validation set generation: Topics by Science.gov

Sample records for validation set generation

Directed Design of Experiments for Validating Probability of Detection Capability of a Testing System

NASA Technical Reports Server (NTRS)

Generazio, Edward R. (Inventor)

2012-01-01

A method of validating a probability of detection (POD) testing system using directed design of experiments (DOE) includes recording an input data set of observed hit and miss or analog data for sample components as a function of size of a flaw in the components. The method also includes processing the input data set to generate an output data set having an optimal class width, assigning a case number to the output data set, and generating validation instructions based on the assigned case number. An apparatus includes a host machine for receiving the input data set from the testing system and an algorithm for executing DOE to validate the test system. The algorithm applies DOE to the input data set to determine a data set having an optimal class width, assigns a case number to that data set, and generates validation instructions based on the case number.
Automatic Generation of Validated Specific Epitope Sets.

PubMed

Carrasco Pro, Sebastian; Sidney, John; Paul, Sinu; Lindestam Arlehamn, Cecilia; Weiskopf, Daniela; Peters, Bjoern; Sette, Alessandro

2015-01-01

Accurate measurement of B and T cell responses is a valuable tool to study autoimmunity, allergies, immunity to pathogens, and host-pathogen interactions and assist in the design and evaluation of T cell vaccines and immunotherapies. In this context, it is desirable to elucidate a method to select validated reference sets of epitopes to allow detection of T and B cells. However, the ever-growing information contained in the Immune Epitope Database (IEDB) and the differences in quality and subjects studied between epitope assays make this task complicated. In this study, we develop a novel method to automatically select reference epitope sets according to a categorization system employed by the IEDB. From the sets generated, three epitope sets (EBV, mycobacteria and dengue) were experimentally validated by detection of T cell reactivity ex vivo from human donors. Furthermore, a web application that will potentially be implemented in the IEDB was created to allow users the capacity to generate customized epitope sets.
Performance of genomic prediction within and across generations in maritime pine.

PubMed

Bartholomé, Jérôme; Van Heerwaarden, Joost; Isik, Fikret; Boury, Christophe; Vidal, Marjorie; Plomion, Christophe; Bouffier, Laurent

2016-08-11

Genomic selection (GS) is a promising approach for decreasing breeding cycle length in forest trees. Assessment of progeny performance and of the prediction accuracy of GS models over generations is therefore a key issue. A reference population of maritime pine (Pinus pinaster) with an estimated effective inbreeding population size (status number) of 25 was first selected with simulated data. This reference population (n = 818) covered three generations (G0, G1 and G2) and was genotyped with 4436 single-nucleotide polymorphism (SNP) markers. We evaluated the effects on prediction accuracy of both the relatedness between the calibration and validation sets and validation on the basis of progeny performance. Pedigree-based (best linear unbiased prediction, ABLUP) and marker-based (genomic BLUP and Bayesian LASSO) models were used to predict breeding values for three different traits: circumference, height and stem straightness. On average, the ABLUP model outperformed genomic prediction models, with a maximum difference in prediction accuracies of 0.12, depending on the trait and the validation method. A mean difference in prediction accuracy of 0.17 was found between validation methods differing in terms of relatedness. Including the progenitors in the calibration set reduced this difference in prediction accuracy to 0.03. When only genotypes from the G0 and G1 generations were used in the calibration set and genotypes from G2 were used in the validation set (progeny validation), prediction accuracies ranged from 0.70 to 0.85. This study suggests that the training of prediction models on parental populations can predict the genetic merit of the progeny with high accuracy: an encouraging result for the implementation of GS in the maritime pine breeding program.
Evaluating the validity of multiple imputation for missing physiological data in the national trauma data bank.

PubMed

Moore, Lynne; Hanley, James A; Lavoie, André; Turgeon, Alexis

2009-05-01

The National Trauma Data Bank (NTDB) is plagued by the problem of missing physiological data. The Glasgow Coma Scale score, Respiratory Rate and Systolic Blood Pressure are an essential part of risk adjustment strategies for trauma system evaluation and clinical research. Missing data on these variables may compromise the feasibility and the validity of trauma group comparisons. To evaluate the validity of Multiple Imputation (MI) for completing missing physiological data in the National Trauma Data Bank (NTDB), by assessing the impact of MI on 1) frequency distributions, 2) associations with mortality, and 3) risk adjustment. Analyses were based on 170,956 NTDB observations with complete physiological data (observed data set). Missing physiological data were artificially imposed on this data set and then imputed using MI (MI data set). To assess the impact of MI on risk adjustment, 100 pairs of hospitals were randomly selected with replacement and compared using adjusted Odds Ratios (OR) of mortality. OR generated by the observed data set were then compared to those generated by the MI data set. Frequency distributions and associations with mortality were preserved following MI. The median absolute difference between adjusted OR of mortality generated by the observed data set and by the MI data set was 3.6% (inter-quartile range: 2.4%-6.1%). This study suggests that, provided it is implemented with care, MI of missing physiological data in the NTDB leads to valid frequency distributions, preserves associations with mortality, and does not compromise risk adjustment in inter-hospital comparisons of mortality.
Routine development of objectively derived search strategies.

PubMed

Hausner, Elke; Waffenschmidt, Siw; Kaiser, Thomas; Simon, Michael

2012-02-29

Over the past few years, information retrieval has become more and more professionalized, and information specialists are considered full members of a research team conducting systematic reviews. Research groups preparing systematic reviews and clinical practice guidelines have been the driving force in the development of search strategies, but open questions remain regarding the transparency of the development process and the available resources. An empirically guided approach to the development of a search strategy provides a way to increase transparency and efficiency. Our aim in this paper is to describe the empirically guided development process for search strategies as applied by the German Institute for Quality and Efficiency in Health Care (Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen, or "IQWiG"). This strategy consists of the following steps: generation of a test set, as well as the development, validation and standardized documentation of the search strategy. We illustrate our approach by means of an example, that is, a search for literature on brachytherapy in patients with prostate cancer. For this purpose, a test set was generated, including a total of 38 references from 3 systematic reviews. The development set for the generation of the strategy included 25 references. After application of textual analytic procedures, a strategy was developed that included all references in the development set. To test the search strategy on an independent set of references, the remaining 13 references in the test set (the validation set) were used. The validation set was also completely identified. Our conclusion is that an objectively derived approach similar to that used in search filter development is a feasible way to develop and validate reliable search strategies. Besides creating high-quality strategies, the widespread application of this approach will result in a substantial increase in the transparency of the development process of search strategies.
Does rational selection of training and test sets improve the outcome of QSAR modeling?

PubMed

Martin, Todd M; Harten, Paul; Young, Douglas M; Muratov, Eugene N; Golbraikh, Alexander; Zhu, Hao; Tropsha, Alexander

2012-10-22

Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external data set, the best way to validate the predictive ability of a model is to perform its statistical external validation. In statistical external validation, the overall data set is divided into training and test sets. Commonly, this splitting is performed using random division. Rational splitting methods can divide data sets into training and test sets in an intelligent fashion. The purpose of this study was to determine whether rational division methods lead to more predictive models compared to random division. A special data splitting procedure was used to facilitate the comparison between random and rational division methods. For each toxicity end point, the overall data set was divided into a modeling set (80% of the overall set) and an external evaluation set (20% of the overall set) using random division. The modeling set was then subdivided into a training set (80% of the modeling set) and a test set (20% of the modeling set) using rational division methods and by using random division. The Kennard-Stone, minimal test set dissimilarity, and sphere exclusion algorithms were used as the rational division methods. The hierarchical clustering, random forest, and k-nearest neighbor (kNN) methods were used to develop QSAR models based on the training sets. For kNN QSAR, multiple training and test sets were generated, and multiple QSAR models were built. The results of this study indicate that models based on rational division methods generate better statistical results for the test sets than models based on random division, but the predictive power of both types of models are comparable.
Optimization and validation of moving average quality control procedures using bias detection curves and moving average validation charts.

PubMed

van Rossum, Huub H; Kemperman, Hans

2017-02-01

To date, no practical tools are available to obtain optimal settings for moving average (MA) as a continuous analytical quality control instrument. Also, there is no knowledge of the true bias detection properties of applied MA. We describe the use of bias detection curves for MA optimization and MA validation charts for validation of MA. MA optimization was performed on a data set of previously obtained consecutive assay results. Bias introduction and MA bias detection were simulated for multiple MA procedures (combination of truncation limits, calculation algorithms and control limits) and performed for various biases. Bias detection curves were generated by plotting the median number of test results needed for bias detection against the simulated introduced bias. In MA validation charts the minimum, median, and maximum numbers of assay results required for MA bias detection are shown for various bias. Their use was demonstrated for sodium, potassium, and albumin. Bias detection curves allowed optimization of MA settings by graphical comparison of bias detection properties of multiple MA. The optimal MA was selected based on the bias detection characteristics obtained. MA validation charts were generated for selected optimal MA and provided insight into the range of results required for MA bias detection. Bias detection curves and MA validation charts are useful tools for optimization and validation of MA procedures.
Utility of NIST Whole-Genome Reference Materials for the Technical Validation of a Multigene Next-Generation Sequencing Test.

PubMed

Shum, Bennett O V; Henner, Ilya; Belluoccio, Daniele; Hinchcliffe, Marcus J

2017-07-01

The sensitivity and specificity of next-generation sequencing laboratory developed tests (LDTs) are typically determined by an analyte-specific approach. Analyte-specific validations use disease-specific controls to assess an LDT's ability to detect known pathogenic variants. Alternatively, a methods-based approach can be used for LDT technical validations. Methods-focused validations do not use disease-specific controls but use benchmark reference DNA that contains known variants (benign, variants of unknown significance, and pathogenic) to assess variant calling accuracy of a next-generation sequencing workflow. Recently, four whole-genome reference materials (RMs) from the National Institute of Standards and Technology (NIST) were released to standardize methods-based validations of next-generation sequencing panels across laboratories. We provide a practical method for using NIST RMs to validate multigene panels. We analyzed the utility of RMs in validating a novel newborn screening test that targets 70 genes, called NEO1. Despite the NIST RM variant truth set originating from multiple sequencing platforms, replicates, and library types, we discovered a 5.2% false-negative variant detection rate in the RM truth set genes that were assessed in our validation. We developed a strategy using complementary non-RM controls to demonstrate 99.6% sensitivity of the NEO1 test in detecting variants. Our findings have implications for laboratories or proficiency testing organizations using whole-genome NIST RMs for testing. Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.
Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates.

PubMed

LeDell, Erin; Petersen, Maya; van der Laan, Mark

In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we obtain an estimate of its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, the process of cross-validating a predictive model on even a relatively small data set can still require a large amount of computation time. Thus, in many practical settings, the bootstrap is a computationally intractable approach to variance estimation. As an alternative to the bootstrap, we demonstrate a computationally efficient influence curve based approach to obtaining a variance estimate for cross-validated AUC.
Computationally efficient confidence intervals for cross-validated area under the ROC curve estimates

PubMed Central

Petersen, Maya; van der Laan, Mark

2015-01-01

In binary classification problems, the area under the ROC curve (AUC) is commonly used to evaluate the performance of a prediction model. Often, it is combined with cross-validation in order to assess how the results will generalize to an independent data set. In order to evaluate the quality of an estimate for cross-validated AUC, we obtain an estimate of its variance. For massive data sets, the process of generating a single performance estimate can be computationally expensive. Additionally, when using a complex prediction method, the process of cross-validating a predictive model on even a relatively small data set can still require a large amount of computation time. Thus, in many practical settings, the bootstrap is a computationally intractable approach to variance estimation. As an alternative to the bootstrap, we demonstrate a computationally efficient influence curve based approach to obtaining a variance estimate for cross-validated AUC. PMID:26279737
How to test validity in orthodontic research: a mixed dentition analysis example.

PubMed

Donatelli, Richard E; Lee, Shin-Jae

2015-02-01

The data used to test the validity of a prediction method should be different from the data used to generate the prediction model. In this study, we explored whether an independent data set is mandatory for testing the validity of a new prediction method and how validity can be tested without independent new data. Several validation methods were compared in an example using the data from a mixed dentition analysis with a regression model. The validation errors of real mixed dentition analysis data and simulation data were analyzed for increasingly large data sets. The validation results of both the real and the simulation studies demonstrated that the leave-1-out cross-validation method had the smallest errors. The largest errors occurred in the traditional simple validation method. The differences between the validation methods diminished as the sample size increased. The leave-1-out cross-validation method seems to be an optimal validation method for improving the prediction accuracy in a data set with limited sample sizes. Copyright © 2015 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.
Integration of SimSET photon history generator in GATE for efficient Monte Carlo simulations of pinhole SPECT.

PubMed

Chen, Chia-Lin; Wang, Yuchuan; Lee, Jason J S; Tsui, Benjamin M W

2008-07-01

The authors developed and validated an efficient Monte Carlo simulation (MCS) workflow to facilitate small animal pinhole SPECT imaging research. This workflow seamlessly integrates two existing MCS tools: simulation system for emission tomography (SimSET) and GEANT4 application for emission tomography (GATE). Specifically, we retained the strength of GATE in describing complex collimator/detector configurations to meet the anticipated needs for studying advanced pinhole collimation (e.g., multipinhole) geometry, while inserting the fast SimSET photon history generator (PHG) to circumvent the relatively slow GEANT4 MCS code used by GATE in simulating photon interactions inside voxelized phantoms. For validation, data generated from this new SimSET-GATE workflow were compared with those from GATE-only simulations as well as experimental measurements obtained using a commercial small animal pinhole SPECT system. Our results showed excellent agreement (e.g., in system point response functions and energy spectra) between SimSET-GATE and GATE-only simulations, and, more importantly, a significant computational speedup (up to approximately 10-fold) provided by the new workflow. Satisfactory agreement between MCS results and experimental data were also observed. In conclusion, the authors have successfully integrated SimSET photon history generator in GATE for fast and realistic pinhole SPECT simulations, which can facilitate research in, for example, the development and application of quantitative pinhole and multipinhole SPECT for small animal imaging. This integrated simulation tool can also be adapted for studying other preclinical and clinical SPECT techniques.
A technique for global monitoring of net solar irradiance at the ocean surface. II - Validation

NASA Technical Reports Server (NTRS)

Chertock, Beth; Frouin, Robert; Gautier, Catherine

1992-01-01

The generation and validation of the first satellite-based long-term record of surface solar irradiance over the global oceans are addressed. The record is generated using Nimbus-7 earth radiation budget (ERB) wide-field-of-view plentary-albedo data as input to a numerical algorithm designed and implemented based on radiative transfer theory. The mean monthly values of net surface solar irradiance are computed on a 9-deg latitude-longitude spatial grid for November 1978-October 1985. The new data set is validated in comparisons with short-term, regional, high-resolution, satellite-based records. The ERB-based values of net surface solar irradiance are compared with corresponding values based on radiance measurements taken by the Visible-Infrared Spin Scan Radiometer aboard GOES series satellites. Errors in the new data set are estimated to lie between 10 and 20 W/sq m on monthly time scales.
Effects of number of training generations on genomic prediction for various traits in a layer chicken population.

PubMed

Weng, Ziqing; Wolc, Anna; Shen, Xia; Fernando, Rohan L; Dekkers, Jack C M; Arango, Jesus; Settar, Petek; Fulton, Janet E; O'Sullivan, Neil P; Garrick, Dorian J

2016-03-19

Genomic estimated breeding values (GEBV) based on single nucleotide polymorphism (SNP) genotypes are widely used in animal improvement programs. It is typically assumed that the larger the number of animals is in the training set, the higher is the prediction accuracy of GEBV. The aim of this study was to quantify genomic prediction accuracy depending on the number of ancestral generations included in the training set, and to determine the optimal number of training generations for different traits in an elite layer breeding line. Phenotypic records for 16 traits on 17,793 birds were used. All parents and some selection candidates from nine non-overlapping generations were genotyped for 23,098 segregating SNPs. An animal model with pedigree relationships (PBLUP) and the BayesB genomic prediction model were applied to predict EBV or GEBV at each validation generation (progeny of the most recent training generation) based on varying numbers of immediately preceding ancestral generations. Prediction accuracy of EBV or GEBV was assessed as the correlation between EBV and phenotypes adjusted for fixed effects, divided by the square root of trait heritability. The optimal number of training generations that resulted in the greatest prediction accuracy of GEBV was determined for each trait. The relationship between optimal number of training generations and heritability was investigated. On average, accuracies were higher with the BayesB model than with PBLUP. Prediction accuracies of GEBV increased as the number of closely-related ancestral generations included in the training set increased, but reached an asymptote or slightly decreased when distant ancestral generations were used in the training set. The optimal number of training generations was 4 or more for high heritability traits but less than that for low heritability traits. For less heritable traits, limiting the training datasets to individuals closely related to the validation population resulted in the best predictions. The effect of adding distant ancestral generations in the training set on prediction accuracy differed between traits and the optimal number of necessary training generations is associated with the heritability of traits.
A high-fidelity weather time series generator using the Markov Chain process on a piecewise level

NASA Astrophysics Data System (ADS)

Hersvik, K.; Endrerud, O.-E. V.

2017-12-01

A method is developed for generating a set of unique weather time-series based on an existing weather series. The method allows statistically valid weather variations to take place within repeated simulations of offshore operations. The numerous generated time series need to share the same statistical qualities as the original time series. Statistical qualities here refer mainly to the distribution of weather windows available for work, including durations and frequencies of such weather windows, and seasonal characteristics. The method is based on the Markov chain process. The core new development lies in how the Markov Process is used, specifically by joining small pieces of random length time series together rather than joining individual weather states, each from a single time step, which is a common solution found in the literature. This new Markov model shows favorable characteristics with respect to the requirements set forth and all aspects of the validation performed.
Generation of ELGA-compatible radiology reports from the Vienna Hospital Association's EHR system.

PubMed

Haider, Jasmin; Hölzl, Konrad; Toth, Herlinde; Duftschmid, Georg

2014-01-01

In the course of setting up the upcoming Austrian national shared EHR system ELGA, adaptors will have to be implemented for the local EHR systems of all participating healthcare providers. These adaptors must be able to transform EHR data from the internal format of the particular local EHR system to the specified format of the ELGA document types and vice versa. In the course of an ongoing diploma thesis we are currently developing a transformation application that shall allow the generation of ELGA-compatible radiology reports from the local EHR system of the Vienna Hospital Association. Up to now a first prototype has been developed that was tested with six radiology reports. It generates technically valid ELGA radiology reports apart from two errors yielded by the ELGA online validator that rather seem to be bugs of the validator. A medical validation of the reports remains to be done.
A computational model-based validation of Guyton's analysis of cardiac output and venous return curves

NASA Technical Reports Server (NTRS)

Mukkamala, R.; Cohen, R. J.; Mark, R. G.

2002-01-01

Guyton developed a popular approach for understanding the factors responsible for cardiac output (CO) regulation in which 1) the heart-lung unit and systemic circulation are independently characterized via CO and venous return (VR) curves, and 2) average CO and right atrial pressure (RAP) of the intact circulation are predicted by graphically intersecting the curves. However, this approach is virtually impossible to verify experimentally. We theoretically evaluated the approach with respect to a nonlinear, computational model of the pulsatile heart and circulation. We developed two sets of open circulation models to generate CO and VR curves, differing by the manner in which average RAP was varied. One set applied constant RAPs, while the other set applied pulsatile RAPs. Accurate prediction of intact, average CO and RAP was achieved only by intersecting the CO and VR curves generated with pulsatile RAPs because of the pulsatility and nonlinearity (e.g., systemic venous collapse) of the intact model. The CO and VR curves generated with pulsatile RAPs were also practically independent. This theoretical study therefore supports the validity of Guyton's graphical analysis.
A Spatio-Temporal Approach for Global Validation and Analysis of MODIS Aerosol Products

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Chu, D. Allen; Mattoo, Shana; Kaufman, Yoram J.; Remer, Lorraine A.; Tanre, Didier; Slutsker, Ilya; Holben, Brent N.; Lau, William K. M. (Technical Monitor)

2001-01-01

With the launch of the MODIS sensor on the Terra spacecraft, new data sets of the global distribution and properties of aerosol are being retrieved, and need to be validated and analyzed. A system has been put in place to generate spatial statistics (mean, standard deviation, direction and rate of spatial variation, and spatial correlation coefficient) of the MODIS aerosol parameters over more than 100 validation sites spread around the globe. Corresponding statistics are also computed from temporal subsets of AERONET-derived aerosol data. The means and standard deviations of identical parameters from MOMS and AERONET are compared. Although, their means compare favorably, their standard deviations reveal some influence of surface effects on the MODIS aerosol retrievals over land, especially at low aerosol loading. The direction and rate of spatial variation from MODIS are used to study the spatial distribution of aerosols at various locations either individually or comparatively. This paper introduces the methodology for generating and analyzing the data sets used by the two MODIS aerosol validation papers in this issue.
A Supervised Learning Process to Validate Online Disease Reports for Use in Predictive Models.

PubMed

Patching, Helena M M; Hudson, Laurence M; Cooke, Warrick; Garcia, Andres J; Hay, Simon I; Roberts, Mark; Moyes, Catherine L

2015-12-01

Pathogen distribution models that predict spatial variation in disease occurrence require data from a large number of geographic locations to generate disease risk maps. Traditionally, this process has used data from public health reporting systems; however, using online reports of new infections could speed up the process dramatically. Data from both public health systems and online sources must be validated before they can be used, but no mechanisms exist to validate data from online media reports. We have developed a supervised learning process to validate geolocated disease outbreak data in a timely manner. The process uses three input features, the data source and two metrics derived from the location of each disease occurrence. The location of disease occurrence provides information on the probability of disease occurrence at that location based on environmental and socioeconomic factors and the distance within or outside the current known disease extent. The process also uses validation scores, generated by disease experts who review a subset of the data, to build a training data set. The aim of the supervised learning process is to generate validation scores that can be used as weights going into the pathogen distribution model. After analyzing the three input features and testing the performance of alternative processes, we selected a cascade of ensembles comprising logistic regressors. Parameter values for the training data subset size, number of predictors, and number of layers in the cascade were tested before the process was deployed. The final configuration was tested using data for two contrasting diseases (dengue and cholera), and 66%-79% of data points were assigned a validation score. The remaining data points are scored by the experts, and the results inform the training data set for the next set of predictors, as well as going to the pathogen distribution model. The new supervised learning process has been implemented within our live site and is being used to validate the data that our system uses to produce updated predictive disease maps on a weekly basis.
Adversarial Threshold Neural Computer for Molecular de Novo Design.

PubMed

Putin, Evgeny; Asadulaev, Arip; Vanhaelen, Quentin; Ivanenkov, Yan; Aladinskaya, Anastasia V; Aliper, Alex; Zhavoronkov, Alex

2018-03-30

In this article, we propose the deep neural network Adversarial Threshold Neural Computer (ATNC). The ATNC model is intended for the de novo design of novel small-molecule organic structures. The model is based on generative adversarial network architecture and reinforcement learning. ATNC uses a Differentiable Neural Computer as a generator and has a new specific block, called adversarial threshold (AT). AT acts as a filter between the agent (generator) and the environment (discriminator + objective reward functions). Furthermore, to generate more diverse molecules we introduce a new objective reward function named Internal Diversity Clustering (IDC). In this work, ATNC is tested and compared with the ORGANIC model. Both models were trained on the SMILES string representation of the molecules, using four objective functions (internal similarity, Muegge druglikeness filter, presence or absence of sp 3 -rich fragments, and IDC). The SMILES representations of 15K druglike molecules from the ChemDiv collection were used as a training data set. For the different functions, ATNC outperforms ORGANIC. Combined with the IDC, ATNC generates 72% of valid and 77% of unique SMILES strings, while ORGANIC generates only 7% of valid and 86% of unique SMILES strings. For each set of molecules generated by ATNC and ORGANIC, we analyzed distributions of four molecular descriptors (number of atoms, molecular weight, logP, and tpsa) and calculated five chemical statistical features (internal diversity, number of unique heterocycles, number of clusters, number of singletons, and number of compounds that have not been passed through medicinal chemistry filters). Analysis of key molecular descriptors and chemical statistical features demonstrated that the molecules generated by ATNC elicited better druglikeness properties. We also performed in vitro validation of the molecules generated by ATNC; results indicated that ATNC is an effective method for producing hit compounds.

The medline UK filter: development and validation of a geographic search filter to retrieve research about the UK from OVID medline.

PubMed

Ayiku, Lynda; Levay, Paul; Hudson, Tom; Craven, Jenny; Barrett, Elizabeth; Finnegan, Amy; Adams, Rachel

2017-07-13

A validated geographic search filter for the retrieval of research about the United Kingdom (UK) from bibliographic databases had not previously been published. To develop and validate a geographic search filter to retrieve research about the UK from OVID medline with high recall and precision. Three gold standard sets of references were generated using the relative recall method. The sets contained references to studies about the UK which had informed National Institute for Health and Care Excellence (NICE) guidance. The first and second sets were used to develop and refine the medline UK filter. The third set was used to validate the filter. Recall, precision and number-needed-to-read (NNR) were calculated using a case study. The validated medline UK filter demonstrated 87.6% relative recall against the third gold standard set. In the case study, the medline UK filter demonstrated 100% recall, 11.4% precision and a NNR of nine. A validated geographic search filter to retrieve research about the UK with high recall and precision has been developed. The medline UK filter can be applied to systematic literature searches in OVID medline for topics with a UK focus. © 2017 Crown copyright. Health Information and Libraries Journal © 2017 Health Libraries GroupThis article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland.
Prediction of Metastasis Using Second Harmonic Generation

DTIC Science & Technology

2016-07-01

extracellular matrix through which metastasizing cells must travel. We and others have demonstrated that tumor collagen structure, as measured with the...algorithm using separate training and validation sets, etc. Keywords: metastasis, overtreatment, extracellular matrix , collagen , second harmonic...optical process called second harmonic generation (SHG), influences tumor metastasis. This suggests that collagen structure may provide prognostic
A global reference database of crowdsourced cropland data collected using the Geo-Wiki platform.

PubMed

Laso Bayas, Juan Carlos; Lesiv, Myroslava; Waldner, François; Schucknecht, Anne; Duerauer, Martina; See, Linda; Fritz, Steffen; Fraisl, Dilek; Moorthy, Inian; McCallum, Ian; Perger, Christoph; Danylo, Olha; Defourny, Pierre; Gallego, Javier; Gilliams, Sven; Akhtar, Ibrar Ul Hassan; Baishya, Swarup Jyoti; Baruah, Mrinal; Bungnamei, Khangsembou; Campos, Alfredo; Changkakati, Trishna; Cipriani, Anna; Das, Krishna; Das, Keemee; Das, Inamani; Davis, Kyle Frankel; Hazarika, Purabi; Johnson, Brian Alan; Malek, Ziga; Molinari, Monia Elisa; Panging, Kripal; Pawe, Chandra Kant; Pérez-Hoyos, Ana; Sahariah, Parag Kumar; Sahariah, Dhrubajyoti; Saikia, Anup; Saikia, Meghna; Schlesinger, Peter; Seidacaru, Elena; Singha, Kuleswar; Wilson, John W

2017-09-26

A global reference data set on cropland was collected through a crowdsourcing campaign using the Geo-Wiki crowdsourcing tool. The campaign lasted three weeks, with over 80 participants from around the world reviewing almost 36,000 sample units, focussing on cropland identification. For quality assessment purposes, two additional data sets are provided. The first is a control set of 1,793 sample locations validated by students trained in satellite image interpretation. This data set was used to assess the quality of the crowd as the campaign progressed. The second data set contains 60 expert validations for additional evaluation of the quality of the contributions. All data sets are split into two parts: the first part shows all areas classified as cropland and the second part shows cropland average per location and user. After further processing, the data presented here might be suitable to validate and compare medium and high resolution cropland maps generated using remote sensing. These could also be used to train classification algorithms for developing new maps of land cover and cropland extent.
A global reference database of crowdsourced cropland data collected using the Geo-Wiki platform

PubMed Central

Laso Bayas, Juan Carlos; Lesiv, Myroslava; Waldner, François; Schucknecht, Anne; Duerauer, Martina; See, Linda; Fritz, Steffen; Fraisl, Dilek; Moorthy, Inian; McCallum, Ian; Perger, Christoph; Danylo, Olha; Defourny, Pierre; Gallego, Javier; Gilliams, Sven; Akhtar, Ibrar ul Hassan; Baishya, Swarup Jyoti; Baruah, Mrinal; Bungnamei, Khangsembou; Campos, Alfredo; Changkakati, Trishna; Cipriani, Anna; Das, Krishna; Das, Keemee; Das, Inamani; Davis, Kyle Frankel; Hazarika, Purabi; Johnson, Brian Alan; Malek, Ziga; Molinari, Monia Elisa; Panging, Kripal; Pawe, Chandra Kant; Pérez-Hoyos, Ana; Sahariah, Parag Kumar; Sahariah, Dhrubajyoti; Saikia, Anup; Saikia, Meghna; Schlesinger, Peter; Seidacaru, Elena; Singha, Kuleswar; Wilson, John W

2017-01-01

A global reference data set on cropland was collected through a crowdsourcing campaign using the Geo-Wiki crowdsourcing tool. The campaign lasted three weeks, with over 80 participants from around the world reviewing almost 36,000 sample units, focussing on cropland identification. For quality assessment purposes, two additional data sets are provided. The first is a control set of 1,793 sample locations validated by students trained in satellite image interpretation. This data set was used to assess the quality of the crowd as the campaign progressed. The second data set contains 60 expert validations for additional evaluation of the quality of the contributions. All data sets are split into two parts: the first part shows all areas classified as cropland and the second part shows cropland average per location and user. After further processing, the data presented here might be suitable to validate and compare medium and high resolution cropland maps generated using remote sensing. These could also be used to train classification algorithms for developing new maps of land cover and cropland extent. PMID:28949323
A global reference database of crowdsourced cropland data collected using the Geo-Wiki platform

NASA Astrophysics Data System (ADS)

Laso Bayas, Juan Carlos; Lesiv, Myroslava; Waldner, François; Schucknecht, Anne; Duerauer, Martina; See, Linda; Fritz, Steffen; Fraisl, Dilek; Moorthy, Inian; McCallum, Ian; Perger, Christoph; Danylo, Olha; Defourny, Pierre; Gallego, Javier; Gilliams, Sven; Akhtar, Ibrar Ul Hassan; Baishya, Swarup Jyoti; Baruah, Mrinal; Bungnamei, Khangsembou; Campos, Alfredo; Changkakati, Trishna; Cipriani, Anna; Das, Krishna; Das, Keemee; Das, Inamani; Davis, Kyle Frankel; Hazarika, Purabi; Johnson, Brian Alan; Malek, Ziga; Molinari, Monia Elisa; Panging, Kripal; Pawe, Chandra Kant; Pérez-Hoyos, Ana; Sahariah, Parag Kumar; Sahariah, Dhrubajyoti; Saikia, Anup; Saikia, Meghna; Schlesinger, Peter; Seidacaru, Elena; Singha, Kuleswar; Wilson, John W.

2017-09-01

A global reference data set on cropland was collected through a crowdsourcing campaign using the Geo-Wiki crowdsourcing tool. The campaign lasted three weeks, with over 80 participants from around the world reviewing almost 36,000 sample units, focussing on cropland identification. For quality assessment purposes, two additional data sets are provided. The first is a control set of 1,793 sample locations validated by students trained in satellite image interpretation. This data set was used to assess the quality of the crowd as the campaign progressed. The second data set contains 60 expert validations for additional evaluation of the quality of the contributions. All data sets are split into two parts: the first part shows all areas classified as cropland and the second part shows cropland average per location and user. After further processing, the data presented here might be suitable to validate and compare medium and high resolution cropland maps generated using remote sensing. These could also be used to train classification algorithms for developing new maps of land cover and cropland extent.
Stochastic Hourly Weather Generator HOWGH: Validation and its Use in Pest Modelling under Present and Future Climates

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Hirschi, M.; Spirig, C.

2014-12-01

To quantify impact of the climate change on a specific pest (or any weather-dependent process) in a specific site, we may use a site-calibrated pest (or other) model and compare its outputs obtained with site-specific weather data representing present vs. perturbed climates. The input weather data may be produced by the stochastic weather generator. Apart from the quality of the pest model, the reliability of the results obtained in such experiment depend on an ability of the generator to represent the statistical structure of the real world weather series, and on the sensitivity of the pest model to possible imperfections of the generator. This contribution deals with the multivariate HOWGH weather generator, which is based on a combination of parametric and non-parametric statistical methods. Here, HOWGH is used to generate synthetic hourly series of three weather variables (solar radiation, temperature and precipitation) required by a dynamic pest model SOPRA to simulate the development of codling moth. The contribution presents results of the direct and indirect validation of HOWGH. In the direct validation, the synthetic series generated by HOWGH (various settings of its underlying model are assumed) are validated in terms of multiple climatic characteristics, focusing on the subdaily wet/dry and hot/cold spells. In the indirect validation, we assess the generator in terms of characteristics derived from the outputs of SOPRA model fed by the observed vs. synthetic series. The weather generator may be used to produce weather series representing present and future climates. In the latter case, the parameters of the generator may be modified by the climate change scenarios based on Global or Regional Climate Models. To demonstrate this feature, the results of codling moth simulations for future climate will be shown. Acknowledgements: The weather generator is developed and validated within the frame of projects WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR), and VALUE (COST ES 1102 action).
Solar power generation system for reducing leakage current

NASA Astrophysics Data System (ADS)

Wu, Jinn-Chang; Jou, Hurng-Liahng; Hung, Chih-Yi

2018-04-01

This paper proposes a transformer-less multi-level solar power generation system. This solar power generation system is composed of a solar cell array, a boost power converter, an isolation switch set and a full-bridge inverter. A unipolar pulse-width modulation (PWM) strategy is used in the full-bridge inverter to attenuate the output ripple current. Circuit isolation is accomplished by integrating the isolation switch set between the solar cell array and the utility, to suppress the leakage current. The isolation switch set also determines the DC bus voltage for the full-bridge inverter connecting to the solar cell array or the output of the boost power converter. Accordingly, the proposed transformer-less multi-level solar power generation system generates a five-level voltage, and the partial power of the solar cell array is also converted to AC power using only the full-bridge inverter, so the power efficiency is increased. A prototype is developed to validate the performance of the proposed transformer-less multi-level solar power generation system.
Development and validation of a registry-based definition of eosinophilic esophagitis in Denmark

PubMed Central

Dellon, Evan S; Erichsen, Rune; Pedersen, Lars; Shaheen, Nicholas J; Baron, John A; Sørensen, Henrik T; Vyberg, Mogens

2013-01-01

AIM: To develop and validate a case definition of eosinophilic esophagitis (EoE) in the linked Danish health registries. METHODS: For case definition development, we queried the Danish medical registries from 2006-2007 to identify candidate cases of EoE in Northern Denmark. All International Classification of Diseases-10 (ICD-10) and prescription codes were obtained, and archived pathology slides were obtained and re-reviewed to determine case status. We used an iterative process to select inclusion/exclusion codes, refine the case definition, and optimize sensitivity and specificity. We then re-queried the registries from 2008-2009 to yield a validation set. The case definition algorithm was applied, and sensitivity and specificity were calculated. RESULTS: Of the 51 and 49 candidate cases identified in both the development and validation sets, 21 and 24 had EoE, respectively. Characteristics of EoE cases in the development set [mean age 35 years; 76% male; 86% dysphagia; 103 eosinophils per high-power field (eos/hpf)] were similar to those in the validation set (mean age 42 years; 83% male; 67% dysphagia; 77 eos/hpf). Re-review of archived slides confirmed that the pathology coding for esophageal eosinophilia was correct in greater than 90% of cases. Two registry-based case algorithms based on pathology, ICD-10, and pharmacy codes were successfully generated in the development set, one that was sensitive (90%) and one that was specific (97%). When these algorithms were applied to the validation set, they remained sensitive (88%) and specific (96%). CONCLUSION: Two registry-based definitions, one highly sensitive and one highly specific, were developed and validated for the linked Danish national health databases, making future population-based studies feasible. PMID:23382628
Constructing a question bank based on script concordance approach as a novel assessment methodology in surgical education.

PubMed

Aldekhayel, Salah A; Alselaim, Nahar A; Magzoub, Mohi Eldin; Al-Qattan, Mohammad M; Al-Namlah, Abdullah M; Tamim, Hani; Al-Khayal, Abdullah; Al-Habdan, Sultan I; Zamakhshary, Mohammed F

2012-10-24

Script Concordance Test (SCT) is a new assessment tool that reliably assesses clinical reasoning skills. Previous descriptions of developing SCT-question banks were merely subjective. This study addresses two gaps in the literature: 1) conducting the first phase of a multistep validation process of SCT in Plastic Surgery, and 2) providing an objective methodology to construct a question bank based on SCT. After developing a test blueprint, 52 test items were written. Five validation questions were developed and a validation survey was established online. Seven reviewers were asked to answer this survey. They were recruited from two countries, Saudi Arabia and Canada, to improve the test's external validity. Their ratings were transformed into percentages. Analysis was performed to compare reviewers' ratings by looking at correlations, ranges, means, medians, and overall scores. Scores of reviewers' ratings were between 76% and 95% (mean 86% ± 5). We found poor correlations between reviewers (Pearson's: +0.38 to -0.22). Ratings of individual validation questions ranged between 0 and 4 (on a scale 1-5). Means and medians of these ranges were computed for each test item (mean: 0.8 to 2.4; median: 1 to 3). A subset of test items comprising 27 items was generated based on a set of inclusion and exclusion criteria. This study proposes an objective methodology for validation of SCT-question bank. Analysis of validation survey is done from all angles, i.e., reviewers, validation questions, and test items. Finally, a subset of test items is generated based on a set of criteria.
The FIRE Project

NASA Technical Reports Server (NTRS)

Mcdougal, D.

1986-01-01

The International Satellite Cloud Climatology Project's (ISCCP) First ISCCP Regional Experiment (FIRE) project is a program to validate the cloud parameters derived by the ISCCP. The 4- to 5-year program will concentrate on clouds in the continental United States, particularly cirrus and marine stratocumulus clouds. As part of the validation process, FIRE will acquire satellite, aircraft, balloon, and surface data. These data (except for the satellite data) will be amalgamated into one common data set. Plans are to generate a standardized format structure for use in the PCDS. Data collection will begin in April 1986, but will not be available to the general scientific community until 1987 or 1988. Additional pertinent data sets already reside in the PCDS. Other qualifications of the PCDS for use in this validation program were enumerated.
The Abbott RealTime High Risk HPV test is a clinically validated human papillomavirus assay for triage in the referral population and use in primary cervical cancer screening in women 30 years and older: a review of validation studies.

PubMed

Poljak, Mario; Oštrbenk, Anja

2013-01-01

Human papillomavirus (HPV) testing has become an essential part of current clinical practice in the management of cervical cancer and precancerous lesions. We reviewed the most important validation studies of a next-generation real-time polymerase chain reaction-based assay, the RealTime High Risk HPV test (RealTime)(Abbott Molecular, Des Plaines, IL, USA), for triage in referral population settings and for use in primary cervical cancer screening in women 30 years and older published in peer-reviewed journals from 2009 to 2013. RealTime is designed to detect 14 high-risk HPV genotypes with concurrent distinction of HPV-16 and HPV-18 from 12 other HPV genotypes. The test was launched on the European market in January 2009 and is currently used in many laboratories worldwide for routine detection of HPV. We concisely reviewed validation studies of a next-generation real-time polymerase chain reaction (PCR)-based assay: the Abbott RealTime High Risk HPV test. Eight validation studies of RealTime in referral settings showed its consistently high absolute clinical sensitivity for both CIN2+ (range 88.3-100%) and CIN3+ (range 93.0-100%), as well as comparative clinical sensitivity relative to the currently most widely used HPV test: the Qiagen/Digene Hybrid Capture 2 HPV DNA Test (HC2). Due to the significantly different composition of the referral populations, RealTime absolute clinical specificity for CIN2+ and CIN3+ varied greatly across studies, but was comparable relative to HC2. Four validation studies of RealTime performance in cervical cancer screening settings showed its consistently high absolute clinical sensitivity for both CIN2+ and CIN3+, as well as comparative clinical sensitivity and specificity relative to HC2 and GP5+/6+ PCR. RealTime has been extensively evaluated in the last 4 years. RealTime can be considered clinically validated for triage in referral population settings and for use in primary cervical cancer screening in women 30 years and older.
Endogenous protein "barcode" for data validation and normalization in quantitative MS analysis.

PubMed

Lee, Wooram; Lazar, Iulia M

2014-07-01

Quantitative proteomic experiments with mass spectrometry detection are typically conducted by using stable isotope labeling and label-free quantitation approaches. Proteins with housekeeping functions and stable expression level such actin, tubulin, and glyceraldehyde-3-phosphate dehydrogenase are frequently used as endogenous controls. Recent studies have shown that the expression level of such common housekeeping proteins is, in fact, dependent on various factors such as cell type, cell cycle, or disease status and can change in response to a biochemical stimulation. The interference of such phenomena can, therefore, substantially compromise their use for data validation, alter the interpretation of results, and lead to erroneous conclusions. In this work, we advance the concept of a protein "barcode" for data normalization and validation in quantitative proteomic experiments. The barcode comprises a novel set of proteins that was generated from cell cycle experiments performed with MCF7, an estrogen receptor positive breast cancer cell line, and MCF10A, a nontumorigenic immortalized breast cell line. The protein set was selected from a list of ~3700 proteins identified in different cellular subfractions and cell cycle stages of MCF7/MCF10A cells, based on the stability of spectral count data generated with an LTQ ion trap mass spectrometer. A total of 11 proteins qualified as endogenous standards for the nuclear and 62 for the cytoplasmic barcode, respectively. The validation of the protein sets was performed with a complementary SKBR3/Her2+ cell line.
The International Classification of Functioning (ICF) core set for breast cancer from the perspective of women with the condition.

PubMed

Cooney, Marese; Galvin, Rose; Connolly, Elizabeth; Stokes, Emma

2013-05-01

The ICF Core Set for breast cancer was generated by international experts for women who have had surgery and radiation but it has not yet been validated. The objective of the study was to validate the ICF Core Set from the perspective of women with breast cancer. A qualitative focus group methodology was used. The sessions were transcribed verbatim. Meaning units were identified by two independent researchers. The agreed list was subsequently linked to ICF categories by two independent researchers according to pre-defined linking rules. Data saturation determined the number of focus groups conducted. Quality of the data analyses was assured by multiple coding and peer review. Thirty-four women participated in seven focus groups. A total of 1621 meaning units were identified which were linked to 74 of the existing 80 Core Set categories. Additional ICF categories not currently included in the Core Set were identified by the women. The validity of the Core Set was largely supported. However, some categories currently not covered by the ICF Core Set for Breast Cancer will need to be considered for inclusion if the Core Set is to reflect all women who have had treatment for breast cancer
An algorithm for deciding the number of clusters and validating using simulated data with application to exploring crop population structure

USDA-ARS?s Scientific Manuscript database

A first step in exploring population structure in crop plants and other organisms is to define the number of subpopulations that exist for a given data set. The genetic marker data sets being generated have become increasingly large over time and commonly are the high-dimension, low sample size (HDL...
Maximum unbiased validation (MUV) data sets for virtual screening based on PubChem bioactivity data.

PubMed

Rohrer, Sebastian G; Baumann, Knut

2009-02-01

Refined nearest neighbor analysis was recently introduced for the analysis of virtual screening benchmark data sets. It constitutes a technique from the field of spatial statistics and provides a mathematical framework for the nonparametric analysis of mapped point patterns. Here, refined nearest neighbor analysis is used to design benchmark data sets for virtual screening based on PubChem bioactivity data. A workflow is devised that purges data sets of compounds active against pharmaceutically relevant targets from unselective hits. Topological optimization using experimental design strategies monitored by refined nearest neighbor analysis functions is applied to generate corresponding data sets of actives and decoys that are unbiased with regard to analogue bias and artificial enrichment. These data sets provide a tool for Maximum Unbiased Validation (MUV) of virtual screening methods. The data sets and a software package implementing the MUV design workflow are freely available at http://www.pharmchem.tu-bs.de/lehre/baumann/MUV.html.
Evaluating Gene Set Enrichment Analysis Via a Hybrid Data Model

PubMed Central

Hua, Jianping; Bittner, Michael L.; Dougherty, Edward R.

2014-01-01

Gene set enrichment analysis (GSA) methods have been widely adopted by biological labs to analyze data and generate hypotheses for validation. Most of the existing comparison studies focus on whether the existing GSA methods can produce accurate P-values; however, practitioners are often more concerned with the correct gene-set ranking generated by the methods. The ranking performance is closely related to two critical goals associated with GSA methods: the ability to reveal biological themes and ensuring reproducibility, especially for small-sample studies. We have conducted a comprehensive simulation study focusing on the ranking performance of seven representative GSA methods. We overcome the limitation on the availability of real data sets by creating hybrid data models from existing large data sets. To build the data model, we pick a master gene from the data set to form the ground truth and artificially generate the phenotype labels. Multiple hybrid data models can be constructed from one data set and multiple data sets of smaller sizes can be generated by resampling the original data set. This approach enables us to generate a large batch of data sets to check the ranking performance of GSA methods. Our simulation study reveals that for the proposed data model, the Q2 type GSA methods have in general better performance than other GSA methods and the global test has the most robust results. The properties of a data set play a critical role in the performance. For the data sets with highly connected genes, all GSA methods suffer significantly in performance. PMID:24558298
The Flexibility Scale: Development and Preliminary Validation of a Cognitive Flexibility Measure in Children with Autism Spectrum Disorders.

PubMed

Strang, John F; Anthony, Laura G; Yerys, Benjamin E; Hardy, Kristina K; Wallace, Gregory L; Armour, Anna C; Dudley, Katerina; Kenworthy, Lauren

2017-08-01

Flexibility is a key component of executive function, and is related to everyday functioning and adult outcomes. However, existing informant reports do not densely sample cognitive aspects of flexibility; the Flexibility Scale (FS) was developed to address this gap. This study investigates the validity of the FS in 221 youth with ASD and 57 typically developing children. Exploratory factor analysis indicates a five-factor scale: Routines/rituals, transitions/change, special interests, social flexibility, and generativity. The FS demonstrated convergent and divergent validity with comparative domains of function in other measures, save for the Generativity factor. The FS discriminated participants with ASD and controls. Thus, this study suggests the FS may be a viable, comprehensive measure of flexibility in everyday settings.
TargetMiner: microRNA target prediction with systematic identification of tissue-specific negative examples.

PubMed

Bandyopadhyay, Sanghamitra; Mitra, Ramkrishna

2009-10-15

Prediction of microRNA (miRNA) target mRNAs using machine learning approaches is an important area of research. However, most of the methods suffer from either high false positive or false negative rates. One reason for this is the marked deficiency of negative examples or miRNA non-target pairs. Systematic identification of non-target mRNAs is still not addressed properly, and therefore, current machine learning approaches are compelled to rely on artificially generated negative examples for training. In this article, we have identified approximately 300 tissue-specific negative examples using a novel approach that involves expression profiling of both miRNAs and mRNAs, miRNA-mRNA structural interactions and seed-site conservation. The newly generated negative examples are validated with pSILAC dataset, which elucidate the fact that the identified non-targets are indeed non-targets.These high-throughput tissue-specific negative examples and a set of experimentally verified positive examples are then used to build a system called TargetMiner, a support vector machine (SVM)-based classifier. In addition to assessing the prediction accuracy on cross-validation experiments, TargetMiner has been validated with a completely independent experimental test dataset. Our method outperforms 10 existing target prediction algorithms and provides a good balance between sensitivity and specificity that is not reflected in the existing methods. We achieve a significantly higher sensitivity and specificity of 69% and 67.8% based on a pool of 90 feature set and 76.5% and 66.1% using a set of 30 selected feature set on the completely independent test dataset. In order to establish the effectiveness of the systematically generated negative examples, the SVM is trained using a different set of negative data generated using the method in Yousef et al. A significantly higher false positive rate (70.6%) is observed when tested on the independent set, while all other factors are kept the same. Again, when an existing method (NBmiRTar) is executed with the our proposed negative data, we observe an improvement in its performance. These clearly establish the effectiveness of the proposed approach of selecting the negative examples systematically. TargetMiner is now available as an online tool at www.isical.ac.in/ approximately bioinfo_miu
Simulation of the transient processes of load rejection under different accident conditions in a hydroelectric generating set

NASA Astrophysics Data System (ADS)

Guo, W. C.; Yang, J. D.; Chen, J. P.; Peng, Z. Y.; Zhang, Y.; Chen, C. C.

2016-11-01

Load rejection test is one of the essential tests that carried out before the hydroelectric generating set is put into operation formally. The test aims at inspecting the rationality of the design of the water diversion and power generation system of hydropower station, reliability of the equipment of generating set and the dynamic characteristics of hydroturbine governing system. Proceeding from different accident conditions of hydroelectric generating set, this paper presents the transient processes of load rejection corresponding to different accident conditions, and elaborates the characteristics of different types of load rejection. Then the numerical simulation method of different types of load rejection is established. An engineering project is calculated to verify the validity of the method. Finally, based on the numerical simulation results, the relationship among the different types of load rejection and their functions on the design of hydropower station and the operation of load rejection test are pointed out. The results indicate that: The load rejection caused by the accident within the hydroelectric generating set is realized by emergency distributing valve, and it is the basis of the optimization for the closing law of guide vane and the calculation of regulation and guarantee. The load rejection caused by the accident outside the hydroelectric generating set is realized by the governor. It is the most efficient measure to inspect the dynamic characteristics of hydro-turbine governing system, and its closure rate of guide vane set in the governor depends on the optimization result in the former type load rejection.
A Mode Propagation Database Suitable for Code Validation Utilizing the NASA Glenn Advanced Noise Control Fan and Artificial Sources

NASA Technical Reports Server (NTRS)

Sutliff, Daniel L.

2014-01-01

The NASA Glenn Research Center's Advanced Noise Control Fan (ANCF) was developed in the early 1990s to provide a convenient test bed to measure and understand fan-generated acoustics, duct propagation, and radiation to the farfield. A series of tests were performed primarily for the use of code validation and tool validation. Rotating Rake mode measurements were acquired for parametric sets of: (i) mode blockage, (ii) liner insertion loss, (iii) short ducts, and (iv) mode reflection.

A Mode Propagation Database Suitable for Code Validation Utilizing the NASA Glenn Advanced Noise Control Fan and Artificial Sources

NASA Technical Reports Server (NTRS)

Sutliff, Daniel L.

2014-01-01

The NASA Glenn Research Center's Advanced Noise Control Fan (ANCF) was developed in the early 1990s to provide a convenient test bed to measure and understand fan-generated acoustics, duct propagation, and radiation to the farfield. A series of tests were performed primarily for the use of code validation and tool validation. Rotating Rake mode measurements were acquired for parametric sets of: (1) mode blockage, (2) liner insertion loss, (3) short ducts, and (4) mode reflection.
Multiyear Plan for Validation of EnergyPlus Multi-Zone HVAC System Modeling using ORNL's Flexible Research Platform

DOE Office of Scientific and Technical Information (OSTI.GOV)

Im, Piljae; Bhandari, Mahabir S.; New, Joshua Ryan

This document describes the Oak Ridge National Laboratory (ORNL) multiyear experimental plan for validation and uncertainty characterization of whole-building energy simulation for a multi-zone research facility using a traditional rooftop unit (RTU) as a baseline heating, ventilating, and air conditioning (HVAC) system. The project’s overarching objective is to increase the accuracy of energy simulation tools by enabling empirical validation of key inputs and algorithms. Doing so is required to inform the design of increasingly integrated building systems and to enable accountability for performance gaps between design and operation of a building. The project will produce documented data sets that canmore » be used to validate key functionality in different energy simulation tools and to identify errors and inadequate assumptions in simulation engines so that developers can correct them. ASHRAE Standard 140, Method of Test for the Evaluation of Building Energy Analysis Computer Programs (ASHRAE 2004), currently consists primarily of tests to compare different simulation programs with one another. This project will generate sets of measured data to enable empirical validation, incorporate these test data sets in an extended version of Standard 140, and apply these tests to the Department of Energy’s (DOE) EnergyPlus software (EnergyPlus 2016) to initiate the correction of any significant deficiencies. The fitness-for-purpose of the key algorithms in EnergyPlus will be established and demonstrated, and vendors of other simulation programs will be able to demonstrate the validity of their products. The data set will be equally applicable to validation of other simulation engines as well.« less
Correcting for Optimistic Prediction in Small Data Sets

PubMed Central

Smith, Gordon C. S.; Seaman, Shaun R.; Wood, Angela M.; Royston, Patrick; White, Ian R.

2014-01-01

The C statistic is a commonly reported measure of screening test performance. Optimistic estimation of the C statistic is a frequent problem because of overfitting of statistical models in small data sets, and methods exist to correct for this issue. However, many studies do not use such methods, and those that do correct for optimism use diverse methods, some of which are known to be biased. We used clinical data sets (United Kingdom Down syndrome screening data from Glasgow (1991–2003), Edinburgh (1999–2003), and Cambridge (1990–2006), as well as Scottish national pregnancy discharge data (2004–2007)) to evaluate different approaches to adjustment for optimism. We found that sample splitting, cross-validation without replication, and leave-1-out cross-validation produced optimism-adjusted estimates of the C statistic that were biased and/or associated with greater absolute error than other available methods. Cross-validation with replication, bootstrapping, and a new method (leave-pair-out cross-validation) all generated unbiased optimism-adjusted estimates of the C statistic and had similar absolute errors in the clinical data set. Larger simulation studies confirmed that all 3 methods performed similarly with 10 or more events per variable, or when the C statistic was 0.9 or greater. However, with lower events per variable or lower C statistics, bootstrapping tended to be optimistic but with lower absolute and mean squared errors than both methods of cross-validation. PMID:24966219
Legitimacy and Justice Perceptions

ERIC Educational Resources Information Center

Mueller, Charles W.; Landsman, Miriam J.

2004-01-01

Consistent with the theoretical argument of Hegtvedt and Johnson, we empirically examine the relationship between collectivity-generated legitimacy of reward procedures and individual-level justice perceptions about reward distributions. Using data from a natural setting, we find that collectivity sources of validity (authorization and…
Validation of two (parametric vs non-parametric) daily weather generators

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Skalak, P.

2015-12-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed-like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30-years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database. Acknowledgements: The weather generator is developed and validated within the frame of projects WG4VALUE (sponsored by the Ministry of Education, Youth and Sports of CR), and VALUE (COST ES 1102 action).
Developing Enhanced Blood–Brain Barrier Permeability Models: Integrating External Bio-Assay Data in QSAR Modeling

PubMed Central

Wang, Wenyi; Kim, Marlene T.; Sedykh, Alexander

2015-01-01

Purpose Experimental Blood–Brain Barrier (BBB) permeability models for drug molecules are expensive and time-consuming. As alternative methods, several traditional Quantitative Structure-Activity Relationship (QSAR) models have been developed previously. In this study, we aimed to improve the predictivity of traditional QSAR BBB permeability models by employing relevant public bio-assay data in the modeling process. Methods We compiled a BBB permeability database consisting of 439 unique compounds from various resources. The database was split into a modeling set of 341 compounds and a validation set of 98 compounds. Consensus QSAR modeling workflow was employed on the modeling set to develop various QSAR models. A five-fold cross-validation approach was used to validate the developed models, and the resulting models were used to predict the external validation set compounds. Furthermore, we used previously published membrane transporter models to generate relevant transporter profiles for target compounds. The transporter profiles were used as additional biological descriptors to develop hybrid QSAR BBB models. Results The consensus QSAR models have R2=0.638 for fivefold cross-validation and R2=0.504 for external validation. The consensus model developed by pooling chemical and transporter descriptors showed better predictivity (R2=0.646 for five-fold cross-validation and R2=0.526 for external validation). Moreover, several external bio-assays that correlate with BBB permeability were identified using our automatic profiling tool. Conclusions The BBB permeability models developed in this study can be useful for early evaluation of new compounds (e.g., new drug candidates). The combination of chemical and biological descriptors shows a promising direction to improve the current traditional QSAR models. PMID:25862462
Design, synthesis and screening studies of potent thiazol-2-amine derivatives as fibroblast growth factor receptor 1 inhibitors.

PubMed

Kumar, B V S Suneel; Lakshmi, Narasu; Kumar, M Ravi; Rambabu, Gundla; Manjashetty, Thimmappa H; Arunasree, Kalle M; Sriram, Dharmarajan; Ramkumar, Kavya; Neamati, Nouri; Dayam, Raveendra; Sarma, J A R P

2014-01-01

Fibroblast growth factor receptor 1 (FGFR1) a tyrosine kinase receptor, plays important roles in angiogenesis, embryonic development, cell proliferation, cell differentiation, and wound healing. The FGFR isoforms and their receptors (FGFRs) considered as a potential targets and under intense research to design potential anticancer agents. Fibroblast growth factors (FGF's) and its growth factor receptors (FGFR) plays vital role in one of the critical pathway in monitoring angiogenesis. In the current study, quantitative pharmacophore models were generated and validated using known FGFR1 inhibitors. The pharmacophore models were generated using a set of 28 compounds (training). The top pharmacophore model was selected and validated using a set of 126 compounds (test set) and also using external validation. The validated pharmacophore was considered as a virtual screening query to screen a database of 400,000 virtual molecules and pharmacophore model retrieved 2800 hits. The retrieved hits were subsequently filtered based on the fit value. The selected hits were subjected for docking studies to observe the binding modes of the retrieved hits and also to reduce the false positives. One of the potential hits (thiazole-2-amine derivative) was selected based the pharmacophore fit value, dock score, and synthetic feasibility. A few analogues of the thiazole-2-amine derivative were synthesized. These compounds were screened for FGFR1 activity and anti-proliferative studies. The top active compound showed 56.87% inhibition of FGFR1 activity at 50 µM and also showed good cellular activity. Further optimization of thiazole-2-amine derivatives is in progress.
Scale/TSUNAMI Sensitivity Data for ICSBEP Evaluations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rearden, Bradley T; Reed, Davis Allan; Lefebvre, Robert A

2011-01-01

The Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI) software developed at Oak Ridge National Laboratory (ORNL) as part of the Scale code system provide unique methods for code validation, gap analysis, and experiment design. For TSUNAMI analysis, sensitivity data are generated for each application and each existing or proposed experiment used in the assessment. The validation of diverse sets of applications requires potentially thousands of data files to be maintained and organized by the user, and a growing number of these files are available through the International Handbook of Evaluated Criticality Safety Benchmark Experiments (IHECSBE) distributed through themore » International Criticality Safety Benchmark Evaluation Program (ICSBEP). To facilitate the use of the IHECSBE benchmarks in rigorous TSUNAMI validation and gap analysis techniques, ORNL generated SCALE/TSUNAMI sensitivity data files (SDFs) for several hundred benchmarks for distribution with the IHECSBE. For the 2010 edition of IHECSBE, the sensitivity data were generated using 238-group cross-section data based on ENDF/B-VII.0 for 494 benchmark experiments. Additionally, ORNL has developed a quality assurance procedure to guide the generation of Scale inputs and sensitivity data, as well as a graphical user interface to facilitate the use of sensitivity data in identifying experiments and applying them in validation studies.« less
NASA TLA workload analysis support. Volume 2: Metering and spacing studies validation data

NASA Technical Reports Server (NTRS)

Sundstrom, J. L.

1980-01-01

Four sets of graphic reports--one for each of the metering and spacing scenarios--are presented. The complete data file from which the reports were generated is also given. The data was used to validate the detail task of both the pilot and copilot for four metering and spacing scenarios. The output presents two measures of demand workload and a report showing task length and task interaction.
Validating Innovative Renewable Energy Technologies: ESTCP Demonstrations at Two DoD Facilities

DTIC Science & Technology

2011-11-01

4. TITLE AND SUBTITLE Validating Innovative Renewable Energy Technologies: ESTCP Demonstrations at Two DoD Facilities 5a. CONTRACT NUMBER 5b...goals of 25% of energy consumed required to be from renewable energy by 2025, the DoD has set aggressive, yet achievable targets. With its array of land...holdings facilities, and environments, the potential for renewable energy generation on DoD lands is great. Reaching these goals will require
Stochastically generating tree diameter lists to populate forest stands based on the linkage variables forest type and stand age

Treesearch

Bernard R. Parresol; F. Thomas Lloyd

2003-01-01

Forest inventory data were used to develop a standage-driven, stochastic predictor of unit-area, frequency weighted lists of breast high tree diameters (DBH). The average of mean statistics from 40 simulation prediction sets of an independent 78-plot validation dataset differed from the observed validation means by 0.5 cm for DBH, and by 12 trees/h for density. The 40...
The FORBIO Climate data set for climate analyses

NASA Astrophysics Data System (ADS)

Delvaux, C.; Journée, M.; Bertrand, C.

2015-06-01

In the framework of the interdisciplinary FORBIO Climate research project, the Royal Meteorological Institute of Belgium is in charge of providing high resolution gridded past climate data (i.e. temperature and precipitation). This climate data set will be linked to the measurements on seedlings, saplings and mature trees to assess the effects of climate variation on tree performance. This paper explains how the gridded daily temperature (minimum and maximum) data set was generated from a consistent station network between 1980 and 2013. After station selection, data quality control procedures were developed and applied to the station records to ensure that only valid measurements will be involved in the gridding process. Thereafter, the set of unevenly distributed validated temperature data was interpolated on a 4 km × 4 km regular grid over Belgium. The performance of different interpolation methods has been assessed. The method of kriging with external drift using correlation between temperature and altitude gave the most relevant results.
Generating Ground Reference Data for a Global Impervious Surface Survey

NASA Technical Reports Server (NTRS)

Tilton, James C.; De Colstoun, Eric Brown; Wolfe, Robert E.; Tan, Bin; Huang, Chengquan

2012-01-01

We are developing an approach for generating ground reference data in support of a project to produce a 30m impervious cover data set of the entire Earth for the years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. Since sufficient ground reference data for training and validation is not available from ground surveys, we are developing an interactive tool, called HSegLearn, to facilitate the photo-interpretation of 1 to 2 m spatial resolution imagery data, which we will use to generate the needed ground reference data at 30m. Through the submission of selected region objects and positive or negative examples of impervious surfaces, HSegLearn enables an analyst to automatically select groups of spectrally similar objects from a hierarchical set of image segmentations produced by the HSeg image segmentation program at an appropriate level of segmentation detail, and label these region objects as either impervious or nonimpervious.
Advanced scatter search approach and its application in a sequencing problem of mixed-model assembly lines in a case company

NASA Astrophysics Data System (ADS)

Liu, Qiong; Wang, Wen-xi; Zhu, Ke-ren; Zhang, Chao-yong; Rao, Yun-qing

2014-11-01

Mixed-model assembly line sequencing is significant in reducing the production time and overall cost of production. To improve production efficiency, a mathematical model aiming simultaneously to minimize overtime, idle time and total set-up costs is developed. To obtain high-quality and stable solutions, an advanced scatter search approach is proposed. In the proposed algorithm, a new diversification generation method based on a genetic algorithm is presented to generate a set of potentially diverse and high-quality initial solutions. Many methods, including reference set update, subset generation, solution combination and improvement methods, are designed to maintain the diversification of populations and to obtain high-quality ideal solutions. The proposed model and algorithm are applied and validated in a case company. The results indicate that the proposed advanced scatter search approach is significant for mixed-model assembly line sequencing in this company.
Identifying FGA peptides as nasopharyngeal carcinoma-associated biomarkers by magnetic beads.

PubMed

Tao, Ya-Lan; Li, Yan; Gao, Jin; Liu, Zhi-Gang; Tu, Zi-Wei; Li, Guo; Xu, Bing-Qing; Niu, Dao-Li; Jiang, Chang-Bin; Yi, Wei; Li, Zhi-Qiang; Li, Jing; Wang, Yi-Ming; Cheng, Zhi-Bin; Liu, Qiao-Dan; Bai, Li; Zhang, Chun; Zhang, Jing-Yu; Zeng, Mu-Sheng; Xia, Yun-Fei

2012-07-01

Early diagnosis and treatment is known to improve prognosis for nasopharyngeal carcinoma (NPC). The study determined the specific peptide profiles by comparing the serum differences between NPC patients and healthy controls, and provided the basis for the diagnostic model and identification of specific biomarkers of NPC. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) can be used to detect the molecular mass of peptides. Mass spectra of peptides were generated after extracting and purification of 40 NPC samples in the training set, 21 in the single center validation set and 99 in the multicenter validation set using weak cationic-exchanger magnetic beads. The spectra were analyzed statistically using FlexAnalysis™ and ClinProt™ bioinformatics software. The four most significant peaks were selected out to train a genetic algorithm model to diagnose NPC. The diagnostic sensitivity and specificity were 100% and 100% in the training set, 90.5% and 88.9% in the single center validation set, 91.9% and 83.3% in the multicenter validation set, and the false positive rate (FPR) and false negative rate (FNR) were obviously lower in the NPC group (FPR, 16.7%; FNR, 8.1%) than in the other cancer group (FPR, 39%; FNR, 61%), respectively. So, the diagnostic model including four peptides can be suitable for NPC but not for other cancers. FGA peptide fragments identified may serve as tumor-associated biomarkers for NPC. Copyright © 2012 Wiley Periodicals, Inc.
Generating Broad-Scale Forest Ownership Maps: A Closest-Neighbor Approach

Treesearch

Brett J. Butler

2005-01-01

A closest-neighbor method for producing a forest ownership map using remotely sensed imagery and point-based ownership information is presented for the Northeastern United States. Based on a validation data set, this method had an accuracy rate of 58 percent.
Building and validating a prediction model for paediatric type 1 diabetes risk using next generation targeted sequencing of class II HLA genes.

PubMed

Zhao, Lue Ping; Carlsson, Annelie; Larsson, Helena Elding; Forsander, Gun; Ivarsson, Sten A; Kockum, Ingrid; Ludvigsson, Johnny; Marcus, Claude; Persson, Martina; Samuelsson, Ulf; Örtqvist, Eva; Pyo, Chul-Woo; Bolouri, Hamid; Zhao, Michael; Nelson, Wyatt C; Geraghty, Daniel E; Lernmark, Åke

2017-11-01

It is of interest to predict possible lifetime risk of type 1 diabetes (T1D) in young children for recruiting high-risk subjects into longitudinal studies of effective prevention strategies. Utilizing a case-control study in Sweden, we applied a recently developed next generation targeted sequencing technology to genotype class II genes and applied an object-oriented regression to build and validate a prediction model for T1D. In the training set, estimated risk scores were significantly different between patients and controls (P = 8.12 × 10 -92 ), and the area under the curve (AUC) from the receiver operating characteristic (ROC) analysis was 0.917. Using the validation data set, we validated the result with AUC of 0.886. Combining both training and validation data resulted in a predictive model with AUC of 0.903. Further, we performed a "biological validation" by correlating risk scores with 6 islet autoantibodies, and found that the risk score was significantly correlated with IA-2A (Z-score = 3.628, P < 0.001). When applying this prediction model to the Swedish population, where the lifetime T1D risk ranges from 0.5% to 2%, we anticipate identifying approximately 20 000 high-risk subjects after testing all newborns, and this calculation would identify approximately 80% of all patients expected to develop T1D in their lifetime. Through both empirical and biological validation, we have established a prediction model for estimating lifetime T1D risk, using class II HLA. This prediction model should prove useful for future investigations to identify high-risk subjects for prevention research in high-risk populations. Copyright © 2017 John Wiley & Sons, Ltd.
Understanding Dynamic Model Validation of a Wind Turbine Generator and a Wind Power Plant: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muljadi, Eduard; Zhang, Ying Chen; Gevorgian, Vahan

Regional reliability organizations require power plants to validate the dynamic models that represent them to ensure that power systems studies are performed to the best representation of the components installed. In the process of validating a wind power plant (WPP), one must be cognizant of the parameter settings of the wind turbine generators (WTGs) and the operational settings of the WPP. Validating the dynamic model of a WPP is required to be performed periodically. This is because the control parameters of the WTGs and the other supporting components within a WPP may be modified to comply with new grid codesmore » or upgrades to the WTG controller with new capabilities developed by the turbine manufacturers or requested by the plant owners or operators. The diversity within a WPP affects the way we represent it in a model. Diversity within a WPP may be found in the way the WTGs are controlled, the wind resource, the layout of the WPP (electrical diversity), and the type of WTGs used. Each group of WTGs constitutes a significant portion of the output power of the WPP, and their unique and salient behaviors should be represented individually. The objective of this paper is to illustrate the process of dynamic model validations of WTGs and WPPs, the available data recorded that must be screened before it is used for the dynamic validations, and the assumptions made in the dynamic models of the WTG and WPP that must be understood. Without understanding the correct process, the validations may lead to the wrong representations of the WTG and WPP modeled.« less
Parametric vs. non-parametric daily weather generator: validation and comparison

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin

2016-04-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30 years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database.
A combined ligand-based and target-based drug design approach for G-protein coupled receptors: application to salvinorin A, a selective kappa opioid receptor agonist

NASA Astrophysics Data System (ADS)

Singh, Nidhi; Chevé, Gwénaël; Ferguson, David M.; McCurdy, Christopher R.

2006-08-01

Combined ligand-based and target-based drug design approaches provide a synergistic advantage over either method individually. Therefore, we set out to develop a powerful virtual screening model to identify novel molecular scaffolds as potential leads for the human KOP (hKOP) receptor employing a combined approach. Utilizing a set of recently reported derivatives of salvinorin A, a structurally unique KOP receptor agonist, a pharmacophore model was developed that consisted of two hydrogen bond acceptor and three hydrophobic features. The model was cross-validated by randomizing the data using the CatScramble technique. Further validation was carried out using a test set that performed well in classifying active and inactive molecules correctly. Simultaneously, a bovine rhodopsin based "agonist-bound" hKOP receptor model was also generated. The model provided more accurate information about the putative binding site of salvinorin A based ligands. Several protein structure-checking programs were used to validate the model. In addition, this model was in agreement with the mutation experiments carried out on KOP receptor. The predictive ability of the model was evaluated by docking a set of known KOP receptor agonists into the active site of this model. The docked scores correlated reasonably well with experimental p K i values. It is hypothesized that the integration of these two independently generated models would enable a swift and reliable identification of new lead compounds that could reduce time and cost of hit finding within the drug discovery and development process, particularly in the case of GPCRs.

Automatic paper sliceform design from 3D solid models.

PubMed

Le-Nguyen, Tuong-Vu; Low, Kok-Lim; Ruiz, Conrado; Le, Sang N

2013-11-01

A paper sliceform or lattice-style pop-up is a form of papercraft that uses two sets of parallel paper patches slotted together to make a foldable structure. The structure can be folded flat, as well as fully opened (popped-up) to make the two sets of patches orthogonal to each other. Automatic design of paper sliceforms is still not supported by existing computational models and remains a challenge. We propose novel geometric formulations of valid paper sliceform designs that consider the stability, flat-foldability and physical realizability of the designs. Based on a set of sufficient construction conditions, we also present an automatic algorithm for generating valid sliceform designs that closely depict the given 3D solid models. By approximating the input models using a set of generalized cylinders, our method significantly reduces the search space for stable and flat-foldable sliceforms. To ensure the physical realizability of the designs, the algorithm automatically generates slots or slits on the patches such that no two cycles embedded in two different patches are interlocking each other. This guarantees local pairwise assembility between patches, which is empirically shown to lead to global assembility. Our method has been demonstrated on a number of example models, and the output designs have been successfully made into real paper sliceforms.
Development and Validation of a Monte Carlo Simulation Tool for Multi-Pinhole SPECT

PubMed Central

Mok, Greta S. P.; Du, Yong; Wang, Yuchuan; Frey, Eric C.; Tsui, Benjamin M. W.

2011-01-01

Purpose In this work, we developed and validated a Monte Carlo simulation (MCS) tool for investigation and evaluation of multi-pinhole (MPH) SPECT imaging. Procedures This tool was based on a combination of the SimSET and MCNP codes. Photon attenuation and scatter in the object, as well as penetration and scatter through the collimator detector, are modeled in this tool. It allows accurate and efficient simulation of MPH SPECT with focused pinhole apertures and user-specified photon energy, aperture material, and imaging geometry. The MCS method was validated by comparing the point response function (PRF), detection efficiency (DE), and image profiles obtained from point sources and phantom experiments. A prototype single-pinhole collimator and focused four- and five-pinhole collimators fitted on a small animal imager were used for the experimental validations. We have also compared computational speed among various simulation tools for MPH SPECT, including SimSET-MCNP, MCNP, SimSET-GATE, and GATE for simulating projections of a hot sphere phantom. Results We found good agreement between the MCS and experimental results for PRF, DE, and image profiles, indicating the validity of the simulation method. The relative computational speeds for SimSET-MCNP, MCNP, SimSET-GATE, and GATE are 1: 2.73: 3.54: 7.34, respectively, for 120-view simulations. We also demonstrated the application of this MCS tool in small animal imaging by generating a set of low-noise MPH projection data of a 3D digital mouse whole body phantom. Conclusions The new method is useful for studying MPH collimator designs, data acquisition protocols, image reconstructions, and compensation techniques. It also has great potential to be applied for modeling the collimator-detector response with penetration and scatter effects for MPH in the quantitative reconstruction method. PMID:19779896
The Consumer Motivation Scale: A detailed review of item generation, exploration, confirmation, and validation procedures.

PubMed

Barbopoulos, I; Johansson, L-O

2017-08-01

This data article offers a detailed description of analyses pertaining to the development of the Consumer Motivation Scale (CMS), from item generation and the extraction of factors, to confirmation of the factor structure and validation of the emergent dimensions. The established goal structure - consisting of the sub-goals Value for Money, Quality, Safety, Stimulation, Comfort, Ethics, and Social Acceptance - is shown to be related to a variety of consumption behaviors in different contexts and for different products, and should thereby prove useful in standard marketing research, as well as in the development of tailored marketing strategies, and the segmentation of consumer groups, settings, brands, and products.
Analysis of genetic association using hierarchical clustering and cluster validation indices.

PubMed

Pagnuco, Inti A; Pastore, Juan I; Abras, Guillermo; Brun, Marcel; Ballarin, Virginia L

2017-10-01

It is usually assumed that co-expressed genes suggest co-regulation in the underlying regulatory network. Determining sets of co-expressed genes is an important task, based on some criteria of similarity. This task is usually performed by clustering algorithms, where the genes are clustered into meaningful groups based on their expression values in a set of experiment. In this work, we propose a method to find sets of co-expressed genes, based on cluster validation indices as a measure of similarity for individual gene groups, and a combination of variants of hierarchical clustering to generate the candidate groups. We evaluated its ability to retrieve significant sets on simulated correlated and real genomics data, where the performance is measured based on its detection ability of co-regulated sets against a full search. Additionally, we analyzed the quality of the best ranked groups using an online bioinformatics tool that provides network information for the selected genes. Copyright © 2017 Elsevier Inc. All rights reserved.
Next-generation sequencing meets genetic diagnostics: development of a comprehensive workflow for the analysis of BRCA1 and BRCA2 genes

PubMed Central

Feliubadaló, Lídia; Lopez-Doriga, Adriana; Castellsagué, Ester; del Valle, Jesús; Menéndez, Mireia; Tornero, Eva; Montes, Eva; Cuesta, Raquel; Gómez, Carolina; Campos, Olga; Pineda, Marta; González, Sara; Moreno, Victor; Brunet, Joan; Blanco, Ignacio; Serra, Eduard; Capellá, Gabriel; Lázaro, Conxi

2013-01-01

Next-generation sequencing (NGS) is changing genetic diagnosis due to its huge sequencing capacity and cost-effectiveness. The aim of this study was to develop an NGS-based workflow for routine diagnostics for hereditary breast and ovarian cancer syndrome (HBOCS), to improve genetic testing for BRCA1 and BRCA2. A NGS-based workflow was designed using BRCA MASTR kit amplicon libraries followed by GS Junior pyrosequencing. Data analysis combined Variant Identification Pipeline freely available software and ad hoc R scripts, including a cascade of filters to generate coverage and variant calling reports. A BRCA homopolymer assay was performed in parallel. A research scheme was designed in two parts. A Training Set of 28 DNA samples containing 23 unique pathogenic mutations and 213 other variants (33 unique) was used. The workflow was validated in a set of 14 samples from HBOCS families in parallel with the current diagnostic workflow (Validation Set). The NGS-based workflow developed permitted the identification of all pathogenic mutations and genetic variants, including those located in or close to homopolymers. The use of NGS for detecting copy-number alterations was also investigated. The workflow meets the sensitivity and specificity requirements for the genetic diagnosis of HBOCS and improves on the cost-effectiveness of current approaches. PMID:23249957
Solving LR Conflicts Through Context Aware Scanning

NASA Astrophysics Data System (ADS)

Leon, C. Rodriguez; Forte, L. Garcia

2011-09-01

This paper presents a new algorithm to compute the exact list of tokens expected by any LR syntax analyzer at any point of the scanning process. The lexer can, at any time, compute the exact list of valid tokens to return only tokens in this set. In the case than more than one matching token is in the valid set, the lexer can resort to a nested LR parser to disambiguate. Allowing nested LR parsing requires some slight modifications when building the LR parsing tables. We also show how LR parsers can parse conflictive and inherently ambiguous languages using a combination of nested parsing and context aware scanning. These expanded lexical analyzers can be generated from high level specifications.
Epidemiological cut-off values for Flavobacterium psychrophilum MIC data generated by a standard test protocol.

PubMed

Smith, P; Endris, R; Kronvall, G; Thomas, V; Verner-Jeffreys, D; Wilhelm, C; Dalsgaard, I

2016-02-01

Epidemiological cut-off values were developed for application to antibiotic susceptibility data for Flavobacterium psychrophilum generated by standard CLSI test protocols. The MIC values for ten antibiotic agents against Flavobacterium psychrophilum were determined in two laboratories. For five antibiotics, the data sets were of sufficient quality and quantity to allow the setting of valid epidemiological cut-off values. For these agents, the cut-off values, calculated by the application of the statistically based normalized resistance interpretation method, were ≤16 mg L(-1) for erythromycin, ≤2 mg L(-1) for florfenicol, ≤0.025 mg L(-1) for oxolinic acid (OXO), ≤0.125 mg L(-1) for oxytetracycline and ≤20 (1/19) mg L(-1) for trimethoprim/sulphamethoxazole. For ampicillin and amoxicillin, the majority of putative wild-type observations were 'off scale', and therefore, statistically valid cut-off values could not be calculated. For ormetoprim/sulphadimethoxine, the data were excessively diverse and a valid cut-off could not be determined. For flumequine, the putative wild-type data were extremely skewed, and for enrofloxacin, there was inadequate separation in the MIC values for putative wild-type and non-wild-type strains. It is argued that the adoption of OXO as a class representative for the quinolone group would be a valid method of determining susceptibilities to these agents. © 2014 John Wiley & Sons Ltd.
K-Fold Crossvalidation in Canonical Analysis.

ERIC Educational Resources Information Center

Liang, Kun-Hsia; And Others

1995-01-01

A computer-assisted, K-fold cross-validation technique is discussed in the framework of canonical correlation analysis of randomly generated data sets. Analysis results suggest that this technique can effectively reduce the contamination of canonical variates and canonical correlations by sample-specific variance components. (Author/SLD)
Simulating Next-Generation Sequencing Datasets from Empirical Mutation and Sequencing Models

PubMed Central

Stephens, Zachary D.; Hudson, Matthew E.; Mainzer, Liudmila S.; Taschuk, Morgan; Weber, Matthew R.; Iyer, Ravishankar K.

2016-01-01

An obstacle to validating and benchmarking methods for genome analysis is that there are few reference datasets available for which the “ground truth” about the mutational landscape of the sample genome is known and fully validated. Additionally, the free and public availability of real human genome datasets is incompatible with the preservation of donor privacy. In order to better analyze and understand genomic data, we need test datasets that model all variants, reflecting known biology as well as sequencing artifacts. Read simulators can fulfill this requirement, but are often criticized for limited resemblance to true data and overall inflexibility. We present NEAT (NExt-generation sequencing Analysis Toolkit), a set of tools that not only includes an easy-to-use read simulator, but also scripts to facilitate variant comparison and tool evaluation. NEAT has a wide variety of tunable parameters which can be set manually on the default model or parameterized using real datasets. The software is freely available at github.com/zstephens/neat-genreads. PMID:27893777
Multisensor system for toxic gases detection generated on indoor environments

NASA Astrophysics Data System (ADS)

Durán, C. M.; Monsalve, P. A. G.; Mosquera, C. J.

2016-11-01

This work describes a wireless multisensory system for different toxic gases detection generated on indoor environments (i.e., Underground coal mines, etc.). The artificial multisensory system proposed in this study was developed through a set of six chemical gas sensors (MQ) of low cost with overlapping sensitivities to detect hazardous gases in the air. A statistical parameter was implemented to the data set and two pattern recognition methods such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA) were used for feature selection. The toxic gases categories were classified with a Probabilistic Neural Network (PNN) in order to validate the results previously obtained. The tests were carried out to verify feasibility of the application through a wireless communication model which allowed to monitor and store the information of the sensor signals for the appropriate analysis. The success rate in the measures discrimination was 100%, using an artificial neural network where leave-one-out was used as cross validation method.
Quantitative structure-activity relationship modeling of rat acute toxicity by oral exposure.

PubMed

Zhu, Hao; Martin, Todd M; Ye, Lin; Sedykh, Alexander; Young, Douglas M; Tropsha, Alexander

2009-12-01

Few quantitative structure-activity relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity end points. In this study, a comprehensive data set of 7385 compounds with their most conservative lethal dose (LD(50)) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire data set was selected that included all 3472 compounds used in TOPKAT's training set. The remaining 3913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R(2) of linear regression between actual and predicted LD(50) values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R(2) ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD(50) for every compound using all five models. The consensus models afforded higher prediction accuracy for the external validation data set with the higher coverage as compared to individual constituent models. The validated consensus LD(50) models developed in this study can be used as reliable computational predictors of in vivo acute toxicity.
Validating EHR documents: automatic schematron generation using archetypes.

PubMed

Pfeiffer, Klaus; Duftschmid, Georg; Rinner, Christoph

2014-01-01

The goal of this study was to examine whether Schematron schemas can be generated from archetypes. The openEHR Java reference API was used to transform an archetype into an object model, which was then extended with context elements. The model was processed and the constraints were transformed into corresponding Schematron assertions. A prototype of the generator for the reference model HL7 v3 CDA R2 was developed and successfully tested. Preconditions for its reusability with other reference models were set. Our results indicate that an automated generation of Schematron schemas is possible with some limitations.
Validation of a global scale to assess the quality of interprofessional teamwork in mental health settings.

PubMed

Tomizawa, Ryoko; Yamano, Mayumi; Osako, Mitue; Hirabayashi, Naotugu; Oshima, Nobuo; Sigeta, Masahiro; Reeves, Scott

2017-12-01

Few scales currently exist to assess the quality of interprofessional teamwork through team members' perceptions of working together in mental health settings. The purpose of this study was to revise and validate an interprofessional scale to assess the quality of teamwork in inpatient psychiatric units and to use it multi-nationally. A literature review was undertaken to identify evaluative teamwork tools and develop an additional 12 items to ensure a broad global focus. Focus group discussions considered adaptation to different care systems using subjective judgements from 11 participants in a pre-test of items. Data quality, construct validity, reproducibility, and internal consistency were investigated in the survey using an international comparative design. Exploratory factor analysis yielded five factors with 21 items: 'patient/community centred care', 'collaborative communication', 'interprofessional conflict', 'role clarification', and 'environment'. High overall internal consistency, reproducibility, adequate face validity, and reasonable construct validity were shown in the USA and Japan. The revised Collaborative Practice Assessment Tool (CPAT) is a valid measure to assess the quality of interprofessional teamwork in psychiatry and identifies the best strategies to improve team performance. Furthermore, the revised scale will generate more rigorous evidence for collaborative practice in psychiatry internationally.
Calling Chromosome Alterations, DNA Methylation Statuses, and Mutations in Tumors by Simple Targeted Next-Generation Sequencing: A Solution for Transferring Integrated Pangenomic Studies into Routine Practice?

PubMed

Garinet, Simon; Néou, Mario; de La Villéon, Bruno; Faillot, Simon; Sakat, Julien; Da Fonseca, Juliana P; Jouinot, Anne; Le Tourneau, Christophe; Kamal, Maud; Luscap-Rondof, Windy; Boeva, Valentina; Gaujoux, Sebastien; Vidaud, Michel; Pasmant, Eric; Letourneur, Franck; Bertherat, Jérôme; Assié, Guillaume

2017-09-01

Pangenomic studies identified distinct molecular classes for many cancers, with major clinical applications. However, routine use requires cost-effective assays. We assessed whether targeted next-generation sequencing (NGS) could call chromosomal alterations and DNA methylation status. A training set of 77 tumors and a validation set of 449 (43 tumor types) were analyzed by targeted NGS and single-nucleotide polymorphism (SNP) arrays. Thirty-two tumors were analyzed by NGS after bisulfite conversion, and compared to methylation array or methylation-specific multiplex ligation-dependent probe amplification. Considering allelic ratios, correlation was strong between targeted NGS and SNP arrays (r = 0.88). In contrast, considering DNA copy number, for variations of one DNA copy, correlation was weaker between read counts and SNP array (r = 0.49). Thus, we generated TARGOMICs, optimized for detecting chromosome alterations by combining allelic ratios and read counts generated by targeted NGS. Sensitivity for calling normal, lost, and gained chromosomes was 89%, 72%, and 31%, respectively. Specificity was 81%, 93%, and 98%, respectively. These results were confirmed in the validation set. Finally, TARGOMICs could efficiently align and compute proportions of methylated cytosines from bisulfite-converted DNA from targeted NGS. In conclusion, beyond calling mutations, targeted NGS efficiently calls chromosome alterations and methylation status in tumors. A single run and minor design/protocol adaptations are sufficient. Optimizing targeted NGS should expand translation of genomics to clinical routine. Copyright © 2017 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.
The virtual people set: developing computer-generated stimuli for the assessment of pedophilic sexual interest.

PubMed

Dombert, Beate; Mokros, Andreas; Brückner, Eva; Schlegl, Verena; Antfolk, Jan; Bäckström, Anna; Zappalà, Angelo; Osterheider, Michael; Santtila, Pekka

2013-12-01

The implicit assessment of pedophilic sexual interest through viewing-time methods necessitates visual stimuli. There are grave ethical and legal concerns against using pictures of real children, however. The present report is a summary of findings on a new set of 108 computer-generated stimuli. The images vary in terms of gender (female/male), explicitness (naked/clothed), and physical maturity (prepubescent, pubescent, and adult) of the persons depicted. A series of three studies tested the internal and external validity of the picture set. Studies 1 and 2 yielded good-to-high estimates of observer agreement with regard to stimulus maturity levels by two methods (categorization and paired comparison). Study 3 extended these findings with regard to judgments made by convicted child sexual offenders.
Conceptual dissonance: evaluating the efficacy of natural language processing techniques for validating translational knowledge constructs.

PubMed

Payne, Philip R O; Kwok, Alan; Dhaval, Rakesh; Borlawsky, Tara B

2009-03-01

The conduct of large-scale translational studies presents significant challenges related to the storage, management and analysis of integrative data sets. Ideally, the application of methodologies such as conceptual knowledge discovery in databases (CKDD) provides a means for moving beyond intuitive hypothesis discovery and testing in such data sets, and towards the high-throughput generation and evaluation of knowledge-anchored relationships between complex bio-molecular and phenotypic variables. However, the induction of such high-throughput hypotheses is non-trivial, and requires correspondingly high-throughput validation methodologies. In this manuscript, we describe an evaluation of the efficacy of a natural language processing-based approach to validating such hypotheses. As part of this evaluation, we will examine a phenomenon that we have labeled as "Conceptual Dissonance" in which conceptual knowledge derived from two or more sources of comparable scope and granularity cannot be readily integrated or compared using conventional methods and automated tools.
Flight evaluation of advanced third-generation midwave infrared sensor

NASA Astrophysics Data System (ADS)

Shen, Chyau N.; Donn, Matthew

1998-08-01

In FY-97 the Counter Drug Optical Upgrade (CDOU) demonstration program was initiated by the Program Executive Office for Counter Drug to increase the detection and classification ranges of P-3 counter drug aircraft by using advanced staring infrared sensors. The demonstration hardware is a `pin-for-pin' replacement of the AAS-36 Infrared Detection Set (IRDS) located under the nose radome of a P-3 aircraft. The hardware consists of a 3rd generation mid-wave infrared (MWIR) sensor integrated into a three axis-stabilized turret. The sensor, when installed on the P- 3, has a hemispheric field of regard and analysis has shown it will be capable of detecting and classifying Suspected Drug Trafficking Aircraft and Vessels at ranges several factors over the current IRDS. This paper will discuss the CDOU system and it's lab, ground, and flight evaluation results. Test targets included target templates, range targets, dedicated target boats, and targets of opportunity at the Naval Air Warfare Center Aircraft Division and at operational test sites. The objectives of these tests were to: (1) Validate the integration concept of the CDOU package into the P-3 aircraft. (2) Validate the end-to-end functionality of the system, including sensor/turret controls and recording of imagery during flight. (3) Evaluate the system sensitivity and resolution on a set of verified resolution targets templates. (4) Validate the ability of the 3rd generation MWIR sensor to detect and classify targets at a significantly increased range.
Generating quality word sense disambiguation test sets based on MeSH indexing.

PubMed

Fan, Jung-Wei; Friedman, Carol

2009-11-14

Word sense disambiguation (WSD) determines the correct meaning of a word that has more than one meaning, and is a critical step in biomedical natural language processing, as interpretation of information in text can be correct only if the meanings of their component terms are correctly identified first. Quality evaluation sets are important to WSD because they can be used as representative samples for developing automatic programs and as referees for comparing different WSD programs. To help create quality test sets for WSD, we developed a MeSH-based automatic sense-tagging method that preferentially annotates terms being topical of the text. Preliminary results were promising and revealed important issues to be addressed in biomedical WSD research. We also suggest that, by cross-validating with 2 or 3 annotators, the method should be able to efficiently generate quality WSD test sets. Online supplement is available at: http://www.dbmi.columbia.edu/~juf7002/AMIA09.
LACO-Wiki: A land cover validation tool and a new, innovative teaching resource for remote sensing and the geosciences

NASA Astrophysics Data System (ADS)

See, Linda; Perger, Christoph; Dresel, Christopher; Hofer, Martin; Weichselbaum, Juergen; Mondel, Thomas; Steffen, Fritz

2016-04-01

The validation of land cover products is an important step in the workflow of generating a land cover map from remotely-sensed imagery. Many students of remote sensing will be given exercises on classifying a land cover map followed by the validation process. Many algorithms exist for classification, embedded within proprietary image processing software or increasingly as open source tools. However, there is little standardization for land cover validation, nor a set of open tools available for implementing this process. The LACO-Wiki tool was developed as a way of filling this gap, bringing together standardized land cover validation methods and workflows into a single portal. This includes the storage and management of land cover maps and validation data; step-by-step instructions to guide users through the validation process; sound sampling designs; an easy-to-use environment for validation sample interpretation; and the generation of accuracy reports based on the validation process. The tool was developed for a range of users including producers of land cover maps, researchers, teachers and students. The use of such a tool could be embedded within the curriculum of remote sensing courses at a university level but is simple enough for use by students aged 13-18. A beta version of the tool is available for testing at: http://www.laco-wiki.net.
Prediction of breast cancer risk with volatile biomarkers in breath.

PubMed

Phillips, Michael; Cataneo, Renee N; Cruz-Ramos, Jose Alfonso; Huston, Jan; Ornelas, Omar; Pappas, Nadine; Pathak, Sonali

2018-03-23

Human breath contains volatile organic compounds (VOCs) that are biomarkers of breast cancer. We investigated the positive and negative predictive values (PPV and NPV) of breath VOC biomarkers as indicators of breast cancer risk. We employed ultra-clean breath collection balloons to collect breath samples from 54 women with biopsy-proven breast cancer and 124 cancer-free controls. Breath VOCs were analyzed with gas chromatography (GC) combined with either mass spectrometry (GC MS) or surface acoustic wave detection (GC SAW). Chromatograms were randomly assigned to a training set or a validation set. Monte Carlo analysis identified significant breath VOC biomarkers of breast cancer in the training set, and these biomarkers were incorporated into a multivariate algorithm to predict disease in the validation set. In the unsplit dataset, the predictive algorithms generated discriminant function (DF) values that varied with sensitivity, specificity, PPV and NPV. Using GC MS, test accuracy = 90% (area under curve of receiver operating characteristic in unsplit dataset) and cross-validated accuracy = 77%. Using GC SAW, test accuracy = 86% and cross-validated accuracy = 74%. With both assays, a low DF value was associated with a low risk of breast cancer (NPV > 99.9%). A high DF value was associated with a high risk of breast cancer and PPV rising to 100%. Analysis of breath VOC samples collected with ultra-clean balloons detected biomarkers that accurately predicted risk of breast cancer.

Differentiating Categories and Dimensions: Evaluating the Robustness of Taxometric Analyses

ERIC Educational Resources Information Center

Ruscio, John; Kaczetow, Walter

2009-01-01

Interest in modeling the structure of latent variables is gaining momentum, and many simulation studies suggest that taxometric analysis can validly assess the relative fit of categorical and dimensional models. The generation and parallel analysis of categorical and dimensional comparison data sets reduces the subjectivity required to interpret…
Common Ada Programming Support Environment (APSE) Interface Set (CAIS) Implementation Validation Capability (CIVC2)

DTIC Science & Technology

1992-06-01

Paper, Version 2.0, December 1989. [Woodcock90] Gary Woodcock , Automated Generation of Hypertext Documents, CIVC Technical Report (working paper...environment setup, performance testing, assessor testing, and analysis) of the ACEC. A captive scenario example could be developed that would guide the
Using Copula Distributions to Support More Accurate Imaging-Based Diagnostic Classifiers for Neuropsychiatric Disorders

PubMed Central

Bansal, Ravi; Hao, Xuejun; Liu, Jun; Peterson, Bradley S.

2014-01-01

Many investigators have tried to apply machine learning techniques to magnetic resonance images (MRIs) of the brain in order to diagnose neuropsychiatric disorders. Usually the number of brain imaging measures (such as measures of cortical thickness and measures of local surface morphology) derived from the MRIs (i.e., their dimensionality) has been large (e.g. >10) relative to the number of participants who provide the MRI data (<100). Sparse data in a high dimensional space increases the variability of the classification rules that machine learning algorithms generate, thereby limiting the validity, reproducibility, and generalizability of those classifiers. The accuracy and stability of the classifiers can improve significantly if the multivariate distributions of the imaging measures can be estimated accurately. To accurately estimate the multivariate distributions using sparse data, we propose to estimate first the univariate distributions of imaging data and then combine them using a Copula to generate more accurate estimates of their multivariate distributions. We then sample the estimated Copula distributions to generate dense sets of imaging measures and use those measures to train classifiers. We hypothesize that the dense sets of brain imaging measures will generate classifiers that are stable to variations in brain imaging measures, thereby improving the reproducibility, validity, and generalizability of diagnostic classification algorithms in imaging datasets from clinical populations. In our experiments, we used both computer-generated and real-world brain imaging datasets to assess the accuracy of multivariate Copula distributions in estimating the corresponding multivariate distributions of real-world imaging data. Our experiments showed that diagnostic classifiers generated using imaging measures sampled from the Copula were significantly more accurate and more reproducible than were the classifiers generated using either the real-world imaging measures or their multivariate Gaussian distributions. Thus, our findings demonstrate that estimated multivariate Copula distributions can generate dense sets of brain imaging measures that can in turn be used to train classifiers, and those classifiers are significantly more accurate and more reproducible than are those generated using real-world imaging measures alone. PMID:25093634
Tumor-infiltrating Neutrophils is Prognostic and Predictive for Postoperative Adjuvant Chemotherapy Benefit in Patients With Gastric Cancer.

PubMed

Zhang, Heng; Liu, Hao; Shen, Zhenbin; Lin, Chao; Wang, Xuefei; Qin, Jing; Qin, Xinyu; Xu, Jiejie; Sun, Yihong

2018-02-01

This study was aimed to investigate the prognostic value of tumor-infiltrating neutrophils (TINs) and to generate a predictive model to refine postoperative risk stratification system for patients with gastric cancer. TIN presents in various malignant tumors, but its clinical significance in gastric cancer remains obscure. The study enrolled 3 independent sets of patients with gastric cancer from 2 institutional medical centers of China. TIN was estimated by immunohistochemical staining of CD66b, and its relationship with clinicopathological features and clinical outcomes were evaluated. Prognostic accuracies were evaluated by C-index and Akaike information criterion. TINs in gastric cancer tissues ranged from 0 to 192 cells/high magnification filed (HPF), 0 to 117 cells/HPF, and 0 to 142 cells/HPF in the training, testing, and validation sets, respectively. TINs were negatively correlated with lymph node classification (P = 0.007, P = 0.041, and P = 0.032, respectively) and tumor stage (P = 0.019, P = 0.013, and P = 0.025, respectively) in the 3 sets. Moreover, multivariate analysis identified TINs and tumor node metastasis (TNM) stage as 2 independent prognostic factors for overall survival. Incorporation of TINs into well-established TNM system generated a predictive model that shows better predictive accuracy for overall survival. More importantly, patients with higher TINs were prone to overall survival benefit from postoperative adjuvant chemotherapy. These results were validated in the independent testing and validation sets. TIN in gastric cancer was identified as an independent prognostic factor, which could be incorporated into standard TNM staging system to refine risk stratification and predict for overall survival benefit from postoperative chemotherapy in patients with gastric cancer.
GeneratorSE: A Sizing Tool for Variable-Speed Wind Turbine Generators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sethuraman, Latha; Dykes, Katherine L

This report documents a set of analytical models employed by the optimization algorithms within the GeneratorSE framework. The initial values and boundary conditions employed for the generation of the various designs and initial estimates for basic design dimensions, masses, and efficiency for the four different models of generators are presented and compared with empirical data collected from previous studies and some existing commercial turbines. These models include designs applicable for variable-speed, high-torque application featuring direct-drive synchronous generators and low-torque application featuring induction generators. In all of the four models presented, the main focus of optimization is electromagnetic design with themore » exception of permanent-magnet and wire-wound synchronous generators, wherein the structural design is also optimized. Thermal design is accommodated in GeneratorSE as a secondary attribute by limiting the winding current densities to acceptable limits. A preliminary validation of electromagnetic design was carried out by comparing the optimized magnetic loading against those predicted by numerical simulation in FEMM4.2, a finite-element software for analyzing electromagnetic and thermal physics problems for electrical machines. For direct-drive synchronous generators, the analytical models for the structural design are validated by static structural analysis in ANSYS.« less
A Multi-Scale Structural Health Monitoring Approach for Damage Detection, Diagnosis and Prognosis in Aerospace Structures

DTIC Science & Technology

2012-01-20

ultrasonic Lamb waves to plastic strain and fatigue life. Theory was developed and validated to predict second harmonic generation for specific mode... Fatigue and damage generation and progression are processes consisting of a series of interrelated events that span large scales of space and time...strain and fatigue life A set of experiments were completed that worked to relate the acoustic nonlinearity measured with Lamb waves to both the
Validity in work-based assessment: expanding our horizons.

PubMed

Govaerts, Marjan; van der Vleuten, Cees P M

2013-12-01

Although work-based assessments (WBA) may come closest to assessing habitual performance, their use for summative purposes is not undisputed. Most criticism of WBA stems from approaches to validity consistent with the quantitative psychometric framework. However, there is increasing research evidence that indicates that the assumptions underlying the predictive, deterministic framework of psychometrics may no longer hold. In this discussion paper we argue that meaningfulness and appropriateness of current validity evidence can be called into question and that we need alternative strategies to assessment and validity inquiry that build on current theories of learning and performance in complex and dynamic workplace settings. Drawing from research in various professional fields we outline key issues within the mechanisms of learning, competence and performance in the context of complex social environments and illustrate their relevance to WBA. In reviewing recent socio-cultural learning theory and research on performance and performance interpretations in work settings, we demonstrate that learning, competence (as inferred from performance) as well as performance interpretations are to be seen as inherently contextualised, and can only be under-stood 'in situ'. Assessment in the context of work settings may, therefore, be more usefully viewed as a socially situated interpretive act. We propose constructivist-interpretivist approaches towards WBA in order to capture and understand contextualised learning and performance in work settings. Theoretical assumptions underlying interpretivist assessment approaches call for a validity theory that provides the theoretical framework and conceptual tools to guide the validation process in the qualitative assessment inquiry. Basic principles of rigour specific to qualitative research have been established, and they can and should be used to determine validity in interpretivist assessment approaches. If used properly, these strategies generate trustworthy evidence that is needed to develop the validity argument in WBA, allowing for in-depth and meaningful information about professional competence. © 2013 John Wiley & Sons Ltd.
The Contribution of TOMS and UARS Data to Our Understanding of Ozone Change

NASA Technical Reports Server (NTRS)

Bhartia, Pawan K.; Einaudi, Franco (Technical Monitor)

2001-01-01

Both TOMS (Total Ozone Mapping Spectrometer) and UARS (Upper Atmosphere Research Satellite) have operated over an extended period, and generated data sets of sufficient accuracy to be of use in determining ozone change (TOMS) and some of the underlying causes (UARS). The basic scientific products have been used for model validation and assimilation to extend our understanding of stratospheric processes. TOMS on Nimbus-7, Earth-Probe, and QuikTOMS, and UARS have led to the next generation of instruments onboard the EOS platforms. Algorithms used for TOMS and UARS are being applied to the new data sets and extended to analysis of European satellite data (e.g., GOME)
Performance optimization and validation of ADM1 simulations under anaerobic thermophilic conditions.

PubMed

Atallah, Nabil M; El-Fadel, Mutasem; Ghanimeh, Sophia; Saikaly, Pascal; Abou-Najm, Majdi

2014-12-01

In this study, two experimental sets of data each involving two thermophilic anaerobic digesters treating food waste, were simulated using the Anaerobic Digestion Model No. 1 (ADM1). A sensitivity analysis was conducted, using both data sets of one digester, for parameter optimization based on five measured performance indicators: methane generation, pH, acetate, total COD, ammonia, and an equally weighted combination of the five indicators. The simulation results revealed that while optimization with respect to methane alone, a commonly adopted approach, succeeded in simulating methane experimental results, it predicted other intermediary outputs less accurately. On the other hand, the multi-objective optimization has the advantage of providing better results than methane optimization despite not capturing the intermediary output. The results from the parameter optimization were validated upon their independent application on the data sets of the second digester. Copyright © 2014 Elsevier Ltd. All rights reserved.
Sociopathic Knowledge Bases: Correct Knowledge Can Be Harmful Even Given Unlimited Computation

DTIC Science & Technology

1989-08-01

pobitive, as false positives generated by a medical program can often be caught by a physician upon further testing . False negatives, however, may be...improvement over the knowledge base tested is obtained. Although our work is pretty much theoretical research oriented one example of ex- periments is...knowledge base, improves the performance by about 10%. of tests . First, we divide the cases into a training set and a validation set with 70% vs. 30% each
Statistically Validated Networks in Bipartite Complex Systems

PubMed Central

Tumminello, Michele; Miccichè, Salvatore; Lillo, Fabrizio; Piilo, Jyrki; Mantegna, Rosario N.

2011-01-01

Many complex systems present an intrinsic bipartite structure where elements of one set link to elements of the second set. In these complex systems, such as the system of actors and movies, elements of one set are qualitatively different than elements of the other set. The properties of these complex systems are typically investigated by constructing and analyzing a projected network on one of the two sets (for example the actor network or the movie network). Complex systems are often very heterogeneous in the number of relationships that the elements of one set establish with the elements of the other set, and this heterogeneity makes it very difficult to discriminate links of the projected network that are just reflecting system's heterogeneity from links relevant to unveil the properties of the system. Here we introduce an unsupervised method to statistically validate each link of a projected network against a null hypothesis that takes into account system heterogeneity. We apply the method to a biological, an economic and a social complex system. The method we propose is able to detect network structures which are very informative about the organization and specialization of the investigated systems, and identifies those relationships between elements of the projected network that cannot be explained simply by system heterogeneity. We also show that our method applies to bipartite systems in which different relationships might have different qualitative nature, generating statistically validated networks in which such difference is preserved. PMID:21483858
The Geostationary Operational Environmental Satellite (GOES) Product Generation System

NASA Technical Reports Server (NTRS)

Haines, S. L.; Suggs, R. J.; Jedlovec, G. J.

2004-01-01

The Geostationary Operational Environmental Satellite (GOES) Product Generation System (GPGS) is introduced and described. GPGS is a set of computer programs developed and maintained at the Global Hydrology and Climate Center and is designed to generate meteorological data products using visible and infrared measurements from the GOES-East Imager and Sounder instruments. The products that are produced by GPGS are skin temperature, total precipitable water, cloud top pressure, cloud albedo, surface albedo, and surface insolation. A robust cloud mask is also generated. The retrieval methodology for each product is described to include algorithm descriptions and required inputs and outputs for the programs. Validation is supplied where applicable.
Strong Generative Capacity and the Empirical Base of Linguistic Theory

PubMed Central

Ott, Dennis

2017-01-01

This Perspective traces the evolution of certain central notions in the theory of Generative Grammar (GG). The founding documents of the field suggested a relation between the grammar, construed as recursively enumerating an infinite set of sentences, and the idealized native speaker that was essentially equivalent to the relation between a formal language (a set of well-formed formulas) and an automaton that recognizes strings as belonging to the language or not. But this early view was later abandoned, when the focus of the field shifted to the grammar's strong generative capacity as recursive generation of hierarchically structured objects as opposed to strings. The grammar is now no longer seen as specifying a set of well-formed expressions and in fact necessarily constructs expressions of any degree of intuitive “acceptability.” The field of GG, however, has not sufficiently acknowledged the significance of this shift in perspective, as evidenced by the fact that (informal and experimentally-controlled) observations about string acceptability continue to be treated as bona fide data and generalizations for the theory of GG. The focus on strong generative capacity, it is argued, requires a new discussion of what constitutes valid empirical evidence for GG beyond observations pertaining to weak generation. PMID:28983268
Overview and Meteorological Validation of the Wind Integration National Dataset toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Draxl, C.; Hodge, B. M.; Clifton, A.

2015-04-13

The Wind Integration National Dataset (WIND) Toolkit described in this report fulfills these requirements, and constitutes a state-of-the-art national wind resource data set covering the contiguous United States from 2007 to 2013 for use in a variety of next-generation wind integration analyses and wind power planning. The toolkit is a wind resource data set, wind forecast data set, and wind power production and forecast data set derived from the Weather Research and Forecasting (WRF) numerical weather prediction model. WIND Toolkit data are available online for over 116,000 land-based and 10,000 offshore sites representing existing and potential wind facilities.
Likelihood ratio data to report the validation of a forensic fingerprint evaluation method.

PubMed

Ramos, Daniel; Haraksim, Rudolf; Meuwly, Didier

2017-02-01

Data to which the authors refer to throughout this article are likelihood ratios (LR) computed from the comparison of 5-12 minutiae fingermarks with fingerprints. These LRs data are used for the validation of a likelihood ratio (LR) method in forensic evidence evaluation. These data present a necessary asset for conducting validation experiments when validating LR methods used in forensic evidence evaluation and set up validation reports. These data can be also used as a baseline for comparing the fingermark evidence in the same minutiae configuration as presented in (D. Meuwly, D. Ramos, R. Haraksim,) [1], although the reader should keep in mind that different feature extraction algorithms and different AFIS systems used may produce different LRs values. Moreover, these data may serve as a reproducibility exercise, in order to train the generation of validation reports of forensic methods, according to [1]. Alongside the data, a justification and motivation for the use of methods is given. These methods calculate LRs from the fingerprint/mark data and are subject to a validation procedure. The choice of using real forensic fingerprint in the validation and simulated data in the development is described and justified. Validation criteria are set for the purpose of validation of the LR methods, which are used to calculate the LR values from the data and the validation report. For privacy and data protection reasons, the original fingerprint/mark images cannot be shared. But these images do not constitute the core data for the validation, contrarily to the LRs that are shared.
Workshop on Strategies for Calibration and Validation of Global Change Measurements

NASA Technical Reports Server (NTRS)

Guenther, Bruce; Butler, James; Ardanuy, Philip

1997-01-01

The Committee on Environment and Natural Resources (CENR) Task Force on Observations and Data Management hosted a Global Change Calibration/Validation Workshop on May 10-12, 1995, in Arlington, Virginia. This Workshop was convened by Robert Schiffer of NASA Headquarters in Washington, D.C., for the CENR Secretariat with a view toward assessing and documenting lessons learned in the calibration and validation of large-scale, long-term data sets in land, ocean, and atmospheric research programs. The National Aeronautics and Space Administration (NASA)/Goddard Space Flight Center (GSFC) hosted the meeting on behalf of the Committee on Earth Observation Satellites (CEOS)/Working Group on Calibration/walidation, the Global Change Observing System (GCOS), and the U. S. CENR. A meeting of experts from the international scientific community was brought together to develop recommendations for calibration and validation of global change data sets taken from instrument series and across generations of instruments and technologies. Forty-nine scientists from nine countries participated. The U. S., Canada, United Kingdom, France, Germany, Japan, Switzerland, Russia, and Kenya were represented.
Using deep RNA sequencing for the structural annotation of the laccaria bicolor mycorrhizal transcriptome.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larsen, P. E.; Trivedi, G.; Sreedasyam, A.

2010-07-06

Accurate structural annotation is important for prediction of function and required for in vitro approaches to characterize or validate the gene expression products. Despite significant efforts in the field, determination of the gene structure from genomic data alone is a challenging and inaccurate process. The ease of acquisition of transcriptomic sequence provides a direct route to identify expressed sequences and determine the correct gene structure. We developed methods to utilize RNA-seq data to correct errors in the structural annotation and extend the boundaries of current gene models using assembly approaches. The methods were validated with a transcriptomic data set derivedmore » from the fungus Laccaria bicolor, which develops a mycorrhizal symbiotic association with the roots of many tree species. Our analysis focused on the subset of 1501 gene models that are differentially expressed in the free living vs. mycorrhizal transcriptome and are expected to be important elements related to carbon metabolism, membrane permeability and transport, and intracellular signaling. Of the set of 1501 gene models, 1439 (96%) successfully generated modified gene models in which all error flags were successfully resolved and the sequences aligned to the genomic sequence. The remaining 4% (62 gene models) either had deviations from transcriptomic data that could not be spanned or generated sequence that did not align to genomic sequence. The outcome of this process is a set of high confidence gene models that can be reliably used for experimental characterization of protein function. 69% of expressed mycorrhizal JGI 'best' gene models deviated from the transcript sequence derived by this method. The transcriptomic sequence enabled correction of a majority of the structural inconsistencies and resulted in a set of validated models for 96% of the mycorrhizal genes. The method described here can be applied to improve gene structural annotation in other species, provided that there is a sequenced genome and a set of gene models.« less
Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors. Part 2; Implementation, Analysis and Validation

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Samanta, Arindam; Schull, Mitchell A.; Shabanov, Nikolay V.; Milesi, Cristina; Nemani, Ramajrushna R,; Knyazikhin, Yuri; Myneni, Ranga B.

2008-01-01

The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the intercomparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.
Microstructure Modeling of 3rd Generation Disk Alloys

NASA Technical Reports Server (NTRS)

Jou, Herng-Jeng

2010-01-01

The objective of this program is to model, validate, and predict the precipitation microstructure evolution, using PrecipiCalc (QuesTek Innovations LLC) software, for 3rd generation Ni-based gas turbine disc superalloys during processing and service, with a set of logical and consistent experiments and characterizations. Furthermore, within this program, the originally research-oriented microstructure simulation tool will be further improved and implemented to be a useful and user-friendly engineering tool. In this report, the key accomplishment achieved during the second year (2008) of the program is summarized. The activities of this year include final selection of multicomponent thermodynamics and mobility databases, precipitate surface energy determination from nucleation experiment, multiscale comparison of predicted versus measured intragrain precipitation microstructure in quench samples showing good agreement, isothermal coarsening experiment and interaction of grain boundary and intergrain precipitates, primary microstructure of subsolvus treatment, and finally the software implementation plan for the third year of the project. In the following year, the calibrated models and simulation tools will be validated against an independently developed experimental data set, with actual disc heat treatment process conditions. Furthermore, software integration and implementation will be developed to provide material engineers valuable information in order to optimize the processing of the 3rd generation gas turbine disc alloys.
Colorado Wind Resource at 50 Meters Above Ground Level

Science.gov Websites

Meters Above Ground Level Geospatial_Data_Presentation_Form: vector digital data Description: Abstract . Supplemental_Information: This data set has been validated by NREL and wind energy meteorological consultants. However, the data is not suitable for micro-siting potential development projects. This shapefile was generated from

Isolated Open Rotor Noise Prediction Assessment Using the F31A31 Historical Blade Set

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Jones, William T.; Boyd, D. Douglas, Jr.; Zawodny, Nikolas S.

2016-01-01

In an effort to mitigate next-generation fuel efficiency and environmental impact concerns for aviation, open rotor propulsion systems have received renewed interest. However, maintaining the high propulsive efficiency while simultaneously meeting noise goals has been one of the challenges in making open rotor propulsion a viable option. Improvements in prediction tools and design methodologies have opened the design space for next generation open rotor designs that satisfy these challenging objectives. As such, validation of aerodynamic and acoustic prediction tools has been an important aspect of open rotor research efforts. This paper describes validation efforts of a combined computational fluid dynamics and Ffowcs Williams and Hawkings equation methodology for open rotor aeroacoustic modeling. Performance and acoustic predictions were made for a benchmark open rotor blade set and compared with measurements over a range of rotor speeds and observer angles. Overall, the results indicate that the computational approach is acceptable for assessing low-noise open rotor designs. Additionally, this approach may be used to provide realistic incident source fields for acoustic shielding/scattering studies on various aircraft configurations.
GENESUS: a two-step sequence design program for DNA nanostructure self-assembly.

PubMed

Tsutsumi, Takanobu; Asakawa, Takeshi; Kanegami, Akemi; Okada, Takao; Tahira, Tomoko; Hayashi, Kenshi

2014-01-01

DNA has been recognized as an ideal material for bottom-up construction of nanometer scale structures by self-assembly. The generation of sequences optimized for unique self-assembly (GENESUS) program reported here is a straightforward method for generating sets of strand sequences optimized for self-assembly of arbitrarily designed DNA nanostructures by a generate-candidates-and-choose-the-best strategy. A scalable procedure to prepare single-stranded DNA having arbitrary sequences is also presented. Strands for the assembly of various structures were designed and successfully constructed, validating both the program and the procedure.
Identification of potential serum peptide biomarkers of biliary tract cancer using MALDI MS profiling

PubMed Central

2014-01-01

Background The aim of this discovery study was the identification of peptide serum biomarkers for detecting biliary tract cancer (BTC) using samples from healthy volunteers and benign cases of biliary disease as control groups. This work was based on the hypothesis that cancer-specific exopeptidases exist and that their activities in serum can generate cancer-predictive peptide fragments from circulating proteins during coagulation. Methods This case control study used a semi-automated platform incorporating polypeptide extraction linked to matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) to profile 92 patient serum samples. Predictive models were generated to test a validation serum set from BTC cases and healthy volunteers. Results Several peptide peaks were found that could significantly differentiate BTC patients from healthy controls and benign biliary disease. A predictive model resulted in a sensitivity of 100% and a specificity of 93.8% in detecting BTC in the validation set, whilst another model gave a sensitivity of 79.5% and a specificity of 83.9% in discriminating BTC from benign biliary disease samples in the training set. Discriminatory peaks were identified by tandem MS as fragments of abundant clotting proteins. Conclusions Serum MALDI MS peptide signatures can accurately discriminate patients with BTC from healthy volunteers. PMID:24495412
Automatic computation and solution of generalized harmonic balance equations

NASA Astrophysics Data System (ADS)

Peyton Jones, J. C.; Yaser, K. S. A.; Stevenson, J.

2018-02-01

Generalized methods are presented for generating and solving the harmonic balance equations for a broad class of nonlinear differential or difference equations and for a general set of harmonics chosen by the user. In particular, a new algorithm for automatically generating the Jacobian of the balance equations enables efficient solution of these equations using continuation methods. Efficient numeric validation techniques are also presented, and the combined algorithm is applied to the analysis of dc, fundamental, second and third harmonic response of a nonlinear automotive damper.
In silico prediction of ROCK II inhibitors by different classification approaches.

PubMed

Cai, Chuipu; Wu, Qihui; Luo, Yunxia; Ma, Huili; Shen, Jiangang; Zhang, Yongbin; Yang, Lei; Chen, Yunbo; Wen, Zehuai; Wang, Qi

2017-11-01

ROCK II is an important pharmacological target linked to central nervous system disorders such as Alzheimer's disease. The purpose of this research is to generate ROCK II inhibitor prediction models by machine learning approaches. Firstly, four sets of descriptors were calculated with MOE 2010 and PaDEL-Descriptor, and optimized by F-score and linear forward selection methods. In addition, four classification algorithms were used to initially build 16 classifiers with k-nearest neighbors [Formula: see text], naïve Bayes, Random forest, and support vector machine. Furthermore, three sets of structural fingerprint descriptors were introduced to enhance the predictive capacity of classifiers, which were assessed with fivefold cross-validation, test set validation and external test set validation. The best two models, MFK + MACCS and MLR + SubFP, have both MCC values of 0.925 for external test set. After that, a privileged substructure analysis was performed to reveal common chemical features of ROCK II inhibitors. Finally, binding modes were analyzed to identify relationships between molecular descriptors and activity, while main interactions were revealed by comparing the docking interaction of the most potent and the weakest ROCK II inhibitors. To the best of our knowledge, this is the first report on ROCK II inhibitors utilizing machine learning approaches that provides a new method for discovering novel ROCK II inhibitors.
The ToMenovela – A Photograph-Based Stimulus Set for the Study of Social Cognition with High Ecological Validity

PubMed Central

Herbort, Maike C.; Iseev, Jenny; Stolz, Christopher; Roeser, Benedict; Großkopf, Nora; Wüstenberg, Torsten; Hellweg, Rainer; Walter, Henrik; Dziobek, Isabel; Schott, Björn H.

2016-01-01

We present the ToMenovela, a stimulus set that has been developed to provide a set of normatively rated socio-emotional stimuli showing varying amount of characters in emotionally laden interactions for experimental investigations of (i) cognitive and (ii) affective Theory of Mind (ToM), (iii) emotional reactivity, and (iv) complex emotion judgment with respect to Ekman’s basic emotions (happiness, anger, disgust, fear, sadness, surprise, Ekman and Friesen, 1975). Stimuli were generated with focus on ecological validity and consist of 190 scenes depicting daily-life situations. Two or more of eight main characters with distinct biographies and personalities are depicted on each scene picture. To obtain an initial evaluation of the stimulus set and to pave the way for future studies in clinical populations, normative data on each stimulus of the set was obtained from a sample of 61 neurologically and psychiatrically healthy participants (31 female, 30 male; mean age 26.74 ± 5.84), including a visual analog scale rating of Ekman’s basic emotions (happiness, anger, disgust, fear, sadness, surprise) and free-text descriptions of the content of each scene. The ToMenovela is being developed to provide standardized material of social scenes that are available to researchers in the study of social cognition. It should facilitate experimental control while keeping ecological validity high. PMID:27994562
Discovery and Validation of Novel Expression Signature for Postcystectomy Recurrence in High-Risk Bladder Cancer

PubMed Central

Lam, Lucia L.; Ghadessi, Mercedeh; Erho, Nicholas; Vergara, Ismael A.; Alshalalfa, Mohammed; Buerki, Christine; Haddad, Zaid; Sierocinski, Thomas; Triche, Timothy J.; Skinner, Eila C.; Davicioni, Elai; Daneshmand, Siamak; Black, Peter C.

2014-01-01

Background Nearly half of muscle-invasive bladder cancer patients succumb to their disease following cystectomy. Selecting candidates for adjuvant therapy is currently based on clinical parameters with limited predictive power. This study aimed to develop and validate genomic-based signatures that can better identify patients at risk for recurrence than clinical models alone. Methods Transcriptome-wide expression profiles were generated using 1.4 million feature-arrays on archival tumors from 225 patients who underwent radical cystectomy and had muscle-invasive and/or node-positive bladder cancer. Genomic (GC) and clinical (CC) classifiers for predicting recurrence were developed on a discovery set (n = 133). Performances of GC, CC, an independent clinical nomogram (IBCNC), and genomic-clinicopathologic classifiers (G-CC, G-IBCNC) were assessed in the discovery and independent validation (n = 66) sets. GC was further validated on four external datasets (n = 341). Discrimination and prognostic abilities of classifiers were compared using area under receiver-operating characteristic curves (AUCs). All statistical tests were two-sided. Results A 15-feature GC was developed on the discovery set with area under curve (AUC) of 0.77 in the validation set. This was higher than individual clinical variables, IBCNC (AUC = 0.73), and comparable to CC (AUC = 0.78). Performance was improved upon combining GC with clinical nomograms (G-IBCNC, AUC = 0.82; G-CC, AUC = 0.86). G-CC high-risk patients had elevated recurrence probabilities (P < .001), with GC being the best predictor by multivariable analysis (P = .005). Genomic-clinicopathologic classifiers outperformed clinical nomograms by decision curve and reclassification analyses. GC performed the best in validation compared with seven prior signatures. GC markers remained prognostic across four independent datasets. Conclusions The validated genomic-based classifiers outperform clinical models for predicting postcystectomy bladder cancer recurrence. This may be used to better identify patients who need more aggressive management. PMID:25344601
An Ethical Issue Scale for Community Pharmacy Setting (EISP): Development and Validation.

PubMed

Crnjanski, Tatjana; Krajnovic, Dusanka; Tadic, Ivana; Stojkov, Svetlana; Savic, Mirko

2016-04-01

Many problems that arise when providing pharmacy services may contain some ethical components and the aims of this study were to develop and validate a scale that could assess difficulties of ethical issues, as well as the frequency of those occurrences in everyday practice of community pharmacists. Development and validation of the scale was conducted in three phases: (1) generating items for the initial survey instrument after qualitative analysis; (2) defining the design and format of the instrument; (3) validation of the instrument. The constructed Ethical Issue scale for community pharmacy setting has two parts containing the same 16 items for assessing the difficulty and frequency thereof. The results of the 171 completely filled out scales were analyzed (response rate 74.89%). The Cronbach's α value of the part of the instrument that examines difficulties of the ethical situations was 0.83 and for the part of the instrument that examined frequency of the ethical situations was 0.84. Test-retest reliability for both parts of the instrument was satisfactory with all Interclass correlation coefficient (ICC) values above 0.6, (for the part that examines severity ICC = 0.809, for the part that examines frequency ICC = 0.929). The 16-item scale, as a self assessment tool, demonstrated a high degree of content, criterion, and construct validity and test-retest reliability. The results support its use as a research tool to asses difficulty and frequency of ethical issues in community pharmacy setting. The validated scale needs to be further employed on a larger sample of pharmacists.
Processing data base information having nonwhite noise

DOEpatents

Gross, Kenneth C.; Morreale, Patricia

1995-01-01

A method and system for processing a set of data from an industrial process and/or a sensor. The method and system can include processing data from either real or calculated data related to an industrial process variable. One of the data sets can be an artificial signal data set generated by an autoregressive moving average technique. After obtaining two data sets associated with one physical variable, a difference function data set is obtained by determining the arithmetic difference between the two pairs of data sets over time. A frequency domain transformation is made of the difference function data set to obtain Fourier modes describing a composite function data set. A residual function data set is obtained by subtracting the composite function data set from the difference function data set and the residual function data set (free of nonwhite noise) is analyzed by a statistical probability ratio test to provide a validated data base.
Software for Automated Testing of Mission-Control Displays

NASA Technical Reports Server (NTRS)

OHagan, Brian

2004-01-01

MCC Display Cert Tool is a set of software tools for automated testing of computerterminal displays in spacecraft mission-control centers, including those of the space shuttle and the International Space Station. This software makes it possible to perform tests that are more thorough, take less time, and are less likely to lead to erroneous results, relative to tests performed manually. This software enables comparison of two sets of displays to report command and telemetry differences, generates test scripts for verifying telemetry and commands, and generates a documentary record containing display information, including version and corrective-maintenance data. At the time of reporting the information for this article, work was continuing to add a capability for validation of display parameters against a reconfiguration file.
Validation Data and Model Development for Fuel Assembly Response to Seismic Loads

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bardet, Philippe; Ricciardi, Guillaume

2016-01-31

Vibrations are inherently present in nuclear reactors, especially in cores and steam generators of pressurized water reactors (PWR). They can have significant effects on local heat transfer and wear and tear in the reactor and often set safety margins. The simulation of these multiphysics phenomena from first principles requires the coupling of several codes, which is one the most challenging tasks in modern computer simulation. Here an ambitious multiphysics multidisciplinary validation campaign is conducted. It relied on an integrated team of experimentalists and code developers to acquire benchmark and validation data for fluid-structure interaction codes. Data are focused on PWRmore » fuel bundle behavior during seismic transients.« less
Objective structured clinical examination for pharmacy students in Qatar: cultural and contextual barriers to assessment.

PubMed

Wilby, K J; Black, E K; Austin, Z; Mukhalalati, B; Aboulsoud, S; Khalifa, S I

2016-07-10

This study aimed to evaluate the feasibility and psychometric defensibility of implementing a comprehensive objective structured clinical examination (OSCE) on the complete pharmacy programme for pharmacy students in a Middle Eastern context, and to identify facilitators and barriers to implementation within new settings. Eight cases were developed, validated, and had standards set according to a blueprint, and were assessed with graduating pharmacy students. Assessor reliability was evaluated using inter-class coefficients (ICCs). Concurrent validity was evaluated by comparing OSCE results to professional skills course grades. Field notes were maintained to generate recommendations for implementation in other contexts. The examination pass mark was 424 points out of 700 (60.6%). All 23 participants passed. Mean performance was 74.6%. Low to moderate inter-rater reliability was obtained for analytical and global components (average ICC 0.77 and 0.48, respectively). In conclusion, OSCE was feasible in Qatar but context-related validity and reliability concerns must be addressed prior to future iterations in Qatar and elsewhere.
Cross-Study Homogeneity of Psoriasis Gene Expression in Skin across a Large Expression Range

PubMed Central

Kerkof, Keith; Timour, Martin; Russell, Christopher B.

2013-01-01

Background In psoriasis, only limited overlap between sets of genes identified as differentially expressed (psoriatic lesional vs. psoriatic non-lesional) was found using statistical and fold-change cut-offs. To provide a framework for utilizing prior psoriasis data sets we sought to understand the consistency of those sets. Methodology/Principal Findings Microarray expression profiling and qRT-PCR were used to characterize gene expression in PP and PN skin from psoriasis patients. cDNA (three new data sets) and cRNA hybridization (four existing data sets) data were compared using a common analysis pipeline. Agreement between data sets was assessed using varying qualitative and quantitative cut-offs to generate a DEG list in a source data set and then using other data sets to validate the list. Concordance increased from 67% across all probe sets to over 99% across more than 10,000 probe sets when statistical filters were employed. The fold-change behavior of individual genes tended to be consistent across the multiple data sets. We found that genes with <2-fold change values were quantitatively reproducible between pairs of data-sets. In a subset of transcripts with a role in inflammation changes detected by microarray were confirmed by qRT-PCR with high concordance. For transcripts with both PN and PP levels within the microarray dynamic range, microarray and qRT-PCR were quantitatively reproducible, including minimal fold-changes in IL13, TNFSF11, and TNFRSF11B and genes with >10-fold changes in either direction such as CHRM3, IL12B and IFNG. Conclusions/Significance Gene expression changes in psoriatic lesions were consistent across different studies, despite differences in patient selection, sample handling, and microarray platforms but between-study comparisons showed stronger agreement within than between platforms. We could use cut-offs as low as log10(ratio) = 0.1 (fold-change = 1.26), generating larger gene lists that validate on independent data sets. The reproducibility of PP signatures across data sets suggests that different sample sets can be productively compared. PMID:23308107
ConfocalGN: A minimalistic confocal image generator

NASA Astrophysics Data System (ADS)

Dmitrieff, Serge; Nédélec, François

Validating image analysis pipelines and training machine-learning segmentation algorithms require images with known features. Synthetic images can be used for this purpose, with the advantage that large reference sets can be produced easily. It is however essential to obtain images that are as realistic as possible in terms of noise and resolution, which is challenging in the field of microscopy. We describe ConfocalGN, a user-friendly software that can generate synthetic microscopy stacks from a ground truth (i.e. the observed object) specified as a 3D bitmap or a list of fluorophore coordinates. This software can analyze a real microscope image stack to set the noise parameters and directly generate new images of the object with noise characteristics similar to that of the sample image. With a minimal input from the user and a modular architecture, ConfocalGN is easily integrated with existing image analysis solutions.
Association Between a Germline OCA2 Polymorphism at Chromosome 15q13.1 and Estrogen Receptor–Negative Breast Cancer Survival

PubMed Central

Tyrer, Jonathan; Fasching, Peter A.; Beckmann, Matthias W.; Ekici, Arif B.; Schulz-Wendtland, Rüdiger; Bojesen, Stig E.; Nordestgaard, Børge G.; Flyger, Henrik; Milne, Roger L.; Arias, José Ignacio; Menéndez, Primitiva; Benítez, Javier; Chang-Claude, Jenny; Hein, Rebecca; Wang-Gohrke, Shan; Nevanlinna, Heli; Heikkinen, Tuomas; Aittomäki, Kristiina; Blomqvist, Carl; Margolin, Sara; Mannermaa, Arto; Kosma, Veli-Matti; Kataja, Vesa; Beesley, Jonathan; Chen, Xiaoqing; Chenevix-Trench, Georgia; Couch, Fergus J.; Olson, Janet E.; Fredericksen, Zachary S.; Wang, Xianshu; Giles, Graham G.; Severi, Gianluca; Baglietto, Laura; Southey, Melissa C.; Devilee, Peter; Tollenaar, Rob A. E. M.; Seynaeve, Caroline; García-Closas, Montserrat; Lissowska, Jolanta; Sherman, Mark E.; Bolton, Kelly L.; Hall, Per; Czene, Kamila; Cox, Angela; Brock, Ian W.; Elliott, Graeme C.; Reed, Malcolm W. R.; Greenberg, David; Anton-Culver, Hoda; Ziogas, Argyrios; Humphreys, Manjeet; Easton, Douglas F.; Caporaso, Neil E.; Pharoah, Paul D. P.

2010-01-01

Background Traditional prognostic factors for survival and treatment response of patients with breast cancer do not fully account for observed survival variation. We used available genotype data from a previously conducted two-stage, breast cancer susceptibility genome-wide association study (ie, Studies of Epidemiology and Risk factors in Cancer Heredity [SEARCH]) to investigate associations between variation in germline DNA and overall survival. Methods We evaluated possible associations between overall survival after a breast cancer diagnosis and 10 621 germline single-nucleotide polymorphisms (SNPs) from up to 3761 patients with invasive breast cancer (including 647 deaths and 26 978 person-years at risk) that were genotyped previously in the SEARCH study with high-density oligonucleotide microarrays (ie, hypothesis-generating set). Associations with all-cause mortality were assessed for each SNP by use of Cox regression analysis, generating a per rare allele hazard ratio (HR). To validate putative associations, we used patient genotype information that had been obtained with 5′ nuclease assay or mass spectrometry and overall survival information for up to 14 096 patients with invasive breast cancer (including 2303 deaths and 70 019 person-years at risk) from 15 international case–control studies (ie, validation set). Fixed-effects meta-analysis was used to generate an overall effect estimate in the validation dataset and in combined SEARCH and validation datasets. All statistical tests were two-sided. Results In the hypothesis-generating dataset, SNP rs4778137 (C>G) of the OCA2 gene at 15q13.1 was statistically significantly associated with overall survival among patients with estrogen receptor–negative tumors, with the rare G allele being associated with increased overall survival (HR of death per rare allele carried = 0.56, 95% confidence interval [CI] = 0.41 to 0.75, P = 9.2 × 10−5). This association was also observed in the validation dataset (HR of death per rare allele carried = 0.88, 95% CI = 0.78 to 0.99, P = .03) and in the combined dataset (HR of death per rare allele carried = 0.82, 95% CI = 0.73 to 0.92, P = 5 × 10−4). Conclusion The rare G allele of the OCA2 polymorphism, rs4778137, may be associated with improved overall survival among patients with estrogen receptor–negative breast cancer. PMID:20308648
Development of a Web Tool for Escherichia coli Subtyping Based on fimH Alleles.

PubMed

Roer, Louise; Tchesnokova, Veronika; Allesøe, Rosa; Muradova, Mariya; Chattopadhyay, Sujay; Ahrenfeldt, Johanne; Thomsen, Martin C F; Lund, Ole; Hansen, Frank; Hammerum, Anette M; Sokurenko, Evgeni; Hasman, Henrik

2017-08-01

The aim of this study was to construct a valid publicly available method for in silico fimH subtyping of Escherichia coli particularly suitable for differentiation of fine-resolution subgroups within clonal groups defined by standard multilocus sequence typing (MLST). FimTyper was constructed as a FASTA database containing all currently known fimH alleles. The software source code is publicly available at https://bitbucket.org/genomicepidemiology/fimtyper, the database is freely available at https://bitbucket.org/genomicepidemiology/fimtyper_db, and a service implementing the software is available at https://cge.cbs.dtu.dk/services/FimTyper FimTyper was validated on three data sets: one containing Sanger sequences of fimH alleles of 42 E. coli isolates generated prior to the current study (data set 1), one containing whole-genome sequence (WGS) data of 243 third-generation-cephalosporin-resistant E. coli isolates (data set 2), and one containing a randomly chosen subset of 40 E. coli isolates from data set 2 that were subjected to conventional fimH subtyping (data set 3). The combination of the three data sets enabled an evaluation and comparison of FimTyper on both Sanger sequences and WGS data. FimTyper correctly predicted all 42 fimH subtypes from the Sanger sequences from data set 1 and successfully analyzed all 243 draft genomes from data set 2. FimTyper subtyping of the Sanger sequences and WGS data from data set 3 were in complete agreement. Additionally, fimH subtyping was evaluated on a phylogenetic network of 122 sequence type 131 (ST131) E. coli isolates. There was perfect concordance between the typology and fimH -based subclones within ST131, with accurate identification of the pandemic multidrug-resistant clonal subgroup ST131- H 30. FimTyper provides a standardized tool, as a rapid alternative to conventional fimH subtyping, highly suitable for surveillance and outbreak detection. Copyright © 2017 American Society for Microbiology.
A reference data set of hillslope rainfall-runoff response, Panola Mountain Research Watershed, United States

USGS Publications Warehouse

Tromp-van, Meerveld; James, A.L.; McDonnell, Jeffery J.; Peters, N.E.

2008-01-01

Although many hillslope hydrologic investigations have been conducted in different climate, topographic, and geologic settings, subsurface stormflow remains a poorly characterized runoff process. Few, if any, of the existing data sets from these hillslope investigations are available for use by the scientific community for model development and validation or conceptualization of subsurface stormflow. We present a high-resolution spatial and temporal rainfall-runoff data set generated from the Panola Mountain Research Watershed trenched experimental hillslope. The data set includes surface and subsurface (bedrock surface) topographic information and time series of lateral subsurface flow at the trench, rainfall, and subsurface moisture content (distributed soil moisture content and groundwater levels) from January to June 2002. Copyright 2008 by the American Geophysical Union.
Automatic, semi-automatic and manual validation of urban drainage data.

PubMed

Branisavljević, N; Prodanović, D; Pavlović, D

2010-01-01

Advances in sensor technology and the possibility of automated long distance data transmission have made continuous measurements the preferable way of monitoring urban drainage processes. Usually, the collected data have to be processed by an expert in order to detect and mark the wrong data, remove them and replace them with interpolated data. In general, the first step in detecting the wrong, anomaly data is called the data quality assessment or data validation. Data validation consists of three parts: data preparation, validation scores generation and scores interpretation. This paper will present the overall framework for the data quality improvement system, suitable for automatic, semi-automatic or manual operation. The first two steps of the validation process are explained in more detail, using several validation methods on the same set of real-case data from the Belgrade sewer system. The final part of the validation process, which is the scores interpretation, needs to be further investigated on the developed system.
A New Generation of Crystallographic Validation Tools for the Protein Data Bank

PubMed Central

Read, Randy J.; Adams, Paul D.; Arendall, W. Bryan; Brunger, Axel T.; Emsley, Paul; Joosten, Robbie P.; Kleywegt, Gerard J.; Krissinel, Eugene B.; Lütteke, Thomas; Otwinowski, Zbyszek; Perrakis, Anastassis; Richardson, Jane S.; Sheffler, William H.; Smith, Janet L.; Tickle, Ian J.; Vriend, Gert; Zwart, Peter H.

2011-01-01

Summary This report presents the conclusions of the X-ray Validation Task Force of the worldwide Protein Data Bank (PDB). The PDB has expanded massively since current criteria for validation of deposited structures were adopted, allowing a much more sophisticated understanding of all the components of macromolecular crystals. The size of the PDB creates new opportunities to validate structures by comparison with the existing database, and the now-mandatory deposition of structure factors creates new opportunities to validate the underlying diffraction data. These developments highlighted the need for a new assessment of validation criteria. The Task Force recommends that a small set of validation data be presented in an easily understood format, relative to both the full PDB and the applicable resolution class, with greater detail available to interested users. Most importantly, we recommend that referees and editors judging the quality of structural experiments have access to a concise summary of well-established quality indicators. PMID:22000512
A new generation of crystallographic validation tools for the protein data bank.

PubMed

Read, Randy J; Adams, Paul D; Arendall, W Bryan; Brunger, Axel T; Emsley, Paul; Joosten, Robbie P; Kleywegt, Gerard J; Krissinel, Eugene B; Lütteke, Thomas; Otwinowski, Zbyszek; Perrakis, Anastassis; Richardson, Jane S; Sheffler, William H; Smith, Janet L; Tickle, Ian J; Vriend, Gert; Zwart, Peter H

2011-10-12

This report presents the conclusions of the X-ray Validation Task Force of the worldwide Protein Data Bank (PDB). The PDB has expanded massively since current criteria for validation of deposited structures were adopted, allowing a much more sophisticated understanding of all the components of macromolecular crystals. The size of the PDB creates new opportunities to validate structures by comparison with the existing database, and the now-mandatory deposition of structure factors creates new opportunities to validate the underlying diffraction data. These developments highlighted the need for a new assessment of validation criteria. The Task Force recommends that a small set of validation data be presented in an easily understood format, relative to both the full PDB and the applicable resolution class, with greater detail available to interested users. Most importantly, we recommend that referees and editors judging the quality of structural experiments have access to a concise summary of well-established quality indicators. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Means for Updating and Validating Mathematics Programs

ERIC Educational Resources Information Center

Dunlap, Laurie A.

2012-01-01

This article describes how to design program assessment for mathematics departments, in two-year and four-year colleges across the Midwest, based on a set of components that was generated from a Delphi survey. An example is provided to illustrate how this was done at a small four-year college. There is an alignment between these components and a…
Materials Database Development for Ballistic Impact Modeling

NASA Technical Reports Server (NTRS)

Pereira, J. Michael

2007-01-01

A set of experimental data is being generated under the Fundamental Aeronautics Program Supersonics project to help create and validate accurate computational impact models of jet engine impact events. The data generated will include material property data generated at a range of different strain rates, from 1x10(exp -4)/sec to 5x10(exp 4)/sec, over a range of temperatures. In addition, carefully instrumented ballistic impact tests will be conducted on flat plates and curved structures to provide material and structural response information to help validate the computational models. The material property data and the ballistic impact data will be generated using materials from the same lot, as far as possible. It was found in preliminary testing that the surface finish of test specimens has an effect on measured high strain rate tension response of AL2024. Both the maximum stress and maximum elongation are greater on specimens with a smoother finish. This report gives an overview of the testing that is being conducted and presents results of preliminary testing of the surface finish study.
Rectification of elemental image set and extraction of lens lattice by projective image transformation in integral imaging.

PubMed

Hong, Keehoon; Hong, Jisoo; Jung, Jae-Hyun; Park, Jae-Hyeung; Lee, Byoungho

2010-05-24

We propose a new method for rectifying a geometrical distortion in the elemental image set and extracting an accurate lens lattice lines by projective image transformation. The information of distortion in the acquired elemental image set is found by Hough transform algorithm. With this initial information of distortions, the acquired elemental image set is rectified automatically without the prior knowledge on the characteristics of pickup system by stratified image transformation procedure. Computer-generated elemental image sets with distortion on purpose are used for verifying the proposed rectification method. Experimentally-captured elemental image sets are optically reconstructed before and after the rectification by the proposed method. The experimental results support the validity of the proposed method with high accuracy of image rectification and lattice extraction.
The Development of Novel Chemical Fragment-Based Descriptors Using Frequent Common Subgraph Mining Approach and Their Application in QSAR Modeling.

PubMed

Khashan, Raed; Zheng, Weifan; Tropsha, Alexander

2014-03-01

We present a novel approach to generating fragment-based molecular descriptors. The molecules are represented by labeled undirected chemical graph. Fast Frequent Subgraph Mining (FFSM) is used to find chemical-fragments (subgraphs) that occur in at least a subset of all molecules in a dataset. The collection of frequent subgraphs (FSG) forms a dataset-specific descriptors whose values for each molecule are defined by the number of times each frequent fragment occurs in this molecule. We have employed the FSG descriptors to develop variable selection k Nearest Neighbor (kNN) QSAR models of several datasets with binary target property including Maximum Recommended Therapeutic Dose (MRTD), Salmonella Mutagenicity (Ames Genotoxicity), and P-Glycoprotein (PGP) data. Each dataset was divided into training, test, and validation sets to establish the statistical figures of merit reflecting the model validated predictive power. The classification accuracies of models for both training and test sets for all datasets exceeded 75 %, and the accuracy for the external validation sets exceeded 72 %. The model accuracies were comparable or better than those reported earlier in the literature for the same datasets. Furthermore, the use of fragment-based descriptors affords mechanistic interpretation of validated QSAR models in terms of essential chemical fragments responsible for the compounds' target property. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Rule extraction from minimal neural networks for credit card screening.

PubMed

Setiono, Rudy; Baesens, Bart; Mues, Christophe

2011-08-01

While feedforward neural networks have been widely accepted as effective tools for solving classification problems, the issue of finding the best network architecture remains unresolved, particularly so in real-world problem settings. We address this issue in the context of credit card screening, where it is important to not only find a neural network with good predictive performance but also one that facilitates a clear explanation of how it produces its predictions. We show that minimal neural networks with as few as one hidden unit provide good predictive accuracy, while having the added advantage of making it easier to generate concise and comprehensible classification rules for the user. To further reduce model size, a novel approach is suggested in which network connections from the input units to this hidden unit are removed by a very straightaway pruning procedure. In terms of predictive accuracy, both the minimized neural networks and the rule sets generated from them are shown to compare favorably with other neural network based classifiers. The rules generated from the minimized neural networks are concise and thus easier to validate in a real-life setting.
QSAR Modeling of Rat Acute Toxicity by Oral Exposure

PubMed Central

Zhu, Hao; Martin, Todd M.; Ye, Lin; Sedykh, Alexander; Young, Douglas M.; Tropsha, Alexander

2009-01-01

Few Quantitative Structure-Activity Relationship (QSAR) studies have successfully modeled large, diverse rodent toxicity endpoints. In this study, a comprehensive dataset of 7,385 compounds with their most conservative lethal dose (LD50) values has been compiled. A combinatorial QSAR approach has been employed to develop robust and predictive models of acute toxicity in rats caused by oral exposure to chemicals. To enable fair comparison between the predictive power of models generated in this study versus a commercial toxicity predictor, TOPKAT (Toxicity Prediction by Komputer Assisted Technology), a modeling subset of the entire dataset was selected that included all 3,472 compounds used in the TOPKAT’s training set. The remaining 3,913 compounds, which were not present in the TOPKAT training set, were used as the external validation set. QSAR models of five different types were developed for the modeling set. The prediction accuracy for the external validation set was estimated by determination coefficient R2 of linear regression between actual and predicted LD50 values. The use of the applicability domain threshold implemented in most models generally improved the external prediction accuracy but expectedly led to the decrease in chemical space coverage; depending on the applicability domain threshold, R2 ranged from 0.24 to 0.70. Ultimately, several consensus models were developed by averaging the predicted LD50 for every compound using all 5 models. The consensus models afforded higher prediction accuracy for the external validation dataset with the higher coverage as compared to individual constituent models. The validated consensus LD50 models developed in this study can be used as reliable computational predictors of in vivo acute toxicity. PMID:19845371
Capitalizing on Citizen Science Data for Validating Models and Generating Hypotheses Describing Meteorological Drivers of Mosquito-Borne Disease Risk

NASA Astrophysics Data System (ADS)

Boger, R. A.; Low, R.; Paull, S.; Anyamba, A.; Soebiyanto, R. P.

2017-12-01

Temperature and precipitation are important drivers of mosquito population dynamics, and a growing set of models have been proposed to characterize these relationships. Validation of these models, and development of broader theories across mosquito species and regions could nonetheless be improved by comparing observations from a global dataset of mosquito larvae with satellite-based measurements of meteorological variables. Citizen science data can be particularly useful for two such aspects of research into the meteorological drivers of mosquito populations: i) Broad-scale validation of mosquito distribution models and ii) Generation of quantitative hypotheses regarding changes to mosquito abundance and phenology across scales. The recently released GLOBE Observer Mosquito Habitat Mapper (GO-MHM) app engages citizen scientists in identifying vector taxa, mapping breeding sites and decommissioning non-natural habitats, and provides a potentially useful new tool for validating mosquito ubiquity projections based on the analysis of remotely sensed environmental data. Our early work with GO-MHM data focuses on two objectives: validating citizen science reports of Aedes aegypti distribution through comparison with accepted scientific data sources, and exploring the relationship between extreme temperature and precipitation events and subsequent observations of mosquito larvae. Ultimately the goal is to develop testable hypotheses regarding the shape and character of this relationship between mosquito species and regions.
MO-C-17A-03: A GPU-Based Method for Validating Deformable Image Registration in Head and Neck Radiotherapy Using Biomechanical Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neylon, J; Min, Y; Qi, S

2014-06-15

Purpose: Deformable image registration (DIR) plays a pivotal role in head and neck adaptive radiotherapy but a systematic validation of DIR algorithms has been limited by a lack of quantitative high-resolution groundtruth. We address this limitation by developing a GPU-based framework that provides a systematic DIR validation by generating (a) model-guided synthetic CTs representing posture and physiological changes, and (b) model-guided landmark-based validation. Method: The GPU-based framework was developed to generate massive mass-spring biomechanical models from patient simulation CTs and contoured structures. The biomechanical model represented soft tissue deformations for known rigid skeletal motion. Posture changes were simulated by articulatingmore » skeletal anatomy, which subsequently applied elastic corrective forces upon the soft tissue. Physiological changes such as tumor regression and weight loss were simulated in a biomechanically precise manner. Synthetic CT data was then generated from the deformed anatomy. The initial and final positions for one hundred randomly-chosen mass elements inside each of the internal contoured structures were recorded as ground truth data. The process was automated to create 45 synthetic CT datasets for a given patient CT. For instance, the head rotation was varied between +/− 4 degrees along each axis, and tumor volumes were systematically reduced up to 30%. Finally, the original CT and deformed synthetic CT were registered using an optical flow based DIR. Results: Each synthetic data creation took approximately 28 seconds of computation time. The number of landmarks per data set varied between two and three thousand. The validation method is able to perform sub-voxel analysis of the DIR, and report the results by structure, giving a much more in depth investigation of the error. Conclusions: We presented a GPU based high-resolution biomechanical head and neck model to validate DIR algorithms by generating CT equivalent 3D volumes with simulated posture changes and physiological regression.« less
RosettaHoles: rapid assessment of protein core packing for structure prediction, refinement, design, and validation.

PubMed

Sheffler, Will; Baker, David

2009-01-01

We present a novel method called RosettaHoles for visual and quantitative assessment of underpacking in the protein core. RosettaHoles generates a set of spherical cavity balls that fill the empty volume between atoms in the protein interior. For visualization, the cavity balls are aggregated into contiguous overlapping clusters and small cavities are discarded, leaving an uncluttered representation of the unfilled regions of space in a structure. For quantitative analysis, the cavity ball data are used to estimate the probability of observing a given cavity in a high-resolution crystal structure. RosettaHoles provides excellent discrimination between real and computationally generated structures, is predictive of incorrect regions in models, identifies problematic structures in the Protein Data Bank, and promises to be a useful validation tool for newly solved experimental structures.
RosettaHoles: Rapid assessment of protein core packing for structure prediction, refinement, design, and validation

PubMed Central

Sheffler, Will; Baker, David

2009-01-01

We present a novel method called RosettaHoles for visual and quantitative assessment of underpacking in the protein core. RosettaHoles generates a set of spherical cavity balls that fill the empty volume between atoms in the protein interior. For visualization, the cavity balls are aggregated into contiguous overlapping clusters and small cavities are discarded, leaving an uncluttered representation of the unfilled regions of space in a structure. For quantitative analysis, the cavity ball data are used to estimate the probability of observing a given cavity in a high-resolution crystal structure. RosettaHoles provides excellent discrimination between real and computationally generated structures, is predictive of incorrect regions in models, identifies problematic structures in the Protein Data Bank, and promises to be a useful validation tool for newly solved experimental structures. PMID:19177366
Improving Escalation of Care: Development and Validation of the Quality of Information Transfer Tool.

PubMed

Johnston, Maximilian J; Arora, Sonal; Pucher, Philip H; Reissis, Yannis; Hull, Louise; Huddy, Jeremy R; King, Dominic; Darzi, Ara

2016-03-01

To develop and provide validity and feasibility evidence for the QUality of Information Transfer (QUIT) tool. Prompt escalation of care in the setting of patient deterioration can prevent further harm. Escalation and information transfer skills are not currently measured in surgery. This study comprised 3 phases: the development (phase 1), validation (phase 2), and feasibility analysis (phase 3) of the QUIT tool. Phase 1 involved identification of core skills needed for successful escalation of care through literature review and 33 semistructured interviews with stakeholders. Phase 2 involved the generation of validity evidence for the tool using a simulated setting. Thirty surgeons assessed a deteriorating postoperative patient in a simulated ward and escalated their care to a senior colleague. The face and content validity were assessed using a survey. Construct and concurrent validity of the tool were determined by comparing performance scores using the QUIT tool with those measured using the Situation-Background-Assessment-Recommendation (SBAR) tool. Phase 3 was conducted using direct observation of escalation scenarios on surgical wards in 2 hospitals. A 7-category assessment tool was developed from phase 1 consisting of 24 items. Twenty-one of 24 items had excellent content validity (content validity index >0.8). All 7 categories and 18 of 24 (P < 0.05) items demonstrated construct validity. The correlation between the QUIT and SBAR tools used was strong indicating concurrent validity (r = 0.694, P < 0.001). Real-time scoring of escalation referrals was feasible and indicated that doctors currently have better information transfer skills than nurses when faced with a deteriorating patient. A validated tool to assess information transfer for deteriorating surgical patients was developed and tested using simulation and real-time clinical scenarios. It may improve the quality and safety of patient care on the surgical ward.
An exploratory study examining the influence of translation on the validity and reliability of qualitative data in nursing research.

PubMed

Twinn, S

1997-08-01

Although the complexity of undertaking qualitative research with non-English speaking informants has become increasingly recognized, few empirical studies exist which explore the influence of translation on the findings of the study. The aim of this exploratory study was therefore to examine the influence of translation on the reliability and validity of the findings of a qualitative research study. In-depth interviews were undertaken in Cantonese with a convenience sample of six women to explore their perceptions of factors influencing their uptake of Pap smears. Data analysis involved three stages. The first stage involved the translation and transcription of all the interviews into English independently by two translators as well as transcription into Chinese by a third researcher. The second stage involved content analysis of the three data sets to develop categories and themes and the third stage involved a comparison of the categories and themes generated from the Chinese and English data sets. Despite no significant differences in the major categories generated from the Chinese and English data, some minor differences were identified in the themes generated from the data. More significantly the results of the study demonstrated some important issues to consider when using translation in qualitative research, in particular the complexity of managing data when no equivalent word exists in the target language and the influence of the grammatical style on the analysis. In addition the findings raise questions about the significance of the conceptual framework of the research design and sampling to the validity of the study. The importance of using only one translator to maximize the reliability of the study was also demonstrated. In addition the author suggests the findings demonstrate particular problems in using translation in phenomenological research designs.
Recent Experimental Results Related to Ejector Mode Studies of Rocket-Based Combined Cycle (RBCC) Engines

NASA Technical Reports Server (NTRS)

Cramer, J. M.; Pal, S.; Marshall, W. M.; Santoro, R. J.

2003-01-01

Contents include the folloving: 1. Motivation. Support NASA's 3d generation launch vehicle technology program. RBCC is promising candidate for 3d generation propulsion system. 2. Approach. Focus on ejector mode p3erformance (Mach 0-3). Perform testing on established flowpath geometry. Use conventional propulsion measurement techniques. Use advanced optical diagnostic techniques to measure local combustion gas properties. 3. Objectives. Gain physical understanding of detailing mixing and combustion phenomena. Establish an experimental data set for CFD code development and validation.
Object-oriented regression for building predictive models with high dimensional omics data from translational studies.

PubMed

Zhao, Lue Ping; Bolouri, Hamid

2016-04-01

Maturing omics technologies enable researchers to generate high dimension omics data (HDOD) routinely in translational clinical studies. In the field of oncology, The Cancer Genome Atlas (TCGA) provided funding support to researchers to generate different types of omics data on a common set of biospecimens with accompanying clinical data and has made the data available for the research community to mine. One important application, and the focus of this manuscript, is to build predictive models for prognostic outcomes based on HDOD. To complement prevailing regression-based approaches, we propose to use an object-oriented regression (OOR) methodology to identify exemplars specified by HDOD patterns and to assess their associations with prognostic outcome. Through computing patient's similarities to these exemplars, the OOR-based predictive model produces a risk estimate using a patient's HDOD. The primary advantages of OOR are twofold: reducing the penalty of high dimensionality and retaining the interpretability to clinical practitioners. To illustrate its utility, we apply OOR to gene expression data from non-small cell lung cancer patients in TCGA and build a predictive model for prognostic survivorship among stage I patients, i.e., we stratify these patients by their prognostic survival risks beyond histological classifications. Identification of these high-risk patients helps oncologists to develop effective treatment protocols and post-treatment disease management plans. Using the TCGA data, the total sample is divided into training and validation data sets. After building up a predictive model in the training set, we compute risk scores from the predictive model, and validate associations of risk scores with prognostic outcome in the validation data (P-value=0.015). Copyright © 2016 Elsevier Inc. All rights reserved.
Object-Oriented Regression for Building Predictive Models with High Dimensional Omics Data from Translational Studies

PubMed Central

Zhao, Lue Ping; Bolouri, Hamid

2016-01-01

Maturing omics technologies enable researchers to generate high dimension omics data (HDOD) routinely in translational clinical studies. In the field of oncology, The Cancer Genome Atlas (TCGA) provided funding support to researchers to generate different types of omics data on a common set of biospecimens with accompanying clinical data and to make the data available for the research community to mine. One important application, and the focus of this manuscript, is to build predictive models for prognostic outcomes based on HDOD. To complement prevailing regression-based approaches, we propose to use an object-oriented regression (OOR) methodology to identify exemplars specified by HDOD patterns and to assess their associations with prognostic outcome. Through computing patient’s similarities to these exemplars, the OOR-based predictive model produces a risk estimate using a patient’s HDOD. The primary advantages of OOR are twofold: reducing the penalty of high dimensionality and retaining the interpretability to clinical practitioners. To illustrate its utility, we apply OOR to gene expression data from non-small cell lung cancer patients in TCGA and build a predictive model for prognostic survivorship among stage I patients, i.e., we stratify these patients by their prognostic survival risks beyond histological classifications. Identification of these high-risk patients helps oncologists to develop effective treatment protocols and post-treatment disease management plans. Using the TCGA data, the total sample is divided into training and validation data sets. After building up a predictive model in the training set, we compute risk scores from the predictive model, and validate associations of risk scores with prognostic outcome in the validation data (p=0.015). PMID:26972839
Leaf Transcriptome Sequencing for Identifying Genic-SSR Markers and SNP Heterozygosity in Crossbred Mango Variety 'Amrapali' (Mangifera indica L.).

PubMed

Mahato, Ajay Kumar; Sharma, Nimisha; Singh, Akshay; Srivastav, Manish; Jaiprakash; Singh, Sanjay Kumar; Singh, Anand Kumar; Sharma, Tilak Raj; Singh, Nagendra Kumar

2016-01-01

Mango (Mangifera indica L.) is called "king of fruits" due to its sweetness, richness of taste, diversity, large production volume and a variety of end usage. Despite its huge economic importance genomic resources in mango are scarce and genetics of useful horticultural traits are poorly understood. Here we generated deep coverage leaf RNA sequence data for mango parental varieties 'Neelam', 'Dashehari' and their hybrid 'Amrapali' using next generation sequencing technologies. De-novo sequence assembly generated 27,528, 20,771 and 35,182 transcripts for the three genotypes, respectively. The transcripts were further assembled into a non-redundant set of 70,057 unigenes that were used for SSR and SNP identification and annotation. Total 5,465 SSR loci were identified in 4,912 unigenes with 288 type I SSR (n ≥ 20 bp). One hundred type I SSR markers were randomly selected of which 43 yielded PCR amplicons of expected size in the first round of validation and were designated as validated genic-SSR markers. Further, 22,306 SNPs were identified by aligning high quality sequence reads of the three mango varieties to the reference unigene set, revealing significantly enhanced SNP heterozygosity in the hybrid Amrapali. The present study on leaf RNA sequencing of mango varieties and their hybrid provides useful genomic resource for genetic improvement of mango.
Leaf Transcriptome Sequencing for Identifying Genic-SSR Markers and SNP Heterozygosity in Crossbred Mango Variety ‘Amrapali’ (Mangifera indica L.)

PubMed Central

Mahato, Ajay Kumar; Sharma, Nimisha; Singh, Akshay; Srivastav, Manish; Jaiprakash; Singh, Sanjay Kumar; Singh, Anand Kumar; Sharma, Tilak Raj; Singh, Nagendra Kumar

2016-01-01

Mango (Mangifera indica L.) is called “king of fruits” due to its sweetness, richness of taste, diversity, large production volume and a variety of end usage. Despite its huge economic importance genomic resources in mango are scarce and genetics of useful horticultural traits are poorly understood. Here we generated deep coverage leaf RNA sequence data for mango parental varieties ‘Neelam’, ‘Dashehari’ and their hybrid ‘Amrapali’ using next generation sequencing technologies. De-novo sequence assembly generated 27,528, 20,771 and 35,182 transcripts for the three genotypes, respectively. The transcripts were further assembled into a non-redundant set of 70,057 unigenes that were used for SSR and SNP identification and annotation. Total 5,465 SSR loci were identified in 4,912 unigenes with 288 type I SSR (n ≥ 20 bp). One hundred type I SSR markers were randomly selected of which 43 yielded PCR amplicons of expected size in the first round of validation and were designated as validated genic-SSR markers. Further, 22,306 SNPs were identified by aligning high quality sequence reads of the three mango varieties to the reference unigene set, revealing significantly enhanced SNP heterozygosity in the hybrid Amrapali. The present study on leaf RNA sequencing of mango varieties and their hybrid provides useful genomic resource for genetic improvement of mango. PMID:27736892
Targeted exploration and analysis of large cross-platform human transcriptomic compendia

PubMed Central

Zhu, Qian; Wong, Aaron K; Krishnan, Arjun; Aure, Miriam R; Tadych, Alicja; Zhang, Ran; Corney, David C; Greene, Casey S; Bongo, Lars A; Kristensen, Vessela N; Charikar, Moses; Li, Kai; Troyanskaya, Olga G.

2016-01-01

We present SEEK (http://seek.princeton.edu), a query-based search engine across very large transcriptomic data collections, including thousands of human data sets from almost 50 microarray and next-generation sequencing platforms. SEEK uses a novel query-level cross-validation-based algorithm to automatically prioritize data sets relevant to the query and a robust search approach to identify query-coregulated genes, pathways, and processes. SEEK provides cross-platform handling, multi-gene query search, iterative metadata-based search refinement, and extensive visualization-based analysis options. PMID:25581801
16th IHIW: Global analysis of registry HLA haplotypes from 20 Million individuals: Report from the IHIW Registry Diversity Group

PubMed Central

Maiers, M; Gragert, L; Madbouly, A; Steiner, D; Marsh, S G E; Gourraud, P-A; Oudshoorn, M; Zanden, H; Schmidt, A H; Pingel, J; Hofmann, J; Müller, C; Eberhard, H-P

2013-01-01

This project has the goal to validate bioinformatics methods and tools for HLA haplotype frequency analysis specifically addressing unique issues of haematopoietic stem cell registry data sets. In addition to generating new methods and tools for the analysis of registry data sets, the intent is to produce a comprehensive analysis of HLA data from 20 million donors from the Bone Marrow Donors Worldwide (BMDW) database. This report summarizes the activity on this project as of the 16IHIW meeting in Liverpool. PMID:23280139
3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme.

PubMed

Murumkar, Prashant R; Giridhar, Rajani; Yadav, Mange Ram

2008-04-01

A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.

GIS-aided Statistical Landslide Susceptibility Modeling And Mapping Of Antipolo Rizal (Philippines)

NASA Astrophysics Data System (ADS)

Dumlao, A. J.; Victor, J. A.

2015-09-01

Slope instability associated with heavy rainfall or earthquake is a familiar geotechnical problem in the Philippines. The main objective of this study is to perform a detailed landslide susceptibility assessment of Antipolo City. The statistical method of assessment used was logistic regression. Landslide inventory was done through interpretation of aerial photographs and satellite images with corresponding field verification. In this study, morphologic and non-morphologic factors contributing to landslide occurrence and their corresponding spatial relationships were considered. The analysis of landslide susceptibility was implemented in a Geographic Information System (GIS). The 17320 randomly selected datasets were divided into training and test data sets. K- cross fold validation is done with k= 5. The subsamples are then fitted five times with k-1 training data set and the remaining fold as the validation data set. The AUROC of each model is validated using each corresponding data set. The AUROC of the five models are; 0.978, 0.977, 0.977, 0.974, and 0.979 respectively, implying that the models are effective in correctly predicting the occurrence and nonoccurrence of landslide activity. Field verification was also done. The landslide susceptibility map was then generated from the model. It is classified into four categories; low, moderate, high and very high susceptibility. The study also shows that almost 40% of Antipolo City has been assessed to be potentially dangerous areas in terms of landslide occurrence.
Development and validation of microsatellite markers for Brachiaria ruziziensis obtained by partial genome assembly of Illumina single-end reads

PubMed Central

2013-01-01

Background Brachiaria ruziziensis is one of the most important forage species planted in the tropics. The application of genomic tools to aid the selection of superior genotypes can provide support to B. ruziziensis breeding programs. However, there is a complete lack of information about the B. ruziziensis genome. Also, the availability of genomic tools, such as molecular markers, to support B. ruziziensis breeding programs is rather limited. Recently, next-generation sequencing technologies have been applied to generate sequence data for the identification of microsatellite regions and primer design. In this study, we present a first validated set of SSR markers for Brachiaria ruziziensis, selected from a de novo partial genome assembly of single-end Illumina reads. Results A total of 85,567 perfect microsatellite loci were detected in contigs with a minimum 10X coverage. We selected a set of 500 microsatellite loci identified in contigs with minimum 100X coverage for primer design and synthesis, and tested a subset of 269 primer pairs, 198 of which were polymorphic on 11 representative B. ruziziensis accessions. Descriptive statistics for these primer pairs are presented, as well as estimates of marker transferability to other relevant brachiaria species. Finally, a set of 11 multiplex panels containing the 30 most informative markers was validated and proposed for B. ruziziensis genetic analysis. Conclusions We show that the detection and development of microsatellite markers from genome assembled Illumina single-end DNA sequences is highly efficient. The developed markers are readily suitable for genetic analysis and marker assisted selection of Brachiaria ruziziensis. The use of this approach for microsatellite marker development is promising for species with limited genomic information, whose breeding programs would benefit from the use of genomic tools. To our knowledge, this is the first set of microsatellite markers developed for this important species. PMID:23324172
SCIAMACHY validation by aircraft remote measurements: design, execution, and first results of the SCIA-VALUE mission

NASA Astrophysics Data System (ADS)

Fix, A.; Ehret, G.; Flentje, H.; Poberaj, G.; Gottwald, M.; Finkenzeller, H.; Bremer, H.; Bruns, M.; Burrows, J. P.; Kleinböhl, A.; Küllmann, H.; Kuttippurath, J.; Richter, A.; Wang, P.; Heue, K.-P.; Platt, U.; Wagner, T.

2004-12-01

For the first time three different remote sensing instruments - a sub-millimeter radiometer, a differential optical absorption spectrometer in the UV-visible spectral range, and a lidar - were deployed aboard DLR's meteorological research aircraft Falcon 20 to validate a large number of SCIAMACHY level 2 and off-line data products such as O3, NO2, N2O, BrO, OClO, H2O, aerosols, and clouds. Within two main validation campaigns of the SCIA-VALUE mission (SCIAMACHY VALidation and Utilization Experiment) extended latitudinal cross-sections stretching from polar regions to the tropics as well as longitudinal cross sections at polar latitudes at about 70° N and the equator have been generated. This contribution gives an overview over the campaigns performed and reports on the observation strategy for achieving the validation goals. We also emphasize the synergetic use of the novel set of aircraft instrumentation and the usefulness of this innovative suite of remote sensing instruments for satellite validation.
SCIAMACHY validation by aircraft remote sensing: design, execution, and first measurement results of the SCIA-VALUE mission

NASA Astrophysics Data System (ADS)

Fix, A.; Ehret, G.; Flentje, H.; Poberaj, G.; Gottwald, M.; Finkenzeller, H.; Bremer, H.; Bruns, M.; Burrows, J. P.; Kleinböhl, A.; Küllmann, H.; Kuttippurath, J.; Richter, A.; Wang, P.; Heue, K.-P.; Platt, U.; Pundt, I.; Wagner, T.

2005-05-01

For the first time three different remote sensing instruments - a sub-millimeter radiometer, a differential optical absorption spectrometer in the UV-visible spectral range, and a lidar - were deployed aboard DLR's meteorological research aircraft Falcon 20 to validate a large number of SCIAMACHY level 2 and off-line data products such as O3, NO2, N2O, BrO, OClO, H2O, aerosols, and clouds. Within two validation campaigns of the SCIA-VALUE mission (SCIAMACHY VALidation and Utilization Experiment) extended latitudinal cross-sections stretching from polar regions to the tropics as well as longitudinal cross sections at polar latitudes at about 70° N and the equator were generated. This contribution gives an overview over the campaigns performed and reports on the observation strategy for achieving the validation goals. We also emphasize the synergetic use of the novel set of aircraft instrumentation and the usefulness of this innovative suite of remote sensing instruments for satellite validation.
Non-Technical Skills for Surgeons (NOTSS): Critical appraisal of its measurement properties.

PubMed

Jung, James J; Borkhoff, Cornelia M; Jüni, Peter; Grantcharov, Teodor P

2018-02-17

To critically appraise the development and measurement properties, including sensibility, reliability, and validity of the Non-Technical Skills of Surgeons (NOTSS) system. Articles that described development process of the NOTSS system were identified. Relevant primary studies that presented evidence of reliability and validity were identified through a comprehensive literature review. NOTSS was developed through robust item generation and reduction strategies. It was shown to have good content validity, acceptability, and feasibility. Inter-rater reliability increased with greater expertise and number of assessors. Studies demonstrated evidence of cross-sectional construct validity, in that the tool was able to differentiate known groups of varied non-technical skill levels. Evidence of longitudinal construct validity also existed to demonstrate that NOTSS detected changes in non-technical skills before and after targeted training. In populations and settings presented in our critical appraisal, NOTSS provided reliable and valid measurements of intraoperative non-technical skills of surgeons. Copyright © 2018 Elsevier Inc. All rights reserved.
Improving Arterial Spin Labeling by Using Deep Learning.

PubMed

Kim, Ki Hwan; Choi, Seung Hong; Park, Sung-Hong

2018-05-01

Purpose To develop a deep learning algorithm that generates arterial spin labeling (ASL) perfusion images with higher accuracy and robustness by using a smaller number of subtraction images. Materials and Methods For ASL image generation from pair-wise subtraction, we used a convolutional neural network (CNN) as a deep learning algorithm. The ground truth perfusion images were generated by averaging six or seven pairwise subtraction images acquired with (a) conventional pseudocontinuous arterial spin labeling from seven healthy subjects or (b) Hadamard-encoded pseudocontinuous ASL from 114 patients with various diseases. CNNs were trained to generate perfusion images from a smaller number (two or three) of subtraction images and evaluated by means of cross-validation. CNNs from the patient data sets were also tested on 26 separate stroke data sets. CNNs were compared with the conventional averaging method in terms of mean square error and radiologic score by using a paired t test and/or Wilcoxon signed-rank test. Results Mean square errors were approximately 40% lower than those of the conventional averaging method for the cross-validation with the healthy subjects and patients and the separate test with the patients who had experienced a stroke (P < .001). Region-of-interest analysis in stroke regions showed that cerebral blood flow maps from CNN (mean ± standard deviation, 19.7 mL per 100 g/min ± 9.7) had smaller mean square errors than those determined with the conventional averaging method (43.2 ± 29.8) (P < .001). Radiologic scoring demonstrated that CNNs suppressed noise and motion and/or segmentation artifacts better than the conventional averaging method did (P < .001). Conclusion CNNs provided superior perfusion image quality and more accurate perfusion measurement compared with those of the conventional averaging method for generation of ASL images from pair-wise subtraction images. © RSNA, 2017.
The pumping lid: investigating multi-material 3D printing for equipment-free, programmable generation of positive and negative pressures for microfluidic applications.

PubMed

Begolo, Stefano; Zhukov, Dmitriy V; Selck, David A; Li, Liang; Ismagilov, Rustem F

2014-12-21

Equipment-free pumping is a challenging problem and an active area of research in microfluidics, with applications for both laboratory and limited-resource settings. This paper describes the pumping lid method, a strategy to achieve equipment-free pumping by controlled generation of pressure. Pressure was generated using portable, lightweight, and disposable parts that can be integrated with existing microfluidic devices to simplify workflow and eliminate the need for pumping equipment. The development of this method was enabled by multi-material 3D printing, which allows fast prototyping, including composite parts that combine materials with different mechanical properties (e.g. both rigid and elastic materials in the same part). The first type of pumping lid we describe was used to produce predictable positive or negative pressures via controlled compression or expansion of gases. A model was developed to describe the pressures and flow rates generated with this approach and it was validated experimentally. Pressures were pre-programmed by the geometry of the parts and could be tuned further even while the experiment was in progress. Using multiple lids or a composite lid with different inlets enabled several solutions to be pumped independently in a single device. The second type of pumping lid, which relied on vapor-liquid equilibrium to generate pressure, was designed, modeled, and experimentally characterized. The pumping lid method was validated by controlling flow in different types of microfluidic applications, including the production of droplets, control of laminar flow profiles, and loading of SlipChip devices. We believe that applying the pumping lid methodology to existing microfluidic devices will enhance their use as portable diagnostic tools in limited resource settings as well as accelerate adoption of microfluidics in laboratories.
How do we estimate survival? External validation of a tool for survival estimation in patients with metastatic bone disease-decision analysis and comparison of three international patient populations.

PubMed

Piccioli, Andrea; Spinelli, M Silvia; Forsberg, Jonathan A; Wedin, Rikard; Healey, John H; Ippolito, Vincenzo; Daolio, Primo Andrea; Ruggieri, Pietro; Maccauro, Giulio; Gasbarrini, Alessandro; Biagini, Roberto; Piana, Raimondo; Fazioli, Flavio; Luzzati, Alessandro; Di Martino, Alberto; Nicolosi, Francesco; Camnasio, Francesco; Rosa, Michele Attilio; Campanacci, Domenico Andrea; Denaro, Vincenzo; Capanna, Rodolfo

2015-05-22

We recently developed a clinical decision support tool, capable of estimating the likelihood of survival at 3 and 12 months following surgery for patients with operable skeletal metastases. After making it publicly available on www.PATHFx.org , we attempted to externally validate it using independent, international data. We collected data from patients treated at 13 Italian orthopaedic oncology referral centers between 2010 and 2013, then applied to PATHFx, which generated a probability of survival at three and 12-months for each patient. We assessed accuracy using the area under the receiver-operating characteristic curve (AUC), clinical utility using Decision Curve Analysis (DCA), and compared the Italian patient data to the training set (United States) and first external validation set (Scandinavia). The Italian dataset contained 287 records with at least 12 months follow-up information. The AUCs for the three-month and 12-month estimates was 0.80 and 0.77, respectively. There were missing data, including the surgeon's estimate of survival that was missing in the majority of records. Physiologically, Italian patients were similar to patients in the training and first validation sets. However notable differences were observed in the proportion of those surviving three and 12-months, suggesting differences in referral patterns and perhaps indications for surgery. PATHFx was successfully validated in an Italian dataset containing missing data. This study demonstrates its broad applicability to European patients, even in centers with differing treatment philosophies from those previously studied.
Development and validation of a predictive score for perioperative transfusion in patients with hepatocellular carcinoma undergoing liver resection.

PubMed

Wang, Hai-Qing; Yang, Jian; Yang, Jia-Yin; Wang, Wen-Tao; Yan, Lu-Nan

2015-08-01

Liver resection is a major surgery requiring perioperative blood transfusion. Predicting the need for blood transfusion for patients undergoing liver resection is of great importance. The present study aimed to develop and validate a model for predicting transfusion requirement in HBV-related hepatocellular carcinoma patients undergoing liver resection. A total of 1543 consecutive liver resections were included in the study. Randomly selected sample set of 1080 cases (70% of the study cohort) were used to develop a predictive score for transfusion requirement and the remaining 30% (n=463) was used to validate the score. Based on the preoperative and predictable intraoperative parameters, logistic regression was used to identify risk factors and to create an integer score for the prediction of transfusion requirement. Extrahepatic procedure, major liver resection, hemoglobin level and platelets count were identified as independent predictors for transfusion requirement by logistic regression analysis. A score system integrating these 4 factors was stratified into three groups which could predict the risk of transfusion, with a rate of 11.4%, 24.7% and 57.4% for low, moderate and high risk, respectively. The prediction model appeared accurate with good discriminatory abilities, generating an area under the receiver operating characteristic curve of 0.736 in the development set and 0.709 in the validation set. We have developed and validated an integer-based risk score to predict perioperative transfusion for patients undergoing liver resection in a high-volume surgical center. This score allows identifying patients at a high risk and may alter transfusion practices.
Validation results of satellite mock-up capturing experiment using nets

NASA Astrophysics Data System (ADS)

Medina, Alberto; Cercós, Lorenzo; Stefanescu, Raluca M.; Benvenuto, Riccardo; Pesce, Vincenzo; Marcon, Marco; Lavagna, Michèle; González, Iván; Rodríguez López, Nuria; Wormnes, Kjetil

2017-05-01

The PATENDER activity (Net parametric characterization and parabolic flight), funded by the European Space Agency (ESA) via its Clean Space initiative, was aiming to validate a simulation tool for designing nets for capturing space debris. This validation has been performed through a set of different experiments under microgravity conditions where a net was launched capturing and wrapping a satellite mock-up. This paper presents the architecture of the thrown-net dynamics simulator together with the set-up of the deployment experiment and its trajectory reconstruction results on a parabolic flight (Novespace A-310, June 2015). The simulator has been implemented within the Blender framework in order to provide a highly configurable tool, able to reproduce different scenarios for Active Debris Removal missions. The experiment has been performed over thirty parabolas offering around 22 s of zero-g conditions. Flexible meshed fabric structure (the net) ejected from a container and propelled by corner masses (the bullets) arranged around its circumference have been launched at different initial velocities and launching angles using a pneumatic-based dedicated mechanism (representing the chaser satellite) against a target mock-up (the target satellite). High-speed motion cameras were recording the experiment allowing 3D reconstruction of the net motion. The net knots have been coloured to allow the images post-process using colour segmentation, stereo matching and iterative closest point (ICP) for knots tracking. The final objective of the activity was the validation of the net deployment and wrapping simulator using images recorded during the parabolic flight. The high-resolution images acquired have been post-processed to determine accurately the initial conditions and generate the reference data (position and velocity of all knots of the net along its deployment and wrapping of the target mock-up) for the simulator validation. The simulator has been properly configured according to the parabolic flight scenario, and executed in order to generate the validation data. Both datasets have been compared according to different metrics in order to perform the validation of the PATENDER simulator.
Development and validation of the AFIT scene and sensor emulator for testing (ASSET)

NASA Astrophysics Data System (ADS)

Young, Shannon R.; Steward, Bryan J.; Gross, Kevin C.

2017-05-01

ASSET is a physics-based model used to generate synthetic data sets of wide field of view (WFOV) electro-optical and infrared (EO/IR) sensors with realistic radiometric properties, noise characteristics, and sensor artifacts. It was developed to meet the need for applications where precise knowledge of the underlying truth is required but is impractical to obtain for real sensors. For example, due to accelerating advances in imaging technology, the volume of data available from WFOV EO/IR sensors has drastically increased over the past several decades, and as a result, there is a need for fast, robust, automatic detection and tracking algorithms. Evaluation of these algorithms is difficult for objects that traverse a wide area (100-10,000 km) because obtaining accurate truth for the full object trajectory often requires costly instrumentation. Additionally, tracking and detection algorithms perform differently depending on factors such as the object kinematics, environment, and sensor configuration. A variety of truth data sets spanning these parameters are needed for thorough testing, which is often cost prohibitive. The use of synthetic data sets for algorithm development allows for full control of scene parameters with full knowledge of truth. However, in order for analysis using synthetic data to be meaningful, the data must be truly representative of real sensor collections. ASSET aims to provide a means of generating such representative data sets for WFOV sensors operating in the visible through thermal infrared. The work reported here describes the ASSET model, as well as provides validation results from comparisons to laboratory imagers and satellite data (e.g. Landsat-8).
Benchmarking Multilayer-HySEA model for landslide generated tsunami. HTHMP validation process.

NASA Astrophysics Data System (ADS)

Macias, J.; Escalante, C.; Castro, M. J.

2017-12-01

Landslide tsunami hazard may be dominant along significant parts of the coastline around the world, in particular in the USA, as compared to hazards from other tsunamigenic sources. This fact motivated NTHMP about the need of benchmarking models for landslide generated tsunamis, following the same methodology already used for standard tsunami models when the source is seismic. To perform the above-mentioned validation process, a set of candidate benchmarks were proposed. These benchmarks are based on a subset of available laboratory data sets for solid slide experiments and deformable slide experiments, and include both submarine and subaerial slides. A benchmark based on a historic field event (Valdez, AK, 1964) close the list of proposed benchmarks. A total of 7 benchmarks. The Multilayer-HySEA model including non-hydrostatic effects has been used to perform all the benchmarking problems dealing with laboratory experiments proposed in the workshop that was organized at Texas A&M University - Galveston, on January 9-11, 2017 by NTHMP. The aim of this presentation is to show some of the latest numerical results obtained with the Multilayer-HySEA (non-hydrostatic) model in the framework of this validation effort.Acknowledgements. This research has been partially supported by the Spanish Government Research project SIMURISK (MTM2015-70490-C02-01-R) and University of Malaga, Campus de Excelencia Internacional Andalucía Tech. The GPU computations were performed at the Unit of Numerical Methods (University of Malaga).
Some unexamined aspects of analysis of covariance in pretest-posttest studies.

PubMed

Ganju, Jitendra

2004-09-01

The use of an analysis of covariance (ANCOVA) model in a pretest-posttest setting deserves to be studied separately from its use in other (non-pretest-posttest) settings. For pretest-posttest studies, the following points are made in this article: (a) If the familiar change from baseline model accurately describes the data-generating mechanism for a randomized study then it is impossible for unequal slopes to exist. Conversely, if unequal slopes exist, then it implies that the change from baseline model as a data-generating mechanism is inappropriate. An alternative data-generating model should be identified and the validity of the ANCOVA model should be demonstrated. (b) Under the usual assumptions of equal pretest and posttest within-subject error variances, the ratio of the standard error of a treatment contrast from a change from baseline analysis to that from ANCOVA is less than 2(1)/(2). (c) For an observational study it is possible for unequal slopes to exist even if the change from baseline model describes the data-generating mechanism. (d) Adjusting for the pretest variable in observational studies may actually introduce bias where none previously existed.
Online Cross-Validation-Based Ensemble Learning

PubMed Central

Benkeser, David; Ju, Cheng; Lendle, Sam; van der Laan, Mark

2017-01-01

Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to identify the algorithm with the best performance. We show that by basing estimates on the cross-validation-selected algorithm, we are asymptotically guaranteed to perform as well as the true, unknown best-performing algorithm. We provide extensions of this approach including online estimation of the optimal ensemble of candidate online estimators. We illustrate excellent performance of our methods using simulations and a real data example where we make streaming predictions of infectious disease incidence using data from a large database. PMID:28474419
Direct Validation of the Wall Interference Correction System of the Ames 11-Foot Transonic Wind Tunnel

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert; Boone, Alan R.

2003-01-01

Data from the test of a large semispan model was used to perform a direct validation of a wall interference correction system for a transonic slotted wall wind tunnel. At first, different sets of uncorrected aerodynamic coefficients were generated by physically changing the boundary condition of the test section walls. Then, wall interference corrections were computed and applied to all data points. Finally, an interpolation of the corrected aerodynamic coefficients was performed. This interpolation made sure that the corrected Mach number of a given run would be constant. Overall, the agreement between corresponding interpolated lift, drag, and pitching moment coefficient sets was very good. Buoyancy corrections were also investigated. These studies showed that the accuracy goal of one drag count may only be achieved if reliable estimates of the wall interference induced buoyancy correction are available during a test.
The Self-Presentation Motives for Physical Activity Questionnaire: Instrument Development and Preliminary Construct Validity Evidence.

PubMed

Howle, Timothy C; Dimmock, James A; Whipp, Peter R; Jackson, Ben

2015-06-01

With the aim of advancing the literature on impression management in physical activity settings, we developed a theoretically derived 2 by 2 instrument that was designed to measure different types of context-specific self-presentation motives. Following item generation and expert review (Study 1), the instrument was completed by 206 group exercise class attendees (Study 2) and 463 high school physical education students (Study 3). Our analyses supported the intended factor structure (i.e., reflecting acquisitive-agentic, acquisitive-communal, protective-agentic, and protective-communal motives). We found some support for construct validity, and the self-presentation motives were associated with variables of theoretical and applied interest (e.g., impression motivation and construction, social anxiety, social and achievement goals, efficacy beliefs, engagement). Taken together, the results indicate that the Self-presentation Motives for Physical Activity Questionnaire (SMPAQ) may be useful for measuring various types of self-presentation motives in physical activity settings.
Remote sensing imagery classification using multi-objective gravitational search algorithm

NASA Astrophysics Data System (ADS)

Zhang, Aizhu; Sun, Genyun; Wang, Zhenjie

2016-10-01

Simultaneous optimization of different validity measures can capture different data characteristics of remote sensing imagery (RSI) and thereby achieving high quality classification results. In this paper, two conflicting cluster validity indices, the Xie-Beni (XB) index and the fuzzy C-means (FCM) (Jm) measure, are integrated with a diversity-enhanced and memory-based multi-objective gravitational search algorithm (DMMOGSA) to present a novel multi-objective optimization based RSI classification method. In this method, the Gabor filter method is firstly implemented to extract texture features of RSI. Then, the texture features are syncretized with the spectral features to construct the spatial-spectral feature space/set of the RSI. Afterwards, cluster of the spectral-spatial feature set is carried out on the basis of the proposed method. To be specific, cluster centers are randomly generated initially. After that, the cluster centers are updated and optimized adaptively by employing the DMMOGSA. Accordingly, a set of non-dominated cluster centers are obtained. Therefore, numbers of image classification results of RSI are produced and users can pick up the most promising one according to their problem requirements. To quantitatively and qualitatively validate the effectiveness of the proposed method, the proposed classification method was applied to classifier two aerial high-resolution remote sensing imageries. The obtained classification results are compared with that produced by two single cluster validity index based and two state-of-the-art multi-objective optimization algorithms based classification results. Comparison results show that the proposed method can achieve more accurate RSI classification.
A generalized land-use scenario generator: a case study for the Congo basin.

NASA Astrophysics Data System (ADS)

Caporaso, Luca; Tompkins, Adrian Mark; Biondi, Riccardo; Bell, Jean Pierre

2014-05-01

The impact of deforestation on climate is often studied using highly idealized "instant deforestation" experiments due to the lack of generalized deforestation scenario generators coupled to climate model land-surface schemes. A new deforestation scenario generator has been therefore developed to fulfill this role known as the deforestation ScenArio GEnerator, or FOREST-SAGE. The model produces distributed maps of deforestation rates that account for local factors such as proximity to transport networks, distance weighted population density, forest fragmentation and presence of protected areas and logging concessions. The integrated deforestation risk is scaled to give the deforestation rate as specified by macro-region scenarios such as "business as usual" or "increased protection legislation" which are a function of future time. FOREST-SAGE was initialized and validated using the MODerate Resolution Imaging Spectroradiometer Vegetation Continuous Field data. Despite the high cloud coverage of Congo Basin over the year, we were able to validate the results with high confidence from 2001 to 2010 in a large forested area. Furthermore a set of scenarios has been used to provide a range of possible pathways for the evolution of land-use change over the Congo Basin for the period 2010-2030.
Representation of research hypotheses

PubMed Central

2011-01-01

Background Hypotheses are now being automatically produced on an industrial scale by computers in biology, e.g. the annotation of a genome is essentially a large set of hypotheses generated by sequence similarity programs; and robot scientists enable the full automation of a scientific investigation, including generation and testing of research hypotheses. Results This paper proposes a logically defined way for recording automatically generated hypotheses in machine amenable way. The proposed formalism allows the description of complete hypotheses sets as specified input and output for scientific investigations. The formalism supports the decomposition of research hypotheses into more specialised hypotheses if that is required by an application. Hypotheses are represented in an operational way – it is possible to design an experiment to test them. The explicit formal description of research hypotheses promotes the explicit formal description of the results and conclusions of an investigation. The paper also proposes a framework for automated hypotheses generation. We demonstrate how the key components of the proposed framework are implemented in the Robot Scientist “Adam”. Conclusions A formal representation of automatically generated research hypotheses can help to improve the way humans produce, record, and validate research hypotheses. Availability http://www.aber.ac.uk/en/cs/research/cb/projects/robotscientist/results/ PMID:21624164
Mspire-Simulator: LC-MS shotgun proteomic simulator for creating realistic gold standard data.

PubMed

Noyce, Andrew B; Smith, Rob; Dalgleish, James; Taylor, Ryan M; Erb, K C; Okuda, Nozomu; Prince, John T

2013-12-06

The most important step in any quantitative proteomic pipeline is feature detection (aka peak picking). However, generating quality hand-annotated data sets to validate the algorithms, especially for lower abundance peaks, is nearly impossible. An alternative for creating gold standard data is to simulate it with features closely mimicking real data. We present Mspire-Simulator, a free, open-source shotgun proteomic simulator that goes beyond previous simulation attempts by generating LC-MS features with realistic m/z and intensity variance along with other noise components. It also includes machine-learned models for retention time and peak intensity prediction and a genetic algorithm to custom fit model parameters for experimental data sets. We show that these methods are applicable to data from three different mass spectrometers, including two fundamentally different types, and show visually and analytically that simulated peaks are nearly indistinguishable from actual data. Researchers can use simulated data to rigorously test quantitation software, and proteomic researchers may benefit from overlaying simulated data on actual data sets.

Instrument development and validation of a quality scale for historical research papers (QSHRP): a pilot study.

PubMed

Kelly, Jacinta; Watson, Roger

2014-12-01

To report a pilot study for the development and validation of an instrument to measure quality in historical research papers. There are no set criteria to assess historical papers published in nursing journals. A three phase mixed method sequential confirmatory design. In 2012, we used a three-phase approach to item generation and content evaluation. In phase 1, we consulted nursing historians using an online survey comprising three open-ended questions and revised the items. In phase 2, we evaluated the revised items for relevance with expert historians using a 4-point Likert scale and Content Validity Index calculation. In phase 3, we conducted reliability testing of the instrument using a 3-point Likert scale. In phase 1, 121 responses were generated via the online survey and revised to 40 interrogatively phrased items. In phase 2, five items with an Item Content Validity Index score of ≥0·7 remained. In phase 3, responses from historians resulted in 100% agreement to questions 1, 2 and 4 and 89% and 78%, respectively, to questions 3 and 5. Items for the QSHRP have been identified, content validated and reliability tested. This scale improves on previous scales, which over-emphasized source criticism. However, a full-scale study is needed with nursing historians to increase its robustness. © 2014 John Wiley & Sons Ltd.
Multi-time scale energy management of wind farms based on comprehensive evaluation technology

NASA Astrophysics Data System (ADS)

Xu, Y. P.; Huang, Y. H.; Liu, Z. J.; Wang, Y. F.; Li, Z. Y.; Guo, L.

2017-11-01

A novel energy management of wind farms is proposed in this paper. Firstly, a novel comprehensive evaluation system is proposed to quantify economic properties of each wind farm to make the energy management more economical and reasonable. Then, a combination of multi time-scale schedule method is proposed to develop a novel energy management. The day-ahead schedule optimizes unit commitment of thermal power generators. The intraday schedule is established to optimize power generation plan for all thermal power generating units, hydroelectric generating sets and wind power plants. At last, the power generation plan can be timely revised in the process of on-line schedule. The paper concludes with simulations conducted on a real provincial integrated energy system in northeast China. Simulation results have validated the proposed model and corresponding solving algorithms.
Single case design studies in music therapy: resurrecting experimental evidence in small group and individual music therapy clinical settings.

PubMed

Geist, Kamile; Hitchcock, John H

2014-01-01

The profession would benefit from greater and routine generation of causal evidence pertaining to the impact of music therapy interventions on client outcomes. One way to meet this goal is to revisit the use of Single Case Designs (SCDs) in clinical practice and research endeavors in music therapy. Given the appropriate setting and goals, this design can be accomplished with small sample sizes and it is often appropriate for studying music therapy interventions. In this article, we promote and discuss implementation of SCD studies in music therapy settings, review the meaning of internal study validity and by extension the notion of causality, and describe two of the most commonly used SCDs to demonstrate how they can help generate causal evidence to inform the field. In closing, we describe the need for replication and future meta-analysis of SCD studies completed in music therapy settings. SCD studies are both feasible and appropriate for use in music therapy clinical practice settings, particularly for testing effectiveness of interventions for individuals or small groups. © the American Music Therapy Association 2014. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies

PubMed Central

2010-01-01

Background All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences. Results The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%. Conclusions This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant applications in evaluating engineered antibodies, and may be adapted for evaluating engineered proteins in general. PMID:20144194
Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies.

PubMed

David, Maria Pamela C; Concepcion, Gisela P; Padlan, Eduardo A

2010-02-08

All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences. The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%. This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant applications in evaluating engineered antibodies, and may be adapted for evaluating engineered proteins in general.
Reliable pre-eclampsia pathways based on multiple independent microarray data sets.

PubMed

Kawasaki, Kaoru; Kondoh, Eiji; Chigusa, Yoshitsugu; Ujita, Mari; Murakami, Ryusuke; Mogami, Haruta; Brown, J B; Okuno, Yasushi; Konishi, Ikuo

2015-02-01

Pre-eclampsia is a multifactorial disorder characterized by heterogeneous clinical manifestations. Gene expression profiling of preeclamptic placenta have provided different and even opposite results, partly due to data compromised by various experimental artefacts. Here we aimed to identify reliable pre-eclampsia-specific pathways using multiple independent microarray data sets. Gene expression data of control and preeclamptic placentas were obtained from Gene Expression Omnibus. Single-sample gene-set enrichment analysis was performed to generate gene-set activation scores of 9707 pathways obtained from the Molecular Signatures Database. Candidate pathways were identified by t-test-based screening using data sets, GSE10588, GSE14722 and GSE25906. Additionally, recursive feature elimination was applied to arrive at a further reduced set of pathways. To assess the validity of the pre-eclampsia pathways, a statistically-validated protocol was executed using five data sets including two independent other validation data sets, GSE30186, GSE44711. Quantitative real-time PCR was performed for genes in a panel of potential pre-eclampsia pathways using placentas of 20 women with normal or severe preeclamptic singleton pregnancies (n = 10, respectively). A panel of ten pathways were found to discriminate women with pre-eclampsia from controls with high accuracy. Among these were pathways not previously associated with pre-eclampsia, such as the GABA receptor pathway, as well as pathways that have already been linked to pre-eclampsia, such as the glutathione and CDKN1C pathways. mRNA expression of GABRA3 (GABA receptor pathway), GCLC and GCLM (glutathione metabolic pathway), and CDKN1C was significantly reduced in the preeclamptic placentas. In conclusion, ten accurate and reliable pre-eclampsia pathways were identified based on multiple independent microarray data sets. A pathway-based classification may be a worthwhile approach to elucidate the pathogenesis of pre-eclampsia. © The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Assuring the Quality of Next-Generation Sequencing in Clinical Microbiology and Public Health Laboratories.

PubMed

Gargis, Amy S; Kalman, Lisa; Lubin, Ira M

2016-12-01

Clinical microbiology and public health laboratories are beginning to utilize next-generation sequencing (NGS) for a range of applications. This technology has the potential to transform the field by providing approaches that will complement, or even replace, many conventional laboratory tests. While the benefits of NGS are significant, the complexities of these assays require an evolving set of standards to ensure testing quality. Regulatory and accreditation requirements, professional guidelines, and best practices that help ensure the quality of NGS-based tests are emerging. This review highlights currently available standards and guidelines for the implementation of NGS in the clinical and public health laboratory setting, and it includes considerations for NGS test validation, quality control procedures, proficiency testing, and reference materials. Copyright © 2016, American Society for Microbiology. All Rights Reserved.
Development and evaluation of the Korean Health Literacy Instrument.

PubMed

Kang, Soo Jin; Lee, Tae Wha; Paasche-Orlow, Michael K; Kim, Gwang Suk; Won, Hee Kwan

2014-01-01

The purpose of this study is to develop and validate the Korean Health Literacy Instrument, which measures the capacity to understand and use health-related information and make informed health decisions in Korean adults. In Phase 1, 33 initial items were generated to measure functional, interactive, and critical health literacy with prose, document, and numeracy tasks. These items included content from health promotion, disease management, and health navigation contexts. Content validity assessment was conducted by an expert panel, and 11 items were excluded. In Phase 2, the 22 remaining items were administered to a convenience sample of 292 adults from community and clinical settings. Exploratory factor and item difficulty and discrimination analyses were conducted and four items with low discrimination were deleted. In Phase 3, the remaining 18 items were administered to a convenience sample of 315 adults 40-64 years of age from community and clinical settings. A confirmatory factor analysis was performed to test the construct validity of the instrument. The Korean Health Literacy Instrument has a range of 0 to 18. The mean score in our validation study was 11.98. The instrument exhibited an internal consistency reliability coefficient of 0.82, and a test-retest reliability of 0.89. The instrument is suitable for screening individuals who have limited health literacy skills. Future studies are needed to further define the psychometric properties and predictive validity of the Korean Health Literacy Instrument.
Hypoalbuminemia, Low Base Excess Values, and Tachypnea Predict 28-Day Mortality in Severe Sepsis and Septic Shock Patients in the Emergency Department.

PubMed

Seo, Min Ho; Choa, Minhong; You, Je Sung; Lee, Hye Sun; Hong, Jung Hwa; Park, Yoo Seok; Chung, Sung Phil; Park, Incheol

2016-11-01

The objective of this study was to develop a new nomogram that can predict 28-day mortality in severe sepsis and/or septic shock patients using a combination of several biomarkers that are inexpensive and readily available in most emergency departments, with and without scoring systems. We enrolled 561 patients who were admitted to an emergency department (ED) and received early goal-directed therapy for severe sepsis or septic shock. We collected demographic data, initial vital signs, and laboratory data sampled at the time of ED admission. Patients were randomly assigned to a training set or validation set. For the training set, we generated models using independent variables associated with 28-day mortality by multivariate analysis, and developed a new nomogram for the prediction of 28-day mortality. Thereafter, the diagnostic accuracy of the nomogram was tested using the validation set. The prediction model that included albumin, base excess, and respiratory rate demonstrated the largest area under the receiver operating characteristic curve (AUC) value of 0.8173 [95% confidence interval (CI), 0.7605-0.8741]. The logistic analysis revealed that a conventional scoring system was not associated with 28-day mortality. In the validation set, the discrimination of a newly developed nomogram was also good, with an AUC value of 0.7537 (95% CI, 0.6563-0.8512). Our new nomogram is valuable in predicting the 28-day mortality of patients with severe sepsis and/or septic shock in the emergency department. Moreover, our readily available nomogram is superior to conventional scoring systems in predicting mortality.
Assess and Predict Automatic Generation Control Performances for Thermal Power Generation Units Based on Modeling Techniques

NASA Astrophysics Data System (ADS)

Zhao, Yan; Yang, Zijiang; Gao, Song; Liu, Jinbiao

2018-02-01

Automatic generation control(AGC) is a key technology to maintain real time power generation and load balance, and to ensure the quality of power supply. Power grids require each power generation unit to have a satisfactory AGC performance, being specified in two detailed rules. The two rules provide a set of indices to measure the AGC performance of power generation unit. However, the commonly-used method to calculate these indices is based on particular data samples from AGC responses and will lead to incorrect results in practice. This paper proposes a new method to estimate the AGC performance indices via system identification techniques. In addition, a nonlinear regression model between performance indices and load command is built in order to predict the AGC performance indices. The effectiveness of the proposed method is validated through industrial case studies.
Equivalent circuit and characteristic simulation of a brushless electrically excited synchronous wind power generator

NASA Astrophysics Data System (ADS)

Wang, Hao; Zhang, Fengge; Guan, Tao; Yu, Siyang

2017-09-01

A brushless electrically excited synchronous generator (BEESG) with a hybrid rotor is a novel electrically excited synchronous generator. The BEESG proposed in this paper is composed of a conventional stator with two different sets of windings with different pole numbers, and a hybrid rotor with powerful coupling capacity. The pole number of the rotor is different from those of the stator windings. Thus, an analysis method different from that applied to conventional generators should be applied to the BEESG. In view of this problem, the equivalent circuit and electromagnetic torque expression of the BEESG are derived on the basis of electromagnetic relation of the proposed generator. The generator is simulated and tested experimentally using the established equivalent circuit model. The experimental and simulation data are then analyzed and compared. Results show the validity of the equivalent circuit model.
45 CFR 162.1011 - Valid code sets.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 45 Public Welfare 1 2012-10-01 2012-10-01 false Valid code sets. 162.1011 Section 162.1011 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES ADMINISTRATIVE DATA STANDARDS AND RELATED REQUIREMENTS ADMINISTRATIVE REQUIREMENTS Code Sets § 162.1011 Valid code sets. Each code set is valid within the dates...
45 CFR 162.1011 - Valid code sets.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 1 2013-10-01 2013-10-01 false Valid code sets. 162.1011 Section 162.1011 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES ADMINISTRATIVE DATA STANDARDS AND RELATED REQUIREMENTS ADMINISTRATIVE REQUIREMENTS Code Sets § 162.1011 Valid code sets. Each code set is valid within the dates...
45 CFR 162.1011 - Valid code sets.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 45 Public Welfare 1 2010-10-01 2010-10-01 false Valid code sets. 162.1011 Section 162.1011 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES ADMINISTRATIVE DATA STANDARDS AND RELATED REQUIREMENTS ADMINISTRATIVE REQUIREMENTS Code Sets § 162.1011 Valid code sets. Each code set is valid within the dates...
45 CFR 162.1011 - Valid code sets.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 45 Public Welfare 1 2014-10-01 2014-10-01 false Valid code sets. 162.1011 Section 162.1011 Public Welfare Department of Health and Human Services ADMINISTRATIVE DATA STANDARDS AND RELATED REQUIREMENTS ADMINISTRATIVE REQUIREMENTS Code Sets § 162.1011 Valid code sets. Each code set is valid within the dates...
45 CFR 162.1011 - Valid code sets.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 45 Public Welfare 1 2011-10-01 2011-10-01 false Valid code sets. 162.1011 Section 162.1011 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES ADMINISTRATIVE DATA STANDARDS AND RELATED REQUIREMENTS ADMINISTRATIVE REQUIREMENTS Code Sets § 162.1011 Valid code sets. Each code set is valid within the dates...
True Randomness from Big Data.

PubMed

Papakonstantinou, Periklis A; Woodruff, David P; Yang, Guang

2016-09-26

Generating random bits is a difficult task, which is important for physical systems simulation, cryptography, and many applications that rely on high-quality random bits. Our contribution is to show how to generate provably random bits from uncertain events whose outcomes are routinely recorded in the form of massive data sets. These include scientific data sets, such as in astronomics, genomics, as well as data produced by individuals, such as internet search logs, sensor networks, and social network feeds. We view the generation of such data as the sampling process from a big source, which is a random variable of size at least a few gigabytes. Our view initiates the study of big sources in the randomness extraction literature. Previous approaches for big sources rely on statistical assumptions about the samples. We introduce a general method that provably extracts almost-uniform random bits from big sources and extensively validate it empirically on real data sets. The experimental findings indicate that our method is efficient enough to handle large enough sources, while previous extractor constructions are not efficient enough to be practical. Quality-wise, our method at least matches quantum randomness expanders and classical world empirical extractors as measured by standardized tests.
Automated diagnosis of coronary artery disease based on data mining and fuzzy modeling.

PubMed

Tsipouras, Markos G; Exarchos, Themis P; Fotiadis, Dimitrios I; Kotsia, Anna P; Vakalis, Konstantinos V; Naka, Katerina K; Michalis, Lampros K

2008-07-01

A fuzzy rule-based decision support system (DSS) is presented for the diagnosis of coronary artery disease (CAD). The system is automatically generated from an initial annotated dataset, using a four stage methodology: 1) induction of a decision tree from the data; 2) extraction of a set of rules from the decision tree, in disjunctive normal form and formulation of a crisp model; 3) transformation of the crisp set of rules into a fuzzy model; and 4) optimization of the parameters of the fuzzy model. The dataset used for the DSS generation and evaluation consists of 199 subjects, each one characterized by 19 features, including demographic and history data, as well as laboratory examinations. Tenfold cross validation is employed, and the average sensitivity and specificity obtained is 62% and 54%, respectively, using the set of rules extracted from the decision tree (first and second stages), while the average sensitivity and specificity increase to 80% and 65%, respectively, when the fuzzification and optimization stages are used. The system offers several advantages since it is automatically generated, it provides CAD diagnosis based on easily and noninvasively acquired features, and is able to provide interpretation for the decisions made.
B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis

PubMed Central

Towfic, Fadi; Gupta, Shakti; Honavar, Vasant; Subramaniam, Shankar

2012-01-01

The initiation of B-cell ligand recognition is a critical step for the generation of an immune response against foreign bodies. We sought to identify the biochemical pathways involved in the B-cell ligand recognition cascade and sets of ligands that trigger similar immunological responses. We utilized several comparative approaches to analyze the gene coexpression networks generated from a set of microarray experiments spanning 33 different ligands. First, we compared the degree distributions of the generated networks. Second, we utilized a pairwise network alignment algorithm, BiNA, to align the networks based on the hubs in the networks. Third, we aligned the networks based on a set of KEGG pathways. We summarized our results by constructing a consensus hierarchy of pathways that are involved in B cell ligand recognition. The resulting pathways were further validated through literature for their common physiological responses. Collectively, the results based on our comparative analyses of degree distributions, alignment of hubs, and alignment based on KEGG pathways provide a basis for molecular characterization of the immune response states of B-cells and demonstrate the power of comparative approaches (e.g., gene coexpression network alignment algorithms) in elucidating biochemical pathways involved in complex signaling events in cells. PMID:22917187
True Randomness from Big Data

NASA Astrophysics Data System (ADS)

Papakonstantinou, Periklis A.; Woodruff, David P.; Yang, Guang

2016-09-01

Generating random bits is a difficult task, which is important for physical systems simulation, cryptography, and many applications that rely on high-quality random bits. Our contribution is to show how to generate provably random bits from uncertain events whose outcomes are routinely recorded in the form of massive data sets. These include scientific data sets, such as in astronomics, genomics, as well as data produced by individuals, such as internet search logs, sensor networks, and social network feeds. We view the generation of such data as the sampling process from a big source, which is a random variable of size at least a few gigabytes. Our view initiates the study of big sources in the randomness extraction literature. Previous approaches for big sources rely on statistical assumptions about the samples. We introduce a general method that provably extracts almost-uniform random bits from big sources and extensively validate it empirically on real data sets. The experimental findings indicate that our method is efficient enough to handle large enough sources, while previous extractor constructions are not efficient enough to be practical. Quality-wise, our method at least matches quantum randomness expanders and classical world empirical extractors as measured by standardized tests.

True Randomness from Big Data

PubMed Central

Papakonstantinou, Periklis A.; Woodruff, David P.; Yang, Guang

2016-01-01

Generating random bits is a difficult task, which is important for physical systems simulation, cryptography, and many applications that rely on high-quality random bits. Our contribution is to show how to generate provably random bits from uncertain events whose outcomes are routinely recorded in the form of massive data sets. These include scientific data sets, such as in astronomics, genomics, as well as data produced by individuals, such as internet search logs, sensor networks, and social network feeds. We view the generation of such data as the sampling process from a big source, which is a random variable of size at least a few gigabytes. Our view initiates the study of big sources in the randomness extraction literature. Previous approaches for big sources rely on statistical assumptions about the samples. We introduce a general method that provably extracts almost-uniform random bits from big sources and extensively validate it empirically on real data sets. The experimental findings indicate that our method is efficient enough to handle large enough sources, while previous extractor constructions are not efficient enough to be practical. Quality-wise, our method at least matches quantum randomness expanders and classical world empirical extractors as measured by standardized tests. PMID:27666514
MicroRNAs for Detection of Pancreatic Neoplasia

PubMed Central

Vila-Navarro, Elena; Vila-Casadesús, Maria; Moreira, Leticia; Duran-Sanchon, Saray; Sinha, Rupal; Ginés, Àngels; Fernández-Esparrach, Glòria; Miquel, Rosa; Cuatrecasas, Miriam; Castells, Antoni; Lozano, Juan José; Gironella, Meritxell

2017-01-01

Objective: The aim of our study was to analyze the miRNome of pancreatic ductal adenocarcinoma (PDAC) and its preneoplastic lesion intraductal papillary mucinous neoplasm (IPMN), to find new microRNA (miRNA)-based biomarkers for early detection of pancreatic neoplasia. Objective: Effective early detection methods for PDAC are needed. miRNAs are good biomarker candidates. Methods: Pancreatic tissues (n = 165) were obtained from patients with PDAC, IPMN, or from control individuals (C), from Hospital Clínic of Barcelona. Biomarker discovery was done using next-generation sequencing in a discovery set of 18 surgical samples (11 PDAC, 4 IPMN, 3 C). MiRNA validation was carried out by quantitative reverse transcriptase PCR in 2 different set of samples. Set 1—52 surgical samples (24 PDAC, 7 IPMN, 6 chronic pancreatitis, 15 C), and set 2—95 endoscopic ultrasound-guided fine-needle aspirations (60 PDAC, 9 IPMN, 26 C). Results: In all, 607 and 396 miRNAs were significantly deregulated in PDAC and IPMN versus C. Of them, 40 miRNAs commonly overexpressed in both PDAC and IPMN were selected for further validation. Among them, significant up-regulation of 31 and 30 miRNAs was confirmed by quantitative reverse transcriptase PCR in samples from set 1 and set 2, respectively. Conclusions: miRNome analysis shows that PDAC and IPMN have differential miRNA profiles with respect to C, with a large number of deregulated miRNAs shared by both neoplastic lesions. Indeed, we have identified and validated 30 miRNAs whose expression is significantly increased in PDAC and IPMN lesions. The feasibility of detecting these miRNAs in endoscopic ultrasound-guided fine-needle aspiration samples makes them good biomarker candidates for early detection of pancreatic cancer. PMID:27232245
Development and Validation of a Measure of Quality of Life for the Young Elderly in Sri Lanka.

PubMed

de Silva, Sudirikku Hennadige Padmal; Jayasuriya, Anura Rohan; Rajapaksa, Lalini Chandika; de Silva, Ambepitiyawaduge Pubudu; Barraclough, Simon

2016-01-01

Sri Lanka has one of the fastest aging populations in the world. Measurement of quality of life (QoL) in the elderly needs instruments developed that encompass the sociocultural settings. An instrument was developed to measure QoL in the young elderly in Sri Lanka (QLI-YES), using accepted methods to generate and reduce items. The measure was validated using a community sample. Construct, criterion and predictive validity and reliability were tested. A first-order model of 24 items with 6 domains was found to have good fit indices (CMIN/df = 1.567, RMR = 0.05, CFI = 0.95, and RMSEA = 0.053). Both criterion and predictive validity were demonstrated. Good internal consistency reliability (Cronbach's α = 0.93) was shown. The development of the QLI-YES using a societal perspective relevant to the social and cultural beliefs has resulted in a robust and valid instrument to measure QoL for the young elderly in Sri Lanka. © 2015 APJPH.
Development and validation of a new instrument for testing functional health literacy in Japanese adults.

PubMed

Nakagami, Katsuyuki; Yamauchi, Toyoaki; Noguchi, Hiroyuki; Maeda, Tohru; Nakagami, Tomoko

2014-06-01

This study aimed to develop a reliable and valid measure of functional health literacy in a Japanese clinical setting. Test development consisted of three phases: generation of an item pool, consultation with experts to assess content validity, and comparison with external criteria (the Japanese Health Knowledge Test) to assess criterion validity. A trial version of the test was administered to 535 Japanese outpatients. Internal consistency reliability, calculated by Cronbach's alpha, was 0.81, and concurrent validity was moderate. Receiver Operating Characteristics and Item Response Theory were used to classify patients as having adequate, marginal, or inadequate functional health literacy. Both inadequate and marginal functional health literacy were associated with older age, lower income, lower educational attainment, and poor health knowledge. The time required to complete the test was 10-15 min. This test should enable health workers to better identify patients with inadequate health literacy. © 2013 Wiley Publishing Asia Pty Ltd.
Development and Validation of a Measure of Quality of Life for the Young Elderly in Sri Lanka

PubMed Central

de Silva, Sudirikku Hennadige Padmal; Jayasuriya, Anura Rohan; Rajapaksa, Lalini Chandika; de Silva, Ambepitiyawaduge Pubudu; Barraclough, Simon

2016-01-01

Sri Lanka has one of the fastest aging populations in the world. Measurement of quality of life (QoL) in the elderly needs instruments developed that encompass the sociocultural settings. An instrument was developed to measure QoL in the young elderly in Sri Lanka (QLI-YES), using accepted methods to generate and reduce items. The measure was validated using a community sample. Construct, criterion and predictive validity and reliability were tested. A first-order model of 24 items with 6 domains was found to have good fit indices (CMIN/df = 1.567, RMR = 0.05, CFI = 0.95, and RMSEA = 0.053). Both criterion and predictive validity were demonstrated. Good internal consistency reliability (Cronbach’s α = 0.93) was shown. The development of the QLI-YES using a societal perspective relevant to the social and cultural beliefs has resulted in a robust and valid instrument to measure QoL for the young elderly in Sri Lanka. PMID:26712893
Electronic Health Management

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Saha, Sankalita; Goebel, Kai

2011-01-01

Accelerated aging methodologies for electrolytic components have been designed and accelerated aging experiments have been carried out. The methodology is based on imposing electrical and/or thermal overstresses via electrical power cycling in order to mimic the real world operation behavior. Data are collected in-situ and offline in order to periodically characterize the devices' electrical performance as it ages. The data generated through these experiments are meant to provide capability for the validation of prognostic algorithms (both model-based and data-driven). Furthermore, the data allow validation of physics-based and empirical based degradation models for this type of capacitor. A first set of models and algorithms has been designed and tested on the data.
The Abbreviation of Personality, or how to Measure 200 Personality Scales with 200 Items

PubMed Central

Yarkoni, Tal

2010-01-01

Personality researchers have recently advocated the use of very short personality inventories in order to minimize administration time. However, few such inventories are currently available. Here I introduce an automated method that can be used to abbreviate virtually any personality inventory with minimal effort. After validating the method against existing measures in Studies 1 and 2, a new 181-item inventory is generated in Study 3 that accurately recaptures scores on 8 different broadband inventories comprising 203 distinct scales. Collectively, the results validate a powerful new way to improve the efficiency of personality measurement in research settings. PMID:20419061
A comparison of the validity of the five-factor model (FFM) personality disorder prototypes. Using FFM self-report and interview measures.

PubMed

Miller, Joshua D; Bagby, R Michael; Pilkonis, Paul A

2005-12-01

Recent studies have demonstrated that personality disorders (PDs) can be assessed via a prototype-matching technique, which enables researchers and clinicians to match an individual's five-factor model (FFM) personality profile to an expert-generated prototype. The current study examined the relations between these prototype scores, using interview and self-report data, and PD symptoms in an outpatient sample (N = 115). Both sets of PD prototype scores demonstrated significant convergent validity with PD symptom counts, suggesting that the FFM PD prototype scores are appropriate for use with both sources of data.
ALHAT System Validation

NASA Technical Reports Server (NTRS)

Brady, Tye; Bailey, Erik; Crain, Timothy; Paschall, Stephen

2011-01-01

NASA has embarked on a multiyear technology development effort to develop a safe and precise lunar landing capability. The Autonomous Landing and Hazard Avoidance Technology (ALHAT) Project is investigating a range of landing hazard detection methods while developing a hazard avoidance capability to best field test the proper set of relevant autonomous GNC technologies. Ultimately, the advancement of these technologies through the ALHAT Project will provide an ALHAT System capable of enabling next generation lunar lander vehicles to globally land precisely and safely regardless of lighting condition. This paper provides an overview of the ALHAT System and describes recent validation experiments that have advanced the highly capable GNC architecture.
World Ocean Circulation Experiment

NASA Technical Reports Server (NTRS)

Clarke, R. Allyn

1992-01-01

The oceans are an equal partner with the atmosphere in the global climate system. The World Ocean Circulation Experiment is presently being implemented to improve ocean models that are useful for climate prediction both by encouraging more model development but more importantly by providing quality data sets that can be used to force or to validate such models. WOCE is the first oceanographic experiment that plans to generate and to use multiparameter global ocean data sets. In order for WOCE to succeed, oceanographers must establish and learn to use more effective methods of assembling, quality controlling, manipulating and distributing oceanographic data.
Phase 1 Validation Testing and Simulation for the WEC-Sim Open Source Code

NASA Astrophysics Data System (ADS)

Ruehl, K.; Michelen, C.; Gunawan, B.; Bosma, B.; Simmons, A.; Lomonaco, P.

2015-12-01

WEC-Sim is an open source code to model wave energy converters performance in operational waves, developed by Sandia and NREL and funded by the US DOE. The code is a time-domain modeling tool developed in MATLAB/SIMULINK using the multibody dynamics solver SimMechanics, and solves the WEC's governing equations of motion using the Cummins time-domain impulse response formulation in 6 degrees of freedom. The WEC-Sim code has undergone verification through code-to-code comparisons; however validation of the code has been limited to publicly available experimental data sets. While these data sets provide preliminary code validation, the experimental tests were not explicitly designed for code validation, and as a result are limited in their ability to validate the full functionality of the WEC-Sim code. Therefore, dedicated physical model tests for WEC-Sim validation have been performed. This presentation provides an overview of the WEC-Sim validation experimental wave tank tests performed at the Oregon State University's Directional Wave Basin at Hinsdale Wave Research Laboratory. Phase 1 of experimental testing was focused on device characterization and completed in Fall 2015. Phase 2 is focused on WEC performance and scheduled for Winter 2015/2016. These experimental tests were designed explicitly to validate the performance of WEC-Sim code, and its new feature additions. Upon completion, the WEC-Sim validation data set will be made publicly available to the wave energy community. For the physical model test, a controllable model of a floating wave energy converter has been designed and constructed. The instrumentation includes state-of-the-art devices to measure pressure fields, motions in 6 DOF, multi-axial load cells, torque transducers, position transducers, and encoders. The model also incorporates a fully programmable Power-Take-Off system which can be used to generate or absorb wave energy. Numerical simulations of the experiments using WEC-Sim will be presented. These simulations highlight the code features included in the latest release of WEC-Sim (v1.2), including: wave directionality, nonlinear hydrostatics and hydrodynamics, user-defined wave elevation time-series, state space radiation, and WEC-Sim compatibility with BEMIO (open source AQWA/WAMI/NEMOH coefficient parser).
New generation pharmacogenomic tools: a SNP linkage disequilibrium Map, validated SNP assay resource, and high-throughput instrumentation system for large-scale genetic studies.

PubMed

De La Vega, Francisco M; Dailey, David; Ziegle, Janet; Williams, Julie; Madden, Dawn; Gilbert, Dennis A

2002-06-01

Since public and private efforts announced the first draft of the human genome last year, researchers have reported great numbers of single nucleotide polymorphisms (SNPs). We believe that the availability of well-mapped, quality SNP markers constitutes the gateway to a revolution in genetics and personalized medicine that will lead to better diagnosis and treatment of common complex disorders. A new generation of tools and public SNP resources for pharmacogenomic and genetic studies--specifically for candidate-gene, candidate-region, and whole-genome association studies--will form part of the new scientific landscape. This will only be possible through the greater accessibility of SNP resources and superior high-throughput instrumentation-assay systems that enable affordable, highly productive large-scale genetic studies. We are contributing to this effort by developing a high-quality linkage disequilibrium SNP marker map and an accompanying set of ready-to-use, validated SNP assays across every gene in the human genome. This effort incorporates both the public sequence and SNP data sources, and Celera Genomics' human genome assembly and enormous resource ofphysically mapped SNPs (approximately 4,000,000 unique records). This article discusses our approach and methodology for designing the map, choosing quality SNPs, designing and validating these assays, and obtaining population frequency ofthe polymorphisms. We also discuss an advanced, high-performance SNP assay chemisty--a new generation of the TaqMan probe-based, 5' nuclease assay-and high-throughput instrumentation-software system for large-scale genotyping. We provide the new SNP map and validation information, validated SNP assays and reagents, and instrumentation systems as a novel resource for genetic discoveries.
Robot path planning using a genetic algorithm

NASA Technical Reports Server (NTRS)

Cleghorn, Timothy F.; Baffes, Paul T.; Wang, Liu

1988-01-01

Robot path planning can refer either to a mobile vehicle such as a Mars Rover, or to an end effector on an arm moving through a cluttered workspace. In both instances there may exist many solutions, some of which are better than others, either in terms of distance traversed, energy expended, or joint angle or reach capabilities. A path planning program has been developed based upon a genetic algorithm. This program assumes global knowledge of the terrain or workspace, and provides a family of good paths between the initial and final points. Initially, a set of valid random paths are constructed. Successive generations of valid paths are obtained using one of several possible reproduction strategies similar to those found in biological communities. A fitness function is defined to describe the goodness of the path, in this case including length, slope, and obstacle avoidance considerations. It was found that with some reproduction strategies, the average value of the fitness function improved for successive generations, and that by saving the best paths of each generation, one could quite rapidly obtain a collection of good candidate solutions.
MS Data Miner: a web-based software tool to analyze, compare, and share mass spectrometry protein identifications.

PubMed

Dyrlund, Thomas F; Poulsen, Ebbe T; Scavenius, Carsten; Sanggaard, Kristian W; Enghild, Jan J

2012-09-01

Data processing and analysis of proteomics data are challenging and time consuming. In this paper, we present MS Data Miner (MDM) (http://sourceforge.net/p/msdataminer), a freely available web-based software solution aimed at minimizing the time required for the analysis, validation, data comparison, and presentation of data files generated in MS software, including Mascot (Matrix Science), Mascot Distiller (Matrix Science), and ProteinPilot (AB Sciex). The program was developed to significantly decrease the time required to process large proteomic data sets for publication. This open sourced system includes a spectra validation system and an automatic screenshot generation tool for Mascot-assigned spectra. In addition, a Gene Ontology term analysis function and a tool for generating comparative Excel data reports are included. We illustrate the benefits of MDM during a proteomics study comprised of more than 200 LC-MS/MS analyses recorded on an AB Sciex TripleTOF 5600, identifying more than 3000 unique proteins and 3.5 million peptides. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Insight into the structural requirements of proton pump inhibitors based on CoMFA and CoMSIA studies.

PubMed

Nayana, M Ravi Shashi; Sekhar, Y Nataraja; Nandyala, Haritha; Muttineni, Ravikumar; Bairy, Santosh Kumar; Singh, Kriti; Mahmood, S K

2008-10-01

In the present study, a series of 179 quinoline and quinazoline heterocyclic analogues exhibiting inhibitory activity against Gastric (H+/K+)-ATPase were investigated using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) methods. Both the models exhibited good correlation between the calculated 3D-QSAR fields and the observed biological activity for the respective training set compounds. The most optimal CoMFA and CoMSIA models yielded significant leave-one-out cross-validation coefficient, q(2) of 0.777, 0.744 and conventional cross-validation coefficient, r(2) of 0.927, 0.914 respectively. The predictive ability of generated models was tested on a set of 52 compounds having broad range of activity. CoMFA and CoMSIA yielded predicted activities for test set compounds with r(pred)(2) of 0.893 and 0.917 respectively. These validation tests not only revealed the robustness of the models but also demonstrated that for our models r(pred)(2) based on the mean activity of test set compounds can accurately estimate external predictivity. The factors affecting activity were analyzed carefully according to standard coefficient contour maps of steric, electrostatic, hydrophobic, acceptor and donor fields derived from the CoMFA and CoMSIA. These contour plots identified several key features which explain the wide range of activities. The results obtained from models offer important structural insight into designing novel peptic-ulcer inhibitors prior to their synthesis.
Clinical validation of the 50 gene AmpliSeq Cancer Panel V2 for use on a next generation sequencing platform using formalin fixed, paraffin embedded and fine needle aspiration tumour specimens.

PubMed

Rathi, Vivek; Wright, Gavin; Constantin, Diana; Chang, Siok; Pham, Huong; Jones, Kerryn; Palios, Atha; Mclachlan, Sue-Anne; Conron, Matthew; McKelvie, Penny; Williams, Richard

2017-01-01

The advent of massively parallel sequencing has caused a paradigm shift in the ways cancer is treated, as personalised therapy becomes a reality. More and more laboratories are looking to introduce next generation sequencing (NGS) as a tool for mutational analysis, as this technology has many advantages compared to conventional platforms like Sanger sequencing. In Australia all massively parallel sequencing platforms are still considered in-house in vitro diagnostic tools by the National Association of Testing Authorities (NATA) and a comprehensive analytical validation of all assays, and not just mere verification, is a strict requirement before accreditation can be granted for clinical testing on these platforms. Analytical validation of assays on NGS platforms can prove to be extremely challenging for pathology laboratories. Although there are many affordable and easily accessible NGS instruments available, there are no standardised guidelines as yet for clinical validation of NGS assays. We present an accreditation development procedure that was both comprehensive and applicable in a setting of hospital laboratory for NGS services. This approach may also be applied to other NGS applications in service laboratories. Copyright © 2016 Royal College of Pathologists of Australasia. Published by Elsevier B.V. All rights reserved.
E-novo: an automated workflow for efficient structure-based lead optimization.

PubMed

Pearce, Bradley C; Langley, David R; Kang, Jia; Huang, Hongwei; Kulkarni, Amit

2009-07-01

An automated E-Novo protocol designed as a structure-based lead optimization tool was prepared through Pipeline Pilot with existing CHARMm components in Discovery Studio. A scaffold core having 3D binding coordinates of interest is generated from a ligand-bound protein structural model. Ligands of interest are generated from the scaffold using an R-group fragmentation/enumeration tool within E-Novo, with their cores aligned. The ligand side chains are conformationally sampled and are subjected to core-constrained protein docking, using a modified CHARMm-based CDOCKER method to generate top poses along with CDOCKER energies. In the final stage of E-Novo, a physics-based binding energy scoring function ranks the top ligand CDOCKER poses using a more accurate Molecular Mechanics-Generalized Born with Surface Area method. Correlation of the calculated ligand binding energies with experimental binding affinities were used to validate protocol performance. Inhibitors of Src tyrosine kinase, CDK2 kinase, beta-secretase, factor Xa, HIV protease, and thrombin were used to test the protocol using published ligand crystal structure data within reasonably defined binding sites. In-house Respiratory Syncytial Virus inhibitor data were used as a more challenging test set using a hand-built binding model. Least squares fits for all data sets suggested reasonable validation of the protocol within the context of observed ligand binding poses. The E-Novo protocol provides a convenient all-in-one structure-based design process for rapid assessment and scoring of lead optimization libraries.
A cis-regulatory logic simulator.

PubMed

Zeigler, Robert D; Gertz, Jason; Cohen, Barak A

2007-07-27

A major goal of computational studies of gene regulation is to accurately predict the expression of genes based on the cis-regulatory content of their promoters. The development of computational methods to decode the interactions among cis-regulatory elements has been slow, in part, because it is difficult to know, without extensive experimental validation, whether a particular method identifies the correct cis-regulatory interactions that underlie a given set of expression data. There is an urgent need for test expression data in which the interactions among cis-regulatory sites that produce the data are known. The ability to rapidly generate such data sets would facilitate the development and comparison of computational methods that predict gene expression patterns from promoter sequence. We developed a gene expression simulator which generates expression data using user-defined interactions between cis-regulatory sites. The simulator can incorporate additive, cooperative, competitive, and synergistic interactions between regulatory elements. Constraints on the spacing, distance, and orientation of regulatory elements and their interactions may also be defined and Gaussian noise can be added to the expression values. The simulator allows for a data transformation that simulates the sigmoid shape of expression levels from real promoters. We found good agreement between sets of simulated promoters and predicted regulatory modules from real expression data. We present several data sets that may be useful for testing new methodologies for predicting gene expression from promoter sequence. We developed a flexible gene expression simulator that rapidly generates large numbers of simulated promoters and their corresponding transcriptional output based on specified interactions between cis-regulatory sites. When appropriate rule sets are used, the data generated by our simulator faithfully reproduces experimentally derived data sets. We anticipate that using simulated gene expression data sets will facilitate the direct comparison of computational strategies to predict gene expression from promoter sequence. The source code is available online and as additional material. The test sets are available as additional material.
Gene Ontology synonym generation rules lead to increased performance in biomedical concept recognition.

PubMed

Funk, Christopher S; Cohen, K Bretonnel; Hunter, Lawrence E; Verspoor, Karin M

2016-09-09

Gene Ontology (GO) terms represent the standard for annotation and representation of molecular functions, biological processes and cellular compartments, but a large gap exists between the way concepts are represented in the ontology and how they are expressed in natural language text. The construction of highly specific GO terms is formulaic, consisting of parts and pieces from more simple terms. We present two different types of manually generated rules to help capture the variation of how GO terms can appear in natural language text. The first set of rules takes into account the compositional nature of GO and recursively decomposes the terms into their smallest constituent parts. The second set of rules generates derivational variations of these smaller terms and compositionally combines all generated variants to form the original term. By applying both types of rules, new synonyms are generated for two-thirds of all GO terms and an increase in F-measure performance for recognition of GO on the CRAFT corpus from 0.498 to 0.636 is observed. Additionally, we evaluated the combination of both types of rules over one million full text documents from Elsevier; manual validation and error analysis show we are able to recognize GO concepts with reasonable accuracy (88 %) based on random sampling of annotations. In this work we present a set of simple synonym generation rules that utilize the highly compositional and formulaic nature of the Gene Ontology concepts. We illustrate how the generated synonyms aid in improving recognition of GO concepts on two different biomedical corpora. We discuss other applications of our rules for GO ontology quality assurance, explore the issue of overgeneration, and provide examples of how similar methodologies could be applied to other biomedical terminologies. Additionally, we provide all generated synonyms for use by the text-mining community.
The development and validation of the Closed-set Mandarin Sentence (CMS) test.

PubMed

Tao, Duo-Duo; Fu, Qian-Jie; Galvin, John J; Yu, Ya-Feng

2017-09-01

Matrix-styled sentence tests offer a closed-set paradigm that may be useful when evaluating speech intelligibility. Ideally, sentence test materials should reflect the distribution of phonemes within the target language. We developed and validated the Closed-set Mandarin Sentence (CMS) test to assess Mandarin speech intelligibility in noise. CMS test materials were selected to be familiar words and to represent the natural distribution of vowels, consonants, and lexical tones found in Mandarin Chinese. Ten key words in each of five categories (Name, Verb, Number, Color, and Fruit) were produced by a native Mandarin talker, resulting in a total of 50 words that could be combined to produce 100,000 unique sentences. Normative data were collected in 10 normal-hearing, adult Mandarin-speaking Chinese listeners using a closed-set test paradigm. Two test runs were conducted for each subject, and 20 sentences per run were randomly generated while ensuring that each word was presented only twice in each run. First, the level of the words in each category were adjusted to produce equal intelligibility in noise. Test-retest reliability for word-in-sentence recognition was excellent according to Cronbach's alpha (0.952). After the category level adjustments, speech reception thresholds (SRTs) for sentences in noise, defined as the signal-to-noise ratio (SNR) that produced 50% correct whole sentence recognition, were adaptively measured by adjusting the SNR according to the correctness of response. The mean SRT was -7.9 (SE=0.41) and -8.1 (SE=0.34) dB for runs 1 and 2, respectively. The mean standard deviation across runs was 0.93 dB, and paired t-tests showed no significant difference between runs 1 and 2 (p=0.74) despite random sentences being generated for each run and each subject. The results suggest that the CMS provides large stimulus set with which to repeatedly and reliably measure Mandarin-speaking listeners' speech understanding in noise using a closed-set paradigm.

A Simple Screening Approach To Prioritize Genes for Functional Analysis Identifies a Role for Interferon Regulatory Factor 7 in the Control of Respiratory Syncytial Virus Disease

PubMed Central

McDonald, Jacqueline U.; Kaforou, Myrsini; Clare, Simon; Hale, Christine; Ivanova, Maria; Huntley, Derek; Dorner, Marcus; Wright, Victoria J.; Levin, Michael; Martinon-Torres, Federico; Herberg, Jethro A.

2016-01-01

ABSTRACT Greater understanding of the functions of host gene products in response to infection is required. While many of these genes enable pathogen clearance, some enhance pathogen growth or contribute to disease symptoms. Many studies have profiled transcriptomic and proteomic responses to infection, generating large data sets, but selecting targets for further study is challenging. Here we propose a novel data-mining approach combining multiple heterogeneous data sets to prioritize genes for further study by using respiratory syncytial virus (RSV) infection as a model pathogen with a significant health care impact. The assumption was that the more frequently a gene is detected across multiple studies, the more important its role is. A literature search was performed to find data sets of genes and proteins that change after RSV infection. The data sets were standardized, collated into a single database, and then panned to determine which genes occurred in multiple data sets, generating a candidate gene list. This candidate gene list was validated by using both a clinical cohort and in vitro screening. We identified several genes that were frequently expressed following RSV infection with no assigned function in RSV control, including IFI27, IFIT3, IFI44L, GBP1, OAS3, IFI44, and IRF7. Drilling down into the function of these genes, we demonstrate a role in disease for the gene for interferon regulatory factor 7, which was highly ranked on the list, but not for IRF1, which was not. Thus, we have developed and validated an approach for collating published data sets into a manageable list of candidates, identifying novel targets for future analysis. IMPORTANCE Making the most of “big data” is one of the core challenges of current biology. There is a large array of heterogeneous data sets of host gene responses to infection, but these data sets do not inform us about gene function and require specialized skill sets and training for their utilization. Here we describe an approach that combines and simplifies these data sets, distilling this information into a single list of genes commonly upregulated in response to infection with RSV as a model pathogen. Many of the genes on the list have unknown functions in RSV disease. We validated the gene list with new clinical, in vitro, and in vivo data. This approach allows the rapid selection of genes of interest for further, more-detailed studies, thus reducing time and costs. Furthermore, the approach is simple to use and widely applicable to a range of diseases. PMID:27822537
Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

PubMed

Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

2017-07-01

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in using RF to develop predictive models with large environmental data sets.
A New Z Score Curve of the Coronary Arterial Internal Diameter Using the Lambda-Mu-Sigma Method in a Pediatric Population.

PubMed

Kobayashi, Tohru; Fuse, Shigeto; Sakamoto, Naoko; Mikami, Masashi; Ogawa, Shunichi; Hamaoka, Kenji; Arakaki, Yoshio; Nakamura, Tsuneyuki; Nagasawa, Hiroyuki; Kato, Taichi; Jibiki, Toshiaki; Iwashima, Satoru; Yamakawa, Masaru; Ohkubo, Takashi; Shimoyama, Shinya; Aso, Kentaro; Sato, Seiichi; Saji, Tsutomu

2016-08-01

Several coronary artery Z score models have been developed. However, a Z score model derived by the lambda-mu-sigma (LMS) method has not been established. Echocardiographic measurements of the proximal right coronary artery, left main coronary artery, proximal left anterior descending coronary artery, and proximal left circumflex artery were prospectively collected in 3,851 healthy children ≤18 years of age and divided into developmental and validation data sets. In the developmental data set, smooth curves were fitted for each coronary artery using linear, logarithmic, square-root, and LMS methods for both sexes. The relative goodness of fit of these models was compared using the Bayesian information criterion. The best-fitting model was tested for reproducibility using the validation data set. The goodness of fit of the selected model was visually compared with that of the previously reported regression models using a Q-Q plot. Because the internal diameter of each coronary artery was not similar between sexes, sex-specific Z score models were developed. The LMS model with body surface area as the independent variable showed the best goodness of fit; therefore, the internal diameter of each coronary artery was transformed into a sex-specific Z score on the basis of body surface area using the LMS method. In the validation data set, a Q-Q plot of each model indicated that the distribution of Z scores in the LMS models was closer to the normal distribution compared with previously reported regression models. Finally, the final models for each coronary artery in both sexes were developed using the developmental and validation data sets. A Microsoft Excel-based Z score calculator was also created, which is freely available online (http://raise.umin.jp/zsp/calculator/). Novel LMS models with which to estimate the sex-specific Z score of each internal coronary artery diameter were generated and validated using a large pediatric population. Copyright © 2016 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.
Predictive validity of the structured assessment of violence risk in youth: A 4-year follow-up.

PubMed

Gammelgård, Monica; Koivisto, Anna-Maija; Eronen, Markku; Kaltiala-Heino, Riittakerttu

2015-07-01

Structured violence risk assessment is an essential part of treatment planning for violent young people. The Structured Assessment of Violence Risk in Youth (SAVRY) has been shown to have good reliability and validity in a range of settings but has hardly been studied in adolescent mental health services. This study aimed to evaluate the long-term predictive validity of the SAVRY in adolescent psychiatry settings. In a prospective study, 200 SAVRY assessments of adolescents were acquired from psychiatric, forensic and correctional settings. Re-offending records from the Finnish National Crime Register were collected. Receiver operating curve statistics were applied. High SAVRY total and individual subscale scores and low values on the protective factor subscale were significantly associated with subsequent adverse outcomes, but the predictive value of the total score was weak. At the risk item level, those indicating antisocial lifestyle, absence of social support and pro-social involvement were strong indicators of subsequent criminal convictions, with or without violence. The SAVRY summary risk rating was the best indicator of likelihood of being convicted of a violent crime. After allowing for sex, age, psychiatric diagnosis and treatment setting, for example, conviction for a violent crime was over nine times more likely among those young people given high SAVRY summary risk ratings. The SAVRY is a valid and useful method for assessing both short-term and long-term risks of violent and non-violent crime by young people in psychiatric as well as criminal justice settings, adding to a traditional risk-centred assessment approach by also indicating where future preventive treatment efforts should be targeted. The next steps should be to evaluate its role in everyday clinical practice when using the knowledge generated to inform and monitor management and treatment strategies. Copyright © 2014 John Wiley & Sons, Ltd.
ACToR - Aggregated Computational Toxicology Resource ...

EPA Pesticide Factsheets

There are too many uncharacterized environmental chemicals to test with current in vivo protocols. Develop predictive in vitro screening assays that can be used to prioritize chemicals for detailed testing. ToxCast program requires large amounts of data: In vitro assays (mainly generated by ToxCast program) and In vivo data to develop and validate predictive signatures ACToR is compiling both sets of data for use in predictive algorithms.
Detection of Spatially Unresolved (Nominally Sub-Pixel) Submerged and Surface Targets Using Hyperspectral Data

DTIC Science & Technology

2012-09-01

Feasibility (MT Modeling ) a. Continuum of mixture distributions interpolated b. Mixture infeasibilities calculated for each pixel c. Valid detections...Visible/Infrared Imaging Spectrometer BRDF Bidirectional Reflectance Distribution Function CASI Compact Airborne Spectrographic Imager CCD...filtering (MTMF), and was designed by Healey and Slater (1999) to use “a physical model to generate the set of sensor spectra for a target that will be
Identifying novel sequence variants of RNA 3D motifs

PubMed Central

Zirbel, Craig L.; Roll, James; Sweeney, Blake A.; Petrov, Anton I.; Pirrung, Meg; Leontis, Neocles B.

2015-01-01

Predicting RNA 3D structure from sequence is a major challenge in biophysics. An important sub-goal is accurately identifying recurrent 3D motifs from RNA internal and hairpin loop sequences extracted from secondary structure (2D) diagrams. We have developed and validated new probabilistic models for 3D motif sequences based on hybrid Stochastic Context-Free Grammars and Markov Random Fields (SCFG/MRF). The SCFG/MRF models are constructed using atomic-resolution RNA 3D structures. To parameterize each model, we use all instances of each motif found in the RNA 3D Motif Atlas and annotations of pairwise nucleotide interactions generated by the FR3D software. Isostericity relations between non-Watson–Crick basepairs are used in scoring sequence variants. SCFG techniques model nested pairs and insertions, while MRF ideas handle crossing interactions and base triples. We use test sets of randomly-generated sequences to set acceptance and rejection thresholds for each motif group and thus control the false positive rate. Validation was carried out by comparing results for four motif groups to RMDetect. The software developed for sequence scoring (JAR3D) is structured to automatically incorporate new motifs as they accumulate in the RNA 3D Motif Atlas when new structures are solved and is available free for download. PMID:26130723
Quasi-experiments to establish causal effects of HIV care and treatment and to improve the cascade of care

PubMed Central

Bor, Jacob; Geldsetzer, Pascal; Venkataramani, Atheendar; Bärnighausen, Till

2015-01-01

Purpose of review Randomized, population-representative trials of clinical interventions are rare. Quasi-experiments have been used successfully to generate causal evidence on the cascade of HIV care in a broad range of real-world settings. Recent findings Quasi-experiments exploit exogenous, or quasi-random, variation occurring naturally in the world or because of an administrative rule or policy change to estimate causal effects. Well designed quasi-experiments have greater internal validity than typical observational research designs. At the same time, quasi-experiments may also have potential for greater external validity than experiments and can be implemented when randomized clinical trials are infeasible or unethical. Quasi-experimental studies have established the causal effects of HIV testing and initiation of antiretroviral therapy on health, economic outcomes and sexual behaviors, as well as indirect effects on other community members. Recent quasi-experiments have evaluated specific interventions to improve patient performance in the cascade of care, providing causal evidence to optimize clinical management of HIV. Summary Quasi-experiments have generated important data on the real-world impacts of HIV testing and treatment and on interventions to improve the cascade of care. With the growth in large-scale clinical and administrative data, quasi-experiments enable rigorous evaluation of policies implemented in real-world settings. PMID:26371463
Quasi-experiments to establish causal effects of HIV care and treatment and to improve the cascade of care.

PubMed

Bor, Jacob; Geldsetzer, Pascal; Venkataramani, Atheendar; Bärnighausen, Till

2015-11-01

Randomized, population-representative trials of clinical interventions are rare. Quasi-experiments have been used successfully to generate causal evidence on the cascade of HIV care in a broad range of real-world settings. Quasi-experiments exploit exogenous, or quasi-random, variation occurring naturally in the world or because of an administrative rule or policy change to estimate causal effects. Well designed quasi-experiments have greater internal validity than typical observational research designs. At the same time, quasi-experiments may also have potential for greater external validity than experiments and can be implemented when randomized clinical trials are infeasible or unethical. Quasi-experimental studies have established the causal effects of HIV testing and initiation of antiretroviral therapy on health, economic outcomes and sexual behaviors, as well as indirect effects on other community members. Recent quasi-experiments have evaluated specific interventions to improve patient performance in the cascade of care, providing causal evidence to optimize clinical management of HIV. Quasi-experiments have generated important data on the real-world impacts of HIV testing and treatment and on interventions to improve the cascade of care. With the growth in large-scale clinical and administrative data, quasi-experiments enable rigorous evaluation of policies implemented in real-world settings.
Validation of Correction Algorithms for Near-IR Analysis of Human Milk in an Independent Sample Set-Effect of Pasteurization.

PubMed

Kotrri, Gynter; Fusch, Gerhard; Kwan, Celia; Choi, Dasol; Choi, Arum; Al Kafi, Nisreen; Rochow, Niels; Fusch, Christoph

2016-02-26

Commercial infrared (IR) milk analyzers are being increasingly used in research settings for the macronutrient measurement of breast milk (BM) prior to its target fortification. These devices, however, may not provide reliable measurement if not properly calibrated. In the current study, we tested a correction algorithm for a Near-IR milk analyzer (Unity SpectraStar, Brookfield, CT, USA) for fat and protein measurements, and examined the effect of pasteurization on the IR matrix and the stability of fat, protein, and lactose. Measurement values generated through Near-IR analysis were compared against those obtained through chemical reference methods to test the correction algorithm for the Near-IR milk analyzer. Macronutrient levels were compared between unpasteurized and pasteurized milk samples to determine the effect of pasteurization on macronutrient stability. The correction algorithm generated for our device was found to be valid for unpasteurized and pasteurized BM. Pasteurization had no effect on the macronutrient levels and the IR matrix of BM. These results show that fat and protein content can be accurately measured and monitored for unpasteurized and pasteurized BM. Of additional importance is the implication that donated human milk, generally low in protein content, has the potential to be target fortified.
Design, development and clinical validation of computer-aided surgical simulation system for streamlined orthognathic surgical planning.

PubMed

Yuan, Peng; Mai, Huaming; Li, Jianfu; Ho, Dennis Chun-Yu; Lai, Yingying; Liu, Siting; Kim, Daeseung; Xiong, Zixiang; Alfi, David M; Teichgraeber, John F; Gateno, Jaime; Xia, James J

2017-12-01

There are many proven problems associated with traditional surgical planning methods for orthognathic surgery. To address these problems, we developed a computer-aided surgical simulation (CASS) system, the AnatomicAligner, to plan orthognathic surgery following our streamlined clinical protocol. The system includes six modules: image segmentation and three-dimensional (3D) reconstruction, registration and reorientation of models to neutral head posture, 3D cephalometric analysis, virtual osteotomy, surgical simulation, and surgical splint generation. The accuracy of the system was validated in a stepwise fashion: first to evaluate the accuracy of AnatomicAligner using 30 sets of patient data, then to evaluate the fitting of splints generated by AnatomicAligner using 10 sets of patient data. The industrial gold standard system, Mimics, was used as the reference. When comparing the results of segmentation, virtual osteotomy and transformation achieved with AnatomicAligner to the ones achieved with Mimics, the absolute deviation between the two systems was clinically insignificant. The average surface deviation between the two models after 3D model reconstruction in AnatomicAligner and Mimics was 0.3 mm with a standard deviation (SD) of 0.03 mm. All the average surface deviations between the two models after virtual osteotomy and transformations were smaller than 0.01 mm with a SD of 0.01 mm. In addition, the fitting of splints generated by AnatomicAligner was at least as good as the ones generated by Mimics. We successfully developed a CASS system, the AnatomicAligner, for planning orthognathic surgery following the streamlined planning protocol. The system has been proven accurate. AnatomicAligner will soon be available freely to the boarder clinical and research communities.
Design, development and clinical validation of computer-aided surgical simulation system for streamlined orthognathic surgical planning

PubMed Central

Yuan, Peng; Mai, Huaming; Li, Jianfu; Ho, Dennis Chun-Yu; Lai, Yingying; Liu, Siting; Kim, Daeseung; Xiong, Zixiang; Alfi, David M.; Teichgraeber, John F.; Gateno, Jaime

2017-01-01

Purpose There are many proven problems associated with traditional surgical planning methods for orthognathic surgery. To address these problems, we developed a computer-aided surgical simulation (CASS) system, the AnatomicAligner, to plan orthognathic surgery following our streamlined clinical protocol. Methods The system includes six modules: image segmentation and three-dimensional (3D) reconstruction, registration and reorientation of models to neutral head posture, 3D cephalometric analysis, virtual osteotomy, surgical simulation, and surgical splint generation. The accuracy of the system was validated in a stepwise fashion: first to evaluate the accuracy of AnatomicAligner using 30 sets of patient data, then to evaluate the fitting of splints generated by AnatomicAligner using 10 sets of patient data. The industrial gold standard system, Mimics, was used as the reference. Result When comparing the results of segmentation, virtual osteotomy and transformation achieved with AnatomicAligner to the ones achieved with Mimics, the absolute deviation between the two systems was clinically insignificant. The average surface deviation between the two models after 3D model reconstruction in AnatomicAligner and Mimics was 0.3 mm with a standard deviation (SD) of 0.03 mm. All the average surface deviations between the two models after virtual osteotomy and transformations were smaller than 0.01 mm with a SD of 0.01 mm. In addition, the fitting of splints generated by AnatomicAligner was at least as good as the ones generated by Mimics. Conclusion We successfully developed a CASS system, the AnatomicAligner, for planning orthognathic surgery following the streamlined planning protocol. The system has been proven accurate. AnatomicAligner will soon be available freely to the boarder clinical and research communities. PMID:28432489
Performance of amplicon-based next generation DNA sequencing for diagnostic gene mutation profiling in oncopathology.

PubMed

Sie, Daoud; Snijders, Peter J F; Meijer, Gerrit A; Doeleman, Marije W; van Moorsel, Marinda I H; van Essen, Hendrik F; Eijk, Paul P; Grünberg, Katrien; van Grieken, Nicole C T; Thunnissen, Erik; Verheul, Henk M; Smit, Egbert F; Ylstra, Bauke; Heideman, Daniëlle A M

2014-10-01

Next generation DNA sequencing (NGS) holds promise for diagnostic applications, yet implementation in routine molecular pathology practice requires performance evaluation on DNA derived from routine formalin-fixed paraffin-embedded (FFPE) tissue specimens. The current study presents a comprehensive analysis of TruSeq Amplicon Cancer Panel-based NGS using a MiSeq Personal sequencer (TSACP-MiSeq-NGS) for somatic mutation profiling. TSACP-MiSeq-NGS (testing 212 hotspot mutation amplicons of 48 genes) and a data analysis pipeline were evaluated in a retrospective learning/test set approach (n = 58/n = 45 FFPE-tumor DNA samples) against 'gold standard' high-resolution-melting (HRM)-sequencing for the genes KRAS, EGFR, BRAF and PIK3CA. Next, the performance of the validated test algorithm was assessed in an independent, prospective cohort of FFPE-tumor DNA samples (n = 75). In the learning set, a number of minimum parameter settings was defined to decide whether a FFPE-DNA sample is qualified for TSACP-MiSeq-NGS and for calling mutations. The resulting test algorithm revealed 82% (37/45) compliance to the quality criteria and 95% (35/37) concordant assay findings for KRAS, EGFR, BRAF and PIK3CA with HRM-sequencing (kappa = 0.92; 95% CI = 0.81-1.03) in the test set. Subsequent application of the validated test algorithm to the prospective cohort yielded a success rate of 84% (63/75), and a high concordance with HRM-sequencing (95% (60/63); kappa = 0.92; 95% CI = 0.84-1.01). TSACP-MiSeq-NGS detected 77 mutations in 29 additional genes. TSACP-MiSeq-NGS is suitable for diagnostic gene mutation profiling in oncopathology.
A set-covering based heuristic algorithm for the periodic vehicle routing problem.

PubMed

Cacchiani, V; Hemmelmayr, V C; Tricoire, F

2014-01-30

We present a hybrid optimization algorithm for mixed-integer linear programming, embedding both heuristic and exact components. In order to validate it we use the periodic vehicle routing problem (PVRP) as a case study. This problem consists of determining a set of minimum cost routes for each day of a given planning horizon, with the constraints that each customer must be visited a required number of times (chosen among a set of valid day combinations), must receive every time the required quantity of product, and that the number of routes per day (each respecting the capacity of the vehicle) does not exceed the total number of available vehicles. This is a generalization of the well-known vehicle routing problem (VRP). Our algorithm is based on the linear programming (LP) relaxation of a set-covering-like integer linear programming formulation of the problem, with additional constraints. The LP-relaxation is solved by column generation, where columns are generated heuristically by an iterated local search algorithm. The whole solution method takes advantage of the LP-solution and applies techniques of fixing and releasing of the columns as a local search, making use of a tabu list to avoid cycling. We show the results of the proposed algorithm on benchmark instances from the literature and compare them to the state-of-the-art algorithms, showing the effectiveness of our approach in producing good quality solutions. In addition, we report the results on realistic instances of the PVRP introduced in Pacheco et al. (2011) [24] and on benchmark instances of the periodic traveling salesman problem (PTSP), showing the efficacy of the proposed algorithm on these as well. Finally, we report the new best known solutions found for all the tested problems.
A set-covering based heuristic algorithm for the periodic vehicle routing problem

PubMed Central

Cacchiani, V.; Hemmelmayr, V.C.; Tricoire, F.

2014-01-01

We present a hybrid optimization algorithm for mixed-integer linear programming, embedding both heuristic and exact components. In order to validate it we use the periodic vehicle routing problem (PVRP) as a case study. This problem consists of determining a set of minimum cost routes for each day of a given planning horizon, with the constraints that each customer must be visited a required number of times (chosen among a set of valid day combinations), must receive every time the required quantity of product, and that the number of routes per day (each respecting the capacity of the vehicle) does not exceed the total number of available vehicles. This is a generalization of the well-known vehicle routing problem (VRP). Our algorithm is based on the linear programming (LP) relaxation of a set-covering-like integer linear programming formulation of the problem, with additional constraints. The LP-relaxation is solved by column generation, where columns are generated heuristically by an iterated local search algorithm. The whole solution method takes advantage of the LP-solution and applies techniques of fixing and releasing of the columns as a local search, making use of a tabu list to avoid cycling. We show the results of the proposed algorithm on benchmark instances from the literature and compare them to the state-of-the-art algorithms, showing the effectiveness of our approach in producing good quality solutions. In addition, we report the results on realistic instances of the PVRP introduced in Pacheco et al. (2011) [24] and on benchmark instances of the periodic traveling salesman problem (PTSP), showing the efficacy of the proposed algorithm on these as well. Finally, we report the new best known solutions found for all the tested problems. PMID:24748696
DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, X; Wang, J; Hu, W

Purpose: The Varian RapidPlan™ is a commercial knowledge-based optimization process which uses a set of clinically used treatment plans to train a model that can predict individualized dose-volume objectives. The purpose of this study is to evaluate the performance of RapidPlan to generate intensity modulated radiation therapy (IMRT) plans for cervical cancer. Methods: Totally 70 IMRT plans for cervical cancer with varying clinical and physiological indications were enrolled in this study. These patients were all previously treated in our institution. There were two prescription levels usually used in our institution: 45Gy/25 fractions and 50.4Gy/28 fractions. 50 of these plans weremore » selected to train the RapidPlan model for predicting dose-volume constraints. After model training, this model was validated with 10 plans from training pool(internal validation) and additional other 20 new plans(external validation). All plans used for the validation were re-optimized with the original beam configuration and the generated priorities from RapidPlan were manually adjusted to ensure that re-optimized DVH located in the range of the model prediction. DVH quantitative analysis was performed to compare the RapidPlan generated and the original manual optimized plans. Results: For all the validation cases, RapidPlan based plans (RapidPlan) showed similar or superior results compared to the manual optimized ones. RapidPlan increased the result of D98% and homogeneity in both two validations. For organs at risk, the RapidPlan decreased mean doses of bladder by 1.25Gy/1.13Gy (internal/external validation) on average, with p=0.12/p<0.01. The mean dose of rectum and bowel were also decreased by an average of 2.64Gy/0.83Gy and 0.66Gy/1.05Gy,with p<0.01/ p<0.01and p=0.04/<0.01 for the internal/external validation, respectively. Conclusion: The RapidPlan model based cervical cancer plans shows ability to systematically improve the IMRT plan quality. It suggests that RapidPlan has great potential to make the treatment planning process more efficient.« less
Broadband Fan Noise Prediction System for Turbofan Engines. Volume 3; Validation and Test Cases

NASA Technical Reports Server (NTRS)

Morin, Bruce L.

2010-01-01

Pratt & Whitney has developed a Broadband Fan Noise Prediction System (BFaNS) for turbofan engines. This system computes the noise generated by turbulence impinging on the leading edges of the fan and fan exit guide vane, and noise generated by boundary-layer turbulence passing over the fan trailing edge. BFaNS has been validated on three fan rigs that were tested during the NASA Advanced Subsonic Technology Program (AST). The predicted noise spectra agreed well with measured data. The predicted effects of fan speed, vane count, and vane sweep also agreed well with measurements. The noise prediction system consists of two computer programs: Setup_BFaNS and BFaNS. Setup_BFaNS converts user-specified geometry and flow-field information into a BFaNS input file. From this input file, BFaNS computes the inlet and aft broadband sound power spectra generated by the fan and FEGV. The output file from BFaNS contains the inlet, aft and total sound power spectra from each noise source. This report is the third volume of a three-volume set documenting the Broadband Fan Noise Prediction System: Volume 1: Setup_BFaNS User s Manual and Developer s Guide; Volume 2: BFaNS User s Manual and Developer s Guide; and Volume 3: Validation and Test Cases. The present volume begins with an overview of the Broadband Fan Noise Prediction System, followed by validation studies that were done on three fan rigs. It concludes with recommended improvements and additional studies for BFaNS.
Validation of Community Models: 2. Development of a Baseline, Using the Wang-Sheeley-Arge Model

NASA Technical Reports Server (NTRS)

MacNeice, Peter

2009-01-01

This paper is the second in a series providing independent validation of community models of the outer corona and inner heliosphere. Here I present a comprehensive validation of the Wang-Sheeley-Arge (WSA) model. These results will serve as a baseline against which to compare the next generation of comparable forecasting models. The WSA model is used by a number of agencies to predict Solar wind conditions at Earth up to 4 days into the future. Given its importance to both the research and forecasting communities, it is essential that its performance be measured systematically and independently. I offer just such an independent and systematic validation. I report skill scores for the model's predictions of wind speed and interplanetary magnetic field (IMF) polarity for a large set of Carrington rotations. The model was run in all its routinely used configurations. It ingests synoptic line of sight magnetograms. For this study I generated model results for monthly magnetograms from multiple observatories, spanning the Carrington rotation range from 1650 to 2074. I compare the influence of the different magnetogram sources and performance at quiet and active times. I also consider the ability of the WSA model to forecast both sharp transitions in wind speed from slow to fast wind and reversals in the polarity of the radial component of the IMF. These results will serve as a baseline against which to compare future versions of the model as well as the current and future generation of magnetohydrodynamic models under development for forecasting use.
3D active shape models of human brain structures: application to patient-specific mesh generation

NASA Astrophysics Data System (ADS)

Ravikumar, Nishant; Castro-Mateos, Isaac; Pozo, Jose M.; Frangi, Alejandro F.; Taylor, Zeike A.

2015-03-01

The use of biomechanics-based numerical simulations has attracted growing interest in recent years for computer-aided diagnosis and treatment planning. With this in mind, a method for automatic mesh generation of brain structures of interest, using statistical models of shape (SSM) and appearance (SAM), for personalised computational modelling is presented. SSMs are constructed as point distribution models (PDMs) while SAMs are trained using intensity profiles sampled from a training set of T1-weighted magnetic resonance images. The brain structures of interest are, the cortical surface (cerebrum, cerebellum & brainstem), lateral ventricles and falx-cerebri membrane. Two methods for establishing correspondences across the training set of shapes are investigated and compared (based on SSM quality): the Coherent Point Drift (CPD) point-set registration method and B-spline mesh-to-mesh registration method. The MNI-305 (Montreal Neurological Institute) average brain atlas is used to generate the template mesh, which is deformed and registered to each training case, to establish correspondence over the training set of shapes. 18 healthy patients' T1-weightedMRimages form the training set used to generate the SSM and SAM. Both model-training and model-fitting are performed over multiple brain structures simultaneously. Compactness and generalisation errors of the BSpline-SSM and CPD-SSM are evaluated and used to quantitatively compare the SSMs. Leave-one-out cross validation is used to evaluate SSM quality in terms of these measures. The mesh-based SSM is found to generalise better and is more compact, relative to the CPD-based SSM. Quality of the best-fit model instance from the trained SSMs, to test cases are evaluated using the Hausdorff distance (HD) and mean absolute surface distance (MASD) metrics.
Analysis of the French insurance market exposure to floods: a stochastic model combining river overflow and surface runoff

NASA Astrophysics Data System (ADS)

Moncoulon, D.; Labat, D.; Ardon, J.; Onfroy, T.; Leblois, E.; Poulard, C.; Aji, S.; Rémy, A.; Quantin, A.

2013-07-01

The analysis of flood exposure at a national scale for the French insurance market must combine the generation of a probabilistic event set of all possible but not yet occurred flood situations with hazard and damage modeling. In this study, hazard and damage models are calibrated on a 1995-2012 historical event set, both for hazard results (river flow, flooded areas) and loss estimations. Thus, uncertainties in the deterministic estimation of a single event loss are known before simulating a probabilistic event set. To take into account at least 90% of the insured flood losses, the probabilistic event set must combine the river overflow (small and large catchments) with the surface runoff due to heavy rainfall, on the slopes of the watershed. Indeed, internal studies of CCR claim database has shown that approximately 45% of the insured flood losses are located inside the floodplains and 45% outside. 10% other percent are due to seasurge floods and groundwater rise. In this approach, two independent probabilistic methods are combined to create a single flood loss distribution: generation of fictive river flows based on the historical records of the river gauge network and generation of fictive rain fields on small catchments, calibrated on the 1958-2010 Météo-France rain database SAFRAN. All the events in the probabilistic event sets are simulated with the deterministic model. This hazard and damage distribution is used to simulate the flood losses at the national scale for an insurance company (MACIF) and to generate flood areas associated with hazard return periods. The flood maps concern river overflow and surface water runoff. Validation of these maps is conducted by comparison with the address located claim data on a small catchment (downstream Argens).

Pharmacophore Based Virtual Screening Approach to Identify Selective PDE4B Inhibitors

PubMed Central

Gaurav, Anand; Gautam, Vertika

2017-01-01

Phosphodiesterase 4 (PDE4) has been established as a promising target in asthma and chronic obstructive pulmonary disease. PDE4B subtype selective inhibitors are known to reduce the dose limiting adverse effect associated with non-selective PDE4B inhibitors. This makes the development of PDE4B subtype selective inhibitors a desirable research goal. To achieve this goal, ligand based pharmacophore modeling approach is employed. Separate pharmacophore hypotheses for PDE4B and PDE4D inhibitors were generated using HypoGen algorithm and 106 PDE4 inhibitors from literature having thiopyrano [3,2-d] Pyrimidines, 2-arylpyrimidines, and triazines skeleton. Suitable training and test sets were created using the molecules as per the guidelines available for HypoGen program. Training set was used for hypothesis development while test set was used for validation purpose. Fisher validation was also used to test the significance of the developed hypothesis. The validated pharmacophore hypotheses for PDE4B and PDE4D inhibitors were used in sequential virtual screening of zinc database of drug like molecules to identify selective PDE4B inhibitors. The hits were screened for their estimated activity and fit value. The top hit was subjected to docking into the active sites of PDE4B and PDE4D to confirm its selectivity for PDE4B. The hits are proposed to be evaluated further using in-vitro assays. PMID:29201082
Mapping health outcome measures from a stroke registry to EQ-5D weights.

PubMed

Ghatnekar, Ola; Eriksson, Marie; Glader, Eva-Lotta

2013-03-07

To map health outcome related variables from a national register, not part of any validated instrument, with EQ-5D weights among stroke patients. We used two cross-sectional data sets including patient characteristics, outcome variables and EQ-5D weights from the national Swedish stroke register. Three regression techniques were used on the estimation set (n=272): ordinary least squares (OLS), Tobit, and censored least absolute deviation (CLAD). The regression coefficients for "dressing", "toileting", "mobility", "mood", "general health" and "proxy-responders" were applied to the validation set (n=272), and the performance was analysed with mean absolute error (MAE) and mean square error (MSE). The number of statistically significant coefficients varied by model, but all models generated consistent coefficients in terms of sign. Mean utility was underestimated in all models (least in OLS) and with lower variation (least in OLS) compared to the observed. The maximum attainable EQ-5D weight ranged from 0.90 (OLS) to 1.00 (Tobit and CLAD). Health states with utility weights <0.5 had greater errors than those with weights ≥ 0.5 (P<0.01). This study indicates that it is possible to map non-validated health outcome measures from a stroke register into preference-based utilities to study the development of stroke care over time, and to compare with other conditions in terms of utility.
Two-Phase and Graph-Based Clustering Methods for Accurate and Efficient Segmentation of Large Mass Spectrometry Images.

PubMed

Dexter, Alex; Race, Alan M; Steven, Rory T; Barnes, Jennifer R; Hulme, Heather; Goodwin, Richard J A; Styles, Iain B; Bunch, Josephine

2017-11-07

Clustering is widely used in MSI to segment anatomical features and differentiate tissue types, but existing approaches are both CPU and memory-intensive, limiting their application to small, single data sets. We propose a new approach that uses a graph-based algorithm with a two-phase sampling method that overcomes this limitation. We demonstrate the algorithm on a range of sample types and show that it can segment anatomical features that are not identified using commonly employed algorithms in MSI, and we validate our results on synthetic MSI data. We show that the algorithm is robust to fluctuations in data quality by successfully clustering data with a designed-in variance using data acquired with varying laser fluence. Finally, we show that this method is capable of generating accurate segmentations of large MSI data sets acquired on the newest generation of MSI instruments and evaluate these results by comparison with histopathology.
An Experimental and Numerical Study of a Supersonic Burner for CFD Model Development

NASA Technical Reports Server (NTRS)

Magnotti, G.; Cutler, A. D.

2008-01-01

A laboratory scale supersonic burner has been developed for validation of computational fluid dynamics models. Detailed numerical simulations were performed for the flow inside the combustor, and coupled with finite element thermal analysis to obtain more accurate outflow conditions. A database of nozzle exit profiles for a wide range of conditions of interest was generated to be used as boundary conditions for simulation of the external jet, or for validation of non-intrusive measurement techniques. A set of experiments was performed to validate the numerical results. In particular, temperature measurements obtained by using an infrared camera show that the computed heat transfer was larger than the measured value. Relaminarization in the convergent part of the nozzle was found to be responsible for this discrepancy, and further numerical simulations sustained this conclusion.
V&V of MCNP 6.1.1 Beta Against Intermediate and High-Energy Experimental Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mashnik, Stepan G

This report presents a set of validation and verification (V&V) MCNP 6.1.1 beta results calculated in parallel, with MPI, obtained using its event generators at intermediate and high-energies compared against various experimental data. It also contains several examples of results using the models at energies below 150 MeV, down to 10 MeV, where data libraries are normally used. This report can be considered as the forth part of a set of MCNP6 Testing Primers, after its first, LA-UR-11-05129, and second, LA-UR-11-05627, and third, LA-UR-26944, publications, but is devoted to V&V with the latest, 1.1 beta version of MCNP6. The MCNP6more » test-problems discussed here are presented in the /VALIDATION_CEM/and/VALIDATION_LAQGSM/subdirectories in the MCNP6/Testing/directory. README files that contain short descriptions of every input file, the experiment, the quantity of interest that the experiment measures and its description in the MCNP6 output files, and the publication reference of that experiment are presented for every test problem. Templates for plotting the corresponding results with xmgrace as well as pdf files with figures representing the final results of our V&V efforts are presented. Several technical “bugs” in MCNP 6.1.1 beta were discovered during our current V&V of MCNP6 while running it in parallel with MPI using its event generators. These “bugs” are to be fixed in the following version of MCNP6. Our results show that MCNP 6.1.1 beta using its CEM03.03, LAQGSM03.03, Bertini, and INCL+ABLA, event generators describes, as a rule, reasonably well different intermediate- and high-energy measured data. This primer isn’t meant to be read from cover to cover. Readers may skip some sections and go directly to any test problem in which they are interested.« less
Systematic feature selection improves accuracy of methylation-based forensic age estimation in Han Chinese males.

PubMed

Feng, Lei; Peng, Fuduan; Li, Shanfei; Jiang, Li; Sun, Hui; Ji, Anquan; Zeng, Changqing; Li, Caixia; Liu, Fan

2018-03-23

Estimating individual age from biomarkers may provide key information facilitating forensic investigations. Recent progress has shown DNA methylation at age-associated CpG sites as the most informative biomarkers for estimating the individual age of an unknown donor. Optimal feature selection plays a critical role in determining the performance of the final prediction model. In this study we investigate methylation levels at 153 age-associated CpG sites from 21 previously reported genomic regions using the EpiTYPER system for their predictive power on individual age in 390 Han Chinese males ranging from 15 to 75 years of age. We conducted a systematic feature selection using a stepwise backward multiple linear regression analysis as well as an exhaustive searching algorithm. Both approaches identified the same subset of 9 CpG sites, which in linear combination provided the optimal model fitting with mean absolute deviation (MAD) of 2.89 years of age and explainable variance (R 2 ) of 0.92. The final model was validated in two independent Han Chinese male samples (validation set 1, N = 65, MAD = 2.49, R 2  = 0.95, and validation set 2, N = 62, MAD = 3.36, R 2  = 0.89). Other competing models such as support vector machine and artificial neural network did not outperform the linear model to any noticeable degree. The validation set 1 was additionally analyzed using Pyrosequencing technology for cross-platform validation and was termed as validation set 3. Directly applying our model, in which the methylation levels were detected by the EpiTYPER system, to the data from pyrosequencing technology showed, however, less accurate results in terms of MAD (validation set 3, N = 65 Han Chinese males, MAD = 4.20, R 2  = 0.93), suggesting the presence of a batch effect between different data generation platforms. This batch effect could be partially overcome by a z-score transformation (MAD = 2.76, R 2  = 0.93). Overall, our systematic feature selection identified 9 CpG sites as the optimal subset for forensic age estimation and the prediction model consisting of these 9 markers demonstrated high potential in forensic practice. An age estimator implementing our prediction model allowing missing markers is freely available at http://liufan.big.ac.cn/AgePrediction. Copyright © 2018 Elsevier B.V. All rights reserved.
Online cross-validation-based ensemble learning.

PubMed

Benkeser, David; Ju, Cheng; Lendle, Sam; van der Laan, Mark

2018-01-30

Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and, as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to identify the algorithm with the best performance. We show that by basing estimates on the cross-validation-selected algorithm, we are asymptotically guaranteed to perform as well as the true, unknown best-performing algorithm. We provide extensions of this approach including online estimation of the optimal ensemble of candidate online estimators. We illustrate excellent performance of our methods using simulations and a real data example where we make streaming predictions of infectious disease incidence using data from a large database. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Mirage: a visible signature evaluation tool

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.; Meehan, Alaster J.; Shao, Q. T.; Richards, Noel

2017-10-01

This paper presents the Mirage visible signature evaluation tool, designed to provide a visible signature evaluation capability that will appropriately reflect the effect of scene content on the detectability of targets, providing a capability to assess visible signatures in the context of the environment. Mirage is based on a parametric evaluation of input images, assessing the value of a range of image metrics and combining them using the boosted decision tree machine learning method to produce target detectability estimates. It has been developed using experimental data from photosimulation experiments, where human observers search for vehicle targets in a variety of digital images. The images used for tool development are synthetic (computer generated) images, showing vehicles in many different scenes and exhibiting a wide variation in scene content. A preliminary validation has been performed using k-fold cross validation, where 90% of the image data set was used for training and 10% of the image data set was used for testing. The results of the k-fold validation from 200 independent tests show a prediction accuracy between Mirage predictions of detection probability and observed probability of detection of r(262) = 0:63, p < 0:0001 (Pearson correlation) and a MAE = 0:21 (mean absolute error).
Overview of the Joint NASA ISRO Imaging Spectroscopy Science Campaign in India

NASA Astrophysics Data System (ADS)

Green, R. O.; Bhattacharya, B. K.; Eastwood, M. L.; Saxena, M.; Thompson, D. R.; Sadasivarao, B.

2016-12-01

In the period from December 2015 to March 2016 the Airborne Visible-Infrared Imaging Spectrometer Next Generation (AVIRIS-NG) was deployed to India for a joint NASA ISRO science campaign. This campaign was conceived to provide first of their kind high fidelity imaging spectroscopy measurements of a diverse set of Asian environments for science and applications research. During this campaign measurements were acquired for 57 high priority sites that have objectives spanning: snow/ice of the Himalaya; coastal habitats and water quality; mangrove forests; soils; dry and humid forests; hydrocarbon alteration; mineralogy; agriculture; urban materials; atmospheric properties; and calibration/validation. Measurements from the campaign have been processed to at-instrument spectral radiance and atmospherically corrected surface reflectance. New AVIRIS-NG algorithms for retrieval of vegetation canopy water and for estimation of the fractions of photosynthetic, non-photosynthetic vegetation have been tested and evaluated on these measurements. An inflight calibration validation experiment was performed on the 11thof December 2015 in Hyderabad to assess the spectral and radiometric calibration of AVIRIS-NG in the flight environment. We present an overview of the campaign, calibration and validation results, and initial science analysis of a subset of these unique and diverse data sets.
Chemometric and biological validation of a capillary electrophoresis metabolomic experiment of Schistosoma mansoni infection in mice.

PubMed

Garcia-Perez, Isabel; Angulo, Santiago; Utzinger, Jürg; Holmes, Elaine; Legido-Quigley, Cristina; Barbas, Coral

2010-07-01

Metabonomic and metabolomic studies are increasingly utilized for biomarker identification in different fields, including biology of infection. The confluence of improved analytical platforms and the availability of powerful multivariate analysis software have rendered the multiparameter profiles generated by these omics platforms a user-friendly alternative to the established analysis methods where the quality and practice of a procedure is well defined. However, unlike traditional assays, validation methods for these new multivariate profiling tools have yet to be established. We propose a validation for models obtained by CE fingerprinting of urine from mice infected with the blood fluke Schistosoma mansoni. We have analysed urine samples from two sets of mice infected in an inter-laboratory experiment where different infection methods and animal husbandry procedures were employed in order to establish the core biological response to a S. mansoni infection. CE data were analysed using principal component analysis. Validation of the scores consisted of permutation scrambling (100 repetitions) and a manual validation method, using a third of the samples (not included in the model) as a test or prediction set. The validation yielded 100% specificity and 100% sensitivity, demonstrating the robustness of these models with respect to deciphering metabolic perturbations in the mouse due to a S. mansoni infection. A total of 20 metabolites across the two experiments were identified that significantly discriminated between S. mansoni-infected and noninfected control samples. Only one of these metabolites, allantoin, was identified as manifesting different behaviour in the two experiments. This study shows the reproducibility of CE-based metabolic profiling methods for disease characterization and screening and highlights the importance of much needed validation strategies in the emerging field of metabolomics.
Valid randomization-based p-values for partially post hoc subgroup analyses.

PubMed

Lee, Joseph J; Rubin, Donald B

2015-10-30

By 'partially post-hoc' subgroup analyses, we mean analyses that compare existing data from a randomized experiment-from which a subgroup specification is derived-to new, subgroup-only experimental data. We describe a motivating example in which partially post hoc subgroup analyses instigated statistical debate about a medical device's efficacy. We clarify the source of such analyses' invalidity and then propose a randomization-based approach for generating valid posterior predictive p-values for such partially post hoc subgroups. Lastly, we investigate the approach's operating characteristics in a simple illustrative setting through a series of simulations, showing that it can have desirable properties under both null and alternative hypotheses. Copyright © 2015 John Wiley & Sons, Ltd.
Statistical Methods for Rapid Aerothermal Analysis and Design Technology: Validation

NASA Technical Reports Server (NTRS)

DePriest, Douglas; Morgan, Carolyn

2003-01-01

The cost and safety goals for NASA s next generation of reusable launch vehicle (RLV) will require that rapid high-fidelity aerothermodynamic design tools be used early in the design cycle. To meet these requirements, it is desirable to identify adequate statistical models that quantify and improve the accuracy, extend the applicability, and enable combined analyses using existing prediction tools. The initial research work focused on establishing suitable candidate models for these purposes. The second phase is focused on assessing the performance of these models to accurately predict the heat rate for a given candidate data set. This validation work compared models and methods that may be useful in predicting the heat rate.
NASA Radiation Protection Research for Exploration Missions

NASA Technical Reports Server (NTRS)

Wilson, John W.; Cucinotta, Francis A.; Tripathi, Ram K.; Heinbockel, John H.; Tweed, John; Mertens, Christopher J.; Walker, Steve A.; Blattnig, Steven R.; Zeitlin, Cary J.

2006-01-01

The HZETRN code was used in recent trade studies for renewed lunar exploration and currently used in engineering development of the next generation of space vehicles, habitats, and EVA equipment. A new version of the HZETRN code capable of simulating high charge and energy (HZE) ions, light-ions and neutrons with either laboratory or space boundary conditions with enhanced neutron and light-ion propagation is under development. Atomic and nuclear model requirements to support that development will be discussed. Such engineering design codes require establishing validation processes using laboratory ion beams and space flight measurements in realistic geometries. We discuss limitations of code validation due to the currently available data and recommend priorities for new data sets.
Study on the Algorithm of Judgment Matrix in Analytic Hierarchy Process

NASA Astrophysics Data System (ADS)

Lu, Zhiyong; Qin, Futong; Jin, Yican

2017-10-01

A new algorithm is proposed for the non-consistent judgment matrix in AHP. A primary judgment matrix is generated firstly through pre-ordering the targeted factor set, and a compared matrix is built through the top integral function. Then a relative error matrix is created by comparing the compared matrix with the primary judgment matrix which is regulated under the control of the relative error matrix and the dissimilar degree of the matrix step by step. Lastly, the targeted judgment matrix is generated to satisfy the requirement of consistence and the least dissimilar degree. The feasibility and validity of the proposed method are verified by simulation results.
A Transfer Voltage Simulation Method for Generator Step Up Transformers

NASA Astrophysics Data System (ADS)

Funabashi, Toshihisa; Sugimoto, Toshirou; Ueda, Toshiaki; Ametani, Akihiro

It has been found from measurements for 13 sets of GSU transformers that a transfer voltage of a generator step-up (GSU) transformer involves one dominant oscillation frequency. The frequency can be estimated from the inductance and capacitance values of the GSU transformer low-voltage-side. This observation has led to a new method for simulating a GSU transformer transfer voltage. The method is based on the EMTP TRANSFORMER model, but stray capacitances are added. The leakage inductance and the magnetizing resistance are modified using approximate curves for their frequency characteristics determined from the measured results. The new method is validated in comparison with the measured results.
Coupling of electromagnetic and structural dynamics for a wind turbine generator

NASA Astrophysics Data System (ADS)

Matzke, D.; Rick, S.; Hollas, S.; Schelenz, R.; Jacobs, G.; Hameyer, K.

2016-09-01

This contribution presents a model interface of a wind turbine generator to represent the reciprocal effects between the mechanical and the electromagnetic system. Therefore, a multi-body-simulation (MBS) model in Simpack is set up and coupled with a quasi-static electromagnetic (EM) model of the generator in Matlab/Simulink via co-simulation. Due to lack of data regarding the structural properties of the generator the modal properties of the MBS model are fitted with respect to results of an experimental modal analysis (EMA) on the reference generator. The used method and the results of this approach are presented in this paper. The MB S model and the interface are set up in such a way that the EM forces can be applied to the structure and the response of the structure can be fed back to the EM model. The results of this cosimulation clearly show an influence of the feedback of the mechanical response which is mainly damping in the torsional degree of freedom and effects due to eccentricity in radial direction. The accuracy of these results will be validated via test bench measurements and presented in future work. Furthermore it is suggested that the EM model should be adjusted in future works so that transient effects are represented.
Developing a cosmic ray muon sampling capability for muon tomography and monitoring applications

NASA Astrophysics Data System (ADS)

Chatzidakis, S.; Chrysikopoulou, S.; Tsoukalas, L. H.

2015-12-01

In this study, a cosmic ray muon sampling capability using a phenomenological model that captures the main characteristics of the experimentally measured spectrum coupled with a set of statistical algorithms is developed. The "muon generator" produces muons with zenith angles in the range 0-90° and energies in the range 1-100 GeV and is suitable for Monte Carlo simulations with emphasis on muon tomographic and monitoring applications. The muon energy distribution is described by the Smith and Duller (1959) [35] phenomenological model. Statistical algorithms are then employed for generating random samples. The inverse transform provides a means to generate samples from the muon angular distribution, whereas the Acceptance-Rejection and Metropolis-Hastings algorithms are employed to provide the energy component. The predictions for muon energies 1-60 GeV and zenith angles 0-90° are validated with a series of actual spectrum measurements and with estimates from the software library CRY. The results confirm the validity of the phenomenological model and the applicability of the statistical algorithms to generate polyenergetic-polydirectional muons. The response of the algorithms and the impact of critical parameters on computation time and computed results were investigated. Final output from the proposed "muon generator" is a look-up table that contains the sampled muon angles and energies and can be easily integrated into Monte Carlo particle simulation codes such as Geant4 and MCNP.
Planar measurement of flow field parameters in a nonreacting supersonic combustor using laser-induced iodine fluorescence

NASA Technical Reports Server (NTRS)

Hartfield, Roy J., Jr.; Hollo, Steven D.; Mcdaniel, James C.

1990-01-01

A nonintrusive optical technique, laser-induced iodine fluorescence, has been used to obtain planar measurements of flow field parameters in the supersonic mixing flow field of a nonreacting supersonic combustor. The combustor design used in this work was configured with staged transverse sonic injection behind a rearward-facing step into a Mach 2.07 free stream. A set of spatially resolved measurements of temperature and injectant mole fraction has been generated. These measurements provide an extensive and accurate experimental data set required for the validation of computational fluid dynamic codes developed for the calculation of highly three-dimensional combustor flow fields.
RWEN: Response-Weighted Elastic Net For Prediction of Chemosensitivity of Cancer Cell Lines. | Office of Cancer Genomics

Cancer.gov

Motivation: In recent years there have been several efforts to generate sensitivity profiles of collections of genomically characterized cell lines to panels of candidate therapeutic compounds. These data provide the basis for the development of in silico models of sensitivity based on cellular, genetic, or expression biomarkers of cancer cells. However, a remaining challenge is an efficient way to identify accurate sets of biomarkers to validate.
DeepMoon: Convolutional neural network trainer to identify moon craters

NASA Astrophysics Data System (ADS)

Silburt, Ari; Zhu, Chenchong; Ali-Dib, Mohamad; Menou, Kristen; Jackson, Alan

2018-05-01

DeepMoon trains a convolutional neural net using data derived from a global digital elevation map (DEM) and catalog of craters to recognize craters on the Moon. The TensorFlow-based pipeline code is divided into three parts. The first generates a set images of the Moon randomly cropped from the DEM, with corresponding crater positions and radii. The second trains a convnet using this data, and the third validates the convnet's predictions.

PrecisePrimer: an easy-to-use web server for designing PCR primers for DNA library cloning and DNA shuffling.

PubMed

Pauthenier, Cyrille; Faulon, Jean-Loup

2014-07-01

PrecisePrimer is a web-based primer design software made to assist experimentalists in any repetitive primer design task such as preparing, cloning and shuffling DNA libraries. Unlike other popular primer design tools, it is conceived to generate primer libraries with popular PCR polymerase buffers proposed as pre-set options. PrecisePrimer is also meant to design primers in batches, such as for DNA libraries creation of DNA shuffling experiments and to have the simplest interface possible. It integrates the most up-to-date melting temperature algorithms validated with experimental data, and cross validated with other computational tools. We generated a library of primers for the extraction and cloning of 61 genes from yeast DNA genomic extract using default parameters. All primer pairs efficiently amplified their target without any optimization of the PCR conditions. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.
Brief surgical procedure code lists for outcomes measurement and quality improvement in resource-limited settings.

PubMed

Liu, Charles; Kayima, Peter; Riesel, Johanna; Situma, Martin; Chang, David; Firth, Paul

2017-11-01

The lack of a classification system for surgical procedures in resource-limited settings hinders outcomes measurement and reporting. Existing procedure coding systems are prohibitively large and expensive to implement. We describe the creation and prospective validation of 3 brief procedure code lists applicable in low-resource settings, based on analysis of surgical procedures performed at Mbarara Regional Referral Hospital, Uganda's second largest public hospital. We reviewed operating room logbooks to identify all surgical operations performed at Mbarara Regional Referral Hospital during 2014. Based on the documented indication for surgery and procedure(s) performed, we assigned each operation up to 4 procedure codes from the International Classification of Diseases, 9th Revision, Clinical Modification. Coding of procedures was performed by 2 investigators, and a random 20% of procedures were coded by both investigators. These codes were aggregated to generate procedure code lists. During 2014, 6,464 surgical procedures were performed at Mbarara Regional Referral Hospital, to which we assigned 435 unique procedure codes. Substantial inter-rater reliability was achieved (κ = 0.7037). The 111 most common procedure codes accounted for 90% of all codes assigned, 180 accounted for 95%, and 278 accounted for 98%. We considered these sets of codes as 3 procedure code lists. In a prospective validation, we found that these lists described 83.2%, 89.2%, and 92.6% of surgical procedures performed at Mbarara Regional Referral Hospital during August to September of 2015, respectively. Empirically generated brief procedure code lists based on International Classification of Diseases, 9th Revision, Clinical Modification can be used to classify almost all surgical procedures performed at a Ugandan referral hospital. Such a standardized procedure coding system may enable better surgical data collection for administration, research, and quality improvement in resource-limited settings. Copyright © 2017 Elsevier Inc. All rights reserved.
Comparing and Validating Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.

PubMed

Lane, Thomas; Russo, Daniel P; Zorn, Kimberley M; Clark, Alex M; Korotcov, Alexandru; Tkachenko, Valery; Reynolds, Robert C; Perryman, Alexander L; Freundlich, Joel S; Ekins, Sean

2018-04-26

Tuberculosis is a global health dilemma. In 2016, the WHO reported 10.4 million incidences and 1.7 million deaths. The need to develop new treatments for those infected with Mycobacterium tuberculosis ( Mtb) has led to many large-scale phenotypic screens and many thousands of new active compounds identified in vitro. However, with limited funding, efforts to discover new active molecules against Mtb needs to be more efficient. Several computational machine learning approaches have been shown to have good enrichment and hit rates. We have curated small molecule Mtb data and developed new models with a total of 18,886 molecules with activity cutoffs of 10 μM, 1 μM, and 100 nM. These data sets were used to evaluate different machine learning methods (including deep learning) and metrics and to generate predictions for additional molecules published in 2017. One Mtb model, a combined in vitro and in vivo data Bayesian model at a 100 nM activity yielded the following metrics for 5-fold cross validation: accuracy = 0.88, precision = 0.22, recall = 0.91, specificity = 0.88, kappa = 0.31, and MCC = 0.41. We have also curated an evaluation set ( n = 153 compounds) published in 2017, and when used to test our model, it showed the comparable statistics (accuracy = 0.83, precision = 0.27, recall = 1.00, specificity = 0.81, kappa = 0.36, and MCC = 0.47). We have also compared these models with additional machine learning algorithms showing Bayesian machine learning models constructed with literature Mtb data generated by different laboratories generally were equivalent to or outperformed deep neural networks with external test sets. Finally, we have also compared our training and test sets to show they were suitably diverse and different in order to represent useful evaluation sets. Such Mtb machine learning models could help prioritize compounds for testing in vitro and in vivo.
Validation of Autoclave Protocols for Successful Decontamination of Category A Medical Waste Generated from Care of Patients with Serious Communicable Diseases

PubMed Central

Reimers, Mallory; Ernst, Neysa; Bova, Gregory; Nowakowski, Elaine; Bukowski, James; Ellis, Brandon C.; Smith, Chris; Sauer, Lauren; Dionne, Kim; Carroll, Karen C.; Maragakis, Lisa L.; Parrish, Nicole M.

2016-01-01

ABSTRACT In response to the Ebola outbreak in 2014, many hospitals designated specific areas to care for patients with Ebola and other highly infectious diseases. The safe handling of category A infectious substances is a unique challenge in this environment. One solution is on-site waste treatment with a steam sterilizer or autoclave. The Johns Hopkins Hospital (JHH) installed two pass-through autoclaves in its biocontainment unit (BCU). The JHH BCU and The Johns Hopkins biosafety level 3 (BSL-3) clinical microbiology laboratory designed and validated waste-handling protocols with simulated patient trash to ensure adequate sterilization. The results of the validation process revealed that autoclave factory default settings are potentially ineffective for certain types of medical waste and highlighted the critical role of waste packaging in successful sterilization. The lessons learned from the JHH validation process can inform the design of waste management protocols to ensure effective treatment of highly infectious medical waste. PMID:27927920
Validation of Autoclave Protocols for Successful Decontamination of Category A Medical Waste Generated from Care of Patients with Serious Communicable Diseases.

PubMed

Garibaldi, Brian T; Reimers, Mallory; Ernst, Neysa; Bova, Gregory; Nowakowski, Elaine; Bukowski, James; Ellis, Brandon C; Smith, Chris; Sauer, Lauren; Dionne, Kim; Carroll, Karen C; Maragakis, Lisa L; Parrish, Nicole M

2017-02-01

In response to the Ebola outbreak in 2014, many hospitals designated specific areas to care for patients with Ebola and other highly infectious diseases. The safe handling of category A infectious substances is a unique challenge in this environment. One solution is on-site waste treatment with a steam sterilizer or autoclave. The Johns Hopkins Hospital (JHH) installed two pass-through autoclaves in its biocontainment unit (BCU). The JHH BCU and The Johns Hopkins biosafety level 3 (BSL-3) clinical microbiology laboratory designed and validated waste-handling protocols with simulated patient trash to ensure adequate sterilization. The results of the validation process revealed that autoclave factory default settings are potentially ineffective for certain types of medical waste and highlighted the critical role of waste packaging in successful sterilization. The lessons learned from the JHH validation process can inform the design of waste management protocols to ensure effective treatment of highly infectious medical waste. Copyright © 2017 American Society for Microbiology.
Use of the recognition heuristic depends on the domain's recognition validity, not on the recognition validity of selected sets of objects.

PubMed

Pohl, Rüdiger F; Michalkiewicz, Martha; Erdfelder, Edgar; Hilbig, Benjamin E

2017-07-01

According to the recognition-heuristic theory, decision makers solve paired comparisons in which one object is recognized and the other not by recognition alone, inferring that recognized objects have higher criterion values than unrecognized ones. However, success-and thus usefulness-of this heuristic depends on the validity of recognition as a cue, and adaptive decision making, in turn, requires that decision makers are sensitive to it. To this end, decision makers could base their evaluation of the recognition validity either on the selected set of objects (the set's recognition validity), or on the underlying domain from which the objects were drawn (the domain's recognition validity). In two experiments, we manipulated the recognition validity both in the selected set of objects and between domains from which the sets were drawn. The results clearly show that use of the recognition heuristic depends on the domain's recognition validity, not on the set's recognition validity. In other words, participants treat all sets as roughly representative of the underlying domain and adjust their decision strategy adaptively (only) with respect to the more general environment rather than the specific items they are faced with.
The Development of Valid Subtypes for Depression in Primary Care Settings

PubMed Central

Karasz, Alison

2009-01-01

A persistent theme in the debate on the classification of depressive disorders is the distinction between biological and environmental depressions. Despite decades of research, there remains little consensus on how to distinguish between depressive subtypes. This preliminary study describes a method that could be useful, if implemented on a larger scale, in the development of valid subtypes of depression in primary care settings, using explanatory models of depressive illness. Seventeen depressed Hispanic patients at an inner city general practice participated in explanatory model interviews. Participants generated illness narratives, which included details about symptoms, cause, course, impact, health seeking, and anticipated outcome. Two distinct subtypes emerged from the analysis. The internal model subtype was characterized by internal attributions, specifically the notion of an “injured self.” The external model subtype conceptualized depression as a reaction to life situations. Each subtype was associated with a distinct constellation of clinical features and health seeking experiences. Future directions for research using explanatory models to establish depressive subtypes are explored. PMID:18414123
Rapid construction of a whole-genome transposon insertion collection for Shewanella oneidensis by Knockout Sudoku.

PubMed

Baym, Michael; Shaket, Lev; Anzai, Isao A; Adesina, Oluwakemi; Barstow, Buz

2016-11-10

Whole-genome knockout collections are invaluable for connecting gene sequence to function, yet traditionally, their construction has required an extraordinary technical effort. Here we report a method for the construction and purification of a curated whole-genome collection of single-gene transposon disruption mutants termed Knockout Sudoku. Using simple combinatorial pooling, a highly oversampled collection of mutants is condensed into a next-generation sequencing library in a single day, a 30- to 100-fold improvement over prior methods. The identities of the mutants in the collection are then solved by a probabilistic algorithm that uses internal self-consistency within the sequencing data set, followed by rapid algorithmically guided condensation to a minimal representative set of mutants, validation, and curation. Starting from a progenitor collection of 39,918 mutants, we compile a quality-controlled knockout collection of the electroactive microbe Shewanella oneidensis MR-1 containing representatives for 3,667 genes that is functionally validated by high-throughput kinetic measurements of quinone reduction.
ION Configuration Editor

NASA Technical Reports Server (NTRS)

Borgen, Richard L.

2013-01-01

The configuration of ION (Inter - planetary Overlay Network) network nodes is a manual task that is complex, time-consuming, and error-prone. This program seeks to accelerate this job and produce reliable configurations. The ION Configuration Editor is a model-based smart editor based on Eclipse Modeling Framework technology. An ION network designer uses this Eclipse-based GUI to construct a data model of the complete target network and then generate configurations. The data model is captured in an XML file. Intrinsic editor features aid in achieving model correctness, such as field fill-in, type-checking, lists of valid values, and suitable default values. Additionally, an explicit "validation" feature executes custom rules to catch more subtle model errors. A "survey" feature provides a set of reports providing an overview of the entire network, enabling a quick assessment of the model s completeness and correctness. The "configuration" feature produces the main final result, a complete set of ION configuration files (eight distinct file types) for each ION node in the network.
Vascular endothelial growth factor receptor-2 (VEGFR-2) inhibitors: development and validation of predictive 3-D QSAR models through extensive ligand- and structure-based approaches

NASA Astrophysics Data System (ADS)

Ragno, Rino; Ballante, Flavio; Pirolli, Adele; Wickersham, Richard B.; Patsilinakos, Alexandros; Hesse, Stéphanie; Perspicace, Enrico; Kirsch, Gilbert

2015-08-01

Vascular endothelial growth factor receptor-2, (VEGFR-2), is a key element in angiogenesis, the process by which new blood vessels are formed, and is thus an important pharmaceutical target. Here, 3-D quantitative structure-activity relationship (3-D QSAR) were used to build a quantitative screening and pharmacophore model of the VEGFR-2 receptors for design of inhibitors with improved activities. Most of available experimental data information has been used as training set to derive optimized and fully cross-validated eight mono-probe and a multi-probe quantitative models. Notable is the use of 262 molecules, aligned following both structure-based and ligand-based protocols, as external test set confirming the 3-D QSAR models' predictive capability and their usefulness in design new VEGFR-2 inhibitors. From a survey on literature, this is the first generation of a wide-ranging computational medicinal chemistry application on VEGFR2 inhibitors.
Validation of the Gratitude Questionnaire in Filipino Secondary School Students.

PubMed

Valdez, Jana Patricia M; Yang, Weipeng; Datu, Jesus Alfonso D

2017-10-11

Most studies have assessed the psychometric properties of the Gratitude Questionnaire - Six-Item Form (GQ-6) in the Western contexts while very few research has been generated to explore the applicability of this scale in non-Western settings. To address this gap, the aim of the study was to examine the factorial validity and gender invariance of the Gratitude Questionnaire in the Philippines through a construct validation approach. There were 383 Filipino high school students who participated in the research. In terms of within-network construct validity, results of confirmatory factor analyses revealed that the five-item version of the questionnaire (GQ-5) had better fit compared to the original six-item version of the gratitude questionnaire. The scores from the GQ-5 also exhibited invariance across gender. Between-network construct validation showed that gratitude was associated with higher levels of academic achievement (β = .46, p <.001), autonomous motivation (β = .73, p <.001), and controlled motivation (β = .28, p <.01). Conversely, gratitude was linked to lower degree of amotivation (β = -.51, p <.001). Theoretical and practical implications are discussed.
Are the major risk/need factors predictive of both female and male reoffending?: a test with the eight domains of the level of service/case management inventory.

PubMed

Andrews, Donald A; Guzzo, Lina; Raynor, Peter; Rowe, Robert C; Rettinger, L Jill; Brews, Albert; Wormith, J Stephen

2012-02-01

The Level of Service/Case Management Inventory (LS/CMI) and the Youth version (YLS/CMI) generate an assessment of risk/need across eight domains that are considered to be relevant for girls and boys and for women and men. Aggregated across five data sets, the predictive validity of each of the eight domains was gender-neutral. The composite total score (LS/CMI total risk/need) was strongly associated with the recidivism of males (mean r = .39, mean AUC = .746) and very strongly associated with the recidivism of females (mean r = .53, mean AUC = .827). The enhanced validity of LS total risk/need with females was traced to the exceptional validity of Substance Abuse with females. The intra-data set conclusions survived the introduction of two very large samples composed of female offenders exclusively. Finally, the mean incremental contributions of gender and the gender-by-risk level interactions in the prediction of criminal recidivism were minimal compared to the relatively strong validity of the LS/CMI risk level. Although the variance explained by gender was minimal and although high-risk cases were high-risk cases regardless of gender, the recidivism rates of lower risk females were lower than the recidivism rates of lower risk males, suggesting possible implications for test interpretation and policy.
Development of estrogen receptor beta binding prediction model using large sets of chemicals.

PubMed

Sakkiah, Sugunadevi; Selvaraj, Chandrabose; Gong, Ping; Zhang, Chaoyang; Tong, Weida; Hong, Huixiao

2017-11-03

We developed an ER β binding prediction model to facilitate identification of chemicals specifically bind ER β or ER α together with our previously developed ER α binding model. Decision Forest was used to train ER β binding prediction model based on a large set of compounds obtained from EADB. Model performance was estimated through 1000 iterations of 5-fold cross validations. Prediction confidence was analyzed using predictions from the cross validations. Informative chemical features for ER β binding were identified through analysis of the frequency data of chemical descriptors used in the models in the 5-fold cross validations. 1000 permutations were conducted to assess the chance correlation. The average accuracy of 5-fold cross validations was 93.14% with a standard deviation of 0.64%. Prediction confidence analysis indicated that the higher the prediction confidence the more accurate the predictions. Permutation testing results revealed that the prediction model is unlikely generated by chance. Eighteen informative descriptors were identified to be important to ER β binding prediction. Application of the prediction model to the data from ToxCast project yielded very high sensitivity of 90-92%. Our results demonstrated ER β binding of chemicals could be accurately predicted using the developed model. Coupling with our previously developed ER α prediction model, this model could be expected to facilitate drug development through identification of chemicals that specifically bind ER β or ER α .
The Chinese Facial Emotion Recognition Database (CFERD): a computer-generated 3-D paradigm to measure the recognition of facial emotional expressions at different intensities.

PubMed

Huang, Charles Lung-Cheng; Hsiao, Sigmund; Hwu, Hai-Gwo; Howng, Shen-Long

2012-12-30

The Chinese Facial Emotion Recognition Database (CFERD), a computer-generated three-dimensional (3D) paradigm, was developed to measure the recognition of facial emotional expressions at different intensities. The stimuli consisted of 3D colour photographic images of six basic facial emotional expressions (happiness, sadness, disgust, fear, anger and surprise) and neutral faces of the Chinese. The purpose of the present study is to describe the development and validation of CFERD with nonclinical healthy participants (N=100; 50 men; age ranging between 18 and 50 years), and to generate normative data set. The results showed that the sensitivity index d' [d'=Z(hit rate)-Z(false alarm rate), where function Z(p), p∈[0,1
Survey of Approaches to Generate Realistic Synthetic Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lim, Seung-Hwan; Lee, Sangkeun; Powers, Sarah S

A graph is a flexible data structure that can represent relationships between entities. As with other data analysis tasks, the use of realistic graphs is critical to obtaining valid research results. Unfortunately, using the actual ("real-world") graphs for research and new algorithm development is difficult due to the presence of sensitive information in the data or due to the scale of data. This results in practitioners developing algorithms and systems that employ synthetic graphs instead of real-world graphs. Generating realistic synthetic graphs that provide reliable statistical confidence to algorithmic analysis and system evaluation involves addressing technical hurdles in a broadmore » set of areas. This report surveys the state of the art in approaches to generate realistic graphs that are derived from fitted graph models on real-world graphs.« less
TH-CD-202-06: A Method for Characterizing and Validating Dynamic Lung Density Change During Quiet Respiration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dou, T; Ruan, D; Heinrich, M

2016-06-15

Purpose: To obtain a functional relationship that calibrates the lung tissue density change under free breathing conditions through correlating Jacobian values to the Hounsfield units. Methods: Free-breathing lung computed tomography images were acquired using a fast helical CT protocol, where 25 scans were acquired per patient. Using a state-of-the-art deformable registration algorithm, a set of the deformation vector fields (DVF) was generated to provide spatial mapping from the reference image geometry to the other free-breathing scans. These DVFs were used to generate Jacobian maps, which estimate voxelwise volume change. Subsequently, the set of 25 corresponding Jacobian and voxel intensity inmore » Hounsfield units (HU) were collected and linear regression was performed based on the mass conservation relationship to correlate the volume change to density change. Based on the resulting fitting coefficients, the tissues were classified into parenchymal (Type I), vascular (Type II), and soft tissue (Type III) types. These coefficients modeled the voxelwise density variation during quiet breathing. The accuracy of the proposed method was assessed using mean absolute difference in HU between the CT scan intensities and the model predicted values. In addition, validation experiments employing a leave-five-out method were performed to evaluate the model accuracy. Results: The computed mean model errors were 23.30±9.54 HU, 29.31±10.67 HU, and 35.56±20.56 HU, respectively, for regions I, II, and III, respectively. The cross validation experiments averaged over 100 trials had mean errors of 30.02 ± 1.67 HU over the entire lung. These mean values were comparable with the estimated CT image background noise. Conclusion: The reported validation experiment statistics confirmed the lung density modeling during free breathing. The proposed technique was general and could be applied to a wide range of problem scenarios where accurate dynamic lung density information is needed. This work was supported in part by NIH R01 CA0096679.« less
Generation, Analysis and Characterization of Anisotropic Engineered Meta Materials

NASA Astrophysics Data System (ADS)

Trifale, Ninad T.

A methodology for a systematic generation of highly anisotropic micro-lattice structures was investigated. Multiple algorithms for generation and validation of engineered structures are developed and evaluated. Set of all possible permutations of structures for an 8-node cubic unit cell were considered and the degree of anisotropy of meta-properties in heat transport and mechanical elasticity were evaluated. Feasibility checks were performed to ensure that the generated unit cell network was repeatable and a continuous lattice structure. Four different strategies for generating permutations of the structures are discussed. Analytical models were developed to predict effective thermal, mechanical and permeability characteristics of these cellular structures.Experimentation and numerical modeling techniques were used to validate the models that are developed. A self-consistent mechanical elasticity model was developed which connects the meso-scale properties to stiffness of individual struts. A three dimensional thermal resistance network analogy was used to evaluate the effective thermal conductivity of the structures. The struts were modeled as a network of one dimensional thermal resistive elements and effective conductivity evaluated. Models were validated against numerical simulations and experimental measurements on 3D printed samples. Model was developed to predict effective permeability of these engineered structures based on Darcy's law. Drag coefficients were evaluated for individual connections in transverse and longitudinal directions and an interaction term was calibrated from the experimental data in literature in order to predict permeability. Generic optimization framework coupled to finite element solver is developed for analyzing any application involving use of porous structures. An objective functions were generated structure to address frequently observed trade-off between the stiffness, thermal conductivity, permeability and porosity. Three application were analyzed for potential use of engineered materials. Heat spreader application involving thermal and mechanical constraints, artificial bone grafts application involving mechanical and permeability constraints and structural materials applications involving mechanical, thermal and porosity constraints is analyzed. Recommendations for optimum topologies for specific operating conditions are provided.
Development and Preliminary Validation of Refugee Trauma History Checklist (RTHC)—A Brief Checklist for Survey Studies

PubMed Central

Gottvall, Maria; Vaez, Marjan

2017-01-01

A high proportion of refugees have been subjected to potentially traumatic experiences (PTEs), including torture. PTEs, and torture in particular, are powerful predictors of mental ill health. This paper reports the development and preliminary validation of a brief refugee trauma checklist applicable for survey studies. Methods: A pool of 232 items was generated based on pre-existing instruments. Conceptualization, item selection and item refinement was conducted based on existing literature and in collaboration with experts. Ten cognitive interviews using a Think Aloud Protocol (TAP) were performed in a clinical setting, and field testing of the proposed checklist was performed in a total sample of n = 137 asylum seekers from Syria. Results: The proposed refugee trauma history checklist (RTHC) consists of 2 × 8 items, concerning PTEs that occurred before and during the respondents’ flight, respectively. Results show low item non-response and adequate psychometric properties Conclusions: RTHC is a usable tool for providing self-report data on refugee trauma history surveys of community samples. The core set of included events can be augmented and slight modifications can be applied to RTHC for use also in other refugee populations and settings. PMID:28976937
Ozone reference models for the middle atmosphere (new CIRA)

NASA Technical Reports Server (NTRS)

Keating, G. M.; Pitts, M. C.; Young, D. F.

1989-01-01

Models of ozone vertical structure were generated that were based on multiple data sets from satellites. The very good absolute accuracy of the individual data sets allowed the data to be directly combined to generate these models. The data used for generation of these models are from some of the most recent satellite measurements over the period 1978 to 1983. A discussion is provided of validation and error analyses of these data sets. Also, inconsistencies in data sets brought about by temporal variations or other factors are indicated. The models cover the pressure range from from 20 to 0.003 mb (25 to 90 km). The models for pressures less than 0.5 mb represent only the day side and are only provisional since there was limited longitudinal coverage at these levels. The models start near 25 km in accord with previous COSPAR international reference atmosphere (CIRA) models. Models are also provided of ozone mixing ratio as a function of height. The monthly standard deviation and interannual variations relative to zonal means are also provided. In addition to the models of monthly latitudinal variations in vertical structure based on satellite measurements, monthly models of total column ozone and its characteristic variability as a function of latitude based on four years of Nimbus 7 measurements, models of the relationship between vertical structure and total column ozone, and a midlatitude annual mean model are incorporated in this set of ozone reference atmospheres. Various systematic variations are discussed including the annual, semiannual, and quasibiennial oscillations, and diurnal, longitudinal, and response to solar activity variations.
Comparison of Aircraft Icing Growth Assessment Software

NASA Technical Reports Server (NTRS)

Wright, William; Potapczuk, Mark G.; Levinson, Laurie H.

2011-01-01

A research project is underway to produce computer software that can accurately predict ice growth under any meteorological conditions for any aircraft surface. An extensive comparison of the results in a quantifiable manner against the database of ice shapes that have been generated in the NASA Glenn Icing Research Tunnel (IRT) has been performed, including additional data taken to extend the database in the Super-cooled Large Drop (SLD) regime. The project shows the differences in ice shape between LEWICE 3.2.2, GlennICE, and experimental data. The project addresses the validation of the software against a recent set of ice-shape data in the SLD regime. This validation effort mirrors a similar effort undertaken for previous validations of LEWICE. Those reports quantified the ice accretion prediction capabilities of the LEWICE software. Several ice geometry features were proposed for comparing ice shapes in a quantitative manner. The resulting analysis showed that LEWICE compared well to the available experimental data.

Numerical simulation of wave-current interaction using the SPH method

NASA Astrophysics Data System (ADS)

He, Ming; Gao, Xi-feng; Xu, Wan-hai

2018-05-01

In this paper, the smoothed particle hydrodynamics (SPH) method is used to build a numerical wave-current tank (NWCT). The wave is generated by using a piston-type wave generator and is absorbed by using a sponge layer. The uniform current field is generated by simultaneously imposing the directional velocity and hydrostatic pressure in both inflow and outflow regions set below the NWCT. Particle cyclic boundaries are also implemented for recycling the Lagrangian fluid particles. Furthermore, to shorten the time to reach a steady state, a temporary rigid-lid treatment for the water surface is proposed. It turns out to be very effective for weakening the undesired oscillatory flow at the beginning stage of the current generation. The calculated water surface elevation and horizontal-velocity profile are validated against the available experimental data. Satisfactory agreements are obtained, demonstrating the good capability of the NWCT.
Development of a realistic, dynamic digital brain phantom for CT perfusion validation

NASA Astrophysics Data System (ADS)

Divel, Sarah E.; Segars, W. Paul; Christensen, Soren; Wintermark, Max; Lansberg, Maarten G.; Pelc, Norbert J.

2016-03-01

Physicians rely on CT Perfusion (CTP) images and quantitative image data, including cerebral blood flow, cerebral blood volume, and bolus arrival delay, to diagnose and treat stroke patients. However, the quantification of these metrics may vary depending on the computational method used. Therefore, we have developed a dynamic and realistic digital brain phantom upon which CTP scans can be simulated based on a set of ground truth scenarios. Building upon the previously developed 4D extended cardiac-torso (XCAT) phantom containing a highly detailed brain model, this work consisted of expanding the intricate vasculature by semi-automatically segmenting existing MRA data and fitting nonuniform rational B-spline surfaces to the new vessels. Using time attenuation curves input by the user as reference, the contrast enhancement in the vessels changes dynamically. At each time point, the iodine concentration in the arteries and veins is calculated from the curves and the material composition of the blood changes to reflect the expected values. CatSim, a CT system simulator, generates simulated data sets of this dynamic digital phantom which can be further analyzed to validate CTP studies and post-processing methods. The development of this dynamic and realistic digital phantom provides a valuable resource with which current uncertainties and controversies surrounding the quantitative computations generated from CTP data can be examined and resolved.
Ligand- and structure-based in silico studies to identify kinesin spindle protein (KSP) inhibitors as potential anticancer agents.

PubMed

Balakumar, Chandrasekaran; Ramesh, Muthusamy; Tham, Chuin Lean; Khathi, Samukelisiwe Pretty; Kozielski, Frank; Srinivasulu, Cherukupalli; Hampannavar, Girish A; Sayyad, Nisar; Soliman, Mahmoud E; Karpoormath, Rajshekhar

2017-11-29

Kinesin spindle protein (KSP) belongs to the kinesin superfamily of microtubule-based motor proteins. KSP is responsible for the establishment of the bipolar mitotic spindle which mediates cell division. Inhibition of KSP expedites the blockade of the normal cell cycle during mitosis through the generation of monoastral MT arrays that finally cause apoptotic cell death. As KSP is highly expressed in proliferating/cancer cells, it has gained considerable attention as a potential drug target for cancer chemotherapy. Therefore, this study envisaged to design novel KSP inhibitors by employing computational techniques/tools such as pharmacophore modelling, virtual database screening, molecular docking and molecular dynamics. Initially, the pharmacophore models were generated from the data-set of highly potent KSP inhibitors and the pharmacophore models were validated against in house test set ligands. The validated pharmacophore model was then taken for database screening (Maybridge and ChemBridge) to yield hits, which were further filtered for their drug-likeliness. The potential hits retrieved from virtual database screening were docked using CDOCKER to identify the ligand binding landscape. The top-ranked hits obtained from molecular docking were progressed to molecular dynamics (AMBER) simulations to deduce the ligand binding affinity. This study identified MB-41570 and CB-10358 as potential hits and evaluated these experimentally using in vitro KSP ATPase inhibition assays.
Quantum-mechanics-derived 13Cα chemical shift server (CheShift) for protein structure validation

PubMed Central

Vila, Jorge A.; Arnautova, Yelena A.; Martin, Osvaldo A.; Scheraga, Harold A.

2009-01-01

A server (CheShift) has been developed to predict 13Cα chemical shifts of protein structures. It is based on the generation of 696,916 conformations as a function of the φ, ψ, ω, χ1 and χ2 torsional angles for all 20 naturally occurring amino acids. Their 13Cα chemical shifts were computed at the DFT level of theory with a small basis set and extrapolated, with an empirically-determined linear regression formula, to reproduce the values obtained with a larger basis set. Analysis of the accuracy and sensitivity of the CheShift predictions, in terms of both the correlation coefficient R and the conformational-averaged rmsd between the observed and predicted 13Cα chemical shifts, was carried out for 3 sets of conformations: (i) 36 x-ray-derived protein structures solved at 2.3 Å or better resolution, for which sets of 13Cα chemical shifts were available; (ii) 15 pairs of x-ray and NMR-derived sets of protein conformations; and (iii) a set of decoys for 3 proteins showing an rmsd with respect to the x-ray structure from which they were derived of up to 3 Å. Comparative analysis carried out with 4 popular servers, namely SHIFTS, SHIFTX, SPARTA, and PROSHIFT, for these 3 sets of conformations demonstrated that CheShift is the most sensitive server with which to detect subtle differences between protein models and, hence, to validate protein structures determined by either x-ray or NMR methods, if the observed 13Cα chemical shifts are available. CheShift is available as a web server. PMID:19805131
A Framework for the Development and Interpretation of Different Sepsis Definitions and Clinical Criteria

PubMed Central

Angus, Derek C.; Seymour, Christopher W.; Coopersmith, Craig M.; Deutschman, Clifford; Klompas, Michael; Levy, Mitchell M.; Martin, Greg S.; Osborn, Tiffany M.; Rhee, Chanu; Watson, R. Scott

2016-01-01

Although sepsis was described more than 2,000 years ago, and clinicians still struggle to define it, there is no “gold standard,” and multiple competing approaches and terms exist. Challenges include the ever-changing knowledge base that informs our understanding of sepsis, competing views on which aspects of any potential definition are most important, and the tendency of most potential criteria to be distributed in at-risk populations in such a way as to hinder separation into discrete sets of patients. We propose that the development and evaluation of any definition or diagnostic criteria should follow four steps: 1) define the epistemologic underpinning, 2) agree on all relevant terms used to frame the exercise, 3) state the intended purpose for any proposed set of criteria, and 4) adopt a scientific approach to inform on their usefulness with regard to the intended purpose. Usefulness can be measured across six domains: 1) reliability (stability of criteria during retesting, between raters, over time, and across settings), 2) content validity (similar to face validity), 3) construct validity (whether criteria measure what they purport to measure), 4) criterion validity (how new criteria fare compared to standards), 5) measurement burden (cost, safety, and complexity), and 6) timeliness (whether criteria are available concurrent with care decisions). The relative importance of these domains of usefulness depends on the intended purpose, of which there are four broad categories: 1) clinical care, 2) research, 3) surveillance, and 4) quality improvement and audit. This proposed methodologic framework is intended to aid understanding of the strengths and weaknesses of different approaches, provide a mechanism for explaining differences in epidemiologic estimates generated by different approaches, and guide the development of future definitions and diagnostic criteria. PMID:26901559
Measuring the impact of diagnostic decision support on the quality of clinical decision making: development of a reliable and valid composite score.

PubMed

Ramnarayan, Padmanabhan; Kapoor, Ritika R; Coren, Michael; Nanduri, Vasantha; Tomlinson, Amanda L; Taylor, Paul M; Wyatt, Jeremy C; Britto, Joseph F

2003-01-01

Few previous studies evaluating the benefits of diagnostic decision support systems have simultaneously measured changes in diagnostic quality and clinical management prompted by use of the system. This report describes a reliable and valid scoring technique to measure the quality of clinical decision plans in an acute medical setting, where diagnostic decision support tools might prove most useful. Sets of differential diagnoses and clinical management plans generated by 71 clinicians for six simulated cases, before and after decision support from a Web-based pediatric differential diagnostic tool (ISABEL), were used. A composite quality score was calculated separately for each diagnostic and management plan by considering the appropriateness value of each component diagnostic or management suggestion, a weighted sum of individual suggestion ratings, relevance of the entire plan, and its comprehensiveness. The reliability and validity (face, concurrent, construct, and content) of these two final scores were examined. Two hundred fifty-two diagnostic and 350 management suggestions were included in the interrater reliability analysis. There was good agreement between raters (intraclass correlation coefficient, 0.79 for diagnoses, and 0.72 for management). No counterintuitive scores were demonstrated on visual inspection of the sets. Content validity was verified by a consultation process with pediatricians. Both scores discriminated adequately between the plans of consultants and medical students and correlated well with clinicians' subjective opinions of overall plan quality (Spearman rho 0.65, p < 0.01). The diagnostic and management scores for each episode showed moderate correlation (r = 0.51). The scores described can be used as key outcome measures in a larger study to fully assess the value of diagnostic decision aids, such as the ISABEL system.
A Framework for the Development and Interpretation of Different Sepsis Definitions and Clinical Criteria.

PubMed

Angus, Derek C; Seymour, Christopher W; Coopersmith, Craig M; Deutschman, Clifford S; Klompas, Michael; Levy, Mitchell M; Martin, Gregory S; Osborn, Tiffany M; Rhee, Chanu; Watson, R Scott

2016-03-01

Although sepsis was described more than 2,000 years ago, and clinicians still struggle to define it, there is no "gold standard," and multiple competing approaches and terms exist. Challenges include the ever-changing knowledge base that informs our understanding of sepsis, competing views on which aspects of any potential definition are most important, and the tendency of most potential criteria to be distributed in at-risk populations in such a way as to hinder separation into discrete sets of patients. We propose that the development and evaluation of any definition or diagnostic criteria should follow four steps: 1) define the epistemologic underpinning, 2) agree on all relevant terms used to frame the exercise, 3) state the intended purpose for any proposed set of criteria, and 4) adopt a scientific approach to inform on their usefulness with regard to the intended purpose. Usefulness can be measured across six domains: 1) reliability (stability of criteria during retesting, between raters, over time, and across settings), 2) content validity (similar to face validity), 3) construct validity (whether criteria measure what they purport to measure), 4) criterion validity (how new criteria fare compared to standards), 5) measurement burden (cost, safety, and complexity), and 6) timeliness (whether criteria are available concurrent with care decisions). The relative importance of these domains of usefulness depends on the intended purpose, of which there are four broad categories: 1) clinical care, 2) research, 3) surveillance, and 4) quality improvement and audit. This proposed methodologic framework is intended to aid understanding of the strengths and weaknesses of different approaches, provide a mechanism for explaining differences in epidemiologic estimates generated by different approaches, and guide the development of future definitions and diagnostic criteria.
Protein Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: Progress and Challenges.

PubMed

Root, Alex; Allen, Peter; Tempst, Paul; Yu, Kenneth

2018-03-07

Approximately 75% of patients with pancreatic ductal adenocarcinoma are diagnosed with advanced cancer, which cannot be safely resected. The most commonly used biomarker CA19-9 has inadequate sensitivity and specificity for early detection, which we define as Stage I/II cancers. Therefore, progress in next-generation biomarkers is greatly needed. Recent reports have validated a number of biomarkers, including combination assays of proteins and DNA mutations; however, the history of translating promising biomarkers to clinical utility suggests that several major hurdles require careful consideration by the medical community. The first set of challenges involves nominating and verifying biomarkers. Candidate biomarkers need to discriminate disease from benign controls with high sensitivity and specificity for an intended use, which we describe as a two-tiered strategy of identifying and screening high-risk patients. Community-wide efforts to share samples, data, and analysis methods have been beneficial and progress meeting this challenge has been achieved. The second set of challenges is assay optimization and validating biomarkers. After initial candidate validation, assays need to be refined into accurate, cost-effective, highly reproducible, and multiplexed targeted panels and then validated in large cohorts. To move the most promising candidates forward, ideally, biomarker panels, head-to-head comparisons, meta-analysis, and assessment in independent data sets might mitigate risk of failure. Much more investment is needed to overcome these challenges. The third challenge is achieving clinical translation. To moonshot an early detection test to the clinic requires a large clinical trial and organizational, regulatory, and entrepreneurial know-how. Additional factors, such as imaging technologies, will likely need to improve concomitant with molecular biomarker development. The magnitude of the clinical translational challenge is uncertain, but interdisciplinary cooperation within the PDAC community is poised to confront it.
Development and validation of a set of six adaptable prognosis prediction (SAP) models based on time-series real-world big data analysis for patients with cancer receiving chemotherapy: A multicenter case crossover study

PubMed Central

Kanai, Masashi; Okamoto, Kazuya; Yamamoto, Yosuke; Yoshioka, Akira; Hiramoto, Shuji; Nozaki, Akira; Nishikawa, Yoshitaka; Yamaguchi, Daisuke; Tomono, Teruko; Nakatsui, Masahiko; Baba, Mika; Morita, Tatsuya; Matsumoto, Shigemi; Kuroda, Tomohiro; Okuno, Yasushi; Muto, Manabu

2017-01-01

Background We aimed to develop an adaptable prognosis prediction model that could be applied at any time point during the treatment course for patients with cancer receiving chemotherapy, by applying time-series real-world big data. Methods Between April 2004 and September 2014, 4,997 patients with cancer who had received systemic chemotherapy were registered in a prospective cohort database at the Kyoto University Hospital. Of these, 2,693 patients with a death record were eligible for inclusion and divided into training (n = 1,341) and test (n = 1,352) cohorts. In total, 3,471,521 laboratory data at 115,738 time points, representing 40 laboratory items [e.g., white blood cell counts and albumin (Alb) levels] that were monitored for 1 year before the death event were applied for constructing prognosis prediction models. All possible prediction models comprising three different items from 40 laboratory items (40C3 = 9,880) were generated in the training cohort, and the model selection was performed in the test cohort. The fitness of the selected models was externally validated in the validation cohort from three independent settings. Results A prognosis prediction model utilizing Alb, lactate dehydrogenase, and neutrophils was selected based on a strong ability to predict death events within 1–6 months and a set of six prediction models corresponding to 1,2, 3, 4, 5, and 6 months was developed. The area under the curve (AUC) ranged from 0.852 for the 1 month model to 0.713 for the 6 month model. External validation supported the performance of these models. Conclusion By applying time-series real-world big data, we successfully developed a set of six adaptable prognosis prediction models for patients with cancer receiving chemotherapy. PMID:28837592
Expression signature as a biomarker for prenatal diagnosis of trisomy 21.

PubMed

Volk, Marija; Maver, Aleš; Lovrečić, Luca; Juvan, Peter; Peterlin, Borut

2013-01-01

A universal biomarker panel with the potential to predict high-risk pregnancies or adverse pregnancy outcome does not exist. Transcriptome analysis is a powerful tool to capture differentially expressed genes (DEG), which can be used as biomarker-diagnostic-predictive tool for various conditions in prenatal setting. In search of biomarker set for predicting high-risk pregnancies, we performed global expression profiling to find DEG in Ts21. Subsequently, we performed targeted validation and diagnostic performance evaluation on a larger group of case and control samples. Initially, transcriptomic profiles of 10 cultivated amniocyte samples with Ts21 and 9 with normal euploid constitution were determined using expression microarrays. Datasets from Ts21 transcriptomic studies from GEO repository were incorporated. DEG were discovered using linear regression modelling and validated using RT-PCR quantification on an independent sample of 16 cases with Ts21 and 32 controls. The classification performance of Ts21 status based on expression profiling was performed using supervised machine learning algorithm and evaluated using a leave-one-out cross validation approach. Global gene expression profiling has revealed significant expression changes between normal and Ts21 samples, which in combination with data from previously performed Ts21 transcriptomic studies, were used to generate a multi-gene biomarker for Ts21, comprising of 9 gene expression profiles. In addition to biomarker's high performance in discriminating samples from global expression profiling, we were also able to show its discriminatory performance on a larger sample set 2, validated using RT-PCR experiment (AUC=0.97), while its performance on data from previously published studies reached discriminatory AUC values of 1.00. Our results show that transcriptomic changes might potentially be used to discriminate trisomy of chromosome 21 in the prenatal setting. As expressional alterations reflect both, causal and reactive cellular mechanisms, transcriptomic changes may thus have future potential in the diagnosis of a wide array of heterogeneous diseases that result from genetic disturbances.
Using the epigenetic field defect to detect prostate cancer in biopsy negative patients.

PubMed

Truong, Matthew; Yang, Bing; Livermore, Andrew; Wagner, Jennifer; Weeratunga, Puspha; Huang, Wei; Dhir, Rajiv; Nelson, Joel; Lin, Daniel W; Jarrard, David F

2013-06-01

We determined whether a novel combination of field defect DNA methylation markers could predict the presence of prostate cancer using histologically normal transrectal ultrasound guided biopsy cores. Methylation was assessed using quantitative Pyrosequencing® in a training set consisting of 65 nontumor and tumor associated prostate tissues from University of Wisconsin. A multiplex model was generated using multivariate logistic regression and externally validated in blinded fashion in a set of 47 nontumor and tumor associated biopsy specimens from University of Washington. We observed robust methylation differences in all genes at all CpGs assayed (p <0.0001). Regression models incorporating individual genes (EVX1, CAV1 and FGF1) and a gene combination (EVX1 and FGF1) discriminated nontumor from tumor associated tissues in the original training set (AUC 0.796-0.898, p <0.001). On external validation uniplex models incorporating EVX1, CAV1 or FGF1 discriminated tumor from nontumor associated biopsy negative specimens (AUC 0.702, 0.696 and 0.658, respectively, p <0.05). A multiplex model (EVX1 and FGF1) identified patients with prostate cancer (AUC 0.774, p = 0.001) and had a negative predictive value of 0.909. Comparison between 2 separate cores in patients in this validation set revealed similar methylation defects, indicating detection of a widespread field defect. A widespread epigenetic field defect can be used to detect prostate cancer in patients with histologically negative biopsies. To our knowledge this assay is unique, in that it detects alterations in nontumor cells. With further validation this marker combination (EVX1 and FGF1) has the potential to decrease the need for repeat prostate biopsies, a procedure associated with cost and complications. Copyright © 2013 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
Characterizing the literature on validity and assessment in medical education: a bibliometric study.

PubMed

Young, Meredith; St-Onge, Christina; Xiao, Jing; Vachon Lachiver, Elise; Torabi, Nazi

2018-05-23

Assessment in Medical Education fills many roles and is under constant scrutiny. Assessments must be of good quality, and supported by validity evidence. Given the high-stakes consequences of assessment, and the many audiences within medical education (e. g., training level, specialty-specific), we set out to document the breadth, scope, and characteristics of the literature reporting on validation of assessments within medical education. Searches in Medline (Ovid), Web of Science, ERIC, EMBASE (Ovid), and PsycINFO (Ovid) identified articles reporting on assessment of learners in medical education published since 1999. Included articles were coded for geographic origin, journal, journal category, targeted assessment, and authors. A map of collaborations between prolific authors was generated. A total of 2,863 articles were included. The majority of articles were from the United States, with Canada producing the most articles per medical school. Most articles were published in journals with medical categorizations (73.1% of articles), but Medical Education was the most represented journal (7.4% of articles). Articles reported on a variety of assessment tools and approaches, and 89 prolific authors were identified, with a total of 228 collaborative links. Literature reporting on validation of assessments in medical education is heterogeneous. Literature is produced by a broad array of authors and collaborative networks, reported to a broad audience, and is primarily generated in North American and European contexts. Our findings speak to the heterogeneity of the medical education literature on assessment validation, and suggest that this heterogeneity may stem, at least in part, from differences in constructs measured, assessment purposes, or conceptualizations of validity.
Mapping health outcome measures from a stroke registry to EQ-5D weights

PubMed Central

2013-01-01

Purpose To map health outcome related variables from a national register, not part of any validated instrument, with EQ-5D weights among stroke patients. Methods We used two cross-sectional data sets including patient characteristics, outcome variables and EQ-5D weights from the national Swedish stroke register. Three regression techniques were used on the estimation set (n = 272): ordinary least squares (OLS), Tobit, and censored least absolute deviation (CLAD). The regression coefficients for “dressing“, “toileting“, “mobility”, “mood”, “general health” and “proxy-responders” were applied to the validation set (n = 272), and the performance was analysed with mean absolute error (MAE) and mean square error (MSE). Results The number of statistically significant coefficients varied by model, but all models generated consistent coefficients in terms of sign. Mean utility was underestimated in all models (least in OLS) and with lower variation (least in OLS) compared to the observed. The maximum attainable EQ-5D weight ranged from 0.90 (OLS) to 1.00 (Tobit and CLAD). Health states with utility weights <0.5 had greater errors than those with weights ≥0.5 (P < 0.01). Conclusion This study indicates that it is possible to map non-validated health outcome measures from a stroke register into preference-based utilities to study the development of stroke care over time, and to compare with other conditions in terms of utility. PMID:23496957
Use of the Ames Check Standard Model for the Validation of Wall Interference Corrections

NASA Technical Reports Server (NTRS)

Ulbrich, N.; Amaya, M.; Flach, R.

2018-01-01

The new check standard model of the NASA Ames 11-ft Transonic Wind Tunnel was chosen for a future validation of the facility's wall interference correction system. The chosen validation approach takes advantage of the fact that test conditions experienced by a large model in the slotted part of the tunnel's test section will change significantly if a subset of the slots is temporarily sealed. Therefore, the model's aerodynamic coefficients have to be recorded, corrected, and compared for two different test section configurations in order to perform the validation. Test section configurations with highly accurate Mach number and dynamic pressure calibrations were selected for the validation. First, the model is tested with all test section slots in open configuration while keeping the model's center of rotation on the tunnel centerline. In the next step, slots on the test section floor are sealed and the model is moved to a new center of rotation that is 33 inches below the tunnel centerline. Then, the original angle of attack sweeps are repeated. Afterwards, wall interference corrections are applied to both test data sets and response surface models of the resulting aerodynamic coefficients in interference-free flow are generated. Finally, the response surface models are used to predict the aerodynamic coefficients for a family of angles of attack while keeping dynamic pressure, Mach number, and Reynolds number constant. The validation is considered successful if the corrected aerodynamic coefficients obtained from the related response surface model pair show good agreement. Residual differences between the corrected coefficient sets will be analyzed as well because they are an indicator of the overall accuracy of the facility's wall interference correction process.
Time Domain Tool Validation Using ARES I-X Flight Data

NASA Technical Reports Server (NTRS)

Hough, Steven; Compton, James; Hannan, Mike; Brandon, Jay

2011-01-01

The ARES I-X vehicle was launched from NASA's Kennedy Space Center (KSC) on October 28, 2009 at approximately 11:30 EDT. ARES I-X was the first test flight for NASA s ARES I launch vehicle, and it was the first non-Shuttle launch vehicle designed and flown by NASA since Saturn. The ARES I-X had a 4-segment solid rocket booster (SRB) first stage and a dummy upper stage (US) to emulate the properties of the ARES I US. During ARES I-X pre-flight modeling and analysis, six (6) independent time domain simulation tools were developed and cross validated. Each tool represents an independent implementation of a common set of models and parameters in a different simulation framework and architecture. Post flight data and reconstructed models provide the means to validate a subset of the simulations against actual flight data and to assess the accuracy of pre-flight dispersion analysis. Post flight data consists of telemetered Operational Flight Instrumentation (OFI) data primarily focused on flight computer outputs and sensor measurements as well as Best Estimated Trajectory (BET) data that estimates vehicle state information from all available measurement sources. While pre-flight models were found to provide a reasonable prediction of the vehicle flight, reconstructed models were generated to better represent and simulate the ARES I-X flight. Post flight reconstructed models include: SRB propulsion model, thrust vector bias models, mass properties, base aerodynamics, and Meteorological Estimated Trajectory (wind and atmospheric data). The result of the effort is a set of independently developed, high fidelity, time-domain simulation tools that have been cross validated and validated against flight data. This paper presents the process and results of high fidelity aerospace modeling, simulation, analysis and tool validation in the time domain.
Review of TRMM/GPM Rainfall Algorithm Validation

NASA Technical Reports Server (NTRS)

Smith, Eric A.

2004-01-01

A review is presented concerning current progress on evaluation and validation of standard Tropical Rainfall Measuring Mission (TRMM) precipitation retrieval algorithms and the prospects for implementing an improved validation research program for the next generation Global Precipitation Measurement (GPM) Mission. All standard TRMM algorithms are physical in design, and are thus based on fundamental principles of microwave radiative transfer and its interaction with semi-detailed cloud microphysical constituents. They are evaluated for consistency and degree of equivalence with one another, as well as intercompared to radar-retrieved rainfall at TRMM's four main ground validation sites. Similarities and differences are interpreted in the context of the radiative and microphysical assumptions underpinning the algorithms. Results indicate that the current accuracies of the TRMM Version 6 algorithms are approximately 15% at zonal-averaged / monthly scales with precisions of approximately 25% for full resolution / instantaneous rain rate estimates (i.e., level 2 retrievals). Strengths and weaknesses of the TRMM validation approach are summarized. Because the dew of convergence of level 2 TRMM algorithms is being used as a guide for setting validation requirements for the GPM mission, it is important that the GPM algorithm validation program be improved to ensure concomitant improvement in the standard GPM retrieval algorithms. An overview of the GPM Mission's validation plan is provided including a description of a new type of physical validation model using an analytic 3-dimensional radiative transfer model.
Control and Non-Payload Communications (CNPC) Prototype Radio Validation Flight Test Report

NASA Technical Reports Server (NTRS)

Shalkhauser, Kurt A.; Ishac, Joseph A.; Iannicca, Dennis C.; Bretmersky, Steven C.; Smith, Albert E.

2017-01-01

This report provides an overview and results from the unmanned aircraft (UA) Control and Non-Payload Communications (CNPC) Generation 5 prototype radio validation flight test campaign. The radios used in the test campaign were developed under cooperative agreement NNC11AA01A between the NASA Glenn Research Center and Rockwell Collins, Inc., of Cedar Rapids, Iowa. Measurement results are presented for flight tests over hilly terrain, open water, and urban landscape, utilizing radio sets installed into a NASA aircraft and ground stations. Signal strength and frame loss measurement data are analyzed relative to time and aircraft position, specifically addressing the impact of line-of-sight terrain obstructions on CNPC data flow. Both the radio and flight test system are described.
Assessing Discriminative Performance at External Validation of Clinical Prediction Models

PubMed Central

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W.

2016-01-01

Introduction External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. Methods We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. Results The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. Conclusion The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients. PMID:26881753
Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

PubMed

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W

2016-01-01

External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.
Analyses of the Integration of Carbon Dioxide Removal Assembly, Compressor, Accumulator and Sabatier Carbon Dioxide Reduction Assembly

NASA Technical Reports Server (NTRS)

Jeng, Frank F.; Lafuse, Sharon; Smith, Frederick D.; Lu, Sao-Dung; Knox, James C.; Campbell, Mellssa L.; Scull, Timothy D.; Green Steve

2010-01-01

A tool has been developed by the Sabatier Team for analyzing/optimizing CO2 removal assembly, CO2 compressor size, its operation logic, water generation from Sabatier, utilization of CO2 from crew metabolic output, and Hz from oxygen generation assembly. Tests had been conducted using CDRA/Simulation compressor set-up at MSFC in 2003. Analysis of test data has validated CO2 desorption rate profile, CO2 compressor performance, CO2 recovery and CO2 vacuum vent in CDRA desorption. Optimizing the compressor size and compressor operation logic for an integrated closed air revitalization system Is being conducted by the Sabatier Team.

A generative model for segmentation of tumor and organs-at-risk for radiation therapy planning of glioblastoma patients

NASA Astrophysics Data System (ADS)

Agn, Mikael; Law, Ian; Munck af Rosenschöld, Per; Van Leemput, Koen

2016-03-01

We present a fully automated generative method for simultaneous brain tumor and organs-at-risk segmentation in multi-modal magnetic resonance images. The method combines an existing whole-brain segmentation technique with a spatial tumor prior, which uses convolutional restricted Boltzmann machines to model tumor shape. The method is not tuned to any specific imaging protocol and can simultaneously segment the gross tumor volume, peritumoral edema and healthy tissue structures relevant for radiotherapy planning. We validate the method on a manually delineated clinical data set of glioblastoma patients by comparing segmentations of gross tumor volume, brainstem and hippocampus. The preliminary results demonstrate the feasibility of the method.
''Smart'' watchdog safety switch

DOEpatents

Kronberg, J.W.

1991-10-01

A method and apparatus for monitoring a process having a periodic output so that the process equipment is not damaged in the event of a controller failure, comprising a low-pass and peak clipping filter, an event detector that generates an event pulse for each valid change in magnitude of the filtered periodic output, a timing pulse generator, a counter that increments upon receipt of any timing pulse and resets to zero on receipt of any event pulse, an alarm that alerts when the count reaches some preselected total count, and a set of relays that opens to stop power to process equipment. An interface module can be added to allow the switch to accept a variety of periodic output signals. 21 figures.
"Smart" watchdog safety switch

DOEpatents

Kronberg, James W.

1991-01-01

A method and apparatus for monitoring a process having a periodic output so that the process equipment is not damaged in the event of a controller failure, comprising a low-pass and peak clipping filter, an event detector that generates an event pulse for each valid change in magnitude of the filtered periodic output, a timing pulse generator, a counter that increments upon receipt of any timing pulse and resets to zero on receipt of any event pulse, an alarm that alerts when the count reaches some preselected total count, and a set of relays that opens to stop power to process equipment. An interface module can be added to allow the switch to accept a variety of periodic output signals.
Liver fibrosis diagnosis by blood test and elastography in chronic hepatitis C: agreement or combination?

PubMed

Calès, P; Boursier, J; Lebigot, J; de Ledinghen, V; Aubé, C; Hubert, I; Oberti, F

2017-04-01

In chronic hepatitis C, the European Association for the Study of the Liver and the Asociacion Latinoamericana para el Estudio del Higado recommend performing transient elastography plus a blood test to diagnose significant fibrosis; test concordance confirms the diagnosis. To validate this rule and improve it by combining a blood test, FibroMeter (virus second generation, Echosens, Paris, France) and transient elastography (constitutive tests) into a single combined test, as suggested by the American Association for the Study of Liver Diseases and the Infectious Diseases Society of America. A total of 1199 patients were included in an exploratory set (HCV, n = 679) or in two validation sets (HCV ± HIV, HBV, n = 520). Accuracy was mainly evaluated by correct diagnosis rate for severe fibrosis (pathological Metavir F ≥ 3, primary outcome) by classical test scores or a fibrosis classification, reflecting Metavir staging, as a function of test concordance. Score accuracy: there were no significant differences between the blood test (75.7%), elastography (79.1%) and the combined test (79.4%) (P = 0.066); the score accuracy of each test was significantly (P < 0.001) decreased in discordant vs. concordant tests. Classification accuracy: combined test accuracy (91.7%) was significantly (P < 0.001) increased vs. the blood test (84.1%) and elastography (88.2%); accuracy of each constitutive test was significantly (P < 0.001) decreased in discordant vs. concordant tests but not with combined test: 89.0 vs. 92.7% (P = 0.118). Multivariate analysis for accuracy showed an interaction between concordance and fibrosis level: in the 1% of patients with full classification discordance and severe fibrosis, non-invasive tests were unreliable. The advantage of combined test classification was confirmed in the validation sets. The concordance recommendation is validated. A combined test, expressed in classification instead of score, improves this rule and validates the recommendation of a combined test, avoiding 99% of biopsies, and offering precise staging. © 2017 John Wiley & Sons Ltd.
Use of Attribute Driven Incremental Discretization and Logic Learning Machine to build a prognostic classifier for neuroblastoma patients.

PubMed

Cangelosi, Davide; Muselli, Marco; Parodi, Stefano; Blengio, Fabiola; Becherini, Pamela; Versteeg, Rogier; Conte, Massimo; Varesio, Luigi

2014-01-01

Cancer patient's outcome is written, in part, in the gene expression profile of the tumor. We previously identified a 62-probe sets signature (NB-hypo) to identify tissue hypoxia in neuroblastoma tumors and showed that NB-hypo stratified neuroblastoma patients in good and poor outcome 1. It was important to develop a prognostic classifier to cluster patients into risk groups benefiting of defined therapeutic approaches. Novel classification and data discretization approaches can be instrumental for the generation of accurate predictors and robust tools for clinical decision support. We explored the application to gene expression data of Rulex, a novel software suite including the Attribute Driven Incremental Discretization technique for transforming continuous variables into simplified discrete ones and the Logic Learning Machine model for intelligible rule generation. We applied Rulex components to the problem of predicting the outcome of neuroblastoma patients on the bases of 62 probe sets NB-hypo gene expression signature. The resulting classifier consisted in 9 rules utilizing mainly two conditions of the relative expression of 11 probe sets. These rules were very effective predictors, as shown in an independent validation set, demonstrating the validity of the LLM algorithm applied to microarray data and patients' classification. The LLM performed as efficiently as Prediction Analysis of Microarray and Support Vector Machine, and outperformed other learning algorithms such as C4.5. Rulex carried out a feature selection by selecting a new signature (NB-hypo-II) of 11 probe sets that turned out to be the most relevant in predicting outcome among the 62 of the NB-hypo signature. Rules are easily interpretable as they involve only few conditions. Our findings provided evidence that the application of Rulex to the expression values of NB-hypo signature created a set of accurate, high quality, consistent and interpretable rules for the prediction of neuroblastoma patients' outcome. We identified the Rulex weighted classification as a flexible tool that can support clinical decisions. For these reasons, we consider Rulex to be a useful tool for cancer classification from microarray gene expression data.
Invalid before impaired: an emerging paradox of embedded validity indicators.

PubMed

Erdodi, Laszlo A; Lichtenstein, Jonathan D

Embedded validity indicators (EVIs) are cost-effective psychometric tools to identify non-credible response sets during neuropsychological testing. As research on EVIs expands, assessors are faced with an emerging contradiction: the range of credible impairment disappears between the 'normal' and 'invalid' range of performance. We labeled this phenomenon as the invalid-before-impaired paradox. This study was designed to explore the origin of this psychometric anomaly, subject it to empirical investigation, and generate potential solutions. Archival data were analyzed from a mixed clinical sample of 312 (M Age = 45.2; M Education = 13.6) patients medically referred for neuropsychological assessment. The distribution of scores on eight subtests of the third and fourth editions of Wechsler Adult Intelligence Scale (WAIS) were examined in relation to the standard normal curve and two performance validity tests (PVTs). Although WAIS subtests varied in their sensitivity to non-credible responding, they were all significant predictors of performance validity. While subtests previously identified as EVIs (Digit Span, Coding, and Symbol Search) were comparably effective at differentiating credible and non-credible response sets, their classification accuracy was driven by their base rate of low scores, requiring different cutoffs to achieve comparable specificity. Invalid performance had a global effect on WAIS scores. Genuine impairment and non-credible performance can co-exist, are often intertwined, and may be psychometrically indistinguishable. A compromise between the alpha and beta bias on PVTs based on a balanced, objective evaluation of the evidence that requires concessions from both sides is needed to maintain/restore the credibility of performance validity assessment.
Predicting chemically-induced skin reactions. Part I: QSAR models of skin sensitization and their application to identify potentially hazardous compounds

PubMed Central

Alves, Vinicius M.; Muratov, Eugene; Fourches, Denis; Strickland, Judy; Kleinstreuer, Nicole; Andrade, Carolina H.; Tropsha, Alexander

2015-01-01

Repetitive exposure to a chemical agent can induce an immune reaction in inherently susceptible individuals that leads to skin sensitization. Although many chemicals have been reported as skin sensitizers, there have been very few rigorously validated QSAR models with defined applicability domains (AD) that were developed using a large group of chemically diverse compounds. In this study, we have aimed to compile, curate, and integrate the largest publicly available dataset related to chemically-induced skin sensitization, use this data to generate rigorously validated and QSAR models for skin sensitization, and employ these models as a virtual screening tool for identifying putative sensitizers among environmental chemicals. We followed best practices for model building and validation implemented with our predictive QSAR workflow using random forest modeling technique in combination with SiRMS and Dragon descriptors. The Correct Classification Rate (CCR) for QSAR models discriminating sensitizers from non-sensitizers were 71–88% when evaluated on several external validation sets, within a broad AD, with positive (for sensitizers) and negative (for non-sensitizers) predicted rates of 85% and 79% respectively. When compared to the skin sensitization module included in the OECD QSAR toolbox as well as to the skin sensitization model in publicly available VEGA software, our models showed a significantly higher prediction accuracy for the same sets of external compounds as evaluated by Positive Predicted Rate, Negative Predicted Rate, and CCR. These models were applied to identify putative chemical hazards in the ScoreCard database of possible skin or sense organ toxicants as primary candidates for experimental validation. PMID:25560674
Generating Models of Infinite-State Communication Protocols Using Regular Inference with Abstraction

NASA Astrophysics Data System (ADS)

Aarts, Fides; Jonsson, Bengt; Uijen, Johan

In order to facilitate model-based verification and validation, effort is underway to develop techniques for generating models of communication system components from observations of their external behavior. Most previous such work has employed regular inference techniques which generate modest-size finite-state models. They typically suppress parameters of messages, although these have a significant impact on control flow in many communication protocols. We present a framework, which adapts regular inference to include data parameters in messages and states for generating components with large or infinite message alphabets. A main idea is to adapt the framework of predicate abstraction, successfully used in formal verification. Since we are in a black-box setting, the abstraction must be supplied externally, using information about how the component manages data parameters. We have implemented our techniques by connecting the LearnLib tool for regular inference with the protocol simulator ns-2, and generated a model of the SIP component as implemented in ns-2.
Photoionization pathways and thresholds in generation of Lyman-α radiation by resonant four-wave mixing in Kr-Ar mixture

NASA Astrophysics Data System (ADS)

Louchev, Oleg A.; Saito, Norihito; Oishi, Yu; Miyazaki, Koji; Okamura, Kotaro; Nakamura, Jumpei; Iwasaki, Masahiko; Wada, Satoshi

2016-09-01

We develop a set of analytical approximations for the estimation of the combined effect of various photoionization processes involved in the resonant four-wave mixing generation of ns pulsed Lyman-α (L-α ) radiation by using 212.556 nm and 820-845 nm laser radiation pulses in Kr-Ar mixture: (i) multi-photon ionization, (ii) step-wise (2+1)-photon ionization via the resonant 2-photon excitation of Kr followed by 1-photon ionization and (iii) laser-induced avalanche ionization produced by generated free electrons. Developed expressions validated by order of magnitude estimations and available experimental data allow us to identify the area for the operation under high input laser intensities avoiding the onset of full-scale discharge, loss of efficiency and inhibition of generated L-α radiation. Calculations made reveal an opportunity for scaling up the output energy of the experimentally generated pulsed L-α radiation without significant enhancement of photoionization.
Multiple receptor conformation docking and dock pose clustering as tool for CoMFA and CoMSIA analysis - a case study on HIV-1 protease inhibitors.

PubMed

Sivan, Sree Kanth; Manga, Vijjulatha

2012-02-01

Multiple receptors conformation docking (MRCD) and clustering of dock poses allows seamless incorporation of receptor binding conformation of the molecules on wide range of ligands with varied structural scaffold. The accuracy of the approach was tested on a set of 120 cyclic urea molecules having HIV-1 protease inhibitory activity using 12 high resolution X-ray crystal structures and one NMR resolved conformation of HIV-1 protease extracted from protein data bank. A cross validation was performed on 25 non-cyclic urea HIV-1 protease inhibitor having varied structures. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were generated using 60 molecules in the training set by applying leave one out cross validation method, r (loo) (2) values of 0.598 and 0.674 for CoMFA and CoMSIA respectively and non-cross validated regression coefficient r(2) values of 0.983 and 0.985 were obtained for CoMFA and CoMSIA respectively. The predictive ability of these models was determined using a test set of 60 cyclic urea molecules that gave predictive correlation (r (pred) (2) ) of 0.684 and 0.64 respectively for CoMFA and CoMSIA indicating good internal predictive ability. Based on this information 25 non-cyclic urea molecules were taken as a test set to check the external predictive ability of these models. This gave remarkable out come with r (pred) (2) of 0.61 and 0.53 for CoMFA and CoMSIA respectively. The results invariably show that this method is useful for performing 3D QSAR analysis on molecules having different structural motifs.
Stromal mast cells in invasive breast cancer are a marker of favourable prognosis: a study of 4,444 cases.

PubMed

Rajput, Ashish B; Turbin, Dmitry A; Cheang, Maggie Cu; Voduc, David K; Leung, Sam; Gelmon, Karen A; Gilks, C Blake; Huntsman, David G

2008-01-01

We have previously demonstrated in a pilot study of 348 invasive breast cancers that mast cell (MC) infiltrates within primary breast cancers are associated with a good prognosis. Our aim was to verify this finding in a larger cohort of invasive breast cancer patients and examine the relationship between the presence of MCs and other clinical and pathological features. Clinically annotated tissue microarrays (TMAs) containing 4,444 cases were constructed and stained with c-Kit (CD-117) using standard immunoperoxidase techniques to identify and quantify MCs. For statistical analysis, we applied a split-sample validation technique. Breast cancer specific survival was analyzed by Kaplan-Meier [KM] method and log rank test was used to compare survival curves. Survival analysis by KM method showed that the presence of stromal MCs was a favourable prognostic factor in the training set (P = 0.001), and the validation set group (P = 0.006). X-tile plot generated to define the optimal number of MCs showed that the presence of any number of stromal MCs predicted good prognosis. Multivariate analysis showed that the MC effect in the training set (Hazard ratio [HR] = 0.804, 95% Confidence interval [CI], 0.653-0.991, P = 0.041) and validation set analysis (HR = 0.846, 95% CI, 0.683-1.049, P = 0.128) was independent of age, tumor grade, tumor size, lymph node, ER and Her2 status. This study concludes that stromal MC infiltration in invasive breast cancer is an independent good prognostic marker and reiterates the critical role of local inflammatory responses in breast cancer progression.
Stromal mast cells in invasive breast cancer are a marker of favourable prognosis: a study of 4,444 cases

PubMed Central

Rajput, Ashish B.; Turbin, Dmitry A.; Cheang, Maggie CU; Voduc, David K.; Leung, Sam; Gelmon, Karen A.; Gilks, C. Blake

2007-01-01

Purpose We have previously demonstrated in a pilot study of 348 invasive breast cancers that mast cell (MC) infiltrates within primary breast cancers are associated with a good prognosis. Our aim was to verify this finding in a larger cohort of invasive breast cancer patients and examine the relationship between the presence of MCs and other clinical and pathological features. Experimental design Clinically annotated tissue microarrays (TMAs) containing 4,444 cases were constructed and stained with c-Kit (CD-117) using standard immunoperoxidase techniques to identify and quantify MCs. For statistical analysis, we applied a split-sample validation technique. Breast cancer specific survival was analyzed by Kaplan–Meier [KM] method and log rank test was used to compare survival curves. Results Survival analysis by KM method showed that the presence of stromal MCs was a favourable prognostic factor in the training set (P = 0.001), and the validation set group (P = 0.006). X-tile plot generated to define the optimal number of MCs showed that the presence of any number of stromal MCs predicted good prognosis. Multivariate analysis showed that the MC effect in the training set (Hazard ratio [HR] = 0.804, 95% Confidence interval [CI], 0.653–0.991, P = 0.041) and validation set analysis (HR = 0.846, 95% CI, 0.683–1.049, P = 0.128) was independent of age, tumor grade, tumor size, lymph node, ER and Her2 status. Conclusions This study concludes that stromal MC infiltration in invasive breast cancer is an independent good prognostic marker and reiterates the critical role of local inflammatory responses in breast cancer progression. PMID:17431762
Reconstruction of an 8-lead surface ECG from two subcutaneous ICD vectors.

PubMed

Wilson, David G; Cronbach, Peter L; Panfilo, D; Greenhut, Saul E; Stegemann, Berthold P; Morgan, John M

2017-06-01

Techniques exist which allow surface ECGs to be reconstructed from reduced lead sets. We aimed to reconstruct an 8-lead ECG from two independent S-ICD sensing electrodes vectors as proof of this principle. Participants with ICDs (N=61) underwent 3minute ECGs using a TMSi Porti7 multi-channel signal recorder (TMS international, The Netherlands) with electrodes in the standard S-ICD and 12-lead positions. Participants were randomised to either a training (N=31) or validation (N=30) group. The transformation used was a linear combination of the 2 independent S-ICD vectors to each of the 8 independent leads of the 12-lead ECG, with coefficients selected that minimized the root mean square error (RMSE) between recorded and derived ECGs when applied to the training group. The transformation was then applied to the validation group and agreement between the recorded and derived lead pairs was measured by Pearson correlation coefficient (r) and normalised RMSE (NRMSE). In total, 27 patients with complete data sets were included in the validation set consisting of 57,888 data points from 216 full lead sets. The distribution of the r and NRMSE were skewed. Mean r=0.770 (SE 0.024), median r=0.925. NRMSE mean=0.233 (SE 0.015) median=0.171. We have demonstrated that the reconstruction of an 8-lead ECG from two S-ICD vectors is possible. If perfected, the ability to generate accurate multi-lead surface ECG data from an S-ICD would potentially allow recording and review of clinical arrhythmias at follow-up. Copyright © 2017 Elsevier B.V. All rights reserved.
Pooled individual patient data from five countries were used to derive a clinical prediction rule for coronary artery disease in primary care.

PubMed

Aerts, Marc; Minalu, Girma; Bösner, Stefan; Buntinx, Frank; Burnand, Bernard; Haasenritter, Jörg; Herzig, Lilli; Knottnerus, J André; Nilsson, Staffan; Renier, Walter; Sox, Carol; Sox, Harold; Donner-Banzhoff, Norbert

2017-01-01

To construct a clinical prediction rule for coronary artery disease (CAD) presenting with chest pain in primary care. Meta-Analysis using 3,099 patients from five studies. To identify candidate predictors, we used random forest trees, multiple imputation of missing values, and logistic regression within individual studies. To generate a prediction rule on the pooled data, we applied a regression model that took account of the differing standard data sets collected by the five studies. The most parsimonious rule included six equally weighted predictors: age ≥55 (males) or ≥65 (females) (+1); attending physician suspected a serious diagnosis (+1); history of CAD (+1); pain brought on by exertion (+1); pain feels like "pressure" (+1); pain reproducible by palpation (-1). CAD was considered absent if the prediction score is <2. The area under the ROC curve was 0.84. We applied this rule to a study setting with a CAD prevalence of 13.2% using a prediction score cutoff of <2 (i.e., -1, 0, or +1). When the score was <2, the probability of CAD was 2.1% (95% CI: 1.1-3.9%); when the score was ≥ 2, it was 43.0% (95% CI: 35.8-50.4%). Clinical prediction rules are a key strategy for individualizing care. Large data sets based on electronic health records from diverse sites create opportunities for improving their internal and external validity. Our patient-level meta-analysis from five primary care sites should improve external validity. Our strategy for addressing site-to-site systematic variation in missing data should improve internal validity. Using principles derived from decision theory, we also discuss the problem of setting the cutoff prediction score for taking action. Copyright © 2016 Elsevier Inc. All rights reserved.
Measuring the construct of executive control in schizophrenia: defining and validating translational animal paradigms for discovery research.

PubMed

Gilmour, Gary; Arguello, Alexander; Bari, Andrea; Brown, Verity J; Carter, Cameron; Floresco, Stan B; Jentsch, David J; Tait, David S; Young, Jared W; Robbins, Trevor W

2013-11-01

Executive control is an aspect of cognitive function known to be impaired in schizophrenia. Previous meetings of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) group have more precisely defined executive control in terms of two constructs: "rule generation and selection", and "dynamic adjustments of control". Next, human cognitive tasks that may effectively measure performance with regard to these constructs were identified to be developed into practical and reliable measures for use in treatment development. The aim of this round of CNTRICS meetings was to define animal paradigms that have sufficient promise to warrant further investigation for their utility in measuring these constructs. Accordingly, "reversal learning" and the "attentional set-shifting task" were nominated to assess the construct of rule generation and selection, and the "stop signal task" for the construct of dynamic adjustments of control. These tasks are described in more detail here, with a particular focus on their utility for drug discovery efforts. Presently, each assay has strengths and weaknesses with regard to this point and increased emphasis on improving practical aspects of testing, understanding predictive validity, and defining biomarkers of performance represent important objectives in attaining confidence in translational validity here. Crown Copyright © 2012. Published by Elsevier Ltd. All rights reserved.
Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data.

PubMed

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

2016-03-01

Estrogen receptors (ERα) are a critical target for drug design as well as a potential source of toxicity when activated unintentionally. Thus, evaluating potential ERα binding agents is critical in both drug discovery and chemical toxicity areas. Using computational tools, e.g., Quantitative Structure-Activity Relationship (QSAR) models, can predict potential ERα binding agents before chemical synthesis. The purpose of this project was to develop enhanced predictive models of ERα binding agents by utilizing advanced cheminformatics tools that can integrate publicly available bioassay data. The initial ERα binding agent data set, consisting of 446 binders and 8307 non-binders, was obtained from the Tox21 Challenge project organized by the NIH Chemical Genomics Center (NCGC). After removing the duplicates and inorganic compounds, this data set was used to create a training set (259 binders and 259 non-binders). This training set was used to develop QSAR models using chemical descriptors. The resulting models were then used to predict the binding activity of 264 external compounds, which were available to us after the models were developed. The cross-validation results of training set [Correct Classification Rate (CCR) = 0.72] were much higher than the external predictivity of the unknown compounds (CCR = 0.59). To improve the conventional QSAR models, all compounds in the training set were used to search PubChem and generate a profile of their biological responses across thousands of bioassays. The most important bioassays were prioritized to generate a similarity index that was used to calculate the biosimilarity score between each two compounds. The nearest neighbors for each compound within the set were then identified and its ERα binding potential was predicted by its nearest neighbors in the training set. The hybrid model performance (CCR = 0.94 for cross validation; CCR = 0.68 for external prediction) showed significant improvement over the original QSAR models, particularly for the activity cliffs that induce prediction errors. The results of this study indicate that the response profile of chemicals from public data provides useful information for modeling and evaluation purposes. The public big data resources should be considered along with chemical structure information when predicting new compounds, such as unknown ERα binding agents.
Implementation of a multi-variable regression analysis in the assessment of the generation rate and composition of hospital solid waste for the design of a sustainable management system in developing countries.

PubMed

Al-Khatib, Issam A; Abu Fkhidah, Ismail; Khatib, Jumana I; Kontogianni, Stamatia

2016-03-01

Forecasting of hospital solid waste generation is a critical challenge for future planning. The composition and generation rate of hospital solid waste in hospital units was the field where the proposed methodology of the present article was applied in order to validate the results and secure the outcomes of the management plan in national hospitals. A set of three multiple-variable regression models has been derived for estimating the daily total hospital waste, general hospital waste, and total hazardous waste as a function of number of inpatients, number of total patients, and number of beds. The application of several key indicators and validation procedures indicates the high significance and reliability of the developed models in predicting the hospital solid waste of any hospital. Methodology data were drawn from existent scientific literature. Also, useful raw data were retrieved from international organisations and the investigated hospitals' personnel. The primal generation outcomes are compared with other local hospitals and also with hospitals from other countries. The main outcome, which is the developed model results, are presented and analysed thoroughly. The goal is this model to act as leverage in the discussions among governmental authorities on the implementation of a national plan for safe hospital waste management in Palestine. © The Author(s) 2016.
Optimization of active distribution networks: Design and analysis of significative case studies for enabling control actions of real infrastructure

NASA Astrophysics Data System (ADS)

Moneta, Diana; Mora, Paolo; Viganò, Giacomo; Alimonti, Gianluca

2014-12-01

The diffusion of Distributed Generation (DG) based on Renewable Energy Sources (RES) requires new strategies to ensure reliable and economic operation of the distribution networks and to support the diffusion of DG itself. An advanced algorithm (DISCoVER - DIStribution Company VoltagE Regulator) is being developed to optimize the operation of active network by means of an advanced voltage control based on several regulations. Starting from forecasted load and generation, real on-field measurements, technical constraints and costs for each resource, the algorithm generates for each time period a set of commands for controllable resources that guarantees achievement of technical goals minimizing the overall cost. Before integrating the controller into the telecontrol system of the real networks, and in order to validate the proper behaviour of the algorithm and to identify possible critical conditions, a complete simulation phase has started. The first step is concerning the definition of a wide range of "case studies", that are the combination of network topology, technical constraints and targets, load and generation profiles and "costs" of resources that define a valid context to test the algorithm, with particular focus on battery and RES management. First results achieved from simulation activity on test networks (based on real MV grids) and actual battery characteristics are given, together with prospective performance on real case applications.
Generation of Ground Truth Datasets for the Analysis of 3d Point Clouds in Urban Scenes Acquired via Different Sensors

NASA Astrophysics Data System (ADS)

Xu, Y.; Sun, Z.; Boerner, R.; Koch, T.; Hoegner, L.; Stilla, U.

2018-04-01

In this work, we report a novel way of generating ground truth dataset for analyzing point cloud from different sensors and the validation of algorithms. Instead of directly labeling large amount of 3D points requiring time consuming manual work, a multi-resolution 3D voxel grid for the testing site is generated. Then, with the help of a set of basic labeled points from the reference dataset, we can generate a 3D labeled space of the entire testing site with different resolutions. Specifically, an octree-based voxel structure is applied to voxelize the annotated reference point cloud, by which all the points are organized by 3D grids of multi-resolutions. When automatically annotating the new testing point clouds, a voting based approach is adopted to the labeled points within multiple resolution voxels, in order to assign a semantic label to the 3D space represented by the voxel. Lastly, robust line- and plane-based fast registration methods are developed for aligning point clouds obtained via various sensors. Benefiting from the labeled 3D spatial information, we can easily create new annotated 3D point clouds of different sensors of the same scene directly by considering the corresponding labels of 3D space the points located, which would be convenient for the validation and evaluation of algorithms related to point cloud interpretation and semantic segmentation.
Nurse staffing levels and outcomes - mining the UK national data sets for insight.

PubMed

Leary, Alison; Tomai, Barbara; Swift, Adrian; Woodward, Andrew; Hurst, Keith

2017-04-18

Purpose Despite the generation of mass data by the nursing workforce, determining the impact of the contribution to patient safety remains challenging. Several cross-sectional studies have indicated a relationship between staffing and safety. The purpose of this paper is to uncover possible associations and explore if a deeper understanding of relationships between staffing and other factors such as safety could be revealed within routinely collected national data sets. Design/methodology/approach Two longitudinal routinely collected data sets consisting of 30 years of UK nurse staffing data and seven years of National Health Service (NHS) benchmark data such as survey results, safety and other indicators were used. A correlation matrix was built and a linear correlation operation was applied (Pearson product-moment correlation coefficient). Findings A number of associations were revealed within both the UK staffing data set and the NHS benchmarking data set. However, the challenges of using these data sets soon became apparent. Practical implications Staff time and effort are required to collect these data. The limitations of these data sets include inconsistent data collection and quality. The mode of data collection and the itemset collected should be reviewed to generate a data set with robust clinical application. Originality/value This paper revealed that relationships are likely to be complex and non-linear; however, the main contribution of the paper is the identification of the limitations of routinely collected data. Much time and effort is expended in collecting this data; however, its validity, usefulness and method of routine national data collection appear to require re-examination.

Assessing validity by comparing transition and static measures of dyspnea in patients with acute decompensated heart failure.

PubMed

Smithline, Howard A; Caglar, Selin; Blank, Fidela S J

2010-01-01

This study assessed the convergent validity of 2 dyspnea measures, the transition measure and the change measure, by comparing them with each other in patients admitted to the hospital with acute decompensated heart failure. Static measures of dyspnea were obtained at baseline (pre-static measure) and at time 1 hour and 4 hour (post-static measures). The change measure was calculated as the difference between the pre-static and post-static measures. Transition measures were obtained at time 1 hour and 4 hour. Visual analog scales and Likert scales were used. Both physicians and patients measured the dyspnea independently. A total of 112 patients had complete data sets at time 0 and 1 hour and 86 patients had complete data sets at all 3 time points. Correlations were calculated between the transition measures and static measures (pre-static, post-static, and change measure). Bland-Altman plots were generated and the mean difference and limits of agreement between the transition measures and the change measures were calculated. In general, short-term dyspnea assessment using transition measures and serial static measures can not be used to validate each other in this population of patients being admitted with acute decompensated heart failure. © 2010 Wiley Periodicals, Inc.
Implications of "Too Good to Be True" for Replication, Theoretical Claims, and Experimental Design: An Example Using Prominent Studies of Racial Bias.

PubMed

Francis, Gregory

2016-01-01

In response to concerns about the validity of empirical findings in psychology, some scientists use replication studies as a way to validate good science and to identify poor science. Such efforts are resource intensive and are sometimes controversial (with accusations of researcher incompetence) when a replication fails to show a previous result. An alternative approach is to examine the statistical properties of the reported literature to identify some cases of poor science. This review discusses some details of this process for prominent findings about racial bias, where a set of studies seems "too good to be true." This kind of analysis is based on the original studies, so it avoids criticism from the original authors about the validity of replication studies. The analysis is also much easier to perform than a new empirical study. A variation of the analysis can also be used to explore whether it makes sense to run a replication study. As demonstrated here, there are situations where the existing data suggest that a direct replication of a set of studies is not worth the effort. Such a conclusion should motivate scientists to generate alternative experimental designs that better test theoretical ideas.
Implications of “Too Good to Be True” for Replication, Theoretical Claims, and Experimental Design: An Example Using Prominent Studies of Racial Bias

PubMed Central

Francis, Gregory

2016-01-01

In response to concerns about the validity of empirical findings in psychology, some scientists use replication studies as a way to validate good science and to identify poor science. Such efforts are resource intensive and are sometimes controversial (with accusations of researcher incompetence) when a replication fails to show a previous result. An alternative approach is to examine the statistical properties of the reported literature to identify some cases of poor science. This review discusses some details of this process for prominent findings about racial bias, where a set of studies seems “too good to be true.” This kind of analysis is based on the original studies, so it avoids criticism from the original authors about the validity of replication studies. The analysis is also much easier to perform than a new empirical study. A variation of the analysis can also be used to explore whether it makes sense to run a replication study. As demonstrated here, there are situations where the existing data suggest that a direct replication of a set of studies is not worth the effort. Such a conclusion should motivate scientists to generate alternative experimental designs that better test theoretical ideas. PMID:27713708
Validation of the MCNP6 electron-photon transport algorithm: multiple-scattering of 13- and 20-MeV electrons in thin foils

NASA Astrophysics Data System (ADS)

Dixon, David A.; Hughes, H. Grady

2017-09-01

This paper presents a validation test comparing angular distributions from an electron multiple-scattering experiment with those generated using the MCNP6 Monte Carlo code system. In this experiment, a 13- and 20-MeV electron pencil beam is deflected by thin foils with atomic numbers from 4 to 79. To determine the angular distribution, the fluence is measured down range of the scattering foil at various radii orthogonal to the beam line. The characteristic angle (the angle for which the max of the distribution is reduced by 1/e) is then determined from the angular distribution and compared with experiment. Multiple scattering foils tested herein include beryllium, carbon, aluminum, copper, and gold. For the default electron-photon transport settings, the calculated characteristic angle was statistically distinguishable from measurement and generally broader than the measured distributions. The average relative difference ranged from 5.8% to 12.2% over all of the foils, source energies, and physics settings tested. This validation illuminated a deficiency in the computation of the underlying angular distributions that is well understood. As a result, code enhancements were made to stabilize the angular distributions in the presence of very small substeps. However, the enhancement only marginally improved results indicating that additional algorithmic details should be studied.
Validation of a social vulnerability index in context to river-floods in Germany

NASA Astrophysics Data System (ADS)

Fekete, A.

2009-03-01

Social vulnerability indices are a means for generating information about people potentially affected by disasters that are e.g. triggered by river-floods. The purpose behind such an index is in this study the development and the validation of a social vulnerability map of population characteristics towards river-floods covering all counties in Germany. This map is based on a composite index of three main indicators for social vulnerability in Germany - fragility, socio-economic conditions and region. These indicators have been identified by a factor analysis of selected demographic variables obtained from federal statistical offices. Therefore, these indicators can be updated annually based on a reliable data source. The vulnerability patterns detected by the factor analysis are verified by using an independent second data set. The interpretation of the second data set shows that vulnerability is revealed by a real extreme flood event and demonstrates that the patterns of the presumed vulnerability match the observations of a real event. It comprises a survey of flood-affected households in three federal states. By using logistic regression, it is demonstrated that the theoretically presumed indications of vulnerability are correct and that the indicators are valid. It is shown that indeed certain social groups like the elderly, the financially weak or the urban residents are higher risk groups.
Validation of geometric accuracy of Global Land Survey (GLS) 2000 data

USGS Publications Warehouse

Rengarajan, Rajagopalan; Sampath, Aparajithan; Storey, James C.; Choate, Michael J.

2015-01-01

The Global Land Survey (GLS) 2000 data were generated from Geocover™ 2000 data with the aim of producing a global data set of accuracy better than 25 m Root Mean Square Error (RMSE). An assessment and validation of accuracy of GLS 2000 data set, and its co-registration with Geocover™ 2000 data set is presented here. Since the availability of global data sets that have higher nominal accuracy than the GLS 2000 is a concern, the data sets were assessed in three tiers. In the first tier, the data were compared with the Geocover™ 2000 data. This comparison provided a means of localizing regions of higher differences. In the second tier, the GLS 2000 data were compared with systematically corrected Landsat-7 scenes that were obtained in a time period when the spacecraft pointing information was extremely accurate. These comparisons localize regions where the data are consistently off, which may indicate regions of higher errors. The third tier consisted of comparing the GLS 2000 data against higher accuracy reference data. The reference data were the Digital Ortho Quads over the United States, orthorectified SPOT data over Australia, and high accuracy check points obtained using triangulation bundle adjustment of Landsat-7 images over selected sites around the world. The study reveals that the geometric errors in Geocover™ 2000 data have been rectified in GLS 2000 data, and that the accuracy of GLS 2000 data can be expected to be better than 25 m RMSE for most of its constituent scenes.
Flow Simulation of N3-X Hybrid Wing-Body Configuration

NASA Technical Reports Server (NTRS)

Kim, Hyoungjin; Liou, Meng-Sing

2013-01-01

System studies show that a N3-X hybrid wing-body aircraft with a turboelectric distributed propulsion system using a mail-slot inlet/nozzle nacelle can meet the environmental and performance goals for N+3 generation transports (three generations beyond the current air transport technology level) set by NASA s Subsonic Fixed Wing Project. In this study, a Navier-Stokes flow simulation of N3-X on hybrid unstructured meshes was conducted, including the mail-slot propulsor. The geometry of the mail-slot propulsor was generated by a CAD (Computer-Aided Design)-free shape parameterization. A body force approach was used for a more realistic and efficient simulation of the turning and loss effects of the fan blades and the inlet-fan interactions. Flow simulation results of the N3-X demonstrates the validity of the present approach.
GRRATS: A New Approach to Inland Altimetry Processing for Major World Rivers

NASA Astrophysics Data System (ADS)

Coss, S. P.

2016-12-01

Here we present work-in-progress results aimed at generating a new radar altimetry dataset GRRATS (Global River Radar Altimetry Time Series) extracted over global ocean-draining rivers wider than 900 m. GRATTS was developed as a component of the NASA MEaSUREs project (PI: Dennis Lettenmaier, UCLA) to generate pre-SWOT data products for decadal or longer global river elevation changes from multi-mission satellite radar altimetry data. The dataset at present includes 909 time series from 39 rivers. A new method of filtering VS (virtual station) height time series is presented where, DEM based heights were used to establish limits for the ice1 retracked Jason2 and Envisat heights at present. While GRRATS is following in the footsteps of several predecessors, it contributes to one of the critical climate data records in generating a validated and comprehensive hydrologic observations in river height. The current data product includes VSs in north and south Americas, Africa and Eurasia, with the most comprehensive set of Jason-2 and Envisat RA time series available for North America and Eurasia. We present a semi-automated procedure to process returns from river locations, identified with Landsat images and updated water mask extent. Consistent methodologies for flagging ice cover are presented. DEM heights used in height filtering were retained and can be used as river height profiles. All non-validated VS have been assigned a letter grade A-D to aid end users in selection of data. Validated VS are accompanied with a suite of fit statistics. Due to the inclusiveness of the dataset, not all VS were able to undergo validation (415 of 909), but those that were demonstrate that confidence in the data product is warranted. Validation was accomplished using records from 45 in situ gauges from 12 rivers. Meta-analysis was performed to compare each gauge with each VS by relative height. Preliminary validation results are as follows. 89.3% of the data have positive Nash Sutcliff Efficiency (NES) values, and the median NSE value is 0.73. The median standard deviation of error (STDE) is .92 m. GRRATS will soon be publicly available in NetCDF format with CF compliant metadata.
Coverability graphs for a class of synchronously executed unbounded Petri net

NASA Technical Reports Server (NTRS)

Stotts, P. David; Pratt, Terrence W.

1990-01-01

After detailing a variant of the concurrent-execution rule for firing of maximal subsets, in which the simultaneous firing of conflicting transitions is prohibited, an algorithm is constructed for generating the coverability graph of a net executed under this synchronous firing rule. The omega insertion criteria in the algorithm are shown to be valid for any net on which the algorithm terminates. It is accordingly shown that the set of nets on which the algorithm terminates includes the 'conflict-free' class.
Analysis of NASA Common Research Model Dynamic Data

NASA Technical Reports Server (NTRS)

Balakrishna, S.; Acheson, Michael J.

2011-01-01

Recent NASA Common Research Model (CRM) tests at the Langley National Transonic Facility (NTF) and Ames 11-foot Transonic Wind Tunnel (11-foot TWT) have generated an experimental database for CFD code validation. The database consists of force and moment, surface pressures and wideband wing-root dynamic strain/wing Kulite data from continuous sweep pitch polars. The dynamic data sets, acquired at 12,800 Hz sampling rate, are analyzed in this study to evaluate CRM wing buffet onset and potential CRM wing flow separation.
Wideband THz Time Domain Spectroscopy based on Optical Rectification and Electro-Optic Sampling

PubMed Central

Tomasino, A.; Parisi, A.; Stivala, S.; Livreri, P.; Cino, A. C.; Busacca, A. C.; Peccianti, M.; Morandotti, R.

2013-01-01

We present an analytical model describing the full electromagnetic propagation in a THz time-domain spectroscopy (THz-TDS) system, from the THz pulses via Optical Rectification to the detection via Electro Optic-Sampling. While several investigations deal singularly with the many elements that constitute a THz-TDS, in our work we pay particular attention to the modelling of the time-frequency behaviour of all the stages which compose the experimental set-up. Therefore, our model considers the following main aspects: (i) pump beam focusing into the generation crystal; (ii) phase-matching inside both the generation and detection crystals; (iii) chromatic dispersion and absorption inside the crystals; (iv) Fabry-Perot effect; (v) diffraction outside, i.e. along the propagation, (vi) focalization and overlapping between THz and probe beams, (vii) electro-optic sampling. In order to validate our model, we report on the comparison between the simulations and the experimental data obtained from the same set-up, showing their good agreement. PMID:24173583
A stochastic evolutionary model generating a mixture of exponential distributions

NASA Astrophysics Data System (ADS)

Fenner, Trevor; Levene, Mark; Loizou, George

2016-02-01

Recent interest in human dynamics has stimulated the investigation of the stochastic processes that explain human behaviour in various contexts, such as mobile phone networks and social media. In this paper, we extend the stochastic urn-based model proposed in [T. Fenner, M. Levene, G. Loizou, J. Stat. Mech. 2015, P08015 (2015)] so that it can generate mixture models, in particular, a mixture of exponential distributions. The model is designed to capture the dynamics of survival analysis, traditionally employed in clinical trials, reliability analysis in engineering, and more recently in the analysis of large data sets recording human dynamics. The mixture modelling approach, which is relatively simple and well understood, is very effective in capturing heterogeneity in data. We provide empirical evidence for the validity of the model, using a data set of popular search engine queries collected over a period of 114 months. We show that the survival function of these queries is closely matched by the exponential mixture solution for our model.
Natural product-like virtual libraries: recursive atom-based enumeration.

PubMed

Yu, Melvin J

2011-03-28

A new molecular enumerator is described that allows chemically and architecturally diverse sets of natural product-like and drug-like structures to be generated from a core structure as simple as a single carbon atom or as complex as a polycyclic ring system. Integrated with a rudimentary machine-learning algorithm, the enumerator has the ability to assemble biased virtual libraries enriched in compounds predicted to meet target criteria. The ability to dynamically generate relatively small focused libraries in a recursive manner could reduce the computational time and infrastructure necessary to construct and manage extremely large static libraries. Depending on enumeration conditions, natural product-like structures can be produced with a wide range of heterocyclic and alicyclic ring assemblies. Because natural products represent a proven source of validated structures for identifying and designing new drug candidates, mimicking the structural and topological diversity found in nature with a dynamic set of virtual natural product-like compounds may facilitate the creation of new ideas for novel, biologically relevant lead structures in areas of uncharted chemical space.
Identification and Validation of Reference Genes and Their Impact on Normalized Gene Expression Studies across Cultivated and Wild Cicer Species

PubMed Central

Reddy, Palakolanu Sudhakar; Sri Cindhuri, Katamreddy; Sivaji Ganesh, Adusumalli; Sharma, Kiran Kumar

2016-01-01

Quantitative Real-Time PCR (qPCR) is a preferred and reliable method for accurate quantification of gene expression to understand precise gene functions. A total of 25 candidate reference genes including traditional and new generation reference genes were selected and evaluated in a diverse set of chickpea samples. The samples used in this study included nine chickpea genotypes (Cicer spp.) comprising of cultivated and wild species, six abiotic stress treatments (drought, salinity, high vapor pressure deficit, abscisic acid, cold and heat shock), and five diverse tissues (leaf, root, flower, seedlings and seed). The geNorm, NormFinder and RefFinder algorithms used to identify stably expressed genes in four sample sets revealed stable expression of UCP and G6PD genes across genotypes, while TIP41 and CAC were highly stable under abiotic stress conditions. While PP2A and ABCT genes were ranked as best for different tissues, ABCT, UCP and CAC were most stable across all samples. This study demonstrated the usefulness of new generation reference genes for more accurate qPCR based gene expression quantification in cultivated as well as wild chickpea species. Validation of the best reference genes was carried out by studying their impact on normalization of aquaporin genes PIP1;4 and TIP3;1, in three contrasting chickpea genotypes under high vapor pressure deficit (VPD) treatment. The chickpea TIP3;1 gene got significantly up regulated under high VPD conditions with higher relative expression in the drought susceptible genotype, confirming the suitability of the selected reference genes for expression analysis. This is the first comprehensive study on the stability of the new generation reference genes for qPCR studies in chickpea across species, different tissues and abiotic stresses. PMID:26863232
Identification and Validation of Reference Genes and Their Impact on Normalized Gene Expression Studies across Cultivated and Wild Cicer Species.

PubMed

Reddy, Dumbala Srinivas; Bhatnagar-Mathur, Pooja; Reddy, Palakolanu Sudhakar; Sri Cindhuri, Katamreddy; Sivaji Ganesh, Adusumalli; Sharma, Kiran Kumar

2016-01-01

Quantitative Real-Time PCR (qPCR) is a preferred and reliable method for accurate quantification of gene expression to understand precise gene functions. A total of 25 candidate reference genes including traditional and new generation reference genes were selected and evaluated in a diverse set of chickpea samples. The samples used in this study included nine chickpea genotypes (Cicer spp.) comprising of cultivated and wild species, six abiotic stress treatments (drought, salinity, high vapor pressure deficit, abscisic acid, cold and heat shock), and five diverse tissues (leaf, root, flower, seedlings and seed). The geNorm, NormFinder and RefFinder algorithms used to identify stably expressed genes in four sample sets revealed stable expression of UCP and G6PD genes across genotypes, while TIP41 and CAC were highly stable under abiotic stress conditions. While PP2A and ABCT genes were ranked as best for different tissues, ABCT, UCP and CAC were most stable across all samples. This study demonstrated the usefulness of new generation reference genes for more accurate qPCR based gene expression quantification in cultivated as well as wild chickpea species. Validation of the best reference genes was carried out by studying their impact on normalization of aquaporin genes PIP1;4 and TIP3;1, in three contrasting chickpea genotypes under high vapor pressure deficit (VPD) treatment. The chickpea TIP3;1 gene got significantly up regulated under high VPD conditions with higher relative expression in the drought susceptible genotype, confirming the suitability of the selected reference genes for expression analysis. This is the first comprehensive study on the stability of the new generation reference genes for qPCR studies in chickpea across species, different tissues and abiotic stresses.
4D Cone-beam CT reconstruction using a motion model based on principal component analysis

PubMed Central

Staub, David; Docef, Alen; Brock, Robert S.; Vaman, Constantin; Murphy, Martin J.

2011-01-01

Purpose: To provide a proof of concept validation of a novel 4D cone-beam CT (4DCBCT) reconstruction algorithm and to determine the best methods to train and optimize the algorithm. Methods: The algorithm animates a patient fan-beam CT (FBCT) with a patient specific parametric motion model in order to generate a time series of deformed CTs (the reconstructed 4DCBCT) that track the motion of the patient anatomy on a voxel by voxel scale. The motion model is constrained by requiring that projections cast through the deformed CT time series match the projections of the raw patient 4DCBCT. The motion model uses a basis of eigenvectors that are generated via principal component analysis (PCA) of a training set of displacement vector fields (DVFs) that approximate patient motion. The eigenvectors are weighted by a parameterized function of the patient breathing trace recorded during 4DCBCT. The algorithm is demonstrated and tested via numerical simulation. Results: The algorithm is shown to produce accurate reconstruction results for the most complicated simulated motion, in which voxels move with a pseudo-periodic pattern and relative phase shifts exist between voxels. The tests show that principal component eigenvectors trained on DVFs from a novel 2D/3D registration method give substantially better results than eigenvectors trained on DVFs obtained by conventionally registering 4DCBCT phases reconstructed via filtered backprojection. Conclusions: Proof of concept testing has validated the 4DCBCT reconstruction approach for the types of simulated data considered. In addition, the authors found the 2D/3D registration approach to be our best choice for generating the DVF training set, and the Nelder-Mead simplex algorithm the most robust optimization routine. PMID:22149852
Construction and Validation of the Rhodobacter sphaeroides 2.4.1 DNA Microarray: Transcriptome Flexibility at Diverse Growth Modes

PubMed Central

Pappas, Christopher T.; Sram, Jakub; Moskvin, Oleg V.; Ivanov, Pavel S.; Mackenzie, R. Christopher; Choudhary, Madhusudan; Land, Miriam L.; Larimer, Frank W.; Kaplan, Samuel; Gomelsky, Mark

2004-01-01

A high-density oligonucleotide DNA microarray, a genechip, representing the 4.6-Mb genome of the facultative phototrophic proteobacterium, Rhodobacter sphaeroides 2.4.1, was custom-designed and manufactured by Affymetrix, Santa Clara, Calif. The genechip contains probe sets for 4,292 open reading frames (ORFs), 47 rRNA and tRNA genes, and 394 intergenic regions. The probe set sequences were derived from the genome annotation generated by Oak Ridge National Laboratory after extensive revision, which was based primarily upon codon usage characteristic of this GC-rich bacterium. As a result of the revision, numerous missing ORFs were uncovered, nonexistent ORFs were deleted, and misidentified start codons were corrected. To evaluate R. sphaeroides transcriptome flexibility, expression profiles for three diverse growth modes—aerobic respiration, anaerobic respiration in the dark, and anaerobic photosynthesis—were generated. Expression levels of one-fifth to one-third of the R. sphaeroides ORFs were significantly different in cells under any two growth modes. Pathways involved in energy generation and redox balance maintenance under three growth modes were reconstructed. Expression patterns of genes involved in these pathways mirrored known functional changes, suggesting that massive changes in gene expression are the major means used by R. sphaeroides in adaptation to diverse conditions. Differential expression was observed for genes encoding putative new participants in these pathways (additional photosystem genes, duplicate NADH dehydrogenase, ATP synthases), whose functionality has yet to be investigated. The DNA microarray data correlated well with data derived from quantitative reverse transcription-PCR, as well as with data from the literature, thus validating the R. sphaeroides genechip as a powerful and reliable tool for studying unprecedented metabolic versatility of this bacterium. PMID:15231807
Ice_Sheets_CCI: Essential Climate Variables for the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Forsberg, R.; Sørensen, L. S.; Khan, A.; Aas, C.; Evansberget, D.; Adalsteinsdottir, G.; Mottram, R.; Andersen, S. B.; Ahlstrøm, A.; Dall, J.; Kusk, A.; Merryman, J.; Hvidberg, C.; Khvorostovsky, K.; Nagler, T.; Rott, H.; Scharrer, M.; Shepard, A.; Ticconi, F.; Engdahl, M.

2012-04-01

As part of the ESA Climate Change Initiative (www.esa-cci.org) a long-term project "ice_sheets_cci" started January 1, 2012, in addition to the existing 11 projects already generating Essential Climate Variables (ECV) for the Global Climate Observing System (GCOS). The "ice_sheets_cci" goal is to generate a consistent, long-term and timely set of key climate parameters for the Greenland ice sheet, to maximize the impact of European satellite data on climate research, from missions such as ERS, Envisat and the future Sentinel satellites. The climate parameters to be provided, at first in a research context, and in the longer perspective by a routine production system, would be grids of Greenland ice sheet elevation changes from radar altimetry, ice velocity from repeat-pass SAR data, as well as time series of marine-terminating glacier calving front locations and grounding lines for floating-front glaciers. The ice_sheets_cci project will involve a broad interaction of the relevant cryosphere and climate communities, first through user consultations and specifications, and later in 2012 optional participation in "best" algorithm selection activities, where prototype climate parameter variables for selected regions and time frames will be produced and validated using an objective set of criteria ("Round-Robin intercomparison"). This comparative algorithm selection activity will be completely open, and we invite all interested scientific groups with relevant experience to participate. The results of the "Round Robin" exercise will form the algorithmic basis for the future ECV production system. First prototype results will be generated and validated by early 2014. The poster will show the planned outline of the project and some early prototype results.
Assessing the accuracy and stability of variable selection ...

EPA Pesticide Factsheets

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological datasets there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used, or stepwise procedures are employed which iteratively add/remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating dataset consists of the good/poor condition of n=1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p=212) of landscape features from the StreamCat dataset. Two types of RF models are compared: a full variable set model with all 212 predictors, and a reduced variable set model selected using a backwards elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors, and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substanti
The measurement of collaboration within healthcare settings: a systematic review of measurement properties of instruments.

PubMed

Walters, Stephen John; Stern, Cindy; Robertson-Malt, Suzanne

2016-04-01

There is a growing call by consumers and governments for healthcare to adopt systems and approaches to care to improve patient safety. Collaboration within healthcare settings is an important factor for improving systems of care. By using validated measurement instruments a standardized approach to assessing collaboration is possible, otherwise it is only an assumption that collaboration is occurring in any healthcare setting. The objective of this review was to evaluate and compare measurement properties of instruments that measure collaboration within healthcare settings, specifically those which have been psychometrically tested and validated. Participants could be healthcare professionals, the patient or any non-professional who contributes to a patient's care, for example, family members, chaplains or orderlies. The term participant type means the designation of any one participant; for example 'nurse', 'social worker' or 'administrator'. More than two participant types was mandatory. The focus of this review was the validity of tools used to measure collaboration within healthcare settings. The types of studies considered for inclusion were validation studies, but quantitative study designs such as randomized controlled trials, controlled trials and case studies were also eligible for inclusion. Studies that focused on Interprofessional Education, were published as an abstract only, contained patient self-reporting only or were not about care delivery were excluded. The outcome of interest was validation and interpretability of the instrument being assessed and included content validity, construct validity and reliability. Interpretability is characterized by statistics such as mean and standard deviation which can be translated to a qualitative meaning. The search strategy aimed to find both published and unpublished studies. A three-step search strategy was utilized in this review. The databases searched included PubMed, CINAHL, Embase, Cochrane Central Register of Controlled Trials, Emerald Fulltext, MD Consult Australia, PsycARTICLES, Psychology and Behavioural Sciences Collection, PsycINFO, Informit Health Databases, Scopus, UpToDate and Web of Science. The search for unpublished studies included EThOS (Electronic Thesis Online Service), Index to Theses and ProQuest- Dissertations and Theses. The assessment of methodological quality of the included studies was undertaken using the COSMIN checklist which is a validated tool that assesses the process of design and validation of healthcare measurement instruments. An Excel spreadsheet version of COSMIN was developed for data collection which included a worksheet for extracting participant characteristics and interpretability data. Statistical pooling of data was not possible for this review. Therefore, the findings are presented in a narrative form including tables and figures to aid in data presentation. To make a synthesis of the assessments of methodological quality of the different studies, each instrument was rated by accounting for the number of studies performed with an instrument, the appraisal of methodological quality and the consistency of results between studies. Twenty-one studies of 12 instruments were included in the review. The studies were diverse in their theoretical underpinnings, target population/setting and measurement objectives. Measurement objectives included: investigating beliefs, behaviors, attitudes, perceptions and relationships associated with collaboration; measuring collaboration between different levels of care or within a multi-rater/target group; assessing collaboration across teams; or assessing internal participation of both teams and patients.Studies produced validity or interpretability data but none of the studies assessed all validity and reliability properties. However, most of the included studies produced a factor structure or referred to prior factor analysis. A narrative synthesis of the individual study factor structures was generated consisting of nine headings: organizational settings, support structures, purpose and goals; communication; reflection on process; cooperation; coordination; role interdependence and partnership; relationships; newly created professional activities; and professional flexibility. Among the many instruments that measure collaboration within healthcare settings, the quality of each instrument varies; instruments are designed for specific populations and purposes, and are validated in various settings. Selecting an instrument requires careful consideration of the qualities of each. Therefore, referring to systematic reviews of measurement properties of instruments may be helpful to clinicians or researchers in instrument selection. Systematic reviews of measurement properties of instruments are valuable in aiding in instrument selection. This systematic review may be useful in instrument selection for the measurement of collaboration within healthcare settings with a complex mix of participant types. Evaluating collaboration provides important information on the strengths and limitations of different healthcare settings and the opportunities for continuous improvement via any remedial actions initiated. Development of a tool that can be used to measure collaboration within teams of healthcare professionals and non-professionals is important for practice. The use of different statistical modelling techniques, such as Item Response Theory modelling and the translation of models into Computer Adaptive Tests, may prove useful. Measurement equivalence is an important consideration for future instrument development and validation. Further development of the COSMIN tool should include appraisal for measurement equivalence. Researchers developing and validating measurement tools should consider multi-method research designs.

Effect of incubation temperature and time on the precision of data generated by antibiotic disc diffusion assays.

PubMed

Smith, P; Kronvall, G

2015-07-01

The influence on the precision of disc diffusion data of the conditions under which the tests were performed was examined by analysing multilaboratory data sets generated after incubation at 35 °C for 18 h, at 28 °C for 24 h and 22 °C for 24 h and 48 h. Analyses of these data sets demonstrated that precision was significantly and progressively decreased as the test temperature was reduced from 35 to 22 °C. Analysis of the data obtained at 22 °C also showed the precision was inversely related to the time of incubation. Temperature and time related decreases in precision were not related to differences in the mean zone sizes of the data sets obtained under these test conditions. Analysis of the zone data obtained at 28 and 22 °C as single laboratory sets demonstrated that reductions of incubation temperature resulted in significant increases in both intralaboratory and interlaboratory variation. Increases in incubation time at 22 °C were, however, associated with statistically significant increases in interlaboratory variation but not with any significant increase in intralaboratory variation. The significance of these observations for the establishment of the acceptable limits of precision of data sets that can be used for the setting of valid epidemiological cut-off values is discussed. © 2014 John Wiley & Sons Ltd.
Calculation of Coupled Vibroacoustics Response Estimates from a Library of Available Uncoupled Transfer Function Sets

NASA Technical Reports Server (NTRS)

Smith, Andrew; LaVerde, Bruce; Hunt, Ron; Fulcher, Clay; Towner, Robert; McDonald, Emmett

2012-01-01

The design and theoretical basis of a new database tool that quickly generates vibroacoustic response estimates using a library of transfer functions (TFs) is discussed. During the early stages of a launch vehicle development program, these response estimates can be used to provide vibration environment specification to hardware vendors. The tool accesses TFs from a database, combines the TFs, and multiplies these by input excitations to estimate vibration responses. The database is populated with two sets of uncoupled TFs; the first set representing vibration response of a bare panel, designated as H(sup s), and the second set representing the response of the free-free component equipment by itself, designated as H(sup c). For a particular configuration undergoing analysis, the appropriate H(sup s) and H(sup c) are selected and coupled to generate an integrated TF, designated as H(sup s +c). This integrated TF is then used with the appropriate input excitations to estimate vibration responses. This simple yet powerful tool enables a user to estimate vibration responses without directly using finite element models, so long as suitable H(sup s) and H(sup c) sets are defined in the database libraries. The paper discusses the preparation of the database tool and provides the assumptions and methodologies necessary to combine H(sup s) and H(sup c) sets into an integrated H(sup s + c). An experimental validation of the approach is also presented.
SU-E-J-92: Validating Dose Uncertainty Estimates Produced by AUTODIRECT, An Automated Program to Evaluate Deformable Image Registration Accuracy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, H; Chen, J; Pouliot, J

2015-06-15

Purpose: Deformable image registration (DIR) is a powerful tool with the potential to deformably map dose from one computed-tomography (CT) image to another. Errors in the DIR, however, will produce errors in the transferred dose distribution. We have proposed a software tool, called AUTODIRECT (automated DIR evaluation of confidence tool), which predicts voxel-specific dose mapping errors on a patient-by-patient basis. This work validates the effectiveness of AUTODIRECT to predict dose mapping errors with virtual and physical phantom datasets. Methods: AUTODIRECT requires 4 inputs: moving and fixed CT images and two noise scans of a water phantom (for noise characterization). Then,more » AUTODIRECT uses algorithms to generate test deformations and applies them to the moving and fixed images (along with processing) to digitally create sets of test images, with known ground-truth deformations that are similar to the actual one. The clinical DIR algorithm is then applied to these test image sets (currently 4) . From these tests, AUTODIRECT generates spatial and dose uncertainty estimates for each image voxel based on a Student’s t distribution. This work compares these uncertainty estimates to the actual errors made by the Velocity Deformable Multi Pass algorithm on 11 virtual and 1 physical phantom datasets. Results: For 11 of the 12 tests, the predicted dose error distributions from AUTODIRECT are well matched to the actual error distributions within 1–6% for 10 virtual phantoms, and 9% for the physical phantom. For one of the cases though, the predictions underestimated the errors in the tail of the distribution. Conclusion: Overall, the AUTODIRECT algorithm performed well on the 12 phantom cases for Velocity and was shown to generate accurate estimates of dose warping uncertainty. AUTODIRECT is able to automatically generate patient-, organ- , and voxel-specific DIR uncertainty estimates. This ability would be useful for patient-specific DIR quality assurance.« less
Validation of the Minority Stress Scale Among Italian Gay and Bisexual Men.

PubMed

Pala, Andrea Norcini; Dell'Amore, Francesca; Steca, Patrizia; Clinton, Lauren; Sandfort, Theodorus; Rael, Christine

2017-12-01

The experience of sexual orientation stigma (e.g., homophobic discrimination and physical aggression) generates minority stress, a chronic form of psychosocial stress. Minority stress has been shown to have a negative effect on gay and bisexual men's (GBM's) mental and physical health, increasing the rates of depression, suicidal ideation, and HIV risk behaviors. In conservative religious settings, such as Italy, sexual orientation stigma can be more frequently and/or more intensively experienced. However, minority stress among Italian GBM remains understudied. The aim of this study was to explore the dimensionality, internal reliability, and convergent validity of the Minority Stress Scale (MSS), a comprehensive instrument designed to assess the manifestations of sexual orientation stigma. The MSS consists of 50 items assessing (a) Structural Stigma, (b) Enacted Stigma, (c) Expectations of Discrimination, (d) Sexual Orientation Concealment, (e) Internalized Homophobia Toward Others, (f) Internalized Homophobia toward Oneself, and (g) Stigma Awareness. We recruited an online sample of 451 Italian GBM to take the MSS. We tested convergent validity using the Perceived Stress Questionnaire. Through exploratory factor analysis, we extracted the 7 theoretical factors and an additional 3-item factor assessing Expectations of Discrimination From Family Members. The MSS factors showed good internal reliability (ordinal α > .81) and good convergent validity. Our scale can be suitable for applications in research settings, psychosocial interventions, and, potentially, in clinical practice. Future studies will be conducted to further investigate the properties of the MSS, exploring the association with additional health-related measures (e.g., depressive symptoms and anxiety).
Analysis of the French insurance market exposure to floods: a stochastic model combining river overflow and surface runoff

NASA Astrophysics Data System (ADS)

Moncoulon, D.; Labat, D.; Ardon, J.; Leblois, E.; Onfroy, T.; Poulard, C.; Aji, S.; Rémy, A.; Quantin, A.

2014-09-01

The analysis of flood exposure at a national scale for the French insurance market must combine the generation of a probabilistic event set of all possible (but which have not yet occurred) flood situations with hazard and damage modeling. In this study, hazard and damage models are calibrated on a 1995-2010 historical event set, both for hazard results (river flow, flooded areas) and loss estimations. Thus, uncertainties in the deterministic estimation of a single event loss are known before simulating a probabilistic event set. To take into account at least 90 % of the insured flood losses, the probabilistic event set must combine the river overflow (small and large catchments) with the surface runoff, due to heavy rainfall, on the slopes of the watershed. Indeed, internal studies of the CCR (Caisse Centrale de Reassurance) claim database have shown that approximately 45 % of the insured flood losses are located inside the floodplains and 45 % outside. Another 10 % is due to sea surge floods and groundwater rise. In this approach, two independent probabilistic methods are combined to create a single flood loss distribution: a generation of fictive river flows based on the historical records of the river gauge network and a generation of fictive rain fields on small catchments, calibrated on the 1958-2010 Météo-France rain database SAFRAN. All the events in the probabilistic event sets are simulated with the deterministic model. This hazard and damage distribution is used to simulate the flood losses at the national scale for an insurance company (Macif) and to generate flood areas associated with hazard return periods. The flood maps concern river overflow and surface water runoff. Validation of these maps is conducted by comparison with the address located claim data on a small catchment (downstream Argens).
Multiple Versus Single Set Validation of Multivariate Models to Avoid Mistakes.

PubMed

Harrington, Peter de Boves

2018-01-02

Validation of multivariate models is of current importance for a wide range of chemical applications. Although important, it is neglected. The common practice is to use a single external validation set for evaluation. This approach is deficient and may mislead investigators with results that are specific to the single validation set of data. In addition, no statistics are available regarding the precision of a derived figure of merit (FOM). A statistical approach using bootstrapped Latin partitions is advocated. This validation method makes an efficient use of the data because each object is used once for validation. It was reviewed a decade earlier but primarily for the optimization of chemometric models this review presents the reasons it should be used for generalized statistical validation. Average FOMs with confidence intervals are reported and powerful, matched-sample statistics may be applied for comparing models and methods. Examples demonstrate the problems with single validation sets.
Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

NASA Astrophysics Data System (ADS)

Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok

2016-05-01

This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.
Lignocellulosic sugar management for xylitol and ethanol fermentation with multiple cell recycling by Kluyveromyces marxianus IIPE453.

PubMed

Dasgupta, Diptarka; Ghosh, Debashish; Bandhu, Sheetal; Adhikari, Dilip K

2017-07-01

Optimum utilization of fermentable sugars from lignocellulosic biomass to deliver multiple products under biorefinery concept has been reported in this work. Alcohol fermentation has been carried out with multiple cell recycling of Kluyveromyces marxianus IIPE453. The yeast utilized xylose-rich fraction from acid and steam treated biomass for cell generation and xylitol production with an average yield of 0.315±0.01g/g while the entire glucose rich saccharified fraction had been fermented to ethanol with high productivity of 0.9±0.08g/L/h. A detailed insight into its genome illustrated the strain's complete set of genes associated with sugar transport and metabolism for high-temperature fermentation. A set flocculation proteins were identified that aided in high cell recovery in successive fermentation cycles to achieve alcohols with high productivity. We have brought biomass derived sugars, yeast cell biomass generation, and ethanol and xylitol fermentation in one platform and validated the overall material balance. 2kg sugarcane bagasse yielded 193.4g yeast cell, and with multiple times cell recycling generated 125.56g xylitol and 289.2g ethanol (366mL). Copyright © 2017 Elsevier GmbH. All rights reserved.
Interaction of two glancing, crossing shock waves with a turbulent boundary-layer at various Mach numbers

NASA Technical Reports Server (NTRS)

Hingst, Warren R.; Williams, Kevin E.

1991-01-01

A preliminary experimental investigation was conducted to study two crossing, glancing shock waves of equal strengths, interacting with the boundary-layer developed on a supersonic wind tunnel wall. This study was performed at several Mach numbers between 2.5 and 4.0. The shock waves were created by fins (shock generators), spanning the tunnel test section, that were set at angles varying from 4 to 12 degrees. The data acquired are wall static pressure measurements, and qualitative information in the form of oil flow and schlieren visualizations. The principle aim is two-fold. First, a fundamental understanding of the physics underlying this flow phenomena is desired. Also, a comprehensive data set is needed for computational fluid dynamic code validation. Results indicate that for small shock generator angles, the boundary-layer remains attached throughout the flow field. However, with increasing shock strengths (increasing generator angles), boundary layer separation does occur and becomes progressively more severe as the generator angles are increased further. The location of the separation, which starts well downstream of the shock crossing point, moves upstream as shock strengths are increased. At the highest generator angles, the separation appears to begin coincident with the generator leading edges and engulfs most of the area between the generators. This phenomena occurs very near the 'unstart' limit for the generators. The wall pressures at the lower generator angles are nominally consistent with the flow geometries (i.e. shock patterns) although significantly affected by the boundary-layer upstream influence. As separation occurs, the wall pressures exhibit a gradient that is mainly axial in direction in the vicinity of the separation. At the limiting conditions the wall pressure gradients are primarily in the axial direction throughout.
Developmental validation of the MiSeq FGx Forensic Genomics System for Targeted Next Generation Sequencing in Forensic DNA Casework and Database Laboratories.

PubMed

Jäger, Anne C; Alvarez, Michelle L; Davis, Carey P; Guzmán, Ernesto; Han, Yonmee; Way, Lisa; Walichiewicz, Paulina; Silva, David; Pham, Nguyen; Caves, Glorianna; Bruand, Jocelyne; Schlesinger, Felix; Pond, Stephanie J K; Varlaro, Joe; Stephens, Kathryn M; Holt, Cydne L

2017-05-01

Human DNA profiling using PCR at polymorphic short tandem repeat (STR) loci followed by capillary electrophoresis (CE) size separation and length-based allele typing has been the standard in the forensic community for over 20 years. Over the last decade, Next-Generation Sequencing (NGS) matured rapidly, bringing modern advantages to forensic DNA analysis. The MiSeq FGx™ Forensic Genomics System, comprised of the ForenSeq™ DNA Signature Prep Kit, MiSeq FGx™ Reagent Kit, MiSeq FGx™ instrument and ForenSeq™ Universal Analysis Software, uses PCR to simultaneously amplify up to 231 forensic loci in a single multiplex reaction. Targeted loci include Amelogenin, 27 common, forensic autosomal STRs, 24 Y-STRs, 7 X-STRs and three classes of single nucleotide polymorphisms (SNPs). The ForenSeq™ kit includes two primer sets: Amelogenin, 58 STRs and 94 identity informative SNPs (iiSNPs) are amplified using DNA Primer Set A (DPMA; 153 loci); if a laboratory chooses to generate investigative leads using DNA Primer Set B, amplification is targeted to the 153 loci in DPMA plus 22 phenotypic informative (piSNPs) and 56 biogeographical ancestry SNPs (aiSNPs). High-resolution genotypes, including detection of intra-STR sequence variants, are semi-automatically generated with the ForenSeq™ software. This system was subjected to developmental validation studies according to the 2012 Revised SWGDAM Validation Guidelines. A two-step PCR first amplifies the target forensic STR and SNP loci (PCR1); unique, sample-specific indexed adapters or "barcodes" are attached in PCR2. Approximately 1736 ForenSeq™ reactions were analyzed. Studies include DNA substrate testing (cotton swabs, FTA cards, filter paper), species studies from a range of nonhuman organisms, DNA input sensitivity studies from 1ng down to 7.8pg, two-person human DNA mixture testing with three genotype combinations, stability analysis of partially degraded DNA, and effects of five commonly encountered PCR inhibitors. Calculations from ForenSeq™ STR and SNP repeatability and reproducibility studies (1ng template) indicate 100.0% accuracy of the MiSeq FGx™ System in allele calling relative to CE for STRs (1260 samples), and >99.1% accuracy relative to bead array typing for SNPs (1260 samples for iiSNPs, 310 samples for aiSNPs and piSNPs), with >99.0% and >97.8% precision, respectively. Call rates of >99.0% were observed for all STRs and SNPs amplified with both ForenSeq™ primer mixes. Limitations of the MiSeq FGx™ System are discussed. Results described here demonstrate that the MiSeq FGx™ System meets forensic DNA quality assurance guidelines with robust, reliable, and reproducible performance on samples of various quantities and qualities. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
R package PRIMsrc: Bump Hunting by Patient Rule Induction Method for Survival, Regression and Classification

PubMed Central

Dazard, Jean-Eudes; Choe, Michael; LeBlanc, Michael; Rao, J. Sunil

2015-01-01

PRIMsrc is a novel implementation of a non-parametric bump hunting procedure, based on the Patient Rule Induction Method (PRIM), offering a unified treatment of outcome variables, including censored time-to-event (Survival), continuous (Regression) and discrete (Classification) responses. To fit the model, it uses a recursive peeling procedure with specific peeling criteria and stopping rules depending on the response. To validate the model, it provides an objective function based on prediction-error or other specific statistic, as well as two alternative cross-validation techniques, adapted to the task of decision-rule making and estimation in the three types of settings. PRIMsrc comes as an open source R package, including at this point: (i) a main function for fitting a Survival Bump Hunting model with various options allowing cross-validated model selection to control model size (#covariates) and model complexity (#peeling steps) and generation of cross-validated end-point estimates; (ii) parallel computing; (iii) various S3-generic and specific plotting functions for data visualization, diagnostic, prediction, summary and display of results. It is available on CRAN and GitHub. PMID:26798326
Measuring cervical cancer risk: development and validation of the CARE Risky Sexual Behavior Index.

PubMed

Reiter, Paul L; Katz, Mira L; Ferketich, Amy K; Ruffin, Mack T; Paskett, Electra D

2009-12-01

To develop and validate a risky sexual behavior index specific to cervical cancer research. Sexual behavior data on 428 women from the Community Awareness Resources and Education (CARE) study were utilized. A weighting scheme for eight risky sexual behaviors was generated and validated in creating the CARE Risky Sexual Behavior Index. Cutpoints were then identified to classify women as having a low, medium, or high level of risky sexual behavior. Index scores ranged from 0 to 35, with women considered to have a low level of risky sexual behavior if their score was less than six (31.3% of sample), a medium level if their score was 6–10 (30.6%), or a high level if their score was 11 or greater (38.1%). A strong association was observed between the created categories and having a previous abnormal Pap smear test (p < 0.001). The CARE Risky Sexual Behavior Index provides a tool for measuring risky sexual behavior level for cervical cancer research. Future studies are needed to validate this index in varied populations and test its use in the clinical setting.
Design and Implementation Content Validity Study: Development of an instrument for measuring Patient-Centered Communication

PubMed Central

Zamanzadeh, Vahid; Ghahramanian, Akram; Rassouli, Maryam; Abbaszadeh, Abbas; Alavi-Majd, Hamid; Nikanfar, Ali-Reza

2015-01-01

Introduction: The importance of content validity in the instrument psychometric and its relevance with reliability, have made it an essential step in the instrument development. This article attempts to give an overview of the content validity process and to explain the complexity of this process by introducing an example. Methods: We carried out a methodological study conducted to examine the content validity of the patient-centered communication instrument through a two-step process (development and judgment). At the first step, domain determination, sampling (item generation) and instrument formation and at the second step, content validity ratio, content validity index and modified kappa statistic was performed. Suggestions of expert panel and item impact scores are used to examine the instrument face validity. Results: From a set of 188 items, content validity process identified seven dimensions includes trust building (eight items), informational support (seven items), emotional support (five items), problem solving (seven items), patient activation (10 items), intimacy/friendship (six items) and spirituality strengthening (14 items). Content validity study revealed that this instrument enjoys an appropriate level of content validity. The overall content validity index of the instrument using universal agreement approach was low; however, it can be advocated with respect to the high number of content experts that makes consensus difficult and high value of the S-CVI with the average approach, which was equal to 0.93. Conclusion: This article illustrates acceptable quantities indices for content validity a new instrument and outlines them during design and psychometrics of patient-centered communication measuring instrument. PMID:26161370
Density matters: Review of approaches to setting organism-based ballast water discharge standards

USGS Publications Warehouse

Lee II,; Frazier,; Ruiz,

2010-01-01

As part of their effort to develop national ballast water discharge standards under NPDES permitting, the Office of Water requested that WED scientists identify and review existing approaches to generating organism-based discharge standards for ballast water. Six potential approaches were identified and the utility and uncertainties of each approach was evaluated. During the process of reviewing the existing approaches, the WED scientists, in conjunction with scientists at the USGS and Smithsonian Institution, developed a new approach (per capita invasion probability or "PCIP") that addresses many of the limitations of the previous methodologies. THE PCIP approach allows risk managers to generate quantitative discharge standards using historical invasion rates, ballast water discharge volumes, and ballast water organism concentrations. The statistical power of sampling ballast water for both the validation of ballast water treatment systems and ship-board compliance monitoring with the existing methods, though it should be possible to obtain sufficient samples during treatment validation. The report will go to a National Academy of Sciences expert panel that will use it in their evaluation of approaches to developing ballast water discharge standards for the Office of Water.
Modeling of the oxidation of methyl esters—Validation for methyl hexanoate, methyl heptanoate, and methyl decanoate in a jet-stirred reactor

PubMed Central

Glaude, Pierre Alexandre; Herbinet, Olivier; Bax, Sarah; Biet, Joffrey; Warth, Valérie; Battin-Leclerc, Frédérique

2013-01-01

The modeling of the oxidation of methyl esters was investigated and the specific chemistry, which is due to the presence of the ester group in this class of molecules, is described. New reactions and rate parameters were defined and included in the software EXGAS for the automatic generation of kinetic mechanisms. Models generated with EXGAS were successfully validated against data from the literature (oxidation of methyl hexanoate and methyl heptanoate in a jet-stirred reactor) and a new set of experimental results for methyl decanoate. The oxidation of this last species was investigated in a jet-stirred reactor at temperatures from 500 to 1100 K, including the negative temperature coefficient region, under stoichiometric conditions, at a pressure of 1.06 bar and for a residence time of 1.5 s: more than 30 reaction products, including olefins, unsaturated esters, and cyclic ethers, were quantified and successfully simulated. Flow rate analysis showed that reactions pathways for the oxidation of methyl esters in the low-temperature range are similar to that of alkanes. PMID:23710076
Virtual screening and rational drug design method using structure generation system based on 3D-QSAR and docking.

PubMed

Chen, H F; Dong, X C; Zen, B S; Gao, K; Yuan, S G; Panaye, A; Doucet, J P; Fan, B T

2003-08-01

An efficient virtual and rational drug design method is presented. It combines virtual bioactive compound generation with 3D-QSAR model and docking. Using this method, it is possible to generate a lot of highly diverse molecules and find virtual active lead compounds. The method was validated by the study of a set of anti-tumor drugs. With the constraints of pharmacophore obtained by DISCO implemented in SYBYL 6.8, 97 virtual bioactive compounds were generated, and their anti-tumor activities were predicted by CoMFA. Eight structures with high activity were selected and screened by the 3D-QSAR model. The most active generated structure was further investigated by modifying its structure in order to increase the activity. A comparative docking study with telomeric receptor was carried out, and the results showed that the generated structures could form more stable complexes with receptor than the reference compound selected from experimental data. This investigation showed that the proposed method was a feasible way for rational drug design with high screening efficiency.
IDG - INTERACTIVE DIF GENERATOR

NASA Technical Reports Server (NTRS)

Preheim, L. E.

1994-01-01

The Interactive DIF Generator (IDG) utility is a tool used to generate and manipulate Directory Interchange Format files (DIF). Its purpose as a specialized text editor is to create and update DIF files which can be sent to NASA's Master Directory, also referred to as the International Global Change Directory at Goddard. Many government and university data systems use the Master Directory to advertise the availability of research data. The IDG interface consists of a set of four windows: (1) the IDG main window; (2) a text editing window; (3) a text formatting and validation window; and (4) a file viewing window. The IDG main window starts up the other windows and contains a list of valid keywords. The keywords are loaded from a user-designated file and selected keywords can be copied into any active editing window. Once activated, the editing window designates the file to be edited. Upon switching from the editing window to the formatting and validation window, the user has options for making simple changes to one or more files such as inserting tabs, aligning fields, and indenting groups. The viewing window is a scrollable read-only window that allows fast viewing of any text file. IDG is an interactive tool and requires a mouse or a trackball to operate. IDG uses the X Window System to build and manage its interactive forms, and also uses the Motif widget set and runs under Sun UNIX. IDG is written in C-language for Sun computers running SunOS. This package requires the X Window System, Version 11 Revision 4, with OSF/Motif 1.1. IDG requires 1.8Mb of hard disk space. The standard distribution medium for IDG is a .25 inch streaming magnetic tape cartridge in UNIX tar format. It is also available on a 3.5 inch diskette in UNIX tar format. The program was developed in 1991 and is a copyrighted work with all copyright vested in NASA. SunOS is a trademark of Sun Microsystems, Inc. X Window System is a trademark of Massachusetts Institute of Technology. OSF/Motif is a trademark of the Open Software Foundation, Inc. UNIX is a trademark of Bell Laboratories.
Predictions of BuChE inhibitors using support vector machine and naive Bayesian classification techniques in drug discovery.

PubMed

Fang, Jiansong; Yang, Ranyao; Gao, Li; Zhou, Dan; Yang, Shengqian; Liu, Ai-Lin; Du, Guan-hua

2013-11-25

Butyrylcholinesterase (BuChE, EC 3.1.1.8) is an important pharmacological target for Alzheimer's disease (AD) treatment. However, the currently available BuChE inhibitor screening assays are expensive, labor-intensive, and compound-dependent. It is necessary to develop robust in silico methods to predict the activities of BuChE inhibitors for the lead identification. In this investigation, support vector machine (SVM) models and naive Bayesian models were built to discriminate BuChE inhibitors (BuChEIs) from the noninhibitors. Each molecule was initially represented in 1870 structural descriptors (1235 from ADRIANA.Code, 334 from MOE, and 301 from Discovery studio). Correlation analysis and stepwise variable selection method were applied to figure out activity-related descriptors for prediction models. Additionally, structural fingerprint descriptors were added to improve the predictive ability of models, which were measured by cross-validation, a test set validation with 1001 compounds and an external test set validation with 317 diverse chemicals. The best two models gave Matthews correlation coefficient of 0.9551 and 0.9550 for the test set and 0.9132 and 0.9221 for the external test set. To demonstrate the practical applicability of the models in virtual screening, we screened an in-house data set with 3601 compounds, and 30 compounds were selected for further bioactivity assay. The assay results showed that 10 out of 30 compounds exerted significant BuChE inhibitory activities with IC50 values ranging from 0.32 to 22.22 μM, at which three new scaffolds as BuChE inhibitors were identified for the first time. To our best knowledge, this is the first report on BuChE inhibitors using machine learning approaches. The models generated from SVM and naive Bayesian approaches successfully predicted BuChE inhibitors. The study proved the feasibility of a new method for predicting bioactivities of ligands and discovering novel lead compounds.
The Development of a Finite Volume Method for Modeling Sound in Coastal Ocean Environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Long, Wen; Yang, Zhaoqing; Copping, Andrea E.

: As the rapid growth of marine renewable energy and off-shore wind energy, there have been concerns that the noises generated from construction and operation of the devices may interfere marine animals’ communication. In this research, a underwater sound model is developed to simulate sound prorogation generated by marine-hydrokinetic energy (MHK) devices or offshore wind (OSW) energy platforms. Finite volume and finite difference methods are developed to solve the 3D Helmholtz equation of sound propagation in the coastal environment. For finite volume method, the grid system consists of triangular grids in horizontal plane and sigma-layers in vertical dimension. A 3Dmore » sparse matrix solver with complex coefficients is formed for solving the resulting acoustic pressure field. The Complex Shifted Laplacian Preconditioner (CSLP) method is applied to efficiently solve the matrix system iteratively with MPI parallelization using a high performance cluster. The sound model is then coupled with the Finite Volume Community Ocean Model (FVCOM) for simulating sound propagation generated by human activities in a range-dependent setting, such as offshore wind energy platform constructions and tidal stream turbines. As a proof of concept, initial validation of the finite difference solver is presented for two coastal wedge problems. Validation of finite volume method will be reported separately.« less
Artificial Neural Network with Hardware Training and Hardware Refresh

NASA Technical Reports Server (NTRS)

Duong, Tuan A. (Inventor)

2003-01-01

A neural network circuit is provided having a plurality of circuits capable of charge storage. Also provided is a plurality of circuits each coupled to at least one of the plurality of charge storage circuits and constructed to generate an output in accordance with a neuron transfer function. Each of a plurality of circuits is coupled to one of the plurality of neuron transfer function circuits and constructed to generate a derivative of the output. A weight update circuit updates the charge storage circuits based upon output from the plurality of transfer function circuits and output from the plurality of derivative circuits. In preferred embodiments, separate training and validation networks share the same set of charge storage circuits and may operate concurrently. The validation network has a separate transfer function circuits each being coupled to the charge storage circuits so as to replicate the training network s coupling of the plurality of charge storage to the plurality of transfer function circuits. The plurality of transfer function circuits may be constructed each having a transconductance amplifier providing differential currents combined to provide an output in accordance with a transfer function. The derivative circuits may have a circuit constructed to generate a biased differential currents combined so as to provide the derivative of the transfer function.

A guided search genetic algorithm using mined rules for optimal affective product design

NASA Astrophysics Data System (ADS)

Fung, Chris K. Y.; Kwong, C. K.; Chan, Kit Yan; Jiang, H.

2014-08-01

Affective design is an important aspect of new product development, especially for consumer products, to achieve a competitive edge in the marketplace. It can help companies to develop new products that can better satisfy the emotional needs of customers. However, product designers usually encounter difficulties in determining the optimal settings of the design attributes for affective design. In this article, a novel guided search genetic algorithm (GA) approach is proposed to determine the optimal design attribute settings for affective design. The optimization model formulated based on the proposed approach applied constraints and guided search operators, which were formulated based on mined rules, to guide the GA search and to achieve desirable solutions. A case study on the affective design of mobile phones was conducted to illustrate the proposed approach and validate its effectiveness. Validation tests were conducted, and the results show that the guided search GA approach outperforms the GA approach without the guided search strategy in terms of GA convergence and computational time. In addition, the guided search optimization model is capable of improving GA to generate good solutions for affective design.
Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis

PubMed Central

Bradley, Phelim; Gordon, N. Claire; Walker, Timothy M.; Dunn, Laura; Heys, Simon; Huang, Bill; Earle, Sarah; Pankhurst, Louise J.; Anson, Luke; de Cesare, Mariateresa; Piazza, Paolo; Votintseva, Antonina A.; Golubchik, Tanya; Wilson, Daniel J.; Wyllie, David H.; Diel, Roland; Niemann, Stefan; Feuerriegel, Silke; Kohl, Thomas A.; Ismail, Nazir; Omar, Shaheed V.; Smith, E. Grace; Buck, David; McVean, Gil; Walker, A. Sarah; Peto, Tim E. A.; Crook, Derrick W.; Iqbal, Zamin

2015-01-01

The rise of antibiotic-resistant bacteria has led to an urgent need for rapid detection of drug resistance in clinical samples, and improvements in global surveillance. Here we show how de Bruijn graph representation of bacterial diversity can be used to identify species and resistance profiles of clinical isolates. We implement this method for Staphylococcus aureus and Mycobacterium tuberculosis in a software package (‘Mykrobe predictor') that takes raw sequence data as input, and generates a clinician-friendly report within 3 minutes on a laptop. For S. aureus, the error rates of our method are comparable to gold-standard phenotypic methods, with sensitivity/specificity of 99.1%/99.6% across 12 antibiotics (using an independent validation set, n=470). For M. tuberculosis, our method predicts resistance with sensitivity/specificity of 82.6%/98.5% (independent validation set, n=1,609); sensitivity is lower here, probably because of limited understanding of the underlying genetic mechanisms. We give evidence that minor alleles improve detection of extremely drug-resistant strains, and demonstrate feasibility of the use of emerging single-molecule nanopore sequencing techniques for these purposes. PMID:26686880
How to do (or not to do)… Measuring health worker motivation in surveys in low- and middle-income countries

PubMed Central

Borghi, J; Lohmann, J; Dale, E; Meheus, F; Goudge, J; Oboirien, K; Kuwawenaruwa, A

2018-01-01

Abstract A health system’s ability to deliver quality health care depends on the availability of motivated health workers, which are insufficient in many low income settings. Increasing policy and researcher attention is directed towards understanding what drives health worker motivation and how different policy interventions affect motivation, as motivation is key to performance and quality of care outcomes. As a result, there is growing interest among researchers in measuring motivation within health worker surveys. However, there is currently limited guidance on how to conceptualize and approach measurement and how to validate or analyse motivation data collected from health worker surveys, resulting in inconsistent and sometimes poor quality measures. This paper begins by discussing how motivation can be conceptualized, then sets out the steps in developing questions to measure motivation within health worker surveys and in ensuring data quality through validity and reliability tests. The paper also discusses analysis of the resulting motivation measure/s. This paper aims to promote high quality research that will generate policy relevant and useful evidence. PMID:29165641
Neural Network-Based Sensor Validation for Turboshaft Engines

NASA Technical Reports Server (NTRS)

Moller, James C.; Litt, Jonathan S.; Guo, Ten-Huei

1998-01-01

Sensor failure detection, isolation, and accommodation using a neural network approach is described. An auto-associative neural network is configured to perform dimensionality reduction on the sensor measurement vector and provide estimated sensor values. The sensor validation scheme is applied in a simulation of the T700 turboshaft engine in closed loop operation. Performance is evaluated based on the ability to detect faults correctly and maintain stable and responsive engine operation. The set of sensor outputs used for engine control forms the network input vector. Analytical redundancy is verified by training networks of successively smaller bottleneck layer sizes. Training data generation and strategy are discussed. The engine maintained stable behavior in the presence of sensor hard failures. With proper selection of fault determination thresholds, stability was maintained in the presence of sensor soft failures.
Using Android-Based Educational Game for Learning Colloid Material

NASA Astrophysics Data System (ADS)

Sari, S.; Anjani, R.; Farida, I.; Ramdhani, M. A.

2017-09-01

This research is based on the importance of the development of student’s chemical literacy on Colloid material using Android-based educational game media. Educational game products are developed through research and development design. In the analysis phase, material analysis is performed to generate concept maps, determine chemical literacy indicators, game strategies and set game paths. In the design phase, product packaging is carried out, then validation and feasibility test are performed. Research produces educational game based on Android that has the characteristics that is: Colloid material presented in 12 levels of game in the form of questions and challenges, presents visualization of discourse, images and animation contextually to develop the process of thinking and attitude. Based on the analysis of validation and trial results, the product is considered feasible to use.
The Use of CASES-97 Observations to Assess and Parameterize the Impact of Land-Surface Heterogeneity on Area-Average Surface Heat Fluxes for Large-Scale Coupled Atmosphere-Hydrology Models

NASA Technical Reports Server (NTRS)

Chen, Fei; Yates, David; LeMone, Margaret

2001-01-01

To understand the effects of land-surface heterogeneity and the interactions between the land-surface and the planetary boundary layer at different scales, we develop a multiscale data set. This data set, based on the Cooperative Atmosphere-Surface Exchange Study (CASES97) observations, includes atmospheric, surface, and sub-surface observations obtained from a dense observation network covering a large region on the order of 100 km. We use this data set to drive three land-surface models (LSMs) to generate multi-scale (with three resolutions of 1, 5, and 10 kilometers) gridded surface heat flux maps for the CASES area. Upon validating these flux maps with measurements from surface station and aircraft, we utilize them to investigate several approaches for estimating the area-integrated surface heat flux for the CASES97 domain of 71x74 square kilometers, which is crucial for land surface model development/validation and area water and energy budget studies. This research is aimed at understanding the relative contribution of random turbulence versus organized mesoscale circulations to the area-integrated surface flux at the scale of 100 kilometers, and identifying the most important effective parameters for characterizing the subgrid-scale variability for large-scale atmosphere-hydrology models.
Property-Based Monitoring of Analog and Mixed-Signal Systems

NASA Astrophysics Data System (ADS)

Havlicek, John; Little, Scott; Maler, Oded; Nickovic, Dejan

In the recent past, there has been a steady growth of the market for consumer embedded devices such as cell phones, GPS and portable multimedia systems. In embedded systems, digital, analog and software components are combined on a single chip, resulting in increasingly complex designs that introduce richer functionality on smaller devices. As a consequence, the potential insertion of errors into a design becomes higher, yielding an increasing need for automated analog and mixed-signal validation tools. In the purely digital setting, formal verification based on properties expressed in industrial specification languages such as PSL and SVA is nowadays successfully integrated in the design flow. On the other hand, the validation of analog and mixed-signal systems still largely depends on simulation-based, ad-hoc methods. In this tutorial, we consider some ingredients of the standard verification methodology that can be successfully exported from digital to analog and mixed-signal setting, in particular property-based monitoring techniques. Property-based monitoring is a lighter approach to the formal verification, where the system is seen as a "black-box" that generates sets of traces, whose correctness is checked against a property, that is its high-level specification. Although incomplete, monitoring is effectively used to catch faults in systems, without guaranteeing their full correctness.
The Initial Atmospheric Transport (IAT) Code: Description and Validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morrow, Charles W.; Bartel, Timothy James

The Initial Atmospheric Transport (IAT) computer code was developed at Sandia National Laboratories as part of their nuclear launch accident consequences analysis suite of computer codes. The purpose of IAT is to predict the initial puff/plume rise resulting from either a solid rocket propellant or liquid rocket fuel fire. The code generates initial conditions for subsequent atmospheric transport calculations. The Initial Atmospheric Transfer (IAT) code has been compared to two data sets which are appropriate to the design space of space launch accident analyses. The primary model uncertainties are the entrainment coefficients for the extended Taylor model. The Titan 34Dmore » accident (1986) was used to calibrate these entrainment settings for a prototypic liquid propellant accident while the recent Johns Hopkins University Applied Physics Laboratory (JHU/APL, or simply APL) large propellant block tests (2012) were used to calibrate the entrainment settings for prototypic solid propellant accidents. North American Meteorology (NAM )formatted weather data profiles are used by IAT to determine the local buoyancy force balance. The IAT comparisons for the APL solid propellant tests illustrate the sensitivity of the plume elevation to the weather profiles; that is, the weather profile is a dominant factor in determining the plume elevation. The IAT code performed remarkably well and is considered validated for neutral weather conditions.« less
An automated framework for hypotheses generation using literature.

PubMed

Abedi, Vida; Zand, Ramin; Yeasin, Mohammed; Faisal, Fazle Elahi

2012-08-29

In bio-medicine, exploratory studies and hypothesis generation often begin with researching existing literature to identify a set of factors and their association with diseases, phenotypes, or biological processes. Many scientists are overwhelmed by the sheer volume of literature on a disease when they plan to generate a new hypothesis or study a biological phenomenon. The situation is even worse for junior investigators who often find it difficult to formulate new hypotheses or, more importantly, corroborate if their hypothesis is consistent with existing literature. It is a daunting task to be abreast with so much being published and also remember all combinations of direct and indirect associations. Fortunately there is a growing trend of using literature mining and knowledge discovery tools in biomedical research. However, there is still a large gap between the huge amount of effort and resources invested in disease research and the little effort in harvesting the published knowledge. The proposed hypothesis generation framework (HGF) finds "crisp semantic associations" among entities of interest - that is a step towards bridging such gaps. The proposed HGF shares similar end goals like the SWAN but are more holistic in nature and was designed and implemented using scalable and efficient computational models of disease-disease interaction. The integration of mapping ontologies with latent semantic analysis is critical in capturing domain specific direct and indirect "crisp" associations, and making assertions about entities (such as disease X is associated with a set of factors Z). Pilot studies were performed using two diseases. A comparative analysis of the computed "associations" and "assertions" with curated expert knowledge was performed to validate the results. It was observed that the HGF is able to capture "crisp" direct and indirect associations, and provide knowledge discovery on demand. The proposed framework is fast, efficient, and robust in generating new hypotheses to identify factors associated with a disease. A full integrated Web service application is being developed for wide dissemination of the HGF. A large-scale study by the domain experts and associated researchers is underway to validate the associations and assertions computed by the HGF.
The photographic knee pain map: locating knee pain with an instrument developed for diagnostic, communication and research purposes.

PubMed

Elson, D W; Jones, S; Caplan, N; Stewart, S; St Clair Gibson, A; Kader, D F

2011-12-01

Pain maps are used to determine the location of pain. Knee pain maps have previously been described, but only one study has reported on reliability and none report validity. The present study describes the generation of a photographic knee pain map (PKPM) together with its validity and reliability. A photographic representation of a pair of knees was chosen by 26 patients, (66.7%) from a group of 39. The selected photograph was modified and a template of anatomical zones was generated. The opinions of 25 independent subject matter experts were canvassed and validity ratios calculated for these zones, ranged from 0.28 to 0.84. Hypothetical comparisons were made between the PKPM and an alternative knee pain map, in a cross-sectional group of 26 patients (35 knees). Convergent patterns of validity were found where hypothesised. Reliability was determined using a different cohort of 44 patients (58 knees) who completed the PKPM before and after a sampling delay. Four of these patients were excluded with a short sampling delay. Calculated agreement of test-retest reproducibility was fair to good. All of the completed PKPM (151 knees) were then subject to further analysis where inter-rater reproducibility was good to very good and intra-rater reproducibility was very good. The PKPM is readily accessible to patients with low completion burden. It is both valid and reliable and we suggest it can be used in both clinical and research settings. Further studies are planned to explore its predictive ability as a diagnostic tool. The PKPM can be found at www.photographickneepainmap.com. Copyright © 2010 Elsevier B.V. All rights reserved.
A System for Cost and Reimbursement Control in Hospitals

PubMed Central

Fetter, Robert B.; Thompson, John D.; Mills, Ronald E.

1976-01-01

This paper approaches the design of a regional or statewide hospital rate-setting system as the underpinning of a larger system which permits a regulatory agency to satisfy the requirements of various public laws now on the books or in process. It aims to generate valid interinstitutional monitoring on the three parameters of cost, utilization, and quality review. Such an approach requires the extension of the usual departmental cost and budgeting system to include consideration of the mix of patients treated and the utilization of various resources, including patient days, in the treatment of these patients. A sampling framework for the application of process-based quality studies and the generation of selected performance measurements is also included. PMID:941461
Spanish language generation engine to enhance the syntactic quality of AAC systems

NASA Astrophysics Data System (ADS)

Narváez A., Cristian; Sastoque H., Sebastián.; Iregui G., Marcela

2015-12-01

People with Complex Communication Needs (CCN) face difficulties to communicate their ideas, feelings and needs. Augmentative and Alternative Communication (AAC) approaches aim to provide support to enhance socialization of these individuals. However, there are many limitations in current applications related with systems operation, target scenarios and language consistency. This work presents an AAC approach to enhance produced messages by applying elements of Natural Language Generation. Specifically, a Spanish language engine, composed of a grammar ontology and a set of linguistic rules, is proposed to improve the naturalness in the communication process, when persons with CCN tell stories about their daily activities to non-disabled receivers. The assessment of the proposed method confirms the validity of the model to improve messages quality.
Cooperative Optimal Coordination for Distributed Energy Resources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Tao; Wu, Di; Ren, Wei

In this paper, we consider the optimal coordination problem for distributed energy resources (DERs) including distributed generators and energy storage devices. We propose an algorithm based on the push-sum and gradient method to optimally coordinate storage devices and distributed generators in a distributed manner. In the proposed algorithm, each DER only maintains a set of variables and updates them through information exchange with a few neighbors over a time-varying directed communication network. We show that the proposed distributed algorithm solves the optimal DER coordination problem if the time-varying directed communication network is uniformly jointly strongly connected, which is a mildmore » condition on the connectivity of communication topologies. The proposed distributed algorithm is illustrated and validated by numerical simulations.« less
Plaque Tissue Morphology-Based Stroke Risk Stratification Using Carotid Ultrasound: A Polling-Based PCA Learning Paradigm.

PubMed

Saba, Luca; Jain, Pankaj K; Suri, Harman S; Ikeda, Nobutaka; Araki, Tadashi; Singh, Bikesh K; Nicolaides, Andrew; Shafique, Shoaib; Gupta, Ajay; Laird, John R; Suri, Jasjit S

2017-06-01

Severe atherosclerosis disease in carotid arteries causes stenosis which in turn leads to stroke. Machine learning systems have been previously developed for plaque wall risk assessment using morphology-based characterization. The fundamental assumption in such systems is the extraction of the grayscale features of the plaque region. Even though these systems have the ability to perform risk stratification, they lack the ability to achieve higher performance due their inability to select and retain dominant features. This paper introduces a polling-based principal component analysis (PCA) strategy embedded in the machine learning framework to select and retain dominant features, resulting in superior performance. This leads to more stability and reliability. The automated system uses offline image data along with the ground truth labels to generate the parameters, which are then used to transform the online grayscale features to predict the risk of stroke. A set of sixteen grayscale plaque features is computed. Utilizing the cross-validation protocol (K = 10), and the PCA cutoff of 0.995, the machine learning system is able to achieve an accuracy of 98.55 and 98.83%corresponding to the carotidfar wall and near wall plaques, respectively. The corresponding reliability of the system was 94.56 and 95.63%, respectively. The automated system was validated against the manual risk assessment system and the precision of merit for same cross-validation settings and PCA cutoffs are 98.28 and 93.92%for the far and the near wall, respectively.PCA-embedded morphology-based plaque characterization shows a powerful strategy for risk assessment and can be adapted in clinical settings.
PCC Framework for Program-Generators

NASA Technical Reports Server (NTRS)

Kong, Soonho; Choi, Wontae; Yi, Kwangkeun

2009-01-01

In this paper, we propose a proof-carrying code framework for program-generators. The enabling technique is abstract parsing, a static string analysis technique, which is used as a component for generating and validating certificates. Our framework provides an efficient solution for certifying program-generators whose safety properties are expressed in terms of the grammar representing the generated program. The fixed-point solution of the analysis is generated and attached with the program-generator on the code producer side. The consumer receives the code with a fixed-point solution and validates that the received fixed point is indeed a fixed point of the received code. This validation can be done in a single pass.
Development and evaluation of the Expressions of Moral Injury Scale-Military Version.

PubMed

Currier, Joseph M; Farnsworth, Jacob K; Drescher, Kent D; McDermott, Ryon C; Sims, Brook M; Albright, David L

2018-05-01

There is consensus that military personnel can encounter a far more diverse set of challenges than researchers and clinicians have historically appreciated. Moral injury (MI) represents an emerging construct to capture behavioural, social, and spiritual suffering that may transcend and overlap with mental health diagnoses (e.g., post-traumatic stress disorder and major depressive disorder). The Expressions of Moral Injury Scale-Military Version (EMIS-M) was developed to provide a reliable and valid means for assessing the warning signs of a MI in military populations. Drawing on independent samples of veterans who had served in a war-zone environment, factor analytic results revealed 2 distinct factors related to MI expressions directed at both self (9 items) and others (8 items). These subscales generated excellent internal consistency and temporal stability over a 6-month period. When compared to measures of post-traumatic stress disorder, major depressive disorder, and other theoretically relevant constructs (e.g., forgiveness, social support, moral emotions, and combat exposure), EMIS-M scores demonstrated strong convergent, divergent, and incremental validity. In addition, although structural equation modelling findings supported a possible general MI factor in Study 2, the patterns of associations for self- and other-directed expressions yielded evidence for differential validity with varying forms of forgiveness and combat exposure. As such, the EMIS-M provides a face valid, psychometrically validated tool for assessing expressions of apparent MI subtypes in research and clinical settings. Looking ahead, the EMIS-M will hopefully advance the scientific understanding of MI while supporting innovation for clinicians to tailor evidence-based treatments and/or develop novel approaches for addressing MI in their work. Copyright © 2017 John Wiley & Sons, Ltd.
An Empiric HIV Risk Scoring Tool to Predict HIV-1 Acquisition in African Women.

PubMed

Balkus, Jennifer E; Brown, Elizabeth; Palanee, Thesla; Nair, Gonasagrie; Gafoor, Zakir; Zhang, Jingyang; Richardson, Barbra A; Chirenje, Zvavahera M; Marrazzo, Jeanne M; Baeten, Jared M

2016-07-01

To develop and validate an HIV risk assessment tool to predict HIV acquisition among African women. Data were analyzed from 3 randomized trials of biomedical HIV prevention interventions among African women (VOICE, HPTN 035, and FEM-PrEP). We implemented standard methods for the development of clinical prediction rules to generate a risk-scoring tool to predict HIV acquisition over the course of 1 year. Performance of the score was assessed through internal and external validations. The final risk score resulting from multivariable modeling included age, married/living with a partner, partner provides financial or material support, partner has other partners, alcohol use, detection of a curable sexually transmitted infection, and herpes simplex virus 2 serostatus. Point values for each factor ranged from 0 to 2, with a maximum possible total score of 11. Scores ≥5 were associated with HIV incidence >5 per 100 person-years and identified 91% of incident HIV infections from among only 64% of women. The area under the curve (AUC) for predictive ability of the score was 0.71 (95% confidence interval [CI]: 0.68 to 0.74), indicating good predictive ability. Risk score performance was generally similar with internal cross-validation (AUC = 0.69; 95% CI: 0.66 to 0.73) and external validation in HPTN 035 (AUC = 0.70; 95% CI: 0.65 to 0.75) and FEM-PrEP (AUC = 0.58; 95% CI: 0.51 to 0.65). A discrete set of characteristics that can be easily assessed in clinical and research settings was predictive of HIV acquisition over 1 year. The use of a validated risk score could improve efficiency of recruitment into HIV prevention research and inform scale-up of HIV prevention strategies in women at highest risk.
Importance of Requirements Analysis & Traceability to Improve Software Quality and Reduce Cost and Risk

NASA Technical Reports Server (NTRS)

Kapoor, Manju M.; Mehta, Manju

2010-01-01

The goal of this paper is to emphasize the importance of developing complete and unambiguous requirements early in the project cycle (prior to Preliminary Design Phase). Having a complete set of requirements early in the project cycle allows sufficient time to generate a traceability matrix. Requirements traceability and analysis are the key elements in improving verification and validation process, and thus overall software quality. Traceability can be most beneficial when the system changes. If changes are made to high-level requirements it implies that low-level requirements need to be modified. Traceability ensures that requirements are appropriately and efficiently verified at various levels whereas analysis ensures that a rightly interpreted set of requirements is produced.
Designing an activity-based costing model for a non-admitted prisoner healthcare setting.

PubMed

Cai, Xiao; Moore, Elizabeth; McNamara, Martin

2013-09-01

To design and deliver an activity-based costing model within a non-admitted prisoner healthcare setting. Key phases from the NSW Health clinical redesign methodology were utilised: diagnostic, solution design and implementation. The diagnostic phase utilised a range of strategies to identify issues requiring attention in the development of the costing model. The solution design phase conceptualised distinct 'building blocks' of activity and cost based on the speciality of clinicians providing care. These building blocks enabled the classification of activity and comparisons of costs between similar facilities. The implementation phase validated the model. The project generated an activity-based costing model based on actual activity performed, gained acceptability among clinicians and managers, and provided the basis for ongoing efficiency and benchmarking efforts.
Quality of Care Measures for the Management of Unhealthy Alcohol Use

PubMed Central

Hepner, Kimberly A.; Watkins, Katherine E.; Farmer, Carrie M.; Rubenstein, Lisa; Pedersen, Eric R.; Pincus, Harold Alan

2017-01-01

There is a paucity of quality measures to assess the care for the range of unhealthy alcohol use, ranging from risky drinking to alcohol use disorders. Using a two-phase expert panel review process, we sought to develop an expanded set of quality of care measures for unhealthy alcohol use, focusing on outpatient care delivered in both primary care and specialty care settings. This process generated 25 candidate measures. Eight measures address screening and assessment, 11 address aspects of treatment, and six address follow-up. These quality measures represent high priority targets for future development, including creating detailed technical specifications and pilot testing them to evaluate their utility in terms of feasibility, reliability, and validity. PMID:28340902

Modern modeling techniques had limited external validity in predicting mortality from traumatic brain injury.

PubMed

van der Ploeg, Tjeerd; Nieboer, Daan; Steyerberg, Ewout W

2016-10-01

Prediction of medical outcomes may potentially benefit from using modern statistical modeling techniques. We aimed to externally validate modeling strategies for prediction of 6-month mortality of patients suffering from traumatic brain injury (TBI) with predictor sets of increasing complexity. We analyzed individual patient data from 15 different studies including 11,026 TBI patients. We consecutively considered a core set of predictors (age, motor score, and pupillary reactivity), an extended set with computed tomography scan characteristics, and a further extension with two laboratory measurements (glucose and hemoglobin). With each of these sets, we predicted 6-month mortality using default settings with five statistical modeling techniques: logistic regression (LR), classification and regression trees, random forests (RFs), support vector machines (SVM) and neural nets. For external validation, a model developed on one of the 15 data sets was applied to each of the 14 remaining sets. This process was repeated 15 times for a total of 630 validations. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminative ability of the models. For the most complex predictor set, the LR models performed best (median validated AUC value, 0.757), followed by RF and support vector machine models (median validated AUC value, 0.735 and 0.732, respectively). With each predictor set, the classification and regression trees models showed poor performance (median validated AUC value, <0.7). The variability in performance across the studies was smallest for the RF- and LR-based models (inter quartile range for validated AUC values from 0.07 to 0.10). In the area of predicting mortality from TBI, nonlinear and nonadditive effects are not pronounced enough to make modern prediction methods beneficial. Copyright © 2016 Elsevier Inc. All rights reserved.
Brazilian validation of the Alberta Infant Motor Scale.

PubMed

Valentini, Nadia Cristina; Saccani, Raquel

2012-03-01

The Alberta Infant Motor Scale (AIMS) is a well-known motor assessment tool used to identify potential delays in infants' motor development. Although Brazilian researchers and practitioners have used the AIMS in laboratories and clinical settings, its translation to Portuguese and validation for the Brazilian population is yet to be investigated. This study aimed to translate and validate all AIMS items with respect to internal consistency and content, criterion, and construct validity. A cross-sectional and longitudinal design was used. A cross-cultural translation was used to generate a Brazilian-Portuguese version of the AIMS. In addition, a validation process was conducted involving 22 professionals and 766 Brazilian infants (aged 0-18 months). The results demonstrated language clarity and internal consistency for the motor criteria (motor development score, α=.90; prone, α=.85; supine, α=.92; sitting, α=.84; and standing, α=.86). The analysis also revealed high discriminative power to identify typical and atypical development (motor development score, P<.001; percentile, P=.04; classification criterion, χ(2)=6.03; P=.05). Temporal stability (P=.07) (rho=.85, P<.001) was observed, and predictive power (P<.001) was limited to the group of infants aged from 3 months to 9 months. Limited predictive validity was observed, which may have been due to the restricted time that the groups were followed longitudinally. In sum, the translated version of AIMS presented adequate validity and reliability.
Situating Standard Setting within Argument-Based Validity

ERIC Educational Resources Information Center

Papageorgiou, Spiros; Tannenbaum, Richard J.

2016-01-01

Although there has been substantial work on argument-based approaches to validation as well as standard-setting methodologies, it might not always be clear how standard setting fits into argument-based validity. The purpose of this article is to address this lack in the literature, with a specific focus on topics related to argument-based…
Imputation of missing data in time series for air pollutants

NASA Astrophysics Data System (ADS)

Junger, W. L.; Ponce de Leon, A.

2015-02-01

Missing data are major concerns in epidemiological studies of the health effects of environmental air pollutants. This article presents an imputation-based method that is suitable for multivariate time series data, which uses the EM algorithm under the assumption of normal distribution. Different approaches are considered for filtering the temporal component. A simulation study was performed to assess validity and performance of proposed method in comparison with some frequently used methods. Simulations showed that when the amount of missing data was as low as 5%, the complete data analysis yielded satisfactory results regardless of the generating mechanism of the missing data, whereas the validity began to degenerate when the proportion of missing values exceeded 10%. The proposed imputation method exhibited good accuracy and precision in different settings with respect to the patterns of missing observations. Most of the imputations obtained valid results, even under missing not at random. The methods proposed in this study are implemented as a package called mtsdi for the statistical software system R.
On the inherent competition between valid and spurious inductive inferences in Boolean data

NASA Astrophysics Data System (ADS)

Andrecut, M.

Inductive inference is the process of extracting general rules from specific observations. This problem also arises in the analysis of biological networks, such as genetic regulatory networks, where the interactions are complex and the observations are incomplete. A typical task in these problems is to extract general interaction rules as combinations of Boolean covariates, that explain a measured response variable. The inductive inference process can be considered as an incompletely specified Boolean function synthesis problem. This incompleteness of the problem will also generate spurious inferences, which are a serious threat to valid inductive inference rules. Using random Boolean data as a null model, here we attempt to measure the competition between valid and spurious inductive inference rules from a given data set. We formulate two greedy search algorithms, which synthesize a given Boolean response variable in a sparse disjunct normal form, and respectively a sparse generalized algebraic normal form of the variables from the observation data, and we evaluate numerically their performance.
Engineering Software Suite Validates System Design

NASA Technical Reports Server (NTRS)

2007-01-01

EDAptive Computing Inc.'s (ECI) EDAstar engineering software tool suite, created to capture and validate system design requirements, was significantly funded by NASA's Ames Research Center through five Small Business Innovation Research (SBIR) contracts. These programs specifically developed Syscape, used to capture executable specifications of multi-disciplinary systems, and VectorGen, used to automatically generate tests to ensure system implementations meet specifications. According to the company, the VectorGen tests considerably reduce the time and effort required to validate implementation of components, thereby ensuring their safe and reliable operation. EDASHIELD, an additional product offering from ECI, can be used to diagnose, predict, and correct errors after a system has been deployed using EDASTAR -created models. Initial commercialization for EDASTAR included application by a large prime contractor in a military setting, and customers include various branches within the U.S. Department of Defense, industry giants like the Lockheed Martin Corporation, Science Applications International Corporation, and Ball Aerospace and Technologies Corporation, as well as NASA's Langley and Glenn Research Centers
Consumer Sleep Technology: An American Academy of Sleep Medicine Position Statement.

PubMed

Khosla, Seema; Deak, Maryann C; Gault, Dominic; Goldstein, Cathy A; Hwang, Dennis; Kwon, Younghoon; O'Hearn, Daniel; Schutte-Rodin, Sharon; Yurcheshen, Michael; Rosen, Ilene M; Kirsch, Douglas B; Chervin, Ronald D; Carden, Kelly A; Ramar, Kannan; Aurora, R Nisha; Kristo, David A; Malhotra, Raman K; Martin, Jennifer L; Olson, Eric J; Rosen, Carol L; Rowley, James A

2018-05-15

Consumer sleep technologies (CSTs) are widespread applications and devices that purport to measure and even improve sleep. Sleep clinicians may frequently encounter CST in practice and, despite lack of validation against gold standard polysomnography, familiarity with these devices has become a patient expectation. This American Academy of Sleep Medicine position statement details the disadvantages and potential benefits of CSTs and provides guidance when approaching patient-generated health data from CSTs in a clinical setting. Given the lack of validation and United States Food and Drug Administration (FDA) clearance, CSTs cannot be utilized for the diagnosis and/or treatment of sleep disorders at this time. However, CSTs may be utilized to enhance the patient-clinician interaction when presented in the context of an appropriate clinical evaluation. The ubiquitous nature of CSTs may further sleep research and practice. However, future validation, access to raw data and algorithms, and FDA oversight are needed. © 2018 American Academy of Sleep Medicine.
Development of multiplex microsatellite PCR panels for the seagrass Thalassia hemprichii (Hydrocharitaceae).

PubMed

van Dijk, Kor-Jent; Mellors, Jane; Waycott, Michelle

2014-11-01

New microsatellites were developed for the seagrass Thalassia hemprichii (Hydrocharitaceae), a long-lived seagrass species that is found throughout the shallow waters of tropical and subtropical Indo-West Pacific. Three multiplex PCR panels were designed utilizing new and previously developed markers, resulting in a toolkit for generating a 16-locus genotype. • Through the use of microsatellite enrichment and next-generation sequencing, 16 new, validated, polymorphic microsatellite markers were isolated. Diversity was between two and four alleles per locus totaling 36 alleles. These markers, plus previously developed microsatellite markers for T. hemprichii and T. testudinum, were tested for suitability in multiplex PCR panels. • The generation of an easily replicated suite of multiplex panels of codominant molecular markers will allow for high-resolution and detailed genetic structure analysis and clonality assessment with minimal genotyping costs. We suggest the establishment of a T. hemprichii primer convention for the unification of future data sets.
Advanced dc motor controller for battery-powered electric vehicles

NASA Technical Reports Server (NTRS)

Belsterling, C. A.

1981-01-01

A motor generation set is connected to run from the dc source and generate a voltage in the traction motor armature circuit that normally opposes the source voltage. The functional feasibility of the concept is demonstrated with tests on a Proof of Principle System. An analog computer simulation is developed, validated with the results of the tests, applied to predict the performance of a full scale Functional Model dc Controller. The results indicate high efficiencies over wide operating ranges and exceptional recovery of regenerated energy. The new machine integrates both motor and generator on a single two bearing shaft. The control strategy produces a controlled bidirectional plus or minus 48 volts dc output from the generator permitting full control of a 96 volt dc traction motor from a 48 volt battery, was designed to control a 20 hp traction motor. The controller weighs 63.5 kg (140 lb.) and has a peak efficiency of 90% in random driving modes and 96% during the SAE J 227a/D driving cycle.
Modal Survey of ETM-3, A 5-Segment Derivative of the Space Shuttle Solid Rocket Booster

NASA Technical Reports Server (NTRS)

Nielsen, D.; Townsend, J.; Kappus, K.; Driskill, T.; Torres, I.; Parks, R.

2005-01-01

The complex interactions between internal motor generated pressure oscillations and motor structural vibration modes associated with the static test configuration of a Reusable Solid Rocket Motor have potential to generate significant dynamic thrust loads in the 5-segment configuration (Engineering Test Motor 3). Finite element model load predictions for worst-case conditions were generated based on extrapolation of a previously correlated 4-segment motor model. A modal survey was performed on the largest rocket motor to date, Engineering Test Motor #3 (ETM-3), to provide data for finite element model correlation and validation of model generated design loads. The modal survey preparation included pretest analyses to determine an efficient analysis set selection using the Effective Independence Method and test simulations to assure critical test stand component loads did not exceed design limits. Historical Reusable Solid Rocket Motor modal testing, ETM-3 test analysis model development and pre-test loads analyses, as well as test execution, and a comparison of results to pre-test predictions are discussed.
DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferraioli, Luigi; Hueller, Mauro; Vitale, Stefano

The scientific objectives of the LISA Technology Package experiment on board of the LISA Pathfinder mission demand accurate calibration and validation of the data analysis tools in advance of the mission launch. The level of confidence required in the mission outcomes can be reached only by intensively testing the tools on synthetically generated data. A flexible procedure allowing the generation of a cross-correlated stationary noise time series was set up. A multichannel time series with the desired cross-correlation behavior can be generated once a model for a multichannel cross-spectral matrix is provided. The core of the procedure comprises a noisemore » coloring, multichannel filter designed via a frequency-by-frequency eigendecomposition of the model cross-spectral matrix and a subsequent fit in the Z domain. The common problem of initial transients in a filtered time series is solved with a proper initialization of the filter recursion equations. The noise generator performance was tested in a two-dimensional case study of the closed-loop LISA Technology Package dynamics along the two principal degrees of freedom.« less
Optimal Shape Design of Mail-Slot Nacelle on N3-X Hybrid Wing-Body Configuration

NASA Technical Reports Server (NTRS)

Kim, Hyoungjin; Liou, Meng-Sing

2013-01-01

System studies show that a N3-X hybrid wing-body aircraft with a turboelectric distributed propulsion system using a mail-slot inlet/nozzle nacelle can meet the environmental and performance goals for N+3 generation transports (three generations beyond the current air transport technology level) set by NASA's Subsonic Fixed Wing Project. In this study, a Navier-Stokes flow simulation of N3-X on hybrid unstructured meshes was conducted, including the mail-slot propulsor. The geometry of the mail-slot propulsor was generated by a CAD (Computer-Aided Design)-free shape parameterization. A novel body force model generation approach was suggested for a more realistic and efficient simulation of the flow turning, pressure rise and loss effects of the fan blades and the inlet-fan interactions. Flow simulation results of the N3-X demonstrates the validity of the present approach. An optimal Shape design of the mail-slot nacelle surface was conducted to reduce strength of shock waves and flow separations on the cowl surface.
MABAL: a Novel Deep-Learning Architecture for Machine-Assisted Bone Age Labeling.

PubMed

Mutasa, Simukayi; Chang, Peter D; Ruzal-Shapiro, Carrie; Ayyala, Rama

2018-02-05

Bone age assessment (BAA) is a commonly performed diagnostic study in pediatric radiology to assess skeletal maturity. The most commonly utilized method for assessment of BAA is the Greulich and Pyle method (Pediatr Radiol 46.9:1269-1274, 2016; Arch Dis Child 81.2:172-173, 1999) atlas. The evaluation of BAA can be a tedious and time-consuming process for the radiologist. As such, several computer-assisted detection/diagnosis (CAD) methods have been proposed for automation of BAA. Classical CAD tools have traditionally relied on hard-coded algorithmic features for BAA which suffer from a variety of drawbacks. Recently, the advent and proliferation of convolutional neural networks (CNNs) has shown promise in a variety of medical imaging applications. There have been at least two published applications of using deep learning for evaluation of bone age (Med Image Anal 36:41-51, 2017; JDI 1-5, 2017). However, current implementations are limited by a combination of both architecture design and relatively small datasets. The purpose of this study is to demonstrate the benefits of a customized neural network algorithm carefully calibrated to the evaluation of bone age utilizing a relatively large institutional dataset. In doing so, this study will aim to show that advanced architectures can be successfully trained from scratch in the medical imaging domain and can generate results that outperform any existing proposed algorithm. The training data consisted of 10,289 images of different skeletal age examinations, 8909 from the hospital Picture Archiving and Communication System at our institution and 1383 from the public Digital Hand Atlas Database. The data was separated into four cohorts, one each for male and female children above the age of 8, and one each for male and female children below the age of 10. The testing set consisted of 20 radiographs of each 1-year-age cohort from 0 to 1 years to 14-15+ years, half male and half female. The testing set included left-hand radiographs done for bone age assessment, trauma evaluation without significant findings, and skeletal surveys. A 14 hidden layer-customized neural network was designed for this study. The network included several state of the art techniques including residual-style connections, inception layers, and spatial transformer layers. Data augmentation was applied to the network inputs to prevent overfitting. A linear regression output was utilized. Mean square error was used as the network loss function and mean absolute error (MAE) was utilized as the primary performance metric. MAE accuracies on the validation and test sets for young females were 0.654 and 0.561 respectively. For older females, validation and test accuracies were 0.662 and 0.497 respectively. For young males, validation and test accuracies were 0.649 and 0.585 respectively. Finally, for older males, validation and test set accuracies were 0.581 and 0.501 respectively. The female cohorts were trained for 900 epochs each and the male cohorts were trained for 600 epochs. An eightfold cross-validation set was employed for hyperparameter tuning. Test error was obtained after training on a full data set with the selected hyperparameters. Using our proposed customized neural network architecture on our large available data, we achieved an aggregate validation and test set mean absolute errors of 0.637 and 0.536 respectively. To date, this is the best published performance on utilizing deep learning for bone age assessment. Our results support our initial hypothesis that customized, purpose-built neural networks provide improved performance over networks derived from pre-trained imaging data sets. We build on that initial work by showing that the addition of state-of-the-art techniques such as residual connections and inception architecture further improves prediction accuracy. This is important because the current assumption for use of residual and/or inception architectures is that a large pre-trained network is required for successful implementation given the relatively small datasets in medical imaging. Instead we show that a small, customized architecture incorporating advanced CNN strategies can indeed be trained from scratch, yielding significant improvements in algorithm accuracy. It should be noted that for all four cohorts, testing error outperformed validation error. One reason for this is that our ground truth for our test set was obtained by averaging two pediatric radiologist reads compared to our training data for which only a single read was used. This suggests that despite relatively noisy training data, the algorithm could successfully model the variation between observers and generate estimates that are close to the expected ground truth.
Goal setting as an outcome measure: A systematic review.

PubMed

Hurn, Jane; Kneebone, Ian; Cropley, Mark

2006-09-01

Goal achievement has been considered to be an important measure of outcome by clinicians working with patients in physical and neurological rehabilitation settings. This systematic review was undertaken to examine the reliability, validity and sensitivity of goal setting and goal attainment scaling approaches when used with working age and older people. To review the reliability, validity and sensitivity of both goal setting and goal attainment scaling when employed as an outcome measure within a physical and neurological working age and older person rehabilitation environment, by examining the research literature covering the 36 years since goal-setting theory was proposed. Data sources included a computer-aided literature search of published studies examining the reliability, validity and sensitivity of goal setting/goal attainment scaling, with further references sourced from articles obtained through this process. There is strong evidence for the reliability, validity and sensitivity of goal attainment scaling. Empirical support was found for the validity of goal setting but research demonstrating its reliability and sensitivity is limited. Goal attainment scaling appears to be a sound measure for use in physical rehabilitation settings with working age and older people. Further work needs to be carried out with goal setting to establish its reliability and sensitivity as a measurement tool.
A keyword spotting model using perceptually significant energy features

NASA Astrophysics Data System (ADS)

Umakanthan, Padmalochini

The task of a keyword recognition system is to detect the presence of certain words in a conversation based on the linguistic information present in human speech. Such keyword spotting systems have applications in homeland security, telephone surveillance and human-computer interfacing. General procedure of a keyword spotting system involves feature generation and matching. In this work, new set of features that are based on the psycho-acoustic masking nature of human speech are proposed. After developing these features a time aligned pattern matching process was implemented to locate the words in a set of unknown words. A word boundary detection technique based on frame classification using the nonlinear characteristics of speech is also addressed in this work. Validation of this keyword spotting model was done using widely acclaimed Cepstral features. The experimental results indicate the viability of using these perceptually significant features as an augmented feature set in keyword spotting.
A hierarchical clustering methodology for the estimation of toxicity.

PubMed

Martin, Todd M; Harten, Paul; Venkatapathy, Raghuraman; Das, Shashikala; Young, Douglas M

2008-01-01

ABSTRACT A quantitative structure-activity relationship (QSAR) methodology based on hierarchical clustering was developed to predict toxicological endpoints. This methodology utilizes Ward's method to divide a training set into a series of structurally similar clusters. The structural similarity is defined in terms of 2-D physicochemical descriptors (such as connectivity and E-state indices). A genetic algorithm-based technique is used to generate statistically valid QSAR models for each cluster (using the pool of descriptors described above). The toxicity for a given query compound is estimated using the weighted average of the predictions from the closest cluster from each step in the hierarchical clustering assuming that the compound is within the domain of applicability of the cluster. The hierarchical clustering methodology was tested using a Tetrahymena pyriformis acute toxicity data set containing 644 chemicals in the training set and with two prediction sets containing 339 and 110 chemicals. The results from the hierarchical clustering methodology were compared to the results from several different QSAR methodologies.
Using Chinese Version of MYMOP in Chinese Medicine Evaluation: Validity, Responsiveness and Minimally Important Change

PubMed Central

2010-01-01

Background Measure Yourself Medical Outcome Profile (MYMOP) is a patient generated outcome instrument applicable in the evaluation of both allopathic and complementary medicine treatment. This study aims to adapt MYMOP into Chinese, and to assess its validity, responsiveness and minimally important change values in a sample of patients using Chinese medicine (CM) services. Methods A Chinese version of MYMOP (CMYMOP) is developed by forward-backward-forward translation strategy, expert panel assessment and pilot testing amongst patients. 272 patients aged 18 or above with subjective symptoms in the past 2 weeks were recruited at a CM clinic, and were invited to complete a set of questionnaire containing CMYMOP and SF-36. Follow ups were performed at 2nd and 4th week after consultation, using the same set of questionnaire plus a global rating of change question. Criterion validity of CMYMOP was assessed by its correlation with SF-36 at baseline, and responsiveness was evaluated by calculating the Cohen effect size (ES) of change at two follow ups. Minimally important difference (MID) values were estimated via anchor based method, while minimally detectable difference (MDC) figures were calculated by distribution based method. Results Criterion validity of CMYMOP was demonstrated by negative correlation between CMYMOP Profile scores and all SF-36 domain and summary scores at baseline. For responsiveness between baseline and 4th week follow up, ES of CMYMOP Symptom 1, Activity and Profile reached the moderate change threshold (ES>0.5), while Symptom 2 and Wellbeing reached the weak change threshold (ES>0.2). None of the SF-36 scores reached the moderate change threshold, implying CMYMOP's stronger responsiveness in CM setting. At 2nd week follow up, MID values for Symptom 1, Symptom 2, Wellbeing and Profile items were 0.894, 0.580, 0.263 and 0.516 respectively. For Activity item, MDC figure of 0.808 was adopted to estimate MID. Conclusions The findings support the validity and responsiveness of CMYMOP for capturing patient centred clinical changes within 2 weeks in a CM clinical setting. Further researches are warranted (1) to estimate Activity item MID, (2) to assess the test-retest reliability of CMYMOP, and (3) to perform further MID evaluation using multiple, item specific anchor questions. PMID:20920284
Support Vector Data Description Model to Map Specific Land Cover with Optimal Parameters Determined from a Window-Based Validation Set.

PubMed

Zhang, Jinshui; Yuan, Zhoumiqi; Shuai, Guanyuan; Pan, Yaozhong; Zhu, Xiufang

2017-04-26

This paper developed an approach, the window-based validation set for support vector data description (WVS-SVDD), to determine optimal parameters for support vector data description (SVDD) model to map specific land cover by integrating training and window-based validation sets. Compared to the conventional approach where the validation set included target and outlier pixels selected visually and randomly, the validation set derived from WVS-SVDD constructed a tightened hypersphere because of the compact constraint by the outlier pixels which were located neighboring to the target class in the spectral feature space. The overall accuracies for wheat and bare land achieved were as high as 89.25% and 83.65%, respectively. However, target class was underestimated because the validation set covers only a small fraction of the heterogeneous spectra of the target class. The different window sizes were then tested to acquire more wheat pixels for validation set. The results showed that classification accuracy increased with the increasing window size and the overall accuracies were higher than 88% at all window size scales. Moreover, WVS-SVDD showed much less sensitivity to the untrained classes than the multi-class support vector machine (SVM) method. Therefore, the developed method showed its merits using the optimal parameters, tradeoff coefficient ( C ) and kernel width ( s ), in mapping homogeneous specific land cover.
The influence of locus number and information content on species delimitation: an empirical test case in an endangered Mexican salamander.

PubMed

Hime, Paul M; Hotaling, Scott; Grewelle, Richard E; O'Neill, Eric M; Voss, S Randal; Shaffer, H Bradley; Weisrock, David W

2016-12-01

Perhaps the most important recent advance in species delimitation has been the development of model-based approaches to objectively diagnose species diversity from genetic data. Additionally, the growing accessibility of next-generation sequence data sets provides powerful insights into genome-wide patterns of divergence during speciation. However, applying complex models to large data sets is time-consuming and computationally costly, requiring careful consideration of the influence of both individual and population sampling, as well as the number and informativeness of loci on species delimitation conclusions. Here, we investigated how locus number and information content affect species delimitation results for an endangered Mexican salamander species, Ambystoma ordinarium. We compared results for an eight-locus, 137-individual data set and an 89-locus, seven-individual data set. For both data sets, we used species discovery methods to define delimitation models and species validation methods to rigorously test these hypotheses. We also used integrated demographic model selection tools to choose among delimitation models, while accounting for gene flow. Our results indicate that while cryptic lineages may be delimited with relatively few loci, sampling larger numbers of loci may be required to ensure that enough informative loci are available to accurately identify and validate shallow-scale divergences. These analyses highlight the importance of striking a balance between dense sampling of loci and individuals, particularly in shallowly diverged lineages. They also suggest the presence of a currently unrecognized, endangered species in the western part of A. ordinarium's range. © 2016 John Wiley & Sons Ltd.
From High-Throughput Microarray-Based Screening to Clinical Application: The Development of a Second Generation Multigene Test for Breast Cancer Prognosis

PubMed Central

Brase, Jan C.; Kronenwett, Ralf; Petry, Christoph; Denkert, Carsten; Schmidt, Marcus

2013-01-01

Several multigene tests have been developed for breast cancer patients to predict the individual risk of recurrence. Most of the first generation tests rely on proliferation-associated genes and are commonly carried out in central reference laboratories. Here, we describe the development of a second generation multigene assay, the EndoPredict test, a prognostic multigene expression test for estrogen receptor (ER) positive, human epidermal growth factor receptor (HER2) negative (ER+/HER2−) breast cancer patients. The EndoPredict gene signature was initially established in a large high-throughput microarray-based screening study. The key steps for biomarker identification are discussed in detail, in comparison to the establishment of other multigene signatures. After biomarker selection, genes and algorithms were transferred to a diagnostic platform (reverse transcription quantitative PCR (RT-qPCR)) to allow for assaying formalin-fixed, paraffin-embedded (FFPE) samples. A comprehensive analytical validation was performed and a prospective proficiency testing study with seven pathological laboratories finally proved that EndoPredict can be reliably used in the decentralized setting. Three independent large clinical validation studies (n = 2,257) demonstrated that EndoPredict offers independent prognostic information beyond current clinicopathological parameters and clinical guidelines. The review article summarizes several important steps that should be considered for the development process of a second generation multigene test and offers a means for transferring a microarray signature from the research laboratory to clinical practice. PMID:27605191

An algebraic homotopy method for generating quasi-three-dimensional grids for high-speed configurations

NASA Technical Reports Server (NTRS)

Moitra, Anutosh

1989-01-01

A fast and versatile procedure for algebraically generating boundary conforming computational grids for use with finite-volume Euler flow solvers is presented. A semi-analytic homotopic procedure is used to generate the grids. Grids generated in two-dimensional planes are stacked to produce quasi-three-dimensional grid systems. The body surface and outer boundary are described in terms of surface parameters. An interpolation scheme is used to blend between the body surface and the outer boundary in order to determine the field points. The method, albeit developed for analytically generated body geometries is equally applicable to other classes of geometries. The method can be used for both internal and external flow configurations, the only constraint being that the body geometries be specified in two-dimensional cross-sections stationed along the longitudinal axis of the configuration. Techniques for controlling various grid parameters, e.g., clustering and orthogonality are described. Techniques for treating problems arising in algebraic grid generation for geometries with sharp corners are addressed. A set of representative grid systems generated by this method is included. Results of flow computations using these grids are presented for validation of the effectiveness of the method.
RS-predictor: a new tool for predicting sites of cytochrome P450-mediated metabolism applied to CYP 3A4.

PubMed

Zaretzki, Jed; Bergeron, Charles; Rydberg, Patrik; Huang, Tao-wei; Bennett, Kristin P; Breneman, Curt M

2011-07-25

This article describes RegioSelectivity-Predictor (RS-Predictor), a new in silico method for generating predictive models of P450-mediated metabolism for drug-like compounds. Within this method, potential sites of metabolism (SOMs) are represented as "metabolophores": A concept that describes the hierarchical combination of topological and quantum chemical descriptors needed to represent the reactivity of potential metabolic reaction sites. RS-Predictor modeling involves the use of metabolophore descriptors together with multiple-instance ranking (MIRank) to generate an optimized descriptor weight vector that encodes regioselectivity trends across all cases in a training set. The resulting pathway-independent (O-dealkylation vs N-oxidation vs Csp(3) hydroxylation, etc.), isozyme-specific regioselectivity model may be used to predict potential metabolic liabilities. In the present work, cross-validated RS-Predictor models were generated for a set of 394 substrates of CYP 3A4 as a proof-of-principle for the method. Rank aggregation was then employed to merge independently generated predictions for each substrate into a single consensus prediction. The resulting consensus RS-Predictor models were shown to reliably identify at least one observed site of metabolism in the top two rank-positions on 78% of the substrates. Comparisons between RS-Predictor and previously described regioselectivity prediction methods reveal new insights into how in silico metabolite prediction methods should be compared.
De novo assembly and characterization of leaf transcriptome for the development of functional molecular markers of the extremophile multipurpose tree species Prosopis alba

PubMed Central

2013-01-01

Background Prosopis alba (Fabaceae) is an important native tree adapted to arid and semiarid regions of north-western Argentina which is of great value as multipurpose species. Despite its importance, the genomic resources currently available for the entire Prosopis genus are still limited. Here we describe the development of a leaf transcriptome and the identification of new molecular markers that could support functional genetic studies in natural and domesticated populations of this genus. Results Next generation DNA pyrosequencing technology applied to P. alba transcripts produced a total of 1,103,231 raw reads with an average length of 421 bp. De novo assembling generated a set of 15,814 isotigs and 71,101 non-assembled sequences (singletons) with an average of 991 bp and 288 bp respectively. A total of 39,000 unique singletons were identified after clustering natural and artificial duplicates from pyrosequencing reads. Regarding the non-redundant sequences or unigenes, 22,095 out of 54,814 were successfully annotated with Gene Ontology terms. Moreover, simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs) were searched, resulting in 5,992 and 6,236 markers, respectively, throughout the genome. For the validation of the the predicted SSR markers, a subset of 87 SSRs selected through functional annotation evidence was successfully amplified from six DNA samples of seedlings. From this analysis, 11 of these 87 SSRs were identified as polymorphic. Additionally, another set of 123 nuclear polymorphic SSRs were determined in silico, of which 50% have the probability of being effectively polymorphic. Conclusions This study generated a successful global analysis of the P. alba leaf transcriptome after bioinformatic and wet laboratory validations of RNA-Seq data. The limited set of molecular markers currently available will be significantly increased with the thousands of new markers that were identified in this study. This information will strongly contribute to genomics resources for P. alba functional analysis and genetics. Finally, it will also potentially contribute to the development of population-based genome studies in the genera. PMID:24125525
A Python tool to set up relative free energy calculations in GROMACS

PubMed Central

Klimovich, Pavel V.; Mobley, David L.

2015-01-01

Free energy calculations based on molecular dynamics (MD) simulations have seen a tremendous growth in the last decade. However, it is still difficult and tedious to set them up in an automated manner, as the majority of the present-day MD simulation packages lack that functionality. Relative free energy calculations are a particular challenge for several reasons, including the problem of finding a common substructure and mapping the transformation to be applied. Here we present a tool, alchemical-setup.py, that automatically generates all the input files needed to perform relative solvation and binding free energy calculations with the MD package GROMACS. When combined with Lead Optimization Mapper [14], recently developed in our group, alchemical-setup.py allows fully automated setup of relative free energy calculations in GROMACS. Taking a graph of the planned calculations and a mapping, both computed by LOMAP, our tool generates the topology and coordinate files needed to perform relative free energy calculations for a given set of molecules, and provides a set of simulation input parameters. The tool was validated by performing relative hydration free energy calculations for a handful of molecules from the SAMPL4 challenge [16]. Good agreement with previously published results and the straightforward way in which free energy calculations can be conducted make alchemical-setup.py a promising tool for automated setup of relative solvation and binding free energy calculations. PMID:26487189
Results for the Aboveground Configuration of the Boiling Water Reactor Dry Cask Simulator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Durbin, Samuel G.; Lindgren, Eric R.

The thermal performance of commercial nuclear spent fuel dry storage casks is evaluated through detailed numerical analysis. These modeling efforts are completed by the vendor to demonstrate performance and regulatory compliance. The calculations are then independently verified by the Nuclear Regulatory Commission (NRC). Carefully measured data sets generated from testing of full-sized casks or smaller cask analogs are widely recognized as vital for validating these models. Recent advances in dry storage cask designs have significantly increased the maximum thermal load allowed in a cask, in part by increasing the efficiency of internal conduction pathways, and also by increasing the internalmore » convection through greater canister helium pressure. These same canistered cask systems rely on ventilation between the canister and the overpack to convect heat away from the canister to the environment for both above- and below-ground configurations. While several testing programs have been previously conducted, these earlier validation attempts did not capture the effects of elevated helium pressures or accurately portray the external convection of above-ground and below-ground canistered dry cask systems. The purpose of the current investigation was to produce data sets that can be used to test the validity of the assumptions associated with the calculations used to determine steady-state cladding temperatures in modern dry casks that utilize elevated helium pressure in the sealed canister in an above-ground configuration.« less
hEIDI: An Intuitive Application Tool To Organize and Treat Large-Scale Proteomics Data.

PubMed

Hesse, Anne-Marie; Dupierris, Véronique; Adam, Claire; Court, Magali; Barthe, Damien; Emadali, Anouk; Masselon, Christophe; Ferro, Myriam; Bruley, Christophe

2016-10-07

Advances in high-throughput proteomics have led to a rapid increase in the number, size, and complexity of the associated data sets. Managing and extracting reliable information from such large series of data sets require the use of dedicated software organized in a consistent pipeline to reduce, validate, exploit, and ultimately export data. The compilation of multiple mass-spectrometry-based identification and quantification results obtained in the context of a large-scale project represents a real challenge for developers of bioinformatics solutions. In response to this challenge, we developed a dedicated software suite called hEIDI to manage and combine both identifications and semiquantitative data related to multiple LC-MS/MS analyses. This paper describes how, through a user-friendly interface, hEIDI can be used to compile analyses and retrieve lists of nonredundant protein groups. Moreover, hEIDI allows direct comparison of series of analyses, on the basis of protein groups, while ensuring consistent protein inference and also computing spectral counts. hEIDI ensures that validated results are compliant with MIAPE guidelines as all information related to samples and results is stored in appropriate databases. Thanks to the database structure, validated results generated within hEIDI can be easily exported in the PRIDE XML format for subsequent publication. hEIDI can be downloaded from http://biodev.extra.cea.fr/docs/heidi .
Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing

PubMed Central

Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

2018-01-01

Aims A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R2), using R2 as the primary metric of assay agreement. However, the use of R2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. Methods We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Results Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. Conclusions The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. PMID:28747393
Stochastic inversion of ocean color data using the cross-entropy method.

PubMed

Salama, Mhd Suhyb; Shen, Fang

2010-01-18

Improving the inversion of ocean color data is an ever continuing effort to increase the accuracy of derived inherent optical properties. In this paper we present a stochastic inversion algorithm to derive inherent optical properties from ocean color, ship and space borne data. The inversion algorithm is based on the cross-entropy method where sets of inherent optical properties are generated and converged to the optimal set using iterative process. The algorithm is validated against four data sets: simulated, noisy simulated in-situ measured and satellite match-up data sets. Statistical analysis of validation results is based on model-II regression using five goodness-of-fit indicators; only R2 and root mean square of error (RMSE) are mentioned hereafter. Accurate values of total absorption coefficient are derived with R2 > 0.91 and RMSE, of log transformed data, less than 0.55. Reliable values of the total backscattering coefficient are also obtained with R2 > 0.7 (after removing outliers) and RMSE < 0.37. The developed algorithm has the ability to derive reliable results from noisy data with R2 above 0.96 for the total absorption and above 0.84 for the backscattering coefficients. The algorithm is self contained and easy to implement and modify to derive the variability of chlorophyll-a absorption that may correspond to different phytoplankton species. It gives consistently accurate results and is therefore worth considering for ocean color global products.
Analysis of 23 364 patient-generated, physician-reviewed malpractice claims from a non-tort, blame-free, national patient insurance system: lessons learned from Sweden.

PubMed

Pukk-Härenstam, K; Ask, J; Brommels, M; Thor, J; Penaloza, R V; Gaffney, F A

2009-02-01

In Sweden, patient malpractice claims are handled administratively and compensated if an independent physician review confirms patient injury resulting from medical error. Full access to all malpractice claims and hospital discharge data for the country provided a unique opportunity to assess the validity of patient claims as indicators of medical error and patient injury. To determine: (1) the percentage of patient malpractice claims validated by independent physician review, (2) actual malpractice claims rates (claims frequency / clinical volume) and (3) differences between Swedish and other national malpractice claims rates. DESIGN, SETTING AND MATERIAL: Swedish national malpractice claims and hospital discharge data were combined, and malpractice claims rates were determined by county, hospital, hospital department, surgical procedure, patient age and sex and compared with published studies on medical error and malpractice. From 1997 to 2004, there were 23 364 inpatient malpractice claims filed by Swedish patients treated at hospitals reporting 11 514 798 discharges. The overall claims rate, 0.20%, was stable over the period of study and was similar to that found in other tort and administrative compensation systems. Over this 8-year period, 49.5% (range 47.0-52.6%) of filed claims were judged valid and eligible for compensation. Claims rates varied significantly across hospitals; surgical specialties accounted for 46% of discharges, but 88% of claims. There were also large differences in claims rates for procedures. Patient-generated malpractice claims, as collected in the Swedish malpractice insurance system and adjusted for clinical volumes, have a high validity, as assessed by standardised physician review, and provide unique new information on malpractice risks, preventable medical errors and patient injuries. Systematic collection and analysis of patient-generated quality of care complaints should be encouraged, regardless of the malpractice compensation system in use.
An example of requirements for Advanced Subsonic Civil Transport (ASCT) flight control system using structured techniques

NASA Technical Reports Server (NTRS)

Mclees, Robert E.; Cohen, Gerald C.

1991-01-01

The requirements are presented for an Advanced Subsonic Civil Transport (ASCT) flight control system generated using structured techniques. The requirements definition starts from initially performing a mission analysis to identify the high level control system requirements and functions necessary to satisfy the mission flight. The result of the study is an example set of control system requirements partially represented using a derivative of Yourdon's structured techniques. Also provided is a research focus for studying structured design methodologies and in particular design-for-validation philosophies.
Bayesian Exploratory Factor Analysis

PubMed Central

Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi

2014-01-01

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements. PMID:25431517
Multi-physics modelling approach for oscillatory microengines: application for a microStirling generator design

NASA Astrophysics Data System (ADS)

Formosa, F.; Fréchette, L. G.

2015-12-01

An electrical circuit equivalent (ECE) approach has been set up allowing elementary oscillatory microengine components to be modelled. They cover gas channel/chamber thermodynamics, viscosity and thermal effects, mechanical structure and electromechanical transducers. The proposed tool has been validated on a centimeter scale Free Piston membrane Stirling engine [1]. We propose here new developments taking into account scaling effects to establish models suitable for any microengines. They are based on simplifications derived from the comparison of the hydraulic radius with respect to the viscous and thermal penetration depths respectively).
Parameterization of Model Validating Sets for Uncertainty Bound Optimizations. Revised

NASA Technical Reports Server (NTRS)

Lim, K. B.; Giesy, D. P.

2000-01-01

Given measurement data, a nominal model and a linear fractional transformation uncertainty structure with an allowance on unknown but bounded exogenous disturbances, easily computable tests for the existence of a model validating uncertainty set are given. Under mild conditions, these tests are necessary and sufficient for the case of complex, nonrepeated, block-diagonal structure. For the more general case which includes repeated and/or real scalar uncertainties, the tests are only necessary but become sufficient if a collinearity condition is also satisfied. With the satisfaction of these tests, it is shown that a parameterization of all model validating sets of plant models is possible. The new parameterization is used as a basis for a systematic way to construct or perform uncertainty tradeoff with model validating uncertainty sets which have specific linear fractional transformation structure for use in robust control design and analysis. An illustrative example which includes a comparison of candidate model validating sets is given.
Older adult mistreatment risk screening: contribution to the validation of a screening tool in a domestic setting.

PubMed

Lindenbach, Jeannette M; Larocque, Sylvie; Lavoie, Anne-Marise; Garceau, Marie-Luce

2012-06-01

ABSTRACTThe hidden nature of older adult mistreatment renders its detection in the domestic setting particularly challenging. A validated screening instrument that can provide a systematic assessment of risk factors can facilitate this detection. One such instrument, the "expanded Indicators of Abuse" tool, has been previously validated in the Hebrew language in a hospital setting. The present study has contributed to the validation of the "e-IOA" in an English-speaking community setting in Ontario, Canada. It consisted of two phases: (a) a content validity review and adaptation of the instrument by experts throughout Ontario, and (b) an inter-rater reliability assessment by home visiting nurses. The adaptation, the "Mistreatment of Older Adult Risk Factors" tool, offers a comprehensive tool for screening in the home setting. This instrument is significant to professional practice as practitioners working with older adults will be better equipped to assess for risk of mistreatment.
When is the Anelastic Approximation a Valid Model for Compressible Convection?

NASA Astrophysics Data System (ADS)

Alboussiere, T.; Curbelo, J.; Labrosse, S.; Ricard, Y. R.; Dubuffet, F.

2017-12-01

Compressible convection is ubiquitous in large natural systems such Planetary atmospheres, stellar and planetary interiors. Its modelling is notoriously more difficult than the case when the Boussinesq approximation applies. One reason for that difficulty has been put forward by Ogura and Phillips (1961): the compressible equations generate sound waves with very short time scales which need to be resolved. This is why they introduced an anelastic model, based on an expansion of the solution around an isentropic hydrostatic profile. How accurate is that anelastic model? What are the conditions for its validity? To answer these questions, we have developed a numerical model for the full set of compressible equations and compared its solutions with those of the corresponding anelastic model. We considered a simple rectangular 2D Rayleigh-Bénard configuration and decided to restrict the analysis to infinite Prandtl numbers. This choice is valid for convection in the mantles of rocky planets, but more importantly lead to a zero Mach number. So we got rid of the question of the interference of acoustic waves with convection. In that simplified context, we used the entropy balances (that of the full set of equations and that of the anelastic model) to investigate the differences between exact and anelastic solutions. We found that the validity of the anelastic model is dictated by two conditions: first, the superadiabatic temperature difference must be small compared with the adiabatic temperature difference (as expected) ɛ = Δ TSA / delta Ta << 1, and secondly that the product of ɛ with the Nusselt number must be small.
Development and psychometric testing of the Nurse Practitioner Primary Care Organizational Climate Questionnaire.

PubMed

Poghosyan, Lusine; Nannini, Angela; Finkelstein, Stacey R; Mason, Emanuel; Shaffer, Jonathan A

2013-01-01

Policy makers and healthcare organizations are calling for expansion of the nurse practitioner (NP) workforce in primary care settings to assure timely access and high-quality care for the American public. However, many barriers, including those at the organizational level, exist that may undermine NP workforce expansion and their optimal utilization in primary care. This study developed a new NP-specific survey instrument, Nurse Practitioner Primary Care Organizational Climate Questionnaire (NP-PCOCQ), to measure organizational climate in primary care settings and conducted its psychometric testing. Using instrument development design, the organizational climate domain pertinent for primary care NPs was identified. Items were generated from the evidence and qualitative data. Face and content validity were established through two expert meetings. Content validity index was computed. The 86-item pool was reduced to 55 items, which was pilot tested with 81 NPs using mailed surveys and then field-tested with 278 NPs in New York State. SPSS 18 and Mplus software were used for item analysis, reliability testing, and maximum likelihood exploratory factor analysis. Nurse Practitioner Primary Care Organizational Climate Questionnaire had face and content validity. The content validity index was .90. Twenty-nine items loaded on four subscale factors: professional visibility, NP-administration relations, NP-physician relations, and independent practice and support. The subscales had high internal consistency reliability. Cronbach's alphas ranged from.87 to .95. Having a strong instrument is important to promote future research. Also, administrators can use it to assess organizational climate in their clinics and propose interventions to improve it, thus promoting NP practice and the expansion of NP workforce.
Validity of food consumption indicators in the Lao context: moving toward cross-cultural standardization.

PubMed

Baumann, Soo Mee; Webb, Patrick; Zeller, Manfred

2013-03-01

Cross-cultural validity of food security indicators is commonly presumed without questioning the suitability of generic indicators in different geographic settings. However, ethnic differences in the perception of and reporting on, food insecurity, as well as variations in consumption patterns, may limit the comparability of results. Although research on correction factors for standardization of food security indicators is in process, so far no universal indicator has been identified. The current paper considers the ability of the Food Consumption Score (FCS) developed by the World Food Programme in southern Africa in 1996 to meet the requirement of local cultural validity in a Laotian context. The analysis is based on research that seeks to identify options for correcting possible biases linked to cultural disparities. Based on the results of a household survey conducted in different agroecological zones of Laos in 2009, the FCS was validated against a benchmark of calorie consumption. Changing the thresholds and excluding small amounts of food items consumed were tested as options to correct for biases caused by cultural disparities. The FCS in its original form underestimates the food insecurity level in the surveyed villages. However, the closeness of fit of the FCS to the benchmark classification improves when small amounts of food items are excluded from the assessment. Further research in different cultural settings is required to generate more insight into the extent to which universal thresholds can be applied to dietary diversity indicators with or without locally determined correction factors such as the exclusion of small amounts of food items.
Validation of the Minority Stress Scale Among Italian Gay and Bisexual Men

PubMed Central

Pala, Andrea Norcini; Dell’Amore, Francesca; Steca, Patrizia; Clinton, Lauren; Sandfort, Theodorus; Rael, Christine

2017-01-01

The experience of sexual orientation stigma (e.g., homophobic discrimination and physical aggression) generates minority stress, a chronic form of psychosocial stress. Minority stress has been shown to have a negative effect on gay and bisexual men’s (GBM’s) mental and physical health, increasing the rates of depression, suicidal ideation, and HIV risk behaviors. In conservative religious settings, such as Italy, sexual orientation stigma can be more frequently and/or more intensively experienced. However, minority stress among Italian GBM remains understudied. The aim of this study was to explore the dimensionality, internal reliability, and convergent validity of the Minority Stress Scale (MSS), a comprehensive instrument designed to assess the manifestations of sexual orientation stigma. The MSS consists of 50 items assessing (a) Structural Stigma, (b) Enacted Stigma, (c) Expectations of Discrimination, (d) Sexual Orientation Concealment, (e) Internalized Homophobia Toward Others, (f) Internalized Homophobia toward Oneself, and (g) Stigma Awareness. We recruited an online sample of 451 Italian GBM to take the MSS. We tested convergent validity using the Perceived Stress Questionnaire. Through exploratory factor analysis, we extracted the 7 theoretical factors and an additional 3-item factor assessing Expectations of Discrimination From Family Members. The MSS factors showed good internal reliability (ordinal α > .81) and good convergent validity. Our scale can be suitable for applications in research settings, psychosocial interventions, and, potentially, in clinical practice. Future studies will be conducted to further investigate the properties of the MSS, exploring the association with additional health-related measures (e.g., depressive symptoms and anxiety). PMID:29479555
Development and Validation of a Polarimetric-MCScene 3D Atmospheric Radiation Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berk, Alexander; Hawes, Frederick; Fox, Marsha

2016-03-15

Polarimetric measurements can substantially enhance the ability of both spectrally resolved and single band imagery to detect the proliferation of weapons of mass destruction, providing data for locating and identifying facilities, materials, and processes of undeclared and proliferant nuclear weapons programs worldwide. Unfortunately, models do not exist that efficiently and accurately predict spectral polarized signatures for the materials of interest embedded in complex 3D environments. Having such a model would enable one to test hypotheses and optimize both the enhancement of scene contrast and the signal processing for spectral signature extraction. The Phase I set the groundwork for development ofmore » fully validated polarimetric spectral signature and scene simulation models. This has been accomplished 1. by (a) identifying and downloading state-of-the-art surface and atmospheric polarimetric data sources, (b) implementing tools for generating custom polarimetric data, and (c) identifying and requesting US Government funded field measurement data for use in validation; 2. by formulating an approach for upgrading the radiometric spectral signature model MODTRAN to generate polarimetric intensities through (a) ingestion of the polarimetric data, (b) polarimetric vectorization of existing MODTRAN modules, and (c) integration of a newly developed algorithm for computing polarimetric multiple scattering contributions; 3. by generating an initial polarimetric model that demonstrates calculation of polarimetric solar and lunar single scatter intensities arising from the interaction of incoming irradiances with molecules and aerosols; 4. by developing a design and implementation plan to (a) automate polarimetric scene construction and (b) efficiently sample polarimetric scattering and reflection events, for use in a to be developed polarimetric version of the existing first-principles synthetic scene simulation model, MCScene; and 5. by planning a validation field measurement program in collaboration with the Remote Sensing and Exploitation group at Sandia National Laboratories (SNL) in which data from their ongoing polarimetric field and laboratory measurement program will be shared and, to the extent allowed, tailored for model validation in exchange for model predictions under conditions and for geometries outside of their measurement domain.« less
Smartphone-Based Self-Assessment of Stress in Healthy Adult Individuals: A Systematic Review

PubMed Central

Þórarinsdóttir, Helga; Kessing, Lars Vedel

2017-01-01

Background Stress is a common experience in today’s society. Smartphone ownership is widespread, and smartphones can be used to monitor health and well-being. Smartphone-based self-assessment of stress can be done in naturalistic settings and may potentially reflect real-time stress level. Objective The objectives of this systematic review were to evaluate (1) the use of smartphones to measure self-assessed stress in healthy adult individuals, (2) the validity of smartphone-based self-assessed stress compared with validated stress scales, and (3) the association between smartphone-based self-assessed stress and smartphone generated objective data. Methods A systematic review of the scientific literature was reported and conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. The scientific databases PubMed, PsycINFO, Embase, IEEE, and ACM were searched and supplemented by a hand search of reference lists. The databases were searched for original studies involving healthy individuals older than 18 years, measuring self-assessed stress using smartphones. Results A total of 35 published articles comprising 1464 individuals were included for review. According to the objectives, (1) study designs were heterogeneous, and smartphone-based self-assessed stress was measured using various methods (e.g., dichotomized questions on stress, yes or no; Likert scales on stress; and questionnaires); (2) the validity of smartphone-based self-assessed stress compared with validated stress scales was investigated in 3 studies, and of these, only 1 study found a moderate statistically significant positive correlation (r=.4; P<.05); and (3) in exploratory analyses, smartphone-based self-assessed stress was found to correlate with some of the reported smartphone generated objective data, including voice features and data on activity and phone usage. Conclusions Smartphones are being used to measure self-assessed stress in different contexts. The evidence of the validity of smartphone-based self-assessed stress is limited and should be investigated further. Smartphone generated objective data can potentially be used to monitor, predict, and reduce stress levels. PMID:28193600

Smartphone-Based Self-Assessment of Stress in Healthy Adult Individuals: A Systematic Review.

PubMed

Þórarinsdóttir, Helga; Kessing, Lars Vedel; Faurholt-Jepsen, Maria

2017-02-13

Stress is a common experience in today's society. Smartphone ownership is widespread, and smartphones can be used to monitor health and well-being. Smartphone-based self-assessment of stress can be done in naturalistic settings and may potentially reflect real-time stress level. The objectives of this systematic review were to evaluate (1) the use of smartphones to measure self-assessed stress in healthy adult individuals, (2) the validity of smartphone-based self-assessed stress compared with validated stress scales, and (3) the association between smartphone-based self-assessed stress and smartphone generated objective data. A systematic review of the scientific literature was reported and conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. The scientific databases PubMed, PsycINFO, Embase, IEEE, and ACM were searched and supplemented by a hand search of reference lists. The databases were searched for original studies involving healthy individuals older than 18 years, measuring self-assessed stress using smartphones. A total of 35 published articles comprising 1464 individuals were included for review. According to the objectives, (1) study designs were heterogeneous, and smartphone-based self-assessed stress was measured using various methods (e.g., dichotomized questions on stress, yes or no; Likert scales on stress; and questionnaires); (2) the validity of smartphone-based self-assessed stress compared with validated stress scales was investigated in 3 studies, and of these, only 1 study found a moderate statistically significant positive correlation (r=.4; P<.05); and (3) in exploratory analyses, smartphone-based self-assessed stress was found to correlate with some of the reported smartphone generated objective data, including voice features and data on activity and phone usage. Smartphones are being used to measure self-assessed stress in different contexts. The evidence of the validity of smartphone-based self-assessed stress is limited and should be investigated further. Smartphone generated objective data can potentially be used to monitor, predict, and reduce stress levels. ©Helga Þórarinsdóttir, Lars Vedel Kessing, Maria Faurholt-Jepsen. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 13.02.2017.
Development and psychometric testing of the Carter Assessment of Critical Thinking in Midwifery (Preceptor/Mentor version).

PubMed

Carter, Amanda G; Creedy, Debra K; Sidebotham, Mary

2016-03-01

develop and test a tool designed for use by preceptors/mentors to assess undergraduate midwifery students׳ critical thinking in practice. a descriptive cohort design was used. participants worked in a range of maternity settings in Queensland, Australia. 106 midwifery clinicians who had acted in the role of preceptor for undergraduate midwifery students. this study followed a staged model for tool development recommended by DeVellis (2012). This included generation of items, content validity testing through mapping of draft items to critical thinking concepts and expert review, administration of items to a convenience sample of preceptors, and psychometric testing. A 24 item tool titled the XXXX Assessment of Critical Thinking in Midwifery (CACTiM) was completed by registered midwives in relation to students they had recently preceptored in the clinical environment. ratings by experts revealed a content validity index score of 0.97, representing good content validity. An evaluation of construct validity through factor analysis generated three factors: 'partnership in practice', 'reflection on practice' and 'practice improvements'. The scale demonstrated good internal reliability with a Cronbach alpha coefficient of 0.97. The mean total score for the CACTiM scale was 116.77 (SD=16.68) with a range of 60-144. Total and subscale scores correlated significantly. the CACTiM (Preceptor/Mentor version) was found to be a valid and reliable tool for use by preceptors to assess critical thinking in undergraduate midwifery students. given the importance of critical thinking skills for midwifery practice, mapping and assessing critical thinking development in students׳ practice across an undergraduate programme is vital. The CACTiM (Preceptor/Mentor version) has utility for clinical education, research and practice. The tool can inform and guide preceptors׳ assessment of students׳ critical thinking in practice. The availability of a reliable and valid tool can be used to research the development of critical thinking in practice. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.
Cross-cultural validation and psychometric evaluation of the Participation and Environment Measure for Children and Youth in Korea.

PubMed

Jeong, Yunwha; Law, Mary; Stratford, Paul; DeMatteo, Carol; Kim, Hwan

2016-11-01

To develop the Korean version of the Participation and Environment Measure for Children and Youth (KPEM-CY) and examine its psychometric properties. The PEM-CY was cross-culturally translated into Korean using a specific guideline: pre-review of participation items, forward/backward translation, expert committee review, pre-test of the KPEM-CY and final review. To establish internal consistency, test-retest reliability and construct validity of the KPEM-CY, 80 parents of children with disabilities aged 5-13 years were recruited in South Korea. Across the home, school and community settings, 76% of participation items and 29% of environment items were revised to improve their fit with Korean culture. Internal consistency was moderate to excellent (0.67-0.92) for different summary scores. Test-retest reliability was excellent (>0.75) in the summary scores of participation frequency and extent of involvement across the three settings and moderate to excellent (0.53-0.95) in all summary scores at home. Child's age, type of school and annual income were the factors that significantly influenced specific dimensions of participation and environment across all settings. Results indicated that the KPEM-CY is equivalent to the original PEM-CY and has initial evidence of reliability and validity for use with Korean children with disabilities. Implications for rehabilitation Because 'participation' is a key outcome of the rehabilitation, measuring comprehensive participation of children with disabilities is necessary. The PEM-CY is a parent-report survey measure to assess comprehensive participation of children and youth and environment, which affect their participation, at home, school and in the community. A cross-cultural adaptation process is mandatory to adapt the measurement tool to a new culture or country. The Korean PEM-CY has both reliability and validity and can therefore generate useful clinical data for Korean children with disabilities.
High-throughput prediction of eucalypt lignin syringyl/guaiacyl content using multivariate analysis: a comparison between mid-infrared, near-infrared, and Raman spectroscopies for model development

PubMed Central

2014-01-01

Background In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). Results The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. Conclusion Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks. PMID:24955114
Assessing the validity of commercial and municipal food environment data sets in Vancouver, Canada.

PubMed

Daepp, Madeleine Ig; Black, Jennifer

2017-10-01

The present study assessed systematic bias and the effects of data set error on the validity of food environment measures in two municipal and two commercial secondary data sets. Sensitivity, positive predictive value (PPV) and concordance were calculated by comparing two municipal and two commercial secondary data sets with ground-truthed data collected within 800 m buffers surrounding twenty-six schools. Logistic regression examined associations of sensitivity and PPV with commercial density and neighbourhood socio-economic deprivation. Kendall's τ estimated correlations between density and proximity of food outlets near schools constructed with secondary data sets v. ground-truthed data. Vancouver, Canada. Food retailers located within 800 m of twenty-six schools RESULTS: All data sets scored relatively poorly across validity measures, although, overall, municipal data sets had higher levels of validity than did commercial data sets. Food outlets were more likely to be missing from municipal health inspections lists and commercial data sets in neighbourhoods with higher commercial density. Still, both proximity and density measures constructed from all secondary data sets were highly correlated (Kendall's τ>0·70) with measures constructed from ground-truthed data. Despite relatively low levels of validity in all secondary data sets examined, food environment measures constructed from secondary data sets remained highly correlated with ground-truthed data. Findings suggest that secondary data sets can be used to measure the food environment, although estimates should be treated with caution in areas with high commercial density.
The Utrecht questionnaire (U-CEP) measuring knowledge on clinical epidemiology proved to be valid.

PubMed

Kortekaas, Marlous F; Bartelink, Marie-Louise E L; de Groot, Esther; Korving, Helen; de Wit, Niek J; Grobbee, Diederick E; Hoes, Arno W

2017-02-01

Knowledge on clinical epidemiology is crucial to practice evidence-based medicine. We describe the development and validation of the Utrecht questionnaire on knowledge on Clinical epidemiology for Evidence-based Practice (U-CEP); an assessment tool to be used in the training of clinicians. The U-CEP was developed in two formats: two sets of 25 questions and a combined set of 50. The validation was performed among postgraduate general practice (GP) trainees, hospital trainees, GP supervisors, and experts. Internal consistency, internal reliability (item-total correlation), item discrimination index, item difficulty, content validity, construct validity, responsiveness, test-retest reliability, and feasibility were assessed. The questionnaire was externally validated. Internal consistency was good with a Cronbach alpha of 0.8. The median item-total correlation and mean item discrimination index were satisfactory. Both sets were perceived as relevant to clinical practice. Construct validity was good. Both sets were responsive but failed on test-retest reliability. One set took 24 minutes and the other 33 minutes to complete, on average. External GP trainees had comparable results. The U-CEP is a valid questionnaire to assess knowledge on clinical epidemiology, which is a prerequisite for practicing evidence-based medicine in daily clinical practice. Copyright © 2016 Elsevier Inc. All rights reserved.
Risk assessment paradigm: an opportunity for rationalizing the choice of biological indicator during the validation of isolator biodecontamination cycles.

PubMed

Sansoë-Bourget, Emmanuelle

2006-01-01

The use of biological indicators is integral to the validation of isolator decontamination cycles. The difficulty in setting up the initial qualification of the decontamination cycle and especially the successive requalifications may vary as a function of not only the installation to be qualified and the sterilizing agent and generator used, but also as a function of the type of biological indicators used. In this article the manufacture and control of biological indicators are analyzed using the hazard analysis and critical control point (HACCP) approach. The HACCP risk analysis, which must take into account the application of the isolator being qualified or requalified, is an efficient simplification tool for performing a decontamination cycle using either hydrogen peroxide gas or peracetic acid in a reliable, economical, and reproducible way.
Mappability of drug-like space: towards a polypharmacologically competent map of drug-relevant compounds

NASA Astrophysics Data System (ADS)

Sidorov, Pavel; Gaspar, Helena; Marcou, Gilles; Varnek, Alexandre; Horvath, Dragos

2015-12-01

Intuitive, visual rendering—mapping—of high-dimensional chemical spaces (CS), is an important topic in chemoinformatics. Such maps were so far dedicated to specific compound collections—either limited series of known activities, or large, even exhaustive enumerations of molecules, but without associated property data. Typically, they were challenged to answer some classification problem with respect to those same molecules, admired for their aesthetical virtues and then forgotten—because they were set-specific constructs. This work wishes to address the question whether a general, compound set-independent map can be generated, and the claim of "universality" quantitatively justified, with respect to all the structure-activity information available so far—or, more realistically, an exploitable but significant fraction thereof. The "universal" CS map is expected to project molecules from the initial CS into a lower-dimensional space that is neighborhood behavior-compliant with respect to a large panel of ligand properties. Such map should be able to discriminate actives from inactives, or even support quantitative neighborhood-based, parameter-free property prediction (regression) models, for a wide panel of targets and target families. It should be polypharmacologically competent, without requiring any target-specific parameter fitting. This work describes an evolutionary growth procedure of such maps, based on generative topographic mapping, followed by the validation of their polypharmacological competence. Validation was achieved with respect to a maximum of exploitable structure-activity information, covering all of Homo sapiens proteins of the ChEMBL database, antiparasitic and antiviral data, etc. Five evolved maps satisfactorily solved hundreds of activity-based ligand classification challenges for targets, and even in vivo properties independent from training data. They also stood chemogenomics-related challenges, as cumulated responsibility vectors obtained by mapping of target-specific ligand collections were shown to represent validated target descriptors, complying with currently accepted target classification in biology. Therefore, they represent, in our opinion, a robust and well documented answer to the key question "What is a good CS map?"
Mappability of drug-like space: towards a polypharmacologically competent map of drug-relevant compounds.

PubMed

Sidorov, Pavel; Gaspar, Helena; Marcou, Gilles; Varnek, Alexandre; Horvath, Dragos

2015-12-01

Intuitive, visual rendering--mapping--of high-dimensional chemical spaces (CS), is an important topic in chemoinformatics. Such maps were so far dedicated to specific compound collections--either limited series of known activities, or large, even exhaustive enumerations of molecules, but without associated property data. Typically, they were challenged to answer some classification problem with respect to those same molecules, admired for their aesthetical virtues and then forgotten--because they were set-specific constructs. This work wishes to address the question whether a general, compound set-independent map can be generated, and the claim of "universality" quantitatively justified, with respect to all the structure-activity information available so far--or, more realistically, an exploitable but significant fraction thereof. The "universal" CS map is expected to project molecules from the initial CS into a lower-dimensional space that is neighborhood behavior-compliant with respect to a large panel of ligand properties. Such map should be able to discriminate actives from inactives, or even support quantitative neighborhood-based, parameter-free property prediction (regression) models, for a wide panel of targets and target families. It should be polypharmacologically competent, without requiring any target-specific parameter fitting. This work describes an evolutionary growth procedure of such maps, based on generative topographic mapping, followed by the validation of their polypharmacological competence. Validation was achieved with respect to a maximum of exploitable structure-activity information, covering all of Homo sapiens proteins of the ChEMBL database, antiparasitic and antiviral data, etc. Five evolved maps satisfactorily solved hundreds of activity-based ligand classification challenges for targets, and even in vivo properties independent from training data. They also stood chemogenomics-related challenges, as cumulated responsibility vectors obtained by mapping of target-specific ligand collections were shown to represent validated target descriptors, complying with currently accepted target classification in biology. Therefore, they represent, in our opinion, a robust and well documented answer to the key question "What is a good CS map?"
A novel classifier based on three preoperative tumor markers predicting the cancer-specific survival of gastric cancer (CEA, CA19-9 and CA72-4).

PubMed

Guo, Jing; Chen, Shangxiang; Li, Shun; Sun, Xiaowei; Li, Wei; Zhou, Zhiwei; Chen, Yingbo; Xu, Dazhi

2018-01-12

Several studies have highlighted the prognostic value of the individual and the various combinations of the tumor markers for gastric cancer (GC). Our study was designed to assess establish a new novel model incorporating carcino-embryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 72-4 (CA72-4). A total of 1,566 GC patients (Primary cohort) between Jan 2000 and July 2013 were analyzed. The Primary cohort was randomly divided into Training set (n=783) and Validation set (n=783). A three-tumor marker classifier was developed in the Training set and validated in the Validation set by multivariate regression and risk-score analysis. We have identified a three-tumor marker classifier (including CEA, CA19-9 and CA72-4) for the cancer specific survival (CSS) of GC (p<0.001). Consistent results were obtained in the both Training set and Validation set. Multivariate analysis showed that the classifier was an independent predictor of GC (All p value <0.001 in the Training set, Validation set and Primary cohort). Furthermore, when the leave-one-out approach was performed, the classifier showed superior predictive value to the individual or two of them (with the highest AUC (Area Under Curve); 0.618 for the Training set, and 0.625 for the Validation set), which ascertained its predictive value. Our three-tumor marker classifier is closely associated with the CSS of GC and may serve as a novel model for future decisions concerning treatments.
Validation and detection of vessel landmarks by using anatomical knowledge

NASA Astrophysics Data System (ADS)

Beck, Thomas; Bernhardt, Dominik; Biermann, Christina; Dillmann, Rüdiger

2010-03-01

The detection of anatomical landmarks is an important prerequisite to analyze medical images fully automatically. Several machine learning approaches have been proposed to parse 3D CT datasets and to determine the location of landmarks with associated uncertainty. However, it is a challenging task to incorporate high-level anatomical knowledge to improve these classification results. We propose a new approach to validate candidates for vessel bifurcation landmarks which is also applied to systematically search missed and to validate ambiguous landmarks. A knowledge base is trained providing human-readable geometric information of the vascular system, mainly vessel lengths, radii and curvature information, for validation of landmarks and to guide the search process. To analyze the bifurcation area surrounding a vessel landmark of interest, a new approach is proposed which is based on Fast Marching and incorporates anatomical information from the knowledge base. Using the proposed algorithms, an anatomical knowledge base has been generated based on 90 manually annotated CT images containing different parts of the body. To evaluate the landmark validation a set of 50 carotid datasets has been tested in combination with a state of the art landmark detector with excellent results. Beside the carotid bifurcation the algorithm is designed to handle a wide range of vascular landmarks, e.g. celiac, superior mesenteric, renal, aortic, iliac and femoral bifurcation.
Deep sequencing of natural and experimental populations of Drosophila melanogaster reveals biases in the spectrum of new mutations.

PubMed

Assaf, Zoe June; Tilk, Susanne; Park, Jane; Siegal, Mark L; Petrov, Dmitri A

2017-12-01

Mutations provide the raw material of evolution, and thus our ability to study evolution depends fundamentally on having precise measurements of mutational rates and patterns. We generate a data set for this purpose using (1) de novo mutations from mutation accumulation experiments and (2) extremely rare polymorphisms from natural populations. The first, mutation accumulation (MA) lines are the product of maintaining flies in tiny populations for many generations, therefore rendering natural selection ineffective and allowing new mutations to accrue in the genome. The second, rare genetic variation from natural populations allows the study of mutation because extremely rare polymorphisms are relatively unaffected by the filter of natural selection. We use both methods in Drosophila melanogaster , first generating our own novel data set of sequenced MA lines and performing a meta-analysis of all published MA mutations (∼2000 events) and then identifying a high quality set of ∼70,000 extremely rare (≤0.1%) polymorphisms that are fully validated with resequencing. We use these data sets to precisely measure mutational rates and patterns. Highlights of our results include: a high rate of multinucleotide mutation events at both short (∼5 bp) and long (∼1 kb) genomic distances, showing that mutation drives GC content lower in already GC-poor regions, and using our precise context-dependent mutation rates to predict long-term evolutionary patterns at synonymous sites. We also show that de novo mutations from independent MA experiments display similar patterns of single nucleotide mutation and well match the patterns of mutation found in natural populations. © 2017 Assaf et al.; Published by Cold Spring Harbor Laboratory Press.
A Generic Framework for Real-Time Multi-Channel Neuronal Signal Analysis, Telemetry Control, and Sub-Millisecond Latency Feedback Generation

PubMed Central

Zrenner, Christoph; Eytan, Danny; Wallach, Avner; Thier, Peter; Marom, Shimon

2010-01-01

Distinct modules of the neural circuitry interact with each other and (through the motor-sensory loop) with the environment, forming a complex dynamic system. Neuro-prosthetic devices seeking to modulate or restore CNS function need to interact with the information flow at the level of neural modules electrically, bi-directionally and in real-time. A set of freely available generic tools is presented that allow computationally demanding multi-channel short-latency bi-directional interactions to be realized in in vivo and in vitro preparations using standard PC data acquisition and processing hardware and software (Mathworks Matlab and Simulink). A commercially available 60-channel extracellular multi-electrode recording and stimulation set-up connected to an ex vivo developing cortical neuronal culture is used as a model system to validate the method. We demonstrate how complex high-bandwidth (>10 MBit/s) neural recording data can be analyzed in real-time while simultaneously generating specific complex electrical stimulation feedback with deterministically timed responses at sub-millisecond resolution. PMID:21060803
Cross-Modal Perception of Noise-in-Music: Audiences Generate Spiky Shapes in Response to Auditory Roughness in a Novel Electroacoustic Concert Setting

PubMed Central

Liew, Kongmeng; Lindborg, PerMagnus; Rodrigues, Ruth; Styles, Suzy J.

2018-01-01

Noise has become integral to electroacoustic music aesthetics. In this paper, we define noise as sound that is high in auditory roughness, and examine its effect on cross-modal mapping between sound and visual shape in participants. In order to preserve the ecological validity of contemporary music aesthetics, we developed Rama, a novel interface, for presenting experimentally controlled blocks of electronically generated sounds that varied systematically in roughness, and actively collected data from audience interaction. These sounds were then embedded as musical drones within the overall sound design of a multimedia performance with live musicians, Audience members listened to these sounds, and collectively voted to create the shape of a visual graphic, presented as part of the audio–visual performance. The results of the concert setting were replicated in a controlled laboratory environment to corroborate the findings. Results show a consistent effect of auditory roughness on shape design, with rougher sounds corresponding to spikier shapes. We discuss the implications, as well as evaluate the audience interface. PMID:29515494
Subgrid spatial variability of soil hydraulic functions for hydrological modelling

NASA Astrophysics Data System (ADS)

Kreye, Phillip; Meon, Günter

2016-07-01

State-of-the-art hydrological applications require a process-based, spatially distributed hydrological model. Runoff characteristics are demanded to be well reproduced by the model. Despite that, the model should be able to describe the processes at a subcatchment scale in a physically credible way. The objective of this study is to present a robust procedure to generate various sets of parameterisations of soil hydraulic functions for the description of soil heterogeneity on a subgrid scale. Relations between Rosetta-generated values of saturated hydraulic conductivity (Ks) and van Genuchten's parameters of soil hydraulic functions were statistically analysed. An universal function that is valid for the complete bandwidth of Ks values could not be found. After concentrating on natural texture classes, strong correlations were identified for all parameters. The obtained regression results were used to parameterise sets of hydraulic functions for each soil class. The methodology presented in this study is applicable on a wide range of spatial scales and does not need input data from field studies. The developments were implemented into a hydrological modelling system.
The baby boomer effect: changing patterns of substance abuse among adults ages 55 and older.

PubMed

Duncan, David F; Nicholson, Thomas; White, John B; Bradley, Dana Burr; Bonaguro, John

2010-07-01

Between now and 2030, the number of adults aged 65 and older in the United States will almost double, from around 37 million to more than 70 million, an increase from 12% of the U.S. population to almost 20%. It was long held that, with only a few isolated exceptions, substance abuse simply did not exist among this population. In light of the impact of the baby boom generation, this assumption may no longer be valid. The authors examined admissions of persons 55 years and older (n = 918,955) from the Treatment Episode Data Set (1998-2006). Total admissions with a primary drug problem with alcohol have remained relatively stable over this time. Admissions for problems with a primary drug other than alcohol have shown a steady and substantial increase. Clearly, data from the Treatment Episode Data Set indicate a coming wave of older addicts whose primary problem is not alcohol. The authors suspect that this wave is led primarily by the continuing emergence of the baby boomer generation.
Cross-Modal Perception of Noise-in-Music: Audiences Generate Spiky Shapes in Response to Auditory Roughness in a Novel Electroacoustic Concert Setting.

PubMed

Liew, Kongmeng; Lindborg, PerMagnus; Rodrigues, Ruth; Styles, Suzy J

2018-01-01

Noise has become integral to electroacoustic music aesthetics. In this paper, we define noise as sound that is high in auditory roughness, and examine its effect on cross-modal mapping between sound and visual shape in participants. In order to preserve the ecological validity of contemporary music aesthetics, we developed Rama , a novel interface, for presenting experimentally controlled blocks of electronically generated sounds that varied systematically in roughness, and actively collected data from audience interaction. These sounds were then embedded as musical drones within the overall sound design of a multimedia performance with live musicians, Audience members listened to these sounds, and collectively voted to create the shape of a visual graphic, presented as part of the audio-visual performance. The results of the concert setting were replicated in a controlled laboratory environment to corroborate the findings. Results show a consistent effect of auditory roughness on shape design, with rougher sounds corresponding to spikier shapes. We discuss the implications, as well as evaluate the audience interface.
Performance Analysis of Continuous Black-Box Optimization Algorithms via Footprints in Instance Space.

PubMed

Muñoz, Mario A; Smith-Miles, Kate A

2017-01-01

This article presents a method for the objective assessment of an algorithm's strengths and weaknesses. Instead of examining the performance of only one or more algorithms on a benchmark set, or generating custom problems that maximize the performance difference between two algorithms, our method quantifies both the nature of the test instances and the algorithm performance. Our aim is to gather information about possible phase transitions in performance, that is, the points in which a small change in problem structure produces algorithm failure. The method is based on the accurate estimation and characterization of the algorithm footprints, that is, the regions of instance space in which good or exceptional performance is expected from an algorithm. A footprint can be estimated for each algorithm and for the overall portfolio. Therefore, we select a set of features to generate a common instance space, which we validate by constructing a sufficiently accurate prediction model. We characterize the footprints by their area and density. Our method identifies complementary performance between algorithms, quantifies the common features of hard problems, and locates regions where a phase transition may lie.
Validity and validation of expert (Q)SAR systems.

PubMed

Hulzebos, E; Sijm, D; Traas, T; Posthumus, R; Maslankiewicz, L

2005-08-01

At a recent workshop in Setubal (Portugal) principles were drafted to assess the suitability of (quantitative) structure-activity relationships ((Q)SARs) for assessing the hazards and risks of chemicals. In the present study we applied some of the Setubal principles to test the validity of three (Q)SAR expert systems and validate the results. These principles include a mechanistic basis, the availability of a training set and validation. ECOSAR, BIOWIN and DEREK for Windows have a mechanistic or empirical basis. ECOSAR has a training set for each QSAR. For half of the structural fragments the number of chemicals in the training set is >4. Based on structural fragments and log Kow, ECOSAR uses linear regression to predict ecotoxicity. Validating ECOSAR for three 'valid' classes results in predictivity of > or = 64%. BIOWIN uses (non-)linear regressions to predict the probability of biodegradability based on fragments and molecular weight. It has a large training set and predicts non-ready biodegradability well. DEREK for Windows predictions are supported by a mechanistic rationale and literature references. The structural alerts in this program have been developed with a training set of positive and negative toxicity data. However, to support the prediction only a limited number of chemicals in the training set is presented to the user. DEREK for Windows predicts effects by 'if-then' reasoning. The program predicts best for mutagenicity and carcinogenicity. Each structural fragment in ECOSAR and DEREK for Windows needs to be evaluated and validated separately.
Viirs Land Science Investigator-Led Processing System

NASA Astrophysics Data System (ADS)

Devadiga, S.; Mauoka, E.; Roman, M. O.; Wolfe, R. E.; Kalb, V.; Davidson, C. C.; Ye, G.

2015-12-01

The objective of the NASA's Suomi National Polar Orbiting Partnership (S-NPP) Land Science Investigator-led Processing System (Land SIPS), housed at the NASA Goddard Space Flight Center (GSFC), is to produce high quality land products from the Visible Infrared Imaging Radiometer Suite (VIIRS) to extend the Earth System Data Records (ESDRs) developed from NASA's heritage Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the EOS Terra and Aqua satellites. In this paper we will present the functional description and capabilities of the S-NPP Land SIPS, including system development phases and production schedules, timeline for processing, and delivery of land science products based on coordination with the S-NPP Land science team members. The Land SIPS processing stream is expected to be operational by December 2016, generating land products either using the NASA science team delivered algorithms, or the "best-of" science algorithms currently in operation at NASA's Land Product Evaluation and Algorithm Testing Element (PEATE). In addition to generating the standard land science products through processing of the NASA's VIIRS Level 0 data record, the Land SIPS processing system is also used to produce a suite of near-real time products for NASA's application community. Land SIPS will also deliver the standard products, ancillary data sets, software and supporting documentation (ATBDs) to the assigned Distributed Active Archive Centers (DAACs) for archival and distribution. Quality assessment and validation will be an integral part of the Land SIPS processing system; the former being performed at Land Data Operational Product Evaluation (LDOPE) facility, while the latter under the auspices of the CEOS Working Group on Calibration & Validation (WGCV) Land Product Validation (LPV) Subgroup; adopting the best-practices and tools used to assess the quality of heritage EOS-MODIS products generated at the MODIS Adaptive Processing System (MODAPS).

Planck 2015 results. XII. Full focal plane simulations

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Castex, G.; Catalano, A.; Challinor, A.; Chamballu, A.; Chiang, H. C.; Christensen, P. R.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.-M.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Ghosh, T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Karakci, A.; Keihänen, E.; Keskitalo, R.; Kiiveri, K.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; Lindholm, V.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Roman, M.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Welikala, N.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

We present the 8th full focal plane simulation set (FFP8), deployed in support of the Planck 2015 results. FFP8 consists of 10 fiducial mission realizations reduced to 18 144 maps, together with the most massive suite of Monte Carlo realizations of instrument noise and CMB ever generated, comprising 104 mission realizations reduced to about 106 maps. The resulting maps incorporate the dominant instrumental, scanning, and data analysis effects, and the remaining subdominant effects will be included in future updates. Generated at a cost of some 25 million CPU-hours spread across multiple high-performance-computing (HPC) platforms, FFP8 is used to validate and verify analysis algorithms and their implementations, and to remove biases from and quantify uncertainties in the results of analyses of the real data.
Identification and Development of Items Comprising Organizational Citizenship Behaviors Among Pharmacy Faculty

PubMed Central

Semsick, Gretchen R.

2016-01-01

Objective. Identify behaviors that can compose a measure of organizational citizenship by pharmacy faculty. Methods. A four-round, modified Delphi procedure using open-ended questions (Round 1) was conducted with 13 panelists from pharmacy academia. The items generated were evaluated and refined for inclusion in subsequent rounds. A consensus was reached after completing four rounds. Results. The panel produced a set of 26 items indicative of extra-role behaviors by faculty colleagues considered to compose a measure of citizenship, which is an expressed manifestation of collegiality. Conclusions. The items generated require testing for validation and reliability in a large sample to create a measure of organizational citizenship. Even prior to doing so, the list of items can serve as a resource for mentorship of junior and senior faculty alike. PMID:28179717
Dimensional analysis of detrimental ozone generation by positive wire-to-plate corona discharge in air

NASA Astrophysics Data System (ADS)

Bo, Z.; Chen, J. H.

2010-02-01

The dimensional analysis technique is used to formulate a correlation between ozone generation rate and various parameters that are important in the design and operation of positive wire-to-plate corona discharges in indoor air. The dimensionless relation is determined by linear regression analysis based on the results from 36 laboratory-scale experiments. The derived equation is validated by experimental data and a numerical model published in the literature. Applications of such derived equation are illustrated through an example selection of the appropriate set of operating conditions in the design/operation of a photocopier to follow the federal regulations of ozone emission. Finally, a new current-voltage characteristic equation is proposed for positive wire-to-plate corona discharges based on the derived dimensionless equation.
Development, pilot testing and psychometric validation of a short version of the coronary artery disease education questionnaire: The CADE-Q SV.

PubMed

Ghisi, Gabriela Lima de Melo; Sandison, Nicole; Oh, Paul

2016-03-01

To develop, pilot test and psychometrically validate a shorter version of the coronary artery disease education questionnaire (CADE-Q), called CADE-Q SV. Based on previous versions of the CADE-Q, cardiac rehabilitation (CR) experts developed 20 items divided into 5 knowledge domains to comprise the first version of the CADE-Q SV. To establish content validity, they were reviewed by an expert panel (N=12). Refined items were pilot-tested in 20 patients, in which clarity was provided. A final version was generated and psychometrically-tested in 132CR patients. Test-retest reliability was assessed via the intraclass correlation coefficient (ICC), the internal consistency using Cronbach's alpha, and criterion validity with regard to patients' education and duration in CR. All ICC coefficients meet the minimum recommended standard. All domains were considered internally consistent (α>0.7). Criterion validity was supported by significant differences in mean scores by educational level (p<0.01) and duration in CR (p<0.05). Knowledge about exercise and nutrition was higher than knowledge about medical condition. The CADE-Q SV was demonstrated to have good reliability and validity. This is a short, quick and appropriate tool for application in clinical and research settings, assessing patients' knowledge during CR and as part of education programming. Copyright © 2015. Published by Elsevier Ireland Ltd.
Development and psychometric validation of a scale to assess information needs in cardiac rehabilitation: the INCR Tool.

PubMed

Ghisi, Gabriela Lima de Melo; Grace, Sherry L; Thomas, Scott; Evans, Michael F; Oh, Paul

2013-06-01

To develop and psychometrically validate a tool to assess information needs in cardiac rehabilitation (CR) patients. After a literature search, 60 information items divided into 11 areas of needs were identified. To establish content validity, they were reviewed by an expert panel (N=10). Refined items were pilot-tested in 34 patients on a 5-point Likert-scale from 1 "really not helpful" to 5 "very important". A final version was generated and psychometrically tested in 203 CR patients. Test-retest reliability was assessed via the intraclass correlation coefficient (ICC), the internal consistency using Cronbach's alpha, and criterion validity was assessed with regard to patient's education and duration in CR. Five items were excluded after ICC analysis as well as one area of needs. All 10 areas were considered internally consistent (Cronbach's alpha>0.7). Criterion validity was supported by significant differences in mean scores by educational level (p<0.05) and duration in CR (p<0.001). The mean total score was 4.08 ± 0.53. Patients rated safety as their greatest information need. The INCR Tool was demonstrated to have good reliability and validity. This is an appropriate tool for application in clinical and research settings, assessing patients' needs during CR and as part of education programming. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Large-scale road safety programmes in low- and middle-income countries: an opportunity to generate evidence.

PubMed

Hyder, Adnan A; Allen, Katharine A; Peters, David H; Chandran, Aruna; Bishai, David

2013-01-01

The growing burden of road traffic injuries, which kill over 1.2 million people yearly, falls mostly on low- and middle-income countries (LMICs). Despite this, evidence generation on the effectiveness of road safety interventions in LMIC settings remains scarce. This paper explores a scientific approach for evaluating road safety programmes in LMICs and introduces such a road safety multi-country initiative, the Road Safety in 10 Countries Project (RS-10). By building on existing evaluation frameworks, we develop a scientific approach for evaluating large-scale road safety programmes in LMIC settings. This also draws on '13 lessons' of large-scale programme evaluation: defining the evaluation scope; selecting study sites; maintaining objectivity; developing an impact model; utilising multiple data sources; using multiple analytic techniques; maximising external validity; ensuring an appropriate time frame; the importance of flexibility and a stepwise approach; continuous monitoring; providing feedback to implementers, policy-makers; promoting the uptake of evaluation results; and understanding evaluation costs. The use of relatively new approaches for evaluation of real-world programmes allows for the production of relevant knowledge. The RS-10 project affords an important opportunity to scientifically test these approaches for a real-world, large-scale road safety evaluation and generate new knowledge for the field of road safety.
Surface- and Contour-Preserving Origamic Architecture Paper Pop-Ups.

PubMed

Le, Sang N; Leow, Su-Jun; Le-Nguyen, Tuong-Vu; Ruiz, Conrado; Low, Kok-Lim

2013-08-02

Origamic architecture (OA) is a form of papercraft that involves cutting and folding a single sheet of paper to produce a 3D pop-up, and is commonly used to depict architectural structures. Because of the strict geometric and physical constraints, OA design requires considerable skill and effort. In this paper, we present a method to automatically generate an OA design that closely depicts an input 3D model. Our algorithm is guided by a novel set of geometric conditions to guarantee the foldability and stability of the generated pop-ups. The generality of the conditions allows our algorithm to generate valid pop-up structures that are previously not accounted for by other algorithms. Our method takes a novel image-domain approach to convert the input model to an OA design. It performs surface segmentation of the input model in the image domain, and carefully represents each surface with a set of parallel patches. Patches are then modified to make the entire structure foldable and stable. Visual and quantitative comparisons of results have shown our algorithm to be significantly better than the existing methods in the preservation of contours, surfaces and volume. The designs have also been shown to more closely resemble those created by real artists.
Surface and contour-preserving origamic architecture paper pop-ups.

PubMed

Le, Sang N; Leow, Su-Jun; Le-Nguyen, Tuong-Vu; Ruiz, Conrado; Low, Kok-Lim

2014-02-01

Origamic architecture (OA) is a form of papercraft that involves cutting and folding a single sheet of paper to produce a 3D pop-up, and is commonly used to depict architectural structures. Because of the strict geometric and physical constraints, OA design requires considerable skill and effort. In this paper, we present a method to automatically generate an OA design that closely depicts an input 3D model. Our algorithm is guided by a novel set of geometric conditions to guarantee the foldability and stability of the generated pop-ups. The generality of the conditions allows our algorithm to generate valid pop-up structures that are previously not accounted for by other algorithms. Our method takes a novel image-domain approach to convert the input model to an OA design. It performs surface segmentation of the input model in the image domain, and carefully represents each surface with a set of parallel patches. Patches are then modified to make the entire structure foldable and stable. Visual and quantitative comparisons of results have shown our algorithm to be significantly better than the existing methods in the preservation of contours, surfaces, and volume. The designs have also been shown to more closely resemble those created by real artists.
Polarization-modulated second harmonic generation ellipsometric microscopy at video rate.

PubMed

DeWalt, Emma L; Sullivan, Shane Z; Schmitt, Paul D; Muir, Ryan D; Simpson, Garth J

2014-08-19

Fast 8 MHz polarization modulation coupled with analytical modeling, fast beam-scanning, and synchronous digitization (SD) have enabled simultaneous nonlinear optical Stokes ellipsometry (NOSE) and polarized laser transmittance imaging with image acquisition rates up to video rate. In contrast to polarimetry, in which the polarization state of the exiting beam is recorded, NOSE enables recovery of the complex-valued Jones tensor of the sample that describes all polarization-dependent observables of the measurement. Every video-rate scan produces a set of 30 images (10 for each detector with three detectors operating in parallel), each of which corresponds to a different polarization-dependent result. Linear fitting of this image set contracts it down to a set of five parameters for each detector in second harmonic generation (SHG) and three parameters for the transmittance of the incident beam. These parameters can in turn be used to recover the Jones tensor elements of the sample. Following validation of the approach using z-cut quartz, NOSE microscopy was performed for microcrystals of both naproxen and glucose isomerase. When weighted by the measurement time, NOSE microscopy was found to provide a substantial (>7 decades) improvement in the signal-to-noise ratio relative to our previous measurements based on the rotation of optical elements and a 3-fold improvement relative to previous single-point NOSE approaches.
An Automatic and Robust Algorithm of Reestablishment of Digital Dental Occlusion

PubMed Central

Chang, Yu-Bing; Xia, James J.; Gateno, Jaime; Xiong, Zixiang; Zhou, Xiaobo; Wong, Stephen T. C.

2017-01-01

In the field of craniomaxillofacial (CMF) surgery, surgical planning can be performed on composite 3-D models that are generated by merging a computerized tomography scan with digital dental models. Digital dental models can be generated by scanning the surfaces of plaster dental models or dental impressions with a high-resolution laser scanner. During the planning process, one of the essential steps is to reestablish the dental occlusion. Unfortunately, this task is time-consuming and often inaccurate. This paper presents a new approach to automatically and efficiently reestablish dental occlusion. It includes two steps. The first step is to initially position the models based on dental curves and a point matching technique. The second step is to reposition the models to the final desired occlusion based on iterative surface-based minimum distance mapping with collision constraints. With linearization of rotation matrix, the alignment is modeled by solving quadratic programming. The simulation was completed on 12 sets of digital dental models. Two sets of dental models were partially edentulous, and another two sets have first premolar extractions for orthodontic treatment. Two validation methods were applied to the articulated models. The results show that using our method, the dental models can be successfully articulated with a small degree of deviations from the occlusion achieved with the gold-standard method. PMID:20529735
Pupil light reflex evoked by light-emitting diode and computer screen: Methodology and association with need for recovery in daily life.

PubMed

Wang, Yang; Zekveld, Adriana A; Wendt, Dorothea; Lunner, Thomas; Naylor, Graham; Kramer, Sophia E

2018-01-01

Pupil light reflex (PLR) has been widely used as a method for evaluating parasympathetic activity. The first aim of the present study is to develop a PLR measurement using a computer screen set-up and compare its results with the PLR generated by a more conventional setup using light-emitting diode (LED). The parasympathetic nervous system, which is known to control the 'rest and digest' response of the human body, is considered to be associated with daily life fatigue. However, only few studies have attempted to test the relationship between self-reported daily fatigue and physiological measurement of the parasympathetic nervous system. Therefore, the second aim of this study was to investigate the relationship between daily-life fatigue, assessed using the Need for Recovery scale, and parasympathetic activity, as indicated by the PLR parameters. A pilot study was conducted first to develop a PLR measurement set-up using a computer screen. PLRs evoked by light stimuli with different characteristics were recorded to confirm the influence of light intensity, flash duration, and color on the PLRs evoked by the system. In the subsequent experimental study, we recorded the PLR of 25 adult participants to light flashes generated by the screen set-up as well as by a conventional LED set-up. PLR parameters relating to parasympathetic and sympathetic activity were calculated from the pupil responses. We tested the split-half reliability across two consecutive blocks of trials, and the relationships between the parameters of PLRs evoked by the two set-ups. Participants rated their need for recovery prior to the PLR recordings. PLR parameters acquired in the screen and LED set-ups showed good reliability for amplitude related parameters. The PLRs evoked by both set-ups were consistent, but showed systematic differences in absolute values of all parameters. Additionally, higher need for recovery was associated with faster and larger constriction of the PLR. This study assessed the PLR generated by a computer screen and the PLR generated by a LED. The good reliability within set-ups and the consistency between the PLRs evoked by the set-ups indicate that both systems provides a valid way to evoke the PLR. A higher need for recovery was associated with faster and larger constricting PLRs, suggesting increased levels of parasympathetic nervous system activity in people experiencing higher levels of need for recovery on a daily basis.
A new approach for shaping of dual-reflector antennas

NASA Technical Reports Server (NTRS)

Lee, Teh-Hong; Burnside, W. D.; Rudduck, Roger C.

1987-01-01

The shaping of 2-D dual-reflector antenna systems to generate a prescribed distribution with uniform phase at the aperture of the second reflector is examined. This method is based on the geometrical nature of Cassegrain and Gregorian dual-reflector antennas. The method of syntheses satisfies the principles of geometrical optics which are the foundations of dual-reflector designs. Instead of setting up differential equations or heuristically designing the subreflector, a set of algebraic equations is formulated and solved numerically to obtain the desired surfaces. The caustics of the reflected rays from the subreflector can be obtained and examined. Several examples of 2-D dual-reflector shaping are shown to validate the study. Geometrical optics and physical optics are used to calculate the scattered fields from the reflectors.
Multi-time Scale Joint Scheduling Method Considering the Grid of Renewable Energy

NASA Astrophysics Data System (ADS)

Zhijun, E.; Wang, Weichen; Cao, Jin; Wang, Xin; Kong, Xiangyu; Quan, Shuping

2018-01-01

Renewable new energy power generation prediction error like wind and light, brings difficulties to dispatch the power system. In this paper, a multi-time scale robust scheduling method is set to solve this problem. It reduces the impact of clean energy prediction bias to the power grid by using multi-time scale (day-ahead, intraday, real time) and coordinating the dispatching power output of various power supplies such as hydropower, thermal power, wind power, gas power and. The method adopts the robust scheduling method to ensure the robustness of the scheduling scheme. By calculating the cost of the abandon wind and the load, it transforms the robustness into the risk cost and optimizes the optimal uncertainty set for the smallest integrative costs. The validity of the method is verified by simulation.
Control of stacking loads in final waste disposal according to the borehole technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feuser, W.; Barnert, E.; Vijgen, H.

1996-12-01

The semihydrostatic model has been developed in order to assess the mechanical toads acting on heat-generating ILW(Q) and HTGR fuel element waste packages to be emplaced in vertical boreholes according to the borehole technique in underground rock salt formations. For the experimental validation of the theory, laboratory test stands reduced in scale are set up to simulate the bottom section of a repository borehole. A comparison of the measurement results with the data computed by the model, a correlation between the test stand results, and a systematic determination of material-typical crushed salt parameters in a separate research project will servemore » to derive a set of characteristic equations enabling a description of real conditions in a future repository.« less
Novel Bioinformatics-Based Approach for Proteomic Biomarkers Prediction of Calpain-2 & Caspase-3 Protease Fragmentation: Application to βII-Spectrin Protein

NASA Astrophysics Data System (ADS)

El-Assaad, Atlal; Dawy, Zaher; Nemer, Georges; Kobeissy, Firas

2017-01-01

The crucial biological role of proteases has been visible with the development of degradomics discipline involved in the determination of the proteases/substrates resulting in breakdown-products (BDPs) that can be utilized as putative biomarkers associated with different biological-clinical significance. In the field of cancer biology, matrix metalloproteinases (MMPs) have shown to result in MMPs-generated protein BDPs that are indicative of malignant growth in cancer, while in the field of neural injury, calpain-2 and caspase-3 proteases generate BDPs fragments that are indicative of different neural cell death mechanisms in different injury scenarios. Advanced proteomic techniques have shown a remarkable progress in identifying these BDPs experimentally. In this work, we present a bioinformatics-based prediction method that identifies protease-associated BDPs with high precision and efficiency. The method utilizes state-of-the-art sequence matching and alignment algorithms. It starts by locating consensus sequence occurrences and their variants in any set of protein substrates, generating all fragments resulting from cleavage. The complexity exists in space O(mn) as well as in O(Nmn) time, where N, m, and n are the number of protein sequences, length of the consensus sequence, and length per protein sequence, respectively. Finally, the proposed methodology is validated against βII-spectrin protein, a brain injury validated biomarker.
Automatic control system generation for robot design validation

NASA Technical Reports Server (NTRS)

Bacon, James A. (Inventor); English, James D. (Inventor)

2012-01-01

The specification and drawings present a new method, system and software product for and apparatus for generating a robotic validation system for a robot design. The robotic validation system for the robot design of a robotic system is automatically generated by converting a robot design into a generic robotic description using a predetermined format, then generating a control system from the generic robotic description and finally updating robot design parameters of the robotic system with an analysis tool using both the generic robot description and the control system.
Coupling a regional warning system to a semantic engine on online news for enhancing landslide prediction

NASA Astrophysics Data System (ADS)

Battistini, Alessandro; Rosi, Ascanio; Segoni, Samuele; Catani, Filippo; Casagli, Nicola

2017-04-01

Landslide inventories are basic data for large scale landslide modelling, e.g. they are needed to calibrate and validate rainfall thresholds, physically based models and early warning systems. The setting up of landslide inventories with traditional methods (e.g. remote sensing, field surveys and manual retrieval of data from technical reports and local newspapers) is time consuming. The objective of this work is to automatically set up a landslide inventory using a state-of-the art semantic engine based on data mining on online news (Battistini et al., 2013) and to evaluate if the automatically generated inventory can be used to validate a regional scale landslide warning system based on rainfall-thresholds. The semantic engine scanned internet news in real time in a 50 months test period. At the end of the process, an inventory of approximately 900 landslides was set up for the Tuscany region (23,000 km2, Italy). The inventory was compared with the outputs of the regional landslide early warning system based on rainfall thresholds, and a good correspondence was found: e.g. 84% of the events reported in the news is correctly identified by the model. In addition, the cases of not correspondence were forwarded to the rainfall threshold developers, which used these inputs to update some of the thresholds. On the basis of the results obtained, we conclude that automatic validation of landslide models using geolocalized landslide events feedback is possible. The source of data for validation can be obtained directly from the internet channel using an appropriate semantic engine. We also automated the validation procedure, which is based on a comparison between forecasts and reported events. We verified that our approach can be automatically used for a near real time validation of the warning system and for a semi-automatic update of the rainfall thresholds, which could lead to an improvement of the forecasting effectiveness of the warning system. In the near future, the proposed procedure could operate in continuous time and could allow for a periodic update of landslide hazard models and landslide early warning systems with minimum human intervention. References: Battistini, A., Segoni, S., Manzo, G., Catani, F., Casagli, N. (2013). Web data mining for automatic inventory of geohazards at national scale. Applied Geography, 43, 147-158.
Spatial prediction of ground subsidence susceptibility using an artificial neural network.

PubMed

Lee, Saro; Park, Inhye; Choi, Jong-Kuk

2012-02-01

Ground subsidence in abandoned underground coal mine areas can result in loss of life and property. We analyzed ground subsidence susceptibility (GSS) around abandoned coal mines in Jeong-am, Gangwon-do, South Korea, using artificial neural network (ANN) and geographic information system approaches. Spatial data of subsidence area, topography, and geology, as well as various ground-engineering data, were collected and used to create a raster database of relevant factors for a GSS map. Eight major factors causing ground subsidence were extracted from the existing ground subsidence area: slope, depth of coal mine, distance from pit, groundwater depth, rock-mass rating, distance from fault, geology, and land use. Areas of ground subsidence were randomly divided into a training set to analyze GSS using the ANN and a test set to validate the predicted GSS map. Weights of each factor's relative importance were determined by the back-propagation training algorithms and applied to the input factor. The GSS was then calculated using the weights, and GSS maps were created. The process was repeated ten times to check the stability of analysis model using a different training data set. The map was validated using area-under-the-curve analysis with the ground subsidence areas that had not been used to train the model. The validation showed prediction accuracies between 94.84 and 95.98%, representing overall satisfactory agreement. Among the input factors, "distance from fault" had the highest average weight (i.e., 1.5477), indicating that this factor was most important. The generated maps can be used to estimate hazards to people, property, and existing infrastructure, such as the transportation network, and as part of land-use and infrastructure planning.
Automated pixel-wise brain tissue segmentation of diffusion-weighted images via machine learning.

PubMed

Ciritsis, Alexander; Boss, Andreas; Rossi, Cristina

2018-04-26

The diffusion-weighted (DW) MR signal sampled over a wide range of b-values potentially allows for tissue differentiation in terms of cellularity, microstructure, perfusion, and T 2 relaxivity. This study aimed to implement a machine learning algorithm for automatic brain tissue segmentation from DW-MRI datasets, and to determine the optimal sub-set of features for accurate segmentation. DWI was performed at 3 T in eight healthy volunteers using 15 b-values and 20 diffusion-encoding directions. The pixel-wise signal attenuation, as well as the trace and fractional anisotropy (FA) of the diffusion tensor, were used as features to train a support vector machine classifier for gray matter, white matter, and cerebrospinal fluid classes. The datasets of two volunteers were used for validation. For each subject, tissue classification was also performed on 3D T 1 -weighted data sets with a probabilistic framework. Confusion matrices were generated for quantitative assessment of image classification accuracy in comparison with the reference method. DWI-based tissue segmentation resulted in an accuracy of 82.1% on the validation dataset and of 82.2% on the training dataset, excluding relevant model over-fitting. A mean Dice coefficient (DSC) of 0.79 ± 0.08 was found. About 50% of the classification performance was attributable to five features (i.e. signal measured at b-values of 5/10/500/1200 s/mm 2 and the FA). This reduced set of features led to almost identical performances for the validation (82.2%) and the training (81.4%) datasets (DSC = 0.79 ± 0.08). Machine learning techniques applied to DWI data allow for accurate brain tissue segmentation based on both morphological and functional information. Copyright © 2018 John Wiley & Sons, Ltd.
Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment.

PubMed

Rosswog, Carolina; Schmidt, Rene; Oberthuer, André; Juraeva, Dilafruz; Brors, Benedikt; Engesser, Anne; Kahlert, Yvonne; Volland, Ruth; Bartenhagen, Christoph; Simon, Thorsten; Berthold, Frank; Hero, Barbara; Faldum, Andreas; Fischer, Matthias

2017-12-01

Current risk stratification systems for neuroblastoma patients consider clinical, histopathological, and genetic variables, and additional prognostic markers have been proposed in recent years. We here sought to select highly informative covariates in a multistep strategy based on consecutive Cox regression models, resulting in a risk score that integrates hazard ratios of prognostic variables. A cohort of 695 neuroblastoma patients was divided into a discovery set (n=75) for multigene predictor generation, a training set (n=411) for risk score development, and a validation set (n=209). Relevant prognostic variables were identified by stepwise multivariable L1-penalized least absolute shrinkage and selection operator (LASSO) Cox regression, followed by backward selection in multivariable Cox regression, and then integrated into a novel risk score. The variables stage, age, MYCN status, and two multigene predictors, NB-th24 and NB-th44, were selected as independent prognostic markers by LASSO Cox regression analysis. Following backward selection, only the multigene predictors were retained in the final model. Integration of these classifiers in a risk scoring system distinguished three patient subgroups that differed substantially in their outcome. The scoring system discriminated patients with diverging outcome in the validation cohort (5-year event-free survival, 84.9±3.4 vs 63.6±14.5 vs 31.0±5.4; P<.001), and its prognostic value was validated by multivariable analysis. We here propose a translational strategy for developing risk assessment systems based on hazard ratios of relevant prognostic variables. Our final neuroblastoma risk score comprised two multigene predictors only, supporting the notion that molecular properties of the tumor cells strongly impact clinical courses of neuroblastoma patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Developing symptom-based predictive models of endometriosis as a clinical screening tool: results from a multicenter study

PubMed Central

Nnoaham, Kelechi E.; Hummelshoj, Lone; Kennedy, Stephen H.; Jenkinson, Crispin; Zondervan, Krina T.

2012-01-01

Objective To generate and validate symptom-based models to predict endometriosis among symptomatic women prior to undergoing their first laparoscopy. Design Prospective, observational, two-phase study, in which women completed a 25-item questionnaire prior to surgery. Setting Nineteen hospitals in 13 countries. Patient(s) Symptomatic women (n = 1,396) scheduled for laparoscopy without a previous surgical diagnosis of endometriosis. Intervention(s) None. Main Outcome Measure(s) Sensitivity and specificity of endometriosis diagnosis predicted by symptoms and patient characteristics from optimal models developed using multiple logistic regression analyses in one data set (phase I), and independently validated in a second data set (phase II) by receiver operating characteristic (ROC) curve analysis. Result(s) Three hundred sixty (46.7%) women in phase I and 364 (58.2%) in phase II were diagnosed with endometriosis at laparoscopy. Menstrual dyschezia (pain on opening bowels) and a history of benign ovarian cysts most strongly predicted both any and stage III and IV endometriosis in both phases. Prediction of any-stage endometriosis, although improved by ultrasound scan evidence of cyst/nodules, was relatively poor (area under the curve [AUC] = 68.3). Stage III and IV disease was predicted with good accuracy (AUC = 84.9, sensitivity of 82.3% and specificity 75.8% at an optimal cut-off of 0.24). Conclusion(s) Our symptom-based models predict any-stage endometriosis relatively poorly and stage III and IV disease with good accuracy. Predictive tools based on such models could help to prioritize women for surgical investigation in clinical practice and thus contribute to reducing time to diagnosis. We invite other researchers to validate the key models in additional populations. PMID:22657249
Reliability and Validity of 10 Different Standard Setting Procedures.

ERIC Educational Resources Information Center

Halpin, Glennelle; Halpin, Gerald

Research indicating that different cut-off points result from the use of different standard-setting techniques leaves decision makers with a disturbing dilemma: Which standard-setting method is best? This investigation of the reliability and validity of 10 different standard-setting approaches was designed to provide information that might help…
Generation of Level 3 SMMR and SSM/I Brightness Temperatures for the Period 1978-1999

NASA Technical Reports Server (NTRS)

Partington, Kim

1999-01-01

The NOAA/NASA Pathfinder Program was initially designed to assure that certain key remote sensing data sets of particular significance to global change research were scientifically validated, consistently processed and made readily available to the research community at minimal cost. Through this Program the National Snow and Ice Data Center (NSIDC), University of Colorado has successfully processed, archived and distributed the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) Level 3 (EASE-Grid format) Pathfinder data sets for the period 1978 to 1999. These data are routinely distributed to approximately 150 researchers through various media including CD-ROM, 8 mm tape, ftp and the EOS Information Management System (IMS). At NSIDC these data are currently being applied in the development and validation of algorithms to derive snow water equivalent (NASA NAG5-6636), the mapping of frozen ground and the detection of the onset of melt over ice sheets, sea ice and snow cover. The EASE-Grid format, developed at NSIDC in conjunction with the SMMR-SSM/I Pathfinder project has also been applied to Advanced Very High Resolution Radiometer (AVHRR) and TOVS Pathfinder data, as well as ancillary data such as digital elevation, land cover classification and several in situ data sets. EASE-Grid will also be used for all land products derived from the NASA EOS AMSR-E instrument.
Three-Class Mammogram Classification Based on Descriptive CNN Features

PubMed Central

Zhang, Qianni; Jadoon, Adeel

2017-01-01

In this paper, a novel classification technique for large data set of mammograms using a deep learning method is proposed. The proposed model targets a three-class classification study (normal, malignant, and benign cases). In our model we have presented two methods, namely, convolutional neural network-discrete wavelet (CNN-DW) and convolutional neural network-curvelet transform (CNN-CT). An augmented data set is generated by using mammogram patches. To enhance the contrast of mammogram images, the data set is filtered by contrast limited adaptive histogram equalization (CLAHE). In the CNN-DW method, enhanced mammogram images are decomposed as its four subbands by means of two-dimensional discrete wavelet transform (2D-DWT), while in the second method discrete curvelet transform (DCT) is used. In both methods, dense scale invariant feature (DSIFT) for all subbands is extracted. Input data matrix containing these subband features of all the mammogram patches is created that is processed as input to convolutional neural network (CNN). Softmax layer and support vector machine (SVM) layer are used to train CNN for classification. Proposed methods have been compared with existing methods in terms of accuracy rate, error rate, and various validation assessment measures. CNN-DW and CNN-CT have achieved accuracy rate of 81.83% and 83.74%, respectively. Simulation results clearly validate the significance and impact of our proposed model as compared to other well-known existing techniques. PMID:28191461
Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring.

PubMed

Lange, Vinzenz; Malmström, Johan A; Didion, John; King, Nichole L; Johansson, Björn P; Schäfer, Juliane; Rameseder, Jonathan; Wong, Chee-Hong; Deutsch, Eric W; Brusniak, Mi-Youn; Bühlmann, Peter; Björck, Lars; Domon, Bruno; Aebersold, Ruedi

2008-08-01

In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.
Three-Class Mammogram Classification Based on Descriptive CNN Features.

PubMed

Jadoon, M Mohsin; Zhang, Qianni; Haq, Ihsan Ul; Butt, Sharjeel; Jadoon, Adeel

2017-01-01

In this paper, a novel classification technique for large data set of mammograms using a deep learning method is proposed. The proposed model targets a three-class classification study (normal, malignant, and benign cases). In our model we have presented two methods, namely, convolutional neural network-discrete wavelet (CNN-DW) and convolutional neural network-curvelet transform (CNN-CT). An augmented data set is generated by using mammogram patches. To enhance the contrast of mammogram images, the data set is filtered by contrast limited adaptive histogram equalization (CLAHE). In the CNN-DW method, enhanced mammogram images are decomposed as its four subbands by means of two-dimensional discrete wavelet transform (2D-DWT), while in the second method discrete curvelet transform (DCT) is used. In both methods, dense scale invariant feature (DSIFT) for all subbands is extracted. Input data matrix containing these subband features of all the mammogram patches is created that is processed as input to convolutional neural network (CNN). Softmax layer and support vector machine (SVM) layer are used to train CNN for classification. Proposed methods have been compared with existing methods in terms of accuracy rate, error rate, and various validation assessment measures. CNN-DW and CNN-CT have achieved accuracy rate of 81.83% and 83.74%, respectively. Simulation results clearly validate the significance and impact of our proposed model as compared to other well-known existing techniques.
Landslide Spreading, Impulse Water Waves and Modelling of the Vajont Rockslide

NASA Astrophysics Data System (ADS)

Crosta, Giovanni B.; Imposimato, Silvia; Roddeman, Dennis

2016-06-01

Landslides can occur in different environments and can interact with or fall into water reservoirs or open sea with different characteristics. The subaerial evolution and the transition from subaerial to subaqueous conditions can strongly control the landslide evolution and the generated impulse waves, and consequently the final hazard zonation. We intend to model the landslide spreading, the impact with the water surface and the generation of the impulse wave under different 2D and 3D conditions and settings. We verify the capabilities of a fully 2D and 3D FEM ALE approach to model and analyse near-field evolution. To this aim we validate the code against 2D laboratory experiments for different Froude number conditions (Fr = 1.4, 3.2). Then the Vajont rockslide (Fr = 0.26-0.75) and the consequent impulse wave are simulated in 2D and 3D. The sliding mass is simulated as an elasto-plastic Mohr-Coulomb material and the lake water as a fully inviscid low compressibility fluid. The rockslide model is validated against field observations, including the total duration, the profile and internal geometry of the final deposit, the maximum water run-up on the opposite valley flank and on the rockslide mass. 2D models are presented for both the case of a dry valley and that of the impounded lake. The set of fully 3D simulations are the first ones available and considering the rockslide evolution, propagation and interaction with the water reservoir. Advantages and disadvantages of the modelling approach are discussed.
A CFD Model for High Pressure Liquid Poison Injection for CANDU-6 Shutdown System No. 2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bo Wook Rhee; Chang Jun Jeong; Hye Jeong Yun

2002-07-01

In CANDU reactor one of the two reactor shutdown systems is the liquid poison injection system which injects the highly pressurized liquid neutron poison into the moderator tank via small holes on the nozzle pipes. To ensure the safe shutdown of a reactor it is necessary for the poison curtains generated by jets provide quick, and enough negative reactivity to the reactor during the early stage of the accident. In order to produce the neutron cross section necessary to perform this work, the poison concentration distribution during the transient is necessary. In this study, a set of models for analyzingmore » the transient poison concentration induced by this high pressure poison injection jet activated upon the reactor trip in a CANDU-6 reactor moderator tank has been developed and used to generate the poison concentration distribution of the poison curtains induced by the high pressure jets injected into the vacant region between the pressure tube banks. The poison injection rate through the jet holes drilled on the nozzle pipes is obtained by a 1-D transient hydrodynamic code called, ALITRIG, and this injection rate is used to provide the inlet boundary condition to a 3-D CFD model of the moderator tank based on CFX4.3, a CFD code, to simulate the formation of the poison jet curtain inside the moderator tank. For validation, an attempt was made to validate this model against a poison injection experiment performed at BARC. As conclusion this set of models is judged to be appropriate. (authors)« less
Validation of the Six Sigma Z-score for the quality assessment of clinical laboratory timeliness.

PubMed

Ialongo, Cristiano; Bernardini, Sergio

2018-03-28

The International Federation of Clinical Chemistry and Laboratory Medicine has introduced in recent times the turnaround time (TAT) as mandatory quality indicator for the postanalytical phase. Classic TAT indicators, namely, average, median, 90th percentile and proportion of acceptable test (PAT), are in use since almost 40 years and to date represent the mainstay for gauging the laboratory timeliness. In this study, we investigated the performance of the Six Sigma Z-score, which was previously introduced as a device for the quantitative assessment of timeliness. A numerical simulation was obtained modeling the actual TAT data set using the log-logistic probability density function. Five thousand replicates for each size of the artificial TAT random sample (n=20, 50, 250 and 1000) were generated, and different laboratory conditions were simulated manipulating the PDF in order to generate more or less variable data. The Z-score and the classic TAT indicators were assessed for precision (%CV), robustness toward right-tailing (precision at different sample variability), sensitivity and specificity. Z-score showed sensitivity and specificity comparable to PAT (≈80% with n≥250), but superior precision that ranged within 20% by moderately small sized samples (n≥50); furthermore, Z-score was less affected by the value of the cutoff used for setting the acceptable TAT, as well as by the sample variability that reflected into the magnitude of right-tailing. The Z-score was a valid indicator of laboratory timeliness and a suitable device to improve as well as to maintain the achieved quality level.
C-MOS bulk metal design handbook. [LSI standard cell (circuits)

NASA Technical Reports Server (NTRS)

Edge, T. M.

1977-01-01

The LSI standard cell array technique was used in the fabrication of more than 20 CMOS custom arrays. This technique consists of a series of computer programs and design automation techniques referred to as the Computer Aided Design And Test (CADAT) system that automatically translate a partitioned logic diagram into a set of instructions for driving an automatic plotter which generates precision mask artwork for complex LSI arrays of CMOS standard cells. The standard cell concept for producing LSI arrays begins with the design, layout, and validation of a group of custom circuits called standard cells. Once validated, these cells are given identification or pattern numbers and are permanently stored. To use one of these cells in a logic design, the user calls for the desired cell by pattern number. The Place, Route in Two Dimension (PR2D) computer program is then used to automatically generate the metalization and/or tunnels to interconnect the standard cells into the required function. Data sheets that describe the function, artwork, and performance of each of the standard cells, the general procedure for implementation of logic in CMOS standard cells, and additional detailed design information are presented.
Fiberfox: facilitating the creation of realistic white matter software phantoms.

PubMed

Neher, Peter F; Laun, Frederik B; Stieltjes, Bram; Maier-Hein, Klaus H

2014-11-01

Phantom-based validation of diffusion-weighted image processing techniques is an important key to innovation in the field and is widely used. Openly available and user friendly tools for the flexible generation of tailor-made datasets for the specific tasks at hand can greatly facilitate the work of researchers around the world. We present an open-source framework, Fiberfox, that enables (1) the intuitive definition of arbitrary artificial white matter fiber tracts, (2) signal generation from those fibers by means of the most recent multi-compartment modeling techniques, and (3) simulation of the actual MR acquisition that allows for the introduction of realistic MRI-related effects into the final image. We show that real acquisitions can be closely approximated by simulating the acquisition of the well-known FiberCup phantom. We further demonstrate the advantages of our framework by evaluating the effects of imaging artifacts and acquisition settings on the outcome of 12 tractography algorithms. Our findings suggest that experiments on a realistic software phantom might change the conclusions drawn from earlier hardware phantom experiments. Fiberfox may find application in validating and further developing methods such as tractography, super-resolution, diffusion modeling or artifact correction. Copyright © 2013 Wiley Periodicals, Inc.
Computational assessment of hemodynamics-based diagnostic tools using a database of virtual subjects: Application to three case studies.

PubMed

Willemet, Marie; Vennin, Samuel; Alastruey, Jordi

2016-12-08

Many physiological indexes and algorithms based on pulse wave analysis have been suggested in order to better assess cardiovascular function. Because these tools are often computed from in-vivo hemodynamic measurements, their validation is time-consuming, challenging, and biased by measurement errors. Recently, a new methodology has been suggested to assess theoretically these computed tools: a database of virtual subjects generated using numerical 1D-0D modeling of arterial hemodynamics. The generated set of simulations encloses a wide selection of healthy cases that could be encountered in a clinical study. We applied this new methodology to three different case studies that demonstrate the potential of our new tool, and illustrated each of them with a clinically relevant example: (i) we assessed the accuracy of indexes estimating pulse wave velocity; (ii) we validated and refined an algorithm that computes central blood pressure; and (iii) we investigated theoretical mechanisms behind the augmentation index. Our database of virtual subjects is a new tool to assist the clinician: it provides insight into the physical mechanisms underlying the correlations observed in clinical practice. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Pharmacophore modeling and virtual screening studies to design some potential histone deacetylase inhibitors as new leads.

PubMed

Vadivelan, S; Sinha, B N; Rambabu, G; Boppana, Kiran; Jagarlapudi, Sarma A R P

2008-02-01

Histone deacetylase is one of the important targets in the treatment of solid tumors and hematological cancers. A total of 20 well-defined inhibitors were used to generate Pharmacophore models using and HypoGen module of Catalyst. These 20 molecules broadly represent 3 different chemotypes. The best HypoGen model consists of four-pharmacophore features--one hydrogen bond acceptor, one hydrophobic aliphatic and two ring aromatic centers. This model was validated against 378 known HDAC inhibitors with a correlation of 0.897 as well as enrichment factor of 2.68 against a maximum value of 3. This model was further used to retrieve molecules from NCI database with 238,819 molecules. A total of 4638 molecules from a pool of 238,819 molecules were identified as hits while 297 molecules were indicated as highly active. Also, a Similarity analysis has been carried out for set of 4638 hits with respect to most active molecule of each chemotypes which validated not only the Virtual Screening potential of the model but also identified the possible new Chemotypes. This type of Similarity analysis would prove to be efficient not only for lead generation but also for lead optimization.
Newt-omics: a comprehensive repository for omics data from the newt Notophthalmus viridescens

PubMed Central

Bruckskotten, Marc; Looso, Mario; Reinhardt, Richard; Braun, Thomas; Borchardt, Thilo

2012-01-01

Notophthalmus viridescens, a member of the salamander family is an excellent model organism to study regenerative processes due to its unique ability to replace lost appendages and to repair internal organs. Molecular insights into regenerative events have been severely hampered by the lack of genomic, transcriptomic and proteomic data, as well as an appropriate database to store such novel information. Here, we describe ‘Newt-omics’ (http://newt-omics.mpi-bn.mpg.de), a database, which enables researchers to locate, retrieve and store data sets dedicated to the molecular characterization of newts. Newt-omics is a transcript-centred database, based on an Expressed Sequence Tag (EST) data set from the newt, covering ∼50 000 Sanger sequenced transcripts and a set of high-density microarray data, generated from regenerating hearts. Newt-omics also contains a large set of peptides identified by mass spectrometry, which was used to validate 13 810 ESTs as true protein coding. Newt-omics is open to implement additional high-throughput data sets without changing the database structure. Via a user-friendly interface Newt-omics allows access to a huge set of molecular data without the need for prior bioinformatical expertise. PMID:22039101
THE VALIDITY OF HUMAN AND COMPUTERIZED WRITING ASSESSMENT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ronald L. Boring

2005-09-01

This paper summarizes an experiment designed to assess the validity of essay grading between holistic and analytic human graders and a computerized grader based on latent semantic analysis. The validity of the grade was gauged by the extent to which the student’s knowledge of the topic correlated with the grader’s expert knowledge. To assess knowledge, Pathfinder networks were generated by the student essay writers, the holistic and analytic graders, and the computerized grader. It was found that the computer generated grades more closely matched the definition of valid grading than did human generated grades.
CoMFA and CoMSIA studies on C-aryl glucoside SGLT2 inhibitors as potential anti-diabetic agents.

PubMed

Vyas, V K; Bhatt, H G; Patel, P K; Jalu, J; Chintha, C; Gupta, N; Ghate, M

2013-01-01

SGLT2 has become a target of therapeutic interest in diabetes research. CoMFA and CoMSIA studies were performed on C-aryl glucoside SGLT2 inhibitors (180 analogues) as potential anti-diabetic agents. Three different alignment strategies were used for the compounds. The best CoMFA and CoMSIA models were obtained by means of Distill rigid body alignment of training and test sets, and found statistically significant with cross-validated coefficients (q²) of 0.602 and 0.618, respectively, and conventional coefficients (r²) of 0.905 and 0.902, respectively. Both models were validated by a test set of 36 compounds giving satisfactory predicted correlation coefficients (r² pred) of 0.622 and 0.584 for CoMFA and CoMSIA models, respectively. A comparison was made with earlier 3D QSAR study on SGLT2 inhibitors, which shows that our 3D QSAR models are better than earlier models to predict good inhibitory activity. CoMFA and CoMSIA models generated in this work can provide useful information to design new compounds and helped in prediction of activity prior to synthesis.
How to do (or not to do)… Measuring health worker motivation in surveys in low- and middle-income countries.

PubMed

Borghi, J; Lohmann, J; Dale, E; Meheus, F; Goudge, J; Oboirien, K; Kuwawenaruwa, A

2018-03-01

A health system's ability to deliver quality health care depends on the availability of motivated health workers, which are insufficient in many low income settings. Increasing policy and researcher attention is directed towards understanding what drives health worker motivation and how different policy interventions affect motivation, as motivation is key to performance and quality of care outcomes. As a result, there is growing interest among researchers in measuring motivation within health worker surveys. However, there is currently limited guidance on how to conceptualize and approach measurement and how to validate or analyse motivation data collected from health worker surveys, resulting in inconsistent and sometimes poor quality measures. This paper begins by discussing how motivation can be conceptualized, then sets out the steps in developing questions to measure motivation within health worker surveys and in ensuring data quality through validity and reliability tests. The paper also discusses analysis of the resulting motivation measure/s. This paper aims to promote high quality research that will generate policy relevant and useful evidence. © The Author 2017. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine.
Nonlinear self-reflection of intense ultra-wideband femtosecond pulses in optical fiber

NASA Astrophysics Data System (ADS)

Konev, Leonid S.; Shpolyanskiy, Yuri A.

2013-05-01

We simulated propagation of few-cycle femtosecond pulses in fused silica fiber based on the set of first-order equations for forward and backward waves that generalizes widely used equation of unidirectional approximation. Appearance of a weak reflected field in conditions default to the unidirectional approach is observed numerically. It arises from nonmatched initial field distribution with the nonlinear medium response. Besides additional field propagating forward along with the input pulse is revealed. The analytical solution of a simplified set of equations valid over distances of a few wavelengths confirms generation of reflected and forward-propagating parts of the backward wave. It allowed us to find matched conditions when the reflected field is eliminated and estimate the amplitude of backward wave via medium properties. The amplitude has the order of the nonlinear contribution to the refractive index divided by the linear refractive index. It is small for the fused silica so the conclusions obtained in the unidirectional approach are valid. The backward wave should be proportionally higher in media with stronger nonlinear response. We did not observe in simulations additional self-reflection not related to non-matched boundary conditions.
Through the eyes of a child: preschoolers' identification of emotional expressions from the child affective facial expression (CAFE) set.

PubMed

LoBue, Vanessa; Baker, Lewis; Thrasher, Cat

2017-08-10

Researchers have been interested in the perception of human emotional expressions for decades. Importantly, most empirical work in this domain has relied on controlled stimulus sets of adults posing for various emotional expressions. Recently, the Child Affective Facial Expression (CAFE) set was introduced to the scientific community, featuring a large validated set of photographs of preschool aged children posing for seven different emotional expressions. Although the CAFE set was extensively validated using adult participants, the set was designed for use with children. It is therefore necessary to verify that adult validation applies to child performance. In the current study, we examined 3- to 4-year-olds' identification of a subset of children's faces in the CAFE set, and compared it to adult ratings cited in previous research. Our results demonstrate an exceptionally strong relationship between adult ratings of the CAFE photos and children's ratings, suggesting that the adult validation of the set can be applied to preschool-aged participants. The results are discussed in terms of methodological implications for the use of the CAFE set with children, and theoretical implications for using the set to study the development of emotion perception in early childhood.
Optimizing the assessment of pediatric injury severity in low-resource settings: Consensus generation through a modified Delphi analysis.

PubMed

St-Louis, Etienne; Deckelbaum, Dan Leon; Baird, Robert; Razek, Tarek

2017-06-01

Although a plethora of pediatric injury severity scoring systems is available, many of them present important challenges and limitations in the low resource setting. Our aim is to generate consensus among a group of experts regarding the optimal parameters, outcomes, and methods of estimating injury severity for pediatric trauma patients in low resource settings. A systematic review of the literature was conducted to identify and compare existing injury scores used in pediatric patients. Qualitative data was extracted from the systematic review, including scoring parameters, settings and outcomes. In order to establish consensus regarding which of these elements are most adapted to pediatric patients in low-resource settings, they were subjected to a modified Delphi survey for external validation. The Delphi process is a structured communication technique that relies on a panel of experts to develop a systematic, interactive consensus method. We invited a group of 38 experts, including adult and pediatric surgeons, emergency physicians and anesthesiologists trauma team leaders from a level 1 trauma center in Montreal, Canada, and a pediatric referral trauma hospital in Santiago, Chile to participate in two successive rounds of our survey. Consensus was reached regarding various features of an ideal pediatric trauma score. Specifically, our experts agreed pediatric trauma scoring tool should differ from its adult counterpart, that it can be derived from point of care data available at first assessment, that blood pressure is an important variable to include in a predictive model for pediatric trauma outcomes, that blood pressure is a late but specific marker of shock in pediatric patients, that pulse rate is a more sensitive marker of hemodynamic instability than blood pressure, that an assessment of airway status should be included as a predictive variable for pediatric trauma outcomes, that the AVPU classification of neurologic status is simple and reliable in the acute setting, and more so than GCS at all ages. Therefore, we conclude that an opportunity exists to develop a new pediatric trauma score, combining the above consensus-generating ideas, that would be best adapted for use in low-resource settings. Copyright © 2017 Elsevier Ltd. All rights reserved.

European validation of The Comprehensive International Classification of Functioning, Disability and Health Core Set for Osteoarthritis from the perspective of patients with osteoarthritis of the knee or hip.

PubMed

Weigl, Martin; Wild, Heike

2017-09-15

To validate the International Classification of Functioning, Disability and Health Comprehensive Core Set for Osteoarthritis from the patient perspective in Europe. This multicenter cross-sectional study involved 375 patients with knee or hip osteoarthritis. Trained health professionals completed the Comprehensive Core Set, and patients completed the Short-Form 36 questionnaire. Content validity was evaluated by calculating prevalences of impairments in body function and structures, limitations in activities and participation and environmental factors, which were either barriers or facilitators. Convergent construct validity was evaluated by correlating the International Classification of Functioning, Disability and Health categories with the Short-Form 36 Physical Component Score and the SF-36 Mental Component Score in a subgroup of 259 patients. The prevalences of all body function, body structure and activities and participation categories were >40%, >32% and >20%, respectively, and all environmental factors were relevant for >16% of patients. Few categories showed relevant differences between knee and hip osteoarthritis. All body function categories and all but two activities and participation categories showed significant correlations with the Physical Component Score. Body functions from the ICF chapter Mental Functions showed higher correlations with the Mental Component Score than with the Physical Component Score. This study supports the validity of the International Classification of Functioning, Disability and Health Comprehensive Core Set for Osteoarthritis. Implications for Rehabilitation Comprehensive International Classification of Functioning, Disability and Health Core Sets were developed as practical tools for application in multidisciplinary assessments. The validity of the Comprehensive International Classification of Functioning, Disability and Health Core Set for Osteoarthritis in this study supports its application in European patients with osteoarthritis. The differences in results between this Europe validation study and a previous Singaporean validation study underscore the need to validate the International Classification of Functioning, Disability and Health Core Sets in different regions of the world.
Prognostic factors in patients with advanced cancer: use of the patient-generated subjective global assessment in survival prediction.

PubMed

Martin, Lisa; Watanabe, Sharon; Fainsinger, Robin; Lau, Francis; Ghosh, Sunita; Quan, Hue; Atkins, Marlis; Fassbender, Konrad; Downing, G Michael; Baracos, Vickie

2010-10-01

To determine whether elements of a standard nutritional screening assessment are independently prognostic of survival in patients with advanced cancer. A prospective nested cohort of patients with metastatic cancer were accrued from different units of a Regional Palliative Care Program. Patients completed a nutritional screen on admission. Data included age, sex, cancer site, height, weight history, dietary intake, 13 nutrition impact symptoms, and patient- and physician-reported performance status (PS). Univariate and multivariate survival analyses were conducted. Concordance statistics (c-statistics) were used to test the predictive accuracy of models based on training and validation sets; a c-statistic of 0.5 indicates the model predicts the outcome as well as chance; perfect prediction has a c-statistic of 1.0. A training set of patients in palliative home care (n = 1,164) was used to identify prognostic variables. Primary disease site, PS, short-term weight change (either gain or loss), dietary intake, and dysphagia predicted survival in multivariate analysis (P < .05). A model including only patients separated by disease site and PS with high c-statistics between predicted and observed responses for survival in the training set (0.90) and validation set (0.88; n = 603). The addition of weight change, dietary intake, and dysphagia did not further improve the c-statistic of the model. The c-statistic was also not altered by substituting physician-rated palliative PS for patient-reported PS. We demonstrate a high probability of concordance between predicted and observed survival for patients in distinct palliative care settings (home care, tertiary inpatient, ambulatory outpatient) based on patient-reported information.
Metabolomic Profile of Ards by Nuclear Magnetic Resonance Spectroscopy in Patients with H1N1 Influenza Virus Pneumonia.

PubMed

Izquierdo-Garcia, Jose L; Nin, Nicolas; Jimenez-Clemente, Jorge; Horcajada, Juan P; Arenas-Miras, Maria Del Mar; Gea, Joaquim; Esteban, Andres; Ruiz-Cabello, Jesus; Lorente, Jose A

2017-12-29

The integrated analysis of changes in the metabolic profile could be critical for the discovery of biomarkers of lung injury, and also for generating new pathophysiological hypotheses and designing novel therapeutic targets for the acute respiratory distress syndrome (ARDS). This study aimed at developing a Nuclear Magnetic Resonance (NMR)-based approach for the identification of the metabolomic profile of ARDS in patients with H1N1 influenza virus pneumonia. Serum samples from 30 patients (derivation set) diagnosed of H1N1 influenza virus pneumonia were analysed by unsupervised Principal Component Analysis (PCA) to identify metabolic differences between patients with and without ARDS by NMR-spectroscopy. A predictive model of partial least squares discriminant analysis (PLS-DA) was developed for the identification of ARDS. PLS-DA was trained with the derivation set and tested in another set of samples from 26 patients also diagnosed of H1N1 influenza virus pneumonia (validation set). Decreased serum glucose, alanine, glutamine, methylhistidine and fatty acids concentrations, and elevated serum phenylalanine and methylguanidine concentrations, discriminated patients with ARDS versus patients without ARDS. PLS-DA model successfully identified the presence of ARDS in the validation set with a success rate of 92% (sensitivity 100% and specificity 91%). The classification functions showed a good correlation with the Sequential Organ Failure Assessment (SOFA) score (R = 0.74, p < 0.0001) and the Pa02/Fi02 ratio (R = 0.41, p = 0.03). The serum metabolomic profile is sensitive and specific to identify ARDS in patients with H1N1 influenza A pneumonia. Future studies are needed to determine the role of NMR-spectroscopy as a biomarker of ARDS.
Multi-institutional validation of a novel textural analysis tool for preoperative stratification of suspected thyroid tumors on diffusion-weighted MRI.

PubMed

Brown, Anna M; Nagala, Sidhartha; McLean, Mary A; Lu, Yonggang; Scoffings, Daniel; Apte, Aditya; Gonen, Mithat; Stambuk, Hilda E; Shaha, Ashok R; Tuttle, R Michael; Deasy, Joseph O; Priest, Andrew N; Jani, Piyush; Shukla-Dave, Amita; Griffiths, John

2016-04-01

Ultrasound-guided fine needle aspirate cytology fails to diagnose many malignant thyroid nodules; consequently, patients may undergo diagnostic lobectomy. This study assessed whether textural analysis (TA) could noninvasively stratify thyroid nodules accurately using diffusion-weighted MRI (DW-MRI). This multi-institutional study examined 3T DW-MRI images obtained with spin echo echo planar imaging sequences. The training data set included 26 patients from Cambridge, United Kingdom, and the test data set included 18 thyroid cancer patients from Memorial Sloan Kettering Cancer Center (New York, New York, USA). Apparent diffusion coefficients (ADCs) were compared over regions of interest (ROIs) defined on thyroid nodules. TA, linear discriminant analysis (LDA), and feature reduction were performed using the 21 MaZda-generated texture parameters that best distinguished benign and malignant ROIs. Training data set mean ADC values were significantly different for benign and malignant nodules (P = 0.02) with a sensitivity and specificity of 70% and 63%, respectively, and a receiver operator characteristic (ROC) area under the curve (AUC) of 0.73. The LDA model of the top 21 textural features correctly classified 89/94 DW-MRI ROIs with 92% sensitivity, 96% specificity, and an AUC of 0.97. This algorithm correctly classified 16/18 (89%) patients in the independently obtained test set of thyroid DW-MRI scans. TA classifies thyroid nodules with high sensitivity and specificity on multi-institutional DW-MRI data sets. This method requires further validation in a larger prospective study. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine.
Validation of tsunami inundation model TUNA-RP using OAR-PMEL-135 benchmark problem set

NASA Astrophysics Data System (ADS)

Koh, H. L.; Teh, S. Y.; Tan, W. K.; Kh'ng, X. Y.

2017-05-01

A standard set of benchmark problems, known as OAR-PMEL-135, is developed by the US National Tsunami Hazard Mitigation Program for tsunami inundation model validation. Any tsunami inundation model must be tested for its accuracy and capability using this standard set of benchmark problems before it can be gainfully used for inundation simulation. The authors have previously developed an in-house tsunami inundation model known as TUNA-RP. This inundation model solves the two-dimensional nonlinear shallow water equations coupled with a wet-dry moving boundary algorithm. This paper presents the validation of TUNA-RP against the solutions provided in the OAR-PMEL-135 benchmark problem set. This benchmark validation testing shows that TUNA-RP can indeed perform inundation simulation with accuracy consistent with that in the tested benchmark problem set.
A new CM SAF Solar Surface Radiation Climate Data Set derived from Meteosat Satellite Observations

NASA Astrophysics Data System (ADS)

Trentmann, J.; Mueller, R. W.; Pfeifroth, U.; Träger-Chatterjee, C.; Cremer, R.

2014-12-01

The incoming surface solar radiation has been defined as an essential climate variable by GCOS. It is mandatory to monitor this part of the earth's energy balance, and thus gain insights on the state and variability of the climate system. In addition, data sets of the surface solar radiation have received increased attention over the recent years as an important source of information for the planning of solar energy applications. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving surface solar radiation from geostationary and polar-orbiting satellite instruments. While CM SAF is focusing on the generation of high-quality long-term climate data records, also operationally data is provided in short time latency within 8 weeks. Here we present SARAH (Solar Surface Radiation Dataset - Heliosat), i.e. the new CM SAF Solar Surface Radiation data set based on Meteosat satellite observations. SARAH provides instantaneous, daily- and monthly-averaged data of the effective cloud albedo (CAL), the direct normalized solar radiation (DNI) and the solar irradiance (SIS) from 1983 to 2013 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). The data sets are generated with a high spatial resolution of 0.05 deg allowing for detailed regional studies, and are available in netcdf-format at no cost without restrictions at www.cmsaf.eu. We provide an overview of the data sets, including a validation against reference measurements from the BSRN and GEBA surface station networks.
Metabolomics as a Hypothesis-Generating Functional Genomics Tool for the Annotation of Arabidopsis thaliana Genes of “Unknown Function”

PubMed Central

Quanbeck, Stephanie M.; Brachova, Libuse; Campbell, Alexis A.; Guan, Xin; Perera, Ann; He, Kun; Rhee, Seung Y.; Bais, Preeti; Dickerson, Julie A.; Dixon, Philip; Wohlgemuth, Gert; Fiehn, Oliver; Barkan, Lenore; Lange, Iris; Lange, B. Markus; Lee, Insuk; Cortes, Diego; Salazar, Carolina; Shuman, Joel; Shulaev, Vladimir; Huhman, David V.; Sumner, Lloyd W.; Roth, Mary R.; Welti, Ruth; Ilarslan, Hilal; Wurtele, Eve S.; Nikolau, Basil J.

2012-01-01

Metabolomics is the methodology that identifies and measures global pools of small molecules (of less than about 1,000 Da) of a biological sample, which are collectively called the metabolome. Metabolomics can therefore reveal the metabolic outcome of a genetic or environmental perturbation of a metabolic regulatory network, and thus provide insights into the structure and regulation of that network. Because of the chemical complexity of the metabolome and limitations associated with individual analytical platforms for determining the metabolome, it is currently difficult to capture the complete metabolome of an organism or tissue, which is in contrast to genomics and transcriptomics. This paper describes the analysis of Arabidopsis metabolomics data sets acquired by a consortium that includes five analytical laboratories, bioinformaticists, and biostatisticians, which aims to develop and validate metabolomics as a hypothesis-generating functional genomics tool. The consortium is determining the metabolomes of Arabidopsis T-DNA mutant stocks, grown in standardized controlled environment optimized to minimize environmental impacts on the metabolomes. Metabolomics data were generated with seven analytical platforms, and the combined data is being provided to the research community to formulate initial hypotheses about genes of unknown function (GUFs). A public database (www.PlantMetabolomics.org) has been developed to provide the scientific community with access to the data along with tools to allow for its interactive analysis. Exemplary datasets are discussed to validate the approach, which illustrate how initial hypotheses can be generated from the consortium-produced metabolomics data, integrated with prior knowledge to provide a testable hypothesis concerning the functionality of GUFs. PMID:22645570
A New Clinicobiological Scoring System for the Prediction of Infection-Related Mortality and Survival after Allogeneic Hematopoietic Stem Cell Transplantation.

PubMed

Forcina, Alessandra; Rancoita, Paola M V; Marcatti, Magda; Greco, Raffaella; Lupo-Stanghellini, Maria Teresa; Carrabba, Matteo; Marasco, Vincenzo; Di Serio, Clelia; Bernardi, Massimo; Peccatori, Jacopo; Corti, Consuelo; Bondanza, Attilio; Ciceri, Fabio

2017-12-01

Infection-related mortality (IRM) is a substantial component of nonrelapse mortality (NRM) after allogeneic hematopoietic stem cell transplantation (allo-HSCT). No scores have been developed to predict IRM before transplantation. Pretransplantation clinical and biochemical data were collected from a study cohort of 607 adult patients undergoing allo-HSCT between January 2009 and February 2017. In a training set of 273 patients, multivariate analysis revealed that age >60 years (P = .003), cytomegalovirus host/donor serostatus different from negative/negative (P < .001), pretransplantation IgA level <1.11 g/L (P = .004), and pretransplantation IgM level <.305 g/L (P = .028) were independent predictors of increased IRM. Based on these results, we developed and subsequently validated a 3-tiered weighted prognostic index for IRM in a retrospective set of patients (n = 219) and a prospective set of patients (n = 115). Patients were assigned to 3 different IRM risk classes based on this index score. The score significantly predicted IRM in the training set, retrospective validation set, and prospective validation set (P < .001, .044, and .011, respectively). In the training set, 100-day IRM was 5% for the low-risk group, 11% for the intermediate-riak group, and 16% for the high-risk groups. In the retrospective validation set, the respective 100-day IRM values were 7%, 17%, and 28%, and in the prospective set, they were 0%, 5%, and 7%. This score predicted also overall survival (P < .001 in the training set, P < 041 in the retrospective validation set, and P < .023 in the prospective validation set). Because pretransplantation levels of IgA/IgM can be modulated by the supplementation of enriched immunoglobulins, these results suggest the possibility of prophylactic interventional studies to improve transplantation outcomes. Copyright © 2017 The American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.
Cerebral 18F-FDG PET in macrophagic myofasciitis: An individual SVM-based approach.

PubMed

Blanc-Durand, Paul; Van Der Gucht, Axel; Guedj, Eric; Abulizi, Mukedaisi; Aoun-Sebaiti, Mehdi; Lerman, Lionel; Verger, Antoine; Authier, François-Jérôme; Itti, Emmanuel

2017-01-01

Macrophagic myofasciitis (MMF) is an emerging condition with highly specific myopathological alterations. A peculiar spatial pattern of a cerebral glucose hypometabolism involving occipito-temporal cortex and cerebellum have been reported in patients with MMF; however, the full pattern is not systematically present in routine interpretation of scans, and with varying degrees of severity depending on the cognitive profile of patients. Aim was to generate and evaluate a support vector machine (SVM) procedure to classify patients between healthy or MMF 18F-FDG brain profiles. 18F-FDG PET brain images of 119 patients with MMF and 64 healthy subjects were retrospectively analyzed. The whole-population was divided into two groups; a training set (100 MMF, 44 healthy subjects) and a testing set (19 MMF, 20 healthy subjects). Dimensionality reduction was performed using a t-map from statistical parametric mapping (SPM) and a SVM with a linear kernel was trained on the training set. To evaluate the performance of the SVM classifier, values of sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV) and accuracy (Acc) were calculated. The SPM12 analysis on the training set exhibited the already reported hypometabolism pattern involving occipito-temporal and fronto-parietal cortices, limbic system and cerebellum. The SVM procedure, based on the t-test mask generated from the training set, correctly classified MMF patients of the testing set with following Se, Sp, PPV, NPV and Acc: 89%, 85%, 85%, 89%, and 87%. We developed an original and individual approach including a SVM to classify patients between healthy or MMF metabolic brain profiles using 18F-FDG-PET. Machine learning algorithms are promising for computer-aided diagnosis but will need further validation in prospective cohorts.
Building a Better Fragment Library for De Novo Protein Structure Prediction

PubMed Central

de Oliveira, Saulo H. P.; Shi, Jiye; Deane, Charlotte M.

2015-01-01

Fragment-based approaches are the current standard for de novo protein structure prediction. These approaches rely on accurate and reliable fragment libraries to generate good structural models. In this work, we describe a novel method for structure fragment library generation and its application in fragment-based de novo protein structure prediction. The importance of correct testing procedures in assessing the quality of fragment libraries is demonstrated. In particular, the exclusion of homologs to the target from the libraries to correctly simulate a de novo protein structure prediction scenario, something which surprisingly is not always done. We demonstrate that fragments presenting different predominant predicted secondary structures should be treated differently during the fragment library generation step and that exhaustive and random search strategies should both be used. This information was used to develop a novel method, Flib. On a validation set of 41 structurally diverse proteins, Flib libraries presents both a higher precision and coverage than two of the state-of-the-art methods, NNMake and HHFrag. Flib also achieves better precision and coverage on the set of 275 protein domains used in the two previous experiments of the the Critical Assessment of Structure Prediction (CASP9 and CASP10). We compared Flib libraries against NNMake libraries in a structure prediction context. Of the 13 cases in which a correct answer was generated, Flib models were more accurate than NNMake models for 10. “Flib is available for download at: http://www.stats.ox.ac.uk/research/proteins/resources”. PMID:25901595
Improving validation methods for molecular diagnostics: application of Bland-Altman, Deming and simple linear regression analyses in assay comparison and evaluation for next-generation sequencing.

PubMed

Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L

2018-02-01

A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Identification, validation and high-throughput genotyping of transcribed gene SNPs in cassava.

PubMed

Ferguson, Morag E; Hearne, Sarah J; Close, Timothy J; Wanamaker, Steve; Moskal, William A; Town, Christopher D; de Young, Joe; Marri, Pradeep Reddy; Rabbi, Ismail Yusuf; de Villiers, Etienne P

2012-03-01

The availability of genomic resources can facilitate progress in plant breeding through the application of advanced molecular technologies for crop improvement. This is particularly important in the case of less researched crops such as cassava, a staple and food security crop for more than 800 million people. Here, expressed sequence tags (ESTs) were generated from five drought stressed and well-watered cassava varieties. Two cDNA libraries were developed: one from root tissue (CASR), the other from leaf, stem and stem meristem tissue (CASL). Sequencing generated 706 contigs and 3,430 singletons. These sequences were combined with those from two other EST sequencing initiatives and filtered based on the sequence quality. Quality sequences were aligned using CAP3 and embedded in a Windows browser called HarvEST:Cassava which is made available. HarvEST:Cassava consists of a Unigene set of 22,903 quality sequences. A total of 2,954 putative SNPs were identified. Of these 1,536 SNPs from 1,170 contigs and 53 cassava genotypes were selected for SNP validation using Illumina's GoldenGate assay. As a result 1,190 SNPs were validated technically and biologically. The location of validated SNPs on scaffolds of the cassava genome sequence (v.4.1) is provided. A diversity assessment of 53 cassava varieties reveals some sub-structure based on the geographical origin, greater diversity in the Americas as opposed to Africa, and similar levels of diversity in West Africa and southern, eastern and central Africa. The resources presented allow for improved genetic dissection of economically important traits and the application of modern genomics-based approaches to cassava breeding and conservation.
A systematic approach to the Planck LFI end-to-end test and its application to the DPC Level 1 pipeline

NASA Astrophysics Data System (ADS)

Frailis, M.; Maris, M.; Zacchei, A.; Morisset, N.; Rohlfs, R.; Meharga, M.; Binko, P.; Türler, M.; Galeotta, S.; Gasparo, F.; Franceschi, E.; Butler, R. C.; D'Arcangelo, O.; Fogliani, S.; Gregorio, A.; Lowe, S. R.; Maggio, G.; Malaspina, M.; Mandolesi, N.; Manzato, P.; Pasian, F.; Perrotta, F.; Sandri, M.; Terenzi, L.; Tomasi, M.; Zonca, A.

2009-12-01

The Level 1 of the Planck LFI Data Processing Centre (DPC) is devoted to the handling of the scientific and housekeeping telemetry. It is a critical component of the Planck ground segment which has to strictly commit to the project schedule to be ready for the launch and flight operations. In order to guarantee the quality necessary to achieve the objectives of the Planck mission, the design and development of the Level 1 software has followed the ESA Software Engineering Standards. A fundamental step in the software life cycle is the Verification and Validation of the software. The purpose of this work is to show an example of procedures, test development and analysis successfully applied to a key software project of an ESA mission. We present the end-to-end validation tests performed on the Level 1 of the LFI-DPC, by detailing the methods used and the results obtained. Different approaches have been used to test the scientific and housekeeping data processing. Scientific data processing has been tested by injecting signals with known properties directly into the acquisition electronics, in order to generate a test dataset of real telemetry data and reproduce as much as possible nominal conditions. For the HK telemetry processing, validation software have been developed to inject known parameter values into a set of real housekeeping packets and perform a comparison with the corresponding timelines generated by the Level 1. With the proposed validation and verification procedure, where the on-board and ground processing are viewed as a single pipeline, we demonstrated that the scientific and housekeeping processing of the Planck-LFI raw data is correct and meets the project requirements.
Procedure for the Selection and Validation of a Calibration Model I-Description and Application.

PubMed

Desharnais, Brigitte; Camirand-Lemyre, Félix; Mireault, Pascal; Skinner, Cameron D

2017-05-01

Calibration model selection is required for all quantitative methods in toxicology and more broadly in bioanalysis. This typically involves selecting the equation order (quadratic or linear) and weighting factor correctly modelizing the data. A mis-selection of the calibration model will generate lower quality control (QC) accuracy, with an error up to 154%. Unfortunately, simple tools to perform this selection and tests to validate the resulting model are lacking. We present a stepwise, analyst-independent scheme for selection and validation of calibration models. The success rate of this scheme is on average 40% higher than a traditional "fit and check the QCs accuracy" method of selecting the calibration model. Moreover, the process was completely automated through a script (available in Supplemental Data 3) running in RStudio (free, open-source software). The need for weighting was assessed through an F-test using the variances of the upper limit of quantification and lower limit of quantification replicate measurements. When weighting was required, the choice between 1/x and 1/x2 was determined by calculating which option generated the smallest spread of weighted normalized variances. Finally, model order was selected through a partial F-test. The chosen calibration model was validated through Cramer-von Mises or Kolmogorov-Smirnov normality testing of the standardized residuals. Performance of the different tests was assessed using 50 simulated data sets per possible calibration model (e.g., linear-no weight, quadratic-no weight, linear-1/x, etc.). This first of two papers describes the tests, procedures and outcomes of the developed procedure using real LC-MS-MS results for the quantification of cocaine and naltrexone. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Genomic Prediction Accounting for Residual Heteroskedasticity

PubMed Central

Ou, Zhining; Tempelman, Robert J.; Steibel, Juan P.; Ernst, Catherine W.; Bates, Ronald O.; Bello, Nora M.

2015-01-01

Whole-genome prediction (WGP) models that use single-nucleotide polymorphism marker information to predict genetic merit of animals and plants typically assume homogeneous residual variance. However, variability is often heterogeneous across agricultural production systems and may subsequently bias WGP-based inferences. This study extends classical WGP models based on normality, heavy-tailed specifications and variable selection to explicitly account for environmentally-driven residual heteroskedasticity under a hierarchical Bayesian mixed-models framework. WGP models assuming homogeneous or heterogeneous residual variances were fitted to training data generated under simulation scenarios reflecting a gradient of increasing heteroskedasticity. Model fit was based on pseudo-Bayes factors and also on prediction accuracy of genomic breeding values computed on a validation data subset one generation removed from the simulated training dataset. Homogeneous vs. heterogeneous residual variance WGP models were also fitted to two quantitative traits, namely 45-min postmortem carcass temperature and loin muscle pH, recorded in a swine resource population dataset prescreened for high and mild residual heteroskedasticity, respectively. Fit of competing WGP models was compared using pseudo-Bayes factors. Predictive ability, defined as the correlation between predicted and observed phenotypes in validation sets of a five-fold cross-validation was also computed. Heteroskedastic error WGP models showed improved model fit and enhanced prediction accuracy compared to homoskedastic error WGP models although the magnitude of the improvement was small (less than two percentage points net gain in prediction accuracy). Nevertheless, accounting for residual heteroskedasticity did improve accuracy of selection, especially on individuals of extreme genetic merit. PMID:26564950
Quantitative structure activity relationship (QSAR) of piperine analogs for bacterial NorA efflux pump inhibitors.

PubMed

Nargotra, Amit; Sharma, Sujata; Koul, Jawahir Lal; Sangwan, Pyare Lal; Khan, Inshad Ali; Kumar, Ashwani; Taneja, Subhash Chander; Koul, Surrinder

2009-10-01

Quantitative structure activity relationship (QSAR) analysis of piperine analogs as inhibitors of efflux pump NorA from Staphylococcus aureus has been performed in order to obtain a highly accurate model enabling prediction of inhibition of S. aureus NorA of new chemical entities from natural sources as well as synthetic ones. Algorithm based on genetic function approximation method of variable selection in Cerius2 was used to generate the model. Among several types of descriptors viz., topological, spatial, thermodynamic, information content and E-state indices that were considered in generating the QSAR model, three descriptors such as partial negative surface area of the compounds, area of the molecular shadow in the XZ plane and heat of formation of the molecules resulted in a statistically significant model with r(2)=0.962 and cross-validation parameter q(2)=0.917. The validation of the QSAR models was done by cross-validation, leave-25%-out and external test set prediction. The theoretical approach indicates that the increase in the exposed partial negative surface area increases the inhibitory activity of the compound against NorA whereas the area of the molecular shadow in the XZ plane is inversely proportional to the inhibitory activity. This model also explains the relationship of the heat of formation of the compound with the inhibitory activity. The model is not only able to predict the activity of new compounds but also explains the important regions in the molecules in quantitative manner.
A Model-Based Method for Content Validation of Automatically Generated Test Items

ERIC Educational Resources Information Center

Zhang, Xinxin; Gierl, Mark

2016-01-01

The purpose of this study is to describe a methodology to recover the item model used to generate multiple-choice test items with a novel graph theory approach. Beginning with the generated test items and working backward to recover the original item model provides a model-based method for validating the content used to automatically generate test…
Generation of “Virtual” Control Groups for Single Arm Prostate Cancer Adjuvant Trials

PubMed Central

Koziol, James A.; Chen, Xin; Xia, Xiao-Qin; Wang, Yipeng; Skarecky, Douglas; Sutton, Manuel; Sawyers, Anne; Ruckle, Herbert; Carpenter, Philip M.; Wang-Rodriguez, Jessica; Jiang, Jun; Deng, Mingsen; Pan, Cong; Zhu, Jian-guo; McLaren, Christine E.; Gurley, Michael J.; Lee, Chung; McClelland, Michael; Ahlering, Thomas; Kattan, Michael W.; Mercola, Dan

2014-01-01

It is difficult to construct a control group for trials of adjuvant therapy (Rx) of prostate cancer after radical prostatectomy (RP) due to ethical issues and patient acceptance. We utilized 8 curve-fitting models to estimate the time to 60%, 65%, … 95% chance of progression free survival (PFS) based on the data derived from Kattan post-RP nomogram. The 8 models were systematically applied to a training set of 153 post-RP cases without adjuvant Rx to develop 8 subsets of cases (reference case sets) whose observed PFS times were most accurately predicted by each model. To prepare a virtual control group for a single-arm adjuvant Rx trial, we first select the optimal model for the trial cases based on the minimum weighted Euclidean distance between the trial case set and the reference case set in terms of clinical features, and then compare the virtual PFS times calculated by the optimum model with the observed PFSs of the trial cases by the logrank test. The method was validated using an independent dataset of 155 post-RP patients without adjuvant Rx. We then applied the method to patients on a Phase II trial of adjuvant chemo-hormonal Rx post RP, which indicated that the adjuvant Rx is highly effective in prolonging PFS after RP in patients at high risk for prostate cancer recurrence. The method can accurately generate control groups for single-arm, post-RP adjuvant Rx trials for prostate cancer, facilitating development of new therapeutic strategies. PMID:24465467
Generation of "virtual" control groups for single arm prostate cancer adjuvant trials.

PubMed

Jia, Zhenyu; Lilly, Michael B; Koziol, James A; Chen, Xin; Xia, Xiao-Qin; Wang, Yipeng; Skarecky, Douglas; Sutton, Manuel; Sawyers, Anne; Ruckle, Herbert; Carpenter, Philip M; Wang-Rodriguez, Jessica; Jiang, Jun; Deng, Mingsen; Pan, Cong; Zhu, Jian-Guo; McLaren, Christine E; Gurley, Michael J; Lee, Chung; McClelland, Michael; Ahlering, Thomas; Kattan, Michael W; Mercola, Dan

2014-01-01

It is difficult to construct a control group for trials of adjuvant therapy (Rx) of prostate cancer after radical prostatectomy (RP) due to ethical issues and patient acceptance. We utilized 8 curve-fitting models to estimate the time to 60%, 65%, … 95% chance of progression free survival (PFS) based on the data derived from Kattan post-RP nomogram. The 8 models were systematically applied to a training set of 153 post-RP cases without adjuvant Rx to develop 8 subsets of cases (reference case sets) whose observed PFS times were most accurately predicted by each model. To prepare a virtual control group for a single-arm adjuvant Rx trial, we first select the optimal model for the trial cases based on the minimum weighted Euclidean distance between the trial case set and the reference case set in terms of clinical features, and then compare the virtual PFS times calculated by the optimum model with the observed PFSs of the trial cases by the logrank test. The method was validated using an independent dataset of 155 post-RP patients without adjuvant Rx. We then applied the method to patients on a Phase II trial of adjuvant chemo-hormonal Rx post RP, which indicated that the adjuvant Rx is highly effective in prolonging PFS after RP in patients at high risk for prostate cancer recurrence. The method can accurately generate control groups for single-arm, post-RP adjuvant Rx trials for prostate cancer, facilitating development of new therapeutic strategies.
Towards optical spectroscopic anatomical mapping (OSAM) for lesion validation in cardiac tissue (Conference Presentation)

NASA Astrophysics Data System (ADS)

Singh-Moon, Rajinder P.; Zaryab, Mohammad; Hendon, Christine P.

2017-02-01

Electroanatomical mapping (EAM) is an invaluable tool for guiding cardiac radiofrequency ablation (RFA) therapy. The principle roles of EAM is the identification of candidate ablation sites by detecting regions of abnormal electrogram activity and lesion validation subsequent to RF energy delivery. However, incomplete lesions may present interim electrical inactivity similar to effective treatment in the acute setting, despite efforts to reveal them with pacing or drugs, such as adenosine. Studies report that the misidentification and recovery of such lesions is a leading cause of arrhythmia recurrence and repeat procedures. In previous work, we demonstrated spectroscopic characterization of cardiac tissues using a fiber optic-integrated RF ablation catheter. In this work, we introduce OSAM (optical spectroscopic anatomical mapping), the application of this spectroscopic technique to obtain 2-dimensional biodistribution maps. We demonstrate its diagnostic potential as an auxiliary method for lesion validation in treated swine preparations. Endocardial lesion sets were created on fresh swine cardiac samples using a commercial RFA system. An optically-integrated catheter console fabricated in-house was used for measurement of tissue optical spectra between 600-1000nm. Three dimensional, Spatio-spectral datasets were generated by raster scanning of the optical catheter across the treated sample surface in the presence of whole blood. Tissue optical parameters were recovered at each spatial position using an inverse Monte Carlo method. OSAM biodistribution maps showed stark correspondence with gross examination of tetrazolium chloride stained tissue specimens. Specifically, we demonstrate the ability of OSAM to readily distinguish between shallow and deeper lesions, a limitation faced by current EAM techniques. These results showcase the OSAMs potential for lesion validation strategies for the treatment of cardiac arrhythmias.

A new map of permafrost distribution on the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Zou, Defu; Zhao, Lin; Sheng, Yu; Chen, Ji; Hu, Guojie; Wu, Tonghua; Wu, Jichun; Xie, Changwei; Wu, Xiaodong; Pang, Qiangqiang; Wang, Wu; Du, Erji; Li, Wangping; Liu, Guangyue; Li, Jing; Qin, Yanhui; Qiao, Yongping; Wang, Zhiwei; Shi, Jianzong; Cheng, Guodong

2017-11-01

The Tibetan Plateau (TP) has the largest areas of permafrost terrain in the mid- and low-latitude regions of the world. Some permafrost distribution maps have been compiled but, due to limited data sources, ambiguous criteria, inadequate validation, and deficiency of high-quality spatial data sets, there is high uncertainty in the mapping of the permafrost distribution on the TP. We generated a new permafrost map based on freezing and thawing indices from modified Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperatures (LSTs) and validated this map using various ground-based data sets. The soil thermal properties of five soil types across the TP were estimated according to an empirical equation and soil properties (moisture content and bulk density). The temperature at the top of permafrost (TTOP) model was applied to simulate the permafrost distribution. Permafrost, seasonally frozen ground, and unfrozen ground covered areas of 1.06 × 106 km2 (0.97-1.15 × 106 km2, 90 % confidence interval) (40 %), 1.46 × 106 (56 %), and 0.03 × 106 km2 (1 %), respectively, excluding glaciers and lakes. Ground-based observations of the permafrost distribution across the five investigated regions (IRs, located in the transition zones of the permafrost and seasonally frozen ground) and three highway transects (across the entire permafrost regions from north to south) were used to validate the model. Validation results showed that the kappa coefficient varied from 0.38 to 0.78 with a mean of 0.57 for the five IRs and 0.62 to 0.74 with a mean of 0.68 within the three transects. Compared with earlier studies, the TTOP modelling results show greater accuracy. The results provide more detailed information on the permafrost distribution and basic data for use in future research on the Tibetan Plateau permafrost.
Impact of metal ionic characteristics on adsorption potential of Ficus carica leaves using QSPR modeling.

PubMed

Batool, Fozia; Iqbal, Shahid; Akbar, Jamshed

2018-04-03

The present study describes Quantitative Structure Property Relationship (QSPR) modeling to relate metal ions characteristics with adsorption potential of Ficus carica leaves for 13 selected metal ions (Ca +2 , Cr +3 , Co +2 , Cu +2 , Cd +2 , K +1 , Mg +2 , Mn +2 , Na +1 , Ni +2 , Pb +2 , Zn +2 , and Fe +2 ) to generate QSPR model. A set of 21 characteristic descriptors were selected and relationship of these metal characteristics with adsorptive behavior of metal ions was investigated. Stepwise Multiple Linear Regression (SMLR) analysis and Artificial Neural Network (ANN) were applied for descriptors selection and model generation. Langmuir and Freundlich isotherms were also applied on adsorption data to generate proper correlation for experimental findings. Model generated indicated covalent index as the most significant descriptor, which is responsible for more than 90% predictive adsorption (α = 0.05). Internal validation of model was performed by measuring [Formula: see text] (0.98). The results indicate that present model is a useful tool for prediction of adsorptive behavior of different metal ions based on their ionic characteristics.
Using Delft3D to Simulate Current Energy Conversion

NASA Astrophysics Data System (ADS)

James, S. C.; Chartrand, C.; Roberts, J.

2015-12-01

As public concern with renewable energy increases, current energy conversion (CEC) technology is being developed to optimize energy output and minimize environmental impact. CEC turbines generate energy from tidal and current systems and create wakes that interact with turbines located downstream of a device. The placement of devices can greatly influence power generation and structural reliability. CECs can also alter the ecosystem process surrounding the turbines, such as flow regimes, sediment dynamics, and water quality. Software is needed to investigate specific CEC sites to simulate power generation and hydrodynamic responses of a flow through a CEC turbine array. This work validates Delft3D against several flume experiments by simulating the power generation and hydrodynamic response of flow through a turbine or actuator disc(s). Model parameters are then calibrated against these data sets to reproduce momentum removal and wake recovery data with 3-D flow simulations. Simulated wake profiles and turbulence intensities compare favorably to the experimental data and demonstrate the utility and accuracy of a fast-running tool for future siting and analysis of CEC arrays in complex domains.
QSPR models for predicting generator-column-derived octanol/water and octanol/air partition coefficients of polychlorinated biphenyls.

PubMed

Yuan, Jintao; Yu, Shuling; Zhang, Ting; Yuan, Xuejie; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu

2016-06-01

Octanol/water (K(OW)) and octanol/air (K(OA)) partition coefficients are two important physicochemical properties of organic substances. In current practice, K(OW) and K(OA) values of some polychlorinated biphenyls (PCBs) are measured using generator column method. Quantitative structure-property relationship (QSPR) models can serve as a valuable alternative method of replacing or reducing experimental steps in the determination of K(OW) and K(OA). In this paper, two different methods, i.e., multiple linear regression based on dragon descriptors and hologram quantitative structure-activity relationship, were used to predict generator-column-derived log K(OW) and log K(OA) values of PCBs. The predictive ability of the developed models was validated using a test set, and the performances of all generated models were compared with those of three previously reported models. All results indicated that the proposed models were robust and satisfactory and can thus be used as alternative models for the rapid assessment of the K(OW) and K(OA) of PCBs. Copyright © 2016 Elsevier Inc. All rights reserved.
Construction and validation of the fatigue impact and severity self-assessment for youth and young adults with cerebral palsy.

PubMed

Brunton, Laura K; Bartlett, Doreen J

2017-07-01

The Fatigue Impact and Severity Self-Assessment (FISSA) was created to assess the impact, severity, and self-management of fatigue for individuals with cerebral palsy (CP) aged 14-31 years. Items were generated from a review of measures and interviews with individuals with CP. Focus groups with health-care professionals were used for item reduction. A mailed survey was conducted (n=163/367) to assess the factor structure, known-groups validity, and test-retest reliability. The final measure contained 31 items in two factors and discriminated between individuals expected to have different levels of fatigue. Individuals with more functional abilities reported less fatigue (p < 0.002) and those with higher pain reported higher fatigue (p < 0.001). The FISSA was shown to have adequate test-retest reliability, intraclass correlation coefficient (ICC)(3,1)=0.74 (95% confidence interval [CI] 0.53-0.87). The FISSA valid and reliable for individuals with CP. It allows for identification of the activities that may be compromised by fatigue to enhance collaborative goal setting and intervention planning.
Introduction to Bayesian statistical approaches to compositional analyses of transgenic crops 1. Model validation and setting the stage.

PubMed

Harrison, Jay M; Breeze, Matthew L; Harrigan, George G

2011-08-01

Statistical comparisons of compositional data generated on genetically modified (GM) crops and their near-isogenic conventional (non-GM) counterparts typically rely on classical significance testing. This manuscript presents an introduction to Bayesian methods for compositional analysis along with recommendations for model validation. The approach is illustrated using protein and fat data from two herbicide tolerant GM soybeans (MON87708 and MON87708×MON89788) and a conventional comparator grown in the US in 2008 and 2009. Guidelines recommended by the US Food and Drug Administration (FDA) in conducting Bayesian analyses of clinical studies on medical devices were followed. This study is the first Bayesian approach to GM and non-GM compositional comparisons. The evaluation presented here supports a conclusion that a Bayesian approach to analyzing compositional data can provide meaningful and interpretable results. We further describe the importance of method validation and approaches to model checking if Bayesian approaches to compositional data analysis are to be considered viable by scientists involved in GM research and regulation. Copyright © 2011 Elsevier Inc. All rights reserved.
Exploring the Validity of the Affect Balance Scale With a Sample of Family Caregivers

PubMed Central

Perkinson, Margaret A.; Albert, Steven M.; Luborsky, Mark; Moss, Miriam; Glicksman, Allen

2014-01-01

Open-ended responses of caregiving daughters and daughters-in-law were generated by a modified random probe technique to investigate the construct validity of the two subscales of the Affect Balance Scale (ABS), i.e., the 5-item Positive Affect Scale (PAS) and the 5-item Negative Affect Scale (NAS). A set of criteria were developed to distinguish between responses that did and did not correspond to Bradburn’s assumptions concerning affect. While most responses met at least one of the criteria, very few met all. In exploring the nature of affect, we found that positive affect was based to a large extent on personal accomplishments and the recognition of others. The assessment of negative affect was a more interior, or self-focused process. For a significant subset of the sample, a negative response to a closed-ended PAS or NAS item implied disagreement or discontent with the wording or the implications of the item itself, rather than an absence of affect. Not all of the ABS items were equally valid measures of affect. PMID:8056955
4D-Fingerprint Categorical QSAR Models for Skin Sensitization Based on Classification Local Lymph Node Assay Measures

PubMed Central

Li, Yi; Tseng, Yufeng J.; Pan, Dahua; Liu, Jianzhong; Kern, Petra S.; Gerberick, G. Frank; Hopfinger, Anton J.

2008-01-01

Currently, the only validated methods to identify skin sensitization effects are in vivo models, such as the Local Lymph Node Assay (LLNA) and guinea pig studies. There is a tremendous need, in particular due to novel legislation, to develop animal alternatives, eg. Quantitative Structure-Activity Relationship (QSAR) models. Here, QSAR models for skin sensitization using LLNA data have been constructed. The descriptors used to generate these models are derived from the 4D-molecular similarity paradigm and are referred to as universal 4D-fingerprints. A training set of 132 structurally diverse compounds and a test set of 15 structurally diverse compounds were used in this study. The statistical methodologies used to build the models are logistic regression (LR), and partial least square coupled logistic regression (PLS-LR), which prove to be effective tools for studying skin sensitization measures expressed in the two categorical terms of sensitizer and non-sensitizer. QSAR models with low values of the Hosmer-Lemeshow goodness-of-fit statistic, χHL2, are significant and predictive. For the training set, the cross-validated prediction accuracy of the logistic regression models ranges from 77.3% to 78.0%, while that of PLS-logistic regression models ranges from 87.1% to 89.4%. For the test set, the prediction accuracy of logistic regression models ranges from 80.0%-86.7%, while that of PLS-logistic regression models ranges from 73.3%-80.0%. The QSAR models are made up of 4D-fingerprints related to aromatic atoms, hydrogen bond acceptors and negatively partially charged atoms. PMID:17226934
Topsoil pollution forecasting using artificial neural networks on the example of the abnormally distributed heavy metal at Russian subarctic

NASA Astrophysics Data System (ADS)

Tarasov, D. A.; Buevich, A. G.; Sergeev, A. P.; Shichkin, A. V.; Baglaeva, E. M.

2017-06-01

Forecasting the soil pollution is a considerable field of study in the light of the general concern of environmental protection issues. Due to the variation of content and spatial heterogeneity of pollutants distribution at urban areas, the conventional spatial interpolation models implemented in many GIS packages mostly cannot provide appreciate interpolation accuracy. Moreover, the problem of prediction the distribution of the element with high variability in the concentration at the study site is particularly difficult. The work presents two neural networks models forecasting a spatial content of the abnormally distributed soil pollutant (Cr) at a particular location of the subarctic Novy Urengoy, Russia. A method of generalized regression neural network (GRNN) was compared to a common multilayer perceptron (MLP) model. The proposed techniques have been built, implemented and tested using ArcGIS and MATLAB. To verify the models performances, 150 scattered input data points (pollutant concentrations) have been selected from 8.5 km2 area and then split into independent training data set (105 points) and validation data set (45 points). The training data set was generated for the interpolation using ordinary kriging while the validation data set was used to test their accuracies. The networks structures have been chosen during a computer simulation based on the minimization of the RMSE. The predictive accuracy of both models was confirmed to be significantly higher than those achieved by the geostatistical approach (kriging). It is shown that MLP could achieve better accuracy than both kriging and even GRNN for interpolating surfaces.
Edge detection for optical synthetic aperture based on deep neural network

NASA Astrophysics Data System (ADS)

Tan, Wenjie; Hui, Mei; Liu, Ming; Kong, Lingqin; Dong, Liquan; Zhao, Yuejin

2017-09-01

Synthetic aperture optics systems can meet the demands of the next-generation space telescopes being lighter, larger and foldable. However, the boundaries of segmented aperture systems are much more complex than that of the whole aperture. More edge regions mean more imaging edge pixels, which are often mixed and discretized. In order to achieve high-resolution imaging, it is necessary to identify the gaps between the sub-apertures and the edges of the projected fringes. In this work, we introduced the algorithm of Deep Neural Network into the edge detection of optical synthetic aperture imaging. According to the detection needs, we constructed image sets by experiments and simulations. Based on MatConvNet, a toolbox of MATLAB, we ran the neural network, trained it on training image set and tested its performance on validation set. The training was stopped when the test error on validation set stopped declining. As an input image is given, each intra-neighbor area around the pixel is taken into the network, and scanned pixel by pixel with the trained multi-hidden layers. The network outputs make a judgment on whether the center of the input block is on edge of fringes. We experimented with various pre-processing and post-processing techniques to reveal their influence on edge detection performance. Compared with the traditional algorithms or their improvements, our method makes decision on a much larger intra-neighbor, and is more global and comprehensive. Experiments on more than 2,000 images are also given to prove that our method outperforms classical algorithms in optical images-based edge detection.
Preservation and Modification of Culture in Family Socialization: Development of Parenting Measures for Korean Immigrant Families

PubMed Central

Choi, Yoonsun; Kim, You Seung; Drankus, Dina; Kim, Hyun Jee

2012-01-01

This study aims to describe the family socialization beliefs and practices of Korean immigrant parents through testing psychometric properties of several newly developed items and scales to assess the major components of the Korean traditional concept of family socialization, ga-jung-kyo-yuk. These new measures were examined for validity and reliability. The findings show that Korean immigrant parents largely preserve their traditional and core parenting values, while also showing meaningful, yet not very dramatic, signs of adopting new cultural traits. The results also suggest that the acculturative process may not be simply bilinear but may generate a new, unique and blended value and behavior set from the two (or more) cultures involved. Culturally appropriate practice requires not only further validation of existing knowledge with minority groups, but the development of a theoretical framework of family socialization that recognizes the cultural uniqueness of immigrant families. PMID:24765236
Baseline performance of the GPU 3 Stirling engine

NASA Technical Reports Server (NTRS)

Thieme, L. G.; Tew, R. C., Jr.

1978-01-01

A 10 horsepower single-cylinder rhombic-drive Stirling engine was converted to a research configuration to obtain data for validation of Stirling computer simulations. The engine was originally built by General Motors Research Laboratories for the U.S. Army in 1965 as part of a 3 kW engine-generator set, designated the GHU 3 (Ground Power Unit). This report presents test results for a range of heater gas temperatures, mean compression-space pressures, and engine speeds with both helium and hydrogen as the working fluids. Also shown are initial data comparisons with computer simulation predictions.
oPOSSUM-3: Advanced Analysis of Regulatory Motif Over-Representation Across Genes or ChIP-Seq Datasets

PubMed Central

Kwon, Andrew T.; Arenillas, David J.; Hunt, Rebecca Worsley; Wasserman, Wyeth W.

2012-01-01

oPOSSUM-3 is a web-accessible software system for identification of over-represented transcription factor binding sites (TFBS) and TFBS families in either DNA sequences of co-expressed genes or sequences generated from high-throughput methods, such as ChIP-Seq. Validation of the system with known sets of co-regulated genes and published ChIP-Seq data demonstrates the capacity for oPOSSUM-3 to identify mediating transcription factors (TF) for co-regulated genes or co-recovered sequences. oPOSSUM-3 is available at http://opossum.cisreg.ca. PMID:22973536
oPOSSUM-3: advanced analysis of regulatory motif over-representation across genes or ChIP-Seq datasets.

PubMed

Kwon, Andrew T; Arenillas, David J; Worsley Hunt, Rebecca; Wasserman, Wyeth W

2012-09-01

oPOSSUM-3 is a web-accessible software system for identification of over-represented transcription factor binding sites (TFBS) and TFBS families in either DNA sequences of co-expressed genes or sequences generated from high-throughput methods, such as ChIP-Seq. Validation of the system with known sets of co-regulated genes and published ChIP-Seq data demonstrates the capacity for oPOSSUM-3 to identify mediating transcription factors (TF) for co-regulated genes or co-recovered sequences. oPOSSUM-3 is available at http://opossum.cisreg.ca.
Correcting Evaluation Bias of Relational Classifiers with Network Cross Validation

DTIC Science & Technology

2010-01-01

classi- fication algorithms: simple random resampling (RRS), equal-instance random resampling (ERS), and network cross-validation ( NCV ). The first two... NCV procedure that eliminates overlap between test sets altogether. The procedure samples for k disjoint test sets that will be used for evaluation...propLabeled ∗ S) nodes from train Pool in f erenceSet =network − trainSet F = F ∪ < trainSet, test Set, in f erenceSet > end for output: F NCV addresses
Exploring discrepancies between quantitative validation results and the geomorphic plausibility of statistical landslide susceptibility maps

NASA Astrophysics Data System (ADS)

Steger, Stefan; Brenning, Alexander; Bell, Rainer; Petschko, Helene; Glade, Thomas

2016-06-01

Empirical models are frequently applied to produce landslide susceptibility maps for large areas. Subsequent quantitative validation results are routinely used as the primary criteria to infer the validity and applicability of the final maps or to select one of several models. This study hypothesizes that such direct deductions can be misleading. The main objective was to explore discrepancies between the predictive performance of a landslide susceptibility model and the geomorphic plausibility of subsequent landslide susceptibility maps while a particular emphasis was placed on the influence of incomplete landslide inventories on modelling and validation results. The study was conducted within the Flysch Zone of Lower Austria (1,354 km2) which is known to be highly susceptible to landslides of the slide-type movement. Sixteen susceptibility models were generated by applying two statistical classifiers (logistic regression and generalized additive model) and two machine learning techniques (random forest and support vector machine) separately for two landslide inventories of differing completeness and two predictor sets. The results were validated quantitatively by estimating the area under the receiver operating characteristic curve (AUROC) with single holdout and spatial cross-validation technique. The heuristic evaluation of the geomorphic plausibility of the final results was supported by findings of an exploratory data analysis, an estimation of odds ratios and an evaluation of the spatial structure of the final maps. The results showed that maps generated by different inventories, classifiers and predictors appeared differently while holdout validation revealed similar high predictive performances. Spatial cross-validation proved useful to expose spatially varying inconsistencies of the modelling results while additionally providing evidence for slightly overfitted machine learning-based models. However, the highest predictive performances were obtained for maps that explicitly expressed geomorphically implausible relationships indicating that the predictive performance of a model might be misleading in the case a predictor systematically relates to a spatially consistent bias of the inventory. Furthermore, we observed that random forest-based maps displayed spatial artifacts. The most plausible susceptibility map of the study area showed smooth prediction surfaces while the underlying model revealed a high predictive capability and was generated with an accurate landslide inventory and predictors that did not directly describe a bias. However, none of the presented models was found to be completely unbiased. This study showed that high predictive performances cannot be equated with a high plausibility and applicability of subsequent landslide susceptibility maps. We suggest that greater emphasis should be placed on identifying confounding factors and biases in landslide inventories. A joint discussion between modelers and decision makers of the spatial pattern of the final susceptibility maps in the field might increase their acceptance and applicability.
An empirical model for prediction of household solid waste generation rate - A case study of Dhanbad, India.

PubMed

Kumar, Atul; Samadder, S R

2017-10-01

Accurate prediction of the quantity of household solid waste generation is very much essential for effective management of municipal solid waste (MSW). In actual practice, modelling methods are often found useful for precise prediction of MSW generation rate. In this study, two models have been proposed that established the relationships between the household solid waste generation rate and the socioeconomic parameters, such as household size, total family income, education, occupation and fuel used in the kitchen. Multiple linear regression technique was applied to develop the two models, one for the prediction of biodegradable MSW generation rate and the other for non-biodegradable MSW generation rate for individual households of the city Dhanbad, India. The results of the two models showed that the coefficient of determinations (R 2 ) were 0.782 for biodegradable waste generation rate and 0.676 for non-biodegradable waste generation rate using the selected independent variables. The accuracy tests of the developed models showed convincing results, as the predicted values were very close to the observed values. Validation of the developed models with a new set of data indicated a good fit for actual prediction purpose with predicted R 2 values of 0.76 and 0.64 for biodegradable and non-biodegradable MSW generation rate respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.
Development and validation of an improved mechanical thorax for simulating cardiopulmonary resuscitation with adjustable chest stiffness and simulated blood flow.

PubMed

Eichhorn, Stefan; Spindler, Johannes; Polski, Marcin; Mendoza, Alejandro; Schreiber, Ulrich; Heller, Michael; Deutsch, Marcus Andre; Braun, Christian; Lange, Rüdiger; Krane, Markus

2017-05-01

Investigations of compressive frequency, duty cycle, or waveform during CPR are typically rooted in animal research or computer simulations. Our goal was to generate a mechanical model incorporating alternate stiffness settings and an integrated blood flow system, enabling defined, reproducible comparisons of CPR efficacy. Based on thoracic stiffness data measured in human cadavers, such a model was constructed using valve-controlled pneumatic pistons and an artificial heart. This model offers two realistic levels of chest elasticity, with a blood flow apparatus that reflects compressive depth and waveform changes. We conducted CPR at opposing levels of physiologic stiffness, using a LUCAS device, a motor-driven plunger, and a group of volunteers. In high-stiffness mode, blood flow generated by volunteers was significantly less after just 2min of CPR, whereas flow generated by LUCAS device was superior by comparison. Optimal blood flow was obtained via motor-driven plunger, with trapezoidal waveform. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.
A comprehensive tool for image-based generation of fetus and pregnant women mesh models for numerical dosimetry studies

NASA Astrophysics Data System (ADS)

Dahdouh, S.; Varsier, N.; Serrurier, A.; De la Plata, J.-P.; Anquez, J.; Angelini, E. D.; Wiart, J.; Bloch, I.

2014-08-01

Fetal dosimetry studies require the development of accurate numerical 3D models of the pregnant woman and the fetus. This paper proposes a 3D articulated fetal growth model covering the main phases of pregnancy and a pregnant woman model combining the utero-fetal structures and a deformable non-pregnant woman body envelope. The structures of interest were automatically or semi-automatically (depending on the stage of pregnancy) segmented from a database of images and surface meshes were generated. By interpolating linearly between fetal structures, each one can be generated at any age and in any position. A method is also described to insert the utero-fetal structures in the maternal body. A validation of the fetal models is proposed, comparing a set of biometric measurements to medical reference charts. The usability of the pregnant woman model in dosimetry studies is also investigated, with respect to the influence of the abdominal fat layer.
3D foot shape generation from 2D information.

PubMed

Luximon, Ameersing; Goonetilleke, Ravindra S; Zhang, Ming

2005-05-15

Two methods to generate an individual 3D foot shape from 2D information are proposed. A standard foot shape was first generated and then scaled based on known 2D information. In the first method, the foot outline and the foot height were used, and in the second, the foot outline and the foot profile were used. The models were developed using 40 participants and then validated using a different set of 40 participants. Results show that each individual foot shape can be predicted within a mean absolute error of 1.36 mm for the left foot and 1.37 mm for the right foot using the first method, and within a mean absolute error of 1.02 mm for the left foot and 1.02 mm for the right foot using the second method. The second method shows somewhat improved accuracy even though it requires two images. Both the methods are relatively cheaper than using a scanner to determine the 3D foot shape for custom footwear design.

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