activities will be conducted with the objective of improving the overall RPP mission by enhancing flexibility and reducing cost and schedule.

  9. Constructing realistic engrams: poststimulus activity of hippocampus and dorsal striatum predicts subsequent episodic memory.

    PubMed

    Ben-Yakov, Aya; Dudai, Yadin

    2011-06-15

    Encoding of real-life episodic memory commonly involves integration of information as the episode unfolds. Offline processing immediately following event offset is expected to play a role in encoding the episode into memory. In this study, we examined whether distinct human brain activity time-locked to the offset of short narrative audiovisual episodes could predict subsequent memory for the gist of the episodes. We found that a set of brain regions, most prominently the bilateral hippocampus and the bilateral caudate nucleus, exhibit memory-predictive activity time-locked to the stimulus offset. We propose that offline activity in these regions reflects registration to memory of integrated episodes. PMID:21677186

  10. Cortical delta activity reflects reward prediction error and related behavioral adjustments, but at different times.

    PubMed

    Cavanagh, James F

    2015-04-15

    Recent work has suggested that reward prediction errors elicit a positive voltage deflection in the scalp-recorded electroencephalogram (EEG); an event sometimes termed a reward positivity. However, a strong test of this proposed relationship remains to be defined. Other important questions remain unaddressed: such as the role of the reward positivity in predicting future behavioral adjustments that maximize reward. To answer these questions, a three-armed bandit task was used to investigate the role of positive prediction errors during trial-by-trial exploration and task-set based exploitation. The feedback-locked reward positivity was characterized by delta band activities, and these related EEG features scaled with the degree of a computationally derived positive prediction error. However, these phenomena were also dissociated: the computational model predicted exploitative action selection and related response time speeding whereas the feedback-locked EEG features did not. Compellingly, delta band dynamics time-locked to the subsequent bandit (the P3) successfully predicted these behaviors. These bandit-locked findings included an enhanced parietal to motor cortex delta phase lag that correlated with the degree of response time speeding, suggesting a mechanistic role for delta band activities in motivating action selection. This dissociation in feedback vs. bandit locked EEG signals is interpreted as a differentiation in hierarchically distinct types of prediction error, yielding novel predictions about these dissociable delta band phenomena during reinforcement learning and decision making. PMID:25676913

  11. In Vitro and In Vivo Activities of Antimicrobial Peptides Developed Using an Amino Acid-Based Activity Prediction Method

    PubMed Central

    Wu, Xiaozhe; Wang, Zhenling; Li, Xiaolu; Fan, Yingzi; He, Gu; Wan, Yang; Yu, Chaoheng; Tang, Jianying; Li, Meng; Zhang, Xian; Zhang, Hailong; Xiang, Rong; Pan, Ying; Liu, Yan; Lu, Lian

    2014-01-01

    To design and discover new antimicrobial peptides (AMPs) with high levels of antimicrobial activity, a number of machine-learning methods and prediction methods have been developed. Here, we present a new prediction method that can identify novel AMPs that are highly similar in sequence to known peptides but offer improved antimicrobial activity along with lower host cytotoxicity. Using previously generated AMP amino acid substitution data, we developed an amino acid activity contribution matrix that contained an activity contribution value for each amino acid in each position of the model peptide. A series of AMPs were designed with this method. After evaluating the antimicrobial activities of these novel AMPs against both Gram-positive and Gram-negative bacterial strains, DP7 was chosen for further analysis. Compared to the parent peptide HH2, this novel AMP showed broad-spectrum, improved antimicrobial activity, and in a cytotoxicity assay it showed lower toxicity against human cells. The in vivo antimicrobial activity of DP7 was tested in a Staphylococcus aureus infection murine model. When inoculated and treated via intraperitoneal injection, DP7 reduced the bacterial load in the peritoneal lavage solution. Electron microscope imaging and the results indicated disruption of the S. aureus outer membrane by DP7. Our new prediction method can therefore be employed to identify AMPs possessing minor amino acid differences with improved antimicrobial activities, potentially increasing the therapeutic agents available to combat multidrug-resistant infections. PMID:24982064

  12. Temperature and Material Flow Prediction in Friction-Stir Spot Welding of Advanced High-Strength Steel

    NASA Astrophysics Data System (ADS)

    Miles, M.; Karki, U.; Hovanski, Y.

    2014-10-01

    Friction-stir spot welding (FSSW) has been shown to be capable of joining advanced high-strength steel, with its flexibility in controlling the heat of welding and the resulting microstructure of the joint. This makes FSSW a potential alternative to resistance spot welding if tool life is sufficiently high, and if machine spindle loads are sufficiently low that the process can be implemented on an industrial robot. Robots for spot welding can typically sustain vertical loads of about 8 kN, but FSSW at tool speeds of less than 3000 rpm cause loads that are too high, in the range of 11-14 kN. Therefore, in the current work, tool speeds of 5000 rpm were employed to generate heat more quickly and to reduce welding loads to acceptable levels. Si3N4 tools were used for the welding experiments on 1.2-mm DP 980 steel. The FSSW process was modeled with a finite element approach using the Forge® software. An updated Lagrangian scheme with explicit time integration was employed to predict the flow of the sheet material, subjected to boundary conditions of a rotating tool and a fixed backing plate. Material flow was calculated from a velocity field that is two-dimensional, but heat generated by friction was computed by a novel approach, where the rotational velocity component imparted to the sheet by the tool surface was included in the thermal boundary conditions. An isotropic, viscoplastic Norton-Hoff law was used to compute the material flow stress as a function of strain, strain rate, and temperature. The model predicted welding temperatures to within 4%, and the position of the joint interface to within 10%, of the experimental results.

  13. Temperature and Material Flow Prediction in Friction-Stir Spot Welding of Advanced High-Strength Steel

    NASA Astrophysics Data System (ADS)

    Miles, M.; Karki, U.; Hovanski, Y.

    2014-09-01

    Friction-stir spot welding (FSSW) has been shown to be capable of joining advanced high-strength steel, with its flexibility in controlling the heat of welding and the resulting microstructure of the joint. This makes FSSW a potential alternative to resistance spot welding if tool life is sufficiently high, and if machine spindle loads are sufficiently low that the process can be implemented on an industrial robot. Robots for spot welding can typically sustain vertical loads of about 8 kN, but FSSW at tool speeds of less than 3000 rpm cause loads that are too high, in the range of 11-14 kN. Therefore, in the current work, tool speeds of 5000 rpm were employed to generate heat more quickly and to reduce welding loads to acceptable levels. Si3N4 tools were used for the welding experiments on 1.2-mm DP 980 steel. The FSSW process was modeled with a finite element approach using the Forge® software. An updated Lagrangian scheme with explicit time integration was employed to predict the flow of the sheet material, subjected to boundary conditions of a rotating tool and a fixed backing plate. Material flow was calculated from a velocity field that is two-dimensional, but heat generated by friction was computed by a novel approach, where the rotational velocity component imparted to the sheet by the tool surface was included in the thermal boundary conditions. An isotropic, viscoplastic Norton-Hoff law was used to compute the material flow stress as a function of strain, strain rate, and temperature. The model predicted welding temperatures to within 4%, and the position of the joint interface to within 10%, of the experimental results.

  14. Temperature and Material Flow Prediction in Friction-Stir Spot Welding of Advanced High-Strength Steel

    SciTech Connect

    Miles, Michael; Karki, U.; Hovanski, Yuri

    2014-10-01

    Friction-stir spot welding (FSSW) has been shown to be capable of joining advanced high-strength steel, with its flexibility in controlling the heat of welding and the resulting microstructure of the joint. This makes FSSW a potential alternative to resistance spot welding if tool life is sufficiently high, and if machine spindle loads are sufficiently low that the process can be implemented on an industrial robot. Robots for spot welding can typically sustain vertical loads of about 8 kN, but FSSW at tool speeds of less than 3000 rpm cause loads that are too high, in the range of 11–14 kN. Therefore, in the current work, tool speeds of 5000 rpm were employed to generate heat more quickly and to reduce welding loads to acceptable levels. Si3N4 tools were used for the welding experiments on 1.2-mm DP 980 steel. The FSSW process was modeled with a finite element approach using the Forge* software. An updated Lagrangian scheme with explicit time integration was employed to predict the flow of the sheet material, subjected to boundary conditions of a rotating tool and a fixed backing plate. Material flow was calculated from a velocity field that is two-dimensional, but heat generated by friction was computed by a novel approach, where the rotational velocity component imparted to the sheet by the tool surface was included in the thermal boundary conditions. An isotropic, viscoplastic Norton-Hoff law was used to compute the material flow stress as a function of strain, strain rate, and temperature. The model predicted welding temperatures to within percent, and the position of the joint interface to within 10 percent, of the experimental results.

  15. Task-free MRI predicts individual differences in brain activity during task performance.

    PubMed

    Tavor, I; Parker Jones, O; Mars, R B; Smith, S M; Behrens, T E; Jbabdi, S

    2016-04-01

    When asked to perform the same task, different individuals exhibit markedly different patterns of brain activity. This variability is often attributed to volatile factors, such as task strategy or compliance. We propose that individual differences in brain responses are, to a large degree, inherent to the brain and can be predicted from task-independent measurements collected at rest. Using a large set of task conditions, spanning several behavioral domains, we train a simple model that relates task-independent measurements to task activity and evaluate the model by predicting task activation maps for unseen subjects using magnetic resonance imaging. Our model can accurately predict individual differences in brain activity and highlights a coupling between brain connectivity and function that can be captured at the level of individual subjects. PMID:27124457

  16. Motor System Activation Predicts Goal Imitation in 7-Month-Old Infants.

    PubMed

    Filippi, Courtney A; Cannon, Erin N; Fox, Nathan A; Thorpe, Samuel G; Ferrari, Pier F; Woodward, Amanda L

    2016-05-01

    The current study harnessed the variability in infants' neural and behavioral responses as a novel method for evaluating the potential relations between motor system activation and social behavior. We used electroencephalography (EEG) to record neural activity as 7-month-old infants observed and responded to the actions of an experimenter. To determine whether motor system activation predicted subsequent imitation behavior, we assessed event-related desynchronization (ERD) at central sites during action observation as a function of subsequent behavior. Greater mu desynchronization over central sites was observed when infants subsequently reproduced the experimenter's goal than when they did not reproduce the goal and instead selected the nongoal object. We also found that mu desynchronization during action execution predicted the infants' later propensity to reproduce the experimenter's goal-directed behavior. These results provide the first evidence that motor system activation predicts the imitation of other individuals' goals during infancy. PMID:27071750

  17. Using Matched Molecular Series as a Predictive Tool To Optimize Biological Activity

    PubMed Central

    2014-01-01

    A matched molecular series is the general form of a matched molecular pair and refers to a set of two or more molecules with the same scaffold but different R groups at the same position. We describe Matsy, a knowledge-based method that uses matched series to predict R groups likely to improve activity given an observed activity order for some R groups. We compare the Matsy predictions based on activity data from ChEMBLdb to the recommendations of the Topliss tree and carry out a large scale retrospective test to measure performance. We show that the basis for predictive success is preferred orders in matched series and that this preference is stronger for longer series. The Matsy algorithm allows medicinal chemists to integrate activity trends from diverse medicinal chemistry programs and apply them to problems of interest as a Topliss-like recommendation or as a hypothesis generator to aid compound design. PMID:24601597

  18. Forecasts and predictions of eruptive activity at Mount St. Helens, USA: 1975-1984

    USGS Publications Warehouse

    Swanson, D.A.; Casadevall, T.J.; Dzurisin, D.; Holcomb, R.T.; Newhall, C.G.; Malone, S.D.; Weaver, C.S.

    1985-01-01

    Public statements about volcanic activity at Mount St. Helens include factual statements, forecasts, and predictions. A factual statement describes current conditions but does not anticipate future events. A forecast is a comparatively imprecise statement of the time, place, and nature of expected activity. A prediction is a comparatively precise statement of the time, place, and ideally, the nature and size of impending activity. A prediction usually covers a shorter time period than a forecast and is generally based dominantly on interpretations and measurements of ongoing processes and secondarily on a projection of past history. The three types of statements grade from one to another, and distinctions are sometimes arbitrary. Forecasts and predictions at Mount St. Helens became increasingly precise from 1975 to 1982. Stratigraphic studies led to a long-range forecast in 1975 of renewed eruptive activity at Mount St. Helens, possibly before the end of the century. On the basis of seismic, geodetic and geologic data, general forecasts for a landslide and eruption were issued in April 1980, before the catastrophic blast and landslide on 18 May 1980. All extrusions except two from June 1980 to the end of 1984 were predicted on the basis of integrated geophysical, geochemical, and geologic monitoring. The two extrusions that were not predicted were preceded by explosions that removed a substantial part of the dome, reducing confining pressure and essentially short-circuiting the normal precursors. ?? 1985.

  19. Finite difference simulations of seismic wave propagation for understanding earthquake physics and predicting ground motions: Advances and challenges

    NASA Astrophysics Data System (ADS)

    Aochi, Hideo; Ulrich, Thomas; Ducellier, Ariane; Dupros, Fabrice; Michea, David

    2013-08-01

    Seismic waves radiated from an earthquake propagate in the Earth and the ground shaking is felt and recorded at (or near) the ground surface. Understanding the wave propagation with respect to the Earth's structure and the earthquake mechanisms is one of the main objectives of seismology, and predicting the strong ground shaking for moderate and large earthquakes is essential for quantitative seismic hazard assessment. The finite difference scheme for solving the wave propagation problem in elastic (sometimes anelastic) media has been more widely used since the 1970s than any other numerical methods, because of its simple formulation and implementation, and its easy scalability to large computations. This paper briefly overviews the advances in finite difference simulations, focusing particularly on earthquake mechanics and the resultant wave radiation in the near field. As the finite difference formulation is simple (interpolation is smooth), an easy coupling with other approaches is one of its advantages. A coupling with a boundary integral equation method (BIEM) allows us to simulate complex earthquake source processes.

  20. Impulsive Approach Tendencies towards Physical Activity and Sedentary Behaviors, but Not Reflective Intentions, Prospectively Predict Non-Exercise Activity Thermogenesis

    PubMed Central

    Cheval, Boris; Sarrazin, Philippe; Pelletier, Luc

    2014-01-01

    Understanding the determinants of non-exercise activity thermogenesis (NEAT) is crucial, given its extensive health benefits. Some scholars have assumed that a proneness to react differently to environmental cues promoting sedentary versus active behaviors could be responsible for inter-individual differences in NEAT. In line with this reflection and grounded on the Reflective-Impulsive Model, we test the assumption that impulsive processes related to sedentary and physical activity behaviors can prospectively predict NEAT, operationalized as spontaneous effort exerted to maintain low intensity muscle contractions within the release phases of an intermittent maximal isometric contraction task. Participants (n = 91) completed a questionnaire assessing their intentions to adopt physical activity behaviors and a manikin task to assess impulsive approach tendencies towards physical activity behaviors (IAPA) and sedentary behaviors (IASB). Participants were then instructed to perform a maximal handgrip strength task and an intermittent maximal isometric contraction task. As hypothesized, multilevel regression analyses revealed that spontaneous effort was (a) positively predicted by IAPA, (b) negatively predicted by IASB, and (c) was not predicted by physical activity intentions, after controlling for some confounding variables such as age, sex, usual PA level and average force provided during the maximal-contraction phases of the task. These effects remained constant throughout all the phases of the task. This study demonstrated that impulsive processes may play a unique role in predicting spontaneous physical activity behaviors. Theoretically, this finding reinforces the utility of a motivational approach based on dual-process models to explain inter-individual differences in NEAT. Implications for health behavior theories and behavior change interventions are outlined. PMID:25526596

  1. Application of Artificial Intelligence to the Prediction of the Antimicrobial Activity of Essential Oils

    PubMed Central

    Daynac, Mathieu; Cortes-Cabrera, Alvaro; Prieto, Jose M.

    2015-01-01

    Essential oils (EOs) are vastly used as natural antibiotics in Complementary and Alternative Medicine (CAM). Their intrinsic chemical variability and synergisms/antagonisms between its components make difficult to ensure consistent effects through different batches. Our aim is to evaluate the use of artificial neural networks (ANNs) for the prediction of their antimicrobial activity. Methods. The chemical composition and antimicrobial activity of 49 EOs, extracts, and/or fractions was extracted from NCCLS compliant works. The fast artificial neural networks (FANN) software was used and the output data reflected the antimicrobial activity of these EOs against four common pathogens: Staphylococcus aureus, Escherichia coli, Candida albicans, and Clostridium perfringens as measured by standardised disk diffusion assays. Results. ANNs were able to predict >70% of the antimicrobial activities within a 10 mm maximum error range. Similarly, ANNs were able to predict 2 or 3 different bioactivities at the same time. The accuracy of the prediction was only limited by the inherent errors of the popular antimicrobial disk susceptibility test and the nature of the pathogens. Conclusions. ANNs can be reliable, fast, and cheap tools for the prediction of the antimicrobial activity of EOs thus improving their use in CAM. PMID:26457111

  2. Using activation status of signaling pathways as mechanism-based biomarkers to predict drug sensitivity

    PubMed Central

    Amadoz, Alicia; Sebastian-Leon, Patricia; Vidal, Enrique; Salavert, Francisco; Dopazo, Joaquin

    2015-01-01

    Many complex traits, as drug response, are associated with changes in biological pathways rather than being caused by single gene alterations. Here, a predictive framework is presented in which gene expression data are recoded into activity statuses of signal transduction circuits (sub-pathways within signaling pathways that connect receptor proteins to final effector proteins that trigger cell actions). Such activity values are used as features by a prediction algorithm which can efficiently predict a continuous variable such as the IC50 value. The main advantage of this prediction method is that the features selected by the predictor, the signaling circuits, are themselves rich-informative, mechanism-based biomarkers which provide insight into or drug molecular mechanisms of action (MoA). PMID:26678097

  3. Early prediction of movie box office success based on Wikipedia activity big data.

    PubMed

    Mestyán, Márton; Yasseri, Taha; Kertész, János

    2013-01-01

    Use of socially generated "big data" to access information about collective states of the minds in human societies has become a new paradigm in the emerging field of computational social science. A natural application of this would be the prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging the gap between "real time monitoring" and "early predicting" remains a big challenge. Here we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie can be predicted much before its release by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia. PMID:23990938

  4. A Predictive Model of Daily Seismic Activity Induced by Mining, Developed with Data Mining Methods

    NASA Astrophysics Data System (ADS)

    Jakubowski, Jacek

    2014-12-01

    The article presents the development and evaluation of a predictive classification model of daily seismic energy emissions induced by longwall mining in sector XVI of the Piast coal mine in Poland. The model uses data on tremor energy, basic characteristics of the longwall face and mined output in this sector over the period from July 1987 to March 2011. The predicted binary variable is the occurrence of a daily sum of tremor seismic energies in a longwall that is greater than or equal to the threshold value of 105 J. Three data mining analytical methods were applied: logistic regression,neural networks, and stochastic gradient boosted trees. The boosted trees model was chosen as the best for the purposes of the prediction. The validation sample results showed its good predictive capability, taking the complex nature of the phenomenon into account. This may indicate the applied model's suitability for a sequential, short-term prediction of mining induced seismic activity.

  5. Comparison of Different 2D and 3D-QSAR Methods on Activity Prediction of Histamine H3 Receptor Antagonists.

    PubMed

    Dastmalchi, Siavoush; Hamzeh-Mivehroud, Maryam; Asadpour-Zeynali, Karim

    2012-01-01

    Histamine H3 receptor subtype has been the target of several recent drug development programs. Quantitative structure-activity relationship (QSAR) methods are used to predict the pharmaceutically relevant properties of drug candidates whenever it is applicable. The aim of this study was to compare the predictive powers of three different QSAR techniques, namely, multiple linear regression (MLR), artificial neural network (ANN), and HASL as a 3D QSAR method, in predicting the receptor binding affinities of arylbenzofuran histamine H3 receptor antagonists. Genetic algorithm coupled partial least square as well as stepwise multiple regression methods were used to select a number of calculated molecular descriptors to be used in MLR and ANN-based QSAR studies. Using the leave-group-out cross-validation technique, the performances of the MLR and ANN methods were evaluated. The calculated values for the mean absolute percentage error (MAPE), ranging from 2.9 to 3.6, and standard deviation of error of prediction (SDEP), ranging from 0.31 to 0.36, for both MLR and ANN methods were statistically comparable, indicating that both methods perform equally well in predicting the binding affinities of the studied compounds toward the H3 receptors. On the other hand, the results from 3D-QSAR studies using HASL method were not as good as those obtained by 2D methods. It can be concluded that simple traditional approaches such as MLR method can be as reliable as those of more advanced and sophisticated methods like ANN and 3D-QSAR analyses. PMID:25317190

  6. Activation of M1/4 receptors phase advances the hamster circadian clock during the day.

    PubMed

    Basu, Priyoneel; Wensel, Adrienne L; McKibbon, Reid; Lefebvre, Nicole; Antle, Michael C

    2016-05-16

    The mammalian circadian clock in the suprachiasmatic nucleus (SCN) can be reset by the cholinergic agonist carbachol. In hamsters, intraSCN carbachol produces phase advances during the day. This phenomenon has previously been attributed to the muscarinic receptors, as carbachol-induced phase shifts are blocked by pretreatment with the muscarinic antagonist atropine. The SCN contains all five muscarinic receptors, leaving open the question as to which muscarinic receptors mediate these shifts. Here we test two selective muscarinic agonists, the M1/4 agonist McN-A-343 and the M2/3 agonist bethanechol, in addition to the non-selective cholinergic agonist carbachol. Consistent with previous reports, carbachol produced significant phase advances when injected to the SCN during the mid-subjective day. At the doses used here, McN-A-343, but not bethanechol, also produced significant phase shifts when injected to the SCN during the mid-subjective day. Phase shifts to McN-A-343 were as large as those produced by carbachol, suggesting that activation of the M1/4 receptors alone can fully account for the daytime phase advances produced by cholinergic agonists. Given acetylcholine's role in arousal, and the similarity between phase advances to carbachol/McN-A-343 and to exercise and arousal manipulations, it is possible that acetylcholine may contribute to non-photic resetting of the circadian clock. PMID:27063283

  7. Comparison between measured and predicted resting metabolic rate in moderately active adolescents.

    PubMed

    De Lorenzo A; Bertini, I; Puijia, A; Testolin, G; Testolin, C

    1999-09-01

    The aim of this study was to check the validity of predictive equations for the calculation of resting metabolic rate (RMR) in moderately active adolescents. The RMR was measured in a sample of 25 healthy 15.5-18.2-year-old boys practicing soccer. The RMR was assessed by indirect calorimetry for 30 min following an overnight fast. Body composition was estimated from skinfold thickness measurements. Among the available equations to predict RMR, we decided to use those a of Molnar et al., Harris-Benedict, Schofield, and Cunningham. Measured and predicted values were compared by means of a one-way ANOVA. Also the Bland-Altman test was performed in order to evaluate the accuracy of the prediction equations compared to the measured value. The measured RMR was found to be 1834 +/- 160 kcal/day (mean +/- SD), while the Molnar et al., Schofield, Harris-Benedict, and Cunningham predicted values were 1707 +/- 78, 1866 +/- 89, 1779 +/- 84 and 1830 +/- 87 kcal/day, respectively. On average, compared to the measured values only the Molnar et al. equation differed significantly. On an individual basis, all the equations demonstrated considerable variability between measured and predicted RMRs. The predicted values also differed significantly. As regards the moderately active subjects (16-18 years old), we recommend the use of the Schofield equation, based on simple anthropometric parameters and also that of Cunningham, even if the estimation or measurement of fat-free mass may be cumbersome for everyday pediatric use. PMID:10664318

  8. Propulsion/ASME Rocket-Based Combined Cycle Activities in the Advanced Space Transportation Program Office

    NASA Technical Reports Server (NTRS)

    Hueter, Uwe; Turner, James

    1998-01-01

    NASA's Office Of Aeronautics and Space Transportation Technology (OASTT) has establish three major coals. "The Three Pillars for Success". The Advanced Space Transportation Program Office (ASTP) at the NASA's Marshall Space Flight Center in Huntsville,Ala. focuses on future space transportation technologies under the "Access to Space" pillar. The Advanced Reusable Technologies (ART) Project, part of ASTP, focuses on the reusable technologies beyond those being pursued by X-33. The main activity over the past two and a half years has been on advancing the rocket-based combined cycle (RBCC) technologies. In June of last year, activities for reusable launch vehicle (RLV) airframe and propulsion technologies were initiated. These activities focus primarily on those technologies that support the year 2000 decision to determine the path this country will take for Space Shuttle and RLV. In February of this year, additional technology efforts in the reusable technologies were awarded. The RBCC effort that was completed early this year was the initial step leading to flight demonstrations of the technology for space launch vehicle propulsion. Aerojet, Boeing-Rocketdyne and Pratt & Whitney were selected for a two-year period to design, build and ground test their RBCC engine concepts. In addition, ASTROX, Pennsylvania State University (PSU) and University of Alabama in Huntsville also conducted supporting activities. The activity included ground testing of components (e.g., injectors, thrusters, ejectors and inlets) and integrated flowpaths. An area that has caused a large amount of difficulty in the testing efforts is the means of initiating the rocket combustion process. All three of the prime contractors above were using silane (SiH4) for ignition of the thrusters. This follows from the successful use of silane in the NASP program for scramjet ignition. However, difficulties were immediately encountered when silane (an 80/20 mixture of hydrogen/silane) was used for rocket

  9. Integrated Application of Active Controls (IAAC) technology to an advanced subsonic transport project: current and advanced act control system definition study

    SciTech Connect

    Not Available

    1982-04-01

    The Current and Advanced Technology ACT control system definition tasks of the Integrated Application of Active Controls (IAAC) Technology project within the Energy Efficient Transport Program are summarized. The systems mechanize six active control functions: (1) pitch augmented stability (2) angle of attack limiting (3) lateral/directional augmented stability (4) gust load alleviation (5) maneuver load control and (6) flutter mode control. The redundant digital control systems meet all function requirements with required reliability and declining weight and cost as advanced technology is introduced.

  10. Integrated Application of Active Controls (IAAC) technology to an advanced subsonic transport project: Current and advanced act control system definition study

    NASA Technical Reports Server (NTRS)

    1982-01-01

    The Current and Advanced Technology ACT control system definition tasks of the Integrated Application of Active Controls (IAAC) Technology project within the Energy Efficient Transport Program are summarized. The systems mechanize six active control functions: (1) pitch augmented stability; (2) angle of attack limiting; (3) lateral/directional augmented stability; (4) gust load alleviation; (5) maneuver load control; and (6) flutter mode control. The redundant digital control systems meet all function requirements with required reliability and declining weight and cost as advanced technology is introduced.

  11. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

    NASA Astrophysics Data System (ADS)

    Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

    2016-01-01

    A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Köhler theory to predict the effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid-liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. The model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.

  12. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

    DOE PAGESBeta

    Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

    2016-01-19

    A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Köhler theory to predict themore » effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid–liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. The model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.« less

  13. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

    DOE PAGESBeta

    Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

    2016-01-19

    A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Kohler theory to predict themore » effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid–liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. Furthermore, the model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.« less

  14. Autonomous Motivation Predicts 7-Day Physical Activity in Hong Kong Students.

    PubMed

    Ha, Amy S; Ng, Johan Y Y

    2015-07-01

    Autonomous motivation predicts positive health behaviors such as physical activity. However, few studies have examined the relation between motivational regulations and objectively measured physical activity and sedentary behaviors. Thus, we investigated whether different motivational regulations (autonomous motivation, controlled motivation, and amotivation) predicted 7-day physical activity, sedentary behaviors, and health-related quality of life (HRQoL) of students. A total of 115 students (mean age = 11.6 years, 55.7% female) self-reported their motivational regulations and health-related quality of life. Physical activity and sedentary behaviors were measured using accelerometers for seven days. Using multilevel modeling, we found that autonomous motivation predicted higher levels of moderate-to-vigorous physical activity, less sedentary behaviors, and better HRQoL. Controlled motivation and amotivation each only negatively predicted one facet of HRQoL. Results suggested that autonomous motivation could be an important predictor of physical activity behaviors in Hong Kong students. Promotion of this form of motivational regulation may also increase HRQoL. PMID:25943335

  15. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

    NASA Astrophysics Data System (ADS)

    Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

    2015-09-01

    A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. The model combines Köhler theory with semi-empirical group contribution methods to estimate molar volumes, activity coefficients and liquid-liquid phase boundaries to predict the effective hygroscopicity parameter, kappa. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of two. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. The model can be incorporated into scale-bridging testbeds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger scale models.

  16. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

    SciTech Connect

    Petters, M. D.; Kreidenweis, S. M.; Ziemann, P. J.

    2016-01-01

    A wealth of recent laboratory and field experiments demonstrate that organic aerosol composition evolves with time in the atmosphere, leading to changes in the influence of the organic fraction to cloud condensation nuclei (CCN) spectra. There is a need for tools that can realistically represent the evolution of CCN activity to better predict indirect effects of organic aerosol on clouds and climate. This work describes a model to predict the CCN activity of organic compounds from functional group composition. Following previous methods in the literature, we test the ability of semi-empirical group contribution methods in Köhler theory to predict the effective hygroscopicity parameter, kappa. However, in our approach we also account for liquid–liquid phase boundaries to simulate phase-limited activation behavior. Model evaluation against a selected database of published laboratory measurements demonstrates that kappa can be predicted within a factor of 2. Simulation of homologous series is used to identify the relative effectiveness of different functional groups in increasing the CCN activity of weakly functionalized organic compounds. Hydroxyl, carboxyl, aldehyde, hydroperoxide, carbonyl, and ether moieties promote CCN activity while methylene and nitrate moieties inhibit CCN activity. The model can be incorporated into scale-bridging test beds such as the Generator of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) to evaluate the evolution of kappa for a complex mix of organic compounds and to develop suitable parameterizations of CCN evolution for larger-scale models.

  17. Synthetic cannabinoids: In silico prediction of the cannabinoid receptor 1 affinity by a quantitative structure-activity relationship model.

    PubMed

    Paulke, Alexander; Proschak, Ewgenij; Sommer, Kai; Achenbach, Janosch; Wunder, Cora; Toennes, Stefan W

    2016-03-14

    The number of new synthetic psychoactive compounds increase steadily. Among the group of these psychoactive compounds, the synthetic cannabinoids (SCBs) are most popular and serve as a substitute of herbal cannabis. More than 600 of these substances already exist. For some SCBs the in vitro cannabinoid receptor 1 (CB1) affinity is known, but for the majority it is unknown. A quantitative structure-activity relationship (QSAR) model was developed, which allows the determination of the SCBs affinity to CB1 (expressed as binding constant (Ki)) without reference substances. The chemically advance template search descriptor was used for vector representation of the compound structures. The similarity between two molecules was calculated using the Feature-Pair Distribution Similarity. The Ki values were calculated using the Inverse Distance Weighting method. The prediction model was validated using a cross validation procedure. The predicted Ki values of some new SCBs were in a range between 20 (considerably higher affinity to CB1 than THC) to 468 (considerably lower affinity to CB1 than THC). The present QSAR model can serve as a simple, fast and cheap tool to get a first hint of the biological activity of new synthetic cannabinoids or of other new psychoactive compounds. PMID:26795018

  18. Activities and operations of the Advanced Computing Research Facility, July-October 1986

    SciTech Connect

    Pieper, G.W.

    1986-01-01

    Research activities and operations of the Advanced Computing Research Facility (ACRF) at Argonne National Laboratory are discussed for the period from July 1986 through October 1986. The facility is currently supported by the Department of Energy, and is operated by the Mathematics and Computer Science Division at Argonne. Over the past four-month period, a new commercial multiprocessor, the Intel iPSC-VX/d4 hypercube was installed. In addition, four other commercial multiprocessors continue to be available for research - an Encore Multimax, a Sequent Balance 21000, an Alliant FX/8, and an Intel iPSC/d5 - as well as a locally designed multiprocessor, the Lemur. These machines are being actively used by scientists at Argonne and throughout the nation in a wide variety of projects concerning computer systems with parallel and vector architectures. A variety of classes, workshops, and seminars have been sponsored to train researchers on computing techniques for the advanced computer systems at the Advanced Computing Research Facility. For example, courses were offered on writing programs for parallel computer systems and hosted the first annual Alliant users group meeting. A Sequent users group meeting and a two-day workshop on performance evaluation of parallel computers and programs are being organized.

  19. Addressing fundamental architectural challenges of an activity-based intelligence and advanced analytics (ABIAA) system

    NASA Astrophysics Data System (ADS)

    Yager, Kevin; Albert, Thomas; Brower, Bernard V.; Pellechia, Matthew F.

    2015-06-01

    The domain of Geospatial Intelligence Analysis is rapidly shifting toward a new paradigm of Activity Based Intelligence (ABI) and information-based Tipping and Cueing. General requirements for an advanced ABIAA system present significant challenges in architectural design, computing resources, data volumes, workflow efficiency, data mining and analysis algorithms, and database structures. These sophisticated ABI software systems must include advanced algorithms that automatically flag activities of interest in less time and within larger data volumes than can be processed by human analysts. In doing this, they must also maintain the geospatial accuracy necessary for cross-correlation of multi-intelligence data sources. Historically, serial architectural workflows have been employed in ABIAA system design for tasking, collection, processing, exploitation, and dissemination. These simpler architectures may produce implementations that solve short term requirements; however, they have serious limitations that preclude them from being used effectively in an automated ABIAA system with multiple data sources. This paper discusses modern ABIAA architectural considerations providing an overview of an advanced ABIAA system and comparisons to legacy systems. It concludes with a recommended strategy and incremental approach to the research, development, and construction of a fully automated ABIAA system.

  20. Patient specific proteolytic activity of monocyte-derived macrophages and osteoclasts predicted with temporal kinase activation states during differentiation

    PubMed Central

    Park, Keon-Young; Li, Weiwei A.; Platt, Manu O.

    2012-01-01

    Patient-to-patient variability in disease progression continues to complicate clinical decisions of treatment regimens for cardiovascular diseases, metastatic cancers and osteoporosis. Here, we investigated if monocytes, circulating white blood cells that enter tissues and contribute to disease progression by differentiating into macrophages or osteoclasts, could be useful in understanding this variability. Monocyte-derived macrophages and osteoclasts produce cysteine cathepsins, powerful extracellular matrix proteases which have been mechanistically linked to accelerated atherosclerotic, osteoporotic, and tumor progression. We hypothesized that multivariate analysis of temporal kinase activation states during monocyte differentiation could predict cathepsin proteolytic responses of monocyte-derived macrophages and osteoclasts in a patient-specific manner. Freshly isolated primary monocytes were differentiated with M-CSF or RANKL into macrophages or osteoclasts, respectively, and phosphorylation of ERK1/2, Akt, p38 MAPK, JNK, c-jun, and IκB-α were measured at days 1, 3, 6, and 9. In parallel, cell diameters and numbers of nuclei were measured, and multiplex cathepsin zymography was used to quantify cathepsins K, L, S, and V activity from cell extracts and conditioned media. There was extensive patient-to-patient variability in temporal kinase activation states, cell morphologies, and cathepsin K, L, S, and V proteolytic activity. Partial least squares regression models trained with temporal kinase activation states successfully predicted patient-specific morphological characteristics (mean cell diameter and number of nuclei) and patient-specific cathepsin proteolytic activity with predictability as high as 95%, even with the challenge of incorporating the complex, unknown cues from individual patients’ unique genetic and biochemical backgrounds. This personalized medicine approach considers patient variability in kinase signals to predict cathepsin activity

  1. Recent Advances in Free-Living Physical Activity Monitoring: A Review

    PubMed Central

    Andre, David; Wolf, Donna L.

    2007-01-01

    It has become clear recently that the epidemic of type 2 diabetes sweeping the globe is associated with decreased levels of physical activity and an increase in obesity. Incorporating appropriate and sufficient physical activity into one's life is an essential component of achieving and maintaining a healthy weight and overall health, especially for those with type II diabetes mellitus. Regular physical activity can have a positive impact by lowering blood glucose, helping the body to be more efficient at using insulin. There are other substantial benefits for patients with diabetes, including prevention of cardiovascular disease, hyperlipidemia, hypertension, and obesity. Several complications of utilizing a self-care treatment methodology involving exercise include (1) patients may not know how much activity that they engage in and (2) health-care providers do not have objective measurements of how much activity their patients perform. However, several technological advances have brought a variety of activity monitoring devices to the market that can address these concerns. Ranging from simple pedometers to multisensor devices, the different technologies offer varying levels of accuracy, comfort, and reliability. The key notion is that by providing feedback to the patient, motivation can be increased and targets can be set and aimed toward. Although these devices are not specific to the treatment of diabetes, the importance of physical activity in treating the disease makes an understanding of these devices important. This article reviews these physical activity monitors and describes the advantages and disadvantages of each. PMID:19885145

  2. Real-time prediction of magnetospheric activity using the Boyle Index

    NASA Astrophysics Data System (ADS)

    Bala, Ramkumar; Reiff, P. H.; Landivar, J. E.

    2009-04-01

    We present a new algorithm with an improvement in the accuracy and lead time in short-term space weather predictions by coupling the Boyle Index, Φ = 10-4ν2 + 11.7Bsin3(?/2) kV, to artificial neural networks. The algorithm takes inputs from ACE and a handful of ground-based magnetometers to predict the next upcoming Kp in real time. The model yields a correlation coefficient of over 86% when predicting Kp with a lead time of 1 hour and over 85% for a 2 hour ahead prediction, significantly larger than the Kp persistence of 0.80. The Boyle Index, available in near-real time from http://space.rice.edu/ISTP/wind.html, has been in use for over 5 years now to predict geomagnetic activity. The logarithm of both 3-hour and 1-hour averages of the Boyle Index correlates well with the following Kp: Kp = 8.93 log10 < Boyle Index> -12.55. Using the Boyle Index alone, the algorithm yields a correlation coefficient of 85% when predicting Kp with a lead time of 1 hour and over 84% for a 3 hour ahead prediction, nearly as good as when using Kp in the history but without any possibility of "persistence contamination." Although the Boyle Index generally overestimates the polar cap potential for severe events, it does predict that severe activity will occur. Also, 1-hour value less than 100 kV is a good indicator that the magnetosphere will be quiet. However, some storm events with Kp > 6 occur when the Boyle Index is relatively low; the new algorithm is successful in predicting those events by capturing the influence of preconditioning.

  3. Active load management with advanced window wall systems: Research and industry perspectives

    SciTech Connect

    Lee, Eleanor S.; Selkowitz, Stephen E.; Levi, Mark S.; Blanc, Steven L.; McConahey, Erin; McClintock, Maurya; Hakkarainen, Pekka; Sbar, Neil L.; Myser, Michael P.

    2002-06-01

    Advanced window wall systems have the potential to provide demand response by reducing peak electric loads by 20-30% in many commercial buildings through the active control of motorized shading systems, switchable window coatings, operable windows, and ventilated double-skin facade systems. These window strategies involve balancing daylighting and solar heat gains, heat rejection through ventilation, and night-time natural ventilation to achieve space-conditioning and lighting energy use reductions without the negative impacts on occupants associated with other demand responsive (DR) strategies. This paper explores conceptually how advanced window systems fit into the context of active load management programs, which cause customers to directly experience the time-varying costs of their consumption decisions. Technological options are suggested. We present pragmatic criteria that building owners use to determine whether to deploy such strategies. A utility's perspective is given. Industry also provides their perspectives on where the technology is today and what needs to happen to implement such strategies more broadly in the US. While there is significant potential for these advanced window concepts, widespread deployment is unlikely to occur with business-as-usual practice. Technologically, integrated window-lighting-HVAC products are underdeveloped. Implementation is hindered by fragmented labor practices, non-standard communication protocols, and lack of technical expertise. Design tools and information products that quantify energy performance, occupant impacts, reliability, and other pragmatic concerns are not available. Interest within the building industry in sustainability, energy-efficiency, and increased occupant amenity, comfort, and productivity will be the driving factors for these advanced facades in the near term--at least until the dust settles on the deregulated electricity market.

  4. An internally and externally validated nomogram for predicting the risk of irinotecan-induced severe neutropenia in advanced colorectal cancer patients

    PubMed Central

    Ichikawa, W; Uehara, K; Minamimura, K; Tanaka, C; Takii, Y; Miyauchi, H; Sadahiro, S; Fujita, K; Moriwaki, T; Nakamura, M; Takahashi, T; Tsuji, A; Shinozaki, K; Morita, S; Ando, Y; Okutani, Y; Sugihara, M; Sugiyama, T; Ohashi, Y; Sakata, Y

    2015-01-01

    Background: In Asians, the risk of irinotecan-induced severe toxicities is related in part to UGT1A1*6 (UGT, UDP glucuronosyltransferase) and UGT1A1*28, variant alleles that reduce the elimination of SN-38, the active metabolite of irinotecan. We prospectively studied the relation between the UGT1A1 genotype and the safety of irinotecan-based regimens in Japanese patients with advanced colorectal cancer, and then constructed a nomogram for predicting the risk of severe neutropenia in the first treatment cycle. Methods: Safety data were obtained from 1312 patients monitored during the first 3 cycles of irinotecan-based regimen in a prospective observational study. In development of the nomogram, multivariable logistic regression analysis was used to test the associations of candidate factors to severe neutropenia in the first cycle. The final nomogram based on the results of multivariable analysis was constructed and validated internally using a bootstrapping technique and externally in an independent data set (n=350). Results: The UGT1A1 genotype was confirmed to be associated with increased risks of irinotecan-induced grade 3 or 4 neutropenia and diarrhoea. The final nomogram included type of regimen, administered dose of irinotecan, gender, age, UGT1A1 genotype, Eastern Cooperative Oncology Group performance status, pre-treatment absolute neutrophil count, and total bilirubin level. The model was validated both internally (bootstrap-adjusted concordance index, 0.69) and externally (concordance index, 0.70). Conclusions: Our nomogram can be used before treatment to accurately predict the probability of irinotecan-induced severe neutropenia in the first cycle of therapy. Additional studies should evaluate the effect of nomogram-guided dosing on efficacy in patients receiving irinotecan. PMID:25880011

  5. Individual Differences in Anterior Cingulate Activation Associated with Attentional Bias Predict Cocaine Use After Treatment

    PubMed Central

    Marhe, Reshmi; Luijten, Maartje; van de Wetering, Ben J M; Smits, Marion; Franken, Ingmar H A

    2013-01-01

    Drug-dependent patients often relapse into drug use after treatment. Behavioral studies show that enhanced attentional bias to drug cues is a precursor of relapse. The present functional magnetic resonance imaging (fMRI) study examined whether brain regions involved in attentional bias are predictive of cocaine use after treatment. Attentional bias-related brain activity was measured—with a cocaine Stroop task—in cocaine-dependent patients during their first week in detoxification treatment and was used to predict cocaine use at 3-month follow-up. The predictive value of attentional bias-related brain activity in a priori defined regions of interest, in addition to other measures such as self-reports of substance severity, craving, and behavioral attentional bias were examined. The results show that craving in the week before treatment and individual variability in attentional bias-related activity in the dorsal anterior cingulate cortex (dACC) were significant predictors of days of cocaine use at 3-month follow-up and accounted for 45% in explained variance. Brain activity in the dACC uniquely contributed 22% of explained variance to the prediction model. These findings suggest that hyperactive attentional bias-related brain activity in the dACC might be a biomarker of relapse vulnerability as early as in the first week of detoxification treatment. Ultimately, this may help to develop individually tailored treatment interventions to reduce relapse risk. PMID:23303067

  6. Evaluation of probabilistic methods to predict muscle activity: implications for neuroprosthetics

    NASA Astrophysics Data System (ADS)

    Johnson, Lise A.; Fuglevand, Andrew J.

    2009-10-01

    Functional electrical stimulation (FES) involves artificial activation of muscles with surface or implanted electrodes to restore motor function in paralyzed individuals. Currently, FES-based prostheses produce only a limited range of movements due to the difficulty associated with identifying patterns of muscle activity needed to evoke more complex behaviour. Here we test three probability-based models (Bayesian density estimation, polynomial curve fitting and dynamic neural network) that use the trajectory of the hand to predict the electromyographic (EMG) activities of 12 arm muscles during complex two- and three-dimensional movements. Across most conditions, the neural network model yielded the best predictions of muscle activity. For three-dimensional movements, the predicted patterns of muscle activity using the neural network accounted for 40% of the variance in the actual EMG signals and were associated with an average root-mean-squared error of 6%. These results suggest that such probabilistic models could be used effectively to predict patterns of muscle stimulation needed to produce complex movements with an FES-based neuroprosthetic.

  7. Towards advanced study of Active Galactic Nuclei with visible light adaptive optics

    NASA Astrophysics Data System (ADS)

    Ammons, Stephen Mark

    It is thought that the immense energies associated with accretion of matter onto black holes in Active Galactic Nuclei (AGN) and Quasi-Stellar Objects (QSOs) may "feedback," via intense photon flux or outward motion of gas, and affect certain properties of the host galaxy. In particular, AGN feedback may contribute to "quenching," or ceasing, of star formation by the expulsion or heating of cold gas, causing the host galaxy to evolve onto the red sequence (e.g., Di Matteo et al. 2005, Hopkins et al. 2006). I probe for the effects of feedback on the stellar populations of 60 X-ray-selected AGN hosts at a redshift of 1 in the Great Observatories Origins Deep Survey (GOODS) Southern field. Combining high spatial resolution optical imaging from the Hubble Space Telescope Advanced Camera for Surveys (HST ACS), and high spatial resolution near infrared data from Keck Laser Guide Star Adaptive Optics (AO) and HST Near-Infrared Camera and Multi-Object Spectrograph (NICMOS), I test for the presence of young stars on sub-kiloparsec scales, independent of dust extinction. Testing for correlations between near-ultraviolet/optical ( NUV- R ) colors and gradients and X-ray parameters such as hardness ratio and luminosity reveals new information about the nature of AGN-driven feedback. These AGN hosts display color gradients in rest-frame NUV - R as far inward as ~400 pc, suggesting stellar mixtures with nonuniform age distributions. There is little (< 0.3 mags) difference between the NUV - R gradients of the obscured (hard in X-ray) sources and the unobscured (soft in X-ray) sources, suggesting that the unobscured sources are not increasingly quenched of star formation. I compare the NUV - R colors of spiral galaxies that host AGN to non-active spirals, finding similar color gradients, but redder colors. These observations support the notion that unobscured intermediate-luminosity AGN hosts do not appear to be increasingly quenched of star formation relative to obscured sources

  8. Activity and loading influence the predicted bone remodeling around cemented hip replacements.

    PubMed

    Dickinson, Alexander S

    2014-04-01

    Periprosthetic bone remodeling is frequently observed after total hip replacement. Reduced bone density increases the implant and bone fracture risk, and a gross loss of bone density challenges fixation in subsequent revision surgery. Computational approaches allow bone remodeling to be predicted in agreement with the general clinical observations of proximal resorption and distal hypertrophy. However, these models do not reproduce other clinically observed bone density trends, including faster stabilizing mid-stem density losses, and loss-recovery trends around the distal stem. These may resemble trends in postoperative joint loading and activity, during recovery and rehabilitation, but the established remodeling prediction approach is often used with identical pre- and postoperative load and activity assumptions. Therefore, this study aimed to evaluate the influence of pre- to postoperative changes in activity and loading upon the predicted progression of remodeling. A strain-adaptive finite element model of a femur implanted with a cemented Charnley stem was generated, to predict 60 months of periprosthetic remodeling. A control set of model input data assumed identical pre- and postoperative loading and activity, and was compared to the results obtained from another set of inputs with three varying activity and load profiles. These represented activity changes during rehabilitation for weak, intermediate and strong recoveries, and pre- to postoperative joint force changes due to hip center translation and the use of walking aids. Predicted temporal bone density change trends were analyzed, and absolute bone density changes and the time to homeostasis were inspected, alongside virtual X-rays. The predicted periprosthetic bone density changes obtained using modified loading inputs demonstrated closer agreement with clinical measurements than the control. The modified inputs also predicted the clinically observed temporal density change trends, but still under

  9. Iron Levels in Hepatocytes and Portal Tract Cells Predict Progression and Outcome of Patients with Advanced Chronic Hepatitis C1

    PubMed Central

    Lambrecht, Richard W.; Sterling, Richard K.; Naishadham, Deepa; Stoddard, Anne M.; Rogers, Thomas; Morishima, Chihiro; Morgan, Timothy R.; Bonkovsky, Herbert L.

    2011-01-01

    Background & Aims Iron might influence severity and progression of non-hemochromatotic liver diseases. We assessed the relationships between iron, variants in HFE, and progression and outcomes using data from the HALT-C Trial. We determined whether therapy with pegylated interferon (PegIFN) affects iron variables. Methods Participants were randomly assigned to groups given long-term therapy with PegIFN (n=400) or no therapy (n=413) for 3.5 y and followed for up to 8.7 y (median 6.0 y). Associations between patient characteristics and iron variables, at baseline and over time, were made using Kaplan-Meier analyses, Cox regression models, and repeated measures analysis of covariance. Iron was detected by Prussian blue staining. Results Patients with poor outcomes (increase in Child-Turcotte-Pugh score to ≥ 7, development of ascites, encephalopathy, variceal bleeding, spontaneous bacterial peritonitis, hepatocellular carcinoma, death) had significantly higher baseline scores for stainable iron in hepatocytes and cells in portal tracts than those without outcomes. Staining for iron in portal triads correlated with lobular and total Ishak inflammatory and fibrosis scores (P<0.0001). High baseline levels of iron in triads increased the risk for poor outcome (hazard ratio=1.35, P=0.02). Iron staining decreased in hepatocytes but increased in portal stromal cells over time (P<0.0001). Serum levels of iron and total iron binding capacity decreased significantly over time (P <0.0001), as did serum ferritin (P=0.0003). Long-term therapy with PegIFN did not affect levels of iron staining. Common variants in HFE did not correlate with outcomes, including development of hepatocellular carcinoma. Conclusions Degree of stainable iron in hepatocytes and portal tract cells predicts progression and clinical and histological outcomes of patients with advanced chronic hepatitis C. Long-term therapy with low-dose PegIFN did not improve outcomes or iron variables. PMID:21335007

  10. Requirements for an Advanced Low Earth Orbit (LEO) Sounder (ALS) for improved regional weather prediction and monitoring of greenhouse gases

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

    Hyperspectral infrared atmospheric sounders (e.g. the Atmospheric Infrared Sounder (AIRS) on Aqua and the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp) 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 forecast1. 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 (1km 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.

  11. Advanced colorectal adenoma related gene expression signature may predict prognostic for colorectal cancer patients with adenoma-carcinoma sequence

    PubMed Central

    Li, Bing; Shi, Xiao-Yu; Liao, Dai-Xiang; Cao, Bang-Rong; Luo, Cheng-Hua; Cheng, Shu-Jun

    2015-01-01

    Background: There are still no absolute parameters predicting progression of adenoma into cancer. The present study aimed to characterize functional differences on the multistep carcinogenetic process from the adenoma-carcinoma sequence. Methods: All samples were collected and mRNA expression profiling was performed by using Agilent Microarray high-throughput gene-chip technology. Then, the characteristics of mRNA expression profiles of adenoma-carcinoma sequence were described with bioinformatics software, and we analyzed the relationship between gene expression profiles of adenoma-adenocarcinoma sequence and clinical prognosis of colorectal cancer. Results: The mRNA expressions of adenoma-carcinoma sequence were significantly different between high-grade intraepithelial neoplasia group and adenocarcinoma group. The biological process of gene ontology function enrichment analysis on differentially expressed genes between high-grade intraepithelial neoplasia group and adenocarcinoma group showed that genes enriched in the extracellular structure organization, skeletal system development, biological adhesion and itself regulated growth regulation, with the P value after FDR correction of less than 0.05. In addition, IPR-related protein mainly focused on the insulin-like growth factor binding proteins. Conclusion: The variable trends of gene expression profiles for adenoma-carcinoma sequence were mainly concentrated in high-grade intraepithelial neoplasia and adenocarcinoma. The differentially expressed genes are significantly correlated between high-grade intraepithelial neoplasia group and adenocarcinoma group. Bioinformatics analysis is an effective way to study the gene expression profiles in the adenoma-carcinoma sequence, and may provide an effective tool to involve colorectal cancer research strategy into colorectal adenoma or advanced adenoma. PMID:26131062

  12. 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.

  13. Systemic inflammatory status at baseline predicts bevacizumab benefit in advanced non-small cell lung cancer patients

    PubMed Central

    Botta, Cirino; Barbieri, Vito; Ciliberto, Domenico; Rossi, Antonio; Rocco, Danilo; Addeo, Raffaele; Staropoli, Nicoletta; Pastina, Pierpaolo; Marvaso, Giulia; Martellucci, Ignazio; Guglielmo, Annamaria; Pirtoli, Luigi; Sperlongano, Pasquale; Gridelli, Cesare; Caraglia, Michele; Tassone, Pierfrancesco; Tagliaferri, Pierosandro; Correale, Pierpaolo

    2013-01-01

    Bevacizumab is a humanized anti-VEGF monoclonal antibody able to produce clinical benefit in advanced non-squamous non-small-cell lung cancer (NSCLC) patients when combined to chemotherapy. At present, while there is a rising attention to bevacizumab-related adverse events and costs, no clinical or biological markers have been identified and validated for baseline patient selection. Preclinical findings suggest an important role for myeloid-derived inflammatory cells, such as neutrophils and monocytes, in the development of VEGF-independent angiogenesis. We conducted a retrospective analysis to investigate the role of peripheral blood cells count and of an inflammatory index, the neutrophil-to-lymphocyte ratio (NLR), as predictors of clinical outcome in NSCLC patients treated with bevacizumab plus chemotherapy. One hundred twelve NSCLC patients treated with chemotherapy ± bevacizumab were retrospectively evaluated for the predictive value of clinical or laboratory parameters correlated with inflammatory status. Univariate analysis revealed that a high number of circulating neutrophils and monocytes as well as a high NLR were associated with shorter progression-free survival (PFS) and overall survival (OS) in bevacizumab-treated patients only. We have thus developed a model based on the absence or the presence of at least one of the above-mentioned inflammatory parameters. We found that the absence of all variables strongly correlated with longer PFS and OS (9.0 vs. 7.0 mo, HR: 0.39, p = 0.002; and 20.0 vs. 12.0 mo, HR: 0.29, p < 0.001 respectively) only in NSCLC patients treated with bevacizumab plus chemotherapy. Our results suggest that a baseline systemic inflammatory status is marker of resistance to bevacizumab treatment in NSCLC patients. PMID:23760488

  14. Systemic inflammatory status at baseline predicts bevacizumab benefit in advanced non-small cell lung cancer patients.

    PubMed

    Botta, Cirino; Barbieri, Vito; Ciliberto, Domenico; Rossi, Antonio; Rocco, Danilo; Addeo, Raffaele; Staropoli, Nicoletta; Pastina, Pierpaolo; Marvaso, Giulia; Martellucci, Ignazio; Guglielmo, Annamaria; Pirtoli, Luigi; Sperlongano, Pasquale; Gridelli, Cesare; Caraglia, Michele; Tassone, Pierfrancesco; Tagliaferri, Pierosandro; Correale, Pierpaolo

    2013-06-01

    Bevacizumab is a humanized anti-VEGF monoclonal antibody able to produce clinical benefit in advanced non-squamous non-small-cell lung cancer (NSCLC) patients when combined to chemotherapy. At present, while there is a rising attention to bevacizumab-related adverse events and costs, no clinical or biological markers have been identified and validated for baseline patient selection. Preclinical findings suggest an important role for myeloid-derived inflammatory cells, such as neutrophils and monocytes, in the development of VEGF-independent angiogenesis. We conducted a retrospective analysis to investigate the role of peripheral blood cells count and of an inflammatory index, the neutrophil-to-lymphocyte ratio (NLR), as predictors of clinical outcome in NSCLC patients treated with bevacizumab plus chemotherapy. One hundred and twelve NSCLC patients treated with chemotherapy ± bevacizumab were retrospectively evaluated for the predictive value of clinical or laboratory parameters correlated with inflammatory status. Univariate analysis revealed that a high number of circulating neutrophils and monocytes as well as a high NLR were associated with shorter progression-free survival (PFS) and overall survival (OS) in bevacizumab-treated patients only. We have thus developed a model based on the absence or the presence of at least one of the above-mentioned inflammatory parameters. We found that the absence of all variables strongly correlated with longer PFS and OS (9.0 vs. 7.0 mo, HR: 0.39, p = 0.002; and 20.0 vs. 12.0 mo, HR: 0.29, p < 0.001 respectively) only in NSCLC patients treated with bevacizumab plus chemotherapy. Our results suggest that a baseline systemic inflammatory status is marker of resistance to bevacizumab treatment in NSCLC patients. PMID:23760488

  15. Office of River Protection Advanced Low-Activity Waste Glass Research and Development Plan

    SciTech Connect

    Peeler, David K.; Kim, Dong-Sang; Vienna, John D.; Schweiger, Michael J.; Piepel, Gregory F.

    2015-11-01

    The U.S. Department of Energy Office of River Protection (ORP) has initiated and leads an integrated Advanced Waste Glass (AWG) program to increase the loading of Hanford tank wastes in glass while meeting melter lifetime expectancies and process, regulatory, and product performance requirements. The integrated ORP program is focused on providing a technical, science-based foundation for making key decisions regarding the successful operation of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) facilities in the context of an optimized River Protection Project (RPP) flowsheet. The fundamental data stemming from this program will support development of advanced glass formulations, key product performance and process control models, and tactical processing strategies to ensure safe and successful operations for both the low-activity waste (LAW) and high-level waste vitrification facilities. These activities will be conducted with the objective of improving the overall RPP mission by enhancing flexibility and reducing cost and schedule. The purpose of this advanced LAW glass research and development plan is to identify the near-term, mid-term, and longer-term research and development activities required to develop and validate advanced LAW glasses, property-composition models and their uncertainties, and an advanced glass algorithm to support WTP facility operations, including both Direct Feed LAW and full pretreatment flowsheets. Data are needed to develop, validate, and implement 1) new glass property-composition models and 2) a new glass formulation algorithm. Hence, this plan integrates specific studies associated with increasing the Na2O and SO3/halide concentrations in glass, because these components will ultimately dictate waste loadings for LAW vitrification. Of equal importance is the development of an efficient and economic strategy for 99Tc management. Specific and detailed studies are being implemented to understand the fate of Tc throughout

  16. The Updated Solar Activity Prediction during the MAVEN Mission, but Should We Believe It?

    NASA Technical Reports Server (NTRS)

    Chamberlin, Philip

    2009-01-01

    Mars atmospheric processes are very dependent not only on the absolute level of the solar irradiance but also the changes in solar irradiance. Correlated with many of these irradiance changes, especially during solar flares, are large particle events called coronal mass ejections that themselves significantly drive processes in the Martian atmosphere. The NOAA Space Weather Prediction Center has issued a consensus solar cycle activity prediction for the upcoming solar cycle 24 maximum, and this maximum period of solar activity will be during the prime MAVEN science mission. This 'consensus' prediction calls for lower activity than the previous solar cycle maximum that occurred during the years 2001-2002, but looking at the wide spread of peer-reviewed predictions there is little faith that can be taken in any one prediction. This drives the importance of real-time measurements from the LPW/EUV diodes and the measurement and modeling results that will be improved upon using results from the Solar Dynamics Observatory (SDO).

  17. Structure-Functional Study of Tyrosine and Methionine Dipeptides: An Approach to Antioxidant Activity Prediction

    PubMed Central

    Torkova, Anna; Koroleva, Olga; Khrameeva, Ekaterina; Fedorova, Tatyana; Tsentalovich, Mikhail

    2015-01-01

    Quantum chemical methods allow screening and prediction of peptide antioxidant activity on the basis of known experimental data. It can be used to design the selective proteolysis of protein sources in order to obtain products with antioxidant activity. Molecular geometry and electronic descriptors of redox-active amino acids, as well as tyrosine and methionine-containing dipeptides, were studied by Density Functional Theory method. The calculated data was used to reveal several descriptors responsible for the antioxidant capacities of the model compounds based on their experimentally obtained antioxidant capacities against ABTS (2,2′-Azino-bis-(3-ethyl-benzothiazoline-6-sulfonate)) and peroxyl radical. A formula to predict antioxidant activity of peptides was proposed. PMID:26512651

  18. Structure-Functional Study of Tyrosine and Methionine Dipeptides: An Approach to Antioxidant Activity Prediction.

    PubMed

    Torkova, Anna; Koroleva, Olga; Khrameeva, Ekaterina; Fedorova, Tatyana; Tsentalovich, Mikhail

    2015-01-01

    Quantum chemical methods allow screening and prediction of peptide antioxidant activity on the basis of known experimental data. It can be used to design the selective proteolysis of protein sources in order to obtain products with antioxidant activity. Molecular geometry and electronic descriptors of redox-active amino acids, as well as tyrosine and methionine-containing dipeptides, were studied by Density Functional Theory method. The calculated data was used to reveal several descriptors responsible for the antioxidant capacities of the model compounds based on their experimentally obtained antioxidant capacities against ABTS (2,2'-Azino-bis-(3-ethyl-benzothiazoline-6-sulfonate)) and peroxyl radical. A formula to predict antioxidant activity of peptides was proposed. PMID:26512651

  19. Operation of the power information center: Performance of secretariat functions and information exchange activities in the advanced power field of the interagency advanced power group

    NASA Technical Reports Server (NTRS)

    1983-01-01

    Highlights of activities conducted during the reporting period to facilitate the exchange of technical information among scientists and engineers both within the federal government and within industry are cited. Interagency Advanced Power Group meetings and special efforts, project briefs, and organization development are considered.

  20. Efficacy of RetroNectin-activated cytokine-induced killer cell therapy in the treatment of advanced hepatocelluar carcinoma

    PubMed Central

    LI, WEI; WANG, YAOMEI; KELLNER, DANIEL B.; ZHAO, LINGDI; XU, LINPING; GAO, QUANLI

    2016-01-01

    The present study aimed to investigate the efficacy of RetroNectin-activated cytokine-induced killer cell (R-CIK) therapy in advanced hepatocellular carcinoma patients as compared with conventional chemotherapy, a comparison that has not yet been thoroughly studied. From January 2010 to October 2013, 74 patients with an initial diagnosis of advanced hepatocelluar carcinoma were enrolled in the study. Patients were assigned to one of two treatment arms: patients in arm 1 (n=37) received R-CIK treatment as the first line therapy, whereas those in arm 2 (n=37) received chemotherapy as the first line treatment. The primary end point measured in this study was median overall survival (mOS). Median progression-free survival time (mPFS) and 1- and 2-year survival rates were recorded as secondary end points. Kaplan-Meier analysis was performed on all mOS and mPFS data, and treatment hazard ratios were established using the Cox proportional hazards model. The 1-year survival rate in treatment arm 1 was 42.47% vs. 24.89% in arm 2 (95% CI, 24.91–59.01% vs. 12.10–40.02%, P=0.066); the 2-year survival rates were 21.24 and 5.53% (95% CI, 4.60–45.86 vs. 0.46–21.06%, P=0.106) in arms 1 and 2, respectively; the mPFS in arm 1 was 4.37 vs. 3.90 (x2=0.182, P=0.670) in arm 2; and the mOS in arm 1 was 14.03 months vs. 9.46 months(x2=4.406, P=0.036) in arm 2. Calculations of univariate analyses of arm 1, R-CIK cycles ≥6, KPS >70, AFP ≤400 ng/ml, and findings of no vascular invasion and no extra-hepatic metastasis were potential predictive factors (P<0.05). Calculations from multivariate analyses similarly identified these factors as potentially having predictive value (P<0.05). The main adverse effects of R-CIK therapy included fever and headache pain. R-CIK treatment may prolong mOS in advanced hepatocellular carcinoma patients compared with conventional chemotherapy. Patients who underwent ≥6 cycles of R-CIK, had KPS scores >70, AFP ≤400 ng/ml, displayed no evidence of

  1. BRAIN REWARD ACTIVITY TO MASKED IN-GROUP SMILING FACES PREDICTS FRIENDSHIP DEVELOPMENT

    PubMed Central

    Chen, Pin-Hao A.; Whalen, Paul J.; Freeman, Jonathan B.; Taylor, James M.; Heatherton, Todd F.

    2015-01-01

    This study examined whether neural responses in the ventral striatum (VS) to in-group facial expressions—presented without explicit awareness—could predict friendship patterns in newly arrived individuals from China six months later. Individuals who initially showed greater VS activity in response to in-group happy expressions during functional neuroimaging later made considerably more in-group friends, suggesting that VS activity might reflect reward processes that drive in-group approach behaviors. PMID:26185595

  2. Remote Bridge Deflection Measurement Using an Advanced Video Deflectometer and Actively Illuminated LED Targets.

    PubMed

    Tian, Long; Pan, Bing

    2016-01-01

    An advanced video deflectometer using actively illuminated LED targets is proposed for remote, real-time measurement of bridge deflection. The system configuration, fundamental principles, and measuring procedures of the video deflectometer are first described. To address the challenge of remote and accurate deflection measurement of large engineering structures without being affected by ambient light, the novel idea of active imaging, which combines high-brightness monochromatic LED targets with coupled bandpass filter imaging, is introduced. Then, to examine the measurement accuracy of the proposed advanced video deflectometer in outdoor environments, vertical motions of an LED target with precisely-controlled translations were measured and compared with prescribed values. Finally, by tracking six LED targets mounted on the bridge, the developed video deflectometer was applied for field, remote, and multipoint deflection measurement of the Wuhan Yangtze River Bridge, one of the most prestigious and most publicized constructions in China, during its routine safety evaluation tests. Since the proposed video deflectometer using actively illuminated LED targets offers prominent merits of remote, contactless, real-time, and multipoint deflection measurement with strong robustness against ambient light changes, it has great potential in the routine safety evaluation of various bridges and other large-scale engineering structures. PMID:27563901

  3. Rocket-Based Combined Cycle Activities in the Advanced Space Transportation Program Office

    NASA Technical Reports Server (NTRS)

    Hueter, Uwe; Turner, James

    1999-01-01

    NASA's Office of Aero-Space Technology (OAST) has established three major goals, referred to as, "The Three Pillars for Success". The Advanced Space Transportation Program Office (ASTP) at the NASA's Marshall Space Flight Center (MSFC) in Huntsville, Ala. focuses on future space transportation technologies Under the "Access to Space" pillar. The Core Technologies Project, part of ASTP, focuses on the reusable technologies beyond those being pursued by X-33. One of the main activities over the past two and a half years has been on advancing the rocket-based combined cycle (RBCC) technologies. In June of last year, activities for reusable launch vehicle (RLV) airframe and propulsion technologies were initiated. These activities focus primarily on those technologies that support the decision to determine the path this country will take for Space Shuttle and RLV. This year, additional technology efforts in the reusable technologies will be awarded. The RBCC effort that was completed early this year was the initial step leading to flight demonstrations of the technology for space launch vehicle propulsion.

  4. Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAR)

    PubMed Central

    Myint, Kyaw Z.; Xie, Xiang-Qun

    2015-01-01

    This chapter focuses on the fingerprint-based artificial neural networks QSAR (FANN-QSAR) approach to predict biological activities of structurally diverse compounds. Three types of fingerprints, namely ECFP6, FP2, and MACCS, were used as inputs to train the FANN-QSAR models. The results were benchmarked against known 2D and 3D QSAR methods, and the derived models were used to predict cannabinoid (CB) ligand binding activities as a case study. In addition, the FANN-QSAR model was used as a virtual screening tool to search a large NCI compound database for lead cannabinoid compounds. We discovered several compounds with good CB2 binding affinities ranging from 6.70 nM to 3.75 μM. The studies proved that the FANN-QSAR method is a useful approach to predict bioactivities or properties of ligands and to find novel lead compounds for drug discovery research. PMID:25502380

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

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

  6. Predicting Atlantic seasonal hurricane activity using outgoing longwave radiation over Africa

    NASA Astrophysics Data System (ADS)

    Karnauskas, Kristopher B.; Li, Laifang

    2016-07-01

    Seasonal hurricane activity is a function of the amount of initial disturbances (e.g., easterly waves) and the background environment in which they develop into tropical storms (i.e., the main development region). Focusing on the former, a set of indices based solely upon the meridional structure of satellite-derived outgoing longwave radiation (OLR) over the African continent are shown to be capable of predicting Atlantic seasonal hurricane activity with very high rates of success. Predictions of named storms based on the July OLR field and trained only on the time period prior to the year being predicted yield a success rate of 87%, compared to the success rate of NOAA's August outlooks of 53% over the same period and with the same average uncertainty range (±2). The resulting OLR indices are statistically robust, highly detectable, physically linked to the predictand, and may account for longer-term observed trends.

  7. Early Prediction of Movie Box Office Success Based on Wikipedia Activity Big Data

    PubMed Central

    Mestyán, Márton; Yasseri, Taha; Kertész, János

    2013-01-01

    Use of socially generated “big data” to access information about collective states of the minds in human societies has become a new paradigm in the emerging field of computational social science. A natural application of this would be the prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging the gap between “real time monitoring” and “early predicting” remains a big challenge. Here we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie can be predicted much before its release by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia. PMID:23990938

  8. NASA's Advanced Propulsion Technology Activities for Third Generation Fully Reusable Launch Vehicle Applications

    NASA Technical Reports Server (NTRS)

    Hueter, Uwe

    2000-01-01

    NASA's Office of Aeronautics and Space Transportation Technology (OASTT) established the following three major goals, referred to as "The Three Pillars for Success": Global Civil Aviation, Revolutionary Technology Leaps, and Access to Space. The Advanced Space Transportation Program Office (ASTP) at the NASA's Marshall Space Flight Center in Huntsville, Ala. focuses on future space transportation technologies under the "Access to Space" pillar. The Propulsion Projects within ASTP under the investment area of Spaceliner100, focus on the earth-to-orbit (ETO) third generation reusable launch vehicle technologies. The goals of Spaceliner 100 is to reduce cost by a factor of 100 and improve safety by a factor of 10,000 over current conditions. The ETO Propulsion Projects in ASTP, are actively developing combination/combined-cycle propulsion technologies that utilized airbreathing propulsion during a major portion of the trajectory. System integration, components, materials and advanced rocket technologies are also being pursued. Over the last several years, one of the main thrusts has been to develop rocket-based combined cycle (RBCC) technologies. The focus has been on conducting ground tests of several engine designs to establish the RBCC flowpaths performance. Flowpath testing of three different RBCC engine designs is progressing. Additionally, vehicle system studies are being conducted to assess potential operational space access vehicles utilizing combined-cycle propulsion systems. The design, manufacturing, and ground testing of a scale flight-type engine are planned. The first flight demonstration of an airbreathing combined cycle propulsion system is envisioned around 2005. The paper will describe the advanced propulsion technologies that are being being developed under the ETO activities in the ASTP program. Progress, findings, and future activities for the propulsion technologies will be discussed.

  9. Posture and Activity Recognition and Energy Expenditure Prediction in a Wearable Platform

    PubMed Central

    Sazonov, Edward; Hegde, Nagaraj; Browning, Raymond C.; Melanson, Edward L.; Sazonova, Nadezhda A.

    2015-01-01

    The use of wearable sensors coupled with the processing power of mobile phones may be an attractive way to provide real-time feedback about physical activity and energy expenditure (EE). Here we describe the use of a shoe-based wearable sensor system (SmartShoe) with a mobile phone for real-time recognition of various postures/physical activities and the resulting EE. To deal with processing power and memory limitations of the phone, we compare use of Support Vector Machines (SVM), Multinomial Logistic Discrimination (MLD), and Multi-Layer Perceptrons (MLP) for posture and activity classification followed by activity-branched EE estimation. The algorithms were validated using data from 15 subjects who performed up to 15 different activities of daily living during a four-hour stay in a room calorimeter. MLD and MLP demonstrated activity classification accuracy virtually identical to SVM (~95%), while reducing the running time and the memory requirements by a factor of >103. Comparison of perminute EE estimation using activity-branched models resulted in accurate EE prediction (RMSE=0.78 kcal/min for SVM and MLD activity classification, 0.77 kcal/min for MLP, vs. RMSE of 0.75 kcal/min for manual annotation). These results suggest that low-power computational algorithms can be successfully used for real-time physical activity monitoring and EE prediction on a wearable platform. PMID:26011870

  10. k-Nearest neighbour local linear prediction of scalp EEG activity during intermittent photic stimulation.

    PubMed

    Erla, Silvia; Faes, Luca; Tranquillini, Enzo; Orrico, Daniele; Nollo, Giandomenico

    2011-05-01

    The characterization of the EEG response to photic stimulation (PS) is an important issue with significant clinical relevance. This study aims to quantify and map the complexity of the EEG during PS, where complexity is measured as the degree of unpredictability resulting from local linear prediction. EEG activity was recorded with eyes closed (EC) and eyes open (EO) during resting and PS at 5, 10, and 15 Hz in a group of 30 healthy subjects and in a case-report of a patient suffering from cerebral ischemia. The mean squared prediction error (MSPE) resulting from k-nearest neighbour local linear prediction was calculated in each condition as an index of EEG unpredictability. The linear or nonlinear nature of the system underlying EEG activity was evaluated quantifying MSPE as a function of the neighbourhood size during local linear prediction, and by surrogate data analysis as well. Unpredictability maps were obtained for each subject interpolating MSPE values over a schematic head representation. Results on healthy subjects evidenced: (i) the prevalence of linear mechanisms in the generation of EEG dynamics, (ii) the lower predictability of EO EEG, (iii) the desynchronization of oscillatory mechanisms during PS leading to increased EEG complexity, (iv) the entrainment of alpha rhythm during EC obtained by 10 Hz PS, and (v) differences of EEG predictability among different scalp regions. Ischemic patient showed different MSPE values in healthy and damaged regions. The EEG predictability decreased moving from the early acute stage to a stage of partial recovery. These results suggest that nonlinear prediction can be a useful tool to characterize EEG dynamics during PS protocols, and may consequently constitute a complement of quantitative EEG analysis in clinical applications. PMID:21216649

  11. Development and Validation of a Model to Predict Aerosol Breathing Zone Concentrations During Common Outdoor Activities

    EPA Science Inventory

    Research has been conducted on aerosol emission rates during various activities as well as aerosol transport into the breathing zone under idealized conditions. However, there has been little effort to link the two into a model for predicting a person’s breathing zone concentrat...

  12. PREDICTING THE ADSORPTION CAPACITY OF ACTIVATED CARBON FOR ORGANIC CONTAMINANTS FROM ADSORBENT AND ADSORBATE PROPERTIES

    EPA Science Inventory

    A quantitative structure-property relationship (QSPR) was developed and combined with the Polanyi-Dubinin-Manes model to predict adsorption isotherms of emerging contaminants on activated carbons with a wide range of physico-chemical properties. Affinity coefficients (βl

  13. DEVELOPMENT OF QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIPS FOR PREDICTING BIODEGRADATION KINETICS

    EPA Science Inventory

    Results have been presented on the development of a structure-activity relationship for biodegradation using a group contribution approach. sing this approach, reported results of the kinetic rate constant agree within 20% with the predicted values. dditional compound studies are...

  14. Factors of Participants and Blogs That Predict Blogging Activeness during Teaching Practice and Induction Year

    ERIC Educational Resources Information Center

    Luik, Piret; Taimalu, Merle

    2016-01-01

    The blog as a type of social software has been used in education for several years, and its positive effect in the field has been asserted in many studies. This study presents the factors of participants and blogs that predict blogging activeness during teaching practice and induction year. During the teaching practice and induction year all…

  15. Role of Parent Literacy and Numeracy Expectations and Activities in Predicting Early Numeracy Skills

    ERIC Educational Resources Information Center

    Segers, Eliane; Kleemans, Tijs; Verhoeven, Ludo

    2015-01-01

    The home numeracy environment (i.e., parents' numeracy expectations and activities), is related to early numeracy in young children. As recent studies have shown that both cognitive and linguistic factors play an important role in predicting numeracy development, it may be assumed that rather than the home "numeracy" environment, the…

  16. Correlates of reward-predictive value in learning-related hippocampal neural activity

    PubMed Central

    Okatan, Murat

    2009-01-01

    Temporal difference learning (TD) is a popular algorithm in machine learning. Two learning signals that are derived from this algorithm, the predictive value and the prediction error, have been shown to explain changes in neural activity and behavior during learning across species. Here, the predictive value signal is used to explain the time course of learning-related changes in the activity of hippocampal neurons in monkeys performing an associative learning task. The TD algorithm serves as the centerpiece of a joint probability model for the learning-related neural activity and the behavioral responses recorded during the task. The neural component of the model consists of spiking neurons that compete and learn the reward-predictive value of task-relevant input signals. The predictive-value signaled by these neurons influences the behavioral response generated by a stochastic decision stage, which constitutes the behavioral component of the model. It is shown that the time course of the changes in neural activity and behavioral performance generated by the model exhibits key features of the experimental data. The results suggest that information about correct associations may be expressed in the hippocampus before it is detected in the behavior of a subject. In this way, the hippocampus may be among the earliest brain areas to express learning and drive the behavioral changes associated with learning. Correlates of reward-predictive value may be expressed in the hippocampus through rate remapping within spatial memory representations, they may represent reward-related aspects of a declarative or explicit relational memory representation of task contingencies, or they may correspond to reward-related components of episodic memory representations. These potential functions are discussed in connection with hippocampal cell assembly sequences and their reverse reactivation during the awake state. The results provide further support for the proposal that neural

  17. Role of spontaneous physical activity in prediction of susceptibility to activity based anorexia in male and female rats

    PubMed Central

    Perez-Leighton, Claudio; Grace, Martha; Billington, Charles J.; Kotz, Catherine M.

    2015-01-01

    Anorexia nervosa (AN) is a chronic eating disorder affecting females and males, defined by body weight loss, higher physical activity levels and restricted food intake. Currently, the commonalities and differences between genders in etiology of AN are not well understood. Animal models of AN, such as activity-based anorexia (ABA), can be helpful in identifying factors determining individual susceptibility to AN. In ABA, rodents are given an access to a running wheel while food restricted, resulting in paradoxical increased physical activity levels and weight loss. Recent studies suggest that different behavioral traits, including voluntary exercise, can predict individual weight loss in ABA. A higher inherent drive for movement can promote development and severity of AN, but this hypothesis remains untested. In rodents and humans, drive for movement is defined as spontaneous physical activity (SPA), which is time spent in low-intensity, non-volitional movements. In this paper, we show that a profile of body weight history and behavioral traits, including SPA, can predict individual weight loss caused by ABA in male and female rats with high accuracy. Analysis of the influence of SPA on ABA susceptibility in males and females rats suggests that either high or low levels of SPA increase the probability of high weight loss in ABA, but with larger effects in males compared to females. These results suggest the same behavioral profile can identify individuals at-risk of AN for both male and female populations and that SPA has predictive value for susceptibility to AN. PMID:24912135

  18. A correction factor to f-chart predictions of active solar fraction in active-passive heating systems

    NASA Astrophysics Data System (ADS)

    Evans, B. L.; Beckman, W. A.; Duffie, J. A.; Mitchell, J. W.; Klein, S. A.

    1983-11-01

    The extent to which a passive system degrades the performance of an active solar space heating system was investigated, and a correction factor to account for these interactions was developed. The transient system simulation program TRNSYS is used to simulate the hour-by-hour performance of combined active-passive (hybrid) space heating systems in order to compare the active system performance with simplified design method predictions. The TRNSYS simulations were compared to results obtained using the simplified design calculations of the f-Chart method. Comparisons of TRNSYS and f-Chart were used to establish the accuracy of the f-Charts for active systems. A correlation was then developed to correct the monthly loads input into the f-Chart method to account for controller deadbands in both hybrid and active only buildings. A general correction factor was generated to be applied to the f-Chart method to produce more accurate and useful results for hybrid systems.

  19. Early functional magnetic resonance imaging activations predict language outcome after stroke.

    PubMed

    Saur, Dorothee; Ronneberger, Olaf; Kümmerer, Dorothee; Mader, Irina; Weiller, Cornelius; Klöppel, Stefan

    2010-04-01

    An accurate prediction of system-specific recovery after stroke is essential to provide rehabilitation therapy based on the individual needs. We explored the usefulness of functional magnetic resonance imaging scans from an auditory language comprehension experiment to predict individual language recovery in 21 aphasic stroke patients. Subjects with an at least moderate language impairment received extensive language testing 2 weeks and 6 months after left-hemispheric stroke. A multivariate machine learning technique was used to predict language outcome 6 months after stroke. In addition, we aimed to predict the degree of language improvement over 6 months. 76% of patients were correctly separated into those with good and bad language performance 6 months after stroke when based on functional magnetic resonance imaging data from language relevant areas. Accuracy further improved (86% correct assignments) when age and language score were entered alongside functional magnetic resonance imaging data into the fully automatic classifier. A similar accuracy was reached when predicting the degree of language improvement based on imaging, age and language performance. No prediction better than chance level was achieved when exploring the usefulness of diffusion weighted imaging as well as functional magnetic resonance imaging acquired two days after stroke. This study demonstrates the high potential of current machine learning techniques to predict system-specific clinical outcome even for a disease as heterogeneous as stroke. Best prediction of language recovery is achieved when the brain activation potential after system-specific stimulation is assessed in the second week post stroke. More intensive early rehabilitation could be provided for those with a predicted poor recovery and the extension to other systems, for example, motor and attention seems feasible. PMID:20299389

  20. Neural activity to a partner's facial expression predicts self-regulation after conflict

    PubMed Central

    Hooker, Christine I.; Gyurak, Anett; Verosky, Sara; Miyakawa, Asako; Ayduk, Özlem

    2009-01-01

    Introduction Failure to self-regulate after an interpersonal conflict can result in persistent negative mood and maladaptive behaviors. Research indicates that lateral prefrontal cortex (LPFC) activity is related to the regulation of emotional experience in response to lab-based affective challenges, such as viewing emotional pictures. This suggests that compromised LPFC function may be a risk-factor for mood and behavior problems after an interpersonal stressor. However, it remains unclear whether LPFC activity to a lab-based affective challenge predicts self-regulation in real-life. Method We investigated whether LPFC activity to a lab-based affective challenge (negative facial expressions of a partner) predicts self-regulation after a real-life affective challenge (interpersonal conflict). During an fMRI scan, healthy, adult participants in committed, dating relationships (N = 27) viewed positive, negative, and neutral facial expressions of their partners. In an online daily-diary, participants reported conflict occurrence, level of negative mood, rumination, and substance-use. Results LPFC activity in response to the lab-based affective challenge predicted self-regulation after an interpersonal conflict in daily life. When there was no interpersonal conflict, LPFC activity was not related to the change in mood or behavior the next day. However, when an interpersonal conflict did occur, ventral LPFC (VLPFC) activity predicted the change in mood and behavior the next day, such that lower VLPFC activity was related to higher levels of negative mood, rumination, and substance-use. Conclusions Low LPFC function may be a vulnerability and high LPFC function may be a protective factor for the development of mood and behavior problems after an interpersonal stressor. PMID:20004365

  1. Dynamics of Population Activity in Rat Sensory Cortex: Network Correlations Predict Anatomical Arrangement and Information Content

    PubMed Central

    Sabri, Mohammad Mahdi; Adibi, Mehdi; Arabzadeh, Ehsan

    2016-01-01

    To study the spatiotemporal dynamics of neural activity in a cortical population, we implanted a 10 × 10 microelectrode array in the vibrissal cortex of urethane-anesthetized rats. We recorded spontaneous neuronal activity as well as activity evoked in response to sustained and brief sensory stimulation. To quantify the temporal dynamics of activity, we computed the probability distribution function (PDF) of spiking on one electrode given the observation of a spike on another. The spike-triggered PDFs quantified the strength, temporal delay, and temporal precision of correlated activity across electrodes. Nearby cells showed higher levels of correlation at short delays, whereas distant cells showed lower levels of correlation, which tended to occur at longer delays. We found that functional space built based on the strength of pairwise correlations predicted the anatomical arrangement of electrodes. Moreover, the correlation profile of electrode pairs during spontaneous activity predicted the “signal” and “noise” correlations during sensory stimulation. Finally, mutual information analyses revealed that neurons with stronger correlations to the network during spontaneous activity, conveyed higher information about the sensory stimuli in their evoked response. Given the 400-μm-distance between adjacent electrodes, our functional quantifications unravel the spatiotemporal dynamics of activity among nearby and distant cortical columns. PMID:27458347

  2. Dynamics of Population Activity in Rat Sensory Cortex: Network Correlations Predict Anatomical Arrangement and Information Content.

    PubMed

    Sabri, Mohammad Mahdi; Adibi, Mehdi; Arabzadeh, Ehsan

    2016-01-01

    To study the spatiotemporal dynamics of neural activity in a cortical population, we implanted a 10 × 10 microelectrode array in the vibrissal cortex of urethane-anesthetized rats. We recorded spontaneous neuronal activity as well as activity evoked in response to sustained and brief sensory stimulation. To quantify the temporal dynamics of activity, we computed the probability distribution function (PDF) of spiking on one electrode given the observation of a spike on another. The spike-triggered PDFs quantified the strength, temporal delay, and temporal precision of correlated activity across electrodes. Nearby cells showed higher levels of correlation at short delays, whereas distant cells showed lower levels of correlation, which tended to occur at longer delays. We found that functional space built based on the strength of pairwise correlations predicted the anatomical arrangement of electrodes. Moreover, the correlation profile of electrode pairs during spontaneous activity predicted the "signal" and "noise" correlations during sensory stimulation. Finally, mutual information analyses revealed that neurons with stronger correlations to the network during spontaneous activity, conveyed higher information about the sensory stimuli in their evoked response. Given the 400-μm-distance between adjacent electrodes, our functional quantifications unravel the spatiotemporal dynamics of activity among nearby and distant cortical columns. PMID:27458347

  3. Linking Complex Problem Solving and General Mental Ability to Career Advancement: Does a Transversal Skill Reveal Incremental Predictive Validity?

    ERIC Educational Resources Information Center

    Mainert, Jakob; Kretzschmar, André; Neubert, Jonas C.; Greiff, Samuel

    2015-01-01

    Transversal skills, such as complex problem solving (CPS) are viewed as central twenty-first-century skills. Recent empirical findings have already supported the importance of CPS for early academic advancement. We wanted to determine whether CPS could also contribute to the understanding of career advancement later in life. Towards this end, we…

  4. Cytochrome P450 2D6 Activity Predicts Discontinuation of Tamoxifen Therapy in Breast Cancer Patients

    PubMed Central

    Rae, James M.; Sikora, Matthew J.; Henry, N. Lynn; Li, Lang; Kim, Seongho; Oesterreich, Steffi; Skaar, Todd; Nguyen, Anne T.; Desta, Zeruesenay; Storniolo, Anna Maria; Flockhart, David A.; Hayes, Daniel F.; Stearns, Vered

    2009-01-01

    The selective estrogen receptor modulator tamoxifen is routinely used for treatment and prevention of estrogen receptor positive breast cancer. Studies of tamoxifen adherence suggest that over half of patients discontinue treatment before the recommended 5 years. We hypothesized that polymorphisms in CYP2D6, the enzyme responsible for tamoxifen activation, predict for tamoxifen discontinuation. Tamoxifen-treated women (n = 297) were genotyped for CYP2D6 variants and assigned a “score” based on predicted allele activities from 0 (no activity) to 2 (high activity). Correlation between CYP2D6 score and discontinuation rates at 4 months were tested. We observed a strong non-linear correlation between higher CYP2D6 score and increased rates of discontinuation (r2 = 0.935, p = 0.018). These data suggest that presence of active CYP2D6 alleles may predict for higher likelihood of tamoxifen discontinuation. Therefore, patients who may be most likely to benefit from tamoxifen may paradoxically be most likely to discontinue treatment prematurely. PMID:19421167

  5. PASS-Predicted Hepatoprotective Activity of Caesalpinia sappan in Thioacetamide-Induced Liver Fibrosis in Rats

    PubMed Central

    Kadir, Farkaad A.; Kassim, Normadiah M.; Abdulla, Mahmood Ameen; Ahmadipour, Fatemeh; Yehye, Wageeh A.

    2014-01-01

    The antifibrotic effects of traditional medicinal herb Caesalpinia sappan (CS) extract on liver fibrosis induced by thioacetamide (TAA) and the expression of transforming growth factor β1 (TGF-β1), α-smooth muscle actin (αSMA), and proliferating cell nuclear antigen (PCNA) in rats were studied. A computer-aided prediction of antioxidant and hepatoprotective activities was primarily performed with the Prediction Activity Spectra of the Substance (PASS) Program. Liver fibrosis was induced in male Sprague Dawley rats by TAA administration (0.03% w/v) in drinking water for a period of 12 weeks. Rats were divided into seven groups: control, TAA, Silymarin (SY), and CS 300 mg/kg body weight and 100 mg/kg groups. The effect of CS on liver fibrogenesis was determined by Masson's trichrome staining, immunohistochemical analysis, and western blotting. In vivo determination of hepatic antioxidant activities, cytochrome P450 2E1 (CYP2E1), and matrix metalloproteinases (MPPS) was employed. CS treatment had significantly increased hepatic antioxidant enzymes activity in the TAA-treated rats. Liver fibrosis was greatly alleviated in rats when treated with CS extract. CS treatment was noted to normalize the expression of TGF-β1, αSMA, PCNA, MMPs, and TIMP1 proteins. PASS-predicted plant activity could efficiently guide in selecting a promising pharmaceutical lead with high accuracy and required antioxidant and hepatoprotective properties. PMID:24701154

  6. U.S. Department of Energy -- Advanced Vehicle Testing Activity: Plug-in Hybrid Electric Vehicle Testing and Demonstration Activities

    SciTech Connect

    James E. Francfort; Donald Karner; John G. Smart

    2009-05-01

    The U.S. Department of Energy’s (DOE) Advanced Vehicle Testing Activity (AVTA) tests plug-in hybrid electric vehicles (PHEV) in closed track, dynamometer and onroad testing environments. The onroad testing includes the use of dedicated drivers on repeated urban and highway driving cycles that range from 10 to 200 miles, with recharging between each loop. Fleet demonstrations with onboard data collectors are also ongoing with PHEVs operating in several dozen states and Canadian Provinces, during which trips- and miles-per-charge, charging demand and energy profiles, and miles-per-gallon and miles-per-kilowatt-hour fuel use results are all documented, allowing an understanding of fuel use when vehicles are operated in charge depleting, charge sustaining, and mixed charge modes. The intent of the PHEV testing includes documenting the petroleum reduction potential of the PHEV concept, the infrastructure requirements, and operator recharging influences and profiles. As of May 2008, the AVTA has conducted track and dynamometer testing on six PHEV conversion models and fleet testing on 70 PHEVs representing nine PHEV conversion models. A total of 150 PHEVs will be in fleet testing by the end of 2008, all with onboard data loggers. The onroad testing to date has demonstrated 100+ miles per gallon results in mostly urban applications for approximately the first 40 miles of PHEV operations. The primary goal of the AVTA is to provide advanced technology vehicle performance benchmark data for technology modelers, research and development programs, and technology goal setters. The AVTA testing results also assist fleet managers in making informed vehicle purchase, deployment and operating decisions. The AVTA is part of DOE’s Vehicle Technologies Program. These AVTA testing activities are conducted by the Idaho National Laboratory and Electric Transportation Engineering Corporation, with Argonne National Laboratory providing dynamometer testing support. The proposed paper

  7. Sound-Induced Activity in Voice-Sensitive Cortex Predicts Voice Memory Ability

    PubMed Central

    Watson, Rebecca; Latinus, Marianne; Bestelmeyer, Patricia E. G.; Crabbe, Frances; Belin, Pascal

    2012-01-01

    The “temporal voice areas” (TVAs; Belin et al., 2000) of the human brain show greater neuronal activity in response to human voices than to other categories of non-vocal sounds. However, a direct link between TVA activity and voice perception behavior has not yet been established. Here we show that a functional magnetic resonance imaging measure of activity in the TVAs predicts individual performance at a separately administered voice memory test. This relation holds when general sound memory ability is taken into account. These findings provide the first evidence that the TVAs are specifically involved in voice cognition. PMID:22485101

  8. Quantitative structure-activity relationship models with receptor-dependent descriptors for predicting peroxisome proliferator-activated receptor activities of thiazolidinedione and oxazolidinedione derivatives.

    PubMed

    Lather, Viney; Kairys, Visvaldas; Fernandes, Miguel X

    2009-04-01

    A quantitative structure-activity relationship study has been carried out, in which the relationship between the peroxisome proliferator-activated receptor alpha and the peroxisome proliferator-activated receptor gamma agonistic activities of thiazolidinedione and oxazolidinedione derivatives and quantitative descriptors, V(site) calculated in a receptor-dependent manner is modeled. These descriptors quantify the volume occupied by the optimized ligands in regions that are either common or specific to the superimposed binding sites of the targets under consideration. The quantitative structure-activity relationship models were built by forward stepwise linear regression modeling for a training set of 27 compounds and validated for a test set of seven compounds, resulting in a squared correlation coefficient value of 0.90 for peroxisome proliferator-activated receptor alpha and of 0.89 for peroxisome proliferator-activated receptor gamma. The leave-one-out cross-validation and test set predictability squared correlation coefficient values for these models were 0.85 and 0.62 for peroxisome proliferator-activated receptor alpha and 0.89 and 0.50 for peroxisome proliferator-activated receptor gamma respectively. A dual peroxisome proliferator-activated receptor model has also been developed, and it indicates the structural features required for the design of ligands with dual peroxisome proliferator-activated receptor activity. These quantitative structure-activity relationship models show the importance of the descriptors here introduced in the prediction and interpretation of the compounds affinity and selectivity. PMID:19243388

  9. Can the theory of planned behaviour predict the physical activity behaviour of individuals?

    PubMed

    Hobbs, Nicola; Dixon, Diane; Johnston, Marie; Howie, Kate

    2013-01-01

    The theory of planned behaviour (TPB) can identify cognitions that predict differences in behaviour between individuals. However, it is not clear whether the TPB can predict the behaviour of an individual person. This study employs a series of n-of-1 studies and time series analyses to examine the ability of the TPB to predict physical activity (PA) behaviours of six individuals. Six n-of-1 studies were conducted, in which TPB cognitions and up to three PA behaviours (walking, gym workout and a personally defined PA) were measured twice daily for six weeks. Walking was measured by pedometer step count, gym attendance by self-report with objective validation of gym entry and the personally defined PA behaviour by self-report. Intra-individual variability in TPB cognitions and PA behaviour was observed in all participants. The TPB showed variable predictive utility within individuals and across behaviours. The TPB predicted at least one PA behaviour for five participants but had no predictive utility for one participant. Thus, n-of-1 designs and time series analyses can be used to test theory in an individual. PMID:22943555

  10. Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership.

    PubMed

    Stang, Paul E; Ryan, Patrick B; Racoosin, Judith A; Overhage, J Marc; Hartzema, Abraham G; Reich, Christian; Welebob, Emily; Scarnecchia, Thomas; Woodcock, Janet

    2010-11-01

    The U.S. Food and Drug Administration (FDA) Amendments Act of 2007 mandated that the FDA develop a system for using automated health care data to identify risks of marketed drugs and other medical products. The Observational Medical Outcomes Partnership is a public-private partnership among the FDA, academia, data owners, and the pharmaceutical industry that is responding to the need to advance the science of active medical product safety surveillance by using existing observational databases. The Observational Medical Outcomes Partnership's transparent, open innovation approach is designed to systematically and empirically study critical governance, data resource, and methodological issues and their interrelationships in establishing a viable national program of active drug safety surveillance by using observational data. This article describes the governance structure, data-access model, methods-testing approach, and technology development of this effort, as well as the work that has been initiated. PMID:21041580

  11. Motion-base simulator results of advanced supersonic transport handling qualities with active controls

    NASA Technical Reports Server (NTRS)

    Feather, J. B.; Joshi, D. S.

    1981-01-01

    Handling qualities of the unaugmented advanced supersonic transport (AST) are deficient in the low-speed, landing approach regime. Consequently, improvement in handling with active control augmentation systems has been achieved using implicit model-following techniques. Extensive fixed-based simulator evaluations were used to validate these systems prior to tests with full motion and visual capabilities on a six-axis motion-base simulator (MBS). These tests compared the handling qualities of the unaugmented AST with several augmented configurations to ascertain the effectiveness of these systems. Cooper-Harper ratings, tracking errors, and control activity data from the MBS tests have been analyzed statistically. The results show the fully augmented AST handling qualities have been improved to an acceptable level.

  12. Optimization of an advanced non-invasive light activated disinfection strategy

    NASA Astrophysics Data System (ADS)

    George, S.; Kishen, A.

    2007-07-01

    A photosensitizer formulation and strategy was developed based on the photophysical, photochemical and photobiological characteristics of methylene blue (MB) for the disinfection of root canal using light activated therapy. Disinfection of matured E. faecalis biofilms on root canal dentine was tried with the newly developed 'Advanced Non- Invasive Light Activated Disinfection' (ANILAD), conventional photodynamic therapy, and conventional root canal therapy alone or in combination with ANILAD. The results showed that, although complete disinfection of nonmatured biofilm is possible by ANILAD alone, a combination of conventional root canal treatment (RCT) with ANILAD could achieve significantly higher bacterial killing (6log 10-7log 10 bacterial reduction) compared to any other tested treatment in matured biofilm (p<0.001).

  13. Accurate similarity index based on activity and connectivity of node for link prediction

    NASA Astrophysics Data System (ADS)

    Li, Longjie; Qian, Lvjian; Wang, Xiaoping; Luo, Shishun; Chen, Xiaoyun

    2015-05-01

    Recent years have witnessed the increasing of available network data; however, much of those data is incomplete. Link prediction, which can find the missing links of a network, plays an important role in the research and analysis of complex networks. Based on the assumption that two unconnected nodes which are highly similar are very likely to have an interaction, most of the existing algorithms solve the link prediction problem by computing nodes' similarities. The fundamental requirement of those algorithms is accurate and effective similarity indices. In this paper, we propose a new similarity index, namely similarity based on activity and connectivity (SAC), which performs link prediction more accurately. To compute the similarity between two nodes, this index employs the average activity of these two nodes in their common neighborhood and the connectivities between them and their common neighbors. The higher the average activity is and the stronger the connectivities are, the more similar the two nodes are. The proposed index not only commendably distinguishes the contributions of paths but also incorporates the influence of endpoints. Therefore, it can achieve a better predicting result. To verify the performance of SAC, we conduct experiments on 10 real-world networks. Experimental results demonstrate that SAC outperforms the compared baselines.

  14. Predicting passive and active tissue:plasma partition coefficients: interindividual and interspecies variability.

    PubMed

    Ruark, Christopher D; Hack, C Eric; Robinson, Peter J; Mahle, Deirdre A; Gearhart, Jeffery M

    2014-07-01

    A mechanistic tissue composition model incorporating passive and active transport for the prediction of steady-state tissue:plasma partition coefficients (K(t:pl)) of chemicals in multiple mammalian species was used to assess interindividual and interspecies variability. This approach predicts K(t:pl) using chemical lipophilicity, pKa, phospholipid membrane binding, and the unbound plasma fraction, together with tissue fractions of water, neutral lipids, neutral and acidic phospholipids, proteins, and pH. Active transport K(t:pl) is predicted using Michaelis-Menten transport parameters. Species-specific biological properties were identified from 126 peer reviewed journal articles, listed in the Supporting Information, for mouse, rat, guinea pig, rabbit, beagle dog, pig, monkey, and human species. Means and coefficients of variation for biological properties were used in a Monte Carlo analysis to assess variability. The results show K(t:pl) interspecies variability for the brain, fat, heart, kidney, liver, lung, muscle, red blood cell, skin, and spleen, but uncertainty in the estimates obscured some differences. Compounds undergoing active transport are shown to have concentration-dependent K(t:pl). This tissue composition-based mechanistic model can be used to predict K(t:pl) for organic chemicals across eight species and 10 tissues, and can be an important component in drug development when scaling K(t:pl) from animal models to humans. PMID:24832575

  15. Advanced sludge treatment affects extracellular polymeric substances to improve activated sludge dewatering.

    PubMed

    Neyens, Elisabeth; Baeyens, Jan; Dewil, Raf; De heyder, Bart

    2004-01-30

    The management of wastewater sludge, now often referred to as biosolids, accounts for a major portion of the cost of the wastewater treatment process and represents significant technical challenges. In many wastewater treatment facilities, the bottleneck of the sludge handling system is the dewatering operation. Advanced sludge treatment (AST) processes have been developed in order to improve sludge dewatering and to facilitate handling and ultimate disposal. The authors have extensively reported lab-scale, semi-pilot and pilot investigations on either thermal and thermochemical processes, or chemical oxidation using hydrogen peroxide. To understand the action of these advanced sludge technologies, the essential role played by extracellular polymeric substances (EPS) needs to be understood. EPS form a highly hydrated biofilm matrix, in which the micro-organisms are embedded. Hence they are of considerable importance in the removal of pollutants from wastewater, in bioflocculation, in settling and in dewatering of activated sludge. The present paper reviews the characteristics of EPS and the influence of thermochemical and oxidation mechanisms on degradation and flocculation of EPS. Experimental investigations on waste activated sludge are conducted by the authors to evaluate the various literature findings. From the experiments, it is concluded that AST methods enhance cake dewaterability in two ways: (i) they degrade EPS proteins and polysaccharides reducing the EPS water retention properties; and (ii) they promote flocculation which reduces the amount of fine flocs. PMID:15177096