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Sample records for 10-fold cross-validation approach

  1. Comprehensive Assessment of Emotional Disturbance: A Cross-Validation Approach

    ERIC Educational Resources Information Center

    Fisher, Emily S.; Doyon, Katie E.; Saldana, Enrique; Allen, Megan Redding

    2007-01-01

    Assessing a student for emotional disturbance is a serious and complex task given the stigma of the label and the ambiguities of the federal definition. One way that school psychologists can be more confident in their assessment results is to cross validate data from different sources using the RIOT approach (Review, Interview, Observe, Test).…

  2. Cross-Validation.

    ERIC Educational Resources Information Center

    Langmuir, Charles R.

    1954-01-01

    Cross-validation in relation to choosing the best tests and selecting the best items in tests is discussed. Cross-validation demonstrated whether a decision derived from one set of data is truly effective when this decision is applied to another independent, but relevant, sample of people. Cross-validation is particularly important after…

  3. Do different decision-analytic modeling approaches produce different results? A systematic review of cross-validation studies.

    PubMed

    Tsoi, Bernice; Goeree, Ron; Jegathisawaran, Jathishinie; Tarride, Jean-Eric; Blackhouse, Gord; O'Reilly, Daria

    2015-06-01

    When choosing a modeling approach for health economic evaluation, certain criteria are often considered (e.g., population resolution, interactivity, time advancement mechanism, resource constraints). However, whether these criteria and their associated modeling approach impacts results remain poorly understood. A systematic review was conducted to identify cross-validation studies (i.e., modeling a problem using different approaches with the same body of evidence) to offer insight on this topic. With respect to population resolution, reviewed studies suggested that both aggregate- and individual-level models will generate comparable results, although a practical trade-off exists between validity and feasibility. In terms of interactivity, infectious-disease models consistently showed that, depending on the assumptions regarding probability of disease exposure, dynamic and static models may produce dissimilar results with opposing policy recommendations. Empirical evidence on the remaining criteria is limited. Greater discussion will therefore be necessary to promote a deeper understanding of the benefits and limits to each modeling approach. PMID:25728942

  4. Cross-Validated Bagged Learning

    PubMed Central

    Petersen, Maya L.; Molinaro, Annette M.; Sinisi, Sandra E.; van der Laan, Mark J.

    2007-01-01

    Many applications aim to learn a high dimensional parameter of a data generating distribution based on a sample of independent and identically distributed observations. For example, the goal might be to estimate the conditional mean of an outcome given a list of input variables. In this prediction context, bootstrap aggregating (bagging) has been introduced as a method to reduce the variance of a given estimator at little cost to bias. Bagging involves applying an estimator to multiple bootstrap samples, and averaging the result across bootstrap samples. In order to address the curse of dimensionality, a common practice has been to apply bagging to estimators which themselves use cross-validation, thereby using cross-validation within a bootstrap sample to select fine-tuning parameters trading off bias and variance of the bootstrap sample-specific candidate estimators. In this article we point out that in order to achieve the correct bias variance trade-off for the parameter of interest, one should apply the cross-validation selector externally to candidate bagged estimators indexed by these fine-tuning parameters. We use three simulations to compare the new cross-validated bagging method with bagging of cross-validated estimators and bagging of non-cross-validated estimators. PMID:19255599

  5. Cross-Validation, Shrinkage, and Multiple Regression.

    ERIC Educational Resources Information Center

    Hynes, Kevin

    One aspect of multiple regression--the shrinkage of the multiple correlation coefficient on cross-validation is reviewed. The paper consists of four sections. In section one, the distinction between a fixed and a random multiple regression model is made explicit. In section two, the cross-validation paradigm and an explanation for the occurrence…

  6. The Proximal Trajectory Algorithm in SVM Cross Validation.

    PubMed

    Astorino, Annabella; Fuduli, Antonio

    2016-05-01

    We propose a bilevel cross-validation scheme for support vector machine (SVM) model selection based on the construction of the entire regularization path. Since such path is a particular case of the more general proximal trajectory concept from nonsmooth optimization, we propose for its construction an algorithm based on solving a finite number of structured linear programs. Our methodology, differently from other approaches, works directly on the primal form of SVM. Numerical results are presented on binary data sets drawn from literature. PMID:27101080

  7. Cross validation in LASSO and its acceleration

    NASA Astrophysics Data System (ADS)

    Obuchi, Tomoyuki; Kabashima, Yoshiyuki

    2016-05-01

    We investigate leave-one-out cross validation (CV) as a determinator of the weight of the penalty term in the least absolute shrinkage and selection operator (LASSO). First, on the basis of the message passing algorithm and a perturbative discussion assuming that the number of observations is sufficiently large, we provide simple formulas for approximately assessing two types of CV errors, which enable us to significantly reduce the necessary cost of computation. These formulas also provide a simple connection of the CV errors to the residual sums of squares between the reconstructed and the given measurements. Second, on the basis of this finding, we analytically evaluate the CV errors when the design matrix is given as a simple random matrix in the large size limit by using the replica method. Finally, these results are compared with those of numerical simulations on finite-size systems and are confirmed to be correct. We also apply the simple formulas of the first type of CV error to an actual dataset of the supernovae.

  8. Application of Discriminant Analysis and Cross-Validation on Proteomics Data.

    PubMed

    Kuligowski, Julia; Pérez-Guaita, David; Quintás, Guillermo

    2016-01-01

    High-throughput proteomic experiments have raised the importance and complexity of bioinformatic analysis to extract useful information from raw data. Discriminant analysis is frequently used to identify differences among test groups of individuals or to describe combinations of discriminant variables. However, even in relatively large studies, the number of detected variables typically largely exceeds the number of samples and the classifiers should be thoroughly validated to assess their performance for new samples. Cross-validation is a widely approach when an external validation set is not available. In this chapter, different approaches for cross-validation are presented including relevant aspects that should be taken into account to avoid overly optimistic results and the assessment of the statistical significance of cross-validated figures of merit. PMID:26519177

  9. Cross-validation of component models: a critical look at current methods.

    PubMed

    Bro, R; Kjeldahl, K; Smilde, A K; Kiers, H A L

    2008-03-01

    In regression, cross-validation is an effective and popular approach that is used to decide, for example, the number of underlying features, and to estimate the average prediction error. The basic principle of cross-validation is to leave out part of the data, build a model, and then predict the left-out samples. While such an approach can also be envisioned for component models such as principal component analysis (PCA), most current implementations do not comply with the essential requirement that the predictions should be independent of the entity being predicted. Further, these methods have not been properly reviewed in the literature. In this paper, we review the most commonly used generic PCA cross-validation schemes and assess how well they work in various scenarios. PMID:18214448

  10. Formula Estimation of Cross-Validated Multiple Correlation.

    ERIC Educational Resources Information Center

    Schmitt, Neal

    A review of cross-validation shrinkage formulas is presented which focuses on the theoretical and practical problems in the use of various formulas. Practical guidelines for use of both formulas and empirical cross-validation are provided. A comparison of results using these formulas in a range of situations is then presented. The result of these…

  11. A K-fold Averaging Cross-validation Procedure

    PubMed Central

    Jung, Yoonsuh; Hu, Jianhua

    2015-01-01

    Cross-validation type of methods have been widely used to facilitate model estimation and variable selection. In this work, we suggest a new K-fold cross validation procedure to select a candidate ‘optimal’ model from each hold-out fold and average the K candidate ‘optimal’ models to obtain the ultimate model. Due to the averaging effect, the variance of the proposed estimates can be significantly reduced. This new procedure results in more stable and efficient parameter estimation than the classical K-fold cross validation procedure. In addition, we show the asymptotic equivalence between the proposed and classical cross validation procedures in the linear regression setting. We also demonstrate the broad applicability of the proposed procedure via two examples of parameter sparsity regularization and quantile smoothing splines modeling. We illustrate the promise of the proposed method through simulations and a real data example.

  12. A cross-validation package driving Netica with python

    USGS Publications Warehouse

    Fienen, Michael N.; Plant, Nathaniel G.

    2014-01-01

    Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica is open-source, written in Python, and extends the Netica software package to perform cross-validation and read, rebuild, and learn BNs from data. Insights gained from cross-validation and implications on prediction versus description are illustrated with: a data-driven oceanographic application; and a model-emulation application. These examples show that overfitting occurs when BNs become more complex than allowed by supporting data and overfitting incurs computational costs as well as causing a reduction in prediction skill. CVNetica evaluates overfitting using several complexity metrics (we used level of discretization) and its impact on performance metrics (we used skill).

  13. Attrition from an Adolescent Addiction Treatment Program: A Cross Validation.

    ERIC Educational Resources Information Center

    Mathisen, Kenneth S.; Meyers, Kathleen

    Treatment attrition is a major problem for programs treating adolescent substance abusers. To isolate and cross validate factors which are predictive of addiction treatment attrition among adolescent substance abusers, screening interview and diagnostic variables from 119 adolescent in-patients were submitted to a discriminant equation analysis.…

  14. The Cross Validation of the Attitudes toward Mainstreaming Scale (ATMS).

    ERIC Educational Resources Information Center

    Berryman, Joan D.; Neal, W. R. Jr.

    1980-01-01

    Reliability and factorial validity of the Attitudes Toward Mainstreaming Scale was supported in a cross-validation study with teachers. Three factors emerged: learning capability, general mainstreaming, and traditional limiting disabilities. Factor intercorrelations varied from .42 to .55; correlations between total scores and individual factors…

  15. Fit-for-purpose bioanalytical cross-validation for LC-MS/MS assays in clinical studies.

    PubMed

    Xu, Xiaohui; Ji, Qin C; Jemal, Mohammed; Gleason, Carol; Shen, Jim X; Stouffer, Bruce; Arnold, Mark E

    2013-01-01

    The paradigm shift of globalized research and conducting clinical studies at different geographic locations worldwide to access broader patient populations has resulted in increased need of correlating bioanalytical results generated in multiple laboratories, often across national borders. Cross-validations of bioanalytical methods are often implemented to assure the equivalency of the bioanalytical results is demonstrated. Regulatory agencies, such as the US FDA and European Medicines Agency, have included the requirement of cross-validations in their respective bioanalytical validation guidance and guidelines. While those documents provide high-level expectations, the detailed implementation is at the discretion of each individual organization. At Bristol-Myers Squibb, we practice a fit-for-purpose approach for conducting cross-validations for small-molecule bioanalytical methods using LC-MS/MS. A step-by-step proposal on the overall strategy, procedures and technical details for conducting a successful cross-validation is presented herein. A case study utilizing the proposed cross-validation approach to rule out method variability as the potential cause for high variance observed in PK studies is also presented. PMID:23256474

  16. Benchmarking protein classification algorithms via supervised cross-validation.

    PubMed

    Kertész-Farkas, Attila; Dhir, Somdutta; Sonego, Paolo; Pacurar, Mircea; Netoteia, Sergiu; Nijveen, Harm; Kuzniar, Arnold; Leunissen, Jack A M; Kocsor, András; Pongor, Sándor

    2008-04-24

    Development and testing of protein classification algorithms are hampered by the fact that the protein universe is characterized by groups vastly different in the number of members, in average protein size, similarity within group, etc. Datasets based on traditional cross-validation (k-fold, leave-one-out, etc.) may not give reliable estimates on how an algorithm will generalize to novel, distantly related subtypes of the known protein classes. Supervised cross-validation, i.e., selection of test and train sets according to the known subtypes within a database has been successfully used earlier in conjunction with the SCOP database. Our goal was to extend this principle to other databases and to design standardized benchmark datasets for protein classification. Hierarchical classification trees of protein categories provide a simple and general framework for designing supervised cross-validation strategies for protein classification. Benchmark datasets can be designed at various levels of the concept hierarchy using a simple graph-theoretic distance. A combination of supervised and random sampling was selected to construct reduced size model datasets, suitable for algorithm comparison. Over 3000 new classification tasks were added to our recently established protein classification benchmark collection that currently includes protein sequence (including protein domains and entire proteins), protein structure and reading frame DNA sequence data. We carried out an extensive evaluation based on various machine-learning algorithms such as nearest neighbor, support vector machines, artificial neural networks, random forests and logistic regression, used in conjunction with comparison algorithms, BLAST, Smith-Waterman, Needleman-Wunsch, as well as 3D comparison methods DALI and PRIDE. The resulting datasets provide lower, and in our opinion more realistic estimates of the classifier performance than do random cross-validation schemes. A combination of supervised and

  17. Free kick instead of cross-validation in maximum-likelihood refinement of macromolecular crystal structures

    SciTech Connect

    Pražnikar, Jure; Turk, Dušan

    2014-12-01

    The maximum-likelihood free-kick target, which calculates model error estimates from the work set and a randomly displaced model, proved superior in the accuracy and consistency of refinement of crystal structures compared with the maximum-likelihood cross-validation target, which calculates error estimates from the test set and the unperturbed model. The refinement of a molecular model is a computational procedure by which the atomic model is fitted to the diffraction data. The commonly used target in the refinement of macromolecular structures is the maximum-likelihood (ML) function, which relies on the assessment of model errors. The current ML functions rely on cross-validation. They utilize phase-error estimates that are calculated from a small fraction of diffraction data, called the test set, that are not used to fit the model. An approach has been developed that uses the work set to calculate the phase-error estimates in the ML refinement from simulating the model errors via the random displacement of atomic coordinates. It is called ML free-kick refinement as it uses the ML formulation of the target function and is based on the idea of freeing the model from the model bias imposed by the chemical energy restraints used in refinement. This approach for the calculation of error estimates is superior to the cross-validation approach: it reduces the phase error and increases the accuracy of molecular models, is more robust, provides clearer maps and may use a smaller portion of data for the test set for the calculation of R{sub free} or may leave it out completely.

  18. Cost-Benefit Considerations in Choosing among Cross-Validation Methods.

    ERIC Educational Resources Information Center

    Murphy, Kevin R.

    There are two general methods of cross-validation: empirical estimation, and formula estimation. In choosing a specific cross-validation procedure, one should consider both costs (e.g., inefficient use of available data in estimating regression parameters) and benefits (e.g., accuracy in estimating population cross-validity). Empirical…

  19. Predicting IQ change from brain structure: A cross-validation study

    PubMed Central

    Price, C.J.; Ramsden, S.; Hope, T.M.H.; Friston, K.J.; Seghier, M.L.

    2013-01-01

    Procedures that can predict cognitive abilities from brain imaging data are potentially relevant to educational assessments and studies of functional anatomy in the developing brain. Our aim in this work was to quantify the degree to which IQ change in the teenage years could be predicted from structural brain changes. Two well-known k-fold cross-validation analyses were applied to data acquired from 33 healthy teenagers – each tested at Time 1 and Time 2 with a 3.5 year interval. One approach, a Leave-One-Out procedure, predicted IQ change for each subject on the basis of structural change in a brain region that was identified from all other subjects (i.e., independent data). This approach predicted 53% of verbal IQ change and 14% of performance IQ change. The other approach used half the sample, to identify regions for predicting IQ change in the other half (i.e., a Split half approach); however – unlike the Leave-One-Out procedure – regions identified using half the sample were not significant. We discuss how these out-of-sample estimates compare to in-sample estimates; and draw some recommendations for k-fold cross-validation procedures when dealing with small datasets that are typical in the neuroimaging literature. PMID:23567505

  20. Cross-Validation of Aerobic Capacity Prediction Models in Adolescents.

    PubMed

    Burns, Ryan Donald; Hannon, James C; Brusseau, Timothy A; Eisenman, Patricia A; Saint-Maurice, Pedro F; Welk, Greg J; Mahar, Matthew T

    2015-08-01

    Cardiorespiratory endurance is a component of health-related fitness. FITNESSGRAM recommends the Progressive Aerobic Cardiovascular Endurance Run (PACER) or One mile Run/Walk (1MRW) to assess cardiorespiratory endurance by estimating VO2 Peak. No research has cross-validated prediction models from both PACER and 1MRW, including the New PACER Model and PACER-Mile Equivalent (PACER-MEQ) using current standards. The purpose of this study was to cross-validate prediction models from PACER and 1MRW against measured VO2 Peak in adolescents. Cardiorespiratory endurance data were collected on 90 adolescents aged 13-16 years (Mean = 14.7 ± 1.3 years; 32 girls, 52 boys) who completed the PACER and 1MRW in addition to a laboratory maximal treadmill test to measure VO2 Peak. Multiple correlations among various models with measured VO2 Peak were considered moderately strong (R = .74-0.78), and prediction error (RMSE) ranged from 5.95 ml·kg⁻¹,min⁻¹ to 8.27 ml·kg⁻¹.min⁻¹. Criterion-referenced agreement into FITNESSGRAM's Healthy Fitness Zones was considered fair-to-good among models (Kappa = 0.31-0.62; Agreement = 75.5-89.9%; F = 0.08-0.65). In conclusion, prediction models demonstrated moderately strong linear relationships with measured VO2 Peak, fair prediction error, and fair-to-good criterion referenced agreement with measured VO2 Peak into FITNESSGRAM's Healthy Fitness Zones. PMID:26186536

  1. Cross-validation analysis of bias models in Bayesian multi-model projections of climate

    NASA Astrophysics Data System (ADS)

    Huttunen, J. M. J.; Räisänen, J.; Nissinen, A.; Lipponen, A.; Kolehmainen, V.

    2016-05-01

    Climate change projections are commonly based on multi-model ensembles of climate simulations. In this paper we consider the choice of bias models in Bayesian multimodel predictions. Buser et al. (Clim Res 44(2-3):227-241, 2010a) introduced a hybrid bias model which combines commonly used constant bias and constant relation bias assumptions. The hybrid model includes a weighting parameter which balances these bias models. In this study, we use a cross-validation approach to study which bias model or bias parameter leads to, in a specific sense, optimal climate change projections. The analysis is carried out for summer and winter season means of 2 m-temperatures spatially averaged over the IPCC SREX regions, using 19 model runs from the CMIP5 data set. The cross-validation approach is applied to calculate optimal bias parameters (in the specific sense) for projecting the temperature change from the control period (1961-2005) to the scenario period (2046-2090). The results are compared to the results of the Buser et al. (Clim Res 44(2-3):227-241, 2010a) method which includes the bias parameter as one of the unknown parameters to be estimated from the data.

  2. International cross-validation of a BOD5 surrogate.

    PubMed

    Muller, Mathieu; Bouguelia, Sihem; Goy, Romy-Alice; Yoris, Alison; Berlin, Jeanne; Meche, Perrine; Rocher, Vincent; Mertens, Sharon; Dudal, Yves

    2014-12-01

    BOD5 dates back to 1912 when the Royal Commission decided to use the mean residence time of water in the rivers of England, 5 days, as a standard to measure the biochemical oxygen demand. Initially designed to protect the quality of river waters from extensive sewage discharge, the use of BOD5 has been quickly extended to waste water treatment plants (WWTPs) to monitor their efficiency on a daily basis. The measurement has been automatized but remains a tedious, time- and resource-consuming analysis. We have cross-validated a surrogate BOD5 method on two sites in France and in the USA with a total of 109 samples. This method uses a fluorescent redox indicator on a 96-well microplate to measure microbial catabolic activity for a large number of samples simultaneously. Three statistical tests were used to compare surrogate and reference methods and showed robust equivalence. PMID:24946712

  3. Cross-validating factors associated with discharges against medical advice.

    PubMed

    Dalrymple, A J; Fata, M

    1993-05-01

    Between six percent and 35% of psychiatric patients discharge themselves from hospital against medical advice (AMA). The discharges may prevent patients from deriving the full benefit of hospitalization and may result in rapid rehospitalization. We examined sociodemographic and clinical characteristics of 195 irregular discharges from a 237 bed psychiatric hospital over a five year period and found that AMA discharges increased over the study period to a peak of 25% in 1986. There was a strong negative correlation between AMA discharge rates and the willingness of physicians to commit patients involuntarily. Multiple discriminant analysis revealed a set of nine variables that accurately classified 78% of cases into regular or irregular discharge categories. Further analysis revealed that there are two distinct subgroups of patients who discharge themselves AMA: those who repeatedly left the hospital AMA in a regular "revolving back door" pattern and those who left AMA only once. The repeat group exceeded the one-time group in terms of prior admissions, appearances before review boards, and percentage of Natives. The repeat group also spent twice as long in hospital, and 27% were readmitted within one-week of the index AMA discharge. Less than three percent of the one-time AMA group was readmitted within a week. These results were cross-validated on a new sample of irregular discharges and matched controls. PMID:8518982

  4. The Importance of Evaluating Whether Results Will Generalize: Application of Cross-Validation in Discriminant Analysis.

    ERIC Educational Resources Information Center

    Loftin, Lynn B.

    Cross-validation, an economical method for assessing whether sample results will generalize, is discussed in this paper. Cross-validation is an invariance technique that uses two subsets of the data sample to derive discriminant function coefficients. The two sets of coefficients are then used with each data subset to derive discriminant function…

  5. Cost-Benefit Considerations in Choosing among Cross-Validation Methods.

    ERIC Educational Resources Information Center

    Murphy, Kevin R.

    1984-01-01

    Outlines costs and benefits associated with different cross-validation strategies; in particular the way in which the study design affects the cost and benefits of different types of cross-validation. Suggests that the choice between empirical estimation methods and formula estimates involves a trade-off between accuracy and simplicity. (JAC)

  6. Double Cross-Validation in Multiple Regression: A Method of Estimating the Stability of Results.

    ERIC Educational Resources Information Center

    Rowell, R. Kevin

    In multiple regression analysis, where resulting predictive equation effectiveness is subject to shrinkage, it is especially important to evaluate result replicability. Double cross-validation is an empirical method by which an estimate of invariance or stability can be obtained from research data. A procedure for double cross-validation is…

  7. Splenectomy Causes 10-Fold Increased Risk of Portal Venous System Thrombosis in Liver Cirrhosis Patients

    PubMed Central

    Qi, Xingshun; Han, Guohong; Ye, Chun; Zhang, Yongguo; Dai, Junna; Peng, Ying; Deng, Han; Li, Jing; Hou, Feifei; Ning, Zheng; Zhao, Jiancheng; Zhang, Xintong; Wang, Ran; Guo, Xiaozhong

    2016-01-01

    Background Portal venous system thrombosis (PVST) is a life-threatening complication of liver cirrhosis. We conducted a retrospective study to comprehensively analyze the prevalence and risk factors of PVST in liver cirrhosis. Material/Methods All cirrhotic patients without malignancy admitted between June 2012 and December 2013 were eligible if they underwent contrast-enhanced CT or MRI scans. Independent predictors of PVST in liver cirrhosis were calculated in multivariate analyses. Subgroup analyses were performed according to the severity of PVST (any PVST, main portal vein [MPV] thrombosis >50%, and clinically significant PVST) and splenectomy. Odds ratios (ORs) and 95% confidence intervals (CIs) were reported. Results Overall, 113 cirrhotic patients were enrolled. The prevalence of PVST was 16.8% (19/113). Splenectomy (any PVST: OR=11.494, 95%CI=2.152–61.395; MPV thrombosis >50%: OR=29.987, 95%CI=3.247–276.949; clinically significant PVST: OR=40.415, 95%CI=3.895–419.295) and higher hemoglobin (any PVST: OR=0.974, 95%CI=0.953–0.996; MPV thrombosis >50%: OR=0.936, 95%CI=0.895–0.980; clinically significant PVST: OR=0.935, 95%CI=0.891–0.982) were the independent predictors of PVST. The prevalence of PVST was 13.3% (14/105) after excluding splenectomy. Higher hemoglobin was the only independent predictor of MPV thrombosis >50% (OR=0.952, 95%CI=0.909–0.997). No independent predictors of any PVST or clinically significant PVST were identified in multivariate analyses. Additionally, PVST patients who underwent splenectomy had a significantly higher proportion of clinically significant PVST but lower MELD score than those who did not undergo splenectomy. In all analyses, the in-hospital mortality was not significantly different between cirrhotic patient with and without PVST. Conclusions Splenectomy may increase by at least 10-fold the risk of PVST in liver cirrhosis independent of severity of liver dysfunction. PMID:27432511

  8. A Test and Cross-Validation of the Revised Two-Factor Study Process Questionnaire Factor Structure among Western University Students

    ERIC Educational Resources Information Center

    Immekus, Jason C.; Imbrie, P. K.

    2010-01-01

    The Revised Two-Factor Study Process Questionnaire (R-SPQ-2F) is a measure of university students' approach to learning. Original evaluation of the scale's psychometric properties was based on a sample of Hong Kong university students' scores. The purpose of this study was to test and cross-validate the R-SPQ-2F factor structure, based on separate…

  9. The Performance of Cross-Validation Indices Used to Select among Competing Covariance Structure Models under Multivariate Nonnormality Conditions

    ERIC Educational Resources Information Center

    Whittaker, Tiffany A.; Stapleton, Laura M.

    2006-01-01

    Cudeck and Browne (1983) proposed using cross-validation as a model selection technique in structural equation modeling. The purpose of this study is to examine the performance of eight cross-validation indices under conditions not yet examined in the relevant literature, such as nonnormality and cross-validation design. The performance of each…

  10. Biased binomial assessment of cross-validated estimation of classification accuracies illustrated in diagnosis predictions

    PubMed Central

    Noirhomme, Quentin; Lesenfants, Damien; Gomez, Francisco; Soddu, Andrea; Schrouff, Jessica; Garraux, Gaëtan; Luxen, André; Phillips, Christophe; Laureys, Steven

    2014-01-01

    Multivariate classification is used in neuroimaging studies to infer brain activation or in medical applications to infer diagnosis. Their results are often assessed through either a binomial or a permutation test. Here, we simulated classification results of generated random data to assess the influence of the cross-validation scheme on the significance of results. Distributions built from classification of random data with cross-validation did not follow the binomial distribution. The binomial test is therefore not adapted. On the contrary, the permutation test was unaffected by the cross-validation scheme. The influence of the cross-validation was further illustrated on real-data from a brain–computer interface experiment in patients with disorders of consciousness and from an fMRI study on patients with Parkinson disease. Three out of 16 patients with disorders of consciousness had significant accuracy on binomial testing, but only one showed significant accuracy using permutation testing. In the fMRI experiment, the mental imagery of gait could discriminate significantly between idiopathic Parkinson's disease patients and healthy subjects according to the permutation test but not according to the binomial test. Hence, binomial testing could lead to biased estimation of significance and false positive or negative results. In our view, permutation testing is thus recommended for clinical application of classification with cross-validation. PMID:24936420

  11. Biased binomial assessment of cross-validated estimation of classification accuracies illustrated in diagnosis predictions.

    PubMed

    Noirhomme, Quentin; Lesenfants, Damien; Gomez, Francisco; Soddu, Andrea; Schrouff, Jessica; Garraux, Gaëtan; Luxen, André; Phillips, Christophe; Laureys, Steven

    2014-01-01

    Multivariate classification is used in neuroimaging studies to infer brain activation or in medical applications to infer diagnosis. Their results are often assessed through either a binomial or a permutation test. Here, we simulated classification results of generated random data to assess the influence of the cross-validation scheme on the significance of results. Distributions built from classification of random data with cross-validation did not follow the binomial distribution. The binomial test is therefore not adapted. On the contrary, the permutation test was unaffected by the cross-validation scheme. The influence of the cross-validation was further illustrated on real-data from a brain-computer interface experiment in patients with disorders of consciousness and from an fMRI study on patients with Parkinson disease. Three out of 16 patients with disorders of consciousness had significant accuracy on binomial testing, but only one showed significant accuracy using permutation testing. In the fMRI experiment, the mental imagery of gait could discriminate significantly between idiopathic Parkinson's disease patients and healthy subjects according to the permutation test but not according to the binomial test. Hence, binomial testing could lead to biased estimation of significance and false positive or negative results. In our view, permutation testing is thus recommended for clinical application of classification with cross-validation. PMID:24936420

  12. Cross-Validation and Extension of the MMPI-A IMM Scale.

    ERIC Educational Resources Information Center

    Zinn, Sandra; McCumber, Stacey; Dahlstrom, W. Grant

    1999-01-01

    Cross-validated the IMM scale of the Minnesota Multiphasic Personality Inventory-Adolescents (MMPI-A), a measure of ego level, with 151 college students. Means and standard deviations were obtained on IMM scale from the MMPI-A and another MMPI version for males and females. (SLD)

  13. Cross-Validation of the Quick Word Test as an Estimator of Adult Mental Ability

    ERIC Educational Resources Information Center

    Grotelueschen, Arden; McQuarrie, Duncan

    1970-01-01

    This report provides additional evidence that the Quick Word Test (Level 2, Form AM) is valid for estimating adult mental ability as defined by the Wechsler Adult Intelligence Scale. The validation sample is also described to facilitate use of the conversion table developed in the cross-validation analysis. (Author/LY)

  14. Cross-Validation of the Risk Matrix 2000 Sexual and Violent Scales

    ERIC Educational Resources Information Center

    Craig, Leam A.; Beech, Anthony; Browne, Kevin D.

    2006-01-01

    The predictive accuracy of the newly developed actuarial risk measures Risk Matrix 2000 Sexual/Violence (RMS, RMV) were cross validated and compared with two risk assessment measures (SVR-20 and Static-99) in a sample of sexual (n = 85) and nonsex violent (n = 46) offenders. The sexual offense reconviction rate for the sex offender group was 18%…

  15. Reliable Digit Span: A Systematic Review and Cross-Validation Study

    ERIC Educational Resources Information Center

    Schroeder, Ryan W.; Twumasi-Ankrah, Philip; Baade, Lyle E.; Marshall, Paul S.

    2012-01-01

    Reliable Digit Span (RDS) is a heavily researched symptom validity test with a recent literature review yielding more than 20 studies ranging in dates from 1994 to 2011. Unfortunately, limitations within some of the research minimize clinical generalizability. This systematic review and cross-validation study was conducted to address these…

  16. Cross Validation and Discriminative Analysis Techniques in a College Student Attrition Application.

    ERIC Educational Resources Information Center

    Smith, Alan D.

    1982-01-01

    Used a current attrition study to show the usefulness of discriminative analysis and a cross validation technique applied to student nonpersister questionnaire respondents and nonrespondents. Results of the techniques allowed delineation of several areas of sample under-representation and established the instability of the regression weights…

  17. Validity Evidence in Scale Development: The Application of Cross Validation and Classification-Sequencing Validation

    ERIC Educational Resources Information Center

    Acar, Tu¨lin

    2014-01-01

    In literature, it has been observed that many enhanced criteria are limited by factor analysis techniques. Besides examinations of statistical structure and/or psychological structure, such validity studies as cross validation and classification-sequencing studies should be performed frequently. The purpose of this study is to examine cross…

  18. Exact Analysis of Squared Cross-Validity Coefficient in Predictive Regression Models

    ERIC Educational Resources Information Center

    Shieh, Gwowen

    2009-01-01

    In regression analysis, the notion of population validity is of theoretical interest for describing the usefulness of the underlying regression model, whereas the presumably more important concept of population cross-validity represents the predictive effectiveness for the regression equation in future research. It appears that the inference…

  19. Cross-validation and calibration of Jackson-Pollock equations with DXA: the TIGER study

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Jackson-Pollock (J&P) body composition equations were developed primarily from data on white men and women using hydrostatically determined body density (BD) as the criterion measure. This study cross-validated the J&P equations with ethnically diverse subjects and percent fat (%fat) determined ...

  20. Cross-Validation of FITNESSGRAM® Health-Related Fitness Standards in Hungarian Youth

    ERIC Educational Resources Information Center

    Laurson, Kelly R.; Saint-Maurice, Pedro F.; Karsai, István; Csányi, Tamás

    2015-01-01

    Purpose: The purpose of this study was to cross-validate FITNESSGRAM® aerobic and body composition standards in a representative sample of Hungarian youth. Method: A nationally representative sample (N = 405) of Hungarian adolescents from the Hungarian National Youth Fitness Study (ages 12-18.9 years) participated in an aerobic capacity assessment…

  1. Apparent behaviour of charged and neutral materials with ellipsoidal fibre distributions and cross-validation of finite element implementations.

    PubMed

    Nagel, Thomas; Kelly, Daniel J

    2012-05-01

    Continuous fibre distribution models can be applied to a variety of biological tissues with both charged and neutral extracellular matrices. In particular, ellipsoidal models have been used to describe the complex material behaviour of tissues such as articular cartilage and their engineered tissue equivalents. The choice of material parameters is more difficult than in classical anisotropic models and the impact that changes to these parameters can have on the predictions of such models are poorly understood. The objective of this study is to demonstrate the apparent behaviour of this class of materials over a range of material parameters. We further introduce a scaling approach to overcome certain counter-intuitive aspects related to the choice of anisotropy parameters and outline the integration method used in our implementations. User material codes for the commercial FE software packages Abaqus and MSC Marc are provided for use by other investigators. Cross-validation of our code against similar implementations in FEBio is also presented. PMID:22498290

  2. Methodology Review: Estimation of Population Validity and Cross-Validity, and the Use of Equal Weights in Prediction.

    ERIC Educational Resources Information Center

    Raju, Nambury S.; Bilgic, Reyhan; Edwards, Jack E.; Fleer, Paul F.

    1997-01-01

    This review finds that formula-based procedures can be used in place of empirical validation for estimating population validity or in place of empirical cross-validation for estimating population cross-validity. Discusses conditions under which the equal weights procedure is a viable alternative. (SLD)

  3. Cross-Validation of easyCBM Reading Cut Scores in Oregon: 2009-2010. Technical Report #1108

    ERIC Educational Resources Information Center

    Park, Bitnara Jasmine; Irvin, P. Shawn; Anderson, Daniel; Alonzo, Julie; Tindal, Gerald

    2011-01-01

    This technical report presents results from a cross-validation study designed to identify optimal cut scores when using easyCBM[R] reading tests in Oregon. The cross-validation study analyzes data from the 2009-2010 academic year for easyCBM[R] reading measures. A sample of approximately 2,000 students per grade, randomly split into two groups of…

  4. A cross-validation scheme for machine learning algorithms in shotgun proteomics

    PubMed Central

    2012-01-01

    Peptides are routinely identified from mass spectrometry-based proteomics experiments by matching observed spectra to peptides derived from protein databases. The error rates of these identifications can be estimated by target-decoy analysis, which involves matching spectra to shuffled or reversed peptides. Besides estimating error rates, decoy searches can be used by semi-supervised machine learning algorithms to increase the number of confidently identified peptides. As for all machine learning algorithms, however, the results must be validated to avoid issues such as overfitting or biased learning, which would produce unreliable peptide identifications. Here, we discuss how the target-decoy method is employed in machine learning for shotgun proteomics, focusing on how the results can be validated by cross-validation, a frequently used validation scheme in machine learning. We also use simulated data to demonstrate the proposed cross-validation scheme's ability to detect overfitting. PMID:23176259

  5. Cross-validation of interferometric synthetic aperture microscopy and optical coherence tomography.

    PubMed

    Ralston, Tyler S; Adie, Steven G; Marks, Daniel L; Boppart, Stephen A; Carney, P Scott

    2010-05-15

    Computationally reconstructed interferometric synthetic aperture microscopy is coregistered with optical coherence tomography (OCT) focal plane data to provide quantitative cross validation with OCT. This is accomplished through a qualitative comparison of images and a quantitative analysis of the width of the point-spread function in simulation and experiment. The width of the ISAM point-spread function is seen to be independent of depth, in contrast to OCT. PMID:20479849

  6. A universal approximate cross-validation criterion for regular risk functions.

    PubMed

    Commenges, Daniel; Proust-Lima, Cécile; Samieri, Cécilia; Liquet, Benoit

    2015-05-01

    Selection of estimators is an essential task in modeling. A general framework is that the estimators of a distribution are obtained by minimizing a function (the estimating function) and assessed using another function (the assessment function). A classical case is that both functions estimate an information risk (specifically cross-entropy); this corresponds to using maximum likelihood estimators and assessing them by Akaike information criterion (AIC). In more general cases, the assessment risk can be estimated by leave-one-out cross-validation. Since leave-one-out cross-validation is computationally very demanding, we propose in this paper a universal approximate cross-validation criterion under regularity conditions (UACVR). This criterion can be adapted to different types of estimators, including penalized likelihood and maximum a posteriori estimators, and also to different assessment risk functions, including information risk functions and continuous rank probability score (CRPS). UACVR reduces to Takeuchi information criterion (TIC) when cross-entropy is the risk for both estimation and assessment. We provide the asymptotic distributions of UACVR and of a difference of UACVR values for two estimators. We validate UACVR using simulations and provide an illustration on real data both in the psychometric context where estimators of the distributions of ordered categorical data derived from threshold models and models based on continuous approximations are compared. PMID:25849800

  7. Novel method for quantifying radiation-induced single-strand-break yields in plasmid DNA highlights 10-fold discrepancy.

    PubMed

    Balagurumoorthy, Pichumani; Adelstein, S James; Kassis, Amin I

    2011-10-15

    The widely used agarose gel electrophoresis method for assessing radiation-induced single-strand-break (SSB) yield in plasmid DNA involves measurement of the fraction of relaxed-circular (C) form that migrates independently from the intact supercoiled (SC) form. We rationalized that this method may underestimate the SSB yield since the position of the relaxed-circular form is not altered when the number of SSB per DNA molecule is >1. To overcome this limitation, we have developed a novel method that directly probes and quantifies SSBs. Supercoiled (3)H-pUC19 plasmid samples were irradiated with γ-rays, alkali-denatured, dephosphorylated, and kinated with γ-[(32)P]ATP, and the DNA-incorporated (32)P activities were used to quantify the SSB yields per DNA molecule, employing a standard curve generated using DNA molecules containing a known number of SSBs. The same irradiated samples were analyzed by agarose gel and SSB yields were determined by conventional methods. Comparison of the data demonstrated that the mean SSB yield per plasmid DNA molecule of [21.2±0.59]×10(-2)Gy(-1) as measured by direct probing is ~10-fold higher than that obtained from conventional gel-based methods. These findings imply that the SSB yields inferred from agarose gels need reevaluation, especially when they were utilized in the determination of radiation risk. PMID:21741945

  8. Variational cross-validation of slow dynamical modes in molecular kinetics

    PubMed Central

    Pande, Vijay S.

    2015-01-01

    Markov state models are a widely used method for approximating the eigenspectrum of the molecular dynamics propagator, yielding insight into the long-timescale statistical kinetics and slow dynamical modes of biomolecular systems. However, the lack of a unified theoretical framework for choosing between alternative models has hampered progress, especially for non-experts applying these methods to novel biological systems. Here, we consider cross-validation with a new objective function for estimators of these slow dynamical modes, a generalized matrix Rayleigh quotient (GMRQ), which measures the ability of a rank-m projection operator to capture the slow subspace of the system. It is shown that a variational theorem bounds the GMRQ from above by the sum of the first m eigenvalues of the system’s propagator, but that this bound can be violated when the requisite matrix elements are estimated subject to statistical uncertainty. This overfitting can be detected and avoided through cross-validation. These result make it possible to construct Markov state models for protein dynamics in a way that appropriately captures the tradeoff between systematic and statistical errors. PMID:25833563

  9. Applicability of Monte Carlo cross validation technique for model development and validation using generalised least squares regression

    NASA Astrophysics Data System (ADS)

    Haddad, Khaled; Rahman, Ataur; A Zaman, Mohammad; Shrestha, Surendra

    2013-03-01

    SummaryIn regional hydrologic regression analysis, model selection and validation are regarded as important steps. Here, the model selection is usually based on some measurements of goodness-of-fit between the model prediction and observed data. In Regional Flood Frequency Analysis (RFFA), leave-one-out (LOO) validation or a fixed percentage leave out validation (e.g., 10%) is commonly adopted to assess the predictive ability of regression-based prediction equations. This paper develops a Monte Carlo Cross Validation (MCCV) technique (which has widely been adopted in Chemometrics and Econometrics) in RFFA using Generalised Least Squares Regression (GLSR) and compares it with the most commonly adopted LOO validation approach. The study uses simulated and regional flood data from the state of New South Wales in Australia. It is found that when developing hydrologic regression models, application of the MCCV is likely to result in a more parsimonious model than the LOO. It has also been found that the MCCV can provide a more realistic estimate of a model's predictive ability when compared with the LOO.

  10. Simulating California reservoir operation using the classification and regression-tree algorithm combined with a shuffled cross-validation scheme

    NASA Astrophysics Data System (ADS)

    Yang, Tiantian; Gao, Xiaogang; Sorooshian, Soroosh; Li, Xin

    2016-03-01

    The controlled outflows from a reservoir or dam are highly dependent on the decisions made by the reservoir operators, instead of a natural hydrological process. Difference exists between the natural upstream inflows to reservoirs and the controlled outflows from reservoirs that supply the downstream users. With the decision maker's awareness of changing climate, reservoir management requires adaptable means to incorporate more information into decision making, such as water delivery requirement, environmental constraints, dry/wet conditions, etc. In this paper, a robust reservoir outflow simulation model is presented, which incorporates one of the well-developed data-mining models (Classification and Regression Tree) to predict the complicated human-controlled reservoir outflows and extract the reservoir operation patterns. A shuffled cross-validation approach is further implemented to improve CART's predictive performance. An application study of nine major reservoirs in California is carried out. Results produced by the enhanced CART, original CART, and random forest are compared with observation. The statistical measurements show that the enhanced CART and random forest overperform the CART control run in general, and the enhanced CART algorithm gives a better predictive performance over random forest in simulating the peak flows. The results also show that the proposed model is able to consistently and reasonably predict the expert release decisions. Experiments indicate that the release operation in the Oroville Lake is significantly dominated by SWP allocation amount and reservoirs with low elevation are more sensitive to inflow amount than others.

  11. A cross-validation of two differing measures of hypnotic depth.

    PubMed

    Pekala, Ronald J; Maurer, Ronald L

    2013-01-01

    Several sets of regression analyses were completed, attempting to predict 2 measures of hypnotic depth: the self-reported hypnotic depth score and hypnoidal state score from variables of the Phenomenology of Consciousness Inventory: Hypnotic Assessment Procedure (PCI-HAP). When attempting to predict self-reported hypnotic depth, an R of .78 with Study 1 participants shrank to an r of .72 with Study 2 participants, suggesting mild shrinkage for this more attributional measure of hypnotic depth. Attempting to predict hypnoidal state (an estimate of trance) using the same procedure, yielded an R of .56, that upon cross-validation shrank to an r of .48. These and other results suggest that, although there is some variance in common, the self-reported hypnotic depth score appears to be tapping a different construct from the hypnoidal state score. PMID:23153387

  12. Statistical analysis of GeneMark performance by cross-validation.

    PubMed

    Kleffe, J; Hermann, K; Borodovsky, M

    1996-03-01

    We have explored the performance of the GeneMark gene identification method using cross-validation over learning samples of E. coli DNA sequences. The computations gave more accurate estimations of the error rates in comparison with previous results when a sample of non-coding regions was derived from GenBank sequences with many true coding regions unannotated. The error rate components have been classified and delineated. It was shown that the method performs differently on class I, II and III genes. The most frequent errors come from misinterpreting the coding potential of the complementary sequence in the same frame. The effects of stop-codons present in alternative frames were also studied to understand better the main factors contributing to GeneMark performance. PMID:16749185

  13. Error criteria for cross validation in the context of chaotic time series prediction

    NASA Astrophysics Data System (ADS)

    Lim, Teck Por; Puthusserypady, Sadasivan

    2006-03-01

    The prediction of a chaotic time series over a long horizon is commonly done by iterating one-step-ahead prediction. Prediction can be implemented using machine learning methods, such as radial basis function networks. Typically, cross validation is used to select prediction models based on mean squared error. The bias-variance dilemma dictates that there is an inevitable tradeoff between bias and variance. However, invariants of chaotic systems are unchanged by linear transformations; thus, the bias component may be irrelevant to model selection in the context of chaotic time series prediction. Hence, the use of error variance for model selection, instead of mean squared error, is examined. Clipping is introduced, as a simple way to stabilize iterated predictions. It is shown that using the error variance for model selection, in combination with clipping, may result in better models.

  14. Multisample cross-validation of a model of childhood posttraumatic stress disorder symptomatology.

    PubMed

    Anthony, Jason L; Lonigan, Christopher J; Vernberg, Eric M; Greca, Annette M La; Silverman, Wendy K; Prinstein, Mitchell J

    2005-12-01

    This study is the latest advancement of our research aimed at best characterizing children's posttraumatic stress reactions. In a previous study, we compared existing nosologic and empirical models of PTSD dimensionality and determined the superior model was a hierarchical one with three symptom clusters (Intrusion/Active Avoidance, Numbing/Passive Avoidance, and Arousal; Anthony, Lonigan, & Hecht, 1999). In this study, we cross-validate this model in two populations. Participants were 396 fifth graders who were exposed to either Hurricane Andrew or Hurricane Hugo. Multisample confirmatory factor analysis demonstrated the model's factorial invariance across populations who experienced traumatic events that differed in severity. These results show the model's robustness to characterize children's posttraumatic stress reactions. Implications for diagnosis, classification criteria, and an empirically supported theory of PTSD are discussed. PMID:16382435

  15. Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement.

    PubMed

    Nguyen, N; Milanfar, P; Golub, G

    2001-01-01

    In many image restoration/resolution enhancement applications, the blurring process, i.e., point spread function (PSF) of the imaging system, is not known or is known only to within a set of parameters. We estimate these PSF parameters for this ill-posed class of inverse problem from raw data, along with the regularization parameters required to stabilize the solution, using the generalized cross-validation method (GCV). We propose efficient approximation techniques based on the Lanczos algorithm and Gauss quadrature theory, reducing the computational complexity of the GCV. Data-driven PSF and regularization parameter estimation experiments with synthetic and real image sequences are presented to demonstrate the effectiveness and robustness of our method. PMID:18255545

  16. Testing alternative ground water models using cross-validation and other methods

    USGS Publications Warehouse

    Foglia, L.; Mehl, S.W.; Hill, M.C.; Perona, P.; Burlando, P.

    2007-01-01

    Many methods can be used to test alternative ground water models. Of concern in this work are methods able to (1) rank alternative models (also called model discrimination) and (2) identify observations important to parameter estimates and predictions (equivalent to the purpose served by some types of sensitivity analysis). Some of the measures investigated are computationally efficient; others are computationally demanding. The latter are generally needed to account for model nonlinearity. The efficient model discrimination methods investigated include the information criteria: the corrected Akaike information criterion, Bayesian information criterion, and generalized cross-validation. The efficient sensitivity analysis measures used are dimensionless scaled sensitivity (DSS), composite scaled sensitivity, and parameter correlation coefficient (PCC); the other statistics are DFBETAS, Cook's D, and observation-prediction statistic. Acronyms are explained in the introduction. Cross-validation (CV) is a computationally intensive nonlinear method that is used for both model discrimination and sensitivity analysis. The methods are tested using up to five alternative parsimoniously constructed models of the ground water system of the Maggia Valley in southern Switzerland. The alternative models differ in their representation of hydraulic conductivity. A new method for graphically representing CV and sensitivity analysis results for complex models is presented and used to evaluate the utility of the efficient statistics. The results indicate that for model selection, the information criteria produce similar results at much smaller computational cost than CV. For identifying important observations, the only obviously inferior linear measure is DSS; the poor performance was expected because DSS does not include the effects of parameter correlation and PCC reveals large parameter correlations. ?? 2007 National Ground Water Association.

  17. Evaluating Processes, Parameters and Observations Using Cross Validation and Computationally Frugal Sensitivity Analysis Methods

    NASA Astrophysics Data System (ADS)

    Foglia, L.; Mehl, S.; Hill, M. C.

    2013-12-01

    Sensitivity analysis methods are used to identify measurements most likely to provide important information for model development and predictions and therefore identify critical processes. Methods range from computationally demanding Monte Carlo and cross-validation methods, to very computationally efficient linear methods. The methods are able to account for interrelations between parameters, but some argue that because linear methods neglect the effects of model nonlinearity, they are not worth considering when examining complex, nonlinear models of environmental systems. However, when faced with computationally demanding models needed to simulate, for example, climate change, the chance of obtaining fundamental insights (such as important and relationships between predictions and parameters) with few model runs is tempting. In the first part of this work, comparisons of local sensitivity analysis and cross-validation are conducted using a nonlinear groundwater model of the Maggia Valley, Southern Switzerland; sensitivity analysis are then applied to an integrated hydrological model of the same system where the impact of more processes and of using different sets of observations on the model results are considered; applicability to models of a variety of situations (climate, water quality, water management) is inferred. Results show that the frugal linear methods produced about 70% of the insight from about 2% of the model runs required by the computationally demanding methods. Regarding important observations, linear methods were not always able to distinguish between moderately and unimportant observations. However, they consistently identified the most important observations which are critical to characterize relationships between parameters and to assess the worth of potential new data collection efforts. Importance both to estimate parameters and predictions of interest was readily identified. The results suggest that it can be advantageous to consider local

  18. Credible Intervals for Precision and Recall Based on a K-Fold Cross-Validated Beta Distribution.

    PubMed

    Wang, Yu; Li, Jihong

    2016-08-01

    In typical machine learning applications such as information retrieval, precision and recall are two commonly used measures for assessing an algorithm's performance. Symmetrical confidence intervals based on K-fold cross-validated t distributions are widely used for the inference of precision and recall measures. As we confirmed through simulated experiments, however, these confidence intervals often exhibit lower degrees of confidence, which may easily lead to liberal inference results. Thus, it is crucial to construct faithful confidence (credible) intervals for precision and recall with a high degree of confidence and a short interval length. In this study, we propose two posterior credible intervals for precision and recall based on K-fold cross-validated beta distributions. The first credible interval for precision (or recall) is constructed based on the beta posterior distribution inferred by all K data sets corresponding to K confusion matrices from a K-fold cross-validation. Second, considering that each data set corresponding to a confusion matrix from a K-fold cross-validation can be used to infer a beta posterior distribution of precision (or recall), the second proposed credible interval for precision (or recall) is constructed based on the average of K beta posterior distributions. Experimental results on simulated and real data sets demonstrate that the first credible interval proposed in this study almost always resulted in degrees of confidence greater than 95%. With an acceptable degree of confidence, both of our two proposed credible intervals have shorter interval lengths than those based on a corrected K-fold cross-validated t distribution. Meanwhile, the average ranks of these two credible intervals are superior to that of the confidence interval based on a K-fold cross-validated t distribution for the degree of confidence and are superior to that of the confidence interval based on a corrected K-fold cross-validated t distribution for the

  19. Inversion of velocity map ion images using iterative regularization and cross validation

    NASA Astrophysics Data System (ADS)

    Renth, F.; Riedel, J.; Temps, F.

    2006-03-01

    Two methods for improved inversion of velocity map images are presented. Both schemes use two-dimensional basis functions to perform the iteratively regularized inversion of the imaging equation in matrix form. The quality of the reconstructions is improved by taking into account the constraints that are derived from prior knowledge about the experimental data, such as non-negativity and noise statistics, using (i) the projected Landweber [Am. J. Math. 73, 615 (1951)] and (ii) the Richardson-Lucy [J. Opt. Soc. Am. 62, 55 (1972); Astron. J. 79, 745 (1974)] algorithms. It is shown that the optimum iteration count, which plays the role of a regularization parameter, can be determined by partitioning the image into quarters or halves and a subsequent cross validation of the inversion results. The methods are tested with various synthetic velocity map images and with velocity map images of the H-atom fragments produced in the photodissociation of HBr at λ =243.1nm using a (2+1) resonantly enhanced multiphoton ionization (REMPI) detection scheme. The versatility of the method, which is only determined by the choice of basis functions, is exploited to take into account the photoelectron recoil that leads to a splitting and broadening of the velocity distribution in the two product channels, and to successfully reconstruct the deconvolved velocity distribution. The methods can also be applied to the cases where higher order terms in the Legendre expansion of the angular distribution are present.

  20. Some psychometric properties of the Chinese version of the Modified Dental Anxiety Scale with cross validation

    PubMed Central

    Yuan, Siyang; Freeman, Ruth; Lahti, Satu; Lloyd-Williams, Ffion; Humphris, Gerry

    2008-01-01

    Objective To assess the factorial structure and construct validity for the Chinese version of the Modified Dental Anxiety Scale (MDAS). Materials and methods A cross-sectional survey was conducted in March 2006 from adults in the Beijing area. The questionnaire consisted of sections to assess for participants' demographic profile and dental attendance patterns, the Chinese MDAS and the anxiety items from the Hospital Anxiety and Depression Scale (HADS). The analysis was conducted in two stages using confirmatory factor analysis and structural equation modelling. Cross validation was tested with a North West of England comparison sample. Results 783 questionnaires were successfully completed from Beijing, 468 from England. The Chinese MDAS consisted of two factors: anticipatory dental anxiety (ADA) and treatment dental anxiety (TDA). Internal consistency coefficients (tau non-equivalent) were 0.74 and 0.86 respectively. Measurement properties were virtually identical for male and female respondents. Relationships of the Chinese MDAS with gender, age and dental attendance supported predictions. Significant structural parameters between the two sub-scales (negative affectivity and autonomic anxiety) of the HADS anxiety items and the two newly identified factors of the MDAS were confirmed and duplicated in the comparison sample. Conclusion The Chinese version of the MDAS has good psychometric properties and has the ability to assess, briefly, overall dental anxiety and two correlated but distinct aspects. PMID:18364045

  1. Approximate l-fold cross-validation with Least Squares SVM and Kernel Ridge Regression

    SciTech Connect

    Edwards, Richard E; Zhang, Hao; Parker, Lynne Edwards; New, Joshua Ryan

    2013-01-01

    Kernel methods have difficulties scaling to large modern data sets. The scalability issues are based on computational and memory requirements for working with a large matrix. These requirements have been addressed over the years by using low-rank kernel approximations or by improving the solvers scalability. However, Least Squares Support VectorMachines (LS-SVM), a popular SVM variant, and Kernel Ridge Regression still have several scalability issues. In particular, the O(n^3) computational complexity for solving a single model, and the overall computational complexity associated with tuning hyperparameters are still major problems. We address these problems by introducing an O(n log n) approximate l-fold cross-validation method that uses a multi-level circulant matrix to approximate the kernel. In addition, we prove our algorithm s computational complexity and present empirical runtimes on data sets with approximately 1 million data points. We also validate our approximate method s effectiveness at selecting hyperparameters on real world and standard benchmark data sets. Lastly, we provide experimental results on using a multi-level circulant kernel approximation to solve LS-SVM problems with hyperparameters selected using our method.

  2. How Nonrecidivism Affects Predictive Accuracy: Evidence from a Cross-Validation of the Ontario Domestic Assault Risk Assessment (ODARA)

    ERIC Educational Resources Information Center

    Hilton, N. Zoe; Harris, Grant T.

    2009-01-01

    Prediction effect sizes such as ROC area are important for demonstrating a risk assessment's generalizability and utility. How a study defines recidivism might affect predictive accuracy. Nonrecidivism is problematic when predicting specialized violence (e.g., domestic violence). The present study cross-validates the ability of the Ontario…

  3. A Cross-Validation of easyCBM[R] Mathematics Cut Scores in Oregon: 2009-2010. Technical Report #1104

    ERIC Educational Resources Information Center

    Anderson, Daniel; Alonzo, Julie; Tindal, Gerald

    2011-01-01

    In this technical report, we document the results of a cross-validation study designed to identify optimal cut-scores for the use of the easyCBM[R] mathematics test in Oregon. A large sample, randomly split into two groups of roughly equal size, was used for this study. Students' performance classification on the Oregon state test was used as the…

  4. Cross-Validating Measures of Technology Integration: A First Step toward Examining Potential Relationships between Technology Integration and Student Achievement

    ERIC Educational Resources Information Center

    Hancock, Robert; Knezek, Gerald; Christensen, Rhonda

    2007-01-01

    The use of proper measurements of diffusion of information technology as an innovation are essential to determining if progress is being made in state, regional, and national level programs. This project provides a national level cross validation study of several instruments commonly used to assess the effectiveness of technology integration in…

  5. A Cross-Validation of Paulson's Discriminant Function-Derived Scales for Identifying "At Risk" Child-Abusive Parents.

    ERIC Educational Resources Information Center

    Beal, Don; And Others

    1984-01-01

    When the six scales were cross-validated on an independent sample from the population of child-abusing parents, significant shrinkage in the accuracy of prediction was found. The use of the special subscales for identifying "at risk" parents in prenatal clinics, pediatric clinics, and mental health centers as originally suggested by Paulson and…

  6. Estimating the Coefficient of Cross-validity in Multiple Regression: A Comparison of Analytical and Empirical Methods.

    ERIC Educational Resources Information Center

    Kromrey, Jeffrey D.; Hines, Constance V.

    1996-01-01

    The accuracy of three analytical formulas for shrinkage estimation and four empirical techniques were investigated in a Monte Carlo study of the coefficient of cross-validity in multiple regression. Substantial statistical bias was evident for all techniques except the formula of M. W. Brown (1975) and multicross-validation. (SLD)

  7. Population Validity and Cross-Validity: Applications of Distribution Theory for Testing Hypotheses, Setting Confidence Intervals, and Determining Sample Size

    ERIC Educational Resources Information Center

    Algina, James; Keselman, H. J.

    2008-01-01

    Applications of distribution theory for the squared multiple correlation coefficient and the squared cross-validation coefficient are reviewed, and computer programs for these applications are made available. The applications include confidence intervals, hypothesis testing, and sample size selection. (Contains 2 tables.)

  8. Electrochemical Performance and Stability of the Cathode for Solid Oxide Fuel Cells. I. Cross Validation of Polarization Measurements by Impedance Spectroscopy and Current-Potential Sweep

    SciTech Connect

    Zhou, Xiao Dong; Pederson, Larry R.; Templeton, Jared W.; Stevenson, Jeffry W.

    2009-12-09

    The aim of this paper is to address three issues in solid oxide fuel cells: (1) cross-validation of the polarization of a single cell measured using both dc and ac approaches, (2) the precise determination of the total areal specific resistance (ASR), and (3) understanding cathode polarization with LSCF cathodes. The ASR of a solid oxide fuel cell is a dynamic property, meaning that it changes with current density. The ASR measured using ac impedance spectroscopy (low frequency interception with real Z´ axis of ac impedance spectrum) matches with that measured from a dc IV sweep (the tangent of dc i-V curve). Due to the dynamic nature of ASR, we found that an ac impedance spectrum measured under open circuit voltage or on a half cell may not represent cathode performance under real operating conditions, particularly at high current density. In this work, the electrode polarization was governed by the cathode activation polarization; the anode contribution was negligible.

  9. The brief cognitive assessment tool (BCAT): cross-validation in a community dwelling older adult sample.

    PubMed

    MacDougall, Elizabeth E; Mansbach, William E; Clark, Kristen; Mace, Ryan A

    2014-08-13

    ABSTRACT Background: Cognitive impairment is underrecognized and misdiagnosed among community-dwelling older adults. At present, there is no consensus about which cognitive screening tool represents the "gold standard." However, one tool that shows promise is the Brief Cognitive Assessment Tool (BCAT), which was originally validated in an assisted living sample and contains a multi-level memory component (e.g. word lists and story recall items) and complex executive functions features (e.g. judgment, set-shifting, and problem-solving). Methods: The present study cross-validated the BCAT in a sample of 75 community-dwelling older adults. Participants completed a short battery of several individually administered cognitive tests, including the BCAT and the Montreal Cognitive Assessment (MoCA). Using a very conservative MoCA cut score of <26, the base rate of cognitive impairment in this sample was 35%. Results: Adequate internal consistency and strong evidence of construct validity were found. A receiver operating characteristic (ROC) curve was calculated from sensitivity and 1-specificity values for the classification of cognitively impaired versus cognitively unimpaired. The area under the ROC curve (AUC) for the BCAT was .90, p < 0.001, 95% CI [0.83, 0.97]. A BCAT cut-score of 45 (scores below 45 suggesting cognitive impairment) resulted in the best balance between sensitivity (0.81) and specificity (0.80). Conclusions: A BCAT cut-score can be used for identifying persons to be referred to appropriate healthcare professionals for more comprehensive cognitive assessment. In addition, guidelines are provided for clinicians to interpret separate BCAT memory and executive dysfunction component scores. PMID:25115580

  10. Cross-validation of a composite pain scale for preschool children within 24 hours of surgery.

    PubMed

    Suraseranivongse, S; Santawat, U; Kraiprasit, K; Petcharatana, S; Prakkamodom, S; Muntraporn, N

    2001-09-01

    This study was designed to cross-validate a composite measure of the pain scales CHEOPS (Children's Hospital of Eastern Ontario Pain Scale), OPS (Objective Pain Scale, simplified for parent use by replacing blood pressure measurement with observation of body language or posture), TPPPS (Toddler Preschool Postoperative Pain Scale) and FLACC (Face, Legs, Activity, Cry, Consolability) in 167 Thai children aged 1-5.5 yr. The pain scales were translated and tested for content, construct and concurrent validity, including inter-rater and intra-rater reliabilities. Discriminative validity in immediate and persistent pain for the age groups < or =3 and >3 yr were also studied. The children's behaviour was videotaped before and after surgery, before analgesia had been given in the post-anaesthesia care unit (PACU), and on the ward. Four observers then rated pain behaviour from rearranged videotapes. The decision to treat pain was based on routine practice and was made by a researcher unaware of the rating procedure. All tools had acceptable content validity and excellent inter-rater and intra-rater reliabilities (intraclass correlation >0.9 and >0.8 respectively). Construct validity was determined by the ability to differentiate the group with no pain before surgery and a high pain level after surgery, before analgesia (P<0.001). The positive correlations among all scales in the PACU and on the ward (r=0.621-0.827, P<0.0001) supported concurrent validity. Use of the kappa statistic indicated that CHEOPS yielded the best agreement with the routine decision to treat pain. The younger and older age groups both yielded very good agreement in the PACU but only moderate agreement on the ward. On the basis of data from this study, we recommend CHEOPS as a valid, reliable and practical tool. PMID:11517123

  11. Airborne environmental endotoxin: a cross-validation of sampling and analysis techniques.

    PubMed Central

    Walters, M; Milton, D; Larsson, L; Ford, T

    1994-01-01

    A standard method for measurement of airborne environmental endotoxin was developed and field tested in a fiberglass insulation-manufacturing facility. This method involved sampling with a capillary-pore membrane filter, extraction in buffer using a sonication bath, and analysis by the kinetic-Limulus assay with resistant-parallel-line estimation (KLARE). Cross-validation of the extraction and assay method was performed by comparison with methanolysis of samples followed by 3-hydroxy fatty acid (3-OHFA) analysis by gas chromatography-mass spectrometry. Direct methanolysis of filter samples and methanolysis of buffer extracts of the filters yielded similar 3-OHFA content (P = 0.72); the average difference was 2.1%. Analysis of buffer extracts for endotoxin content by the KLARE method and by gas chromatography-mass spectrometry for 3-OHFA content produced similar results (P = 0.23); the average difference was 0.88%. The source of endotoxin was gram-negative bacteria growing in recycled washwater used to clean the insulation-manufacturing equipment. The endotoxin and bacteria become airborne during spray cleaning operations. The types of 3-OHFAs in bacteria cultured from the washwater, present in the washwater and in the air, were similar. Virtually all of the bacteria cultured from air and water were gram negative composed mostly of two species, Deleya aesta and Acinetobacter johnsonii. Airborne countable bacteria correlated well with endotoxin (r2 = 0.64). Replicate sampling showed that results with the standard sampling, extraction, and Limulus assay by the KLARE method were highly reproducible (95% confidence interval for endotoxin measurement +/- 0.28 log10). These results demonstrate the accuracy, precision, and sensitivity of the standard procedure proposed for airborne environmental endotoxin. PMID:8161191

  12. Development and cross-validation of prediction equations for estimating resting energy expenditure in severely obese Caucasian children and adolescents.

    PubMed

    Lazzer, Stefano; Agosti, Fiorenza; De Col, Alessandra; Sartorio, Alessandro

    2006-11-01

    The objectives of the present study were to develop and cross-validate new equations for predicting resting energy expenditure (REE) in severely obese children and adolescents, and to determine the accuracy of new equations using the Bland-Altman method. The subjects of the study were 574 obese Caucasian children and adolescents (mean BMI z-score 3.3). REE was determined by indirect calorimetry and body composition by bioelectrical impedance analysis. Equations were derived by stepwise multiple regression analysis using a calibration cohort of 287 subjects and the equations were cross-validated in the remaining 287 subjects. Two new specific equations based on anthropometric parameters were generated as follows: (1) REE=(Sex x 892.68)-(Age x 115.93)+(Weight x 54.96)+(Stature x 1816.23)+1484.50 (R(2) 0.66; se 1028.97 kJ); (2) REE=(Sex x 909.12)-(Age x 107.48)+(fat-free mass x 68.39)+(fat mass x 55.19)+3631.23 (R(2) 0.66; se 1034.28 kJ). In the cross-validation group, mean predicted REE values were not significantly different from the mean measured REE for all children and adolescents, as well as for boys and for girls (difference <2 %) and the limits of agreement (+/-2 sd) were +2.06 and -1.77 MJ/d (NS). The new prediction equations allow an accurate estimation of REE in groups of severely obese children and adolescents. These equations might be useful for health care professionals and researchers when estimating REE in severely obese children and adolescents. PMID:17092390

  13. Cross-validation of the reduced form of the Food Craving Questionnaire-Trait using confirmatory factor analysis

    PubMed Central

    Iani, Luca; Barbaranelli, Claudio; Lombardo, Caterina

    2015-01-01

    Objective: The Food Craving Questionnaire-Trait (FCQ-T) is commonly used to assess habitual food cravings among individuals. Previous studies have shown that a brief version of this instrument (FCQ-T-r) has good reliability and validity. This article is the first to use Confirmatory factor analysis to examine the psychometric properties of the FCQ-T-r in a cross-validation study. Method: Habitual food cravings, as well as emotion regulation strategies, affective states, and disordered eating behaviors, were investigated in two independent samples of non-clinical adult volunteers (Sample 1: N = 368; Sample 2: N = 246). Confirmatory factor analyses were conducted to simultaneously test model fit statistics and dimensionality of the instrument. FCQ-T-r reliability was assessed by computing the composite reliability coefficient. Results: Analysis supported the unidimensional structure of the scale and fit indices were acceptable for both samples. The FCQ-T-r showed excellent reliability and moderate to high correlations with negative affect and disordered eating. Conclusion: Our results indicate that the FCQ-T-r scores can be reliably used to assess habitual cravings in an Italian non-clinical sample of adults. The robustness of these results is tested by a cross-validation of the model using two independent samples. Further research is required to expand on these findings, particularly in children and adolescents. PMID:25918510

  14. Cross-Validation of Magnetic Resonance Elastography and Ultrasound-Based Transient Elastography: A Preliminary Phantom Study

    PubMed Central

    Chen, Jun; Glaser, Kevin J; Miette, Véronique; Sandrin, Laurent; Ehman, Richard L

    2010-01-01

    Purpose To cross-validate two recent noninvasive elastographic techniques, Ultrasound-based Transient Elastography (UTE) and Magnetic Resonance Elastography (MRE). As potential alternatives to liver biopsy, UTE and MRE are undergoing clinical investigations for liver fibrosis diagnosis and liver disease management around the world. These two techniques use tissue stiffness as a marker for disease state and it is important to do a cross-validation study of both elastographic techniques to determine the consistency with which the two techniques can measure the mechanical properties of materials. Materials and Methods In this paper, 19 well-characterized phantoms with a range of stiffness values were measured by two clinical devices (a Fibroscan and a MRE system based respectively on the UTE and MRE techniques) successively with the operators double-blinded. Results Statistical analysis showed that the correlation coefficient was r2=0.93 between MRE and UTE, and there was no evidence of a systematic difference between them within the range of stiffnesses examined. Conclusion These two noninvasive methods, MRE and UTE, provide clinicians with important new options for improving patient care regarding liver diseases in terms of the diagnosis, prognosis, and monitoring of fibrosis progression, as well for evaluating the efficacy of treatment. PMID:19856447

  15. Bayes and Empirical Bayes Shrinkage Estimation of Regression Coefficients: A Cross-Validation Study.

    ERIC Educational Resources Information Center

    Nebebe, Fassil; Stroud, T. W. F.

    1988-01-01

    Bayesian and empirical Bayes approaches to shrinkage estimation of regression coefficients and uses of these in prediction (i.e., analyzing intelligence test data of children with learning problems) are investigated. The two methods are consistently better at predicting response variables than are either least squares or least absolute deviations.…

  16. Validating clinical terminology structures: integration and cross-validation of Read Thesaurus and GALEN.

    PubMed Central

    Rogers, J. E.; Price, C.; Rector, A. L.; Solomon, W. D.; Smejko, N.

    1998-01-01

    A European pre-standard and an intermediate representation facilitated exchange of two independently authored compositional knowledge bases: one formal and automatically classified, the other manually classified. The exchange highlights different strengths and weaknesses in each approach, and offers a mechanism for partial, mutual quality assurance. PMID:9929338

  17. Standardization and cross validation of alloreactive IFNγ ELISPOT assays within the clinical trials in organ transplantation consortium.

    PubMed

    Ashoor, I; Najafian, N; Korin, Y; Reed, E F; Mohanakumar, T; Ikle, D; Heeger, P S; Lin, M

    2013-07-01

    Emerging evidence indicates memory donor-reactive T cells are detrimental to transplant outcome and that quantifying the frequency of IFNγ-producing, donor-reactive PBMCs by ELISPOT has potential utility as an immune monitoring tool. Nonetheless, differences in assay performance among laboratories limit the ability to compare results. In an effort to standardize assays, we prepared a panel of common cellular reagent standards, developed and cross validated a standard operating procedure (SOP) for alloreactive IFNγ ELISPOT assays in several research laboratories supported by the NIH-funded Clinical Trials in Organ Transplantation (CTOT) Consortium. We demonstrate that strict adherence to the SOP and centralized data analysis results in high reproducibility with a coefficient of variance (CV) of ≈ 30%. This standardization of IFNγ ELISPOT assay will facilitate interpretation of data from multicenter transplantation research studies and provide the foundation for developing clinical laboratory testing strategies to guide therapeutic decision-making in transplant patients. PMID:23710568

  18. A bayesian cross-validation approach to evaluate genetic baselines and forecast the necessary number of informative single nucleotide polymorphisms

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Mixed stock analysis (MSA) is a powerful tool used in the management and conservation of numerous species. Its function is to estimate the sources of contributions in a mixture of populations of a species, as well as to estimate the probabilities that individuals originated at a source. Considerable...

  19. Evidence cross-validation and Bayesian inference of MAST plasma equilibria

    NASA Astrophysics Data System (ADS)

    von Nessi, G. T.; Hole, M. J.; Svensson, J.; Appel, L.

    2012-01-01

    In this paper, current profiles for plasma discharges on the mega-ampere spherical tokamak are directly calculated from pickup coil, flux loop, and motional-Stark effect observations via methods based in the statistical theory of Bayesian analysis. By representing toroidal plasma current as a series of axisymmetric current beams with rectangular cross-section and inferring the current for each one of these beams, flux-surface geometry and q-profiles are subsequently calculated by elementary application of Biot-Savart's law. The use of this plasma model in the context of Bayesian analysis was pioneered by Svensson and Werner on the joint-European tokamak [Svensson and Werner,Plasma Phys. Controlled Fusion 50(8), 085002 (2008)]. In this framework, linear forward models are used to generate diagnostic predictions, and the probability distribution for the currents in the collection of plasma beams was subsequently calculated directly via application of Bayes' formula. In this work, we introduce a new diagnostic technique to identify and remove outlier observations associated with diagnostics falling out of calibration or suffering from an unidentified malfunction. These modifications enable a good agreement between Bayesian inference of the last-closed flux-surface with other corroborating data, such as that from force balance considerations using EFIT++ [Appel et al., "A unified approach to equilibrium reconstruction" Proceedings of the 33rd EPS Conference on Plasma Physics (Rome, Italy, 2006)]. In addition, this analysis also yields errors on the plasma current profile and flux-surface geometry as well as directly predicting the Shafranov shift of the plasma core.

  20. An Improved Systematic Approach to Predicting Transcription Factor Target Genes Using Support Vector Machine

    PubMed Central

    Cui, Song; Youn, Eunseog; Lee, Joohyun; Maas, Stephan J.

    2014-01-01

    Biological prediction of transcription factor binding sites and their corresponding transcription factor target genes (TFTGs) makes great contribution to understanding the gene regulatory networks. However, these approaches are based on laborious and time-consuming biological experiments. Numerous computational approaches have shown great potential to circumvent laborious biological methods. However, the majority of these algorithms provide limited performances and fail to consider the structural property of the datasets. We proposed a refined systematic computational approach for predicting TFTGs. Based on previous work done on identifying auxin response factor target genes from Arabidopsis thaliana co-expression data, we adopted a novel reverse-complementary distance-sensitive n-gram profile algorithm. This algorithm converts each upstream sub-sequence into a high-dimensional vector data point and transforms the prediction task into a classification problem using support vector machine-based classifier. Our approach showed significant improvement compared to other computational methods based on the area under curve value of the receiver operating characteristic curve using 10-fold cross validation. In addition, in the light of the highly skewed structure of the dataset, we also evaluated other metrics and their associated curves, such as precision-recall curves and cost curves, which provided highly satisfactory results. PMID:24743548

  1. Cross-Validation of the Recumbent Stepper Submaximal Exercise Test to Predict Peak Oxygen Uptake in Older Adults

    PubMed Central

    Herda, Ashley A.; Lentz, Angela A.; Mattlage, Anna E.; Sisante, Jason-Flor

    2014-01-01

    Background Submaximal exercise testing can have a greater application in clinical settings because peak exercise testing is generally not available. In previous work, a prediction equation was developed to estimate peak oxygen consumption (V̇o2) using a total body recumbent stepper (TBRS) and the Young Men's Christian Association (YMCA) protocol in adults who were healthy. Objective The purpose of the present study was to cross-validate the TBRS peak V̇o2 prediction equation in older adults. Design A cross-sectional study was conducted. Methods Thirty participants (22 female, 8 male; mean age=66.8 years, SD=5.52; mean weight=68.51 kg, SD=13.39) who previously completed a peak exercise test and met the inclusion criteria were invited to participate in the cross-validation study. Within 5 days of the peak V̇o2 test, participants completed the TBRS submaximal exercise test. The TBRS submaximal exercise test equation was used to estimate peak V̇o2. The variables in the equation included age, weight, sex, watts (at the end of the submaximal exercise test), and heart rate (at the end of the submaximal exercise test). Results A strong correlation was found between the predicted peak V̇o2 and the measured peak V̇o2. The difference between the values was 0.9 mL·kg−1·min−1, which was not statistically different. The standard error of the estimate was 4.2 mL·kg−1·min−1. Limitations The sample included individuals who volunteered to perform a peak exercise test, which may have biased the results toward those willing to exercise to fatigue. Conclusion The data suggest the TBRS submaximal exercise test and prediction equation can be used to predict peak V̇o2 in older adults. This finding is important for health care professionals wanting to provide information to their patients or clients regarding their fitness level. PMID:24435104

  2. An intercomparison of a large ensemble of statistical downscaling methods for Europe: Overall results from the VALUE perfect predictor cross-validation experiment

    NASA Astrophysics Data System (ADS)

    Gutiérrez, Jose Manuel; Maraun, Douglas; Widmann, Martin; Huth, Radan; Hertig, Elke; Benestad, Rasmus; Roessler, Ole; Wibig, Joanna; Wilcke, Renate; Kotlarski, Sven

    2016-04-01

    VALUE is an open European network to validate and compare downscaling methods for climate change research (http://www.value-cost.eu). A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. This framework is based on a user-focused validation tree, guiding the selection of relevant validation indices and performance measures for different aspects of the validation (marginal, temporal, spatial, multi-variable). Moreover, several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur (assessment of intrinsic performance, effect of errors inherited from the global models, effect of non-stationarity, etc.). The list of downscaling experiments includes 1) cross-validation with perfect predictors, 2) GCM predictors -aligned with EURO-CORDEX experiment- and 3) pseudo reality predictors (see Maraun et al. 2015, Earth's Future, 3, doi:10.1002/2014EF000259, for more details). The results of these experiments are gathered, validated and publicly distributed through the VALUE validation portal, allowing for a comprehensive community-open downscaling intercomparison study. In this contribution we describe the overall results from Experiment 1), consisting of a European wide 5-fold cross-validation (with consecutive 6-year periods from 1979 to 2008) using predictors from ERA-Interim to downscale precipitation and temperatures (minimum and maximum) over a set of 86 ECA&D stations representative of the main geographical and climatic regions in Europe. As a result of the open call for contribution to this experiment (closed in Dec. 2015), over 40 methods representative of the main approaches (MOS and Perfect Prognosis, PP) and techniques (linear scaling, quantile mapping, analogs, weather typing, linear and generalized regression, weather generators, etc.) were submitted, including information both data

  3. An Efficient Leave-One-Out Cross-Validation-Based Extreme Learning Machine (ELOO-ELM) With Minimal User Intervention.

    PubMed

    Shao, Zhifei; Er, Meng Joo; Wang, Ning

    2016-08-01

    It is well known that the architecture of the extreme learning machine (ELM) significantly affects its performance and how to determine a suitable set of hidden neurons is recognized as a key issue to some extent. The leave-one-out cross-validation (LOO-CV) is usually used to select a model with good generalization performance among potential candidates. The primary reason for using the LOO-CV is that it is unbiased and reliable as long as similar distribution exists in the training and testing data. However, the LOO-CV has rarely been implemented in practice because of its notorious slow execution speed. In this paper, an efficient LOO-CV formula and an efficient LOO-CV-based ELM (ELOO-ELM) algorithm are proposed. The proposed ELOO-ELM algorithm can achieve fast learning speed similar to the original ELM without compromising the reliability feature of the LOO-CV. Furthermore, minimal user intervention is required for the ELOO-ELM, thus it can be easily adopted by nonexperts and implemented in automation processes. Experimentation studies on benchmark datasets demonstrate that the proposed ELOO-ELM algorithm can achieve good generalization with limited user intervention while retaining the efficiency feature. PMID:26259254

  4. Accuracy of Population Validity and Cross-Validity Estimation: An Empirical Comparison of Formula-Based, Traditional Empirical, and Equal Weights Procedures.

    ERIC Educational Resources Information Center

    Raju, Nambury S.; Bilgic, Reyhan; Edwards, Jack E.; Fleer, Paul F.

    1999-01-01

    Performed an empirical Monte Carlo study using predictor and criterion data from 84,808 U.S. Air Force enlistees. Compared formula-based, traditional empirical, and equal-weights procedures. Discusses issues for basic research on validation and cross-validation. (SLD)

  5. Cross-Validation of a Recently Published Equation Predicting Energy Expenditure to Run or Walk a Mile in Normal-Weight and Overweight Adults

    ERIC Educational Resources Information Center

    Morris, Cody E.; Owens, Scott G.; Waddell, Dwight E.; Bass, Martha A.; Bentley, John P.; Loftin, Mark

    2014-01-01

    An equation published by Loftin, Waddell, Robinson, and Owens (2010) was cross-validated using ten normal-weight walkers, ten overweight walkers, and ten distance runners. Energy expenditure was measured at preferred walking (normal-weight walker and overweight walkers) or running pace (distance runners) for 5 min and corrected to a mile. Energy…

  6. A Cross-Validation of easyCBM Mathematics Cut Scores in Washington State: 2009-2010 Test. Technical Report #1105

    ERIC Educational Resources Information Center

    Anderson, Daniel; Alonzo, Julie; Tindal, Gerald

    2011-01-01

    In this technical report, we document the results of a cross-validation study designed to identify optimal cut-scores for the use of the easyCBM[R] mathematics test in the state of Washington. A large sample, randomly split into two groups of roughly equal size, was used for this study. Students' performance classification on the Washington state…

  7. Cross-Validation of the Behavioral and Emotional Rating Scale-2 Youth Version: An Exploration of Strength-Based Latent Traits

    ERIC Educational Resources Information Center

    Furlong, Michael J.; Sharkey, Jill D.; Boman, Peter; Caldwell, Roslyn

    2007-01-01

    High-quality measurement is a necessary requirement to develop and evaluate the effectiveness of programs that use strength-based principles and strategies. Using independent cross-validation samples, we report two studies that explored the construct validity of the BERS-2 Youth Report, a popular measure designed to assess youth strengths, whose…

  8. Cross-validation of generalised body composition equations with diverse young men and women: the Training Intervention and Genetics of Exercise Response (TIGER) Study

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Generalised skinfold equations developed in the 1970s are commonly used to estimate laboratory-measured percentage fat (BF%). The equations were developed on predominately white individuals using Siri's two-component percentage fat equation (BF%-GEN). We cross-validated the Jackson-Pollock (JP) gene...

  9. Latent Structure and Reliability Analysis of the Measure of Body Apperception: Cross-Validation for Head and Neck Cancer Patients

    PubMed Central

    Jean-Pierre, Pascal; Fundakowski, Christopher; Perez, Enrique; Jean-Pierre, Shadae E.; Jean-Pierre, Ashley R.; Melillo, Angelica B.; Libby, Rachel; Sargi, Zoukaa

    2014-01-01

    Purpose Cancer and its treatments are associated with psychological distress that can negatively impact self-perception, psychosocial functioning, and quality of life. Patients with Head and neck cancers (HNC) are particularly susceptible to psychological distress. This study involved a cross-validation of the Measure of Body Apperception (MBA) for HNC patients. Methods One hundred twenty-two English-fluent HNC patients between 20 and 88 years of age completed the MBA on a Likert scale ranging from “1=Disagree” to “4=Agree”. We assessed the latent structure and internal consistency reliability of the MBA using Principal Components Analysis (PCA) and Cronbach's coefficient alpha (α), respectively. We determined convergent and divergent validities of the MBA using correlations with the Hospital Anxiety and Depression Scale (HADS), observer disfigurement rating, and patients’ clinical and demographic variables. Results The PCA revealed a coherent set of items that explained 38% of the variance. The Keiser-Meyer-Olkin measure of sampling adequacy was .73 and the Bartlett's Test of Sphericity was statistically significant (χ2 (28) = 253.64; p < .001), confirming the suitability of the data for dimension reduction analysis. The MBA had good internal consistency reliability (α = .77) and demonstrated adequate convergent and divergent validities based on statistically significant moderate correlations with the HADS (p < .01) and observer rating of disfigurement (p < .026), and non-statistically significant correlations with patients’ clinical and demographic variables: tumor location, age at diagnosis, and birth place (all ps > .05). Conclusions The MBA is a valid and reliable screening measure of body apperception for HNC patients. PMID:22886430

  10. Multiple dimensions of health locus of control in a representative population sample: ordinal factor analysis and cross-validation of an existing three and a new four factor model

    PubMed Central

    2011-01-01

    Background Based on the general approach of locus of control, health locus of control (HLOC) concerns control-beliefs due to illness, sickness and health. HLOC research results provide an improved understanding of health related behaviour and patients' compliance in medical care. HLOC research distinguishes between beliefs due to Internality, Externality powerful Others (POs) and Externality Chance. However, evidences for differentiating the POs dimension were found. Previous factor analyses used selected and predominantly clinical samples, while non-clinical studies are rare. The present study is the first analysis of the HLOC structure based on a large representative general population sample providing important information for non-clinical research and public health care. Methods The standardised German questionnaire which assesses HLOC was used in a representative adult general population sample for a region in Northern Germany (N = 4,075). Data analyses used ordinal factor analyses in LISREL and Mplus. Alternative theory-driven models with one to four latent variables were compared using confirmatory factor analysis. Fit indices, chi-square difference tests, residuals and factor loadings were considered for model comparison. Exploratory factor analysis was used for further model development. Results were cross-validated splitting the total sample randomly and using the cross-validation index. Results A model with four latent variables (Internality, Formal Help, Informal Help and Chance) best represented the HLOC construct (three-dimensional model: normed chi-square = 9.55; RMSEA = 0.066; CFI = 0.931; SRMR = 0.075; four-dimensional model: normed chi-square = 8.65; RMSEA = 0.062; CFI = 0.940; SRMR = 0.071; chi-square difference test: p < 0.001). After excluding one item, the superiority of the four- over the three-dimensional HLOC construct became very obvious (three-dimensional model: normed chi-square = 7.74; RMSEA = 0.059; CFI = 0.950; SRMR = 0.079; four

  11. Predicting Chinese Children and Youth's Energy Expenditure Using ActiGraph Accelerometers: A Calibration and Cross-Validation Study

    ERIC Educational Resources Information Center

    Zhu, Zheng; Chen, Peijie; Zhuang, Jie

    2013-01-01

    Purpose: The purpose of this study was to develop and cross-validate an equation based on ActiGraph accelerometer GT3X output to predict children and youth's energy expenditure (EE) of physical activity (PA). Method: Participants were 367 Chinese children and youth (179 boys and 188 girls, aged 9 to 17 years old) who wore 1 ActiGraph GT3X…

  12. Development and cross-validation of prognostic models to assess the treatment effect of cisplatin/pemetrexed chemotherapy in lung adenocarcinoma patients.

    PubMed

    Mou, Wenjun; Liu, Zhaoqi; Luo, Yuan; Zou, Meng; Ren, Chao; Zhang, Chunyan; Wen, Xinyu; Wang, Yong; Tian, Yaping

    2014-09-01

    Better understanding of the treatment effect of cisplatin/pemetrexed chemotherapy on lung adenocarcinoma patients is needed to facilitate chemotherapy planning and patient care. In this retrospective study, we will develop prognostic models by the cross-validation method using clinical and serum factors to predict outcomes of cisplatin/pemetrexed chemotherapy in lung adenocarcinoma patients. Lung adenocarcinoma patients admitted between 2008 and 2013 were enrolled. 29 serum parameters of laboratory tests and 14 clinical factors were analyzed to develop the prognostic models. First, the stepwise selection and five-fold cross-validation were performed to identify candidate prognostic factors. Then a classification of all patients based on the number of metastatic sites resulted in four distinct subsets. In each subset, a prognostic model was fitted with the most accurate prognostic factors from the candidate prognostic factors. Categorical survival prediction was estimated using a log-rank test and visualized with Kaplan-Meier method. 227 lung adenocarcinoma patients were enrolled. Twenty candidate prognostic factors evaluated using the five-fold cross-validation method were total protein, total bilirubin, direct bilirubin, creatine kinase, age, smoking index, neuron-specific enolase, bone metastasis, total triglyceride, albumin, gender, uric acid, CYFRA21-1, lymph node metastasis, liver metastasis, lactate dehydrogenase, CA153, peritoneal metastasis, CA125, and CA199. From these 20 candidate prognostic factors, the multivariate Cox proportional hazard model with the highest prognostic accuracy in each subset was identified by the stepwise forward selection method, which generated significant prognostic stratifications in Kaplan-Meier survival analyses (all log-rank p < 0.01). Generally, the prognostic models using five-fold cross-validation achieve a good prediction performance. The prognostic models can be administered safely to lung adenocarcinoma patients treated

  13. Quantification of rainfall prediction uncertainties using a cross-validation based technique. Methodology description and experimental validation.

    NASA Astrophysics Data System (ADS)

    Fraga, Ignacio; Cea, Luis; Puertas, Jerónimo; Salsón, Santiago; Petazzi, Alberto

    2016-04-01

    In this paper we present a new methodology to compute rainfall fields including the quantification of predictions uncertainties using raingauge network data. The proposed methodology comprises two steps. Firstly, the ordinary krigging technique is used to determine the estimated rainfall depth in every point of the study area. Then multiple equi-probable errors fields, which comprise both interpolation and measuring uncertainties, are added to the krigged field resulting in multiple rainfall predictions. To compute these error fields first the standard deviation of the krigging estimation is determined following the cross-validation based procedure described in Delrieu et al. (2014). Then, the standard deviation field is sampled using non-conditioned Gaussian random fields. The proposed methodology was applied to study 7 rain events in a 60x60 km area of the west coast of Galicia, in the Northwest of Spain. Due to its location at the junction between tropical and polar regions, the study area suffers from frequent intense rainfalls characterized by a great variability in terms of both space and time. Rainfall data from the tipping bucket raingauge network operated by MeteoGalicia were used to estimate the rainfall fields using the proposed methodology. The obtained predictions were then validated using rainfall data from 3 additional rain gauges installed within the CAPRI project (Probabilistic flood prediction with high resolution hydrologic models from radar rainfall estimates, funded by the Spanish Ministry of Economy and Competitiveness. Reference CGL2013-46245-R.). Results show that both the mean hyetographs and the peak intensities are correctly predicted. The computed hyetographs present a good fit to the experimental data and most of the measured values fall within the 95% confidence intervals. Also, most of the experimental values outside the confidence bounds correspond to time periods of low rainfall depths, where the inaccuracy of the measuring devices

  14. A semi-mechanism approach based on MRI and proteomics for prediction of conversion from mild cognitive impairment to Alzheimer’s disease

    PubMed Central

    Liu, Haochen; Zhou, Xiaoting; Jiang, Hao; He, Hua; Liu, Xiaoquan; Weiner, Michael W.; Aisen, Paul; Petersen, Ronald; Jack, Clifford R.; Jagust, William; Trojanowki, John Q.; Toga, Arthur W.; Beckett, Laurel; Green, Robert C.; Saykin, Andrew J.; Morris, John; Shaw, Leslie M.; Khachaturian, Zaven; Sorensen, Greg; Carrillo, Maria; Kuller, Lew; Raichle, Marc; Paul, Steven; Davies, Peter; Fillit, Howard; Hefti, Franz; Holtzman, Davie; Mesulam, M. Marcel; Potter, William; Snyder, Peter; Montine, Tom; Thomas, Ronald G.; Donohue, Michael; Walter, Sarah; Sather, Tamie; Jiminez, Gus; Balasubramanian, Archana B.; Mason, Jennifer; Sim, Iris; Harvey, Danielle; Bernstein, Matthew; Fox, Nick; Thompson, Paul; Schuff, Norbert; DeCArli, Charles; Borowski, Bret; Gunter, Jeff; Senjem, Matt; Vemuri, Prashanthi; Jones, David; Kantarci, Kejal; Ward, Chad; Koeppe, Robert A.; Foster, Norm; Reiman, Eric M.; Chen, Kewei; Mathis, Chet; Landau, Susan; Cairns, Nigel J.; Householder, Erin; Taylor-Reinwald, Lisa; Lee, Virginia; Korecka, Magdalena; Figurski, Michal; Crawford, Karen; Neu, Scott; Foroud, Tatiana M.; Potkin, Steven; Shen, Li; Faber, Kelley; Kim, Sungeun; Nho, Kwangsik; Thal, Lean; Frank, Richard; Hsiao, John; Kaye, Jeffrey; Quinn, Joseph; Silbert, Lisa; Lind, Betty; Carter, Raina; Dolen, Sara; Ances, Beau; Carroll, Maria; Creech, Mary L.; Franklin, Erin; Mintun, Mark A.; Schneider, Stacy; Oliver, Angela; Schneider, Lon S.; Pawluczyk, Sonia; Beccera, Mauricio; Teodoro, Liberty; Spann, Bryan M.; Brewer, James; Vanderswag, Helen; Fleisher, Adam; Marson, Daniel; Griffith, Randall; Clark, David; Geldmacher, David; Brockington, John; Roberson, Erik; Love, Marissa Natelson; Heidebrink, Judith L.; Lord, Joanne L.; Mason, Sara S.; Albers, Colleen S.; Knopman, David; Johnson, Kris; Grossman, Hillel; Mitsis, Effie; Shah, Raj C.; deToledo-Morrell, Leyla; Doody, Rachelle S.; Villanueva-Meyer, Javier; Chowdhury, Munir; Rountree, Susan; Dang, Mimi; Duara, Ranjan; Varon, Daniel; Greig, Maria T.; Roberts, Peggy; Stern, Yaakov; Honig, Lawrence S.; Bell, Karen L.; Albert, Marilyn; Onyike, Chiadi; D’Agostino II, Daniel; Kielb, Stephanie; Galvin, James E.; Cerbone, Brittany; Michel, Christina A.; Pogorelec, Dana M.; Rusinek, Henry; de Leon, Mony J.; Glodzik, Lidia; De Santi, Susan; Womack, Kyle; Mathews, Dana; Quiceno, Mary; Doraiswamy, P. Murali; Petrella, Jeffrey R.; Borges-Neto, Salvador; Wong, Terence Z.; Coleman, Edward; Levey, Allan I.; Lah, James J.; Cella, Janet S.; Burns, Jeffrey M.; Swerdlow, Russell H.; Brooks, William M.; Arnold, Steven E.; Karlawish, Jason H.; Wolk, David; Clark, Christopher M.; Apostolova, Liana; Tingus, Kathleen; Woo, Ellen; Silverman, Daniel H.S.; Lu, Po H.; Bartzokis, George; Smith, Charles D.; Jicha, Greg; Hardy, Peter; Sinha, Partha; Oates, Elizabeth; Conrad, Gary; Graff-Radford, Neill R; Parfitt, Francine; Kendall, Tracy; Johnson, Heather; Lopez, Oscar L.; Oakley, MaryAnn; Simpson, Donna M.; Farlow, Martin R.; Hake, Ann Marie; Matthews, Brandy R.; Brosch, Jared R.; Herring, Scott; Hunt, Cynthia; Porsteinsson, Anton P.; Goldstein, Bonnie S.; Martin, Kim; Makino, Kelly M.; Ismail, M. Saleem; Brand, Connie; Mulnard, Ruth A.; Thai, Gaby; Mc-Adams-Ortiz, Catherine; van Dyck, Christopher H.; Carson, Richard E.; MacAvoy, Martha G.; Varma, Pradeep; Chertkow, Howard; Bergman, Howard; Hosein, Chris; Black, Sandra; Stefanovic, Bojana; Caldwell, Curtis; Robin Hsiung, Ging-Yuek; Feldman, Howard; Mudge, Benita; Assaly, Michele; Finger, Elizabeth; Pasternack, Stephen; Rachisky, Irina; Trost, Dick; Kertesz, Andrew; Bernick, Charles; Munic, Donna; Lipowski, Kristine; Weintraub, MASandra; Bonakdarpour, Borna; Kerwin, Diana; Wu, Chuang-Kuo; Johnson, Nancy; Sadowsky, Carl; Villena, Teresa; Turner, Raymond Scott; Johnson, Kathleen; Reynolds, Brigid; Sperling, Reisa A.; Johnson, Keith A.; Marshall, Gad; Yesavage, Jerome; Taylor, Joy L.; Lane, Barton; Rosen, Allyson; Tinklenberg, Jared; Sabbagh, Marwan N.; Belden, Christine M.; Jacobson, Sandra A.; Sirrel, Sherye A.; Kowall, Neil; Killiany, Ronald; Budson, Andrew E.; Norbash, Alexander; Johnson, Patricia Lynn; Obisesan, Thomas O.; Wolday, Saba; Allard, Joanne; Lerner, Alan; Ogrocki, Paula; Tatsuoka, Curtis; Fatica, Parianne; Fletcher, Evan; Maillard, Pauline; Olichney, John; Carmichael, Owen; Kittur, Smita; Borrie, Michael; Lee, T-Y; Bartha, Rob; Johnson, Sterling; Asthana, Sanjay; Carlsson, Cynthia M.; Preda, Adrian; Nguyen, Dana; Tariot, Pierre; Burke, Anna; Trncic, Nadira; Fleisher, Adam; Reeder, Stephanie; Bates, Vernice; Capote, Horacio; Rainka, Michelle; Scharre, Douglas W.; Kataki, Maria; Adeli, Anahita; Zimmerman, Earl A.; Celmins, Dzintra; Brown, Alice D.; Pearlson, Godfrey D.; Blank, Karen; Anderson, Karen; Flashman, Laura A.; Seltzer, Marc; Hynes, Mary L.; Santulli, Robert B.; Sink, Kaycee M.; Gordineer, Leslie; Williamson, Jeff D.; Garg, Pradeep; Watkins, Franklin; Ott, Brian R.; Querfurth, Henry; Tremont, Geoffrey; Salloway, Stephen; Malloy, Paul; Correia, Stephen; Rosen, Howard J.; Miller, Bruce L.; Perry, David; Mintzer, Jacobo; Spicer, Kenneth; Bachman, David; Finger, Elizabether; Pasternak, Stephen; Rachinsky, Irina; Rogers, John; Drost, Dick; Pomara, Nunzio; Hernando, Raymundo; Sarrael, Antero; Schultz, Susan K.; Boles Ponto, Laura L.; Shim, Hyungsub; Smith, Karen Ekstam; Relkin, Norman; Chaing, Gloria; Lin, Michael; Ravdin, Lisa; Smith, Amanda; Raj, Balebail Ashok; Fargher, Kristin

    2016-01-01

    Mild cognitive impairment (MCI) is a precursor phase of Alzheimer’s disease (AD). As current treatments may be effective only at the early stages of AD, it is important to track MCI patients who will convert to AD. The aim of this study is to develop a high performance semi-mechanism based approach to predict the conversion from MCI to AD and improve our understanding of MCI-to-AD conversion mechanism. First, analysis of variance (ANOVA) test and lasso regression are employed to identify the markers related to the conversion. Then the Bayesian network based on selected markers is established to predict MCI-to-AD conversion. The structure of Bayesian network suggests that the conversion may start with fibrin clot formation, verbal memory impairment, eating pattern changing and hyperinsulinemia. The Bayesian network achieves a high 10-fold cross-validated prediction performance with 96% accuracy, 95% sensitivity, 65% specificity, area under the receiver operating characteristic curve of 0.82 on data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The semi-mechanism based approach provides not only high prediction performance but also clues of mechanism for MCI-to-AD conversion. PMID:27273250

  15. A semi-mechanism approach based on MRI and proteomics for prediction of conversion from mild cognitive impairment to Alzheimer's disease.

    PubMed

    Liu, Haochen; Zhou, Xiaoting; Jiang, Hao; He, Hua; Liu, Xiaoquan

    2016-01-01

    Mild cognitive impairment (MCI) is a precursor phase of Alzheimer's disease (AD). As current treatments may be effective only at the early stages of AD, it is important to track MCI patients who will convert to AD. The aim of this study is to develop a high performance semi-mechanism based approach to predict the conversion from MCI to AD and improve our understanding of MCI-to-AD conversion mechanism. First, analysis of variance (ANOVA) test and lasso regression are employed to identify the markers related to the conversion. Then the Bayesian network based on selected markers is established to predict MCI-to-AD conversion. The structure of Bayesian network suggests that the conversion may start with fibrin clot formation, verbal memory impairment, eating pattern changing and hyperinsulinemia. The Bayesian network achieves a high 10-fold cross-validated prediction performance with 96% accuracy, 95% sensitivity, 65% specificity, area under the receiver operating characteristic curve of 0.82 on data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The semi-mechanism based approach provides not only high prediction performance but also clues of mechanism for MCI-to-AD conversion. PMID:27273250

  16. An efficient diagnosis system for Parkinson's disease using kernel-based extreme learning machine with subtractive clustering features weighting approach.

    PubMed

    Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Zhao, Xue-Hua

    2014-01-01

    A novel hybrid method named SCFW-KELM, which integrates effective subtractive clustering features weighting and a fast classifier kernel-based extreme learning machine (KELM), has been introduced for the diagnosis of PD. In the proposed method, SCFW is used as a data preprocessing tool, which aims at decreasing the variance in features of the PD dataset, in order to further improve the diagnostic accuracy of the KELM classifier. The impact of the type of kernel functions on the performance of KELM has been investigated in detail. The efficiency and effectiveness of the proposed method have been rigorously evaluated against the PD dataset in terms of classification accuracy, sensitivity, specificity, area under the receiver operating characteristic (ROC) curve (AUC), f-measure, and kappa statistics value. Experimental results have demonstrated that the proposed SCFW-KELM significantly outperforms SVM-based, KNN-based, and ELM-based approaches and other methods in the literature and achieved highest classification results reported so far via 10-fold cross validation scheme, with the classification accuracy of 99.49%, the sensitivity of 100%, the specificity of 99.39%, AUC of 99.69%, the f-measure value of 0.9964, and kappa value of 0.9867. Promisingly, the proposed method might serve as a new candidate of powerful methods for the diagnosis of PD with excellent performance. PMID:25484912

  17. An Efficient Diagnosis System for Parkinson's Disease Using Kernel-Based Extreme Learning Machine with Subtractive Clustering Features Weighting Approach

    PubMed Central

    Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Zhao, Xue-Hua

    2014-01-01

    A novel hybrid method named SCFW-KELM, which integrates effective subtractive clustering features weighting and a fast classifier kernel-based extreme learning machine (KELM), has been introduced for the diagnosis of PD. In the proposed method, SCFW is used as a data preprocessing tool, which aims at decreasing the variance in features of the PD dataset, in order to further improve the diagnostic accuracy of the KELM classifier. The impact of the type of kernel functions on the performance of KELM has been investigated in detail. The efficiency and effectiveness of the proposed method have been rigorously evaluated against the PD dataset in terms of classification accuracy, sensitivity, specificity, area under the receiver operating characteristic (ROC) curve (AUC), f-measure, and kappa statistics value. Experimental results have demonstrated that the proposed SCFW-KELM significantly outperforms SVM-based, KNN-based, and ELM-based approaches and other methods in the literature and achieved highest classification results reported so far via 10-fold cross validation scheme, with the classification accuracy of 99.49%, the sensitivity of 100%, the specificity of 99.39%, AUC of 99.69%, the f-measure value of 0.9964, and kappa value of 0.9867. Promisingly, the proposed method might serve as a new candidate of powerful methods for the diagnosis of PD with excellent performance. PMID:25484912

  18. Derivation and Cross-Validation of Cutoff Scores for Patients With Schizophrenia Spectrum Disorders on WAIS-IV Digit Span-Based Performance Validity Measures.

    PubMed

    Glassmire, David M; Toofanian Ross, Parnian; Kinney, Dominique I; Nitch, Stephen R

    2016-06-01

    Two studies were conducted to identify and cross-validate cutoff scores on the Wechsler Adult Intelligence Scale-Fourth Edition Digit Span-based embedded performance validity (PV) measures for individuals with schizophrenia spectrum disorders. In Study 1, normative scores were identified on Digit Span-embedded PV measures among a sample of patients (n = 84) with schizophrenia spectrum diagnoses who had no known incentive to perform poorly and who put forth valid effort on external PV tests. Previously identified cutoff scores resulted in unacceptable false positive rates and lower cutoff scores were adopted to maintain specificity levels ≥90%. In Study 2, the revised cutoff scores were cross-validated within a sample of schizophrenia spectrum patients (n = 96) committed as incompetent to stand trial. Performance on Digit Span PV measures was significantly related to Full Scale IQ in both studies, indicating the need to consider the intellectual functioning of examinees with psychotic spectrum disorders when interpreting scores on Digit Span PV measures. PMID:25997434

  19. The German Bight: Preparing for Sentinel-3 wit a Cross Validation of SAR and PLRM CryoSat-2 Altimeter Data

    NASA Astrophysics Data System (ADS)

    Fenoglio-Marc, L.; Buchhaupt, C.; Dinardo, S.; Scharroo, R.; Benveniste, J.; Becker, M.

    2015-12-01

    As preparatory work for Sentinel-3, we retrieve the three geophysical parameters: sea surface height (SSH), significant wave height (SWH) and wind speed at 10 meters height (U10) from CryoSat-2 data in our validation region in North Sea. The CryoSat-2 SAR echoes are processed with a coherent and an incoherent processing to generate SAR and PLRM data respectively. We derive precision and accuracy at 1 Hz in open ocean, at distances larger than 10 kilometres from the coast. A cross-validation of the SAR and PLRM altimeter data is performed to investigate the differences between the products. Look Up Tables (LUT) are applied in both schemes to correct for approximations applied in both retracking procedures. Additionally a numerical retracker is used in PLRM. The results are validated against in-situ and model data. The analysis is performed for a period of four years, from July 2010 to May 2014. The regional cross-validation analysis confirms the good consistency between PLRM and SAR data. Using LUT the agreement for the sea wave heights increases by 10%.

  20. Robustness of two single-item self-esteem measures: cross-validation with a measure of stigma in a sample of psychiatric patients.

    PubMed

    Bagley, Christopher

    2005-08-01

    Robins' Single-item Self-esteem Inventory was compared with a single item from the Coopersmith Self-esteem. Although a new scoring format was used, there was good evidence of cross-validation in 83 current and former psychiatric patients who completed Harvey's adapted measure of stigma felt and experienced by users of mental health services. Scores on the two single-item self-esteem measures correlated .76 (p < .001), .76 and .71 with scores on the longer scales from which they were taken, and .58 and .53, respectively, with Harvey's adapted stigma scale. Complex and perhaps competing models may explain links between felt stigma and poorer self-esteem in users of mental health services. PMID:16350637

  1. Parallel processing of chemical information in a local area network--II. A parallel cross-validation procedure for artificial neural networks.

    PubMed

    Derks, E P; Beckers, M L; Melssen, W J; Buydens, L M

    1996-08-01

    This paper describes a parallel cross-validation (PCV) procedure, for testing the predictive ability of multi-layer feed-forward (MLF) neural networks models, trained by the generalized delta learning rule. The PCV program has been parallelized to operate in a local area computer network. Development and execution of the parallel application was aided by the HYDRA programming environment, which is extensively described in Part I of this paper. A brief theoretical introduction on MLF networks is given and the problems, associated with the validation of predictive abilities, will be discussed. Furthermore, this paper comprises a general outline of the PCV program. Finally, the parallel PCV application is used to validate the predictive ability of an MLF network modeling a chemical non-linear function approximation problem which is described extensively in the literature. PMID:8799999

  2. SILAC-Pulse Proteolysis: A Mass Spectrometry-Based Method for Discovery and Cross-Validation in Proteome-Wide Studies of Ligand Binding

    NASA Astrophysics Data System (ADS)

    Adhikari, Jagat; Fitzgerald, Michael C.

    2014-12-01

    Reported here is the use of stable isotope labeling with amino acids in cell culture (SILAC) and pulse proteolysis (PP) for detection and quantitation of protein-ligand binding interactions on the proteomic scale. The incorporation of SILAC into PP enables the PP technique to be used for the unbiased detection and quantitation of protein-ligand binding interactions in complex biological mixtures (e.g., cell lysates) without the need for prefractionation. The SILAC-PP technique is demonstrated in two proof-of-principle experiments using proteins in a yeast cell lysate and two test ligands including a well-characterized drug, cyclosporine A (CsA), and a non-hydrolyzable adenosine triphosphate (ATP) analogue, adenylyl imidodiphosphate (AMP-PNP). The well-known tight-binding interaction between CsA and cyclophilin A was successfully detected and quantified in replicate analyses, and a total of 33 proteins from a yeast cell lysate were found to have AMP-PNP-induced stability changes. In control experiments, the method's false positive rate of protein target discovery was found to be in the range of 2.1% to 3.6%. SILAC-PP and the previously reported stability of protein from rates of oxidation (SPROX) technique both report on the same thermodynamic properties of proteins and protein-ligand complexes. However, they employ different probes and mass spectrometry-based readouts. This creates the opportunity to cross-validate SPROX results with SILAC-PP results, and vice-versa. As part of this work, the SILAC-PP results obtained here were cross-validated with previously reported SPROX results on the same model systems to help differentiate true positives from false positives in the two experiments.

  3. Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

    NASA Astrophysics Data System (ADS)

    Pradhan, Biswajeet

    2010-05-01

    This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross

  4. A Multiscale Decomposition Approach to Detect Abnormal Vasculature in the Optic Disc

    PubMed Central

    Agurto, Carla; Yu, Honggang; Murray, Victor; Pattichis, Marios S.; Nemeth, Sheila; Barriga, Simon; Soliz, Peter

    2015-01-01

    This paper presents a multiscale method to detect neovascularization in the optic disc (NVD) using fundus images. Our method is applied to a manually selected region of interest (ROI) containing the optic disc. All the vessels in the ROI are segmented by adaptively combining contrast enhancement methods with a vessel segmentation technique. Textural features extracted using multiscale amplitude-modulation frequency-modulation, morphological granulometry, and fractal dimension are used. A linear SVM is used to perform the classification, which is tested by means of 10-fold cross-validation. The performance is evaluated using 300 images achieving an AUC of 0.93 with maximum accuracy of 88%. PMID:25698545

  5. Annotation of protein residues based on a literature analysis: cross-validation against UniProtKb

    PubMed Central

    Nagel, Kevin; Jimeno-Yepes, Antonio; Rebholz-Schuhmann, Dietrich

    2009-01-01

    Background A protein annotation database, such as the Universal Protein Resource knowledge base (UniProtKb), is a valuable resource for the validation and interpretation of predicted 3D structure patterns in proteins. Existing studies have focussed on point mutation extraction methods from biomedical literature which can be used to support the time consuming work of manual database curation. However, these methods were limited to point mutation extraction and do not extract features for the annotation of proteins at the residue level. Results This work introduces a system that identifies protein residues in MEDLINE abstracts and annotates them with features extracted from the context written in the surrounding text. MEDLINE abstract texts have been processed to identify protein mentions in combination with taxonomic species and protein residues (F1-measure 0.52). The identified protein-species-residue triplets have been validated and benchmarked against reference data resources (UniProtKb, average F1-measure of 0.54). Then, contextual features were extracted through shallow and deep parsing and the features have been classified into predefined categories (F1-measure ranges from 0.15 to 0.67). Furthermore, the feature sets have been aligned with annotation types in UniProtKb to assess the relevance of the annotations for ongoing curation projects. Altogether, the annotations have been assessed automatically and manually against reference data resources. Conclusion This work proposes a solution for the automatic extraction of functional annotation for protein residues from biomedical articles. The presented approach is an extension to other existing systems in that a wider range of residue entities are considered and that features of residues are extracted as annotations. PMID:19758468

  6. Improved GRACE regional mass balance estimates of the Greenland ice sheet cross-validated with the input-output method

    NASA Astrophysics Data System (ADS)

    Xu, Zheng; Schrama, Ernst J. O.; van der Wal, Wouter; van den Broeke, Michiel; Enderlin, Ellyn M.

    2016-04-01

    In this study, we use satellite gravimetry data from the Gravity Recovery and Climate Experiment (GRACE) to estimate regional mass change of the Greenland ice sheet (GrIS) and neighboring glaciated regions using a least squares inversion approach. We also consider results from the input-output method (IOM). The IOM quantifies the difference between the mass input and output of the GrIS by studying the surface mass balance (SMB) and the ice discharge (D). We use the Regional Atmospheric Climate Model version 2.3 (RACMO2.3) to model the SMB and derive the ice discharge from 12 years of high-precision ice velocity and thickness surveys. We use a simulation model to quantify and correct for GRACE approximation errors in mass change between different subregions of the GrIS, and investigate the reliability of pre-1990s ice discharge estimates, which are based on the modeled runoff. We find that the difference between the IOM and our improved GRACE mass change estimates is reduced in terms of the long-term mass change when using a reference discharge derived from runoff estimates in several subareas. In most regions our GRACE and IOM solutions are consistent with other studies, but differences remain in the northwestern GrIS. We validate the GRACE mass balance in that region by considering several different GIA models and mass change estimates derived from data obtained by the Ice, Cloud and land Elevation Satellite (ICESat). We conclude that the approximated mass balance between GRACE and IOM is consistent in most GrIS regions. The difference in the northwest is likely due to underestimated uncertainties in the IOM solutions.

  7. Geostatistical validation and cross-validation of magnetometric measurements of soil pollution with Potentially Toxic Elements in problematic areas

    NASA Astrophysics Data System (ADS)

    Fabijańczyk, Piotr; Zawadzki, Jarosław

    2016-04-01

    Field magnetometry is fast method that was previously effectively used to assess the potential soil pollution. One of the most popular devices that are used to measure the soil magnetic susceptibility on the soil surface is a MS2D Bartington. Single reading using MS2D device of soil magnetic susceptibility is low time-consuming but often characterized by considerable errors related to the instrument or environmental and lithogenic factors. In this connection, measured values of soil magnetic susceptibility have to be usually validated using more precise, but also much more expensive, chemical measurements. The goal of this study was to analyze validation methods of magnetometric measurements using chemical analyses of a concentration of elements in soil. Additionally, validation of surface measurements of soil magnetic susceptibility was performed using selected parameters of a distribution of magnetic susceptibility in a soil profile. Validation was performed using selected geostatistical measures of cross-correlation. The geostatistical approach was compared with validation performed using the classic statistics. Measurements were performed at selected areas located in the Upper Silesian Industrial Area in Poland, and in the selected parts of Norway. In these areas soil magnetic susceptibility was measured on the soil surface using a MS2D Bartington device and in the soil profile using MS2C Bartington device. Additionally, soil samples were taken in order to perform chemical measurements. Acknowledgment The research leading to these results has received funding from the Polish-Norwegian Research Programme operated by the National Centre for Research and Development under the Norwegian Financial Mechanism 2009-2014 in the frame of Project IMPACT - Contract No Pol-Nor/199338/45/2013.

  8. A Cross-Validation Approach to Approximate Basis Function Selection of the Stall Flutter Response of a Rectangular Wing in a Wind Tunnel

    NASA Technical Reports Server (NTRS)

    Kukreja, Sunil L.; Vio, Gareth A.; Andrianne, Thomas; azak, Norizham Abudl; Dimitriadis, Grigorios

    2012-01-01

    The stall flutter response of a rectangular wing in a low speed wind tunnel is modelled using a nonlinear difference equation description. Static and dynamic tests are used to select a suitable model structure and basis function. Bifurcation criteria such as the Hopf condition and vibration amplitude variation with airspeed were used to ensure the model was representative of experimentally measured stall flutter phenomena. Dynamic test data were used to estimate model parameters and estimate an approximate basis function.

  9. Cross validation of gas chromatography-flame photometric detection and gas chromatography-mass spectrometry methods for measuring dialkylphosphate metabolites of organophosphate pesticides in human urine.

    PubMed

    Prapamontol, Tippawan; Sutan, Kunrunya; Laoyang, Sompong; Hongsibsong, Surat; Lee, Grace; Yano, Yukiko; Hunter, Ronald Elton; Ryan, P Barry; Barr, Dana Boyd; Panuwet, Parinya

    2014-01-01

    We report two analytical methods for the measurement of dialkylphosphate (DAP) metabolites of organophosphate pesticides in human urine. These methods were independently developed/modified and implemented in two separate laboratories and cross validated. The aim was to develop simple, cost effective, and reliable methods that could use available resources and sample matrices in Thailand and the United States. While several methods already exist, we found that direct application of these methods required modification of sample preparation and chromatographic conditions to render accurate, reliable data. The problems encountered with existing methods were attributable to urinary matrix interferences, and differences in the pH of urine samples and reagents used during the extraction and derivatization processes. Thus, we provide information on key parameters that require attention during method modification and execution that affect the ruggedness of the methods. The methods presented here employ gas chromatography (GC) coupled with either flame photometric detection (FPD) or electron impact ionization-mass spectrometry (EI-MS) with isotopic dilution quantification. The limits of detection were reported from 0.10ng/mL urine to 2.5ng/mL urine (for GC-FPD), while the limits of quantification were reported from 0.25ng/mL urine to 2.5ng/mL urine (for GC-MS), for all six common DAP metabolites (i.e., dimethylphosphate, dimethylthiophosphate, dimethyldithiophosphate, diethylphosphate, diethylthiophosphate, and diethyldithiophosphate). Each method showed a relative recovery range of 94-119% (for GC-FPD) and 92-103% (for GC-MS), and relative standard deviations (RSD) of less than 20%. Cross-validation was performed on the same set of urine samples (n=46) collected from pregnant women residing in the agricultural areas of northern Thailand. The results from split sample analysis from both laboratories agreed well for each metabolite, suggesting that each method can produce

  10. A Novel Local Learning based Approach With Application to Breast Cancer Diagnosis

    SciTech Connect

    Xu, Songhua; Tourassi, Georgia

    2012-01-01

    The purpose of this study is to develop and evaluate a novel local learning-based approach for computer-assisted diagnosis of breast cancer. Our new local learning based algorithm using the linear logistic regression method as its base learner is described. Overall, our algorithm will perform its stochastic searching process until the total allowed computing time is used up by our random walk process in identifying the most suitable population subdivision scheme and their corresponding individual base learners. The proposed local learning-based approach was applied for the prediction of breast cancer given 11 mammographic and clinical findings reported by physicians using the BI-RADS lexicon. Our database consisted of 850 patients with biopsy confirmed diagnosis (290 malignant and 560 benign). We also compared the performance of our method with a collection of publicly available state-of-the-art machine learning methods. Predictive performance for all classifiers was evaluated using 10-fold cross validation and Receiver Operating Characteristics (ROC) analysis. Figure 1 reports the performance of 54 machine learning methods implemented in the machine learning toolkit Weka (version 3.0). We introduced a novel local learning-based classifier and compared it with an extensive list of other classifiers for the problem of breast cancer diagnosis. Our experiments show that the algorithm superior prediction performance outperforming a wide range of other well established machine learning techniques. Our conclusion complements the existing understanding in the machine learning field that local learning may capture complicated, non-linear relationships exhibited by real-world datasets.

  11. An improved approach for predicting drug-target interaction: proteochemometrics to molecular docking.

    PubMed

    Shaikh, Naeem; Sharma, Mahesh; Garg, Prabha

    2016-02-23

    Proteochemometric (PCM) methods, which use descriptors of both the interacting species, i.e. drug and the target, are being successfully employed for the prediction of drug-target interactions (DTI). However, unavailability of non-interacting dataset and determining the applicability domain (AD) of model are a main concern in PCM modeling. In the present study, traditional PCM modeling was improved by devising novel methodologies for reliable negative dataset generation and fingerprint based AD analysis. In addition, various types of descriptors and classifiers were evaluated for their performance. The Random Forest and Support Vector Machine models outperformed the other classifiers (accuracies >98% and >89% for 10-fold cross validation and external validation, respectively). The type of protein descriptors had negligible effect on the developed models, encouraging the use of sequence-based descriptors over the structure-based descriptors. To establish the practical utility of built models, targets were predicted for approved anticancer drugs of natural origin. The molecular recognition interactions between the predicted drug-target pair were quantified with the help of a reverse molecular docking approach. The majority of predicted targets are known for anticancer therapy. These results thus correlate well with anticancer potential of the selected drugs. Interestingly, out of all predicted DTIs, thirty were found to be reported in the ChEMBL database, further validating the adopted methodology. The outcome of this study suggests that the proposed approach, involving use of the improved PCM methodology and molecular docking, can be successfully employed to elucidate the intricate mode of action for drug molecules as well as repositioning them for new therapeutic applications. PMID:26822863

  12. FDDS: A Cross Validation Study.

    ERIC Educational Resources Information Center

    Sawyer, Judy Parsons

    The Family Drawing Depression Scale (FDDS) was created by Wright and McIntyre to provide a clear and reliable scoring method for the Kinetic Family Drawing as a procedure for detecting depression. A study was conducted to confirm the value of the FDDS as a systematic tool for interpreting family drawings with populations of depressed individuals.…

  13. Cross-validation of IFN-γ Elispot assay for measuring alloreactive memory/effector T cell responses in renal transplant recipients.

    PubMed

    Bestard, O; Crespo, E; Stein, M; Lúcia, M; Roelen, D L; de Vaal, Y J; Hernandez-Fuentes, M P; Chatenoud, L; Wood, K J; Claas, F H; Cruzado, J M; Grinyó, J M; Volk, H D; Reinke, P

    2013-07-01

    Assessment of donor-specific alloreactive memory/effector T cell responses using an IFN-γ Elispot assay has been suggested to be a novel immune-monitoring tool for evaluating the cellular immune risk in renal transplantation. Here, we report the cross-validation data of the IFN-γ Elispot assay performed within different European laboratories taking part of the EU RISET consortium. For this purpose, development of a standard operating procedure (SOP), comparisons of lectures of IFN-γ plates assessing intra- and interlaboratory assay variability of allogeneic or peptide stimuli in both healthy and kidney transplant individuals have been the main objectives. We show that the use of a same SOP and count-settings of the Elispot bioreader allow low coefficient variation between laboratories. Frozen and shipped samples display slightly lower detectable IFN-γ frequencies than fresh samples. Importantly, a close correlation between different laboratories is obtained when measuring high frequencies of antigen-specific primed/memory T cell alloresponses. Interestingly, significant high donor-specific alloreactive T cell responses can be similarly detected among different laboratories in kidney transplant patients displaying histological patterns of acute T cell mediated rejection. In conclusion, assessment of circulating alloreactive memory/effector T cells using an INF-γ Elispot assay can be accurately achieved using the same SOP, Elispot bioreader and experienced technicians in kidney transplantation. PMID:23763435

  14. Improving the accuracy of NMR structures of RNA by means of conformational database potentials of mean force as assessed by complete dipolar coupling cross-validation.

    PubMed

    Clore, G Marius; Kuszewski, John

    2003-02-12

    The description of the nonbonded contact terms used in simulated annealing refinement can have a major impact on nucleic acid structures generated from NMR data. Using complete dipolar coupling cross-validation, we demonstrate that substantial improvements in coordinate accuracy of NMR structures of RNA can be obtained by making use of two conformational database potentials of mean force: a nucleic acid torsion angle database potential consisting of various multidimensional torsion angle correlations; and an RNA specific base-base positioning potential that provides a simple geometric, statistically based, description of sequential and nonsequential base-base interactions. The former is based on 416 nucleic acid crystal structures solved at a resolution of

  15. Sediment transport patterns in the San Francisco Bay Coastal System from cross-validation of bedform asymmetry and modeled residual flux

    USGS Publications Warehouse

    Barnard, Patrick L.; Erikson, Li H.; Elias, Edwin P.L.; Dartnell, Peter

    2013-01-01

    The morphology of ~ 45,000 bedforms from 13 multibeam bathymetry surveys was used as a proxy for identifying net bedload sediment transport directions and pathways throughout the San Francisco Bay estuary and adjacent outer coast. The spatially-averaged shape asymmetry of the bedforms reveals distinct pathways of ebb and flood transport. Additionally, the region-wide, ebb-oriented asymmetry of 5% suggests net seaward-directed transport within the estuarine-coastal system, with significant seaward asymmetry at the mouth of San Francisco Bay (11%), through the northern reaches of the Bay (7-8%), and among the largest bedforms (21% for λ > 50 m). This general indication for the net transport of sand to the open coast strongly suggests that anthropogenic removal of sediment from the estuary, particularly along clearly defined seaward transport pathways, will limit the supply of sand to chronically eroding, open-coast beaches. The bedform asymmetry measurements significantly agree (up to ~ 76%) with modeled annual residual transport directions derived from a hydrodynamically-calibrated numerical model, and the orientation of adjacent, flow-sculpted seafloor features such as mega-flute structures, providing a comprehensive validation of the technique. The methods described in this paper to determine well-defined, cross-validated sediment transport pathways can be applied to estuarine-coastal systems globally where bedforms are present. The results can inform and improve regional sediment management practices to more efficiently utilize often limited sediment resources and mitigate current and future sediment supply-related impacts.

  16. Sediment transport patterns in the San Francisco Bay Coastal System from cross-validation of bedform asymmetry and modeled residual flux

    USGS Publications Warehouse

    Barnard, Patrick L.; Erikson, Li H.; Elias, Edwin P.L.; Dartnell, Peter

    2013-01-01

    The morphology of ~ 45,000 bedforms from 13 multibeam bathymetry surveys was used as a proxy for identifying net bedload sediment transport directions and pathways throughout the San Francisco Bay estuary and adjacent outer coast. The spatially-averaged shape asymmetry of the bedforms reveals distinct pathways of ebb and flood transport. Additionally, the region-wide, ebb-oriented asymmetry of 5% suggests net seaward-directed transport within the estuarine-coastal system, with significant seaward asymmetry at the mouth of San Francisco Bay (11%), through the northern reaches of the Bay (7–8%), and among the largest bedforms (21% for λ > 50 m). This general indication for the net transport of sand to the open coast strongly suggests that anthropogenic removal of sediment from the estuary, particularly along clearly defined seaward transport pathways, will limit the supply of sand to chronically eroding, open-coast beaches. The bedform asymmetry measurements significantly agree (up to ~ 76%) with modeled annual residual transport directions derived from a hydrodynamically-calibrated numerical model, and the orientation of adjacent, flow-sculpted seafloor features such as mega-flute structures, providing a comprehensive validation of the technique. The methods described in this paper to determine well-defined, cross-validated sediment transport pathways can be applied to estuarine-coastal systems globally where bedforms are present. The results can inform and improve regional sediment management practices to more efficiently utilize often limited sediment resources and mitigate current and future sediment supply-related impacts.

  17. Revealing latent value of clinically acquired CTs of traumatic brain injury through multi-atlas segmentation in a retrospective study of 1,003 with external cross-validation

    NASA Astrophysics Data System (ADS)

    Plassard, Andrew J.; Kelly, Patrick D.; Asman, Andrew J.; Kang, Hakmook; Patel, Mayur B.; Landman, Bennett A.

    2015-03-01

    Medical imaging plays a key role in guiding treatment of traumatic brain injury (TBI) and for diagnosing intracranial hemorrhage; most commonly rapid computed tomography (CT) imaging is performed. Outcomes for patients with TBI are variable and difficult to predict upon hospital admission. Quantitative outcome scales (e.g., the Marshall classification) have been proposed to grade TBI severity on CT, but such measures have had relatively low value in staging patients by prognosis. Herein, we examine a cohort of 1,003 subjects admitted for TBI and imaged clinically to identify potential prognostic metrics using a "big data" paradigm. For all patients, a brain scan was segmented with multi-atlas labeling, and intensity/volume/texture features were computed in a localized manner. In a 10-fold crossvalidation approach, the explanatory value of the image-derived features is assessed for length of hospital stay (days), discharge disposition (five point scale from death to return home), and the Rancho Los Amigos functional outcome score (Rancho Score). Image-derived features increased the predictive R2 to 0.38 (from 0.18) for length of stay, to 0.51 (from 0.4) for discharge disposition, and to 0.31 (from 0.16) for Rancho Score (over models consisting only of non-imaging admission metrics, but including positive/negative radiological CT findings). This study demonstrates that high volume retrospective analysis of clinical imaging data can reveal imaging signatures with prognostic value. These targets are suited for follow-up validation and represent targets for future feature selection efforts. Moreover, the increase in prognostic value would improve staging for intervention assessment and provide more reliable guidance for patients.

  18. Methane cross-validation between three Fourier transform spectrometers: SCISAT ACE-FTS, GOSAT TANSO-FTS, and ground-based FTS measurements in the Canadian high Arctic

    NASA Astrophysics Data System (ADS)

    Holl, Gerrit; Walker, Kaley A.; Conway, Stephanie; Saitoh, Naoko; Boone, Chris D.; Strong, Kimberly; Drummond, James R.

    2016-05-01

    We present cross-validation of remote sensing measurements of methane profiles in the Canadian high Arctic. Accurate and precise measurements of methane are essential to understand quantitatively its role in the climate system and in global change. Here, we show a cross-validation between three data sets: two from spaceborne instruments and one from a ground-based instrument. All are Fourier transform spectrometers (FTSs). We consider the Canadian SCISAT Atmospheric Chemistry Experiment (ACE)-FTS, a solar occultation infrared spectrometer operating since 2004, and the thermal infrared band of the Japanese Greenhouse Gases Observing Satellite (GOSAT) Thermal And Near infrared Sensor for carbon Observation (TANSO)-FTS, a nadir/off-nadir scanning FTS instrument operating at solar and terrestrial infrared wavelengths, since 2009. The ground-based instrument is a Bruker 125HR Fourier transform infrared (FTIR) spectrometer, measuring mid-infrared solar absorption spectra at the Polar Environment Atmospheric Research Laboratory (PEARL) Ridge Laboratory at Eureka, Nunavut (80° N, 86° W) since 2006. For each pair of instruments, measurements are collocated within 500 km and 24 h. An additional collocation criterion based on potential vorticity values was found not to significantly affect differences between measurements. Profiles are regridded to a common vertical grid for each comparison set. To account for differing vertical resolutions, ACE-FTS measurements are smoothed to the resolution of either PEARL-FTS or TANSO-FTS, and PEARL-FTS measurements are smoothed to the TANSO-FTS resolution. Differences for each pair are examined in terms of profile and partial columns. During the period considered, the number of collocations for each pair is large enough to obtain a good sample size (from several hundred to tens of thousands depending on pair and configuration). Considering full profiles, the degrees of freedom for signal (DOFS) are between 0.2 and 0.7 for TANSO-FTS and

  19. Methane cross-validation between three Fourier Transform Spectrometers: SCISAT ACE-FTS, GOSAT TANSO-FTS, and ground-based FTS measurements in the Canadian high Arctic

    NASA Astrophysics Data System (ADS)

    Holl, G.; Walker, K. A.; Conway, S.; Saitoh, N.; Boone, C. D.; Strong, K.; Drummond, J. R.

    2015-12-01

    We present cross-validation of remote sensing measurements of methane profiles in the Canadian high Arctic. Accurate and precise measurements of methane are essential to understand quantitatively its role in the climate system and in global change. Here, we show a cross-validation between three datasets: two from spaceborne instruments and one from a ground-based instrument. All are Fourier Transform Spectrometers (FTSs). We consider the Canadian SCISAT Atmospheric Chemistry Experiment (ACE)-FTS, a solar occultation infrared spectrometer operating since 2004, and the thermal infrared band of the Japanese Greenhouse Gases Observing Satellite (GOSAT) Thermal And Near infrared Sensor for carbon Observation (TANSO)-FTS, a nadir/off-nadir scanning FTS instrument operating at solar and terrestrial infrared wavelengths, since 2009. The ground-based instrument is a Bruker 125HR Fourier Transform Infrared (FTIR) spectrometer, measuring mid-infrared solar absorption spectra at the Polar Environment Atmospheric Research Laboratory (PEARL) Ridge Lab at Eureka, Nunavut (80° N, 86° W) since 2006. For each pair of instruments, measurements are collocated within 500 km and 24 h. An additional criterion based on potential vorticity values was found not to significantly affect differences between measurements. Profiles are regridded to a common vertical grid for each comparison set. To account for differing vertical resolutions, ACE-FTS measurements are smoothed to the resolution of either PEARL-FTS or TANSO-FTS, and PEARL-FTS measurements are smoothed to the TANSO-FTS resolution. Differences for each pair are examined in terms of profile and partial columns. During the period considered, the number of collocations for each pair is large enough to obtain a good sample size (from several hundred to tens of thousands depending on pair and configuration). Considering full profiles, the degrees of freedom for signal (DOFS) are between 0.2 and 0.7 for TANSO-FTS and between 1.5 and 3

  20. Using the concept of Chou's pseudo amino acid composition to predict protein solubility: an approach with entropies in information theory.

    PubMed

    Xiaohui, Niu; Nana, Li; Jingbo, Xia; Dingyan, Chen; Yuehua, Peng; Yang, Xiao; Weiquan, Wei; Dongming, Wang; Zengzhen, Wang

    2013-09-01

    Protein solubility plays a major role and has strong implication in the proteomics. Predicting the propensity of a protein to be soluble or to form inclusion body is a fundamental and not fairly resolved problem. In order to predict the protein solubility, almost 10,000 protein sequences were downloaded from NCBI. Then the sequences were eliminated for the high homologous similarity by CD-HIT. Thus, there were 5692 sequences remained. Based on protein sequences, amino acid and dipeptide compositions were generally extracted to predict protein solubility. In this study, the entropy in information theory was introduced as another predictive factor in the model. Experiments involving nine different feature vector combinations, including the above-mentioned three kinds of factors, were conducted with support vector machines (SVMs) as prediction engine. Each combination was evaluated by re-substitution test and 10-fold cross-validation test. According to the evaluation results, the accuracies and Matthew's Correlation Coefficient (MCC) values were boosted by the introduction of the entropy. The best combination was the one with amino acid, dipeptide compositions and their entropies. Its accuracy reached 90.34% and Matthew's Correlation Coefficient (MCC) value was 0.7494 in re-substitution test, while 88.12% and 0.7945 respectively for 10-fold cross-validation. In conclusion, the introduction of the entropy significantly improved the performance of the predictive method. PMID:23524162

  1. Determination of snow avalanche return periods using a tree-ring based reconstruction in the French Alps: cross validation with the predictions of a statistical-dynamical model

    NASA Astrophysics Data System (ADS)

    Schläppy, Romain; Eckert, Nicolas; Jomelli, Vincent; Grancher, Delphine; Brunstein, Daniel; Stoffel, Markus; Naaim, Mohamed

    2013-04-01

    rare events, i.e. to the tail of the local runout distance distribution. Furthermore, a good agreement exists with the statistical-numerical model's prediction, i.e. a 10-40 m difference for return periods ranging between 10 and 300 years, which is rather small with regards to the uncertainty levels to be considered in avalanche probabilistic modeling and dendrochronological reconstructions. It is important to note that such a cross validation on independent extreme predictions has never been undertaken before. It suggest that i) dendrochronological reconstruction can provide valuable information for anticipating future extreme avalanche events in the context of risk management, and, in turn, that ii) the statistical-numerical model, while properly calibrated, can be used with reasonable confidence to refine these predictions, with for instance evaluation of pressure and flow depth distributions at each position of the runout zone. A strong sensitivity to the determination of local avalanche and dendrological record frequencies is however highlighted, indicating that this step is an essential step for an accurate probabilistic characterization of large-extent events.

  2. Cross-validation of a mass spectrometric-based method for the therapeutic drug monitoring of irinotecan: implementation of matrix-assisted laser desorption/ionization mass spectrometry in pharmacokinetic measurements.

    PubMed

    Calandra, Eleonora; Posocco, Bianca; Crotti, Sara; Marangon, Elena; Giodini, Luciana; Nitti, Donato; Toffoli, Giuseppe; Traldi, Pietro; Agostini, Marco

    2016-07-01

    Irinotecan is a widely used antineoplastic drug, mostly employed for the treatment of colorectal cancer. This drug is a feasible candidate for therapeutic drug monitoring due to the presence of a wide inter-individual variability in the pharmacokinetic and pharmacodynamic parameters. In order to determine the drug concentration during the administration protocol, we developed a quantitative MALDI-MS method using CHCA as MALDI matrix. Here, we demonstrate that MALDI-TOF can be applied in a routine setting for therapeutic drug monitoring in humans offering quick and accurate results. To reach this aim, we cross validated, according to FDA and EMA guidelines, the MALDI-TOF method in comparison with a standard LC-MS/MS method, applying it for the quantification of 108 patients' plasma samples from a clinical trial. Standard curves for irinotecan were linear (R (2) ≥ 0.9842) over the concentration ranges between 300 and 10,000 ng/mL and showed good back-calculated accuracy and precision. Intra- and inter-day precision and accuracy, determined on three quality control levels were always <12.8 % and between 90.1 and 106.9 %, respectively. The cross-validation procedure showed a good reproducibility between the two methods, the percentage differences within 20 % in more than 70 % of the total amount of clinical samples analysed. PMID:27235158

  3. Methane Cross-Validation Between Spaceborne Solar Occultation Observations from ACE-FTS, Spaceborne Nadir Sounding from Gosat, and Ground-Based Solar Absorption Measurements, at a High Arctic Site.

    NASA Astrophysics Data System (ADS)

    Holl, G.; Walker, K. A.; Conway, S. A.; Saitoh, N.; Boone, C. D.; Strong, K.; Drummond, J. R.

    2014-12-01

    We present cross-validation of remote sensing observations of methane profiles in the Canadian High Arctic. Methane is the third most important greenhouse gas on Earth, and second only to carbon dioxide in its contribution to anthropogenic global warming. Accurate and precise observations of methane are essential to understand quantitatively its role in the climate system and in global change. The Arctic is a particular region of concern, as melting permafrost and disappearing sea ice might lead to accelerated release of methane into the atmosphere. Global observations require spaceborne instruments, in particular in the Arctic, where surface measurements are sparse and expensive to perform. Satellite-based remote sensing is an underconstrained problem, and specific validation under Arctic circumstances is required. Here, we show a cross-validation between two spaceborne instruments and ground-based measurements, all Fourier Transform Spectrometers (FTS). We consider the Canadian SCISAT ACE-FTS, a solar occultation spectrometer operating since 2004, and the Japanese GOSAT TANSO-FTS, a nadir-pointing FTS operating at solar and terrestrial infrared wavelengths, since 2009. The ground-based instrument is a Bruker Fourier Transform Infrared (FTIR) spectrometer, measuring mid-infrared solar absorption spectra at the Polar Environmental and Atmospheric Research Laboratory (PEARL) at Eureka, Nunavut (80°N, 86°W) since 2006. Measurements are collocated considering temporal, spatial, and geophysical criteria and regridded to a common vertical grid. We perform smoothing on the higher-resolution instrument results to account for different vertical resolutions. Then, profiles of differences for each pair of instruments are examined. Any bias between instruments, or any accuracy that is worse than expected, needs to be understood prior to using the data. The results of the study will serve as a guideline on how to use the vertically resolved methane products from ACE and

  4. A widespread distribution of genomic CeMyoD binding sites revealed and cross validated by ChIP-Chip and ChIP-Seq techniques.

    PubMed

    Lei, Haiyan; Fukushige, Tetsunari; Niu, Wei; Sarov, Mihail; Reinke, Valerie; Krause, Michael

    2010-01-01

    Identifying transcription factor binding sites genome-wide using chromatin immunoprecipitation (ChIP)-based technology is becoming an increasingly important tool in addressing developmental questions. However, technical problems associated with factor abundance and suitable ChIP reagents are common obstacles to these studies in many biological systems. We have used two completely different, widely applicable methods to determine by ChIP the genome-wide binding sites of the master myogenic regulatory transcription factor HLH-1 (CeMyoD) in C. elegans embryos. The two approaches, ChIP-seq and ChIP-chip, yield strongly overlapping results revealing that HLH-1 preferentially binds to promoter regions of genes enriched for E-box sequences (CANNTG), known binding sites for this well-studied class of transcription factors. HLH-1 binding sites were enriched upstream of genes known to be expressed in muscle, consistent with its role as a direct transcriptional regulator. HLH-1 binding was also detected at numerous sites unassociated with muscle gene expression, as has been previously described for its mouse homolog MyoD. These binding sites may reflect several additional functions for HLH-1, including its interactions with one or more co-factors to activate (or repress) gene expression or a role in chromatin organization distinct from direct transcriptional regulation of target genes. Our results also provide a comparison of ChIP methodologies that can overcome limitations commonly encountered in these types of studies while highlighting the complications of assigning in vivo functions to identified target sites. PMID:21209968

  5. A Widespread Distribution of Genomic CeMyoD Binding Sites Revealed and Cross Validated by ChIP-Chip and ChIP-Seq Techniques

    PubMed Central

    Lei, Haiyan; Fukushige, Tetsunari; Niu, Wei; Sarov, Mihail; Reinke, Valerie; Krause, Michael

    2010-01-01

    Identifying transcription factor binding sites genome-wide using chromatin immunoprecipitation (ChIP)-based technology is becoming an increasingly important tool in addressing developmental questions. However, technical problems associated with factor abundance and suitable ChIP reagents are common obstacles to these studies in many biological systems. We have used two completely different, widely applicable methods to determine by ChIP the genome-wide binding sites of the master myogenic regulatory transcription factor HLH-1 (CeMyoD) in C. elegans embryos. The two approaches, ChIP-seq and ChIP-chip, yield strongly overlapping results revealing that HLH-1 preferentially binds to promoter regions of genes enriched for E-box sequences (CANNTG), known binding sites for this well-studied class of transcription factors. HLH-1 binding sites were enriched upstream of genes known to be expressed in muscle, consistent with its role as a direct transcriptional regulator. HLH-1 binding was also detected at numerous sites unassociated with muscle gene expression, as has been previously described for its mouse homolog MyoD. These binding sites may reflect several additional functions for HLH-1, including its interactions with one or more co-factors to activate (or repress) gene expression or a role in chromatin organization distinct from direct transcriptional regulation of target genes. Our results also provide a comparison of ChIP methodologies that can overcome limitations commonly encountered in these types of studies while highlighting the complications of assigning in vivo functions to identified target sites. PMID:21209968

  6. Cross-Validation of Suspended Sediment Concentrations Derived from Satellite Imagery and Numerical Modeling of the 1997 New Year's Flood on the Feather River, CA

    NASA Astrophysics Data System (ADS)

    Kilham, N. E.

    2009-12-01

    Image analysis was applied to assess suspended sediment concentrations (SSC) predicted by a numerical model of 2D hydraulics and sediment transport (Telemac-2D), coupled to a solver for the advection-diffusion equation (SISYPHE) and representing 18 days of flooding over 70 kilometers of the lower Feather-Yuba Rivers. Sisyphe treats the suspended load as a tracer, removed from the flow if the bed shear velocity, u* is lower than an empirically derived threshold (ud* = 7.8E-3 m s-1). Agreement between model (D50 = 0.03 mm) and image-derived SSC (mg L-1) suggests that image interpretation could prove to be a viable approach for verifying spatially-distributed models of floodplain sediment transport if imagery is acquired for a particular flood and at a sufficient spatial and radiometric resolution. However, remotely derived SSC represents the integrated concentration of suspended sediment at the water surface. Hence, comparing SSC magnitudes derived from imagery and numerical modeling requires that a relationship is first established between the total suspended load and the portion of this load suspended within the optical range of the sensor (e.g., Aalto, 1995). Using the optical depth (0.5 m) determined from radiative transfer modeling, surface SSC measured from a 1/14/97 Landsat TM5 image (30 m) were converted to depth-integrated SSC with the Rouse (1937) equation. Surface concentrations were derived using a look-up table for the sensor to convert endmember fractions obtained from a spectral mixture analysis of the image. A two-endmember model (2.0 and 203 mg L-1) was used, with synthetic endmembers derived from optical and radiative transfer modeling and inversion of field spectra collected from the Sacramento and Feather Rivers and matched to measured SSC values. Remotely sensed SSC patterns were then compared to the Telemac results for the same day and time. Modeled concentrations are a function of both the rating curve boundary conditions, and the transport and

  7. In silico prediction of toxicity of non-congeneric industrial chemicals using ensemble learning based modeling approaches

    SciTech Connect

    Singh, Kunwar P. Gupta, Shikha

    2014-03-15

    Ensemble learning approach based decision treeboost (DTB) and decision tree forest (DTF) models are introduced in order to establish quantitative structure–toxicity relationship (QSTR) for the prediction of toxicity of 1450 diverse chemicals. Eight non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals was evaluated using Tanimoto similarity index. Stochastic gradient boosting and bagging algorithms supplemented DTB and DTF models were constructed for classification and function optimization problems using the toxicity end-point in T. pyriformis. Special attention was drawn to prediction ability and robustness of the models, investigated both in external and 10-fold cross validation processes. In complete data, optimal DTB and DTF models rendered accuracies of 98.90%, 98.83% in two-category and 98.14%, 98.14% in four-category toxicity classifications. Both the models further yielded classification accuracies of 100% in external toxicity data of T. pyriformis. The constructed regression models (DTB and DTF) using five descriptors yielded correlation coefficients (R{sup 2}) of 0.945, 0.944 between the measured and predicted toxicities with mean squared errors (MSEs) of 0.059, and 0.064 in complete T. pyriformis data. The T. pyriformis regression models (DTB and DTF) applied to the external toxicity data sets yielded R{sup 2} and MSE values of 0.637, 0.655; 0.534, 0.507 (marine bacteria) and 0.741, 0.691; 0.155, 0.173 (algae). The results suggest for wide applicability of the inter-species models in predicting toxicity of new chemicals for regulatory purposes. These approaches provide useful strategy and robust tools in the screening of ecotoxicological risk or environmental hazard potential of chemicals. - Graphical abstract: Importance of input variables in DTB and DTF classification models for (a) two-category, and (b) four-category toxicity intervals in T. pyriformis data. Generalization and predictive abilities of the

  8. Cross-validation and evaluation of the performance of methods for the elemental analysis of forensic glass by μ-XRF, ICP-MS, and LA-ICP-MS.

    PubMed

    Trejos, Tatiana; Koons, Robert; Becker, Stefan; Berman, Ted; Buscaglia, JoAnn; Duecking, Marc; Eckert-Lumsdon, Tiffany; Ernst, Troy; Hanlon, Christopher; Heydon, Alex; Mooney, Kim; Nelson, Randall; Olsson, Kristine; Palenik, Christopher; Pollock, Edward Chip; Rudell, David; Ryland, Scott; Tarifa, Anamary; Valadez, Melissa; Weis, Peter; Almirall, Jose

    2013-06-01

    Elemental analysis of glass was conducted by 16 forensic science laboratories, providing a direct comparison between three analytical methods [micro-x-ray fluorescence spectroscopy (μ-XRF), solution analysis using inductively coupled plasma mass spectrometry (ICP-MS), and laser ablation inductively coupled plasma mass spectrometry]. Interlaboratory studies using glass standard reference materials and other glass samples were designed to (a) evaluate the analytical performance between different laboratories using the same method, (b) evaluate the analytical performance of the different methods, (c) evaluate the capabilities of the methods to correctly associate glass that originated from the same source and to correctly discriminate glass samples that do not share the same source, and (d) standardize the methods of analysis and interpretation of results. Reference materials NIST 612, NIST 1831, FGS 1, and FGS 2 were employed to cross-validate these sensitive techniques and to optimize and standardize the analytical protocols. The resulting figures of merit for the ICP-MS methods include repeatability better than 5% RSD, reproducibility between laboratories better than 10% RSD, bias better than 10%, and limits of detection between 0.03 and 9 μg g(-1) for the majority of the elements monitored. The figures of merit for the μ-XRF methods include repeatability better than 11% RSD, reproducibility between laboratories after normalization of the data better than 16% RSD, and limits of detection between 5.8 and 7,400 μg g(-1). The results from this study also compare the analytical performance of different forensic science laboratories conducting elemental analysis of glass evidence fragments using the three analytical methods. PMID:23673570

  9. Prediction of Biofilm Inhibiting Peptides: An In silico Approach

    PubMed Central

    Gupta, Sudheer; Sharma, Ashok K.; Jaiswal, Shubham K.; Sharma, Vineet K.

    2016-01-01

    Approximately 75% of microbial infections found in humans are caused by microbial biofilms. These biofilms are resistant to host immune system and most of the currently available antibiotics. Small peptides are extensively studied for their role as anti-microbial peptides, however, only a limited studies have shown their potential as inhibitors of biofilm. Therefore, to develop a unique computational method aimed at the prediction of biofilm inhibiting peptides, the experimentally validated biofilm inhibiting peptides sequences were used to extract sequence based features and to identify unique sequence motifs. Biofilm inhibiting peptides were observed to be abundant in positively charged and aromatic amino acids, and also showed selective abundance of some dipeptides and sequence motifs. These individual sequence based features were utilized to construct Support Vector Machine-based prediction models and additionally by including sequence motifs information, the hybrid models were constructed. Using 10-fold cross validation, the hybrid model displayed the accuracy and Matthews Correlation Coefficient (MCC) of 97.83% and 0.87, respectively. On the validation dataset, the hybrid model showed the accuracy and MCC value of 97.19% and 0.84, respectively. The validated model and other tools developed for the prediction of biofilm inhibiting peptides are available freely as web server at http://metagenomics.iiserb.ac.in/biofin/ and http://metabiosys.iiserb.ac.in/biofin/. PMID:27379078

  10. Outlier detection and removal improves accuracy of machine learning approach to multispectral burn diagnostic imaging.

    PubMed

    Li, Weizhi; Mo, Weirong; Zhang, Xu; Squiers, John J; Lu, Yang; Sellke, Eric W; Fan, Wensheng; DiMaio, J Michael; Thatcher, Jeffrey E

    2015-12-01

    Multispectral imaging (MSI) was implemented to develop a burn tissue classification device to assist burn surgeons in planning and performing debridement surgery. To build a classification model via machine learning, training data accurately representing the burn tissue was needed, but assigning raw MSI data to appropriate tissue classes is prone to error. We hypothesized that removing outliers from the training dataset would improve classification accuracy. A swine burn model was developed to build an MSI training database and study an algorithm’s burn tissue classification abilities. After the ground-truth database was generated, we developed a multistage method based on Z -test and univariate analysis to detect and remove outliers from the training dataset. Using 10-fold cross validation, we compared the algorithm’s accuracy when trained with and without the presence of outliers. The outlier detection and removal method reduced the variance of the training data. Test accuracy was improved from 63% to 76%, matching the accuracy of clinical judgment of expert burn surgeons, the current gold standard in burn injury assessment. Given that there are few surgeons and facilities specializing in burn care, this technology may improve the standard of burn care for patients without access to specialized facilities. PMID:26305321

  11. A new approach: role of data mining in prediction of survival of burn patients.

    PubMed

    Patil, Bankat Madhavrao; Joshi, Ramesh C; Toshniwal, Durga; Biradar, Siddeshwar

    2011-12-01

    The prediction of burn patient survivability is a difficult problem to investigate till present times. In present study a prediction Model for patients with burns was built, and its capability to accurately predict the survivability was assessed. We have compared different data mining techniques to asses the performance of various algorithms based on the different measures used in the analysis of information pertaining to medical domain. Obtained results were evaluated for correctness with the help of registered medical practitioners. The dataset was collected from SRT (Swami Ramanand Tirth) Hospital in India, which is one of the Asia's largest rural hospitals. Dataset contains records of 180 patients mainly suffering from burn injuries collected during period from the year 2002 to 2006. Features contain patients' age, sex and percentage of burn received for eight different parts of the body. Prediction models have been developed through rigorous comparative study of important and relevant data mining classification techniques namely, navie bayes, decision tree, support vector machine and back propagation. Performance comparison was also carried out for measuring unbiased estimate of the prediction models using 10-fold cross-validation method. Using the analysis of obtained results, we show that Navie bayes is the best predictor with an accuracy of 97.78% on the holdout samples, further, both the decision tree and support vector machine (SVM) techniques demonstrated an accuracy of 96.12%, and back propagation technique resulted in achieving accuracy of 95%. PMID:20703764

  12. A PSO-Based Approach for Pathway Marker Identification From Gene Expression Data.

    PubMed

    Mandal, Monalisa; Mondal, Jyotirmay; Mukhopadhyay, Anirban

    2015-09-01

    In this article, a new and robust pathway activity inference scheme is proposed from gene expression data using Particle Swarm Optimization (PSO). From microarray gene expression data, the corresponding pathway information of the genes are collected from a public database. For identifying the pathway markers, the expression values of each pathway consisting of genes, termed as pathway activity, are summarized. To measure the goodness of a pathway activity vector, t-score is widely used in the existing literature. The weakness of existing techniques for inferring pathway activity is that they intend to consider all the member genes of a pathway. But in reality, all the member genes may not be significant to the corresponding pathway. Therefore, those genes, which are responsible in the corresponding pathway, should be included only. Motivated by this, in the proposed method, using PSO, important genes with respect to each pathway are identified. The objective is to maximize the average t-score. For the pathway activities inferred from different percentage of significant pathways, the average absolute t -scores are plotted. In addition, the top 50% pathway markers are evaluated using 10-fold cross validation and its performance is compared with that of other existing techniques. Biological relevance of the results is also studied. PMID:25935045

  13. Outlier detection and removal improves accuracy of machine learning approach to multispectral burn diagnostic imaging

    NASA Astrophysics Data System (ADS)

    Li, Weizhi; Mo, Weirong; Zhang, Xu; Squiers, John J.; Lu, Yang; Sellke, Eric W.; Fan, Wensheng; DiMaio, J. Michael; Thatcher, Jeffrey E.

    2015-12-01

    Multispectral imaging (MSI) was implemented to develop a burn tissue classification device to assist burn surgeons in planning and performing debridement surgery. To build a classification model via machine learning, training data accurately representing the burn tissue was needed, but assigning raw MSI data to appropriate tissue classes is prone to error. We hypothesized that removing outliers from the training dataset would improve classification accuracy. A swine burn model was developed to build an MSI training database and study an algorithm's burn tissue classification abilities. After the ground-truth database was generated, we developed a multistage method based on Z-test and univariate analysis to detect and remove outliers from the training dataset. Using 10-fold cross validation, we compared the algorithm's accuracy when trained with and without the presence of outliers. The outlier detection and removal method reduced the variance of the training data. Test accuracy was improved from 63% to 76%, matching the accuracy of clinical judgment of expert burn surgeons, the current gold standard in burn injury assessment. Given that there are few surgeons and facilities specializing in burn care, this technology may improve the standard of burn care for patients without access to specialized facilities.

  14. Sex estimation from the tarsal bones in a Portuguese sample: a machine learning approach.

    PubMed

    Navega, David; Vicente, Ricardo; Vieira, Duarte N; Ross, Ann H; Cunha, Eugénia

    2015-05-01

    Sex estimation is extremely important in the analysis of human remains as many of the subsequent biological parameters are sex specific (e.g., age at death, stature, and ancestry). When dealing with incomplete or fragmented remains, metric analysis of the tarsal bones of the feet has proven valuable. In this study, the utility of 18 width, length, and height tarsal measurements were assessed for sex-related variation in a Portuguese sample. A total of 300 males and females from the Coimbra Identified Skeletal Collection were used to develop sex prediction models based on statistical and machine learning algorithm such as discriminant function analysis, logistic regression, classification trees, and artificial neural networks. All models were evaluated using 10-fold cross-validation and an independent test sample composed of 60 males and females from the Identified Skeletal Collection of the 21st Century. Results showed that tarsal bone sex-related variation can be easily captured with a high degree of repeatability. A simple tree-based multivariate algorithm involving measurements from the calcaneus, talus, first and third cuneiforms, and cuboid resulted in 88.3% correct sex estimation both on training and independent test sets. Traditional statistical classifiers such as the discriminant function analysis were outperformed by machine learning techniques. Results obtained show that machine learning algorithm are an important tool the forensic practitioners should consider when developing new standards for sex estimation. PMID:25186617

  15. puffMarker: A Multi-Sensor Approach for Pinpointing the Timing of First Lapse in Smoking Cessation

    PubMed Central

    Saleheen, Nazir; Ali, Amin Ahsan; Hossain, Syed Monowar; Sarker, Hillol; Chatterjee, Soujanya; Marlin, Benjamin; Ertin, Emre; al’Absi, Mustafa; Kumar, Santosh

    2015-01-01

    Recent researches have demonstrated the feasibility of detecting smoking from wearable sensors, but their performance on real-life smoking lapse detection is unknown. In this paper, we propose a new model and evaluate its performance on 61 newly abstinent smokers for detecting a first lapse. We use two wearable sensors — breathing pattern from respiration and arm movements from 6-axis inertial sensors worn on wrists. In 10-fold cross-validation on 40 hours of training data from 6 daily smokers, our model achieves a recall rate of 96.9%, for a false positive rate of 1.1%. When our model is applied to 3 days of post-quit data from 32 lapsers, it correctly pinpoints the timing of first lapse in 28 participants. Only 2 false episodes are detected on 20 abstinent days of these participants. When tested on 84 abstinent days from 28 abstainers, the false episode per day is limited to 1/6. PMID:26543927

  16. Evaluation and cross-validation of Environmental Models

    NASA Astrophysics Data System (ADS)

    Lemaire, Joseph

    Before scientific models (statistical or empirical models based on experimental measurements; physical or mathematical models) can be proposed and selected as ISO Environmental Standards, a Commission of professional experts appointed by an established International Union or Association (e.g. IAGA for Geomagnetism and Aeronomy, . . . ) should have been able to study, document, evaluate and validate the best alternative models available at a given epoch. Examples will be given, indicating that different values for the Earth radius have been employed in different data processing laboratories, institutes or agencies, to process, analyse or retrieve series of experimental observations. Furthermore, invariant magnetic coordinates like B and L, commonly used in the study of Earth's radiation belts fluxes and for their mapping, differ from one space mission data center to the other, from team to team, and from country to country. Worse, users of empirical models generally fail to use the original magnetic model which had been employed to compile B and L , and thus to build these environmental models. These are just some flagrant examples of inconsistencies and misuses identified so far; there are probably more of them to be uncovered by careful, independent examination and benchmarking. A meter prototype, the standard unit length that has been determined on 20 May 1875, during the Diplomatic Conference of the Meter, and deposited at the BIPM (Bureau International des Poids et Mesures). In the same token, to coordinate and safeguard progress in the field of Space Weather, similar initiatives need to be undertaken, to prevent wild, uncontrolled dissemination of pseudo Environmental Models and Standards. Indeed, unless validation tests have been performed, there is guaranty, a priori, that all models on the market place have been built consistently with the same units system, and that they are based on identical definitions for the coordinates systems, etc... Therefore, preliminary analyses should be carried out under the control and authority of an established international professional Organization or Association, before any final political decision is made by ISO to select a specific Environmental Models, like for example IGRF and DGRF. Of course, Commissions responsible for checking the consistency of definitions, methods and algorithms for data processing might consider to delegate specific tasks (e.g. bench-marking the technical tools, the calibration procedures, the methods of data analysis, and the software algorithms employed in building the different types of models, as well as their usage) to private, intergovernmental or international organization/agencies (e.g.: NASA, ESA, AGU, EGU, COSPAR, . . . ); eventually, the latter should report conclusions to the Commissions members appointed by IAGA or any established authority like IUGG.

  17. Backward Variable Elimination Canonical Correlation and Canonical Cross-Validation.

    ERIC Educational Resources Information Center

    Eason, Sandra

    This paper suggests that multivariate analysis techniques are very important in educational research, and that one multivariate technique--canonical correlation analysis--may be particularly useful. The logic of canonical analysis is explained. It is suggested that a backward variable elimination strategy can make the method even more powerful, by…

  18. AnL1 smoothing spline algorithm with cross validation

    NASA Astrophysics Data System (ADS)

    Bosworth, Ken W.; Lall, Upmanu

    1993-08-01

    We propose an algorithm for the computation ofL1 (LAD) smoothing splines in the spacesWM(D), with . We assume one is given data of the formyiD(f(ti) +ɛi, iD1,...,N with {itti}iD1N ⊂D, theɛi are errors withE(ɛi)D0, andf is assumed to be inWM. The LAD smoothing spline, for fixed smoothing parameterλ?;0, is defined as the solution,sλ, of the optimization problem (1/N)∑iD1N yi-g(ti +λJM(g), whereJM(g) is the seminorm consisting of the sum of the squaredL2 norms of theMth partial derivatives ofg. Such an LAD smoothing spline,sλ, would be expected to give robust smoothed estimates off in situations where theɛi are from a distribution with heavy tails. The solution to such a problem is a "thin plate spline" of known form. An algorithm for computingsλ is given which is based on considering a sequence of quadratic programming problems whose structure is guided by the optimality conditions for the above convex minimization problem, and which are solved readily, if a good initial point is available. The "data driven" selection of the smoothing parameter is achieved by minimizing aCV(λ) score of the form .The combined LAD-CV smoothing spline algorithm is a continuation scheme in λ↘0 taken on the above SQPs parametrized inλ, with the optimal smoothing parameter taken to be that value ofλ at which theCV(λ) score first begins to increase. The feasibility of constructing the LAD-CV smoothing spline is illustrated by an application to a problem in environment data interpretation.

  19. Cross-Validation of the Computerized Adaptive Screening Test (CAST).

    ERIC Educational Resources Information Center

    Pliske, Rebecca M.; And Others

    The Computerized Adaptive Screening Test (CAST) was developed to provide an estimate at recruiting stations of prospects' Armed Forces Qualification Test (AFQT) scores. The CAST was designed to replace the paper-and-pencil Enlistment Screening Test (EST). The initial validation study of CAST indicated that CAST predicts AFQT at least as accurately…

  20. Cross-Validation of the JSORRAT-II in Iowa.

    PubMed

    Ralston, Christopher A; Epperson, Douglas L; Edwards, Sarah R

    2016-09-01

    The predictive validity of the Juvenile Sexual Offense Recidivism Risk Assessment Tool-II (JSORRAT-II) was evaluated using an exhaustive sample of 11- to 17-year-old male juveniles who offended sexually (JSOs) between 2000 and 2006 in Iowa (n = 529). The validity of the tool in predicting juvenile sexual recidivism was significant (area under the receiver operating characteristic curve [AUC] = .70, 99% confidence interval [CI] = [.60, .81], d = 0.70). Non-significant predictive validity coefficients were observed for the prediction of non-sexual forms of recidivism. Additional analyses were undertaken to test hypotheses about the tool's performance with various subsamples. The age of the JSO at the time of the index sexual offense and time at risk outside secure facility placements interacted significantly with JSORRAT-II scores to predict juvenile sexual recidivism. The implications of these findings for practice and research on the validation of risk assessment tools are discussed. PMID:25179400

  1. [Cross validity of the UCLA Loneliness Scale factorization].

    PubMed

    Borges, Africa; Prieto, Pedro; Ricchetti, Giacinto; Hernández-Jorge, Carmen; Rodríguez-Naveiras, Elena

    2008-11-01

    Loneliness is an unpleasant experience that takes place when a person's network of social relationships is significantly deficient in quality and quantity, and it is associated with negative feelings. Loneliness is a fundamental construct that provides information about several psychological processes, especially in the clinical setting. It is well known that this construct is related to isolation and emotional loneliness. One of the most well-known psychometric instruments to measure loneliness is the revised UCLA Loneliness Scale, which has been factorized in several populations. A controversial issue related to the UCLA Loneliness Scale is its factor structure, because the test was first created based on a unidimensional structure; however, subsequent research has proved that its structure may be bipolar or even multidimensional. In the present work, the UCLA Loneliness Scale was completed by two populations: Spanish and Italian undergraduate university students. Results show a multifactorial structure in both samples. This research presents a theoretically and analytically coherent bifactorial structure. PMID:18940104

  2. A fast approach for detection of erythemato-squamous diseases based on extreme learning machine with maximum relevance minimum redundancy feature selection

    NASA Astrophysics Data System (ADS)

    Liu, Tong; Hu, Liang; Ma, Chao; Wang, Zhi-Yan; Chen, Hui-Ling

    2015-04-01

    In this paper, a novel hybrid method, which integrates an effective filter maximum relevance minimum redundancy (MRMR) and a fast classifier extreme learning machine (ELM), has been introduced for diagnosing erythemato-squamous (ES) diseases. In the proposed method, MRMR is employed as a feature selection tool for dimensionality reduction in order to further improve the diagnostic accuracy of the ELM classifier. The impact of the type of activation functions, the number of hidden neurons and the size of the feature subsets on the performance of ELM have been investigated in detail. The effectiveness of the proposed method has been rigorously evaluated against the ES disease dataset, a benchmark dataset, from UCI machine learning database in terms of classification accuracy. Experimental results have demonstrated that our method has achieved the best classification accuracy of 98.89% and an average accuracy of 98.55% via 10-fold cross-validation technique. The proposed method might serve as a new candidate of powerful methods for diagnosing ES diseases.

  3. A novel approach to CAD system for the detection of lung nodules in CT images.

    PubMed

    Javaid, Muzzamil; Javid, Moazzam; Rehman, Muhammad Zia Ur; Shah, Syed Irtiza Ali

    2016-10-01

    Detection of pulmonary nodule plays a significant role in the diagnosis of lung cancer in early stage that improves the chances of survival of an individual. In this paper, a computer aided nodule detection method is proposed for the segmentation and detection of challenging nodules like juxtavascular and juxtapleural nodules. Lungs are segmented from computed tomography (CT) images using intensity thresholding; brief analysis of CT image histogram is done to select a suitable threshold value for better segmentation results. Simple morphological closing is used to include juxtapleural nodules in segmented lung regions. K-means clustering is applied for the initial detection and segmentation of potential nodules; shape specific morphological opening is implemented to refine segmentation outcomes. These segmented potential nodules are then divided into six groups on the basis of their thickness and percentage connectivity with lung walls. Grouping not only helped in improving system's efficiency but also reduced computational time, otherwise consumed in calculating and analyzing unnecessary features for all nodules. Different sets of 2D and 3D features are extracted from nodules in each group to eliminate false positives. Small size nodules are differentiated from false positives (FPs) on the basis of their salient features; sensitivity of the system for small nodules is 83.33%. SVM classifier is used for the classification of large nodules, for which the sensitivity of the proposed system is 93.8% applying 10-fold cross-validation. Receiver Operating Characteristic (ROC) curve is used for the analysis of CAD system. Overall sensitivity of the system is 91.65% with 3.19 FPs per case, and accuracy is 96.22%. The system took 3.8 seconds to analyze each image. PMID:27586486

  4. A comparison of different chemometrics approaches for the robust classification of electronic nose data.

    PubMed

    Gromski, Piotr S; Correa, Elon; Vaughan, Andrew A; Wedge, David C; Turner, Michael L; Goodacre, Royston

    2014-11-01

    Accurate detection of certain chemical vapours is important, as these may be diagnostic for the presence of weapons, drugs of misuse or disease. In order to achieve this, chemical sensors could be deployed remotely. However, the readout from such sensors is a multivariate pattern, and this needs to be interpreted robustly using powerful supervised learning methods. Therefore, in this study, we compared the classification accuracy of four pattern recognition algorithms which include linear discriminant analysis (LDA), partial least squares-discriminant analysis (PLS-DA), random forests (RF) and support vector machines (SVM) which employed four different kernels. For this purpose, we have used electronic nose (e-nose) sensor data (Wedge et al., Sensors Actuators B Chem 143:365-372, 2009). In order to allow direct comparison between our four different algorithms, we employed two model validation procedures based on either 10-fold cross-validation or bootstrapping. The results show that LDA (91.56% accuracy) and SVM with a polynomial kernel (91.66% accuracy) were very effective at analysing these e-nose data. These two models gave superior prediction accuracy, sensitivity and specificity in comparison to the other techniques employed. With respect to the e-nose sensor data studied here, our findings recommend that SVM with a polynomial kernel should be favoured as a classification method over the other statistical models that we assessed. SVM with non-linear kernels have the advantage that they can be used for classifying non-linear as well as linear mapping from analytical data space to multi-group classifications and would thus be a suitable algorithm for the analysis of most e-nose sensor data. PMID:25286877

  5. Validation of the modified Becker's split-window approach for retrieving land surface temperature from AVHRR

    NASA Astrophysics Data System (ADS)

    Quan, Weijun; Chen, Hongbin; Han, Xiuzhen; Ma, Zhiqiang

    2015-10-01

    To further verify the modified Becker's split-window approach for retrieving land surface temperature (LST) from long-term Advanced Very High Resolution Radiometer (AVHRR) data, a cross-validation and a radiance-based (R-based) validation are performed and examined in this paper. In the cross-validation, 3481 LST data pairs are extracted from the AVHRR LST product retrieved with the modified Becker's approach and compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (MYD11A1) for the period 2002-2008, relative to the positions of 548 weather stations in China. The results show that in most cases, the AVHRR LST values are higher than the MYD11A1. When the AVHRR LSTs are adjusted with a linear regression, the values are close to the MYD11A1, showing a good linear relationship between the two datasets ( R 2 = 0.91). In the R-based validation, comparison is made between AVHRR LST retrieved from the modified Becker's approach and the inversed LST from the Moderate Resolution Transmittance Model (MODTRAN) consolidated with observed temperature and humidity profiles at four radiosonde stations. The results show that the retrieved AVHRR LST deviates from the MODTRAN inversed LST by-1.3 (-2.5) K when the total water vapor amount is less (larger) than 20 mm. This provides useful hints for further improvement of the LST retrieval algorithms' accuracy and consistency.

  6. A methodological approach to the classification of dermoscopy images

    PubMed Central

    Celebi, M. Emre; Kingravi, Hassan A.; Uddin, Bakhtiyar; Iyatomi, Hitoshi; Aslandogan, Y. Alp; Stoecker, William V.; Moss, Randy H.

    2011-01-01

    In this paper a methodological approach to the classification of pigmented skin lesions in dermoscopy images is presented. First, automatic border detection is performed to separate the lesion from the background skin. Shape features are then extracted from this border. For the extraction of color and texture related features, the image is divided into various clinically significant regions using the Euclidean distance transform. This feature data is fed into an optimization framework, which ranks the features using various feature selection algorithms and determines the optimal feature subset size according to the area under the ROC curve measure obtained from support vector machine classification. The issue of class imbalance is addressed using various sampling strategies, and the classifier generalization error is estimated using Monte Carlo cross validation. Experiments on a set of 564 images yielded a specificity of 92.34% and a sensitivity of 93.33%. PMID:17387001

  7. A novel fractal approach for predicting G-protein-coupled receptors and their subfamilies with support vector machines.

    PubMed

    Nie, Guoping; Li, Yong; Wang, Feichi; Wang, Siwen; Hu, Xuehai

    2015-01-01

    G-protein-coupled receptors (GPCRs) are seven membrane-spanning proteins and regulate many important physiological processes, such as vision, neurotransmission, immune response and so on. GPCRs-related pathways are the targets of a large number of marketed drugs. Therefore, the design of a reliable computational model for predicting GPCRs from amino acid sequence has long been a significant biomedical problem. Chaos game representation (CGR) reveals the fractal patterns hidden in protein sequences, and then fractal dimension (FD) is an important feature of these highly irregular geometries with concise mathematical expression. Here, in order to extract important features from GPCR protein sequences, CGR algorithm, fractal dimension and amino acid composition (AAC) are employed to formulate the numerical features of protein samples. Four groups of features are considered, and each group is evaluated by support vector machine (SVM) and 10-fold cross-validation test. To test the performance of the present method, a new non-redundant dataset was built based on latest GPCRDB database. Comparing the results of numerical experiments, the group of combined features with AAC and FD gets the best result, the accuracy is 99.22% and Matthew's correlation coefficient (MCC) is 0.9845 for identifying GPCRs from non-GPCRs. Moreover, if it is classified as a GPCR, it will be further put into the second level, which will classify a GPCR into one of the five main subfamilies. At this level, the group of combined features with AAC and FD also gets best accuracy 85.73%. Finally, the proposed predictor is also compared with existing methods and shows better performances. PMID:26405954

  8. A Bayesian Shrinkage Approach for AMMI Models.

    PubMed

    da Silva, Carlos Pereira; de Oliveira, Luciano Antonio; Nuvunga, Joel Jorge; Pamplona, Andrezza Kéllen Alves; Balestre, Marcio

    2015-01-01

    Linear-bilinear models, especially the additive main effects and multiplicative interaction (AMMI) model, are widely applicable to genotype-by-environment interaction (GEI) studies in plant breeding programs. These models allow a parsimonious modeling of GE interactions, retaining a small number of principal components in the analysis. However, one aspect of the AMMI model that is still debated is the selection criteria for determining the number of multiplicative terms required to describe the GE interaction pattern. Shrinkage estimators have been proposed as selection criteria for the GE interaction components. In this study, a Bayesian approach was combined with the AMMI model with shrinkage estimators for the principal components. A total of 55 maize genotypes were evaluated in nine different environments using a complete blocks design with three replicates. The results show that the traditional Bayesian AMMI model produces low shrinkage of singular values but avoids the usual pitfalls in determining the credible intervals in the biplot. On the other hand, Bayesian shrinkage AMMI models have difficulty with the credible interval for model parameters, but produce stronger shrinkage of the principal components, converging to GE matrices that have more shrinkage than those obtained using mixed models. This characteristic allowed more parsimonious models to be chosen, and resulted in models being selected that were similar to those obtained by the Cornelius F-test (α = 0.05) in traditional AMMI models and cross validation based on leave-one-out. This characteristic allowed more parsimonious models to be chosen and more GEI pattern retained on the first two components. The resulting model chosen by posterior distribution of singular value was also similar to those produced by the cross-validation approach in traditional AMMI models. Our method enables the estimation of credible interval for AMMI biplot plus the choice of AMMI model based on direct posterior

  9. A Bayesian Shrinkage Approach for AMMI Models

    PubMed Central

    de Oliveira, Luciano Antonio; Nuvunga, Joel Jorge; Pamplona, Andrezza Kéllen Alves

    2015-01-01

    Linear-bilinear models, especially the additive main effects and multiplicative interaction (AMMI) model, are widely applicable to genotype-by-environment interaction (GEI) studies in plant breeding programs. These models allow a parsimonious modeling of GE interactions, retaining a small number of principal components in the analysis. However, one aspect of the AMMI model that is still debated is the selection criteria for determining the number of multiplicative terms required to describe the GE interaction pattern. Shrinkage estimators have been proposed as selection criteria for the GE interaction components. In this study, a Bayesian approach was combined with the AMMI model with shrinkage estimators for the principal components. A total of 55 maize genotypes were evaluated in nine different environments using a complete blocks design with three replicates. The results show that the traditional Bayesian AMMI model produces low shrinkage of singular values but avoids the usual pitfalls in determining the credible intervals in the biplot. On the other hand, Bayesian shrinkage AMMI models have difficulty with the credible interval for model parameters, but produce stronger shrinkage of the principal components, converging to GE matrices that have more shrinkage than those obtained using mixed models. This characteristic allowed more parsimonious models to be chosen, and resulted in models being selected that were similar to those obtained by the Cornelius F-test (α = 0.05) in traditional AMMI models and cross validation based on leave-one-out. This characteristic allowed more parsimonious models to be chosen and more GEI pattern retained on the first two components. The resulting model chosen by posterior distribution of singular value was also similar to those produced by the cross-validation approach in traditional AMMI models. Our method enables the estimation of credible interval for AMMI biplot plus the choice of AMMI model based on direct posterior

  10. Hyperdimensional computing approach to word sense disambiguation.

    PubMed

    Berster, Bjoern-Toby; Goodwin, J Caleb; Cohen, Trevor

    2012-01-01

    Coping with the ambiguous meanings of words has long been a hurdle for information retrieval and natural language processing systems. This paper presents a new word sense disambiguation approach using high-dimensional binary vectors, which encode meanings of words based on the different contexts in which they occur. In our approach, a randomly constructed vector is assigned to each ambiguous term, and another to each sense of this term. In the context of a sense-annotated training set, a reversible vector transformation is used to combine these vectors, such that both the term and the sense assigned to a context in which the term occurs are encoded into vectors representing the surrounding terms in this context. When a new context is encountered, the information required to disambiguate this term is extracted from the trained semantic vectors for the terms in this context by reversing the vector transformation to recover the correct sense of the term. On repeated experiments using ten-fold cross-validation and a standard test set, we obtained results comparable to the best obtained in previous studies. These results demonstrate the potential of our methodology, and suggest directions for future research. PMID:23304389

  11. Quantifying the lifetime circadian rhythm of physical activity: a covariate-dependent functional approach

    PubMed Central

    Xiao, Luo; Huang, Lei; Schrack, Jennifer A.; Ferrucci, Luigi; Zipunnikov, Vadim; Crainiceanu, Ciprian M.

    2015-01-01

    Objective measurement of physical activity using wearable devices such as accelerometers may provide tantalizing new insights into the association between activity and health outcomes. Accelerometers can record quasi-continuous activity information for many days and for hundreds of individuals. For example, in the Baltimore Longitudinal Study on Aging physical activity was recorded every minute for 773 adults for an average of 7 days per adult. An important scientific problem is to separate and quantify the systematic and random circadian patterns of physical activity as functions of time of day, age, and gender. To capture the systematic circadian pattern, we introduce a practical bivariate smoother and two crucial innovations: (i) estimating the smoothing parameter using leave-one-subject-out cross validation to account for within-subject correlation and (ii) introducing fast computational techniques that overcome problems both with the size of the data and with the cross-validation approach to smoothing. The age-dependent random patterns are analyzed by a new functional principal component analysis that incorporates both covariate dependence and multilevel structure. For the analysis, we propose a practical and very fast trivariate spline smoother to estimate covariate-dependent covariances and their spectra. Results reveal several interesting, previously unknown, circadian patterns associated with human aging and gender. PMID:25361695

  12. Prediction of 10-fold coordinated TiO2 and SiO2 structures at multimegabar pressures

    PubMed Central

    Lyle, Matthew J.; Pickard, Chris J.; Needs, Richard J.

    2015-01-01

    We predict by first-principles methods a phase transition in TiO2 at 6.5 Mbar from the Fe2P-type polymorph to a ten-coordinated structure with space group I4/mmm. This is the first report, to our knowledge, of the pressure-induced phase transition to the I4/mmm structure among all dioxide compounds. The I4/mmm structure was found to be up to 3.3% denser across all pressures investigated. Significant differences were found in the electronic properties of the two structures, and the metallization of TiO2 was calculated to occur concomitantly with the phase transition to I4/mmm. The implications of our findings were extended to SiO2, and an analogous Fe2P-type to I4/mmm transition was found to occur at 10 TPa. This is consistent with the lower-pressure phase transitions of TiO2, which are well-established models for the phase transitions in other AX2 compounds, including SiO2. As in TiO2, the transition to I4/mmm corresponds to the metallization of SiO2. This transformation is in the pressure range reached in the interiors of recently discovered extrasolar planets and calls for a reformulation of the equations of state used to model them. PMID:25991859

  13. Prediction of 10-fold coordinated TiO2 and SiO2 structures at multimegabar pressures.

    PubMed

    Lyle, Matthew J; Pickard, Chris J; Needs, Richard J

    2015-06-01

    We predict by first-principles methods a phase transition in TiO2 at 6.5 Mbar from the Fe2P-type polymorph to a ten-coordinated structure with space group I4/mmm. This is the first report, to our knowledge, of the pressure-induced phase transition to the I4/mmm structure among all dioxide compounds. The I4/mmm structure was found to be up to 3.3% denser across all pressures investigated. Significant differences were found in the electronic properties of the two structures, and the metallization of TiO2 was calculated to occur concomitantly with the phase transition to I4/mmm. The implications of our findings were extended to SiO2, and an analogous Fe2P-type to I4/mmm transition was found to occur at 10 TPa. This is consistent with the lower-pressure phase transitions of TiO2, which are well-established models for the phase transitions in other AX2 compounds, including SiO2. As in TiO2, the transition to I4/mmm corresponds to the metallization of SiO2. This transformation is in the pressure range reached in the interiors of recently discovered extrasolar planets and calls for a reformulation of the equations of state used to model them. PMID:25991859

  14. The H50Q mutation induces a 10-fold decrease in the solubility of α-synuclein.

    PubMed

    Porcari, Riccardo; Proukakis, Christos; Waudby, Christopher A; Bolognesi, Benedetta; Mangione, P Patrizia; Paton, Jack F S; Mullin, Stephen; Cabrita, Lisa D; Penco, Amanda; Relini, Annalisa; Verona, Guglielmo; Vendruscolo, Michele; Stoppini, Monica; Tartaglia, Gian Gaetano; Camilloni, Carlo; Christodoulou, John; Schapira, Anthony H V; Bellotti, Vittorio

    2015-01-23

    The conversion of α-synuclein from its intrinsically disordered monomeric state into the fibrillar cross-β aggregates characteristically present in Lewy bodies is largely unknown. The investigation of α-synuclein variants causative of familial forms of Parkinson disease can provide unique insights into the conditions that promote or inhibit aggregate formation. It has been shown recently that a newly identified pathogenic mutation of α-synuclein, H50Q, aggregates faster than the wild-type. We investigate here its aggregation propensity by using a sequence-based prediction algorithm, NMR chemical shift analysis of secondary structure populations in the monomeric state, and determination of thermodynamic stability of the fibrils. Our data show that the H50Q mutation induces only a small increment in polyproline II structure around the site of the mutation and a slight increase in the overall aggregation propensity. We also find, however, that the H50Q mutation strongly stabilizes α-synuclein fibrils by 5.0 ± 1.0 kJ mol(-1), thus increasing the supersaturation of monomeric α-synuclein within the cell, and strongly favors its aggregation process. We further show that wild-type α-synuclein can decelerate the aggregation kinetics of the H50Q variant in a dose-dependent manner when coaggregating with it. These last findings suggest that the precise balance of α-synuclein synthesized from the wild-type and mutant alleles may influence the natural history and heterogeneous clinical phenotype of Parkinson disease. PMID:25505181

  15. 13 Years of TOPEX/POSEIDON Precision Orbit Determination and the 10-fold Improvement in Expected Orbit Accuracy

    NASA Technical Reports Server (NTRS)

    Lemoine, F. G.; Zelensky, N. P.; Luthcke, S. B.; Rowlands, D. D.; Beckley, B. D.; Klosko, S. M.

    2006-01-01

    Launched in the summer of 1992, TOPEX/POSEIDON (T/P) was a joint mission between NASA and the Centre National d Etudes Spatiales (CNES), the French Space Agency, to make precise radar altimeter measurements of the ocean surface. After the remarkably successful 13-years of mapping the ocean surface T/P lost its ability to maneuver and was de-commissioned January 2006. T/P revolutionized the study of the Earth s oceans by vastly exceeding pre-launch estimates of surface height accuracy recoverable from radar altimeter measurements. The precision orbit lies at the heart of the altimeter measurement providing the reference frame from which the radar altimeter measurements are made. The expected quality of orbit knowledge had limited the measurement accuracy expectations of past altimeter missions, and still remains a major component in the error budget of all altimeter missions. This paper describes critical improvements made to the T/P orbit time series over the 13-years of precise orbit determination (POD) provided by the GSFC Space Geodesy Laboratory. The POD improvements from the pre-launch T/P expectation of radial orbit accuracy and Mission requirement of 13-cm to an expected accuracy of about 1.5-cm with today s latest orbits will be discussed. The latest orbits with 1.5 cm RMS radial accuracy represent a significant improvement to the 2.0-cm accuracy orbits currently available on the T/P Geophysical Data Record (GDR) altimeter product.

  16. Coastal water quality estimation from Geostationary Ocean Color Imager (GOCI) satellite data using machine learning approaches

    NASA Astrophysics Data System (ADS)

    Im, Jungho; Ha, Sunghyun; Kim, Yong Hoon; Ha, Hokyung; Choi, Jongkuk; Kim, Miae

    2014-05-01

    It is important to monitor coastal water quality using key parameters such as chlorophyll-a concentration and suspended sediment to better manage coastal areas as well as to better understand the nature of biophysical processes in coastal seawater. Remote sensing technology has been commonly used to monitor coastal water quality due to its ability of covering vast areas at high temporal resolution. While it is relatively straightforward to estimate water quality in open ocean (i.e., Case I water) using remote sensing, coastal water quality estimation is still challenging as many factors can influence water quality, including various materials coming from inland water systems and tidal circulation. There are continued efforts to accurately estimate water quality parameters in coastal seawater from remote sensing data in a timely manner. In this study, two major water quality indicators, chlorophyll-a concentration and the amount of suspended sediment, were estimated using Geostationary Ocean Color Imager (GOCI) satellite data. GOCI, launched in June 2010, is the first geostationary ocean color observation satellite in the world. GOCI collects data hourly for 8 hours a day at 6 visible and 2 near-infrared bands at a 500 m resolution with 2,500 x 2,500 km square around Korean peninsula. Along with conventional statistical methods (i.e., various linear and non-linear regression), three machine learning approaches such as random forest, Cubist, and support vector regression were evaluated for coastal water quality estimation. In situ measurements (63 samples; including location, two water quality parameters, and the spectra of surface water using a hand-held spectroradiometer) collected during four days between 2011 and 2012 were used as reference data. Due to the small sample size, leave-one-out cross validation was used to assess the performance of the water quality estimation models. Atmospherically corrected radiance data and selected band-ratioed images were used

  17. A Predictive Approach to Network Reverse-Engineering

    NASA Astrophysics Data System (ADS)

    Wiggins, Chris

    2005-03-01

    A central challenge of systems biology is the ``reverse engineering" of transcriptional networks: inferring which genes exert regulatory control over which other genes. Attempting such inference at the genomic scale has only recently become feasible, via data-intensive biological innovations such as DNA microrrays (``DNA chips") and the sequencing of whole genomes. In this talk we present a predictive approach to network reverse-engineering, in which we integrate DNA chip data and sequence data to build a model of the transcriptional network of the yeast S. cerevisiae capable of predicting the response of genes in unseen experiments. The technique can also be used to extract ``motifs,'' sequence elements which act as binding sites for regulatory proteins. We validate by a number of approaches and present comparison of theoretical prediction vs. experimental data, along with biological interpretations of the resulting model. En route, we will illustrate some basic notions in statistical learning theory (fitting vs. over-fitting; cross- validation; assessing statistical significance), highlighting ways in which physicists can make a unique contribution in data- driven approaches to reverse engineering.

  18. Comparison of mapping approaches of design annual maximum daily precipitation

    NASA Astrophysics Data System (ADS)

    Szolgay, J.; Parajka, J.; Kohnová, S.; Hlavčová, K.

    2009-05-01

    In this study 2-year and 100-year annual maximum daily precipitation for rainfall-runoff studies and estimating flood hazard were mapped. The daily precipitation measurements at 23 climate stations from 1961-2000 were used in the upper Hron basin in central Slovakia. The choice of data preprocessing and interpolation methods was guided by their practical applicability and acceptance in the engineering hydrologic community. The main objective was to discuss the quality and properties of maps of design precipitation with a given return period with respect to the expectations of the end user. Four approaches to the preprocessing of annual maximum 24-hour precipitation data were used, and three interpolation methods employed. The first approach is the direct mapping of at-site estimates of distribution function quantiles; the second is the direct mapping of local estimates of the three parameters of the GEV distribution. In the third, the daily precipitation totals were interpolated into a regular grid network, and then the time series of the maximum daily precipitation totals in each grid point of the selected region were statistically analysed. In the fourth, the spatial distribution of the design precipitation was modeled by quantiles predicted by regional precipitation frequency analysis using the Hosking and Wallis procedure. The three interpolation methods used were the inverse distance weighting, nearest neighbor and the kriging method. Visual inspection and jackknife cross-validation were used to compare the combination of approaches.

  19. Origin of aromatase inhibitory activity via proteochemometric modeling

    PubMed Central

    Simeon, Saw; Spjuth, Ola; Lapins, Maris; Nabu, Sunanta; Anuwongcharoen, Nuttapat; Prachayasittikul, Virapong; Wikberg, Jarl E.S.

    2016-01-01

    Aromatase, the rate-limiting enzyme that catalyzes the conversion of androgen to estrogen, plays an essential role in the development of estrogen-dependent breast cancer. Side effects due to aromatase inhibitors (AIs) necessitate the pursuit of novel inhibitor candidates with high selectivity, lower toxicity and increased potency. Designing a novel therapeutic agent against aromatase could be achieved computationally by means of ligand-based and structure-based methods. For over a decade, we have utilized both approaches to design potential AIs for which quantitative structure–activity relationships and molecular docking were used to explore inhibitory mechanisms of AIs towards aromatase. However, such approaches do not consider the effects that aromatase variants have on different AIs. In this study, proteochemometrics modeling was applied to analyze the interaction space between AIs and aromatase variants as a function of their substructural and amino acid features. Good predictive performance was achieved, as rigorously verified by 10-fold cross-validation, external validation, leave-one-compound-out cross-validation, leave-one-protein-out cross-validation and Y-scrambling tests. The investigations presented herein provide important insights into the mechanisms of aromatase inhibitory activity that could aid in the design of novel potent AIs as breast cancer therapeutic agents. PMID:27190705

  20. Origin of aromatase inhibitory activity via proteochemometric modeling.

    PubMed

    Simeon, Saw; Spjuth, Ola; Lapins, Maris; Nabu, Sunanta; Anuwongcharoen, Nuttapat; Prachayasittikul, Virapong; Wikberg, Jarl E S; Nantasenamat, Chanin

    2016-01-01

    Aromatase, the rate-limiting enzyme that catalyzes the conversion of androgen to estrogen, plays an essential role in the development of estrogen-dependent breast cancer. Side effects due to aromatase inhibitors (AIs) necessitate the pursuit of novel inhibitor candidates with high selectivity, lower toxicity and increased potency. Designing a novel therapeutic agent against aromatase could be achieved computationally by means of ligand-based and structure-based methods. For over a decade, we have utilized both approaches to design potential AIs for which quantitative structure-activity relationships and molecular docking were used to explore inhibitory mechanisms of AIs towards aromatase. However, such approaches do not consider the effects that aromatase variants have on different AIs. In this study, proteochemometrics modeling was applied to analyze the interaction space between AIs and aromatase variants as a function of their substructural and amino acid features. Good predictive performance was achieved, as rigorously verified by 10-fold cross-validation, external validation, leave-one-compound-out cross-validation, leave-one-protein-out cross-validation and Y-scrambling tests. The investigations presented herein provide important insights into the mechanisms of aromatase inhibitory activity that could aid in the design of novel potent AIs as breast cancer therapeutic agents. PMID:27190705

  1. A single vs. multi-sensor approach to enhanced detection of smartphone placement.

    PubMed

    Guiry, John J; Karr, Chris J; van de Ven, Pepijn; Nelson, John; Begale, Mark

    2014-01-01

    In this paper, the authors evaluate the ability to detect on-body device placement of smartphones. A feasibility study is undertaken with N=5 participants to identify nine key locations, including in the hand, thigh and backpack, using a multitude of commonly available smartphone sensors. Sensors examined include the accelerometer, magnetometer, gyroscope, pressure and light sensors. Each sensor is examined independently, to identify the potential contributions it can offer, before a fused approach, using all sensors is adopted. A total of 139 features are generated from these sensors, and used to train five machine learning algorithms, i.e. C4.5, CART, Naïve Bayes, Multilayer Perceptrons, and Support Vector Machines. Ten-fold cross validation is used to validate these models, achieving classification results as high as 99%. PMID:25570792

  2. In-silico predictive mutagenicity model generation using supervised learning approaches

    PubMed Central

    2012-01-01

    Background Experimental screening of chemical compounds for biological activity is a time consuming and expensive practice. In silico predictive models permit inexpensive, rapid “virtual screening” to prioritize selection of compounds for experimental testing. Both experimental and in silico screening can be used to test compounds for desirable or undesirable properties. Prior work on prediction of mutagenicity has primarily involved identification of toxicophores rather than whole-molecule predictive models. In this work, we examined a range of in silico predictive classification models for prediction of mutagenic properties of compounds, including methods such as J48 and SMO which have not previously been widely applied in cheminformatics. Results The Bursi mutagenicity data set containing 4337 compounds (Set 1) and a Benchmark data set of 6512 compounds (Set 2) were taken as input data set in this work. A third data set (Set 3) was prepared by joining up the previous two sets. Classification algorithms including Naïve Bayes, Random Forest, J48 and SMO with 10 fold cross-validation and default parameters were used for model generation on these data sets. Models built using the combined performed better than those developed from the Benchmark data set. Significantly, Random Forest outperformed other classifiers for all the data sets, especially for Set 3 with 89.27% accuracy, 89% precision and ROC of 95.3%. To validate the developed models two external data sets, AID1189 and AID1194, with mutagenicity data were tested showing 62% accuracy with 67% precision and 65% ROC area and 91% accuracy, 91% precision with 96.3% ROC area respectively. A Random Forest model was used on approved drugs from DrugBank and metabolites from the Zinc Database with True Positives rate almost 85% showing the robustness of the model. Conclusion We have created a new mutagenicity benchmark data set with around 8,000 compounds. Our work shows that highly accurate predictive

  3. Ordinary kriging approach to predicting long-term particulate matter concentrations in seven major Korean cities

    PubMed Central

    Kim, Sun-Young; Yi, Seon-Ju; Eum, Young Seob; Choi, Hae-Jin; Shin, Hyesop; Ryou, Hyoung Gon; Kim, Ho

    2014-01-01

    Objectives Cohort studies of associations between air pollution and health have used exposure prediction approaches to estimate individual-level concentrations. A common prediction method used in Korean cohort studies is ordinary kriging. In this study, performance of ordinary kriging models for long-term particulate matter less than or equal to 10 μm in diameter (PM10) concentrations in seven major Korean cities was investigated with a focus on spatial prediction ability. Methods We obtained hourly PM10 data for 2010 at 226 urban-ambient monitoring sites in South Korea and computed annual average PM10 concentrations at each site. Given the annual averages, we developed ordinary kriging prediction models for each of the seven major cities and for the entire country by using an exponential covariance reference model and a maximum likelihood estimation method. For model evaluation, cross-validation was performed and mean square error and R-squared (R2) statistics were computed. Results Mean annual average PM10 concentrations in the seven major cities ranged between 45.5 and 66.0 μg/m3 (standard deviation=2.40 and 9.51 μg/m3, respectively). Cross-validated R2 values in Seoul and Busan were 0.31 and 0.23, respectively, whereas the other five cities had R2 values of zero. The national model produced a higher crossvalidated R2 (0.36) than those for the city-specific models. Conclusions In general, the ordinary kriging models performed poorly for the seven major cities and the entire country of South Korea, but the model performance was better in the national model. To improve model performance, future studies should examine different prediction approaches that incorporate PM10 source characteristics. PMID:25262773

  4. A novel logic-based approach for quantitative toxicology prediction.

    PubMed

    Amini, Ata; Muggleton, Stephen H; Lodhi, Huma; Sternberg, Michael J E

    2007-01-01

    There is a pressing need for accurate in silico methods to predict the toxicity of molecules that are being introduced into the environment or are being developed into new pharmaceuticals. Predictive toxicology is in the realm of structure activity relationships (SAR), and many approaches have been used to derive such SAR. Previous work has shown that inductive logic programming (ILP) is a powerful approach that circumvents several major difficulties, such as molecular superposition, faced by some other SAR methods. The ILP approach reasons with chemical substructures within a relational framework and yields chemically understandable rules. Here, we report a general new approach, support vector inductive logic programming (SVILP), which extends the essentially qualitative ILP-based SAR to quantitative modeling. First, ILP is used to learn rules, the predictions of which are then used within a novel kernel to derive a support-vector generalization model. For a highly heterogeneous dataset of 576 molecules with known fathead minnow fish toxicity, the cross-validated correlation coefficients (R2CV) from a chemical descriptor method (CHEM) and SVILP are 0.52 and 0.66, respectively. The ILP, CHEM, and SVILP approaches correctly predict 55, 58, and 73%, respectively, of toxic molecules. In a set of 165 unseen molecules, the R2 values from the commercial software TOPKAT and SVILP are 0.26 and 0.57, respectively. In all calculations, SVILP showed significant improvements in comparison with the other methods. The SVILP approach has a major advantage in that it uses ILP automatically and consistently to derive rules, mostly novel, describing fragments that are toxicity alerts. The SVILP is a general machine-learning approach and has the potential of tackling many problems relevant to chemoinformatics including in silico drug design. PMID:17451225

  5. Practical approach to determine sample size for building logistic prediction models using high-throughput data.

    PubMed

    Son, Dae-Soon; Lee, DongHyuk; Lee, Kyusang; Jung, Sin-Ho; Ahn, Taejin; Lee, Eunjin; Sohn, Insuk; Chung, Jongsuk; Park, Woongyang; Huh, Nam; Lee, Jae Won

    2015-02-01

    An empirical method of sample size determination for building prediction models was proposed recently. Permutation method which is used in this procedure is a commonly used method to address the problem of overfitting during cross-validation while evaluating the performance of prediction models constructed from microarray data. But major drawback of such methods which include bootstrapping and full permutations is prohibitively high cost of computation required for calculating the sample size. In this paper, we propose that a single representative null distribution can be used instead of a full permutation by using both simulated and real data sets. During simulation, we have used a dataset with zero effect size and confirmed that the empirical type I error approaches to 0.05. Hence this method can be confidently applied to reduce overfitting problem during cross-validation. We have observed that pilot data set generated by random sampling from real data could be successfully used for sample size determination. We present our results using an experiment that was repeated for 300 times while producing results comparable to that of full permutation method. Since we eliminate full permutation, sample size estimation time is not a function of pilot data size. In our experiment we have observed that this process takes around 30min. With the increasing number of clinical studies, developing efficient sample size determination methods for building prediction models is critical. But empirical methods using bootstrap and permutation usually involve high computing costs. In this study, we propose a method that can reduce required computing time drastically by using representative null distribution of permutations. We use data from pilot experiments to apply this method for designing clinical studies efficiently for high throughput data. PMID:25555898

  6. Chronic subdural hematoma: Surgical management and outcome in 986 cases: A classification and regression tree approach

    PubMed Central

    Rovlias, Aristedis; Theodoropoulos, Spyridon; Papoutsakis, Dimitrios

    2015-01-01

    Background: Chronic subdural hematoma (CSDH) is one of the most common clinical entities in daily neurosurgical practice which carries a most favorable prognosis. However, because of the advanced age and medical problems of patients, surgical therapy is frequently associated with various complications. This study evaluated the clinical features, radiological findings, and neurological outcome in a large series of patients with CSDH. Methods: A classification and regression tree (CART) technique was employed in the analysis of data from 986 patients who were operated at Asclepeion General Hospital of Athens from January 1986 to December 2011. Burr holes evacuation with closed system drainage has been the operative technique of first choice at our institution for 29 consecutive years. A total of 27 prognostic factors were examined to predict the outcome at 3-month postoperatively. Results: Our results indicated that neurological status on admission was the best predictor of outcome. With regard to the other data, age, brain atrophy, thickness and density of hematoma, subdural accumulation of air, and antiplatelet and anticoagulant therapy were found to correlate significantly with prognosis. The overall cross-validated predictive accuracy of CART model was 85.34%, with a cross-validated relative error of 0.326. Conclusions: Methodologically, CART technique is quite different from the more commonly used methods, with the primary benefit of illustrating the important prognostic variables as related to outcome. Since, the ideal therapy for the treatment of CSDH is still under debate, this technique may prove useful in developing new therapeutic strategies and approaches for patients with CSDH. PMID:26257985

  7. Discovery of Potent Succinate-Ubiquinone Oxidoreductase Inhibitors via Pharmacophore-linked Fragment Virtual Screening Approach.

    PubMed

    Xiong, Li; Zhu, Xiao-Lei; Gao, Hua-Wei; Fu, Yu; Hu, Sheng-Quan; Jiang, Li-Na; Yang, Wen-Chao; Yang, Guang-Fu

    2016-06-22

    Succinate-ubiquinone oxidoreductase (SQR) is an attractive target for fungicide discovery. Herein, we report the discovery of novel SQR inhibitors using a pharmacophore-linked fragment virtual screening approach, a new drug design method developed in our laboratory. Among newly designed compounds, compound 9s was identified as the most potent inhibitor with a Ki value of 34 nM against porcine SQR, displaying approximately 10-fold higher potency than that of the commercial control penthiopyrad. Further inhibitory kinetics studies revealed that compound 9s is a noncompetitive inhibitor with respect to the substrate cytochrome c and DCIP. Interestingly, compounds 8a, 9h, 9j, and 9k exhibited good in vivo preventive effects against Rhizoctonia solani. The results obtained from molecular modeling showed that the orientation of the R(2) group had a significant effect on binding with the protein. PMID:27225833

  8. A PCA approach to population analysis: with application to a Phase II depression trial.

    PubMed

    Marostica, Eleonora; Russu, Alberto; Gomeni, Roberto; Zamuner, Stefano; De Nicolao, Giuseppe

    2013-04-01

    For psychiatric diseases, established mechanistic models are lacking and alternative empirical mathematical structures are usually explored by a trial-and-error procedure. To address this problem, one of the most promising approaches is an automated model-free technique that extracts the model structure directly from the statistical properties of the data. In this paper, a linear-in-parameter modelling approach is developed based on principal component analysis (PCA). The model complexity, i.e. the number of components entering the PCA-based model, is selected by either cross-validation or Mallows' Cp criterion. This new approach has been validated on both simulated and clinical data taken from a Phase II depression trial. Simulated datasets are generated through three parametric models: Weibull, Inverse Bateman and Weibull-and-Linear. In particular, concerning simulated datasets, it is found that the PCA approach compares very favourably with some of the popular parametric models used for analyzing data collected during psychiatric trials. Furthermore, the proposed method performs well on the experimental data. This approach can be useful whenever a mechanistic modelling procedure cannot be pursued. Moreover, it could support subsequent semi-mechanistic model building. PMID:23504512

  9. A Multiscale Approach to InSAR Time Series Analysis

    NASA Astrophysics Data System (ADS)

    Hetland, E. A.; Muse, P.; Simons, M.; Lin, N.; Dicaprio, C. J.

    2010-12-01

    We present a technique to constrain time-dependent deformation from repeated satellite-based InSAR observations of a given region. This approach, which we call MInTS (Multiscale InSAR Time Series analysis), relies on a spatial wavelet decomposition to permit the inclusion of distance based spatial correlations in the observations while maintaining computational tractability. As opposed to single pixel InSAR time series techniques, MInTS takes advantage of both spatial and temporal characteristics of the deformation field. We use a weighting scheme which accounts for the presence of localized holes due to decorrelation or unwrapping errors in any given interferogram. We represent time-dependent deformation using a dictionary of general basis functions, capable of detecting both steady and transient processes. The estimation is regularized using a model resolution based smoothing so as to be able to capture rapid deformation where there are temporally dense radar acquisitions and to avoid oscillations during time periods devoid of acquisitions. MInTS also has the flexibility to explicitly parametrize known time-dependent processes that are expected to contribute to a given set of observations (e.g., co-seismic steps and post-seismic transients, secular variations, seasonal oscillations, etc.). We use cross validation to choose the regularization penalty parameter in the inversion of for the time-dependent deformation field. We demonstrate MInTS using a set of 63 ERS-1/2 and 29 Envisat interferograms for Long Valley Caldera.

  10. A novel approach for food intake detection using electroglottography

    PubMed Central

    Farooq, Muhammad; Fontana, Juan M; Sazonov, Edward

    2014-01-01

    Many methods for monitoring diet and food intake rely on subjects self-reporting their daily intake. These methods are subjective, potentially inaccurate and need to be replaced by more accurate and objective methods. This paper presents a novel approach that uses an Electroglottograph (EGG) device for an objective and automatic detection of food intake. Thirty subjects participated in a 4-visit experiment involving the consumption of meals with self-selected content. Variations in the electrical impedance across the larynx caused by the passage of food during swallowing were captured by the EGG device. To compare performance of the proposed method with a well-established acoustical method, a throat microphone was used for monitoring swallowing sounds. Both signals were segmented into non-overlapping epochs of 30 s and processed to extract wavelet features. Subject-independent classifiers were trained using Artificial Neural Networks, to identify periods of food intake from the wavelet features. Results from leave-one-out cross-validation showed an average per-epoch classification accuracy of 90.1% for the EGG-based method and 83.1% for the acoustic-based method, demonstrating the feasibility of using an EGG for food intake detection. PMID:24671094

  11. A multiscale approach to InSAR time series analysis

    NASA Astrophysics Data System (ADS)

    Simons, M.; Hetland, E. A.; Muse, P.; Lin, Y. N.; Dicaprio, C.; Rickerby, A.

    2008-12-01

    We describe a new technique to constrain time-dependent deformation from repeated satellite-based InSAR observations of a given region. This approach, which we call MInTS (Multiscale analysis of InSAR Time Series), relies on a spatial wavelet decomposition to permit the inclusion of distance based spatial correlations in the observations while maintaining computational tractability. This approach also permits a consistent treatment of all data independent of the presence of localized holes in any given interferogram. In essence, MInTS allows one to considers all data at the same time (as opposed to one pixel at a time), thereby taking advantage of both spatial and temporal characteristics of the deformation field. In terms of the temporal representation, we have the flexibility to explicitly parametrize known processes that are expected to contribute to a given set of observations (e.g., co-seismic steps and post-seismic transients, secular variations, seasonal oscillations, etc.). Our approach also allows for the temporal parametrization to includes a set of general functions (e.g., splines) in order to account for unexpected processes. We allow for various forms of model regularization using a cross-validation approach to select penalty parameters. The multiscale analysis allows us to consider various contributions (e.g., orbit errors) that may affect specific scales but not others. The methods described here are all embarrassingly parallel and suitable for implementation on a cluster computer. We demonstrate the use of MInTS using a large suite of ERS-1/2 and Envisat interferograms for Long Valley Caldera, and validate our results by comparing with ground-based observations.

  12. Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification

    PubMed Central

    Yilmaz, Nihat; Inan, Onur

    2013-01-01

    This paper offers a hybrid approach that uses the artificial bee colony (ABC) algorithm for feature selection and support vector machines for classification. The purpose of this paper is to test the effect of elimination of the unimportant and obsolete features of the datasets on the success of the classification, using the SVM classifier. The developed approach conventionally used in liver diseases and diabetes diagnostics, which are commonly observed and reduce the quality of life, is developed. For the diagnosis of these diseases, hepatitis, liver disorders and diabetes datasets from the UCI database were used, and the proposed system reached a classification accuracies of 94.92%, 74.81%, and 79.29%, respectively. For these datasets, the classification accuracies were obtained by the help of the 10-fold cross-validation method. The results show that the performance of the method is highly successful compared to other results attained and seems very promising for pattern recognition applications. PMID:23983632

  13. Predicting lipase types by improved Chou's pseudo-amino acid composition.

    PubMed

    Zhang, Guang-Ya; Li, Hong-Chun; Gao, Jia-Qiang; Fang, Bai-Shan

    2008-01-01

    By proposing a improved Chou's pseudo amino acid composition approach to extract the features of the sequences, a powerful predictor based on k-nearest neighbor was introduced to identify the types of lipases according to their sequences. To avoid redundancy and bias, demonstrations were performed on a dataset where none of the proteins has > or =25% sequence identity to any other. The overall success rate thus obtained by the 10-fold cross-validation test was over 90%, indicating that the improved Chou's pseudo amino acid composition might be a useful tool for extracting the features of protein sequences, or at lease can play a complementary role to many of the other existing approaches. PMID:19075826

  14. A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach.

    PubMed

    Weichenthal, Scott; Ryswyk, Keith Van; Goldstein, Alon; Bagg, Scott; Shekkarizfard, Maryam; Hatzopoulou, Marianne

    2016-04-01

    Existing evidence suggests that ambient ultrafine particles (UFPs) (<0.1µm) may contribute to acute cardiorespiratory morbidity. However, few studies have examined the long-term health effects of these pollutants owing in part to a need for exposure surfaces that can be applied in large population-based studies. To address this need, we developed a land use regression model for UFPs in Montreal, Canada using mobile monitoring data collected from 414 road segments during the summer and winter months between 2011 and 2012. Two different approaches were examined for model development including standard multivariable linear regression and a machine learning approach (kernel-based regularized least squares (KRLS)) that learns the functional form of covariate impacts on ambient UFP concentrations from the data. The final models included parameters for population density, ambient temperature and wind speed, land use parameters (park space and open space), length of local roads and rail, and estimated annual average NOx emissions from traffic. The final multivariable linear regression model explained 62% of the spatial variation in ambient UFP concentrations whereas the KRLS model explained 79% of the variance. The KRLS model performed slightly better than the linear regression model when evaluated using an external dataset (R(2)=0.58 vs. 0.55) or a cross-validation procedure (R(2)=0.67 vs. 0.60). In general, our findings suggest that the KRLS approach may offer modest improvements in predictive performance compared to standard multivariable linear regression models used to estimate spatial variations in ambient UFPs. However, differences in predictive performance were not statistically significant when evaluated using the cross-validation procedure. PMID:26720396

  15. Cross-Validation of the Norwegian Teacher's Self-Efficacy Scale (NTSES)

    ERIC Educational Resources Information Center

    Avanzi, Lorenzo; Miglioretti, Massimo; Velasco, Veronica; Balducci, Cristian; Vecchio, Luca; Fraccaroli, Franco; Skaalvik, Einar M.

    2013-01-01

    The study assesses the psychometric properties of the Italian version of the Norwegian Teacher Self-Efficacy Scale--NTSES. Multiple group confirmatory factor analysis was used to explore the measurement invariance of the scale across two countries. Analyses performed on Italian and Norwegian samples confirmed a six-factor structure of the scale…

  16. Cross-Validation of the Implementation Leadership Scale (ILS) in Child Welfare Service Organizations.

    PubMed

    Finn, Natalie K; Torres, Elisa M; Ehrhart, Mark G; Roesch, Scott C; Aarons, Gregory A

    2016-08-01

    The Implementation Leadership Scale (ILS) is a brief, pragmatic, and efficient measure that can be used for research or organizational development to assess leader behaviors and actions that actively support effective implementation of evidence-based practices (EBPs). The ILS was originally validated with mental health clinicians. This study validates the ILS factor structure with providers in community-based organizations (CBOs) providing child welfare services. Participants were 214 service providers working in 12 CBOs that provide child welfare services. All participants completed the ILS, reporting on their immediate supervisor. Confirmatory factor analyses were conducted to examine the factor structure of the ILS. Internal consistency reliability and measurement invariance were also examined. Confirmatory factor analyses showed acceptable fit to the hypothesized first- and second-order factor structure. Internal consistency reliability was strong and there was partial measurement invariance for the first-order factor structure when comparing child welfare and mental health samples. The results support the use of the ILS to assess leadership for implementation of EBPs in child welfare organizations. PMID:27002137

  17. CROSS-VALIDATION OF LIPOMETER ESTIMATES OF BODY COMPOSITION: THE EFFECT OF GENDER AND SKIN COLOR

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Lipometer (v12.1e; Graz, Austria) uses light-emitting diodes (lambda=660 nm) and a photodetector to measure subcutaneous adipose tissue (SAT) and estimate percent body fat (%fat). Since, the Lipometer uses a light beam to measure SAT, it is possible that skin color may influence the results, cre...

  18. Cross-validation of marker configurations to measure pelvic kinematics in gait.

    PubMed

    Vogt, Lutz; Portscher, Martin; Brettmann, Kirsten; Pfeifer, Klaus; Banzer, Winfried

    2003-12-01

    External tracking of three-dimensional lumbar spine and pelvic oscillations is a method recently used in clinical gait analysis. This investigation validated the use of plate mounted marker configurations overlying the median sacral crest (S1) against single marker sets placed over the anterior and posterior superior iliac spine for the assessment of angular kinematic profiles of the pelvis during treadmill ambulation. Rotational pelvic movements of 12 asymptomatic male subjects were recorded by a 3D-ultrasonic measurement device using four single markers placed over the anterior and posterior superior iliac spine. Additionally, three external ultrasound markers were mounted on a rigid plate placed over S1. No significant differences (P > 0.05) for movement variability or range of motion between marker configurations could be obtained. It could be concluded that trucking of plate-mounted markers overlying S1 seems to be adequate for monitoring rotational pelvic motions in normal gait. PMID:14667951

  19. Embedded Performance Validity Measures with Postdeployment Veterans: Cross-Validation and Efficiency with Multiple Measures.

    PubMed

    Shura, Robert D; Miskey, Holly M; Rowland, Jared A; Yoash-Gantz, Ruth E; Denning, John H

    2016-01-01

    Embedded validity measures support comprehensive assessment of performance validity. The purpose of this study was to evaluate the accuracy of individual embedded measures and to reduce them to the most efficient combination. The sample included 212 postdeployment veterans (average age = 35 years, average education = 14 years). Thirty embedded measures were initially identified as predictors of Green's Word Memory Test (WMT) and were derived from the California Verbal Learning Test-Second Edition (CVLT-II), Conners' Continuous Performance Test-Second Edition (CPT-II), Trail Making Test, Stroop, Wisconsin Card Sorting Test-64, the Wechsler Adult Intelligence Scale-Third Edition Letter-Number Sequencing, Rey Complex Figure Test (RCFT), Brief Visuospatial Memory Test-Revised, and the Finger Tapping Test. Eight nonoverlapping measures with the highest area-under-the-curve (AUC) values were retained for entry into a logistic regression analysis. Embedded measure accuracy was also compared to cutoffs found in the existing literature. Twenty-one percent of the sample failed the WMT. Previously developed cutoffs for individual measures showed poor sensitivity (SN) in the current sample except for the CPT-II (Total Errors, SN = .41). The CVLT-II (Trials 1-5 Total) showed the best overall accuracy (AUC = .80). After redundant measures were statistically eliminated, the model included the RCFT (Recognition True Positives), CPT-II (Total Errors), and CVLT-II (Trials 1-5 Total) and increased overall accuracy compared with the CVLT-II alone (AUC = .87). The combination of just 3 measures from the CPT-II, CVLT-II, and RCFT was the most accurate/efficient in predicting WMT performance. PMID:26375185

  20. Cross-validation of strainmeter observations in Cascadia using GPS and tremor-derived slip distributions

    NASA Astrophysics Data System (ADS)

    Krogstad, R. D.; Schmidt, D. A.

    2013-12-01

    We address calibration and resolvability issues associated with strainmeter observations in Cascadia, with the ultimate goal of integrating strainmeters, GPS, and tremor observations of slow slip events. The distribution and propagation of episodic tremor and slow slip (ETS) events in Cascadia have primarily been characterized with observations from a broad network of GPS and seismic stations. Slip models spatially constrained by tremor are more heterogeneous than suggested by GPS. Geodetically derived slip distributions tend to be spatially and temporally smoothed and slightly offset from tremor distributions. These discrepancies may be real, or they may be a consequence of the resolution of GPS data or an artifact of the inversion methodology. Borehole strainmeters can potentially bridge the gap between GPS and seismic observations, given the greater sensitivity of the strainmeters. However, high noise values, the inclusion of non-tectonic artifacts, and difficulties in the calibration of the strainmeters have made deriving reliable information from strainmeters during slip events difficult. We examine the strainmeter time series of multiple stations for the 2010 to 2012 events in northern Washington. After accounting for nontectonic signals, such as atmospheric pressure, hydraulic loading and the curing of borehole grout, instrument drift and in situ calibrations using modeled earth tides account for a significant portion of the observational uncertainty of strain. We evaluate the strain observations of ETS events by predicting strain transients using synthetic forward slip models, GPS inversions, and slip models based on tremor distributions. To evaluate the magnitude of observed strain transients during slow slip events, we compare the strain observations with predicted strain transients derived from time-dependent GPS inversions. Preliminary results show that for well-behaved strainmeters (e.g. B003, B004, B005, etc.), the predicted strain is typically of similar duration and form, but may differ in amplitude by up to one order-of-magnitude. In an effort to reconcile the independent GPS, strainmeter, and seismic observations, we construct slip distributions using tremor occurrences as a proxy for localized slip on the plate interface. The magnitude of slip is then scaled by matching the predicted surface displacements derived from the tremor-based slip model with GPS observations of surface displacements. Once a slip model is obtained that satisfies the GPS and seismic data, the resultant strain predictions are evaluated in relation to the observed strain measurements. Preliminary results for the August 2012 event suggest that the observed strain at multiple stations occurs a couple days later than the strain predicted from the tremor-based slip model. Apart from the magnitude of strain change during an event, the sign of the strain change is also useful in constraining the along-dip extent and propagation of slow slip events. An instance where the sign of the observed strain differs from GPS-derived predictions likely indicates the slip distribution solution is either too narrow or too broad.

  1. Psychosocial factors and adjustment to chronic pain in spinal cord injury: replication and cross-validation.

    PubMed

    Molton, Ivan R; Stoelb, Brenda L; Jensen, Mark P; Ehde, Dawn M; Raichle, Katherine A; Cardenas, Diana D

    2009-01-01

    Recent studies have documented the importance of psychological factors in the experience of chronic pain in persons with spinal cord injury (SCI). The current study sought to replicate and extend previous work demonstrating associations among specific pain-related beliefs, coping, mental health, and pain outcomes in persons with SCI. A return-by-mail survey assessing psychological functioning and pain was completed by 130 individuals with SCI. Measures included short forms of the Survey of Pain Attitudes and the Chronic Pain Coping Inventory. After factor analysis, multiple regression was used to predict pain outcomes (psychological functioning and pain interference) after controlling for pain intensity. Results indicated that psychological factors, particularly beliefs about pain (including catastrophizing) and pain-related coping strategies (including passive coping), were significant predictors of pain outcomes and accounted for 21% to 25% of unique variance. Zero-order correlations suggested that the specific variables most closely associated with negative pain outcomes were perception of oneself as disabled, perceptions of low control over pain, and tendency to catastrophize. In general, negative attributions and coping were stronger predictors of pain adjustment than were positive ones. Results highlight the importance of psychological factors in understanding chronic pain in persons with SCI and provide further support for the biopsychosocial model. PMID:19533518

  2. The Adolescent Religious Coping Scale: Development, Validation, and Cross-Validation

    ERIC Educational Resources Information Center

    Bjorck, Jeffrey P.; Braese, Robert W.; Tadie, Joseph T.; Gililland, David D.

    2010-01-01

    Research literature on adolescent coping is growing, but typically such studies have ignored religious coping strategies and their potential impact on functioning. To address this lack, we developed the Adolescent Religious Coping Scale and used its seven subscales to examine the relationship between religious coping and emotional functioning. A…

  3. "Hits" (Not "Discussion Posts") Predict Student Success in Online Courses: A Double Cross-Validation Study

    ERIC Educational Resources Information Center

    Ramos, Cheryl; Yudko, Errol

    2008-01-01

    The efficacy of individual components of an online course on positive course outcome was examined via stepwise multiple regression analysis. Outcome was measured as the student's total score on all exams given during the course. The predictors were page hits, discussion posts, and discussion reads. The vast majority of the variance of outcome was…

  4. Basic Cross-Validation: Using the "Holdout" Method To Assess the Generalizability of Results.

    ERIC Educational Resources Information Center

    Oxford, Raquel M.; Daniel, Larry G.

    2001-01-01

    Uses a heuristic example, data from K. Holzinger and F. Swineford (1939) to illustrate the "holdout" method to assess the generalizability of results in multiple regression. Regression weighted from one data subset are used to compare estimated dependent variable scores from the opposite subset. (SLD)

  5. Psychophysiological Associations between Chronic Tinnitus and Sleep: A Cross Validation of Tinnitus and Insomnia Questionnaires

    PubMed Central

    Schecklmann, Martin; Pregler, Maximilian; Kreuzer, Peter M.; Poeppl, Timm B.; Lehner, Astrid; Crönlein, Tatjana; Wetter, Thomas C.; Frank, Elmar; Landgrebe, Michael; Langguth, Berthold

    2015-01-01

    Background. The aim of the present study was to assess the prevalence of insomnia in chronic tinnitus and the association of tinnitus distress and sleep disturbance. Methods. We retrospectively analysed data of 182 patients with chronic tinnitus who completed the Tinnitus Questionnaire (TQ) and the Regensburg Insomnia Scale (RIS). Descriptive comparisons with the validation sample of the RIS including exclusively patients with primary/psychophysiological insomnia, correlation analyses of the RIS with TQ scales, and principal component analyses (PCA) in the tinnitus sample were performed. TQ total score was corrected for the TQ sleep items. Results. Prevalence of insomnia was high in tinnitus patients (76%) and tinnitus distress correlated with sleep disturbance (r = 0.558). TQ sleep subscore correlated with the RIS sum score (r = 0.690). PCA with all TQ and RIS items showed one sleep factor consisting of all RIS and the TQ sleep items. PCA with only TQ sleep and RIS items showed sleep- and tinnitus-specific factors. The sleep factors (only RIS items) were sleep depth and fearful focusing. The TQ sleep items represented tinnitus-related sleep problems. Discussion. Chronic tinnitus and primary insomnia are highly related and might share similar psychological and neurophysiological mechanisms leading to impaired sleep quality. PMID:26583109

  6. Computational Steroidogenesis Model To Predict Biochemical Responses to Endocrine Active Chemicals: Model Development and Cross Validation

    EPA Science Inventory

    Steroids, which have an important role in a wide range of physiological processes, are synthesized primarily in the gonads and adrenal glands through a series of enzyme-mediated reactions. The activity of steroidogenic enzymes can be altered by a variety of endocrine active chem...

  7. Initial Factor Analysis and Cross-Validation of the Multicultural Teaching Competencies Inventory

    ERIC Educational Resources Information Center

    Prieto, Loreto R.

    2012-01-01

    The Multicultural Teaching Competencies Inventory (MTCI) contains items based on the tri-parte model of cultural competencies established by Sue and associates (Sue et al., 1992, 1982, 2003) that identify multicultural Awareness, Knowledge, and Skill as central characteristics of a culturally sensitive professional. The development and validation…

  8. The Severe Sexual Sadism Scale: cross-validation and scale properties.

    PubMed

    Mokros, Andreas; Schilling, Frank; Eher, Reinhard; Nitschke, Joachim

    2012-09-01

    The Severe Sexual Sadism Scale (SSSS) is a screening device for the file-based assessment of forensically relevant sexual sadism. The SSSS consists of 11 dichotomous (yes/no) items that code behavioral indicators of severe sexual sadism within sexual offenses. Based on an Austrian sample of 105 sexual offenders, the present study replicated the 1-dimensional scale structure of the SSSS, as evidenced by confirmatory factor analysis. More specifically, the scale was commensurate with the 1-parameter logistic test model (Rasch model). Reliability was estimated to be good. Criterion validity for the clinical diagnosis of sexual sadism was good. With a cutoff value of 7 points, sensitivity and specificity were estimated at 56% and 90%, respectively. PMID:22142424

  9. Cross-Validation of a Psychological Test Battery to Detect Faked Insanity.

    ERIC Educational Resources Information Center

    Schretlen, David; And Others

    1992-01-01

    Eight predictor variables from the Minnesota Multiphasic Personality Inventory, the Bender Gestalt, and a Malingering Scale differentiated 20 prison inmates faking insanity from 40 nonfaking controls. A second experiment with 22 substance abusers faking insanity and 20 schizophrenics also supports the use of the test battery to detect faking. (SLD)

  10. Cross-Validation of the Emotion Awareness Questionnaire for Children in Three Populations

    ERIC Educational Resources Information Center

    Lahaye, Magali; Mikolajczak, Moira; Rieffe, Carolien; Villanueva, Lidon; Van Broeck, Nady; Bodart, Eddy; Luminet, Olivier

    2011-01-01

    The main aim of the present study was to examine the cross-cultural equivalence of a newly developed questionnaire, the Emotion Awareness Questionnaire (EAQ30) that assesses emotional awareness of children through self-report. Participants were recruited in three countries: the Netherlands (N = 665), Spain (N = 464), and Belgium (N = 707),…

  11. Cross-Validation of a PACER Prediction Equation for Assessing Aerobic Capacity in Hungarian Youth

    ERIC Educational Resources Information Center

    Saint-Maurice, Pedro F.; Welk, Gregory J.; Finn, Kevin J.; Kaj, Mónika

    2015-01-01

    Purpose: The purpose of this article was to evaluate the validity of the Progressive Aerobic Cardiovascular and Endurance Run (PACER) test in a sample of Hungarian youth. Method: Approximately 500 participants (aged 10-18 years old) were randomly selected across Hungary to complete both laboratory (maximal treadmill protocol) and field assessments…

  12. Evaluating the Replicability of Sample Results: A Tutorial of Double Cross-Validation Methods

    ERIC Educational Resources Information Center

    Guan, Jianmin; Xiang, Ping; Keating, Xiaofen Deng

    2004-01-01

    Although replication is important to the validity of a study and is endorsed by more and more scholars, few researchers in kinesiology attend to this issue. Some researchers may believe that statistical significance and effect size are the most important statistical issues in their research and thereby may have ignored the importance of result…

  13. The African American Acculturation Scale II: Cross-Validation and Short Form.

    ERIC Educational Resources Information Center

    Landrine, Hope; Klonoff, Elizabeth A.

    1995-01-01

    Studied African American culture, using a new, shortened, 33-item African American Acculturation Scale (AAAS-33) to assess the scale's validity and reliability. Comparisons between the original form and AAAS-33 reveal high correlations, however, the longer form may be sensitive to some beliefs, practices, and attitudes not assessed by the short…

  14. Repeated holdout Cross-Validation of Model to Estimate Risk of Lyme Disease by Landscape Attributes

    EPA Science Inventory

    We previously modeled Lyme disease (LD) risk at the landscape scale; here we evaluate the model's overall goodness-of-fit using holdout validation. Landscapes were characterized within road-bounded analysis units (AU). Observed LD cases (obsLD) were ascertained per AU. Data were ...

  15. Cross-validation of spaceborne radar and ground polarimetric radar observations

    NASA Astrophysics Data System (ADS)

    Bolen, Steven Matthew

    There is great potential for spaceborne weather radar to make significant observations of the precipitating medium on global scales. The Tropical Rainfall Mapping Mission (TRMM) is the first mission dedicated to measuring rainfall in the tropics from space using radar. The Precipitation Radar (PR) is one of several instruments aboard the TRMM satellite that is operating in a nearly circular orbit at 350 km altitude and 35 degree inclination. The PR is a single frequency Ku-band instrument that is designed to yield information about the vertical storm structure so as to gain insight into the intensity and distribution of rainfall. Attenuation effects on PR measurements, however, can be significant, which can be as high as 10--15 dB. This can seriously impair the accuracy of rain rate retrieval algorithms derived from PR returns. Direct inter-comparison of meteorological measurements between space and ground radar observations can be used to evaluate spaceborne processing algorithms. Though conceptually straightforward, this can be a challenging task. Differences in viewing aspects between space and earth point observations, propagation frequencies, resolution volume size and time synchronization mismatch between measurements can contribute to direct point-by-point inter-comparison errors. The problem is further complicated by spatial geometric distortions induced into the space-based observations caused by the movements and attitude perturbations of the spacecraft itself. A method is developed to align space and ground radar observations so that a point-by-point inter-comparison of measurements can be made. Ground-based polarimetric observations are used to estimate the attenuation of PR signal returns along individual PR beams, and a technique is formulated to determine the true PR return from GR measurements via theoretical modeling of specific attenuation (k) at PR wavelength with ground-based S-band radar observations. The statistical behavior of the parameters of a three-parameter gamma raindrop size distribution (RSD) model is also presented along with analysis of the initial PR RSD model on rain rate estimates. Data is taken from the TExas and FLorida UNderflights (TEFLUN-B) and the TRMM Large-scale Biosphere Atmosphere (LBA) field campaigns. Data from the Kwajalein KPOL radar is also used to validate the algorithms developed.

  16. Cross-validation of Predicted Wechsler Memory Scale--Revised Scores.

    ERIC Educational Resources Information Center

    Axelrod, Bradley N.; And Others

    1996-01-01

    Equations for prorating the Wechsler Memory Scale--Revised General Memory (GM) and Delayed Recall (DR) index scores were confirmed in a clinical sample of 258 patients. These prediction equations for the GM and DR summary scores have validity for patient samples similar to those of the present study. (SLD)

  17. Confirmatory Factor Analysis of the Assessment for Living and Learning Scale: A Cross-Validation Investigation.

    ERIC Educational Resources Information Center

    Denzine, Gypsy M.; Kowalski, Gerard J.

    2002-01-01

    The Assessment for Living and Learning (ALL; G.M. Denzine, 1994, 1996) measures college students' perceptions of the academic climate in their residence hall. Confirmatory factor analyses results reveal that the data did not provide an adequate fit to the measurement model underlying the ALL. A revised model was tested and is recommended for use.…

  18. Categories of Counselors Behavior as Defined from Cross-Validated Factoral Descriptions.

    ERIC Educational Resources Information Center

    Zimmer, Jules M.; And Others

    The intent of the study was to explore and categorize counselor responses. Three separate filmed presentations were shown. Participating with the same client were Albert Ellis, Frederick Perls, and Carl Rogers. At the beginning of each counselor statement, a number was inserted in sequence and remained on the videotape until completion of that…

  19. Bias of Exploratory and Cross-Validated DETECT Index under Unidimensionality

    ERIC Educational Resources Information Center

    Monahan, Patrick O.; Stump, Timothy E.; Finch, Holmes; Hambleton, Ronald K.

    2007-01-01

    DETECT is a nonparametric "full" dimensionality assessment procedure that clusters dichotomously scored items into dimensions and provides a DETECT index of magnitude of multidimensionality. Four factors (test length, sample size, item response theory [IRT] model, and DETECT index) were manipulated in a Monte Carlo study of bias, standard error,…

  20. The Bland-Altman Method Should Not Be Used in Regression Cross-Validation Studies

    ERIC Educational Resources Information Center

    O'Connor, Daniel P.; Mahar, Matthew T.; Laughlin, Mitzi S.; Jackson, Andrew S.

    2011-01-01

    The purpose of this study was to demonstrate the bias in the Bland-Altman (BA) limits of agreement method when it is used to validate regression models. Data from 1,158 men were used to develop three regression equations to estimate maximum oxygen uptake (R[superscript 2] = 0.40, 0.61, and 0.82, respectively). The equations were evaluated in a…

  1. Cross-Validation of the PAI Negative Distortion Scale for Feigned Mental Disorders: A Research Report

    ERIC Educational Resources Information Center

    Rogers, Richard; Gillard, Nathan D.; Wooley, Chelsea N.; Kelsey, Katherine R.

    2013-01-01

    A major strength of the Personality Assessment Inventory (PAI) is its systematic assessment of response styles, including feigned mental disorders. Recently, Mogge, Lepage, Bell, and Ragatz developed and provided the initial validation for the Negative Distortion Scale (NDS). Using rare symptoms as its detection strategy for feigning, the…

  2. Cross-Validation of Mental Health Recovery Measures in a Hong Kong Chinese Sample

    ERIC Educational Resources Information Center

    Ye, Shengquan; Pan, Jia-Yan; Wong, Daniel Fu Keung; Bola, John Robert

    2013-01-01

    Objectives: The concept of recovery has begun shifting mental health service delivery from a medical perspective toward a client-centered recovery orientation. This shift is also beginning in Hong Kong, but its development is hampered by a dearth of available measures in Chinese. Method: This article translates two measures of recovery (mental…

  3. The Severe Sexual Sadism Scale: Cross-Validation and Scale Properties

    ERIC Educational Resources Information Center

    Mokros, Andreas; Schilling, Frank; Eher, Reinhard; Nitschke, Joachim

    2012-01-01

    The Severe Sexual Sadism Scale (SSSS) is a screening device for the file-based assessment of forensically relevant sexual sadism. The SSSS consists of 11 dichotomous (yes/no) items that code behavioral indicators of severe sexual sadism within sexual offenses. Based on an Austrian sample of 105 sexual offenders, the present study replicated the…

  4. Correlates of Achievement: Prediction and Cross-Validation for Intermediate Grade Levels.

    ERIC Educational Resources Information Center

    Marshall, Jon C.; Powers, Jerry M.

    A study was conducted to: (1) determine the simple and multiple correlation coefficients between selected educational/personal variables and academic achievement at intermediate grade levels as measured by the Iowa Tests of Basic Skills; (2) determine the multiple linear regression equations for predicting individual student achievement as…

  5. Cross-Validation of Levenson's Psychopathy Scale in a Sample of Federal Female Inmates

    ERIC Educational Resources Information Center

    Brinkley, Chad A.; Diamond, Pamela M.; Magaletta, Philip R.; Heigel, Caron P.

    2008-01-01

    Levenson, Kiehl, and Fitzpatrick's Self-Report Psychopathy Scale (LSRPS) is evaluated to determine the factor structure and concurrent validity of the instrument among 430 federal female inmates. Confirmatory factor analysis fails to validate the expected 2-factor structure. Subsequent exploratory factor analysis reveals a 3-factor structure…

  6. An extensive cocktail approach for rapid risk assessment of in vitro CYP450 direct reversible inhibition by xenobiotic exposure.

    PubMed

    Spaggiari, Dany; Daali, Youssef; Rudaz, Serge

    2016-07-01

    Acute exposure to environmental factors strongly affects the metabolic activity of cytochrome P450 (P450). As a consequence, the risk of interaction could be increased, modifying the clinical outcomes of a medication. Because toxic agents cannot be administered to humans for ethical reasons, in vitro approaches are therefore essential to evaluate their impact on P450 activities. In this work, an extensive cocktail mixture was developed and validated for in vitro P450 inhibition studies using human liver microsomes (HLM). The cocktail comprised eleven P450-specific probe substrates to simultaneously assess the activities of the following isoforms: 1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, 2J2 and subfamily 3A. The high selectivity and sensitivity of the developed UHPLC-MS/MS method were critical for the success of this methodology, whose main advantages are: (i) the use of eleven probe substrates with minimized interactions, (ii) a low HLM concentration, (iii) fast incubation (5min) and (iv) the use of metabolic ratios as microsomal P450 activities markers. This cocktail approach was successfully validated by comparing the obtained IC50 values for model inhibitors with those generated with the conventional single probe methods. Accordingly, reliable inhibition values could be generated 10-fold faster using a 10-fold smaller amount of HLM compared to individual assays. This approach was applied to assess the P450 inhibition potential of widespread insecticides, namely, chlorpyrifos, fenitrothion, methylparathion and profenofos. In all cases, P450 2B6 was the most affected with IC50 values in the nanomolar range. For the first time, mixtures of these four insecticides incubated at low concentrations showed a cumulative inhibitory in vitro effect on P450 2B6. PMID:27105555

  7. Approachability & Visibility

    ERIC Educational Resources Information Center

    Ruder, Robert

    2006-01-01

    To be approachable and visible may be one of the greatest lessons a retired middle level principal ever learned. Being approachable is an expectation of the principalship. Keeping the office door shut or restricting or limiting talk time with students, teachers, or parents sends a strong message to those constituents: "I've got more important…

  8. Fully automated 3D prostate central gland segmentation in MR images: a LOGISMOS based approach

    NASA Astrophysics Data System (ADS)

    Yin, Yin; Fotin, Sergei V.; Periaswamy, Senthil; Kunz, Justin; Haldankar, Hrishikesh; Muradyan, Naira; Turkbey, Baris; Choyke, Peter

    2012-02-01

    One widely accepted classification of a prostate is by a central gland (CG) and a peripheral zone (PZ). In some clinical applications, separating CG and PZ from the whole prostate is useful. For instance, in prostate cancer detection, radiologist wants to know in which zone the cancer occurs. Another application is for multiparametric MR tissue characterization. In prostate T2 MR images, due to the high intensity variation between CG and PZ, automated differentiation of CG and PZ is difficult. Previously, we developed an automated prostate boundary segmentation system, which tested on large datasets and showed good performance. Using the results of the pre-segmented prostate boundary, in this paper, we proposed an automated CG segmentation algorithm based on Layered Optimal Graph Image Segmentation of Multiple Objects and Surfaces (LOGISMOS). The designed LOGISMOS model contained both shape and topology information during deformation. We generated graph cost by training classifiers and used coarse-to-fine search. The LOGISMOS framework guarantees optimal solution regarding to cost and shape constraint. A five-fold cross-validation approach was applied to training dataset containing 261 images to optimize the system performance and compare with a voxel classification based reference approach. After the best parameter settings were found, the system was tested on a dataset containing another 261 images. The mean DSC of 0.81 for the test set indicates that our approach is promising for automated CG segmentation. Running time for the system is about 15 seconds.

  9. Cysteine peptidases from Phytomonas serpens: biochemical and immunological approaches.

    PubMed

    Elias, Camila G R; Aor, Ana Carolina; Valle, Roberta S; d'Avila-Levy, Claudia M; Branquinha, Marta H; Santos, André L S

    2009-12-01

    Phytomonas serpens, a phytoflagellate trypanosomatid, shares common antigens with Trypanosoma cruzi. In the present work, we compared the hydrolytic capability of cysteine peptidases in both trypanosomatids. Trypanosoma cruzi epimastigotes presented a 10-fold higher efficiency in hydrolyzing the cysteine peptidase substrate Z-Phe-Arg-AMC than P. serpens promastigotes. Moreover, two weak cysteine-type gelatinolytic activities were detected in P. serpens, while a strong 50-kDa cysteine peptidase was observed in T. cruzi. Cysteine peptidase activities were detected at twofold higher levels in the cytoplasmic fraction when compared with the membrane-rich or the content released from P. serpens. The cysteine peptidase secreted by P. serpens cleaved several proteinaceous substrates. Corroborating these findings, the cellular distribution of the cruzipain-like molecules in P. serpens was attested through immunocytochemistry analysis. Gold particles were observed in all cellular compartments, including the cytoplasm, plasma membrane, flagellum, flagellar membrane and flagellar pocket. Interestingly, some gold particles were visualized free in the flagellar pocket, suggesting the release of the cruzipain-like molecule. The antigenic properties of the cruzipain-like molecules of P. serpens were also analyzed. Interestingly, sera from chagasic patients recognized both cellular and extracellular antigens of P. serpens, including the cruzipain-like molecule. These results point to the use of P. serpens antigens, especially the cruzipain-like cysteine-peptidases, as an alternative vaccination approach to T. cruzi infection. PMID:19780820

  10. COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS.

    PubMed

    Regenbogen, Sam; Wilkins, Angela D; Lichtarge, Olivier

    2016-01-01

    Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses. PMID:26776170

  11. COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS

    PubMed Central

    REGENBOGEN, SAM; WILKINS, ANGELA D.; LICHTARGE, OLIVIER

    2015-01-01

    Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses. PMID:26776170

  12. Supervised learning for neural manifold using spatiotemporal brain activity

    NASA Astrophysics Data System (ADS)

    Kuo, Po-Chih; Chen, Yong-Sheng; Chen, Li-Fen

    2015-12-01

    Objective. Determining the means by which perceived stimuli are compactly represented in the human brain is a difficult task. This study aimed to develop techniques for the construction of the neural manifold as a representation of visual stimuli. Approach. We propose a supervised locally linear embedding method to construct the embedded manifold from brain activity, taking into account similarities between corresponding stimuli. In our experiments, photographic portraits were used as visual stimuli and brain activity was calculated from magnetoencephalographic data using a source localization method. Main results. The results of 10 × 10-fold cross-validation revealed a strong correlation between manifolds of brain activity and the orientation of faces in the presented images, suggesting that high-level information related to image content can be revealed in the brain responses represented in the manifold. Significance. Our experiments demonstrate that the proposed method is applicable to investigation into the inherent patterns of brain activity.

  13. Prediction of substrate-enzyme-product interaction based on molecular descriptors and physicochemical properties.

    PubMed

    Niu, Bing; Huang, Guohua; Zheng, Linfeng; Wang, Xueyuan; Chen, Fuxue; Zhang, Yuhui; Huang, Tao

    2013-01-01

    It is important to correctly and efficiently predict the interaction of substrate-enzyme and to predict their product in metabolic pathway. In this work, a novel approach was introduced to encode substrate/product and enzyme molecules with molecular descriptors and physicochemical properties, respectively. Based on this encoding method, KNN was adopted to build the substrate-enzyme-product interaction network. After selecting the optimal features that are able to represent the main factors of substrate-enzyme-product interaction in our prediction, totally 160 features out of 290 features were attained which can be clustered into ten categories: elemental analysis, geometry, chemistry, amino acid composition, predicted secondary structure, hydrophobicity, polarizability, solvent accessibility, normalized van der Waals volume, and polarity. As a result, our predicting model achieved an MCC of 0.423 and an overall prediction accuracy of 89.1% for 10-fold cross-validation test. PMID:24455714

  14. Future Performance Trend Indicators: A Current Value Approach to Human Resources Accounting. Report III. Multivariate Predictions of Organizational Performance Across Time.

    ERIC Educational Resources Information Center

    Pecorella, Patricia A.; Bowers, David G.

    Multiple regression in a double cross-validated design was used to predict two performance measures (total variable expense and absence rate) by multi-month period in five industrial firms. The regressions do cross-validate, and produce multiple coefficients which display both concurrent and predictive effects, peaking 18 months to two years…

  15. A novel approach of computer-aided detection of focal ground-glass opacity in 2D lung CT images

    NASA Astrophysics Data System (ADS)

    Li, Song; Liu, Xiabi; Yang, Ali; Pang, Kunpeng; Zhou, Chunwu; Zhao, Xinming; Zhao, Yanfeng

    2013-02-01

    Focal Ground-Glass Opacity (fGGO) plays an important role in diagnose of lung cancers. This paper proposes a novel approach for detecting fGGOs in 2D lung CT images. The approach consists of two stages: extracting regions of interests (ROIs) and labeling each ROI as fGGO or non-fGGO. In the first stage, we use the techniques of Otsu thresholding and mathematical morphology to segment lung parenchyma from lung CT images and extract ROIs in lung parenchyma. In the second stage, a Bayesian classifier is constructed based on the Gaussian mixture Modeling (GMM) of the distribution of visual features of fGGOs to fulfill ROI identification. The parameters in the classifier are estimated from training data by the discriminative learning method of Max-Min posterior Pseudo-probabilities (MMP). A genetic algorithm is further developed to select compact and discriminative features for the classifier. We evaluated the proposed fGGO detection approach through 5-fold cross-validation experiments on a set of 69 lung CT scans that contain 70 fGGOs. The proposed approach achieves the detection sensitivity of 85.7% at the false positive rate of 2.5 per scan, which proves its effectiveness. We also demonstrate the usefulness of our genetic algorithm based feature selection method and MMP discriminative learning method through comparing them with without-selection strategy and Support Vector Machines (SVMs), respectively, in the experiments.

  16. On approaches to analyze the sensitivity of simulated hydrologic fluxes to model parameters in the community land model

    SciTech Connect

    Bao, Jie; Hou, Zhangshuan; Huang, Maoyi; Liu, Ying

    2015-12-04

    Here, effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash-Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalized linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.

  17. On approaches to analyze the sensitivity of simulated hydrologic fluxes to model parameters in the community land model

    DOE PAGESBeta

    Bao, Jie; Hou, Zhangshuan; Huang, Maoyi; Liu, Ying

    2015-12-04

    Here, effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash-Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalizedmore » linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.« less

  18. HOW LONG WILL MY MOUSE LIVE? MACHINE LEARNING APPROACHES FOR PREDICTION OF MOUSE LIFESPAN

    PubMed Central

    Swindell, William R.; Harper, James M.; Miller, Richard A.

    2009-01-01

    Prediction of individual lifespan based upon characteristics evaluated at middle-age represents a challenging objective for aging research. In this study, we used machine learning algorithms to construct models that predict lifespan in a stock of genetically heterogeneous mice. Lifespan-prediction accuracy of 22 algorithms was evaluated using a cross-validation approach, in which models were trained and tested with distinct subsets of data. Using a combination of body weight and T-cell subset measures evaluated before two years of age, we show that the lifespan quartile to which an individual mouse belongs can be predicted with an accuracy of 35.3% (± 0.10%). This result provides a new benchmark for the development of lifespan-predictive models, but improvement can be expected through identification of new predictor variables and development of computational approaches. Future work in this direction can provide tools for aging research and will shed light on associations between phenotypic traits and longevity. PMID:18840793

  19. The typology of Irish hard-rock aquifers based on an integrated hydrogeological and geophysical approach

    NASA Astrophysics Data System (ADS)

    Comte, Jean-Christophe; Cassidy, Rachel; Nitsche, Janka; Ofterdinger, Ulrich; Pilatova, Katarina; Flynn, Raymond

    2012-12-01

    Groundwater flow in hard-rock aquifers is strongly controlled by the characteristics and distribution of structural heterogeneity. A methodology for catchment-scale characterisation is presented, based on the integration of complementary, multi-scale hydrogeological, geophysical and geological approaches. This was applied to three contrasting catchments underlain by metamorphic rocks in the northern parts of Ireland (Republic of Ireland and Northern Ireland, UK). Cross-validated surface and borehole geophysical investigations confirm the discontinuous overburden, lithological compartmentalisation of the bedrock and important spatial variations of the weathered bedrock profiles at macro-scale. Fracture analysis suggests that the recent (Alpine) tectonic fabric exerts strong control on the internal aquifer structure at meso-scale, which is likely to impact on the anisotropy of aquifer properties. The combination of the interpretation of depth-specific hydraulic-test data with the structural information provided by geophysical tests allows characterisation of the hydrodynamic properties of the identified aquifer units. Regionally, the distribution of hydraulic conductivities can be described by inverse power laws specific to the aquifer litho-type. Observed groundwater flow directions reflect this multi-scale structure. The proposed integrated approach applies widely available investigative tools to identify key dominant structures controlling groundwater flow, characterising the aquifer type for each catchment and resolving the spatial distribution of relevant aquifer units and associated hydrodynamic parameters.

  20. A prediction model for Atlantic named storm frequency using a year-by-year increment approach

    NASA Astrophysics Data System (ADS)

    Fan, K.

    2010-12-01

    This paper presents a year-by-year incremental approach to forecasting the Atlantic named storm frequency (ATSF) for the hurricane season (June 1- November 30). The year-by-year increase or decrease in the ATSF is first forecasted to yield a net ATSF prediction. Six key predictors for the year-by-year increment in the number of Atlantic named tropical storms have been identified that are available before May 1. The forecast model for the year-by-year increment of the ATSF is first established using a multi-linear regression method based on data taken from the years of 1965-1999, and the forecast model of the ATSF is then derived. The prediction model for the ATSF shows good prediction skill. Compared to the climatological average mean absolute error (MAE) of 4.1, the percentage improvement in the MAE is 29 % for the hindcast period of 2004-2009 and 46 % for the cross-validation test from 1985-2009 (26 yrs). This work demonstrates that the year-by-year incremental approach has the potential to improve operational forecasting skill for the ATSF.

  1. A Market-Basket Approach to Predict the Acute Aquatic Toxicity of Munitions and Energetic Materials.

    PubMed

    Burgoon, Lyle D

    2016-06-01

    An ongoing challenge in chemical production, including the production of insensitive munitions and energetics, is the ability to make predictions about potential environmental hazards early in the process. To address this challenge, a quantitative structure activity relationship model was developed to predict acute fathead minnow toxicity of insensitive munitions and energetic materials. Computational predictive toxicology models like this one may be used to identify and prioritize environmentally safer materials early in their development. The developed model is based on the Apriori market-basket/frequent itemset mining approach to identify probabilistic prediction rules using chemical atom-pairs and the lethality data for 57 compounds from a fathead minnow acute toxicity assay. Lethality data were discretized into four categories based on the Globally Harmonized System of Classification and Labelling of Chemicals. Apriori identified toxicophores for categories two and three. The model classified 32 of the 57 compounds correctly, with a fivefold cross-validation classification rate of 74 %. A structure-based surrogate approach classified the remaining 25 chemicals correctly at 48 %. This result is unsurprising as these 25 chemicals were fairly unique within the larger set. PMID:27091326

  2. A new approach for cuttings identification using laser induced breakdown spectroscopy

    NASA Astrophysics Data System (ADS)

    Wang, Zhen-nan; Tian, Ye; Li, Ying; Zheng, Rong-er

    2011-06-01

    In the process of oil exploration and development, it becomes difficult to identify the lithology of cuttings due to the small size of cutting particles produced by extensively used Polycrystalline Diamond Compact (PDC) drill bit. Laser Induced Breakdown Spectroscopy (LIBS) is an appealing technique compared with many other conventional analysis methods due to its simple set-up, on-line, real time, stand off and multi-element analytical capabilities. In this paper, a newly developed approach for cuttings identification using laser-induced breakdown spectroscopy was introduced. Principal component analysis (PCA) and partial least squares (PLS) were applied to analyze LIBS spectra of three drill cuttings to perform cuttings identification. With the purpose of reducing workload and improving predictive accuracy, 23 characteristic spectra ranges were extracted as "fingerprints" from each integrated LIBS spectrum. Leave-one-out cross-validation method (LOO-CV) was used to evaluate the predictive capability of this approach. All the LIBS spectra were identified correctly under a lax criterion. The obtained preliminary results demonstrated the potential feasibility of cutting identification using LIBS in combination with chemometric methods.

  3. A Systematic Approach to Predicting Spring Force for Sagittal Craniosynostosis Surgery.

    PubMed

    Zhang, Guangming; Tan, Hua; Qian, Xiaohua; Zhang, Jian; Li, King; David, Lisa R; Zhou, Xiaobo

    2016-05-01

    Spring-assisted surgery (SAS) can effectively treat scaphocephaly by reshaping crania with the appropriate spring force. However, it is difficult to accurately estimate spring force without considering biomechanical properties of tissues. This study presents and validates a reliable system to accurately predict the spring force for sagittal craniosynostosis surgery. The authors randomly chose 23 patients who underwent SAS and had been followed for at least 2 years. An elastic model was designed to characterize the biomechanical behavior of calvarial bone tissue for each individual. After simulating the contact force on accurate position of the skull strip with the springs, the finite element method was applied to calculating the stress of each tissue node based on the elastic model. A support vector regression approach was then used to model the relationships between biomechanical properties generated from spring force, bone thickness, and the change of cephalic index after surgery. Therefore, for a new patient, the optimal spring force can be predicted based on the learned model with virtual spring simulation and dynamic programming approach prior to SAS. Leave-one-out cross-validation was implemented to assess the accuracy of our prediction. As a result, the mean prediction accuracy of this model was 93.35%, demonstrating the great potential of this model as a useful adjunct for preoperative planning tool. PMID:27159856

  4. Evaluating the Reliability of the Stream Tracer Approach to Characterize Stream-Subsurface Water Exchange

    NASA Astrophysics Data System (ADS)

    Harvey, Judson W.; Wagner, Brian J.; Bencala, Kenneth E.

    1996-08-01

    Stream water was locally recharged into shallow groundwater flow paths that returned to the stream (hyporheic exchange) in St. Kevin Gulch, a Rocky Mountain stream in Colorado contaminated by acid mine drainage. Two approaches were used to characterize hyporheic exchange: sub-reach-scale measurement of hydraulic heads and hydraulic conductivity to compute streambed fluxes (hydrometric approach) and reachscale modeling of in-stream solute tracer injections to determine characteristic length and timescales of exchange with storage zones (stream tracer approach). Subsurface data were the standard of comparison used to evaluate the reliability of the stream tracer approach to characterize hyporheic exchange. The reach-averaged hyporheic exchange flux (1.5 mL s-1 m-1), determined by hydrometric methods, was largest when stream base flow was low (10 L s-1); hyporheic exchange persisted when base flow was 10-fold higher, decreasing by approximately 30%. Reliability of the stream tracer approach to detect hyporheic exchange was assessed using first-order uncertainty analysis that considered model parameter sensitivity. The stream tracer approach did not reliably characterize hyporheic exchange at high base flow: the model was apparently more sensitive to exchange with surface water storage zones than with the hyporheic zone. At low base flow the stream tracer approach reliably characterized exchange between the stream and gravel streambed (timescale of hours) but was relatively insensitive to slower exchange with deeper alluvium (timescale of tens of hours) that was detected by subsurface measurements. The stream tracer approach was therefore not equally sensitive to all timescales of hyporheic exchange. We conclude that while the stream tracer approach is an efficient means to characterize surface-subsurface exchange, future studies will need to more routinely consider decreasing sensitivities of tracer methods at higher base flow and a potential bias toward

  5. Evaluating the reliability of the stream tracer approach to characterize stream-subsurface water exchange

    USGS Publications Warehouse

    Harvey, J.W.; Wagner, B.J.; Bencala, K.E.

    1996-01-01

    Stream water was locally recharged into shallow groundwater flow paths that returned to the stream (hyporheic exchange) in St. Kevin Gulch, a Rocky Mountain stream in Colorado contaminated by acid mine drainage. Two approaches were used to characterize hyporheic exchange: sub- reach-scale measurement of hydraulic heads and hydraulic conductivity to compute streambed fluxes (hydrometric approach) and reachscale modeling of in- stream solute tracer injections to determine characteristic length and timescales of exchange with storage zones (stream tracer approach). Subsurface data were the standard of comparison used to evaluate the reliability of the stream tracer approach to characterize hyporheic exchange. The reach-averaged hyporheic exchange flux (1.5 mL s-1 m-1), determined by hydrometric methods, was largest when stream base flow was low (10 L s-1); hyporheic exchange persisted when base flow was 10- fold higher, decreasing by approximately 30%. Reliability of the stream tracer approach to detect hyporheic exchange was assessed using first- order uncertainty analysis that considered model parameter sensitivity. The stream tracer approach did not reliably characterize hyporheic exchange at high base flow: the model was apparently more sensitive to exchange with surface water storage zones than with the hyporheic zone. At low base flow the stream tracer approach reliably characterized exchange between the stream and gravel streambed (timescale of hours) but was relatively insensitive to slower exchange with deeper alluvium (timescale of tens of hours) that was detected by subsurface measurements. The stream tracer approach was therefore not equally sensitive to all timescales of hyporheic exchange. We conclude that while the stream tracer approach is an efficient means to characterize surface-subsurface exchange, future studies will need to more routinely consider decreasing sensitivities of tracer methods at higher base flow and a potential bias toward

  6. The Object-analogue approach for probabilistic forecasting

    NASA Astrophysics Data System (ADS)

    Frediani, M. E.; Hopson, T. M.; Anagnostou, E. N.; Hacker, J.

    2015-12-01

    The object-analogue is a new method to estimate forecast uncertainty and to derive probabilistic predictions of gridded forecast fields over larger regions rather than point locations. The method has been developed for improving the forecast of 10-meter wind speed over the northeast US, and it can be extended to other forecast variables, vertical levels, and other regions. The object-analogue approach combines the analog post-processing technique (Hopson 2005; Hamill 2006; Delle Monache 2011) with the Method for Object-based Diagnostic Evaluation (MODE) for forecast verification (Davis et al 2006a, b). Originally, MODE is used to verify mainly precipitation forecasts using features of a forecast region represented by an object. The analog technique is used to reduce the NWP systematic and random errors of a gridded forecast field. In this study we use MODE-derived objects to characterize the wind fields forecasts into attributes such as object area, centroid location, and intensity percentiles, and apply the analogue concept to these objects. The object-analogue method uses a database of objects derived from reforecasts and their respective reanalysis. Given a real-time forecast field, it searches the database and selects the top-ranked objects with the most similar set of attributes using the MODE fuzzy logic algorithm for object matching. The attribute probabilities obtained with the set of selected object-analogues are used to derive a multi-layer probabilistic prediction. The attribute probabilities are combined into three uncertainty layers that address the main concerns of most applications: location, area, and magnitude. The multi-layer uncertainty can be weighted and combined or used independently in such that it provides a more accurate prediction, adjusted according to the application interest. In this study we present preliminary results of the object-analogue method. Using a database with one hundred storms we perform a leave-one-out cross-validation to

  7. A practical and automated approach to large area forest disturbance mapping with remote sensing.

    PubMed

    Ozdogan, Mutlu

    2014-01-01

    In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover

  8. A Practical and Automated Approach to Large Area Forest Disturbance Mapping with Remote Sensing

    PubMed Central

    Ozdogan, Mutlu

    2014-01-01

    In this paper, I describe a set of procedures that automate forest disturbance mapping using a pair of Landsat images. The approach is built on the traditional pair-wise change detection method, but is designed to extract training data without user interaction and uses a robust classification algorithm capable of handling incorrectly labeled training data. The steps in this procedure include: i) creating masks for water, non-forested areas, clouds, and cloud shadows; ii) identifying training pixels whose value is above or below a threshold defined by the number of standard deviations from the mean value of the histograms generated from local windows in the short-wave infrared (SWIR) difference image; iii) filtering the original training data through a number of classification algorithms using an n-fold cross validation to eliminate mislabeled training samples; and finally, iv) mapping forest disturbance using a supervised classification algorithm. When applied to 17 Landsat footprints across the U.S. at five-year intervals between 1985 and 2010, the proposed approach produced forest disturbance maps with 80 to 95% overall accuracy, comparable to those obtained from traditional approaches to forest change detection. The primary sources of mis-classification errors included inaccurate identification of forests (errors of commission), issues related to the land/water mask, and clouds and cloud shadows missed during image screening. The approach requires images from the peak growing season, at least for the deciduous forest sites, and cannot readily distinguish forest harvest from natural disturbances or other types of land cover change. The accuracy of detecting forest disturbance diminishes with the number of years between the images that make up the image pair. Nevertheless, the relatively high accuracies, little or no user input needed for processing, speed of map production, and simplicity of the approach make the new method especially practical for forest cover

  9. Defining the Ischemic Penumbra using Magnetic Resonance Oxygen Metabolic Index

    PubMed Central

    An, Hongyu; Ford, Andria L.; Chen, Yasheng; Zhu, Hongtu; Ponisio, Rosana; Kumar, Gyanendra; Shanechi, Amirali Modir; Khoury, Naim; Vo, Katie D.; Williams, Jennifer; Derdeyn, Colin P.; Diringer, Michael N.; Panagos, Peter; Powers, William J.; Lee, Jin-Moo; Lin, Weili

    2015-01-01

    Background and Purpose Penumbral biomarkers promise to individualize treatment windows in acute ischemic stroke. We used a novel MRI approach which measures oxygen metabolic index (OMI), a parameter closely related to PET-derived cerebral metabolic rate of oxygen utilization, to derive a pair of ischemic thresholds: (1) an irreversible-injury threshold which differentiates ischemic core from penumbra and (2) a reversible-injury threshold which differentiates penumbra from tissue not-at-risk for infarction. Methods Forty acute ischemic stroke patients underwent MRI at three time-points after stroke onset: < 4.5 hours (for OMI threshold derivation), 6 hours (to determine reperfusion status), and 1 month (for infarct probability determination). A dynamic susceptibility contrast method measured CBF, and an asymmetric spin echo sequence measured OEF, to derive OMI (OMI=CBF*OEF). Putative ischemic threshold pairs were iteratively tested using a computation-intensive method to derive infarct probabilities in three tissue groups defined by the thresholds (core, penumbra, and not-at-risk tissue). An optimal threshold pair was chosen based on its ability to predict: infarction in the core, reperfusion-dependent survival in the penumbra, and survival in not-at-risk tissue. The predictive abilities of the thresholds were then tested within the same cohort using a 10-fold cross-validation method. Results The optimal OMI ischemic thresholds were found to be 0.28 and 0.42 of normal values in the contralateral hemisphere. Using the 10-fold cross-validation method, median infarct probabilities were 90.6% for core, 89.7% for non-reperfused penumbra, 9.95% for reperfused penumbra, and 6.28% for not-at-risk tissue. Conclusions OMI thresholds, derived using voxel-based, reperfusion-dependent infarct probabilities, delineated the ischemic penumbra with high predictive ability. These thresholds will require confirmation in an independent patient sample. PMID:25721017

  10. Differential Label-free Quantitative Proteomic Analysis of Shewanella oneidensis Cultured under Aerobic and Suboxic Conditions by Accurate Mass and Time Tag Approach

    SciTech Connect

    Fang, Ruihua; Elias, Dwayne A.; Monroe, Matthew E.; Shen, Yufeng; McIntosh, Martin; Wang, Pei; Goddard, Carrie D.; Callister, Stephen J.; Moore, Ronald J.; Gorby, Yuri A.; Adkins, Joshua N.; Fredrickson, Jim K.; Lipton, Mary S.; Smith, Richard D.

    2006-04-01

    We describe the application of liquid chromatography coupled to mass spectrometry (LC/MS) without the use of stable isotope labeling for differential quantitative proteomics analysis of whole cell lysates of Shewanella oneidensis MR-1 cultured under aerobic and sub-oxic conditions. Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) was used to initially identify peptide sequences, and LC coupled to Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR) was used to confirm these identifications, as well as measure relative peptide abundances. 2343 peptides, covering 668 proteins were identified with high confidence and quantified. Among these proteins, a subset of 56 changed significantly using statistical approaches such as SAM, while another subset of 56 that were annotated as performing housekeeping functions remained essentially unchanged in relative abundance. Numerous proteins involved in anaerobic energy metabolism exhibited up to a 10-fold increase in relative abundance when S. oneidensis is transitioned from aerobic to sub-oxic conditions.

  11. A Multiscale Approach to InSAR Time Series Analysis

    NASA Astrophysics Data System (ADS)

    Simons, M.; Hetland, E. A.; Muse, P.; Lin, Y.; Dicaprio, C. J.

    2009-12-01

    We describe progress in the development of MInTS (Multiscale analysis of InSAR Time Series), an approach to constructed self-consistent time-dependent deformation observations from repeated satellite-based InSAR images of a given region. MInTS relies on a spatial wavelet decomposition to permit the inclusion of distance based spatial correlations in the observations while maintaining computational tractability. In essence, MInTS allows one to considers all data at the same time as opposed to one pixel at a time, thereby taking advantage of both spatial and temporal characteristics of the deformation field. This approach also permits a consistent treatment of all data independent of the presence of localized holes due to unwrapping issues in any given interferogram. Specifically, the presence of holes is accounted for through a weighting scheme that accounts for the extent of actual data versus the area of holes associated with any given wavelet. In terms of the temporal representation, we have the flexibility to explicitly parametrize known processes that are expected to contribute to a given set of observations (e.g., co-seismic steps and post-seismic transients, secular variations, seasonal oscillations, etc.). Our approach also allows for the temporal parametrization to include a set of general functions in order to account for unexpected processes. We allow for various forms of model regularization using a cross-validation approach to select penalty parameters. We also experiment with the use of sparsity inducing regularization as a way to select from a large dictionary of time functions. The multiscale analysis allows us to consider various contributions (e.g., orbit errors) that may affect specific scales but not others. The methods described here are all embarrassingly parallel and suitable for implementation on a cluster computer. We demonstrate the use of MInTS using a large suite of ERS-1/2 and Envisat interferograms for Long Valley Caldera, and validate

  12. Vocal individuality cues in the African penguin (Spheniscus demersus): a source-filter theory approach.

    PubMed

    Favaro, Livio; Gamba, Marco; Alfieri, Chiara; Pessani, Daniela; McElligott, Alan G

    2015-01-01

    The African penguin is a nesting seabird endemic to southern Africa. In penguins of the genus Spheniscus vocalisations are important for social recognition. However, it is not clear which acoustic features of calls can encode individual identity information. We recorded contact calls and ecstatic display songs of 12 adult birds from a captive colony. For each vocalisation, we measured 31 spectral and temporal acoustic parameters related to both source and filter components of calls. For each parameter, we calculated the Potential of Individual Coding (PIC). The acoustic parameters showing PIC ≥ 1.1 were used to perform a stepwise cross-validated discriminant function analysis (DFA). The DFA correctly classified 66.1% of the contact calls and 62.5% of display songs to the correct individual. The DFA also resulted in the further selection of 10 acoustic features for contact calls and 9 for display songs that were important for vocal individuality. Our results suggest that studying the anatomical constraints that influence nesting penguin vocalisations from a source-filter perspective, can lead to a much better understanding of the acoustic cues of individuality contained in their calls. This approach could be further extended to study and understand vocal communication in other bird species. PMID:26602001

  13. Calibrating regionally downscaled precipitation over Norway through quantile-based approaches

    NASA Astrophysics Data System (ADS)

    Bolin, David; Frigessi, Arnoldo; Guttorp, Peter; Haug, Ola; Orskaug, Elisabeth; Scheel, Ida; Wallin, Jonas

    2016-06-01

    Dynamical downscaling of earth system models is intended to produce high-resolution climate information at regional to local scales. Current models, while adequate for describing temperature distributions at relatively small scales, struggle when it comes to describing precipitation distributions. In order to better match the distribution of observed precipitation over Norway, we consider approaches to statistical adjustment of the output from a regional climate model when forced with ERA-40 reanalysis boundary conditions. As a second step, we try to correct downscalings of historical climate model runs using these transformations built from downscaled ERA-40 data. Unless such calibrations are successful, it is difficult to argue that scenario-based downscaled climate projections are realistic and useful for decision makers. We study both full quantile calibrations and several different methods that correct individual quantiles separately using random field models. Results based on cross-validation show that while a full quantile calibration is not very effective in this case, one can correct individual quantiles satisfactorily if the spatial structure in the data are accounted for. Interestingly, different methods are favoured depending on whether ERA-40 data or historical climate model runs are adjusted.

  14. Neural network approach to quantum-chemistry data: Accurate prediction of density functional theory energies

    NASA Astrophysics Data System (ADS)

    Balabin, Roman M.; Lomakina, Ekaterina I.

    2009-08-01

    Artificial neural network (ANN) approach has been applied to estimate the density functional theory (DFT) energy with large basis set using lower-level energy values and molecular descriptors. A total of 208 different molecules were used for the ANN training, cross validation, and testing by applying BLYP, B3LYP, and BMK density functionals. Hartree-Fock results were reported for comparison. Furthermore, constitutional molecular descriptor (CD) and quantum-chemical molecular descriptor (QD) were used for building the calibration model. The neural network structure optimization, leading to four to five hidden neurons, was also carried out. The usage of several low-level energy values was found to greatly reduce the prediction error. An expected error, mean absolute deviation, for ANN approximation to DFT energies was 0.6±0.2 kcal mol-1. In addition, the comparison of the different density functionals with the basis sets and the comparison of multiple linear regression results were also provided. The CDs were found to overcome limitation of the QD. Furthermore, the effective ANN model for DFT/6-311G(3df,3pd) and DFT/6-311G(2df,2pd) energy estimation was developed, and the benchmark results were provided.

  15. A Bayesian Approach to the Design and Analysis of Computer Experiments

    SciTech Connect

    Currin, C.

    1988-01-01

    We consider the problem of designing and analyzing experiments for prediction of the function y(f), t {element_of} T, where y is evaluated by means of a computer code (typically by solving complicated equations that model a physical system), and T represents the domain of inputs to the code. We use a Bayesian approach, in which uncertainty about y is represented by a spatial stochastic process (random function); here we restrict attention to stationary Gaussian processes. The posterior mean function can be used as an interpolating function, with uncertainties given by the posterior standard deviations. Instead of completely specifying the prior process, we consider several families of priors, and suggest some cross-validational methods for choosing one that performs relatively well on the function at hand. As a design criterion, we use the expected reduction in the entropy of the random vector y (T*), where T* {contained_in} T is a given finite set of ''sites'' (input configurations) at which predictions are to be made. We describe an exchange algorithm for constructing designs that are optimal with respect to this criterion. To demonstrate the use of these design and analysis methods, several examples are given, including one experiment on a computer model of a thermal energy storage device and another on an integrated circuit simulator.

  16. Multivariate approach to gill pathology in European sea bass after experimental exposure to cadmium and terbuthylazine.

    PubMed

    Manera, Maurizio; Sayyaf Dezfuli, Bahram; DePasquale, Joseph A; Giari, Luisa

    2016-07-01

    The combined use of guided quantitative expert analysis and of multivariate exploratory data analysis is reported as a robust, sensitive and sufficiently specific approach to study European sea bass gill secondary lamellar pathology after exposure to incremental doses of cadmium and terbuthylazine up to 48h. The following elementary pathological findings were considered: "epithelial lifting", "epithelial shrinkage", "epithelial swelling", "pillar cells coarctation", "pillar cells detachment", "channels fusion", "chloride cells swelling", and "chloride cells invasion". The relative spatial extension was determined according to exposure class and data were analyzed by means of canonical correspondence analysis (CCA), linear discriminant analysis (LDA) and canonical variates analysis (CVA). Histologically and ultrastructurally, cellular shrinkage/coarctation prevailed in cadmium exposed lamellae, whereas cellular swelling and epithelial lifting were predominant in terbuthylazine exposed lamellae compared to unexposed fish. Both CCA and CVA permit a good graphical data grouping according to exposure classes by means of the convex hull minimum polygons. This also reveals exposure dose and time gradients in CCA plot. Accordingly, epithelial swelling and epithelial shrinkage were comparatively associated to higher exposure time, whereas epithelial shrinkage and pillar cells coarctation were comparatively associated to higher exposure dose. LDA with only "epithelial shrinkage", "epithelial swelling" and "pillar cells coarctation" in the model classified correctly 87.5% of the cross-validated cases. A possible pathogenetic relationship between the discriminant elementary lesions and the toxic mode of action at the cellular level of both cadmium and terbuthylazine is also discussed. PMID:27057996

  17. A Hybrid BPSO-CGA Approach for Gene Selection and Classification of Microarray Data

    PubMed Central

    Chuang, Li-Yeh; Yang, Cheng-Huei; Li, Jung-Chike

    2012-01-01

    Abstract Microarray analysis promises to detect variations in gene expressions, and changes in the transcription rates of an entire genome in vivo. Microarray gene expression profiles indicate the relative abundance of mRNA corresponding to the genes. The selection of relevant genes from microarray data poses a formidable challenge to researchers due to the high-dimensionality of features, multiclass categories being involved, and the usually small sample size. A classification process is often employed which decreases the dimensionality of the microarray data. In order to correctly analyze microarray data, the goal is to find an optimal subset of features (genes) which adequately represents the original set of features. A hybrid method of binary particle swarm optimization (BPSO) and a combat genetic algorithm (CGA) is to perform the microarray data selection. The K-nearest neighbor (K-NN) method with leave-one-out cross-validation (LOOCV) served as a classifier. The proposed BPSO-CGA approach is compared to ten microarray data sets from the literature. The experimental results indicate that the proposed method not only effectively reduce the number of genes expression level, but also achieves a low classification error rate. PMID:21210743

  18. Vocal individuality cues in the African penguin (Spheniscus demersus): a source-filter theory approach

    PubMed Central

    Favaro, Livio; Gamba, Marco; Alfieri, Chiara; Pessani, Daniela; McElligott, Alan G.

    2015-01-01

    The African penguin is a nesting seabird endemic to southern Africa. In penguins of the genus Spheniscus vocalisations are important for social recognition. However, it is not clear which acoustic features of calls can encode individual identity information. We recorded contact calls and ecstatic display songs of 12 adult birds from a captive colony. For each vocalisation, we measured 31 spectral and temporal acoustic parameters related to both source and filter components of calls. For each parameter, we calculated the Potential of Individual Coding (PIC). The acoustic parameters showing PIC ≥ 1.1 were used to perform a stepwise cross-validated discriminant function analysis (DFA). The DFA correctly classified 66.1% of the contact calls and 62.5% of display songs to the correct individual. The DFA also resulted in the further selection of 10 acoustic features for contact calls and 9 for display songs that were important for vocal individuality. Our results suggest that studying the anatomical constraints that influence nesting penguin vocalisations from a source-filter perspective, can lead to a much better understanding of the acoustic cues of individuality contained in their calls. This approach could be further extended to study and understand vocal communication in other bird species. PMID:26602001

  19. Prediction of community prevalence of human onchocerciasis in the Amazonian onchocerciasis focus: Bayesian approach.

    PubMed Central

    Carabin, Hélène; Escalona, Marisela; Marshall, Clare; Vivas-Martínez, Sarai; Botto, Carlos; Joseph, Lawrence; Basáñez, María-Gloria

    2003-01-01

    OBJECTIVE: To develop a Bayesian hierarchical model for human onchocerciasis with which to explore the factors that influence prevalence of microfilariae in the Amazonian focus of onchocerciasis and predict the probability of any community being at least mesoendemic (>20% prevalence of microfilariae), and thus in need of priority ivermectin treatment. METHODS: Models were developed with data from 732 individuals aged > or =15 years who lived in 29 Yanomami communities along four rivers of the south Venezuelan Orinoco basin. The models' abilities to predict prevalences of microfilariae in communities were compared. The deviance information criterion, Bayesian P-values, and residual values were used to select the best model with an approximate cross-validation procedure. FINDINGS: A three-level model that acknowledged clustering of infection within communities performed best, with host age and sex included at the individual level, a river-dependent altitude effect at the community level, and additional clustering of communities along rivers. This model correctly classified 25/29 (86%) villages with respect to their need for priority ivermectin treatment. CONCLUSION: Bayesian methods are a flexible and useful approach for public health research and control planning. Our model acknowledges the clustering of infection within communities, allows investigation of links between individual- or community-specific characteristics and infection, incorporates additional uncertainty due to missing covariate data, and informs policy decisions by predicting the probability that a new community is at least mesoendemic. PMID:12973640

  20. TransportTP: A two-phase classification approach for membrane transporter prediction and characterization

    PubMed Central

    2009-01-01

    Background Membrane transporters play crucial roles in living cells. Experimental characterization of transporters is costly and time-consuming. Current computational methods for transporter characterization still require extensive curation efforts, especially for eukaryotic organisms. We developed a novel genome-scale transporter prediction and characterization system called TransportTP that combined homology-based and machine learning methods in a two-phase classification approach. First, traditional homology methods were employed to predict novel transporters based on sequence similarity to known classified proteins in the Transporter Classification Database (TCDB). Second, machine learning methods were used to integrate a variety of features to refine the initial predictions. A set of rules based on transporter features was developed by machine learning using well-curated proteomes as guides. Results In a cross-validation using the yeast proteome for training and the proteomes of ten other organisms for testing, TransportTP achieved an equivalent recall and precision of 81.8%, based on TransportDB, a manually annotated transporter database. In an independent test using the Arabidopsis proteome for training and four recently sequenced plant proteomes for testing, it achieved a recall of 74.6% and a precision of 73.4%, according to our manual curation. Conclusions TransportTP is the most effective tool for eukaryotic transporter characterization up to date. PMID:20003433

  1. Identification of Real MicroRNA Precursors with a Pseudo Structure Status Composition Approach

    PubMed Central

    Liu, Bin; Fang, Longyun; Liu, Fule; Wang, Xiaolong; Chen, Junjie; Chou, Kuo-Chen

    2015-01-01

    Containing about 22 nucleotides, a micro RNA (abbreviated miRNA) is a small non-coding RNA molecule, functioning in transcriptional and post-transcriptional regulation of gene expression. The human genome may encode over 1000 miRNAs. Albeit poorly characterized, miRNAs are widely deemed as important regulators of biological processes. Aberrant expression of miRNAs has been observed in many cancers and other disease states, indicating they are deeply implicated with these diseases, particularly in carcinogenesis. Therefore, it is important for both basic research and miRNA-based therapy to discriminate the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops). Particularly, with the avalanche of RNA sequences generated in the postgenomic age, it is highly desired to develop computational sequence-based methods in this regard. Here two new predictors, called “iMcRNA-PseSSC” and “iMcRNA-ExPseSSC”, were proposed for identifying the human pre-microRNAs by incorporating the global or long-range structure-order information using a way quite similar to the pseudo amino acid composition approach. Rigorous cross-validations on a much larger and more stringent newly constructed benchmark dataset showed that the two new predictors (accessible at http://bioinformatics.hitsz.edu.cn/iMcRNA/) outperformed or were highly comparable with the best existing predictors in this area. PMID:25821974

  2. PDP-CON: prediction of domain/linker residues in protein sequences using a consensus approach.

    PubMed

    Chatterjee, Piyali; Basu, Subhadip; Zubek, Julian; Kundu, Mahantapas; Nasipuri, Mita; Plewczynski, Dariusz

    2016-04-01

    The prediction of domain/linker residues in protein sequences is a crucial task in the functional classification of proteins, homology-based protein structure prediction, and high-throughput structural genomics. In this work, a novel consensus-based machine-learning technique was applied for residue-level prediction of the domain/linker annotations in protein sequences using ordered/disordered regions along protein chains and a set of physicochemical properties. Six different classifiers-decision tree, Gaussian naïve Bayes, linear discriminant analysis, support vector machine, random forest, and multilayer perceptron-were exhaustively explored for the residue-level prediction of domain/linker regions. The protein sequences from the curated CATH database were used for training and cross-validation experiments. Test results obtained by applying the developed PDP-CON tool to the mutually exclusive, independent proteins of the CASP-8, CASP-9, and CASP-10 databases are reported. An n-star quality consensus approach was used to combine the results yielded by different classifiers. The average PDP-CON accuracy and F-measure values for the CASP targets were found to be 0.86 and 0.91, respectively. The dataset, source code, and all supplementary materials for this work are available at https://cmaterju.org/cmaterbioinfo/ for noncommercial use. PMID:26969678

  3. PancreApp: An Innovative Approach to Computational Individualization of Nutritional Therapy in Chronic Gastrointestinal Disorders.

    PubMed

    Stawiski, Konrad; Strzałka, Alicja; Puła, Anna; Bijakowski, Krzysztof

    2015-01-01

    Medical nutrition therapy has a pivotal role in the management of chronic gastrointestinal disorders, like chronic pancreatitis, inflammatory bowel diseases (Leśniowski-Crohn's disease and ulcerative colitis) or irritable bowel syndrome. The aim of this study is to develop, deploy and evaluate an interactive application for Windows and Android operating systems, which could serve as a digital diet diary and as an analysis and a prediction tool both for the patient and the doctor. The software is gathering details about patients' diet and associated fettle in order to estimate fettle change after future meals, specifically for an individual patient. In this paper we have described the process of idea development and application design, feasibility assessment using a phone survey, a preliminary evaluation on 6 healthy individuals and early results of a clinical trial, which is still an ongoing study. Results suggest that applied approximative approach (Shepard's method of 6-dimensional metric interpolation) has a potential to predict the fettle accurately; as shown in leave-one-out cross-validation (LOOCV). PMID:26262064

  4. A Metabolomic Approach to Target Compounds from the Asteraceae Family for Dual COX and LOX Inhibition

    PubMed Central

    Chagas-Paula, Daniela A.; Zhang, Tong; Da Costa, Fernando B.; Edrada-Ebel, RuAngelie

    2015-01-01

    The application of metabolomics in phytochemical analysis is an innovative strategy for targeting active compounds from a complex plant extract. Species of the Asteraceae family are well-known to exhibit potent anti-inflammatory (AI) activity. Dual inhibition of the enzymes COX-1 and 5-LOX is essential for the treatment of several inflammatory diseases, but there is not much investigation reported in the literature for natural products. In this study, 57 leaf extracts (EtOH-H2O 7:3, v/v) from different genera and species of the Asteraceae family were tested against COX-1 and 5-LOX while HPLC-ESI-HRMS analysis of the extracts indicated high diversity in their chemical compositions. Using O2PLS-DA (R2 > 0.92; VIP > 1 and positive Y-correlation values), dual inhibition potential of low-abundance metabolites was determined. The O2PLS-DA results exhibited good validation values (cross-validation = Q2 > 0.7 and external validation = P2 > 0.6) with 0% of false positive predictions. The metabolomic approach determined biomarkers for the required biological activity and detected active compounds in the extracts displaying unique mechanisms of action. In addition, the PCA data also gave insights on the chemotaxonomy of the family Asteraceae across its diverse range of genera and tribes. PMID:26184333

  5. A glucose-sensing contact lens: a new approach to noninvasive continuous physiological glucose monitoring

    NASA Astrophysics Data System (ADS)

    Badugu, Ramachandram; Lakowicz, Joseph R.; Geddes, Chris D.

    2004-06-01

    We have developed a new technology for the non-invasive continuous monitoring of tear glucose using a daily use, disposable contact lens, embedded with sugar-sensing boronic acid containing fluorophores. Our findings show that our approach may be suitable for the continuous monitoring of tear glucose levels in the range 50 - 500 μM, which track blood glucose levels that are typically ~ 5-10 fold higher. We initially tested the sensing concept with well-established, previously published, boronic acid probes and the results could conclude the used probes, with higher pKa values, are almost insensitive toward glucose within the contact lens, attributed to the low pH and polarity inside the lens. Subsequently, we have developed a range of probes based on the quinolinium backbone, having considerably lower pKa values, which enables them to be suitable to sense the physiological glucose in the acidic pH contact lens. Herein we describe the results based on our findings towards the development of glucose sensing contact lens and therefore an approach to non-invasive continuous monitoring of tear glucose using a contact lens.

  6. Trypanothione Reductase: A Target Protein for a Combined In Vitro and In Silico Screening Approach

    PubMed Central

    Garoff, Linnéa; Noack, Sandra; Krauth-Siegel, R. Luise; Selzer, Paul M.

    2015-01-01

    With the goal to identify novel trypanothione reductase (TR) inhibitors, we performed a combination of in vitro and in silico screening approaches. Starting from a highly diverse compound set of 2,816 compounds, 21 novel TR inhibiting compounds could be identified in the initial in vitro screening campaign against T. cruzi TR. All 21 in vitro hits were used in a subsequent similarity search-based in silico screening on a database containing 200,000 physically available compounds. The similarity search resulted in a data set containing 1,204 potential TR inhibitors, which was subjected to a second in vitro screening campaign leading to 61 additional active compounds. This corresponds to an approximately 10-fold enrichment compared to the initial pure in vitro screening. In total, 82 novel TR inhibitors with activities down to the nM range could be identified proving the validity of our combined in vitro/in silico approach. Moreover, the four most active compounds, showing IC50 values of <1 μM, were selected for determining the inhibitor constant. In first on parasites assays, three compounds inhibited the proliferation of bloodstream T. brucei cell line 449 with EC50 values down to 2 μM. PMID:26042772

  7. A Hybrid Approach Using Case-Based Reasoning and Rule-Based Reasoning to Support Cancer Diagnosis: A Pilot Study.

    PubMed

    Saraiva, Renata M; Bezerra, João; Perkusich, Mirko; Almeida, Hyggo; Siebra, Clauirton

    2015-01-01

    Recently there has been an increasing interest in applying information technology to support the diagnosis of diseases such as cancer. In this paper, we present a hybrid approach using case-based reasoning (CBR) and rule-based reasoning (RBR) to support cancer diagnosis. We used symptoms, signs, and personal information from patients as inputs to our model. To form specialized diagnoses, we used rules to define the input factors' importance according to the patient's characteristics. The model's output presents the probability of the patient having a type of cancer. To carry out this research, we had the approval of the ethics committee at Napoleão Laureano Hospital, in João Pessoa, Brazil. To define our model's cases, we collected real patient data at Napoleão Laureano Hospital. To define our model's rules and weights, we researched specialized literature and interviewed health professional. To validate our model, we used K-fold cross validation with the data collected at Napoleão Laureano Hospital. The results showed that our approach is an effective CBR system to diagnose cancer. PMID:26262174

  8. Identification of interface residues in protease-inhibitor and antigen-antibody complexes: a support vector machine approach

    PubMed Central

    Honavar, Vasant; Dobbs, Drena

    2010-01-01

    In this paper, we describe a machine learning approach for sequence-based prediction of protein-protein interaction sites. A support vector machine (SVM) classifier was trained to predict whether or not a surface residue is an interface residue (i.e., is located in the protein-protein interaction surface), based on the identity of the target residue and its ten sequence neighbors. Separate classifiers were trained on proteins from two categories of complexes, antibody-antigen and protease-inhibitor. The effectiveness of each classifier was evaluated using leave-one-out (jack-knife) cross-validation. Interface and non-interface residues were classified with relatively high sensitivity (82.3% and 78.5%) and specificity (81.0% and 77.6%) for proteins in the antigen-antibody and protease-inhibitor complexes, respectively. The correlation between predicted and actual labels was 0.430 and 0.462, indicating that the method performs substantially better than chance (zero correlation). Combined with recently developed methods for identification of surface residues from sequence information, this offers a promising approach to predict residues involved in protein-protein interactions from sequence information alone. PMID:20526429

  9. Novel Approaches for the Accumulation of Oxygenated Intermediates to Multi-Millimolar Concentrations

    PubMed Central

    Krebs, Carsten; Dassama, Laura M. K.; Matthews, Megan L.; Jiang, Wei; Price, John C.; Korboukh, Victoria; Li, Ning; Bollinger, J. Martin

    2012-01-01

    Metalloenzymes that utilize molecular oxygen as a co-substrate catalyze a wide variety of chemically difficult oxidation reactions. Significant insight into the reaction mechanisms of these enzymes can be obtained by the application of a combination of rapid kinetic and spectroscopic methods to the direct structural characterization of intermediate states. A key limitation of this approach is the low aqueous solubility (< 2 mM) of the co-substrate, O2, which undergoes further dilution (typically by one-third or one-half) upon initiation of reactions by rapid-mixing. This situation imposes a practical upper limit on [O2] (and therefore on the concentration of reactive intermediate(s) that can be rapidly accumulated) of ∼1-1.3 mM in such experiments as they are routinely carried out. However, many spectroscopic methods benefit from or require significantly greater concentrations of the species to be studied. To overcome this problem, we have recently developed two new approaches for the preparation of samples of oxygenated intermediates: (1) direct oxygenation of reduced metalloenzymes using gaseous O2 and (2) the in situ generation of O2 from chlorite catalyzed by the enzyme chlorite dismutase (Cld). Whereas the former method is applicable only to intermediates with half lives of several minutes, owing to the sluggishness of transport of O2 across the gas-liquid interface, the latter approach has been successfully applied to trap several intermediates at high concentration and purity by the freeze-quench method. The in situ approach permits generation of a pulse of at least 5 mM O2 within ∼ 1 ms and accumulation of O2 to effective concentrations of up to ∼ 11 mM (i.e. ∼ 10-fold greater than by the conventional approach). The use of these new techniques for studies of oxygenases and oxidases is discussed. PMID:24368870

  10. In silico approach to screen compounds active against parasitic nematodes of major socio-economic importance

    PubMed Central

    2011-01-01

    Background Infections due to parasitic nematodes are common causes of morbidity and fatality around the world especially in developing nations. At present however, there are only three major classes of drugs for treating human nematode infections. Additionally the scientific knowledge on the mechanism of action and the reason for the resistance to these drugs is poorly understood. Commercial incentives to design drugs that are endemic to developing countries are limited therefore, virtual screening in academic settings can play a vital role is discovering novel drugs useful against neglected diseases. In this study we propose to build robust machine learning model to classify and screen compounds active against parasitic nematodes. Results A set of compounds active against parasitic nematodes were collated from various literature sources including PubChem while the inactive set was derived from DrugBank database. The support vector machine (SVM) algorithm was used for model development, and stratified ten-fold cross validation was used to evaluate the performance of each classifier. The best results were obtained using the radial basis function kernel. The SVM method achieved an accuracy of 81.79% on an independent test set. Using the model developed above, we were able to indentify novel compounds with potential anthelmintic activity. Conclusion In this study, we successfully present the SVM approach for predicting compounds active against parasitic nematodes which suggests the effectiveness of computational approaches for antiparasitic drug discovery. Although, the accuracy obtained is lower than the previously reported in a similar study but we believe that our model is more robust because we intentionally employed stringent criteria to select inactive dataset thus making it difficult for the model to classify compounds. The method presents an alternative approach to the existing traditional methods and may be useful for predicting hitherto novel anthelmintic

  11. A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases.

    PubMed

    Berenstein, Ariel José; Magariños, María Paula; Chernomoretz, Ariel; Agüero, Fernán

    2016-01-01

    Drug development for neglected diseases has been historically hampered due to lack of market incentives. The advent of public domain resources containing chemical information from high throughput screenings is changing the landscape of drug discovery for these diseases. In this work we took advantage of data from extensively studied organisms like human, mouse, E. coli and yeast, among others, to develop a novel integrative network model to prioritize and identify candidate drug targets in neglected pathogen proteomes, and bioactive drug-like molecules. We modeled genomic (proteins) and chemical (bioactive compounds) data as a multilayer weighted network graph that takes advantage of bioactivity data across 221 species, chemical similarities between 1.7 105 compounds and several functional relations among 1.67 105 proteins. These relations comprised orthology, sharing of protein domains, and shared participation in defined biochemical pathways. We showcase the application of this network graph to the problem of prioritization of new candidate targets, based on the information available in the graph for known compound-target associations. We validated this strategy by performing a cross validation procedure for known mouse and Trypanosoma cruzi targets and showed that our approach outperforms classic alignment-based approaches. Moreover, our model provides additional flexibility as two different network definitions could be considered, finding in both cases qualitatively different but sensible candidate targets. We also showcase the application of the network to suggest targets for orphan compounds that are active against Plasmodium falciparum in high-throughput screens. In this case our approach provided a reduced prioritization list of target proteins for the query molecules and showed the ability to propose new testable hypotheses for each compound. Moreover, we found that some predictions highlighted by our network model were supported by independent

  12. A Multilayer Network Approach for Guiding Drug Repositioning in Neglected Diseases

    PubMed Central

    Chernomoretz, Ariel; Agüero, Fernán

    2016-01-01

    Drug development for neglected diseases has been historically hampered due to lack of market incentives. The advent of public domain resources containing chemical information from high throughput screenings is changing the landscape of drug discovery for these diseases. In this work we took advantage of data from extensively studied organisms like human, mouse, E. coli and yeast, among others, to develop a novel integrative network model to prioritize and identify candidate drug targets in neglected pathogen proteomes, and bioactive drug-like molecules. We modeled genomic (proteins) and chemical (bioactive compounds) data as a multilayer weighted network graph that takes advantage of bioactivity data across 221 species, chemical similarities between 1.7 105 compounds and several functional relations among 1.67 105 proteins. These relations comprised orthology, sharing of protein domains, and shared participation in defined biochemical pathways. We showcase the application of this network graph to the problem of prioritization of new candidate targets, based on the information available in the graph for known compound-target associations. We validated this strategy by performing a cross validation procedure for known mouse and Trypanosoma cruzi targets and showed that our approach outperforms classic alignment-based approaches. Moreover, our model provides additional flexibility as two different network definitions could be considered, finding in both cases qualitatively different but sensible candidate targets. We also showcase the application of the network to suggest targets for orphan compounds that are active against Plasmodium falciparum in high-throughput screens. In this case our approach provided a reduced prioritization list of target proteins for the query molecules and showed the ability to propose new testable hypotheses for each compound. Moreover, we found that some predictions highlighted by our network model were supported by independent

  13. Curriculum: Which Approach?

    ERIC Educational Resources Information Center

    Rulloda, Rudolfo Barcena

    2010-01-01

    Curriculum has two major approaches, technical and scientific approach and the nontechnical-nonscientific approach. Both are different and distinct. Schools need to distinguish which approach is suited for their students.

  14. Estimation of extreme daily precipitation: comparison between regional and geostatistical approaches.

    NASA Astrophysics Data System (ADS)

    Hellies, Matteo; Deidda, Roberto; Langousis, Andreas

    2016-04-01

    addition, KUD avoids separation of the study region in contiguous areas, allowing for a continuous representation of the spatial variation of distribution parameters. Comparisons based on different error metrics, conducted with the method of cross-validation, show better performance of the geostatistical approach relative to the regional one. In addition, the geostatistical approach better represents local features of the spatial variability of rainfall, while overcoming the issue of abrupt shifts of distribution parameters at the boundaries between contiguous homogeneous regions.

  15. Network-based biomarkers enhance classical approaches to prognostic gene expression signatures

    PubMed Central

    2014-01-01

    Background Classical approaches to predicting patient clinical outcome via gene expression information are primarily based on differential expression of unrelated genes (single-gene approaches) or genes related by, for example, biologic pathway or function (gene-sets). Recently, network-based approaches utilising interaction information between genes have emerged. An open problem is whether such approaches add value to the more traditional methods of signature modelling. We explored this question via comparison of the most widely employed single-gene, gene-set, and network-based methods, using gene expression microarray data from two different cancers: melanoma and ovarian. We considered two kinds of network approaches. The first of these identifies informative genes using gene expression and network connectivity information combined, the latter drawn from prior knowledge of protein-protein interactions. The second approach focuses on identification of informative sub-networks (small networks of interacting proteins, again from prior knowledge networks). For all methods we performed 100 rounds of 5-fold cross-validation under 3 different classifiers. For network-based approaches, we considered two different protein-protein interaction networks. We quantified resulting patterns of misclassification and discussed the relative value of each relative to ongoing development of prognostic biomarkers. Results We found that single-gene, gene-set and network methods yielded similar error rates in melanoma and ovarian cancer data. Crucially, however, our novel and detailed patient-level analyses revealed that the different methods were correctly classifying alternate subsets of patients in each cohort. We also found that the network-based NetRank feature selection method was the most stable. Conclusions Next-generation methods of gene expression signature modelling harness data from external networks and are foreshadowed as a standard mode of analysis. But what do they add

  16. Modeling particulate matter concentrations measured through mobile monitoring in a deletion/substitution/addition approach

    NASA Astrophysics Data System (ADS)

    Su, Jason G.; Hopke, Philip K.; Tian, Yilin; Baldwin, Nichole; Thurston, Sally W.; Evans, Kristin; Rich, David Q.

    2015-12-01

    Land use regression modeling (LUR) through local scale circular modeling domains has been used to predict traffic-related air pollution such as nitrogen oxides (NOX). LUR modeling for fine particulate matters (PM), which generally have smaller spatial gradients than NOX, has been typically applied for studies involving multiple study regions. To increase the spatial coverage for fine PM and key constituent concentrations, we designed a mobile monitoring network in Monroe County, New York to measure pollutant concentrations of black carbon (BC, wavelength at 880 nm), ultraviolet black carbon (UVBC, wavelength at 3700 nm) and Delta-C (the difference between the UVBC and BC concentrations) using the Clarkson University Mobile Air Pollution Monitoring Laboratory (MAPL). A Deletion/Substitution/Addition (D/S/A) algorithm was conducted, which used circular buffers as a basis for statistics. The algorithm maximizes the prediction accuracy for locations without measurements using the V-fold cross-validation technique, and it reduces overfitting compared to other approaches. We found that the D/S/A LUR modeling approach could achieve good results, with prediction powers of 60%, 63%, and 61%, respectively, for BC, UVBC, and Delta-C. The advantage of mobile monitoring is that it can monitor pollutant concentrations at hundreds of spatial points in a region, rather than the typical less than 100 points from a fixed site saturation monitoring network. This research indicates that a mobile saturation sampling network, when combined with proper modeling techniques, can uncover small area variations (e.g., 10 m) in particulate matter concentrations.

  17. A high-resolution approach to estimating ecosystem respiration at continental scales using operational satellite data.

    PubMed

    Jägermeyr, Jonas; Gerten, Dieter; Lucht, Wolfgang; Hostert, Patrick; Migliavacca, Mirco; Nemani, Ramakrishna

    2014-04-01

    A better understanding of the local variability in land-atmosphere carbon fluxes is crucial to improving the accuracy of global carbon budgets. Operational satellite data backed by ground measurements at Fluxnet sites proved valuable in monitoring local variability of gross primary production at highly resolved spatio-temporal resolutions. Yet, we lack similar operational estimates of ecosystem respiration (Re) to calculate net carbon fluxes. If successful, carbon fluxes from such a remote sensing approach would form an independent and sought after measure to complement widely used dynamic global vegetation models (DGVMs). Here, we establish an operational semi-empirical Re model, based only on data from the Moderate Resolution Imaging Spectroradiometer (MODIS) with a resolution of 1 km and 8 days. Fluxnet measurements between 2000 and 2009 from 100 sites across North America and Europe are used for parameterization and validation. Our analysis shows that Re is closely tied to temperature and plant productivity. By separating temporal and intersite variation, we find that MODIS land surface temperature (LST) and enhanced vegetation index (EVI) are sufficient to explain observed Re across most major biomes with a negligible bias [R² = 0.62, RMSE = 1.32 (g C m(-2) d(-1)), MBE = 0.05 (g C m(-2) d(-1))]. A comparison of such satellite-derived Re with those simulated by the DGVM LPJmL reveals similar spatial patterns. However, LPJmL shows higher temperature sensitivities and consistently simulates higher Re values, in high-latitude and subtropical regions. These differences remain difficult to explain and they are likely associated either with LPJmL parameterization or with systematic errors in the Fluxnet sampling technique. While uncertainties remain with Re estimates, the model formulated in this study provides an operational, cross-validated and unbiased approach to scale Fluxnet Re to the continental scale and advances knowledge of spatio-temporal Re variability

  18. A multivariate approach for assessing leaf photo-assimilation performance using the IPL index.

    PubMed

    Losciale, Pasquale; Manfrini, Luigi; Morandi, Brunella; Pierpaoli, Emanuele; Zibordi, Marco; Stellacci, Anna Maria; Salvati, Luca; Corelli Grappadelli, Luca

    2015-08-01

    The detection of leaf functionality is of pivotal importance for plant scientists from both theoretical and practical point of view. Leaves are the sources of dry matter and food, and they sequester CO2 as well. Under the perspective of climate change and primary resource scarcity (i.e. water, fertilizers and soil), assessing leaf photo-assimilation in a rapid but comprehensive way can be helpful for understanding plant behavior under different environmental conditions and for managing the agricultural practices properly. Several approaches have been proposed for this goal, however, some of them resulted very efficient but little reliable. On the other hand, the high reliability and exhaustive information of some models used for estimating net photosynthesis are at the expense of time and ease of measurement. The present study employs a multivariate statistical approach to assess a model aiming at estimating leaf photo-assimilation performance, using few and easy-to-measure variables. The model, parameterized for apple and pear and subjected to internal and external cross validation, involves chlorophyll fluorescence, carboxylative activity of ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCo), air and leaf temperature. Results prove that this is a fair-predictive model allowing reliable variable assessment. The dependent variable, called IPL index, was found strongly and linearly correlated to net photosynthesis. IPL and the model behind it seem to be (1) reliable, (2) easy and fast to measure and (3) usable in vivo and in the field for such cases where high amount of data is required (e.g. precision agriculture and phenotyping studies). PMID:25625618

  19. Computational chemistry approach for the early detection of drug-induced idiosyncratic liver toxicity.

    PubMed

    Cruz-Monteagudo, Maykel; Cordeiro, M Natália D S; Borges, Fernanda

    2008-03-01

    Idiosyncratic drug toxicity (IDT), considered as a toxic host-dependent event, with an apparent lack of dose response relationship, is usually not predictable from early phases of clinical trials, representing a particularly confounding complication in drug development. Albeit a rare event (usually <1/5000), IDT is often life threatening and is one of the major reasons new drugs never reach the market or are withdrawn post marketing. Computational methodologies, like the computer-based approach proposed in the present study, can play an important role in addressing IDT in early drug discovery. We report for the first time a systematic evaluation of classification models to predict idiosyncratic hepatotoxicity based on linear discriminant analysis (LDA), artificial neural networks (ANN), and machine learning algorithms (OneR) in conjunction with a 3D molecular structure representation and feature selection methods. These modeling techniques (LDA, feature selection to prevent over-fitting and multicollinearity, ANN to capture nonlinear relationships in the data, as well as the simple OneR classifier) were found to produce QSTR models with satisfactory internal cross-validation statistics and predictivity on an external subset of chemicals. More specifically, the models reached values of accuracy/sensitivity/specificity over 84%/78%/90%, respectively in the training series along with predictivity values ranging from ca. 78 to 86% of correctly classified drugs. An LDA-based desirability analysis was carried out in order to select the levels of the predictor variables needed to trigger the more desirable drug, i.e. the drug with lower potential for idiosyncratic hepatotoxicity. Finally, two external test sets were used to evaluate the ability of the models in discriminating toxic from nontoxic structurally and pharmacologically related drugs and the ability of the best model (LDA) in detecting potential idiosyncratic hepatotoxic drugs, respectively. The computational

  20. Spatial Analysis of Geothermal Resource Potential in New York and Pennsylvania: A Stratified Kriging Approach

    NASA Astrophysics Data System (ADS)

    Smith, J. D.; Whealton, C. A.; Stedinger, J. R.

    2014-12-01

    Resource assessments for low-grade geothermal applications employ available well temperature measurements to determine if the resource potential is sufficient for supporting district heating opportunities. This study used a compilation of bottomhole temperature (BHT) data from recent unconventional shale oil and gas wells, along with legacy oil, gas, and storage wells, in Pennsylvania (PA) and New York (NY). Our study's goal was to predict the geothermal resource potential and associated uncertainty for the NY-PA region using kriging interpolation. The dataset was scanned for outliers, and some observations were removed. Because these wells were drilled for reasons other than geothermal resource assessment, their spatial density varied widely. An exploratory spatial statistical analysis revealed differences in the spatial structure of the geothermal gradient data (the kriging semi-variogram and its nugget variance, shape, sill, and the degree of anisotropy). As a result, a stratified kriging procedure was adopted to better capture the statistical structure of the data, to generate an interpolated surface, and to quantify the uncertainty of the computed surface. The area was stratified reflecting different physiographic provinces in NY and PA that have geologic properties likely related to variations in the value of the geothermal gradient. The kriging prediction and the variance-of-prediction were determined for each province by the generation of a semi-variogram using only the wells that were located within that province. A leave-one-out cross validation (LOOCV) was conducted as a diagnostic tool. The results of stratified kriging were compared to kriging using the whole region to determine the impact of stratification. The two approaches provided similar predictions of the geothermal gradient. However, the variance-of-prediction was different. The stratified approach is recommended because it gave a more appropriate site-specific characterization of uncertainty

  1. Individual exposure to air pollution and lung function in Korea: spatial analysis using multiple exposure approaches.

    PubMed

    Son, Ji-Young; Bell, Michelle L; Lee, Jong-Tae

    2010-11-01

    Interpolation methods can estimate individual-level exposures to air pollution from ambient monitors; however, few studies have evaluated how different approaches may affect health risk estimates. We applied multiple methods of estimating exposure for several air pollutants. We investigated how different methods of estimating exposure may influence health effect estimates in a case study of lung function data, forced expiratory volume in 1s (FEV1), and forced vital capacity (FVC), for 2102 cohort subjects in Ulsan, Korea, for 2003-2007. Measurements from 13 monitors for particulate matter <10 μm (PM(10)), ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide were used to estimate individual-level exposures by averaging across values from all monitors, selecting the value from the nearest monitor, inverse distance weighting, and kriging. We assessed associations between pollutants and lung function in linear regression models, controlling for age, sex, and body mass index. Cross-validation indicated that kriging provided the most accurate estimated exposures. FVC was associated with all air pollutants under all methods of estimating exposure. Only ozone was associated with FEV1. An 11 ppb increase in lag-0-2 8-h maximum ozone was associated with a 6.1% (95% confidence interval 5.0, 7.3%) decrease in FVC and a 0.50% (95% confidence interval 0.03, 0.96%) decrease in FEV1, based on kriged exposures. Central health effect estimates were generally higher using exposures based on averaging across all monitors or kriging. Results based on the nearest monitor approach had the lowest variance. Findings suggest that spatial interpolation methods may provide better estimates than monitoring values alone by reflecting the spatial variability of individual-level exposures and generating estimates for locations without monitors. PMID:20832787

  2. A novel meta-analytic approach: Mining frequent co-activation patterns in neuroimaging databases

    PubMed Central

    Caspers, Julian; Zilles, Karl; Beierle, Christoph; Rottschy, Claudia; Eickhoff, Simon B.

    2016-01-01

    In recent years, coordinate-based meta-analyses have become a powerful and widely used tool to study coactivity across neuroimaging experiments, a development that was supported by the emergence of large-scale neuroimaging databases like BrainMap. However, the evaluation of co-activation patterns is constrained by the fact that previous coordinate-based meta-analysis techniques like Activation Likelihood Estimation (ALE) and Multilevel Kernel Density Analysis (MKDA) reveal all brain regions that show convergent activity within a dataset without taking into account actual within-experiment co-occurrence patterns. To overcome this issue we here propose a novel meta-analytic approach named PaMiNI that utilizes a combination of two well-established data-mining techniques, Gaussian mixture modeling and the Apriori algorithm. By this, PaMiNI enables a data-driven detection of frequent co-activation patterns within neuroimaging datasets. The feasibility of the method is demonstrated by means of several analyses on simulated data as well as a real application. The analyses of the simulated data show that PaMiNI identifies the brain regions underlying the simulated activation foci and perfectly separates the co-activation patterns of the experiments in the simulations. Furthermore, PaMiNI still yields good results when activation foci of distinct brain regions become closer together or if they are non-Gaussian distributed. For the further evaluation, a real dataset on working memory experiments is used, which was previously examined in an ALE meta-analysis and hence allows a cross-validation of both methods. In this latter analysis, PaMiNI revealed a fronto-parietal “core” network of working memory and furthermore indicates a left-lateralization in this network. Finally, to encourage a widespread usage of this new method, the PaMiNI approach was implemented into a publicly available software system. PMID:24365675

  3. Dynamic frequency feature selection based approach for classification of motor imageries.

    PubMed

    Luo, Jing; Feng, Zuren; Zhang, Jun; Lu, Na

    2016-08-01

    Electroencephalography (EEG) is one of the most popular techniques to record the brain activities such as motor imagery, which is of low signal-to-noise ratio and could lead to high classification error. Therefore, selection of the most discriminative features could be crucial to improve the classification performance. However, the traditional feature selection methods employed in brain-computer interface (BCI) field (e.g. Mutual Information-based Best Individual Feature (MIBIF), Mutual Information-based Rough Set Reduction (MIRSR) and cross-validation) mainly focus on the overall performance on all the trials in the training set, and thus may have very poor performance on some specific samples, which is not acceptable. To address this problem, a novel sequential forward feature selection approach called Dynamic Frequency Feature Selection (DFFS) is proposed in this paper. The DFFS method emphasized the importance of the samples that got misclassified while only pursuing high overall classification performance. In the DFFS based classification scheme, the EEG data was first transformed to frequency domain using Wavelet Packet Decomposition (WPD), which is then employed as the candidate set for further discriminatory feature selection. The features are selected one by one in a boosting manner. After one feature being selected, the importance of the correctly classified samples based on the feature will be decreased, which is equivalent to increasing the importance of the misclassified samples. Therefore, a complement feature to the current features could be selected in the next run. The selected features are then fed to a classifier trained by random forest algorithm. Finally, a time series voting-based method is utilized to improve the classification performance. Comparisons between the DFFS-based approach and state-of-art methods on BCI competition IV data set 2b have been conducted, which have shown the superiority of the proposed algorithm. PMID:27253616

  4. Random forests, a novel approach for discrimination of fish populations using parasites as biological tags.

    PubMed

    Perdiguero-Alonso, Diana; Montero, Francisco E; Kostadinova, Aneta; Raga, Juan Antonio; Barrett, John

    2008-10-01

    Due to the complexity of host-parasite relationships, discrimination between fish populations using parasites as biological tags is difficult. This study introduces, to our knowledge for the first time, random forests (RF) as a new modelling technique in the application of parasite community data as biological markers for population assignment of fish. This novel approach is applied to a dataset with a complex structure comprising 763 parasite infracommunities in population samples of Atlantic cod, Gadus morhua, from the spawning/feeding areas in five regions in the North East Atlantic (Baltic, Celtic, Irish and North seas and Icelandic waters). The learning behaviour of RF is evaluated in comparison with two other algorithms applied to class assignment problems, the linear discriminant function analysis (LDA) and artificial neural networks (ANN). The three algorithms are used to develop predictive models applying three cross-validation procedures in a series of experiments (252 models in total). The comparative approach to RF, LDA and ANN algorithms applied to the same datasets demonstrates the competitive potential of RF for developing predictive models since RF exhibited better accuracy of prediction and outperformed LDA and ANN in the assignment of fish to their regions of sampling using parasite community data. The comparative analyses and the validation experiment with a 'blind' sample confirmed that RF models performed more effectively with a large and diverse training set and a large number of variables. The discrimination results obtained for a migratory fish species with largely overlapping parasite communities reflects the high potential of RF for developing predictive models using data that are both complex and noisy, and indicates that it is a promising tool for parasite tag studies. Our results suggest that parasite community data can be used successfully to discriminate individual cod from the five different regions of the North East Atlantic studied

  5. Prediction of selective estrogen receptor beta agonist using open data and machine learning approach

    PubMed Central

    Niu, Ai-qin; Xie, Liang-jun; Wang, Hui; Zhu, Bing; Wang, Sheng-qi

    2016-01-01

    Background Estrogen receptors (ERs) are nuclear transcription factors that are involved in the regulation of many complex physiological processes in humans. ERs have been validated as important drug targets for the treatment of various diseases, including breast cancer, ovarian cancer, osteoporosis, and cardiovascular disease. ERs have two subtypes, ER-α and ER-β. Emerging data suggest that the development of subtype-selective ligands that specifically target ER-β could be a more optimal approach to elicit beneficial estrogen-like activities and reduce side effects. Methods Herein, we focused on ER-β and developed its in silico quantitative structure-activity relationship models using machine learning (ML) methods. Results The chemical structures and ER-β bioactivity data were extracted from public chemogenomics databases. Four types of popular fingerprint generation methods including MACCS fingerprint, PubChem fingerprint, 2D atom pairs, and Chemistry Development Kit extended fingerprint were used as descriptors. Four ML methods including Naïve Bayesian classifier, k-nearest neighbor, random forest, and support vector machine were used to train the models. The range of classification accuracies was 77.10% to 88.34%, and the range of area under the ROC (receiver operating characteristic) curve values was 0.8151 to 0.9475, evaluated by the 5-fold cross-validation. Comparison analysis suggests that both the random forest and the support vector machine are superior for the classification of selective ER-β agonists. Chemistry Development Kit extended fingerprints and MACCS fingerprint performed better in structural representation between active and inactive agonists. Conclusion These results demonstrate that combining the fingerprint and ML approaches leads to robust ER-β agonist prediction models, which are potentially applicable to the identification of selective ER-β agonists. PMID:27486309

  6. An NMR metabolomics approach for the diagnosis of leptomeningeal carcinomatosis in lung adenocarcinoma cancer patients.

    PubMed

    An, Yong Jin; Cho, Hye Rim; Kim, Tae Min; Keam, Bhumsuk; Kim, Jin Wook; Wen, He; Park, Chul-Kee; Lee, Se-Hoon; Im, Seock-Ah; Kim, Jeong Eun; Choi, Seung Hong; Park, Sunghyouk

    2015-01-01

    Leptomeningeal carcinomatosis (LC) is a metastatic cancer invading the central nervous system (CNS). We previously reported a metabolomic diagnostic approach as tested on an animal model and compared with current modalities. Here, we provide a proof of concept by applying it to human LC originating from lung cancer, the most common cause of CNS metastasis. Cerebrospinal fluid from LC (n = 26) and normal groups (n = 41) were obtained, and the diagnosis was established with clinical signs, cytology, MRI and biochemical tests. The cytology on the CSF, the current gold standard, exhibited 69% sensitivity (~100% specificity) from the first round of CSF tapping. In comparison, the nuclear magnetic resonance spectra on the CSF showed a clear difference in the metabolic profile between the LC and normal groups. Multivariate analysis and cross-validation yielded the diagnostic sensitivity of 92%, the specificity of 96% and the area under the curve (AUC) of 0.991. Further spectral and statistical analysis identified myo-inositol (p < 5 × 10(-14)), creatine (p < 7 × 10(-8)), lactate (p < 9 × 10(-4)), alanine (p < 7.9 × 10(-3)) and citrate (p < 3 × 10(-4)) as the most contributory metabolites, whose combination exhibited an receiver-operating characteristic diagnostic AUC of 0.996. In addition, the metabolic profile could be correlated with the grading of radiological leptomeningeal enhancement (R(2) = 0.3881 and p = 6.66 × 10(-4)), suggesting its potential utility in grading LC. Overall, we propose that the metabolomic approach might augment current diagnostic modalities for LC, the accurate diagnosis of which remains a challenge. PMID:24798643

  7. A novel approach for honey pollen profile assessment using an electronic tongue and chemometric tools.

    PubMed

    Dias, Luís G; Veloso, Ana C A; Sousa, Mara E B C; Estevinho, Letícia; Machado, Adélio A S C; Peres, António M

    2015-11-01

    Nowadays the main honey producing countries require accurate labeling of honey before commercialization, including floral classification. Traditionally, this classification is made by melissopalynology analysis, an accurate but time-consuming task requiring laborious sample pre-treatment and high-skilled technicians. In this work the potential use of a potentiometric electronic tongue for pollinic assessment is evaluated, using monofloral and polyfloral honeys. The results showed that after splitting honeys according to color (white, amber and dark), the novel methodology enabled quantifying the relative percentage of the main pollens (Castanea sp., Echium sp., Erica sp., Eucaliptus sp., Lavandula sp., Prunus sp., Rubus sp. and Trifolium sp.). Multiple linear regression models were established for each type of pollen, based on the best sensors' sub-sets selected using the simulated annealing algorithm. To minimize the overfitting risk, a repeated K-fold cross-validation procedure was implemented, ensuring that at least 10-20% of the honeys were used for internal validation. With this approach, a minimum average determination coefficient of 0.91 ± 0.15 was obtained. Also, the proposed technique enabled the correct classification of 92% and 100% of monofloral and polyfloral honeys, respectively. The quite satisfactory performance of the novel procedure for quantifying the relative pollen frequency may envisage its applicability for honey labeling and geographical origin identification. Nevertheless, this approach is not a full alternative to the traditional melissopalynologic analysis; it may be seen as a practical complementary tool for preliminary honey floral classification, leaving only problematic cases for pollinic evaluation. PMID:26572837

  8. Automatic approach to solve the morphological galaxy classification problem using the sparse representation technique and dictionary learning

    NASA Astrophysics Data System (ADS)

    Diaz-Hernandez, R.; Ortiz-Esquivel, A.; Peregrina-Barreto, H.; Altamirano-Robles, L.; Gonzalez-Bernal, J.

    2016-04-01

    The observation of celestial objects in the sky is a practice that helps astronomers to understand the way in which the Universe is structured. However, due to the large number of observed objects with modern telescopes, the analysis of these by hand is a difficult task. An important part in galaxy research is the morphological structure classification based on the Hubble sequence. In this research, we present an approach to solve the morphological galaxy classification problem in an automatic way by using the Sparse Representation technique and dictionary learning with K-SVD. For the tests in this work, we use a database of galaxies extracted from the Principal Galaxy Catalog (PGC) and the APM Equatorial Catalogue of Galaxies obtaining a total of 2403 useful galaxies. In order to represent each galaxy frame, we propose to calculate a set of 20 features such as Hu's invariant moments, galaxy nucleus eccentricity, gabor galaxy ratio and some other features commonly used in galaxy classification. A stage of feature relevance analysis was performed using Relief-f in order to determine which are the best parameters for the classification tests using 2, 3, 4, 5, 6 and 7 galaxy classes making signal vectors of different length values with the most important features. For the classification task, we use a 20-random cross-validation technique to evaluate classification accuracy with all signal sets achieving a score of 82.27 % for 2 galaxy classes and up to 44.27 % for 7 galaxy classes.

  9. The cleverSuite approach for protein characterization: predictions of structural properties, solubility, chaperone requirements and RNA-binding abilities

    PubMed Central

    Klus, Petr; Bolognesi, Benedetta; Agostini, Federico; Marchese, Domenica; Zanzoni, Andreas; Tartaglia, Gian Gaetano

    2014-01-01

    Motivation: The recent shift towards high-throughput screening is posing new challenges for the interpretation of experimental results. Here we propose the cleverSuite approach for large-scale characterization of protein groups. Description: The central part of the cleverSuite is the cleverMachine (CM), an algorithm that performs statistics on protein sequences by comparing their physico-chemical propensities. The second element is called cleverClassifier and builds on top of the models generated by the CM to allow classification of new datasets. Results: We applied the cleverSuite to predict secondary structure properties, solubility, chaperone requirements and RNA-binding abilities. Using cross-validation and independent datasets, the cleverSuite reproduces experimental findings with great accuracy and provides models that can be used for future investigations. Availability: The intuitive interface for dataset exploration, analysis and prediction is available at http://s.tartaglialab.com/clever_suite. Contact: gian.tartaglia@crg.es Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24493033

  10. Validation of a high voltage leak detector for use with pharmaceutical blow-fill-seal containers--a practical approach.

    PubMed

    Möll, F; Doyle, D L; Haerer, M; Morton Guazzo, D

    1998-01-01

    Proposed requirements for pharmaceutical package integrity testing outlined in the EU Guide for Sterile Medicinal Products may make it necessary to evaluate and validate alternate ways to perform 100% leak inspection. One such method is high voltage leak detection (HVLD). Even though HVLD has been used for glass ampoules and vials for years, qualification and validation strategies are not well established. In this article, we describe and discuss our practical approach to validation and the protocols used to qualify and validate a high voltage leak detector for use with blow-fill-seal containers. For this work, we used laser drilled pinholes as a model for pinholes produced during manufacturing and defined a "window diagram." This diagram allowed us to plot the parameters of influence and the settings of the HVLD in an easy to visualize pictorial display. In the validation step, we initially determined the most sensitive standard integrity test for our product and container design from the available choices, the vacuum chamber, dye bath and microbial challenge visual inspection tests. In the next phase of our work, the HVLD was crossed-validated against the most sensitive of these tests, the dye bath visual inspection test. This was accomplished with a large number of containers mixed with deliberately defective ampoules. Our conclusion from this work is that the HVLD is an appropriate and feasible integrity test for 100% inspection of blow-fill-seal containers. PMID:9846069

  11. Automatic approach to solve the morphological galaxy classification problem using the sparse representation technique and dictionary learning

    NASA Astrophysics Data System (ADS)

    Diaz-Hernandez, R.; Ortiz-Esquivel, A.; Peregrina-Barreto, H.; Altamirano-Robles, L.; Gonzalez-Bernal, J.

    2016-06-01

    The observation of celestial objects in the sky is a practice that helps astronomers to understand the way in which the Universe is structured. However, due to the large number of observed objects with modern telescopes, the analysis of these by hand is a difficult task. An important part in galaxy research is the morphological structure classification based on the Hubble sequence. In this research, we present an approach to solve the morphological galaxy classification problem in an automatic way by using the Sparse Representation technique and dictionary learning with K-SVD. For the tests in this work, we use a database of galaxies extracted from the Principal Galaxy Catalog (PGC) and the APM Equatorial Catalogue of Galaxies obtaining a total of 2403 useful galaxies. In order to represent each galaxy frame, we propose to calculate a set of 20 features such as Hu's invariant moments, galaxy nucleus eccentricity, gabor galaxy ratio and some other features commonly used in galaxy classification. A stage of feature relevance analysis was performed using Relief-f in order to determine which are the best parameters for the classification tests using 2, 3, 4, 5, 6 and 7 galaxy classes making signal vectors of different length values with the most important features. For the classification task, we use a 20-random cross-validation technique to evaluate classification accuracy with all signal sets achieving a score of 82.27 % for 2 galaxy classes and up to 44.27 % for 7 galaxy classes.

  12. A topological restricted maximum likelihood (TopREML) approach to regionalize trended runoff signatures in stream networks

    NASA Astrophysics Data System (ADS)

    Müller, M. F.; Thompson, S. E.

    2015-01-01

    We introduce TopREML as a method to predict runoff signatures in ungauged basins. The approach is based on the use of linear mixed models with spatially correlated random effects. The nested nature of streamflow networks is taken into account by using water balance considerations to constrain the covariance structure of runoff and to account for the stronger spatial correlation between flow-connected basins. The restricted maximum likelihood (REML) framework generates the best linear unbiased predictor (BLUP) of both the predicted variable and the associated prediction uncertainty, even when incorporating observable covariates into the model. The method was successfully tested in cross validation analyses on mean streamflow and runoff frequency in Nepal (sparsely gauged) and Austria (densely gauged), where it matched the performance of comparable methods in the prediction of the considered runoff signature, while significantly outperforming them in the prediction of the associated modeling uncertainty. TopREML's ability to combine deterministic and stochastic information to generate BLUPs of the prediction variable and its uncertainty makes it a particularly versatile method that can readily be applied in both densely gauged basins, where it takes advantage of spatial covariance information, and data-scarce regions, where it can rely on covariates, which are increasingly observable thanks to remote sensing technology.

  13. TopREML: a topological restricted maximum likelihood approach to regionalize trended runoff signatures in stream networks

    NASA Astrophysics Data System (ADS)

    Müller, M. F.; Thompson, S. E.

    2015-06-01

    We introduce topological restricted maximum likelihood (TopREML) as a method to predict runoff signatures in ungauged basins. The approach is based on the use of linear mixed models with spatially correlated random effects. The nested nature of streamflow networks is taken into account by using water balance considerations to constrain the covariance structure of runoff and to account for the stronger spatial correlation between flow-connected basins. The restricted maximum likelihood (REML) framework generates the best linear unbiased predictor (BLUP) of both the predicted variable and the associated prediction uncertainty, even when incorporating observable covariates into the model. The method was successfully tested in cross-validation analyses on mean streamflow and runoff frequency in Nepal (sparsely gauged) and Austria (densely gauged), where it matched the performance of comparable methods in the prediction of the considered runoff signature, while significantly outperforming them in the prediction of the associated modeling uncertainty. The ability of TopREML to combine deterministic and stochastic information to generate BLUPs of the prediction variable and its uncertainty makes it a particularly versatile method that can readily be applied in both densely gauged basins, where it takes advantage of spatial covariance information, and data-scarce regions, where it can rely on covariates, which are increasingly observable via remote-sensing technology.

  14. Homology modeling and virtual screening of inhibitors against TEM- and SHV-type-resistant mutants: A multilayer filtering approach.

    PubMed

    Baig, Mohammad H; Balaramnavar, Vishal M; Wadhwa, Gulshan; Khan, Asad U

    2015-01-01

    TEM and SHV are class-A-type β-lactamases commonly found in Escherichia coli and Klebsiella pneumoniae. Previous studies reported S130G and K234R mutations in SHVs to be 41- and 10-fold more resistant toward clavulanic acid than SHV-1, respectively, whereas TEM S130G and R244S also showed the same level of resistance. These selected mutants confer higher level of resistance against clavulanic acid. They also show little susceptibility against other commercially available β-lactamase inhibitors. In this study, we have used docking-based virtual screening approach in order to screen potential inhibitors against some of the major resistant mutants of SHV and TEM types β-lactamase. Two different inhibitor-resistant mutants from SHV and TEM were selected. Moreover, we have retained the active site water molecules within each enzyme. Active site water molecules were placed within modeled structure of the mutant whose structure was unavailable with protein databank. The novelty of this work lies in the use of multilayer virtual screening approach for the prediction of best and accurate results. We are reporting five inhibitors on the basis of their efficacy against all the selected resistant mutants. These inhibitors were selected on the basis of their binding efficacies and pharmacophore features. PMID:25779642

  15. An evaluation of popular hyperspectral images classification approaches

    NASA Astrophysics Data System (ADS)

    Kuznetsov, Andrey; Myasnikov, Vladislav

    2015-12-01

    This work is devoted to the problem of the best hyperspectral images classification algorithm selection. The following algorithms are used for comparison: decision tree using full cross-validation; decision tree C 4.5; Bayesian classifier; maximum-likelihood method; MSE minimization classifier, including a special case - classification by conjugation; spectral angle classifier (for empirical mean and nearest neighbor), spectral mismatch classifier and support vector machine (SVM). There are used AVIRIS and SpecTIR hyperspectral images to conduct experiments.

  16. Prediction of bacterial protein subcellular localization by incorporating various features into Chou's PseAAC and a backward feature selection approach.

    PubMed

    Li, Liqi; Yu, Sanjiu; Xiao, Weidong; Li, Yongsheng; Li, Maolin; Huang, Lan; Zheng, Xiaoqi; Zhou, Shiwen; Yang, Hua

    2014-09-01

    Information on the subcellular localization of bacterial proteins is essential for protein function prediction, genome annotation and drug design. Here we proposed a novel approach to predict the subcellular localization of bacterial proteins by fusing features from position-specific score matrix (PSSM), Gene Ontology (GO) and PROFEAT. A backward feature selection approach by linear kennel of SVM was then used to rank the integrated feature vectors and extract optimal features. Finally, SVM was applied for predicting protein subcellular locations based on these optimal features. To validate the performance of our method, we employed jackknife cross-validation tests on three low similarity datasets, i.e., M638, Gneg1456 and Gpos523. The overall accuracies of 94.98%, 93.21%, and 94.57% were achieved for these three datasets, which are higher (from 1.8% to 10.9%) than those by state-of-the-art tools. Comparison results suggest that our method could serve as a very useful vehicle for expediting the prediction of bacterial protein subcellular localization. PMID:24929100

  17. iLOGP: a simple, robust, and efficient description of n-octanol/water partition coefficient for drug design using the GB/SA approach.

    PubMed

    Daina, Antoine; Michielin, Olivier; Zoete, Vincent

    2014-12-22

    The n-octanol/water partition coefficient (log Po/w) is a key physicochemical parameter for drug discovery, design, and development. Here, we present a physics-based approach that shows a strong linear correlation between the computed solvation free energy in implicit solvents and the experimental log Po/w on a cleansed data set of more than 17,500 molecules. After internal validation by five-fold cross-validation and data randomization, the predictive power of the most interesting multiple linear model, based on two GB/SA parameters solely, was tested on two different external sets of molecules. On the Martel druglike test set, the predictive power of the best model (N = 706, r = 0.64, MAE = 1.18, and RMSE = 1.40) is similar to six well-established empirical methods. On the 17-drug test set, our model outperformed all compared empirical methodologies (N = 17, r = 0.94, MAE = 0.38, and RMSE = 0.52). The physical basis of our original GB/SA approach together with its predictive capacity, computational efficiency (1 to 2 s per molecule), and tridimensional molecular graphics capability lay the foundations for a promising predictor, the implicit log P method (iLOGP), to complement the portfolio of drug design tools developed and provided by the SIB Swiss Institute of Bioinformatics. PMID:25382374

  18. Identification of potential Gly/NMDA receptor antagonists by cheminformatics approach: a combination of pharmacophore modelling, virtual screening and molecular docking studies.

    PubMed

    Ugale, V G; Bari, S B

    2016-01-01

    The Gly/NMDA receptor has become known as potential target for the management of neurodegenerative diseases. Discovery of Gly/NMDA antagonists has thus attracted much attention in recent years. In the present research, a cheminformatics approach has been used to determine structural requirements for Gly/NMDA antagonism and to identify potential antagonists. Here, 37 quinoxaline derivatives were selected to develop a significant pharmacophore model with good certainty. The selected model was validated by leave-one-out cross-validation, an external test set, decoy set and Y-randomization test. Applicability domain was verified by the standardization approach. The validated 3D-QSAR model was used to screen virtual hits from the ZINC database by pharmacophore mapping. Molecular docking was used for assessment of receptor-ligand binding modes and binding affinities. The GlideScore and molecular interactions with critical amino acids were considered as crucial features to identify final hits. Furthermore, hits were analysed for in silico pharmacokinetic parameters and Lipinski's rule of five, demonstrating their potential as drug-like candidates. The PubChem and SciFinder search tools were used to authenticate the novelty of leads retrieved. Finally, five different leads have been suggested as putative novel candidates for the exploration of potent Gly/NMDA receptor antagonists. PMID:26911562

  19. Progressive Elaboration and Cross-Validation of a Latent Class Typology of Adolescent Alcohol Involvement in a National Sample

    PubMed Central

    Donovan, John E.; Chung, Tammy

    2015-01-01

    Objective: Most studies of adolescent drinking focus on single alcohol use behaviors (e.g., high-volume drinking, drunkenness) and ignore the patterning of adolescents’ involvement across multiple alcohol behaviors. The present latent class analyses (LCAs) examined a procedure for empirically determining multiple cut points on the alcohol use behaviors in order to establish a typology of adolescent alcohol involvement. Method: LCA was carried out on six alcohol use behavior indicators collected from 6,504 7th through 12th graders who participated in Wave I of the National Longitudinal Study of Adolescent Health (AddHealth). To move beyond dichotomous indicators, a “progressive elaboration” strategy was used, starting with six dichotomous indicators and then evaluating a series of models testing additional cut points on the ordinal indicators at progressively higher points for one indicator at a time. Analyses were performed on one random half-sample, and confirmatory LCAs were performed on the second random half-sample and in the Wave II data. Results: The final model consisted of four latent classes (never or non–current drinkers, low-intake drinkers, non–problem drinkers, and problem drinkers). Confirmatory LCAs in the second random half-sample from Wave I and in Wave II support this four-class solution. The means on the four latent classes were also generally ordered on an array of measures reflecting psychosocial risk for problem behavior. Conclusions: These analyses suggest that there may be four different classes or types of alcohol involvement among adolescents, and, more importantly, they illustrate the utility of the progressive elaboration strategy for moving beyond dichotomous indicators in latent class models. PMID:25978828

  20. Nine scoring models for short-term mortality in alcoholic hepatitis: cross-validation in a biopsy-proven cohort

    PubMed Central

    Papastergiou, V; Tsochatzis, E A; Pieri, G; Thalassinos, E; Dhar, A; Bruno, S; Karatapanis, S; Luong, T V; O'Beirne, J; Patch, D; Thorburn, D; Burroughs, A K

    2014-01-01

    Background Several prognostic models have emerged in alcoholic hepatitis (AH), but lack of external validation precludes their universal use. Aim To validate the Maddrey Discriminant Function (DF); Glasgow Alcoholic Hepatitis Score (GAHS); Mayo End-stage Liver Disease (MELD); Age, Bilirubin, INR, Creatinine (ABIC); MELD-Na, UK End-stage Liver Disease (UKELD), and three scores of corticosteroid response at 1 week: an Early Change in Bilirubin Levels (ECBL), a 25% fall in bilirubin, and the Lille score. Methods Seventy-one consecutive patients with biopsy-proven AH, admitted between November 2007-September 2011, were evaluated. The clinical and biochemical parameters were analysed to assess prognostic models with respect to 30- and 90-day mortality. Results There were no significant differences in the areas under the receiver operating characteristics curve (AUROCs) relative to 30-day/90-day mortality: MELD 0.79/0.84, DF 0.71/0.74, GAHS 0.75/0.78, ABIC 0.71/0.78, MELD-Na 0.68/0.76, UKELD 0.56/0.68. One-week rescoring yielded a trend towards improved predictive accuracies (30-day/90-day AUROCs: 0.69–0.84/0.77–0.86). In patients with admission DF ≥32 (n = 31), response to corticosteroids according to ECBL, 25% fall in bilirubin and the Lille model yielded AUROCs of 0.73/0.73, 0.78/0.72 and 0.81/0.82 for a 30-day/90-day outcome respectively. All models showed excellent negative predictive values (NPVs; range: 86–100%), while the positive ones were low (range: 17–50%). Conclusions MELD, DF, GAHS, ABIC and scores of corticosteroid response proved to be valid in an independent cohort of biopsy-proven alcoholic hepatitis. MELD modifications incorporating sodium did not confer any prognostic advantage over classical MELD. Based on excellent NPVs, the models are best to identify patients at low risk of death. PMID:24612165

  1. Evaluating the Replicability of Multivariate Assessment and Evaluation Results: A Review of Various Applications of the Cross-Validation Logic.

    ERIC Educational Resources Information Center

    Crowley, Susan L.; Thompson, Bruce

    Selected methods for evaluating the stability of research results empirically are described, especially with regard to multivariate analysis. It is critically important to evaluate the influences of sampling error on obtained results; statistical significance testing does not inform judgment regarding the probable replicability or the sampling…

  2. Anticipating Mathematics Performance: A Cross-Validation Comparison of AID3 and Regression. AIR 1988 Annual Forum Paper.

    ERIC Educational Resources Information Center

    Bloom, Allan M.; And Others

    In response to the increasing importance of student performance in required classes, research was conducted to compare two prediction procedures, linear modeling using multiple regression and nonlinear modeling using AID3. Performance in the first college math course (College Mathematics, Calculus, or Business Calculus Matrices) was the dependent…

  3. The Relationship between Work Values and Job Satisfaction for Community College Leadership Trainees: A Replication and Cross-Validation.

    ERIC Educational Resources Information Center

    Torres, Belinda M.; Kapes, Jerome T.

    A study was conducted in 1990-91 to explore the work values and job satisfaction of minority professionals in community colleges and technical institutes who aspire to advance in leadership positions. The sample consisted of 59 Black and Hispanic educators from community colleges and technical institutes across Texas who participated in the…

  4. Cross-Validation of the YMCA Submaximal Cycle Ergometer Test to Predict V[o.sub.2] Max

    ERIC Educational Resources Information Center

    Beekley, Matthew D.; Brechue, William F.; deHoyos, Diego V.; Garzarella, Linda; Werber-Zion, Galila; Pollock, Michael L.

    2004-01-01

    Maximal oxygen uptake (V[O.sub.2]max) is an important indicator of health-risk status, specifically for coronary heart disease (Blair et al., 1989). Direct measurement of V[O.sub.2]max is considered to be the most accurate means of determining cardiovascular fitness level. Typically, this measurement is taken using a progressive exercise test on a…

  5. USING CROSS-VALIDATION TO EVALUATE CERES-MAIZE YIELD SIMULATIONS WITHIN A DECISION SUPPORT SYSTEM FOR PRECISION AGRICULTURE

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Crop growth models have recently been implemented to study precision agriculture questions within the framework of a decision support system (DSS) that automates simulations across management zones. Model calibration in each zone has occurred by automatically optimizing select model parameters to mi...

  6. Measuring Life-Cycle Transitions in Young Adulthood: A Cross-Validation of Data from Three Prospective Surveys.

    ERIC Educational Resources Information Center

    Goldscheider, Frances Kobrin

    This document examines three important national surveys that provide periodic longitudinal data on the transition to adulthood during the late 1960s and 1970s: (1) the Parnes Young Men and Women Panels, initiated in 1966 and 1968; (2) the Panel Study of Income Dynamics, initiated in 1968; and (3) the National Longitudinal Study of the High School…

  7. Cross Validation and Generalization of a Content Analysis of the Narrative Sections of Navy Performance Evaluation for Senior Enlisted Personnel.

    ERIC Educational Resources Information Center

    Ramsey-Klee, Diane M.; Richman, Vivian

    In an earlier pilot study of the narrative sections of Navy performance evaluations for senior enlisted personnel in pay grade E-7, it was determined by content analytic techniques that it is possible to differentiate between the performance of typical and superlative chief petty officers based on the narrative content of Evaluation Reports. A…

  8. The Relationships Between Low-Inference Measures of Classroom Behavior and Pupil Growth: A Cross-Validation.

    ERIC Educational Resources Information Center

    Lorentz, Jeffrey L.; Coker, Homer

    As part of the Competency Based Teacher Certification Project in Carroll County, Georgia, large samples of elementary and secondary school teachers and students were observed during a two-year period. Four low-inference observation measures were used to record teacher behaviors and student-teacher interactions: (1) Teacher Practices Observation…

  9. A fast cross-validation method for alignment of electron tomography images based on Beer-Lambert law.

    PubMed

    Yan, Rui; Edwards, Thomas J; Pankratz, Logan M; Kuhn, Richard J; Lanman, Jason K; Liu, Jun; Jiang, Wen

    2015-11-01

    In electron tomography, accurate alignment of tilt series is an essential step in attaining high-resolution 3D reconstructions. Nevertheless, quantitative assessment of alignment quality has remained a challenging issue, even though many alignment methods have been reported. Here, we report a fast and accurate method, tomoAlignEval, based on the Beer-Lambert law, for the evaluation of alignment quality. Our method is able to globally estimate the alignment accuracy by measuring the goodness of log-linear relationship of the beam intensity attenuations at different tilt angles. Extensive tests with experimental data demonstrated its robust performance with stained and cryo samples. Our method is not only significantly faster but also more sensitive than measurements of tomogram resolution using Fourier shell correlation method (FSCe/o). From these tests, we also conclude that while current alignment methods are sufficiently accurate for stained samples, inaccurate alignments remain a major limitation for high resolution cryo-electron tomography. PMID:26455556

  10. Analysis of Human Innate Immune Responses to PRINT Fabricated Nanoparticles with Cross Validation Using a Humanized Mouse Model

    PubMed Central

    Robbins, GR; Roberts, RA; Guo, H; Reuter, K; Shen, T; Sempowski, GD; McKinnon, Karen P.; Su, L; DeSimone, JM; Ting, JP

    2015-01-01

    Ideal nanoparticle (NP)-based drug and vaccine delivery vectors should be free of inherent cytotoxic or immunostimulatory properties. Therefore, determining baseline immune responses to nanomaterials is of utmost importance when designing human therapeutics. We characterized the response of human immune cells to hydrogel NPs fabricated using Particle Replication in Non-wetting Templates (PRINT) technology. We found preferential NP uptake by primary CD14+ monocytes, which was significantly reduced upon PEGylation of the NP surface. Multiplex cytokine analysis of NP treated primary human peripheral blood mononuclear cells (hu-PBMC) suggests that PRINT based hydrogel NPs do not evoke significant inflammatory responses nor do they induce cytotoxicity or complement activation. We furthered these studies using an in vivo humanized mouse model and similarly found preferential NP uptake by human CD14+ monocytes without systemic inflammatory cytokine responses. These studies suggest that PRINT hydrogel particles form a desirable platform for vaccine and drug delivery as they neither induce inflammation nor toxicity. PMID:25596079

  11. Suicidal Ideation, Parent-Child Relationships, and Adverse Childhood Experiences: A Cross-Validation Study Using a Graphical Markov Model

    ERIC Educational Resources Information Center

    Hardt, Jochen; Herke, Max; Schier, Katarzyna

    2011-01-01

    Suicide is one of the leading causes of death in many Western countries. An exploration of factors associated with suicidality may help to understand the mechanisms that lead to suicide. Two samples in Germany (n = 500 and n = 477) were examined via Internet regarding suicidality, depression, alcohol abuse, adverse childhood experiences, and…

  12. Cross validation of geotechnical and geophysical site characterization methods: near surface data from selected accelerometric stations in Crete (Greece)

    NASA Astrophysics Data System (ADS)

    Loupasakis, C.; Tsangaratos, P.; Rozos, D.; Rondoyianni, Th.; Vafidis, A.; Kritikakis, G.; Steiakakis, M.; Agioutantis, Z.; Savvaidis, A.; Soupios, P.; Papadopoulos, I.; Papadopoulos, N.; Sarris, A.; Mangriotis, M.-D.; Dikmen, U.

    2015-06-01

    The specification of the near surface ground conditions is highly important for the design of civil constructions. These conditions determine primarily the ability of the foundation formations to bear loads, the stress - strain relations and the corresponding settlements, as well as the soil amplification and corresponding peak ground motion in case of dynamic loading. The static and dynamic geotechnical parameters as well as the ground-type/soil-category can be determined by combining geotechnical and geophysical methods, such as engineering geological surface mapping, geotechnical drilling, in situ and laboratory testing and geophysical investigations. The above mentioned methods were combined, through the Thalis ″Geo-Characterization″ project, for the site characterization in selected sites of the Hellenic Accelerometric Network (HAN) in the area of Crete Island. The combination of the geotechnical and geophysical methods in thirteen (13) sites provided sufficient information about their limitations, setting up the minimum tests requirements in relation to the type of the geological formations. The reduced accuracy of the surface mapping in urban sites, the uncertainties introduced by the geophysical survey in sites with complex geology and the 1D data provided by the geotechnical drills are some of the causes affecting the right order and the quantity of the necessary investigation methods. Through this study the gradual improvement on the accuracy of site characterization data is going to be presented by providing characteristic examples from a total number of thirteen sites. Selected examples present sufficiently the ability, the limitations and the right order of the investigation methods.

  13. Advances in the regionalization approach: geostatistical techniques for estimating flood quantiles

    NASA Astrophysics Data System (ADS)

    Chiarello, Valentina; Caporali, Enrica; Matthies, Hermann G.

    2015-04-01

    The knowledge of peak flow discharges and associated floods is of primary importance in engineering practice for planning of water resources and risk assessment. Streamflow characteristics are usually estimated starting from measurements of river discharges at stream gauging stations. However, the lack of observations at site of interest as well as the measurement inaccuracies, bring inevitably to the necessity of developing predictive models. Regional analysis is a classical approach to estimate river flow characteristics at sites where little or no data exists. Specific techniques are needed to regionalize the hydrological variables over the considered area. Top-kriging or topological kriging, is a kriging interpolation procedure that takes into account the geometric organization and structure of hydrographic network, the catchment area and the nested nature of catchments. The continuous processes in space defined for the point variables are represented by a variogram. In Top-kriging, the measurements are not point values but are defined over a non-zero catchment area. Top-kriging is applied here over the geographical space of Tuscany Region, in Central Italy. The analysis is carried out on the discharge data of 57 consistent runoff gauges, recorded from 1923 to 2014. Top-kriging give also an estimation of the prediction uncertainty in addition to the prediction itself. The results are validated using a cross-validation procedure implemented in the package rtop of the open source statistical environment R The results are compared through different error measurement methods. Top-kriging seems to perform better in nested catchments and larger scale catchments but no for headwater or where there is a high variability for neighbouring catchments.

  14. A volatolomic approach for studying plant variability: the case of selected Helichrysum species (Asteraceae).

    PubMed

    Giuliani, Claudia; Lazzaro, Lorenzo; Calamassi, Roberto; Calamai, Luca; Romoli, Riccardo; Fico, Gelsomina; Foggi, Bruno; Mariotti Lippi, Marta

    2016-10-01

    The species of Helichrysum sect. Stoechadina (Asteraceae) are well-known for their secondary metabolite content and the characteristic aromatic bouquets. In the wild, populations exhibit a wide phenotypic plasticity which makes critical the circumscription of species and infraspecific ranks. Previous investigations on Helichrysum italicum complex focused on a possible phytochemical typification based on hydrodistilled essential oils. Aims of this paper are three-fold: (i) characterizing the volatile profiles of different populations, testing (ii) how these profiles vary across populations and (iii) how the phytochemical diversity may contribute in solving taxonomic problems. Nine selected Helichrysum populations, included within the H. italicum complex, Helichrysum litoreum and Helichrysum stoechas, were investigated. H. stoechas was chosen as outgroup for validating the method. After collection in the wild, plants were cultivated in standard growing conditions for over one year. Annual leafy shoots were screened in the post-blooming period for the emissions of volatile organic compounds (VOCs) by means of headspace solid phase microextraction coupled with gas-chromatography and mass spectrometry (HS-SPME-GC/MS). The VOC composition analysis revealed the production of overall 386 different compounds, with terpenes being the most represented compound class. Statistical data processing allowed the identification of the indicator compounds that differentiate the single populations, revealing the influence of the geographical provenance area in determining the volatile profiles. These results suggested the potential use of VOCs as valuable diacritical characters in discriminating the Helichrysum populations. In addition, the cross-validation analysis hinted the potentiality of this volatolomic study in the discrimination of the Helichrysum species and subspecies, highlighting a general congruence with the current taxonomic treatment of the genus. The consistency

  15. A pragmatic approach to estimate the number of days in exceedance of PM10 limit value

    NASA Astrophysics Data System (ADS)

    Beauchamp, Maxime; Malherbe, Laure; de Fouquet, Chantal

    2015-06-01

    European legislation on ambient air quality requests that Member States report the annual number of exceedances of short-term concentration regulatory thresholds for PM10 and delimit the concerned areas. Measurements at the monitoring stations do not allow to fully describe those areas. We present a methodology to estimate the number of exceedances of the daily limit value over a year, that can be extended to any similar issue. This methodology is applied to PM10 concentrations in France for which the daily limit value is 50 μg m-3, not to be exceeded more that 35 days. A probabilistic model is built using preliminary mapping of daily mean concentrations. First, daily atmospheric concentration fields are estimated at 1 km resolution by external drift kriging, combining surface monitoring observations and outputs from the CHIMERE chemistry transport model. Setting a conventional Gaussian hypothesis for the estimation error, the kriging variance is used to compute the probability of exceeding the daily limit value and to identify three areas: those where we can suppose as certain that the concentrations exceed or not the daily limit value and those where the situation is indeterminate because of the estimation uncertainty. Then, from the set of 365 daily mappings of the probability to exceed the daily limit value, the parameters of a translated Poisson distribution is fitted on the annual number of exceedances of the daily limit value at each grid cell, which enables to compute the probability for this number to exceed 35. The methodology is tested for three years (2007, 2009 and 2011) which present numerous exceedances of the daily limit concentration at some monitoring stations. A cross-validation analysis is carried out to check the efficiency of the methodology. The way to interpret probability maps is discussed. A comparison is made with simpler kriging approaches using indicator kriging of exceedances. Lastly, estimation of the population exposed to PM10

  16. A novel approach for accurate prediction of spontaneous passage of ureteral stones: support vector machines.

    PubMed

    Dal Moro, F; Abate, A; Lanckriet, G R G; Arandjelovic, G; Gasparella, P; Bassi, P; Mancini, M; Pagano, F

    2006-01-01

    The objective of this study was to optimally predict the spontaneous passage of ureteral stones in patients with renal colic by applying for the first time support vector machines (SVM), an instance of kernel methods, for classification. After reviewing the results found in the literature, we compared the performances obtained with logistic regression (LR) and accurately trained artificial neural networks (ANN) to those obtained with SVM, that is, the standard SVM, and the linear programming SVM (LP-SVM); the latter techniques show an improved performance. Moreover, we rank the prediction factors according to their importance using Fisher scores and the LP-SVM feature weights. A data set of 1163 patients affected by renal colic has been analyzed and restricted to single out a statistically coherent subset of 402 patients. Nine clinical factors are used as inputs for the classification algorithms, to predict one binary output. The algorithms are cross-validated by training and testing on randomly selected train- and test-set partitions of the data and reporting the average performance on the test sets. The SVM-based approaches obtained a sensitivity of 84.5% and a specificity of 86.9%. The feature ranking based on LP-SVM gives the highest importance to stone size, stone position and symptom duration before check-up. We propose a statistically correct way of employing LR, ANN and SVM for the prediction of spontaneous passage of ureteral stones in patients with renal colic. SVM outperformed ANN, as well as LR. This study will soon be translated into a practical software toolbox for actual clinical usage. PMID:16374437

  17. A Machine Learning Approach to Estimate Riverbank Geotechnical Parameters from Sediment Particle Size Data

    NASA Astrophysics Data System (ADS)

    Iwashita, Fabio; Brooks, Andrew; Spencer, John; Borombovits, Daniel; Curwen, Graeme; Olley, Jon

    2015-04-01

    Assessing bank stability using geotechnical models traditionally involves the laborious collection of data on the bank and floodplain stratigraphy, as well as in-situ geotechnical data for each sedimentary unit within a river bank. The application of geotechnical bank stability models are limited to those sites where extensive field data has been collected, where their ability to provide predictions of bank erosion at the reach scale are limited without a very extensive and expensive field data collection program. Some challenges in the construction and application of riverbank erosion and hydraulic numerical models are their one-dimensionality, steady-state requirements, lack of calibration data, and nonuniqueness. Also, numerical models commonly can be too rigid with respect to detecting unexpected features like the onset of trends, non-linear relations, or patterns restricted to sub-samples of a data set. These shortcomings create the need for an alternate modelling approach capable of using available data. The application of the Self-Organizing Maps (SOM) approach is well-suited to the analysis of noisy, sparse, nonlinear, multidimensional, and scale-dependent data. It is a type of unsupervised artificial neural network with hybrid competitive-cooperative learning. In this work we present a method that uses a database of geotechnical data collected at over 100 sites throughout Queensland State, Australia, to develop a modelling approach that enables geotechnical parameters (soil effective cohesion, friction angle, soil erodibility and critical stress) to be derived from sediment particle size data (PSD). The model framework and predicted values were evaluated using two methods, splitting the dataset into training and validation set, and through a Bootstrap approach. The basis of Bootstrap cross-validation is a leave-one-out strategy. This requires leaving one data value out of the training set while creating a new SOM to estimate that missing value based on the

  18. Markov blanket-based approach for learning multi-dimensional Bayesian network classifiers: an application to predict the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39).

    PubMed

    Borchani, Hanen; Bielza, Concha; Martı Nez-Martı N, Pablo; Larrañaga, Pedro

    2012-12-01

    Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems, where each instance in the data set has to be assigned to more than one class variable. In this paper, we propose a Markov blanket-based approach for learning MBCs from data. Basically, it consists of determining the Markov blanket around each class variable using the HITON algorithm, then specifying the directionality over the MBC subgraphs. Our approach is applied to the prediction problem of the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39) in order to estimate the health-related quality of life of Parkinson's patients. Fivefold cross-validation experiments were carried out on randomly generated synthetic data sets, Yeast data set, as well as on a real-world Parkinson's disease data set containing 488 patients. The experimental study, including comparison with additional Bayesian network-based approaches, back propagation for multi-label learning, multi-label k-nearest neighbor, multinomial logistic regression, ordinary least squares, and censored least absolute deviations, shows encouraging results in terms of predictive accuracy as well as the identification of dependence relationships among class and feature variables. PMID:22897950

  19. Unbiased estimation of chloroplast number in mesophyll cells: advantage of a genuine three-dimensional approach

    PubMed Central

    Kubínová, Zuzana

    2014-01-01

    Chloroplast number per cell is a frequently examined quantitative anatomical parameter, often estimated by counting chloroplast profiles in two-dimensional (2D) sections of mesophyll cells. However, a mesophyll cell is a three-dimensional (3D) structure and this has to be taken into account when quantifying its internal structure. We compared 2D and 3D approaches to chloroplast counting from different points of view: (i) in practical measurements of mesophyll cells of Norway spruce needles, (ii) in a 3D model of a mesophyll cell with chloroplasts, and (iii) using a theoretical analysis. We applied, for the first time, the stereological method of an optical disector based on counting chloroplasts in stacks of spruce needle optical cross-sections acquired by confocal laser-scanning microscopy. This estimate was compared with counting chloroplast profiles in 2D sections from the same stacks of sections. Comparing practical measurements of mesophyll cells, calculations performed in a 3D model of a cell with chloroplasts as well as a theoretical analysis showed that the 2D approach yielded biased results, while the underestimation could be up to 10-fold. We proved that the frequently used method for counting chloroplasts in a mesophyll cell by counting their profiles in 2D sections did not give correct results. We concluded that the present disector method can be efficiently used for unbiased estimation of chloroplast number per mesophyll cell. This should be the method of choice, especially in coniferous needles and leaves with mesophyll cells with lignified cell walls where maceration methods are difficult or impossible to use. PMID:24336344

  20. Validating a Scale for the Measurement of Credibility: A Covariance Structure Modeling Approach.

    ERIC Educational Resources Information Center

    West, Mark Douglas

    1994-01-01

    Presents an attempt to cross-validate a widely used set of standard credibility scales. Finds that the Meyer modification of the Gaziano-McGrath scales appears to validly and reliably measure credibility per se but that a second set of scales posited to measure community affiliation is not sufficiently reliable in its current form for use without…

  1. Bifactor Approach to Modeling Multidimensionality of Physical Self-Perception Profile

    ERIC Educational Resources Information Center

    Chung, ChihMing; Liao, Xiaolan; Song, Hairong; Lee, Taehun

    2016-01-01

    The multi-dimensionality of Physical Self-Perception Profile (PSPP) has been acknowledged by the use of correlated-factor model and second-order model. In this study, the authors critically endorse the bifactor model, as a substitute to address the multi-dimensionality of PSPP. To cross-validate the models, analyses are conducted first in…

  2. Home Environment, Self-Concept, and Academic Achievement: A Causal Modeling Approach.

    ERIC Educational Resources Information Center

    Song, In-Sub; Hattie, John

    1984-01-01

    Structural equation modeling was used to investigate the relation between home environment, self-concept, and academic achievement. It was found and cross-validated over four samples of 2,297 Korean adolescents that self-concept is a mediating variable between home environment and academic achievement. (Author/BS)

  3. Anti-spoofing for display and print attacks on palmprint verification systems

    NASA Astrophysics Data System (ADS)

    Kanhangad, Vivek; Bhilare, Shruti; Garg, Pragalbh; Singh, Pranjalya; Chaudhari, Narendra

    2015-05-01

    A number of approaches for personal authentication using palmprint features have been proposed in the literature, majority of which focus on improving the matching performance. However, of late, preventing potential attacks on biometric systems has become a major concern as more and more biometric systems get deployed for wide range of applications. Among various types of attacks, sensor level attack, commonly known as spoof attack, has emerged as the most common attack due to simplicity in its execution. In this paper, we present an approach for detection of display and print based spoof attacks on palmprint verifcation systems. The approach is based on the analysis of acquired hand images for estimating surface re ectance. First and higher order statistical features computed from the distributions of pixel intensities and sub-band wavelet coeefficients form the feature set. A trained binary classifier utilizes the discriminating information to determine if the acquired image is of real hand or a fake one. Experiments are performed on a publicly available hand image dataset, containing 1300 images corresponding to 230 subjects. Experimental results show that the real hand biometrics samples can be substituted by the fake digital or print copies with an alarming spoof acceptance rate as high as 79.8%. Experimental results also show that the proposed spoof detection approach is very effective for discriminating between real and fake palmprint images. The proposed approach consistently achieves over 99% average 10-fold cross validation classification accuracy in our experiments.

  4. Charge-controlled nanoprecipitation as a modular approach to ultrasmall polymer nanocarriers: making bright and stable nanoparticles.

    PubMed

    Reisch, Andreas; Runser, Anne; Arntz, Youri; Mély, Yves; Klymchenko, Andrey S

    2015-05-26

    Ultrasmall polymer nanoparticles are rapidly gaining importance as nanocarriers for drugs and contrast agents. Here, a straightforward modular approach to efficiently loaded and stable sub-20-nm polymer particles is developed. In order to obtain ultrasmall polymer nanoparticles, we investigated the influence of one to two charged groups per polymer chain on the size of particles obtained by nanoprecipitation. Negatively charged carboxylate and sulfonate or positively charged trimethylammonium groups were introduced into the polymers poly(d,l-lactide-co-glycolide) (PLGA), polycaprolactone (PCL), and poly(methyl methacrylate) (PMMA). According to dynamic light scattering, atomic force and electron microscopy, the presence of one to two charged groups per polymer chain can strongly reduce the size of polymer nanoparticles made by nanoprecipitation. The particle size can be further decreased to less than 15 nm by decreasing the concentration of polymer in the solvent used for nanoprecipitation. We then show that even very small nanocarriers of 15 nm size preserve the capacity to encapsulate large amounts of ionic dyes with bulky counterions at efficiencies >90%, which generates polymer nanoparticles 10-fold brighter than quantum dots of the same size. Postmodification of their surface with the PEG containing amphiphiles Tween 80 and pluronic F-127 led to particles that were stable under physiological conditions and in the presence of 10% fetal bovine serum. This modular route could become a general method for the preparation of ultrasmall polymer nanoparticles as nanocarriers of contrast agents and drugs. PMID:25894117

  5. Morpheus Surface Approach

    NASA Video Gallery

    This animation shows the Project Morpheus lander flying a kilometer-long simulated surface approach while avoiding hazards in a landing field. The approach takes place at the Shuttle Landing Facili...

  6. Mountain permafrost detection inferred by a combined remote sensing, geomorphological and geophysical approach

    NASA Astrophysics Data System (ADS)

    Klug, Christoph; Mössinger, Max; Ott, Patrick; Rieg, Lorenzo; Sailer, Rudolf; Sass, Oliver; Stötter, Johann

    2013-04-01

    of the single datasets, a tomography including all results was created. For a further investigation of the occurrence and distribution of permafrost, 15 temperature-loggers were installed, which measured the base temperature of the snowpack (BTS) during the whole winter and so recorded potential freezing and thawing of the ground. This offered a further possibility for validation of the geophysical measurements. Additionally, the BTS was measured two times in the area close to the end of the winter snow accumulation period, to get a general idea of the possible distribution of permafrost or ice in the underground. The results of the measurements at Rofenberg show good correlation. In the areas detected within the multitemporal ALS dataset permafrost is assumed at a depth between 2 meters and 8 meters and similar ground structures can be spotted for every geophysical method. The combined approach of geophysical methods, remote sensing and field investigations allowed a profound cross-validation of the different methods.

  7. Holistic Approaches to Health.

    ERIC Educational Resources Information Center

    Dinkmeyer, Don; Dinkmeyer, Don, Jr.

    1979-01-01

    The holistic approach to health includes a spectrum of concepts that have an important influence on our health. Elementary school counselors must recognize this previously neglected need for a holistic approach. Stress, relaxation response, biofeedback, and the orthomolecular approach are discussed. (Author/BEF)

  8. MRI-based treatment plan simulation and adaptation for ion radiotherapy using a classification-based approach

    PubMed Central

    2013-01-01

    Background In order to benefit from the highly conformal irradiation of tumors in ion radiotherapy, sophisticated treatment planning and simulation are required. The purpose of this study was to investigate the potential of MRI for ion radiotherapy treatment plan simulation and adaptation using a classification-based approach. Methods Firstly, a voxelwise tissue classification was applied to derive pseudo CT numbers from MR images using up to 8 contrasts. Appropriate MR sequences and parameters were evaluated in cross-validation studies of three phantoms. Secondly, ion radiotherapy treatment plans were optimized using both MRI-based pseudo CT and reference CT and recalculated on reference CT. Finally, a target shift was simulated and a treatment plan adapted to the shift was optimized on a pseudo CT and compared to reference CT optimizations without plan adaptation. Results The derivation of pseudo CT values led to mean absolute errors in the range of 81 - 95 HU. Most significant deviations appeared at borders between air and different tissue classes and originated from partial volume effects. Simulations of ion radiotherapy treatment plans using pseudo CT for optimization revealed only small underdosages in distal regions of a target volume with deviations of the mean dose of PTV between 1.4 - 3.1% compared to reference CT optimizations. A plan adapted to the target volume shift and optimized on the pseudo CT exhibited a comparable target dose coverage as a non-adapted plan optimized on a reference CT. Conclusions We were able to show that a MRI-based derivation of pseudo CT values using a purely statistical classification approach is feasible although no physical relationship exists. Large errors appeared at compact bone classes and came from an imperfect distinction of bones and other tissue types in MRI. In simulations of treatment plans, it was demonstrated that these deviations are comparable to uncertainties of a target volume shift of 2 mm in two directions

  9. A Novel Approach to Determining Violence Risk in Schizophrenia: Developing a Stepped Strategy in 13,806 Discharged Patients

    PubMed Central

    Singh, Jay P.; Grann, Martin; Lichtenstein, Paul; Långström, Niklas; Fazel, Seena

    2012-01-01

    Clinical guidelines recommend that violence risk be assessed in schizophrenia. Current approaches are resource-intensive as they employ detailed clinical assessments of dangerousness for most patients. An alternative approach would be to first screen out patients at very low risk of future violence prior to more costly and time-consuming assessments. In order to implement such a stepped strategy, we developed a simple tool to screen out individuals with schizophrenia at very low risk of violent offending. We merged high quality Swedish national registers containing information on psychiatric diagnoses, socio-demographic factors, and violent crime. A cohort of 13,806 individuals with hospital discharge diagnoses of schizophrenia was identified and followed for up to 33 years for violent crime. Cox regression was used to determine risk factors for violent crime and construct the screening tool, the predictive validity of which was measured using four outcome statistics. The instrument was calibrated on 6,903 participants and cross-validated using three independent replication samples of 2,301 participants each. Regression analyses resulted in a tool composed of five items: male sex, previous criminal conviction, young age at assessment, comorbid alcohol abuse, and comorbid drug abuse. At 5 years after discharge, the instrument had a negative predictive value of 0.99 (95% CI = 0.98–0.99), meaning that very few individuals who the tool screened out (n = 2,359 out of original sample of 6,903) were subsequently convicted of a violent offence. Screening out patients who are at very low risk of violence prior to more detailed clinical assessment may assist the risk assessment process in schizophrenia. PMID:22359622

  10. Data-driven approach to Type Ia supernovae: variable selection on the peak luminosity and clustering in visual analytics

    NASA Astrophysics Data System (ADS)

    Uemura, Makoto; Kawabata, Koji S.; Ikeda, Shiro; Maeda, Keiichi; Wu, Hsiang-Yun; Watanabe, Kazuho; Takahashi, Shigeo; Fujishiro, Issei

    2016-03-01

    Type Ia supernovae (SNIa) have an almost uniform peak luminosity, so that they are used as “standard candle” to estimate distances to galaxies in cosmology. In this article, we introduce our two recent works on SNIa based on data-driven approach. The diversity in the peak luminosity of SNIa can be reduced by corrections in several variables. The color and decay rate have been used as the explanatory variables of the peak luminosity in past studies. However, it is proposed that their spectral data could give a better model of the peak luminosity. We use cross-validation in order to control the generalization error and a LASSO-type estimator in order to choose the set of variables. Using 78 samples and 276 candidates of variables, we confirm that the peak luminosity depends on the color and decay rate. Our analysis does not support adding any other variables in order to have a better generalization error. On the other hand, this analysis is based on the assumption that SNIa originate in a single population, while it is not trivial. Indeed, several sub-types possibly having different nature have been proposed. We used a visual analytics tool for the asymmetric biclustering method to find both a good set of variables and samples at the same time. Using 14 variables and 132 samples, we found that SNIa can be divided into two categories by the expansion velocity of ejecta. Those examples demonstrate that the data-driven approach is useful for high-dimensional large-volume data which becomes common in modern astronomy.

  11. Small-molecule interferon inducers. Toward the comprehension of the molecular determinants through ligand-based approaches.

    PubMed

    Musmuca, Ira; Simeoni, Silvia; Caroli, Antonia; Ragno, Rino

    2009-07-01

    Hepatitis C is becoming an increasingly common cause of mortality especially in the HIV-coinfected group. Due to the efficacy of interferon (IFN) based therapy in the treatment of hepatitis C, various compounds possessing IFN-inducing activity have been hitherto reported. In the present study, we describe how steric, electrostatic, hydrophobic, and hydrogen-bonding interactions might influence the biological activity of a published set of IFN inducers, using a three-dimensional quantitative structure-activity relationship (3-D QSAR) approach. Analyses were conducted evaluating different series of compounds structurally related to 8-hydroxyadenines and 1H-imidazo[4,5-c]quinolines. A ligand-based alignment protocol in combination with the GRID/GOLPE approach was applied: 62 3-D QSAR models were derived using different GRID probes and several training sets. Performed 3-D QSAR investigations proved to be of good statistical value displaying r2, q2CV-LOO, and cross-validated SDEP values of 0.73, 0.61, 0.61 and 0.89, 0.64, 0.58 using the OH or the DRY probe, respectively. Additionally, the predictive performance was evaluated using an external test set of 20 compounds. Analyses of the resulting models led to the definition of a pharmacophore model that can be of interest to explain the observed affinities of known compounds as well as to design novel low molecular weight IFN inducers (IFNIs). To the best of our knowledge, this is the first 3-D QSAR application on IFN-inducing agents. PMID:19499914

  12. Computer-aided detection of microcalcifications in digital breast tomosynthesis (DBT): a multichannel signal detection approach on projection views

    NASA Astrophysics Data System (ADS)

    Wei, Jun; Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A.; Zhou, Chuan; Lu, Yao

    2012-03-01

    DBT is one of the promising imaging modalities that may improve the sensitivity and specificity for breast cancer detection. We are developing a computer-aided detection (CADe) system for clustered microcalcifications (MC) in DBT. A data set of two-view DBTs from 42 breasts was collected with a GE prototype system. We investigated a 2D approach to MC detection using projection view (PV) images rather than reconstructed 3D DBT volume. Our 2D approach consisted of two major stages: 1) detecting individual MC candidates on each PV, and 2) correlating the MC candidates from the different PVs and detecting clusters in the breast volume. With the MC candidates detected by prescreening on PVs, a trained multi-channel (MCH) filter bank was used to extract signal response from each MC candidate. A ray-tracing process was performed to fuse the MCH responses and localize the MC candidates in 3D using the geometrical information of the DBT system. Potential MC clusters were then identified by dynamic clustering of the MCs in 3D. A two-fold cross-validation method was used to train and test the CADe system. The detection performance of clustered MCs was assessed by free receiver operating characteristic (FROC) analysis. It was found that the CADe system achieved a case-based sensitivity of 90% at an average false positive rate of 2.1 clusters per DBT volume. Our study demonstrated that the CADe system using 2D MCH filter bank is promising for detection of clustered MCs in DBT.

  13. Coronal loop detection and salient contour group extraction from solar images

    NASA Astrophysics Data System (ADS)

    Durak, Nurcan

    2011-01-01

    This dissertation addresses two different problems: 1) coronal loop detection from solar images: and 2) salient contour group extraction from cluttered images. In the first part, we propose two different solutions to the coronal loop detection problem. The first solution is a block-based coronal loop mining method that detects coronal loops from solar images by dividing the solar image into fixed sized blocks, labeling the blocks as "Loop" or "Non-Loop", extracting features from the labeled blocks, and finally training classifiers to generate learning models that can classify new image blocks. The block-based approach achieves 64% accuracy in 10-fold cross validation experiments. To improve the accuracy and scalability, we propose a contour-based coronal loop detection method that extracts contours from cluttered regions, then labels the contours as "Loop" and "Non-Loop", and extracts geometric features from the labeled contours. The contour-based approach achieves 85% accuracy in 10-fold cross validation experiments, which is a 20% increase compared to the block-based approach. In the second part, we propose a method to extract semi-elliptical open curves from cluttered regions. Our method consists of the following steps: obtaining individual smooth contours along with their saliency measures; then starting from the most salient contour, searching for possible grouping options for each contour; and continuing the grouping until an optimum solution is reached. Our work involved the design and development of a complete system for coronal loop mining in solar images, which required the formulation of new Gestalt perceptual rules and a systematic methodology to select and combine them in a fully automated judicious manner using machine learning techniques that eliminate the need to manually set various weight and threshold values to define an effective cost function. After finding salient contour groups, we close the gaps within the contours in each group and perform

  14. Modeling temporal sequences of cognitive state changes based on a combination of EEG-engagement, EEG-workload, and heart rate metrics.

    PubMed

    Stikic, Maja; Berka, Chris; Levendowski, Daniel J; Rubio, Roberto F; Tan, Veasna; Korszen, Stephanie; Barba, Douglas; Wurzer, David

    2014-01-01

    The objective of this study was to investigate the feasibility of physiological metrics such as ECG-derived heart rate and EEG-derived cognitive workload and engagement as potential predictors of performance on different training tasks. An unsupervised approach based on self-organizing neural network (NN) was utilized to model cognitive state changes over time. The feature vector comprised EEG-engagement, EEG-workload, and heart rate metrics, all self-normalized to account for individual differences. During the competitive training process, a linear topology was developed where the feature vectors similar to each other activated the same NN nodes. The NN model was trained and auto-validated on combat marksmanship training data from 51 participants that were required to make "deadly force decisions" in challenging combat scenarios. The trained NN model was cross validated using 10-fold cross-validation. It was also validated on a golf study in which additional 22 participants were asked to complete 10 sessions of 10 putts each. Temporal sequences of the activated nodes for both studies followed the same pattern of changes, demonstrating the generalization capabilities of the approach. Most node transition changes were local, but important events typically caused significant changes in the physiological metrics, as evidenced by larger state changes. This was investigated by calculating a transition score as the sum of subsequent state transitions between the activated NN nodes. Correlation analysis demonstrated statistically significant correlations between the transition scores and subjects' performances in both studies. This paper explored the hypothesis that temporal sequences of physiological changes comprise the discriminative patterns for performance prediction. These physiological markers could be utilized in future training improvement systems (e.g., through neurofeedback), and applied across a variety of training environments. PMID:25414629

  15. Learning Sequence Determinants of Protein:Protein Interaction Specificity with Sparse Graphical Models

    PubMed Central

    Kamisetty, Hetunandan; Ghosh, Bornika; Langmead, Christopher James; Bailey-Kellogg, Chris

    2015-01-01

    Abstract In studying the strength and specificity of interaction between members of two protein families, key questions center on which pairs of possible partners actually interact, how well they interact, and why they interact while others do not. The advent of large-scale experimental studies of interactions between members of a target family and a diverse set of possible interaction partners offers the opportunity to address these questions. We develop here a method, DgSpi (data-driven graphical models of specificity in protein:protein interactions), for learning and using graphical models that explicitly represent the amino acid basis for interaction specificity (why) and extend earlier classification-oriented approaches (which) to predict the ΔG of binding (how well). We demonstrate the effectiveness of our approach in analyzing and predicting interactions between a set of 82 PDZ recognition modules against a panel of 217 possible peptide partners, based on data from MacBeath and colleagues. Our predicted ΔG values are highly predictive of the experimentally measured ones, reaching correlation coefficients of 0.69 in 10-fold cross-validation and 0.63 in leave-one-PDZ-out cross-validation. Furthermore, the model serves as a compact representation of amino acid constraints underlying the interactions, enabling protein-level ΔG predictions to be naturally understood in terms of residue-level constraints. Finally, the model DgSpi readily enables the design of new interacting partners, and we demonstrate that designed ligands are novel and diverse. PMID:25973864

  16. Modeling temporal sequences of cognitive state changes based on a combination of EEG-engagement, EEG-workload, and heart rate metrics

    PubMed Central

    Stikic, Maja; Berka, Chris; Levendowski, Daniel J.; Rubio, Roberto F.; Tan, Veasna; Korszen, Stephanie; Barba, Douglas; Wurzer, David

    2014-01-01

    The objective of this study was to investigate the feasibility of physiological metrics such as ECG-derived heart rate and EEG-derived cognitive workload and engagement as potential predictors of performance on different training tasks. An unsupervised approach based on self-organizing neural network (NN) was utilized to model cognitive state changes over time. The feature vector comprised EEG-engagement, EEG-workload, and heart rate metrics, all self-normalized to account for individual differences. During the competitive training process, a linear topology was developed where the feature vectors similar to each other activated the same NN nodes. The NN model was trained and auto-validated on combat marksmanship training data from 51 participants that were required to make “deadly force decisions” in challenging combat scenarios. The trained NN model was cross validated using 10-fold cross-validation. It was also validated on a golf study in which additional 22 participants were asked to complete 10 sessions of 10 putts each. Temporal sequences of the activated nodes for both studies followed the same pattern of changes, demonstrating the generalization capabilities of the approach. Most node transition changes were local, but important events typically caused significant changes in the physiological metrics, as evidenced by larger state changes. This was investigated by calculating a transition score as the sum of subsequent state transitions between the activated NN nodes. Correlation analysis demonstrated statistically significant correlations between the transition scores and subjects' performances in both studies. This paper explored the hypothesis that temporal sequences of physiological changes comprise the discriminative patterns for performance prediction. These physiological markers could be utilized in future training improvement systems (e.g., through neurofeedback), and applied across a variety of training environments. PMID:25414629

  17. A Novel Two-Stage Tandem Mass Spectrometry Approach and Scoring Scheme for the Identification of O-GlcNAc Modified Peptides

    NASA Astrophysics Data System (ADS)

    Hahne, Hannes; Kuster, Bernhard

    2011-05-01

    The modification of serine and threonine residues in proteins by a single N-acetylglucosamine (O-GlcNAc) residue is an emerging post-translational modification (PTM) with broad biological implications. However, the systematic or large-scale analysis of this PTM is hampered by several factors, including low stoichiometry and the lability of the O-glycosidic bond during tandem mass spectrometry. Using a library of 72 synthetic glycopeptides, we developed a two-stage tandem MS approach consisting of pulsed Q dissociation (PQD) for O-GlcNAc peptide detection and electron transfer dissociation (ETD) for identification and site localization. Based on a set of O-GlcNAc specific fragment ions, we further developed a score (OScore) that discriminates O-GlcNAc peptide spectra from spectra of unmodified peptides with 95% sensitivity and >99% specificity. Integrating the OScore into the two-stage LC-MS/MS approach detected O-GlcNAc peptides in the low fmol range and at 10-fold better sensitivity than a single data-dependent ETD tandem MS experiment.

  18. Selection of a T7 promoter mutant with enhanced in vitro activity by a novel multi-copy bead display approach for in vitro evolution.

    PubMed

    Paul, Siddhartha; Stang, Alexander; Lennartz, Klaus; Tenbusch, Matthias; Überla, Klaus

    2013-01-01

    In vitro evolution of nucleic acids and proteins is a powerful strategy to optimize their biological and physical properties. To select proteins with the desired phenotype from large gene libraries, the proteins need to be linked to the gene they are encoded by. To facilitate selection of the desired phenotype and isolation of the encoding DNA, a novel bead display approach was developed, in which each member of a library of beads is first linked to multiple copies of a clonal gene variant by emulsion polymerase chain reaction. Beads are transferred to a second emulsion for an in vitro transcription-translation reaction, in which the protein encoded by each bead's amplicon covalently binds to the bead present in the same picoliter reactor. The beads then contain multiple copies of a clonal gene variant and multiple molecules of the protein encoded by the bead's gene variant and serve as the unit of selection. As a proof of concept, we screened a randomized library of the T7 promoter for high expression levels by flow cytometry and identified a T7 promoter variant with an ~10-fold higher in vitro transcriptional activity, confirming that the multi-copy bead display approach can be efficiently applied to in vitro evolution. PMID:23074193

  19. Selection of a T7 promoter mutant with enhanced in vitro activity by a novel multi-copy bead display approach for in vitro evolution

    PubMed Central

    Paul, Siddhartha; Stang, Alexander; Lennartz, Klaus; Tenbusch, Matthias; Überla, Klaus

    2013-01-01

    In vitro evolution of nucleic acids and proteins is a powerful strategy to optimize their biological and physical properties. To select proteins with the desired phenotype from large gene libraries, the proteins need to be linked to the gene they are encoded by. To facilitate selection of the desired phenotype and isolation of the encoding DNA, a novel bead display approach was developed, in which each member of a library of beads is first linked to multiple copies of a clonal gene variant by emulsion polymerase chain reaction. Beads are transferred to a second emulsion for an in vitro transcription–translation reaction, in which the protein encoded by each bead’s amplicon covalently binds to the bead present in the same picoliter reactor. The beads then contain multiple copies of a clonal gene variant and multiple molecules of the protein encoded by the bead’s gene variant and serve as the unit of selection. As a proof of concept, we screened a randomized library of the T7 promoter for high expression levels by flow cytometry and identified a T7 promoter variant with an ∼10-fold higher in vitro transcriptional activity, confirming that the multi-copy bead display approach can be efficiently applied to in vitro evolution. PMID:23074193

  20. Endoscopic thyroidectomy: retroauricular approach.

    PubMed

    Lee, Doh Young; Baek, Seung-Kuk; Jung, Kwang-Yoong

    2016-06-01

    The incidence of thyroid cancer has abruptly increased recently, with a female predominance. Conventional thyroidectomy using transcervical incision inevitably leaves an unfavorable neck scar; therefore, various extracervical approaches have been introduced to improve cosmetic satisfaction after thyroidectomy. Several reports demonstrated that these extracervical approaches have advantages not only in terms of cosmesis but also in terms of surgical outcomes and postoperative functional preservation. The retroauricular approach has advantages as the dissection area is smaller than that in the transaxillary approach (TA) and surgical anatomy is familiar to the head and neck surgeons. In addition, there is no concern about paresthesia around the nipple or anterior chest, and surgical direction makes central neck dissection easier than with the other extracervical approaches. Herein, we aim to introduce the surgical procedure of retroauricular approach thyroidectomy and present our experiences of postoperative outcomes. PMID:27294041

  1. Endoscopic thyroidectomy: retroauricular approach

    PubMed Central

    Lee, Doh Young; Baek, Seung-Kuk

    2016-01-01

    The incidence of thyroid cancer has abruptly increased recently, with a female predominance. Conventional thyroidectomy using transcervical incision inevitably leaves an unfavorable neck scar; therefore, various extracervical approaches have been introduced to improve cosmetic satisfaction after thyroidectomy. Several reports demonstrated that these extracervical approaches have advantages not only in terms of cosmesis but also in terms of surgical outcomes and postoperative functional preservation. The retroauricular approach has advantages as the dissection area is smaller than that in the transaxillary approach (TA) and surgical anatomy is familiar to the head and neck surgeons. In addition, there is no concern about paresthesia around the nipple or anterior chest, and surgical direction makes central neck dissection easier than with the other extracervical approaches. Herein, we aim to introduce the surgical procedure of retroauricular approach thyroidectomy and present our experiences of postoperative outcomes. PMID:27294041

  2. Risk Prediction of One-Year Mortality in Patients with Cardiac Arrhythmias Using Random Survival Forest

    PubMed Central

    Miao, Fen; Cai, Yun-Peng; Zhang, Yu-Xiao; Li, Ye; Zhang, Yuan-Ting

    2015-01-01

    Existing models for predicting mortality based on traditional Cox proportional hazard approach (CPH) often have low prediction accuracy. This paper aims to develop a clinical risk model with good accuracy for predicting 1-year mortality in cardiac arrhythmias patients using random survival forest (RSF), a robust approach for survival analysis. 10,488 cardiac arrhythmias patients available in the public MIMIC II clinical database were investigated, with 3,452 deaths occurring within 1-year followups. Forty risk factors including demographics and clinical and laboratory information and antiarrhythmic agents were analyzed as potential predictors of all-cause mortality. RSF was adopted to build a comprehensive survival model and a simplified risk model composed of 14 top risk factors. The built comprehensive model achieved a prediction accuracy of 0.81 measured by c-statistic with 10-fold cross validation. The simplified risk model also achieved a good accuracy of 0.799. Both results outperformed traditional CPH (which achieved a c-statistic of 0.733 for the comprehensive model and 0.718 for the simplified model). Moreover, various factors are observed to have nonlinear impact on cardiac arrhythmias prognosis. As a result, RSF based model which took nonlinearity into account significantly outperformed traditional Cox proportional hazard model and has great potential to be a more effective approach for survival analysis. PMID:26379761

  3. Predicting hydrofacies and hydraulic conductivity from direct-push data using a data-driven relevance vector machine approach: Motivations, algorithms, and application

    NASA Astrophysics Data System (ADS)

    Paradis, Daniel; Lefebvre, René; Gloaguen, Erwan; Rivera, Alfonso

    2015-01-01

    The spatial heterogeneity of hydraulic conductivity (K) exerts a major control on groundwater flow and solute transport. The heterogeneous spatial distribution of K can be imaged using indirect geophysical data as long as reliable relations exist to link geophysical data to K. This paper presents a nonparametric learning machine approach to predict aquifer K from cone penetrometer tests (CPT) coupled with a soil moisture and resistivity probe (SMR) using relevance vector machines (RVMs). The learning machine approach is demonstrated with an application to a heterogeneous unconsolidated littoral aquifer in a 12 km2 subwatershed, where relations between K and multiparameters CPT/SMR soundings appear complex. Our approach involved fuzzy clustering to define hydrofacies (HF) on the basis of CPT/SMR and K data prior to the training of RVMs for HFs recognition and K prediction on the basis of CPT/SMR data alone. The learning machine was built from a colocated training data set representative of the study area that includes K data from slug tests and CPT/SMR data up-scaled at a common vertical resolution of 15 cm with K data. After training, the predictive capabilities of the learning machine were assessed through cross validation with data withheld from the training data set and with K data from flowmeter tests not used during the training process. Results show that HF and K predictions from the learning machine are consistent with hydraulic tests. The combined use of CPT/SMR data and RVM-based learning machine proved to be powerful and efficient for the characterization of high-resolution K heterogeneity for unconsolidated aquifers.

  4. Critical Approaches to Film.

    ERIC Educational Resources Information Center

    Bywater, Timothy Robert

    This study deals primarily with recent academically oriented critical material, but it also embraces the range of film criticism that has been written for the mass audience in newspapers and periodicals. The study considers eight types of critical approaches to analyzing film: the journalistic approach, which contains both a reportorial-review and…

  5. Approaches to Truancy Prevention.

    ERIC Educational Resources Information Center

    Mogulescu, Sara; Segal, Heidi J.

    This report examines how New York counties can systematically and programmatically improve approaches to managing persons in need of supervision (PINS), describing approaches to truancy prevention and diversion that have been instituted nationwide and may be applicable to the PINS operating system. Researchers surveyed truancy-specific programs…

  6. Stuttering-Psycholinguistic Approach

    ERIC Educational Resources Information Center

    Hategan, Carolina Bodea; Anca, Maria; Prihoi, Lacramioara

    2012-01-01

    This research promotes psycholinguistic paradigm, it focusing in delimitating several specific particularities in stuttering pathology. Structural approach, on language sides proves both the recurrent aspects found within specialized national and international literature and the psycholinguistic approaches dependence on the features of the…

  7. The NLERAP Approach

    ERIC Educational Resources Information Center

    Nieto, Sonia; Rivera, Melissa; Irizarry, Jason

    2012-01-01

    From the start, NLERAP has been based on two major premises: one is that a sociocultural and sociopolitical approach to learning is more effective than a traditional approach, particularly in the case of populations that have historically been marginalized through their education; and the second is that research is more meaningful and inclusive…

  8. The Strategies Instructional Approach.

    ERIC Educational Resources Information Center

    Deshler, Donald D.; Lenz, B. Keith

    1989-01-01

    The strategies instructional approach developed at the University of Kansas Institute for Research in Learning Disabilities is described. The approach teaches students strategies in the academic, social, motivational, and executive functioning areas that will enable students to meet content learning demands and modifies instructional environments…

  9. Modular Approach for Ethics

    ERIC Educational Resources Information Center

    Wyne, Mudasser F.

    2010-01-01

    It is hard to define a single set of ethics that will cover an entire computer users community. In this paper, the issue is addressed in reference to code of ethics implemented by various professionals, institutes and organizations. The paper presents a higher level model using hierarchical approach. The code developed using this approach could be…

  10. Three-dimensional textural features of conventional MRI improve diagnostic classification of childhood brain tumours.

    PubMed

    Fetit, Ahmed E; Novak, Jan; Peet, Andrew C; Arvanitits, Theodoros N

    2015-09-01

    The aim of this study was to assess the efficacy of three-dimensional texture analysis (3D TA) of conventional MR images for the classification of childhood brain tumours in a quantitative manner. The dataset comprised pre-contrast T1 - and T2-weighted MRI series obtained from 48 children diagnosed with brain tumours (medulloblastoma, pilocytic astrocytoma and ependymoma). 3D and 2D TA were carried out on the images using first-, second- and higher order statistical methods. Six supervised classification algorithms were trained with the most influential 3D and 2D textural features, and their performances in the classification of tumour types, using the two feature sets, were compared. Model validation was carried out using the leave-one-out cross-validation (LOOCV) approach, as well as stratified 10-fold cross-validation, in order to provide additional reassurance. McNemar's test was used to test the statistical significance of any improvements demonstrated by 3D-trained classifiers. Supervised learning models trained with 3D textural features showed improved classification performances to those trained with conventional 2D features. For instance, a neural network classifier showed 12% improvement in area under the receiver operator characteristics curve (AUC) and 19% in overall classification accuracy. These improvements were statistically significant for four of the tested classifiers, as per McNemar's tests. This study shows that 3D textural features extracted from conventional T1 - and T2-weighted images can improve the diagnostic classification of childhood brain tumours. Long-term benefits of accurate, yet non-invasive, diagnostic aids include a reduction in surgical procedures, improvement in surgical and therapy planning, and support of discussions with patients' families. It remains necessary, however, to extend the analysis to a multicentre cohort in order to assess the scalability of the techniques used. PMID:26256809

  11. Urinary Cell mRNA Profiles and Differential Diagnosis of Acute Kidney Graft Dysfunction

    PubMed Central

    Matignon, Marie; Ding, Ruchuang; Dadhania, Darshana M.; Mueller, Franco B.; Hartono, Choli; Snopkowski, Catherine; Li, Carol; Lee, John R.; Sjoberg, Daniel; Seshan, Surya V.; Sharma, Vijay K.; Yang, Hua; Nour, Bakr; Vickers, Andrew J.; Suthanthiran, Manikkam

    2014-01-01

    Noninvasive tests to differentiate the basis for acute dysfunction of the kidney allograft are preferable to invasive allograft biopsies. We measured absolute levels of 26 prespecified mRNAs in urine samples collected from kidney graft recipients at the time of for-cause biopsy for acute allograft dysfunction and investigated whether differential diagnosis of acute graft dysfunction is feasible using urinary cell mRNA profiles. We profiled 52 urine samples from 52 patients with biopsy specimens indicating acute rejection (26 acute T cell–mediated rejection and 26 acute antibody-mediated rejection) and 32 urine samples from 32 patients with acute tubular injury without acute rejection. A stepwise quadratic discriminant analysis of mRNA measures identified a linear combination of mRNAs for CD3ε, CD105, TLR4, CD14, complement factor B, and vimentin that distinguishes acute rejection from acute tubular injury; 10-fold cross-validation of the six-gene signature yielded an estimate of the area under the curve of 0.92 (95% confidence interval, 0.86 to 0.98). In a decision analysis, the six-gene signature yielded the highest net benefit across a range of reasonable threshold probabilities for biopsy. Next, among patients diagnosed with acute rejection, a similar statistical approach identified a linear combination of mRNAs for CD3ε, CD105, CD14, CD46, and 18S rRNA that distinguishes T cell–mediated rejection from antibody-mediated rejection, with a cross-validated estimate of the area under the curve of 0.81 (95% confidence interval, 0.68 to 0.93). Incorporation of these urinary cell mRNA signatures in clinical decisions may reduce the number of biopsies in patients with acute dysfunction of the kidney allograft. PMID:24610929

  12. Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach?

    NASA Astrophysics Data System (ADS)

    Archfield, S. A.; Pugliese, A.; Castellarin, A.; Skøien, J. O.; Kiang, J. E.

    2013-04-01

    In the United States, estimation of flood frequency quantiles at ungauged locations has been largely based on regional regression techniques that relate measurable catchment descriptors to flood quantiles. More recently, spatial interpolation techniques of point data have been shown to be effective for predicting streamflow statistics (i.e., flood flows and low-flow indices) in ungauged catchments. Literature reports successful applications of two techniques, canonical kriging, CK (or physiographical-space-based interpolation, PSBI), and topological kriging, TK (or top-kriging). CK performs the spatial interpolation of the streamflow statistic of interest in the two-dimensional space of catchment descriptors. TK predicts the streamflow statistic along river networks taking both the catchment area and nested nature of catchments into account. It is of interest to understand how these spatial interpolation methods compare with generalized least squares (GLS) regression, one of the most common approaches to estimate flood quantiles at ungauged locations. By means of a leave-one-out cross-validation procedure, the performance of CK and TK was compared to GLS regression equations developed for the prediction of 10, 50, 100 and 500 yr floods for 61 streamgauges in the southeast United States. TK substantially outperforms GLS and CK for the study area, particularly for large catchments. The performance of TK over GLS highlights an important distinction between the treatments of spatial correlation when using regression-based or spatial interpolation methods to estimate flood quantiles at ungauged locations. The analysis also shows that coupling TK with CK slightly improves the performance of TK; however, the improvement is marginal when compared to the improvement in performance over GLS.

  13. Topological and canonical kriging for design flood prediction in ungauged catchments: an improvement over a traditional regional regression approach?

    USGS Publications Warehouse

    Archfield, Stacey A.; Pugliese, Alessio; Castellarin, Attilio; Skøien, Jon O.; Kiang, Julie E.

    2013-01-01

    In the United States, estimation of flood frequency quantiles at ungauged locations has been largely based on regional regression techniques that relate measurable catchment descriptors to flood quantiles. More recently, spatial interpolation techniques of point data have been shown to be effective for predicting streamflow statistics (i.e., flood flows and low-flow indices) in ungauged catchments. Literature reports successful applications of two techniques, canonical kriging, CK (or physiographical-space-based interpolation, PSBI), and topological kriging, TK (or top-kriging). CK performs the spatial interpolation of the streamflow statistic of interest in the two-dimensional space of catchment descriptors. TK predicts the streamflow statistic along river networks taking both the catchment area and nested nature of catchments into account. It is of interest to understand how these spatial interpolation methods compare with generalized least squares (GLS) regression, one of the most common approaches to estimate flood quantiles at ungauged locations. By means of a leave-one-out cross-validation procedure, the performance of CK and TK was compared to GLS regression equations developed for the prediction of 10, 50, 100 and 500 yr floods for 61 streamgauges in the southeast United States. TK substantially outperforms GLS and CK for the study area, particularly for large catchments. The performance of TK over GLS highlights an important distinction between the treatments of spatial correlation when using regression-based or spatial interpolation methods to estimate flood quantiles at ungauged locations. The analysis also shows that coupling TK with CK slightly improves the performance of TK; however, the improvement is marginal when compared to the improvement in performance over GLS.

  14. Continuous streamflow prediction in ungauged basins: The effects of equifinality and parameter set selection on uncertainty in regionalization approaches

    NASA Astrophysics Data System (ADS)

    Arsenault, Richard; Brissette, François P.

    2014-07-01

    This paper focuses on evaluating the uncertainty of three common regionalization methods for predicting continuous streamflow in ungauged basins. A set of 268 basins covering 1.6 million km2 in the province of Quebec was used to test the regionalization strategies. The multiple linear regression, spatial proximity, and physical similarity approaches were evaluated on the catchments using a leave-one-out cross-validation scheme. The lumped conceptual HSAMI hydrological model was used throughout the study. A bootstrapping method was chosen to further estimate uncertainty due to parameter set selection for each of the parameter set/regionalization method pairs. Results show that parameter set selection can play an important role in regionalization method performance depending on the regionalization methods (and their variants) used and that equifinality does not contribute significantly to the overall uncertainty witnessed throughout the regionalization methods applications. Regression methods fail to consistently assign behavioral parameter sets to the pseudoungauged basins (i.e., the ones left out). Spatial proximity and physical similarity score better, the latter being the best. It is also shown that combining either physical similarity or spatial proximity with the multiple linear regression method can lead to an even more successful prediction rate. However, even the best methods were shown to be unreliable to an extent, as successful prediction rates never surpass 75%. Finally, this paper shows that the selection of catchment descriptors is crucial to the regionalization strategies' performance and that for the HSAMI model, the optimal number of donor catchments for transferred parameter sets lies between four and seven.

  15. VOXEL-LEVEL MAPPING OF TRACER KINETICS IN PET STUDIES: A STATISTICAL APPROACH EMPHASIZING TISSUE LIFE TABLES1

    PubMed Central

    O’Sullivan, Finbarr; Muzi, Mark; Mankoff, David A.; Eary, Janet F.; Spence, Alexander M.; Krohn, Kenneth A.

    2014-01-01

    Most radiotracers used in dynamic positron emission tomography (PET) scanning act in a linear time-invariant fashion so that the measured time-course data are a convolution between the time course of the tracer in the arterial supply and the local tissue impulse response, known as the tissue residue function. In statistical terms the residue is a life table for the transit time of injected radiotracer atoms. The residue provides a description of the tracer kinetic information measurable by a dynamic PET scan. Decomposition of the residue function allows separation of rapid vascular kinetics from slower blood-tissue exchanges and tissue retention. For voxel-level analysis, we propose that residues be modeled by mixtures of nonparametrically derived basis residues obtained by segmentation of the full data volume. Spatial and temporal aspects of diagnostics associated with voxel-level model fitting are emphasized. Illustrative examples, some involving cancer imaging studies, are presented. Data from cerebral PET scanning with 18F fluoro-deoxyglucose (FDG) and 15O water (H2O) in normal subjects is used to evaluate the approach. Cross-validation is used to make regional comparisons between residues estimated using adaptive mixture models with more conventional compartmental modeling techniques. Simulations studies are used to theoretically examine mean square error performance and to explore the benefit of voxel-level analysis when the primary interest is a statistical summary of regional kinetics. The work highlights the contribution that multivariate analysis tools and life-table concepts can make in the recovery of local metabolic information from dynamic PET studies, particularly ones in which the assumptions of compartmental-like models, with residues that are sums of exponentials, might not be certain. PMID:25392718

  16. Data Mining Approach for Evaluating Vegetation Dynamics in Earth System Models (ESMs) Using Satellite Remote Sensing Products

    NASA Astrophysics Data System (ADS)

    Shu, S.; Hoffman, F. M.; Kumar, J.; Hargrove, W. W.; Jain, A. K.

    2014-12-01

    biome types. However, Mapcurves results showed a relatively low goodness of fit score for modeled phenology projected onto observations. This study demonstrates the utility of a data mining approach for cross-validation of observations and evaluation of model performance.

  17. DisoMCS: Accurately Predicting Protein Intrinsically Disordered Regions Using a Multi-Class Conservative Score Approach

    PubMed Central

    Wang, Zhiheng; Yang, Qianqian; Li, Tonghua; Cong, Peisheng

    2015-01-01

    The precise prediction of protein intrinsically disordered regions, which play a crucial role in biological procedures, is a necessary prerequisite to further the understanding of the principles and mechanisms of protein function. Here, we propose a novel predictor, DisoMCS, which is a more accurate predictor of protein intrinsically disordered regions. The DisoMCS bases on an original multi-class conservative score (MCS) obtained by sequence-order/disorder alignment. Initially, near-disorder regions are defined on fragments located at both the terminus of an ordered region connecting a disordered region. Then the multi-class conservative score is generated by sequence alignment against a known structure database and represented as order, near-disorder and disorder conservative scores. The MCS of each amino acid has three elements: order, near-disorder and disorder profiles. Finally, the MCS is exploited as features to identify disordered regions in sequences. DisoMCS utilizes a non-redundant data set as the training set, MCS and predicted secondary structure as features, and a conditional random field as the classification algorithm. In predicted near-disorder regions a residue is determined as an order or a disorder according to the optimized decision threshold. DisoMCS was evaluated by cross-validation, large-scale prediction, independent tests and CASP (Critical Assessment of Techniques for Protein Structure Prediction) tests. All results confirmed that DisoMCS was very competitive in terms of accuracy of prediction when compared with well-established publicly available disordered region predictors. It also indicated our approach was more accurate when a query has higher homologous with the knowledge database. Availability The DisoMCS is available at http://cal.tongji.edu.cn/disorder/. PMID:26090958

  18. Predicting The Rainy Season Over Southern West Africa From Global Predictors and Climate Model Output: A Mos Approach

    NASA Astrophysics Data System (ADS)

    Paeth, H.; Born, K.; Hense, A.

    As 75 % of annual precipitation over the Sahel and Guinea Coast region are confined to the rainy season between June and September, prediction of this season is largely rel- evant in terms of fresh water availability for vegetation and human activity. Therefore, we present various global near-surface predictors of summertime rainfall for different regions of West Africa. The most important predictability arises from more regional information such as the SST in the tropical and subtropical Atlantic or the large-scale surface pressure field over the West African subcontinent. However, there are some teleconnections to the tropical Pacific, involving ENSO and the Walker circulation. The extratropical circulation modes such as the NAO play a minor role over the north- western part of West Africa. Based on the whole 20th century validation period the impact of increasing GHG is barely apparent. The same goes for all India rainfall and the QBO. Using multiple regression and cross validation a forecast model for the rainy season is developped by which we gain insight into the optimal number of relevant predictors. Thus, predictors which result from statistical correlation rather than physical rela- tionship are discarded. The remaining predictors, partly derived from the EOF space, account for around 55 % of the simulated interannual variability. In terms of the ob- servations, the forecast model is composed of the global predictors mentioned above and the simulated seasonal rainfall from different global climate models. Then, the method reveals a forecast potential of slightly more than 50 % for the observed inter- annual variations in summertime rainfall over southern West Africa. Given the strong autocorrelation of tropical SST, our approach could be used for operational seasonal forecasting with reasonable computing time.

  19. A wrapper-based approach for feature selection and classification of major depressive disorder-bipolar disorders.

    PubMed

    Tekin Erguzel, Turker; Tas, Cumhur; Cebi, Merve

    2015-09-01

    Feature selection (FS) and classification are consecutive artificial intelligence (AI) methods used in data analysis, pattern classification, data mining and medical informatics. Beside promising studies in the application of AI methods to health informatics, working with more informative features is crucial in order to contribute to early diagnosis. Being one of the prevalent psychiatric disorders, depressive episodes of bipolar disorder (BD) is often misdiagnosed as major depressive disorder (MDD), leading to suboptimal therapy and poor outcomes. Therefore discriminating MDD and BD at earlier stages of illness could help to facilitate efficient and specific treatment. In this study, a nature inspired and novel FS algorithm based on standard Ant Colony Optimization (ACO), called improved ACO (IACO), was used to reduce the number of features by removing irrelevant and redundant data. The selected features were then fed into support vector machine (SVM), a powerful mathematical tool for data classification, regression, function estimation and modeling processes, in order to classify MDD and BD subjects. Proposed method used coherence, a promising quantitative electroencephalography (EEG) biomarker, values calculated from alpha, theta and delta frequency bands. The noteworthy performance of novel IACO-SVM approach stated that it is possible to discriminate 46 BD and 55 MDD subjects using 22 of 48 features with 80.19% overall classification accuracy. The performance of IACO algorithm was also compared to the performance of standard ACO, genetic algorithm (GA) and particle swarm optimization (PSO) algorithms in terms of their classification accuracy and number of selected features. In order to provide an almost unbiased estimate of classification error, the validation process was performed using nested cross-validation (CV) procedure. PMID:26164033

  20. A hybrid approach for rapid, accurate, and direct kilovoltage radiation dose calculations in CT voxel space

    SciTech Connect

    Kouznetsov, Alexei; Tambasco, Mauro

    2011-03-15

    Purpose: To develop and validate a fast and accurate method that uses computed tomography (CT) voxel data to estimate absorbed radiation dose at a point of interest (POI) or series of POIs from a kilovoltage (kV) imaging procedure. Methods: The authors developed an approach that computes absorbed radiation dose at a POI by numerically evaluating the linear Boltzmann transport equation (LBTE) using a combination of deterministic and Monte Carlo (MC) techniques. This hybrid approach accounts for material heterogeneity with a level of accuracy comparable to the general MC algorithms. Also, the dose at a POI is computed within seconds using the Intel Core i7 CPU 920 2.67 GHz quad core architecture, and the calculations are performed using CT voxel data, making it flexible and feasible for clinical applications. To validate the method, the authors constructed and acquired a CT scan of a heterogeneous block phantom consisting of a succession of slab densities: Tissue (1.29 cm), bone (2.42 cm), lung (4.84 cm), bone (1.37 cm), and tissue (4.84 cm). Using the hybrid transport method, the authors computed the absorbed doses at a set of points along the central axis and x direction of the phantom for an isotropic 125 kVp photon spectral point source located along the central axis 92.7 cm above the phantom surface. The accuracy of the results was compared to those computed with MCNP, which was cross-validated with EGSnrc, and served as the benchmark for validation. Results: The error in the depth dose ranged from -1.45% to +1.39% with a mean and standard deviation of -0.12% and 0.66%, respectively. The error in the x profile ranged from -1.3% to +0.9%, with standard deviations of -0.3% and 0.5%, respectively. The number of photons required to achieve these results was 1x10{sup 6}. Conclusions: The voxel-based hybrid method evaluates the LBTE rapidly and accurately to estimate the absorbed x-ray dose at any POI or series of POIs from a kV imaging procedure.

  1. A hierarchical approach for online temporal lobe seizure detection in long-term intracranial EEG recordings

    NASA Astrophysics Data System (ADS)

    Liang, Sheng-Fu; Chen, Yi-Chun; Wang, Yu-Lin; Chen, Pin-Tzu; Yang, Chia-Hsiang; Chiueh, Herming

    2013-08-01

    Objective. Around 1% of the world's population is affected by epilepsy, and nearly 25% of patients cannot be treated effectively by available therapies. The presence of closed-loop seizure-triggered stimulation provides a promising solution for these patients. Realization of fast, accurate, and energy-efficient seizure detection is the key to such implants. In this study, we propose a two-stage on-line seizure detection algorithm with low-energy consumption for temporal lobe epilepsy (TLE). Approach. Multi-channel signals are processed through independent component analysis and the most representative independent component (IC) is automatically selected to eliminate artifacts. Seizure-like intracranial electroencephalogram (iEEG) segments are fast detected in the first stage of the proposed method and these seizures are confirmed in the second stage. The conditional activation of the second-stage signal processing reduces the computational effort, and hence energy, since most of the non-seizure events are filtered out in the first stage. Main results. Long-term iEEG recordings of 11 patients who suffered from TLE were analyzed via leave-one-out cross validation. The proposed method has a detection accuracy of 95.24%, a false alarm rate of 0.09/h, and an average detection delay time of 9.2 s. For the six patients with mesial TLE, a detection accuracy of 100.0%, a false alarm rate of 0.06/h, and an average detection delay time of 4.8 s can be achieved. The hierarchical approach provides a 90% energy reduction, yielding effective and energy-efficient implementation for real-time epileptic seizure detection. Significance. An on-line seizure detection method that can be applied to monitor continuous iEEG signals of patients who suffered from TLE was developed. An IC selection strategy to automatically determine the most seizure-related IC for seizure detection was also proposed. The system has advantages of (1) high detection accuracy, (2) low false alarm, (3) short

  2. Validation of the Chinese Version of the Life Orientation Test with a Robust Weighted Least Squares Approach

    ERIC Educational Resources Information Center

    Li, Cheng-Hsien

    2012-01-01

    Of the several measures of optimism presently available in the literature, the Life Orientation Test (LOT; Scheier & Carver, 1985) has been the most widely used in empirical research. This article explores, confirms, and cross-validates the factor structure of the Chinese version of the LOT with ordinal data by using robust weighted least squares…

  3. Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects.

    PubMed

    Moradi, Elaheh; Pepe, Antonietta; Gaser, Christian; Huttunen, Heikki; Tohka, Jussi

    2015-01-01

    Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive decline and Alzheimer's disease (AD). For the effective treatment of AD, it would be important to identify MCI patients at high risk for conversion to AD. In this study, we present a novel magnetic resonance imaging (MRI)-based method for predicting the MCI-to-AD conversion from one to three years before the clinical diagnosis. First, we developed a novel MRI biomarker of MCI-to-AD conversion using semi-supervised learning and then integrated it with age and cognitive measures about the subjects using a supervised learning algorithm resulting in what we call the aggregate biomarker. The novel characteristics of the methods for learning the biomarkers are as follows: 1) We used a semi-supervised learning method (low density separation) for the construction of MRI biomarker as opposed to more typical supervised methods; 2) We performed a feature selection on MRI data from AD subjects and normal controls without using data from MCI subjects via regularized logistic regression; 3) We removed the aging effects from the MRI data before the classifier training to prevent possible confounding between AD and age related atrophies; and 4) We constructed the aggregate biomarker by first learning a separate MRI biomarker and then combining it with age and cognitive measures about the MCI subjects at the baseline by applying a random forest classifier. We experimentally demonstrated the added value of these novel characteristics in predicting the MCI-to-AD conversion on data obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. With the ADNI data, the MRI biomarker achieved a 10-fold cross-validated area under the receiver operating characteristic curve (AUC) of 0.7661 in discriminating progressive MCI patients (pMCI) from stable MCI patients (sMCI). Our aggregate biomarker based on MRI data together with baseline cognitive measurements and age achieved a 10-fold cross-validated

  4. Evaluation of the predictive capacity of DNA variants associated with straight hair in Europeans.

    PubMed

    Pośpiech, Ewelina; Karłowska-Pik, Joanna; Marcińska, Magdalena; Abidi, Sarah; Andersen, Jeppe Dyrberg; van den Berge, Margreet; Carracedo, Ángel; Eduardoff, Mayra; Freire-Aradas, Ana; Morling, Niels; Sijen, Titia; Skowron, Małgorzata; Söchtig, Jens; Syndercombe-Court, Denise; Weiler, Natalie; Schneider, Peter M; Ballard, David; Børsting, Claus; Parson, Walther; Phillips, Chris; Branicki, Wojciech

    2015-11-01

    DNA-based prediction of hair morphology, defined as straight, curly or wavy hair, could contribute to an improved description of an unknown offender and allow more accurate forensic reconstructions of physical appearance in the field of forensic DNA phenotyping. Differences in scalp hair morphology are significant at the worldwide scale and within Europe. The only genome-wide association study made to date revealed the Trichohyalin gene (TCHH) to be significantly associated with hair morphology in Europeans and reported weaker associations for WNT10A and FRAS1 genes. We conducted a study that centered on six SNPs located in these three genes with a sample of 528 individuals from Poland. The predictive capacity of the candidate DNA variants was evaluated using logistic regression; classification and regression trees; and neural networks, by applying a 10-fold cross validation procedure. Additionally, an independent test set of 142 males from six European populations was used to verify performance of the developed prediction models. Our study confirmed association of rs11803731 (TCHH), rs7349332 (WNT10A) and rs1268789 (FRAS1) SNPs with hair morphology. The combined genotype risk score for straight hair had an odds ratio of 2.7 and these predictors explained ∼ 8.2% of the total variance. The selected three SNPs were found to predict straight hair with a high sensitivity but low specificity when a 10-fold cross validation procedure was applied and the best results were obtained using the neural networks approach (AUC=0.688, sensitivity=91.2%, specificity=23.0%). Application of the neural networks model with 65% probability threshold on an additional test set gave high sensitivity (81.4%) and improved specificity (50.0%) with a total of 78.7% correct calls, but a high non-classification rate (66.9%). The combined TTGGGG SNP genotype for rs11803731, rs7349332, rs1268789 (European frequency=4.5%) of all six straight hair-associated alleles was identified as the best

  5. The case study approach

    PubMed Central

    2011-01-01

    The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports. PMID:21707982

  6. Approaches to Human Communication.

    ERIC Educational Resources Information Center

    Budd, Richard W., Ed.; Ruben, Brent D., Ed.

    This anthology of essays approaches human communication from the points of view of: anthropology, art biology, economics, encounter groups, semantics, general system theory, history, information theory, international behavior, journalism, linguistics, mass media, neurophysiology, nonverbal behavior, organizational behavior, philosophy, political…

  7. Tiny Asteroid Approaches Earth

    NASA Video Gallery

    On Oct. 15, 2010, NASA astronomer Rob Suggs captured this view of the tiny asteroid 2010 TG19 as it made its way among the stars of the constellation Pegasus. It will continue to approach during th...

  8. SOHO Sees Venus' Approach

    NASA Video Gallery

    This video taken by the Solar and Heliospheric Observatory (SOHO) shows the Sun's corona and Venus' approach for the transit. This was taken with the Extreme ultraviolet Imaging Telescope (EIT) in ...

  9. Interdisciplinary Approaches to Astronomy.

    ERIC Educational Resources Information Center

    Fraknoi, Andrew

    1986-01-01

    Provides a bibliography of materials which deal with astronomy and: (1) science fiction; (2) poetry; (3) general fiction; (4) music; (5) psychology; and (6) the law. Also cites two general references on interdisciplinary approaches with astronomy topics. (JN)

  10. ECASTAR systems approach

    NASA Technical Reports Server (NTRS)

    1975-01-01

    The methodology of ECASTAR was presented and a discussion of the application of technology to energy conservation was given. This methodology constitutes an overview and blueprint for the analysis of energy conservation actions, and is subdivided into the following sections: the systems approach, constraints and criteria, application of the method (systems approach display, ECASTAR team, study phases and objectives, requirements and impacts, trade-off, integration, and feedback), an example of the method (technology applications).

  11. Cultural Approaches to Parenting

    PubMed Central

    Bornstein, Marc H.

    2012-01-01

    SYNOPSIS This article first introduces some main ideas behind culture and parenting and next addresses philosophical rationales and methodological considerations central to cultural approaches to parenting, including a brief account of a cross-cultural study of parenting. It then focuses on universals, specifics, and distinctions between form (behavior) and function (meaning) in parenting as embedded in culture. The article concludes by pointing to social policy implications as well as future directions prompted by a cultural approach to parenting. PMID:22962544

  12. Ten practice redesign approaches.

    PubMed

    Slayton, Val

    2013-01-01

    As healthcare delivery continues to evolve at a rapid pace, practices need to consider redesign approaches to stay ahead of the pack. From national policy and private payer initiatives to societal macro trends and the growing use of mobile technologies, delivering value, understanding customer needs, and assessing satisfaction are important elements to achieve and maintain success. This article discusses 10 practice redesign approaches. PMID:24228375

  13. Using nanoinformatics methods for automatically identifying relevant nanotoxicology entities from the literature.

    PubMed

    García-Remesal, Miguel; García-Ruiz, Alejandro; Pérez-Rey, David; de la Iglesia, Diana; Maojo, Víctor

    2013-01-01

    Nanoinformatics is an emerging research field that uses informatics techniques to collect, process, store, and retrieve data, information, and knowledge on nanoparticles, nanomaterials, and nanodevices and their potential applications in health care. In this paper, we have focused on the solutions that nanoinformatics can provide to facilitate nanotoxicology research. For this, we have taken a computational approach to automatically recognize and extract nanotoxicology-related entities from the scientific literature. The desired entities belong to four different categories: nanoparticles, routes of exposure, toxic effects, and targets. The entity recognizer was trained using a corpus that we specifically created for this purpose and was validated by two nanomedicine/nanotoxicology experts. We evaluated the performance of our entity recognizer using 10-fold cross-validation. The precisions range from 87.6% (targets) to 93.0% (routes of exposure), while recall values range from 82.6% (routes of exposure) to 87.4% (toxic effects). These results prove the feasibility of using computational approaches to reliably perform different named entity recognition (NER)-dependent tasks, such as for instance augmented reading or semantic searches. This research is a "proof of concept" that can be expanded to stimulate further developments that could assist researchers in managing data, information, and knowledge at the nanolevel, thus accelerating research in nanomedicine. PMID:23509721

  14. Using Nanoinformatics Methods for Automatically Identifying Relevant Nanotoxicology Entities from the Literature

    PubMed Central

    García-Remesal, Miguel; García-Ruiz, Alejandro; Pérez-Rey, David; de la Iglesia, Diana; Maojo, Víctor

    2013-01-01

    Nanoinformatics is an emerging research field that uses informatics techniques to collect, process, store, and retrieve data, information, and knowledge on nanoparticles, nanomaterials, and nanodevices and their potential applications in health care. In this paper, we have focused on the solutions that nanoinformatics can provide to facilitate nanotoxicology research. For this, we have taken a computational approach to automatically recognize and extract nanotoxicology-related entities from the scientific literature. The desired entities belong to four different categories: nanoparticles, routes of exposure, toxic effects, and targets. The entity recognizer was trained using a corpus that we specifically created for this purpose and was validated by two nanomedicine/nanotoxicology experts. We evaluated the performance of our entity recognizer using 10-fold cross-validation. The precisions range from 87.6% (targets) to 93.0% (routes of exposure), while recall values range from 82.6% (routes of exposure) to 87.4% (toxic effects). These results prove the feasibility of using computational approaches to reliably perform different named entity recognition (NER)-dependent tasks, such as for instance augmented reading or semantic searches. This research is a “proof of concept” that can be expanded to stimulate further developments that could assist researchers in managing data, information, and knowledge at the nanolevel, thus accelerating research in nanomedicine. PMID:23509721

  15. A novel method for predicting post-translational modifications on serine and threonine sites by using site-modification network profiles.

    PubMed

    Wang, Minghui; Jiang, Yujie; Xu, Xiaoyi

    2015-11-01

    Post-translational modifications (PTMs) regulate many aspects of biological behaviours including protein-protein interactions and cellular processes. Identification of PTM sites is helpful for understanding the PTM regulatory mechanisms. The PTMs on serine and threonine sites include phosphorylation, O-linked glycosylation and acetylation. Although a lot of computational approaches have been developed for PTM site prediction, currently most of them generate the predictive models by employing only local sequence information and few of them consider the relationship between different PTMs. In this paper, by adopting the site-modification network (SMNet) profiles that efficiently incorporate in situ PTM information, we develop a novel method to predict PTM sites on serine and threonine. PTM data are collected from various PTM databases and the SMNet is built to reflect the relationship between multiple PTMs, from which SMNet profiles are extracted to train predictive models based on SVM. Performance analysis of the SVM models shows that the SMNet profiles play an important role in accurately predicting PTM sites on serine and threonine. Furthermore, the proposed method is compared with existing PTM prediction approaches. The results from 10-fold cross-validation demonstrate that the proposed method with SMNet profiles performs remarkably better than existing methods, suggesting the power of SMNet profiles in identifying PTM sites. PMID:26344496

  16. Segmentation of skin strata in reflectance confocal microscopy depth stacks

    NASA Astrophysics Data System (ADS)

    Hames, Samuel C.; Ardigò, Marco; Soyer, H. Peter; Bradley, Andrew P.; Prow, Tarl W.

    2015-03-01

    Reflectance confocal microscopy is an emerging tool for imaging human skin, but currently requires expert human assessment. To overcome the need for human experts it is necessary to develop automated tools for automatically assessing reflectance confocal microscopy imagery. This work presents a novel approach to this task, using a bag of visual words approach to represent and classify en-face optical sections from four distinct strata of the skin. A dictionary of representative features is learned from whitened and normalised patches using hierarchical spherical k-means. Each image is then represented by extracting a dense array of patches and encoding each with the most similar element in the dictionary. Linear discriminant analysis is used as a simple linear classifier. The proposed framework was tested on 308 depth stacks from 54 volunteers. Parameters are tuned using 10 fold cross validation on a training sub-set of the data, and final evaluation was performed on a held out test set. The proposed method generated physically plausible profiles of the distinct strata of human skin, and correctly classified 81.4% of sections in the test set.

  17. Integrated Cortical Structural Marker for Alzheimer’s Disease

    PubMed Central

    Ming, Jing; Harms, Michael P.; Morris, John C.; Beg, Mirza Faisal; Wang, Lei

    2014-01-01

    In this paper we propose an approach to integrate cortical morphology measures for improving the discrimination of individuals with and without very mild AD. FreeSurfer was applied to scans collected from 83 participants with very mild AD and 124 cognitively normal individuals. We generated cortex thickness, white matter convexity (aka “sulcal depth”) and white matter surface metric distortion measures on a normalized surface atlas in this first study to integrate high resolution gray matter thickness and white matter surface geometric measures in identifying very mild AD. Principal component analysis (PCA) was applied to each individual structural measure to generate eigenvectors. Discrimination power based on individual and combined measures are compared, based on stepwise logistic regression and 10-fold cross-validation. Global AD likelihood index and surface-based likelihood maps were also generated. Our results show complementary patterns on the cortical surface between thickness, which reflects gray matter atrophy, convexity, which reflects white matter sulcal depth changes; and metric distortion, which reflects white matter surface area changes. The classifier integrating all three types of surface measures significantly improved classification performance compared to classification based on single measures. The PCA-based approach provides a framework for achieving high discrimination power by integrating high-dimensional data, and this method could be very powerful in future studies for early diagnosis of diseases that are known to be associated with abnormal gyral and sulcal patterns. PMID:25444604

  18. [Prediction of lipases types by different scale pseudo-amino acid composition].

    PubMed

    Zhang, Guangya; Li, Hongchun; Gao, Jiaqiang; Fang, Baishan

    2008-11-01

    Lipases are widely used enzymes in biotechnology. Although they catalyze the same reaction, their sequences vary. Therefore, it is highly desired to develop a fast and reliable method to identify the types of lipases according to their sequences, or even just to confirm whether they are lipases or not. By proposing two scales based pseudo amino acid composition approaches to extract the features of the sequences, a powerful predictor based on k-nearest neighbor was introduced to address the problems. The overall success rates thus obtained by the 10-fold cross-validation test were shown as below: for predicting lipases and nonlipase, the success rates were 92.8%, 91.4% and 91.3%, respectively. For lipase types, the success rates were 92.3%, 90.3% and 89.7%, respectively. Among them, the Z scales based pseudo amino acid composition was the best, T scales was the second. They outperformed significantly than 6 other frequently used sequence feature extraction methods. The high success rates yielded for such a stringent dataset indicate predicting the types of lipases is feasible and the different scales pseudo amino acid composition might be a useful tool for extracting the features of protein sequences, or at lease can play a complementary role to many of the other existing approaches. PMID:19256347

  19. Integrated cortical structural marker for Alzheimer's disease.

    PubMed

    Ming, Jing; Harms, Michael P; Morris, John C; Beg, M Faisal; Wang, Lei

    2015-01-01

    In this article, we propose an approach to integrate cortical morphology measures for improving the discrimination of individuals with and without very mild Alzheimer's disease (AD). FreeSurfer was applied to scans collected from 83 participants with very mild AD and 124 cognitively normal individuals. We generated cortex thickness, white matter convexity (aka "sulcal depth"), and white matter surface metric distortion measures on a normalized surface atlas in this first study to integrate high resolution gray matter thickness and white matter surface geometric measures in identifying very mild AD. Principal component analysis was applied to each individual structural measure to generate eigenvectors. Discrimination power based on individual and combined measures are compared, based on stepwise logistic regression and 10-fold cross-validation. Global AD likelihood index and surface-based likelihood maps were also generated. Our results show complementary patterns on the cortical surface between thickness, which reflects gray matter atrophy, convexity, which reflects white matter sulcal depth changes and metric distortion, which reflects white matter surface area changes. The classifier integrating all 3 types of surface measures significantly improved classification performance compared with classification based on single measures. The principal component analysis-based approach provides a framework for achieving high discrimination power by integrating high-dimensional data, and this method could be very powerful in future studies for early diagnosis of diseases that are known to be associated with abnormal gyral and sulcal patterns. PMID:25444604

  20. Combining Land-Use Regression and Chemical Transport Modeling in a Spatiotemporal Geostatistical Model for Ozone and PM2.5.

    PubMed

    Wang, Meng; Sampson, Paul D; Hu, Jianlin; Kleeman, Michael; Keller, Joshua P; Olives, Casey; Szpiro, Adam A; Vedal, Sverre; Kaufman, Joel D

    2016-05-17

    Assessments of long-term air pollution exposure in population studies have commonly employed land-use regression (LUR) or chemical transport modeling (CTM) techniques. Attempts to incorporate both approaches in one modeling framework are challenging. We present a novel geostatistical modeling framework, incorporating CTM predictions into a spatiotemporal LUR model with spatial smoothing to estimate spatiotemporal variability of ozone (O3) and particulate matter with diameter less than 2.5 μm (PM2.5) from 2000 to 2008 in the Los Angeles Basin. The observations include over 9 years' data from more than 20 routine monitoring sites and specific monitoring data at over 100 locations to provide more comprehensive spatial coverage of air pollutants. Our composite modeling approach outperforms separate CTM and LUR models in terms of root-mean-square error (RMSE) assessed by 10-fold cross-validation in both temporal and spatial dimensions, with larger improvement in the accuracy of predictions for O3 (RMSE [ppb] for CTM, 6.6; LUR, 4.6; composite, 3.6) than for PM2.5 (RMSE [μg/m(3)] CTM: 13.7, LUR: 3.2, composite: 3.1). Our study highlights the opportunity for future exposure assessment to make use of readily available spatiotemporal modeling methods and auxiliary gridded data that takes chemical reaction processes into account to improve the accuracy of predictions in a single spatiotemporal modeling framework. PMID:27074524

  1. MOWGLI: prediction of protein-MannOse interacting residues With ensemble classifiers usinG evoLutionary Information.

    PubMed

    Pai, Priyadarshini P; Mondal, Sukanta

    2016-10-01

    Proteins interact with carbohydrates to perform various cellular interactions. Of the many carbohydrate ligands that proteins bind with, mannose constitute an important class, playing important roles in host defense mechanisms. Accurate identification of mannose-interacting residues (MIR) may provide important clues to decipher the underlying mechanisms of protein-mannose interactions during infections. This study proposes an approach using an ensemble of base classifiers for prediction of MIR using their evolutionary information in the form of position-specific scoring matrix. The base classifiers are random forests trained by different subsets of training data set Dset128 using 10-fold cross-validation. The optimized ensemble of base classifiers, MOWGLI, is then used to predict MIR on protein chains of the test data set Dtestset29 which showed a promising performance with 92.0% accurate prediction. An overall improvement of 26.6% in precision was observed upon comparison with the state-of-art. It is hoped that this approach, yielding enhanced predictions, could be eventually used for applications in drug design and vaccine development. PMID:26457920

  2. Ontology driven decision support for the diagnosis of mild cognitive impairment.

    PubMed

    Zhang, Xiaowei; Hu, Bin; Ma, Xu; Moore, Philip; Chen, Jing

    2014-03-01

    In recent years, mild cognitive impairment (MCI) has attracted significant attention as an indicator of high risk for Alzheimer's disease (AD), and the diagnosis of MCI can alert patient to carry out appropriate strategies to prevent AD. To avoid subjectivity in diagnosis, we propose an ontology driven decision support method which is an automated procedure for diagnosing MCI through magnetic resonance imaging (MRI). In this approach, we encode specialized MRI knowledge into an ontology and construct a rule set using machine learning algorithms. Then we apply these two parts in conjunction with reasoning engine to automatically distinguish MCI patients from normal controls (NC). The rule set is trained by MRI data of 187 MCI patients and 177 normal controls selected from Alzheimer's Disease Neuroimaging Initiative (ADNI) using C4.5 algorithm. By using a 10-fold cross validation, we prove that the performance of C4.5 with 80.2% sensitivity is better than other algorithms, such as support vector machine (SVM), Bayesian network (BN) and back propagation (BP) neural networks, and C4.5 is suitable for the construction of reasoning rules. Meanwhile, the evaluation results suggest that our approach would be useful to assist physicians efficiently in real clinical diagnosis for the disease of MCI. PMID:24468160

  3. A fast SCOP fold classification system using content-based E-Predict algorithm

    PubMed Central

    Chi, Pin-Hao; Shyu, Chi-Ren; Xu, Dong

    2006-01-01

    Background Domain experts manually construct the Structural Classification of Protein (SCOP) database to categorize and compare protein structures. Even though using the SCOP database is believed to be more reliable than classification results from other methods, it is labor intensive. To mimic human classification processes, we develop an automatic SCOP fold classification system to assign possible known SCOP folds and recognize novel folds for newly-discovered proteins. Results With a sufficient amount of ground truth data, our system is able to assign the known folds for newly-discovered proteins in the latest SCOP v1.69 release with 92.17% accuracy. Our system also recognizes the novel folds with 89.27% accuracy using 10 fold cross validation. The average response time for proteins with 500 and 1409 amino acids to complete the classification process is 4.1 and 17.4 seconds, respectively. By comparison with several structural alignment algorithms, our approach outperforms previous methods on both the classification accuracy and efficiency. Conclusion In this paper, we build an advanced, non-parametric classifier to accelerate the manual classification processes of SCOP. With satisfactory ground truth data from the SCOP database, our approach identifies relevant domain knowledge and yields reasonably accurate classifications. Our system is publicly accessible at . PMID:16872501

  4. Exploration of the structural requirements of HIV-protease inhibitors using pharmacophore, virtual screening and molecular docking approaches for lead identification.

    PubMed

    Islam, Md Ataul; Pillay, Tahir S

    2015-03-01

    Pharmacoinformatics approaches are widely used in the field of drug discovery as it saves time, investment and animal sacrifice. In the present study, pharmacore-based virtual screening was adopted to identify potential HIV-protease ligands as anti-HIV agents. Pharmacophore is the 3D orientation and spatial arrangement of functional groups that are critical for binding at the active site cavity. Virtual screening retrieves potential hit molecules from databases based on imposed criteria. A set of 30 compounds were selected with inhibition constant as training set from 129 compounds of dataset set and subsequently the pharmacophore model was developed. The selected best model consists of hydrogen bond acceptor and donor, hydrophobic and aromatic ring, features critical for HIV-protease inhibitors. The model exhibits high correlation (R=0.933), less rmsd (1.014), high cross validated correlation coefficient (Q(2)=0.872) among the ten models examined and validated by Fischer's randomization test at 95% confidence level. The acceptable parameters of test set prediction, such as R(pred)(2)=0.768 and r(m(test))(2)=0.711 suggested that external predictivity of the model was significant. The pharmacophore model was used to perform a virtual screening employing the NCI database. Initial hits were sorted using a number of parameters and finally seven compounds were proposed as potential HIV-protease molecules. One potential HIV-protease ligand is reportedly confirmed as an active agent for anti-HIV screening, validating the current approach. It can be postulated that the pharmacophore model facilitates the selection of novel scaffold of HIV-protease inhibitors and can also allow the design of new chemical entities. PMID:25541527

  5. Development of 3D-QSAR Model for Acetylcholinesterase Inhibitors Using a Combination of Fingerprint, Molecular Docking, and Structure-Based Pharmacophore Approaches.

    PubMed

    Lee, Sehan; Barron, Mace G

    2015-11-01

    Acetylcholinesterase (AChE), a serine hydrolase vital for regulating the neurotransmitter acetylcholine in animals, has been used as a target for drugs and pesticides. With the increasing availability of AChE crystal structures, with or without ligands bound, structure-based approaches have been successfully applied to AChE inhibitors (AChEIs). The major limitation of these approaches has been the small applicability domain due to the lack of structural diversity in the training set. In this study, we developed a 3 dimensional quantitative structure-activity relationship (3D-QSAR) for inhibitory activity of 89 reversible and irreversible AChEIs including drugs and insecticides. A 3D-fingerprint descriptor encoding protein-ligand interactions was developed using molecular docking and structure-based pharmacophore to rationalize the structural requirements responsible for the activity of these compounds. The obtained 3D-QSAR model exhibited high correlation value (R(2) = 0.93) and low mean absolute error (MAE = 0.32 log units) for the training set (n = 63). The model was predictive across a range of structures as shown by the leave-one-out cross-validated correlation coefficient (Q(2) = 0.89) and external validation results (n = 26, R(2) = 0.89, and MAE = 0.38 log units). The model revealed that the compounds with high inhibition potency had proper conformation in the active site gorge and interacted with key amino acid residues, in particular Trp84 and Phe330 at the catalytic anionic site, Trp279 at the peripheral anionic site, and Gly118, Gly119, and Ala201 at the oxyanion hole. The resulting universal 3D-QSAR model provides insight into the multiple molecular interactions determining AChEI potency that may guide future chemical design and regulation of toxic AChEIs. PMID:26202430

  6. Determining satellite close approaches

    NASA Astrophysics Data System (ADS)

    Alfano, Salvatore; Negron, David, Jr.

    1993-06-01

    This paper presents a numerical method to evaluate close approaches of two satellites. The algorithm is based on a space curve modeling technique originally developed by Overhauser, presented here as an independent derivation. The method to determine minimum spacing between two space objects is based on creating a relative distance waveform, delta(t), versus time. The waveform is produced from either uniform or arbitrarily spaced data points, from which intervals of close approach are obtained by extracting the real roots of a localized cubic polynomial. This method is free of both transcendental equations and the computation of acceleration terms of the two objects of interest. For this study, a close approach truth table is constructed using a 0.1 second sequential step along the orbits, then differencing the two position vectors. The close approach entrance and exit times for an ellipsoidal quadric surface are then located using a piecewise linear interpolator, and serve as a benchmark for comparison. The simulation results show this algorithm produces encounter times almost identical to those in the truth table, with a 99.84 percent reduction in computer runtime. The results, created from real orbital data, include solution sets for three operational uses of close-approach logic. For this study, satellite orbital motion is modeled using first-order secular perturbations caused by mass anomalies.

  7. Eponymous hip joint approaches.

    PubMed

    Somford, Matthijs P; Hoornenborg, Daniël; Wiegerinck, Johannes I; Bolder, Stefan B T; Schreurs, Berend W

    2016-07-01

    After the low friction arthroplasty by John Charnley was no longer confined to specialized hospitals but commonplace in the general orthopedic practice, the issue remained how to most optimally reach the hip. The names of the authors of these approaches remain in a lot of cases connected to the approach. By evaluating the original articles in which the approaches are described we ascertain the original description and technique. By various sources we obtained the (short) biography of the people whose name is connected to the approach. Our research covers the biographies of colleagues Smith-Petersen, Watson-Jones, Hardinge, Charnley, Moore and Ludloff. The eponymous approaches are shown and described after the short biography on each individual. This study shows that without the work of our colleagues we cannot proceed in our profession. An understanding and knowledge of the people who dedicated themselves to developing the orthopedic surgery to the high standard it has today is the least honour we should give them. PMID:27139185

  8. Personal Approaches to Career Planning.

    ERIC Educational Resources Information Center

    DeMont, Billie; DeMont, Roger

    1983-01-01

    Identifies four approaches to career planning based on situational leadership theory: the network approach, self-help approach, engineering approach, and mentor approach. Guidelines for the selection of a planning method based on the nature of the work environment and personal preference are discussed. (JAC)

  9. Comparison of a neural net-based QSAR algorithm (PCANN) with Hologram- and multiple linear regression-based QSAR approaches: application to 1,4-dihydropyridine-based calcium channel antagonists.

    PubMed

    Viswanadhan, V N; Mueller, G A; Basak, S C; Weinstein, J N

    2001-01-01

    A QSAR algorithm (PCANN) has been developed and applied to a set of calcium channel blockers which are of special interest because of their role in cardiac disease and also because many of them interact with P-glycoprotein, a membrane protein associated with multidrug resistance to anticancer agents. A database of 46 1,4-dihydropyridines with known Ca2+ channel binding affinities was employed for the present analysis. The QSAR algorithm can be summarized as follows: (1) a set of 90 graph theoretic and information theoretic descriptors representing various structural and topological characteristics was calculated for each of the 1,4-dihydropyridines and (2) principal component analysis (PCA) was used to compress these 90 into the eight best orthogonal composite descriptors for the database. These eight sufficed to explain 96% of the variance in the original descriptor set. (3) Two important empirical descriptors, the Leo-Hansch lipophilic constant and the Hammet electronic parameter, were added to the list of eight. (4) The 10 resulting descriptors were used as inputs to a back-propagation neural network whose output was the predicted binding affinity. (5) The predictive ability of the network was assessed by cross-validation. A comparison of the present approach with two other QSAR approaches (multiple linear regression using the same variables and a Hologram QSAR model) is made and shows that the PCANN approach can yield better predictions, once the right network configuration is identified. The present approach (PCANN) may prove useful for rapid assessment of the potential for biological activity when dealing with large chemical libraries. PMID:11410024

  10. Technical approach document

    SciTech Connect

    Not Available

    1989-12-01

    The Uranium Mill Tailings Radiation Control Act (UMTRCA) of 1978, Public Law 95-604 (PL95-604), grants the Secretary of Energy the authority and responsibility to perform such actions as are necessary to minimize radiation health hazards and other environmental hazards caused by inactive uranium mill sites. This Technical Approach Document (TAD) describes the general technical approaches and design criteria adopted by the US Department of Energy (DOE) in order to implement remedial action plans (RAPS) and final designs that comply with EPA standards. It does not address the technical approaches necessary for aquifer restoration at processing sites; a guidance document, currently in preparation, will describe aquifer restoration concerns and technical protocols. This document is a second revision to the original document issued in May 1986; the revision has been made in response to changes to the groundwater standards of 40 CFR 192, Subparts A--C, proposed by EPA as draft standards. New sections were added to define the design approaches and designs necessary to comply with the groundwater standards. These new sections are in addition to changes made throughout the document to reflect current procedures, especially in cover design, water resources protection, and alternate site selection; only minor revisions were made to some of the sections. Sections 3.0 is a new section defining the approach taken in the design of disposal cells; Section 4.0 has been revised to include design of vegetated covers; Section 8.0 discusses design approaches necessary for compliance with the groundwater standards; and Section 9.0 is a new section dealing with nonradiological hazardous constituents. 203 refs., 18 figs., 26 tabs.

  11. Structural Margins Assessment Approach

    NASA Technical Reports Server (NTRS)

    Ryan, Robert S.

    1988-01-01

    A general approach to the structural design and verification used to determine the structural margins of the space vehicle elements under Marshall Space Flight Center (MSFC) management is described. The Space Shuttle results and organization will be used as illustrations for techniques discussed. Given also are: (1) the system analyses performed or to be performed by, and (2) element analyses performed by MSFC and its contractors. Analysis approaches and their verification will be addressed. The Shuttle procedures are general in nature and apply to other than Shuttle space vehicles.

  12. Financial Management: An Organic Approach

    ERIC Educational Resources Information Center

    Laux, Judy

    2013-01-01

    Although textbooks present corporate finance using a topical approach, good financial management requires an organic approach that integrates the various assignments financial managers confront every day. Breaking the tasks into meaningful subcategories, the current article offers one approach.

  13. New Ideas and Approaches

    ERIC Educational Resources Information Center

    Lukov, V. A.

    2014-01-01

    The article examines theories of youth that have been proposed in the past few years by Russian scientists, and presents the author's original version of a theory of youth that is based on the thesaurus methodological approach. It addresses the ways in which biosocial characteristics may be reflected in new theories of youth.

  14. Adopting a Pluricentric Approach

    ERIC Educational Resources Information Center

    van Kerckvoorde, Colette

    2012-01-01

    This article argues for a "D-A-CH" approach, which stands for Germany (D), Austria (A), and Switzerland (CH), in language classes from the introductory level on. I begin by tracing the emergence and development of distinct Standard Swiss and Austrian German varieties. I then discuss marketing efforts for Swiss and Austrian German, and…

  15. Nutrition: An Interdisciplinary Approach.

    ERIC Educational Resources Information Center

    Graef, Judy; Pettingell, Margaret S.

    1981-01-01

    Describes a pilot program in which the Dairy, Food and Nutrition Council of East Orange, New Jersey, introduced a new education series entitled "Food in Today's World." This approach outlined the role of the home economist as coordinator of a nutrition program in which educators from various disciplines participate. (CT)

  16. Marxian Approaches to Education.

    ERIC Educational Resources Information Center

    Carnoy, Martin

    Traditional Marxist approaches to the state relegate superstructural institutions like the school to a minor role in the process of social change. More recent theories like those of Gramsci, Althusser, and Poulantzas raise the state and the class struggle in the state apparatuses to a much more prominent position: superstructure, including the…

  17. Systems Approach to Training.

    ERIC Educational Resources Information Center

    British Gas, London (England). Training and Development Dept.

    This pamphlet is intended to assist managers and professional trainers alike in using a systems approach to training. Addressed in the individual sections of the guide are the following topics: identifying the training need (the main job objectives, the conditions under which the job is performed, and the responsibilities it involves); analyzing…

  18. Approaches to acceptable risk

    SciTech Connect

    Whipple, C.

    1997-04-30

    Several alternative approaches to address the question {open_quotes}How safe is safe enough?{close_quotes} are reviewed and an attempt is made to apply the reasoning behind these approaches to the issue of acceptability of radiation exposures received in space. The approaches to the issue of the acceptability of technological risk described here are primarily analytical, and are drawn from examples in the management of environmental health risks. These include risk-based approaches, in which specific quantitative risk targets determine the acceptability of an activity, and cost-benefit and decision analysis, which generally focus on the estimation and evaluation of risks, benefits and costs, in a framework that balances these factors against each other. These analytical methods tend by their quantitative nature to emphasize the magnitude of risks, costs and alternatives, and to downplay other factors, especially those that are not easily expressed in quantitative terms, that affect acceptance or rejection of risk. Such other factors include the issues of risk perceptions and how and by whom risk decisions are made.

  19. Orion Emergency Mask Approach

    NASA Technical Reports Server (NTRS)

    Tuan, George C.; Graf, John C.

    2008-01-01

    Emergency mask approach on Orion poses a challenge to the traditional Shuttle or Station approaches. Currently, in the case of a fire or toxic spill event, the crew utilizes open loop oxygen masks that provide the crew with oxygen to breath, but also dumps the exhaled oxygen into the cabin. For Orion, with a small cabin volume, the extra oxygen will exceed the flammability limit within a short period of time, unless a nitrogen purge is also provided. Another approach to a fire or toxic spill event is the use of a filtering emergency masks. These masks utilize some form of chemical beds to scrub the air clean of toxic providing the crew safe breathing air for a period without elevating the oxygen level in the cabin. Using the masks and a form of smoke-eater filter, it may be possible to clean the cabin completely or to a level for safe transition to a space suit to perform a cabin purge. Issues with filters in the past have been the reaction temperature and high breathing resistance. Development in a new form of chemical filters has shown promise to make the filtering approach feasible.

  20. Orion Emergency Mask Approach

    NASA Technical Reports Server (NTRS)

    Tuan, George C.; Graf, John C.

    2009-01-01

    Emergency mask approach on Orion poses a challenge to the traditional Shuttle or Station approaches. Currently, in the case of a fire or toxic spill event, the crew utilizes open loop oxygen masks that provide the crew with oxygen to breath, but also dumps the exhaled oxygen into the cabin. For Orion, with a small cabin volume, the extra oxygen will exceed the flammability limit within a short period of time, unless a nitrogen purge is also provided. Another approach to a fire or toxic spill event is the use of a filtering emergency masks. These masks utilize some form of chemical beds to scrub the air clean of toxic providing the crew safe breathing air for a period without elevating the oxygen level in the cabin. Using the masks and a form of smoke-eater filter, it may be possible to clean the cabin completely or to a level for safe transition to a space suit to perform a cabin purge. Issues with filters in the past have been the reaction time, breakthroughs, and high breathing resistance. Development in a new form of chemical filters has shown promise to make the filtering approach feasible.

  1. A Fresh Approach

    ERIC Educational Resources Information Center

    Violino, Bob

    2011-01-01

    Facilities and services are a huge drain on community college budgets. They are also vital to the student experience. As funding dries up across the country, many institutions are taking a team approach, working with partner colleges and private service providers to offset costs and generate revenue without sacrificing the services and amenities…

  2. Overview of Curricular Approaches

    ERIC Educational Resources Information Center

    Hartz, Cameo V.; Parker, Jill

    2012-01-01

    Institutions of higher education address the transition from after-college life in a variety of curricular approaches. Articulation agreements provide greater transferability of courses from one college to another, thereby easing the transition for students. Career courses, which are typically taught by career center staff, are a common offering…

  3. Salt repository design approach

    SciTech Connect

    Matthews, S.C.

    1983-01-01

    This paper presents a summary discussion of the approaches that have been and will be taken in design of repository facilities for use with disposal of radioactive wastes in salt formations. Since specific sites have yet to be identified, the discussion is at a general level, supplemented with illustrative examples where appropriate. 5 references, 1 figure.

  4. The Resettlement Approach.

    ERIC Educational Resources Information Center

    McInnis, Kathleen M.

    1983-01-01

    Reports on a follow-up study of secondary migration among Indochinese refugees resettled by Lutheran Social Services of Wisconsin and Upper Michigan. Suggests that cultural misunderstanding, rigid sponsorship approaches, and an insensitivity to the special mental risks of refugee populations have contributed to the incidence of secondary…

  5. Implementation of Communicative Approach

    ERIC Educational Resources Information Center

    Jabeen, Shazi Shah

    2014-01-01

    In the contemporary age of high professional requirements such as excellent communicative skills, the need for successful learning of communicative skills of English language suggests communicative ability to be the goal of language teaching. In other words, to teach English language using communicative approach becomes essential. Studies to…

  6. Predicting the efficacy of radiotherapy in individual glioblastoma patients in vivo: a mathematical modeling approach

    NASA Astrophysics Data System (ADS)

    Rockne, R.; Rockhill, J. K.; Mrugala, M.; Spence, A. M.; Kalet, I.; Hendrickson, K.; Lai, A.; Cloughesy, T.; Alvord, E. C., Jr.; Swanson, K. R.

    2010-06-01

    Glioblastoma multiforme (GBM) is the most malignant form of primary brain tumors known as gliomas. They proliferate and invade extensively and yield short life expectancies despite aggressive treatment. Response to treatment is usually measured in terms of the survival of groups of patients treated similarly, but this statistical approach misses the subgroups that may have responded to or may have been injured by treatment. Such statistics offer scant reassurance to individual patients who have suffered through these treatments. Furthermore, current imaging-based treatment response metrics in individual patients ignore patient-specific differences in tumor growth kinetics, which have been shown to vary widely across patients even within the same histological diagnosis and, unfortunately, these metrics have shown only minimal success in predicting patient outcome. We consider nine newly diagnosed GBM patients receiving diagnostic biopsy followed by standard-of-care external beam radiation therapy (XRT). We present and apply a patient-specific, biologically based mathematical model for glioma growth that quantifies response to XRT in individual patients in vivo. The mathematical model uses net rates of proliferation and migration of malignant tumor cells to characterize the tumor's growth and invasion along with the linear-quadratic model for the response to radiation therapy. Using only routinely available pre-treatment MRIs to inform the patient-specific bio-mathematical model simulations, we find that radiation response in these patients, quantified by both clinical and model-generated measures, could have been predicted prior to treatment with high accuracy. Specifically, we find that the net proliferation rate is correlated with the radiation response parameter (r = 0.89, p = 0.0007), resulting in a predictive relationship that is tested with a leave-one-out cross-validation technique. This relationship predicts the tumor size post-therapy to within inter

  7. Dual system approach to computer-aided detection of breast masses on mammograms

    SciTech Connect

    Wei Jun; Chan, H.-P.; Sahiner, Berkman; Hadjiiski, Lubomir M.; Helvie, Mark A.; Roubidoux, Marilyn A.; Zhou Chuan; Ge Jun

    2006-11-15

    In this study, our purpose was to improve the performance of our mass detection system by using a new dual system approach which combines a computer-added detection (CAD) system optimized with ''average'' masses with another CAD system optimized with ''subtle'' masses. The two single CAD systems have similar image processing steps, which include prescreening, object segmentation, morphological and texture feature extraction, and false positive (FP) reduction by rule-based and linear discriminant analysis (LDA) classifiers. A feed-forward backpropagation artificial neural network was trained to merge the scores from the LDA classifiers in the two single CAD systems and differentiate true masses from normal tissue. For an unknown test mammogram, the two single CAD systems are applied to the image in parallel to detect suspicious objects. A total of three data sets were used for training and testing the systems. The first data set of 230 current mammograms, referred to as the average mass set, was collected from 115 patients. We also collected 264 mammograms, referred to as the subtle mass set, which were one to two years prior to the current exam from these patients. Both the average and the subtle mass sets were partitioned into two independent data sets in a cross validation training and testing scheme. A third data set containing 65 cases with 260 normal mammograms was used to estimate the FP marker rates during testing. When the single CAD system trained on the average mass set was applied to the test set with average masses, the FP marker rates were 2.2, 1.8, and 1.5 per image at the case-based sensitivities of 90%, 85%, and 80%, respectively. With the dual CAD system, the FP marker rates were reduced to 1.2, 0.9, and 0.7 per image, respectively, at the same case-based sensitivities. Statistically significant (p<0.05) improvements on the free response receiver operating characteristic curves were observed when the dual system and the single system were compared

  8. Genotoxic mode of action predictions from a multiplexed flow cytometric assay and a machine learning approach.

    PubMed

    Bryce, Steven M; Bernacki, Derek T; Bemis, Jeffrey C; Dertinger, Stephen D

    2016-04-01

    Several endpoints associated with cellular responses to DNA damage as well as overt cytotoxicity were multiplexed into a miniaturized, "add and read" type flow cytometric assay. Reagents included a detergent to liberate nuclei, RNase and propidium iodide to serve as a pan-DNA dye, fluorescent antibodies against γH2AX, phospho-histone H3, and p53, and fluorescent microspheres for absolute nuclei counts. The assay was applied to TK6 cells and 67 diverse reference chemicals that served as a training set. Exposure was for 24 hrs in 96-well plates, and unless precipitation or foreknowledge about cytotoxicity suggested otherwise, the highest concentration was 1 mM. At 4- and 24-hrs aliquots were removed and added to microtiter plates containing the reagent mix. Following a brief incubation period robotic sampling facilitated walk-away data acquisition. Univariate analyses identified biomarkers and time points that were valuable for classifying agents into one of three groups: clastogenic, aneugenic, or non-genotoxic. These mode of action predictions were optimized with a forward-stepping process that considered Wald test p-values, receiver operator characteristic curves, and pseudo R(2) values, among others. A particularly high performing multinomial logistic regression model was comprised of four factors: 4 hr γH2AX and phospho-histone H3 values, and 24 hr p53 and polyploidy values. For the training set chemicals, the four-factor model resulted in 94% concordance with our a priori classifications. Cross validation occurred via a leave-one-out approach, and in this case 91% concordance was observed. A test set of 17 chemicals that were not used to construct the model were evaluated, some of which utilized a short-term treatment in the presence of a metabolic activation system, and in 16 cases mode of action was correctly predicted. These initial results are encouraging as they suggest a machine learning strategy can be used to rapidly and reliably predict new chemicals

  9. On merging rainfall data from diverse sources using a Bayesian approach

    NASA Astrophysics Data System (ADS)

    Bhattacharya, Biswa; Tarekegn, Tegegne

    2014-05-01

    Numerous studies have presented comparison of satellite rainfall products, such as from Tropical Rainfall Measuring Mission (TRMM), with rain gauge data and have concluded, in general, that the two sources of data are comparable at suitable space and time scales. The comparison is not a straightforward one as they employ different measurement techniques and are dependent on very different space-time scales of measurements. The number of available gauges in a catchment also influences the comparability and thus adds to the complexity. The TRMM rainfall data also has been directly used in hydrological modelling. As the space-time scale reduces so does the accuracy of these models. It seems that combining the two sources of rainfall data, or more sources of rainfall data, can enormously benefit hydrological studies. Various rainfall data, due to the differences in their space-time structure, contains information about the spatio-temporal distribution of rainfall, which is not available to a single source of data. In order to harness this benefit we have developed a method of merging these two (or more) rainfall products under the framework of Bayesian Data Fusion (BDF) principle. By applying this principle the rainfall data from the various sources can be combined to a single time series of rainfall data. The usefulness of the approach has been explored in a case study on Lake Tana Basin of Upper Blue Nile Basin in Ethiopia. A 'leave one rain gauge out' cross validation technique was employed for evaluating the accuracy of the rainfall time series with rainfall interpolated from rain gauge data using Inverse Distance Weighting (referred to as IDW), TRMM and the fused data (BDF). The result showed that BDF prediction was better compared to the TRMM and IDW. Further evaluation of the three rainfall estimates was done by evaluating the capability in predicting observed stream flow using a lumped conceptual rainfall-runoff model using NAM. Visual inspection of the

  10. Mapping Natural Terroir Units using a multivariate approach and legacy data

    NASA Astrophysics Data System (ADS)

    Priori, Simone; Barbetti, Roberto; L'Abate, Giovanni; Bucelli, Piero; Storchi, Paolo; Costantini, Edoardo A. C.

    2014-05-01

    Natural Terroir Unit (NTU) is a volume of earth's biosphere that is characterized by a stable set of variables related to the topography, climate, geology and soil. Methods to study the association soil-climate-vines are numerous, but the main question is always: which variables are actually important for the quality and the typicality of grapevines, and then wine, for a particular scale? This work aimed to setting up a multivariate methodology to define viticultural terroirs at the province scale (1:125,000), using viticultural and oenological legacy data. The study area was the Siena province in the Tuscany region (Central Italy). The reference grapevine cultivar was "Sangiovese", which is the most important cultivar of the region. The methodology was based upon the creation of a GIS storing several viticultural and oenological legacy data of 55 experimental vineyards (vintages between 1989-2009), the long term climate data, the digital elevation model, the soil-landscapes (land systems) and the soil profiles with the soil analysis. The selected viticultural and oenological parameters were: must sugar content, sugar accumulation rate from veraison to harvest, must titratable acidity, grape yield per vine, number of bunches for vine, mean bunch weight, and mean weight of berries. The environmental parameters related to viticulture, selected by an explorative PCA, were: elevation, mean annual temperature, mean soil temperature, annual precipitation, clay, sand and gravel content of soils, soil water availability, redoximorphic features and rooting depth. The geostatistical models of the variables interpolation were chosen on the best of mean standardize error, obtained by the cross-validation, between "Simple cokriging with varying local mean", "Multicollocated simple cokriging with varying local mean" and "Regression kriging". These variables were used for a k-means clustering aimed to map the Natural Terroirs Units (NTUs). The viticultural areas of Siena province

  11. Controlled Incremental Filtration: A simplified approach to design and fabrication of high-throughput microfluidic devices for selective enrichment of particles†

    PubMed Central

    Gifford, Sean C.; Spillane, Angela M.; Vignes, Seth M.; Shevkoplyas, Sergey S.

    2014-01-01

    The number of microfluidic strategies aimed at separating particles or cells of a specific size within a continuous flow system continues to grow. The wide array of biomedical and other applications that would benefit from successful development of such technology has motivated the extensive research in this area over the past 15 years. However, despite promising advancements in microfabrication capabilities, a versatile approach that is suitable for a large range of particle sizes and high levels of enrichment, with a volumetric throughput sufficient for large-scale applications, has yet to emerge. Here we describe a straightforward method that enables the rapid design of microfluidic devices that are capable of enriching/removing particles within a complex aqueous mixture, with an unprecedented range of potential cutoff diameter (below 1µm to above 100µm) and an easily scalable degree of enrichment/filtration (up to 10-fold and well beyond). A simplified model of a new approach to crossflow filtration – controlled incremental filtration – was developed and validated for its ability to generate microfluidic devices that efficiently separate particles on the order of 1–10µm, with throughputs of tens of µL/min, without the use of a pump. Precise control of the amount of fluid incrementally diverted at each filtration “gap” of the device allows for the gap size (~20µm) to be much larger than the particles of interest, while the simplicity of the model allows for many thousands of these filtration points to be readily incorporated into a desired device design. This new approach should enable truly high-throughput microfluidic particle-separation devices to be generated, even by users only minimally experienced in fluid mechanics and microfabrication techniques. PMID:25254358

  12. Predicting Optimal Outcomes in Cognitive Therapy or Interpersonal Psychotherapy for Depressed Individuals Using the Personalized Advantage Index Approach

    PubMed Central

    Huibers, Marcus J. H.; Cohen, Zachary D.; Lemmens, Lotte H. J. M.; Arntz, Arnoud; Peeters, Frenk P. M. L.; Cuijpers, Pim; DeRubeis, Robert J.

    2015-01-01

    Introduction Although psychotherapies for depression produce equivalent outcomes, individual patients respond differently to different therapies. Predictors of outcome have been identified in the context of randomized trials, but this information has not been used to predict which treatment works best for the depressed individual. In this paper, we aim to replicate a recently developed treatment selection method, using data from an RCT comparing the effects of cognitive therapy (CT) and interpersonal psychotherapy (IPT). Methods 134 depressed patients completed the pre- and post-treatment BDI-II assessment. First, we identified baseline predictors and moderators. Second, individual treatment recommendations were generated by combining the identified predictors and moderators in an algorithm that produces the Personalized Advantage Index (PAI), a measure of the predicted advantage in one therapy compared to the other, using standard regression analyses and the leave-one-out cross-validation approach. Results We found five predictors (gender, employment status, anxiety, personality disorder and quality of life) and six moderators (somatic complaints, cognitive problems, paranoid symptoms, interpersonal self-sacrificing, attributional style and number of life events) of treatment outcome. The mean average PAI value was 8.9 BDI points, and 63% of the sample was predicted to have a clinically meaningful advantage in one of the therapies. Those who were randomized to their predicted optimal treatment (either CT or IPT) had an observed mean end-BDI of 11.8, while those who received their predicted non-optimal treatment had an end-BDI of 17.8 (effect size for the difference = 0.51). Discussion Depressed patients who were randomized to their predicted optimal treatment fared much better than those randomized to their predicted non-optimal treatment. The PAI provides a great opportunity for formal decision-making to improve individual patient outcomes in depression. Although

  13. Seasonal precipitation forecasts for selected regions in West Africa using circulation type classifications in combination with further statistical approaches - Conceptual framework and first results

    NASA Astrophysics Data System (ADS)

    Bliefernicht, Jan; Laux, Patrik; Waongo, Moussa; Kunstmann, Harald

    2015-04-01

    Providing valuable forecasts of the seasonal precipitation amount for the upcoming rainy season is one of the big challenges for the national weather services in West Africa. Every year a harmonized forecast of the seasonal precipitation amount for the West African region is issued by the national weather services within the PRESAO framework. The PREASO forecast is based on various statistical approaches ranging from a simple subjective analog method based on the experiences of a meteorological expert to objective regression-based approaches by using various sources of input information such as predicted monsoon winds or observed sea surface temperature anomalies close to the West African coastline. The objective of this study is to perform an evaluation of these techniques for selected West African regions and to introduce classification techniques in the current operational practices and to combine these approaches with further techniques for an additional refinement of the forecasting procedure. We use a fuzzy-rule based technique for a classification of (sub-) monthly large-scale atmospheric and oceanic patterns which are combined to further statistical approaches such as an analog method and a data depth approach for the prediction of the (sub-) seasonal precipitation amounts and additional precipitation indices. The study regions are located from the Edges of the Sahel region in the North of Burkina Faso to the coastline of Ghana. A novel precipitation archive based on daily observations provided by the meteorological services of Burkina Faso and Ghana is the basis for the predictands and is used as reference for model evaluation. The performance of the approach is evaluated over a long period (e.g. 50 years) using cross-validation techniques and sophisticated verification measures for an evaluation of a probability forecast. The precipitation forecast of the classification techniques are also compared to the techniques of the PREASAO community, the

  14. Domain Approach: An Alternative Approach in Moral Education

    ERIC Educational Resources Information Center

    Vengadasalam, Chander; Mamat, Wan Hasmah Wan; Mail, Fauziah; Sudramanian, Munimah

    2014-01-01

    This paper discusses the use of the domain approach in moral education in an upper secondary school in Malaysia. Moral Education needs a creative and an innovative approach. Therefore, a few forms of approaches are used in the teaching-learning of Moral Education. This research describes the use of domain approach which comprises the moral domain…

  15. A comparative approach to 7, 12-dimethylbenz[a]anthracene effects: Metabolism and mutagenesis in mice and fish

    SciTech Connect

    Gallagher, K.; Cline, J.; Burkhart, J.G.; Gundersen, J.L.

    1997-10-01

    A comparative approach was used to examine the effects of exposure to the potent carcinogen 7,12-dimethylbenz[a]anthracene (DMBA) in two divergent sentinel species, mouse and fish, containing a common transgenic reporter, the bacteriophage {O}X174am3. Effects of DMBA were examined using both in vitro and in vivo studies through the analysis of metabolites, cytochrome P450 was examined 72 hours after DMBA dosing using an assay for 7-ethoxyresorufin-o-deethylase (EROD) activity. Fish showed an increasing trend of EROD induction with increasing dose, with the EROD level at the highest dose being significantly greater than corn oil controls and the lowest DMBA dose. DMBA had less of an effect on mouse P450 levels. Metabolites of DMBA in the bile at 12 hours were quantified in both species using HPLC/PDA detection. Bile extracts were enzyme digested to differentiate glucuronide, sulfate and glutathione conjugates. Primary metabolites in mice were 2-hydroxy-7,12-dimethylbenz[a]anthracene, 7-hydroxymethyl-12-methylbenz[a]anthracene. The same metabolites were detected in the fish with the addition of 7,12-bis-hydrodxymethylbenz[a]anthracene. In vitro assays using uninduced and 3-methylcholanthrene-induced mouse microsomes showed no increase over background mutant frequencies of 1-3x10{sup -6} when 0X DNA was incubated with DMBA. In vivo induced mutation was also examined in mice and fish liver. The 1.9 and 19 mg/kg doses of DMBA resulted in a 10-fold increase in mutation frequency over controls in fish. There was a similar increase in mutation frequency at the 19 mg/kg dose in mice. Analysis of the 1.9 mb/kg dosed mice and the replicate variance among treated and control animals is underway.

  16. The imaging spectrometer approach

    NASA Technical Reports Server (NTRS)

    Wellman, J. B.

    1982-01-01

    Two important sensor design drivers are the requirement for spatial registration of the spectral components and the implementation of the advanced multispectral capability, including spectral band width, number of bands and programmability. The dispersive approach, fundamental to the imaging spectrometer concept, achieves these capabilities by utilizing a spectrometer to disperse the spectral content while preserving the spatial identity of the information in the cross-track direction. Area array detectors in the spectrometer focal plane detect and store the spatial and multispectral content for each line of the image. The choice of spectral bands, image IFOV and swath width is implemented by programmed readout of the focal plane. These choices in conjunction with data compression are used to match the output data rate with the telemetry link capability. Progress in the key technologies of optics, focal plane detector arrays, onboard processing, and focal plane cooling supports the viability of the imaging spectrometer approach.

  17. Automated identification of protein-ligand interaction features using Inductive Logic Programming: a hexose binding case study

    PubMed Central

    2012-01-01

    Background There is a need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP), which automatically generates comprehensible rules in addition to prediction. The development of ILP systems which can learn rules of the complexity required for studies on protein structure remains a challenge. In this work we use a new ILP system, ProGolem, and demonstrate its performance on learning features of hexose-protein interactions. Results The rules induced by ProGolem detect interactions mediated by aromatics and by planar-polar residues, in addition to less common features such as the aromatic sandwich. The rules also reveal a previously unreported dependency for residues cys and leu. They also specify interactions involving aromatic and hydrogen bonding residues. This paper shows that Inductive Logic Programming implemented in ProGolem can derive rules giving structural features of protein/ligand interactions. Several of these rules are consistent with descriptions in the literature. Conclusions In addition to confirming literature results, ProGolem’s model has a 10-fold cross-validated predictive accuracy that is superior, at the 95% confidence level, to another ILP system previously used to study protein/hexose interactions and is comparable with state-of-the-art statistical learners. PMID:22783946

  18. Uniting Cheminformatics and Chemical Theory To Predict the Intrinsic Aqueous Solubility of Crystalline Druglike Molecules

    PubMed Central

    2014-01-01

    We present four models of solution free-energy prediction for druglike molecules utilizing cheminformatics descriptors and theoretically calculated thermodynamic values. We make predictions of solution free energy using physics-based theory alone and using machine learning/quantitative structure–property relationship (QSPR) models. We also develop machine learning models where the theoretical energies and cheminformatics descriptors are used as combined input. These models are used to predict solvation free energy. While direct theoretical calculation does not give accurate results in this approach, machine learning is able to give predictions with a root mean squared error (RMSE) of ∼1.1 log S units in a 10-fold cross-validation for our Drug-Like-Solubility-100 (DLS-100) dataset of 100 druglike molecules. We find that a model built using energy terms from our theoretical methodology as descriptors is marginally less predictive than one built on Chemistry Development Kit (CDK) descriptors. Combining both sets of descriptors allows a further but very modest improvement in the predictions. However, in some cases, this is a statistically significant enhancement. These results suggest that there is little complementarity between the chemical information provided by these two sets of descriptors, despite their different sources and methods of calculation. Our machine learning models are also able to predict the well-known Solubility Challenge dataset with an RMSE value of 0.9–1.0 log S units. PMID:24564264

  19. A novel algorithm for detecting multiple covariance and clustering of biological sequences.

    PubMed

    Shen, Wei; Li, Yan

    2016-01-01

    Single genetic mutations are always followed by a set of compensatory mutations. Thus, multiple changes commonly occur in biological sequences and play crucial roles in maintaining conformational and functional stability. Although many methods are available to detect single mutations or covariant pairs, detecting non-synchronous multiple changes at different sites in sequences remains challenging. Here, we develop a novel algorithm, named Fastcov, to identify multiple correlated changes in biological sequences using an independent pair model followed by a tandem model of site-residue elements based on inter-restriction thinking. Fastcov performed exceptionally well at harvesting co-pairs and detecting multiple covariant patterns. By 10-fold cross-validation using datasets of different scales, the characteristic patterns successfully classified the sequences into target groups with an accuracy of greater than 98%. Moreover, we demonstrated that the multiple covariant patterns represent co-evolutionary modes corresponding to the phylogenetic tree, and provide a new understanding of protein structural stability. In contrast to other methods, Fastcov provides not only a reliable and effective approach to identify covariant pairs but also more powerful functions, including multiple covariance detection and sequence classification, that are most useful for studying the point and compensatory mutations caused by natural selection, drug induction, environmental pressure, etc. PMID:27451921

  20. Generating One Biometric Feature from Another: Faces from Fingerprints

    PubMed Central

    Ozkaya, Necla; Sagiroglu, Seref

    2010-01-01

    This study presents a new approach based on artificial neural networks for generating one biometric feature (faces) from another (only fingerprints). An automatic and intelligent system was designed and developed to analyze the relationships among fingerprints and faces and also to model and to improve the existence of the relationships. The new proposed system is the first study that generates all parts of the face including eyebrows, eyes, nose, mouth, ears and face border from only fingerprints. It is also unique and different from similar studies recently presented in the literature with some superior features. The parameter settings of the system were achieved with the help of Taguchi experimental design technique. The performance and accuracy of the system have been evaluated with 10-fold cross validation technique using qualitative evaluation metrics in addition to the expanded quantitative evaluation metrics. Consequently, the results were presented on the basis of the combination of these objective and subjective metrics for illustrating the qualitative properties of the proposed methods as well as a quantitative evaluation of their performances. Experimental results have shown that one biometric feature can be determined from another. These results have once more indicated that there is a strong relationship between fingerprints and faces. PMID:22399877

  1. A novel algorithm for detecting multiple covariance and clustering of biological sequences

    PubMed Central

    Shen, Wei; Li, Yan

    2016-01-01

    Single genetic mutations are always followed by a set of compensatory mutations. Thus, multiple changes commonly occur in biological sequences and play crucial roles in maintaining conformational and functional stability. Although many methods are available to detect single mutations or covariant pairs, detecting non-synchronous multiple changes at different sites in sequences remains challenging. Here, we develop a novel algorithm, named Fastcov, to identify multiple correlated changes in biological sequences using an independent pair model followed by a tandem model of site-residue elements based on inter-restriction thinking. Fastcov performed exceptionally well at harvesting co-pairs and detecting multiple covariant patterns. By 10-fold cross-validation using datasets of different scales, the characteristic patterns successfully classified the sequences into target groups with an accuracy of greater than 98%. Moreover, we demonstrated that the multiple covariant patterns represent co-evolutionary modes corresponding to the phylogenetic tree, and provide a new understanding of protein structural stability. In contrast to other methods, Fastcov provides not only a reliable and effective approach to identify covariant pairs but also more powerful functions, including multiple covariance detection and sequence classification, that are most useful for studying the point and compensatory mutations caused by natural selection, drug induction, environmental pressure, etc. PMID:27451921

  2. Prediction of fat-free body mass from bioelectrical impedance and anthropometry among 3-year-old children using DXA

    PubMed Central

    Ejlerskov, Katrine T.; Jensen, Signe M.; Christensen, Line B.; Ritz, Christian; Michaelsen, Kim F.; Mølgaard, Christian

    2014-01-01

    For 3-year-old children suitable methods to estimate body composition are sparse. We aimed to develop predictive equations for estimating fat-free mass (FFM) from bioelectrical impedance (BIA) and anthropometry using dual-energy X-ray absorptiometry (DXA) as reference method using data from 99 healthy 3-year-old Danish children. Predictive equations were derived from two multiple linear regression models, a comprehensive model (height2/resistance (RI), six anthropometric measurements) and a simple model (RI, height, weight). Their uncertainty was quantified by means of 10-fold cross-validation approach. Prediction error of FFM was 3.0% for both equations (root mean square error: 360 and 356 g, respectively). The derived equations produced BIA-based prediction of FFM and FM near DXA scan results. We suggest that the predictive equations can be applied in similar population samples aged 2–4 years. The derived equations may prove useful for studies linking body composition to early risk factors and early onset of obesity. PMID:24463487

  3. Will my protein crystallize? A sequence-based predictor.

    PubMed

    Smialowski, Pawel; Schmidt, Thorsten; Cox, Jürgen; Kirschner, Andreas; Frishman, Dmitrij

    2006-02-01

    We propose a machine-learning approach to sequence-based prediction of protein crystallizability in which we exploit subtle differences between proteins whose structures were solved by X-ray analysis [or by both X-ray and nuclear magnetic resonance (NMR) spectroscopy] and those proteins whose structures were solved by NMR spectroscopy alone. Because the NMR technique is usually applied on relatively small proteins, sequence length distributions of the X-ray and NMR datasets were adjusted to avoid predictions biased by protein size. As feature space for classification, we used frequencies of mono-, di-, and tripeptides represented by the original 20-letter amino acid alphabet as well as by several reduced alphabets in which amino acids were grouped by their physicochemical and structural properties. The classification algorithm was constructed as a two-layered structure in which the output of primary support vector machine classifiers operating on peptide frequencies was combined by a second-level Naive Bayes classifier. Due to the application of metamethods for cost sensitivity, our method is able to handle real datasets with unbalanced class representation. An overall prediction accuracy of 67% [65% on the positive (crystallizable) and 69% on the negative (noncrystallizable) class] was achieved in a 10-fold cross-validation experiment, indicating that the proposed algorithm may be a valuable tool for more efficient target selection in structural genomics. A Web server for protein crystallizability prediction called SECRET is available at http://webclu.bio.wzw.tum.de:8080/secret. PMID:16315316

  4. Systematic Characterization and Prediction of Post-Translational Modification Cross-Talk*

    PubMed Central

    Huang, Yuanhua; Xu, Bosen; Zhou, Xueya; Li, Ying; Lu, Ming; Jiang, Rui; Li, Tingting

    2015-01-01

    Post-translational modification (PTM)1 plays an important role in regulating the functions of proteins. PTMs of multiple residues on one protein may work together to determine a functional outcome, which is known as PTM cross-talk. Identification of PTM cross-talks is an emerging theme in proteomics and has elicited great interest, but their properties remain to be systematically characterized. To this end, we collected 193 PTM cross-talk pairs in 77 human proteins from the literature and then tested location preference and co-evolution at the residue and modification levels. We found that cross-talk events preferentially occurred among nearby PTM sites, especially in disordered protein regions, and cross-talk pairs tended to co-evolve. Given the properties of PTM cross-talk pairs, a naïve Bayes classifier integrating different features was built to predict cross-talks for pairwise combination of PTM sites. By using a 10-fold cross-validation, the integrated prediction model showed an area under the receiver operating characteristic (ROC) curve of 0.833, superior to using any individual feature alone. The prediction performance was also demonstrated to be robust to the biases in the collected PTM cross-talk pairs. The integrated approach has the potential for large-scale prioritization of PTM cross-talk candidates for functional validation and was implemented as a web server available at http://bioinfo.bjmu.edu.cn/ptm-x/. PMID:25605461

  5. Neurocognitive disorder detection based on feature vectors extracted from VBM analysis of structural MRI.

    PubMed

    Savio, A; García-Sebastián, M T; Chyzyk, D; Hernandez, C; Graña, M; Sistiaga, A; López de Munain, A; Villanúa, J

    2011-08-01

    Dementia is a growing concern due to the aging process of the western societies. Non-invasive detection is therefore a high priority research endeavor. In this paper we report results of classification systems applied to the feature vectors obtained by a feature extraction method computed on structural magnetic resonance imaging (sMRI) volumes for the detection of two neurological disorders with cognitive impairment: myotonic dystrophy of type 1 (MD1) and Alzheimer disease (AD). The feature extraction process is based on the voxel clusters detected by voxel-based morphometry (VBM) analysis of sMRI upon a set of patient and control subjects. This feature extraction process is specific for each kind of disease and is grounded on the findings obtained by medical experts. The 10-fold cross-validation results of several statistical and neural network based classification algorithms trained and tested on these features show high specificity and moderate sensitivity of the classifiers, suggesting that the approach is better suited for rejecting than for detecting early stages of the diseases. PMID:21621760

  6. Biomarker Discovery Based on Hybrid Optimization Algorithm and Artificial Neural Networks on Microarray Data for Cancer Classification.

    PubMed

    Moteghaed, Niloofar Yousefi; Maghooli, Keivan; Pirhadi, Shiva; Garshasbi, Masoud

    2015-01-01

    The improvement of high-through-put gene profiling based microarrays technology has provided monitoring the expression value of thousands of genes simultaneously. Detailed examination of changes in expression levels of genes can help physicians to have efficient diagnosing, classification of tumors and cancer's types as well as effective treatments. Finding genes that can classify the group of cancers correctly based on hybrid optimization algorithms is the main purpose of this paper. In this paper, a hybrid particle swarm optimization and genetic algorithm method are used for gene selection and also artificial neural network (ANN) is adopted as the classifier. In this work, we have improved the ability of the algorithm for the classification problem by finding small group of biomarkers and also best parameters of the classifier. The proposed approach is tested on three benchmark gene expression data sets: Blood (acute myeloid leukemia, acute lymphoblastic leukemia), colon and breast datasets. We used 10-fold cross-validation to achieve accuracy and also decision tree algorithm to find the relation between the biomarkers for biological point of view. To test the ability of the trained ANN models to categorize the cancers, we analyzed additional blinded samples that were not previously used for the training procedure. Experimental results show that the proposed method can reduce the dimension of the data set and confirm the most informative gene subset and improve classification accuracy with best parameters based on datasets. PMID:26120567

  7. Predicting the distribution of canine leishmaniasis in western Europe based on environmental variables.

    PubMed

    Franco, Ana O; Davies, Clive R; Mylne, Adrian; Dedet, Jean-Pierre; Gállego, Montserrat; Ballart, Cristina; Gramiccia, Marina; Gradoni, Luigi; Molina, Ricardo; Gálvez, Rosa; Morillas-Márquez, Francisco; Barón-López, Sergio; Pires, Carlos Alves; Afonso, Maria Odete; Ready, Paul D; Cox, Jonathan

    2011-12-01

    The domestic dog is the reservoir host of Leishmania infantum, the causative agent of zoonotic visceral leishmaniasis endemic in Mediterranean Europe. Targeted control requires predictive risk maps of canine leishmaniasis (CanL), which are now explored. We databased 2187 published and unpublished surveys of CanL in southern Europe. A total of 947 western surveys met inclusion criteria for analysis, including serological identification of infection (504, 369 dogs tested 1971-2006). Seroprevalence was 23 2% overall (median 10%). Logistic regression models within a GIS framework identified the main environmental predictors of CanL seroprevalence in Portugal, Spain, France and Italy, or in France alone. A 10-fold cross-validation approach determined model capacity to predict point-values of seroprevalence and the correct seroprevalence class (<5%, 5-20%, >20%). Both the four-country and France-only models performed reasonably well for predicting correctly the <5% and >20% seroprevalence classes (AUC >0 70). However, the France-only model performed much better for France than the four-country model. The four-country model adequately predicted regions of CanL emergence in northern Italy (<5% seroprevalence). Both models poorly predicted intermediate point seroprevalences (5-20%) within regional foci, because surveys were biased towards known rural foci and Mediterranean bioclimates. Our recommendations for standardizing surveys would permit higher-resolution risk mapping. PMID:21914251

  8. Biomarker Discovery Based on Hybrid Optimization Algorithm and Artificial Neural Networks on Microarray Data for Cancer Classification

    PubMed Central

    Moteghaed, Niloofar Yousefi; Maghooli, Keivan; Pirhadi, Shiva; Garshasbi, Masoud

    2015-01-01

    The improvement of high-through-put gene profiling based microarrays technology has provided monitoring the expression value of thousands of genes simultaneously. Detailed examination of changes in expression levels of genes can help physicians to have efficient diagnosing, classification of tumors and cancer's types as well as effective treatments. Finding genes that can classify the group of cancers correctly based on hybrid optimization algorithms is the main purpose of this paper. In this paper, a hybrid particle swarm optimization and genetic algorithm method are used for gene selection and also artificial neural network (ANN) is adopted as the classifier. In this work, we have improved the ability of the algorithm for the classification problem by finding small group of biomarkers and also best parameters of the classifier. The proposed approach is tested on three benchmark gene expression data sets: Blood (acute myeloid leukemia, acute lymphoblastic leukemia), colon and breast datasets. We used 10-fold cross-validation to achieve accuracy and also decision tree algorithm to find the relation between the biomarkers for biological point of view. To test the ability of the trained ANN models to categorize the cancers, we analyzed additional blinded samples that were not previously used for the training procedure. Experimental results show that the proposed method can reduce the dimension of the data set and confirm the most informative gene subset and improve classification accuracy with best parameters based on datasets. PMID:26120567

  9. Rapid Diagnostic Algorithms as a Screening Tool for Tuberculosis: An Assessor Blinded Cross-Sectional Study

    PubMed Central

    Ratzinger, Franz; Bruckschwaiger, Harald; Wischenbart, Martin; Parschalk, Bernhard; Fernandez-Reyes, Delmiro; Lagler, Heimo; Indra, Alexandra; Graninger, Wolfgang; Winkler, Stefan; Krishna, Sanjeev; Ramharter, Michael

    2012-01-01

    Background A major obstacle to effectively treat and control tuberculosis is the absence of an accurate, rapid, and low-cost diagnostic tool. A new approach for the screening of patients for tuberculosis is the use of rapid diagnostic classification algorithms. Methods We tested a previously published diagnostic algorithm based on four biomarkers as a screening tool for tuberculosis in a Central European patient population using an assessor-blinded cross-sectional study design. In addition, we developed an improved diagnostic classification algorithm based on a study population at a tertiary hospital in Vienna, Austria, by supervised computational statistics. Results The diagnostic accuracy of the previously published diagnostic algorithm for our patient population consisting of 206 patients was 54% (CI: 47%–61%). An improved model was constructed using inflammation parameters and clinical information. A diagnostic accuracy of 86% (CI: 80%–90%) was demonstrated by 10-fold cross validation. An alternative model relying solely on clinical parameters exhibited a diagnostic accuracy of 85% (CI: 79%–89%). Conclusion Here we show that a rapid diagnostic algorithm based on clinical parameters is only slightly improved by inclusion of inflammation markers in our cohort. Our results also emphasize the need for validation of new diagnostic algorithms in different settings and patient populations. PMID:23185397

  10. Detecting Lung Diseases from Exhaled Aerosols: Non-Invasive Lung Diagnosis Using Fractal Analysis and SVM Classification

    PubMed Central

    Xi, Jinxiang; Zhao, Weizhong; Yuan, Jiayao Eddie; Kim, JongWon; Si, Xiuhua; Xu, Xiaowei

    2015-01-01

    Background Each lung structure exhales a unique pattern of aerosols, which can be used to detect and monitor lung diseases non-invasively. The challenges are accurately interpreting the exhaled aerosol fingerprints and quantitatively correlating them to the lung diseases. Objective and Methods In this study, we presented a paradigm of an exhaled aerosol test that addresses the above two challenges and is promising to detect the site and severity of lung diseases. This paradigm consists of two steps: image feature extraction using sub-regional fractal analysis and data classification using a support vector machine (SVM). Numerical experiments were conducted to evaluate the feasibility of the breath test in four asthmatic lung models. A high-fidelity image-CFD approach was employed to compute the exhaled aerosol patterns under different disease conditions. Findings By employing the 10-fold cross-validation method, we achieved 100% classification accuracy among four asthmatic models using an ideal 108-sample dataset and 99.1% accuracy using a more realistic 324-sample dataset. The fractal-SVM classifier has been shown to be robust, highly sensitive to structural variations, and inherently suitable for investigating aerosol-disease correlations. Conclusion For the first time, this study quantitatively linked the exhaled aerosol patterns with their underlying diseases and set the stage for the development of a computer-aided diagnostic system for non-invasive detection of obstructive respiratory diseases. PMID:26422016

  11. Sequence-based prediction of protein-peptide binding sites using support vector machine.

    PubMed

    Taherzadeh, Ghazaleh; Yang, Yuedong; Zhang, Tuo; Liew, Alan Wee-Chung; Zhou, Yaoqi

    2016-05-15

    Protein-peptide interactions are essential for all cellular processes including DNA repair, replication, gene-expression, and metabolism. As most protein-peptide interactions are uncharacterized, it is cost effective to investigate them computationally as the first step. All existing approaches for predicting protein-peptide binding sites, however, are based on protein structures despite the fact that the structures for most proteins are not yet solved. This article proposes the first machine-learning method called SPRINT to make Sequence-based prediction of Protein-peptide Residue-level Interactions. SPRINT yields a robust and consistent performance for 10-fold cross validations and independent test. The most important feature is evolution-generated sequence profiles. For the test set (1056 binding and non-binding residues), it yields a Matthews' Correlation Coefficient of 0.326 with a sensitivity of 64% and a specificity of 68%. This sequence-based technique shows comparable or more accurate than structure-based methods for peptide-binding site prediction. SPRINT is available as an online server at: http://sparks-lab.org/. © 2016 Wiley Periodicals, Inc. PMID:26833816

  12. Patient Machine Interface for the Control of Mechanical Ventilation Devices

    PubMed Central

    Grave de Peralta, Rolando; Gonzalez Andino, Sara; Perrig, Stephen

    2013-01-01

    The potential of Brain Computer Interfaces (BCIs) to translate brain activity into commands to control external devices during mechanical ventilation (MV) remains largely unexplored. This is surprising since the amount of patients that might benefit from such assistance is considerably larger than the number of patients requiring BCI for motor control. Given the transient nature of MV (i.e., used mainly over night or during acute clinical conditions), precluding the use of invasive methods, and inspired by current research on BCIs, we argue that scalp recorded EEG (electroencephalography) signals can provide a non-invasive direct communication pathway between the brain and the ventilator. In this paper we propose a Patient Ventilator Interface (PVI) to control a ventilator during variable conscious states (i.e., wake, sleep, etc.). After a brief introduction on the neural control of breathing and the clinical conditions requiring the use of MV we discuss the conventional techniques used during MV. The schema of the PVI is presented followed by a description of the neural signals that can be used for the on-line control. To illustrate the full approach, we present data from a healthy subject, where the inspiration and expiration periods during voluntary breathing were discriminated with a 92% accuracy (10-fold cross-validation) from the scalp EEG data. The paper ends with a discussion on the advantages and obstacles that can be forecasted in this novel application of the concept of BCI. PMID:24961620

  13. Computer-Aided Diagnosis for Breast Ultrasound Using Computerized BI-RADS Features and Machine Learning Methods.

    PubMed

    Shan, Juan; Alam, S Kaisar; Garra, Brian; Zhang, Yingtao; Ahmed, Tahira

    2016-04-01

    This work identifies effective computable features from the Breast Imaging Reporting and Data System (BI-RADS), to develop a computer-aided diagnosis (CAD) system for breast ultrasound. Computerized features corresponding to ultrasound BI-RADs categories were designed and tested using a database of 283 pathology-proven benign and malignant lesions. Features were selected based on classification performance using a "bottom-up" approach for different machine learning methods, including decision tree, artificial neural network, random forest and support vector machine. Using 10-fold cross-validation on the database of 283 cases, the highest area under the receiver operating characteristic (ROC) curve (AUC) was 0.84 from a support vector machine with 77.7% overall accuracy; the highest overall accuracy, 78.5%, was from a random forest with the AUC 0.83. Lesion margin and orientation were optimum features common to all of the different machine learning methods. These features can be used in CAD systems to help distinguish benign from worrisome lesions. PMID:26806441

  14. DisPredict: A Predictor of Disordered Protein Using Optimized RBF Kernel

    PubMed Central

    Iqbal, Sumaiya; Hoque, Md Tamjidul

    2015-01-01

    Intrinsically disordered proteins or, regions perform important biological functions through their dynamic conformations during binding. Thus accurate identification of these disordered regions have significant implications in proper annotation of function, induced fold prediction and drug design to combat critical diseases. We introduce DisPredict, a disorder predictor that employs a single support vector machine with RBF kernel and novel features for reliable characterization of protein structure. DisPredict yields effective performance. In addition to 10-fold cross validation, training and testing of DisPredict was conducted with independent test datasets. The results were consistent with both the training and test error minimal. The use of multiple data sources, makes the predictor generic. The datasets used in developing the model include disordered regions of various length which are categorized as short and long having different compositions, different types of disorder, ranging from fully to partially disordered regions as well as completely ordered regions. Through comparison with other state of the art approaches and case studies, DisPredict is found to be a useful tool with competitive performance. DisPredict is available at https://github.com/tamjidul/DisPredict_v1.0. PMID:26517719

  15. Developing a QSAR model for hepatotoxicity screening of the active compounds in traditional Chinese medicines.

    PubMed

    Huang, Shan-Han; Tung, Chun-Wei; Fülöp, Ferenc; Li, Jih-Heng

    2015-04-01

    The perception that natural substances are deemed safe has made traditional Chinese medicine (TCM) popular in the treatment and prevention of disease globally. However, such an assumption is often misleading owing to a lack of scientific validation. To assess the safety of TCM, in silico screening provides major advantages over the classical laboratory approaches in terms of resource- and time-saving and full reproducibility. To screen the hepatotoxicity of the active compounds of TCMs, a quantitative structure-activity relationship (QSAR) model was firstly established by utilizing drugs from the Liver Toxicity Knowledge Base. These drugs were annotated with drug-induced liver injury information obtained from clinical trials and post-marketing surveillance. The performance of the model after nested 10-fold cross-validation was 79.1%, 91.2%, 53.8% for accuracy, sensitivity, and specificity, respectively. The external validation of 91 well-known ingredients of common herbal medicines yielded a high accuracy (87%). After screening the TCM Database@Taiwan, the world's largest TCM database, a total of 6853 (74.8%) ingredients were predicted to have hepatotoxic potential. The one-hundred chemical ingredients predicted to have the highest hepatotoxic potential by our model were further verified by published literatures. Our study indicated that this model can serve as a complementary tool to evaluate the safety of TCM. PMID:25660478

  16. Identification of exercise-induced ischemia using QRS slopes.

    PubMed

    Firoozabadi, Reza; Gregg, Richard E; Babaeizadeh, Saeed

    2016-01-01

    In this work we studied a computer-aided approach using QRS slopes as unconventional ECG features to identify the exercise-induced ischemia during exercise stress testing and demonstrated that the performance is comparable to the experts' manual analysis using standard criteria involving ST-segment depression. We evaluated the performance of our algorithm using a database including 927 patients undergoing exercise stress tests and simultaneously collecting the ECG recordings and SPECT results. High resolution 12-lead ECG recordings were collected continuously throughout the rest, exercise, and recovery phases. Patients in the database were classified into three categories of moderate/severe ischemia, mild ischemia, and normal according to the differences in sum of the individual segment scores for the rest and stress SPECT images. Philips DXL 16-lead diagnostic algorithm was run on all 10-s segments of 12-lead ECG recordings for each patient to acquire the representative beats, ECG fiducial points from the representative beats, and other ECG parameters. The QRS slopes were extracted for each lead from the averaged representative beats and the leads with highest classification power were selected. We employed linear discriminant analysis and measured the performance using 10-fold cross-validation. Comparable performance of this method to the conventional ST-segment analysis exhibits the classification power of QRS slopes as unconventional ECG parameters contributing to improved identification of exercise-induced ischemia. PMID:26607407

  17. Enhanced QSAR models for drug-triggered inhibition of the main cardiac ion currents.

    PubMed

    Wiśniowska, Barbara; Mendyk, Aleksander; Szlęk, Jakub; Kołaczkowski, Michał; Polak, Sebastian

    2015-09-01

    The currently changing cardiac safety testing paradigm suggests, among other things, a shift towards using in silico models of cellular electrophysiology and assessment of a concomitant block of multiple ion channels. In this study, a set of four enhanced QSAR models have been developed: for the rapid delayed rectifying potassium current (IKr), slow delayed rectifying potassium current (IKs), peak sodium current (INa) and late calcium current (ICaL), predicting ion currents changes for the specific in vitro experiment from the 2D structure of the compounds. The models are a combination of both in vitro study parameters and physico-chemical descriptors, which is a novel approach in drug-ion channels interactions modeling. Their predictive power assessed in the enhanced, more demanding than standard procedure, 10-fold cross validation was reasonably high. Rough comparison with published pure in silico hERG interaction models shows that the quality of the model predictions does not differ from other models available in the public domain, however, it takes its advantage in accounting for inter-experimental settings variability. Developed models are implemented in the Cardiac Safety Simulator, a commercially available platform enabling the in vitro-in vivo extrapolation of the drugs proarrhythmic effect and ECG simulation. A more comprehensive assessment of the effects of the compounds on ion channels allows for making more informed decisions regarding the risk - and thus avoidance - of exclusion of potentially safe and effective drugs. PMID:25559930

  18. Construction the model on the breast cancer survival analysis use support vector machine, logistic regression and decision tree.

    PubMed

    Chao, Cheng-Min; Yu, Ya-Wen; Cheng, Bor-Wen; Kuo, Yao-Lung

    2014-10-01

    The aim of the paper is to use data mining technology to establish a classification of breast cancer survival patterns, and offers a treatment decision-making reference for the survival ability of women diagnosed with breast cancer in Taiwan. We studied patients with breast cancer in a specific hospital in Central Taiwan to obtain 1,340 data sets. We employed a support vector machine, logistic regression, and a C5.0 decision tree to construct a classification model of breast cancer patients' survival rates, and used a 10-fold cross-validation approach to identify the model. The results show that the establishment of classification tools for the classification of the models yielded an average accuracy rate of more than 90% for both; the SVM provided the best method for constructing the three categories of the classification system for the survival mode. The results of the experiment show that the three methods used to create the classification system, established a high accuracy rate, predicted a more accurate survival ability of women diagnosed with breast cancer, and could be used as a reference when creating a medical decision-making frame. PMID:25119239

  19. A computational method to predict carbonylation sites in yeast proteins.

    PubMed

    Lv, H Q; Liu, J; Han, J Q; Zheng, J G; Liu, R L

    2016-01-01

    Several post-translational modifications (PTM) have been discussed in literature. Among a variety of oxidative stress-induced PTM, protein carbonylation is considered a biomarker of oxidative stress. Only certain proteins can be carbonylated because only four amino acid residues, namely lysine (K), arginine (R), threonine (T) and proline (P), are susceptible to carbonylation. The yeast proteome is an excellent model to explore oxidative stress, especially protein carbonylation. Current experimental approaches in identifying carbonylation sites are expensive, time-consuming and limited in their abilities to process proteins. Furthermore, there is no bioinformational method to predict carbonylation sites in yeast proteins. Therefore, we propose a computational method to predict yeast carbonylation sites. This method has total accuracies of 86.32, 85.89, 84.80, and 86.80% in predicting the carbonylation sites of K, R, T, and P, respectively. These results were confirmed by 10-fold cross-validation. The ability to identify carbonylation sites in different kinds of features was analyzed and the position-specific composition of the modification site-flanking residues was discussed. Additionally, a software tool has been developed to help with the calculations in this method. Datasets and the software are available at https://sourceforge.net/projects/hqlstudio/ files/CarSpred.Y/. PMID:27420944

  20. An Approach to Cosmeceuticals.

    PubMed

    Milam, Emily C; Rieder, Evan A

    2016-04-01

    The cosmeceutical industry is a multi-billion dollar, consumer-driven market. Products promise highly desirable anti-aging benefits, but are not subject to regulation. We present an introduction to cosmeceuticals for the general and cosmetic dermatologist, including definitions and explanations of key terms, an approach to the evidence base, a dissection of chamomile and green tea, two paradigmatic cosmeceutical products, and a window into the underlying psychology of this vast marketplace. PMID:27050700

  1. Theoretical Approaches to Nanoparticles

    NASA Astrophysics Data System (ADS)

    Kempa, Krzysztof

    Nanoparticles can be viewed as wave resonators. Involved waves are, for example, carrier waves, plasmon waves, polariton waves, etc. A few examples of successful theoretical treatments that follow this approach are given. In one, an effective medium theory of a nanoparticle composite is presented. In another, plasmon polaritonic solutions allow to extend concepts of radio technology, such as an antenna and a coaxial transmission line, to the visible frequency range.

  2. Disability: a welfarist approach

    PubMed Central

    Savulescu, Julian; Kahane, Guy

    2011-01-01

    In this paper, we offer a new account of disability. According to our account, some state of a person's biology or psychology is a disability if that state makes it more likely that a person's life will get worse, in terms of his or her own wellbeing, in a given set of social and environmental circumstances. Unlike the medical model of disability, our welfarist approach does not tie disability to deviation from normal species’ functioning, nor does it understand disability in essentialist terms. Like the social model of disability, the welfarist approach sees disability as a harmful state that results from the interaction between a person's biology and psychology and his or her surrounding environment. However, unlike the social model, it denies that the harm associated with disability is entirely due to social prejudice or injustice. In this paper, we outline and clarify the welfarist approach, answer common objections and illustrate its usefulness in addressing a range of difficult ethical questions involving disability. PMID:22140353

  3. Computational vaccinology: quantitative approaches.

    PubMed

    Flower, Darren R; McSparron, Helen; Blythe, Martin J; Zygouri, Christianna; Taylor, Debra; Guan, Pingping; Wan, Shouzhan; Coveney, Peter V; Walshe, Valerie; Borrow, Persephone; Doytchinova, Irini A

    2003-01-01

    The immune system is hierarchical and has many levels, exhibiting much emergent behaviour. However, at its heart are molecular recognition events that are indistinguishable from other types of biomacromolecular interaction. These can be addressed well by quantitative experimental and theoretical biophysical techniques, and particularly by methods from drug design. We review here our approach to computational immunovaccinology. In particular, we describe the JenPep database and two new techniques for T cell epitope prediction. One is based on quantitative structure-activity relationships (a 3D-QSAR method based on CoMSIA and another 2D method based on the Free-Wilson approach) and the other on atomistic molecular dynamic simulations using high performance computing. JenPep (http://www.jenner.ar.uk/ JenPep) is a relational database system supporting quantitative data on peptide binding to major histocompatibility complexes, TAP transporters, TCR-pMHC complexes, and an annotated list of B cell and T cell epitopes. Our 2D-QSAR method factors the contribution to peptide binding from individual amino acids as well as 1-2 and 1-3 residue interactions. In the 3D-QSAR approach, the influence of five physicochemical properties (volume, electrostatic potential, hydrophobicity, hydrogen-bond donor and acceptor abilities) on peptide affinity were considered. Both methods are exemplified through their application to the well-studied problem of peptide binding to the human class I MHC molecule HLA-A*0201. PMID:14712934

  4. Enteral approaches in malabsorption.

    PubMed

    Avitzur, Yaron; Courtney-Martin, Glenda

    2016-04-01

    Enteral autonomy and freedom from parenteral nutrition dependency is the ultimate therapeutic goal in children with intestinal failure. This can be achieved following attainment of bowel adaptation in conditions such as short bowel syndrome. Enteral nutrition is a major therapeutic cornerstone in the management of children with intestinal failure. It promotes physiological development, bowel adaptation and enhances weaning from parenteral nutrition. The optimal method of delivery, type of nutrients, timing of initiation, promotion of feeds and transition to solid food in children with short bowel syndrome are debated. Lack of high quality human data hampers evidence based conclusions and impacts daily practices in the field. Clinical approaches and therapeutic decisions are regularly influenced by expert opinion and center practices. This review summarizes the physiological principles, medical evidence and practice recommendations on enteral nutrition approaches in short bowel syndrome and provides a practical framework for daily treatment of this unique group of patients. Oral and tube feeding, bolus and continuous feeding, type of nutrients, formulas, trace elements and solid food options are reviewed. Future collaborative multicenter, high quality clinical trials are needed to support enteral nutrition approaches in intestinal failure. PMID:27086892

  5. Parsec's astrometry direct approaches .

    NASA Astrophysics Data System (ADS)

    Andrei, A. H.

    Parallaxes - and hence the fundamental establishment of stellar distances - rank among the oldest, keyest, and hardest of astronomical determinations. Arguably amongst the most essential too. The direct approach to obtain trigonometric parallaxes, using a constrained set of equations to derive positions, proper motions, and parallaxes, has been labeled as risky. Properly so, because the axis of the parallactic apparent ellipse is smaller than one arcsec even for the nearest stars, and just a fraction of its perimeter can be followed. Thus the classical approach is of linearizing the description by locking the solution to a set of precise positions of the Earth at the instants of observation, rather than to the dynamics of its orbit, and of adopting a close examination of the never many points available. In the PARSEC program the parallaxes of 143 brown dwarfs were aimed at. Five years of observation of the fields were taken with the WIFI camera at the ESO 2.2m telescope, in Chile. The goal is to provide a statistically significant number of trigonometric parallaxes to BD sub-classes from L0 to T7. Taking advantage of the large, regularly spaced, quantity of observations, here we take the risky approach to fit an ellipse in ecliptical observed coordinates and derive the parallaxes. We also combine the solutions from different centroiding methods, widely proven in prior astrometric investigations. As each of those methods assess diverse properties of the PSFs, they are taken as independent measurements, and combined into a weighted least-square general solution.

  6. Spatiotemporal Modeling of Ozone Levels in Quebec (Canada): A Comparison of Kriging, Land-Use Regression (LUR), and Combined Bayesian Maximum Entropy–LUR Approaches

    PubMed Central

    Adam-Poupart, Ariane; Brand, Allan; Fournier, Michel; Jerrett, Michael

    2014-01-01

    Background: Ambient air ozone (O3) is a pulmonary irritant that has been associated with respiratory health effects including increased lung inflammation and permeability, airway hyperreactivity, respiratory symptoms, and decreased lung function. Estimation of O3 exposure is a complex task because the pollutant exhibits complex spatiotemporal patterns. To refine the quality of exposure estimation, various spatiotemporal methods have been developed worldwide. Objectives: We sought to compare the accuracy of three spatiotemporal models to predict summer ground-level O3 in Quebec, Canada. Methods: We developed a land-use mixed-effects regression (LUR) model based on readily available data (air quality and meteorological monitoring data, road networks information, latitude), a Bayesian maximum entropy (BME) model incorporating both O3 monitoring station data and the land-use mixed model outputs (BME-LUR), and a kriging method model based only on available O3 monitoring station data (BME kriging). We performed leave-one-station-out cross-validation and visually assessed the predictive capability of each model by examining the mean temporal and spatial distributions of the average estimated errors. Results: The BME-LUR was the best predictive model (R2 = 0.653) with the lowest root mean-square error (RMSE ;7.06 ppb), followed by the LUR model (R2 = 0.466, RMSE = 8.747) and the BME kriging model (R2 = 0.414, RMSE = 9.164). Conclusions: Our findings suggest that errors of estimation in the interpolation of O3 concentrations with BME can be greatly reduced by incorporating outputs from a LUR model developed with readily available data. Citation: Adam-Poupart A, Brand A, Fournier M, Jerrett M, Smargiassi A. 2014. Spatiotemporal modeling of ozone levels in Quebec (Canada): a comparison of kriging, land-use regression (LUR), and combined Bayesian maximum entropy–LUR approaches. Environ Health Perspect 122:970–976; http://dx.doi.org/10.1289/ehp.1306566 PMID:24879650

  7. [Approaches to radial shaft].

    PubMed

    Bartoníček, J; Naňka, O; Tuček, M

    2015-10-01

    In the clinical practice, radial shaft may be exposed via two approaches, namely the posterolateral Thompson and volar (anterior) Henry approaches. A feared complication of both of them is the injury to the deep branch of the radial nerve. No consensus has been reached, yet, as to which of the two approaches is more beneficial for the proximal half of radius. According to our anatomical studies and clinical experience, Thompson approach is safe only in fractures of the middle and distal thirds of the radial shaft, but highly risky in fractures of its proximal third. Henry approach may be used in any fracture of the radial shaft and provides a safe exposure of the entire lateral and anterior surfaces of the radius.The Henry approach has three phases. In the first phase, incision is made along the line connecting the biceps brachii tendon and the styloid process of radius. Care must be taken not to damage the lateral cutaneous nerve of forearm.In the second phase, fascia is incised and the brachioradialis identified by the typical transition from the muscle belly to tendon and the shape of the tendon. On the lateral side, the brachioradialis lines the space with the radial artery and veins and the superficial branch of the radial nerve running at its bottom. On the medial side, the space is defined by the pronator teres in the proximal part and the flexor carpi radialis in the distal part. The superficial branch of the radial nerve is retracted together with the brachioradialis laterally, and the radial artery medially.In the third phase, the attachment of the pronator teres is identified by its typical tendon in the middle of convexity of the lateral surface of the radial shaft. The proximal half of the radius must be exposed very carefully in order not to damage the deep branch of the radial nerve. Dissection starts at the insertion of the pronator teres and proceeds proximally along its lateral border in interval between this muscle and insertion of the supinator

  8. Repository program licensing approach

    SciTech Connect

    Williamson, T.M.; Gil, A.V.

    1994-12-31

    Yucca Mountain, Nevada is currently being studied by the US Department of Energy (DOE) as a potential site for a mined geologic repository for high-level nuclear waste. DOE has the responsibility to determine the suitability of the site and to develop a license application (LA) for authorization to construct the potential repository. If the site is suitable, the license application would be submitted to the US Nuclear Regulatory Commission (NRC). The repository program licensing approach is focused on the timely acquisition of information needed in licensing and the resolution of potential licensing issues with the NRC staff. Licensing involves an iterative process requiring refinements as data are acquired, analyzed, and evaluated. The repository licensing approach presented in this paper ensures that the information is available when needed to facilitate the licensing process. Identifying the information needed to evaluate compliance with the performance objectives in 10 CFR 60, monitoring the acquisition of such information, and developing a successful license application are integral elements of DOE`s repository program licensing approach. Activities to characterize the site are being systematically conducted as planned in the Site Characterization Plan (SCP). In addition, DOE is implementing the issue resolution initiative, the license application annotated outline (LAAO) process, and interim licensability evaluations to update the early planning in the SCP and to focus site characterization, design, and performance assessment activities on the acquisition of information needed for a site suitability determination and licensing. Collectively, the issue resolution initiative, LAAO process, and interim licensability evaluations are key elements of a transition to the iterative process to answer the question: {open_quotes}When do we have enough data to support licensing?{close_quotes}

  9. Approaches to Quantum Gravity

    NASA Astrophysics Data System (ADS)

    Oriti, Daniele

    2009-03-01

    Preface; Part I. Fundamental Ideas and General Formalisms: 1. Unfinished revolution C. Rovelli; 2. The fundamental nature of space and time G. 't Hooft; 3. Does locality fail at intermediate length scales R. Sorkin; 4. Prolegomena to any future quantum gravity J. Stachel; 5. Spacetime symmetries in histories canonical gravity N. Savvidou; 6. Categorical geometry and the mathematical foundations of quantum gravity L. Crane; 7. Emergent relativity O. Dreyer; 8. Asymptotic safety R. Percacci; 9. New directions in background independent quantum gravity F. Markopoulou; Questions and answers; Part II: 10. Gauge/gravity duality G. Horowitz and J. Polchinski; 11. String theory, holography and quantum gravity T. Banks; 12. String field theory W. Taylor; Questions and answers; Part III: 13. Loop Quantum Gravity T. Thiemann; 14. Covariant loop quantum gravity? E. LIvine; 15. The spin foam representation of loop quantum gravity A. Perez; 16. 3-dimensional spin foam quantum gravity L. Freidel; 17. The group field theory approach to quantum gravity D. Oriti; Questions and answers; Part IV. Discrete Quantum Gravity: 18. Quantum gravity: the art of building spacetime J. Ambjørn, J. Jurkiewicz and R. Loll; 19. Quantum Regge calculations R. Williams; 20. Consistent discretizations as a road to quantum gravity R. Gambini and J. Pullin; 21. The causal set approach to quantum gravity J. Henson; Questions and answers; Part V. Effective Models and Quantum Gravity Phenomenology: 22. Quantum gravity phenomenology G. Amelino-Camelia; 23. Quantum gravity and precision tests C. Burgess; 24. Algebraic approach to quantum gravity II: non-commutative spacetime F. Girelli; 25. Doubly special relativity J. Kowalski-Glikman; 26. From quantum reference frames to deformed special relativity F. Girelli; 27. Lorentz invariance violation and its role in quantum gravity phenomenology J. Collins, A. Perez and D. Sudarsky; 28. Generic predictions of quantum theories of gravity L. Smolin; Questions and

  10. The collaboratory approach

    SciTech Connect

    Peskin, A.M.

    1997-04-01

    A {open_quotes}collaboratory{close_quotes} has been defined as a center without walls, in which researchers can perform their work without regard to geographical location. To an increasing degree, engineering design and development is also taking the form of far-flung collaborations among divisions of a plant, subcontractors, university consultants and customers. It has long been recognized that quality engineering education presents the student with an environment that duplicates as much as possible that which the graduate will encounter in industry. To that end, it is important that engineering schools begin to introduce the collaboratory approach in its preparation, and even use it in delivery of subject matter to students.

  11. Combined approach brings success.

    PubMed

    Law, Oliver

    2014-06-01

    Sixteen months ago, according to Trumpf Medical Systems, which managed the project, 'something out of the ordinary' happened at Leighton Hospital in Crewe. When making plans to upgrade ageing operating theatres and critical care units, the estates department took the decision to involve other disciplines from the very start of the process. Clinicians, nursing staff, architects, patient representatives, and suppliers, all played their part, with the estates team always at the hub. As Oliver Law, managing director of the UK medical technology specialist, explains, this multidisciplinary approach had a profound effect on the outcome. PMID:25004555

  12. Approaches to Numerical Relativity

    NASA Astrophysics Data System (ADS)

    d'Inverno, Ray

    2005-07-01

    Introduction Ray d'Inverno; Preface C. J. S. Clarke; Part I. Theoretical Approaches: 1. Numerical relativity on a transputer array Ray d'Inverno; 2. Some aspects of the characteristic initial value problem in numerical relativity Nigel Bishop; 3. The characteristic initial value problem in general relativity J. M. Stewart; 4. Algebraic approachs to the characteristic initial value problem in general relativity Jõrg Frauendiener; 5. On hyperboidal hypersurfaces Helmut Friedrich; 6. The initial value problem on null cones J. A. Vickers; 7. Introduction to dual-null dynamics S. A. Hayward; 8. On colliding plane wave space-times J. B. Griffiths; 9. Boundary conditions for the momentum constraint Niall O Murchadha; 10. On the choice of matter model in general relativity A. D. Rendall; 11. A mathematical approach to numerical relativity J. W. Barrett; 12. Making sense of the effects of rotation in general relativity J. C. Miller; 13. Stability of charged boson stars and catastrophe theory Franz E. Schunck, Fjodor V. Kusmartsev and Eckehard W. Mielke; Part II. Practical Approaches: 14. Numerical asymptotics R. Gómez and J. Winicour; 15. Instabilities in rapidly rotating polytropes Scott C. Smith and Joan M. Centrella; 16. Gravitational radiation from coalescing binary neutron stars Ken-Ichi Oohara and Takashi Nakamura; 17. 'Critical' behaviour in massless scalar field collapse M. W. Choptuik; 18. Goudunov-type methods applied to general relativistic gravitational collapse José Ma. Ibánez, José Ma. Martí, Juan A. Miralles and J. V. Romero; 19. Astrophysical sources of gravitational waves and neutrinos Silvano Bonazzola, Eric Gourgoulhon, Pawel Haensel and Jean-Alain Marck; 20. Gravitational radiation from triaxial core collapse Jean-Alain Marck and Silvano Bonazzola; 21. A vacuum fully relativistic 3D numerical code C. Bona and J. Massó; 22. Solution of elliptic equations in numerical relativity using multiquadrics M. R. Dubal, S. R. Oliveira and R. A. Matzner; 23

  13. An evolutionary approach

    NASA Astrophysics Data System (ADS)

    Healy, Thomas J.

    1993-04-01

    The paper describes an evolutionary approach to the development of aerospace systems, represented by the introduction of integrated product teams (IPTs), which are now used at Rockwell's Space Systems Division on all new programs and are introduced into existing projects after demonstrations of increases in quality and reductions in cost and schedule due to IPTs. Each IPT is unique and reflects its own program and lasts for the life of the program. An IPT includes customers, suppliers, subcontractors, and associate contractors, and have a charter, mission, scope of authority, budget, and schedule. Functional management is responsible for the staffing, training, method development, and generic technology development.

  14. Engineering approaches to biomanipulation.

    PubMed

    Desai, Jaydev P; Pillarisetti, Anand; Brooks, Ari D

    2007-01-01

    This article presents a review on the existing techniques for manipulating biological cells. Because biomanipulation involves a wide range of disciplines, from biology to engineering, we concentrate on some of the key methodologies that would result in an efficient biomanipulation system. Some of the key methodologies discussed in this article for cell manipulation relate to the use of magnetics, microelectromechanical systems (MEMS)-based approaches, optics, electric field, and mechanical techniques. Recent advances in engineering have allowed researchers worldwide to address the problems arising from conventional manipulation techniques. This paper assimilates significance and limitations of biomanipulation techniques described in the literature. PMID:17362196

  15. Cognitive approaches to emotions.

    PubMed

    Oatley, Keith; Johnson-Laird, P N

    2014-03-01

    Cognitive approaches offer clear links between how emotions are thought about in everyday life and how they are investigated psychologically. Cognitive researchers have focused on how emotions are caused when events or other people affect concerns and on how emotions influence processes such as reasoning, memory, and attention. Three representative cognitive theories of emotion continue to develop productively: the action-readiness theory, the core-affect theory, and the communicative theory. Some principles are common to them and divergences can be resolved by future research. Recent explanations have included how emotions structure social relationships, how they function in psychological illnesses, and how they are central to music and fiction. PMID:24389368

  16. New approaches for immunosuppression

    SciTech Connect

    Eiseman, B.; Hansbrough, J.; Weil, R.

    1980-01-01

    New approaches for experimental immunosuppression have been reviewed. These include the following: (1) cyclosporin A, a metabolite from fungus that suppresses multiplying but not resting T and B lymphocytes and can be used in pulsed manner with interspersed drug-free periods; (2) total lymphoid irradiation (transplantation tolerance in rats has been achieved by pretransplant radiation); (3) thoracic duct drainage, which is being revived following its demonstrated effectiveness in the treatment of some autoimmune diseases; (4) hyperbaric oxygen (HBOX). We have found that HBOX 2 1/2 ATA for five hours daily depresses cell-mediated immunity in mice and that this can be reversed by intravenous administration of autologous macrophages.

  17. Authentication of Kalix (N.E. Sweden) vendace caviar using inductively coupled plasma-based analytical techniques: evaluation of different approaches.

    PubMed

    Rodushkin, I; Bergman, T; Douglas, G; Engström, E; Sörlin, D; Baxter, D C

    2007-02-01

    Different analytical approaches for origin differentiation between vendace and whitefish caviars from brackish- and freshwaters were tested using inductively coupled plasma double focusing sector field mass spectrometry (ICP-SFMS) and multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS). These approaches involve identifying differences in elemental concentrations or sample-specific isotopic composition (Sr and Os) variations. Concentrations of 72 elements were determined by ICP-SFMS following microwave-assisted digestion in vendace and whitefish caviar samples from Sweden (from both brackish and freshwater), Finland and USA, as well as in unprocessed vendace roe and salt used in caviar production. This data set allows identification of elements whose contents in caviar can be affected by salt addition as well as by contamination during production and packaging. Long-term method reproducibility was assessed for all analytes based on replicate caviar preparations/analyses and variations in element concentrations in caviar from different harvests were evaluated. The greatest utility for differentiation was demonstrated for elements with varying concentrations between brackish and freshwaters (e.g. As, Br, Sr). Elemental ratios, specifically Sr/Ca, Sr/Mg and Sr/Ba, are especially useful for authentication of vendace caviar processed from brackish water roe, due to the significant differences between caviar from different sources, limited between-harvest variations and relatively high concentrations in samples, allowing precise determination by modern analytical instrumentation. Variations in the 87Sr/86Sr ratio for vendace caviar from different harvests (on the order of 0.05-0.1%) is at least 10-fold less than differences between caviar processed from brackish and freshwater roe. Hence, Sr isotope ratio measurements (either by ICP-SFMS or by MC-ICP-MS) have great potential for origin differentiation. On the contrary, it was impossible to

  18. Avenue of approach generation

    SciTech Connect

    Powell, D.R.; Storm, G.

    1988-01-01

    Los Alamos National Laboratory is conducting research on developing a dynamic planning capability within an Army corps level combat simulation. Central to this research is the development of a computer based ability to ''understand'' terrain and how it is used in military planning. Such a capability demands data structures that adequately represent terrain features used in the planning process. These features primarily relate to attributes of mobility and visibility. Mobility concepts are abstracted to networks of mobility corridors. Notions of visibility are, for the purposes of planning, incorporated into the definition of key terrain. Prior work at Los Alamos has produced algorithms to generate mobility corridors from digitized terrain data. Mobility corridors, by definition, are the building blocks for avenues of approach, and the latter are the context in which key terrain is defined. The purpose of this paper is to describe recent work in constructing avenues of approach, characterization of avenues using summary characteristics, and their role in military planning. 7 refs., 4 figs., 1 tab.

  19. Modular Approach to Spintronics

    PubMed Central

    Camsari, Kerem Yunus; Ganguly, Samiran; Datta, Supriyo

    2015-01-01

    There has been enormous progress in the last two decades, effectively combining spintronics and magnetics into a powerful force that is shaping the field of memory devices. New materials and phenomena continue to be discovered at an impressive rate, providing an ever-increasing set of building blocks that could be exploited in designing transistor-like functional devices of the future. The objective of this paper is to provide a quantitative foundation for this building block approach, so that new discoveries can be integrated into functional device concepts, quickly analyzed and critically evaluated. Through careful benchmarking against available theory and experiment we establish a set of elemental modules representing diverse materials and phenomena. These elemental modules can be integrated seamlessly to model composite devices involving both spintronic and nanomagnetic phenomena. We envision the library of modules to evolve both by incorporating new modules and by improving existing modules as the field progresses. The primary contribution of this paper is to establish the ground rules or protocols for a modular approach that can build a lasting bridge between materials scientists and circuit designers in the field of spintronics and nanomagnetics. PMID:26066079

  20. Approaches to robustness

    NASA Astrophysics Data System (ADS)

    Cox, Henry; Heaney, Kevin D.

    2003-04-01

    The term robustness in signal processing applications usually refers to approaches that are not degraded significantly when the assumptions that were invoked in defining the processing algorithm are no longer valid. Highly tuned algorithms that fall apart in real-world conditions are useless. The classic example is super-directive arrays of closely spaced elements. The very narrow beams and high directivity could be predicted under ideal conditions, could not be achieved under realistic conditions of amplitude, phase and position errors. The robust design tries to take into account the real environment as part of the optimization problem. This problem led to the introduction of the white noise gain constraint and diagonal loading in adaptive beam forming. Multiple linear constraints have been introduced in pursuit of robustness. Sonar systems such as towed arrays operate in less than ideal conditions, making robustness a concern. A special problem in sonar systems is failed array elements. This leads to severe degradation in beam patterns and bearing response patterns. Another robustness issue arises in matched field processing that uses an acoustic propagation model in the beamforming. Knowledge of the environmental parameters is usually limited. This paper reviews the various approaches to achieving robustness in sonar systems.

  1. Common approaches for adolescents.

    PubMed

    1998-01-01

    A South-South program organized by JOICFP provided an excellent opportunity for the exchange of experiences in the field of adolescent reproductive health (RH) between Mexico and the Philippines. Alfonso Lopez Juarez, executive director, Mexican Foundation for Family Planning (MEXFAM), shared MEXFAM's experiences with field personnel and GO-NGO representatives related to JOICFP's RH-oriented project in the Philippines while in the country from November 16 to 21. The program was also effective for identifying common issues and effective approaches to adolescent health issues and communicating with youth on RH and sexual health. The exchange was supported by the Hoken Kaikan Foundation and organized by JOICFP in collaboration with UNFPA-Manila and the Commission on Population (POPCOM). Lopez shared some of the lessons of MEXFAM's decade-long Gente Joven IEC program on adolescent health with GO and NGO representatives at a forum held on November 18. The event was opened by Dr. Carmencita Reodica, secretary, Department of Health (DOH). He then moved to the project sites of Balayan and Malvar municipalities of Batangas Province, where he spoke with field staff and demonstrated MEXFAM's approach in classroom situations with young people. Lopez also observed various adolescent activities such as group work with peer facilitators. "I am pleased that we can share some applicable experiences and learn from each other's projects," commented Lopez. PMID:12348336

  2. Breakfast: a multidisciplinary approach

    PubMed Central

    2013-01-01

    Background The role of breakfast as an essential part of an healthy diet has been only recently promoted even if breakfast practices were known since the Middle Age. The growing scientific evidences on this topic are extremely sector-based nevertheless breakfast could be regarded from different point of views and from different expertises. This approach, that take into account history, sociology, anthropology, medicine, psychology and pedagogy, is useful to better understand the value of this meal in our culture. The aim of this paper was to analyse breakfast-related issues based on a multidisciplinary approach with input by specialists from different fields of learning. Discussion Breakfast is now recommended as part of a diet because it is associated with healthier macro- and micronutrient intakes, body mass index and lifestyle. Moreover recent studies showed that breakfast improves cognitive function, intuitive perception and academic performance. Research demonstrates the importance of providing breakfast not only to children but in adults and elderly too. Although the important role breakfast plays in maintaining the health, epidemiological data from industrialised countries reveal that many individuals either eat a nutritionally unhealthy breakfast or skip it completely. Summary The historical, bio-psychological and educational value of breakfast in our culture is extremely important and should be recognized and stressed by the scientific community. Efforts should be done to promote this practice for the individual health and well-being. PMID:23842429

  3. Pharmacogenetics approach to therapeutics.

    PubMed

    Koo, Seok Hwee; Lee, Edmund Jon Deoon

    2006-01-01

    1. Pharmacogenetics refers to the study of genetically controlled variations in drug response. Functional variants caused by single nucleotide polymorphisms (SNPs) in genes encoding drug-metabolising enzymes, transporters, ion channels and drug receptors have been known to be associated with interindividual and interethnic variation in drug response. Genetic variations in these genes play a role in influencing the efficacy and toxicity of medications. 2. Rapid, precise and cost-effective high-throughput technological platforms are essential for performing large-scale mutational analysis of genetic markers involved in the aetiology of variable responses to drug therapy. 3. The application of a pharmacogenetics approach to therapeutics in general clinical practice is still far from being achieved today owing to various constraints, such as limited accessibility of technology, inadequate knowledge, ambiguity of the role of variants and ethical concerns. 4. Drug actions are determined by the interplay of several genes encoding different proteins involved in various biochemical pathways. With rapidly emerging SNP discovery technological platforms and widespread knowledge on the role of SNPs in disease susceptibility and variability in drug response, the pharmacogenetics approach to therapeutics is anticipated to take off in the not-too-distant future. This will present profound clinical, economic and social implications for health care. PMID:16700889

  4. A Blend Approach to P3HT Based Field Effect Transistor Performance Enhancement via Inclusion of 2,5-bis(3-dodecylthiophen-2-yl)thieno[3,2-b]thiophene

    NASA Astrophysics Data System (ADS)

    Chu, Ping-Hsun; Zhang, Lei; Park, Jung Ok; Srinivasarao, Mohan; Briseño, Alejandro L.; Reichmanis, Elsa

    2015-03-01

    Improved OFET performance through a polymer-small molecule semiconductor blend approach was demonstrated. However, a number of serious issues remain. For example, the threshold voltage (Vth) of the blend OFETs is still at a relatively high value (|Vth|>10V), which is incompatible with most of portable electronics. Moreover, electrode treatment or thermal annealing is required to avoid a sacrifice in the device performance. Herein, a small molecule, 2,5-bis(3-dodecylthiophen-2-yl)thieno[3,2-b]thiophene (BTTT), is proposed to be incorporated within poly(3-hexylthiophene) (P3HT) polymer thin-films and is demonstrated to lead to overall improvement in transistor performance. The resultant blend OFETs exhibited approximately a 5-fold increase in charge carrier mobility, 10-fold increase in on-off current ratio and concomitantly, controlled the Vth as low as 1.7 V. It is worth noting that no pre- or post-treatment is required during the blend OFET fabrication process. Further, the thin-film deposition was conducted under ambient conditions using a volatile low boiling point solvent, suggesting a promising method for low-cost, high-throughput, large-area flexible device fabrication under non-stringent conditions.

  5. Coordinated Parallel Runway Approaches

    NASA Technical Reports Server (NTRS)

    Koczo, Steve

    1996-01-01

    The current air traffic environment in airport terminal areas experiences substantial delays when weather conditions deteriorate to Instrument Meteorological Conditions (IMC). Expected future increases in air traffic will put additional pressures on the National Airspace System (NAS) and will further compound the high costs associated with airport delays. To address this problem, NASA has embarked on a program to address Terminal Area Productivity (TAP). The goals of the TAP program are to provide increased efficiencies in air traffic during the approach, landing, and surface operations in low-visibility conditions. The ultimate goal is to achieve efficiencies of terminal area flight operations commensurate with Visual Meteorological Conditions (VMC) at current or improved levels of safety.

  6. Engineering students' sustainability approaches

    NASA Astrophysics Data System (ADS)

    Haase, S.

    2014-05-01

    Sustainability issues are increasingly important in engineering work all over the world. This article explores systematic differences in self-assessed competencies, interests, importance, engagement and practices of newly enrolled engineering students in Denmark in relation to environmental and non-environmental sustainability issues. The empirical base of the article is a nation-wide, web-based survey sent to all newly enrolled engineering students in Denmark commencing their education in the fall term 2010. The response rate was 46%. The survey focused on a variety of different aspects of what can be conceived as sustainability. By means of cluster analysis, three engineering student approaches to sustainability are identified and described. The article provides knowledge on the different prerequisites of engineering students in relation to the role of sustainability in engineering. This information is important input to educators trying to target new engineering students and contribute to the provision of engineers equipped to meet sustainability challenges.

  7. Neuroblastoma: A neurochemical approach

    SciTech Connect

    Schor, N.F. )

    1991-07-01

    Neuroblastoma is among the most common malignancies of childhood. Despite greatly improved therapy for some pediatric tumors, the prognosis for children with metastatic neuroblastoma has not changed significantly in the past 10 years. With conventional chemotherapy, radiation therapy, and surgery, children with metastatic neuroblastoma have a 20% long-term survival rate. The authors describe here approaches to neuroblastoma that target its neuronal characteristics. On the one hand, the neurotransmitter receptors on the surface of the neuroblastoma cells and, on the other hand, specific isozymes that distinguish neuroblastoma cells from their normal counterparts are the focus of these experimental therapies. In the former case, specificity for tumor cells is effected by (1) selective protection of normal neuronal elements from toxicity, or (2) selective potentiation of toxicity for neural tumor cells. It is hoped that these strategies will be generalizable to other neural crest-derived tumors. 32 references.

  8. Therapeutic approaches for shankopathies.

    PubMed

    Wang, Xiaoming; Bey, Alexandra L; Chung, Leeyup; Krystal, Andrew D; Jiang, Yong-Hui

    2014-02-01

    Despite recent advances in understanding the molecular mechanisms of autism spectrum disorders (ASD), the current treatments for these disorders are mostly focused on behavioral and educational approaches. The considerable clinical and molecular heterogeneity of ASD present a significant challenge to the development of an effective treatment targeting underlying molecular defects. Deficiency of SHANK family genes causing ASD represent an exciting opportunity for developing molecular therapies because of strong genetic evidence for SHANK as causative genes in ASD and the availability of a panel of Shank mutant mouse models. In this article, we review the literature suggesting the potential for developing therapies based on molecular characteristics and discuss several exciting themes that are emerging from studying Shank mutant mice at the molecular level and in terms of synaptic function. PMID:23536326

  9. Modelling approaches for angiogenesis.

    PubMed

    Taraboletti, G; Giavazzi, R

    2004-04-01

    The development of a functional vasculature within a tumour is a requisite for its growth and progression. This fact has led to the design of therapies directed toward the tumour vasculature, aiming either to prevent the formation of new vessels (anti-angiogenic) or to damage existing vessels (vascular targeting). The development of agents with different mechanisms of action requires powerful preclinical models for the analysis and optimization of these therapies. This review concerns 'classical' assays of angiogenesis in vitro and in vivo, recent approaches to target identification (analysis of gene and protein expression), and the study of morphological and functional changes in the vasculature in vivo (imaging techniques). It mainly describes assays designed for anti-angiogenic compounds, indicating, where possible, their application to the study of vascular-targeting agents. PMID:15120043

  10. Editorial: Approaching 125.

    PubMed

    Goodman, Sherryl

    2012-02-01

    With this issue, beginning Volume 121, the editorial team shifts from the strong leadership of David Watson to a team under my direction. Approaching 125 years of publication, the Journal of Abnormal Psychology has earned its place as the preeminent outlet for research in psychopathology. With gratitude to the newly assembled team of associate editors (AEs), consulting editors, and ad hoc reviewers, I look forward to guiding the journal through this next term. Nine well-respected scholars have agreed to serve as AEs: Timothy Brown, Laurie Chassin, Jeff Epstein, Jutta Joormann, Pamela Keel, Kate Keenan, Scott Lilienfeld, Angus MacDonald, and Michael Young. The new team is dedicated to working tirelessly to maintain and enhance the journal's esteemed tradition of excellence. Given the well-established strengths of the journal, I will not suggest any fundamental changes. PMID:22329705

  11. Approaching the new reality

    NASA Technical Reports Server (NTRS)

    Diaz, Al V.

    1993-01-01

    I'm very pleased to be here and to have this opportunity to discuss with you what I view as the current challenges in space science. Today, NASA finds itself at a major crossroads. We are in the process of moving from one era in our existence into another. As we continue to launch important science missions, we are simultaneously changing the way we do business, in a very fundamental way. We are again focusing on more frequent access to space through smaller, less costly missions. We are again focusing on NASA's role as a source of technological advancement within the U.S. economy. And we are returning to the leaner, more flexible approach to managing our projects. In short, NASA has embarked on a new journey, and a challenging journey it will be.

  12. Approaching the new reality

    NASA Astrophysics Data System (ADS)

    Diaz, Al V.

    I'm very pleased to be here and to have this opportunity to discuss with you what I view as the current challenges in space science. Today, NASA finds itself at a major crossroads. We are in the process of moving from one era in our existence into another. As we continue to launch important science missions, we are simultaneously changing the way we do business, in a very fundamental way. We are again focusing on more frequent access to space through smaller, less costly missions. We are again focusing on NASA's role as a source of technological advancement within the U.S. economy. And we are returning to the leaner, more flexible approach to managing our projects. In short, NASA has embarked on a new journey, and a challenging journey it will be.

  13. An environmental approach

    SciTech Connect

    Geerling, C.

    1996-11-01

    The Shell Petroleum Development Company is operating in southern Nigeria in the delta of the Niger River. This delta covers an area 70,000 square kin of coastal ridge barriers, mangroves, freshwater swamp forest and lowland rain forests. Over the past decades considerable changes has occurred through coastal zone modifications, upstream urban and hydrological infrastructure, deforestation, agriculture, fisheries, industrial development, oil operation, as well as demographic changes. The problems associated with these changes are: (1) over-exploitation of renewable natural resources and breakdown of traditional management structures; (2) impact from industry such as pollution and physical changes, and (3) a perception of lack of social and economic equity. This paper describes approaches to help counteract theses problems.

  14. Children and Complementary Health Approaches

    MedlinePlus

    ... Ewsichek What’s the Bottom Line? How much do we know about complementary health approaches for children? We ... about their effects and safety. 1 What do we know about the effectiveness of complementary health approaches ...

  15. Alternative approaches to population structure.

    PubMed

    Morton, N E

    1995-01-01

    There are three approaches to DNA identification: tectonic, halieutic and icarian, of which the tectonic is sensible, the halieutic impractical, and the icarian idiotic. The rationale and consequences of these approaches are detailed. PMID:7607451

  16. Television Criticism: A Multifarious Approach.

    ERIC Educational Resources Information Center

    Oseguera, A. Anthony

    Recognizing the need for a multifarious approach to television, this paper provides the reader with the following multidimensional approaches to television criticism: rhetorical, dramatic, literary, cinematic, content analysis, myth, linguistics, semiotics, phenomenalism, phenomenology, interpersonal communication, public relations, image,…

  17. Cancer and Complementary Health Approaches

    MedlinePlus

    ... Legislation Advisory Council Job Opportunities All About NCCIH Health Topics A-Z # A B C D E ... from NCI at www.cancer.gov . About Complementary Health Approaches Complementary health approaches are a group of ...

  18. Approaching attometer laser vibrometry

    SciTech Connect

    Rembe, Christian; Kadner, Lisa; Giesen, Moritz

    2014-05-27

    The heterodyne two-beam interferometer has been proven to be the optimal solution for laser-Doppler vibrometry regarding accuracy and signal robustness. The theoretical resolution limit for a two-beam interferometer of laser class 3R (up to 5 mW visible measurement-light) is in the regime of a few femtometer per square-root Hertz and well suited to study vibrations in microstructures. However, some new applications of RF-MEM resonators, nanostructures, and surface-nano-defect detection require resolutions beyond that limit. The resolution depends only on the noise and the sensor sensitivity to specimen displacements. The noise is already defined in nowadays systems by the quantum nature of light for a properly designed optical sensor and more light would lead to an inacceptable influence like heating of a very tiny structure. Thus, noise can only be improved by squeezed-light techniques which require a negligible loss of measurement light which is impossible for almost all technical measurement tasks. Thus, improving the sensitivity is the only possible path which could make attometer laser vibrometry possible. Decreasing the measurement wavelength would increase the sensitivity but would also increase the photon shot noise. In this paper, we discuss an approach to increase the sensitivity by assembling an additional mirror between interferometer and specimen to form an optical cavity. A detailed theoretical analysis of this setup is presented and we derive the resolution limit, discuss the main contributions to the uncertainty budget, and show a first experiment proving the sensitivity amplification of our approach.

  19. Neptune - closest approach

    NASA Technical Reports Server (NTRS)

    1989-01-01

    The Voyager spacecraft took this picture after closest approach to Neptune on Aug. 25 1989, using the clear filter of the wide-angle camera with an exposure time of 255 seconds. The view back towards Neptune at a phase angle of 135 degrees found the two known rings to be five to 10 times brighter than seen in backscattering during Voyager approach at much lower phase angle. This brightness increase implies a large percentage of microscopic particles within the rings. Although the dominant arc-like clump of the outer ring is not seen here, the inner ring appears brighter than the outer ring at the longitudes seen in this image. A faint sheet of material is also revealed that extends from the faint ring at a radius of 53,200 kilometers(33,000 miles). A new and even fainter ring was discovered in this image at about 41,000 kilometers (25,400 miles), seen running from the lower left corner to about one-third the way across the top of the frame. This ring is quite broad, about 2,500 kilometers (1,550 miles) in radial width. In contrast to the two previously discovered rings, this feature is quite diffuse and has no well defined radial boundaries. The Voyager imaging experiment has now detected ring material in all of the radial regions in which it has been detected by groundbased stellar occultation experiments. The Voyager spacecraft was 720,000 kilometers (446,400 miles) from Neptune at the time of this exposure. The Voyager Mission is conducted by JPL for NASA's Office of Space Science and Applications.

  20. Approaches to Multicultural Curriculum Reform.

    ERIC Educational Resources Information Center

    Banks, James A.

    1990-01-01

    Discusses the pros and cons of the contributions of ethnic additive, transformation, decision-making, and social action approaches to multicultural curriculum development. Suggests that movement from a mainstream-centric approach to social action approach is gradual and cumulative. (GG)

  1. Cross-validation Methodology between Ground and GPM Satellite-based Radar Rainfall Product over Dallas-Fort Worth (DFW) Metroplex

    NASA Astrophysics Data System (ADS)

    Chen, H.; Chandrasekar, V.; Biswas, S.

    2015-12-01

    Over the past two decades, a large number of rainfall products have been developed based on satellite, radar, and/or rain gauge observations. However, to produce optimal rainfall estimation for a given region is still challenging due to the space time variability of rainfall at many scales and the spatial and temporal sampling difference of different rainfall instruments. In order to produce high-resolution rainfall products for urban flash flood applications and improve the weather sensing capability in urban environment, the center for Collaborative Adaptive Sensing of the Atmosphere (CASA), in collaboration with National Weather Service (NWS) and North Central Texas Council of Governments (NCTCOG), has developed an urban radar remote sensing network in DFW Metroplex. DFW is the largest inland metropolitan area in the U.S., that experiences a wide range of natural weather hazards such as flash flood and hailstorms. The DFW urban remote sensing network, centered by the deployment of eight dual-polarization X-band radars and a NWS WSR-88DP radar, is expected to provide impacts-based warning and forecasts for benefit of the public safety and economy. High-resolution quantitative precipitation estimation (QPE) is one of the major goals of the development of this urban test bed. In addition to ground radar-based rainfall estimation, satellite-based rainfall products for this area are also of interest for this study. Typical example is the rainfall rate product produced by the Dual-frequency Precipitation Radar (DPR) onboard Global Precipitation Measurement (GPM) Core Observatory satellite. Therefore, cross-comparison between ground and space-based rainfall estimation is critical to building an optimal regional rainfall system, which can take advantages of the sampling differences of different sensors. This paper presents the real-time high-resolution QPE system developed for DFW urban radar network, which is based upon the combination of S-band WSR-88DP and X-band CASA radars. In addition, we focuses on the cross-comparison between rainfall estimation from this ground based QPE system and GPM rainfall products. The observations collected during the GPM satellite overpasses over DFW area will be used extensively in this study. Data alignment for better comparison will also be presented.

  2. Cross-validation of the factorial structure of the Neighborhood Environment Walkability Scale (NEWS) and its abbreviated form (NEWS-A)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The Neighborhood Environment Walkability Scale (NEWS) and its abbreviated form (NEWS-A) assess perceived environmental attributes believed to influence physical activity. A multilevel confirmatory factor analysis (MCFA) conducted on a sample from Seattle, WA, showed that, at the respondent level, th...

  3. Cross-Validation of the Spanish HP-Version of the Jefferson Scale of Empathy Confirmed with Some Cross-Cultural Differences

    PubMed Central

    Alcorta-Garza, Adelina; San-Martín, Montserrat; Delgado-Bolton, Roberto; Soler-González, Jorge; Roig, Helena; Vivanco, Luis

    2016-01-01

    Context: Medical educators agree that empathy is essential for physicians' professionalism. The Health Professional Version of the Jefferson Scale of Empathy (JSE-HP) was developed in response to a need for a psychometrically sound instrument to measure empathy in the context of patient care. Although extensive support for its validity and reliability is available, the authors recognize the necessity to examine psychometrics of the JSE-HP in different socio-cultural contexts to assure the psychometric soundness of this instrument. The first aim of this study was to confirm its psychometric properties in the cross-cultural context of Spain and Latin American countries. The second aim was to measure the influence of social and cultural factors on the development of medical empathy in health practitioners. Methods: The original English version of the JSE-HP was translated into International Spanish using back-translation procedures. The Spanish version of the JSE-HP was administered to 896 physicians from Spain and 13 Latin American countries. Data were subjected to exploratory factor analysis using principal component analysis (PCA) with oblique rotation (promax) to allow for correlation among the resulting factors, followed by a second analysis, using confirmatory factor analysis (CFA). Two theoretical models, one based on the English JSE-HP and another on the first Spanish student version of the JSE (JSE-S), were tested. Demographic variables were compared using group comparisons. Results: A total of 715 (80%) surveys were returned fully completed. Cronbach's alpha coefficient of the JSE for the entire sample was 0.84. The psychometric properties of the Spanish JSE-HP matched those of the original English JSE-HP. However, the Spanish JSE-S model proved more appropriate than the original English model for the sample in this study. Group comparisons among physicians classified by gender, medical specialties, cultural and cross-cultural backgrounds yielded statistically significant differences (p < 0.001). Conclusions: The findings support the underlying factor structure of the Jefferson Scale of Empathy (JSE). The results reveal the importance of culture in the development of medical empathy. The cross-cultural differences described could open gates for further lines of medical education research. PMID:27462282

  4. Cross-validation of IASI/MetOp derived tropospheric δD with TES and ground-based FTIR observations

    NASA Astrophysics Data System (ADS)

    Lacour, J.-L.; Clarisse, L.; Worden, J.; Schneider, M.; Barthlott, S.; Hase, F.; Risi, C.; Clerbaux, C.; Hurtmans, D.; Coheur, P.-F.

    2014-11-01

    The Infrared Atmospheric Sounding Interferometer (IASI) flying on-board MetOpA and MetOpB is able to capture fine isotopic variations of the HDO to H2O ratio (δD) in the troposphere. Such observations at the high spatio temporal resolution of the sounder are of great interest to improve our understanding of the mechanisms controlling humidity in the troposphere. In this study we aim to empirically assess the validity of our error estimation previously evaluated theoretically. To achieve this, we compare IASI δD retrieved profiles with other available profiles of δD, from the TES infrared sounder onboard AURA and from three ground-based FTIR stations produced within the MUSICA project: the NDACC (Network for the Detection of Atmospheric Composition Change) sites Kiruna and Izana, and the TCCON site Karlsruhe, which in addition to near-infrared TCCON spectra also records mid-infrared spectra. We describe the achievable level of agreement between the different retrievals and show that these theoretical errors are in good agreement with empirical differences. The comparisons are made at different locations from tropical to Arctic latitudes, above sea and above land. Generally IASI and TES are similarly sensitive to δD in the free troposphere which allows to compare their measurements directly. At tropical latitudes where IASI's sensitivity is lower than that of TES, we show that the agreement improves when taking into account the sensitivity of IASI in the TES retrieval. For the comparison IASI-FTIR only direct comparisons are performed because of similar sensitivities. We identify a quasi negligible bias in the free troposphere (-3‰) between IASI retrieved δD with the TES one, which are bias corrected, but an important with the ground-based FTIR reaching -47‰. We also suggest that model-satellite observations comparisons could be optimized with IASI thanks to its high spatial and temporal sampling.

  5. Cross-validation of IASI/MetOp derived tropospheric δD with TES and ground-based FTIR observations

    NASA Astrophysics Data System (ADS)

    Lacour, J.-L.; Clarisse, L.; Worden, J.; Schneider, M.; Barthlott, S.; Hase, F.; Risi, C.; Clerbaux, C.; Hurtmans, D.; Coheur, P.-F.

    2015-03-01

    The Infrared Atmospheric Sounding Interferometer (IASI) flying onboard MetOpA and MetOpB is able to capture fine isotopic variations of the HDO to H2O ratio (δD) in the troposphere. Such observations at the high spatio-temporal resolution of the sounder are of great interest to improve our understanding of the mechanisms controlling humidity in the troposphere. In this study we aim to empirically assess the validity of our error estimation previously evaluated theoretically. To achieve this, we compare IASI δD retrieved profiles with other available profiles of δD, from the TES infrared sounder onboard AURA and from three ground-based FTIR stations produced within the MUSICA project: the NDACC (Network for the Detection of Atmospheric Composition Change) sites Kiruna and Izaña, and the TCCON site Karlsruhe, which in addition to near-infrared TCCON spectra also records mid-infrared spectra. We describe the achievable level of agreement between the different retrievals and show that these theoretical errors are in good agreement with empirical differences. The comparisons are made at different locations from tropical to Arctic latitudes, above sea and above land. Generally IASI and TES are similarly sensitive to δD in the free troposphere which allows one to compare their measurements directly. At tropical latitudes where IASI's sensitivity is lower than that of TES, we show that the agreement improves when taking into account the sensitivity of IASI in the TES retrieval. For the comparison IASI-FTIR only direct comparisons are performed because the sensitivity profiles of the two observing systems do not allow to take into account their differences of sensitivity. We identify a quasi negligible bias in the free troposphere (-3‰) between IASI retrieved δD with the TES, which are bias corrected, but important with the ground-based FTIR reaching -47‰. We also suggest that model-satellite observation comparisons could be optimized with IASI thanks to its high spatial and temporal sampling.

  6. Adaptive neuro-fuzzy inference systems with k-fold cross-validation for energy expenditure predictions based on heart rate.

    PubMed

    Kolus, Ahmet; Imbeau, Daniel; Dubé, Philippe-Antoine; Dubeau, Denise

    2015-09-01

    This paper presents a new model based on adaptive neuro-fuzzy inference systems (ANFIS) to predict oxygen consumption (V˙O2) from easily measured variables. The ANFIS prediction model consists of three ANFIS modules for estimating the Flex-HR parameters. Each module was developed based on clustering a training set of data samples relevant to that module and then the ANFIS prediction model was tested against a validation data set. Fifty-eight participants performed the Meyer and Flenghi step-test, during which heart rate (HR) and V˙O2 were measured. Results indicated no significant difference between observed and estimated Flex-HR parameters and between measured and estimated V˙O2 in the overall HR range, and separately in different HR ranges. The ANFIS prediction model (MAE = 3 ml kg(-1) min(-1)) demonstrated better performance than Rennie et al.'s (MAE = 7 ml kg(-1) min(-1)) and Keytel et al.'s (MAE = 6 ml kg(-1) min(-1)) models, and comparable performance with the standard Flex-HR method (MAE = 2.3 ml kg(-1) min(-1)) throughout the HR range. The ANFIS model thus provides practitioners with a practical, cost- and time-efficient method for V˙O2 estimation without the need for individual calibration. PMID:25959320

  7. Near surface geotechnical and geophysical data cross validated for site characterization applications. The cases of selected accelerometric stations in Crete island (Greece)

    NASA Astrophysics Data System (ADS)

    Loupasakis, Constantinos; Tsangaratos, Paraskevas; Rozos, Dimitrios; Rondoyianni, Theodora; Vafidis, Antonis; Steiakakis, Emanouil; Agioutantis, Zacharias; Savvaidis, Alexandros; Soupios, Pantelis; Papadopoulos, Ioannis; Papadopoulos, Nikos; Sarris, Apostolos; Mangriotis, Maria-Dafni; Dikmen, Unal

    2015-04-01

    The near surface ground conditions are highly important for the design of civil constructions. These conditions determine primarily the ability of the foundation formations to bear loads, the stress - strain relations and the corresponding deformations, as well as the soil amplification and corresponding peak ground motion in case of dynamic loading. The static and dynamic geotechnical parameters as well as the ground-type/soil-category can be determined by combining geotechnical and geophysical methods, such as engineering geological surface mapping, geotechnical drilling, in situ and laboratory testing and geophysical investigations. The above mentioned methods were combined for the site characterization in selected sites of the Hellenic Accelerometric Network (HAN) in the area of Crete Island. The combination of the geotechnical and geophysical methods in thirteen (13) sites provided sufficient information about their limitations, setting up the minimum tests requirements in relation to the type of the geological formations. The reduced accuracy of the surface mapping in urban sites, the uncertainties introduced by the geophysical survey in sites with complex geology and the 1-D data provided by the geotechnical drills are some of the causes affecting the right order and the quantity of the necessary investigation methods. Through this study the gradual improvement on the accuracy of the site characterization data in regards to the applied investigation techniques is presented by providing characteristic examples from the total number of thirteen sites. As an example of the gradual improvement of the knowledge about the ground conditions the case of AGN1 strong motion station, located at Agios Nikolaos city (Eastern Crete), is briefly presented. According to the medium scale geological map of IGME the station was supposed to be founded over limestone. The detailed geological mapping reveled that a few meters of loose alluvial deposits occupy the area, expected to lay over the Neogene marly formations and the Mesozoic limestone, identified at the surrounding area. This changes the ground type to E instead of A, based on the EC8 classification. According the geophysical survey the Neogene formations extend down several meters and the mean Vs30 is 476m/s, increasing the rank of the ground type to B. Finally, the geotechnical drill reviled that the loose alluvial deposits extend down 13m containing two clearly identified layers of liquefiable loose sand. Below the alluvial deposits a thin layer (1,5m thick) of Neogene marly formations and the karstified limestone was located, as expected. So finally it was proved that the ground type category at the site is S2, setting up the geotechnical drills as the determinant investigation technique for this site. Besides the above described case, all selected examples present sufficiently the ability, the limitations and the right order of the investigation methods aiming to the site characterization. This research has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

  8. Cross-Validation of the Taiwan Version of the Moorehead–Ardelt Quality of Life Questionnaire II with WHOQOL and SF-36

    PubMed Central

    Chang, Chi-Yang; Huang, Chih-Kun; Chang, Yu-Yin; Tai, Chi-Ming; Lin, Jaw-Town

    2009-01-01

    Background Obesity has become a major worldwide public health issue. There is a need for tools to measure patient-reported outcomes. The Moorehead–Ardelt Quality of Life Questionnaire II (MA II) contains six items. The objective of this study was to translate the MA II into Chinese and validate it in patients with morbid obesity. Methods The MA II was translated into Chinese and back-translated into English by two language specialists to create the Taiwan version, which was validated by correlations with two other generic questionnaires of health-related quality of life (HRQOL), Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36), and World Health Organization Quality of Life (WHOQOL)-BREF Taiwan version. The convergent validity was accomplished by a series of Spearman rank correlations. Reliability of the MA II Taiwan version was determined by internal consistency obtained by Cronbach’s alpha coefficient and test–retest reliability obtained by intraclass correlation coefficient. Results One hundred subjects with morbid obesity were enrolled to test the MA II Taiwan version convergent validity and internal consistency. Test–retest studies (2 weeks apart) were applied to 30 morbidly obese patients. Satisfactory internal consistency was demonstrated by a Cronbach’s alpha coefficient of 0.79. Good test–retest reliability was shown by intraclass correlations ranging from 0.73 to 0.91. The total sum of MA II scores was significantly correlated with all four domains of the WHOQOL-BREF and two major components of SF-36 (all correlations, p < 0.01; range, 0.44–0.64). All six MA II items showed significant correlations with each other (r = 0.34–0.69, p < 0.01), and the total sum of MA II scores was negatively correlated with body mass index (r = −0.31, p < 0.01), indicating a one-dimensional questionnaire of HRQOL. Conclusions The MA II Taiwan version is an obesity-specific questionnaire for QOL evaluation with satisfactory reliability and validity. It has the advantages of extensive evaluation for HRQOL, cross-cultural application, rapid completion, high response rates, and an advanced scoring system. PMID:19255812

  9. Direct spectral analysis of tea samples using 266 nm UV pulsed laser-induced breakdown spectroscopy and cross validation of LIBS results with ICP-MS.

    PubMed

    Gondal, M A; Habibullah, Y B; Baig, Umair; Oloore, L E

    2016-05-15

    Tea is one of the most common and popular beverages spanning vast array of cultures all over the world. The main nutritional benefits of drinking tea are its anti-oxidant properties, presumed protection against certain cancers, inhibition of inflammation and possible protective effects against diabetes. Laser induced breakdown spectrometer (LIBS) was assembled as a powerful tool for qualitative and quantitative analysis of various brands of tea samples using 266 nm pulsed UV laser. LIBS spectra for six brands of tea samples in the wavelength range of 200-900 nm was recorded and all elements present in our tea samples were identified. The major toxic elements detected in several brands of tea samples were bromine, chromium and minerals like iron, calcium, potassium and silicon. The spectral assignment was conducted prior to the determination of concentration of each element. For quantitative analysis, calibration curves were drawn for each element using standard samples prepared in known concentration in the tea matrix. The plasma parameters (electron temperature and electron density) were also determined prior to the tea samples spectroscopic analysis. The concentration of iron, chromium, potassium, bromine, copper, silicon and calcium detected in all tea samples was between 378-656, 96-124, 1421-6785, 99-1476, 17-36, 2-11 and 92-130 mg L(-1) respectively. The limits of detection estimated for Fe, Cr, K, Br, Cu, Si, Ca in tea samples were 22, 12, 14, 11, 6, 1 and 12 mg L(-1) respectively. To further confirm the accuracy of our LIBS results, we determined the concentration of each element present in tea samples by using standard analytical technique like ICP-MS. The concentrations detected with our LIBS system are in excellent agreement with ICP-MS results. The system assembled for spectral analysis in this work could be highly applicable for testing the quality and purity of food and also pharmaceuticals products. PMID:26992530

  10. RegulonDB v8.0: omics data sets, evolutionary conservation, regulatory phrases, cross-validated gold standards and more

    PubMed Central

    Salgado, Heladia; Peralta-Gil, Martin; Gama-Castro, Socorro; Santos-Zavaleta, Alberto; Muñiz-Rascado, Luis; García-Sotelo, Jair S.; Weiss, Verena; Solano-Lira, Hilda; Martínez-Flores, Irma; Medina-Rivera, Alejandra; Salgado-Osorio, Gerardo; Alquicira-Hernández, Shirley; Alquicira-Hernández, Kevin; López-Fuentes, Alejandra; Porrón-Sotelo, Liliana; Huerta, Araceli M.; Bonavides-Martínez, César; Balderas-Martínez, Yalbi I.; Pannier, Lucia; Olvera, Maricela; Labastida, Aurora; Jiménez-Jacinto, Verónica; Vega-Alvarado, Leticia; del Moral-Chávez, Victor; Hernández-Alvarez, Alfredo; Morett, Enrique; Collado-Vides, Julio

    2013-01-01

    This article summarizes our progress with RegulonDB (http://regulondb.ccg.unam.mx/) during the past 2 years. We have kept up-to-date the knowledge from the published literature regarding transcriptional regulation in Escherichia coli K-12. We have maintained and expanded our curation efforts to improve the breadth and quality of the encoded experimental knowledge, and we have implemented criteria for the quality of our computational predictions. Regulatory phrases now provide high-level descriptions of regulatory regions. We expanded the assignment of quality to various sources of evidence, particularly for knowledge generated through high-throughput (HT) technology. Based on our analysis of most relevant methods, we defined rules for determining the quality of evidence when multiple independent sources support an entry. With this latest release of RegulonDB, we present a new highly reliable larger collection of transcription start sites, a result of our experimental HT genome-wide efforts. These improvements, together with several novel enhancements (the tracks display, uploading format and curational guidelines), address the challenges of incorporating HT-generated knowledge into RegulonDB. Information on the evolutionary conservation of regulatory elements is also available now. Altogether, RegulonDB version 8.0 is a much better home for integrating knowledge on gene regulation from the sources of information currently available. PMID:23203884

  11. The alpha-globin genotype does not influence sickle cell disease severity in a retrospective cross-validation study of the pediatric severity score.

    PubMed

    Joly, Philippe; Pondarré, Corinne; Bardel, Claire; Francina, Alain; Martin, Cyril

    2012-01-01

    To validate the recently proposed pediatric severity score (PSS) for sickle cell disease (SCD), we retrospectively assembled clinical data from a cohort of 122 patients with SCD (105 S/S or S/β(0) -thal. and 17 S/C) followed up for at least 2 years. Besides age and α- and β-globin genotypes, four new parameters were also tested against the PSS: duration of data assembly, neonatal screening, use of transcranial Doppler ultrasound to prevent vasculopathies and β-globin gene cluster haplotype. Once again, the PSS clearly differentiated patients by their β-globin genotype (P=0.004) but not by their age during data assembly (P=0.159). But, surprisingly, alpha-gene deletions were not associated with a lower PSS (P=0.604), possibly reflecting the opposite effects of α-thalassemia on global SCD severity. As for the newly tested parameters, the PSS appeared not to be influenced by the duration of data assembly (P=0.071) and neonatal screening (P=0.678) but rather by the introduction of transcranial Doppler ultrasound (P=0.006). Moreover, the Senegal haplotype at the homozygous state may be associated with a lower PSS. Methodologically, our data globally confirm the usefulness of the PSS to identify major etiological factors of SCD gravity. Nevertheless, the score is surely underestimated for patients who have been switched to a chronic therapy before the main SCD complications. Biologically, our study questions about the exact influence of α-thalassemia on global SCD severity. PMID:21910753

  12. Cross-validation study using item response theory: the health-related quality of life for eating disorders questionnaire-short version.

    PubMed

    Bilbao, Amaia; Las Hayas, Carlota; Forero, Carlos G; Padierna, Angel; Martin, Josune; Quintana, José M

    2014-08-01

    The Health-Related Quality of Life for Eating Disorder-Short questionnaire is one of the most suitable existing instruments for measuring quality of life in patients with eating disorders. The objective of the study was to evaluate its reliability, validity, and responsiveness in a cohort of 377 patients. A comprehensive validation process was performed, including confirmatory factor analysis and a graded response model, and assessments of reliability and responsiveness at 1 year of follow-up. The confirmatory factor analysis confirmed the two second-order latent traits, social maladjustment, and mental health and functionality. The graded response model results showed that all items were good for discriminating their respective latent traits. Cronbach's alpha coefficients were high, and responsiveness parameters showed moderate changes. In conclusion, this short questionnaire has good psychometric properties. Its simplicity and ease of application further enhance its acceptability and usefulness in clinical research and trials, as well as in routine practice. PMID:24235177

  13. Predicting the likelihood of future sexual recidivism: pilot study findings from a California sex offender risk project and cross-validation of the Static-99.

    PubMed

    Sreenivasan, Shoba; Garrick, Thomas; Norris, Randall; Cusworth-Walker, Sarah; Weinberger, Linda E; Essres, Garrett; Turner, Susan; Fain, Terry

    2007-01-01

    Pilot findings on 137 California sex offenders followed up over 10 years after release from custody (excluding cases in which legal jurisdiction expired) are presented. The sexual recidivism rate, very likely inflated by sample selection, was 31 percent at five years and 40 percent at 10 years. Cumulatively, markers of sexual deviance (multiple victim types) and criminality (prior parole violations and prison terms) led to improved prediction of sexual recidivism (receiver operating characteristic [ROC] = .71, r = .46) than singly (multiple victim types: ROC = .60, r = .31; prior parole violations and prison terms: ROC = .66, r = .37). Long-term Static-99 statistical predictive accuracy for sexual recidivism was lower in our sample (ROC = .62, r =.24) than the values presented in the developmental norms. Sexual recidivism rates were higher in our study for Static-99 scores of 2 and 3 than in the developmental sample, and lower for scores of 4 and 6. Given failures to replicate developmental norms, the Static-99 method of ranking sexual recidivism risk warrants caution when applied to individual offenders. PMID:18086738

  14. Cross-validation of the Self-Appraisal Questionnaire (SAQ): an offender risk and need assessment measure on Australian, British, Canadian, Singaporean, and American offenders.

    PubMed

    Loza, Wagdy; Cumbleton, Anita; Shahinfar, Ariana; Neo, Lee Hong; Evans, Maggie; Conley, Michael; Summers, Roger

    2004-10-01

    The Self-Appraisal Questionnaire (SAQ) is a 72-item self-report measure designed to predict violent and nonviolent recidivism among adult criminal offenders. The results from using samples from Australia, Canada, England, Singapore, and two samples from the United States (North Carolina and Pennsylvania) indicated that (a) the SAQ has sound psychometric properties, with acceptable reliability and concurrent validity for assessing recidivism and institutional adjustment; (b) there were no significant differences among the scores of the White, African American, Hispanic, and Aboriginal Australian offenders on the SAQ; (c) there were no significant differences among offenders who completed the SAQ for research purposes versus offenders who completed it as part of a decision-making process. Results provided support for the validity of the SAQ to be used with the culturally diverse offenders involved in this research and provided further evidence that contradicts concerns that the SAQ as a self-report measure may be susceptible to lying, and self-presentation biases. PMID:15358941

  15. Reexamining the Factorial Structure of the Maslach Burnout Inventory for Elementary, Intermediate, and Secondary Teachers: A Cross-Validated Confirmatory Factor Analytic Study.

    ERIC Educational Resources Information Center

    Byrne, Barbara M.

    The factorial validity of the Maslach Burnout Inventory (MBI) was studied for 2,931 Canadian teachers (48.2% males and 51.8% females) as a single professional group and for subsamples of this group (1,159 elementary school teachers, 388 intermediate school teachers, and 1,384 secondary school teachers). Study participants were full-time teachers…

  16. Cross-validation of δ15N and FishBase estimates of fish trophic position in a Mediterranean lagoon: The importance of the isotopic baseline

    NASA Astrophysics Data System (ADS)

    Mancinelli, Giorgio; Vizzini, Salvatrice; Mazzola, Antonio; Maci, Stefano; Basset, Alberto

    2013-12-01

    FishBase, a relational database freely available on the Internet, is to date widely used as a source of quantitative information on the trophic position of marine fish species. Here, we compared FishBase estimates for an assemblage of 30 fish species sampled in a Mediterranean lagoon (Acquatina lagoon, SE Italy) with their trophic positions calculated using nitrogen stable isotopes.

  17. Improved cross validation of a static ubiquitin structure derived from high precision residual dipolar couplings measured in a drug-based liquid crystalline phase.

    PubMed

    Maltsev, Alexander S; Grishaev, Alexander; Roche, Julien; Zasloff, Michael; Bax, Ad

    2014-03-12

    The antibiotic squalamine forms a lyotropic liquid crystal at very low concentrations in water (0.3-3.5% w/v), which remains stable over a wide range of temperature (1-40 °C) and pH (4-8). Squalamine is positively charged, and comparison of the alignment of ubiquitin relative to 36 previously reported alignment conditions shows that it differs substantially from most of these, but is closest to liquid crystalline cetyl pyridinium bromide. High precision residual dipolar couplings (RDCs) measured for the backbone (1)H-(15)N, (15)N-(13)C', (1)H(α)-(13)C(α), and (13)C'-(13)C(α) one-bond interactions in the squalamine medium fit well to the static structural model previously derived from NMR data. Inclusion into the structure refinement procedure of these RDCs, together with (1)H-(15)N and (1)H(α)-(13)C(α) RDCs newly measured in Pf1, results in improved agreement between alignment-induced changes in (13)C' chemical shift, (3)JHNHα values, and (13)C(α)-(13)C(β) RDCs and corresponding values predicted by the structure, thereby validating the high quality of the single-conformer structural model. This result indicates that fitting of a single model to experimental data provides a better description of the average conformation than does averaging over previously reported NMR-derived ensemble representations. The latter can capture dynamic aspects of a protein, thus making the two representations valuable complements to one another. PMID:24568736

  18. Improved Cross Validation of a Static Ubiquitin Structure Derived from High Precision Residual Dipolar Couplings Measured in a Drug-Based Liquid Crystalline Phase

    PubMed Central

    2014-01-01

    The antibiotic squalamine forms a lyotropic liquid crystal at very low concentrations in water (0.3-3.5% w/v), which remains stable over a wide range of temperature (1-40 °C) and pH (4-8). Squalamine is positively charged, and comparison of the alignment of ubiquitin relative to 36 previously reported alignment conditions shows that it differs substantially from most of these, but is closest to liquid crystalline cetyl pyridinium bromide. High precision residual dipolar couplings (RDCs) measured for the backbone 1H-15N, 15N-13C′, 1Hα-13Cα, and 13C′-13Cα one-bond interactions in the squalamine medium fit well to the static structural model previously derived from NMR data. Inclusion into the structure refinement procedure of these RDCs, together with 1H-15N and 1Hα-13Cα RDCs newly measured in Pf1, results in improved agreement between alignment-induced changes in 13C′ chemical shift, 3JHNHα values, and 13Cα-13Cβ RDCs and corresponding values predicted by the structure, thereby validating the high quality of the single-conformer structural model. This result indicates that fitting of a single model to experimental data provides a better description of the average conformation than does averaging over previously reported NMR-derived ensemble representations. The latter can capture dynamic aspects of a protein, thus making the two representations valuable complements to one another. PMID:24568736

  19. [Hypercholesterolemia: a therapeutic approach].

    PubMed

    Moráis López, A; Lama More, R A; Dalmau Serra, J

    2009-05-01

    High blood cholesterol levels represent an important cardiovascular risk factor. Hypercholesterolemia is defined as levels of total cholesterol and low-density lipoprotein cholesterol above 95th percentile for age and gender. For the paediatric population, selective screening is recommended in children older than 2 years who are overweight, with a family history of early cardiovascular disease or whose parents have high cholesterol levels. Initial therapeutic approach includes diet therapy, appropriate physical activity and healthy lifestyle changes. Drug treatment should be considered in children from the age of 10 who, after having followed appropriate diet recommendations, still have very high LDL-cholesterol levels or moderately high levels with concomitant risk factors. In case of extremely high LDL-cholesterol levels, drug treatment should be taken into consideration at earlier ages (8 years old). Modest response is usually observed with bile acid-binding resins. Statins can be considered first-choice drugs, once evidence on their efficacy and safety has been shown. PMID:19427823

  20. Variational Approach to SAW

    NASA Astrophysics Data System (ADS)

    Burlatsky, Sergei F.; Reinhardt, S.; Lach; Ovchinnikov, Yu.

    1996-03-01

    A new variational technique is used to analyze both analytically and numerically the scaling behavior of Self Avoiding Walks. We present a set of lower bounds for the survival provability (the ratio of total number of self avoiding paths to total number of random paths) which is based on Jensen inequality. This set is generated by the hierarchy of different trial hamiltonians which correspond to: unconstrained random walk, mean field approximation, original Flory model and to a new approach which allows to vary independently the scales of fluctuations, corresponding to different path length scales. The D=2, D=3, and Darrow 4, cases are analyzed separately. The results of analytical variational procedure reproduce classical mean field exponents for small scales and Flory - type critical exponents for large scales, and present new estimates for the chemical potential of SAW. Possible generalizations to branching self avoiding paths are discussed. The numerical algorithm which is based on proposed trial hamiltonian might increase the efficiency with which the chemical potential and scaling properties of chain molecules with a finite number of discrete conformations can be computed. This work was supported in part by ONR Grant N00014-94-0647.

  1. Halitosis: the multidisciplinary approach

    PubMed Central

    Bollen, Curd ML; Beikler, Thomas

    2012-01-01

    Halitosis, bad breath or oral malodour are all synonyms for the same pathology. Halitosis has a large social and economic impact. For the majority of patients suffering from bad breath, it causes embarrassment and affects their social communication and life. Moreover, halitosis can be indicative of underlying diseases. Only a limited number of scientific publications were presented in this field until 1995. Ever since, a large amount of research is published, often with lack of evidence. In general, intraoral conditions, like insufficient dental hygiene, periodontitis or tongue coating are considered to be the most important cause (85%) for halitosis. Therefore, dentists and periodontologists are the first-line professionals to be confronted with this problem. They should be well aware of the origin, the detection and especially of the treatment of this pathology. In addition, ear–nose–throat-associated (10%) or gastrointestinal/endocrinological (5%) disorders may contribute to the problem. In the case of halitophobia, psychiatrical or psychological problems may be present. Bad breath needs a multidisciplinary team approach: dentists, periodontologists, specialists in family medicine, ear–nose–throat surgeons, internal medicine and psychiatry need to be updated in this field, which still is surrounded by a large taboo. Multidisciplinary bad breath clinics offer the best environment to examine and treat this pathology that affects around 25% of the whole population. This article describes the origin, detection and treatment of halitosis, regarded from the different etiological origins. PMID:22722640

  2. Combined approach for gynecomastia

    PubMed Central

    El-Sabbagh, Ahmed Hassan

    2016-01-01

    Background: Gynecomastia is a deformity of male chest. Treatment of gynecomastia varied from direct surgical excision to other techniques (mainly liposuction) to a combination of both. Skin excision is done according to the grade. In this study, experience of using liposuction adjuvant to surgical excision was described. Patients and methods: Between September 2012 and April 2015, a total of 14 patients were treated with liposuction and surgical excision through a periareolar incision. Preoperative evaluation was done in all cases to exclude any underlying cause of gynecomastia. Results: All fourteen patients were treated bilaterally (28 breast tissues). Their ages ranged between 13 and 33 years. Two patients were classified as grade I, and four as grade IIa, IIb or III, respectively. The first 3 patients showed seroma. Partial superficial epidermolysis of areola occurred in 2 cases. Superficial infection of incision occurred in one case and was treated conservatively. Conclusion: All grades of gynecomastia were managed by the same approach. Skin excision was added to a patient that had severe skin excess with limited activity and bad skin complexion. No cases required another setting or asked for 2nd opinion. PMID:26955509

  3. The Stepping Stone Approach

    NASA Astrophysics Data System (ADS)

    Brumfitt, A.

    Education is a profession in its own right. It has its own parameters, passions and language. Having the responsibility both of educare and educere, education has a focus of delivering specific factual knowledge whilst drawing out the creative mind. Space Science is a special vehicle having the properties of both educare and educere. It has a magic and wonder that touches the very essence of an individual and his place in time and space; it offers the "wow" factor that all teachers strive for. Space Science is the wrapping paper for other elements in the curriculum, e.g. cross-curricula and skill-based activities, such as language development, creativity, etc. as well as the pure sciences which comprise of engineering, physics and other natural sciences from astronomy to chemistry to biology. Each of these spheres of influence are relevant from kindergarten to undergraduate studies and complement, and in addition support informal education in museums, science centers and the world of e-learning. ESA Science Education has devised the "Stepping Stone Approach" to maximize the greatest outreach to all education stakeholders in Europe. In this paper we illustrate how to best reach these target groups with very specific activities to trigger and sustain enthusiasm whilst supporting the pedagogical, subject content and skill-based needs of a prescribed curriculum.

  4. COMPRENDO: Focus and Approach

    PubMed Central

    Schulte-Oehlmann, Ulrike; Albanis, Triantafyllos; Allera, Axel; Bachmann, Jean; Berntsson, Pia; Beresford, Nicola; Carnevali, Daniela Candia; Ciceri, Francesca; Dagnac, Thierry; Falandysz, Jerzy; Galassi, Silvana; Hala, David; Janer, Gemma; Jeannot, Roger; Jobling, Susan; King, Isabella; Klingmüller, Dietrich; Kloas, Werner; Kusk, Kresten Ole; Levada, Ramon; Lo, Susan; Lutz, Ilka; Oehlmann, Jörg; Oredsson, Stina; Porte, Cinta; Rand-Weaver, Marian; Sakkas, Vasilis; Sugni, Michela; Tyler, Charles; van Aerle, Ronny; van Ballegoy, Christoph; Wollenberger, Leah

    2006-01-01

    Tens of thousands of man-made chemicals are in regular use and discharged into the environment. Many of them are known to interfere with the hormonal systems in humans and wildlife. Given the complexity of endocrine systems, there are many ways in which endocrine-disrupting chemicals (EDCs) can affect the body’s signaling system, and this makes unraveling the mechanisms of action of these chemicals difficult. A major concern is that some of these EDCs appear to be biologically active at extremely low concentrations. There is growing evidence to indicate that the guiding principle of traditional toxicology that “the dose makes the poison” may not always be the case because some EDCs do not induce the classical dose–response relationships. The European Union project COMPRENDO (Comparative Research on Endocrine Disrupters—Phylogenetic Approach and Common Principles focussing on Androgenic/Antiandrogenic Compounds) therefore aims to develop an understanding of potential health problems posed by androgenic and antiandrogenic compounds (AACs) to wildlife and humans by focusing on the commonalities and differences in responses to AACs across the animal kingdom (from invertebrates to vertebrates). PMID:16818253

  5. Endoscopic Endonasal Transsphenoidal Approach

    PubMed Central

    Cappabianca, Paolo; Alfieri, Alessandra; Colao, Annamaria; Ferone, Diego; Lombardi, Gaetano; de Divitiis, Enrico

    1999-01-01

    The outcome of endoscopic endonasal transsphenoidal surgery in 10 patients with pituitary adenomas was compared with that of traditional transnasal transsphenoidal approach (TTA) in 20 subjects. Among the 10 individuals subjected to “pure endoscopy,” 2 had a microadenoma, 1 an intrasellar macroadenoma, 4 had a macroadenoma with suprasellar expansion, 2 had a macroadenoma with supra-parasellar expansion, and 1 a residual tumor; 5 had acromegaly and 5 had a nonfunctioning adenoma (NFA). Among the patients subjected to TTA, 4 had a microadenoma, 2 had an intrasellar macroadenoma, 6 had a macroadenoma with suprasellar expansion, 4 had a macroadenoma with supra-parasellar expansion, and 4 had a residual tumor; 9 patients had acromegaly, 1 hyperprolactinemia, 1 Cushing's disease, and 9 a NFA. At the macroscopic evaluation, tumor removal was total (100%) after endoscopy in 9 patients and after TTA in 14 patients. Six months after surgery, magnetic resonance imaging (MRI) confirmed the total tumor removal in 21 of 23 patients (91.3%). Circulating growth hormone (GH) and insulin-like growth factor-I (IGF-I) significantly decreased 6 months after surgery in all 14 acromegalic patients: normalization of plasma IGF-I levels was obtained in 4 of 5 patients after the endoscopic procedure and in 4 of 9 patients after TTA. Before surgery, pituitary hormone deficiency was present in 14 out of 30 patients: pituitary function improved in 4 patients, remaining unchanged in the other 10 patients. Visual field defects were present before surgery in 4 patients, and improved in all. Early surgical results in the group of 10 patients who underwent endoscopic pituitary tumor removal were at least equivalent to those of standard TTA, with excellent postoperative course. Postsurgical hospital stay was significantly shorter (3.1 ± 0.4 vs. 6.2 ± 0.3 days, p < 0.001) after endoscopy as compared to TTA. ImagesFigure 1Figure 2 PMID:17171126

  6. Skull base approaches in neurosurgery

    PubMed Central

    2010-01-01

    The skull base surgery is one of the most demanding surgeries. There are different structures that can be injured easily, by operating in the skull base. It is very important for the neurosurgeon to choose the right approach in order to reach the lesion without harming the other intact structures. Due to the pioneering work of Cushing, Hirsch, Yasargil, Krause, Dandy and other dedicated neurosurgeons, it is possible to address the tumor and other lesions in the anterior, the mid-line and the posterior cranial base. With the transsphenoidal, the frontolateral, the pterional and the lateral suboccipital approach nearly every region of the skull base is exposable. In the current state many different skull base approaches are described for various neurosurgical diseases during the last 20 years. The selection of an approach may differ from country to country, e.g., in the United States orbitozygomaticotomy for special lesions of the anterior skull base or petrosectomy for clivus meningiomas, are found more frequently than in Europe. The reason for writing the review was the question: Are there keyhole approaches with which someone can deal with a vast variety of lesions in the neurosurgical field? In my opinion the different surgical approaches mentioned above cover almost 95% of all skull base tumors and lesions. In the following text these approaches will be described. These approaches are: 1) pterional approach 2) frontolateral approach 3) transsphenoidal approach 4) suboccipital lateral approach These approaches can be extended and combined with each other. In the following we want to enhance this philosophy. PMID:20602753

  7. LacSubPred: predicting subtypes of Laccases, an important lignin metabolism-related enzyme class, using in silico approaches

    PubMed Central

    2014-01-01

    , a supervised learning system was developed from the clusters. The models showed high performance with an overall accuracy of 99.03%, error of 0.49%, MCC of 0.9367, precision of 94.20%, sensitivity of 94.20%, and specificity of 99.47% in a 5-fold cross-validation test. In an independent test, our models still provide a high accuracy of 97.98%, error rate of 1.02%, MCC of 0.8678, precision of 87.88%, sensitivity of 87.88% and specificity of 98.90%. Conclusion This study provides a useful classification system for better understanding of Laccases from their physicochemical properties perspective. We also developed a publically available web tool for the characterization of Laccase protein sequences (http://lacsubpred.bioinfo.ucr.edu/). Finally, the programs used in the study are made available for researchers interested in applying the system to other enzyme classes (https://github.com/tweirick/SubClPred). PMID:25350584

  8. Predicting and analyzing DNA-binding domains using a systematic approach to identifying a set of informative physicochemical and biochemical properties

    PubMed Central

    2011-01-01

    Background Existing methods of predicting DNA-binding proteins used valuable features of physicochemical properties to design support vector machine (SVM) based classifiers. Generally, selection of physicochemical properties and determination of their corresponding feature vectors rely mainly on known properties of binding mechanism and experience of designers. However, there exists a troublesome problem for designers that some different physicochemical properties have similar vectors of representing 20 amino acids and some closely related physicochemical properties have dissimilar vectors. Results This study proposes a systematic approach (named Auto-IDPCPs) to automatically identify a set of physicochemical and biochemical properties in the AAindex database to design SVM-based classifiers for predicting and analyzing DNA-binding domains/proteins. Auto-IDPCPs consists of 1) clustering 531 amino acid indices in AAindex into 20 clusters using a fuzzy c-means algorithm, 2) utilizing an efficient genetic algorithm based optimization method IBCGA to select an informative feature set of size m to represent sequences, and 3) analyzing the selected features to identify related physicochemical properties which may affect the binding mechanism of DNA-binding domains/proteins. The proposed Auto-IDPCPs identified m=22 features of properties belonging to five clusters for predicting DNA-binding domains with a five-fold cross-validation accuracy of 87.12%, which is promising compared with the accuracy of 86.62% of the existing method PSSM-400. For predicting DNA-binding sequences, the accuracy of 75.50% was obtained using m=28 features, where PSSM-400 has an accuracy of 74.22%. Auto-IDPCPs and PSSM-400 have accuracies of 80.73% and 82.81%, respectively, applied to an independent test data set of DNA-binding domains. Some typical physicochemical properties discovered are hydrophobicity, secondary structure, charge, solvent accessibility, polarity, flexibility, normalized Van Der

  9. A Unified Spatiotemporal Modeling Approach for Predicting Concentrations of Multiple Air Pollutants in the Multi-Ethnic Study of Atherosclerosis and Air Pollution

    PubMed Central

    Olives, Casey; Kim, Sun-Young; Sheppard, Lianne; Sampson, Paul D.; Szpiro, Adam A.; Oron, Assaf P.; Lindström, Johan; Vedal, Sverre; Kaufman, Joel D.

    2014-01-01

    Background: Cohort studies of the relationship between air pollution exposure and chronic health effects require predictions of exposure over long periods of time. Objectives: We developed a unified modeling approach for predicting fine particulate matter, nitrogen dioxide, oxides of nitrogen, and black carbon (as measured by light absorption coefficient) in six U.S. metropolitan regions from 1999 through early 2012 as part of the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). Methods: We obtained monitoring data from regulatory networks and supplemented those data with study-specific measurements collected from MESA Air community locations and participants’ homes. In each region, we applied a spatiotemporal model that included a long-term spatial mean, time trends with spatially varying coefficients, and a spatiotemporal residual. The mean structure was derived from a large set of geographic covariates that was reduced using partial least-squares regression. We estimated time trends from observed time series and used spatial smoothing methods to borrow strength between observations. Results: Prediction accuracy was high for most models, with cross-validation R2 (R2CV) > 0.80 at regulatory and fixed sites for most regions and pollutants. At home sites, overall R2CV ranged from 0.45 to 0.92, and temporally adjusted R2CV ranged from 0.23 to 0.92. Conclusions: This novel spatiotemporal modeling approach provides accurate fine-scale predictions in multiple regions for four pollutants. We have generated participant-specific predictions for MESA Air to investigate health effects of long-term air pollution exposures. These successes highlight modeling advances that can be adopted more widely in modern cohort studies. Citation: Keller JP, Olives C, Kim SY, Sheppard L, Sampson PD, Szpiro AA, Oron AP, Lindström J, Vedal S, Kaufman JD. 2015. A unified spatiotemporal modeling approach for predicting concentrations of multiple air pollutants in the Multi

  10. Defining biocultural approaches to conservation.

    PubMed

    Gavin, Michael C; McCarter, Joe; Mead, Aroha; Berkes, Fikret; Stepp, John Richard; Peterson, Debora; Tang, Ruifei

    2015-03-01

    We contend that biocultural approaches to conservation can achieve effective and just conservation outcomes while addressing erosion of both cultural and biological diversity. Here, we propose a set of guidelines for the adoption of biocultural approaches to conservation. First, we draw lessons from work on biocultural diversity and heritage, social-ecological systems theory, integrated conservation and development, co-management, and community-based conservation to define biocultural approaches to conservation. Second, we describe eight principles that characterize such approaches. Third, we discuss reasons for adopting biocultural approaches and challenges. If used well, biocultural approaches to conservation can be a powerful tool for reducing the global loss of both biological and cultural diversity. PMID:25622889

  11. The narrative approach to personalisation

    NASA Astrophysics Data System (ADS)

    Conlan, Owen; Staikopoulos, Athanasios; Hampson, Cormac; Lawless, Séamus; O'keeffe, Ian

    2013-06-01

    This article describes the narrative approach to personalisation. This novel approach to the generation of personalised adaptive hypermedia experiences employs runtime reconciliation between a personalisation strategy and a number of contextual models (e.g. user and domain). The approach also advocates the late binding of suitable content and services to the generated personalised pathway resulting in an interactive composition that comprises services as well as content. This article provides a detailed definition of the narrative approach to personalisation and showcases the approach through the examination of two use-cases: the personalised digital educational games developed by the ELEKTRA and 80Days projects; and the personalised learning activities realised as part of the AMAS project. These use-cases highlight the general applicability of the narrative approach and how it has been applied to create a diverse range of real-world systems.

  12. Geometric approaches to mesh generation

    SciTech Connect

    Hoffmann, C.M.

    1995-12-31

    We review three approaches to mesh generation that axe based on analyzing and accounting for the geometric structure of the domain. In the first approach, due to Armstrong, the domain is partitioned into subdomains based on the medial-axis transform, a tool for analyzing spatial structures. In the second approach, due to Cox, the design history defines a geometric structure of the domain. The design primitives of that structure are meshed separately, and mesh overlap is accounted for by coupling equations. The third approach argues that mesh generation ought to be integrated into the shape design process, by meshing design features separately and resolving overlapping meshes by standard geometric computations.

  13. Anterolateral Approach to the Pilon.

    PubMed

    Hickerson, Lindsay E; Verbeek, Diederik O; Klinger, Craig E; Helfet, David L

    2016-08-01

    This video reviews the indications, surgical approach, and case examples of the anterolateral approach to a distal tibial plafond fracture. If this approach is used in a staged fashion, when the soft envelope is ready, it affords excellent visualization for fracture fixation through thick skin flaps. An associated article reviews a cohort of 44 mainly type C3 pilon injuries treated by 2 orthopaedic traumatologist using the anterolateral approach after staged external fixation. An anatomic or good fracture reduction was obtained in 41 fractures with 13.6% of patients undergoing a secondary surgical procedure for infection or nonunion. PMID:27441938

  14. Microbial Burden Approach : New Monitoring Approach for Measuring Microbial Burden

    NASA Technical Reports Server (NTRS)

    Venkateswaran, Kasthuri; Vaishampayan, Parag; Barmatz, Martin

    2013-01-01

    Advantages of new approach for differentiating live cells/ spores from dead cells/spores. Four examples of Salmonella outbreaks leading to costly destruction of dairy products. List of possible collaboration activities between JPL and other industries (for future discussion). Limitations of traditional microbial monitoring approaches. Introduction to new approach for rapid measurement of viable (live) bacterial cells/spores and its areas of application. Detailed example for determining live spores using new approach (similar procedure for determining live cells). JPL has developed a patented approach for measuring amount of live and dead cells/spores. This novel "molecular" method takes less than 5 to 7 hrs. compared to the seven days required using conventional techniques. Conventional "molecular" techniques can not discriminate live cells/spores among dead cells/spores. The JPL-developed novel method eliminates false positive results obtained from conventional "molecular" techniques that lead to unnecessary delay in the processing and to unnecessary destruction of food products.

  15. Exomars Mission Verification Approach

    NASA Astrophysics Data System (ADS)

    Cassi, Carlo; Gilardi, Franco; Bethge, Boris

    According to the long-term cooperation plan established by ESA and NASA in June 2009, the ExoMars project now consists of two missions: A first mission will be launched in 2016 under ESA lead, with the objectives to demonstrate the European capability to safely land a surface package on Mars, to perform Mars Atmosphere investigation, and to provide communi-cation capability for present and future ESA/NASA missions. For this mission ESA provides a spacecraft-composite, made up of an "Entry Descent & Landing Demonstrator Module (EDM)" and a Mars Orbiter Module (OM), NASA provides the Launch Vehicle and the scientific in-struments located on the Orbiter for Mars atmosphere characterisation. A second mission with it launch foreseen in 2018 is lead by NASA, who provides spacecraft and launcher, the EDL system, and a rover. ESA contributes the ExoMars Rover Module (RM) to provide surface mobility. It includes a drill system allowing drilling down to 2 meter, collecting samples and to investigate them for signs of past and present life with exobiological experiments, and to investigate the Mars water/geochemical environment, In this scenario Thales Alenia Space Italia as ESA Prime industrial contractor is in charge of the design, manufacturing, integration and verification of the ESA ExoMars modules, i.e.: the Spacecraft Composite (OM + EDM) for the 2016 mission, the RM for the 2018 mission and the Rover Operations Control Centre, which will be located at Altec-Turin (Italy). The verification process of the above products is quite complex and will include some pecu-liarities with limited or no heritage in Europe. Furthermore the verification approach has to be optimised to allow full verification despite significant schedule and budget constraints. The paper presents the verification philosophy tailored for the ExoMars mission in line with the above considerations, starting from the model philosophy, showing the verification activities flow and the sharing of tests

  16. Heterogeneous Ensemble Combination Search Using Genetic Algorithm for Class Imbalanced Data Classification

    PubMed Central

    Haque, Mohammad Nazmul; Noman, Nasimul; Berretta, Regina; Moscato, Pablo

    2016-01-01

    Classification of datasets with imbalanced sample distributions has always been a challenge. In general, a popular approach for enhancing classification performance is the construction of an ensemble of classifiers. However, the performance of an ensemble is dependent on the choice of constituent base classifiers. Therefore, we propose a genetic algorithm-based search method for finding the optimum combination from a pool of base classifiers to form a heterogeneous ensemble. The algorithm, called GA-EoC, utilises 10 fold-cross validation on training data for evaluating the quality of each candidate ensembles. In order to combine the base classifiers decision into ensemble’s output, we used the simple and widely used majority voting approach. The proposed algorithm, along with the random sub-sampling approach to balance the class distribution, has been used for classifying class-imbalanced datasets. Additionally, if a feature set was not available, we used the (α, β) − k Feature Set method to select a better subset of features for classification. We have tested GA-EoC with three benchmarking datasets from the UCI-Machine Learning repository, one Alzheimer’s disease dataset and a subset of the PubFig database of Columbia University. In general, the performance of the proposed method on the chosen datasets is robust and better than that of the constituent base classifiers and many other well-known ensembles. Based on our empirical study we claim that a genetic algorithm is a superior and reliable approach to heterogeneous ensemble construction and we expect that the proposed GA-EoC would perform consistently in other cases. PMID:26764911

  17. In Silico target fishing: addressing a “Big Data” problem by ligand-based similarity rankings with data fusion

    PubMed Central

    2014-01-01

    Background Ligand-based in silico target fishing can be used to identify the potential interacting target of bioactive ligands, which is useful for understanding the polypharmacology and safety profile of existing drugs. The underlying principle of the approach is that known bioactive ligands can be used as reference to predict the targets for a new compound. Results We tested a pipeline enabling large-scale target fishing and drug repositioning, based on simple fingerprint similarity rankings with data fusion. A large library containing 533 drug relevant targets with 179,807 active ligands was compiled, where each target was defined by its ligand set. For a given query molecule, its target profile is generated by similarity searching against the ligand sets assigned to each target, for which individual searches utilizing multiple reference structures are then fused into a single ranking list representing the potential target interaction profile of the query compound. The proposed approach was validated by 10-fold cross validation and two external tests using data from DrugBank and Therapeutic Target Database (TTD). The use of the approach was further demonstrated with some examples concerning the drug repositioning and drug side-effects prediction. The promising results suggest that the proposed method is useful for not only finding promiscuous drugs for their new usages, but also predicting some important toxic liabilities. Conclusions With the rapid increasing volume and diversity of data concerning drug related targets and their ligands, the simple ligand-based target fishing approach would play an important role in assisting future drug design and discovery. PMID:24976868

  18. Statistical machine learning to identify traumatic brain injury (TBI) from structural disconnections of white matter networks.

    PubMed

    Mitra, Jhimli; Shen, Kai-kai; Ghose, Soumya; Bourgeat, Pierrick; Fripp, Jurgen; Salvado, Olivier; Pannek, Kerstin; Taylor, D Jamie; Mathias, Jane L; Rose, Stephen

    2016-04-01

    Identifying diffuse axonal injury (DAI) in patients with traumatic brain injury (TBI) presenting with normal appearing radiological MRI presents a significant challenge. Neuroimaging methods such as diffusion MRI and probabilistic tractography, which probe the connectivity of neural networks, show significant promise. We present a machine learning approach to classify TBI participants primarily with mild traumatic brain injury (mTBI) based on altered structural connectivity patterns derived through the network based statistical analysis of structural connectomes generated from TBI and age-matched control groups. In this approach, higher order diffusion models were used to map white matter connections between 116 cortical and subcortical regions. Tracts between these regions were generated using probabilistic tracking and mean fractional anisotropy (FA) measures along these connections were encoded in the connectivity matrices. Network-based statistical analysis of the connectivity matrices was performed to identify the network differences between a representative subset of the two groups. The affected network connections provided the feature vectors for principal component analysis and subsequent classification by random forest. The validity of the approach was tested using data acquired from a total of 179 TBI patients and 146 controls participants. The analysis revealed altered connectivity within a number of intra- and inter-hemispheric white matter pathways associated with DAI, in consensus with existing literature. A mean classification accuracy of 68.16%±1.81% and mean sensitivity of 80.0%±2.36% were achieved in correctly classifying the TBI patients evaluated on the subset of the participants that was not used for the statistical analysis, in a 10-fold cross-validation framework. These results highlight the potential for statistical machine learning approaches applied to structural connectomes to identify patients with diffusive axonal injury. PMID

  19. Approaches to Teaching Foreign Languages.

    ERIC Educational Resources Information Center

    Hesse, M. G., Ed.

    Works by European and American educators from the Renaissance to the twentieth century are presented. A historical re-evaluation of foreign-language teaching combined with the scientific approach of modern linguistics can provide valuable insights for current teaching and learning approaches. Selections are presented from the writings of the…

  20. Cognitive Approaches to Automated Instruction.

    ERIC Educational Resources Information Center

    Regian, J. Wesley, Ed.; Shute, Valerie J., Ed.

    This book contains a snapshot of state-of-the-art research on the design of automated instructional systems. Selected cognitive psychologists were asked to describe their approach to instruction and cognitive diagnosis, the theoretical basis of the approach, its utility and applicability, and the knowledge engineering or task analysis methods…