Science.gov

Sample records for advanced predictive activity

  1. Predicting Epileptic Seizures in Advance

    PubMed Central

    Moghim, Negin; Corne, David W.

    2014-01-01

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

  2. 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. 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.

  4. Recent advances in turbulence prediction

    NASA Astrophysics Data System (ADS)

    Bhattacharya, Atreyee

    2012-08-01

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

  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. Predictive markers in advanced renal cell carcinoma.

    PubMed

    Michaelson, M Dror; Stadler, Walter M

    2013-08-01

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

  8. Advances in Activity Cliff Research.

    PubMed

    Dimova, Dilyana; Bajorath, Jürgen

    2016-05-01

    Activity cliffs, i.e. similar compounds with large potency differences, are of interest from a chemical and informatics viewpoint; as a source of structure-activity relationship information, for compound optimization, and activity prediction. Herein, recent highlights of activity cliff research are discussed including studies that have further extended our understanding of activity cliffs, yielded unprecedented insights, or paved the way for practical applications.

  9. Advances in Activity Cliff Research.

    PubMed

    Dimova, Dilyana; Bajorath, Jürgen

    2016-05-01

    Activity cliffs, i.e. similar compounds with large potency differences, are of interest from a chemical and informatics viewpoint; as a source of structure-activity relationship information, for compound optimization, and activity prediction. Herein, recent highlights of activity cliff research are discussed including studies that have further extended our understanding of activity cliffs, yielded unprecedented insights, or paved the way for practical applications. PMID:27492084

  10. 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

  11. 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.

  12. Substrate Deformation Predicts Neuronal Growth Cone Advance

    PubMed Central

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

    2015-01-01

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

  13. Predicting impact factor one year in advance.

    PubMed

    Ketcham, Catherine M

    2007-06-01

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

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

    SciTech Connect

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

    1991-02-01

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

  15. 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.

  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. DNA Methyltransferase Activity Assays: Advances and Challenges.

    PubMed

    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.

  18. Predicting Malignancy in Thyroid Nodules: Molecular Advances

    PubMed Central

    Melck, Adrienne L.; Yip, Linwah

    2016-01-01

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

  19. 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.

  20. Advances in tilt rotor noise prediction

    NASA Astrophysics Data System (ADS)

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

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

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. Recent advances in active noise control

    NASA Astrophysics Data System (ADS)

    Guicking, D.

    Advances in the field of active noise control over the last few years are reviewed. Some commercially available products and their technical applications are described, with particular attention given to broadband duct noise silencers, broadband active headphones, waveform synthesis, and LMS controllers. Recent theoretical and experimental research activities are then reviewed. These activities are concerned with duct noise, structural sound, interior spaces, algorithms, echo cancellation, and miscellaneous applications.

  7. Advanced Placement Economics. Microeconomics: Student Activities.

    ERIC Educational Resources Information Center

    Morton, John S.

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

  8. Advanced Placement Economics. Macroeconomics: Student Activities.

    ERIC Educational Resources Information Center

    Morton, John S.

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

  9. Predicting the acceptance of advanced rider assistance systems.

    PubMed

    Huth, Véronique; Gelau, Christhard

    2013-01-01

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

  10. 76 FR 52954 - Workshop: Advancing Research on Mixtures; New Perspectives and Approaches for Predicting Adverse...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-24

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  12. 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.

  13. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    NASA Technical Reports Server (NTRS)

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

    2014-01-01

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

  14. Prediction and monitoring of volcanic activities

    SciTech Connect

    Sudradjat, A.

    1986-07-01

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

  15. Dynamo theory prediction of solar activity

    NASA Technical Reports Server (NTRS)

    Schatten, Kenneth H.

    1988-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-06-01

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

  17. 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;

  18. 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.

  19. Prediction of concurrent chemoradiotherapy outcome in advanced oropharyngeal cancer

    PubMed Central

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

    2014-01-01

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

  20. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project

    PubMed Central

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

    2016-01-01

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

  1. 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.

  2. 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.

  3. 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.

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

    PubMed Central

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

    2016-01-01

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

  5. 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.

  6. 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

  7. Place cell activation predicts subsequent memory.

    PubMed

    Robitsek, R Jonathan; White, John A; Eichenbaum, Howard

    2013-10-01

    A major quandary in memory research is how hippocampal place cells, widely recognized as elements of a spatial map, contribute to episodic memory, our capacity to remember unique experiences that depends on hippocampal function. Here we recorded from hippocampal neurons as rats performed a T-maze alternation task in which they were required to remember a preceding experience over a delay in order to make a subsequent spatial choice. As it has been reported previously in other variations of this task, we observed differential firing that predicted correct subsequent choices, even as the animal traversed identical locations prior to the choice. Here we also observed that most place cells also fired differently on correct as compared to error trials. Among these cells, a large majority fired strongly before the delay or during the retrieval phase but were less active or failed to activate when the animal subsequently made an error. These findings join the place cell phenomenon with episodic memory performance dependent on the hippocampus, revealing that memory accuracy can be predicted by the activation of single place cells in the hippocampus.

  8. 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.

  9. 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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

    Pasotti, Lorenzo; Zucca, Susanna

    2014-01-01

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

  12. 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.

  13. 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…

  14. 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…

  15. 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…

  16. "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…

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

    PubMed Central

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

    2015-01-01

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

  18. Neural predictive control for active buffet alleviation

    NASA Astrophysics Data System (ADS)

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

    1998-06-01

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

  19. Advanced propulsion activities in the USA

    NASA Astrophysics Data System (ADS)

    Garrison, P. W.

    Advances in propulsion system performance are necessary to meet the projected requirements of future launch vehicles, orbit transfer vehicles, satellites and planetary spacecraft. Ongoing U.S. space propulsion research programs are aggressively pursuing the development of the technology to meet these requirements. This paper reviews advanced propulsion research in the USA. Work accomplished in 1985 and future plans for ongoing research programs are discussed. Theoretical and experimental research programs and system studies of augmented hydrazine, arcjet, magnetoplasma dynamic thruster, ion thruster, metastable chemical, solar thermal, light sail, microwave and laser propulsion, nuclear fission rockets, and fusion and antimatter propulsion systems are addressed.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

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

    PubMed

    Kinsella, S M; Norris, M C

    1996-01-01

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

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

    PubMed

    Kinsella, S M; Norris, M C

    1996-01-01

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

  8. 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

  9. 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.

  10. 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

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

    PubMed

    Parenti, Marco Daniele; Rastelli, Giulio

    2012-01-01

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

  12. 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.

  13. 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

  14. Prediction of Human Activity by Discovering Temporal Sequence Patterns.

    PubMed

    Li, Kang; Fu, Yun

    2014-08-01

    Early prediction of ongoing human activity has become more valuable in a large variety of time-critical applications. To build an effective representation for prediction, human activities can be characterized by a complex temporal composition of constituent simple actions and interacting objects. Different from early detection on short-duration simple actions, we propose a novel framework for long -duration complex activity prediction by discovering three key aspects of activity: Causality, Context-cue, and Predictability. The major contributions of our work include: (1) a general framework is proposed to systematically address the problem of complex activity prediction by mining temporal sequence patterns; (2) probabilistic suffix tree (PST) is introduced to model causal relationships between constituent actions, where both large and small order Markov dependencies between action units are captured; (3) the context-cue, especially interactive objects information, is modeled through sequential pattern mining (SPM), where a series of action and object co-occurrence are encoded as a complex symbolic sequence; (4) we also present a predictive accumulative function (PAF) to depict the predictability of each kind of activity. The effectiveness of our approach is evaluated on two experimental scenarios with two data sets for each: action-only prediction and context-aware prediction. Our method achieves superior performance for predicting global activity classes and local action units. PMID:26353344

  15. Advances in active and nonlinear metamaterials

    NASA Astrophysics Data System (ADS)

    Boardman, A. D.; Mitchell-Thomas, R. C.; Rapoport, Y. G.

    2012-09-01

    Metamaterial research is an extremely important global activity that promises to change our lives in many different ways. These include making objects invisible and the dramatic impact of metamaterials upon the energy and medical sectors of society. Behind all of the applications, however, lies the business of creating metamaterials that are not going to be crippled by the kind of loss that is naturally heralded by use of resonant responses in their construction. Under the general heading of active and tunable metamaterials, an elegant route to the inclusion of nonlinearity and waveguide complexity coupled to soliton behavior suggested by forms of transformation dynamics is presented. In addition, various discussions will be framed within a magnetooptical environment that deploys externally applied magnetic field orientations. Light can then be directed to achieve energy control and be deployed for a variety of outcomes. Quite apart from the fact that the manufacture of metamaterials is attracting such a lot of global attention, the ability to control light, for example, in these materials is also immensely interesting and will lead to a new dawn of integrated circuits and computers. Recognizing the role of nonlinearity raises the possibility that dramatic manufacturing and applications are on the horizon.

  16. 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

  17. 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.

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

    PubMed Central

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

    2009-01-01

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

  19. Advanced ASON prototyping research activities in China

    NASA Astrophysics Data System (ADS)

    Hu, WeiSheng; Jin, Yaohui; Guo, Wei; Su, Yikai; He, Hao; Sun, Weiqiang

    2005-02-01

    This paper provides an overview of prototyping research activities of automatically switched optical networks and transport networks (ASONs/ASTNs) in China. In recent years, China has recognized the importance and benefits of the emerging ASON/ASTN techniques. During the period of 2001 and 2002, the national 863 Program of China started the preliminary ASON research projects with the main objectives to build preliminary ASON testbeds, develop control plane protocols and test their performance in the testbeds. During the period of 2003 and 2004, the 863 program started ASTN prototyping equipment projects for more practical applications. Totally 12 ASTN equipments are being developed by three groups led by Chinese venders: ZTE with Beijing University of Posts and Telecommunications (BUPT), Wuhan Research Institute of Posts and Telecommunication (WRI) with Shanghai Jiao Tong University (SJTU), and Huawei Inc. Meanwhile, as the ASTN is maturing, some of the China"s carries are participating in the OIF"s World Interoperability Demonstration, carrying out ASTN test, or deploying ASTN backbone networks. Finally, several ASTN backbone networks being tested or deployed now will be operated by the carries in 2005. The 863 Program will carry out an ASTN field trail in Yangtse River Delta, and finally deploy the 3TNET. 3TNET stands for Tbps transmission, Tbps switching, and Tbps routing, as well as a network integrating the above techniques. A task force under the "863" program is responsible for ASTN equipment specifications and interoperation agreements, technical coordination among all the participants, schedule of the whole project during the project undergoing, and organization of internetworking of all the equipments in the laboratories and field trials.

  20. 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

  1. 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.

  2. 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

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

    NASA Technical Reports Server (NTRS)

    Schubert, Siegfried

    2010-01-01

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

  4. 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.

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

    PubMed Central

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

    2016-01-01

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

  6. 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.

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

    NASA Astrophysics Data System (ADS)

    Erdal, Halil Ibrahim; Karakurt, Onur

    2013-01-01

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

  8. Langley Research Center contributions in advancing active control technology

    NASA Technical Reports Server (NTRS)

    Abel, I.; Newsom, J. R.

    1981-01-01

    The application of active control technology to reduce aeroelastic response of aircraft structures offers a potential for significant payoffs in terms of aerodynamic efficiency and weight savings. Some of the contributions of the Langley Research Center in advancing active control technology are described. Contributions are categorized into the development of appropriate analysis tools, control law synthesis methodology, and experimental investigations aimed at verifying both analysis and synthesis methodology.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  10. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  12. 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...

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    1992-02-01

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

  15. 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.

  16. 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

  17. Activities of the IERS Working Group on prediction

    NASA Astrophysics Data System (ADS)

    Wooden, W.

    2008-04-01

    The International Earth Rotation and Reference Systems Service (IERS) established a Working Group on Prediction (WGP) to investigate what IERS prediction products are useful to the user community in addition to making a detailed examination of the fundamental properties of the different input data sets and algorithms. The major goals and objectives of the WGP are to determine the desired Earth orientation prediction products, the importance of observational accuracy, which types of input data provide an optimal prediction, the strengths and weaknesses of various prediction algorithms, and the interactions between series and algorithms that are beneficial or harmful. To focus the research efforts of the WGP, the user community was polled to ascertain what prediction products are needed and at what level of accuracy. The current status of WGP activities and the anticipated future directions are presented.

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

    PubMed Central

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

    2012-01-01

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

  19. 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

  20. 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

  1. 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.

  2. 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.

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

    PubMed

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

    2015-12-10

    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.

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

    PubMed Central

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

    2006-01-01

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

  5. 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.

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

    NASA Technical Reports Server (NTRS)

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

    2012-01-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2011-01-01

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

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

    PubMed

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

    2015-09-28

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  12. Advances in the chemical analysis and biological activities of chuanxiong.

    PubMed

    Li, Weixia; Tang, Yuping; Chen, Yanyan; Duan, Jin-Ao

    2012-01-01

    Chuanxiong Rhizoma (Chuan-Xiong, CX), the dried rhizome of Ligusticum chuanxiong Hort. (Umbelliferae), is one of the most popular plant medicines in the World. Modern research indicates that organic acids, phthalides, alkaloids, polysaccharides, ceramides and cerebrosides are main components responsible for the bioactivities and properties of CX. Because of its complex constituents, multidisciplinary techniques are needed to validate the analytical methods that support CX's use worldwide. In the past two decades, rapid development of technology has advanced many aspects of CX research. The aim of this review is to illustrate the recent advances in the chemical analysis and biological activities of CX, and to highlight new applications and challenges. Emphasis is placed on recent trends and emerging techniques. PMID:22955453

  13. 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.

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

    PubMed

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

    2016-06-15

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  17. 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

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

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

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

    PubMed

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

    2016-08-01

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

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

    PubMed Central

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

    2016-01-01

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

  1. A neural network model for olfactory glomerular activity prediction

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    PubMed Central

    2012-01-01

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

  3. 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

  4. 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.

  5. 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.

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

    PubMed

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

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

  7. 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

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

    PubMed

    Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito

    2014-01-01

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

  9. 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.

  10. 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.

  11. 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.

  12. Advancing from offline to online activity recognition with wearable sensors.

    PubMed

    Ermes, Miikka; Parkka, Juha; Cluitmans, Luc

    2008-01-01

    Activity recognition with wearable sensors could motivate people to perform a variety of different sports and other physical exercises. We have earlier developed algorithms for offline analysis of activity data collected with wearable sensors. In this paper, we present our current progress in advancing the platform for the existing algorithms to an online version, onto a PDA. Acceleration data are obtained from wireless motion bands which send the 3D raw acceleration signals via a Bluetooth link to the PDA which then performs the data collection, feature extraction and activity classification. As a proof-of-concept, the online activity system was tested with three subjects. All of them performed at least 5 minutes of each of the following activities: lying, sitting, standing, walking, running and cycling with an exercise bike. The average second-by-second classification accuracies for the subjects were 99%, 97%, and 82 %. These results suggest that earlier developed offline analysis methods for the acceleration data obtained from wearable sensors can be successfully implemented in an online activity recognition application. PMID:19163702

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    PubMed Central

    2010-01-01

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

  15. Resting alpha activity predicts learning ability in alpha neurofeedback

    PubMed Central

    Wan, Feng; Nan, Wenya; Vai, Mang I.; Rosa, Agostinho

    2014-01-01

    Individuals differ in their ability to learn how to regulate the brain activity by neurofeedback. This study aimed to investigate whether the resting alpha activity can predict the learning ability in alpha neurofeedback. A total of 25 subjects performed 20 sessions of individualized alpha neurofeedback and the learning ability was assessed by three indices respectively: the training parameter changes between two periods, within a short period and across the whole training time. It was found that the resting alpha amplitude measured before training had significant positive correlations with all learning indices and could be used as a predictor for the learning ability prediction. This finding would help the researchers in not only predicting the training efficacy in individuals but also gaining further insight into the mechanisms of alpha neurofeedback. PMID:25071528

  16. Visualization and Interpretation of Support Vector Machine Activity Predictions.

    PubMed

    Balfer, Jenny; Bajorath, Jürgen

    2015-06-22

    Support vector machines (SVMs) are among the preferred machine learning algorithms for virtual compound screening and activity prediction because of their frequently observed high performance levels. However, a well-known conundrum of SVMs (and other supervised learning methods) is the black box character of their predictions, which makes it difficult to understand why models succeed or fail. Herein we introduce an approach to rationalize the performance of SVM models based upon the Tanimoto kernel compared with the linear kernel. Model comparison and interpretation are facilitated by a visualization technique, making it possible to identify descriptor features that determine compound activity predictions. An implementation of the methodology has been made freely available. PMID:25988274

  17. 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…

  18. 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) ...

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

    ERIC Educational Resources Information Center

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

    2005-01-01

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

  20. A novel approach to predict active sites of enzyme molecules.

    PubMed

    Chou, Kuo-Chen; Cai, Yu-dong

    2004-04-01

    Enzymes are critical in many cellular signaling cascades. With many enzyme structures being solved, there is an increasing need to develop an automated method for identifying their active sites. However, given the atomic coordinates of an enzyme molecule, how can we predict its active site? This is a vitally important problem because the core of an enzyme molecule is its active site from the viewpoints of both pure scientific research and industrial application. In this article, a topological entity was introduced to characterize the enzymatic active site. Based on such a concept, the covariant discriminant algorithm was formulated for identifying the active site. As a paradigm, the serine hydrolase family was demonstrated. The overall success rate by jackknife test for a data set of 88 enzyme molecules was 99.92%, and that for a data set of 50 independent enzyme molecules was 99.91%. Meanwhile, it was shown through an example that the prediction algorithm can also be used to find any typographic error of a PDB file in annotating the constituent amino acids of catalytic triad and to suggest a possible correction. The very high success rates are due to the introduction of a covariance matrix in the prediction algorithm that makes allowance for taking into account the coupling effects among the key constituent atoms of active site. It is anticipated that the novel approach is quite promising and may become a useful high throughput tool in enzymology, proteomics, and structural bioinformatics. PMID:14997541

  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. 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.

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

    ERIC Educational Resources Information Center

    DeRose, Diego S.; Clement, Russell W.

    2011-01-01

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

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

    PubMed

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

    2012-03-01

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

  5. 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

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

    PubMed

    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

    2014-12-01

    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.

  7. 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.

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

    PubMed Central

    Hao, Bibo; Guan, Zengda; Zhu, Tingshao

    2014-01-01

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

  9. Mathematical models for predicting indoor air quality from smoking activity.

    PubMed Central

    Ott, W R

    1999-01-01

    Much progress has been made over four decades in developing, testing, and evaluating the performance of mathematical models for predicting pollutant concentrations from smoking in indoor settings. Although largely overlooked by the regulatory community, these models provide regulators and risk assessors with practical tools for quantitatively estimating the exposure level that people receive indoors for a given level of smoking activity. This article reviews the development of the mass balance model and its application to predicting indoor pollutant concentrations from cigarette smoke and derives the time-averaged version of the model from the basic laws of conservation of mass. A simple table is provided of computed respirable particulate concentrations for any indoor location for which the active smoking count, volume, and concentration decay rate (deposition rate combined with air exchange rate) are known. Using the indoor ventilatory air exchange rate causes slightly higher indoor concentrations and therefore errs on the side of protecting health, since it excludes particle deposition effects, whereas using the observed particle decay rate gives a more accurate prediction of indoor concentrations. This table permits easy comparisons of indoor concentrations with air quality guidelines and indoor standards for different combinations of active smoking counts and air exchange rates. The published literature on mathematical models of environmental tobacco smoke also is reviewed and indicates that these models generally give good agreement between predicted concentrations and actual indoor measurements. PMID:10350523

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

    SciTech Connect

    DiMaio, Frank

    2013-11-01

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

  11. 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.

  12. Using theoretical descriptors in structure activity relationships: Validating toxicity predictions

    SciTech Connect

    Famini, G.R.; Wilson, L.Y.; Chester, N.A.; Sterling, P.A.

    1995-12-01

    Quantitative Structure Activity Relationships (QSAR) and Linear Free Energy Relationships (LFER) are very useful for correlating toxicological data, and in characterizating trends in terms of structural and electronic effects. Several years ago, we developed a series of equations correlating a number of toxicity tests with theoretically determined descriptors. One of these tests was the Microtox test, using the degradation in light from Photobacteriurn phosphoreum. Recently, several new compounds have been tested in our laboratory using the Microtox test, and compared against the predicted values. The agreement between experimental and theoretical results will be discussed, as will reasons for {open_quotes}good{close_quotes} or {open_quotes}poor{close_quotes} predictions.

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

    NASA Astrophysics Data System (ADS)

    Nicholls, N.

    2014-12-01

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

  14. 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

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

    PubMed

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

    2015-07-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  17. 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.

  18. BNL Activities in Advanced Neutron Source Development: Past and Present

    SciTech Connect

    Hastings, J.B.; Ludewig, H.; Montanez, P.; Todosow, M.; Smith, G.C.; Larese, J.Z.

    1998-06-14

    Brookhaven National Laboratory has been involved in advanced neutron sources almost from its inception in 1947. These efforts have mainly focused on steady state reactors beginning with the construction of the first research reactor for neutron beams, the Brookhaven Graphite Research Reactor. This was followed by the High Flux Beam Reactor that has served as the design standard for all the subsequent high flux reactors constructed worldwide. In parallel with the reactor developments BNL has focused on the construction and use of high energy proton accelerators. The first machine to operate over 1 GeV in the world was the Cosmotron. The machine that followed this, the AGS, is still operating and is the highest intensity proton machine in the world and has nucleated an international collaboration investigating liquid metal targets for next generation pulsed spallation sources. Early work using the Cosmotron focused on spallation product studies for both light and heavy elements into the several GeV proton energy region. These original studies are still important today. In this report we discuss the facilities and activities at BNL focused on advanced neutron sources. BNL is involved in the proton source for the Spallation Neutron source, spectrometer development at LANSCE, target studies using the AGS and state-of-the-art neutron detector development.

  19. BNL ACTIVITIES IN ADVANCED NEUTRON SOURCE DEVELOPMENT: PAST AND PRESENT

    SciTech Connect

    HASTINGS,J.B.; LUDEWIG,H.; MONTANEZ,P.; TODOSOW,M.; SMITH,G.C.; LARESE,J.Z.

    1998-06-14

    Brookhaven National Laboratory has been involved in advanced neutron sources almost from its inception in 1947. These efforts have mainly focused on steady state reactors beginning with the construction of the first research reactor for neutron beams, the Brookhaven Graphite Research Reactor. This was followed by the High Flux Beam Reactor that has served as the design standard for all the subsequent high flux reactors constructed worldwide. In parallel with the reactor developments BNL has focused on the construction and use of high energy proton accelerators. The first machine to operate over 1 GeV in the world was the Cosmotron. The machine that followed this, the AGS, is still operating and is the highest intensity proton machine in the world and has nucleated an international collaboration investigating liquid metal targets for next generation pulsed spallation sources. Early work using the Cosmotron focused on spallation product studies for both light and heavy elements into the several GeV proton energy region. These original studies are still important today. In the sections below the authors discuss the facilities and activities at BNL focused on advanced neutron sources. BNL is involved in the proton source for the Spallation Neutron source, spectrometer development at LANSCE, target studies using the AGS and state-of-the-art neutron detector development.

  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. 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

  2. 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.

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

    PubMed

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

    2008-05-01

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

  4. 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.

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

    NASA Astrophysics Data System (ADS)

    Peterson, E. J.; Izad, O.; Tyler, D. J.

    2011-08-01

    The 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 uses 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 improve prediction of axon activation based on properties of the applied field in a computationally efficient manner.

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

    PubMed Central

    Hao, Ming; Zhang, Shuwei; Qiu, Jieshan

    2012-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    PubMed

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

    2015-10-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Saanouni, K.

    2013-05-01

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

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

    SciTech Connect

    Lu, P-Y.; Yuracko, K.

    2011-02-25

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-08-01

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

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

    PubMed

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

    2016-07-01

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

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

    PubMed Central

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

    2014-01-01

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

  15. 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.

  16. 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.

  17. 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.

  18. 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

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed

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

    2013-05-22

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

  1. 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

  2. Predictive motor activation during action observation in human infants.

    PubMed

    Southgate, Victoria; Johnson, Mark H; Osborne, Tamsin; Csibra, Gergely

    2009-12-23

    Certain regions of the human brain are activated both during action execution and action observation. This so-called 'mirror neuron system' has been proposed to enable an observer to understand an action through a process of internal motor simulation. Although there has been much speculation about the existence of such a system from early in life, to date there is little direct evidence that young infants recruit brain areas involved in action production during action observation. To address this question, we identified the individual frequency range in which sensorimotor alpha-band activity was attenuated in nine-month-old infants' electroencephalographs (EEGs) during elicited reaching for objects, and measured whether activity in this frequency range was also modulated by observing others' actions. We found that observing a grasping action resulted in motor activation in the infant brain, but that this activity began prior to observation of the action, once it could be anticipated. These results demonstrate not only that infants, like adults, display overlapping neural activity during execution and observation of actions, but that this activation, rather than being directly induced by the visual input, is driven by infants' understanding of a forthcoming action. These results provide support for theories implicating the motor system in action prediction. PMID:19675001

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

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

  6. Predicting flow at work: investigating the activities and job characteristics that predict flow states at work.

    PubMed

    Nielsen, Karina; Cleal, Bryan

    2010-04-01

    Flow (a state of consciousness where people become totally immersed in an activity and enjoy it intensely) has been identified as a desirable state with positive effects for employee well-being and innovation at work. Flow has been studied using both questionnaires and Experience Sampling Method (ESM). In this study, we used a newly developed 9-item flow scale in an ESM study combined with a questionnaire to examine the predictors of flow at two levels: the activities (brainstorming, planning, problem solving and evaluation) associated with transient flow states and the more stable job characteristics (role clarity, influence and cognitive demands). Participants were 58 line managers from two companies in Denmark; a private accountancy firm and a public elder care organization. We found that line managers in elder care experienced flow more often than accountancy line managers, and activities such as planning, problem solving, and evaluation predicted transient flow states. The more stable job characteristics included in this study were not, however, found to predict flow at work.

  7. Prediction of Antifungal Activity of Gemini Imidazolium Compounds

    PubMed Central

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

    2015-01-01

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

  8. Artificial neural network prediction of antisense oligodeoxynucleotide activity.

    PubMed

    Giddings, Michael C; Shah, Atul A; Freier, Sue; Atkins, John F; Gesteland, Raymond F; Matveeva, Olga V

    2002-10-01

    An mRNA transcript contains many potential antisense oligodeoxynucleotide target sites. Identification of the most efficacious targets remains an important and challenging problem. Building on separate work that revealed a strong correlation between the inclusion of short sequence motifs and the activity level of an oligo, we have developed a predictive artificial neural network system for mapping tetranucleotide motif content to antisense oligo activity. Trained for high-specificity prediction, the system has been cross-validated against a database of 348 oligos from the literature and a larger proprietary database of 908 oligos. In cross- validation tests the system identified effective oligos (i.e. oligos capable of reducing target mRNA expression to <25% that of the control) with 53% accuracy, in contrast to the <10% success rates commonly reported for trial-and-error oligo selection, suggesting a possible 5-fold reduction in the in vivo screening required to find an active oligo. We have implemented a web interface to a trained neural network. Given an RNA transcript as input, the system identifies the most likely oligo targets and provides estimates of the probabilities that oligos targeted against these sites will be effective. PMID:12364609

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

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

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

  10. Parahippocampal cortex activation during context reinstatement predicts item recollection

    PubMed Central

    Diana, Rachel A.; Yonelinas, Andrew P.; Ranganath, Charan

    2014-01-01

    Episodic memory is the binding of an event with information about the context in which that event (or item) was experienced. The context of an event may include its spatial and temporal location as well as goal-directed, conscious thoughts evoked during the event. We call this latter type of information “cognitive context.” The Binding of Items and Context (BIC) theory of medial temporal lobe function proposes that parahippocampal cortex (PHc) plays a key role in processing cognitive context. Therefore, we predicted that activity in PHc during reactivation of a previously experienced cognitive context would be correlated with item recollection, even when the associated item and its episodic binding had not yet been retrieved. Using a novel paradigm, we measured brain activation with fMRI in response to covert reinstatement of a cognitive context, prior to presenting an item memory probe. Contexts were studied with multiple items to ensure that spontaneous item retrieval would not occur prior to the test probe. At test, contexts were reinstated for eight seconds before the test probe was presented. We manipulated whether the reinstated context matched the encoding context of the test probe that followed. For such matching contexts, we found that increased PHc activation prior to the test probe predicted recollection following the test probe. If a context unrelated to the eventual test item probe was reinstated, there was no such association between PHc activation during context reinstatement and eventual memory judgments. These findings suggest that PHc activation is correlated with cognitive context retrieval. PMID:23937182

  11. 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...

  12. 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

  13. 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.

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

    SciTech Connect

    G. R. Odette; G. E. Lucas

    2005-11-15

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

  15. 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

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

    PubMed

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

    2015-09-01

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

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

    PubMed

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

    2015-09-01

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

  18. 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…

  19. Prediction of Solar Activity Based on Neuro-Fuzzy Modeling

    NASA Astrophysics Data System (ADS)

    Attia, Abdel-Fattah; Abdel-Hamid, Rabab; Quassim, Maha

    2005-03-01

    This paper presents an application of the neuro-fuzzy modeling to analyze the time series of solar activity, as measured through the relative Wolf number. The neuro-fuzzy structure is optimized based on the linear adapted genetic algorithm with controlling population size (LAGA-POP). Initially, the dimension of the time series characteristic attractor is obtained based on the smallest regularity criterion (RC) and the neuro-fuzzy model. Then the performance of the proposed approach, in forecasting yearly sunspot numbers, is favorably compared to that of other published methods. Finally, a comparison predictions for the remaining part of the 22nd and the whole 23rd cycle of the solar activity are presented.

  20. Predictions of adsorption equilibria of nonpolar hydrocarbons onto activated carbon

    SciTech Connect

    Do, D.D.; Wang, K.

    1998-12-08

    This paper presents a new approach to analyze the adsorption equilibria of nonpolar hydrocarbons onto activated carbon. The kinetic theory of gases and the 10-4-3 potential energy were employed to describe the adsorption process inside micropores. On the basis of this theory, a general isotherm model was proposed which possesses the potential capability of predicting the adsorption equilibria of an adsorbent by using the knowledge of its microporous structure and molecular properties of adsorbates. Experimental data of gases and vapors on Ajax activated carbon were employed to examine the model. Adsorption equilibria of binary mixtures were also investigated with the model, and it is shown that the model is capable of simulating the nonideal, or azeotropic, adsorption behaviors resulting from the structural heterogeneity of the adsorbent.

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

    PubMed

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

    2013-12-01

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

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

    PubMed

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

    2015-01-01

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

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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

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

    PubMed

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

    2012-03-15

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

  9. 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...

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

    ERIC Educational Resources Information Center

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

    2001-01-01

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

  11. 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

  12. 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

  13. The sequential structure of brain activation predicts skill.

    PubMed

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

    2016-01-29

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

  14. Working memory delay activity predicts individual differences in cognitive abilities.

    PubMed

    Unsworth, Nash; Fukuda, Keisuke; Awh, Edward; Vogel, Edward K

    2015-05-01

    A great deal of prior research has examined the relation between estimates of working memory and cognitive abilities. Yet, the neural mechanisms that account for these relations are still not very well understood. The current study explored whether individual differences in working memory delay activity would be a significant predictor of cognitive abilities. A large number of participants performed multiple measures of capacity, attention control, long-term memory, working memory span, and fluid intelligence, and latent variable analyses were used to examine the data. During two working memory change detection tasks, we acquired EEG data and examined the contralateral delay activity. The results demonstrated that the contralateral delay activity was significantly related to cognitive abilities, and importantly these relations were because of individual differences in both capacity and attention control. These results suggest that individual differences in working memory delay activity predict individual differences in a broad range of cognitive abilities, and this is because of both differences in the number of items that can be maintained and the ability to control access to working memory. PMID:25436671

  15. Working Memory Delay Activity Predicts Individual Differences in Cognitive Abilities

    PubMed Central

    Unsworth, Nash; Fukuda, Keisuke; Awh, Edward; Vogel, Edward K.

    2015-01-01

    A great deal of prior research has examined the relation between estimates of working memory and cognitive abilities. Yet, the neural mechanisms that account for these relations are still not very well understood. The current study explored whether individual differences in working memory delay activity would be a significant predictor of cognitive abilities. A large number of participants performed multiple measures of capacity, attention control, long-term memory, working memory span, and fluid intelligence, and latent variable analyses were used to examine the data. During two working memory change detection tasks, we acquired EEG data and examined the contra-lateral delay activity. The results demonstrated that the contralateral delay activity was significantly related to cognitive abilities, and importantly these relations were because of individual differences in both capacity and attention control. These results suggest that individual differences in working memory delay activity predict individual differences in a broad range of cognitive abilities, and this is because of both differences in the number of items that can be maintained and the ability to control access to working memory. PMID:25436671

  16. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  18. Structure activity relationships: their function in biological prediction

    SciTech Connect

    Schultz, T.W.

    1982-01-01

    Quantitative structure activity relationships provide a means of ranking or predicting biological effects based on chemical structure. For each compound used to formulate a structure activity model two kinds of quantitative information are required: (1) biological activity and (2) molecular properties. Molecular properties are of three types: (1) molecular shape, (2) physiochemical parameters, and (3) abstract quantitations of molecular structure. Currently the two best descriptors are the hydrophobic parameter, log 1-octanol/water partition coefficient (log P), and the /sup 1/X/sup v/(one-chi-v) molecular connectivity index. Biological responses can be divided into three main categories: (1) non-specific effects due to membrane perturbation, (2) non-specific effects due to interaction with functional groups of proteins, and (3) specific effects due to interaction with receptors. Twenty-six synthetic fossil fuel-related nitrogen-containing aromatic compounds were examined to determine the quantitative correlation between log P and /sup 1/X/sup v/ and population growth impairment of Tetrahymena pyriformis. Nitro-containing compounds are the most active, followed by amino-containing compounds and azaarenes. Within each analog series activity increases with alkyl substitution and ring addition. The planar model log BR = 0.5564 log P + 0.3000 /sup 1/X/sup v/ -2.0138 was determined using mono-nitrogen substituted compounds. Attempts to extrapolate this model to dinitrogen-containing molecules were, for the most part, unsuccessful because of a change in mode of action from membrane perturbation to uncoupling of oxidative phosphoralation.

  19. 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

  20. A Geomagnetic Precursor Technique for Predicting the Solar Activity Cycle

    NASA Astrophysics Data System (ADS)

    Sobel, E. I.; Rabin, D. M.

    2015-12-01

    The Western hemisphere has been recording sunspot numbers since Galileo discovered sunspots in the early 17th century, and the roughly 11-year solar cycle has been recognized since the 19th century. However, predicting the strength of any particular cycle remains a relatively imprecise task. This project's aim was to update and improve a forecasting technique based on geomagnetic precursors of future solar activity The model is a refinement of R. J. Thompson's 1993 paper that relates the number of geomagnetically disturbed days, as defined by the aa and Ap indices, to the sum of the sunspot number in the current and the previous cycle, Rn + Rn-1.[1] The method exploits the fact that two cycles coexist for some period on the Sun near solar minimum and therefore that the number of sunspots and disturbed days during the declining phase of one cycle gives an indication of the following cycle's strength. We wrote and updated IDL software procedures to define disturbed days with varying threshold values and graphed Rn + Rn-1 against them. The aa threshold was derived from the Ap threshold. After comparing the graphs for Ap values from 20 to 50, an Ap threshold of 30 and the corresponding aa threshold of 44 were chosen as yielding the best correlation. Confidence regions were computed to provide a quantitative uncertainty on future predictions. The 80% confidence region gives a range of ±40 in sunspot number. [1] Thompson, R. J. (1993). A technique for predicting the amplitude of the solar cycle. Solar Physics, 148, 2, 383-388.

  1. 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.

  2. 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.

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

    PubMed

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

    2016-06-28

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

  4. 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

  5. Multiplexed model predictive control for active vehicle suspensions

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  6. Parent Modeling: Perceptions of Parents’ Physical Activity Predict Girls’ Activity throughout Adolescence

    PubMed Central

    Madsen, Kristine A.; McCulloch, Charles; Crawford, Patricia B.

    2009-01-01

    Objectives To determine if parent modeling of physical activity has a differential impact on girls’ physical activity (PA) by race, if the association declines over time, and to assess the contribution of parent modeling to girls’ activity relative to other potential predictors. Study design Longitudinal examination of parent modeling’s impact on future log transformed metabolic equivalents (log METs) of leisure-time PA among 1213 African-American and 1166 Caucasian girls in the NHLBI Growth and Health Study, from age 9-10 through 18-19 years, using linear regression. Race interaction terms and time trends were examined. Results Girls’ perceptions of parent modeling significantly predicted future log METs in each study year; associations remained stable over time and were similar by race. Girls’ perception of parent PA better predicted girl log METs than did parent self-report. On average, girls reporting that their parents exercised ≥3x/week were about 50% more active than girls with sedentary parents. Conclusions Girls’ perception of parent activity predicts PA for girls throughout adolescence, despite age-associated decreases in PA. We did not find differences in this association by race. Interventions designed to increase parental activity may improve parent health, positively influence daughters’ activity, and begin to address disparities in cardiovascular health. PMID:18789455

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

    NASA Astrophysics Data System (ADS)

    Bagayoko, Diola

    2010-10-01

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

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

    PubMed

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

    2015-03-01

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

  9. Brain monoamine oxidase A activity predicts trait aggression.

    PubMed

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

    2008-05-01

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

  10. Pharmacokinetic and pharmacogenetic predictive markers of irinotecan activity and toxicity.

    PubMed

    Di Paolo, Antonello; Bocci, Guido; Polillo, Marialuisa; Del Re, Marzia; Di Desidero, Teresa; Lastella, Marianna; Danesi, Romano

    2011-12-01

    After the rapid development of new classes of antineoplastic drugs, research activities have focused their efforts to the identification of predictive markers of drug activity and tolerability. Irinotecan (CPT-11) may induce severe toxicities (diarrhea, neutropenia) that limit its clinical use, but the increasing knowledge of its pharmacokinetics offered a potential approach to treatment optimization. Pharmacokinetics, the first area of investigation, has identified markers such as biliary index, the relative extent of conversion and the glucuronidation ratio, which are capable to define the risk for severe adverse effects. Because of the existence of some issues concerning the adoption of pharmacokinetic strategies to optimize CPT-11 dose and schedule, analyses of genetic polymorphisms seemed to offer a more reliable and safer approach for the identification of patients at risk than pharmacokinetics. In this view, the uridine diphosphate glucuronosil transferase isoform 1A1 (UGT1A1) was associated with significant changes in disposition of CPT-11 and its metabolites, and consequently with treatment-induced toxicities. However, the complex pharmacokinetics of irinotecan and the involvement of several enzymes other than UGT (i.e., carboxyl estherases, CYP450 isoforms), and transmembrane transporters (ABCB1, ABCC1, ABCG2, SLCO1B1) make difficult the identification of patients with an optimal sensitivity and specificity, and a large part of variability among patients still remains unexplained. Furthermore, prospective clinical studies that should demonstrate the reliability of those pharmacokinetic and pharmacogenetic markers are still lacking. In the present review, pharmacokinetic and pharmacogenetic markers will be discussed. PMID:21787264

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

    ERIC Educational Resources Information Center

    Froman, Terry; Brown, Shelly; Tirado, Arleti

    2008-01-01

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

  12. 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…

  13. 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

  14. 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

  15. 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

  16. 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.

  17. 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.

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

    PubMed

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

    2016-09-10

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

  19. 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

  20. 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.

  1. Prediction of activated carbon adsorption capacities for organic vapors using quantitative structure-activity relationship methods

    SciTech Connect

    Nirmalakhandan, N.N. ); Speece, R.E. )

    1993-08-01

    Quantitative structure-activity relationship (QSAR) methods were used to develop models to estimate and predict activated carbon adsorption capacities for organic vapors. Literature isothermal data from two sources for 22 organic contaminants on six different carbons were merged to form a training set of 75 data points. Two different QSAR approaches were evaluated: the molecular connectivity approach and the linear solvation energy relationship approach. The QSAR model developed in this study using the molecular connectivity approach was able to fit the experimental data with r = 0.96 and standard error of 0.09. The utility of the model was demonstrated by using predicted k values to calculate adsorption capacities of 12 chemicals on two different carbons and comparing them with experimentally determined values. 9 refs., 1 fig., 3 tabs.

  2. 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…

  3. 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

  4. 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.

  5. 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...

  6. 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.

  7. 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

  8. 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.

  9. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

  11. 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.

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

    PubMed Central

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

    2016-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1977-01-01

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

  14. 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.

  15. New advances on glial activation in health and disease

    PubMed Central

    Lee, Kim Mai; MacLean, Andrew G

    2015-01-01

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

  16. Quantitative structure-activity relationship (QSAR) for insecticides: development of predictive in vivo insecticide activity models.

    PubMed

    Naik, P K; Singh, T; Singh, H

    2009-07-01

    Quantitative structure-activity relationship (QSAR) analyses were performed independently on data sets belonging to two groups of insecticides, namely the organophosphates and carbamates. Several types of descriptors including topological, spatial, thermodynamic, information content, lead likeness and E-state indices were used to derive quantitative relationships between insecticide activities and structural properties of chemicals. A systematic search approach based on missing value, zero value, simple correlation and multi-collinearity tests as well as the use of a genetic algorithm allowed the optimal selection of the descriptors used to generate the models. The QSAR models developed for both organophosphate and carbamate groups revealed good predictability with r(2) values of 0.949 and 0.838 as well as [image omitted] values of 0.890 and 0.765, respectively. In addition, a linear correlation was observed between the predicted and experimental LD(50) values for the test set data with r(2) of 0.871 and 0.788 for both the organophosphate and carbamate groups, indicating that the prediction accuracy of the QSAR models was acceptable. The models were also tested successfully from external validation criteria. QSAR models developed in this study should help further design of novel potent insecticides.

  17. Predicting anti-androgenic activity of bisphenols using molecular docking and quantitative structure-activity relationships.

    PubMed

    Yang, Xianhai; Liu, Huihui; Yang, Qian; Liu, Jining; Chen, Jingwen; Shi, Lili

    2016-11-01

    Both in vivo and in vitro assay indicated that bisphenols can inhibit the androgen receptor. However, the underlying antagonistic mechanism is unclear. In this study, molecular docking was employed to probe the interaction mechanism between bisphenols and human androgen receptor (hAR). The binding pattern of ligands in hAR crystal structures was also analyzed. Results show that hydrogen bonding and hydrophobic interactions are the dominant interactions between the ligands and hAR. The critical amino acid residues involved in forming hydrogen bonding between bisphenols and hAR is Asn 705 and Gln 711. Furthermore, appropriate molecular structural descriptors were selected to characterize the non-bonded interactions. Stepwise multiple linear regressions (MLR) analysis was employed to develop quantitative structure-activity relationship (QSAR) models for predicting the anti-androgenic activity of bisphenols. Based on the QSAR development and validation guideline issued by OECD, the goodness-of-fit, robustness and predictive ability of constructed QSAR model were assessed. The model application domain was characterized by the Euclidean distance and Williams plot. The mechanisms of the constructed model were also interpreted based on the selected molecular descriptors i.e. the number of hydroxyl groups (nROH), the most positive values of the molecular surface potential (Vs,max) and the lowest unoccupied molecular orbital energy (ELUMO). Finally, based on the model developed, the data gap for other twenty-six bisphenols on their anti-androgenic activity was filled. The predicted results indicated that the anti-androgenic activity of seven bisphenols was higher than that of bisphenol A. PMID:27561732

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

    PubMed Central

    Mulder, Karen; Spratlin, Jennifer

    2014-01-01

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

  19. What clinical activities do advanced-practice registered dietitian nutritionists perform? Results of a Delphi study.

    PubMed

    Brody, Rebecca A; Byham-Gray, Laura; Touger-Decker, Riva; Passannante, Marian R; Rothpletz Puglia, Pamela; O'Sullivan Maillet, Julie

    2014-05-01

    Activities performed by advanced-practice registered dietitian nutritionists (RDNs) have yet to be clearly elucidated. The study aimed to gain consensus on the practice activities of advanced-practice RDNs who provide direct clinical nutrition care. A three-round Delphi study was conducted. Purposive sampling identified 117 RDN experts working as clinicians and/or managers in direct care settings that met inclusion criteria for advanced-level practice. In Round 1, 85 experts provided open-ended advanced-level practice activities linked to the Nutrition Care Process sections. Using content analysis, the responses were coded into activity statements. In Round 2, experts rated the essentiality of these activities. In Round 3, experts re-rated statements not reaching consensus while viewing their previous rating, the group median, and comments. Median ratings of 1.0 to 3.0 were defined as essential, 4.0 were neither essential nor nonessential, and 5.0 to 7.0 were nonessential. Consensus was reached when the interquartile range of responses to each question was <2.0. Seventy-six (89.4%) experts completed all rounds. From 770 comments, 129 activity statements were generated. All statements reached consensus: 97.7% as essential; 0.8% as nonessential; and 1.5% as neither. Of essential activities, 67.5% were highly essential with limited variability (median=1.0; interquartile range≤2.0). Advanced-practice RDNs' tasks are patient-centered and reflect complex care; involve a comprehensive and discriminating approach; are grounded in advanced knowledge and expertise in clinical nutrition; include use of advanced interviewing, education, and counseling strategies; and require communication with patient, families, and the health care team. The high-level of consensus from experts suggest advanced-level clinical nutrition practice exists and can be defined.

  20. 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

  1. 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.

  2. In vitro anti-Mycobacterium avium activities of quinolones: predicted active structures and mechanistic considerations.

    PubMed

    Klopman, G; Li, J Y; Wang, S; Pearson, A J; Chang, K; Jacobs, M R; Bajaksouzian, S; Ellner, J J

    1994-08-01

    The relationship between the structures of quinolones and their anti-Mycobacterium avium activities has been previously derived by using the Multiple Computer-Automated Structure Evaluation program. A number of substructural constraints required to overcome the resistance of most of the strains have been identified. Nineteen new quinolones which qualify under these substructural requirements were identified by the program and subsequently tested. The results show that the substructural attributes identified by the program produced a successful a priori prediction of the anti-M. avium activities of the new quinolones. All 19 quinolones were found to be active, and 4 of them are as active or better than ciprofloxacin. With these new quinolones, the updated multiple computer-automated structure evaluation program structure-activity relationship analysis has helped to uncover additional information about the nature of the substituents at the C5 and C7 positions needed for optimal inhibitory activity. A possible explanation of drug resistance based on the observation of suicide inactivation of bacterial cytochrome P-450 by the cyclopropylamine moiety has also been proposed and is discussed in this report. Furthermore, we confirm the view that the amount of the uncharged form present in a neutral pH solution plays a crucial role in the drug's penetration ability.

  3. 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.

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

    ERIC Educational Resources Information Center

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

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

  5. 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.

  6. 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.

  7. 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…

  8. Natural Killer Activity: Early Days, Advances, and Seminal Observations

    PubMed Central

    Ortaldo, John R.; Wiltrout, Robert H.; Reynolds, Craig W.

    2014-01-01

    This manuscript describes the early history of NK cell discovery, with emphasis on the events in the first decade of NK cell studies, 1972–1982. The authors highlight some of the earliest and most important observations that would later prove to be milestones in the study of NK cells and their activity. PMID:24941370

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

    NASA Technical Reports Server (NTRS)

    Morrell, Michael Randy

    2002-01-01

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

  10. 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.

  11. 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

  12. 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.

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

    SciTech Connect

    Feldman, E.

    2011-06-09

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

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1986-01-01

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

  20. 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.

  1. 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.

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

    NASA Astrophysics Data System (ADS)

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

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

  3. 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.

  4. Advanced low-activation materials. Fibre-reinforced ceramic composites

    NASA Astrophysics Data System (ADS)

    Fenici, P.; Scholz, H. W.

    1994-09-01

    A serious safety and environmental concern for thermonuclear fusion reactor development regards the induced radioactivity of the first wall and structural components. The use of low-activation materials (LAM) in a demonstration reactor would reduce considerably its potential risk and facilitate its maintenance. Moreover, decommissioning and waste management including disposal or even recycling of structural materials would be simplified. Ceramic fibre-reinforced SiC materials offer highly appreciable low activation characteristics in combination with good thermomechanical properties. This class of materials is now under experimental investigation for structural application in future fusion reactors. An overview on the recent results is given, covering coolant leak rates, thermophysical properties, compatibility with tritium breeder materials, irradiation effects, and LAM-consistent purity. SiC/SiC materials present characteristics likely to be optimised in order to meet the fusion application challenge. The scope is to put into practice the enormous potential of inherent safety with fusion energy.

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

    EPA Science Inventory

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

  6. 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

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

    SciTech Connect

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

    2012-12-10

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

  8. 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.

  9. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    PubMed

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

    2015-08-01

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

  12. Recent advances in active fiber composites for structural control

    NASA Astrophysics Data System (ADS)

    Bent, Aaron A.; Pizzochero, Alessandro E.

    2000-06-01

    Active Fiber Composites (AFCs) provide a novel method for large scale actuation and sensing in active structures. The composite comprises unidirectionally aligned piezoelectric fibers, a resin matrix system, and interdigital electrode. AFCs have demonstrated distinct advantages over current monolithic piezoceramic actuators, including: higher planar actuation strain, tailorable orthotropic actuation, robustness to damage, conformability to curved surfaces, and potential for large area distributed actuation/sensing system. This manuscript focuses on recent developments in three key areas. The first area describes the completion of a standard AFC baseline material. The baseline AFC consists of 5.5mil diameter PZT-5A fibers laminated with an epoxy film adhesive and silver screen-printed electrodes. A scalable fabrication process based on lamination industry equipment has been implemented. Baseline AFC performance has been characterized, including free strains and blocked force. The send area describes continued work in developing optimized geometry/materials for future AFCs. AFC performance and efficiency can be affected significantly by changes in electrode pitch and fiber diameter and/or cross- sectional geometry. Various improved design have been identified. Third is review of application demonstration that exploit the benefits of AFCs to solve structural control problems.

  13. Subgenual PFC Activity Predicts Individual Differences in HPA Activity Across Different Contexts

    PubMed Central

    Jahn, Allison L.; Fox, Andrew S.; Abercrombie, Heather C.; Shelton, Steven E.; Oakes, Terrence R.; Davidson, Richard J.; Kalin, Ned H.

    2009-01-01

    Background Hypothalamic-pituitary-adrenal (HPA) system activation is adaptive in response to stress, and HPA dysregulation occurs in stress-related psychopathology. It is important to understand the mechanisms that modulate HPA output; yet, few studies have addressed the neural circuitry associated with HPA regulation in primates and humans. Using high-resolution [F-18]-fluoro-deoxyglucose (FDG) positron emission tomography (PET) in rhesus monkeys, we assessed the relation between individual differences in brain activity and HPA function across multiple contexts that varied in stressfulness. Methods Using a logical AND conjunctions analysis, we assessed cortisol and brain metabolic activity with FDG-PET in 35 adolescent rhesus monkeys exposed to two threat and two home-cage conditions. To test the robustness of our findings, we used similar methods in an archival data set. In this data set, brain metabolic activity and cortisol were assessed in 17 adolescent male rhesus monkeys that were exposed to three different stress-related contexts. Results Results from the two studies, revealed that subgenual PFC metabolism (Area 25/24) consistently predicted individual differences in plasma cortisol concentrations regardless of the context in which brain activity and cortisol were assessed. Conclusions These findings suggest that activation in subgenual PFC may be related to HPA output across a variety of contexts (including familiar settings and novel or threatening situations). Individuals prone to elevated subgenual PFC activity across multiple contexts may be individuals who consistently show heightened cortisol, and may be at risk for stress-related HPA dysregulation. PMID:19846063

  14. 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...

  15. Factors Predicting Physical Activity Among Children With Special Needs

    PubMed Central

    Yee, Chu Tang; Chung, Paul J.

    2013-01-01

    Introduction Obesity is especially prevalent among children with special needs. Both lack of physical activity and unhealthful eating are major contributing factors. The objective of our study was to investigate barriers to physical activity among these children. Methods We surveyed parents of the 171 children attending Vista Del Mar School in Los Angeles, a nonprofit school serving a socioeconomically diverse group of children with special needs from kindergarten through 12th grade. Parents were asked about their child’s and their own physical activity habits, barriers to their child’s exercise, and demographics. The response rate was 67%. Multivariate logistic regression was used to examine predictors of children being physically active at least 3 hours per week. Results Parents reported that 45% of the children were diagnosed with attention deficit hyperactivity disorder, 38% with autism, and 34% with learning disabilities; 47% of children and 56% of parents were physically active less than 3 hours per week. The top barriers to physical activity were reported as child’s lack of interest (43%), lack of developmentally appropriate programs (33%), too many behavioral problems (32%), and parents’ lack of time (29%). However, child’s lack of interest was the only parent-reported barrier independently associated with children’s physical activity. Meanwhile, children whose parents were physically active at least 3 hours per week were 4.2 times as likely to be physically active as children whose parents were less physically active (P = .01). Conclusion In this group of students with special needs, children’s physical activity was strongly associated with parental physical activity; parent-reported barriers may have had less direct effect. Further studies should examine the importance of parental physical activity among children with special needs. PMID:23866163

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

    SciTech Connect

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

    2015-07-22

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

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

    NASA Astrophysics Data System (ADS)

    Zhang, Yang; Zhang, Xin; Wang, Kai; He, Jian; Leung, L. Ruby; Fan, Jiwen; Nenes, Athanasios

    2015-07-01

    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

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

    NASA Technical Reports Server (NTRS)

    Barath, F. T.

    1977-01-01

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

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

    PubMed

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

    2016-03-30

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

  20. Plant folklore: a tool for predicting sources of antitumor activity?

    PubMed

    Spjut, R W; Perdue, R E

    1976-08-01

    The National Cancer Institute's record of "active plants" (extracts which showed a significant inhibitory effect in experimental tumor systems) was compared with plants reported in folklore to have medicinal or poisonous properties. The occurrence of active plants was found to be higher in plants reported in folk literature than in plants collected at random, suggesting a correlation between plants used in folklore and those with anticancer activity.

  1. Monitoring the biological activity of micropollutants during advanced wastewater treatment with ozonation and activated carbon filtration.

    PubMed

    Macova, M; Escher, B I; Reungoat, J; Carswell, S; Chue, K Lee; Keller, J; Mueller, J F

    2010-01-01

    A bioanalytical test battery was used to monitor the removal efficiency of organic micropollutants during advanced wastewater treatment in the South Caboolture Water Reclamation Plant, Queensland, Australia. This plant treats effluent from a conventional sewage treatment plant for industrial water reuse. The aqueous samples were enriched using solid-phase extraction to separate some organic micropollutants of interest from metals, nutrients and matrix components. The bioassays were chosen to provide information on groups of chemicals with a common mode of toxic action. Therefore they can be considered as sum indicators to detect certain relevant groups of chemicals, not as the most ecologically or human health relevant endpoints. The baseline toxicity was quantified with the bioluminescence inhibition test using the marine bacterium Vibrio fischeri. The specific modes of toxic action that were targeted with five additional bioassays included aspects of estrogenicity, dioxin-like activity, genotoxicity, neurotoxicity, and phytotoxicity. While the accompanying publication discusses the treatment steps in more detail by drawing from the results of chemical analysis as well as the bioanalytical results, here we focus on the applicability and limitations of using bioassays for the purpose of determining the treatment efficacy of advanced water treatment and for water quality assessment in general. Results are reported in toxic equivalent concentrations (TEQ), that is, the concentration of a reference compound required to elicit the same response as the unknown and unidentified mixture of micropollutants actually present. TEQ proved to be useful and easily communicable despite some limitations and uncertainties in their derivation based on the mixture toxicity theory. The results obtained were reproducible, robust and sensitive. The TEQ in the influent ranged in the same order of magnitude as typically seen in effluents of conventional sewage treatment plants. In the

  2. 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.

  3. Advanced Predictive Model and Real-World Results for Medium Concentration CPV

    NASA Astrophysics Data System (ADS)

    Karney, Bruce; Finot, Marc

    2011-12-01

    Skyline Solar has developed a novel medium concentration PV product. The system is a linear concentrator that tracks the sun with a 1-axis horizontal tracker. Reflectors are used to concentrate sunlight 7-50x using non-imaging optics. The receivers use Silicon cells and passive cooling. The product's design has been guided by a detailed Performance Prediction Tool (PPT) that relates component characteristics and climate data to the overall energy production. In contrast with other tools, the PPT captures the non-linearity of conditions such as weather, system architecture (stringing, shadow management) and the value of energy as a function of time of day and season. This paper describes the key elements of the PPT and compares its predictions to real-world results from different locations with significantly different DNI. Moderate DNI sites are San Jose, California and Kona, Hawaii. The higher DNI site is Nipton, California (DNI ˜7.2). Skyline's PPT accurately predicts the energy harvest for two Skyline Solar systems including the HGS 1000 and the new Skyline Solar X14 System.

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  6. 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.

  7. 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.

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

    PubMed

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

    2016-09-01

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

  9. Towards computational prediction of microRNA function and activity

    PubMed Central

    Ulitsky, Igor; Laurent, Louise C.; Shamir, Ron

    2010-01-01

    While it has been established that microRNAs (miRNAs) play key roles throughout development and are dysregulated in many human pathologies, the specific processes and pathways regulated by individual miRNAs are mostly unknown. Here, we use computational target predictions in order to automatically infer the processes affected by human miRNAs. Our approach improves upon standard statistical tools by addressing specific characteristics of miRNA regulation. Our analysis is based on a novel compendium of experimentally verified miRNA-pathway and miRNA-process associations that we constructed, which can be a useful resource by itself. Our method also predicts novel miRNA-regulated pathways, refines the annotation of miRNAs for which only crude functions are known, and assigns differential functions to miRNAs with closely related sequences. Applying our approach to groups of co-expressed genes allows us to identify miRNAs and genomic miRNA clusters with functional importance in specific stages of early human development. A full list of the predicted mRNA functions is available at http://acgt.cs.tau.ac.il/fame/. PMID:20576699

  10. 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.

  11. 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

  12. Advances in mechanisms of activation and deactivation of environmental chemicals.

    PubMed Central

    Goldstein, J A; Faletto, M B

    1993-01-01

    Environmental chemicals are both activated and detoxified by phase I and phase II enzymes. The principal enzymes involved in phase I reactions are the cytochrome P-450s. The phase II enzymes include hydrolase and the conjugative enzymes such as glucuronyltransferases, glutathione transferases, N-acetyltransferase, and sulfotransferase. Although other phase I and phase II enzymes exist, the present review is limited to these enzymes. Once thought to be a single enzyme, multiple cytochrome P-450 enzymes have been purified and characterized from many different species across the evolutionary tree. The application of molecular biology techniques to this field has identified more than 150 cytochrome P-450 genes to date. At least 20-30 cytochrome P-450 enzymes appear to exist in each mammalian species, and many polymorphisms in these enzymes are being identified. The cytochrome P-450 enzymes can now be expressed in recombinant form using cDNA expression systems. The phase II conjugative enzymes add a hydrophilic moiety such as sulfate, glucuronide, or acetate to compounds, which increases their water solubility and facilitates their excretion. However, conjugates of a number of compounds also result in more reactive electrophilic species, which appear to be the ultimate carcinogens. Many of these phase II enzymes also represent families of enzymes, and polymorphisms can affect the ability of these enzymes to metabolize chemicals. Whenever possible, we have reviewed knowledge of the human enzymes involved in particular pathways. PMID:8354165

  13. 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.

  14. [Advances in transcription activator-like effectors--a review].

    PubMed

    Yu, Tang; Li, Lisha; Lin, Jun

    2015-07-01

    As a protein originally found in plant pathogenic bacteria, transcription activator-like effectors (TALEs) can be fused with the cleaving domain of restriction endonuclease (For example Fok I) to form artificial nucleases named TALENs. These proteins are dependent on variable numbers of tandem Repeats of TALEs to recognize and bind DNA sequences. Each of these repeats consists of a set of approximately 34 amino acids, composed of about 32 conserved amino acids and 2 highly variable amino acids called repeat variant di-residues (RVDs). RVDs distinguish one TALE from another and can make TALEs have a simple cipher for the one-to-one recognition for proteins and DNA bases. Based on this, in theory, artificially constructed TALENs could recognize and break DNA sites specifically and arbitrarily to perform gene knockout, insertion or modification. We reviewed the development of this technology in multi-level and multi species, and its advantages and disadvantages compared with ZFNs and CRISPR/Cas technology. We also address its special advantages in industrial microbe breeding, vector construction, targeting precision, high efficiency of editing and biological safety. PMID:26647578

  15. Development of actively cooled panels for advanced propulsion systems

    NASA Astrophysics Data System (ADS)

    Hauber, Brett K.

    1998-01-01

    Development of actively cooled flowpath panels for the National Aero-Space Plane (NASP) propulsion system was a critical task in the development plan of the air vehicle system. This task encompassed development of design requirements and loads, and component design and testing. In the early 90's the effort focused on six cooled panel designs based in five different materials (NARloy-Z, Haynes 188, MoRe, IN909, C/C and C/SiC), each satisfying requirements in a different area of the propulsion flowpath. Eventually, three of these designs were fabricated and tested. For these tests, two primary facilities were used. The first was a radiant heating facility at Wright Patterson Air Force Base (WPAFB), and the second, a vitiated air heater at General Applied Science Laboratories (GASL) Inc. In these facilities, tests were run to validate thermal and mechanical models and to demonstrate coating durability and effectiveness. Additional tests to assess the damage tolerance of these designs were planned but never run. These tests ultimately exposed strengths and weaknesses in the designs and the analysis methods.

  16. 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.

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

    PubMed

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

    2015-10-01

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

  18. 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.

  19. 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…

  20. Advanced modeling of active control of fan noise for ultra high bypass turbofan engines

    NASA Astrophysics Data System (ADS)

    Hutcheson, Florence Vanel

    1999-11-01

    An advanced model of active control of fan noise for ultra high bypass turbofan engines has been developed. This model is based on a boundary integral equation method and simulates the propagation, radiation and control of the noise generated by an engine fan surrounded by a duct of finite length and cylindrical shape, placed in a uniform flow. Control sources, modeled by point monopoles placed along the wall of the engine inlet or outlet duct, inject anti-noise into the duct to destructively interfere with the sound field generated by the fan. The duct inner wall can be lined or rigid. Unlike current methods, reflection from the duct openings is taken into account, as well as the presence of the evanescent modes. Forward, as well as backward (i.e., from the rear of the engine), external radiation is computed. The development of analytical expressions for the sound field resulting from both the fan loading noise and the control sources is presented. Two fan models are described. The first model uses spinning line sources with radially distributed strength to model the loading force that the fan blades exert on the medium. The second model uses radial arrays of spinning point dipoles to simulate the generation of fan modes of specific modal amplitudes. It is shown that these fan models can provide a reasonable approximation of actual engine fan noise in the instance when the modal amplitude of the propagating modes or the loading force distribution on the fan blades, is known. Sample cases of active noise control are performed to demonstrate the feasibility of the model. The results from these tests indicate that this model (1)is conducive to more realistic studies of active control of fan noise on ultra high bypass turbofan engines because it accounts for the presence of evanescent modes and for interference between inlet and outlet radiation, which were shown to have some impact on the performance of the active control system; (2)is very useful because it allows

  1. Prediction of Activity Cliffs Using Condensed Graphs of Reaction Representations, Descriptor Recombination, Support Vector Machine Classification, and Support Vector Regression.

    PubMed

    Horvath, Dragos; Marcou, Gilles; Varnek, Alexandre; Kayastha, Shilva; de la Vega de León, Antonio; Bajorath, Jürgen

    2016-09-26

    Activity cliffs (ACs) are formed by structurally similar compounds with large differences in activity. Accordingly, ACs are of high interest for the exploration of structure-activity relationships (SARs). ACs reveal small chemical modifications that result in profound biological effects. The ability to foresee such small chemical changes with significant biological consequences would represent a major advance for drug design. Nevertheless, only few attempts have been made so far to predict whether a pair of analogues is likely to represent an AC-and even fewer went further to quantitatively predict how "deep" a cliff might be. This might be due to the fact that such predictions must focus on compound pairs. Matched molecular pairs (MMPs), defined as pairs of structural analogs that are only distinguished by a chemical modification at a single site, are a preferred representation of ACs. Herein, we report new strategies for AC prediction that are based upon two different approaches: (i) condensed graphs of reactions, which were originally introduced for modeling of chemical reactions and were here adapted to encode MMPs, and, (ii) plain descriptor recombination-a strategy used for quantitative structure-property relationship (QSPR) modeling of nonadditive mixtures (MQSPR). By applying these concepts, ACs were encoded as single descriptor vectors used as input for support vector machine (SVM) classification and support vector regression (SVR), yielding accurate predictions of AC status (i.e., cliff vs noncliff) and potency differences, respectively. The latter were predicted in a compound order-sensitive manner returning the signed value of expected potency differences between AC compounds. PMID:27564682

  2. Prediction of Activity Cliffs Using Condensed Graphs of Reaction Representations, Descriptor Recombination, Support Vector Machine Classification, and Support Vector Regression.

    PubMed

    Horvath, Dragos; Marcou, Gilles; Varnek, Alexandre; Kayastha, Shilva; de la Vega de León, Antonio; Bajorath, Jürgen

    2016-09-26

    Activity cliffs (ACs) are formed by structurally similar compounds with large differences in activity. Accordingly, ACs are of high interest for the exploration of structure-activity relationships (SARs). ACs reveal small chemical modifications that result in profound biological effects. The ability to foresee such small chemical changes with significant biological consequences would represent a major advance for drug design. Nevertheless, only few attempts have been made so far to predict whether a pair of analogues is likely to represent an AC-and even fewer went further to quantitatively predict how "deep" a cliff might be. This might be due to the fact that such predictions must focus on compound pairs. Matched molecular pairs (MMPs), defined as pairs of structural analogs that are only distinguished by a chemical modification at a single site, are a preferred representation of ACs. Herein, we report new strategies for AC prediction that are based upon two different approaches: (i) condensed graphs of reactions, which were originally introduced for modeling of chemical reactions and were here adapted to encode MMPs, and, (ii) plain descriptor recombination-a strategy used for quantitative structure-property relationship (QSPR) modeling of nonadditive mixtures (MQSPR). By applying these concepts, ACs were encoded as single descriptor vectors used as input for support vector machine (SVM) classification and support vector regression (SVR), yielding accurate predictions of AC status (i.e., cliff vs noncliff) and potency differences, respectively. The latter were predicted in a compound order-sensitive manner returning the signed value of expected potency differences between AC compounds.

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

    PubMed

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

    2016-01-01

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

  4. 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

  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. Compound Structure-Independent Activity Prediction in High-Dimensional Target Space.

    PubMed

    Balfer, Jenny; Hu, Ye; Bajorath, Jürgen

    2014-08-01

    Profiling of compound libraries against arrays of targets has become an important approach in pharmaceutical research. The prediction of multi-target compound activities also represents an attractive task for machine learning with potential for drug discovery applications. Herein, we have explored activity prediction in high-dimensional target space. Different types of models were derived to predict multi-target activities. The models included naïve Bayesian (NB) and support vector machine (SVM) classifiers based upon compound structure information and NB models derived on the basis of activity profiles, without considering compound structure. Because the latter approach can be applied to incomplete training data and principally depends on the feature independence assumption, SVM modeling was not applicable in this case. Furthermore, iterative hybrid NB models making use of both activity profiles and compound structure information were built. In high-dimensional target space, NB models utilizing activity profile data were found to yield more accurate activity predictions than structure-based NB and SVM models or hybrid models. An in-depth analysis of activity profile-based models revealed the presence of correlation effects across different targets and rationalized prediction accuracy. Taken together, the results indicate that activity profile information can be effectively used to predict the activity of test compounds against novel targets.

  7. 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.

  8. Activity predicts male reproductive success in a polygynous lizard.

    PubMed

    Keogh, J Scott; Noble, Daniel W A; Wilson, Eleanor E; Whiting, Martin J

    2012-01-01

    Activity patterns and social interactions play a key role in determining reproductive success, although this is poorly understood for species that lack overt social behaviour. We used genetic paternity analysis to quantify both multiple paternity and the relative roles of activity and social behaviour in determining reproductive success in a nondescript Australian lizard. During the breeding season we intensively followed and recorded the behaviour of a group of seven males and 13 females in a naturalistic outdoor enclosure to examine the relative roles of body size, activity and social interactions in determining male fertilization success. We found multiple paternity in 42% of clutches. No single behaviour was a significant predictor of male fertilization success in isolation, but male-female association, interactions and courtship explained 41% of the variation in male fertilization success. Males with the highest number of offspring sired invested heavily in interacting with females but spent very little time in interactions with males. These same males also sired offspring from more clutches. When taken collectively, an index of overall male activity, including locomotion and all social interactions, significantly explained 81% of the variation in the total number of offspring sired and 90% of the variation in the number of clutches in which males sired offspring. We suggest that the most successful male strategy is a form of endurance rivalry in which active mate searching and interactions with females have the greatest fitness benefits.

  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. 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.

  11. [Advance in researches on vegetation cover and management factor in the soil erosion prediction model].

    PubMed

    Zhang, Yan; Yuan, Jianping; Liu, Baoyuan

    2002-08-01

    Vegetation cover and land management are the main limiting factors of soil erosion, and quantitative evaluation on the effect of different vegetation on soil erosion is essential to land use and soil conservation planning. The vegetation cover and management factor (C) in the universal soil loss equation (USLE) is an index to evaluate this effect, which has been studied deeply and used widely. However, the C factor study is insufficient in China. In order to strengthen the research of C factor, this paper reviewed the developing progress of C factor, and compared the methods of estimating C value in different USLE versions. The relative studies in China were also summarized from the aspects of vegetation canopy coverage, soil surface cover, and root density. Three problems in C factor study were pointed out. The authors suggested that cropland C factor research should be furthered, and its methodology should be unified in China to represent reliable C values for soil loss prediction and conservation planning.

  12. Application of neural networks to prediction of advanced composite structures mechanical response and behavior

    NASA Technical Reports Server (NTRS)

    Cios, K. J.; Vary, A.; Berke, L.; Kautz, H. E.

    1992-01-01

    Two types of neural networks were used to evaluate acousto-ultrasonic (AU) data for material characterization and mechanical reponse prediction. The neural networks included a simple feedforward network (backpropagation) and a radial basis functions network. Comparisons of results in terms of accuracy and training time are given. Acousto-ultrasonic (AU) measurements were performed on a series of tensile specimens composed of eight laminated layers of continuous, SiC fiber reinforced Ti-15-3 matrix. The frequency spectrum was dominated by frequencies of longitudinal wave resonance through the thickness of the specimen at the sending transducer. The magnitude of the frequency spectrum of the AU signal was used for calculating a stress-wave factor based on integrating the spectral distribution function and used for comparison with neural networks results.

  13. 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.

  14. Advanced Prediction of Tool Wear by Taking the Load History into Consideration

    NASA Astrophysics Data System (ADS)

    Ersoy, K.; Nuernberg, G.; Herrmann, G.; Hoffmann, H.

    2007-04-01

    A disadvantage of the conventional methods of simulating the wear occurring in deep drawing processes is that the wear coefficient, and thus wear too, is considered to be constant along loading duration, which, in case of deep drawing, corresponds to sliding distance and number of punch strokes. However, in reality, it is a known fact that wear development is not constant over time. In former studies, the authors presented a method, which makes it possible to consider the number of punch strokes in the simulation of wear. Another enhancement of this method is introduced in this paper. It is proposed to consider wear as a function of wear work instead of the number of punch strokes. Using this approach, the wear coefficients are implemented as a function of wear work and fully take into account the load history of the respective node. This enhancement makes it possible to apply the variable wear coefficients to completely different geometries, where one punch stroke involves different sliding distance or pressure values than the experiments with which the wear coefficients were determined. In this study, deep drawing experiments with a cylindrical cup geometry were carried out, in which the characteristic wear coefficient values as well as their gradients along the life cycle were determined. In this case, the die was produced via rapid tooling techniques. The prediction of tool wear is carried out with REDSY, a wear simulation software which was developed at the Institute of Metal Forming and Casting, TU-Muenchen. The wear predictions made by this software are based on the results of a conventional deep drawing simulation. For the wear modelling a modified Archard model was used.

  15. Similarity of Cortical Activity Patterns Predicts generalization Behavior

    PubMed Central

    Engineer, Crystal T.; Perez, Claudia A.; Carraway, Ryan S.; Chang, Kevin Q.; Roland, Jarod L.; Sloan, Andrew M.; Kilgard, Michael P.

    2013-01-01

    Humans and animals readily generalize previously learned knowledge to new situations. Determining similarity is critical for assigning category membership to a novel stimulus. We tested the hypothesis that category membership is initially encoded by the similarity of the activity pattern evoked by a novel stimulus to the patterns from known categories. We provide behavioral and neurophysiological evidence that activity patterns in primary auditory cortex contain sufficient information to explain behavioral categorization of novel speech sounds by rats. Our results suggest that category membership might be encoded by the similarity of the activity pattern evoked by a novel speech sound to the patterns evoked by known sounds. Categorization based on featureless pattern matching may represent a general neural mechanism for ensuring accurate generalization across sensory and cognitive systems. PMID:24147140

  16. Worry tendencies predict brain activation during aversive imagery.

    PubMed

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

    2009-09-25

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

  17. Family History Predicts Stress Fracture in Active Female Adolescents

    PubMed Central

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

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  19. Physical activity related information sources predict physical activity behaviors in adults with type 2 diabetes.

    PubMed

    Plotnikoff, Ronald C; Johnson, Steven T; Karunamuni, Nandini; Boule, Normand G

    2010-12-01

    Physical activity (PA) is a key management strategy for type 2 diabetes. Despite the known benefits, PA levels are low. Whether the low level of PA is related to lack of knowledge or support is not fully understood. This study was conducted to describe where and how often adults with type 2 diabetes receive and seek information related to PA and examine the relationships between the source and quality of PA information with PA behaviors. A series of questions related to the source and quality of PA information were added to a baseline survey distributed to the participants (N = 244) of the Canadian Aerobic and Resistance Training in Diabetes (CARED) study. Physicians and television were found to be the main sources of PA-related information. In our cross-sectional model, sources of PA-related information other than that from health care professionals explained 14% (p = .05) and 16% (p < .05) of the variance for aerobic-based and resistance training behaviors and 22% (p < .01) and 15% (p < .05) for these behaviors in our longitudinal model. Physical activity (PA)-related information is widely available to adults with type 2 diabetes. Neither the quantity nor the quality of the PA information provided by health care professionals predicted PA behavior. These data provide further insight into the modes with which PA can be promoted to adults with type 2 diabetes. PMID:21170787

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

    Toukach, Filip V; Ananikov, Valentine P

    2013-11-01

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

  2. Predictive biomarkers in advance of a companion drug: ahead of their time?

    PubMed

    Kelley, Robin K; Atreya, Chloe; Venook, Alan P; Febbo, Phillip G

    2012-03-01

    Because of a surge in molecular testing capabilities concurrent with the rising numbers of targeted therapies in clinical development, the commercial use of predictive biomarkers before clinical validation is available is a topic of growing relevance to medical oncologists. Increasingly, patients will present questions about, requests for, and results from commercial biomarker tests for their oncologists to address. The sheer numbers of tests reaching the market, along with forecasted American Medical Association reforms in current procedural terminology coding and increasing FDA oversight of in vitro companion diagnostic device development, are likely to draw intense scrutiny to the regulation of commercial molecular testing in the near future, which will also require clinicians to remain abreast of the level of clinical validation of the biomarker tests available in practice. In addition to the direct risks of novel biomarker testing, including financial cost and ethical issues, the indirect risks encompass those associated with any clinical decision based on the biomarker test results. A great need exists for comprehensive and dynamic practice guidelines for all types of biomarker testing according to tumor type. PMID:22393192

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2015-01-01

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

  5. HPV Genotypes Predict Survival Benefits From Concurrent Chemotherapy and Radiation Therapy in Advanced Squamous Cell Carcinoma of the Cervix

    SciTech Connect

    Wang, Chun-Chieh; Lai, Chyong-Huey; Huang, Yi-Ting; Chao, Angel; Chou, Hung-Hsueh; Hong, Ji-Hong

    2012-11-15

    Purpose: To study the prognostic value of human papillomavirus (HPV) genotypes in patients with advanced cervical cancer treated with radiation therapy (RT) alone or concurrent chemoradiation therapy (CCRT). Methods and Materials: Between August 1993 and May 2000, 327 patients with advanced squamous cell carcinoma of the cervix (International Federation of Gynecology and Obstetrics stage III/IVA or stage IIB with positive lymph nodes) were eligible for this study. HPV genotypes were determined using the Easychip Registered-Sign HPV genechip. Outcomes were analyzed using Kaplan-Meier survival analysis and the Cox proportional hazards model. Results: We detected 22 HPV genotypes in 323 (98.8%) patients. The leading 4 types were HPV16, 58, 18, and 33. The 5-year overall and disease-specific survival estimates for the entire cohort were 41.9% and 51.4%, respectively. CCRT improved the 5-year disease-specific survival by an absolute 9.8%, but this was not statistically significant (P=.089). There was a significant improvement in disease-specific survival in the CCRT group for HPV18-positive (60.9% vs 30.4%, P=.019) and HPV58-positive (69.3% vs 48.9%, P=.026) patients compared with the RT alone group. In contrast, the differences in survival with CCRT compared with RT alone in the HPV16-positive and HPV-33 positive subgroups were not statistically significant (P=.86 and P=.53, respectively). An improved disease-specific survival was observed for CCRT treated patients infected with both HPV16 and HPV18, but these differenced also were not statistically significant. Conclusions: The HPV genotype may be a useful predictive factor for the effect of CCRT in patients with advanced squamous cell carcinoma of the cervix. Verifying these results in prospective trials could have an impact on tailoring future treatment based on HPV genotype.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-10-27

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

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

    PubMed

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

    2015-03-25

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

  9. 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

  10. A DNA Sequence Element That Advances Replication Origin Activation Time in Saccharomyces cerevisiae

    PubMed Central

    Pohl, Thomas J.; Kolor, Katherine; Fangman, Walton L.; Brewer, Bonita J.; Raghuraman, M. K.

    2013-01-01

    Eukaryotic origins of DNA replication undergo activation at various times in S-phase, allowing the genome to be duplicated in a temporally staggered fashion. In the budding yeast Saccharomyces cerevisiae, the activation times of individual origins are not intrinsic to those origins but are instead governed by surrounding sequences. Currently, there are two examples of DNA sequences that are known to advance origin activation time, centromeres and forkhead transcription factor binding sites. By combining deletion and linker scanning mutational analysis with two-dimensional gel electrophoresis to measure fork direction in the context of a two-origin plasmid, we have identified and characterized a 19- to 23-bp and a larger 584-bp DNA sequence that are capable of advancing origin activation time. PMID:24022751

  11. 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.

  12. 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…

  13. 25 CFR 170.615 - Can a tribe receive advance payments for non-construction activities?

    Code of Federal Regulations, 2012 CFR

    2012-04-01

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

  14. 25 CFR 170.615 - Can a tribe receive advance payments for non-construction activities?

    Code of Federal Regulations, 2011 CFR

    2011-04-01

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

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

    Code of Federal Regulations, 2010 CFR

    2010-04-01

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

  16. 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,…

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

    ERIC Educational Resources Information Center

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

    2004-01-01

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

  18. 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.

  19. 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

  20. 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…

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

    ERIC Educational Resources Information Center

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

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Kaneda, Yoshiyuki

    2015-04-01

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

  3. 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

  4. 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.

  5. 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...

  6. 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...

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

    PubMed Central

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

    2011-01-01

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

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

    PubMed

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

    2015-07-01

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

  9. DNA methylation status predicts cell type-specific enhancer activity

    PubMed Central

    Wiench, Malgorzata; John, Sam; Baek, Songjoon; Johnson, Thomas A; Sung, Myong-Hee; Escobar, Thelma; Simmons, Catherine A; Pearce, Kenneth H; Biddie, Simon C; Sabo, Pete J; Thurman, Robert E; Stamatoyannopoulos, John A; Hager, Gordon L

    2011-01-01

    Cell-selective glucocorticoid receptor (GR) binding to distal regulatory elements is associated with cell type-specific regions of locally accessible chromatin. These regions can either pre-exist in chromatin (pre-programmed) or be induced by the receptor (de novo). Mechanisms that create and maintain these sites are not well understood. We observe a global enrichment of CpG density for pre-programmed elements, and implicate their demethylated state in the maintenance of open chromatin in a tissue-specific manner. In contrast, sites that are actively opened by GR (de novo) are characterized by low CpG density, and form a unique class of enhancers devoid of suppressive effect of agglomerated methyl-cytosines. Furthermore, treatment with glucocorticoids induces rapid changes in methylation levels at selected CpGs within de novo sites. Finally, we identify GR-binding elements with CpGs at critical positions, and show that methylation can affect GR–DNA interactions in vitro. The findings present a unique link between tissue-specific chromatin accessibility, DNA methylation and transcription factor binding and show that DNA methylation can be an integral component of gene regulation by nuclear receptors. PMID:21701563

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

    PubMed

    Albrecht, Tara A; Taylor, Ann Gill

    2012-06-01

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

  11. Advanced glycation end products and their circulating receptors predict cardiovascular disease mortality in older community-dwelling women

    PubMed Central

    Semba, Richard D.; Ferrucci, Luigi; Sun, Kai; Beck, Justine; Dalal, Mansi; Varadhan, Ravi; Walston, Jeremy; Guralnik, Jack M.; Fried, Linda P.

    2008-01-01

    Objective To characterize the relationship between advanced glycation end products (AGEs) and circulating receptors for AGEs (RAGE) with cardiovascular disease mortality. Methods The relationships between serum AGEs, total RAGE (sRAGE), and endogenous secretory RAGE (esRAGE), and mortality were characterized in 559 community-dwelling women, ≥65 years, in Baltimore, Maryland. Results During 4.5 years of follow-up, 123 (22%) women died, of whom 54 died with cardiovascular disease. The measure of serum AGEs was carboxymethyl-lysine (CML), a dominant AGE. Serum CML predicted cardiovascular disease mortality (Hazards Ratio [H.R.] for highest versus lower three quartiles 1.94, 95% Confidence Interval [C.I.] 1.08-3.48, P = 0.026), after adjusting for age, race, body mass index, and renal insufficiency. Serum sRAGE (ng/mL) and esRAGE (ng/mL) predicted cardiovascular disease mortality (H.R. per 1 Standard Deviation [S.D.] 1.27, 95% C.I. 0.98-1.65, P = 0.07; H.R. 1.28, 95% C.I. 1.02-1.63, P = 0.03), after adjusting for the same covariates. Among non-diabetic women, serum CML, sRAGE, and esRAGE, respectively, predicted cardiovascular disease mortality (H.R. for highest versus lower three quartiles, 2.29, 95% C.I. 1.21-4.34, P = 0.01; H.R. per 1 S.D., 1.24, 95% C.I. 0.92-1.65, P = 0.16; H.R. per 1 S.D. 1.45, 95% C.I. 1.08-1.93, P = 0.01), after adjusting for the same covariates. Conclusions High circulating AGEs and RAGE predict cardiovascular disease mortality among older community-dwelling women. AGEs are a potential target for interventions, as serum AGEs can be lowered by change in dietary pattern and pharmacological treatment. PMID:19448391

  12. 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.

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

    SciTech Connect

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

    2007-08-01

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

  14. 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.

  15. 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.

  16. New Quantitative Structure-Activity Relationship Models Improve Predictability of Ames Mutagenicity for Aromatic Azo Compounds.

    PubMed

    Manganelli, Serena; Benfenati, Emilio; Manganaro, Alberto; Kulkarni, Sunil; Barton-Maclaren, Tara S; Honma, Masamitsu

    2016-10-01

    Existing Quantitative Structure-Activity Relationship (QSAR) models have limited predictive capabilities for aromatic azo compounds. In this study, 2 new models were built to predict Ames mutagenicity of this class of compounds. The first one made use of descriptors based on simplified molecular input-line entry system (SMILES), calculated with the CORAL software. The second model was based on the k-nearest neighbors algorithm. The statistical quality of the predictions from single models was satisfactory. The performance further improved when the predictions from these models were combined. The prediction results from other QSAR models for mutagenicity were also evaluated. Most of the existing models were found to be good at finding toxic compounds but resulted in many false positive predictions. The 2 new models specific for this class of compounds avoid this problem thanks to a larger set of related compounds as training set and improved algorithms.

  17. New Quantitative Structure-Activity Relationship Models Improve Predictability of Ames Mutagenicity for Aromatic Azo Compounds.

    PubMed

    Manganelli, Serena; Benfenati, Emilio; Manganaro, Alberto; Kulkarni, Sunil; Barton-Maclaren, Tara S; Honma, Masamitsu

    2016-10-01

    Existing Quantitative Structure-Activity Relationship (QSAR) models have limited predictive capabilities for aromatic azo compounds. In this study, 2 new models were built to predict Ames mutagenicity of this class of compounds. The first one made use of descriptors based on simplified molecular input-line entry system (SMILES), calculated with the CORAL software. The second model was based on the k-nearest neighbors algorithm. The statistical quality of the predictions from single models was satisfactory. The performance further improved when the predictions from these models were combined. The prediction results from other QSAR models for mutagenicity were also evaluated. Most of the existing models were found to be good at finding toxic compounds but resulted in many false positive predictions. The 2 new models specific for this class of compounds avoid this problem thanks to a larger set of related compounds as training set and improved algorithms. PMID:27413112

  18. Predicting hand orientation in reach-to-grasp tasks using neural activities from primary motor cortex.

    PubMed

    Zhang, Peng; Ma, Xuan; Huang, Hailong; He, Jiping

    2014-01-01

    Hand orientation is an important control parameter during reach-to-grasp task. In this paper, we presented a study for predicting hand orientation of non-human primate by decoding neural activities from primary motor cortex (M1). A non-human primate subject was guided to do reaching and grasping tasks meanwhile neural activities were acquired by chronically implanted microelectrode arrays. A Support Vector Machines (SVMs) classifier has been trained for predicting three different hand orientations using these M1 neural activities. Different number of neurons were selected and analyzed; the classifying accuracy was 94.1% with 2 neurons and was 100% with 8 neurons. Data from highly event related neuron units contribute a lot to the accuracy of hand orientation prediction. These results indicate that three different hand orientations can be predicted accurately and effectively before the actual movements occurring with a small number of related neurons in M1.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    DOEpatents

    Xiong, Yongliang; Wang, Yifeng

    2016-04-19

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

  2. 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.

  3. Nestin predicts a favorable prognosis in early ampullary adenocarcinoma and functions as a promoter of metastasis in advanced cancer.

    PubMed

    Shan, Yan-Shen; Chen, Yi-Ling; Lai, Ming-Derg; Hsu, Hui-Ping

    2015-01-01

    Nestin exhibits stemness characteristics and is overexpressed in several types of cancers. Downstream signaling of nestin [cyclin-dependent kinase 5 (CDK5) and Ras-related C3 botulinum toxin substrate 1 (Rac1)] functions in cancer to modulate cellular behaviors. We studied the function of nestin in ampullary adenocarcinoma. Immunohistochemistry (IHC), reverse transcription-polymerase chain reaction, and cDNA microarray of nestin in ampullary adenocarcinoma was compared with normal duodenum. CDK5 and Rac1 were assessed by western blotting. We hypothesized that nestin/CDK5/Rac1 signaling behaves different in early and advanced cancer. We found that the presence of nestin mRNA was increased in the early stages of cancer (T2N0 or T3N0) and advanced cancer with lymph node metastasis (T4N1). A total of 102 patients were enrolled in the IHC staining. Weak nestin expression was correlated with favorable characteristics of cancer, decreased incidence of local recurrence and lower risk of recurrence within 12 months after surgery. Patients with weak nestin expression had the most favorable recurrence‑free survival rates. Patients with mild to strong nestin expression exhibited an advanced behavior of cancer and increased possibility of cancer recurrence. The reciprocal expression of nestin and RAC1 were explored using a cDNA microarray analysis in the early stages of ampullary adenocarcinoma. Increased level of CDK5 with simultaneously decreased expression of Rac1 was detected by western blotting of ampullary adenocarcinoma in patients without cancer recurrence. The activation of multiple oncogenic pathways, combined with the stemness characteristics of nestin, formed a complex network in advanced ampullary adenocarcinoma. Our study demonstrated that nestin performs a dual role in ampullary adenocarcinoma. Appropriate amount of nestin enhances CDK5 function to suppress Rac1 and excessive nestin/CDK5 participates in multiple oncogenic pathways to promote cancer invasiveness

  4. 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.

  5. 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...

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

    ERIC Educational Resources Information Center

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

    2012-01-01

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

  7. Predictive activity profiling of drugs by topological-fragment-spectra-based support vector machines.

    PubMed

    Kawai, Kentaro; Fujishima, Satoshi; Takahashi, Yoshimasa

    2008-06-01

    Aiming at the prediction of pleiotropic effects of drugs, we have investigated the multilabel classification of drugs that have one or more of 100 different kinds of activity labels. Structural feature representation of each drug molecule was based on the topological fragment spectra method, which was proposed in our previous work. Support vector machine (SVM) was used for the classification and the prediction of their activity classes. Multilabel classification was carried out by a set of the SVM classifiers. The collective SVM classifiers were trained with a training set of 59,180 compounds and validated by another set (validation set) of 29,590 compounds. For a test set that consists of 9,864 compounds, the classifiers correctly classified 80.8% of the drugs into their own active classes. The SVM classifiers also successfully performed predictions of the activity spectra for multilabel compounds. PMID:18533712

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

    PubMed

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

    2016-04-01

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

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

    PubMed

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

    2016-04-01

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

  10. 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.

  11. 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.

  12. 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

  13. 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. PMID:25526596

  14. 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.

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

    PubMed

    Mestyán, Márton; Yasseri, Taha; Kertész, János

    2013-01-01

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

  16. A Predictive Model of Daily Seismic Activity Induced by Mining, Developed with Data Mining Methods

    NASA Astrophysics Data System (ADS)

    Jakubowski, Jacek

    2014-12-01

    The article presents the development and evaluation of a predictive classification model of daily seismic energy emissions induced by longwall mining in sector XVI of the Piast coal mine in Poland. The model uses data on tremor energy, basic characteristics of the longwall face and mined output in this sector over the period from July 1987 to March 2011. The predicted binary variable is the occurrence of a daily sum of tremor seismic energies in a longwall that is greater than or equal to the threshold value of 105 J. Three data mining analytical methods were applied: logistic regression,neural networks, and stochastic gradient boosted trees. The boosted trees model was chosen as the best for the purposes of the prediction. The validation sample results showed its good predictive capability, taking the complex nature of the phenomenon into account. This may indicate the applied model's suitability for a sequential, short-term prediction of mining induced seismic activity.

  17. Comparison of Different 2D and 3D-QSAR Methods on Activity Prediction of Histamine H3 Receptor Antagonists

    PubMed Central

    Dastmalchi, Siavoush; Hamzeh-Mivehroud, Maryam; Asadpour-Zeynali, Karim

    2012-01-01

    Histamine H3 receptor subtype has been the target of several recent drug development programs. Quantitative structure-activity relationship (QSAR) methods are used to predict the pharmaceutically relevant properties of drug candidates whenever it is applicable. The aim of this study was to compare the predictive powers of three different QSAR techniques, namely, multiple linear regression (MLR), artificial neural network (ANN), and HASL as a 3D QSAR method, in predicting the receptor binding affinities of arylbenzofuran histamine H3 receptor antagonists. Genetic algorithm coupled partial least square as well as stepwise multiple regression methods were used to select a number of calculated molecular descriptors to be used in MLR and ANN-based QSAR studies. Using the leave-group-out cross-validation technique, the performances of the MLR and ANN methods were evaluated. The calculated values for the mean absolute percentage error (MAPE), ranging from 2.9 to 3.6, and standard deviation of error of prediction (SDEP), ranging from 0.31 to 0.36, for both MLR and ANN methods were statistically comparable, indicating that both methods perform equally well in predicting the binding affinities of the studied compounds toward the H3 receptors. On the other hand, the results from 3D-QSAR studies using HASL method were not as good as those obtained by 2D methods. It can be concluded that simple traditional approaches such as MLR method can be as reliable as those of more advanced and sophisticated methods like ANN and 3D-QSAR analyses. PMID:25317190

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

    PubMed

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

    2016-03-15

    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.

  19. 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.

  20. The current status and future applicability of quantitative structure-activity relationships (QSARs) in predicting toxicity.

    PubMed

    Cronin, Mark T D

    2002-12-01

    The current status of quantitative structure-activity relationships (QSARs) in predicting toxicity is assessed. Widespread use of these methods to predict toxicity from chemical structure is possible, both by industry to develop new compounds, and also by regulatory agencies. The current use of QSARs is restricted by the lack of suitable toxicity data available for modelling, the suitability of simplistic modelling approaches for the prediction of certain endpoints, and the poor definition and utilisation of the applicability domain of models. Suggestions to resolve these issues are made.

  1. 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%.

  2. 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

  3. 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.

  4. 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.

  5. Autonomous Motivation Predicts 7-Day Physical Activity in Hong Kong Students.

    PubMed

    Ha, Amy S; Ng, Johan Y Y

    2015-07-01

    Autonomous motivation predicts positive health behaviors such as physical activity. However, few studies have examined the relation between motivational regulations and objectively measured physical activity and sedentary behaviors. Thus, we investigated whether different motivational regulations (autonomous motivation, controlled motivation, and amotivation) predicted 7-day physical activity, sedentary behaviors, and health-related quality of life (HRQoL) of students. A total of 115 students (mean age = 11.6 years, 55.7% female) self-reported their motivational regulations and health-related quality of life. Physical activity and sedentary behaviors were measured using accelerometers for seven days. Using multilevel modeling, we found that autonomous motivation predicted higher levels of moderate-to-vigorous physical activity, less sedentary behaviors, and better HRQoL. Controlled motivation and amotivation each only negatively predicted one facet of HRQoL. Results suggested that autonomous motivation could be an important predictor of physical activity behaviors in Hong Kong students. Promotion of this form of motivational regulation may also increase HRQoL. PMID:25943335

  6. 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.

  7. 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.

  8. 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.

  9. Machine Learning Methods and Docking For Predicting Human Pregnane X Receptor Activation

    PubMed Central

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

    2008-01-01

    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 non-activators 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 % to 98.9 % of activators and 62.0 % to 88.6 % of non-activators. 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 to 93.3 %, representing an improvement over models previously reported. All models were tested with a second test set (n =145) and prediction accuracy ranged from 63−67 % overall. These test set molecules were found to cover the same area in a principal component analysis plot as the training set, suggesting the predictions were within the applicability domain. The FlexX docking method combined with logistic regression performed poorly in classifying this PXR test set 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. PMID:18547065

  10. 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.

  11. An internally and externally validated nomogram for predicting the risk of irinotecan-induced severe neutropenia in advanced colorectal cancer patients

    PubMed Central

    Ichikawa, W; Uehara, K; Minamimura, K; Tanaka, C; Takii, Y; Miyauchi, H; Sadahiro, S; Fujita, K; Moriwaki, T; Nakamura, M; Takahashi, T; Tsuji, A; Shinozaki, K; Morita, S; Ando, Y; Okutani, Y; Sugihara, M; Sugiyama, T; Ohashi, Y; Sakata, Y

    2015-01-01

    Background: In Asians, the risk of irinotecan-induced severe toxicities is related in part to UGT1A1*6 (UGT, UDP glucuronosyltransferase) and UGT1A1*28, variant alleles that reduce the elimination of SN-38, the active metabolite of irinotecan. We prospectively studied the relation between the UGT1A1 genotype and the safety of irinotecan-based regimens in Japanese patients with advanced colorectal cancer, and then constructed a nomogram for predicting the risk of severe neutropenia in the first treatment cycle. Methods: Safety data were obtained from 1312 patients monitored during the first 3 cycles of irinotecan-based regimen in a prospective observational study. In development of the nomogram, multivariable logistic regression analysis was used to test the associations of candidate factors to severe neutropenia in the first cycle. The final nomogram based on the results of multivariable analysis was constructed and validated internally using a bootstrapping technique and externally in an independent data set (n=350). Results: The UGT1A1 genotype was confirmed to be associated with increased risks of irinotecan-induced grade 3 or 4 neutropenia and diarrhoea. The final nomogram included type of regimen, administered dose of irinotecan, gender, age, UGT1A1 genotype, Eastern Cooperative Oncology Group performance status, pre-treatment absolute neutrophil count, and total bilirubin level. The model was validated both internally (bootstrap-adjusted concordance index, 0.69) and externally (concordance index, 0.70). Conclusions: Our nomogram can be used before treatment to accurately predict the probability of irinotecan-induced severe neutropenia in the first cycle of therapy. Additional studies should evaluate the effect of nomogram-guided dosing on efficacy in patients receiving irinotecan. PMID:25880011

  12. Validity of APCS score as a risk prediction score for advanced colorectal neoplasia in Chinese asymptomatic subjects

    PubMed Central

    Li, Wenbin; Zhang, Lili; Hao, Jianyu; Wu, Yongdong; Lu, Di; Zhao, Haiying; Wang, Zhenjie; Xu, Tianming; Yang, Hong; Qian, Jiaming; Li, Jingnan

    2016-01-01

    Abstract The Asia-Pacific Colorectal Screening (APCS) score is a risk-stratification tool that helps predict the risk for advanced colorectal neoplasia (ACN) in asymptomatic Asian populations, but has not yet been assessed for its validity of use in Mainland China. The aim of the study was to assess the validity of APCS score in asymptomatic Chinese population, and to identify other risk factors associated with ACN. Asymptomatic subjects (N = 1010) who underwent colonoscopy screening between 2012 and 2014 in Beijing were enrolled. APCS scores based on questionnaires were used to stratify subjects into high, moderate, and average-risk tiers. Cochran–Armitage test for trend was used to assess the association between ACN and risk tiers. Univariate and multivariate logistic regression was performed with ACN as the outcome, adjusting for APCS score, body mass index, alcohol consumption, self-reported diabetes, and use of nonsteroidal anti-inflammatory drugs as independent variables. The average age was 53.5 (standard deviation 8.4) years. The prevalence of ACN was 4.1% overall, and in the high, moderate, and average-risk tiers, the prevalence was 8.8%, 2.83%, and 1.55%, respectively (P < 0.001). High-risk tier had 3.3 and 6.1-fold increased risk of ACN as compared with those in the moderate and average-risk tiers, respectively. In univariate analysis, high-risk tier, obesity, diabetes, and alcohol consumption were associated with ACN. In multivariate analysis, only high-risk tier was an independent predictor of ACN. The APCS score can effectively identify a subset of asymptomatic Chinese population at high risk for ACN. Further studies are required to identify other risk factors, and the acceptability of the score to the general population will need to be further examined. PMID:27741134

  13. 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.

  14. 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

  15. Systemic inflammatory status at baseline predicts bevacizumab benefit in advanced non-small cell lung cancer patients

    PubMed Central

    Botta, Cirino; Barbieri, Vito; Ciliberto, Domenico; Rossi, Antonio; Rocco, Danilo; Addeo, Raffaele; Staropoli, Nicoletta; Pastina, Pierpaolo; Marvaso, Giulia; Martellucci, Ignazio; Guglielmo, Annamaria; Pirtoli, Luigi; Sperlongano, Pasquale; Gridelli, Cesare; Caraglia, Michele; Tassone, Pierfrancesco; Tagliaferri, Pierosandro; Correale, Pierpaolo

    2013-01-01

    Bevacizumab is a humanized anti-VEGF monoclonal antibody able to produce clinical benefit in advanced non-squamous non-small-cell lung cancer (NSCLC) patients when combined to chemotherapy. At present, while there is a rising attention to bevacizumab-related adverse events and costs, no clinical or biological markers have been identified and validated for baseline patient selection. Preclinical findings suggest an important role for myeloid-derived inflammatory cells, such as neutrophils and monocytes, in the development of VEGF-independent angiogenesis. We conducted a retrospective analysis to investigate the role of peripheral blood cells count and of an inflammatory index, the neutrophil-to-lymphocyte ratio (NLR), as predictors of clinical outcome in NSCLC patients treated with bevacizumab plus chemotherapy. One hundred twelve NSCLC patients treated with chemotherapy ± bevacizumab were retrospectively evaluated for the predictive value of clinical or laboratory parameters correlated with inflammatory status. Univariate analysis revealed that a high number of circulating neutrophils and monocytes as well as a high NLR were associated with shorter progression-free survival (PFS) and overall survival (OS) in bevacizumab-treated patients only. We have thus developed a model based on the absence or the presence of at least one of the above-mentioned inflammatory parameters. We found that the absence of all variables strongly correlated with longer PFS and OS (9.0 vs. 7.0 mo, HR: 0.39, p = 0.002; and 20.0 vs. 12.0 mo, HR: 0.29, p < 0.001 respectively) only in NSCLC patients treated with bevacizumab plus chemotherapy. Our results suggest that a baseline systemic inflammatory status is marker of resistance to bevacizumab treatment in NSCLC patients. PMID:23760488

  16. 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

  17. 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.

  18. Towards advanced study of Active Galactic Nuclei with visible light adaptive optics

    NASA Astrophysics Data System (ADS)

    Ammons, Stephen Mark

    It is thought that the immense energies associated with accretion of matter onto black holes in Active Galactic Nuclei (AGN) and Quasi-Stellar Objects (QSOs) may "feedback," via intense photon flux or outward motion of gas, and affect certain properties of the host galaxy. In particular, AGN feedback may contribute to "quenching," or ceasing, of star formation by the expulsion or heating of cold gas, causing the host galaxy to evolve onto the red sequence (e.g., Di Matteo et al. 2005, Hopkins et al. 2006). I probe for the effects of feedback on the stellar populations of 60 X-ray-selected AGN hosts at a redshift of 1 in the Great Observatories Origins Deep Survey (GOODS) Southern field. Combining high spatial resolution optical imaging from the Hubble Space Telescope Advanced Camera for Surveys (HST ACS), and high spatial resolution near infrared data from Keck Laser Guide Star Adaptive Optics (AO) and HST Near-Infrared Camera and Multi-Object Spectrograph (NICMOS), I test for the presence of young stars on sub-kiloparsec scales, independent of dust extinction. Testing for correlations between near-ultraviolet/optical ( NUV- R ) colors and gradients and X-ray parameters such as hardness ratio and luminosity reveals new information about the nature of AGN-driven feedback. These AGN hosts display color gradients in rest-frame NUV - R as far inward as ~400 pc, suggesting stellar mixtures with nonuniform age distributions. There is little (< 0.3 mags) difference between the NUV - R gradients of the obscured (hard in X-ray) sources and the unobscured (soft in X-ray) sources, suggesting that the unobscured sources are not increasingly quenched of star formation. I compare the NUV - R colors of spiral galaxies that host AGN to non-active spirals, finding similar color gradients, but redder colors. These observations support the notion that unobscured intermediate-luminosity AGN hosts do not appear to be increasingly quenched of star formation relative to obscured sources

  19. 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

  20. 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.

  1. 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).

  2. The Updated Solar Activity Prediction during the MAVEN Mission, but Should We Believe It?

    NASA Technical Reports Server (NTRS)

    Chamberlin, Philip

    2009-01-01

    Mars atmospheric processes are very dependent not only on the absolute level of the solar irradiance but also the changes in solar irradiance. Correlated with many of these irradiance changes, especially during solar flares, are large particle events called coronal mass ejections that themselves significantly drive processes in the Martian atmosphere. The NOAA Space Weather Prediction Center has issued a consensus solar cycle activity prediction for the upcoming solar cycle 24 maximum, and this maximum period of solar activity will be during the prime MAVEN science mission. This 'consensus' prediction calls for lower activity than the previous solar cycle maximum that occurred during the years 2001-2002, but looking at the wide spread of peer-reviewed predictions there is little faith that can be taken in any one prediction. This drives the importance of real-time measurements from the LPW/EUV diodes and the measurement and modeling results that will be improved upon using results from the Solar Dynamics Observatory (SDO).

  3. 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

  4. 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

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

    PubMed

    Tian, Long; Pan, Bing

    2016-01-01

    An advanced video deflectometer using actively illuminated LED targets is proposed for remote, real-time measurement of bridge deflection. The system configuration, fundamental principles, and measuring procedures of the video deflectometer are first described. To address the challenge of remote and accurate deflection measurement of large engineering structures without being affected by ambient light, the novel idea of active imaging, which combines high-brightness monochromatic LED targets with coupled bandpass filter imaging, is introduced. Then, to examine the measurement accuracy of the proposed advanced video deflectometer in outdoor environments, vertical motions of an LED target with precisely-controlled translations were measured and compared with prescribed values. Finally, by tracking six LED targets mounted on the bridge, the developed video deflectometer was applied for field, remote, and multipoint deflection measurement of the Wuhan Yangtze River Bridge, one of the most prestigious and most publicized constructions in China, during its routine safety evaluation tests. Since the proposed video deflectometer using actively illuminated LED targets offers prominent merits of remote, contactless, real-time, and multipoint deflection measurement with strong robustness against ambient light changes, it has great potential in the routine safety evaluation of various bridges and other large-scale engineering structures. PMID:27563901

  6. 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

  7. 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.

  8. 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

  9. Population activity in the human dorsal pathway predicts the accuracy of visual motion detection.

    PubMed

    Donner, Tobias H; Siegel, Markus; Oostenveld, Robert; Fries, Pascal; Bauer, Markus; Engel, Andreas K

    2007-07-01

    A person's ability to detect a weak visual target stimulus varies from one viewing to the next. We tested whether the trial-to-trial fluctuations of neural population activity in the human brain are related to the fluctuations of behavioral performance in a "yes-no" visual motion-detection task. We recorded neural population activity with whole head magnetoencephalography (MEG) while subjects searched for a weak coherent motion signal embedded in spatiotemporal noise. We found that, during motion viewing, MEG activity in the 12- to 24-Hz ("beta") frequency range is higher, on average, before correct behavioral choices than before errors and that it predicts correct choices on a trial-by-trial basis. This performance-predictive activity is not evident in the prestimulus baseline and builds up slowly after stimulus onset. Source reconstruction revealed that the performance-predictive activity is expressed in the posterior parietal and dorsolateral prefrontal cortices and, less strongly, in the visual motion-sensitive area MT+. The 12- to 24-Hz activity in these key stages of the human dorsal visual pathway is correlated with behavioral choice in both target-present and target-absent conditions. Importantly, in the absence of the target, 12- to 24-Hz activity tends to be higher before "no" choices ("correct rejects") than before "yes" choices ("false alarms"). It thus predicts the accuracy, and not the content, of subjects' upcoming perceptual reports. We conclude that beta band activity in the human dorsal visual pathway indexes, and potentially controls, the efficiency of neural computations underlying simple perceptual decisions.

  10. 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

  11. 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

  12. 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.

  13. k-Nearest neighbour local linear prediction of scalp EEG activity during intermittent photic stimulation.

    PubMed

    Erla, Silvia; Faes, Luca; Tranquillini, Enzo; Orrico, Daniele; Nollo, Giandomenico

    2011-05-01

    The characterization of the EEG response to photic stimulation (PS) is an important issue with significant clinical relevance. This study aims to quantify and map the complexity of the EEG during PS, where complexity is measured as the degree of unpredictability resulting from local linear prediction. EEG activity was recorded with eyes closed (EC) and eyes open (EO) during resting and PS at 5, 10, and 15 Hz in a group of 30 healthy subjects and in a case-report of a patient suffering from cerebral ischemia. The mean squared prediction error (MSPE) resulting from k-nearest neighbour local linear prediction was calculated in each condition as an index of EEG unpredictability. The linear or nonlinear nature of the system underlying EEG activity was evaluated quantifying MSPE as a function of the neighbourhood size during local linear prediction, and by surrogate data analysis as well. Unpredictability maps were obtained for each subject interpolating MSPE values over a schematic head representation. Results on healthy subjects evidenced: (i) the prevalence of linear mechanisms in the generation of EEG dynamics, (ii) the lower predictability of EO EEG, (iii) the desynchronization of oscillatory mechanisms during PS leading to increased EEG complexity, (iv) the entrainment of alpha rhythm during EC obtained by 10 Hz PS, and (v) differences of EEG predictability among different scalp regions. Ischemic patient showed different MSPE values in healthy and damaged regions. The EEG predictability decreased moving from the early acute stage to a stage of partial recovery. These results suggest that nonlinear prediction can be a useful tool to characterize EEG dynamics during PS protocols, and may consequently constitute a complement of quantitative EEG analysis in clinical applications. PMID:21216649

  14. Development and Validation of a Model to Predict Aerosol Breathing Zone Concentrations During Common Outdoor Activities

    EPA Science Inventory

    Research has been conducted on aerosol emission rates during various activities as well as aerosol transport into the breathing zone under idealized conditions. However, there has been little effort to link the two into a model for predicting a person’s breathing zone concentrat...

  15. 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.

  16. 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…

  17. 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.…

  18. 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

  19. 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…

  20. 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

  1. Correlates of reward-predictive value in learning-related hippocampal neural activity

    PubMed Central

    Okatan, Murat

    2009-01-01

    Temporal difference learning (TD) is a popular algorithm in machine learning. Two learning signals that are derived from this algorithm, the predictive value and the prediction error, have been shown to explain changes in neural activity and behavior during learning across species. Here, the predictive value signal is used to explain the time course of learning-related changes in the activity of hippocampal neurons in monkeys performing an associative learning task. The TD algorithm serves as the centerpiece of a joint probability model for the learning-related neural activity and the behavioral responses recorded during the task. The neural component of the model consists of spiking neurons that compete and learn the reward-predictive value of task-relevant input signals. The predictive-value signaled by these neurons influences the behavioral response generated by a stochastic decision stage, which constitutes the behavioral component of the model. It is shown that the time course of the changes in neural activity and behavioral performance generated by the model exhibits key features of the experimental data. The results suggest that information about correct associations may be expressed in the hippocampus before it is detected in the behavior of a subject. In this way, the hippocampus may be among the earliest brain areas to express learning and drive the behavioral changes associated with learning. Correlates of reward-predictive value may be expressed in the hippocampus through rate remapping within spatial memory representations, they may represent reward-related aspects of a declarative or explicit relational memory representation of task contingencies, or they may correspond to reward-related components of episodic memory representations. These potential functions are discussed in connection with hippocampal cell assembly sequences and their reverse reactivation during the awake state. The results provide further support for the proposal that neural

  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. 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.

  4. Early functional magnetic resonance imaging activations predict language outcome after stroke.

    PubMed

    Saur, Dorothee; Ronneberger, Olaf; Kümmerer, Dorothee; Mader, Irina; Weiller, Cornelius; Klöppel, Stefan

    2010-04-01

    An accurate prediction of system-specific recovery after stroke is essential to provide rehabilitation therapy based on the individual needs. We explored the usefulness of functional magnetic resonance imaging scans from an auditory language comprehension experiment to predict individual language recovery in 21 aphasic stroke patients. Subjects with an at least moderate language impairment received extensive language testing 2 weeks and 6 months after left-hemispheric stroke. A multivariate machine learning technique was used to predict language outcome 6 months after stroke. In addition, we aimed to predict the degree of language improvement over 6 months. 76% of patients were correctly separated into those with good and bad language performance 6 months after stroke when based on functional magnetic resonance imaging data from language relevant areas. Accuracy further improved (86% correct assignments) when age and language score were entered alongside functional magnetic resonance imaging data into the fully automatic classifier. A similar accuracy was reached when predicting the degree of language improvement based on imaging, age and language performance. No prediction better than chance level was achieved when exploring the usefulness of diffusion weighted imaging as well as functional magnetic resonance imaging acquired two days after stroke. This study demonstrates the high potential of current machine learning techniques to predict system-specific clinical outcome even for a disease as heterogeneous as stroke. Best prediction of language recovery is achieved when the brain activation potential after system-specific stimulation is assessed in the second week post stroke. More intensive early rehabilitation could be provided for those with a predicted poor recovery and the extension to other systems, for example, motor and attention seems feasible. PMID:20299389

  5. Neural activity to a partner's facial expression predicts self-regulation after conflict

    PubMed Central

    Hooker, Christine I.; Gyurak, Anett; Verosky, Sara; Miyakawa, Asako; Ayduk, Özlem

    2009-01-01

    Introduction Failure to self-regulate after an interpersonal conflict can result in persistent negative mood and maladaptive behaviors. Research indicates that lateral prefrontal cortex (LPFC) activity is related to the regulation of emotional experience in response to lab-based affective challenges, such as viewing emotional pictures. This suggests that compromised LPFC function may be a risk-factor for mood and behavior problems after an interpersonal stressor. However, it remains unclear whether LPFC activity to a lab-based affective challenge predicts self-regulation in real-life. Method We investigated whether LPFC activity to a lab-based affective challenge (negative facial expressions of a partner) predicts self-regulation after a real-life affective challenge (interpersonal conflict). During an fMRI scan, healthy, adult participants in committed, dating relationships (N = 27) viewed positive, negative, and neutral facial expressions of their partners. In an online daily-diary, participants reported conflict occurrence, level of negative mood, rumination, and substance-use. Results LPFC activity in response to the lab-based affective challenge predicted self-regulation after an interpersonal conflict in daily life. When there was no interpersonal conflict, LPFC activity was not related to the change in mood or behavior the next day. However, when an interpersonal conflict did occur, ventral LPFC (VLPFC) activity predicted the change in mood and behavior the next day, such that lower VLPFC activity was related to higher levels of negative mood, rumination, and substance-use. Conclusions Low LPFC function may be a vulnerability and high LPFC function may be a protective factor for the development of mood and behavior problems after an interpersonal stressor. PMID:20004365

  6. Individual Differences in Crossmodal Brain Activity Predict Arcuate Fasciculus Connectivity in Developing Readers

    PubMed Central

    Gullick, Margaret M.; Booth, James R.

    2016-01-01

    Crossmodal integration of auditory and visual information, such as phonemes and graphemes, is a critical skill for fluent reading. Previous work has demonstrated that white matter connectivity along the arcuate fasciculus (AF) is predicted by reading skill and that crossmodal processing particularly activates the posterior STS (pSTS). However, the relationship between this crossmodal activation and white matter integrity has not been previously reported. We investigated the interrelationship of crossmodal integration, both in terms of behavioral performance and pSTS activity, with AF tract coherence using a rhyme judgment task in a group of 47 children with a range of reading abilities. We demonstrate that both response accuracy and pSTS activity for crossmodal (auditory–visual) rhyme judgments was predictive of fractional anisotropy along the left AF. Unimodal (auditory-only or visual-only) pSTS activity was not significantly related to AF connectivity. Furthermore, activity in other reading-related ROIs did not show the same AV-only AF coherence relationship, and AV pSTS activity was not related to connectivity along other language-related tracts. This study is the first to directly show that crossmodal brain activity is specifically related to connectivity in the AF, supporting its role in phoneme–grapheme integration ability. More generally, this study helps to define an interdependent neural network for reading-related integration. PMID:24456399

  7. 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

  8. Dynamics of Population Activity in Rat Sensory Cortex: Network Correlations Predict Anatomical Arrangement and Information Content.

    PubMed

    Sabri, Mohammad Mahdi; Adibi, Mehdi; Arabzadeh, Ehsan

    2016-01-01

    To study the spatiotemporal dynamics of neural activity in a cortical population, we implanted a 10 × 10 microelectrode array in the vibrissal cortex of urethane-anesthetized rats. We recorded spontaneous neuronal activity as well as activity evoked in response to sustained and brief sensory stimulation. To quantify the temporal dynamics of activity, we computed the probability distribution function (PDF) of spiking on one electrode given the observation of a spike on another. The spike-triggered PDFs quantified the strength, temporal delay, and temporal precision of correlated activity across electrodes. Nearby cells showed higher levels of correlation at short delays, whereas distant cells showed lower levels of correlation, which tended to occur at longer delays. We found that functional space built based on the strength of pairwise correlations predicted the anatomical arrangement of electrodes. Moreover, the correlation profile of electrode pairs during spontaneous activity predicted the "signal" and "noise" correlations during sensory stimulation. Finally, mutual information analyses revealed that neurons with stronger correlations to the network during spontaneous activity, conveyed higher information about the sensory stimuli in their evoked response. Given the 400-μm-distance between adjacent electrodes, our functional quantifications unravel the spatiotemporal dynamics of activity among nearby and distant cortical columns. PMID:27458347

  9. 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

  10. 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

  11. 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

  12. Cytochrome P450 2D6 Activity Predicts Discontinuation of Tamoxifen Therapy in Breast Cancer Patients

    PubMed Central

    Rae, James M.; Sikora, Matthew J.; Henry, N. Lynn; Li, Lang; Kim, Seongho; Oesterreich, Steffi; Skaar, Todd; Nguyen, Anne T.; Desta, Zeruesenay; Storniolo, Anna Maria; Flockhart, David A.; Hayes, Daniel F.; Stearns, Vered

    2009-01-01

    The selective estrogen receptor modulator tamoxifen is routinely used for treatment and prevention of estrogen receptor positive breast cancer. Studies of tamoxifen adherence suggest that over half of patients discontinue treatment before the recommended 5 years. We hypothesized that polymorphisms in CYP2D6, the enzyme responsible for tamoxifen activation, predict for tamoxifen discontinuation. Tamoxifen-treated women (n = 297) were genotyped for CYP2D6 variants and assigned a “score” based on predicted allele activities from 0 (no activity) to 2 (high activity). Correlation between CYP2D6 score and discontinuation rates at 4 months were tested. We observed a strong non-linear correlation between higher CYP2D6 score and increased rates of discontinuation (r2 = 0.935, p = 0.018). These data suggest that presence of active CYP2D6 alleles may predict for higher likelihood of tamoxifen discontinuation. Therefore, patients who may be most likely to benefit from tamoxifen may paradoxically be most likely to discontinue treatment prematurely. PMID:19421167

  13. PASS-Predicted Hepatoprotective Activity of Caesalpinia sappan in Thioacetamide-Induced Liver Fibrosis in Rats

    PubMed Central

    Kadir, Farkaad A.; Kassim, Normadiah M.; Abdulla, Mahmood Ameen; Ahmadipour, Fatemeh; Yehye, Wageeh A.

    2014-01-01

    The antifibrotic effects of traditional medicinal herb Caesalpinia sappan (CS) extract on liver fibrosis induced by thioacetamide (TAA) and the expression of transforming growth factor β1 (TGF-β1), α-smooth muscle actin (αSMA), and proliferating cell nuclear antigen (PCNA) in rats were studied. A computer-aided prediction of antioxidant and hepatoprotective activities was primarily performed with the Prediction Activity Spectra of the Substance (PASS) Program. Liver fibrosis was induced in male Sprague Dawley rats by TAA administration (0.03% w/v) in drinking water for a period of 12 weeks. Rats were divided into seven groups: control, TAA, Silymarin (SY), and CS 300 mg/kg body weight and 100 mg/kg groups. The effect of CS on liver fibrogenesis was determined by Masson's trichrome staining, immunohistochemical analysis, and western blotting. In vivo determination of hepatic antioxidant activities, cytochrome P450 2E1 (CYP2E1), and matrix metalloproteinases (MPPS) was employed. CS treatment had significantly increased hepatic antioxidant enzymes activity in the TAA-treated rats. Liver fibrosis was greatly alleviated in rats when treated with CS extract. CS treatment was noted to normalize the expression of TGF-β1, αSMA, PCNA, MMPs, and TIMP1 proteins. PASS-predicted plant activity could efficiently guide in selecting a promising pharmaceutical lead with high accuracy and required antioxidant and hepatoprotective properties. PMID:24701154

  14. U.S. Department of Energy -- Advanced Vehicle Testing Activity: Plug-in Hybrid Electric Vehicle Testing and Demonstration Activities

    SciTech Connect

    James E. Francfort; Donald Karner; John G. Smart

    2009-05-01

    The U.S. Department of Energy’s (DOE) Advanced Vehicle Testing Activity (AVTA) tests plug-in hybrid electric vehicles (PHEV) in closed track, dynamometer and onroad testing environments. The onroad testing includes the use of dedicated drivers on repeated urban and highway driving cycles that range from 10 to 200 miles, with recharging between each loop. Fleet demonstrations with onboard data collectors are also ongoing with PHEVs operating in several dozen states and Canadian Provinces, during which trips- and miles-per-charge, charging demand and energy profiles, and miles-per-gallon and miles-per-kilowatt-hour fuel use results are all documented, allowing an understanding of fuel use when vehicles are operated in charge depleting, charge sustaining, and mixed charge modes. The intent of the PHEV testing includes documenting the petroleum reduction potential of the PHEV concept, the infrastructure requirements, and operator recharging influences and profiles. As of May 2008, the AVTA has conducted track and dynamometer testing on six PHEV conversion models and fleet testing on 70 PHEVs representing nine PHEV conversion models. A total of 150 PHEVs will be in fleet testing by the end of 2008, all with onboard data loggers. The onroad testing to date has demonstrated 100+ miles per gallon results in mostly urban applications for approximately the first 40 miles of PHEV operations. The primary goal of the AVTA is to provide advanced technology vehicle performance benchmark data for technology modelers, research and development programs, and technology goal setters. The AVTA testing results also assist fleet managers in making informed vehicle purchase, deployment and operating decisions. The AVTA is part of DOE’s Vehicle Technologies Program. These AVTA testing activities are conducted by the Idaho National Laboratory and Electric Transportation Engineering Corporation, with Argonne National Laboratory providing dynamometer testing support. The proposed paper

  15. Variability of single trial brain activation predicts fluctuations in reaction time.

    PubMed

    Bender, Stephan; Banaschewski, Tobias; Roessner, Veit; Klein, Christoph; Rietschel, Marcella; Feige, Bernd; Brandeis, Daniel; Laucht, Manfred

    2015-03-01

    Brain activation stability is crucial to understanding attention lapses. EEG methods could provide excellent markers to assess neuronal response variability with respect to temporal (intertrial coherence) and spatial variability (topographic consistency) as well as variations in activation intensity (low frequency variability of single trial global field power). We calculated intertrial coherence, topographic consistency and low frequency amplitude variability during target P300 in a continuous performance test in 263 15-year-olds from a cohort with psychosocial and biological risk factors. Topographic consistency and low frequency amplitude variability predicted reaction time fluctuations (RTSD) in a linear model. Higher RTSD was only associated with higher psychosocial adversity in the presence of the homozygous 6R-10R dopamine transporter haplotype. We propose that topographic variability of single trial P300 reflects noise as well as variability in evoked cortical activation patterns. Dopaminergic neuromodulation interacted with environmental and biological risk factors to predict behavioural reaction time variability.

  16. Lateralized human hippocampal activity predicts navigation based on sequence or place memory

    PubMed Central

    Iglói, Kinga; Doeller, Christian F.; Berthoz, Alain; Rondi-Reig, Laure; Burgess, Neil

    2010-01-01

    The hippocampus is crucial for both spatial navigation and episodic memory, suggesting that it provides a common function to both. Here we adapt a spatial paradigm, developed for rodents, for use with functional MRI in humans to show that activation of the right hippocampus predicts the use of an allocentric spatial representation, and activation of the left hippocampus predicts the use of a sequential egocentric representation. Both representations can be identified in hippocampal activity before their effect on behavior at subsequent choice-points. Our results suggest that, rather than providing a single common function, the two hippocampi provide complementary representations for navigation, concerning places on the right and temporal sequences on the left, both of which likely contribute to different aspects of episodic memory. PMID:20660746

  17. Activated sludge pilot plant: comparison between experimental and predicted concentration profiles using three different modelling approaches.

    PubMed

    Le Moullec, Y; Potier, O; Gentric, C; Leclerc, J P

    2011-05-01

    This paper presents an experimental and numerical study of an activated sludge channel pilot plant. Concentration profiles of oxygen, COD, NO(3) and NH(4) have been measured for several operating conditions. These profiles have been compared to the simulated ones with three different modelling approaches, namely a systemic approach, CFD and compartmental modelling. For these three approaches, the kinetics model was the ASM-1 model (Henze et al., 2001). The three approaches allowed a reasonable simulation of all the concentration profiles except for ammonium for which the simulations results were far from the experimental ones. The analysis of the results showed that the role of the kinetics model is of primary importance for the prediction of activated sludge reactors performance. The fact that existing kinetics parameters in the literature have been determined by parametric optimisation using a systemic model limits the reliability of the prediction of local concentrations and of the local design of activated sludge reactors. PMID:21489593

  18. Can the theory of planned behaviour predict the physical activity behaviour of individuals?

    PubMed

    Hobbs, Nicola; Dixon, Diane; Johnston, Marie; Howie, Kate

    2013-01-01

    The theory of planned behaviour (TPB) can identify cognitions that predict differences in behaviour between individuals. However, it is not clear whether the TPB can predict the behaviour of an individual person. This study employs a series of n-of-1 studies and time series analyses to examine the ability of the TPB to predict physical activity (PA) behaviours of six individuals. Six n-of-1 studies were conducted, in which TPB cognitions and up to three PA behaviours (walking, gym workout and a personally defined PA) were measured twice daily for six weeks. Walking was measured by pedometer step count, gym attendance by self-report with objective validation of gym entry and the personally defined PA behaviour by self-report. Intra-individual variability in TPB cognitions and PA behaviour was observed in all participants. The TPB showed variable predictive utility within individuals and across behaviours. The TPB predicted at least one PA behaviour for five participants but had no predictive utility for one participant. Thus, n-of-1 designs and time series analyses can be used to test theory in an individual.

  19. Can the theory of planned behaviour predict the physical activity behaviour of individuals?

    PubMed

    Hobbs, Nicola; Dixon, Diane; Johnston, Marie; Howie, Kate

    2013-01-01

    The theory of planned behaviour (TPB) can identify cognitions that predict differences in behaviour between individuals. However, it is not clear whether the TPB can predict the behaviour of an individual person. This study employs a series of n-of-1 studies and time series analyses to examine the ability of the TPB to predict physical activity (PA) behaviours of six individuals. Six n-of-1 studies were conducted, in which TPB cognitions and up to three PA behaviours (walking, gym workout and a personally defined PA) were measured twice daily for six weeks. Walking was measured by pedometer step count, gym attendance by self-report with objective validation of gym entry and the personally defined PA behaviour by self-report. Intra-individual variability in TPB cognitions and PA behaviour was observed in all participants. The TPB showed variable predictive utility within individuals and across behaviours. The TPB predicted at least one PA behaviour for five participants but had no predictive utility for one participant. Thus, n-of-1 designs and time series analyses can be used to test theory in an individual. PMID:22943555

  20. Sound-Induced Activity in Voice-Sensitive Cortex Predicts Voice Memory Ability

    PubMed Central

    Watson, Rebecca; Latinus, Marianne; Bestelmeyer, Patricia E. G.; Crabbe, Frances; Belin, Pascal

    2012-01-01

    The “temporal voice areas” (TVAs; Belin et al., 2000) of the human brain show greater neuronal activity in response to human voices than to other categories of non-vocal sounds. However, a direct link between TVA activity and voice perception behavior has not yet been established. Here we show that a functional magnetic resonance imaging measure of activity in the TVAs predicts individual performance at a separately administered voice memory test. This relation holds when general sound memory ability is taken into account. These findings provide the first evidence that the TVAs are specifically involved in voice cognition. PMID:22485101

  1. Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership.

    PubMed

    Stang, Paul E; Ryan, Patrick B; Racoosin, Judith A; Overhage, J Marc; Hartzema, Abraham G; Reich, Christian; Welebob, Emily; Scarnecchia, Thomas; Woodcock, Janet

    2010-11-01

    The U.S. Food and Drug Administration (FDA) Amendments Act of 2007 mandated that the FDA develop a system for using automated health care data to identify risks of marketed drugs and other medical products. The Observational Medical Outcomes Partnership is a public-private partnership among the FDA, academia, data owners, and the pharmaceutical industry that is responding to the need to advance the science of active medical product safety surveillance by using existing observational databases. The Observational Medical Outcomes Partnership's transparent, open innovation approach is designed to systematically and empirically study critical governance, data resource, and methodological issues and their interrelationships in establishing a viable national program of active drug safety surveillance by using observational data. This article describes the governance structure, data-access model, methods-testing approach, and technology development of this effort, as well as the work that has been initiated.

  2. Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership.

    PubMed

    Stang, Paul E; Ryan, Patrick B; Racoosin, Judith A; Overhage, J Marc; Hartzema, Abraham G; Reich, Christian; Welebob, Emily; Scarnecchia, Thomas; Woodcock, Janet

    2010-11-01

    The U.S. Food and Drug Administration (FDA) Amendments Act of 2007 mandated that the FDA develop a system for using automated health care data to identify risks of marketed drugs and other medical products. The Observational Medical Outcomes Partnership is a public-private partnership among the FDA, academia, data owners, and the pharmaceutical industry that is responding to the need to advance the science of active medical product safety surveillance by using existing observational databases. The Observational Medical Outcomes Partnership's transparent, open innovation approach is designed to systematically and empirically study critical governance, data resource, and methodological issues and their interrelationships in establishing a viable national program of active drug safety surveillance by using observational data. This article describes the governance structure, data-access model, methods-testing approach, and technology development of this effort, as well as the work that has been initiated. PMID:21041580

  3. Low podoplanin expression in pretreatment biopsy material predicts poor prognosis in advanced-stage squamous cell carcinoma of the uterine cervix treated by primary radiation.

    PubMed

    Dumoff, Kimberly L; Chu, Christina S; Harris, Eleanor E; Holtz, David; Xu, Xiaowei; Zhang, Paul J; Acs, Geza

    2006-05-01

    Lymphatic invasion and nodal metastasis are predictors of poor outcome in cervix carcinoma. We have recently found that low podoplanin immunoreactivity in cervix carcinoma correlated with the presence of lymphatic invasion and nodal metastasis. In the current study, we examined whether podoplanin expression in pretreatment cervical biopsies can predict the presence lymphatic invasion, nodal metastasis, and outcome in advanced-stage tumors treated by nonsurgical means. Podoplanin expression was analyzed by immunohistochemistry in 48 cervical biopsies and corresponding hysterectomy specimens of early-stage invasive squamous cell carcinoma and in 74 pretreatment biopsies from advanced-stage tumors treated with primary radiation. We found a highly significant correlation between podoplanin expression obtained in biopsy and corresponding hysterectomy materials (r = 0.8962, P < 0.0001). Low podoplanin expression showed a significant correlation with lymphatic invasion (P < 0.0001) and nodal metastasis (P = 0.0058). Low podoplanin expression in pretreatment biopsy material showed a significant correlation with poor disease-free (P = 0.0009) and overall (P = 0.0002) survival in advanced-stage tumors. Our results suggest that in advanced-stage cervix carcinomas treated by radiation, when traditional prognostic indicators are not available and treatment decisions are based on biopsy material and clinical staging parameters, examination of podoplanin expression in pretreatment biopsy material may be a useful marker to predict lymphatic metastasis and patient outcome. Prospective studies involving larger numbers of patients are needed to further evaluate the clinical utility of examination of podoplanin expression in patients with cervix carcinoma.

  4. Predicting passive and active tissue:plasma partition coefficients: interindividual and interspecies variability.

    PubMed

    Ruark, Christopher D; Hack, C Eric; Robinson, Peter J; Mahle, Deirdre A; Gearhart, Jeffery M

    2014-07-01

    A mechanistic tissue composition model incorporating passive and active transport for the prediction of steady-state tissue:plasma partition coefficients (K(t:pl)) of chemicals in multiple mammalian species was used to assess interindividual and interspecies variability. This approach predicts K(t:pl) using chemical lipophilicity, pKa, phospholipid membrane binding, and the unbound plasma fraction, together with tissue fractions of water, neutral lipids, neutral and acidic phospholipids, proteins, and pH. Active transport K(t:pl) is predicted using Michaelis-Menten transport parameters. Species-specific biological properties were identified from 126 peer reviewed journal articles, listed in the Supporting Information, for mouse, rat, guinea pig, rabbit, beagle dog, pig, monkey, and human species. Means and coefficients of variation for biological properties were used in a Monte Carlo analysis to assess variability. The results show K(t:pl) interspecies variability for the brain, fat, heart, kidney, liver, lung, muscle, red blood cell, skin, and spleen, but uncertainty in the estimates obscured some differences. Compounds undergoing active transport are shown to have concentration-dependent K(t:pl). This tissue composition-based mechanistic model can be used to predict K(t:pl) for organic chemicals across eight species and 10 tissues, and can be an important component in drug development when scaling K(t:pl) from animal models to humans.

  5. Accurate similarity index based on activity and connectivity of node for link prediction

    NASA Astrophysics Data System (ADS)

    Li, Longjie; Qian, Lvjian; Wang, Xiaoping; Luo, Shishun; Chen, Xiaoyun

    2015-05-01

    Recent years have witnessed the increasing of available network data; however, much of those data is incomplete. Link prediction, which can find the missing links of a network, plays an important role in the research and analysis of complex networks. Based on the assumption that two unconnected nodes which are highly similar are very likely to have an interaction, most of the existing algorithms solve the link prediction problem by computing nodes' similarities. The fundamental requirement of those algorithms is accurate and effective similarity indices. In this paper, we propose a new similarity index, namely similarity based on activity and connectivity (SAC), which performs link prediction more accurately. To compute the similarity between two nodes, this index employs the average activity of these two nodes in their common neighborhood and the connectivities between them and their common neighbors. The higher the average activity is and the stronger the connectivities are, the more similar the two nodes are. The proposed index not only commendably distinguishes the contributions of paths but also incorporates the influence of endpoints. Therefore, it can achieve a better predicting result. To verify the performance of SAC, we conduct experiments on 10 real-world networks. Experimental results demonstrate that SAC outperforms the compared baselines.

  6. Activity Prediction and Molecular Mechanism of Bovine Blood Derived Angiotensin I-Converting Enzyme Inhibitory Peptides

    PubMed Central

    Zhang, Ting; Nie, Shaoping; Liu, Boqun; Yu, Yiding; Zhang, Yan; Liu, Jingbo

    2015-01-01

    Development of angiotensin I-converting enzyme (ACE, EC 3.4.15.1) inhibitory peptides from food protein is under extensive research as alternative for the prevention of hypertension. However, it is difficult to identify peptides released from food sources. To accelerate the progress of peptide identification, a three layer back propagation neural network model was established to predict the ACE-inhibitory activity of pentapeptides derived from bovine hemoglobin by simulated enzyme digestion. The pentapeptide WTQRF has the best predicted value with experimental IC50 23.93 μM. The potential molecular mechanism of the WTQRF / ACE interaction was investigated by flexible docking. PMID:25768442

  7. Activity prediction and molecular mechanism of bovine blood derived angiotensin I-converting enzyme inhibitory peptides.

    PubMed

    Zhang, Ting; Nie, Shaoping; Liu, Boqun; Yu, Yiding; Zhang, Yan; Liu, Jingbo

    2015-01-01

    Development of angiotensin I-converting enzyme (ACE, EC 3.4.15.1) inhibitory peptides from food protein is under extensive research as alternative for the prevention of hypertension. However, it is difficult to identify peptides released from food sources. To accelerate the progress of peptide identification, a three layer back propagation neural network model was established to predict the ACE-inhibitory activity of pentapeptides derived from bovine hemoglobin by simulated enzyme digestion. The pentapeptide WTQRF has the best predicted value with experimental IC50 23.93 μM. The potential molecular mechanism of the WTQRF / ACE interaction was investigated by flexible docking. PMID:25768442

  8. The role of pleasantness and activation-based well-being in performance prediction.

    PubMed

    Wright, T A; Bonett, D G

    1997-07-01

    This study examined the relationships between 2 measures of psychological well-being and work performance using the circumplex model of emotion as the theoretical framework. Although the pleasantness-based measure of well-being predicted subsequent work performance, the results failed to establish a relationship between the activation-based measure of well-being and work performance. Future directions and implications of the findings regarding the further refinement of the role of psychological well-being in performance prediction are introduced. PMID:9552291

  9. 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

  10. Adaptability and Prediction of Anticipatory Muscular Activity Parameters to Different Movements in the Sitting Position.

    PubMed

    Chikh, Soufien; Watelain, Eric; Faupin, Arnaud; Pinti, Antonio; Jarraya, Mohamed; Garnier, Cyril

    2016-08-01

    Voluntary movement often causes postural perturbation that requires an anticipatory postural adjustment to minimize perturbation and increase the efficiency and coordination during execution. This systematic review focuses specifically on the relationship between the parameters of anticipatory muscular activities and movement finality in sitting position among adults, to study the adaptability and predictability of anticipatory muscular activities parameters to different movements and conditions in sitting position in adults. A systematic literature search was performed using PubMed, Science Direct, Web of Science, Springer-Link, Engineering Village, and EbscoHost. Inclusion and exclusion criteria were applied to retain the most rigorous and specific studies, yielding 76 articles, Seventeen articles were excluded at first reading, and after the application of inclusion and exclusion criteria, 23 were retained. In a sitting position, central nervous system activity precedes movement by diverse anticipatory muscular activities and shows the ability to adapt anticipatory muscular activity parameters to the movement direction, postural stability, or charge weight. In addition, these parameters could be adapted to the speed of execution, as found for the standing position. Parameters of anticipatory muscular activities (duration, order, and amplitude of muscle contractions constituting the anticipatory muscular activity) could be used as a predictive indicator of forthcoming movement. In addition, this systematic review may improve methodology in empirical studies and assistive technology for people with disabilities. PMID:27440765

  11. Predicting anti-HIV activity of TIBO derivatives: a computational approach using a novel topological descriptor.

    PubMed

    Sardana, Satish; Madan, Anil Kumar

    2002-08-01

    A novel highly discriminating adjacency-cum-distance-based topological descriptor, termed the adjacent eccentric distance sum index, has been conceptualized and its discriminating power investigated with regard to the anti-HIV activity of 4,5,6,7-tetrahydro-imidazo-[4,5,1- jk] [1,4] benzodiazepin-2 (1 H)-one (TIBO) derivatives. The discriminating power of the adjacent eccentric distance sum index was compared with that of the eccentric connectivity index - another adjacency-cum-distance-based topological descriptor. The values of the eccentric connectivity index and the adjacent eccentric distance sum index of each of 121 analogues comprising the data set were computed and active ranges were identified. Subsequently, a biological activity was assigned to each analogue involved in the data set and this was then compared with the reported anti-HIV activity. Excellent correlations were observed between anti-HIV activity and both the topological descriptors. Although the overall accuracy of prediction was found to be approximately 84% in case of the eccentric connectivity index and approximately 86% in case of adjacent eccentric distance sum index, the predictability using the adjacent eccentric distance sum index in the active range itself was >92%. The proposed index offers a vast potential for structure-activity/property studies.

  12. Adaptability and Prediction of Anticipatory Muscular Activity Parameters to Different Movements in the Sitting Position.

    PubMed

    Chikh, Soufien; Watelain, Eric; Faupin, Arnaud; Pinti, Antonio; Jarraya, Mohamed; Garnier, Cyril

    2016-08-01

    Voluntary movement often causes postural perturbation that requires an anticipatory postural adjustment to minimize perturbation and increase the efficiency and coordination during execution. This systematic review focuses specifically on the relationship between the parameters of anticipatory muscular activities and movement finality in sitting position among adults, to study the adaptability and predictability of anticipatory muscular activities parameters to different movements and conditions in sitting position in adults. A systematic literature search was performed using PubMed, Science Direct, Web of Science, Springer-Link, Engineering Village, and EbscoHost. Inclusion and exclusion criteria were applied to retain the most rigorous and specific studies, yielding 76 articles, Seventeen articles were excluded at first reading, and after the application of inclusion and exclusion criteria, 23 were retained. In a sitting position, central nervous system activity precedes movement by diverse anticipatory muscular activities and shows the ability to adapt anticipatory muscular activity parameters to the movement direction, postural stability, or charge weight. In addition, these parameters could be adapted to the speed of execution, as found for the standing position. Parameters of anticipatory muscular activities (duration, order, and amplitude of muscle contractions constituting the anticipatory muscular activity) could be used as a predictive indicator of forthcoming movement. In addition, this systematic review may improve methodology in empirical studies and assistive technology for people with disabilities.

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

    PubMed

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

    2006-10-01

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

  14. Intraseasonal Tropical Storm Activity Prediction with the NCEP CFSv2 45-day Forecasts

    NASA Astrophysics Data System (ADS)

    Schemm, J. K. E.; Long, L. N.

    2015-12-01

    Global predictability of intraseasonal tropical storm (TS) activity is assessed using the 1999-2012 CFSv2 45-day hindcast suite and real-time predictions for 2014-2015. Weekly TS activities in the CFSv2 45-day forecasts were determined using the TS detection and tracking method devised by Carmago and Zebiak (2002). The forecast periods are divided into weekly intervals for Week 1 through Week 4. The TS activities in those intervals are compared to the observed activities based on the NHC HURDAT and JTWC Best Track datasets.The CFSv2 45-day hindcast suite is made of forecast runs initialized at 00, 06, 12 and 18Z every day during the 1999 - 2012 period. For predictability evaluation, forecast TS activities are analyzed based on 20-member ensemble forecasts comprised of 45-day runs made during the most recent 5 days prior to the verification period. The forecast TS activities are evaluated in terms of the number of storms, genesis locations and storm tracks during the weekly periods. The CFSv2 forecasts are shown to have a fair level of skill in predicting the anomalous number of storms over most of the seven ocean basins during the 1999-2012 active seasons. The average temporal correlation score for Week 1 forecasts is between 0.50-0.52 in the Eastern and Western North Pacific, the South Indian and South Pacific basins, while correlations drop to around 0.20 for Week 4 forecasts. The forecast track is also examined using density distribution maps and false alarm statistics compiled using the hindcast analyses with Heidke Skill Scores peaking at around 0.35. Real-time weekly TS activity predictions began in December 2013 using the climatological TS forecast statistics to make the model bias corrections in terms of the storm counts, track distribution and removal of false alarm storms. This operational implementation provides an objective tool for the CPC's Global Tropical Hazards Outlooks. Verification and evaluation of the 2014 and 2015 seasons will be discussed.

  15. A comparison of the activity profile and physiological demands between advanced and recreational veteran tennis players.

    PubMed

    Fernandez-Fernandez, Jaime; Sanz-Rivas, David; Sanchez-Muñoz, Cristobal; Pluim, Babette M; Tiemessen, Ivo; Mendez-Villanueva, Alberto

    2009-03-01

    The aim of the study was to examine whether differences in playing level influence the activity profile and physiological demands of advanced and recreational veteran men's tennis players during an hour of tennis match play. Ten advanced (International Tennis Number [ITN] 3-5, 45.3 +/- 5.1 years) and 10 recreational (ITN 7-9, 44.8 +/- 4.7 years) veteran men's tennis players participated in 4 experimental sessions: (1) an ITN on-court assessment, (2) a laboratory incremental treadmill test, (3) an hour of simulated tennis match play, and (4) 30 minutes of tennis match play using a portable gas analyzer. Subjects' VO2 and heart rate (HR) were recorded by portable analyzers. Moreover, energy expenditure was evaluated by indirect calorimetry. Temporal structure and distance covered were determined from video recordings. Subjects' VO2 (24.5 +/- 4.1 vs. 23.3 +/- 3 ml x kg x min), HR (148.3 +/- 11.5 vs. 149.8 +/- 8.4 bpm), duration of rallies (DR) (6.3 +/- 4.1 vs. 7.6 +/- 5.5 seconds), and effective playing time (EPT) (21.7 +/- 5.0 vs. 23.6 +/- 5.4%), HR (148.3 +/- 11.5 vs. 149.8 +/- 8.4 bpm), and energy expenditure (263.1 +/- 49.4 and 281.3 +/- 61.8 kcal x min) during play did not differ significantly (p > 0.05) between advanced and recreational players. The advanced players covered significantly more meters than the recreational players during their 1-hour tennis matches (mean +/- SD: 3568.8 +/- 532.2 vs. 3173.8 +/- 226 m, p < 0.01) at lower running speeds. The results indicate that, independently of ability, tennis match play satisfies the American College of Sports Medicine recommendations for quantity and quality of exercise for the development and maintenance of cardiovascular fitness in healthy adults and seems to be a viable and highly popular mode of healthy activity.

  16. Lateral prefrontal cortex activity during cognitive control of emotion predicts response to social stress in schizophrenia.

    PubMed

    Tully, Laura M; Lincoln, Sarah Hope; Hooker, Christine I

    2014-01-01

    LPFC dysfunction is a well-established neural impairment in schizophrenia and is associated with worse symptoms. However, how LPFC activation influences symptoms is unclear. Previous findings in healthy individuals demonstrate that lateral prefrontal cortex (LPFC) activation during cognitive control of emotional information predicts mood and behavior in response to interpersonal conflict, thus impairments in these processes may contribute to symptom exacerbation in schizophrenia. We investigated whether schizophrenia participants show LPFC deficits during cognitive control of emotional information, and whether these LPFC deficits prospectively predict changes in mood and symptoms following real-world interpersonal conflict. During fMRI, 23 individuals with schizophrenia or schizoaffective disorder and 24 healthy controls completed the Multi-Source Interference Task superimposed on neutral and negative pictures. Afterwards, schizophrenia participants completed a 21-day online daily-diary in which they rated the extent to which they experienced mood and schizophrenia-spectrum symptoms, as well as the occurrence and response to interpersonal conflict. Schizophrenia participants had lower dorsal LPFC activity (BA9) during cognitive control of task-irrelevant negative emotional information. Within schizophrenia participants, DLPFC activity during cognitive control of emotional information predicted changes in positive and negative mood on days following highly distressing interpersonal conflicts. Results have implications for understanding the specific role of LPFC in response to social stress in schizophrenia, and suggest that treatments targeting LPFC-mediated cognitive control of emotion could promote adaptive response to social stress in schizophrenia.

  17. Design and prediction of new acetylcholinesterase inhibitor via quantitative structure activity relationship of huprines derivatives.

    PubMed

    Zhang, Shuqun; Hou, Bo; Yang, Huaiyu; Zuo, Zhili

    2016-05-01

    Acetylcholinesterase (AChE) is an important enzyme in the pathogenesis of Alzheimer's disease (AD). Comparative quantitative structure-activity relationship (QSAR) analyses on some huprines inhibitors against AChE were carried out using comparative molecular field analysis (CoMFA), comparative molecular similarity indices analysis (CoMSIA), and hologram QSAR (HQSAR) methods. Three highly predictive QSAR models were constructed successfully based on the training set. The CoMFA, CoMSIA, and HQSAR models have values of r (2) = 0.988, q (2) = 0.757, ONC = 6; r (2) = 0.966, q (2) = 0.645, ONC = 5; and r (2) = 0.957, q (2) = 0.736, ONC = 6. The predictabilities were validated using an external test sets, and the predictive r (2) values obtained by the three models were 0.984, 0.973, and 0.783, respectively. The analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the AChE to further understand the vital interactions between huprines and the protease. On the basis of the QSAR study, 14 new potent molecules have been designed and six of them are predicted to be more active than the best active compound 24 described in the literature. The final QSAR models could be helpful in design and development of novel active AChE inhibitors.

  18. Predicting Outcome using Butyrylcholinesterase Activity in Organophosphorus Pesticide Self-Poisoning

    PubMed Central

    Eddleston, Michael; Eyer, Peter; Worek, Franz; Rezvi Sheriff, MH; Buckley, Nick A

    2008-01-01

    Background The usefulness of a low butyrylcholinesterase activity on admission for predicting severity in acute organophosphorus insecticide poisoning has long been debated. Previous studies have been confounded by the inclusion of multiple insecticides with differing inhibitory kinetics. Aim We aimed to assess the usefulness of admission butyrylcholinesterase activity, together with plasma organophosphorus concentration, for predicting death with identified organophosphorus insecticides. Design A prospective cohort of self-poisoned patients Methods We prospectively studied 91 and 208 patients with proven dimethoate or chlorpyrifos self-poisoning treated using a standard protocol. Plasma butyrylcholinesterase activity and organophosphorus concentration were measured on admission and clinical outcomes recorded. Results The usefulness of a plasma butyrylcholinesterase activity <600mU/ml on admission varied markedly - while highly sensitive in chlorpyrifos poisoning (sensitivity 11/11 deaths; 100%, 95%CI 71.5-100), its specificity was only 17.7% (95%CI 12.6-23.7). In contrast, while poorly sensitive for deaths in dimethoate poisoning (12/25 patients; 48%, 95%CI 27.9-68.7) it was reasonably specific (86.4%, 95%CI 75.7-93.6). A high organophosphorus concentration on admission was associated with worse outcome; however, a clear threshold concentration was only present for dimethoate poisoning. Conclusions Plasma butyrylcholinesterase activity on admission can provide useful information; however, it must be interpreted carefully. It can only be used to predict need for critical care and death when the insecticide ingested is known and its sensitivity and specificity for that insecticide has been studied. Plasma concentration of some organophosphorus insecticides predicts outcome. The development of rapid bedside tests for organophosphorus detection may aid early assessment of severity. PMID:18375477

  19. Using social cognitive theory to predict physical activity and fitness in underserved middle school children.

    PubMed

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

    2011-06-01

    Few researchers have used social cognitive theory and environment-based constructs to predict physical activity (PA) and fitness in underserved middle-school children. Hence, we evaluated social cognitive variables and perceptions of the school environment to predict PA and fitness in middle school children (N = 506, ages 10-14 years). Using multiple regression analyses we accounted for 12% of the variance in PA and 13-21% of the variance in fitness. The best predictors of PA were barrier self-efficacy, classmate social support, and gender; whereas, only gender predicted fitness. The results affirmed the importance of barrier self-efficacy and gender differences. Our findings regarding classmate social support are some of the first to illuminate the importance of school-specific peers in promoting PA.

  20. Prediction of the antiglycation activity of polysaccharides from Benincasa hispida using a response surface methodology.

    PubMed

    Jiang, Xiang; Kuang, Fei; Kong, Fansheng; Yan, Chunyan

    2016-10-20

    Benincasa hispida is a popular vegetable in China. Our previous experiments suggested that polysaccharides isolated from B. hispida fruits (PBH) have antiglycation effect and DPPH free radical scavenging activity. Ultrasonic treatments can be used to extract polysaccharides from Benincasa hispida (PBH). The aim of this study was to investigate the correlation between the ultrasonic treatment conditions and the antiglycation activity of PBH. A mathematical model was generated with an artificial neural network (ANN) toolbox from MATLAB to analyze the effects of ultrasonic treatment conditions on antiglycation activity. The response surface plots showed relationships between ultrasonic extraction conditions and bioactivity. The R(2) value of the model was 0.9919, which suggested good fitness of the neural network. The application of genetic algorithms showed that the optimal ultrasonic extraction conditions resulted in the highest antiglycation activity for PBH. These were 150W, 46°C, and 35min. These conditions produced a predicted antiglycation activity of 41.2%; the actual activity was 40.9% under optimal conditions. This is very close to the predicted value. The experimental data indicated that the PBH possessed both antiglycation and antioxidant activities. The maximum actual value of antiglycation was 101.7% that of the positive control, and the PBH inhibited the DPPH free radicals with an EC50 value of 0.98mg/mL. This is 66.2% that of ascorbic acid. These results explained the observations that B. hispida can decrease glucose levels in diabetic patients. The experimental results also showed that the ANN could be used for optimization and prediction. PMID:27474577

  1. Energy expenditure in children predicted from heart rate and activity calibrated against respiration calorimetry.

    PubMed

    Treuth, M S; Adolph, A L; Butte, N F

    1998-07-01

    The purpose of this study was to predict energy expenditure (EE) from heart rate (HR) and activity calibrated against 24-h respiration calorimetry in 20 children. HR, oxygen consumption (VO2), carbon dioxide production (VCO2), and EE were measured during rest, sleep, exercise, and over 24 h by room respiration calorimetry on two separate occasions. Activity was monitored by a leg vibration sensor. The calibration day (day 1) consisted of specified behaviors categorized as inactive (lying, sitting, standing) or active (two bicycle sessions). On the validation day (day 2), the child selected activities. Separate regression equations for VO2, VCO2, and EE for method 1 (combining awake and asleep using HR, HR2, and HR3), method 2 (separating awake and asleep), and method 3 (separating awake into active and inactive, and combining activity and HR) were developed using the calibration data. For day 1, the errors were similar for 24-h VO2, VCO2, and EE among methods and also among HR, HR2, and HR3. The methods were validated using measured data from day 2. There were no significant differences in HR, VO2, VCO2, respiratory quotient, and EE values during rest, sleep, or over the 24 h between days 1 and 2. Applying the linear HR equations to day 2 data, the errors were the lowest with the combined HR/activity method (-2.6 +/- 5.2%, -4.1 +/- 5.9%, -2.9 +/- 5.1% for VO2, VCO2, and EE, respectively). To demonstrate the utility of the HR/activity method, HR and activity were monitored for 24 h at home (day 3). Free-living EE was predicted as 7,410 +/- 1,326 kJ/day. In conclusion, the combination of HR and activity is an acceptable method for determining EE not only for groups of children, but for individuals.

  2. Predicting trace organic compound attenuation with spectroscopic parameters in powdered activated carbon processes.

    PubMed

    Ziska, Austin D; Park, Minkyu; Anumol, Tarun; Snyder, Shane A

    2016-08-01

    The removal of trace organic compounds (TOrCs) is of growing interest in water research and society. Powdered activated carbon (PAC) has been proven to be an effective method of removal for TOrCs in water, with the degree of effectiveness depending on dosage, contact time, and activated carbon type. In this study, the attenuation of TOrCs in three different secondary wastewater effluents using four PAC materials was studied in order to elucidate the effectiveness and efficacy of PAC for TOrC removal. With the notable exception of hydrochlorothiazide, all 14 TOrC indicators tested in this study exhibited a positive correlation of removal rate with their log Dow values, demonstrating that the main adsorption mechanism was hydrophobic interaction. As a predictive model, the modified Chick-Watson model, often used for the prediction of microorganism inactivation by disinfectants, was applied. The applied model exhibited good predictive power for TOrC attenuation by PAC in wastewater. In addition, surrogate models based upon spectroscopic measurements including UV absorbance at 254 nm and total fluorescence were applied to predict TOrC removal by PAC. The surrogate model was found to provide an excellent prediction of TOrC attenuation for all combinations of water quality and PAC type included in this study. The success of spectrometric parameters as surrogates in predicting TOrC attenuation by PAC are particularly useful because of their potential application in real-time on-line sensor monitoring and process control at full-scale water treatment plants, which could lead to significantly reduced operator response times and PAC operational optimization. PMID:27174829

  3. IL-2-Activated Killer Cells and Native Cytokines in Treatment of Patients with Advanced Cancer.

    PubMed

    Ostanin, Alexander A.; Chernykh, Helena R.; Leplina, Olga Y.; Shevela, Ekaterina Ya.; Niconov, Sergey D.; Kozlov, Vladimir A.

    1997-12-01

    We evaluated the efficiency/tolerability of and the immunological changes induced by the adoptive immunotherapy (AIT) with IL-2-activated killer cells, and preparation of native cytokines from swine spleen (PSS) in treatment of 20 patients with advanced cancer (10 patients with primary lung cancer; 3 with metastatic melanoma; 2 with advanced neuroblastoma; 2 with ovarian cancer; renal cancer; gastric adenocarcinoma; and colorectal cancer). The partial/minor response of duration period 2-10 months was observed in 20% of patients. 2/4 patients, who underwent partial surgical tumor resection and following AIT course, sustained the event-free survival for more than 24 months. The response to the therapy was revealed in 4/10 patients with lung cancer, 2/2 patients with neuroblastoma, of whom each had ovarian and colorectal cancers. The evaluation of a dose of infused LAKcells as well as combined i.v./local (endobronchial or endoperitoneal) LAK administration were necessary to assure positive response in patients. The cytokine and/or side effects were moderate and the combined LAK-PSS infusions were generally well tolerated by the patients. The treatment was followed by activation of the patient immune system that included: (i) rebound in amount of peripheral blood lymphocytes; (ii) gain in amount of CD3(+) T cells and those CD4(+) helper/inducer; (iii) enchantment of lymphocyte proliferation and cytokine production (IL-2, IL-1, TNF-alpha). Being injected to patients in combination with LAK cells, cytokines related to PSS action and/or those, either exogenous or secondary, and released by in vitro and in vivo, activated lymphocytes and could cause the therapeutic effects.

  4. 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.

  5. Prediction of the applicability of active damping elements in high-precision machines

    NASA Astrophysics Data System (ADS)

    Holterman, Jan; de Vries, Theo J. A.

    2004-07-01

    The Smart Disc project at the Drebbel Institute of the University of Twente is aimed at the development of active structural elements for high-precision machines. The active elements consist of a piezoelectric position actuator and a collocated piezoelectric force sensor. As the actuators and sensors are collocated, the elements are especially suited for implementing robust active damping. The decision whether or not to incorporate active damping elements in a high-precision machine should ideally be made in an early design stage, i.e., at a time at which only limited knowledge of the vibration problem is available. Despite the uncertainties that may exist at that stage, one would like to be able to roughly predict the amount of damping that could possibly be obtained. For that reason, the present paper is concerned with the development of an analysis tool that may help in predicting the applicability of active damping elements in a mechanical structure of which only a rough model is available. Based on extensive simulations, several practical rules of thumb are given for the requirements for the mechanical structure and the active elements, in order to enable the realisation of relative damping values as high as 10%.

  6. Predicting physical activity and outcome expectations in cancer survivors: an application of Self-Determination Theory.

    PubMed

    Wilson, Philip M; Blanchard, Chris M; Nehl, Eric; Baker, Frank

    2006-07-01

    The purpose of this study was to examine the contributions of autonomous and controlled motives drawn from Self-Determination Theory (SDT; Intrinsic Motivation and Self-determination in Human Behavior. Plenum Press: New York, 1985; Handbook of Self-determination Research. University of Rochester Press: New York, 2002) towards predicting physical activity behaviours and outcome expectations in adult cancer survivors. Participants were cancer-survivors (N=220) and a non-cancer comparison cohort (N=220) who completed an adapted version of the Treatment Self-Regulation Questionnaire modified for physical activity behaviour (TSRQ-PA), an assessment of the number of minutes engaged in moderate-to-vigorous physical activity (MVPA) weekly, and the anticipated outcomes expected from regular physical activity (OE). Simultaneous multiple regression analyses indicated that autonomous motives was the dominant predictor of OEs across both cancer and non-cancer cohorts (R(2adj)=0.29-0.43), while MVPA was predicted by autonomous (beta's ranged from 0.21 to 0.34) and controlled (beta's ranged from -0.04 to -0.23) motives after controlling for demographic considerations. Cancer status (cancer versus no cancer) did not moderate the motivation-physical activity relationship. Collectively, these findings suggest that the distinction between autonomous and controlled motives is useful and compliments a growing body of evidence supporting SDT as a framework for understanding motivational processes in physical activity contexts with cancer survivors. PMID:16304621

  7. Predicting physical activity and outcome expectations in cancer survivors: an application of Self-Determination Theory.

    PubMed

    Wilson, Philip M; Blanchard, Chris M; Nehl, Eric; Baker, Frank

    2006-07-01

    The purpose of this study was to examine the contributions of autonomous and controlled motives drawn from Self-Determination Theory (SDT; Intrinsic Motivation and Self-determination in Human Behavior. Plenum Press: New York, 1985; Handbook of Self-determination Research. University of Rochester Press: New York, 2002) towards predicting physical activity behaviours and outcome expectations in adult cancer survivors. Participants were cancer-survivors (N=220) and a non-cancer comparison cohort (N=220) who completed an adapted version of the Treatment Self-Regulation Questionnaire modified for physical activity behaviour (TSRQ-PA), an assessment of the number of minutes engaged in moderate-to-vigorous physical activity (MVPA) weekly, and the anticipated outcomes expected from regular physical activity (OE). Simultaneous multiple regression analyses indicated that autonomous motives was the dominant predictor of OEs across both cancer and non-cancer cohorts (R(2adj)=0.29-0.43), while MVPA was predicted by autonomous (beta's ranged from 0.21 to 0.34) and controlled (beta's ranged from -0.04 to -0.23) motives after controlling for demographic considerations. Cancer status (cancer versus no cancer) did not moderate the motivation-physical activity relationship. Collectively, these findings suggest that the distinction between autonomous and controlled motives is useful and compliments a growing body of evidence supporting SDT as a framework for understanding motivational processes in physical activity contexts with cancer survivors.

  8. Predicting Promoter-Induced Bond Activation on Solid Catalysts Using Elementary Bond Orders.

    PubMed

    Tsai, Charlie; Latimer, Allegra A; Yoo, Jong Suk; Studt, Felix; Abild-Pedersen, Frank

    2015-09-17

    In this Letter, we examine bond activation induced by nonmetal surface promoters in the context of dehydrogenation reactions. We use C-H bond activation in methane dehydrogenation on transition metals as an example to understand the origin of the promoting or poisoning effect of nonmetals. The electronic structure of the surface and the bond order of the promoter are found to establish all trends in bond activation. On the basis of these results, we develop a predictive model that successfully describes the energetics of C-H, O-H, and N-H bond activation across a range of reactions. For a given reaction step, a single data point determines whether a nonmetal will promote bond activation or poison the surface and by how much. We show how our model leads to general insights that can be directly used to predict bond activation energetics on transition metal sulfides and oxides, which can be perceived as promoted surfaces. These results can then be directly used in studies on full catalytic pathways. PMID:26722740

  9. 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). PMID:26544602

  10. 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 pr