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Sample records for ricinosomes predict programmed

  1. Ricinosomes provide an early indicator of suspensor and endosperm cells destined to die during late seed development in quinoa (Chenopodium quinoa).

    Science.gov (United States)

    López-Fernández, M P; Maldonado, S

    2013-11-01

    In mature quinoa (Chenopodium quinoa) seeds, the lasting endosperm forms a micropylar cone covering the radicle. The suspensor cells lie within the centre of the cone. During the final stage of seed development, the cells of the lasting endosperm accumulate protein and lipids while the rest are crushed and disintegrated. Both the suspensor and endosperm die progressively from the innermost layers surrounding the embryo and extending towards the nucellar tissue. Ricinosomes are endoplasmic reticulum-derived organelles that accumulate both the pro-form and the mature form of cysteine endopeptidase (Cys-EP), first identified in castor bean (Ricinus communis) endosperm during germination. This study sought to identify associations between the presence of ricinosomes and programmed cell death (PCD) hallmarks in suspensor and endosperm cells predestined to die during quinoa seed development. A structural study using light microscopy and transmission electron microscopy was performed. To detect the presence of Cys-EP, both western blot and in situ immunolocalization assays were carried out using anti-R. communis Cys-EP antibody. A TUNEL assay was used to determine DNA fragmentation. Except for the one or two cell layers that constitute the lasting endosperm in the mature seed, ricinosomes were found in suspensor and endosperm cells. These cells were also the site of morphological abnormalities, including misshapen and fragmented nuclei, vesiculation of the cytosol, vacuole collapse and cell wall disorganization. It is proposed that, in suspensor and endosperm cells, the early detection of Cys-EP in ricinosomes predicts the occurrence of PCD during late seed development.

  2. EPRI MOV performance prediction program

    International Nuclear Information System (INIS)

    Hosler, J.F.; Damerell, P.S.; Eidson, M.G.; Estep, N.E.

    1994-01-01

    An overview of the EPRI Motor-Operated Valve (MOV) Performance Prediction Program is presented. The objectives of this Program are to better understand the factors affecting the performance of MOVs and to develop and validate methodologies to predict MOV performance. The Program involves valve analytical modeling, separate-effects testing to refine the models, and flow-loop and in-plant MOV testing to provide a basis for model validation. The ultimate product of the Program is an MOV Performance Prediction Methodology applicable to common gate, globe, and butterfly valves. The methodology predicts thrust and torque requirements at design-basis flow and differential pressure conditions, assesses the potential for gate valve internal damage, and provides test methods to quantify potential for gate valve internal damage, and provides test methods to quantify potential variations in actuator output thrust with loading condition. Key findings and their potential impact on MOV design and engineering application are summarized

  3. The Use of Linear Programming for Prediction.

    Science.gov (United States)

    Schnittjer, Carl J.

    The purpose of the study was to develop a linear programming model to be used for prediction, test the accuracy of the predictions, and compare the accuracy with that produced by curvilinear multiple regression analysis. (Author)

  4. MOV predictive maintenance program at Darlington NGS

    International Nuclear Information System (INIS)

    Morrison, J.F.

    1992-01-01

    This paper details the Motor Operated Valve (MOV) Predictive Maintenance program at Darlington Nuclear Generating Station. The program encompasses the use of diagnostics tooling in conjunction with more standard maintenance techniques, with the goal of improving performance of MOV's. Problems encountered and solutions developed during the first two phases of this program are presented, along with proposed actions for the final trending phase of the program. This paper also touches on the preventive and corrective maintenance aspects of an overall MOV maintenance program. 6 refs., 6 tabs., 6 figs

  5. Speedup predictions on large scientific parallel programs

    International Nuclear Information System (INIS)

    Williams, E.; Bobrowicz, F.

    1985-01-01

    How much speedup can we expect for large scientific parallel programs running on supercomputers. For insight into this problem we extend the parallel processing environment currently existing on the Cray X-MP (a shared memory multiprocessor with at most four processors) to a simulated N-processor environment, where N greater than or equal to 1. Several large scientific parallel programs from Los Alamos National Laboratory were run in this simulated environment, and speedups were predicted. A speedup of 14.4 on 16 processors was measured for one of the three most used codes at the Laboratory

  6. Establishing a predictive maintenance program at the Hanford Site

    International Nuclear Information System (INIS)

    Winslow, R.W.

    1994-05-01

    This document contains information about a new Predictive Maintenance Program being developed and implemented at the Hanford Reservation. Details of the document include: background on persons developing the program, history of predictive maintenance, implementation of new program, engineering task analysis, network development and new software, issues to be resolved, benefits expected, and appendix gives information about the symposium from which this paper is based

  7. Statistical and Machine Learning Models to Predict Programming Performance

    OpenAIRE

    Bergin, Susan

    2006-01-01

    This thesis details a longitudinal study on factors that influence introductory programming success and on the development of machine learning models to predict incoming student performance. Although numerous studies have developed models to predict programming success, the models struggled to achieve high accuracy in predicting the likely performance of incoming students. Our approach overcomes this by providing a machine learning technique, using a set of three significant...

  8. Programming Useful Life Prediction (PULP), Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Accurately predicting Remaining Useful Life (RUL) provides significant benefits—it increases safety and reduces financial and labor resource requirements. Relying on...

  9. Caregiver Responsiveness to the Family Bereavement Program: What predicts responsiveness? What does responsiveness predict?

    OpenAIRE

    Schoenfelder, Erin N.; Sandler, Irwin N.; Millsap, Roger E.; Wolchik, Sharlene A.; Berkel, Cady; Ayers, Timothy S.

    2013-01-01

    The study developed a multi-dimensional measure to assess participant responsiveness to a preventive intervention, and applied this measure to study how participant baseline characteristics predict responsiveness and how responsiveness predicts program outcomes. The study was conducted with caregivers who participated in the parenting-focused component of the Family Bereavement Program (FBP), a prevention program for families that have experienced parental death. The sample consisted of 89 ca...

  10. Large-scale linear programs in planning and prediction.

    Science.gov (United States)

    2017-06-01

    Large-scale linear programs are at the core of many traffic-related optimization problems in both planning and prediction. Moreover, many of these involve significant uncertainty, and hence are modeled using either chance constraints, or robust optim...

  11. Program integration of predictive maintenance with reliability centered maintenance

    International Nuclear Information System (INIS)

    Strong, D.K. Jr; Wray, D.M.

    1990-01-01

    This paper addresses improving the safety and reliability of power plants in a cost-effective manner by integrating the recently developed reliability centered maintenance techniques with the traditional predictive maintenance techniques of nuclear power plants. The topics of the paper include a description of reliability centered maintenance (RCM), enhancing RCM with predictive maintenance, predictive maintenance programs, condition monitoring techniques, performance test techniques, the mid-Atlantic Reliability Centered Maintenance Users Group, test guides and the benefits of shared guide development

  12. Integrated predictive maintenance program vibration and lube oil analysis: Part I - history and the vibration program

    Energy Technology Data Exchange (ETDEWEB)

    Maxwell, H.

    1996-12-01

    This paper is the first of two papers which describe the Predictive Maintenance Program for rotating machines at the Palo Verde Nuclear Generating Station. The organization has recently been restructured and significant benefits have been realized by the interaction, or {open_quotes}synergy{close_quotes} between the Vibration Program and the Lube Oil Analysis Program. This paper starts with the oldest part of the program - the Vibration Program and discusses the evolution of the program to its current state. The {open_quotes}Vibration{close_quotes} view of the combined program is then presented.

  13. Integrated predictive maintenance program vibration and lube oil analysis: Part I - history and the vibration program

    International Nuclear Information System (INIS)

    Maxwell, H.

    1996-01-01

    This paper is the first of two papers which describe the Predictive Maintenance Program for rotating machines at the Palo Verde Nuclear Generating Station. The organization has recently been restructured and significant benefits have been realized by the interaction, or open-quotes synergyclose quotes between the Vibration Program and the Lube Oil Analysis Program. This paper starts with the oldest part of the program - the Vibration Program and discusses the evolution of the program to its current state. The open-quotes Vibrationclose quotes view of the combined program is then presented

  14. Geometric Semantic Genetic Programming Algorithm and Slump Prediction

    OpenAIRE

    Xu, Juncai; Shen, Zhenzhong; Ren, Qingwen; Xie, Xin; Yang, Zhengyu

    2017-01-01

    Research on the performance of recycled concrete as building material in the current world is an important subject. Given the complex composition of recycled concrete, conventional methods for forecasting slump scarcely obtain satisfactory results. Based on theory of nonlinear prediction method, we propose a recycled concrete slump prediction model based on geometric semantic genetic programming (GSGP) and combined it with recycled concrete features. Tests show that the model can accurately p...

  15. Experience in the application of erosion-corrosion prediction programs

    International Nuclear Information System (INIS)

    Castiella Villacampa, E.; Cacho Cordero, L.; Pascual Velazquez, A.; Casar Asuar, M.

    1994-01-01

    Recently the results of the Nuclear Regulatory Commission's follow-on programme relating to the application of erosion-corrosion supervision and control programs were published. The main problems encountered in their practical application are highlighted, namely those associated with prediction, calculation of minimum thickness acceptable by code, results analyses of the thicknesses measured using ultrasound technology, cases of incorrect substitution, etc. A number of power plants in Spain are currently using a computerised prediction and monitoring program for the erosion-corrosion phenomenon. The experience gained in the application of this program has been such that it has led to a number or benefits: an improvement in the application of the program, proof of its suitability to real situation, the establishment of a series of criteria relative to the inclusion or exclusion of consideration during data input, the monitoring of the phenomenon, selection of elements for inspection, etc. The report describes these areas, using typical examples as illustrations. (Author)

  16. Aircraft noise prediction program theoretical manual: Rotorcraft System Noise Prediction System (ROTONET), part 4

    Science.gov (United States)

    Weir, Donald S.; Jumper, Stephen J.; Burley, Casey L.; Golub, Robert A.

    1995-01-01

    This document describes the theoretical methods used in the rotorcraft noise prediction system (ROTONET), which is a part of the NASA Aircraft Noise Prediction Program (ANOPP). The ANOPP code consists of an executive, database manager, and prediction modules for jet engine, propeller, and rotor noise. The ROTONET subsystem contains modules for the prediction of rotor airloads and performance with momentum theory and prescribed wake aerodynamics, rotor tone noise with compact chordwise and full-surface solutions to the Ffowcs-Williams-Hawkings equations, semiempirical airfoil broadband noise, and turbulence ingestion broadband noise. Flight dynamics, atmosphere propagation, and noise metric calculations are covered in NASA TM-83199, Parts 1, 2, and 3.

  17. Genomic prediction in a breeding program of perennial ryegrass

    DEFF Research Database (Denmark)

    Fé, Dario; Ashraf, Bilal; Greve-Pedersen, Morten

    2015-01-01

    We present a genomic selection study performed on 1918 rye grass families (Lolium perenne L.), which were derived from a commercial breeding program at DLF-Trifolium, Denmark. Phenotypes were recorded on standard plots, across 13 years and in 6 different countries. Variants were identified...... this set. Estimated Breeding Value and prediction accuracies were calculated trough two different cross-validation schemes: (i) k-fold (k=10); (ii) leaving out one parent combination at the time, in order to test for accuracy of predicting new families. Accuracies ranged between 0.56 and 0.97 for scheme (i....... A larger set of 1791 F2s were used as training set to predict EBVs of 127 synthetic families (originated from poly-crosses between 5-11 single plants) for heading date and crown rust resistance. Prediction accuracies were 0.93 and 0.57 respectively. Results clearly demonstrate considerable potential...

  18. Constraint Logic Programming approach to protein structure prediction

    Directory of Open Access Journals (Sweden)

    Fogolari Federico

    2004-11-01

    Full Text Available Abstract Background The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Results Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. Conclusions The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

  19. Constraint Logic Programming approach to protein structure prediction.

    Science.gov (United States)

    Dal Palù, Alessandro; Dovier, Agostino; Fogolari, Federico

    2004-11-30

    The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known) secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

  20. PBF/LOFT Lead Rod Test Program experiment predictions document

    International Nuclear Information System (INIS)

    Varacalle, D.J.; Cox, W.R.; Niebruegge, D.A.; Seiber, S.J.; Brake, T.E.; Driskell, W.E.; Nigg, D.W.; Tolman, E.L.

    1978-12-01

    The PBF/LOFT Lead Rod (LLR) Test Program is being conducted to provide experimental information on the behavior of nuclear fuel under normal and accident conditions in the Power Burst Facility (PBF) at the Idaho National Engineering Laboratory. The PBF/LLR tests are designed to simulate the test conditions for the LOFT Power Ascension Tests L2-3 through L2-5. The test program has been designed to provide a parametric evaluation of the LOFT fuel (center and peripheral modules) over a wide range of power. This report presents the experiment predictions for the three four-rod LOCA tests

  1. Predicting introductory programming performance: A multi-institutional multivariate study

    Science.gov (United States)

    Bergin, Susan; Reilly, Ronan

    2006-12-01

    A model for predicting student performance on introductory programming modules is presented. The model uses attributes identified in a study carried out at four third-level institutions in the Republic of Ireland. Four instruments were used to collect the data and over 25 attributes were examined. A data reduction technique was applied and a logistic regression model using 10-fold stratified cross validation was developed. The model used three attributes: Leaving Certificate Mathematics result (final mathematics examination at second level), number of hours playing computer games while taking the module and programming self-esteem. Prediction success was significant with 80% of students correctly classified. The model also works well on a per-institution level. A discussion on the implications of the model is provided and future work is outlined.

  2. Genetic Programming for Sea Level Predictions in an Island Environment

    Directory of Open Access Journals (Sweden)

    M.A. Ghorbani

    2010-03-01

    Full Text Available Accurate predictions of sea-level are important for geodetic applications, navigation, coastal, industrial and tourist activities. In the current work, the Genetic Programming (GP and artificial neural networks (ANNs were applied to forecast half-daily and daily sea-level variations from 12 hours to 5 days ahead. The measurements at the Cocos (Keeling Islands in the Indian Ocean were used for training and testing of the employed artificial intelligence techniques. A comparison was performed of the predictions from the GP model and the ANN simulations. Based on the comparison outcomes, it was found that the Genetic Programming approach can be successfully employed in forecasting of sea level variations.

  3. Activity, exposure rate and spectrum prediction with Java programming

    International Nuclear Information System (INIS)

    Sahin, D.; Uenlue, K.

    2009-01-01

    In order to envision the radiation exposure during Neutron Activation Analysis (NAA) experiments, a software called Activity Predictor is developed using Java TM programming language. The Activity Predictor calculates activities, exposure rates and gamma spectra of activated samples for NAA experiments performed at Radiation Science and Engineering Center (RSEC), Penn State Breazeale Reactor (PSBR). The calculation procedure for predictions involves both analytical and Monte Carlo methods. The Activity Predictor software is validated with a series of activation experiments. It has been found that Activity Predictor software calculates the activities and exposure rates precisely. The software also predicts gamma spectrum for each measurement. The predicted spectra agreed partially with measured spectra. The error in net photo peak areas varied from 4.8 to 51.29%, which is considered to be due to simplistic modeling, statistical fluctuations and unknown contaminants in the samples. (author)

  4. Modular Engine Noise Component Prediction System (MCP) Program Users' Guide

    Science.gov (United States)

    Golub, Robert A. (Technical Monitor); Herkes, William H.; Reed, David H.

    2004-01-01

    This is a user's manual for Modular Engine Noise Component Prediction System (MCP). This computer code allows the user to predict turbofan engine noise estimates. The program is based on an empirical procedure that has evolved over many years at The Boeing Company. The data used to develop the procedure include both full-scale engine data and small-scale model data, and include testing done by Boeing, by the engine manufacturers, and by NASA. In order to generate a noise estimate, the user specifies the appropriate engine properties (including both geometry and performance parameters), the microphone locations, the atmospheric conditions, and certain data processing options. The version of the program described here allows the user to predict three components: inlet-radiated fan noise, aft-radiated fan noise, and jet noise. MCP predicts one-third octave band noise levels over the frequency range of 50 to 10,000 Hertz. It also calculates overall sound pressure levels and certain subjective noise metrics (e.g., perceived noise levels).

  5. RFI Math Model programs for predicting intermodulation interference

    Science.gov (United States)

    Stafford, J. M.

    1974-01-01

    Receivers operating on a space vehicle or an aircraft having many on-board transmitters are subject to intermodulation interference from mixing in the transmitting antenna systems, the external environment, or the receiver front-ends. This paper presents the techniques utilized in RFI Math Model computer programs that were developed to aid in the prevention of interference by predicting problem areas prior to occurrence. Frequencies and amplitudes of possible intermodulation products generated in the external environment are calculated and compared to receiver sensitivities. Intermodulation products generated in receivers are evaluated to determine the adequacy of preselector ejection.

  6. Gstat: a program for geostatistical modelling, prediction and simulation

    Science.gov (United States)

    Pebesma, Edzer J.; Wesseling, Cees G.

    1998-01-01

    Gstat is a computer program for variogram modelling, and geostatistical prediction and simulation. It provides a generic implementation of the multivariable linear model with trends modelled as a linear function of coordinate polynomials or of user-defined base functions, and independent or dependent, geostatistically modelled, residuals. Simulation in gstat comprises conditional or unconditional (multi-) Gaussian sequential simulation of point values or block averages, or (multi-) indicator sequential simulation. Besides many of the popular options found in other geostatistical software packages, gstat offers the unique combination of (i) an interactive user interface for modelling variograms and generalized covariances (residual variograms), that uses the device-independent plotting program gnuplot for graphical display, (ii) support for several ascii and binary data and map file formats for input and output, (iii) a concise, intuitive and flexible command language, (iv) user customization of program defaults, (v) no built-in limits, and (vi) free, portable ANSI-C source code. This paper describes the class of problems gstat can solve, and addresses aspects of efficiency and implementation, managing geostatistical projects, and relevant technical details.

  7. PREDICTION OF MEAT PRODUCT QUALITY BY THE MATHEMATICAL PROGRAMMING METHODS

    Directory of Open Access Journals (Sweden)

    A. B. Lisitsyn

    2016-01-01

    Full Text Available Abstract Use of the prediction technologies is one of the directions of the research work carried out both in Russia and abroad. Meat processing is accompanied by the complex physico-chemical, biochemical and mechanical processes. To predict the behavior of meat raw material during the technological processing, a complex of physico-technological and structural-mechanical indicators, which objectively reflects its quality, is used. Among these indicators are pH value, water binding and fat holding capacities, water activity, adhesiveness, viscosity, plasticity and so on. The paper demonstrates the influence of animal proteins (beef and pork on the physico-chemical and functional properties before and after thermal treatment of minced meat made from meat raw material with different content of the connective and fat tissues. On the basis of the experimental data, the model (stochastic dependence parameters linking the quantitative resultant and factor variables were obtained using the regression analysis, and the degree of the correlation with the experimental data was assessed. The maximum allowable levels of meat raw material replacement with animal proteins (beef and pork were established by the methods of mathematical programming. Use of the information technologies will significantly reduce the costs of the experimental search and substantiation of the optimal level of replacement of meat raw material with animal proteins (beef, pork, and will also allow establishing a relationship of product quality indicators with quantity and quality of minced meat ingredients.

  8. Flow discharge prediction in compound channels using linear genetic programming

    Science.gov (United States)

    Azamathulla, H. Md.; Zahiri, A.

    2012-08-01

    SummaryFlow discharge determination in rivers is one of the key elements in mathematical modelling in the design of river engineering projects. Because of the inundation of floodplains and sudden changes in river geometry, flow resistance equations are not applicable for compound channels. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results only in laboratory flumes. Due to the ability to model complex phenomena, the artificial intelligence methods have recently been employed for wide applications in various fields of water engineering. Linear genetic programming (LGP), a branch of artificial intelligence methods, is able to optimise the model structure and its components and to derive an explicit equation based on the variables of the phenomena. In this paper, a precise dimensionless equation has been derived for prediction of flood discharge using LGP. The proposed model was developed using published data compiled for stage-discharge data sets for 394 laboratories, and field of 30 compound channels. The results indicate that the LGP model has a better performance than the existing models.

  9. Predicting Attrition in a Military Special Program Training Command

    Science.gov (United States)

    2016-05-20

    made by assessing additional psychological factors. Specifically, motivation (s) to enter the training program (e.g., intrinsic versus extrinsic ...this and other training programs. Motivations to enter the training program could be assessed using a measure such as the Work Extrinsic and...MEDICINE GRADUATE PROGRAMS Graduate Education Office (A 1045), 4301 Jones Bridge Road, Bethesda, MD 20814 APPROVAL OF THE DOCTORAL DISSERTATION IN THE

  10. Predicting daily physical activity in a lifestyle intervention program

    NARCIS (Netherlands)

    Long, Xi; Pauws, S.C.; Pijl, M.; Lacroix, J.; Goris, A.H.C.; Aarts, R.M.; Gottfried, B.; Aghajan, H.

    2011-01-01

    The growing number of people adopting a sedentary lifestyle these days creates a serious need for effective physical activity promotion programs. Often, these programs monitor activity, provide feedback about activity and offer coaching to increase activity. Some programs rely on a human coach who

  11. Prediction Markets as a Way to Manage Acquisition Programs

    Science.gov (United States)

    2011-06-01

    volume helps management set production levels, but if management increases advertising it will undermine the market . This becomes critical for the DoD...34 Corporate Strategy Board. Gaspoz, C. (2008). "Prediction markets as an innovative way to manage R&D portfolios." CAiSE Doctoral Consortium. Montpellier...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA MBA PROFESSIONAL REPORT Prediction Markets as a Way to Manage Acquisition

  12. Nonlinear Time Series Prediction Using LS-SVM with Chaotic Mutation Evolutionary Programming for Parameter Optimization

    International Nuclear Information System (INIS)

    Xu Ruirui; Chen Tianlun; Gao Chengfeng

    2006-01-01

    Nonlinear time series prediction is studied by using an improved least squares support vector machine (LS-SVM) regression based on chaotic mutation evolutionary programming (CMEP) approach for parameter optimization. We analyze how the prediction error varies with different parameters (σ, γ) in LS-SVM. In order to select appropriate parameters for the prediction model, we employ CMEP algorithm. Finally, Nasdaq stock data are predicted by using this LS-SVM regression based on CMEP, and satisfactory results are obtained.

  13. The Coastal Ocean Prediction Systems program: Understanding and managing our coastal ocean

    International Nuclear Information System (INIS)

    Eden, H.F.; Mooers, C.N.K.

    1990-06-01

    The goal of COPS is to couple a program of regular observations to numerical models, through techniques of data assimilation, in order to provide a predictive capability for the US coastal ocean including the Great Lakes, estuaries, and the entire Exclusive Economic Zone (EEZ). The objectives of the program include: determining the predictability of the coastal ocean and the processes that govern the predictability; developing efficient prediction systems for the coastal ocean based on the assimilation of real-time observations into numerical models; and coupling the predictive systems for the physical behavior of the coastal ocean to predictive systems for biological, chemical, and geological processes to achieve an interdisciplinary capability. COPS will provide the basis for effective monitoring and prediction of coastal ocean conditions by optimizing the use of increased scientific understanding, improved observations, advanced computer models, and computer graphics to make the best possible estimates of sea level, currents, temperatures, salinities, and other properties of entire coastal regions

  14. Predicting Success: How Predictive Analytics Are Transforming Student Support and Success Programs

    Science.gov (United States)

    Boerner, Heather

    2015-01-01

    Every year, Lone Star College in Texas hosts a "Men of Honor" program to provide assistance and programming to male students, but particularly those who are Hispanic and black, in hopes their academic performance will improve. Lone Star might have kept directing its limited resources toward these students--and totally missed the subset…

  15. Benchmarking of gene prediction programs for metagenomic data.

    Science.gov (United States)

    Yok, Non; Rosen, Gail

    2010-01-01

    This manuscript presents the most rigorous benchmarking of gene annotation algorithms for metagenomic datasets to date. We compare three different programs: GeneMark, MetaGeneAnnotator (MGA) and Orphelia. The comparisons are based on their performances over simulated fragments from one hundred species of diverse lineages. We defined four different types of fragments; two types come from the inter- and intra-coding regions and the other types are from the gene edges. Hoff et al. used only 12 species in their comparison; therefore, their sample is too small to represent an environmental sample. Also, no predecessors has separately examined fragments that contain gene edges as opposed to intra-coding regions. General observations in our results are that performances of all these programs improve as we increase the length of the fragment. On the other hand, intra-coding fragments of our data show low annotation error in all of the programs if compared to the gene edge fragments. Overall, we found an upper-bound performance by combining all the methods.

  16. Surveying the elements of successful infrared predictive maintenance programs

    Science.gov (United States)

    Snell, John R., Jr.; Spring, Robert W.

    1991-03-01

    This paper summarizes the results of a survey of over three hundred maintenance personnel who use imaging equipment within their company or organization. All had previously participated in one or more of our training programs. The companies took in a broad range of industry, including, among other, power generation, pulp and paper, metals, mining, petrochemical, automotive and general manufacturing. The organizations were mainly quite large, either commercial or public, and included governmental agencies, military, colleges and universities, municipalities, and utilities. Although we had a very tight time line for the survey, we were pleased to have a 15% response rate. The results show that some of the causes of success and failure in infrared programs are not unlike those associated with any type of program in an organizational structure, i.e. the need for accurate and timely communications; justification requirements; etc. Another set of problems was shared more closely with other startup maintenance technologies (for example, vibration monitoring), such as the need for trending data; providing appropriate technical training; achieving reproducible results; etc. Finally, some of the driving mechanisms are more specific to this technology, such as re-designing equipment so that it can be thermally inspected; establishing effective documentation strategies; etc.

  17. Stream Flow Prediction by Remote Sensing and Genetic Programming

    Science.gov (United States)

    Chang, Ni-Bin

    2009-01-01

    A genetic programming (GP)-based, nonlinear modeling structure relates soil moisture with synthetic-aperture-radar (SAR) images to present representative soil moisture estimates at the watershed scale. Surface soil moisture measurement is difficult to obtain over a large area due to a variety of soil permeability values and soil textures. Point measurements can be used on a small-scale area, but it is impossible to acquire such information effectively in large-scale watersheds. This model exhibits the capacity to assimilate SAR images and relevant geoenvironmental parameters to measure soil moisture.

  18. Experimental validation of the twins prediction program for rolling noise. Pt.2: results

    NARCIS (Netherlands)

    Thompson, D.J.; Fodiman, P.; Mahé, H.

    1996-01-01

    Two extensive measurement campaigns have been carried out to validate the TWINS prediction program for rolling noise, as described in part 1 of this paper. This second part presents the experimental results of vibration and noise during train pass-bys and compares them with predictions from the

  19. Predicting Dropout Student: An Application of Data Mining Methods in an Online Education Program

    Science.gov (United States)

    Yukselturk, Erman; Ozekes, Serhat; Turel, Yalin Kilic

    2014-01-01

    This study examined the prediction of dropouts through data mining approaches in an online program. The subject of the study was selected from a total of 189 students who registered to the online Information Technologies Certificate Program in 2007-2009. The data was collected through online questionnaires (Demographic Survey, Online Technologies…

  20. Participatory cues and program familiarity predict young children’s learning from educational television

    NARCIS (Netherlands)

    Piotrowski, J.

    2014-01-01

    The capacity model is designed to predict young children's learning from educational television. It posits that select program features and individual child characteristics can support this learning either by increasing total working memory allocated to the program or altering the allocation of

  1. Development of Wind Farm AEP Prediction Program Considering Directional Wake Effect

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Kyoungboo; Cho, Kyungho; Huh, Jongchul [Jeju Nat’l Univ., Jeju (Korea, Republic of)

    2017-07-15

    For accurate AEP prediction in a wind farm, it is necessary to effectively calculate the wind speed reduction and the power loss due to the wake effect in each wind direction. In this study, a computer program for AEP prediction considering directional wake effect was developed. The results of the developed program were compared with the actual AEP of the wind farm and the calculation result of existing commercial software to confirm the accuracy of prediction. The applied equations are identical with those of commercial software based on existing theories, but there is a difference in the calculation process of the detection of the wake effect area in each wind direction. As a result, the developed program predicted to be less than 1% of difference to the actual capacity factor and showed more than 2% of better results compared with the existing commercial software.

  2. POLYAR, a new computer program for prediction of poly(A sites in human sequences

    Directory of Open Access Journals (Sweden)

    Qamar Raheel

    2010-11-01

    Full Text Available Abstract Background mRNA polyadenylation is an essential step of pre-mRNA processing in eukaryotes. Accurate prediction of the pre-mRNA 3'-end cleavage/polyadenylation sites is important for defining the gene boundaries and understanding gene expression mechanisms. Results 28761 human mapped poly(A sites have been classified into three classes containing different known forms of polyadenylation signal (PAS or none of them (PAS-strong, PAS-weak and PAS-less, respectively and a new computer program POLYAR for the prediction of poly(A sites of each class was developed. In comparison with polya_svm (till date the most accurate computer program for prediction of poly(A sites while searching for PAS-strong poly(A sites in human sequences, POLYAR had a significantly higher prediction sensitivity (80.8% versus 65.7% and specificity (66.4% versus 51.7% However, when a similar sort of search was conducted for PAS-weak and PAS-less poly(A sites, both programs had a very low prediction accuracy, which indicates that our knowledge about factors involved in the determination of the poly(A sites is not sufficient to identify such polyadenylation regions. Conclusions We present a new classification of polyadenylation sites into three classes and a novel computer program POLYAR for prediction of poly(A sites/regions of each of the class. In tests, POLYAR shows high accuracy of prediction of the PAS-strong poly(A sites, though this program's efficiency in searching for PAS-weak and PAS-less poly(A sites is not very high but is comparable to other available programs. These findings suggest that additional characteristics of such poly(A sites remain to be elucidated. POLYAR program with a stand-alone version for downloading is available at http://cub.comsats.edu.pk/polyapredict.htm.

  3. Prediction of Student Dropout in E-Learning Program Through the Use of Machine Learning Method

    OpenAIRE

    Mingjie Tan; Peiji Shao

    2015-01-01

    The high rate of dropout is a serious problem in E-learning program. Thus it has received extensive concern from the education administrators and researchers. Predicting the potential dropout students is a workable solution to prevent dropout. Based on the analysis of related literature, this study selected student’s personal characteristic and academic performance as input attributions. Prediction models were developed using Artificial Neural Network (ANN), Decision Tree (DT) and Bayesian Ne...

  4. Prediction Modeling for Academic Success in Professional Master's Athletic Training Programs

    Science.gov (United States)

    Bruce, Scott L.; Crawford, Elizabeth; Wilkerson, Gary B.; Rausch, David; Dale, R. Barry; Harris, Martina

    2016-01-01

    Context: A common goal of professional education programs is to recruit the students best suited for the professional career. Selection of students can be a difficult process, especially if the number of qualified candidates exceeds the number of available positions. The ability to predict academic success in any profession has been a challenging…

  5. Genomic selection accuracy using multi-family prediction models in a wheat breeding program

    Science.gov (United States)

    Genomic selection (GS) uses genome-wide molecular marker data to predict the genetic value of selection candidates in breeding programs. In plant breeding, the ability to produce large numbers of progeny per cross allows GS to be conducted within each family. However, this approach requires phenotyp...

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

    Science.gov (United States)

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

    2016-01-01

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

  7. Predicting Improvement After a Bystander Program for the Prevention of Sexual and Dating Violence.

    Science.gov (United States)

    Hines, Denise A; Palm Reed, Kathleen M

    2015-07-01

    Although evidence suggests that bystander prevention programs are promising interventions for decreasing sexual violence and dating violence on college campuses, there have been no studies to date evaluating moderators of bystander program effectiveness. The current study evaluates whether different demographic characteristics, attitudes, knowledge, and behaviors at pretest predict change over a 6-month follow-up for students who participated in a bystander prevention program. Participants in the three assessments (pretest, posttest, 6-month follow-up) included 296 college students who were mandated to attend a bystander program during their first year orientation. Analyses showed that with few exceptions, the bystander program worked best for students who were most at risk given their pretest demographics and levels of attitudes condoning dating violence and sexual violence, bystander efficacy, and bystander behaviors. Results are discussed in terms of suggestions for future research. © 2014 Society for Public Health Education.

  8. An influence function method based subsidence prediction program for longwall mining operations in inclined coal seams

    Energy Technology Data Exchange (ETDEWEB)

    Yi Luo; Jian-wei Cheng [West Virginia University, Morgantown, WV (United States). Department of Mining Engineering

    2009-09-15

    The distribution of the final surface subsidence basin induced by longwall operations in inclined coal seam could be significantly different from that in flat coal seam and demands special prediction methods. Though many empirical prediction methods have been developed, these methods are inflexible for varying geological and mining conditions. An influence function method has been developed to take the advantage of its fundamentally sound nature and flexibility. In developing this method, significant modifications have been made to the original Knothe function to produce an asymmetrical influence function. The empirical equations for final subsidence parameters derived from US subsidence data and Chinese empirical values have been incorporated into the mathematical models to improve the prediction accuracy. A corresponding computer program is developed. A number of subsidence cases for longwall mining operations in coal seams with varying inclination angles have been used to demonstrate the applicability of the developed subsidence prediction model. 9 refs., 8 figs.

  9. Evaluation of Monticello Nuclear Power Plant, Environmental Impact Prediction, based on monitoring programs

    International Nuclear Information System (INIS)

    Gore, K.L.; Thomas, J.M.; Kannberg, L.D.; Watson, D.G.

    1976-11-01

    This report evaluates quantitatively the nonradiological environmental monitoring programs at Monticello Nuclear Generating Plant. The general objective of the study is to assess the effectiveness of monitoring programs in the measurement of environmental impacts. Specific objectives include the following: (1) Assess the validity of environmental impact predictions made in the Environmental Statement by analysis of nonradiological monitoring data; (2) evaluate the general adequacy of environmental monitoring programs for detecting impacts and their responsiveness to Technical Specifications objectives; (3) assess the adequacy of preoperational monitoring programs in providing a sufficient data base for evaluating operational impacts; (4) identify possible impacts that were not predicted in the environmental statement and identify monitoring activities that need to be added, modified or deleted; and (5) assist in identifying environmental impacts, monitoring methods, and measurement problems that need additional research before quantitative predictions can be attempted. Preoperational as well as operational monitoring data were examined to test the usefulness of baseline information in evaluating impacts. This included an examination of the analytical methods used to measure ecological and physical parameters, and an assessment of sampling periodicity and sensitivity where appropriate data were available

  10. Strategies for Selecting Crosses Using Genomic Prediction in Two Wheat Breeding Programs.

    Science.gov (United States)

    Lado, Bettina; Battenfield, Sarah; Guzmán, Carlos; Quincke, Martín; Singh, Ravi P; Dreisigacker, Susanne; Peña, R Javier; Fritz, Allan; Silva, Paula; Poland, Jesse; Gutiérrez, Lucía

    2017-07-01

    The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The aim of this study was to compare the best crosses predicted using combinations of mid-parent value and variance prediction accounting for linkage disequilibrium (V) or assuming linkage equilibrium (V). After predicting the mean and the variance of each cross, we selected crosses based on mid-parent value, the top 10% of the progeny, and weighted mean and variance within progenies for grain yield, grain protein content, mixing time, and loaf volume in two applied wheat ( L.) breeding programs: Instituto Nacional de Investigación Agropecuaria (INIA) Uruguay and CIMMYT Mexico. Although the variance of the progeny is important to increase the chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses drove the genetic gain but the variance of the progeny had a small impact on genetic gain for grain yield. However, the relative importance of the variance of the progeny was larger for quality traits. Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses. Copyright © 2017 Crop Science Society of America.

  11. Modeling transducer impulse responses for predicting calibrated pressure pulses with the ultrasound simulation program Field II

    DEFF Research Database (Denmark)

    Bæk, David; Jensen, Jørgen Arendt; Willatzen, Morten

    2010-01-01

    FIELD II is a simulation software capable of predicting the field pressure in front of transducers having any complicated geometry. A calibrated prediction with this program is, however, dependent on an exact voltage-to-surface acceleration impulse response of the transducer. Such impulse response...... is not calculated by FIELD II. This work investigates the usability of combining a one-dimensional multilayer transducer modeling principle with the FIELD II software. Multilayer here refers to a transducer composed of several material layers. Measurements of pressure and current from Pz27 piezoceramic disks...... transducer model and the FIELD II software in combination give good agreement with measurements....

  12. Predicting compliance with an information-based residential outdoor water conservation program

    Science.gov (United States)

    Landon, Adam C.; Kyle, Gerard T.; Kaiser, Ronald A.

    2016-05-01

    Residential water conservation initiatives often involve some form of education or persuasion intended to change the attitudes and behaviors of residential consumers. However, the ability of these instruments to change attitudes toward conservation and their efficacy in affecting water use remains poorly understood. In this investigation the authors examine consumer attitudes toward complying with a persuasive water conservation program, the extent to which those attitudes predict compliance, and the influence of environmental contextual factors on outdoor water use. Results indicate that the persuasive program was successful in developing positive attitudes toward compliance, and that those attitudes predict water use. However, attitudinal variables explain a relatively small proportion of the variance in objectively measured water use behavior. Recommendations for policy are made stressing the importance of understanding both the effects of attitudes and environmental contextual factors in behavior change initiatives in the municipal water sector.

  13. A Seasonal Time-Series Model Based on Gene Expression Programming for Predicting Financial Distress

    Directory of Open Access Journals (Sweden)

    Ching-Hsue Cheng

    2018-01-01

    Full Text Available The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations. Therefore, this study employed the nonlinear attribute selection method to build a nonlinear financial distress prediction model: that is, this paper proposed a novel seasonal time-series gene expression programming model for predicting the financial distress of companies. The proposed model has several advantages including the following: (i the proposed model is different from the previous models lacking the concept of time series; (ii the proposed integrated attribute selection method can find the core attributes and reduce high dimensional data; and (iii the proposed model can generate the rules and mathematical formulas of financial distress for providing references to the investors and decision makers. The result shows that the proposed method is better than the listing classifiers under three criteria; hence, the proposed model has competitive advantages in predicting the financial distress of companies.

  14. A Seasonal Time-Series Model Based on Gene Expression Programming for Predicting Financial Distress

    Science.gov (United States)

    2018-01-01

    The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations. Therefore, this study employed the nonlinear attribute selection method to build a nonlinear financial distress prediction model: that is, this paper proposed a novel seasonal time-series gene expression programming model for predicting the financial distress of companies. The proposed model has several advantages including the following: (i) the proposed model is different from the previous models lacking the concept of time series; (ii) the proposed integrated attribute selection method can find the core attributes and reduce high dimensional data; and (iii) the proposed model can generate the rules and mathematical formulas of financial distress for providing references to the investors and decision makers. The result shows that the proposed method is better than the listing classifiers under three criteria; hence, the proposed model has competitive advantages in predicting the financial distress of companies. PMID:29765399

  15. A Seasonal Time-Series Model Based on Gene Expression Programming for Predicting Financial Distress.

    Science.gov (United States)

    Cheng, Ching-Hsue; Chan, Chia-Pang; Yang, Jun-He

    2018-01-01

    The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations. Therefore, this study employed the nonlinear attribute selection method to build a nonlinear financial distress prediction model: that is, this paper proposed a novel seasonal time-series gene expression programming model for predicting the financial distress of companies. The proposed model has several advantages including the following: (i) the proposed model is different from the previous models lacking the concept of time series; (ii) the proposed integrated attribute selection method can find the core attributes and reduce high dimensional data; and (iii) the proposed model can generate the rules and mathematical formulas of financial distress for providing references to the investors and decision makers. The result shows that the proposed method is better than the listing classifiers under three criteria; hence, the proposed model has competitive advantages in predicting the financial distress of companies.

  16. Predicting changes in hypertension control using electronic health records from a chronic disease management program

    Science.gov (United States)

    Sun, Jimeng; McNaughton, Candace D; Zhang, Ping; Perer, Adam; Gkoulalas-Divanis, Aris; Denny, Joshua C; Kirby, Jacqueline; Lasko, Thomas; Saip, Alexander; Malin, Bradley A

    2014-01-01

    Objective Common chronic diseases such as hypertension are costly and difficult to manage. Our ultimate goal is to use data from electronic health records to predict the risk and timing of deterioration in hypertension control. Towards this goal, this work predicts the transition points at which hypertension is brought into, as well as pushed out of, control. Method In a cohort of 1294 patients with hypertension enrolled in a chronic disease management program at the Vanderbilt University Medical Center, patients are modeled as an array of features derived from the clinical domain over time, which are distilled into a core set using an information gain criteria regarding their predictive performance. A model for transition point prediction was then computed using a random forest classifier. Results The most predictive features for transitions in hypertension control status included hypertension assessment patterns, comorbid diagnoses, procedures and medication history. The final random forest model achieved a c-statistic of 0.836 (95% CI 0.830 to 0.842) and an accuracy of 0.773 (95% CI 0.766 to 0.780). Conclusions This study achieved accurate prediction of transition points of hypertension control status, an important first step in the long-term goal of developing personalized hypertension management plans. PMID:24045907

  17. Predicting changes in hypertension control using electronic health records from a chronic disease management program.

    Science.gov (United States)

    Sun, Jimeng; McNaughton, Candace D; Zhang, Ping; Perer, Adam; Gkoulalas-Divanis, Aris; Denny, Joshua C; Kirby, Jacqueline; Lasko, Thomas; Saip, Alexander; Malin, Bradley A

    2014-01-01

    Common chronic diseases such as hypertension are costly and difficult to manage. Our ultimate goal is to use data from electronic health records to predict the risk and timing of deterioration in hypertension control. Towards this goal, this work predicts the transition points at which hypertension is brought into, as well as pushed out of, control. In a cohort of 1294 patients with hypertension enrolled in a chronic disease management program at the Vanderbilt University Medical Center, patients are modeled as an array of features derived from the clinical domain over time, which are distilled into a core set using an information gain criteria regarding their predictive performance. A model for transition point prediction was then computed using a random forest classifier. The most predictive features for transitions in hypertension control status included hypertension assessment patterns, comorbid diagnoses, procedures and medication history. The final random forest model achieved a c-statistic of 0.836 (95% CI 0.830 to 0.842) and an accuracy of 0.773 (95% CI 0.766 to 0.780). This study achieved accurate prediction of transition points of hypertension control status, an important first step in the long-term goal of developing personalized hypertension management plans.

  18. Using an admissions exam to predict student success in an ADN program.

    Science.gov (United States)

    Gallagher, P A; Bomba, C; Crane, L R

    2001-01-01

    Nursing faculty strive to admit students who are likely to successfully complete the nursing curriculum and pass NCLEX-RN. The high cost of academic preparation and the nursing shortage make this selection process even more critical. The authors discuss how one community college nursing program examined academic achievement measures to determine how well they predicted student success. Results provided faculty with useful data to improve the success and retention of nursing.

  19. Prediction of Student Dropout in E-Learning Program Through the Use of Machine Learning Method

    Directory of Open Access Journals (Sweden)

    Mingjie Tan

    2015-02-01

    Full Text Available The high rate of dropout is a serious problem in E-learning program. Thus it has received extensive concern from the education administrators and researchers. Predicting the potential dropout students is a workable solution to prevent dropout. Based on the analysis of related literature, this study selected student’s personal characteristic and academic performance as input attributions. Prediction models were developed using Artificial Neural Network (ANN, Decision Tree (DT and Bayesian Networks (BNs. A large sample of 62375 students was utilized in the procedures of model training and testing. The results of each model were presented in confusion matrix, and analyzed by calculating the rates of accuracy, precision, recall, and F-measure. The results suggested all of the three machine learning methods were effective in student dropout prediction, and DT presented a better performance. Finally, some suggestions were made for considerable future research.

  20. The Coastal Ocean Prediction Systems program: Understanding and managing our coastal ocean. Volume 1: Strategic summary

    Energy Technology Data Exchange (ETDEWEB)

    1990-05-15

    The proposed COPS (Coastal Ocean Prediction Systems) program is concerned with combining numerical models with observations (through data assimilation) to improve our predictive knowledge of the coastal ocean. It is oriented toward applied research and development and depends upon the continued pursuit of basic research in programs like COOP (Coastal Ocean Processes); i.e., to a significant degree it is involved with ``technology transfer`` from basic knowledge to operational and management applications. This predictive knowledge is intended to address a variety of societal problems: (1) ship routing, (2) trajectories for search and rescue operations, (3) oil spill trajectory simulations, (4) pollution assessments, (5) fisheries management guidance, (6) simulation of the coastal ocean`s response to climate variability, (7) calculation of sediment transport, (8) calculation of forces on structures, and so forth. The initial concern is with physical models and observations in order to provide a capability for the estimation of physical forces and transports in the coastal ocean. For all these applications, there are common needs for physical field estimates: waves, tides, currents, temperature, and salinity, including mixed layers, thermoclines, fronts, jets, etc. However, the intent is to work with biologists, chemists, and geologists in developing integrated multidisciplinary prediction systems as it becomes feasible to do so. From another perspective, by combining observations with models through data assimilation, a modern approach to monitoring is provided through whole-field estimation.

  1. The Coastal Ocean Prediction Systems program: Understanding and managing our coastal ocean

    International Nuclear Information System (INIS)

    1990-01-01

    The proposed COPS (Coastal Ocean Prediction Systems) program is concerned with combining numerical models with observations (through data assimilation) to improve our predictive knowledge of the coastal ocean. It is oriented toward applied research and development and depends upon the continued pursuit of basic research in programs like COOP (Coastal Ocean Processes); i.e., to a significant degree it is involved with ''technology transfer'' from basic knowledge to operational and management applications. This predictive knowledge is intended to address a variety of societal problems: (1) ship routing, (2) trajectories for search and rescue operations, (3) oil spill trajectory simulations, (4) pollution assessments, (5) fisheries management guidance, (6) simulation of the coastal ocean's response to climate variability, (7) calculation of sediment transport, (8) calculation of forces on structures, and so forth. The initial concern is with physical models and observations in order to provide a capability for the estimation of physical forces and transports in the coastal ocean. For all these applications, there are common needs for physical field estimates: waves, tides, currents, temperature, and salinity, including mixed layers, thermoclines, fronts, jets, etc. However, the intent is to work with biologists, chemists, and geologists in developing integrated multidisciplinary prediction systems as it becomes feasible to do so. From another perspective, by combining observations with models through data assimilation, a modern approach to monitoring is provided through whole-field estimation

  2. Microcomputer based program for predicting heat transfer under reactor accident conditions. Volume I

    International Nuclear Information System (INIS)

    Cheng, S.C.; Groeneveld, D.C.; Leung, L.K.H.; Wong, Y.L.; Nguyen, C.

    1987-07-01

    A microcomputer based program called Heat Transfer Prediction Software (HTPS) has been developed. It calculates the heat transfer for the tube and bundle geometries for steady state and transient conditions. This program is capable of providing the best estimated of the hot pin temperatures during slow transients for 37- and 28-element CANDU type fuel bundles. The program is designed for an IBM-PC AT/XT (or IBM-PC compatible computer) equipped with a Math Co-processor. The following input parameters are required: pressure, mass flux, hydraulic diameter, and quality. For the steady state case, the critical heat flux (CHF), the critical heat flux temperature, the minimum film boiling temperature, and the minimum film boiling heat flux are the primary outputs. With either the surface heat flux or wall temperature specified, the program determines the heat transfer regime and calculates the surface heat flux, wall temperatures and heat transfer coefficient. For the slow transient case, the pressure, mass flux, quality, and volumetric heat generation rate are the time dependent input parameters required to calculate the hot pin sheath temperatures and surface heat fluxes. A simple routine for generating properties has been developed for light water to support the above program. It contains correlations that have been verified for pressures ranging from 0.6kPa to 30 MPa, and temperatures up to 1100 degrees Celcius. The thermodynamic and transport properties that can be generated from this routine are: density, specific volume, enthalpy, specific heat capacity, conductivity, viscosity, surface tension and Prandtl number for saturated liquid, saturated vapour, subcooled liquid for superheated vapour. A software for predicting flow regime has also been developed. It determines the flow pattern at specific flow conditions, and provides a correction factor for calculating the CHF during partially stratified horizontal flow. The technical bases for the program and its

  3. Microcomputer based program for predicting heat transfer under reactor accident conditions. Volume II

    International Nuclear Information System (INIS)

    Cheng, S.C.; Groeneveld, D.C.; Leung, L.K.H.; Wong, Y.L.; Nguyen, C.

    1987-07-01

    A microcomputer based program called Heat Transfer Prediction Software (HTPS) has been developed. It calculates the heat transfer for tube and bundle geometries for steady state and transient conditions. This program is capable of providing the best estimated of the hot pin temperatures during slow transients for 37- and 28-element CANDU type fuel bundles. The program is designed for an IBM-PC AT/XT (or IBM-PC compatible computer) equipped with a Math Co-processor. The following input parameters are required: pressure, mass flux, hydraulic diameter, and quality. For the steady state case, the critical heat flux (CHF), the critical heat flux temperature, the minimum film boiling temperature, and the minimum film boiling heat flux are the primary outputs. With either the surface heat flux or wall temperature specified, the program determines the heat transfer regime and calculates the surface heat flux, wall temperature and heat transfer coefficient. For the slow transient case, the pressure, mass flux, quality, and volumetric heat generation rate are the time dependent input parameters are required to calculate the hot pin sheath temperatures and surface heat fluxes. A simple routine for generating properties has been developed for light water to support the above program. It contains correlations that have been verified for pressures ranging from 0.6kPa to 30 MPa, and temperatures up to 1100 degrees Celcius. The thermodynamic and transport properties that can be generated from this routine are: density, specific volume, enthalpy, specific heat capacity, conductivity, viscosity, surface tension and Prandtle number for saturated liquid, saturated vapour, subcooled liquid of superheated vapour. A software for predicting flow regime has also been developed. It determines the flow pattern at specific flow conditions, and provides a correction factor for calculating the CHF during partially stratified horizontal flow. The technical bases for the program and its structure

  4. Linear genetic programming application for successive-station monthly streamflow prediction

    Science.gov (United States)

    Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit

    2014-09-01

    In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.

  5. Bi-objective integer programming for RNA secondary structure prediction with pseudoknots.

    Science.gov (United States)

    Legendre, Audrey; Angel, Eric; Tahi, Fariza

    2018-01-15

    RNA structure prediction is an important field in bioinformatics, and numerous methods and tools have been proposed. Pseudoknots are specific motifs of RNA secondary structures that are difficult to predict. Almost all existing methods are based on a single model and return one solution, often missing the real structure. An alternative approach would be to combine different models and return a (small) set of solutions, maximizing its quality and diversity in order to increase the probability that it contains the real structure. We propose here an original method for predicting RNA secondary structures with pseudoknots, based on integer programming. We developed a generic bi-objective integer programming algorithm allowing to return optimal and sub-optimal solutions optimizing simultaneously two models. This algorithm was then applied to the combination of two known models of RNA secondary structure prediction, namely MEA and MFE. The resulting tool, called BiokoP, is compared with the other methods in the literature. The results show that the best solution (structure with the highest F 1 -score) is, in most cases, given by BiokoP. Moreover, the results of BiokoP are homogeneous, regardless of the pseudoknot type or the presence or not of pseudoknots. Indeed, the F 1 -scores are always higher than 70% for any number of solutions returned. The results obtained by BiokoP show that combining the MEA and the MFE models, as well as returning several optimal and several sub-optimal solutions, allow to improve the prediction of secondary structures. One perspective of our work is to combine better mono-criterion models, in particular to combine a model based on the comparative approach with the MEA and the MFE models. This leads to develop in the future a new multi-objective algorithm to combine more than two models. BiokoP is available on the EvryRNA platform: https://EvryRNA.ibisc.univ-evry.fr .

  6. FREC-4A: a computer program to predict fuel rod performance under normal reactor operation

    International Nuclear Information System (INIS)

    Harayama, Yasuo; Izumi, Fumio

    1981-10-01

    The program FREC-4A (Fuel Reliability Evaluation Code-version 4A) is used for predicting fuel rod performance in normal reactor operation. The performance is calculated in accordance with the irradiation history of fuel rods. Emphasis is placed on the prediction of the axial elongation of claddings induced by pellet-cladding mechanical interaction, including the influence of initially preloaded springs inserted in fuel rod lower plenums. In the FREC-4A, an fuel rod is divided into axial segments. In each segment, it is assumed that the temperature, stress and strain are axi-symmetrical, and the axial strain in constant in fuel pellets and in a cladding, though the values in the pellets and in the cladding are different. The calculation of the contact load and the clearance along the length of a fuel rod and the stress and strain in each segment is explained. The method adopted in the FREC-4A is simple, and suitable to predict the deformation of fuel rods over their full length. This report is described on the outline of the program, the method of solving the stiffness equations, the calculation models, the input data such as irradiation history, output distribution, material properties and pores, the printing-out of input data and calculated results. (Kako, I.)

  7. Prediction of protein interaction hot spots using rough set-based multiple criteria linear programming.

    Science.gov (United States)

    Chen, Ruoying; Zhang, Zhiwang; Wu, Di; Zhang, Peng; Zhang, Xinyang; Wang, Yong; Shi, Yong

    2011-01-21

    Protein-protein interactions are fundamentally important in many biological processes and it is in pressing need to understand the principles of protein-protein interactions. Mutagenesis studies have found that only a small fraction of surface residues, known as hot spots, are responsible for the physical binding in protein complexes. However, revealing hot spots by mutagenesis experiments are usually time consuming and expensive. In order to complement the experimental efforts, we propose a new computational approach in this paper to predict hot spots. Our method, Rough Set-based Multiple Criteria Linear Programming (RS-MCLP), integrates rough sets theory and multiple criteria linear programming to choose dominant features and computationally predict hot spots. Our approach is benchmarked by a dataset of 904 alanine-mutated residues and the results show that our RS-MCLP method performs better than other methods, e.g., MCLP, Decision Tree, Bayes Net, and the existing HotSprint database. In addition, we reveal several biological insights based on our analysis. We find that four features (the change of accessible surface area, percentage of the change of accessible surface area, size of a residue, and atomic contacts) are critical in predicting hot spots. Furthermore, we find that three residues (Tyr, Trp, and Phe) are abundant in hot spots through analyzing the distribution of amino acids. Copyright © 2010 Elsevier Ltd. All rights reserved.

  8. Genomic Selection Accuracy using Multifamily Prediction Models in a Wheat Breeding Program

    Directory of Open Access Journals (Sweden)

    Elliot L. Heffner

    2011-03-01

    Full Text Available Genomic selection (GS uses genome-wide molecular marker data to predict the genetic value of selection candidates in breeding programs. In plant breeding, the ability to produce large numbers of progeny per cross allows GS to be conducted within each family. However, this approach requires phenotypes of lines from each cross before conducting GS. This will prolong the selection cycle and may result in lower gains per year than approaches that estimate marker-effects with multiple families from previous selection cycles. In this study, phenotypic selection (PS, conventional marker-assisted selection (MAS, and GS prediction accuracy were compared for 13 agronomic traits in a population of 374 winter wheat ( L. advanced-cycle breeding lines. A cross-validation approach that trained and validated prediction accuracy across years was used to evaluate effects of model selection, training population size, and marker density in the presence of genotype × environment interactions (G×E. The average prediction accuracies using GS were 28% greater than with MAS and were 95% as accurate as PS. For net merit, the average accuracy across six selection indices for GS was 14% greater than for PS. These results provide empirical evidence that multifamily GS could increase genetic gain per unit time and cost in plant breeding.

  9. A predictive modeling approach to increasing the economic effectiveness of disease management programs.

    Science.gov (United States)

    Bayerstadler, Andreas; Benstetter, Franz; Heumann, Christian; Winter, Fabian

    2014-09-01

    Predictive Modeling (PM) techniques are gaining importance in the worldwide health insurance business. Modern PM methods are used for customer relationship management, risk evaluation or medical management. This article illustrates a PM approach that enables the economic potential of (cost-) effective disease management programs (DMPs) to be fully exploited by optimized candidate selection as an example of successful data-driven business management. The approach is based on a Generalized Linear Model (GLM) that is easy to apply for health insurance companies. By means of a small portfolio from an emerging country, we show that our GLM approach is stable compared to more sophisticated regression techniques in spite of the difficult data environment. Additionally, we demonstrate for this example of a setting that our model can compete with the expensive solutions offered by professional PM vendors and outperforms non-predictive standard approaches for DMP selection commonly used in the market.

  10. A Pareto-optimal moving average multigene genetic programming model for daily streamflow prediction

    Science.gov (United States)

    Danandeh Mehr, Ali; Kahya, Ercan

    2017-06-01

    Genetic programming (GP) is able to systematically explore alternative model structures of different accuracy and complexity from observed input and output data. The effectiveness of GP in hydrological system identification has been recognized in recent studies. However, selecting a parsimonious (accurate and simple) model from such alternatives still remains a question. This paper proposes a Pareto-optimal moving average multigene genetic programming (MA-MGGP) approach to develop a parsimonious model for single-station streamflow prediction. The three main components of the approach that take us from observed data to a validated model are: (1) data pre-processing, (2) system identification and (3) system simplification. The data pre-processing ingredient uses a simple moving average filter to diminish the lagged prediction effect of stand-alone data-driven models. The multigene ingredient of the model tends to identify the underlying nonlinear system with expressions simpler than classical monolithic GP and, eventually simplification component exploits Pareto front plot to select a parsimonious model through an interactive complexity-efficiency trade-off. The approach was tested using the daily streamflow records from a station on Senoz Stream, Turkey. Comparing to the efficiency results of stand-alone GP, MGGP, and conventional multi linear regression prediction models as benchmarks, the proposed Pareto-optimal MA-MGGP model put forward a parsimonious solution, which has a noteworthy importance of being applied in practice. In addition, the approach allows the user to enter human insight into the problem to examine evolved models and pick the best performing programs out for further analysis.

  11. Gene expression programming for prediction of scour depth downstream of sills

    Science.gov (United States)

    Azamathulla, H. Md.

    2012-08-01

    SummaryLocal scour is crucial in the degradation of river bed and the stability of grade control structures, stilling basins, aprons, ski-jump bucket spillways, bed sills, weirs, check dams, etc. This short communication presents gene-expression programming (GEP), which is an extension to genetic programming (GP), as an alternative approach to predict scour depth downstream of sills. Published data were compiled from the literature for the scour depth downstream of sills. The proposed GEP approach gives satisfactory results (R2 = 0.967 and RMSE = 0.088) compared to the existing predictors (Chinnarasri and Kositgittiwong, 2008) with R2 = 0.87 and RMSE = 2.452 for relative scour depth.

  12. MHA admission criteria and program performance: do they predict career performance?

    Science.gov (United States)

    Porter, J; Galfano, V J

    1987-01-01

    The purpose of this study was to determine to what extent admission criteria predict graduate school and career performance. The study also analyzed which objective and subjective criteria served as the best predictors. MHA graduates of the University of Minnesota from 1974 to 1977 were surveyed to assess career performance. Student files served as the data base on admission criteria and program performance. Career performance was measured by four variables: total compensation, satisfaction, fiscal responsibility, and level of authority. High levels of MHA program performance were associated with women who had high undergraduate GPAs from highly selective undergraduate colleges, were undergraduate business majors, and participated in extracurricular activities. High levels of compensation were associated with relatively low undergraduate GPAs, high levels of participation in undergraduate extracurricular activities, and being single at admission to graduate school. Admission to MHA programs should be based upon both objective and subjective criteria. Emphasis should be placed upon the selection process for MHA students since admission criteria are shown to explain 30 percent of the variability in graduate program performance, and as much as 65 percent of the variance in level of position authority.

  13. Evaluation of Haddam Neck (Connecticut Yankee) Nuclear Power Plant, environmental impact prediction, based on monitoring programs

    International Nuclear Information System (INIS)

    Gore, K.L.; Thomas, J.M.; Kannberg, L.D.; Mahaffey, J.A.; Waton, D.G.

    1976-12-01

    A study was undertaken by the U.S. Nuclear Regulatory Commission (NRC) to evaluate the nonradiological environmental data obtained from three nuclear power plants operating for a period of one year or longer. The document presented reports the second of three nuclear power plants to be evaluated in detail by Battelle, Pacific Northwest Laboratories. Haddam Neck (Connecticut Yankee) Nuclear Power Plant nonradiological monitoring data were assessed to determine their effectiveness in the measurement of environmental impacts. Efforts were made to determine if: (1) monitoring programs, as designed, can detect environmental impacts, (2) appropriate statistical analyses were performed and if they were sensitive enough to detect impacts, (3) predicted impacts could be verified by monitoring programs, and (4) monitoring programs satisfied the requirements of the Environmental Technical Specifications. Both preoperational and operational monitoring data were examined to test the usefulness of baseline information in evaluating impacts. This included an examination of the methods used to measure ecological, chemical, and physical parameters, and an assessment of sampling periodicity and sensitivity where appropriate data sets were available. From this type of analysis, deficiencies in both preoperational and operational monitoring programs may be identified and provide a basis for suggested improvement

  14. Predictive Models of Duration of Ground Delay Programs in New York Area Airports

    Science.gov (United States)

    Kulkarni, Deepak

    2011-01-01

    Initially planned GDP duration often turns out to be an underestimate or an overestimate of the actual GDP duration. This, in turn, results in avoidable airborne or ground delays in the system. Therefore, better models of actual duration have the potential of reducing delays in the system. The overall objective of this study is to develop such models based on logs of GDPs. In a previous report, we described descriptive models of Ground Delay Programs. These models were defined in terms of initial planned duration and in terms of categorical variables. These descriptive models are good at characterizing the historical errors in planned GDP durations. This paper focuses on developing predictive models of GDP duration. Traffic Management Initiatives (TMI) are logged by Air Traffic Control facilities with The National Traffic Management Log (NTML) which is a single system for automated recoding, coordination, and distribution of relevant information about TMIs throughout the National Airspace System. (Brickman, 2004 Yuditsky, 2007) We use 2008-2009 GDP data from the NTML database for the study reported in this paper. NTML information about a GDP includes the initial specification, possibly one or more revisions, and the cancellation. In the next section, we describe general characteristics of Ground Delay Programs. In the third section, we develop models of actual duration. In the fourth section, we compare predictive performance of these models. The final section is a conclusion.

  15. Predicting Workplace Transfer of Learning: A Study of Adult Learners Enrolled in a Continuing Professional Education Training Program

    Science.gov (United States)

    Nafukho, Fredrick Muyia; Alfred, Mary; Chakraborty, Misha; Johnson, Michelle; Cherrstrom, Catherine A.

    2017-01-01

    Purpose: The primary purpose of this study was to predict transfer of learning to workplace among adult learners enrolled in a continuing professional education (CPE) training program, specifically training courses offered through face-to-face, blended and online instruction formats. The study examined the predictive capacity of trainee…

  16. Rapid Prediction of Bacterial Heterotrophic Fluxomics Using Machine Learning and Constraint Programming.

    Directory of Open Access Journals (Sweden)

    Stephen Gang Wu

    2016-04-01

    Full Text Available 13C metabolic flux analysis (13C-MFA has been widely used to measure in vivo enzyme reaction rates (i.e., metabolic flux in microorganisms. Mining the relationship between environmental and genetic factors and metabolic fluxes hidden in existing fluxomic data will lead to predictive models that can significantly accelerate flux quantification. In this paper, we present a web-based platform MFlux (http://mflux.org that predicts the bacterial central metabolism via machine learning, leveraging data from approximately 100 13C-MFA papers on heterotrophic bacterial metabolisms. Three machine learning methods, namely Support Vector Machine (SVM, k-Nearest Neighbors (k-NN, and Decision Tree, were employed to study the sophisticated relationship between influential factors and metabolic fluxes. We performed a grid search of the best parameter set for each algorithm and verified their performance through 10-fold cross validations. SVM yields the highest accuracy among all three algorithms. Further, we employed quadratic programming to adjust flux profiles to satisfy stoichiometric constraints. Multiple case studies have shown that MFlux can reasonably predict fluxomes as a function of bacterial species, substrate types, growth rate, oxygen conditions, and cultivation methods. Due to the interest of studying model organism under particular carbon sources, bias of fluxome in the dataset may limit the applicability of machine learning models. This problem can be resolved after more papers on 13C-MFA are published for non-model species.

  17. Logic programming to predict cell fate patterns and retrodict genotypes in organogenesis.

    Science.gov (United States)

    Hall, Benjamin A; Jackson, Ethan; Hajnal, Alex; Fisher, Jasmin

    2014-09-06

    Caenorhabditis elegans vulval development is a paradigm system for understanding cell differentiation in the process of organogenesis. Through temporal and spatial controls, the fate pattern of six cells is determined by the competition of the LET-23 and the Notch signalling pathways. Modelling cell fate determination in vulval development using state-based models, coupled with formal analysis techniques, has been established as a powerful approach in predicting the outcome of combinations of mutations. However, computing the outcomes of complex and highly concurrent models can become prohibitive. Here, we show how logic programs derived from state machines describing the differentiation of C. elegans vulval precursor cells can increase the speed of prediction by four orders of magnitude relative to previous approaches. Moreover, this increase in speed allows us to infer, or 'retrodict', compatible genomes from cell fate patterns. We exploit this technique to predict highly variable cell fate patterns resulting from dig-1 reduced-function mutations and let-23 mosaics. In addition to the new insights offered, we propose our technique as a platform for aiding the design and analysis of experimental data. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

  18. Establishing a predictive maintenance (PdM) program at the Hanford Site

    International Nuclear Information System (INIS)

    Murray, W.A.; Winslow, R.G.

    1994-02-01

    The production reactors have been shut down for some time. But for the rest of the site, there is currently about 16,000 people engaged in a multi-billion dollar effort to safely process wastes which have been stored at the site since the 1940's. This effort also includes demolition of some older facilities and environmental restoration of much of the site. This is expected to take approximately 30 to 40 years. The concept of a site-wide predictive maintenance (PdM) program began to form in early 1993. Several informal studies showed that the stand alone predictive maintenance groups which had prevailed on site to date were less than 15% effective at trending equipment conditions and predicting failures. To improve the effectiveness of PdM within the company, an engineering analysis by Rick Winslow confirmed that utilization of software networking technology which was now available would significantly overcome many of these built in handicaps. A site-wide predictive maintenance network would make PdM technology accessible to all of the areas and facilities at the site regardless of geographical distances and company division lines. Site resident vibration experts can easily be located and provide consultations on the network. However, it was recognized that strong leadership and management skills would be required within each of the two organizations for effective implementation. To start this process, a letter of understanding and agreement between the facilities and Tank Farm divisions was drafted and endorsed by company management. The agreement assigned the primary responsibility of acquiring the network software and licensee to the Tank Farms division. The acquisition and installation of the network server would be the responsibility of the facilities division. This paper describes the rest of the network development and implementation process

  19. Genetic programming based quantitative structure-retention relationships for the prediction of Kovats retention indices.

    Science.gov (United States)

    Goel, Purva; Bapat, Sanket; Vyas, Renu; Tambe, Amruta; Tambe, Sanjeev S

    2015-11-13

    The development of quantitative structure-retention relationships (QSRR) aims at constructing an appropriate linear/nonlinear model for the prediction of the retention behavior (such as Kovats retention index) of a solute on a chromatographic column. Commonly, multi-linear regression and artificial neural networks are used in the QSRR development in the gas chromatography (GC). In this study, an artificial intelligence based data-driven modeling formalism, namely genetic programming (GP), has been introduced for the development of quantitative structure based models predicting Kovats retention indices (KRI). The novelty of the GP formalism is that given an example dataset, it searches and optimizes both the form (structure) and the parameters of an appropriate linear/nonlinear data-fitting model. Thus, it is not necessary to pre-specify the form of the data-fitting model in the GP-based modeling. These models are also less complex, simple to understand, and easy to deploy. The effectiveness of GP in constructing QSRRs has been demonstrated by developing models predicting KRIs of light hydrocarbons (case study-I) and adamantane derivatives (case study-II). In each case study, two-, three- and four-descriptor models have been developed using the KRI data available in the literature. The results of these studies clearly indicate that the GP-based models possess an excellent KRI prediction accuracy and generalization capability. Specifically, the best performing four-descriptor models in both the case studies have yielded high (>0.9) values of the coefficient of determination (R(2)) and low values of root mean squared error (RMSE) and mean absolute percent error (MAPE) for training, test and validation set data. The characteristic feature of this study is that it introduces a practical and an effective GP-based method for developing QSRRs in gas chromatography that can be gainfully utilized for developing other types of data-driven models in chromatography science

  20. A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy.

    Science.gov (United States)

    Ji, Zhiwei; Wang, Bing; Yan, Ke; Dong, Ligang; Meng, Guanmin; Shi, Lei

    2017-12-21

    In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc. In this study, we developed a Ternary status based Integer Linear Programming (TILP) method to infer cell-specific signaling pathway network and predict compounds' treatment efficacy. The novelty of our study is that phosphor-proteomic data and prior knowledge are combined for modeling and optimizing the signaling network. To test the power of our approach, a generic pathway network was constructed for a human breast cancer cell line MCF7; and the TILP model was used to infer MCF7-specific pathways with a set of phosphor-proteomic data collected from ten representative small molecule chemical compounds (most of them were studied in breast cancer treatment). Cross-validation indicated that the MCF7-specific pathway network inferred by TILP were reliable predicting a compound's efficacy. Finally, we applied TILP to re-optimize the inferred cell-specific pathways and predict the outcomes of five small compounds (carmustine, doxorubicin, GW-8510, daunorubicin, and verapamil), which were rarely used in clinic for breast cancer. In the simulation, the proposed approach facilitates us to identify a compound's treatment efficacy qualitatively and quantitatively, and the cross validation analysis indicated good accuracy in predicting effects of five compounds. In summary, the TILP model is useful for discovering new drugs for clinic use, and also elucidating the potential mechanisms of a compound to targets.

  1. Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

    Science.gov (United States)

    Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

    2015-03-01

    A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Prediction methodologies for target scene generation in the aerothermal targets analysis program (ATAP)

    Science.gov (United States)

    Hudson, Douglas J.; Torres, Manuel; Dougherty, Catherine; Rajendran, Natesan; Thompson, Rhoe A.

    2003-09-01

    The Air Force Research Laboratory (AFRL) Aerothermal Targets Analysis Program (ATAP) is a user-friendly, engineering-level computational tool that features integrated aerodynamics, six-degree-of-freedom (6-DoF) trajectory/motion, convective and radiative heat transfer, and thermal/material response to provide an optimal blend of accuracy and speed for design and analysis applications. ATAP is sponsored by the Kinetic Kill Vehicle Hardware-in-the-Loop Simulator (KHILS) facility at Eglin AFB, where it is used with the CHAMP (Composite Hardbody and Missile Plume) technique for rapid infrared (IR) signature and imagery predictions. ATAP capabilities include an integrated 1-D conduction model for up to 5 in-depth material layers (with options for gaps/voids with radiative heat transfer), fin modeling, several surface ablation modeling options, a materials library with over 250 materials, options for user-defined materials, selectable/definable atmosphere and earth models, multiple trajectory options, and an array of aerodynamic prediction methods. All major code modeling features have been validated with ground-test data from wind tunnels, shock tubes, and ballistics ranges, and flight-test data for both U.S. and foreign strategic and theater systems. Numerous applications include the design and analysis of interceptors, booster and shroud configurations, window environments, tactical missiles, and reentry vehicles.

  3. Integrating genomics and proteomics data to predict drug effects using binary linear programming.

    Science.gov (United States)

    Ji, Zhiwei; Su, Jing; Liu, Chenglin; Wang, Hongyan; Huang, Deshuang; Zhou, Xiaobo

    2014-01-01

    The Library of Integrated Network-Based Cellular Signatures (LINCS) project aims to create a network-based understanding of biology by cataloging changes in gene expression and signal transduction that occur when cells are exposed to a variety of perturbations. It is helpful for understanding cell pathways and facilitating drug discovery. Here, we developed a novel approach to infer cell-specific pathways and identify a compound's effects using gene expression and phosphoproteomics data under treatments with different compounds. Gene expression data were employed to infer potential targets of compounds and create a generic pathway map. Binary linear programming (BLP) was then developed to optimize the generic pathway topology based on the mid-stage signaling response of phosphorylation. To demonstrate effectiveness of this approach, we built a generic pathway map for the MCF7 breast cancer cell line and inferred the cell-specific pathways by BLP. The first group of 11 compounds was utilized to optimize the generic pathways, and then 4 compounds were used to identify effects based on the inferred cell-specific pathways. Cross-validation indicated that the cell-specific pathways reliably predicted a compound's effects. Finally, we applied BLP to re-optimize the cell-specific pathways to predict the effects of 4 compounds (trichostatin A, MS-275, staurosporine, and digoxigenin) according to compound-induced topological alterations. Trichostatin A and MS-275 (both HDAC inhibitors) inhibited the downstream pathway of HDAC1 and caused cell growth arrest via activation of p53 and p21; the effects of digoxigenin were totally opposite. Staurosporine blocked the cell cycle via p53 and p21, but also promoted cell growth via activated HDAC1 and its downstream pathway. Our approach was also applied to the PC3 prostate cancer cell line, and the cross-validation analysis showed very good accuracy in predicting effects of 4 compounds. In summary, our computational model can be

  4. A dynamic food-chain model and program for predicting the radiological consequences of nuclear accident

    International Nuclear Information System (INIS)

    Hu Erbang; Gao Zhanrong; Zhang Heyuan; Wei Weiqiang

    1996-12-01

    A dynamic food-chain model and program, DYFOM-95, for predicting the radiological consequences of nuclear accident has been developed, which is not only suitable to the West food-chain but also to Chinese food chain. The following processes, caused by accident release which will make an impact on radionuclide concentration in the edible parts of vegetable are considered: dry and wet deposition interception and initial retention, translocation, percolation, root uptake and tillage. Activity intake rate of animals, effects of processing and activity intake of human through ingestion pathway are also considered in calculations. The effects of leaf area index LAI of vegetable are considered in dry deposition model. A method for calculating the contribution of rain with different period and different intensity to total wet deposition is established. The program contains 1 main code and 5 sub-codes to calculate dry and wet deposition on surface of vegetable and soil, translocation of nuclides in vegetable, nuclide concentration in the edible parts of vegetable and in animal products and activity intake of human and so on. (24 refs., 9 figs., 11 tabs.)

  5. Identification of cognitive and non-cognitive predictive variables related to attrition in baccalaureate nursing education programs in Mississippi

    Science.gov (United States)

    Hayes, Catherine

    2005-07-01

    This study sought to identify a variable or variables predictive of attrition among baccalaureate nursing students. The study was quantitative in design and multivariate correlational statistics and discriminant statistical analysis were used to identify a model for prediction of attrition. The analysis then weighted variables according to their predictive value to determine the most parsimonious model with the greatest predictive value. Three public university nursing education programs in Mississippi offering a Bachelors Degree in Nursing were selected for the study. The population consisted of students accepted and enrolled in these three programs for the years 2001 and 2002 and graduating in the years 2003 and 2004 (N = 195). The categorical dependent variable was attrition (includes academic failure or withdrawal) from the program of nursing education. The ten independent variables selected for the study and considered to have possible predictive value were: Grade Point Average for Pre-requisite Course Work; ACT Composite Score, ACT Reading Subscore, and ACT Mathematics Subscore; Letter Grades in the Courses: Anatomy & Physiology and Lab I, Algebra I, English I (101), Chemistry & Lab I, and Microbiology & Lab I; and Number of Institutions Attended (Universities, Colleges, Junior Colleges or Community Colleges). Descriptive analysis was performed and the means of each of the ten independent variables was compared for students who attrited and those who were retained in the population. The discriminant statistical analysis performed created a matrix using the ten variable model that was able to correctly predicted attrition in the study's population in 77.6% of the cases. Variables were then combined and recombined to produce the most efficient and parsimonious model for prediction. A six variable model resulted which weighted each variable according to predictive value: GPA for Prerequisite Coursework, ACT Composite, English I, Chemistry & Lab I, Microbiology

  6. Reliability of nine programs of topological predictions and their application to integral membrane channel and carrier proteins.

    Science.gov (United States)

    Reddy, Abhinay; Cho, Jaehoon; Ling, Sam; Reddy, Vamsee; Shlykov, Maksim; Saier, Milton H

    2014-01-01

    We evaluated topological predictions for nine different programs, HMMTOP, TMHMM, SVMTOP, DAS, SOSUI, TOPCONS, PHOBIUS, MEMSAT-SVM (hereinafter referred to as MEMSAT), and SPOCTOPUS. These programs were first evaluated using four large topologically well-defined families of secondary transporters, and the three best programs were further evaluated using topologically more diverse families of channels and carriers. In the initial studies, the order of accuracy was: SPOCTOPUS > MEMSAT > HMMTOP > TOPCONS > PHOBIUS > TMHMM > SVMTOP > DAS > SOSUI. Some families, such as the Sugar Porter Family (2.A.1.1) of the Major Facilitator Superfamily (MFS; TC #2.A.1) and the Amino Acid/Polyamine/Organocation (APC) Family (TC #2.A.3), were correctly predicted with high accuracy while others, such as the Mitochondrial Carrier (MC) (TC #2.A.29) and the K(+) transporter (Trk) families (TC #2.A.38), were predicted with much lower accuracy. For small, topologically homogeneous families, SPOCTOPUS and MEMSAT were generally most reliable, while with large, more diverse superfamilies, HMMTOP often proved to have the greatest prediction accuracy. We next developed a novel program, TM-STATS, that tabulates HMMTOP, SPOCTOPUS or MEMSAT-based topological predictions for any subdivision (class, subclass, superfamily, family, subfamily, or any combination of these) of the Transporter Classification Database (TCDB; www.tcdb.org) and examined the following subclasses: α-type channel proteins (TC subclasses 1.A and 1.E), secreted pore-forming toxins (TC subclass 1.C) and secondary carriers (subclass 2.A). Histograms were generated for each of these subclasses, and the results were analyzed according to subclass, family and protein. The results provide an update of topological predictions for integral membrane transport proteins as well as guides for the development of more reliable topological prediction programs, taking family-specific characteristics into account. © 2014 S. Karger AG, Basel.

  7. Augmenting Predictive Modeling Tools with Clinical Insights for Care Coordination Program Design and Implementation.

    Science.gov (United States)

    Johnson, Tracy L; Brewer, Daniel; Estacio, Raymond; Vlasimsky, Tara; Durfee, Michael J; Thompson, Kathy R; Everhart, Rachel M; Rinehart, Deborath J; Batal, Holly

    2015-01-01

    The Center for Medicare and Medicaid Innovation (CMMI) awarded Denver Health's (DH) integrated, safety net health care system $19.8 million to implement a "population health" approach into the delivery of primary care. This major practice transformation builds on the Patient Centered Medical Home (PCMH) and Wagner's Chronic Care Model (CCM) to achieve the "Triple Aim": improved health for populations, care to individuals, and lower per capita costs. This paper presents a case study of how DH integrated published predictive models and front-line clinical judgment to implement a clinically actionable, risk stratification of patients. This population segmentation approach was used to deploy enhanced care team staff resources and to tailor care-management services to patient need, especially for patients at high risk of avoidable hospitalization. Developing, implementing, and gaining clinical acceptance of the Health Information Technology (HIT) solution for patient risk stratification was a major grant objective. In addition to describing the Information Technology (IT) solution itself, we focus on the leadership and organizational processes that facilitated its multidisciplinary development and ongoing iterative refinement, including the following: team composition, target population definition, algorithm rule development, performance assessment, and clinical-workflow optimization. We provide examples of how dynamic business intelligence tools facilitated clinical accessibility for program design decisions by enabling real-time data views from a population perspective down to patient-specific variables. We conclude that population segmentation approaches that integrate clinical perspectives with predictive modeling results can better identify high opportunity patients amenable to medical home-based, enhanced care team interventions.

  8. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff

    Science.gov (United States)

    Cingolani, Pablo; Platts, Adrian; Wang, Le Lily; Coon, Melissa; Nguyen, Tung; Wang, Luan; Land, Susan J.; Lu, Xiangyi; Ruden, Douglas M.

    2012-01-01

    We describe a new computer program, SnpEff, for rapidly categorizing the effects of variants in genome sequences. Once a genome is sequenced, SnpEff annotates variants based on their genomic locations and predicts coding effects. Annotated genomic locations include intronic, untranslated region, upstream, downstream, splice site, or intergenic regions. Coding effects such as synonymous or non-synonymous amino acid replacement, start codon gains or losses, stop codon gains or losses, or frame shifts can be predicted. Here the use of SnpEff is illustrated by annotating ~356,660 candidate SNPs in ~117 Mb unique sequences, representing a substitution rate of ~1/305 nucleotides, between the Drosophila melanogaster w1118; iso-2; iso-3 strain and the reference y1; cn1 bw1 sp1 strain. We show that ~15,842 SNPs are synonymous and ~4,467 SNPs are non-synonymous (N/S ~0.28). The remaining SNPs are in other categories, such as stop codon gains (38 SNPs), stop codon losses (8 SNPs), and start codon gains (297 SNPs) in the 5′UTR. We found, as expected, that the SNP frequency is proportional to the recombination frequency (i.e., highest in the middle of chromosome arms). We also found that start-gain or stop-lost SNPs in Drosophila melanogaster often result in additions of N-terminal or C-terminal amino acids that are conserved in other Drosophila species. It appears that the 5′ and 3′ UTRs are reservoirs for genetic variations that changes the termini of proteins during evolution of the Drosophila genus. As genome sequencing is becoming inexpensive and routine, SnpEff enables rapid analyses of whole-genome sequencing data to be performed by an individual laboratory. PMID:22728672

  9. Predicting the performance of a strategic alliance: an analysis of the Community Clinical Oncology Program.

    Science.gov (United States)

    Kaluzny, A D; Lacey, L M; Warnecke, R; Hynes, D M; Morrissey, J; Ford, L; Sondik, E

    1993-06-01

    This study is designed to examine the effects of environment and structure of the Community Clinical Oncology Program (CCOP) on performance as measured by patient accrual to National Cancer Institute (NCI)-approved treatment protocols. Data and analysis are part of a larger evaluation of the NCI Community Clinical Oncology Program during its second funding cycle, June 1987-May 1990. Data, taken from primary and secondary sources, included a survey of selected informants in CCOPs and research bases, CCOP grant applications, CCOP annual progress reports, and site visits to a subsample of CCOPs (N = 20) and research bases (N = 5). Accrual data were obtained from NCI records. Analysis involved three complementary sets of factors: the local health care resources environment available to the CCOP, the larger policy environment as reflected by the relationship of the CCOP to selected research bases and the NCI, and the operational structure of the CCOP itself. A hierarchical model examined the separate and cumulative effects of local and policy environment and structure on performance. Other things equal, the primary predictors of treatment accrual were: (1) the larger policy environment, as measured by the attendance of nurses at research base meetings; and (2) operational structure, as measured by the number and character of components within participating CCOPs and the number of hours per week worked by data managers. These factors explained 73 percent of the total variance in accrual performance. Findings suggest criteria for selecting the types of organizations to participate in the alliance, as well as for establishing guidelines for managing such alliances. A future challenge is to determine the extent to which factors predicting accrual to cancer treatment clinical trials are equally important as predictors of accrual to cancer prevention and control trials.

  10. Evaluation of nuclear power plant environmental impact prediction, based on monitoring programs. Summary and recommendations

    International Nuclear Information System (INIS)

    Gore, K.L.; Thomas, J.M.; Kannberg, L.D.; Watson, D.G.

    1977-02-01

    An evaluation of the effectivenss of non-radiological environmental monitoring programs is presented. The monitoring programs for Monticello, Haddam Neck, and Millstone Nuclear Generating Plants are discussed. Recommendations for improvements in monitoring programs are presented

  11. Predicting temperature drop rate of mass concrete during an initial cooling period using genetic programming

    Science.gov (United States)

    Bhattarai, Santosh; Zhou, Yihong; Zhao, Chunju; Zhou, Huawei

    2018-02-01

    Thermal cracking on concrete dams depends upon the rate at which the concrete is cooled (temperature drop rate per day) within an initial cooling period during the construction phase. Thus, in order to control the thermal cracking of such structure, temperature development due to heat of hydration of cement should be dropped at suitable rate. In this study, an attempt have been made to formulate the relation between cooling rate of mass concrete with passage of time (age of concrete) and water cooling parameters: flow rate and inlet temperature of cooling water. Data measured at summer season (April-August from 2009 to 2012) from recently constructed high concrete dam were used to derive a prediction model with the help of Genetic Programming (GP) software “Eureqa”. Coefficient of Determination (R) and Mean Square Error (MSE) were used to evaluate the performance of the model. The value of R and MSE is 0.8855 and 0.002961 respectively. Sensitivity analysis was performed to evaluate the relative impact on the target parameter due to input parameters. Further, testing the proposed model with an independent dataset those not included during analysis, results obtained from the proposed GP model are close enough to the real field data.

  12. Accuracy of Genomic Prediction in a Commercial Perennial Ryegrass Breeding Program

    Directory of Open Access Journals (Sweden)

    Dario Fè

    2016-11-01

    Full Text Available The implementation of genomic selection (GS in plant breeding, so far, has been mainly evaluated in crops farmed as homogeneous varieties, and the results have been generally positive. Fewer results are available for species, such as forage grasses, that are grown as heterogenous families (developed from multiparent crosses in which the control of the genetic variation is far more complex. Here we test the potential for implementing GS in the breeding of perennial ryegrass ( L. using empirical data from a commercial forage breeding program. Biparental F and multiparental synthetic (SYN families of diploid perennial ryegrass were genotyped using genotyping-by-sequencing, and phenotypes for five different traits were analyzed. Genotypes were expressed as family allele frequencies, and phenotypes were recorded as family means. Different models for genomic prediction were compared by using practically relevant cross-validation strategies. All traits showed a highly significant level of genetic variance, which could be traced using the genotyping assay. While there was significant genotype × environment (G × E interaction for some traits, accuracies were high among F families and between biparental F and multiparental SYN families. We have demonstrated that the implementation of GS in grass breeding is now possible and presents an opportunity to make significant gains for various traits.

  13. Prenatal attitudes and parity predict selection into a U.S. child health program: a short report.

    Science.gov (United States)

    Martin-Anderson, Sarah

    2013-10-01

    Public policies are a determinant of child health disparities; sound evaluation of these programs is essential for good governance. It is impossible in most countries to randomize assignment into child health programs that directly offer benefits. In the absence of this, researchers face the threat of selection bias-the idea that there are innate, immeasurable differences between those who take-up treatment and those who don't. In the field of Program Evaluation we are most concerned with the differences between the eligible people who take-up a program and the eligible people who choose not to enroll. Using a case study of a large U.S. nutrition program, this report illustrates how the perceived benefits of participation may affect the decision to take-up a program. In turn, this highlights sources of potential selection bias. Using data from a longitudinal study of mothers and infants conducted between May and December of 2005, I show that attitudes and beliefs prenatally toward breastfeeding determine enrollment in a U.S nutrition program that offers free Infant Formula. I also find that the significance of the selection bias differs by parity. Analysis reveals that maternal attitudinal responses are more highly predictive of future behavior, compared to standard demographic variables. In sum, this paper makes a case for rigorously understanding the factors that determine take-up of a program and how those factors can modify the results of a program evaluation. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

    KAUST Repository

    Kouramas, K.I.; Faí sca, N.P.; Panos, C.; Pistikopoulos, E.N.

    2011-01-01

    This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques

  15. Quality of life predicts outcome in a heart failure disease management program.

    LENUS (Irish Health Repository)

    O'Loughlin, Christina

    2012-02-01

    BACKGROUND: Chronic heart failure (HF) is associated with a poor Health Related Quality of Life (HRQoL). HRQoL has been shown to be a predictor of HF outcomes however, variability in the study designs make it difficult to apply these findings to a clinical setting. The aim of this study was to establish if HRQoL is a predictor of long-term mortality and morbidity in HF patients followed-up in a disease management program (DMP) and if a HRQoL instrument could be applied to aid in identifying high-risk patients within a clinical context. METHODS: This is a retrospective analysis of HF patients attending a DMP with 18+\\/-9 months follow-up. Clinical and biochemical parameters were recorded on discharge from index HF admission and HRQoL measures were recorded at 2 weeks post index admission. RESULTS: 225 patients were enrolled into the study (mean age=69+\\/-12 years, male=61%, and 78%=systolic HF). In multivariable analysis, all dimensions of HRQoL (measured by the Minnesota Living with HF Questionnaire) were independent predictors of both mortality and readmissions particularly in patients <80 years. A significant interaction between HRQoL and age (Total((HRQoL))age: p<0.001) indicated that the association of HRQoL with outcomes diminished as age increased. CONCLUSIONS: These data demonstrate that HRQoL is a predictor of outcome in HF patients managed in a DMP. Younger patients (<65 years) with a Total HRQoL score of > or =50 are at high risk of an adverse outcome. In older patients > or =80 years HRQoL is not useful in predicting outcome.

  16. Grading Prediction of Enterprise Financial Crisis Based on Nonlinear Programming Evaluation: A Case Study of Chinese Transportation Industry

    Directory of Open Access Journals (Sweden)

    Zhi-yuan Li

    2014-01-01

    Full Text Available As the core of the effective financial crisis prevention, enterprise finance crisis prediction has been the focal attention of both theorists and businessmen. Financial crisis predictions need to apply a variety of financial and operating indicators for its analysis. Therefore, a new evaluation model based on nonlinear programming is established, the nature of the model is proved, the detailed solution steps of the model are given, and the significance and algorithm of the model are thoroughly discussed in this study. The proposed model can deal with the case of missing data, and has the good isotonic property and profound theoretical background. In the empirical analysis to predict the financial crisis and through the comparison of the analysis of historical data and the real enterprises with financial crisis, we find that the results are in accordance with the real enterprise financial conditions and the proposed model has a good predictive ability.

  17. Frequency Domain Computer Programs for Prediction and Analysis of Rail Vehicle Dynamics : Volume 1. Technical Report

    Science.gov (United States)

    1975-12-01

    Frequency domain computer programs developed or acquired by TSC for the analysis of rail vehicle dynamics are described in two volumes. Volume I defines the general analytical capabilities required for computer programs applicable to single rail vehi...

  18. Genomic prediction in early selection stages using multi-year data in a hybrid rye breeding program.

    Science.gov (United States)

    Bernal-Vasquez, Angela-Maria; Gordillo, Andres; Schmidt, Malthe; Piepho, Hans-Peter

    2017-05-31

    The use of multiple genetic backgrounds across years is appealing for genomic prediction (GP) because past years' data provide valuable information on marker effects. Nonetheless, single-year GP models are less complex and computationally less demanding than multi-year GP models. In devising a suitable analysis strategy for multi-year data, we may exploit the fact that even if there is no replication of genotypes across years, there is plenty of replication at the level of marker loci. Our principal aim was to evaluate different GP approaches to simultaneously model genotype-by-year (GY) effects and breeding values using multi-year data in terms of predictive ability. The models were evaluated under different scenarios reflecting common practice in plant breeding programs, such as different degrees of relatedness between training and validation sets, and using a selected fraction of genotypes in the training set. We used empirical grain yield data of a rye hybrid breeding program. A detailed description of the prediction approaches highlighting the use of kinship for modeling GY is presented. Using the kinship to model GY was advantageous in particular for datasets disconnected across years. On average, predictive abilities were 5% higher for models using kinship to model GY over models without kinship. We confirmed that using data from multiple selection stages provides valuable GY information and helps increasing predictive ability. This increase is on average 30% higher when the predicted genotypes are closely related with the genotypes in the training set. A selection of top-yielding genotypes together with the use of kinship to model GY improves the predictive ability in datasets composed of single years of several selection cycles. Our results clearly demonstrate that the use of multi-year data and appropriate modeling is beneficial for GP because it allows dissecting GY effects from genomic estimated breeding values. The model choice, as well as ensuring

  19. Ethical dilemmas in genetic testing: examples from the Cuban program for predictive diagnosis of hereditary ataxias.

    Science.gov (United States)

    Mariño, Tania Cruz; Armiñán, Rubén Reynaldo; Cedeño, Humberto Jorge; Mesa, José Miguel Laffita; Zaldivar, Yanetza González; Rodríguez, Raúl Aguilera; Santos, Miguel Velázquez; Mederos, Luis Enrique Almaguer; Herrera, Milena Paneque; Pérez, Luis Velázquez

    2011-06-01

    Predictive testing protocols are intended to help patients affected with hereditary conditions understand their condition and make informed reproductive choices. However, predictive protocols may expose clinicians and patients to ethical dilemmas that interfere with genetic counseling and the decision making process. This paper describes ethical dilemmas in a series of five cases involving predictive testing for hereditary ataxias in Cuba. The examples herein present evidence of the deeply controversial situations faced by both individuals at risk and professionals in charge of these predictive studies, suggesting a need for expanded guidelines to address such complexities.

  20. Cancer predictive value of cytogenetic markers used in occupational health surveillance programs

    DEFF Research Database (Denmark)

    Hagmar, L; Bonassi, S; Strömberg, U

    1998-01-01

    It has not previously been clear whether cytogenetic biomarkers in healthy subjects will predict cancer. Earlier analyses of a Nordic and an Italian cohort indicated predictivity for chromosomal aberrations (CAS) but not for sister chromatid exchanges (SCES). A pooled analysis of the updated......, occupational exposures and smoking, will be assessed in a case-referent study within the study base....

  1. Evaluation of Millstone Nuclear Power Plant, Environmental Impact prediction, based on monitoring programs

    International Nuclear Information System (INIS)

    Gore, K.L.; Thomas, J.M.; Kannberg, L.D.; Watson, D.G.

    1977-02-01

    This report evaluates the nonradiological monitoring program at Millstone Nuclear Power Plant. Both operational as well as preoperational monitoring programs were analyzed to produce long-term (5 yr or longer) data sets, where possible. In order to determine the effectiveness of these monitoring programs, the appropriate data sets have to be analyzed by the appropriate statistical analysis. Thus, both open literature and current statistical analysis being developed at Pacific Northwest Laboratories (PNL) were employed in data analysis

  2. Evaluation of Millstone Nuclear Power Plant, Environmental Impact prediction, based on monitoring programs

    Energy Technology Data Exchange (ETDEWEB)

    Gore, K.L.; Thomas, J.M.; Kannberg, L.D.; Watson, D.G.

    1977-02-01

    This report evaluates the nonradiological monitoring program at Millstone Nuclear Power Plant. Both operational as well as preoperational monitoring programs were analyzed to produce long-term (5 yr or longer) data sets, where possible. In order to determine the effectiveness of these monitoring programs, the appropriate data sets have to be analyzed by the appropriate statistical analysis. Thus, both open literature and current statistical analysis being developed at Pacific Northwest Laboratories (PNL) were employed in data analysis.

  3. Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

    International Nuclear Information System (INIS)

    Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor

    2017-01-01

    Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the

  4. Development of a Program for Predicting Flow Instability in a Once-through Sodium-Heated Steam Generator (III)

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Eui Kwang; Yoon, Jung; Kim, Jong Bum; Jeong, Jiyoung [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2016-10-15

    Two-phase flow systems can be subjected to several types of instability problems. Density-wave oscillation is the most common and important type of instability in boiling channels. Such instability gives difficulties in predictions of system performance and system control, and component failure due to thermal fatigue. A computer program developed for predicting two-phase flow instability in a steam generator heated by liquid sodium was presented in the previous works. Limit cycle was predicted even in a fixed node system. The amplitude of inlet flow rate is larger than that of outlet flow rate. The amplitude of phase change location oscillation within boiling-to-vapor boundary node is larger than that of liquid-to-boiling boundary node. Sodium and steam temperature are invariant at tube exit.

  5. Attending to Structural Programming Features Predicts Differences in Learning and Motivation

    Science.gov (United States)

    Witherspoon, Eben B.; Schunn, Christian D.; Higashi, Ross M.; Shoop, Robin

    2018-01-01

    Educational robotics programs offer an engaging opportunity to potentially teach core computer science concepts and practices in K-12 classrooms. Here, we test the effects of units with different programming content within a virtual robotics context on both learning gains and motivational changes in middle school (6th-8th grade) robotics…

  6. MARKETING PREDICTIONS IN ANTI-DRUG SOCIAL PROGRAMS: USE OF CAUSAL METHODS IN THE STUDY AND PREVENTION OF DRUG ABUSE

    Directory of Open Access Journals (Sweden)

    Serban Corina

    2010-12-01

    Full Text Available Drug use is one of the major challenges that todays society faces; its effects are felt at the level of various social, professional and age categories. Over 50 non-profit organizations are involved in the development of anti-drug social programs in Romania. Their role is to improve the degree of awareness of the target population concerning the risks associated with drug use, but also to steer consumers towards healthy areas, beneficial to their future. This paper aims to detail the issue of drug use in Romania, by making predictions based on the evolution of this phenomenon during the next five years. The obtained results have revealed the necessity to increase the number of programs preventing drug use, aswell as the need to continue social programs that have proved effective in previous years.

  7. Predicting Ranger Assessment and Selection Program 1 Success and Optimizing Class Composition

    Science.gov (United States)

    2017-06-01

    Healthcare Specialist) 149 150 68X ( Mental Health Specialist) 1 74 74D (Chemical Operations Specialist) 15 15 88 88M (Motor Transport Operator) 27 27 89...regression and partition tree models to identify significant factors that contribute to a candidate’s success at RASP1 and predict graduation rates. We...tree models to identify significant factors that contribute to a candidate’s success at RASP1 and predict graduation rates. We use an integer linear

  8. A general strategy for performing temperature-programming in high performance liquid chromatography--prediction of segmented temperature gradients.

    Science.gov (United States)

    Wiese, Steffen; Teutenberg, Thorsten; Schmidt, Torsten C

    2011-09-28

    In the present work it is shown that the linear elution strength (LES) model which was adapted from temperature-programming gas chromatography (GC) can also be employed to predict retention times for segmented-temperature gradients based on temperature-gradient input data in liquid chromatography (LC) with high accuracy. The LES model assumes that retention times for isothermal separations can be predicted based on two temperature gradients and is employed to calculate the retention factor of an analyte when changing the start temperature of the temperature gradient. In this study it was investigated whether this approach can also be employed in LC. It was shown that this approximation cannot be transferred to temperature-programmed LC where a temperature range from 60°C up to 180°C is investigated. Major relative errors up to 169.6% were observed for isothermal retention factor predictions. In order to predict retention times for temperature gradients with different start temperatures in LC, another relationship is required to describe the influence of temperature on retention. Therefore, retention times for isothermal separations based on isothermal input runs were predicted using a plot of the natural logarithm of the retention factor vs. the inverse temperature and a plot of the natural logarithm of the retention factor vs. temperature. It could be shown that a plot of lnk vs. T yields more reliable isothermal/isocratic retention time predictions than a plot of lnk vs. 1/T which is usually employed. Hence, in order to predict retention times for temperature-gradients with different start temperatures in LC, two temperature gradient and two isothermal measurements have been employed. In this case, retention times can be predicted with a maximal relative error of 5.5% (average relative error: 2.9%). In comparison, if the start temperature of the simulated temperature gradient is equal to the start temperature of the input data, only two temperature

  9. Ability of commercially available dairy ration programs to predict duodenal flows of protein and essential amino acids in dairy cows.

    Science.gov (United States)

    Pacheco, D; Patton, R A; Parys, C; Lapierre, H

    2012-02-01

    The objective of this analysis was to compare the rumen submodel predictions of 4 commonly used dairy ration programs to observed values of duodenal flows of crude protein (CP), protein fractions, and essential AA (EAA). The literature was searched and 40 studies, including 154 diets, were used to compare observed values with those predicted by AminoCow (AC), Agricultural Modeling and Training Systems (AMTS), Cornell-Penn-Miner (CPM), and National Research Council 2001 (NRC) models. The models were evaluated based on their ability to predict the mean, their root mean square prediction error (RMSPE), error bias, and adequacy of regression equations for each protein fraction. The models predicted the mean duodenal CP flow within 5%, with more than 90% of the variation due to random disturbance. The models also predicted within 5% the mean microbial CP flow except CPM, which overestimated it by 27%. Only NRC, however, predicted mean rumen-undegraded protein (RUP) flows within 5%, whereas AC and AMTS underpredicted it by 8 to 9% and CPM by 24%. Regarding duodenal flows of individual AA, across all diets, CPM predicted substantially greater (>10%) mean flows of Arg, His, Ile, Met, and Lys; AMTS predicted greater flow for Arg and Met, whereas AC and NRC estimations were, on average, within 10% of observed values. Overpredictions by the CPM model were mainly related to mean bias, whereas the NRC model had the highest proportion of bias in random disturbance for flows of EAA. Models tended to predict mean flows of EAA more accurately on corn silage and alfalfa diets than on grass-based diets, more accurately on corn grain-based diets than on non-corn-based diets, and finally more accurately in the mid range of diet types. The 4 models were accurate at predicting mean dry matter intake. The AC, AMTS, and NRC models were all sufficiently accurate to be used for balancing EAA in dairy rations under field conditions. Copyright © 2012 American Dairy Science Association

  10. Can Thrifty Gene(s or Predictive Fetal Programming for Thriftiness Lead to Obesity?

    Directory of Open Access Journals (Sweden)

    Ulfat Baig

    2011-01-01

    Full Text Available Obesity and related disorders are thought to have their roots in metabolic “thriftiness” that evolved to combat periodic starvation. The association of low birth weight with obesity in later life caused a shift in the concept from thrifty gene to thrifty phenotype or anticipatory fetal programming. The assumption of thriftiness is implicit in obesity research. We examine here, with the help of a mathematical model, the conditions for evolution of thrifty genes or fetal programming for thriftiness. The model suggests that a thrifty gene cannot exist in a stable polymorphic state in a population. The conditions for evolution of thrifty fetal programming are restricted if the correlation between intrauterine and lifetime conditions is poor. Such a correlation is not observed in natural courses of famine. If there is fetal programming for thriftiness, it could have evolved in anticipation of social factors affecting nutrition that can result in a positive correlation.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-10-18

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

  12. Application of numerical analysis technique to make up for pipe wall thinning prediction program

    International Nuclear Information System (INIS)

    Hwang, Kyeong Mo; Jin, Tae Eun; Park, Won; Oh, Dong Hoon

    2009-01-01

    Flow Accelerated Corrosion (FAC) leads to wall thinning of steel piping exposed to flowing water or wet steam. Experience has shown that FAC damage to piping at fossil and nuclear plants can lead to costly outages and repairs and can affect plant reliability and safety. CHEWORKS have been utilized in domestic nuclear plants as a predictive tool to assist FAC engineers in planning inspections and evaluating the inspection data to prevent piping failures caused by FAC. However, CHECWORKS may be occasionally left out local susceptible portions owing to predicting FAC damage by pipeline group after constructing a database for all secondary side piping in nuclear plants. This paper describes the methodologies that can complement CHECWORKS and the verifications of the CHECWORKS prediction results in terms of numerical analysis. FAC susceptible locations based on CHECWORKS for the two pipeline groups of a nuclear plant was compared with those of numerical analysis based on FLUENT.

  13. Supplementation of Flow Accelerated Corrosion Prediction Program Using Numerical Analysis Technique

    International Nuclear Information System (INIS)

    Hwang, Kyeong Mo; Jin, Tae Eun; Park, Won; Oh, Dong Hoon

    2010-01-01

    Flow-accelerated corrosion (FAC) leads to thinning of steel pipe walls that are exposed to flowing water or wet steam. From experience, it is seen that FAC damage to piping at fossil and nuclear plants can result in outages that require expensive repairs and can affect plant reliability and safety. CHECWORKS have been utilized in domestic nuclear plants as a predictive tool to assist FAC engineers in planning inspections and evaluating the inspection data so that piping failures caused by FAC can be prevented. However, CHECWORKS may be occasionally ignore local susceptible portions when predicting FAC damage in a group of pipelines after constructing a database for all the secondary side piping in nuclear plants. This paper describes the methodologies that can complement CHECWORKS and the verifications of CHECWORKS prediction results using numerical analysis. FAC susceptible locations determined using CHECWORKS for two pipeline groups of a nuclear plant was compared with determined using the numerical-analysis-based FLUENT

  14. Computer program for prediction of the deposition of material released from fixed and rotary wing aircraft

    Science.gov (United States)

    Teske, M. E.

    1984-01-01

    This is a user manual for the computer code ""AGDISP'' (AGricultural DISPersal) which has been developed to predict the deposition of material released from fixed and rotary wing aircraft in a single-pass, computationally efficient manner. The formulation of the code is novel in that the mean particle trajectory and the variance about the mean resulting from turbulent fluid fluctuations are simultaneously predicted. The code presently includes the capability of assessing the influence of neutral atmospheric conditions, inviscid wake vortices, particle evaporation, plant canopy and terrain on the deposition pattern.

  15. Factors predicting health practitioners' awareness of UNHS program in Malaysian non-public hospitals.

    Science.gov (United States)

    Ismail, Abdussalaam Iyanda; Abdul Majid, Abdul Halim; Zakaria, Mohd Normani; Abdullah, Nor Azimah Chew; Hamzah, Sulaiman; Mukari, Siti Zamratol-Mai Sarah

    2018-06-01

    The current study aims to examine the effects of human resource (measured with the perception of health workers' perception towards UNHS), screening equipment, program layout and screening techniques on healthcare practitioners' awareness (measured with knowledge) of universal newborn hearing screening (UNHS) in Malaysian non-public hospitals. Via cross sectional approach, the current study collected data using a validated questionnaire to obtain information on the awareness of UNHS program among the health practitioners and to test the formulated hypotheses. 51, representing 81% response rate, out of 63 questionnaires distributed to the health professionals were returned and usable for statistical analysis. The survey instruments involving healthcare practitioners' awareness, human resource, program layout, screening instrument, and screening techniques instruments were adapted and scaled with 7-point Likert scale ranging from 1 (little) to 7 (many). Partial Least Squares (PLS) algorithm and bootstrapping techniques were employed to test the hypotheses of the study. With the result involving beta values, t-values and p-values (i.e. β=0.478, t=1.904, phealth practitioners. Likewise, program layout, human resource, screening technique and screening instrument explain 71% variance in health practitioners' awareness. Health practitioners' awareness is explained by program layout, human resource, and screening instrument with effect size (f2) of 0.065, 0.621, and 0.211 respectively, indicating that program layout, human resource, and screening instrument have small, large and medium effect size on health practitioners' awareness respectively. However, screening technique has zero effect on health practitioners' awareness, indicating the reason why T-statistics is not significant. Having started the UNHS program in 2003, non-public hospitals have more experienced and well-trained employees dealing with the screening tools and instrument, and the program layout is well

  16. The Sensitivity, Specificity and Predictive Values of Snellen Chart Compared to the Diagnostic Test in Amblyopia Screening Program in Iran

    Directory of Open Access Journals (Sweden)

    Fatemeh Rivakani

    2015-12-01

    Full Text Available Introduction Amblyopia is a leading cause of visual impairment in both childhood and adult populations. Our aim in this study was to assess the epidemiological characteristics of the amblyopia screening program in Iran. Materials and Methods A cross-sectional study was done on a randomly selected sample of 4,636 Iranian children who were referred to screening program in 2013 were participated in validity study, too. From each provinces the major city were selected. Screening and diagnostic tests were done by instructors in first stage and optometrists in second stage, respectively. Finally data were analyzed by Stata version 13. Results The sensitivity was ranged from 74% to 100% among the various provinces such that Fars and Ardabil province had maximum and minimum values, respectively. The pattern of specificity was differ and ranged 44% to 84% among the provinces; Hormozgan and Fars had maximum and minimum values, respectively. The positive predictive value was also ranged from 35% to %81 which was assigned to Khuzestan and Ardabil provinces, respectively. The range of Negative Predictive value was 61% to 100% which was belonged to Ardabil and Fars provinces. Conclusion The total sensitivity (89% and negative predictive values (93% of screening test among children aged 3-6 years is acceptable, but only 51% of children refereed to second stage are true positive and this imposes considerable cost to health system.

  17. A Genetic Programming Method for the Identification of Signal Peptides and Prediction of Their Cleavage Sites

    Directory of Open Access Journals (Sweden)

    David Lennartsson

    2004-01-01

    Full Text Available A novel approach to signal peptide identification is presented. We use an evolutionary algorithm for automatic evolution of classification programs, so-called programmatic motifs. The variant of evolutionary algorithm used is called genetic programming where a population of solution candidates in the form of full computer programs is evolved, based on training examples consisting of signal peptide sequences. The method is compared with a previous work using artificial neural network (ANN approaches. Some advantages compared to ANNs are noted. The programmatic motif can perform computational tasks beyond that of feed-forward neural networks and has also other advantages such as readability. The best motif evolved was analyzed and shown to detect the h-region of the signal peptide. A powerful parallel computer cluster was used for the experiment.

  18. The Coastal Ocean Prediction Systems program: Understanding and managing our coastal ocean

    International Nuclear Information System (INIS)

    1990-01-01

    This document is a compilation of summaries of papers presented at the Coastal Ocean Prediction Systems workshop. Topics include; marine forecasting, regulatory agencies and regulations, research and application models, research and operational observing, oceanic and atmospheric data assimilation, and coastal physical processes

  19. Genomic Selection for Predicting Fusarium Head Blight Resistance in a Wheat Breeding Program

    Directory of Open Access Journals (Sweden)

    Marcio P. Arruda

    2015-11-01

    Full Text Available Genomic selection (GS is a breeding method that uses marker–trait models to predict unobserved phenotypes. This study developed GS models for predicting traits associated with resistance to head blight (FHB in wheat ( L.. We used genotyping-by-sequencing (GBS to identify 5054 single-nucleotide polymorphisms (SNPs, which were then treated as predictor variables in GS analysis. We compared how the prediction accuracy of the genomic-estimated breeding values (GEBVs was affected by (i five genotypic imputation methods (random forest imputation [RFI], expectation maximization imputation [EMI], -nearest neighbor imputation [kNNI], singular value decomposition imputation [SVDI], and the mean imputation [MNI]; (ii three statistical models (ridge-regression best linear unbiased predictor [RR-BLUP], least absolute shrinkage and operator selector [LASSO], and elastic net; (iii marker density ( = 500, 1500, 3000, and 4500 SNPs; (iv training population (TP size ( = 96, 144, 192, and 218; (v marker-based and pedigree-based relationship matrices; and (vi control for relatedness in TPs and validation populations (VPs. No discernable differences in prediction accuracy were observed among imputation methods. The RR-BLUP outperformed other models in nearly all scenarios. Accuracies decreased substantially when marker number decreased to 3000 or 1500 SNPs, depending on the trait; when sample size of the training set was less than 192; when using pedigree-based instead of marker-based matrix; or when no control for relatedness was implemented. Overall, moderate to high prediction accuracies were observed in this study, suggesting that GS is a very promising breeding strategy for FHB resistance in wheat.

  20. Dynamic fMRI networks predict success in a behavioral weight loss program among older adults.

    Science.gov (United States)

    Mokhtari, Fatemeh; Rejeski, W Jack; Zhu, Yingying; Wu, Guorong; Simpson, Sean L; Burdette, Jonathan H; Laurienti, Paul J

    2018-06-01

    More than one-third of adults in the United States are obese, with a higher prevalence among older adults. Obesity among older adults is a major cause of physical dysfunction, hypertension, diabetes, and coronary heart diseases. Many people who engage in lifestyle weight loss interventions fail to reach targeted goals for weight loss, and most will regain what was lost within 1-2 years following cessation of treatment. This variability in treatment efficacy suggests that there are important phenotypes predictive of success with intentional weight loss that could lead to tailored treatment regimen, an idea that is consistent with the concept of precision-based medicine. Although the identification of biochemical and metabolic phenotypes are one potential direction of research, neurobiological measures may prove useful as substantial behavioral change is necessary to achieve success in a lifestyle intervention. In the present study, we use dynamic brain networks from functional magnetic resonance imaging (fMRI) data to prospectively identify individuals most likely to succeed in a behavioral weight loss intervention. Brain imaging was performed in overweight or obese older adults (age: 65-79 years) who participated in an 18-month lifestyle weight loss intervention. Machine learning and functional brain networks were combined to produce multivariate prediction models. The prediction accuracy exceeded 95%, suggesting that there exists a consistent pattern of connectivity which correctly predicts success with weight loss at the individual level. Connectivity patterns that contributed to the prediction consisted of complex multivariate network components that substantially overlapped with known brain networks that are associated with behavior emergence, self-regulation, body awareness, and the sensory features of food. Future work on independent datasets and diverse populations is needed to corroborate our findings. Additionally, we believe that efforts can begin to

  1. COMSAT: Residue contact prediction of transmembrane proteins based on support vector machines and mixed integer linear programming.

    Science.gov (United States)

    Zhang, Huiling; Huang, Qingsheng; Bei, Zhendong; Wei, Yanjie; Floudas, Christodoulos A

    2016-03-01

    In this article, we present COMSAT, a hybrid framework for residue contact prediction of transmembrane (TM) proteins, integrating a support vector machine (SVM) method and a mixed integer linear programming (MILP) method. COMSAT consists of two modules: COMSAT_SVM which is trained mainly on position-specific scoring matrix features, and COMSAT_MILP which is an ab initio method based on optimization models. Contacts predicted by the SVM model are ranked by SVM confidence scores, and a threshold is trained to improve the reliability of the predicted contacts. For TM proteins with no contacts above the threshold, COMSAT_MILP is used. The proposed hybrid contact prediction scheme was tested on two independent TM protein sets based on the contact definition of 14 Å between Cα-Cα atoms. First, using a rigorous leave-one-protein-out cross validation on the training set of 90 TM proteins, an accuracy of 66.8%, a coverage of 12.3%, a specificity of 99.3% and a Matthews' correlation coefficient (MCC) of 0.184 were obtained for residue pairs that are at least six amino acids apart. Second, when tested on a test set of 87 TM proteins, the proposed method showed a prediction accuracy of 64.5%, a coverage of 5.3%, a specificity of 99.4% and a MCC of 0.106. COMSAT shows satisfactory results when compared with 12 other state-of-the-art predictors, and is more robust in terms of prediction accuracy as the length and complexity of TM protein increase. COMSAT is freely accessible at http://hpcc.siat.ac.cn/COMSAT/. © 2016 Wiley Periodicals, Inc.

  2. Meeting the need to belong: Predicting effects of a friendship enrichment program for older women

    NARCIS (Netherlands)

    Stevens, N.L.; Martina, C.M.S.; Westerhof, G.J.

    2006-01-01

    Purpose: This study explores the effects of participation in a program designed to enrich friendship and reduce loneliness among women in later life. Several hypotheses based on the need to belong, socioemotional selectivity theory, and the social compensation model were tested. Design and Methods:

  3. Predicting Stereotype Endorsement and Academic Motivation in Women in Science Programs: A Longitudinal Model

    Science.gov (United States)

    Delisle, Marie-Noelle; Guay, Frederic; Senecal, Caroline; Larose, Simon

    2009-01-01

    This study proposed and tested a model based on stereotype threat theory. The hypothesis is that women who are exposed to a low percentage of women in a science program are more likely to endorse the gender stereotype that science is a male domain, which will in turn undermine their autonomous academic motivation. A total of 167 women university…

  4. Meeting the Need to Belong: Predicting Effects of a Friendship Enrichment Program for Older Women

    Science.gov (United States)

    Stevens, Nan L.; Martina, Camille M. S.; Westerhof, Gerben J.

    2006-01-01

    Purpose: This study explores the effects of participation in a program designed to enrich friendship and reduce loneliness among women in later life. Several hypotheses based on the need to belong, socioemotional selectivity theory, and the social compensation model were tested. Design and Methods: Study 1 involved two measurement points, one at…

  5. What Can Schools, Colleges, and Youth Programs Do with Predictive Analytics? Practitioner Brief

    Science.gov (United States)

    Balu, Rekha; Porter, Kristin

    2017-01-01

    Many low-income young people are not reaching important milestones for success (for example, completing a program or graduating from school on time). But the social-service organizations and schools that serve them often struggle to identify who is at more or less risk. These institutions often either over- or underestimate risk, missing…

  6. Linking linear programming and spatial simulation models to predict landscape effects of forest management alternatives

    Science.gov (United States)

    Eric J. Gustafson; L. Jay Roberts; Larry A. Leefers

    2006-01-01

    Forest management planners require analytical tools to assess the effects of alternative strategies on the sometimes disparate benefits from forests such as timber production and wildlife habitat. We assessed the spatial patterns of alternative management strategies by linking two models that were developed for different purposes. We used a linear programming model (...

  7. Predicting Employment Outcomes for Consumers in Community College Short-Term Training Programs

    Science.gov (United States)

    Flannery, K. Brigid; Benz, Michael R.; Yovanoff, Paul; Kato, Mary McGrath; Lindstrom, Lauren

    2011-01-01

    Postsecondary education has been linked to improved access to employment opportunities for individuals with and without disabilities. The purpose of this study was to determine factors associated with increased employment outcomes for Vocational Rehabilitation consumers enrolled in community college short term occupational skill training programs.…

  8. Admitting At-Risk Students into a Principal Preparation Program: Predicting Success.

    Science.gov (United States)

    Malone, Bobby G.; Nelson, Jacquelyn S.; Nelson, C. Van

    2001-01-01

    Study of graduation rates of at-risk students admitted to a master's degree program at a doctoral-degree-granting university found that the best predictor of degree completion was the product of the undergraduate GPA multiplied by the GRE Verbal score. (Contains 41 references.)

  9. Analysis and monitoring of energy security and prediction of indicator values using conventional non-linear mathematical programming

    Directory of Open Access Journals (Sweden)

    Elena Vital'evna Bykova

    2011-09-01

    Full Text Available This paper describes the concept of energy security and a system of indicators for its monitoring. The indicator system includes more than 40 parameters that reflect the structure and state of fuel and energy complex sectors (fuel, electricity and heat & power, as well as takes into account economic, environmental and social aspects. A brief description of the structure of the computer system to monitor and analyze energy security is given. The complex contains informational, analytical and calculation modules, provides applications for forecasting and modeling energy scenarios, modeling threats and determining levels of energy security. Its application to predict the values of the indicators and methods developed for it are described. This paper presents a method developed by conventional nonlinear mathematical programming needed to address several problems of energy and, in particular, the prediction problem of the security. An example of its use and implementation of this method in the application, "Prognosis", is also given.

  10. Towards agile large-scale predictive modelling in drug discovery with flow-based programming design principles.

    Science.gov (United States)

    Lampa, Samuel; Alvarsson, Jonathan; Spjuth, Ola

    2016-01-01

    Predictive modelling in drug discovery is challenging to automate as it often contains multiple analysis steps and might involve cross-validation and parameter tuning that create complex dependencies between tasks. With large-scale data or when using computationally demanding modelling methods, e-infrastructures such as high-performance or cloud computing are required, adding to the existing challenges of fault-tolerant automation. Workflow management systems can aid in many of these challenges, but the currently available systems are lacking in the functionality needed to enable agile and flexible predictive modelling. We here present an approach inspired by elements of the flow-based programming paradigm, implemented as an extension of the Luigi system which we name SciLuigi. We also discuss the experiences from using the approach when modelling a large set of biochemical interactions using a shared computer cluster.Graphical abstract.

  11. Optimization of Artificial Neural Network using Evolutionary Programming for Prediction of Cascading Collapse Occurrence due to the Hidden Failure Effect

    Science.gov (United States)

    Idris, N. H.; Salim, N. A.; Othman, M. M.; Yasin, Z. M.

    2018-03-01

    This paper presents the Evolutionary Programming (EP) which proposed to optimize the training parameters for Artificial Neural Network (ANN) in predicting cascading collapse occurrence due to the effect of protection system hidden failure. The data has been collected from the probability of hidden failure model simulation from the historical data. The training parameters of multilayer-feedforward with backpropagation has been optimized with objective function to minimize the Mean Square Error (MSE). The optimal training parameters consists of the momentum rate, learning rate and number of neurons in first hidden layer and second hidden layer is selected in EP-ANN. The IEEE 14 bus system has been tested as a case study to validate the propose technique. The results show the reliable prediction of performance validated through MSE and Correlation Coefficient (R).

  12. Prediction of monthly rainfall on homogeneous monsoon regions of India based on large scale circulation patterns using Genetic Programming

    Science.gov (United States)

    Kashid, Satishkumar S.; Maity, Rajib

    2012-08-01

    SummaryPrediction of Indian Summer Monsoon Rainfall (ISMR) is of vital importance for Indian economy, and it has been remained a great challenge for hydro-meteorologists due to inherent complexities in the climatic systems. The Large-scale atmospheric circulation patterns from tropical Pacific Ocean (ENSO) and those from tropical Indian Ocean (EQUINOO) are established to influence the Indian Summer Monsoon Rainfall. The information of these two large scale atmospheric circulation patterns in terms of their indices is used to model the complex relationship between Indian Summer Monsoon Rainfall and the ENSO as well as EQUINOO indices. However, extracting the signal from such large-scale indices for modeling such complex systems is significantly difficult. Rainfall predictions have been done for 'All India' as one unit, as well as for five 'homogeneous monsoon regions of India', defined by Indian Institute of Tropical Meteorology. Recent 'Artificial Intelligence' tool 'Genetic Programming' (GP) has been employed for modeling such problem. The Genetic Programming approach is found to capture the complex relationship between the monthly Indian Summer Monsoon Rainfall and large scale atmospheric circulation pattern indices - ENSO and EQUINOO. Research findings of this study indicate that GP-derived monthly rainfall forecasting models, that use large-scale atmospheric circulation information are successful in prediction of All India Summer Monsoon Rainfall with correlation coefficient as good as 0.866, which may appears attractive for such a complex system. A separate analysis is carried out for All India Summer Monsoon rainfall for India as one unit, and five homogeneous monsoon regions, based on ENSO and EQUINOO indices of months of March, April and May only, performed at end of month of May. In this case, All India Summer Monsoon Rainfall could be predicted with 0.70 as correlation coefficient with somewhat lesser Correlation Coefficient (C.C.) values for different

  13. Psychosocial and nonclinical factors predicting hospital utilization in patients of a chronic disease management program: a prospective observational study.

    Science.gov (United States)

    Tran, Mark W; Weiland, Tracey J; Phillips, Georgina A

    2015-01-01

    Psychosocial factors such as marital status (odds ratio, 3.52; 95% confidence interval, 1.43-8.69; P = .006) and nonclinical factors such as outpatient nonattendances (odds ratio, 2.52; 95% confidence interval, 1.22-5.23; P = .013) and referrals made (odds ratio, 1.20; 95% confidence interval, 1.06-1.35; P = .003) predict hospital utilization for patients in a chronic disease management program. Along with optimizing patients' clinical condition by prescribed medical guidelines and supporting patient self-management, addressing psychosocial and nonclinical issues are important in attempting to avoid hospital utilization for people with chronic illnesses.

  14. A Homogeneous and Self-Dual Interior-Point Linear Programming Algorithm for Economic Model Predictive Control

    DEFF Research Database (Denmark)

    Sokoler, Leo Emil; Frison, Gianluca; Skajaa, Anders

    2015-01-01

    We develop an efficient homogeneous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control of constrained linear systems with linear objective functions. The algorithm is based on a Riccati iteration procedure, which is adapted to the linear...... system of equations solved in homogeneous and self-dual IPMs. Fast convergence is further achieved using a warm-start strategy. We implement the algorithm in MATLAB and C. Its performance is tested using a conceptual power management case study. Closed loop simulations show that 1) the proposed algorithm...

  15. Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery

    DEFF Research Database (Denmark)

    Hickey, John M.; Chiurugwi, Tinashe; Mackay, Ian

    2017-01-01

    The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human...... that unifies breeding approaches, biological discovery, and tools and methods. Here we compare and contrast some animal and plant breeding approaches to make a case for bringing the two together through the application of genomic selection. We propose a strategy for the use of genomic selection as a unifying...... use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic prediction of breeding values has the potential to improve selection, reduce costs and provide a platform...

  16. Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery.

    Science.gov (United States)

    Hickey, John M; Chiurugwi, Tinashe; Mackay, Ian; Powell, Wayne

    2017-08-30

    The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic prediction of breeding values has the potential to improve selection, reduce costs and provide a platform that unifies breeding approaches, biological discovery, and tools and methods. Here we compare and contrast some animal and plant breeding approaches to make a case for bringing the two together through the application of genomic selection. We propose a strategy for the use of genomic selection as a unifying approach to deliver innovative 'step changes' in the rate of genetic gain at scale.

  17. Development of a hot water tank simulation program with improved prediction of thermal stratification in the tank

    DEFF Research Database (Denmark)

    Fan, Jianhua; Furbo, Simon; Yue, Hongqiang

    2015-01-01

    A simulation program SpiralSol was developed in previous investigations to calculate thermal performance of a solar domestic hot water (SDHW) system with a hot water tank with a built-in heat exchanger spiral [1]. The simulation program is improved in the paper in term of prediction of thermal...... stratification in the tank. The transient fluid flow and heat transfer in the hot water tank during cooling caused by standby heat loss are investigated by validated computational fluid dynamics (CFD) calculations. Detailed CFD investigations are carried out to determine the influence of thickness and material...... property of the tank wall on thermal stratification in the tank. It is elucidated how thermal stratification in the tank is influenced by the natural convection and how the heat loss from the tank sides will be distributed at different levels of the tank at different thermal conditions. The existing...

  18. Upper Bounds Prediction of the Execution Time of Programs Running on ARM Cortex-A Systems

    OpenAIRE

    Fedotova , Irina; Krause , Bernd; Siemens , Eduard

    2017-01-01

    Part 6: Embedded and Real Time Systems; International audience; This paper describes the application of statistical analysis of the timing behavior for a generic real-time task model. Using specific processor of ARM Cortex-A series and an empirical approach of time values retrieval, the algorithm to predict the upper bounds for the task of the time acquisition operation has been formulated. For the experimental verification of the algorithm, we have used the robust Measurement-Based Probabili...

  19. Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery

    OpenAIRE

    Hickey, John M; Chiurugwi, Tinashe; Mackay, Ian; Powell, Wayne; Implementing Genomic Selection in CGIAR Breeding Programs Workshop Participants

    2017-01-01

    The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic pre...

  20. Bagging Approach for Increasing Classification Accuracy of CART on Family Participation Prediction in Implementation of Elderly Family Development Program

    Directory of Open Access Journals (Sweden)

    Wisoedhanie Widi Anugrahanti

    2017-06-01

    Full Text Available Classification and Regression Tree (CART was a method of Machine Learning where data exploration was done by decision tree technique. CART was a classification technique with binary recursive reconciliation algorithms where the sorting was performed on a group of data collected in a space called a node / node into two child nodes (Lewis, 2000. The aim of this study was to predict family participation in Elderly Family Development program based on family behavior in providing physical, mental, social care for the elderly. Family involvement accuracy using Bagging CART method was calculated based on 1-APER value, sensitivity, specificity, and G-Means. Based on CART method, classification accuracy was obtained 97,41% with Apparent Error Rate value 2,59%. The most important determinant of family behavior as a sorter was society participation (100,00000, medical examination (98,95988, providing nutritious food (68.60476, establishing communication (67,19877 and worship (57,36587. To improved the stability and accuracy of CART prediction, used CART Bootstrap Aggregating (Bagging with 100% accuracy result. Bagging CART classifies a total of 590 families (84.77% were appropriately classified into implement elderly Family Development program class.

  1. Development of computer program ENMASK for prediction of residual environmental masking-noise spectra, from any three independent environmental parameters

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Y.-S.; Liebich, R. E.; Chun, K. C.

    2000-03-31

    Residual environmental sound can mask intrusive4 (unwanted) sound. It is a factor that can affect noise impacts and must be considered both in noise-impact studies and in noise-mitigation designs. Models for quantitative prediction of sensation level (audibility) and psychological effects of intrusive noise require an input with 1/3 octave-band spectral resolution of environmental masking noise. However, the majority of published residual environmental masking-noise data are given with either octave-band frequency resolution or only single A-weighted decibel values. A model has been developed that enables estimation of 1/3 octave-band residual environmental masking-noise spectra and relates certain environmental parameters to A-weighted sound level. This model provides a correlation among three environmental conditions: measured residual A-weighted sound-pressure level, proximity to a major roadway, and population density. Cited field-study data were used to compute the most probable 1/3 octave-band sound-pressure spectrum corresponding to any selected one of these three inputs. In turn, such spectra can be used as an input to models for prediction of noise impacts. This paper discusses specific algorithms included in the newly developed computer program ENMASK. In addition, the relative audibility of the environmental masking-noise spectra at different A-weighted sound levels is discussed, which is determined by using the methodology of program ENAUDIBL.

  2. MASBAL: A computer program for predicting the composition of nuclear waste glass produced by a slurry-fed ceramic melter

    International Nuclear Information System (INIS)

    Reimus, P.W.

    1987-07-01

    This report is a user's manual for the MASBAL computer program. MASBAL's objectives are to predict the composition of nuclear waste glass produced by a slurry-fed ceramic melter based on a knowledge of process conditions; to generate simulated data that can be used to estimate the uncertainty in the predicted glass composition as a function of process uncertainties; and to generate simulated data that can be used to provide a measure of the inherent variability in the glass composition as a function of the inherent variability in the feed composition. These three capabilities are important to nuclear waste glass producers because there are constraints on the range of compositions that can be processed in a ceramic melter and on the range of compositions that will be acceptable for disposal in a geologic repository. MASBAL was developed specifically to simulate the operation of the West Valley Component Test system, a commercial-scale ceramic melter system that will process high-level nuclear wastes currently stored in underground tanks at the site of the Western New York Nuclear Services Center (near West Valley, New York). The program is flexible enough, however, to simulate any slurry-fed ceramic melter system. 4 refs., 16 figs., 5 tabs

  3. Teaching aspects of the instrumental neutron activation analysis advance prediction computer program

    International Nuclear Information System (INIS)

    Guinn, V.P.

    1990-01-01

    The INAA APCP was developed, and is extensively used, primarily as a very useful guide for efficient INAA work. From the exact or approximate elemental composition of a material, it calculates the proper sample weight, and all details of the germanium gamma-ray pulse height spectrum for any and all input flux, detector, irradiation time, decay time, and counting time conditions specified. For each set of conditions, it also prints out the five largest induced activities and the five largest gamma-ray emitters at five different decay periods. The program also provides an excellent educational device for students in a radiochemistry course

  4. Pulse Rate and Transit Time Analysis to Predict Hypotension Events After Spinal Anesthesia During Programmed Cesarean Labor.

    Science.gov (United States)

    Bolea, Juan; Lázaro, Jesús; Gil, Eduardo; Rovira, Eva; Remartínez, José M; Laguna, Pablo; Pueyo, Esther; Navarro, Augusto; Bailón, Raquel

    2017-09-01

    Prophylactic treatment has been proved to reduce hypotension incidence after spinal anesthesia during cesarean labor. However, the use of pharmacological prophylaxis could carry out undesirable side-effects on mother and fetus. Thus, the prediction of hypotension becomes an important challenge. Hypotension events are hypothesized to be related to a malfunctioning of autonomic nervous system (ANS) regulation of blood pressure. In this work, ANS responses to positional changes of 51 pregnant women programmed for a cesarean labor were explored for hypotension prediction. Lateral and supine decubitus, and sitting position were considered while electrocardiographic and pulse photoplethysmographic signals were recorded. Features based on heart rate variability, pulse rate variability (PRV) and pulse transit time (PTT) analysis were used in a logistic regression classifier. The results showed that PRV irregularity changes, assessed by approximate entropy, from supine to lateral decubitus, and standard deviation of PTT in supine decubitus were found as the combination of features that achieved the best classification results sensitivity of 76%, specificity of 70% and accuracy of 72%, being normotensive the positive class. Peripheral regulation and blood pressure changes, measured by PRV and PTT analysis, could help to predict hypotension events reducing prophylactic side-effects in the low-risk population.

  5. Positive predictive values by mammographic density and screening mode in the Norwegian Breast Cancer Screening Program.

    Science.gov (United States)

    Moshina, Nataliia; Ursin, Giske; Roman, Marta; Sebuødegård, Sofie; Hofvind, Solveig

    2016-01-01

    To investigate the probability of breast cancer among women recalled due to abnormal findings on the screening mammograms (PPV-1) and among women who underwent an invasive procedure (PPV-2) by mammographic density (MD), screening mode and age. We used information about 28,826 recall examinations from 26,951 subsequently screened women in the Norwegian Breast Cancer Screening Program, 1996-2010. The radiologists who performed the recall examinations subjectively classified MD on the mammograms into three categories: fatty (70%). Screening mode was defined as screen-film mammography (SFM) and full-field digital mammography (FFDM). We examined trends of PPVs by MD, screening mode and age. We used logistic regression to estimate odds ratio (OR) of screen-detected breast cancer associated with MD among women recalled, adjusting for screening mode and age. PPV-1 and PPV-2 decreased by increasing MD, regardless of screening mode (p for trend breasts. Among women recalled, the adjusted OR of breast cancer decreased with increasing MD. Compared with women with fatty breasts, the OR was 0.90 (95% CI: 0.84-0.96) for those with medium dense breasts and 0.85 (95% CI: 0.76-0.95) for those with dense breasts. PPVs decreased by increasing MD. Fewer women needed to be recalled or undergo an invasive procedure to detect one breast cancer among those with fatty versus dense breasts in the screening program in Norway, 1996-2010. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  6. The Nordic back pain subpopulation program: predicting outcome among chiropractic patients in Finland

    Directory of Open Access Journals (Sweden)

    Pekkarinen Harri

    2008-11-01

    Full Text Available Abstract Background In a previous Swedish study it was shown that it is possible to predict which chiropractic patients with persistent LBP will not report definite improvement early in the course of treatment, namely those with LBP for altogether at least 30 days in the past year, who had leg pain, and who did not report definite general improvement by the second treatment. The objectives of this study were to investigate if the predictive value of this set of variables could be reproduced among chiropractic patients in Finland, and if the model could be improved by adding some new potential predictor variables. Methods The study was a multi-centre prospective outcome study with internal control groups, carried out in private chiropractic practices in Finland. Chiropractors collected data at the 1st, 2nd and 4th visits using standardized questionnaires on new patients with LBP and/or radiating leg pain. Status at base-line was identified in relation to pain and disability, at the 2nd visit in relation to disability, and "definitely better" at the 4th visit in relation to a global assessment. The Swedish questionnaire was used including three new questions on general health, pain in other parts of the spine, and body mass index. Results The Swedish model was reproduced in this study sample. An alternative model including leg pain (yes/no, improvement at 2nd visit (yes/no and BMI (underweight/normal/overweight or obese was also identified with similar predictive values. Common throughout the testing of various models was that improvement at the 2nd visit had an odds ratio of approximately 5. Additional analyses revealed a dose-response in that 84% of those patients who fulfilled none of these (bad criteria were classified as "definitely better" at the 4th visit, vs. 75%, 60% and 34% of those who fulfilled 1, 2 or all 3 of the criteria, respectively. Conclusion When treating patients with LBP, at the first visits, the treatment strategy should be

  7. Coupled information diffusion--pest dynamics models predict delayed benefits of farmer cooperation in pest management programs.

    Science.gov (United States)

    Rebaudo, François; Dangles, Olivier

    2011-10-01

    Worldwide, the theory and practice of agricultural extension system have been dominated for almost half a century by Rogers' "diffusion of innovation theory". In particular, the success of integrated pest management (IPM) extension programs depends on the effectiveness of IPM information diffusion from trained farmers to other farmers, an important assumption which underpins funding from development organizations. Here we developed an innovative approach through an agent-based model (ABM) combining social (diffusion theory) and biological (pest population dynamics) models to study the role of cooperation among small-scale farmers to share IPM information for controlling an invasive pest. The model was implemented with field data, including learning processes and control efficiency, from large scale surveys in the Ecuadorian Andes. Our results predict that although cooperation had short-term costs for individual farmers, it paid in the long run as it decreased pest infestation at the community scale. However, the slow learning process placed restrictions on the knowledge that could be generated within farmer communities over time, giving rise to natural lags in IPM diffusion and applications. We further showed that if individuals learn from others about the benefits of early prevention of new pests, then educational effort may have a sustainable long-run impact. Consistent with models of information diffusion theory, our results demonstrate how an integrated approach combining ecological and social systems would help better predict the success of IPM programs. This approach has potential beyond pest management as it could be applied to any resource management program seeking to spread innovations across populations.

  8. AI based HealthCare Platform for Real Time, Predictive and Prescriptive Analytics using Reactive Programming

    Science.gov (United States)

    Kaur, Jagreet; Singh Mann, Kulwinder, Dr.

    2018-01-01

    AI in Healthcare needed to bring real, actionable insights and Individualized insights in real time for patients and Doctors to support treatment decisions., We need a Patient Centred Platform for integrating EHR Data, Patient Data, Prescriptions, Monitoring, Clinical research and Data. This paper proposes a generic architecture for enabling AI based healthcare analytics Platform by using open sources Technologies Apache beam, Apache Flink Apache Spark, Apache NiFi, Kafka, Tachyon, Gluster FS, NoSQL- Elasticsearch, Cassandra. This paper will show the importance of applying AI based predictive and prescriptive analytics techniques in Health sector. The system will be able to extract useful knowledge that helps in decision making and medical monitoring in real-time through an intelligent process analysis and big data processing.

  9. Prediction of Layer Thickness in Molten Borax Bath with Genetic Evolutionary Programming

    Science.gov (United States)

    Taylan, Fatih

    2011-04-01

    In this study, the vanadium carbide coating in molten borax bath process is modeled by evolutionary genetic programming (GEP) with bath composition (borax percentage, ferro vanadium (Fe-V) percentage, boric acid percentage), bath temperature, immersion time, and layer thickness data. Five inputs and one output data exist in the model. The percentage of borax, Fe-V, and boric acid, temperature, and immersion time parameters are used as input data and the layer thickness value is used as output data. For selected bath components, immersion time, and temperature variables, the layer thicknesses are derived from the mathematical expression. The results of the mathematical expressions are compared to that of experimental data; it is determined that the derived mathematical expression has an accuracy of 89%.

  10. Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

    KAUST Repository

    Kouramas, K.I.

    2011-08-01

    This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The algorithm features two key steps: (i) a dynamic programming step, in which the mp-MPC problem is decomposed into a set of smaller subproblems in which only the current control, state variables, and constraints are considered, and (ii) a multi-parametric programming step, in which each subproblem is solved as a convex multi-parametric programming problem, to derive the control variables as an explicit function of the states. The key feature of the proposed method is that it overcomes potential limitations of previous methods for solving multi-parametric programming problems with dynamic programming, such as the need for global optimization for each subproblem of the dynamic programming step. © 2011 Elsevier Ltd. All rights reserved.

  11. Predictable Particle Engineering: Programming the Energy Level, Carrier Generation, and Conductivity of Core-Shell Particles.

    Science.gov (United States)

    Yuan, Conghui; Wu, Tong; Mao, Jie; Chen, Ting; Li, Yuntong; Li, Min; Xu, Yiting; Zeng, Birong; Luo, Weiang; Yu, Lingke; Zheng, Gaofeng; Dai, Lizong

    2018-06-20

    Core-shell structures are of particular interest in the development of advanced composite materials as they can efficiently bring different components together at nanoscale. The advantage of this structure greatly relies on the crucial design of both core and shell, thus achieving an intercomponent synergistic effect. In this report, we show that decorating semiconductor nanocrystals with a boronate polymer shell can easily achieve programmable core-shell interactions. Taking ZnO and anatase TiO 2 nanocrystals as inner core examples, the effective core-shell interactions can narrow the band gap of semiconductor nanocrystals, change the HOMO and LUMO levels of boronate polymer shell, and significantly improve the carrier density of core-shell particles. The hole mobility of core-shell particles can be improved by almost 9 orders of magnitude in comparison with net boronate polymer, while the conductivity of core-shell particles is at most 30-fold of nanocrystals. The particle engineering strategy is based on two driving forces: catechol-surface binding and B-N dative bonding and having a high ability to control and predict the shell thickness. Also, this approach is applicable to various inorganic nanoparticles with different components, sizes, and shapes.

  12. Analysis and computer program for rupture-risk prediction of abdominal aortic aneurysms

    Directory of Open Access Journals (Sweden)

    Li Zhonghua

    2006-03-01

    Full Text Available Abstract Background Ruptured abdominal aortic aneurysms (AAAs are the 13th leading cause of death in the United States. While AAA rupture may occur without significant warning, its risk assessment is generally based on critical values of the maximum AAA diameter (>5 cm and AAA-growth rate (>0.5 cm/year. These criteria may be insufficient for reliable AAA-rupture risk assessment especially when predicting possible rupture of smaller AAAs. Methods Based on clinical evidence, eight biomechanical factors with associated weighting coefficients were determined and summed up in terms of a dimensionless, time-dependent severity parameter, SP(t. The most important factor is the maximum wall stress for which a semi-empirical correlation has been developed. Results The patient-specific SP(t indicates the risk level of AAA rupture and provides a threshold value when surgical intervention becomes necessary. The severity parameter was validated with four clinical cases and its application is demonstrated for two AAA cases. Conclusion As part of computational AAA-risk assessment and medical management, a patient-specific severity parameter 0

  13. Prediction of ovarian hyperstimulation syndrome in coasted patients in an IVF/ICSI program

    Directory of Open Access Journals (Sweden)

    Fatimah Y Aljawoan

    2012-01-01

    Full Text Available Aim: To determine why a subgroup of coasted patients developed moderate/severe ovarian hyperstimulation syndrome (OHSS in an assisted reproduction setting. Materials and Methods: Retrospective study of 2948 in-vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI treatment cycles with 327 patients requiring coasting. Long protocol gonadotrophin releasing hormone analogue (GnRH-a regimen was used and serum estradiol (E 2 checked when ≥20 follicles were noted on follicular tracking. Coasting was initiated when leading three follicles were ≥15mm with E 2 ≥1635pg/ml. Results: The incidence of moderate/severe OHSS was 10.4% in coasted patients (equivalent 1.15% of the total IVF/ICSI cycles in the Center. Coasted patients who subsequently developed OHSS showed a significantly higher number of retrieved oocytes, higher serum E 2 level on the day of human chorionic gonadotrophin (hCG administration, and multiple pregnancies. No significant differences were noted with female age, BMI, cause of infertility, gonadotrophin dosage, coasting duration, and % of E 2 drop. Conclusion: Moderate/severe OHSS might be predicted in coasted patients by a combination of total oocyte numbers and E 2 level on the day of hCG. Multiple pregnancies also significantly increased the risk.

  14. Adaptive temperature regulation in the little bird in winter: predictions from a stochastic dynamic programming model.

    Science.gov (United States)

    Brodin, Anders; Nilsson, Jan-Åke; Nord, Andreas

    2017-09-01

    Several species of small birds are resident in boreal forests where environmental temperatures can be -20 to -30 °C, or even lower, in winter. As winter days are short, and food is scarce, winter survival is a challenge for small endothermic animals. A bird of this size will have to gain almost 10% of its lean body mass in fat every day to sustain overnight metabolism. Birds such as parids (titmice and chickadees) can use facultative hypothermia, a process in which body temperature is actively down-regulated to a specific level, to reduce heat loss and thus save energy. During cold winter nights, these birds may decrease body temperature from the normal from 42 ° down to 35 °C, or even lower in some species. However, birds are unable to move in this deep hypothermic state, making it a risky strategy if predators are around. Why, then, do small northern birds enter a potentially dangerous physiological state for a relatively small reduction in energy expenditure? We used stochastic dynamic programming to investigate this. Our model suggests that the use of nocturnal hypothermia at night is paramount in these biomes, as it would increase winter survival for a small northern bird by 58% over a winter of 100 days. Our model also explains the phenomenon known as winter fattening, and its relationship to thermoregulation, in northern birds.

  15. The problems and solutions of predicting participation in energy efficiency programs

    International Nuclear Information System (INIS)

    Davis, Alexander L.; Krishnamurti, Tamar

    2013-01-01

    Highlights: • Energy efficiency pilot studies suffer from severe volunteer bias. • We formulate an approach for accommodating volunteer bias. • A short questionnaire and classification trees can control for the bias. - Abstract: This paper discusses volunteer bias in residential energy efficiency studies. We briefly evaluate the bias in existing studies. We then show how volunteer bias can be corrected when not avoidable, using an on-line study of intentions to enroll in an in-home display trial as an example. We found that the best predictor of intentions to enroll was expected benefit from the in-home display. Constraints on participation, such as time in the home and trust in scientists, were also associated with enrollment intentions. Using Breiman’s classification tree algorithm we found that the best model of intentions to enroll contained only five variables: expected enjoyment of the program, presence in the home during morning hours, trust (in friends and in scientists), and perceived ability to handle unexpected problems. These results suggest that a short questionnaire, that takes at most 1 min to complete, would allow better control of volunteer bias than a more extensive questionnaire. This paper should allow researchers who employ field studies involving human behavior to be better equipped to address volunteer bias

  16. Predicting changes in drug use and treatment entry for local programs: a case study.

    Science.gov (United States)

    Flaherty, E W; Olsen, K; Bencivengo, M

    1980-01-01

    Recent sharp decline in treatment admissions by opiate abusers stimulated the conduct of a study designed to provide timely data to treatment system administrators for the next cycle of program and budgetary planning. The process of designing the study involved definition of required study characteristics, review of four categories of drug abuse research, and generation of seven locally relevant hypotheses. Interviews were conducted with 335 heroin adicts: 196 new admissions to treatment and 139 "street" addicts not currently in treatment. Major findings were a marked reduction in the quality, availability, and price of heroin; very negative perceptions of methadone maintenance, especially by female respondents; decline in heroin popularity and increase in reported use of alcohol, amphetamines, and barbiturates; and differing perceptions of treatment by sex of respondent. Response patterns suggest that users who are not entering treatment are less "strung-out than those entering treatment because of decline in availability and quality of heroin and consequent increased mixing of drugs. The emphasis in the report is on the conduct of a study which can be timely, feasible, and useful to local planners. The study weaknesses and recommended remedies are discussed, as well as the characteristics which made the findings immediately useful to administrators and planners.

  17. Predicting likelihood of seeking help through the employee assistance program among salaried and union hourly employees.

    Science.gov (United States)

    Delaney, W; Grube, J W; Ames, G M

    1998-03-01

    This research investigated belief, social support and background predictors of employee likelihood to use an Employee Assistance Program (EAP) for a drinking problem. An anonymous cross-sectional survey was administered in the home. Bivariate analyses and simultaneous equations path analysis were used to explore a model of EAP use. Survey and ethnographic research were conducted in a unionized heavy machinery manufacturing plant in the central states of the United States. A random sample of 852 hourly and salaried employees was selected. In addition to background variables, measures included: likelihood of going to an EAP for a drinking problem, belief the EAP can help, social support for the EAP from co-workers/others, belief that EAP use will harm employment, and supervisor encourages the EAP for potential drinking problems. Belief in EAP efficacy directly increased the likelihood of going to an EAP. Greater perceived social support and supervisor encouragement increased the likelihood of going to an EAP both directly and indirectly through perceived EAP efficacy. Black and union hourly employees were more likely to say they would use an EAP. Males and those who reported drinking during working hours were less likely to say they would use an EAP for a drinking problem. EAP beliefs and social support have significant effects on likelihood to go to an EAP for a drinking problem. EAPs may wish to focus their efforts on creating an environment where there is social support from coworkers and encouragement from supervisors for using EAP services. Union networks and team members have an important role to play in addition to conventional supervisor intervention.

  18. Social support for healthy behaviors: Scale psychometrics and prediction of weight loss among women in a behavioral program

    Science.gov (United States)

    Kiernan, Michaela; Moore, Susan D.; Schoffman, Danielle E.; Lee, Katherine; King, Abby C.; Taylor, C. Barr; Kiernan, Nancy Ellen; Perri, Michael G.

    2015-01-01

    Social support could be a powerful weight-loss treatment moderator or mediator but is rarely assessed. We assessed the psychometric properties, initial levels, and predictive validity of a measure of perceived social support and sabotage from friends and family for healthy eating and physical activity (eight subscales). Overweight/obese women randomized to one of two 6-month, group-based behavioral weight-loss programs (N=267; mean BMI 32.1±3.5; 66.3% White) completed subscales at baseline, and weight loss was assessed at 6 months. Internal consistency, discriminant validity, and content validity were excellent for support subscales and adequate for sabotage subscales; qualitative responses revealed novel deliberate instances not reflected in current sabotage items. Most women (>75%) “never” or “rarely” experienced support from friends or family. Using non-parametric classification methods, we identified two subscales—support from friends for healthy eating and support from family for physical activity—that predicted three clinically meaningful subgroups who ranged in likelihood of losing ≥5% of initial weight at 6 months. Women who “never” experienced family support were least likely to lose weight (45.7% lost weight) whereas women who experienced both frequent friend and family support were more likely to lose weight (71.6% lost weight). Paradoxically, women who “never” experienced friend support were most likely to lose weight (80.0% lost weight), perhaps because the group-based programs provided support lacking from friendships. Psychometrics for support subscales were excellent; initial support was rare; and the differential roles of friend versus family support could inform future targeted weight-loss interventions to subgroups at risk. PMID:21996661

  19. The Climate Variability & Predictability (CVP) Program at NOAA - Observing and Understanding Processes Affecting the Propagation of Intraseasonal Oscillations in the Maritime Continent Region

    Science.gov (United States)

    Lucas, S. E.

    2017-12-01

    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). In 2017, the CVP Program had a call for proposals focused on observing and understanding processes affecting the propagation of intraseasonal oscillations in the Maritime Continent region. This poster will present the recently funded CVP projects, the expected scientific outcomes, the geographic areas of their work in the Maritime Continent region, and the collaborations with the Office of Naval Research, Indonesian Agency for Meteorology, Climatology and Geophysics (BMKG), Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and other partners.

  20. Prediction of Basic Math Course Failure Rate in the Physics, Meteorology, Mathematics, Actuarial Sciences and Pharmacy Degree Programs

    Directory of Open Access Journals (Sweden)

    Luis Rojas-Torres

    2014-09-01

    Full Text Available This paper summarizes a study conducted in 2013 with the purpose of predicting the failure rate of math courses taken by Pharmacy, Mathematics, Actuarial Science, Physics and Meteorology students at Universidad de Costa Rica (UCR. Using the Logistics Regression statistical techniques applied to the 2010 cohort, failure rates were predicted of students in the aforementioned programs in one of their Math introductory courses (Calculus 101 for Physics and Meteorology, Math Principles for Mathematics and Actuarial Science and Applied Differential Equations for Pharmacy. For these models, the UCR admission average, the student’s genre, and the average correct answers in the Quantitative Skills Test were used as predictor variables. The most important variable for all models was the Quantitative Skills Test, and the model with the highest correct classification rate was the Logistics Regression. For the estimated Physics-Meteorology, Pharmacy and Mathematics-Actuarial Science models, correct classifications were 89.8%, 73.6%, and 93.9%, respectively.

  1. Improved functional capacity evaluation performance predicts successful return to work one year after completing a functional restoration rehabilitation program.

    Science.gov (United States)

    Fore, Lisa; Perez, Yoheli; Neblett, Randy; Asih, Sali; Mayer, Tom G; Gatchel, Robert J

    2015-04-01

    To evaluate whether functional capacity evaluation (FCE) scores are responsive to functional restoration treatment, and to assess the ability of FCEs at program discharge to predict work outcomes. An interdisciplinary cohort study of prospectively collected data. A functional restoration center. A consecutive sample of 354 patients with chronic disabling occupational musculoskeletal disorders (CDOMDs) completed a functional restoration program consisting of quantitatively directed exercise progression and multi-modal disability management with interdisciplinary medical supervision. Each patient participated in an FCE at admission and discharge from treatment. The results of each FCE yielded the physical demand level (PDL) at which patients were functioning. Patients were initially divided into 5 PDL groups, based on job-of-injury lifting, carrying, and pushing/pulling requirements, for the pre- to posttreatment responsiveness analyses. Patients were subsequently divided into 5 PDL groups, based on their performance on the FCE upon program completion. Outcome measures included admission-to-discharge changes in PDLs and 2 specific FCE lifting tasks: isokinetic lifting; and the Progressive Isoinertial Lifting Evaluation (PILE). Socioeconomic outcomes were also evaluated, including post-discharge work return and work retention 1-year after treatment completion. Overall, 96% of the patients demonstrated improvement in their PDLs from admission to discharge. A majority of patients (56%) were able to achieve a discharge PDL that was comparable to their estimated job-of-injury lifting requirement or higher (P work return (P work retention (P work return after treatment completion and work retention 1 year later. Copyright © 2015 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

  2. Survival prediction algorithms miss significant opportunities for improvement if used for case selection in trauma quality improvement programs.

    Science.gov (United States)

    Heim, Catherine; Cole, Elaine; West, Anita; Tai, Nigel; Brohi, Karim

    2016-09-01

    Quality improvement (QI) programs have shown to reduce preventable mortality in trauma care. Detailed review of all trauma deaths is a time and resource consuming process and calculated probability of survival (Ps) has been proposed as audit filter. Review is limited on deaths that were 'expected to survive'. However no Ps-based algorithm has been validated and no study has examined elements of preventability associated with deaths classified as 'expected'. The objective of this study was to examine whether trauma performance review can be streamlined using existing mortality prediction tools without missing important areas for improvement. We conducted a retrospective study of all trauma deaths reviewed by our trauma QI program. Deaths were classified into non-preventable, possibly preventable, probably preventable or preventable. Opportunities for improvement (OPIs) involve failure in the process of care and were classified into clinical and system deviations from standards of care. TRISS and PS were used for calculation of probability of survival. Peer-review charts were reviewed by a single investigator. Over 8 years, 626 patients were included. One third showed elements of preventability and 4% were preventable. Preventability occurred across the entire range of the calculated Ps band. Limiting review to unexpected deaths would have missed over 50% of all preventability issues and a third of preventable deaths. 37% of patients showed opportunities for improvement (OPIs). Neither TRISS nor PS allowed for reliable identification of OPIs and limiting peer-review to patients with unexpected deaths would have missed close to 60% of all issues in care. TRISS and PS fail to identify a significant proportion of avoidable deaths and miss important opportunities for process and system improvement. Based on this, all trauma deaths should be subjected to expert panel review in order to aim at a maximal output of performance improvement programs. Copyright © 2016 Elsevier

  3. Internet-based motivation program for women with eating disorders: eating disorder pathology and depressive mood predict dropout.

    Science.gov (United States)

    von Brachel, Ruth; Hötzel, Katrin; Hirschfeld, Gerrit; Rieger, Elizabeth; Schmidt, Ulrike; Kosfelder, Joachim; Hechler, Tanja; Schulte, Dietmar; Vocks, Silja

    2014-03-31

    One of the main problems of Internet-delivered interventions for a range of disorders is the high dropout rate, yet little is known about the factors associated with this. We recently developed and tested a Web-based 6-session program to enhance motivation to change for women with anorexia nervosa, bulimia nervosa, or related subthreshold eating pathology. The aim of the present study was to identify predictors of dropout from this Web program. A total of 179 women took part in the study. We used survival analyses (Cox regression) to investigate the predictive effect of eating disorder pathology (assessed by the Eating Disorders Examination-Questionnaire; EDE-Q), depressive mood (Hopkins Symptom Checklist), motivation to change (University of Rhode Island Change Assessment Scale; URICA), and participants' age at dropout. To identify predictors, we used the least absolute shrinkage and selection operator (LASSO) method. The dropout rate was 50.8% (91/179) and was equally distributed across the 6 treatment sessions. The LASSO analysis revealed that higher scores on the Shape Concerns subscale of the EDE-Q, a higher frequency of binge eating episodes and vomiting, as well as higher depression scores significantly increased the probability of dropout. However, we did not find any effect of the URICA or age on dropout. Women with more severe eating disorder pathology and depressive mood had a higher likelihood of dropping out from a Web-based motivational enhancement program. Interventions such as ours need to address the specific needs of women with more severe eating disorder pathology and depressive mood and offer them additional support to prevent them from prematurely discontinuing treatment.

  4. Internet-Based Motivation Program for Women With Eating Disorders: Eating Disorder Pathology and Depressive Mood Predict Dropout

    Science.gov (United States)

    Hirschfeld, Gerrit; Rieger, Elizabeth; Schmidt, Ulrike; Kosfelder, Joachim; Hechler, Tanja; Schulte, Dietmar; Vocks, Silja

    2014-01-01

    Background One of the main problems of Internet-delivered interventions for a range of disorders is the high dropout rate, yet little is known about the factors associated with this. We recently developed and tested a Web-based 6-session program to enhance motivation to change for women with anorexia nervosa, bulimia nervosa, or related subthreshold eating pathology. Objective The aim of the present study was to identify predictors of dropout from this Web program. Methods A total of 179 women took part in the study. We used survival analyses (Cox regression) to investigate the predictive effect of eating disorder pathology (assessed by the Eating Disorders Examination-Questionnaire; EDE-Q), depressive mood (Hopkins Symptom Checklist), motivation to change (University of Rhode Island Change Assessment Scale; URICA), and participants’ age at dropout. To identify predictors, we used the least absolute shrinkage and selection operator (LASSO) method. Results The dropout rate was 50.8% (91/179) and was equally distributed across the 6 treatment sessions. The LASSO analysis revealed that higher scores on the Shape Concerns subscale of the EDE-Q, a higher frequency of binge eating episodes and vomiting, as well as higher depression scores significantly increased the probability of dropout. However, we did not find any effect of the URICA or age on dropout. Conclusions Women with more severe eating disorder pathology and depressive mood had a higher likelihood of dropping out from a Web-based motivational enhancement program. Interventions such as ours need to address the specific needs of women with more severe eating disorder pathology and depressive mood and offer them additional support to prevent them from prematurely discontinuing treatment. PMID:24686856

  5. The AFHSC-Division of GEIS Operations Predictive Surveillance Program: a multidisciplinary approach for the early detection and response to disease outbreaks.

    Science.gov (United States)

    Witt, Clara J; Richards, Allen L; Masuoka, Penny M; Foley, Desmond H; Buczak, Anna L; Musila, Lillian A; Richardson, Jason H; Colacicco-Mayhugh, Michelle G; Rueda, Leopoldo M; Klein, Terry A; Anyamba, Assaf; Small, Jennifer; Pavlin, Julie A; Fukuda, Mark M; Gaydos, Joel; Russell, Kevin L; Wilkerson, Richard C; Gibbons, Robert V; Jarman, Richard G; Myint, Khin S; Pendergast, Brian; Lewis, Sheri; Pinzon, Jorge E; Collins, Kathrine; Smith, Matthew; Pak, Edwin; Tucker, Compton; Linthicum, Kenneth; Myers, Todd; Mansour, Moustafa; Earhart, Ken; Kim, Heung Chul; Jiang, Ju; Schnabel, Dave; Clark, Jeffrey W; Sang, Rosemary C; Kioko, Elizabeth; Abuom, David C; Grieco, John P; Richards, Erin E; Tobias, Steven; Kasper, Matthew R; Montgomery, Joel M; Florin, Dave; Chretien, Jean-Paul; Philip, Trudy L

    2011-03-04

    The Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System Operations (AFHSC-GEIS) initiated a coordinated, multidisciplinary program to link data sets and information derived from eco-climatic remote sensing activities, ecologic niche modeling, arthropod vector, animal disease-host/reservoir, and human disease surveillance for febrile illnesses, into a predictive surveillance program that generates advisories and alerts on emerging infectious disease outbreaks. The program's ultimate goal is pro-active public health practice through pre-event preparedness, prevention and control, and response decision-making and prioritization. This multidisciplinary program is rooted in over 10 years experience in predictive surveillance for Rift Valley fever outbreaks in Eastern Africa. The AFHSC-GEIS Rift Valley fever project is based on the identification and use of disease-emergence critical detection points as reliable signals for increased outbreak risk. The AFHSC-GEIS predictive surveillance program has formalized the Rift Valley fever project into a structured template for extending predictive surveillance capability to other Department of Defense (DoD)-priority vector- and water-borne, and zoonotic diseases and geographic areas. These include leishmaniasis, malaria, and Crimea-Congo and other viral hemorrhagic fevers in Central Asia and Africa, dengue fever in Asia and the Americas, Japanese encephalitis (JE) and chikungunya fever in Asia, and rickettsial and other tick-borne infections in the U.S., Africa and Asia.

  6. Assessing the Effectiveness of Statistical Classification Techniques in Predicting Future Employment of Participants in the Temporary Assistance for Needy Families Program

    Science.gov (United States)

    Montoya, Isaac D.

    2008-01-01

    Three classification techniques (Chi-square Automatic Interaction Detection [CHAID], Classification and Regression Tree [CART], and discriminant analysis) were tested to determine their accuracy in predicting Temporary Assistance for Needy Families program recipients' future employment. Technique evaluation was based on proportion of correctly…

  7. The AFHSC-Division of GEIS Operations Predictive Surveillance Program: a multidisciplinary approach for the early detection and response to disease outbreaks

    Science.gov (United States)

    2011-01-01

    The Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System Operations (AFHSC-GEIS) initiated a coordinated, multidisciplinary program to link data sets and information derived from eco-climatic remote sensing activities, ecologic niche modeling, arthropod vector, animal disease-host/reservoir, and human disease surveillance for febrile illnesses, into a predictive surveillance program that generates advisories and alerts on emerging infectious disease outbreaks. The program’s ultimate goal is pro-active public health practice through pre-event preparedness, prevention and control, and response decision-making and prioritization. This multidisciplinary program is rooted in over 10 years experience in predictive surveillance for Rift Valley fever outbreaks in Eastern Africa. The AFHSC-GEIS Rift Valley fever project is based on the identification and use of disease-emergence critical detection points as reliable signals for increased outbreak risk. The AFHSC-GEIS predictive surveillance program has formalized the Rift Valley fever project into a structured template for extending predictive surveillance capability to other Department of Defense (DoD)-priority vector- and water-borne, and zoonotic diseases and geographic areas. These include leishmaniasis, malaria, and Crimea-Congo and other viral hemorrhagic fevers in Central Asia and Africa, dengue fever in Asia and the Americas, Japanese encephalitis (JE) and chikungunya fever in Asia, and rickettsial and other tick-borne infections in the U.S., Africa and Asia. PMID:21388561

  8. Can a fatigue test of the isolated lumbar extensor muscles of untrained young men predict strength progression in a resistance exercise program?

    NARCIS (Netherlands)

    Helmhout, P.; Staal, B.; Dijk, J. van; Harts, C.; Bertina, F.; Bie, R. de

    2010-01-01

    AIM: The aim of this exploratory study was to investigate the predictive value of a fatigue test of the lumbar extensor muscles for training progression in a group of 28 healthy but predominantly sedentary male students, in an 8-week resistance exercise program. METHODS: A three-phased fatigue test

  9. Programming

    International Nuclear Information System (INIS)

    Jackson, M.A.

    1982-01-01

    The programmer's task is often taken to be the construction of algorithms, expressed in hierarchical structures of procedures: this view underlies the majority of traditional programming languages, such as Fortran. A different view is appropriate to a wide class of problem, perhaps including some problems in High Energy Physics. The programmer's task is regarded as having three main stages: first, an explicit model is constructed of the reality with which the program is concerned; second, this model is elaborated to produce the required program outputs; third, the resulting program is transformed to run efficiently in the execution environment. The first two stages deal in network structures of sequential processes; only the third is concerned with procedure hierarchies. (orig.)

  10. Evaluation of the 1996 predictions of the run-timing of wild migrant spring/summer yearling chinook in the Snake River Basin using Program RealTime

    International Nuclear Information System (INIS)

    Townsend, R.L.; Yasuda, D.; Skalski, J.R.

    1997-03-01

    This report is a post-season analysis of the accuracy of the 1996 predictions from the program RealTime. Observed 1996 migration data collected at Lower Granite Dam were compared to the predictions made by RealTime for the spring outmigration of wild spring/summer chinook. Appendix A displays the graphical reports of the RealTime program that were interactively accessible via the World Wide Web during the 1996 migration season. Final reports are available at address http://www.cqs.washington.edu/crisprt/. The CRISP model incorporated the predictions of the run status to move the timing forecasts further down the Snake River to Little Goose, Lower Monumental and McNary Dams. An analysis of the dams below Lower Granite Dam is available separately

  11. Programming

    OpenAIRE

    Jackson, M A

    1982-01-01

    The programmer's task is often taken to be the construction of algorithms, expressed in hierarchical structures of procedures: this view underlies the majority of traditional programming languages, such as Fortran. A different view is appropriate to a wide class of problem, perhaps including some problems in High Energy Physics. The programmer's task is regarded as having three main stages: first, an explicit model is constructed of the reality with which the program is concerned; second, thi...

  12. Predicting Vandalism in a General Youth Sample via the HEW Youth Development Model's Community Program Impact Scales, Age, and Sex.

    Science.gov (United States)

    Truckenmiller, James L.

    The former HEW National Strategy for Youth Development model was a community-based planning and procedural tool to enhance and to prevent delinquency through a process of youth needs assessments, needs targeted programs, and program impact evaluation. The program's 12 Impact Scales have been found to have acceptable reliabilities, substantial…

  13. The necessity for complex long-term predictions while designing systems for disposal of radwaste and role of those predictions in development of programs for environment protection

    International Nuclear Information System (INIS)

    Kedrovsky, O.L.; Schishitz, I.Y.

    1993-01-01

    Development of nuclear power in the future depends on solving two problems: creation of safe reactors; and reliable isolation of radwaste formed during all stages of the nuclear-fuel-cycle. The peculiarity of the second problem consists of the fact that considerable financial expenses are necessary for its decision. The range of the problem is characterized by the predictions of waste accumulation according to which summary activity of those materials (by the year 2000) will come up to 6 x 10 10 mCu. To successfully solve the radwaste isolation problem on the governmental level, it is necessary to formulate the corresponding regulation system. The main task of development of geological aspects of radwaste isolation consists of elimination of dangerous situations, reaching minimum damage effect, and development of a system for hydromonitoring, which includes blocks for search and standard prediction. The paper discusses the activities being carried out in Russia to solve the problems of radwaste disposal

  14. Prediction of drug-related cardiac adverse effects in humans--B: use of QSAR programs for early detection of drug-induced cardiac toxicities.

    Science.gov (United States)

    Frid, Anna A; Matthews, Edwin J

    2010-04-01

    This report describes the use of three quantitative structure-activity relationship (QSAR) programs to predict drug-related cardiac adverse effects (AEs), BioEpisteme, MC4PC, and Leadscope Predictive Data Miner. QSAR models were constructed for 9 cardiac AE clusters affecting Purkinje nerve fibers (arrhythmia, bradycardia, conduction disorder, electrocardiogram, palpitations, QT prolongation, rate rhythm composite, tachycardia, and Torsades de pointes) and 5 clusters affecting the heart muscle (coronary artery disorders, heart failure, myocardial disorders, myocardial infarction, and valve disorders). The models were based on a database of post-marketing AEs linked to 1632 chemical structures, and identical training data sets were configured for three QSAR programs. Model performance was optimized and shown to be affected by the ratio of the number of active to inactive drugs. Results revealed that the three programs were complementary and predictive performances using any single positive, consensus two positives, or consensus three positives were as follows, respectively: 70.7%, 91.7%, and 98.0% specificity; 74.7%, 47.2%, and 21.0% sensitivity; and 138.2, 206.3, and 144.2 chi(2). In addition, a prospective study using AE data from the U.S. Food and Drug Administration's (FDA's) MedWatch Program showed 82.4% specificity and 94.3% sensitivity. Furthermore, an external validation study of 18 drugs with serious cardiotoxicity not considered in the models had 88.9% sensitivity. Published by Elsevier Inc.

  15. Babcock and Wilcox revisions to CONTEMPT, computer program for predicting containment pressure-temperature response to a loss-of-coolant accident

    International Nuclear Information System (INIS)

    Hsii, Y.H.

    1975-01-01

    The CONTEMPT computer program predicts the pressure-temperature response of a single-volume reactor building to a loss-of-coolant accident. The analytical model used for the program is described. CONTEMPT assumes that the loss-of-coolant accident can be separated into two phases; the primary system blowdown and reactor building pressurization. The results of the blowdown analysis serve as the boundary conditions and are input to the CONTEMPT program. Thus, the containment model is only concerned with the pressure and temperature in the reactor building and the temperature distribution through the reactor building structures. The program also calculates building leakage and the effects of engineered safety features such as reactor building sprays, decay heat coolers, sump coolers, etc. 11 references. (U.S.)

  16. Predicted effect of landscape position on wildlife habitat value of Conservation Reserve Enhancement Program wetlands in a tile-drained agricultural region

    Science.gov (United States)

    Otis, David L.; Crumpton, William R.; Green, David; Loan-Wilsey, Anna; Cooper, Tom; Johnson, Rex R.

    2013-01-01

    Justification for investment in restored or constructed wetland projects are often based on presumed net increases in ecosystem services. However, quantitative assessment of performance metrics is often difficult and restricted to a single objective. More comprehensive performance assessments could help inform decision-makers about trade-offs in services provided by alternative restoration program design attributes. The primary goal of the Iowa Conservation Reserve Enhancement Program is to establish wetlands that efficiently remove nitrates from tile-drained agricultural landscapes. A secondary objective is provision of wildlife habitat. We used existing wildlife habitat models to compare relative net change in potential wildlife habitat value for four alternative landscape positions of wetlands within the watershed. Predicted species richness and habitat value for birds, mammals, amphibians, and reptiles generally increased as the wetland position moved lower in the watershed. However, predicted average net increase between pre- and post-project value was dependent on taxonomic group. The increased average wetland area and changes in surrounding upland habitat composition among landscape positions were responsible for these differences. Net change in predicted densities of several grassland bird species at the four landscape positions was variable and species-dependent. Predicted waterfowl breeding activity was greater for lower drainage position wetlands. Although our models are simplistic and provide only a predictive index of potential habitat value, we believe such assessment exercises can provide a tool for coarse-level comparisons of alternative proposed project attributes and a basis for constructing informed hypotheses in auxiliary empirical field studies.

  17. [Prognostic prediction of the functional capacity and effectiveness of functional improvement program of the musculoskeletal system among users of preventive care service under long-term care insurance].

    Science.gov (United States)

    Sone, Toshimasa; Nakaya, Naoki; Tomata, Yasutake; Aida, Jun; Okubo, Ichiro; Ohara, Satoko; Obuchi, Shuichi; Sugiyama, Michiko; Yasumura, Seiji; Suzuki, Takao; Tsuji, Ichiro

    2013-01-01

    The purpose of this study was to examine the effectiveness of the Functional Improvement Program of the Musculoskeletal System among users of Preventive Care Service under Long-Term Care Insurance. A total of 3,073 subjects were analyzed. We used the prediction formula to estimate the predicted value of the Kihon Checklist after one year, and calculated the measured value minus the predicted value. The subjects were divided into two groups according to the measured value minus predicted value tertiles: the lowest and middle tertile (good-to-fair measured value) and the highest tertile (poor measured value). We used a multiple logistic regression model to calculate the odds ratio (OR) and 95% confidence interval (CI) of the good-to-fair measured values of the Kihon Checklist after one year, according to the Functional Improvement Program of the Musculoskeletal System. In potentially dependent elderly, the multivariate adjusted ORs (95% CI) of the good-to-fair measured values were 2.4 (1.3-4.4) for those who attended the program eight times or more in a month (vs those who attended it three times or less in a month), 1.3 (1.0-1.8) for those who engaged in strength training using machines (vs those who did not train), and 1.4 (1.0-1.9) for those who engaged in endurance training. In this study, among potentially dependent elderly, those who attended the program eight times or more in a month and those who engaged in strength training using machines or endurance training showed a significant improvement of their functional capacity.

  18. The Integrative Model of Behavior Prediction to Explain Technology Use in Post-Graduate Teacher Education Programs in the Netherlands

    Science.gov (United States)

    Admiraal, Wilfried; Lockhorst, Ditte; Smit, Ben; Weijers, Sanne

    2013-01-01

    This study examined technology in post-graduate teacher training programs in the Netherlands. A questionnaire was completed by 111 teacher educators from 12 Dutch universities with a post-graduate teacher training program. The general view of the use of technology in Dutch post-graduate teacher education was quite conventional. Basic technology…

  19. Retention time prediction in temperature-​programmed, comprehensive two-​dimensional gas chromatography: Modeling and error assessment

    NARCIS (Netherlands)

    Barcaru, A.; Anroedh-Sampat, A.; Janssen, H.-G.; Vivó-Truyols, G.

    2014-01-01

    In this paper we present a model relating exptl. factors (column lengths, diams. and thickness, modulation times, pressures and temp. programs) with retention times. Unfortunately, an anal. soln. to calc. the retention in temp. programmed GC×GC is impossible, making thus necessary to perform a

  20. Earthquake prediction

    International Nuclear Information System (INIS)

    Ward, P.L.

    1978-01-01

    The state of the art of earthquake prediction is summarized, the possible responses to such prediction are examined, and some needs in the present prediction program and in research related to use of this new technology are reviewed. Three basic aspects of earthquake prediction are discussed: location of the areas where large earthquakes are most likely to occur, observation within these areas of measurable changes (earthquake precursors) and determination of the area and time over which the earthquake will occur, and development of models of the earthquake source in order to interpret the precursors reliably. 6 figures

  1. Beyond the GRE: using a composite score to predict 
the success of Puerto Rican students in a biomedical 
PhD program.

    Science.gov (United States)

    Pacheco, Wendy I; Noel, Richard J; Porter, James T; Appleyard, Caroline B

    2015-01-01

    The use and validity of the Graduate Record Examination General Test (GRE) to predict the success of graduate school applicants is heavily debated, especially for its possible impact on the selection of underrepresented minorities into science, technology, engineering, and math fields. To better identify candidates who would succeed in our program with less reliance on the GRE and grade point average (GPA), we developed and tested a composite score (CS) that incorporates additional measurable predictors of success to evaluate incoming applicants. Uniform numerical values were assigned to GPA, GRE, research experience, advanced course work or degrees, presentations, and publications. We compared the CS of our students with their achievement of program goals and graduate school outcomes. The average CS was significantly higher in those students completing the graduate program versus dropouts (p thesis defense. In contrast, these outcomes were not predicted by GPA, science GPA, or GRE. Recent implementation of an impromptu writing assessment during the interview suggests the CS can be improved further. We conclude that the CS provides a broader quantitative measure that better predicts success of students in our program and allows improved evaluation and selection of the most promising candidates. © 2015 W. I. Pacheco et al. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  2. The 136 MHz/400 MHz earth station antenna-noise temperature prediction program documentation for RAE-B

    Science.gov (United States)

    Chin, M.

    1972-01-01

    A simulation study to determine the 136 MHz and 400 MHz noise temperature of the ground network antennas which will track the RAE-B satellite during data transmission periods is described. Since the noise temperature of the antenna effectively sets the signal-to-noise ratio (SNR) of the received signal, a knowledge of SNR will be helpful in locating the optimum time windows for data transmission during low-noise periods. Antenna-noise temperatures at 136 MHz and 400 MHz will be predicted for selected earth-based ground stations which will support RAE-B. The antenna-noise temperature predictions will include the effects of galactic-brightness temperature, the sun, and the brightest radio stars. Predictions will cover the ten-month period from March 1, 1973 to December 31, 1973. The RAE-B mission will be expecially susceptible to SNR degradation during the two eclipses of the Sun occurring in this period.

  3. The 136 MHZ/400 MHz earth station antenna-noise temperature prediction program for RAE-B

    Science.gov (United States)

    Taylor, R. E.; Fee, J. J.; Chin, M.

    1972-01-01

    A simulation study was undertaken to determine the 136 MHz and 400 MHz noise temperature of the ground network antennas which will track the RAE-B satellite during data transmission periods. Since the noise temperature of the antenna effectively sets the signal-to-noise ratio of the received signal, a knowledge of SNR will be helpful in locating the optimum time windows for data transmission during low noise periods. Antenna noise temperatures will be predicted for selected earth-based ground stations which will support RAE-B. Telemetry data acquisition will be at 400 MHz; tracking support at 136 MHz will be provided by the Goddard Range and Range Rate (RARR) stations. The antenna-noise temperature predictions will include the effects of galactic-brightness temperature, the sun, and the brightest radio stars. Predictions will cover the ten-month period from March 1, 1973 to December 31, 1973.

  4. Using Machine Learning to Predict Swine Movements within a Regional Program to Improve Control of Infectious Diseases in the US.

    Science.gov (United States)

    Valdes-Donoso, Pablo; VanderWaal, Kimberly; Jarvis, Lovell S; Wayne, Spencer R; Perez, Andres M

    2017-01-01

    Between-farm animal movement is one of the most important factors influencing the spread of infectious diseases in food animals, including in the US swine industry. Understanding the structural network of contacts in a food animal industry is prerequisite to planning for efficient production strategies and for effective disease control measures. Unfortunately, data regarding between-farm animal movements in the US are not systematically collected and thus, such information is often unavailable. In this paper, we develop a procedure to replicate the structure of a network, making use of partial data available, and subsequently use the model developed to predict animal movements among sites in 34 Minnesota counties. First, we summarized two networks of swine producing facilities in Minnesota, then we used a machine learning technique referred to as random forest, an ensemble of independent classification trees, to estimate the probability of pig movements between farms and/or markets sites located in two counties in Minnesota. The model was calibrated and tested by comparing predicted data and observed data in those two counties for which data were available. Finally, the model was used to predict animal movements in sites located across 34 Minnesota counties. Variables that were important in predicting pig movements included between-site distance, ownership, and production type of the sending and receiving farms and/or markets. Using a weighted-kernel approach to describe spatial variation in the centrality measures of the predicted network, we showed that the south-central region of the study area exhibited high aggregation of predicted pig movements. Our results show an overlap with the distribution of outbreaks of porcine reproductive and respiratory syndrome, which is believed to be transmitted, at least in part, though animal movements. While the correspondence of movements and disease is not a causal test, it suggests that the predicted network may approximate

  5. Strengthening the case that elevated levels of programmed death ligand 1 predict poor prognosis in hepatocellular carcinoma patients

    Directory of Open Access Journals (Sweden)

    Zhong J

    2016-12-01

    Full Text Available Jian-Hong Zhong,1,* Cheng-Piao Luo,2,* Chun-Yan Zhang,2 Le-Qun Li1 1Hepatobiliary Surgery Department, 2Experimental Department, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, People’s Republic of China *These authors contributed equally to this work Abstract: Immunotherapy targeting programmed death receptor 1 and programmed death ligand 1 (PD-L1 has shown impressive antitumor efficacy in several solid cancers, including advanced hepatocellular carcinoma (HCC. Since response rates of various cancers to such immunotherapy appear to correlate with PD-L1 expression levels, several studies have examined whether PD-L1 expression correlates with HCC pathology and patient prognosis. In this paper, we analyzed the strength and limitations of a recent meta-analysis of associations of PD-L1 with HCC characteristics and patient prognosis. Keywords: hepatocellular carcinoma, programmed death ligand 1, hepatic resection, prognoses

  6. The Coastal Ocean Prediction Systems program: Understanding and managing our coastal ocean. Volume 2: Overview and invited papers

    Energy Technology Data Exchange (ETDEWEB)

    1990-05-15

    This document is a compilation of summaries of papers presented at the Coastal Ocean Prediction Systems workshop. Topics include; marine forecasting, regulatory agencies and regulations, research and application models, research and operational observing, oceanic and atmospheric data assimilation, and coastal physical processes.

  7. The Prediction of Reading Levels between Second and Third Grade Limited English Proficient Students in a Bilingual Program

    Science.gov (United States)

    Moses, Britani Creel

    2010-01-01

    The purpose of this study was to predict the third grade English reading TAKS scores while considering the same students' native language, Spanish, reading level as assessed by a state-approved reading assessment, the Evaluacion del desarrollo de la lectura (EDL), from the end of the second grade year. In addition, this study was been designed to…

  8. "In this together": Social identification predicts health outcomes (via self-efficacy) in a chronic disease self-management program.

    Science.gov (United States)

    Cameron, James E; Voth, Jennifer; Jaglal, Susan B; Guilcher, Sara J T; Hawker, Gillian; Salbach, Nancy M

    2018-03-05

    Self-management programs are an established approach to helping people cope with the challenges of chronic disease, but the psychological mechanisms underlying their effectiveness are not fully understood. A key assumption of self-management interventions is that enhancing people's self-efficacy (e.g., via the development of relevant skills and behaviours) encourages adaptive health-related behaviors and improved health outcomes. However, the group-based nature of the programs allows for the possibility that identification with other program members is itself a social psychological platform for positive changes in illness-related confidence (i.e., group-derived efficacy) and physical and mental health. The researchers evaluated this hypothesis in a telehealth version of a chronic disease self-management program delivered in 13 rural and remote communities in northern Ontario, Canada (September 2007 to June 2008). Participants were 213 individuals with a self-reported physician diagnosis of chronic lung disease, heart disease, stroke, or arthritis. Measures of social identification, group-derived efficacy, and individual efficacy were administered seven weeks after baseline, and mental and physical health outcomes (health distress, psychological well-being, depression, vitality, pain, role limits, and disability) were assessed at four months. Structural equation modeling indicated that social identification was a positive predictor of group-derived efficacy and (in turn) individual self-efficacy (controlling for baseline), which was significantly associated with better physical and mental health outcomes. The results are consistent with growing evidence of the value of a social identity-based approach in various health and clinical settings. The success of chronic disease self-management programs could be enhanced by attending to and augmenting group identification during and after the program. Copyright © 2018 Elsevier Ltd. All rights reserved.

  9. Head Start Program Quality: Examination of Classroom Quality and Parent Involvement in Predicting Children's Vocabulary, Literacy, and Mathematics Achievement Trajectories

    Science.gov (United States)

    Wen, Xiaoli; Bulotsky-Shearer, Rebecca J.; Hahs-Vaughn, Debbie L.; Korfmacher, Jon

    2012-01-01

    Guided by a developmental-ecological framework and Head Start's two-generational approach, this study examined two dimensions of Head Start program quality, classroom quality and parent involvement and their unique and interactive contribution to children's vocabulary, literacy, and mathematics skills growth from the beginning of Head Start…

  10. Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Lee-Ing Tong

    2012-02-01

    Full Text Available Solar energy has become an important energy source in recent years as it generates less pollution than other energies. A photovoltaic (PV system, which typically has many components, converts solar energy into electrical energy. With the development of advanced engineering technologies, the transfer efficiency of a PV system has been increased from low to high. The combination of components in a PV system influences its transfer efficiency. Therefore, when predicting the transfer efficiency of a PV system, one must consider the relationship among system components. This work accurately predicts whether transfer efficiency of a PV system is high or low using a novel hybrid model that combines rough set theory (RST, data envelopment analysis (DEA, and genetic programming (GP. Finally, real data-set are utilized to demonstrate the accuracy of the proposed method.

  11. A Japanese Stress Check Program screening tool predicts employee long-term sickness absence: a prospective study.

    Science.gov (United States)

    Tsutsumi, Akizumi; Shimazu, Akihito; Eguchi, Hisashi; Inoue, Akiomi; Kawakami, Norito

    2018-01-25

    On December 1, 2015, the Japanese government launched the Stress Check Program, a new occupational health policy to screen employees for high psychosocial stress in the workplace. As only weak evidence exists for the effectiveness of the program, we sought to estimate the risk of stress-associated long-term sickness absence as defined in the program manual. Participants were 7356 male and 7362 female employees in a financial service company who completed the Brief Job Stress Questionnaire (BJSQ). We followed them for 1 year and used company records to identify employees with sickness absence of 1 month or longer. We defined high-risk employees using the BJSQ and criteria recommended by the program manual. We used the Cox proportional regression model to evaluate the prospective association between stress and long-term sickness absence. During the follow-up period, we identified 34 male and 35 female employees who took long-term sickness absence. After adjustment for age, length of service, job type, position, and post-examination interview, hazard ratios (95% confidence intervals) for incident long-term sickness absence in high-stress employees were 6.59 (3.04-14.25) for men and 2.77 (1.32-5.83) for women. The corresponding population attributable risks for high stress were 23.8% (10.3-42.6) for men and 21.0% (4.6-42.1) for women. During the 1-year follow-up, employees identified as high stress (as defined by the Stress Check Program manual) had significantly elevated risks for long-term sickness absence.

  12. U.S. aerospace industry opinion of the effect of computer-aided prediction-design technology on future wind-tunnel test requirements for aircraft development programs

    Science.gov (United States)

    Treon, S. L.

    1979-01-01

    A survey of the U.S. aerospace industry in late 1977 suggests that there will be an increasing use of computer-aided prediction-design technology (CPD Tech) in the aircraft development process but that, overall, only a modest reduction in wind-tunnel test requirements from the current level is expected in the period through 1995. Opinions were received from key spokesmen in 23 of the 26 solicited major companies or corporate divisions involved in the design and manufacture of nonrotary wing aircraft. Development programs for nine types of aircraft related to test phases and wind-tunnel size and speed range were considered.

  13. Use of Admission Criteria to Predict Performance of Students in an Entry-Level Master's Program on Fieldwork Placements and in Academic Courses.

    Science.gov (United States)

    Kirchner, G L; Stone, R G; Holm, M B

    2001-01-01

    The relationships among clinical outcomes, academic success, and predictors used to screen applicants for entrance into a Master in Occupational Therapy Program (MOT) were examined. The dependent variables were grade point average in occupational therapy courses (OT-GPA), client therapy outcomes at the clinic, and ratings of MOT students by Level II Fieldwork supervisors. Predictor variables included undergraduate GPA, scores on the Graduate Record Examination (GRE), and an essay. Both undergraduate GPA and scores on the GRE were found to predict OT-GPA. The analytical section of the GRE was also positively correlated with fieldwork supervisors' ratings of students.

  14. Babcock and Wilcox revisions to CONTEMPT, computer program for predicting containment pressure-temperature response to a loss-of-coolant accident

    International Nuclear Information System (INIS)

    Hsii, Y.H.

    1976-06-01

    The CONTEMPT computer program predicts the pressure-temperature response of a single-volume reactor building to a loss-of-coolant accident. The report describes the analytical model used for the program. CONTEMPT assumes that the loss-of-coolant accident can be separated into two phases; the primary system blowdown and reactor building pressurization. The results of the blowdown analysis serve as the boundary conditions and are input to the CONTEMPT program. Thus, the containment model is only concerned with the pressure and temperature in the reactor building and the temperature distribution through the reactor building structures. The user is required to input the description of the discharge of coolant, the boiling of residual water by reactor decay heat, the superheating of steam passing through the core, and metal-water reactions. The reactor building is separated into liquid and vapor regions. Each region is in thermal equilibrium itself, but the two may not be in thermal equilibrium; the liquid and gaseous regions may have different temperatures. The reactor building is represented as consisting of several heat-conducting structures whose thermal behavior can be described by the one-dimensional multi-region heat conduction equation. The program also calculates building leakage and the effects of engineered safety features such as reactor building sprays, decay heat coolers, sump coolers, etc

  15. Contempt-LT: a computer program for predicting containment pressure-temperature response to a loss-of-coolant accident

    International Nuclear Information System (INIS)

    Wheat, L.L.; Wagner, R.J.; Niederauer, G.F.; Obenchain, C.F.

    1975-06-01

    CONTEMPT-LT is a digital computer program, written in FORTRAN IV, developed to describe the long-term behavior of water-cooled nuclear reactor containment systems subjected to postulated loss-of-coolant accident (LOCA) conditions. The program calculates the time variation of compartment pressures, temperatures, mass and energy inventories, heat structure temperature distributions, and energy exchange with adjacent compartments. The program is capable of describing the effects of leakage on containment response. Models are provided to describe fan cooler and cooling spray engineered safety systems. Up to four compartments can be modeled with CONTEMPT-LT, and any compartment except the reactor system may have both a liquid pool region and an air-vapor atmosphere region above the pool. Each region is assumed to have a uniform temperature, but the temperatures of the two regions may be different. CONTEMPT-LT can be used to model all current boiling water reactor pressure suppression systems, including containments with either vertical or horizontal vent systems. CONTEMPT-LT can also be used to model pressurized water reactor dry containments, subatmospheric containments, and dual volume containments with an annulus region, and can be used to describe containment responses in experimental containment systems. The program user defines which compartments are used, specifies input mass and energy additions, defines heat structure and leakage systems, and describes the time advancement and output control. CONTEMPT-LT source decks are available in double precision extended-binary-coded-decimal-interchange-code (EBCDIC) versions. Sample problems have been run on the IBM360/75 computer. (U.S.)

  16. Comparison of deterministically predicted genetic gains with those realised in a South African Eucalyptus grandis breeding program

    CSIR Research Space (South Africa)

    Verryn, SD

    2009-06-01

    Full Text Available breeding endeavours, are essential for modelling and predicting the economic impact of further genetic improvement. Materials and Methods The “South African Population” (plantation origin) breeding lines with the F1 generation (‘SSO’-series), F2 (‘A... trials SSO1 and SSO4, as representatives of the improvement. It was assumed that selective thinning of the ‘male families’ took place at 50%. (Male families are trees which contribute towards the pollen cloud. These families may be selectively thinned...

  17. Balance of Autonomic Nervous System Predicts Who Benefits from a Self-management Intervention Program for Irritable Bowel Syndrome.

    Science.gov (United States)

    Jarrett, Monica E; Cain, Kevin C; Barney, Pamela G; Burr, Robert L; Naliboff, Bruce D; Shulman, Robert; Zia, Jasmine; Heitkemper, Margaret M

    2016-01-31

    To determine if potential biomarkers can be used to identify subgroups of people with irritable bowel syndrome (IBS) who will benefit the most or the least from a comprehensive self-management (CSM) intervention. In a two-armed randomized controlled trial a CSM (n = 46) was compared to a usual care (n = 46) group with follow-up at 3 and 6 months post randomization. Biomarkers obtained at baseline included heart rate variability, salivary cortisol, interleukin-10 produced by unstimulated peripheral blood mononuclear cells, and lactulose/mannitol ratio. Linear mixed models were used to test whether these biomarkers predicted improvements in the primary outcomes including daily abdominal pain, Gastrointestinal Symptom score and IBS-specific quality of life. The nurse-delivered 8-session CSM intervention is more effective than usual care in reducing abdominal pain, reducing Gastrointestinal Symptom score, and enhancing quality of life. Participants with lower nighttime high frequency heart rate variability (vagal modulation) and increased low frequency/high frequency ratio (sympathovagal balance) had less benefit from CSM on abdominal pain. Salivary cortisol, IL-10, and lactulose/mannitol ratio were not statistically significant in predicting CSM benefit. Baseline symptom severity interacts with treatment, namely the benefit of CSM is greater in those with higher baseline symptoms. Cognitively-focused therapies may be less effective in reducing abdominal pain in IBS patients with higher sympathetic tone. Whether this a centrally-mediated patient characteristic or related to heightened arousal remains to be determined.

  18. Motivation and Treatment Credibility Predicts Dropout, Treatment Adherence, and Clinical Outcomes in an Internet-Based Cognitive Behavioral Relaxation Program: A Randomized Controlled Trial.

    Science.gov (United States)

    Alfonsson, Sven; Olsson, Erik; Hursti, Timo

    2016-03-08

    In previous research, variables such as age, education, treatment credibility, and therapeutic alliance have shown to affect patients' treatment adherence and outcome in Internet-based psychotherapy. A more detailed understanding of how such variables are associated with different measures of adherence and clinical outcomes may help in designing more effective online therapy. The aims of this study were to investigate demographical, psychological, and treatment-specific variables that could predict dropout, treatment adherence, and treatment outcomes in a study of online relaxation for mild to moderate stress symptoms. Participant dropout and attrition as well as data from self-report instruments completed before, during, and after the online relaxation program were analyzed. Multiple linear and logistical regression analyses were conducted to predict early dropout, overall attrition, online treatment progress, number of registered relaxation exercises, posttreatment symptom levels, and reliable improvement. Dropout was significantly predicted by treatment credibility, whereas overall attrition was associated with reporting a focus on immediate consequences and experiencing a low level of intrinsic motivation for the treatment. Treatment progress was predicted by education level and treatment credibility, whereas number of registered relaxation exercises was associated with experiencing intrinsic motivation for the treatment. Posttreatment stress symptoms were positively predicted by feeling external pressure to participate in the treatment and negatively predicted by treatment credibility. Reporting reliable symptom improvement after treatment was predicted by treatment credibility and therapeutic bond. This study confirmed that treatment credibility and a good working alliance are factors associated with successful Internet-based psychotherapy. Further, the study showed that measuring adherence in different ways provides somewhat different results, which

  19. Mathematical Modelling of a Friction Stir Welding Process to Predict the Joint Strength of Two Dissimilar Aluminium Alloys Using Experimental Data and Genetic Programming

    Directory of Open Access Journals (Sweden)

    Mohammed Yunus

    2018-01-01

    Full Text Available Friction stir welding (FSW is the most popular and efficient method of solid-state joining for similar as well as dissimilar metals and alloys. It is mostly used in applications for aerospace, rail, automotive, and marine industries. Many researchers are currently working with different perspectives on this FSW process for various combinations of materials. The general input process parameters are the thickness of the plate, axial load, rotational speed, welding speed, and tilt angle. The output parameters are joint hardness, % of elongation, and impact and yield strengths. Genetic programming (GP is a relatively new method of evolutionary computing with the principal advantage of this approach being to evaluate efficacious predictive mathematical models or equations without any prior assumption regarding the possible form of the functional relationship. This paper both defines and illustrates how GP can be applied to the FSW process to derive precise relationships between the output and input parameters in order to obtain a generalized prediction model. A GP model will assist engineers in quantifying the performance of FSW, and the results from this study can then be utilized to estimate future requirements based on the historical data to provide a robust solution. The obtained results from the GP models showed good agreement with experimental and target data at an average prediction error of 0.72%.

  20. Perceived difficulty quitting predicts enrollment in a smoking-cessation program for patients with head and neck cancer.

    Science.gov (United States)

    Duffy, Sonia A; Scheumann, Angela L; Fowler, Karen E; Darling-Fisher, Cynthia; Terrell, Jeffrey E

    2010-05-01

    To determine the predictors of participation in a smoking-cessation program among patients with head and neck cancer. This cross-sectional study is a substudy of a larger, randomized trial of patients with head and neck cancer that determined the predictors of smokers' participation in a cessation intervention. Otolaryngology clinics at three Veterans Affairs medical centers (Ann Arbor, MI, Gainesville, FL, and Dallas, TX), and the University of Michigan Hospital in Ann Arbor. 286 patients who had smoked within six months of the screening survey were eligible for a smoking-cessation intervention. Descriptive statistics and bivariate and multivariate logistic regression were used to determine the independent predictors of smokers' participation in an intervention study. Perceived difficulty quitting (as a construct of self-efficacy), health behaviors (i.e., smoking and problem drinking), clinical characteristics (i.e., depression and cancer site and stage), and demographic variables. Forty-eight percent of those eligible participated. High perceived difficulty quitting was the only statistically significant predictor of participation, whereas problem drinking, lower depressive symptoms, and laryngeal cancer site approached significance. Special outreach may be needed to reach patients with head and neck cancer who are overly confident in quitting, problem drinkers, and patients with laryngeal cancer. Oncology nurses are in an opportune position to assess patients' perceived difficulty quitting smoking and motivate them to enroll in cessation programs, ultimately improving quality of life, reducing risk of recurrence, and increasing survival for this population.

  1. A Universal Intervention Program Increases Ethnic-Racial Identity Exploration and Resolution to Predict Adolescent Psychosocial Functioning One Year Later.

    Science.gov (United States)

    Umaña-Taylor, Adriana J; Kornienko, Olga; Douglass Bayless, Sara; Updegraff, Kimberly A

    2018-01-01

    Ethnic-racial identity formation represents a key developmental task that is especially salient during adolescence and has been associated with many indices of positive adjustment. The Identity Project intervention, which targeted ethnic-racial identity exploration and resolution, was designed based on the theory that program-induced changes in ethnic-racial identity would lead to better psychosocial adjustment (e.g., global identity cohesion, self-esteem, mental health, academic achievement). Adolescents (N =215; Mage =15.02, SD =.68; 50% female) participated in a small-scale randomized control trial with an attention control group. A cascading mediation model was tested using pre-test and three follow-up assessments (12, 18, and 67 weeks after baseline). The program led to increases in exploration, subsequent increases in resolution and, in turn, higher global identity cohesion, higher self-esteem, lower depressive symptoms, and better grades. Results support the notion that increasing adolescents' ethnic-racial identity can promote positive psychosocial functioning among youth.

  2. CRAB-II: a computer program to predict hydraulics and scram dynamics of LMFBR control assemblies and its validation

    International Nuclear Information System (INIS)

    Carelli, M.D.; Baker, L.A.; Willis, J.M.; Engel, F.C.; Nee, D.Y.

    1982-01-01

    This paper presents an analytical method, the computer code CRAB-II, which calculates the hydraulics and scram dynamics of LMFBR control assemblies of the rod bundle type and its validation against prototypic data obtained for the Clinch River Breeder Reactor (CRBR) primary control assemblies. The physical-mathematical model of the code is presented, followed by a description of the testing of prototypic CRBR control assemblies in water and sodium to characterize, respectively, their hydraulic and scram dynamics behavior. Comparison of code predictions against the experimental data are presened in detail; excellent agreement was found. Also reported are experimental data and empirical correlations for the friction factor of the absorber bundle in the entire flow range (laminar to turbulent) which represent an extension of the state-of-the-art, since only fuel and blanket assemblies friction factor correlations were previously reported in the open literature

  3. Frailty Index Predicts All-Cause Mortality for Middle-Aged and Older Taiwanese: Implications for Active-Aging Programs.

    Science.gov (United States)

    Lin, Shu-Yu; Lee, Wei-Ju; Chou, Ming-Yueh; Peng, Li-Ning; Chiou, Shu-Ti; Chen, Liang-Kung

    2016-01-01

    Frailty Index, defined as an individual's accumulated proportion of listed health-related deficits, is a well-established metric used to assess the health status of old adults; however, it has not yet been developed in Taiwan, and its local related structure factors remain unclear. The objectives were to construct a Taiwan Frailty Index to predict mortality risk, and to explore the structure of its factors. Analytic data on 1,284 participants aged 53 and older were excerpted from the Social Environment and Biomarkers of Aging Study (2006), in Taiwan. A consensus workgroup of geriatricians selected 159 items according to the standard procedure for creating a Frailty Index. Cox proportional hazard modeling was used to explore the association between the Taiwan Frailty Index and mortality. Exploratory factor analysis was used to identify structure factors and produce a shorter version-the Taiwan Frailty Index Short-Form. During an average follow-up of 4.3 ± 0.8 years, 140 (11%) subjects died. Compared to those in the lowest Taiwan Frailty Index tertile ( 0.23) had significantly higher risk of death (Hazard ratio: 3.2; 95% CI 1.9-5.4). Thirty-five items of five structure factors identified by exploratory factor analysis, included: physical activities, life satisfaction and financial status, health status, cognitive function, and stresses. Area under the receiver operating characteristic curves (C-statistics) of the Taiwan Frailty Index and its Short-Form were 0.80 and 0.78, respectively, with no statistically significant difference between them. Although both the Taiwan Frailty Index and Short-Form were associated with mortality, the Short-Form, which had similar accuracy in predicting mortality as the full Taiwan Frailty Index, would be more expedient in clinical practice and community settings to target frailty screening and intervention.

  4. Symptoms of depression and anxiety predict mortality in patients undergoing oral anticoagulation: Results from the thrombEVAL study program.

    Science.gov (United States)

    Michal, Matthias; Prochaska, Jürgen H; Keller, Karsten; Göbel, Sebastian; Coldewey, Meike; Ullmann, Alexander; Schulz, Andreas; Lamparter, Heidrun; Münzel, Thomas; Reiner, Iris; Beutel, Manfred E; Wild, Philipp S

    2015-01-01

    Depression and anxiety are highly prevalent in cardiovascular patients. Therefore, we examined whether the 4-item Patient Health Questionnaire (PHQ-4, measuring symptoms of depression and anxiety) predicts all-cause mortality in outpatients with long-term oral anticoagulation (OAC). The sample comprised n=1384 outpatients from a regular medical care setting receiving long-term OAC with vitamin K antagonists. At baseline, symptoms of anxiety and depression were assessed with the PHQ-4 and the past medical history was taken. The outcome was all-cause mortality in the 24 month observation period. The median follow-up time was 13.3 months. N=191 patients from n=1384 died (death rate 13.8%). Each point increase in the PHQ-4 score was associated with a 10% increase in mortality (hazard ratio [HR] 1.10, 95% confidence interval [95% CI] 1.05-1.16) after adjustment for age, sex, high school graduation, partnership, smoking, obesity, frailty according to the Barthel Index, Charlson Comorbidity Index and CHA2DS2-VASc score. The depression component (PHQ-2) increased mortality by 22% and anxiety (GAD-2) by 11% respectively. Neither medical history of any mental disorder, nor intake of antidepressants, anxiolytics or hypnotics predicted excess mortality. Elevated symptoms of depression and, to a lesser degree, symptoms of anxiety are independently associated with all-cause mortality in OAC outpatients. The PHQ-4 questionnaire provides valuable prognostic information. These findings emphasize the need for implementing regular screening procedures and the development and evaluation of appropriate psychosocial treatment approaches for OAC patients. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  5. Verification and validation of predictive computer programs describing the near and far-field chemistry of radioactive waste disposal systems

    International Nuclear Information System (INIS)

    Read, D.; Broyd, T.W.

    1988-01-01

    This paper provides an introduction to CHEMVAL, an international project concerned with establishing the applicability of chemical speciation and coupled transport models to the simulation of realistic waste disposal situations. The project aims to validate computer-based models quantitatively by comparison with laboratory and field experiments. Verification of the various computer programs employed by research organisations within the European Community is ensured through close inter-laboratory collaboration. The compilation and review of thermodynamic data forms an essential aspect of this work and has led to the production of an internally consistent standard CHEMVAL database. The sensitivity of results to variation in fundamental constants is being monitored at each stage of the project and, where feasible, complementary laboratory studies are used to improve the data set. Currently, thirteen organisations from five countries are participating in CHEMVAL which forms part of the Commission of European Communities' MIRAGE 2 programme of research. (orig.)

  6. Clinical Use of Programmed Cell Death-1 and Its Ligand Expression as Discriminatory and Predictive Markers in Ovarian Cancer.

    Science.gov (United States)

    Chatterjee, Jayanta; Dai, Wei; Aziz, Nor Haslinda Abd; Teo, Pei Yun; Wahba, John; Phelps, David L; Maine, Christian J; Whilding, Lynsey M; Dina, Roberto; Trevisan, Giorgia; Flower, Kirsty J; George, Andrew J T; Ghaem-Maghami, Sadaf

    2017-07-01

    Purpose: We aimed to establish whether programmed cell death-1 (PD-1) and programmed cell death ligand 1 (PD-L1) expression, in ovarian cancer tumor tissue and blood, could be used as biomarkers for discrimination of tumor histology and prognosis of ovarian cancer. Experimental Design: Immune cells were separated from blood, ascites, and tumor tissue obtained from women with suspected ovarian cancer and studied for the differential expression of possible immune biomarkers using flow cytometry. PD-L1 expression on tumor-associated inflammatory cells was assessed by immunohistochemistry and tissue microarray. Plasma soluble PD-L1 was measured using sandwich ELISA. The relationships among immune markers were explored using hierarchical cluster analyses. Results: Biomarkers from the discovery cohort that associated with PD-L1 + cells were found. PD-L1 + CD14 + cells and PD-L1 + CD11c + cells in the monocyte gate showed a distinct expression pattern when comparing benign tumors and epithelial ovarian cancers (EOCs)-confirmed in the validation cohort. Receiver operating characteristic curves showed PD-L1 + and PD-L1 + CD14 + cells in the monocyte gate performed better than the well-established tumor marker CA-125 alone. Plasma soluble PD-L1 was elevated in patients with EOC compared with healthy women and patients with benign ovarian tumors. Low total PD-1 + expression on lymphocytes was associated with improved survival. Conclusions: Differential expression of immunological markers relating to the PD-1/PD-L1 pathway in blood can be used as potential diagnostic and prognostic markers in EOC. These data have implications for the development and trial of anti-PD-1/PD-L1 therapy in ovarian cancer. Clin Cancer Res; 23(13); 3453-60. ©2016 AACR . ©2016 American Association for Cancer Research.

  7. Construction of predictive models for radionuclide sorption applied to radioactive waste deep storage: an overview of the CEA research program

    International Nuclear Information System (INIS)

    Christophe Poinssot; Etienne Tevissen; Jacques Ly; Michael Descostes; Virginie Blin; Catherine Beaucaire; Florence Goutelard; Christelle Latrille; Philippe Jacquier

    2006-01-01

    Full text of publication follows: Deep geological storage is studied in France as one of the three potential options for managing long lived nuclear waste in the framework of the 1991 Law. One of the key topics of research deals with the behaviour of radionuclides (RN) in the geological environment, focusing in particular on the retention at the solid/water interfaces (in the engineered barriers or within the host rock), the diffusion process within the rock as well as the coupling between chemistry and transport processes. The final aim is to develop validated and reliable long-term predictive migration models. These researches are mainly coping with Callovo-Oxfordian argilites and near field materials such as cement and bentonite. Research are dealing both with the near-field environment - which is characterised by its evolution with time in terms of temperature, Eh balance, water composition - and the far-field environment, the chemistry of which is assumed to be roughly constant. Modelling the global RN migration in geological disposal requires having models which are intrinsically able to account for the evolution of the physical and chemical conditions of the environment. From the standpoint of performance assessment it is then necessary to acquire thermodynamic descriptions of the retention processes in order to perform calculations of the reactive transport of radionuclides In a first approach, CEA is developing for more than 15 years experiments and modelling to derive reliable predictive models for the RN migration in the geological disposal. For this purpose, a specific approach entitled the Ion-Exchangers Theory IXT was developed. It allows first to characterise the intrinsic retention properties of the pure minerals, i.e. to get evidence about the mono or multi-site character of the surface, to quantify the site(s) concentration(s) and to study the relative affinity of major solutes generally present in natural waters. This work provided a broad data

  8. A quantitative analysis of factors that influence and predict students' intention to major in and complete an undergraduate program in STEM or non-STEM

    Science.gov (United States)

    Yang, Xuemei

    2005-11-01

    The goal of this study was to explore and understand the factors that influence students' intention to major in and complete an undergraduate program in a science, technology, engineering, or mathematics (STEM) discipline, in a non-STEM field, and how students' gender directly and indirectly affects their success in college. A quantitative study of three thousand four (3004) ACT-tested students who entered a Midwestern, land-grant university as freshmen in fall, 1999 was conducted based on their ACT Assessment information and their enrollment and graduation status after five years. A wide variety of variables were considered and logistic regression, factor analysis, and path analysis were used to analyze the data. The results show that students who intended to major in or completed STEM programs generally have better academic qualifications than their counterparts who intended to major in non-STEM fields. Students who intended to major in or completed STEM programs came from lower income families and smaller communities than those who intended to major in or graduated from non-STEM programs. In this study, gender's direct effect on students' college achievement is eleven times the total of gender's indirect effects through several major factors for students in both STEM fields and non-STEM fields. Perhaps nature has favored females when students' achievement is measured as their college GPA. The results also show that the overall high dropout rate is strongly associated with students' inadequate preparation in high school and family income. Out-of-school accomplishment in community service is a negative influence on their completion of a college degree. ACT scores are not necessary for prediction of college graduation.

  9. Prediction of Participation of Undergraduate University Students in a Music and Dance Master’s Degree Program

    Directory of Open Access Journals (Sweden)

    Evangelos Bebetsos

    2015-07-01

    Full Text Available The aim of the study was the investigation of students’ attitudes and intention towards their possible participation in a graduate Music and Dance Distance Learning Master’s Degree Program. The sample consisted of consisted of 229 undergraduate University students, between the ages of 20 to 63 yrs. of age (M=34.24, SD=10.70. More specifically, 134 were students of the Hellenic Open University and 95 were students of the School of Physical Education and Sport Science, of the Democritus University of Thrace. The sample completed the version the “Planned Behavior Theory” questionnaire. Results revealed differences among students of both Universities, between experienced and less experienced ones, and also among age groups. On the contrary, no sex differences in any of the questionnaire’s factors were indicated. In conclusion, the findings of this research allow a better understanding of the distance education process, which explains the attitudes and intention(s of students’ participation, and the factors that might influence theirparticular participation.

  10. Tailoring the operative approach for appendicitis to the patient: a prediction model from national surgical quality improvement program data.

    Science.gov (United States)

    Senekjian, Lara; Nirula, Raminder

    2013-01-01

    Laparoscopic appendectomy (LA) is increasingly being performed in the United States, despite controversy about differences in infectious complication rates compared with open appendectomy (OA). Subpopulations exist in which infectious complication rates, both surgical site and organ space, differ with respect to LA compared with OA. All appendectomies in the National Surgical Quality Improvement Program database were analyzed with respect to surgical site infection (SSI) and organ space infection (OSI). Multivariate logistic regression analysis identified independent predictors of SSI or OSI. Probabilities of SSI or OSI were determined for subpopulations to identify when LA was superior to OA. From 2005 to 2009, there were 61,830 appendectomies performed (77.5% LA), of which 9,998 (16.2%) were complicated (58.7% LA). The risk of SSI was considerably lower for LA in both noncomplicated and complicated appendicitis. Across all ages, body mass index, renal function, and WBCs, LA was associated with a lower probability of SSI. The risk of OSI was considerably greater for LA in both noncomplicated and complicated appendicitis. In complicated appendicitis, OA was associated with a lower probability of OSI in patients with WBC >12 cells × 10(3)/μL. In noncomplicated appendicitis, OA was associated with a lower probability of OSI in patients with a body mass index OSI, however, SSI is consistently lower in LA patients. Copyright © 2013 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

  11. DARTAB: a program to combine airborne radionuclide environmental exposure data with dosimetric and health effects data to generate tabulations of predicted health impacts

    International Nuclear Information System (INIS)

    Begovich, C.L.; Eckerman, K.F.; Schlatter, E.C.; Ohr, S.Y.; Chester, R.O.

    1981-08-01

    The DARTAB computer code combines radionuclide environmental exposure data with dosimetric and health effects data to generate tabulations of the predicted impact of radioactive airborne effluents. DARTAB is independent of the environmental transport code used to generate the environmental exposure data and the codes used to produce the dosimetric and health effects data. Therefore human dose and risk calculations need not be added to every environmental transport code. Options are included in DARTAB to permit the user to request tabulations by various topics (e.g., cancer site, exposure pathway, etc.) to facilitate characterization of the human health impacts of the effluents. The DARTAB code was written at ORNL for the US Environmental Protection Agency, Office of Radiation Programs

  12. Predictive factors of adherence to frequency and duration components in home exercise programs for neck and low back pain: an observational study

    Directory of Open Access Journals (Sweden)

    Jimeno-Serrano Francisco J

    2009-12-01

    Full Text Available Abstract Background Evidence suggests that to facilitate physical activity sedentary people may adhere to one component of exercise prescriptions (intensity, duration or frequency without adhering to other components. Some experts have provided evidence for determinants of adherence to different components among healthy people. However, our understanding remains scarce in this area for patients with neck or low back pain. The aims of this study are to determine whether patients with neck or low back pain have different rates of adherence to exercise components of frequency per week and duration per session when prescribed with a home exercise program, and to identify if adherence to both exercise components have distinct predictive factors. Methods A cohort of one hundred eighty-four patients with chronic neck or low back pain who attended physiotherapy in eight primary care centers were studied prospectively one month after intervention. The study had three measurement periods: at baseline (measuring characteristics of patients and pain, at the end of physiotherapy intervention (measuring characteristics of the home exercise program and a month later (measuring professional behaviors during clinical encounters, environmental factors and self-efficacy, and adherence behavior. Results Adherence to duration per session (70.9% ± 7.1 was more probable than adherence to frequency per week (60.7% ± 7.0. Self-efficacy was a relevant factor for both exercise components (p Conclusion We have shown in a clinic-based study that adherence to exercise prescription frequency and duration components have distinct levels and predictive factors. We recommend additional study, and advise that differential attention be given in clinical practice to each exercise component for improving adherence.

  13. Worksite health screening programs for predicting the development of Metabolic Syndrome in middle-aged employees: a five-year follow-up study

    Directory of Open Access Journals (Sweden)

    Chen Jong-Dar

    2010-12-01

    Full Text Available Abstract Background Metabolic syndrome (MetS management programs conventionally focus on the adults having MetS. However, risk assessment for MetS development is also important for many adults potentially at risk but do not yet fulfill MetS criteria at screening. Therefore, we conducted this follow-up study to explore whether initial screening records can be efficiently applied on the prediction of the MetS occurrence in healthy middle-aged employees. Methods Utilizing health examination data, a five-year follow-up observational study was conducted for 1384 middle-aged Taiwanese employees not fulfilling MetS criteria. Data analyzed included: gender, age, MetS components, uric acid, insulin, liver enzymes, sonographic fatty liver, hepatovirus infections and lifestyle factors. Multivariate logistic regression was used to estimate the adjusted odds ratios (OR and 95% confidence interval (CI of risk for MetS development. The synergistic index (SI values and their confidence intervals of risk factor combinations were calculated; and were used to estimate the interacting effects of coupling MetS components on MetS development. Results Within five years, 13% (175 out of 1384 participants fulfilled MetS criteria. The ORs for MetS development among adults initially having one or two MetS components were 2.8 and 7.3, respectively (both p Conclusion MetS component count and combination can be used in predicting MetS development for participants potentially at risk. Worksite MetS screening programs simultaneously allow for finding out cases and for assessing risk of MetS development.

  14. Predicting the admission into medical school of African American college students who have participated in summer academic enrichment programs.

    Science.gov (United States)

    Hesser, A; Cregler, L L; Lewis, L

    1998-02-01

    To identify cognitive and noncognitive variables as predictors of the admission into medical school of African American college students who have participated in summer academic enrichment programs (SAEPs). The study sample comprised 309 African American college students who participated in SAEPs at the Medical College of Georgia School of Medicine from 1980 to 1989 and whose educational and occupational statuses were determined by follow-up tracking. A three-step logistic regression was used to analyze the data (with alpha = .05); the criterion variable was admission to medical school. The 17 predictor variables studied were one of two types, cognitive and noncognitive. The cognitive variables were (1) Scholastic Aptitude Test mathematics (SAT-M) score, (2) SAT verbal score, (3) college grade-point average (GPA), (4) college science GPA, (5) SAEP GPA, and (6) SAEP basic science GPA (BSGPA). The noncognitive variables were (1) gender, (2) highest college level at the time of the last SAEP application, (3) type of college attended (historically African American or predominately white), (4) number of SAEPs attended, (5) career aspiration (physician or another health science option) (6) parents who were professionals, (7) parents who were health care role models, (8) evidence of leadership, (9) evidence of community service, (10) evidence of special motivation, and (11) strength of letter of recommendation in the SAEP application. For each student the rating scores for the last four noncognitive variables were determined by averaging the ratings of two judges who reviewed relevant information in each student's file. In step 1, which explained 20% of the admission decision variance, SAT-M score, SAEP BSGPA, and college GPA were the three significant cognitive predictors identified. In step 2, which explained 31% of the variance, the three cognitive predictors identified in step 1 were joined by three noncognitive predictors: career aspiration, type of college, and

  15. Rapid determination of thermodynamic parameters from one-dimensional programmed-temperature gas chromatography for use in retention time prediction in comprehensive multidimensional chromatography.

    Science.gov (United States)

    McGinitie, Teague M; Ebrahimi-Najafabadi, Heshmatollah; Harynuk, James J

    2014-01-17

    A new method for estimating the thermodynamic parameters of ΔH(T0), ΔS(T0), and ΔCP for use in thermodynamic modeling of GC×GC separations has been developed. The method is an alternative to the traditional isothermal separations required to fit a three-parameter thermodynamic model to retention data. Herein, a non-linear optimization technique is used to estimate the parameters from a series of temperature-programmed separations using the Nelder-Mead simplex algorithm. With this method, the time required to obtain estimates of thermodynamic parameters a series of analytes is significantly reduced. This new method allows for precise predictions of retention time with the average error being only 0.2s for 1D separations. Predictions for GC×GC separations were also in agreement with experimental measurements; having an average relative error of 0.37% for (1)tr and 2.1% for (2)tr. Copyright © 2013 Elsevier B.V. All rights reserved.

  16. Alberta Stroke Program Early CT Score-Time Score Predicts Outcome after Endovascular Therapy in Patients with Acute Ischemic Stroke: A Retrospective Single-Center Study.

    Science.gov (United States)

    Todo, Kenichi; Sakai, Nobuyuki; Kono, Tomoyuki; Hoshi, Taku; Imamura, Hirotoshi; Adachi, Hidemitsu; Yamagami, Hiroshi; Kohara, Nobuo

    2018-04-01

    Clinical outcomes after successful endovascular therapy in patients with acute ischemic stroke are associated with several factors including onset-to-reperfusion time (ORT), the National Institute of Health Stroke Scale (NIHSS) score, and the Alberta Stroke Program Early CT Score (ASPECTS). The NIHSS-time score, calculated as follows: [NIHSS score] × [onset-to-treatment time (h)] or [NIHSS score] × [ORT (h)], has been reported to predict clinical outcomes after intravenous recombinant tissue plasminogen activator therapy and endovascular therapy for acute stroke. The objective of the current study was to assess whether the combination of the ASPECTS and the ORT can predict the outcomes after endovascular therapy. The charts of 117 consecutive ischemic stroke patients with successful reperfusion after endovascular therapy were retrospectively reviewed. We analyzed the association of ORT, ASPECTS, and ASPECTS-time score with clinical outcome. ASPECTS-time score was calculated as follows: [11 - ASPECTS] × [ORT (h)]. Rates of good outcome for patients with ASPECTS-time scores of tertile values, scores 5.67 or less, scores greater than 5.67 to 10.40 or less, and scores greater than 10.40, were 66.7%, 56.4%, and 33.3%, respectively (P < .05). Ordinal logistic regression analysis showed that the ASPECTS-time score (per category increase) was an independent predictor for better outcome (common odds ratio: .374; 95% confidence interval: .150-0.930; P < .05). A lower ASPECTS-time score may predict better clinical outcomes after endovascular treatment. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  17. Fisher: a program for the detection of H/ACA snoRNAs using MFE secondary structure prediction and comparative genomics - assessment and update.

    Science.gov (United States)

    Freyhult, Eva; Edvardsson, Sverker; Tamas, Ivica; Moulton, Vincent; Poole, Anthony M

    2008-07-21

    The H/ACA family of small nucleolar RNAs (snoRNAs) plays a central role in guiding the pseudouridylation of ribosomal RNA (rRNA). In an effort to systematically identify the complete set of rRNA-modifying H/ACA snoRNAs from the genome sequence of the budding yeast, Saccharomyces cerevisiae, we developed a program - Fisher - and previously presented several candidate snoRNAs based on our analysis 1. In this report, we provide a brief update of this work, which was aborted after the publication of experimentally-identified snoRNAs 2 identical to candidates we had identified bioinformatically using Fisher. Our motivation for revisiting this work is to report on the status of the candidate snoRNAs described in 1, and secondly, to report that a modified version of Fisher together with the available multiple yeast genome sequences was able to correctly identify several H/ACA snoRNAs for modification sites not identified by the snoGPS program 3. While we are no longer developing Fisher, we briefly consider the merits of the Fisher algorithm relative to snoGPS, which may be of use for workers considering pursuing a similar search strategy for the identification of small RNAs. The modified source code for Fisher is made available as supplementary material. Our results confirm the validity of using minimum free energy (MFE) secondary structure prediction to guide comparative genomic screening for RNA families with few sequence constraints.

  18. SCINFUL: A Monte Carlo based computer program to determine a scintillator full energy response to neutron detection for E/sub n/ between 0. 1 and 80 MeV: Program development and comparisons of program predictions with experimental data

    Energy Technology Data Exchange (ETDEWEB)

    Dickens, J.K.

    1988-04-01

    This document provides a discussion of the development of the FORTRAN Monte Carlo program SCINFUL (for scintillator full response), a program designed to provide a calculated full response anticipated for either an NE-213 (liquid) scintillator or an NE-110 (solid) scintillator. The program may also be used to compute angle-integrated spectra of charged particles (p, d, t, /sup 3/He, and ..cap alpha..) following neutron interactions with /sup 12/C. Extensive comparisons with a variety of experimental data are given. There is generally overall good agreement (<10% differences) of results from SCINFUL calculations with measured detector responses, i.e., N(E/sub r/) vs E/sub r/ where E/sub r/ is the response pulse height, reproduce measured detector responses with an accuracy which, at least partly, depends upon how well the experimental configuration is known. For E/sub n/ < 16 MeV and for E/sub r/ > 15% of the maximum pulse height response, calculated spectra are within +-5% of experiment on the average. For E/sub n/ up to 50 MeV similar good agreement is obtained with experiment for E/sub r/ > 30% of maximum response. For E/sub n/ up to 75 MeV the calculated shape of the response agrees with measurements, but the calculations underpredicts the measured response by up to 30%. 65 refs., 64 figs., 3 tabs.

  19. Predicting performance using background characteristics of international medical graduates in an inner-city university-affiliated Internal Medicine residency training program

    Directory of Open Access Journals (Sweden)

    Akhuetie Jane

    2009-07-01

    years and USMLE step I & step II clinical skills scores were 85 (IQR: 80–88 & 82 (IQR: 79–87 respectively. The median aggregate CBE scores during training were: PG1 5.8 (IQR: 5.6–6.3; PG2 6.3 (IQR 6–6.8 & PG3 6.7 (IQR: 6.7 – 7.1. 25% of our residents scored consistently above US national median ITE scores in all 3 years of training and 16% pursued a fellowship. Younger residents had higher aggregate annual CBE score than the program median (p Conclusion Background IMG features namely, age and USMLE scores predict performance evaluation and in-training examination scores during residency training. In addition enhanced research activities during residency training could facilitate fellowship goals among interested IMGs.

  20. Final Results of the Telaprevir Access Program: FibroScan Values Predict Safety and Efficacy in Hepatitis C Patients with Advanced Fibrosis or Cirrhosis.

    Directory of Open Access Journals (Sweden)

    Antonia Lepida

    Full Text Available Liver stiffness determined by transient elastography is correlated with hepatic fibrosis stage and has high accuracy for detecting severe fibrosis and cirrhosis in chronic hepatitis C patients. We evaluated the clinical value of baseline FibroScan values for the prediction of safety and efficacy of telaprevir-based therapy in patients with advanced fibrosis and cirrhosis in the telaprevir Early Access Program HEP3002.1,772 patients with HCV-1 and bridging fibrosis or cirrhosis were treated with telaprevir plus pegylated interferon-α and ribavirin (PR for 12 weeks followed by PR alone, the total treatment duration depending on virological response and previous response type. Liver fibrosis stage was determined either by liver biopsy or by non-invasive markers. 1,282 patients (72% had disease stage assessed by FibroScan; among those 46% were classified as Metavir F3 at baseline and 54% as F4.Overall, 1,139 patients (64% achieved a sustained virological response (SVR by intention-to-treat analysis. Baseline FibroScan values were tested for association with SVR and the occurrence of adverse events. By univariate analysis, higher baseline FibroScan values were predictive of lower sustained virological response rates and treatment-related anemia. By multivariate analysis, FibroScan was no longer statistically significant as an independent predictor, but higher FibroScan values were correlated with the occurrence of infections and serious adverse events.FibroScan has a limited utility as a predictor of safety and efficacy in patients treated with telaprevir-based triple therapy. Nevertheless it can be used in association with other clinical and biological parameters to help determine patients who will benefit from the triple regiments.ClinicalTrials.gov NCT01508286.

  1. Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces.

    Science.gov (United States)

    Samal, Lipika; D'Amore, John D; Bates, David W; Wright, Adam

    2017-11-01

    Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry so are rarely used. Due to new data interoperability standards for electronic health records (EHRs), other options are available. As a clinical case study, we sought to build a scalable, web-based system that would automate calculation of kidney failure risk and display clinical decision support to users in primary care practices. We developed a single-page application, web server, database, and application programming interface to calculate and display kidney failure risk. Data were extracted from the EHR using the Consolidated Clinical Document Architecture interoperability standard for Continuity of Care Documents (CCDs). EHR users were presented with a noninterruptive alert on the patient's summary screen and a hyperlink to details and recommendations provided through a web application. Clinic schedules and CCDs were retrieved using existing application programming interfaces to the EHR, and we provided a clinical decision support hyperlink to the EHR as a service. We debugged a series of terminology and technical issues. The application was validated with data from 255 patients and subsequently deployed to 10 primary care clinics where, over the course of 1 year, 569 533 CCD documents were processed. We validated the use of interoperable documents and open-source components to develop a low-cost tool for automated clinical decision support. Since Consolidated Clinical Document Architecture-based data extraction extends to any certified EHR, this demonstrates a successful modular approach to clinical decision support. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

  2. Fisher: a program for the detection of H/ACA snoRNAs using MFE secondary structure prediction and comparative genomics – assessment and update

    Directory of Open Access Journals (Sweden)

    Tamas Ivica

    2008-07-01

    Full Text Available Abstract Background The H/ACA family of small nucleolar RNAs (snoRNAs plays a central role in guiding the pseudouridylation of ribosomal RNA (rRNA. In an effort to systematically identify the complete set of rRNA-modifying H/ACA snoRNAs from the genome sequence of the budding yeast, Saccharomyces cerevisiae, we developed a program – Fisher – and previously presented several candidate snoRNAs based on our analysis 1. Findings In this report, we provide a brief update of this work, which was aborted after the publication of experimentally-identified snoRNAs 2 identical to candidates we had identified bioinformatically using Fisher. Our motivation for revisiting this work is to report on the status of the candidate snoRNAs described in 1, and secondly, to report that a modified version of Fisher together with the available multiple yeast genome sequences was able to correctly identify several H/ACA snoRNAs for modification sites not identified by the snoGPS program 3. While we are no longer developing Fisher, we briefly consider the merits of the Fisher algorithm relative to snoGPS, which may be of use for workers considering pursuing a similar search strategy for the identification of small RNAs. The modified source code for Fisher is made available as supplementary material. Conclusion Our results confirm the validity of using minimum free energy (MFE secondary structure prediction to guide comparative genomic screening for RNA families with few sequence constraints.

  3. Predicting Success in Nursing Programs

    Science.gov (United States)

    Herrera, Cheryl; Blair, Jennifer

    2015-01-01

    As the U.S. population ages and policy changes emerge, such as the Patient Protection and Affordable Care Act of 2010, the U.S. will experience a significant shortage of Registered Nurses (RNs). Many colleges and universities are attempting to increase the size of nursing cohorts to respond to this imminent shortage. Notwithstanding a 2.6%…

  4. Predicting performance using background characteristics of international medical graduates in an inner-city university-affiliated Internal Medicine residency training program

    Science.gov (United States)

    Kanna, Balavenkatesh; Gu, Ying; Akhuetie, Jane; Dimitrov, Vihren

    2009-01-01

    I & step II clinical skills scores were 85 (IQR: 80–88) & 82 (IQR: 79–87) respectively. The median aggregate CBE scores during training were: PG1 5.8 (IQR: 5.6–6.3); PG2 6.3 (IQR 6–6.8) & PG3 6.7 (IQR: 6.7 – 7.1). 25% of our residents scored consistently above US national median ITE scores in all 3 years of training and 16% pursued a fellowship. Younger residents had higher aggregate annual CBE score than the program median (p ITE scores, reflecting exam-taking skills. Success in acquiring a fellowship was associated with consistent fellowship interest (p < 0.05) and research publications or presentations (p <0.05). None of the other characteristics including visa status were associated with the outcomes. Conclusion Background IMG features namely, age and USMLE scores predict performance evaluation and in-training examination scores during residency training. In addition enhanced research activities during residency training could facilitate fellowship goals among interested IMGs. PMID:19594918

  5. Low pain intensity after opioid withdrawal as a first step of a comprehensive pain rehabilitation program predicts long-term nonuse of opioids in chronic noncancer pain.

    Science.gov (United States)

    Krumova, Elena K; Bennemann, Philipp; Kindler, Doris; Schwarzer, Andreas; Zenz, Michael; Maier, Christoph

    2013-09-01

    In specialized pain clinics there is an increasing number of patients with severe chronic noncancer pain (CNCP) despite long-term opioid medication. Few clinical studies show short-term pain relief after opioid withdrawal (OW). We have evaluated the relation between pain intensity after OW and long-term opioid nonuse. One hundred two consecutive patients with severe CNCP despite opioid medication (mean treatment duration, 43 mo) reported pain intensity (numerical rating scale, 0 to 10), Pain Disability Index, mood (CES-D), and quality of life (Short Form 36) before, shortly, and 12 to 24 months after inpatient OW. Total opioid withdrawal (n = 78) or significant dose reduction (DR; n = 24, mean reduction, 82%) was performed after individual decision. Opioid intake 12 to 24 months later, respectively dose increase ≥ 100% (DR group), was considered relapse. T tests, multivariable analysis of variance, logistic regression. After OW current pain intensity significantly decreased on an average by 41% (6.4 ± 2.4 vs. 3.8 ± 2.5), maximal and average pain by 18% and 24%, respectively. Twelve to 24 months later 42 patients (41%) relapsed (31 of the total opioid withdrawal group, 6 of the DR group, 5 lost). Patients without later relapse showed significantly lower pain scores than the later relapsed patients already shortly after OW (5.0 ± 2.2 vs. 5.9 ± 2.1) and 12 to 24 months later (5.5 ± 2.4 vs. 6.5 ± 2.0). There was a significant relation between relapse probability and pain intensity immediately after OW. In many patients with severe CNCP, despite opioid medication, sustainable pain relief can be achieved if OW is included in the rehabilitation program. Consequently, we recommend OW for opioid-resistant CNCP before any opioid escalation. Lower pain intensity shortly after OW may predict the long-term opioid nonuse probability.

  6. Baseline β-catenin, programmed death-ligand 1 expression and tumour-infiltrating lymphocytes predict response and poor prognosis in BRAF inhibitor-treated melanoma patients.

    Science.gov (United States)

    Massi, Daniela; Romano, Emanuela; Rulli, Eliana; Merelli, Barbara; Nassini, Romina; De Logu, Francesco; Bieche, Ivan; Baroni, Gianna; Cattaneo, Laura; Xue, Gongda; Mandalà, Mario

    2017-06-01

    The activation of oncogenic Wnt/β-catenin pathway in melanoma contributes to a lack of T-cell infiltration. Whether baseline β-catenin expression in the context of tumour-infiltrating lymphocytes (TILs) and programmed death ligand-1 (PD-L1) overexpression correlates with prognosis of metastatic melanoma patients (MMPs) treated with mitogen-activated protein kinase, MAPK inhibitor (MAPKi) monotherapy, however, has not been fully clarified. Sixty-four pre-treatment formalin-fixed and paraffin embedded melanoma samples from MMP treated with a BRAF inhibitor (n = 39) or BRAF and MEK inhibitors (n = 25) were assessed for presence of β-catenin, PD-L1, cluster of differentiation (CD)8, CD103 and forkhead box protein P3 (FOXP3) expression by immunohistochemistry, and results were correlated with clinical outcome. Quantitative assessment of mRNA transcripts associated with Wnt/β-catenin pathway and immune response was performed in 51 patients. We found an inverse correlation between tumoural β-catenin expression and the level of CD8, CD103 or forkhead box protein P3 (FOXP3) positivity in the tumour microenvironment (TME). By multivariate analysis, PD-L1 <5% (odds ratio, OR 0.12, 95% confidence interval, CI 0.03-0.53, p = 0.005) and the presence of CD8+ T cells (OR 18.27, 95%CI 2.54-131.52, p = 0.004) were significantly associated with a higher probability of response to MAPKi monotherapy. Responding patients showed a significantly increased expression of mRNA transcripts associated with adaptive immunity and antigen presentation. By multivariate analysis, progression-free survival (PFS) (hazards ratio (HR) = 0.25 95%CI 0.10-0.61, p = 0.002) and overall survival (OS) (HR = 0.24 95%CI 0.09-0.67, p = 0.006) were longer in patients with high density of CD8+ T cells and β-catenin <10% than those without CD8+ T cells infiltration and β-catenin ≥10%. Our findings provide evidence that in the context of MAPKi monotherapy, immune subsets in the (TME) and

  7. Modeling land use and cover change: Predicting re-enrollment in the Conservation Reserve Program using GIS and data mining procedures

    Science.gov (United States)

    Shcherbaniuk, Mykola Vasylyovych

    In this research, the concept of the CRP lands being re-enrolled or returned to crop production was considered as a part of a larger conceptual domain of land use and cover change (LUCC). The aim of the study was to develop models for predicting the probability of farmers' re-enrollment in the Conservation Reserve Program (CRP) in the Cache River Watershed, in Southern Illinois. The results of these analyses showed that the probability of the CRP re-enrollment is a function of a number of factors including both the economic incentives to farmers as well as the spatial and non-spatial characteristics of the farms and the CRP land parcels. Both logistical regressions and decision tree models confirmed the importance of seven individual variables. It was found that the probability of CRP re-enrollment was higher for parcels located closer to a stream, the national forest, a road and a town. Also higher re-enrollment was indicated for predominant farm location adjacent to the national forest and within a floodplain and on dry soils, higher proportion of farmland in pasture and higher elevation and population density. Alternatively, the probability of re-enrollment was found to be lower closer to an interstate highway, predominant farm location adjacent to the national refuge and higher proportion of farmland in row crops. The probability of CRP re-enrollment was found to be higher at higher CRP rental rates, lower commodity prices, lower cropland acreage, and lower proportion of farmland in cropland. For two additional important determinants, the probability of re-enrollment was found to be higher for lower proportion of cropland enrolled in CRP and in cases where the farmer was both the owner and operator. Overall, the results of this study indicate that the spatial heterogeneity of farms and land parcels (as accounted by spatial variables that were found to be relevant) should be taken into account while malting the plans for the CRP re-enrollment for the 2007 farm

  8. Evaluate the capability and accuracy of response-2000 program in prediction of the shear capacities of reinforced and prestressed concrete members

    Directory of Open Access Journals (Sweden)

    Ibrahim M. Metwally

    2012-08-01

    Member response analysis and sectional analysis were both used in Response-2000 to predict the behavior of the beams. Member response calculates the full member behavior including the deflection and curvature along the member length, as well as predicted failure modes. The analysis was performed by specifying the length subjected to shear and any constant moment region. Response-2000 provided a very good prediction of experimental behavior when compared to a database of 534 beams tested in shear. These include prestressed and reinforced sections, very large footing-like sections, sections made with very high strength concrete and elements with unusual geometry. All are predicted well. The results include that Response-2000 can predict the failure shear with an average experimental over predicted shear ratio of 1.05 with a coefficient of variation of 12%. This compares favorably to the ACI 318-08 [2] Code prediction ratios that have an average of 1.20 and a coefficient of variation of 32%.

  9. Predicting Treatment Success in Social Skills Training for Adolescents with Autism Spectrum Disorders: The UCLA Program for the Education and Enrichment of Relational Skills

    Science.gov (United States)

    Chang, Ya-Chih; Laugeson, Elizabeth A.; Gantman, Alexander; Ellingsen, Ruth; Frankel, Fred; Dillon, Ashley R.

    2014-01-01

    This study seeks to examine the predictors of positive social skills outcomes from the University of California, Los Angeles Program for the Education and Enrichment of Relational Skills, an evidence-based parent-assisted social skills program for high-functioning middle school and high school adolescents with autism spectrum disorders. The…

  10. Predicting Wanton Assault in a General Youth Sample via the HEW Youth Development Model's Community Program Impact Scales, Age and Sex.

    Science.gov (United States)

    Truckenmiller, James L.

    The former HEW National Strategy for Youth Development Model was a community-based planning and procedural tool designed to enhance positive youth development and prevent delinquency through a process of youth needs assessment, development of targeted programs, and program impact evaluation. A series of 12 Impact Scales most directly reflect the…

  11. Pulverized coal devolatilization prediction

    International Nuclear Information System (INIS)

    Rojas, Andres F; Barraza, Juan M

    2008-01-01

    The aim of this study was to predict the two bituminous coals devolatilization at low rate of heating (50 Celsius degrade/min), with program FG-DVC (functional group Depolymerization. Vaporization and crosslinking), and to compare the devolatilization profiles predicted by program FG-DVC, which are obtained in the thermogravimetric analyzer. It was also study the volatile liberation at (10 4 k/s) in a drop-tube furnace. The tar, methane, carbon monoxide, and carbon dioxide, formation rate profiles, and the hydrogen, oxygen, nitrogen and sulphur, elemental distribution in the devolatilization products by FG-DVC program at low rate of heating was obtained; and the liberation volatile and R factor at high rate of heating was calculated. it was found that the program predicts the bituminous coals devolatilization at low rate heating, at high rate heating, a volatile liberation around 30% was obtained

  12. WALS Prediction

    NARCIS (Netherlands)

    Magnus, J.R.; Wang, W.; Zhang, Xinyu

    2012-01-01

    Abstract: Prediction under model uncertainty is an important and difficult issue. Traditional prediction methods (such as pretesting) are based on model selection followed by prediction in the selected model, but the reported prediction and the reported prediction variance ignore the uncertainty

  13. Factors predicting crisis counselor referrals to other crisis counseling, disaster relief, and psychological services: a cross-site analysis of post-Katrina programs.

    Science.gov (United States)

    Rosen, Craig S; Matthieu, Monica M; Norris, Fran H

    2009-05-01

    An important aspect of crisis counseling is linking survivors with services for their unmet needs. We examined determinants of referrals for disaster relief, additional crisis counseling, and psychological services in 703,000 crisis counseling encounters 3-18 months after Hurricane Katrina. Referrals for disaster relief were predicted by clients' losses, age (adults rather than children), and urbanicity. Referrals for additional counseling and psychological services were predicted by urbanicity, losses and trauma exposure, prior trauma, and preexisting mental health problems. Counseling and psychological referrals declined over time despite continuing mental health needs. Results confirm large urban-rural disparities in access to services.

  14. CONTEMPT-LT/028: a computer program for predicting containment pressure-temperature response to a loss-of-coolant accident

    International Nuclear Information System (INIS)

    Hargroves, D.W.; Metcalfe, L.J.; Wheat, L.L.; Niederauer, G.F.; Obenchain, C.F.

    1979-03-01

    CONTEMPT-LT is a digital computer program, written in FORTRAN IV, developed to describe the long-term behavior of water-cooled nuclear reactor containment systems subjected to postulated loss-of-coolant accident (LOCA) conditions. The program calculates the time variation of compartment pressures, temperatures, mass and energy inventories, heat structure temperature distributions, and energy exchange with adjacent compartments. The program is capable of describing the effects of leakage on containment response. Models are provided to describe fan cooler and cooling spray engineered safety systems. An annular fan model is also provided to model pressure control in the annular region of dual containment systems. Up to four compartments can be modeled with CONTEMPT-LT, and any compartment except the reactor system may have both a liquid pool region and an air--vapor atmosphere region above the pool. Each region is assumed to have a uniform temperature, but the temperatures of the two regions may be different

  15. Development of a computing program for prediction of wind power for midsize and wide grid areas. Final report; Entwicklung eines Rechenmodells zur Vorhersage der Windleistung fuer mittlere und grosse Versorgungsgebiete. Abschlussbericht

    Energy Technology Data Exchange (ETDEWEB)

    Reeder, L.; Rohrig, K.; Ernst, B.; Schorn, P.; Bettels, B.

    2002-06-30

    In co-operation with partners out of industry and research a machine program was developed predicting the output of wind power plants. Three attributes should be realised by this prediction tool: Short computing time, usable for various grid regions, high reliability. Therewith the transmission system operators get a tool for reducing the amount of control energy which is needed to ensure the balance between power generation and consumption in their networks. This prediction tool for up to two days was developed exemplary for the northern grid area of the transmission system operator 'E.ON Netz GmbH' (ENE). The wind power prediction is based on numerical weather forecast from the German weather service (Deutscher Wetterdienst). The weather forecast is given for 16 representative sites within the ENE-area. The meso-scale model KLIMM (Klima Model Mainz) was used to calculate the meteorological variables near to the wind farms, which are connected to the one transformer substation belonging to one representative place. Therefor KLIMM is fed with the weather forecast given for one limited location in the representative sites. The transformation of the meteorological variables to the output of wind power plants at the representative site is done by Neural Networks. These Neural Networks have been trained with corresponding measurements. Using an existing online-model the total wind power for the whole ENE-area will be calculated from the individual wind power of the representative sites. The Evaluation of the prediction- and measured data from 2001 shows comparing with reference-models, that the prediction-model evolved in the project lead to very good results. (orig.)

  16. Admission Factors Predicting Family Medicine Specialty Choice: A Literature Review and Exploratory Study among Students in the Rural Medical Scholars Program

    Science.gov (United States)

    Avery, Daniel M., Jr.; Wheat, John R.; Leeper, James D.; McKnight, Jerry T.; Ballard, Brent G.; Chen, Jia

    2012-01-01

    Purpose: The Rural Medical Scholars Program (RMSP) was created to increase production of rural family physicians in Alabama. Literature review reveals reasons medical students choose careers in family medicine, and these reasons can be categorized into domains that medical schools can address through admission, curriculum, and structural…

  17. Verification tests for GRAD, a computer program to predict nonuniform deformation and failure of Zr-2.5 wt percent Nb pressure tubes during a postulated loss-of-coolant accident

    International Nuclear Information System (INIS)

    Shewfelt, R.S.W.; Godin, D.P.

    1985-03-01

    During a postulated loss-of-coolant accident in a CANDU reactor, the temperature of the pressure tubes could rise sufficiently so that ballooning could occur. It is also likely that there would be a variation in temperature around the tube circumference, causing the deformation to be nonuniform. Since the deformation of the pressure tube controls how the core heat is transferred to the surrounding moderator, which is a large heat sink, a computer program, GRAD, has been developed to predict this nonuniform deformation. Numerous biaxial creep tests were done, where the temperature of internally pressurized sections of Zr-2.5 wt percent Nb pressure tubes were ramped to check the ability of GRAD to predict the resulting nonuniform deformation and possible tube failure. GRAD was successful in predicting the average transverse creep strain observed during the tests and the local transverse creep strain at the end of the tests. GRAD was also able to predict the failure time and average transverse creep strain at failure for all the specimens that failed

  18. User manual of Soil and Cesium Transport (SACT), a program to predict long-term Cs distribution using USLE for soil erosion, transportation and deposition

    International Nuclear Information System (INIS)

    Saito, Hiroshi; Yamaguchi, Masaaki; Kitamura, Akihiro

    2016-12-01

    This manual provides useful and necessary information to users of 'SACT' (Soil and Cesium Transport), which Japan Atomic Energy Agency (JAEA) has developed to predict a long-term distribution of Cs deposited on the land surface of Fukushima due to the Fukushima Daiichi Nuclear Power Station accident on March 11, 2011. SACT calculates soil movement (erosion, transportation and deposition) and resulting Cs migration, and predicts its future distribution, with the assumption that Cs is adhered to soil initially. SACT uses USLE (Universal Soil Loss Equation) for potential soil loss and simple hydraulic equations for soil transportation and deposition in which soil is divided into course-grained sand and fine-grained silt/clay. The amount of Cs moved with soil is predicted by the amount of above-mentioned soil movement and concentration ratio of Cs for each grain-size. SACT utilizes the 'ArcGIS' software and the GIS (Geographical Information System). SACT is characterized by its simplicity which enables fast calculation for wide area for long-term duration, using existing simple equations including USLE. Data for used parameters are widely available, and site-specific calculations are possible by using data obtained from the targeted area. (author)

  19. REGULATORY AND TRANSPORT PROTEINS OF BLOOD SERUM AND FOLLICULAR FLUID IN PREDICTION OF EFFICIENCY OF THE PROGRAMS OF IN VITRO FERTILIZATION IN WOMEN WITH ADENOMYOSIS

    Directory of Open Access Journals (Sweden)

    Виктория Васильевна Лихачева

    2017-09-01

    Full Text Available Research objective: Study of the content as well as the effect on the outcomes of in vitro fertilization (IVF programs of some regulatory and transport proteins: (alfa-2-macroglobulin (α2-МG, alfa-1-antitrypsin (α1-АТ, pregnancy associated alfa-2-glycoprotein (PAG, lactoferrin (LF, and albumin (ALB in blood serum and follicular fluid in women with adenomyosis and tubal factor of infertility. Materials and methods. The study included 89 patients, among them in 31 women the cause of infertility was adenomyosis (as a result of IVF, 12 patients got pregnant and 19 did not, and 58 patients with tubal infertility (24 patients got pregnant and 34 did not. The content of alfa-2-macroglobulin (α2-MG, alfa-1-antitrypsin (α1-АТ and pregnancy associated alfa-2-glycoprotein (PAG, lactoferrin (LF was determined by the quantitative rocket ummunoelectrophoresis method with the application of research test systems developed on the basis of research laboratory (RL of immunology at Novokuznetsk State Institute for Further Training of Physicians. The concentration of albumin was determined by biochemistry methods (with bromcresol green. Results. The research revealed that serum levels of alfa-2-macroglobulin, alfa-1-antitrypsin, pregnancy associated globulin, lactoferrin and albumin in women with adenomyosis generally over the group did not reliably differ from such indexes in women with tubal infertility. In the group of women with adenomyosis the low level of alfa-2-macroglobulin (less than 1.75 g/L and alfa-1-antitrypsin (less than 1.9 g/L in blood serum was associated with negative IVF program outcome. In tubal infertility negative outcome of IVF program was registered at the reduction in the blood serum albumin level below 41.5 g/L. Conclusion: The revealed changes, namely the α2-MG level below 1.75 g/L and α1-AT below 1.9 g/L in the infertile patients with adenomyosis, as well as the serum albumin level below 41.5 g/L in women with

  20. Climate prediction and predictability

    Science.gov (United States)

    Allen, Myles

    2010-05-01

    Climate prediction is generally accepted to be one of the grand challenges of the Geophysical Sciences. What is less widely acknowledged is that fundamental issues have yet to be resolved concerning the nature of the challenge, even after decades of research in this area. How do we verify or falsify a probabilistic forecast of a singular event such as anthropogenic warming over the 21st century? How do we determine the information content of a climate forecast? What does it mean for a modelling system to be "good enough" to forecast a particular variable? How will we know when models and forecasting systems are "good enough" to provide detailed forecasts of weather at specific locations or, for example, the risks associated with global geo-engineering schemes. This talk will provide an overview of these questions in the light of recent developments in multi-decade climate forecasting, drawing on concepts from information theory, machine learning and statistics. I will draw extensively but not exclusively from the experience of the climateprediction.net project, running multiple versions of climate models on personal computers.

  1. Gate valve performance prediction

    International Nuclear Information System (INIS)

    Harrison, D.H.; Damerell, P.S.; Wang, J.K.; Kalsi, M.S.; Wolfe, K.J.

    1994-01-01

    The Electric Power Research Institute is carrying out a program to improve the performance prediction methods for motor-operated valves. As part of this program, an analytical method to predict the stem thrust required to stroke a gate valve has been developed and has been assessed against data from gate valve tests. The method accounts for the loads applied to the disc by fluid flow and for the detailed mechanical interaction of the stem, disc, guides, and seats. To support development of the method, two separate-effects test programs were carried out. One test program determined friction coefficients for contacts between gate valve parts by using material specimens in controlled environments. The other test program investigated the interaction of the stem, disc, guides, and seat using a special fixture with full-sized gate valve parts. The method has been assessed against flow-loop and in-plant test data. These tests include valve sizes from 3 to 18 in. and cover a considerable range of flow, temperature, and differential pressure. Stem thrust predictions for the method bound measured results. In some cases, the bounding predictions are substantially higher than the stem loads required for valve operation, as a result of the bounding nature of the friction coefficients in the method

  2. Cancer predictive value of cytogenetic markers used in occupational health surveillance programs. A report from an ongoing study by the European Study Group on Cytogenetic Biomarkers and Health

    Energy Technology Data Exchange (ETDEWEB)

    Hagmar, Lars; Stroemberg, Ulf; Mikoczy, Zoli; Tinnerberg, Hakan; Skerfving, Staffan [Department of Occupational and Environmental Medicine, Lund University, S-221 85 Lund (Sweden); Bonassi, Stefano; Lando, Cecilia [Department of Environmental Epidemiology, Istituto Nazionale per la Ricerca sul Cancro, Viale Benedetto XV, I-1016132 Genoa (Italy); Hansteen, Inger-Lise [Department of Occupational Medicine, Telemark Central Hospital, N-3710 Skien (Norway); Montagud, Alicia Huici [Centro Nacional de Condiciones de Trabajo, Instituto Nacional de Seguridad e Higiene en el Trabajo, Dulcet 2-10, ES-08034 Barcelona (Spain); Knudsen, Lisbeth [National Institute of Occupational Health, Lersoe Parkalle 105, DK-2100 Copenhagen (Denmark); Norppa, Hannu [Finnish Institute of Occupational Health, Topeliuksekatu 41 aA, FIN-00250 Helsinki (Finland); Reuterwall, Christina [National Institute of Work Life, S-171 84 Solna (Sweden); Broegger, Anton [Norwegian Radium Hospital, Oslo (Norway); Forni, Alessandra [Istituto di Medicina del Lavoro Clinica del Lavoro `L. Devoto`, Milan (Italy); Hoegstedt, Benkt [Department of Occupational Medicine, Central Hospital, Halmstad (Sweden); Lambert, Bo [Department of Environmental Medicine, Centre for Nutrition and Toxicology, Karolinska Institute, Stockholm (Sweden); Mitelman, Felix [Department of Clinical Genetics, Lund University, Lund (Sweden); Nordenson, Ingrid [National Institute of Work Life, Umea (Sweden); Salomaa, Sisko [Finnish Center for Radiation and Nuclear Safety, Helsinki (Finland)

    1998-09-20

    The cytogenetic endpoints in peripheral blood lymphocytes: chromosomal aberrations (CA), sister chromatid exchange (SCE) and micronuclei (MN) are established biomarkers of exposure for mutagens or carcinogens in the work environment. However, it is not clear whether these biomarkers also may serve as biomarkers for genotoxic effects which will result in an enhanced cancer risk. In order to assess this problem, Nordic and Italian cohorts were established, and preliminary results from these two studies indicated a predictive value of CA frequency for cancer risk, whereas no such associations were observed for SCE or MN. A collaborative study between the Nordic and Italian research groups, will enable a more thorough evaluation of the cancer predictivity of the cytogenetic endpoints. We here report on the establishment of a joint data base comprising 5271 subjects, examined 1965-1988 for at least one cytogenetic biomarker. Totally, 3540 subjects had been examined for CA, 2702 for SCE and 1496 for MN. These cohorts have been followed-up with respect to subsequent cancer mortality or cancer incidence, and the expected values have been calculated from rates derived from the general populations in each country. Stratified cohort analyses will be performed with respect to the levels of the cytogenetic biomarkers. The importance of potential effect modifiers such as gender, age at test, and time since test, will be evaluated using Poisson regression models. The remaining two potential effect modifiers, occupational exposures and smoking, will be assessed in a case-referent study within the study base

  3. Cancer predictive value of cytogenetic markers used in occupational health surveillance programs. A report from an ongoing study by the European Study Group on Cytogenetic Biomarkers and Health

    International Nuclear Information System (INIS)

    Hagmar, Lars; Stroemberg, Ulf; Mikoczy, Zoli; Tinnerberg, Hakan; Skerfving, Staffan; Bonassi, Stefano; Lando, Cecilia; Hansteen, Inger-Lise; Montagud, Alicia Huici; Knudsen, Lisbeth; Norppa, Hannu; Reuterwall, Christina; Broegger, Anton; Forni, Alessandra; Hoegstedt, Benkt; Lambert, Bo; Mitelman, Felix; Nordenson, Ingrid; Salomaa, Sisko

    1998-01-01

    The cytogenetic endpoints in peripheral blood lymphocytes: chromosomal aberrations (CA), sister chromatid exchange (SCE) and micronuclei (MN) are established biomarkers of exposure for mutagens or carcinogens in the work environment. However, it is not clear whether these biomarkers also may serve as biomarkers for genotoxic effects which will result in an enhanced cancer risk. In order to assess this problem, Nordic and Italian cohorts were established, and preliminary results from these two studies indicated a predictive value of CA frequency for cancer risk, whereas no such associations were observed for SCE or MN. A collaborative study between the Nordic and Italian research groups, will enable a more thorough evaluation of the cancer predictivity of the cytogenetic endpoints. We here report on the establishment of a joint data base comprising 5271 subjects, examined 1965-1988 for at least one cytogenetic biomarker. Totally, 3540 subjects had been examined for CA, 2702 for SCE and 1496 for MN. These cohorts have been followed-up with respect to subsequent cancer mortality or cancer incidence, and the expected values have been calculated from rates derived from the general populations in each country. Stratified cohort analyses will be performed with respect to the levels of the cytogenetic biomarkers. The importance of potential effect modifiers such as gender, age at test, and time since test, will be evaluated using Poisson regression models. The remaining two potential effect modifiers, occupational exposures and smoking, will be assessed in a case-referent study within the study base

  4. Cancer predictive value of cytogenetic markers used in occupational health surveillance programs: a report from an ongoing study by the European Study Group on Cytogenetic Biomarkers and Health

    DEFF Research Database (Denmark)

    Hagmar, L; Bonassi, S; Strömberg, U

    1998-01-01

    cytogenetic biomarker. Totally, 3540 subjects had been examined for CA, 2702 for SCE and 1496 for MN. These cohorts have been followed-up with respect to subsequent cancer mortality or cancer incidence, and the expected values have been calculated from rates derived from the general populations in each...... as biomarkers for genotoxic effects which will result in an enhanced cancer risk. In order to assess this problem, Nordic and Italian cohorts were established, and preliminary results from these two studies indicated a predictive value of CA frequency for cancer risk, whereas no such associations were observed...... country. Stratified cohort analyses will be performed with respect to the levels of the cytogenetic biomarkers. The importance of potential effect modifiers such as gender, age at test, and time since test, will be evaluated using Poisson regression models. The remaining two potential effect modifiers...

  5. Hydrological Aspects of Weather Prediction and Flood Warnings: Report of the Ninth Prospectus Development Team of the U.S. Weather Research Program

    Science.gov (United States)

    Droegemeier, K.K.; Smith, J.D.; Businger, S.; Doswell, C.; Doyle, J.; Duffy, C.; Foufoula-Georgiou, E.; Graziano, T.; James, L.D.; Krajewski, V.; LeMone, M.; Lettenmaier, D.; Mass, C.; Pielke, R.; Ray, P.; Rutledge, S.; Schaake, J.; Zipser, E.

    2000-01-01

    Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists - in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems - to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research

  6. Do the Results of the Process Indicators in the Norwegian Breast Cancer Screening Program Predict Future Mortality Reduction from Breast Cancer?

    International Nuclear Information System (INIS)

    Hofvind, Solveig; Wang, Hege; Thoresen, Steinar

    2004-01-01

    Continuous emphases of quality control are required to achieve reduction in mortality from breast cancer as a consequence of breast cancer screening. Results of the process indicators in the first 6 years in 4 counties in the Norwegian Breast Cancer Screening Program are evaluated and will be presented. Data from women who had their initial (n=173?402) and subsequent (n=220?058) screening provide the basis for the analysis. The breast cancer detection ratio was 3.2 the expected incidence (based on the incidence before the screening started, 1991-1995) among the initially screened women, decreasing to 2.3 among the subsequently screened. The ratio of interval cancer among the initially screened was 0.25 and 0.72 of the expected incidence, 0-12 and 13-23 months after screening, respectively. For those subsequently screened the proportions were 0.22 and 0.64, respectively. More than 50% of the invasive tumors were less than 15 mm in size, and more than 75% were lymph node negative, among both the initially and subsequently screened. The process indicators achieved in the NBCSP are promising as regards future mortality reduction. The incidence of interval cancer 13-24 months after screening is higher than recommended in the European guidelines

  7. Advanced MRI assessment to predict benefit of anti-programmed cell death 1 protein immunotherapy response in patients with recurrent glioblastoma

    Energy Technology Data Exchange (ETDEWEB)

    Qin, Lei [Dana-Farber Cancer Institute, Department of Imaging, Boston, MA (United States); Harvard Medical School, Department of Radiology, Boston, MA (United States); Li, Xiang; Qu, Jinrong [Affiliated Cancer Hospital of Zhengzhou University, Department of Radiology, Zhengzhou, Henan (China); Brigham and Women' s Hospital, Department of Radiology, Boston, MA (United States); Stroiney, Amanda [Dana-Farber Cancer Institute, Department of Imaging, Boston, MA (United States); Northeastern University, Department of Behavioral Neuroscience, College of Sciences, Boston, MA (United States); Helgager, Jeffrey [Brigham and Women' s Hospital, Department of Pathology, Boston, MA (United States); Reardon, David A. [Dana-Farber Cancer Institute, CenterforNeuro-Oncology, Boston, MA (United States); Department of Medicine, Boston, MA (United States); Young, Geoffrey S. [Harvard Medical School, Department of Radiology, Boston, MA (United States); Brigham and Women' s Hospital, Department of Radiology, Boston, MA (United States)

    2017-02-15

    We describe the imaging findings encountered in GBM patients receiving immune checkpoint blockade and assess the potential of quantitative MRI biomarkers to differentiate patients who derive therapeutic benefit from those who do not. A retrospective analysis was performed on longitudinal MRIs obtained on recurrent GBM patients enrolled on clinical trials. Among 10 patients with analyzable data, bidirectional diameters were measured on contrast enhanced T1 (pGd-T1WI) and volumes of interest (VOI) representing measurable abnormality suggestive of tumor were selected on pGdT1WI (pGdT1 VOI), FLAIR-T2WI (FLAIR VOI), and ADC maps. Intermediate ADC (IADC) VOI represented voxels within the FLAIR VOI having ADC in the range of highly cellular tumor (0.7-1.1 x 10{sup -3} mm{sup 2}/s) (IADC VOI). Therapeutic benefit was determined by tissue pathology and survival on trial. IADC VOI, pGdT1 VOI, FLAIR VOI, and RANO assessment results were correlated with patient benefit. Five patients were deemed to have received therapeutic benefit and the other five patients did not. The average time on trial for the benefit group was 194 days, as compared to 81 days for the no benefit group. IADC VOI correlated well with the presence or absence of clinical benefit in 10 patients. Furthermore, pGd VOI, FLAIR VOI, and RANO assessment correlated less well with response. MRI reveals an initial increase in volumes of abnormal tissue with contrast enhancement, edema, and intermediate ADC suggesting hypercellularity within the first 0-6 months of immunotherapy. Subsequent stabilization and improvement in IADC VOI appear to better predict ultimate therapeutic benefit from these agents than conventional imaging. (orig.)

  8. Does Receiving a Blood Transfusion Predict for Length of Stay in Children Undergoing Cranial Vault Remodeling for Craniosynostosis? Outcomes Using the Pediatric National Surgical Quality Improvement Program Dataset.

    Science.gov (United States)

    Markiewicz, Michael R; Alden, Tord; Momin, Mohmed Vasim; Olsson, Alexis B; Jurado, Ray J; Abdullah, Fizan; Miloro, Michael

    2017-08-01

    Recent interventions have aimed at reducing the need for blood transfusions in the perioperative period in patients with craniosynostosis undergoing cranial vault remodeling. However, little is known regarding whether the receipt of a blood transfusion influences the length of hospital stay. The purpose of this study was to assess whether the receipt of a blood transfusion in patients undergoing cranial vault remodeling is associated with an increased length of stay. To address the research purposes, we designed a retrospective cohort study using the 2014 Pediatric National Surgical Quality Improvement Program (NSQIP Peds) dataset. The primary predictor variable was whether patients received a blood transfusion during cranial vault remodeling. The primary outcome variable was length of hospital stay after the operation. The association between the receipt of blood transfusions and length of stay was assessed using the Student t test. The association between other covariates and the outcome variable was assessed using linear regression, analysis of variance, and the Tukey test for post hoc pair-wise comparisons. The sample was composed of 756 patients who underwent cranial vault remodeling: 503 who received blood transfusions and 253 who did not. The primary predictor variable of blood transfusion was associated with an increased length of stay (4.1 days vs 3.0 days, P = .03). Other covariates associated with an increased length of stay included race, American Society of Anesthesiologists status, premature birth, presence of a congenital malformation, and number of sutures involved in craniosynostosis. The receipt of a blood transfusion in the perioperative period in patients with craniosynostosis undergoing cranial vault remodeling was associated with an increased length of stay. Copyright © 2017 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

  9. Systems Training for Emotional Predictability and Problem Solving (STEPPS): program efficacy and personality features as predictors of drop-out -- an Italian study.

    Science.gov (United States)

    Alesiani, Roberta; Boccalon, Silvia; Giarolli, Laura; Blum, Nancee; Fossati, Andrea

    2014-05-01

    In this study we present a clinical application of the STEPPS model in an Italian sample of severely affected patients with borderline personality disorder (BPD) or personality disorder (PD) with prominent borderline features in comorbidity with a mood disorder. The aims of this work are: 1) to confirm our preliminary results in a larger sample and at a 12-month follow-up, and 2) to identify predictors of drop-out vs completion of STEPPS in order to understand which characteristics of patients make them suitable or not for this treatment. The sample is composed of 32 subjects recruited from a population of inpatients of the Mood Disorders Center, Department of Clinical Neurosciences, Hospital San Raffaele-Turro, Milan. To confirm STEPPS efficacy at 12-month follow-up, we selected the following outcome criteria: reduction in the number of hospitalizations related to self-harm acts; reduction in the number of suicidal attempts; reduction of perceived emotional intensity levels; changes in cognitive filter scores; changes in the scores on self-report questionnaires. To identify predictors of drop-out vs completion, we analysed the following variables: demographic features (sex, marital status, school level achieved, and job status); Axis-I diagnosis; Axis-II categorical and dimensional diagnosis; and personality features. Seventeen (53%) subjects completed the treatment successfully. The drop-out rate was 47%. Patients who completed the program show a significant decrease in the number of hospitalizations, both at the end of the treatment and at 12-month follow-up. Friedman ANOVA test shows a significant decrease in suicidal attempts during and after STEPPS, and at 12-month follow-up. Analysis of drop-outs showed no significant differences with regard to sex, marital status, school level and job status between the two groups. Axis-I and Axis-II categorical diagnoses did not discriminate between the two groups. Those patients who dropped differ significantly from

  10. Programmed death-ligand 1 expression correlates with diminished CD8+ T cell infiltration and predicts poor prognosis in anal squamous cell carcinoma patients

    Directory of Open Access Journals (Sweden)

    Zhao Y

    2017-12-01

    Full Text Available Yu-Jie Zhao,1 Wei-Peng Sun,2 Jian-Hong Peng,1 Yu-Xiang Deng,1 Yu-Jing Fang,1 Jun Huang,2 Hui-Zhong Zhang,3 De-Sen Wan,1 Jun-Zhong Lin,1,* Zhi-Zhong Pan,1,* 1Department of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, 2Department of Colorectal Surgery, The Sixth Affiliated Hospital of Sun Yat-sen University, 3Department of Pathology, Sun Yat-sen University Cancer Center, Guangzhou, People’s Republic of China *These authors contributed equally to this work Objective: Increased expression of programmed death-ligand 1 (PD-L1 on tumor cells can be found in various malignancies; however, very limited information is known about its role in anal squamous cell carcinoma (ASCC. This study explored PD-L1 expression in ASCC patients and its association with patients’ clinicopathological features, CD8+ T cell infiltration, and prognosis.Methods: Formalin-fixed paraffin-embedded tumor samples from 26 patients with ASCC were retrieved. The levels of PD-L1 expression on the membrane of both tumor cells and tumor-infiltrating mononuclear cells (TIMCs were evaluated by immunohistochemistry. CD8+ T cell densities, both within tumors and at the tumor–stromal interface, were also analyzed. Baseline clinicopathological characteristics, human papilloma virus (HPV status, and outcome data correlated with PD-L1-positive staining.Results: PD-L1 expression on tumor cells and TIMCs was observed in 46% and 50% of patients, respectively. Nineteen patients (73% were HPV positive, with 7 showing PD-L1-positive staining on tumor cells and 9 showing PD-L1-positive staining on TIMCs. Increasing CD8+ density within tumors, but not immune stroma, was significantly associated with decreased PD-L1 expression by both tumor cells and TIMCs (P=0.0043 and P=0.0007. Patients with negative PD-L1 expression had significantly better progression-free survival (P=0.038 and P

  11. Program overview: Subsurface science program

    International Nuclear Information System (INIS)

    1994-03-01

    The OHER Subsurface Science Program is DOE's core basic research program concerned with subsoils and groundwater. These practices have resulted in contamination by mixtures of organic chemicals, inorganic chemicals, and radionuclides. A primary long-term goal is to provide a foundation of knowledge that will lead to the reduction of environmental risks and to cost-effective cleanup strategies. Since the Program was initiated in 1985, a substantial amount of research in hydrogeology, subsurface microbiology, and the geochemistry of organically complexed radionuclides has been completed, leading to a better understanding of contaminant transport in groundwater and to new insights into microbial distribution and function in the subsurface environments. The Subsurface Science Program focuses on achieving long-term scientific advances that will assist DOE in the following key areas: providing the scientific basis for innovative in situ remediation technologies that are based on a concept of decontamination through benign manipulation of natural systems; understanding the complex mechanisms and process interactions that occur in the subsurface; determining the influence of chemical and geochemical-microbial processes on co-contaminant mobility to reduce environmental risks; improving predictions of contaminant transport that draw on fundamental knowledge of contaminant behavior in the presence of physical and chemical heterogeneities to improve cleanup effectiveness and to predict environmental risks

  12. Predictive medicine

    NARCIS (Netherlands)

    Boenink, Marianne; ten Have, Henk

    2015-01-01

    In the last part of the twentieth century, predictive medicine has gained currency as an important ideal in biomedical research and health care. Research in the genetic and molecular basis of disease suggested that the insights gained might be used to develop tests that predict the future health

  13. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff: SNPs in the genome of Drosophila melanogaster strain w1118; iso-2; iso-3.

    Science.gov (United States)

    Cingolani, Pablo; Platts, Adrian; Wang, Le Lily; Coon, Melissa; Nguyen, Tung; Wang, Luan; Land, Susan J; Lu, Xiangyi; Ruden, Douglas M

    2012-01-01

    We describe a new computer program, SnpEff, for rapidly categorizing the effects of variants in genome sequences. Once a genome is sequenced, SnpEff annotates variants based on their genomic locations and predicts coding effects. Annotated genomic locations include intronic, untranslated region, upstream, downstream, splice site, or intergenic regions. Coding effects such as synonymous or non-synonymous amino acid replacement, start codon gains or losses, stop codon gains or losses, or frame shifts can be predicted. Here the use of SnpEff is illustrated by annotating ~356,660 candidate SNPs in ~117 Mb unique sequences, representing a substitution rate of ~1/305 nucleotides, between the Drosophila melanogaster w(1118); iso-2; iso-3 strain and the reference y(1); cn(1) bw(1) sp(1) strain. We show that ~15,842 SNPs are synonymous and ~4,467 SNPs are non-synonymous (N/S ~0.28). The remaining SNPs are in other categories, such as stop codon gains (38 SNPs), stop codon losses (8 SNPs), and start codon gains (297 SNPs) in the 5'UTR. We found, as expected, that the SNP frequency is proportional to the recombination frequency (i.e., highest in the middle of chromosome arms). We also found that start-gain or stop-lost SNPs in Drosophila melanogaster often result in additions of N-terminal or C-terminal amino acids that are conserved in other Drosophila species. It appears that the 5' and 3' UTRs are reservoirs for genetic variations that changes the termini of proteins during evolution of the Drosophila genus. As genome sequencing is becoming inexpensive and routine, SnpEff enables rapid analyses of whole-genome sequencing data to be performed by an individual laboratory.

  14. Predictive maintenance primer

    International Nuclear Information System (INIS)

    Flude, J.W.; Nicholas, J.R.

    1991-04-01

    This Predictive Maintenance Primer provides utility plant personnel with a single-source reference to predictive maintenance analysis methods and technologies used successfully by utilities and other industries. It is intended to be a ready reference to personnel considering starting, expanding or improving a predictive maintenance program. This Primer includes a discussion of various analysis methods and how they overlap and interrelate. Additionally, eighteen predictive maintenance technologies are discussed in sufficient detail for the user to evaluate the potential of each technology for specific applications. This document is designed to allow inclusion of additional technologies in the future. To gather the information necessary to create this initial Primer the Nuclear Maintenance Applications Center (NMAC) collected experience data from eighteen utilities plus other industry and government sources. NMAC also contacted equipment manufacturers for information pertaining to equipment utilization, maintenance, and technical specifications. The Primer includes a discussion of six methods used by analysts to study predictive maintenance data. These are: trend analysis; pattern recognition; correlation; test against limits or ranges; relative comparison data; and statistical process analysis. Following the analysis methods discussions are detailed descriptions for eighteen technologies analysts have found useful for predictive maintenance programs at power plants and other industrial facilities. Each technology subchapter has a description of the operating principles involved in the technology, a listing of plant equipment where the technology can be applied, and a general description of the monitoring equipment. Additionally, these descriptions include a discussion of results obtained from actual equipment users and preferred analysis techniques to be used on data obtained from the technology. 5 refs., 30 figs

  15. Prediction Markets

    DEFF Research Database (Denmark)

    Horn, Christian Franz; Ivens, Bjørn Sven; Ohneberg, Michael

    2014-01-01

    In recent years, Prediction Markets gained growing interest as a forecasting tool among researchers as well as practitioners, which resulted in an increasing number of publications. In order to track the latest development of research, comprising the extent and focus of research, this article...... provides a comprehensive review and classification of the literature related to the topic of Prediction Markets. Overall, 316 relevant articles, published in the timeframe from 2007 through 2013, were identified and assigned to a herein presented classification scheme, differentiating between descriptive...... works, articles of theoretical nature, application-oriented studies and articles dealing with the topic of law and policy. The analysis of the research results reveals that more than half of the literature pool deals with the application and actual function tests of Prediction Markets. The results...

  16. Predicting unpredictability

    Science.gov (United States)

    Davis, Steven J.

    2018-04-01

    Analysts and markets have struggled to predict a number of phenomena, such as the rise of natural gas, in US energy markets over the past decade or so. Research shows the challenge may grow because the industry — and consequently the market — is becoming increasingly volatile.

  17. Phenology prediction component of GypsES

    Science.gov (United States)

    Jesse A. Logan; Lukas P. Schaub; F. William Ravlin

    1991-01-01

    Prediction of phenology is an important component of most pest management programs, and considerable research effort has been expended toward development of predictive tools for gypsy moth phenology. Although phenological prediction is potentially valuable for timing of spray applications (e.g. Bt, or Gypcheck) and other management activities (e.g. placement and...

  18. Unification predictions

    International Nuclear Information System (INIS)

    Ghilencea, D.; Ross, G.G.; Lanzagorta, M.

    1997-07-01

    The unification of gauge couplings suggests that there is an underlying (supersymmetric) unification of the strong, electromagnetic and weak interactions. The prediction of the unification scale may be the first quantitative indication that this unification may extend to unification with gravity. We make a precise determination of these predictions for a class of models which extend the multiplet structure of the Minimal Supersymmetric Standard Model to include the heavy states expected in many Grand Unified and/or superstring theories. We show that there is a strong cancellation between the 2-loop and threshold effects. As a result the net effect is smaller than previously thought, giving a small increase in both the unification scale and the value of the strong coupling at low energies. (author). 15 refs, 5 figs

  19. Functional Programming

    OpenAIRE

    Chitil, Olaf

    2009-01-01

    Functional programming is a programming paradigm like object-oriented programming and logic programming. Functional programming comprises both a specific programming style and a class of programming languages that encourage and support this programming style. Functional programming enables the programmer to describe an algorithm on a high-level, in terms of the problem domain, without having to deal with machine-related details. A program is constructed from functions that only map inputs to ...

  20. Can we predict nuclear proliferation

    International Nuclear Information System (INIS)

    Tertrais, Bruno

    2011-01-01

    The author aims at improving nuclear proliferation prediction capacities, i.e. the capacities to identify countries susceptible to acquire nuclear weapons, to interpret sensitive activities, and to assess nuclear program modalities. He first proposes a retrospective assessment of counter-proliferation actions since 1945. Then, based on academic studies, he analyzes what causes and motivates proliferation, with notably the possibility of existence of a chain phenomenon (mechanisms driving from one program to another). He makes recommendations for a global approach to proliferation prediction, and proposes proliferation indices and indicators

  1. Genomic Prediction in Barley

    DEFF Research Database (Denmark)

    Edriss, Vahid; Cericola, Fabio; Jensen, Jens D

    2015-01-01

    to next generation. The main goal of this study was to see the potential of using genomic prediction in a commercial Barley breeding program. The data used in this study was from Nordic Seed company which is located in Denmark. Around 350 advanced lines were genotyped with 9K Barely chip from Illumina....... Traits used in this study were grain yield, plant height and heading date. Heading date is number days it takes after 1st June for plant to head. Heritabilities were 0.33, 0.44 and 0.48 for yield, height and heading, respectively for the average of nine plots. The GBLUP model was used for genomic...

  2. SCINFUL: A Monte Carlo based computer program to determine a scintillator full energy response to neutron detection for E/sub n/ between 0.1 and 80 MeV: Program development and comparisons of program predictions with experimental data

    International Nuclear Information System (INIS)

    Dickens, J.K.

    1988-04-01

    This document provides a discussion of the development of the FORTRAN Monte Carlo program SCINFUL (for scintillator full response), a program designed to provide a calculated full response anticipated for either an NE-213 (liquid) scintillator or an NE-110 (solid) scintillator. The program may also be used to compute angle-integrated spectra of charged particles (p, d, t, 3 He, and α) following neutron interactions with 12 C. Extensive comparisons with a variety of experimental data are given. There is generally overall good agreement ( 15% of the maximum pulse height response, calculated spectra are within +-5% of experiment on the average. For E/sub n/ up to 50 MeV similar good agreement is obtained with experiment for E/sub r/ > 30% of maximum response. For E/sub n/ up to 75 MeV the calculated shape of the response agrees with measurements, but the calculations underpredicts the measured response by up to 30%. 65 refs., 64 figs., 3 tabs

  3. PISCES: A Tool for Predicting Software Testability

    Science.gov (United States)

    Voas, Jeffrey M.; Miller, Keith W.; Payne, Jeffery E.

    1991-01-01

    Before a program can fail, a software fault must be executed, that execution must alter the data state, and the incorrect data state must propagate to a state that results directly in an incorrect output. This paper describes a tool called PISCES (developed by Reliable Software Technologies Corporation) for predicting the probability that faults in a particular program location will accomplish all three of these steps causing program failure. PISCES is a tool that is used during software verification and validation to predict a program's testability.

  4. Viral IRES prediction system - a web server for prediction of the IRES secondary structure in silico.

    Directory of Open Access Journals (Sweden)

    Jun-Jie Hong

    Full Text Available The internal ribosomal entry site (IRES functions as cap-independent translation initiation sites in eukaryotic cells. IRES elements have been applied as useful tools for bi-cistronic expression vectors. Current RNA structure prediction programs are unable to predict precisely the potential IRES element. We have designed a viral IRES prediction system (VIPS to perform the IRES secondary structure prediction. In order to obtain better results for the IRES prediction, the VIPS can evaluate and predict for all four different groups of IRESs with a higher accuracy. RNA secondary structure prediction, comparison, and pseudoknot prediction programs were implemented to form the three-stage procedure for the VIPS. The backbone of VIPS includes: the RNAL fold program, aimed to predict local RNA secondary structures by minimum free energy method; the RNA Align program, intended to compare predicted structures; and pknotsRG program, used to calculate the pseudoknot structure. VIPS was evaluated by using UTR database, IRES database and Virus database, and the accuracy rate of VIPS was assessed as 98.53%, 90.80%, 82.36% and 80.41% for IRES groups 1, 2, 3, and 4, respectively. This advance useful search approach for IRES structures will facilitate IRES related studies. The VIPS on-line website service is available at http://140.135.61.250/vips/.

  5. Predicting Employer's Benefits from Cooperative Education.

    Science.gov (United States)

    Wiseman, Richard L.; Page, Norman R.

    1983-01-01

    Attempts to predict employer benefits resulting from their involvement in cooperative education programs. Benefits include a good source of quality employees, increased worker motivation, and increased respect between students and employers. (JOW)

  6. Topology and prediction of RNA pseudoknots

    DEFF Research Database (Denmark)

    Reidys, Christian; Huang, Fenix; Andersen, Jørgen Ellegaard

    2011-01-01

    Motivation: Several dynamic programming algorithms for predicting RNA structures with pseudoknots have been proposed that differ dramatically from one another in the classes of structures considered. Results: Here, we use the natural topological classification of RNA structures in terms...

  7. Predictable Medea

    Directory of Open Access Journals (Sweden)

    Elisabetta Bertolino

    2010-01-01

    Full Text Available By focusing on the tragedy of the 'unpredictable' infanticide perpetrated by Medea, the paper speculates on the possibility of a non-violent ontological subjectivity for women victims of gendered violence and whether it is possible to respond to violent actions in non-violent ways; it argues that Medea did not act in an unpredictable way, rather through the very predictable subject of resentment and violence. 'Medea' represents the story of all of us who require justice as retribution against any wrong. The presupposition is that the empowered female subjectivity of women’s rights contains the same desire of mastering others of the masculine current legal and philosophical subject. The subject of women’s rights is grounded on the emotions of resentment and retribution and refuses the categories of the private by appropriating those of the righteous, masculine and public subject. The essay opposes the essentialised stereotypes of the feminine and the maternal with an ontological approach of people as singular, corporeal, vulnerable and dependent. There is therefore an emphasis on the excluded categories of the private. Forgiveness is taken into account as a category of the private and a possibility of responding to violence with newness. A violent act is seen in relations to the community of human beings rather than through an isolated setting as in the case of the individual of human rights. In this context, forgiveness allows to risk again and being with. The result is also a rethinking of feminist actions, feminine subjectivity and of the maternal. Overall the paper opens up the Arendtian category of action and forgiveness and the Cavarerian unique and corporeal ontology of the selfhood beyond gendered stereotypes.

  8. Water Quality Analysis Simulation Program (WASP)

    Science.gov (United States)

    The Water Quality Analysis Simulation Program (WASP) model helps users interpret and predict water quality responses to natural phenomena and manmade pollution for various pollution management decisions.

  9. Nucleic acid secondary structure prediction and display.

    OpenAIRE

    Stüber, K

    1986-01-01

    A set of programs has been developed for the prediction and display of nucleic acid secondary structures. Information from experimental data can be used to restrict or enforce secondary structural elements. The predictions can be displayed either on normal line printers or on graphic devices like plotters or graphic terminals.

  10. Pharmacy Utilization: A Study to Predict BAMC Outpatient Pharmacy Usage by Dual-Eligible Military Retiree/Medicare-Eligible Beneficiaries Resulting From Implementation of the TRICARE Senior Pharmacy Program (TSRx)

    National Research Council Canada - National Science Library

    Lankowicz, Andrew

    2001-01-01

    .... The problem that confronted Brooke Army Medical Center (BAMC) was the lack of knowledge about the effect that the TSRx program might have on utilization of the hospital s outpatient pharmacies. A survey (Appendix C...

  11. Program specialization

    CERN Document Server

    Marlet, Renaud

    2013-01-01

    This book presents the principles and techniques of program specialization - a general method to make programs faster (and possibly smaller) when some inputs can be known in advance. As an illustration, it describes the architecture of Tempo, an offline program specializer for C that can also specialize code at runtime, and provides figures for concrete applications in various domains. Technical details address issues related to program analysis precision, value reification, incomplete program specialization, strategies to exploit specialized program, incremental specialization, and data speci

  12. Mental Models and Programming Aptitude

    DEFF Research Database (Denmark)

    Caspersen, Michael Edelgaard; Bennedsen, Jens; Larsen, Kasper Dalgaard

    2007-01-01

    Predicting the success of students participating in introductory programming courses has been an active research area for more than 25 years. Until recently, no variables or tests have had any significant predictive power. However, Dehnadi and Bornat claim to have found a simple test for programm......Predicting the success of students participating in introductory programming courses has been an active research area for more than 25 years. Until recently, no variables or tests have had any significant predictive power. However, Dehnadi and Bornat claim to have found a simple test...... for programming aptitude to cleanly separate programming sheep from non-programming goats. We briefly present their theory and test instrument. We have repeated their test in our local context in order to verify and perhaps generalise their findings, but we could not show that the test predicts students' success...... in our introductory program-ming course. Based on this failure of the test instrument, we discuss various explanations for our differing results and suggest a research method from which it may be possible to generalise local results in this area. Furthermore, we discuss and criticize Dehnadi and Bornat...

  13. Child Development Program Evaluation Scale.

    Science.gov (United States)

    Fiene, Richard J.

    The Child Development Program Evaluation Scale (CDPES) is actually two scales in one, a licensing scale and a quality scale. Licensing predictor items have been found to predict overall compliance of child day care centers with state regulations in four states. Quality scale items have been found to predict the overall quality of child day care…

  14. Nuclear criticality predictability

    International Nuclear Information System (INIS)

    Briggs, J.B.

    1999-01-01

    As a result of lots of efforts, a large portion of the tedious and redundant research and processing of critical experiment data has been eliminated. The necessary step in criticality safety analyses of validating computer codes with benchmark critical data is greatly streamlined, and valuable criticality safety experimental data is preserved. Criticality safety personnel in 31 different countries are now using the 'International Handbook of Evaluated Criticality Safety Benchmark Experiments'. Much has been accomplished by the work of the ICSBEP. However, evaluation and documentation represents only one element of a successful Nuclear Criticality Safety Predictability Program and this element only exists as a separate entity, because this work was not completed in conjunction with the experimentation process. I believe; however, that the work of the ICSBEP has also served to unify the other elements of nuclear criticality predictability. All elements are interrelated, but for a time it seemed that communications between these elements was not adequate. The ICSBEP has highlighted gaps in data, has retrieved lost data, has helped to identify errors in cross section processing codes, and has helped bring the international criticality safety community together in a common cause as true friends and colleagues. It has been a privilege to associate with those who work so diligently to make the project a success. (J.P.N.)

  15. Baseline leptin and leptin reduction predict improvements in metabolic variables and long-term fat loss in obese children and adolescents: a prospective study of an inpatient weight-loss program

    NARCIS (Netherlands)

    Murer, S.B.; Knopfli, B.H.; Aeberli, I.; Jung, A.; Wildhaber, J.; Wildhaber-Brooks, J.; Zimmermann, M.B.

    2011-01-01

    Background: It is unclear whether high plasma leptin in obese individuals represents leptin resistance or whether individuals with marked reductions in leptin concentrations in response to weight loss may be at greater risk of regaining weight. Moreover, whether changes in leptin predict metabolic

  16. Adaptation and Implementation of Predictive Maintenance Technique with Nondestructive Testing for Power Plants

    International Nuclear Information System (INIS)

    Jung, Gye Jo; Jung, Nam Gun

    2010-01-01

    Many forces are pressuring utilities to reduce operating and maintenance costs without cutting back on reliability or availability. Many utility managers are re-evaluating maintenance strategies to meet these demands. To utilities how to reduce maintenance costs and extent the effective operating life of equipment, predictive maintenance technique can be adapted. Predictive maintenance had three types program which are in-house program, engineering company program and mixed program. We can approach successful predictive maintenance program with 'smart trust' concept

  17. Quantification of design margins and safety factors based on the prediction uncertainty in tritium production rate from fusion integral experiments of the USDOE/JAERI collaborative program on fusion blanket neutronics

    International Nuclear Information System (INIS)

    Youssef, M.Z.; Konno, C.; Maekawa, F.; Ikeda, Y.; Kosako, K.; Nakagawa, M.; Mori, T.; Maekawa, H.

    1995-01-01

    Several fusion integral experiments were performed within a collaboration between the USA and Japan on fusion breeder neutronics aimed at verifying the prediction accuracy of key neutronics parameters in a fusion reactor blanket based on current neutron transport codes and basic nuclear databases. The focus has been on the tritium production rate (TRP) as an important design parameter to resolve the issue of tritium self-sufficiency in a fusion reactor. In this paper, the calculational and experimental uncertainties (errors) in local TPR in each experiment performed i were interpolated and propagated to estimate the prediction uncertainty u i in the line-integrated TPR and its standard deviation σ i . The measured data are based on Li-glass and NE213 detectors. From the quantities u i and σ i , normalized density functions (NDFs) were constructed, considering all the experiments and their associated analyses performed independently by the UCLA and JAERI. Several statistical parameters were derived, including the mean prediction uncertainties u and the possible spread ±σ u around them. Design margins and safety factors were derived from these NDFs. Distinction was made between the results obtained by UCLA and JAERI and between calculational results based on the discrete ordinates and Monte Carlo methods. The prediction uncertainties, their standard deviations and the design margins and safety factors were derived for the line-integrated TPR from Li-6 T 6 , and Li-7 T 7 . These parameters were used to estimate the corresponding uncertainties and safety factor for the line-integrated TPR from natural lithium T n . (orig.)

  18. Prediction of ground motion from underground nuclear weapons tests as it relates to siting of a nuclear waste storage facility at NTS and compatibility with the weapons test program

    International Nuclear Information System (INIS)

    Vortman, L.J. IV.

    1980-04-01

    This report assumes reasonable criteria for NRC licensing of a nuclear waste storage facility at the Nevada Test Site where it would be exposed to ground motion from underground nuclear weapons tests. Prediction equations and their standard deviations have been determined from measurements on a number of nuclear weapons tests. The effect of various independent parameters on standard deviation is discussed. That the data sample is sufficiently large is shown by the fact that additional data have little effect on the standard deviation. It is also shown that coupling effects can be separated out of the other contributions to the standard deviation. An example, based on certain licensing assumptions, shows that it should be possible to have a nuclear waste storage facility in the vicinity of Timber Mountain which would be compatible with a 700 kt weapons test in the Buckboard Area if the facility were designed to withstand a peak vector acceleration of 0.75 g. The prediction equation is a log-log linear equation which predicts acceleration as a function of yield of an explosion and the distance from it

  19. Making detailed predictions makes (some) predictions worse

    Science.gov (United States)

    Kelly, Theresa F.

    In this paper, we investigate whether making detailed predictions about an event makes other predictions worse. Across 19 experiments, 10,895 participants, and 415,960 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes information that is relatively useless for predicting the winning team more readily accessible in memory and therefore incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of games will and will not be susceptible to the negative effect of making detailed predictions.

  20. Program History

    Science.gov (United States)

    Learn how the National Cancer Institute transitioned the former Cooperative Groups Program to the National Clinical Trials Network (NCTN) program. The NCTN gives funds and other support to cancer research organizations to conduct cancer clinical trials.

  1. Program auto

    International Nuclear Information System (INIS)

    Rawool-Sullivan, M.W.; Plagnol, E.

    1990-01-01

    The program AUTO was developed to be used in the analysis of dE vs E type spectra. This program is written in FORTRAN and calculates dE vs E lines in MeV. The provision is also made in the program to convert these lines from MeV to ADC channel numbers to facilitate the comparison with the raw data from the experiments. Currently the output of this program can be plotted with the display program, called VISU, but it can also be used independent of the program VISU, with little or no modification in the actual fortran code. The program AUTO has many useful applications. In this article the program AUTO is described along with its applications

  2. Disruption prediction at JET

    International Nuclear Information System (INIS)

    Milani, F.

    1998-12-01

    assigning a disruption probability to every plasma input pattern. The second method determines the novelty of an input pattern by calculating the probability density distribution of successful plasma patterns that have been run at JET. The density distribution is represented as a mixture distribution, and its parameters are determined using the Expectation-Maximisation method. If the dataset, used to determine the distribution parameters, covers sufficiently well the machine operational space, then, the patterns flagged as novel can be regarded as patterns belonging to a disrupting plasma. Together with these methods, a network has been designed to predict the vertical forces, that a disruption can cause, in order to avoid that too dangerous plasma configurations are run. This network can be run before the pulse using the pre-programmed plasma configuration or on line becoming a tool that allows to stop dangerous plasma configuration. All these methods have been implemented in real time on a dual Pentium Pro based machine. The Disruption Prediction and Prevention System has shown that internal plasma parameters can be determined on-line with a good accuracy. Also the disruption detection algorithms showed promising results considering the fact that JET is an experimental machine where always new plasma configurations are tested trying to improve its performances. (author)

  3. Beyond [lambda][subscript max] Part 2: Predicting Molecular Color

    Science.gov (United States)

    Williams, Darren L.; Flaherty, Thomas J.; Alnasleh, Bassam K.

    2009-01-01

    A concise roadmap for using computational chemistry programs (i.e., Gaussian 03W) to predict the color of a molecular species is presented. A color-predicting spreadsheet is available with the online material that uses transition wavelengths and peak-shape parameters to predict the visible absorbance spectrum, transmittance spectrum, chromaticity…

  4. Dynamical Predictability of Monthly Means.

    Science.gov (United States)

    Shukla, J.

    1981-12-01

    perturbations. The 30-day means for days 16-46 over certain areas are also significantly different from the valances due to random perturbations.These results suggest that the evolution of long waves remains sufficiently predictable at least up to one month, and possibly up to 45 days, so that the combined effects of their own nonpredictability and their depredictabilization by synoptic-scale instabilities is not large enough to degrade the dynamical prediction of monthly means. The Northern Hemisphere appears to be more predictable than the Southern Hemisphere.It is noteworthy that the lack of predictability for the second month is not because the model simulations relax to the same model state but because of very large departures in the simulated model states. This suggests that, with improvements in model resolution and physical parameterizations, there is potential for extending the predictability of time averages even beyond one month.Here, we have examined only the dynamical predictability, because the boundary conditions are identical in all the integrations. Based on these results, and the possibility of additional predictability due to the influence of persistent anomalies of sea surface temperature, sea ice, snow and soil moisture, it is suggested that there is sufficient physical basis to undertake a systematic program to establish the feasibility of predicting monthly means by numerical integrations of realistic dynamical models.

  5. Part 2 -- current program integrating strategies and lubrication technology

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, B.

    1996-12-01

    This paper is the second of two that describe the Predictive Maintenance Program for rotating machinery at the Palo Verde Nuclear Generating Station. The Predictive Maintenance program has been enhanced through organizational changes and improved interdisciplinary usage of technology. This paper will discuss current program strategies that have improved the interaction between the Vibration and Lube Oil programs. The {open_quotes}Lube Oil{close_quotes} view of the combined program along with case studies will then be presented.

  6. Part 2 -- current program integrating strategies and lubrication technology

    International Nuclear Information System (INIS)

    Johnson, B.

    1996-01-01

    This paper is the second of two that describe the Predictive Maintenance Program for rotating machinery at the Palo Verde Nuclear Generating Station. The Predictive Maintenance program has been enhanced through organizational changes and improved interdisciplinary usage of technology. This paper will discuss current program strategies that have improved the interaction between the Vibration and Lube Oil programs. The open-quotes Lube Oilclose quotes view of the combined program along with case studies will then be presented

  7. Verification, validation, and reliability of predictions

    International Nuclear Information System (INIS)

    Pigford, T.H.; Chambre, P.L.

    1987-04-01

    The objective of predicting long-term performance should be to make reliable determinations of whether the prediction falls within the criteria for acceptable performance. Establishing reliable predictions of long-term performance of a waste repository requires emphasis on valid theories to predict performance. The validation process must establish the validity of the theory, the parameters used in applying the theory, the arithmetic of calculations, and the interpretation of results; but validation of such performance predictions is not possible unless there are clear criteria for acceptable performance. Validation programs should emphasize identification of the substantive issues of prediction that need to be resolved. Examples relevant to waste package performance are predicting the life of waste containers and the time distribution of container failures, establishing the criteria for defining container failure, validating theories for time-dependent waste dissolution that depend on details of the repository environment, and determining the extent of congruent dissolution of radionuclides in the UO 2 matrix of spent fuel. Prediction and validation should go hand in hand and should be done and reviewed frequently, as essential tools for the programs to design and develop repositories. 29 refs

  8. Monitoring and evaluation of smolt migration in the Columbia Basin, Volume II: Evaluation of the 1996 predictions of the run-timing of wild migrant subyearling chinook in the Snake River Basin using Program RealTime.; TOPICAL

    International Nuclear Information System (INIS)

    Skalski, John R.; Townsend, Richard L.; Yasuda, Dean

    1998-01-01

    This project was initiated in 1991 in response to the Endangered Species Act (ESA) listings in the Snake River Basin of the Columbia River Basin. Primary objectives and management implications of this project include: (1)to address the need for further synthesis of historical tagging and other biological information to improve understanding and identify future research and analysis needs; (2)to assist in the development of improved monitoring capabilities, statistical methodologies and software tools to aid management in optimizing operational and fish passage strategies to maximize the protection and survival of listed threatened and endangered Snake River salmon populations and other listed and nonlisted stocks in the Columbia River Basin; (3)to design better analysis tools for evaluation programs; and (4)to provide statistical support to the Bonneville Power Administration and the Northwest fisheries community

  9. Monitoring and evaluation of smolt migration in the Columbia River Basin; Volume 1; Evaluation of the 1995 predictions of the run-timing of wild migrant subyearling chinook in the Snake River Basin using Program RealTime

    International Nuclear Information System (INIS)

    Skalski, John R.; Townsend, Richard L.; Yasuda, Dean

    1997-01-01

    This project was initiated in response to the Endangered Species Act (ESA) listings in the Snake River Basin of the Columbia River Basin. Primary objectives and management implications of the project include: (1)to address the need for further synthesis of historical tagging and other biological information to improve understanding and to help identify future research and analysis needs; (2)to assist in the development of improved monitoring capabilities, statistical methodologies and software tools to assist in optimizing operational and fish passage strategies to maximize the protection and survival of listed threatened and endangered Snake River salmon populations and other listed and nonlisted stocks in the Columbia River Basin; and (3)to design better analysis tools for evaluation programs; and (4)to provide statistical support to the Bonneville Power Administration and the Northwest fisheries community

  10. Material Programming

    DEFF Research Database (Denmark)

    Vallgårda, Anna; Boer, Laurens; Tsaknaki, Vasiliki

    2017-01-01

    . Consequently we ask what the practice of programming and giving form to such materials would be like? How would we be able to familiarize ourselves with the dynamics of these materials and their different combinations of cause and effect? Which tools would we need and what would they look like? Will we program......, and color, but additionally being capable of sensing, actuating, and computing. Indeed, computers will not be things in and by themselves, but embedded into the materials that make up our surroundings. This also means that the way we interact with computers and the way we program them, will change...... these computational composites through external computers and then transfer the code them, or will the programming happen closer to the materials? In this feature we outline a new research program that floats between imagined futures and the development of a material programming practice....

  11. Effective Programming

    DEFF Research Database (Denmark)

    Frost, Jacob

    To investigate the use of VTLoE as a basis for formal derivation of functional programs with effects. As a part of the process, a number of issues central to effective formal programming are considered. In particular it is considered how to develop a proof system suitable for pratical reasoning......, how to implement this system in the generic proof assistant Isabelle and finally how to apply the logic and the implementation to programming....

  12. Program Fullerene

    DEFF Research Database (Denmark)

    Wirz, Lukas; Peter, Schwerdtfeger,; Avery, James Emil

    2013-01-01

    Fullerene (Version 4.4), is a general purpose open-source program that can generate any fullerene isomer, perform topological and graph theoretical analysis, as well as calculate a number of physical and chemical properties. The program creates symmetric planar drawings of the fullerene graph, an......-Fowler, and Brinkmann-Fowler vertex insertions. The program is written in standard Fortran and C++, and can easily be installed on a Linux or UNIX environment....

  13. Predictive access control for distributed computation

    DEFF Research Database (Denmark)

    Yang, Fan; Hankin, Chris; Nielson, Flemming

    2013-01-01

    We show how to use aspect-oriented programming to separate security and trust issues from the logical design of mobile, distributed systems. The main challenge is how to enforce various types of security policies, in particular predictive access control policies — policies based on the future beh...... behavior of a program. A novel feature of our approach is that we can define policies concerning secondary use of data....

  14. Programming F#

    CERN Document Server

    Smith, Chris

    2009-01-01

    Why learn F#? This multi-paradigm language not only offers you an enormous productivity boost through functional programming, it also lets you develop applications using your existing object-oriented and imperative programming skills. With Programming F#, you'll quickly discover the many advantages of Microsoft's new language, which includes access to all the great tools and libraries of the .NET platform. Learn how to reap the benefits of functional programming for your next project -- whether it's quantitative computing, large-scale data exploration, or even a pursuit of your own. With th

  15. PLC Programming

    International Nuclear Information System (INIS)

    Lee, Seong Jae; Wi, Seong Dong; Yoo, Jong Seon; Kim, Se Chan

    2001-02-01

    This book tells of PLC programming for KGL-WIN with summary of PLC, performance and function of PLC like characteristic of KGL-WIN, connection method with PLC, basic performance of K200S/K300S/K1000S, diagram of input and output H/W, writing project, staring the program, editing of program, on-line function, debugging and instructions like control, timer and counter, data transmission, comparison, rotation and moving, system, data operating data conversion and application program.

  16. Programming Interactivity

    CERN Document Server

    Noble, Joshua

    2009-01-01

    Make cool stuff. If you're a designer or artist without a lot of programming experience, this book will teach you to work with 2D and 3D graphics, sound, physical interaction, and electronic circuitry to create all sorts of interesting and compelling experiences -- online and off. Programming Interactivity explains programming and electrical engineering basics, and introduces three freely available tools created specifically for artists and designers: Processing, a Java-based programming language and environment for building projects on the desktop, Web, or mobile phonesArduino, a system t

  17. Evaluation of environmental impact predictions

    International Nuclear Information System (INIS)

    Cunningham, P.A.; Adams, S.M.; Kumar, K.D.

    1977-01-01

    An analysis and evaluation of the ecological monitoring program at the Surry Nuclear Power Plant showed that predictions of potential environmental impact made in the Final Environmental Statement (FES), which were based on generally accepted ecological principles, were not completely substantiated by environmental monitoring data. The Surry Nuclear Power Plant (Units 1 and 2) was chosen for study because of the facility's relatively continuous operating history and the availability of environmental data adequate for analysis. Preoperational and operational fish monitoring data were used to assess the validity of the FES prediction that fish would congregate in the thermal plume during winter months and would avoid the plume during summer months. Analysis of monitoring data showed that fish catch per unit effort (CPE) was generally high in the thermal plume during winter months; however, the highest fish catches occurred in the plume during the summer. Possible explanations for differences between the FES prediction and results observed in analysis of monitoring data are discussed, and general recommendations are outlined for improving impact assessment predictions

  18. Prediction of natural gas consumption

    International Nuclear Information System (INIS)

    Zhang, R.L.; Walton, D.J.; Hoskins, W.D.

    1993-01-01

    Distributors of natural gas need to predict future consumption in order to purchase a sufficient supply on contract. Distributors that offer their customers equal payment plans need to predict the consumption of each customer 12 months in advance. Estimates of previous consumption are often used for months when meters are inaccessible, or bimonthly-read meters. Existing methods of predicting natural gas consumption, and a proposed new method for each local region are discussed. The proposed model distinguishes the consumption load factors from summer to other seasons by attempting to adjust them by introducing two parameters. The problem is then reduced to a quadratic programming problem. However, since it is not necessary to use both parameters simultaneously, the problem can be solved with a simple iterative procedure. Results show that the new model can improve the two-equation model to a certain scale. The adjustment to heat load factor can reduce the error of prediction markedly while that to base load factor influences the error marginally. 3 refs., 11 figs., 2 tabs

  19. Predictive modeling of complications.

    Science.gov (United States)

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

    2016-09-01

    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.

  20. Wind farm production prediction - The Zephyr model

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Giebel, G. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Madsen, H. [IMM (DTU), Kgs. Lyngby (Denmark); Nielsen, T.S. [IMM (DTU), Kgs. Lyngby (Denmark); Joergensen, J.U. [Danish Meteorologisk Inst., Copenhagen (Denmark); Lauersen, L. [Danish Meteorologisk Inst., Copenhagen (Denmark); Toefting, J. [Elsam, Fredericia (DK); Christensen, H.S. [Eltra, Fredericia (Denmark); Bjerge, C. [SEAS, Haslev (Denmark)

    2002-06-01

    This report describes a project - funded by the Danish Ministry of Energy and the Environment - which developed a next generation prediction system called Zephyr. The Zephyr system is a merging between two state-of-the-art prediction systems: Prediktor of Risoe National Laboratory and WPPT of IMM at the Danish Technical University. The numerical weather predictions were generated by DMI's HIRLAM model. Due to technical difficulties programming the system, only the computational core and a very simple version of the originally very complex system were developed. The project partners were: Risoe, DMU, DMI, Elsam, Eltra, Elkraft System, SEAS and E2. (au)

  1. Butterfly valve torque prediction methodology

    International Nuclear Information System (INIS)

    Eldiwany, B.H.; Sharma, V.; Kalsi, M.S.; Wolfe, K.

    1994-01-01

    As part of the Motor-Operated Valve (MOV) Performance Prediction Program, the Electric Power Research Institute has sponsored the development of methodologies for predicting thrust and torque requirements of gate, globe, and butterfly MOVs. This paper presents the methodology that will be used by utilities to calculate the dynamic torque requirements for butterfly valves. The total dynamic torque at any disc position is the sum of the hydrodynamic torque, bearing torque (which is induced by the hydrodynamic force), as well as other small torque components (such as packing torque). The hydrodynamic torque on the valve disc, caused by the fluid flow through the valve, depends on the disc angle, flow velocity, upstream flow disturbances, disc shape, and the disc aspect ratio. The butterfly valve model provides sets of nondimensional flow and torque coefficients that can be used to predict flow rate and hydrodynamic torque throughout the disc stroke and to calculate the required actuation torque and the maximum transmitted torque throughout the opening and closing stroke. The scope of the model includes symmetric and nonsymmetric discs of different shapes and aspects ratios in compressible and incompressible fluid applications under both choked and nonchoked flow conditions. The model features were validated against test data from a comprehensive flowloop and in situ test program. These tests were designed to systematically address the effect of the following parameters on the required torque: valve size, disc shapes and disc aspect ratios, upstream elbow orientation and its proximity, and flow conditions. The applicability of the nondimensional coefficients to valves of different sizes was validated by performing tests on 42-in. valve and a precisely scaled 6-in. model. The butterfly valve model torque predictions were found to bound test data from the flow-loop and in situ testing, as shown in the examples provided in this paper

  2. Collaboratory for the Study of Earthquake Predictability

    Science.gov (United States)

    Schorlemmer, D.; Jordan, T. H.; Zechar, J. D.; Gerstenberger, M. C.; Wiemer, S.; Maechling, P. J.

    2006-12-01

    Earthquake prediction is one of the most difficult problems in physical science and, owing to its societal implications, one of the most controversial. The study of earthquake predictability has been impeded by the lack of an adequate experimental infrastructure---the capability to conduct scientific prediction experiments under rigorous, controlled conditions and evaluate them using accepted criteria specified in advance. To remedy this deficiency, the Southern California Earthquake Center (SCEC) is working with its international partners, which include the European Union (through the Swiss Seismological Service) and New Zealand (through GNS Science), to develop a virtual, distributed laboratory with a cyberinfrastructure adequate to support a global program of research on earthquake predictability. This Collaboratory for the Study of Earthquake Predictability (CSEP) will extend the testing activities of SCEC's Working Group on Regional Earthquake Likelihood Models, from which we will present first results. CSEP will support rigorous procedures for registering prediction experiments on regional and global scales, community-endorsed standards for assessing probability-based and alarm-based predictions, access to authorized data sets and monitoring products from designated natural laboratories, and software to allow researchers to participate in prediction experiments. CSEP will encourage research on earthquake predictability by supporting an environment for scientific prediction experiments that allows the predictive skill of proposed algorithms to be rigorously compared with standardized reference methods and data sets. It will thereby reduce the controversies surrounding earthquake prediction, and it will allow the results of prediction experiments to be communicated to the scientific community, governmental agencies, and the general public in an appropriate research context.

  3. PAN AIR: A computer program for predicting subsonic or supersonic linear potential flows about arbitrary configurations using a higher order panel method. Volume 2: User's manual (version 3.0)

    Science.gov (United States)

    Sidwell, Kenneth W.; Baruah, Pranab K.; Bussoletti, John E.; Medan, Richard T.; Conner, R. S.; Purdon, David J.

    1990-01-01

    A comprehensive description of user problem definition for the PAN AIR (Panel Aerodynamics) system is given. PAN AIR solves the 3-D linear integral equations of subsonic and supersonic flow. Influence coefficient methods are used which employ source and doublet panels as boundary surfaces. Both analysis and design boundary conditions can be used. This User's Manual describes the information needed to use the PAN AIR system. The structure and organization of PAN AIR are described, including the job control and module execution control languages for execution of the program system. The engineering input data are described, including the mathematical and physical modeling requirements. Version 3.0 strictly applies only to PAN AIR version 3.0. The major revisions include: (1) inputs and guidelines for the new FDP module (which calculates streamlines and offbody points); (2) nine new class 1 and class 2 boundary conditions to cover commonly used modeling practices, in particular the vorticity matching Kutta condition; (3) use of the CRAY solid state Storage Device (SSD); and (4) incorporation of errata and typo's together with additional explanation and guidelines.

  4. Computer Programs.

    Science.gov (United States)

    Anderson, Tiffoni

    This module provides information on development and use of a Material Safety Data Sheet (MSDS) software program that seeks to link literacy skills education, safety training, and human-centered design. Section 1 discusses the development of the software program that helps workers understand the MSDSs that accompany the chemicals with which they…

  5. BASIC Programming.

    Science.gov (United States)

    Jennings, Carol Ann

    Designed for use by both secondary- and postsecondary-level business teachers, this curriculum guide consists of 10 units of instructional materials dealing with Beginners All-Purpose Symbol Instruction Code (BASIC) programing. Topics of the individual lessons are numbering BASIC programs and using the PRINT, END, and REM statements; system…

  6. Fusion Simulation Program

    International Nuclear Information System (INIS)

    Greenwald, Martin

    2011-01-01

    Many others in the fusion energy and advanced scientific computing communities participated in the development of this plan. The core planning team is grateful for their important contributions. This summary is meant as a quick overview the Fusion Simulation Program's (FSP's) purpose and intentions. There are several additional documents referenced within this one and all are supplemental or flow down from this Program Plan. The overall science goal of the DOE Office of Fusion Energy Sciences (FES) Fusion Simulation Program (FSP) is to develop predictive simulation capability for magnetically confined fusion plasmas at an unprecedented level of integration and fidelity. This will directly support and enable effective U.S. participation in International Thermonuclear Experimental Reactor (ITER) research and the overall mission of delivering practical fusion energy. The FSP will address a rich set of scientific issues together with experimental programs, producing validated integrated physics results. This is very well aligned with the mission of the ITER Organization to coordinate with its members the integrated modeling and control of fusion plasmas, including benchmarking and validation activities. (1). Initial FSP research will focus on two critical Integrated Science Application (ISA) areas: ISA1, the plasma edge; and ISA2, whole device modeling (WDM) including disruption avoidance. The first of these problems involves the narrow plasma boundary layer and its complex interactions with the plasma core and the surrounding material wall. The second requires development of a computationally tractable, but comprehensive model that describes all equilibrium and dynamic processes at a sufficient level of detail to provide useful prediction of the temporal evolution of fusion plasma experiments. The initial driver for the whole device model will be prediction and avoidance of discharge-terminating disruptions, especially at high performance, which are a critical

  7. Plasma Simulation Program

    Energy Technology Data Exchange (ETDEWEB)

    Greenwald, Martin

    2011-10-04

    Many others in the fusion energy and advanced scientific computing communities participated in the development of this plan. The core planning team is grateful for their important contributions. This summary is meant as a quick overview the Fusion Simulation Program's (FSP's) purpose and intentions. There are several additional documents referenced within this one and all are supplemental or flow down from this Program Plan. The overall science goal of the DOE Office of Fusion Energy Sciences (FES) Fusion Simulation Program (FSP) is to develop predictive simulation capability for magnetically confined fusion plasmas at an unprecedented level of integration and fidelity. This will directly support and enable effective U.S. participation in International Thermonuclear Experimental Reactor (ITER) research and the overall mission of delivering practical fusion energy. The FSP will address a rich set of scientific issues together with experimental programs, producing validated integrated physics results. This is very well aligned with the mission of the ITER Organization to coordinate with its members the integrated modeling and control of fusion plasmas, including benchmarking and validation activities. [1]. Initial FSP research will focus on two critical Integrated Science Application (ISA) areas: ISA1, the plasma edge; and ISA2, whole device modeling (WDM) including disruption avoidance. The first of these problems involves the narrow plasma boundary layer and its complex interactions with the plasma core and the surrounding material wall. The second requires development of a computationally tractable, but comprehensive model that describes all equilibrium and dynamic processes at a sufficient level of detail to provide useful prediction of the temporal evolution of fusion plasma experiments. The initial driver for the whole device model will be prediction and avoidance of discharge-terminating disruptions, especially at high performance, which are a

  8. Choreographic Programming

    DEFF Research Database (Denmark)

    Montesi, Fabrizio

    , as they offer a concise view of the message flows enacted by a system. For this reason, in the last decade choreographies have been used in the development of programming languages, giving rise to a programming paradigm that in this dissertation we refer to as Choreographic Programming. Recent studies show...... endpoint described in a choreography can then be automatically generated, ensuring that such implementations are safe by construction. However, current formal models for choreographies do not deal with critical aspects of distributed programming, such as asynchrony, mobility, modularity, and multiparty...... sessions; it remains thus unclear whether choreographies can still guarantee safety when dealing with such nontrivial features. This PhD dissertation argues for the suitability of choreographic programming as a paradigm for the development of safe distributed systems. We proceed by investigating its...

  9. Firebird-III program description

    International Nuclear Information System (INIS)

    Lin, M.R.; Prawirosochardjo, S.; Rennick, D.F.; Wessman, E.; Blain, R.J.D.; Wilson, J.M.

    1979-09-01

    The FIREBIRD-III digital computer program is a general network code developed primarily for predicting the thermalhydraulic behaviour of CANDU power reactors during a postulated loss-of-coolant accident and the subsequent emergency coolant injection. Because of its flexibility, the code can also be used to solve a large variety of general two-phase flow problems. This report describes the thermalhydraulic models and the computation methods used in the program

  10. Predicting outdoor sound

    CERN Document Server

    Attenborough, Keith; Horoshenkov, Kirill

    2014-01-01

    1. Introduction  2. The Propagation of Sound Near Ground Surfaces in a Homogeneous Medium  3. Predicting the Acoustical Properties of Outdoor Ground Surfaces  4. Measurements of the Acoustical Properties of Ground Surfaces and Comparisons with Models  5. Predicting Effects of Source Characteristics on Outdoor Sound  6. Predictions, Approximations and Empirical Results for Ground Effect Excluding Meteorological Effects  7. Influence of Source Motion on Ground Effect and Diffraction  8. Predicting Effects of Mixed Impedance Ground  9. Predicting the Performance of Outdoor Noise Barriers  10. Predicting Effects of Vegetation, Trees and Turbulence  11. Analytical Approximations including Ground Effect, Refraction and Turbulence  12. Prediction Schemes  13. Predicting Sound in an Urban Environment.

  11. Prediction of GNSS satellite clocks

    International Nuclear Information System (INIS)

    Broederbauer, V.

    2010-01-01

    This thesis deals with the characterisation and prediction of GNSS-satellite-clocks. A prerequisite to develop powerful algorithms for the prediction of clock-corrections is the thorough study of the behaviour of the different clock-types of the satellites. In this context the predicted part of the IGU-clock-corrections provided by the Analysis Centers (ACs) of the IGS was compared to the IGS-Rapid-clock solutions to determine reasonable estimates of the quality of already existing well performing predictions. For the shortest investigated interval (three hours) all ACs obtain almost the same accuracy of 0,1 to 0,4 ns. For longer intervals the individual predictions results start to diverge. Thus, for a 12-hours- interval the differences range from nearly 10 ns (GFZ, CODE) until up to some 'tens of ns'. Based on the estimated clock corrections provided via the IGS Rapid products a simple quadratic polynomial turns out to be sufficient to describe the time series of Rubidium-clocks. On the other hand Cesium-clocks show a periodical behaviour (revolution period) with an amplitude of up to 6 ns. A clear correlation between these amplitudes and the Sun elevation angle above the orbital planes can be demonstrated. The variability of the amplitudes is supposed to be caused by temperature-variations affecting the oscillator. To account for this periodical behaviour a quadratic polynomial with an additional sinus-term was finally chosen as prediction model both for the Cesium as well as for the Rubidium clocks. The three polynomial-parameters as well as amplitude and phase shift of the periodic term are estimated within a least-square-adjustment by means of program GNSS-VC/static. Input-data are time series of the observed part of the IGU clock corrections. With the estimated parameters clock-corrections are predicted for various durations. The mean error of the prediction of Rubidium-clock-corrections for an interval of six hours reaches up to 1,5 ns. For the 12-hours

  12. Icobj Programming

    OpenAIRE

    Boussinot , Frédéric

    1996-01-01

    A simple and fully graphical programming method is presented, using a powerful means to combine behaviors. This programming is based on the notion of an «icobj» which has a behavioral aspect («object» part), a graphical aspect («icon» part), with an «animation» aspect. Icobj programming provides parallelism, broadcast event communication and migration through the network. An experimental system based on this approach is described in details. Its implementation with reactive scripts is also pr...

  13. Programming Python

    CERN Document Server

    Lutz, Mark

    2011-01-01

    If you've mastered Python's fundamentals, you're ready to start using it to get real work done. Programming Python will show you how, with in-depth tutorials on the language's primary application domains: system administration, GUIs, and the Web. You'll also explore how Python is used in databases, networking, front-end scripting layers, text processing, and more. This book focuses on commonly used tools and libraries to give you a comprehensive understanding of Python's many roles in practical, real-world programming. You'll learn language syntax and programming techniques in a clear and co

  14. Development of genomic prediction in sorghum

    NARCIS (Netherlands)

    Hunt, Colleen H.; Eeuwijk, van Fred A.; Mace, Emma S.; Hayes, Ben J.; Jordan, David R.

    2018-01-01

    Genomic selection can increase the rate of genetic gain in plant breeding programs by shortening the breeding cycle. Gain can also be increased through higher selection intensities, as the size of the population available for selection can be increased by predicting performance of nonphenotyped, but

  15. Predicting Secretory Proteins with SignalP

    DEFF Research Database (Denmark)

    Nielsen, Henrik

    2017-01-01

    SignalP is the currently most widely used program for prediction of signal peptides from amino acid sequences. Proteins with signal peptides are targeted to the secretory pathway, but are not necessarily secreted. After a brief introduction to the biology of signal peptides and the history...

  16. Predictive microbiology for food packaging applications

    Science.gov (United States)

    Mathematical modeling has been applied to describe the microbial growth and inactivation in foods for decades and is also known as ‘Predictive microbiology’. When models are developed and validated, their applications may save cost and time. The Pathogen Modeling Program (PMP), a collection of mode...

  17. Applied predictive control

    CERN Document Server

    Sunan, Huang; Heng, Lee Tong

    2002-01-01

    The presence of considerable time delays in the dynamics of many industrial processes, leading to difficult problems in the associated closed-loop control systems, is a well-recognized phenomenon. The performance achievable in conventional feedback control systems can be significantly degraded if an industrial process has a relatively large time delay compared with the dominant time constant. Under these circumstances, advanced predictive control is necessary to improve the performance of the control system significantly. The book is a focused treatment of the subject matter, including the fundamentals and some state-of-the-art developments in the field of predictive control. Three main schemes for advanced predictive control are addressed in this book: • Smith Predictive Control; • Generalised Predictive Control; • a form of predictive control based on Finite Spectrum Assignment. A substantial part of the book addresses application issues in predictive control, providing several interesting case studie...

  18. Program overview

    International Nuclear Information System (INIS)

    Anon.

    1977-01-01

    The program overview describes the following resources and facilities; laser facilities, main laser room, target room, energy storage, laboratory area, building support systems, general plant project, and the new trailer complex

  19. Linear programming

    CERN Document Server

    Solow, Daniel

    2014-01-01

    This text covers the basic theory and computation for a first course in linear programming, including substantial material on mathematical proof techniques and sophisticated computation methods. Includes Appendix on using Excel. 1984 edition.

  20. Science Programs

    Science.gov (United States)

    Laboratory Delivering science and technology to protect our nation and promote world stability Science & ; Innovation Collaboration Careers Community Environment Science & Innovation Facilities Science Pillars Research Library Science Briefs Science News Science Highlights Lab Organizations Science Programs Applied

  1. Predicting transportation routes for radioactive wastes

    International Nuclear Information System (INIS)

    Joy, D.S.; Johnson, P.E.; Clarke, D.B.; McGuire, S.C.

    1981-01-01

    Oak Ridge National Laboratory (ORNL) has been involved in transportation logistics of radioactive wastes as part of the overall waste transportation program. A Spent Fuel Logistics Model (SFLM), was developed to predict overall material balances representing the flow of spent fuel assemblies from reactors to away-from-reactor storage facilities and/or to federal repositories. The transportation requirements to make these shipments are also itemized. The next logical step in the overall transportation project was the development of a set of computer codes which would predict likely transportation routes for waste shipments. Two separate routing models are now operational at ORNL. Routes for truck transport can be estimated with the HIGHWAY program, and rail and barge routes can be predicted with the INTERLINE model. This paper discusses examples of the route estimates and applications of the routing models

  2. Accurate predictions for the LHC made easy

    CERN Multimedia

    CERN. Geneva

    2014-01-01

    The data recorded by the LHC experiments is of a very high quality. To get the most out of the data, precise theory predictions, including uncertainty estimates, are needed to reduce as much as possible theoretical bias in the experimental analyses. Recently, significant progress has been made in computing Next-to-Leading Order (NLO) computations, including matching to the parton shower, that allow for these accurate, hadron-level predictions. I shall discuss one of these efforts, the MadGraph5_aMC@NLO program, that aims at the complete automation of predictions at the NLO accuracy within the SM as well as New Physics theories. I’ll illustrate some of the theoretical ideas behind this program, show some selected applications to LHC physics, as well as describe the future plans.

  3. SPOT Program

    Science.gov (United States)

    Smith, Jason T.; Welsh, Sam J.; Farinetti, Antonio L.; Wegner, Tim; Blakeslee, James; Deboeck, Toni F.; Dyer, Daniel; Corley, Bryan M.; Ollivierre, Jarmaine; Kramer, Leonard; hide

    2010-01-01

    A Spacecraft Position Optimal Tracking (SPOT) program was developed to process Global Positioning System (GPS) data, sent via telemetry from a spacecraft, to generate accurate navigation estimates of the vehicle position and velocity (state vector) using a Kalman filter. This program uses the GPS onboard receiver measurements to sequentially calculate the vehicle state vectors and provide this information to ground flight controllers. It is the first real-time ground-based shuttle navigation application using onboard sensors. The program is compact, portable, self-contained, and can run on a variety of UNIX or Linux computers. The program has a modular objec-toriented design that supports application-specific plugins such as data corruption remediation pre-processing and remote graphics display. The Kalman filter is extensible to additional sensor types or force models. The Kalman filter design is also strong against data dropouts because it uses physical models from state and covariance propagation in the absence of data. The design of this program separates the functionalities of SPOT into six different executable processes. This allows for the individual processes to be connected in an a la carte manner, making the feature set and executable complexity of SPOT adaptable to the needs of the user. Also, these processes need not be executed on the same workstation. This allows for communications between SPOT processes executing on the same Local Area Network (LAN). Thus, SPOT can be executed in a distributed sense with the capability for a team of flight controllers to efficiently share the same trajectory information currently being computed by the program. SPOT is used in the Mission Control Center (MCC) for Space Shuttle Program (SSP) and International Space Station Program (ISSP) operations, and can also be used as a post -flight analysis tool. It is primarily used for situational awareness, and for contingency situations.

  4. Sprego programming

    OpenAIRE

    Csernoch, Mária; Biró, Piroska

    2015-01-01

    Spreadsheet management is a border-land between office applications and programming, however, it is rather communicated that spreadsheet is nothing more than an easily handled fun piece. Consequently, the complexity of spreadsheet handling, the unprepared end-users, their problem solving abilities and approaches do not match. To overcome these problems we have developed and introduced Sprego (Spreadsheet Lego). Sprego is a simplified functional programming language in spreadsheet environment,...

  5. Recombinant Programming

    OpenAIRE

    Pawlak , Renaud; Cuesta , Carlos; Younessi , Houman

    2004-01-01

    This research report presents a promising new approach to computation called Recombinant Programming. The novelty of our approach is that it separates the program into two layers of computation: the recombination and the interpretation layer. The recombination layer takes sequences as inputs and allows the programmer to recombine these sequences through the definition of cohesive code units called extensions. The output of such recombination is a mesh that can be used by the interpretation la...

  6. Predictable or not predictable? The MOV question

    International Nuclear Information System (INIS)

    Thibault, C.L.; Matzkiw, J.N.; Anderson, J.W.; Kessler, D.W.

    1994-01-01

    Over the past 8 years, the nuclear industry has struggled to understand the dynamic phenomena experienced during motor-operated valve (MOV) operation under differing flow conditions. For some valves and designs, their operational functionality has been found to be predictable; for others, unpredictable. Although much has been accomplished over this period of time, especially on modeling valve dynamics, the unpredictability of many valves and designs still exists. A few valve manufacturers are focusing on improving design and fabrication techniques to enhance product reliability and predictability. However, this approach does not address these issues for installed and inpredictable valves. This paper presents some of the more promising techniques that Wyle Laboratories has explored with potential for transforming unpredictable valves to predictable valves and for retrofitting installed MOVs. These techniques include optimized valve tolerancing, surrogated material evaluation, and enhanced surface treatments

  7. CNN-PROMOTER, NEW CONSENSUS PROMOTER PREDICTION PROGRAM BASED ON NEURAL NETWORKS CNN-PROMOTER, NUEVO PROGRAMA PARA LA PREDICCIÓN DE PROMOTORES BASADO EN REDES NEURONALES CNN-PROMOTER, NOVO PROGRAMA PARA A PREDIÇÃO DE PROMOTORES BASEADO EM REDES NEURONAIS

    Directory of Open Access Journals (Sweden)

    Óscar Bedoya

    2011-06-01

    Full Text Available A new promoter prediction program called CNN-Promoter is presented. CNN-Promoter allows DNA sequences to be submitted and predicts them as promoter or non-promoter. Several methods have been developed to predict the promoter regions of genomes in eukaryotic organisms including algorithms based on Markov's models, decision trees, and statistical methods. Although there are plenty of programs proposed, there is still a need to improve the sensitivity and specificity values. In this paper, a new program is proposed; it is based on the consensus strategy of using experts to make a better prediction. The consensus strategy is developed by using neural networks. During the training process, the sensitivity and specificity were 100 % and during the test process the model reaches a sensitivity of 74.5 % and a specificity of 82.7 %.En este artículo se presenta un programa nuevo para la predicción de promotores llamado CNN-Promoter, que toma como entrada secuencias de ADN y las clasifica como promotor o no promotor. Se han desarrollado diversos métodos para predecir las regiones promotoras en organismos eucariotas, muchos de los cuales se basan en modelos de Markov, árboles de decisión y métodos estadísticos. A pesar de la variedad de programas existentes para la predicción de promotores, se necesita aún mejorar los valores de sensibilidad y especificidad. Se propone un nuevo programa que se basa en la estrategia de mezcla de expertos usando redes neuronales. Los resultados obtenidos en las pruebas alcanzan valores de sensibilidad y especificidad de 100 % en el entrenamiento y de 74,5 % de sensibilidad y 82,7 % de especificidad en los conjuntos de validación y prueba.Neste artigo a presenta-se um novo programa para a predição de promotores chamado CNN-Promoter, que toma como entrada sequências de DNA e as classifica como promotor ou não promotor. Desenvolveramse diversos métodos para predizer as regiões promotoras em organismos eucariotas

  8. MDOT Pavement Management System : Prediction Models and Feedback System

    Science.gov (United States)

    2000-10-01

    As a primary component of a Pavement Management System (PMS), prediction models are crucial for one or more of the following analyses: : maintenance planning, budgeting, life-cycle analysis, multi-year optimization of maintenance works program, and a...

  9. Predictive systems ecology.

    Science.gov (United States)

    Evans, Matthew R; Bithell, Mike; Cornell, Stephen J; Dall, Sasha R X; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J; Lewis, Simon L; Mace, Georgina M; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K J; Petchey, Owen; Smith, Matthew; Travis, Justin M J; Benton, Tim G

    2013-11-22

    Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

  10. Advanced maintenance research programs

    International Nuclear Information System (INIS)

    Marston, T.U.; Gelhaus, F.; Burke, R.

    1985-01-01

    The purpose of this paper is to provide the reader with an idea of the advanced maintenance research program at the Electric Power Research Institute (EPRI). A brief description of the maintenance-related activities is provided as a foundation for the advanced maintenance research projects. The projects can be divided into maintenance planning, preventive maintenance program development and implementation, predictive (or conditional) maintenance, and innovative maintenance techniques. The projects include hardware and software development, human factors considerations, and technology promotion and implementation. The advanced concepts include: the incorporation of artificial intelligence into outage planning; turbine and pump maintenance; rotating equipment monitoring and diagnostics with the aid of expert systems; and the development of mobile robots for nuclear power plant maintenance

  11. Seismology for rockburst prediction.

    CSIR Research Space (South Africa)

    De Beer, W

    2000-02-01

    Full Text Available project GAP409 presents a method (SOOTHSAY) for predicting larger mining induced seismic events in gold mines, as well as a pattern recognition algorithm (INDICATOR) for characterising the seismic response of rock to mining and inferring future... State. Defining the time series of a specific function on a catalogue as a prediction strategy, the algorithm currently has a success rate of 53% and 65%, respectively, of large events claimed as being predicted in these two cases, with uncertainties...

  12. Predictability of Conversation Partners

    Science.gov (United States)

    Takaguchi, Taro; Nakamura, Mitsuhiro; Sato, Nobuo; Yano, Kazuo; Masuda, Naoki

    2011-08-01

    Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information-theoretic method to the spatiotemporal data of cell-phone locations, [C. Song , ScienceSCIEAS0036-8075 327, 1018 (2010)] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one’s conversation partners is defined as the degree to which one’s next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to a certain extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual’s predictability is correlated with the position of the individual in the static social network derived from the data. Individuals confined in a community—in the sense of an abundance of surrounding triangles—tend to have low predictability, and those bridging different communities tend to have high predictability.

  13. Predictability of Conversation Partners

    Directory of Open Access Journals (Sweden)

    Taro Takaguchi

    2011-09-01

    Full Text Available Recent developments in sensing technologies have enabled us to examine the nature of human social behavior in greater detail. By applying an information-theoretic method to the spatiotemporal data of cell-phone locations, [C. Song et al., Science 327, 1018 (2010SCIEAS0036-8075] found that human mobility patterns are remarkably predictable. Inspired by their work, we address a similar predictability question in a different kind of human social activity: conversation events. The predictability in the sequence of one’s conversation partners is defined as the degree to which one’s next conversation partner can be predicted given the current partner. We quantify this predictability by using the mutual information. We examine the predictability of conversation events for each individual using the longitudinal data of face-to-face interactions collected from two company offices in Japan. Each subject wears a name tag equipped with an infrared sensor node, and conversation events are marked when signals are exchanged between sensor nodes in close proximity. We find that the conversation events are predictable to a certain extent; knowing the current partner decreases the uncertainty about the next partner by 28.4% on average. Much of the predictability is explained by long-tailed distributions of interevent intervals. However, a predictability also exists in the data, apart from the contribution of their long-tailed nature. In addition, an individual’s predictability is correlated with the position of the individual in the static social network derived from the data. Individuals confined in a community—in the sense of an abundance of surrounding triangles—tend to have low predictability, and those bridging different communities tend to have high predictability.

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

    Energy Technology Data Exchange (ETDEWEB)

    Cuccio, J.C.; Brehm, P.; Fang, H.T. [Allied-Signal Aerospace Co., Phoenix, AZ (United States). Garrett Engine Div.] [and others

    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.

  15. Is Time Predictability Quantifiable?

    DEFF Research Database (Denmark)

    Schoeberl, Martin

    2012-01-01

    Computer architects and researchers in the realtime domain start to investigate processors and architectures optimized for real-time systems. Optimized for real-time systems means time predictable, i.e., architectures where it is possible to statically derive a tight bound of the worst......-case execution time. To compare different approaches we would like to quantify time predictability. That means we need to measure time predictability. In this paper we discuss the different approaches for these measurements and conclude that time predictability is practically not quantifiable. We can only...... compare the worst-case execution time bounds of different architectures....

  16. Predicting scholars' scientific impact.

    Directory of Open Access Journals (Sweden)

    Amin Mazloumian

    Full Text Available We tested the underlying assumption that citation counts are reliable predictors of future success, analyzing complete citation data on the careers of ~150,000 scientists. Our results show that i among all citation indicators, the annual citations at the time of prediction is the best predictor of future citations, ii future citations of a scientist's published papers can be predicted accurately (r(2 = 0.80 for a 1-year prediction, P<0.001 but iii future citations of future work are hardly predictable.

  17. CERAPP: Collaborative estrogen receptor activity prediction project

    DEFF Research Database (Denmark)

    Mansouri, Kamel; Abdelaziz, Ahmed; Rybacka, Aleksandra

    2016-01-01

    ). 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...... 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......: 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...

  18. Predicting RNA Structure Using Mutual Information

    DEFF Research Database (Denmark)

    Freyhult, E.; Moulton, V.; Gardner, P. P.

    2005-01-01

    , to display and predict conserved RNA secondary structure (including pseudoknots) from an alignment. Results: We show that MIfold can be used to predict simple pseudoknots, and that the performance can be adjusted to make it either more sensitive or more selective. We also demonstrate that the overall...... package. Conclusion: MIfold provides a useful supplementary tool to programs such as RNA Structure Logo, RNAalifold and COVE, and should be useful for automatically generating structural predictions for databases such as Rfam. Availability: MIfold is freely available from http......Background: With the ever-increasing number of sequenced RNAs and the establishment of new RNA databases, such as the Comparative RNA Web Site and Rfam, there is a growing need for accurately and automatically predicting RNA structures from multiple alignments. Since RNA secondary structure...

  19. GAPIT: genome association and prediction integrated tool.

    Science.gov (United States)

    Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

    2012-09-15

    Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

  20. Integer programming

    CERN Document Server

    Conforti, Michele; Zambelli, Giacomo

    2014-01-01

    This book is an elegant and rigorous presentation of integer programming, exposing the subject’s mathematical depth and broad applicability. Special attention is given to the theory behind the algorithms used in state-of-the-art solvers. An abundance of concrete examples and exercises of both theoretical and real-world interest explore the wide range of applications and ramifications of the theory. Each chapter is accompanied by an expertly informed guide to the literature and special topics, rounding out the reader’s understanding and serving as a gateway to deeper study. Key topics include: formulations polyhedral theory cutting planes decomposition enumeration semidefinite relaxations Written by renowned experts in integer programming and combinatorial optimization, Integer Programming is destined to become an essential text in the field.

  1. Programming Algol

    CERN Document Server

    Malcolme-Lawes, D J

    2014-01-01

    Programming - ALGOL describes the basics of computer programming using Algol. Commands that could be added to Algol and could increase its scope are described, including multiplication and division and the use of brackets. The idea of labeling or naming a command is also explained, along with a command allowing two alternative results. Most of the important features of Algol syntax are discussed, and examples of compound statements (that is, sets of commands enclosed by a begin ... end command) are given.Comprised of 11 chapters, this book begins with an introduction to the digital computer an

  2. Programming Interactivity

    CERN Document Server

    Noble, Joshua

    2012-01-01

    Ready to create rich interactive experiences with your artwork, designs, or prototypes? This is the ideal place to start. With this hands-on guide, you'll explore several themes in interactive art and design-including 3D graphics, sound, physical interaction, computer vision, and geolocation-and learn the basic programming and electronics concepts you need to implement them. No previous experience is necessary. You'll get a complete introduction to three free tools created specifically for artists and designers: the Processing programming language, the Arduino microcontroller, and the openFr

  3. Small Spacecraft Technology Initiative Education Program

    Science.gov (United States)

    1995-01-01

    A NASA engineer with the Commercial Remote Sensing Program (CRSP) at Stennis Space Center works with students from W.P. Daniels High School in New Albany, Miss., through NASA's Small Spacecraft Technology Initiative Program. CRSP is teaching students to use remote sensing to locate a potential site for a water reservoir to offset a predicted water shortage in the community's future.

  4. Perceptual Speed and Psychomotor Ability Predict Laparoscopic Skill Acquisition on a Simulator

    NARCIS (Netherlands)

    Groenier, Marleen; Groenier, Klaas H.; Miedema, Heleen A. T.; Broeders, Ivo A. M. J.

    2015-01-01

    OBJECTIVE: Performing minimally invasive surgery puts high demands on a surgeon's cognitive and psychomotor abilities. Assessment of these abilities can be used to predict a surgeon's learning curve, to create individualized training programs, and ultimately in selection programs for surgical

  5. Mathematical model for dissolved oxygen prediction in Cirata ...

    African Journals Online (AJOL)

    This paper presents the implementation and performance of mathematical model to predict theconcentration of dissolved oxygen in Cirata Reservoir, West Java by using Artificial Neural Network (ANN). The simulation program was created using Visual Studio 2012 C# software with ANN model implemented in it. Prediction ...

  6. The Prediction Value

    NARCIS (Netherlands)

    Koster, M.; Kurz, S.; Lindner, I.; Napel, S.

    2013-01-01

    We introduce the prediction value (PV) as a measure of players’ informational importance in probabilistic TU games. The latter combine a standard TU game and a probability distribution over the set of coalitions. Player i’s prediction value equals the difference between the conditional expectations

  7. Predictability of Stock Returns

    Directory of Open Access Journals (Sweden)

    Ahmet Sekreter

    2017-06-01

    Full Text Available Predictability of stock returns has been shown by empirical studies over time. This article collects the most important theories on forecasting stock returns and investigates the factors that affecting behavior of the stocks’ prices and the market as a whole. Estimation of the factors and the way of estimation are the key issues of predictability of stock returns.

  8. Predicting AD conversion

    DEFF Research Database (Denmark)

    Liu, Yawu; Mattila, Jussi; Ruiz, Miguel �ngel Mu�oz

    2013-01-01

    To compare the accuracies of predicting AD conversion by using a decision support system (PredictAD tool) and current research criteria of prodromal AD as identified by combinations of episodic memory impairment of hippocampal type and visual assessment of medial temporal lobe atrophy (MTA) on MRI...

  9. Predicting Free Recalls

    Science.gov (United States)

    Laming, Donald

    2006-01-01

    This article reports some calculations on free-recall data from B. Murdock and J. Metcalfe (1978), with vocal rehearsal during the presentation of a list. Given the sequence of vocalizations, with the stimuli inserted in their proper places, it is possible to predict the subsequent sequence of recalls--the predictions taking the form of a…

  10. Archaeological predictive model set.

    Science.gov (United States)

    2015-03-01

    This report is the documentation for Task 7 of the Statewide Archaeological Predictive Model Set. The goal of this project is to : develop a set of statewide predictive models to assist the planning of transportation projects. PennDOT is developing t...

  11. Genomic Prediction of Barley Hybrid Performance

    Directory of Open Access Journals (Sweden)

    Norman Philipp

    2016-07-01

    Full Text Available Hybrid breeding in barley ( L. offers great opportunities to accelerate the rate of genetic improvement and to boost yield stability. A crucial requirement consists of the efficient selection of superior hybrid combinations. We used comprehensive phenotypic and genomic data from a commercial breeding program with the goal of examining the potential to predict the hybrid performances. The phenotypic data were comprised of replicated grain yield trials for 385 two-way and 408 three-way hybrids evaluated in up to 47 environments. The parental lines were genotyped using a 3k single nucleotide polymorphism (SNP array based on an Illumina Infinium assay. We implemented ridge regression best linear unbiased prediction modeling for additive and dominance effects and evaluated the prediction ability using five-fold cross validations. The prediction ability of hybrid performances based on general combining ability (GCA effects was moderate, amounting to 0.56 and 0.48 for two- and three-way hybrids, respectively. The potential of GCA-based hybrid prediction requires that both parental components have been evaluated in a hybrid background. This is not necessary for genomic prediction for which we also observed moderate cross-validated prediction abilities of 0.51 and 0.58 for two- and three-way hybrids, respectively. This exemplifies the potential of genomic prediction in hybrid barley. Interestingly, prediction ability using the two-way hybrids as training population and the three-way hybrids as test population or vice versa was low, presumably, because of the different genetic makeup of the parental source populations. Consequently, further research is needed to optimize genomic prediction approaches combining different source populations in barley.

  12. SLED program

    International Nuclear Information System (INIS)

    Farkas, Z.D.

    1977-04-01

    A FORTRAN program is described which, for a given cavity and timing, yields all fields as a (piecewise) function of time, and which, for any mix of SLEDded and non-SLEDded klystrons of any given energy/klystron, yields the SLED operation parameters. The note explains the input and output parameters as they appear in the code output. 3 figures, 19 tables

  13. ORGEL program

    Energy Technology Data Exchange (ETDEWEB)

    none

    1963-09-01

    Parameter optimization studies for an ORGEL power plant are reported, and the ESSOR test reactor used in the program is described. Research at Ispra in reactor physics, technology, metallurgy, heat transfer, chemistry, and physical chemistry associated with ORGEL development is also summarized. (D.C.W.)

  14. Program evaluation

    Energy Technology Data Exchange (ETDEWEB)

    1988-01-01

    This book contains the proceedings from the panel on program evaluation. Some of the papers included are the following: Seattle City Light's Industrial Retrofit Demonstration Project Uses Quasi-Experimental Research Design and Metering to Measure Savings, Evaluation for PUCs, and The Takeback Effect Low-income Weatherizations Fact or Fiction

  15. Sprego Programming

    Directory of Open Access Journals (Sweden)

    Maria Csernoch

    2015-02-01

    Full Text Available Spreadsheet management is a border-land between office applications and programming, however, it is rather communicated that spreadsheet is nothing more than an easily handled fun piece. Consequently, the complexity of spreadsheet handling, the unprepared end-users, their problem solving abilities and approaches do not match. To overcome these problems we have developed and introduced Sprego (Spreadsheet Lego. Sprego is a simplified functional programming language in spreadsheet environment, and such as can be used both as introductory language and the language of end-user programmers. The essence of Sprego is that we use as few and simple functions as possible and based on these functions build multilevel formulas. With this approach, similar to high level programming, we are able solve advanced problems, developing algorithmic skills, computational thinking. The advantage of Sprego is the simplicity of the language, when the emphasis is not on the coding but on the problem. Beyond that spreadsheets would provide real life problems with authentic data and tables which students are more interested in than the artificial environment and semi-authentic problems of high level programming languages.

  16. Polytypic Programming

    NARCIS (Netherlands)

    Jeuring, J.T.; Jansson, P.

    1996-01-01

    Many functions have to be written over and over again for different datatypes, either because datatypes change during the development of programs, or because functions with similar functionality are needed on different datatypes. Examples of such functions are pretty printers, debuggers, equality

  17. Evaluating prediction uncertainty

    International Nuclear Information System (INIS)

    McKay, M.D.

    1995-03-01

    The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is applied in two analysis applications to select subsets of input variables which are the dominant causes of uncertainty in the model predictions. Comparison with results from methods which assume linearity shows how those methods may fail. Finally, suggestions for treating structural uncertainty for submodels are presented

  18. Ground motion predictions

    Energy Technology Data Exchange (ETDEWEB)

    Loux, P C [Environmental Research Corporation, Alexandria, VA (United States)

    1969-07-01

    Nuclear generated ground motion is defined and then related to the physical parameters that cause it. Techniques employed for prediction of ground motion peak amplitude, frequency spectra and response spectra are explored, with initial emphasis on the analysis of data collected at the Nevada Test Site (NTS). NTS postshot measurements are compared with pre-shot predictions. Applicability of these techniques to new areas, for example, Plowshare sites, must be questioned. Fortunately, the Atomic Energy Commission is sponsoring complementary studies to improve prediction capabilities primarily in new locations outside the NTS region. Some of these are discussed in the light of anomalous seismic behavior, and comparisons are given showing theoretical versus experimental results. In conclusion, current ground motion prediction techniques are applied to events off the NTS. Predictions are compared with measurements for the event Faultless and for the Plowshare events, Gasbuggy, Cabriolet, and Buggy I. (author)

  19. Ground motion predictions

    International Nuclear Information System (INIS)

    Loux, P.C.

    1969-01-01

    Nuclear generated ground motion is defined and then related to the physical parameters that cause it. Techniques employed for prediction of ground motion peak amplitude, frequency spectra and response spectra are explored, with initial emphasis on the analysis of data collected at the Nevada Test Site (NTS). NTS postshot measurements are compared with pre-shot predictions. Applicability of these techniques to new areas, for example, Plowshare sites, must be questioned. Fortunately, the Atomic Energy Commission is sponsoring complementary studies to improve prediction capabilities primarily in new locations outside the NTS region. Some of these are discussed in the light of anomalous seismic behavior, and comparisons are given showing theoretical versus experimental results. In conclusion, current ground motion prediction techniques are applied to events off the NTS. Predictions are compared with measurements for the event Faultless and for the Plowshare events, Gasbuggy, Cabriolet, and Buggy I. (author)

  20. Refurbishment programs

    International Nuclear Information System (INIS)

    Irish, C.S.

    2004-01-01

    As nuclear plants age, equipment becomes obsolete, outdated or just simply unreliable. This puts a lot of emphasis on replacement of the subject equipment. This can be an expensive proposition for safety related equipment due to design changes, requalification charges and the cost of the new equipment, specifically when the original component is obsolete. The presentation will explain how comprehensive refurbishment programs on many different types of equipment can alleviate this situation. The refurbishment program is a systematic refurbishment of equipment to an as new condition by replacing all of the age sensitive components within the equipment. This is carried out on all of the same type of equipment in a scheduled program. For example the plant may to decide to refurbish all of their Lambda LME-24 power supplies, or all of their Bailey modules, or all of their Agastat DSC Series relays. Independent of the item the process is the same. Refurbish each piece of equipment to an as new condition by replacing all of the age sensitive equipment. The equipment is then returned to the client as safety related, existing qualification maintained and with a new service life/warranty. This is not a simple repair. It is a planned refurbishment to an as new condition of certain equipment types throughout the plant and then carried out from equipment piece to equipment piece. The refurbishment program may even include introducing new spares into the plant. This is normally performed by upgrading (dedicating for safety related use and refurbishing to an 'as new' condition) surplus equipment and using these equipment pieces in the rotation of the plant equipment to refurbish the entire population of a selected piece of equipment at the plant. This process can be performed on many equipment types including power supplies, circuit boards, modules, relays, motors, breakers, and many more. The refurbishment program greatly increases the reliability of the equipment without the

  1. Prediction of glycosylation sites using random forests

    Directory of Open Access Journals (Sweden)

    Hirst Jonathan D

    2008-11-01

    Full Text Available Abstract Background Post translational modifications (PTMs occur in the vast majority of proteins and are essential for function. Prediction of the sequence location of PTMs enhances the functional characterisation of proteins. Glycosylation is one type of PTM, and is implicated in protein folding, transport and function. Results We use the random forest algorithm and pairwise patterns to predict glycosylation sites. We identify pairwise patterns surrounding glycosylation sites and use an odds ratio to weight their propensity of association with modified residues. Our prediction program, GPP (glycosylation prediction program, predicts glycosylation sites with an accuracy of 90.8% for Ser sites, 92.0% for Thr sites and 92.8% for Asn sites. This is significantly better than current glycosylation predictors. We use the trepan algorithm to extract a set of comprehensible rules from GPP, which provide biological insight into all three major glycosylation types. Conclusion We have created an accurate predictor of glycosylation sites and used this to extract comprehensible rules about the glycosylation process. GPP is available online at http://comp.chem.nottingham.ac.uk/glyco/.

  2. Status of CHAP: composite HTGR analysis program

    International Nuclear Information System (INIS)

    Secker, P.A.; Gilbert, J.S.

    1975-12-01

    Development of an HTGR accident simulation program is in progress for the prediction of the overall HTGR plant transient response to various initiating events. The status of the digital computer program named CHAP (Composite HTGR Analysis Program) as of June 30, 1975, is given. The philosophy, structure, and capabilities of the CHAP code are discussed. Mathematical descriptions are given for those HTGR components that have been modeled. Component model validation and evaluation using auxiliary analysis codes are also discussed

  3. Preliminary evaluation of the BIODOSE computer program

    International Nuclear Information System (INIS)

    Bonner, N.A.; Ng, Y.C.

    1979-09-01

    The BIODOSE computer program simulates the environmental transport of radionuclides released to surface water and predicts the dosage to humans. We have evaluated the program for its suitability to the needs of the Nuclear Regulatory Commission Waste Management Program. In particular, it is an evaluation to determine whether BIODOSE models account for the significant pathways and mechanisms resulting in radiological doses to man. In general, BIODOSE is a satisfactory code for converting radionuclide releases to the aqueous environment into doses to man

  4. Structural prediction in aphasia

    Directory of Open Access Journals (Sweden)

    Tessa Warren

    2015-05-01

    Full Text Available There is considerable evidence that young healthy comprehenders predict the structure of upcoming material, and that their processing is facilitated when they encounter material matching those predictions (e.g., Staub & Clifton, 2006; Yoshida, Dickey & Sturt, 2013. However, less is known about structural prediction in aphasia. There is evidence that lexical prediction may be spared in aphasia (Dickey et al., 2014; Love & Webb, 1977; cf. Mack et al, 2013. However, predictive mechanisms supporting facilitated lexical access may not necessarily support structural facilitation. Given that many people with aphasia (PWA exhibit syntactic deficits (e.g. Goodglass, 1993, PWA with such impairments may not engage in structural prediction. However, recent evidence suggests that some PWA may indeed predict upcoming structure (Hanne, Burchert, De Bleser, & Vashishth, 2015. Hanne et al. tracked the eyes of PWA (n=8 with sentence-comprehension deficits while they listened to reversible subject-verb-object (SVO and object-verb-subject (OVS sentences in German, in a sentence-picture matching task. Hanne et al. manipulated case and number marking to disambiguate the sentences’ structure. Gazes to an OVS or SVO picture during the unfolding of a sentence were assumed to indicate prediction of the structure congruent with that picture. According to this measure, the PWA’s structural prediction was impaired compared to controls, but they did successfully predict upcoming structure when morphosyntactic cues were strong and unambiguous. Hanne et al.’s visual-world evidence is suggestive, but their forced-choice sentence-picture matching task places tight constraints on possible structural predictions. Clearer evidence of structural prediction would come from paradigms where the content of upcoming material is not as constrained. The current study used self-paced reading study to examine structural prediction among PWA in less constrained contexts. PWA (n=17 who

  5. Mathematical Model for Prediction of Flexural Strength of Mound ...

    African Journals Online (AJOL)

    The mound soil-cement blended proportions were mathematically optimized by using scheffe's approach and the optimization model developed. A computer program predicting the mix proportion for the model was written. The optimal proportion by the program was used prepare beam samples measuring 150mm x 150mm ...

  6. Predicting Performance in Higher Education Using Proximal Predictors

    NARCIS (Netherlands)

    Niessen, A Susan M; Meijer, Rob R; Tendeiro, Jorge N

    2016-01-01

    We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach,

  7. Prediction of Lower Extremity Movement by Cyclograms

    Directory of Open Access Journals (Sweden)

    P. Kutilek

    2012-01-01

    Full Text Available Human gait is nowadays undergoing extensive analysis. Predictions of leg movements can be used for orthosis and prosthesis programming, and also for rehabilitation. Our work focuses on predicting human gait with the use of angle-angle diagrams, also called cyclograms. In conjunction with artificial intelligence, cyclograms offer a wide area of medical applications. We have identified cyclogram characteristics such as the slope and the area of the cyclogram for a neural network learning algorithm. Neural networks learned by cyclograms offer wide applications in prosthesis control systems.

  8. TAD- THEORETICAL AERODYNAMICS PROGRAM

    Science.gov (United States)

    Barrowman, J.

    1994-01-01

    This theoretical aerodynamics program, TAD, was developed to predict the aerodynamic characteristics of vehicles with sounding rocket configurations. These slender, axisymmetric finned vehicle configurations have a wide range of aeronautical applications from rockets to high speed armament. Over a given range of Mach numbers, TAD will compute the normal force coefficient derivative, the center-of-pressure, the roll forcing moment coefficient derivative, the roll damping moment coefficient derivative, and the pitch damping moment coefficient derivative of a sounding rocket configured vehicle. The vehicle may consist of a sharp pointed nose of cone or tangent ogive shape, up to nine other body divisions of conical shoulder, conical boattail, or circular cylinder shape, and fins of trapezoid planform shape with constant cross section and either three or four fins per fin set. The characteristics computed by TAD have been shown to be accurate to within ten percent of experimental data in the supersonic region. The TAD program calculates the characteristics of separate portions of the vehicle, calculates the interference between separate portions of the vehicle, and then combines the results to form a total vehicle solution. Also, TAD can be used to calculate the characteristics of the body or fins separately as an aid in the design process. Input to the TAD program consists of simple descriptions of the body and fin geometries and the Mach range of interest. Output includes the aerodynamic characteristics of the total vehicle, or user-selected portions, at specified points over the mach range. The TAD program is written in FORTRAN IV for batch execution and has been implemented on an IBM 360 computer with a central memory requirement of approximately 123K of 8 bit bytes. The TAD program was originally developed in 1967 and last updated in 1972.

  9. A Predictive Study of Student Satisfaction in Online Education Programs

    Directory of Open Access Journals (Sweden)

    Yu-Chun Kuo

    2013-03-01

    Full Text Available This paper is intended to investigate the degree to which interaction and other predictors contribute to student satisfaction in online learning settings. This was a preliminary study towards a dissertation work which involved the establishment of interaction and satisfaction scales through a content validity survey. Regression analysis was performed to determine the contribution of predictor variables to student satisfaction. The effects of student background variables on predictors were explored. The results showed that learner-instructor interaction, learner-content interaction, and Internet self-efficacy were good predictors of student satisfaction while interactions among students and self-regulated learning did not contribute to student satisfaction. Learner-content interaction explained the largest unique variance in student satisfaction. Additionally, gender, class level, and time spent online per week seemed to have influence on learner-learner interaction, Internet self-efficacy, and self-regulation.

  10. Computer Program for Vibration Prediction of Fighter Aircraft Equipments

    Science.gov (United States)

    1977-11-01

    Y,*70q, X, S VJPPF 768 2? c ,l0 -1-qv** o, ~7 Aljl VIPRF 26q OTNT I,(TPL A NE(T),T=I ,),JFLITE,IMOPLT VIPPF 770 F,7 T(1rRp, 2Y, 0FSPITION OARD*/2 0 Y...VTPPF 2261 VIPPF 2262 VTPPF 2267 H-r,< Ww P D "lrgFPTTT O ,l, rAPD WAS RSA VIPRF 2264 17 VTPPF 22E5 1I f =ILT =2(1 1iP(I.WE.IS NnL.An..NF.IIU r

  11. Prediction of bull fertility.

    Science.gov (United States)

    Utt, Matthew D

    2016-06-01

    Prediction of male fertility is an often sought-after endeavor for many species of domestic animals. This review will primarily focus on providing some examples of dependent and independent variables to stimulate thought about the approach and methodology of identifying the most appropriate of those variables to predict bull (bovine) fertility. Although the list of variables will continue to grow with advancements in science, the principles behind making predictions will likely not change significantly. The basic principle of prediction requires identifying a dependent variable that is an estimate of fertility and an independent variable or variables that may be useful in predicting the fertility estimate. Fertility estimates vary in which parts of the process leading to conception that they infer about and the amount of variation that influences the estimate and the uncertainty thereof. The list of potential independent variables can be divided into competence of sperm based on their performance in bioassays or direct measurement of sperm attributes. A good prediction will use a sample population of bulls that is representative of the population to which an inference will be made. Both dependent and independent variables should have a dynamic range in their values. Careful selection of independent variables includes reasonable measurement repeatability and minimal correlation among variables. Proper estimation and having an appreciation of the degree of uncertainty of dependent and independent variables are crucial for using predictions to make decisions regarding bull fertility. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Constraint Programming versus Mathematical Programming

    DEFF Research Database (Denmark)

    Hansen, Jesper

    2003-01-01

    Constraint Logic Programming (CLP) is a relatively new technique from the 80's with origins in Computer Science and Artificial Intelligence. Lately, much research have been focused on ways of using CLP within the paradigm of Operations Research (OR) and vice versa. The purpose of this paper...

  13. A Program to Teach Programming.

    Science.gov (United States)

    Fenichel, Robert R.; And Others

    1969-01-01

    The TEACH system was developed to provide inexpensive, effective, virtually instructorless instruction in programing. The TEACH system employed an interactive language, UNCL. Two full sections of the TEACH course were taught. The results of this experience suggested ways in which the research and development effort on the system should be…

  14. Program Director Participation in a Leadership and Management Skills Fellowship and Characteristics of Program Quality.

    Science.gov (United States)

    Carek, Peter J; Mims, Lisa D; Conry, Colleen M; Maxwell, Lisa; Greenwood, Vicki; Pugno, Perry A

    2015-01-01

    The association between a residency program director completing a leadership and management skills fellowship and characteristics of quality and innovation of his/her residency program has not been studied. Therefore, the aim of this study is to examine the association between a residency program director's completion of a specific fellowship addressing these skills (National Institute for Program Director Development or NIPDD) and characteristics of quality and innovation of the program they direct. Using information from the American Academy of Family Physicians (AAFP), National Resident Matching Program (NRMP) and FREIDA® program characteristics were obtained. Descriptive statistics were used to summarize the data. The relationship between programs with a NIPDD graduate as director and program quality measures and indicators of innovation was analyzed using both chi square and logistic regression. Initial analyses showed significant associations between the NIPDD graduate status of a program director and regional location, mean years of program director tenure, and the program's 5-year aggregate ABFM board pass rate from 2007--2011. After grouping the programs into tertiles, the regression model showed significant positive associations with programs offering international experiences and being a NIPDD graduate. Program director participation in a fellowship addressing leadership and management skills (ie, NIPDD) was found to be associated with higher pass rates of new graduates on a Board certification examination and predictive of programs being in the upper tertile of programs in terms of Board pass rates.

  15. Bootstrap prediction and Bayesian prediction under misspecified models

    OpenAIRE

    Fushiki, Tadayoshi

    2005-01-01

    We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...

  16. Prediction ranges. Annual review

    Energy Technology Data Exchange (ETDEWEB)

    Parker, J.C.; Tharp, W.H.; Spiro, P.S.; Keng, K.; Angastiniotis, M.; Hachey, L.T.

    1988-01-01

    Prediction ranges equip the planner with one more tool for improved assessment of the outcome of a course of action. One of their major uses is in financial evaluations, where corporate policy requires the performance of uncertainty analysis for large projects. This report gives an overview of the uses of prediction ranges, with examples; and risks and uncertainties in growth, inflation, and interest and exchange rates. Prediction ranges and standard deviations of 80% and 50% probability are given for various economic indicators in Ontario, Canada, and the USA, as well as for foreign exchange rates and Ontario Hydro interest rates. An explanatory note on probability is also included. 23 tabs.

  17. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  18. Protein Sorting Prediction

    DEFF Research Database (Denmark)

    Nielsen, Henrik

    2017-01-01

    and drawbacks of each of these approaches is described through many examples of methods that predict secretion, integration into membranes, or subcellular locations in general. The aim of this chapter is to provide a user-level introduction to the field with a minimum of computational theory.......Many computational methods are available for predicting protein sorting in bacteria. When comparing them, it is important to know that they can be grouped into three fundamentally different approaches: signal-based, global-property-based and homology-based prediction. In this chapter, the strengths...

  19. 'Red Flag' Predictions

    DEFF Research Database (Denmark)

    Hallin, Carina Antonia; Andersen, Torben Juul; Tveterås, Sigbjørn

    -generation prediction markets and outline its unique features as a third-generation prediction market. It is argued that frontline employees gain deep insights when they execute operational activities on an ongoing basis in the organization. The experiential learning from close interaction with internal and external......This conceptual article introduces a new way to predict firm performance based on aggregation of sensing among frontline employees about changes in operational capabilities to update strategic action plans and generate innovations. We frame the approach in the context of first- and second...

  20. Towards Predictive Association Theories

    DEFF Research Database (Denmark)

    Kontogeorgis, Georgios; Tsivintzelis, Ioannis; Michelsen, Michael Locht

    2011-01-01

    Association equations of state like SAFT, CPA and NRHB have been previously applied to many complex mixtures. In this work we focus on two of these models, the CPA and the NRHB equations of state and the emphasis is on the analysis of their predictive capabilities for a wide range of applications....... We use the term predictive in two situations: (i) with no use of binary interaction parameters, and (ii) multicomponent calculations using binary interaction parameters based solely on binary data. It is shown that the CPA equation of state can satisfactorily predict CO2–water–glycols–alkanes VLE...

  1. Prediction of intermetallic compounds

    International Nuclear Information System (INIS)

    Burkhanov, Gennady S; Kiselyova, N N

    2009-01-01

    The problems of predicting not yet synthesized intermetallic compounds are discussed. It is noted that the use of classical physicochemical analysis in the study of multicomponent metallic systems is faced with the complexity of presenting multidimensional phase diagrams. One way of predicting new intermetallics with specified properties is the use of modern processing technology with application of teaching of image recognition by the computer. The algorithms used most often in these methods are briefly considered and the efficiency of their use for predicting new compounds is demonstrated.

  2. Linear programming

    CERN Document Server

    Karloff, Howard

    1991-01-01

    To this reviewer’s knowledge, this is the first book accessible to the upper division undergraduate or beginning graduate student that surveys linear programming from the Simplex Method…via the Ellipsoid algorithm to Karmarkar’s algorithm. Moreover, its point of view is algorithmic and thus it provides both a history and a case history of work in complexity theory. The presentation is admirable; Karloff's style is informal (even humorous at times) without sacrificing anything necessary for understanding. Diagrams (including horizontal brackets that group terms) aid in providing clarity. The end-of-chapter notes are helpful...Recommended highly for acquisition, since it is not only a textbook, but can also be used for independent reading and study. —Choice Reviews The reader will be well served by reading the monograph from cover to cover. The author succeeds in providing a concise, readable, understandable introduction to modern linear programming. —Mathematics of Computing This is a textbook intend...

  3. Program of telluric lines monitoring

    Directory of Open Access Journals (Sweden)

    Vince I.

    2006-01-01

    Full Text Available A new observational program of telluric lines monitoring was introduced at Belgrade Astronomical Observatory. The ultimate goal of this program is to investigate the properties of Earth’s atmosphere through modeling the observed profiles of telluric lines. The program is intend to observe infrared molecular oxygen lines that were selected according to spectral sensitivity of the available CCD camera. In this paper we give the initial and the final selection criteria for spectral lines included in the program the description of equipment and procedures used for observations and reduction, a review of preliminary observational results with the estimated precision, and a short discussion on the comparison of the theoretical predictions and the measurements.

  4. Steam generator tube integrity program

    International Nuclear Information System (INIS)

    Dierks, D.R.; Shack, W.J.; Muscara, J.

    1996-01-01

    A new research program on steam generator tubing degradation is being sponsored by the U.S. Nuclear Regulatory Commission (NRC) at Argonne National Laboratory. This program is intended to support a performance-based steam generator tube integrity rule. Critical areas addressed by the program include evaluation of the processes used for the in-service inspection of steam generator tubes and recommendations for improving the reliability and accuracy of inspections; validation and improvement of correlations for evaluating integrity and leakage of degraded steam generator tubes, and validation and improvement of correlations and models for predicting degradation in steam generator tubes as aging occurs. The studies will focus on mill-annealed Alloy 600 tubing, however, tests will also be performed on replacement materials such as thermally-treated Alloy 600 or 690. An overview of the technical work planned for the program is given

  5. Program summary

    International Nuclear Information System (INIS)

    1982-07-01

    The operating, construction, and development activities of the Department of Energy in the areas of uranium enrichment are described. The DOE supplies the enrichment service through toll enrichment contracts with foreign and domestic utilities by enriching uranium supplied by the utility to the desired U-235 level. This role will continue well into the next century. In addition it provides enriched uranium for US Government needs and for R and D purposes. At the present time, almost all the world's capacity to produce enriched uranium uses the gaseous diffusion process. The United States built the first gaseous diffusion plant during World War II. Later this plant was expanded and two additional plants were built. There is presently a $1.5 billion improvement and uprating program near completion which will improve the plant efficiency and increase the total capacity of the three plants by 60 percent to 27.3 million SWU per year. The Administration's energy message in 1977 provided for a further expansion of this capacity by using gas centrifuge technology. The new gas centrifuge plant is being built near the existing GDP near Portsmouth, Ohio. The normal capacity of an 8 building process plant will be 13.2 million SWU per year. The first 2.2 million SWU of capacity is scheduled to be available in 1989. The remaining capacity will be added as needed to meet demand and the overall goal of the program. The goal of the Uranium Enrichment Program is to meet domestic, foreign, and US Government requirements for uranium enrichment services in an economical, reliable, safe and environmentally acceptable manner. To ensure accomplishment of this goal, the overall program is broken down into three areas of implementation; Enrichment Operations; Capacity Upgrading Operations; and Business Operations

  6. Robot Programming.

    Science.gov (United States)

    1982-12-01

    Paris, France, June, 1982, 519-530. Latoinbe, J. C. "Equipe Intelligence Artificielle et Robotique: Etat d’avancement des recherches," Laboratoire...8217AD-A127 233 ROBOT PROGRRMMING(U) MASSACHUSETTS INST OFGTECHi/ CAMBRIDGE ARTIFICIAL INTELLIGENCE LAB T LOZANO-PEREZ UNCLASSIFIED DC8 AI-9 N884...NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK Artificial Intelligence Laboratory AREA I WORK UNIT NUMBERS ,. 545 Technology Square Cambridge

  7. Micro Programming

    OpenAIRE

    Spanjersberg , Herman

    2012-01-01

    International audience; In the 1970s a need arose to perform special arithmetic operations on minicomputers much more quickly than had been possible in the past. This paper tells the story of why micro programming was needed for special arithmetic operations on mini computers in the 1970s and how it was implemented. The paper tells how the laboratory in which the first experiment took place had a PDP-9 minicomputer from Digital Equipment Corporation and how the author, with several colleagues...

  8. Choreographic Programming

    OpenAIRE

    Montesi, Fabrizio

    2014-01-01

    Choreographies are descriptions of distributed systems where the developer gives a global view of how messages are exchanged by endpoint nodes (endpoints for short), instead of separately defining the behaviour of each endpoint. They have a significant impact on the quality of software, as they offer a concise view of the message flows enacted by a system. For this reason, in the last decade choreographies have been used in the development of programming languages, giving rise to a programmin...

  9. Filtering and prediction

    CERN Document Server

    Fristedt, B; Krylov, N

    2007-01-01

    Filtering and prediction is about observing moving objects when the observations are corrupted by random errors. The main focus is then on filtering out the errors and extracting from the observations the most precise information about the object, which itself may or may not be moving in a somewhat random fashion. Next comes the prediction step where, using information about the past behavior of the object, one tries to predict its future path. The first three chapters of the book deal with discrete probability spaces, random variables, conditioning, Markov chains, and filtering of discrete Markov chains. The next three chapters deal with the more sophisticated notions of conditioning in nondiscrete situations, filtering of continuous-space Markov chains, and of Wiener process. Filtering and prediction of stationary sequences is discussed in the last two chapters. The authors believe that they have succeeded in presenting necessary ideas in an elementary manner without sacrificing the rigor too much. Such rig...

  10. CMAQ predicted concentration files

    Data.gov (United States)

    U.S. Environmental Protection Agency — CMAQ predicted ozone. This dataset is associated with the following publication: Gantt, B., G. Sarwar, J. Xing, H. Simon, D. Schwede, B. Hutzell, R. Mathur, and A....

  11. Methane prediction in collieries

    CSIR Research Space (South Africa)

    Creedy, DP

    1999-06-01

    Full Text Available The primary aim of the project was to assess the current status of research on methane emission prediction for collieries in South Africa in comparison with methods used and advances achieved elsewhere in the world....

  12. Climate Prediction Center - Outlooks

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Outreach > Publications > Climate Diagnostics Bulletin Climate Diagnostics Bulletin - Tropics Climate Diagnostics Bulletin - Forecast Climate Diagnostics

  13. CMAQ predicted concentration files

    Data.gov (United States)

    U.S. Environmental Protection Agency — model predicted concentrations. This dataset is associated with the following publication: Muñiz-Unamunzaga, M., R. Borge, G. Sarwar, B. Gantt, D. de la Paz, C....

  14. Comparing Spatial Predictions

    KAUST Repository

    Hering, Amanda S.; Genton, Marc G.

    2011-01-01

    Under a general loss function, we develop a hypothesis test to determine whether a significant difference in the spatial predictions produced by two competing models exists on average across the entire spatial domain of interest. The null hypothesis

  15. Genomic prediction using subsampling

    OpenAIRE

    Xavier, Alencar; Xu, Shizhong; Muir, William; Rainey, Katy Martin

    2017-01-01

    Background Genome-wide assisted selection is a critical tool for the?genetic improvement of plants and animals. Whole-genome regression models in Bayesian framework represent the main family of prediction methods. Fitting such models with a large number of observations involves a prohibitive computational burden. We propose the use of subsampling bootstrap Markov chain in genomic prediction. Such method consists of fitting whole-genome regression models by subsampling observations in each rou...

  16. Predicting Online Purchasing Behavior

    OpenAIRE

    W.R BUCKINX; D. VAN DEN POEL

    2003-01-01

    This empirical study investigates the contribution of different types of predictors to the purchasing behaviour at an online store. We use logit modelling to predict whether or not a purchase is made during the next visit to the website using both forward and backward variable-selection techniques, as well as Furnival and Wilson’s global score search algorithm to find the best subset of predictors. We contribute to the literature by using variables from four different categories in predicting...

  17. Empirical Flutter Prediction Method.

    Science.gov (United States)

    1988-03-05

    been used in this way to discover species or subspecies of animals, and to discover different types of voter or comsumer requiring different persuasions...respect to behavior or performance or response variables. Once this were done, corresponding clusters might be sought among descriptive or predictive or...jump in a response. The first sort of usage does not apply to the flutter prediction problem. Here the types of behavior are the different kinds of

  18. Stuck pipe prediction

    KAUST Repository

    Alzahrani, Majed

    2016-03-10

    Disclosed are various embodiments for a prediction application to predict a stuck pipe. A linear regression model is generated from hook load readings at corresponding bit depths. A current hook load reading at a current bit depth is compared with a normal hook load reading from the linear regression model. A current hook load greater than a normal hook load for a given bit depth indicates the likelihood of a stuck pipe.

  19. Stuck pipe prediction

    KAUST Repository

    Alzahrani, Majed; Alsolami, Fawaz; Chikalov, Igor; Algharbi, Salem; Aboudi, Faisal; Khudiri, Musab

    2016-01-01

    Disclosed are various embodiments for a prediction application to predict a stuck pipe. A linear regression model is generated from hook load readings at corresponding bit depths. A current hook load reading at a current bit depth is compared with a normal hook load reading from the linear regression model. A current hook load greater than a normal hook load for a given bit depth indicates the likelihood of a stuck pipe.

  20. Genomic prediction using subsampling.

    Science.gov (United States)

    Xavier, Alencar; Xu, Shizhong; Muir, William; Rainey, Katy Martin

    2017-03-24

    Genome-wide assisted selection is a critical tool for the genetic improvement of plants and animals. Whole-genome regression models in Bayesian framework represent the main family of prediction methods. Fitting such models with a large number of observations involves a prohibitive computational burden. We propose the use of subsampling bootstrap Markov chain in genomic prediction. Such method consists of fitting whole-genome regression models by subsampling observations in each round of a Markov Chain Monte Carlo. We evaluated the effect of subsampling bootstrap on prediction and computational parameters. Across datasets, we observed an optimal subsampling proportion of observations around 50% with replacement, and around 33% without replacement. Subsampling provided a substantial decrease in computation time, reducing the time to fit the model by half. On average, losses on predictive properties imposed by subsampling were negligible, usually below 1%. For each dataset, an optimal subsampling point that improves prediction properties was observed, but the improvements were also negligible. Combining subsampling with Gibbs sampling is an interesting ensemble algorithm. The investigation indicates that the subsampling bootstrap Markov chain algorithm substantially reduces computational burden associated with model fitting, and it may slightly enhance prediction properties.

  1. Deep Visual Attention Prediction

    Science.gov (United States)

    Wang, Wenguan; Shen, Jianbing

    2018-05-01

    In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

  2. Predictive analytics can support the ACO model.

    Science.gov (United States)

    Bradley, Paul

    2012-04-01

    Predictive analytics can be used to rapidly spot hard-to-identify opportunities to better manage care--a key tool in accountable care. When considering analytics models, healthcare providers should: Make value-based care a priority and act on information from analytics models. Create a road map that includes achievable steps, rather than major endeavors. Set long-term expectations and recognize that the effectiveness of an analytics program takes time, unlike revenue cycle initiatives that may show a quick return.

  3. SUCO program

    International Nuclear Information System (INIS)

    Knebel, J.U.

    1995-01-01

    The SUCO program is a three-step series of scaled model experiments investigating the optional sump cooling concept of the EPR. This concept is entirely based on passive safety features. This report presents the basic physical phenomena and scaling criteria of decay heat removal from a large coolant pool by single-phase and two-phase natural circulation flow. The physical significance of the dimensionless similarity groups derived is evaluated. The report gives first measurement results of the 1:20 linearly scaled plane two-dimensional SUCOS-2D test facility. The real height SUCOT test facility that is in its building up phase is presented. (orig.)

  4. Programming Pig

    CERN Document Server

    Gates, Alan

    2011-01-01

    This guide is an ideal learning tool and reference for Apache Pig, the open source engine for executing parallel data flows on Hadoop. With Pig, you can batch-process data without having to create a full-fledged application-making it easy for you to experiment with new datasets. Programming Pig introduces new users to Pig, and provides experienced users with comprehensive coverage on key features such as the Pig Latin scripting language, the Grunt shell, and User Defined Functions (UDFs) for extending Pig. If you need to analyze terabytes of data, this book shows you how to do it efficiently

  5. Predictive Methods of Pople

    Indian Academy of Sciences (India)

    Chemistry for their pioneering contri butions to the development of computational methods in quantum chemistry and density functional theory .... program of Pop Ie for ab-initio electronic structure calculation of molecules. This ab-initio MO ...

  6. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...... the possibilities w.r.t. different numerical weather predictions actually available to the project....

  7. Energy prediction using spatiotemporal pattern networks

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun; Henze, Gregor P.; Sarkar, Soumik

    2017-11-01

    This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated by the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.

  8. Application of 'SPICE' to predict temperature distribution in heat pipes

    Energy Technology Data Exchange (ETDEWEB)

    Li, H M; Liu, Y; Damodaran, M [Nanyang Technological Univ., Singapore (SG). School of Mechanical and Production Engineering

    1991-11-01

    This article presents a new alternative approach to predict temperature distribution in heat pipes. In this method, temperature distribution in a heat pipe, modelled as an analogous electrical circuit, is predicted by applying SPICE, a general-purpose circuit simulation program. SPICE is used to simulate electrical circuit designs before the prototype is assembled. Useful predictions are obtained for heat pipes with and without adiabatic sections and for heat pipes with various evaporator and condenser lengths. Comparison of the predicted results with experiments demonstrates fairly good agreement. It is also shown how interdisciplinary developments could be used appropriately. (author).

  9. Role of peptide processing predictions in T cell epitope identification : contribution of different prediction programs

    NARCIS (Netherlands)

    Calis, Jorg J A; Reinink, Peter; Keller, Christin; Kloetzel, Peter M; Kesmir, Can

    2015-01-01

    Proteolysis is the general term to describe the process of protein degradation into peptides. Proteasomes are the main actors in cellular proteolysis, and their activity can be measured in in vitro digestion experiments. However, in vivo proteolysis can be different than what is measured in these

  10. Transionospheric propagation predictions

    Science.gov (United States)

    Klobucher, J. A.; Basu, S.; Basu, S.; Bernhardt, P. A.; Davies, K.; Donatelli, D. E.; Fremouw, E. J.; Goodman, J. M.; Hartmann, G. K.; Leitinger, R.

    1979-01-01

    The current status and future prospects of the capability to make transionospheric propagation predictions are addressed, highlighting the effects of the ionized media, which dominate for frequencies below 1 to 3 GHz, depending upon the state of the ionosphere and the elevation angle through the Earth-space path. The primary concerns are the predictions of time delay of signal modulation (group path delay) and of radio wave scintillation. Progress in these areas is strongly tied to knowledge of variable structures in the ionosphere ranging from the large scale (thousands of kilometers in horizontal extent) to the fine scale (kilometer size). Ionospheric variability and the relative importance of various mechanisms responsible for the time histories observed in total electron content (TEC), proportional to signal group delay, and in irregularity formation are discussed in terms of capability to make both short and long term predictions. The data base upon which predictions are made is examined for its adequacy, and the prospects for prediction improvements by more theoretical studies as well as by increasing the available statistical data base are examined.

  11. Predictable grammatical constructions

    DEFF Research Database (Denmark)

    Lucas, Sandra

    2015-01-01

    My aim in this paper is to provide evidence from diachronic linguistics for the view that some predictable units are entrenched in grammar and consequently in human cognition, in a way that makes them functionally and structurally equal to nonpredictable grammatical units, suggesting that these p......My aim in this paper is to provide evidence from diachronic linguistics for the view that some predictable units are entrenched in grammar and consequently in human cognition, in a way that makes them functionally and structurally equal to nonpredictable grammatical units, suggesting...... that these predictable units should be considered grammatical constructions on a par with the nonpredictable constructions. Frequency has usually been seen as the only possible argument speaking in favor of viewing some formally and semantically fully predictable units as grammatical constructions. However, this paper...... semantically and formally predictable. Despite this difference, [méllo INF], like the other future periphrases, seems to be highly entrenched in the cognition (and grammar) of Early Medieval Greek language users, and consequently a grammatical construction. The syntactic evidence speaking in favor of [méllo...

  12. FFTF-cycle 10 program and future plan

    Science.gov (United States)

    Kohyama, Akira

    1988-04-01

    Brief outlines are provided of the FFTF cycle 10 program and future plans in consideration. The primary objective of the Japan-US collaboration program is to enable predictions of material behavior in MFRs to be made from data obtained in other irradiation environments. Major program goals are outlined.

  13. Geothermal Technologies Program Overview - Peer Review Program

    Energy Technology Data Exchange (ETDEWEB)

    Milliken, JoAnn [Office of Energy Efficiency and Renewable Energy (EERE), Washington, DC (United States)

    2011-06-06

    This Geothermal Technologies Program presentation was delivered on June 6, 2011 at a Program Peer Review meeting. It contains annual budget, Recovery Act, funding opportunities, upcoming program activities, and more.

  14. Essays on Earnings Predictability

    DEFF Research Database (Denmark)

    Bruun, Mark

    This dissertation addresses the prediction of corporate earnings. The thesis aims to examine whether the degree of precision in earnings forecasts can be increased by basing them on historical financial ratios. Furthermore, the intent of the dissertation is to analyze whether accounting standards...... forecasts are not more accurate than the simpler forecasts based on a historical timeseries of earnings. Secondly, the dissertation shows how accounting standards affect analysts’ earnings predictions. Accounting conservatism contributes to a more volatile earnings process, which lowers the accuracy...... of analysts’ earnings forecasts. Furthermore, the dissertation shows how the stock market’s reaction to the disclosure of information about corporate earnings depends on how well corporate earnings can be predicted. The dissertation indicates that the stock market’s reaction to the disclosure of earnings...

  15. Predicting Ideological Prejudice.

    Science.gov (United States)

    Brandt, Mark J

    2017-06-01

    A major shortcoming of current models of ideological prejudice is that although they can anticipate the direction of the association between participants' ideology and their prejudice against a range of target groups, they cannot predict the size of this association. I developed and tested models that can make specific size predictions for this association. A quantitative model that used the perceived ideology of the target group as the primary predictor of the ideology-prejudice relationship was developed with a representative sample of Americans ( N = 4,940) and tested against models using the perceived status of and choice to belong to the target group as predictors. In four studies (total N = 2,093), ideology-prejudice associations were estimated, and these observed estimates were compared with the models' predictions. The model that was based only on perceived ideology was the most parsimonious with the smallest errors.

  16. Inverse and Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Syracuse, Ellen Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-09-27

    The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an even greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.

  17. Tide Predictions, California, 2014, NOAA

    Data.gov (United States)

    U.S. Environmental Protection Agency — The predictions from the web based NOAA Tide Predictions are based upon the latest information available as of the date of the user's request. Tide predictions...

  18. Predicting tile drainage discharge

    DEFF Research Database (Denmark)

    Iversen, Bo Vangsø; Kjærgaard, Charlotte; Petersen, Rasmus Jes

    used in the analysis. For the dynamic modelling, a simple linear reservoir model was used where different outlets in the model represented tile drain as well as groundwater discharge outputs. This modelling was based on daily measured tile drain discharge values. The statistical predictive model...... was based on a polynomial regression predicting yearly tile drain discharge values using site specific parameters such as soil type, catchment topography, etc. as predictors. Values of calibrated model parameters from the dynamic modelling were compared to the same site specific parameter as used...

  19. Linguistic Structure Prediction

    CERN Document Server

    Smith, Noah A

    2011-01-01

    A major part of natural language processing now depends on the use of text data to build linguistic analyzers. We consider statistical, computational approaches to modeling linguistic structure. We seek to unify across many approaches and many kinds of linguistic structures. Assuming a basic understanding of natural language processing and/or machine learning, we seek to bridge the gap between the two fields. Approaches to decoding (i.e., carrying out linguistic structure prediction) and supervised and unsupervised learning of models that predict discrete structures as outputs are the focus. W

  20. Predicting Anthracycline Benefit

    DEFF Research Database (Denmark)

    Bartlett, John M S; McConkey, Christopher C; Munro, Alison F

    2015-01-01

    PURPOSE: Evidence supporting the clinical utility of predictive biomarkers of anthracycline activity is weak, with a recent meta-analysis failing to provide strong evidence for either HER2 or TOP2A. Having previously shown that duplication of chromosome 17 pericentromeric alpha satellite as measu......PURPOSE: Evidence supporting the clinical utility of predictive biomarkers of anthracycline activity is weak, with a recent meta-analysis failing to provide strong evidence for either HER2 or TOP2A. Having previously shown that duplication of chromosome 17 pericentromeric alpha satellite...

  1. Prediction of Antibody Epitopes

    DEFF Research Database (Denmark)

    Nielsen, Morten; Marcatili, Paolo

    2015-01-01

    Antibodies recognize their cognate antigens in a precise and effective way. In order to do so, they target regions of the antigenic molecules that have specific features such as large exposed areas, presence of charged or polar atoms, specific secondary structure elements, and lack of similarity...... to self-proteins. Given the sequence or the structure of a protein of interest, several methods exploit such features to predict the residues that are more likely to be recognized by an immunoglobulin.Here, we present two methods (BepiPred and DiscoTope) to predict linear and discontinuous antibody...

  2. Basis of predictive mycology.

    Science.gov (United States)

    Dantigny, Philippe; Guilmart, Audrey; Bensoussan, Maurice

    2005-04-15

    For over 20 years, predictive microbiology focused on food-pathogenic bacteria. Few studies concerned modelling fungal development. On one hand, most of food mycologists are not familiar with modelling techniques; on the other hand, people involved in modelling are developing tools dedicated to bacteria. Therefore, there is a tendency to extend the use of models that were developed for bacteria to moulds. However, some mould specificities should be taken into account. The use of specific models for predicting germination and growth of fungi was advocated previously []. This paper provides a short review of fungal modelling studies.

  3. Dopamine reward prediction error coding

    OpenAIRE

    Schultz, Wolfram

    2016-01-01

    Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards?an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less...

  4. TNS Program

    International Nuclear Information System (INIS)

    Anon.

    1979-01-01

    The fusion program plan is briefly reviewed and the role of the prototype experimental power reactor, thought of as The Next Step (TNS), is discussed. The required device capabilities and basic reactor concepts for a TNS fusion electric plant are given. A detailed discussion of the physics considerations for the Power Generating Fusion Reactor (PGFR), including plasma heating, MHD equilibrium and stability, burn control resulting from toroidal field ripple, fueling, and boundary effects, is presented. Engineering considerations of the major PGFR systems, as well as diagnostics, instrumentation, control, and programmatic issues are also considered in detail. It is concluded that TNS design studies have established the existence of a technical basis for constructing a long pulse, D-T burning tokamak to be operational prior to 1990

  5. Telemedicine Program

    Science.gov (United States)

    1996-01-01

    Since the 1970s, NASA has been involved in the research and demonstration of telemedicine for its potential in the care of astronauts in flight and Earth-bound applications. A combination of NASA funding, expertise and off-the-shelf computer and networking systems made telemedicine possible for a medically underserved hospital in Texas. Through two-way audio/video relay, the program links pediatric oncology specialists at the University of Texas Health Science Center in San Antonio to South Texas Hospital in Harlingen, providing easier access and better care to children with cancer. Additionally, the hospital is receiving teleclinics on pediatric oncology nursing, family counseling and tuberculosis treatment. VTEL Corporation, Sprint, and the Healthcare Open Systems and Trials Consortium also contributed staff and hardware.

  6. Russian programs

    International Nuclear Information System (INIS)

    Heywood, A.

    1993-01-01

    Lawrence Livermore National Laboratory (LLNL) initiated several projects with the Boreskov Institute of Catalysis to develop innovative process technologies for the treatment of mixed and hazardous wastes containing a high percentage of organic material. Each of these processes involves the use of catalysts for oxidation (or initial reduction) of the hazardous organic constituents. Because of their commitment to a national mixed waste treatment program, both the Department of Energy/Office of Environmental Management (DOE/EM) and LLNL Environmental Restoration and Waste Management/Applied Technologies (ER-WM/AT) programs have a considerable interest in innovative/alternative flowsheets for organic mixed waste treatment. Selective Catalytic Reduction (SCR) using ammonia as a reducing agent is current a preferred method of treating NO x in off-gases. The advantages of SCR over methods, such as wet scrubbing, include compact design, low maintenance, and the absence of gas cooling requirements and secondary wastes. Any further improvements in catalyst design would lower costs, improve their resistance to poisons, expand their ability to promote oxidation/reduction in mixtures such as NO x /CO, and increase their mechanical strength. An additional requirement of catalysts to be used in California is that the catalyst formulations must meet the California Land Ban disposal restrictions. A monitoring network is needed in Russia to coordinate the environmental monitoring activities of government (including military establishments and facilities) and commercial entities. The network shall incorporate existing as well as proposed monitoring stations. It will comply with all toxic substance control regulations and include analyses for all priority radiochemical and chemical substances. A database compatible with the Environmental Technologies for Remedial Actions Data Exchange (EnviroTRADE) database will ultimately be compiled

  7. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  8. Steering smog prediction

    NARCIS (Netherlands)

    R. van Liere (Robert); J.J. van Wijk (Jack)

    1997-01-01

    textabstractThe use of computational steering for smog prediction is described. This application is representative for many underlying issues found in steering high performance applications: high computing times, large data sets, and many different input parameters. After a short description of the

  9. Predicting Sustainable Work Behavior

    DEFF Research Database (Denmark)

    Hald, Kim Sundtoft

    2013-01-01

    Sustainable work behavior is an important issue for operations managers – it has implications for most outcomes of OM. This research explores the antecedents of sustainable work behavior. It revisits and extends the sociotechnical model developed by Brown et al. (2000) on predicting safe behavior...

  10. Prediction method abstracts

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1994-12-31

    This conference was held December 4--8, 1994 in Asilomar, California. The purpose of this meeting was to provide a forum for exchange of state-of-the-art information concerning the prediction of protein structure. Attention if focused on the following: comparative modeling; sequence to fold assignment; and ab initio folding.

  11. Predicting Intrinsic Motivation

    Science.gov (United States)

    Martens, Rob; Kirschner, Paul A.

    2004-01-01

    Intrinsic motivation can be predicted from participants' perceptions of the social environment and the task environment (Ryan & Deci, 2000)in terms of control, relatedness and competence. To determine the degree of independence of these factors 251 students in higher vocational education (physiotherapy and hotel management) indicated the…

  12. Predicting visibility of aircraft.

    Directory of Open Access Journals (Sweden)

    Andrew Watson

    Full Text Available Visual detection of aircraft by human observers is an important element of aviation safety. To assess and ensure safety, it would be useful to be able to be able to predict the visibility, to a human observer, of an aircraft of specified size, shape, distance, and coloration. Examples include assuring safe separation among aircraft and between aircraft and unmanned vehicles, design of airport control towers, and efforts to enhance or suppress the visibility of military and rescue vehicles. We have recently developed a simple metric of pattern visibility, the Spatial Standard Observer (SSO. In this report we examine whether the SSO can predict visibility of simulated aircraft images. We constructed a set of aircraft images from three-dimensional computer graphic models, and measured the luminance contrast threshold for each image from three human observers. The data were well predicted by the SSO. Finally, we show how to use the SSO to predict visibility range for aircraft of arbitrary size, shape, distance, and coloration.

  13. Climate Prediction Center

    Science.gov (United States)

    Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Organization Enter Search Term(s): Search Search the CPC Go NCEP Quarterly Newsletter Climate Highlights U.S Climate-Weather El Niño/La Niña MJO Blocking AAO, AO, NAO, PNA Climatology Global Monsoons Expert

  14. Predicting Commissary Store Success

    Science.gov (United States)

    2014-12-01

    stores or if it is possible to predict that success. Multiple studies of private commercial grocery consumer preferences , habits and demographics have...appropriate number of competitors due to the nature of international cultures and consumer preferences . 2. Missing Data Four of the remaining stores

  15. Predicting Job Satisfaction.

    Science.gov (United States)

    Blai, Boris, Jr.

    Psychological theories about human motivation and accommodation to environment can be used to achieve a better understanding of the human factors that function in the work environment. Maslow's theory of human motivational behavior provided a theoretical framework for an empirically-derived method to predict job satisfaction and explore the…

  16. Ocean Prediction Center

    Science.gov (United States)

    Social Media Facebook Twitter YouTube Search Search For Go NWS All NOAA Weather Analysis & Forecasts of Commerce Ocean Prediction Center National Oceanic and Atmospheric Administration Analysis & Unified Surface Analysis Ocean Ocean Products Ice & Icebergs NIC Ice Products NAIS Iceberg Analysis

  17. Predicting Reasoning from Memory

    Science.gov (United States)

    Heit, Evan; Hayes, Brett K.

    2011-01-01

    In an effort to assess the relations between reasoning and memory, in 8 experiments, the authors examined how well responses on an inductive reasoning task are predicted from responses on a recognition memory task for the same picture stimuli. Across several experimental manipulations, such as varying study time, presentation frequency, and the…

  18. Predicting coronary heart disease

    DEFF Research Database (Denmark)

    Sillesen, Henrik; Fuster, Valentin

    2012-01-01

    Atherosclerosis is the leading cause of death and disabling disease. Whereas risk factors are well known and constitute therapeutic targets, they are not useful for prediction of risk of future myocardial infarction, stroke, or death. Therefore, methods to identify atherosclerosis itself have bee...

  19. ANTHROPOMETRIC PREDICTIVE EQUATIONS FOR ...

    African Journals Online (AJOL)

    Keywords: Anthropometry, Predictive Equations, Percentage Body Fat, Nigerian Women, Bioelectric Impedance ... such as Asians and Indians (Pranav et al., 2009), ... size (n) of at least 3o is adjudged as sufficient for the ..... of people, gender and age (Vogel eta/., 1984). .... Fish Sold at Ile-Ife Main Market, South West Nigeria.

  20. Predicting Pilot Retention

    Science.gov (United States)

    2012-06-15

    forever… Gig ‘Em! Dale W. Stanley III vii Table of Contents Page Acknowledgments...over the last 20 years. Airbus predicted that these trends would continue as emerging economies , especially in Asia, were creating a fast growing...US economy , pay differential and hiring by the major airlines contributed most to the decision to separate from the Air Force (Fullerton, 2003: 354

  1. Predicting ideological prejudice

    NARCIS (Netherlands)

    Brandt, M.J.

    2018-01-01

    A major shortcoming of current models of ideological prejudice is that although they can anticipate the direction of the association between participants’ ideology and their prejudice against a range of target groups, they cannot predict the size of this association. I developed and tested models

  2. Application of monitoring techniques of operational parameters for the implementation of preventive and predictive maintenance programs to gas turbines; Aplicacion de tecnicas de monitoreo de parametros operacionales para la implantacion de programas de mantenimiento predictivo y preventivo en turbinas de gas

    Energy Technology Data Exchange (ETDEWEB)

    Gutierrez Villareal, Julio Cesar

    1998-12-31

    This thesis was made with the purpose to implement a preventive and predictive maintenance program, based on the monitoring parameters techniques that will let us systematize, document and conduct the maintenance activity. The methodology of maintenance describes in this document it has been applied to a gas turbine in the Terminal Maritima Dos Bocas Tabasco, Mexico. Preventive maintenance is based on the periodic inspections of the equipment, the inspection is carried out with a check list in which the idea is to detect problems that will bring an equipment to fail and to repair or adjustment them so as prevent the failure. Nevertheless the possibility that the inspected equipment may be in perfect operating conditions and during conditions and during the inspections the operator might have caused a new damage or problem that will delay the start up. Predictive maintenance is based on techniques that will allow the detection and identification of incipient failures of the equipment. The recommended techniques in this thesis are: Vibration analysis; Non destructive testing and Boroscopy inspection. The contents of each chapter in this thesis is the following: Chapter one describes maintenance programs and strategies, their advantage and disadvantage when there are applied to the continuos operation industries. The procedure and design of maintenance program is presented. Chapter two describe how to manage the resource and materials of maintenance, the inspections techniques applied to the gas turbines, and last but not least; check list for inspections were design as preventive maintenance tools. The following chapter describe the techniques for the predictive maintenance: Chapter three describes some of the capabilities of the vibrations analysis and show the metodology applied for the identifications of the source of vibrations and diagnostic techniques. Chapter four describes some of the techniques for nondestructive test than can be used in gas turbine

  3. [Predictive ocular motor control in Parkinson's disease].

    Science.gov (United States)

    Ying, Li; Liu, Zhen-Guo; Chen, Wei; Gan, Jing; Wang, Wen-An

    2008-02-19

    To investigate the changes of predictive ocular motor function in the patients with Parkinson's disease (PD), and to discuss its clinical value. Videonystagmography (VNG) was used to examine 24 patients with idiopathic Parkinson's disease, 15 males and 9 females, aged 61 +/- 6 (50-69), and 24 sex and age-matched healthy control subjects on random ocular saccade (with the target moving at random intervals to random positions) and predictive ocular saccade (with the 1.25-second light target moving 10 degrees right or left from the center). In the random ocular saccade program, the latency of saccade of the PD patients was 284 ms +/- 58 ms, significantly longer than that of the healthy controls (236 ms +/- 37 ms, P = 0.003). In the predictive ocular saccade pattern, the latency of saccades the PD patients was 150 ms +/- 138 ms, significantly longer than that of the healthy controls (59 ms +/- 102 ms, P = 0.002). The appearance rate of predictive saccades (with the latency of saccade <80 ms) in the PD group was 21%, significantly lower than that in the control group (31%, P = 0.003). There is dysfunction of predictive ocular motor control in the PD patients, and the cognitive function may be impaired at the early stage of PD.

  4. Combat Wound Initiative program.

    Science.gov (United States)

    Stojadinovic, Alexander; Elster, Eric; Potter, Benjamin K; Davis, Thomas A; Tadaki, Doug K; Brown, Trevor S; Ahlers, Stephen; Attinger, Christopher E; Andersen, Romney C; Burris, David; Centeno, Jose; Champion, Hunter; Crumbley, David R; Denobile, John; Duga, Michael; Dunne, James R; Eberhardt, John; Ennis, William J; Forsberg, Jonathan A; Hawksworth, Jason; Helling, Thomas S; Lazarus, Gerald S; Milner, Stephen M; Mullick, Florabel G; Owner, Christopher R; Pasquina, Paul F; Patel, Chirag R; Peoples, George E; Nissan, Aviram; Ring, Michael; Sandberg, Glenn D; Schaden, Wolfgang; Schultz, Gregory S; Scofield, Tom; Shawen, Scott B; Sheppard, Forest R; Stannard, James P; Weina, Peter J; Zenilman, Jonathan M

    2010-07-01

    The Combat Wound Initiative (CWI) program is a collaborative, multidisciplinary, and interservice public-private partnership that provides personalized, state-of-the-art, and complex wound care via targeted clinical and translational research. The CWI uses a bench-to-bedside approach to translational research, including the rapid development of a human extracorporeal shock wave therapy (ESWT) study in complex wounds after establishing the potential efficacy, biologic mechanisms, and safety of this treatment modality in a murine model. Additional clinical trials include the prospective use of clinical data, serum and wound biomarkers, and wound gene expression profiles to predict wound healing/failure and additional clinical patient outcomes following combat-related trauma. These clinical research data are analyzed using machine-based learning algorithms to develop predictive treatment models to guide clinical decision-making. Future CWI directions include additional clinical trials and study centers and the refinement and deployment of our genetically driven, personalized medicine initiative to provide patient-specific care across multiple medical disciplines, with an emphasis on combat casualty care.

  5. Genomic Prediction of Manganese Efficiency in Winter Barley

    Directory of Open Access Journals (Sweden)

    Florian Leplat

    2016-07-01

    Full Text Available Manganese efficiency is a quantitative abiotic stress trait controlled by several genes each with a small effect. Manganese deficiency leads to yield reduction in winter barley ( L.. Breeding new cultivars for this trait remains difficult because of the lack of visual symptoms and the polygenic features of the trait. Hence, Mn efficiency is a potential suitable trait for a genomic selection (GS approach. A collection of 248 winter barley varieties was screened for Mn efficiency using Chlorophyll (Chl fluorescence in six environments prone to induce Mn deficiency. Two models for genomic prediction were implemented to predict future performance and breeding value of untested varieties. Predictions were obtained using multivariate mixed models: best linear unbiased predictor (BLUP and genomic best linear unbiased predictor (G-BLUP. In the first model, predictions were based on the phenotypic evaluation, whereas both phenotypic and genomic marker data were included in the second model. Accuracy of predicting future phenotype, , and accuracy of predicting true breeding values, , were calculated and compared for both models using six cross-validation (CV schemes; these were designed to mimic plant breeding programs. Overall, the CVs showed that prediction accuracies increased when using the G-BLUP model compared with the prediction accuracies using the BLUP model. Furthermore, the accuracies [] of predicting breeding values were more accurate than accuracy of predicting future phenotypes []. The study confirms that genomic data may enhance the prediction accuracy. Moreover it indicates that GS is a suitable breeding approach for quantitative abiotic stress traits.

  6. What do reversible programs compute?

    DEFF Research Database (Denmark)

    Axelsen, Holger Bock; Glück, Robert

    2011-01-01

    Reversible computing is the study of computation models that exhibit both forward and backward determinism. Understanding the fundamental properties of such models is not only relevant for reversible programming, but has also been found important in other fields, e.g., bidirectional model...... transformation, program transformations such as inversion, and general static prediction of program properties. Historically, work on reversible computing has focussed on reversible simulations of irreversible computations. Here, we take the viewpoint that the property of reversibility itself should...... are not strictly classically universal, but that they support another notion of universality; we call this RTM-universality. Thus, even though the RTMs are sub-universal in the classical sense, they are powerful enough as to include a self-interpreter. Lifting this to other computation models, we propose r...

  7. BEHAVE: fire behavior prediction and fuel modeling system-BURN Subsystem, part 1

    Science.gov (United States)

    Patricia L. Andrews

    1986-01-01

    Describes BURN Subsystem, Part 1, the operational fire behavior prediction subsystem of the BEHAVE fire behavior prediction and fuel modeling system. The manual covers operation of the computer program, assumptions of the mathematical models used in the calculations, and application of the predictions.

  8. Prediction-based dynamic load-sharing heuristics

    Science.gov (United States)

    Goswami, Kumar K.; Devarakonda, Murthy; Iyer, Ravishankar K.

    1993-01-01

    The authors present dynamic load-sharing heuristics that use predicted resource requirements of processes to manage workloads in a distributed system. A previously developed statistical pattern-recognition method is employed for resource prediction. While nonprediction-based heuristics depend on a rapidly changing system status, the new heuristics depend on slowly changing program resource usage patterns. Furthermore, prediction-based heuristics can be more effective since they use future requirements rather than just the current system state. Four prediction-based heuristics, two centralized and two distributed, are presented. Using trace driven simulations, they are compared against random scheduling and two effective nonprediction based heuristics. Results show that the prediction-based centralized heuristics achieve up to 30 percent better response times than the nonprediction centralized heuristic, and that the prediction-based distributed heuristics achieve up to 50 percent improvements relative to their nonprediction counterpart.

  9. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... Trauma Programs Trauma Programs About Trauma Programs Violence Prevention BleedingControl.org Trauma Quality Programs National Trauma Data ... Conference Publications and Posters National Trauma System Injury Prevention and Control Quality and Safety Conference Quality and ...

  10. Human Reliability Program Overview

    Energy Technology Data Exchange (ETDEWEB)

    Bodin, Michael

    2012-09-25

    This presentation covers the high points of the Human Reliability Program, including certification/decertification, critical positions, due process, organizational structure, program components, personnel security, an overview of the US DOE reliability program, retirees and academia, and security program integration.

  11. Vehicle Technologies Program Overview

    Energy Technology Data Exchange (ETDEWEB)

    none,

    2006-09-05

    Overview of the Vehicle Technologies Program including external assessment and market view; internal assessment, program history and progress; program justification and federal role; program vision, mission, approach, strategic goals, outputs, and outcomes; and performance goals.

  12. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... Trauma Trauma Programs Trauma Programs About Trauma Programs Violence Prevention BleedingControl.org Trauma Quality Programs National Trauma ... Benefits Current Openings Newsroom Newsroom Newsroom Press Releases Media Resources The FIRST Trial ACS Publications ACS in ...

  13. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... and Safety Conference Participant Use Data File Surgical Risk Calculator Frequently Asked Questions Participant Hub Contact Us ... Trauma Programs Trauma Programs About Trauma Programs Violence Prevention BleedingControl.org Trauma Quality Programs National Trauma Data ...

  14. Practical C++ programming

    National Research Council Canada - National Science Library

    Oualline, Steve

    2003-01-01

    ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 4 6 3 2. The Basics of Program Writing Programs from Conception to Execution Creating a Real Program Getting Help in Unix Getting Help in an IDE Programming...

  15. Functional Python programming

    CERN Document Server

    Lott, Steven

    2015-01-01

    This book is for developers who want to use Python to write programs that lean heavily on functional programming design patterns. You should be comfortable with Python programming, but no knowledge of functional programming paradigms is needed.

  16. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... Membership Directory 2017 Annual Meeting 2016 Annual Meeting Women's Committee Mentorship Program Outside Activities ACS Archives Contact Us Quality Programs Quality Programs Overview About Quality Programs ACS ...

  17. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... Continuous Certification Requirements SSR Login MIPS Resources and Education Quality and Safety Conference Trauma Trauma Programs Trauma Programs About Trauma Programs Violence Prevention BleedingControl.org Trauma Quality Programs National Trauma ...

  18. Ostomy Home Skills Program

    Medline Plus

    Full Text Available ... Membership Directory 2017 Annual Meeting 2016 Annual Meeting Women's Committee Mentorship Program Outside Activities ACS Archives Contact Us Quality Programs Quality Programs Overview About Quality Programs ACS Leadership in Quality ACS Leadership in Quality Setting the ...

  19. Probabilistic Structural Analysis Program

    Science.gov (United States)

    Pai, Shantaram S.; Chamis, Christos C.; Murthy, Pappu L. N.; Stefko, George L.; Riha, David S.; Thacker, Ben H.; Nagpal, Vinod K.; Mital, Subodh K.

    2010-01-01

    NASA/NESSUS 6.2c is a general-purpose, probabilistic analysis program that computes probability of failure and probabilistic sensitivity measures of engineered systems. Because NASA/NESSUS uses highly computationally efficient and accurate analysis techniques, probabilistic solutions can be obtained even for extremely large and complex models. Once the probabilistic response is quantified, the results can be used to support risk-informed decisions regarding reliability for safety-critical and one-of-a-kind systems, as well as for maintaining a level of quality while reducing manufacturing costs for larger-quantity products. NASA/NESSUS has been successfully applied to a diverse range of problems in aerospace, gas turbine engines, biomechanics, pipelines, defense, weaponry, and infrastructure. This program combines state-of-the-art probabilistic algorithms with general-purpose structural analysis and lifting methods to compute the probabilistic response and reliability of engineered structures. Uncertainties in load, material properties, geometry, boundary conditions, and initial conditions can be simulated. The structural analysis methods include non-linear finite-element methods, heat-transfer analysis, polymer/ceramic matrix composite analysis, monolithic (conventional metallic) materials life-prediction methodologies, boundary element methods, and user-written subroutines. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. NASA/NESSUS 6.2c is structured in a modular format with 15 elements.

  20. Programas de alimentação para matrizes pesadas após o pico de postura, com base em modelos para predizer a exigência energética Feeding programs for broiler breeder hens after peak production based on models to predict energy requirements

    Directory of Open Access Journals (Sweden)

    Nilva Kazue Sakomura

    2004-10-01

    Full Text Available Este trabalho foi conduzido com o objetivo de avaliar o desempenho de matrizes pesadas, submetidas a diferentes programas de alimentação estabelecidos pela aplicação de modelos para predizer as exigências energéticas, após o pico de postura. O experimento foi conduzido no setor de avicultura da UNESP Campus Jaboticabal, com duração de 84 dias (três períodos de 28 dias. Foram utilizadas 740 matrizes de corte Hubbard Hy-Yield e 80 machos Petterson, com 55 semanas de idade. O delineamento foi inteiramente casualizado, com quatro tratamentos e cinco repetições de 37 aves por repetição (box e um modelo fatorial 4´3 (quatro tratamentos ´ três períodos. Os programas de alimentação avaliados foram: T1 - Fornecimento de ração de acordo com o padrão da linhagem (428 kcal/ave/dia de 55 a 66 semanas de idade; T2 - Redução semanal de energia (2 kcal de EM/ave em cada semana; T3 - Fornecimento de ração de acordo com o modelo de exigência de EM, UNESP (2000; e T4 - Fornecimento de ração de acordo com o modelo, NRC (1994. O programa de alimentação com redução semanal de energia foi adequado para manter os desempenhos produtivo e reprodutivo das aves, indicando a possibilidade de redução de 2 kcal/ave/dia, em cada semana, na alimentação de matrizes pesadas após 55 semanas de idade. Os modelos UNESP e NRC proporcionaram estimativas mais elevadas das exigências energéticas que o modelo padrão, provavelmente em decorrência do ganho de peso das matrizes, que esteve acima do recomendado para a linhagem, promovendo maiores exigências de energia para mantença.This research was carried out to evaluate the performance of broiler breeder hens submitted to different feeding programs applying models to predict the metabolizable energy requirements after peak production. The experiment was conducted during 84 days (three periods of 28 days, at the Sao Paulo State University - Jaboticabal. Seven hundred and forty female broiler

  1. Thermophysical Properties Program

    Science.gov (United States)

    1997-01-01

    This is a computer generated model of a ground based casting. The objective of the therophysical properties program is to measure thermal physical properties of commercial casting alloys for use in computer programs that predict soldification behavior. This could reduce trial and error in casting design and promote less scrap, sounder castings, and less weight. In order for the computer models to reliably simulate the details of industrial alloy solidification, the input thermophysical property data must be absolutely reliable. Recently Auburn University and TPRL Inc. formed a teaming relationship to establish reliable measurement techniques for the most critical properties of commercially important alloys: transformation temperatures, thermal conductivity, electrical conductivity, specific heat, latent heat, density, solid fraction evolution, surface tension, and viscosity. A new initiative with the American Foundrymens Society has been started to measure the thermophysical properties of commercial ferrous and non-ferrous casting alloys and make the thermophysical property data widely available. Development of casting processes for the new gamma titanium aluminide alloys as well as existing titanium alloys will remain a trial-and-error procedure until accurate thermophysical properties can be obtained. These molten alloys react with their containers on earth and change their composition - invalidating the measurements even while the data are being acquired in terrestrial laboratories. However, measurements on the molten alloys can be accomplished in space using freely floating droplets which are completely untouched by any container. These data are expected to be exceptionally precise because of the absence of impurity contamination and buoyancy convection effects. Although long duration orbital experiments will be required for the large scale industrial alloy measurement program that results from this research, short duration experiments on NASA's KC-135 low

  2. Behavioral program synthesis with genetic programming

    CERN Document Server

    Krawiec, Krzysztof

    2016-01-01

    Genetic programming (GP) is a popular heuristic methodology of program synthesis with origins in evolutionary computation. In this generate-and-test approach, candidate programs are iteratively produced and evaluated. The latter involves running programs on tests, where they exhibit complex behaviors reflected in changes of variables, registers, or memory. That behavior not only ultimately determines program output, but may also reveal its `hidden qualities' and important characteristics of the considered synthesis problem. However, the conventional GP is oblivious to most of that information and usually cares only about the number of tests passed by a program. This `evaluation bottleneck' leaves search algorithm underinformed about the actual and potential qualities of candidate programs. This book proposes behavioral program synthesis, a conceptual framework that opens GP to detailed information on program behavior in order to make program synthesis more efficient. Several existing and novel mechanisms subs...

  3. Genomic Prediction of Sunflower Hybrids Oil Content

    Directory of Open Access Journals (Sweden)

    Brigitte Mangin

    2017-09-01

    Full Text Available Prediction of hybrid performance using incomplete factorial mating designs is widely used in breeding programs including different heterotic groups. Based on the general combining ability (GCA of the parents, predictions are accurate only if the genetic variance resulting from the specific combining ability is small and both parents have phenotyped descendants. Genomic selection (GS can predict performance using a model trained on both phenotyped and genotyped hybrids that do not necessarily include all hybrid parents. Therefore, GS could overcome the issue of unknown parent GCA. Here, we compared the accuracy of classical GCA-based and genomic predictions for oil content of sunflower seeds using several GS models. Our study involved 452 sunflower hybrids from an incomplete factorial design of 36 female and 36 male lines. Re-sequencing of parental lines allowed to identify 468,194 non-redundant SNPs and to infer the hybrid genotypes. Oil content was observed in a multi-environment trial (MET over 3 years, leading to nine different environments. We compared GCA-based model to different GS models including female and male genomic kinships with the addition of the female-by-male interaction genomic kinship, the use of functional knowledge as SNPs in genes of oil metabolic pathways, and with epistasis modeling. When both parents have descendants in the training set, the predictive ability was high even for GCA-based prediction, with an average MET value of 0.782. GS performed slightly better (+0.2%. Neither the inclusion of the female-by-male interaction, nor functional knowledge of oil metabolism, nor epistasis modeling improved the GS accuracy. GS greatly improved predictive ability when one or both parents were untested in the training set, increasing GCA-based predictive ability by 10.4% from 0.575 to 0.635 in the MET. In this scenario, performing GS only considering SNPs in oil metabolic pathways did not improve whole genome GS prediction but

  4. Prediction of dementia in primary care patients.

    Directory of Open Access Journals (Sweden)

    Frank Jessen

    Full Text Available BACKGROUND: Current approaches for AD prediction are based on biomarkers, which are however of restricted availability in primary care. AD prediction tools for primary care are therefore needed. We present a prediction score based on information that can be obtained in the primary care setting. METHODOLOGY/PRINCIPAL FINDINGS: We performed a longitudinal cohort study in 3.055 non-demented individuals above 75 years recruited via primary care chart registries (Study on Aging, Cognition and Dementia, AgeCoDe. After the baseline investigation we performed three follow-up investigations at 18 months intervals with incident dementia as the primary outcome. The best set of predictors was extracted from the baseline variables in one randomly selected half of the sample. This set included age, subjective memory impairment, performance on delayed verbal recall and verbal fluency, on the Mini-Mental-State-Examination, and on an instrumental activities of daily living scale. These variables were aggregated to a prediction score, which achieved a prediction accuracy of 0.84 for AD. The score was applied to the second half of the sample (test cohort. Here, the prediction accuracy was 0.79. With a cut-off of at least 80% sensitivity in the first cohort, 79.6% sensitivity, 66.4% specificity, 14.7% positive predictive value (PPV and 97.8% negative predictive value of (NPV for AD were achieved in the test cohort. At a cut-off for a high risk population (5% of individuals with the highest risk score in the first cohort the PPV for AD was 39.1% (52% for any dementia in the test cohort. CONCLUSIONS: The prediction score has useful prediction accuracy. It can define individuals (1 sensitively for low cost-low risk interventions, or (2 more specific and with increased PPV for measures of prevention with greater costs or risks. As it is independent of technical aids, it may be used within large scale prevention programs.

  5. Dopamine reward prediction error coding.

    Science.gov (United States)

    Schultz, Wolfram

    2016-03-01

    Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards-an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware.

  6. Urban pluvial flood prediction

    DEFF Research Database (Denmark)

    Thorndahl, Søren Liedtke; Nielsen, Jesper Ellerbæk; Jensen, David Getreuer

    2016-01-01

    Flooding produced by high-intensive local rainfall and drainage system capacity exceedance can have severe impacts in cities. In order to prepare cities for these types of flood events – especially in the future climate – it is valuable to be able to simulate these events numerically both...... historically and in real-time. There is a rather untested potential in real-time prediction of urban floods. In this paper radar data observations with different spatial and temporal resolution, radar nowcasts of 0–2 h lead time, and numerical weather models with lead times up to 24 h are used as inputs...... to an integrated flood and drainage systems model in order to investigate the relative difference between different inputs in predicting future floods. The system is tested on a small town Lystrup in Denmark, which has been flooded in 2012 and 2014. Results show it is possible to generate detailed flood maps...

  7. Predicting Bankruptcy in Pakistan

    Directory of Open Access Journals (Sweden)

    Abdul RASHID

    2011-09-01

    Full Text Available This paper aims to identify the financial ratios that are most significant in bankruptcy prediction for the non-financial sector of Pakistan based on a sample of companies which became bankrupt over the time period 1996-2006. Twenty four financial ratios covering four important financial attributes, namely profitability, liquidity, leverage, and turnover ratios, were examined for a five-year period prior bankruptcy. The discriminant analysis produced a parsimonious model of three variables viz. sales to total assets, EBIT to current liabilities, and cash flow ratio. Our estimates provide evidence that the firms having Z-value below zero fall into the “bankrupt” whereas the firms with Z-value above zero fall into the “non-bankrupt” category. The model achieved 76.9% prediction accuracy when it is applied to forecast bankruptcies on the underlying sample.

  8. Predicting Lotto Numbers

    DEFF Research Database (Denmark)

    Jørgensen, Claus Bjørn; Suetens, Sigrid; Tyran, Jean-Robert

    numbers based on recent drawings. While most players pick the same set of numbers week after week without regards of numbers drawn or anything else, we find that those who do change, act on average in the way predicted by the law of small numbers as formalized in recent behavioral theory. In particular......We investigate the “law of small numbers” using a unique panel data set on lotto gambling. Because we can track individual players over time, we can measure how they react to outcomes of recent lotto drawings. We can therefore test whether they behave as if they believe they can predict lotto......, on average they move away from numbers that have recently been drawn, as suggested by the “gambler’s fallacy”, and move toward numbers that are on streak, i.e. have been drawn several weeks in a row, consistent with the “hot hand fallacy”....

  9. Comparing Spatial Predictions

    KAUST Repository

    Hering, Amanda S.

    2011-11-01

    Under a general loss function, we develop a hypothesis test to determine whether a significant difference in the spatial predictions produced by two competing models exists on average across the entire spatial domain of interest. The null hypothesis is that of no difference, and a spatial loss differential is created based on the observed data, the two sets of predictions, and the loss function chosen by the researcher. The test assumes only isotropy and short-range spatial dependence of the loss differential but does allow it to be non-Gaussian, non-zero-mean, and spatially correlated. Constant and nonconstant spatial trends in the loss differential are treated in two separate cases. Monte Carlo simulations illustrate the size and power properties of this test, and an example based on daily average wind speeds in Oklahoma is used for illustration. Supplemental results are available online. © 2011 American Statistical Association and the American Society for Qualitys.

  10. Chaos detection and predictability

    CERN Document Server

    Gottwald, Georg; Laskar, Jacques

    2016-01-01

    Distinguishing chaoticity from regularity in deterministic dynamical systems and specifying the subspace of the phase space in which instabilities are expected to occur is of utmost importance in as disparate areas as astronomy, particle physics and climate dynamics.   To address these issues there exists a plethora of methods for chaos detection and predictability. The most commonly employed technique for investigating chaotic dynamics, i.e. the computation of Lyapunov exponents, however, may suffer a number of problems and drawbacks, for example when applied to noisy experimental data.   In the last two decades, several novel methods have been developed for the fast and reliable determination of the regular or chaotic nature of orbits, aimed at overcoming the shortcomings of more traditional techniques. This set of lecture notes and tutorial reviews serves as an introduction to and overview of modern chaos detection and predictability techniques for graduate students and non-specialists.   The book cover...

  11. Time-predictable architectures

    CERN Document Server

    Rochange, Christine; Uhrig , Sascha

    2014-01-01

    Building computers that can be used to design embedded real-time systems is the subject of this title. Real-time embedded software requires increasingly higher performances. The authors therefore consider processors that implement advanced mechanisms such as pipelining, out-of-order execution, branch prediction, cache memories, multi-threading, multicorearchitectures, etc. The authors of this book investigate the timepredictability of such schemes.

  12. Cultural Resource Predictive Modeling

    Science.gov (United States)

    2017-10-01

    CR cultural resource CRM cultural resource management CRPM Cultural Resource Predictive Modeling DoD Department of Defense ESTCP Environmental...resource management ( CRM ) legal obligations under NEPA and the NHPA, military installations need to demonstrate that CRM decisions are based on objective...maxim “one size does not fit all,” and demonstrate that DoD installations have many different CRM needs that can and should be met through a variety

  13. Predictive Game Theory

    Science.gov (United States)

    Wolpert, David H.

    2005-01-01

    Probability theory governs the outcome of a game; there is a distribution over mixed strat.'s, not a single "equilibrium". To predict a single mixed strategy must use our loss function (external to the game's players. Provides a quantification of any strategy's rationality. Prove rationality falls as cost of computation rises (for players who have not previously interacted). All extends to games with varying numbers of players.

  14. Predicting appointment breaking.

    Science.gov (United States)

    Bean, A G; Talaga, J

    1995-01-01

    The goal of physician referral services is to schedule appointments, but if too many patients fail to show up, the value of the service will be compromised. The authors found that appointment breaking can be predicted by the number of days to the scheduled appointment, the doctor's specialty, and the patient's age and gender. They also offer specific suggestions for modifying the marketing mix to reduce the incidence of no-shows.

  15. Adjusting estimative prediction limits

    OpenAIRE

    Masao Ueki; Kaoru Fueda

    2007-01-01

    This note presents a direct adjustment of the estimative prediction limit to reduce the coverage error from a target value to third-order accuracy. The adjustment is asymptotically equivalent to those of Barndorff-Nielsen & Cox (1994, 1996) and Vidoni (1998). It has a simpler form with a plug-in estimator of the coverage probability of the estimative limit at the target value. Copyright 2007, Oxford University Press.

  16. Space Weather Prediction

    Science.gov (United States)

    2014-10-31

    prominence eruptions and the ensuing coronal mass ejections. The ProMag is a spectro - polarimeter, consisting of a dual-beam polarization modulation unit...feeding a visible camera and an infrared camera. The instrument is designed to measure magnetic fields in solar prominences by simultaneous spectro ...as a result of coronal hole regions, we expect to improve UV predictions by incorporating an estimate of the Earth-side coronal hole regions. 5

  17. Instrument uncertainty predictions

    International Nuclear Information System (INIS)

    Coutts, D.A.

    1991-07-01

    The accuracy of measurements and correlations should normally be provided for most experimental activities. The uncertainty is a measure of the accuracy of a stated value or equation. The uncertainty term reflects a combination of instrument errors, modeling limitations, and phenomena understanding deficiencies. This report provides several methodologies to estimate an instrument's uncertainty when used in experimental work. Methods are shown to predict both the pretest and post-test uncertainty

  18. Predictive Systems Toxicology

    KAUST Repository

    Kiani, Narsis A.; Shang, Ming-Mei; Zenil, Hector; Tegner, Jesper

    2018-01-01

    In this review we address to what extent computational techniques can augment our ability to predict toxicity. The first section provides a brief history of empirical observations on toxicity dating back to the dawn of Sumerian civilization. Interestingly, the concept of dose emerged very early on, leading up to the modern emphasis on kinetic properties, which in turn encodes the insight that toxicity is not solely a property of a compound but instead depends on the interaction with the host organism. The next logical step is the current conception of evaluating drugs from a personalized medicine point-of-view. We review recent work on integrating what could be referred to as classical pharmacokinetic analysis with emerging systems biology approaches incorporating multiple omics data. These systems approaches employ advanced statistical analytical data processing complemented with machine learning techniques and use both pharmacokinetic and omics data. We find that such integrated approaches not only provide improved predictions of toxicity but also enable mechanistic interpretations of the molecular mechanisms underpinning toxicity and drug resistance. We conclude the chapter by discussing some of the main challenges, such as how to balance the inherent tension between the predictive capacity of models, which in practice amounts to constraining the number of features in the models versus allowing for rich mechanistic interpretability, i.e. equipping models with numerous molecular features. This challenge also requires patient-specific predictions on toxicity, which in turn requires proper stratification of patients as regards how they respond, with or without adverse toxic effects. In summary, the transformation of the ancient concept of dose is currently successfully operationalized using rich integrative data encoded in patient-specific models.

  19. Predictive systems ecology

    OpenAIRE

    Evans, Matthew R.; Bithell, Mike; Cornell, Stephen J.; Dall, Sasha R. X.; D?az, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J.; Lewis, Simon L.; Mace, Georgina M.; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim

    2013-01-01

    Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of ...

  20. UXO Burial Prediction Fidelity

    Science.gov (United States)

    2017-07-01

    models to capture detailed projectile dynamics during the early phases of water entry are wasted with regard to sediment -penetration depth prediction...ordnance (UXO) migrates and becomes exposed over time in response to water and sediment motion.  Such models need initial sediment penetration estimates...munition’s initial penetration depth into the sediment ,  the velocity of water at the water - sediment boundary (i.e., the bottom water velocity

  1. Predictive Systems Toxicology

    KAUST Repository

    Kiani, Narsis A.

    2018-01-15

    In this review we address to what extent computational techniques can augment our ability to predict toxicity. The first section provides a brief history of empirical observations on toxicity dating back to the dawn of Sumerian civilization. Interestingly, the concept of dose emerged very early on, leading up to the modern emphasis on kinetic properties, which in turn encodes the insight that toxicity is not solely a property of a compound but instead depends on the interaction with the host organism. The next logical step is the current conception of evaluating drugs from a personalized medicine point-of-view. We review recent work on integrating what could be referred to as classical pharmacokinetic analysis with emerging systems biology approaches incorporating multiple omics data. These systems approaches employ advanced statistical analytical data processing complemented with machine learning techniques and use both pharmacokinetic and omics data. We find that such integrated approaches not only provide improved predictions of toxicity but also enable mechanistic interpretations of the molecular mechanisms underpinning toxicity and drug resistance. We conclude the chapter by discussing some of the main challenges, such as how to balance the inherent tension between the predictive capacity of models, which in practice amounts to constraining the number of features in the models versus allowing for rich mechanistic interpretability, i.e. equipping models with numerous molecular features. This challenge also requires patient-specific predictions on toxicity, which in turn requires proper stratification of patients as regards how they respond, with or without adverse toxic effects. In summary, the transformation of the ancient concept of dose is currently successfully operationalized using rich integrative data encoded in patient-specific models.

  2. Predictive Surface Complexation Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences

    2016-11-29

    Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

  3. Predicting Human Cooperation.

    Directory of Open Access Journals (Sweden)

    John J Nay

    Full Text Available The Prisoner's Dilemma has been a subject of extensive research due to its importance in understanding the ever-present tension between individual self-interest and social benefit. A strictly dominant strategy in a Prisoner's Dilemma (defection, when played by both players, is mutually harmful. Repetition of the Prisoner's Dilemma can give rise to cooperation as an equilibrium, but defection is as well, and this ambiguity is difficult to resolve. The numerous behavioral experiments investigating the Prisoner's Dilemma highlight that players often cooperate, but the level of cooperation varies significantly with the specifics of the experimental predicament. We present the first computational model of human behavior in repeated Prisoner's Dilemma games that unifies the diversity of experimental observations in a systematic and quantitatively reliable manner. Our model relies on data we integrated from many experiments, comprising 168,386 individual decisions. The model is composed of two pieces: the first predicts the first-period action using solely the structural game parameters, while the second predicts dynamic actions using both game parameters and history of play. Our model is successful not merely at fitting the data, but in predicting behavior at multiple scales in experimental designs not used for calibration, using only information about the game structure. We demonstrate the power of our approach through a simulation analysis revealing how to best promote human cooperation.

  4. Predicting big bang deuterium

    Energy Technology Data Exchange (ETDEWEB)

    Hata, N.; Scherrer, R.J.; Steigman, G.; Thomas, D.; Walker, T.P. [Department of Physics, Ohio State University, Columbus, Ohio 43210 (United States)

    1996-02-01

    We present new upper and lower bounds to the primordial abundances of deuterium and {sup 3}He based on observational data from the solar system and the interstellar medium. Independent of any model for the primordial production of the elements we find (at the 95{percent} C.L.): 1.5{times}10{sup {minus}5}{le}(D/H){sub {ital P}}{le}10.0{times}10{sup {minus}5} and ({sup 3}He/H){sub {ital P}}{le}2.6{times}10{sup {minus}5}. When combined with the predictions of standard big bang nucleosynthesis, these constraints lead to a 95{percent} C.L. bound on the primordial abundance deuterium: (D/H){sub best}=(3.5{sup +2.7}{sub {minus}1.8}){times}10{sup {minus}5}. Measurements of deuterium absorption in the spectra of high-redshift QSOs will directly test this prediction. The implications of this prediction for the primordial abundances of {sup 4}He and {sup 7}Li are discussed, as well as those for the universal density of baryons. {copyright} {ital 1996 The American Astronomical Society.}

  5. Operational budgeting using fuzzy goal programming

    OpenAIRE

    Saeed Mohammadi; Kamran Feizi; Ali Khatami Firouz Abadi

    2013-01-01

    Having an efficient budget normally has different advantages such as measuring the performance of various organizations, setting appropriate targets and promoting managers based on their achievements. However, any budgeting planning requires prediction of different cost components. There are various methods for budgeting planning such as incremental budgeting, program budgeting, zero based budgeting and performance budgeting. In this paper, we present a fuzzy goal programming to estimate oper...

  6. SCRAM: a program for calculating scram times

    International Nuclear Information System (INIS)

    Bourquin, R.D.; Birney, K.R.

    1975-01-01

    Prediction of scram times is one facet of design analysis for control rod assemblies. Parameters for the entire control rod sub-system must be considered in such analyses and experimental verification is used when it is available. The SCRAM computer program was developed for design analysis of improved control rod assemblies for the Fast Flux Test Facility (FFTF). A description of the evolution of the program from basic equations to a functional design analysis tool is presented

  7. Predicting Schedule Duration for Defense Acquisition Programs: Program Initiation to Initial Operational Capability

    Science.gov (United States)

    2016-03-24

    statistically significant. Variance inflation is a consequence of multicollinearity and the VIF scores are a common way for detecting 43 such a...produced an initial model and we have ascertained there are no issues (and tested that) with respect to multicollinearity (VIF scores), influential...The analysis of this tells us that there is no consequence of multicollinearity present in the preliminary model. By this, there is no linear

  8. Atmospheric Radiation Measurement Program Plan

    International Nuclear Information System (INIS)

    1990-02-01

    In order to understand energy's role in anthropogenic global climate change, significant reliance is being placed on General Circulation Models (GCMs). A major goal of the Department is to foster the development of GCMs capable of predicting the timing and magnitude of greenhouse gas-induced global warming and the regional effects of such warming. DOE research has revealed that cloud radiative feedback is the single most important effect determining the magnitude of possible climate responses to human activity. However, cloud radiative forcing and feedbacks are not understood at the levels needed for reliable climate prediction. The Atmospheric Radiation Measurement (ARM) Program will contribute to the DOE goal by improving the treatment of cloud radiative forcing and feedbacks in GCMs. Two issues will be addressed: the radiation budget and its spectral dependence and the radiative and other properties of clouds. Understanding cloud properties and how to predict them is critical because cloud properties may very well change as climate changes. The experimental objective of the ARM Program is to characterize empirically the radiative processes in the Earth's atmosphere with improved resolution and accuracy. A key to this characterization is the effective treatment of cloud formation and cloud properties in GCMs. Through this characterization of radiative properties, it will be possible to understand both the forcing and feedback effects. GCM modelers will then be able to better identify the best approaches to improved parameterizations of radiative transfer effects. This is expected to greatly improve the accuracy of long-term, GCM predictions and the efficacy of those predictions at the important regional scale, as the research community and DOE attempt to understand the effects of greenhouse gas emissions on the Earth's climate. 153 refs., 24 figs., 6 tabs

  9. Predicting Performance in Higher Education Using Proximal Predictors

    Science.gov (United States)

    Niessen, A. Susan M.; Meijer, Rob R.; Tendeiro, Jorge N.

    2016-01-01

    We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach, and specific skills tests in English and math. Test scores were used to predict academic achievement and progress after the first year, achievement in specific course types, enrollment, and dropout after the first year. All tests showed positive significant correlations with the criteria. The trial-studying test was consistently the best predictor in the admission procedure. We found no significant differences between the predictive validity of the trial-studying test and prior educational performance, and substantial shared explained variance between the two predictors. Only applicants with lower trial-studying scores were significantly less likely to enroll in the program. In conclusion, the trial-studying test yielded predictive validities similar to that of prior educational performance and possibly enabled self-selection. In admissions aimed at student-program fit, or in admissions in which past educational performance is difficult to use, a trial-studying test is a good instrument to predict academic performance. PMID:27073859

  10. Model predictive control for a thermostatic controlled system

    DEFF Research Database (Denmark)

    Shafiei, Seyed Ehsan; Rasmussen, Henrik; Stoustrup, Jakob

    2013-01-01

    This paper proposes a model predictive control scheme to provide temperature set-points to thermostatic controlled cooling units in refrigeration systems. The control problem is formulated as a convex programming problem to minimize the overall operating cost of the system. The foodstuff temperat......This paper proposes a model predictive control scheme to provide temperature set-points to thermostatic controlled cooling units in refrigeration systems. The control problem is formulated as a convex programming problem to minimize the overall operating cost of the system. The foodstuff...

  11. Thermoviscoelastic characterization and prediction of Kevlar/epoxy composite laminates

    Science.gov (United States)

    Gramoll, K. C.; Dillard, D. A.; Brinson, H. F.

    1990-01-01

    The thermoviscoelastic characterization of Kevlar 49/Fiberite 7714A epoxy composite lamina and the development of a numerical procedure to predict the viscoelastic response of any general laminate constructed from the same material were studied. The four orthotropic material properties, S sub 11, S sub 12, S sub 22, and S sub 66, were characterized by 20 minute static creep tests on unidirectional (0) sub 8, (10) sub 8, and (90) sub 16 lamina specimens. The Time-Temperature Superposition-Principle (TTSP) was used successfully to accelerate the characterization process. A nonlinear constitutive model was developed to describe the stress dependent viscoelastic response for each of the material properties. A numerical procedure to predict long term laminate properties from lamina properties (obtained experimentally) was developed. Numerical instabilities and time constraints associated with viscoelastic numerical techniques were discussed and solved. The numerical procedure was incorporated into a user friendly microcomputer program called Viscoelastic Composite Analysis Program (VCAP), which is available for IBM PC type computers. The program was designed for ease of use. The final phase involved testing actual laminates constructed from the characterized material, Kevlar/epoxy, at various temperatures and load level for 4 to 5 weeks. These results were compared with the VCAP program predictions to verify the testing procedure and to check the numerical procedure used in the program. The actual tests and predictions agreed for all test cases which included 1, 2, 3, and 4 fiber direction laminates.

  12. Availability program: Phase I report

    International Nuclear Information System (INIS)

    Thomson, S.L.; Dabiri, A.; Keeton, D.C.; Riemer, B.W.; Waganer, L.M.

    1985-05-01

    An Availability Working Group was formed within the Office of Fusion Energy in March 1984 to consider the establishment of an availability program for magnetic fusion. The scope of this program is defined to include the development of (1) a comprehensive data base, (2) empirical correlations, and (3) analytical methods for application to fusion facilities and devices. The long-term goal of the availability program is to develop a validated, integrated methodology that will provide (1) projections of plant availability and (2) input to design decisions on maintainability and system reliability requirements. The Phase I study group was commissioned to assess the status of work in progress that is relevant to the availability program. The scope of Phase I included surveys of existing data and data collection programs at operating fusion research facilities, the assessment of existing computer models to calculate system availability, and the review of methods to predict and correlate data on component failure and maintenance. The results of these investigations are reported to the Availability Working Group in this document

  13. An Intelligent Robot Programing

    Energy Technology Data Exchange (ETDEWEB)

    Hong, Seong Yong

    2012-01-15

    This book introduces an intelligent robot programing with background of the begging, introduction of VPL, and SPL, building of environment for robot platform, starting of robot programing, design of simulation environment, robot autonomy drive control programing, simulation graphic. Such as SPL graphic programing graphical image and graphical shapes, and graphical method application, application of procedure for robot control, robot multiprogramming, robot bumper sensor programing, robot LRF sencor programing and robot color sensor programing.

  14. System programming languages

    OpenAIRE

    Šmit, Matej

    2016-01-01

    Most operating systems are written in the C programming language. Similar is with system software, for example, device drivers, compilers, debuggers, disk checkers, etc. Recently some new programming languages emerged, which are supposed to be suitable for system programming. In this thesis we present programming languages D, Go, Nim and Rust. We defined the criteria which are important for deciding whether programming language is suitable for system programming. We examine programming langua...

  15. Purely Functional Structured Programming

    OpenAIRE

    Obua, Steven

    2010-01-01

    The idea of functional programming has played a big role in shaping today's landscape of mainstream programming languages. Another concept that dominates the current programming style is Dijkstra's structured programming. Both concepts have been successfully married, for example in the programming language Scala. This paper proposes how the same can be achieved for structured programming and PURELY functional programming via the notion of LINEAR SCOPE. One advantage of this proposal is that m...

  16. An Intelligent Robot Programing

    International Nuclear Information System (INIS)

    Hong, Seong Yong

    2012-01-01

    This book introduces an intelligent robot programing with background of the begging, introduction of VPL, and SPL, building of environment for robot platform, starting of robot programing, design of simulation environment, robot autonomy drive control programing, simulation graphic. Such as SPL graphic programing graphical image and graphical shapes, and graphical method application, application of procedure for robot control, robot multiprogramming, robot bumper sensor programing, robot LRF sencor programing and robot color sensor programing.

  17. The Plowshare Program

    Energy Technology Data Exchange (ETDEWEB)

    Hamburger, R [U.S. Atomic Energy Commission, Germantown, MD (United States)

    1969-07-01

    The Plowshare Program was established in 1957 as a research and development program to develop peaceful uses for nuclear explosives. During that year, the basic concepts, which have guided the program, were proposed for using nuclear explosives in large excavation projects, conservation and management of natural resources, and Scientific research. Research has been conducted primarily by the Lawrence Radiation Laboratory at Livermore, California; however, substantial assistance has been provided by a number of other government agencies and national laboratories. Sufficient knowledge of the phenomenology of underground nuclear explosions and their effects has been developed to permit consideration of industrial use of such explosions. To this end, the first government industry cooperative nuclear experiment, Project Gasbuggy, was conducted in December 1967. Additional proposals have been received for using nuclear explosives in stimulating natural gas production from reservoirs of varying characteristics: The storage of natural gas, the recovery of copper from a low-grade deposit, and preparing oil shales for in situ retorting. It is believed that several experiments in each of these fields are necessary to develop a proven technology. The timely development of a nuclear excavation technology for use in large-scale excavation projects is a primary program objective and, although additional research and development are needed, substantial progress has been made in several areas. A capability for predicting crater sizes from single and row charges has been successfully demonstrated. The development of low fission nuclear explosives for use in excavation projects has been very successful. It is believed that such projects can be conducted safely. Large nuclear excavation projects, such as harbors and canals, must be closely examined in view of the restraints of the limited Test Ban Treaty. Industry's interest and participation in Plowshare continue to increase and

  18. The Plowshare Program

    International Nuclear Information System (INIS)

    Hamburger, R.

    1969-01-01

    The Plowshare Program was established in 1957 as a research and development program to develop peaceful uses for nuclear explosives. During that year, the basic concepts, which have guided the program, were proposed for using nuclear explosives in large excavation projects, conservation and management of natural resources, and Scientific research. Research has been conducted primarily by the Lawrence Radiation Laboratory at Livermore, California; however, substantial assistance has been provided by a number of other government agencies and national laboratories. Sufficient knowledge of the phenomenology of underground nuclear explosions and their effects has been developed to permit consideration of industrial use of such explosions. To this end, the first government industry cooperative nuclear experiment, Project Gasbuggy, was conducted in December 1967. Additional proposals have been received for using nuclear explosives in stimulating natural gas production from reservoirs of varying characteristics: The storage of natural gas, the recovery of copper from a low-grade deposit, and preparing oil shales for in situ retorting. It is believed that several experiments in each of these fields are necessary to develop a proven technology. The timely development of a nuclear excavation technology for use in large-scale excavation projects is a primary program objective and, although additional research and development are needed, substantial progress has been made in several areas. A capability for predicting crater sizes from single and row charges has been successfully demonstrated. The development of low fission nuclear explosives for use in excavation projects has been very successful. It is believed that such projects can be conducted safely. Large nuclear excavation projects, such as harbors and canals, must be closely examined in view of the restraints of the limited Test Ban Treaty. Industry's interest and participation in Plowshare continue to increase and

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

    Science.gov (United States)

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

    1972-01-01

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

  20. A Predictive Method of Teacher's Structure in China's University (1985--2000)

    OpenAIRE

    Chen Ling; Pen Guozhong

    1987-01-01

    In this paper, a predictive model is designed to provide the Educational Department of China with the information necessary to draw up the program (1985--2000) for education development. This model contains two submodels, that is, the predictive model to the annual teacher's number of each title and the fuzzy predictive model to the annual teacher's number of each age. The first submodel is a Markov Chain model and the second submodel is a fuzzy predictive model. Before establishing the secon...