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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. Advanced hydrologic prediction system

    NASA Astrophysics Data System (ADS)

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

    1999-08-01

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

  3. 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).

  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. 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…

  6. 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.

  7. 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.

  8. Developing a musculoskeletal model of the primate skull: predicting muscle activations, bite force, and joint reaction forces using multibody dynamics analysis and advanced optimisation methods.

    PubMed

    Shi, Junfen; Curtis, Neil; Fitton, Laura C; O'Higgins, Paul; Fagan, Michael J

    2012-10-07

    An accurate, dynamic, functional model of the skull that can be used to predict muscle forces, bite forces, and joint reaction forces would have many uses across a broad range of disciplines. One major issue however with musculoskeletal analyses is that of muscle activation pattern indeterminacy. A very large number of possible muscle force combinations will satisfy a particular functional task. This makes predicting physiological muscle recruitment patterns difficult. Here we describe in detail the process of development of a complex multibody computer model of a primate skull (Macaca fascicularis), that aims to predict muscle recruitment patterns during biting. Using optimisation criteria based on minimisation of muscle stress we predict working to balancing side muscle force ratios, peak bite forces, and joint reaction forces during unilateral biting. Validation of such models is problematic; however we have shown comparable working to balancing muscle activity and TMJ reaction ratios during biting to those observed in vivo and that peak predicted bite forces compare well to published experimental data. To our knowledge the complexity of the musculoskeletal model is greater than any previously reported for a primate. This complexity, when compared to more simple representations provides more nuanced insights into the functioning of masticatory muscles. Thus, we have shown muscle activity to vary throughout individual muscle groups, which enables them to function optimally during specific masticatory tasks. This model will be utilised in future studies into the functioning of the masticatory apparatus.

  9. Structure-Based Predictions of Activity Cliffs

    PubMed Central

    Husby, Jarmila; Bottegoni, Giovanni; Kufareva, Irina; Abagyan, Ruben; Cavalli, Andrea

    2015-01-01

    In drug discovery, it is generally accepted that neighboring molecules in a given descriptors' space display similar activities. However, even in regions that provide strong predictability, structurally similar molecules can occasionally display large differences in potency. In QSAR jargon, these discontinuities in the activity landscape are known as ‘activity cliffs’. In this study, we assessed the reliability of ligand docking and virtual ligand screening schemes in predicting activity cliffs. We performed our calculations on a diverse, independently collected database of cliff-forming co-crystals. Starting from ideal situations, which allowed us to establish our baseline, we progressively moved toward simulating more realistic scenarios. Ensemble- and template-docking achieved a significant level of accuracy, suggesting that, despite the well-known limitations of empirical scoring schemes, activity cliffs can be accurately predicted by advanced structure-based methods. PMID:25918827

  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. 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.

  12. Parameters of Stromal Activation and Epithelial to Mesenchymal Transition as Predictive Biomarkers for Induction Chemotherapy in Patients With Locally Advanced Oral Cavity and Oropharyngeal Squamous Cell Cancer

    PubMed Central

    Geweiler, Jana; Inhestern, Johanna; Berndt, Alexander; Guntinas-Lichius, Orlando

    2016-01-01

    Objectives Induction chemotherapy (IC) is likely to be effective for biologically distinct subgroups of oral cancer and biomarker development may lead to identification of those patients. Methods We evaluated immune cell infiltration, stroma formation and structure of the invasive front as well as the immunohistochemical expression of alpha smooth muscle actin (ASMA), CD163, E-cadherin, N-cadherin, and the laminin gamma 2 chain in pretreatment biopsy specimens and surgical resections after IC in 20 patients with locally advanced oral cancer who were treated in a prospective, ongoing, phase II trial on IC using docetaxel, cisplatin, and 5-fluorouracil (TPF). Results Significant negative prognostic factors for incomplete pathological tumor response to IC were alcohol abuse (P=0.032), cN+ (P=0.042), and <30% tumor reduction after first cycle of IC (P=0.034). Of the investigated histological parameters and biomarkers only a low membrane-bound expression of E-cadherin showed a trend to be associated with incomplete response to IC (P=0.061). Low expression of ASMA in stromal vessels and a strong tumor invasion front were significantly associated to tumor recurrence (P=0.024 and P=0.004, respectively). The median follow-up of all patients was 35 months. Alcohol abuse (P<0.001), <30% tumor reduction after first cycle of IC (P=0.005), and a strong tumor invasion front (P=0.019) were negative prognostic factors for overall survival. Conclusion A strong predictive biomarker among the investigated parameters for benefitting from TPF IC could not be found. The extent of the tumor invasion front was a negative prognostic marker for recurrence and survival in oral cancer treated by TPF IC followed by surgery and postoperative radiochemotherapy. PMID:27416733

  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. Predicting RNA structure: advances and limitations.

    PubMed

    Hofacker, Ivo L; Lorenz, Ronny

    2014-01-01

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

  16. 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

  17. 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.

  18. Advances in tilt rotor noise prediction

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  19. 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.

  20. 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

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

    NASA Technical Reports Server (NTRS)

    Sokolowski, Daniel E.; Ensign, C. Robert

    1986-01-01

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

  2. 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.

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

    PubMed

    Nazerfard, Ehsan; Cook, Diane J

    2015-04-01

    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.

  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 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

  6. 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.

  7. Advanced Performance Modeling with Combined Passive and Active Monitoring

    SciTech Connect

    Dovrolis, Constantine; Sim, Alex

    2015-04-15

    To improve the efficiency of resource utilization and scheduling of scientific data transfers on high-speed networks, the "Advanced Performance Modeling with combined passive and active monitoring" (APM) project investigates and models a general-purpose, reusable and expandable network performance estimation framework. The predictive estimation model and the framework will be helpful in optimizing the performance and utilization of networks as well as sharing resources with predictable performance for scientific collaborations, especially in data intensive applications. Our prediction model utilizes historical network performance information from various network activity logs as well as live streaming measurements from network peering devices. Historical network performance information is used without putting extra load on the resources by active measurement collection. Performance measurements collected by active probing is used judiciously for improving the accuracy of predictions.

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

    PubMed

    Lee, E A

    1999-05-01

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

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

    PubMed

    Lee, Ernesto A

    2007-10-01

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

  10. 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…

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

    DTIC Science & Technology

    2006-05-01

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

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

    NASA Astrophysics Data System (ADS)

    Feng, Rong; Duan, Wansuo; Mu, Mu

    2017-02-01

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

  13. 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.

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

    PubMed

    Mills, Jeremy F

    2005-02-01

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

  15. The prediction of transonic loading on advancing helicopter rotors

    NASA Technical Reports Server (NTRS)

    Strawn, R. C.; Tung, C.

    1986-01-01

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

  16. The prediction of transonic loading advancing helicopter rotors

    NASA Technical Reports Server (NTRS)

    Strawn, R.; Tung, C.

    1986-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

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

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  1. 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.

  2. 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;

  3. 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.

  4. Use of prediction markets to forecast infectious disease activity.

    PubMed

    Polgreen, Philip M; Nelson, Forrest D; Neumann, George R

    2007-01-15

    Prediction markets have accurately forecasted the outcomes of a wide range of future events, including sales of computer printers, elections, and the Federal Reserve's decisions about interest rates. We propose that prediction markets may be useful for tracking and forecasting emerging infectious diseases, such as severe acute respiratory syndrome and avian influenza, by aggregating expert opinion quickly, accurately, and inexpensively. Data from a pilot study in the state of Iowa suggest that these markets can accurately predict statewide seasonal influenza activity 2-4 weeks in advance by using clinical data volunteered from participating health care workers. Information revealed by prediction markets may help to inform treatment, prevention, and policy decisions. Also, these markets could help to refine existing surveillance systems.

  5. Early Prediction of Lupus Nephritis Using Advanced Proteomics

    DTIC Science & Technology

    2012-06-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

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

    Cancer.gov

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

  8. 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.

  9. 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.

  10. 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

  11. 76 FR 52954 - Workshop: Advancing Research on Mixtures; New Perspectives and Approaches for Predicting Adverse...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-24

    ... HUMAN SERVICES Workshop: Advancing Research on Mixtures; New Perspectives and Approaches for Predicting... ``Advancing Research on Mixtures: New Perspectives and Approaches for Predicting Adverse Human Health Effects....niehs.nih.gov/conferences/dert/mixtures/ . The deadline to register for this workshop is...

  12. Lifetime prediction modeling of airfoils for advanced power generation

    NASA Astrophysics Data System (ADS)

    Karaivanov, Ventzislav Gueorguiev

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

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

    DTIC Science & Technology

    2011-09-01

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

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

    PubMed

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

    2017-01-01

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

  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. 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

  18. 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

  19. "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…

  20. Predicting the Environmental Impact of Active Sonar

    NASA Astrophysics Data System (ADS)

    Duncan, Alec J.; McCauley, Robert D.; Maggi, Amos L.

    2004-11-01

    The effect of active sonar on marine animals, particularly mammals, has become a hot topic in recent times. The Australian Environmental Protection and Biodiversity Conservation Act 1999 obligates Defence to avoid significant environmental impacts from Navy activities including those which produce underwater sound such as active sonar. It is in the interests of all parties that these effects be modeled accurately to facilitate both the quantitative evaluation of the consequences of any proposed sonar trials, and the identification of suitable mitigation procedures. This paper discusses the received signal parameters that are of importance when predicting the effect of sonar systems on marine animals and techniques for modeling both the expected values of these parameters and their statistical fluctuations.

  1. 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…

  2. 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…

  3. Perceptions and Predictions of Expertise in Advanced Musical Learners

    ERIC Educational Resources Information Center

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

    2010-01-01

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

  4. 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

  5. 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.

  6. Improving active space telescope wavefront control using predictive thermal modeling

    NASA Astrophysics Data System (ADS)

    Gersh-Range, Jessica; Perrin, Marshall D.

    2015-01-01

    Active control algorithms for space telescopes are less mature than those for large ground telescopes due to differences in the wavefront control problems. Active wavefront control for space telescopes at L2, such as the James Webb Space Telescope (JWST), requires weighing control costs against the benefits of correcting wavefront perturbations that are a predictable byproduct of the observing schedule, which is known and determined in advance. To improve the control algorithms for these telescopes, we have developed a model that calculates the temperature and wavefront evolution during a hypothetical mission, assuming the dominant wavefront perturbations are due to changes in the spacecraft attitude with respect to the sun. Using this model, we show that the wavefront can be controlled passively by introducing scheduling constraints that limit the allowable attitudes for an observation based on the observation duration and the mean telescope temperature. We also describe the implementation of a predictive controller designed to prevent the wavefront error (WFE) from exceeding a desired threshold. This controller outperforms simpler algorithms even with substantial model error, achieving a lower WFE without requiring significantly more corrections. Consequently, predictive wavefront control based on known spacecraft attitude plans is a promising approach for JWST and other future active space observatories.

  7. 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.

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

    PubMed

    Miao, Zhichao; Westhof, Eric

    2017-03-30

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

  9. Predicting Single-Neuron Activity in Locally Connected Networks

    PubMed Central

    Azhar, Feraz; Anderson, William S.

    2014-01-01

    The characterization of coordinated activity in neuronal populations has received renewed interest in the light of advancing experimental techniques that allow recordings from multiple units simultaneously. Across both in vitro and in vivo preparations, nearby neurons show coordinated responses when spontaneously active and when subject to external stimuli. Recent work (Truccolo, Hochberg, & Donoghue, 2010) has connected these coordinated responses to behavior, showing that small ensembles of neurons in arm-related areas of sensorimotor cortex can reliably predict single-neuron spikes in behaving monkeys and humans. We investigate this phenomenon using an analogous point process model, showing that in the case of a computational model of cortex responding to random background inputs, one is similarly able to predict the future state of a single neuron by considering its own spiking history, together with the spiking histories of randomly sampled ensembles of nearby neurons. This model exhibits realistic cortical architecture and displays bursting episodes in the two distinct connectivity schemes studied. We conjecture that the baseline predictability we find in these instances is characteristic of locally connected networks more broadly considered. PMID:22845824

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

    NASA Astrophysics Data System (ADS)

    Knowles, K.

    1986-07-01

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

  11. Early Prediction of Lupus Nephritis Using Advanced Proteomics

    DTIC Science & Technology

    2009-06-01

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

  12. Solar activity cycle - History and predictions

    SciTech Connect

    Withbroe, G.L. )

    1989-12-01

    The solar output of short-wavelength radiation, solar wind, and energetic particles depends strongly on the solar cycle. These energy outputs from the sun control conditions in the interplanetary medium and in the terrestrial magnetosphere and upper atmosphere. Consequently, there is substantial interest in the behavior of the solar cycle and its effects. This review briefly discusses historical data on the solar cycle and methods for predicting its further behavior, particularly for the current cycle, which shows signs that it will have moderate to exceptionally high levels of activity. During the next few years, the solar flux of short-wavelength radiation and particles will be more intense than normal, and spacecraft in low earth orbit will reenter earlier than usual. 46 refs.

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

  15. Early Prediction of Lupus Nephritis Using Advanced Proteomics

    DTIC Science & Technology

    2008-06-01

    nephropathies with similar urinary findings. The respective amendment has been submitted to the CCHMC IRB and the ORP will be notified once approval at...and 133 kDa. These biomarkers were strongly correlated with renal disease activity and with renal damage. For the diagnosis of active nephritis...noninvasive technique for exploring pathological metabolic and toxicological processes in humans42-44 and is being developed as a tool for diagnosis of

  16. 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.

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

    PubMed

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

    2016-01-01

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

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. 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

  4. Advances in chalcones with anticancer activities.

    PubMed

    Karthikeyan, Chandrabose; Moorthy, Narayana S H Narayana; Ramasamy, Sakthivel; Vanam, Uma; Manivannan, Elangovan; Karunagaran, Devarajan; Trivedi, Piyush

    2015-01-01

    Chalcones are naturally occurring compounds exhibiting broad spectrum biological activities including anticancer activity through multiple mechanisms. Literature on anticancer chalcones highlights the employment of three pronged strategies, namely; structural manipulation of both aryl rings, replacement of aryl rings with heteroaryl scaffolds, molecular hybridization through conjugation with other pharmacologically interesting scaffolds for enhancement of anticancer properties. Methoxy substitutions on both the aryl rings (A and B) of the chalcones, depending upon their positions in the aryl rings appear to influence anticancer and other activities. Similarly, heterocyclic rings either as ring A or B in chalcones, also influence the anticancer activity shown by this class of compounds. Hybrid chalcones formulated by chemically linking chalcones to other prominent anticancer scaffolds such as pyrrol[2,1-c][1,4]benzodiazepines, benzothiazoles, imidazolones have demonstrated synergistic or additive pharmacological activities. The successful application of these three pronged strategies for discovering novel anticancer agents based on chalcone scaffold has resulted in many novel and chemically diverse chalcones with potential therapeutic application for many types of cancer. This review summarizes the concerted efforts expended on the design and development of anticancer chalcones recorded in recent literature and also provides an overview of the patents published in this area between 2007 and 2014 (WO2013022951, WO201201745 & US2012029489).

  5. 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.

  6. 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.

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

    PubMed

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

    2017-03-01

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

  8. 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.

  9. 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…

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

    PubMed

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

    2016-08-16

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

  11. 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.

  12. 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

  13. Model-based prediction of fusimotor activity and its effect on muscle spindle activity during voluntary wrist movements.

    PubMed

    Grandjean, Bernard; Maier, Marc A

    2014-08-01

    Muscle spindles provide critical information about movement position and velocity. They have been shown to act as stretch receptors in passive muscle, however, during active movements their behavior is less clear. In particular, spindle responses have been shown to be out-of-phase or phase advanced with respect to their expected muscle length-sensitivity. Whether this apparent discrepancy of spindle responses between passive and active movements is due to fusimotor (γ-drive) remains unresolved, since the activity of fusimotor neurons during voluntary non-locomotor movements are largely unknown. We developed a computational model to predict fusimotor activity and to investigate whether fusimotor activity could explain the empirically observed phase advance of spindle responses. The model links a biomechanical wrist model to length- and γ-drive-dependent transfer functions of type Ia and type II muscle spindle activity. Our simulations of two wrist-movement tasks suggest that (i) experimentally observed type Ia and type II activity profiles can to a large part be explained by appropriate, i.e. strongly modulated and task-dependent, γ-drive. That (ii) the empirically observed phase advance of type Ia or of type II profiles during active movement can be similarly explained by appropriate γ-drive. In summary, the simulation predicts that a highly task-modulated activation of the γ-system is instrumental in producing a large part of the empirically observed muscle spindle activity for voluntary wrist movements.

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

    PubMed

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

    2009-01-01

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

  15. 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.

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

    ERIC Educational Resources Information Center

    Luperchio, Dan

    2009-01-01

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

  17. 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

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

    PubMed Central

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

    2016-01-01

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

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

    SciTech Connect

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

    1990-08-01

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

  20. Computer Aided Prediction of Biological Activity Spectra: Study of Correlation between Predicted and Observed Activities for Coumarin-4-Acetic Acids

    PubMed Central

    Basanagouda, M.; Jadhav, V. B.; Kulkarni, M. V.; Rao, R. Nagendra

    2011-01-01

    Coumarin-4-acetic acids have been synthesized from various phenols and citric acid under Pechmann cyclisation conditions. All the compounds have been evaluated for antiinflammatory and analgesic activity in acute models. Compounds have also been evaluated for their ulcerogenic potential. Using the computer program, prediction of activity spectra for substances, prediction results and their Pharma Expert software, we have found a correlation between the observed and predicted antiinflammatory activity. PMID:22131629

  1. 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.

  2. 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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-08-01

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

  5. Prediction limits of mobile phone activity modelling

    PubMed Central

    Grauwin, Sebastian; Kallus, Zsófia; Gódor, István; Sobolevsky, Stanislav; Ratti, Carlo

    2017-01-01

    Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also, we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events. PMID:28386443

  6. Amino acid composition predicts prion activity.

    PubMed

    Afsar Minhas, Fayyaz Ul Amir; Ross, Eric D; Ben-Hur, Asa

    2017-04-10

    Many prion-forming proteins contain glutamine/asparagine (Q/N) rich domains, and there are conflicting opinions as to the role of primary sequence in their conversion to the prion form: is this phenomenon driven primarily by amino acid composition, or, as a recent computational analysis suggested, dependent on the presence of short sequence elements with high amyloid-forming potential. The argument for the importance of short sequence elements hinged on the relatively-high accuracy obtained using a method that utilizes a collection of length-six sequence elements with known amyloid-forming potential. We weigh in on this question and demonstrate that when those sequence elements are permuted, even higher accuracy is obtained; we also propose a novel multiple-instance machine learning method that uses sequence composition alone, and achieves better accuracy than all existing prion prediction approaches. While we expect there to be elements of primary sequence that affect the process, our experiments suggest that sequence composition alone is sufficient for predicting protein sequences that are likely to form prions. A web-server for the proposed method is available at http://faculty.pieas.edu.pk/fayyaz/prank.html, and the code for reproducing our experiments is available at http://doi.org/10.5281/zenodo.167136.

  7. Shuttle program. Solar activity prediction of sunspot numbers, predicted solar radio flux

    NASA Technical Reports Server (NTRS)

    Johnson, G. G.; Newman, S. R.

    1980-01-01

    A solar activity prediction technique for monthly mean sunspot numbers over a period of approximately ten years from February 1979 to January 1989 is presented. This includes the predicted maximum epoch of solar cycle 21, approximately January 1980, and the predicted minimum epoch of solar cycle 22, approximately March 1987. Additionally, the solar radio flux 10.7 centimeter smooth values are included for the same time frame using a smooth 13 month empirical relationship. The incentive for predicting solar activity values is the requirement of solar flux data as input to upper atmosphere density models utilized in mission planning satellite orbital lifetime studies.

  8. 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.

  9. Daily update of motor predictions by physical activity.

    PubMed

    Gueugneau, Nicolas; Schweighofer, Nicolas; Papaxanthis, Charalambos

    2015-12-03

    Motor prediction, i.e., the ability to predict the sensory consequences of motor commands, is critical for adapted motor behavior. Like speed or force, the accuracy of motor prediction varies in a 24-hour basis. Although the prevailing view is that basic biological markers regulate this circadian modulation, behavioral factors such as physical activity, itself modulated by the alternation of night and day, can also regulate motor prediction. Here, we propose that physical activity updates motor prediction on a daily basis. We tested our hypothesis by up- and down-regulating physical activity via arm-immobilization and high-intensity training, respectively. Motor prediction was assessed by measuring the timing differences between actual and mental arm movements. Results show that although mental movement time was modulated during the day when the arm was unconstrained, it remained constant when the arm was immobilized. Additionally, increase of physical activity, via release from immobilization or intense bout of training, significantly reduced mental movement time. Finally, mental and actual times were similar in the afternoon in the unconstrained condition, indicating that predicted and actual movements match after sufficient amount of physical activity. Our study supports the view that physical activity calibrates motor predictions on a daily basis.

  10. Ceramide structure predicts tumor ganglioside immunosuppressive activity.

    PubMed Central

    Ladisch, S; Li, R; Olson, E

    1994-01-01

    Molecular determinants of biological activity of gangliosides are generally believed to be carbohydrate in nature. However, our studies of immunomodulation by highly purified naturally occurring tumor gangliosides provide another perspective: while the immunosuppressive activity of gangliosides requires the intact molecule (both carbohydrate and ceramide moieties), ceramide structure strikingly influences ganglioside immunosuppressive activity. Molecular species of human neuroblastoma GD2 ganglioside in which the ceramide contains a shorter fatty acyl chain (C16:0, C18:0) were 6- to 10-fold more active than those with a longer fatty acyl chain (C22:0/C24:1, C24:0). These findings were confirmed in studies of ceramide species of human leukemia sialosylparagloboside and murine lymphoma GalNAcGM1b. Gangliosides that contain shorter-chain fatty acids (and are most immunosuppressive) are known to be preferentially shed by tumor cells. Therefore, the results suggest that the tumor cell is optimized to protect itself from host immune destruction by selective shedding of highly active ceramide species of gangliosides. Images PMID:8127917

  11. Predicting mining activity with parallel genetic algorithms

    USGS Publications Warehouse

    Talaie, S.; Leigh, R.; Louis, S.J.; Raines, G.L.; Beyer, H.G.; O'Reilly, U.M.; Banzhaf, Arnold D.; Blum, W.; Bonabeau, C.; Cantu-Paz, E.W.; ,; ,

    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.

  12. 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.

  13. 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.…

  14. 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.

  15. 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

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

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  17. Polymeric drugs: Advances in the development of pharmacologically active polymers

    PubMed Central

    Li, Jing; Yu, Fei; Chen, Yi; Oupický, David

    2015-01-01

    Synthetic polymers play a critical role in pharmaceutical discovery and development. Current research and applications of pharmaceutical polymers are mainly focused on their functions as excipients and inert carriers of other pharmacologically active agents. This review article surveys recent advances in alternative pharmaceutical use of polymers as pharmacologically active agents known as polymeric drugs. Emphasis is placed on the benefits of polymeric drugs that are associated with their macromolecular character and their ability to explore biologically relevant multivalency processes. We discuss the main therapeutic uses of polymeric drugs as sequestrants, antimicrobials, antivirals, and anticancer and anti-inflammatory agents. PMID:26410809

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

    NASA Astrophysics Data System (ADS)

    Hughes, Jerry

    2012-10-01

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

  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. 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.

  1. Predicting the degradability of waste activated sludge.

    PubMed

    Jones, Richard; Parker, Wayne; Zhu, Henry; Houweling, Dwight; Murthy, Sudhir

    2009-08-01

    The objective of this study was to identify methods for estimating anaerobic digestibility of waste activated sludge (WAS). The WAS streams were generated in three sequencing batch reactors (SBRs) treating municipal wastewater. The wastewater and WAS properties were initially determined through simulation of SBR operation with BioWin (EnviroSim Associates Ltd., Flamborough, Ontario, Canada). Samples of WAS from the SBRs were subsequently characterized through respirometry and batch anaerobic digestion. Respirometry was an effective tool for characterizing the active fraction of WAS and could be a suitable technique for determining sludge composition for input to anaerobic models. Anaerobic digestion of the WAS revealed decreasing methane production and lower chemical oxygen demand removals as the SRT of the sludge increased. BioWin was capable of accurately describing the digestion of the WAS samples for typical digester SRTs. For extended digestion times (i.e., greater than 30 days), some degradation of the endogenous decay products was assumed to achieve accurate simulations for all sludge SRTs.

  2. 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...

  3. 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

  4. 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).

  5. Combining Satellite Observations of Fire Activity and Numerical Weather Prediction to Improve the Prediction of Smoke Emissions

    NASA Astrophysics Data System (ADS)

    Peterson, D. A.; Wang, J.; Hyer, E. J.; Ichoku, C. M.

    2012-12-01

    Smoke emissions estimates used in air quality and visibility forecasting applications are currently limited by the information content of satellite fire observations, and the lack of a skillful short-term forecast of changes in fire activity. This study explores the potential benefits of a recently developed sub-pixel-based calculation of fire radiative power (FRPf) from the MODerate Resolution Imaging Spectroradiometer (MODIS), which provides more precise estimates of the radiant energy (over the retrieved fire area) that in turn, improves estimates of the thermal buoyancy of smoke plumes and may be helpful characterizing the meteorological effects on fire activity for large fire events. Results show that unlike the current FRP product, the incorporation of FRPf produces a statistically significant correlation (R = 0.42) with smoke plume height data provided by the Multi-angle Imaging SpectroRadiometer (MISR) and several meteorological variables, such as surface wind speed and temperature, which may be useful for discerning cases where smoke was injected above the boundary layer. Drawing from recent advances in numerical weather prediction (NWP), this study also examines the meteorological conditions characteristic of fire ignition, growth, decay, and extinction, which are used to develop an automated, 24-hour prediction of satellite fire activity. Satellite fire observations from MODIS and geostationary sensors show that the fire prediction model is an improvement (RMSE reduction of 13 - 20%) over the forecast of persistence commonly used by near-real-time fire emission inventories. The ultimate goal is to combine NWP data and satellite fire observations to improve both analysis and prediction of biomass-burning emissions, through improved understanding of the interactions between fire activity and weather at scales appropriate for operational modeling. This is a critical step toward producing a global fire prediction model and improving operational forecasts of

  6. MSFC solar activity predictions for satellite orbital lifetime estimation

    NASA Technical Reports Server (NTRS)

    Fuler, H. C.; Lundquist, C. A.; Vaughan, W. W.

    1979-01-01

    The procedure to predict solar activity indexes for use in upper atmosphere density models is given together with an example of the performance. The prediction procedure employs a least square linear regression model to generate the predicted smoothed vinculum R sub 13 and geomagnetic vinculum A sub p(13) values. Linear regression equations are then employed to compute corresponding vinculum F sub 10.7(13) solar flux values from the predicted vinculum R sub 13 values. The output is issued principally for satellite orbital lifetime estimations.

  7. 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.

  8. 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

  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.

  10. 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

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

    PubMed

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

    2017-01-01

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

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

    PubMed Central

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

    2017-01-01

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

  13. 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.

  14. 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

  15. 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.

  16. Predicting reading and mathematics from neural activity for feedback learning.

    PubMed

    Peters, Sabine; Van der Meulen, Mara; Zanolie, Kiki; Crone, Eveline A

    2017-01-01

    Although many studies use feedback learning paradigms to study the process of learning in laboratory settings, little is known about their relevance for real-world learning settings such as school. In a large developmental sample (N = 228, 8-25 years), we investigated whether performance and neural activity during a feedback learning task predicted reading and mathematics performance 2 years later. The results indicated that feedback learning performance predicted both reading and mathematics performance. Activity during feedback learning in left superior dorsolateral prefrontal cortex (DLPFC) predicted reading performance, whereas activity in presupplementary motor area/anterior cingulate cortex (pre-SMA/ACC) predicted mathematical performance. Moreover, left superior DLPFC and pre-SMA/ACC activity predicted unique variance in reading and mathematics ability over behavioral testing of feedback learning performance alone. These results provide valuable insights into the relationship between laboratory-based learning tasks and learning in school settings, and the value of neural assessments for prediction of school performance over behavioral testing alone. (PsycINFO Database Record

  17. 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.

  18. 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

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. External validation and prediction employing the predictive squared correlation coefficient test set activity mean vs training set activity mean.

    PubMed

    Schüürmann, Gerrit; Ebert, Ralf-Uwe; Chen, Jingwen; Wang, Bin; Kühne, Ralph

    2008-11-01

    The external prediction capability of quantitative structure-activity relationship (QSAR) models is often quantified using the predictive squared correlation coefficient, q (2). This index relates the predictive residual sum of squares, PRESS, to the activity sum of squares, SS, without postprocessing of the model output, the latter of which is automatically done when calculating the conventional squared correlation coefficient, r (2). According to the current OECD guidelines, q (2) for external validation should be calculated with SS referring to the training set activity mean. Our present findings including a mathematical proof demonstrate that this approach yields a systematic overestimation of the prediction capability that is triggered by the difference between the training and test set activity means. Example calculations with three regression models and data sets taken from literature show further that for external test sets, q (2) based on the training set activity mean may become even larger than r (2). As a consequence, we suggest to always use the test set activity mean when quantifying the external prediction capability through q (2) and to revise the respective OECD guidance document accordingly. The discussion includes a comparison between r (2) and q (2) value ranges and the q (2) statistics for cross-validation.

  5. 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

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

    SciTech Connect

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

    2011-06-01

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

  7. Stepwise advancement versus maximum jumping with headgear activator.

    PubMed

    Wey, Mang Chek; Bendeus, Margareta; Peng, Li; Hägg, Urban; Rabie, A Bakr M; Robinson, Wayne

    2007-06-01

    The aim of this study was to compare the effects of stepwise mandibular advancement versus maximum jumping and extended treatment versus early retention. The material was obtained prospectively and consisted of lateral cephalograms taken at the start (T0), after initial (T1), and at the end (T2) of treatment, from two groups of consecutively treated skeletal Class II patients who had undergone therapy with headgear activators. The first headgear activator group, HGA-S (n=24; mean age 11.9 +/- 1.2 years), was treated for 13 months and had 4-mm mandibular advancement every 3 months. The second headgear activator group, HGA-M (n=31; mean age 11.2 +/- 1.5 years), had maximum jumping, 6-8 mm interincisal opening, for a total of 15.4 months, and with reduced wear for the last 6.9 months. The dropout over 12 months was 41 and 46 per cent, respectively. Pre-treatment growth changes were obtained as a reference. An independent t-test was used to determine differences in baseline dentofacial morphology between the groups, a paired t-test for intra-group comparisons, and an independent t-test to evaluate differences between the groups. The results, in both groups, showed enhanced mandibular prognathism during the initial phase (T0-T1), followed by normal growth (T1-T2), and lower face height enhancement throughout treatment (T0-T2). For both groups, the mandibular plane and occlusal angle increased, possibly enhanced by 'extrusion' of the lower molars. For both groups, maxillary forward growth was restrained only during the initial phase, but the effect remained significant at T2 for the HGA-S group. In the HGA-M group, the lower incisors were protruded, while in the HGA-S group, they were unaffected. The findings indicate that both modes of mandibular jumping resulted in skeletal and dental effects. The length of active treatment seemed to be decisive in maintaining the treatment effects; stepwise advancement had less dental effects.

  8. Active Vibration Reduction of the Advanced Stirling Convertor

    NASA Technical Reports Server (NTRS)

    Wilson, Scott D.; Metscher, Jonathan F.; Schifer, Nicholas A.

    2016-01-01

    Stirling Radioisotope Power Systems (RPS) are being developed as an option to provide power on future space science missions where robotic spacecraft will orbit, flyby, land or rove. A Stirling Radioisotope Generator (SRG) could offer space missions a more efficient power system that uses one fourth of the nuclear fuel and decreases the thermal footprint compared to the current state of the art. The Stirling Cycle Technology Development (SCTD) Project is funded by the RPS Program to developing Stirling-based subsystems, including convertors and controller maturation efforts that have resulted in high fidelity hardware like the Advanced Stirling Radioisotope Generator (ASRG), Advanced Stirling Convertor (ASC), and ASC Controller Unit (ACU). The SCTD Project also performs research to develop less mature technologies with a wide variety of objectives, including increasing temperature capability to enable new environments, improving system reliability or fault tolerance, reducing mass or size, and developing advanced concepts that are mission enabling. Active vibration reduction systems (AVRS), or "balancers", have historically been developed and characterized to provide fault tolerance for generator designs that incorporate dual-opposed Stirling convertors or enable single convertor, or small RPS, missions. Balancers reduce the dynamic disturbance forces created by the power piston and displacer internal moving components of a single operating convertor to meet spacecraft requirements for induced disturbance force. To improve fault tolerance for dual-opposed configurations and enable single convertor configurations, a breadboard AVRS was implemented on the Advanced Stirling Convertor (ASC). The AVRS included a linear motor, a motor mount, and a closed-loop controller able to balance out the transmitted peak dynamic disturbance using acceleration feedback. Test objectives included quantifying power and mass penalty and reduction in transmitted force over a range of ASC

  9. Active Vibration Reduction of the Advanced Stirling Convertor

    NASA Technical Reports Server (NTRS)

    Wilson, Scott D.; Metscher, Jonathan F.; Schifer, Nicholas A.

    2016-01-01

    Stirling Radioisotope Power Systems (RPS) are being developed as an option to provide power on future space science missions where robotic spacecraft will orbit, flyby, land or rove. A Stirling Radioisotope Generator (SRG) could offer space missions a more efficient power system that uses one fourth of the nuclear fuel and decreases the thermal footprint compared to the current state of the art. The Stirling Cycle Technology Development (SCTD) Project is funded by the RPS Program to developing Stirling-based subsystems, including convertors and controller maturation efforts that have resulted in high fidelity hardware like the Advanced Stirling Radioisotope Generator (ASRG), Advanced Stirling Convertor (ASC), and ASC Controller Unit (ACU). The SCTD Project also performs research to develop less mature technologies with a wide variety of objectives, including increasing temperature capability to enable new environments, improving system reliability or fault tolerance, reducing mass or size, and developing advanced concepts that are mission enabling. Active vibration reduction systems (AVRS), or "balancers", have historically been developed and characterized to provide fault tolerance for generator designs that incorporate dual-opposed Stirling convertors or enable single convertor, or small RPS, missions. Balancers reduce the dynamic disturbance forces created by the power piston and displacer internal moving components of a single operating convertor to meet spacecraft requirements for induced disturbance force. To improve fault tolerance for dual-opposed configurations and enable single convertor configurations, a breadboard AVRS was implemented on the Advanced Stirling Convertor (ASC). The AVRS included a linear motor, a motor mount, and a closed-loop controller able to balance out the transmitted peak dynamic disturbance using acceleration feedback. Test objectives included quantifying power and mass penalty and reduction in transmitted force over a range of ASC

  10. 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.

  11. Physical Activity Predicts Performance in an Unpracticed Bimanual Coordination Task

    PubMed Central

    Boisgontier, Matthieu P.; Serbruyns, Leen; Swinnen, Stephan P.

    2017-01-01

    Practice of a given physical activity is known to improve the motor skills related to this activity. However, whether unrelated skills are also improved is still unclear. To test the impact of physical activity on an unpracticed motor task, 26 young adults completed the international physical activity questionnaire and performed a bimanual coordination task they had never practiced before. Results showed that higher total physical activity predicted higher performance in the bimanual task, controlling for multiple factors such as age, physical inactivity, music practice, and computer games practice. Linear mixed models allowed this effect of physical activity to be generalized to a large population of bimanual coordination conditions. This finding runs counter to the notion that generalized motor abilities do not exist and supports the existence of a “learning to learn” skill that could be improved through physical activity and that impacts performance in tasks that are not necessarily related to the practiced activity. PMID:28265253

  12. 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.

  13. 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.

  14. Physical activity behavior predicts endogenous pain modulation in older adults.

    PubMed

    Naugle, Kelly M; Ohlman, Thomas; Naugle, Keith E; Riley, Zachary A; Keith, NiCole R

    2017-03-01

    Older adults compared with younger adults are characterized by greater endogenous pain facilitation and a reduced capacity to endogenously inhibit pain, potentially placing them at a greater risk for chronic pain. Previous research suggests that higher levels of self-reported physical activity are associated with more effective pain inhibition and less pain facilitation on quantitative sensory tests in healthy adults. However, no studies have directly tested the relationship between physical activity behavior and pain modulatory function in older adults. This study examined whether objective measures of physical activity behavior cross-sectionally predicted pain inhibitory function on the conditioned pain modulation (CPM) test and pain facilitation on the temporal summation (TS) test in healthy older adults. Fifty-one older adults wore an accelerometer on the hip for 7 days and completed the CPM and TS tests. Measures of sedentary time, light physical activity (LPA), and moderate to vigorous physical activity (MVPA) were obtained from the accelerometer. Hierarchical linear regressions were conducted to determine the relationship of TS and CPM with levels of physical activity, while controlling for demographic, psychological, and test variables. The results indicated that sedentary time and LPA significantly predicted pain inhibitory function on the CPM test, with less sedentary time and greater LPA per day associated with greater pain inhibitory capacity. Additionally, MVPA predicted pain facilitation on the TS test, with greater MVPA associated with less TS of pain. These results suggest that different types of physical activity behavior may differentially impact pain inhibitory and facilitatory processes in older adults.

  15. 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

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

    PubMed Central

    Jeon, Yong-Jin; Kim, Gyoung-Mo

    2017-01-01

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

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

    PubMed

    Jeon, Yong-Jin; Kim, Gyoung-Mo

    2017-02-01

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

  18. 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.

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

    PubMed

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

    2013-01-01

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

  20. [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.

  1. 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.

  2. 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.

  3. Using Recent Planetary Science Data to Develop Advanced Undergraduate Physics and Astronomy Activities

    NASA Astrophysics Data System (ADS)

    Steckloff, Jordan; Lindell, Rebecca

    2016-10-01

    Teaching science by having students manipulate real data is a popular trend in astronomy and planetary science education. However, many existing activities simply couple this data with traditional "cookbook" style verification labs. As with most topics within science, this instructional technique does not enhance the average students' understanding of the phenomena being studied. Here we present a methodology for developing "science by doing" activities that incorporate the latest discoveries in planetary science with up-to-date constructivist pedagogy to teach advanced concepts in Physics and Astronomy. In our methodology, students are first guided to understand, analyze, and plot real raw scientific data; develop and test physical and computational models to understand and interpret the data; finally use their models to make predictions about the topic being studied and test it with real data.To date, two activities have been developed according to this methodology: Understanding Asteroids through their Light Curves (hereafter "Asteroid Activity"), and Understanding Exoplanetary Systems through Simple Harmonic Motion (hereafter "Exoplanet Activity"). The Asteroid Activity allows students to explore light curves available on the Asteroid Light Curve Database (ALCDB) to discover general properties of asteroids, including their internal structure, strength, and mechanism of asteroid moon formation. The Exoplanet Activity allows students to investigate the masses and semi-major axes of exoplanets in a system by comparing the radial velocity motion of their host star to that of a coupled simple harmonic oscillator. Students then explore how noncircular orbits lead to deviations from simple harmonic motion. These activities will be field tested during the Fall 2016 semester in an advanced undergraduate mechanics and astronomy courses at a large Midwestern STEM-focused university. We will present the development methodologies for these activities, description of the

  4. Predicting participation in meaningful activity for older adults with cancer

    PubMed Central

    Pergolotti, Mackenzi; Cutchin, Malcolm P.; Muss, Hyman B.

    2015-01-01

    Purpose Participation in activity that is personally meaningful leads to improved emotional and physical well-being and quality of life. However, little is known about what predicts participation in meaningful activity by older adults with cancer. Methods Seventy-one adults aged 65 years and older with a diagnosis of cancer were enrolled. All adults were evaluated with the following: a brief geriatric assessment, the meaningful activity participation assessment (MAPA), and the Possibilities for Activity Scale (PActS). The MAPA measures participation in meaningful activity, and the PActS measures what older adults believe they should and could be doing. A regression approach was used to assess the predictors of meaningful activity participation. Results The PActS (B = .56, p < .001) was the strongest predictor of meaningful activity participation. Conclusions What older adults with cancer feel they should and could do significantly predicted meaningful participation in activities above and beyond clinical and demographic factors. In future research, perceptions of possibilities for activity may be useful in the design of interventions targeted to improve meaningful participation in older adults with cancer. PMID:25381123

  5. Prefrontal Brain Activity Predicts Temporally Extended Decision-Making Behavior

    ERIC Educational Resources Information Center

    Yarkoni, Tal; Braver, Todd S.; Gray, Jeremy R.; Green, Leonard

    2005-01-01

    Although functional neuroimaging studies of human decision-making processes are increasingly common, most of the research in this area has relied on passive tasks that generate little individual variability. Relatively little attention has been paid to the ability of brain activity to predict overt behavior. Using functional magnetic resonance…

  6. 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) ...

  7. 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…

  8. 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

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

    PubMed

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

    2011-01-01

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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Predicting brain activity using a Bayesian spatial model.

    PubMed

    Derado, Gordana; Bowman, F Dubois; Zhang, Lijun

    2013-08-01

    Increasing the clinical applicability of functional neuroimaging technology is an emerging objective, e.g. for diagnostic and treatment purposes. We propose a novel Bayesian spatial hierarchical framework for predicting follow-up neural activity based on an individual's baseline functional neuroimaging data. Our approach attempts to overcome some shortcomings of the modeling methods used in other neuroimaging settings, by borrowing strength from the spatial correlations present in the data. Our proposed methodology is applicable to data from various imaging modalities including functional magnetic resonance imaging and positron emission tomography, and we provide an illustration here using positron emission tomography data from a study of Alzheimer's disease to predict disease progression.

  16. 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

  17. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  19. 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.

  20. 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.

  1. Predicting myelinated axon activation using spatial characteristics of the extracellular field

    PubMed Central

    Peterson, EJ; Izad, O; Tyler, DJ

    2011-01-01

    Computation time required for modeling the nonlinear response of an axon to an applied electric field is a significant limitation to optimizing a large number of neural interface design parameters through use of advanced computer algorithms. This paper introduces two methods of predicting axon activation that incorporate a threshold that includes the magnitude of the extracellular potential to achieve increased accuracy over previous computationally efficient methods. Each method employs the use of a modified driving function that includes the second spatial difference of the applied extracellular voltage to predict the electrical excitation of a nerve. The first method uses the second spatial difference taken at a single node of Ranvier, while the second uses a weighted sum of the second spatial differences taken at all nodes of Ranvier. This study quantifies prediction accuracy for cases with single and multiple point source stimulating electrodes. While both new methods address the major criticism of linearized prediction models, the weighted sum method provides the most robust response across single and multiple point sources. These methods eimprove prediction of axon activation based on properties of the applied field in a computationally efficient manner. PMID:21750371

  2. 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

  3. 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.

  4. 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

  5. A new fingerprint to predict nonribosomal peptides activity

    NASA Astrophysics Data System (ADS)

    Abdo, Ammar; Caboche, Ségolène; Leclère, Valérie; Jacques, Philippe; Pupin, Maude

    2012-10-01

    Bacteria and fungi use a set of enzymes called nonribosomal peptide synthetases to provide a wide range of natural peptides displaying structural and biological diversity. So, nonribosomal peptides (NRPs) are the basis for some efficient drugs. While discovering new NRPs is very desirable, the process of identifying their biological activity to be used as drugs is a challenge. In this paper, we present a novel peptide fingerprint based on monomer composition (MCFP) of NRPs. MCFP is a novel method for obtaining a representative description of NRP structures from their monomer composition in fingerprint form. Experiments with Norine NRPs database and MCFP show high prediction accuracy (>93 %). Also a high recall rate (>82 %) is obtained when MCFP is used for screening NRPs database. From this study it appears that our fingerprint, built from monomer composition, allows an effective screening and prediction of biological activities of NRPs database.

  6. DPIV prediction of flow induced platelet activation-comparison to numerical predictions.

    PubMed

    Raz, Sagi; Einav, Shmuel; Alemu, Yared; Bluestein, Danny

    2007-04-01

    Flow induced platelet activation (PA) can lead to platelet aggregation, deposition onto the blood vessel wall, and thrombus formation. PA was thoroughly studied under unidirectional flow conditions. However, in regions of complex flow, where the platelet is exposed to varying levels of shear stress for varying durations, the relationship between flow and PA is not well understood. Numerical models were developed for studying flow induced PA resulting from stress histories along Lagrangian trajectories in the flow field. However, experimental validation techniques such as Digital Particle Image Velocimetry (DPIV) were not extended to include such models. In this study, a general experimental tool for PA analysis by means of continuous DPIV was utilized and compared to numerical simulation in a model of coronary stenosis. A scaled up (5:1) 84% eccentric and axisymetric coronary stenosis model was used for analysis of shear stress and exposure time along particle trajectories. Flow induced PA was measured using the PA State (PAS) assay. An algorithm for computing the PA level in pertinent trajectories was developed as a tool for extracting information from DPIV measurements for predicting the flow induced thrombogenic potential. CFD, DPIV and PAS assay results agreed well in predicting the level of PA. In addition, the same trend predicted by the DPIV was measured in vitro using the Platelet Activity State (PAS) assay, namely, that the symmetric stenosis activated the platelets more as compared to the eccentric stenosis.

  7. 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…

  8. 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.

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

    DTIC Science & Technology

    2015-08-24

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

  10. 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

  11. 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…

  12. Planning for subacute care: predicting demand using acute activity data.

    PubMed

    Green, Janette P; McNamee, Jennifer P; Kobel, Conrad; Seraji, Md Habibur R; Lawrence, Suanne J

    2016-04-07

    Objective The aim of the present study was to develop a robust model that uses the concept of 'rehabilitation-sensitive' Diagnosis Related Groups (DRGs) in predicting demand for rehabilitation and geriatric evaluation and management (GEM) care following acute in-patient episodes provided in Australian hospitals.Methods The model was developed using statistical analyses of national datasets, informed by a panel of expert clinicians and jurisdictional advice. Logistic regression analysis was undertaken using acute in-patient data, published national hospital statistics and data from the Australasian Rehabilitation Outcomes Centre.Results The predictive model comprises tables of probabilities that patients will require rehabilitation or GEM care after an acute episode, with columns defined by age group and rows defined by grouped Australian Refined (AR)-DRGs.Conclusions The existing concept of rehabilitation-sensitive DRGs was revised and extended. When applied to national data, the model provided a conservative estimate of 83% of the activity actually provided. An example demonstrates the application of the model for service planning.What is known about the topic? Health service planning is core business for jurisdictions and local areas. With populations ageing and an acknowledgement of the underservicing of subacute care, it is timely to find improved methods of estimating demand for this type of care. Traditionally, age-sex standardised utilisation rates for individual DRGs have been applied to Australian Bureau of Statistics (ABS) population projections to predict the future need for subacute services. Improved predictions became possible when some AR-DRGs were designated 'rehabilitation-sensitive'. This improved methodology has been used in several Australian jurisdictions.What does this paper add? This paper presents a new tool, or model, to predict demand for rehabilitation and GEM services based on in-patient acute activity. In this model, the methodology

  13. Spontaneous brain activity predicts learning ability of foreign sounds.

    PubMed

    Ventura-Campos, Noelia; Sanjuán, Ana; González, Julio; Palomar-García, María-Ángeles; Rodríguez-Pujadas, Aina; Sebastián-Gallés, Núria; Deco, Gustavo; Ávila, César

    2013-05-29

    Can learning capacity of the human brain be predicted from initial spontaneous functional connectivity (FC) between brain areas involved in a task? We combined task-related functional magnetic resonance imaging (fMRI) and resting-state fMRI (rs-fMRI) before and after training with a Hindi dental-retroflex nonnative contrast. Previous fMRI results were replicated, demonstrating that this learning recruited the left insula/frontal operculum and the left superior parietal lobe, among other areas of the brain. Crucially, resting-state FC (rs-FC) between these two areas at pretraining predicted individual differences in learning outcomes after distributed (Experiment 1) and intensive training (Experiment 2). Furthermore, this rs-FC was reduced at posttraining, a change that may also account for learning. Finally, resting-state network analyses showed that the mechanism underlying this reduction of rs-FC was mainly a transfer in intrinsic activity of the left frontal operculum/anterior insula from the left frontoparietal network to the salience network. Thus, rs-FC may contribute to predict learning ability and to understand how learning modifies the functioning of the brain. The discovery of this correspondence between initial spontaneous brain activity in task-related areas and posttraining performance opens new avenues to find predictors of learning capacities in the brain using task-related fMRI and rs-fMRI combined.

  14. Loneliness Predicts Reduced Physical Activity: Cross-Sectional & Longitudinal Analyses

    PubMed Central

    Hawkley, Louise C.; Thisted, Ronald A.; Cacioppo, John T.

    2009-01-01

    Objective To determine cross-sectional and prospective associations between loneliness and physical activity, and to evaluate the roles of social control and emotion regulation as mediators of these associations. Design A population-based sample of 229 White, Black, and Hispanic men and women, age 50 to 68 years at study onset, were tested annually for each of 3 years. Main Outcome Measures Physical activity probability, and changes in physical activity probability over a 3-year period. Results Replicating and extending prior cross-sectional research, loneliness was associated with a significantly reduced odds of physical activity (OR = 0.65 per SD of loneliness) net of sociodemographic variables (age, gender, ethnicity, education, income), psychosocial variables (depressive symptoms, perceived stress, hostility, social support), and self-rated health. This association was mediated by hedonic emotion regulation, but not by social control as indexed by measures of social network size, marital status, contact with close ties, group membership, or religious group affiliation. Longitudinal analyses revealed that loneliness predicted diminished odds of physical activity in the next two years (OR = 0.61), and greater likelihood of transitioning from physical activity to inactivity (OR = 1.58). Conclusion Loneliness among middle and older age adults is an independent risk factor for physical inactivity and increases the likelihood that physical activity will be discontinued over time. PMID:19450042

  15. Cortical activity predicts good variation in human motor output.

    PubMed

    Babikian, Sarine; Kanso, Eva; Kutch, Jason J

    2017-02-04

    Human movement patterns have been shown to be particularly variable if many combinations of activity in different muscles all achieve the same task goal (i.e., are goal-equivalent). The nervous system appears to automatically vary its output among goal-equivalent combinations of muscle activity to minimize muscle fatigue or distribute tissue loading, but the neural mechanism of this "good" variation is unknown. Here we use a bimanual finger task, electroencephalography (EEG), and machine learning to determine if cortical signals can predict goal-equivalent variation in finger force output. 18 healthy participants applied left and right index finger forces to repeatedly perform a task that involved matching a total (sum of right and left) finger force. As in previous studies, we observed significantly more variability in goal-equivalent muscle activity across task repetitions compared to variability in muscle activity that would not achieve the goal: participants achieved the task in some repetitions with more right finger force and less left finger force (right > left) and in other repetitions with less right finger force and more left finger force (left > right). We found that EEG signals from the 500 milliseconds (ms) prior to each task repetition could make a significant prediction of which repetitions would have right > left and which would have left > right. We also found that cortical maps of sites contributing to the prediction contain both motor and pre-motor representation in the appropriate hemisphere. Thus, goal-equivalent variation in motor output may be implemented at a cortical level.

  16. 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.

  17. 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.

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

    PubMed

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

    2013-12-01

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

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

    PubMed

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

    2001-04-01

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

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

    PubMed

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

    2015-02-01

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

  1. 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...

  2. 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...

  3. Motor cortex activity predicts response alternation during sensorimotor decisions

    PubMed Central

    Pape, Anna-Antonia; Siegel, Markus

    2016-01-01

    Our actions are constantly guided by decisions based on sensory information. The motor cortex is traditionally viewed as the final output stage in this process, merely executing motor responses based on these decisions. However, it is not clear if, beyond this role, the motor cortex itself impacts response selection. Here, we report activity fluctuations over motor cortex measured using MEG, which are unrelated to choice content and predict responses to a visuomotor task seconds before decisions are made. These fluctuations are strongly influenced by the previous trial's response and predict a tendency to switch between response alternatives for consecutive decisions. This alternation behaviour depends on the size of neural signals still present from the previous response. Our results uncover a response-alternation bias in sensorimotor decision making. Furthermore, they suggest that motor cortex is more than an output stage and instead shapes response selection during sensorimotor decision making. PMID:27713396

  4. Neural activity predicts attitude change in cognitive dissonance.

    PubMed

    van Veen, Vincent; Krug, Marie K; Schooler, Jonathan W; Carter, Cameron S

    2009-11-01

    When our actions conflict with our prior attitudes, we often change our attitudes to be more consistent with our actions. This phenomenon, known as cognitive dissonance, is considered to be one of the most influential theories in psychology. However, the neural basis of this phenomenon is unknown. Using a Solomon four-group design, we scanned participants with functional MRI while they argued that the uncomfortable scanner environment was nevertheless a pleasant experience. We found that cognitive dissonance engaged the dorsal anterior cingulate cortex and anterior insula; furthermore, we found that the activation of these regions tightly predicted participants' subsequent attitude change. These effects were not observed in a control group. Our findings elucidate the neural representation of cognitive dissonance, and support the role of the anterior cingulate cortex in detecting cognitive conflict and the neural prediction of attitude change.

  5. Proposed neutron activation analysis facilities in the Advanced Neutron Source

    SciTech Connect

    Robinson, L.; Dyer, F.F.; Emery, J.F.

    1990-01-01

    A number of analytical chemistry experimental facilities are being proposed for the Advanced Neutron Source. Experimental capabilities will include gamma-ray analysis and neutron depth profiling. This paper describes the various systems proposed and some of their important characteristics.

  6. 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

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

    PubMed Central

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

    2015-01-01

    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

  8. Building gene expression signatures indicative of transcription factor activation to predict AOP modulation

    EPA Science Inventory

    Building gene expression signatures indicative of transcription factor activation to predict AOP modulation Adverse outcome pathways (AOPs) are a framework for predicting quantitative relationships between molecular initiatin...

  9. A prediction of accelerator-produced activation products.

    PubMed

    Culp, Todd

    2007-02-01

    The operational radiation protection issues associated with the Z-Machine accelerator located at Sandia National Laboratories are large: a variety of materials can be placed into the machine; these materials can be subjected to a variety of nuclear reactions, producing a variety of activation products. Without full understanding of the most likely contaminants, a realistic identification of the radiological hazards and appropriate controls is not possible. This paper presents a process developed to provide a realistic prediction of the accelerator-produced radionuclides of interest.

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

    PubMed Central

    2012-01-01

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

  11. 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

  12. XRCC2 as a predictive biomarker for radioresistance in locally advanced rectal cancer patients undergoing preoperative radiotherapy

    PubMed Central

    Qin, Chang-Jiang; Song, Xin-Ming; Chen, Zhi-Hui; Ren, Xue-Qun; Xu, Kai-Wu; Jing, Hong; He, Yu-Long

    2015-01-01

    XRCC2 has been shown to increase the radioresistance of some cancers. Here, XRCC2 expression was investigated as a predictor of preoperative radiotherapy (PRT) treatment response in locally advanced rectal cancer (LARC). XRCC2 was found to be overexpressed in rectal cancer tissues resected from patients who underwent surgery without PRT. In addition, overall survival for LARC patients was improved in XRCC2-negative patients compared with XRCC2-positive patients after treatment with PRT (P < 0.001). XRCC2 expression was also associated with an increase in LARC radioresistance. Conversely, XRCC2-deficient cancer cells were more sensitive to irradiation in vitro, and a higher proportion of these cells underwent cell death induced by G2/M phase arrest and apoptosis. When XRCC2 was knocked down, the repair of DNA double-strand breaks caused by irradiation was impaired. Therefore, XRCC2 may increases LARC radioresistance by repairing DNA double-strand breaks and preventing cancer cell apoptosis. Moreover, the present data suggest that XRCC2 is a useful predictive biomarker of PRT treatment response in LARC patients. Thus, inhibition of XRCC2 expression or activity represents a potential therapeutic strategy for improving PRT response in LARC patients. PMID:26320178

  13. 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

  14. Working Memory-Related Neural Activity Predicts Future Smoking Relapse

    PubMed Central

    Loughead, James; Wileyto, E Paul; Ruparel, Kosha; Falcone, Mary; Hopson, Ryan; Gur, Ruben; Lerman, Caryn

    2015-01-01

    Brief abstinence from smoking impairs cognition, particularly executive function, and this has a role in relapse to smoking. This study examined whether working memory-related brain activity predicts subsequent smoking relapse above and beyond standard clinical and behavioral measures. Eighty treatment-seeking smokers completed two functional magnetic resonance imaging sessions (smoking satiety vs 24 h abstinence challenge) during performance of a visual N-back task. Brief counseling and a short-term quit attempt followed. Relapse during the first 7 days was biochemically confirmed by the presence of the nicotine metabolite cotinine. Mean percent blood oxygen level-dependent (BOLD) signal change was extracted from a priori regions of interest: bilateral dorsolateral prefrontal cortex (DLPFC), medial frontal/cingulate gyrus, posterior cingulate cortex (PCC), and ventromedial prefrontal cortex. Signal from these brain regions and additional clinical measures were used to model outcome status, which was then validated with resampling techniques. Relapse to smoking was predicted by increased withdrawal symptoms, decreased left DLPFC and increased PCC BOLD percent signal change (abstinence vs smoking satiety). Receiver operating characteristic analysis demonstrated 81% area under the curve using these predictors, a significant improvement over the model with clinical variables only. The combination of abstinence-induced decreases in left DLPFC activation and reduced suppression of PCC may be a prognostic marker for poor outcome, specifically early smoking relapse. PMID:25469682

  15. 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

  16. Adding structure to the transition process to advanced mathematical activity

    NASA Astrophysics Data System (ADS)

    Engelbrecht, Johann

    2010-03-01

    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 deductive reasoning, required in advanced mathematics. It is necessary to assist students in this transition process, in moving from general to mathematical thinking. In this article some structure is suggested for this transition period. This essay is an argumentative exposition supported by personal experience and international literature. This makes this study theoretical rather than empirical.

  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. Functional Embedding Predicts the Variability of Neural Activity

    PubMed Central

    Mišić, Bratislav; Vakorin, Vasily A.; Paus, Tomáš; McIntosh, Anthony R.

    2011-01-01

    Neural activity is irregular and unpredictable, yet little is known about why this is the case and how this property relates to the functional architecture of the brain. Here we show that the variability of a region’s activity systematically varies according to its topological role in functional networks. We recorded the resting-state electroencephalogram (EEG) and constructed undirected graphs of functional networks. We measured the centrality of each node in terms of the number of connections it makes (degree), the ease with which the node can be reached from other nodes in the network (efficiency) and the tendency of the node to occupy a position on the shortest paths between other pairs of nodes in the network (betweenness). As a proxy for variability, we estimated the information content of neural activity using multiscale entropy analysis. We found that the rate at which information was generated was largely predicted by centrality. Namely, nodes with greater degree, betweenness, and efficiency were more likely to have high information content, while peripheral nodes had relatively low information content. These results suggest that the variability of regional activity reflects functional embedding. PMID:22164135

  19. 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

  20. Incorporating an advanced aerosol activation parameterization into WRF-CAM5: Model evaluation and parameterization intercomparison: An Advanced Aerosol Activation Scheme

    SciTech Connect

    Zhang, Yang; Zhang, Xin; Wang, Kai; He, Jian; Leung, L. Ruby; 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

  1. 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…

  2. 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…

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

    PubMed

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

    2015-03-01

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

  4. 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.

  5. Pallidal spiking activity reflects learning dynamics and predicts performance

    PubMed Central

    Noblejas, Maria Imelda; Mizrahi, Aviv D.; Dauber, Omer; Bergman, Hagai

    2016-01-01

    The basal ganglia (BG) network has been divided into interacting actor and critic components, modulating the probabilities of different state–action combinations through learning. Most models of learning and decision making in the BG focus on the roles of the striatum and its dopaminergic inputs, commonly overlooking the complexities and interactions of BG downstream nuclei. In this study, we aimed to reveal the learning-related activity of the external segment of the globus pallidus (GPe), a downstream structure whose computational role has remained relatively unexplored. Recording from monkeys engaged in a deterministic three-choice reversal learning task, we found that changes in GPe discharge rates predicted subsequent behavioral shifts on a trial-by-trial basis. Furthermore, the activity following the shift encoded whether it resulted in reward or not. The frequent changes in stimulus–outcome contingencies (i.e., reversals) allowed us to examine the learning-related neural activity and show that GPe discharge rates closely matched across-trial learning dynamics. Additionally, firing rates exhibited a linear decrease in sequences of correct responses, possibly reflecting a gradual shift from goal-directed execution to automaticity. Thus, modulations in GPe spiking activity are highest for attention-demanding aspects of behavior (i.e., switching choices) and decrease as attentional demands decline (i.e., as performance becomes automatic). These findings are contrasted with results from striatal tonically active neurons, which show none of these task-related modulations. Our results demonstrate that GPe, commonly studied in motor contexts, takes part in cognitive functions, in which movement plays a marginal role. PMID:27671661

  6. Autonomic activity during sleep predicts memory consolidation in humans

    PubMed Central

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

    2016-01-01

    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

  7. 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.

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

    PubMed

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

    2017-01-01

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

  9. 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

  10. 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.

  11. 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,…

  12. 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

  13. Prediction of oxygen uptake dynamics by machine learning analysis of wearable sensors during activities of daily living

    PubMed Central

    Beltrame, T.; Amelard, R.; Wong, A.; Hughson, R. L.

    2017-01-01

    Currently, oxygen uptake () is the most precise means of investigating aerobic fitness and level of physical activity; however, can only be directly measured in supervised conditions. With the advancement of new wearable sensor technologies and data processing approaches, it is possible to accurately infer work rate and predict during activities of daily living (ADL). The main objective of this study was to develop and verify the methods required to predict and investigate the dynamics during ADL. The variables derived from the wearable sensors were used to create a predictor based on a random forest method. The temporal dynamics were assessed by the mean normalized gain amplitude (MNG) obtained from frequency domain analysis. The MNG provides a means to assess aerobic fitness. The predicted during ADL was strongly correlated (r = 0.87, P < 0.001) with the measured and the prediction bias was 0.2 ml·min−1·kg−1. The MNG calculated based on predicted was strongly correlated (r = 0.71, P < 0.001) with MNG calculated based on measured data. This new technology provides an important advance in ambulatory and continuous assessment of aerobic fitness with potential for future applications such as the early detection of deterioration of physical health. PMID:28378815

  14. Prediction of oxygen uptake dynamics by machine learning analysis of wearable sensors during activities of daily living.

    PubMed

    Beltrame, T; Amelard, R; Wong, A; Hughson, R L

    2017-04-05

    Currently, oxygen uptake () is the most precise means of investigating aerobic fitness and level of physical activity; however, can only be directly measured in supervised conditions. With the advancement of new wearable sensor technologies and data processing approaches, it is possible to accurately infer work rate and predict during activities of daily living (ADL). The main objective of this study was to develop and verify the methods required to predict and investigate the dynamics during ADL. The variables derived from the wearable sensors were used to create a predictor based on a random forest method. The temporal dynamics were assessed by the mean normalized gain amplitude (MNG) obtained from frequency domain analysis. The MNG provides a means to assess aerobic fitness. The predicted during ADL was strongly correlated (r = 0.87, P < 0.001) with the measured and the prediction bias was 0.2 ml·min(-1)·kg(-1). The MNG calculated based on predicted was strongly correlated (r = 0.71, P < 0.001) with MNG calculated based on measured data. This new technology provides an important advance in ambulatory and continuous assessment of aerobic fitness with potential for future applications such as the early detection of deterioration of physical health.

  15. Medial Temporal Lobe Activity Predicts Successful Relational Memory Binding

    PubMed Central

    Hannula, Deborah E.; Ranganath, Charan

    2009-01-01

    Previous neuropsychological findings have implicated medial temporal lobe (MTL) structures in retaining object-location relations over the course of short delays, but MTL effects have not always been reported in neuroimaging investigations with similar short-term memory requirements. Here, we used event-related functional magnetic resonance imaging to test the hypothesis that the hippocampus and related MTL structures support accurate retention of relational memory representations, even across short delays. On every trial, four objects were presented, each in one of nine possible locations of a three-dimensional grid. Participants were to mentally rotate the grid and then maintain the rotated representation in anticipation of a test stimulus: a rendering of the grid, rotated 90° from the original viewpoint. The test stimulus was either a “match” display, in which object-location relations were intact, or a “mismatch” display, in which one object occupied a new, previously unfilled location (mismatch position), or two objects had swapped locations (mismatch swap). Encoding phase activation in anterior and posterior regions of the left hippocampus, and in bilateral perirhinal cortex, predicted subsequent accuracy on the short-term memory decision, as did bilateral posterior hippocampal activity after the test stimulus. Notably, activation in these posterior hippocampal regions was also sensitive to the degree to which object-location bindings were preserved in the test stimulus; activation was greatest for match displays, followed by mismatch-position displays, and finally mismatch-swap displays. These results indicate that the hippocampus and related MTL structures contribute to successful encoding and retrieval of relational information in visual short-term memory. PMID:18171929

  16. 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…

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

    DTIC Science & Technology

    2015-10-01

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

  18. Binding Activity Prediction of Cyclin-Dependent Inhibitors.

    PubMed

    Saha, Indrajit; Rak, Benedykt; Bhowmick, Shib Sankar; Maulik, Ujjwal; Bhattacharjee, Debotosh; Koch, Uwe; Lazniewski, Michal; Plewczynski, Dariusz

    2015-07-27

    The Cyclin-Dependent Kinases (CDKs) are the core components coordinating eukaryotic cell division cycle. Generally the crystal structure of CDKs provides information on possible molecular mechanisms of ligand binding. However, reliable and robust estimation of ligand binding activity has been a challenging task in drug design. In this regard, various machine learning techniques, such as Support Vector Machine, Naive Bayesian classifier, Decision Tree, and K-Nearest Neighbor classifier, have been used. The performance of these heterogeneous classification techniques depends on proper selection of features from the data set. This fact motivated us to propose an integrated classification technique using Genetic Algorithm (GA), Rotational Feature Selection (RFS) scheme, and Ensemble of Machine Learning methods, named as the Genetic Algorithm integrated Rotational Ensemble based classification technique, for the prediction of ligand binding activity of CDKs. This technique can automatically find the important features and the ensemble size. For this purpose, GA encodes the features and ensemble size in a chromosome as a binary string. Such encoded features are then used to create diverse sets of training points using RFS in order to train the machine learning method multiple times. The RFS scheme works on Principal Component Analysis (PCA) to preserve the variability information of the rotational nonoverlapping subsets of original data. Thereafter, the testing points are fed to the different instances of trained machine learning method in order to produce the ensemble result. Here accuracy is computed as a final result after 10-fold cross validation, which also used as an objective function for GA to maximize. The effectiveness of the proposed classification technique has been demonstrated quantitatively and visually in comparison with different machine learning methods for 16 ligand binding CDK docking and rescoring data sets. In addition, the best possible features

  19. 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

  20. Temsirolimus in advanced leiomyosarcomas: patterns of response and correlation with the activation of the mammalian target of rapamycin pathway.

    PubMed

    Italiano, Antoine; Kind, Michèle; Stoeckle, Eberhard; Jones, Natalie; Coindre, Jean-Michel; Bui, Binh

    2011-06-01

    Preclinical data have indicated that alteration of PTEN and activation of the mammalian target of rapamycin (mTOR) pathway play a crucial role in the oncogenesis of leiomyosarcoma. The objective of this exploratory study was to assess the clinical role of mTOR inhibition in patients with advanced leiomyosarcoma refractory to standard chemotherapy. Patients with advanced leiomyosarcoma were treated with temsirolimus and consented to retrospective collection of data from their medical records and analysis of archival tumor specimens. Tumor response was determined according to the response evaluation criteria in solid tumor (RECIST) and Choi criteria. Tumors were assessed for immunohistochemical evidence of PTEN loss of expression and mTOR activation. Six patients participated in the study. According to the RECIST, three patients had stable disease and three patients had progressive disease. The three patients with RECIST stable disease had partial response according to the Choi criteria. Partial response according to the Choi criteria was associated with clinical improvement and biological signs of temsirolimus antitumor activity. The immunohistochemical status of PTEN and phosphorylated S6 ribosomal protein was not predictive of the outcome. This exploratory study indicates antitumor activity of temsirolimus in leiomyosarcoma, possibly through a mechanism involving aberration of the PTEN gene. Further investigations of the phosphoinositide 3-kinases/PTEN/Akt/mTOR pathway are needed to explore the role of mTOR inhibitors, either alone or in combination, in patients with advanced sarcoma.

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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.

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

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew J.; Sankararaman, Shankar

    2013-01-01

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

  9. 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.

  10. 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

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

    PubMed Central

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

    2016-01-01

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

  12. Advances in neuromagnetic instrumentation and studies of spontaneous brain activity.

    PubMed

    Williamson, S J; Kaufman, L

    1989-01-01

    Rapid progress in neuromagnetic technology has been achieved during the past two years with the introduction of a method for accurately indicating magnetic sensor locations with respect to a head-based coordinate system and the advent of refrigerator-cooled sensors and larger arrays of sensors. These make possible the real-time monitoring of evoked activity at several widely separated locations over the scalp, thus revealing sequential activity in, e.g., sensory-motor tasks. Arrays of magnetic sensors also provide sufficient information to locate the sources of spontaneous activity, such as alpha rhythm. The locations of discrete generators (alphons) of individual alpha spindles is now possible with an array of 14 sensors. Mapping techniques with a 5-sensor system have revealed preferential suppression of alpha activity within certain regions of the occipital lobe to tasks involving mental comparisons of abstract figures. These studies provide evidence that the machinery of visual cortex is involved in mental imagery.

  13. 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.

  14. Electrophysiological correlates of competitor activation predict retrieval-induced forgetting.

    PubMed

    Hellerstedt, Robin; Johansson, Mikael

    2014-06-01

    The very act of retrieval modifies the accessibility of memory for knowledge and past events and can also cause forgetting. A prominent theory of such retrieval-induced forgetting (RIF) holds that retrieval recruits inhibition to overcome interference from competing memories, rendering these memories inaccessible. The present study tested a fundamental tenet of the inhibitory-control account: The competition-dependence assumption. Event-related potentials (ERPs) were recorded while participants engaged in a competitive retrieval task. Competition levels were manipulated within the retrieval task by varying the cue-item associative strength of competing items. In order to temporally separate ERP correlates of competitor activation and target retrieval, memory was probed with the sequential presentation of 2 cues: A category cue, to reactivate competitors, and a target cue. As predicted by the inhibitory-control account, competitors with strong compared with weak cue-competitor association were more susceptible to forgetting. Furthermore, competition-sensitive ERP modulations, elicited by the category cue, were observed over anterior regions and reflected individual differences in ensuing forgetting. The present study demonstrates ERP correlates of the reactivation of tightly bound associated memories (the competitors) and provides support for the inhibitory-control account of RIF.

  15. Extremely Randomized Machine Learning Methods for Compound Activity Prediction.

    PubMed

    Czarnecki, Wojciech M; Podlewska, Sabina; Bojarski, Andrzej J

    2015-11-09

    Speed, a relatively low requirement for computational resources and high effectiveness of the evaluation of the bioactivity of compounds have caused a rapid growth of interest in the application of machine learning methods to virtual screening tasks. However, due to the growth of the amount of data also in cheminformatics and related fields, the aim of research has shifted not only towards the development of algorithms of high predictive power but also towards the simplification of previously existing methods to obtain results more quickly. In the study, we tested two approaches belonging to the group of so-called 'extremely randomized methods'-Extreme Entropy Machine and Extremely Randomized Trees-for their ability to properly identify compounds that have activity towards particular protein targets. These methods were compared with their 'non-extreme' competitors, i.e., Support Vector Machine and Random Forest. The extreme approaches were not only found out to improve the efficiency of the classification of bioactive compounds, but they were also proved to be less computationally complex, requiring fewer steps to perform an optimization procedure.

  16. 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.

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

    ERIC Educational Resources Information Center

    Patterson, Jonathan Sparks

    2012-01-01

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

  18. Utilizing Selected Di- and Trinucleotides of siRNA to Predict RNAi Activity

    PubMed Central

    Han, Ye; Liu, Yuanning; Zhang, Hao; He, Fei; Shu, Chonghe

    2017-01-01

    Small interfering RNAs (siRNAs) induce posttranscriptional gene silencing in various organisms. siRNAs targeted to different positions of the same gene show different effectiveness; hence, predicting siRNA activity is a crucial step. In this paper, we developed and evaluated a powerful tool named “siRNApred” with a new mixed feature set to predict siRNA activity. To improve the prediction accuracy, we proposed 2-3NTs as our new features. A Random Forest siRNA activity prediction model was constructed using the feature set selected by our proposed Binary Search Feature Selection (BSFS) algorithm. Experimental data demonstrated that the binding site of the Argonaute protein correlates with siRNA activity. “siRNApred” is effective for selecting active siRNAs, and the prediction results demonstrate that our method can outperform other current siRNA activity prediction methods in terms of prediction accuracy. PMID:28243313

  19. 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

  20. 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.

  1. 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...

  2. 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…

  3. 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.

  4. 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.

  5. 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

  6. Validation of Quantitative Structure-Activity Relationship (QSAR) Model for Photosensitizer Activity Prediction

    PubMed Central

    Frimayanti, Neni; Yam, Mun Li; Lee, Hong Boon; Othman, Rozana; Zain, Sharifuddin M.; Rahman, Noorsaadah Abd.

    2011-01-01

    Photodynamic therapy is a relatively new treatment method for cancer which utilizes a combination of oxygen, a photosensitizer and light to generate reactive singlet oxygen that eradicates tumors via direct cell-killing, vasculature damage and engagement of the immune system. Most of photosensitizers that are in clinical and pre-clinical assessments, or those that are already approved for clinical use, are mainly based on cyclic tetrapyrroles. In an attempt to discover new effective photosensitizers, we report the use of the quantitative structure-activity relationship (QSAR) method to develop a model that could correlate the structural features of cyclic tetrapyrrole-based compounds with their photodynamic therapy (PDT) activity. In this study, a set of 36 porphyrin derivatives was used in the model development where 24 of these compounds were in the training set and the remaining 12 compounds were in the test set. The development of the QSAR model involved the use of the multiple linear regression analysis (MLRA) method. Based on the method, r2 value, r2 (CV) value and r2 prediction value of 0.87, 0.71 and 0.70 were obtained. The QSAR model was also employed to predict the experimental compounds in an external test set. This external test set comprises 20 porphyrin-based compounds with experimental IC50 values ranging from 0.39 μM to 7.04 μM. Thus the model showed good correlative and predictive ability, with a predictive correlation coefficient (r2 prediction for external test set) of 0.52. The developed QSAR model was used to discover some compounds as new lead photosensitizers from this external test set. PMID:22272096

  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. 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.

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

    SciTech Connect

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

    2012-01-01

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

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

    PubMed

    Vanaja, Sivapriya K; Rathinam, Vijay A K; Fitzgerald, Katherine A

    2015-05-01

    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 procaspase-1 into an active cysteine-protease enzyme, caspase-1, which subsequently activates the proinflammatory cytokines, interleukins IL-1β and IL-18, and induces pyroptosis, a highly-pyrogenic inflammatory form of cell death. Studies over the past 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.

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

    PubMed

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

    2017-02-17

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

  12. 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.

  13. 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.

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

    PubMed

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

    2017-02-23

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

  15. Word List Memory Predicts Everyday Function and Problem-Solving in the Elderly: Results from the ACTIVE Cognitive Intervention Trial

    PubMed Central

    Gross, Alden L.; Rebok, George W.; Unverzagt, Frederick W.; Willis, Sherry L.; Brandt, Jason

    2011-01-01

    Data from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) trial (N=2,802) were analyzed to examine whether word list learning predicts future everyday functioning. Using stepwise random effects modeling, measures from the modified administrations of the Hopkins Verbal Learning Test (HVLT) and the Auditory Verbal Learning Test (AVLT) were independently predictive of everyday IADL functioning, problem-solving, and psychomotor speed. Associations between memory scores and everyday functioning outcomes remained significant across follow-up intervals spanning five years. HVLT total recall score was consistently the strongest predictor of each functional outcome. Results suggest that verbal memory measures are uniquely associated with both current and future functioning and that specific verbal memory tests like the HVLT and AVLT have important clinical utility in predicting future functional ability among older adults. PMID:21069610

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

    PubMed

    DeRosier, Melissa E; Thomas, James M

    2003-01-01

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

  17. 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.

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

    PubMed Central

    Abut, Fatih; Akay, Mehmet Fatih

    2015-01-01

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

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

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

    SciTech Connect

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

    1993-06-01

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

  6. 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…

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

    PubMed Central

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

    2015-01-01

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

  8. 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...

  9. 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.

  10. Machine Learning Methods for Predicting HLA–Peptide Binding Activity

    PubMed Central

    Luo, Heng; Ye, Hao; Ng, Hui Wen; Shi, Leming; Tong, Weida; Mendrick, Donna L.; Hong, Huixiao

    2015-01-01

    As major histocompatibility complexes in humans, the human leukocyte antigens (HLAs) have important functions to present antigen peptides onto T-cell receptors for immunological recognition and responses. Interpreting and predicting HLA–peptide binding are important to study T-cell epitopes, immune reactions, and the mechanisms of adverse drug reactions. We review different types of machine learning methods and tools that have been used for HLA–peptide binding prediction. We also summarize the descriptors based on which the HLA–peptide binding prediction models have been constructed and discuss the limitation and challenges of the current methods. Lastly, we give a future perspective on the HLA–peptide binding prediction method based on network analysis. PMID:26512199

  11. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  13. Application of Active Learning Techniques to an Advanced Course

    NASA Astrophysics Data System (ADS)

    Knop, R. A.

    2004-05-01

    The New Faculty Workshop provided a wealth of techniques as well as an overriding philosophy for the teaching of undergraduate Physics and Astronomy courses. The focus of the workshop was active learning, summarized in ``Learner-Centered Astronomy Teaching" by Slater & Adams: it's not what you do in class that matters, it's what the students do. Much of the specific focus of the New Faculty Workshop is on teaching the large, introductory Physics classes that many of the faculty present are sure to teach, both algebra-based and calculus-based. Many of these techniques apply directly and with little modification to introductory Astronomy courses. However, little direct attention is given to upper-division undergraduate, or even graduate, courses. In this presentation, I will share my experience in attempting to apply some of the techniques discussed at the New Faculty Workshop to an upper-division course in Galactic Astrophysics at Vanderbilt University during the Spring semester of 2004.

  14. Recent advances in organic thermally activated delayed fluorescence materials.

    PubMed

    Yang, Zhiyong; Mao, Zhu; Xie, Zongliang; Zhang, Yi; Liu, Siwei; Zhao, Juan; Xu, Jiarui; Chi, Zhenguo; Aldred, Matthew P

    2017-02-06

    Organic materials that exhibit thermally activated delayed fluorescence (TADF) are an attractive class of functional materials that have witnessed a booming development in recent years. Since Adachi et al. reported high-performance TADF-OLED devices in 2012, there have been many reports regarding the design and synthesis of new TADF luminogens, which have various molecular structures and are used for different applications. In this review, we summarize and discuss the latest progress concerning this rapidly developing research field, in which the majority of the reported TADF systems are discussed, along with their derived structure-property relationships, TADF mechanisms and applications. We hope that such a review provides a clear outlook of these novel functional materials for a broad range of scientists within different disciplinary areas and attracts more researchers to devote themselves to this interesting research field.

  15. 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.

  16. 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.

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

    PubMed

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

    2007-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

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

  19. 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

  20. 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.

  1. 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.

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

    PubMed

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

    2010-07-01

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

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

    DTIC Science & Technology

    2006-01-01

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

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

    DTIC Science & Technology

    2014-07-31

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

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

    DTIC Science & Technology

    1989-02-27

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

  6. 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.

  7. 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.

  8. 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

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

    PubMed

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

    2016-10-01

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

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

    PubMed

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

    2015-03-01

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

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

    PubMed

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

    2015-05-01

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

  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 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.

  13. 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.

  14. 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.

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

    PubMed Central

    Jiang, Wenpeng; Wang, Zhou; Jia, Yang

    2017-01-01

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

  16. 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

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

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

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

  19. 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

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

    DTIC Science & Technology

    1984-04-04

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

  1. 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

  2. Predicting enhancer activity and variant impact using gkm-SVM.

    PubMed

    Beer, Michael A

    2017-01-25

    We participated in the Critical Assessment of Genome Interpretation eQTL challenge to further test computational models of regulatory variant impact and their association with human disease. Our prediction model is based on a discriminative gapped-kmer SVM (gkm-SVM) trained on genome-wide chromatin accessibility data in the cell type of interest. The comparisons with massively parallel reporter assays (MPRA) in lymphoblasts show that gkm-SVM is among the most accurate prediction models even though all other models used the MPRA data for model training, and gkm-SVM did not. In addition, we compare gkm-SVM with other MPRA datasets and show that gkm-SVM is a reliable predictor of expression and that deltaSVM is a reliable predictor of variant impact in K562 cells and mouse retina. We further show that DHS (DNase-I hypersensitive sites) and ATAC-seq (assay for transposase-accessible chromatin using sequencing) data are equally predictive substrates for training gkm-SVM, and that DHS regions flanked by H3K27Ac and H3K4me1 marks are more predictive than DHS regions alone.

  3. Is gardening a stimulating activity for people with advanced Huntington's disease?

    PubMed

    Spring, Josephine A; Viera, Marc; Bowen, Ceri; Marsh, Nicola

    2014-11-01

    This study evaluated adapted gardening as an activity for people with advanced Huntington's disease (HD) and explored its therapeutic aspects. Visitors and staff completed a questionnaire and participated in structured interviews to capture further information, whereas a pictorial questionnaire was designed for residents with communication difficulties. Staff reported that gardening was a constructive, outdoor activity that promoted social interaction, physical activity including functional movement and posed cognitive challenges. Half the staff thought the activity was problem free and a third used the garden for therapy. Visitors used the garden to meet with residents socially. Despite their disabilities, HD clients enjoyed growing flourishing flowers and vegetables, labelling plants, being outside in the sun and the quiet of the garden. The garden is valued by all three groups. The study demonstrates the adapted method of gardening is a stimulating and enjoyable activity for people with advanced HD.

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

    PubMed

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

    2016-06-03

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

  6. 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

  7. 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.

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

    SciTech Connect

    Gutierrez, Marte

    2016-12-31

    The research project aims to develop and validate an advanced computer model that can be used in the planning and design of stimulation techniques to create engineered reservoirs for Enhanced Geothermal Systems. The specific objectives of the proposal are to: 1) Develop a true three-dimensional hydro-thermal fracturing simulator that is particularly suited for EGS reservoir creation. 2) Perform laboratory scale model tests of hydraulic fracturing and proppant flow/transport using a polyaxial loading device, and use the laboratory results to test and validate the 3D simulator. 3) Perform discrete element/particulate modeling of proppant transport in hydraulic fractures, and use the results to improve understand of proppant flow and transport. 4) Test and validate the 3D hydro-thermal fracturing simulator against case histories of EGS energy production. 5) Develop a plan to commercialize the 3D fracturing and proppant flow/transport simulator. The project is expected to yield several specific results and benefits. Major technical products from the proposal include: 1) A true-3D hydro-thermal fracturing computer code that is particularly suited to EGS, 2) Documented results of scale model tests on hydro-thermal fracturing and fracture propping in an analogue crystalline rock, 3) Documented procedures and results of discrete element/particulate modeling of flow and transport of proppants for EGS applications, and 4) Database of monitoring data, with focus of Acoustic Emissions (AE) from lab scale modeling and field case histories of EGS reservoir creation.

  9. 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.

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

    PubMed Central

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

    2010-01-01

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

  11. 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.

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

    PubMed

    Kapur, Payal

    2012-01-01

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

  13. 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.

  14. 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.

  15. 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.

  16. Mothers' Prenatal Activities Predict Adjustment to Pregnancy and Early Parenting.

    ERIC Educational Resources Information Center

    Abraham, Ronalda; Turner, Nita

    This study examined the activities of pregnant women and how these activities facilitated a positive adjustment to pregnancy and early parenting. Subjects were 49 expectant first-time mothers ranging in age from 20 to 41 and attending a childhood preparation class. Eighty-two percent of the women were married. Subjects completed two questionnaires…

  17. 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,…

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

    PubMed

    Toukach, Filip V; Ananikov, Valentine P

    2013-11-07

    All living systems are comprised of four fundamental classes of macromolecules--nucleic acids, proteins, lipids, and carbohydrates (glycans). Glycans play a unique role of joining three principal hierarchical levels of the living world: (1) the molecular level (pathogenic agents and vaccine recognition by the immune system, metabolic pathways involving saccharides that provide cells with energy, and energy accumulation via photosynthesis); (2) the nanoscale level (cell membrane mechanics, structural support of biomolecules, and the glycosylation of macromolecules); (3) the microscale and macroscale levels (polymeric materials, such as cellulose, starch, glycogen, and biomass). NMR spectroscopy is the most powerful research approach for getting insight into the solution structure and function of carbohydrates at all hierarchical levels, from monosaccharides to oligo- and polysaccharides. Recent progress in computational procedures has opened up novel opportunities to reveal the structural information available in the NMR spectra of saccharides and to advance our understanding of the corresponding biochemical processes. The ability to predict the molecular geometry and NMR parameters is crucial for the elucidation of carbohydrate structures. In the present paper, we review the major NMR spectrum simulation techniques with regard to chemical shifts, coupling constants, relaxation rates and nuclear Overhauser effect prediction applied to the three levels of glycomics. Outstanding development in the related fields of genomics and proteomics has clearly shown that it is the advancement of research tools (automated spectrum analysis, structure elucidation, synthesis, sequencing and amplification) that drives the large challenges in modern science. Combining NMR spectroscopy and the computational analysis of structural information encoded in the NMR spectra reveals a way to the automated elucidation of the structure of carbohydrates.

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

    PubMed

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

    2014-03-01

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

  1. 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.

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2005-09-01

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

  4. 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…

  5. [Bioessay with brine Artemia to predict antibacterial and pharmacologic activity].

    PubMed

    Sánchez, C; Gupta, M; Vásquez, M; de Noriega, Y M; Montenegro, G

    1993-01-01

    The Brine Shrimp Test (BST) is a simple and inexpensive method to test cytotoxity, to biodirect phytochemical fractionation of natural products and as a predictor for antitumor and pesticidal activity. In this work, the BST test, an antibacterial test and the rat hippocratic screening test were used on 25 plant extracts and fractions, to evaluate the correlation, if any, between the BST and the others. Preliminary results show that the BST is not a predictor of antibacterial activity nor the hippocratic screening test.

  6. 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.

  7. 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.

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

    PubMed

    Martin, T M

    2016-01-01

    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 binding. In vitro classification models yielded balanced accuracies ranging from 0.65 to 0.85 for the external prediction set. In vivo ER classification models yielded balanced accuracies ranging from 0.72 to 0.83. If used as additional biological descriptors for in vivo models, in vitro scores were found to increase the prediction accuracy of in vivo ER models. If in vitro activity was used directly as a surrogate for in vivo activity, the results were poor (balanced accuracy ranged from 0.49 to 0.72). Under-sampling negative compounds in the training set was found to increase the coverage (fraction of chemicals which can be predicted) and increase prediction sensitivity.

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

    PubMed Central

    2012-01-01

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

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

    PubMed

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

    2006-08-01

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

  11. Biological Activity Predictions and Hydrogen Bonding Analysis in Quinolines

    NASA Astrophysics Data System (ADS)

    Gupta, Palvi; Kamni

    The paper has been designed to make a comprehensive review of a particular series of organic molecular assembly in the form of compendium. An overview of general description of fifteen quinoline derivatives has been given. The biological activity spectra of quinoline derivatives have been correlated on structure activity relationships base which provides the different Pa (possibility of activity) and Pi (possibility of inactivity) values. Expositions of the role of intermolecular interactions in the identified derivatives have been discussed with the standard distance and angle cut-off criteria criteria as proposed by Desiraju and Steiner (1999) in an International monogram on crystallography. Distance-angle scatter plots for intermolecular interactions are presented for a better understanding of the packing interactions which exist in quinoline derivatives.

  12. 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.

  13. 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.

  14. 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.

  15. Predicting Reading and Mathematics from Neural Activity for Feedback Learning

    ERIC Educational Resources Information Center

    Peters, Sabine; Van der Meulen, Mara; Zanolie, Kiki; Crone, Eveline A.

    2017-01-01

    Although many studies use feedback learning paradigms to study the process of learning in laboratory settings, little is known about their relevance for real-world learning settings such as school. In a large developmental sample (N = 228, 8-25 years), we investigated whether performance and neural activity during a feedback learning task…

  16. Lifespan Mental Activity Predicts Diminished Rate of Hippocampal Atrophy

    PubMed Central

    Valenzuela, Michael J.; Sachdev, Perminder; Wen, Wei; Chen, Xiaohua; Brodaty, Henry

    2008-01-01

    Objective Epidemiological studies suggest that complex mental activity may reduce the risk for dementia, however an underlying mechanism remains unclear. Our objective was to determine whether individual differences in lifespan complex mental activity are linked to altered rates of hippocampal atrophy independent of global measures of neurodegeneration. Methods Thirty seven healthy older individuals had their complex mental activity levels estimated using the Lifetime of Experiences Questionnaire (LEQ) and completed serial MRI investigations at baseline and three years follow-up. Hippocampal volume and semi-automatic quantitation of whole brain volume (WBV) and white matter hyperintensities (WMHs) were compared at both time points. Results Higher LEQ scores were correlated with hippocampal volume independent of covariates at the three year follow-up stage (r = 0.43, p = 0.012). Moreover, those with higher LEQ scores experienced less hippocampal atrophy over the follow-up period (r = 0.41, p = 0.02). High LEQ individuals had less than half the hippocampal volume decline of low LEQ individuals in a multivariate analysis (F = 4.47, p = 0.042). No parallel changes were found in measures of WBV and WMHs. Conclusions High level of complex mental activity across the lifespan was correlated with a reduced rate of hippocampal atrophy. This finding could not be explained by general differences in intracranial volume, larger hippocampi at baseline, presence of hypertensive disease, gender or low mood. Our results suggest that neuroprotection in medial temporal lobe may be one mechanism underlying the link between mental activity and lower rates of dementia observed in population-based studies. Additional studies are required to further explore this novel finding. PMID:18612379

  17. 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

  18. 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

  19. Model predictions of myoelectrical activity of the small bowel.

    PubMed

    Miftakhov, R N; Abdusheva, G R; Wingate, D L

    1996-02-01

    A mathematical model for the periodic electrical activity of a functional unit of the small intestine is developed. Based on real morphological and electrophysiological data, the model assumes that: the functional unit is an electromyogenic syncytium; the kinetics of L, T-type Ca2+, mixed Ca(2+)-dependent K+, potential sensitive K+ and Cl- channels determines electrical activity of the functional unit; the basic neural circuit, represented by a single cholinergic neurone, provides an excitatory input to the functional unit via receptor-linked L-type Ca2+ channels. Numerical simulation of the model has shown that it is capable of displaying the slow waves and that slight modifications of some of the parameters result in different electrical responses. The effects of the variations of the main parameters have been analyzed for their ability to reproduce various electrical patterns. The results are in good qualitative and quantitative agreement with results of experiments conducted on the small intestine.

  20. Initial Implementation of an Active Prediction Capability in Bellhop

    DTIC Science & Technology

    2010-10-01

    Résumé Le présent rapport traite du programme actif Bellhop de RDDC, conçu pour produire la réverbération et l’excédent de signaux d’après des...l’effet du milieu océanique sur l’émission d’impulsions de sonar actif . Résultats : La version BellhopDRDC_active_v4 de RDDC Atlantique est la...version du Bellhop spécifiquement conçue pour offrir une capacité active. Le modèle est présentement configuré pour accepter des capteurs multiples et

  1. Baseline activity predicts working memory load of preceding task condition.

    PubMed

    Pyka, Martin; Hahn, Tim; Heider, Dominik; Krug, Axel; Sommer, Jens; Kircher, Tilo; Jansen, Andreas

    2013-11-01

    The conceptual notion of the so-called resting state of the brain has been recently challenged by studies indicating a continuing effect of cognitive processes on subsequent rest. In particular, activity in posterior parietal and medial prefrontal areas has been found to be modulated by preceding experimental conditions. In this study, we investigated which brain areas show working memory dependent patterns in subsequent baseline periods and how specific they are for the preceding experimental condition. During functional magnetic resonance imaging, 94 subjects performed a letter-version of the n-back task with the conditions 0-back and 2-back followed by a low-level baseline in which subjects had to passively observe the letters appearing. In a univariate analysis, 2-back served as control condition while 0-back, baseline after 0-back and baseline after 2-back were modeled as regressors to test for activity changes between both baseline conditions. Additionally, we tested, using Gaussian process classifiers, the recognition of task condition from functional images acquired during baseline. Besides the expected activity changes in the precuneus and medial prefrontal cortex, we found differential activity in the thalamus, putamen, and postcentral gyrus that were affected by the preceding task. The multivariate analysis revealed that images of the subsequent baseline block contain task related patterns that yield a recognition rate of 70%. The results suggest that the influence of a cognitive task on subsequent baseline is strong and specific for some areas but not restricted to areas of the so-called default mode network.

  2. APOE ε4 genotype predicts memory for everyday activities.

    PubMed

    Bailey, Heather R; Sargent, Jesse Q; Flores, Shaney; Nowotny, Petra; Goate, Alison; Zacks, Jeffrey M

    2015-01-01

    The apolipoprotein E (ApOE) ε4 allele is associated with neuropathological buildup of amyloid in the brain, and with lower performance on some laboratory measures of memory in some populations. In two studies, we tested whether ApOE genotype affects memory for everyday activities. In Study 1, participants aged 20-79 years old (n = 188) watched movies of actors engaged in daily activities and completed memory tests for the activities in the movies. In Study 2, cognitively healthy and demented older adults (n = 97) watched and remembered similar movies, and also underwent structural MRI scanning. All participants provided saliva samples for genetic analysis. In both samples we found that, in older adults, ApOE ε4 carriers demonstrated worse everyday memory performance than did ε4 noncarriers. In Study 2, ApOE ε4 carriers had smaller medial temporal lobes (MTL) volumes, and MTL volume mediated the relationship between ApOE genotype and everyday memory performance. These everyday memory tasks measure genetically determined cognitive decline that can occur prior to a clinical diagnosis of dementia. Further, these tasks are easily administered and may be a useful clinical tool in identifying ε4 carriers who may be at risk for MTL atrophy and further cognitive decline that is a common characteristic of the earliest stages of Alzheimer's disease.

  3. APOE ε4 Genotype Predicts Memory for Everyday Activities

    PubMed Central

    Bailey, Heather R.; Sargent, Jesse Q.; Flores, Shaney; Nowotny, Petra; Goate, Alison; Zacks, Jeffrey M.

    2015-01-01

    The apolipoprotein E (ApoE) ε4 allele is associated with neuropathological buildup of amyloid in the brain, and with lower performance on some laboratory measures of memory in some populations. In two studies, we tested whether ApoE genotype affects memory for everyday activities. In Study 1, participants aged 20-79 years old (n = 188) watched movies of actors engaged in daily activities and completed memory tests for the activities in the movies. In Study 2, cognitively healthy and demented older adults (n = 97) watched and remembered similar movies, and also underwent structural MRI scanning. All participants provided saliva samples for genetic analysis. In both samples we found that, in older adults, ApoE ε4 carriers demonstrated worse everyday memory performance than did ε4 non-carriers. In Study 2, ApoE ε4 carriers had smaller MTL volumes, and MTL volume mediated the relationship between ApoE genotype and everyday memory performance. These everyday memory tasks measure genetically-determined cognitive decline that can occur prior to a clinical diagnosis of dementia. Further, these tasks are easily administered and may be a useful clinical tool in identifying ε4 carriers who may be at risk for MTL atrophy and further cognitive decline that is a common characteristic of the earliest stages of Alzheimer's disease. PMID:25754878

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

    SciTech Connect

    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.

  5. Putamen Activation Represents an Intrinsic Positive Prediction Error Signal for Visual Search in Repeated Configurations.

    PubMed

    Sommer, Susanne; Pollmann, Stefan

    2016-01-01

    We investigated fMRI responses to visual search targets appearing at locations that were predicted by the search context. Based on previous work in visual category learning we expected an intrinsic reward prediction error signal in the putamen whenever the target appeared at a location that was predicted with some degree of uncertainty. Comparing target appearance at locations predicted with 50% probability to either locations predicted with 100% probability or unpredicted locations, increased activation was observed in left posterior putamen and adjacent left posterior insula. Thus, our hypothesis of an intrinsic prediction error-like signal was confirmed. This extends the observation of intrinsic prediction error-like signals, driven by intrinsic rather than extrinsic reward, to memory-driven visual search.

  6. Putamen Activation Represents an Intrinsic Positive Prediction Error Signal for Visual Search in Repeated Configurations

    PubMed Central

    Sommer, Susanne; Pollmann, Stefan

    2016-01-01

    We investigated fMRI responses to visual search targets appearing at locations that were predicted by the search context. Based on previous work in visual category learning we expected an intrinsic reward prediction error signal in the putamen whenever the target appeared at a location that was predicted with some degree of uncertainty. Comparing target appearance at locations predicted with 50% probability to either locations predicted with 100% probability or unpredicted locations, increased activation was observed in left posterior putamen and adjacent left posterior insula. Thus, our hypothesis of an intrinsic prediction error-like signal was confirmed. This extends the observation of intrinsic prediction error-like signals, driven by intrinsic rather than extrinsic reward, to memory-driven visual search. PMID:27867436

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

    PubMed

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

    2016-12-01

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

  8. Outcome prediction of advanced mantle cell lymphoma by international prognostic index versus different mantle cell lymphoma indexes: one institution study.

    PubMed

    Todorovic, Milena; Balint, Bela; Andjelic, Bosko; Stanisavljevic, Dejana; Kurtovic, Nada Kraguljac; Radisavljevic, Ziv; Mihaljevic, Biljana

    2012-09-01

    The aim of this study was to evaluate the prognostic significance of international prognostic index (IPI), mantle cell lymphoma IPI (MIPI), simplified MIPI (sMIPI), and MIPI biological (MIPIb), as well as their correlation with immunophenotype, clinical characteristics, and overall survival (OS), in a selected group of 54 patients with advanced-stage mantle cell lymphoma (MCL), treated uniformly with CHOP. Seventeen patients had IV clinical stage (CS), while other 37 had leukemic phase at presentation. Diffuse type of marrow infiltration was verified in 68.5% and nodular in remainder patients. Extranodal localization (25.9%) included bowel (20.4%), pleural effusion, sinus, and palpebral infiltration. All of analyzed patients expressed typical MCL immunophenotypic profile: CD19(+)CD20(+)CD22(+)CD5(+)Cyclin-D1(+)FMC7(+)CD79b(+)smIg(+)CD38(+/-)CD23(-)CD10(-). Median OS of the whole group was 23 months, without significant differences between IV CS and leukemic phase patients. Thirty-two patients (59.3%) responded to initial treatment, 9 (16.7%) with complete and 23 (42.6%) with partial remission. Negative prognostic influence on OS had high IPI (P < 0.01), high sMIPI (P < 0.001), MIPI (P < 0.01), MIPIb (P < 0.01), extranodal localization (P < 0.01), and diffuse marrow infiltration (P < 0.01). Testing between randomly selected groups showed that patients with lower proportion of CD5(+) cells (<80%) correlated with cytological blastoid variant and had shorter survival comparing with the group with higher proportion of CD5(+) cells (>80%) (P < 0.01). Using univariate Cox regression, we proved that IPI, sMIPI, MIPI, and MIPIb had an independent predictive importance (P < 0.01) for OS in uniformly treated advanced MCL patients, although sMIPI prognostic significance was the highest (P < 0.001).

  9. 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.

  10. The synchronization of spontaneous BOLD activity predicts extraversion and neuroticism.

    PubMed

    Wei, Luqing; Duan, Xujun; Yang, Yang; Liao, Wei; Gao, Qing; Ding, Ju-rong; Zhang, Zhiqiang; Zeng, Weixi; Li, Yuan; Lu, Guangming; Chen, Huafu

    2011-10-24

    There is an increasing body of evidence pointing to a relationship between personality and brain markers. The purpose of this study was to identify the associations between personality dimensions of extraversion and neuroticism and the local synchronization of spontaneous blood oxygen level-dependent (BOLD) activity assessed by regional homogeneity (ReHo) approach. Our results revealed the significant negative correlation between neuroticism and ReHo in the left middle frontal gyrus, providing evidence for the left frontal activation involved in pleasant emotion. ReHo was correlated negatively with extraversion in the medial prefrontal cortex (MPFC), an important portion of the default mode network (DMN), thus further indicating the relationship between DMN and personality. In addition, ReHo in the insula, cerebellum and cingulate gyrus was correlated positively with extraversion, suggesting the associations between individual difference in extraversion and specific brain regions involved in affective processing. These findings shed light on the important relationship between the synchronization of spontaneous fluctuations and personality dimensions of extraversion and neuroticism, which provide further evidence for the neural underpinning of individual difference in personality traits.

  11. Reliable activation to novel stimuli predicts higher fluid intelligence.

    PubMed

    Euler, Matthew J; Weisend, Michael P; Jung, Rex E; Thoma, Robert J; Yeo, Ronald A

    2015-07-01

    The ability to reliably respond to stimuli could be an important biological determinant of differences in fluid intelligence (Gf). However, most electrophysiological studies of Gf employ event-related potential (ERP) measures that average brain activity over trials, and hence have limited power to quantify neural variability. Time-frequency analyses can capture cross-trial variation in the phase of neural activity, and thus can help address the importance of neural reliability to differences in Gf. This study recruited a community sample of healthy adults and measured inter-trial phase clustering (ITPC), total spectral power, and ERP amplitudes elicited by Repeated and Novel non-target stimuli during two visual oddball tasks. Condition effects, relations among the EEG measures, and relations with Gf were assessed. Early visual responses to Repeated stimuli elicited higher ITPC, yet only ITPC elicited by Novel stimuli was associated with Gf. Analyses of spectral power further highlighted the contribution of phase consistency to the findings. The link between Gf and reliable responding to changing inputs suggests an important role for flexible resource allocation in fluid intellectual skills.

  12. 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…

  13. 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.

  14. 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.

  15. Systemic activation of NF-κB driven luciferase activity in transgenic mice fed advanced glycation end products modified albumin.

    PubMed

    Nass, Norbert; Bayreuther, Kristina; Simm, Andreas

    2017-04-01

    Advanced glycation end products (AGEs) are stable end products of the Maillard reaction and accumulate with progressing ageing and degenerative diseases. Significant amounts of AGE-modified peptides are also consumed with processed food. AGEs bind to specific receptors, especially the receptor of AGEs (RAGE). Activation of RAGE then evokes intracellular signalling, finally resulting in the activation of the NF-κB transcription factor and therefore a proinflammatory state. We here analysed, whether NF-κB is activated in short term upon feeding an AGE-modified protein in-vivo. Transgenic mice expressing firefly luciferase under the control of an NF-κB responsive promoter were intraperitoneally injected or fed with AGE-modified- or control albumin and luciferase expression was analysed by in-vivo imaging and by in-vitro by determination of luciferase enzyme activity in heart, lung, gut, spleen, liver and kidney. In all organs, an activation of the luciferase reporter gene was observed in response to AGE-BSA feeding, however with different intensity and timing. The gut exhibited highest luciferase activity and this activity peaked 6-8 h post AGE-feeding. In heart and kidney, luciferase activity increased for up to 12 h post feeding. All other organs tested, exhibited highest activity at 10 h after AGE-consumption. Altogether, these data demonstrate that feeding AGE-modified protein resulted in a transient and systemic activation of the NF-κB reporter.

  16. 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...

  17. Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression.

    EPA Science Inventory

    Building predictive gene signatures through simultaneous assessment of transcription factor activation and gene expression Exposure to many drugs and environmentally-relevant chemicals can cause adverse outcomes. These adverse outcomes, such as cancer, have been linked to mol...

  18. 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

  19. 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

  20. Improving the performance of solar flare prediction using active longitudes information

    NASA Astrophysics Data System (ADS)

    Huang, X.; Zhang, L.; Wang, H.; Li, L.

    2013-01-01

    Context. Solar flare prediction models normally depend on properties of active regions, such as sunspot area, McIntosh classifications, Mount Wilson classifications, and various measures of the magnetic field. Nevertheless, the positional information of active regions has not been used. Aims: We define a metric, DARAL (distance between active regions and predicted active longitudes), to depict the positional relationship between active regions and predicted active longitudes and add DARAL to our solar flare prediction model to improve its performance. Methods: Combining DARAL with other solar magnetic field parameters, we build a solar flare prediction model with the instance-based learning method, which is a simple and effective algorithm in machine learning. We extracted 70 078 active region instances from the Solar and Heliospheric Observatory (SOHO)/Michelson Doppler Imager (MDI) magnetograms containing 1055 National Oceanic and Atmospheric Administration (NOAA) active regions within 30° of the solar disk center from 1996 to 2007 and used them to train and test the solar flare prediction model. Results: Using four performance measures (true positive rate, true negative rate, true skill statistic, and Heidke skill score), we compare performances of the solar flare prediction model with and without DARAL. True positive rate, true negative rate, true skill statistic, and Heidke skill score increase by 6.7% ± 1.3%, 4.2% ± 0.5%, 10.8% ± 1.4% and 8.7% ± 1.0%, respectively. Conclusions: The comparison indicates that the metric DARAL is beneficial to performances of the solar flare prediction model.

  1. 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.

  2. 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.

  3. cN-II expression predicts survival in patients receiving gemcitabine for advanced non-small cell lung cancer.

    PubMed

    Sève, Pascal; Mackey, John R; Isaac, Sylvie; Trédan, Olivier; Souquet, Pierre Jean; Pérol, Maurice; Cass, Carol; Dumontet, Charles

    2005-09-01

    Resistance to gemcitabine is likely to be multifactorial and could involve a number of mechanisms involved in drug penetration, metabolism and targeting. In vitro studies of resistant human cell lines have confirmed that human equilibrative nucleoside transporter 1 (hENT1)-deficient cells display resistance to gemcitabine. Overexpression of certain nucleotidases, such as cN-II, has also been frequently shown in gemcitabine-resistant models. In this study, we applied immunohistochemical methods to assess the protein abundance of cN-II, hENT1, human concentrative nucleoside transporter 3 (hCNT3) and deoxycitidine kinase (dCK) in malignant cells in from 43 patients with treatment-naïve locally advanced or metastatic non-small cell lung cancer (NSCLC). All patients subsequently received gemcitabine-based chemotherapy. Response to chemotherapy, progression-free survival (PFS), and overall survival (OS) were correlated with abundance of these proteins. Among the 43 samples, only 7 (16%) expressed detectable hENT1, with a low percentage of positive cells, 18 expressed hCNT3 (42%), 36 (86%) expressed cN-II and 28 (66%) expressed dCK. In univariate analysis, only cN-II expression levels were correlated with overall survival. None of the parameters were correlated with freedom from progression survival nor with response. Patients with low levels of expression of cN-II (less than 40% positively stained cells) had worse overall survival than patients with higher levels of cN-II expression (6 months and 11 months, respectively). In a multivariate analysis taking into account age, sex, weight loss, stage and immunohistochemical results, cN-II was the only predictive factor associated with overall survival. This study suggests that cN-II nucleotidase expression levels identify subgroups of NSCLC patients with different outcomes under gemcitabine-based therapy. Larger prospective studies are warranted to confirm the predictive value of cN-II in these patients.

  4. De novo sequencing of circulating miRNAs identifies novel markers predicting clinical outcome of locally advanced breast cancer

    PubMed Central

    2012-01-01

    Background MicroRNAs (miRNAs) have been recently detected in the circulation of cancer patients, where they are associated with clinical parameters. Discovery profiling of circulating small RNAs has not been reported in breast cancer (BC), and was carried out in this study to identify blood-based small RNA markers of BC clinical outcome. Methods The pre-treatment sera of 42 stage II-III locally advanced and inflammatory BC patients who received neoadjuvant chemotherapy (NCT) followed by surgical tumor resection were analyzed for marker identification by deep sequencing all circulating small RNAs. An independent validation cohort of 26 stage II-III BC patients was used to assess the power of identified miRNA markers. Results More than 800 miRNA species were detected in the circulation, and observed patterns showed association with histopathological profiles of BC. Groups of circulating miRNAs differentially associated with ER/PR/HER2 status and inflammatory BC were identified. The relative levels of selected miRNAs measured by PCR showed consistency with their abundance determined by deep sequencing. Two circulating miRNAs, miR-375 and miR-122, exhibited strong correlations with clinical outcomes, including NCT response and relapse with metastatic disease. In the validation cohort, higher levels of circulating miR-122 specifically predicted metastatic recurrence in stage II-III BC patients. Conclusions Our study indicates that certain miRNAs can serve as potential blood-based biomarkers for NCT response, and that miR-122 prevalence in the circulation predicts BC metastasis in early-stage patients. These results may allow optimized chemotherapy treatments and preventive anti-metastasis interventions in future clinical applications. PMID:22400902

  5. Prediction Signatures in the Brain: Semantic Pre-Activation during Language Comprehension

    PubMed Central

    Maess, Burkhard; Mamashli, Fahimeh; Obleser, Jonas; Helle, Liisa; Friederici, Angela D.

    2016-01-01

    There is broad agreement that context-based predictions facilitate lexical-semantic processing. A robust index of semantic prediction during language comprehension is an evoked response, known as the N400, whose amplitude is modulated as a function of semantic context. However, the underlying neural mechanisms that utilize relations of the prior context and the embedded word within it are largely unknown. We measured magnetoencephalography (MEG) data while participants were listening to simple German sentences in which the verbs were either highly predictive for the occurrence of a particular noun (i.e., provided context) or not. The identical set of nouns was presented in both conditions. Hence, differences for the evoked responses of the nouns can only be due to differences in the earlier context. We observed a reduction of the N400 response for highly predicted nouns. Interestingly, the opposite pattern was observed for the preceding verbs: highly predictive (that is more informative) verbs yielded stronger neural magnitude compared to less predictive verbs. A negative correlation between the N400 effect of the verb and that of the noun was found in a distributed brain network, indicating an integral relation between the predictive power of the verb and the processing of the subsequent noun. This network consisted of left hemispheric superior and middle temporal areas and a subcortical area; the parahippocampus. Enhanced activity for highly predictive relative to less predictive verbs, likely reflects establishing semantic features associated with the expected nouns, that is a pre-activation of the expected nouns. PMID:27895573

  6. 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.

  7. Predicting involvement in prison gang activity: street gang membership, social and psychological factors.

    PubMed

    Wood, Jane L; Alleyne, Emma; Mozova, Katarina; James, Mark

    2014-06-01

    The aim of this study was to examine whether street gang membership, psychological factors, and social factors such as preprison experiences could predict young offenders' involvement in prison gang activity. Data were collected via individual interviews with 188 young offenders held in a Young Offenders Institution in the United Kingdom. Results showed that psychological factors such as the value individuals attached to social status, a social dominance orientation, and antiauthority attitudes were important in predicting young offenders' involvement in prison gang activity. Further important predictors included preimprisonment events such as levels of threat, levels of individual delinquency, and levels of involvement in group crime. Longer current sentences also predicted involvement in prison gang activity. However, street gang membership was not an important predictor of involvement in prison gang activity. These findings have implications for identifying prisoners involved in prison gang activity and for considering the role of psychological factors and group processes in gang research.

  8. 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.

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

    PubMed

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

    2007-05-01

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

  10. 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.

  11. 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

  12. Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation.

    PubMed

    Anderson, Andrew James; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Aguilar, Mario; Wang, Xixi; Doko, Donias; Raizada, Rajeev D S

    2016-08-12

    We introduce an approach that predicts neural representations of word meanings contained in sentences then superposes these to predict neural representations of new sentences. A neurobiological semantic model based on sensory, motor, social, emotional, and cognitive attributes was used as a foundation to define semantic content. Previous studies have predominantly predicted neural patterns for isolated words, using models that lack neurobiological interpretation. Fourteen participants read 240 sentences describing everyday situations while undergoing fMRI. To connect sentence-level fMRI activation patterns to the word-level semantic model, we devised methods to decompose the fMRI data into individual words. Activation patterns associated with each attribute in the model were then estimated using multiple-regression. This enabled synthesis of activation patterns for trained and new words, which were subsequently averaged to predict new sentences. Region-of-interest analyses revealed that prediction accuracy was highest using voxels in the left temporal and inferior parietal cortex, although a broad range of regions returned statistically significant results, showing that semantic information is widely distributed across the brain. The results show how a neurobiologically motivated semantic model can decompose sentence-level fMRI data into activation features for component words, which can be recombined to predict activation patterns for new sentences.

  13. Regeneration of siloxane-exhausted activated carbon by advanced oxidation processes.

    PubMed

    Cabrera-Codony, Alba; Gonzalez-Olmos, Rafael; Martín, Maria J

    2015-03-21

    In the context of the biogas upgrading, siloxane exhausted activated carbons need to be regenerated in order to avoid them becoming a residue. In this work, two commercial activate carbons which were proved to be efficient in the removal of octamethylcyclotetrasiloxane (D4) from biogas, have been regenerated through advanced oxidation processes using both O3 and H2O2. After the treatment with O3, the activated carbon recovered up to 40% of the original adsorption capacity while by the oxidation with H2O2 the regeneration efficiency achieved was up to 45%. In order to enhance the H2O2 oxidation, activated carbon was amended with iron. In this case, the regeneration efficiency increased up to 92%.

  14. 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.

  15. 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.

  16. Plasma Cholesterol–Induced Lesion Networks Activated before Regression of Early, Mature, and Advanced Atherosclerosis

    PubMed Central

    Björkegren, Johan L. M.; Hägg, Sara; Jain, Rajeev K.; Cedergren, Cecilia; Shang, Ming-Mei; Rossignoli, Aránzazu; Takolander, Rabbe; Melander, Olle; Hamsten, Anders; Michoel, Tom; Skogsberg, Josefin

    2014-01-01

    Plasma cholesterol lowering (PCL) slows and sometimes prevents progression of atherosclerosis and may even lead to regression. Little is known about how molecular processes in the atherosclerotic arterial wall respond to PCL and modify responses to atherosclerosis regression. We studied atherosclerosis regression and global gene expression responses to PCL (≥80%) and to atherosclerosis regression itself in early, mature, and advanced lesions. In atherosclerotic aortic wall from Ldlr−/−Apob 100/100 Mttp flox/floxMx1-Cre mice, atherosclerosis regressed after PCL regardless of lesion stage. However, near-complete regression was observed only in mice with early lesions; mice with mature and advanced lesions were left with regression-resistant, relatively unstable plaque remnants. Atherosclerosis genes responding to PCL before regression, unlike those responding to the regression itself, were enriched in inherited risk for coronary artery disease and myocardial infarction, indicating causality. Inference of transcription factor (TF) regulatory networks of these PCL-responsive gene sets revealed largely different networks in early, mature, and advanced lesions. In early lesions, PPARG was identified as a specific master regulator of the PCL-responsive atherosclerosis TF-regulatory network, whereas in mature and advanced lesions, the specific master regulators were MLL5 and SRSF10/XRN2, respectively. In a THP-1 foam cell model of atherosclerosis regression, siRNA targeting of these master regulators activated the time-point-specific TF-regulatory networks and altered the accumulation of cholesterol esters. We conclude that PCL leads to complete atherosclerosis regression only in mice with early lesions. Identified master regulators and related PCL-responsive TF-regulatory networks will be interesting targets to enhance PCL-mediated regression of mature and advanced atherosclerotic lesions. PMID:24586211

  17. Plasma cholesterol-induced lesion networks activated before regression of early, mature, and advanced atherosclerosis.

    PubMed

    Björkegren, Johan L M; Hägg, Sara; Talukdar, Husain A; Foroughi Asl, Hassan; Jain, Rajeev K; Cedergren, Cecilia; Shang, Ming-Mei; Rossignoli, Aránzazu; Takolander, Rabbe; Melander, Olle; Hamsten, Anders; Michoel, Tom; Skogsberg, Josefin

    2014-02-01

    Plasma cholesterol lowering (PCL) slows and sometimes prevents progression of atherosclerosis and may even lead to regression. Little is known about how molecular processes in the atherosclerotic arterial wall respond to PCL and modify responses to atherosclerosis regression. We studied atherosclerosis regression and global gene expression responses to PCL (≥80%) and to atherosclerosis regression itself in early, mature, and advanced lesions. In atherosclerotic aortic wall from Ldlr(-/-)Apob (100/100) Mttp (flox/flox)Mx1-Cre mice, atherosclerosis regressed after PCL regardless of lesion stage. However, near-complete regression was observed only in mice with early lesions; mice with mature and advanced lesions were left with regression-resistant, relatively unstable plaque remnants. Atherosclerosis genes responding to PCL before regression, unlike those responding to the regression itself, were enriched in inherited risk for coronary artery disease and myocardial infarction, indicating causality. Inference of transcription factor (TF) regulatory networks of these PCL-responsive gene sets revealed largely different networks in early, mature, and advanced lesions. In early lesions, PPARG was identified as a specific master regulator of the PCL-responsive atherosclerosis TF-regulatory network, whereas in mature and advanced lesions, the specific master regulators were MLL5 and SRSF10/XRN2, respectively. In a THP-1 foam cell model of atherosclerosis regression, siRNA targeting of these master regulators activated the time-point-specific TF-regulatory networks and altered the accumulation of cholesterol esters. We conclude that PCL leads to complete atherosclerosis regression only in mice with early lesions. Identified master regulators and related PCL-responsive TF-regulatory networks will be interesting targets to enhance PCL-mediated regression of mature and advanced atherosclerotic lesions.

  18. 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...

  19. 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.…

  20. 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

  1. 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.

  2. 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.

  3. 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

    2016-04-08

    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.

  4. 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

  5. In vitro and in vivo activities of antimicrobial peptides developed using an amino acid-based activity prediction method.

    PubMed

    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; Yang, Li

    2014-09-01

    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.

  6. 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

  7. 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.

  8. Solar geomagnetic activity prediction using the fractal analysis and neural network

    NASA Astrophysics Data System (ADS)

    Ouadfeul, Sid-Ali; Aliouane, Leila

    2010-05-01

    The main goal of this work is to predict the Solar geomagnetic field activity using the neural network combined with the fractal analysis, first a multilayer perceptron neural network model is proposed to predict the future Solar geomagnetic field, the input of this machine is the geographic Coordinates and the time .The output is the three geomagnetic field components and the total field intensity recorded by the Orsted Satellite Mission. Holder Exponents of the measured geomagnetic field components and the total field intensity are calculated using the continuous wavelet transform. The Set of Holder exponents is used to train a Kohonen's Self-Organizing Map (SOM) neural machine which will become a classifier of the solar magnetic activity nature. The SOM neural network machine is used to predict the future solar magnetic storms, in this step the input is the calculated set of the Holder exponents of the predicted geomagnetic field components and the total field intensity. Obtained results show that the proposed technique is a powerful tool and can enhance the solar magnetic field activity prediction. Keywords: Solar geomagnetic activity, neural network, prediction, Orsted, Holder Exponents, Solar magnetic storms.

  9. Advances in structural modifications and biological activities of berberine: an active compound in traditional Chinese medicine.

    PubMed

    Huang, Z-J; Zeng, Y; Lan, P; Sun, P-H; Chen, W-M

    2011-11-01

    Berberine is an isoquinoline alkaloid isolated from Chinese herbs such as Coptidis Rhizome. This paper is a systematic review of the structural modifications of berberine for different biological activities such as antitumor, antimicrobial, anti-Alzheimer's disease, antihyperglycemic, anti-inflammatory and antimalaria. The current review would provide some useful information for further studies on structural modification of berberine for discovering new drug leads.

  10. 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

  11. 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.

  12. 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.

  13. Core biological marker candidates of Alzheimer's disease - perspectives for diagnosis, prediction of outcome and reflection of biological activity.

    PubMed

    Hampel, H; Mitchell, A; Blennow, K; Frank, R A; Brettschneider, S; Weller, L; Möller, H-J

    2004-03-01

    Alzheimer's disease (AD) is a complex neurodegenerative dementing illness. Over the past few years, however, remarkable advances have taken place in understanding both the genetic and molecular biology with the intracellular processing of amyloid and tau and the changes leading to the pathologic formation of extracellular amyloid plaques and the intraneuronal aggregation of hyperphosphorylated tau into neurofibrillary tangles. This progress in our understanding of the molecular pathology has set the stage for clinically meaningful advances in the development of biomarkers. Emerging diagnostic methods that are based on biochemical and imaging biomarkers of disease specific pathology hold the potential to provide effective measures of natural history (marker of disease that is predictive of outcome), biological activity (such as magnitude and frequency of response correlating with drug potency) and markers of surrogate endpoints (single or composite marker that accounts for clinical benefit of the therapy). Markers of biological activity should be also evaluated regarding their value to reflect disease progression, heterogeneity of the clinical population, for early decision making and characterization of new treatments. We focussed on the current status of core analytes which provide reasonable evidence for association with key mechanisms of pathogenesis or neurodegeneration in AD. In addition, feasibility was important, such as availability of a validated assay for the biological measure in question, with properties that included high precision and reliability of measurement, reagents and standards well described. On this basis we reviewed the body of literature that has examined CSF total tau (t-tau) and beta-amyloid 1-42 (Abeta(1-42)), phosphorylated tau (p-tau) and beta-amyloid-antibodies as diagnostic tests for AD versus clinically representative comparison groups. Measurement of t-tau and Abeta(1-42) in the CSF seems useful to discriminate early and incipient

  14. 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.

  15. PREDICTING CIRRHOSIS AND CLINICAL OUTCOMES IN PATIENTS WITH ADVANCED CHRONIC HEPATITIS C WITH A PANEL OF GENETIC MARKERS (CRS7)

    PubMed Central

    Curto, Teresa M.; Lagier, Robert J.; Lok, Anna S.; Everhart, James E.; Rowland, Charles M.; Sninsky, John J.

    2011-01-01

    Objectives Genetic factors may play a role in fibrosis progression in patients with chronic hepatitis C (CHC). A cirrhosis risk score (CRS7) with 7 SNPs was previously shown to correlate with cirrhosis in patients with CHC. This study aimed to assess the validity of CRS7 as a marker of fibrosis progression and cirrhosis and as a predictor of clinical outcomes in patients with CHC. Methods A total of 938 patients (677 Caucasians, 165 African Americans, and 96 Hispanic/Other) in the HALT-C Trial were studied. CRS7 was categorized a priori as high risk (n=440), medium risk (n=310) or low risk (n=188). Patients were assessed for four possible outcomes: fibrosis progression, cirrhosis, clinical outcomes (decompensation or hepatocellular carcinoma [HCC]), or HCC alone. Results 29% (142/493) developed an increase in fibrosis score by ≥ 2 points on follow-up biopsies, 58% had cirrhosis on one or more biopsies, 35% developed at least one clinical outcome, and 13% developed HCC. CRS7 (trend test) was associated with risk for fibrosis progression (p=0.04) with adjusted hazard ratio (HR) of 1.27 (95%CI: 1.01–1.58) and with cirrhosis (p=0.05) with adjusted odds ratio (OR) of 1.19 (1.00–1.41). Rates of HCC and clinical outcomes were increased in patients with higher CRS7 scores, but were not statistically significant (p=0.12 clinical outcomes, and p=0.07 HCC). A SNP in AZIN1 was significantly associated with fibrosis progression. Conclusions CRS7 was validated as a predictor of fibrosis progression and cirrhosis among HALT-C patients, who all had advanced fibrosis. CRS7 was not predictive of clinical outcome. PMID:21946897

  16. 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

  17. Neural Activity During Health Messaging Predicts Reductions in Smoking Above and Beyond Self-Report

    PubMed Central

    Falk, Emily B.; Berkman, Elliot T.; Whalen, Danielle; Lieberman, Matthew D.

    2011-01-01

    Objective The current study tested whether neural activity in response to messages designed to help smokers quit could predict smoking reduction, above and beyond self-report. Design Using neural activity in an a priori region of interest (a subregion of medial prefrontal cortex [MPFC]), in response to ads designed to help smokers quit smoking, we prospectively predicted reductions in smoking in a community sample of smokers (N = 28) who were attempting to quit smoking. Smoking was assessed via expired carbon monoxide (CO; a biological measure of recent smoking) at baseline and 1 month following exposure to professionally developed quitting ads. Results A positive relationship was observed between activity in the MPFC region of interest and successful quitting (increased activity in MPFC was associated with a greater decrease in expired CO). The addition of neural activity to a model predicting changes in CO from self-reported intentions, self-efficacy, and ability to relate to the messages significantly improved model fit, doubling the variance explained ( Rself−report2=.15,Rself−report+neuralactivity2=.35,Rchange2=.20). Conclusion: Neural activity is a useful complement to existing self-report measures. In this investigation, we extend prior work predicting behavior change based on neural activity in response to persuasive media to an important health domain and discuss potential psychological interpretations of the brain–behavior link. Our results support a novel use of neuroimaging technology for understanding the psychology of behavior change and facilitating health promotion. PMID:21261410

  18. Impulsive approach tendencies towards physical activity and sedentary behaviors, but not reflective intentions, prospectively predict non-exercise activity thermogenesis.

    PubMed

    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.

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

    PubMed

    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.

  20. 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

  1. Mapping ECoG channel contributions to trajectory and muscle activity prediction in human sensorimotor cortex

    PubMed Central

    Nakanishi, Yasuhiko; Yanagisawa, Takufumi; Shin, Duk; Kambara, Hiroyuki; Yoshimura, Natsue; Tanaka, Masataka; Fukuma, Ryohei; Kishima, Haruhiko; Hirata, Masayuki; Koike, Yasuharu

    2017-01-01

    Studies on brain-machine interface techniques have shown that electrocorticography (ECoG) is an effective modality for predicting limb trajectories and muscle activity in humans. Motor control studies have also identified distributions of “extrinsic-like” and “intrinsic-like” neurons in the premotor (PM) and primary motor (M1) cortices. Here, we investigated whether trajectories and muscle activity predicted from ECoG were obtained based on signals derived from extrinsic-like or intrinsic-like neurons. Three participants carried objects of three different masses along the same counterclockwise path on a table. Trajectories of the object and upper arm muscle activity were predicted using a sparse linear regression. Weight matrices for the predictors were then compared to determine if the ECoG channels contributed more information about trajectory or muscle activity. We found that channels over both PM and M1 contributed highly to trajectory prediction, while a channel over M1 was the highest contributor for muscle activity prediction. PMID:28361947

  2. Mapping ECoG channel contributions to trajectory and muscle activity prediction in human sensorimotor cortex.

    PubMed

    Nakanishi, Yasuhiko; Yanagisawa, Takufumi; Shin, Duk; Kambara, Hiroyuki; Yoshimura, Natsue; Tanaka, Masataka; Fukuma, Ryohei; Kishima, Haruhiko; Hirata, Masayuki; Koike, Yasuharu

    2017-03-31

    Studies on brain-machine interface techniques have shown that electrocorticography (ECoG) is an effective modality for predicting limb trajectories and muscle activity in humans. Motor control studies have also identified distributions of "extrinsic-like" and "intrinsic-like" neurons in the premotor (PM) and primary motor (M1) cortices. Here, we investigated whether trajectories and muscle activity predicted from ECoG were obtained based on signals derived from extrinsic-like or intrinsic-like neurons. Three participants carried objects of three different masses along the same counterclockwise path on a table. Trajectories of the object and upper arm muscle activity were predicted using a sparse linear regression. Weight matrices for the predictors were then compared to determine if the ECoG channels contributed more information about trajectory or muscle activity. We found that channels over both PM and M1 contributed highly to trajectory prediction, while a channel over M1 was the highest contributor for muscle activity prediction.

  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.

  4. Optimization of a mathematical topological pattern for the prediction of antihistaminic activity

    NASA Astrophysics Data System (ADS)

    Duart, M. J.; García-Domenech, R.; Antón-Fos, G. M.; Gálvez, J.

    2001-06-01

    Molecular topology was used to develop a mathematical model capable of classifying compounds according to antihistaminic activity. The equations used for this purpose were derived using multilinear regression and linear discriminant analysis. The topological pattern of activity obtained allows the reliable prediction of antihistaminic activity in drugs frequently used for other therapeutic purposes. Based on the results, the proposed pattern is seemingly only valid for drugs that interact with histamine through competitive inhibition with H1 receptors.

  5. 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.

  6. Remote Bridge Deflection Measurement Using an Advanced Video Deflectometer and Actively Illuminated LED Targets.

    PubMed

    Tian, Long; Pan, Bing

    2016-08-23

    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.

  7. Remote Bridge Deflection Measurement Using an Advanced Video Deflectometer and Actively Illuminated LED Targets

    PubMed Central

    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

  8. Predicting the activation states of the muscles governing upper esophageal sphincter relaxation and opening

    PubMed Central

    Jones, Corinne A.; Hammer, Michael J.; Cock, Charles; Dinning, Philip; Wiklendt, Lukasz; Costa, Marcello; McCulloch, Timothy M.

    2016-01-01

    The swallowing muscles that influence upper esophageal sphincter (UES) opening are centrally controlled and modulated by sensory information. Activation and deactivation of neural inputs to these muscles, including the intrinsic cricopharyngeus (CP) and extrinsic submental (SM) muscles, results in their mechanical activation or deactivation, which changes the diameter of the lumen, alters the intraluminal pressure, and ultimately reduces or promotes flow of content. By measuring the changes in diameter, using intraluminal impedance, and the concurrent changes in intraluminal pressure, it is possible to determine when the muscles are passively or actively relaxing or contracting. From these “mechanical states” of the muscle, the neural inputs driving the specific motor behaviors of the UES can be inferred. In this study we compared predictions of UES mechanical states directly with the activity measured by electromyography (EMG). In eight subjects, pharyngeal pressure and impedance were recorded in parallel with CP- and SM-EMG activity. UES pressure and impedance swallow profiles correlated with the CP-EMG and SM-EMG recordings, respectively. Eight UES muscle states were determined by using the gradient of pressure and impedance with respect to time. Guided by the level and gradient change of EMG activity, mechanical states successfully predicted the activity of the CP muscle and SM muscle independently. Mechanical state predictions revealed patterns consistent with the known neural inputs activating the different muscles during swallowing. Derivation of “activation state” maps may allow better physiological and pathophysiological interpretations of UES function. PMID:26767985

  9. 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.

  10. ANL's electric vehicle battery activities for USABC. [US Advanced Battery Consortium (USABC)

    SciTech Connect

    Not Available

    1992-01-01

    The Electrochemical Technology Program at Argonne National Laboratory (ANL) provides advanced battery R D; technology transfer to industry; technical analyses, assessments, modeling, and databases; and independent testing and post-test analyses of advanced batteries. These capabilities and services are being offered to the US Advanced Battery Consortium (USABC) and Cooperative Research and Development Agreements (CRADA) are being negotiated for USABC-sponsored work at ANL. A small portion of DOE's cost share for USABC projects has been provided to ANL to continue R D and testing activities on key technologies that were previously supported directly by DOE. This report summarizes progress on these USABC projects during the period of April I through September 30, 1992. In this report, the objective, background, technical progress, and status are described for each task. The work is organized into the following task areas: 1.0 Lithium/Sulfide Batteries; 2.0 Nickel/Metal Hydride Support 3.0 EV Battery Performance and Life Evaluation.

  11. Clinical activity of sunitinib in patients with advanced desmoplastic round cell tumor: a case series.

    PubMed

    Italiano, Antoine; Kind, Michèle; Cioffi, Angela; Maki, Robert G; Bui, Binh

    2013-09-01

    Desmoplastic small round cell tumor (DSRCT) is a rare and aggressive malignancy with poor outcome occurring in adolescents and young adults. Therapeutic options for patients with advanced disease are limited. Preclinical studies have shown that VEGFR-2 and VEGFA are overexpressed in DSRCT and that DSRCT xenografts were highly responsive to anti-VEGF agents such as bevacizumab. We report here the clinical activity of sunitinib in eight patients with DSCRT. Our data suggest that sunitinib may be associated with clinical benefit even in heavily pretreated patients.

  12. Sipuleucel-T (Provenge): active cellular immunotherapy for advanced prostate cancer.

    PubMed

    McKarney, I

    2007-09-01

    (1) Sipuleucel-T (Provenge) is an active cellular immunotherapy (therapeutic vaccine) that is designed to stimulate the patient's T-cells to recognize and attack prostate cancer cells that express prostatic acid phosphatase (PAP) antigen. (2) Sipuleucel-T demonstrated a survival benefit in men with advanced androgen-independent prostate cancer (AIPC), although this preliminary finding requires confirmation in larger trials. (3) Mild to moderate myalgia, chills, fever, and tremor are the most commonly reported adverse events for patients receiving sipuleucel-T. These events generally resolve quickly. (4) More studies are needed to evaluate sipuleucel-T in the earlier stages of prostate cancer and in combination with conventional therapies.

  13. Prediction of cloud condensation nuclei activity for organic compounds using functional group contribution methods

    DOE PAGES

    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

  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.

  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.

    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.

  16. Computer-aided design and activity prediction of leucine aminopeptidase inhibitors

    NASA Astrophysics Data System (ADS)

    Grembecka, J.; Sokalski, W. A.; Kafarski, P.

    2000-08-01

    The Ligand Design (LUDI) approach has been used in order to design leucine aminopeptidase inhibitors, predict their activity and analyze their interactions with the enzyme. The investigation was based on the crystal structure of bovine lens leucine aminopeptidase (LAP) complexed with its inhibitor - the phosphonic acid analogue of leucine (LeuP). More than 50 potential leucine aminopeptidase inhibitors have been obtained, including the most potent aminophosphonic LAP inhibitors with experimentally known activity, which have been the subject of more detailed studies. A reasonable agreement between theoretical and experimental activities has been obtained for most of the studied inhibitors. Our results confirm that LUDI is a powerful tool for the design of enzyme inhibitors as well as in the prediction of their activity. In addition, for inhibitor-active site interactions dominated by the electrostatic effects it is possible to improve binding energy estimates by using a more accurate description of inhibitor charge distribution.

  17. Physical activity as an indicator of predictive functional disability in elderly.

    PubMed

    Virtuoso Júnior, Jair Sindra; Tribess, Sheilla; Paulo, Thais Reis Silva De; Martins, Cristiane Alves; Romo-Perez, Vicente

    2012-01-01

    To analyze the time spent on physical activity in female and male individuals as a predictor of the absence of functional disability in older adults, a cross-sectional study was conducted with 624 individuals. Receiver Operating Characteristic curves (ROC) were constructed and compared to areas of physical activity by gender and the absence of functional disability. We identified cutoffs of physical activity (minutes / week) to predict the absence of functional disability (CI 95%). It was found that there is a higher area under the ROC curve for the time spent on physical activities in females. It was observed that 280 minutes / week (women) or 410 minutes / week (men) were the best cutoff points for predicting the absence of functional disability. Time spent on physical activity practices can serve as an important indicator to sort priority groups for certain interventions.

  18. NESmapper: accurate prediction of leucine-rich nuclear export signals using activity-based profiles.

    PubMed

    Kosugi, Shunichi; Yanagawa, Hiroshi; Terauchi, Ryohei; Tabata, Satoshi

    2014-09-01

    The nuclear export of proteins is regulated largely through the exportin/CRM1 pathway, which involves the specific recognition of leucine-rich nuclear export signals (NESs) in the cargo proteins, and modulates nuclear-cytoplasmic protein shuttling by antagonizing the nuclear import activity mediated by importins and the nuclear import signal (NLS). Although the prediction of NESs can help to define proteins that undergo regulated nuclear export, current methods of predicting NESs, including computational tools and consensus-sequence-based searches, have limited accuracy, especially in terms of their specificity. We found that each residue within an NES largely contributes independently and additively to the entire nuclear export activity. We created activity-based profiles of all classes of NESs with a comprehensive mutational analysis in mammalian cells. The profiles highlight a number of specific activity-affecting residues not only at the conserved hydrophobic positions but also in the linker and flanking regions. We then developed a computational tool, NESmapper, to predict NESs by using profiles that had been further optimized by training and combining the amino acid properties of the NES-flanking regions. This tool successfully reduced the considerable number of false positives, and the overall prediction accuracy was higher than that of other methods, including NESsential and Wregex. This profile-based prediction strategy is a reliable way to identify functional protein motifs. NESmapper is available at http://sourceforge.net/projects/nesmapper.

  19. Modeled changes of cerebellar activity in mutant mice are predictive of their learning impairments

    PubMed Central

    Badura, Aleksandra; Clopath, Claudia; Schonewille, Martijn; De Zeeuw, Chris I.

    2016-01-01

    Translating neuronal activity to measurable behavioral changes has been a long-standing goal of systems neuroscience. Recently, we have developed a model of phase-reversal learning of the vestibulo-ocular reflex, a well-established, cerebellar-dependent task. The model, comprising both the cerebellar cortex and vestibular nuclei, reproduces behavioral data and accounts for the changes in neural activity during learning in wild type mice. Here, we used our model to predict Purkinje cell spiking as well as behavior before and after learning of five different lines of mutant mice with distinct cell-specific alterations of the cerebellar cortical circuitry. We tested these predictions by obtaining electrophysiological data depicting changes in neuronal spiking. We show that our data is largely consistent with the model predictions for simple spike modulation of Purkinje cells and concomitant behavioral learning in four of the mutants. In addition, our model accurately predicts a shift in simple spike activity in a mutant mouse with a brainstem specific mutation. This combination of electrophysiological and computational techniques opens a possibility of predicting behavioral impairments from neural activity. PMID:27805050

  20. Modeled changes of cerebellar activity in mutant mice are predictive of their learning impairments

    NASA Astrophysics Data System (ADS)

    Badura, Aleksandra; Clopath, Claudia; Schonewille, Martijn; de Zeeuw, Chris I.

    2016-11-01

    Translating neuronal activity to measurable behavioral changes has been a long-standing goal of systems neuroscience. Recently, we have developed a model of phase-reversal learning of the vestibulo-ocular reflex, a well-established, cerebellar-dependent task. The model, comprising both the cerebellar cortex and vestibular nuclei, reproduces behavioral data and accounts for the changes in neural activity during learning in wild type mice. Here, we used our model to predict Purkinje cell spiking as well as behavior before and after learning of five different lines of mutant mice with distinct cell-specific alterations of the cerebellar cortical circuitry. We tested these predictions by obtaining electrophysiological data depicting changes in neuronal spiking. We show that our data is largely consistent with the model predictions for simple spike modulation of Purkinje cells and concomitant behavioral learning in four of the mutants. In addition, our model accurately predicts a shift in simple spike activity in a mutant mouse with a brainstem specific mutation. This combination of electrophysiological and computational techniques opens a possibility of predicting behavioral impairments from neural activity.

  1. PASS assisted prediction and pharmacological evaluation of novel nicotinic analogs for nootropic activity in mice.

    PubMed

    Khurana, Navneet; Ishar, Mohan Pal Singh; Gajbhiye, Asmita; Goel, Rajesh Kumar

    2011-07-15

    The aim of present study is to predict the probable nootropic activity of novel nicotine analogues with the help of computer program, PASS (prediction of activity spectra for substances) and evaluate the same. Two compounds from differently substituted pyridines were selected for synthesis and evaluation of nootropic activity based on their high probable activity (Pa) value predicted by PASS computer program. Evaluation of nootropic activity of compounds after acute and chronic treatment was done with transfer latency (TL) and step down latency (SDL) methods which showed significant nootropic activity. The effect on scopolamine induced amnesia was also observed along with their acetylcholine esterase inhibitory activity which also showed positive results which strengthened their efficacy as nootropic agents through involvement of cholinergic system. This nootropic effect was similar to the effect of nicotine and donepezil used as standard drugs. Muscle coordination and locomotor activity along with their addiction liability, safety and tolerability studies were also evaluated. These studies showed that these compounds are well tolerable and safe over a wide range of doses tested along with the absence of withdrawal effect which is present in nicotine due to its addiction liability. The study showed that these compounds are true nicotine analogs with desirable efficacy and safety profile for their use as effective nootropic agents.

  2. 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…

  3. Recent advances in endophytic exopolysaccharides: Production, structural characterization, physiological role and biological activity.

    PubMed

    Liu, Jun; Wang, Xingchi; Pu, Huimin; Liu, Shuang; Kan, Juan; Jin, Changhai

    2017-02-10

    Endophytes are microorganisms that colonize living, internal tissues of plants without causing any immediate, overt negative effects. In recent years, both endophytic bacteria and fungi have been demonstrated to be excellent exopolysaccharides (EPS) producers. This review focuses on the recent advances in EPS produced by endophytes, including its production, isolation and purification, structural characterization, physiological role and biological activity. In general, EPS production is influenced by media components and cultivation conditions. The structures of purified EPS range from linear homopolysaccharides to highly branched heteropolysaccharides. These structurally novel EPS not only play important roles in plant-endophyte interactions; but also exhibit several biological functions, such as antioxidant, antitumor, anti-inflammatory, anti-allergic and prebiotic activities. In order to utilize endophytic EPS on an industrial scale, both yield and productivity enhancement strategies are required at several levels. Besides, the exact mechanisms on the physiological roles and biological functions of EPS should be elucidated in future.

  4. 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

    2010-11-02

    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.

  5. Dopamine regulates distinctively the activity patterns of striatal output neurons in advanced parkinsonian primates

    PubMed Central

    Singh, Arun; Liang, Li; Kaneoke, Yoshiki; Cao, Xuebing

    2014-01-01

    Nigrostriatal dopamine denervation plays a major role in basal ganglia circuitry disarray and motor abnormalities of Parkinson's disease (PD). Studies in rodent and primate models have revealed that striatal projection neurons, namely, medium spiny neurons (MSNs), increase the firing frequency. However, their activity pattern changes and the effects of dopaminergic stimulation in such conditions are unknown. Using single-cell recordings in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated primates with advanced parkinsonism, we studied MSN activity patterns in the transition to different motor states following levodopa administration. In the “off” state (baseline parkinsonian disability), a burst-firing pattern accompanied by prolonged silences (pauses) was found in 34% of MSNs, and 80% of these exhibited a levodopa response compatible with dopamine D1 receptor activation (direct pathway MSNs). This pattern was highly responsive to levodopa given that bursting/pausing almost disappeared in the “on” state (reversal of parkinsonism after levodopa injection), although this led to higher firing rates. Nonbursty MSNs fired irregularly with marked pausing that increased in the on state in the MSN subset with a levodopa response compatible with dopamine D2 receptor activation (indirect pathway MSNs), although the pause increase was not sustained in some units during the appearance of dyskinesias. Data indicate that the MSN firing pattern in the advanced parkinsonian monkey is altered by bursting and pausing changes and that dopamine differentially and inefficiently regulates these behaviorally correlated patterns in MSN subpopulations. These findings may contribute to understand the impact of striatal dysfunction in the basal ganglia network and its role in motor symptoms of PD. PMID:25505120

  6. Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products.

    PubMed

    Hong, Huixiao; Rua, Diego; Sakkiah, Sugunadevi; Selvaraj, Chandrabose; Ge, Weigong; Tong, Weida

    2016-09-29

    Sunscreen products are predominantly regulated as over-the-counter (OTC) drugs by the US FDA. The "active" ingredients function as ultraviolet filters. Once a sunscreen product is generally recognized as safe and effective (GRASE) via an OTC drug review process, new formulations using these ingredients do not require FDA review and approval, however, the majority of ingredients have never been tested to uncover any potential endocrine activity and their ability to interact with the estrogen receptor (ER) is unknown, despite the fact that this is a very extensively studied target related to endocrine activity. Consequently, we have developed an in silico model to prioritize single ingredient estrogen receptor activity for use when actual animal data are inadequate, equivocal, or absent. It relies on consensus modeling to qualitatively and quantitatively predict ER binding activity. As proof of concept, the model was applied to ingredients commonly used in sunscreen products worldwide and a few reference chemicals. Of the 32 chemicals with unknown ER binding activity that were evaluated, seven were predicted to be active estrogenic compounds. Five of the seven were confirmed by the published data. Further experimental data is needed to confirm the other two predictions.

  7. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  9. NASA's Advancements in Space-Based Spectrometry Lead to Improvements in Weather Prediction and Understanding of Climate Processes

    NASA Technical Reports Server (NTRS)

    Susskind, Joel; Iredell, Lena

    2010-01-01

    AIRS (Atmospheric Infra-Red Sounder), was launched, in conjunction with AMSU-A (Advanced Microwave Sounding Unit-A) on the NASA polar orbiting research satellite EOS (Earth Observing System) Aqua satellite in May 2002 as a next generation atmospheric sounding system. Atmospheric sounders provide information primarily about the vertical distribution of atmospheric temperature and water vapor distribution. This is achieved by measuring outgoing radiation in discrete channels (spectral intervals) which are sensitive primarily to variations of these geophysical parameters. The primary objectives of AIRS/AMSU were to utilize such information in order to improve the skill of numerical weather prediction as well as to measure climate variability and trends. AIRS is a multi-detector array grating spectrometer with 2378 channels covering the spectral range 650/cm (15 microns) to 2660/cm (3.6 microns) with a resolving power (i/a i) of roughly 1200 where a i is the spectral channel bandpass. Atmospheric temperature profile can be determined from channel observations taken within the 15 micron (the long-wave CO2 absorption band) and within the 4.2 micron (the short-wave CO2 absorption band). Radiances in these (and all other) spectral intervals in the infrared are also sensitive to the presence of clouds in the instrument?s field of view (FOV), which are present about 95% of the time. AIRS was designed so as to allow for the ability to produce accurate Quality Controlled atmospheric soundings under most cloud conditions. This was achieved by having 1) extremely low channel noise values in the shortwave portion of the spectrum and 2) a very flat spatial response function within a channel?s FOV. IASI, the high spectral resolution IR interferometer flying on the European METOP satellite, does not contain either of these important characteristics. The AIRS instrument was also designed to be extremely stabile with regard to its spectral radiometric characteristics, which is

  10. The predictability of serum anti-Müllerian level in IVF/ICSI outcomes for patients of advanced reproductive age

    PubMed Central

    2011-01-01

    Background The role of serum anti-Müllerian hormone (AMH) as predictor of in-vitro fertilization outcomes has been much debated. The aim of the present study is to investigate the practicability of combining serum AMH level with biological age as a simple screening method for counseling IVF candidates of advanced reproductive age with potential poor outcomes prior to treatment initiation. Methods A total of 1,538 reference patients and 116 infertile patients aged greater than or equal to 40 years enrolled in IVF/ICSI cycles were recruited in this retrospective analysis. A reference chart of the age-related distribution of serum AMH level for Asian population was first created. IVF/ICSI patients aged greater than or equal to 40 years were then divided into three groups according to the low, middle and high tertiles the serum AMH tertiles derived from the reference population of matching age. The cycle outcomes were analyzed and compared among each individual group. Results For reference subjects aged greater than or equal to 40 years, the serum AMH of the low, middle and high tertiles were equal or lesser than 0.48, 0.49-1.22 and equal or greater than 1.23 ng/mL respectively. IVF/ICSI patients aged greater than or equal to 40 years with AMH levels in the low tertile had the highest cycle cancellation rate (47.6%) with zero clinical pregnancy. The nadir AMH level that has achieved live birth was 0.56 ng/mL, which was equivalent to the 36.4th percentile of AMH level from the age-matched reference group. The optimum cut-off levels of AMH for the prediction of nonpregnancy and cycle cancellation were 1.05 and 0.68 ng/mL, respectively. Conclusions Two criteria: (1) age greater than or equal to 40 years and (2) serum AMH level in the lowest tertile (equal or lesser than 33.3rd percentile) of the matching age group, may be used as markers of futility for counseling IVF/ICSI candidates. PMID:21843363

  11. Mice Expressing Activated PI3K Rapidly Develop Advanced Colon Cancer

    PubMed Central

    Leystra, Alyssa A.; Deming, Dustin A.; Zahm, Christopher D.; Farhoud, Mohammed; Paul Olson, Terrah J.; Hadac, Jamie N.; Nettekoven, Laura A.; Albrecht, Dawn M.; Clipson, Linda; Sullivan, Ruth; Washington, Mary Kay; Torrealba, Jose R.; Weichert, Jamey P.; Halberg, Richard B.

    2012-01-01

    Aberrations in the phosphatidylinositide-3-kinase (PI3K) signaling pathway play a key role in the pathogenesis of numerous cancers by altering cellular growth, metabolism, proliferation, and apoptosis (1). Mutations in the catalytic domain of PI3K that generate a dominantly active kinase are commonly found in human colorectal cancers and have been thought to drive tumor progression, but not initiation (2). However, the effects of constitutively activated PI3K upon the intestinal mucosa have not been previously studied in animal models. Here, we demonstrate that the expression of a dominantly active form of the PI3K protein in the mouse intestine results in hyperplasia and advanced neoplasia. Mice expressing constitutively active PI3K in the epithelial cells of the distal small bowel and colon rapidly developed invasive adenocarcinomas in the colon that spread into the mesentery and adjacent organs. The histological characteristics of these tumors were strikingly similar to invasive mucinous colon cancers in humans. Interestingly, these tumors formed without a benign polypoid intermediary, consistent with the lack of aberrant WNT signaling observed. Together, our findings indicate a non-canonical mechanism of colon tumor initiation that is mediated through activation of PI3K. This unique model has the potential to further our understanding of human disease and facilitate the development of therapeutics through pharmacologic screening and biomarker identification. PMID:22525701

  12. Hydrogen Sulfide Prevents Advanced Glycation End-Products Induced Activation of the Epithelial Sodium Channel

    PubMed Central

    Wang, Qiushi; Song, Binlin; Jiang, Shuai; Liang, Chen; Chen, Xiao; Shi, Jing; Li, Xinyuan; Sun, Yingying; Wu, Mingming; Zhao, Dan; Zhang, Zhi-Ren; Ma, He-Ping

    2015-01-01

    Advanced glycation end-products (AGEs) are complex and heterogeneous compounds implicated in diabetes. Sodium reabsorption through the epithelial sodium channel (ENaC) at the distal nephron plays an important role in diabetic hypertension. Here, we report that H2S antagonizes AGEs-induced ENaC activation in A6 cells. ENaC open probability (PO) in A6 cells was significantly increased by exogenous AGEs and that this AGEs-induced ENaC activity was abolished by NaHS (a donor of H2S) and TEMPOL. Incubating A6 cells with the catalase inhibitor 3-aminotriazole (3-AT) mimicked the effects of AGEs on ENaC activity, but did not induce any additive effect. We found that the expression levels of catalase were significantly reduced by AGEs and both AGEs and 3-AT facilitated ROS uptake in A6 cells, which were significantly inhibited by NaHS. The specific PTEN and PI3K inhibitors, BPV(pic) and LY294002, influence ENaC activity in AGEs-pretreated A6 cells. Moreover, after removal of AGEs from AGEs-pretreated A6 cells for 72 hours, ENaC PO remained at a high level, suggesting that an AGEs-related “metabolic memory” may be involved in sodium homeostasis. Our data, for the first time, show that H2S prevents AGEs-induced ENaC activation by targeting the ROS/PI3K/PTEN pathway. PMID:26078825

  13. Hydrogen Sulfide Prevents Advanced Glycation End-Products Induced Activation of the Epithelial Sodium Channel.

    PubMed

    Wang, Qiushi; Song, Binlin; Jiang, Shuai; Liang, Chen; Chen, Xiao; Shi, Jing; Li, Xinyuan; Sun, Yingying; Wu, Mingming; Zhao, Dan; Zhang, Zhi-Ren; Ma, He-Ping

    2015-01-01

    Advanced glycation end-products (AGEs) are complex and heterogeneous compounds implicated in diabetes. Sodium reabsorption through the epithelial sodium channel (ENaC) at the distal nephron plays an important role in diabetic hypertension. Here, we report that H2S antagonizes AGEs-induced ENaC activation in A6 cells. ENaC open probability (P O ) in A6 cells was significantly increased by exogenous AGEs and that this AGEs-induced ENaC activity was abolished by NaHS (a donor of H2S) and TEMPOL. Incubating A6 cells with the catalase inhibitor 3-aminotriazole (3-AT) mimicked the effects of AGEs on ENaC activity, but did not induce any additive effect. We found that the expression levels of catalase were significantly reduced by AGEs and both AGEs and 3-AT facilitated ROS uptake in A6 cells, which were significantly inhibited by NaHS. The specific PTEN and PI3K inhibitors, BPV(pic) and LY294002, influence ENaC activity in AGEs-pretreated A6 cells. Moreover, after removal of AGEs from AGEs-pretreated A6 cells for 72 hours, ENaC P O remained at a high level, suggesting that an AGEs-related "metabolic memory" may be involved in sodium homeostasis. Our data, for the first time, show that H2S prevents AGEs-induced ENaC activation by targeting the ROS/PI3K/PTEN pathway.

  14. Inhibition of AKR1C3 Activation Overcomes Resistance to Abiraterone in Advanced Prostate Cancer.

    PubMed

    Liu, Chengfei; Armstrong, Cameron M; Lou, Wei; Lombard, Alan; Evans, Christopher P; Gao, Allen C

    2017-01-01

    Abiraterone suppresses intracrine androgen synthesis via inhibition of CYP17A1. However, clinical evidence suggests that androgen synthesis is not fully inhibited by abiraterone and the sustained androgen production may lead to disease relapse. In the present study, we identified AKR1C3, an important enzyme in the steroidogenesis pathway, as a critical mechanism driving resistance to abiraterone through increasing intracrine androgen synthesis and enhancing androgen signaling. We found that overexpression of AKR1C3 confers resistance to abiraterone while downregulation of AKR1C3 resensitizes resistant cells to abiraterone treatment. In abiraterone-resistant prostate cancer cells, AKR1C3 is overexpressed and the levels of intracrine androgens are elevated. In addition, AKR1C3 activation increases intracrine androgen synthesis and enhances androgen receptor (AR) signaling via activating AR transcriptional activity. Treatment of abiraterone-resistant cells with indomethacin, an AKR1C3 inhibitor, overcomes resistance and enhances abiraterone therapy both in vitro and in vivo by reducing the levels of intracrine androgens and diminishing AR transcriptional activity. These results demonstrate that AKR1C3 activation is a critical mechanism of resistance to abiraterone through increasing intracrine androgen synthesis and enhancing androgen signaling. Furthermore, this study provides a preclinical proof-of-principle for clinical trials investigating the combination of targeting AKR1C3 using indomethacin with abiraterone for advanced prostate cancer. Mol Cancer Ther; 16(1); 35-44. ©2016 AACR.

  15. Music-induced emotions can be predicted from a combination of brain activity and acoustic features.

    PubMed

    Daly, Ian; Williams, Duncan; Hallowell, James; Hwang, Faustina; Kirke, Alexis; Malik, Asad; Weaver, James; Miranda, Eduardo; Nasuto, Slawomir J

    2015-12-01

    It is widely acknowledged that music can communicate and induce a wide range of emotions in the listener. However, music is a highly-complex audio signal composed of a wide range of complex time- and frequency-varying components. Additionally, music-induced emotions are known to differ greatly between listeners. Therefore, it is not immediately clear what emotions will be induced in a given individual by a piece of music. We attempt to predict the music-induced emotional response in a listener by measuring the activity in the listeners electroencephalogram (EEG). We combine these measures with acoustic descriptors of the music, an approach that allows us to consider music as a complex set of time-varying acoustic features, independently of any specific music theory. Regression models are found which allow us to predict the music-induced emotions of our participants with a correlation between the actual and predicted responses of up to r=0.234,p<0.001. This regression fit suggests that over 20% of the variance of the participant's music induced emotions can be predicted by their neural activity and the properties of the music. Given the large amount of noise, non-stationarity, and non-linearity in both EEG and music, this is an encouraging result. Additionally, the combination of measures of brain activity and acoustic features describing the music played to our participants allows us to predict music-induced emotions with significantly higher accuracies than either feature type alone (p<0.01).

  16. Neural Activities Underlying the Feedback Express Salience Prediction Errors for Appetitive and Aversive Stimuli

    PubMed Central

    Gu, Yan; Hu, Xueping; Pan, Weigang; Yang, Chun; Wang, Lijun; Li, Yiyuan; Chen, Antao

    2016-01-01

    Feedback information is essential for us to adapt appropriately to the environment. The feedback-related negativity (FRN), a frontocentral negative deflection after the delivery of feedback, has been found to be larger for outcomes that are worse than expected, and it reflects a reward prediction error derived from the midbrain dopaminergic projections to the anterior cingulate cortex (ACC), as stated in reinforcement learning theory. In contrast, the prediction of response-outcome (PRO) model claims that the neural activity in the mediofrontal cortex (mPFC), especially the ACC, is sensitive to the violation of expectancy, irrespective of the valence of feedback. Additionally, increasing evidence has demonstrated significant activities in the striatum, anterior insula and occipital lobe for unexpected outcomes independently of their valence. Thus, the neural mechanism of the feedback remains under dispute. Here, we investigated the feedback with monetary reward and electrical pain shock in one task via functional magnetic resonance imaging. The results revealed significant prediction-error-related activities in the bilateral fusiform gyrus, right middle frontal gyrus and left cingulate gyrus for both money and pain. This implies that some regions underlying the feedback may signal a salience prediction error rather than a reward prediction error. PMID:27694920

  17. Variability in affective activation predicts non-suicidal self-injury in eating disorders.

    PubMed

    Vansteelandt, Kristof; Claes, Laurence; Muehlenkamp, Jennifer; De Cuyper, Kathleen; Lemmens, Jos; Probst, Michel; Vanderlinden, Johan; Pieters, Guido

    2013-03-01

    We examined whether affective variability can predict non-suicidal self-injury (NSSI) in eating disorders. Affect was represented by valence (positive versus negative) and activation (high versus low). Twenty-one patients with anorexia nervosa-restricting type, 18 patients with anorexia nervosa-binge-purging type and 20 patients with bulimia nervosa reported their momentary affect at nine random times a day during a one week period using a hand-held computer. Affective variability was calculated as the within-person standard deviation of valence and activation over time. Results indicate that patients displaying greater variability in activation and using selective serotonin reuptake inhibitors have a higher probability to engage in lifetime NSSI after adjustment for depression and borderline personality disorder. Neither variability of valence nor mean level of valence and activation had any predictive association with engaging in NSSI. It is suggested that the treatment of NSSI should focus on affect stabilization rather than reducing negative affect.

  18. 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

  19. 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

  20. 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.

  1. Structural maturation and brain activity predict future working memory capacity during childhood development.

    PubMed

    Ullman, Henrik; Almeida, Rita; Klingberg, Torkel

    2014-01-29

    Human working memory capacity develops during childhood and is a strong predictor of future academic performance, in particular, achievements in mathematics and reading. Predicting working memory development is important for the early identification of children at risk for poor cognitive and academic development. Here we show that structural and functional magnetic resonance imaging data explain variance in children's working memory capacity 2 years later, which was unique variance in addition to that predicted using cognitive tests. While current working memory capacity correlated with frontoparietal cortical activity, the future capacity could be inferred from structure and activity in basal ganglia and thalamus. This gives a novel insight into the neural mechanisms of childhood development and supports the idea that neuroimaging can have a unique role in predicting children's cognitive development.

  2. 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

  3. 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

  4. 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…

  5. QSAR classification models for the prediction of endocrine disrupting activity of brominated flame retardants.

    PubMed

    Kovarich, Simona; Papa, Ester; Gramatica, Paola

    2011-06-15

    The identification of potential endocrine disrupting (ED) chemicals is an important task for the scientific community due to their diffusion in the environment; the production and use of such compounds will be strictly regulated through the authorization process of the REACH regulation. To overcome the problem of insufficient experimental data, the quantitative structure-activity relationship (QSAR) approach is applied to predict the ED activity of new chemicals. In the present study QSAR classification models are developed, according to the OECD principles, to predict the ED potency for a class of emerging ubiquitary pollutants, viz. brominated flame retardants (BFRs). Different endpoints related to ED activity (i.e. aryl hydrocarbon receptor agonism and antagonism, estrogen receptor agonism and antagonism, androgen and progesterone receptor antagonism, T4-TTR competition, E2SULT inhibition) are modeled using the k-NN classification method. The best models are selected by maximizing the sensitivity and external predictive ability. We propose simple QSARs (based on few descriptors) characterized by internal stability, good predictive power and with a verified applicability domain. These models are simple tools that are applicable to screen BFRs in relation to their ED activity, and also to design safer alternatives, in agreement with the requirements of REACH regulation at the authorization step.

  6. 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

  7. Prediction of Muscle Activities from Electrocorticograms in Primary Motor Cortex of Primates

    PubMed Central

    Kambara, Hiroyuki; Nambu, Atsushi; Isa, Tadashi; Nishimura, Yukio; Koike, Yasuharu

    2012-01-01

    Electrocorticography (ECoG) has drawn attention as an effective recording approach for brain-machine interfaces (BMI). Previous studies have succeeded in classifying movement intention and predicting hand trajectories from ECoG. Despite such successes, however, there still remains considerable work for the realization of ECoG-based BMIs as neuroprosthetics. We developed a method to predict multiple muscle activities from ECoG measurements. We also verified that ECoG signals are effective for predicting muscle activities in time varying series when performing sequential movements. ECoG signals were band-pass filtered into separate sensorimotor rhythm bands, z-score normalized, and smoothed with a Gaussian filter. We used sparse linear regression to find the best fit between frequency bands of ECoG and electromyographic activity. The best average correlation coefficient and the normalized root-mean-square error were 0.92±0.06 and 0.06±0.10, respectively, in the flexor digitorum profundus finger muscle. The δ (1.5∼4Hz) and γ2 (50∼90Hz) bands contributed significantly more strongly than other frequency bands (P<0.001). These results demonstrate the feasibility of predicting muscle activity from ECoG signals in an online fashion. PMID:23110153

  8. Testing Predictions of the Interactive Activation Model in Recovery from Aphasia after Treatment

    ERIC Educational Resources Information Center

    Jokel, Regina; Rochon, Elizabeth; Leonard, Carol

    2004-01-01

    This paper presents preliminary results of pre- and post-treatment error analysis from an aphasic patient with anomia. The Interactive Activation (IA) model of word production (Dell, Schwartz, Martin, Saffran, & Gagnon, 1997) is utilized to make predictions about the anticipated changes on a picture naming task and to explain emerging patterns.…

  9. Predicting Social Responsibility and Belonging in Urban After-School Physical Activity Programs with Underserved Children

    ERIC Educational Resources Information Center

    Martin, Jeffrey J.; Byrd, Brigid; Garn, Alex; McCaughtry, Nate; Kulik, Noel; Centeio, Erin

    2016-01-01

    The purpose of this cross sectional study was to predict feelings of belonging and social responsibility based on the motivational climate perceptions and contingent self-worth of children participating in urban after-school physical activity programs. Three-hundred and four elementary school students from a major Midwestern city participated.…

  10. 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…

  11. Consensus Modeling for Prediction of Estrogenic Activity of Ingredients Commonly Used in Sunscreen Products

    PubMed Central

    Hong, Huixiao; Rua, Diego; Sakkiah, Sugunadevi; Selvaraj, Chandrabose; Ge, Weigong; Tong, Weida

    2016-01-01

    Sunscreen products are predominantly regulated as over-the-counter (OTC) drugs by the US FDA. The “active” ingredients function as ultraviolet filters. Once a sunscreen product is generally recognized as safe and effective (GRASE) via an OTC drug review process, new formulations using these ingredients do not require FDA review and approval, however, the majority of ingredients have never been tested to uncover any potential endocrine activity and their ability to interact with the estrogen receptor (ER) is unknown, despite the fact that this is a very extensively studied target related to endocrine activity. Consequently, we have developed an in silico model to prioritize single ingredient estrogen receptor activity for use when actual animal data are inadequate, equivocal, or absent. It relies on consensus modeling to qualitatively and quantitatively predict ER binding activity. As proof of concept, the model was applied to ingredients commonly used in sunscreen products worldwide and a few reference chemicals. Of the 32 chemicals with unknown ER binding activity that were evaluated, seven were predicted to be active estrogenic compounds. Five of the seven were confirmed by the published data. Further experimental data is needed to confirm the other two predictions. PMID:27690075

  12. Machine learning methods and docking for predicting human pregnane X receptor activation.

    PubMed

    Khandelwal, Akash; Krasowski, Matthew D; Reschly, Erica J; Sinz, Michael W; Swaan, Peter W; Ekins, Sean

    2008-07-01

    The pregnane X receptor (PXR) regulates the expression of genes involved in xenobiotic metabolism and transport. In vitro methods to screen for PXR agonists are used widely. In the current study, computational models for human PXR activators and PXR nonactivators were developed using recursive partitioning (RP), random forest (RF), and support vector machine (SVM) algorithms with VolSurf descriptors. Following 10-fold randomization, the models correctly predicted 82.6-98.9% of activators and 62.0-88.6% of nonactivators. The models were validated using separate test sets. The overall ( n = 15) test set prediction accuracy for PXR activators with RP, RF, and SVM PXR models is 80-93.3%, representing an improvement over models previously reported. All models were tested with a second test set ( n = 145), and the prediction accuracy ranged from 63 to 67% overall. These test set molecules were found to cover the same area in a principal component analysis plot as the training set, suggesting that the predictions were within the applicability domain. The FlexX docking method combined with logistic regression performed poorly in classifying this PXR test set as compared with RP, RF, and SVM but may be useful for qualitative interpretion of interactions within the LBD. From this analysis, VolSurf descriptors and machine learning methods had good classification accuracy and made reliable predictions within the model applicability domain. These methods could be used for high throughput virtual screening to assess for PXR activation, prior to in vitro testing to predict potential drug-drug interactions.

  13. Can activated sludge treatments and advanced oxidation processes remove organophosphorus flame retardants?

    PubMed

    Cristale, Joyce; Ramos, Dayana D; Dantas, Renato F; Machulek Junior, Amilcar; Lacorte, Silvia; Sans, Carme; Esplugas, Santiago

    2016-01-01

    This study aims to determine the occurrence of 10 OPFRs (including chlorinated, nonchlorinated alkyl and aryl compounds) in influent, effluent wastewaters and partitioning into sludge of 5 wastewater treatment plants (WWTP) in Catalonia (Spain). All target OPFRs were detected in the WWTPs influents, and the total concentration ranged from 3.67 µg L(-1) to 150 µg L(-1). During activated sludge treatment, most OPFRs were accumulated in the sludge at concentrations from 35.3 to 9980 ng g(-1) dw. Chlorinated compounds tris(2-chloroethyl) phosphate (TCEP), tris(2-chloroisopropyl) phosphate (TCIPP) and tris(2,3-dichloropropyl) phosphate (TDCPP) were not removed by the conventional activated sludge treatment and they were released by the effluents at approximately the same inlet concentration. On the contrary, aryl compounds tris(methylphenyl) phosphate (TMPP) and 2-ethylhexyl diphenyl phosphate (EHDP) together with alkyl tris(2-ethylhexyl) phosphate (TEHP) were not detected in any of the effluents. Advanced oxidation processes (UV/H2O2 and O3) were applied to investigate the degradability of recalcitrant OPFRs in WWTP effluents. Those detected in the effluent sample (TCEP, TCIPP, TDCPP, tributyl phosphate (TNBP), tri-iso-butyl phosphate (TIBP) and tris(2-butoxyethyl) phosphate (TBOEP)) had very low direct UV-C photolysis rates. TBOEP, TNBP and TIBP were degraded by UV/H2O2 and O3. Chlorinated compounds TCEP, TDCPP and TCIPP were the most recalcitrant OPFR to the advanced oxidation processes applied. The study provides information on the partitioning and degradability pathways of OPFR within conventional activated sludge WWTPs.

  14. Carbon fibers: Thermochemical recovery from advanced composite materials and activation to an adsorbent

    NASA Astrophysics Data System (ADS)

    Staley, Todd Andrew

    This research addresses an expanding waste disposal problem brought about by the increasing use of advanced composite materials, and the lack of technically and environmentally viable recycling methods for these materials. A thermochemical treatment process was developed and optimized for the recycling of advanced composite materials. Counter-current gasification was employed for the treatment of carbon fiber reinforced-epoxy resin composite wastes. These materials were treated, allowing the reclamation of the material's valuable components. As expected in gasification, the organic portion of the waste was thermochemically converted to a combustible gas with small amounts of organic compounds that were identified by GC/MS. These compounds were expected based on data in the literature. The composites contain 70% fiber reinforcement, and gasification yielded approximately 70% recovered fibers, representing nearly complete recovery of fibers from the waste. Through SEM and mechanical testing, the recovered carbon fibers were found to be structurally and mechanically intact, and amenable to re-use in a variety of applications, some of which were identified and tested. In addition, an application was developed for the carbon fiber component of the waste, as an activated carbon fiber adsorbent for the treatment of wastewaters. This novel class of adsorbent was found to have adsorption rates, for various organic molecules, up to a factor of ten times those of commercial granular activated carbon, and adsorption capacities similar to conventional activated carbons. Overall, the research addresses an existing environmental waste problem, employing a thermochemical technique to recycle and reclaim the waste. Components of the reclaimed waste material are then employed, after further modification, to address other existing and potential environmental waste problems.

  15. Role of spontaneous physical activity in prediction of susceptibility to activity based anorexia in male and female rats.

    PubMed

    Perez-Leighton, Claudio E; Grace, Martha; Billington, Charles J; Kotz, Catherine M

    2014-08-01

    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 may 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 that 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.

  16. Activity of gefitinib in advanced non-small-cell lung cancer with very poor performance status.

    PubMed

    Chang, Gee-Chen; Chen, Kun-Chieh; Yang, Tsung-Ying; Yin, Ming-Chang; Lin, Ching-Pei; Kuo, Benjamin Ing-Tiau; Hsu, Jeng-Yuan

    2005-01-01

    Advanced non-small-cell lung cancer (NSCLC) patients with poor performance status (PS) are less likely to respond to chemotherapy, or to have an improvement in survival, but more likely to experience toxicity. We retrospectively evaluated the efficacy and tolerability of gefitinib in patients with advanced NSCLC and very poor PS in Taiwan. Patients with stage IIIB, IV NSCLC with an Eastern Cooperative Oncology Group (ECOG) PS of 3-4 received oral gefitinib 250 mg once daily. Totally, 52 patients were included (25 men, 27 women). Forty-three patients (82.7%) were in a PS of 3. Tumor response rate was 25.0% (13/52). Tumor response rate to gefitinib was highest in chemonaive patients 38.1% (8/21) vs. failed 1 chemotherapy regimen 13.3% (2/15) vs. failed 2 or more chemotherapy regimens 18.8% (3/16), p = 0.015. The median overall survival was 2.5 months (response group 9.1 months, stable disease 3.1 months, and progressive group 0.8 month, p < 0.001). Adverse events, mainly skin reactions and diarrhea, were generally mild (grade 1 or 2) except paronychia and acne. Thus, gefitinib has clinically antitumor activity and good tolerability in Taiwan patients with advanced NSCLC and very poor performance status, with a higher response rate than that seen Europe or in European heritage Americans. Chemonaive patients responded better than patients with prior chemotherapy. Formal clinical trials are warranted to evaluate the role of gefitinib in this situation.

  17. Integrated Application of Active Controls (IAAC) technology to an advanced subsonic transport project: Current and advanced act control system definition study. Volume 2: Appendices

    NASA Technical Reports Server (NTRS)

    Hanks, G. W.; Shomber, H. A.; Dethman, H. A.; Gratzer, L. B.; Maeshiro, A.; Gangsaas, D.; Blight, J. D.; Buchan, S. M.; Crumb, C. B.; Dorwart, R. J.

    1981-01-01

    The current status of the Active Controls Technology (ACT) for the advanced subsonic transport project is investigated through analysis of the systems technical data. Control systems technologies under examination include computerized reliability analysis, pitch axis fly by wire actuator, flaperon actuation system design trade study, control law synthesis and analysis, flutter mode control and gust load alleviation analysis, and implementation of alternative ACT systems. Extensive analysis of the computer techniques involved in each system is included.

  18. Advanced glycation end products regulate anabolic and catabolic activities via NLRP3-inflammasome activation in human nucleus pulposus cells.

    PubMed

    Song, Yu; Wang, Yan; Zhang, Yukun; Geng, Wen; Liu, Wei; Gao, Yong; Li, Shuai; Wang, Kun; Wu, Xinghuo; Kang, Liang; Yang, Cao

    2017-02-22

    Intervertebral disc degeneration is widely recognized as a cause of lower back pain, neurological dysfunction and other musculoskeletal disorders. The major inflammatory cytokine IL-1β is associated with intervertebral disc degeneration; however, the molecular mechanisms that drive IL-1β production in the intervertebral disc, especially in nucleus pulposus (NP) cells, are unknown. In some tissues, advanced glycation end products (AGEs), which accumulate in NP tissues and promote its degeneration, increase oxidative stress and IL-1β secretion, resulting in disorders, such as obesity, diabetes mellitus and ageing. It remains unclear whether AGEs exhibit similar effects in NP cells. In this study, we observed significant activation of the NLRP3 inflammasome in NP tissues obtained from patients with degenerative disc disease compared to that with idiopathic scoliosis according to results detected by Western blot and immunofluorescence. Using NP cells established from healthy tissues, our in vitro study revealed that AGEs induced an inflammatory response in NP cells and a degenerative phenotype in a NLRP3-inflammasome-dependent manner related to the receptor for AGEs (RAGE)/NF-κB pathway and mitochondrial damage induced by mitochondrial reactive oxygen species (mtROS) generation, mitochondrial permeability transition pore (mPTP) activation and calcium mobilization. Among these signals, both RAGE and mitochondrial damage primed NLRP3 and pro-IL-1β activation as upstream signals of NF-κB activity, whereas mitochondrial damage was critical for the assembly of inflammasome components. These results revealed that accumulation of AGEs in NP tissue may initiate inflammation-related degeneration of the intervertebral disc via activation of the NLRP3 inflammasome.

  19. Feeling the Pulse of the Stratosphere: An Emerging Opportunity for Predicting Continental-Scale Cold Air Outbreaks One Month in Advance

    NASA Astrophysics Data System (ADS)

    Cai, M.

    2015-12-01

    Extreme weather events such as cold air outbreaks (CAOs) pose great threats to human life and socioeconomic well-being of the modern society. In the past, our capability to predict their occurrences is constrained by the 2-week predictability limit for weather. We demonstrate here for the first time that a rapid increase of air mass transported into the polar stratosphere, referred to as "the pulse of the stratosphere (PULSE)", can be predicted with a useful skill 4-6 weeks in advance by operational forecast models. We further show that the probability of the occurrence of continental-scale CAOs in mid-latitudes increases substantially above the normal condition within a short time period from one week before to 1-2 weeks after the peak day of a PULSE event. In particular, we reveal that the three massive CAOs over North America in January and February of 2014 were preceded by three episodes of extreme mass transport into the polar stratosphere with peak intensities reaching a trillion tons per day, twice of that on an average winter day. Therefore, our capability to predict the PULSEs with operational forecast models, in conjunction with its linkage to continental-scale CAOs, opens up a new opportunity for 30-day forecasts of continental-scale CAOs, such as those occurring over North America in the 2013-14 winter. A real time forecast experiment inaugurated in the winter of 2014-15 has confirmed the feasibility of forecasting CAOs one month in advance.

  20. 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

  1. Asymmetric frontal brain activity and parental rejection predict altruistic behavior: moderation of oxytocin effects.

    PubMed

    Huffmeijer, Renske; Alink, Lenneke R A; Tops, Mattie; Bakermans-Kranenburg, Marian J; van IJzendoorn, Marinus H

    2012-06-01

    Asymmetric frontal brain activity has been widely implicated in reactions to emotional stimuli and is thought to reflect individual differences in approach-withdrawal motivation. Here, we investigate whether asymmetric frontal activity, as a measure of approach-withdrawal motivation, also predicts charitable donations after a charity's (emotion-eliciting) promotional video showing a child in need is viewed, in a sample of 47 young adult women. In addition, we explore possibilities for mediation and moderation, by asymmetric frontal activity, of the effects of intranasally administered oxytocin and parental love withdrawal on charitable donations. Greater relative left frontal activity was related to larger donations. In addition, we found evidence of moderation: Low levels of parental love withdrawal predicted larger donations in the oxytocin condition for participants showing greater relative right frontal activity. We suggest that when approach motivation is high (reflected in greater relative left frontal activity), individuals are generally inclined to take action upon seeing someone in need and, thus, to donate money to actively help out. Only when approach motivation is low (reflected in less relative left/greater relative right activity) do empathic concerns affected by oxytocin and experiences of love withdrawal play an important part in deciding about donations.

  2. Factors Predicting the Physical Activity Behavior of Female Adolescents: A Test of the Health Promotion Model

    PubMed Central

    Mohamadian, Hashem

    2014-01-01

    Objectives Physical activity behavior begins to decline during adolescence and continues to decrease throughout young adulthood. This study aims to explain factors that influence physical activity behavior in a sample of female adolescents using a health promotion model framework. Methods This cross-sectional survey was used to explore physical activity behavior among a sample of female adolescents. Participants completed measures of physical activity, perceived self-efficacy, self-esteem, social support, perceived barriers, and perceived affect. Interactions among the variables were examined using path analysis within a covariance modeling framework. Results The final model accounted for an R2 value of 0.52 for physical activity and offered a good model-data fit. The results indicated that physical activity was predicted by self-esteem (β=0.46, p<0.001), perceived self-efficacy (β=0.40, p<0.001), social support (β=0.24, p<0.001), perceived barriers (β=-0.19, p<0.001), and perceived affect (β=0.17, p<0.001). Conclusions The findings of this study showed that the health promotion model was useful to predict physical activity behavior among the Iranian female adolescents. Information related to the predictors of physical activity behavior will help researchers plan more tailored culturally relevant health promotion interventions for this population. PMID:24570808

  3. Interspecies quantitative structure-activity-activity relationships (QSAARs) for prediction of acute aquatic toxicity of aromatic amines and phenols.

    PubMed

    Furuhama, A; Hasunuma, K; Aoki, Y

    2015-01-01

    We propose interspecies quantitative structure-activity-activity relationships (QSAARs), that is, QSARs with descriptors, to estimate species-specific acute aquatic toxicity. Using training datasets consisting of more than 100 aromatic amines and phenols, we found that the descriptors that predicted acute toxicities to fish (Oryzias latipes) and algae were daphnia toxicity, molecular weight (an indicator of molecular size and uptake) and selected indicator variables that discriminated between the absence or presence of various substructures. Molecular weight and the selected indicator variables improved the goodness-of-fit of the fish and algae toxicity prediction models. External validations of the QSAARs proved that algae toxicity could be predicted within 1.0 log unit and revealed structural profiles of outlier chemicals with respect to fish toxicity. In addition, applicability domains based on leverage values provided structural alerts for the predicted fish toxicity of chemicals with more than one hydroxyl or amino group attached to an aromatic ring, but not for fluoroanilines, which were not included in the training dataset. Although these simple QSAARs have limitations, their applicability is defined so clearly that they may be practical for screening chemicals with molecular weights of ≤364.9.

  4. Self-reported Physical Activity Predicts Pain Inhibitory and Facilitatory Function

    PubMed Central

    Naugle, Kelly M.; Riley, Joseph L.

    2013-01-01

    Considerable evidence suggests regular physical activity can reduce chronic pain symptoms. Dysfunction of endogenous facilitatory and inhibitory systems has been implicated in multiple chronic pain conditions. However, few studies have investigated the relationship between levels of physical activity and descending pain modulatory function. Purpose This study’s purpose was to determine whether self-reported levels of physical activity in healthy adults predicted 1) pain sensitivity to heat and cold stimuli, 2) pain facilitatory function as tested by temporal summation of pain (TS), and 3) pain inhibitory function as tested by conditioned pain modulation (CPM) and offset analgesia. Methods Forty-eight healthy adults (age range 18–76) completed the International Physical Activity Questionnaire (IPAQ) and the following pain tests: heat pain thresholds (HPT), heat pain suprathresholds, cold pressor pain (CPP), temporal summation of heat pain, conditioned pain modulation, and offset analgesia. The IPAQ measured levels of walking, moderate, vigorous and total physical activity over the past seven days. Hierarchical linear regressions were conducted to determine the relationship between each pain test and self-reported levels of physical activity, while controlling for age, sex and psychological variables. Results Self-reported total and vigorous physical activity predicted TS and CPM (p’s <.05). Individuals who self-reported more vigorous and total physical activity exhibited reduced temporal summation of pain and greater CPM. The IPAQ measures did not predict any of the other pain measures. Conclusion Thus, these results suggest that healthy older and younger adults who self-report greater levels of vigorous and total physical activity exhibit enhanced descending pain modulatory function. Improved descending pain modulation may be a mechanism through which exercise reduces or prevents chronic pain symptoms. PMID:23899890

  5. KRAS and BRAF Mutations and PTEN Expression Do Not Predict Efficacy of Cetuximab-Based Chemoradiotherapy in Locally Advanced Rectal Cancer

    SciTech Connect

    Erben, Philipp; Stroebel, Philipp; Horisberger, Karoline; Popa, Juliana; Bohn, Beatrice; Hanfstein, Benjamin; Kaehler, Georg; Kienle, Peter; Post, Stefan; Wenz, Frederik; Hochhaus, Andreas

    2011-11-15

    Purpose: Mutations in KRAS and BRAF genes as well as the loss of expression of phosphatase and tensin homolog (PTEN) (deleted on chromosome 10) are associated with impaired activity of antibodies directed against epidermal growth factor receptor in patients with metastatic colorectal cancer. The predictive and prognostic value of the KRAS and BRAF point mutations as well as PTEN expression in patients with locally advanced rectal cancer (LARC) treated with cetuximab-based neoadjuvant chemoradiotherapy is unknown. Methods and Materials: We have conducted phase I and II trials of the combination of weekly administration of cetuximab and irinotecan and daily doses of capecitabine in conjunction with radiotherapy (45 Gy plus 5.4 Gy) in patients with LARC (stage uT3/4 or uN+). The status of KRAS and BRAF mutations was determined with direct sequencing, and PTEN expression status was determined with immunohistochemistry testing of diagnostic tumor biopsies. Tumor regression was evaluated by using standardized regression grading, and disease-free survival (DFS) was calculated according to the Kaplan-Meier method. Results: A total of 57 patients were available for analyses. A total of 31.6% of patients carried mutations in the KRAS genes. No BRAF mutations were found, while the loss of PTEN expression was observed in 9.6% of patients. Six patients achieved complete remission, and the 3-year DFS rate was 73%. No correlation was seen between tumor regression or DFS rate and a single marker or a combination of all markers. Conclusions: In the present series, no BRAF mutation was detected. The presence of KRAS mutations and loss of PTEN expression were not associated with impaired response to cetuximab-based chemoradiotherapy and 3-year DFS.

  6. To Excavate Biomarkers Predictive of the Response for Capecitabine plus RAD001 through Nanostring-Based Multigene Assay in Advanced Gastric Cancer Patients

    PubMed Central

    Lee, Hansang; Lee, Jeeyun; Sohn, Insuk; Park, Se Hoon; Park, Joon Oh; Park, Young Suk; Kim, Kyoung-Mee; Kang, Won Ki; Kim, Seung Tae

    2016-01-01

    Comprehensive characterization of individual patients' tumour is important to realize personalized medicine. Here, we investigate to identify subsets that benefit from capecitabine plus RAD001 in advanced gastric cancer (GC) patients by comprehensive high-throughput genomic analysis (nCounter assay). Archival tumour tissue blocks, if possible, were collected at phase II trial of capecitabine plus RAD001 in 47 refractory GC patients (at clinicaltrials.gov NCT#01099527). A total of 42 formalin-fixed, paraffin-embedded (FFPE) tumour samples were available for nanostring based-multigene Assay. An nCounter assay of 519 kinase panels has been used. We performed correlatio